Search Results (263)

Enhancing nitrogen (N) use efficiency (NUE) is crucial for reconciling food security with fertilizer reduction and environmental protection in Sichuan province. This study used statistical data of rice, wheat, maize, and rapeseed in Sichuan Province from 2008 to 2022 to evaluate crop NUE within a regional N balance framework and compare spatiotemporal differences across the five major economic zones. Results showed that provincial NUE presented a distinct three-stage pattern: a gradual increase from 2008 to 2014, a significant surge in 2015, and a period of high-level but fluctuating NUE after 2016, the drivers of which require further investigation. By 2022, rice and rapeseed demonstrated the highest NUE values (42.89% and 42.90%, respectively), followed by maize (35.46%) and wheat (28.77%). Notable spatial heterogeneity was detected, with a general tendency of higher NUE in the southeastern and basin areas and lower NUE in the northwestern mountainous areas. Northeastern Sichuan, Southern Sichuan and the Chengdu Plain consistently exhibited better performance, while Northwest Sichuan remained the region with the weakest performance. These findings suggest that improving NUE in Sichuan province necessitates region- and crop-specific strategies, with priority being given to stabilizing the high NUE of rice and rapeseed, while targeting infrastructure improvement and precision fertilizer management in wheat-dominated and low-efficiency areas. Full article

Optimizing the interaction between planting density and nitrogen (N) application rate is critical for simultaneously improving grain yield and nitrogen use efficiency (NUE) in winter wheat (Triticum aestivum L.). However, the underlying regulatory mechanism remains poorly understood in the fluvo-aquic soil region of the southern Huang–Huai–Hai Plain. This study aimed to elucidate the physiological mechanism by which planting density and nitrogen application interactively regulate source–sink coordination to achieve synergistic high grain yield and high NUE, and to screen the optimal local cultivation combination for winter wheat in southeastern Henan. A two-year consecutive field experiment was conducted from 2018 to 2020 in Shangshui, Henan, using a split-plot design. Three planting densities (D1: 225 × 10⁴ plants ha⁻¹; D2: 375 × 10⁴ plants ha⁻¹; D3: 525 × 10⁴ plants ha⁻¹) and five N rates (N0: 0; N1: 180; N2: 240; N3: 300; N4: 360 kg N ha⁻¹) were established. Results demonstrated that planting density, N rate, and their interaction significantly regulated grain yield, NUE, and dry matter and N allocation, with consistent trends across both years. Increasing density enhanced total biomass and N accumulation, but dry matter and N partitioning to grains declined when density exceeded 375 × 10⁴ plants ha⁻¹. Grain yield exhibited a quadratic response to N rate; the optimal N rate for maximum yield decreased from 296.33 kg ha⁻¹ at low density (D1) to 237.50–245.38 kg ha⁻¹ at medium and high densities. The combination of 240 kg N ha⁻¹ and 375 × 10⁴ plants ha⁻¹ (D2N2) produced the highest average grain yield (8875.35 kg ha⁻¹), with simultaneous improvements in spike number and kernels per spike as well as superior dry matter and N partitioning to grains. This combination also maintained high nitrogen recovery efficiency (NRE) and nitrogen agronomic efficiency (NAE). Correlation analysis revealed that grain yield and NUE were significantly positively correlated with dry matter accumulation, N accumulation, and their partitioning proportions to grains. Overall, D2N2 achieved simultaneous high yield and high NUE by coordinately optimizing dry matter and N partitioning to grains. We therefore recommend reducing N fertilizer to approximately 240 kg ha⁻¹ combined with a moderate planting density of 375 × 10⁴ plants ha⁻¹ as the preferred strategy for sustainable and intensive winter wheat production in the fluvo-aquic soil region of southeastern Henan and adjacent areas. Full article

This study aims to reveal the spatial-temporal evolution rule and driving mechanism of cropland multifunctionality in major grain-producing areas. Taking Henan Province as the research case, we establish a comprehensive evaluation index system covering production, living, ecological and cultural functions based on multi-source datasets spanning 2013–2022. It adopts the entropy weight method, spatial analysis and geographical detector (GeoDetector) model to analyze the spatial-temporal differentiation characteristics and influencing mechanism of cropland multifunctionality systematically. The results show that the overall level of cropland multifunctionality in Henan Province rose from 2013 to 2022. Its spatial pattern presents a feature of high in the south and low in the north, with obvious agglomeration in southern Henan. The production function is high in the east and low in the west with a stable pattern. The living, ecological and cultural functions all show a distribution of high in the south and low in the north, with prominent regional differences. Factor detection results indicate that average slope, population density and average annual temperature are the core driving factors. The overall influence of natural factors is stronger than that of socio-economic factors. Interaction detection shows that all factors produce a strengthening effect, mainly in the form of nonlinear enhancement effects. Based on this, the research has proposed targeted and differentiated strategies for the management of cultivated land. Specifically, southern Henan should consolidate its inherent multifunctional advantages and strengthen the coordinated development of production, ecological and cultural functions. Northern and western Henan needs to mitigate terrain and climatic constraints, optimize agricultural infrastructure, and improve overall cropland service capacity. Eastern plain areas should further stabilize grain production function while balancing ecological protection. Central urban agglomerations should coordinate urban expansion and cropland protection to restrain multifunctional degradation. Full article

Raptors are high-trophic-level predators and scavengers that are sensitive to habitat alteration, human disturbance, and climate variability, yet province-wide assessments of their habitat suitability and climate-change responses remain limited in subtropical China. Hunan Province, located along the inland section of the East Asian–Australasian Flyway, contains complex mountain systems, plains, wetlands, and land-use mosaics that may support diverse raptor assemblages. Based on raptor survey records collected across Hunan from January 2022 to July 2023, we used biomod2 ensemble species distribution models to assess current habitat suitability, identify key environmental predictors, and project future changes under the SSP2-4.5 and SSP5-8.5 scenarios for the 2050s and 2090s. We recorded 39 raptor species and retained 3637 valid geographic locations and 4855 observed individuals after data cleaning. Nine representative species were further selected to construct 22 species–season combinations covering resident species, summer visitors, winter visitors, and four phenological stages. The EMwmean weighted ensemble model consistently outperformed the best single models, increasing mean AUC from 0.882 to 0.970 and the mean TSS from 0.611 to 0.845. Temperature seasonality (BIO4), the Human Footprint Index (HFP), precipitation in the driest month (BIO14), and the Normalized Difference Vegetation Index (NDVI) were the dominant predictors, although their relative importance varied among residency types and phenological stages. Under current conditions, highly suitable and most suitable habitats covered 65,259.67 km², accounting for 30.81% of Hunan Province, and were mainly concentrated in western, southern, and eastern mountain regions. Future projections indicated a marked contraction of high-suitability habitats, especially under SSP5-8.5, with no HSI > 0.6 habitat identified by the 2090s. High-suitability habitats also became increasingly concentrated at higher elevations. These findings identify mountain regions as key conservation priorities and provide a spatial framework for climate-adaptive raptor conservation in Hunan Province. Full article

Soil erosion is a global ecological and environmental issue that severely degrades terrestrial ecosystems. A range of soil and water conservation measures, notably the construction of check dams in gullies, have been widely implemented to mitigate soil erosion and sustain agricultural productivity. In this study, Ningxia province in China was selected as the study area. High-resolution Google Earth imagery and digital elevation model (DEM) data were integrated with three representative deep learning semantic segmentation models—FCN, U-Net, and DeepLab v3+—to achieve automatic extraction and spatial distribution analysis of engineered check dams. Model performance was quantified using overall accuracy (OA), F1-score, and mean intersection over union (mIoU), among other metrics. The results demonstrated that U-Net outperformed FCN and DeepLab v3+ across all evaluation metrics. On the test dataset, U-Net’s F1-score exceeded those of FCN and DeepLab v3+ by 3.89% and 7.08%, while mIoU increased by 2.17% and 6.57%, demonstrating superior boundary delineation. Based on the precise area extraction by U-Net, a piecewise empirical equation was subsequently developed to relate predicted silted land area to actual sediment volume, achieving R² values of 0.92 for small dams and 0.96 for large dams. Spatial distribution analysis revealed that check dams are predominantly concentrated in the southern mountainous and hilly-gully regions, moderately distributed in the central areas, and relatively sparse in the northern plains. Overall, this study demonstrates the feasibility and effectiveness of deep learning-based semantic segmentation for automated check dam mapping and sediment volume estimation. Full article

Long-term groundwater overexploitation in the North China Plain has triggered severe land subsidence. Meanwhile, the implementation of the Middle Route of the South-to-North Water Diversion (SNWD) project and extreme precipitation events driven by climate change are exerting profound impacts on the regional hydrogeological environment. However, the localized deformation response mechanisms at a sub-kilometer to kilometer scale under the combined influence of large-scale hydraulic engineering and extreme weather events remain unclear. In this study, we utilized ascending Sentinel-1A SAR data from 2017 to 2025. By employing the Small Baseline Subset InSAR (SBAS-InSAR) technique, coupled with the Generic Atmospheric Correction Online Service (GACOS) and multi-track mosaicking, we acquired high-spatiotemporal-resolution vertical land deformation fields in the piedmont of the Taihang Mountains (Northern Henan to Southern Hebei section). Furthermore, we analyzed these deformation fields by integrating deformation pattern classification with the spatial distribution of geological structures and water diversion projects. Through this approach, we explored the controlling factors and impacts of heavy rainfall events and the SNWD project on regional land deformation. Full article

Ratoon rice monoculture system (RR) is a labor-efficient and high-yielding cropping system in southern China. The rice–duck coculture system has been increasingly recognized as a mutually beneficial agricultural practice. However, the environmental impacts, economic performance, and sustainability of transitioning from a RR monoculture to a ratoon rice–duck system (RR-D) coculture remain unclear. A three-year (2022–2024) field experiment with three replications was therefore conducted in the Jianghan Plain, China (29°41′ N, 112°25′ E), to compare greenhouse gas (GHG) emissions, economic benefits, and emergy-based sustainability indicators between the RR and RR-D systems at a significant level of p < 0.05. The results showed that the RR-D significantly reduced CH₄ emissions by 25.7–39.5% but increased N₂O emissions by 18.7–122.2%. The average global warming potential (GWP) and GHG intensity decreased by 27.8% and 30.7%, respectively. Meanwhile, RR-D increased economic benefits by 131.0–167.1%, but lowered the unit emergy value per economic benefit (UEV_Benefits), renewable emergy ratio (%R), emergy yield ratio (EYR), and emergy sustainability index (ESI), and increased the environmental loading ratio (ELR). Overall, RR-D may improve economic returns and GHG mitigation, but its emergy-based sustainability requires optimization of feed, labor, and duck stocking density. Full article

Rapid urbanization and stringent ecological protection policies in China have reshaped spatial competition among urban, agricultural, and ecological spaces. However, existing studies often overlook how this competition evolves across different slope structures. To address this, this study establishes a fine-scale analytical framework using H3 hexagonal grids and slope spectrum analysis to investigate slope structure evolution and spatial competition patterns from 1990 to 2023. The results reveal a distinct topographic stratification: urban space dominates low-slope regions (<6°) but exhibits a pervasive “upslope expansion” trend, with its average slope increasing from $1.81°$ to $2.07°$, equivalent to an annualized increase of approximately $0.008°{\mathrm{yr}}^{-1}$; agricultural space characterizes the transition zones (6–$15°$), showing an “upslope migration” in the Southeastern Hills associated with urban expansion pressure in low-slope areas; and ecological space functions as a stable barrier in steep terrains (>15°) but faces encroachment in transition zones. Furthermore, cluster analysis identifies significant regional heterogeneity aligned with China’s macro-topography, including “low-slope agglomeration” in the Eastern Plains, “interwoven upslope” patterns in the Southern Hilly Regions, and ecological dominance in the Western Highlands. Association analysis using GeoDetector and Multiscale Geographically Weighted Regression (MGWR) indicates that competition intensity is most strongly associated with human activity factors, especially human footprint and nighttime lights ($q>0.29$), which show the highest explanatory power among the examined factor groups. The interaction between human activity and elevation further shows relatively high explanatory power ($q=0.41$), suggesting that spatial competition is more pronounced where intensive human activities overlap with topographic constraints. Crucially, this study challenges the traditional flat-projection planning model. We propose a transition to “three-dimensional topographic regulation,” advocating differentiated management strategies—such as strict “slope redlines” for urban-agricultural transition zones—to mitigate intensifying spatial conflicts in complex terrains and safeguard agricultural sustainability. Full article

This study presents the first systematic evaluation of the capability of the Surface Water and Ocean Topography (SWOT) satellite Level-2 High Rate Pixel Cloud (L2_HR_PIXC) product for retrieving topography in reservoir drawdown zones under varying terrain conditions in arid and semi-arid regions. Three representative reservoirs in southern Xinjiang, China—characterized by plain, canyon, and pocket-shaped canyon morphologies—were selected to establish a terrain-dependent validation framework. A novel multi-feature clustering strategy integrating elevation and radar backscatter coefficients was explored to reduce the misclassification of wet mudflats as water pixels in the PIXC product, aiming to improve DEM accuracy in reservoir drawdown zones. Based on this framework, multi-cycle SWOT-derived digital elevation models (DEMs) were generated and quantitatively evaluated against high-resolution unmanned aerial vehicle (UAV) Light Detection and Ranging (LiDAR) DEMs. Results demonstrate a strong terrain dependency in SWOT-derived elevation accuracy. In low-relief environments, sub-meter accuracy is achieved, with the root mean square error (RMSE) below 0.25 m, confirming the suitability of SWOT for high-precision monitoring. However, errors increase significantly in steep and complex terrains, reaching up to ±6 m, primarily due to interferometric decorrelation, geometric distortion, and slope-induced biases. Despite these limitations, multi-temporal observations exhibit generally similar spatial error patterns across terrains, indicating reasonable repeatability under the tested conditions. This study reveals the performance boundaries of SWOT-derived DEMs in dynamic land–water transition zones and provides a robust methodological framework for improving DEM extraction in similar environments. The findings contribute to advancing the application of SWOT data in hydrological monitoring and geomorphological analysis at regional scales. Full article

The anthropogenic transformation of the steppe zone in the southern East European Plain has led to the destruction and catastrophic fragmentation of natural ecosystems. Due to the presence of highly fertile lands and the deposits of the Donetsk coal basin, up to 90% of the territory is occupied by agricultural and industrial activities, urban agglomerations, other settlements, and extensive transportation networks. The predominant use of introduced species in artificial plantings (within the city limits, the ratio of species to quantity is 7:3) leads to the widespread spread of alien species, further isolation of natural habitats, and their subsequent degradation. The problem of preserving natural ecosystems and restoring a stable balance in their functioning can be solved through the widespread introduction of native species into all types of plantings capable of serving as ecological corridors. In this regard, we analyzed the key characteristics of native tree and shrub species that determine their functional value. The results indicate that of the 85 native plant species, only two cannot be used because they carry pests and diseases dangerous to agricultural crops. The remaining 83 species are suitable for various planting types, based on a set of individual characteristics, and 29 of these are universal for all planting types. Outside urban ecosystems, these 83 native species can completely replace introduced species. Within urban ecosystems, the need for their combination remains. Despite a number of advantages identified in native species in conditions of anthropogenic pollution (relatively high viability, long lifespan, good resistance to mechanical stress), native species lack a number of categories of traits necessary for the more effective functioning of urban green infrastructure. Among them, there is an insufficient number of tall species (>25 m) and conifers, which are more effective in purifying and improving the health of the atmosphere, as well as beautifully flowering and generally highly decorative species necessary for recreational areas and other territories that, among other things, perform esthetic functions. Full article

As a crucial national ecological barrier, China’s Southern Collective Forest Region (SCFR) plays an essential role in maintaining regional ecological security and promoting sustainable development. Understanding the mechanisms driving the evolution of its ecosystem service value (ESV) is of great significance. Based on county-level data from 2000 to 2023, this study integrated the equivalent factor method, spatial autocorrelation analysis, the XGBoost-SHAP model, geographically and temporally weighted regression (GTWR), and partial least squares structural equation modeling (PLS-SEM) to examine the spatio-temporal evolution patterns and driving mechanisms of ESV in the SCFR. The results showed that ESV in the SCFR exhibited an overall downward trend, with a cumulative loss of 1973.77 × 10⁸ CNY. This was primarily due to marked reductions in hydrological and climate regulation services. The spatial distribution of ESV exhibited a significant heterogeneity—higher in the southwestern and southeastern mountainous regions, and lower in the northern plains and coastal zones, with the center of gravity shifting first to the northeast and then to the southwest. Local spatial autocorrelation revealed relatively stable “High–High” and “Low–Low” clustering characteristics, where high-value clusters were consistently distributed in core forest zones, while low-value clusters overlapped highly with urban agglomerations. Socio-economic factors exerted a significantly stronger influence on ESV than natural factors. Population density (POP), land use intensity (LUI), and gross domestic product (GDP) were identified as the dominant drivers, exhibiting distinct non-linear threshold effects and significant spatio-temporal heterogeneity. PLS-SEM analysis further quantified LUI as the dominant direct inhibitory pathway on ESV, highlighting urbanization’s indirect negative effect mediated through intensified LUI. Meanwhile, terrain effects were confirmed to positively influence ESV indirectly by constraining LUI and modulating local climate. The analytical framework of “threshold identification–spatio-temporal heterogeneity–causal pathway analysis” proposed in this study elucidated the complex driving mechanisms of ESV evolution, providing valuable guidance for ecological restoration evaluation and differentiated environmental governance. Full article

Background: Improving grain yield in wheat remains a top priority, requiring integrated breeding and genetic strategies. This complexity poses a major challenge, driven by quantitative polygenic inheritance, environmental influence, and intricate genetic interactions. We investigated genetic factors and their interactions for agronomic and yield traits in two high-yielding winter wheat cultivars adapted to the US Southern Great Plains. Methods: A bi-parental mapping population consisting of 221 F₇ recombinant inbred lines (RIL) derived from ‘TAM 204’ and ‘Iba’ was evaluated for three years in 11 Texas environments. Both parents and RIL population were genotyped on Illumina NovaSeq 6000 and sequences were aligned to IWGSC RefSeq v1.0 using Bowtie2 for SNP calling. For QTL analyses, each trait was analyzed by individual environment, across multiple environments and mega-environments. Results: A total of 86 QTL were mapped for five traits and among them 32 were consistent in more than one environment or analysis. Among consistent QTL, four were pleiotropic to more than one agronomic or yield traits mapped on chromosomes 2B (57.18, 59.47 Mb) and 2D (29.34, 40.64 Mb). The consistent QTL on chromosome 2D (29.34 Mb) was pleiotropic to GYLD, DTH, TW, TKW and explained maximum phenotypic variation for all traits, representing photoperiod gene (Ppd-D1). Another QTL on chromosome 2D (40.64 Mb) was pleiotropic to GYLD and TW and based on the physical position comparisons it likely reflects a unique locus in Iba. The pleiotropic consistent QTL Qgyld.tamu.2B.59 from TAM 204 represents Ppd-B1 gene. Moreover, it is more likely that Qdth.tamu.5B.575 represents the Vrn-B1 gene in Iba. A total of 23 digenic epistatic interactions involved consistent QTL for all traits. Amongst these, epistatic interactions between the consistent QTL on 2B (57.18 Mb) and 2D (29.34 Mb) were observed for GYLD, DTH and TKW. Conclusions: Our findings revealed key allelic diversity and interaction effects in elite wheat cultivars, paving the way for marker development for identified pleiotropic loci and implementation in marker-assisted selection and recombination breeding. Full article

The Historical Lateral Mobility Zone (HLMZ) represents the portion of the alluvial plain occupied by the river channel over the last decades or centuries and represents the most flood-prone sector of the floodplain. Mapping Land-Use–Land Cover (LULC) changes within HLMZs helps reconstruct human-driven land-use dynamics and identify the areas potentially exposed to the highest flood risk. Among the rivers of Southern Italy, the Sele River is characterized by one of the largest mean annual discharges and has experienced extreme and destructive floods, such as those from 1935 and 2010. Over the last 150 years, it has also undergone remarkable channel adjustments, consisting of narrowing up to ~120 m, morphological changes, and riverbed degradation. In this study, LULC changes that occurred between 1988 and 2023 within the HLMZ of the Sele River, formed over the last 150 years, were analyzed and mapped in a GIS environment. Active channels were digitized from historical maps, topographic maps, and orthophotos to map the HLMZ. LULC changes were assessed through visual interpretation of orthophotos and Google Earth imagery in a GIS environment. Results show a transition, over 35 years towards more pristine conditions, with forest expansion, reduction in agricultural areas, and absence of further artificialization. LULC dynamics appear to be strictly controlled by an increased awareness of the high flood hazard within the HLMZ, with positive implications in terms of flood risk, which, however, should be further assessed quantitatively in future studies and, possibly, reduced, given the high proneness of the Sele River to destructive floods. Full article

Ice clouds play a significant role in the Earth’s radiation balance due to their unique microphysical and radiative properties, which vary with formation mechanisms and regions and influence the local energy budget. In this study, six years of Ka-band Zenith Radar (KAZR) observations from the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) and the Southern Great Plains (SGP) sites, combined with the Fu–Liou radiative transfer model, were used to examine the macrophysical and microphysical properties of ice clouds, their radiative effects, and contributions to the surface energy budget. The results show that the frequency of ice cloud occurrence at SACOL is 40%, significantly higher than the 27% observed at SGP. At both sites, ice cloud altitudes exhibit an increasing trend in the context of recent warming, with a more pronounced increase at SGP. Seasonal variations are evident, with spring characterized by relatively thick and widespread ice clouds, while summer is dominated by high-altitude, optically thin clouds. Ice cloud occurrence peaks at night and decreases during the day at both sites; however, cloud diurnal variations in summer are much greater at SGP than at SACOL. Radiative analysis indicates that longwave radiation-induced warming dominates ice cloud radiative forcing. Net radiative forcing at the top of the atmosphere is 6.08 W/m² at SACOL and 3.06 W/m² at SGP, contributing to atmospheric heating within and beneath cloud layers. At the surface, sensible heat dominates the energy budget at SACOL (over 63%) due to its arid climate, whereas latent heat dominates at SGP (about 67%) because of abundant moisture; and ice clouds have the greatest impact in winter, reducing surface net radiation by 29% at SACOL and 26% at SGP, producing a cooling effect. Full article

To address the challenges of strong tectonic stress anisotropy, multi-scale pore networks, and complex seepage pathways in the tight sandstone reservoirs of the Shaximiao Formation, southern Sichuan Basin, this study integrates petrophysical analysis with machine learning techniques to develop an intelligent flow unit identification methodology applicable to complex structural settings. Based on core petrophysical properties, mercury injection capillary pressure (MICP) data, and production dynamics, the reservoirs were classified into a fracture-type plus four conventional-type (I–IV) flow unit system. Quantitative identification of flow units was achieved using conventional well-logging curves (Gamma Ray, Spontaneous Potential, Caliper, etc.—eight curves total) using the Gradient Boosting Decision Tree (GBDT), Backpropagation Neural Network (BPANN), and Supervised Self-Organizing Map (SSOM) algorithms. Key findings include the following: The SSOM algorithm delivered optimal performance, achieving a 90.1% average accuracy on the test set, significantly outperforming GBDT (87.8%) and BPANN (85.5%), particularly in capturing nonlinear responses of fracture-type reservoirs and class-overlapping samples. Flow unit spatial distribution exhibits dual sedimentary-structural control: High-quality units (Types I/II) are enriched at the base of distributary channels in deltaic plain facies (J₂S1²), while fracture-type units cluster near fault peripheries. Strong planar heterogeneity is observed in the J₂S1³ sub-member: Near-source areas (south/southwest) develop banded Type I/II units, whereas distal regions are dominated by Type IV units. This methodology provides a theoretical foundation and intelligent technological pathway for the efficient development of highly heterogeneous tight sandstone reservoirs. Full article