Predicting the Distribution of Yellowfin Tuna in Philippine Waters

Abstract:

The Philippines is considered as a major tuna producer in the Western and Central Pacific Ocean, both for domestic consumption and on industrial scale. However, with the ever-increasing demand of growing population, it has always been a challenge to achieve sustainable fishing. The creation of satellite-derived potential fishing zone maps is a technology that has been adopted by advanced countries for almost three decades already and has led to reduction in search times by up to 40%. In this study, a Generalized Additive Model (GAM) is developed to predict the distribution of the Yellowfin tuna species in seas surrounding the Philippines based on the Catch-Per-Unit-Effort (CPUE) index. Level 3 gridded chlorophyll-a and sea surface temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua satellite of the National Aeronautics and Space Administration (NASA) are the main input parameters of the model. Chlorophyll-a is linked with the presence of phytoplankton, which indicates primary productivity and suggests potential regions of fish aggregation. Fish also prefers to stay in regions where the temperature is stable, thus the sea surface temperature fronts serve as a guide to locate concentrations of fish school. Historical monthly tuna catch data from Western and Central Pacific Commissions (WCPFC) is used to train the model. The resulting predictions are converted to potential fishing zone maps and are evaluated within and beyond the historical time range of the training data used. Diagnostic tests involving adjusted R² value, GAM residual plots and root mean square error value are used to assess the accuracy of the model. The generated maps were able to confirm locations of known tuna fishing grounds in Mindanao and other parts of the country, as well us detect their seasonality and interannual variability. To improve the performance of the model, ancillary data such as surface winds reanalysis from National Centers for Environmental Prediction (NCEP) is also incorporated in the model. Results of the model are further analyzed by comparing the fish maps with the night fishing activities in the Philippine waters. This was done through the use of night light monthly images gathered by Visible Infrared Imaging Radiometer Suite (VIIRS) within the Philippine Exclusive Economic Zone (EEZ).