Exploring the incentivisation and biodiversity returns of treescapes using agent based models

The broad aim of this project is to help deliver conservation outcomes from healthy treescapes by understanding the feedbacks created by policy interventions. Treescapes are extended networks of woodland that provide many ecosystem services, e.g. wellbeing, cultural services, biodiversity. The spatiotemporal structure ("connectivity") of these networks affects biodiversity and robustness to climate change, but also exposure to threats such as pests and diseases.

The wide range of private and social benefits derived from land managers' decisions are affected by the interactions among the multiple actors across the landscape, the uncertainty and imperfect information context in which these decisions take place, as well as the response of natural-social systems to policy interventions. Standard game-theoretic modelling frameworks cannot capture the spatio-temporal complexity of these interactions.

We will use a novel agent-based modelling approach to capture these socio-ecological interactions in the context of policy incentives and other schemes (e.g. Environmental Land Management Scheme & "Big Nature Fund"). Specifically: (i) we will model how the decisions of land managers (e.g. farmers) are affected by their beliefs and expected economic benefits, the behaviour of neighbouring farmers, and the outcomes in the landscapes they manage; (ii) we will use population- and metapopulation dynamics to model the natural populations in these treescapes.

This will allow us to explore the effectiveness of different incentive structures (different payment schemes, different metrics) in delivering conservation outcomes, and identify unintended consequences (e.g. increased connectivity can benefit biodiversity, but also promote risks from disease and extreme events).