PLOS ONE2013-11-19 1:15 AM

Confronting Uncertainty in Wildlife Management: Performance of Grizzly Bear Management 野生动物管理考虑不确定性:棕熊管理效率研究

Abstract Scientific management of wildlife requires confronting the complexities of natural and social systems. Uncertainty poses a central problem. Whereas the importance of considering uncertainty has been widely discussed, studies of the effects of unaddressed uncertainty on real management systems have been rare. We examined the effects of outcome uncertainty and components of biological uncertainty on hunt management performance, illustrated with grizzly bears (Ursus arctos horribilis) in British Columbia, Canada. We found that both forms of uncertainty can have serious impacts on management performance. Outcome uncertainty alone – discrepancy between expected and realized mortality levels – led to excess mortality in 19% of cases (population-years) examined. Accounting for uncertainty around estimated biological parameters (i.e., biological uncertainty) revealed that excess mortality might have occurred in up to 70% of cases. We offer a general method for identifying targets for exploited species that incorporates uncertainty and maintains the probability of exceeding mortality limits below specified thresholds. Setting targets in our focal system using this method at thresholds of 25% and 5% probability of overmortality would require average target mortality reductions of 47% and 81%, respectively. Application of our transparent and generalizable framework to this or other systems could improve management performance in the presence of uncertainty. 论文摘要 野生动物的科学管理需要考虑自然和社会系统的复杂性。不确定性是最大的问题。考虑不确定性的重要性被广泛讨论,而未知的不确定性对真实管理系统的作用的研究却并不多见。以加拿大不列颠哥伦比亚省的棕熊为例, 我们测试了结果不确定性和生物不确定性对狩猎管理绩效的影响。 我们发现这两种不确定性可以对管理绩效产生严重的影响。 结果不确定性-预期和真实死亡率水平的差异-导致在19%的观测年份内出现超额死亡率。 统计预期生物变量(比如生物不确定性)不确定性后发现将近70%的观测年份死亡率也许已经超额。 我们提供了一种统一的方法来为管理的物种确定目标,这个目标值既会考虑不确定性也将允许存在一定阀值内的死亡率超限的可能性。 用这种方法在我们的核心系统设置25%的阀值和5%的超额死亡率可能性作为目标值将分别需要47%到81%的平均目标死亡率的减少。 将我们这一透明而统一的框架应用到这个或者其他的系统将提高不确定性存在的情况下的野生动物管理绩效。

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