Habitat suitability of Pacific saury (Cololabis saira) based on a yield-density model and weighted analysis

Abstract

The Pacific saury (Cololabis saira) supports one of the most important pelagic fisheries in the Northwestern Pacific Ocean. However, changing oceanographic conditions could result in difficulties in predicting fishing grounds and fishery management. We combined a yield-density model and weighted statistical analysis to develop a habitat suitability index (HSI) model to identify the relationship between oceanographic variables and potential habitat. This approach was applied to fishing data from the Chinese saury fishery during the main fishing season (June–November) from 2013 to 2015. The oceanographic variables considered included sea surface temperature (SST), horizontal sea surface temperature gradient (SSTG) and sea surface height (SSH). The HSI model was validated using fishery and oceanographic data for 2016. This study indicated that (1) the yield-density model can be reliably used to fit a curvilinear relation between the suitability index (SI) and SST, SSTG, and SSH, and the optimal habitat conditions for the three variables were obtained; (2) weighted analysis-based boosted regression trees revealed that SSTG had the most important influence on SI each month, followed by SST and SSH; and (3) approximately 70% of the fishing effort occurred in the areas where HSI > 0.5 in each month. Results of this study could help to further understand the effects of oceanographic conditions on habitat distribution and provide a way to forecast saury fishing grounds.