Abstract
Understanding factors that influence the success of protected areas in curbing unsustainable resource consumption is essential for determining best management strategies and allocating limited resources to those projects most likely to succeed. I used a law-enforcement and monitoring game-theory model from the political science literature to identify three key variables useful in predicting the success of a protected area: costs of monitoring for rule breakers, benefits of catching a rule breaker, and probability of catching a rule breaker if monitoring. Although assigning exact values for each of these variables was difficult, the variables had a strong predictive capacity even when coded as coarse ordinal values. A model in which such values were used correctly predicted the outcome of 88 of 116 protected areas sampled from the peer-reviewed literature. The model identified a critical zone of common mismatch between protected-area circumstances and management policies. In situations where the costs of monitoring were greater than the product of the probability of catching a rule breaker and the benefit of doing so, conservation was unlikely to succeed. Control of illegal use of protected resources was reported in only 8% of such cases, regardless of strategies to motivate potential users to cooperate with conservation. My model does not prescribe a best management policy for conserving natural resources; rather, it can be used as a tool to help predict whether a proposed management policy will likely succeed in a given situation.
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