Foi realizada uma análise das precipitações pluviais mensais durante anos influenciados pelos fenômenos El Niño-Oscilação Sul (ENOS) no Vale do Ribeira de Iguape, localizado no sudeste do estado de São Paulo. Dados de 1970 a 2017 de 18 postos pluviométricos distribuídos pelo alto, médio e baixo curso do rio Ribeira de Iguape foram analisados utilizando a metodologia Box-Plot para a identificação de anos-padrão mensais. Observou-se um excedente hídrico nas precipitações durante anos de influência de ENOS, enquanto em anos de influência dos fenômenos La Niña (LA) verificou-se uma maior variabilidade nas precipitações pluviais. Em muitos anos de ENOS, os excedentes ocorreram principalmente na primavera (outubro, novembro e dezembro) e no final do verão (janeiro, fevereiro e março). Na fase de LA, as secas foram mais evidentes na primavera (setembro e outubro) e nos meses de fevereiro e março. Conclui-se que o fenômeno na região apresenta variabilidade mensal e não segue um padrão constante e espacialmente regular. Portanto, é necessário analisar e compreender outros fenômenos atmosféricos, como as frentes frias, o Modo Anular Sul (MAS), o Dipolo do Atlântico Sul, e o EN Canônico/Modoki, entre outros, que podem influenciar as dinâmicas das precipitações pluviais na região.

This study examines long-term mangrove vegetation dynamics in the Cananéia–Iguape Coastal System (CICS), southeastern Brazil, with emphasis on their relevance for coastal ecosystem monitoring and sustainability. Land-use and land-cover (LULC) data from MapBiomas were combined with MODIS-derived vegetation indices, namely the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), and Fractional Vegetation Cover (FVC) to assess spatial variability and temporal trends from 2003 to 2024. Spatial anomalies were calculated as deviations from long-term mean conditions, whereas temporal trajectories were evaluated using the non-parametric Mann–Kendall test and Sen’s slope estimator. The results indicate limited spatial variability, with 98.35% of the study area for the NDVI and 99.51% for the EVI showing no detectable deviations from long-term averages. Within mangrove areas, however, statistically significant positive trends were identified for the NDVI (Z_MK = 2.43; p = 0.02), EVI (Z_MK = 2.03; p = 0.04), and FVC (Z_MK = 2.43; p = 0.02), suggesting a gradual increase in spectral greenness and FVC-derived vegetation density. The moderate correlation between mangrove extent and the NDVI (r = 0.61; p < 0.05) indicates that the mapped mangrove area is partially associated with variations in spectral greenness, although this relationship should not be interpreted as direct evidence of ecological recovery or improved ecosystem conditions. Overall, the findings point to low-magnitude but consistent vegetation index changes in a predominantly stable mangrove system. The integration of LULC information, spectral indices, and FVC provides a consistent regional-scale basis for interpreting mangrove dynamics in heterogeneous coastal environments and for guiding long-term monitoring efforts.

Hydroclimatic variability and land-use and land-cover (LULC) change were investigated in the Ribeira de Iguape River Basin, Brazil, using precipitation records from 14 gauges and mean, maximum and minimum streamflow from 10 stations within 1960–2024, alongside annual LULC maps for 1985–2024. Hamed–Rao Mann–Kendall tests, Sen’s slopes and change-point analyses were complemented by temporal-dependence, interstation-consistency and false-discovery-rate diagnostics. After adjustment, seven precipitation stations exhibited increasing annual trends and one showed a decrease. The largest positive slopes occurred at Balsa do Cerro Azul (+101.5 mm decade⁻¹), Guanhanha (+98.3 mm decade⁻¹) and Capela da Ribeira (+90.1 mm decade⁻¹). However, pronounced departures from regional reference series around 1981 at two neighbouring gauges preclude an unequivocal climatic interpretation. Streamflow responses were more localised. Declining maximum discharge at Juquiá (−16.2 m³ s⁻¹ decade⁻¹) was the only annual streamflow trend retained after adjustment, without a comparable downstream decline over common years. Urban and mining areas expanded, whereas forest cover initially declined and subsequently recovered partially, remaining below its 1985 extent. Land-cover proportions extracted within ten independently DEM-delineated upstream catchments yielded 228 estimable contemporaneous LULC–discharge correlations. Although 21 were nominally significant, none remained significant after Benjamini–Hochberg adjustment within the corresponding discharge-metric families or across the pooled set. These findings reveal spatially differentiated hydroclimatic and landscape trajectories, without establishing a causal contribution of LULC change to observed streamflow variability.

Understanding land-use and land-cover (LULC) dynamics is fundamental for the management and conservation of fragile coastal ecosystems. This study investigates the spatiotemporal transitions within the Cananéia–Iguape Coastal System (CICS), a UNESCO World Heritage site in Brazil, over a 37-year period (1985–2022). The research addresses the gap in long-term, high-resolution monitoring of this estuarine-lagoon complex, which is vital for biodiversity and local livelihoods. Using MapBiomas Collection 8.0 data processed via the Google Earth Engine, we analyzed LULC transitions and stability across several classes, with a specific focus on mangrove dynamics, landscape stability, and anthropogenic expansion. Our findings reveal that the CICS maintains a high degree of landscape integrity, with natural vegetation covering approximately 90% of the area in 2022. Mapped mangrove cover remained relatively persistent throughout the study period, although small variations in mangrove extent should be interpreted cautiously because they may be influenced by classification uncertainty in the original MapBiomas dataset. However, significant transitions were identified in “Pasture” and “Mosaic of Uses,” reflecting localized anthropogenic pressures. The results indicate that the overall landscape structure of the CICS remained largely preserved. Nevertheless, continuous monitoring is required to track the progression of human-modified landscapes and support adaptive management strategies. This study concludes that the integration of cloud-based geospatial data provides a robust framework for coastal governance. The documented landscape stability of the CICS provides valuable information for environmental monitoring and supports the development of conservation and management strategies in tropical coastal zones. Graphical Abstract This visual summary serves as a pivotal entry point into the research, offering a concise overview of the study’s core findings and methodologies regarding the Cananéia–Iguape Coastal System (CICS). The graphical abstract illustrates the integration of MapBiomas time series data (1985–2022) with advanced geospatial processing via Google Earth Engine to monitor land-use and land-cover (LULC) changes. It highlights the five essential components: (1) Data, focusing on the historical satellite imagery of the CICS; (2) Analyses, depicting the transition matrices and temporal trends; (3) Model, showcasing the classification logic used by MapBiomas; (4) Results, emphasizing the persistence of the mapped mangrove class and the increase of selected anthropogenic land-cover classes; and (5) Conclusion, summarizing the importance of these dynamics for coastal management. By providing a quick, visually appealing summary, this abstract allows readers to rapidly comprehend the research’s essence, including the study area’s geographic context and the methodological flow from data acquisition to environmental interpretation, without requiring a full reading of the manuscript.