Search Results (6,666)

The Loess Plateau (China) is an ecologically fragile region where understanding the impact of forest naturalness on soil carbon content is critical for ecological restoration and enhancing carbon sequestration. This study investigates this relationship in the Cuiying Mountain area (Yuzhong County, Lanzhou City), a representative landscape of the semi-arid Loess Plateau. The Cuiying Mountain ecosystem is characterized by coniferous forests and Gray-cinnamon soils. We assessed forest naturalness using several key indicators: herb coverage, shrub coverage, tree biodiversity, and stand structural attributes. The results revealed a generally low level of forest naturalness at Cuiying Mountain. Although herb coverage was high, shrub coverage was minimal (2.1%), and tree biodiversity was low (Shannon index = 0.09). The stand structure was simple, characterized by considerable variation in individual tree sizes and a single canopy layer (mean mingling degree = 0.14). This structural simplicity aligns with the area’s history of plantation management. Furthermore, analysis of soil physicochemical properties and their relationship with plant diversity identified plant diversity as a significant factor influencing soil carbon content. The strongest correlation was observed between plant species number and topsoil organic carbon (r = 0.77), indicating a particularly pronounced effect of plant diversity on surface soil organic carbon. In summary, while forest naturalness at Cuiying Mountain is generally low, increased plant diversity enhances the accumulation of litter/root exudates and carbonates, suggesting that enhancing plant diversity is an effective strategy for increasing total soil carbon content. This study provides valuable insights for refining ecological restoration practices and strengthening the soil carbon sink function in forest ecosystems across the Loess Plateau and similar semi-arid regions. Full article

Water-extractable carbon is thought to originate from labile organic carbon pools and has been used as an active carbon indicator for soil evaluation in numerous studies. This study aims to explore the regional variation patterns of water-extractable organic carbon (WEOC) and the environmental impact factors associated with it. It examines the variability of WEOC under different climatic conditions and land use types, including grasslands and woodlands, thereby enhancing our understanding of WEOC. We measured the WEOC in the surface soil layers (0–10 cm) of woodlands and grasslands in arid and semi-arid regions. Additionally, we analyzed the effects of varying climatic conditions and land use types on WEOC based on data from literature research. WEOC distribution patterns diverged spatially from soil organic carbon (SOC). WEOC fractions decreased with increasing precipitation, and surface soil WEOC accumulation was observed in arid regions. This accumulation was more pronounced in forest-land, resulting in a more marked divergence in WEOC concentrations between woodlands and grasslands in arid regions. We inferred that the inconsistent correlation between WEOC and SOC across regions arises from their distinct distribution patterns along environmental humidity gradients. Owing to the climate sensitivity of WEOC, its surface soil accumulation in arid areas may increase the vulnerability of soil ecosystems, rendering them more susceptible to environmental disturbances. Such susceptibility could drive organic carbon loss and soil quality degradation. These findings hold promise for improving our understanding of WEOC dynamic, and will also give insight into refining soil carbon balance models and soil management strategies to address environmental changes. Full article

Human settlements’ suitability in ecologically fragile regions is critical for sustainable development and ecological security. However, comprehensive assessments that integrate multiple natural environmental factors are insufficient. Here, we establish a human settlements suitability index (HSI) to assess human settlements’ suitability on the Qinghai–Tibet Plateau, including Relief Degree of Land Surface (RDLS), Temperature–Humidity Index (THI), Land Surface Water Abundance Index (LSWAI), and Land Cover Index (LCI). The results show that: (1) The RDLS of the Qinghai–Tibet Plateau was generally high, reflecting elevated terrain and steep topography, with strong regional variation. THI increases from the northwest arid region to the southeast, while high LSWAI and LCI were concentrated and show a zonal distribution. (2) The HSI ranged from 0.07 to 1, with seven suitability types. Low-suitability was distributed in the Kunlun, Gangdise, Himalayas, and the northern and southern parts of the Tibetan valleys. Mid-suitability appeared in the Sichuan–Tibet Alpine Canyon, while high-suitability was concentrated in the northeast (Qaidam Basin, Qilian, Hengduan Mountains), the west (Menyu), and the Qaidam Basin. (3) Low-suitability covered over 70% of the Qinghai–Tibet Plateau but hosts only 20% of the population. Mid-suitability occupied about 20% of the land, yet contained nearly 70% of the population. High-suitability (HSI > 0.7) areas were limited but concentrated populations in the Qaidam Basin, southern Tibetan valleys, and eastern Sichuan–Tibet Alpine Valleys. Future development should target these high-suitability regions to support sustainable population growth and reduce land pressure. These findings provide a scientific basis for regional planning, population distribution, and ecological security on the Qinghai–Tibet Plateau. Full article

Under the global goals of carbon peaking and carbon neutrality, China’s northern agro-pastoral ecotone—an ecologically fragile transition zone with drastic land use/cover change (LUCC)—is characterized by a lack of in-depth understanding of its “land use conflict–carbon sink response” mechanism, which is essential for regional land optimization and carbon neutrality. This study quantified the spatiotemporal dynamics of carbon storage in the zone from 2000 to 2020 using the InVEST model and identified key driving factors by combining the XGBoost model (R² = 0.73–0.88) with the SHAP framework. The results showed that regional total carbon storage increased by 30.11 × 10⁶ tons (a net growth of 0.57%), mainly driven by forest carbon sinks (+65.74 × 10⁶ tons, accounting for 218.3% of the total increase), while cropland and grassland underwent continuous carbon loss (−53.87 × 10⁶ tons and −35.80 × 10⁶ tons, respectively). Spatially, this presents a pattern of “high-value agglomeration in the central–southern region and low-value fragmentation at urban–rural edges”. The Normalized Difference Vegetation Index (NDVI) was the primary driver (average SHAP value: 426.15–718.91), with its interacting temperature factor evolving from air temperature (2000) to nighttime surface temperature (2020). This study reveals the coupling mechanism of “vegetation restoration–microenvironment regulation–carbon sink gain” driven by the Grain for Green Program, providing empirical support for land use optimization and carbon neutrality in agro-pastoral areas. Full article

Unmanned surface vessels may encounter unknown surface obstacles when sailing. Accurate detection has a significant impact on the subsequent decision-making process. In order to deal with the complex water environment, this paper proposes an object detection framework based on the fusion of LiDAR and camera. The detection framework can achieve real-time and accurate water surface object detection without training, and has strong anti-interference ability. The detection framework achieves the data fusion of LiDAR and camera through external calibration and then uses the detection algorithm of sky–sea boundary (SSB) to establish a clear search area for LiDAR. Then, a two-stage clustering algorithm based on point cloud attributes and distribution information achieves more accurate segmentation. The region of interest (RoI) is obtained from the detection results by image projection. Finally, the region of interest is finely segmented by the saliency object detection algorithm. The experimental results show the effectiveness and robustness of the algorithm. Full article

Land use change is closely related to land surface temperature (LST). Based on remote sensing data from 2001 to 2020, this study analyzed the spatiotemporal variations and driving mechanisms of daytime and nighttime LST in the Urumqi Metropolitan Area (UMA) by combining traditional methods with the eXtreme Gradient Boosting (XGBoost)–SHAP coupled model. Although the average LST trend in the region was one of warming, the pixel-level significance analysis indicated that statistically significant warming (p < 0.05) is concentrated mainly in the urban core (2.65% of the area), while the majority of the region (70%) showed a non-significant warming trend. LST displayed significant spatial clustering, with Moran’s I remaining above 0.990, indicating a positive spatial autocorrelation in spatial distribution. With the advancement of urbanization, the proportion of impervious surfaces increased from 0.87% to 1.14%, while wastelands consistently accounted for approximately 50% of the total area. Different land use types showed distinct effects on the urban heat island (UHI) phenomenon: water bodies, grasslands, and forests played cooling roles, whereas barren land and impervious areas were the main heat contributors. The XGBoost-SHAP analysis further revealed that the importance ranking of driving factors has evolved over time. Among these factors, Elevation dominates, while the influence of population-related factors increased significantly in 2020. This study provides a scientific basis for regulating the thermal environment of cities in arid regions from the perspective of land use. This study provides a scientific basis for regulating the thermal environment of arid-region cities from the perspective of land use. Full article

The Building Information Model (BIM) has been increasingly adopted for building maintenance and management. For existing buildings lacking prior digital models, a BIM is often generated from 3D scanned point clouds. In recent years, the automatic construction of simple BIMs comprising major structural elements, such as floors, walls, ceilings, and columns, has become feasible. However, the automated generation of detailed BIMs that incorporate building equipment, such as electrical installations and safety systems, remains a significant challenge, despite their essential role in facility maintenance. This process not only enriches the information content of the BIM but also provides a foundation for evaluating building safety and hazard levels, as well as for supporting evacuation planning and disaster-preparedness simulations. Such equipment is typically attached to ceilings or walls and is difficult to detect due to its small surface area and thin geometric profile. This paper proposes a method for detecting building equipment based on laser reflection intensity, with the objective of facilitating the automatic construction of detailed BIMs from point clouds acquired by mobile laser scanners (MLSs). The proposed approach first corrects the reflection intensity by eliminating the effects of distance and incidence angle using polynomial approximation, thereby normalizing the intensity values for surfaces composed of identical materials. Given that the corrected intensity approximately follows a normal distribution, outliers are extracted as candidate points for building equipment via thresholding. Subsequently, the point cloud is converted into a 2D image representation, and equipment regions are extracted using morphological operations and connected component labeling. Experiments conducted on point clouds of building ceilings and walls demonstrate that the proposed method achieves a high detection accuracy for various types of building equipment. Full article

Nitrate pollution from agricultural activities is a major cause of surface and groundwater degradation across Europe. In Andalusia, southern Spain, approximately 26% of the regional territory is affected by this type of contamination. To mitigate and prevent nitrate pollution, a regulatory framework has been implemented, establishing specific restrictions and recommendations for agricultural practices and nitrogen fertilization management in designated areas. However, the effectiveness of these measures is often constrained by limited awareness of the issue, insufficient understanding of existing regulations, and a general lack of training in nitrogen fertilization management among farmers. To address these challenges, a specialized training program on crop fertilization was developed for agricultural professionals. This initiative aimed to raise awareness of the environmental impacts of nitrate pollution, disseminate information about relevant legislation, and strengthen technical knowledge related to nitrogen fertilization planning and management, thereby enhancing on-farm decision-making. This study analysed the impact of this training activity on the level of awareness and knowledge regarding nitrate-related issues in Andalusia. Full article

Background/Objectives: Appropriate biomarkers are necessary for early diagnosis and multidisciplinary treatment of pancreatic ductal adenocarcinoma (PDAC). In recent years, the clinical utility of circulating tumor cells (CTC) as biomarkers for various can-cers has been reported; however, their detection rate in PDAC remains low, and clinical evidence is not yet established. CTC detection methods with high reliability and per-formance are essential for clarifying the importance of CTC in patients with PDAC. Methods: A total of 5 mL peripheral blood samples were collected from 38 patients newly diagnosed with PDAC and 17 healthy controls. Negatively enriched cells were immunofluorescently stained with EpCAM-phycoerythrin and cell surface vi-mentin-fluorescein isothiocyanate (CSV). Images were automatically captured using an all-in-one fluorescence microscope. Cellular regions were detected from these images, and the average luminance of the cellular regions was calculated. A total of 9086 and 1071 cell images were obtained from patients with PDAC and healthy controls, respec-tively. Results: In the EpCAM assay, a threshold that included 95% of healthy individuals was optimal for distinguishing patients with PDAC from healthy controls, with a sensi-tivity, specificity, and area under the curve of 0.74, 0.76, and 0.84, respectively. At this threshold, the CTC-positivity rate in patients with PDAC was 76.3%. Conversely, the CSV assay failed to demonstrate a valid threshold to distinguish patients with PDAC from healthy controls. No significant differences were found between CTC and clini-copathological features among patients with PDAC. Conclusions: The method using high-resolution image scanning has the potential to identify CTC with greater objectiv-ity by quantifying cell luminance values. Full article

Urbanization in Cyprus has accelerated significantly over the past 35 years, driven by population growth, infrastructure development, and the expansion of urban centres. This rapid urban transformation has contributed to notable changes in the local climate, primarily through the intensification of the Urban Heat Island (UHI) effect—a phenomenon where urban areas experience significantly higher temperatures than surrounding rural regions. As global climate change continues to influence regional weather patterns, understanding and mitigating local climatic variations such as UHI becomes increasingly critical for sustainable development and public health. In Cyprus, the cities of Nicosia, Limassol, Larnaca, and Paphos have witnessed considerable land use changes, with a growing contrast between densely built urban cores and less developed surrounding areas. This contrast results in uneven energy absorption, reduced vegetation cover, and altered surface temperatures, further exacerbating the effects of climate change at the local level. Full article

Most risk assessment and source apportionment studies of the heavy metals in the surface soils in China have focused primarily on East China, whereas studies focused on Northwest China, particularly regarding heavy metals in surface soils in the central and western areas, remain limited. In this study, surface soils in the central–western Ali region were investigated, and the concentrations of nine heavy metals were determined. Moreover, the distribution patterns and ecological risks of these heavy metals were elucidated via a combination of the geoaccumulation index, pollution load index ($PLI$), comprehensive potential ecological risk index ($RI$), and integrated X-ray diffraction (XRD)–multivariate statistical techniques. Additionally, the pollution characteristics and sources were analyzed. The results indicated the following: (1) The spatial distribution of heavy metal pollution is closely linked to the geological background, and high–pollution zones (e.g., Cr, Ni, Co, Cu, As, and Cd) conform well with the distributions of ultramafic rocks and iron/chromite ore beds. The geoaccumulation index revealed that Cd caused slight and moderate contamination at 29.1% and 5.5% of the sites, respectively, whereas As affected 14.6% of the sites. The pollution load index indicated moderate pollution in 20% of the sites, and the potential ecological risk index indicated that 41.8% of the sites posed moderate risks, which was largely driven by Cd (mean $E_r^i$ = 43.1). The comprehensive ecological risk index ($RI$ = 115) confirmed a moderate risk level overall. Principal component analysis revealed three primary sources: natural weathering (Cr–Ni–Co–Cu, 39.1%); a mixed source influenced by nonagricultural anthropogenic activities such as transport and regional deposition, combined with natural processes such as arid climate and alkaline soil conditions that influence Cd mobility (Cd–Mo–Pb, 20.8%); and industrial/mining activities (As–Sb, 14.2%). Mineralogical analyses further indicated that heavy metals are present via lattice substitution, adsorption, and precipitation. This study systematically clarifies the composite pollution pattern and sources of heavy metals in the alpine Ali region, supporting targeted contamination control. Full article

Organic pores serve as crucial storage spaces for shale gas, whose morphology and structure vary significantly among different types of organic matter, directly influencing the storage and seepage capacity of shale gas. The Upper Permian shale in the Western Hubei Trough formed in diverse sedimentary facies and has undergone multiple geological activities, resulting in strong heterogeneity of organic pores across different strata and regions. To figure out the heterogeneous characteristics of organic pores and the forming reason, the occurrence state of organic matter, pore morphology, and structural parameters (pore size, specific surface area, pore volume, and fractal dimension) of the Upper Permian shale in Western Hubei, have been discussed in detail, based on the data of field emission scanning electron microscopy and low-temperature nitrogen adsorption experiments conducted on the extracted organic matter. On this basis, fractal dimension theory was applied to discuss the heterogeneity of organic pores in different layers, and the reason for heterogeneity has been analyzed in detail. The results indicate that the occurrence mode of organic matter in different layers presents various characteristics: in the Gufeng Formation, the organic matters distribute primarily dispersed in flocculent state; at the bottom of Wujiaping Formation, they occur as isolated individuals, while the organic matters turn into discontinuous laminated distribution in the middle and upper Wujiaping Formation; in the Dalong Formation, the organic matters show continuous parallel banded distribution. Moreover, the morphology and structural parameters of organic pores exhibit obvious changes from the Gufeng Formation to the Dalong Formation: (a) the pore morphology shows the changed trend as extremely complex-simple-complex; (b) the specific surface area and pore volume follow the trend as large-small-large; (c) the pore size distribution displays in the pattern of bimodal-unimodal-bimodal; (d) the data of fractal dimension show the variation of high–low–high. Overall, the various sedimentary environments during the Upper Permian shale depositional period determined the differences in organic sources, which dominated the heterogeneity of organic pores in shale. These data clarify the development and variation characteristics of organic matter pores under different depositional environments, providing a theoretical basis for shale gas exploration and development during the transition from marine to marine–continental facies. Full article

Urban heat island (UHI), a significant environmental issue caused by urbanization, is a pressing challenge in modern society. To mitigate it, urban thermal policies have been implemented globally. However, despite differences in topographical and environmental characteristics between cities and within the same city, these policies are largely uniform and fail to reflect contexts, creating notable drawbacks. This study analyzed three cities in Korea with high land surface temperatures (LSTs) to identify factors influencing LST by applying Extreme Gradient Boosting (XGBoost) with Shapley Additive explanations (SHAP) and Geographically Weighted Regression (GWR). Each variable was derived by calculating the average values from May to September 2020. LST was the dependent variable, and the independent variables were chosen based on previous studies: Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), ALBEDO, Population Density (POP_D), Digital Elevation Model (DEM), and SLOPE. XGBoost-SHAP was used to derive the relative importance of the variables, followed by GWR to assess spatial variation in effects. The results indicate that NDBI, reflecting building density, is the primary factor influencing the thermal environment in all three cities. However, the second most influential factor differed by city: SLOPE had a strong effect in Daegu, characterized by surrounding mountains; POP_D had greater influence in Incheon, where population distribution varies due to clustered islands; and DEM was more influential in Seoul, which contains a mix of plains, mountains, and river landscapes. Furthermore, while NDBI and ALBEDO consistently contributed to LST increases across all regions, the effects of the remaining variables were spatially heterogeneous. These findings highlight that urban areas are not homogeneous and that variations in land use, development patterns, and morphology significantly shape heat environments. Therefore, UHI mitigation strategies should prioritize improving urban form while incorporating localized planning tailored to each region’s physical and socio-environmental characteristics. The results can serve as a foundation for developing strategies and policy decisions to mitigate UHI effects. Full article

The northwest of Mexico has important zones for biodiversity conservation, denominated Priority Marine Regions (PMRs), and to study key oceanographic features related to ecological structure, it is necessary to understand environmental variability and observe climatic trends. Sea Surface Temperature (SST) is tightly associated with photosynthesis and serves as a control and driver for biological processes linked to the phytoplankton. Global climatic systems, like El Niño Southern Oscillation (ENSO), are responsible for the interannual and interdecadal variation in SST, since global circulation is modified by them. An important metric to assess phytoplanktonic biomass/photosynthesis is Chlorophyll a (Chl a), constituting the primary basis of the marine trophic web. The present study aims to examine the interannual oceanographic variability across 24 PMRs by employing monthly SST (°C) and Chl a (mg/m³) data derived from remote sensing instruments with spatial resolution of 4 km and 1 km from September 1997 to October 2018. We grouped the Priority Marine Regions into 18 main areas, based on a cluster analysis of Sea Surface Temperature. Significant differences were observed, showing higher SST levels during El Niño phase and higher Chl a concentration during La Niña phase, primarily in winter and spring, which will impact marine ecosystems. Full article

According to existing ecological problems, one of the promising developments is the creation of polyfunctional materials, which can be biodegradable, along with possessing antibacterial activity. The present research proposes biocomposites based on PLA with silver nanoparticles (AgNPs) and natural polysaccharides obtained in a twin-screw extruder. Introduction of polysaccharides to PLA-based biocomposites with/without AgNPs led to significant decrease in the elastic modulus and tensile strength, while the elongation at break remained almost unchanged. Thanks to the presence of natural polysaccharides, there was intensified biodegradation in soil despite the AgNP availability. The maximal mass loss was 29% for the PLA–PEG₁₀₀₀–starch + AgNPs (80:10:10 + 0.5 wt%) biocomposite. Analyses of the systems before and after soil exposure were carried out using DSC and FTIR spectroscopy methods. According to a thermal analysis, it was found that PLA crystalline regions degrade during exposure to soil. The same feature was detected during the spectral analysis. The intensity of the characteristic absorption bands of PLA decreased. Furthermore, it was found that the dark areas on the surface of the materials are of a polysaccharide nature and may be signs of biofouling of the materials by microbial flora. The tests on fungus resistance showed that biocidal additives such as AgNPs in PLA-based biocomposites with polysaccharides did not inhibit the development of mycelial fungi–biodestructors. And the increased amount of chitosan in the films contributed to their more active destruction by the end of the observation period. It was demonstrated that such biocomposites can inhibit bacterial growth. Full article