What we do:
I am interested in what happens to ecosystems and the species within them when apex predator numbers are altered. I develop theory, and test it by constructing and parameterizing models with field data collected from animals and plants living in the wild. We use machine learning and artificial neural networks to parameterize models, and we gain insight through the analysis of the resulting models.
What a project would look like
Opportunities to gain fieldwork experience in Yellowstone, Trinidad and/or Australia, access to large amounts of existing data from individually marked animals, construction, parameterization and analysis of models to investigate how natural systems respond to environmental change.
A couple of relevant publications:
Bonnaffé, Willem, and Tim Coulson. "Fast fitting of neural ordinary differential equations by Bayesian neural gradient matching to infer ecological interactions from time‐series data." Methods in Ecology and Evolution 14.6 (2023): 1543-1563.
Bonnaffé, Willem, Ben C. Sheldon, and Tim Coulson. "Neural ordinary differential equations for ecological and evolutionary time‐series analysis." Methods in Ecology and Evolution 12.7 (2021): 1301-1315.
Cubaynes, Sarah, et al. "Disease outbreaks select for mate choice and coat color in wolves." Science 378.6617 (2022): 300-303.
Lachish, Shelly, et al. "Investigating the dynamics of elk population size and body mass in a seasonal environment using a mechanistic integral projection model." The American Naturalist 196.2 (2020): E23-E45.
