An Evaluation of Harvest Control Rules for Data-Poor Fisheries

John Wiedenmann, Michael J. Wilberg, Thomas J. Miller

Research output: Contribution to journalArticlepeer-review

35 Scopus citations

Abstract

For federally managed fisheries in the USA, National Standard 1 requires that an acceptable biological catch be set for all fisheries and that this catch avoid overfishing. Achieving this goal for data-poor stocks, for which stock assessments are not possible, is particularly challenging. A number of harvest control rules have very recently been developed to set sustainable catches in data-poor fisheries, but the ability of most of these rules to avoid overfishing has not been tested. We conducted a management strategy evaluation to assess several control rules proposed for data-poor situations. We examined three general life histories ("slow," "medium," and "fast") and three exploitation histories (under-, fully, and overexploited) to identify control rules that balance the competing objectives of avoiding overfishing and maintaining high levels of harvest. Many of the control rules require information on species life history and relative abundance, so we explored a scenario in which unbiased knowledge was used in the control rule and one in which highly inflated estimates of stock biomass were used. Our analyses showed that no single control rule performed well across all scenarios, with those that performed well in the unbiased scenario performing poorly in the biased scenarios and vice versa. Only the most conservative data-poor control rules limited the probability of overfishing across most of the life history and exploitation scenarios explored, but these rules typically required very conservative catches under the unbiased scenarios.

Original languageEnglish (US)
Pages (from-to)845-860
Number of pages16
JournalNorth American Journal of Fisheries Management
Volume33
Issue number4
DOIs
StatePublished - Aug 2013

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Aquatic Science
  • Ecology
  • Management, Monitoring, Policy and Law

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