Abstract
Predicting biodiversity responses to climate change requires linking plant communities to climate at appropriate scales. Commonly used climatic datasets (e.g. WorldClim) provide coarse estimates that fail to capture how plants experience microclimate, particularly in forests where canopy structure strongly buffers understory conditions. Mechanistic models such as microclimf can simulate microclimates but rely on remotely sensed inputs (e.g. leaf area index, tree height), which may not capture ground truth plant community composition. We present a framework that estimates climate-buffering capacity based on tree functional types and canopy composition, using vegetation data including tree height and canopy cover. The model is validated against in situ microclimate observations from widely distributed forest habitats, demonstrating strong performance across multiple temperature variables (monthly and annual means and extremes). Our pipeline improves understanding of baseline diversity and refines predictions for biodiversity change under future climate scenarios by situating plant species within environmental conditions they actually experience.
Georg J. A. Hähn
My research focus on community assembly processes, microclimate, forests & plant diversity.