Impactos climáticos e conservação da Sumaúma na Amazônia Brasileira

Abstract

In recent decades, the Amazon phytogeographic domain has faced extreme drought events caused by the El Niño phenomenon, intensified by global climate change. Climate projections indicate that more severe and prolonged droughts are likely to become more frequent, although the adaptive responses of Amazonian forest species are still poorly understood. Among these species, kapok stands out, a large tree with an important ecological, cultural, and socioeconomic role. This study aimed to model the potential distribution of Ceiba pentandra, Ceiba samauma, and Ceiba lupuna in the Amazon phytogeographic domain, considering the current period and future climate scenarios for 2041–2060, 2061–2080, and 2081–2100, under two IPCC greenhouse gas (GHG) emissions scenarios: SSP2 4.5 (less pessimistic) and SSP5 8.5 (more pessimistic), using species distribution modeling (SDM). Thirty-three environmental variables (19 climatic and 14 soil) and five: Bioclim (BIO), Maximum Entropy (MXD), Random Forests (RDF), Support Vector Machine (SVM), and Generalized Linear Models (GLM) were used. Model performance was evaluated using Area Under the Curve (AUC), kappa, True Skill Statistic (TSS), Sorensen index, and Jaccard index. Principal component analysis (PCA) indicated that the first twelve components explained approximately 95% of the total data variability, with PC1 and PC2 accounting for 40.31% and 21.40%, respectively. Among the algorithms, GAU, RDF, and SVM presented the highest AUC values (≥0.98) for all species. In the current scenario, the potential distribution of C. pentandra, C. samauma, and C. lupuna reflects their strong adaptation to the region's humid tropical conditions and flooded soils. However, projections indicate a widespread reduction in environmental suitability across all periods and scenarios, especially in the SSP5 8.5 scenario. These results highlight the need for effective environmental policies that guide sustainable actions and regulations capable of minimizing the negative impacts of human activity on Amazonian species.