%0 Journal Article
%9 ACL : Articles dans des revues avec comité de lecture répertoriées par l'AERES
%A Behivoke, F.
%A Etienne, M. P.
%A Guitton, J.
%A Randriatsara, R. M.
%A Ranaivoson, E.
%A Léopold, Marc
%T Estimating fishing effort in small-scale fisheries using GPS tracking data and random forests
%D 2021
%L fdi:010081012
%G ENG
%J Ecological Indicators
%@ 1470-160X
%K Boat movement ; Fishery map ; GPS track ; Madagascar ; Spatial data ; Speed threshold
%K MADAGASCAR
%M ISI:000615921800004
%P 107321 [7 ]
%R 10.1016/j.ecolind.2020.107321
%U https://www.documentation.ird.fr/hor/fdi:010081012
%> https://horizon.documentation.ird.fr/exl-doc/pleins_textes/divers21-03/010081012.pdf
%V 123
%W Horizon (IRD)
%X During the last decade spatial patterns of industrial fisheries have been increasingly characterized using tracking technologies and machine learning analytical algorithms. In contrast, for small-scale fisheries, fishers' behaviour for estimating and mapping fishing effort has only been anecdotally explored. Following a comparative approach, we conducted a boat tracking survey in a small-scale reef fishery in Madagascar and investigated the performance of a learning random forest algorithm and a speed threshold for estimating and mapping fishing effort. We monitored the movements of a sample of 31 traditional sailing fishing boats at around 45 s time interval using small GPS trackers. A total of 306 daily tracks were recorded among five gear types (beach seine, mosquito trawl net, gillnet, handline, and speargun). To ground-truth GPS location data, fishers' behaviour was simultaneously recorded by a single on-board observer for 49 tracks. Typical, gear-specific track patterns were observed. Overall, the random forest model was found to be the most reliable, generic, and complex method for processing boat GPS tracks and detecting spatially-explicit fishing events regardless gear type. Predictions of mean fishing effort per trip showed that both methods reached from 89.4% to 97.0% accuracy across gear types. Our findings showed that boat tracking combined with on-board observation would improve the reliability of spatial fishing effort indicators in small-scale fisheries and contribute to more efficient management. Selection of the most appropriate GPS data processing method is dependent on local gear use, fishing effort indicators, and available analytical expertise.
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