期刊
ECOLOGICAL APPLICATIONS
卷 19, 期 1, 页码 198-205出版社
WILEY
DOI: 10.1890/07-1641.1
关键词
Bayesian decision analysis; harvest models; maximum likelihood; modeling a semelparous species; natural-resource management; optimal model complexity; Ricker model equations
资金
- NSF [9905197]
- Gordon and Betty Moore Foundation
- Divn Of Social and Economic Sciences
- Direct For Social, Behav & Economic Scie [9905197] Funding Source: National Science Foundation
Previous studies have shown that, for managing harvest of natural resources, overly complex models perform poorly. Decision-analytic approaches treat uncertainly differently from the maximum-likelihood approaches these studies employed. By simulation using a simple. sheries model, I show that decision-analytic approaches to managing harvest also can suffer from using overly complex models. Managers using simpler models can outperform managers using more complex models, even if the more complex models are correct and even if their use allows the incorporation of additional relevant information. Decision-analytic approaches outperformed maximum-likelihood approaches in my simulations, even when Bayesian priors were uninformative.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据