Résumé
Fire is a natural disturbance capable of altering plant distributions and community assemblages, influencing species evolution through the selection of traits and strategies, and affecting biogeochemical cycles. This powerful tool of landscape transformation can negatively impact even a fire-dependent ecosystem when natural fire regimes are altered. In recent times, interactions between human activities in the Cerrado (e.g., deforestation and intentional fires used to clear land), and a hotter and drier climate (due to climate change), have altered natural fire regimes causing more frequent and intense fire events, negatively impacting biodiversity, human health, and the regional climate. These fire-disturbed areas are widespread and highly vulnerable to future degradation from compounding disturbances, but they still harbour valuable biodiversity and carbon stocks that deserve protection and restoration. Monitoring the impacts of fire disturbance on vegetation structure and the potential pathways of recovery is critical to understand and protect resilient ecosystems under a rapidly changing climate. Robust monitoring requires the integration of modelled and field-based data tools and techniques. Field inventories alone are insufficient to capture the spatiotemporal variability of impacts of fire on native vegetation and should be coupled with remotely sensed data, among which, LiDAR (light detection and ranging) is unparalleled in characterising 3-D vegetation structure.