Uncertainty associated with river health assessment in a varying environment: The case of a predictive fish-based index in France

•Uncertainty and uncontrolled variability of bio-indicators have crucial implications for water management decisions and need to be acknowledged.•A Bayesian method appropriate to build a multi-metric index associated with a measure of predictive uncertainty was developed.•Resulting index scores are...

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Veröffentlicht in:Ecological indicators 2014-08, Vol.43, p.195-204
Hauptverfasser: Marzin, Anahita, Delaigue, Olivier, Logez, Maxime, Belliard, Jérôme, Pont, Didier
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Sprache:eng
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Zusammenfassung:•Uncertainty and uncontrolled variability of bio-indicators have crucial implications for water management decisions and need to be acknowledged.•A Bayesian method appropriate to build a multi-metric index associated with a measure of predictive uncertainty was developed.•Resulting index scores are independent from natural variability and are sensitive to human-induced disturbances.•Index predictive uncertainty is globally lower for the multi-metric index than for individual underlying metrics.•Our results support the use of multi-metric index and examination of uncertainty to improve the assessment power of bio-indicators. Sensitive biological measures of river ecosystem quality are needed to assess, maintain or restore ecological conditions of water bodies. Since our understanding of these complex systems is imperfect, decision-making requires recognizing uncertainty. In this study, a new predictive multi-metric index based on fish functional traits was developed to assess French rivers. Information on fish assemblage structure, local environment and human-induced disturbances of 1654 French river sites was compiled. A Bayesian framework was used to predict theoretical metric values in absence of human pressure and to estimate the uncertainty associated with these predictions. The uncertainty associated with the index score gives the confidence associated with the evaluation of site ecological conditions. Among the 228 potential metrics tested, only 11 were retained for the index computation. The final index is independent from natural variability and sensitive to human-induced disturbances. In particular, it is affected by the accumulation of different degradations and specific degradations including hydrological perturbations. Predictive uncertainty is globally lower for IPR+ than for underlying metrics. This new methodology seems appropriate to develop bio-indication tools accounting for uncertainty related to reference condition definition and could be extended to other biological groups and areas. Our results support the use of multi-metric indexes to assess rivers and strengthen the idea that examination of uncertainty could contribute greatly to the improvement of the assessment power of bio-indicators.
ISSN:1470-160X
1872-7034
DOI:10.1016/j.ecolind.2014.02.011