Ecological scenarios for prospective risk assessment of aquatic ecosystems

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1 Ecological scenarios for prospective risk assessment of aquatic ecosystems Sanne van den Berg, Andreas Focks, Hans Baveco, Antonio Franco, Frederik de Laender and Paul van den Brink

2 Status quo How to increase realism? Ecological scenarios Sensitive species Model ecosystem

3 Beware of surrealism

4 Research aim Develop realistic ecological scenarios for higher tier risk assessment of aquatic ecosystems which consider the most vulnerable species

5 Work-flow Toxic mode of action Toxicity Mode Specific Sensitivity Traits Phylogenetics Predictive models Community composition Predict sensitivity

6 Work-flow Toxic mode of action

7 Frequency Frequency Why toxic Mode Of Action? Key determinant of sensitivity Interspecies variation Internal concentration Esher and Hermens 2002

8 Work-flow MOAtox Toxic mode of action Barron et. al. 2015

9 Work-flow MOAtox Toxic mode of action Toxicity ECOTOX U.S. Environmental Protection Agency (US EPA) 2017

10 Work-flow MOAtox Toxic mode of action Toxicity ECOTOX Mode Specific Sensitivity U.S. Environmental Protection Agency (US EPA) 2017

11 Calculate Mode Specific Sensitivity (MSS) Per chemical: Calculate Relative Sensitivity (RS) Over all chemicals: MSS = Average RS Nr. of species tested per chemical Rubach et. al. 2010

12 Order Results Mode Specific Sensitivity Tylenchida Mysida Harpacticoida Heterotrichida Plecoptera Trichoptera Ephemeroptera Hymenostomatida Anostraca Odonata Diplostraca Calanoida Amphipoda Lumbriculida Podocopida Neoophora Cyclopoida Decapoda Sarcoptiformes Isopoda Diptera Anthoathecatae Bdelloidea Gastropoda Hemiptera Ploima Megaloptera Coleoptera Arhynchobdellida Oligochaeta Tubificida Unionoida Hypotrichida Veneroida Trombidiformes Rhynchobdellida Araneae Rhabditida MSS

13 Order Results Mode Specific Sensitivity Tylenchida Mysida Harpacticoida Heterotrichida Plecoptera Trichoptera Ephemeroptera Hymenostomatida Anostraca Odonata Diplostraca Calanoida Amphipoda Lumbriculida Podocopida Neoophora Cyclopoida Decapoda Sarcoptiformes Isopoda Diptera Anthoathecatae Bdelloidea Gastropoda Hemiptera Ploima Megaloptera Coleoptera Arhynchobdellida Oligochaeta Tubificida Unionoida Hypotrichida Veneroida Trombidiformes Rhynchobdellida Araneae Rhabditida MSS

14 Order Results Mode Specific Sensitivity Tylenchida Mysida Harpacticoida Heterotrichida Plecoptera Trichoptera Ephemeroptera Hymenostomatida Anostraca Odonata Diplostraca Calanoida Amphipoda Lumbriculida Podocopida Neoophora Cyclopoida Decapoda Sarcoptiformes Isopoda Diptera Anthoathecatae Bdelloidea Gastropoda Hemiptera Ploima Megaloptera Coleoptera Arhynchobdellida Oligochaeta Tubificida Unionoida Hypotrichida Veneroida Trombidiformes Rhynchobdellida Araneae Rhabditida MSS

15 Work-flow MOAtox Toxic mode of action Toxicity ECOTOX Mode Specific Sensitivity

16 Work-flow MOAtox Toxic mode of action Toxicity ECOTOX Mode Specific Sensitivity Predictive models

17 Work-flow MOAtox Toxic mode of action Toxicity ECOTOX Mode Specific Sensitivity Traits Predictive models

18 Why traits? Wiberg-Larsen et. al. 2016

19 Work-flow MOAtox Toxic mode of action Toxicity ECOTOX Mode Specific Sensitivity Tachet Traits Predictive models Tachet et. al. 2000

20 How did we build the model? Factorial traits: 1 st axis PCA 118 predictors (22 traits) Continuous traits: Fraction notation Remove correlated traits 22 predictors Select on significance 13 predictors 2 predictors

21 Results Predictive models MSS = * Feeding habits * Biogeographic regions (R 2 = 0.240, p < 0.001)

22 Work-flow MOAtox Toxic mode of action Toxicity ECOTOX Mode Specific Sensitivity Tachet Traits Predictive models

23 Work-flow MOAtox Toxic mode of action Toxicity ECOTOX Mode Specific Sensitivity Tachet Traits Phylogenetics Predictive models

24 Why phyologenetics? Larras et. al. 2014

25 Work-flow MOAtox Toxic mode of action Toxicity ECOTOX Mode Specific Sensitivity Tachet Traits Phylogenetics GenBank Predictive models National Centre for Biotechnology Information (NCBI) 2017

26 Results Phylogenetics Selection of null species Distance

27 Work-flow MOAtox Toxic mode of action Toxicity ECOTOX Mode Specific Sensitivity Tachet Traits Phylogenetics NCBI Predictive models

28 Work-flow MOAtox Toxic mode of action Toxicity ECOTOX Mode Specific Sensitivity Tachet Traits Phylogenetics NCBI Predictive models Predict sensitivity

29 Work-flow MOAtox Toxic mode of action Toxicity ECOTOX Mode Specific Sensitivity Tachet Traits Phylogenetics NCBI Predictive models Community composition WFD ecoregions Predict sensitivity European Environmental Agency (EEA) 2004

30 WFD ecoregions European Environmental Agency (EEA) 2004

31 Results WFD ecoregions

32 Conclusions We are able to Rank species according to their sensitivity Predict the sensitivity of untested species Identify most sensitive regions or river types Use ecological scenarios as a basis for ecosystem modelling!

33 Ecological scenarios for aquatic risk assessment!

34 References Esher and Hermens 2002, Modes of action in ecotoxicology: their role in body burdens, species sensitivity, QSARs, and mixture effects. Environmental Science and Technology 36, Barron et. al. 2015, MOAtox: A comprehensive mode of action and acute aquatic toxicity database for predictive model development. Aquatic Toxicology 161, U.S. Environmental Protection Agency 2017, ECOTOX User Guide: ECOTOXicology Knowledgebase System. Version 4.0, available from Rubach, Baird and Van den Brink 2010, A new method for ranking mode-specific sensitivity of freshwater arthropods to insecticides and its relationship to biological traits. Environmental Toxicology and Chemistry 29, Wiberg-Larsen et. al 2016, Trait characteristics determine pyrethroid sensitivity in nonstandard test species of freshwater macroinvertebrates: a reality check. Environmental Science and Technology 50, Tachet et. al. 2000, Invertébrés d'eau douce: systématique, biologie, écologie. CNRS éditions Paris. Larras et. al 2014, Linking diatom sensitivity to herbicides to phylogeny: a step forward for biomonitoring? Environmental Science and Technology 48, Centre for Biotechnology Information (NCBI) European Environmental Ag.ency (EEA) 2004

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