Combined modeling of fish behavior and fishing operations for conger eel fishery in Ise Bay

Shigeru Tabeta, Shota Suzuki and Yoshiharu Nakamura

Ecological Modelling, 2015, vol. 313, issue C, 266-275

Abstract: In order to simulate the conger eel (Conger myriaster) fishery in Ise Bay, a typical semi-enclosed bay in Japan, we developed a fishery simulator that consists of a fish behavioral model and a fishing operations model. The fish behavioral model considers the migration effect as well as the growth rate of individuals and changes in population size. In the behavioral model with migration, the direction of fish movement is determined by the preference intensities for the environmental factors of water temperature and dissolved oxygen. The change in population size is calculated by using a general population dynamics model considering natural and fishing mortalities. In the first step, the fishing mortality was estimated by the actual fish catch data. Studies have clarified that environmental conditions such as oxygen-deficient water in summer have a large influence on the migration and distribution of C. myriaster. Although the simulated catch per unit effort (CPUE) based on actual fishing operations data was able to describe general features of the annual variability, some improvement of the model will be necessary for more accurate prediction. In the next step, the fish behavioral model was combined with a fishing operations model, which predicts the behavior of trawling boats based on economic conditions and resource distribution. The combined model reproduced the boats’ fishing locations and their fish catch amounts well. The model was applied to evaluate the effects of fishery management and clarified that the control of fine-net use is an effective means to increase the fishery profit.

Keywords: Fish migration; Fishing operation; Conger myriaster; Ise Bay; Bottom otter trawling (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:313:y:2015:i:c:p:266-275

DOI: 10.1016/j.ecolmodel.2015.06.043

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