Abstract

ABSTRACT Global fisheries face significant challenges in the coming years due to climate change. Understanding and anticipating the impacts of climate change is a necessity for implementing appropriate fisheries management. This study uses a panel dataset of individual fishing vessels to examine how variation in ocean temperature affects fish harvest. Using the American lobster (Homarus americanus) fishery in the Maritimes region of Canada as a case study, this paper employs a generalised linear mixed model (GLMM) taking into account heterogeneity amongst fishers, gear, vessels, and fishing areas. The GLMM is found to have better performance and estimations when compared against alternative specifications. As expected, a significant and positive relationship was found, further contributing to the existing evidence of warming impacts on the lobster fishery. The implications of this study are twofold: first, it provides further evidence that environmental change does have a significant positive impact on harvest. This information should be considered by fishing industry and fisheries authorities when implementing appropriate adaptive management strategies and measures in their decision making. Second, it illustrates that allowing for mixed-effects using GLMMs is a valuable empirical tool when dealing with hierarchical data structures.

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