Exploring natural regeneration potential in degraded Amazonian lands under restoration scenarios

Understanding how forest restoration affects future regeneration is crucial for advancing restoration science. This study examines the impact of vegetation recovery on the natural regeneration potential of forests in Brazil's Amazon biome, focusing on areas with varying levels of pasture degradation. A Random Forest model was developed to predict regeneration potential based on biophysical variables, including climate, soil properties, and forest proximity. Three restoration scenarios were analyzed: (1) severely degraded pastures, (2) moderately degraded pastures, and (3) both combined. Using geospatial datasets and spatial modeling, we identified positive feedback loops between restored forests and nearby landscapes, such as abandoned pastures, facilitating broader regeneration. Severely degraded pastures, despite occupying smaller areas, play a critical role in enhancing natural regeneration by mitigating extreme conditions and fostering favorable microclimates. These areas also amplify the regeneration potential of adjacent moderately degraded pastures. Notable gains were observed in the “arc of deforestation” regions, including Mato Grosso, southeastern Pará, Rondônia, and Maranhão. While prioritizing moderately degraded pastures is cost‐effective and efficient, restoring severely degraded areas yields substantial benefits, strengthening ecological recovery across the landscape. Future research should explore feedback dynamics between secondary vegetation and young forests, while integrating biophysical, socio‐economic, and political factors. Addressing degradation levels and ensuring forest conservation are vital, as ongoing deforestation threatens large‐scale passive restoration efforts.