Mara Baudena

This study models fire-vegetation dynamics in central Italy under climate change scenarios, showing that extreme fire events shape landscape resilience and influence vegetation composition over time.

This study uses machine learning and remote sensing to analyze post-fire vegetation recovery in a Mediterranean area, finding rapid regrowth of shrubs and trees but slower recovery of coniferous stands.

The paper models plant communities under varying fire frequencies to show that compositional and functional diversity peak at intermediate fire frequencies, with functional similarity needed for maximum species richness.