期刊
ECOLOGICAL ECONOMICS
卷 86, 期 -, 页码 78-85出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.ecolecon.2012.09.017
关键词
Forest pathogens; Surveillance; Optimal management; Uncertainty; Ceratocystis fagacearum
资金
- U.S. Forest Service
- Northern Research Station
- Minnesota Agricultural Experiment Station
- Economic Research Service's (USDA) PREISM economics of invasive species management program [58-7000-6-0081]
Cost-effective strategies are needed to find and remove diseased trees in forests damaged by pathogens. We develop a model of cost-minimizing surveillance and control of forest pathogens across multiple sites where there is uncertainty about the extent of the infestation in each site and when the goal is to minimize the expected number of new infections. We allow for a heterogeneous landscape, where grid cells may be differentiated by the number of trees, the expected number of infected trees, rates of infection growth, and costs of surveillance and control. In our application to oak wilt in Anoka County, Minnesota, USA, we develop a cost curve associated with saving healthy trees from infection. Assuming an annual infection growth rate of 8%, a $1 million budget would save an expected 185 trees from infection for an average of $5400 per tree. We investigate how more precise prior estimates of disease and reduced detection sensitivity affect model performance. We evaluate rules of thumb, finding that prioritizing sites with high proportions of infected trees is best. Our model provides practical guidance about the spatial allocation of surveillance and control resources for well-studied forest pathogens when only modest information about their geographic distribution is available. (C) 2012 Elsevier B.V. All rights reserved.
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