Improving the interpretation of fishing effort and pressures in mixed fisheries using spatial overlap metrics

Type Article
Date 2019-04
Language English
Author(s) Bourdaud PierreORCID1, Travers-Trolet MorganeORCID2, 3, Vermard YouenORCID3, Marchal PaulORCID4
Affiliation(s) 1 : Ifremer Centre Manche Mer du Nord, 121237, 150 quai Gambetta, Boulogne-sur-Mer, France, 62321;
2 : IFREMER, F-62321 Boulogne-sur-Mer, cedex, France
3 : Ifremer Centre Atlantique, 70611, Nantes, Pays de la Loire, France
4 : Ifremer, Channel and North Sea Fisheries Research Unit, 150 Quai Gambetta, Boulogne sur mer, France, 62321, , ;
Source Canadian Journal Of Fisheries And Aquatic Sciences (0706-652X) (Canadian Science Publishing), 2019-04 , Vol. 76 , N. 4 , P. 586-596
DOI 10.1139/cjfas-2017-0529
Abstract

Managing mixed fisheries requires understanding fishers’ behaviour to allow predicting future fisheries distribution and impact on marine ecosystems. A new approach was developed to compare fine scale fishing effort distribution of Eastern English Channel (EEC) bottom trawlers, to the monthly- and spatially-resolved abundance distributions of commercial species. First, the added-value of using species-specific spatial overlap metric to quantify effective fishing effort and improve the relationship between fishing effort and fishing mortality was assessed. Second, based on the Ideal Free Distribution (IFD) theory, the species-specific weights given by fishers to different species were estimated by maximizing the overlap between target species assemblage and effort distributions in October. At a seasonal scale our results emphasized the importance of cuttlefish and red mullet for the global distribution of EEC bottom trawlers. In October, cuttlefish and red mullet were clearly more determining fishers’ location choice than historically harvested species, and also than the overall expected revenue. This is likely due to external constraints such as low cod quota, causing IFD assumptions violated. This study evidenced the importance of getting good insights into spatio-temporal distributions of stocks and fleets to understand fishers’ behaviour and improve mixed fisheries management advice

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