Contribution of benthic invertebrate biological traits to the survey and restoration of stream ecological quality Cédric Mondy 1,2 , Nele Schuwirth 2 & Philippe Usseglio-Polatera 1 1 : Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC), CNRS UMR 7360, Université de Lorraine, Metz, France 2 : Eawag – Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
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Contribution of benthic invertebrate biological traits to the survey and restoration of stream
ecological quality
Cédric Mondy1,2, Nele Schuwirth2 & Philippe Usseglio-Polatera1
1: Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC), CNRS UMR 7360, Université de Lorraine, Metz, France
2: Eawag – Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
The Water Framework Directive (WFD: European Council 2000)
European Council. Directive 2000/60/EC. Office for official publications of the European Communities, Brussels 2000
Three steps: 1- Assessing the actual ecological quality of water bodies 2- Identifying the stressors that could have led to ecological impairment 3- Predicting which management options could potentially lead to the best improvement of ecological quality
dynamics in response to changes in environmental conditions
Best management/restoration option: Stream management option (e.g. upgrading of WWTP, change in agricultural practices, hydromorphological restoration) that would lead to the highest level of ecological quality improvement for a given amount of investment.
Further model development should: • take into account parameter
uncertainty
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Step 3- Predicting best management options
marginal prior (dashed lines) and posterior (solid lines with grey shading) parameter distributions; the posterior resulting from conditioning with the data
Schuwirth N & Reichert P. Ecology 2013;94:368–79
Further model development should: • take into account parameter
uncertainty • learn from data about
parameters (Bayesian inference)
• use other traits
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Baetis
Further model development should: • take into account parameter
uncertainty • learn from data about
parameters (Bayesian inference)
• use other traits • be tested and calibrated in
other streams subjected to other pressure conditions
• Scenario analysis
Step 3- Predicting best management options
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Conclusions
Traits can improve: - ecological assessment - stressor identification - ecosystem forecasting Further works: - improving our understanding and description of driving processes - extending the model to other relevant processes (dispersal, emergence…) - multi-criteria decision analysis taking into account ecological, economic, and societal endpoints