Project R-16468

Developing novel statistical approaches to study biodiversity dynamics across space and time using massive opportunistically collected datasets (Research)

Anthropogenic stressors such as climate change and habitat modification are reshuffling biodiversity patterns worldwide. Efforts to quantify biodiversity change are typically constrained in their geographical, temporal, and taxonomic scope and resolution, as rigorous long-term monitoring schemes are expensive and have yet to be deployed at a global scale. In this interdisciplinary project, we capitalise on a novel statistical approach to leverage massive, opportunistically sourced data collected by naturalists and citizen scientists through online biodiversity portals such as Observation.org and iNaturalist, to retrospectively map and understand how climate change and habitat modification modulate biodiversity change. First, we will develop a modelling approach that accommodates over a century's worth of opportunistic butterfly records to explore long-term community dynamics. Second, we will build a mechanistic model to map climate-induced range shifts among insects at a continental scale with unprecedented biological realism. Additionally, we will develop an approach to quantify the spatial, seasonal, and interannual scales at which land use affects distribution patterns using fine-grained remote sensing data. Finally, we will use this modelling framework to cost-effectively monitor nature restoration efforts, by tracking how the divergence between partially observed communities and their target composition varies over time, while identifying possible bottlenecks.

01 January 2026 - 31 December 2029