Conflicts between those interested in using versus conserving biodiversity are widely recognised as both damaging to human livelihoods and biodiversity and are increasing in scope and scale. Yet, despite this recognition, there is a lack of theory to help guide the resolution of these problematic issues. This project will combine two approaches that have recently been introduced to conservation – management strategy evaluation (MSE) and behavioural economic games – to understand the roles that parties take in searching for solutions to conservation conflicts. The project will use a timely UK conservation conflict as a case study: the conflict over the management of increasing geese numbers in the UK which impose costs on farming.
Conflicts can be considered as decision-making problems with multiple parties seeking different outcomes. The idea of conflict resolution is to bring those parties together to find a shared solution to the problem that all parties can accept. Conservationists therefore need to understand both (a) the conditions under which negotiated solutions are likely to be possible, and (b) what outcomes are likely for different ecosystems and their characteristics when solutions are negotiated vs. when stakeholders act solely according to their own interests.
In order to do this, we will build on recent advances in behavioural games to understand people’s choices and incentives and linked social-ecological models to test scenarios that are beneficial to people and biodiversity. We will develop a framework that combines detailed existing understanding of the ecological dynamics of the goose system and new understanding of stakeholder decision-making developed from experimental games and game theory designed to explore factors that influence (1) whether or not players are willing to negotiate, and when they are, how (2) differential pay-offs and (3) uncertainty influence the likelihood that they will reach consensus. The project will study trade-offs between stakeholders exploring alternative management scenarios that could lead to consensus, non-cooperative and cooperative solutions or win-win situations.