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dc.contributor.authorHintzen, N.T.*
dc.contributor.authorRoel, B.*
dc.contributor.authorBenden, D.*
dc.contributor.authorClarke, M.*
dc.contributor.authorEgan, A.*
dc.contributor.authorNash, R.D.M.*
dc.contributor.authorRohlf, N.*
dc.contributor.authorHatfield, E.M.C.*
dc.date.accessioned2015-04-24T11:02:07Z
dc.date.available2015-04-24T11:02:07Z
dc.date.issued2014
dc.identifier.citationHintzen, N. T., Roel, B., Benden, D., Clarke, M., Egan, A., Nash, R. D. M., … Hatfield, E. M. C. (2014). Managing a complex population structure: exploring the importance of information from fisheries-independent sources. ICES Journal of Marine Science, 72(2), 528–542. doi:10.1093/icesjms/fsu102en_GB
dc.identifier.issn1095-9289
dc.identifier.urihttp://hdl.handle.net/10793/1076
dc.descriptionPeer-reviewed. This is a pre-copy-editing, author-produced PDF of an article accepted for publication in ICES Journal of Marine Science following peer review. The definitive publisher-authenticated version is available online at: doi: 10.1093/icesjms/fsu102en_GB
dc.description.abstractNatural resource managers aim to manage fish stocks at sustainable levels. Often, management of these stocks is based on the results of analytical stock assessments. Accurate catch data, which can be attributed to a specific population unit and reflects the population structure, are needed for these approaches. Often though, the quality of the catch data is compromised when dealing with a complex population structure where fish of different population units mix in a fishery. The herring population units west of the British Isles are prone to mixing. Here, the inability to perfectly allocate the fish caught to the population unit they originate from, due to classification problems, poses problems for management. These mixing proportions are often unknown; therefore, we use simulation modelling combined with management strategy evaluation to evaluate the role fisheries-independent surveys can play in an assessment to provide unbiased results, irrespective of population unit mixing and classification success. We show that failure to account for mixing is one of the major drivers of biased estimates of population abundance, affecting biomass reference points and MSY targets. When mixing of population units occurs, the role a survey can play to provide unbiased assessment results is limited. Either different assessment models should be employed or stock status should be considered from the survey data alone. In addition, correctly classifying the origin of fish is especially important for those population units that are markedly smaller in size than other units in the population complex. Without high classification success rates, smaller population units are extremely vulnerable to overexploitation.en_GB
dc.description.sponsorshipFunder: Marine Instituteen_GB
dc.language.isoenen_GB
dc.publisherOxford University Pressen_GB
dc.relation.ispartofseriesICES Journal of Marine Science;72(2), 528-542
dc.subjectAtlantic Herringen_GB
dc.subjectBritish Islesen_GB
dc.subjectClassificationen_GB
dc.subjectClupea harengusen_GB
dc.subjectFLRen_GB
dc.subjectmanagement strategy evaluationen_GB
dc.subjectMixingen_GB
dc.subjectscientific surveyen_GB
dc.subjectStock structureen_GB
dc.titleManaging a complex population structure: exploring the importance of information from fisheries-independent sourcesen_GB
dc.typeArticleen_GB
refterms.dateFOA2018-01-12T03:02:59Z


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