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Exploring conflicting management objectives in rebuilding of multi-stock fisheries

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Abstract
Rebuilding depleted fish stocks and preventing the collapse of fisheries are major challenges for most coastal countries. In addition to human-induced factors, interactions between fish stocks within a food web add further complexity to the task of stock rebuilding. In this study we use a stylized bioeconomic model of a multi-stock fishery to study how different management objectives are affected by the nature of stock interactions and to identify potential trade-offs between multiple objectives in stock rebuilding. The results show that the type and strength of stock interactions determine directly the trade-offs between the biological and economic objectives of the fishery as well as the short-term and long-term objectives in stock rebuilding. Compared to a single species perspective, the opportunity cost of hastening the speed of stock rebuilding by reducing the fishing capacity is lower when the depleted stocks have a competitive relationship and higher when the interdependence between the stocks is predatory-prey or mutually beneficial. Our model results further show that stock interactions directly influence whether full or partial rebuilding of depleted stocks is achieved and whether the biomass of rebuilt stocks remains above the management target over time. Even a simple form of competitive or predator-prey interaction can prolong the duration of the rebuilding process and reverse initial rebuilding success or prevent it entirely, underlying the importance of stock interactions for the rebuilding of fisheries
Item Type: | Article |
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Authors/Creators: | Zimmerman, F and Yamazaki, S |
Keywords: | food web interactions, conflicting objectives, rebuilding plan, fisheries management, bioeconomic modelling |
Journal or Publication Title: | Ocean & Coastal Management |
Publisher: | Elsevier Sci Ltd |
ISSN: | 0964-5691 |
DOI / ID Number: | https://doi.org/10.1016/j.ocecoaman.2017.01.014 |
Copyright Information: | Copyright 2017 Elsevier Ltd. |
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