Using a trait-based approach to understand the efficiency of a selective device in a multispecific fishery
|Author(s)||Mouchet Maud1, Poirson Manon1, Morandeau Fabien2, Vogel Camille3, Méhault Sonia2, Kopp Dorothee2|
|Affiliation(s)||1 : UMR 7204 MNHN-SU-CNRS Centre d’Ecologie et des Sciences de la Conservation, CP135, 43 rue Buffon, 75005, Paris, France
2 : IFREMER, Unité de Sciences et Technologies Halieutiques, Laboratoire de Technologie et Biologie Halieutique, 8 rue François Toullec, F-56100, Lorient, France
3 : IFREMER, Department of Biological Resources and Environment/Fisheries Science for the English Channel and North Sea/Fisheries Resources Laboratory, Avenue du Général de Gaulle, 14520, Port-en-Bessin-Huppain, France
|Source||Scientific Reports (2045-2322) (Springer Science and Business Media LLC), 2019-08 , Vol. 9 , N. 1 , P. 12489 (8p.)|
|WOS© Times Cited||1|
Improving the selectivity of a fishing gear is one technical management measure to significantly reduce by-catch of non-commercial species or undersized individuals. The efficiency of selective device is mainly estimated by comparing species composition, the biomass and length spectrum of caught individuals and escapees while the functional traits of species are rarely accounted for. Using an innovative technical device to reduce catches of undersized individuals in a multispecific bottom trawl fishery in the Bay of Biscay, namely a T90 mesh cylinder, we measured functional traits on both caught and escaped individuals of 18 species. Using a Principal Component Analysis and K-means partitioning, we clustered species into 6 groups illustrating 6 different locomotion strategies. We identified functional traits related to body size, visual ability and locomotion, differing between caught individuals and escapees using Linear Mixed-effects Models. As expected, escapees were smaller on average but also tended to be more streamlined, with a high position of the eyes and fin features characteristic of manoeuvrability and propulsion. Here, we present how a trait-based approach can shed light on the biological characteristics influencing the efficiency of selective devices.