文摘
Habitat models, such as the habitat suitable index (HSI), have been extensively used to estimate the spatial distribution of fish species based on the quality of habitat. Fishery dependent data from commercial fishing vessels are an important or potentially the only source of scientific information available in these fisheries, especially for the highly migratory stocks in the high seas. In this study we use catch and effort data from the Chinese trawl fishery combined with remote sensing data including sea surface temperature (SST), sea surface height (SSH) and sea surface chlorophyll-a concentration (Chl-a) to define suitable index (SI) for jack mackerel (Trachurus murphyi) in the South East Pacific Ocean. Observed SI values were calculated based on the frequency distribution of fishing effort for each environmental variable, and parameters of the SI models were estimated using nonlinear regression. SI models for SST, SSH, and Chl-a were combined into two empirical HSI models, the arithmetic mean model (AMM) and the geometric mean model (GMM). Results indicate that the AMM performs better than the GMM model to quantify the scale of best available habitat for jack mackerel. Catch distribution fit well with the predicted high-quality habitat in 2013: 85.5%, 100.0% and 97.0% of total catch in fall, winter and spring respectively, were caught in areas predicted with better habitat. The seasonal variation of suitable habitat in latitude is consistent with that of the gravity centers of fishing effort and the 15 °C isotherm. There is strong agreement between annual total catch by the international trawl fishery and mean suitable habitat area during the period 2001–2010, but an opposite tendency from 2011 to 2013. This may be related to the lowest biomass of jack mackerel and catch quota introduced by the South Pacific Regional Fisheries Management Organization since 2010.