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Disasters caused by rainfall extremes represent social challenges in several sectors, especially in climate change scenarios. Along with changes in land use and land cover, this relationship may become more complex. Thus, the present study aimed to detect recent trends in the pattern of rainfall indicators and associate them with records of natural disasters and the evolution of changes in land use and land cover for the state of Espírito Santo, southeastern Brazil. Daily rainfall data from 77 rain gauge stations from 1970 to 2018 were used to analyze climate trends in different rainfall indicators obtained using the RClimDex software. Records of natural disasters from 1991 to 2020 in the state of Espírito Santo were gathered from the Brazilian Integrated Disaster Information System. Additionally, land use and land cover data from 1985 and 2019 were also used. The Mann–Kendall (MK) test and the Sen slope were used to detect and quantify trends. In the Litoral Norte Espírito-santense and Noroeste Espírito-santense mesoregions of the State, trends of drought intensification are expected mainly in the regions further north. Associated with the great recent agricultural expansion in the region, this trend is concerning. The Central Espírito-santense and Sul Espírito-santense mesoregions tend to become wetter, which explains the recent increase in floods and heavy rainfall. No significant trends were found in the other regions studied. The approach adopted in this study has the potential to assist decision-making, implement mitigation and/or adaptation measures, and reduce the impacts of natural disasters in different regions of the world. [ABSTRACT FROM AUTHOR]

Understanding the trends in land use and land cover (LULC) is crucial for modeling streamflow and sediment yield, particularly in hydrological basins. This study examined the impact of LULC on the dynamics of streamflow and sediment yield within a humid tropical basin of the Atlantic Forest biome in Brazil, focusing on the period from 2000 to 2016. Changes in LULC were analyzed using annual MapBiomas data products for the same period. The Soil and Water Assessment Tool (SWAT) model was deployed to simulate streamflow and sediment yield based on LULC changes. To investigate temporal trends in LULC, a suite of non-parametric statistical tests, including the Mann–Kendall, Pettitt, and Sen's slope estimator tests, was employed. Ecological diversity indices such as Shannon–Weaver, Simpson, and Pielou were applied to assess forest fragmentation, along with the Forest Fragmentation Index. The results revealed a growing trend in urban and sugarcane areas, coupled with a decline in dense vegetation, mangroves, and other forms of dense vegetation. With regard to the correlation between land uses and hydrological variables, the findings indicate minor variations in hydrological balance, attributable to the not-so-significant changes among the studied land-use scenarios, except for sediment yield estimates, which showed more considerable alterations. Notably, the estimates for 2000 and 2013–2016 were the most divergent. In a broader scientific context, this research conclusively establishes that the incorporation of dynamic LULC data into the SWAT model augments the precision and robustness of simulations pertaining to agricultural watersheds, thereby enabling a more comprehensive hydrological characterization of the study area. [ABSTRACT FROM AUTHOR]

Large-scale land use/land cover changes have occurred in Mato Grosso State (hereafter MT), Brazil, following the introduction of extensive mechanized agriculture and pastoral activities since the 1980s. Author investigated what kind of agro-pastoral activities which are both cattle ranching and top five crops (soybean, sugarcane, corn, cotton and rice) that are closely related to land use change on lands experiencing conversion land use change (such as deforestation and the increase in deeply anthropogenically influenced areas) at each municipal district in MT. Then, this study identifies the volume of exports including contribution ratio by municipal districts where land use changed due to agro-pastoral activities. The patterns of vegetation change indicated that cattle ranching, corn, cotton, rice croplands in the northwest, and soybean and sugarcane fields in the central areas are the main contributors to deforestation. It is shown that land use change due to soybean or corn cultivation occurs mainly in the west and the southeast, respectively. Corn cultivation is associated with a greater increase in anthropogenically influenced areas than soybean cultivation. The municipal districts that export each agro-pastoral product with land use change are limited. Exports of soybeans, corn, and cotton in the municipal districts associated with deforestation had increased dramatically after experienced land use change. For example, Sapezal, which has experienced deforestation, was the only municipal district associated with export of corn to only Switzerland. Since 2007, the number of export partners has increased to 56 countries with the export volume increased 2300 times. These findings highlight the overall non-sustainability of environmental resource development activities in MT. [ABSTRACT FROM AUTHOR]

Biomass burning (BB) emissions negatively impact the biosphere and human lives. Orbital remote sensing and modelling are used to estimate BB emissions on regional to global scales, but these estimates are subject to errors related to the parameters, data, and methods available. For example, emission factors (mass emitted by species during BB per mass of dry matter burned) are based on land use and land cover (LULC) classifications that vary considerably across products. In this work, we evaluate how BB emissions vary in the PREP-CHEM-SRC emission estimator tool (version 1.8.3) when it is run with original LULC data from MDC12Q1 (collection 5.1) and newer LULC data from MapBiomas (collection 6.0). We compare the results using both datasets in the Brazilian Amazon and Cerrado biomes during the 2002–2020 time series. A major reallocation of emissions occurs within Brazil when using the MapBiomas product, with emissions decreasing by 788 Gg (−1.91% year−1) in the Amazon and emissions increasing by 371 Gg (2.44% year−1) in the Cerrado. The differences identified are mostly associated with the better capture of the deforestation process in the Amazon and forest formations in Northern Cerrado with the MapBiomas product, as emissions in forest-related LULCs decreased by 5260 Gg in the Amazon biome and increased by 1676 Gg in the Cerrado biome. This is an important improvement to PREP-CHEM-SRC, which could be considered the tool to build South America's official BB emission inventory and to provide a basis for setting emission reduction targets and assessing the effectiveness of mitigation strategies. [ABSTRACT FROM AUTHOR]

The way water resources behave in the face of changes in land use are essential for managing a watershed. The Ibicuí river basin, located in the center of the state of Rio Grande do Sul, Brazil, has great agricultural potential and peculiar characteristics regarding its hydrological regime. Changes in land use and land cover with the purpose of expanding economic activities in this area can generate major impacts on the flow regimes of this watershed. This study shows an analysis of the influence of land use and land cover changes on the flow regime in the Ibicuí river basin from the large-basin hydrological model (MGB-IPH), considering maps of land use history and vegetation cover in the study area. The results were used to analyze the changes in the maximum and minimum annual and monthly average flows. The efficiency of the model was evaluated by the Nash-Sutcliffe coefficient (between 0.636 and 0.801) for peak flows and by the Nash-Sutcliffe log (between 0.682 and 0.863) for recession flows, indicating high correlation and low volume error (- 0.45 to - 8.20%). The greatest change in land use was the forest coverage reduction associated with agriculture land use. As a result, an increase in the average monthly flows and in the reference flow Q90 was verified. In some sub-basins, a significant modification in the reference Q90 flow and maximum flow was verified. The Mann-Whitney test showed that the results were accurate. The results indicated that changes in forest coverage and land use have an impact in the flow regime in the Ibicuí Watershed. [ABSTRACT FROM AUTHOR]

Remote sensing is valuable for estimating aboveground biomass (AGB) stocks. However, its application in agricultural and pasture areas is limited compared with forest areas. This study quantifies AGB in agriculture–pasture mosaics within Brazil's Campo Maior Complex (CMC). The methodology employs remote sensing cloud processing and utilizes an estimator to incorporate vegetation indices. The results reveal significant changes in biomass values among land use and land cover classes over the past ten years, with notable variations observed in forest plantation, pasture, sugar cane, and soybean areas. The estimated AGB values range from 0 to 20 Mg.ha−1 (minimum), 53 to 419 Mg.ha−1 (maximum), and 19 to 57 Mg.ha−1 (mean). In Forest formation areas, AGB values range from approximately 0 to 278 Mg.ha−1, with an average annual value of 56.44 Mg.ha−1. This study provides valuable insights for rural landowners and government officials in managing the semiarid territory and environment. It aids in decision making regarding agricultural management, irrigation and fertilization practices, agricultural productivity, land use and land cover changes, biodiversity loss, soil degradation, conservation strategies, the identification of priority areas for environmental restoration, and the optimization of resource utilization. [ABSTRACT FROM AUTHOR]

This work aims to develop a new method to map Land Use and Land Cover (LULC) classes in the São Paulo State, Brazil, using Landsat-8 Operational Land Imager (OLI) data. The novelty of the proposed method consists of selecting the images based on the spectral and temporal characteristics of the LULC classes. First, we defined the six classes to be mapped in the year 2020 as forest, forest plantation, water bodies, urban areas, agriculture, and pasture. Second, we visually analyzed their variability spectral characteristics over the year. Then, we pre-processed these images to highlight each LULC class. For the classification, the Random Forest algorithm available on the Google Earth Engine (GEE) platform was utilized individually for each LULC class. Afterward, we integrated the classified maps to create the final LULC map. The results revealed that forest areas are primarily concentrated in the eastern region of São Paulo, predominantly on steeper slopes, accounting for 19% of the study area. On the other hand, pasture and agriculture dominated 73% of all São Paulo's landscape, reaching 39% and 34%, respectively. The overall accuracy of the classification achieved 89.10%, while producer and user accuracies were greater than 84.20% and 76.62%, respectively. To validate the results, we compared our findings with the MapBiomas Project classification, obtaining an overall accuracy of 85.47%. Therefore, our method demonstrates its potential to minimize classification errors and offers the advantage of facilitating post-classification editing for individual mapped classes. [ABSTRACT FROM AUTHOR]

Interactions between land use and cover and a basin hydrological regime are complex and dynamics. The identification of trends and changes in rainfall and flow regimes in a region is relevant in water resources planning and management so that environmental, economic and social adversities are avoided. Thus, this study aims to identify possible trends in the historical series of rainfall and fluviometric stations in Rio das Mortes basin, Minas Gerais, Brazil, as well as to relate the modifications in the flow rate behaviour due to changes in land use and cover in the basin between the years of 1985 and 2017. For that, hydrological data were used from the Ibituruna-MG river station and 12 rainfall stations and orbital images from Landsat-5 and Sentinel satellites. Flow rate and precipitation behavior were performed using the nonparametric Mann-Kendall test and the Pettitt's test, while the land use and cover classification was performed in an eCognition Developer® 64 environment. Significant trends were observed in the average of total annual rainfall series and decreasing trends in the average of monthly flow rate series of lowest runoff over the years 1925 to 2014. There were changes in land use and cover in the studied region, however, these were not significant enough to modify the hydrological regime of Rio das Mortes basin during the analysed period. [ABSTRACT FROM AUTHOR]

The Amazon region comprises the largest tropical forest on the planet and is responsible for absorbing huge amounts of CO2 from the atmosphere. However, changes in land use and cover have contributed to an increase in greenhouse gas emissions, especially CO2, and in endangered indigenous lands and protected areas in the region. The objective of this study was to detect changes in CO2 emissions and removals associated with land use and land cover changes in the Brazilian Legal Amazon (BLA) through the analysis of multispectral satellite images from 2009 to 2019. The Gross Primary Production (GPP) and CO2Flux variables were estimated by the MODIS sensor onboard Terra and Aqua satellite, representing carbon absorption by vegetation during the photosynthesis process. Atmospheric CO2 concentration was estimated from the GOSAT satellite. The variables GPP and CO2Flux showed the effective flux of carbon in the BLA to atmosphere, which were weakly correlated with precipitation (r = 0.191 and 0.133). The forest absorbed 211.05 TgC annually but, due to its partial conversion to other land uses, the loss of 135,922.34 km2 of forest area resulted in 5.82 TgC less carbon being absorbed. Pasture and agriculture, which comprise the main land conversions, increased by 100,340.39 km2 and absorbed 1.32 and 3.19 TgC less, and emitted close to twice more, than forest in these areas. Atmospheric CO2 concentrations increased from 2.2 to 2.8 ppm annually in BLA, with hotspots observed in the southeast Amazonia, and CO2 capture by GPP showed an increase over the years, mainly after 2013, in the north and west of the BLA. This study brings to light the carbon dynamics, by GPP and CO2Flux models, as related to the land use and land cover in one of the biggest world carbon reservoirs, the Amazon, which is also important to fulfillment of international agreements signed by Brazil to reduce greenhouse gas emissions and for biodiversity conservation and other ecosystem services in the region. [ABSTRACT FROM AUTHOR]

Precipitation estimation is a challenging task, especially in regions where its spatial distribution is irregular and highly variable. This study evaluated the spatial distribution of annual rainfall in a semiarid Brazilian basin under different regimes and its impact on land use and land cover dynamics. Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) records and observed data from 40 weather stations over a time series of 55 years were used, in addition to the Standardized Precipitation Index. Spatiotemporal analysis was carried out based on geostatistics. Remote sensing images were also interpreted for different rainfall regimes using the Normalized Difference Vegetation Index and Modified Normalized Difference Water Index. The Gaussian semivariogram model best represented the rainfall spatial structure, showing strong spatial dependence. Results indicated that rainfall amount in the basin significantly increases with elevation, as expected. There is high variation in the dynamics of water storage that can threaten water security in the region. Our findings point out that the application of geostatistics for mapping both the annual precipitation and the Standardized Precipitation Index provides a powerful framework to support hydrological analysis, as well as land use and land cover management in semiarid regions. [ABSTRACT FROM AUTHOR]

This work performs an analysis of the spatial pattern of the coffee harvested area in the Rio de Janeiro state between 1988 and 2018. To relate changes in land cover and land use with the coffee land abandonment, geographically weighted regressions (GWR) were adopted with the rates of change in forest and pasture cover, and also with changes in the size of the cattle herd. The coffee-crop area evolution identifies three behaviors: the concentration of planted area in the northwest, with constant growth after the 1990s; a remaining area in the mountainous region; and the abandonment of coffee farms in the south. Although bivariate models can't explain the changes in land cover and land use, geographically weighted regressions point to a trend of replacing coffee cover with pasturelands in the south region of the state, while eventual changes for forest cover are more likely in other regions. [ABSTRACT FROM AUTHOR]

Effects of natural processes on community building and the modification of nature by man's hands are an intrinsic part of the co-production of the landscape between man and nature. However, the interactions of this co-production have scarcely been analyzed. Based on data from the MapBiomas project, an analysis of the variation in land use and cover over 35 years in the Quilombola São Roque and Mãe dos Homens communities in southern Brazil was carried out. The sociogeomorphological units in the study area were established, and its geomorphological units and social units were analyzed and described. There is a prevalence of more than 50% of forest formation. Cluster analysis classified the analyzed variables into two groups, with the first corresponding to forest and grassland formations associated with more natural landscape features. The second group is formed by anthropogenic activities. Social units including traditional communities seem to be more related to the stimulation of forest formation. The action of conservation units influences the variation in land use and land cover. There is a Supplementary Material which explains abbreviations concerning the manuscript. [ABSTRACT FROM AUTHOR]

Studying a watershed in the Amazon region requires understanding that this region has national and global relevance. The fact that the study area is located in the socalled arc of deforestation raises the need to understand its context, its vulnerabilities, and its physical, environmental, and anthropic components. This research assesses the environmental vulnerability of the Buriticupu River Watershed in Maranhão State, Brazil. The aim is to foster improvements that may contribute to environmental planning and, specifically, to water resource management. For this purpose, the authors used the Geographic Information System environment to work with Map Algebra, interrelating primary and secondary data on geology, relief, pedology, and land use and land cover to generate synthesis cartography. The results pointed to areas with predominantly medium vulnerability. However, the analyses highlight alluvial plains, which became the most fragile areas from an environmental point of view. This is mainly because these areas comprise water-saturated soils (gleysols), unconsolidated deposits of sand and silt (alluvial deposits), and extensive humid vegetation, characteristics of igapó and floodplain forests. This research generated a document that applies is applicable to the study area. It also provided, in a systemic and integrated way, a product that will help in planning, which is very important for the creation of a watershed committee, something necessary and still embryonic in Maranhão State, Brazil. [ABSTRACT FROM AUTHOR]

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Subterranean habitats around the world can shelter diversified and threatened faunal communities. However, issues related to alterations in the landscape and structure of subterranean habitats still need to be better understood. Therefore, we used a multi-spatial scale analysis of land cover, land use, and cave habitats to predict the diversity of communities of subterranean invertebrates. We hypothesized that changes in land cover promote alterations in both faunal richness and composition and microhabitat diversity and that microhabitat features determined subterranean biodiversity. Sixteen limestone caves were sampled in Brazil at micro, meso, and macro scales using quadrats (1m²), transects (100 meters) as sample units inside caves and buffers with the radius of 100 and 250 meters in the surroundings of the cave entrances. Models performed showed that land cover and land use influenced cave environments, regarding both microhabitats traits and terrestrial invertebrate richness and composition. We also observed a relationship between microhabitat structure and terrestrial invertebrate richness and composition. Our results showed that deforested areas had negative effects on species richness and changed their composition, while natural areas had positive effects on microhabitat diversity. The same effects were observed for both 100 and 250 meters buffers. Invertebrate richness was negatively predicted by deforested areas while positively predicted by natural areas. Richness was also positively predicted by the combination of all microhabitat traits, and dissimilarity of fauna was influenced by microhabitat diversity in mesoscale and microscale by all microhabitat elements. The results highlight the importance of the landscape surrounding the caves to conserve the subterranean habitats and their fauna. Due to the spatial and temporal changes in the global environmental scenario, we argue the urgency of further detailed studies in fragmented landscapes to define minimum areas of protection for cave environments. [ABSTRACT FROM AUTHOR]

Climatic changes and land usage and cover (LULC) can significantly impact the availability of water resources in a region. On the other hand, water resources are intrinsically linked to economic production. Thus, managing water resources and their know-how on how they are affected by the climate and LULC are essential in regional development. The Global Climatic Model evaluated water resource management on its effects of climatic changes (2019–2099) based on four R epresentative Concentration Pathways (RCP 2.6, 4.5, 6.0, and 8.5) and the impact of changes in LULC in the Hydrographic Basin of the Cubatão River (HBCR), in Brazil. The fragilities of water resource management were observed. The scarcity of precipitation data made a direct impact on the estimated monthly average flow, as the estimated reduction was 45.4 % (RCP 2.6), 41.9 % (RCP 4.5), 43.2 % (RCP 6.0), and 41.7 % (RCP 8.5) by the end of the century. The forecast change in LULC reduces the impact on the decreased average monthly flow to 2.9 % by 2099 (RCP 2.6), 2.5 % (RCP 4.5), and 2.7 % (RCP 6.0 and 8.5). The actual evapotranspiration will be less than 2.4 % (RCP 2.6 and 6.0) and 2.3 % (RCP 4.5 and 8.5) with changes in the LULC in future scenarios. The HBCR already uses the entire status of authorized flow that will further aggravate as population growth continues. The results display faulty water resource maintenance of the basin that indeed will interfere in local economic development. • Climate change models estimate higher precipitation, but it is still insufficient. • Without the management of water resources, economic development is threatened. • The lack of instrument prevents the management of water resources. [ABSTRACT FROM AUTHOR]

In this study, we explored the association between land use and fish species richness on 52 coastal lagoons in Southeast and South Brazil. We measured the proportion of agriculture and urbanization around lagoons over 26 years and used the coefficient of variation (CV) as a surrogate of the temporal land cover variability. We compiled species occurrences from primary data, from the literature and from museum records, and assigned each recorded species to different habitat use groups: benthic/bottom or water column, and littoral or limnetic zones. In the Southeast, where most lagoons are subject to marine influence, richness was negatively associated to agriculture and positively associated to urbanization. In the South, where freshwater lagoons predominate, richness was negatively associated to urbanization and positively associated to agriculture. The results suggest that fish communities from freshwater coastal lagoons are more sensitive to land use than brackish lagoons. Differently from brackish lagoons, that are colonized by both freshwater and marine species, freshwater lagoons rely on neighboring lagoons as species donors. However, this apparent resilience of the brackish lagoons must be regarded with caution, since the increase in marine connections due to artificial sandbar openings may impair freshwater species with time. [ABSTRACT FROM AUTHOR]

Landscape change s driven by anthropogenic activities often have negative impacts on ecosystems, jeopardizing the provision of vital services that sustain biotic elements and wildlife. Predicting the effects of such transformations is crucial for developing strategies to mitigate ecological damage. This study explores the interaction of land use changes and habitat quality estimates in the Upper Paraguay River Basin in Brazil, using the InVEST Habitat Quality model to estimate spatiotemporal landscape trends and evaluate the potential impact of land use policies for the future. Under a business-as-usual scenario by 2050, potential land use changes are simulated for shaping habitat quality, habitat degradation, and habitat rarity estimates as landscape proxies for biodiversity conservation. Results show an extensive expansion of pastures through deforestation, leading to progressive habitat degradation with a significant decay in the predicted and observed habitat quality. The habitat quality index estimates show a spatial decrease from 0.78 to 0.57 for the 1989–2050 period. The same trend is observed in protected areas for the period 2019–2050, with an increase of anthropogenic land use and a decrease of the habitat quality from 0.80 to 0.57 in conservation units, and from 0.75 to 0.53 in indigenous lands. For improved conservation outcomes, this work introduces new insights for shaping environmental actions that can be flagged as sustainable land management practices and ecological perspectives towards spatial pressures at different scales. Therefore, government institutions responsible for the protection of conservation units and indigenous communities can be informed about potential land use impacts on their territories. The findings suggest that incorporating additional scenario trends and climate-related variables could be a valuable direction for future studies to extend further the modelling approaches explored in this work. • Landscape changes threaten biodiversity in Brazil's Upper Paraguay River Basin. • Habitat quality is projected to sharply decline by 2050. • Protected areas are predicted to lose 20% of natural land cover under a BAU scenario. • Conservation units and indigenous lands face high-risk from anthropogenic pressures. • A shift to sustainable and innovative agro-pastoral practices is suggested. [ABSTRACT FROM AUTHOR]

The objective of this work was to carry out a multitemporal analysis of changes in land use and land cover in the municipality of Floresta, Pernambuco State in Brazil. Landsat images were used in the years 1985, 1989, 1993, 1997, 2001, 2005, 2009, 2014, and 2019, and the classes were broken down into areas: water, exposed soil, agriculture, and forestry, and using the Bhattacharya classifier, the classification was carried out for generating land use maps. The data was validated by the Kappa index and points collected in the field, and the projection of the dynamics of use for 2024 was constructed. The thematic maps of land use and coverage from 1985 to 2019 show more significant changes in the forest and exposed soil classes. The increase in the forest class and the consequent reduction in exposed soil are consequences of the interaction between climate and human activities and the quality of the spatial resolution of the satellite images used between the years analyzed. [ABSTRACT FROM AUTHOR]

Although global climate change is receiving considerable attention, the loss of biodiversity worldwide continues. In this study, dynamics of land use/land cover (LULC) change in the Paraguai/Jauquara Basin, Mato Grosso, Brazil, were investigated. Two analyses were performed using R software. The first was a comparative study of LULC among the LULC classes at the polygon scale, and the second was a spatio-temporal analysis of moving polygons restricted to the agricultural regions in terms of topology, size, distance, and direction of change. The data consisted of Landsat images captured in 1993, 1997, 2001, 2005, 2009, 2013, and 2016 and processed using ArcGIS software. The proposed analytical approach handled complex data structures and allowed for a deeper understanding of LULC change over time. The results showed that there was a statistically significant change from regions of natural vegetation to pastures, agricultural regions, and land for other uses, accompanied by a significant trend of expansion of agricultural regions, appearing to stabilize from 2005. Furthermore, different patterns of LULC change were found according to soil type and elevation. In particular, the purple latosol soil type presented the highest expansion indexes since 2001, and the elevated agricultural areas have been expanding and/or stabilizing since 1997. [ABSTRACT FROM AUTHOR]

Climate variability, land use and land cover changes (LULCC) have a considerable impact on runoff–erosion processes. This study analyzed the relationships between climate variability and spatiotemporal LULCC on runoff–erosion processes in different scenarios of land use and land cover (LULC) for the Almas River basin, located in the Cerrado biome in Brazil. Landsat images from 1991, 2006, and 2017 were used to analyze changes and the LULC scenarios. Two simulations based on the Soil and Water Assessment Tool (SWAT) were compared: (1) default application using the standard model database (SWATd), and (2) application using remote sensing multiple gridded datasets (albedo and leaf area index) downloaded using the Google Earth Engine (SWATrs). In addition, the SWAT model was applied to analyze the impacts of streamflow and erosion in two hypothetical scenarios of LULC. The first scenario was the optimistic scenario (OS), which represents the sustainable use and preservation of natural vegetation, emphasizing the recovery of permanent preservation areas close to watercourses, hilltops, and mountains, based on the Brazilian forest code. The second scenario was the pessimistic scenario (PS), which presents increased deforestation and expansion of farming activities. The results of the LULC changes show that between 1991 and 2017, the area occupied by agriculture and livestock increased by 75.38%. These results confirmed an increase in the sugarcane plantation and the number of cattle in the basin. The SWAT results showed that the difference between the simulated streamflow for the PS was 26.42%, compared with the OS. The sediment yield average estimation in the PS was 0.035 ton/ha/year, whereas in the OS, it was 0.025 ton/ha/year (i.e., a decrease of 21.88%). The results demonstrated that the basin has a greater predisposition for increased streamflow and sediment yield due to the LULC changes. In addition, measures to contain the increase in agriculture should be analyzed by regional managers to reduce soil erosion in this biome. [ABSTRACT FROM AUTHOR]

The future of land use and cover change in Brazil, particularly due to deforestation and forest restoration processes, is critical for the future of global climate and biodiversity, given the richness of its five biomes. These changes in Brazil depend on the interlink between global factors due to its role as one of the main exporters of commodities globally and the national to local institutional, socioeconomic, and biophysical contexts. Aiming to develop scenarios that consider the balance between global (e.g., GDP growth, population growth, per capita consumption of agricultural products, international trade policies, and climatic conditions) and local factors (e.g., land use, agrarian structure, agricultural suitability, protected areas, distance to roads, and other infrastructure projects), a new set of land-use change scenarios for Brazil were developed that aligned with the global structure Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathway (RCPs) developed by the global change research community. The narratives of the new scenarios align with SSP1/RCP 1.9 (Sustainable development scenario), SSP2/RCP 4.5 (Middle of the road scenario), and SSP3/RCP 7.0 (Strong inequality scenario). The scenarios were developed by combining the LuccME spatially explicit land change allocation modeling framework and the INLAND surface model to incorporate the climatic variables in water deficit. Based on detailed biophysical, socioeconomic, and institutional factors for each biome in Brazil, we have created spatially explicit scenarios until 2050, considering the following classes: forest vegetation, grassland vegetation, planted pasture, agriculture, a mosaic of small land uses, and forestry. The results aim to detail global models regionally. They could be used regionally to support decision-making and enrich the global analysis. [ABSTRACT FROM AUTHOR]

Caatinga biome, located in the Brazilian semi-arid region, is the most populous semi-arid region in the world, causing intensification in land degradation and loss of biodiversity over time. The main objective of this paper is to determine and analyze the changes in land cover and use, over time, on the biophysical parameters in the Caatinga biome in the semi-arid region of Brazil using remote sensing. Landsat-8 images were used, along with the Surface Energy Balance Algorithm for Land (SEBAL) in the Google Earth Engine platform, from 2013 to 2019, through spatiotemporal modeling of vegetation indices, i.e., leaf area index (LAI) and vegetation cover (VC). Moreover, land surface temperature (LST) and actual evapotranspiration (ETa) in Petrolina, the semi-arid region of Brazil, was used. The principal component analysis was used to select descriptive variables and multiple regression analysis to predict ETa. The results indicated significant effects of land use and land cover changes on energy balances over time. In 2013, 70.2% of the study area was composed of Caatinga, while the lowest percentages were identified in 2015 (67.8%) and 2017 (68.7%). Rainfall records in 2013 ranged from 270 to 480 mm, with values higher than 410 mm in 46.5% of the study area, concentrated in the northern part of the municipality. On the other hand, in 2017 the lowest annual rainfall values (from 200 to 340 mm) occurred. Low vegetation cover rate was observed by LAI and VC values, with a range of 0 to 25% vegetation cover in 52.3% of the area, which exposes the effects of the dry season on vegetation. The highest LST was mainly found in urban areas and/or exposed soil. In 2013, 40.5% of the region's area had LST between 48.0 and 52.0 °C, raising ETa rates (~4.7 mm day−1). Our model has shown good outcomes in terms of accuracy and concordance (coefficient of determination = 0.98, root mean square error = 0.498, and Lin's concordance correlation coefficient = 0.907). The significant increase in agricultural areas has resulted in the progressive reduction of the Caatinga biome. Therefore, mitigation and sustainable planning is vital to decrease the impacts of anthropic actions. [ABSTRACT FROM AUTHOR]

Low-order streams are important places for river formation and are highly vulnerable to changes in terrestrial ecosystems. Thus, the land-use/land-cover plays an important role in the maintenance of water quality. However, only land-use/land-cover composition may not explain the spatial variation in water quality, because it does not consider land-use/land-cover configuration and forest cover pattern. In this context, the study aimed to evaluate the forest cover pattern effects on water quality on low-order streams located in an agricultural landscape. Applying a paired watershed method, we selected two watersheds classified according to their morphometry and average slope to discard other physical factors that could influence the water quality. Land-use/land-cover pattern was analyzed for composition and forest cover configuration using landscape metrics, including the riparian zone composition. Water quality variables were obtained every two weeks during the hydrological year. This way, watersheds had similar morphometry, slope, and land-use/land-cover composition but differed in forest cover pattern. Watershed with more aggregated forest cover had a better water quality than the other one. The results show that forest cover contributes to water quality maintenance, while forest fragmentation influences the water quality negatively, especially in sediment retention. Agricultural practices are sources of sediment and nutrients to the river, especially in steep relief. Thus, in addition to land-use/land-cover composition, forest cover pattern must be considered in management of low-order streams in tropical agricultural watersheds. [ABSTRACT FROM AUTHOR]

Developing conservation strategies to mitigate cumulative impacts requires the understanding of historic land use and land cover changes at the regional scale. By using a multisensory and multitemporal approach, we identified the major changes driving cumulative impacts on native vegetation in northeastern Amazon. Comparing two regions, one with mining as the key driver and another where mining is associated with other industrial activities (cellulose), we explore the land use and land cover historic dynamics and derive implications for the assessment of cumulative impacts. Transitions of forest cover to pastureland, silviculture, and urban expansion were mapped in detail over a 20-year period, revealing that silviculture growth cleared more forests than pastureland expansion when associated with pulp mill activities and kaolin mining. In contrast, in a region with gold and iron mining, pastureland expansion was more relevant, clearing mainly areas surrounding new roads. This research shows that the interplay of major mining and industrial investments can produce cumulative losses of native vegetation, depending on the associated industries and infrastructure required for the project development. Our findings emphasize that the definition of spatial and temporal boundaries for the assessment of cumulative impacts must consider different trends in impact accumulation and changes in their spatial distribution over time. [ABSTRACT FROM AUTHOR]

Native vegetation in private lands plays an important role in providing ecosystem services and safeguarding biodiversity worldwide. Legal protection rules of this vegetation are thus crucial. In Brazil, since 1934, there has been a requirement for landowners to preserve a percentage of their land covered with native vegetation, the Legal Reserve. However, the 1934 legislation applies only to arboreal vegetation, while the protection of savannahs and grasslands begins after 1965 and 1989. The reference year for the application of Legal Reserves can thus have significant impacts on the amount of native vegetation legally protected. Here we tested the effects on Legal Reserve cover in São Paulo State, considering two different legal benchmarks as starting points: 1934 and 1965. Given that the 1934 law precedes the first aerial mapping in Brazil, we developed a methodology to estimate past native vegetation cover through a probabilistic approach. The forest deficit considering 1934 as the initial point is 3% lower than the one starting with the 1965 benchmark. Comparing both scenarios, the 1934 led to a reduction of 1255 farms with Legal Reserve deficit from a total of 30,417. For both scenarios, Legal Reserve deficits were concentrated in the West, Northwest, and Mid-west regions of the state. The outcomes showed that the benchmark change does not significantly affect the total area of Legal Reserves protection, the number of farms potentially benefited by this mechanism, and the amount of native vegetation deficit. However, the use of the 1934 as an initial date for considering protection of Legal Reserve can delay the implementation of the law due to a time-consuming farm-by-farm analysis, once the probabilistic map has an intrinsic limitation for an automatic process. Thus, the environmental gains with the adoption of 1934 as the initial date do not overcome the limitations of using a probabilistic map, suggesting that effective law enforcement depends on reliable and more recent baselines, allowing semi-automated analyses. This scientific evidence can be adopted by the other Brazilian States that have not yet defined the initial legal benchmark, balancing the advantages and disadvantages of adopting the 1934 Forest Act. • We compare scenarios for the Forest Act implementation considering different past vegetation cover benchmarks (1934 and 1965). • We developed a methodology for estimating native vegetation cover in 1934, because of lack of past spatialized land-use data. • The forest deficit for the benchmark of 1934 is only 3% higher than the one of the 1965 benchmark. • Given the uncertainties of the probabilistic map, the policy implementation can be delayed if 1934 benchmark is adopted. • Even with restrictions, this is the best possible map for the 1934 benchmark and can support decision-making. [ABSTRACT FROM AUTHOR]

Aim: To explore spatiotemporal changes in Hyacinth Macaw Anodorhynchus hyacinthinus distribution and the impacts of land use change over 25 years, across its vast range in central/eastern South America. Location: Brazil, Bolivia and Paraguay, South America, covering almost 3 million km2. Methods: We use a novel, multi‐temporal species distribution model, to combine both year‐specific occurrence records and land use/cover data in a single model that is subsequently projected over a land cover time series. We investigate changes in geographic range over 25 years and potential drivers of range extent at multiple spatial scales (10 and 30 km) and time‐lags (current and 10 years previously). We also assess protected area coverage and impacts from degazettement within the remaining range and highlight priority areas to search for undiscovered populations. Results: The modelled range of the species increased by 75,000 km2 to over 500,000 km2 between 1995 and 2019, during which period agriculture and pasture increased by 600,000 km2 within the species' extent of occurrence. Habitat suitability was influenced most strongly by distribution of palms, forest cover and changes in pasture over 10 years and usually by predictors measured at larger spatial scales. Just 8% of the macaw's modelled range falls within protected areas, and more than 20,500 km2 of protected areas overlapping with the range have been degazetted in the last 40 years. We highlight key areas to search for undiscovered populations in under‐sampled and remote areas, especially led by community citizen science initiatives involving indigenous groups and protected area staff. Main conclusions: Novel modelling methods, combining multi‐temporal occurrence records and land cover data, appropriate for small sample sizes per year, have revealed habitat dynamics and changes to the range of this threatened species over 25 years. The method may have wide applicability for a range of species, including elusive and poorly studied species. [ABSTRACT FROM AUTHOR]

The Amazonian biome is important not only for South America but also for the entire planet, providing essential environmental services. The state of Rondônia ranks third in deforestation rates in the Brazilian Legal Amazon (BLA) political division. This study aims to evaluate the land use/land cover (LULC) changes over the past ten years (2009–2019), as well as, to predict the LULC in the next 10 years, using TerrSet 18.3 software, in the state of Rondônia, Brazil. The machine learning algorithms within the Google Earth Engine cloud-based platform employed a Random Forest classifier in image classifications. The Markov-CA deep learning algorithm predicted future LULC changes by comparing scenarios of one and three transitions. The results showed a reduction in forested areas of about 15.7% between 2009 and 2019 in the Rondônia state. According to the predictive model, by 2030, around 30% of the remaining forests will be logged, most likely converted into occupied areas. The results reinforce the importance of measures and policies integrated with investments in research and satellite monitoring to reduce deforestation in the Brazilian Amazon and ensure the continuity of the Amazonian role in halting climate change. [ABSTRACT FROM AUTHOR]

Gully erosion represents the most severe soil loss, with far-reaching consequences beyond the immediate site. Assessing the stability of gullies is particularly challenging in tropical regions with sandy soils and limited accurate data. Nonetheless, initiating gully inventories is a crucial first step in guiding public policies and conservation projects. In this study, we focus on the Upper Taquari River Basin (UTRB) situated on the fringes of the Brazilian Pantanal, where extensive erosion occurs in the upper regions and flooding occurs in the plains. We present the first qualitative and quantitative analysis of gullies in this region. Considering the historical context of the UTRB, it has long suffered from land mismanagement, particularly in livestock activities. Our objective was to evaluate the correspondence between gullies and land use classes in the MapBiomas Project, Brazil's most reliable non-governmental land use map, and the Rural Environmental Registry (CAR), the official information shared between landowners and public authorities. Thirteen remote-sensed indicators encompassing vegetation, water, soil, and terrain indices were assessed for 2022. Gullies were digitized through visual interpretation of a high-resolution Maxar Vivid Basic 2017 image. The classification was performed using the Random Forest (RF) algorithm, wherein pixels were classified into three classes: active, intermediate, and stable, based on the degree of vegetation cover and bare soil. The agreement of the gullies with the features of MapBiomas and CAR was also examined. The results revealed an overall accuracy of 96% and a Kappa index of 93% for the pixel classification. In the study area, 2960 gullies were digitized, with 60% classified as active features and only 2% as stable. Furthermore, the MapBiomas algorithm misclassified many pixels with active gullies as pasture. Conversely, the CAR data failed to identify gullies as areas demanding restoration. To address these issues, we recommend revising both land use maps to accurately represent the presence of erosions and improve decision-making that favors efficient conservation efforts of the region. As a further result of our actions, the method described here may prove valuable in formulating restoration plans for other tropical savanna regions. [Display omitted] • Visual interpretation and machine learning provide accurate gully mapping. • The percentage of vegetation cover is a viable metric for evaluating pixels. • Active pixels were misinterpreted in CAR and MapBiomas maps. • Include erosion class into land use platforms would help guide for prompt recovery. • Our method serves as previous inventory at severely degraded basins at low cost. [ABSTRACT FROM AUTHOR]

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There is an increasing availability of spatially explicit, freely available land use and cover (LUC) time series worldwide. Because of the enormous amount of data this represents, the continuous updates and improvements in spatial and temporal resolution and category differentiation, as well as increasingly dynamic and complex changes made, manual data extraction and analysis is highly time consuming, and making software tools available to automatize LUC data assessment is becoming imperative. This paper presents a software developed in R, which combines LUC raster time series data and their transitions, calculates state-of-the-art LUC change indicators, and creates spatio-temporal visualizations, all in a coherent workflow. The functionality of the application developed is demonstrated using an LUC dataset of the Pantanal floodplain contribution area in Central Brazil. [ABSTRACT FROM AUTHOR]

Copyright of Revista Ambiente e Água is the property of Revista Ambiente e Agua and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The largest and most dynamic agricultural frontier in Brazil is known as MATOPIBA, an area that covers part of the Cerrado biome. Within this region, Western Bahia stands out as a large producer of soy and cotton. There are no studies that quantify carbon stocks for different land uses and land cover types in Western Bahia, which hinders comprehension of the role of agricultural expansion in carbon dynamics and the development of sustainable agriculture policies. Here, we evaluate how the land use changes in this region have affected the carbon balance in the aboveground biomass (AGB), belowground biomass (BGB), and soil reservoirs. We collected soil samples for areas with different land uses and land cover types to estimate soil carbon stocks (SCS) and combined remote sensing results and modeling techniques to develop a historical reconstruction of spatial patterns of SCS, AGB, and BGB during the period 1990–2018. The replacement of areas from the forest formations class with pasture and rainfed agriculture reduced the 100 cm depth SCS (SCS100) by 37.3% (p = 0.031) and 30.3% (p = 0.053), respectively. By contrast, the conversion of pasture and rainfed agriculture to irrigated agriculture increased SCS100 by 34% (p = 0.034) and 26.5% (p = 0.022), respectively. Spatial changes in historical carbon stocks are strongly associated with land use changes that occurred between 1990 and 2018. We estimated a non-significant loss of 61.9 Tg-C (p = 0.726) from the total carbon stocks (calculated as the sum of AGB, BGB, and SCS) of which 80% of the losses came from soil stocks, 11% from BGB, and 8% from AGB. These findings reveal the need to monitor carbon stocks in sandy soils to reduce the uncertainties of estimates and support the development of effective sustainable agriculture policies. The best alternatives for reducing carbon losses in the Cerrado are to maintain natural forest cover and to recover soils through sustainable soil management, especially in pasturelands where soil carbon stocks are lowest. [ABSTRACT FROM AUTHOR]

The Território Quilombola Kalunga de Goiás (TKG) was established by law nº. 11,409/GO, and was federally regularized as territory in 2009. Its total area covers three Municipalities of Goiás: Monte Alegre de Goiás, Teresina de Goiás and Cavalcante. There live remaining communities of quilombolas. The present work aims to evaluate the recurrence of fires in this Territory and in its surroundings, doing relationships between land use and land cover and burned areas. For this purpose, were used data generated from satellite images, made available in public databases, and procedures in GIS. During the annualized time, the frequency of fires was moderate. Grassland had the largest proportion of burned areas. [ABSTRACT FROM AUTHOR]

The factors that contribute to land use change in the municipality of Gaúcha do Norte - MT, are entirely linked to the economic process and agricultural production. This process has left Brazil in a state of alert due to the process of deforestation and loss of tropical forests. From 2000 to 2010, the forest areas converted into agriculture accounted for 13.3%, the main factor that directly potentiated with deforestation was the cultivation of soybeans, which in turn was occupying places previously occupied by livestock and pushing the livestock forest inside. The phenomena of land use change and land cover start from multidimensional issues in the environmental and economic context. The use of environmental modeling through cellular automata to analyze land use change phenomena and reproduce the trajectory through future land use simulations and evolution establishes an integration associated by mathematical models and flow integration systems. That predict the trajectory of land use change, thus generating a dynamic model capable of predicting future land use changes by replicating possible patterns of landscape evolution and enabling assessments of future ecological implications for the environment. [ABSTRACT FROM AUTHOR]

Pastures are complex land covers with a variety of land use systems. This land cover occupies large areas in the globe and is mainly used for livestock production. Brazil is one of the largest livestock producers and has extensive pasture areas. We analyzed the pasture land cover change of the São Paulo State between the years 2000 to 2015. São Paulo was chosen as study case due to its large industrial and agricultural importance and its expressive land cover changes over past decades. It was analyzed land covers databases generated by the Brazilian Annual Land Use and Land Cover Mapping Project (MapBiomas Project) – Collection 4. Transition matrix was generated to analyze the land cover change during the period. Gain, loss, total change, net change and swap were calculated in terms of area. Total pasture area decreased but continues the largest land cover of the São Paulo State; with 79.5% of persistence in the area. Main changes were from losses of pastures and gains in agriculture. Most of the changes to pasture came from other non vegetated areas and grassland categories. These results demonstrated the relevance of pastures areas in land cover change dynamics to address land use policy and plan future land use scenarios. [ABSTRACT FROM AUTHOR]

The Brazilian savanna (Cerrado) is one of the most important biodiversity hotspots in the world. Being a fire-dependent biome, its structure and vegetation dynamics are shaped by and rely on the natural occurring fire regime. Over the last decades, Cerrado has been increasingly threatened by accelerated land cover changes, namely the uncontrolled and intense use of fire for land expansion. This is particularly seen in Brazil's new agricultural frontier in northeastern Cerrado: the MATOPIBA region. Changes in MATOPIBA's fire regime resulting from this rapid expansion are still poorly understood. Here we use satellite-derived datasets to analyze burned area patterns in MATOPIBA over the last 18 years, at the microregions level. We further evaluate the role of climate and land use in spatial and temporal burned area variability and assess their trends in the last two decades. Results show an increased contribution of MATOPIBA to Cerrado's total burned area over the last few years: Maranhão and Tocantins present the highest values of total burned area with some microregions burning more than twice its area over the study period. Climate is shown to play a relevant role in MATOPIBA's fire activity, explaining 52% of the interannual variance, whereas land use and burned area were found to have more complex interactions that are highly dependent on the regional context. Lastly, climate and land use drivers are found to have an overall increasing trend over the last two decades, whereas burned area trends show much heterogeneity within MATOPIBA. [ABSTRACT FROM AUTHOR]

Since 1984, nearly 1,000 people have been killed in the Brazilian Amazon due to land conflicts stemming from unequal distribution of land, land tenure insecurity, and lawlessness. During this same period, the region experienced almost complete deforestation (< 8% forest cover by 2010). Land conflict exacts a human toll, but it also affects agents' decisions about land use, the subject of this article. Using a property-level panel dataset covering the period of redemocratization in Brazil (1984) until the privatization of long-term leases in the Eastern Amazon (2010), we show that deforestation is affected by land conflict, particularly in cases of expropriation of property for agrarian reform settlement formation and when that conflict involves fatalities. Deforestation on agrarian reform settlements is much greater when soils are poor for agriculture and when the land has been the object of past conflict. Deforestation and conflict are episodic, and both agronomic drivers and contentious drivers of land change are active in the region. Ultimately, the outcome of these processes of contentious and agronomic land change is substantial deforestation, regardless of who was in possession and control of the land. [ABSTRACT FROM AUTHOR]

This paper presents a dataset of yearly land use and land cover classification maps for Mato Grosso State, Brazil, from 2001 to 2017. Mato Grosso is one of the world's fast moving agricultural frontiers. To ensure multi-year compatibility, the work uses MODIS sensor analysis-ready products and an innovative method that applies machine learning techniques to classify satellite image time series. The maps provide information about crop and pasture expansion over natural vegetation, as well as spatially explicit estimates of increases in agricultural productivity and trade-offs between crop and pasture expansion. Therefore, the dataset provides new and relevant information to understand the impact of environmental policies on the expansion of tropical agriculture in Brazil. Using such results, researchers can make informed assessments of the interplay between production and protection within Amazon, Cerrado, and Pantanal biomes. Measurement(s) land • land use Technology Type(s) computational modeling technique Factor Type(s) year • geographic location • land use and cover class Sample Characteristic - Environment land Sample Characteristic - Location Mato Grosso State Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.11440461 [ABSTRACT FROM AUTHOR]

Copyright of Anuario do Instituto de Geociencias is the property of Universidade Federal do Rio de Janeiro, Instituto de Geociencias and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Sustainability in Debate / Sustentabilidade em Debate is the property of University of Brasilia, Center for Sustainable Development and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The desertification process directly influences agricultural production and the maintenance of terrestrial life. Despite being an important agricultural centre, Brazil's semi-arid region is experiencing significant desertification. However, the relationship between land management and climate in this process is still poorly understood. This research was conducted in areas predominantly covered by the Caatinga Formation (62.2%), as well as agropastoral and pasture areas (29.9%). Our primary objective was to assess the land use change trajectories and land occupation patterns in the region while also analysing how vegetation and precipitation temporal patterns have changed from 1985 to 2019. The trends in vegetation and precipitation were evaluated using the Mann-Kendall test. Land use and occupation patterns were analysed using segmented regression and Monte Carlo simulation for future forecasting in the period 2020–240 under different scenarios (pessimistic, conservative, and optimistic). The Mann-Kendall test indicated that the precipitation trends were not statistically significant. However, the normalized vegetation index (NDVI) exhibited a significant trend in areas near the São Francisco River, an important agricultural area. Land use and occupation showed breakpoints from 1990 onwards for most classes. Monte Carlo simulations demonstrated that the Caatinga Formation will likely to remain the predominant vegetation class in the region for the next 21 years in all predicted scenarios. Agropastoral and pasture classes are projected to increase by 8% and 3%, respectively, while the area covered by native vegetation is expected to decrease by 7.5%. Furthermore, the predictions showed a decline in the rivers and lakes class, which may result in significant economic and social problems. Our findings contribute to a better understanding of the impacts of land use change in the Brazilian semi-arid region and provide science-based information for environmental public policies. Representation of the change in land use caused by the removal of native vegetation cover for agricultural use incorrectly, resulting in soil degradation, with salinization as the main consequence. [Display omitted] • Land use changes and trends of vegetation and precipitation were analysed. • Land use scenarios were forecasted for the next 21 years (2020–2040). • A significant positive NDVI trend was observed. • Caatinga Formation will remain the predominant land cover in the area. • Agropastoral will expand for the next 21 years, surpassing the pasture cover. [ABSTRACT FROM AUTHOR]

Mangroves play an essential ecological role in the maintenance of the coastal zone and are extremely important for the socioeconomics of coastal communities. However, mangrove ecosystems are impacted by a range of anthropogenic pressures, and the loss of this habitat can be attributed primarily to the human occupation of the coastal zone. In the present study, we analyzed the spatial patterns of land use in the mangrove of the Brazilian Amazon coast, and evaluated the anthropogenic drivers of this impact, using a remote sensing approach. We mapped the road network using RapidEye images, and human settlements using global data. The results of these analyses indicate that the Brazilian Amazon coast has a low population density and low rates of anthropogenic impact in most of the coastal microregions investigated, factors that contribute to the maintenance and conservation of the region’s mangrove. The study also revealed that the paved road network is one of the principal drivers of land use in the mangrove, whereas other factors, such as population density, urban centers, and the number of settlements are much less important. While the region has 2024 km of paved highways, unpaved roads (17,496 km) facilitate access to the mangrove, with approximately 90% of anthropogenic impact being recorded within a 3 km radius of these roads. While the network of paved highways is relatively reduced in extension, preventive measures are urgently required to impede any major shift in the current scenario, caused by the expansion of major development programs. The results of the study indicate that biophysical, economic, and political factors may also contribute to the reduction, stability, and development of one of the world’s largest areas of mangrove forest. [ABSTRACT FROM AUTHOR]

Farmland expansion in the Brazilian Cerrado, considered one of the largest agricultural frontiers in the world, has the potential to alter water fluxes on different spatial scales. Despite some large-scale studies being developed, there are still few investigations in experimental sites in this region. Here, we investigate the water balance components in experimental plots and the groundwater table fluctuation in different land covers: wooded Cerrado, sugarcane, pasture and bare soil. Furthermore, we identify possible water balance trade-offs due to the different land covers. This study was developed between 2012 and 2016 in the central region of the state of São Paulo in southern Brazil. Hydrometeorological variables, groundwater table, surface runoff and other water balance components were monitored inside experimental plots containing different land covers; the datasets were analyzed using statistical parameters; and the water balance components uncertainties were computed. Replacing wooded Cerrado by pastureland and sugarcane shifts the overland flow (up to 42 mm yr -1) and the water balance residual (up to 504 mm yr -1) and may affect groundwater table behavior. This fact suggests significant changes in the water partitioning in a transient land cover and land use (LCLU) system, as the evapotranspiration is lower (up to 719 mm yr -1) in agricultural land covers than in the undisturbed Cerrado. We recommend long-term observations for continuing the evaluations initiated in this study, mainly because there are few basic studies on tropical environments at the hillslope scale and more assessments are needed for a better understanding of the real field conditions. Such efforts should be made to reduce uncertainties, validate the water balance hypothesis and catch the variability of hydrological processes. [ABSTRACT FROM AUTHOR]

Protected areas (PAs) remain the dominant policy to protect biodiversity and ecosystem services but have been shown to have limited impact when development interests force them to locations with lower deforestation pressure. Far less known is that such interests also cause widespread tempering, reduction, or removal of protection [i.e., PA downgrading, downsizing, and degazettement (PADDD)]. We inform responses to PADDD by proposing and testing a bargaining explanation for PADDD risks and deforestation impacts. We examine recent degazettements for hydropower development and rural settlements in the state of Rondônia in the Brazilian Amazon. Results support two hypotheses: (i) ineffective PAs (i.e., those where internal deforestation was similar to nearby rates) were more likely to be degazetted and (ii) degazettement of ineffective PAs caused limited, if any, additional deforestation. We also report on cases in which ineffective portions were upgraded. Overall our results suggest that enhancing PAs' ecological impacts enhances their legal durability. [ABSTRACT FROM AUTHOR]

Forest fires cause many environmental impacts, including air pollution. Brazil is a very fire-prone region where few studies have investigated the impact of wildfires on air quality and health. We proposed to test two hypotheses in this study: i) the wildfires in Brazil have increased the levels of air pollution and posed a health hazard in 2003–2018, and ii) the magnitude of this phenomenon depends on the type of land use and land cover (e.g., forest area, agricultural area, etc.). Satellite and ensemble models derived data were used as input in our analyses. Wildfire events were retrieved from Fire Information for Resource Management System (FIRMS), provided by NASA; air pollution data from the Copernicus Atmosphere Monitoring Service (CAMS); meteorological variables from the ERA-Interim model; and land use/cover data were derived from pixel-based classification of Landsat satellite images by MapBiomas. We used a framework that infers the "wildfire penalty" by accounting for differences in linear pollutant annual trends (β) between two models to test these hypotheses. The first model was adjusted for Wildfire-related Land Use activities (WLU), considered as an adjusted model. In the second model, defined as an unadjusted model, we removed the wildfire variable (WLU). Both models were controlled by meteorological variables. We used a generalized additive approach to fit these two models. To estimate mortality associated with wildfire penalties, we applied health impact function. Our findings suggest that wildfire events between 2003 and 2018 have increased the levels of air pollution and posed a significant health hazard in Brazil, supporting our first hypothesis. For example, in the Pampa biome, we estimated an annual wildfire penalty of 0.005 μg/m3 (95%CI: 0.001; 0.009) on PM 2.5. Our results also confirm the second hypothesis. We observed that the greatest impact of wildfires on PM 2.5 concentrations occurred in soybean areas in the Amazon biome. During the 16 years of the study period, wildfires originating from soybean areas in the Amazon biome were associated with a total penalty of 0.64 μg/m3 (95%CI: 0.32; 0.96) on PM 2.5 , causing an estimated 3872 (95%CI: 2560; 5168) excess deaths. Sugarcane crops were also a driver of deforestation-related wildfires in Brazil, mainly in Cerrado and Atlantic Forest biomes. Our findings suggest that between 2003 and 2018, fires originating from sugarcane crops were associated with a total penalty of 0.134 μg/m3 (95%CI: 0.037; 0.232) on PM 2.5 in Atlantic Forest biome, resulting in an estimated 7600 (95%CI: 4400; 10,800) excess deaths during the study period, and 0.096 μg/m3 (95%CI: 0.048; 0.144) on PM 2.5 in Cerrado biome, resulting in an estimated 1632 (95%CI: 1152; 2112) excess deaths during the study period. Considering that the wildfire penalties observed during our study period may continue to be a challenge in the future, this study should be of interest to policymakers to prepare future strategies related to forest protection, land use management, agricultural activities, environmental health, climate change, and sources of air pollution. • Effects of wildfires on air pollution and health in Brazil varies across land use. • Greatest effect of wildfires on PM 2.5 occurred in soybean areas in the Amazon. • Soybean in the Amazon was linked with a penalty of 0.72 μg/m3 on PM 2.5. • Wildfires from soybean areas caused 3872 excess deaths. • Sugarcane crops area driver of deforestation-related wildfires in Brazil. [ABSTRACT FROM AUTHOR]

The city of Rio de Janeiro (Brazil) is located in a tropical zone of the planet, in medium latitude that experiences strong insolation throughout the year. The existence of different geographic factors, and different land uses and covers favor the diversity of existing microclimates. This study aims to analyze the different land uses and covers during the last 30 years that impact the varying climatic conditions in the city of Rio de Janeiro, especially for the development of the urban heat and fresh islands. To accomplish this research, images were used from the satellites Landsat-5 and Landsat-7 to capture the apparent surface temperatures, and land use and land cover maps. Comparing these three decades (1986, 1997 and 2016), an increase in the temperatures of urban areas is noticeable toward the last year, 2016. The neighborhoods located in the West and North zones showed the highest temperatures. The areas near the Pedra Branca, Tijuca and Mendanha massifs showed lower temperatures. Therefore, it is possible to recognize a relationship between land cover and temperature behavior; the greenest areas tend to register lower temperatures, and the urban areas demonstrate higher temperatures. [ABSTRACT FROM AUTHOR]

This study aims to analyse the dynamics of land-use and land-cover (LULC) in a selected southern Amazonian area (Brazil), monitoring and distinguishing trajectories in NDVI (Normalized Difference Vegetation Index) variations for the last three decades. The area, with a total of 17336 km², has been subject to significant LULC changes associated with deforestation progress and use of fire. Considering available Landsat time series, it was selected an image per year from 1984 to 2013 (path/row -231/66), at a particular period of year, atmospherically corrected using LEDAPS tools. NDVIs values were generated for each selected image. Furthermore, the images of 1984 and 2010 still underwent a classification of LULC differentiate five categories: water, forest, secondary/degraded forest, savannah/pasture and crop/bare soil. The trajectories in NDVI variation values were analysed by R software, considering intersections of classified categories. The pixels identified as forests on the images of 1984 and 2010 displayed stable trajectories of NDVI values, with average value 0.824 and coefficient of variation 3.9%. While the pixels of savannah/pasture, which was periodically affected by fire, had an average NDVI value 0.585 and coefficient of variation 15,1%. The main regressive trajectory was the transition "forest to crop/bare soil", identifying 1999 as the starting point in the drop in NDVI values, associated with an increase of the deforested areas. Therefore, the results show distinct trajectories associated with NDVIs and LULC changes that assist in better understanding the dynamics of ecological processes and the human impacts operating in the area. [ABSTRACT FROM AUTHOR]

Approximately 57% of the Brazilian northeast region is recognized as semi-arid land and has been undergoing intense land use processes in the last decades, which have resulted in severe degradation of its natural assets. Therefore, the objective of this study is to identify the areas that are susceptible to desertification in this region based on the 11 influencing factors of desertification (pedology, geology, geomorphology, topography data, land use and land cover change, aridity index, livestock density, rural population density, fire hot spot density, human development index, conservation units) which were simulated for two different periods: 2000 and 2010. Each indicator were assigned weights ranging from 1 to 2 (representing the best and the worst conditions), representing classes indicating low, moderate and high susceptibility to desertification. The results indicate that 94% of the Brazilian northeast region is under moderate to high susceptibility to desertification. The areas that were susceptible to soil desertification increased by approximately 4.6% (83.4 km²) from 2000 to 2010. The implementation of the methodology provides the technical basis for decisionmaking that involves mitigating actions and the first comprehensive national assessment within the United Nations Convention to Combat Desertification framework. [ABSTRACT FROM AUTHOR]

Changes in land cover, especially the replacement of forest by agricultural activities affect the hydrological processes of river catchments, resulting in physical and chemical compositional changes of water draining from affected basins. The aim of this study was to evaluate landscape influences at different spatial scales (catchment and riparian) on the physical and chemical composition of stream water in 15 agricultural catchments, belonging to the Corumbataíbasin (Brazil). We calculated the average slope (%), average elevation (m), soil classes (%), major land use classes (%), average distance from the forest cover in relation to the hydrographic network (m), largest patch index (%) at the catchment scale and riparian zone of drainage network scale within a 30 m buffer. Water samples were collected in two seasons (dry and rainy) to characterize physical and chemical properties: turbidity, suspended solids, total nitrogen, nitrate and total phosphorus. Our results showed higher concentration of nitrate in sugarcane fields and larger amount of suspended solids and turbidity in pasture areas. We concluded that degraded and highly fragmented forests may not be effectively contributing toward the protection of aquatic ecosystems. [ABSTRACT FROM AUTHOR]