4.6 Article

Assessing and managing data-limited ornamental fisheries in coral reefs

期刊

FISH AND FISHERIES
卷 15, 期 4, 页码 661-675

出版社

WILEY
DOI: 10.1111/faf.12040

关键词

Aquarium trade; curio trade; data-poor fisheries; ornamental fisheries; productivity susceptibility analysis; sustainable fisheries management

资金

  1. NSF [DGE-1144085]

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Coral reefs support numerous ornamental fisheries, but there are concerns about stock sustainability due to the volume of animals caught. Such impacts are difficult to quantify and manage because fishery data are often lacking. Here, we suggest a framework that integrates several data-poor assessment and management methods in order to provide management guidance for fisheries that differ widely in the kinds and amounts of data available. First, a resource manager could assess the status of the ecosystem (using quantitative metrics where data are available and semi-quantitative risk assessment where they are not) and determine whether overall fishing mortality should be reduced. Next, productivity susceptibility analysis can be used to estimate vulnerability to fishing using basic information on life history and the nature of the fishery. Information on the relative degree of exploitation (e.g. export data or ratios of fish density inside and outside no-take marine reserves) is then combined with the vulnerability ranks to prioritize species for precautionary management and further analysis. For example, species that are both highly exploited and vulnerable are good candidates for precautionary reductions in allowable capture. Species that appear to be less vulnerable could be managed on a stock-specific basis to prevent over-exploitation of some species resulting from the use of aggregate catch limits. The framework could be applied to coral reef ornamental fisheries which typically lack landings, catch-per-unit-effort and age-size data to generate management guidance to reduce overfishing risk. We illustrate the application of this framework to an ornamental fishery in Indonesia.

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