Assessing anthropogenic pressures on streams: A random forest approach based on benthic diatom communities
Evaluation de la pression anthropique exercée sur les cours d'eau : une approche basée sur les random forest et les communautés de diatomées benthiques
Larras, F. ; Coulaud, R. ; Gautreau, E. ; Billoir, E. ; Rosebery, J. ; Usseglio Polatera, P.
Type de document
Article de revue scientifique à comité de lecture
Affiliation de l'auteur
CNRS UNIVERSITE DE LORRAINE UMR 7360 LIEC METZ FRA ; CNRS UNIVERSITE DE LORRAINE UMR 7360 LIEC METZ FRA ; CNRS UNIVERSITE DE LORRAINE UMR 7360 LIEC METZ FRA ; CNRS UNIVERSITE DE LORRAINE UMR 7360 LIEC METZ FRA ; IRSTEA BORDEAUX UR EABX FRA ; CNRS UNIVERSITE DE LORRAINE UMR 7360 LIEC METZ FRA
Résumé / Abstract
Benthic diatoms have been widely used to assess the ecological status of freshwater ecosystems, especially in the context of recent international water framework directive policies (e.g. the WFD). Despite diatom-based indices are known to respond fastly to water quality degradation, they are not designed to precisely identify the nature of pressures co-occurring in the environment. Based on large scale monitoring data, we aimed at building models able to estimate the risk of stream impairment by many types of anthropogenic pressures from taxonomy based and trait-based characteristics of diatom assemblages. Random forest models were built to individually evaluate the impairment risk of diatom assemblages for six chemical and five hydromorphological or land-use related pressure categories. Eight models provided good impairment risk assessment (Area Under the Curve >= 0.70). Under multi-pressure scenarios, models built for chemical pressures exhibited a better accuracy than hydromorphological or land-use related ones. Models were able to detect both ecological restoration and degradation, based on long-term surveys. These models have been implemented in a R user-friendly routine, to help stream managers to early identify degrading processes and prioritize management actions. (C) 2017 Elsevier B.V. All rights reserved.
Science of the Total Environment, vol. 586, p. 1101 - 1112