Assessing Atlantic Forest successional stages using remote sensing

The assessment of successional stages plays a strategic role in forest management and is crucial for understanding forest dynamics and patterns. In the Atlantic Forest (AF), this remains a challenge due to the complexity of its ecosystems. Here, we identify AF successional stages using remote sensing and assess the influence of anthropogenic and environmental factors in the Serra da Tiririca State Park, an important protected area in Rio de Janeiro, Brazil. We integrated MapBiomas data with vegetation indices to select the generalized linear mixed model (GLMM) that best predicted successional stages. Generalized linear models (GLMs) identified key variables explaining local AF successional patterns. We found an adequate classification, with successional stages moderately correlated with the Normalized Difference Vegetation Index (NDVI, R²=0.3) using the GLMM. The study area exhibited a mean annual regeneration rate of 95 ha and a suppression rate of 22 ha. Notably, soil organic carbon emerged as an important threshold in the GLMs for all successional stages, while wind played a key role in the early stage, and precipitation was important for the late stage. Our approach provides a replicable strategy for other AF sites, offering insights for biodiversity conservation and management of protected areas.

Keywords:
anthropic pressure; environmental drivers; habitat dynamics; landscape ecology; secondary forest; Serra da Tiririca state park; vegetation mapping