Many studies have investigated nutrient cycling in seasonally dry tropical forests, but few have assessed the contribution of different functional groups to these processes. Here, we investigated general litter dynamics patterns and the contribution of legume and non-legume trees to litter dynamics and carbon (C), nitrogen (N), and phosphorus (P) inputs in a fragment of secondary seasonally dry tropical forest after half a century of forest succession in the Atlantic Forest biome in Brazil. Between 2016 and 2017, we quantified litterfall production, canopy cover, forest floor, and soil C and N storage in 11 permanent plots distributed in the fragment. Vegetation identity and structure had been previously assessed. We quantified the seasonal inputs of leaf litter and C, N, and P separately for each functional group (legume and non-legume tree species). We also analyzed the correlations between the variables measured for each functional group with the variables measured at the plot level. Litter dynamics and nutrient input were affected by climate and functional group. Litterfall production during the two driest months was three times higher than during the other periods of the year, suggesting that species synchronicity is likely to minimize drought-related damage on trees. Legume trees had twice the basal area attained by non-legume trees, but while legumes were larger, non-legumes were more abundant and dominant in the smaller diameter class. Legumes deposited twice as much N during the driest period of the year as non-legumes. Although leaf litter, C, and P inputs by legumes were generally higher than those of non-legumes, these differences during the dry season were not statistically significant. We also found that the legume variables correlated better with the plot-level variables, compared to the non-legume functional group. Our results also indicated potential effects of the leaf litter and nutrient inputs by the legume functional group on the decomposition constant and, consequently, on the time of forest floor decomposition. Further studies should assess the role of different functional groups in litter dynamics and nutrient inputs in seasonally dry tropical forests.

Leaf-cutting ants are the most important herbivore in the neotropics, represent active agents of pedobioturbation, and are regarded as ecosystem engineers. These ants have a wide variety of ecological functions, such as pollination, seed dispersal, and tree-growing control. Despite this importance, little is known on their distribution in relation to possible soil and environmental conditions that affect Atta ants occurrence. This study aimed to spatialize the main occurrences of Atta species in the Brazilian territory and evaluate the main [...] ABSTRACT Leaf-cutting ants are the most important herbivore in the neotropics, represent active agents of pedobioturbation, and are regarded as ecosystem engineers. These ants have a wide variety of ecological functions, such as pollination, seed dispersal, and tree-growing control. Despite this importance, little is known on their distribution in relation to possible soil and environmental conditions that affect Atta ants occurrence. This study aimed to spatialize the main occurrences of Atta species in the Brazilian territory and evaluate the main

Flooding occurrence is one of the most common phenomena that impact urban areas, and this intensifies during heavy rainfall periods. Knowing the areas with the greatest vulnerability is of paramount importance as it allows mitigating actions to be implemented in order to minimize the generated impacts. In this context, this study aimed to use Geographic Information System (GIS) tools to identify the areas with greater flooding vulnerability in Espírito Santo state, Brazil. The study was based on the following methodological steps: (1) a Digital Elevation Model (DEM) acquisition and watersheds delimitation; (2) maximum and accumulated rainfall intensity calculations for the three studied periods using meteorological data; (3) a land use and occupation map reclassification regarding flood vulnerability and fuzzy logic application; (4) an application of Euclidean distance and fuzzy logic in hydrography and water mass vector variables; (5) a flood vulnerability model generation. Based on the found results, it was observed that the metropolitan and coastal regions presented as greater flood vulnerability areas during the dry season, as in these regions, almost all of the 9.18% of the state’s area was classified as highly vulnerable, while during rainy season, the most vulnerable areas were concentrated in Caparaó and in the coastal and immigration and metropolitan regions, as in these regions, almost all of the 12.72% of the state’s area was classified as highly vulnerable. In general, by annually distributing the rainfall rates, a greater flood vulnerability was observed in the metropolitan and coastal and immigration regions, as in these areas, almost all of the 7.72% of the state’s area was classified as highly vulnerable. According to the study, Espírito Santo state was mostly classified as a low (29.15%) and medium (28.06%) flood vulnerability area considering the annual period, while its metropolitan region has a very high flood vulnerability risk. Finally, GIS modeling is important to assist in decision making regarding public management and the employed methodology presents worldwide application potential.

Tropical forests, particularly the Atlantic Forest, are among the most biodiverse and threatened ecosystems on Earth. Intense fragmentation, historical deforestation, and climate change have compromised their integrity and endangered endemic and rare species. The situation is even more critical in the Doce River Basin (DRB), a biodiversity hotspot in southeastern Brazil, due to the expansion of pastureland and mining, as well as the 2015 Mariana disaster. Understanding how future climate may affect the persistence of threatened tree species in the region is essential. This study evaluated the effects of climate scenarios on the distribution of 26 rare and/or threatened tree species in the DRB. We used Species Distribution Models (SDMs), combining algorithms (GLM, RDF, SVM, MaxEnt) into a consensus ensemble model under SSP3-7.0 and SSP5-8.5 scenarios for 2050 and 2090. Climatic, topographic, and edaphic variables were predictors, with climate explaining most environmental variation. Among the 26 species, 19 are projected to lose over 75% of their suitable area, with local extinction likely for range-restricted and specialized species such as Handroanthus arianeae and Grazielodendron rio-docensis . Species associated with mature forests and humid microclimates were most severely affected, while some generalists showed resilience, maintaining or expanding suitable areas. Although all species retain some suitable habitats within Protected Areas (PAs), results indicate the current PA network will be insufficient for long-term conservation. Complementary strategies such as assisted translocation, habitat connectivity, and priority-area identification based on climate projections are needed. This study provides critical insights for policies and land-use planning aimed at conserving the DRB’s threatened flora.

Forest edge effects are commonly interpreted as radial gradients from the edge toward the interior, but this assumption may oversimplify the spatial organization of heterogeneous tropical forest fragments. Here, we integrated field-based phytosociological data with Sentinel-2 spectral indices to evaluate whether edge-related structural interpretation depends on analytical scale in Semideciduous Seasonal Forest fragments embedded in the Brazilian Cerrado. Five fragments were analyzed using transect-based plots and continuous pixel-level modeling. Basal area showed a strong positive correlation with the Normalized Difference Vegetation Index (NDVI) (r = 0.95), supporting its use as the main spectral proxy for basal-area-related structural variation. Plot-level segmented regression detected statistical transitions along the edge–interior gradient, with breakpoints ranging from approximately 13 to 39 m. However, pixel-level modeling revealed scale-dependent responses, including shorter estimated transition distances in the rural Ipameri fragment (IF) and the Campo Alegre de Goiás fragment (AC), an intermediate transition in the Caldas Novas fragment (CN), a longer estimated transition distance in the UEG–Ipameri fragment (IP), and high internal heterogeneity without a single dominant radial transition in Panga. The first two axes of the Principal Component Analysis (PCA) explained approximately 81% of the total variance, reinforcing the structural–spectral correspondence. These findings show that edge-related spectral–structural patterns are detectable but are not adequately represented by fixed radial zones alone. Pixel-level Sentinel-2 modeling provides a complementary spatial framework for interpreting edge-related heterogeneity in fragmented tropical forests when integrated with field-based structural data.