Complex human-deer interactions challenge conventional management approaches: the need to consider power, trust, and emotion

In the United States, the management of white-tailed deer (Odocoileus virginianus) has typically focused on improvinghunting opportunities and mitigating human-deer conflicts. Yet the expansion and diversification of human communities and activitiesimplies that human-deer interactions may also be diversifying. Approaches based on complex adaptive systems theories have beenposited as a way to better attend to the diversity of these interactions between humans and wildlife. Using Indiana as a case, this studydraws from the Integrated Adaptive Behavior Model (IABM) to understand human-deer interactions as a complex system. We useempirical social science to understand how citizens across Indiana perceive deer populations, what outcomes they desire, and how theseperceptions could be integrated into Indiana's deer management plan. In Indiana, neither wildlife managers nor researchers haveassessed public perceptions of deer beyond hunting and farming stakeholders. From May to September 2019, we collected 59 semi-structured interviews and two focus groups (n = 14) with deer stakeholders including woodland owners, farmers, deer hunters, andurban area residents. Through mixed inductive-deductive coding, we found that Indiana citizens hold complex emotions toward deerregardless of their stakeholder identity. Factors influencing these emotions include past experiences, current livelihood and behavioralcontexts, beliefs about responsibilities and ethics in deer management, and beliefs about other social groups. Our results suggest thatthe IABM, despite adding in much-needed complexity and realism to the analysis of human-wildlife interactions, still lacks explanatorypower over several important dynamics that emerged from our interviews. Here, we discuss how mixed emotions, situational context,and power dynamics challenge conventional management approaches that focus narrowly on mitigating human-deer conflicts, and thatreduce public interests to demographic categorizations. To better inform social-ecological governance, models of complex humanbehavior should account for power within management institutions and across management scales. Our work contributes a refinedunderstanding of how multidimensional emotions and experiences influence public (dis)interest in natural resource management, andwhat this implies for managers who aim to balance competing social interests with ecological conditions.