Interim report of the HELCOM CORESET project

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200 4.27. EROD/CYP1A induction The candidate indicator for measuring the Ethoxyresorufi n-O-deethylase (EROD) activity is developed by the BONUS+ project BEAST (particularly Henryka Dabrowska). This report lacks a proper documentation for the indicator, but information provided by the BEAST project has been compiled. Table 4.7. Overview of the use, monitoring, cause-effect relationships, assessment criteria and available guidance. Country codes: DK-Denmark, EE-Estonia, FI-Finland, DE-Germany, LV-Latvia, LT-Lithuania, PL-Poland, RU-Russia, SE-Sweden. Used by OSPAR, CEMP or pre-CEMP or MEDPOL 1) Used in national monitoring programmes in Baltic Sea countries 2) Research monitoring data available pre-CEMP 1) DK, SE, 2) PL, FI, Pl, EE Studied in large Baltic Sea research projects BEEP BEAST Biological Indication (BI) Cause/ effect (C/E) relationship BI – to Ahreceptor active chemicals such as PAH, planar PCB, and dioxins Availability of AC specifi c for the Baltic Sea (for detailes see Table 2 BAC, under development (BEAST) EAC –not yet available Monitoring Guidelines, other important info Method costs (High-Medium- Low) ICES TIMES 13 and 23 QA-YES Low costs Abbreviations – BAC – Background Assessment Criteria – EAC – Environmental Assessment Criteria (concentrations above which there is concern that negative effects might be observed in marine organisms. EAC describes the direct linkage to adverse health effects of the individuals) – AC – Numerical Assessment Criteria – QA – Quality Assurance measures – CEMP – guidelines, quality assurance and assessment tools are in place - monitoring of the component is mandatory for OSPAR contracting parties – pre-CEMP – agreed to be included as components of the CEMP, guidelines, QA tools and/or assessment tools are currently not all in place. Monitoring of the components is voluntary Table 4.8. Numerical Assessment Criteria (AC) for Baltic Sea organisms to assess biological effects. Values for Background Assessment Criteria (BAC) and Environmental Assessment Criteria (EAC) are given where available or relevant. Full details of AC and how they have been derived can be found in the ICES SGIMC 2010, SGIMC 2011 and WKIMC 2009 reports on the ICES website and in the SGEH Background Documents for the individual biological effects methods. NOTE: All missing information will soon be available from the output of the ongoing projects mentioned. Biological effect method (unit, other information) Ethoxyresorufi n-O-deethylase activity (EROD) [pmol/min/mg protein] pmol/min/ mg S9 protein *pmol/min/ mg microsomal protein Target species/ tissue/endpoint BAC EAC Flounder (male) 24 not yet available Eelpout 10 (Belt Sea data) not yet available Herring under development BEAST not yet available
5. Supplementary indicators for environmental assessments The HELCOM CORESET project identifi ed a number of supplementary indicators, which were not included in the core set, because they either did not fulfi l the HELCOM principles for core indicators or they were considered as redundant. Some supplementary indicators can fulfi l some of the strict requirements of the core indicators, including the requirement for a quantitative GES boundary, while others can be more descriptive indicators, for example, describing temporal development of parameters that are not linked or weakly linked to anthropogenic pressures. Nevertheless, the supplementary indicators provide valuable information for environmental assessments. Their role is to support the core indicators and provide information of causative factors behind status assessments. 201
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Baltic Sea Environment Proceedings
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2 Helsinki Commission Katajanokanla
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4 4.16. Cumulative impact on benthi
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6 descriptions of the indicators. T
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8 The CORESET expert group on biodi
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10 fi sh stocks and change in diet,
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12 Figure 2.3. The prevalence of pr
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14 Seasonal changes in blubber thic
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16 Blubber thickness suggestions Bl
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18 Weaknesses/gaps Monitoring of th
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20 2.3. Population growth rate of m
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22 Annual adult survival 1 0,95 0,9
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24 Existing monitoring data Informa
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26 References Bäcklin, B. M. 2011.
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28 Reproduction in the Baltic eagle
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30 Breeding success The proportion
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32 of the real number of nestlings
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34 Gaps and weaknesses Minimum dete
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36 2.5. Abundance of wintering popu
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38 Table 2.10. Pressures affecting
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40 Refrences Skov et al. (2000) Bir
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42 termined by application of the 7
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44 Approach for defi ning GES All s
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46 Sampling It is suggested to incl
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48 2.7. Fish population abundance 2
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50 Coastal Fish - Community Abundan
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52 When a reference data set cannot
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54 well, but were not included in t
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56 Weighting For Nordic Costal mult
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58 12. Current monitoring Monitored
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60 Błeńska M., Osowiecki A., Kra
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62 10. Spatial considerations Fucus
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64 2.15. Trend in the arrival of ne
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66 jectives is to reach “No intro
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68 Sweden Figure 2.23 shows the rat
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70 Strengths and weaknesses of data
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72 need to be revisited in light of
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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
Page 152 and 153: 150 Strand, J, Dahllöf, I. (2005).
Page 154 and 155: 152 of contaminants in sediments wi
Page 156 and 157: 154 Eriksson Wiklund, A-K., and Sun
Page 158 and 159: 156 4. Candidate indicators for bio
Page 160 and 161: 158 Zooplankton-phytoplankton bioma
Page 162 and 163: 160 4.2. By-catch of marine mammals
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Page 166 and 167: 164 4.4. Fatty-acid composition of
Page 168 and 169: 166 7. Use of the indicator in prev
Page 170 and 171: 168 10. Spatial considerations Balt
Page 172 and 173: 170 4.10. Large fi sh individuals f
Page 174 and 175: 172 11. Temporal considerations Sam
Page 180 and 181: 178 A proposal for an approach to a
Page 182 and 183: 180 Technical data Metadata This is
Page 184 and 185: 182 F igure 4.1. Map showing the cu
Page 186 and 187: 184 4.17. Biomass of copepods 1. Wo
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Page 192 and 193: 190 Notes for the GES boundary The
Page 194 and 195: 192 Step 3: Prepare a list of speci
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Page 198 and 199: 196 4. Policy relevance Nonylphenol
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Page 204 and 205: 202 5.1. Summary of all supplementa
Page 206 and 207: 204 Table 5.1. (continues) Suppleme
Page 208 and 209: 206 5.5. Biopollution level index 1
Page 210 and 211: 208 NIS for aquaculture purposes. O
Page 212 and 213: 210 Balanus improvisus Baltic Katte
Page 214 and 215: 212 Figure 5.3. The scheme for asse
Page 216 and 217: 214 5.6. Organochlorine compounds G
Page 218 and 219: 216 EU Directive 2008/105/ EC Daugh
Page 220 and 221: 218 Table 5.4. Monitoring of HCB, H
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