Do accurate stock estimates increase harvest and reduce variability in fisheries yields?

Myrseth, J., Enberg, K., Heino, M. ORCID: https://orcid.org/0000-0003-2928-3940, & Fiksen, O. (2011). Do accurate stock estimates increase harvest and reduce variability in fisheries yields? Natural Resource Modeling 24 (2) 222-241. 10.1111/j.1939-7445.2011.00089.x.

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Abstract

Fisheries managers normally make decisions based on stock abundance estimates subject to process, observation, and model uncertainties. Considerable effort is invested in gathering information about stock size to decrease these uncertainties. However, few studies have evaluated benefits from collecting such information in terms of yield and stability of annual harvest. Here, we develop a strategic age-structured population model for a long-lived fish with stochastic recruitment, resembling the Norwegian spring-spawning herring (NSSH, Clupea harengus L.). We evaluate how uncertainties in population estimates influence annual yield, spawning stock biomass (SSB), and variation in annual harvest, using both the proportional threshold harvesting (PTH) and the current harvest control rule for NSSH as harvest strategies. Results show that the consequences of a biased estimate are sensitive to the harvest strategy employed. If the harvest strategy is suitably chosen, the benefits of accurate information are low, and less information about the stock is necessary to maintain high average yield. Reduced harvest intensity effectively removes the need for accurate stock estimates. PTH (a variant of the constant escapement strategy) with low harvest ratio and the current NSSH harvest control rule both provide remarkable stability in yield and SSB. However, decreased uncertainty will often decrease year-to-year variation in harvest and the frequency of fishing moratoria.

Item Type:	Article
Uncontrolled Keywords:	Age-structured model; Management strategy evaluation; Multiple uncertainty; Norwegian spring-spawning herring; Optimal harvesting
Research Programs:	Evolution and Ecology (EEP)
Bibliographic Reference:	Natural Resource Modeling; 24(2):222-241 (May 2011) (Published online 22 March 2011)
Depositing User:	IIASA Import
Date Deposited:	15 Jan 2016 08:45
Last Modified:	27 Aug 2021 17:21
URI:	https://pure.iiasa.ac.at/9608

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