Shaping sustainable harvest boundaries for marine populations despite estimation bias

Abstract

Imperfect knowledge of social–ecological systems can obscure predictability of resource fluctuation and, in turn, lead to erroneous risk assessments and delayed management actions. Systematic error in population status such as persistent overestimation of abundance is a pervasive conservation problem and has plagued assessments of commercial exploitation of marine species, threatening its sustainability.Using North Sea saithe (Pollachius virens)–a demersal (bottom-water) predatory fish–as a real-world case study, we illustrate a precautionary approach to diagnose robustness of harvest rules to persistent estimation bias (overestimated stock abundance and underestimated fishing mortality rate) and to develop alternative protective measures that minimize population depletion (quasi-extinction) risk by propagating known sources of uncertainty (process, observation, and implementation) through closed-loop simulation of resource–management feedback systems (management strategy evaluation, MSE).Analyses showed that the harvest rules set for saithe are robust to a moderate amount (10– 30%) of estimation bias. More severe bias sets overly optimistic catch limits and promotes overexploitation only in the short term; unacceptably high quasi-extinction risks, however, result primarily from progressively amplified amplitudes of catch fluctuation. Although these undesirable outcomes were, to some extent, mitigated by applying a policy tool to suppress catch fluctuation, this tool falls short of being an effective measure to achieve management goals.More consistent performance of management measures was achieved by developing and applying more precautionary harvest rules through MSE by explicitly accounting for bias. When bias became more severe, raising threshold abundance (by 8–24%) that triggers management actions and lowering target exploitation rate (by 6–29%) would not only safeguard against overexploitation and depletion but also provide catch stability (less disruption in fishing operations).We show that the precautionary approach to risk management through MSE offers a powerful tool to set safe harvest boundaries when assessments are persistently biased. Given challenges in identifying the sources, we suggest bias be routinely evaluated through MSE, and alternative measures be developed to set catch limits when needed. By explicitly accounting for key sources of uncertainty in managing commercial exploitation, our proposed approach ensures effective conservation and sustainable exploitation of living marine resources even under profound uncertainty.

Risk equivalence in data‐limited and data‐rich fisheries management: An example based on the ICES advice framework

“…For the three case study stocks considered in this study, model fits of the state‐space SAM model (Nielsen & Berg, 2014) were readily available and allowed the rapid conditioning of OMs. SAM is increasingly used in Europe (despite occasional criticism such as Aldrin et al, 2019) and could facilitate MSE development for many stocks, and has already been used by ICES (2019b, 2020b) and Goto et al (2022). However, for most data‐limited stocks, the data required to fit such a model are typically unavailable.…”

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…”

“…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), This article reports a study that empirically explores how past fishing, management action, and climate variability influenced the transient dynamics of recovering fish populations in the northeast Atlantic Ocean (FAO Major Fishing Area 27, Figure 1a).…”