Abstract

In the present study, an attempt was made to investigate temporal and spatial patterns of multi-day fishing in the Indian Ocean off Sri Lanka to elucidate how such patterns related to fishing methods of multi-day fishing vessels targeting different pelagic fish species. In the analysis, 269,564 fishing operations from 37,349 fishing trips of multi-day fishing vessels during 2019 and 2020 were used. Based on the standardized fishing effort of the three major fishing methods (i.e., longlining, drift gillnetting and ring netting), species-wise catch per unit effort (CPUE) was determined for each fishing operation.The CPUE values of the three fishing methods were grouped for fishing locations in three major basins of the Indian Ocean, and according to three monsoonal seasons having varying influences of cyclones. Accordingly, 269,564 fishing operations were summarized into 77 datasets during the study period. The mean CPUE values (kg per fishing operation) were 257.3 for longlining, 163.3 for drift gillnetting and 1642.7 for ring netting. The patterns of the data matrix were investigated using the self-organizing map routine of the Artificial Neural Network. Accordingly, based on the occurrence of target species, data were classified into six clusters from which spatio-temporal patterns of fishing operations could be visualized. Ring netting was predominantly concentrated in the equatorial region and to a lesser extent in the Bay of Bengal region, with a temporal occurrence during all three seasons. Longline fishing was also predominant in the equatorial Indian Ocean region with the majority registered in the non-cyclone period. Most drift gillnet fishing operations were concentrated in the equatorial region and the Arabian Sea region, especially during the northern Indian Ocean cyclone period. These results would provide important pieces of information for the management of pelagic fish species through monitoring, control and surveillance (MCS) of the fishery.

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