Broadening the toolset for stakeholder engagement to explore consensus over wolf management

Area of Science:

• Conservation Biology
• Human-Wildlife Conflict Resolution
• Environmental Management

Background:

• Large carnivore conservation in human-dominated landscapes faces challenges due to negative impacts on human interests.
• Recent wolf recovery in central Italy has led to social tensions and a stalemate in management strategies.
• Previous top-down mitigation policies, like damage compensation, have proven ineffective.

Purpose of the Study:

• To test a participatory approach engaging diverse stakeholder groups in dialogue to co-create solutions for wolf management.
• To explore the application of the meta-consensus theory and Multi-Criteria Decision Analysis (MCDA) in resolving human-carnivore conflict.
• To foster understanding and agreement on coexistence strategies in an area with recent wolf recolonization.

Main Methods:

• A 3-month participatory process involving five workshops with representatives from farming, hunting, environmental associations, and a biologist.
• Utilized Multi-Criteria Decision Analysis (MCDA) as a decision support tool to facilitate dialogue and consensus-building.
• Focused on sharing understanding of the problem and co-creating potential management solutions.

Main Results:

• Stakeholders identified shared objectives and agreed on management interventions, including managing free-ranging dogs and implementing damage prevention and compensation systems.
• The process improved stakeholder relations and enhanced knowledge on wolf-related issues.
• Positive social outcomes and a willingness for further discussion on management preferences were observed.

Conclusions:

• Multi-Criteria Decision Analysis (MCDA) is a valuable tool for initiating participatory and deliberative processes in wolf management.
• The participatory approach successfully laid groundwork for coexistence strategies, despite challenges with participant numbers and methodology complexity.
• Further efforts are needed to involve broader representation and simplify the decision-making tools for wider applicability.