Simulating global deforestation

Chris Littleboy


I stumbled into a exciting research project after joining the ConFooBio team at Stirling University in October 2021. It became exciting and topical a few weeks after I began the research, when at COP26 there was an ambitious commitment to end deforestation. My work – developing a model which predicts at a global scale where deforestation will be most acute and how conservation resources might be best spent – now has new relevance!

Before I joined, the team had developed Generalised Management Strategy Evaluation framework (GMSE), an agent-based model to simulate human-environment interactions. The model is designed for predicting conservation outcomes where there are potential conflicts of interest between conservation and food security. Imagine rare geese which eat farmers’ seeds, or forest elephants which trample crops. ‘Managers’ try to protect wildlife for conservation while ‘users’ try to get the best yields. Using evolutionary game theory, the model predicts an adaptive strategy for each individual to simulate how these conflicts might resolve under various starting conditions.

During my PhD I worked extensively with land cover and population distribution data. There, the goal was to understand how land scarcity impacts property rights and agricultural productivity. But as the data is free to access, global in scale, and rarely integrated into research in social/environmental sciences, adapting the GMSE to deforestation seemed a perfect match of my experience and the work of the team. And as of today I’m about half way through!

This has involved setting up the input data for 14,000+ forests by:

And to do:

An fun project which will hopefully get some traction!