Economists counting fish: modeling profit-maximizing behavior to improve stock assessments

Le résumé fourni par la source

Stock assessments are an integral part of contemporary fisheries management, estimating the health of wild fish populations and ensuring sustainable marine resource management. Fishery-independent data (e.g., scientific surveys) usually provide unbiased information not influenced by fisher targeting, although fishery-dependent data can be more widely available. One reason the use of fishery-dependent data in assessments is treated with care is that the data do not account for the spatial site selection and economic behavior of fishers. By understanding and explicitly modeling how fishers make tradeoffs, economic models can correct for selection if fishers systematically choose areas with greater expected catches or revenues. We develop and test an approach to correct abundance indices taking into account the sampling process of fishers in a simulation framework. Corrected indices can supplement fishery-independent surveys and improve the accuracy of spawning biomass estimates in some scenarios, but are unreliable in others. We demonstrate the potential for economic models to serve as a tool to improve certain stock assessments and the management based upon them.

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