Interim report of the HELCOM CORESET project

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140 main nuclei were not counted as MN. The area to be scored should fi rst be examined under low magnifi cation to select the part of the slide showing the highest quality (good staining, non overlapping cells). Scoring of MN should then be undertaken at 1000x magnifi cation. Confounding factors Earlier studies on MN formation in mussels have disclosed a signifi cant infl uence of environmental and physiological factors (Dixon et al. 2002). Therefore, the role of the confounding factors should be considered prior to the application of MN assay in biomonitoring programs, as well as in description of genetic risk zones, or ecosystem health assessments. Water temperature. MN induction is a cell cycle-related process and depends on water temperature, which is a confounding factor for the mitotic activity in poikilotherm animals. Several studies have demonstrated that baseline frequencies of MN in mussels are related to water temperature (Brunetti et al. 1988, 1992; Kopecka et al. 2006). Baseline frequencies of MN are regarded as the incidence of MN observed in the absence of environmental risk or before exposure to genotoxins (Fenech 1993). In fi sh MN frequencies showed also seasonal differences in relation to water temperature with lower MN levels in winter than in autumn (Rybakovas et al. 2009). This was assumed to be an effect of higher mitotic activity and MN formation due to high water temperatures in the autumn (Brunetti et al. 1988). Additionally, it has been reported that increases in water temperature (4 - 37ºC) can increase the ability of genotoxic compounds to damage DNA (Buschini et al. 2003). Cell type. MN may be seen in any type of cell, both somatic and germinal and thus the micronucleus test can be carried out in any active tissue. Nevertheless there are some limitations using different types of cells, for example, agranular and granular haemocytes in mussels. There are also differences between MN induction level in mussel haemolymph and gill cells, mainly because gills are primary targets for the action of contaminants. The anatomical architecture of the spleen in fi sh does not allow erythrocytes removal in the spleen (Udroiu et al. 2006), though, in mammals this process go. Salinity. The infl uence of salinity on the formation of MN was observed in mussels from the Danish coast located in the transitional zone between the Baltic and North Sea. No relationship between salinity and MN frequencies in mussels could be found for mussels from the Wismar Bay and Lithuanian coast. Similar results were found for Macoma balthica from the Baltic Sea in the Gulfs of Bothnia, Finland, Riga and in the Lithuanian EEZ (Baršienė et al., unpublished data). Individual size. Since the linear regression analysis of animal’s length and induction of MN shows that the size could be a confounding factor, sampling of organisms with similar sizes should take place (Baršienė et al., unpublished data). It should also be noted that size is not always indicative of age and therefore age could also potentially affect the response of genotoxicity in the fi sh. Diet. Results have shown that MN formation was not infl uenced in mussels who were maintained under simple laboratory conditions without feeding (Baršienė et al. 2006d). Ecological relevance Markers of genotoxic effects refl ect damage to genetic material of organisms and thus get a lot of attention (Moore et al. 2004). Different methods have been developed for the detection of both double- and single-strand breaks of DNA, DNA-adducts, MN formation and chromosome aberrations. The assessment of chemical induced genetic damage has been widely utilized to predict the genotoxic, mutagenic and carcinogenic potency of a range of substances, however these investigations have mainly been restricted to humans or mammals (Siu et al. 2004). MN formation indicates chromosomal breaks, known to result in teratogenesis (effects on offspring) in mammals. There is however limited knowledge of relationships
etween MN formation and effects on offspring in aquatic organisms. With a growing concern over the presence of genotoxins in the aquatic media, the application of cytogenetic assays on ecologically relevant species offers the chance to perform early tests on health in relation to exposure to contaminants. Quality Assurance The MN test showed to be a useful in vivo assay for genotoxicity testing. However, many aspects of its protocol need to be refi ned, knowledge of confounding factors should be improved and inter-species differences need further investigation. In 2009 an inter-laboratory comparison exercise was organised within the framework of the MED POL programme using the mussel M. galloprovincialis as test species. The results are expected by mid 2011. Intercalibration of MN analysis in fi sh was done between experts from NRC and Caspian Akvamiljo laboratories, as well as between NRC experts and the University of Aveiro, Portugal (Santos et al. 2010). It is recommended that these relatively simple interlaboratory collaborations are expanded to include material from all the commonly used indicator species in 2011/12. Assessment Criteria Baseline or background frequency of MN can be defi ned as incidence of MN observed in the absence of environmental risk or before exposure to genotoxins (Fenech, 1993). In fi sh, MN frequencies lower than 0.05‰ has been suggested by Rybakovas et al. (2009) as a reference level in the peripheral blood erythrocytes of the fl atfi sh fl ounder (Platichthys fl esus) and dab (Limanda limanda) and also cod (Gadus morhua) after analyzing 479 specimens from 12 offshore sites in the Baltic Sea. The frequencies of MN in marine species sampled from the Baltic Sea reference sites are summarized in Table 3.21. Table 3.21. The reference levels of micronuclei (MN/1000 cells) in Baltic Sea species in situ. Species Tissue Response MN/1000 cells Reference Mytilus edulis Gills 0.37 ± 0.09 Baršienė et al. 2006b Mytilus trossulus Gills 2.07 ± 0.32 Baršienė et al. 2006b; Kopecka et al. 2006 Macoma baltica Gills 0.53 - 1.28 Baršienė et al. 2008b, unpublished data (NRC, Lithuania) Platichthys fl esus Blood erythrocytes 0.15 ± 0.03 Baršienė et al. 2004 Platichthys fl esus Blood erythrocytes 0.0 ± 0.0 Kohler, Ellesat, 2008 Platichthys fl esus Blood erythrocytes 0.08 ± 0.02 Napierska et al. 2009 Zoarces viviparus Blood erythrocytes 0.02 ± 0.02 Baršienė et al. unpublished data (NRC, Lithuania) Gadus morhua Blood, kidney erythrocytes 0.03 ± 0.02 Rybakovas et al. 2009 Clupea harengus Blood erythrocytes 0.03 ± 0.03 Baršienė et al. unpublished data (NRC, Lithuania) Scophthalmus maximus Blood erythrocytes 0.10 ± 0.04 Baršienė et al. unpublished data (NRC, Lithuania) Perca fl uviatilis Blood erythrocytes 0.06 ± 0.02 Baršienė et al. 2005a; Baršienė et al. unpublished data (NRC, Lithuania) Assessment Criteria (AC) have been established by using data available from studies of molluscs and fi sh in the Baltic Sea (NRC database). The background/threshold level of MN incidences is calculated as the empirical 90% percentile (P90). Until more data becomes available, values should be interpreted from exist- 141
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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
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
Page 102 and 103: 100 Ariese F, Burgers I, Oudhoff K,
Page 104 and 105: 102 GES boundaries and matrices Exi
Page 106 and 107: 104 3.7. Cesium-137 Authors: Jürge
Page 108 and 109: 106 Figure 3.5. Average surface lev
Page 110 and 111: 108 Temporal trends in concentratio
Page 112 and 113: 110 Other important sources are glo
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 132 and 133: 130 3.11. Fish Disease Index: Exter
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
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
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
Page 188 and 189: 186 4.19. Zooplankton species diver
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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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