Abstract Wildlife damage to livestock and crops is the primary cause of conflict and a major barrier to human–wildlife coexistence across Europe and beyond. Data on such damages play a key role in understanding and shaping these conflicts. Policy responses have emphasised prevention and compensation to support extensive husbandry practices; however, these measures do not necessarily prevent conflicts, and damage management remains highly contested in some regions. Farmers' trust in the damage response system is decisive for coexistence strategies. Trust likely impacts whether affected farmers submit reliable depredation information, which is key to data validity. Trustful relations with authorities may also influence willingness to put in place livestock protection measures. Yet little is known about how choices in the damage response system affect trust. In this perspective, we argue that key pressure points impact three aspects of trust: (1) trust in institutional outcomes; (2) trust in institutional processes; and (3) interpersonal trust. Building on experience gathered in researching and implementing large carnivore management systems across the European Union (EU), and the exploration of case studies from five EU countries with contrasting wildlife governance systems and administrative processes, we discuss four aspects of the damage response system that have significant implications for trust: the role of the inspector; degree of centralisation and type of coordination; speed and predictability of response; and level of compensation. Beyond technical improvements, building trust should be a central focus of research and policy. The damage response system remains under‐examined and needs further empirical investigation and comparative work, including exploration of farmers' views. The professionalism, neutrality, and empathy of inspectors can foster positive farmer experiences and strengthen interpersonal trust in day‐to‐day wildlife management. Institutional trust can be reinforced through a well‐coordinated, fair compensation system with predictable responses within an agreed, ideally short, timeframe. Read the free Plain Language Summary for this article on the Journal blog.
Marsden et al. (Sat,) studied this question.