Search Results (428)

This study aimed to evaluate the impact of vineyard cultivation time and the use of metal-based fungicides on the chemical fractions of soil organic matter (SOM) as well as their interactions with Cu, Zn, and Mn in vineyard soils from Southern Brazil with varying histories of fungicide application. Soil samples were collected in 2017 from vineyards aged 35, 37, and 39 years in the Serra Gaúcha region and 13, 19, and 36 years in the Campanha Gaúcha. In each region, samples were also collected from a non-anthropized reference area. In the oldest vineyards, sampling was conducted both within and between the rows of planting. Chemical fractionation of SOM was performed: non-humic substances (nHSs), particulate organic matter (POM), fulvic acid (FA), humic acid (HA), and humin (Hu). Fourier-transform infrared (FTIR) spectra were obtained for the HA, from which the aromaticity index (AI) and relative intensities (RIs) were calculated. In each SOM fraction, total organic carbon and the concentrations of Cu, Zn, and Mn were determined. Changes in land use alter the forms and distribution of soil organic carbon (SOC) and, consequently, of metals. Elemental and spectroscopic analyses of HS revealed that HA in the reference areas (forest and native grassland) was more aliphatic and had higher concentrations of polysaccharides, indicating fractions with a lower degree of stabilization. However, in vineyard areas, HA exhibited greater humification and aromaticity. Increasing cultivation time gradually increased soil carbon content, indicating that viticultural agroecosystems can sequester carbon in the soil over time, reaching levels similar to those observed in the reference areas. When comparing vineyard areas alone, with row collections and inter-row collections, we observed an increase in SOC levels in areas managed with cover crops, demonstrating the importance of conservation management in these areas. When evaluating the distribution of metals in these soils, we could observe the high affinity of Cu for the functional groups of SOM, with FA and HA responsible for the complexation of these elements in the soil. For Zn and Mn, the greatest accumulations were observed in the Hu fraction due to their greater affinity for soil clay minerals. This shows that soil organic matter is a key component in the complexation of metals in soils, reducing their availability and potential toxicity to cultivated plants. Full article

Urbanization profoundly alters environmental conditions (e.g., temperature, artificial light at night (ALAN), and precipitation) that strongly influence vegetation phenology. However, the rate and extent of vegetation phenological responses to urbanization, as well as their underlying mechanisms, remain underexplored, particularly the roles of CO₂ emissions and PM₂.₅ concentrations, as well as the interactions among environmental conditions. We first used road network density (RND) to represent urbanization effects and quantified the phenological response rate and extent across 31 cities in China (2014–2022) using slope and range metrics derived from linear regressions of phenostages (start of season (SOS), end of season (EOS), length of season (LOS)) against RND. Partial least squares structural equation modeling was applied to assess the direct and indirect effects of RND on phenology via all five key environmental factors. Our results identified substantial differences in the urban phenological responses across latitudinal, hydrothermal, and land−cover gradients. And the impact of urbanization on phenology was most pronounced during early expansion (at a RND threshold of 2.02 ± 0.41 km/km²) but diminished with continued growth. Environmental factors distinctly affected phenological response rate and extent through RND; temperature, ALAN, and CO₂ emissions were the dominant drivers of slope, negatively affecting SOS (β = −0.37 to −0.69) but positively affecting EOS and LOS (β = 0.31 to 0.68). PM₂.₅ played a crucial role in determining the range of SOS (β = −0.31), and precipitation had the largest impact on the range of EOS (β = −0.37). Our study innovatively uses RND to quantify urbanization intensity and improve understanding of the combined effects of multiple drivers, especially PM₂.₅ and CO₂, on phenological responses, which may offer a useful reference for future urban planning strategies that aim to balance development with ecosystem functioning. Full article

Flash floods, exacerbated by climate change and land use alterations, are among the most destructive natural hazards globally, leading to significant damage and loss of life. In this context, the Flash Flood Potential Index (FFPI), which is a terrain and land surface-based model, and Google Earth Engine (GEE) were used to assess flood-prone zones across North Macedonia’s watersheds. The presented GEE-based assessment was accomplished by a custom script that automates the FFPI calculation process by integrating key factors derived from publicly available sources. These factors, which define susceptibility to torrential floods, include slope (Copernicus GLO-30 DEM), land cover (Copernicus GLO-30 DEM), soil type (SoilGrids), vegetation (ESA World Cover), and erodibility (CHIRPS). The spatial distribution of average FFPI values across 1396 small catchments (10–100 km²) revealed that a total of 45.4% of the area exhibited high to very high susceptibility, with notable spatial variability. The CHIRPS rainfall data (2000–2024) that combines satellite imagery and in situ measurements was used to estimate peak 24 h runoff and discharge. To improve the accuracy of CHIRPS, the data were adjusted by 30–50% to align with meteorological station records, along with normalized FFPI values as runoff coefficients. Validation against 328 historical river flood and flash flood records confirmed that 73.2% of events aligned with moderate to very high flash flood susceptibility catchments, underscoring the model’s reliability. Thus, the presented cloud-based scenario highlights the potential of the GEE’s efficacy in scalability and robustness for flash flood modeling and regional risk management at national scale. Full article

White-tailed deer (Odocoileus virginianus) are a cervid species native to the Americas with ecological, social, and economic significance. Managers must consider several factors when working to maintain the health and sustainability of these wild herds, including reproduction, particularly pregnancy and recruitment rates. White-tailed deer have a variable reproductive capacity, with age, health, and habitat influencing this variability. However, it is unknown whether chronic wasting disease (CWD) impacts reproduction and, more specifically, if CWD infection alters a female deer’s probability of pregnancy. Our study addressed this question using data from 9783 female deer culled in northern Illinois between 2003 and 2023 as part of the Illinois Department of Natural Resources’ ongoing CWD management program. Multilevel Bayesian logistic regression was employed to quantify the relationship between pregnancy probability and covariates like maternal age, deer population density, and date of culling. Maternal infection with CWD was found to have no significant effect on pregnancy probability, raising concerns that the equal ability of infected and non-infected females to reproduce could make breeding, which inherently involves close physical contact, an important source of disease transmission between males and females and females and their fawns. The results also identified that female fawns (<1 year old) are sensitive to county-level deer land cover utility (LCU) and deer population density, and that there was no significant difference in how yearlings (1–2 years old) and adult (2+ years old) responded to these variables. Full article

The Brazilian Amazon is recognized worldwide for its biodiversity and it plays a key role in maintaining the regional and global climate balance. However, it has recently been greatly impacted by changes in land use, such as replacing native forests with agricultural activities. These changes have resulted in serious environmental consequences, including significant alterations to climate and hydrological cycles. This study aims to analyze changes in land use and land covered in the Brazilian Amazon between 2001 and 2023, as well as the resulting effects on precipitation variability, land surface temperature, and evapotranspiration. Data obtained via remote sensing and processed on the Google Earth Engine platform were used, including MODIS, CHIRPS, Hansen products. The results revealed significant changes: forest formation decreased by 8.55%, while agricultural land increased by 575%. Between 2016 and 2023, accumulated deforestation reached 242,689 km². Precipitation decreased, reaching minimums of 772.7 mm in 2015 and 726.4 mm in 2020. Evapotranspiration was concentrated between 941 and 1360 mm in 2020, and surface temperatures ranged between 30 °C and 34 °C in 2015, 2020, and 2023. We conclude that anthropogenic transformations in the Brazilian Amazon directly impact vegetation cover and the regional climate. Therefore, conservation and monitoring measures are essential for mitigating these effects. Full article

Land cover, topography, precipitation, and socio-economic factors exert both direct and indirect influences on urban land surface temperatures. Within the broader context of global climate change, these influences are magnified by the escalating intensity of the urban heat island effect. However, the interplay and underlying mechanisms of natural and socio-economic determinants of land surface temperatures remain inadequately explored, particularly in the context of cold-region cities located in the northern temperate zone of China. This study focuses on Changchun City, employing multispectral remote sensing imagery to derive and spatially map the distribution of land surface temperatures and topographic attributes. Through comprehensive analysis, the research identifies the principal drivers of temperature variations and delineates their seasonal dynamics. The findings indicate that population density, night-time light intensity, land use, GDP (Gross Domestic Product), relief, and elevation exhibit positive correlations with land surface temperature, whereas slope demonstrates a negative correlation. Among natural factors, the correlations of slope, relief, and elevation with land surface temperature are comparatively weak, with determination coefficients (R²) consistently below 0.15. In contrast, socio-economic factors exert a more pronounced influence, ranked as follows: population density (R² = 0.4316) > GDP (R² = 0.2493) > night-time light intensity (R² = 0.1626). The overall hierarchy of the impact of individual factors on the temperature model, from strongest to weakest, is as follows: population, night-time light intensity, land use, GDP, slope, relief, and elevation. In examining Changchun and analogous cold-region cities within the northern temperate zone, the research underscores that socio-economic factors substantially outweigh natural determinants in shaping urban land surface temperatures. Notably, human activities catalyzed by population growth emerge as the most influential factor, profoundly reshaping the urban thermal landscape. These activities not only directly escalate anthropogenic heat emissions, but also alter land cover compositions, thereby undermining natural cooling mechanisms and exacerbating the urban heat island phenomenon. Full article

Vegetation succession is a critical indicator of ecosystem structure and function and is often disrupted by the expansion of invasive species. However, ecosystem-scale studies elucidating invasion-driven succession mechanisms remain limited. This research focused on the Yancheng coastal salt marsh and analyzed the distribution variation of invasive species (Spartina alterniflora) and native species (Suaeda salsa and Phragmites australis) from 1987 to 2022 via the Google Earth Engine and random forest method. Logistic/Gaussian models were used to quantify land–sea distribution changes and vegetation succession trajectories. By integrating data on soil salinity, invasion duration, and fractional vegetation cover, generalized additive models (GAMs) were applied to identify the main factors influencing vegetation succession and to explore how Spartina alterniflora invasion affects the succession of salt marsh vegetation. The results indicated that the areas of Spartina alterniflora and Phragmites australis significantly increased by 3787.49 ha and 3452.60 ha in 35 years, respectively, contrasting with Suaeda salsa’s 82.46% decline. The FVC in the area has significantly increased by 42.10%, especially in the coexisted areas of different vegetation communities, indicating intensified interspecific competition. The overall trend of soil salinity was decreasing, with a decrease in soil salinity in native species areas from 0.72% to 0.37%. From the results of GAMs, soil salinity, tidal action, and invasion duration were significant factors influencing the distribution of native species, but salinity was not a significant factor affecting the Spartina alterniflora distribution. The findings revealed that the expansion of Spartina alterniflora changed the soil salinity and interspecific interactions, thereby altering the original plant community structure and establishing a new vegetation succession. This study enhances the understanding of the impacts of invasive species on ecosystems and offers theoretical support for salt marsh restoration. Full article

Eco-migration (EM) constitutes a specialized form of migration aimed at enhancing living environments and alleviating ecological pressure. Nevertheless, large-scale external migration has intensified habitat fragmentation (HF) in resettlement areas. This paper takes the Shule River Resettlement Project (SRRP) as a case, based on the China Land Cover Dataset (CLCD) data of the resettlement area from 1996 to 2020, using the Landscape Pattern Index (LPI) and the land use transfer matrix (LTM) to clearly define the stages of migration and the types of resettlement areas and to quantitative explore how EM affects HF. The results show that (1) EM accelerates the transformation of natural habitats (NHs) to artificial habitats (AHs) and shows the characteristics of sudden changes in the initial stage (1996–2002), with stability in the middle stage (2002–2006) and late stage (2007–2010) and dramatic changes in the post-migration stage (2011–2020). In IS, MS, LS, and PS, AH increased by 26.145 km², 21.573 km², 22.656 km², and 16.983 km², respectively, while NH changed by 73.116 km², −21.575 km², −22.655 km², −121.82 km², and −213.454 km², respectively. The more dispersed the resettlement areas are the more obvious the expansion of AH will be, indicating that the resettlement methods for migrants have a significant effect on habitat changes. (2) During the resettlement process, the total number of plaques (NP), edge density (ED), diversity (SHDI), and dominance index (SHEI) all continued to increase, while the contagion index (C) and aggregation index (AI) continued to decline, indicating that the habitat is transforming towards fragmentation, diversification, and complexity. Compared with large-scale migration bases (LMBs), both small-scale migration bases (SMBs), and scattered migration settlement points (SMSPs) exhibit a higher degree of HF, which reflects how the scale of migration influences the extent of habitat fragmentation. While NHs are experiencing increasing fragmentation, AHs tend to show a decreasing trend in fragmentation. Ecological migrants play a dual role: they contribute to the alteration and fragmentation of natural habitat patterns, while simultaneously promoting the formation and continuity of artificial habitat structures. This study offers valuable practical insights and cautionary lessons for the resettlement of ecological migrants. Full article

This study aimed to investigate land-use and land-cover change and the associated change in the ecological stability of the model area Dobrá–Opatová (district of Trenčín, Slovakia), where increasing landscape transformation has raised concerns about declining ecological resilience. Despite the importance of sustainable land management, few studies in this region have addressed long-term landscape dynamics in relation to ecological stability. This research fills that gap by evaluating historical and recent LULC changes and their ecological consequences. Four time horizons were analysed: 1850, 1949, 2009, and 2024. Although the selected time periods are irregular, they reflect key milestones in the region’s land development, such as pre-industrial land use, post-war collectivisation, and recent land consolidation. These activities significantly altered the structure of the landscape. To assess future trends, we used the MOLUSCE plug-in in QGIS to simulate ecological stability for the future. The greatest structural landscape changes occurred between 1850 and 1949. Significant transformation in agricultural areas was observed between 1949 and 2009, when collectivisation reshaped small plots into large block structures and major water management projects were implemented. The 2009–2024 period was marked by land consolidation, mainly resulting in the construction of gravel roads. These structural changes have contributed to a continuous decrease in ecological stability, calculated using the coefficient of ecological stability derived from LULC categories. To explore future trends, we simulated ecological stability for the year 2030 and the simulation confirmed a continued decline in ecological stability, highlighting the need for sustainable land-use planning in the area. Full article

Rivers in tropical semi-arid regions face increasing anthropogenic pressures yet remain critically understudied despite their global importance. This study evaluated the aquatic macroinvertebrate community structure in the Ranchería River, Colombia, across three land use conditions: conserved zones (CZs), urban/agricultural zones (UAZs), and mining influence zones (MZs). Ten sampling stations were established, and macroinvertebrate communities were assessed alongside physical, chemical, and hydromorphological variables during the dry season (January–March 2021). A total of 9288 individuals from 84 genera across 16 orders were collected. Generalized Linear Models revealed significant differences among zones for 67 genera (79.8%), indicating strong community responses to land use gradients. Conserved zones exhibited the highest diversity according to the Hill numbers and were dominated by sensitive taxa, including Simulium, Smicridea, and Leptohyphes. Urban/agricultural zones showed the lowest richness (35 genera) and were characterized by disturbance-tolerant species, particularly Melanoides. Mining zones displayed intermediate diversity but exhibited severe habitat alterations. A redundancy analysis with variance partitioning revealed that land use types constituted the primary driver of community structure (a 24.1% pure effect), exceeding the physical and chemical variables (19.5%) and land cover characteristics (19.2%). The integrated model explained 63.5% of the total compositional variation, demonstrating that landscape-scale anthropogenic disturbances exert a greater influence on aquatic communities than local environmental conditions alone. Different anthropogenic activities create distinct environmental filters affecting macroinvertebrate assemblages, emphasizing the importance of land use planning for maintaining aquatic ecosystem integrity in semi-arid watersheds. Full article

Rapid urbanization and industrial development have significantly altered land use and cover across the globe, intensifying urban thermal environments and exacerbating the urban heat island (UHI) effect. Gujranwala, Pakistan, represents an industrial growth that has driven substantial land use/land cover (LULC) changes and temperature increases; however, the directional and distance-based patterns of these changes remain unquantified. Therefore, this study is conducted to examine spatiotemporal changes in LULC and variations in the Urban Thermal Field Variation Index (UTFVI) between 2001 and 2021 and to project future scenarios for 2031 and 2041 using (1) Earth Observation Indices (EOIs) with machine learning (ML) classifiers (Random Forest) for precise LULC mapping through the Google Earth Engine (GEE) platform, (2) Cellular Automata–Artificial Neural Networks (CA-ANNs) for future scenario projection, and (3) Gradient Directional Analysis (GDA) to quantify directional (16-axis) and distance-based (concentric zones) patterns of urban expansion and thermal variation from 2001–2021. The study revealed significant LULC changes, with built-up areas expanding by 7.5% from 2001 to 2021, especially in the east, northeast, and southeast directions within a 20 km radius. Due to urban encroachment, vegetation and cropland decreased by 1.47% and 1.83%, respectively. The urban thermal environment worsened, with the highest land surface temperature (LST) rising from 41 °C in 2001 to 55 °C in 2021. Additionally, the UTFVI showed expanding areas under the ‘strong’ and ‘strongest’ categories, increasing from 30.58% in 2001 to 33.42% in 2041. Directional analysis highlighted severe thermal stress in the southern and southwestern areas linked to industrial activities and urban sprawl. This integrated approach provides a template for analyzing urban thermal environments in developing cities, supporting targeted mitigation strategies through direction- and distance-specific planning interventions to mitigate UHI impacts. Full article

This study used Jilin-1 satellite data and unmanned aerial vehicle (UAV)-collected visible-thermal infrared imagery to calculate twelve spectral indices and evaluate their effectiveness in distinguishing post-fire forest areas and identifying human-altered land-cover changes in Jinyun Mountain, Chongqing. The research goals included mapping wildfire impacts with M-statistic separability, measuring land-cover distinguishability through Jeffries–Matusita (JM) distance analysis, classifying land-cover types using the random forest (RF) algorithm, and verifying classification accuracy. Cumulative human disturbances—such as land clearing, replanting, and road construction—significantly blocked the natural recovery of burn scars, and during long-term human-assisted recovery periods over one year, the Red Green Blue Index (RGBI), Green Leaf Index (GLI), and Excess Green Index (EXG) showed high classification accuracy for six land-cover types: road, bare soil, deadwood, bamboo, broadleaf, and grass. Key accuracy measures showed producer accuracy (PA) > 0.8, user accuracy (UA) > 0.8, overall accuracy (OA) > 90%, and a kappa coefficient > 0.85. Validation results confirmed that visible-spectrum indices are good at distinguishing photosynthetic vegetation, thermal bands help identify artificial surfaces, and combined thermal-visible indices solve spectral confusion in deadwood recognition. Spectral indices provide high-precision quantitative evidence for monitoring post-fire land-cover changes, especially under human intervention, thus offering important data support for time-based modeling of post-fire forest recovery and improvement of ecological restoration plans. Full article

Anthropogenic activities and climate change have significantly altered runoff generation in the upper Han River basin, posing a challenge to the water supply sustainability for the Middle Route of the South-to-North Water Diversion Project. Land use/cover changes (LUCCs) affect hydrological processes by modifying evapotranspiration, infiltration and soil moisture content. Based on hydro-meteorological data from 1961 to 2023 and LUCC data series from 1985 to 2023, this study aimed to identify the temporal trend in hydro-meteorological variables, to quantify the impacts of underlying land surface and climate factors at different time scales and to clarify the effects of LUCCs and basin greening on the runoff generation process. The results showed that (1) inflow runoff declined at a rate of −1.71 mm/year from 1961 to 2023, with a marked shift around 1985, while potential evapotranspiration increased at a rate of 2.06 mm/year within the same time frame. (2) Annual climate factors accounted for 61.01% of the runoff reduction, while underlying land surface contributed 38.99%. Effective precipitation was the dominant climatic factor during the flood season, whereas potential evapotranspiration had a greater influence during the dry season. (3) From 1985 to 2023, the LUCC changed significantly, mainly manifested by the increasing forest area and decreasing crop land area. The NDVI also showed an upward trend over the years; the actual evapotranspiration increased by 1.163 billion m³ due to the LUCC. This study addresses the climate-driven and human-induced hydrological changes in the Danjiangkou Reservoir and provides an important reference for water resource management. Full article

The construction of hydroelectric dams leads to substantial land-cover alterations, particularly through the removal of vegetation in wetland and valley areas. This results in exposed sediment that is susceptible to erosion, potentially leading to dust storms. While the reintroduction of vegetation plays a crucial role in restoring these landscapes and mitigating erosion, such efforts incur substantial costs and require detailed information to help optimize vegetation densities that effectively reduce dust storm risk. This study evaluates the performance of drones for measuring the growth of introduced low-lying grasses on reservoir beaches. A set of test flights was conducted to compare LiDAR and photogrammetry data, assessing factors such as flight altitude, speed, and image side overlap. The results indicate that, for this specific vegetation type, photogrammetry at lower altitudes significantly enhanced the accuracy of vegetation classification, permitting effective quantitative assessments of vegetation densities for dust storm risk reduction. Full article

Increasing forest destruction from land use and land cover change (LULCC) has altered catchment hydrological processes worldwide. This trend is also endemic to the Belize River Watershed (BRW), a significant source of land and water resources for Belize. This study aims to understand LULCC impacts on BRW hydrological responses from 2000 to 2020 by applying the widely used Soil and Water Assessment Tool (SWAT). This study identified historical trends in LULCC in the BRW and explored an alternative 2020 land cover scenario to elucidate the role of protected forests for hydrological response regulation. A SWAT model for the BRW was developed at the monthly timescale and calibrated on in situ streamflow using SWAT Calibrations and Uncertainty Programs (SWAT-CUP). The results showed that the BRW SWAT model performed satisfactorily for streamflow simulation at the Benque Viejo (BV) gauge station but performed variably at the Double Run (DR) gauge station. Overall, the findings revealed watershed-level increases in monthly average sediment yield (34.40%), surface runoff (24.95%), streamflow (16.86%), water yield (16.02%), baseflow (11.58%), and percolation (3.40%), and decreases in monthly average evapotranspiration (ET) (3.52%). In conclusion, the BRW SWAT model is promising for uncovering the hydrological impacts of LULCCs with opportunities for further model improvement. Full article