Shaping sustainable harvest boundaries for marine populations despite estimation bias

Abstract

Biased 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 resourcemanagement feedback systems: management strategy evaluation. Using saithe (Pollachius virens), a bottom water, apex predator in the North Sea, as a realworld 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, B trigger , and target exploitation rate, F target ) that maximize yield while keeping stock abundance above a precautionary level. When the biases become too severe, optimized control parameters-for saithe, raising B trigger and lowering F target -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

Transient demographic dynamics of recovering fish populations shaped by past climate variability, harvest, and management

“…Exploited marine fish species are an integral part of an ecosystem and changes in their abundances and demographic structures may propagate through community and ecosystem dynamics (Jennings & Kaiser, 1998), triggering a series of changes in ecologically connected species (Goto, Devine, et al, 2022; Pérez‐Rodríguez et al, 2022). As adult survival improves in historically overharvested populations, ecological processes including resource competition and predation also may indirectly modify vital rates and demographic structures of non‐target species (van Gemert & Andersen, 2018).…”

“…These population assessments form the scientific basis for the implementation of management measures like catch limits. When population size declines below a predefined threshold (a reference point set under the precautionary principle, ICES, 2021; Goto, Devine, et al, 2022), for example, fishing pressure may be adjusted to mitigate the risk of overharvesting. This adaptive management cycle (human–natural system feedback through monitoring, assessment, and management action) thus can be considered a natural experiment (Hilborn & Walters, 1992; Jensen et al, 2012), providing opportunities to gain insights into the transient dynamics of managed populations in variable environments.…”

Transient demographic dynamics of recovering fish populations shaped by past climate variability, harvest, and management

“…These population assessments form the scientific basis for the implementation of management measures like catch limits. When population size declines below a predefined threshold (a reference point set under the precautionary principle, ICES 2021; Goto et al 2022a), for example, fishing pressure may be adjusted to mitigate the risk of overharvesting. This adaptive management cycle (human-natural system feedbacks through monitoring, assessment, and management action) thus can be considered as natural experiment (Hilborn & Walters 1992;Jensen, Branch & Hilborn 2012), providing opportunities to gain insights into the transient dynamics of managed populations in variable environments.…”

“…These population assessments form the scientific basis for the implementation of management measures like catch limits. When population size declines below a predefined threshold (a reference point set under the precautionary principle, ICES 2021; Goto et al . 2022a), for example, fishing pressure may be adjusted to mitigate the risk of overharvesting.…”

Estimating fish mortality rates from catch curves: A plea for the abandonment of Ricker (1975)'s linear regression method

“…Mortality, which can be estimated through different approaches (Lees et al ., 2021; Miranda & Bettoli, 2007), constitutes a pivotal biodemographic component for stock status assessment and population dynamics modeling (Johnson & Zúñiga‐Vega, 2009; Wikström et al ., 2016). Accurately estimating mortality rates is thus of prime importance to avoid any misevaluation of a given fish stock status or potentially producing overoptimistic projections from relying on downwardly biased estimates (Goto et al ., 2022). Here, we advocate that this situation may arise when the linear regression (LR) method of Ricker (1975) is used to estimate mortality from catch‐curve data.…”