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On implementing maximum economic yield in commercial fisheries
Economists have long argued that a fishery that maximizes its economic potential usually will also satisfy its conservation objectives. Recently, maximum economic yield (MEY) has been identified as a primary management objective for Australian fisheries and is under consideration elsewhere. However,...
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Published in: | Proceedings of the National Academy of Sciences - PNAS 2010-01, Vol.107 (1), p.16-21 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Economists have long argued that a fishery that maximizes its economic potential usually will also satisfy its conservation objectives. Recently, maximum economic yield (MEY) has been identified as a primary management objective for Australian fisheries and is under consideration elsewhere. However, first attempts at estimating MEY as an actual management target for a real fishery (rather than a conceptual or theoretical exercise) have highlighted some substantial complexities generally unconsidered by fisheries economists. Here, we highlight some of the main issues encountered in our experience and their implications for estimating and transitioning to MEY. Using a bioeconomic model of an Australian fishery for which MEY is the management target, we note that unconstrained optimization may result in effort trajectories that would not be acceptable to industry or managers. Different assumptions regarding appropriate constraints result in different outcomes, each of which may be considered a valid MEY. Similarly, alternative treatments of prices and costs may result in differing estimates of MEY and their associated effort trajectories. To develop an implementable management strategy in an adaptive management framework, a set of assumptions must be agreed among scientists, economists, and industry and managers, indicating that operationalizing MEY is not simply a matter of estimating the numbers but requires strong industry commitment and involvement. |
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ISSN: | 0027-8424 1091-6490 |
DOI: | 10.1073/pnas.0912091107 |