Nádia Gilma Beserra de Lima

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.

Mangroves near subtropical range limits may benefit from fewer cold constraints, yet warmer conditions can also increase atmospheric water demand. These competing possibilities were examined in the Cananéia-Iguape Coastal System, southeastern Brazil, by combining ERA5 2 m air temperature with MODIS normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and leaf area index (LAI). Air-temperature trends were assessed for 1979–2019 with the Mann-Kendall test and Sen’s slope. Temperature-vegetation associations were calculated for 2003–2019 from mangrove-wide means and from individual grid cells at annual, monthly, and fixed calendar-quarter scales. Mean annual air temperature increased by about 0.02 °C year⁻ ¹ ; the highest quarter-scale rate occurred in July–September (0.03 °C year⁻ ¹ ). Annual temperature correlated positively with NDVI ( r = 0.61, R ² = 0.38, p = 0.009) and EVI ( r = 0.55, R ² = 0.30, p = 0.022), whereas the LAI relationship was not significant ( r = 0.27, R ² = 0.07, p = 0.304). The sign of the association changed within the year: NDVI and EVI were negative in July–September, while positive EVI and LAI relationships occurred in October-December. Significant grid-cell relationships occupied limited and discontinuous areas. The temperature record shows regional warming, whereas canopy associations vary among metrics, periods, and locations. Given the bivariate design and coarse ERA5 grid, these associations should not be interpreted as causal or as responses to temperature alone.

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.

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.

O objetivo deste trabalho é analisar a variação dos índices de vegetação obtidos nos manguezais do Sistema Costeiro Cananéia-Iguape, e relacioná-los com os atributos climáticos para o período de 2003 até 2022. Para está pesquisa foram utilizados dados dos índices de vegetação como NDVI, EVI e LAI, dados de temperatura de superfície e precipitação pluvial. Os dados foram trabalhados em processamento em nuvem, sendo que a correlação temporal realizada no Google Colab e a correlação espacial no Google Earth Engine. Os resultados indicaram que a correlação temporal anual entre os índices de vegetação e os atributos climáticos não tem correlação significativa. No entanto, a correlação temporal sazonal foi significante para o NDVI e a precipitação pluvial em julho, agosto e setembro - JAS (r = - 0,54) e outubro, novembro e dezembro - OND (r = - 0,47) , EVI e precipitação em OND (r = - 0,50) e LAI e temperatura de superfície em JFM (r = 0,72) e JAS (r = 0,45). Na correlação espacial, o setor oeste do Parque Estadual da Ilha do Cardoso e no curso inferior do Rio Ribeira de Iguape correspondem as áreas que mais tiveram correlação significativa com os atributos climáticos. Esses resultados mostraram serem promissores nas análises dos atributos climáticos em relação ao impacto no manguezal. No entanto, precisa-se aprofundar na compreensão das respostas tardias dos índices de vegetação para melhor entender como o manguezal responde a mudanças nos atributos climáticos.

Os manguezais são ecossistemas de transição, onde o ambiente fluvial encontra o mar. Se desenvolve na faixa intertropical do globo, de modo que este ambiente demanda condições de elevadas temperaturas médias e totais pluviométricos para seu desenvolvimento. A vegetação do manguezal atua como um controle do atributo climático, criando uma condição microclimática específica abaixo e acima do dossel. É a partir da diferença entre os dois ambientes que se baseia o estudo multiescalar do clima, onde o ambiente microclimático dentro do bosque sofre influência da vegetação, e esta da dinâmica atmosférica regional que atua acima do dossel. É a partir desta relação entre as escalas do clima que se estrutura a análise multiescalar climática em ambiente de manguezal.

Este trabalho buscou correlacionar os valores do Índice de Vegetação por Diferença Normalizada (NDVI) com a precipitação pluvial, no manguezal do Sistema Costeiro Cananéia-Iguape (SCCI), no Estado de São Paulo. Para a realização desta pesquisa, utilizaram-se dados de precipitação pluvial, do obtidos do sensor Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS), e os do NDVI, pelo Moderate-Resolution Imaging Spectroradiometer (MODIS/Aqua) referentes ao período de 01.01. 2003 a 31.12.2022. O processamento dos dados e aquisição das imagens foram realizados na plataforma Google Earth Engine (GEE). Os dados mensais e anuais da chuva foram obtidos pela soma dos diários e mensais e os de NDVI, pelas respectivas médias. O recorte temporal desses dados refere-se ao limite do SCCI. Os principais resultados indicaram que o NDVI do manguezal variou entre 0,5 e 0,8, que equivale a uma vegetação densa e com alta atividade fotossintética. Os coeficientes de correlação de Pearson (r) e os de correlação cruzada entre as variáveis considerando tempo zero e defasagens, mostraram que a influência da precipitação pluvial versus NDVI não é imediato e, portanto, ocorre quatro meses após a sua ocorrência, com r = 0,44. Além disso, o NDVI do manguezal não varia somente em função da precipitação pluvial, haja vista a existência de outros fatores que influenciam na variação do NDVI, mas precisam ser investigados.