Uncertainty associated with river health assessment in a varying environment: The case of a predictive fish-based index in France |
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| Institution: | 1. Institute of Water Resources System, Inha University, Incheon 22212, Republic of Korea;2. Risk Management Office, KB Claims Survey & Adjusting, Seoul 06212, Republic of Korea;3. Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, CO 80523, USA;4. Department of Civil Engineering, Inha University, Incheon 22212, Republic of Korea;1. State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China;2. Chongqing Academy of Environmental Sciences, Chongqing 401147, China;1. College of Water Sciences, Beijing Normal University, Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, Beijing 100875, PR China;2. School of Geography, Beijing Normal University, Beijing 100875, PR China;3. Jinan Survey Bureau of Hydrology and Water Resources, Jinan 250013, PR China;4. School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, PR China;5. School of Life Sciences, Faculty of Science, University of Technology, Sydney, NSW 2007, Australia;6. School of the Environment, Faculty of Science, University of Technology, Sydney, NSW 2007, Australia;7. ICube, UdS, CNRS (UMR 7357), 300 Bld Sebastien Brant, CS 10413, 67412 Illkirch, France |
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| Abstract: | 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. |
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| Keywords: | Ecological river assessment Multi-metric index Functional traits Uncertainty Bayesian modelling Water framework directive |
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