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Project Title: Unified Spatio-Temporal Biodiversity Modelling
Summary: This project aims to improve how we study biodiversity over time and space. Traditionally, scientists use models that treat nature like a collection of separate communities connected by species moving between them. But nature is more continuous, and these models don’t always capture the full picture.
To tackle this, we will run large scale simulations of metacommunities in artificial landscapes using an advanced ecological model. The results will be used to train a generative AI model. This AI will help us predict the ranges of real species based on limited observation data. The goal is to create high level biodiversity maps such as identifying rare species habitats.
By combining ecological modeling with AI, this project will help us better understand how species spread and respond to environmental changes.
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