Forecasting dynamics of red snapper (Lutjanus campechanus) in the US Gulf of Mexico
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2016 Elsevier B.V. Understanding dynamics and stock structures of fish is particularly relevant to assessments and management of marine living resources. Using the nonparametric, nonlinear time series (NLTS) approach, we modeled dynamics of red snapper (Lutjanus campechanus) represented by time series of two fisheries-independent abundance indices and two fisheries-dependent abundance indices in the eastern and western portions of the U.S. Gulf of Mexico (Gulf). Further, we examined regional dynamics of red snapper in the two areas and explored the utility of NLTS models in generating short term forecasts. Overall, red snapper in the eastern Gulf and western Gulf displayed distinct patterns in terms of the Gulf-wide ecosystem indicators, which likely implies different underlying regional dynamics of the species. Moreover, dynamic features of red snapper differed between the two regions. Specifically, the system dimension (mean SE), i.e., the number of potential processes affecting the underlying dynamics of the species, was higher in the western Gulf (5.5 1.32) than in the eastern Gulf (3.75 1.44). The NLTS models exhibited significant skill (i.e., a measure of the goodness of fit () between observations and predictions) in forecasting red snapper abundance indices. The forecast skill (one year ahead) was 0.48 0.01 for indices representing the eastern Gulf and 0.33 0.05 for indices representing the western Gulf. The average dimension and forecast skill was 3 1.43 and 0.37 0.01 for fisheries-dependent indices, and 6.25 1.32 and 0.45 0.05 for fisheries-independent indices. These findings have implications for the Gulf red snapper fisheries in that the NLTS approach shows potential for forecasting stock abundance indices, and provides new information regarding the appropriate spatial scale for management of the species. Moreover, the ecosystem considerations in this study can be further explored to forecast the dynamics of red snapper for better assessments and management of the species.
