Optimal harvesting policy of an inland fishery resource under incomplete information

Hidekazu Yoshioka, Yuta Yaegashi, Yumi Yoshioka and Kentaro Tsugihashi

Applied Stochastic Models in Business and Industry, 2019, vol. 35, issue 4, 939-962

Abstract: A new mathematical model for finding the optimal harvesting policy of an inland fishery resource under incomplete information is proposed in this paper. The model is based on a stochastic control formalism in a regime‐switching environment. The incompleteness of information is due to uncertainties involved in the body growth rate of the fishery resource: a key biological parameter. Finding the most cost‐effective harvesting policy of the fishery resource ultimately reduces to solving a terminal and boundary value problem of a Hamilton‐Jacobi‐Bellman equation: a nonlinear and degenerate parabolic partial differential equation. A simple finite difference scheme for solving the equation is then presented, which turns out to be convergent and generates numerical solutions that comply with certain theoretical upper and lower bounds. The model is finally applied to the management of Plecoglossus altivelis, a major inland fishery resource in Japan. The regime switching in this case is due to the temporal dynamics of benthic algae, the main food of the fish. Model parameter values are identified from field measurement results in 2017. Our computational results clearly show the dependence of the optimal harvesting policy on the river environmental and biological conditions. The proposed model would serve as a mathematical tool for fishery resource management under uncertainties.

Date: 2019
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https://doi.org/10.1002/asmb.2428

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Persistent link: https://EconPapers.repec.org/RePEc:wly:apsmbi:v:35:y:2019:i:4:p:939-962

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