Volume 67

A Multi-indicator Framework for Adaptive Management of Data-limited Fisheries with a Case Study from Belize

McDonald, G., R. Carcamo, R. Fujita, T. Gedamke, K. Karr, and J. Wilson
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Date: November, 2014

Pages: 107 - 114

Event: Proceedings of the Sixty seven Annual Gulf and Caribbean Fisheries Institute

City: Christ Church

Country: Barbados


Management decisions in data-limited fisheries regarding how to adjust fishing pressure, and by how much, can be the most difficult decisions managers must make. Too often, these fisheries are not managed at all or are managed based on standard practices without an adequate scientific basis; this creates a high risk of overfishing and potential loss of economic and social benefits from fisheries. Here, we describe a multi-indicator framework for making fisheries management decisions in data-limited fisheries. The framework is adaptive so that managers can respond to changing environmental, socioeconomic, and fishing conditions. Using stakeholder-defined goals as a foundation, fishery performance indicators are chosen that can be evaluated easily using available data. Reference points are set for each indicator based on fishery goals. Multiple performance indicators from multiple data streams are used to gain a more complete understanding of the fishery and to reduce the implications of uncertainty; corroboration between indicators can allow for a confident interpretation of fishery performance. Data-limited methods can be used to evaluate performance indicators within this framework in lieu of conventional stock assessments. Each year, managers and stakeholders evaluate each performance indicator against the associated reference points, interpret the results using scientific and local knowledge, and adjust management accordingly using pre-defined harvest control rules. A case study is presented that describes the application of this framework to the management of conch and lobster fisheries of Belize.

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