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Accounting for potential nonlinearity between catch and effort using meta-analysis and applying GLM and GLMM to fishing data from deployments of fixed and mobile gear

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dc.contributor.supervisor Gillis, Darren (Biological sciences) en_US
dc.contributor.author Aljafary, Michelle
dc.date.accessioned 2016-04-12T19:44:19Z
dc.date.available 2016-04-12T19:44:19Z
dc.date.issued 2016
dc.identifier.uri http://hdl.handle.net/1993/31208
dc.description.abstract My thesis examines nonlinearity between catch and effort. I use a meta-analysis of published literature and generalized linear mixed-effects models (GLMM) on both fixed and mobile gear fisheries of Atlantic Canada. The meta-analysis examines the proportionality of catch to effort using the slope of the reduced major axis (RMA) log-log regression, which accounts for “errors-in-variables”. The GLMMs explored proportionality while accounting for variation among fishing vessels. Both analyses found evidence for disproportionality between catch and effort. Catch that increases disproportionally to effort could result from either facilitation or recruitment of effort into the fishery. Catch increases that are less than proportional are expected from competitive interactions among fishers or gear saturation. The GLMM also revealed that the level of aggregation (by set, trip, monthly, or annually) can affect the apparent proportionality between catch and effort. In general, catch and effort should not be considered to be proportional. en_US
dc.subject meta-analysis, generalized linear mixed-effects model (GLMM), catch, effort, error-in-variables, proportionality, disproportionality, mixed effects, RMA, OLS, aggregation. en_US
dc.title Accounting for potential nonlinearity between catch and effort using meta-analysis and applying GLM and GLMM to fishing data from deployments of fixed and mobile gear en_US
dc.degree.discipline Biological Sciences en_US
dc.contributor.examiningcommittee Davoren, Gail (Biological sciences) Muthukumarana, Saman (Statistics) en_US
dc.degree.level Master of Science (M.Sc.) en_US
dc.description.note May 2016 en_US


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