Across South America, the expansion of commodity land uses has underpinned substantial economic development at the expense of natural land cover and associated ecosystem services. Here, we show that such human impact on the continent's land surface, specifically land use conversion and natural land cover modification, expanded by 268 million hectares (Mha), or 60%, from 1985 to 2018. By 2018, 713 Mha, or 40%, of the South American landmass was impacted by human activity. Since 1985, the area of natural tree cover decreased by 16%, and pasture, cropland, and plantation land uses increased by 23, 160, and 288%, respectively. A substantial area of disturbed natural land cover, totaling 55 Mha, had no discernable land use, representing land that is degraded in terms of ecosystem function but not economically productive. These results illustrate the extent of ongoing human appropriation of natural ecosystems in South America, which intensifies threats to ecosystem-scale functions.
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http://dx.doi.org/10.1126/sciadv.abg1620 | DOI Listing |
Ecohealth
January 2025
Forestry and Forest Products Research Institute, Matsunosato 1, Tsukuba, Ibaraki, 305-8687, Japan.
Anthropogenic disturbances degrade ecosystems, elevating the risk of emerging infectious diseases from wildlife. However, the key environmental factors for preventing tick-borne disease infection in relation to host species, landscape components, and climate conditions remain unknown. This study focuses on identifying crucial environmental factors contributing to the outbreak of severe fever with thrombocytopenia syndrome (SFTS), a tick-borne disease, in Miyazaki Prefecture, southern Japan.
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January 2025
School of Geography and Environment, Liaocheng University, Liaocheng, 252059, Shandong, China.
The complex topography of the mountain cities leads to uneven distribution of land resources. Currently, available studies mainly focuse on land use and landscape patterns (LU and LP) in plains or plateaus. Thus, it is necessary to carry out an analysis of the drivers of changes in LU and LP in mountain cities.
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January 2025
College of Ecology and Environment, Hainan University, Haikou, 570228, China.
Agroforestry systems are known to enhance soil health and climate resilience, but their impact on greenhouse gas (GHG) emissions in rubber-based agroforestry systems across diverse configurations is not fully understood. Here, six representative rubber-based agroforestry systems (encompassing rubber trees intercropped with arboreal, shrub, and herbaceous species) were selected based on a preliminary investigation, including Hevea brasiliensis intercropping with Alpinia oxyphylla (AOM), Alpinia katsumadai (AKH), Coffea arabica (CAA), Theobroma cacao (TCA), Cinnamomum cassia (CCA), and Pandanus amaryllifolius (PAR), and a rubber monoculture as control (RM). Soil physicochemical properties, enzyme activities, and GHG emission characteristics were determined at 0-20 cm soil depth.
View Article and Find Full Text PDFSci Data
January 2025
Remote Sensing Centre for Earth System Research (RSC4Earth), Leipzig University, Leipzig, 04103, Germany.
With climate extremes' rising frequency and intensity, robust analytical tools are crucial to predict their impacts on terrestrial ecosystems. Machine learning techniques show promise but require well-structured, high-quality, and curated analysis-ready datasets. Earth observation datasets comprehensively monitor ecosystem dynamics and responses to climatic extremes, yet the data complexity can challenge the effectiveness of machine learning models.
View Article and Find Full Text PDFSci Total Environ
January 2025
Department of Biology, Ecology and Earth Sciences (DIBEST), University of Calabria, Ponte Bucci street, cube 15B, 87036 Rende, Italy.
The work aims to estimate natural greenhouse gas emissions from soils in the Sibari Coastal Plain (Southern Italy), to understand (i) the contribution in terms of the total amount of CO and CH emitted in non-volcanic areas, (ii) the relationship among emitted gas, land use, organic matter and tectonic structures, and (iii) their potential environmental implications. Data were elaborated with statistical and geostatistical methods to separate the different populations and obtain prediction and probability maps. Methane fluxes had values consistently below the detection limit (0.
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