Navigating the science-policy interface
As a wildlife population ecologist who wants to conduct useful science, I find the Endangered Species Act (ESA), like other federal wildlife statutes, an intriguing read. The topic is in my wheelhouse—fish, wildlife, and plants, with a focus at the population and species levels. There is an emphasis on science, in fact, the “best scientific and commercial data available.” And there are intriguing questions: what threats does a species face? What habitat would be critical for its survival? Could any federal actions put the species or critical habitat in greater peril? I am not alone in this attraction. Hundreds of scientists continue to consider the types of scientific analysis suggested by the ESA. The enthusiasm is palpable. If the first cursory read of the ESA is intriguing to me as a scientist, the second close read is tantalizing—I realize that something very attractive is just out of reach. I know how to estimate the probability of extinction, but I do not know what “in danger of extinction” means. I know how to evaluate the incremental change in status that might arise from some level of proposed take, but I do not know what “is not likely to jeopardize the continued existence” of a species means. The standards expressed in the statute are not stated in purely scientific terms. Thus, ESA decisions cannot be based solely on science, and require additional policy interpretation. Clarity about these policy interpretations—even awareness that they are needed—can be hard to find, leaving a gap between what I can provide as a scientist and what an ESA decision maker needs. This awareness of the interaction between science and policy is also occurring in the larger field of conservation science, where there has been an increasing recognition of a research-implementation gap, the need for actionable science, and the promise of translational ecology. All of these terms emphasize that science alone does not result in action; instead, action arises out of decisions that are informed both by science and by values. At the interface of science and policy, a scientist can deliver relevant knowledge, and a decision maker can explain the policy context in which that science is needed. As a scientist wanting to conduct useful science, I crave this two-way conversation. But how can this conversation be structured in a meaningful and appropriate way? In this chapter, I explore how decision analysis can be used to navigate the science-policy interface for ESA decisions. Decision analysis is a large, well-established field that studies how decisions are made and how they could be made, with explicit attention given to clarifying and separating the values-based and science-based elements of a decision; identifying the impediments that make a decision difficult; and providing tools to overcome those impediments. There have been concerted efforts to apply formal decision analysis to ESA decisions, but the practice is not yet widespread across both the U.S. Fish and Wildlife Service and the National Marine Fisheries Service (the Services). The chapter begins with an introduction to decision analysis and how it seeks to bridge the science-policy interface. In subsequent sections, I explore how a decision analyst might frame listing and reclassification decisions, recovery planning, section 7 consultation, budget allocations, and a few other ESA decisions, with an emphasis on two questions: for each type of decision, what policy clarifications does the decision maker need to make; and knowing the policy context, what type of scientific assessment is needed. In the final discussion, I identify common themes among the types of decisions, and offer thoughts on how decision analysis could be more widely used to integrate science into ESA decisions.