Developing and evaluating a management strategy evaluation framework for the Gulf of Maine cod (Gadus morhua)

Ming Sun, Yunzhou Li, Yiping Ren and Yong Chen

Ecological Modelling, 2019, vol. 404, issue C, 27-35

Abstract: Management strategy evaluation (MSE) is an effective tool to evaluate the performance of harvest control rules (HCRs) and alternative management strategies. However, a comprehensive MSE framework advising management is still absent for the severely depleted Gulf of Maine (GoM) cod (Gadus morhua). In the present study, we developed a conceptual MSE framework and conditioned on this stock utilizing stock-specific parameterization. We highlighted the simulation of a few key processes with semi-independent sub-models and accounted for uncertainties from multiple sources. The simulated population dynamics was calibrated and validated against the historical trend in hindcasting. Forecasting simulations were also conducted and validated to examine the effectiveness in the context of uncertainty. Hindcasting results suggested that the calibrated MSE framework could capture the stock dynamics assuming different recruitment dynamics indicated by residuals lower than 5%. Forecasting stochastic runs demonstrated a minor disparity between management effects of fishing-mortality-based and catch-based HCRs when the segregated stock recruitment relationship was adopted with a difference in simulated spawning stock biomass lower than 10%. Additionally, the results were comparable to assessment and projections made in the stock assessment, indicating the robustness of the framework. The framework can potentially help disentangle complex issues related to the mixed fishery, decision-making, and performance evaluation of a monitoring system.

Keywords: Fishery management; Management strategy evaluation; Harvest control rules; Uncertainty (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:404:y:2019:i:c:p:27-35

DOI: 10.1016/j.ecolmodel.2019.04.007

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