Cadre de modélisation pour l'évaluation du stock de flétan du Groenland (Reinhardtius hippoglossoides) de la sous-zone 0+1 (au large des côtes) de l'Organisation des pêches de l'Atlantique Nord-Ouest et des stratégies de pêche connexes

Abstract

This paper presents an assessment modeling framework that integrates all available fishery monitoring and survey data into a Spatially Implicit Statistical Catch-At-Length (SISCAL) operating model for Northwest Atlantic Fishery Organization (NAFO) Subareas 0+1 (offshore) Greenland Halibut (GH-0+1). The model is subsequently used to provide both an assessment of stock status and productivity as well as a closed loop simulation framework for evaluating GH-0+1 feedback harvest strategies. The SISCAL model fit reasonably well to GH-0+1 data, as determined by standard goodness of fit metrics, although some sensitivities and data issues were noted. The retrospective behaviour of the model was also within reason. Simulation evaluation self-tests also showed that the model was unlikely to be biased over a large number of simulated data sets. After model testing, SISCAL was used to condition a closed-loop simulation framework for testing GH-0+1 management procedures against performance metrics based on NAFO precautionary approach fishery management policy. As an illustrative example, we defined an adaptive model/index-based management procedure that set total allowable catches on a biennial basis, using decision rule parameters that were updated via simulated SISCAL stock assessments every 6 years. Simulated SISCAL stock assessments were fit to historical and simulated catch and biological data from six commercial fleets, differing by nation and gear type, and stock indices and length compositions from three fishery independent surveys. The three surveys included two existing offshore (NAFO Divisions 0A1CD) and inshore (NAFO Divisions 1A to F) research vessel surveys, as well as an additional proposed survey that will begin in 2022 and was assumed to encounter small fish in inshore waters of Divisions 0A and 0B. For comparison, a non-adaptive index-based method was also tested, where decision rule parameters are based off the initial SISCAL model for the entire simulation. The adaptive procedure performed well, keeping biomass above the limit reference point of 𝐵lim = 0.3Bmsy in all simulations, and avoiding the limit fishing mortality rate 𝐹lim = 𝐹msy with high probability. In contrast, the non-adaptive procedure ended up slightly overfishing the GH-0+1 stock, with biomass appearing to continue declining past the end of the simulation. Moreover, the non-adaptive procedure had a roughly neutral probability of exceeding 𝐹lim, making it unacceptable under NAFO policy. We close with recommendations for future work to expand this framework to a full management strategy evaluation, enabling the development of a full harvest strategy for the GH-0+1 fishery consistent with fishery management policy.