Search Results (4,501)

Mining and metallurgical activities negatively impact ecosystems due to the release of potentially toxic elements (PTEs). This study assesses PTE pollution and accumulation in native plant species that have spontaneously colonized a historical mining site (Michaly, site A) and a nearby metallurgical smelter site (Varvara, site B) on the Lavreotiki Peninsula, Attika, Greece. Soils were analyzed for As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Sb, and Zn. A total of 89 native plant taxa across 28 families were identified. The aerial parts from dominant species were analyzed for PTE concentrations, and bioconcentration factors (BCFs) were calculated. One-way ANOVA and principal component analysis (PCA) using R were used for statistical evaluation. Soils at both sites showed elevated As, Cd, Cr, Cu, Ni, Pb, Sb, and Zn; Mn was high only at site B, while Co and Fe remained at background levels. Several plant species, especially at Michaly, had elevated concentrations of As, Cd, Co, Cr, Fe, Pb, Sb, and Zn in their aerial parts. BCFs indicated general PTE exclusion from aerial parts, particularly at site B. Native vegetation on these contaminated sites shows resilience and PTE exclusion, highlighting their potential for phytoremediation, especially phytostabilization, and ecological restoration in similarly polluted Mediterranean environments. Full article

Cotton is a globally strategic crop that plays a crucial role in sustaining national economies and livelihoods. To address the challenges of accurate cotton field extraction in the complex planting environments of Xinjiang’s Alaer reclamation area, a cotton field identification model was developed that integrates multi-source satellite remote sensing data with machine learning methods. Using imagery from Sentinel-2, GF-1, and Landsat 8, we performed feature fusion using principal component, Gram–Schmidt (GS), and neural network techniques. Analyses of spectral, vegetation, and texture features revealed that the GS-fused blue bands of Sentinel-2 and Landsat 8 exhibited optimal performance, with a mean value of 16,725, a standard deviation of 2290, and an information entropy of 8.55. These metrics improved by 10,529, 168, and 0.28, respectively, compared with the original Landsat 8 data. In comparative classification experiments, the endmember-based random forest classifier (RFC) achieved the best traditional classification performance, with a kappa value of 0.963 and an overall accuracy (OA) of 97.22% based on 250 samples, resulting in a cotton-field extraction error of 38.58 km². By enhancing the deep learning model, we proposed a U-Net architecture that incorporated a Convolutional Block Attention Module and Atrous Spatial Pyramid Pooling. Using the GS-fused blue band data, the model achieved significantly improved accuracy, with a kappa coefficient of 0.988 and an OA of 98.56%. This advancement reduced the area estimation error to 25.42 km², representing a 34.1% decrease compared with that of the RFC. Based on the optimal model, we constructed a digital map of continuous cotton cropping from 2021 to 2023, which revealed a consistent decline in cotton acreage within the reclaimed areas. This finding underscores the effectiveness of crop rotation policies in mitigating the adverse effects of large-scale monoculture practices. This study confirms that the synergistic integration of multi-source satellite feature fusion and deep learning significantly improves crop identification accuracy, providing reliable technical support for agricultural policy formulation and sustainable farmland management. Full article

Diptera belonging to the families Calliphoridae and Sarcophagidae are known for their diversified trophic preferences and for their forensic and medical-veterinary relevance. The ecological preferences (distribution, abundance and habitat) of these two families were investigated along four years in the Region Calabria (Southern Italy) in 17 sampling sites located in four areas: the Aspromonte National Park, the Sila National Park, the Natural Regional Park of Serre, and a suburban area at the University of Calabria (Rende, Cosenza, Italy). A total of 39,537 individuals were collected, with 36,253 belonging to 14 species of Calliphoridae and 3284 belonging to 35 species of Sarcophagidae. The most abundant species among Calliphoridae was Calliphora vomitoria (Linnaeus, 1758); among Sarcophagidae, it was Sarcophaga (Sarcophaga) croatica Baranov, 1941. The highest species richness and abundance of Calliphoridae were observed in forest areas and those of Sarcophagidae in open and humid environments. The results also show a close association between the distribution of both families and environmental factors such as altitude, vegetation type, season, and temperature. Full article

With intensifying watershed pollution pressures and growing ecological vulnerability, scientifically revealing and enhancing the water environmental carrying capacity is crucial for ensuring the long-term health of the basin and the sustainable socioeconomic development of the region. However, the dynamic regulatory mechanisms linking narrow-sense and broad-sense water environmental carrying capacity remain poorly understood, limiting the development of integrated management strategies. This study systematically investigated the changing trends of both the narrow-sense and broad-sense water environmental carrying capacity in the Harbin section of the Songhua River basin through model calculations, along with the regulatory mechanisms of its key influence indicators. The results of the study on the carrying capacity of the water environment in the narrow sense show that permanganate, total phosphorus, and ammonia nitrogen exhibited partial carrying capacity across water periods, while dissolved oxygen decreased during flat and dry periods, with only limited capacity remaining at the Ash River estuary and in the Hulan River. The biochemical oxygen demand in the Ash River was consistently overloaded, and total nitrogen showed insufficient capacity except during the abundant water period. Broad-sense analysis indicated that improving urbanization quality, water supply infrastructure, and drinking water safety could effectively reduce future overload risks, with projections suggesting a transition from critical to loadable levels by 2030, though latent threats persist. Correlation analysis between narrow- and broad-sense indicators informed targeted control strategies, including stricter regulation of nitrogen- and phosphorus-rich industrial discharges, restoration of aquatic vegetation, and periodic dredging of riverbed sediments. This work is the first to dynamically integrate pollutant and socio-economic indicators through a hybrid modelling framework, providing a scientific basis and actionable strategies for improving water quality and achieving sustainable management in the Songhua River Basin. Full article

The increasing threat of salinity, exacerbated by climate change and unsustainable agricultural practices, necessitates innovative and sustainable crop management strategies to safeguard vegetable crop production and global food security. This review highlights a comprehensive framework that combines physiological insights with practical interventions aimed at enhancing salinity tolerance in vegetable crops. Key strategies include grafting, precision irrigation and fertilization, biofortification, and biostimulant application. These practices are applicable to both soil-based and soilless cultivation systems, offering broad relevance across diverse production environments. Combining and adapting these strategies to specific crops and environments is essential for developing sustainable, productive vegetable farming systems that can survive rising salinity and secure future food supplies. Future research focus on optimizing these integrated methods and elucidating their underlying mechanisms to enable wider and more effective adoption. Full article

Soybean (Glycine max (L.) Merrill) is highly sensitive to water deficit, particularly during the vegetative phase, when morphological and metabolic plasticity support continued growth and photosynthetic efficiency. We applied eleven water regimes, from full irrigation (W100) to total water withholding (W0), to plants grown under controlled conditions. After 14 days, we quantified morphophysiological, biochemical, leaf optical, gas exchange, and chlorophyll a fluorescence traits. Drought induces significant reductions in leaf area, biomass, pigment pools, and photosynthetic rates (A, g_s, ΦPSII) while increasing the levels of oxidative stress markers (electrolyte leakage, ROS) and proline accumulation. OJIP transients and JIP test metrics revealed reduced electron-transport efficiency and increased energy dissipation for many parameters under severe stress. Principal component analysis (PCA) clearly separated those treatments. PC1 captured growth and water status variation, whereas PC2 reflected photoprotective adjustments. These data show that progressive drought limits carbon assimilation via coordinated diffusive and biochemical constraints and that the accumulation of proline, phenolics, and lignin is associated with osmotic adjustment, antioxidant buffering, and cell wall reinforcement under stress. The combined use of hyperspectral sensors, gas exchange, chlorophyll fluorescence, and multivariate analyses for phenotyping offers a rapid, nondestructive diagnostic tool for assessing drought severity and the possibility of selecting drought-resistant genotypes and phenotypes in a changing stress environment. Full article

Urban vitality acts as a key driver of sustainable urban development, while the built environment serves as its physical foundation. However, spatial heterogeneity in urban landscapes leads to imbalanced impacts of economic, social, and environmental factors on vitality. Therefore, it is essential to investigate the underlying principles governing vitality impacts imposed by diverse components of the built environment at the spatial level. This study synthesized multi-source remote sensing data alongside geospatial datasets aiming to quantify vitality and built environment indicators across Shenyang, China. We applied Ordinary Least Squares (OLS) regression for collinearity diagnosis and Multi-scale Geographically Weighted Regression (MGWR) to model spatial heterogeneity impacts at the planning-unit level. The regression factor analysis yielded three primary conclusions: (1) Functional Mixture Degree, Bus Stop Density, and Subway Station Density demonstrated a statistically significant positive correlation with urban vitality. (2) FAR (Floor Area Ratio), Vegetation Coverage, Commercial Facility Density, and Road Density exhibited differentiated effects in core areas versus peripheral areas. (3) Public Facility Density and Bus Stop Density showed a negative correlation trend with vitality levels in Industrial Functional Zones. We propose a geospatial analysis framework that leverages remote sensing to decode spatially heterogeneous built environment–vitality linkages. This approach supports precision urban renewal planning by identifying location-specific interventions. Geospatial big data and MGWR offer replicable tools for analyzing urban sustainability. Future work should integrate real-time sensor data to track vitality dynamics. Full article

Ecological restoration in arid coal-mining regions faces extreme challenges due to soil infertility, salinization, and water scarcity. This study addresses these limitations in the Santanghu Shitoumei No. 1 open-pit mine (Xinjiang), where gypsum gray-brown desert soil, minimal rainfall (199 mm/yr), high evaporation (1716 mm/yr), and persistent gale-force winds exacerbate revegetation efforts. To overcome the high cost, short lifespan, and poor practicality of commercial water-retaining agents, we developed a novel humic acid (HA) and sodium carboxymethyl cellulose (CMC) composite water-absorbing resin (HA-CMC). Optimal synthesis parameters—identified as acrylic acid (AA)–carboxymethyl cellulose (CMC)–humic acid (HA)–Acrylamide (AM)–N,N’-methylene diacrylamide (MBA)–Ammonium persulphate (APS) = 100%:15%:4.5%:25%:0.6%:0.8%—yielded effective crosslinking, confirmed via FTIR and SEM. Performance benchmarking against existing agents demonstrated superior attributes. Field application in the mine’s demonstration area significantly enhanced surface vegetation and soil fertility, confirming the resin’s potential for large-scale soil remediation and ecological restoration in arid mining environments. Full article

Biodiversity in arid river basins is highly climate-sensitive, yet the multi-pathway relations among the environment, landscape structure, connectivity, and plant diversity remain unclear. Framed by a scale–place–space sustainability perspective, we evaluated, in the Hotan River Basin (NW China), how the environmental factors affect plant diversity directly and indirectly via the landscape configuration and functional connectivity. We integrated Landsat images (2000, 2012, and 2023), 57 vegetation plots, topographic and meteorological data; computed the landscape indices and Conefor connectivity metrics (PC, IIC); and fitted a partial least squares structural equation model (PLS-SEM). From 2000 to 2023, the bare land declined, converted mainly into shrubland and cropland; the construction land is projected to expand under SSP1-2.6/SSP2-4.5/SSP5-8.5 by 2035 and 2050. The landscape metrics showed a rising PD, DIVISION, and SHDI/SHEI, and a declining AI and CONTAG, indicating finer, more heterogeneous mosaics. Plant diversity peaked on low–moderate slopes and with ~32–36 mm annual precipitation. The PLS-SEM revealed significant direct effects on diversity from environmental factors (positive), landscape structure (negative), and connectivity (positive). The dominant chained mediation (environment → structure → connectivity → diversity) indicated that environmental constraints first reconfigure the spatial structure and then propagate to community responses via connectivity, highlighting connectivity’s role in buffering climatic stress and stabilizing communities. The findings provide a quantitative framework to inform biodiversity conservation and sustainable landscape planning in arid basins. Full article

Vegetation restoration enhances soil erosion resistance by enhancing soil aggregates, but the function of these aggregates and their relationship with soil nutrients and microbes remain unclear. In this study, two land cover types that induce different aggregate ratios were selected to determine the soil aggregate ratio, aggregate ability, nutrients, and microbes. The results showed that high vegetation cover induced a higher macroaggregate ratio and soil water content; stronger soil shear strength; higher mean weight and geometric mean diameters; and lower soil bulk density. Macroaggregates had a lower soil organic matter (SOM) content compared with small macroaggregates. The aggregates and SOM influenced soil microbial diversity, especially microbial species and functions, and the large and small macroaggregate soils contained more microbes involved in SOM degradation, which accelerated the degradation and induced macroaggregate fragmentation. Total phosphorus (TP) had a direct impact on macroaggregates, and TP and macroaggregates showed the same correlation with the main microbial abundance. Taken together, we conclude that in the environment studied, SOM influenced soil microbes and the microbial function in SOM degradation affecting soil aggregates. TP contributed more to soil aggregate variations, especially in large macroaggregate formation. Full article

Vegetation plays an important role in the hydrological cycle, carbon storage and regional climate. It provides multiple ecosystem services, regulates ecosystem structure and promotes the sustainable and stable development of the earth’s ecosystem. Under the interference of the ever-changing environment, vegetation vulnerability is increasingly evident. This study focuses on Yunnan Province, China, where we analyze the spatiotemporal dynamics of NDVI at both provincial and municipal scales. Utilizing methods such as geographical detectors, time-lag analysis, and residual analysis, we identify key drivers of NDVI changes in Yunnan. From 2001 to 2023, the multi-year average NDVI in Yunnan decreases spatially from southwest to southeast, with the annual maximum NDVI increasing at a rate of 0.025 per decade. Qujing City exhibits the fastest NDVI growth, while Diqing City shows the slowest. Vegetation degradation is primarily concentrated in central Yunnan. The NDVI in Yunnan demonstrates significant spatial heterogeneity, influenced by a combination of climatic, topographic, and anthropogenic factors. The interaction between land use type and precipitation is identified as a key driver, explaining over 50% of the spatial distribution of NDVI. Approximately 83% and 82% of vegetated areas in Yunnan exhibit delayed responses to precipitation and temperature changes, respectively. Notably, 73% of the NDVI increase and 7% of the NDVI decrease in Yunnan were jointly affected by climate change and human activities, and positive contributions from these factors cover 92% and 90% of the area, respectively. The impact of human activities on vegetation is mainly positive, although urbanization in central Yunnan significantly inhibits NDVI. By elucidating key mechanisms, this work fosters balanced vegetation–environment synergies in Yunnan and supports the building of ecological safeguards in China. Full article

Evaluating the restoration quality of university outdoor spaces is often constrained by subjective surveys and manual assessment, limiting scalability and objectivity. This study addresses this gap by applying explainable machine learning to predict restorative quality from campus imagery, enabling large-scale, data-driven evaluation and capturing complex nonlinear relationships that traditional methods may overlook. Using Fujian Agriculture and Forestry University as a case study, this study extracted road network data, generated 297 coordinates at 50-m intervals, and collected 1197 images. Surveys were conducted to obtain restorative quality scores. The Mask2Former model was used to extract landscape features, and decision tree algorithms (RF, XGBoost, GBR) were selected based on MAE, MSE, and EVS metrics. The combination of optimal algorithms and SHAP was employed to predict restoration quality and identify key features. This research also used a multivariate linear regression model to identify features with significant statistical impact but lower features importance ranking. Finally, the study also analyzed heterogeneity in scores for three restoration indicators and five campus zones using k-means clustering. Empirical results show that natural elements like vegetation and water positively affect psychological perception, while structural components like walls and fences have negative or nonlinear effects. On this basis, this study proposes spatial optimization strategies for different campus areas, offering a foundation for creating high-quality outdoor environments with restorative and social functions. Full article

Semitransparent plastic films containing red-fluorescent pigments can increase the growth of some greenhouse crops despite a lower transmitted photosynthetic photon flux density (PPFD), but the underlying mechanism by which this occurs is not fully understood. We postulated it can be attributed to a lower blue-light environment that increases leaf expansion and thus photon capture. We examined the growth response and photosynthetic capacity of vegetable and ornamental greenhouse crops under a red-fluorescent plastic, plastics with varying transmission percentages of blue light (from 6% to 20%), and an uncovered greenhouse control with a 40% greater PPFD. When the transmitted PPFD was similar, decreasing the percentage of blue light increased the extension growth for some but not all species tested. Transmitted PPFD had a more pronounced effect on extension growth than the percentage of blue light. Lettuce shoot dry mass was greater under the red-fluorescent film than the other covered treatments and similar to the uncovered control with 40% more light. Regardless of the transmission spectrum, decreasing the transmitted PPFD reduced tomato fruit fresh mass and generally decreased the number of flowers ornamental on the species. Maximum photosynthetic rate (A_max), stomatal conductance (g_sw), and quantum yield of photosystem II (PhiPSII) consistently decreased as the percentage of blue light transmission decreased, but this did not correlate to biomass accumulation. An experimental red-fluorescent film had cultivar and species-specific effects on growth, highlighting both its potential for leafy greens and potential challenges for greenhouse crops with a greater quantum requirement. Full article

Efficient irrigation management is essential for optimizing yield and quality in specialty crops like hot peppers (Capsicum chinense), particularly under controlled greenhouse environments. This study employed a novel sensor-based system integrating soil moisture and sap flux monitoring to evaluate water use dynamics in Capsicum chinense, a species for which such applications have not been widely reported. Three cultivars—Habanero, Helios, and Lantern—were grown under three volumetric soil moisture contents: low (15%), medium (18%), and high (21%). Water uptake was measured at leaf (transpiration, stomatal conductance) and plant levels (sap flux via heat balance sensors). Photosynthesis, fruit yield, and capsaicinoid concentrations were assessed. Compared to high irrigation, medium and low irrigation increased photosynthesis by 16.6% and 22.2%, respectively, whereas high irrigation favored greater sap flux and vegetative growth. Helios exhibited an approximately 8.5% higher sap flux as compared to Habanero and about 10% higher as compared to Lantern. Helios produced over 30% higher fruits than Habanero and Lantern under high irrigation. Habanero recorded the highest pungency, with a capsaicinoid level of 187,292 SHU—exceeding Lantern and Helios by 56% and 76%, respectively. Similarly, nordihydrocapsaicin and dihydrocapsaicin accumulation were more cultivar-dependent than irrigation-dependent. No significant interaction between cultivar and irrigation was observed, indicating genotype-driven water use strategies. Our study contributes to precision horticulture by integrating soil moisture and sap flux sensors to reveal cultivar-specific water use strategies in Capsicum chinense, thereby demonstrating the potential of an integrated sensor-based irrigation system for efficient irrigation management under increasing water scarcity in protected environments. As a preliminary greenhouse study aimed at maintaining consistent irrigation throughout the growing season across three volumetric soil moisture levels, these findings provide a foundation for subsequent validation and exploration under diverse soil moisture conditions including variations in stress duration, stress frequency, and stress application at different phenological stages. Full article

It is of great importance to study the spatiotemporal variation in vegetation and its influencing factors at a regional scale in plateau mountainous cities for ecological restoration and management and maintenance of ecosystem stability. This study employed MODIS NDVI data to construct a kNDVI dataset for the growing season in Kunming, with the aim of exploring the spatiotemporal variations in vegetation more precisely. The study analyzed the trends and stability of kNDVI and investigated the primary drivers of kNDVI dynamics in Kunming. The results show that the regional proportion of higher-level kNDVI is more than half, and vegetation in the growing season has shown an improvement trend. The primary factors influencing kNDVI variations in Kunming include soil type, landform type, nighttime light intensity, and slope gradient. The pairwise interactions among factors have a more substantial impact on vegetation dynamics compared to individual factors, with the interaction between soil type and nighttime light intensity being particularly pronounced. The results offer scientific bases for assessing and managing ecological environment quality in plateau-mountainous cities. Full article