N. van Tiel

The paper introduces a geospatial mapping pipeline to generate quantitative, spatially explicit predictions for ecological and biophysical processes.

This paper maps tree species' ecological suitability globally using machine learning to guide climate-resilient forest restoration.

This study shows that ignoring fossil age uncertainty leads to less accurate tree topologies and divergence times, especially with high character sampling.