Tim Newbold

This study shows land use and climate warming interact to reshape avian biodiversity through ecological filtering and homogenisation, with distinct effects across different land-use types and warming levels.

The paper constructs a global database of pest herbivores and their natural enemies by using a large language model to extract species interactions from scientific literature.

The paper quantifies the risk of functional misalignment in North American forests under future climate conditions using trait-based analysis of forest inventory data.

The paper develops a statistical method to correct global biodiversity indicators by accounting for hard-to-sample species, finding they decline more with land-use intensity.

This paper evaluates GPT-4's ability to extract pest and controller information from ecological literature, showing high accuracy in species and location extraction.