Subjectivity in Expert Decision Making: Risk Assessment, Acceptability, and Cognitive Biases affecting Endangered Species Act Listing Judgments for the Greater Yellowstone Ecosystem Grizzly Bear
A Graduate Defense Seminar by Harmony Szarek, MS Student in Environmental Social Science, who will present Subjectivity in Expert Decision Making: Risk Assessment, Acceptability, and Cognitive Biases affecting Endangered Species Act Listing Judgments for the Greater Yellowstone Ecosystem Grizzly Bear in 370 Kottman Hall.
The Endangered Species Act (ESA) was signed into U.S. law in 1973, with the purpose of conserving species at risk of extinction. The law mandates that “the best scientific and commercial data available” be used to determine the protection status of wildlife species and provides a process in which decision makers answer two questions: What is the risk to the species? and, Is that risk acceptable? The first question can be answered by science, but the second cannot; ultimately, acceptability of a certain level of risk is an ethical or policy decision rather than a scientific decision. Scientific factors and objectivity are scrutinized in this type of expert decision making process, however the other factors such as individual perspective, biases, and heuristics, that may influence the decision making process have received limited attention to date. This research investigates the process of expert decision making involved in listing determinations for the grizzly bear (Ursus arctos horribilis) in the Greater Yellowstone Ecosystem (GYE) during the timeframe where proposals to delist this population segment of grizzlies from the ESA are being considered. A web-based survey of researchers who have published peer-reviewed findings on Ursus arctos within the past 10 years, and Interagency Grizzly Bear Committee members was conducted to investigate the degree of consensus regarding the threats facing the GYE grizzly and also to understand what factors influence expert listing recommendations. Level of expertise, threat assessment, and six individual biases were analyzed in a bivariate logistic regression to determine which factors have an impact on the choice between keeping the GYE grizzly listed or delisted.