Show simple item record

dc.contributor.authorWhite, Kascia
dc.date.accessioned2016-02-03T01:50:06Z
dc.date.available2016-02-03T01:50:06Z
dc.date.issued2015-11-23
dc.identifier.urihttp://hdl.handle.net/10222/70750
dc.description.abstractThe 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.en_US
dc.language.isoenen_US
dc.subjectBermudaen_US
dc.subjectshallow water snapperen_US
dc.subjectdata-limited fisheriesen_US
dc.subjectadaptive managementen_US
dc.subjectfisher knowledgeen_US
dc.subjectLane snapperen_US
dc.subjectGrey snapperen_US
dc.subjectYellowtail snapperen_US
dc.subjectecosystem-based fisheries managementen_US
dc.subjectFISHE frameworken_US
dc.subjectcomplianceen_US
dc.subjectenforcementen_US
dc.titleApplying Adaptive Management Approaches to Data Limited Fisheries: The Case of Bermuda’s Shallow Water Snapper Species [graduate project].en_US
dc.typeOther
 Find Full text

Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record