Marine ecosystem analyses in the Guf of Ulloa, Mexico: BAC meets Ecopath

Abstract

The Ecopath modelling package (EwE) satisfies some of the international guidelines for promoting an ecosystem-based fisheries management; however, proper definition of ecological management units has not been fully accomplished. The Biological Action Centre (BAC) concept may address this problem. BACs are small, highly productive coastal areas whose productivity is almost constant throughout the year when compared to adjacent zones; thus these areas may sustain large amounts of exploitable biomass. By using EwE it was possible to characterize the Gulf of Ulloa, Mexico, as a BAC, since it shows high absolute and instantaneous productivity rates, despite sharing certain ecological attributes with upwelling zones. Using temporal (Ecosim) and spatial (Ecospace) dynamic versions of the model, we simulated abundance and distribution patterns of the main fishery resources and key ecological groups in the area. For the blue abalone CPUE time series, the best fitting resulted from the addition of annual sea level anomalies as a forcing factor. Dynamic simulation of biomass time series of the Pacific sardine showed a relatively poor fit, even after introducing forcing factors whose influence on this stock is well documented. The low sensitivity of Ecosim was possibly due to the model’s underlying assumption of the existence of a linear relationship among forcing factors and between forcing factors and sardine stock dynamics. Simulations of geographical distribution patterns of phytoplankton and zooplankton and the estimation of exported biomass from this BAC to adjacent systems using the Ecospace model were very similar to those estimated with alternative methods and data. Whilst EwE was shown to be useful to analyze key functional, organizational and structural aspects of highly productive marine ecological systems such as the BACs, the model must take into account at least causal nonlinear relationships between forcing factors and stock dynamics in order to derive more relevant information to fisheries management.