期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2016
卷号：113
期号：13
页码：3563-3566
DOI：10.1073/pnas.1525085113
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：Listing endangered and threatened species under the US Endangered Species Act is presumed to offer a defense against extinction and a solution to achieve recovery of imperiled populations, but only if effective conservation action ensues after listing occurs. The amount of government funding available for species protection and recovery is one of the best predictors of successful recovery; however, government spending is both insufficient and highly disproportionate among groups of species, and there is significant discrepancy between proposed and actualized budgets across species. In light of an increasing list of imperiled species requiring evaluation and protection, an explicit approach to allocating recovery funds is urgently needed. Here I provide a formal decision-theoretic approach focusing on return on investment as an objective and a transparent mechanism to achieve the desired recovery goals. I found that less than 25% of the $1.21 billion/year needed for implementing recovery plans for 1,125 species is actually allocated to recovery. Spending in excess of the recommended recovery budget does not necessarily translate into better conservation outcomes. Rather, elimination of only the budget surplus for “costly yet futile” recovery plans can provide sufficient funding to erase funding deficits for more than 180 species. Triage by budget compression provides better funding for a larger sample of species, and a larger sample of adequately funded recovery plans should produce better outcomes even if by chance. Sharpening our focus on deliberate decision making offers the potential to achieve desired outcomes in avoiding extinction for Endangered Species Act-listed species.
关键词：endangered species ; conservation triage ; conservation prioritization ; return on investment ; cost
