Interim report of the HELCOM CORESET project

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32 of the real number of nestlings by 11% (Hauff & Wölfel 2002). Using this correction factor for the nests not climbed (about 50% of the total German sample), the corrected brood size for Mecklenburg-Western Pomerania is 1.56, which is still clearly on the low side compared to most coastal records from Sweden (Figures 2.11 and 2.12). Figure 2.12. Mean nestling brood size 1996-2004 on the Swedish Baltic coastline (15 km zone), counties indicated by letters, and in Mecklenburg-Western Pomerania, (German data corrected for nests checked from the ground). Sample sizes given in brackets. The reference level up to 1950 based on data from the Swedish coast was 1.84, with 95% confi dence limits 1.64 - 2.04. Factors affecting the white-tailed sea eagle reproductive success Organic contaminants Abundance, distribution and condition of the white-tailed sea eagle population Productivity Nestling brood size Breeding success Food availability Availability of territories (e.g. nest sites) Nest disturbance Persecution Figure 2.13. The productivity of the white-tailed sea eagle is affected by several anthropogenic pressures acting through the nestling brood size (number of nestlings) and the breeding success (success in raising one nestling per pair).
Monitoring In Sweden, surveys of breeding populations and reproduction, sampling, sample preparation, storage in specimen bank and evaluation of results are carried out by the Department of Contaminant Research at the Swedish Museum of Natural History, Stockholm. Surveys of breeding populations and reproduction of reference freshwater populations are carried out by the Swedish Society for Nature Conservation (Project Sea Eagle), Stockholm. Chemical Analysis is carried out at the Institute of Applied Environmental Research at Stockholm University. In Western Pomerania, Germany, data are collected by voluntary ornithologists, co-ordinated by the “Project group for large bird species” under the auspices of the Agency for Environment, Nature Conservation and Geology. The country-wide white-tailed sea eagle data are compiled by Peter Hauff, who submits the annual reports to the mentioned governmental agency. Eagles are presently breeding along the coasts of the whole Baltic Sea, and are monitored in a network of national projects with harmonized methodology. Monitoring of nests is done in all coastal areas of the Baltic Sea with circa 300 nests in Sweden, 300 in Finland and 230 in Germany. There are no large gaps in the monitoring, but the compilation of data has not been done yet, except from Finland, Germany and Sweden. Monitoring of sea eagle reproduction in Sweden is included in the National Environment Monitoring Programme since 1989 as indicator of effects from chemical pollutants. In Finland, the monitoring is done by WWF working group. The fi rst years of the data sets are as follows: in Sweden 1964, in Germany 1973, in Finland 1970. Method and frequency of data collection As nests are climbed for assessment of the reproductive parameters, nestlings are also measured (wing chord for estimation of age in days, tarsus width and depth for estimation of sex, see Helander 1981, Helander et al. 2007), and weighed (for nutritional status), sampled (feather and blood), and ringed within an international colour ringing programme, for identifi cations in the fi eld (Helander 2003b). Dead eggs and shell pieces are collected for measurements, investigation of contents and chemical analyses, for studies on relationships with reproduction. Also shed feathers from adults are collected at all sites and archived. These materials are used in the assessment of other parameters/indicators. Brood size records from nests inspected only from the ground in Germany were corrected by multiplying by a factor 1.11 (Hauff & Wölfel 2002). Methodology of data analyses Simple log-linear regression analysis has been carried out to investigate average changes over time. To check for signifi cant nonlinear trend components, a LOESS smoother was applied and an analysis of variance was used to check whether the smoother explained signifi cantly more than the regression line. Statistical power analyses were used to estimate the minimum annual trend likely to be detected at a statistical power of 80% during a monitoring period of 10 years. To investigate the possible effect of a future reduced sampling scheme, repeated random sampling (5000 times) from 1991 to 2006 in the current database was carried out, simulating a maximum of 50, 25, 20, 15, and 10 records each year. Contingency analysis, using the G-test with Williams correction, a log-likelihood ratio test, was applied for comparisons between geographical regions and time periods. For references see (Helander et al. 2008). 33
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 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
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
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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
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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
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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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