1. 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

2. 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

3. 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

4. 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

5. 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

6. 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)

7. 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)

8. 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)

9. 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)

10. 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

11. 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

12. 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

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

14. 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)

15. 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

16. 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

17. 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.