Data Selection for Making Biodiversity Management Decisions: Best Available Science and Institutionalized Agency Norms
Administration & Society, 2013
(with John David Gerlach and Colleen E. Forcina)
Best available science has long been the standard for using science to inform environmental and natural resource policy. This study examines the selection of data from federal, state or local, and nongovernmental sources for use in making ground-level natural resource policy, or biodiversity management decisions. The authors argue that aspects of neo-institutional theory are explanatory of data selection within a natural resource agency. They empirically test their theory by analyzing original data collected from a 2007 survey of U.S. Fish and Wildlife Service field offices, which attained a response rate of 36.6% (204 of 557 field offices). The authors find that data selection cannot merely be explained by the discussion of best available science. Rather, neo-institutional theory tenets of normative isomorphism and path dependency are explanatory of how science is selected for use in making biodiversity management decisions. However, coercive isomorphism does not possess the same explanatory ability with regard to U.S. Fish and Wildlife Service field office data selection.