Climate-Vegetation-Soil Interactions in Wildfire Risk Prediction: Evidence from Two Atlantic Forest Conservation Units, Brazil

This study presents a fire risk prediction framework applied to two conservation units within the Atlantic Forest biome (AFb): Serra da Gandarela National Park (PNSG), Minas Gerais, and Campos de Palmas Wildlife Refuge (RVSCP), Paraná. Daily climate data (2001–2023), remote sensing vegetation indices Normalized Difference Vegetation Index (NDVI) and Normalized Multi Band Drought Index (NMDI), fire foci, and estimates of soil volumetric moisture were integrated to analyze the climatic and environmental drivers of fire occurrence and to develop predictive models. Sea Surface Temperature (SST) anomalies in the Niño 3.4 region revealed the influence of El Niño–Southern Oscillation (ENSO) variability on local hydrometeorological dynamics. Vegetation indices and soil moisture data reinforced this relationship, with NMDI values below 0.4 and sharp declines in volumetric moisture indicating water stress during the dry season. Kernel density maps identified clusters of fire foci during this period, confirming the strong seasonality of fire occurrence. Based on climatic predictors and environmental indicators, fire risk indices were developed for each conservation unit and validated using independent data. Model performance showed moderate explanatory capacity, with coefficients of determination ranging from 0.53 to 0.68 and high agreement between estimated and observed values. Validation stratified by ENSO phases (Neutral, El Niño, and La Niña) demonstrated stable performance across contrasting climatic regimes, indicating temporal resilience of the modeling framework. Overall, the integration of climate data, spectral indices, and soil moisture information improves the ability to anticipate fire risk in Atlantic Forest conservation units, providing a useful tool to support prevention, monitoring, and decision-making in protected areas.