FN Archimer Export Format
PT J
TI A Bayesian framework to objectively combine metrics when developing stressor specific multimetric indicator
BT 
AF DROUINEAU, Hilaire
   LOBRY, Jeremy
   DELPECH, C.
   BOUCHOUCHA, Marc
   MAHEVAS, Stephanie
   COURRAT, A.
   PASQUAUD, S.
   LEPAGE, M.
AS 1:1;2:1;3:1;4:2;5:3;6:1;7:1;8:1;
FF 1:;2:;3:;4:PDG-ODE-LER-LERPAC;5:PDG-RBE-EMH;6:;7:;8:;
C1 Cemagref, UR EPBX EPBX, F-33612 Gazinet, Cestas, France.
   Ifremer, Lab Environm Ressources, ZP Bregaillon, F-83507 La Seyne Sur Mer, France.
   Ifremer, Dept EMH, F-44311 Nantes 03, France.
C2 CEMAGREF, FRANCE
   IFREMER, FRANCE
   IFREMER, FRANCE
SI TOULON
   NANTES
SE PDG-ODE-LER-LERPAC
   PDG-RBE-EMH
IN WOS Ifremer jusqu'en 2018
   copubli-france
   copubli-p187
IF 2.89
TC 14
UR https://archimer.ifremer.fr/doc/00049/16037/13572.pdf
LA English
DT Article
DE ;Multimetric fish-based indicator;Bayesian method;Pressure-impact models;Water Framework Directive;Anthropogenic pressure;Monitoring program;Transitional waters
AB In the context of the European Water Framework Directive (WFD), monitoring programs and related indicators have been developed to assess anthropogenic impacts on various components of aquatic ecosystems. While great precautions are usually taken when selecting and calculating relevant core metrics, little attention is generally paid to the generation of the multimetric indicator, i.e. the combination of the different core metrics. Indeed, most multimetric indicators are generated by simply averaging or summing metrics, without taking into account their sensitivity and their variability. Moreover, few indicators provide a rigorous estimate of the uncertainty of the assessments, while this estimation is essential for managers. In this context, we developed a Bayesian framework to build multimetric indicators aiming at improving those two weaknesses. This framework is based on two phases. First, pressure-impact statistical models are developed to quantify the impact of pressure on various fish metrics. Then the Bayesian theorem is applied to estimate probabilities of being at a certain anthropogenic pressure level from fish observation and pressure-impact models outputs. The Bayesian theorem allows to combine objectively the different core metrics, taking into account their sensitivity and their variability, and to provide rigorous uncertainty quantification, which is especially valuable in the WFD context. The method is applied as illustrative example on transitional French water bodies to demonstrate its relevance, especially in the Water Framework Directive context though the method is generic enough to be applied in various contexts. (C) 2011 Elsevier Ltd. All rights reserved.
PY 2012
PD FEB
SO Ecological Indicators
SN 1470-160X
PU Elsevier Science Bv
VL 13
IS 1
UT 000296042500034
BP 314
EP 321
DI 10.1016/j.ecolind.2011.06.029
ID 16037
ER

EF