Interim report of the HELCOM CORESET project

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38 Table 2.10. Pressures affecting the waterbird populations. Species (wintering population) Anthropogenic pressure Black-throated diver eutrophication, oil, by-catch Red-throated diver eutrophication, oil, by-catch Great crested grebe eutrophication, oil, by-catch Goosander eutrophication, oil, by-catch Red-breasted merganser eutrophication, oil, by-catch Razorbill eutrophication, oil, by-catch Common guillemot eutrophication, oil, by-catch Black guillemot eutrophication, oil, by-catch Velvet scoter eutrophication, oil, by-catch Common scoter eutrophication, oil, by-catch Long-tailed duck eutrophication, oil, by-catch Eider eutrophication, oil, by-catch Tufted duck eutrophication, by-catch Greater scaup eutrophication, by-catch Goldeneye eutrophication, by-catch Mute swan eutrophication Mallard eutrophication Coot eutrophication Because the pressures affecting the selected key seabirds in the winter populations are similar, it is possible to make an index indicator where assessment can be fi rst made on the species level and then functional groups are assessed separately. Finally, an integration of all the species can be made to describe abundance of all wintering seabirds. How this integration will be made is not yet clear. Because the species and functional groups may have different signifi cances in the ecosystem, weighting factors should be considered. They could be based on the conservation value of the Baltic population in the European context or the proportion of the species in the wintering seabird abundance. Approach for defi ning GES boundaries All the species or functional groups respond to anthropogenic pressures slightly differently, although the pressures behind the change are similar. Therefore the targets, which show the boundary of GES, must be set for each species separately. It is proposed that the GES boundaries are set on the basis of (1) time series data and (2) relation to other indicators (e.g. nutrients, chlorophyll, zoobenthos, plant abundance, fi sh stocks). The GES boundaries should be given separately for all the sub-basins of the Baltic Sea (see Figure). As defi ning GES for all of the sub-basins may take time, the fi rst step should be to defi ne GES for those subbasins which have highest abundance of seabirds in the winter. Time series data: it is obvious that there are gaps in the time series datasets of wintering seabirds. The available data sets should be used as far as possible, using also best estimates. Temporal trends should be checked, because they show changes in the environment. Available sources of information are Skov et al. (2000, 2007 and 2011). Relations to other indicators: When assessing GES of the Baltic Sea, there should not be any mismatch between GES of different indicators. For example, the nutrient concentration targets in the Baltic Sea have been agreed in the HELCOM BSAP. Therefore, the seabird GES boundaries should not be set on levels which cannot be reached when nutrient targets have been reached. In addition, competitive interactions between fi sh feeding birds and large fi sh affect the target setting. With the current long-term management plan of cod, the cod stocks will increase, which likely affects the food availability for birds. The GES boundaries for birds should not be set too high in such conditions.
The policy decisions under different frameworks have possibly confl icting objectives. The Favourable Conservation Status under the Birds Directive may be diffi cult to reach, if the environment changes to more oligotrophic direction. However, decrease of by-catch, oil pollution and hunting would allow higher bird populations and may mitigate this confl ict. Provisional GES boundaries: Until modeling studies have confi rmed possible GES boundaries for the selected bird species, it is proposed that provisional GES boundaries are used. The GES is tentatively defi ned as a 50% deviation from mean of the reference period of 1992-1993 (based on available temporal trends in Skov et al. 2011). Ultimately, the GES could be set by modelling the population size based on the GES for eutrophication related core indicators, because the abundance of seabirds depends on the trophic state of the ecosystem and the objective of decreasing the eutrophication will affect the seabird populations. Assessment units for the seabird indicators The abundance of wintering seabird populations differs among Baltic sub-basins. Therefore the indicator should be assessed per sub-basin. That means that also the targets must be set for each of the sub-basins. Figure 2.14. Sub-basin assessment units in the Baltic Sea (blue lines). Sampling and data analyses See Skov et al. 2007 and 2011 Gaps and weaknesses The indicator has currently a couple of weaknesses which must be addressed in near future: – not all wintering grounds are covered, – monitoring methods differ between the offshore monitoring and national monitoring practices, – GES boundary is tentative, because of the uncertainty of interlinkages with other GES boundaries. 39
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 26 and 27: 24 Existing monitoring data Informa
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 42 and 43: 40 Refrences Skov et al. (2000) Bir
Page 44 and 45: 42 termined by application of the 7
Page 46 and 47: 44 Approach for defi ning GES All s
Page 48 and 49: 46 Sampling It is suggested to incl
Page 50 and 51: 48 2.7. Fish population abundance 2
Page 52 and 53: 50 Coastal Fish - Community Abundan
Page 54 and 55: 52 When a reference data set cannot
Page 56 and 57: 54 well, but were not included in t
Page 58 and 59: 56 Weighting For Nordic Costal mult
Page 60 and 61: 58 12. Current monitoring Monitored
Page 62 and 63: 60 Błeńska M., Osowiecki A., Kra
Page 64 and 65: 62 10. Spatial considerations Fucus
Page 66 and 67: 64 2.15. Trend in the arrival of ne
Page 68 and 69: 66 jectives is to reach “No intro
Page 70 and 71: 68 Sweden Figure 2.23 shows the rat
Page 72 and 73: 70 Strengths and weaknesses of data
Page 74 and 75: 72 need to be revisited in light of
Page 76 and 77: 74 Considering the data set availab
Page 78 and 79: 76 In Denmark, the highest contamin
Page 80 and 81: 78 Status of a compound on internat
Page 82 and 83: 80 A temporal analysis (EU-RAR 2006
Page 84 and 85: 82 Pathways of PFOS to the Baltic e
Page 86 and 87: 84 In regions less affected by anth
Page 88 and 89: 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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