Distinct drivers of extreme and non-extreme fires in the Brazilian Amazon

Abstract The Brazilian Amazon suffers from frequent fires with varying sizes and intensities, but the causes for extreme and non-extreme fires remain unclear. Here, using multiple satellite-based observations and explainable machine learning models, we find distinct drivers of burned area variation for extreme (burned area > the 90th percentile) and non-extreme fires in the Brazilian Amazon between 1985 and 2020. The absolute land use fraction of pasture and forest are dominant drivers for non-extreme fires, while the extreme fires are more driven by the fire weather conditions and land use change from forest to pasture in the adjacent two years. In future climate and land use change scenarios, our predicted annual total burned area from extreme fires and non-extreme fires increases from 2021 to 2050. Compared with the historical period, contributions of future climate change and anthropogenic activities to the annual total burned area are positive for non-extreme fires but negative for extreme fires due to reduced pasture expansion and deforestation. Therefore, mitigating climate change and implementing local sustainable land use strategies are crucial for restricting fires in the Brazilian Amazon.