Anthony MAIRE - Jean-Marc BAUDOIN - Christine ARGILLIER A multi-faceted assessment of lake fish communities: implications for conservation and restoration in France Anthony MAIRE - Jean-Marc BAUDOIN - Christine ARGILLIER IRSTEA - UR HYAX Pôle ONEMA-IRSTEA - Aix-en-Provence - France Bernard Dumont/IRSTEA Martin Daufresne/IRSTEA

Sébastien Merckle/IRSTEA BACKGROUND A lot of existing tools  Indices of biotic integrity (e.g. ELFI related to fish in natural lakes) Argillier et al. (2013) © PrioFish Gerpho.com Sébastien Merckle/IRSTEA Water Framework Directive (WFD) European Commission (2000)  Assessment of the ecological status of water bodies Birk et al. (2012) abritel.fr Caramaps.com However some aspects of the diversity of biological communities are not often accounted for: Species conservation importance Socio-economic value of species Overall functional diversity … One of the final aims of the bioindication scheme is to prioritize management actions on the basis of these indices Hering et al. (2010) 2

OBJECTIVE To develop a complementary approach which: Focuses on fish assemblages in lakes Relies on the data collected for the WFD Includes different facets of fish assemblage diversity and combines them into a prioritization framework 3

LAKES IN FRANCE & FISH DATA Great environmental diversity of lakes Quantitative sampling of fish assemblages  Standardized fishing protocol (CEN prEN 14757) using multi-mesh gillnets Stéphanie Pedron/IRSTEA Natural Lakes N = 46 Reservoirs N = 186 Gillnet Lake shoreline 100 km Comparable data on species abundance and biomass  Focus on Natural Lakes 4

APPLICATION OF A MULTI-FACETED FRAMEWORK OF DIVERSITY Adaptation of a framework previously developed on rivers Maire et al. (2013)  Four non-redundant facets of diversity involving various quantitative indices 5

FACET 1: TAXONOMIC DIVERSITY Species richness Originality of the assemblage of species Range-sized rarity of the species present Rutilus rutilus Salvelinus umbla - + Rarity 6 Maire et al. (2013) Fattorini (2006)

FACET 2: FUNCTIONAL DIVERSITY Trait diversity Functional originality Functional uniqueness Originality Uniqueness Combination of life history and morphological traits Type of trait Examples Life history Feeding habitat Breeding habitat Morphological Body depth Mouth position Schleuter et al. (2012)  Removal of the redundancy among the 17 traits 7 Buisson et al. (2013)

FACET 3: CONSERVATION IMPORTANCE Conservation status of the species present CR Anguilla anguilla Critically Endangered VU Coregonus lavaretus Vulnerable LC Esox lucius Least Concern Thymallus thymallus Appendix V Rhodeus amarus Appendix III Habitat Directive 8 Bergerot et al. (2008)

FACET 4: SOCIO-ECONOMIC VALUE Fishing interest of the species present Species without fishing interest Species of interest for sportive anglers Species of global interest for anglers and fishermen aquaportail.com Lepomis gibbosus Sander lucioperca Cyprinus carpio aappma-belves.wifeo.com pecheur.info 9 Maire et al. (2013)

AGGREGATION OF THE INDICES BY FACET All the indices were computed on three fish data variants: Presence-absence (PA) Catch per unit effort (CPUE) Biomass per unit effort (BPUE) Standardisation of the indices and aggregation by facet  Three values of each facet by lake 10

RESPONSE OF THE FACETS TO ENVIRONMENTAL PREDICTORS AND STRESSORS Generalized Linear Models (GLM) with stepwise procedure Faceti ~ Environment1,…,n + Stressor1,…k Altitude Maximum depth Lake area Catchment area Mean annual temperature Annual thermal range Eutrophication: Total Phosphorus (TP) Proportion of Non-Natural Land-Covers in the catchment (NNLC) Hydromorphological alterations: Proportion of the lake shore altered (HM) For each facet: PA, CPUE and BPUE variants were tested  The variant with the ‘best model’ was selected Maximizing explained deviance Mixing “natural” variability and significant responses to stressors 11

RESPONSE OF THE FACETS TO ENVIRONMENTAL PREDICTORS AND STRESSORS Generalized Linear Models (GLM) with stepwise procedure Facet Variant R² Significant effect of stressors TAXONOMIC PA 0.74 TP - NNLC - HM FUNCTIONAL 0.62 TP CONSERVATION 0.67 SOCIO-ECONOMIC CPUE 0.77 Socio-Economic Value (CPUE) log(Total Phosphorus [µg/L]) log(Total Phosphorus [µg/L]) Conservation Importance (PA)  Final Synthetic Index = Sum of the 4 selected variants after standardization Synthetic Index = TAXO[PA] + FUNCT[PA] + CONSERV[PA] + SOCIO-ECO[CPUE] For each lake: one synthetic value = Preservation priority 12

LAKE PRESERVATION PRIORITIES Final Synthetic Index log(Maximum Depth [m]) Priority + log(Total Phosphorus [µg/L]) Final Synthetic Index - 100 km 13

ESTIMATION OF FACET VALUES UNDER REDUCED ANTHROPOGENIC STRESSORS Hindcasting modelling of the reference conditions  Reduction of stressors to low values in the models Facet ~ (Environment + Stressors) 1 Modelling - GLM 2 Reference: Facet = Environment Stressors ≈ 0 3 Scoring Reference: Synthetic Index = Σ Facets New synthetic index value expected under low anthropogenic disturbances by summing the predicted values of the four facets 4 Restoration potential Deviation = Reference - Observed  Restoration priority 14 Launois et al. (2011); Maire et al. (2015)

LAKE RESTORATION PRIORITIES Only 10% of the French natural lakes with high restoration priority More than 50% of them with very low potential No redundancy with the WFD national index (ELFI) ρSpearman = 0.05 Priority + - 100 km 15

CONCLUSION & PERSPECTIVES 100 km + - Preservation Priority Original approach which provides two additional information regarding lake management priorities  Complementary to existing bioindication tools Extension of this approach to Heavily Modified Water Bodies  4x more reservoirs than natural lakes in France Comparison with expert knowledge before validation by national authorities and local decision-makers Relationships with the results obtained on rivers?  To bring new insights for a more integrative management at the catchment scale 16

THANK YOU Contact Acknowledgments References anthony.maire@irstea.fr We would like to thank all the territorial agents of the French National Agency for Water and Aquatic Environment (ONEMA) implied in the collection of the biological data. References Argillier, C. et al. (2013). Hydrobiologia, 704. Bergerot, B. et al. (2008). Biodiversity and Conservation, 17. Birk, S. et al. (2012). Ecological Indicators, 18. Buisson, L. et al. (2013). Global Change Biology, 19. European Commission. (2000). Official Journal of the European Communities. Fattorini, S. (2006). Animal Conservation, 9. Hering, D. et al. (2010). Science of The Total Environment, 408. Launois, L. et al. (2011). Ecological Indicators, 11. Maire, A. et al. (2013). Ecological Indicators, 34. Maire, A. et al. (2015). Aquatic Conservation: Marine and Freshwater Ecosystems, in press. Schleuter, D. et al. (2012). Global Ecology and Biogeography, 21.