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Assessing opportunity and relocation costs of marine protected areas using a behavioural model of longline fleet dynamics
Author(s) -
Dowling Natalie A,
Wilcox Chris,
Mangel Marc,
Pascoe Sean
Publication year - 2012
Publication title -
fish and fisheries
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.747
H-Index - 109
eISSN - 1467-2979
pISSN - 1467-2960
DOI - 10.1111/j.1467-2979.2011.00422.x
Subject(s) - relocation , fishing , profit (economics) , fishery , stock (firearms) , fisheries management , operations research , business , economics , computer science , microeconomics , geography , engineering , archaeology , biology , programming language
Increasing use of spatial management tools in fisheries requires an understanding of fleet response, and in particular to where displaced fishing effort is likely to move. We develop a state‐dependent decision‐making model to address the spatial allocation of effort in an Australian tuna longline fishery. We assume that fishers have an economic objective in deciding where to fish, but that decisions in any period are also influenced by the remaining quota held at the time of the decision. Key features of the model include endogenous price dynamics, a moving stock and a competitive pool of different vessel types operating from different port locations. We utilize this model to illustrate fleet responses to marine reserves and limits on fishing effort. The results illustrate that the model framework provides advantages over statistically based models in that decisions made in response to the imposition of a reserve are not consistent with a proportional reallocation of effort. Rather, the stochastic dynamic model yielded an overall profit level of ∼4% higher relative to scenarios with no reserve. Incorporating the opportunity cost of a quota into the model resulted in an optimal utilization of effort, in which effort was concentrated in time periods and locations yielding maximized profit. Under a low level of effort relative to the season length, the model indicated an overall profit level 43% greater than the highest obtained when the same level of effort was applied solely within any given quarter of the season.