Abstract
AbstractBiased estimates of population status are a pervasive conservation problem. This problem has plagued assessments of commercial exploitation of marine species and can threaten the sustainability of both populations and fisheries. We develop a computer‐intensive approach to minimize adverse effects of persistent estimation bias in assessments by optimizing operational harvest measures (harvest control rules) with closed‐loop simulation of resource‐management feedback systems: management strategy evaluation. Using saithe (Pollachius virens), a bottom water, apex predator in the North Sea, as a real‐world case study, we illustrate the approach by first diagnosing robustness of the existing harvest control rule and then optimizing it through propagation of biases (overestimated stock abundance and underestimated fishing pressure) along with select process and observation uncertainties. Analyses showed that severe biases lead to overly optimistic catch limits and then progressively magnify the amplitude of catch fluctuation, thereby posing unacceptably high overharvest risks. Consistent performance of management strategies to conserve the resource can be achieved by developing more robust control rules. These rules explicitly account for estimation bias through a computational grid search for a set of control parameters (threshold abundance that triggers management action, Btrigger, and target exploitation rate, Ftarget) that maximize yield while keeping stock abundance above a precautionary level. When the biases become too severe, optimized control parameters—for saithe, raising Btrigger and lowering Ftarget—would safeguard against a overharvest risk (<3.5% probability of stock depletion) and provide short‐term stability in catch limit (<20% year‐to‐year variation), thereby minimizing disruption to fishing communities. The precautionary approach to fine‐tuning adaptive risk management through management strategy evaluation offers a powerful tool to better shape sustainable harvest boundaries for exploited resource populations when estimation bias persists. By explicitly accounting for emergent sources of uncertainty, our proposed approach ensures effective conservation and sustainable exploitation of living marine resources even under profound uncertainty.
Highlights
Managers and policymakers increasingly face trade-offs in sustainably managing extractive use of living marine resources while effectively conserving biodiversity under the precautionary principle (FAO 1996, Hilborn et al 2001, Harwood and Stokes 2003)
We evaluate how robust current management procedures are to persistent estimation bias, and demonstrate how management procedures can remain precautionary through the optimization of harvest control rules to avert mismanagement–setting overly optimistic catch limits that promote stock depletion and a future fishery closure
The framework consists of submodels that simulate 1) true population and harvest dynamics at sea, from which observations through monitoring surveys and catch reporting are made, and 2) management processes–assessments based on observations from the surveys and reported catch and subsequent decision making (Fig. 1a, Punt et al 2016)
Summary
Managers and policymakers increasingly face trade-offs in sustainably managing extractive use of living marine resources while effectively conserving biodiversity under the precautionary principle (FAO 1996, Hilborn et al 2001, Harwood and Stokes 2003). Scientific uncertainty (imprecision in measurements) of current population status can obscure the assessment of decline or extinction threats (Ripa and Lundberg 1996, Ovaskainen and Meerson 2010). Assessments of current population status provide a scientific basis for setting a threshold for safe harvest to prevent the decline of fish stocks. This approach may include using biological thresholds such as the population abundance that produces maximum sustainable yield (Beddington et al 2007). Accurate population assessments contribute to successful implementation of management measures to sustain longterm commercial exploitation of fish populations (Hilborn et al 2020). Overestimated abundance and underestimated exploitation rates, which often heighten extinction risk, have led to some historical collapses of oceanic predators
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