“Too Big To Ignore”: A feasibility analysis of detecting fishing events in Gabonese small-scale fisheries

Type Article
Date 2020-06
Language English
Author(s) Cardiec Floriane1, 2, Bertrand Sophie3, Witt Matthew J.4, Metcalfe Kristian5, Godley Brendan J.5, McClellan Catherine6, Vilela Raul2, Parnell Richard J.2, Le Loch Francois1
Affiliation(s) 1 : IRD, Univ Brest, CNRS, Ifremer, LEMAR, Plouzané, France
2 : Wildlife Conservation Society, Gabon Program, Libreville, Gabon
3 : IRD, UMR Marbec, Univ Montpelier, CNRS, Ifremer, Sète, France
4 : Hatherly Laboratories, College of Life and Environmental Sciences, University of Exeter, Exeter, United Kingdom
5 : Centre for Ecology & Conservation, College of Life and Environmental Sciences, University of Exeter, Penryn Campus, Penryn, United Kingdom
6 : ONG Manga, Akanda, Gabon
Source Plos One (1932-6203) (Public Library of Science (PLoS)), 2020-06 , Vol. 15 , N. 6 , P. e0234091 (19p.)
DOI 10.1371/journal.pone.0234091
WOS© Times Cited 1
Abstract

In many developing countries, small-scale fisheries provide employment and important food security for local populations. To support resource management, the description of the spatiotemporal extent of fisheries is necessary, but often poorly understood due to the diffuse nature of effort, operated from numerous small wooden vessels. Here, in Gabon, Central Africa, we applied Hidden Markov Models to detect fishing patterns in seven different fisheries (with different gears) from GPS data. Models were compared to information collected by on-board observers (7 trips) and, at a larger scale, to a visual interpretation method (99 trips). Models utilizing different sampling resolutions of GPS acquisition were also tested. Model prediction accuracy was high with GPS data sampling rates up to three minutes apart. The minor loss of accuracy linked to model classification is largely compensated by the savings in time required for analysis, especially in a context of nations or organizations with limited resources. This method could be applied to larger datasets at a national or international scale to identify and more adequately manage fishing effort.

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How to cite 

Cardiec Floriane, Bertrand Sophie, Witt Matthew J., Metcalfe Kristian, Godley Brendan J., McClellan Catherine, Vilela Raul, Parnell Richard J., Le Loch Francois (2020). “Too Big To Ignore”: A feasibility analysis of detecting fishing events in Gabonese small-scale fisheries. Plos One, 15(6), e0234091 (19p.). Publisher's official version : https://doi.org/10.1371/journal.pone.0234091 , Open Access version : https://archimer.ifremer.fr/doc/00633/74526/