An examination of factors that explain the use of data in the natural resource policy process

Natural resource policy-making agencies often seek to make decisions based on best available science. However, the sources of biological information available to decision makers have multiplied significantly over the past several years. This study identifies key factors which predict why natural resource professionals choose one data source over another. The findings of this study may be used by researchers, practitioners, and data producers to better understand the use of science in making natural resource policy.;This study draws upon neo-institutional theory literature to pinpoint potential organizational factors which influence data selection, as well as diffusion theory literature to identify potential environmental factors. These factors inform a research model, which is tested through the collection of original data. These data are used to examine a series of theory-driven organizational and environmental research questions and hypotheses. This study serves to determine the salience of specific aspects of neo-institutional and diffusion theories with regard to explaining data selection decisions.;Data were collected using a web-based survey, which asked questions pertaining to data use, organizational characteristics and perceptions, and decision-making practices. The survey was sent via e-mail to 557 U.S. Fish & Wildlife Service field offices, representing all eight regions of the agency. Some 204 field offices completed the survey, providing a response rate of 36.6%. Multiple analysis of covariance (MANCOVA) procedures were conducted to assess the effects of 22 organizational and environmental independent variables on dependent variables measuring data selection and data newness (federal, state or local, and non-governmental sources).;This study suggests that federal data are used most frequently by U.S. Fish & Wildlife Service field offices for the purpose of making natural resource policy decisions, followed by state or local data and non-governmental data sources, respectively. Results indicate the U.S. Fish & Wildlife Service may influence its field offices to use nongovernmental data sources to supplement governmental data when making policy decisions. This study also suggests that collaborating with a non-governmental organization when making natural resource policy is positively related to the selection of non-governmental data sources. However, the data marketing efforts of non-governmental data producers do not positively relate to non-governmental data selection.;Certain aspects of neo-institutional and diffusion theories were proven salient with regard to explaining data selection among U.S. Fish & Wildlife Service field offices. The neo-institutional theory tenets of institutional isomorphism and path dependency were proven explanatory of data selection decisions. Diffusion theory literature which suggests that interest or advocacy group relationships and the adoption of an innovation by a similar entity positively affect the diffusion of innovations was also proven salient with regard to explaining data selection.;This study recommends that natural resource agency field offices continually reassess their data selection procedures in an effort to select data based on quality. In the quest to make natural resource policy decisions based on best available science, it appears that field offices "satisfice" in their data selection decisions and are highly influenced (1) by relationships with non-governmental organizations and (2) the data selection decisions of other field offices. "Satisficing" potentially leads to making natural resource policy based on popular data rather than quality data. This study also recommends that collaboration with natural resource agencies is the best avenue by which data producers can assure their data sets impact policy.