Title of article :
Can we predict biological condition of stream ecosystems? A multi-stressors approach linking three biological indices to physico-chemistry, hydromorphology and land use
Author/Authors :
Villeneuve، نويسنده , , B. and Souchon، نويسنده , , Y. and Usseglio-Polatera، نويسنده , , P. and Ferréol، نويسنده , , M. and Valette، نويسنده , , L.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2015
Pages :
11
From page :
88
To page :
98
Abstract :
We built a corpus of models capable of explaining the variability of the biological indices used in the French surveillance monitoring network and also predict the ecological status of non-monitored water bodies. Benthic macroinvertebrates, diatoms and fish indices have been used to determine the ecological status of 1100 sites of the monitoring network distributed homogeneously over national territory. essures taken into account to explain and predict ecological status cover three spatial scales: catchment, reach, site. The set of predictive data cover three types of pressure: land use pressure, hydromorphological pressure and physico-chemical pressure measured at catchment, reach and site scale, respectively. wed that the parameters characterising the load of nutrients and organic matter had a predominant effect on the three biological compartments, and that land use variables played an integrating role of the different pressures acting on rivers and explained a major part of their degradation. On the contrary, we also showed that it was more difficult to characterise the role of the hydromorphological descriptors measured at the intermediate scale of the reach due to the difficulty of characterising the links between scales. ree predictive models developed demonstrated good performances to evaluate biological condition and are of great interest for managers as it permits using a set of pressure data to successively predict the status of water bodies for which biological monitoring data are unavailable.
Keywords :
Modelling , Biological condition , stressors , multi-scale , Stream ecosystems
Journal title :
Ecological Indicators
Serial Year :
2015
Journal title :
Ecological Indicators
Record number :
2094362
Link To Document :
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