Istituto di Scienza e Tecnologie dell'Informazione     
Froese R., Demirel N., Coro G., Kleisner K., Winker H. Estimating fisheries reference points from catch and resilience. In: Fish and Fisheries, vol. 18 (3) pp. 506 - 526. [Online First 18 October 2016] Wiley, 2017.
This study presents a Monte Carlo method (CMSY) for estimating fisheries reference points from catch, resilience and qualitative stock status information on data-limited stocks. It also presents a Bayesian state-space implementation of the Schaefer production model (BSM), fitted to catch and biomass or catch-per-unit-of-effort (CPUE) data. Special emphasis was given to derive informative priors for productivity, unexploited stock size, catchability and biomass from population dynamics theory. Both models gave good predictions of the maximum intrinsic rate of population increase r, unexploited stock size k and maximum sustainable yield MSY when validated against simulated data with known parameter values. CMSY provided, in addition, reasonable predictions of relative biomass and exploitation rate. Both models were evaluated against 128 real stocks, where estimates of biomass were available from full stock assessments. BSM estimates of r, k and MSY were used as benchmarks for the respective CMSY estimates and were not significantly different in 76% of the stocks. A similar test against 28 data-limited stocks, where CPUE instead of biomass was available, showed that BSM and CMSY estimates of r, k and MSY were not significantly different in 89% of the stocks. Both CMSY and BSM combine the production model with a simple stock-recruitment model, accounting for reduced recruitment at severely depleted stock sizes.
URL: http://onlinelibrary.wiley.com/doi/10.1111/faf.12190/full
DOI: 10.1111/faf.12190
Subject Bayesian state-space models
Gibbs sampling
Stock assessment
Monte Carlo methods
Markov Chains

Icona documento 1) Download Document PDF
Icona documento 2) Download Document PDF

Icona documento Open access Icona documento Restricted Icona documento Private


Per ulteriori informazioni, contattare: Librarian http://puma.isti.cnr.it

Valid HTML 4.0 Transitional