A model-based approach to incorporate environmental variability into assessment of a commercial fishery: a case study with the American lobster fishery in the Gulf of Maine and Georges Bank

• Published in: ICES Journal of Marine Science
• Main Authors: Tanaka, Kisei R, Cao, Jie, Shank, Burton V, Truesdell, Samuel B, Mazur, Mackenzie D, Xu, Luoliang, Chen, Yong
• Other Authors: Anderson, Emory
• Format: Article in Journal/Newspaper
• Language: English
• Published: Oxford University Press (OUP) 2019
• Subjects: Northwest Atlantic
• Online Access: http://dx.doi.org/10.1093/icesjms/fsz024; http://academic.oup.com/icesjms/article-pdf/76/4/884/31238870/fsz024.pdf

Abstract Changes in bottom-up forcing are fundamental drivers of fish population dynamics. Recent literature has highlighted the need to incorporate the role of dynamic environmental conditions in stock assessments as a key step towards adaptive fishery management. Combining a bioclimate envelope model and a population dynamic model, we propose a model-based approach that can incorporate ecosystem products into single-species stock assessments. The framework was applied to a commercially important American lobster (Homarus americanus) stock in the Northwest Atlantic. The bioclimate envelope model was used to hindcast temporal variability in a lobster recruitment habitat suitability index (HSI) using bottom temperature and salinity. The climate-driven HSI was used to inform the lobster recruitment dynamics within the size-structured population dynamics model. The performance of the assessment model with an environment-explicit recruitment function is evaluated by comparing relevant assessment outputs such as recruitment, annual fishing mortality, and magnitude of retrospective biases. The environmentally-informed assessment model estimated (i) higher recruitment and lower fishing mortality and (ii) reduced retrospective patterns. This analysis indicates that climate-driven changes in lobster habitat suitability contributed to increased lobster recruitment and present potential improvement to population assessment. Our approach is extendable to other stocks that are impacted by similar environmental variability.