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GENETIC AND DEMOGRAPHIC INVESTIGATION OF 

POPULATION STRUCTURE AND SOCIAL SYSTEM IN 

FOUR DELPHINID SPECIES 

Marc Oremus 

A thesis submitted in fulfilment of the requirements for the Degree of Doctor of 

Philosophy in Biological Sciences 

The University of Auckland 

2008

Thesis Abstract 

Population structure, genetic diversity and social system were investigated in four 

species of dolphins, thought to present contrasting habitat preferences and social 

organisation: spinner dolphins, rough-toothed dolphins, long-finned and short-finned 

pilot whales. To overcome methodological limitations, I combined molecular markers 

(mitochondrial DNA, -or mtDNA-, and microsatellite loci) and observational data 

(photo-identification and mass strandings) where possible. Genetic samples were 

obtained from skin biopsies of free-ranging (n = 243) and stranded (n = 375) 

dolphins. 

As with many species of delphinids, spinner dolphins (Stenella longirostris) form 

communities in which social and reproductive boundaries are poorly understood. In 

French Polynesia, capture-recapture analyses based on photographs of distinctly 

marked individuals (DMIs) and microsatellite genotypes (12 loci) indicated a 

community of about 150 dolphins around Moorea that is relatively closed on a 

generational time scale. Distinct communities, likely to follow a similar demographic 

pattern, were observed around neighbouring islands (Tahiti, Raiatea, Huahine and 

Bora Bora), as indicated by photo-identification data and restricted gene flow (FST = 

0.143, n = 154). Surprisingly high levels of insular mtDNA genetic diversity (average 

π = 1.44%, suggesting Nef ~ 100,000) contrasted with demographic characteristics of 

these communities. There was no evidence for a recent bottleneck effect, suggesting 

that this pattern is the result of metapopulation structure, based on numerous insular 

communities connected through male and female gene flow. 

Investigation of the worldwide mtDNA diversity and phylogeography of long-finned 

and short-finned pilot whale species revealed a complex evolutionary history 

(Globicephala melas, n = 434; and G. macrorhynchus, n = 134, including published 

and unpublished sequences). Strong genetic differentiation between long-finned pilot 

whales from the North Atlantic (G. m. melas) and Southern Hemisphere (G. m. 

edwardii) indicated severely restricted gene flow, although shared haplotypes 

suggested some recent contact between the two subspecies. Low genetic distances 

among haplotypes and a star-like phylogeny suggested a recent worldwide 

expansion for this species. Higher levels of diversity (although low compared to other 

cetaceans) were found in short-finned pilot whales, in particular among samples from 

around Japan. Phylogeographic studies suggested that Japanese samples originate 

from three distinct populations, one of which could be the ancestral population of the 

species. Overall, my results confirmed that worldwide mtDNA diversity is low in the 

two species, probably due to a recent worldwide population expansion and, 

potentially, to a matrilineal social structure. 

The molecular ecology of the mass strandings of long-finned pilot whales around 

New Zealand was investigated to test the hypothesis that individuals stranding 

together are part of an extended matrilineal group. Analyses of mtDNA sequences 

indicate that more than one haplotype was found in five of the seven mass strandings 

i

investigated (n = 275), demonstrating that groups are sometimes composed of 

unrelated maternal lineages. This was further supported by analyses of relatedness 

within and between strandings based on microsatellites (14 loci). These analyses 

discount kinship as the only factor causing large mass strandings in long-finned pilot 

whales. Parentage analyses confirmed some aspects of previous studies in the North 

Atlantic, suggesting a social system with at least some level of male and female 

philopatry to the maternal group, and infrequent paternities within the group. In a 

detailed study of a large mass stranding (Stewart Island 2003, n = 122), there was no 

correlation between position of the whales on the beach and genetic relatedness 

(based on 20 microsatellite loci), discounting the assumption that kinship bonds are 

maintained during these traumatic events. This was further supported by the striking 

separation of stranded mothers and dependant calves. This disruption of kinship 

bonds could help explain the behavioural distress of stranded individuals and the 

tendency of many whales to re-strand even after being re-floated. 

Finally, a study of rough-toothed dolphins (Steno bredanensis) in the Society 

Archipelago, French Polynesia, provided new insights in the ecology of this poorlyknown 

species. Although traditionally viewed as a pelagic dolphin, analyses 

supported a pattern of local communities, in some ways similar to spinner dolphins, 

with fine-scale population genetic structure (FST = 0.60, p < 0.001 based on mtDNA, 

n = 65) and local fidelity. These communities also showed a low level of mtDNA 

haplotype diversity (four unique haplotypes at Moorea compared to 18 for spinner 

dolphins), suggesting the potential influence of a matrilineal social structure similar to 

long-finned pilot whales. 

ii

Dedication 

To my parents 

Bernadette and Jean-Louis OREMUS 

For always being here for me 

iii

Acknowledgments 

During the first weeks of my thesis, preparing my fieldwork at Moorea, I have to say 

that I felt very lonely far from home and family left behind in France. As my next three 

(to five…) years were meant to be spent in French Polynesia and New Zealand, I had 

the first impression that I was about to live a great but rather solitary experience. 

Instead, it did not take very long for me to realise that I would not go anywhere in this 

endeavour alone. From fixing holes in the inflatable boat (which is pretty much how I 

started my PhD) to the last proof readings of my chapters, I received continuous and 

tremendous help and support from many many people that I wish to thank here. 

My first acknowledgments go to my main supervisor, Prof. C. Scott Baker, and my 

co-supervisor, Dr. M. Michael Poole. Thanks Scott for all your guidance, support and 

encouragement during this thesis (without forgeting your tonnes of editing). Thanks 

for the freedom you gave me, but always keeping an eye on my work to put me back 

on the right direction when I needed it. Michael, I’ll never be grateful enough for 

giving me this incredible opportunity to continue your research on dolphins in French 

Polynesia, and for sharing so much with me. This could well remain the greatest 

experience of my life. Thank you. 

This research has been possible thanks to the New Zealand Marsden Fund which 

provided the main funding for this project. I also thank the following institutions for 

providing additional funding: the Whale and Dolphin Adoption Project, the University 

of Auckland Graduate Research Fund, IFAW, Vista Press, Englehard Foundation, the 

SBS contestable travel fund and the Society for Marine Mammalogy student travel 

grant. 

To people in French Polynesia: 

Many thanks to Prof. René Galzin for all his advices and support during my fieldwork 

at Moorea. You always took the time to enquire about the progress of my thesis even 

though I was not your student. It has been very valuable help for me. 

Thanks to all my fellows at CRIOBE for all these great moments together and for 

coming on the boat with me when nobody else was there: I think in particular of 

Caroline Vieux, Marie Younger, Julien Million, Romain Foki, Elodie Lagouy, 

Catherine Gonnot, Thomas Binet, Lucie Penin, Medhi Adjerhoud, Moira Decima, and, 

of course, my dear Féroce & Rotui. Thanks to Yannick Chancerelle, Pascal Ung and 

James Algret from CRIOBE, for helping me so much with logistic. Thanks also to 

Emilie Leprêtre and Pierre Petitjean for your help on the field. 

Special thanks go to my friend Andrew Carroll, one of the most caring and loveable 

people I have ever met, with who I shared so much during my time at Moorea 

(including a lot of Hinano). I wish you all the best my friend. 

Big thanks to Rodolphe Holler and his family. I really hope that we’ll get the chance to 

go back on the field together during the whale season. I want to thank Yves Ducreux 

iv

and Véronique Pérard with the help of who I have been able to conduct some 

surveys in the Leeward Islands of the Society Archipelago and in the Tuamotu, 

aboard the superb Touaou. God, I was so sick on this boat… but the trip was still 

worth it, that’s for sure! Thanks also to Nelly and Laurent from Raiatea. I had a great 

time with you, driving the poti marara and going diving at night. All of you guys are so 

devoted to the cause; I truly admire you for your commitment. You offer the best help 

we (the ‘bloody scientists’) can hope for and we owe you a lot for our ‘scientific’ 

achievements. Thanks. 

Thank you to my “impeccable” colleague and friend, Manuel Ballesteros, who came 

to give me a hand during my first field season. It was a lot of fun. Please, let me know 

if I can give you a hand with your birds, it would be a pleasure for me to help you 

back. Thanks to Fred Jacques at Raiatea and Xavier Curvat from the Diving Club in 

Nuku Hiva for kindly providing me with a roof or a boat during my time in the outer 

islands. 

I wish to thank the “Ministère de l’Environnement” and the “Délégation à 

l’Environnement” of French Polynesia for allowing my research to be conducted 

under the research permit attributed to Dr. Poole. 

To the people in New Zealand: 

I would like to acknowledge the staff, past and present, of the Department of 

Conservation, for collecting so many stinky samples of stranded whales around New 

Zealand. In particular, I thank Helen Kettles and Caren Schröder, who dealt with 

large mass strandings in Stewart Island and Farewell Spit. Thanks to Sheryl Gybney 

for interesting discussions and for passing on some of her knowledge on cetacean 

mass strandings. 

Thank you to my lab mates from the laboratory of Molecular Ecology and Evolution 

for entertaining me, helping me, taking me on the field, and for enduring my moaning 

in French when PCRs were not working. An incredible mix of people with, I believe, 

as many as 11 nationalities represented. It’s not something that I would have got the 

chance to experience in a French laboratory! So a big thanks to you guys: Carlos 

Olavarría, Nicky Wiseman, Dorothea Heimeier, Gabriela de Tezanos Pinto, Susanna 

Caballero, Shane Lavery, Fabianna Mourão, Kirsty Russell, Colm Carraher, Alana 

Alexander, Jess Hayward, Hamish MacInnes, Murdock Vant, Emma Carroll, 

Vimoksalehi Lukoschek, Jennifer Jackson, Lida Pimper, Rebecca Hamner, Danielle 

Hannan, Andrew Veale and Agnes Le Port. I also wish good luck to the new ones in 

the Lavery lab: Leah, Claire, Martin and Frank. Thanks to my other fellows at SBS, I 

think in particular of Karin Farreyrol (now in La Reunion) and Björn Heijstra. I also 

want to thank Kristine Boxen for great help and great smile in the sequencing room. 

Thanks to the glorious ancients of the Baker lab: Merel Dalebout, Rochelle 

Constantine, Franz Pichler, Nathalie Patenaude and Tony Hickey. That was not an 

easy task to come after you guys, because you all did such a great job for your PhD. 

I tried to find inspiration in your manuscript, but I often ended up getting quite 

depressed, realising that it will be pretty hard for me to reach the same quality. 

Anyway, you all helped me in various ways at one stage or another of my thesis, so 

v

thank you. Special thank to you, Rochelle, for helping me finding extra funding to 

work on the pilot whale samples, first with the WADAP and now with the ACCAMS. 

Last in the lab but not least, I thank Debbie Steel for her tremendous help from day 1 

to the day of submission. I should have counted the number of questions I asked you 

during my thesis. I’m sure it is quite an impressive number… Thank you very much 

Debbie, I owe you a lot (sorry I was not able to teach you how to pronounce a proper 

“r” in French…). 

Thanks to the French community in Auckland for providing me with a taste of France, 

and a lot of fun parties: in particular, I thank Louis Ranjard (thanks also for your help 

with MATLAB, and appreciable coffee breaks at the lab), Jean Markarian, Julien 

Arnoux, Karine David, Stéphane Guindon, Elsa Kassardjian and Bénédicte Madon. 

To people around the world: 

I wish to thanks Tetsuya Endo and Naoko Funahashi in Japan, and Rosemary Gales 

in Australia for providing samples of long-finned pilot whale from ‘whale-meat’ market 

and strandings. Thanks to Michael Russello, Christina Pomilla, Michael Krützen, 

Anna Chao and Steven Kalinowski for help with computer programs. 

Many thanks to Claire Garrigue from Opération Cétacés for her help, friendship and 

for giving me the opportunity to go in New Caledonia during the whale season. 

Thanks also for being such a great example for me. I thank the rest of the Opération 

Cétacés team, including Aline Schaffar, Remy Dodemont and Hughes Ducreux. 

Thanks to the members of the South Pacific Whale Research Consortium for 

supporting my research through collaborative work and accepting one more 

Frenchman into the circle. Thanks to Lui Bell and SPREP for giving me the 

opportunity to present my results during the workshop at Samoa, in August 2005. 

To people in France (so it will be in French): 

Je remercie la famille Moreau pour leur soutient et leur amitié depuis temps 

d’années. Merci à Arnaud Legrand et sa petite famille. Je ne désespère pas de 

pouvoir travailler un jour avec toi mon ami. En Polynésie ou à Chizé les Bains, peu 

importe… Je salue Sandra Gaborit, Julie Pradera, Caroline Poupart, Badr Slassi, 

Arnaud Delaire, les familles Legarrec et Renaud, ainsi que tous mes amis en France. 

Merci à Laurent Grammont pour avoir été présent dans les moments difficiles. 

Egalement un énorme merci à mes amis très chers que sont Etienne Preys, Yohann 

Cardon et Mallorie Baussey. Pleins de bonnes choses à tous. 

Merci à toute ma famille, côté Oremus et côté Blanchard, pour leur soutien moral et 

mais aussi financier. Je n’oublie pas que mes parents et ma grand mère Oremus 

m’ont évité la banqueroute dans les moments difficiles. Merci pour tout, sans vous j’y 

serai encore… Une pensée toute particulière va à mes deux grands pères, Johnny 

Oremus et Claude Blanchard. 

vi

Un remerciement tout spécial revient à Elise Mechain qui, durant cette thèse, m’a 

tant donné et apporté sans jamais compter. Difficile de trouver les mots bien 

évidemment mais sache que… 

Enfin, je remercie mes « brothers » - Cedric Delaire, Vincent Legarrec, Alexandre 

Renaud, Willy Praud et Jérémie Batsalle - pour être reste fidèle à eux même et fidèle 

à nous. Je vais essayer de ne pas trop sombrer dans le sentimental car ce n’est pas 

trop le style de la maison (excepté à 2 g) mais je tiens à vous dire que pour moi, 

derrière le terme un peu puéril de « brothers » se cache une vérité : vous êtes la 

famille. Merci d’être là. 

Lasts but not least (English and French): 

A huge thanks to Sarah “limpet” Wells for giving me a normal life back and for her 

invaluable help, support and love during these last two years. I can’t believe you 

managed to live aside a PhD student in the last part of his thesis (probably one of the 

worst types of human being). I promise you that I’ll try to do as well as you when 

you’ll come to do your PhD. Thank you so much limpet, you cannot imagine how 

lucky I feel to have you next to me. 

Je fini avec ceux avec qui tout a commencé, mes parents Bernadette et Jean- 

Louis Oremus. Il n’y pas de mot suffisamment fort pour vous remercier comme 

il se doit. Sans votre soutient, sans votre amour, il n’y aurait rien eu de tout ca. 

On entend souvent des parents dire combien ils sont fiers de leurs enfants ; je 

peux vous dire aujourd’hui combien je suis fier de mes parents. 

vii

Table of Contents 

Thesis Abstract ................................................................................................... i 

Dedication .......................................................................................................... iii 

Acknowledgments............................................................................................. iv 

Table of Contents ............................................................................................ viii 

List of Tables ................................................................................................... xiii 

List of Figures................................................................................................... xv 

1. General Introduction ............................................................................... 1 

1.1. Overview......................................................................................... 1 

1.2. Brief review on the systematics of dolphins ................................... 2 

1.2.1. Mechanisms of speciation in dolphins........................................ 3 

1.2.2. Phylogeny and sources of paraphyly ......................................... 4 

1.2.3. Convergence with terrestrial mammals ...................................... 5 

1.3. Investigation of population structure .............................................. 7 

1.3.1. A challenging task in delphinid species...................................... 7 

1.4. 

1.3.2. Factors driving dolphin population structure............................... 9 

Genetic diversity ........................................................................... 12 

1.5. Social system ............................................................................... 14 

1.6. Principal methodological tools used in this study......................... 19 

1.6.1. Photo-identification................................................................... 19 

1.6.2. Biopsy sampling ....................................................................... 20 

1.6.3. Molecular markers.................................................................... 22 

1.7. Thesis outline and collaborators................................................... 24 

2. Isolation and interchange among insular spinner dolphin communities in 

the South Pacific revealed by individual identification and genetic diversity 28 

2.1. Abstract......................................................................................... 29 

2.2. Introduction................................................................................... 30 

2.3. Materials & Methods..................................................................... 34 

2.3.1. Study area and small-boat surveys.......................................... 34 

2.3.2. Collection and analysis of photo-identification data ................. 35 

2.3.3. Biopsy sampling and DNA extraction....................................... 36 

2.3.4. mtDNA sequencing, genotyping and sex identification ............ 36 

viii

2.3.5. Moorea community size estimate............................................. 37 

2.3.6. mtDNA and microsatellite diversity........................................... 38 

2.3.7. Population structure and sex specific dispersal ....................... 39 

2.3.8. Female long-term effective population size (Nef)...................... 39 

2.3.9. Testing for recent bottleneck effect .......................................... 40 

2.4. Results.......................................................................................... 41 

2.4.1. Survey effort and sample size.................................................. 41 

2.4.2. Demographic closure at Moorea .............................................. 42 

2.4.3. Abundance of Moorea community............................................ 44 

2.4.4. Individual interchange among islands ...................................... 45 

2.4.5. mtDNA diversity and effective population size ......................... 46 

2.4.6. Population differentiation.......................................................... 48 

2.4.7. Sex-biased dispersal................................................................ 49 

2.4.8. Genetic signature of community bottleneck ............................. 50 

2.5. Discussion .................................................................................... 51 

2.5.1. Demographic closure of Moorea community............................ 51 

2.5.2. Demographic community trends in the Society Archipelago .... 51 

2.5.3. Population genetic structure and sex-biased dispersal ............ 52 

2.5.4. Pelagic colonisation or island metapopulation? ....................... 54 

3. Worldwide mtDNA phylogeography and diversity of pilot whale species 

(Globicephala spp.) .......................................................................................... 57 

3.1. Abstract......................................................................................... 58 

3.2. Introduction................................................................................... 59 

3.3. Materials & Methods..................................................................... 65 

3.3.1. Sample collection and additional sequences ........................... 65 

3.3.2. Laboratory analyses of tissue samples .................................... 67 

3.3.3. Phylogenetic reconstruction ..................................................... 68 

3.3.4. Geographical areas and adjusted sampling............................. 69 

3.3.5. Genetic diversity and population structure ............................... 70 

3.3.6. Demographic history ................................................................ 71 

3.4. Results.......................................................................................... 72 

3.4.1. Phylogenetic reconstruction and sequence variation............... 72 

3.4.2. Long-finned pilot whales (Globicephala melas)........................ 76 

3.4.3. Short-finned pilot whales (Globicephala macrorhynchus) ........ 80 

3.5. Discussion .................................................................................... 85 

3.5.1. Pilot whale species and sub-species........................................ 85 

ix

3.5.2. Long-finned pilot whale phylogeography.................................. 86 

3.5.3. Short-finned pilot whales phylogeography ............................... 88 

4. Patterns of kinship and mtDNA lineage within mass strandings of longfinned 

pilot whales around New Zealand ...................................................... 94 

4.1. Abstract......................................................................................... 95 

4.2. Introduction................................................................................... 96 

4.3. Materials & Methods................................................................... 100 

4.3.1. Data collection........................................................................ 100 

4.3.2. DNA extraction and sequencing............................................. 102 

4.3.3. Microsatellite genotyping........................................................ 102 

4.3.4. Age/sex classes ..................................................................... 103 

4.3.5. mtDNA control region............................................................. 104 

4.3.6. Patterns of relatedness .......................................................... 104 

4.3.7. Parentage analyses ............................................................... 105 

4.4. Results........................................................................................ 107 

4.4.1. Molecular sexing and age/sex classes................................... 107 

4.4.2. Overall mtDNA diversity ......................................................... 107 

4.4.3. mtDNA haplotype distribution................................................. 108 

4.4.4. Microsatellite statistics............................................................ 110 

4.4.5. Relatedness estimator............................................................ 110 

4.4.6. Within-stranding mean relatedness........................................ 111 

4.4.7. mtDNA haplotypes and microsatellite relatedness................. 113 

4.4.8. Parentage inference............................................................... 114 

4.5. Discussion .................................................................................. 115 

4.5.1. Unrelated maternal lineages in mass strandings ................... 115 

4.5.2. Using mass stranding data to infer social structure................ 117 

4.5.3. A scenario of “unrelated matrilineal groups”........................... 117 

4.5.4. A similar social system to the North Atlantic .......................... 118 

4.5.5. Comparison to other matrilineal species of odontocetes........ 120 

5. “O’ mother where art thou?” Social disruption in a mass stranding of 

long-finned pilot whales ................................................................................ 122 

5.1. Abstract....................................................................................... 123 

5.2. Introduction................................................................................. 124 

5.3. Materials & Methods................................................................... 127 

5.3.1. Circumstances of the stranding.............................................. 127 


x

5.3.3. DNA extraction and microsatellite genotyping........................ 129 

5.3.4. Age/sex class ......................................................................... 130 

5.3.5. Spatial autocorrelation analyses ............................................ 131 

5.3.6. Relatedness analyses ............................................................ 131 

5.3.7. Parentage analyses ............................................................... 132 

5.4. Results........................................................................................ 133 

5.4.1. Sex/age class information ...................................................... 133 

5.4.2. Microsatellite analyses ........................................................... 134 

5.4.3. Spatial autocorrelation analyses ............................................ 134 

5.4.4. Relatedness and overall spatial distribution........................... 135 

5.4.5. Parentage inference............................................................... 136 

5.5. Discussion .................................................................................. 140 

5.5.1. Missing mothers ..................................................................... 140 

5.5.2. Potential scenarios explaining social disruption..................... 141 

5.5.3. Management of future strandings and animal welfare ........... 143 

6. Evidence of fine-scale population structure in rough-toothed dolphins 

from the Society Archipelago, French Polynesia ....................................... 145 

6.1. Abstract....................................................................................... 146 

6.2. Introduction................................................................................. 147 

6.3. Materials and Methods ............................................................... 149 

6.3.1. Study site and sample collection............................................ 149 

6.3.2. Laboratory procedures ........................................................... 150 

6.3.3. Microsatellite loci statistics ..................................................... 151 

6.3.4. Mitochondrial DNA diversity and haplotype network.............. 152 

6.3.5. Kinship and population structure............................................ 153 

6.3.6. Testing for recent genetic bottleneck ..................................... 154 

6.4. Results........................................................................................ 154 


6.4.2. Photo-identification................................................................. 154 

6.4.3. Microsatellite diversity and sex identification.......................... 155 

6.4.4. Mitochondrial DNA diversity ................................................... 157 

6.4.5. Kinship and population structure............................................ 159 

6.4.6. Bottleneck tests...................................................................... 161 

6.5. Discussion .................................................................................. 161 

6.5.1. Rough-toothed dolphins in the Society Archipelago............... 161 

6.5.2. Fine-scale population structure .............................................. 162 

xi

6.5.3. Sex-biased dispersal.............................................................. 163 

6.5.4. A spinner dolphin community structure with a pilot whales 

social organisation? ............................................................................ 164 

6.5.5. Conclusions............................................................................ 165 

7. General Discussion and Future Work ............................................... 167 

7.1. Overview..................................................................................... 167 

7.2. Metapopulation of spinner dolphins............................................ 171 

7.3. Pilot whales evolutionary history ................................................ 173 

7.4. Social systems and matrilineality ............................................... 175 

8. Appendices .......................................................................................... 178 

Appendix 1............................................................................................. 179 

Appendix 2:............................................................................................ 180 

Appendix 3............................................................................................. 181 

Appendix 4............................................................................................. 183 

Appendix 5............................................................................................. 184 

Electronic Appendices........................................................................... 187 

Appendix 6 .......................................................................................... 187 

Appendix 7 .......................................................................................... 187 

Appendix 8 .......................................................................................... 187 

Appendix 9 .......................................................................................... 188 

Appendix 10 ........................................................................................ 188 

9. References ........................................................................................... 189 

xii

List of Tables 

CHAPTER 1 

Table 1.1. Social system and life history attributes of dolphins under investigation in this thesis....... 24 

CHAPTER 2 

Table 2.1. Boat surveys conducted from 2002 to 2004 in French Polynesia...................................... 34 

Table 2.2. Microsatellite diversity for spinner dolphins from French Polynesia................................... 37 

Table 2.3. Sex identification and genetic diversity statistics for spinner dolphins. .............................. 42 

Table 2.4. Analysis of genetic differentiation among island communities........................................... 48 

Table 2.5. Differences in sex-specific FST values and variance of corrected assignment index.......... 49 

Table 2.6. Summary statistics of various tests to detect a recent bottleneck effect............................ 50 

CHAPTER 3 

Table 3.1. Sample data for all pilot whale specimens used in this study. ........................................... 63 

Table 3.2. Variable nucleotide positions within the mtDNA control region of Globicephala sp.. ......... 73 

Table 3.3. Genetic diversity statistics and neutrality tests in long-finned pilot whales. ....................... 76 

Table 3.4. Analysis of genetic differentiation in long-finned pilot whales. ........................................... 78 

Table 3.5. Genetic diversity statistics and neutrality test in short-finned pilot whales......................... 80 

Table 3.6. Analysis of genetic differentiation in short-finned pilot whales........................................... 81 

CHAPTER 4 

Table 4.1. Summary of seven mass strandings from around New Zealand. .................................... 103 

Table 4.2. Summary statistics of the 14 microsatellite loci in long-finned pilot whales. .................... 103 

Table 4.3. Statistical behaviour of four relatedness estimators. ....................................................... 114 

Table 4.4. Results of parentage analyses within three mass strandings. ......................................... 115 

Table 4.5. Results of parentage analyses between three mass strandings...................................... 116 

CHAPTER 5 

Table 5.1. Microsatellite diversity of long-finned pilot whales from Stewart Island. .......................... 130 

Table 5.2. Results of the parentage analyses in the mass stranding at Stewart Island 2003. .......... 138 

CHAPTER 6 

Table 6.1. Microsatellite diversity of rough-toothed dolphins from the Society Archipelago. ............ 151 

Table 6.2. Samples of rough-toothed dolphins collected outside French Polynesia......................... 152 

Table 6.3. List of samples identified as genetic re-sampling. ........................................................... 156 

Table 6.4. Sex identification and genetic diversity in rough-toothed dolphins................................... 157 

xiii

Table 6.5. Mitochondrial DNA haplotypes in rough-toothed dolphins of the Society Archipelago..... 158 

Table 6.6. List of the pairs of individuals showing a high-level of microsatellite relatedness. ........... 160 

Table 6.7. Summary statistics of various tests to detect a bottleneck effect..................................... 161 

CHAPTER 7 

Table 7.1. Summary of genetic parameters for the four species investigated in this study. ............. 171 

APPENDICES 

Table 8.1. Description of criteria used to assess the quality of dorsal fin images............................. 182 

Table 8.2. Behavioural responses to biopsy sampling in three species of dolphins. ........................ 183 

Table 8.3. Genotypes of four pilot whales from the mass stranding of Stewart Island 2003............. 187 

xiv

List of Figures 

CHAPTER 2 

Figure 2.1. Location and details of the study area in relationship to worldwide distribution of spinner 

dolphins. ............................................................................................................................................. 31 

Figure 2.2. Discovery curves based on the cumulative number of new DMIs. ................................... 43 

Figure 2.3. Inferred genealogical relationship among mtDNA haplotypes from spinner dolphins....... 47 

CHAPTER 3 

Figure 3.1. Lateral view of the short-finned pilot whale and long-finned pilot whale……………………60 

Figure 3.2. Global distribution of Globicephala spp..................................................................... ……61 

Figure 3.3. The origin and number of Japanese and Korean short-finned pilot whale products. ........ 67 

Figure 3.4. Phylogenetic relationships among pilot whale haplotypes................................................ 75 

Figure 3.5. Inferred genealogical relationships among long-finned pilot whale haplotypes.. .............. 79 

Figure 3.6. Inferred genealogical relationships among short-finned pilot whale haplotypes.. ............. 84 

CHAPTER 4 

Figure 4.1. Alternative scenarios of the social system of long-finned pilot whales. ............................ 98 

Figure 4.2. Distribution and size of the mass strandings around New Zealand................................ 109 

Figure 4.3. Observed mean relatedness within mass strandings. .................................................... 113 

CHAPTER 5 

Figure 5.1. Aerial view of the mass stranding at the Old Sand Neck, Stewart Island. ...................... 122 

Figure 5.2. Illustration and interpretation of the progression of a mass stranding. ........................... 126 

Figure 5.3. Geographical location of the mass stranding at Stewart Island...................................... 128 

Figure 5.4: Correlogram plots of the genetic correlation coefficient as a function of distance. .......... 135 

Figure 5.5. Distribution frequency of pairwise relatedness (rML). ...................................................... 136 

Figure 5.6. Spatial distribution of long-finned pilot whales on the beach of Stewart Island............... 141 

CHAPTER 6 

Figure 6.1. Discovery curve based on the cumulative number of new DMIs. ................................... 155 

Figure 6.2. Inferred genealogical relationship among rough-toothed dolphin mtDNA haplotypes .... 159 

APPENDICES 

Figure 8.1. Patterns of behavioural reactions to biopsy sampling for three species of dolphin......... 184 

Figure 8.2. Parental connexions between four pilot whales from the Stewart Island 2003 stranding 188 

xv

1.1. Overview 

1. General Introduction 

Chapter One: General Introduction 

Pryor & Norris (1991) noted several misconceptions concerning dolphin research. 

These misconceptions, some of which have persisted to the present day, include the 

assumption that wild dolphins are so inaccessible that it is “not worthwhile” to study 

them, and the assumption that the social behaviour and organisation of all dolphin 

species is similar to Tursiops. However, the development of novel methods, such as 

photo-identification, telemetry, biopsy sampling and molecular markers, and the 

recent improvements in data analyses provide an opportunity to dismiss these 

misconceptions. 

It is true that a large proportion of dolphin studies have concerned bottlenose 

dolphins (Genera Tursiops, composed of two species, T. truncatus and T. aduncus). 

Around the world, bottlenose dolphins form small resident coastal populations 

(Connor et al. 2000b), generally living in small groups, thus making them easier to 

study than most other dolphin species. Tursiops is one of only two genera of 

cetaceans in which some populations have been the subject of studies long enough 

to gather information over more than one generation (see review by Mann et al. 

2000). Only one other species of dolphin has benefited from a similar kind of 

attention; the killer whale (Orcinus orca) from eastern North Pacific (e.g., Bigg et al. 

1990, Baird 2000). Other long term studies on other dolphin species have been or 

are currently being undertaken (e.g., Norris et al. 1994), but none have reached the 

level of detail obtained on populations of bottlenose dolphins and killer whales. 

Considering that more than 30 species of dolphins are currently recognised 

worldwide (Rice 1998), it is evident that our knowledge on the ecology and status of 

this taxonomic family remains very limited. 

In this thesis, I used genetic and observational data to investigate the population 

structure and social system of four species of dolphins which have not benefited from 

1


the high level of attention directed to Tursiops and Orcinus. These are: the spinner 

dolphin (Stenella longirostris); the long-finned pilot whale (Globicephala melas); the 

short-finned pilot whale (Globicephala macrorhynchus); and the rough-toothed 

dolphin (Steno bredanensis). My project was part of a larger research program led by 

Prof. C.S. Baker, primarily using molecular markers to investigate the communities of 

several species of dolphins with contrasting social systems and habitat use. 

Therefore, I investigated several subjects that helped to address some of the specific 

objectives of this larger research program. These were: 

- Objective 1: Investigate comparative genetic structure of dolphin societies with 

different life history attributes and habitat specialisation. 

- Objective 2: Investigate genetic structure of dolphin societies in relation to 

predictions concerning the genetic consequences of social systems on the structure 

of local communities. 

- Objective 3: Investigate whether dolphin groups and communities are structured 

strictly along a single maternal lineage, or whether the social groups include multiple 

maternal lineages. 

- Objective 4: Investigate whether mating is directed outside of matrilineal groups 

through permanent emigration of males, as characteristic of most mammals, or 

whether mating occurs by temporary social fusion or interchange. 

- Objective 5: Investigate whether some dolphins have adapted to inbreeding as a 

strategy for maintaining social cohesion or because of geographic isolation. 

In this chapter, I review some of the current knowledge of dolphin ecology and 

evolutionary history. I also provide an outline for the rest of the manuscript as well as 

information on my collaborators. 

1.2. Brief review on the systematics of dolphins 

In this thesis, the terms “dolphin” and “delphinid”, refer to all species of the family 

Delphinidae, as described in Rice (1998). The family Delphinidae belongs to the 

super-family Delphinoidea (along with the Monodontidae and the Phocoenidae), suborder 

Odontoceti, and order Cetacea. 

2


Delphinids likely arose in the mid- to late Miocene (10-11 mya) from kentriodontid-like 

ancestors (Barnes 1985). They are relatively uncommon in the fossil record of the 

latest Miocene and Pliocene deposits, suggesting that the present diversity of 

delphinids is the result of an explosive species radiation occurring in the later part of 

the Pliocene (Barnes 2002). Delphinids represent the most diverse family of marine 

mammals with 37 currently recognised (and generally accepted) species, including 

the recently described Orcaella heinsohni (Beasley et al. 2005). It is very likely, 

however, that this number will continue to increase as new species are still being 

described, for example, the recognition of Sotalia as two distinct species: S. fluviatilis 

and S. guianensis (Cunha et al. 2005, Caballero et al. 2007). 

Dolphins show wide variation in their external morphology, including the length of the 

beak, colour pattern and size (ranging from 1.5 m in some Cephalorhynchus spp. and 

Stenella longirostris to 9.8 m in Orcinus orca). Several species of cosmopolitan, 

largely pelagic dolphins also exhibit a large degree of morphological variation 

throughout their geographic distribution (e.g., spinner dolphins, Perrin 1990). Overall, 

dolphins are widespread in the world’s oceans, with the killer whales being the most 

widely distributed. The highest species-level diversity is found in tropical and warm 

temperate latitudes with many species showing a pantropical distribution (e.g., 

Stenella spp.). In contrast, several species are distributed anti-tropically, including 

notably, the six species of Lagenorhynchus (Cipriano 1997). 

1.2.1. Mechanisms of speciation in dolphins 

The rapid radiation of delphinids is not fully understood, but several mechanisms of 

speciation have been proposed. Allopatric speciation events might have occurred 

following large geographical changes and the appearance of new barriers to gene 

flow. Davies (1963) suggested that the African continent could have played a 

significant role in cetacean evolution, acting as a geographical barrier to dispersal of 

tropical cetacean species during the Pleistocene glaciations. This hypothesis was 

later revisited by Perrin et al. (1978) and Rosel et al. (1994) to explain the current 

distribution of Stenella and Delphinus spp. 

3


Other physical barriers, such as water temperature, are not as apparent as land 

masses but are also likely to have had a large influence on the biogeographical 

distribution of many dolphin species. The variation of sea temperature in the tropical 

zone during the Pleistocene glacial/interglacial cycles is suspected to have resulted 

in the anti-tropical distribution of some closely related species (e.g., the right whale 

dolphins, Lissodelphis spp.), through the movement across the equator of individuals 

usually restricted to temperate and cold waters, resulting in subsequent geographic 

isolation (Davis 1963). Whether speciation occurred as a consequence of founder 

events by a few individuals or through vicariant isolation of large populations remains 

a source of debate (Davis 1963, Cipriano 1997, Hare et al. 2002). In the case of 

Lagenorhynchus spp., recent genetic evidence seems to support vicariant isolation 

(Hare et al. 2002). Using mtDNA variation, Pichler et al. (2001) describe the radiation 

process of the four species of Cephalorhynchus, showing that they likely originated in 

the waters of South Africa, before colonising New Zealand and then South America, 

following the West Wind Drift. Their results suggest that even coastal, depth-limited 

odontocetes are occasionally prone to long-distance movements, perhaps following 

periods of climatic change, ultimately resulting in speciation events. 

Contrary to these examples which represent cases of allopatric or peripatric 

speciation, it has also been suggested that some species of cetaceans could have 

differentiated in sympatry (Hoelzel 1998). Dolphins have not only radiated 

dramatically in terms of the number of species, but also in terms of ecological 

characteristics, including a wide range of habitats, social systems and feeding 

behaviours. Segregation on the basis of these ecological differences could have 

acted as a barrier to gene flow. For instance, in the eastern North Pacific, two distinct 

“forms” of killer whales exist sympatrically, one specialised in preying on mammals 

and the other preying on fish. It is suspected that the two forms are in the process of 

speciation (Baird & Dill 1995, Barrett-Lennard 2000). 

1.2.2. Phylogeny and sources of paraphyly 

Due to high morphological variability and the recent radiation of this group resulting in 

incomplete lineage sorting of genes, much uncertainty exists in the evolutionary 

relationships among delphinid species (Reeves et al. 2004). Although genetic 

4


information may help reveal and clarify important features of cetacean taxonomy 

(e.g., Milinkovitch 1997), it also has some inherent limitations as a tool for 

systematics. The alleles of sister species reach monophyly after all ancestral 

polymorphism is lost through genetic drift or directional selection. Although drift is 

expected to be much quicker for mitochondrial genes than nuclear genes (as a 

consequence of a smaller effective population size for the former), incomplete 

lineage sorting can still affect mitochondrial gene trees, especially in the case of 

rapidly radiating taxa in which successive speciation events occur before sorting is 

completed (Funk & Omland 2003). Such an effect is suspected to obscure the 

phylogeny of delphinids, in particular within the group commonly referred to as STDL, 

which encompass the species of Stenella, Sousa, Tursiops, Delphinus and 

Lagenodelphis (Reeves et al. 2004). As a result, several molecular markers, 

including mitochondrial and nuclear markers, are now commonly combined to resolve 

phylogenetic relationships among cetacean species (e.g., Harlin-Cognato & 

Honeycutt 2006, Caballero et al. 2007). 

Other sources of uncertainty may exist. Natoli et al. (2006) recently suggested that 

the populations of long-beaked common dolphin (Delphinus capensis) in the Pacific 

and South Africa could have each radiated independently from their sister-species, 

the short-beaked common dolphin (Delphinus delphis). This would represent a case 

of morphological convergence, rather than being the sole consequence of incomplete 

lineage sorting. Similarly, it is believed that the morphotypic similarities between the 

Asian and South African populations of Tursiops aduncus are a result of 

convergence, the two being highly genetically differentiated (Natoli et al. 2004). 

Ultimately, in order to resolve the taxonomic status of dolphin species it has been 

recommended that congeneric analyses be conducted, including, for each of the 

series of putative taxa, a large number of specimens from across its range (Funk & 

Omland 2003, Reeves et al. 2004). 

1.2.3. Convergence with terrestrial mammals 

Perhaps the most striking and interesting characteristic of cetacean evolution (and of 

odontocetes in particular), is the several lines of convergence found with terrestrial 

5


mammals (Best 1979, Würsig 1989, Weilgart et al. 1996). For example, comparisons 

between dolphins and apes shows convergence towards large brain size*, long lifespan, 

slow rate of reproduction, complex social organisation and cultural 

transmission (Connor et al. 2000a, Marino 2002, Krützen et al. 2005, Connor 2007). 

Yet, cetaceans and terrestrial mammals evolved entirely isolated from each other 

since early in the Cenozoic radiation of mammals (archaecete cetaceans were 

established at sea by early Eocene time, about 50 mya (Barnes et al. 1985)). 

The evolution of cetaceans and terrestrial mammals occurred in radically different 

physical and ecological environments, leading to numerous anatomical and 

physiological adaptations in the former (Würsig 1989). These differences include a 

lower cost of locomotion and a lack of refuge from predators in the ocean (Connor et 

al. 1998). The availability of resources is also likely to differ with richer but less 

predictable concentrations of prey in the marine environment (Connor et al. 1998). It 

implies, a priori, different ecological pressures and thus different systems which 

maximise fitness by best balancing the competing demands an organism faces with 

respect to reproduction and survival. Yet, contrary to the expectation that different 

environmental pressures should have resulted on different ecologies, the comparison 

of social organisation between odontocetes and terrestrial mammals shows 

numerous examples of convergence. The most striking example is found in the social 

structure of the sperm whale and the African savannah elephant; in both species 

mature females and their young form stable groups, while bachelor males herd 

together and wide-ranging lone bulls rove, searching for mating opportunities 

(Weilgart et al. 1996). Many examples are also found among dolphins. The structure 

of some bottlenose dolphin communities appears to be very similar to the “fissionfusion” 

structure of chimpanzee societies (Tayler & Saayman 1972, Würsig 1978), 

notably regarding the alliances formed between males to coerce females (Connor et 

al. 1992). These alliances have also been described in lions (Packer et al. 1991). In 

killer whales and bonobos, mothers and sons seem to form very strong associations 

*It seems that odontocete brain size has co-evolved with extended life history periods (similarly to 

primates and birds) and that lengthened adult period could have been an important component of 

their encephalisation (Lefebvre et al. 2006). Although primates and cetaceans have evolved very 

different ways of increasing their brain mass (Marino 2002), it is thought that large brain size is 

directly related to the development of social bonds and the formation of co-operative relationships 6 

(e.g., Barton 1996, Connor 2007, but see Healy & Rowe 2007).


(Connor et al. 2000a). Despite these similarities, long-term studies revealed that the 

fish-eating “resident” killer whales along the western coast of North America present 

a particularly interesting system of social structure that has not been yet described in 

any terrestrial mammal. Indeed, within these killer whale communities, neither males 

nor females disperse from their natal group (while bonobo and chimpanzee females 

do disperse). This pattern could be extended to other species of delphinids such as 

the long-finned pilot whales (as suggested from molecular studies, Amos et al. 1993). 

Although these comparisons appear as a promising framework to study the forces 

behind the evolution of mammalian societies, it is obvious that such investigation is 

still limited by the lack of knowledge on cetaceans in comparison to that available on 

terrestrial mammals. Futhermore, the examples above illustrate the fact that it is not 

simple to determine the evolutionary drivers behind the social patterns observed at 

sea and on land. 

1.3. Investigation of population structure 

1.3.1. A challenging task in delphinid species 

Populations constitute interbreeding units with more or less autonomous dynamics 

and recruitment (but note that there are many different definitions of 'populations', 

(Waples & Gaggiotti 2006)). Whilst the boundaries of some populations are rather 

obvious, others are not. Yet, a crucial pre-requisite for management and effective 

conservation of any population is a clear understanding of its structure within 

demographic and evolutionary time scales (Lande & Barrowclough 1987, Taylor & 

Dizon 1999). Note that in dolphin studies, and in analogy to primate studies, the 

terms “community” or “society” (Struhsaker 1969) have often been employed as a 

complement to, or instead of, the term “population” (e.g., Bigg 1982, Wells 1986). 

Here, I will employ the definition proposed by Wells (1986, p19) for a dolphin 

community: i.e., “an assemblage of dolphins that inhabited similar ranges and that 

interacted socially more with each other than with adjacent assemblages”. 

Investigating dolphin populations or communities poses a particular challenge 

because of the lack of obvious geographical boundaries and because of the mobility 

of individuals. It is hard to determine the population subdivisions of species that have 

7


a vast geographic distribution and that migrate widely in relation to seasonal or 

environmental changes (Hayano et al. 2003). Furthermore, well-known physical 

oceanographic barriers to gene flow (e.g., currents, physio-chemical water 

properties) that affect many marine species do not necessarily affect the movements 

of highly mobile cetaceans. 

Contrary to the expectation of large panmictic populations as a result of a few 

geographical and physical barriers, many dolphins show a relatively extensive 

structure among populations (Hoelzel et al. 2002a). Hoelzel et al. (1994, 1998) 

highlighted that geographical barriers, or the apparent lack of them, are not 

necessarily good indicators of population genetic structure in cetaceans. Whilst some 

differentiation may be expected on the basis of allopatry and isolation by distance, or 

restricted gene flow due to physical boundaries, many other examples cannot be 

easily explained in this way. In the western North Atlantic, investigation of the genetic 

population structure of the Atlantic spotted dolphin (Stenella frontalis) showed 

significant genetic differentiation even though this species is continuously distributed 

in this area (Adams & Rosel 2006). Following this, the authors suggested that in 

other areas where Stenella frontalis is continuously distributed (e.g., in the eastern 

Atlantic), the population might not be panmictic either. Consequently, this lack of 

information could have a detrimental effect on the long-term viability and 

maintenance of genetic diversity in this species in regions where incidental humaninduced 

mortality occurs (Adams & Rosel 2006). Another example is provided by 

Pichler et al. (1998) who found a high level of population differentiation across the 

range of Hector’s dolphins (Cephalorhynchus hectori) in New Zealand although no 

obvious geographic boundaries separate these regional populations. Behavioural 

observations and the movement of naturally marked individuals also suggest that 

isolation among local populations is the result of ecological preferences and strong 

philopatry (Dawson & Slooten 1993). The low rate of female dispersal in Hector’s 

dolphins, as evidenced by mtDNA structure, indicates a vulnerability to local 

extinctions and a poor ability to recover via recruitment of non-indigenous females 

(Pichler et al. 1998, Pichler & Baker 2000). 

8


Many of the observed patterns are likely due to a complex interaction between 

historical changes in marine environments (e.g., the impact of ice ages), resource 

requirements and specialisations, and aspects of life history and demographics 

(Hoelzel et al. 2002a). In this context, the use of molecular markers has played an 

increasingly important role in the study of cetacean population structure and thus, in 

the management and conservation of these species (e.g., Rosel et al. 1994, Baker & 

Palumbi 1995, García-Martínez et al. 1999). Genetic data contain information on the 

present and past structure of the populations that can not be obtained by any other 

method (Avise 2004). As such, most examples of dolphin population structure 

mentioned in this thesis have been revealed by molecular studies. Note, however, 

that it is not the only tool, as photo-identification or telemetry data can provide 

valuable and complementary information on the patterns of individuals’ movements 

(Whitehead 2001). 

1.3.2. Factors driving dolphin population structure 

Different factors such as sea-surface temperature, behavioural specialisation, 

isolation-by-distance, social system and historical processes are thought to shape the 

structure of dolphin populations (Hoelzel et al. 2002a). This section presents a few 

examples which illustrate these factors. 

In the North Atlantic, the patterns of genetic differentiation in long-finned pilot whales 

(Globicephala melas) suggest that population isolation occurs between areas that 

differ in sea-surface temperature (Fullard et al. 2000). On the other hand, population 

differentiation shows no correlation with geographical distance (Fullard et al. 2000). 

Temperature also seems to be the primary factor determining the relative distribution 

of two populations of short-finned pilot whales off the coast of Japan (Kasuya et al. 

1988). However, these correlations might not illustrate a particular sensitivity of these 

two species for sea-surface temperature, but instead may be the result of other 

ecological factors such as prey behaviour (Sergeant 1962). Such a pattern has been 

suggested for several other species of dolphins such as the dusky dolphin 

(Lagenorhynchus obscurus) in Argentina (Würsig & Würsig 1980). In temperate 

waters, water temperature could affect prey distribution and in turn affect the 

distribution of dolphin species (Norris 1967, Kasuya et al. 1988). For pilot whales, it is 

9


also possible that other mechanisms are involved in these segregations, such the 

effects of strong maternal philopatry (Whitehead 1998, Fullard et al. 2000). 

Hoelzel (1998) suggested that an important mechanism for the formation of intraspecific 

genetic differentiation within a geographic region is resource and/or habitat 

specialisation. The best documented example is found in the sympatric forms of fisheating 

“resident” and mammal-eating “transient” killer whales of the eastern North 

Pacific (Bigg et al. 1990). Evidence suggests that they are genetically isolated from 

one another at the mitochondrial and nuclear level (Stevens et al. 1989, Hoelzel & 

Dover 1991, Hoelzel et al. 1998a, Barrett-Lennard 2000). 

Another striking example of segregation likely to be the result of resource or habitat 

specialisation is found in the parapatric populations of nearshore and offshore 

Tursiops truncatus in the western North Atlantic and Gulf of Mexico. Here, genetic 

comparisons suggest limited or no gene flow in the recent past between the two 

forms (Duffield et al. 1983, Hoelzel et al. 1998b, Sellas et al. 2005). It is also known 

that in the western North Atlantic, the nearshore form feeds primarily on coastal 

fishes while the offshore form forages on deep-water squids (Mead & Potter 1995). 

In the eastern North Atlantic and Mediterranean Sea, Natoli et al. (2005) identified 

five genetic populations of bottlenose dolphins and observed that the boundaries 

between these populations coincide with variations of different oceanographic 

parameters. From this, they suggested that local populations are habitat dependent 

in such a way that it defines patterns of movement (Natoli et al. 2005). Such patterns 

in bottlenose dolphin populations are also supported by other ecological data with, for 

example, a relationship between feeding behaviour and habitat type (Gannon & 

Waples 2004, Hastie et al. 2004). 

For the bottlenose dolphins in Shark Bay, Australia (referred here as Tursiops sp., 

since molecular and morphological data failed to differentiate between truncatus and 

aduncus; M. Krützen pers. comm.), a significant correlation was found between 

genetic differentiation (using nuclear and mtDNA markers) and distance between 

localities (Krützen et al. 2004b). Isolation-by-distance appears to be a factor that can 

10


shape local dolphin populations. This finding was supported by behavioural data that 

suggested natal philopatry for Shark Bay dolphins (Connor et al. 1992, Smolker et al. 

1992, Richards 1996). However, on a larger scale, no such relation of isolation-bydistance 

was found between the populations of bottlenose dolphins from Moray Firth, 

north Scotland, and the neighbouring populations (Parsons et al. 2002). 

Krützen et al. (2004b) suggested that population structure in male bottlenose 

dolphins in Shark Bay may also be related to the evolution of mating systems. Males 

are known to form alliances which permit these allied males to more successfully 

compete for access to females (Connor et al. 1992). Evolutionary theory predicts that 

if the males cooperating in this manner are related to each other, then they may gain 

inclusive fitness benefits (Hamilton 1964a, b). Long-range dispersal of males to other 

areas would thus minimise the chance of allying with a related partner (it was shown 

that long-lasting alliances are biased toward related males, Krützen et al. 2003). 

Therefore, social system would be simultaneously impacting with geographical 

distances on the structure of the population. 

At Sarasota Bay, central west Florida, USA, genetic analyses and extensive 

behavioural data also support the hypothesis that the genetic distinction of a small 

community of bottlenose dolphins (in regards to similar neighbouring communities) is 

due to their social system (Wells 1986, Duffield & Wells 1991, Sellas et al. 2005). 

There is, however, some gene flow with adjacent communities, thought to be largely 

but not exclusively driven by male movements, as illustrated by the sharing of mtDNA 

haplotypes between communities (Duffield & Wells 2002). 

Finally, historical processes might also shape the structure of contemporary dolphin 

populations. In particular, the glacial/interglacial events of the Pleistocene epoch 

(1,808,000 to 11,550 years BP) could have played an important role, considering the 

recent radiation of dolphin species. Hayano et al. (2004) suggested that the lowering 

of the sea level during the late Pleistocene resulted in the isolation of some Pacific 

white-sided dolphins in the Sea of Japan from the rest of the North Pacific population. 

This may explain the genetic differentiation currently observed between the 

11


population in Japanese coastal waters and the offshore population of the North 

Pacific. 

1.4. Genetic diversity 

Throughout their evolutionary history, each species has had to face variations in their 

environment; for example, climatic changes. To survive these variations, genetic 

diversity is thought to be the base material upon which adaptation and speciation 

depend. Maintenance of populations’ genetic diversity is thus a major focus in 

conservation biology (Frankham et al. 2002), especially considering that 

environmental changes are now augmented by anthropogenic impacts (e.g., through 

the effects of global warming, pollution and habitat destruction). In general, high 

levels of genetic variability are seen as healthy, while low levels of variability are seen 

as limiting a species’ ability to respond to various threats in both the long- and shortterm. 

Measures of intra-specific genetic diversity (traditionally based on protein allozymes) 

vary considerably across taxa, with a tendency for large mammals to show relatively 

low levels compared to that of other taxa (Nei 1987, Avise 2004). Diversity may be 

gained either through mutation or through gene flow from a neighbouring population, 

while loss of diversity occurs either passively through genetic drift or actively through 

natural selection. Based on these principles, various processes can potentially 

reduce genetic diversity in a population. Among them, demographic bottleneck (i.e., a 

dramatic reduction in abundance) is one of the most important, in particular from a 

conservation point of view (Frankham et al. 2002). 

Among dolphins, Pichler & Baker (2000) found unusually low levels of mitochondrial 

diversity in contemporary populations of Hector’s dolphins in New Zealand. A 

comparison with historical samples revealed a significant decline in diversity which is 

most likely the result of abundance depletion due to dolphin mortality in gill-nets. A 

bottleneck is also thought to have reduced the mitochondrial diversity in the 

population of dusky dolphins along the coast of Peru (Cassens et al. 2005). The use 

of several molecular markers suggests, however, that this bottleneck is rather 

ancient, pre-dating the recent El Niño oscillations and human exploitation of this 

12


population (Cassens et al. 2005). On a larger scale, Hoelzel et al. (2002b) suggested 

a historical bottleneck as a potential cause for the low worldwide genetic diversity of 

killer whales. Other processes might also be involved in shaping the genetic diversity 

in this species (see below in this section). 

Hayano et al. (2004) suggested that the low genetic diversity found in the population 

of Pacific white-sided dolphins along the coast of Japan was a result of a population 

reduction. This could have occurred when the individuals in the Sea of Japan 

became isolated from the rest of the North Pacific population during a glacial period 

in the Late Pleistocene. This could also be considered a founder event rather than a 

demographic bottleneck, since it does not necessarily represent a real decrease in 

abundance. Although they represent different demographic processes, bottleneck 

and founder events can have the same effect on the level of genetic diversity in a 

population. Cases of founder events have been suggested for several nearshore 

populations of bottlenose dolphins (notably in the western North Atlantic and South 

Africa) in order to explain the lower level of genetic diversity than that in the offshore 

populations from which they could have originated (Hoelzel et al. 1998b, Natoli et al. 

2004). 

Social behaviour can also reduce genetic diversity within local populations, for 

instance as a result of high philopatry. This could be the case for the population of 

about 130 bottlenose dolphins at Moray Firth, Scotland, that show no evidence of 

contemporary exchange with neighbour populations (Wilson et al. 1999). Indeed, 

Parsons et al. (2002) found a very low level of mtDNA variability among these 

dolphins, which, in such a small population, could be due to the relative importance 

of genetic drift. A similar case of low mtDNA diversity is observed in Doubtful Sound, 

New Zealand (de Tezanos Pinto et al., unpublished data), within a small and isolated 

community of bottlenose dolphins living in a fiord. 

Unusually low levels of mitochondrial diversity were also found in several species of 

dolphins thought to live in matrilineal societies (Whitehead 1998). These include killer 

whales, long-finned pilot whales and short-finned pilot whales (with sperm whales 

following a similar pattern). To explain this trend, Whitehead (1998, 2005) 

13


hypothesised a form of “cultural hitchhiking” where mtDNA diversity is reduced by 

parallel selection on maternally transmitted cultural traits. However, several authors 

argue against this theory (e.g., Mesnick et al. 1999) and alternative models based on 

demographic processes were proposed to explain low mtDNA diversity in matrilineal 

whales (e.g., Tiedemann & Milinkovitch 1999). At this stage, the debate continues, 

illustrating the difficulty in interpreting patterns of genetic diversity in these species 

(Alexander 2006). 

1.5. Social system 

Alexander (1974) argued that while there seems to be no universal benefit from 

group-living, there are universal detriments, such as parasite transmission and 

competition for resources. Yet, one of the most obvious characteristics of dolphin 

ecology is their propensity to live in groups. In contrast to random aggregations (for 

example, due to food concentration), dolphin groups are more usually seen as 

mutualistic groups, i.e., based on the exchange of benefits among individuals 

(hereafter, I will simply use the term ‘group’). 

For many scientists, predation is believed to be the major factor promoting group 

formation (Alexander 1974, van Schaik 1983). This hypothesis lends well to dolphins, 

and especially smaller open-ocean species, considering the lack of refuges in the 

oceans within which they could hide from their main predators, i.e., oceanic sharks 

and killer whales (Norris & Schilt 1988). For a review of the different ways by which a 

group can reduce the risks of predation, see Connor (2000). Similarly to other taxa, 

additional factors can also favour group-living in dolphins; for instance, the defence of 

resources (Wrangham 1980, 1982), the defence of females against other males 

(Wrangham 1980), and the protection of females against male aggression. In addition 

to these benefits of group living, it has been suggested that, contrary to terrestrial 

mammals, the low cost of locomotion in the water might reduce food competition, and 

thus reduce the cost of grouping and philopatry in cetaceans (Connor 2000). 

As illustrated by their strong tendency to live in groups, all dolphin species are social 

to some degree (LeDuc 2002). However, characteristic group sizes for the different 

species range from small pods of just a few individuals to large schools numbering in 

14


the thousands. Group sizes can also vary within population depending on the 

behavioural state of the dolphins (e.g., Würsig & Würsig 1980). These variations 

presumably represent adaptation to different environmental pressures, depending on 

life history parameters of, and habitat use by, the species. In general, the social 

structure of female mammals is thought to be more influenced by predation and prey 

resources, while male social structure is more influenced by access to mates 

(Wrangham & Rubenstein 1986). 

In the delphinid family, other than the few populations that have been investigated in 

detail, the sizes of stable social units and the social boundaries of the communities 

are unknown. Furthermore, these populations that have been studied over long time 

scales are those that form relatively stable and small social groups within a short 

distance of the coast and whose movements do not regularly take them out of their 

study areas. Therefore, one must be aware that the social patterns of these 

populations may not reflect the organisation of offshore populations of the same 

species (LeDuc 2002). 

An accurate model of a social system is essential to improve understanding of the 

ecological pressures affecting sociality (Myers 1983). Here, social system refers to 

the combination of three distinct elements: social organisation, social structure and 

mating system (Kappeler & van Schaik 2002). Social organisation describes the size, 

sexual composition and spatio-temporal cohesion of a community. Social structure 

refers to the pattern of social interactions and the resulting relationships among the 

members of a community. Mating system describes social interactions related to 

mating (social component) and the reproductive consequences of these interactions 

(genetic component). The study of sociality in dolphins is still in its early stages 

compared, for example, to research on primates (Smuts et al. 1987, Kappeler & van 

Schaik 2002). However, despite limited information, previous studies have revealed a 

high level of diversity and complexity in the social systems of dolphins. Interestingly, 

diversity exists between species as well as within species. Many populations of 

bottlenose dolphins around the world have been described as ‘fission-fusion’ 

societies (Connor et al. 2000b), where fission-fusion refers to social systems in which 

individuals of a same population live in subgroups that frequently merge and 

15


dissociate again with similar or different memberships. However, long-term studies of 

populations in different regions have shown that association patterns can show 

substantial variability for both males and females (Connor et al. 2000b). 

In Shark Bay, Australia, bottlenose dolphin males (Tursiops sp.) show a complex 

pattern of alliances. There are stable ‘first-order’ pairs and trios that herd individual 

females; ‘second-order’ teams of two first-order alliances that join forces against 

rivals in contests for females; and ‘super-alliances’ where males form highly labile 

pairs or trios that herd females, contrasting with the stable alliances (Connor et al. 

1992, Connor et al. 1999). In Sarasota Bay, Florida, male bottlenose dolphins are 

also found to form stable pairs (95% of their time spent together, Wells et al. 1987). 

These pairs tend to form at sexual maturity between males of similar age, and seem 

to be maintained through life, until one member dies (Wells et al. 1987). In contrast to 

Shark Bay, however, the level of aggression between males and receptive females in 

Sarasota is minimal. It was suggested that, in Sarasota, female choice could play an 

important role in determining mating opportunities (Connor et al. 2000a). A different 

pattern is found in the Moray Firth, Scotland, where male bottlenose dolphins do not 

show the high association coefficients with other males that are typically observed in 

other populations (Wilson 1995). This could be related to the wide coastal range for 

bottlenose dolphins of this population, in comparison to smaller ranges of resident 

dolphins of Shark Bay or Sarasota which stay in a limited area over several years. 

However, in the Bay of Islands, New Zealand, where bottlenose dolphins are also 

found to range widely along the coast (Constantine 2002), Mourão (2006) described 

a similar pattern to Shark Bay and Sarasota bottlenose populations, with several 

close and long-lasting associations within and between sexes. Finally, in Fiordland, 

New Zealand, Lusseau et al. (2003) observed that, contrary to most populations of 

the T. truncatus, bottlenose dolphins (both males and females) form a temporally 

stable community, where constant companionship is prevalent. This is a much higher 

degree of social stability than in other studied populations of bottlenose dolphins, with 

strong association occurring within and between sexes. They hypothesised that 

ecological constraints are an important factor shaping social interactions within the 

community. 

16


Similarly, two populations of spinner dolphins from distant islands in the Hawaiian 

Archipelago (the Big Island and Midway Atoll) have been found to have different 

social organisations (Norris et al. 1994, Karczmarski et al. 2005). In the remote atoll 

of Midway, spinner dolphins seem to live in a smaller and more stable society, with 

no obvious fission-fusion fusion. This is unlike the large groups and fission-fusion 

observed in spinner dolphins at the Big Island (Karczmarski et al. 2005). The authors 

suggest that these disparate characteristics were triggered by different environmental 

pressures. 

A common pattern in terrestrial mammals is a male-biased dispersal with female 

philopatry (Greenwood 1980). Such a pattern also seems to occur in some dolphin 

populations, as shown by molecular studies on bottlenose (Möller & Beheregaray 

2004) and dusky dolphins (Cassens et al. 2005), and also by long-term demographic 

studies (e.g., Wells 1986). However, female philopatry and male dispersal is not 

always the rule in dolphins. Long-term studies on killer whales and molecular studies 

on long-finned pilot whales have suggested that in some populations of these two 

species, individuals live in matrilineal groups with no dispersal by either sex (Bigg et 

al. 1990, Amos et al. 1993). Such an extreme scenario of philopatry has not yet been 

described in any terrestrial mammals (Connor 2000). Note that killer whales offer 

another example of intra-species diversity of social structure. In the eastern North 

Pacific, communities of fish-eating “resident” killer whales (where no dispersal of 

either sex occurs) are more stable than the communities of mammal-eating 

“transient” killer whales, where individuals of both sexes might disperse from their 

natal group (Baird & Whitehead 2000). The authors suggest that these dissimilar 

social structures could be related to differences in foraging ecology. 

Among the factors influencing group composition in social mammals, kinship is 

thought to play a major role. While an individual can enhance its fitness directly by 

maximising its own reproduction (Williams 1966), it can also do so indirectly by 

maximising the reproduction of its relatives (Hamilton 1964a, b). Following the latter, 

kin selection theory predicts that individuals should preferentially associate and 

cooperate with kin whenever the inclusive benefits outweigh the costs (Hamilton 

1964a, b). In the population of Tursiops sp. from Shark Bay, Krützen et al. (2003) 

17


show that males in first- and second-order alliances are more related than expected 

by chance, suggesting that they could gain inclusive fitness benefits from alliance 

membership. On the other hand, they found no significant relationship between 

members of super-alliances. Therefore, it seems that different models of the 

evolution of social behaviour can favour association between males of this 

population, similar to that in lions (Packer et al. 1991). In Tursiops truncatus males, 

which form long-term alliances in the Bahamas, Parsons et al. (2003) found highly 

significant correlations between patterns of association and both mitochondrial DNA 

haplotype identity and microsatellite relatedness, as expected under the kin selection 

theory. Contrary to the last two examples, however, no correlation was found 

between associations/alliance membership and maternal kinship or genetic 

relatedness in male Tursiops aduncus of Port Stephens, Australia (Möller et al. 

2001). In that resident population, the majority of male pairs within alliances were 

randomly related, although high relatedness values were found between males of 

different alliances. Therefore, mechanisms other than kin selection seem to favour 

cooperation between males in this case. However, Möller et al. (2006) showed that 

among female Tursiops aduncus of the same population, association correlates with 

kinship, although kinship relations are not necessarily a prerequisite for membership 

in social clusters. Möller et al. (2006) hypothesised that different evolutionary forces 

acting on female bottlenose dolphin sociality might promote the formation of 

associations. 

Note that correlation between behavioural association and kinship must be 

interpreted with caution. Griffin & West (2002) argued that such a relationship is not, 

in itself, sufficient evidence that kin selection is operating. Rather, a direct evaluation 

of the relative reproductive success is necessary (e.g., Griffin et al. 2003). The study 

by Krützen et al. (2004a) was a first attempt to do so in a population of dolphins, 

revealing notably, that being a member of a bottlenose dolphin alliance is not a 

prerequisite for paternity. Further similar studies are needed to allow a more 

productive comparison of dolphin social organisation to that of terrestrial mammals. 

18


1.6. Principal methodological tools used in this study 

1.6.1. Photo-identification 

Individual identification has a long history in the study of animal ecology; for example, 

the use of coloured bands to follow the movement of birds (Lockley & Russell 1953). 

In cetaceans, the first method utilised to identify individual animals was based on 

“discovery marks” that were shot by the whalers into the blubber of whales and 

recovered later when the animals were killed and flensed (Brown 1978). In the 1970s, 

biologists started to use natural marks to recognise individuals, notably using 

photographs of scars on and the shape of dolphins’ dorsal fins (e.g., Würsig & Würsig 

1977). 

Since then, identification of individual whales and dolphins by using photographs of 

natural markings (e.g., trailing edge and pigmentation of humpback whales’ flukes, or 

head callosities of right whales) has been a key component to all long-term and 

reasonably detailed studies of cetacean social organisation (e.g., Bigg et al. 1990). 

This technique has now been applied to more than 30 species of cetaceans (Mann 

2000). Photo-identification can provide a wide range of information, including 

movements and association patterns, population size and dynamics (e.g., Wells 

1986, Smolker & Richards 1992, Rossbach & Herzing 1998, Wilson et al. 1999, Parra 

et al. 2006). In long-term studies, it can also provide information on basic life history 

parameters (Würsig & Jefferson 1990, Wells 2003) and in combination with other 

information such as group composition, it has the potential to provide a model of 

social systems (Whitehead 1997). See Whitehead et al. (2000) for a review on photoidentification 

techniques. 

For this thesis, photo-identification techniques was used on spinner dolphins 

(Chapter 2) and rough-toothed dolphins (Chapter 6) to investigate various aspects of 

their social organisation, including community size, pattern of residency and rate of 

inter-change. 

19

1.6.2. Biopsy sampling 


For many research questions, observational methods alone are not sufficient. For 

example, by using photo-identification it is possible to obtain some knowledge of 

population structure, although this method provides information over only a short time 

scale (one generation or a few at best). Using molecular tools, however, one can 

easily study the structure and dynamics of a population on an evolutionary time scale 

(over several generations), providing critical information for conservation issues. 

Collecting the tissue samples necessary to conduct genetic analyses is not trivial. 

Among the sources of samples exploited by scientists for cetacean studies are 

strandings (e.g., Pichler et al. 1998), incidental by-catch (e.g., Dizon et al. 1991) and 

direct hunting (e.g., Amos et al. 1993). Although these sources have proven to be 

extremely valuable in many instances, they also have major drawbacks. These 

sources can be unreliable or inconsistent (for example, some species rarely strand or 

are not involved by-catch) or may be considered unethical (in particular those 

samples obtained from direct hunting). More importantly, they might offer a poor 

dataset for addressing specific issues such as demographics. Because of these 

limitations, biopsy sampling from wild, free-ranging cetaceans has been increasingly 

used, originally on large baleen whales (Lambertsen 1987). Biopsies are most often 

collected by using crossbows and modified rifles firing darts that collect small plugs of 

skin which provide enough material for genetic analyses (e.g., Barrett-Lennard et al. 

1996, Weller et al. 1997, but see Bilgmann et al. 2007). Recently developed biopsy 

systems use rifles with adjustable firing pressure and smaller dart cutting heads 

(Krützen et al. 2002). These systems are more appropriate for sampling small 

cetaceans, and it is now possible to biopsy dolphins with minimal impact. These 

systems have been shown typically to elicit only short-term behavioural responses by 

sampled animals, and no physiological complications have been reported during 

wound healing (Weller et al. 1997, Krützen et al. 2002). 

Other techniques of tissue collection on free-ranging cetaceans have also been 

developed that are even less invasive than biopsy sampling. These include skin 

swabbing (Harlin et al. 1999), faecal sampling (Parsons et al. 1999) and sloughed- 

20


skin sampling (Whitehead et al. 1990). However, these techniques also present some 

important disadvantages, such as a lower quality and quantity of tissue, which can 

greatly limit the genetic analyses (especially when using nuclear markers such 

microsatellite loci). Note also that, in terms of behaviour, a technique such as skin 

swabbing does not necessarily provoke less reaction by the sampled dolphin than 

does biopsy sampling (Harlin et al. 1999, Krützen et al. 2002). Therefore, depending 

on the research question asked and conservation status of the species, the 

advantages and drawbacks of the different methods should be considered so as to 

choose the most appropriate sampling technique (Bilgmann et al. 2007). 

Here, the Paxarms biopsy system©, described by Krützen et al. (2002), was used to 

collect skin samples of spinner dolphins (Chapter 2), short-finned pilot whales 

(Chapter 3) and rough-toothed dolphins (Chapter 4). This system is based on a small 

stainless-steel biopsy dart fired from a modified veterinary capture rifle equipped with 

a variable pressure valve (Krützen et al. 2002). The primary advantages of this 

system for this study were: (1) it provides the capability to rapidly adjust the rifle 

pressure in relation to the distance between the targeted dolphin and the boat 

(between two and ten metres) and with regards to the skin of the targeted species (at 

a similar distance from the boat, biopsy attempts on short-finned pilot whales 

required a higher pressure cartridges than on spinner dolphins for the dart to properly 

rebound off the animal and not remain attached); and (2) it obtains high quality tissue 

samples which allow the screening of microsatellite loci. Note that in the first stages 

of this study, skin swabbing with a pole was attempted, but this method was 

inefficient: spinner dolphins at Moorea rarely broke the surface while bow-riding the 

boat if the swabbing pole was hanging over their heads; in addition, samples 

collected with this technique on short-finned pilot whales provided poor quality DNA 

(data not shown). 

Most tissue samples used in Chapter 3, 4 and 5 were obtained from alternative 

sources; primarily strandings (see details in each chapter’s methods). 

21

1.6.3. Molecular markers 


Genetic data can provide information on individual identity, sex, kinship, philopatry, 

dispersal, mating systems and gene flow (Avise 2004). Some of these are difficult or 

impossible to obtain by any other means when investigating dolphin populations. For 

dolphins, and for cetaceans in general, microsatellite DNA markers and mitochondrial 

DNA (mtDNA) sequences have been particularly useful in population-level studies 

(e.g., Baker et al. 1993, Rosel et al. 1999, Escorza-Trevino & Dizon 2000). It is 

particularly productive to combine these two types of molecular markers in a study, 

as they present different advantages and characteristics. 

Mitochondrial DNA sequences – Over the years, mtDNA has become a definitive tool 

of choice in molecular systematics and conservation genetics (Avise 2004). Several 

of its characteristics make it especially valuable for investigating and understanding 

patterns of genetic variation. First, it is a relatively straightforward technique. Notably, 

there are several thousands of mitochondria in each cell, meaning that it is easier to 

extract and amplify its DNA compared to the single copy of nuclear DNA. This is 

particularly valuable when tissue samples are of limited size or bad quality (which 

occurs frequently for cetaceans). Second, the mutation rate in mtDNA is relatively 

high, in particular in the non-coding control region (D-Loop). The resulting high levels 

of polymorphism have allowed researchers to conduct both intra- and inter-population 

studies. Mitochondrial DNA is generally considered as a strictly neutral marker but 

this has been controversial (e.g. Rand & Kann 1996) and it is recommended to 

conduct tests of neutrality to explore this question (Ballard & Rand 2005). Third, there 

is generally no recombination between mitochondrial molecules (but see Rokas et al. 

2003). As a result, it is much easier, over space and time, to follow mitochondrial 

lineages than nuclear lineages. Last, the mitochondrial genome is haploid and 

maternally inherited in most species. It represents therefore only one quarter of the 

effective population size of the diploid nuclear DNA, and is more sensitive to certain 

demographic events (e.g., bottleneck events). Note however that if individuals are 

usually homoplasmic for one mitochondrial haplotype, heteroplasmic conditions have 

still been reported in several species (e.g. Wilkinson & Chapman 1991). 

22


In this thesis, sequences of the mtDNA control region were amplified using universal 

primers (see Chapter 2) to allow for comparison between species. The genetic 

diversity of this mtDNA region has also been investigated in several dolphin 

populations, allowing me to compare my results to those of other studies (Table 1.1). 

Microsatellites – At present, microsatellites (or short tandem repeat) are the most 

widely used DNA markers in population genetics, notably for molecular ecology and 

conservation studies (Chambers & MacAvoy 2000, Avise 2004). Their main 

advantage is that they are usually highly polymorphic, even in small populations and 

endangered species. This high polymorphism results from a high mutation rate, likely 

due to slipped-strand mis-pairing during DNA replication (Schlötterer & Tautz 1992). 

See Chambers & MacAvoy (2000) and Goldstein & Schlötterer (1999) for a review of 

these markers. 

Microsatellite variability has been investigated in cetaceans to address a number of 

different parameters, such as population structure, social structure (e.g., Amos et al. 

1993), mating system (e.g., Krützen et al. 2004a), dispersal pattern (e.g., Möller & 

Beheregaray 2004), recent evolutionary history (e.g., Dalebout et al. 2006) and 

individual recognition. Interestingly, the primers developed for one species can often 

be used for closely related species since the primer sites are generally highly 

conserved (e.g., Goldstein & Schlötterer 1999). In this thesis, advantage was taken of 

this characteristic by using a set of available ‘cetacean’ microsatellite primers 

developed for other species. A summary of the primers used for each species is 

presented in Appendix 1. Microsatellite variation was used to address questions 

related to population structure (Chapter 2 and 6), population size (Chapter 2), social 

organisation (Chapter 4, 5 and 6), sex dispersal (Chapter 2 and 6) and individual 

identification (Chapter 2 and 6). 

23

1.7. Thesis outline and collaborators 


This thesis aims to provide new insights into the population structure and social 

organisation of four species of dolphins: the spinner dolphin (Stenella longirostris), 

the long-finned pilot whale (Globicephala melas), the short-finned pilot whale 

(Globicephala macrorhynchus) and the rough-toothed dolphin (Steno bredanensis). 

These species were chosen because they represent different characteristics of 

habitat use and social organisation, providing a framework for comparison among 

species (Table 1.1). Here an outline of the work accomplished during the thesis and 

collaborators involved is provided. Note that general information on the four species 

is provided in the introduction of each of the following chapters. 

Table 1.1. Social system and life history attributes of dolphins under investigation in this thesis. 

Species 

Focal 

location 

Group 

Size 

Community 

size 

Community 

range 

Social 

structure 

Philopatry Habitat 

Spinner 

dolphin 

Moorea 

Society 

Archipelago 

10-90 

~150 

Unknown 

Moorea/ 

Tahiti? 

Fission/ 

fusion 

Insular 

Day: insular 

Night: semipelagic 

Long-finned 

pilot whale 

Worldwide 

New 

Zealand 

10-300+ Large Unknown Matrilineal Nomadic Pelagic 

Short-finned 

pilot whale 

Worldwide 10-300 Large Unknown Matrilineal? Nomadic Pelagic 

Rough-toothed Moorea 

dolphin Raiatea 

10-50 Unknown Unknown Unknown Regional? 

Semipelagic 

Chapter two examines the social and reproductive boundaries of insular 

communities of spinner dolphins in French Polynesia. First, the community around 

the island of Moorea was investigated in details, estimating its size and demographic 

stability using capture-recapture datasets based on photo-identification and genetic 

sampling. Then, demographic and genetic connectedness between different 

communities of the Society Archipelago was estimated to describe the dynamics of 

24


the insular spinner dolphin population in this region. These results have been 

published in Marine Ecology - Progress Series: 

Oremus M., Poole M.M., Steel D. and Baker C.S. (2007) Isolation and interchange 

among insular spinner dolphin communities in the South Pacific revealed by 

individual identification and genetic diversity. Marine Ecology Progress Series 

336: 275-289. 

I collected the data used in this chapter (photographs and biopsy samples) during 

three field seasons in French Polynesia (2002 to 2004), which I organised with the 

help of my supervisors, C.S. Baker (The University of Auckland, NZ/Oregon State 

University, US) and M.M. Poole (Marine Mammal Research Program, Moorea, 

French Polynesia). Analyses benefited from the photo-identification catalogue of 

spinner dolphin dorsal fins compiled by M.M. Poole between 1987 and 1992 at 

Moorea (Poole 1995). 

Chapter three describes the worldwide mtDNA diversity of long-finned and shortfinned 

pilot whales. Phylogenetic reconstructions and phylogeography of mtDNA 

haplotypes were investigated to test monophyly of the two species and to attempt to 

explain the current distribution of worldwide mtDNA diversity. 

Samples used in this chapter were made available by several people and institutions 

(the samples’ places of origin are in parentheses): C. Garrigue, Opération Cétacés 

(New Caledonia), C. Olavarría (Samoa), S. Gaitan-Caballero and A. Mignucci- 

Giannoni (Puerto Rico), C.S. Baker (New Zealand, Japan, and Korea), R. Gales 

(Tasmania), N. Funahashi and T. Endo (Japan). Samples from New Zealand were 

collected courtesy of the Department of Conservation (DoC) and staff from the 

University of Auckland (including C.S. Baker, R. Constantine, D. Steel and A. 

Alexander). I collected biopsy samples in French Polynesia between 2002 and 2004 

during opportunistic encounters that occurred while I conducted small-boat surveys. 

All the sequences from Japanese samples were provided by C.S. Baker (as analysed 

by himself, M.L. Dalebout, S. Lavery and V. Lukoschek). I genetically processed and 

analysed most of the other samples but some were processed by D. Steel and M.L. 

25


Dalebout. Previously published sequences from GenBank were also added to this 

dataset. 

A manuscript based on these results is in preparation to be submitted for publication, 

from which I will be first author. Co-authors include C.S. Baker, M.L. Dalebout 

(University of New South Wales, Australia), R. Gales (Department of Primary Industry 

and Waters, Tasmania, Australia), N. Funahashi (International Fund for Animal 

Welfare, Japan), T. Endo (University of Hokkaido, Japan) and T. Kage. 

In Chapter four, a genetic study of mass strandings in New Zealand was conducted 

to investigate the social system of long-finned pilot whales. In particular, I test the 

hypothesis that this species lives in extended matrilineal groups, an assumption 

recently questioned by the results of a behavioural study (Ottensmeyer & Whitehead 

2003). 

All of the samples used in the chapter came from the marine mammal tissue archives 

held at the University of Auckland. These samples were collected over the last 15 

years by staff from the University of Auckland and DoC, in collaboration with Anton 

van Helden and the National Museum of New Zealand (Te Papa Tongarewa). 

Additional samples were made available by C. Schroeder and F. Pichler. I genetically 

processed and analysed most of these samples. However, similarly to Chapter 3, 

some were processed for DNA extraction, molecular sexing and mtDNA control 

region sequencing by D. Steel and M.L. Dalebout. 

A manuscript based on these results is in preparation and will be co-authored by C.S. 

Baker and D. Steel (Oregon State University, USA). 

Chapter five explores the long-standing assumption that long-finned pilot whales 

maintain social bonds during mass strandings. To test this assumption, I searched for 

a correlation between kinship and spatial distribution of the whales stranded on a 

beach after a large mass stranding at Stewart Island, New Zealand in 2003. This 

work was made possible thanks to the data collected by DoC Southland staff, 

coordinated by Helen Kettles. I processed and analysed all the samples used in this 

26


chapter. The manuscript derived from this chapter will be co-authored by C.S. Baker 

and H. Kettles. 

Results presented in the Chapters 4 and 5 were presented in December 2005 at the 

Society for Marine Mammalogy conference at San Diego, US: 

Oremus M., Kettles H., Schroeder C., Gales R., Steel D. and Baker C.S. (2005) ‘O 

mother where art thou?’ Genetic investigation into mass strandings of longfinned 

pilot whales. 16 th Biennial Conference on the Biology of Marine 

Mammals. San Diego, USA, December 12-16, 2005 

Chapter six describes the population structure of rough-toothed dolphins observed 

in the nearshore waters of the Society Islands, French Polynesia. Photo-identification 

data and levels of mtDNA diversity provide new insights into their social structure 

when compared to results obtained on spinner dolphins and pilot whales. Similarly to 

Chapter 2, I collected and processed all data for this chapter during three field 

seasons in French Polynesia, between 2002 and 2004. A manuscript based on this 

chapter is intended for submission to the journal Conservation Genetics: 

Oremus M., Poole M.M. and Baker C.S. (in prep) Evidence of fine-scale population 

structure in rough-toothed dolphins from the Society Archipelago, French 

Polynesia. 

Chapter seven provides some final conclusions, proposes future research following 

the results presented in this thesis and reviews the completion of the primary 

objectives of this study. 

27

Chapter Two: Insular communities of spinner dolphins. 

2. Isolation and interchange among insular spinner 

dolphin communities in the South Pacific revealed 

by individual identification and genetic diversity 

A spinner dolphin bow-riding in Tahiti, November 2003. 

28

2.1. Abstract 


Spinner dolphins (Stenella longirostris) are found in apparently relatively small and 

discrete communities around many islands throughout the Pacific. However, the 

boundaries of these communities on the scale of a dolphin’s lifespan or across 

generations are unknown. Here a combined demographic and genetic approach is 

reported to describe the isolation and interchange of insular spinner dolphins among 

island communities of the Society Archipelago, French Polynesia. Dorsal fin 

photographs for individual identification and biopsy samples for genetic analyses (n = 

154) were collected from six island communities during 189 small-boat surveys over 

three years. Capture-recapture analyses at Moorea (the primary study site), based on 

long-term observations of distinctively marked individuals and microsatellite 

genotypes (12 loci), indicated a local community of about 150 dolphins. This 

community appeared relatively closed on an intra-generational scale, as confirmed by 

re-sightings of individuals across 15 years. Surveys around neighbouring islands 

indicated the presence of similar distinct communities, likely to follow similar 

demographic patterns to Moorea, with relatively low level of interchange between 

communities. Overall, significant differentiation at both mitochondrial and nuclear 

levels indicates restricted gene flow among neighbouring communities, although 

some individual movement was documented. High levels of insular mtDNA genetic 

diversity (Nef ~ 100,000) contrasted with demographic characteristics. No evidence of 

a bottleneck was found in microsatellite allele frequencies or mtDNA haplotypes, 

discounting the possibility of a recent founder effect. Instead, this genetic pattern 

suggests that it is the result of metapopulation structure, based on numerous insular 

communities evolutionarily connected through male and female gene flow. 

29

2.2. Introduction 


Dolphins are often found in relatively small and apparently discrete coastal or insular 

communities that are assumed to exhibit genetic exchange with neighbouring 

communities or larger pelagic populations (e.g., Wells 2003). However, with the 

exception of a few populations that have been the focus of extensive studies, the 

social and reproductive boundaries of the communities and the extent of 

demographic and genetic interchange remain unknown. 

Demographic approaches, based principally on photographic documentation of 

naturally marked individuals (i.e., photo-identification), can provide valuable 

information on social relationships and local abundance. These methods are limited, 

however, when assessing large-scale geographic structure and population dynamics 

that extend across generations. On the other hand, evolutionary approaches are 

often aimed primarily at estimating population genetic parameters but do not provide 

a clear distinction between the relative importance of contemporary and historical 

processes. Combining demographic and genetic methods can help overcome the 

limitations of each (Lande 1988). 

Spinner dolphins (Stenella longirostris) pose an interesting challenge to the 

description of community structure. The species has a worldwide circum-tropical and 

subtropical distribution (Perrin & Gilpatrick 1994) within which four subspecies have 

been described based on morphological characters, distribution and habitat 

preferences (Perrin & Gilpatrick 1994, Perrin et al. 1999): the eastern spinner 

(Stenella longirostris orientalis), the Central American spinner (S. l. 

centroamericana), the dwarf spinner (S. l. roseiventris) and Gray’s spinner (S. l. 

longirostris) (Figure 2.1a). The distribution of the Central American spinner is limited 

to waters of the west coast of southern Mexico to the Gulf of Panama, while the dwarf 

spinner is only found in the Gulf of Thailand and Timor Sea (Perrin et al. 1999). In the 

Eastern Tropical Pacific (ETP), the eastern spinner and the whitebelly spinner (an 

apparent hybrid form between S. l. orientalis and S. l. longirostris) form large, pelagic, 

mixed-species aggregations with spotted dolphins (Stenella attenuata) and yellow- 

30


fin tuna (Thunnus albacares). Due to this association with tuna, millions of these 

dolphins have been killed as by-catch in the yellow-fin tuna purse-seine fishery during 

the last four decades (Wade & Gerrodette 1993). Concerns about the impact of this 

large-scale dolphin mortality led to numerous studies on various aspects of their 

biology, including genetic diversity and population structure (e.g. Galver 2002), 

mating strategies (Perrin & Mesnick 2003), and abundance (e.g. Wade & Gerrodette 

1993). 

Figure 2.1. The location and details of the study area in relationship to worldwide distribution of 

spinner dolphins. (a) Global distribution of spinner dolphin subspecies (from Galver 2002; A = Stenella 

longirostris longirostris, B = S.l. orientalis and whitebelly spinner dolphin, C = S.l. centroamericana, D 

= S.l. roseiventris. (b) Map of French Polynesia, including the Society Islands and Nuku Hiva in the 

Marquesas Islands. (c) Map of the Society Islands; arrows indicate movement of individuals between 

islands based on photo-identification (full line) and genotyping (dashed line). Number of events 

represented by each arrow is given (d) Map of Moorea, the primary study site. 

In contrast to the pelagic distribution of the eastern and whitebelly spinner, Gray’s 

spinner dolphin is primarily insular in habitat preference (Perrin & Gilpatrick 1994). 

31


Although absent from the ETP, its geographic distribution is much greater than the 

distribution of the other sub-species, extending across the tropical and subtropical 

waters of the Atlantic, Indian and Pacific Oceans (Figure 2.1a). Much of what is 

known about the population dynamics of S. l. longirostris has been derived from a 

few island locations: behavioural observation and photo-identification at the Big 

Island, Oahu and Midway Atoll in Hawaii (Norris et al. 1994, Lammers 2004, 

Karczmarski et al. 2005), Fernando de Noronha in Brazil (Silva-Jr et al. 2005) and 

Moorea, in the Society Archipelago of French Polynesia (Poole 1995). These studies 

reveal that insular Gray’s spinner dolphins (hereafter referred to as spinner dolphins) 

follow a similar daily cycle at each location; during the day, they rest and socialise in 

inshore habitats and at dusk, they move offshore where they feed on squid, shrimp 

and mesopelagic fish. Demography and social organisation, on the other hand, 

appear to be substantially different in each of the studies locations. 

Around the Big Island of Hawaii, where the dolphins use specific bays and shallow 

reefs during the daytime, Norris et al. (1994) found a ‘fission-fusion’ model of social 

organisation, with groups forming and separating from day to day. Because of the 

regular identification of new individuals in the resting groups, the authors concluded 

that the dolphins observed around this island form an open population of more than 

1,000 individuals (Norris et al. 1994). More recently, Karczmarski et al. (2005) has 

described a very different social organisation of spinner dolphins at the remote atoll 

of Midway, in the far-western leeward Hawaiian Islands. This population of about 200 

individuals was found to be closed with respect to immigration/emigration (or nearly 

so), with strong geographic fidelity and no obvious fission-fusion (Karczmarski et al. 

2005). 

In the Society Archipelago of French Polynesia, Poole (1995) described an 

intermediate form of social organisation. Around the island of Moorea, the primary 

study site (Figure 2.1), groups of spinners rest and socialise in a series of 10 

pass/bay complexes (Figure 2.1d). These groups follow the same fission-fusion 

model of social organisation observed at the Big Island, with day to day fluidity in 

group composition (Poole 1995). However, similar to Midway Atoll, photoidentification 

surveys over six years indicated that Moorea’s spinner dolphins were 

32


year-round long-term residents forming a small and apparently closed community, 

although some low-level of interchange was documented with the sister island of 

Tahiti, just 17 km away (Poole 1995). 

These island specific studies revealed important features of the behavioural ecology 

of insular spinner dolphins, but left unanswered several crucial questions related to 

genetic diversity and population dynamics: Do spinner dolphins typically form 

relatively closed island communities distinct from one another, as suggested by 

observations at Moorea and Midway? What are the social and genetic boundaries of 

insular spinner dolphin communities? Is there any interchange of dolphins between 

island communities and at what frequency? Are island communities formed by 

colonisation events followed by isolation or do they maintain connectivity to ‘parent’ 

populations, forming large metapopulations? 

To address these questions, evolutionary and demographic approaches were 

combined, using microsatellite genotyping and mitochondrial DNA sequences 

obtained from biopsy samples, and photographic sighting - re-sighting of distinctively 

marked individuals, respectively, to describe community structure of spinner dolphins 

frequenting the nearshore island waters of the Society Archipelago, French 

Polynesia. First, to evaluate isolation or ‘closure’, intensive small-boat surveys at 

Moorea were conducted, investigating in detail the demography and genetic diversity 

of spinner dolphins around this island, and also taking advantage of the previous 

photo-identification study conducted by Poole (1995) from 1987 to 1992. Second, to 

address demographic and genetic connectedness, additional data (including biopsy 

samples and photographs) were collected around the main islands of the Society 

Archipelago and at Nuku Hiva in the Marquesas Archipelago, to provide insights on 

population structure at a larger scale (Figure 2.1b). By combining demographic and 

evolutionary approaches on a local and regional scale, it was hoped to provide a 

more comprehensive description of the long- and short-term dynamics of insular 

spinner dolphin populations. 

33

2.3. Materials & Methods 


2.3.1. Study area and small-boat surveys 

From April 2002 to November 2004, spinner dolphins were photographed and 

genetically sampled in French Polynesia, located in the central South Pacific Ocean 

(Figure 2.1). Small-boat surveys were conducted (n = 189) around six islands of the 

Society Archipelago including Moorea, Tahiti, Huahine, Raiatea, Tahaa and Bora 

Bora (Figure 2.1c, Table 2.1). Efforts were made to survey the entire coastline of 

each island (except in Tahiti), in order to avoid geographic bias in the sampling. 

Because of logistical limitations, surveys in Tahiti were limited to the eastern part of 

the island (from Point Venus to Papara). Four boat surveys were also conducted at 

Nuku Hiva (n = 4), in the Marquesas Archipelago, 1,500 km north of Tahiti (Figure 

2.1b). The islands of Raiatea and Tahaa were considered as one location (referred 

as Raiatea-Tahaa), since they are enclosed within the same lagoon. Moorea, Tahiti 

and Raiatea-Tahaa were visited on two consecutive years (Table 2.1). 

Table 2.1. Boat surveys conducted from 2002 to 2004 in French Polynesia. DMI refers to Distinctively 

Marked Individuals. Q is the quality rate of the photographs. 

Island Year Start End 

Moorea 

Tahiti 

2002 

2003 

2003 

2004 

18/04 

09/07 

28/11 

19/10 

01/11 

10/09 

01/12 

31/10 

# 

surveys 

107 

32 

4 

12 

# 

encounters 

126 

44 

7 

19 

# photos 

Q ≥ 3 

6985 

792 

342 

1999 

# DMIs 

Bora Bora 2003 19/10 29/10 6 3 144 2 

Raiatea-Tahaa 2003 

2004 

29/10 

04/11 

04/11 

17/11 

7 

14 

9 

20 

181 

1447 

Huahine 2003 05/11 12/11 7 6 288 5 

Nuku Hiva 2004 22/11 27/11 4 4 - - 

The primary study site was Moorea, where intensive boat surveys were conducted 

from April to November 2002 (n = 107) and from July to September 2003 (n = 32) 

(Table 2.1). This island was chosen since a previous study was carried out there by 

25 

23 

24 

34


Poole (1995), who conducted 275 boat surveys from 1987 to 1992, taking 

photographs of 249 groups of spinner dolphins. Poole (1995) also conducted 13 boat 

surveys along the north-east coast of Tahiti in 1988-89. 

2.3.2. Collection and analysis of photo-identification data 

During each encounter, group size was estimated by visual counts and dorsal fin 

photographs were taken of as many individuals as possible, regardless of distinctive 

marks. Photographs were taken using a digital Olympus E10 (4 megapixel CCD) 

equipped with a 200 mm lens and Canon Digital Rebel (6.3 megapixel CMOS) 

equipped with a 300 mm lens. Dorsal fin photographs were first assessed for quality 

independently of distinctiveness of fins. Five criteria were used to assign photographs 

a quality rating (Q) on a scale of 1 to 5 (poor to excellent): focus, size, exposure and 

percentage of the dorsal fin visible on the photo (Arnborn 1987). Only images that 

rated Q ≥ 3 were considered for the analyses (but see Appendix 2 for details). 

Most spinner dolphins showed some unique marks on their dorsal fins but Poole 

(1995) found that, overall, only a limited percentage of individuals (about 15% of the 

population) are sufficiently distinctive to be confidently identified across time. 

Therefore, in this study, only dolphins with deep distinctive nicks or deformations on 

the edge of the dorsal fin were considered as ‘marked’ for the purpose of individual 

identification. This allowed comparisons of images taken from either side of an 

individual. This subset of dolphins is referred to as ‘Distinctively Marked Individuals’ 

or DMIs. All other photographed dolphins were classified as ‘unmarked’. 

Based on the images of DMIs collected during the surveys, a photo-identification 

catalogue was created for each island. All catalogues were compared to find resights 

within and between islands. Inter-annual re-sightings around the same island 

were also recorded for islands where surveys were conducted during two 

consecutive years. Finally, the DMI catalogues from this study were compared to 

Poole’s (1995) catalogues comprising DMI photographs taken around Moorea and 

Tahiti between 1987 and 1992. 

35


2.3.3. Biopsy sampling and DNA extraction 

Skin samples for genetic analyses were collected from spinner dolphins using a small 


a variable pressure valve (Krützen et al. 2002). Short-term behavioural responses to 

biopsy attempts were recorded and are reported in Appendix 3. All samples were 

preserved in 70% ethanol and stored at -20°C for subsequent analysis. Total cellular 

DNA was isolated from skin tissue by digestion with proteinase K followed by a 

standard phenol: chloroform extraction method (Sambrook et al. 1989) as modified 

for small samples by Baker et al. (1994). 

2.3.4. mtDNA sequencing, genotyping and sex identification 

An 800 base pair (bp) fragment of the 5’ end of the mtDNA control region (d-loop) 

was amplified using the polymerase chain reaction (PCR) and the primers lightstrand, 

tPro-whale M13-Dlp-1.5 (5'-TCACCCAAAGCTGRATTCTA-3', Dalebout et al. 

1998), and heavy strand, Dlp-8G (5'-GGAGTACTATGTCCTGTAACCA-3', designed 

by G. Lento as reported in Dalebout et al. 2005). All amplification reactions were 

carried out in a total volume of 20 µL with 1 x Ampli-Taq buffer, 2.5 mM MgCl2, 0.4 

µM each primer, 0.2 mM dNTPs and 0.5 U of Ampli-Taq® DNA polymerase. The 

PCR temperature profile was as follows: a preliminary denaturing period of 2 minutes 

at 94°C followed by 35 cycles of denaturation for 30 seconds at 94°C, primer 

annealing for 45 seconds at 55°C and polymerase extension for 40 seconds at 72°C. 

A final extension period of 10 minutes at 72°C was included at the end of the cycle. 

PCR products were purified for sequencing with ExoSAP-IT (USB) and sequenced in 

both directions with BigDye terminator chemistry v.3.1 on an ABI 3100 DNA 

sequencer (Applied Biosystems Inc.). Sequences were aligned using Sequencher TM 

(version 4.1.2, Genes Codes Co.) and edited manually. Variable sites and unique 

haplotypes were identified using MacClade v. 4.0 (Maddison & Maddison 2000). 

Samples were genotyped using 12 published microsatellite loci developed from other 

cetacean species (Table 2.2). Amplification via PCR was performed following 

standard protocols, in 10 µL volumes with 1 x Platinium-Taq buffer, 1.5 mM MgCl2, 

36


0.4 µM each primer, 0.2 mM dNTPs and 1/8 U of Platinium-Taq® DNA polymerase, 

and annealing temperature varying by locus (Table 2.2). PCR products were run on 

an ABI 377 DNA automated sequencer with a TAMRA350 size ladder (Applied 

Biosystems Inc.). Data were collected by GeneScan v. 3.7, and the fragment size 

was measured using Genotyper v. 2.5 (Applied Biosystems Inc.). The sex of sampled 

dolphins was identified by amplification of a fragment of the sry gene multiplexed with 

ZFX positive control, as described by Gilson et al. (1998). 

Table 2.2. Microsatellite diversity for spinner dolphins from French Polynesia. HO is the observed 

heterozygosity and HE is the expected heterozygosity. No significant deviation (p > 0.05) was found 

after Bonferroni correction (pcrit = 0.042). k is the number of alleles found and n is the number of 

screened chromosomes. 

Locus k n HO HE 

Null allele 

frequencies References 

415/416 12 132 0.788 0.833 +0.0274 (Amos et al. 1993) a 

AAT44 10 136 0.757 0.812 +0.0346 (Caldwell et al. 2002) c 

EV1 15 136 0.743 0.843 +0.0623 (Valsecchi & Amos 1996) b 

EV94 20 136 0.816 0.849 +0.0164 (Valsecchi & Amos 1996) b 

GATA98 9 137 0.825 0.815 -0.0069 (Palsbøll et al. 1997) b 

GT6 10 135 0.726 0.771 +0.0298 (Caldwell et al. 2002) b 

GT575 8 135 0.726 0.775 +0.0305 (Bérubé et al. 2000) a 

KWM12a 11 136 0.838 0.821 -0.0121 (Hoelzel et al. 1998b) b 

MK5 12 137 0.825 0.823 +0.0013 (Krützen et al. 2001) b 

MK6 19 136 0.809 0.875 +0.0395 (Krützen et al. 2001) b 

Ppho131 14 137 0.861 0.855 -0.0036 (Rosel et al. 1999) a 

Ppho142 10 132 0.674 0.677 +0.0010 (Rosel et al. 1999) a 

abc indicate different PCR temperature profiles: (a) 94°-10’, (94°-30”, 55°-30”, 72°-20”) 30x, 72°-3’; (b) 

94°-10’, (94°-30”, 50°-30”, 72°-30”) 35x, 72°-3’; (c) as reported in the original paper. 

2.3.5. Moorea community size estimate 

An extensive photographic collection at Moorea allowed estimation of the dolphins’ 

community size using the Bowden estimator for closed populations (Bowden & Kufeld 

1995), as implemented in the program Noremark (White 1996a). This model requires 

only a small proportion of the population to be marked, and provides an estimate of 

the total population size and confidence intervals, taking into account the frequency 

of sightings of each marked individual and the total number of sightings for unmarked 

37


individuals. It allows for continuous sampling over long periods of time, removing the 

need to sub-divide the dataset into sampling periods. This estimator is known to be 

robust to heterogeneity of sighting probabilities (White 1996b). 

Abundance was also estimated with the program Capwire (Miller et al. 2005), using 

the frequency of capture-recapture found by genotyping of biopsy samples. This 

method, based on a simple urn model, assumes a closed population and can be 

applied using a single continuous sampling session. Simulations showed that it 

performs better than commonly used capture-recapture models when population size 

is small (not more than a few hundreds individuals) and heterogeneity occurs in 

capture probability (Miller et al. 2005). Equal likelihood of capture was tested by 

comparing the frequencies of capture to the zero-truncated Poisson distribution as 

described by Caughley (1977). Biopsy samples were collected without consideration 

of previous sampling of marked or unmarked individuals and therefore, provided a 

dataset independent of photo-identification that was for the purpose of capturerecapture 

analyses. 

2.3.6. mtDNA and microsatellite diversity 

The software Arlequin v. 3.01 (Excoffier et al. 2005) was used to estimate the number 

of polymorphic sites, as well as haplotype diversity (h) and nucleotide diversity (π) of 

the mtDNA control region, overall and for each island. Due to computer limitations, 

the best model of substitution proposed by Modeltest v. 3.7 (Posada & Crandall 

1998) could not be used, i.e., HKY+I+G; ti/tv ratio = 37.79; gamma correction = 

0.4941, but instead used the closely related Tamura-Nei model of substitution with a 

gamma correction of 0.4941. 

Microsatellite loci were tested for departure from Hardy-Weinberg equilibrium using 

the software Arlequin. The potential frequency of null alleles was estimated using 

Cervus v. 2.0 (Marshall et al. 1998). The probability of identity (PID) was estimated, as 

implemented in the program GenAlEx v. 6 (Peakall & Smouse 2005), and the 

matching genotypes, assumed to represent replicate samples of individuals, were 

found with Cervus. The PID is an estimate of the average probability that any two 

individuals chosen by chance from the population would share an identical genotype. 

38


Number of alleles per locus and allelic richness were calculated with the program 

FSTAT v. 2.9.3.2 (Goudet 2001). 

2.3.7. Population structure and sex specific dispersal 

A median-joining network was constructed to infer phylogenetic relationship among 

the mtDNA control region haplotypes using the program Network v. 4.1.0.8 (Bandelt 

et al. 1999). Analyses of molecular variance (AMOVA) were conducted with Arlequin, 

grouping animals by islands, based on the mtDNA control region (using FST and ΦST) 

and on the microsatellite loci (using FST). The ΦST statistic takes into account the 

relationship between haplotypes based on molecular distances, while FST uses only 

the difference in frequencies of haplotype (Excoffier et al. 1992). 

To test for bias in dispersal between males and females, we analysed microsatellite 

genotypes and mtDNA (by coding individuals as homozygotes) using the “biased 

dispersal” option implemented in FSTAT (Goudet 2001). From this program, two tests 

are reported that seem to perform best across a range of conditions (Goudet et al. 

2002): the comparison of sex-specific FST values; and, the sex-specific variance of 

assignment index (νAIc) (Goudet et al. 2002). For the FST test, the value of the more 

dispersing sex is expected to be lower than for the more philopatric sex. For the νAic 

test, variance is expected to be higher in the dispersing sex. The significance of both 

tests was judged by generating null distributions with 10,000 permutations. 

2.3.8. Female long-term effective population size (Nef) 

For comparison to the estimated census size of local communities, Nef was estimated 

for island samples based on mtDNA diversity using the relationship, Nef = θf/2µ, 

where µ is the neutral mutation rate per nucleotide per generation and θf is, in this 

case, a measure of mtDNA diversity. The parameter θf was estimated with the 

maximum likelihood coalescent approach implemented in the program Lamarc v. 2.0 

(Kuhner 2006); searches included 10 short chains (500 trees used of 10,000 

sampled) and 2 long chains (10,000 trees used of 200,000 sampled). Three runs of 

Lamarc were performed for each sample, and the median value was chosen for a 

39


final Nef estimate. For µ, a mutation rate of 7.46 – 9.35 x 10 -9 nucleotides per year 

was calculated (λ = d/2T) from the evolutionary distance (d) of 0.1775 +/- 0.0283 

between Delphinidae and Phocoenidae (using our dataset and a harbour porpoise 

sequence from Genbank, accession number AJ554063 (Arnason et al. 2004)), and 

an assumed divergence time (T) of 1.0 – 1.1 x 10 7 years ago based on the fossil 

record (Barnes 1985). Such a mutation rate is comparable to mutation rates 

previously reported for baleen whales (Baker et al. 1993) and Cuvier’s beaked 

whales (Dalebout et al. 2005). The value was adjusted using a generation time of 15 

years for spinner dolphins, estimated as the average age of mature females following 

data from Perrin and Henderson (1984), for a final mutation rate estimate of µ = 1.12 

– 1.40 x 10 -7 nucleotides per generation. 

2.3.9. Testing for recent bottleneck effect 

The sample of mtDNA sequences from each island was tested for departures from 

mutation-drift equilibrium with Tajima’s D test (Tajima 1989b) and Fu’s FS test (Fu 

1997), as implemented in Arlequin. A positive Tajima’s D can indicate an admixture 

of two distinct populations, while a negative Tajima’s D can be explained by a recent 

bottleneck effect or population expansion (Tajima 1989a, Aris-Brosou & Excoffier 

1996). Large negative values of Fu’s FS statistics can also indicate a population 

demographic expansion (Fu 1997). Significance of both statistics was inferred by 

randomisation (10,000 steps), using a coalescent simulation algorithm (Hudson 

1990) as implemented in Arlequin. 

For microsatellites, a test based on allele frequencies and implemented in the 

program Bottleneck v. 1.2.02 was used (Cornuet & Luikart 1996); the Wilcoxon onetailed 

test for heterozygote excess, run under the stepwise mutation model (SMM) 

and the two-phased model (TPM; variance = 30, 70% stepwise mutational model, 

1000 iterations). The distribution of allelic frequencies was also inspected to detect a 

mode-shift distortion due to the loss of rare alleles (Luikart et al. 1998). Finally, the 

method implemented in the programs M_P_Val and Critical_M (Garza & Williamson 

2001) was applied, to test if the M ratios (mean ratio of the number of alleles to the 

range in allele size) of island samples were significantly smaller than expected under 

40


a range of expected neutral values. Expected values of M were simulated assuming 

a TPM, with parameters ∆g = 3.5 and ps = 90% (Garza & Williamson 2001) and 

considering θ values of 1, 10 and 50, i.e., pre-bottleneck effective population sizes 

ranging from 500 to 25,000 when µ = 5x10 -4 nucleotides per generation (Goldstein & 

Schlötterer 1999). 

2.4. Results 

2.4.1. Survey effort and sample size 

Groups of spinner dolphins were found around all six islands surveyed. The number 

of encounters at each island ranged from six to 170 (Table 2.1), and was highly 

correlated with the number of surveys (Spearman R = 0.94; p < 0.005). Average 

group size was 36.4 dolphins (ranging from three to 90). A large number of 

photographs were taken for individual identification (Table 2.1), particularly at Moorea 

in 2002. From the photographs, a total of 82 DMIs were identified, with the largest 

numbers identified around Moorea, Tahiti and Raiatea-Tahaa (Table 2.1). No DMIs 

were identified at Nuku Hiva. Long-term associations with calves (expected to be 

mothers) and molecular sexing from biopsy samples of a few DMIs indicate that both 

males and females can be distinctively marked (results not shown). 

A total of 154 genetic samples were collected from dolphins around all the islands 

visited during this study (Table 2.3); 151 were biopsy samples and three were 

samples from dead stranded dolphins (Moorea, January 2003 and September 2005, 

n = 2 + 1). Biopsy samples were collected from 79 different groups of dolphins (Table 

2.3). Each sample was genotyped at nine to 12 microsatellite loci. All loci were found 

to be highly polymorphic overall (Table 2.2) and within island samples (Table 2.3). 

The PID was 6.8 x 10 -12 , when calculated across the first nine loci (the minimum 

number of loci successfully genotyped for each sample), and 8.59 x 10 -16 over 12 

loci. Comparison of genotypes from the 154 biopsies revealed that 17 individuals 

were sampled on two occasions while two were sampled on three occasions (i.e., 19 

individuals sampled more than once). All other pair-wise comparisons showed 

mismatches at five or more loci between individuals, making false exclusion (due to 

41


genotyping error) highly unlikely. From these data, it was concluded that a total of 

133 individual dolphins were sampled during this study. 

Table 2.3. Sex identification and genetic diversity statistics for microsatellite loci and mtDNA control 

region. The column for the Society Archipelago encompasses data collected at Moorea, Tahiti, Bora 

Bora, Raiatea-Tahaa and Huahine, and are indicated in bold. k is the mean number of alleles per 

locus (across 12 loci). For mtDNA control region, h is the haplotype diversity and π is the nucleotide 

diversity. Nef estimates are given in thousands and represent female long-term effective population 

size. 

Moorea Tahiti* 

Bora 

Bora 

Raiatea- 

Tahaa 

Huahine 

Society 

Archipelago 

No. of samples 70 34 6 19 17 146 8 

No. of individuals 59 33 6 16 15 129 8 

No. of groups 41 17 3 10 4 75 4 

No. of females 20 13 3 8 3 47 3 

No. of males 39 19 3 8 12 81 5 

Nuku 

Hiva 

Microsatellites 

k 10.42 7.50 5.42 8.33 8.67 11.92 7.50 

Allelic richness 5.59 4.85 5.42 5.79 6.13 5.64 5.84 

mtDNA 

No. of haplotypes 18 4 5 12 10 27 5 

h 

0.93 +/- 

0.01 

0.47 +/- 

0.08 

0.93 +/- 

0.12 

0.97 +/- 

0.03 

0.95 +/- 

0.03 

0.90 +/- 0.02 

0.86 +/- 

0.11 

π (%) 

1.62 +/- 

0.84 

0.64 +/- 

0.37 

1.69+/- 

1.04 

1.73 +/- 

0.94 

1.54 +/- 

0.85 

1.48 +/- 0.77 

1.43 +/- 

0.85 

Nef (thousands) 103 23 103 169 112 127 74 

(95% CI) 

(76-190) (12-52) (42-390) (96-398) (60-275) (100-200) (32-239) 

* the sex could not be determined for one of the samples collected at Tahiti 

2.4.2. Demographic closure at Moorea 

Photo-identification records from intensive boat surveys at Moorea in 2002-2003 

were used to assess the degree of demographic closure/openness of this insular 

community. A total of 126 groups of spinner dolphins were encountered around 

Moorea in 2002 and 44 groups in 2003, and 6,892 photographs of Q ≥ 3 were taken, 

from which 24 DMIs were identified. The discovery curve, based on the cumulative 

number of new DMIs across the two-year scale of the study, supported Poole’s 

(1995) previous findings that spinner dolphins around Moorea are part of a 

demographically closed community (Figure 2.2). In 2002, the discovery curve of the 

42


DMIs increased during the first 25 surveys but then reached an asymptote for two 

and half months at 18 DMIs (44 encounters) (Figure 2.2). Based on their pattern of 

frequent re-sightings, these DMIs were considered as “regular members” of the 

community frequenting Moorea’s nearshore waters in 2002. Seventeen of the 18 

individuals were photographically re-sighted on 13 to 37 days throughout the field 

season. The remaining individual was not seen after the 6 th of June, although it was 

re-sighted on six days during the first two months of surveys. 

On the 28 th and 29 th of August 2002, five new DMIs were photographed together 

(Figure 2.2). After these two consecutive encounters, these five new DMIs were 

never seen again at Moorea. Considering these two sightings and also subsequent 

re-sightings of four of these five dolphins at Tahiti (see below), these animals were 

considered to be “visitors” (i.e., temporary immigrants) at Moorea. Another new DMI 

was identified at Moorea in late 2002 (Figure 2.2), but its fresh scars suggested a 

newly acquired mark rather than immigration. 

Figure 2.2. Discovery curves based on the cumulative number of new DMIs identified at Moorea in 

2002-2003 and in 2003 only. Identification of the five visitors in August 2002 is indicated by a spike. 

Dark circles show cumulative discovery over two years. Open circles show discovery for 2003 surveys 

only. 

43


During the surveys conducted from July to September 2003, 17 DMIs were 

photographically identified on two to 10 occasions each (Figure 2.2). Only one of 

these was not known from the previous 2002 surveys, but it could not be determined 

if it was a visitor, a recent immigrant, or a previous member of the community with 

recently acquired but already healed scars. Apart from this last DMI, photoidentification 

data collected in 2003 did not alter the asymptote of the discovery curve 

started in 2002 (Figure 2.2), suggesting strong community stability over the two years 

of surveys. An independent discovery curve using only the 2003 photographs 

reached asymptote after only 20 surveys (Figure 2.2). 

Comparison to the data of Poole (1995) showed that five of the DMIs identified as 

member of the community in 2002-2003 had been regularly photographed previously 

around Moorea between 1987 and 1992. These five DMIs, three of which were first 

identified in 1987 as adults (i.e., at least five years old), were also regularly 

photographed around Moorea between the 1987-92 study and the 2002-03 study 

(Poole. Unpublished data), supporting site fidelity of up to 15 years. Based on field 

observations and/or molecular data, it was found that these five dolphins included at 

least two females and one male (females: Slo02Mo15 and Slo02Mo16; male: 

Slo02Mo27). 

2.4.3. Abundance of Moorea community 

The abundance of the Moorea community was estimated based on the frequency of 

photographic recapture of the 18 DMIs identified as “regular members” of the 

community during 2002. During the 106 encounters considered for the purpose of the 

estimate, the 18 DMIs were photographed from 13 to 84 times each (based on Q ≥ 3 

photos), giving a total of 811 sighting – re-sighting events. Photographs of unmarked 

individuals (Q ≥ 3) represented 5295 ‘sightings’. Based on the frequencies of resighting 

of each DMI and on the total number of unmarked individual sightings, the 

Bowden estimator gave an abundance of 135 (95% CI. 112 – 163) for the Moorea 

community. As expected, my estimate was slightly larger (due to demographic 

effects) when including 2003 photographs (148, 95% CI. 121 – 181). 

44


To corroborate the estimate from photo-identification, the abundance of the Moorea 

community was also estimated by genotyping. Unlike the photo-identification, all 

individuals were expected to be uniquely identifiable by genotyping but the number of 

sampling events was much smaller. Of the total of 62 skin samples collected around 

Moorea in 2002, comparison of genotypes revealed that 42 individuals were sampled 

once, seven were sampled twice and two were sampled on three occasions. 

Comparison to a zero-truncated Poisson distribution indicates that dolphins had 

unequal likelihood of biopsy sampling (χ² = 6.67, p < 0.01). Based on these 

frequencies of capture-recapture, the program Capwire provided an estimate of 151 

individuals (95% CI. 97-294), showing relatively close agreement with the Bowden 

estimate based on photo-identification. 

2.4.4. Individual interchange among islands 

Comparison among DMIs from all of the islands provided insight into low levels of 

demographic interchanges and temporary immigration. Of the 23 DMIs identified at 

Tahiti, six were encountered during surveys conducted at Moorea in 2002 and 2003. 

Two of these dolphins were known as members of the Moorea community. The other 

four DMIs were the “visitors” observed at Moorea in August 2002, supporting further 

the particular status of these dolphins. A review of photographs collected previously 

by Poole (1995) showed that one of these “visitors” was first identified at Tahiti in 

1989. No matching of DMIs was found between Huahine (five DMIs), Raiatea-Tahaa 

(24 DMIs) and Bora Bora (two DMIs), although these islands are geographically close 

to one another (Figure 2.1c). Surprisingly, one DMI was observed at both Moorea 

and Bora Bora, more than 200 km distant from each other (Figure 2.1). This dolphin 

was the DMI regularly observed at Moorea for the first two months of surveys 

conducted in 2002 but not seen after June (see above), suggesting a long-term 

(perhaps permanent) emigration from Moorea. 

Comparison of genotypes from biopsy samples collected at the outer islands 

provided additional information on individual interchange among islands. Most of the 

recapture events were around the island where the individuals were initially sampled 

(11 at Moorea, one at Tahiti, two at Huahine and three at Raiatea-Tahaa), but four 

dolphins were re-sampled at different islands. Among them, three dolphins (all males) 

45


were biopsied in both Huahine and Raiatea, demonstrating at least occasional 

interchange between these two islands. No genotype match was found between 

Moorea and Tahiti. Finally, a female sampled at Moorea in May 2002 was re-sampled 

at Bora Bora in 2003. This genetic recapture supports the other immigration event 

between these two islands illustrated by the recapture of the DMI. 

Replicate samples of individuals collected around the same islands (n = 17) were 

removed from the dataset for subsequent analyses of genetic diversity, population 

structure, sex-dispersal and bottleneck tests. However, replicate samples from 

different islands (n = 4) were retained for these analyses, except where mentioned, 

providing a total sample size of 137 individuals. 

2.4.5. mtDNA diversity and effective population size 

Considering the relative demographic closure of insular communities, levels of 

mitochondrial genetic diversity were surprisingly high at Moorea and for the other 

island samples. Across the 555 base pair region of the mtDNA control region that 

was analysed, at total of 52 variable sites were found defining 31 haplotypes 

(GenBank accession numbers EF558737 to EF558767) for the 59 individuals. The 

overall haplotype diversity was 0.92 +/- 0.014 and nucleotide diversity was 1.59 % +/- 

0.82 % (Table 2.3). Similar levels of diversity were observed for within-island 

samples, except in Tahiti which showed much lower levels of haplotype and 

nucleotide diversity (Table 2.3). There were no obvious differences in mtDNA control 

region diversity between males (n = 83) and females (n = 49) (results not shown). 

The median-joining network of mtDNA haplotypes showed no obvious overall 

phylogeographic structuring but did indicate a striking absence of expected sister 

lineage, i.e., haplotypes related by a single substitution to observed haplotypes 

(Figure 2.3). In contrast to the other islands, samples from Tahiti were dominated by 

only a few haplotypes (Slo02FP11 and Slo02FP27) shared with several other islands 

of the Society Archipelago. Huahine showed four unique haplotypes, while Bora Bora 

had one and Raiatea-Tahaa had none. Moorea had the largest number of unique 

haplotypes (n = 7) but it also represented the largest data set. Finally, four of the five 

46


haplotypes identified at Nuku Hiva, in the remote Marquesas Islands, were not found 

in the Society Archipelago. 

Based on the estimated substitution rate of 1.12 - 1.40 x 10 -7 nucleotides per 

generation, estimates of long-term Nef for each island sample ranged from 23,000 to 

169,000, (Table 2.3). Note that the estimate of Nef at Moorea (Nef = 103,000) showed 

obvious discrepancy with the current census size estimates (Ncensus < 200). 

Interestingly, long-term Nef estimated for the whole Society Archipelago was of the 

same order as estimates from single islands (such as Moorea, Raiatea and Huahine). 

Figure 2.3. Inferred genealogical relationship among mtDNA haplotypes (n = 31) from spinner 

dolphins of French Polynesia based on the median-joining algorithm. The diameter of each circle is 

proportional to the number of individuals found for the haplotype (nind = 137). White dots represent 

inferred node haplotypes not found in the samples. Each hash mark corresponds to a single inferred 

mutational step. Codes refer to individuals chosen to represent haplotypes. 

47

2.4.6. Population differentiation 


An analysis of molecular variance (AMOVA) showed significant differentiation in 

mtDNA variation among the six island communities at both the haplotype and 

nucleotide level (FST = 0.143; ΦST = 0.129; p < 0.001). Pairwise comparisons showed 

that the overall effect was strongly influenced by Tahiti and Nuku Hiva despite the 

small sample size of the latter (Table 2.4). Nonetheless, significant differences were 

also found between Moorea and Huahine based on FST (although not for ΦST). 

Analysis of the microsatellite loci also showed significant differentiation among 

islands, but it was weaker than that obtained from mtDNA (FST = 0.029; p < 0.001). 

Pairwise comparisons showed significant differentiation between all communities 

except Raiatea and Huahine. Even here, when the three individuals found in both 

datasets were excluded from the analysis (since they were sampled at both 

locations), differences between these two islands were significant (p = 0.014). There 

was no evidence of null alleles or significant deviation from Hardy-Weinberg 

expectations for the overall sample. 

Table 2.4. Analysis of genetic differentiation among island communities based on pairwise Fstatistics. 

Below diagonal, genetic distances are given for mtDNA control region sequence data: first 

line, FST values, second line ΦST values. Above diagonal, FST values are given for the 12 microsatellite 

loci. p < 0.001, ***; p < 0.01, **; p < 0.05, *; p > 0.05, ns . 

Moorea Tahiti Bora Bora Raiatea- 

Tahaa 

Huahine 

Nuku 

Hiva 

Moorea 0.015*** 0.038** 0.019*** 0.017** 0.048*** 

Tahiti 

Bora Bora 

0.205*** 

0.170*** 

-0.001 ns 0.289** 

-0.042 ns 0.267** 

0.011 ns 0.281*** -0.050 ns 

Raiatea-Tahaa 0.017 ns 0.297*** -0.038 ns 

Huahine 

Nuku Hiva 

0.036* 0.315*** 0.012 ns 0.003 ns 

0.021 ns 0.258*** -0.037 ns 0.026 ns 

0.075*** 0.043*** 0.042*** 0.084*** 

0.026* 0.028* 0.078*** 

0.098** 0.399*** 0.107 ns 0.062* 0.091*** 

0.138** 0.519*** 0.184* 0.049 ns 0.196** 

0.009 ns 0.029** 

0.030** 

48

2.4.7. Sex-biased dispersal 


Sex-specific AMOVAs showed significant population differentiation for males and 

females at both nuclear and mitochondrial level, discounting the null hypothesis of 

panmixia for either sex (Table 2.5). However, these analyses showed a trend toward 

larger FST values for females at both mtDNA control region and microsatellite loci, 

suggesting greater female philopatry and some male biased dispersal, although the 

effect was not significant given our sample size. This trend was confirmed by the test 

of variance of the corrected assignment index (νAIc), which was significant 

regardless of whether or not the four replicate samples were included (Table 2.5). 

Table 2.5. Differences in sex-specific FST values and variance of corrected assignment index (νAIc), 

based on mtDNA control region and microsatellite loci. Results are reported for tests including (w/ 

repli) or not including (no repli) the replicate samples obtained from different islands (p-values in bold). 

Significance levels of genetic differentiation, estimated with Arlequin v.3.01, are also indicated for FST 

values. p < 0.001, ***; p < 0.05, *; p > 0.05, ns . 

mtDNA control region Microsatellite loci 

All locations Society Islands All locations Society Islands 

w/ repli no repli w/ repli no repli w/ repli no repli w/ repli no repli 

FST (Males) 0.109*** 0.109 0.105*** 0.104 0.021*** 0.023 0.017*** 0.018 

FST (Females) 0.167*** 0.175 0.173*** 0.182 0.035*** 0.036 0.035*** 0.036 

p-value 0.187 ns 0.142 ns 0.149 ns 0.110 ns 0.163 ns 0.161 ns 0.077 ns 0.082 ns 

νAIc (Males) - - - - 18.89 20.15 19.27 20.65 

νAIc (Females) - - - - 11.17 11.60 11.79 12.26 

p-value - - - - 0.049* 0.032* 0.069 ns 0.047* 

To evaluate sex-bias dispersal on a smaller geographical scale, I carried out the 

same tests considering only samples from the Society Islands (Table 2.5). The same 

trend of larger FST for females and larger νAIc for males were observed within this 

dataset (i.e., supporting dispersal biased toward males). In this case, νAIc tests were 

only significant when the four replicate samples from different islands were excluded 

(Table 2.5). 

49


2.4.8. Genetic signature of community bottleneck 

Various tests based on mtDNA control region and microsatellite loci failed to detect 

the signature of a recent bottleneck effect in the islands’ communities. Tajima’s and 

Fu’s tests for mtDNA did not differ significantly from expected under a neutral model 

of evolution for any of the data sets, except Tahiti which showed a significantly 

positive Fu’s FS value (Table 2.6). Similarly, the three tests for a bottleneck using 

allele frequencies of microsatellite loci showed no evidence of a recent population 

decline or colonization event. No significant heterozygosity excess was found after 

correcting for multiple comparisons (Table 2.6) and the distribution of allelic 

frequencies did not show significant departure from a standard L-shape in the modeshift 

test, indicating no loss of rare alleles in any of the communities (results not 

shown). Finally, applying the approach of Garza & Williamson (2001), observed M 

values (Table 2.6) were consistent with the null distribution (p > 0.05) under the 

expectation of equilibrium for all the islands and at the different θ values considered. 

Table 2.6. Summary statistics of various tests to detect a recent bottleneck effect, based on mtDNA 

control region and microsatellite loci. p < 0.05, *; p > 0.05, ns . The Wilcoxon test found no significant 

heterozygosity excess after Bonferroni correction (pcrit = 0.008). SMM: stepwise mutation model. TPM: 

two-phased model 

mtDNA Microsatellites 

Tajima's D Fu's F 

Wilcoxon test 

(p-value) 

M Ratio 

SMM TPM 

Moorea 0.066 ns 0.417 ns 0.998 0.117 0.840 ns 

Tahiti -0.820 ns 5.331* 0.912 0.604 0.741 ns 

Bora Bora -0.461 ns 0.703 ns 0.979 0.924 0.735 ns 

Raiatea-Tahaa -0.283 ns -1.638 ns 0.849 0.396 0.796 ns 

Huahine -0.298 ns -0.542 ns 0.339 0.021 0.758 ns 

Nuku Hiva -0.110 ns 1.826 ns 0.515 0.032 0.729 ns 

50

2.5. Discussion 


2.5.1. Demographic closure of Moorea community 

The photo-identification surveys conducted at Moorea in 2002-2003 support Poole’s 

(1995) previous observation that, on an intra-generational time scale, spinner 

dolphins using the nearshore waters of this island form a small and relatively closed 

community. The re-sightings in 2002 of five DMIs previously known as members of 

the community between 1987 and 1992 (Poole 1995), coupled with Poole’s 

unpublished re-sightings of these individuals in the intervening years, suggest a lifetime 

site fidelity for at least some individuals (life-span is not precisely known for 

Gray’s spinner dolphins but is likely to be around 20-25 years old). A similar level of 

site fidelity has been reported from intermittent re-sights data at Oahu, Hawaii 

(Marten & Psarakos 1999), but Moorea is, to my knowledge, the only location where 

individual spinner dolphins have been re-sighted regularly over such a long period of 

time. 

Although observations also indicate some level of social openness, notably to 

dolphins from Tahiti, overall the level of interchange appears to be low. In the present 

study, no evidence of permanent immigration was found, while Poole (1995) 

recorded only two cases of long-term immigrants across the five years of his surveys. 

Contrary to Midway Atoll (Karczmarski et al. 2005), Moorea is not geographically 

isolated from any other island, Tahiti being just 17km distant (the closest island to 

Midway is Kure Atoll, 96km to the east). Despite this proximity, our photoidentification 

and genetic results clearly indicate that a distinct community of spinner 

dolphins use the nearshore waters of Tahiti. Note that interchanges with the 

neighbour community also occur in the form of temporary ‘visits’, as recorded in 

August 2002. 

2.5.2. Demographic community trends in the Society Archipelago 

Compared to what is known at Moorea from photo-identification, demographic 

information from the other islands is incomplete. However, from similarities in habitat 

use, group size and behaviour among the different islands, it seems reasonable to 

51


assume that the general demographic pattern described here (i.e., a small and 

relatively closed community on an intra-generational time scale) also holds for the 

other spinner dolphin communities, at least in the Society Archipelago. This pattern of 

island fidelity is also supported by the re-sighting of similar DMIs on two consecutive 

years at Tahiti and Raiatea. Indeed, four of the five DMIs identified at Tahiti in 2003 

were re-sighted in 2004, while three of the four DMIs identified at Raiatea in 2003 

were re-sighted in 2004 (Table 2.1). 

Based on contrasting results from the Big Island in Hawaii (Norris et al. 1994), 

Karczmarski et al. (2005) suggested that small population size and social stability at 

Midway Atoll are driven by habitat variation and geographic isolation. This does not 

seem entirely true in the Society Islands. Stable demography at Moorea (based on 

photo-identification data) and significant genetic structure in the archipelago (see 

below) indicate that small and closed communities can occur in groups of islands that 

are not geographically isolated. Therefore, benefits resulting from habitat fidelity (e.g., 

social interactions, local knowledge), or ecological constraints other than geographic 

isolation (e.g., competition for habitat), seem to influence the demographic closure of 

insular communities. 

2.5.3. Population genetic structure and sex-biased dispersal 

Although island fidelity is likely to represent the norm in the Society Archipelago, 

evolutionary history and current connectivity between communities would remain 

unknown without the support of molecular data. The molecular analyses presented 

here reveal a fine-scale genetic structure in these insular communities of spinner 

dolphins. Although recent population divergence could explain low level genetic 

differentiation, demographic data suggest that, for these islands, on-going gene flow 

is more likely to be responsible for such a pattern. 

A surprising result was the genetic isolation and low diversity at Tahiti. This difference 

was evident even when compared to the neighbouring community at Moorea, 

indicating low level gene flow between the two islands’ communities, particularly 

female gene flow (i.e., mtDNA). This differentiation with other island samples was 

also illustrated by a comparatively low level of mtDNA genetic diversity at Tahiti. 

52


Although this genetic pattern could be explained by a recent demographic bottleneck 

followed by population expansion (as suggested by a significant Fu’s FS), this 

scenario is not supported by the bottleneck tests based on microsatellites. An 

alternate explanation would be a fairly strict closure to immigration (at least 

concerning females) driven by social and/or demographic forces. Note that the 

southwest coastline of Tahiti (opposite side of the island from Moorea) was not 

surveyed during this study. Therefore, the existence of another community of spinner 

dolphins within this unexplored area cannot be excluded. 

Although only a small number of samples were collected at Nuku Hiva (n = 8), a high 

level of genetic differentiation between this community and those at all other islands 

was found. Unlike the differences among the Society Islands, the differentiation of 

Nuku Hiva is most likely due to the geographic isolation between the two 

archipelagos (1500 km). However, the absence of phylogeographic structure 

between samples and the finding of one common haplotype between both 

archipelagos suggest a recent isolation or low levels of on-going gene flow. 

Overall, gene flow appeared to be biased toward males, showing agreement with the 

predominate mating system in mammals (Greenwood 1980), and that of other 

delphinid species (Escorza-Trevino & Dizon 2000, Möller & Beheregaray 2004). 

Although the degree of bias is difficult to judge, the greater effect apparent in the sex- 

specific νAIc, compared to the sex-specific FST, suggests that dispersal rate is low 

overall (less than 10% per generation, Goudet et al. 2002). A trend in male-biased 

dispersal was also supported by the observation of three males at Raiatea 

(established by genotypes matches), who were initially sampled at Huahine. 

However, dispersal is not totally restricted to males, as one female was successively 

sampled at Moorea and Bora Bora, and female gene flow was indicated by numerous 

shared mtDNA haplotype, and low levels of mtDNA differentiation between some 

island samples. Taken together, these results suggest two distinct mechanisms of 

gene flow in insular communities of spinner dolphins: gene flow resulting from 

overlapping home-range and temporary ‘visits’ (possibly biased toward males), and 

gene flow resulting from occasional long-term immigration, by females as well as 

53


males, perhaps travelling in groups. Males might also disperse but achieve little or no 

reproductive success as immigrants. Such demographic trends could explain our field 

observations and the actual genetic pattern of mitochondrial and nuclear DNA. 

2.5.4. Pelagic colonisation or island metapopulation? 

A striking characteristic of my results was the high level of mitochondrial genetic 

diversity (as illustrated by estimates of Nef) in contrast to the relative demographic 

isolation of small communities. Note that Nef estimates are subject to considerable 

uncertainty due to the method used to estimate µ and θ, and must be interpreted 

cautiously (Waples 2002). However, even lower values of the 95% confidence 

intervals are still indicating very large Nef. 

Observed levels of genetic diversity could reflect the effect of founder events, due to 

recent colonisation of insular habitats. In such a case, the diversity would simply be 

the signal of the historical polymorphisms contained in a large parental population, 

potentially from a pelagic source, such as the Eastern Tropical Pacific. Long-term Ne 

can indeed reflect, for a few generations at least, a population’s pre-bottleneck 

history rather than its current demography (e.g., Storz et al. 2002). However, in the 

data, no indirect evidence was found for such a colonisation scenario in the 

frequencies of mtDNA haplotypes or microsatellite alleles using various tests for a 

bottleneck. Furthermore, dedicated boat surveys (Gannier 2000) and aerial surveys 

(Poole 1995) in the inshore and offshore waters of the Society Archipelago found no 

evidence for the existence of an offshore population of spinner dolphins in this area. 

Thus it appears unlikely that current connectivity with a large pelagic population can 

explain the high genetic diversity in spinner dolphins of the Society Islands. 

Instead, I consider that current levels of mitochondrial diversity in insular communities 

of the Society Archipelago are more likely the result of a metapopulation dynamic. In 

the classical metapopulation model, the environment consists of spatially isolated 

patches of suitable habitat positioned within a continuum of unsuitable habitat that 

individuals can traverse but within which cannot breed (Levins 1969). The 

demographic pattern described here and the significant genetic differences between 

these insular communities suggest that spinner dolphins from the Society 

54


Archipelago, follow this model. In a metapopulation dynamic, the observed 

discrepancy between the high level of genetic diversity and census size is not 

unexpected. Indeed, it has been shown that long-term Ne often exceeds the 

instantaneous census number of populations that are subdivided into a network of 

socially defined breeding groups (e.g., Sugg et al. 1996). Moreover, with sufficient 

dispersal between patches, Ne of subpopulations can approach Ne of the whole 

metapopulation (Hedrick & Gilpin 1997). My results support this pattern, with Nef 

estimated for the Society Archipelago islands being comparable to Nef estimated for 

single islands. 

Note that even under a metapopulation dynamic, my estimates of Nef are so large 

that they suggest an overall population that must extend beyond the boundaries of 

the Society Archipelago. Several evolutionary histories could explain this pattern: (1) 

spinner dolphins are commonly distributed throughout the insular habitats of the 

tropical and sub-tropical Pacific (SPWRC 2004), which include more than 20,000 

islands, more or less remote from one another. The extent of this habitat could thus 

support a very large metapopulation (following the model described here for the 

Society Archipelago) and would explain the current high levels of genetic diversity. 

However, the results here suggest that geographic distance can represent a limit to 

gene flow. (2) Current gene flow occurs between insular spinner dolphins and large 

pelagic populations found in the ETP. The distributional limit of the whitebelly spinner 

dolphin is fairly close to the Marquesas Archipelago (Figure 2.1a) and could 

represent a zone of interchange with the insular spinner dolphins of the Central and 

West Pacific. In this case, the metapopulation would follow a mainland-island model 

(Harrison 1991), where the mainland is represented by pelagic populations. In a 

worldwide study of spinner dolphin genetic diversity, Galver (2002) found no obvious 

phylogeographic structuring in mtDNA haplotypes, even between sub-species of 

spinner dolphins (although no samples from French Polynesia were available in this 

study). Current gene flow between sub-species is thus a possibility. Finally (3), 

Galver (2002) suggested a recent worldwide demographic expansion of spinner 

dolphins to explain a lack of phylogeographic structure. Such a global event could 

also have influenced the current genetic diversity found in the population, although 

55


such diversity could not persist in the small island communities without additional 

influence. 

By combining a demographic approach with molecular tools, this study provides 

valuable insights into the structure and dynamics of insular spinner dolphins’ 

communities. This work showed that these communities are based on a complex 

equilibrium between isolation and interchange. While social stability and site fidelity 

represent strong components, genetic diversity reveals that communities are still 

evolutionary connected through gene flow. However, further studies covering a larger 

geographical scale are still needed to clarify the extent of the metapopulation and the 

influence of historical events as well as proximate social reproductive barriers on 

current patterns of genetic diversity. From a conservation perspective, the complex 

population dynamic described here shows that geographically isolated communities 

of insular spinner dolphins are likely to represent separate management units on an 

ecological time scale. Considering the regular use of inshore habitat by this species, 

a detailed assessment of the degree of connectivity (intra- and inter-generation) of 

communities that are particularly exposed to human activity is recommended in order 

to ensure proper management for their long-term viability and equilibrium of the 

metapopulation dynamic. 

56

Chapter three: Worldwide mtDNA diversity of pilot whale spp. 

3. Worldwide mtDNA phylogeography and diversity 

of pilot whale species (Globicephala spp.) 

A group of short-finned pilot whales on the west coast of Moorea, August 2002. 

57

3.1. Abstract 


Pilot whales (Globicephala melas and G. macrorhynchus) provide an interesting 

example of recent complex evolutionary history in a pelagic environment. Both 

species have very wide ranges but are largely parapatric: G. melas (long-finned pilot 

whale) is anti-tropical except in the North Pacific, while G. macrorhynchus (shortfinned 

pilot whale) has a circum-global distribution, mainly in the tropics and 

subtropics. To investigate pilot whale evolution and biogeography, we analysed 

worldwide population structure for the mitochondrial (mt) DNA control region (335 bp) 

using newly generated and previously published and unpublished sequences from a 

variety of sources (long-finned pilot whale = 434; short-finned pilot whale = 134), 

including strandings in New Zealand and surveys of whalemeat markets in Japan 

and Korea. Both species had very low worldwide mtDNA diversity compared to other 

widespread cetaceans (long-finned pilot whale, π = 0.31%; short-finned pilot whale, 

π = 0.87%). Six fixed diagnostic nucleotide substitutions (synapomorphies) 

distinguish these sister taxa. However, phylogenetic reconstruction suggested that 

the short-finned pilot whale was paraphyletic with respect to long-finned pilot whale; a 

result which could be due to incomplete lineage sorting. Long-finned pilot whale 

showed strong differentiation between ocean basins (FST = 0.468, p < 0.001), but the 

presence of shared haplotypes between the North Atlantic “edwardii” and Southern 

Ocean “melas” forms suggests that current subspecies designations may require 

revision. Overall, long-finned pilot whale phylogeography seems best explained by a 

recent worldwide demographic expansion. For short-finned pilot whale, Japanese 

waters appear to represent an important centre of diversity. Assuming locations of 

purchases generally reflected locations of hunting, analyses strongly support the 

genetic distinctiveness of the “Northern” and “Southern” forms previously described 

from this region (FST = 0.413, p < 0.001). Based on results from a worldwide 

haplotype network, a third population also occurs in these waters, products from 

which are also sold on the Japanese market. Overall, higher diversity observed in 

south Japan and phylogenetic evidence suggests that the “Southern” form represents 

an ancestral, but now genetically isolated population. 

58



Genetic boundaries among populations in the marine environment are particularly 

difficult to describe, as the physical and biological factors that determine gene flow 

patterns are often poorly understood (Palumbi et al. 1997). Although the high 

dispersal potential of marine species can result in low genetic differentiation across 

large areas (Hellberg 1994, Graves 1996), there are also many examples of finescale 

population structure (Palumbi 1994). Among cetaceans, limits to gene flow are 

complex and thought to be the result of behavioural specialisations for resources, 

social organisation, and historical environmental changes (Hoelzel 1998). However, 

because studies of free-swimming cetaceans are challenging (particularly for pelagic 

species), the demography and evolutionary history of most species remains unclear 

or unknown. In the family Delphinidae (including pilot whales), these issues are 

further obscured by the relatively recent evolution of this group. The Delphinidae are 

thought to have arisen about 11 million years ago (Barnes 1985), and subsequently 

have undergone a rapid radiation, such that there has been comparatively little time 

for the evolution and fixation of diagnostic morphological and genetic characters 

among species. 

The two recognised species of the genus Globicephala provide an interesting 

example of a recent and probably complex evolutionary history. The long-finned pilot 

whale (G. melas, Traill 1809) and the short-finned pilot whale (G. macrorhynchus, 

Gray 1846) are widely-distributed and abundant species of large dolphins (up to 

seven meters for the males) (Figure 3.1). Although their similar appearance and 

morphology has resulted in some confusion, a number of features, in particular the 

shape of the skull, validate the distinctiveness of the two species (van Bree 1971). 

Phylogenetic analyses of mitochondrial DNA (mtDNA) cytochrome b sequences also 

supported the distinctiveness of these species (LeDuc et al. 1999, May-Collado & 

Agnarsson 2006), although only 1 – 2 individuals were used to represent each taxon 

in these studies. The two species are wide ranging but also largely parapatric. There 

are no global estimates of abundance for either species, but several regional 

estimates are available (see Olson & Reilly 2002 for a review), suggesting that they 

59

are relatively abundant worldwide. 


Figure 3.1. Lateral view of a female short-finned pilot whale (Globicephala macrorhynchus) (top) and 

a female long-finned pilot whale (Globicephala melas) (bottom). Drawings by P. Folkens. Location of 

the main morphological differences between the two species are indicated by arrows: the skull shape 

(s), the number of teeth (t) and the length of the flippers (f). 

Pilot whales are amongst the most gregarious of cetaceans, forming groups of up to 

several hundred individuals. Their social system is thought to be matrilineal, with 

groups comprising of several generations of maternally-related individuals (Amos et 

al. 1993, Heimlich-Boran 1993). They are well-known for their highly cohesive 

behaviour, which allows them to be herded by a small number of boats and exploited 

by “drive-kill” fisheries. This strong social cohesion is also thought to be the reason 

behind their propensity for mass stranding. As with other matrilineal odontocetes 

(toothed whales), such as the killer whale and the sperm whale, Globicephala spp. 

seem to have low genetic diversity at the maternally-inherited mtDNA (Siemann 

1994, Whitehead 1998). The reasons for this pattern of low diversity remain subject 

to debate; some authors have argued in favour of demographic processes 

influencing the mtDNA genome (e.g., Mesnick et al. 1999), while Whitehead (1998, 

2005) proposed a form of “cultural hitchhiking”, where mtDNA diversity is reduced by 

parallel selection on maternally-transmitted cultural traits. A genetic bottleneck has 

also been suggested as potential factor in reducing the worldwide diversity of the 

sperm whale and killer whale (Lyrholm et al. 1996, Hoelzel et al. 2002b). Such a 

scenario could apply to pilot whales but until now their mtDNA diversity has only 

been investigated in the North Atlantic (Siemann 1994). 

60


Figure 3.2. Global distribution of Globicephala spp., with number and source locations of sequences 

used in this study (n = full dataset/corrected dataset, see section 3.3.4 for explanation). Stripped area 

shows the range of the long-finned pilot whale (Globicephala melas), while dark grey shows the range 

of the short-finned pilot whale (G. macrorhynchus). The black area is the range of overlapping 

distribution between the two species. 

Long-finned pilot whales (G. melas) inhabit the cold temperate waters of the North 

Atlantic and the Southern Hemisphere, such that two widely-separated populations 

are apparently isolated by equatorial waters (Figure 3.2). Based on some differences 

in colour pattern, populations in the Northern Atlantic and Southern Hemispheres 

were described as different species by Rayner (1939), but Davies (1960) reduced 

them to sub-species rank: G. melas melas in the North Atlantic and G. melas 

edwardii in the Southern Hemisphere. Davies (1960) argued that the last contact 

between the two current subspecies would have occurred about 10,000 years ago 

during the last Pleistocene glaciation, when equatorial waters were substantially 

cooler. No study has yet explored the genetic relationship between the North Atlantic 

and Southern Ocean subspecies of long-finned pilot whales. Although long-finned 

pilot whales are now absent in the North Pacific, skulls identified as this species have 

also been recovered at several archaeological sites in Japan (dating from the 8th to 

61


12th centuries, Kasuya 1975) and Alaska (dating from the 3,500 to 2,500 BP, Frey et 

al. 2005), suggesting a recent extinction in this ocean. 

Short-finned pilot whales (G. macrorhynchus) range across the tropical and warmtemperate 

waters of the Atlantic, Pacific and Indian Ocean (Figure 3.2). Off the coast 

of Japan, a “Southern” form and a “Northern” form of short-finned pilot whales have 

been described on the basis of morphological, genetic and ecological differences 

(Kasuya 1986, Kasuya et al. 1988, Wada 1988, Kage 1999, Figure 3.3). The 

Northern form appears to be larger (Kasuya 1986), possibly an adaptation to colder 

waters, and has a more distinct saddle mark, and rounder contour to the head 

(Kasuya et al. 1988). The geographical ranges of the two forms occasionally overlap 

(seasonally), but mixed groups are thought to be very rare (Kasuya et al. 1988). A 

similar segregation of northern and southern forms might exists among short-finned 

pilot whales in the eastern North Pacific, with the larger form again found in the 

cooler temperate waters (Polisini 1980). 

Here, we use sequences of the mtDNA control region to examine genetic population 

structure of long-finned (n = 434) and short-finned (n = 134) pilot whales worldwide. 

The aim was to provide new information on the evolutionary history of this genus by 

investigating the phylogenetic relationships and inter- and intra-species genetic 

diversity. Studies of cetacean phylogeography often assume that the species under 

consideration represent independent lineages. However, it has been shown that 

paraphyly and polyphyly of mtDNA lineages is not uncommon in the family 

Delphinidae (LeDuc et al. 1999, Reeves et al. 2004). Therefore, among closely 

related taxa, it is important to test monophyly through comprehensive surveys of 

population-level sequence variation. Here we test the hypothesis of species-level 

monophyly of mtDNA lineages for these taxa. Diversity and phylogeography of both 

species were then investigated, with particular focus on two issues: (1) for longfinned 

pilot whales - the level of genetic diversity and relationships between the two 

subspecies; and, (2) for short-finned pilot whales - the evolutionary history of 

Northern and Southern forms around Japan in relation to those in other regions. 

62


Table 3.1. Sample data for all pilot whale specimens used in this study. 

Code 

Type of 

sampling 

event 

# 

individuals 

per event 

Long-finned pilot whale (Globicephala melas) 

New Zealand 

Glo001-004 and 

Glo023-047 

Collection 

Date* 

Location* Haplotypes ¥ Source 

MS 27 07 Dec 1993 Long Bay Auckland O(13), P(14) (1) 

Glo005-007 MS 3 21 Oct 1995 Cape Palliser P(3) (1) 

Glo008 IS 1 26 Oct 1995 Muriwai P (1) 

Glo015 IS 1 22 Nov 1996 Rumati P (1) 

Glo016 IS 1 30 Oct 1997 Kawakawa Bay P (1) 

Glo017 IS 1 ? ? R (1) 

Glo018 IS 1 1997 Opotiki P (1) 

Glo019 IS 1 28 Oct 1998 Hokitika P (1) 

Glo020-022 MS 3 30 Nov 1998 Chatham Island P(3) (1) 

Glo049 IS 1 18 Nov 1998 Bay of Penty P (1) 

Glo050 IS 1 22 July 1999 Sandfly Bay, Otago P (1) 

Glo051-061 MS 11 24 Oct 1999 Pitt Island P(10), T(1) (1) 

Glo062 IS 1 ? New Plymouth P (1) 

Glo063 IS 1 22 Apr 1998 New Plymouth R (1) 

Glo064 IS 1 30 nov 1999 Westland P (1) 

Glo065 IS 1 30 nov 2000 Chatham Island Q (1) 

Glo066-085 MS 20 

21-22 Dec 

2000 

Stewart Island P(19), U(1) (1) 

Glo086 IS 1 11 Nov 2002 Jackson Bay U (1) 

Glo087-089 MS 3 17-18 Oct 2002 Sponge Bay, Gisborne P(3) (1) 

Glo090-213 MS 124 08 Jan 2003 Stewart Island P(124) (1) 

Glo214 IS 1 27 Dec 2002 Haast, Jackson Bay P (1) 

Glo215-217 MS 3 21 Dec 2003 Sponge Bay, Gisborne S(3) (1) 

Glo218 IS 1 Jan 2004 Manaia P (1) 

Glo219 IS 1 29 May 2004 Poutawa Stream Mouth P (1) 

Glo220-230 MS 11 04 Jul 2004 Mahurangi Peninsula P(11) (1) 

Glo231 IS 1 04 Jul 2004 Mahia, Opoutama P (1) 

Glo234-284 MS 51 29 Nov 2004 Opoutere Beach O(1), P(50) (1) 

Glo285 IS 1 18 Dec 2004 Muriwai Beach P (1) 

Glo286-318 MS 33 

28-30 Dec 

1992 

Golden Bay 

P(15), Q(2), 

U(15), V(1) 

(1) 

Glo320-330 MS 11 09 Nov 1993 Golden Bay P(11) (1) 

Glo333-337 MS 5 14 Feb 1995 Otago, Waianakarua P(5) (1) 

Glo338-342 MS 5 21 Oct 1995 Wellington P(5) (1) 

Glo343-348 MS 6 15 Feb 1996 Golden Bay P(6) (1) 

Glo349-351 MS 3 17 Nov 1993 Golden Bay P(3) (1) 

Australia 

11b IS 1 14 Sep 2002 Sisters Beach - Rocky Cape Q (2) 

20c-24c MS 5 28 Nov 2004 King Island. Q(2), R(2), W(1) (2) 

29c-33c MS 5 19 Nov 2003 Point Hibbs, West Coast Q(5) (2) 

48a-66a MS 16 29 Nov 2004 Darlington, Maria Island P(15), U(1) (2) 

North Atlantic 

Siemann01-02 BC 2 ? Western North Atlantic S(2) (3) 

Siemann03-06 BC 4 1989 Western North Atlantic S(4) (3) 

Siemann07-09 BC 3 09 Mar 1990 3932N/7246W S(3) (3) 

Siemann10 BC 1 05 Apr 1990 3900N/7300W S (3) 

Siemann11-12 BC 2 06 Apr 1990 3954N/7157W S(2) (3) 

Siemann13-15 BC 3 16 Apr 1990 4014N/7055W S(3) (3) 

Siemann16-21 BC 6 Apr 1990 4010N/7001W S(6) (3) 

Siemann22-24 BC 3 1992 Western North Atlantic S(3) (3) 

Siemann25-37 MS 13 11 Dec 1990 Hyannis, USA S(13) (3) 

Siemann38-42 MS 5 Sep 1991 Dennis/Sandwich/Truro,USA S(5) (3) 

Siemann43 IS 1 Sep 1991 Wellfleet/Brewster, USA S (3) 

Siemann44-48 MS 5 Sep 1991 Eastham, USA S(5) (3) 

Siemann49-51 MS 3 07 Jul 1991 Sable Island, Nova Scotia X(3) (3) 

Siemann52 IS 1 ? Gros Morin, Newfoundland P (3) 

Siemann53-54 MS 2 1976 The Wash, eastern England S(2) (3) 

Siemann55 IS 1 1990 Liverpool, England S (3) 

Siemann56-59 MS 4 1992 Western Scotland S(4) (3) 

Dizon01 ? 1 ? Faeroe Islands S (4) 

Dizon02-11 ? 10 ? Faeroe Islands P (10) (4) 

63

Table 3.1 continued 

Code 


sampling 

event 


# 

individuals 

per event 

Collection 

Date* 

Short-finned pilot whale (Globicephala macrorhynchus) 


South-Pacific 

Glo009 IS 1 02 Feb 1996 New Zealand A (1) 

Glo011-014 MS 4 01 Feb 1996 New Zealand A(2), C(2) (1) 

Glo048 IS 1 Nov 1998 New Zealand A (1) 

Glo02FP01-06 BS 5 12 Aug 2002 Moorea, French Polynesia C(5) (1) 

Glo02FP07-09 BS 3 29 Aug 2002 Moorea, French Polynesia A(2), B(1) (1) 

Glo03FP01-09 BS 9 16 Sept 2003 Moorea, French Polynesia A(7), C(2) (1) 

Glo04FP01-07 BS 7 07 Oct 2004 Moorea, French Polynesia A(3), C(4) (1) 

Glo97NC01-02 MS 2 1997 New Caledonia A(1), C(1) (5) 

Glo03Sa01-03 BS 3 24 Sept 2003 Samoa C(3) (6) 

Japan/Korea 

Ja98-89 M 1 1998 ? L (7) 

J98D-32 M 1 1998 Chiba M (7) 

J98D-55 M 1 1998 Miyagi E (7) 

J98D-66 M 1 1998 Wakayama K (7) 

J98D-71 M 1 1998 Wakayama M (7) 

J99-004 M 1 1999 Miyagi F (7) 

J99-032 M 1 1999 Chiba M (7) 

J99-040 M 1 1999 Wakayama N (7) 

J99-078 M 1 1999 Osaka I (7) 

J9983 M 1 1999 Osaka M (7) 

J00.35 M 1 2000 Osaka K (7) 

J00.72 M 1 2000 Wakayama C (7) 

J00.73 M 1 2000 Osaka L (7) 

J02.073 M 1 2002 Miyagi M (7) 

J02.096 M 1 2002 Fukuoka G (7) 

J02.043 M 1 2002 Miyagi E (7) 

J02.132 M 1 2002 Wakayama L (7) 

J02-OK22 M 1 2002 Okinawa C (7) 

JE02.M07 M 1 2002 Miyagi E (7) 

JE02.OK13 M 1 2002 Okinawa C (7) 

J02.OK13 M 1 2002 Okinawa I (7) 

J02.OK20 M 1 2002 Okinawa J (7) 

JE02-W03 M 1 2002 Wakayama C (7) 

JE02-W10 M 1 2002 Wakayama M (7) 

JE02-W13 M 1 2002 Wakayama M (7) 

JE02-W14 M 1 2002 Wakayama I (7) 



JE02-W24 M 1 2002 Wakayama G (7) 

JHK02.7 M 1 2002 ? M (7) 

JHK02.15 M 1 2002 Wakayama G (7) 

J02.S5 M 1 2002 Miyagi E (7) 

J02.TG1 M 1 2002 Wakayama M (7) 

J03-68 M 1 2003 Wakayama H (7) 

J03.43 M 1 2003 Miyagi E (7) 

JE03-OK8 M 1 2003 Okinawa K (7) 

JE03-OK14 M 1 2003 Okinawa I (7) 

JE03-OK18 M 1 2003 Okinawa C (7) 

JE03-OK38 M 1 2003 Okinawa I (7) 

JE03-OK44 M 1 2003 Okinawa J (7) 

JKH03.16 M 1 2003 ? K (7) 

JP03.08 M 1 2003 Wakayama C (7) 

J04-12 M 1 2004 Wakayama M (7) 

J04-58 M 1 2004 Wakayama N (7) 

J04-OK27 M 1 2004 Okinawa J (7) 

K04-13 M 1 2004 Korea, Ulsan M (7) 

Kage01-04 (nf) CF 4 ? Hokkaido E(4) (8) 

Kage05-07 (sf) CF 3 ? Tokyo K(1), M(2) (8) 

Kage08-14 (sf) CF 7 ? Tokyo M(7) (8) 

Kage15-22 (sf) CF 8 ? Tokyo J(1), K(3), M(4) (8) 

Kage23-24 (sf) CF 2 ? Tokyo I(2) (8) 

Kage25-31 (sf) CF 7 ? Tokyo M(7) (8) 

Kage32-36 (sf) CF 5 ? Tokyo I(5) (8) 

Kage37-40 (sf) CF 4 ? Tokyo I(1), K(3) (8) 

64

Table 3.1 continued 

Code 


sampling 

event 


# 

individuals 

per event 

Collection 

Date* 


eastern North Pacific 

Siemann60 BC 1 27 Sep 1990 East Tropical Pacific E (3) 

Siemann61 BC 1 28 Jul 1992 Southern California A (3) 

Atlantic 

NEPST637 IS 1 Porto Rico A (9) 

Siemann62 IS 1 07 Apr 1978 North Carolina, USA D (3) 

Siemann63 IS 1 12 Apr 1978 North Carolina, USA D (3) 

Siemann64 IS 1 18 May 1983 North Carolina, USA D (3) 

Siemann65 IS 1 11 Nov 1991 Delaware, USA D (3) 

Siemann66-69 BC 4 8 Nov 1990 Western North Atlantic D(4) (3) 

Siemann70 BC 1 17 Nov 1990 Western North Atlantic D (3) 

Siemann71-72 BC 2 18 Oct 1992 Western North Atlantic D(2) (3) 

‡ Mass strandings with (nf) and (sf) refer to “Northern” form and “Southern” form of Japanese shortfined 

pilot whale, respectively, as reported by Kage (1999). ¥ Numbers in brackets in the haplotype 

column indicate the number of individuals sharing the haplotype within the sampling event. * For 

market products, collection date and location refer to the year and prefecture where the products were 

purchased. Codes for sampling events: MS (Mass Stranding), IS (Individual Stranding), BC (By- 

Catch), BS (Biopsy Sample), MP (‘whale-meat’ Market Product) and CF (Coastal Fisheries). 

Sample sources: 

(1) University of Auckland, New Zealand cetacean molecular archive, and courtesy Department of 

Conservation. 

(2) Department of Primaries Industries and Waters, Tasmania, Australia. 

(3) Siemann (1994): GenBank accession numbers U20921 to U20923 (short-finned pilot whale), and 

U20926 to U20928 (long-finned pilot whale). 

(4) Dizon et al. (1993), as reported in Siemann (1994) 

(5) Claire Garrigue, Opération Cétacés, New Caledonia. 

(6) Olavarría et al. (2003). 

(7) University of Auckland whale meat market surveys. 

(8) Kage (1999), PhD thesis. 

(9) Red Caribeña de Varamientos, Caribbean Stranding Network. 


3.3.1. Sample collection and additional sequences 

Long-finned pilot whales - A total of 364 tissue samples of long-finned pilot whales 

were collected from 19 single and 19 mass strandings around New Zealand and 

Tasmania, Australia (Table 3.1). In addition, sequences of three mtDNA control 

region haplotypes were available from GenBank, representing a total of 70 

individuals sampled in the North Atlantic. The relative numbers of individuals with 

65


each haplotype were deduced from the haplotype frequencies reported in Siemann 

(1994) (Table 3.1). Siemann’s (1994) samples came from stranding events and 

incidental fisheries takes (by-catch). 

Short-finned pilot whales – A total of 36 tissue samples of short-finned pilot whales 

were collected in the South Pacific (New Zealand, n = 6; French Polynesia, n = 24; 

New Caledonia, n = 2; and Samoa, n = 3) and in the North Atlantic (Puerto Rico, n = 

1); nine of these samples came from stranded animals (three single and two mass 

strandings), while 27 samples were collected from five groups at sea using a small 


a variable pressure valve (Krützen et al. 2002, Table 3.1). Three additional haplotype 

sequences of short-finned pilot whale mtDNA control regions were available from 

GenBank, representing 13 individuals as reported in Siemann (1994) (see Table 3.1). 

These samples came from strandings and by-catch. 

Sequences of short-finned pilot whales from Japan and Korea were obtained from 

two distinct sources: the study by Kage (1999) based on data from the Japanese 

coastal drive-kill fisheries; and “whale-meat” products purchased in the commercial 

markets of Japan and Korea as reported in Dalebout et al. (2004b) and/or archived 

by C. S. Baker at the University of Auckland (Table 3.1). Sequences from Kage 

(1999) represent a total of 40 individuals from Japanese coastal hunts. These 

sequences were reported to belong to either the “Northern” (n = 4) or “Southern” form 

(n = 36) of the Japanese short-finned pilot whale (Table 3.1). Sequences reported in 

Dalebout et al. (2004b) and/or archived by C. S. Baker represent a total of 45 

individuals from Japan, plus one individual from South Korea. Although no 

information was available on what regional form these ‘whale-meat’ market products 

represented, products from small cetaceans are generally assumed to originate from 

coastal hunting or by-catch near the prefecture of sale (Endo et al. 2005). This 

information was available for all market products but three (Table 3.1, Figure 3.3). 

The final sample sizes were 434 long-finned and 134 short-finned pilot whales 

sequences. 

66


Figure 3.3. The origin and number of Japanese and Korean short-finned pilot whale products from 

which sequences were used in this study (n = full dataset/corrected dataset, see section 3.3.4 for 

explanation). All sequences from Hokkaido and Tokyo were from Kage’s (1999) study and were 

known to come from the “Northern” and “Southern” form of short-finned pilot whales, respectively. All 

other sequences were from products purchased during “whale-meat” market surveys (Baker et al. 

1996), as reported in Dalebout et al. (2004b) and/or archived by C.S. Baker at the University of 

Auckland. The distinction between ‘North Japan’ and ‘South Japan’ as described in the text is 

illustrated by the dashed line and the light grey colour for the ‘North Japan’ waters. 

3.3.2. Laboratory analyses of tissue samples 

Total cellular DNA was isolated from skin tissue (for stranding and biopsy samples) 

by digestion with proteinase K followed by a standard phenol:chloroform extraction 

method (Sambrook et al. 1989) as modified for small samples by Baker et al. (1994). 

An 800 base pair (bp) fragment of the 5’ end of the mtDNA control region (d-loop) 

was then amplified using the Polymerase Chain Reaction (PCR) and the primers 

light-strand, tPro-whale M13-Dlp-1.5 (Baker et al. 1996), and heavy strand, Dlp-8G 

67


(designed by G. Lento as reported in Dalebout et al. 2005). Primer sequences are 

reported in Chapter 2, section 2.3.4. All amplification reactions were carried out in a 

total volume of 20 µL with 1 x Ampli-Taq buffer, 2.5 mM MgCl2, 0.4 µM of each 

primer, 0.2 mM dNTPs and 0.5 U of Ampli-Taq® DNA polymerase. The PCR 

temperature profile was as follows: a preliminary denaturing period of 2 min at 94°C 

followed by 35 cycles of denaturation for 30 sec at 94°C, primer annealing for 45 sec 

at 55°C and polymerase extension for 40 sec at 72°C. A final extension period of 10 

min at 72°C was included at the end of the cycle. PCR products were purified for 

sequencing with ExoSAP-IT (USB) and sequenced in both directions with BigDye 

terminator chemistry v.3.1 on an ABI3100 DNA sequencer (Applied Biosystems Inc.). 

New sequences and previously published or reported sequences were aligned using 

Sequencher TM v. 4.1.2 (Genes Codes Co.) and edited manually. These were trimmed 

to a consensus length of 345 bp. Variable sites and unique haplotypes were 

identified using MacClade v. 4.0 (Maddison & Maddison 2000). 

3.3.3. Phylogenetic reconstruction 

The phylogenetic relationship of the mtDNA haplotypes was reconstructed using 

neighbour joining (NJ), maximum-parsimony (MP), and maximum likelihood (ML) 

methods, as implemented in PAUP* v. 4.0b10 (Swofford 2000), and Bayesian 

analyses (BA), as implemented in MrBayes v. 3.1.2 (Huelsenbeck & Ronquist 2001, 

Ronquist & Huelsenbeck 2003). Following the recommendations of Nei & Kumar 

(2000), a simple p-distance (or uncorrected ‘p’) model of nucleotide substitution was 

used for the NJ reconstruction, considering the low number of nucleotide 

substitutions per site (< 0.05). The heuristic search conditions for MP used starting 

trees obtained by stepwise addition with 10 random sequence addition replicates and 

tree-bisection-reconnection (TBR) branch swapping. For ML, heuristic search 

conditions were similar, and the model of sequence evolution recommended by 

Modeltest v. 3.7 (Posada & Crandall 1998) was used (HKY+G, with estimated 

nucleotide frequencies A = 0.3102, C = 0.2193, G = 0.1050, T = 0.3655, 

transition/transversion ratio = 14.8107, and gamma shape parameter G = 0.0157). 

The BA was also run based on an HKY+G model; that is, with two substitution types 

(“nst” = 2), base frequencies set to the empirically observed values (“basefreq” = 

68


empirical), and rate variation across sites modelled using a gamma distribution 

(“rates” = gamma). Further, six chains were used for phylogeny estimation. Analysis 

was started with a random tree, and was run for 2,000,000 generations (every 

1,000th tree was sampled). Using the ‘sumt’ command of MrBayes, the initial 5,000 

trees were discarded as burn-in. Homologous sequences of one or two closely 

related species, melon-headed dolphin (Peponocephala electra) and/or Risso’s 

dolphin (Grampus griseus), were used as outgroups. The robustness of phylogenetic 

groupings was assessed by bootstrap re-sampling (replicates: NJ-5,000; MP-1,000; 

ML-200) and, for the BA, using the Bayesian posterior probabilities obtained from the 

50% majority-rule consensus of all trees sampled after trees from the initial burn-in 

stage had been removed. Clades with bootstrap values > 70% were considered 

robust (Hillis & Bull 1993). 

3.3.4. Geographical areas and adjusted sampling 

To investigate phylogeographic structure, the specimens from each species were 

grouped in different geographical units. Three units were considered for long-finned 

pilot whales: North Atlantic (n = 70), Tasmania (n = 27) and New Zealand (n = 337); 

and four areas were considered for short-finned pilot whales: Japan/Korea (n = 85), 

South Pacific (n = 35), North-East Pacific (n = 2) and Atlantic (n = 12) (Figure 3.2). 

For subsequent analyses, some of these areas were grouped together, subdivided 

further (Japan/Korea) or excluded, depending on the question addressed. 

Given the assumed matrilineal social system of pilot whales (Amos et al. 1993, 

however see Chapter 4), animals in the same mass stranding event or forming part 

of the same group at sea (represented here by samples from by-catch or biopsies) 

are likely to have a close maternal relationship. In order to avoid a bias towards 

related individuals, only one representative of each unique matriline (i.e., of each 

mtDNA haplotype) was selected per ‘sampling event’, where a sampling event was 

considered to be either: a single stranding, a mass stranding, a by-catch event (all 

animals caught in the same area, over a short period of time), a market sampling 

event (all samples purchased on one day or consecutive days in the same 

prefecture) or biopsy sampling from a group at sea (Table 3.1, Figure 3.2). Note that 

the use of such an “adjusted dataset” greatly reduces the sample size (long-finned 

69


pilot whales, n = 66, short-finned pilot whales, n = 83). As a consequence, it is likely 

to be highly conservative, and could potentially result in a bias in the opposite 

direction (due to exclusion of non-kin individuals sharing the same common 

haplotype by chance), and potential overestimation of diversity and underestimation 

of genetic structure. For comparison, some analyses were also run using the full 

dataset (results are presented in Appendix 4). 

3.3.5. Genetic diversity and population structure 

Standard indices of genetic variation, including nucleotide diversity (π) and haplotype 

diversity (h), were calculated for each species and for each geographic unit, using 

Arlequin v. 3.01 (Excoffier et al. 2005). 

To test for genetic differentiation between geographic units, analyses of molecular 

variance (AMOVA) were conducted independently for each species, using FST and 

ΦST as implemented in Arlequin (see Chapter 2 for details on FST and ΦST). Statistical 

significance was tested over 20,000 permutations of the data. For long-finned pilot 

whales, the analysis was conducted by considering the three geographical units 

described in the section above. For short-finned pilot whales, the AMOVA was 

conducted by considering samples from South Pacific, Atlantic and Japan/Korea; the 

samples from eastern North Pacific were not considered here because of the small 

sample size (n = 2). The samples from Japan/Korea were further sub-divided in two 

distinct sub-units, in order to address the question of genetic differentiation between 

the “Northern” and “Southern” form of Japanese short-finned pilot whales (as 

described in Section 3.2). However, since there was no information on the form from 

which the market products originated, samples were allocated to their sub-unit based 

on the prefectures of sale (for “whale-meat” market samples) and prefecture of 

collection (for Kage’s (1999) samples). To avoid confusion with the “Northern” form 

and “Southern” form as identified from morphology, here the two sub-units were 

referred to as ‘North Japan’ and ‘South Japan’. ‘North Japan’ encompassed samples 

from the prefectures of Miyagi and Hokkaido, while the ‘South Japan’ encompassed 

samples from the prefectures south of Miyagi; i.e., the prefectures of Chiba, Tokyo, 

Wakayama, Osaka, Fukuoka, Okinawa, as well as the sample from Ulsan, South 

Korea (Figure 3.3). This boundary between ‘North Japan’ and ‘South Japan’ was 

70


determined by considering the distributions of the “Northern” and “Southern” forms of 

Japanese pilot whales described by Kasuya et al. (1988). As these distributions are 

known to overlap depending on the seasons (Kasuya et al. 1988), the categorisation 

of the prefectures is probably not a completely accurate representation of the two 

forms. However, this overlap is sufficiently small to anticipate that the effects of miscategorisation 

should be small. The three market products with unknown prefecture 

of origin were not included in the analyses segregating ‘North Japan’ and ‘South 

Japan’ (Table 3.1). 

3.3.6. Demographic history 

To investigate the demographic history of the two species, departure from mutationdrift 

equilibrium was tested within each area by estimating the D values of Tajima 

(1989b) and the FS values of Fu (1997). In addition to providing a test of neutrality for 

the locus under investigation, these statistics can also detect the occurrence of 

particular demographic events, such as a population expansion or a recent 

bottleneck event (Rand 1996, Fu 1997, see Chapter 2 for details on these methods). 

Their significance was inferred by randomisation (10,000 steps) using a coalescent 

simulation algorithm (Hudson 1990). 

Within-species phylogeography was further inferred using haplotype network 

reconstruction. Here, two different methods of reconstruction were used to assure 

consistency between algorithms (Cassens et al. 2003): the median-joining algorithm 

(MJ) implemented in the program Network v. 4.2.0.0 (Bandelt et al. 1999), and 

statistical parsimony algorithm implemented in TCS v. 1.21 (Clement et al. 2000). In 

addition to the network reconstruction, the program TCS also estimates the 

haplotype outgroup probabilities, in order to identify the most-likely ancestral 

haplotype in the network (Clement et al. 2000). Ancestral haplotypes were identified 

by their internal position in the network, by the number of lineages that arise from 

them, and by their occurrence (Castelloe & Templeton 1994). 

As an alternative approach to traditional population genetic methods, a nested-clade 

analysis (NCA, Templeton et al. 1995, Templeton 1998) was also conducted. NCA 

contrasts gene frequency and genealogical data with geographic distance within a 

71


hierarchical nested-clade structure and can be used to infer spatial and temporal 

processes (Templeton et al. 1995, Templeton 1998). First, the set of rules proposed 

by Templeton and Sing (1993) was used to produce a nested series of haplotypes 

and clades, based on the underlying genealogy estimated with TCS. Ambiguities 

(loops or homoplasies) in resulting networks were resolved following methods 

proposed by Crandall and Templeton (1993). NCA was then conducted using the 

program Geodis v.2.5 (Posada et al. 2000), which performs various tests based on 

the clade distance (Dc) and nested-clade distance (Dn) statistics, including the 

randomised Chi-squared test for association between haplotypes/clades and 

geographic sampling locations. 

3.4. Results 

3.4.1. Phylogenetic reconstruction and sequence variation 

A total of 568 sequences of the mtDNA control region were available for the two 

species of pilot whales. A maximum sequence length of 620 bp was available for a 

subset of 261 samples from New Zealand strandings. However, to allow comparison 

to all available sequences (including sequences from GenBank and market samples), 

the length was reduced to a consensus fragment of 345 bp. This consensus fragment 

showed a total of 24 variable sites (Table 3.2); eight sites were variable among longfinned 

pilot whales (six transitions and one 2 bp deletion), while 13 were variable 

among short-finned pilot whales (12 transitions and one transversion). Three sites 

were found to be polymorphic in both species. Six fixed differences were found 

between the two species (five transitions and one transversion). 

Comparison of the consensus length sequence to the maximum length sequence 

(ranging between 345 bp and 620 bp) suggested that the former encompasses most 

of the variable sites. Only two additional variable sites were found in the full-length 

sequence beyond position 345 (one site variable in short-finned and long-finned pilot 

whales, and one fixed difference between the two species); one new haplotype was 

defined for each species using this maximum length (M’ and P’; Table 3.2). This is in 

agreement with the pattern of lower diversity within the central domain of the control 

region that has been observed in some other cetacean species (Hoelzel et al. 1991, 

Dalebout et al. 2004a). 

72


Table 3.2. Variable nucleotide positions (n = 24) within the 345 bp consensus fragment of the mtDNA 

control region of Globicephala spp. used in this study. Additional variable sites (position 359 and 407), 

identified when considering the maximum lengths of sequences (345 to 620bp) are also indicated 

(dashed borders), defining two extra haplotypes: M’ and P’. Dots indicate the site is identical to the top 

sequence (Haplotype A). Positions in grey indicate fixed differences between long-finned pilot whales 

(Globicephala melas) and short-finned pilot whales (G. macrorhynchus). 

Short-finned pilot whale 

Long-finned pilot whale 

4 4 4 4 4 5 6 9 1 1 1 1 1 1 1 2 2 2 2 2 3 3 3 3 3 4 

4 5 6 7 9 4 6 4 0 0 1 4 5 5 9 1 2 2 3 3 2 4 4 4 5 0 

Haplotypes 0 1 7 3 4 5 8 9 4 6 2 3 1 1 2 4 9 7 

Haplo A T A T A A T C C A T C G C C G T C A C C T A C C A T 

Haplo B . . . . G . T . . . . . . . . . . . . . C . . . . . 

Haplo C . . . . . . T . . . . . . . . . . . . . C . . . . . 

Haplo D . . . . . . . . . . . . . . . . . . . . . . T . . . 

Haplo E . . . . . . . . . . . . . . . . . . . T . . . . . . 

Haplo F . . . . . . . . . . . . . . . . . G . T . . . . . . 

Haplo G . . . . . . . . . . . A . . . . . . . . . . . . . . 

Haplo H C . . . . . . . . . . A . . . . . . . . . . . . . . 

Haplo I . . . . . . . . . . . A . . . C . . . . . . . . . . 

Haplo J . . . . . . . . . . T A . . . C . . . . . . . . . . 

Haplo K . . . . . . . . . . . A . T . C . . . . . . . . . . 

Haplo L . . . . . . . . . . T A . T . C . . . . . T . . . . 

Haplo M . . . . . . . . . . . A . T . C . . . . . T . . . . 

Haplo M’ . . . . . . . . . . . A . T . C . . . . . T . . G . 

Haplo N . . . . . . . . . . . A . . . C . . T . . . . . . . 

Haplo O . . C G . C . A - - . A T . A C T . T T C . . T . C 

Haplo P . . C G . C . A . . . A T . A C T . T T C . . T . C 

Haplo P’ . . C G . C . A . . . A T . A C T . T T C . . T G C 

Haplo Q . . C G . C . A . . . A T . A C T . T T C . T T . C 

Haplo R . . C G . C . A . . . A . . A C . . T T C . . T . C 

Haplo S . . C G . C . A . . . A T . A C . . T T C . . T . C 

Haplo T . . C G . C . A . . T A T . A C T . T T C . . T . C 

Haplo U . . C G . C . A . . . A . . A C T . T T C . . T . C 

Haplo V . G C G . C . A . . . A . . A C T . T T C . . T . C 

Haplo W . . C G . C . A . . . A . . A C . . T T C . T T . C 

Haplo X . . C G . C . A . . . A T . A C T G T T C . . T . C 

The variable sites in the 345 bp consensus fragment defined 14 haplotypes in shortfinned 

pilot whales and 10 haplotypes in long-finned pilot whales. Overall, the mtDNA 

haplotype and nucleotide diversity, based on the corrected dataset, were low in both 

species although the latter was substantially higher for short-finned pilot whales (h = 

0.899 +/- 0.013; π = 0.87% +/- 0.51%) than for long-finned pilot whales (h = 0.710 +/- 

73


0.044; π = 0.31% +/- 0.23%). As expected, the levels of diversity were lower when all 

available samples were considered (short-finned: h = 0.871 +/- 0.012 and π = 0.85% 

+/- 0.50%; long-finned: h = 0.428 +/- 0.028 and π = 0.16% +/- 0.15%, Appendix 4). 

All phylogenetic reconstructions confirmed the monophyly of Globicephala spp. 

mtDNA lineages with regards to closely related species (melon-headed and Risso’s 

dolphins), with 70% or more bootstrap support (Figure 3.4). Phylogenetic analyses 

also resolved the long-finned pilot whale species clade with strong support (bootstrap 

support > 89 and posterior probability = 1.00). There was no support for a shortfinned 

pilot whale species clade using ML, MP and BA, suggesting potential 

paraphyly of this species in relation to long-finned pilot whales. However, reciprocal 

monophyly was supported by NJ as well as shared-derived sites. Furthermore, an 

exhaustive search resulted in 258 equally parsimonious MP trees (tree length = 67), 

six of which represented reciprocal monophyly. To investigate further if reciprocal 

monophyly was rejected or simply not strongly supported in the ML framework, a 

Shimodaira-Hasegawa test was conducted (Shimodaira & Hasegawa 1999). I found 

that monophyly of short-finned pilot whale haplotypes was not rejected by the dataset 

(-ln L = 790.84, p = 0.93). 

74


Figure 3.4. Phylogenetic relationships among 10 haplotypes of long-finned pilot whales (Globicephala 

melas) and 14 haplotypes of short-finned pilot whales (G. macrorhynchus), using maximum likelihood. 

Melon-headed and Risso’s dolphins sequences were used as an outgroup. Haplotype frequencies by 

geographic unit (based on the corrected dataset) are indicated to the right of the tree. Numbers above 

branches indicate bootstrap values obtained from neighbour-joining (NJ), maximum parsimony (MP) 

and maximum likelihood (ML), displayed as follows: NJ/MP/ML (values are only indicated for branches 

with bootstrap values of more than 50 for at least one of the three methods). Posterior probability 

support values based on the Bayesian reconstruction are shown below branches. (sf) and (nf) indicate 

the haplotypes identified by Kage (1999) from specimens confirmed as “Southern” form and “Northern” 

form of Japanese short-finned pilot whales, respectively (note that these haplotypes are also 

represented in “whale-meat” market products; see Table 3.1 for details on the frequencies). Samples 

collected at an unknown place around Japan are shown in the column labelled as “?”. 

75


3.4.2. Long-finned pilot whales (Globicephala melas) 

3.4.2.1. Genetic diversity 

The levels of mtDNA diversity were low in each of the three geographic units (New 

Zealand, Tasmania and North Atlantic), although there were substantial differences 

in diversity (Table 3.3). The largest number of haplotypes was found in New Zealand 

(n = 8), although the largest sample size was also from this area. However, the 

highest level of mtDNA diversity, both at the haplotype and nucleotide level, was 

actually found in Tasmania which showed five different haplotypes among four 

sampling events (Table 3.3). Samples from the North Atlantic displayed a lower 

diversity than samples from Tasmania or New Zealand, with only three haplotypes 

from 19 sampling events. As expected, when New Zealand and Tasmania were 

grouped together for comparison between G. m. edwardii (Southern Hemisphere) 

and G. m. melas (North Atlantic), the samples from Southern Hemisphere showed a 

higher level of diversity than the samples from the North Atlantic (Table 3.3). Trends 

in genetic diversity between areas were similar across the full dataset (Appendix 4). 

Table 3.3. Summary of the genetic diversity statistics and neutrality tests for the mtDNA control region 

of long-finned pilot whales (Globicephala melas), based on the corrected dataset. h is the haplotype 

diversity and π is the nucleotide diversity. * represents significant p-values for neutrality tests (p < 

0.05), and ‘# ind. adjusted’ indicates the sample size when considering only one representative of 

each unique haplotype per sampling event. The column for the Southern Hemisphere encompasses 

data from New Zealand and Tasmania. 

New Zealand Tasmania 

Southern 

Hemisphere 

North Atlantic Overall 

# individuals 337 27 364 70 434 

# ind. corrected 40 7 47 19 66 

# sampling events 34 4 38 19 57 

# haplotypes 8 5 9 3 10 

h 0.508 +/- 0.095 0.857 +/- 0.137 0.573 +/- 0.083 0.292 +/- 0.127 0.710 +/- 0.044 

π (%) 0.23 +/- 0.19 0.47 +/- 0.36 0.26 +/- 0.20 0.11 +/- 0.12 0.31 +/- 0.23 

Tajima’s D -1.243 -0.093 -0.915 -0.778 -0.617 

p-value 0.097 0.948 0.206 0.239 0.294 

Fu’s FS -4.402 -2.019 -4.932 -0.725 -4.471 

p-value 0.003* 0.032* 0.005* 0.200 0.011* 

76


3.4.2.2. Phylogeography 

Haplotype distribution, AMOVA and neutrality tests – Of the three haplotypes found 

in the North Atlantic (P, S, and X), two haplotypes (haplotype P and S) were also 

found in the Southern Hemisphere (Figure 3.5). However, the frequencies of the 

haplotypes within these two subsets showed strong phylogeographic patterns. 

Among the North Atlantic specimens, haplotype S was the most common (84% and 

80% of the whales, based on the corrected and full dataset, respectively), while in the 

Southern Hemisphere, haplotype P was the most common (62% and 85% of the 

whales, based on the corrected and full dataset, respectively). The shared 

haplotypes between G. m. melas and G. m. edwardii were thus also the most 

common haplotypes represented in the North Atlantic or Southern Hemisphere. Apart 

from these two common haplotypes, all other haplotypes were only found in five or 

less sampling events within the Southern Hemisphere or North Atlantic sample, 

representing a maximum of 3% of the whales based on the full dataset (Table 3.1, 

Figure 3.4). 

Within the Southern Hemisphere, the distribution of haplotype frequencies showed 

an interesting pattern, although the adjusted sample size was small in Tasmania. 

Based on the corrected dataset, haplotype P was the most common in New Zealand, 

while haplotype Q was the most common in Tasmania, where it was identified in 

three of the four sampling events from this area. Also, haplotype W was unique to 

Tasmania, and not found in New Zealand despite a large sample size. Note that 

when considering the full dataset, haplotype P became the most common haplotype 

found in the Tasmanian samples (n = 15, but all these samples originate from a 

single mass stranding). 

As expected from this haplotype distribution, the AMOVA showed strong population 

genetic structure, both at the haplotype and nucleotide level (FST = 0.468, p < 0.001; 

ΦST = 0.420, p < 0.001). Similar results were obtained with the full dataset (Appendix 

4). Pairwise comparisons confirmed that all three geographic units were significantly 

different from one another (Table 3.4). Overall genetic differentiation was mainly 

driven by the North Atlantic samples. All units showed negative Tajima’s D values, 

although none were significant. Fu’s FS values were significantly negative for New 

77


Zealand and Tasmania but not for the North Atlantic. When grouping New Zealand 

and Tasmania, FS was also significant, while D was negative but not significantly 

(Table 3.3). 

Table 3.4. Analysis of genetic differentiation between subsets of long-finned pilot whales 

(Globicephala melas) samples. FST values are given below diagonal and ΦST values are given above 

diagonal. p < 0.001, ***; p < 0.01, **; p < 0.05, *; p > 0.05, ns . 

New Zealand 

N = 40 

Tasmania 

n = 7 

North Atlantic 

n = 19 

New Zealand 0.264* 0.472*** 

Tasmania 0.265* 0.521*** 

North Atlantic 0.533*** 0.502*** 

Network reconstruction - The two methods of network reconstruction recovered a 

similar relationship between long-finned pilot whale haplotypes (Figure 3.5). There 

was no inference of a missing ancestral haplotype and no more than one mutational 

step between closest haplotypes. One loop was inferred in the network, but it was 

unambiguously resolved following Crandall & Templeton’s rules (1993). The 

algorithm implemented in TCS designated haplotype P as the ancestral haplotype. 

This designation was consistent whether or not the sequences were collapsed into 

unique haplotypes (i.e., ignoring frequencies). However, haplotype R was the most 

closely related to G. macrorhynchus haplotypes suggesting that it could be the most 

ancestral (Figure 3.5). The low level of haplotype diversity resulted in only one 

nested level in the network, limiting the power of a NCA. However, the nested 

contingency analysis showed a significant relationship among the spatial distribution 

of haplotypes for clade 1-3, indicating a continuous range expansion (Figure 3.5). 

This clade included haplotypes from all three regions and both ocean basins 

considered here, including all G. m. melas haplotypes. 

78


Figure 3.5. Inferred genealogical relationships, recovered by median-joining and statistical parsimony 

algorithms, and nested cladograms among long-finned pilot whale (Globicephala melas) haplotypes. 

The size of each circle or square is proportional to the number of individuals found with the haplotype 

based on ‘adjusted’ frequencies. Length of the branches is proportional to the number of inferred 

mutational steps that they represent. Numbers give the positions of the mutations across the 345 bp 

consensus fragment investigated here. The haplotype represented by a square indicates the ancestral 

haplotype as inferred by TCS. 

79


3.4.3. Short-finned pilot whales (Globicephala macrorhynchus) 

3.4.3.1. Genetic diversity 

In comparison to the long-finned pilot whale, short-finned pilot whales showed a more 

complex pattern of genetic diversity and phylogeography. The levels of genetic 

diversity within geographic units were relatively low although there were substantial 

differences from one area to another (Table 3.5, Appendix 4). The lowest level of 

diversity was found in the Atlantic sequences (although sample size from this area 

was also small). In the South Pacific, the level of diversity was higher, although only 

three haplotypes were identified from nine sampling events. The highest level of 

diversity was found in Japan/Korea, at both the haplotype and nucleotide level (Table 

3.5). A total of 11 haplotypes were identified from these samples, nine of which were 

unique to the region. Indices of diversity were also calculated considering the ‘North 

Japan’ and ‘South Japan’ sub-units, as described in the section 3.3.5 (Table 3.5). 

The samples purchased in prefectures of ‘North Japan’ (π = 0.43%) showed less 

diversity than samples purchased in ‘South Japan’ (π = 0.74%; Table 3.5). 

Table 3.5. Genetic diversity statistics and neutrality test for the mtDNA control region of short-finned 

pilot whales (G. macrorhynchus) based on the corrected dataset. See legend of Table 3.3 for details. 

Note that overall calculations for short-finned pilot whales comprised two additional samples from the 

eastern North Pacific. 

Atlantic 

South 

Pacific 

Japan/Korea 

‘North 

Japan’ 

‘South 

Japan’ 

Overall 

# individuals 12 35 85 11 71 134 

# ind. corrected 9 14 58 8 47 83 

# sampling events 9 9 54 7 43 72 

# haplotypes 2 3 11 3 9 14 

h 

0.222 +/- 

0.166 

0.604 +/- 

0.076 

0.873 +/- 

0.022 

0.464 +/- 

0.200 

0.852 +/- 

0.026 

0.899 +/- 

0.013 

π (%) 0.06 +/- 0.09 0.35 +/- 0.27 0.82 +/- 0.49 0.43 +/- 0.33 0.74 +/- 0.45 0.87 +/- 0.51 

Tajima’s D -1.088 0.897 0.537 -1,64 0.721 0.428 

p-value 0.192 0.807 0.753 0.026* 0.789 0.733 

Fu’s F -0.263 1.293 -0.926 0.971 -0,359 -1.824 

p-value 0.176 0.811 0.383 0.721 0.481 0.302 

80


3.4.3.2. Phylogeography 

Haplotype distribution, AMOVA and neutrality tests – The distribution of haplotype 

frequencies differed considerably among geographic units (Figure 3.4, Figure 3.6). 

While South Pacific samples possessed mainly haplotypes A and C (49% of all 

individuals, Figure 3.6), samples from the Atlantic showed mainly haplotype D (92%). 

Most of the products purchased in ‘South Japan’ carried haplotypes not found 

anywhere else (seven unique haplotypes out of nine found in total, Figure 3.4). The 

exception was a substantial number of products carrying haplotype C (n = 8), also 

found in the South Pacific. In addition to haplotype C, two other haplotypes were 

identified in more than one area. These were shared between: South Pacific, eastern 

North Pacific and Atlantic (haplotype A); and eastern North Pacific and ‘North Japan’ 

(haplotype E). 

As mentioned in the methods, the AMOVA for short-finned pilot whales was 

conducted by segregation of samples for ‘North Japan’, ‘South Japan’, Atlantic and 

South Pacific. This analysis showed strong population genetic structure, at both the 

haplotype and nucleotide levels (FST = 0.319, p < 0.001; ΦST = 0.471, p < 0.001). 

Pairwise comparisons confirmed that all regions were significantly different from one 

another (Table 3.6). None of the D values of Tajima (1989b) or the FS values of Fu 

(1997) were significantly different from expectation, apart from the ‘North Japan’ D 

value which was significantly negative. 

Table 3.6. Analysis of genetic differentiation between subsets of short-finned pilot whales (G. 

macrorhynchus) samples. FST values are given below diagonal and ΦST values are given above 

diagonal. p < 0.001, ***; p < 0.01, **; p < 0.05, *; p > 0.05, ns . 

South 

Pacific 

n = 14 

North 

Japan 

n = 8 

South 

Japan 

n = 47 

Atlantic 

n = 9 

South Pacific 0.481*** 0.426*** 0.592*** 

North Japan 0.454*** 0.413*** 0.653*** 

South Japan 0.194*** 0.264*** 0.506*** 

Atlantic 0.533*** 0.663*** 0.364*** 

81


Network reconstruction - Similar haplotype networks were inferred by the medianjoining 

and statistical parsimony algorithms, revealing an interesting phylogeographic 

pattern (Figure 3.6). After following the usual rules of haplotype nesting (Templeton & 

Sing 1993), two main clusters of haplotypes were found: clade 2-1 and clade 2-2. 

Clade 2-1 included all the samples from the South Pacific, Atlantic, eastern North 

Pacific (Figure 3.6). It also included all the products or samples from ‘North Japan’, 

except one product purchased in Miyagi and representing haplotype M. Clade 2-2, at 

the other end of the network, contained only samples collected in ‘South Japan’, 

except for the one sample collected at Miyagi (‘North Japan’). Only one haplotype 

identified in samples from ‘South Japan’ was represented in clade 2-1 (haplotype C). 

The nesting rules resulted in the clustering of haplotypes I, J, K, L, M and N into the 

clade 2-2, but haplotypes G and H remained in the clade 1-6. This clade was 

equidistant to its nesting alternatives (clade 2-1 and clade 2-2) which had almost 

equal sample sizes (40 and 39, respectively). Therefore, Templeton and Sing’s 

(1993) set of rules were theoretically not applicable to this particular case. However, 

considering the phylogeographic pattern of the network, clade 1-6 was included with 

clade 2-2 (both clades comprising only samples from Japan/Korea). 

Japanese “Northern” and “Southern” forms – In his PhD thesis, Kage (1999) 

identified one haplotype among the “Northern” form (haplotype E) and four 

haplotypes among the “Southern” form (haplotypes I, J, K and M). This is largely 

consistent with information from the market samples. Indeed, all market samples 

possessing haplotype E were purchased in ‘North Japan’, while all but one of the 

samples possessing haplotypes I, J, K or M were purchased in ‘South Japan’. 

However, six haplotypes identified among market products were not reported in Kage 

(1999). One was from a sample collected in ‘North Japan’ (haplotype F). This 

haplotype was only one base-pair different from the haplotype represented by the 

“Northern form” of Kage (haplotype E). Four haplotypes (haplotype G, H, L and N) 

were found at low frequencies from samples collected in markets from ‘South Japan’. 

These haplotypes were no more than one or two base-pairs different from at least 

one of the haplotypes found in the “Southern” form” by Kage (Figure 3.6). Finally, the 

last and most interesting haplotype of these six haplotypes not reported in Kage 

(1999) was haplotype C (n = 8, 17% of the market products from ‘South Japan’), also 

82


mentioned above. This haplotype was found at a relatively high frequency among 

market products purchased in the prefectures of Okinawa and Wakayama (‘South 

Japan’). They were also common in samples from the South Pacific. There were 

three mutational steps between haplotype C and the next most closely related 

haplotypes found among market samples (haplotypes E and G). 

The exact root probabilities calculated by TCS indicated haplotype K as an ancestral 

haplotype in the network (Figure 3.6). However, this method is sensitive to the 

relative proportion of the haplotypes, and after collapsing sequences into one 

representative for each unique haplotypes, the inferred ancestral haplotype was 

found to be haplotype I. Note also that haplotype N was found to be the root to longfinned 

pilot whale haplotypes, making it another potential candidate for the ancestral 

haplotype. Therefore, inference of the ancestral haplotype must be interpreted with 

caution. The uncertainty linked to the origin and relationships among 

Japanese/Korean samples prevented a NCA for the short-finned pilot whales. 

83


Figure 3.6. Inferred genealogical relationships recovered by median-joining and statistical parsimony 

algorithms, and nested cladograms among short-finned pilot whale (Globicephala macrorhynchus) 

haplotypes. (sf) and (nf) indicate the haplotypes identified by Kage (1999) from specimens confirmed 

as “Southern” form and “Northern” form of Japanese short-finned pilot whales, respectively. See 

legend of Figure 3.5 for details. 

84



3.5.1. Pilot whale species and sub-species 

The examination of inter-species and intra-species mtDNA variation, based on largescale 

population sampling, confirmed that the two recognised species of pilot whales 

can be distinguished by several fixed nucleotide differences. However, divergence 

between the species was low and reciprocal monophyly of the mtDNA control region 

was not well supported (although not conclusively rejected). 

Such a phylogenetic pattern is not uncommon in delphinids with many uncertainties 

existing in the genera Stenella, Tursiops and Delphinus (Reeves et al. 2004). Several 

explanations of this pattern are possible, such as inadequate phylogenetic 

information, for example, a mutation rate too slow relative to the rate of speciation, or 

not enough information in the gene marker per se (Funk & Omland 2003). Incomplete 

lineage sorting is also a common source of paraphyly, although it is generally less of 

a problem for mitochondrial markers compared with nuclear genes (Funk & Omland 

2003). However, considering that some of the potential reasons behind low mtDNA 

diversity in pilot whales involve selective processes, such as cultural hitchhiking 

(Whitehead 1998), it would be interesting to further investigate the phylogeny of 

these two species using the whole mitochondrial genome and nuclear markers. 

The control region of the two Globicephala species differed from each other by 3.7% 

(or 2.9% after adjustment for within species diversity). Within the family Delphinidae, 

such a level of divergence appears to be comparatively low, illustrating a relatively 

recent divergence. It is lower than the level of divergence between Lagenorhynchus 

species (5.17 - 13.02%, Cipriano 1997) but higher than that observed between 

Delphinus delphis and D. capiensis in the Pacific (1.11%, Rosel et al. 1994). It can be 

compared to the levels found in allopatric groups with recent radiations such as the 

Cephalorhynchus species (2.5 - 4.0%, Pichler et al. 2001). Within the 

Cephalorhynchus genus, Pichler et al. (2001) found good support for the monophyly 

of the four species, based on 442 bp of the mtDNA control region. 

85


3.5.2. Long-finned pilot whale phylogeography 

3.5.2.1. Recent history of anti-tropical distribution 

Anti-tropical distribution patterns with sister species being distributed on one side or 

the other of the warm tropical belt around the equator are relatively common among 

cetaceans (Davis 1963). However, the long-finned pilot whale represents a special 

case among the Odontocetes. It is the only recognised species that is anti-tropically 

distributed in temperate waters in both hemispheres*. In all other cases, antitropicality 

refers to closely related species distributed in one hemisphere or the other. 

Comparison of morphological characters shows few differences between the two 

populations of long-finned pilot whales, which led taxonomists to consider them 

separate only at the sub-species level (Davis 1960). Here, the comparisons of 

mtDNA genetic structure between specimens from both hemispheres are consistent 

with the morphological similarity and assumed recent evolutionary history of these 

populations, confirming that historical species-level ranking was inappropriate. In 

fact, the sharing of two out of the three haplotypes from the North Atlantic (G. melas 

melas) with haplotypes from the Southern hemisphere (G. m. edwardii) fails to 

support the sub-species status currently recognized. Only the apparent allopatry of 

the two populations supports this ranking. In the absence of any supporting evidence 

(such as morphological and genetic data), geographic distribution alone is 

considered insufficient for sub-species ranking in cetaceans (Reeves et al. 2004). 

However, haplotype frequencies between the two populations of long-finned pilot 

whales were very different, suggesting strong restrictions on current gene flow. Two 

alternative hypotheses have been proposed to explain anti-tropical cetacean 

distributions: the equatorial transgression and subsequent isolation hypothesis (Davis 

1963), and the vicariance hypothesis, which assumes that anti-tropical organisms 

abandoned low latitudes in response to a warming event (White 1986). Hare et al. 

(2002) suggested vicariant isolation as being responsible for the anti-tropical 

distribution of Lagenorhynchus obliquidens and L. obscurus based on a history of 

large population sizes for both species (no evidence of a bottleneck effect). In the 

*This could also be the case for the true beaked whale (Mesoplodon mirus), but data on this 

species are scarcer (Dalebout et al. in press). 

86


long-finned pilot whale, the level of mtDNA genetic diversity in the North Atlantic was 

already known to be very low (Siemann 1994), and one of the proposed scenarios to 

explain this unusual level of diversity was that the North Atlantic population originated 

from a colonisation event by the Southern population(s) (Fullard 2000). Although this 

was consistent with the higher level of mtDNA diversity found in the Southern 

Hemisphere, any conclusion at this stage would be premature. Indeed, despite being 

relatively higher, mtDNA diversity in the South Pacific was also low, and there was no 

clear evidence of a bottleneck event for the North Atlantic based on the results of 

Tajima’s D test and Fu’s FS test. Additional genetic markers and samples from the 

South Atlantic should be investigated to clarify this point. 

3.5.2.2. Population structure in the Southern Hemisphere 

Population structure of the long-finned pilot whale in the North Atlantic has been 

investigated by Fullard et al. (2000) based on microsatellite loci. For these nuclear 

loci, FST was low but significant between the Faroe Islands, West Greenland and 

Cape Cod, the average distance between these areas being 3197 km. However, 

population structure in the North Atlantic seems to be influenced by sea temperatures 

rather than isolation-by-distance (Fullard et al. 2000). This indicates that although 

long-finned pilot whales are nomadic and known to travel relatively long distances 

(Mate et al. 2005), barriers are maintained between populations. Here, analyses of 

mtDNA diversity indicated that population structure also exists in the Southern 

distribution of this species at a scale even finer than that reported in the North 

Atlantic: a significant difference between the samples from New Zealand and 

Tasmania was found, with these areas only being about 1200 km apart. Interestingly, 

one haplotype identified in Tasmania (n = 27) could not be found in New Zealand (n 

= 337). At this stage, it is difficult to say if sea temperature is also an important factor 

driving population structure in the Southern Hemisphere, but it is a likely scenario 

and examination of a larger sample size, as well as other genetic markers, should 

allow this prediction to be tested. 

3.5.2.3. Recent worldwide expansion 

The star-like haplotype network and low levels of sequence divergence in long-finned 

pilot whales is similar to the pattern observed in coconut-crabs (Lavery et al. 1996), 

and suggests a recent worldwide population expansion. This conclusion was further 

87


supported by negative Fu’s FS values and the result of the NCA for the main clade 

(clade 1-3; Figure 3.5). On the other hand, there was little evidence of a bottleneck, 

apart from the low level of haplotype diversity. Unlike to killer whales, for which a 

bottleneck has been suggested (Hoelzel et al. 2002b), there were no missing sister 

haplotypes in the network reconstruction and almost no variation which could be 

considered ancestral, in the central ‘conserved’ domain of the control region. 

Further, phylogenetic comparisons suggest that the long-finned pilot whale does not 

have a slower mtDNA control region substitution rate than other species of dolphins 

(Alexander 2006). Such a network of low worldwide haplotype diversity could thus be 

the sign of a recent evolutionary origin or population expansion. However, the 

influence of matrilineal social organisation on mtDNA diversity is still debated and the 

influence of selective processes such as cultural hitchhiking could interfere in an 

unknown way on the genetic characteristics of this species. 

3.5.3. Short-finned pilot whales phylogeography 

3.5.3.1. How many populations in the Japanese waters? 

The pattern of mtDNA diversity in short-finned pilot whales was complex and 

obscured by the uncertainty about the two distinct forms present in the waters around 

Japan. While no information was available on the form of pilot whales from which 

“whale-meat” market samples originate, a clear phylogeographic pattern was found 

by combining data from Kage (1999) and the location of the prefectures where the 

market products were purchased. These data strongly suggest that the haplotypes of 

the clade 2-2 (haplotype I, J, K, L, M and N; Figure 3.6) were represented by 

individuals of the “Southern” form. The only exception was one sample possessing 

haplotype M obtained in a prefecture classified as ‘North Japan’ (prefecture of 

Miyagi). However, this is not inconsistent with the seasonally overlapping 

distributions of the two forms (Kasuya et al. 1988); therefore, it is possible that an 

individual of the “Southern” form was hunted on the coast of Miyagi. 

More puzzling was the substantial number of samples possessing haplotype C and 

collected only in the ‘South Japan’ (prefectures of Wakayama and Okinawa), where 

there are no reports of the “Northern” form of pilot whale, regardless of the season 

88


(Kasuya et al. 1988). Indeed, while the locations of purchase strongly argued that 

these samples belonged to the “Southern” form, genetic data suggests that they 

could originate from a distinct population more closely related to the population(s) of 

the South Pacific (which also showed a high frequency of haplotype C). Haplotype C 

was also the only haplotype found in high frequency in market products but not 

represented in Kage’s (1999) samples of the “Southern” form. Finally, this haplotype 

was four mutational steps distant from the closest haplotype confirmed as coming 

from a “Southern” form by Kage (1999), that is, haplotype I. Therefore, together these 

results support Kasuya et al’s (1988) hypothesis of a ‘third stock’ of short-finned pilot 

whales in the southern waters of Japan. As supporting evidence for this, Kasuya et al 

(1988) noticed a density hiatus in the distribution of pilot whales between coastal 

area and offshore Kuroshio Current area. However, field studies are still needed to 

confirm existence of this ‘third stock’. 

An alternative explanation for the C haplotype on the market is that the products 

originated from outside Japanese coastal waters. Such exploitation would potentially 

represent a violation of the CITES (Convention on International Trade in Endangered 

Species), similar to that already suggested in Japan/Korea for other species of 

cetaceans (Baker & Palumbi 1994, Baker et al. 2000, Dalebout et al. 2005). Note that 

in the South Pacific where haplotype C is frequently represented, haplotype A is also 

equally represented (49% of the individuals each). Therefore, it is puzzling to find 

representatives of haplotype C among the “whale-meat” market products but no 

representatives of haplotype A. This suggests that the market product 

representatives of haplotype C came from a population genetically distinct from the 

‘South Pacific’ population described here (i.e., with equal proportions of haplotype A 

and C representatives). 

Smaller numbers of samples were collected from the markets of ‘North Japan’ but 

they also showed a fairly clear phylogeographic pattern, consistent with the 

information from Kage (1999), who identified haplotype E from his samples of the 

“Northern” form. The high frequency of this haplotype in market samples from ‘North 

Japan’ and no occurrence in ‘South Japan’ suggest that it is a haplotype specific to 

the “Northern” form. Given this information, and considering its genetic relationship to 

haplotype E, it is also likely that haplotype F belongs to the “Northern” form of the 

89

short-finned pilot whale (Figure 3.6). 


Although uncertainties remain about the exact origin of the market samples, the 

patterns described here strongly suggest that: (1) the “Southern” form was 

represented by the clade 2-2, (2) the “Northern” form was represented by the clade 

1-2, and (3) the market products carrying haplotype C represented specimens of a 

third population from around Japan or an importation from outside Japanese coastal 

waters (Figure 3.6). 

3.5.3.2. Origin of the “Northern” form 

Low levels of mtDNA diversity were found in the ‘North Japan’ samples, in 

comparison to those from ‘South Japan’, which probably illustrates a true difference 

between the “Northern” and “Southern” forms. Population size of the “Southern” form 

is thought to be larger than the population of the “Northern” form (estimated at 20,300 

and 5,000 individuals respectively, Kasuya 2007). This is consistent with a lower 

level of genetic diversity within the latter. However, there is no reliable information on 

the demographic and genetic boundaries of the “Northern” form population. 

Therefore, the observed level of genetic diversity could illustrate current demography 

as well as recent evolutionary history. Note that the “Northern” form is the only 

population of short-finned pilot whale currently considered at risk by the IUCN (The 

World Conservation Union). 

As mentioned earlier, a larger form of the short-finned pilot whale also exists in the 

eastern North Pacific (Polisini 1980). Unfortunately, little information from this region 

was available to infer relatedness with the Japanese samples. It is worth noting, 

however, that from the two sequences available (Siemann 1994), one was haplotype 

E, that is the haplotype thought to be specific to the larger “Northern” form of the 

Japanese short-finned pilot whale. Further genetic investigation of eastern North 

Pacific samples are needed to clarify the relationship with the “Northern” form of 

Japan. However, this result suggests recent gene flow between these two regions. 

Uncertainty remains on the origin of northern population(s) of short-finned pilot 

whales from the North Pacific. However, available evidence suggests that the 

“Northern” form of short-finned pilot whales around Japan are more closely related to 

90


the population found in the South Pacific than the “Southern” form of Japan. Indeed, 

the closest haplotype in proximity clade 1-2 (presumably representing the “Northern” 

form; Figure 3.6) is haplotype A, which is commonly found in the South Pacific (and 

also in the eastern North Pacific and Atlantic) but is apparently absent around Japan. 

3.5.3.3. Origin of the “Southern form” 

While it is unclear if the distribution of the “Northern” form extends further east in the 

Pacific, it seems that the “Southern” form is confined to the waters surrounding 

Japan. This is illustrated by the numerous haplotypes apparently unique to ‘South 

Japan’, while haplotypes of the other regions are shared across oceans and 

hemispheres. The genetic isolation observed here raises new concerns about the 

conservation status of the “Southern” form of Japanese short-finned pilot whales; this 

population is still an important target of small coastal whaling stations and drive-kill 

fisheries, and several hundred individuals are caught annually (Kasuya 2007). To 

date there is no model to evaluate if the current annual takes are sustainable in the 

long-term. This is now further complicated by the potential existence of a third 

population of short-finned pilot whales around Japan (Section 3.5.3.1). Indeed, if 

such population has been confused with the real “Southern” form, it could have 

biased previous census estimates, leading to an over-estimate of population size of 

the “Southern form”. 

Dall’s porpoises (Phocoenoides dalli) also exist in different geographic forms around 

Japan. As in the “Southern” form of short-finned pilot whales, one of these forms, the 

Sea of Japan-Okhotsk dalli-type, shows a distribution restricted to the coast of the 

country (although in this case it is the north-east coast), providing an interesting 

parallel between the two species. Hayano et al. (2003) suggested that the Sea of 

Japan-Okhotsk dalli-type could have originated from a small founding population that 

colonized the Sea of Japan during an interglacial period in the Late Pleistocene, or 

that this population underwent a size reduction when this Sea was isolated from the 

North Pacific in the last glacial period. A similar scenario was also proposed for the 

Pacific white-sided dolphin (Lagenorhynchus obliquidens) off the coast of Japan, 

which appears to have restricted gene flow with offshore population(s) of the North 

Atlantic (Hayano et al. 2004). 

91


It is possible that the “Southern” form of Japanese short-finned pilot whales went 

through a similar evolutionary history to that of the Dall’s porpoise and Pacific whitesided 

dolphin, which would explain why the population is restricted to the coast of 

Japan. However, one major difference was found when comparing Japanese shortfinned 

pilot whales to these two species. The populations of Dall’s porpoise and 

Pacific white-sided dolphin thought to originate from the Sea of Japan, have a lower 

level of mtDNA diversity than other populations of the same species in the North 

Pacific, which is an indication of a potential founder event or bottleneck effect* 

(Hayano et al. 2003, Hayano et al. 2004). In short-finned pilot whales, the opposite 

pattern was found, with a higher diversity in the “Southern” form of pilot whales than 

in any other region around the world. 

In fact, several lines of evidence suggest that the “Southern” form could represent the 

ancestral population of the short-finned pilot whale (and potentially all Globicephala if 

the paraphyly as described previously was confirmed). Firstly, this is supported by a 

higher level of mtDNA diversity than anywhere else in the world; secondly, the 

ancestral haplotypes inferred by the program TCS (haplotype K or I) were identified 

among specimens of the “Southern” form (Kage 1999); finally, phylogenetic and 

network reconstructions showed that the short-finned pilot whale haplotype most 

closely related to the long-finned pilot whale haplotypes is presumably a haplotype of 

the “Southern” form (haplotype N). Therefore, these results suggest that a different 

scenario must explain the current phylogeography of short-finned pilot whales in 

comparison to Dall’s porpoises and Pacific white-sided dolphins. 

3.5.3.4. Worldwide phylogeography of short-finned pilot whales 

Although the short-finned pilot whale shows more diversity than the long-finned pilot 

whale (which is mostly explained by short-finned samples from ‘South Japan’), the 

overall mitochondrial variability observed remains relatively low in comparison to 

other species of dolphins with wide distributions, such as spinner dolphins (Chapter 

2). As with the long-finned pilot whale, no obvious signature supporting a recent 

genetic bottleneck was found in the populations of short-finned pilot whales, aside 

* It must be noted that short-finned pilot whales seem to be uncommon in the Sea of Japan and 

that there are no data to indicate which forms are distributed there (Kasuya et al. 1988). 

92


from the low mtDNA diversity. Contrary to the long-finned pilot whale, however, the 

haplotype network does not seem to support a recent worldwide demographic 

expansion. Thus, the low level of worldwide mtDNA diversity in short-finned pilot 

whales remains open to alternative scenarios such as cultural hitchhiking (Whitehead 

1998, 2005). 

93

Chapter four: Kinship in long-finned pilot whale mass strandings 

4. Patterns of kinship and mtDNA lineage within 

mass strandings of long-finned pilot whales 

around New Zealand 

Mass stranding of long-finned pilot whales at Stewart Island, New Zealand in 2000. Photo courtesy of 

Helen Kettles, Department of Conservation. 

94

4.1. Abstract 


Microsatellite genetic studies of kinship in the North Atlantic suggested that both male 

and female long-finned pilot whales (Globicephala melas) present some degree of 

natal group philopatry, a pattern so far observed in only one other mammalian 

species, the killer whale. While this is generally accepted, it remains unclear if groups 

of long-finned pilot whales at sea are strictly composed of maternally related 

individuals (i.e., representing extended matrilineal units) or if they are sometimes 

composed of several unrelated matrilineal units. The frequent mass strandings of this 

largely pelagic species and the use of maternally and bi-parentally inherited genetic 

markers offer the opportunity to address this question in more detail. Here, genetic 

variability within mtDNA control region sequences (365 bp) and 14 microsatellite loci 

genotypes was investigated within and between seven mass strandings (nTOT = 275) 

from around New Zealand. Analysis of mtDNA variation discounted the scenario of a 

strictly matrilineal social structure of stranded groups. Representatives of different 

mtDNA haplotypes were found within the same mass stranding in five of the seven 

strandings examined. The presence of multiple maternal lineages is consistent with a 

photo-identification study on long-finned pilot whales in Nova Scotia showing fluidity 

in group composition, but is in contradiction with previous microsatellite genetic 

studies on long-finned pilot whales caught in drive-fisheries in the Faroe Islands. This 

could be explained by different social systems between studied areas, however, 

kinship analyses based on microsatellite loci suggest similarities in the genetic 

pattern from mass strandings in New Zealand and the Faroe Islands groups. Notably, 

parentage inference confirms that at least some mature males and females remain in 

their natal group. These results show that the long-finned pilot whale matrilineal 

social system has both similarities and differences to ‘resident’ killer whales of the 

eastern North Pacific and sperm whales. 

95



Kinship is thought to play an important role in the evolution of social systems and 

group living, in part through the benefits of inclusive fitness (Hamilton 1964a, b). So 

far our understanding of the influence of kinship in group formation primarily benefits 

from the studies on terrestrial species, primates in particular. Less attention has been 

devoted toward cetaceans, as their aquatic environment and high dispersal ability 

make them difficult to study for such a topic. However, most species of odontocetes 

(or toothed whales; i.e., dolphins, sperm whales, porpoises and beaked whales) are 

known for their gregarious behaviour, and an increasing number of studies are 

revealing the complexity and diversity of their social systems (Connor et al. 1998, 

Connor 2007). 

One of the most fascinating patterns of group living so far described for mammals is 

found in two species of delphinid: the killer whale (Orcinus orca) and long-finned pilot 

whale (Globicephala melas). Amongst ‘resident’ populations of killer whales off the 

British Columbia and Washington State, long-term photo-identification surveys 

showed that adult males and females remain in close social contact with their mother, 

presumably for life (e.g., Bigg et al. 1990). Amongst mammals, this social system 

represents the best-documented case of natal group philopatry for both sexes (in the 

case of cetaceans, which do not show any territoriality, natal philopatry must be 

interpreted as the absence of social dispersal from the natal group). 

Less direct evidence also suggests natal group fidelity for both sexes in long-finned 

pilot whales. Unlike the killer whales described above, they live in social groups that 

can range from a few individuals to several hundred (see Ottensmeyer 2001 for a 

review of average group size). They are also thought to be nomadic and pelagic. 

Perhaps the most notable characteristic of long-finned pilot whales’ natural history is 

their high propensity to mass strand, much higher than any other species of 

cetacean. Although the reasons behind mass stranding remain unknown, strong 

social bonds within groups are thought to be an important factor (Perrin & Geraci 

2002). 

96


Although long-finned pilot whales are distributed in two distinct areas located in the 

North Atlantic and the Southern Hemisphere (Figure 3.2), they have been studied 

primarily in the North Atlantic. To date, genetic analyses have focused mainly on 

samples from traditional drive-kill fisheries in the Faroe Islands, where entire groups 

of whales (called “grinds” by the Faroese) are herded and driven to the shore before 

being killed for their meat (Bloch et al. 1993). Analyses of nuclear DNA ‘fingerprints’ 

suggested that long-finned pilot whales have a matrilineal social structure, where 

individuals of both sexes remain with their maternal group (Amos et al. 1991). This 

was further supported by pedigree inference from extensive microsatellite analyses, 

which showed that the groups contain multigenerational sets of maternally related 

males and females, and that mating between maternally related individuals is rare or 

non-existent (Amos et al. 1993, Fullard 2000). 

While these analyses provide compelling evidence for some degree of natal 

philopatry in both sexes, the overall social structure of long-finned pilot whale groups 

remains controversial. Indeed, two opposing scenarios of group structure have been 

proposed, based on different methodologies; here, they were called the “extended 

matrilineal group” scenario and the “unrelated matrilineal group” scenario (Figure 

4.1). In the “extended matrilineal group” scenario, groups are thought to be strictly 

composed of individuals originating from the same ancestral female. This scenario is 

based on various analyses of genetic relatedness on samples from the Faroese’s 

drive-kill fisheries (Andersen 1988, Amos et al. 1993, Fullard 2000). It suggests that 

groups observed at sea (that sometimes comprise more than 100 individuals) 

represent persistent behavioural units, somewhat similar to the “pods” described for 

‘resident’ killer whales of the eastern North Pacific (members of which spend more 

than 50% of their time together, Bigg et al. 1990). This scenario also found some 

support in results from studies using alternative data such as metal traces and 

pollutant concentration, which showed significant differences between some of the 

groups investigated (Aguilar et al. 1993, Caurant et al. 1993). In the alternate 

scenario of “unrelated matrilineal group”, large groups of long-finned pilot whales are 

thought to represent temporary social units composed of smaller, stable entities of 

approximately 11-12 individuals, which represent the real matrilineal groups 

(Ottensmeyer & Whitehead 2003). This scenario was derived from a behavioural 

97


study in Nova Scotia, which investigated patterns of association in groups of longfinned 

pilot whales using photo-identification information (Ottensmeyer & Whitehead 

2003). 

Figure 4.1. Alternative scenarios of the social system of long-finned pilot whales based on previous 

genetic and behavioural studies, and genetic expectation deduced from these scenarios. 

One of the limitations of previously published genetic analyses is that cross-sectional 

data can only offer a limited view of the true dynamics of social groups (Ottensmeyer 

98


& Whitehead 2003). Another limitation of this work, that has not been raised 

previously, is the absence of mitochondrial DNA (mtDNA) analysis to complement biparental 

(i.e., nuclear) markers. Indeed, the clonal and strictly maternal inheritance of 

mtDNA in mammals provides the perfect candidate to trace maternal lineages within 

social groups (e.g., Avise 2004). Among cetaceans, it has been widely used to 

address these issues in other species thought to have matrilineal social structure, 

notably in sperm whales and killer whales (e.g., Richards et al. 1996, Barrett-Lennard 

2000). 

Here I report the first study of long-finned pilot whales social system from the 

Southern Hemisphere, based on genetic analyses of mass strandings from around 

New Zealand. Firstly, the distribution of distinct maternal lineages within and between 

mass strandings was investigated using mtDNA control region sequences in order to 

test the prediction stated in Figure 4.1; under the hypothesis of “extended matrilineal 

group”, only one mtDNA haplotype should be found per mass stranding, while under 

“unrelated matrilineal group”, some groups, at least, should have more than one 

haplotype. Relatedness estimates, based on microsatellite loci polymorphism, were 

used to support mtDNA results by testing the prediction that a shared mtDNA 

haplotype within mass strandings should reflect higher level of kinship. Additional 

relatedness and parentage analyses were also conducted to allow comparison with 

previous studies of long-finned pilot whales from North Atlantic. This comparison was 

performed to investigate if a higher level of microsatellite relatedness than expected 

by chance was found within the groups (mass strandings in this case), and if 

parentage inferences supported some level of philopatry to the maternal group in 

adult long-finned pilot whales of both sexes. For parentage analyses, the principal 

expectation within groups was to find first-order relatives for mature females amongst 

every class of individual (males and female, mature and immature), and to find firstorder 

relatives of mature males only amongst mature females (supposedly their 

mother). Considering that mass strandings should be seen as an “unusual” event in 

the life of pilot whales, the ability of such a dataset to provide information on social 

systems is discussed, as well as the implications of the results in terms of mass 

stranding social dynamics. 

99


Several terms have been used in the literature to refer to an aggregation of longfinned 

pilot whales, and in particular the term “pod” (e.g., Amos et al. 1991). 

However, and as mentioned above, “pods” were initially defined as long-term stable 

entities as observed in killer whales (Bigg et al. 1990). Therefore, in this chapter (and 

elsewhere in the thesis), I preferred to use the term “group” for long-finned pilot 

whales, which I think is more general than the term “pod”; indeed, many uncertainties 

remain on the social system of this species and drawing a parallel with killer whale 

“pods” would be premature at this stage. A distinction was also made between 

“matrilineal group” and “maternal lineage”. A “matrilineal group” refers to a social 

group of individuals related by mother-offspring bonds, which originated no more than 

a few generations ago and that represents the basis of the matrilineal social system. 

A “maternal lineage” refers to individuals sharing the same mtDNA haplotype, which 

can reflect relationships across hundreds or thousands of generations (depending on 

mutation rates). Thus, although members of a “matrilineal grou”p must also share a 

“maternal lineage”, not all individuals of a given lineage are close relatives. 


4.3.1. Data collection 

Skin samples were collected from 275 long-finned pilot whales from seven mass 

strandings around New Zealand, by the Department of Conservation staff (DoC, New 

Zealand), between 1992 and 2004 (Table 4.1). These were subsequently transferred 

to the University of Auckland cetacean molecular archive. Information on the total 

length of the whales (from the tip of the upper jaw to the deepest part of fluke notch) 

was available for all strandings except for Long Bay and Pitt Island. The number of 

whales involved in each of the strandings ranged from 11 to 159 but data were 

generally obtained from only a subset of individuals (Table 4.1). In the case of 

Mahurangi (11 whales), all the beached individuals were sampled. However, it is 

known that the night before the stranding, 100 to 200 pilot whales were roving off the 

same reef (DoC, debrief report). These 11 individuals could thus represent only a 

small subset of a much larger group. At Golden Bay, Stewart Island 2003 and 

Opoutere, more than 50% of the whales involved were sampled, representing a good 

coverage of these events (Table 4.1). 

100

Table 4.1. Summary of the seven mass strandings from around New Zealand, including number of individuals involved in the stranding, 

number of samples collected, sex information and mitochondrial genetic diversity indices. Individuals were classified as immature or mature 

based on total body length (see section 4.3.4). 


Haplotype 

diversity 

Nucleotide 

diversity (%) 

# Males 

# Females 

# mtDNA 

haplotypes 

# samples 

# Ind. 

involved 

Year 

Mass Stranding 

Mature 

Immat. 

Mature 

Immat. 

0.600 +/- 0.045 

0.19 +/- 0.16 

3 

9 

16 

5 

4 

33 

63 

1992 

Golden Bay 

0.520 +/- 0.028 

0.28 +/- 0.22 

11 

14 

2 

27 

~90 

1993 

Long Bay 

0.346 +/- 0.172 

0.10 +/- 0.12 

2 

4 

3 

11 

128 

1999 

Pitt Island 

0.100 +/- 0.088 

0.03 +/- 0.05 

2 

5 

12 

1 

2 

20 

67 

2000 

Stewart Island 

0.000 +/- 0.000 

0.00 +/- 0.00 

14 

32 

56 

20 

1 

122 

159 

2003 


0.039 +/- 0.037 

0.02 +/- 0.05 

6 

11 

26 

8 

2 

51 

73 

2004 

Opoutere 

0.000 +/- 0.000 

0.00 +/- 0.00 

1 

2 

8 

0 

1 

11 

11* 

2004 

Mahurangi 

0.233+/- 0.033 

0.10 +/- 0.10 

26 

59 

118 

34 

7 

275 

- 

- 

Total 

* the number of whales stranded at Mahurangi is thought to represent only a small subset of individuals from a larger group (see section 4.3.1). 

101


4.3.2. DNA extraction and sequencing 

Total cellular DNA was isolated from skin tissue by digestion with proteinase K 

followed by a standard phenol: chloroform extraction method (Sambrook et al. 1989) 

as modified for small samples by Baker et al. (1994). 

A fragment of the mtDNA control region was amplified by Polymerase Chain 

Reaction (PCR) for all the samples using the primers light-strand, tPro-whale Dlp-1.5 

(Baker et al. 1998), and heavy strand, Dlp-8G (designed by G. Lento as reported in 

Dalebout et al. 2005). See section 2.3.4 of Chapter 2 for PCR reaction conditions, 

cycling profile and primers sequences. PCR products were purified for sequencing 

with ExoSAP-IT (USB) and sequenced with BigDye TM terminator chemistry v. 3.1 on 

an ABI3100 sequencer (Applied Biosystem Inc.). Sequences were aligned using 

Sequencher TM v. 4.1.2 (Gene Codes Co.) and edited manually. 

4.3.3. Microsatellite genotyping 

Samples were genotyped using 14 previously published microsatellite loci developed 

from different cetacean species (Table 4.2). PCR reactions were performed in 10µL 

volumes, with 1 x Platinium-Taq buffer, 1.5 mM MgCl2, 0.4 µM each primer, 0.2 mM 

dNTPs and 1/8 U of Platinium-Taq® DNA polymerase, and cycling profile varying by 

locus (Table 4.2). PCR products were run on an ABI 377 or an ABI 3100 DNA 

automated sequencer. Data were collected by GeneScan v. 3.7, and the fragments’ 

size was measured using Genotyper v. 3.7 (Applied Biosystems Inc.). The rate of 

genotyping error was assessed by re-genotyping an average of 80 individuals per 

locus, and by calculating the ratio between the observed number of allelic differences 

and the total number of allelic comparisons (Bonin et al. 2004). The probability of 

identity (PID) per locus and over all loci was calculated using GenAlEx v. 6 (Peakall & 

Smouse 2005). See Chapter 2, section 2.3.6, for a definition of the PID. To verify the 

suitability of the loci for kinship analyses, I tested each for deviation from Hardy- 

Weinberg equilibrium and linkage disequilibria using the program Genepop v. 3.4 

(Raymond & Rousset 1995). The presence of null alleles was estimated using a 

maximum-likelihood estimator implemented in the program ML-Relate (Kalinowski et 

al. 2006). 

102


Table 4.2. Summary statistics of the 14 microsatellite loci. n is the number of screened chromosomes 

(2x the individuals), T°A is the annealing temperature applied during polymerase chain reactions and k 

is the number of alleles found. HO is the observed heterozygosity, HE is the expected heterozygosity 

and PID is the probability of identity per locus. HWE p-value refers to the results of the exact tests for 

deviation of Hardy-Weinberg equilibrium. 

Locus n T°A k HO HE PID 

HWE 

p-value 

Null Allele 

Frequency Source 

409/470 254 45 12 0.878 0.825 0.050 0.955 0.000 Amos et al. (1993) 

415/416 266 45 9 0.793 0.794 0.073 0.016 0.016 Amos et al. (1993) 

464/465 261 45 9 0.682 0.693 0.118 0.177 0.008 Amos et al. (1993) 

DlrFCB1 267 50 15 0.715 0.760 0.093 0.294 0.005 Buchanan (1996) 

DlrFCB6 262 62 7 0.691 0.677 0.162 0.740 0.000 Buchanan (1996) 

EV1 266 45 14 0.726 0.757 0.084 0.136 0.011 Valsecchi & Amos (1996) 



GATA53 240 55 8 0.825 0.830 0.053 0.081 0.007 Pasbøll et al. (1997) 

GT23 267 55 5 0.528 0.483 0.334 0.968 0.000 Berube et al. (2000) 

GT51 261 60 3 0.337 0.325 0.501 0.665 0.000 Caldwell et al. (2002) 

GT575 265 50 11 0.819 0.833 0.049 0.461 0.000 Bérubé et al (2000) 

MK8 228 50 13 0.833 0.813 0.060 0.214 0.000 Krützen et al. (2001) 

Ppho131 267 60 11 0.727 0.740 0.107 0.679 0.000 Rosel et al. (1999) 

The PCR cycling profile was [93°-2', (92°-30", T°A-45", 72°-50") 15x, (89°-30", T°A-45", 72°-50") 20x, 

72°-3'], except for GT51, which was amplified using the profile reported by the original paper. 

4.3.4. Age/sex classes 

The sex of each whale was identified by amplification of a fragment of the sry gene 

multiplexed with a ZFX positive control, as described by Gilson et al. (1998). Based 

on total length measurement, each sex was classified as likely mature or likely 

immature. It has been shown that sexual maturity in long-finned pilot whales from the 

Faroe Islands is closely related to body size (rather than age), with all males less 

than 480 cm and all females less than 375 cm being immature individuals (Block et 

al. 1993). Given that long-finned pilot whales from around New Zealand appear to 

have similar parameters of growth and reproductive status to those off the Faroe 

Islands (Schröder & Castle 1998), these thresholds were considered appropriate for 

this dataset. 

103


4.3.5. mtDNA control region 

Variable sites and unique haplotypes of the mtDNA control region sequences were 

identified using MEGA v. 3.1 (Kumar et al. 2004). Overall haplotype and nucleotide 

diversity were estimated using a Kimura 2-parameter, as implemented in Arlequin v. 

3.01 (Excoffier et al. 2005). The frequencies of mtDNA haplotypes was used to infer 

the presence, or not, of unrelated maternal lineages within mass strandings of longfinned 

pilot whales. 

4.3.6. Patterns of relatedness 

Monte-Carlo simulations were run to select a relatedness estimator that performed 

best for the dataset of 14 microsatellites typed for all individuals (as suggested by 

Van de Casteele et al. 2001). Three commonly used method-of-moment estimators 

and one maximum-likelihood estimator were compared. They are referred to as: rLR 

(Lynch & Ritland 1999), rQG (Queller & Goodnight 1989), rW (Wang 2002) and rML 

(Milligan 2003), respectively. First, four datasets; of 1,000 pairs of genotypes each, 

were generated using a Matlab program written by Russello & Amato (2004). Each 

dataset simulated one of four possible types of relationship; unrelated individuals 

(UR), half-sibling (HS), full-sibling (FS) and parent-offspring (PO). Expected 

relatedness for each of these is: UR, r = 0; HS, r = 0.25; FS, r = 0.5; and PO, r = 0.5. 

Genotypes were simulated based on the observed allele frequencies of the 

population. Relatedness was then estimated for each simulated pair using the 

program Identix (Belkhir et al. 2002) for rLR and rQG, Mer (Wang 2002) for rW, and ML- 

Relate for rML. The sampling variance of the different estimators was calculated as 

the standard deviation of the relatedness estimates for each dataset, while bias was 

quantified as the deviation of the mean from the expected relatedness value (UR, 0; 

HS, 0.25; FS, 0.5; PO, 0.5). The root mean-square error (RMSE) was also calculated 

to integrate both variance and bias of the estimators. The choice among the different 

estimators was made by comparing their statistical behaviour for these three 

parameters (Milligan 2003). Note that contrary to the maximum-likelihood estimator 

(rML), the method-of-moments estimators are not constrained within the biologically 

relevant range of [0,1]. Therefore, to account for the effect of different ranges, 

method-of-moments estimates were re-examined after truncating the r-value 

104


distributions to fit between [0,1], i.e., with negative values of r being replaced by 

zeros (Milligan 2003). 

Using the best estimator, pairwise relatedness was calculated between all individuals 

of the dataset. To test if the level of observed relatedness within mass strandings 

was higher than expected by chance, a null distribution of mean relatedness between 

any two individuals per mass stranding was generated using re-sampling simulations. 

Each mass stranding event was recreated 10,000 times by randomly selecting 

individuals of the dataset, keeping the sample size and sex-ratio consistent with the 

original strandings. The mean value of r was then calculated for each of the 10,000 

replicates to create the null distribution of each mass strandings. To be more 

conservative, the analysis was also run after excluding immature individuals from the 

dataset. Indeed, even if groups of long-finned pilot whales were composed of random 

individuals, pairs of mothers and young calves would still be represented, inducing an 

positive bias in the mean level of relatedness within the group. 

To investigate whether shared mtDNA haplotypes within a stranding predicted a 

higher level of microsatellite relatedness, values of r were compared within mass 

stranding between pairs of individuals with the same mtDNA haplotype and pairs of 

individuals with different haplotypes. A Mantel test of matrix correlation was used to 

investigate this hypothesis for each of the strandings with more than one mtDNA 

haplotype, i.e., pairwise mtDNA information was compared to pairwise r. In the matrix 

containing mitochondrial information, pairs representing a shared haplotype were 

assigned a one, while pairs representing different haplotypes were assigned a zero. 

Significant correlation between the two matrices was assessed using Monte-Carlo 

randomisation (10,000 replicates), as implemented in GenAlEx. As above, the test 

was also run after excluding immature individuals of the dataset in order to be more 

conservative. 

4.3.7. Parentage analyses 

The analyses of parentage were restricted to the three mass strandings with good 

sampling coverage (nTOT = 206): Golden Bay 1992, Stewart Islands 2003 and 

Opoutere 2004. Two sets of candidate parents were considered for all three 

105


strandings considered here: mature females (n = 98) and mature males (n = 23). 

Both sets were compared to all immature (n = 85) and all mature whales (n = 120), 

searching for potential parentage. 

Parentages were inferred using the likelihood-based approach implemented in the 

program Cervus v. 2.0 (Marshall et al. 1998). This program calculates and compares 

the likelihood ratio of each candidate parent based on population allele frequencies 

(that is, the likelihood of parentage of that candidate parent relative to the likelihood 

of parentage of an arbitrary unrelated candidate parent). The confidence of each 

parentage inference is assessed by calculating the difference between the LOD 

score (that is, the sum of the log-likelihood ratios at each locus) of the most-likely 

candidate parent and the second most-likely parent in the sample (i.e., with the next 

highest LOD score). The critical value of this difference, referred to as the ∆-value, is 

generated through simulation, taking into account allele frequencies in the 

population, the number of possible candidate parents, the proportion of candidate 

parents sampled, and the percentage of missing genetic data and genotyping errors. 

Here, the input parameters were set as follows: 10,000 candidate parents, 25% of the 

parents sampled, 99.8% of the loci typed and genotyping error of 0.01. Furthermore, 

considering that mass strandings are likely to be composed of numerous maternally 

related members, simulations were run allowing the presence of relatives in the 

dataset (set as three relatives at r = 0.25 for the candidate parents). Rather 

conservative settings were chosen (several simulations with different input 

parameters were performed) to compensate for the absence of biological basis for 

some of the parameters required by Cervus. A 95% confidence level for the ∆-value 

was used in order to reduce the potential of false inclusion. However, it must be 

noted that with this criterion, Cervus is likely to omit a substantial number of true 

parentages, i.e., false exclusion (in particular with cases where neither parent is 

known). Therefore, for comparison, the results based on a strict-exclusion approach 

were also reported. In this approach, all pairs sharing at least one allele at each locus 

are considered to be potential first-order relatives. Contrary to the likelihood-based 

approach, strict-exclusion is likely to give false parentage connections (or false 

positives), especially when there is not enough genetic variability. This method is also 

sensitive to genotyping error, which in this case, could result in false exclusion. 

106


In the case of parentage assignment between two mature whales, it was not possible 

to determine which individual was the parent and which one was the offspring. 

Therefore, they were simply refered to as first-order relatives. 

4.4. Results 

4.4.1. Molecular sexing and age/sex classes 

Sex was identified for a total of 98 males and 170 females, giving a sex ratio of 

1:1.72, significantly different from a theoretical 1:1 sex ratio (χ² = 19.2, p < 0.005) but 

similar to that previously found for drive-kill fisheries and strandings in the North 

Atlantic (e.g., Bloch et al. 1993, Sigurjónsson et al. 1993). The sex could not be 

determined for seven samples. Based on total length of each individual, overall mass 

stranding composition was as follows: 40.3% mature females, 13.4% mature males, 

20.2% immature females and 26.1% immature males (see Table 4.1 for details of 

each mass strandings). The proportion of age/sex classes also showed close 

agreement with studies from the drive-kill fisheries in the North Atlantic (Bloch et al. 

1993). 

4.4.2. Overall mtDNA diversity 

The length of mtDNA control region sequences obtained varied amongst samples, 

ranging from 389 to 620 bp. Comparison of these sequences revealed a total of 

seven variable sites (five transition substitutions and one 2 bp insertion-deletion) 

defining seven unique haplotypes. The largest consensus sequence available for all 

275 samples was 365 bp long and encompassed all variable sites resolved in the 

dataset. Examination of longer sequences (590 bp) for 194 samples did not detect 

additional variable sites (see also Chapter 3). The overall level of mitochondrial 

diversity was very low, with haplotype diversity, h, of 0.233 +/- 0.033 and nucleotide 

diversity, π, of 0.10% +/- 0.10% (Table 4.1). 

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4.4.3. mtDNA haplotype distribution 

Although the overall mtDNA diversity was low, haplotype distribution within mass 

strandings confirmed cases of multiple maternal lineages. One haplotype (haplotype 

a) was shared by a large majority of whales (88%; n = 253) and was found in all 

seven mass strandings*. In five of these mass strandings, representatives of more 

than one mtDNA haplotype were found, thus indicating the presence of individuals 

from unrelated maternal lineages (Figure 4.2). Mixed haplotypes within the same 

stranding included individuals from both sexes. 

At Opoutere and Stewart Island 2000, all whales but one shared haplotype a; a 

mature female had haplotype b at Opoutere and an immature male had haplotype g 

at Stewart Island (Figure 4.2). The most striking cases of multiple maternal lineages 

were at Long Bay and Golden Bay. In each of these two strandings, several 

individuals were found to share one of the less common haplotype (haplotype b and 

g, respectively) while the rest of the group mainly shared haplotype a (Figure 4.2). 

Only one haplotype was found in the mass strandings at Stewart Island 2003 and 

Mahurangi. In both cases it was haplotype a. A chi-squared test of independence 

indicated that the distribution of haplotypes among the mass strandings was not 

homogenous (χ² = 295, p < 0.005). Note, however, that the assumptions for this test 

were not fulfilled following Cochran’s set of rules (several frequencies used for the 

test were equal to 0 or 1). 

*Note that the haplotype names given in this chapter are independent of the names given for 

long-finned pilot whales mtDNA sequences in Chapter 3. This is because of a difference in the 

length of the consensus fragment used in the two chapters. 

108


Figure 4.2. Distribution and size of the mass strandings around New Zealand, and frequencies of the 

seven mtDNA haplotypes. N indicates samples sizes. Sex composition per mass stranding per 

haplotype is given, with F, M and “?” representing the number of females, males and individuals of 

unknown sex, respectively. 

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4.4.4. Microsatellite statistics 

The mean number of alleles per locus was 9.07 (ranging from 3 to 14) and mean 

observed heterozygosity, HO, was 0.708 (ranging from 0.337 to 0.878). Over the 14 

loci, the PID was 2.7 x 10 -14 . There was no evidence of linkage disequilibrium (results 

not shown) and no locus but 415/416 was found to deviate from the Hardy-Weinberg 

equilibrium in the pooled sample (Table 4.2). The frequency estimate of null alleles at 

the locus 415/416 was 1.6%. Despite this result, this locus was not excluded from 

subsequent analyses since the parentage and relatedness methods used later can 

take into account such a bias (Kalinowski & Taper 2006). A total of seven errors (one 

binning error and six allelic dropout, spread over four loci) were found after regenotyping 

2,400 alleles, giving an estimated error rate of 0.0031 per allele, i.e., less 

than the 1% recommended for parentage analyses (Taberlet & Luikart 1999). 

Some samples repeatedly failed to amplify for several microsatellite loci, probably as 

a result of degraded tissue. In order to limit the bias that this could cause to kinship 

analyses, 12 samples with less than 10 microsatellite loci successfully screened were 

excluded from analyses: seven were from the Long Bay mass stranding and five 

were from the Pitt Island mass stranding. The remaining 263 samples were 

genotyped at 10 to 14 loci each with an average of 13.65 loci per sample. 

4.4.5. Relatedness estimator 

The statistical behaviour of the four relatedness estimators, inferred from Monte- 

Carlo simulations, showed close agreement with Milligan’s (2003) previous results. 

The rML gave the lowest standard deviation for all relationships except UR, for which 

the rLR appeared to perform better (Table 4.3). The rLR, however, performed poorly for 

all other categories of relatedness. These results were consistent whether or not the 

distribution was truncated for the method-of-moment estimators (Table 4.3). Although 

rML showed the largest bias for HS and PO, the related measures of RMSE were still 

found to be the lowest of all estimators, indicating that the bias was of little biological 

consequence (Milligan 2003). Therefore, the rML performed better overall and was 

chosen to calculate pairwise relatedness between all individuals. 

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4.4.6. Within-stranding mean relatedness 

Mean relatedness within each strandings ranged from 0.04 +/- 0.01 to 0.11 +/- 0.03 

(Figure 4.3). Given the different sampling coverage of each stranding, direct 

comparison of these means should be considered with caution. However, a few 

features are still worth noting. Firstly, comparisons to the null distribution revealed 

that the overall levels of relatedness at Stewart Island 2003 and Opoutere were 

higher than expected by chance. Interestingly, these two events represent large 

strandings (over 50 individuals involved) with the best sampling coverage in the 

dataset (Table 4.1). Relatedness within these two strandings was still significantly 

higher than expected after excluding immature individuals (results not shown). On the 

other hand, the mean relatedness at Mahurangi appeared to be relatively low 

(although not significantly different from expectation based on null distribution) 

despite the fact that all the stranded whales were sampled (Figure 4.3). However, it is 

believed that the 11 whales stranded at Mahurangi were part of a larger group, most 

of which did not strand, as mentioned in the section 4.3.1. 

111

Table 4.3. Statistical behaviour of four relatedness estimators based on simulated populations consisting of 1000 pairs of unrelated 

(UR), half-sib (HS), full-sib (FS) or parent-offspring (PO) individuals. Mean and standard deviation (SD) from the three method-of- 

moment estimators were calculated from untruncated (ranging from -1 to 1) and truncated (ranging from 0 to 1) pairwise 

relatedness estimates. The best statistics are given in bold, while the worst are given in italics (one of each for each simulated 

category). 


PO 

FS 

HS 

UR 

Estimator 

RMSE 

Bias 

Mean + SD 

RMSE 

Bias 

Mean + SD 

RMSE 

Bias 

Mean + SD 

RMSE 

Bias 

Mean + SD 

Statistics 

0.053 

0.026 

0.526+/- 

0.045 

0.129 

0.002 

0.502+/- 

0.129 

0.141 

0.012 

0.262+/- 

0.141 

0.096 

0.051 

0.051+/- 

0.082 

rML 

Untruncated 

0.171 

0.005 

0.505+/- 

0.171 

0.193 

0.008 

0.508+/- 

0.193 

0.18 

-0.005 

0.245+/- 

0.180 

0.1 

-0.005 

-0.005+/- 

0.100 

rLR 

0.095 

0.006 

0.506+/- 

0.095 

0.139 

0.001 

0.500+/- 

0.139 

0.153 

-0.001 

0.249+/- 

0.153 

0.157 

-0.001 

-0.001+/- 

0.157 

rQG 

0.078 

0.001 

0.500+/- 

0.078 

0.139 

-0.001 

0.499+/- 

0.139 

0.149 

-0.004 

0.245+/- 

0.149 

0.165 

-0.007 

-0.005+/- 

0.165 

rW 

Truncated 

0.171 

0.005 

0.505+/- 

0.171 

0.193 

0.008 

0.508+/- 

0.193 

-0.003 0.177 

0.247+/- 

0.177 

0.079 

0.035 

0.035+/- 

0.071 

rLR 

0.095 

0.006 

0.506+/- 

0.095 

0.139 

0.001 

0.500+/- 

0.139 

0.145 

0.002 

0.252+/- 

0.146 

0.115 

0.062 

0.062+/- 

0.097 

rQG 

0.078 

0.001 

0.500+/- 

0.078 

0.139 

-0.001 

0.499+/- 

0.139 

0.142 

-0.001 

0.249+/- 

0.142 

0.114 

0.061 

0.061+/- 

0.096 

rW 

112


Figure 4.3. Observed mean relatedness (rML) within mass strandings, showing error bars. The shaded 

rectangles represent 90% of the null distribution of mean rML per mass stranding, obtained from the resampling 

simulation under expectation for unrelated individuals (10,000 replicates). 

4.4.7. mtDNA haplotypes and microsatellite relatedness 

The Long Bay (n = 15) and Golden Bay (n = 33) strandings were used to test for 

relatedness within and between mtDNA haplotypes, as only these strandings had 

representatives of more than one haplotype (Figure 4.2). For both samples, the 

pairwise mean relatedness between individuals sharing the same haplotype was 

larger that the mean relatedness between individuals with different haplotypes (at 

Long Bay, these were 0.079 and 0.049, respectively; at Golden Bay, they were 0.099 

and 0.049 respectively). The Mantel statistic was only significant for Golden Bay 

1992, where, it indicated significantly more microsatellite relatedness between 

individuals sharing a mtDNA haplotype than expected by chance (R² = 0.042, p < 

0.001). This trend persisted, and was significant, after excluding immature individuals 

from the analysis (R² = 0.045, p < 0.05). The Mantel statistic was not significant for 

Long Bay (R² = 0.019, p = 0.097). However, in this stranding, the lower sampling 

coverage and the exclusion of numerous whales (as a result of too much missing 

microsatellite data) may have substantially weakened the analysis. 

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4.4.8. Parentage inference 

The number and percentage of mature females and mature males with at least one 

assigned parentage among immature and mature whales of their mass stranding 

were reported in Table 4.4, for the likelihood-based approach and the strict-exclusion 

approach. As expected, the likelihood-based approach was found to be more 

conservative than the strict-exclusion approach, with fewer parentage assignments in 

the former. This was also illustrated by a larger number of between stranding 

assignments when using strict-exclusion (see Table 4.5 for results of parentage 

inferences between stranding and further discussion on this point). The strictexclusion 

approach was not conservative enough to elucidate true parentage 

relationships based on this dataset. However, although the likelihood-based and 

strict-exclusion approach yielded different frequencies of assignment, the comparison 

of the percentages of assigned individuals for each category showed similar 

tendencies (Table 4.4). These were: (1) a substantial proportion of mature females 

were assigned as potential mothers to immature whales; (2) rare assignments of 

parentage were found between mature males and immature whales; (3) and, similar 

proportions of parentage assignment to mature individuals were observed for mature 

males and mature females. 

Based on the likelihood-based approach, all the mature individuals assigned as a 

first-order relative of a mature male were females, presumably their mother. 

However, based on strict-exclusion approach, three mature males were identified as 

potential first-order relatives of other mature males (two of these pairs were 

confirmed based on 20 loci, results not shown). Note that one mature male (Glo118) 

was identified as a potential father of an immature from his group (Glo131, male), 

based on the likelihood-based approach (i.e., the method thought to be overconservative). 

This result was confirmed after screening a total of 20 microsatellite 

loci (results not shown, see Chapter 5). See Appendix 5 for more details on this 

particular case. 

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Table 4.4. Results of parentage analyses within three mass strandings using likelihood-based 

approach and strict-exclusion approach. Numbers indicate the frequencies (and the proportion, %) of 

mature females and mature males that were assigned at least one first-order relative in their mass 

stranding. Distinction was made between assignments to at least one immature individual (Vs. 

immatures) and assignments to at least one mature individual (Vs. matures). * indicates an 

assignment between two individuals mismatching at one locus. 

Mass strandings 

Likelihood 

Strict-exclusion 


Mature females Mature males 

Vs. 

immatures 

Vs. matures 

Vs. 

immatures 

Vs. matures 


2003 

8 (14%) 10 (18%) 1 (7%) 3 (21%) 

Opoutere 3 (12%) 7 (27%) 0 (0%) 1 (17%) 

Golden Bay 1 (6%) 0 (0%) 0 (0%) 1* (33%) 

Total 12 (12%) 17 (17%) 1 (4%) 5 (21%) 


2003 

33 (59%) 43 (77%) 1 (7%) 13 (93%) 

Opoutere 12 (46%) 18 (69%) 0 (0%) 2 (33%) 

Golden Bay 2 (13%) 2 (13%) 0 (0%) 0 (0%) 

Total 47 (48%) 63 (64%) 1 (4%) 15 (65%) 

4.5.1. Unrelated maternal lineages in mass strandings 

Many hypotheses have been proposed to explain mass strandings but none, so far, 

have reached a global consensus. Although the results presented here do not offer a 

final answer, they indicate that kinship, which is thought to be the basis of social 

cohesion in the case of long-finned pilot whales, is not the only factor which compels 

the whales to follow their counterparts to their death. The analysis of mtDNA revealed 

that more than one haplotype was found in five of seven mass strandings from New 

Zealand, indicating that long-finned pilot whales involved in the same stranding event 

are not always descendent from the same female ancestor. It is unlikely that the 

presence of different haplotypes is a sole consequence of mutations, since two of the 

rare haplotypes (haplotypes b and g) were found in more than one stranding. This 

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result is similar to findings in mass strandings of sperm whales, where multiple 

haplotypes were found in three different events (Mesnick 2001). Only one of the four 

strandings examined by Mesnick (2001) showed a single haplotype, which was the 

most common haplotype in sperm whales. This was the case in the long-finned pilot 

whale mass strandings of Stewart Island 2003 and Mahurangi, where all individuals 

shared the same most-common haplotype (i.e., haplotype a). Considering the low 

mtDNA diversity in long-finned pilot whales from New Zealand (as well as worldwide, 

see Chapter 3), the showing of a common haplotype will be expected by chance 

alone, as well as by recent descent. In fact, analysis of microsatellite variability 

indicates a surprisingly low average level of relatedness between the 11 stranded 

individuals at Mahurangi (which is the only stranding from which all individuals were 

sampled). This rather suggests that these individuals were largely unrelated, 

although they shared the same mtDNA haplotype. 

Table 4.5. Results of parentage inferences between individuals from three mass strandings 

comparing a conservative likelihood-based approach to a less-conservative strict-exclusion approach. 

Numbers indicate the frequencies of mature males or females with at least one assignment among 

immature and mature candidate first-order relatives. * indicates an assignment between two 

individuals mismatching at one locus. 

Mass strandings 

Likelihood 

Strictexclusion 

Mature females Mature males 

to 

immatures 

to all 

matures 

to 

immatures 

to all 

matures 


2003 

0 0 0 0 

Opoutere 0 0 0 1* 

Golden Bay 0 0 0 0 


2003 

5 5 2 2 

Opoutere 5 6 1 2 

Golden Bay 3 3 0 0 

Note: This analysis indicates than many between-stranding first-order parentages were assigned 

based on strict-exclusion approach (n = 34), while only one was found using the likelihood-based 

approach. Considering that the total number of individuals used in this analysis is thought to represent 

only a very small fraction of the total population of long-finned pilot whales around (although no 

population abundance estimate is available), and that these individuals have been sampled from 

independent strandings over the last 15 years, it seems unlikely that these between-stranding 

parentage assignments represent true pairs of first-order relatives (at least for the majority of them). 

Therefore, these results illustrate the fact the likelihood-based approach provides more conservative 

results than strict-exclusion approach for this dataset. 

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4.5.2. Using mass stranding data to infer social structure 

Mass strandings offer a particular type of data since they represent an “unusual” 

event. Therefore, these data must be considered carefully before using them to 

address questions on social systems. Here, two lines of evidence suggest that the 

main result described above was not biased by the nature of mass stranding events, 

and thus, that it applies to groups of long-finned pilot whales at sea. First, the 

sex/age class composition of the mass stranded groups investigated here closely 

matches the composition of the groups caught in the Faroe Islands and 

Newfoundland (Sergeant 1962, Bloch et al. 1993). These similarities in group 

structure suggest thus that mass strandings offer a fairly good demographic picture of 

the groups at sea. Second, it is likely that, if biased, mass stranding data would be 

skewed toward higher relatedness rather than to the contrary. No current hypothesis 

on the cause(s) of mass stranding suggests a skew toward lower relatedness than in 

living groups. Therefore, even if mass stranding data are biased, it should not alter 

the conclusions presented in the following section. Note also that in her study of 

relatedness with groups of sperm whales, Mesnick (2001) found similar genetic 

patterns in mass strandings and in groups at sea. 

4.5.3. A scenario of “unrelated matrilineal groups” 

The presence of several mtDNA lineages found within mass strandings is 

inconsistent with to the scenario of “extended matrilineal groups” proposed from 

microsatellite analyses on the Faroe Islands’ long-finned pilot whales (Amos et al. 

1993, Fullard 2000, Figure 4.1). However, information from the mtDNA is limited in its 

ability to test for the alternate scenario of “unrelated matrilineal groups”, which also 

implies some level of matrilineal social structure. Indeed, the mtDNA pattern 

observed here does not provide strong evidence of philopatry due to the overrepresentation 

of haplotype a, which obscures the relationship between individuals or 

matrilineal groups. At Stewart Island 2003 for instance, no strong conclusion could be 

made based on mtDNA, since all the whales shared a single haplotype (haplotype a). 

This haplotype is so common that some of these whales could originate from largely 

unrelated matrilineal groups and still share the same mitochondrial haplotype by 

chance. However, that the distribution of haplotypes b and g (Figure 4.2), which 

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show numerous representatives in one stranding (Long Bay and Golden Bay, 

respectively) but almost none in the others, is consistent with a matrilineal subgroup 

(this is also supported by result of the chi-square test on the homogeneity of 

haplotype distribution, see Section 4.4.3). 

The analyses of microsatellite loci variation conducted here complement the analyses 

of mtDNA to show that there was some level of matrilineal social structure amongst 

long-finned pilot whales from New Zealand mass strandings. The level of 

microsatellite relatedness was found to be significantly higher between individuals 

sharing the same mtDNA haplotype than individuals with different haplotypes within 

the same stranding. This is in agreement with the prediction from the “unrelated 

matrilineal group” scenario (Figure 4.1), where large groups of long-finned pilot 

whales are likely to be unstable associations composed of several stable entities of a 

smaller size. Furthermore, the parentage analyses confirmed that at least some 

individuals, males and females, remained with their mother after reaching sexual 

maturity. It also showed that mature males were rarely found to breed within their 

group (although this might happen occasionally, Table 4.4 and Appendix 5), and that 

their only first-order relative is likely to be their mother. Such a pattern represents the 

basis of a matrilineal social system with some degree of natal philopatry for both 

sexes. 

4.5.4. A similar social system to the North Atlantic 

Ottensmeyer and Whitehead (2003) suggested that different social systems between 

studied areas could potentially explain the conflicting group structure scenarios 

resulting from the genetic and behavioural studies from the North Atlantic. Intraspecific 

variations in social systems are not unusual for cetaceans, notably among 

species thought to be matrilineal in their group structure (e.g., killer whale, Baird & 

Whitehead 2000). However, since the data used in both studies were different, 

Ottensmeyer and Whitehead (2003) could not properly investigate whether or not 

there are differences between the social systems of Nova Scotia and Faroese longfinned 

pilot whales. The study presented here is the first investigation of long-finned 

pilot whales social structure in their Southern Hemisphere range and therefore, it was 

important to consider the possibility of different social systems to other studied areas. 

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Here, the use of microsatellite markers allowed comparison, to some extent, to the 

previous genetic studies in the Faroe Islands showing that, overall, patterns of 

parentage relationships and level of relatedness amongst individuals from mass 

strandings were similar to that of groups caught by drive-kill fisheries. 

First, and as described in the previous section, it was shown that at least some 

individuals (of both sexes) stayed with their mother after reaching maturity, and that 

mature males were unlikely to father within their own matrilineal group. This is similar 

to results described by Fullard (2000) in the Faroe Islands. Analyses based on 

relatedness also offered the opportunity to compare results from the present 

analyses to previous studies in the Faroe Islands. Unfortunately, as a consequence 

of incomplete sampling coverage of the mass strandings and the lack of detailed age 

information, it was not possible to repeat accurately the analyses conducted by Amos 

(1993) and Fullard (2000): Amos (1993) searched for a correlation between the age 

of females and the probability of finding the alleles carried by these females within 

their ‘grind’ (testing significance through simulations); Fullard (2000) compared the 

mean relatedness of “old” females (aged ≥ 25 years) within and between grinds using 

a randomisation procedure. Here, only the comparison of within mass stranding 

mean relatedness to null distributions provided an analysis close to what these 

authors reported. This analysis showed that mean relatedness was higher than 

expected by chance was found at Stewart Island 2003 and Opoutere. The question 

is: do these results support a scenario of “extended matrilineal unit”, as proposed by 

studies from the Faroes? I believe this is unlikely given the counter-evidence from the 

distribution of mtDNA haplotypes among mass strandings. High mean relatedness 

would also be expected in groups composed of several matrilineal units (Figure 4.1) 

and the significant difference observed here with the null distribution is more likely to 

be the result of good sampling coverage in these two mass strandings. 

Overall, I concur with Ottensmeyer and Whitehead (2003) on questioning the validity 

of the “extended matrilineal group” scenario and suggest that additional 

investigations of mtDNA for the Faroes’ groups could reveal the presence of more 

than one maternal lineages per “grind”. 

119


4.5.5. Comparison to other matrilineal species of odontocetes 

Signs of matrilineal social structure have been proposed in four species of 

odontocetes to date (Whitehead 1998); killer whales (Bigg et al. 1990), short-finned 

pilot whales (Heimlich-Boran 1993), long-finned pilot whales (Amos et al. 1993) and 

sperm whales (Richards et al. 1996). Studies on killer whales and sperm whales 

have benefited from additional long-term behavioural data which, in both cases, 

revealed several hierarchical levels of social organisation (Bigg et al. 1990, 

Whitehead & Weilgart 2000). Such information is still unavailable in long-finned pilot 

whales and will be required to describe their social system in detail. However, the 

increasing knowledge from independent genetic and short-term behavioural studies 

now provides a better framework for comparison to these two better-known species. 

Fullard (2000) suggested that groups of long-finned pilot whales caught in the Faroe 

Islands are similar to the “pods” of resident killer whales from British Columbia and 

Washington State. These pods are composed of several matrilineal groups travelling 

together more than 50% of their time (Bigg et al. 1990), they have an average size of 

twelve individuals (ranging from three to 59 individuals (Barrett-Lennard 2000)), and 

they are thought to include only genetically related individuals, as illustrated by the 

systematic mtDNA haplotype sharing between the members (Barrett-Lennard 2000, 

Hoelzel 1998). The finding of several mtDNA haplotypes in the group of long-finned 

pilot whales stranded around New Zealand clearly stands against this comparison. It 

is, on the other hand, similar to results described for sperm whales (Christal 1998, 

Mesnick 2001). Indeed, genetic studies have shown that “groups” and even “units” of 

sperm whales (the most stable behavioural entity in the social organisation of this 

species) do not necessarily represent strict matrilineal groups as originally thought. 

However, this does not mean, that long-finned pilot whales follow the same social 

system as sperm whales. It is known that in sperm whales, mature males disperse 

from their maternal groups (Whitehead & Weilgart 2000). Contrary to this, my results 

confirmed some natal philopatry for both-sexes in long-finned pilot whales, similar to 

that observed in killer whales. Therefore, at this stage, a reasonable statement would 

be that long-finned pilot whales social structure is situated somewhere between those 

which are known for ‘resident’ killer whales of the eastern North Pacific and sperm 

120


whales. Further studies combining behavioural and genetic information from 

strandings and free-ranging groups will help to refine our view of long-finned pilot 

whale social system(s). 

121

Chapter five: Social dynamic of pilot whale mass strandings 

5. “O’ mother where art thou?” Social disruption in a 

mass stranding of long-finned pilot whales 

Figure 5.1. Aerial view of the mass stranding at the Old Sand Neck on Stewart Island, on the 8 th 

January 2003. Some people are circled for scale. Photo courtesy of Helen Kettles, Department of 

Conservation. 

122

5.1. Abstract 


The proximate causes of cetacean mass strandings remain unclear. Social bonds 

between the individuals that strand together are assumed to play a critical role but, to 

date, this assumption has received little direct investigation. The long-finned pilot 

whale (Globicephala melas) is the most common species involved in mass 

strandings, often comprising more than a hundred individuals in a single event. Here, 

the assumption that social bonds are maintained during these traumatic events was 

investigated. To do so, advantage was taken of a unique dataset from a large mass 

stranding of this species (n = 122) in 2003 at Stewart Island, New Zealand. The 

position and age/sex class of each stranded whale was mapped along the beach, 

and samples were taken for genetic analyses. Kinship was estimated (based on 20 

microsatellite loci) by conducting relatedness and parentage analyses. Contrary to 

the expectation that close kin would be closely associated during these last moments 

of life, various analyses failed to detect a correlation of kinship with the spatial 

distribution of stranded individuals. Even inferred mother-and-calf pairs were often 

found widely separated along the beach. Although the observed separation of close 

kin could either be a cause or a consequence of the stranding event, this disruption 

of kinship bonds could help to explain the behavioural distress of stranded individuals 

and the tendency of many whales to re-strand after being re-floated. 

123



The phenomenon of cetaceans mass stranding has been a source of interest and 

puzzlement since Aristotle, 350 BCE (Historia Animalia, Book IX, Ch. 48). Mass 

strandings frequently involve over a hundred animals at a time, providing a 

compelling problem for animal welfare and human management. Despite centuries 

of questioning, this phenomenon is still subject to controversies regarding its causes. 

In some cases, pathology suggests direct causal mechanism (Geraci et al. 1989, 

Jepson et al. 2003), but for most mass strandings, the animals appear to be in 

perfect health. 

Among the many hypotheses proposed to explain mass strandings, one of the most 

popular has been that social cohesion drives the whales to follow their kin aground 

(Odell et al. 1980, Cordes 1982). Support for this hypothesis comes from several 

observations: 1) only species of cetaceans thought to form long-term social bonds 

(and belonging to the sub-order of toothed-whales, or Odontoceti) are affected by 

mass strandings; 2) several studies have reported cases whereby healthy cetaceans 

have mass stranded, apparently because they remained in the vicinity of a sick 

individual or an individual in difficulty (Porter 1977, Robson 1984, Rogan et al. 

1997); 3) the re-stranding of healthy animals, after being re-floated and driven 

offshore, has been interpreted as a social response to individuals that remained 

ashore (Porter 1977, Robson 1984). 

Although typically listed in the potential causes, the hypothesis that social bonds 

play a role in the dynamics of these events has received little direct investigation. 

Instead, studies have focused on testing hypotheses about the factors influencing 

the distribution of strandings in space and time: for example, currents and coastal 

topography (Brabyn & McLean 1992, Sundaram et al. 2006), geomagnetic 

disturbance (Klinowska 1986), and climate events (Evans et al. 2005). It has been 

recently pointed out that studies based on the distribution of mass strandings give 

little insight into the mechanisms driving such behaviour but rather indicate where or 

when strandings are more likely to occur (Bradshaw et al. 2005). Contrary to these 

hypotheses, the influence of social bonds on mass strandings lacks data for 

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statistical testing or modelling. For instance, it is particularly difficult to infer strength 

of social bonds in cetaceans, and in general, long-term studies are required to reach 

this aim (Bigg et al. 1990). 

However, in long-finned pilot whales (Globicephala melas), which is the primary 

species involved in mass strandings around the world, some assumptions can be 

made about their social bonds. Because of their propensity to mass strand, but also 

because of their herding behaviour when they are hunted by whalers, long-finned 

pilot whales have long been thought to be highly social in nature (Kritzler 1952). 

Genetic studies, initially conducted on the groups caught in the drive-kill fisheries of 

the Faroe Islands (Amos et al. 1991, Amos et al. 1993, Fullard 2000), and now on 

mass strandings from around New Zealand (Chapter 4), have started to provide 

explanations of these behaviours. These studies indicate some level of philopatry to 

the natal group for both males and females after reaching sexual maturity (a pattern 

thought to be rare in mammals). Therefore, although a lot remains to be explained 

on their social system, it appears that sociality in long-finned pilot whales is at least 

in part driven by kinship. 

In New Zealand, where mass strandings of long-finned pilot whales are common 

(Baker 1981), pioneering descriptions by naturalist Frank D. Robson have largely 

influenced the public views on these events. They have also helped to develop 

successful prevention and rescue techniques to save stranded whales (techniques 

which were notably taken up by Project Jonah, a non-profit organisation devoted to 

whale rescue, S. Gibney pers. comm.). Robson put particular emphasis on 

describing the behaviour of the whales just before and during a stranding (Robson 

1984). Based on 16 years of field experience, he noticed that the species 

responsible for large mass strandings, such as long-finned pilot whales, exhibit a 

typical pre-stranding behavioural pattern. This can be summarized as follows: the 

herd (as referred to by Robson) stops its normal travelling behaviour and alters its 

swimming style to engage in a vigorous milling on the surface (circling in a tight 

group); within minutes (although apparently this behaviour can last much longer, 

Geraci & Lounsbury 1993), an individual, the ‘key whale’, detaches from the herd 

and swims toward the shallows; once grounded, this ‘key whale’ begins to emit 

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‘distress’ calls; soon after, a group detaches from the herd and beaches themselves; 

this triggers a chain reaction in which successive groups of the herd strand one after 

another (Robson 1984). Robson considered that a “social problem” (for which he did 

not give a more detailed definition) was the most likely catalyst for these large mass 

strandings and that once an individual was stranded, its close relatives would 

invariably come ashore, responding to the ‘distress calls’ of their kin. The successive 

groups coming ashore were considered by Robson as distinct family units (Figure 

5.2), and thus social bonds were thought to be maintained during these last 

moments of life. Following this model, calves are expected to stay close to their 

mother during live strandings. Today, this assumption still has a direct implication 

during rescue attempts; in order to avoid re-stranding, the smallest individuals tend 

to be re-floated at the same time as the mature females found in their proximity, 

under the assumption that one of them is the mother (Geraci & Lounsbury 1993). 

Figure 5.2. Illustration and interpretation of the progression of a mass stranding on an open beach, 

from Robson (1984). While the whales are engaged in a milling behaviour, family groups gradually 

detach from the rest of the group and get stranded. As the position of the group moves with the drift, 

family groups spread at intervals along the beach. 

126


As Robson’s hypotheses were empirical, not experimental, G.S. Saayman noted in 

the forewords of Robson’s book, published in 1984, that some of his theories were 

likely to “raise eyebrows in ‘scientific’ circles”. However, 20 years later and after 

thousands of whales have been re-floated, Robson’s observations still constitute the 

most complete published observations on the behaviour of whales before and during 

mass strandings, providing an interesting framework to test hypotheses on the social 

dynamics of these events. 

In this chapter, a large mass stranding of long-finned pilot whales on a beach of 

Stewart Island, New Zealand in January 2003, was investigated in order to explore 

the assumption that social bonds were maintained throughout the stranding. To do 

so, advantage was taken of molecular techniques (based on microsatellite loci 

variability) to estimate kinship and infer parentage. First, spatial autocorrelation 

analyses and Mantel tests of matrix correlation were used to test the hypothesis that 

genetically related individuals were more likely to have stranded in geographic 

proximity than expected by chance. Then, pairs of mother-and-calf were searched to 

test the hypothesis that these bonds (likely to represent the strongest social 

connections in the group) were preserved during the stranding. 


5.3.1. Circumstances of the stranding 

On January 8 2003, 159 long-finned pilot whales were reported to have live-stranded 

on a sandy beach at the Old Sand Neck on Stewart Island, New Zealand (46° 58’ S, 

168° 11’ E, Figure 5.3). The whales were lying on the high tide line, suggesting that 

the stranding happened around 6:30 in the morning. About 60% of the whales were 

already dead by the time a rescue team from the Department of Conservation (DoC) 

arrived on site, around midday. Deaths were thought to be mainly due to overheating 

(DoC, Debrief notes and recommendations). A total of 37 whales were refloated and 

herded out to sea. The re-floating effort was apparently a success with no sign of restranding 

on the following days (although two whales, with healing skin damage, livestranded 

at a different location of the island on January 25). 

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Figure 5.3. Geographical location of the mass stranding of long-finned pilot whales at Stewart Island 

(indicated by the astericks), in 2003, with a larger perspective of the position of New Zealand in the 

South Pacific. 


Data were collected from the 122 whales that died on the beach (i.e., 77% of the 

whales initially stranded); this included total length measurements (from tip of upper 

jaw to deepest part of fluke notch), sex identification (from mammary slits 

observation) and collection of skin samples. All samples were transferred to the 

laboratory of Molecular Ecology and Evolution at the University of Auckland, where 

they were preserved in 70% ethanol and stored at -20°C for subsequent analyses. 

128


In addition to these data, the distribution of the whales on the beach was manually 

mapped by Helen Kettles, DoC Southland. The resulting map is not precise in terms 

of distances, but give an accurate picture of the position of the whales relative to 

each other, as confirmed by aerial and beachside photographs (Figure 5.1). A high 

tide occurred between the stranding and the time of data collection, slightly modifying 

the initial positions where the whales beached, but this was not more than a few 

meters (H. Kettles, pers. comm.). Thus these positions were thought to be 

representative of the location where the whales initially beached themselves. The 

carcasses were spread out along 150 meters, with no clear cluster of individuals 

(Figure 5.1). Based on the map, Y-axis and X-axis coordinates were allocated to 

each individual using an arbitrary linear scale. 

5.3.3. DNA extraction and microsatellite genotyping 

Total cellular DNA was extracted from skin samples using methods reported in 

Chapter 2. Samples were genotyped using polymerase chain reaction (PCR) with a 

panel of 20 previously published microsatellite loci developed from different cetacean 

species (Table 5.1, Appendix 1). PCR products were sized using an ABI 377 or ABI 

3100 DNA automated sequencer, and analysed with the softwares GeneScan v. 3.7 

and Genotyper v. 3.7 (Applied Biosystems Inc.). The average probability of identity, 

PID, was calculated from the formula of Paetkau & Strobeck (1994), using GenAlEx v. 

6 (Peakall & Smouse 2005). See Chapter 2, section 2.3.6, for a definition of the PID. 

To verify the suitability of the 20 loci for kinship analyses, I tested for deviation from 

Hardy-Weinberg equilibrium and linkage disequilibrium using the program Genepop 

v. 3.4 (Raymond & Rousset 1995). The potential frequency of null alleles was 

estimated using ML-Relate (Kalinowski et al. 2006). The rate of genotyping error was 

estimated by re-genotyping an average of 73 individuals per loci, calculating the ratio 

between the observed number of allelic differences and the total number of allelic 

comparisons (Bonin et al. 2004). 

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Table 5.1. Microsatellite diversity of long-finned pilot whales from the mass stranding of Stewart Island 

2003. 

Locus n T°A k HO HE 

HWE 

p-value 

Null Allele 

Frequency References 

409/470 122 45 10 0.885 0.822 0.513 0.000 Amos et al. (1993) 

415/416 122 45 9 0.795 0.795 0.150 0.023 Amos et al. (1993) 

464/465 122 45 9 0.648 0.681 0.699 0.017 Amos et al. (1993) 

DlrFCB1 122 50 11 0.672 0.754 0.295 0.024 Buchanan et al. (1996) 

DlrFCB6 122 62 7 0.656 0.658 0.170 0.000 Buchanan et al. (1996) 

EV1 122 45 11 0.713 0.718 0.958 0.000 Valsecchi & Amos (1996) 



GATA53 122 55 8 0.869 0.838 0.662 0.001 Palsbøll et al (1997) 

GT6 122 60 7 0.221 0.227 0.819 0.000 Caldwell et al. (2002) 

GT23 122 55 4 0.500 0.452 0.527 0.000 Bérubé et al. (2000) 



GT575 122 50 10 0.787 0.822 0.282 0.009 Bérubé et al. (2000) 

MK5 122 55 7 0.516 0.465 0.826 0.000 Krützen et al. (2001) 




Ppho110 122 50 5 0.164 0.163 0.607 0.000 Rosel et al. (1999) 


Average - - 7 0.608 0.595 - 0.004 - 

n is the number of screened individuals, T°A is the annealing temperature applied during polymerase 

chain reactions and k is the number of alleles found. HO is the observed heterozygosity and HE is the 

expected heterozygosity. HWE p-value refers to the results of the exact tests for deviation of Hardy- 

Weinberg equilibrium. The PCR cycling profile was [93°-2', (92°-30", T°A-45", 72°-50") 15x, (89°-30", 

T°A-45", 72°-50") 20x, 72°-3'], except for GT6 and GT51, which were amplified using the profile 

reported by the original paper. 

5.3.4. Age/sex class 

The whales were classified into four categories (female mature, male mature, female 

immature and male immature) based on sex and length measurement information, as 

described in Chapter 4. A fifth category was considered here to represent the 

youngest calves thought to be un-weaned, i.e., still dependent on their mothers for 

lactation; they were referred to as ‘un-weaned calves’. Growth and reproduction 

parameters estimated from studies of long-finned pilot whales in the Faroe Islands 

were also used to confirm the length threshold for this fifth category. The mean 

duration of lactation in long-finned pilot whale has been estimated at 3.4 years 

130


(Martin & Rothery 1993). The average length of female and male calves just before 

this age, i.e., 3 years old, has been estimated at 309 cm (SE = 1.9) and 317 cm (SE 

= 2.6), respectively (Block et al. 1993). Therefore, based on these estimates, all the 

immature whales measuring 300 cm or less were classified as ‘un-weaned calves’. In 

order to confirm field observations, sex of the whales was genetically identified by 

amplification of a fragment of the sry gene multiplexed with ZFX positive control, 

following the protocol of Gilson et al. (1998). Sex PCRs were conducted twice to 

confirm the results (which did not yield any inconsistencies). 

5.3.5. Spatial autocorrelation analyses 

To investigate the hypothesis that related individuals were more likely to be found 

closer to each other on the beach than expected by chance, analysis of global spatial 

auto-correlation was conducted (following the term used by Anselin 1995). This 

analysis requires pairwise geographic and pairwise squared genetic distance 

matrices individuals. Genetic distances were calculated as outlined in Peakall et al. 

(1995) and Smouse & Peakall (1999). The program GenAlEx was used to generate 

these matrices based on individual spatial coordinates and genotypic information. 

The method developed by Smouse and Peakall (1999), also implemented in 

GenAlEx, was used. It employs a multivariate approach to simultaneously assess the 

spatial signal generated by multiple genetic loci. This analysis generates an 

autocorrelation coefficient R for each distance class, providing a measure of the 

genetic similarity between pairs of individuals whose geographic separation falls 

within the specified distance class. Here, the data were analysed for several sizes of 

distance class, ranging from 25 to 200 units (arbitrary scale). By varying distance 

class size, the presence of spatial genetic structure was investigated using different 

average number of individuals per distance class. Statistical significance was tested 

by 10,000 random permutations. 

5.3.6. Relatedness analyses 

Autocorrelation coefficients such as R are closely related with estimates of 

relatedness (Banks et al. 2005). However, they do not provide a surrogate measure 

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of genealogical relationships. In order to test further for a correlation between kinship 

and spatial distribution, the pairwise relatedness (rML) was calculated between all 

individuals of the mass stranding, using Milligan’s (2003) maximum-likelihood 

estimator (values of this estimator range from 0 to 1, see Chapter 4 for details), as 

implemented in the program ML-Relate. To detect a potential correlation, the 

obtained matrix of relatedness indices was compared to the matrix of geographic 

distances using a Mantel test of matrix correlation (Mantel 1967) with Monte-Carlo 

simulation (10,000 permutations), as implemented in GenAlEx. Since Mantel tests 

can be affected by extreme values (Dietz 1983), a similar test was conducted using a 

different method to estimate pairwise coefficients of relatedness where the values 

can range from -1 to 1; the estimator rQG, developed by Queller & Goodnight (1989) 

was chosen. A comparison between the two estimators illustrate the effect of extreme 

negative values on the Mantel test results (see Results section). 

5.3.7. Parentage analyses 

The maintenance of social bonds during the mass stranding was investigated using 

parentage analyses. Here, I focused on inferring the mother of immature individuals, 

assuming that the mother-and-calf pairs were likely to represent the strongest social 

bonds in the group. Distinction was made between the ‘un-weaned calves’ and the 

other immature whales. 

Maternity of all immature whales was inferred using the strict-exclusion approach and 

the likelihood-based approach implemented in the program Cervus v. 2.0 (Marshall et 

al. 1998). See Chapter 4 for details on the methods. For the strict-exclusion 

approach, any mature females showing no mis-matching locus with the genotype of 

an offspring were considered as a ‘potential mother’. This approach is likely to avoid 

false negative (i.e., excluding a female that really is the mother) if genotyping error is 

low. On the other hand, several putative mothers can potentially be assigned to the 

same offspring. An important strength of this approach is to provide information on 

the number of calves found to have no ‘potential mother’ in the dataset. 

The likelihood-based approach offers complementary results as it is more 

conservative than the strict-exclusion method. To limit type I errors (i.e, false positive 

132


parentage), I applied conservative parameters to run the simulation used by Cervus 

to address statistical significance. These parameters were set as follows: 10,000 

candidate parents (the maximum allowed by Cervus); 10% of the parents sampled; 

99.8% of the loci typed; genotyping error of 0.005; and presence of five relatives at r 

= 0.5 for each candidate parent. I report the pairs with 80 and 95% confidence levels 

for ∆-values. 

A Mantel test of matrix correlation with Monte-Carlo simulation (10,000 permutations) 

was used to test for a non-random relationship between mother-and-calf bonds and 

position on the beach (Mantel 1967). The matrices were restricted to mature females 

and immature whales involved in a pair of mother-and-calf inferred from parentage 

analysis. For the kinship matrix, pairs of mother-and-calf were denoted as ‘one’, while 

all other pairs were denoted as ‘zero’. The test was conducted with the program 

GenAlEx. 

5.4. Results 

5.4.1. Sex/age class information 

Field observations (confirmed by molecular analyses) revealed that 76 females and 

46 males were present among the beached whales. All individuals except two were 

allocated concordant sex information from the examination of mammary slits in the 

field and the sex PCR in the laboratory (Glo097 and Glo162 were judged to be 

females in the field but males by PCR). It was chosen to give the priority to the 

molecular sexing for conflicting results but the possibility that these sample tubes 

were mislabelled, and thus that the initial sex identification was correct, cannot be 

discounted. However, it is unlikely that the potential mix-up of two samples had a 

substantial effect on the general tendency of the results. 

The sex/age group composition was as follows: 56 mature females (46%), 14 mature 

males (11.5%), 20 immature females (16%) and 32 immature males (26.5%). Among 

immature whales, eight females and nine males were classified as ‘un-weaned 

calves’ (i.e., ‘un-weaned calves’ represented 14% of the total dead stranded). 

133

5.4.2. Microsatellite analyses 


The 122 whales were genotyped for 18 to 20 loci, providing an average PID of 5.48 x 

10 -16 . The number of alleles per locus varied from 3 to 11 (7.3 on average) and the 

level of heterozygosity ranged from 0.082 to 0.881 (average 0.608; Table 5.1). No 

significant deviation from the Hardy-Weinberg equilibrium (Table 5.1) or evidence of 

linkage disequilibrium was found for the 20 loci (results not shown). Estimates of null 

alleles were low for all loci (Table 5.1). A total of 10 errors (spread over seven loci) 

were found after re-genotyping 3541 alleles (six allelic dropouts and four human 

errors), giving an estimated error rate of 0.0028 per allele. 

5.4.3. Spatial autocorrelation analyses 

Based on the arbitrary linear scale, the whales were spread out on a range of about 

1400 units on the X-axis and 60 units on the Y-axis, where 1400 units represent 

approximately 150 metres. Average distance between two individuals was 415 units 

(~ 45 m), ranging from 5 to 1391 units. The results of the global autocorrelation 

analyses found no significantly positive R within any of the distance class sizes 

considered here. These results for distance class sizes of 50 and 200 are 

summarised by a correlogram where the autocorrelation coefficients R are plotted as 

a function of distance (Figure 5.4). All R were found to fall between the upper and 

lower 95% confidence limits (correlograms are not shown for 25 and 100 distance 

class sizes but results were similar to correlograms shown in Figure 5.4). 

134


Figure 5.4: Correlogram plots of the genetic correlation coefficient (R) as a function of distance (in 

units), for distance class of (a) 50 and (b) 200 units. The permuted 95% confidence interval (dashed 

lines) and the bootstrapped 95% confidence interval error bars are also shown. The number of 

pairwise comparisons with each distance class is presented above the plotted values. 

5.4.4. Relatedness and overall spatial distribution 

Estimates of pairwise relatedness coefficient, rML, over the whole group, ranged from 

0.00 to 0.67 with an average of 0.05 (Figure 5.5). The large number of pairs with an 

rML equal to 0 (n = 3889) is explained by the fact that this estimator truncates the 

coefficients to fit in a range of 0 to 1. Therefore, instead of resulting in negative 

values of r between unrelated individuals (which is biologically meaningless), it simply 

allocates a 0 value. The frequency distribution shows a small secondary peak around 

the 0.5 values, illustrating the presence of first-order relatives in the group. A total of 

77 pairs presented a coefficient rML ≥ 0.5. 

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Figure 5.5. Distribution frequency of pairwise relatedness (rML, Milligan 2003) among long-finned pilot 

whales of the mass stranding of Stewart Island in 2003. 

The Mantel test resulted in a significant negative correlation between maximum 

likelihood coefficients of relatedness, rML, and geographic distances (p = 0.996). 

Surprisingly, however, a similar test based on the Queller & Goodnight coefficient of 

relatedness, rQG, yielded a contradictory result, indicating a significant positive 

correlation (p = 0.031). In both cases, the coefficients of correlation (r) were very 

small (maximum-likelihood, r = -0.034; Queller & Goodnight, r = 0.038), indicating 

that the tendency was weak. The test gave a non-significant result when the values 

of rQG were truncated to range between 0 and 1 (p = 0.228). Contradictory results 

yielded by the two estimators could be explained by the fact that Mantel tests can be 

strongly affected by large or small outlying values (Dietz 1983). Therefore, it was 

concluded that these last analyses did not provide satisfactory results to interpret the 

pattern of genetic relatedness and geographic distances in the mass stranding. 

5.4.5. Parentage inference 

Strict-exclusion method - Based on the genotypes of 52 immature whales and 56 

mature females, 37 candidate offspring (69% of the total) were found to match the 

136


genotype of candidate mothers with a minimum of one allele at each locus, that is, 

under the strict exclusion method (Table 5.2). Among them, three were found to 

match more than one mature female (Glo110; Glo131; Glo211). For the remaining 

34, all except one mature female were excluded as potential mothers. No potential 

mother could be found based on strict-exclusion for 15 candidate offspring, including 

six ‘un-weaned calves’. 

Likelihood-based method - The likelihood-based approach gave more conservative 

results with 17 and 11 assignments of offspring to a most-likely mother at 80 and 

95% confidence level, respectively (Table 5.2). Although a genotyping error of 0.005 

was allowed for the simulation (i.e., a value above the estimated genotyping error), 

none of the pairs proposed by Cervus showed mismatching locus (i.e., all agreed 

with results of the strict-exclusion method). Five ‘un-weaned calves’ were assigned a 

most-likely mother at 80% confidence level, and three at 95% confidence level (Table 

5.2). Therefore, nine ‘un-weaned calves’ were unassigned based on likelihood. 

Spatial distribution of mother-and-calf pairs - The distribution on the beach of motherand-calf 

pairs inferred by Cervus showed no obvious pattern of geographic 

association, regardless of the level of confidence considered for parentage inference 

(Figure 5.6). There was no pattern either when only considering the pairs of mothers 

and ‘un-weaned calves’ (Figure 5.6A). The average distance between assigned 

mother-and-calf pairs showed little difference from the overall average distance 

between any two individuals from the mass stranding (i.e, d = 415 units). Indeed, 

average distance between any mother-and-calf was 404 or 433 when considering 

pairs assigned using strict-exclusion or likelihood 80% confidence, respectively 

(Mann-Whitney U test; p = 0.75 and p = 0.86, respectively). Interestingly, when 

considering pairs assigned using likelihood 95% confidence, the average distance 

was even higher (615 units) than the average distance between any two individuals 

(Mann-Whitney U test; p = 0.03). A Mantel test showed no relationship between 

kinship (mother-and-calf against others) and distance between individuals on the 

beach, and this was consistent when considering pairs inferred by strict-exclusion (p 

= 0.636), likelihood 80% confidence (p = 0.551) and likelihood 95% confidence (p = 

0.071). 

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Table 5.2. Results of the parentage analyses in the mass stranding of long-finned pilot whales at 

Stewart Island 2003, using strict-exclusion and likelihood-based approach. Cells in grey indicate the 

“un-weaned” calves. (+) represent 80% confidence level for ∆-value. (++) represent 95% confidence 

level. (–) indicate pairs supported by strict-exclusion criteria only. Bold boxes indicate match of 

immature whale with more than one mature female under strict-exclusion criteria. 

Immature 

Candidate 

Mother 

Distance 

(units) 

Probability of 

non-exclusion 

LOD ∆-value Confidence 

level 

rML 

Glo090 Glo200 1083 1.93 x 10 -4 Glo094 Glo183 856 4.95 x 10 

8.56 7.30 ++ 0.52 

-5 Glo097 Glo098 18 1.23 x 10 

10.2 7.38 ++ 0.50 

-3 Glo099 Glo107 49 5.27 x 10 

5.40 5.28 + 0.50 

-4 Glo104 Glo193 878 4.68 x 10 

10.4 6.79 + 0.55 

-3 Glo105 Glo148 457 6.21 x 10 

5.32 2.34 - 0.50 

-4 9.08 6.79 + 0.52 


5.18 0.99 - 0.50 

-3 0.96 0.00 0.34 


7.27 6.45 + 0.50 

-4 Glo113 Glo180 616 8.76 x 10 

5.35 4.66 + 0.50 

-4 Glo120 Glo196 732 3.03 x 10 

5.28 5.28 + 0.51 

-4 Glo123 Glo200 735 2.29 x 10 

10.6 6.33 + 0.55 

-4 10.1 7.53 ++ 0.64 


8.00 14.20 - 0.58 

-3 6.58 0.00 0.50 


11.5 8.59 ++ 0.50 

-4 Glo142 Glo149 57 2.92 x 10 

6.29 3.90 - 0.55 

-4 Glo151 Glo202 470 2.62 x 10 

6.70 5.99 + 0.50 

-3 Glo152 Glo191 357 1.12 x 10 

11.1 8.05 ++ 0.61 

-4 Glo163 Glo181 154 6.83 x 10 

8.45 5.80 + 0.52 

-4 Glo164 Glo091 707 4.46 x 10 

7.48 5.68 + 0.50 

-3 Glo165 Glo203 394 1.03 x 10 

10.1 5.10 + 0.50 

-3 Glo168 Glo159 49 2.39 x 10 

10.9 8.88 ++ 0.65 

-3 Glo171 Glo176 28 1.63 x 10 

5.26 4.62 + 0.51 

-3 Glo177 Glo206 403 1.88 x 10 

7.01 4.75 + 0.50 

-3 Glo178 Glo139 295 1.57 x 10 

8.50 5.61 + 0.50 

-4 Glo182 Glo196 160 2.52 x 10 

7.41 7.41 ++ 0.50 

-4 Glo185 Glo204 262 1.58 x 10 

6.87 4.98 + 0.50 

-4 Glo186 Glo100 819 1.30 x 10 

6.39 0.00 - 0.50 

-3 Glo188 Glo172 124 4.24 x 10 

7.30 4.86 + 0.52 

-4 Glo194 Glo202 97 8.83 x 10 

7.04 3.24 - 0.57 

-4 Glo199 Glo179 201 8.50 x 10 

7.39 4.82 + 0.55 

-3 Glo201 Glo124 775 2.61 x 10 

3.59 0.62 - 0.50 

-4 Glo205 Glo149 608 2.69 x 10 

11.7 9.66 ++ 0.58 

-4 Glo207 Glo117 1023 1.02 x 10 

10.0 9.72 ++ 0.54 

-3 Glo208 Glo193 264 1.36 x 10 

8.60 7.31 ++ 0.62 

-2 Glo209 Glo181 438 8.08 x 10 

2.07 0.36 - 0.23 

-4 10.1 7.93 ++ 0.56 


8.15 0.50 - 0.50 

-3 Glo210 Glo206 128 8.67 x 10 

7.65 0.00 0.54 

-3 4.09 0.00 0.50 

Average 404 2.08 x 10 -3 7.56 - - 0.52 

138


Figure 5.6. Spatial distribution of long-finned pilot whales on the beach of Stewart Island, showing the position of the pairs of mother-and-calf 

inferred using likelihood-based approach. Distances are given in units where 1400 units represent approximately 150 metres. Dashed arrows and 

full arrows link mother-and-calf pairs inferred at 80% and 95% level of confidence for ∆-value, respectively. Arrows point at the calf and numbers 

refer to the numerical code of each individual involved in the assigned parentages. Green, red and blue dots indicate mothers, female immature 

and male immature whales, respectively. Black dots represent the rest of the group. (A) includes only the pairs comprising an ‘un-weaned’ calf. (B) 

139 

includes pairs comprising all other immature whales (excluding un-weaned claves).



The analyses of spatial auto-correlation presented here showed that there was no 

correlation between position of the whales on the beach and genetic distances in the 

stranding event of Stewart Island 2003. This is contrary to the assumption that 

kinship bonds are maintained during mass strandings. The pattern of social 

disruption was further confirmed by a striking separation of the pairs of mother-andcalf 

along the beach. In most cases, even the younger calves (‘un-weaned calves’), 

thought to be highly dependant on lactation, were not found close to their mother 

(Figure 5.6). 

5.5.1. Missing mothers 

Interestingly, no potential mother was found for a substantial number of immature 

whales (including six ‘un-weaned calves’) that died during this mass stranding, even 

when considering the less conservative method of parentage assignment (i.e., strictexclusion). 

The absence of some candidate mothers could be explained by 

genotyping errors when using strict-exclusion. However, my estimate of genotyping 

error rate was low enough to suggest that it is probably not the primary explanation. 

The true mothers could also have simply been absent from the group which mass 

stranded. Indeed, many uncertainties remain on the social organisation of long-finned 

pilot whales (see Chapter 4). Dispersal of juveniles from the matrilineal group when 

they approach maturity, could be more frequent than previously thought, as observed 

in transient killer whales of the eastern North Pacific (Baird & Whitehead 2000). In 

this case, some juveniles from the Stewart Island mass stranding could have been 

immigrant which had recently joined the group, explaining the absence of their 

mother among the stranded whales. However, this is unlikely to explain the absence 

of mothers for the ‘un-weaned calves’. Another potential explanation is that several of 

these ‘mothers’ were successfully re-floated while their calves died on the beach. If 

this is confirmed, it would suggest that re-floated whales do not always restrand to 

remain with close kin. Finally, some of these mothers may simply not have stranded 

despite being initially in the same group as their calves. This could be the 

consequence of a pre-stranding social disruption as described above, resulting in a 

separation of kinship bonds before the stranding. An exhaustive sampling of the 

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whales involved in the stranding (including re-floated whales) is critical in explaining 

these missing mothers. 

5.5.2. Potential scenarios explaining social disruption 

The unexpected pattern of social disruption obversed in the stranding raises an 

interesting question; why were these whales separated from their kin during these 

last moments of life, since they are assumed to form tight kinship bonds in the wild? 

The answer to this question is not yet known but several scenarios could help explain 

the observed pattern. The simpliest explanation would be that there is only weak 

spatial autocorrelation with relatedness within free ranging groups of pilot whales and 

thus, questioning the assumption of tight kinship bonds in the wild. In this case, the 

social disruption observed on the shore would simply be a reflexion of the structure of 

a normal group at sea. Such scenario can potentially explain the separation for some 

of the mother and calf pairs. For instance, killer whale calves rarely leave their 

mothers’ side during the first 6 months of life, but later may be accompanied by a few 

other particular members of the social group in the absence of the mother (Haenel 

1986). At time, calves of sperm whales are also known to be separated from their 

mother, staying with other adults (babysitting), in particular during foraging bouts 

(Whitehead 1996). Unfortunately, the strength and temporal pattern of mother and 

calf associations is not well known in long-finned pilot whales, leaving this question 

opened. Conversaly and assuming that kinship bonds are indeed tightly maintained 

in the wild, alternate scenarios could explain this pattern of social disruption in which 

the stranding would be a cause or a consequence of the disruption of kinship bonds. 

Consequence of the stranding in a restricted area - The spatial distribution of 

cetaceans after a mass stranding can show various configurations depending on the 

event and where it takes place (Robson 1984). Sometimes the animals are 

discontinuously distributed along the shore with obvious clusters of individuals 

(Fehring & Wells 1976). In the case of Stewart Island, the whales were linearly 

spread out over a fairly long section of the beach (150 meters) but with only subtle 

clusters of individuals (Figure 5.1). This distribution suggests that if several groups 

had stranded successively (i.e., following a typical mass stranding dynamic), they did 

it close to each other and perhaps, on top of each other. Individuals from different 

141


groups could thus have mixed together in the final stages of the stranding; therefore, 

the pattern of distance-kinship investigated here might not offer a proper reflection of 

the social dynamic of the event. It is unlikely, however, that this effect alone explains 

why some mothers and calves were found at opposite ends of the stranding. 

Consequence of the stranding of the ‘key whale’ - One potential explanation is that 

the initial stranding of the ‘key whale’ was what provoked the social disruption in the 

group. The stranding of this individual could have induced a panic reaction, followed 

by the disorganised stranding of the rest of the group explaining the disruption of 

kinship bonds. Various factors have been suggested as causes of stranding events; 

for example, sick individual, disorientation, inshore feeding, and predator 

harassment. Any of these, depending on the cases, could explain the initial stranding 

of the ‘key whale’. 

Cause of social interactions pre-stranding - Relatively little consideration has been 

given to aggressive or competitive behaviours as causes of strandings. Yet, these 

interactions could potentially be at the origin of the social disruption observed among 

the whales of Stewart Island and, ultimately, a cause of stranding. Indeed, another 

possible scenario is that social disruption occurs before any stranding event (even 

before the stranding of the ‘key whale’) and that instead of being a consequence it 

was the cause of the stranding. Although the analyses presented here failed to detect 

the clustering of “family groups” suggested by Robson, this scenario concurs with his 

observations of mass strandings as well as with some of his interpretations. Robson 

wrote that the first individual to leave the milling herd, or ‘key whale’, “is usually 

driven off by two or three adult females which do so by harassment rather than by 

physical attack” (Robson did not propose any explanation for this behaviour). 

Heading to the shore, the ‘key whale’ then strands possibly due to emotional 

disorientation, inattention to its surroundings and reduced echolocation efficiency. 

These interpretations suggest thus that strong social interactions (harassment) occur 

before any stranding. 

In agreement with this scenario, previous studies suggest that it is within these large 

groups that reproductive behaviours, and thus competition to access mating, are 

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more likely to occur. Indeed, it has been emphasized in Chapter 4 that large stranded 

groups are composed of multiple unrelated matrilines rather than one extended 

matrilineal group. Since mature males seem to rarely mate with their kin, sexual 

activity must occur mostly when several matrilineal groups travel together, that is, in 

large groups. Note that studies on long-finned pilot whales in the North Atlantic have 

found two peaks in the mating (or conception) season of long-finned pilot whales; 

one in early summer and one in autumn (Sergeant 1962, Martin & Rothery 1993). 

Interestingly, these periods of the year (inverted in the Southern Hemisphere) also 

correspond to the peaks of pilot whale mass strandings around New Zealand (Baker 

1981). Unfortunately, it was not possible, in the mass stranding of Stewart Island, to 

confirm the presence of unrelated matrilines based on mitochondrial DNA analyses, 

as all the whales shared the same and most common haplotype in long-finned pilot 

whales from around New Zealand (see Chapter 3 & 4). However, this pattern was 

probably the result of the very low mitochondrial genetic diversity (which obscures the 

differences between unrelated matrilineal groups) rather than the expression of an 

extended matrilineal group. On the other hand, a pattern of unrelated matrilineal 

groups was supported by the large number of rML = 0 kinship pairs. 

5.5.3. Management of future strandings and animal welfare 

My results indicate that proximity on the beach is not a reliable way to identify the 

mother of a calf during a rescue attempt and should not be used as a basis to re-float 

them simultaneously. This mistaken assumption could help to explain the tendency of 

many whales to re-strand even after being re-floated. Note, however, that many restranding 

events may simply be explained with disorientation and weakness of the 

whales resulting from the initial stranding event (Geraci & Lounsbury 1993). Further 

studies, with improved data collection and more detailed observations of behaviour, 

could provide a better understanding of mass strandings and recommendations for 

improved efficiency of rescue efforts and animal welfare practices (e.g., reduced 

distress of mothers and dependent young) during stranding events. 

First, pre-stranding studies are required. Behavioural studies of long-finned pilot 

whale groups in the wild are still lacking. A better understanding of their social 

structure and mating system could provide new insights to the phenomenon of mass 

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stranding. This would allow comparisons of the behaviour of groups just before they 

strand, helping to answer some critical questions. For instance, does milling 

behaviour (typically observed before mass strandings) always result in a mass 

stranding? Or is it just a normal behavioural state like others (such as travelling or 

feeding), but which is sometimes followed by a mass stranding? Whenever possible, 

behavioural and temporal information should also be recorded during the stranding 

as this could be extremely valuable in investigating social dynamics of each event. In 

particular, it would be interesting to know which whale stranded when and with which 

other whale. Are these individuals adult or juvenile, male or female? Do these 

individuals that strand at the same time and/or the same place, share close kinship 

bonds? 

Post-stranding, it would be highly beneficial to collect tissue samples on every animal 

involved in the stranding, including individuals still alive. This would greatly improve 

the outcome of subsequent molecular studies, giving a complete genetic picture of 

the group. An appreciable benefit would be the possibility to re-identify stranded 

whales (using highly variable markers such as microsatellites) in cases of restranding 

in the following days, months or years. This could provide information on 

the success of the re-floating effort, which is still a subject of debate regarding the 

welfare of the animals. On a long-term basis, such data could help to confirm and 

refine the pattern of social organisation as described in Chapter 4. It could also offer 

valuable information on the home range of these pelagic species subject to mass 

stranding. Finally, the deployment of satellite radio-tagging on multiple rescued 

whales would also provide much information on the success of the re-floating effort, 

the social organisation (to determine whether the animals remain associated within 

the same group after being re-floated), and population structure. 

144

Chapter Six: Population structure of rough-toothed dolphins 

6. Evidence of fine-scale population structure in 

rough-toothed dolphins from the Society 

Archipelago, French Polynesia 

A rough-toothed dolphin, Moorea, July 2003. 

145

6.1. Abstract 


Rough-toothed dolphins (Steno bredanensis) are widespread in tropical and 

subtropical waters around the globe and yet little is known about their population 

structure, mating strategies or social organisation. Preliminary analyses of the 

population structure and level of genetic diversity of rough-toothed dolphins in the 

nearshore waters of the Society Archipelago, French Polynesia, were conducted. 

Biopsy samples (n = 65) and dorsal fin photographs (n = 582) were collected 

opportunistically during 189 non-dedicated small-boat surveys around the islands of 

Moorea and Raiatea over three years (2002-04). Samples were sequenced for the 

mitochondrial DNA (mtDNA) control region (450 base pairs consensus) and 

genotyped for 15 microsatellite loci. Photographic and genetic recaptures around the 

same island over different years indicate some level of site fidelity. Furthermore, 

significant genetic differentiation was found between the two islands’ samples, at 

both mitochondrial (FST = 0.60, p < 0.001) and nuclear levels (FST = 0.06, p < 0.005), 

suggesting a local and relatively closed community structure, somewhat similar to 

insular spinner dolphins. However, the level of mtDNA haplotype diversity within each 

island sample was found to be surprisingly low (Moorea, h = 0.457; Raiatea, h = 

0.167). This could be explained by a highly stable social structure, as observed in 

matrilineal cetacean species such as long-finned pilot whales. 

146



Rough-toothed dolphins, Steno bredanensis, are distributed in tropical to warmtemperate 

waters around the world (Miyazaki & Perrin 1994). They are generally 

found in depths > 500 m, where they seem to feed on a variety of fishes and 

cephalopods. Usually described as an open-ocean species (Miyazaki & Perrin 1994), 

recent studies in certain areas indicate that they are also found around ocean islands 

and that they are not necessarily nomadic. Off La Gomera (Canary Islands), around 

Utila in Honduras and in the Hawaiian Archipelago, photographic individual 

recognition surveys (or photo-identification) have shown a high level of individual resightings, 

suggesting the presence of resident populations (Mayr & Ritter 2005, 

Kuczaj & Yeiter 2007, Baird et al. in press). In the Society Archipelago, French 

Polynesia, previous studies have shown that rough-toothed dolphins are commonly 

observed in nearshore waters (Nekoba-Dutertre et al. 1999, Gannier & West 2005), 

which are defined here as waters between 500 m and 10 km from the barrier reef (< 

500 m is considered here as inshore waters). Sightings also occur in offshore waters 

(> 10 km from the barrier reef) but the rate of encounters is lower than in nearshore 

waters (Gannier & West 2005). Thus, although not considered a coastal species, 

sensu stricto, Steno bredanensis appears not to be strictly pelagic, and in some 

areas around the world shows a predominantly nearshore distribution. 

Essentially nothing is known about the social organisation of rough-toothed dolphins. 

They are found in moderate-sized groups, most commonly of 10 to 20 dolphins, with 

for instance, a mean of 12.5 dolphins/group in Hawaii (Webster et al. 2005) and 10.8 

in Tahiti and Moorea, French Polynesia (Gannier & West 2005). The nature of these 

groups is poorly understood, although Mayr & Ritter (2005) reported that off La 

Gomera they show some fluidity in group composition, but a high coefficient of 

association between some individuals of different age class. Baird et al. (in press) 

have recently shown that there are some significant preferred/avoided associations 

between rough toothed dolphins in the Hawaiian Archipelago. Similar patterns are 

reported for bottlenose dolphins, which are known to have a complex social 

organisation with strong social bonds (Connor et al. 2000b). 

147


Studies from different parts of the world suggest that rough-toothed dolphins are not 

particularly abundant (Jefferson 2002): for instance, in the Eastern Tropical Pacific 

(Wade & Gerrodette 1993), the western Indian Ocean (Ballance & Pitman 1998) or 

the Gulf of Mexico (Waring et al. 2006). However, in the Society Archipelago, they 

are the second most frequently observed species after spinner dolphins, Stenella 

longirostris, which could suggest an unusual local abundance of this species (34% of 

dolphin sightings, Gannier 2000). Despite being widely distributed, rough-toothed 

dolphins have proven difficult to study in the wild. Consequently, little is known about 

their ecology and population status, and the species is listed as data deficient on the 

IUCN red list. Potential threats for this species are direct fisheries and by-catch, 

which have been reported at many different places (Miyazaki & Perrin 1994 and 

references therein). Rough-toothed dolphins are also one of the few species of 

Odontocetes which are subject to frequent mass strandings (e.g. Miyazaki & Perrin 

1994, Maigret 1995). 

The high frequency of encounters around the islands of the Society Archipelago 

provided an opportunity to investigate their population dynamics in that region of the 

South Pacific. Here, I report the results of a study on the genetic diversity of roughtoothed 

dolphins from around two islands of this Archipelago, Moorea and Raiatea, 

based on microsatellite genotyping and mitochondrial (mt) DNA sequences obtained 

from biopsy samples. To test the hypothesis of island-specific populations in the 

Society Archipelago, levels of diversity and genetic differentiation were investigated 

between dolphins observed at the two islands. The results from mitochondrial and 

nuclear DNA were also compared to address population dynamics and to test for a 

recent bottleneck. To better understand the phylogeographic structure of roughtoothed 

dolphins, mtDNA sequences from different areas around the world were 

compared to the Society Islands dataset. Genetic analyses were supported by 

photographic sighting – re-sighting data of distinctively marked individuals. 

148

6.3. Materials and Methods 


6.3.1. Study site and sample collection 

Small-boat surveys (n = 189) were conducted over three years (2002-2004) around 

six islands of the Society Archipelago, French Polynesia. The island of Moorea was 

the primary study site (n = 139), while additional surveys were conducted at Tahiti (n 

= 16), Huahine (n = 7), Raiatea-Tahaa (n = 21) and Bora Bora (n = 6) (Figure 2.1). 

The targeted species during these surveys was the spinner dolphin (Stenella 

longirostris) and, therefore, efforts were primarily concentrated in inshore water, i.e., 

within 500 m from the barrier reef and within the lagoon (see Chapter 2). At Tahiti 

and Moorea, rough-toothed dolphins are most often distributed 1.8 to 5.5 km from the 

barrier reef (Gannier & West 2005), although their distribution ranges from 100 m 

from the barrier reef to over 30 km offshore (Nekoba-Dutertre et al. 1999, Gannier & 

West 2005). Therefore, it must be noted that search efforts were not optimal for 

observations of this species. 

After a group of rough-toothed dolphins was spotted, priority was given to the 

collection of skin samples for genetic analyses. The Paxarms system© was 

employed to collect biopsy samples (Krützen et al. 2002). It uses a small biopsy dart 

fired from a modified 22-caliber veterinary capture rifle equipped with variable 

pressure valve. This system was especially developed to assure minimal impact on 

small cetaceans. Biopsies were only collected on individuals presumed to be mature, 

i.e., dolphins with body length > 2 m (Miyazaki & Perrin 1994). Short-term 

behavioural responses to biopsy attempts were recorded and are reported in 

Appendix 3. Samples were preserved in 70% ethanol and stored at -20°C for 

subsequent analyses. 

In addition to biopsy samples, dorsal fin photographs were taken for the purpose of 

individual identification using a digital Olympus E10 (4 megapixel CCD) equipped 

with a 200 mm lens, and a Canon Digital Rebel (6.3 megapixel CMOS) equipped with 

a 300 mm lens. Photographs were graded for quality (only photographs of Q ≥ 3 were 

used, see section 2.3.2 of Chapter 2 and Appendix) and dolphins with deep 

distinctive nicks or deformations on the edge of the dorsal fin were assigned 

149


identification codes (referred to as ‘Distinctively Marked Individuals’ or DMIs, see 

Chapter 2). Each photograph could include more than one dorsal fin. Based on the 

images of DMIs collected during the surveys, a photo-identification catalogue was 

created for each island. These catalogues were compared to find re-sights within and 

between islands. 

In this study, I defined a “group” as a spatial aggregation of animals that appears to 

be involved in a similar activity (e.g., foraging, socialising, resting or travelling, 

(Shane et al. 1986)). However, as with observations off La Gomera (Ritter 2002), 

groups of rough-toothed dolphins observed in the Society Archipelago were often 

found to be dispersed over a fairly large area, making estimation of group sizes 

difficult (especially with sea states of Beaufort scale > 3). On the other hand, large 

groups or aggregations were sometimes composed of distinct subgroups showing 

coordinated swimming (as described by Ritter 2002), for which the size could be 

more accurately estimated. 

6.3.2. Laboratory procedures 

Total DNA was isolated from skin tissue by digestion with proteinase K followed by a 

standard phenol: chloroform extraction method (Sambrook et al. 1989) as modified 

for small samples by Baker et al. (1994). A fragment of the 5’ end of the mtDNA 

control region (d-loop) was amplified using the primers and protocol described in 

Chapter 2. 

Samples were genotyped at 15 microsatellite loci isolated from other cetacean 

species (Table 6.1). The PCR reaction conditions were as reported in Chapter 2. The 

annealing temperature varied depending on the locus (Table 6.1). PCR products 

were run on an ABI 3100 DNA automated sequencer. Data were collected by 

GeneScan v. 3.7, and the fragment size was measure using Genotyper v. 2.5 

(Applied Biosystems Inc.). 

Sex was identified by co-amplification of the male-specific sry gene and the ZFX 

positive control gene, as described by Gilson et al. (1998). 

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Table 6.1. Microsatellite diversity of rough-toothed dolphins from the Society Archipelago. 

Locus n T°A k HO HE 

HWE 

p-value 

Null Allele 

Frequency References 

415/416 50 45 8 0.700 0.726 0.084 0.019 Amos et al. (1993) 

DlrFCB1 53 45 8 0.925 0.743 0.999 0.000 Buchanan (1996) 




GATA98 55 50 3 0.145 0.139 0.131 0.000 Pasbøll et al. (1997) 

GT6 51 61* 10 0.804 0.856 0.172 0.015 Caldwell et al. (2002) 

GT23 55 55 3 0.345 0.344 0.320 0.000 Bérubé et al. (2000) 



MK6 54 50* 4 0.556 0.534 0.529 0.000 Kürtzen et al. (2001) 

MK8 53 50 9 0.755 0.838 0.164 0.025 Kürtzen et al. (2001) 

MK9 55 50 10 0.818 0.815 0.547 0.000 Kürtzen et al. (2001) 



n is the number of screened chromosomes, T°A is the annealing temperature applied during PCR and 

k is the number of alleles found. HO is the observed heterozygosity and HE is the expected 

heterozygosity. HWE p-values refer to the results of the exact tests for deviation of Hardy-Weinberg 

equilibrium. The PCR cycling profile was [93°-2', (92°-30", T°A -45", 72°-50") 15x, (89°-30", T°A -45", 

72°-50") 20x, 72°-3'], except for GT6 and GT51, which were amplified using the profile reported by the 

original paper. 

6.3.3. Microsatellite loci statistics 

Replicate samples were identified by comparison of genotypes using the program 

Cervus v. 2.0 (Marshall et al. 1998), allowing for two loci with inexact matches. The 

probability of identity (PID) per locus and over all loci was calculated using GenAlEx v. 

6 (Peakall & Smouse 2005), from the formula of Paetkau & Strobeck (1994). See 

Chapter 2, section 2.3.6, for a definition of the PID. Based on the low PID (see results), 

samples with matching genotypes were assumed to be replicates and were removed 

from subsequent analyses. 

The exact test based on Markov chain iterations implemented in the software 

Arlequin v. 3.01 (Excoffier et al. 2005) was used to test for deviations from Hardy- 

Weinberg equilibrium (HWE) for each locus by population (Guo & Thompson 1992). 

The program Genepop v. 3.4 was used to test for linkage disequilibrium between loci 

151


within population (Raymond & Rousset 1995). To detect the presence of null alleles 

and estimate frequencies, the maximum-likelihood approach implemented in ML- 

Relate was used (Kalinowski et al. 2006). Bonferroni corrections (Rice 1989) were 

applied to all pairwise test results to adjust for multiple comparisons. 

The level of microsatellite loci diversity was estimated for each population and overall 

as, observed heterozygosity (HO), expected heterozygosity (HE), inbreeding 

coefficient (FIS), mean number of alleles per locus (K) and allelic richness, using the 

program FSTAT v. 2.9.3.2 (Goudet 2001). Allelic richness takes into account unequal 

sample size using the rarefaction method. 

6.3.4. Mitochondrial DNA diversity and haplotype network 

Mitochondrial control region sequences were aligned using Sequencher TM v. 4.1.2, 

(Genes Codes Co.) and edited manually. Variable sites and unique haplotypes were 

identified using MacClade v. 4.0 (Maddison & Maddison 2000). The software Arlequin 

was used to estimate standard indices of genetic variation, i.e., nucleotide diversity, 

π, and haplotype diversity, h. 

Table 6.2. Information on samples of rough-toothed dolphins collected outside French Polynesia. 

Code 


sampling 

Collection date Location 

Haplotype 

code 

Source 

Sbr03Sa01 Biopsy 24/09/2003 Samoa Sbr03FP12 (1) 



Sbr03Sa04 Biopsy 25/09/2003 Samoa h6 (1) 

J02OK01 Market sample January 2002 Japan Sbr00FP02 (2) 

JE03OK13 Market sample March 2003 Japan h7 (2) 

Sbre10936 Stranding 01/10/1998 eastern Pacific h8 (3) 

Sbre138 Stranding 14/01/1991 eastern Pacific h9 (3) 

Sbre18431 Biopsy 02/11/2000 eastern Pacific h10 (3) 

Sbre18126 Biopsy 23/08/2000 eastern Pacific h11 (3) 

Sbre9838 Stranding 03/05/1996 Atlantic h12 (3) 




Sources: 

(1): Olavarría et al. (2003) 

(2): ‘Whale-meat’ market surveys, C.S. Baker, The University of Auckland 

(3): Southwest Fisheries Science Center (La Jolla, CA, U.S.A) 

152


A median-joining network was generated to infer phylogenetic relationships among 

the mtDNA haplotypes, using the program Network v. 4.2 (Bandelt et al. 1999). 

Sequences from four other areas around the world (Japan, Samoa, eastern Pacific 

Ocean and Atlantic Ocean) were added into the network to provide a worldwide 

perspective of rough-toothed dolphin mtDNA diversity in the Society Archipelago. 

Source and origin of these additional samples are listed in the Table 6.2. Note that 

samples from Japan (n = 2) were obtained from ‘whale-meat’ market surveys, and, 

as such, their exact origin is uncertain. 

6.3.5. Kinship and population structure 

In general, more than one individual was sampled from each group of rough-toothed 

dolphins encountered during this study. Depending on the social structure of the 

species under investigation, such a sampling design can result in an overrepresentation 

of closely related individuals in each sample of the dataset, in 

particular if a limited number of groups are represented. Subsequently, this bias can 

lead to an over-estimation of population differentiation (Hansen et al. 1997). To take 

this potential bias into account, the pairs of individuals with a high coefficient of 

relatedness were identified in each island sample. Pairwise coefficients of 

relatedness (rML) were calculated using the maximum-likelihood estimate derived 

from the software ML-Relate (Kalinowski et al. 2006). A cut-off value of r ≥ 0.5 was 

used to identify closely related pairs (i.e., first-order relatives). Analyses of population 

genetic differentiation were conducted independently, using all individuals and with 

kin removed. 

Genetic differentiation among island samples was then estimated using analysis of 

molecular variance (AMOVA) as implemented in Arlequin. For mtDNA sequences, 

the differentiation was estimated using conventional FST (based on haplotype 

frequencies) and its nucleotide equivalent, ΦST, which incorporates information on the 

genetic distance between haplotypes. Kimura 2-parameter corrected distance was 

used for ΦST analysis. For microsatellites, subdivision was assessed employing allele 

frequencies (FST) and Slatkin’s microsatellite-specific FST analogue, RST. Significance 

was tested by 20,000 permutations of the original datasets. 

153


6.3.6. Testing for recent genetic bottleneck 

MtDNA and microsatellite variation were investigated to detect the signs of a recent 

bottleneck event. For mtDNA, I used neutrality tests implemented in Arlequin, while 

for microsatellite loci, I used two different methods implemented in the program 

Bottleneck v. 1.2.02 (Cornuet & Luikart 1996) and M_P_Val and Critical_M (Garza & 

Williamson 2001). See Chapter 2 for details on these methods and parameters used. 

6.4. Results 


Rough-toothed dolphins were encountered on 23 occasions during this study: 19 

encounters at Moorea, two encounters at Raiatea, and one encounter each at 

Huahine and Bora Bora. Group size ranged from four to more than 50 individuals per 

group. The average group size was not calculated, since the visual estimates were 

often unreliable (uncertainties existed for 12 of the 23 encounters). However, the size 

of 20 sub-groups was estimated with accuracy, resulting in an average 5.6 +/- 1.9 

individuals per sub-group. On five occasions, the dolphins were observed within 500 

m of the barrier reef (three times at Moorea; one time each at Raiatea and Huahine). 

A total of 65 biopsy samples were collected (51 at Moorea, 13 at Raiatea and 1 at 

Huahine) and 406 photographs of Q ≥ 3 were taken (for a total of 582 dorsal fins). 

Inclement weather prevented pictures being taken of the groups observed at Bora 

Bora and Huahine. 

6.4.2. Photo-identification 

From 2002 to 2004, 55 DMIs were identified at Moorea, while in 2004, eight DMIs 

were identified at Raiatea. There were no matches of DMIs between the two islands. 

An additional 45 individuals were distinguished from marks on their dorsal fins but 

either these marks were minor (requiring excellent quality photographs to re-identify 

the individual with certainty) or the photograph was of poor quality. Overall, 45% of 

the dorsal fins showed highly distinctive marks (based on Q ≥ 3 photographs). 

154


Although it was difficult to distinguish between adults and juveniles based on 

photographs, it appears that most of the largest individuals in the population 

(approximately 90%) present some level of unique marking on their dorsal fin. 

At Moorea, the rate of re-sighting per DMI, based on photographic data, ranged from 

1 to 4 sightings across the 16 encounters. A total of 14 DMIs were seen on more than 

one occasion. Among them, 12 were re-sighted in different years but none were seen 

in all three years. A discovery curve was plotted based on the cumulative number of 

newly identified DMIs across these 16 surveys (Figure 6.1). It showed no sign of an 

asymptote, with new DMIs still being identified toward the end of the study. For 

example, 13 new DMIs were identified in the last group observed in 2004. 

Figure 6.1. Discovery curve based on the cumulative number of new Distinctively Marked Individuals 

(DMIs) identified at Moorea from 2002 to 2004 (line), and number of DMIs identified per survey (bars). 

6.4.3. Microsatellite diversity and sex identification 

Samples were genotyped at 8 to 15 loci each. For all 15 loci, the PID was 1.2 x 10 -15 . 

Genotype comparison revealed that six pairs of samples were identical matches and 

one pair had a single mismatching locus. The six pairs were compared for at least 12 

loci, providing a low average PID (Table 6.3) and, therefore, were considered re- 

samples of the same individual. Similarly, the pair with one mismatching locus had a 

155


very low PID across 14 shared loci, indicating that the mismatching locus was 

probably due to a genotyping error. These two samples were also assumed to come 

from the same individual, and information at the mismatching loci was not considered 

for subsequent analyses. As expected, all seven sample pairs also matched for 

mtDNA haplotype and sex. Thus, a total of 58 individuals were represented in the 

sample set, five of which were sampled two times and one was sampled three times. 

Three of these re-samplings occurred in different years: two at Moorea, and one with 

initial sampling at Huahine and re-sampling at Raiatea the following year. The 

individual sampled three times was sampled on three different days during the same 

year at Moorea. Sex-based PCR revealed that 23 females and 35 males were 

sampled in total (Table 6.4). This was not significantly different from a theoretical 1:1 

sex ratio (χ² = 2.48, p > 0.05). 

Table 6.3. List of samples identified as genetic re-sampling through comparison of microsatellite 

genotypes. PID refers to the probability of identity. 

Sample 1 Sample 2 

# Matching 

loci 

# Mismatching 

loci 

Sbr03FP12 Sbr04FP40 12 0 6,78139E-11 

Sbr03FP17 Sbr04FP05 13 0 3,32552E-13 

Sbr03FP18 Sbr04FP04 15 0 1,21758E-15 

Sbr04FP06 Sbr04FP17 13 0 6,38918E-13 

Sbr04FP06 Sbr04FP21 12 0 1,33927E-12 

Sbr04FP17 Sbr04FP21 15 0 1,21758E-15 

Sbr04FP31 Sbr04FP35 14 1 - 

Two island samples, or ‘populations’, were considered for subsequent analyses: 

Moorea (n = 46) and Raiatea (n = 12). All loci were polymorphic (three to 16 alleles), 

overall (Table 6.1) and within population, except GATA98 which was monomorphic at 

Raiatea (not shown). Presence of null alleles was detected for some loci; however, 

frequencies were low (> 0.025; Table 6.1), except for GT39 (null allele frequency = 

0.104) which also showed deviation from HWE. This locus was not considered for 

subsequent analyses. All other loci did not deviate from HWE, and, after adjustment 

for multiple comparisons, there was no evidence of linkage disequilibrium between 

pairs of loci within and across populations. 

PID 

156


Table 6.4. Sex identification and genetic diversity for mitochondrial (mt) DNA control region and 

microsatellite loci. 

n 

Male/ 

Female 

Microsatellite mtDNA 

HO FIS K 

Allelic 

richness 

# 

haplotypes 

Moorea 46 25/21 0.681 -0.023 7.87 4.995 4 

Raiatea 12 10/2 0.723 -0.057 4.47 4.171 2 

h π (%) 

0.457 +/- 

0.078 

0.167 +/- 

0.134 

0.88 +/- 

0.50 

0.30 +/- 

0.22 

0.624 +/- 1.10 +/- 

Overall 61 35/21 0.678 0.012 7.93 4.985 5 

0.056 0.60 

n is the number of individuals. For microsatellite, HO is the observed heterozygosity, FIS is the 

coefficient of inbreeding and K is the mean number of alleles per locus across 15 loci. For mtDNA, h is 

the haplotype diversity and π is the nucleotide diversity. 

Levels of microsatellite diversity were similar for the two populations with an average 

observed heterozygosity of 0.678 (Table 6.4). Allelic richness, based on a minimal 

sample size of seven individuals, was slightly higher for Moorea than Raiatea. 

However, due to the small sample size at Raiatea, the mean number of alleles per 

locus K was larger at Moorea (Table 6.4). The overall FIS values were negative for 

both island samples, but not significantly different from expectation. 

6.4.4. Mitochondrial DNA diversity 

All samples were sequenced for a 450 bp consensus fragment of the mtDNA control 

region. Among samples from the Society Archipelago, a total of 15 variable sites 

were identified (all transition substitutions), which defined five unique haplotypes 

(Table 6.5). Overall, haplotype diversity was 0.624 +/- 0.056 and nucleotide diversity 

was 1.10% +/- 0.60%. The level of mtDNA diversity was higher at Moorea than 

Raiatea (Table 6.4). The most-common haplotype for Moorea was haplotype 

Sbr02FP03 which was represented by 72% of the individual samples. At Raiatea, the 

most-common haplotype was haplotype Sbr03FP12, representing 92% of the 

samples. Neither haplotype Sbr02FP03 nor haplotype Sbr03FP12 were found in 

Raiatea or Moorea, respectively. 

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Table 6.5. Mitochondrial DNA haplotypes (L-strand control region, 5’ to 3’ sequence) in rough-toothed 

dolphins of the Society Archipelago, showing variable sites with reference to haplotype Sbr00FP01. 

Haplotype frequencies of the samples collected around Moorea and Raiatea are indicated on the right; 

the frequencies of males and females for each haplotype are given in brackets. 

2 8 1 2 2 2 2 2 2 3 3 3 4 4 4 Haplotype frequencies 

4 4 0 4 4 7 7 7 8 6 7 7 3 3 3 

6 3 7 1 2 9 1 9 0 1 1 3 5 Moorea Raiatea 

(male+female) (male+female) 

haplotypes 

Sbr00FP01 C C C A T T C T A C T T C G C 8 (5+3) - 

Sbr00FP02 T T T G C . . . G T C . T A T 4 (2+2) 1 (1+0) 

Sbr02FP02 T . . G . C T C G . C C T A T 1 (0+1) - 

Sbr02FP03 T T T G C C . . G T C . T A T 33 (17+14) - 

Sbr03FP12 . . . G . . . . . . C . . A . - 11 (9+2) 

Ten more haplotypes were found when sequences from other locations around the 

world were included (Table 6.2), for a total of 30 variable sites. The median-joining 

network showed no obvious phylogeographic structuring (Figure 6.2). However, 

Atlantic samples were very different. Overall, haplotypes from the Society 

Archipelago were found to be largely distant from one another (with the exception of 

haplotypes Sbr00FP02 and Sbr02FP03), within and between island samples, with an 

average of 7.5 mutational steps between them. Matching haplotypes were found 

between Samoa and French Polynesia (Sbr03FP12) and Japanese ‘whale-meat’ 

market and French Polynesia (Sbr00FP02). 

158


Figure 6.2. Inferred genealogical relationship among mtDNA haplotypes (n = 15) from worldwide 

rough-toothed dolphins. The diameter of each circle is proportional to the number of individuals found 

for the haplotype. Black dots represent inferred node haplotypes not found in the samples. Numbers 

on the branches indicate the number of mutational steps. 

6.4.5. Kinship and population structure 

Before conducting the analyses of population structure, close relatives within the 

dataset were inferred based on microsatellite information. Maximum-likelihood 

estimates of relatedness indicated that 12 pairs of individuals from the same island, 

and three pairs from different islands, had a pairwise coefficient ≥ 0.5 (Table 6.6). As 

expected under the assumption that these individuals are first-order relatives (i.e., 

parent/offspring), all the pairs made up of two females shared the same mtDNA 

haplotype. Within island samples, three pairs were male/female, four pairs were 

male/male and 5 pairs were female/female. Overall, 54% of the individuals involved 

in these 12 pairs were females (46% were males). Although, this is contrary to the 

sex-ratio in the total sample (1.7:1, male/female), these proportions are not 

significantly different from each other (χ² = 1.45, p > 0.05). None of the three pairs 

159


between islands were composed of two females (one pair of female-male and two 

pairs of male-male, Table 6.6). In order to eliminate one individual from each of these 

pairs, I had to remove seven samples from Moorea and two samples from Raiatea, 

giving a new sample size of 39 and 10, respectively. 

Table 6.6. List of the pairs of individuals showing a high-level of microsatellite relatedness, including 

information on sex class and mtDNA haplotype. rML stand for the maximum-likelihood coefficient of 

relatedness. Cells in grey indicate individuals sampled at Raiatea, while the others represent the 

individuals sampled at Moorea. 

Individual 1 Sex 

mtDNA 

haplotype 

Individual 2 Sex 

mtDNA 

haplotype 

Sbr04FP10 Male Sbr02FP03 Sbr04Ra33 Male Sbr03FP12 0.61 

Sbr04FP34 Female Sbr03FP12 Sbr04Ra36 Male Sbr03FP12 0.60 

Sbr04FP07 Male Sbr02FP03 Sbr04Mo17 Female Sbr02FP03 0.55 

Sbr04FP16 Female Sbr02FP03 Sbr04Mo17 Female Sbr02FP03 0.52 


Sbr02FP04 Male Sbr00FP02 Sbr04Mo05 Male Sbr02FP03 0.50 


Sbr03FP08 Female Sbr02FP03 Sbr04Ra36 Male Sbr03FP12 0.50 







Sbr04FP33 Male Sbr03FP12 Sbr04Ra37 Female Sbr03FP12 0.50 

Based on this reduced dataset, the AMOVA showed highly significant differentiation 

in mtDNA (FST = 0.60, p < 0.001; ΦST = 0.56, p < 0.001) and microsatellite (FST = 

0.06, p < 0.005; RST = 0.07, p < 0.05) variation among the two island samples. The 

complete dataset yielded similar results (not shown). Unfortunately, too few females 

were sampled at Raiatea (n = 2) to allow tests for sex-bias dispersal detection, such 

as the ones implemented in the program FSTAT (see section 2.3.7, Chapter 2). 

Similarly, the maximum-likelihood coalescent approach to estimate migration rates 

(using the software Lamarc, Kuhner 2006) did not yield satisfactory results because 

of the small number of haplotypes and samples (results not shown). 

rML 

160

6.4.6. Bottleneck tests 


None of the tests based on mtDNA or microsatellite loci detect evidence of a recent 

bottleneck event in the sample from Moorea (Table 6.7). On the other hand, 

significant results were found for the Tajima’s D, the Wilcoxon test (under TPM) and 

the M-Ratio test (when θ = 1) at Raiatea (Table 6.7). 

Table 6.7. Summary statistics of various tests to detect a bottleneck effect based on mitochondrial 

DNA control region and 14 microsatellite loci. n is the number of individuals. p < 0.05, *; p > 0.05, ns . 


mtDNA microsatellite 

Tajima’s test Fu’s test 

Wilcoxon test 

(p-value) 

M ratio 

n D p-value F p-value SMM TPM M θ = 1 θ = 10 θ = 50 

Moorea 46 0.414 0.719 ns 6.931 0.983 ns 0.982 ns 0.094 ns 0.821 ns ns ns 

Raiatea 12 -1,983 0.008* 3.113 0.924 ns 0.855 ns 0.018* 0.699 * ns ns 

6.5.1. Rough-toothed dolphins in the Society Archipelago 

Steno bredanensis was found to be a commonly observed species around the main 

islands of the Society Archipelago, with groups observed around the islands of 

Moorea, Raiatea, Huahine and Bora Bora. This confirms observations made by 

Gannier (2000) and Nekoba-Dutertre (1999). However, the number of encounters 

during the course of this study was relatively low in comparison to the number of 

surveys conducted (23 encounters during 189 surveys). This result can be explained 

by the fact that research effort was mostly concentrated in the passes or within 500 m 

from the barrier reef of the islands, searching primarily for spinner dolphin groups 

(Chapter 2). Groups of Steno bredanensis were mostly encountered further offshore 

where the effort was less intensive. 

A large proportion of the rough-toothed dolphins showed distinctive marks on their 

dorsal fin, apparently from intra-specific interactions and shark bites. This contrasts 

with spinner dolphins of the same area (Chapter 2), and is more similar to bottlenose 

161


dolphins in general (Scott et al. 1990). A similar proportion of marked individuals was 

found in rough-toothed dolphins of the Hawaiian Archipelago (Baird et al. 2003), 

illustrating the strong potential of photo-identification surveys on this species. 

In the Society Archipelago, rough-toothed dolphins seem to show preferences for 

coastal insular waters (Nekoba-Dutertre et al. 1999, Gannier & West 2005), 

contrasting with the usual description made of their primary habitat, i.e., pelagic 

waters (Jefferson 2002). In other species of delphinids, such a pattern of preference 

for nearshore habitat is thought to have led to fine-scale population structuring, 

underlying, in some cases, conservation issues (e.g., Hoelzel et al. 1998b, Pichler et 

al. 1998, Sellas et al. 2005). Although the conservation of Steno bredanensis is 

currently not of concern on a species-wide level, limited knowledge of its status and 

ecology make it necessary to investigate the populations from around these islands 

in further detail. 

6.5.2. Fine-scale population structure 

The analyses of mtDNA and microsatellite loci presented here reveal strong genetic 

differentiation between rough-toothed dolphins sampled around two islands 

separated by only 150 km, Moorea and Raiatea, rejecting the hypothesis of panmixia. 

One potential concern with this result was that the detected population differentiation 

reflected a high degree of relatedness among the sampled animals rather than a true 

population structure. However, that genetic differentiation was found to persist after 

closely related individuals were removed from the analysis, although the sample size 

was relatively small for Raiatea. Furthermore, tests for significant FIS values did not 

reveal evidence for inbreeding in any of the samples. 

Differentiation at both maternal and biparentally inherited markers indicates that the 

restricted gene flow is not due solely to female philopatry. This fine-scale population 

structure could suggest that rough-toothed dolphins from around these islands form 

stable resident populations or “communities”. Results from photo-identification 

surveys and genetic re-sampling events support this pattern since several individuals 

were “recaptured” across the years. This is concordant with high site-fidelity reported 

in the Canary Islands and Hawaiian Islands based on photo-identification data (Mayr 

162


& Ritter 2005, Webster et al. 2005). Inter-annual re-sighting of DMIs at Moorea was 

also previously reported by Nekoba-Dutertre et al. (1999). Although the discovery 

curve based on the cumulative number of DMIs identified at Moorea during the 

current study did not asymptote, this can simply be due to the limited number of 

encounters (n = 19) rather than the demographic openness of the population. In 

comparison, the discovery curve for the small community of spinner dolphins around 

the same island reached asymptote after only 25 encounters (Chapter 2). Additional 

surveys are necessary to determine with certainty if the population/community of 

rough-toothed dolphins sampled around Moorea is geographically closed, and if so, 

of what size. At this stage, the real boundaries of the populations investigated here 

remain unknown. The dataset was too limited to do an abundance estimate for these 

communities but the relatively high level of re-sighting at Moorea (25% of the DMIs) 

compared to the low number of encounters suggest that this community of roughtoothed 

dolphins might be relatively small (in the order of a few hundred individuals at 

most). 

6.5.3. Sex-biased dispersal 

The level of mtDNA differentiation between Moorea and Raiatea was surprisingly 

high, illustrating a very low rate of recent female gene flow. In comparison, 

microsatellite differentiation was not as marked, although still significant. Such a 

pattern has often been interpreted as a consequence of male biased gene flow in 

cetacean populations (e.g., Escorza-Trevino & Dizon 2000). Although this is a 

possibility, it could also be explained by the difference in mutation rates between 

mtDNA and microsatellite loci (Hedrick 1999). Furthermore, estimates of effective 

migration rate based on F-statistics are subject to uncertainties in non-equilibrium 

populations, and caution is required before inferring demographic trends from these 

values (Whitlock & McCauley 1999). However, male-biased dispersal appears to be a 

common feature in cetacean populations (e.g., Möller & Beheregaray 2004, Cassens 

et al. 2005) and in mammals in general (Greenwood 1980). Therefore, it would be 

interesting to examine more samples from Raiatea’s rough-toothed dolphins and 

conduct marker-specific tests (e.g., Goudet et al. 2002) to assess this (see Chapter 

2). 

163


6.5.4. A spinner dolphin community structure with a pilot whales 

social organisation? 

The fine-scale population structure described here in rough-toothed dolphins from the 

Society Archipelago provides an interesting parallel to the communities of spinner 

dolphins investigated in Chapter 2. For the latter, genetic differentiation was also 

observed between island samples while gene flow was biased toward males. I was 

unable to determine if rough-toothed dolphins form island-specific communities 

regardless of the distances between islands, as observed for spinner dolphins 

(Chapter 2). However, the re-sampling at Raiatea of an individual initially sampled at 

Huahine could illustrate a pattern of regional communities rather than insular 

communities. It can be noted that the two species appear to take advantage of 

inshore and nearshore insular waters for different reasons: spinner dolphins use 

them as safe resting areas (mainly in the shallow inshore and lagoon waters), while 

rough-toothed dolphins are more likely to be there for increased levels of food 

resources along the shelf (i.e., in the deepest nearshore waters). 

One striking difference between communities of the two species was the level of 

mitochondrial haplotype diversity: 18 and 12 unique haplotypes were found among 

59 and 16 individuals in the spinner dolphins’ communities at Moorea and Raiatea, 

while only four and two unique haplotypes were identified among 46 and 12 roughtoothed 

dolphins sampled around the same islands, respectively. Several scenarios 

could potentially explain the low level of mtDNA haplotype diversity observed in 

rough-toothed dolphins: (1) a greater demographic isolation than that of spinner 

dolphins; (2) a bottleneck effect; or, (3) a matrilineal social organisation. 

(1) Greater demographic isolation – In such a case, a low level of immigration as a 

source of variability would lead to a greater effect of genetic drift within each 

community of rough-toothed dolphins. However, rough-toothed dolphins, like spinner 

dolphins, have a high potential for long distance movements, and it seems unlikely 

that environmental factors, solely, could reduce gene flow in one of these species 

and not the other. 

164


(2) Bottleneck effect – Low mtDNA diversity could also be the result of a bottleneck 

event, due to recent colonisation of an insular habitat. The absence of 

phylogeographic pattern and the large genetic distance between mtDNA haplotypes 

indicate that the structuring in the studied area is probably fairly recent. However, no 

significant evidence for a bottleneck was found within Moorea sample. At Raiatea, 

signs of a potential bottleneck were detected at the mtDNA and microsatellite level, 

but the sample size was small (n = 12). I do not know if the presence of a few close 

relatives in such a small sample could affect the results of these tests. Examination of 

more individuals is probably required before drawing any conclusion on this point. 

(3) Social organisation - An alternative explanation is that the small scale genetic 

structure and low mtDNA diversity described here are the result of a highly stable 

social organisation. It has been shown that social organisation can have a profound 

impact on population genetic structure (e.g., Storz 1999). Notably, socially defined 

population structure has the general effect of increasing the importance of genetic 

drift relative to other evolutionary forces. In cetaceans, unexpectedly low levels of 

mtDNA diversity were described amongst species thought to have a matrilineal social 

organisation (Whitehead 1998); this is, for instance, the case for long-finned pilot 

whales (see Chapters 4 and 5). Further demographic and genetic studies could help 

clarify if rough-toothed dolphin’s social organisation is also matrilineal or if it follows a 

fission/fusion model with males forming stable alliances, as observed in some 

populations of bottlenose dolphins (Connor et al. 2000b). It is worth noting that 

rough-toothed dolphins show a propensity to mass strand (Jefferson 2002); and 

although the reasons for mass strandings are probably multiple, it is largely accepted 

that they somehow involve tight social bonds among individuals (Perrin & Geraci 

2002). Interestingly, the primary species involved in mass strandings (sperm whales 

and long-finned pilot whales) are thought to be matrilineal. 

6.5.5. Conclusions 

This study has revealed a surprising degree of local site fidelity suggesting a 

community structure among rough-toothed dolphins sampled in the Society 

Archipelago. Most importantly, the detection of this fine-scale population structure 

raises new concerns for the conservation and management of these populations. 

165


Indeed, although the limits of the two communities/populations sampled at Moorea 

and Raiatea are still unclear, my results indicate that they should be considered as 

distinct management units. Rough-toothed dolphins are known in some places to be 

caught in drive fisheries (for example in Japan) and to be victims of by-catch 

(Miyazaki & Perrin 1994, Monteiro et al. 2000). In the South Pacific, studies on roughtoothed 

dolphins have only been conducted in the Society Archipelago of French 

Polynesia, which was referred to as a hotspot for this species (e.g., Baird et al. 2003). 

However, the tropical Pacific is still an under-studied area and further surveys in 

other archipelagos could reveal that rough-toothed dolphins are common throughout 

the nearshore shore waters of these islands. 

166

Chapter Seven: General Discussion and Future Work 

7. General Discussion and Future Work 

7.1. Overview 

This thesis has provided new insights into the evolutionary history, population 

structure and social system of spinner dolphins, short-finned pilot whales, long-finned 

pilot whales and rough-toothed dolphins. Although intensive research efforts were 

previously dedicated to some of these species (e.g., Bloch et al. 1993, Heimlich- 

Boran 1993, Norris et al. 1994), they remain relatively unknown in comparison to 

most species of large terrestrial mammals as well as to some other cetaceans, i.e., 

bottlenose dolphin and killer whale. Here, to overcome some of difficulties typically 

encountered when studying cetaceans, I have combined demographic and molecular 

approaches, and I also took advantage of previous studies and data collections. In 

Chapter 2, I used molecular and photo-identification data together, to understand the 

community dynamic of insular spinner dolphins on a demographic and evolutionary 

time scale. Chapter 3 used pilot whales mitochondrial DNA obtained from many 

different sources (e.g., biopsy samples, mass strandings, ‘whale-meat’ market 

products, GenBank sequences), and allowed me to address questions on a 

worldwide geographical scale. Chapters 4 and 5 combined kinship information 

(based on molecular analyses) and observational/behavioural data from mass 

strandings to investigate the social system of long-finned pilot whales. It also allowed 

the testing for the first time, of a hypothesis on the social dynamics of mass 

strandings. Finally, in Chapter 6, I used data similar to Chapter 2 to investigate 

communities of rough-toothed dolphins, although given the opportunistic nature of 

data collection the analyses did not reach the same level of detail as the former 

chapter. It is therefore very promising for future research that substantial information 

was obtained from this study, especially considering the status usually given to 

rough-toothed dolphin of a pelagic and difficult to study dolphin species. 

As discussed in Chapter 1, this thesis project was part of a larger research program 

aimed at investigating the genetic diversity and population structure among 

167


communities of species of dolphins with contrasting social systems and habitat use. 

While I focused my work on four species, the overall program included studies on 12 

species or subspecies. At this stage, it is useful to consider if the results of this thesis 

have offered new insights to answer the objectives presented at the beginning of the 

manuscript. 

- Objective 1 and Objective 2: Investigate comparative genetic structure of 

dolphin societies with different life history attributes and habitat specialisation, 

and in relation to predictions concerning the genetic consequences of social 

systems on the structure of local communities. Although none of the previous 

chapters directly aimed at comparing the four species under investigation between 

each other, several findings have shown interesting parallels and discrepancies. For 

example, insular genetic structure was observed in spinner dolphins as well as, and 

less expectedly, in rough-toothed dolphins; however, spinner dolphins showed a 

much higher level of mtDNA diversity than rough-toothed dolphins, suggesting 

different social systems (Table 7.1). I also found genetic evidence that social 

organisation of long-finned pilot whales is more complex than previously assumed, 

involving multiple matrilineal groups associating in mass strandings. This supports 

findings in Nova Scotia where groups of long-finned pilot whales are observed to 

change in composition over days, as observed in spinner dolphins. Note, however, 

that the two species show very different habitat preferences and, probably, social 

structure. Another interesting parallel was found, with the possible matrilineal social 

structure of rough-toothed dolphins as suggested by low mtDNA variability and 

comparable to the genetic diversity of other matrilineal species such as pilot whales. 

The results presented in this thesis have provided new information on the genetic 

structure of the four species, contributing to the ongoing research aiming at 

understanding the evolutionary forces responsible for contemporary genetic structure 

of dolphins’ communities. 

168

Table 7.1. Comparison of genetic parameters obtained from the four species investigated here at different study sites. bp: base pair. 

Values shown for pilot whales species are based on a corrected dataset (see Chapter 3). k is the average number of alleles per locus. p < 

0.001, ***; p < 0.01, **. 

Microsatellite 

mtDNA control region sequences 

FST 

k 

# Loci 

ΦST 

FST 

haplotype 

diversity 

# nucleotide 

haplotypes diversity (%) 

Sample 

Size 

Study Range 

Species 

bp 


- 

10.4 

12 

- 

- 

0.93 +/- 0.01 

1.62 +/- 0.84 

18 

555 

70 

Moorea 

- 

7.50 

12 

- 

- 

0.47 +/- 0.08 

0.64 +/- 0.37 

4 

555 

34 

Tahiti 

Spinner dolphin 

0.029*** 

11.9 

12 

0.110*** 

0.135*** 

0.90 +/- 0.02 

1.48 +/- 0.77 

27 

555 

146 

Society 

- 

9.07 

12-20 

- 

- 

0.508 +/- 0.095 

0.23 +/- 0.19 

8 

345 

337 

New Zealand 

Long-finned pilot 

whale 

- 

- 

- 

0.420*** 

0.468*** 

0.710 +/- 0.044 

0.31 +/- 0.23 

10 

345 

434 

Worldwide 

- 

- 

- 

- 

- 

0.873 +/- 0.022 

0.82 +/- 0.49 

3 

345 

85 

Japan 

- 

- 

- 

- 

- 

0.604 +/- 0.076 

0.35 +/- 0.27 

11 

345 

35 

South Pacific 

Short-finned pilot 

whale 

- 

- 

- 

0.471*** 

0.319*** 

0.899 +/- 0.013 

0.87 +/- 0.51 

14 

345 

134 

Worldwide 

- 

7.87 

15 

- 

- 

0.457 +/- 0.078 

0.88 +/- 0.50 

4 

450 

46 

Moorea 

Rough-toothed 

dolphin 

0.06** 

7.93 

15 

0.56*** 

0.60*** 

0.624 +/- 0.056 

1.10 +/- 0.60 

5 

450 

65 

Moorea/Raiatea 

169


- Objective 3: Investigate whether dolphin groups and communities are 

structured strictly along a single maternal lineage or whether the social groups 

include multiple maternal lineages. Results have shown that none of the species 

investigated here are strictly matrilineal in their social structure. While this was 

expected for spinner dolphins (Chapter 2), it was not expected for long-finned pilot 

whales based on results from previous genetic studies (Chapter 4). However, 

parentage and relatedness analyses conducted here confirmed that a least some 

females as well as males of this species remain with their mother after reaching 

maturity. Therefore, matrilineality, although not strict, represents a strong component 

of long-finned pilot whales social system. There was no obvious expectation for 

rough-toothed dolphins in regards to this question. However, while the analyses 

revealed the presence of multiple maternal lineages within groups, the mtDNA 

diversity potentially suggested, as mentioned above, some level of matrilineal social 

structure in this species. 

- Objective 4: Investigate whether mating is directed outside of matrilineal 

groups through permanent emigration of males, as characteristic of most 

mammals, or whether mating occurs by temporary social fusion or 

interchange. I found that neighbouring communities of spinner dolphins were 

genetically different from each other at the mitochondrial and nuclear level. This 

suggests that spinner dolphins are more likely to mate with members of their own 

community. The pattern of fission/fusion observed in group composition further 

suggests that mating probably occurs during temporary fusion. However, much 

remains to be learned about the social system of this species within the community. 

Notably, the nature of long-term association observed between individuals of the 

same sex and individuals of different sexes still needs to be explained. Although 

mating is thought to occur largely within an island community, my analyses indicated 

some male-biased dispersal between communities of spinner dolphins, as typically 

observed in other species of mammals, including other cetaceans (see Chapter 1). 

Parentage analyses within mass strandings of long-finned pilot whales confirmed that 

mature males rarely mate with females of their own group. The detection of several 

maternal lineages within the mass strandings further suggests that groups at sea 

170


(and especially the large ones) do not represent stable behavioural units. Therefore, 

mating in this species is more likely to occur during temporary social interchange. 

Here again, much work remains to be done on the social system of pilot whales. For 

example, there is no clear evidence so far to discount some level of male and female 

dispersal from their maternal group, even though this is expected to be low. 

- Objective 5: Investigate whether some dolphins have adapted to inbreeding 

as a strategy for maintaining social cohesion or because of geographic 

isolation. Chapter 2 and 6 on spinner dolphins and rough-toothed dolphins have 

made interesting contribution to this subject. It was shown that neighbouring 

communities could be distinct genetically and demographically although being in 

close geographical proximity. This was especially obvious for the communities of 

spinner dolphins from Moorea and Tahiti. Social components are thus likely to 

maintain boundaries between these communities. However, it is also likely that 

geographical isolation still plays a role, but at a larger geographical scale. The extent 

to which sociality and spatial isolation have contributed to shape contemporary 

genetic structure probably varies between communities. This study also confirmed 

that genetic diversity can vary considerably between communities (even within the 

same species), and that it can be independent of local community size (Table 7.1). 

However, it is still not clear if this is specifically related to inbreeding avoidance or 

not. Further investigations might help to describe a general model of genetic structure 

in this environment, but at this stage the status of insular communities still needs to 

be assessed case by case. 

To conclude this thesis, I briefly revisit some of the primary findings and provide 

further discussion in the context of future research interests. 

7.2. Metapopulation of spinner dolphins 

In the Chapter 2, I described a contrasting pattern of demographic closure and 

evolutionary openness in insular communities of spinner dolphins from the Society 

Archipelago, French Polynesia. In order to explain the large female effective 

population size observed, I proposed that the spinner dolphins of this region live in a 

metapopulation composed of insular communities inter-connected through male and 

171


female gene flow. Such a model of population structure seems surprising for a 

species capable of long-range movements and living in an environment lacking of 

obvious geographical barriers. However, the open ocean appears to be an unsuitable 

habitat for spinner dolphins in this region (as suggested by the absence of sightings 

offshore during plane and boat surveys), and thus it can be considered that overall 

their habitat is highly fragmented, i.e., favourable to metapopulation structure. The 

size of this metapopulation remains unknown, but it could extend beyond the 

boundaries of the Society Islands. Further studies including samples from 

surrounding areas are thus needed to investigate this question. To begin, additional 

samples should be collected in the South west Pacific where spinner dolphins appear 

to be commonly observed in the nearshore waters of the tropical islands. This 

includes Cook Islands, Samoa, Tonga, New Caledonia, Tuvalu and others (Reeves 

et al. 1999, South Pacific Whale Research Consortium, pers. comm.). 

The reasons behind habitat fidelity of insular spinner dolphins are still unclear. 

Although geographic isolation might, in some cases, play a role (Karczmarski et al. 

2005), the strong genetic differentiation observed between the neighbouring 

communities of Moorea and Tahiti indicated that additional factors are involved. 

These could, for instance, imply social mechanisms, food competition and/or 

competition for suitable resting areas. At this stage, only the abundance of Moorea’s 

community was estimated in the Society Archipelago but it would be interesting to 

estimate abundance from communities around smaller and larger islands, in order to 

test hypotheses on island carrying capacity. At the Big Island, in Hawaii, Würsig et al. 

(1994) suggested that the insular habitat has an approximate carrying capacity of 

spinner dolphins that could be determined by the size and distribution of useable 

resting areas. A similar tendency is possible in the Society Archipelago, since the 

frequencies of encountered with groups of spinner dolphins appear to be higher 

around islands with more passes (i.e., more resting areas for spinner dolphins). If 

confirmed, this would suggest a model of density dependence, in which the size of 

insular communities is regulated by daytime resting areas rather than food availability 

(since spinner dolphins feed offshore, on mesopelagic preys). 

172


A metapopulation structure for the communities of spinner dolphins from the Society 

Archipelago raises some concerns from a conservation and management point of 

view. Although spinner dolphins from French Polynesia appear to be relatively safe 

from fisheries impact (e.g., no directed take or report of by-catch) they might not be 

safe from tourism pressures and habitat degradation. The coastal environment 

appears to be crucial for these animals and no studies have been undertaken in 

French Polynesia to investigate anthropogenic impact. The consequences of local 

displacement or extinction on metapopulation structure are unknown but such event 

could potentially have deleterious effects on surrounding communities too (for 

example, by severing links within the network of communities). Application of the 

metapopulation theory on insular spinner dolphins could result in a much better 

understanding of their population dynamics and thus better tools to predict and 

prevent local disturbance and extinctions. Whether or not this theory can be applied 

efficiently is still debated (Baguette 2004, Hanski 2004), especially for large 

mammals (Elmhagen & Angerbjörn 2001), but the usefulness of this approach for 

spinner dolphin (and maybe rough-toothed dolphin) communities should be explored. 

7.3. Pilot whales evolutionary history 

Results from Chapter 3 confirmed low levels of worldwide mtDNA diversity in the two 

species of pilot whales (Table 7.1), as previously suspected from studies in the North 

Atlantic (Siemann 1994). There was no evidence for a bottleneck effect to explain this 

pattern, but a recent worldwide expansion could have played a role, in particular for 

the long-finned pilot whale. It would be interesting to investigate the level of diversity 

throughout the range of the species as it could help to identify the centre of 

dispersion. Interestingly, phylogenetic reconstructions presented in Chapter 3 

suggest that the “Southern” form of short-finned pilot whale in Japan could potentially 

represent the ancestral population of the genus Globicephala. If this is confirmed by 

further analyses, one expectation would be to find higher genetic diversity in longfinned 

pilot whale populations ranging close to Japan (that is, in the southwest 

Pacific) than in populations distributed further away (for example, South Atlantic and 

North Atlantic). 

173


Analyses of mtDNA diversity confirmed a strong population differentiation between 

long-finned pilot whales from the North Atlantic and Southern Hemisphere. However, 

the presence of shared haplotypes does not support the current status of subspecies 

for these two populations. The mtDNA diversity appears to be lower in the 

North Atlantic than in samples from the Southern Hemisphere, which could potentially 

illustrate a recent founder event. The separation between the North Atlantic and the 

Southern Hemisphere long-finned pilot whales could date from one of the recent 

glaciation periods. However, any attempt to estimate the time of this event will also 

require samples from the South Atlantic where the migrants would be more likely to 

originate. South Atlantic populations could be genetically very different from the 

populations in New Zealand and Tasmania, and more similar to the populations in the 

North Atlantic. If this was the case, then it would imply that the colonization of the 

North Atlantic was more recent than the estimates given using samples of the 

southwest Pacific. The alternative scenario of current gene flow through unknown 

corridors also remains a possibility, although it seems very unlikely considering the 

obvious geographical segregation. Investigation of these questions would also 

benefit from analyses of nuclear markers. 

Long-finned pilot whales are distributed throughout the temperate waters of the 

Southern Hemisphere oceans but the population structure and abundance across 

this range is unknown. Unexpectedly, fine-scale population structure was observed 

between long-finned pilot whales stranded in Tasmania and New Zealand, although 

examination of additional samples from Australia is needed to confirm this pattern. It 

would be interesting to investigate the potential impact of sea surface temperature on 

the population structure, since this factor is known to play an important role in the 

ecology of pilot whales (Kasuya et al. 1988, Fullard et al. 2000). 

Finally, results from Chapter 3 revealed a complex pattern of mtDNA diversity in 

short-finned pilot whales, in particular through the inclusion of the samples from 

around Japan. The relatively high level of mtDNA diversity in this region contrasts 

with the low diversity observed in the South Pacific and Atlantic Ocean. This was 

particularly true for samples thought to represent essentially the “Southern” form of 

Japanese pilot whales. Unfortunately, uncertainties remain on the form of origin of 

174


the Japanese whale-meat market samples (“Northern” or “Southern” form), limiting 

the interpretations of the patterns of phylogeography. Future studies should integrate 

this information in order to investigate some of the hypotheses formulated in this 

thesis. For instance, it could help to confirm the presence of two or three distinct 

populations of short-finned pilot whales in the waters of Japan. It could also help to 

clarify the origin of the “Northern” form population. Examination of samples from the 

eastern North Pacific would also be extremely valuable in determining this. Indeed, 

the limited data available here suggest recent or current gene flow between the 

“Northern” form of Japan and the eastern North Pacific. This could indicate that these 

populations emerged from the same common ancestor, providing an explanation for 

larger body sizes observed in animals of these two regions. On the other hand, it 

would discount a scenario of independent morphological convergence toward larger 

size, such as the one recently suggested for common dolphins (Natoli et al. 2006). 

The low level of mtDNA diversity inferred in the “Northern” form could further suggest 

a recent and rapid demographic expansion of the larger form of short-finned pilot 

whale throughout the North Pacific. This is consistent with the absence of shortfinned 

pilot whales in the fossil record from this area (Kasuya 1975). Such a rapid 

demographic expansion could have played a role in the recent extinction of longfinned 

pilot whales in the North Pacific. Indeed, Kasuya (1975), although he did not 

name short-finned pilot whales as a potential competitor of long-finned pilot whales, 

suggested that inter-specific competition could have been the cause of this 

extinction. 

7.4. Social systems and matrilineality 

In most species of cetaceans, investigation of social systems (i.e., social 

organisation, social structure and mating system) is extremely difficult, due to 

offshore distribution and absence of residency which prevent from conducting 

longitudinal studies. Results of Chapter 4 showed that data from long-finned pilot 

whales mass strandings can provide valuable information as an alternative to longterm 

studies. Notably, it has been possible to bring new insights into a controversial 

hypothesis, that large groups of long-finned pilot whales at sea are not necessarily 

composed of related matrilineal groups (Amos et al. 1993, Fullard 2000, Ottensmeyer 

175


& Whitehead 2003). However, parentage analyses confirm that some level of 

philopatry to maternal group exists for both sexes, recalling the society of “resident” 

killer whales described in the eastern North Pacific (Bigg et al. 1990). Unfortunately, 

too many uncertainties remain around pilot whales social organisation to conduct a 

thorough comparison to killer whales. For instance, some level of philopatry does not 

imply that all individuals remain in the vicinity of their mother for life. On this, 

“transient” killer whales differ from “resident” killer whales (Baird & Whitehead 2000). 

It is not known if the social organisation of long-finned pilot whales from New Zealand 

is closer to the “transient” or “resident” populations of killer whales. Different levels of 

association could also exist beyond the simple matrilineal group, related or not to 

kinship. In sperm whales for instance, Christal (1998) showed that long-term social 

units sometimes include non-kin members. 

Further analyses could be conducted with an exhaustive sampling of mass 

strandings, including sampling of the whale returned to sea. However, cross-sectional 

information, such as the one obtained from mass strandings, will always be limited for 

the prospect of investigating social systems. In his conceptual framework, Hinde 

(1976) described social structure as the content, quality and patterning of 

relationships. The temporal aspect included in this definition can not be covered 

when working on mass strandings. Therefore, research at sea is still necessary. It is 

only from such studies that sufficient knowledge will be acquired to allow comparison 

of pilot whales social systems to the patterns observed in killer whales and other 

species. One major obstacle will be to find a population accessible enough to 

investigation on a long-term basis. For such purpose, more opportunities might be 

found among short-finned pilot whales, since several resident populations have been 

described, notably around tropical and sub-tropical islands (e.g., Heimlich-Boran 

1993). 

Although showing a high level of fluidity, the social organisation of spinner dolphins 

from Moorea (Chapter 2) is also characterized by some long-term associations 

between individuals of both sexes (result not shown), as observed among long-finned 

pilot whales of Nova Scotia (Ottensmeyer & Whitehead 2003) and short-finned pilot 

whales of Canary Islands (Heimlich-Boran 1993). I do not know if spinner dolphins 

176


present some level of matrilineal philopatry in their social structure, but this is a 

possibility. It can be noted that a matrilineal structure was suggested in bottlenose 

dolphins from Sarasota Bay (which form small coastal and resident communities 

similar in many ways to insular spinner dolphins), even though it is clearly not as 

strict as “resident” killer whale matrilineal structure (Duffield & Wells 1991). 

Unfortunately, during the course of my fieldwork, I was rarely able to obtain 

photographs of the individual spinner dolphins from which I collected genetic samples 

(due to the lack of an experienced photographer on the boat during sampling). 

Therefore, I only have confirmation of genetic sampling for a few DMIs (Distinctively 

Marked Individuals) of my photo-identification catalogue, preventing me from testing 

for patterns of high relatedness or shared mtDNA haplotype in relation to long-term 

association. Further studies should be conducted on this subject, in order to offer a 

clearer description of spinner dolphin social system. This would provide valuable 

material for comparison to other species of dolphins, notably to bottlenose dolphins 

which also follow (in most case at least) a fission/fusion model of social organisation. 

Among the four species investigated in this thesis, rough-toothed dolphins are by far 

the least known, particularly in terms of social system (Chapter 6). The low level of 

mtDNA diversity observed in the communities of this species could indicate 

matrilineal structure, as described for other matrilineal species of odontocetes 

(Whitehead 1998). I do not have at this stage direct evidence to support this 

hypothesis, although long-term associations seem to occur among rough-toothed 

dolphins at Moorea (Results not shown). Once again, this highlights the need for 

long-term studies in support to molecular information. So far, most of the genetic 

studies looking at the role of kinship in the patterns of dolphins’ social systems have 

focused on Tursiops sp. (e.g., Krützen et al. 2003, Parsons et al. 2003, Möller et al. 

2006). Although populations of spinner and rough-toothed dolphins are generally 

harder to investigate than populations of bottlenose dolphins, they still represent 

good candidates for such a purpose. Comparative studies combining complementary 

tools, such as molecular markers and observational data, should provide further 

fascinating results and help explain the striking differences observed within and 

between different species of dolphin. 

177

8. Appendices 

Biopsy sampling of rough-toothed at Moorea, August 2004 

Appendices 

178

Appendices 

Appendix 1: List of microsatellite loci used in this thesis, including the number of 

individuals screened for each species (n), the number of alleles found (k), and the 

alleles’ size ranges (range). 

Locus Sources Motif 


Rough-toothed 

dolphin 

Long-finned pilot 

whale 

n k (range) n k (range) n k (range) 

409/470 (1) ? - - 33 4 (167-173) 254 12 (168-202) 

415/416 (1) GT23 132 12 (216-238) 50 8 (216-232) 266 9 (210-238) 

464/465 (1) GT3CTGT20 - - - - 261 9 (136-154) 

AAT44 (2) AAT12 136 10 (82-109) 6 2 (82-84) 7 1 (76) 

DlrFCB1 (3) AC16 62 13 (106-150) 53 8 (101-117) 267 15 (95-137) 

DlrFCB6 (3) TG28 - - - - 262 7 (161-179) 

EV1 (4) AC13TC8 136 15 (123-175) 56 5 (114-122) 266 14 (139-167) 

EV37 (4) AC24 8 4 (179-185) 49 16 (194-232) 267 9 (172-194) 

EV94 (4) TC6…AC20 136 20 (230-270) 43 13 (213-239) 265 6 (267-277) 

GATA53 (5) GATAn - - - - 240 8 (266-294) 

GATA98 (5) GATAn 137 9 (84-116) 55 3 (79-87) 34 1 (86) 

GT23 (6) GTn - - 55 3 (64-70) 267 5 (72-80) 

GT39 (2) AC21 - - 51 10 (152-176) 121 4 (139-155) 

GT48 (2) CT17N9CA18 48 17 (180-232) - - 118 18 (192-240) 

GT51 (2) GT16 93 9 (194-228) 6 2 (200-202) 261 3 (101-105) 

GT142 (2) TG20 96 8 (180-198) 6 1 (178) 7 1 (182) 

GT575 (6) GTn 135 8 (138-152) 6 1 (132) 265 11 (143-167) 

GT6 (2) CA18 135 10 (186-204) 51 10 (200-228) 122 7 (190-212) 

KWM12a (7) ? 136 11 (157-183) - - 38 2 (154-156) 

MK5 (8) 

# 

137 12 (202-230) 54 9 (209-229) 122 7 (215-227) 

MK6 (8) GT17 136 19 (143-183) 54 4 (118-132) 122 3 (134-140) 

MK8 (8) CA23 61 7 (76-102) 53 9 (94-110) 228 13 (92-114) 

MK9 (8) CA17 113 8(159-181) 55 10 (156-176) 120 4 (157-163) 

Ppho110 (9) CA22 - - 52 3 (112-118) 122 5 (105-113) 

Ppho131 (9) CA13 137 14 (162-202) 52 8 (183-205) 267 11 (183-205) 

Ppho142 (9) CA22 132 10 (131-153) - - 7 1 (174) 

Values in bold indicate that the locus was used for the thesis analyses. Otherwise, the locus was 

rejected for analyses. The reasons for rejecting a locus were either: low variability, unclear peaks, 

detection of null allele or detection of linkage disequilibrium. Empty cells stand for the loci which failed 

to amplify from polymerase chain reaction or the loci providing messy peaks preventing accurate allele 

calling. Sources: (1) (Amos et al. 1993); (2) (Caldwell et al. 2002); (3) (Buchanan et al. 1996); (4) 

(Valsecchi & Amos 1996); (5) (Palsbøll et al. 1997); (6) (Bérubé et al. 2000); (7) (Hoelzel et al. 1998b); 

(8) (Krützen et al. 2001); (9) (Rosel et al. 1999). # (TG)13CT(TG)2CA(TG)2(TA)2(TG)4. 

179

Appendices 

Appendix 2: Spinner dolphin photographs quality assessment based on Q-values 

categories. 

The quality of the dorsal fin photographs used in Chapter 2 was assessed on the 

basis of five criteria, also used in previous cetacean photo-identification studies 

(Arnborn 1987, Ottensmeyer 2001). These are: focus, size of the dorsal fin on the 

image, exposure, orientation and percentage visible. For each criterion, the 

photographs were assigned a grade from 1 to 5 (Table 8.1). The final Q-value of 

each dorsal fin was calculated as the average grade over the five criteria. Therefore, 

the Q-values also ranged from 1 to 5. All photographs ranking 1 for at least one 

criterion were excluded from the analysis of community size estimate, along with the 

dorsal fin images that rated Q < 3. Size of the dorsal fins on the images were 

measured based on the “actual size” of the image on the computer screen. 

Table 8.1 Description of the criteria used to assess the quality of dorsal fin images 

Criterion Grade Description 

FOCUS 1 Very blurry 

2 Blurry but general outline visible 

3 Reasonable, but small nicks not visible 

4 Reasonable, small nicks visible 

5 Excellent, everything in focus 

SIZE 1 Less than 2 cm 

2 Between 2 and 4 cm 



5 More than 10 cm 

EXPOSURE 1 Over or under exposed, only silhouette is visible 

2 Too light or dark and some details are not seen 

3 A little light or dark but all details are thought to be seen 

4 A little light or dark but all details are clearly seen 

5 Excellent 

ORIENTATION 1 Perpendicular 

2 > 45 degrees 

3 About 45 degrees 

4 < 45 degrees 

5 Parallel 

PERCENTAGE VISIBLE 1 < 60% visible 

2 Between 60 and 80% visible 

3 About 80% visible 

4 Between 80 and 100% visible 

5 100% visible 

180

Appendix 3: Dolphin behavioural responses to biopsy sampling 

Appendices 

Skin samples were collected from free-ranging dolphins for three of the four species 

investigated in this thesis: spinner dolphin, rough-toothed dolphin and short-finned 

pilot whale. Biopsy samples were obtained with lightweight darts fired by a variablepressure 

PAXARMS© biopsy rifle (Krützen et al. 2002). The cutting tip of the dart 

measured 4mm in diameter and 6mm in length. 

Sampling was only undertaken in sea state up to Beaufort scale three. Following 

each biopsy sampling attempt, the behavioural response of the targeted dolphin was 

recorded by the biopsier. Each shot was classified as ‘hit’ or ‘miss’; shots where the 

dart touched the dolphin were considered a ‘hit’, regardless of the success in getting 

a tissue sample in the tip. Responses were classified in five categories, following 

Krützen et al. (2002): 

- (0): no visible reaction, dolphin continued pre-biopsy behaviour; 

- (1): “startle” response, dolphin moved away (flinch) but stayed in the 

immediate vicinity of the boat; 

- (2): splashing during moving away and/or tail slap, with or without return to 

the boat; 

- (3): single leap or porpoise; 

- (4): multiple leaps or porpoises. 

Frequencies of responses for each of the three species are compiled in Table 8.2. 

Table 8.2: Summary of the behavioural responses shown to biopsy sampling by three species of 

dolphins. 

Response 


Rough-toothed 

dolphin 

Short-finned pilot 

whale 

Hit Miss Total Hit Miss Total Hit Miss Total 

(0) 4 4 8 0 5 5 0 4 4 

(1) 30 25 55 7 10 17 26 2 28 

(2) 91 59 150 34 10 44 13 0 13 

(3) 16 16 32 16 0 17 0 0 0 

(4) 1 1 2 14 0 14 0 0 0 

total 142 105 247 71 25 97 39 6 45 

181

Appendices 

Interestingly, proportional frequencies revealed different patterns of responses 

between these species (Figure 8.1). For instance, spinner dolphins showed no 

significant differences in behavioural responses for hit or miss shots; on the other 

hand, rough-toothed dolphins appeared to react more to hit shots (results not 

shown). Another interesting tendency was the lower level of reaction shown by shortfinned 

pilot whales to hit shots compared to the level of reaction by spinner and 

rough-toothed dolphins. 

Figure 8.1: Patterns of behavioural reactions to biopsy sampling for three species of dolphins. Results 

are shown for hit and miss shots. 

182

Appendices 

Appendix 4: Genetic diversity statistics, neutrality test and genetic differentiation, 

for the full datasets of long-finned pilot whale (Globicephala melas) (a) and shortfinned 

pilot whale (G. macrorhynchus) (b), used in Chapter 3. See legends of Table 

3.3 and 3.4 for details. 

a) Long-finned pilot whale (Globicephala melas) 

New Zealand Tasmania North Atlantic Overall 

# individuals 337 27 70 434 

# haplotypes 8 5 3 10 

h 0.225 +/- 0.030 0.618 +/- 0.075 0.323 +/- 0.065 0.428 +/- 0.028 

π (%) 0.05 +/- 0.07 0.27 +/- 0.21 0.11 +/- 0.12 0.16 +/- 0.15 

Tajima’s D -1,402 0.469 -0,086 -0,961 

p-value 0.033 0.706 0.455 0.175 

Fu’s F -5,806 -0,941 0.063 -5,244 

p-value 0.019 0.260 0.411 0.046 

AMOVA New Zealand Tasmania North Atlantic 

New Zealand 0.343*** 0.754*** 

Tasmania 0.267*** 0.530*** 

North Atlantic 0.710*** 0.528*** 

b) Short-finned pilot whale (Globicephala macrorhynchus) 

Atlantic South Pacific Japan/Korea North Japan South Japan Overall 

# individuals 12 35 85 11 71 134 

# haplotypes 2 3 11 3 9 14 

h 0.166 +/- 0.134 0.543 +/- 0.033 0.819 +/- 0.028 0.345 +/- 0.172 0.783 +/- 0.034 0.871 +/- 0.012 

π (%) 0.05 +/- 0.08 0.31 +/- 0.24 0.73 +/- 0.44 0.32 +/- 0.25 0.62 +/- 0.39 0.85 +/- 0.50 

Tajima’s D -1,14 1.106 0.389 -1,851 0.376 0.608 

p-value 0.178 0.860 0.701 0.014 0.690 0.778 

Fu’s F -0,476 1.996 -0,729 0.762 -0,381 -1,004 

p-value 0.126 0.862 0.427 0.643 0.482 0.405 

AMOVA South Pacific North Japan South Japan Atlantic 

South Pacific 0.551*** 0.606*** 0.561*** 

North Japan 0.525*** 0.73*** 0.533*** 

South Japan 0.569*** 0.747*** 0.597*** 

Atlantic 0.285*** 0.345*** 0.419*** 

183

Appendices 

Appendix 5: Case of potential paternity within a matrilineal group of long-finned 

pilot whales 

Parentage analyses of the long-finned pilot whale mass strandings from New 

Zealand have confirmed that, overall, mature males do not reproduce with mature 

females of their own group (Chapter 4), as suggested by previous genetic studies in 

the Faroe Islands (Amos et al. 1993, Fullard 2000). However, I found one exception 

within the mass stranding of Stewart Island 2003, where a mature male (Glo118) was 

found to be the potential father of an immature whale from the same mass stranding 

(Glo131, male). This assignment was supported by 95% confidence based on the 

Cervus likelihood-based approach (14 microsatellite loci, see section 4.3.7 for details 

on the method). It was further confirmed by the analyses of 6 additional loci screened 

for the purpose of Chapter 5 (20 loci total, Table 8.3). Directionality of this 

relationship was assumed based on body size of the two individuals, Glo118 = 550 

cm and Glo131 = 370 cm. 

Analyses to identify the mother of the offspring among mature females of the mass 

stranding revealed two potential mothers with no mismatches at 20 loci (Glo109 and 

Glo200, Table 8.3). Unfortunately, Cervus was not able to designate, with 95% or 

80% confidence, one of the two females as the most-likely mother. Assuming that 

Glo118 was the real father of Glo131 (as supported by the likelihood statistic), I 

compared genotypes of all four individuals to determine if at least one of the two 

potential mothers carried the alleles complementary to the alleles of Glo118 which 

could resolve the full genotype of offspring Glo131 (i.e., a female carrying all alleles 

found in the offspring which could not come from its father). Glo109 had such 

complementary alleles, while Glo200 was missing several of them (Table 8.3). 

Therefore, this gives support to the pair Glo118 and Glo109 as being the parents of 

Glo131, and it fully discounts the scenario where Glo118 and Glo200 are the two 

parents. 

184

Appendices 

Table 8.3: Genotypes for 20 microsatellite loci of: the offspring, Glo131; its most-likely father, Glo118; 

and its two potential mothers, Glo109 and Glo200. * indicates the loci excluding Glo200 as a potential 

mother of Glo131 under the assumption that Glo118 is the real father. 

Offspring Most-likely 

father 

Potential mothers 

Code Glo131 Glo118 Glo109 Glo200 

Size 370 550 390 430 

Sex male male female female 

EV37 188 192 180 192 188 192 180 192 * 

Ppho131 195 197 189 195 197 205 195 197 

415/416 226 228 224 228 210 226 226 228 

MK9 161 163 161 161 161 163 157 161 * 

EV94 271 275 271 275 275 275 275 275 

GT575 151 151 151 151 151 153 151 153 

GT51 201 203 203 203 201 203 203 203 * 

MK5 217 219 215 219 217 219 217 219 

GT23 72 76 72 76 72 76 72 76 

Ppho110 109 109 109 109 109 109 109 109 

DlrFCB1 125 125 125 125 125 127 125 127 

DlrFCB6 175 177 175 177 175 175 169 175 

409/470 184 186 184 194 186 198 184 186 

464/465 140 140 140 148 140 148 140 140 

EV1 149 151 149 151 149 149 149 149 

GT6 190 204 190 204 190 190 190 190 

MK6 138 138 138 138 138 140 138 138 

GATA53 278 286 278 286 282 286 282 286 

MK8 104 106 102 106 96 104 96 106 * 

GT39 139 139 139 151 139 151 139 139 

Interestingly, parentage analyses among mature individuals (results not shown) 

revealed that Glo200 was the most-likely mother (95% confidence) of both Glo118 

and Glo109 (Figure 8.2). Indeed, the body length of Glo200 was 430cm while the 

body length of Glo109 was 390cm, indicating that the former was the oldest (i.e., the 

mother and not the daughter of Glo109). Note that it can not be ruled out that Glo118 

was the father of Glo200 (and thus the grand-father of Glo109) but this is unlikely in 

regards to the overall trends in social structure of this species (see Chapter 4). 

Glo118 and Glo109 were thus most-likely half-siblings. This relationship indicates 

that mating between close relatives in long-finned pilot whales is likely to occur on 

some occasions although it clearly represents a small percentage of parentages (see 

Chapter 4). Further analyses should help estimate the true frequency of such mating 

events in long-finned pilot whales. 

185

Appendices 

Figure 8.2: Parental connexions and inferred genealogy between four individuals of Stewart Island 

2003 mass stranding based on strict exclusion (no mismatch at 20 loci). Information on the level of 

confidence in parentage relationships as derived from likelihood-based approach is also given; full 

lines indicate 95% confidence while dotted lines indicate no support at 80% confidence. White box: 

female; grey box: male. The total body length of each individual is also given. 

186

Appendices 

Electronic Appendices: Description of the Appendices included on CD-ROM 

(inside back cover) 

Appendix 6 Sex, sequence and genotype datasets for Chapter 2 

Appendix 6 – 

Data Chapter 2 

Appendix 7 Sequence dataset for Chapter 3 



This folder contains two files. The first one, “Chapter2 Dlp 

haplotypes”, is a FASTA file with the sequences of the 31 

mtDNA control region haplotypes found in spinner 

dolphins from French Polynesia (555 base pairs). 

The second one, “Data Chapter2”, is an XLS file with 

information on the genetic samples collected for this 

study. The first worksheet, “Chapter2 samples+mtDNA”, 

shows information on the sampling date, location of 

sampling, sex and mtDNA haplotype. The second 

worksheet, “Chapter2 microsatellites”, gives the 

genotypes of the samples collected at 12 microsatellite 

loci. 

This folder contains one file, “Chapter3 Dlp haplotypes”. 

This is a FASTA file with the sequences of the 24 mtDNA 

control region haplotypes of long-finned and short-finned 

pilot whales defined in Chapter 3, plus the two sequences 

used as outgroups (345 base pairs). 





haplotypes”, is a FASTA file with the sequences of the 

seven mtDNA control region haplotypes found in longfinned 

pilot whale mass strandings in New Zealand (365 

base pairs). 



study. The first worksheet, “Chapter4 samples+mtDNA”, 

shows information on the sampling date, location of 

sampling, sex, body length and mtDNA haplotype. The 

second worksheet, “Chapter4 microsatellites”, gives the 


loci. 

187

Appendix 9 Genotype dataset for Chapter 5 






Appendices 

This folder contains one file, “Data Chapter5”. This is an 

XLS file with the genotypes, at 20 microsatellite loci, of 

the 122 long-finned pilot whales from the mass stranding 

of Stewart Island in 2003. 


haplotypes”, is a FASTA file with the sequences of the 

five mtDNA control region haplotypes found in roughtoothed 

dolphins from French Polynesia (450 base pairs). 



chapter. The first worksheet, “Chapter6 samples 

+mtDNA”, shows information on the sampling date, 

location of sampling, sex and mtDNA haplotype. The 

second worksheet, “Chapter6 microsatellites”, gives the 


loci. 

188

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APPENDIX 6 – DATA CHAPTER 2 

Chapter 2 Dlp Haplotypes 

>Haplotype Slo02FP01 

ACACCACAGTACTATGTCAGTATTAAAAGTAATTTGTTTTAAAAACATTTTACCATACACATTACATA 

CACATACACGTGTGCATGCTAATATTT-AGTCT- 

CTCCTTGTAAATATTCATATATACATGCTATGTATTATTGTGCATTCATTTATTTTCCATACGATAAG 

TTAAAGCTCGTATTAATTATCATTAATTTTACATATTACATAATATGCATACTCTTACATATTATATAT 

CCCCTATCAATTTTATCTCCATTATATTCTATGGTCGCTCCATTAGATCACGAGCTTAATCACCATG 

CCGCGTGAAACCAGCAACCCGCTCGGCAGGGATCCCTCTTCTCGCACCGGGCCCATATCTCGTG 

GGGGTAGCTAAATAATGATCTTTATAAGACATCTGGTTCTTACTTCAGGACCATTTTAACTTAAAAT 

CGCCCACTCGTTCCTCTTAAATAAGACATCTCGATGGATTCATGACTAATCAGCCCATGCCTAACA 

TAACTGAGGTTTCATACATTTGGTATTTTTTAATTTTTGGGGGGGAGCTTGC 


ACACCACAGTACTATGTCAGTATTAAAAGTAATTTGTTTTAAAAACATTTTACTGTACACATTACATA 

CACATACACGTGTGCATGCTAATATTT- 

AGTCTTCTCCTTGTAAATATTCATATATACATGCTATGTATTATTGTGCATTCATTTATTTTCCATAC 

GATAAGTTAAAGCTCGTATTAATTATCATTAATTTTACATATTACATAATATGTATACTCTTACATATT 

ATATATCCCCTATCAATTTTATTTCCATTATACCCTATGGTCGCTCCATTAGATCACGAGCTTAGTC 

ACCATGCCGCGTGAAACCAGCAACCCGCTTGGCAGGGATCCCCCTCCTCGCACCGGGCCCATA 

CATCGTGGGGGTAGCTAAATAATGATCTTTATAAGACATCTGGTTCTTACTTCAGGACCATTTTAA 

CTTAAAATCGCCCACTCGTTCCTCTTAAATAAGACATCTCGATGGACTCATGACTAATCAGCCCAT 

GCCTAACATAACTGAGGTTTCATACATTTGGTATCTTTTAATTTTTGGGGGGGAGCTTGC 



CATATACACATGTGCATGCTAATATTT-AGTCT- 


TTAAAGCTCGTATTAATTATCATTAATTTTACATATTACATAATATGTATACTCTTACATATTATATAT 

CCCCTATCAATTTTATCTCCATTATACCCTATGGCCACTCCATTAGATCACGAGCTTAATCACCAT 

GCCGCGTGAAACCAGCAACCCGCTTGGCAGGGATCCCCCTCCTCGCACCGGGCCCATACATCG 

TGGGGGTAGCTAAATAATGATCTTTATAAGACATCTGGTTCTTACTTCAGGACCATTTTAACTTAAA 

ATCGCCCACTCGTTCCTCTTAAATAAGACATCTCGATGGACTCATGACTAATCAGCCCATGCCTAA 

CATAACTGAGGTTTCATACATTTGGTATTTTTTAATTTTTGGGGGGGAGCTTGC 



CATATACACATGTGCATGCTAATATTT-AGTCT- 



CCCCTATCAATTTTATCTCCATTATACTCTATGGCCACTCCATTAGATCACGAGCTTAATCACCATG 

CCGCGTGAAACCAGCAACCCGCTTGGCAGGGATCCCCCTCCTCGCACCGGGCCCATACATCGT 

GGGGGTAGCTAAATAATGATCTTTATAAGACATCTGGTTCTTACTTCAGGACCATTTTAACTTAAAA 

TCGCCCACTCGTTCCTCTTAAATAAGACATCTCGATGGACTCATGACTAATCAGCCCATGCCTAAC 

ATAACTGAGGTTTCATACATTTGGTATTTTTTAATTTTTGGGGGGGAGCTTGC 



CACATACACGTGTACATGCTAATATTT-AGTCT- 



CCCCTATCAATTTTATCTCCATTATACTCTATGGCCGCTCCATTAGATCACGAGCTTAATCACCAT 

GCCGCGTGAAACCAGCAACCCGCTTGGCAGGGATCCCCCTTCTCGCACCGGGCCCATACATCGT 


TCGCCCACTCGTTCCTCTTAAATAAGACATCTCGATGGACTTATGACTAATCAGCCCATGCCTAAC 






TTAAAGCTCGTATTAATTATCATTAATTTTACATATTACATAATATGTATACTCTTACATATTATATAT

CCCCTATCAATTTTATCTCCATTATACTCTATGGTCGCTCCATTAGATCACGAGCTTAATCACCATG 

CCGCGTGAAACCAGCAACCCGCTTGGCAGGGATCCCCCTCCTCGCACCGGGCCCATATATCGTG 


CGCCCACTCGTTCCTCTTAAATAAGACATCTCGATGGACTCATGACTAATCAGCCCATGCCTAACA 

TAACTGAGGTTTCATACATTTGGTATCTTTTAATTTTTGGGGGGGAGCTTGC 



CACATACACATGTGCATGCTAATATTT-AGTCT- 



CCCCTATCAATTTTATCTCCATTATACCCTATGGCCGCTCCATTAGATCACGAGCTTAATCACCAT 







CACATACACGTGTGCATGCTAATATTT- 

AGTCTTCTCCTTGTAAATATTCATATATACATGCTATGTATTATTGTGCATTCATTTATTTTCCATAC 

GATAAGTTAAAGCTCGTATTAATTATCATTAATTTTACATATTACATAATATGTATACTCTTACATATT 

ATATATCCTCTATCAATTTTATCTCCATTATACCCTATGGTCGCTCCATTAGATCACGAGCTTAATC 

ACCATGCCGCGTGAAACCAGCAACCCGCTTGGCAGGGATCCCCCTCCTCGCACCGGGCCCATA 

CATCGTGGGGGTAGCTAAATAATGATCTTTATAAGACATCTGGTTCTTACTTCAGGACCATTTTAA 

CTTAAAATCGCCCACTCGTTCCTCTTAAATAAGACATCTCGATGGACTCATGACTAATCAGCCCAT 

GCCTAACATAACTGAGGTTTCATACATTTGGTATCTTTTAATTTTTGGGGGGGAGCTTGC 





TTAAAGCTCGTATTAATTATCATTAATTTTACATATTACATAATATGTATGCTTTTACATATTATATAT 

CCCCTATCAATTTTATCTCCCTTATACTCTATGGTCTCTCCATTAGATCACGAGCTTAATCACCATG 


GGGGTAGCTAAGTAATGATCTTTATAAGACATCTGGTTCTTACTTCAGGACCATTTTAACTTAAAAT 

CGCCCACTCGTTCCTCTTAAATAAGACATCTCGATGGATTCATGACTAATCAGCCCATGCCTAACA 



ACACCACAGTACTATGTCAGTATTAAAAGTAATTTGTTTTAAAAACATTTTACTGTACATATTACATA 


CTCCTCGTAAATATTCATATATACATGCTATGTATTATTGTGCATTCATTTATTTTCCATACGATAAG 


CCCCTATCAATTTTATCCCCATTATACCCTATGGCCGCTCCATTAGATCACGAGCTTAATCACCAT 

GCCGCGTGAAACCAGCAACCCGCTTGGCAGGGATCCCCCTCCTCGCACCGGGCCCATATATCGT 





ACACCACAGTACTATGTCAGTATTAAAAATAATTTGTTTTAAAAACATTTTACTGTACACATTACATA 




CCTCTATCAATTTTATCTCCATTATACCCTATGGCCGCTCCATTAGATCACGAGCTTAATCACCAT 

GCCGCGTGAAACCAGCAACCCGCTCGGCAGGGATCCCCCTTCTCGCACCGGGCCCATACATCG 


ATCGCCCACTCGTTCCTCTTAAATAAGACATCTCGATGGACTCATGACTAATCAGCCCATGCCCAA 








CCGCGTGAAACCAGCAACCCGCTCGGCAGGGATCCCCCTCCTCGCACCGGGCCCATATATCGT 

GGGGGTAGCTAGATAATGATCTTTATAAGACATCTGGTTCTTACTTCAGGACCATTTTAACTTAAA 

ATCGCCCACTCGTTCCTCTTAAATAAGACATCTCGATGGACTCATGACTAATCAGCCCATGCCCAA 

CATAACTGAGGTTTCATACATTTGGTATCTTTTAATTTTTGGGGGGGAGCTTGC 



CACATACGCGTGTGCATGCTAATATTT-AGTCT- 



CCCCTATCAATTTTATCTCCATTATACCCTATGGTCGCTCCATCAGATCACGAGCTTAATCACCAT 

GCCGCGTGAAACCAGCAACCCGCTCGGCAGGGATCCCCCTCCTCGCACCGGGCCCATATATCG 


ATCGCCCACTCGTTCCTCTTAAATAAGACATCTCGATGGACTTATGACTAATCAGCCCATGCCTAA 



ACACCACAGTACTATGTCAGTATTAAAAGTAATTTATTTTAAAAACATTTTACTGTACACATTACATA 




CCCCTATCAATTTTATTTCCATTATACCCTATGGTCGCTCCATTAGATCACGAGCTTAATCACCATG 







CACATACATGTGTGCATGCTAATATTT-AGTCT- 



CCCCTATCAATTTTATCTCCATTATACCCTATGGTCGCTCCATTAGATCACGAGCTTAATCACCAT 

GCCGCGTGAAACCAGCAACCCGCTTGGCAGGGATCCCTCTTCTCGCACCGGGCCCATATCTCGT 


TCGCCCACTCGTTCCTCTTAAATAAGACATCTCGATGGATTCGTGACTAATCAGCCCATGCCTAAC 

ATAACTGAGGTTTCATACATTTGGTATCTTTTAATTTTTGGGGGGGAGCTTGC 



CACATATACATGTACATGCTAATATTT-AGTCT- 


TTAAAGCCCGTATTAATTATCATTAATTTTACATATTACATAATATGCATACTCTTACATATTATATAT 


GCCGCGTGAAACCAGCAACCCGCTCGGCAGGGATCCCCCTTCTCGCACCGGGCCCATATCTCG 

TGGGGGTAGCTAAATAATGATCTTTATAAGACATCTGGTTCTTACTTCAGGACCATTTCAACTTAAA 

ATCGCCCACTCGTTCCTCTTAAATAAGACATCTCGATGGATTCGTGACTAATCAGCCCATGCCTAA 







CCCCTATCAATTTTATCCCCATTATACCCTATGGTCGCTCCATTAGATCACGAGCTTAATCACCAT 



TCGCCCACTCGTTCCTCTTAAATAAGACATCTCGATGGACTTATGACTAATCAGCCCATGCCCAAC 










CGCCCACTCGTTCCTCTTAAATAAGACATCTCGATGGGTTCATGACTAATCAGCCCATGCCTAACA 




CACATACACATGTGCATGCTAATACTT-AGTCT- 



CCCCTATCAATTTTATCCCCATTATACCCTATGGTCACTCCATTAGATCACGAGCTTAATCACCAT 



TCGCCCACTCGTTCCTCTTAAATAAGACATCTCGATGGACTTATGACTAATCAGCCCATGCCTAAC 




CACATACATGTGTGCATACTAATATTTTAGTCT- 




GCCGCGTGAAACCAGCAACCCGCTTGGCAGGGATCCCTCTTCTCGCACCGGGCCCATATCTCGT 


TCGCCCACTCGTTCCTCTTAAATAAGACATCTCGATGGATTCGTGACTAATCAGCCCATGCCTAAC 




CACATACACGTGTGCATGCTAGTATTT-AGTCT- 













CCCCTATCAATTTTATCCCCATTATACCCTATGGTCGCTCCATTAGATCACGAGCTTAATCACCAT 



TCGCCCACTCGTTCCTCTTAAATAAGACATCTCGATGGACTCATGACTAATCAGCCCATGCCCAA 



ACACCACAGTACTATGTCAGTATTAAAAGTAATTTGTTTTAAAAACATTTTACTGTATACATTACATA 



TTAAAGCTCGTATTAATTATCATTAATTTTACATATTACATAATATGTATACTCTTACATATTATATGT 

CCCCTATCAATTTTACCTCCATTATACCCTATGGTCACTCCATTAGATCACGAGCTTAATCACCAT 

GCCGCGTGAAACCAGCAACCCGCTCGGCAGGGATCCCTCTTCTCGCACCGGGCCCATATCTCGT 

GGGGGTAGCTAAATAATGATCTTTATAAGACATCTGGTTCTTACTTCAGGACCATTTTAATTTAAAA 

TCGCCCACTCGTTCCTCTTAAATAAGACATCTCGATGGGTTCATGACTAATCAGCCCATGCCTAAC 






TTAAAGCTCGTATTAATTATCATTAATTTTACATATTACATAATATGCATACTCTTACATATTATATAT




ATCGCCCACTCGTTCCTCTTAAATAAGACATCTCGATGGATTCGTGACTAATCAGCCCATGCCTAA 




CACATACACATGTGCATGCTAATATTT-AGTCT- 



CCCCTATCAATTTTATTTCCATTATACTCTATGGCCGCTCCATTAGATCACGAGCTTAATCACCATG 

CCGCGTGAAACCAGCAACCCGCTTGGCAGGGATCCCCCTTCTCGCACCGGGCCCATATATCGTG 







CTCCTTGTAAATATTCATATGTACATGCTATGTATTATTGTGCATTCATTTATTTTCCATACGATAAG 


CCCCTATCAATTTTACTTCCATTATACTCTATGGTCGCTCCATTAGATCACGAGCTTAATCACCATG 






ACACCACAGTACTATGTCAGTATTAAAAGTAATTTGTTTTAAAAACATTTTACCGTACACATTACAT 

ACACATACACGTGTGCATGCTAATATTT-AGTCT- 


TTAAAGCTCGTATTAATTATCATTAATTTTACATATTACATAATATGCATACTCTTACATATTATATAT 

CCCCTATCAATTTTATCTCCATTATATTCTATGGTCGCTCCATTAGATCACGAGCTTAATCACCATG 







CACATACACGTGTACATGCTAATATTT-AGTCT- 




GCCGCGTGAAACCAGCAACCCGCTCGGCAGGGATCCCCCTCCTCGCACCGGGCCCATACATCG 


ATCGCCCACTCGTTCCTCTTAAATAAGACATCTCGATGGACTTATGACTAATCAGCCCATGCCTAA 








GCCGCGTGAAACCAGCAACCCGCTTGGCAGGGATCCCCCTTCTCGCACCGGGCCCATACATCGT 

GGGGGTAGCTAAGTAATGATCTTTATAAGACATCTGGTTCTTACTTCAGGACCATTTTAACTTAAA 








CCCCTATCAATTCTATCTCCATTATATTCTATGGTCGCTCCATTAGATCACGAGCTTAATCACCATG 

CCGCGTGAAACCAGCAACCCGCTCGGCAGGGATCCCCCTTCTCGCACCGGGCCCATATCTTGTG 


CGCCCACTCGTTCCTCTTAAATAAGACATCTCGATGGATTCGTGACTAATCAGCCCATGCCTAACA 









GGGGTAGCTAGATAATGATCTTTATAAGACATCTGGTTCTTACTTCAGGACCATTTTAACTTAAAAT 

CGCCCACTCGTTCCTCTTAAATAAGACATCTCGATGGGTTCATGACTAATCAGCCCATGCCTAACA 

TAACTGAGGTTTCATACATTTGGTATCTTTTAATTTTTGGGGGGGAGCTTGC

Spinner dolphin’s samples used in Chapter 2 

(?) indicate missing data 

Code 

Sampling 

date 

Type of sample Location Sex 

mtDNA haplotype 

555bp 

1 Slo02FP01 08/04/2002 biopsy Moorea Male Slo02FP01 

2 Slo02FP02 08/04/2002 biopsy Moorea Female Slo02FP02 












































46 Slo02FP46 28/08/2002 biopsy Moorea Male Slo02FP15















61 Slo02FP61 janvier 2002 stranding Moorea Male Slo02FP22 

62 Slo02FP62 janvier 2002 stranding Moorea Male Slo02FP11 









71 Slo03FP16 19/10/2003 biopsy BoraBora Male Slo02FP27 

72 Slo03FP17 28/10/2003 biopsy BoraBora Female Slo02FP09 



75 Slo03FP20 29/10/2003 biopsy BoraBora Male Slo02FP15 

76 Slo03FP21 29/10/2003 biopsy BoraBora 

Tahaa- 

Male Slo02FP07 

77 Slo03FP22 30/10/2003 biopsy Raiatea 

Tahaa- 

Female Slo02FP09 


Tahaa- 


79 Slo03FP24 31/10/2003 biopsy 

Raiatea Female Slo02FP15 

80 Slo03FP25 31/10/2003 biopsy 

Tahaa- 


81 Slo03FP26 05/11/2003 biopsy Huahine Female Slo03FP26 

82 Slo03FP27 05/11/2003 biopsy Huahine Male Slo02FP07 













95 Slo03FP40 08/11/2003 biopsy Huahine Male Slo02FP05



98 Slo03FP44 28/11/2003 biopsy Tahiti Female Slo02FP27 

99 Slo03FP45 28/11/2003 biopsy Tahiti Male Slo02FP27 















114 Slo04FP45 22/10/2004 biopsy Tahiti ? Slo02FP27 

















131 Slo04FP62 31/10/2004 biopsy Tahiti 

Tahaa- 



Tahaa- 



Tahaa- 



Tahaa- 



Tahaa- 



Tahaa- 



Tahaa- 



Tahaa- 


139 Slo04FP70 13/11/2004 biopsy 

140 Slo04FP71 14/11/2004 biopsy 


Tahaa- 

Raiatea Male Slo02FP07

141 Slo04FP72 14/11/2004 biopsy 

Tahaa- 

Raiatea 

Tahaa- 



Tahaa- 



Tahaa- 



Tahaa- 



Tahaa- 


146 Slo04FP77 15/11/2004 biopsy Raiatea Male Slo03FP41 

147 Slo04FP78 22/11/2004 biopsy Nuku Hiva Female Slo03FP01 

148 Slo04FP79 23/11/2004 biopsy Nuku Hiva Male Slo04FP79 






154 Slo04FP85 27/11/2004 biopsy Nuku Hiva Male Slo04FP83

Spinner dolphin microsatellite genotypes used in Chapter 2 

(-) indicates missing data 

Locus GATA98 MK5 Ppho142 EV94 GT575 KWM12a Ppho131 MK6 GT6 AAT44 415/416 EV1 

Slo02FP01 100 104 212 212 147 147 236 250 142 152 165 173 190 190 157 157 188 196 94 100 228 236 131 149 

Slo02FP02 84 104 208 212 141 147 238 250 144 144 169 175 192 194 153 157 188 192 82 97 216 228 149 149 

Slo02FP03 100 104 210 222 145 147 260 262 138 146 169 171 192 196 165 165 190 200 94 100 220 220 143 167 

Slo02FP04 100 100 210 218 141 151 238 238 144 146 171 173 192 194 157 163 200 200 94 97 220 236 147 149 

Slo02FP05 100 108 208 214 141 151 252 266 144 144 171 177 192 200 157 165 198 198 97 97 220 222 141 145 

Slo02FP06 96 108 210 224 141 147 236 270 138 142 165 167 192 192 147 157 196 198 94 97 230 232 141 153 

Slo02FP07 108 108 208 208 141 147 236 250 138 142 163 175 192 192 149 153 196 196 88 94 224 228 143 153 

Slo02FP08 88 108 212 214 147 151 252 256 140 150 169 177 188 190 153 157 196 198 88 88 228 228 149 153 

Slo02FP09 108 112 210 214 145 147 254 260 140 144 169 171 172 202 153 155 194 196 88 103 226 232 149 149 

Slo02FP10 104 104 208 208 145 147 250 250 142 142 167 169 194 196 153 153 194 196 94 106 216 228 129 149 

Slo02FP11 104 104 208 224 145 151 236 262 144 144 165 165 190 200 155 161 196 198 94 100 220 232 129 151 

Slo02FP12 96 108 216 230 145 151 238 262 138 144 171 173 176 184 153 169 196 196 97 103 234 234 143 153 

Slo02FP13 100 112 208 222 145 151 250 260 146 148 171 171 190 192 163 165 192 192 100 100 220 228 149 149 

Slo02FP14 96 108 212 216 145 147 258 260 144 150 163 165 188 188 149 165 196 200 94 94 216 222 147 147 

Slo02FP15 84 96 208 222 145 147 236 250 138 150 167 169 192 192 153 165 196 200 85 100 228 236 145 167 

Slo02FP16 84 108 212 214 145 149 236 236 138 144 175 175 190 192 153 165 196 202 88 100 220 234 147 153 

Slo02FP17 96 116 208 222 145 147 236 250 144 144 167 171 188 192 153 159 196 198 88 88 220 228 153 153 

Slo02FP18 104 104 208 208 145 147 250 250 142 142 167 169 194 196 153 153 194 196 94 106 216 228 129 149 

Slo02FP19 84 104 208 212 145 149 250 262 138 144 165 169 190 200 157 161 196 198 100 100 220 228 129 147 

Slo02FP20 100 104 208 222 145 151 238 252 144 146 169 171 174 198 163 173 198 200 97 100 220 230 143 153 

Slo02FP21 100 104 208 222 145 151 238 252 144 146 169 171 174 198 163 173 198 200 97 100 220 230 143 153 

Slo02FP22 100 104 212 212 145 147 236 250 144 144 169 173 196 198 153 153 188 196 88 100 228 230 131 167 

Slo02FP23 100 104 212 214 145 149 236 252 138 144 169 173 198 200 167 173 196 196 88 94 220 228 149 149 

Slo02FP24 104 108 208 226 145 151 250 262 146 150 169 177 192 196 155 173 190 198 88 100 220 234 151 151 

Slo02FP25 96 108 208 212 145 151 238 266 144 146 171 171 196 198 165 171 198 198 97 100 216 220 129 143 

Slo02FP26 96 100 212 212 145 147 250 250 142 144 167 175 190 194 153 157 194 196 88 100 220 228 129 153 

Slo02FP27 104 108 208 208 145 151 250 250 142 144 169 181 194 196 163 167 194 196 94 100 216 234 129 149 

Slo02FP28 96 100 212 214 145 147 236 250 142 144 171 173 176 190 153 153 192 200 88 97 216 220 149 155

Slo02FP29 100 108 212 218 145 147 236 256 144 150 167 173 190 192 153 153 - - 88 97 228 228 149 151 

Slo02FP30 100 112 212 216 145 151 238 262 138 144 167 175 198 198 165 165 192 198 94 100 216 228 143 149 

Slo02FP31 104 104 212 212 145 141 236 262 - - 169 173 176 192 149 167 186 196 94 100 - - - - 

Slo02FP32 84 96 208 222 145 147 236 250 138 150 167 169 192 192 153 165 196 200 85 100 228 236 145 167 

Slo02FP33 100 108 208 212 145 147 250 252 144 144 169 169 190 198 149 157 188 194 85 88 230 236 129 155 

Slo02FP34 104 116 212 222 145 147 236 250 138 140 167 169 190 200 157 159 196 198 88 94 220 236 131 153 

Slo02FP35 84 108 210 212 145 149 246 264 144 144 173 175 184 190 157 165 188 196 88 88 228 230 145 155 

Slo02FP36 104 112 210 212 145 151 236 252 146 146 171 175 192 192 161 169 196 196 88 97 230 234 143 151 

Slo02FP37 96 104 208 224 145 151 236 238 144 144 171 171 198 200 167 169 196 196 100 109 236 236 147 151 

Slo02FP38 84 104 208 214 145 147 236 250 142 144 169 171 176 192 159 177 196 196 85 106 216 228 151 151 

Slo02FP39 100 108 212 212 145 147 250 262 142 152 167 173 196 198 149 153 188 188 94 100 228 228 155 155 

Slo02FP40 96 104 212 212 145 147 250 250 146 146 167 169 190 190 149 153 194 198 97 100 228 230 129 151 

Slo02FP41 100 108 212 212 145 147 250 262 142 152 167 173 196 198 149 153 188 188 94 100 228 228 155 155 

Slo02FP42 96 104 208 212 145 147 236 262 144 150 167 173 190 192 149 153 196 198 85 100 228 236 155 155 

Slo02FP43 100 104 208 216 145 147 236 250 142 144 165 171 196 198 157 163 194 198 100 100 216 234 129 149 

Slo02FP44 104 108 212 224 145 147 246 262 138 142 169 173 190 196 153 163 196 196 94 106 216 216 149 149 

Slo02FP45 104 108 210 212 145 147 262 262 138 138 167 171 192 192 163 165 196 200 85 94 220 220 149 149 

Slo02FP46 104 108 208 210 145 151 250 262 138 144 171 175 192 198 157 173 192 198 94 94 220 228 149 155 

Slo02FP47 84 104 208 222 145 147 234 254 138 146 169 173 192 194 155 165 196 198 94 94 228 234 149 151 

Slo02FP48 84 104 208 222 145 147 234 254 138 146 169 173 192 194 155 165 196 198 94 94 228 234 149 151 

Slo02FP49 96 108 208 212 145 147 236 250 140 152 169 177 190 196 149 153 - - 88 100 - - 151 153 

Slo02FP50 100 108 208 212 145 147 250 252 144 144 169 169 190 198 149 157 188 194 85 88 230 236 129 155 

Slo02FP51 100 112 208 212 145 147 236 262 142 142 169 169 190 190 153 153 188 196 - - 228 228 129 149 

Slo02FP52 84 104 208 222 145 147 234 254 138 146 169 173 192 194 155 165 196 198 94 94 228 234 149 151 

Slo02FP53 108 112 210 214 145 147 254 260 140 144 169 171 172 202 153 155 194 196 88 103 226 232 149 149 

Slo02FP54 104 108 212 224 145 147 236 238 138 152 165 169 190 200 149 149 196 196 94 109 236 236 131 147 

Slo02FP55 84 100 208 224 145 149 250 262 138 138 165 169 190 192 149 165 196 200 88 100 220 220 147 149 

Slo02FP56 100 108 212 212 145 141 236 266 144 144 169 181 194 198 149 149 196 196 88 97 228 230 149 155 

Slo02FP57 96 108 208 222 145 147 250 250 142 144 167 173 190 194 157 169 188 198 82 94 220 230 129 149 

Slo02FP58 104 108 208 210 145 151 250 262 138 144 171 175 192 198 157 173 192 198 94 94 220 228 149 155 

Slo02FP59 96 104 208 216 145 147 236 250 144 144 165 169 196 198 157 167 194 196 88 88 216 216 129 129 

Slo02FP60 104 112 208 210 145 147 250 250 138 144 163 175 192 192 149 157 196 196 97 100 228 232 149 153 

Slo02FP61 100 108 208 212 145 147 250 252 144 144 169 169 190 198 149 157 188 194 85 88 230 236 129 155 

Slo02FP62 100 104 212 214 145 149 236 252 138 144 169 173 198 200 167 173 196 196 88 94 220 228 149 149

Slo03FP08 84 100 210 212 145 147 250 262 138 142 169 175 198 200 153 165 192 194 94 100 228 236 129 149 

Slo03FP09 104 104 208 212 145 151 250 262 142 144 167 171 188 190 159 163 188 196 97 106 228 234 149 153 

Slo03FP10 84 100 214 222 145 151 236 250 142 146 169 171 192 194 163 169 196 198 88 100 228 228 149 149 

Slo03FP11 96 100 212 212 145 147 250 266 144 144 171 171 190 194 153 153 188 198 97 100 228 228 149 151 

Slo03FP12 108 108 208 216 145 151 250 256 146 150 171 173 190 196 153 173 198 198 88 100 220 234 129 149 

Slo03FP13 96 112 208 222 145 147 250 262 138 144 167 175 190 198 153 165 194 198 94 97 220 234 123 145 

Slo03FP14 100 104 212 222 145 151 234 250 144 150 167 171 192 198 153 155 190 194 85 88 230 234 149 151 

Slo03FP15 96 100 208 226 145 147 242 252 144 144 169 171 184 198 173 173 196 200 88 88 216 220 151 153 

Slo03FP16 96 108 212 212 145 147 250 266 142 144 167 175 176 196 165 169 196 196 94 97 220 220 149 149 

Slo03FP17 108 112 208 224 145 147 242 250 142 144 171 171 172 198 155 163 198 198 94 103 222 230 149 149 

Slo03FP18 100 108 208 210 145 145 248 250 138 148 169 171 190 192 157 165 192 196 94 100 220 224 149 149 

Slo03FP19 108 108 208 208 145 147 236 250 138 142 163 175 192 192 149 153 196 196 88 94 224 228 143 153 

Slo03FP20 108 108 216 218 145 147 252 266 138 144 171 173 192 198 153 155 196 200 94 100 220 220 143 149 

Slo03FP21 108 108 208 210 145 141 236 260 138 150 169 169 192 200 151 165 194 196 94 94 224 230 147 149 

Slo03FP22 104 104 214 222 145 141 246 252 144 150 169 173 176 196 153 165 196 196 88 88 220 234 153 153 

Slo03FP23 108 112 208 216 145 145 246 252 138 148 169 173 176 198 159 173 198 198 97 97 220 228 149 157 

Slo03FP24 108 112 208 216 145 145 246 252 138 148 169 173 176 198 159 173 198 198 97 97 220 228 149 157 

Slo03FP25 108 108 218 222 145 145 242 246 138 146 169 169 196 198 153 159 188 198 82 94 220 220 153 157 

Slo03FP26 108 108 212 218 145 145 254 256 142 144 157 169 188 202 151 161 194 198 88 97 226 228 149 149 

Slo03FP27 96 104 214 222 145 147 236 250 138 138 163 175 194 198 149 169 196 198 88 94 220 222 149 149 

Slo03FP28 96 96 210 216 145 141 254 256 140 146 167 169 192 196 157 163 196 198 88 100 230 236 143 143 

Slo03FP29 96 100 210 214 145 147 248 252 144 146 163 173 176 194 157 163 196 196 94 97 228 234 149 153 

Slo03FP30 104 112 210 216 145 147 246 266 144 144 167 171 192 192 179 179 196 200 88 103 220 236 143 167 

Slo03FP31 100 108 208 214 145 147 236 256 144 150 167 173 192 198 153 169 192 202 88 88 226 232 143 143 

Slo03FP32 100 108 214 218 145 145 248 248 144 146 171 175 190 190 163 183 196 198 88 106 220 230 127 143 

Slo03FP33 100 100 208 208 - - 236 246 150 150 169 173 192 194 173 179 188 202 88 97 226 228 143 149 

Slo03FP34 104 104 214 226 145 147 236 242 138 142 169 171 192 194 153 163 188 196 88 106 216 230 149 151 

Slo03FP35 88 104 210 222 145 147 242 250 142 144 163 169 190 192 157 163 196 196 94 94 226 230 149 149 

Slo03FP36 96 100 212 216 145 147 234 248 146 152 169 171 190 192 163 183 198 198 91 94 - - 143 143 

Slo03FP37 84 92 210 224 145 147 262 268 142 144 169 169 162 176 151 163 194 196 94 94 230 236 143 145 

Slo03FP38 104 104 214 226 145 147 236 242 138 142 169 171 192 194 153 163 188 196 88 106 216 230 149 151 

Slo03FP39 100 108 214 218 145 145 248 248 144 146 171 175 190 190 163 183 196 198 88 106 220 230 127 143 

Slo03FP40 84 96 212 212 145 145 250 260 144 144 173 175 188 194 165 181 196 202 100 100 220 224 141 145 

Slo03FP41 108 112 208 222 145 147 250 256 140 146 171 175 194 202 153 179 198 200 94 100 220 228 145 149

Slo03FP42 100 112 210 212 145 147 250 258 146 150 171 177 162 196 163 179 198 200 97 97 216 230 141 143 

Slo03FP44 100 108 212 222 145 147 234 262 144 144 169 169 190 192 153 167 188 192 94 106 220 236 149 149 

Slo03FP45 96 104 212 216 145 147 250 256 144 150 171 171 176 192 153 153 196 198 88 97 230 238 151 153 

Slo03FP46 84 96 222 228 145 147 236 262 138 144 171 175 176 192 153 157 192 198 106 109 216 230 149 153 

Slo03FP47 84 100 214 216 145 151 236 250 138 144 171 173 190 198 155 165 196 198 88 97 228 230 151 151 

Slo03FP48 96 108 206 212 145 147 236 252 144 150 171 173 192 194 153 163 196 198 88 97 220 224 153 155 

Slo03FP49 104 104 212 222 145 147 250 262 142 150 171 171 190 192 153 157 196 198 97 100 216 220 149 151 

Slo03FP50 100 112 212 212 145 147 250 250 144 146 171 175 190 192 153 163 192 192 88 88 228 232 153 155 

Slo03FP51 100 104 212 212 145 147 250 266 144 144 167 169 192 192 157 157 188 198 97 97 228 228 151 151 

Slo04FP37 96 108 214 222 147 147 250 252 142 142 167 167 176 196 153 153 198 202 82 97 228 228 149 151 

Slo04FP38 100 108 222 224 147 147 250 250 144 152 169 173 184 192 153 153 196 196 94 106 228 228 149 151 

Slo04FP39 84 100 212 222 147 147 254 262 142 146 167 171 190 194 153 167 198 198 94 94 230 234 145 149 

Slo04FP40 100 104 212 212 141 145 250 266 142 144 175 175 190 198 157 163 194 198 97 97 216 220 151 153 

Slo04FP41 96 100 212 214 141 147 250 250 144 150 167 169 190 194 157 167 188 192 82 94 228 234 149 149 

Slo04FP42 96 100 214 218 147 147 250 266 142 144 171 173 190 194 153 171 188 200 97 97 216 216 149 155 

Slo04FP43 104 108 212 222 147 147 250 266 138 152 173 175 192 192 153 153 196 196 94 97 228 228 151 153 

Slo04FP44 96 104 212 218 147 147 236 236 144 144 171 173 190 194 153 157 196 196 88 94 216 228 151 151 

Slo04FP45 96 108 212 216 - - 246 256 144 150 167 173 188 192 153 167 196 198 82 100 216 230 149 151 

Slo04FP46 84 96 212 222 - - 234 266 144 144 171 173 190 192 167 171 188 198 97 106 228 228 149 151 

Slo04FP47 84 84 208 214 141 147 236 238 144 146 169 173 192 194 157 167 196 198 94 94 - - 153 153 

Slo04FP48 84 100 212 222 147 151 230 234 144 150 169 171 194 196 153 153 196 196 94 97 220 228 149 153 

Slo04FP49 108 112 212 212 141 147 250 262 144 150 171 173 192 194 153 157 188 198 97 106 220 228 149 149 

Slo04FP50 100 108 208 212 147 151 234 250 142 144 169 171 192 196 167 169 192 196 94 100 228 228 149 153 

Slo04FP51 96 104 212 212 147 147 246 250 144 150 167 171 192 194 149 177 192 192 88 97 228 234 149 151 

Slo04FP52 100 108 212 214 141 147 236 250 138 142 175 177 190 192 153 157 188 194 88 94 228 230 153 155 

Slo04FP53 96 108 208 218 147 147 230 256 144 144 169 171 190 190 153 153 192 196 100 100 228 232 151 151 

Slo04FP54 100 100 208 212 147 151 250 250 144 144 169 173 192 194 153 153 192 196 88 100 228 228 149 167 

Slo04FP55 100 108 208 216 151 151 262 262 142 146 171 175 192 198 169 173 192 192 94 97 230 230 149 151 

Slo04FP56 104 104 208 214 141 147 250 266 146 150 169 171 194 196 165 171 188 196 88 106 228 230 167 167 

Slo04FP57 100 108 208 212 147 151 250 250 142 152 169 173 192 196 153 153 192 194 94 97 228 228 153 153 

Slo04FP58 104 108 212 212 147 149 250 256 144 146 167 169 190 190 157 165 196 198 97 97 220 228 149 155 

Slo04FP59 104 108 208 212 141 147 250 250 138 144 171 171 176 196 153 157 196 198 82 106 220 228 153 167 

Slo04FP60 100 108 208 212 147 151 250 250 142 152 169 173 192 196 153 153 192 194 94 97 228 228 153 153 

Slo04FP61 108 112 212 212 147 149 238 250 138 144 167 169 190 192 153 165 194 198 88 94 228 228 145 155

Slo04FP62 84 100 208 222 147 147 234 250 144 152 169 175 192 196 153 169 196 196 97 100 228 228 149 153 

Slo04FP63 104 104 214 222 139 151 242 250 142 144 169 173 176 192 153 163 196 198 88 88 220 232 153 155 

Slo04FP64 84 104 208 212 141 149 246 250 142 144 169 171 190 192 151 157 192 196 88 106 220 228 143 149 

Slo04FP65 96 104 216 226 141 147 234 234 142 144 169 171 176 196 153 173 196 198 94 94 220 234 151 153 

Slo04FP66 104 112 210 216 145 147 246 266 144 144 167 171 192 192 179 179 196 200 88 103 220 236 143 167 

Slo04FP67 108 108 208 224 141 147 250 262 142 142 169 169 184 192 149 149 198 200 85 94 234 236 145 151 

Slo04FP68 104 104 214 222 137 141 246 252 144 150 169 173 176 196 153 165 196 196 88 88 220 234 153 153 

Slo04FP69 104 108 214 214 141 147 250 262 142 144 169 169 184 188 - - 192 198 85 109 224 230 151 151 

Slo04FP70 96 100 212 224 147 147 246 250 142 142 169 173 198 198 153 163 196 196 94 94 228 234 149 151 

Slo04FP71 96 112 212 222 145 149 254 256 138 138 171 173 162 194 159 165 194 198 94 100 216 220 149 155 

Slo04FP72 100 108 214 222 143 147 236 266 138 142 165 169 184 202 147 179 198 200 94 97 216 230 149 155 

Slo04FP73 108 108 218 222 141 145 242 246 138 146 169 169 196 198 153 159 188 198 82 94 220 220 153 157 

Slo04FP74 96 96 208 212 147 147 250 250 146 146 169 169 190 198 157 165 196 196 94 94 220 234 149 167 

Slo04FP75 96 100 212 214 141 147 246 256 142 144 169 169 176 194 163 165 192 196 82 94 220 234 151 151 

Slo04FP76 96 104 214 222 141 147 236 250 138 138 163 175 194 198 149 169 196 198 88 94 220 222 149 149 

Slo04FP77 108 112 208 222 141 147 250 256 140 146 171 175 194 202 153 179 198 200 94 100 220 228 145 149 

Slo04FP78 104 108 212 222 137 149 238 252 138 142 169 171 170 184 159 171 194 196 94 97 226 232 143 147 

Slo04FP79 104 112 214 224 145 149 242 250 142 144 167 183 192 194 165 165 192 200 88 97 228 232 129 149 

Slo04FP80 96 104 214 222 145 147 250 252 - - 167 169 190 200 153 157 194 194 94 100 218 220 131 153 

Slo04FP81 104 104 212 214 141 141 248 252 138 144 167 177 184 188 153 163 198 200 94 97 220 232 147 155 

Slo04FP82 100 104 214 214 - - 238 238 142 142 171 173 190 194 159 169 194 196 85 97 220 230 143 155 

Slo04FP83 96 104 214 224 145 147 236 252 142 142 167 175 198 202 143 163 200 204 88 94 220 232 147 155 

Slo04FP84 96 112 212 218 141 141 240 248 144 148 173 183 188 194 155 159 196 198 94 97 220 230 147 149 

Slo04FP85 104 108 212 214 137 141 248 252 144 146 - - 184 200 163 163 196 196 97 97 232 234 147 175



>Haplotype A 

TAAAAGTAATTTATTTTAAAAACATTTTACTGTACACATCACATATATATATATACGTACACATACCA 

ATATC- 

TAGTCTTTCCTTATAAATATCTATATATACATGCTATGTATTACTGTGCATTCATTTATTTTCCATAC 

GGTAAGTTAAAGCCCGTATTAATTATCATTAATTTTACATATTACATAATATGTATGCTCTTACATAT 

TATATATCCTCTAACAATTTTACCTCCATTATATCCTATGGTCGCTT- 

ATATTAGACCACGAGCTTTATCACCATGCCGCGTGAAACCAGCAACCCGCTCGGCAGGGATCCC 

TCTTCTCGCACCGGGCCCATACACC 

>Haplotype B 

TAAAAGTAATTTATTTTAAAAACATTTTACTGTACACATCACATATATGTATATACGTACACATATCA 

ATATC- 





CCTTCTCGCACCGGGCCCATACACC 

>Haplotype C 

TAAAAGTAATTTATTTTAAAAACATTTTACTGTACACATCACATATATATATATACGTACACATATCA 

ATATC- 





CCTTCTCGCACCGGGCCCATACACC 

>Haplotype D 


ATATC- 





TCTTCTCGCACCGGGCCCATATACC 

>Haplotype E 


ATATC- 



TATATATCCTCTAACAATTTTACTTCCATTATATCCTATGGTCGCTT- 



>Haplotype F 


ATATC- 



TATATATCCTCTAACAGTTTTACTTCCATTATATCCTATGGTCGCTT- 



>Haplotype G 


ATATC- 


GATAAGTTAAAGCCCGTATTAATTATCATTAATTTTACATATTACATAATATGTATGCTCTTACATAT 

TATATATCCTCTAACAATTTTACCTCCATTATATCCTATGGTCGCTT-



>Haplotype H 

TAAAAGTAATTTATTTTAAAAACATTTTACTGTACACATCACACATATATATATACGTACACATACCA 

ATATC- 






>Haplotype I 


ATATC- 



TATATATCCCCTAACAATTTTACCTCCATTATATCCTATGGTCGCTT- 



>Haplotype J 


ATATC- 

TAGTCTTTCCTTATAAATATCTATATATACATGCTATGTATTATTGTGCATTCATTTATTTTCCATAC 





>Haplotype K 


ATATC- 


GATAAGTTAAAGCTCGTATTAATTATCATTAATTTTACATATTACATAATATGTATGCTCTTACATAT 




>Haplotype L 


ATATC- 

TAGTCTTTCCTTATAAATATCTATATATACATGCTATGTATTATTGTGCATTCATTTATTTTCCATAC 




TCTTCTCGCACCGGGCCCATTCACC 

>Haplotype M 


ATATC- 





TCTTCTCGCACCGGGCCCATTCACC 

>Haplotype N 


ATATC- 



TATATATCCCCTAACAATTTTATCTCCATTATATCCTATGGTCGCTT- 



>Haplotype O

TAAAAGTAATTTATTTTAAAAACATTTTACTGTACACATCACATACGTATATACACGTACACATACCA 

ATATC-TAGTCTTTCCTTATAAATATATATAT-- 

ACATGCTATGTATTACTGTGCATTCATTTATTTTCCATACGATAAGTTAAAGTCCGTATTAATTATCA 

TTAATTTTACATATTACATAATATGTATACTCTTACATATTATATATCCCCTAATAATTTTATTTCCAT 

TATATCCTATGGTCGCTT- 


CCTTCTCGCACCGGGCCCATACATC 

>Haplotype P 


ATATC- 

TAGTCTTTCCTTATAAATATATATATATACATGCTATGTATTACTGTGCATTCATTTATTTTCCATAC 

GATAAGTTAAAGTCCGTATTAATTATCATTAATTTTACATATTACATAATATGTATACTCTTACATATT 

ATATATCCCCTAATAATTTTATTTCCATTATATCCTATGGTCGCTT- 



>Haplotype Q 


ATATC- 





CCTTCTCGCACCGGGCCCATATATC 

>Haplotype R 


ATATC- 


GATAAGTTAAAGCCCGTATTAATTATCATTAATTTTACATATTACATAATATGTATACTCTTACATAT 

TATATATCCCCTAACAATTTTATTTCCATTATATCCTATGGTCGCTT- 



>Haplotype S 


ATATC- 



ATATATCCCCTAACAATTTTATTTCCATTATATCCTATGGTCGCTT- 



>Haplotype T 


ATATC- 

TAGTCTTTCCTTATAAATATATATATATACATGCTATGTATTATTGTGCATTCATTTATTTTCCATAC 





>Haplotype U 


ATATC- 



TATATATCCCCTAATAATTTTATTTCCATTATATCCTATGGTCGCTT- 



>Haplotype V 

TAAAAGTAATTTATTTTAAAAACATTTTACTGTACACATCACATGCGTATATACACGTACACATACC 

AATATC- 


GATAAGTTAAAGCCCGTATTAATTATCATTAATTTTACATATTACATAATATGTATACTCTTACATAT

TATATATCCCCTAATAATTTTATTTCCATTATATCCTATGGTCGCTT- 



>Haplotype W 


ATATC- 



TATATATCCCCTAACAATTTTATTTCCATTATATCCTATGGTCGCTT- 


CCTTCTCGCACCGGGCCCATATATC 

>Haplotype X 


ATATC- 



ATATATCCCCTAATAGTTTTATTTCCATTATATCCTATGGTCGCTT- 



>Outgroup DQ851148 

TAAAAGTAACT-GTTTTAAAAACATTCCACTGTACACACCACATACACACATACA-- 

CATACATATTAATATTCTAGTCTTCTCTTTATAATATTCGTATATACATGCTATGTATTATTGTGCAT 

TCATTTATTTTCCATACGATAAGTTAAAGCCCGTATTAATTATCATTAATTTTACATATTACATAATTT 

GCATGCTCTTACATATTATATGTCCCCTAATATTTTTACTTCCATTATATCCTATGGTCACTC-- 

CATTAGATCACGAGCTTAATCACCATGCCGCGTGAAACCAGCAACCCGCTTGGCAGGGATCCCT 

CTTCTCGCACCGGGCCCATATCTC 

>Outgroup DQ668050 

TAAAAGTAATTTGTTTTAAAAACATTTTACTATATACATCACACACGTACAAGTA------ 

CATACTAATATT- 

TAGTCTTTCCTTATAAATATTCATATATACATGCTATGTATTATTGTGCATTCATTTATTTTCCATAC 

GATAAGTTAAAGCTCGTATTAATTATCATTAATTTTACATATTACATAATATGCATGCTCTTACATAT 

TATATGTCCTCTAACAATTTTATTTCCATTATATCCTATGGTCGCCTAGTATTAGATCACGAGCTTA 

GTCACCATGCCGCGTGAAACCAGCAACCCGCTTGGCAGGGATCCCTCTTCTCGCACCGGGCCCA 

TACCTC 

>Outgroup Pel03FP03 

TAAAAATAATTTATTTTAAAAACATTTTACTGTACACATCACATATATACACATA-- 

TACGCATACCAATATT- 

TAGTCTTTCCTTGTAAATATTCATATATACATGCTATGTATTATTGTGCATTCATTTATTTTCCATAC 

GATAAGTTAAAGCTCGTATTGATTATCATTAATTTTACATATTACATAATATGTATGCTCTTACATAT 

TATATCTCCTCTAACAATTTTATCTCCATTATATCCTATGGTCACCC- 

GTATTAGACCACGAGCTTTATCACCATGCCGCGTGAAACCAGCAACCCGCTCGGCAGGGATCCC 

TCTTCTCGCACCGGGCCCATATCCT



>Haplotype a 


ATATCTAGTCTTTCCTTATAAATATATATATATACATGCTATGTATTACTGTGCATTCATTTATTTTCC 

ATACGATAAGTTAAAGTCCGTATTAATTATCATTAATTTTACATATTACATAATATGTATACTCTTAC 

ATATTATATATCCCCTAATAATTTTATTTCCATTATATCCTATGGTCGCTTATATTAGACCACGAGCT 

TTATCACCATGCCGCGTGAAACCAGCAACCCGCTCGGCAGGGATCCCCCTTCTCGCACCGGGCC 

CATACATCGTGGGGGTAGCTAATAATGA 

>Haplotype b 


ATATCTAGTCTTTCCTTATAAATATA-- 

TATATACATGCTATGTATTACTGTGCATTCATTTATTTTCCATACGATAAGTTAAAGTCCGTATTAAT 

TATCATTAATTTTACATATTACATAATATGTATACTCTTACATATTATATATCCCCTAATAATTTTATT 

TCCATTATATCCTATGGTCGCTTATATTAGACCACGAGCTTTATCACCATGCCGCGTGAAACCAGC 

AACCCGCTCGGCAGGGATCCCCCTTCTCGCACCGGGCCCATACATCGTGGGGGTAGCTAATAAT 

GA 

>Haplotype c 


ATATCTAGTCTTTCCTTATAAATATATATATATACATGCTATGTATTATTGTGCATTCATTTATTTTCC 




CATACATCGTGGGGGTAGCTAATAATGA 

>Haplotype d 






CATACATCGTGGGGGTAGCTAGTAATGA 

>Haplotype e 

TAAAAGTAATTTATTTTAAAAACATTTTACTGTACACATCACATGCGTATATACACGTACACATACC 

AATATCTAGTCTTTCCTTATAAATATATATATATACATGCTATGTATTACTGTGCATTCATTTATTTTC 

CATACGATAAGTTAAAGCCCGTATTAATTATCATTAATTTTACATATTACATAATATGTATACTCTTA 

CATATTATATATCCCCTAATAATTTTATTTCCATTATATCCTATGGTCGCTTATATTAGACCACGAGC 

TTTATCACCATGCCGCGTGAAACCAGCAACCCGCTCGGCAGGGATCCCCCTTCTCGCACCGGGC 

CCATACATCGTGGGGGTAGCTAATAATGA 

>Haplotype f 






CATATATCGTGGGGGTAGCTAATAATGA 

>Haplotype g 



ATACGATAAGTTAAAGCCCGTATTAATTATCATTAATTTTACATATTACATAATATGTATACTCTTAC 



CATACATCGTGGGGGTAGCTAATAATGA

Long-finned pilot whale's samples used in Chapter 4 


Code Date 


sampling 

Location Sex Size 

mtDNA 

haplotype 

365bp 

1 Glo001 07/12/1993 mass stranding Long Bay Auckland female 200 b 

2 Glo002 07/12/1993 mass stranding Long Bay Auckland female 300-400 b 

3 Glo003 07/12/1993 mass stranding Long Bay Auckland female 150 b 

4 Glo004 07/12/1993 mass stranding Long Bay Auckland male 500-600 b 

5 Glo023 07/12/1993 mass stranding Long Bay Auckland male ? b 

6 Glo024 07/12/1993 mass stranding Long Bay Auckland male ? a 

7 Glo025 07/12/1993 mass stranding Long Bay Auckland female ? b 



10 Glo028 07/12/1993 mass stranding Long Bay Auckland female ? a 

11 Glo029 07/12/1993 mass stranding Long Bay Auckland ? ? b 



14 Glo032 07/12/1993 mass stranding Long Bay Auckland male ? b 




18 Glo036 07/12/1993 mass stranding Long Bay Auckland ? ? b 



21 Glo039 07/12/1993 mass stranding Long Bay Auckland male ? c 







28 Glo051 24/10/1999 mass stranding Pitt island female ? a 

29 Glo052 24/10/1999 mass stranding Pitt island ? ? a 


31 Glo054 24/10/1999 mass stranding Pitt island male ? a 

32 Glo055 24/10/1999 mass stranding Pitt island male ? a 

33 Glo056 24/10/1999 mass stranding Pitt island female ? c 

34 Glo057 24/10/1999 mass stranding Pitt island female ? a 



37 Glo060 24/10/1999 mass stranding Pitt island female ? d 


39 Glo066 21-22 dec 00 mass stranding Stewart island female 408 a 


41 Glo068 21-22 dec 00 mass stranding Stewart island male 491 a 





46 Glo073 21-22 dec 00 mass stranding Stewart island male 461 a



49 Glo076 21-22 dec 00 mass stranding Stewart island male 443 g 










59 Glo090 08/01/2003 mass stranding Stewart island male 380 a 

60 Glo091 08/01/2003 mass stranding Stewart island female 420 a 
































92 Glo123 08/01/2003 mass stranding Stewart island female ? a 






98 Glo129 08/01/2003 mass stranding Stewart island female 410 a




















































150 Glo181 08/01/2003 mass stranding Stewart island female 450 a






























180 Glo211 08/01/2003 mass stranding Stewart island 

Mahurangi 

female 390 a 

181 Glo220 04/07/2004 mass stranding Peninsula 

Mahurangi 

male 475 a 


Mahurangi 

female 420 a 


Mahurangi 

female 419 a 


Mahurangi 

female 440 a 


Mahurangi 

female 421 a 


Mahurangi 

female 416 a 


Mahurangi 

female 419 a 


Mahurangi 

female 419 a 


Mahurangi 

male 535 a 

190 Glo229 04/07/2004 mass stranding 

Peninsula female 433 a 

191 Glo230 04/07/2004 mass stranding 

Mahurangi 

Peninsula male 358 a 

192 Glo234 29/11/2004 mass stranding Opoutere Beach male 473 a 

193 Glo235 29/11/2004 mass stranding Opoutere Beach female 315 a 

194 Glo236 29/11/2004 mass stranding Opoutere Beach female 191 a



















213 Glo255 29/11/2004 mass stranding Opoutere Beach female 380 b 






























243 Glo286 28/12/1992 mass stranding Golden Bay female 426 a 

244 Glo287 28/12/1992 mass stranding Golden Bay male 466 a 

245 Glo288 28/12/1992 mass stranding Golden Bay female 433 g 

246 Glo289 28/12/1992 mass stranding Golden Bay female 450 a


248 Glo291 28/12/1992 mass stranding Golden Bay female 398 e 

249 Glo292 28/12/1992 mass stranding Golden Bay female 449 f 



252 Glo296 28/12/1992 mass stranding Golden Bay male 313 g 





257 Glo301 28/12/1992 mass stranding Golden Bay female 434 f 


















275 Glo319 30/12/1992 mass stranding Golden Bay female 177 a

Long-finned pilot whales microsatellite genotypes used in Chapter 4 


CODE EV37 Ppho131 415/416 EV94 GT575 GT5 

1 

GT2 

3 

DlrFCB1 DlrFCB6 409/470 464/465 EV1 GATA53 MK8 

Glo001 178 182 197 199 210 210 275 275 159 159 203 203 72 76 121 129 175 177 194 196 148 148 145 145 274 290 104 104 

Glo002 182 182 195 199 224 232 271 273 153 159 201 203 72 76 121 121 169 169 186 196 148 150 139 157 286 290 96 106 

Glo003 182 182 199 205 224 226 275 275 161 165 203 203 76 78 125 127 169 177 186 194 148 150 149 149 282 290 104 106 

Glo004 172 188 195 197 210 224 271 275 153 161 203 203 76 76 121 123 169 177 188 198 138 138 155 157 278 278 104 106 

Glo023 180 188 197 201 210 224 271 275 159 159 201 203 74 76 125 127 177 177 - - - - 149 149 282 286 106 106 

Glo025 182 182 195 197 224 238 273 275 151 159 203 203 76 76 109 123 177 177 186 190 148 152 155 161 270 278 102 104 

Glo027 172 182 197 197 210 210 275 275 153 161 - - 76 76 125 127 169 177 - - 138 148 147 149 278 290 99 104 

Glo028 180 180 197 197 224 224 273 275 157 167 201 203 72 72 125 125 173 177 186 192 138 148 149 155 282 290 94 104 

Glo030 172 188 195 197 210 224 275 275 153 161 203 203 76 76 121 123 - - - - - - 155 157 278 278 98 104 

Glo031 182 182 195 197 224 238 269 273 151 159 203 203 76 76 109 123 177 177 - - 148 152 155 161 270 278 94 102 

Glo032 172 188 191 199 210 224 271 273 159 161 203 203 72 76 119 125 169 177 186 190 148 148 145 149 274 286 102 104 

Glo033 180 188 195 203 224 232 273 275 153 165 203 203 72 76 123 127 169 169 - - - - 147 159 274 282 98 106 

Glo034 172 180 195 195 226 232 275 275 157 159 203 203 72 78 123 123 169 177 188 190 148 148 147 149 - - 96 104 

Glo035 180 188 197 199 210 210 273 275 - - 203 203 76 76 123 125 - - - - - - 149 149 274 278 94 104 

Glo037 178 182 195 197 224 226 269 273 151 165 201 203 72 72 109 123 169 177 190 196 146 150 147 149 270 282 102 106 

Glo038 180 180 195 195 224 228 269 275 155 165 201 203 72 76 123 125 175 177 186 196 148 150 149 151 282 286 102 110 

Glo039 180 182 195 199 224 228 271 275 151 159 201 203 76 76 127 127 175 177 - - 148 152 149 153 286 290 108 108 

Glo041 180 188 197 201 224 232 273 273 161 165 201 203 76 78 123 123 169 169 186 190 148 148 149 151 286 290 96 106 

Glo042 182 188 197 197 224 224 273 273 - - - - 72 76 123 125 - - - - - - 147 149 278 278 102 102 

Glo043 180 182 195 195 210 230 271 275 151 153 203 203 76 76 119 123 173 175 188 202 148 148 149 149 270 274 104 108 

Glo045 188 194 195 197 224 228 275 275 153 157 203 203 72 76 123 127 169 169 - - - - 145 149 274 290 102 104 

Glo047 178 192 199 199 224 226 273 275 153 153 201 203 72 76 109 127 169 177 186 198 148 148 151 157 274 278 102 102 

Glo051 172 192 193 195 224 224 275 275 159 159 201 203 72 80 121 127 169 177 - - 148 148 147 153 - - - - 

Glo054 184 192 195 195 224 228 275 275 151 155 203 203 72 76 125 125 169 177 184 186 148 150 149 151 - - - - 

Glo055 182 188 185 197 226 226 273 275 151 155 201 203 72 76 119 123 169 177 186 194 148 148 155 163 - - - - 

Glo056 180 180 195 195 224 228 275 275 159 163 201 201 72 76 123 123 169 177 194 196 148 148 147 147 - - - - 

Glo057 180 182 195 199 210 226 271 275 151 151 203 203 76 78 125 129 169 173 194 198 148 152 149 151 - - - - 

Glo060 182 182 195 195 224 228 275 275 153 163 201 203 76 76 125 133 169 177 190 192 148 148 147 147 - - - - 

Glo066 180 188 195 195 226 228 273 275 161 161 201 203 72 76 123 123 169 177 190 196 148 148 139 151 - - - -

Glo067 180 188 197 197 210 226 275 275 151 155 201 203 76 78 121 125 169 169 190 192 148 148 159 159 - - - - 

Glo068 188 190 195 199 210 224 275 275 157 159 201 201 76 76 123 123 169 177 186 190 148 148 149 149 - - - - 

Glo069 182 190 195 199 228 230 271 273 151 157 203 203 72 72 95 125 177 177 188 192 140 148 149 153 - - - - 

Glo070 180 192 195 201 226 230 271 275 153 159 203 203 74 76 123 125 169 177 186 196 146 148 145 153 - - - - 

Glo071 182 190 197 199 210 224 271 273 159 165 201 205 76 76 125 125 169 169 184 186 138 152 149 149 - - - - 

Glo072 192 194 197 197 210 226 269 271 159 159 203 203 76 76 123 127 175 177 186 186 148 148 153 153 - - - - 

Glo073 182 188 193 195 210 230 271 271 151 163 203 203 72 76 121 125 169 177 192 196 140 148 149 153 - - - - 

Glo074 180 180 191 197 224 226 267 275 161 165 201 203 76 76 123 123 169 175 190 196 140 148 139 149 - - - - 

Glo075 180 188 195 195 224 226 273 275 161 161 203 203 72 76 123 125 175 177 194 196 138 148 149 151 - - - - 

Glo076 180 182 197 197 224 224 275 275 155 157 201 203 72 76 125 125 169 169 184 194 148 148 149 149 - - - - 

Glo077 172 180 195 197 224 228 275 275 155 165 203 203 72 76 121 127 161 175 188 194 138 148 151 153 - - - - 

Glo078 180 190 195 195 210 230 275 275 159 165 - - 76 76 107 123 - - 186 196 138 150 149 149 - - - - 

Glo079 180 182 197 197 224 226 271 275 151 159 203 203 76 76 123 125 171 177 186 194 150 152 149 149 - - - - 

Glo080 178 188 195 195 226 226 275 275 161 165 - - 72 76 123 123 - - - - 138 150 149 151 - - - - 

Glo081 182 182 197 201 224 230 271 271 151 153 203 203 72 76 95 121 177 177 192 194 140 140 153 153 - - - - 

Glo082 180 188 195 197 228 228 271 275 151 159 203 203 76 76 123 125 175 177 192 196 142 148 149 149 - - - - 

Glo083 180 192 197 197 224 228 275 275 151 161 - - 76 80 125 129 169 175 - - 140 148 149 149 - - - - 

Glo084 172 180 195 195 226 226 271 275 159 165 203 203 76 80 123 123 169 177 184 190 140 148 145 149 - - - - 

Glo085 172 194 195 195 228 230 275 275 153 155 203 203 76 80 123 123 171 177 186 186 136 148 147 149 - - - - 

Glo090 180 188 197 197 228 230 275 275 151 159 203 203 72 72 123 127 175 177 184 194 140 140 149 157 286 286 96 106 

Glo091 180 192 197 199 228 228 271 271 151 159 201 203 76 80 123 127 177 177 168 188 138 140 145 147 278 282 92 104 

Glo092 178 182 197 197 224 226 273 277 159 159 203 203 76 78 127 127 169 169 186 192 148 148 147 151 290 290 96 106 

Glo093 182 188 191 201 224 238 271 273 151 165 203 203 76 76 123 123 169 175 182 186 148 150 149 153 274 290 104 114 

Glo094 178 194 197 197 210 222 275 277 157 161 201 203 76 76 125 127 169 177 188 194 148 150 149 149 286 290 106 108 

Glo095 180 182 197 199 210 210 271 275 151 159 203 203 76 76 121 123 175 177 186 186 138 148 149 149 270 290 96 102 

Glo096 172 188 183 201 210 224 273 275 151 157 201 203 72 76 117 125 169 169 188 198 148 148 149 163 278 286 102 104 

Glo097 180 188 195 197 224 228 275 275 153 161 203 203 72 76 123 123 173 177 186 196 148 148 149 161 274 274 104 104 

Glo098 188 188 195 199 210 228 275 275 159 161 201 203 72 76 123 123 177 179 186 196 148 150 149 153 274 282 104 110 

Glo099 180 180 197 201 224 224 271 273 151 153 203 205 76 76 109 127 169 169 188 190 138 148 147 149 278 278 104 112 

Glo100 180 180 197 197 224 228 271 275 151 159 201 203 72 76 123 125 169 177 168 186 140 148 145 163 282 290 92 104 

Glo101 180 188 195 201 224 232 271 275 151 159 203 203 72 76 123 125 169 169 186 192 148 148 151 153 274 294 102 104 

Glo102 180 188 191 195 224 226 271 273 151 159 203 203 76 76 121 123 161 175 190 194 148 152 149 153 266 266 98 104 

Glo103 180 182 183 197 224 226 275 275 153 165 203 203 76 76 123 129 169 169 186 192 140 148 149 149 274 278 104 110 

Glo104 180 182 195 197 224 238 275 275 153 161 203 203 72 72 123 125 169 175 186 194 148 148 147 149 274 290 104 106 

Glo105 180 188 195 197 226 232 269 275 159 159 201 203 72 76 109 127 175 175 186 188 148 148 145 149 270 286 102 104

Glo106 178 188 195 197 210 226 269 271 159 159 201 203 72 72 123 127 169 175 190 196 148 150 147 147 282 286 102 110 

Glo107 178 180 197 201 224 226 269 273 151 153 203 205 76 80 109 119 169 177 188 194 148 152 149 149 278 282 104 112 

Glo108 172 188 199 203 224 228 275 275 155 155 203 203 76 76 123 125 169 177 194 196 148 154 149 155 274 286 102 104 

Glo109 188 192 197 205 210 226 275 275 151 153 201 203 72 76 125 127 175 175 186 198 140 148 149 149 282 286 96 104 

Glo110 180 182 193 195 224 226 273 275 165 165 201 203 72 76 123 127 169 169 190 194 146 148 149 157 278 282 96 104 

Glo111 188 188 195 195 228 232 273 275 161 165 201 203 76 76 123 123 173 177 186 194 148 148 149 149 282 286 110 110 

Glo112 180 180 195 195 224 226 271 273 153 155 201 203 76 76 119 123 169 175 188 196 138 138 149 153 274 290 102 106 

Glo113 182 188 195 199 224 226 275 275 151 161 203 203 76 76 125 125 161 175 190 196 148 148 149 149 266 278 104 106 

Glo114 182 188 195 195 224 224 273 275 159 159 203 203 76 80 125 127 169 177 188 194 148 150 149 149 274 286 102 104 

Glo115 182 188 197 201 224 226 275 275 157 159 203 203 76 76 123 123 175 175 186 192 148 152 149 155 282 286 104 106 

Glo116 180 188 193 201 224 228 273 275 157 161 203 203 72 76 125 125 169 169 190 194 148 148 149 157 278 282 98 104 

Glo117 172 188 195 195 210 228 275 275 153 159 203 203 76 76 125 125 169 177 188 190 148 148 147 149 290 290 102 110 

Glo118 180 192 189 195 224 228 271 275 151 151 203 203 72 76 125 125 175 177 184 194 140 148 149 151 278 286 102 106 

Glo119 180 188 197 199 210 224 271 275 159 159 203 203 72 76 121 125 169 175 186 192 138 148 149 149 270 290 102 102 

Glo120 172 182 195 199 224 228 271 275 153 161 203 203 72 76 117 127 171 177 186 192 138 152 147 149 286 290 102 106 

Glo121 188 188 197 199 210 224 275 275 151 161 201 203 72 76 123 123 175 177 186 196 148 150 149 153 270 282 94 110 

Glo122 180 188 195 201 224 228 275 275 159 159 203 203 72 76 125 125 169 169 190 192 148 148 149 149 278 290 102 106 

Glo123 172 192 195 197 228 228 275 275 151 165 203 203 72 76 121 127 169 175 186 192 140 146 149 149 282 286 96 106 

Glo124 182 182 195 195 226 234 273 275 153 159 203 203 72 76 127 127 169 169 196 196 146 150 153 153 270 278 96 104 

Glo125 178 178 195 197 224 228 271 275 151 159 201 201 76 78 123 125 169 177 186 190 148 148 149 153 278 286 102 102 

Glo126 188 188 197 199 226 226 273 275 151 165 201 203 72 72 119 125 169 177 186 190 148 148 149 151 282 286 102 106 

Glo127 182 188 183 197 226 234 271 271 159 159 203 203 72 76 109 127 169 169 186 196 140 148 147 149 282 290 96 104 

Glo128 180 188 199 201 224 226 271 273 155 159 203 203 72 76 123 127 169 177 186 192 138 148 147 153 274 278 102 104 

Glo129 180 180 195 197 224 228 273 273 153 165 203 203 72 76 123 123 169 175 194 196 148 152 147 149 274 278 94 104 

Glo130 180 188 195 197 210 224 271 275 151 159 203 203 76 76 123 127 175 177 186 186 148 148 149 149 270 278 96 102 

Glo131 188 192 195 197 226 228 271 275 151 151 201 203 72 76 125 125 175 177 184 186 140 140 149 151 278 286 104 106 

Glo132 180 188 201 203 224 224 273 275 153 159 201 203 76 76 121 125 169 177 194 196 148 148 147 149 274 286 94 104 

Glo133 180 182 195 197 224 226 273 273 153 153 203 203 76 76 127 129 169 169 186 196 136 150 153 153 278 278 96 102 

Glo134 182 188 197 201 224 228 273 275 157 165 203 203 72 76 121 125 169 169 194 196 140 152 149 153 274 286 102 102 

Glo135 188 194 195 197 224 230 273 275 159 159 203 203 76 76 125 127 169 177 186 186 140 148 147 149 270 290 104 106 

Glo136 182 188 195 197 224 226 271 275 159 159 203 203 72 76 125 127 169 171 190 192 138 150 149 149 282 286 106 108 

Glo137 180 180 195 197 210 210 273 275 151 155 201 203 76 76 117 123 175 177 184 186 148 148 149 153 286 290 96 108 

Glo138 178 188 195 199 226 228 271 275 153 161 203 203 72 76 125 127 177 177 186 194 146 150 149 149 290 290 106 110 

Glo139 188 192 197 199 230 230 273 275 153 165 203 203 72 76 121 125 169 177 184 186 138 148 147 151 282 282 102 102 

Glo140 180 188 197 201 224 226 275 275 159 159 201 203 76 76 123 125 169 175 186 196 138 148 147 149 286 286 104 104

Glo141 180 180 191 195 210 226 273 273 159 165 201 201 72 76 123 125 169 177 194 196 148 154 147 153 270 290 102 106 

Glo142 180 188 197 199 224 224 271 275 153 165 203 203 76 76 127 127 169 175 186 190 148 148 147 147 266 274 96 98 

Glo143 188 194 193 203 210 210 275 275 151 161 203 203 76 76 125 125 169 169 184 188 148 150 149 157 282 290 102 104 

Glo144 182 188 195 195 224 230 275 275 159 165 203 203 76 76 119 125 169 169 186 196 140 148 149 149 270 270 102 104 

Glo145 180 180 195 197 210 224 275 275 151 153 201 203 76 76 123 123 169 177 184 194 148 148 149 153 282 286 102 106 

Glo146 180 182 191 197 226 230 273 275 151 157 201 203 72 76 109 123 175 175 186 186 136 148 147 149 282 286 102 104 

Glo147 188 188 195 197 224 226 271 273 159 161 201 203 76 76 125 125 169 169 188 190 138 148 149 149 274 286 102 108 

Glo148 180 182 195 197 226 232 269 275 159 161 203 203 72 76 109 125 169 175 188 196 136 148 145 149 286 290 98 104 

Glo149 180 180 191 199 224 228 273 275 151 165 203 203 72 76 125 127 169 169 186 196 148 148 147 149 266 282 98 102 

Glo150 180 188 195 195 210 226 271 275 155 159 201 203 72 72 123 123 169 175 192 196 150 152 149 153 278 290 106 108 

Glo151 180 188 195 197 226 228 271 275 159 159 203 203 76 80 95 127 169 175 196 196 138 148 145 149 270 274 102 102 

Glo152 188 188 195 197 210 226 273 275 153 167 201 203 72 76 123 123 169 177 184 186 148 148 139 161 282 286 102 108 

Glo153 188 192 195 195 224 226 271 275 153 159 203 203 76 76 121 127 169 177 184 186 148 150 147 159 282 290 102 104 

Glo154 180 182 197 201 224 226 271 273 157 165 203 203 76 76 123 125 169 173 184 186 148 148 149 149 270 286 102 110 

Glo155 180 188 195 195 224 224 271 273 147 151 203 203 76 76 117 123 169 177 168 192 138 148 147 151 278 278 96 102 

Glo156 180 188 195 197 224 226 273 275 151 159 203 203 76 76 123 123 175 175 186 186 148 148 147 147 274 286 102 104 

Glo157 180 180 197 199 210 210 271 273 151 161 203 203 76 76 123 125 169 175 184 186 148 148 147 149 286 290 96 102 

Glo158 180 192 195 197 226 232 275 275 159 167 203 203 72 80 95 115 169 175 194 198 136 148 139 149 270 278 102 106 

Glo159 178 182 195 201 226 226 273 275 159 161 203 203 72 76 123 127 169 177 186 192 148 148 145 153 278 286 102 106 

Glo160 180 182 195 199 226 226 269 275 155 159 203 205 76 76 123 125 169 177 186 196 140 148 153 155 274 286 102 106 

Glo161 178 188 197 201 210 226 271 273 151 153 203 203 76 76 109 125 169 175 188 192 148 148 147 149 278 290 96 104 

Glo162 178 182 191 197 224 226 273 275 159 165 203 203 76 76 125 125 169 169 192 194 150 152 147 147 270 286 102 102 

Glo163 178 188 191 195 224 226 273 275 151 161 201 203 76 76 123 123 169 169 194 196 142 150 145 149 274 282 102 106 

Glo164 172 180 195 197 224 228 271 273 151 165 201 203 76 76 123 123 169 177 168 186 140 148 147 153 278 286 92 102 

Glo165 188 188 191 197 224 228 275 275 151 165 201 205 76 80 123 127 169 177 194 196 140 150 149 153 274 282 102 104 

Glo166 180 188 193 195 224 228 273 275 151 153 201 203 76 76 119 125 171 175 196 196 138 148 149 159 278 290 102 108 

Glo167 180 192 197 197 224 224 271 273 153 159 203 203 72 76 119 125 169 169 186 186 148 148 147 147 282 290 102 102 

Glo168 182 188 197 201 224 226 271 275 159 161 201 203 76 76 125 127 169 177 186 188 140 148 145 153 274 286 106 106 

Glo169 172 188 195 203 210 228 273 275 153 161 201 203 72 76 117 125 169 169 184 196 146 148 153 157 282 282 102 110 

Glo170 180 180 191 193 224 228 271 271 151 159 203 203 72 76 125 127 169 177 186 196 138 140 149 159 278 278 102 102 

Glo171 182 188 197 199 228 232 269 275 153 165 203 203 76 76 125 125 177 179 194 196 136 148 149 153 278 286 102 106 

Glo172 172 180 197 199 210 228 271 275 155 159 203 203 72 76 123 125 173 177 184 196 148 154 147 149 274 278 102 104 

Glo173 188 188 195 201 210 224 273 273 159 161 203 203 76 80 125 129 169 177 186 194 148 148 149 153 286 290 102 104 

Glo174 180 182 195 201 226 226 271 273 151 165 201 203 76 76 123 123 169 169 168 184 138 148 149 151 278 286 96 106 

Glo175 188 188 197 197 228 234 - - 159 161 203 203 76 76 125 127 169 177 184 192 138 146 149 153 282 286 98 106

Glo176 182 188 197 199 232 232 271 275 153 157 203 203 72 76 123 125 169 177 186 194 136 136 149 149 270 278 102 106 

Glo177 180 188 191 193 224 224 271 273 151 153 201 203 76 76 121 123 169 177 184 186 140 148 149 149 282 290 98 106 

Glo178 182 192 199 199 224 230 273 275 155 165 201 203 72 76 125 135 169 169 184 198 148 148 147 149 282 290 102 108 

Glo179 180 180 191 195 224 228 275 275 159 165 203 203 76 76 123 123 169 175 194 194 146 148 149 149 278 282 96 102 

Glo180 180 188 191 195 224 228 271 275 151 159 201 203 76 76 121 125 161 177 168 190 138 148 149 149 266 278 104 106 

Glo181 178 180 195 197 226 226 275 275 159 161 203 203 72 76 123 123 169 177 192 196 142 148 145 149 278 282 98 106 

Glo182 180 188 197 199 210 228 273 275 153 163 203 203 72 72 125 127 177 177 186 196 150 150 149 149 278 290 98 102 

Glo183 178 188 183 197 222 226 275 277 157 159 203 203 76 78 127 127 169 177 188 192 148 148 147 149 278 290 106 106 

Glo184 178 192 191 195 226 226 273 273 165 165 203 203 76 76 125 127 169 177 186 192 136 152 145 147 278 286 102 106 

Glo185 180 188 195 197 210 226 273 275 153 155 203 203 76 76 121 125 177 177 184 190 138 138 145 153 286 290 106 108 

Glo186 180 182 197 201 226 228 271 273 151 151 201 203 72 76 125 127 169 177 186 186 140 148 153 163 282 290 98 104 

Glo187 180 182 197 199 224 228 271 273 159 159 203 203 76 76 123 125 169 177 186 196 140 148 149 149 274 286 94 102 

Glo188 172 190 197 199 228 234 275 275 155 159 203 203 76 76 123 125 173 177 186 196 148 148 147 153 274 282 102 104 

Glo189 180 192 191 195 224 226 273 275 161 165 203 203 72 76 127 127 173 177 186 190 148 152 147 147 278 282 98 104 

Glo190 180 188 195 195 210 226 271 273 159 165 201 203 76 76 125 127 169 169 186 196 148 150 147 153 270 282 94 102 

Glo191 188 188 197 199 210 226 275 275 163 167 201 203 76 76 123 123 177 177 184 194 148 148 139 153 278 286 102 104 

Glo192 180 188 193 197 228 230 271 275 153 159 203 203 76 76 125 125 169 175 192 196 138 146 149 159 270 278 96 102 

Glo193 182 188 197 205 210 224 275 275 151 161 203 203 72 76 121 123 169 175 186 194 148 148 147 149 270 290 102 104 

Glo194 180 188 195 195 226 228 271 275 159 159 203 203 76 80 125 129 169 169 186 196 148 148 139 157 274 290 98 102 

Glo195 180 188 193 197 228 230 275 275 153 153 203 203 76 76 123 125 169 175 186 186 140 148 149 149 282 286 96 98 

Glo196 172 188 199 199 224 228 271 273 153 153 203 203 72 76 125 127 177 177 186 192 150 152 149 149 274 290 102 106 

Glo197 188 188 195 195 224 232 271 273 153 165 203 203 72 76 125 127 169 177 186 196 140 146 147 149 278 290 104 106 

Glo198 182 188 195 197 224 224 271 273 147 157 201 203 72 76 123 125 169 169 168 186 148 150 145 151 278 278 102 102 

Glo199 180 180 195 197 224 228 - - 159 161 201 203 76 76 123 125 169 169 190 194 138 148 145 149 278 286 96 104 

Glo200 180 192 195 197 226 228 275 275 151 153 203 203 72 76 125 127 169 175 184 186 140 140 149 149 282 286 96 106 

Glo201 182 188 195 197 234 234 271 275 153 159 203 203 72 76 127 127 169 169 186 196 146 148 147 153 270 282 96 104 

Glo202 180 188 195 195 226 230 275 275 159 159 203 203 76 80 95 125 169 175 196 198 138 148 139 145 270 274 98 102 

Glo203 180 188 191 197 210 224 275 275 151 165 203 205 76 76 123 123 177 177 186 196 140 150 149 153 274 282 104 112 

Glo204 180 188 195 195 226 232 273 273 153 165 203 203 72 76 125 125 169 177 184 186 138 148 145 149 278 290 96 106 

Glo205 180 182 199 203 210 228 269 275 151 151 203 203 72 76 127 127 169 169 186 186 148 152 147 149 266 282 98 104 

Glo206 180 188 193 197 224 230 271 275 153 153 203 203 76 76 121 123 169 169 186 196 140 148 149 153 286 290 98 104 

Glo207 188 190 195 197 228 228 275 275 153 159 203 203 76 76 125 125 169 177 188 196 148 148 147 151 290 290 102 110 

Glo208 182 188 197 201 210 224 271 275 151 161 203 203 76 76 123 125 169 177 186 192 148 148 147 149 278 290 104 106 

Glo209 180 188 197 197 226 238 275 275 159 161 203 203 72 76 123 123 169 169 186 192 140 142 145 149 270 278 98 102 

Glo210 180 188 195 197 224 228 273 275 151 153 203 203 72 76 123 123 169 173 186 194 148 148 149 149 278 286 96 98

Glo211 180 188 193 195 228 228 275 275 153 153 203 203 76 76 123 125 169 171 186 186 140 148 147 149 286 290 98 98 

Glo212 180 188 195 197 226 228 275 275 159 159 201 203 76 80 95 127 169 175 186 198 148 148 145 149 270 274 98 104 

Glo213 182 188 197 197 226 228 271 275 151 159 203 203 72 76 125 127 175 177 186 196 146 148 145 153 270 286 104 106 

Glo220 180 182 195 197 228 228 273 273 151 161 203 203 76 76 125 127 169 177 190 198 152 152 149 153 282 286 - - 

Glo221 180 188 197 197 224 230 271 277 157 159 201 203 72 76 119 121 169 177 184 186 148 152 147 155 278 286 - - 

Glo222 180 188 197 199 224 228 269 275 157 161 203 203 72 76 123 123 169 173 168 198 136 150 155 159 278 278 - - 

Glo223 180 180 195 195 210 224 273 275 159 161 - - 72 72 123 127 173 175 168 186 136 148 145 147 278 282 - - 

Glo224 188 190 195 201 210 224 271 271 151 167 201 203 76 78 121 123 175 177 192 196 138 146 149 153 290 290 - - 

Glo225 178 194 193 203 210 224 275 275 153 161 203 203 76 76 125 125 177 177 186 186 138 148 147 149 278 282 - - 

Glo226 188 190 195 197 224 224 267 271 161 165 203 203 72 76 123 123 169 169 186 194 148 148 147 161 282 290 - - 

Glo227 180 180 195 195 226 228 273 275 151 161 203 203 76 76 121 127 169 177 186 190 148 152 149 153 282 286 - - 

Glo228 178 182 195 197 210 228 275 275 157 159 203 203 72 76 125 125 175 177 186 196 148 148 147 157 286 290 - - 

Glo229 184 192 197 199 226 238 271 275 151 153 203 203 76 76 109 123 169 173 186 194 140 148 149 149 274 286 - - 

Glo230 178 180 193 199 226 228 271 275 161 165 203 203 72 76 123 125 169 169 184 196 138 148 143 151 282 290 - - 

Glo234 180 182 195 195 224 224 275 275 161 165 203 203 72 76 121 127 169 175 194 196 148 148 153 155 274 286 98 104 

Glo235 180 182 195 197 224 230 275 275 153 161 203 203 76 76 125 125 169 169 190 192 150 152 149 153 286 286 104 106 

Glo236 172 188 195 199 210 228 275 275 153 159 203 203 72 76 119 123 169 173 186 188 148 148 153 153 274 294 102 104 

Glo237 182 188 195 199 210 210 275 275 153 157 203 203 72 76 123 127 177 177 188 194 146 148 147 149 290 294 102 104 

Glo238 188 190 195 197 224 224 273 275 159 163 201 203 76 76 109 125 169 175 186 196 136 148 149 149 282 286 94 102 

Glo239 172 188 195 195 224 226 275 275 155 165 203 203 72 76 123 127 177 177 186 194 148 152 147 151 282 290 - - 

Glo240 172 192 193 195 210 226 271 275 153 161 203 203 76 76 123 125 177 177 186 194 148 148 149 149 278 286 106 106 

Glo241 188 188 195 197 210 224 275 275 151 163 203 203 76 76 125 125 169 173 186 198 136 148 149 151 278 282 102 104 

Glo242 180 188 195 195 210 224 275 275 161 163 203 203 76 76 117 125 169 177 194 198 136 148 149 155 274 282 96 102 

Glo243 182 192 197 197 224 230 271 275 151 159 201 203 76 76 127 127 169 169 186 196 140 148 147 155 278 282 104 110 

Glo244 188 188 197 197 224 230 275 275 159 167 203 203 76 78 119 125 169 169 186 186 146 150 147 149 290 290 102 106 

Glo245 178 192 197 205 228 230 275 275 159 161 203 203 76 76 117 125 169 175 186 194 140 148 151 155 278 290 98 104 

Glo246 188 194 191 197 210 230 273 275 165 167 203 203 72 78 119 123 169 169 186 190 146 148 147 149 266 290 96 106 

Glo247 180 188 201 203 224 226 275 275 153 165 203 203 72 76 123 125 175 175 186 186 148 148 159 167 286 294 102 104 

Glo248 182 188 195 195 226 232 275 275 159 165 201 203 72 72 123 123 169 175 188 194 138 148 139 149 282 282 104 106 

Glo249 180 182 201 203 224 226 275 275 165 165 203 203 72 76 123 125 169 175 186 196 138 148 149 159 278 286 104 108 

Glo250 188 188 191 195 210 228 275 275 151 153 203 203 76 76 123 125 175 179 194 196 140 148 149 149 286 290 102 104 

Glo251 180 188 195 195 224 230 275 275 153 161 201 201 76 76 119 123 169 175 184 186 140 148 149 149 282 286 102 102 

Glo252 180 188 191 195 230 230 273 275 153 159 201 203 76 76 123 125 169 175 192 194 146 148 153 153 266 282 104 112 

Glo253 172 188 195 197 210 226 275 275 159 159 203 203 72 80 117 125 169 169 186 186 138 148 145 149 278 282 104 112 

Glo254 188 192 195 195 226 226 271 275 159 159 201 203 72 76 119 127 169 177 196 198 138 140 153 165 282 282 102 106

Glo255 178 188 193 197 228 228 271 271 151 159 201 203 72 76 123 125 175 177 186 188 136 152 151 157 278 278 - - 

Glo256 182 188 195 199 224 224 269 271 153 153 203 203 76 78 127 127 169 175 186 188 140 148 145 149 278 290 98 106 

Glo257 188 188 195 201 210 226 273 275 159 161 203 203 72 76 123 125 169 175 186 194 138 148 147 149 282 282 102 104 

Glo258 180 182 195 197 228 230 273 275 153 167 201 201 76 76 123 125 169 175 192 194 140 146 149 153 266 278 102 112 

Glo259 180 188 191 203 210 224 275 275 151 165 203 203 72 76 125 127 169 175 194 194 138 148 149 153 286 290 98 104 

Glo260 180 188 199 199 224 228 271 273 153 165 201 203 76 78 119 127 169 175 186 188 140 150 149 149 278 278 98 112 

Glo261 188 192 195 195 224 228 273 275 151 151 203 203 76 76 123 125 177 179 186 194 140 148 149 149 286 290 104 104 

Glo262 182 188 195 195 210 228 275 275 159 167 203 203 72 76 123 123 169 175 188 188 148 148 149 153 274 290 102 106 

Glo263 182 192 195 201 224 228 271 275 151 165 203 203 76 76 121 123 177 177 186 190 138 150 143 149 274 286 96 106 

Glo264 188 188 195 197 210 232 273 275 161 165 203 203 72 76 119 123 169 171 186 192 138 148 147 155 278 290 102 106 

Glo265 172 180 195 197 224 230 275 275 153 159 201 203 76 76 119 121 169 175 184 186 138 140 147 149 282 290 102 104 

Glo266 182 182 193 195 224 228 271 275 165 165 201 203 76 76 123 123 169 175 194 194 148 152 145 147 286 286 102 106 

Glo267 180 188 195 195 224 232 275 275 153 159 201 203 72 76 121 127 175 177 186 192 138 148 147 149 274 290 102 104 

Glo268 188 194 195 197 224 228 273 275 161 165 203 203 72 76 125 127 169 169 186 194 148 148 149 155 266 290 102 102 

Glo269 188 188 197 203 224 224 273 275 143 161 201 203 76 76 125 127 177 177 186 196 148 150 147 155 286 286 102 106 

Glo270 180 182 191 197 224 228 275 275 153 161 201 203 72 76 123 133 171 175 194 194 146 148 153 155 266 282 94 112 

Glo271 180 192 197 197 210 228 273 275 159 165 203 203 72 76 95 123 169 175 184 192 146 148 149 153 282 290 102 104 

Glo272 182 188 191 193 228 228 275 275 159 165 201 201 76 76 123 125 171 175 190 194 140 152 147 147 274 286 102 106 

Glo273 180 188 199 199 224 224 271 271 153 153 201 203 76 78 119 125 169 169 186 186 140 140 147 149 274 278 98 110 

Glo274 188 192 195 197 224 226 271 271 159 165 201 203 72 76 123 127 177 177 190 198 138 140 143 153 274 282 106 106 

Glo275 172 188 195 195 224 232 273 275 159 165 203 203 72 76 123 123 175 177 186 194 136 148 147 149 282 286 106 106 

Glo276 182 188 197 197 228 230 273 273 165 167 203 203 76 78 125 133 169 169 196 196 148 148 145 153 286 290 96 102 

Glo277 180 188 195 197 210 226 275 275 155 161 203 205 76 76 123 127 169 177 186 186 148 148 147 149 274 286 102 106 

Glo278 180 188 195 197 210 224 273 275 153 161 201 203 72 76 123 125 169 175 186 188 140 148 - - 282 282 102 104 

Glo279 172 182 195 195 226 230 273 275 153 159 201 203 76 76 125 125 169 177 186 192 146 152 149 149 266 286 104 112 

Glo280 182 188 197 199 228 228 271 271 153 159 203 203 76 76 123 123 175 177 198 198 140 154 147 153 274 286 96 112 

Glo281 180 188 195 195 210 230 275 275 159 167 201 203 72 72 123 125 169 177 188 192 136 148 149 159 274 274 104 106 

Glo282 180 188 191 195 228 232 271 275 155 161 203 203 72 76 119 123 169 175 186 186 148 152 149 149 286 290 98 106 

Glo283 180 182 197 199 210 224 273 275 159 159 203 203 76 76 123 127 169 175 186 188 140 148 147 149 290 290 106 106 

Glo284 180 180 191 195 224 230 267 275 151 161 201 203 76 76 119 123 169 169 186 196 140 148 149 149 282 290 102 102 

Glo286 188 192 195 197 224 224 271 273 159 165 203 203 76 76 125 131 175 177 186 200 136 152 149 149 278 286 102 102 

Glo287 180 188 197 199 210 226 273 275 159 159 203 203 76 80 121 123 169 179 184 186 150 150 147 149 266 282 96 106 

Glo288 180 182 195 195 210 226 271 275 159 161 203 203 72 76 123 125 175 177 186 194 148 148 149 151 274 278 106 106 

Glo289 180 180 195 197 210 228 273 275 151 159 203 203 76 76 121 125 177 179 184 186 140 150 147 151 278 282 98 102 

Glo290 182 182 195 201 226 230 273 275 157 159 203 203 76 76 125 127 169 177 186 188 148 148 139 155 278 282 96 100

Glo291 178 188 195 199 210 232 269 271 161 165 203 203 72 76 123 129 169 171 188 194 148 148 153 153 278 286 102 112 

Glo292 180 182 197 203 224 226 273 273 153 159 201 203 72 76 125 125 177 177 190 194 136 148 149 149 282 282 106 112 

Glo294 180 194 195 195 226 228 275 275 151 159 201 203 72 76 125 127 177 177 186 192 136 150 151 151 282 286 104 104 

Glo295 182 188 191 195 226 226 273 275 159 165 201 203 72 76 123 123 177 177 190 196 148 152 145 153 282 282 104 106 

Glo296 180 188 197 199 226 228 271 275 157 159 201 203 72 76 123 125 169 177 188 194 136 146 147 147 290 290 102 102 

Glo297 180 188 197 199 226 228 275 275 159 165 201 203 72 74 123 125 175 177 - - 136 140 149 153 282 290 106 106 

Glo298 172 182 195 195 224 226 271 273 159 161 203 203 72 76 123 123 169 175 188 192 148 148 149 151 282 290 98 102 

Glo299 194 194 193 195 224 228 273 273 151 153 201 203 76 76 123 125 169 177 194 196 148 154 149 149 286 286 102 106 

Glo300 182 188 195 195 - - 273 275 157 159 203 203 76 76 123 125 175 177 188 198 148 148 147 149 278 282 104 106 

Glo301 182 188 195 203 224 228 273 275 165 167 201 203 76 76 123 137 175 175 186 196 148 150 149 153 274 282 98 106 

Glo302 180 182 195 197 224 226 271 275 157 161 203 203 72 76 123 123 169 175 188 192 146 148 147 149 286 290 106 106 

Glo303 188 188 191 203 210 226 275 275 161 161 203 203 76 76 123 127 169 175 168 190 138 148 147 157 282 286 102 106 

Glo304 180 180 195 197 224 224 273 275 155 161 203 203 72 72 123 127 169 175 186 198 148 152 149 149 286 286 98 104 

Glo305 180 188 195 201 210 210 271 275 161 165 203 203 72 76 123 125 169 169 184 198 140 148 151 157 282 286 104 104 

Glo306 180 180 195 201 210 224 271 275 153 165 203 203 72 72 125 131 169 177 184 192 138 140 153 157 274 282 102 110 

Glo307 180 188 191 197 210 228 271 273 151 161 203 203 76 76 123 125 177 177 186 192 140 148 147 153 274 282 96 98 

Glo308 188 188 195 195 224 224 275 275 155 157 203 203 72 76 119 123 169 177 186 192 142 152 149 157 274 290 102 108 

Glo309 180 194 193 197 210 230 273 275 153 161 203 203 76 76 123 125 177 177 186 192 148 148 147 153 282 290 100 102 

Glo310 178 188 193 197 224 228 275 275 151 151 203 203 76 76 127 129 169 177 186 196 146 148 149 155 282 282 98 102 

Glo311 180 188 195 199 226 228 273 275 155 159 201 203 76 76 109 125 169 177 188 188 148 150 147 149 282 286 102 106 

Glo312 182 188 195 203 210 224 273 275 151 159 203 203 72 72 123 125 169 169 186 196 138 148 149 151 270 274 102 102 

Glo313 194 194 195 197 224 228 273 275 151 153 203 203 72 76 121 125 175 177 186 194 148 148 139 145 270 278 102 102 

Glo314 182 182 195 197 226 226 275 275 151 159 203 203 72 78 125 125 169 177 194 196 136 148 147 149 274 274 96 114 

Glo315 188 188 191 195 228 230 273 275 151 159 201 203 72 76 123 123 169 177 188 190 148 148 159 161 282 282 102 102 

Glo316 180 188 197 197 224 228 273 275 159 159 203 203 76 76 121 123 169 173 186 190 148 150 147 149 278 282 104 106 

Glo317 178 188 193 197 224 228 275 275 159 159 203 203 76 76 119 121 169 173 186 192 140 150 149 149 282 282 102 106 

Glo318 180 182 197 197 224 232 275 275 159 161 203 203 72 76 121 123 169 177 186 190 136 136 147 149 274 290 98 106 

Glo319 182 188 195 197 226 228 275 275 153 159 203 203 76 76 123 123 169 177 186 186 138 140 153 157 278 290 102 112


Long-finned pilot whales microsatellite genotypes used in Chapter 5 


Code Sex EV37 Ppho131 415/416 MK9 EV94 GT575 GT51 MK5 GT23 Ppho110 DlrFCB1 

Glo090 male 180 188 197 197 228 230 157 161 275 275 151 159 203 203 219 219 72 72 105 109 123 127 

Glo091 female 180 192 197 199 228 228 161 163 271 271 151 159 201 203 219 219 76 80 109 109 123 127 

Glo092 female 178 182 197 197 224 226 161 161 273 277 159 159 203 203 219 219 76 78 109 109 127 127 

Glo093 male 182 188 191 201 224 238 159 163 271 273 151 165 203 203 217 219 76 76 109 109 123 123 

Glo094 male 178 194 197 197 210 222 161 161 275 277 157 161 201 203 219 219 76 76 109 109 125 127 

Glo095 female 180 182 197 199 210 210 159 161 271 275 151 159 203 203 219 219 76 76 109 113 121 123 

Glo096 male 172 188 183 201 210 224 157 161 273 275 151 157 201 203 217 219 72 76 105 109 117 125 

Glo097 male 180 188 195 197 224 228 161 161 275 275 153 161 203 203 215 219 72 76 107 109 123 123 

Glo098 female 188 188 195 199 210 228 159 161 275 275 159 161 201 203 219 221 72 76 109 109 123 123 

Glo099 female 180 180 197 201 224 224 159 161 271 273 151 153 203 205 219 219 76 76 109 109 109 127 

Glo100 female 180 180 197 197 224 228 161 163 271 275 151 159 201 203 219 219 72 76 109 109 123 125 

Glo101 female 180 188 195 201 224 232 159 159 271 275 151 159 203 203 217 219 72 76 109 109 123 125 

Glo102 male 180 188 191 195 224 226 159 161 271 273 151 159 203 203 219 223 76 76 109 109 121 123 

Glo103 female 180 182 183 197 224 226 161 161 275 275 153 165 203 203 219 219 76 76 109 109 123 129 

Glo104 male 180 182 195 197 224 238 159 161 275 275 153 161 203 203 219 219 72 72 109 109 123 125 

Glo105 male 180 188 195 197 226 232 161 161 269 275 159 159 201 203 217 221 72 76 107 109 109 127 

Glo106 female 178 188 195 197 210 226 159 161 269 271 159 159 201 203 219 219 72 72 109 113 123 127 

Glo107 female 178 180 197 201 224 226 159 161 269 273 151 153 203 205 219 225 76 80 109 109 109 119 

Glo108 female 172 188 199 203 224 228 159 163 275 275 155 155 203 203 219 221 76 76 109 109 123 125 

Glo109 female 188 192 197 205 210 226 161 163 275 275 151 153 201 203 217 219 72 76 109 109 125 127 

Glo110 male 180 182 193 195 224 226 161 161 273 275 165 165 201 203 219 223 72 76 109 109 123 127 

Glo111 male 188 188 195 195 228 232 161 163 273 275 161 165 201 203 219 221 76 76 109 109 123 123 

Glo112 female 180 180 195 195 224 226 159 161 271 273 153 155 201 203 219 219 76 76 109 109 119 123 

Glo113 female 182 188 195 199 224 226 161 161 275 275 151 161 203 203 219 219 76 76 107 109 125 125 

Glo114 male 182 188 195 195 224 224 161 163 273 275 159 159 203 203 219 219 76 80 109 109 125 127 

Glo115 female 182 188 197 201 224 226 159 159 275 275 157 159 203 203 217 219 76 76 109 109 123 123

Glo116 female 180 188 193 201 224 228 159 161 273 275 157 161 203 203 219 219 72 76 109 109 125 125 

Glo117 female 172 188 195 195 210 228 159 159 275 275 153 159 203 203 217 219 76 76 109 111 125 125 

Glo118 male 180 192 189 195 224 228 161 161 271 275 151 151 203 203 215 219 72 76 109 109 125 125 

Glo119 male 180 188 197 199 210 224 159 161 271 275 159 159 203 203 219 219 72 76 109 109 121 125 

Glo120 female 172 182 195 199 224 228 159 159 271 275 153 161 203 203 219 219 72 76 109 109 117 127 

Glo121 male 188 188 197 199 210 224 161 163 275 275 151 161 201 203 217 219 72 76 107 109 123 123 

Glo122 male 180 188 195 201 224 228 159 161 275 275 159 159 203 203 217 217 72 76 111 113 125 125 

Glo123 female 172 192 195 197 228 228 157 161 275 275 151 165 203 203 219 219 72 76 109 109 121 127 

Glo124 female 182 182 195 195 226 234 159 161 273 275 153 159 203 203 219 223 72 76 109 109 127 127 

Glo125 male 178 178 195 197 224 228 159 161 271 275 151 159 201 201 219 219 76 78 109 109 123 125 

Glo126 female 188 188 197 199 226 226 159 161 273 275 151 165 201 203 217 219 72 72 109 109 119 125 

Glo127 male 182 188 183 197 226 234 159 161 271 271 159 159 203 203 217 219 72 76 109 109 109 127 

Glo128 female 180 188 199 201 224 226 161 161 271 273 155 159 203 203 219 219 72 76 109 109 123 127 

Glo129 female 180 180 195 197 224 228 159 161 273 273 153 165 203 203 217 219 72 76 109 109 123 123 

Glo130 female 180 188 195 197 210 224 161 161 271 275 151 159 203 203 217 219 76 76 109 113 123 127 

Glo131 male 188 192 195 197 226 228 161 163 271 275 151 151 201 203 217 219 72 76 109 109 125 125 

Glo132 female 180 188 201 203 224 224 159 163 273 275 153 159 201 203 217 219 76 76 109 109 121 125 

Glo133 male 180 182 195 197 224 226 159 159 273 273 153 153 203 203 219 223 76 76 109 109 127 129 

Glo134 female 182 188 197 201 224 228 161 163 273 275 157 165 203 203 219 219 72 76 109 109 121 125 

Glo135 male 188 194 195 197 224 230 159 163 273 275 159 159 203 203 219 219 76 76 109 111 125 127 

Glo136 male 182 188 195 197 224 226 161 163 271 275 159 159 203 203 219 219 72 76 109 109 125 127 

Glo137 female 180 180 195 197 210 210 161 161 273 275 151 155 201 203 219 219 76 76 109 109 117 123 

Glo138 female 178 188 195 199 226 228 159 159 271 275 153 161 203 203 217 219 72 76 109 109 125 127 

Glo139 female 188 192 197 199 230 230 161 161 273 275 153 165 203 203 219 219 72 76 109 109 121 125 

Glo140 female 180 188 197 201 224 226 163 163 275 275 159 159 201 203 219 219 76 76 109 109 123 125 

Glo141 male 180 180 191 195 210 226 159 161 273 273 159 165 201 201 219 219 72 76 109 109 123 125 

Glo142 male 180 188 197 199 224 224 159 159 271 275 153 165 203 203 217 219 76 76 109 109 127 127 

Glo143 male 188 194 193 203 210 210 159 161 275 275 151 161 203 203 219 219 76 76 109 109 125 125 

Glo144 female 182 188 195 195 224 230 161 163 275 275 159 165 203 203 219 219 76 76 109 111 119 125 

Glo145 male 180 180 195 197 210 224 159 161 275 275 151 153 201 203 219 223 76 76 109 109 123 123 

Glo146 female 180 182 191 197 226 230 161 163 273 275 151 157 201 203 219 221 72 76 109 109 109 123 

Glo147 female 188 188 195 197 224 226 161 163 271 273 159 161 201 203 217 219 76 76 109 109 125 125 

Glo148 female 180 182 195 197 226 232 159 161 269 275 159 161 203 203 217 219 72 76 109 109 109 125 

Glo149 female 180 180 191 199 224 228 159 159 273 275 151 165 203 203 217 219 72 76 109 111 125 127

Glo150 male 180 188 195 195 210 226 159 159 271 275 155 159 201 203 217 221 72 72 109 109 123 123 

Glo151 male 180 188 195 197 226 228 159 161 271 275 159 159 203 203 219 225 76 80 109 109 95 127 

Glo152 male 188 188 195 197 210 226 159 159 273 275 153 167 201 203 217 223 72 76 109 111 123 123 

Glo153 female 188 192 195 195 224 226 161 161 271 275 153 159 203 203 219 219 76 76 109 109 121 127 

Glo154 female 180 182 197 201 224 226 161 161 271 273 157 165 203 203 219 221 76 76 109 109 123 125 

Glo155 female 180 188 195 195 224 224 163 163 271 273 147 151 203 203 219 219 76 76 109 109 117 123 

Glo156 male 180 188 195 197 224 226 159 161 273 275 151 159 203 203 219 219 76 76 109 109 123 123 

Glo157 female 180 180 197 199 210 210 159 161 271 273 151 161 203 203 217 219 76 76 109 109 123 125 

Glo158 male 180 192 195 197 226 232 159 161 275 275 159 167 203 203 217 219 72 80 109 109 95 115 

Glo159 female 178 182 195 201 226 226 159 161 273 275 159 161 203 203 219 219 72 76 109 109 123 127 

Glo160 female 180 182 195 199 226 226 161 163 269 275 155 159 203 205 219 219 76 76 109 111 123 125 

Glo161 female 178 188 197 201 210 226 157 159 271 273 151 153 203 203 217 219 76 76 109 109 109 125 

Glo162 female 178 182 191 197 224 226 161 161 273 275 159 165 203 203 219 219 76 76 109 109 125 125 

Glo163 female 178 188 191 195 224 226 159 159 273 275 151 161 201 203 219 219 76 76 109 109 123 123 

Glo164 male 172 180 195 197 224 228 161 161 271 273 151 165 201 203 219 219 76 76 109 109 123 123 

Glo165 male 188 188 191 197 224 228 161 163 275 275 151 165 201 205 219 219 76 80 109 109 123 127 

Glo166 female 180 188 193 195 224 228 161 163 273 275 151 153 201 203 219 219 76 76 109 109 119 125 

Glo167 male 180 192 197 197 224 224 159 161 271 273 153 159 203 203 219 221 72 76 109 109 119 125 

Glo168 male 182 188 197 201 224 226 159 159 271 275 159 161 201 203 217 219 76 76 109 109 125 127 

Glo169 male 172 188 195 203 210 228 161 161 273 275 153 161 201 203 219 219 72 76 109 109 117 125 

Glo170 male 180 180 191 193 224 228 161 161 271 271 151 159 203 203 219 223 72 76 109 109 125 127 

Glo171 male 182 188 197 199 228 232 159 161 269 275 153 165 203 203 219 219 76 76 109 109 125 125 

Glo172 female 172 180 197 199 210 228 159 163 271 275 155 159 203 203 217 221 72 76 109 109 123 125 

Glo173 male 188 188 195 201 210 224 159 163 273 273 159 161 203 203 217 219 76 80 109 109 125 129 

Glo174 male 180 182 195 201 226 226 161 163 271 273 151 165 201 203 217 219 76 76 109 109 123 123 

Glo175 male 188 188 197 197 228 234 - - - - 159 161 203 203 217 219 76 76 109 109 125 127 

Glo176 female 182 188 197 199 232 232 159 159 271 275 153 157 203 203 219 219 72 76 109 109 123 125 

Glo177 male 180 188 191 193 224 224 159 161 271 273 151 153 201 203 219 227 76 76 109 109 121 123 

Glo178 male 182 192 199 199 224 230 161 161 273 275 155 165 201 203 219 219 72 76 109 109 125 135 

Glo179 female 180 180 191 195 224 228 161 161 275 275 159 165 203 203 217 219 76 76 109 109 123 123 

Glo180 female 180 188 191 195 224 228 159 161 271 275 151 159 201 203 219 219 76 76 109 109 121 125 

Glo181 female 178 180 195 197 226 226 159 161 275 275 159 161 203 203 219 219 72 76 109 109 123 123 

Glo182 female 180 188 197 199 210 228 161 161 273 275 153 163 203 203 217 219 72 72 109 109 125 127 

Glo183 female 178 188 183 197 222 226 161 161 275 277 157 159 203 203 219 219 76 78 109 109 127 127

Glo184 female 178 192 191 195 226 226 159 161 273 273 165 165 203 203 219 219 76 76 109 109 125 127 

Glo185 female 180 188 195 197 210 226 159 161 273 275 153 155 203 203 219 219 76 76 109 109 121 125 

Glo186 female 180 182 197 201 226 228 161 161 271 273 151 151 201 203 219 219 72 76 109 109 125 127 

Glo187 female 180 182 197 199 224 228 161 163 271 273 159 159 203 203 219 221 76 76 109 109 123 125 

Glo188 male 172 190 197 199 228 234 159 161 275 275 155 159 203 203 217 219 76 76 109 109 123 125 

Glo189 female 180 192 191 195 224 226 161 161 273 275 161 165 203 203 217 219 72 76 109 109 127 127 

Glo190 female 180 188 195 195 210 226 159 161 271 273 159 165 201 203 219 219 76 76 109 109 125 127 

Glo191 female 188 188 197 199 210 226 159 161 275 275 163 167 201 203 217 221 76 76 109 111 123 123 

Glo192 female 180 188 193 197 228 230 161 161 271 275 153 159 203 203 217 219 76 76 109 109 125 125 

Glo193 female 182 188 197 205 210 224 161 161 275 275 151 161 203 203 217 219 72 76 109 113 121 123 

Glo194 female 180 188 195 195 226 228 159 161 271 275 159 159 203 203 217 219 76 80 109 109 125 129 

Glo195 female 180 188 193 197 228 230 159 163 275 275 153 153 203 203 219 223 76 76 109 109 123 125 

Glo196 female 172 188 199 199 224 228 159 161 271 273 153 153 203 203 219 219 72 76 109 109 125 127 

Glo197 female 188 188 195 195 224 232 159 161 271 273 153 165 203 203 217 219 72 76 109 109 125 127 

Glo198 female 182 188 195 197 224 224 159 163 271 273 147 157 201 203 219 219 72 76 109 109 123 125 

Glo199 female 180 180 195 197 224 228 - - - - 159 161 201 203 219 219 76 76 109 109 123 125 

Glo200 female 180 192 195 197 226 228 157 161 275 275 151 153 203 203 217 219 72 76 109 109 125 127 

Glo201 female 182 188 195 197 234 234 157 161 271 275 153 159 203 203 219 223 72 76 109 113 127 127 

Glo202 female 180 188 195 195 226 230 159 159 275 275 159 159 203 203 219 219 76 80 109 109 95 125 

Glo203 female 180 188 191 197 210 224 161 163 275 275 151 165 203 205 219 219 76 76 109 109 123 123 

Glo204 female 180 188 195 195 226 232 157 159 273 273 153 165 203 203 219 219 72 76 109 109 125 125 

Glo205 male 180 182 199 203 210 228 159 161 269 275 151 151 203 203 217 219 72 76 109 111 127 127 

Glo206 female 180 188 193 197 224 230 159 159 271 275 153 153 203 203 219 219 76 76 109 109 121 123 

Glo207 male 188 190 195 197 228 228 159 161 275 275 153 159 203 203 219 219 76 76 109 109 125 125 

Glo208 female 182 188 197 201 210 224 161 161 271 275 151 161 203 203 215 219 76 76 109 109 123 125 

Glo209 female 180 188 197 197 226 238 159 159 275 275 159 161 203 203 219 219 72 76 109 109 123 123 

Glo210 male 180 188 195 197 224 228 159 161 273 275 151 153 203 203 219 223 72 76 109 109 123 123 

Glo211 female 180 188 193 195 228 228 159 161 275 275 153 153 203 203 219 223 76 76 109 109 123 125 

DlrFCB6 409/470 464/465 EV1 GT6 MK6 GATA53 MK8 GT39 X Y 

175 177 184 194 140 140 149 157 190 190 134 138 286 286 96 106 139 151 25.00 59.00 

177 177 168 188 138 140 145 147 190 194 138 138 278 282 92 104 139 151 55.00 58.00

169 169 186 192 148 148 147 151 190 190 138 138 290 290 96 106 139 151 66.00 50.00 

169 175 182 186 148 150 149 153 190 204 138 138 274 290 104 114 139 155 73.00 54.00 

169 177 188 194 148 150 149 149 190 190 138 138 286 290 106 108 139 139 84.00 57.00 

175 177 186 186 138 148 149 149 190 190 138 138 270 290 96 102 139 151 110.00 41.00 

169 169 188 198 148 148 149 163 190 190 138 138 278 286 102 104 139 151 109.00 58.00 

173 177 186 196 148 148 149 161 190 190 138 140 274 274 104 104 151 151 110.00 64.00 

177 179 186 196 148 150 149 153 190 190 138 140 274 282 104 110 151 153 123.00 51.00 

169 169 188 190 138 148 147 149 190 204 138 138 278 278 104 112 139 151 134.00 67.00 

169 177 168 186 140 148 145 163 190 190 138 138 282 290 92 104 151 151 148.00 69.00 

169 169 186 192 148 148 151 153 204 204 138 138 274 294 102 104 151 151 164.00 61.00 

161 175 190 194 148 152 149 153 190 204 138 138 266 266 98 104 151 151 149.00 46.00 

169 169 186 192 140 148 149 149 190 190 138 138 274 278 104 110 151 153 151.00 40.00 

169 175 186 194 148 148 147 149 190 190 138 138 274 290 104 106 151 151 172.00 46.00 

175 175 186 188 148 148 145 149 190 190 138 138 270 286 102 104 151 151 180.00 46.00 

169 175 190 196 148 150 147 147 190 190 138 138 282 286 102 110 139 153 189.00 44.00 

169 177 188 194 148 152 149 149 190 204 138 138 278 282 104 112 139 139 181.00 54.00 

169 177 194 196 148 154 149 155 190 204 138 140 274 286 102 104 139 151 208.00 65.00 

175 175 186 198 140 148 149 149 190 190 138 140 282 286 96 104 139 151 212.00 59.00 

169 169 190 194 146 148 149 157 190 190 138 138 278 282 96 104 139 151 233.00 58.00 

173 177 186 194 148 148 149 149 190 190 138 138 282 286 110 110 151 153 256.00 68.00 

169 175 188 196 138 138 149 153 190 190 138 138 274 290 102 106 139 151 256.00 62.00 

161 175 190 196 148 148 149 149 190 190 138 138 266 278 104 106 151 151 267.00 60.00 

169 177 188 194 148 150 149 149 190 190 138 140 274 286 102 104 139 151 287.00 55.00 

175 175 186 192 148 152 149 155 190 190 138 138 282 286 104 106 151 151 296.00 74.00 

169 169 190 194 148 148 149 157 190 190 138 138 278 282 98 104 151 153 290.00 70.00 

169 177 188 190 148 148 147 149 190 190 138 138 290 290 102 110 139 151 300.00 58.00 

175 177 184 194 140 148 149 151 190 204 138 138 278 286 102 106 139 151 327.00 53.00 

169 175 186 192 138 148 149 149 190 190 138 138 270 290 102 102 139 139 340.00 50.00 

171 177 186 192 138 152 147 149 190 190 138 138 286 290 102 106 139 139 344.00 64.00 

175 177 186 196 148 150 149 153 190 190 138 138 270 282 94 110 151 153 360.00 62.00 

169 169 190 192 148 148 149 149 190 190 138 138 278 290 102 106 139 139 370.00 53.00 

169 175 186 192 140 146 149 149 190 190 138 138 282 286 96 106 139 151 373.00 59.00 

169 169 196 196 146 150 153 153 190 190 138 138 270 278 96 104 151 151 384.00 57.00 

169 177 186 190 148 148 149 153 190 204 138 138 278 286 102 102 139 151 390.00 59.00

169 177 186 190 148 148 149 151 190 190 138 138 282 286 102 106 151 151 403.00 70.00 

169 169 186 196 140 148 147 149 190 190 138 140 282 290 96 104 151 151 387.00 42.00 

169 177 186 192 138 148 147 153 190 204 138 138 274 278 102 104 151 151 415.00 70.00 

169 175 194 196 148 152 147 149 190 190 138 138 274 278 94 104 151 151 440.00 71.00 

175 177 186 186 148 148 149 149 190 190 138 138 270 278 96 102 151 151 444.00 61.00 

175 177 184 186 140 140 149 151 190 204 138 138 278 286 104 106 139 139 458.00 59.00 

169 177 194 196 148 148 147 149 190 190 138 138 274 286 94 104 139 151 462.00 53.00 

169 169 186 196 136 150 153 153 190 190 138 138 278 278 96 102 151 151 470.00 48.00 

169 169 194 196 140 152 149 153 190 190 138 138 274 286 102 102 139 151 478.00 46.00 

169 177 186 186 140 148 147 149 190 190 138 138 270 290 104 106 139 139 505.00 36.00 

169 171 190 192 138 150 149 149 190 204 138 140 282 286 106 108 139 151 528.00 30.00 

175 177 184 186 148 148 149 153 190 190 138 138 286 290 96 108 151 151 538.00 27.00 

177 177 186 194 146 150 149 149 190 212 138 138 290 290 106 110 139 151 559.00 28.00 

169 177 184 186 138 148 147 151 190 190 138 138 282 282 102 102 151 151 577.00 42.00 

169 175 186 196 138 148 147 149 190 190 138 138 286 286 104 104 139 151 592.00 34.00 

169 177 194 196 148 154 147 153 190 190 138 138 270 290 102 106 139 151 597.00 27.00 

169 175 186 190 148 148 147 147 190 190 138 138 266 274 96 98 151 151 606.00 30.00 

169 169 184 188 148 150 149 157 190 190 138 138 282 290 102 104 139 151 629.00 36.00 

169 169 186 196 140 148 149 149 190 190 138 140 270 270 102 104 139 151 626.00 26.00 

169 177 184 194 148 148 149 153 190 190 138 138 282 286 102 106 151 151 648.00 24.00 

175 175 186 186 136 148 147 149 190 190 138 138 282 286 102 104 139 151 609.00 44.00 

169 169 188 190 138 148 149 149 190 204 138 140 274 286 102 108 139 139 637.00 48.00 

169 175 188 196 136 148 145 149 190 190 138 138 286 290 98 104 139 151 637.00 41.00 

169 169 186 196 148 148 147 149 190 190 138 138 266 282 98 102 139 151 661.00 43.00 

169 175 192 196 150 152 149 153 190 190 138 138 278 290 106 108 139 151 677.00 26.00 

169 175 196 196 138 148 145 149 190 190 138 138 270 274 102 102 139 151 678.00 48.00 

169 177 184 186 148 148 139 161 190 190 138 138 282 286 102 108 139 151 667.00 52.00 

169 177 184 186 148 150 147 159 190 190 138 138 282 290 102 104 151 151 687.00 44.00 

169 173 184 186 148 148 149 149 190 190 138 138 270 286 102 110 151 153 693.00 37.00 

169 177 168 192 138 148 147 151 190 190 138 138 278 278 96 102 139 151 713.00 45.00 

175 175 186 186 148 148 147 147 190 190 138 138 274 286 102 104 139 151 721.00 40.00 

169 175 184 186 148 148 147 149 190 190 138 138 286 290 96 102 151 151 747.00 30.00 

169 175 194 198 136 148 139 149 190 190 138 138 270 278 102 106 139 151 750.00 38.00 

169 177 186 192 148 148 145 153 190 190 138 138 278 286 102 106 151 151 747.00 46.00

169 177 186 196 140 148 153 155 190 190 138 138 274 286 102 106 151 153 765.00 55.00 

169 175 188 192 148 148 147 149 190 204 138 138 278 290 96 104 139 151 763.00 25.00 

169 169 192 194 150 152 147 147 190 190 138 138 270 286 102 102 151 151 761.00 30.00 

169 169 194 196 142 150 145 149 190 190 138 138 274 282 102 106 151 151 770.00 32.00 

169 177 168 186 140 148 147 153 190 194 138 138 278 286 92 102 139 151 762.00 40.00 

169 177 194 196 140 150 149 153 190 212 138 138 274 282 102 104 151 151 784.00 45.00 

171 175 196 196 138 148 149 159 190 190 138 138 278 290 102 108 151 151 788.00 51.00 

169 169 186 186 148 148 147 147 190 190 138 138 282 290 102 102 - - 790.00 61.00 

169 177 186 188 140 148 145 153 190 190 138 138 274 286 106 106 151 151 795.00 55.00 

169 169 184 196 146 148 153 157 190 202 138 138 282 282 102 110 139 151 820.00 48.00 

169 177 186 196 138 140 149 159 190 190 138 138 278 278 102 102 139 151 840.00 47.00 

177 179 194 196 136 148 149 153 190 190 138 138 278 286 102 106 139 139 831.00 62.00 

173 177 184 196 148 154 147 149 190 190 138 138 274 278 102 104 151 151 860.00 49.00 

169 177 186 194 148 148 149 153 190 190 138 138 286 290 102 104 151 153 839.00 36.00 

169 169 168 184 138 148 149 151 190 190 138 138 278 286 96 106 139 151 837.00 67.00 

169 177 184 192 138 146 149 153 190 190 138 138 282 286 98 106 151 151 848.00 71.00 

169 177 186 194 136 136 149 149 190 190 138 138 270 278 102 106 139 151 859.00 67.00 

169 177 184 186 140 148 149 149 190 202 138 138 282 290 98 106 139 151 887.00 47.00 

169 169 184 198 148 148 147 149 190 190 138 138 282 290 102 108 139 151 871.00 68.00 

169 175 194 194 146 148 149 149 190 190 138 138 278 282 96 102 151 151 913.00 61.00 

161 177 168 190 138 148 149 149 190 190 138 138 266 278 104 106 139 151 883.00 59.00 

169 177 192 196 142 148 145 149 190 190 138 138 278 282 98 106 139 151 924.00 40.00 

177 177 186 196 150 150 149 149 190 190 138 138 278 290 98 102 139 139 917.00 71.00 

169 177 188 192 148 148 147 149 190 190 138 138 278 290 106 106 139 151 940.00 53.00 

169 177 186 192 136 152 145 147 190 204 138 138 278 286 102 106 151 151 954.00 59.00 

177 177 184 190 138 138 145 153 190 190 138 138 286 290 106 108 151 151 965.00 65.00 

169 177 186 186 140 148 153 163 190 190 138 138 282 290 98 104 151 151 967.00 47.00 

169 177 186 196 140 148 149 149 190 190 138 138 274 286 94 102 139 151 966.00 40.00 

173 177 186 196 148 148 147 153 190 204 138 138 274 282 102 104 151 151 984.00 52.00 

173 177 186 190 148 152 147 147 190 190 138 138 278 282 98 104 139 151 989.00 72.00 

169 169 186 196 148 150 147 153 190 190 138 138 270 282 94 102 139 151 1011.00 57.00 

177 177 184 194 148 148 139 153 190 190 138 138 278 286 102 104 139 151 1024.00 59.00 

169 175 192 196 138 146 149 159 190 192 138 138 270 278 96 102 139 151 1020.00 43.00 

169 175 186 194 148 148 147 149 190 190 138 138 270 290 102 104 151 151 1050.00 63.00

169 169 186 196 148 148 139 157 190 190 138 138 274 290 98 102 139 151 1051.00 55.00 

169 175 186 186 140 148 149 149 190 202 138 138 282 286 96 98 151 151 1068.00 40.00 

177 177 186 192 150 152 149 149 190 190 138 138 274 290 102 106 139 139 1076.00 51.00 

169 177 186 196 140 146 147 149 190 190 138 138 278 290 104 106 151 151 1087.00 37.00 

169 169 168 186 148 150 145 151 190 190 138 138 278 278 102 102 139 151 1101.00 48.00 

169 169 190 194 138 148 145 149 190 190 138 138 278 286 96 104 151 151 1114.00 56.00 

169 175 184 186 140 140 149 149 190 190 138 138 282 286 96 106 139 139 1108.00 51.00 

169 169 186 196 146 148 147 153 190 190 138 138 270 282 96 104 151 151 1159.00 44.00 

169 175 196 198 138 148 139 145 190 190 138 138 270 274 98 102 139 151 1148.00 56.00 

177 177 186 196 140 150 149 153 190 190 138 138 274 282 104 112 151 151 1178.00 58.00 

169 177 184 186 138 148 145 149 190 190 138 138 278 290 96 106 139 151 1227.00 66.00 

169 169 186 186 148 152 147 149 190 190 138 138 266 282 98 104 139 139 1269.00 66.00 

169 169 186 196 140 148 149 153 190 202 138 138 286 290 98 104 151 151 1289.00 70.00 

169 177 188 196 148 148 147 151 190 206 138 138 290 290 102 110 139 151 1323.00 71.00 

169 177 186 192 148 148 147 149 190 194 138 138 278 290 104 106 139 151 1313.00 81.00 

169 169 186 192 140 142 145 149 190 190 138 138 270 278 98 102 139 151 1361.00 75.00 

169 173 186 194 148 148 149 149 190 202 138 138 278 286 96 98 151 151 1393.00 74.00 

169 171 186 186 140 148 147 149 190 202 138 138 286 290 98 98 151 151 1416.00 58.00



>Haplotype Sbr00FP01 

TACCACAGCATCACAGTACTATGCCAGTATTAAAAGTAATCTGTTTTAAAAACATT 

TTACTGTACATATCACATACACATATACGCATACATGTTAACACTTAGTCTCTCCT 

TATAAATATCCATGTATACATGCTATGTATTATTGTGCATTCATTTATTTTCCATAC 

GATAAGTTAAAGCTCGTATTAATTATCATTAATTTTACATATTACATAATATGTATG 

CTCTTACATATTATATATCCTCTAACAATTTTATTTCCATTATATCCTATGGTCACT 

CCATTAGATCACGAGCTTAATCACCATGCCGCGTGAAACCAGCAACCCGCTCGG 

CAGGGATCCCTCTTCTCGCACCGGGCCCATACTTCGTGGGGGTAGCTAACGGT 

GATCTTTATAAGACATCTGGTTCTTACTTCAGGACCATTTCAGCCTAAAATCGCC 

CACTC 


TACCACAGCATCACAGTACTATGTCAGTATTAAAAGTAATCTGTTTTAAAAACATT 

TTACTGTACATATCACATACACATATATGCATACATGTTAACACTTAGTTTCTCCT 



CTCTTACATATTATATGTCCCCTAACAATTTTATTTCCATTATATCCTATGGTCGC 

TCCATTAGATCACGAGCTTAATCACCATGCCGCGTGAAACCAGCAACCCGCTCG 

GCAGGGATCCCTCTTCTCGCACCGGGCCCATATCTCGTGGGGGTAGCTAACGG 

TGATCTTTATAAGACATCTGGTTCTTACTTCAGGACCATTTTAACTTAAAATCGCC 

CACTC 






CTCTTACATATTATATGTCCTCTAACAATTTTATTTCCATTATACTCTATGGCCGC 


GCAGGGATCCCTCTTCTCGCACCGGGCCCATACCCCGTGGGGGTAGCTAACGG 


CACTC 






CTCTTACATATTATATGTCCCCTAACAATTTTATTTCCATTATACCCTATGGTCGC 


GCAGGGATCCCTCTTCTCGCACCGGGCCCATATCTCGTGGGGGTAGCTAACGG 


CACTC 






CTCTTACATATTATATGTCCTCTAACAATTTTATTTCCATTATATCCTATGGTCACT


CAGGGATCCCTCTTCTCGCACCGGGCCCATACCTCGTGGGGGTAGCTAACGGT 

GATCTTTATAAGACATCTGGTTCTTACTTCAGGACCATTTCAACCTAAAATCGCC 

CACTC 

>Haplotype h6 





CTCTTACATATTATATGTCCTCTAACAATTTTATTTCCATTATATCCTATGGTCACT 


CAGGGATCCCTCTTCTCGCACCGGGCCCATACCTCGTGGGGGTAGCTAACGGT 

GATCTTTATAAGACATCTGGTTCTTACTTCAGGACCATTTCAACTTAAAATCGCC 

CACTC 

>Haplotype h7 





CTCTTACATATTATATGTCCTCTAACAATTTTATTTCCATTATACCCTATGGTCGC 


GCAGGGATCCCTCTTCTCGCACCGGGCCCATACCCCGTGGGGGTAGCTAACGG 


CACTC 

>Haplotype h8 







GCAGGGATCCCTCTTCTCGCACCGGGCCCATATCCCGTGGGGGTAGCTAACGG 

TGATCTTTATAAGACATCTGGTTCTTACTTCAGG?????????????????????????? 

? 

>Haplotype h9 


TTACTGTACATATCACATACACATATACGCATACATGTTAACACTTAGTTTCTCCT 



CTCTTACATATTATATATCCTCTAACAATTTTATTTCCATTATATCCTATGGTCACT 


CAGGGATCCCTCTTCTCGCACCGGGCCCATATCTCGTGGGGGTAGCTAACGGT 

GATCTTTATAAGACATCTGGTTCTTACTTCAGG??????????????????????????? 

>Haplotype h10 


TTACTGTACATATCACATACACATATACGCATACATGTTAATACTTAGTTTCTCCT 

TATAAATATCCATATATACATGCTATGTATTATTGTGCATTCATTTATTTTCCATAC 



TCCATTAGATCACGAGCTTAATCACCATGCCGCGTGAAACCAGCAACCCGCTCG

GCAGGGATCCCTCTTCTCGCACCGGGCCCATATCTTGTGGGGGTAGCTAACGG 


? 


CACCACAGCATCACAGTACTATGTCAGTATTAAAAGTAATCTGTTTTAAAAACATT 




CTCTTACATATTATATGTCCTCTAACAATTTTATTTCCATTATACCCTATGGTCACT 


CAGGGATCCCCCTTCTCGCACCGGGCCCATATCCCGTGGGGGTAGCTAACGGT 

GGTCTTTATAAGACATCTGGTTCTTACTTCAGG??????????????????????????? 


CACCACAGCATCACAGTACTATGTCAGTATTAAAAGTAATCTGTTTTAAAAACATT 



GATAAGTTAAAGCTCGTATTAATTATCATTAATTTTACATATTACATAATATGCATG 

CTCTTACATATTATATGTCCTCTAACAATTTTATTTCCATTATACCCTATGGTCACT 

CCATTAGATCACGAGCTTAATCACCATGCCGCGTGAAACCAACAACCCGCTCGG 

CAGGGATCCCTCTTCTCGCACCGGGCCCATACCCCGTGGGGGTAGCTAACGGT 

GATCTTTATAAGACATCTGGTTCTTACTTCAGG??????????????????????????? 


TACCACAGCATCACAGTACTATGCCAGTATTAAAAGTAATCTGTTTTAAAAGCATT 

TTACTGTACACATCACATACACATATACACATACATGTTAATACTTAGTCTCTCCT 



CTCTTACATATTATATGTCCCCTAATAATTTTATTTCCATTATACCCTATGGTCGC 

CCCATTAGATCACGAGCTTAATCACCATGCCGCGTGAAACCAGCAACCCGCTCG 

GCAGGGATCCCTCTTCTCGCACCGGGCCCATATCCCGTGGGGGTAGCTAACGG 

TGGTCTTTATAAGACATCTGGTTCTTACTTCAGG?????????????????????????? 

? 


TACCACAGCATCACAGTACTATGTCAGTATTAAAAGTAATCTGTTTTAAAAGCATT 



GATAAGTTAAAGCCCGTATTAATTATCATTAATTTTACATATTACATAATATGTATG 

CTCTTACATATTATATGTCCCCTAATAATTTTATTTCCATTATACCCTATGGTCGC 


GCAGGGATCCCTCTTCTCGCACCGGGCCCATACTCCGTGGGGGTAGCTAACGG 


? 


TACCACAGCATCACAGTACTATGTCAGTATTAAAAGTAATCTGTTTTAAAAGCATT 




CTCTTACATATTATATGTCCCCTAATAATTTTATTTCCATTATATCCTATGGTCGC 


GCAGGGATCCCTCTTCTCGCACCGGGCCCATGCTCCGTGGGGGTAGCTAACGG

TGGTCTTTATAAGACATCTGGTTCTTACTTCAGG?????????????????????????? 

?

Rough-toothed dolphin's samples used in Chapter 6 


Code 

Sampling 

date 


sampling Location Sex mtDNA haplotype 450bp 

1 Sbr02FP02 01/09/2002 biopsy Moorea Female Sbr02FP02 

2 Sbr02FP03 01/09/2002 biopsy Moorea Male Sbr02FP03 






8 Sbr03FP05 27/07/2003 biopsy Moorea ? Sbr02FP03 







15 Sbr03FP12 06/11/2003 biopsy Huahine Male Sbr03FP12 































46 Sbr04FP24 07/10/2004 biopsy Moorea Male Sbr00FP01







53 Sbr04FP31 07/11/2004 biopsy Raiatea Male Sbr00FP02 



56 Sbr04FP34 07/11/2004 biopsy Raiatea Female Sbr03FP12 



59 Sbr04FP37 13/11/2004 biopsy Raiatea Female Sbr03FP12 






65 Sbr04FP43 13/11/2004 biopsy Raiatea Male Sbr03FP12

Rough-toothed dolphins microsatellite genotypes used in Chapter 6 


Code 

GATA 

98a 

Ppho 

MK9a EV94a 415/416a 

131a 

MK6a EV1a GT6a EV37a GT39 MK8 DlrFCB1 Ppho110 GT23 MK5 

Sbr02FP02 83 83 158 162 - - 224 228 185 185 128 132 118 122 222 222 196 196 164 166 100 108 103 117 116 116 68 68 215 223 

Sbr02FP03 83 83 156 162 215 233 222 224 - - 126 128 114 116 206 220 196 218 160 166 100 108 111 113 116 116 68 70 211 223 

Sbr02FP04 79 83 168 176 223 229 222 222 187 187 128 128 116 118 206 206 208 218 160 160 96 104 111 113 116 116 68 70 215 217 

Sbr02FP05 83 83 162 170 - - - - 187 205 118 126 116 120 - - 196 198 - - 96 100 - - - - 64 68 215 219 

Sbr03FP01 83 83 158 168 215 217 222 222 187 187 118 126 116 122 200 224 194 216 152 160 100 100 113 115 116 116 68 68 211 215 

Sbr03FP02 83 83 164 166 229 229 222 232 185 205 118 126 118 118 202 228 194 218 160 168 104 110 113 117 116 116 68 68 209 215 

Sbr03FP03 83 83 166 176 213 227 222 232 187 197 126 126 116 118 200 202 196 208 160 164 98 100 113 115 112 116 68 68 215 223 

Sbr03FP05 83 83 - - - - 222 224 185 197 128 128 116 116 - - 216 218 156 164 - - - - 112 116 - - - - 

Sbr03FP06 83 83 162 168 215 221 222 226 185 205 126 126 116 116 224 228 216 218 160 174 100 100 103 113 116 116 68 70 215 219 

Sbr03FP07 83 83 160 176 - - - - 187 189 126 128 116 118 202 220 - - 164 166 94 94 103 115 116 116 64 68 - - 

Sbr03FP08 83 87 166 172 213 221 222 232 185 185 126 128 118 120 200 200 210 212 158 168 106 110 103 115 112 116 68 68 215 217 

Sbr03FP09 83 83 158 166 - - - - 187 189 - - 116 120 200 218 196 210 160 160 108 110 103 115 116 116 68 68 217 229 

Sbr03FP10 83 83 166 166 - - 224 230 185 199 126 126 116 120 204 206 - - 156 156 100 102 105 113 116 118 68 68 213 215 

Sbr03FP11 83 83 164 166 - - 222 232 189 205 126 126 118 120 200 200 - - 164 168 104 110 103 113 112 116 68 70 209 215 

Sbr03FP12 83 83 156 158 - - 232 232 185 197 128 132 114 118 - - 196 212 168 168 102 106 113 113 112 116 70 70 211 215 

Sbr03FP13 83 83 168 176 - - 216 216 187 197 126 128 118 122 - - - - - - 100 108 105 113 116 116 68 68 217 219 

Sbr03FP14 83 83 168 170 231 233 222 222 187 199 126 126 116 118 218 228 - - 160 160 94 104 103 115 116 116 68 68 215 215 

Sbr03FP15 83 83 162 166 221 229 222 222 185 185 126 128 114 118 200 206 216 226 160 168 100 100 113 115 112 116 68 68 215 227 

Sbr03FP16 83 83 162 170 213 239 222 224 185 187 126 126 120 122 218 224 196 206 164 166 100 102 103 113 116 118 68 68 215 217 

Sbr03FP17 83 83 166 176 - - - - 187 189 128 128 118 120 206 228 202 208 160 164 102 104 113 115 112 116 68 70 215 217 

Sbr03FP18 83 83 166 166 227 229 222 224 185 185 128 128 114 114 206 224 226 226 164 168 102 102 113 115 116 116 68 68 217 217 

Sbr03FP19 83 87 158 162 225 229 216 224 187 205 126 128 114 120 218 226 200 226 162 162 100 104 113 115 116 116 68 68 215 217 

Sbr04FP01 83 83 166 166 - - 222 222 185 187 126 128 118 120 202 202 202 216 176 176 94 104 103 117 112 116 68 70 213 215 

Sbr04FP02 83 83 166 166 233 237 222 224 185 185 126 128 118 120 202 206 200 216 160 160 94 100 113 117 112 112 68 70 215 217 

Sbr04FP03 83 83 166 166 233 237 222 224 185 185 126 128 118 120 202 206 200 216 160 160 94 100 113 117 112 112 68 70 215 217 

Sbr04FP04 83 83 166 166 227 229 222 224 185 185 128 128 114 114 206 224 226 226 164 168 102 102 113 115 116 116 68 68 217 217

Sbr04FP05 83 83 166 176 229 229 222 224 187 189 128 128 118 120 206 228 202 208 160 164 102 104 113 115 112 116 68 70 215 217 

Sbr04FP06 79 83 166 166 215 229 - - 185 195 126 126 116 116 202 206 - - 160 164 100 100 103 113 116 116 68 68 219 223 

Sbr04FP07 83 83 164 166 229 229 222 232 187 195 126 126 116 116 202 206 194 204 164 164 100 110 103 113 116 116 68 68 211 223 

Sbr04FP08 83 83 166 168 - - 222 232 185 185 126 128 116 118 200 206 196 218 160 168 100 100 103 115 116 116 68 68 219 219 

Sbr04FP09 83 83 158 166 213 233 - - - - 118 126 116 116 218 228 204 208 - - 104 106 113 115 116 116 68 68 213 219 

Sbr04FP10 83 83 156 162 - - 224 232 187 199 126 128 116 116 206 206 208 214 - - 104 104 113 115 116 116 68 68 211 215 

Sbr04FP11 83 83 162 166 233 239 224 232 199 205 126 126 116 120 200 206 218 218 166 166 100 100 101 113 116 116 68 70 215 217 

Sbr04FP12 83 83 162 168 213 215 216 222 183 185 126 128 120 120 202 206 198 204 158 164 104 110 105 111 116 116 68 70 211 215 

Sbr04FP13 83 83 168 168 215 221 222 222 185 197 128 128 114 120 200 222 216 232 160 160 98 106 103 115 112 116 68 68 215 217 

Sbr04FP14 83 83 162 166 213 223 222 222 197 205 118 126 116 118 222 222 196 228 160 166 94 102 107 113 116 116 64 68 213 217 

Sbr04FP15 83 83 162 166 229 237 222 232 185 205 126 128 120 120 222 224 194 194 160 164 104 104 103 115 112 116 68 68 215 219 

Sbr04FP16 83 83 162 166 215 221 222 232 185 185 126 126 116 118 200 202 204 218 164 166 100 106 113 117 116 116 68 68 211 223 

Sbr04FP17 79 83 166 166 215 229 222 232 185 195 126 126 116 116 202 206 204 218 160 164 100 100 103 113 116 116 68 68 219 223 

Sbr04FP18 83 83 168 170 213 225 216 222 185 197 126 126 114 116 200 206 194 194 160 160 94 100 105 113 116 116 68 70 219 223 

Sbr04FP19 83 87 158 170 213 227 224 232 185 205 126 126 118 120 200 228 202 228 160 176 94 102 113 115 116 118 68 68 217 219 

Sbr04FP20 83 87 158 168 227 235 222 224 187 205 126 126 116 120 200 220 218 228 160 160 100 102 103 113 116 116 68 68 217 217 

Sbr04FP21 79 83 166 166 215 229 222 232 185 195 126 126 116 116 202 206 204 218 160 164 100 100 103 113 116 116 - - 219 223 

Sbr04FP22 79 83 166 168 213 227 224 232 183 189 126 126 114 120 206 224 194 202 158 164 100 100 103 105 116 116 68 70 217 219 

Sbr04FP23 83 83 162 166 227 229 232 232 189 205 126 128 116 120 202 222 194 196 158 160 104 110 103 115 112 116 68 68 209 219 

Sbr04FP24 79 83 162 166 229 229 226 228 197 205 126 126 118 120 200 224 202 228 166 166 94 94 103 113 116 116 68 68 215 217 

Sbr04FP25 83 83 162 166 213 235 222 224 183 189 126 126 116 116 206 206 196 204 162 168 106 108 113 115 112 116 68 68 217 223 

Sbr04FP26 83 83 162 168 213 215 222 228 199 205 126 128 116 118 202 206 216 228 164 164 94 100 105 113 116 116 68 68 213 215 

Sbr04FP27 83 83 166 172 227 239 222 222 189 197 126 126 114 118 202 218 202 228 160 164 100 100 113 115 116 116 68 68 217 223 

Sbr04FP28 83 83 162 162 215 229 222 224 185 185 126 128 116 118 202 220 198 216 160 160 96 100 103 113 116 116 68 68 213 215 

Sbr04FP29 83 83 166 166 225 229 222 224 197 205 126 126 116 122 222 228 194 228 158 160 96 102 103 113 116 116 68 68 215 219 

Sbr04FP30 83 83 162 166 229 233 222 232 185 187 128 128 118 120 206 226 198 206 160 164 96 104 103 105 116 116 68 68 215 219 

Sbr04FP31 83 83 162 166 215 227 228 232 185 185 126 128 118 118 206 220 196 218 158 168 94 108 103 115 112 116 68 70 219 223 

Sbr04FP32 83 83 156 168 215 227 224 232 185 199 126 128 116 120 206 206 198 202 160 164 98 106 103 113 116 116 68 68 223 223 

Sbr04FP33 83 83 162 162 - - - - - - 126 128 116 116 - - - - 158 158 - - 113 115 - - 68 70 215 223 

Sbr04FP34 - - 156 166 227 227 - - 189 205 - - 118 118 200 200 198 214 - - 100 106 113 113 - - 68 68 215 217 

Sbr04FP35 83 83 162 166 215 227 228 232 185 185 126 128 118 118 206 220 196 218 158 168 94 108 113 113 112 116 68 70 219 223 

Sbr04FP36 83 83 156 166 - - 232 232 - - 126 128 118 118 - - - - 160 168 - - 113 115 - - 68 70 213 217

Sbr04FP37 83 83 156 162 233 233 232 232 185 197 126 128 116 118 206 226 194 202 158 166 100 106 113 113 112 116 68 70 215 219 

Sbr04FP38 83 83 156 168 233 233 218 232 185 197 126 128 116 120 206 224 196 206 160 166 98 100 103 113 112 116 68 70 215 217 

Sbr04FP39 83 83 162 168 215 215 232 232 195 199 126 128 116 118 200 206 198 202 160 168 94 108 113 113 112 116 68 68 217 219 

Sbr04FP40 83 83 156 158 217 227 232 232 185 197 128 132 114 118 222 226 - - 168 168 102 106 113 113 112 116 70 70 211 215 

Sbr04FP41 83 83 156 156 227 235 232 232 185 197 126 128 118 118 222 226 194 194 160 168 102 106 103 117 112 112 70 70 215 219

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