Are wildlife value orientations useful tools to explain tolerance and illegal killing of wildlife by farmers in response to crop damage?

Understanding human-wildlife conflicts and monitoring their consequences, such as wildlife persecution, is crucial for biological conservation. Although most theoretical models suggest that the influence of value orientations on behavior is mediated by higher order constructs such as attitudes and norms, wildlife value orientations are widely used to assess human-wildlife relationships and to predict human behavior towards wildlife. We have no evidence of studies which have measured them in Mediterranean countries, where the highest biodiversity level in temperate Western countries is present. In spring 2016, we administered a questionnaire to local farmers in Central Italy to measure the association between wildlife value orientations and illegal killing of wildlife, in response to crop or poultry damages (n = 352). We obtained the prevalence of illegal killing with the Randomized Response Technique, ensuring complete individual protection to respondents. We modeled the effect of wildlife value orientations over illegal wildlife killing with a Bayesian logistic regression for three taxa: the red fox, the crested porcupine, and birds, as most of persecution by farmers in our study site is exerted towards them. We found that domination predicted illegal killing for the red fox only. On the other hand, mutualism predicted tolerance towards all the study taxa. Combining wildlife value orientations and the Randomized Response Technique can be a promising approach to explore human-wildlife conflicts and their consequences. Furthermore, the Mediterranean setting of our study filled existing geographical gaps about wildlife value orientations in Europe. We encourage future research on the application of wildlife value orientations to conflicts involving wildlife and extensive farmers, i.e., at large scale, as well as future large-scale research on wildlife value orientations in Europe.