Applying Adaptive Management Approaches to Data Limited Fisheries: The Case of Bermuda’s Shallow Water Snapper Species [graduate project].
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The sustainable management of ecosystems, marine resources, and resource users is essential to ensure ecosystem health and resilience. A vast majority of global fish stocks lack adequate data to determine fish stock health using conventional fish stock assessment methods. These fisheries are often left unmanaged causing dramatic declines in fisheries health and potential economic and socio-cultural losses to coastal communities. To address these data limitations, fisheries managers are incorporating data-limited methodologies to scientifically assess fish stocks, estimate overfishing and set catch limits. With the dynamic nature of the natural environment, it is important that management strategies are adaptive and continually restructured. With limited biological data available for the shallow water snapper species in Bermuda, and limited resources to collect additional data, new methods of managing these species need to be considered. This research examines the options for adaptively managing Bermuda’s shallow water snapper species by incorporating fishers’ knowledge with current data-limited approaches.