Implementing the precautionary approach into fisheries management: Biomass reference points and uncertainty buffers

Tobias K. Mildenberger*, Casper W. Berg, Alexandros Kokkalis, Adrian R. Hordyk, Chantel Wetzel, Nis S. Jacobsen, André E. Punt, J. Rasmus Nielsen

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

The precautionary approach to fisheries management advocates for risk-averse management strategies that include biological reference points and account for scientific uncertainty (i.e. process, model and observation uncertainty). In this regard, two approaches have been recommended: (a) biomass reference points to safeguard against low stock biomass, and (b) uncertainty buffers that reduce the catch limit as a function of the scientific uncertainty. This study compares the effectiveness of these two precautionary approaches in recovering over-exploited fish stocks. We evaluate the performance of more than 80 harvest control rules (HCRs) within a stochastic management strategy evaluation (MSE) framework for three stocks with contrasting life-history parameters and under various levels of scientific uncertainty. The results show that both approaches reduce the risk of overfishing at the expense of expected yield. This risk-yield trade-off strongly depends on the HCRs, life-history parameters of the species, as well as the level of the scientific uncertainty. Nevertheless, some combinations of biomass threshold and limit reference points as well as uncertainty buffers lead to a more favourable risk-yield trade-off than other rules. This study elucidates the multiple factors affecting the effectiveness of management strategies and highlights key features of HCRs for precautionary fisheries management.
Original languageEnglish
JournalFish and Fisheries
Number of pages20
ISSN1467-2960
DOIs
Publication statusAccepted/In press - 2021

Keywords

  • Harvest control rules (HRCs)
  • Management procedures
  • Management strategy evaluation (MSE)
  • Risk assessment
  • Scientific uncertainty

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