Using the best of two worlds: A bio‐economic stock assessment (BESA) method using catch and price data

• Published in: Fish and fisheries (Oxford, England) Vol. 24; no. 5; pp. 744 - 758
• Main Authors: Lancker, Kira, Voss, Rudi, Zimmermann, Fabian, Quaas, Martin F.
• Format: Journal Article
• Language: English
• Published: Oxford Blackwell Publishing Ltd 01.09.2023
• Subjects: Bayesian analysis; Bayesian estimation; Benchmarks; data‐poor; Econometric models; Economic analysis; Economic models; Economics; Estimation; Extended Kalman filter; Fisheries; Fisheries management; Fishery data; Fishery management; Kalman filter; Kalman filters; Marine crustaceans; Mathematical models; open access; Parameters; Probability theory; state space modeling; Stock assessment; Stocks; Sustainable fisheries
• ISSN: 1467-2960; 1467-2979
• DOI: 10.1111/faf.12759

Reliable stock assessments are essential for successful and sustainable fisheries management. Advanced stock assessment methods are expensive, as they require age‐ or length‐structured catch and detailed fishery‐independent data, which prevents their widespread use, especially in developing regions. Furthermore, modern fisheries management increasingly includes socio‐economic considerations. Integrated ecological‐economic advice can be provided by bio‐economic models, but this requires the estimation of economic parameters. To improve accuracy of data‐limited stock assessment while jointly estimating biological and economic parameters, we propose to use price data, in addition to catches, in a new bio‐economic stock assessment (‘BESA’) approach for de‐facto open access stocks. Price data are widely available, also in the Global South. BESA is based on a state‐space approach and uncovers biomass dynamics by use of the extended Kalman filter in combination with Bayesian estimation. We show that estimates for biological and economic parameters can be obtained jointly, with reliability gains for the stock assessment from the additional information inherent in price data, compared to alternative assessment methods for data‐poor stocks. In a real‐world application to Barents Sea shrimp (Pandalus borealis, Pandalidae), we show that BESA benchmarks well also against advanced stock assessment results. BESA can thus be both a stand‐alone approach for currently unassessed stocks as well as a complement to other available methods by providing bio‐economic information for advanced fisheries management.