Tropical tuna fishing by purse-seine is one of the most important fisheries in the world. The use of fishing aggregate devices (FADs) revolutionised tropical tuna purse-seine fishery by facilitating the locating of tunas and increasing efficiency dramatically. However, the combination of fishing modes with FAD fishing and traditional free-swimming schools (FSS) fishing also increased challenges for tuna stock management. To improve the management of this important resource, an effective method for monitoring two fishing modes is needed. With the help of vessel monitoring system (VMS) data, this study proposes a characterisation method based on purse-seiner relocation pattern analysis and daily rhythm of fishing activities. Compared to FSS sets, fishing sets on FADs are led by a more direct trajectory, involve more navigation time at night and are conducted mainly in the first hours of the day. Random forest classification was performed to separate the fishing sets into two modes. The cross-validation demonstrated an overall classification accuracy of 74%. This work provides a promising tool to standardise fishing effort and monitor compliance with different FAD management measures.
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