Testing Decision Rules for Categorizing Species’ Extinction Risk to Help Develop Quantitative Listing Criteria for the U.S. Endangered Species Act

Abstract

Lack of guidance for interpreting the definitions of endangered and threatened in the U.S. Endangered Species Act (ESA) has resulted in case-by-case decision making leaving the process vulnerable to being considered arbitrary or capricious. Adopting quantitative decision rules would remedy this but requires the agency to specify the relative urgency concerning extinction events over time, cutoff risk values corresponding

Effects of uncertainty and variability on population declines and IUCN Red List classifications

“…(), Regan et al. (), and Connors et al. () evaluated the impact of different sources of uncertainty in PVA in the context of decision making.…”

A Tale of Two Acts: Endangered Species Listing Practices in Canada and the United States

“…We agree with the NRC (1995), DeMaster and colleagues (2004), Cochrane and colleagues (2011), and others, who have called for clear legal or policy guidance regarding the interpretation of the ambiguous ESA definitions of threatened and endangered species. For example, the USFWS and the NMFS could adopt a policy stipulating that, for the purposes of the ESA, an endangered species is one that has a certain probability of extinction within a certain number of years, and a threatened species has a certain probability of becoming endangered within a certain number years; alternatively, more sophisticated permutations could be framed in decision-analytic terms (DeMaster et al 2004, Regan et al 2013. Providing specific thresholds that define the degree of risk equating to threatened and endangered status would promote consistency, transparency, and scientific rigor in classification decisions, even for the large fraction of species for which quantitative estimates of extinction risk are not feasible.…”

Fear of failure in conservation: The problem and potential solutions to aid conservation of extremely small populations

“…We need to incorporate better strategies for dealing with, rather than being immobilized by, uncertainty in conservation decisionmaking (Regan et al, 2013). As Ludwig et al (1993) state, ''effective policies are possible under conditions of uncertainty, but they must take uncertainty into account.''…”

“…Advanced statistical and modeling methods that incorporate uncertainty into projections (e.g., stochastic matrix models, ensemble modeling) and quantify multiple aspects of uncertainty in observations (e.g., process versus observation uncertainty in state-space models, uncertainty at different scales in hierarchical models) have been a fertile area of research (e.g. Fieberg and Ellner, 2001;Regan et al, 2013). These methods can be used to evaluate predicted outcomes under different management approaches, and may be particularly important for forecasting population fluctuations of ESPs, for which stochastic effects can be magnified and the proximity of the population to the persistence threshold a pressing management concern.…”