Development of a stochastic bioeconomic model for the red octopus fishery on the Yucatan Peninsula: Implications for management

Abstract

Although much effort has been dedicated to the management of the red octopus fishery on the Yucatan Peninsula (Mexico), managers have yet to incorporate economic aspects to ensure sustainable and profitable exploitation of this fishery resource. We developed a bioeconomic model that incorporated the uncertainty for the r and K parameters. We fit 3 models (Schaefer, Fox, and Pella–Tomlinson) to abundance index survey data and used the Akaike information criterion for model selection. The best fit corresponded to the Schaefer model. We built deterministic and stochastic versions of the Gordon–Schaefer model. Economic data (costs and prices) were determined from inter[1]views with fishermen. To estimate the posterior distributions of parameters and indicators, we used Bayesian methods with Markov chain Monte Carlo (MCMC) simulations. The deterministic results suggested that the maximum sustainable income was Mex$851.70 million, with a fishing effort of 3,650 fishing boats, while the maximum sustainable profit was $390.8 million, with a fishing effort of 2,472 fishing boats. The equilibrium point corresponded to an effort of 4,945 fishing boats. Regarding the stochastic model, the MCMC simulation results suggest that the maximum sustainable income distribution was not normal; its average was $856.1 million (SE 1.8) and the most likely value was $849.50 million. The most likely fishing effort at equilibrium was 4,970 fishing boats. Our results suggest the fishery could be operating close to the economic equilibrium point; if this is the case, fishing effort must decrease in order for annual profit to increase. Our approach will help make periodical re-evaluations of the fishery and establish management strategies to ensure the profitable and sustainable exploitation of the red octopus on the Yucatan Peninsula.