Abundance vs biomass: effects of the traits weighting on the measure of functional diversity
Lise Bacouillard  1, *@  , Noémie Baux  2@  , Jean-Claude Dauvin  2@  , Nicolas Desroy  3@  , Katja Juliana Geiger  1@  , Franck Gentil  1@  , Céline Houbin  4@  , Eric Thiébaut  1@  
1 : Sorbonne Université, CNRS, Station Biologique de Roscoff, UMR7144 - Adaptation et Diversité en Milieu Marin
Sorbonne Université, CNRS, Station Biologique de Roscoff, UMR7144 - AD2M
Place Georges Teissier, 29680 Roscoff -  France
2 : Normandie université, CNRS, UMR6143 - Laboratoire Morphodynamique Continentale et Côtière  (UNICAEN)
Normandie université, CNRS, UMR6143 - Laboratoire Morphodynamique Continentale et Côtière
24 rue des Tilleuls 14000 Caen -  France
3 : IFREMER, Station de Dinard, LER Bretagne Nord
IFREMER, Station de Dinard, LER Bretagne Nord
38 rue du Port Blanc 35800 Dinard -  France
4 : Sorbonne Université, CNRS, Station Biologique de Roscoff, FR2424
Sorbonne Université, CNRS, Station Biologique de Roscoff, FR2424
Place Georges Teissier -  France
* : Corresponding author

While coastal ecosystems experience increasing pressures due to human activities and climate change, measurement of functional diversity based on the biological traits analysis (BTA) is increasingly used as a tool to assess ecosystem functioning and its responses to disturbance. A review of more than 80 papers published since 2003 highlights large differences in the methodology used to measure functional diversity, for instance in terms of the number of traits used, ranging from 3 to 25, the identity of the traits, the nature of the raw data (abundance vs. biomass). Using two different datasets on benthic macrofauna in the English Channel (i.e. a time-series of samples collected yearly from 1977 to 2016, and a spatial survey of 72 stations sampled once in 2016), we analysed how some methodological choices affect the measures of functional diversity, its spatial or temporal changes. The local diversity was calculated from different diversity indices while multivariate methods were applied to describe β-diversity. A peculiar attention is given on the effects of one methodological choice: the selection of biomass data rather than more commonly used abundance data.


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