Abstract

Understanding the fluctuations in marine fish stocks is important for the management of fisheries, and attempts were made to demonstrate links with oceanographic and climatic variability. The pelagic longline observer program is a useful tool for studying correlations between environmental and vessel parameters and the various species caught by the longline fleet because of its high spatial resolution, which allows a linkage between the catch data and environmental parameters. We modeled catch-per-unit-effort (CPUE) of dolphinfish (Coryphaena hippurus) with several other species that are frequently caught by the United States Pelagic longline fleet in a Principle Components Analysis (PCA) in two distinct biogeographic areas: the Gulf of Mexico and the east coast of the United States. The catch PCA demonstrated that the species were not strongly intercorrelated and therefore dolphinfish were analyzed individually with the environmental parameters. PCAs are presented for dolphinfish individually against oceanic conditions and effort characteristics both for the total datasets and by season for the east and west. In all cases, over 70% of the variability in the data was explained by the first three components. Results suggest that dolphinfish are positively correlated with SST and negatively correlated with proximity of a front, and that the PCAs provide a picture of the areas in each region that are important for higher CPUEs of dolphinfish

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