Assessing the relationship between river water pollution and the LULC composition of a basin in the Isthmus of Tehuantepec in Oaxaca, Mexico.

Water pollution originating from land use and land cover (LULC) can disrupt river ecosystems, posing a threat to public health, safety, and socioeconomic sustainability. Although the interactions between terrestrial and aquatic systems have been investigated for decades, the scale at which land use practices, whether in the entire basin or separately in parts, significantly impact water quality still needs to be determined. In this research, we used multitemporal data (field measurements, Sentinel 2 images, and elevation data) to investigate how the LULC composition in the catchment area (CA) of each water pollution measurement station located in the river course of the Los Perros Basin affects water pollution indicators (WPIs). We examined whether the CAs form a sequential runoff aggregation system for certain pollutants from the highest to the lowest part of the basin. Our research applied statistical (correlation, time series analysis, and canonical correspondence analysis) and geo-visual analyses to identify relationships at the CA level between satellite-based LULC composition and WPI concentrations. We observed that pollutants such as nitrogen, phosphorus, coliforms, and water temperature form a sequential runoff aggregation system from the highest to the lowest part of the basin. We concluded that the observed decrease in natural cover and increase in built-up and agricultural cover in the upper CAs of the study basin between the study period (2016 to 2020) are related to elevated WPI values for suspended solids and coliforms, which exceeded the allowed limits on all CAs and measured dates.

Soil erosion assessment in the Amazon basin in the last 60 years of deforestation.

Anthropic activities in the Amazon basin have been compromising the environmental sustainability of this complex biome. The main economic activities depend on the deforestation of the rainforest for pasture cattle ranching and agriculture. This study analyzes soil erosion to understand how deforestation has impacted the Amazon basin in this context, using three land-use temporal maps (1960, 1990, 2019) through the revised universal soil loss equation (RUSLE). Our results point to a significant influence of deforestation due to the expansion of agricultural and livestock activities on soil erosion rates in the Amazon Basin. The average soil erosion rate has increased by more than 600% between 1960 and 2019, ranging from 0.015 Mg ha-1 year-1 to 0.117 Mg ha-1 year-1. During this period, deforestation of the Amazon rainforest was approximately 7% (411,857 km2), clearly the leading cause of this increase in soil erosion, especially between 1990 and 2019. The south and southeast regions are the most impacted by increasing soil erosion, in which deforestation was accelerated for expanding agriculture and livestock activities, mainly in the sub-basins of the Madeira, Solimões, Xingu, and Tapajós that present soil erosion increases of 390%, 350%, 280%, and 240%, respectively. The sub-basins with the highest sediment delivery rate (SDR) are under the influence of the Andes, highlighting Solimões (27%), Madeira (13%), and Negro (6%) due to the increase in the soil erosion rate increase in these sub-basins.

Four-decade (1977-2017) landscape tale of tourist reservoir hotspot El Piñol-Guatapé, Colombia.

Efficient management of land use/land cover (LULC) features is vital for a balanced sustainable ecosystem. Thus, this work aimed to document the LULC changes in the less studied El Peñol-Guatapé reservoir, Antioquia, Colombia, especially in the reservoir area due to the construction of a hydro-electric power plant. For this study, Landsat images of 1977, 1986, 1997, and 2017 were used and the results indicated an increase in the settlement area and road networks by 0.10 and 0.60%, respectively, while during 1986 to 2017, cropland, plantation, dense forest, and open forest areas presented an increase of 0.52, 1.06, 2.87 and 2.61%, respectively. However, the marshy vegetation, scrub forest and fallow land decreased to - 0.51, - 3.79 and - 4.29%, respectively, in the same period. The water body before and after the completion of reservoir project denoted an increase from 13.1 km2 in 1977 to 45.7 km2 in 1986. This study provides a first-hand report on LULC dynamics in this tourism dominated municipalities that will serve as a reference for ecosystem management to reconcile the conflicts between different LULC classes in ecologically enriched regions.

Investigation of pre and post environmental impact of the lockdown (COVID-19) on the water quality of the Capibaribe and Tejipió rivers, Recife metropolitan region, Brazil.

The coronavirus pandemic has seriously affected human health, although some improvements on environmental indexes have temporarily occurred, due to changes on socio-cultural and economic standards. The objective of this study was to evaluate the impacts of the coronavirus and the influence of the lockdown associated with rainfall on the water quality of the Capibaribe and Tejipió rivers, Recife, Northeast Brazil, using cloud remote sensing on the Google Earth Engine (GEE) platform. The study was carried out based on eight representative images from Sentinel-2. Among the selected images, two refer to the year 2019 (before the pandemic), three refer to 2020 (during a pandemic), two from the lockdown period (2020), and one for the year 2021. The land use and land cover (LULC) and slope of the study region were determined and classified. Water turbidity data were subjected to descriptive and multivariate statistics. When analyzing the data on LULC for the riparian margin of the Capibaribe and Tejipió rivers, a low permanent preservation area was found, with a predominance of almost 100% of the urban area to which the deposition of soil particles in rivers are minimal. The results indicated that turbidity values in the water bodies varied from 6 mg. L-1 up to 40 mg. L-1. Overall, the reduction in human-based activities generated by the lockdown enabled improvements in water quality of these urban rivers.

Spatio-temporal analysis of land use/land cover change dynamics in Paraguai/Jauquara Basin, Brazil.

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.

Increased burned area in the Pantanal over the past two decades.

Wildfires are behaving differently now compared to other time in history in relation to frequency, intensity and affected ecosystems. In Brazil, unprecedented fires are being experienced in the last decade. Thus, to prevent and minimize similar disasters, we must better understand the natural and human drivers of such extreme events. The Brazilian Pantanal is the largest contiguous wetland in the world and a complex environmental system. In 2020, Pantanal experienced catastrophic wildfires due to the synergy between climate, inadequate fire management strategies and weak environmental regulations. In this study, we analyzed recent patterns and changes in fire behavior across the Pantanal based on land use and cover (LULC) classes. The inter-annual variability of the fire and land cover changes between 2000 and 2021 was assessed using BA from MCD64A1 V.6 product and LULC data from Landsat satellite. Our work reveals that fires in the Pantanal over the last two decades tended to occur more frequently in grassland than in others land cover types, but the 2020 fires have preferentially burned forest regions. Large fire patches are more frequent in forest and grasslands; in contrast, croplands exhibit small patches. The results highlight that a broad scale analysis does not reflect distinct localized patterns, thus stratified and refined studies are required. Our work contributes as a first step to disentangling the role of anthropogenic-related drivers, namely LULC changes, in shaping the fire regime in the Pantanal biome. This is crucial not only to predict future fire activity but also to guide appropriated fire management in the region.

A classification of cultivated pastures in the Brazilian Cerrado for sustainable intensification and savanna restoration.

The Brazilian Cerrado, with over 200 million hectares, has approximately 28% of its area occupied by cultivated pasturelands and 39% of them are degraded. In this study, we propose a new classification of the Cerrado pastures and recommendations for sustainable intensification and savanna restoration. We propose seven classes of pastures based on the ground cover proportions of exotic grass, bare soil, and native vegetation. These lands need to be acknowledged for their biodiversity conservation and potential for sustainable intensification and restoration. In order to make ecological intensification available for the ranchers, research and technology transfer have to embrace native tree species-based silviculture, native-grass-based forage management and enhancement, and value chain of biodiversity-friendly products. The pasture management proposals of this paper are based on a concept of biodiversity as an ecosystem service, promoting local productivity and global ecosystem services.

Data for: Terrain units, land use/cover, and gross primary productivity of the largest fluvial basin in the Brazilian Amazonia/Cerrado ecotone: The Araguaia River Basin.

Integrity of most of tropical wetlands is threatened because they are often considered freely available resources of land and water. The Araguaia River Basin is one of the Brazilian basins most influenced by tropical seasonal floods, in addition to being rich in biodiversity and providing diverse ecosystem services. Here, we propose the analysis of the landscape of Araguaia Basin in terms of terrain units, rainfall, land use/cover and gross primary productivity (GPP). For this, the integration of different databases was made, including the topographic domains, protected areas and indigenous lands; land use/cover map (year 2016); time series of GPP derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor (period of 2000-2015); Shuttle Radar Topography Mission (SRTM) digital elevation models (DEM); and precipitation data produced by the WorldClim version 2 dataset. GPP time serie were processed using statistical methods of decomposition throughout R software. The proposed methodology can assist in new studies aimed at land use changes and carbon cycles.

The transparency, reliability and utility of tropical rainforest land-use and land-cover change models.

Land-use and land-cover (LULC) change is one of the largest drivers of biodiversity loss and carbon emissions globally. We use the tropical rainforests of the Amazon, the Congo basin and South-East Asia as a case study to investigate spatial predictive models of LULC change. Current predictions differ in their modelling approaches, are highly variable and often poorly validated. We carried out a quantitative review of 48 modelling methodologies, considering model spatio-temporal scales, inputs, calibration and validation methods. In addition, we requested model outputs from each of the models reviewed and carried out a quantitative assessment of model performance for tropical LULC predictions in the Brazilian Amazon. We highlight existing shortfalls in the discipline and uncover three key points that need addressing to improve the transparency, reliability and utility of tropical LULC change models: (1) a lack of openness with regard to describing and making available the model inputs and model code; (2) the difficulties of conducting appropriate model validations; and (3) the difficulty that users of tropical LULC models face in obtaining the model predictions to help inform their own analyses and policy decisions. We further draw comparisons between tropical LULC change models in the tropics and the modelling approaches and paradigms in other disciplines, and suggest that recent changes in the climate change and species distribution modelling communities may provide a pathway that tropical LULC change modellers may emulate to further improve the discipline. Climate change models have exerted considerable influence over public perceptions of climate change and now impact policy decisions at all political levels. We suggest that tropical LULC change models have an equally high potential to influence public opinion and impact the development of land-use policies based on plausible future scenarios, but, to do that reliably may require further improvements in the discipline.