The cloudberry - Centre de recherche Les Buissons

THE CLOUDBERRY:
BRIDGING THE GAP BETWEEN WILDCRAFTING AND
DOMESTICATION
RAPPORT FINAL
Projet # 806120
PROGRAMME DE SOUTIEN À L’INNOVATION
EN AGROALIMENTAIRE
Responsable du projet :
S. Kristine Naess
Centre de recherche Les Buissons
Octobre 2010

CHERCHEURS IMPLIQUÉS
S. Kristine Naess, Centre de recherche Les Buissons, responsable scientifique
358 rue Principale, Pointe-aux-Outardes, Québec, G0H 1M0
Tél: 418 567 2235 poste 222, FAX: 418 567 8791
Line Lapointe, Université Laval, directrice de l‟étudiante à la maitrise
Département de biologie & Centre d'étude de la forêt,
Université Laval, Québec, G1V 0A6
Tél: 418 656-2822, FAX: 418 656-2043
Léon-Étienne Parent, Université Laval, directeur de l‟étudiante à la maitrise
Département des sols et de génie agroalimentaire, Pavillon Paul-Comtois, local 2223
Université Laval, Québec, G1V 0A6
Tél: 418 656-2131 poste 3037, FAX: 418 656 3723
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LA CHICOUTÉ : ENTRE L’ÉTAT SAUVAGE ET LA DOMESTICATION
S. Kristine Naess 1 , Line Lapointe 2 , Léon-Étienne Parent 3 , et Valérie Hébert-Gentile 2
1. Centre de recherche Les Buissons, Pointe-aux-Outardes, Québec, G0H 1M0, 2. Département de biologie
& Centre d'étude de la forêt, Université Laval, Québec, G1V 0A6, 3. Département des sols et de génie
agroalimentaire, Pavillon Paul-Comtois, local 2223, Université Laval, Québec, G1V 0A6
Durée : 04/2007-09/2010
FAITS SAILLANTS
Dans un premier volet du projet portant sur l‟utilisation des brise-vents/clôtures à neige pour accroître les
rendements de chicouté en milieu naturel, les clôtures à neige installées au début d‟automne ont mené à une
augmentation du nombre de fleurs et des rendements en fruit doublés. La période de floraison de la chicouté
était retardée lorsque les clôtures à neige étaient installées fin janvier, une fois le sol bien gelé. Cependant,
en 2009 ce retard de floraison n‟a pas été suffisant pour protéger les fleurs contre des gels tardifs. Les
brise-vents en place pendant l‟été n‟ont eu aucun effet sur la pollinisation ou les rendements de chicouté
pendant les deux saisons du projet. Dans un deuxième volet du projet, nous avons testé l‟impact d‟une
fertilisation organo-minérale à base de farine de crabe et de farine de poisson sur la performance de la
chicouté en tourbière naturelle. L‟engrais a été appliqué pendant trois ans. Les effets de la fertilisation sur la
croissance, le développement et la nutrition minérale de la plante ont été très limités autant en tourbière
humide à sphaignes qu‟en tourbière sèche à lichens.
OBJECTIF ET MÉTHODOLOGIE
L‟objectif du projet était d‟augmenter les rendements de chicouté en milieu naturel soit en modifiant le
microclimat (volet I) ou en utilisant des engrais biologiques produit à partir d‟une farine de crabe (volet II).
Pour la modification du microclimat cinq traitements utilisant des clôtures de plastique ont été essayés, soit
des clôtures d‟octobre à juin (neige), des clôtures de février à juin (neige retardée), des clôtures durant toute
l‟année (neige et vent), des clôtures de juin à octobre (vent) et le témoin sans clôture. Des données sur le
microclimat, la phénologie, la pollinisation, le nombre de fleurs et fruits ainsi que sur les rendements ont
été prises. Les engrais biologiques ont été appliqués dans le sol à 15 cm de profondeur chaque année au
printemps pendant trois ans. Des données sur la dispersion des engrais et la teneur de minéraux dans des
plants de chicouté ont été prises ainsi que des données sur le nombre de fleurs, de fruits et des rendements
de chicouté.
RÉSULTATS SIGNIFICATIFS POUR L’INDUSTRIE
Les clôtures à neige installées à l‟automne ont maintenu les températures du sol plus élevées pendant
l‟hiver. Cet effet a persisté jusqu'à la mi-été. Les brise-vents installés au printemps ont légèrement
augmenté les températures maximales pendant la période de floraison. Des changements du microclimat
provoqués par les traitements ont influencé la phénologie de la chicouté. Avec le traitement « neige
retardée » la floraison a été retardée au cours des deux années du projet alors que les traitements « vent » et
« neige et vent » ont avancé la période de floraison quelque peu. Les changements obtenus dans la période
de floraison n‟ont pas été suffisants pour protéger les fleurs contre des gels tardifs en 2009. Dans les
traitements « neige » et « neige et vent » une augmentation du nombre de fleurs a été observée dans la
tourbière humide par rapport aux traitements « témoin » et « vent ». Une légère augmentation du nombre
d‟insectes pollinisateurs a été observée dans les traitements « vent » et « neige et vent » mais aucune
augmentation significative dans le pourcentage de fleurs pollinisées ou dans les quantités de pollen
déposées n‟a été observée. Les meilleurs rendements ont été obtenus avec le traitement « neige » dû à un
plus grand nombre de fleurs et fruits produits avec ce traitement.
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Les effets des traitements sur les rendements moyens de chicouté.
Traitement Fruits par 10 m 2 Poids par fruit (g) Rendements (kg/hectare)
Témoin 100 b 0.86 b 47 b
Neige retardé 125 ab 0.98 a 63 ab
Neige 249 a 0.88 b 118 a
Neige et Vent 142 ab 0.92 ab 68 ab
Vent 124 b 0.85 b 59 b
Les résultats de la fertilisation de la chicouté à l‟aide d‟un engrais composé de farine de crabe, de farine de
poisson et de muriate de potassium indiquent que cet engrais n‟est pas approprié pour la fertilisation de la
chicouté en tourbière naturelle sur la Basse Côte Nord. Nous n‟avons observé aucun impact important sur
la croissance, la floraison ou la production de fruits de la chicouté. Nous n‟avons pas non plus observé
d‟augmentation de la teneur en nutriments de la chicouté suite à la fertilisation. Il semble donc que l‟azote
organique ne s‟est pas minéralisé suffisamment pour atteindre les rhizomes de chicouté et que la chicouté
n‟est pas une plante compétitive à court ou moyen terme (un à trois ans) pour les éléments nutritifs.
Toutefois, la chicouté tend généralement à accumuler des éléments nutritifs sur de plus longues périodes
pour assurer sa survie dans ces milieux. Des suivis annuels des parcelles pourraient être faits.
APPLICATIONS POSSIBLES POUR L’INDUSTRIE
Le piégeage de la neige avec des clôtures à neige installées à l‟automne est une méthode efficace menant à
des rendements accrus de chicouté en milieu naturel. Les clôtures doivent être installées aux endroits ayant
au moins 10 fleurs femelles au mètre carré pour les rentabiliser. Pour prévenir les gels tardifs une méthode
de gestion de l‟eau sera à privilégier.
En ce qui concerne l‟utilisation d‟engrais à base de farine de crabe et de poisson pour la fertilisation de la
chicouté, nos résultats suggèrent que ces engrais ne conviendraient pas pour stimuler la croissance annuelle
et augmenter le rendement de la chicouté en tourbière naturelle. Comme pour les plantes cultivées,
plusieurs essais sont nécessaires pour trouver les formules et les doses d‟engrais organiques requises pour la
fertilisation de la chicouté. D‟autres pratiques culturales pourraient aussi être évaluées, comme ce fut le cas
de l‟atoca et du bleuet nain.
POINT DE CONTACT
S. Kristine Naess, Centre de recherche Les Buissons, 418 567 2235 poste 222, 418 567 8791,
Kristine.naess@lesbuissons.qc.ca
PARTENAIRES FINANCIERS
L‟équipe de recherche tient à remercier le ministère de l'Agriculture, des Pêcheries et de l'Alimentation, le
ministère du Développement économique, de l'Innovation et de l'Exportation et la Conférence
régionale des élus de la Côte-Nord pour leur soutien financier, sans lequel le projet n‟aurait pu se
concrétiser. Nous tenons également à remercier le Centre d‟étude de la forêt qui a octroyé une bourse à
Mme Hébert-Gentile afin de lui permettre de participer à la 7 ieme Conférence International sur l‟Agriculture
Circumpolaire à Alta, Norvège en septembre 2010. Dr. Léon Etienne Parent a mis à notre disposition le
personnel, les produits et les équipements analytiques requis pour les analyses de sols et de tissus végétaux.
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ACTIVITÉS DE DIFFUSION ET DE TRANSFERT AUX UTILISATEURS
Des données préliminaires du projet ont été présentées à la communauté de Blanc-Sablon, le 6
aout 2008 par Kristine Naess et Valérie Hébert-Gentile. Le programme ainsi qu‟une liste des
participants sont présentés en annexe du rapport (Annexe 1).
Les résultats préliminaires du projet ont été présentés aux producteurs et d‟autres intervenants
intéressés par les petits fruits nordiques lors du Colloque Bioalimentaire Côte-Nord 2009. Le
programme du colloque est présenté en annexe du rapport (Annexe 2).
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ACTIVITÉS DE TRANSFERT SCIENTIFIQUE
Une présentation PowerPoint des résultats du volet engrais biologiques a été présentée par Valérie
Hébert-Gentile, étudiante à la maitrise, lors du 7 ieme Conférence International sur l‟Agriculture
Circumpolaire à Alta, Norvège qui a eu lieu du 6 au 8 septembre 2010. Le programme et les
résumés sont présentés en annexes (Annexe 3 et Annexe 4).
Mme Hébert-Gentile a également présenté une conférence intitulée : Fertilisation biologique en
tourbière naturelle : minéralisation, dispersion et effets sur la chicouté‟ lors du symposium annuel
des étudiants de 2 e et de 3 e cycles en biologie, à l‟Université Laval qui s‟est tenu en février 2010.
Et finalement, elle a présenté lors du colloque annuel du Centre d‟étude de la forêt en mars 2010
une conférence intitulée „La fertilisation de la chicouté : un casse-tête nutritionnel!‟
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Table of Contents
List of Figures………………………………………………………..
List of Tables…………………………………………………………
Introduction………………………………………………………….
Soil Fertility………………………………………………………….
Materials and methods…………………………………………………………. 13
Location and field work………………………………………………………….. 13
Cloudberry fertilization study…………………………………………………………… 14
Fertilizer dispersion study………………………………………………………………. 14
Laboratory analysis………………………………………………………………. 15
Cloudberry fertilization study…………………………………………………………… 15
Fertilizer dispersion study………………………………………………………………. 15
Data analysis……………………………………………………………………… 15
Cloudberry fertilization study…………………………………………………………… 15
Fertilizer dispersion study……………………………………………………………….. 16
Results……………………………………………………………………………. 16
Cloudberry fertilization study…………………………………………………….. 16
Pearson’s correlations…………………………………………………………………… 16
Cloudberry fertilization…………………………………………………………………. 18
Fertilizer absorption……………………………………………………………………… 20
Fertilizer dispersion study………………………………………………………… 21
Discussion………………………………………………………………………… 23
Cloudberry fertilization…………………………………………………………… 23
Pearson’s correlations…………………………………………………………………… 23
Cloudberry fertilization…………………………………………………………………. 23
Fertilizer dispersion……………………………………………………………….. 24
9
11
12
13
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Micro-climate Management………………………………………..
Materials and methods…………………………………………………………. 26
Location………………………………………………………………………….. 26
Experimental design……………………………………………………………… 26
Plot establishment………………………………………………………………… 26
Treatment application…………………………………………………………….. 27
Data Collection…………………………………………………………………… 27
Micro-climate data……………………………………………………………………….. 27
Flowering phenology, shoot numbers, flower numbers and sex ratio…………….. 27
Pollinating insects……………………………………………………………………….. 28
Pollination, fruit and seed set………………………………………………………….. 28
Fruit ripening and floral bud development…………………………………………… 28
Yields……………………………………………………………………………………… 28
Data analysis…………………………………………………………………….. 28
Results……………………………………………………………………………. 29
Baseline data……………………………………………………………………… 29
Micro-climate data……………………………………………………………….. 29
Flowering phenology……………………………………………………………... 38
Shoot and Flower numbers……………………………………………………….. 40
Pollinating insects………………………………………………………………… 41
Pollination…………………………………………………………………………. 43
Fruit and seedset…………………………………………………………………... 45
Fruit ripening and bud development………………………………………………. 46
Yields……………………………………………………………………………… 48
Discussion…………………………………………………………………………. 50
References…………………………………………………………….
Acknowledgements…………………………………………………..
Annexes……………………………………………………………….
25
52
56
57
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List of Figures
Figure 1. Correlations (coefficients of Pearson (r) and P values) between total number of ramets
m -2 and the percentage of these ramets that were floral (a) and the female on floral ramets percent
(b), in the two bogs, wet (filled circles) and dry (empty circles), studied on the Lower-North-
Shore.
Figure 2. Correlations (coefficients of Pearson (r) and P values) between individual fruit mass and
the density of female ramets (a) as well as the proportion of floral ramets that were female (b), in
the wet (filled circles) and dry (empty circles) bogs studied on the Lower-North-Shore.
Figure 3. Correlations (coefficients of Pearson (r) and P values) between previous year fruit
density and following year female ramet density (a and b), between fruit density in two subsequent
years (c) and between individual fruit mass in two subsequent years (d), in the wet (filled circles)
and dry (empty circles) bogs studied on the Lower-North-Shore.
Figure 4. Ionic concentration (mg kg -1 dry soil) of potassium and ammonium ions (mean ± SE) as
a function of the distance from the fertilization point (cm) in the wet and dry bogs, one year after
fertilizer application, on the Lower North-Shore.
Figure 5. Total concentration (mg kg -1 dry soil) of different nutrients (mean ± SE) as a function of
the distance from fertilization point in the wet bog, one year after fertilizer application, on the
Lower North-Shore.
Figure 6. Soil temperatures 10 cm below ground logged in plots with and with snow fences or with
snow fences put up late winter (“Delayed Snow Fence”) during the 2007/2008 winter
superimposed over snow accumulation data collected at the airport in Blanc-Sablon.
Figure 7. Soil temperatures 10 cm below ground logged in plots with and with snow fences or with
snow fences put up late winter (“Delayed Snow Fence”) during the 2008/2009 winter
superimposed over snow accumulation data collected at the airport in Blanc-Sablon.
Figure 8. Soil temperatures 10 cm below ground logged in plots with and with snow fences or with
snow fences put up late winter (“Delayed Snow Fence”) during the spring and summer of 2008.
Figure 9. Soil temperatures 10 cm below ground logged in plots with and with snow fences or with
snow fences put up late winter (“Delayed Snow Fence”) during the spring and summer of 2009.
Figure 10. Depth of thawed ground as affected by snow fences and windbreaks in 2008 and 2009.
Figure 11. Maximum daily air temperatures at 10 cm above ground in plots protected by wind
breaks and those without wind breaks during the summer of 2008.
Figure 12. Maximum and minimum daily air temperatures at 10 cm above ground in plots
protected by wind breaks and those without wind breaks during the summer of 2009.
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Figure 13. Minimum temperatures recorded in the dry and the wet bog during the summer of 2009.
Figure 14. Windspeeds recorded in the SW and NE sampling plots of plots with and without
windbreaks during the cloudberry flowering period, 2008.
Figure 15. Flowering phenology in the wet and dry bogs, 2008 and 2009.
Figure 16. Cumulative flowering proportion as affected by the snow fence and windbreak
treatments in 2008 and in 2009.
Figure 17. Treatment effects on flower numbers in the wet and the dry bog.
Figure 18. Insects observed foraging on cloudberry flowers in plots protected by windbreaks (Yes)
and in plots without windbreaks (No).
Figure 19. Pollen loads per stigma decreased as the season progressed.
Figure 20. Fruitset in the dry and the wet bogs varied with the tagging date.
Figure 21. Fruit ripening as affected by the snow fence and windbreak treatments in 2008 and
2009.
Figure 22. Meristem developmental stage in buds subtending fruiting shoots. 1=vegetative,
2=sepal and petal development, 3=anther development, 4=carpel development, 5=carpel lobes
closed.
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List of Tables
Table 1. Cloudberry shoot and fruit characteristics (mean ± SE in parentheses) for control and
fertilized plots, during the three years of the study, in the wet and dry bogs studied on the Lower-
North-Shore.
Table 2. F and P values of ANOVAs testing the impact of the fertilizer application on the different
nutrient concentrations in cloudberry rhizome (2009), leaf (2009) and fruit (2008 and 2009) in the
wet and dry bogs studied on the Lower-North-Shore.
Table 3. Snow fence application and removal dates for the various treatments.
Table 4. Baseline data taken on the plots in 2007 display considerable natural variation in
important yield factors.
Table 5. Treatment effects on flowering phenology in 2008 and 2009.
Table 6. The number of baseline adjusted floral shoots produced in the dry and wet bogs as
influenced by snow fences.
Table 7. The types of insects observed in the bogs during the cloudberry flowering season.
Table 8. The effects of snow fences and windbreaks on cloudberry pollination.
Table 9. Treatment effects on fruit ripening in the wet and dry bog.
Table 10. Cloudberry yield variations between bogs in 2008 and 2009.
Table 11. The effects of snow fences and windbreaks on cloudberry yields.
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The cloudberry: Bridging the gap between wildcrafting and domestication
Introduction
The cloudberry, Rubus chamaemorus, is a small unarmed bramble fruit exclusive to the peat bogs
of the northern hemisphere. The amber berry has a unique musky flavor and has been highly
treasured by northern peoples for centuries. In Quebec commercial uses include the production of
the prizewinning liqueur Chicoutai and a cottage industry has evolved around the production of
cloudberry jams, jellies, butters and pastries. Communities along the North Shore of Quebec have
shown an interest in the further development of this industry (CEPRO, 2004)
Cloudberries are still harvested from the wild where it is nature alone that controls the harvest.
Yields are notoriously low and variable making commercialization of the cloudberry beyond the
cottage industry stage difficult. The results of a recently completed four year yield study (Otrysko
et al., unpublished results) covering 100 km 2 between Old Fort and Blanc-Sablon illustrate well
both the problems and opportunities awaiting the developing cloudberry industry. In this study,
100 randomly selected yield plots representing the actual average yields obtained from cloudberry
peatlands were compared with yields obtained from a dozen plots pointed out to us by cloudberry
pickers. Average yields from 100 randomly selected plots ranged from less than 1kg per hectare in
2005 to 25 kg/hectare in 2004. Good pickers who are able to gather 40 kg a day in a good year
must cover over 20 km of bogland to net 20 kg a day in an average year. Thus year to year yield
instability in the field, compounded with the increased harvest costs in bad years, result in the
current instability of cloudberry availability. However, during these same years, plots chosen by
cloudberry pickers averaged 108 kg/hectare and the best plot produced close to 600 kg/hectare,
rivalling production figures from fully cultivated test plots in Norway (Rapp, per. com.) not to
mention blueberry yields on the north shore. These high yielding plots, in addition to
demonstrating the enormous potential for cloudberry production in the area, remind us that
tremendous progress may be made despite unpredictable and uncontrollable weather conditions,
through modification of the factors underlying the observed differences between high yielding and
randomly selected plots. Of the many biotic and abiotic factors governing cloudberry yields, soil
fertility, micro-climate and pollination success have all been shown to limit production in the wild.
In this project we examine low impact methods to manage the micro-climate and improve soil
fertility in order to deal with two of the factors limiting cloudberry yields in the wild.
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Soil Fertility
The cloudberry is well adapted to the acid and nutrient poor conditions of the boglands in which it
grows. Nonetheless, increased soil fertility, and in particular an increase in phosphorus, was soon
recognized as important to cloudberry growth and yields (Sandved 1959). Gauci (2008) found that
both phosphorus and potassium were important to fruit set in cloudberry and more recently, the
use of boron fertilization in increasing cloudberry yields has been examined (Zhou et al.,
unpublished results). Recorded attempts at increasing cloudberry yields in the natural setting
through the use of manures and fertilizers go back to the 1950‟s. These early experiments with
surface applied complete or single component chemical fertilizers had generally insignificant and
sometimes negative effects on cloudberry yields while leading to markedly increased growth in
competing plant species (Østgård, 1964). Later experiments examining the uptake of phosphorus
by cloudberry and several competing species from different depths in the bog led to the
recommendation that selective fertilization, at depths of ca 20 cm, would be beneficial to
cloudberry yields (Rapp and Steenberg, 1977). Published guidelines now call for the placement of
40-50 grams of complete (14-6-16) fertilizer per meter at a depth of 20 cm (Rapp, 2004), a
fertilization rate which has led to threefold increases in cloudberry yields in a recently completed
study in Norway (Ballari, 2001). While encouraging in terms of cloudberry industry development,
the sustainability of a peatland fertilization program using chemical fertilizers on public lands is
questionable. The use of organic fertilizers at more reasonable rates could be a lower impact
method leading to increased yields without tarnishing the healthy image of the cloudberry. In the
course of this exploratory project, we will examine the effects of an organic fertilizer derived from
fish offal on cloudberry growth and fruit production. We first checked the diffusion of phosphorus
and potassium fertilizers from the application point to determine the influence zone of the fertilizer
and to check for possible cross-contamination between fertilizer and non fertilized treatments.
Materials and methods
Location and field work
The experiment was located in two large bogs North West of Blanc-Sablon, Québec. One of the
bogs is a wet sphagnum (Sphagnum fuscum and Sphagnum rubellum) bog while the other is a
considerably dryer bog and its vegetation is mainly composed of caribou lichen (Cladonia
rangiferina). Beside cloudberry, some Ericaceae, such as crowberry (Empetrum nigrum), Labrador
tea (Ledum groenlandicum), blueberries (Vaccinium uliginosum and Vaccinium angustifolium),
cranberry (Vaccinium oxycoccus), Kalmia polifolia, Chamaedaphne calyculata, and Andromeda
glaucophylla are present along with some herbaceous species such as Eriophorum sp., Carex sp.
(wet bog only), Drosera rotundifolia, and Maianthenum canadense (wet bog only).
Soil was frozen, 27 cm below ground at the beginning of June. In 2008, the grounds in the two
bogs were completely thawed by mid-August. The mean water table depth during summer 2008
was 13.3 ± 1.0 cm in the wet bog and below 30 cm in the dry bog. The soil temperature varied
between 5 and 7°C at the beginning of the 2008 flowering season and increased up to 13°C when
the fruits were ripening.
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Cloudberry fertilization study
The experimental design used was a complete block design repeated in two sites (sphagnum and
lichen bogs). In each block, two plots of 1 meter wide by 5 meter long were established in areas
presenting similar cloudberry density, in spring 2007 before plants began to grow. The two
treatments (fertilised or control) were assigned randomly to either plot, within each block. Five
blocks were established per site. There was at least 5 meters between plots within each block, and
at least 30 meters between blocks.
The fertilizer used was composed of 48 % fish meal (9.5 % N total – 9.7 % P2O5 – 0.42 % K2O;
JEFO company), 40 % crab meal (4.7 % N total – 5.9 % P2O5 – 0.3 % K2O) and 12 % potassium
chloride (0 % N total – 0 % P2O5 – 60 % K2O) (Nicolas Samson, pers. comm.) for a final
composition of 6.4 % total N, 7.1 % available P2O5 and 7.0 % exchangeable K2O (Nicolas
Samson, data not shown).
Every year, holes of 15 cm depth were dug in each plot (2007: 5 holes per plot; 2008 and 2009: 6
holes per plot) and 40 g of fertilizer were applied in each hole in the fertilized plots. This is
equivalent to 29 kg of nitrogen per hectare per year.
During the flowering season, every other day, the blooming flowers were hand-pollinated to insure
a uniform pollination among plots. Every hand-pollinated flower‟s shoot was identified by a code
associated with their pollination day.
At the end of the flowering season, all floral (male and female) and non-floral shoots were counted
within the plots. In 2008 and 2009, 25 floral female shoots were randomly selected. Once the fruit
started ripening the plots were visited every other day again. All stage 12 and 13 (Beaulieu et al.,
2001) fruit were collected, counted, weighed and frozen for further analysis in the laboratory. The
harvest day of each fruit was noted to calculate the duration of their development period (from
pollination date to harvest date). The selected shoots‟ fruit had their pistils and drupelets counted.
In 2009, absorption of the fertilizer by the cloudberry plants was investigated by collecting
rhizome and leaf samples. After the flowering season and before the fertilizer application, six fruitbearing
shoots were randomly selected and harvested for their rhizomes (first 10 cm) and leaves,
in each plot. The samples were dried (48 hours at 65°C) for further analysis in the laboratory.
Fertilizer dispersion study
In 2008, one plot per block was established at a minimal distance of 5 meters from the Cloudberry
fertilizer plots, for a total of 5 plots per bog. Fertilizer was applied in the center of each plot the
same day and the same way as in the Cloudberry fertilizer study (40 g in a 15 cm depth hole). In
2007, before any fertilizer was applied in either experiment, soil samples were collected near, but
outside, the plots used for the Cloudberry fertilization study. Those samples were used as control
samples for the Fertilizer dispersion study.
In 2009, soil samples were collected from 0 to 15 cm depth and from 15 to 30 cm depth at 10, 20,
40 and 80 cm from the point where the fertilizer had been applied the year before. Samples were
harvested in four directions (North, East, South and West) for a total of 16 samples per depth, per
fertilization point. Each sample was frozen for further analysis in the laboratory.
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Laboratory analysis
Cloudberry fertilization study
Dried rhizome and leaf samples were ground. Frozen fruit samples were first freeze-dried (Flexi-
Dry MP, 72 h) and then ground. Then, all rhizome, leaf and fruit samples were digested with nitric
and perchloric acids (Barnhisel and Bertsch, 1982) and their nutrient concentrations (P, K, Ca, Mg,
Fe, Mn, Cu, Zn, B, S and Al) were quantified by ICP-OES (Inductively coupled plasma optical
emission spectrometry). Their total C, N and S concentrations were determined by dry combustion
using the CNS-2000 LECO analyzer.
Fertilizer dispersion study
Sub-samples of the different soil samples were thawed then extracted using 0.01 M CaCl2 (Dou et
al., 2000). Nitrate was separated on AG11 and AS11 columns whereas phosphate was separated
on AG18 A and AS18 A columns, then quantified with an ion chromatography system (ICS-2000
RFIC). Ammonium was quantified by colorimetry (Nkonge and Ballance, 1982) and potassium
by atomic emission spectrometry.
To determine if live sphagnum had absorbed part of the nutrients from the fertilizers, sub-samples
of the soil samples from the wet bog were dried (72 h at 45°C), ground, wet digested with sulfuric
and selenic acid (Sahrawat et al. 2002), and N (Nkonge and Ballance, 1982) and P (Tandon et al.
1968) concentrations were quantified by colorimetry while K, Ca and Mg were measured by
atomic absorption spectrometry. The same analyses were performed on the control soil samples
that have been collected nearby the Cloudberry fertilizer plots in 2007.
Data analysis
Cloudberry fertilization study
Pearson‟s correlations were calculated on the different biotic variables within years, and among
years for the same plots. Significant correlations that increased our understanding of the biology of
the species are presented in the Results section.
A two-way analysis of variance with repeated measures (year) was used to study the effect of the
fertilizer on the growth and fruit production of cloudberry, using the MIXED procedure of the
SAS 1 program. Variables, for which data were collected in 2007 i.e. before the fertilizers were
applied, were analysed as a percentage of the 2007 data value. We thus compared rate of changes
rather than absolute values which tend to vary greatly among plots in natural habitats.
Since all flowers and fruit aborted in the lichen bog in 2009, the fruit variables were analysed in
two different ways. In the first series of analyses, the two bogs were included but only for the year
2008. In the second series of analyses, the two years (2008 and 2009) were included but only for
the sphagnum bog.
Nutrient concentrations in leaves and rhizomes were analysed with one-way ANOVAs with the
treatment as fixed factor and the bog as random factor, except for the fruit data in 2009 which
were available only for the sphagnum bog.
15

Fertilizer dispersion study
Dispersion from a source point being considered as an exponential phenomenon, nutrient
concentrations (mg kg -1 dry soil) were log-transformed. Dispersion is a diffusion-advection
process whereby an ion concentration gradient is determined by the ionic diffusion process
(Brownian movement in absence of water flow) and ion turbulence and mixture is promoted by the
convection (water flow) process.
Only data obtained from the samples collected between 0 and 15 cm depth were statistically
analysed because there was no variation in the concentrations of the samples collected between 15
and 30 cm depth, regardless of distance from the fertilizer point. Similarly, we did not notice any
variation among the four directions (N, E, S and W). Data from the four directions were thus used
as replicates. One-way ANOVAs with the distance from fertilization point as fixed factor and the
plot as random factor were run for each nutrient, within each bog. Data harvested from the control
plots were averaged and their mean and standard error compared with the fertilized samples.
When necessary, variables were transformed to meet the normality and the homogeneity of the
variance. Pairwise comparisons were made using protected Fisher LSD tests (least significant
difference).
Results
Cloudberry fertilization study
Pearson’s correlations
The percentage of ramets that were floral increased with the total number of ramets, but in the dry
bog only (fig. 1a). However, the proportion of floral ramets that were female was not influenced
by ramet density in either bog (fig. 1b). Sex ratio is apparently not influenced by the numbers of
floral nor by the total number of ramets.
The individual fruit mass seemed to be proportional to the density of female ramets (fig. 2a) but
also to the proportion of floral ramets that were female (fig. 2b), but only in the wet bog. Thus, the
more female ramets there are - both in absolute data and as a percent of total floral ramets - the
bigger should be the fruits.
It seems that the plots producing a large number of fruits can still produce a large number of
female ramets and fruits the following year, particularly in the wet bog (fig. 3a, 3b and 3c). Fruit
mass is correlated between years which means that the same plots produce the largest fruits on
average each year (fig. 3d).
16

Floral / Total (%)
50
40
30
20
10
0
Dry bog
r = 0.681
P = 0.000
0 100 200 300 400 500 600
Total number of ramets*m -2
a
Wet bog
r = 0.030
P = 0.878
Female / Floral (%)
120
100
80
60
40
20
0
0 100 200 300 400 500 600
Total number of ramets*m -2
Dry bog
r = -0.102
P = 0.591
b
Wet bog
r = 0.026
P = 0.894
Figure 6. Correlations (coefficients of Pearson (r) and P values) between total number of ramets m -2 and the
percentage of these ramets that were floral (a) and the female on floral ramets percent (b), in the two bogs, wet (filled
circles) and dry (empty circles), studied on the Lower-North-Shore.
Individual fruit mass (g)
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
0 20 40 60 80
Number of female ramets*m -2
Wet bog
r = 0.804
P = 0.000
Dry bog
r = 0.028
P = 0.906
a
Individual fruit mass (g)
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
0 20 40 60 80 100 120
Female / Floral (%)
Wet bog
r = 0.477
P = 0.010
Dry bog
r = 0.380
P = 0.098
Figure 7. Correlations (coefficients of Pearson (r) and P values) between individual fruit mass and the density of
female ramets (a) as well as the proportion of floral ramets that were female (b), in the wet (filled circles) and dry
(empty circles) bogs studied on the Lower-North-Shore.
b
17

Number of female ramets*m -2
Year 2008
Number of fruits*m -2
Year 2008
80
70
60
50
40
30
20
10
0
70
60
50
40
30
20
10
0
Dry bog
r = 0.461
P = 0.180 Wet bog
r = 0.950
P = 0.000
Dry bog
r = 0.465
P = 0.176
0 2 4 6 8 10
Number of fruits*m -2
Year 2007
Wet bog
r = 0.929
P = 0.000
0 2 4 6 8 10
Number of fruits*m -2
Year 2007
a
c
Individual fruit mass (g)
Year 2008
1.6
1.4
1.2
1.0
0.8
Number of female ramets*m -2
Year 2009
Dry bog
r = 0.747
P = 0.013
80
60
40
20
0
0 10 20 30 40 50 60 70
Individual fruit mass (g)
Year 2007
Number of fruits*m -2
Year 2008
Dry bog
r = 0.982
P = 0.000
0.6
0.4
Wet bog
r = 0.860
P = 0.001
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6
b
Wet bog
r = 0.960
P = 0.000
Figure 8. Correlations (coefficients of Pearson (r) and P values) between previous year fruit density and following
year female ramet density (a and b), between fruit density in two subsequent years (c) and between individual fruit
mass in two subsequent years (d), in the wet (filled circles) and dry (empty circles) bogs studied on the Lower-North-
Shore.
Cloudberry fertilization
The only variables on which the fertilizer application had a significant effect were fruit percent dry
matter and seed set (table 1). The fruit percent dry matter was lower (in 2008 only) and the seed
set higher (in wet bog only) with fertilization. One needs to take into account that there was no
data collected in 2007 for these two variables so there could have already been a difference
between the fertilized and the control plots. There were many significant differences between
years and between the two bogs.
d
18

Table 3. Cloudberry shoot and fruit characteristics (mean ± SE in parentheses) for control and fertilized plots, during
the three years of the study, in the wet and dry bogs studied on the Lower-North-Shore. C = Control plot, F =
Fertilized plot; N = 5. Data for 2007 and for the last three variables are absolute values, whereas all other data are
presented as a percentage of the value measured in 2007. Direct comparisons between 2007 and either 2008 or 2009
are thus not possible.
Wet Bog Dry Bog
2007 2008 2009 2007 2008 2009
Variables C F C F C F C F C F C F
‡
Total number
of ramets m -2
‡
Number of
non-floral
ramets m -2
Number of
male ramets m -
2
‡
Number of
female
ramets m -2
Floral/Total
(%)
Female/Floral
(%)
3
Fruit
development
period (day)
3
Number of
fruits m -2
3;4 Total fruit
mass m -2 (g)
4 Individual
fruit mass (g)
Number of
drupelets
Drupelet mass
(g)
177
(16)
154
(19)
17.2
(6.8)
6.28
(2.27)
14.2
(4.0)
34.2
(16.6)
41.2
(0.2) 2
4.32
(1.37)
2.64
(0.71)
0.942
(0.141)
6.66
(0.88)
0.144
(0.022)
229
(25)
200
(28)
19.1
(7.1)
9.12
(2.89)
13.2
(3.3)
36.7
(12.4)
41.3
(0.2) 1
5.24
(1.47)
3.86
(1.24)
180
(7)
0.959
(0.102) 101
(8)
6.16
(0.44)
172
(4)
155
(11) 147
(5)
178
(8)
169
(11)
308
(43) 360
(78) 294
(29)
455
(101) 349
(21) 407
(64)
200
(23) 219
(33) 181
(25)
128
(24) 100
(14) 127
(11)
44.1
(0.5) 43.1
(0.7) 44.4
(1.1)
453
(61) 443
(76) 403
(55)
192
(6)
180
(9)
102
(12)
97.4
(18) 167
(18)
93.6
(11.7) 86.9
(15.1) 145
(11)
350
(85) 4.92
(2.30) 4.56
(1.1) 212
(72)
389
(52) 3.32
(0.97) 5.92
(2.19) 728
(151)
188
(45) 7.76
(3.12) 9.84
(1.62) 354
(128)
132
(40) 55.0
(12.9) 52.3
(7.2) 152
(30)
43.8
(1.0) 40.7
(1.0)
41.4 41.2
2 2
(0.3)
(0.6)
174
(11)
146
(8)
150
(56)
745
(155)
254
(25)
161
(16)
42.2
(0.8)
521
(57) 1.88
(0.15) 2.48
(1.19) 870
(214) 2545
(1293)
320
(106) 419
(81) 763
(223) 889
(119) 1.77
(0.32) 1.87
(1.06) 791
(272) 7672
(6426)
107
(4)
136
(19)
104
(16) 129
(12) 114
(13)
0.152
(0.012) 123
(15) 102
(9)
120
(11)
4;5 Seed set (%) - - 59.3
(2.3) 71.5
(5.2) 75.1
(1.0)
Number of
pistils
4;6 Dry matter
(%)
145
(7)
1.17
(0.11) 0.91
(0.25) 107
(10)
151
(15) 7.41
(0.69) 6.08
(0.44) 112
(13)
114
(10) 0.15
(0.01) 0.14
(0.03) 103
(4)
84.8
(3.1)
- - 11.2
(0.7) 11.1
(0.9) 9.56
(0.61) 10.7
(0.3)
- - 16.0
(0.5) 15.1
(0.3) 14.5
(0.2)
14.4
(0.2)
- - 68.4
(5.3)
- - 11.8
(0.6)
- - 16.3
(0.5)
1 N = 3, 2 N = 4
‡ Results of LSD tests (P ≤ 0.05) :
Total number of ramets : Dry Bog in 2009 a < Dry Bog in 2008 b = Wet Bog in 2008 b ≤ Wet Bog in 2009 bc
Number of non-floral ramets : Dry Bog in 2009 a < Dry Bog in 2008 b = Wet Bog in 2008 b < Wet Bog in 2009 c
Number of female ramets : Wet Bog in 2009 a = Wet Bog in 2008 a = Dry Bog in 2009 a < Dry Bog in 2008 b
3 Significant differences between bogs in 2008
4 Significant differences between years in the wet bog
5 Significant differences between treatments in the wet bog (2008 and 2009)
6 Significant differences between treatments in 2008 (wet and dry bogs)
241
(126)
128
(32)
225
(138)
63.8
(6.4)
11.7
(1.0)
15.8
(0.3)
150
(21)
131
(9) 1
153
(10)
130
(7)
260 184
1
(90) (77)
568 581
1
(117) (102)
331 252
1
(120) (20)
145 147
1
(30) (16)
- -
- -
- -
- -
- -
- -
- -
- -
- -
19

Fertilizer absorption
Among all nutrients, only the sulfur concentrations in the fruits in 2009 were higher in the
fertilized plots (0.092 % ± 0.005) than in the control plots (0.078 % ± 0.003) (table 2). All the
other nutrients did not significantly differ between the two treatments in either fruit, rhizome, or
leaf.
Table 4. F and P values of ANOVAs testing the impact of the fertilizer application on the different nutrient
concentrations in cloudberry rhizome (2009), leaf (2009) and fruit (2008 and 2009) in the wet and dry bogs studied on
the Lower-North-Shore. In 2009, there were fruits only in the wet bog. The degrees of freedom are 17, except for the
2009 fruits where degrees of freedom are indicated.
2008 2009
Fruit Rhizome Leaf Fruit
Nutrient F P F P F P df F P
Carbon 1.25 0.279 0.89 0.359 0.00 0.988 8 0.50 0.500
Sulfur 0.53 0.478 0.07 0.792 0.33 0.572 8 6.51 0.034
Nitrogen 0.28 0.603 0.18 0.676 1.24 0.281 8 2.15 0.181
Phosphorus 0.26 0.618 0.15 0.707 0.17 0.687 7 0.41 0.543
Potassium 1.90 0.186 0.12 0.736 0.43 0.520 7 4.81 0.065
Calcium 3.46 0.080 0.02 0.897 0.49 0.492 7 0.19 0.679
Magnesium 0.71 0.411 0.48 0.496 2.10 0.166 7 0.43 0.534
Manganese 0.05 0.829 0.01 0.943 0.01 0.943 7 0.22 0.656
Iron 0.18 0.678 0.20 0.663 0.03 0.866 7 1.56 0.251
Aluminium - - 1.42 0.250 1.56 0.229 7 0.22 0.656
Copper 1.05 0.319 2.56 0.128 2.36 0.143 7 0.18 0.684
Zinc 0.34 0.565 0.29 0.598 0.01 0.914 7 1.23 0.304
Boron - - 0.05 0.827 0.05 0.827 7 0.07 0.792
- Nutrient not quantified or not quantifiable
20

Fertilizer dispersion study
No nitrate or phosphate could be detected in either bog. In the dry bog, ammonium and potassium
ion were dispersed up to 10 cm (fig. 4). There was non linear dispersion of ammonium and
potassium in the dry bog (figure 4) and of calcium in the wet bog (figure 5) probably due in part to
ionic affinity with adsorption surfaces made of organic acids and humic substances. Obviously,
there was no cross-contamination between treatments using a 5 m spacing. The nutrient
concentrations reported near application point were comparable to nutrient concentrations in the
plots in 2007 before any fertilizer application (fig. 5), indicating little impact of the fertilization on
the nutritional status of the bog.
Ionic concentration (mg kg -1 dry soil)
800
600
400
200
0
100
80
60
40
20
Wet bog
Potassium ion
F = 0.46; P = 0.709
Ammonium
F = 0.42; P = 0.739
Distance from fertilisation point (cm)
Dry bog
Potassium ion
F = 6.99; P < 0.001
Ammonium
F = 9.23; P < 0.001
0
0 20 40 60 80 100 0 20 40 60 80 100
Figure 9. Ionic concentration (mg kg -1 dry soil) of potassium and ammonium ions (mean ± SE) as a function of the
distance from the fertilization point (cm) in the wet and dry bogs, one year after fertilizer application, on the Lower
North-Shore. F and P values of ANOVAs conducted to compare the concentrations between distances are shown.
Different lower case letters indicate significant differences between distances for a specific ion, based on LSD tests.
a
a
b
b
b
b
b
b
21

Total concentration (mg kg -1 dry soil)
Total concentration (mg kg -1 dry soil)
Total concentration (mg kg -1 dry soil)
10000
9000
8000
7000
6000
5000
950
900
850
800
750
700
650
600
550
1400
1350
1300
1250
1200
Nitrogen
F = 0.36; P = 0.779
Potassium
F = 0.31; P = 0.818
Magnesium
F = 0.19; P = 0.901
1150
0 20 40 60 80 100
Distance fromfertilisation point (cm)
420
400
380
360
340
320
300
2100
2000
1900
1800
1700
1600
1500
Phosphorus
F = 0.74; P = 0.532
Calcium
F = 2.82; P = 0.045
1400
0 20 40 60 80 100
Distance from fertilisation point (cm)
Figure 10. Total concentration (mg kg -1 dry soil) of different nutrients (mean ± SE) as a function of the distance from
fertilization point in the wet bog, one year after fertilizer application, on the Lower North-Shore. F and P values of
ANOVAs conducted to compare the concentrations between distances are shown. Different lower case letters indicate
significant differences between distances for a specific ion, based on LSD tests. The horizontal lines indicate the mean
values measured in the control plots in 2007. The dashed lines represent the mean and the dotted lines the standarderror
of the mean.
a
a b
a b
b
22

Discussion
Cloudberry fertilization
Pearson’s correlations
Bierzychudek and Eckhart (1988) suggested that female plants would occupy better sites than
male clones in dioecious species to compensate for higher reproductive costs. In the present study,
the plots presenting the higher female floral ramet density were also the ones producing the bigger
fruits. It appears that the better sites not only have higher female ramet density but they also
provided the conditions needed for a better flowering frequency and a better fruiting success.
Cloudberry‟s fruiting success varies greatly from year to year being mostly limited by climatic
conditions such as late spring frosts (Resvoll, 1929; Mäkinen and Oikarinen, 1974; Kortesharju,
1984). Ågren (1988) suggested that the “over-initiation” of cloudberry flower buds in autumn
allows the plant to take advantage of years favourable for flowering and fruit development to reach
a high reproductive success. However, Ågren (1988) reported that fruit-producing female ramets
had a lower probability of flowering the subsequent year than male ramets and that this might limit
fruit production the year following a high fruiting success year. Still, his study also suggested that
a year with a high fruit yield does not significantly limit the production of female flower buds for
the following year. In the present study, there were two successive years with a high fruit yield
suggesting that the plant might not be limited, neither in terms of female flower bud production
nor in terms of fruit production by the fruiting success of the previous year. In fact, in the wet bog,
the number of female ramets and fruits were proportional to the number of fruits of the previous
year. This suggests that cloudberry might use a strategy of over-initiation of flower buds each
year, regardless of the reproductive success of the previous year, and that fruit yield might be more
influenced by the current year‟s conditions than by the previous year‟s fruit yield. It appears that
good sites remain the same year after year, although the actual fruit yields can vary greatly from
year to year for a given site as shown in the present study.
Cloudberry fertilization
The fertilisation treatment had no impact on either ramet density, flowering frequency or fruit
production even after three years of application. Fertilization decreased the fruit percent dry matter
and increased seed set but either for a single year or in one bog only. As fruit mass did not
changed, an increased seed set was apparently compensated by slightly smaller druplets to yield
similar fruit mass.
Sulfur concentration was higher in the fertilized fruits. However, this result has to be considered
with caution considering that the methods available for sulfur determination are being criticized
and that the fertilizer used was not a significant source of sulfur (0.40 %). Besides, sulfur was the
only nutrient that did change following fertilization. Therefore, since no change in the main
nutrient concentrations were observed in either rhizomes, leaves, or fruits, we consider that the
fertilizer was simply not absorbed by the cloudberry plants which could explain the lack of
fertiliser impact on ramet density and flower and fruit production.
23

Many studies have been conducted on cloudberry fertilization over the years and a few
recommendations have been proposed. Rapp and Steenberg (1977) recommended applying the
fertilizer at cloudberry‟s rhizomes depth instead of on the ground surface to reduce the absorption
by competing vegetation. Kortesharju and Rantala (1980) suggested an annual fertilizer
application, or at least, more frequent than every four years because the fertilizer effects seems to
fade out after four years. Cloudberry has been identified as a slow growing plant (Chapin, 1980)
that store nutrients when available to use it over a number of years. That would explain why it is
important to run longer term studies as the impact on fruit production is often reported three to
four years after the fertilization (Kortesharju and Rantala, 1980; Gauci, 2008; Bellemare et al.,
2009).
Fertilizer dispersion
Applied as KCl, potassium was totally soluble in water. There was limited dispersion of potassium
in the dry bog probably caused by the increased tortuosity while moving away from the point of
application in the dry bog compared to the wet bog (Saripalli et al., 2002).
Therefore, dispersion should be facilitated in the wet bog. The potassium concentration profiles
suggested that potassium moved to greater distances – most likely beyond 80 cm – in the wet bog
than in the dry bog. But it is also possible that the wet bog already had a higher potassium
concentration than the dry bog and that potassium from the fertilizer was just washed away
towards the edge of the bog (Damman, 1986).
Chemical analysis of the fertilizer indicated that some of the organic nitrogen present in the
fertilizer had already been mineralized into ammonium before application. Therefore, some
ammonium should have been readily available to the plant at the time of fertilizer application. In
the dry bog, a certain amount of ammonium was detected 10 cm from the fertilization point. Two
phenomena could explain this result. There might have been some nitrogen mineralization in the
dry bog, potentially due to more suitable conditions for mineralization in the dry than in the wet
bog (Updegraff et al., 1995). Or, as suggested for potassium, tortuosity limited the dispersion of
ammonium in the dry bog. However, there was very low ammonium concentration in the wet bog
suggesting that very little ammonium was dispersed from the fertilizer over one year.
One of the main differences between the wet and dry bogs was the presence of living sphagnum in
the wet bog. We thus hypothesized that living sphagnum might have absorbed part of the nutrients
from the fertilizer and transformed it into an organic form (Malmer et al., 2003). To test this
hypothesis, we analyzed the total nutrient concentration in the soil samples from the wet bog. Most
nutrient concentrations observed near fertilization point were comparable to nutrient
concentrations in control soil samples collected in 2007, i.e. before any fertilizer application. Thus
even the living sphagnum did not absorb much of the fertilizer nutrients. Nitrogen and phosphorus
concentrations were particularly low compared to the concentrations measured in control plots.
Since these two nutrients are usually considered as the most limiting to plant growth, we
concluded that the organo-mineral fertilizer used in the present study was not suitable for use in
bogs where N and P mineralization might be limited by high water content, low temperatures
(Updegraff, 1995) and pH (Fellman and D‟Amore, 2007) and limited microbial activity (Gogo and
Pearce, 2009).
24

Micro-climate Management
The correlation between bumper crops of cloudberry and snowy winters has been noted by many
berry pickers along the north shore. In northern Norway as well, sites where snow persists the
longest have been noted as particularly good cloudberry sites (Sæbø 1977). Protection from winter
injury and delayed flowering are among the many possible benefits of increased snow cover.
Cloudberry plants from both coastal and inland regions of Norway (Rapp and Stushnoff 1979) are
not particularly hardy despite their sub-arctic distribution. In laboratory tests, Rapp and Stushnoff
(1979) found that rhizome buds, at their hardiest during midwinter, were only hardy to -13 C.
Under a good snow cover, soil temperatures are moderated and perennial herbs are protected from
cold injury and desiccation. Thus, a good snow cover may in some years have positive effects on
cloudberry yields by protecting floral buds. A late spring frost is however the most frequently cited
reason for crop failure in cloudberry both in Canada and in Scandinavia (Kortesharju 1995,
Yudina 1993, Kortesharju 1988, Ågren 1988, Dumas and Mailliette 1987, Lid 1961, Resvoll 1929,
among others). As little as a week delay in flowering, due respectively to shading or mulching, has
been observed to have significant effects on cloudberry yields (Yudina 1993, Lid 1961).
Significant delays in flowering can also be realised through snow management techniques. In a
pilot experiment conducted in the region of Minganie and on the Lower North Shore using
enclosures to modify microclimate, significant delays in flowering were achieved (Naess et al.,
unpublished results).
While no differences in flower numbers were observed, fruit set and yields were increased in the
Minganie area the season following treatment application. In the second season of the experiment,
following the mild winter of 2005/2006, no delays in flowering were obtained on the lower north
shore, nor were there observable differences in fruit set between treatments. However, a significant
increase in the numbers of female flowers was observed in snow treatment plots relative to control
plots, resulting in greater yields. Depending on the timing of the arrival of cold weather relative to
snowfall, snow fences may have very different effects on soil temperatures (Decker et al., 2003)
and consequently also on spring phenology. Thus a delay in the deployment of snowfencing until
after cold temperatures have arrived may be the most effective way of delaying spring flowering.
Snowfences must nonetheless be applied before the cloudberry begins to lose hardiness midwinter
in order to take advantage of any positive effect snow may have on protecting floral buds from
freeze injury (Kaurin et al., 1981).
Thekla Resvoll, in her classic work on the biology of Rubus chamaemorus (1929), is perhaps the
first to speculate on the importance of temperatures to cloudberry fruit production. Increased
temperatures during flowering can have beneficial effects both on fruit set and on the activity of
pollinating insects. Nonetheless, few experiments aimed towards increasing temperatures in
general have been carried out despite several studies correlating above average temperatures with
increased yields. These correlations have been found, perhaps not unexpectedly, for temperatures
during flowering (Wallenius, 1999). More interestingly, a positive correlation between relatively
warm late summer temperatures and female flower bud formation, and thus potential yields, has
been observed (Arntzen 1976, Rapp 1989). One way of increasing temperatures which might be
practically applied to peatlands is through the use of windbreaks. Preliminary trials on the use of
windbreaks in cloudberry production were initiated as early as the late 1950‟s (Østgård 1964) with
more detailed trials reported in 1980 (Bottengård). Bottengard, using a permanent plastic snow
25

fence, obtained wind reductions of 20-50% and daytime temperature increases behind the fence of
3ºC on an open bog in Norway. In the shelter of these fences both flower numbers and fruit size
increased. Windbreaks were left in place permanently and the effects of increased snowcover
could not be distinguished from those of decreased winds. It is important to separate out these
factors in order to increase our understanding of how the added shelter is affecting yields.
Important interactions between snow accumulation and wind reduction could effect how the
producer might use this technology. In a pilot project examining the use of enclosures for snow
accumulation and summer windbreaks, yields and fruit set were better in both snow accumulation
and wind sheltered plots than in the controls but these difference were significant only for snow
accumulation plots (Naess, 2007).
Materials and methods
Location
The experiment was located in two large bogs North West of Blanc-Sablon, Québec. One of the
bogs is a wet sphagnum bog while the other is a considerably dryer bog with less sphagnum and
more caribou lichen. A description of these two bogs is given under the soil fertility section of this
report.
Experimental design
The experimental design used was a complete randomized nested block design with 2 bogs and
five treatments applied in replicate (two blocks) to each of the bogs. The five treatments were the
following:
1) Control: no fencing applied at any time of the year
2) Snow: snow fences applied in the fall and dismantled in the spring
3) Delayed snow: snow fences applied mid-winter and dismantled in the spring
4) Wind: snow fences applied in the spring and dismantled in the fall
5) Snow and Wind: snow fences applied and left in place all year round
Sampling plot direction (NE or SW relative to the fencing) was nested within treatment.
Plot establishment
Plots were established in the spring of 2007 before the plants began to grow. Areas in each bog
with the presence of at least some female cloudberry plants as indicated by the presence of
previous years fruiting structures were chosen for plot establishment. The treatment plots,
consisting of a row of fence posts with two meter spacing, were 30 meters long oriented from the
southeast towards the northwest. On either side of the fences two sampling plots were established.
These plots were 10 meters long by 1 meter wide and covered the central 10 meters to the
northeast and southwest of the fences. The two sampling plots on either side of the fences were
located respectively 1.5 and 3.5 meters from the fences.
26

Treatment application
Tensar high density polyethylene snow fencing (Agriflex incorporated, Ontario, Canada) with a
50 % porosity factor was used for all treatments. The snow fencing was 1.2 meter high and 30
meters long.
Treatment application commenced in the fall of 2007, after a season‟s worth of baseline data had
been taken. The dates of snow fence application for the various treatments are given in table 3.
Table 3. Snow fence application and removal dates for the various treatments.
Treatment Application Removal Application Removal
Control None None None None
Snow 12.10.2007 02.06.2008 27.10.2008 09.06.2009
Delayed Snow 31.01.2008 02.06.2008 01.02.2009 09.06.2009
Wind 02.06.2008 27.10.2008 09.06.2009 10.11.2009
Snow and Wind 12.10.2007 None Still up None
Data Collection
Micro-climate data
Proseries H8 HOBO data loggers (Onset Computer Corporation, MA, USA) were used to log
temperatures in the field. Data loggers were installed 3 meters from the fencing and centered on
the plot of one set of treatments in the dry bog. Additional loggers were added later to a set of
treatments in the wet bog. Probes were placed at 10 cm above ground for recording ambient air
temperatures and 10 below ground for soil temperatures. For the “Control”, “Snow” and “Delayed
Snow” treatments hobo loggers were placed to the SW of the fencing where the effects of the
fencing was expected to be greatest. For the “Wind” treatment the logger was placed to the NE of
the fencing blocking the predominantly southwest summertime winds. For the “Snow and Wind”
treatment a hobo data logger was placed on either side of the fencing.
Data on wind speeds were taken every other day during the flowering season using a hand held
anemometer.
Data on depth of frost was taken by poking a thin metal rod into the ground until frozen ground
was reached and measuring the distance.
Flowering phenology, shoot numbers, flower numbers and sex ratio
The bogs were visited every other day during the flowering season. Open male and female
flowers were counted in all the sampling plots at that time. In 2007 there was only one sampling
plot on either side of the fence-line early in the season. However, due to a lack of flowers,
additional sampling plots were established 1 meter from the first sampling plots and the data from
the two sampling plots on either side of the fence-line was combined for analyses. At the end of
the flowering season, all shoots and flowering shoots were counted within the plots and the sex
ratios calculated.
27

Pollinating insects
Transects passing by all of the plots were established in both bogs. At each visit during the
flowering season, the transects were slowly walked and all pollinating insects seen on cloudberry
or on other flowers was noted. Each transect took approximately half an hour to walk. Insects
seen were identified to the following groups: bumble bees, other bees, small, medium or large
flies, hover flies, butterflies and moths, ants, beetles, and unknown.
Pollination, fruit and seed set
Every four days during the flowering season, up to 10 flowers per sampling plot were tagged for
later analysis of pollen loads, fruit and seed set. These flowers were gathered two weeks after
tagging and placed in 70% ethanol until analysis. At analysis, the flowers or developing fruit were
rinsed in water to remove the ethanol and stained in aceto carmine for 20 minutes. The number of
pistils and developing druplets was noted. Stigmas were cut from the pistils and mounted on
slides for examination. The number of grains of cloudberry pollen per stigma was counted. The
number and type of other grains of pollen was also noted.
Fruit ripening and floral bud development
Fruit ripening data were taken as the fruit ripened. In 2009 only, five stage 13 (ripe) fruiting
shoots were tagged per plot every four days for a period of 16 days in order to see if there was a
relationship between fruit ripening and bud development. Buds subtending the floral shoots were
collected 6 weeks after the last tagging date and placed in 70% ethanol until analysis. At analysis,
the apical meristem in the bud was scored for developmental stage on a 1-5 scale where 1=
vegetative, 2= corolla developing, 3= anthers developing, 4=carpels developing and 5= carpel
lobes closed.
Yields
Once the fruit started ripening the plots were visited every other day again. All stage 12 and 13
(Beaulieu et al., 2001) fruit were collected, counted and weighed.
Data analysis
Data were analysed using the proc mixed procedure in the SAS program (SAS 1999). Where
appropriate a repeated measures analysis within the mixed procedure was applied to the data.
Baseline data collected in 2007 before treatment application were used as covariates in the
analyses.
28

Results
Baseline data
There was significant variation between plots and bogs with respect to shoot densities, flower
numbers, and fruit in 2007 before the snow fences and/or windbreaks were put in place (table 4).
2007 was not a particularly good year for cloudberry and yields in the plots averaged only 9.8
kg/hectare in the dry bog and 30.6 kg /hectare in the wet bog. There was considerable variation
between the plots with yields ranging from less than 1 kg/hectare in the poorest plot to up to 198
kg per hectare in the best plot.
Due to the considerable natural variation in important yield factors between the plots these
baseline data are used as covariates in the analyses of data collected from the plots in 2008 and
2009.
Table 4. Baseline data taken on the plots in 2007 display considerable natural variation in
important yield factors.
Bog Shoots
(per 10 m 2 Flowers
plot) (per 10 m 2 Fruit
plot) (per 10 m 2 Yields (kg/hectare)
plot)
Average Range Average Range Average Range Average Range
Dry 508 80-1042 61 9-176 10.5 0.5-29 9.8 0.2-29
Wet 1054 291-2069 109 20-237 30.2 1-92 30.6 4.3-99
Micro-climate data
No differences in air or soil temperature data collected from the treatment plots were observed in
the baseline data collected before treatment application. However, air temperatures at 10 cm above
ground were slightly though significantly warmer in the dry bog than in the wet bog (1.7°C
difference). No differences were observed in the soil temperatures collected at 10 cm below
ground between the two bogs which averaged 10°C during the summer and fall period preceding
treatment application.
Snow fences had significant effects on soil temperatures collected at 10 cm below ground
throughout the winter season. In figure 6, soil temperature data averaged across plots sheltered by
snow fences during the winter (“Snow” and “Snow and Wind” treatments) and those without snow
fences (“Control” and “Wind” treatments) is displayed along with data collected from a “Delayed
Snow” treatment plot. These data are superimposed onto snow accumulation data collected at the
airport at Blanc-Sablon for illustration purposes. (Note that by the 2008-2009 season many of the
hobo data loggers were no longer functioning, thus temperature data shown for that season is not
replicated).
In snow fenced plots mean soil temperatures collected at 10 cm below ground remained above -
1°C throughout the 2007/2008 winter season while in unprotected plots mean temperatures fell to -
6°C in late January and remained below -1°C from late December 2007 through the first week of
29

April, 2008. Unfortunately one of the hobo data loggers placed in a “Delayed Snow” treatment
plot malfunctioned, thus data presented is from only 1 temperature probe. In this plot soil
temperatures at 10 cm below ground rose above -1°C within three weeks of snow fence
application at the end of January and remained above -1°C throughout the rest of the season.
Accumulated snow (cm)
70
60
50
40
30
20
10
0
12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 3123456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30123456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 3123456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 3123456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29123456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 3123456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30123456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
10 11 12 1 2 3 4 5 6
2007 2008
Year and Month
6
4
2
0
-2
-4
-6
-8
Temperature ° C
Snow on ground (cm)
No Snow Fence
Snow Fence
Delayed Snow Fence
Figure 6. Soil temperatures 10 cm below ground logged in plots with and with snow fences or with
snow fences put up late winter (“Delayed Snow Fence”) during the 2007/2008 winter
superimposed over snow accumulation data collected at the airport in Blanc-Sablon.
30

Accumulated snow (cm)
100
90
80
70
60
50
40
30
20
10
0
123456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 3123456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30123456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 3123456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 3123456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28123456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 3123456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30123456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
10 11 12 1 2 3 4 5
2008 2009
Year and Month
10
8
6
4
2
0
-2
-4
-6
-8
-10
Snow on ground
Delayed Snow Fence
No Snow Fence
Snow Fence
Figure 7. Soil temperatures 10 cm below ground logged in plots with and with snow fences or with
snow fences put up late winter (“Delayed Snow Fence”) during the 2008/2009 winter
superimposed over snow accumulation data collected at the airport in Blanc-Sablon.
Similar treatment effects on minimum winter soil temperatures were obtained during the 2008-
2009 winter season (fig. 7). Soil temperatures in the plot with snow fencing remained above 0°C
throughout the winter while soil temperatures in the unprotected plots or plots where snow fencing
was applied late winter descended to -8°C in late December, 2008. Snow accumulation in the
2008-2009 season was greater than in the previous year, with accumulations of almost a meter
recorded at the airport at Blanc-Sablon. Nonetheless, minimum soil temperatures recorded at
10cm below ground remained below freezing in plots without snow fences and those with delayed
snow fences throughout the season.
31

Soil temperatures at 10 cm below ground (°C)
18
16
14
12
10
8
6
4
2
0
2
3
4
5
6
7
8
9
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123456789
6 7 8
Month and Date 2008
10
11
12
13
14
15
16
17
18
19
20
Delayed Snow Fence
No Snow Fence
Snow Fence
Figure 8. Soil temperatures 10 cm below ground logged in plots with and with snow fences or with
snow fences put up late winter (“Delayed Snow Fence”) during the spring and summer of 2008.
Significant differences in soil temperatures among plots with and without snow fences during the
winter season were observed well into the summer season. Soil temperatures at 10 cm below
ground were an average of 1.8 °C warmer in plots which had been protected by snow fences than
those not protected by snow fences in June and July while temperature differences observed in
August were not significant (fig. 8). Soil temperatures in the “Delayed Snow” treatment plots were
cooler than those in all other plots in the month of June and remained cooler than temperatures
observed in plots protected by snow fences in July.
In the summer season of 2008 there were also significant differences in soil temperatures between
the dry and the wet bog. Soil temperatures in the wet bog were two to three degrees warmer than
in the dry bog throughout the summer season.
In the 2009 summer season also, mean soil temperatures observed at 10 cm below ground
remained warmer in plots previously protected with snow fences during the fall and winter season
while in the “Delayed Snow” treatment soil temperatures were cooler (fig. 9).
32

Soil temperatures 10 cm below ground (°C)
18
16
14
12
10
8
6
4
2
0
-2
1
2
3
4
5
6
7
8
9
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5 6 7
2009
Year and month
10
11
12
13
14
15
16
17
18
19
Delayed Snow Fence
No Snow Fence
Snow Fence
Figure 9. Soil temperatures 10 cm below ground logged in plots with and with snow fences or with
snow fences put up late winter (“Delayed Snow Fence”) during the spring and summer of 2009.
In both 2008 and 2009 soils thawed much earlier in the spring in the “Snow” and “Snow and
Wind” treatment plots than in the treatment plots not protected by snow fences or those where the
snow fences were put up midwinter (fig. 10). Soil thawed more quickly in the wet bog than in the
dry bog. In the wet bog the distance to frozen ground was on average 12 cm greater than in the
dry bog throughout the month of June and into July.
33

Thawed ground (cm)
120
100
80
60
40
20
0
13 15 17 19 21 23 25 27 29 1 3 5 7 9 11 13 9 11 13 15 17 19 21 23 25 27 29 1 3 5 7 9 11
6 7 6 7
2008 2009
Date
CONTROL
DELASNOW
SNOW
SNOWIND
Figure 10. Depth of thawed ground as affected by snow fences and windbreaks in 2008 and 2009.
Maximum daily air temperatures at 10 cm above ground were significantly warmer in plots
protected by wind breaks during the month of July but observed differences in June and in August
were not significant (fig. 11). Average daily maximum temperature differences between plots
protected by wind breaks and those without wind breaks ranged from less than 1°C to a maximum
of 3°C. Differences in minimum air temperatures between plots with wind breaks and those
without wind breaks were not significant. During the 2008 summer season air temperatures at 10
cm above ground fell below the freezing point on the fourth, fifth and sixth of June, before the
cloudberry flowering period had begun.
While soil temperatures were warmer in the wet bog than the dry bog, maximum daily air
temperatures were 1 to 2 °C warmer in the dry bog than in the wet bog during the months of June
and July, 2008.
WIND
34

Air Temperature at 10 cm °C
35
30
25
20
15
10
5
0
-5
Month and Date 2008
Min Air Temp - No Wind break
Min Air Temp - Wind break
Max Air Temp - No Wind break
Max Air Temp - Wind break
Figure 11. Maximum and minimum daily air temperatures at 10 cm above ground in plots
protected by wind breaks and those without wind breaks during the summer of 2008.
Similar treatment effects on maximum and minimum air temperatures were observed in 2009 (fig.
12). However, during the 2009 flowering season many spring frosts were observed in the dry bog
but not in the wet bog (fig. 13). As late as July 9 th , 2009 a frost of -3°C was observed in the dry
bog while minimum temperatures measured in the wet bog on that date averaged 1.7°C. There
were no significant effects of windbreaks on minimum temperatures in either bog.
35

Air temperatures at 10 cm (°C)
35
30
25
20
15
10
5
0
-5
June and July, 2009
No Windbreak - Max air temp
No Windbreak - Min air temp
Windbreak - Max air temp
Windbreak - Min air temp
Figure 12. Maximum and minimum daily air temperatures at 10 cm above ground in plots
protected by wind breaks and those without wind breaks during the summer of 2009.
Minimum air temperatures at 10 cm (°C)
14
12
10
8
6
4
2
0
-2
-4
-6
June and July, 2009
Dry bog
Wet bog
Figure 13. Minimum temperatures recorded in the dry and the wet bog during the summer of 2009.
36

Windspeed (m/s)
8
7
6
5
4
3
2
1
0
13 15 17 19 21 23 25 27 29 1 3 5 7 11 13
6 7
Month and Date 2008
No Wind break - NE
No Wind break - SW
Wind break - NE
Wind break - SW
Figure 14. Windspeeds recorded in the SW and NE sampling plots of plots with and without
windbreaks during the cloudberry flowering period, 2008.
Windspeeds were significantly reduced in plots protected by wind breaks relative to those without
wind breaks. The reduction in wind speed was more pronounced on the leeward side of the wind
breaks which in 2008 shifted from the southwest towards the northeast in July (fig. 14). Overall
wind speeds were reduced by 0.33 m/s in protected plots while reductions on the leeward side
averaged 1.6 m/s in June and 0.75 m/s in July.
37

Flowering phenology
Data on flowering phenology were taken every two days throughout the flowering season.
However, as flower numbers per data collection day and plot were sometimes low, data from two
consecutive data collection days were combined into collection periods for analysis and
presentation purposes. In both 2008 and 2009 data on flowering phenology were collected over a
period of 32 days or 8 periods.
Baseline phenology data collected in 2007 was not correlated with phenology data collected in
2008 or 2009 and was thus dropped from the analysis.
Flowering phenology varied between the two years of the experiment, between bogs and between
treatments during the two seasons monitored in this experiment. Flowering phenology varied
significantly between the wet and dry bogs in 2008 but not in 2009 (fig. 15). In 2008, flowering in
the wet bog peaked 8 days earlier than flowering in the dry bog.
Flowers
9000
8000
7000
6000
5000
4000
3000
2000
1000
0
1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8
2008 2009
Year and Period
Figure 15. Flowering phenology in the wet and dry bogs, 2008 and 2009.
Dry Bog
Wet Bog
Significant treatment effects on flowering phenology were obtained in both 2008 and in 2009 (fig.
16). In both years, flowering was delayed in the “Delayed Snow” treatment relative to all other
treatments while the “Wind” and “Snow and Wind” treatments advanced flowering relative to the
“Snow” and “Control” treatments. Treatment effects were not constant across the two years of the
study. In 2009 when the flowering season was more concentrated, the “Delayed Snow” treatment
significantly delayed flowering but differences among the other treatments were not significant
38

(table 5). In the “Delayed Snow” treatment flowering peaked 8 days later in 2008 and 5 days later
in 2009 than in the other treatments.
Proportion flowered
1.2
1
0.8
0.6
0.4
0.2
0
1 2 3 4 5 6 7 8 9 1 2 3 4 5 6 7 8
2008 2009
Year and Period
Control
Delayed Snow
Snow
Snow and Wind
Figure 16. Cumulative flowering proportion as affected by the snow fence and windbreak
treatments in 2008 and in 2009.
Table 5. Treatment effects on mean cumulative flowering percentage in 2008 and 2009.
Treatment Mean Cumulative Flowering Percentage
2008 2009
Control 60 ab 70 a
Snow 56 b 72 a
Delayed Snow 50 c 64 b
Wind 65 a 74 a
Snow and Wind 63 a 73 a
Means in columns followed by the same letter are not significantly different at p=0.05
Wind
39

Shoot and Flower numbers
Shoot and flower numbers were analysed using baseline data as a covariate in the analyses. While
there were significant differences between the bogs with respect to shoot numbers per plot, the
treatments had no effect on this variable. In the dry bog shoot numbers, adjusted for baseline data,
averaged 77 per m 2 vs 97 per m 2 for the wet bog.
There were significant treatment effects on the number of flowers produced in the plots in the wet
bog while in the dry bog differences between treatments were not significant (fig. 17). In the wet
bog the increase in floral shoots in plots protected by snow fences in the winter (“Snow” and
“Snow and Wind” treatments) was largely due to a significant increase in the number of male
flowers (table 6). In the wet bog there were almost three times as many male flowers in snow
fenced plots as compared to plots not protected by snow fences during the winter. There was also
an increase in the number of female flowers in these plots, however the observed difference was
not significant.
Floral shoots per plot
600
500
400
300
200
100
0
Dry Wet
Figure 17. Treatment effects on flower numbers in the wet and the dry bog.
Bog
Control
Delayed Snow
Snow
Snow and Wind
Wind
40

Table 6. The number of baseline adjusted floral shoots produced in the dry and wet bogs as
influenced by snow fences.
Bog Snow fenced # Baseline adjusted floral shoots per plot (10m 2 )
Females Males Floral
Dry No 142 a 107 b 256 b
Dry Yes 135 a 84 b 228 b
Wet No 90 a 95 b 183 b
Wet Yes 139 a 267 a 393 a
Means in columns followed by the same letter are not significantly different at p=0.05
Pollinating insects
Relatively few insects were seen in the bogs while walking the transects past the plots. Weather
conditions during the flowering season in 2007 were poor and no insects were seen in either bog
on five of the 15 survey days. On an additional five days insects were seen in only one of the two
bogs surveyed. On average only 5 insects were observed per day in 2007 with a range of 0 to 15
insects seen depending on the survey day. In 2008 insects seen per day ranged from 0 to 31 and
averaged 7 while in 2009 insects were more abundant with a range of 0-58 insects seen per day
and an average of 20.
Over half the insects observed in the bogs were foraging on cloudberry flowers (table 7). Of these
by far the most important group were the dipterans. Of the hymenoptera the bumble bees were the
most frequently seen but they were most often observed flying by rather than working the flowers.
Both the dipterans and the hymenoptera were more frequently viewed in male cloudberry flowers
than in the female flowers. The lepidoptera were the most frequently observed insects in the bogs
but these were rarely viewed on flowers.
41

Table 7. The types of insects observed in the bogs during the cloudberry flowering season.
Insect order Type On Cloudberry Flowers On
Not on Insects
Ericaceae Flowers Total
Male Female Unknown Total
Diptera
Syrphids 41 4 45 6 13 64
Others 123 81 3 207 12 22 244
Coleoptera 2 1 3 2 5
Homoptera 14 29 43 43
Hymenoptera
Bumblebees 5 3 8 8 21 39
Ants 12 12 24 24
Others 8 8 1 3 12
Lepidoptera 7 4 3 14 5 245 269
Other insects 3 4 1 8 13 23
Insects total 215 135 10 360 32 319 723
42

There were no significant treatment effects on the number of insects observed in the plots.
Slightly more insects were observed on cloudberry flowers in plots protected by windbreaks than
in plots without windbreaks (fig. 18) but this difference was not significant.
Insects foraging on cloudberry flowers
40
35
30
25
20
15
10
5
0
2008 2009
Year
Figure 18. Insects observed foraging on cloudberry flowers in plots protected by windbreaks (Yes)
and in plots without windbreaks (No).
Pollination
Pollination of tagged flowers, as defined by the presence of at least one cloudberry or ericaceous
pollen grain on a stigma of the cloudberry flower, was excellent in both years following treatment
application. There were only slight though significant differences between the years with 88% of
tagged flowers pollinated in 2008 versus 92% in 2009. There were also differences between the
two bogs; a greater percentage of tagged flowers were pollinated in the dry bog (92%) than in the
wet bog (88%). Pollination percentage varied significantly from day to day in both 2008 and 2009
and ranged from a low of 88% in 2008 to a high of 99% in 2009. There were no treatment effects
on pollination percentage in either year (Table 6). The total display of flowers in the plot as well
as the ratio of male to female flowers were used as significant covariates in the analysis. While an
increase in the ratio of male to female flowers was positively correlated with pollination
percentage, the total display per plot was negatively correlated with pollination percentage.
Virtually all of the pollinated flowers received at least some cloudberry pollen. Only 1% of the
observed flowers received only pollen from ericaceous species. Pollen from ericaceous species
was present on the stigmas of respectively 30 and 59% of the tagged flowers in 2008 and 2009. A
No
Yes
43

greater percentage of flowers in the dry bog (57%) were pollinated with pollen from ericaceous
species than in the wet bog (32%).
The proportion of pistils per flower which were pollinated was correlated with the proportion of
flowers pollinated per plot. In 2008 66% of pistils per flower were pollinated while in 2009 76%
were pollinated. Although there was no overall effect of the bog on the proportion of pistils
pollinated, in 2008 significantly fewer pistils per flower (60%) were pollinated in the wet bog than
in the dry bog while in 2009 no differences between bogs were observed. The proportion of pistils
pollinated varied depending on the tagging day from a low of 50% in 2008 to a high of 93% in
2009.
Pollen loads per pistil averaged 10 in 2008 and 13 in 2009. There were no significant differences
between the two bogs in the experiment with respect to pollen loads. Pollen loads per stigma were
significantly lower in the “Delayed Snow” treatment in 2008 than in all other treatments while
there were no significant treatment effects on pollen loads in 2009 (table 8). Pollen loads varied
significantly between tagging days and ranged from a low of 7 pollen grains per stigma in 2009 to
a high of 18 grains per stigma, also in 2009 (fig. 19)
Pollen grains per pistil
20
18
16
14
12
10
8
6
4
2
0
2008 2009
Year and tag day (1,2,3)
Figure 19. Pollen loads per stigma decreased as the season progressed.
1
2
3
44

Table 8. The effects of snow fences and windbreaks on cloudberry pollination.
Treatment Year % Flowers pollinated % Pistils pollinated Pollen per pistil
Control 2008 89 67 10.38 b
Delayed Snow 2008 84 55 5.51 c
Snow 2008 87 67 11.39 ab
Snow and Wind 2008 91 76 13.47 ab
Wind 2008 89 67 10.69 b
Control 2009 90 73 11.91 ab
Delayed Snow 2009 95 78 12.68 ab
Snow 2009 95 76 12.77 ab
Snow and Wind 2009 94 84 14.88 a
Wind 2009 87 71 12.06 ab
Means in columns followed by the same letter are not significantly different at p=0.05
Fruit and seedset
Fruitset in tagged flowers averaged 75%. In both years fruitset was best earlier in the season,
averaging 95% on the first tagging day and falling to only 52% by the third tagging day (fig. 20).
In 2009 only 8% of tagged flowers in the dry bog set fruit on the third day.
There were no treatment effects on fruitset. The percentage of male flowers in the plots on the
tagging date was however a significant covariate in the analysis.
45

Fruitset %
120
100
80
60
40
20
0
Dry
2008
Wet Dry
2009
Year and Bog
Figure 20. Fruitset in the dry and the wet bogs varied with the tagging date.
Seedset was closely correlated to fruitset and varied between the years, bogs and the tagging day.
On average 51% of the pistils per flower set seed. Seedset was greatest early in the season at 75%
but dropped to 32% by the third tagging day. No treatment effects on seedset were observed in the
two years of the experiment.
Fruit ripening and bud development
Data on fruit ripening were taken every two days throughout the fruiting season. However, as fruit
numbers per data collection day and plot were sometimes low, data from two consecutive data
collection days were combined into collection periods for analysis and presentation purposes.
Due to late frosts in the dry bog in 2009 too few fruit were produced in this bog. The analysis of
fruit ripening was therefore across years only for the wet bog and across bogs only for 2008.
In the wet bog, fruit ripening was delayed in both years in the “Delayed Snow” treatment (fig. 21).
In 2008 50 % of the fruit were ripe in the other treatments by the fourth fruit collection period
while 50% fruit ripening was attained only 12 days later, by the 7 th collection period, in the
“Delayed Snow” treatment. Similar but smaller differences were observed in 2009.
Wet
1
2
3
46

Cumulative fruit ripening (%)
120
100
80
60
40
20
0
1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7
2008 2009
Collection period
Control
Delayed Snow
Snow
Snow and Wind
Figure 21. Fruit ripening as affected by the snow fence and windbreak treatments in 2008 and
2009.
Table 9. Treatment effects on fruit ripening in the wet and dry bog.
Treatment Average Accumulated Ripening
Bog
Dry Wet
Control 51 b 56 a
Delayed Snow 60 ab 35 b
Snow 56 ab 57 a
Snow and Wind 60 ab 60 a
Wind 65 a 65 a
Means in columns followed by the same letter are not significantly different at p=0.05
Treatment effects on fruit ripening however were not consistent between the two bogs. In 2008,
the delay in fruit ripening observed in the “Delayed Snow” treatment in the wet bog was not
observed in the dry bog (table 9). In both bogs fruit ripened earliest in plots protected by
windbreaks. Midseason, average accumulated ripening had attained 62% in plots protected by
windbreaks as opposed to 55% in those without windbreaks in 2008.
Wind
47

In 2009, no significant effect of fruit ripening on the developmental stage reached by the meristem
in the bud subtending the fruiting shoot was detected. There were however significant treatment
effects on this factor. Buds subtending fruiting shoots in the “Wind” and “Snow and Wind”
treatments were more advanced by the collection period than those from the other treatments (fig.
22).
% of buds
50
45
40
35
30
25
20
15
10
5
0
1 2 3 4 5
Bud development stage
Control
Delayed Snow
Snow
Snow and Wind
Figure 22. Meristem developmental stage in buds subtending fruiting shoots. 1=vegetative,
2=sepal and petal development, 3=anther development, 4=carpel development, 5=carpel lobes
closed.
Yields
Cloudberry yields varied significantly between years and between the two bogs in the experiment
(table 10). While the number of fruit produced per plot as well as fruit size were superior in the dry
bog than in the wet bog in 2008 the opposite was true in 2009 when a severe late spring frost killed
most flowers and developing fruit in the dry bog. Yields in the dry bog in 2009 averaged only 26
kg per hectare as compared to 120 kg per hectare in the wet bog.
Wind
48

Table 10. Cloudberry yield variations between bogs in 2008 and 2009.
Year Bog Fruit per plot (10m 2 ) Fruit size (gr) Yields (kg/hectare)
2008 Dry 187 a 0.99 a 91 ab
2008 Wet 114 b 0.84 b 48 bc
2009 Dry 60 b 0.74 c 26 c
2009 Wet 232 a 1.02 a 120 a
Means in columns followed by the same letter are not significantly different at p=0.05
There were also significant treatment effects on yields (table 11). The number of fruit produced
and thus also the yields in the “Snow” treatment were over twice that produced in the control plots
(respectively 118 vs 47 kg per hectare). While fruit size was somewhat greater in the “Delayed
Snow” treatment than in the other treatments, the number of fruit per plot and the yields did not
differ from that of the other treatments.
Table 11. The effects of snow fences and windbreaks on cloudberry yields.
Treatment Fruit per plot (10 m 2 ) Fruit size (gr) Yields (kg/hectare)
Control 100 b 0.86 b 47 b
Delayed Snow 125 ab 0.98 a 63 ab
Snow 249 a 0.88 b 118 a
Snow and Wind 142 ab 0.92 ab 68 ab
Wind 124 b 0.85 b 59 b
Means in columns followed by the same letter are not significantly different at p=0.05
49

Discussion
Both the winter of 2007-2008 and in particular that of 2008-2009 were snowy winters in the region
of Blanc-Sablon with sustained snow accumulation of over 20 cm from the end of January through
the month of April. Nonetheless, the addition of snow fence treatments applied in the fall as well
as those applied mid winter had significant moderating effects on soil temperatures throughout the
winter and into the summer season relative to control treatments. While we had expected the
“Delayed Snow” treatment to maintain cooler springtime soil temperatures this was not so at 10cm
below ground. However, the ground thawed much more slowly with this treatment than with the
two treatments where the snow fences were put up in the fall, thus soil temperature probes placed
deeper in the bog may have picked up on differences between these treatments that were missed at
10 cm.
Though the windbreak treatments had significant effects on wind speeds and air temperatures
during the flowering season, the rise in air temperatures were less than we had expected based on
data presented in the literature (Bottengård, 1980).
Snow trapping with snow fences put up in the fall and in particular those put up mid winter
effectively delayed flowering in both years of the experiment. However, the maximum delay in
flowering obtained with the “Delayed Snow” treatment was 8 days in 2008 and only 5 days in
2009. These differences were not much greater than the differences in flowering phenology
observed between the wet and the dry bog in 2008. The delay in flowering obtained with the
“Delayed Snow” treatment was not sufficient to protect flowering shoots from the late spring
frosts which occurred in the dry bog in 2009. Indeed, most of the fruit to develop in the dry bog in
2009 were from flowers flowering early in the season which were already developing fruit by the
time of the last spring frost. A delay in flowering might have exacerbated the problem of late
spring frosts as flowers are more vulnerable to freezes than are developing fruit. Thus while using
snow trapping to control flowering phenology as a means of dealing with late spring frosts may be
effective in some years, this was not the case in the two years of the present project. Being able to
control the water levels in the bog appears to be a better answer to spring frost control (Huikari,
1972). However, this requires more drastic and expensive interventions than does the use of snow
trapping.
As was seen in an earlier pilot project on the use of snow fences in cloudberry production (Naess,
2007), snow trapping led to an increase in the number of floral shoots while windbreaks put up
during the summer had no effect on flower numbers. In a similar experiment Aerts et al., (2004)
also found that increasing summer temperatures had no effect on floral shoot production in
cloudberry. While increased spring time temperatures in their experiment led to increased flower
numbers the same spring, this was not the case for increased snow. Their treatments however
were only 50 cm high with no porosity and were thus not entirely comparable to our treatments.
We had expected the positive effect of snow trapping on floral shoot production to be more
evident in the dry bog than in the wet bog; however the opposite was true. In the dry bog no
treatment effects on floral shoot numbers were observed while in the wet bog male and female
shoot numbers in snow fenced plots were respectively 2.8 and 1.5 fold those found in plots
without snow fencing. It would be of interest to identify the reasons underlying the observed
50

increase in floral shoots, whether they are due to a reduction in floral bud mortality or an increase
in the development of floral buds into mature flowers in the spring.
Inadequate numbers of insects were observed on cloudberry flowers to be able to detect direct
treatment effects on the activity of pollinating insects had there been any. The examination of
stigmatic pollen loads however did permit the detection of treatment effects on pollination. Pollen
loads were best in plots snow fenced during the winter. The effect of snow fences on flower
numbers, and in particular on the number of male flowers in the snow fenced plots, are probably
responsible for this effect though local increases in the winter survival of pollinating insects can
not be neglected as a possible reason. Despite the decreased wind strengths and increased
temperatures observed in plots protected by windbreaks during the summer, an increase in
pollination was not observed in these plots. The proportion of male flowers in these plots was low
(30-40 %) thus an increase in the numbers or activity of pollinating insects in these plots might go
un-noticed in pollen load studies. In 2008, pollen loads were significantly less in the “Delayed
Snow” treated plots than in all other plots. Flowering may have been delayed in these plots
beyond the time of maximum insect activity.
Neither fruitset nor seedset in tagged flowers were affected by the applied treatments. These
factors were correlated with pollen loads which in turn were correlated with the number of males
present in the plots on the tagging date.
Fruit ripening followed the same trend as flowering phenology with the “Delayed Snow” treatment
causing delayed fruit ripening in the wet bog. Fruit ripened was advanced in plots sheltered by
windbreaks during the summer. While fruit ripening date per se was not found to have an impact
on the development of floral winter buds, the development of these buds was more advanced in
plots sheltered by windbreaks during the summer than in the other plots. This might be expected to
lead to increased flower numbers in these plots in coming years, however no such effect of
windbreaks on flower numbers was observed during the two year project period.
The best cloudberry yields were obtained in plots with snow fences put up in the fall. An increase
in the number of floral shoots along with favourable pollination and fruit set conditions appear to
be responsible for these yield increases as opposed to frost avoidance (Mäkinen and Oikarinen,
1974). In order to best take advantage of this technique, potential cloudberry producers should put
the snow fences up in the fall in areas with good cloudberry potential and in bogs not susceptible
to late spring frosts.
51

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55

Acknowledgements
We would like to thank the following people for their good work without which the project could
not have been completed:
Marius Blais
Technicien Centre de recherche Les Buissons Coordination, Microscopy
Stephanié Devost
Laboratory Aide Centre de recherche Les Buissons Microscopy
Valérie Hébert-Gentile
Masters Student Université Laval Field work, Laboratory analyses
Marie-Claire Gervais
Technicien Centre de recherche Les Buissons Supervision, Field work
Charles Jones
Field Worker Centre de recherche Les Buissons Field work
Derek Lynch
Technicien Centre de recherche Les Buissons Microscopy
Gabrielle Mathon-Roy
Technicien Centre de recherche Les Buissons Supervision, Field work, Microscopy
Lorrie Pike
Field Worker Centre de recherche Les Buissons Field work
Finally, we wish to thank the organisations who have funded this project:
Le ministère de l'Agriculture, des Pêcheries et de l'Alimentation
Le ministère du Développement économique, de l'Innovation et de l'Exportation
La Conférence régionale des élus de la Côte-Nord
56

Annexe 1
Rencontre d’information à Blanc-Sablon
Quand : le mercredi 6 août 2008
Durée : de 8h30 à 17h00
Endroit : Bureau Municipale de Blanc-Sablon
Frais de déplacements et de séjours assumés par les participants
8h30 Présentation des participants
8h45 Présentation du projet Domestication par Kristine Naess du Centre de recherche
9h30 Présentation du projet Semi domestication, volet engrais biologique
par Valérie Hébert-Gentile étudiante en maîtrise sous la direction de Line Lapointe et
de Léon-Etienne Parent de l’université Laval et de Kristine Naess du Centre de
recherche
10h30 Pause café
10h45 Présentation du projet Semi domestication, volet brise-vent par Kristine Naess
11h30 Table ronde
12h00 Dîner
13h30 Visite des installations en tourbières
17h00 Fermeture de la rencontre
Prévoir 2 nuitées à Blanc-Sablon
Arrivée à Blanc-Sablon le 5 août en fin d’après-midi
Départ le 7 août tôt le matin
57

Liste de participants :
David Calderisi CLD de Blanc-Sablon
Alexandre Dumas Coasters Association
Réjean L. Dumas Directeur général Municipalité de Blanc-Sablon
Réginal Hancock Maire de Forteau, Labrador
Armand Joncas Maire de Blanc-Sablon
Bruce Moores Labrador Straits Development Corporation, Labrador
Roberto Stéa DEC, Sept Iles
Jane White Fruit Crop Development Officer, Terre-Neuve
58

Annexe 2
Date: jeudi le 19 novembre 2009
Colloque Bioalimentaire
Endroit: Baie-Comeau, Jardin des Glaciers
3 Denonville, dans le quartier St-Georges
Programmation
Côte-Nord 2009
8h15 Accueil des participants(es)
8h30 Mot d‟ouverture, Alain Côté, direction régionale du MAPAQ
8h45 à 11h30 Ateliers par secteur du bioalimentaire :
Un travail situé dans deux salles différentes
Agroalimentaire-secteur petits fruits
nordiques
Pêche et aquaculture
Mot de bienvenue du porte-parole du Conseil Mot de bienvenue du porte-parole du Conseil
Bilan annuel Enjeux et dossiers stratégiques
Enjeux et dossiers stratégiques Retour sur le plan d‟action 2009-2010
Retour sur le plan d‟action 2009-2010 Élections des membres au Conseil de l‟industrie des
Mot de bienvenue de l‟UPA Côte-Nord
Portrait de la production agricole
pêches
Avant-midi
Volet Agroalimentaire-secteur Petits fruits nordiques et production agricole
8h45
10h15
10h30
11h15
Mot du porte-parole du Conseil de l‟industrie des petits fruits nordiques
Bilan de la dernière année :
Portrait des récoltes et la situation du marché
Accès des terres publiques : dossier CRRNT et situation par territoire
UPA Côte-Nord : bilan des dossiers de la dernière année et besoins futurs, Ghislaine
Morin, présidente
Pause
Centre de recherche Les Buissons : présentation de l‟équipe recherche et résultats de travaux
menés sur le territoire
Plan d‟actions 2009-2010- Projet d‟une ressource-filière petits fruits nordiques
59

Après-midi
Volet Bioalimentaire
Les deux groupes sont réunis dans la même salle
11h30
Dossier-Appellation d’origine ou géographique, Rémy Lambert, vice-recteur à la recherche
de l‟université Laval
12h
Dîner-Conférence : marketing Six Continents Inc. ,Gilbert H. Aura, vice-président
13h30
Vitrine régionale des produits : logo ou autres initiatives
13h45 Mise en place de la Table bioalimentaire Côte-nord
Mandats de la Table bioalimentaire Côte-Nord
16h
Aspect corporatif et composition du conseil d,administration
Orientations et axes d‟interventions
Élection des postes vacants
Mot de fermeture du colloque régional
60