Interim report of the HELCOM CORESET project

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24 Existing monitoring data Information derived from national reports to HELCOM CORESET (note that not all countries have reported their monitoring) Table 2.8. Monitoring of marine mammal abundance. Country Area/Basin Species Method Noted parameters Germany Kiel Bay & Little Belt, Bay of Mecklenburg Germany Kiel Bay, Bay of Mecklenburg, Southern Baltic Proper Germany Bay of Mecklenburg & Pomeranian Bay, internal lagoons Germany Bay of Mecklenburg & Pomeranian Bay, internal lagoons subpopulation Phocoena phocoena western Baltic subpopulation Phocoena phocoena western Baltic line transect sampling n individuals, n pups POD (Porpoise detectors = self-contained submersible data logger for cetacean echolocation clicks) Harbour Seal observation of potential haul-out sites; collection of accidental sightings Grey Seal observation of actual and potential haul-out or resting sites; collection of accidental sightings See method n individuals n individuals Lithuania Southern Baltic proper n individuals? Sweden Baltic Proper, Gulf of Bothnia Finland Gulf of Bothnia, Kvarken, Åland Sea, Archipelago Sea, Gulf of Finland Grey seal Aerial, boat or land of grey seal haulouts Grey seal Aerial surveys of grey seal haulouts during the molting season in spring Finland Archipelago Sea Grey seal Aerial surveys of grey seal pupping islands during the breeding season in early spring Finland Archipelago Sea, Gulf of Bothnia Finland Gulf of Bothnia, and the Quark Sweden Gulf of Bothnia and the Quark Baltic ringed seal Aerial surveys of ringed seals during the molting season in spring Baltic ringed seal Aerial surveys of ringed seals during the molting season in spring Baltic ringed seal Aerial surveys of ringed seals during the molting season in spring n individuals n individuals n individuals, n pups n individuals n individuals n individuals Sweden Kalmarsund Baltic harbour seal Aerial surveys during moult n individuals Sweden Kalmarsund Baltic harbour seal Landbased pup counts in June and July n pups Sweden/ Denmark Southern Baltic and the Kattegat Harbour seal Aerial surveys during moult n individuals
Sampling Monitoring of marine mammal abundance require methods tailored for the different species. Whales and porpoises have usually been surveyed using ship based line transect methodology, where a certain proportion of the sea surface is covered during favourable weather conditions. Large-scale surveys such as SCANS have monitored the abundance of whales in the entire North Sea and adjacent waters (Hammond et al. 2002). This method is appropriate in areas where whale abundance is relatively high, but gives very wide confi dence limits in low abundance areas such as the Baltic. The cost in man hours is also very high which is why such surveys only have been repeated about once a decade. Alternative methods in low density areas include submerged hydrophonic devices that record sounds produced by whales. Such devices have been used in the Southern Baltic and an on-going project is deploying sonic equipment elsewhere in the Baltic. This method provides information on the distribution of porpoises but still needs to be evaluated for abundance estimates. Ringed seals are monitored annually in the Bothnian Bay using strip sensus methodology (Härkönen et al. 1998), where more than 13% of the sea ice is covered during peak moulting season in the end of April (20th of April to the 1 st of May) each year. Such surveys have been conducted since 1988 in the Bothnian Bay, whereas the southern populations in the Archipelago Sea, the Gulf of Finland and the Gulf of Riga and Estonian coastal waters only can be surveyed with this method when ice cover is permitting. Land based surveys of hauled out ringed seals provide complementary information from the Gulf of Finland. Harbour seals in the Kalmarsund, southern Baltic and the Kattegat are surveyed during the peak moulting season in the latter half of August each year. All seal sites are photographed and seals are later counted on the photos. All seal sites are surveyed three times each season, and the mean number hauled out in the two highest counts are used for abundance estimates and trend analyses (Teilmann et al. 2010). Surveys are coordinated between Sweden and Denmark. Grey seals are surveyed in a similar way as harbour seals, where all haul-out sites of seals are photographed and where seals are counted on the photos retrospectively. Surveys are conducted during peak haul-out season in the last week of May and the fi rst week of June. Flights are coordinated among teams from Estonia, Finland and Sweden. Methodology of data analyses All methods except for the sonic method used for harbour porpoises give data on relative abundance since some seals always are submerged. However, since the surveys are standardized, a similar proportion of the seals can be expected to haul out during surveys among years. Consequently, estimates of relative abundance can be used for trend analyses, and the growth rate of populations can be estimated with good precision (Teilmann et al. 2010). Using capture/recapture methodology photo-id studies or branded or tagged animals can be used to estimate total abundance. Sub populations are treated separately in the analyses where abundance and trend estimates are given for the following management units: – Ringed seal: The Bothnian Bay including the North Quark, the Archipelago Sea, the Gulf of Finland, Estonian coastal waters including the Gulf of Riga. – Harbour seal: Kalmarsund, the Southern Baltic, and the Kattegat. – Grey seal: The entire Baltic. 25
Page 1: Baltic Sea Environment Proceedings
Page 4 and 5: 2 Helsinki Commission Katajanokanla
Page 6 and 7: 4 4.16. Cumulative impact on benthi
Page 8 and 9: 6 descriptions of the indicators. T
Page 10 and 11: 8 The CORESET expert group on biodi
Page 12 and 13: 10 fi sh stocks and change in diet,
Page 14 and 15: 12 Figure 2.3. The prevalence of pr
Page 16 and 17: 14 Seasonal changes in blubber thic
Page 18 and 19: 16 Blubber thickness suggestions Bl
Page 20 and 21: 18 Weaknesses/gaps Monitoring of th
Page 22 and 23: 20 2.3. Population growth rate of m
Page 24 and 25: 22 Annual adult survival 1 0,95 0,9
Page 28 and 29: 26 References Bäcklin, B. M. 2011.
Page 30 and 31: 28 Reproduction in the Baltic eagle
Page 32 and 33: 30 Breeding success The proportion
Page 34 and 35: 32 of the real number of nestlings
Page 36 and 37: 34 Gaps and weaknesses Minimum dete
Page 38 and 39: 36 2.5. Abundance of wintering popu
Page 40 and 41: 38 Table 2.10. Pressures affecting
Page 42 and 43: 40 Refrences Skov et al. (2000) Bir
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Page 46 and 47: 44 Approach for defi ning GES All s
Page 48 and 49: 46 Sampling It is suggested to incl
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74 Considering the data set availab
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76 In Denmark, the highest contamin
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78 Status of a compound on internat
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80 A temporal analysis (EU-RAR 2006
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82 Pathways of PFOS to the Baltic e
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84 In regions less affected by anth
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86 3.4. Polychlorinated biphenyls a
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88 actions related to the environme
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90 The CORESET expert group decided
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92 pheric deposition pattern (lowes
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94 3.5. Polyaromatic hydrocarbons (
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96 GES boundaries and matrix Existi
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98 Quality Assurance of PAH metabol
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100 Ariese F, Burgers I, Oudhoff K,
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102 GES boundaries and matrices Exi
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104 3.7. Cesium-137 Authors: Jürge
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106 Figure 3.5. Average surface lev
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108 Temporal trends in concentratio
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110 Other important sources are glo
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112 Conceptual model of the sources
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114 3.8 Tributyltin (TBT) and the i
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116 GES boundaries and matrix Exist
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118 Monitoring the compound Status
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120 Recommendation TBT measurements
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122 3. Frogs have been shown to app
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124 not fi sh (Köhler et al. 2002;
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126 The use of different fi sh spec
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128 Kirchin, M.A. Moore, M.N. Dean,
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130 3.11. Fish Disease Index: Exter
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132 Confounding factors The multifa
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134 analyses ICES data from various
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136 An EAC is the threshold beyond
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138 3.12. Micronucleus test Authors
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140 main nuclei were not counted as
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142 ing national data sets. Note: t
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144 Baršienė J. Rybakovas A. 2006
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146 3.13 A. Reproductive disorders
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148 dead larvae can be induced by s
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150 Strand, J, Dahllöf, I. (2005).
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152 of contaminants in sediments wi
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154 Eriksson Wiklund, A-K., and Sun
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156 4. Candidate indicators for bio
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158 Zooplankton-phytoplankton bioma
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160 4.2. By-catch of marine mammals
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162 4.3. Impacts of anthropogenic u
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164 4.4. Fatty-acid composition of
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166 7. Use of the indicator in prev
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168 10. Spatial considerations Balt
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170 4.10. Large fi sh individuals f
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172 11. Temporal considerations Sam
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178 A proposal for an approach to a
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180 Technical data Metadata This is
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182 F igure 4.1. Map showing the cu
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184 4.17. Biomass of copepods 1. Wo
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186 4.19. Zooplankton species diver
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188 indirectly impacted by eutrophi
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190 Notes for the GES boundary The
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192 Step 3: Prepare a list of speci
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194 4.22. Phytoplankton diversity 1
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196 4. Policy relevance Nonylphenol
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198 among different studies/measure
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200 4.27. EROD/CYP1A induction The
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202 5.1. Summary of all supplementa
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204 Table 5.1. (continues) Suppleme
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206 5.5. Biopollution level index 1
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208 NIS for aquaculture purposes. O
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210 Balanus improvisus Baltic Katte
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212 Figure 5.3. The scheme for asse
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214 5.6. Organochlorine compounds G
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216 EU Directive 2008/105/ EC Daugh
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218 Table 5.4. Monitoring of HCB, H
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