Interim report of the HELCOM CORESET project

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130 3.11. Fish Disease Index: Externally visible fi sh diseases, macroscopic liver neoplasms and liver histopathology Authors: Thomas Lang, Doris Schiedek & Kari Lehtonen ICES SGEH Biological Effects methods Background Documents for the Baltic Sea region (ICES/OSPAR document from the ICES SGIMC Report 2011, complemented and modifi ed by SGEH 2011 with information relevant for application in the Baltic Sea region) Description of the indicator Diseases of wild marine fi sh have been studied on a regular basis by many ICES Member Countries for more than two decades. Disease surveys are often integrated with other types of biological and chemical investigations as part of national monitoring programmes aiming at an assessment of the health of the marine environment, in particular in relation to the impact of human activities (Lang 2002). On an international level, fi sh disease data have been used for environmental assessments in the framework of the North Sea Task Force and its Quality Status Report (North Sea Task Force 1993), the OSPAR Quality Status Reports 2000 and 2010 (OSPAR Commission 2000, 2010a) and in the 3rd and 4th HELCOM assessments (HELCOM 1996, 2002). Studies on externally visible diseases, macroscopic liver neoplasms and liver histopathology are on the list of techniques for general and contaminant-specifi c biological effects monitoring as part of the OSPAR pre-CEMP (OSPAR 2010b). In the Baltic Sea, fi sh diseases have been monitored on a more or less regular basis since the beginning of the 1980s (Lang 2002). Baltic Sea countries currently carrying out fi sh disease surveys in the Baltic Sea on an annual basis are Germany (vTI Institute of Fisheries Ecology, Cuxhaven), Poland (Sea Fisheries Institute, Gdynia) and Russia (AtlantNIRO, Kaliningrad) (ICES 2011). While Polish and Russian studies are restricted to national EEZs, the German programme covers larger areas of the southern Baltic Sea, including sampling sites in ICES Subdivision 22, 24, 25 and 26. Other Baltic Sea countries not mentioned have some experience in fi sh disease monitoring from studies carried out in the 1980s and 1990s, but have stopped regular activities. Most of the regular disease surveys are so far focussed on fi sh species sampled in offshore areas, with the main target species fl ounder (Platichthys fl esus), cod (Gadus morhua) and, to a lesser extent, herring (Clupea harengus). In the western Baltic Sea, the common dab (Limanda limanda) is another target species. Other common species have been examined on a more irregular basis. A wide and species-dependent range of diseases (incl. some parasite species) is being monitored, with an emphasis on externally visible lesions and parasites. Only in fl ounder have regular studies on liver pathology (largely related to neoplastic lesions) been included partly (Lang et al. 2006). The methodologies applied largely follow ICES guidelines (Bucke et al. 1996, Feist et al. 2004) which can easily be adapted for other species relevant for fi sh monitoring in the Baltic Sea. Methodologies and diagnostic criteria involved in the monitoring of contaminantspecifi c liver neoplasms and liver histopathology have largely been developed based on studies with fl atfi sh species, in Europe mainly dab and fl ounder, but can also be adapted to other fl atfi sh species (e.g. plaice (Pleuronectes platessa) and also to bottom-dwelling roundfi sh species, such as viviparous blenny (Zoarces viviparus). New disease trends in Baltic Sea fi sh species have been reviewed regularly by the ICES Working Group on Pathology and Diseases of Marine Organisms (WGPDMO) and relevant information has partly been incorporated in the HELCOM Periodic Assessments (HELCOM 1996, 2002). However, compared to the North Sea, fi sh disease monitoring and assessment in the Baltic Sea is less developed and, so far, only few fi sh disease data from the Baltic Sea have been submitted to the ICES Environmental Databank. In the light of present developments in ICES and in HELCOM, the ICES WGPDMO recommended at its 2007 meeting that
Baltic Sea countries running fi sh disease monitoring programmes in the Baltic Sea make attempts to submit their disease data to the ICES Environmental Databank in order to make them available for integrated assessments, such as those carried out by the ICES/HELCOM Working Group on Integrated Assessment of the Baltic Sea (WGIAB) and as part of the periodic HELCOM assessments (ICES 2007). In 2005, the ICES Workshop on Fish Disease Monitoring in the Baltic Sea (WKFDM) started to develop an integrative tool for the analysis and assessment of the health status of fi sh which was later termed ‘Fish Disease Index (FDI)’ (ICES 2006a,b). In contrast to previous attempts, largely focusing on the analysis and assessment of changes in prevalence of single diseases, the FDI approach was developed with the primary aim to analyse and assess changes in spatial and temporal patterns in the overall disease status of fi sh, by summarising information on the prevalence of a variety of common diseases affecting the fi sh species as well as their severity grades and effects on the host into a robust numerical value calculated for individual fi sh and, as mean values, for representative samples from a population. The common dab (Limanda limanda) from the North Sea was selected as a model species for the construction of the FDI approach because most existing data are from fi sh disease surveys with the dab as primary target species. However, the FDI approach is constructed in a way that it can easily be adapted to other fi sh species for which disease data are available. The development of an analogous FDI approach for Baltic Sea fi sh species is on the agenda of the ICES Working Group on Pathology and Diseases of Marine Organisms (WGPDMO) and will be fi nalised during 2011 (ICES 2011). In fi rst instance, the efforts will focus on fl ounder and cod, species for which most data are available from national fi sh disease monitoring in the Baltic Sea. Fish disease surveys and associated FDI data analyses and assessments according to the OSPAR and ICES requirements address four categories of diseases. These categories also are the basis for fi sh disease monitoring/assessment in the Baltic Sea (see Table 3.20). Other target species and diseases may be added when more experience and data are available. Table 3.20. Categories and diseases/lesions for disease monitoring and assessment with Baltic Sea fi sh species (ICES 2011; modifi ed) Disease Category Externally visible diseases Macroscopic liver neoplasms Non-specifi c liver histopathology Contaminant-specifi c liver histopathology Diseases/Lesions Flounder (P. fl esus) Cod (G. morhua) Lymphocystis Acute/healing skin ulcerations Acute/healing fi n rot/erosion Epidermal hyperplasia/ papilloma Cryptocotyle sp. Lepeophtheirus pectoralis Benign and malignant liver tumours > 2 mm in diameter Non-specifi c degenerative/regenerative change Infl ammatory lesions Parasites Early toxicopathic non-neoplastic lesions Foci of cellular alteration Benign neoplasms Malignant neoplasms Acute/healing skin ulcerations Acute/healing fi n rot/erosion Skeletal deformities Pseudobranchial swelling Epidermal hyperplasia/papilloma Cryptocotyle lingua Lernaeocera branchialis Benign and malignant liver tumours > 2 mm in diameter Non-specifi c degenerative/regenerative change Infl ammatory lesions Parasites Early toxicopathic non-neoplastic lesions Foci of cellular alteration Benign neoplasms Malignant neoplasms 131
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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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Page 90 and 91: 88 actions related to the environme
Page 92 and 93: 90 The CORESET expert group decided
Page 94 and 95: 92 pheric deposition pattern (lowes
Page 96 and 97: 94 3.5. Polyaromatic hydrocarbons (
Page 98 and 99: 96 GES boundaries and matrix Existi
Page 100 and 101: 98 Quality Assurance of PAH metabol
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Page 106 and 107: 104 3.7. Cesium-137 Authors: Jürge
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Page 114 and 115: 112 Conceptual model of the sources
Page 116 and 117: 114 3.8 Tributyltin (TBT) and the i
Page 118 and 119: 116 GES boundaries and matrix Exist
Page 120 and 121: 118 Monitoring the compound Status
Page 122 and 123: 120 Recommendation TBT measurements
Page 124 and 125: 122 3. Frogs have been shown to app
Page 126 and 127: 124 not fi sh (Köhler et al. 2002;
Page 128 and 129: 126 The use of different fi sh spec
Page 130 and 131: 128 Kirchin, M.A. Moore, M.N. Dean,
Page 134 and 135: 132 Confounding factors The multifa
Page 136 and 137: 134 analyses ICES data from various
Page 138 and 139: 136 An EAC is the threshold beyond
Page 140 and 141: 138 3.12. Micronucleus test Authors
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Page 144 and 145: 142 ing national data sets. Note: t
Page 146 and 147: 144 Baršienė J. Rybakovas A. 2006
Page 148 and 149: 146 3.13 A. Reproductive disorders
Page 150 and 151: 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
Page 164 and 165: 162 4.3. Impacts of anthropogenic u
Page 166 and 167: 164 4.4. Fatty-acid composition of
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Page 172 and 173: 170 4.10. Large fi sh individuals f
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Page 180 and 181: 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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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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