
Background Across the western United States, compensation programs that pay livestock producers for losses seek to mitigate the impact of carnivore depredation on livestock. However, data suggest not all livestock producers report wolf depredations or utilize compensation programs. Understanding factors influencing producers to report depredations and to use compensation programs will be critical to program efficacy. Methods We designed a questionnaire expanding the Theory of Planned Behavior to explore which social-psychological and demographic factors most strongly correlate with compensation use and conflict reporting intentions. Our questionnaire was distributed across the inland western United States with confirmed wolf populations including Washington, Oregon, California, Idaho, Montana, Wyoming, Colorado, Arizona, and New Mexico, as well as Alberta, Canada. Results Perceptions of how commonly other producers were reporting wolf depredation (descriptive norms) and worry about future wolf depredation (perceptions of risk probability) were the strongest predictors of reporting intention. A lack of trust in state agencies, perceived financial risk without access to depredation compensation, descriptive norms, attitudes, age, and producer state of residence were the strongest predictors of compensation use intention. Our findings suggest that reducing operational financial vulnerability, building trust in agency personnel, and peer-to-peer knowledge sharing may be effective strategies for increasing reporting and compensation use. Though our sample size was relatively small, our results are informative and have important implications for compensation programs and reporting.
Male, Adult, Wolves, Livestock, Intention, Middle Aged, United States, Anthropology, Surveys and Questionnaires, Compensation and Redress, Animals, Humans, Hunting, Female
Male, Adult, Wolves, Livestock, Intention, Middle Aged, United States, Anthropology, Surveys and Questionnaires, Compensation and Redress, Animals, Humans, Hunting, Female
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