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Canadian Science Publishing, Canadian Journal of Fisheries and Aquatic Sciences, 9(71), p. 1363-1370

DOI: 10.1139/cjfas-2013-0552

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Deriving high-resolution spatiotemporal fishing effort of large-scale longline fishery from vessel monitoring system (VMS) data and validated by observer data

Journal article published in 2014 by Shui-Kai Chang ORCID, Tzu-Lun Yuan, Verena Trenkel
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

Estimating geo-referenced fishing effort is vital to develop advice for effective fisheries management. Many studies in recent decades have attempted to obtain complete, high-resolution effort data from vessel monitoring systems (VMSs). The main challenge in this regard is to develop a classification method for differentiating fishing activities (e.g., fishing days) from nonfishing activities in VMS data. This study developed a simple, novel classification criterion for a large-scale tuna longline (LTLL) fishery that has not been studied before. LTLL operations were first explored using observer data. Three approaches were designed for developing fishing-day classification criteria, using maximizing sum of sensitivity and specificity (SS) as the major performance measure and minimizing difference of SS as a reference. At least one VMS report with speed in the range of 2–5 kn (1 kn = 1.852 km·h–1) detected during the time-of-day period of 14:00–23:00 h was recommended as the criterion for defining a fishing day. Possible explanations for the differences between the estimated fishing days from VMS data and those reported on logbooks are discussed; most causes were related to specific features of the fishery.