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

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.