Prediction of the yield of Skipjack Tuna (Katsuwonus pelamis) Using Remote Sensing Techniques

Abstract

Analysis of relationship amongst sea surface temperature (SST), chlorophyll-a (Chl-a) and fish catch help understand the productivity of the ocean. Satellite images provide reliable important information on oceanographic conditions and, at the same time support marine environmental monitoring and assessment. SST and Chl-a are the key indicators in determining the presence of fishes, especially the pelagic fishes. To describe the shortterm relationship between oceanographic conditions and distribution of skipjack tuna, and visualize their distribution and catch, remotely sensed satellite based-oceanographic sea surface temperature and chl-a together with fisheries data were used to check the distribution of Katsuwonus pelamis. In this context, monthly images of Moderate Resolution Imaging Spectroradiometer satellite (MODIS-Aqua) derived Chl-a, and SST from January 2015 to December 2018 were used. Also, monthly fish catch data in 2018 were used to perform statistical modelling for predicting the catchable yield of K. pelamis in 2019 around in the Indian ocean, south to Sri Lanka. Data were processed and analyzed using ArcGIS 10.7.1, Minitab 19 and SPSS 25. Results indicated that there was a negative correlation between SST and Chl-a (r= -0.724, p=0.000). A Positive correlation was found between Chl-a, and catch of K. pelamis (r=0.431, p=0.035) and a negative correlation was found between SST and catch of K. pelamis (r= -0.547, p=0.006). Prediction of 2019 yield of K. pelamis indicated the 27.4% accuracy (r2= -0.274). The present study indicates that integration of remote sensing technology, statistical modelling, and geographic information systems (GIS) could be used to determine the relationship between sea surface temperature (SST) and chlorophyll-a (Chl-a), as well as to predict the yield of Skipjack Tuna and their distribution in the Indian ocean south of Sri Lanka. In addition, use of GIS, satellite remote sensing and statistical analysis are the effective instruments for fishing activities, and useful in fisheries management. Thus, the present findings contribute to the decision-making for management of fisheries and reduce costs incurred for search hunting in offshore fisheries of Sri Lanka.