Search Results (5,915)

Rapid and cost-effective estimation of soil total nitrogen (TN) is essential for soil fertility assessment and nutrient management. However, the performance of laboratory visible–near-infrared (Vis–NIR) models is shaped not only by preprocessing and modeling strategy but also by sample preparation and the soil’s compositional background. In this study, TN prediction was evaluated using 376 topsoil samples from two contrasting datasets: Mollisols from the black-soil region of Northeast China and Ultisols from Qiyang County, Hunan Province, southern China. Spectra acquired over 350–2500 nm for three particle-size fractions were preprocessed using Savitzky–Golay smoothing combined with standard normal variate (SNV), first-derivative, or second-derivative transformations, and modeled using partial least squares regression (PLSR), support vector regression (SVR), and extreme gradient boosting (XGBoost). Model development used a 5 × 5 nested cross-validation followed by evaluation on a sample-grouped held-out test set. Among all combinations, XGBoost with first-derivative preprocessing on the 0.25 mm fraction produced the best performance, with test R² values of 0.91 for Mollisol and 0.78 for Ultisol. Shapley additive explanations (SHAP) and principal component analysis (PCA) consistently identified informative spectral regions at 430–480 and 1330–1450 nm for Mollisol and at 585–635, 820–900, and 2180–2240 nm for Ultisol. Prediction errors were larger in the sampled Ultisol dataset and increased with DCB-extractable Fe and mineral backgrounds. A second-stage log-domain residual correction incorporating ancillary soil properties further reduced the Ultisol RMSE from 0.30 to 0.27 g kg⁻¹. These findings support the 0.25 mm , first-derivative, XGBoost workflow as a robust laboratory Vis–NIR approach for TN prediction and indicate that composition-aware residual correction can improve prediction in oxide- and mineral-rich soils. Full article

Assessing the ecological and environmental quality of old industrial cities is crucial for understanding the spatial heterogeneity of ecological quality and its associated factors during regional transformation. Taking Tangshan, a typical old industrial city in China, as a case study, this study employed Landsat 8/9 remote sensing imagery and multi-source auxiliary data from 2015 to 2024 to calculate annual Remote Sensing Ecological Index (RSEI) values using a unified multi-year standardization and principal component analysis framework. Global and local Moran’s I analyses were conducted to examine spatial clustering patterns, and the Optimal-Parameter Geographical Detector (OPGD) was used to quantify the spatial correspondence between RSEI and selected natural and anthropogenic explanatory factors. The results indicate the following. (1) The mean RSEI in Tangshan fluctuated between 0.34 and 0.54 from 2015 to 2024, exhibiting significant interannual variability. (2) Higher RSEI values were primarily distributed in the northern mountainous and southern coastal ecological zones, while lower values were concentrated in the central and eastern industrial-mining zones. (3) The global Moran’s I was significantly positive in all years (0.702–0.778, p = 0.001), indicating the persistence of spatial clustering; the proportion of non-significant local spatial units decreased from 72.00% in 2015 to 69.46% in 2024. (4) Land use/land cover (LULC) exhibited the most consistently high explanatory power. Elevation (ELE), nighttime light (NTL), and built-up intensity (BUILT) also formed a leading group of spatially associated factors, although their relative ranking varied between the optimal-parameter results and the robustness analysis. Slope (SLOPE), annual precipitation (Pre), and annual mean temperature (Tmean) generally showed relatively lower explanatory power. Interaction detection showed that pairwise factor combinations generally had higher q values than individual factors, with LULC × ELE showing consistently high explanatory power in representative years. This study provides a scientific reference for ecological and environmental monitoring and differentiated management in old industrial cities. Full article

Anthracnose, caused by Colletotrichum gloeosporioides, is a globally distributed phytopathogenic disease with a broad host range, posing a serious threat to the healthy growth of forest trees, including Cunninghamia lanceolata. To enable rapid and accurate on-site detection of this pathogen, this study developed a comprehensive field-deployable detection method. The approach integrates the EZ-D method (EASY DNA extraction) for rapid nucleic acid extraction with recombinase polymerase amplification (RPA) and the CRISPR/Cas12a system. A specific target gene, designated Cglo6922, was identified for the detection of C. gloeosporioides. The entire detection process can be completed within approximately 25 min, comprising a 10-min isothermal RPA at 39 °C followed by a 15-min Cas12a cleavage reaction. Specificity evaluation showed that the method successfully detected two C. gloeosporioides isolates derived from different hosts, while no cross-reactivity was observed against a panel of 32 other isolates, including ten Colletotrichum species, eight Phytophthora species, six Pythium species, seven Fusarium species, and one Botryosphaeria dothidea isolate, demonstrating robust species-level specificity. Sensitivity testing revealed that the method achieved a limit of detection (LOD) of 10 pg/μL of genomic DNA for C. gloeosporioides. Furthermore, by incorporating the EZ-D rapid extraction method (requiring only one minute for DNA extraction at a cost of approximately $0.03 USD per sample), target nucleic acid was successfully extracted from artificially inoculated Cunninghamia lanceolata branch samples and proved compatible with the RPA-CRISPR/Cas12a detection system. In conclusion, this study establishes a novel field-deployable detection method for C. gloeosporioides that is rapid, cost-effective, highly specific, and highly sensitive, providing a powerful tool for point-of-care testing (POCT) of this disease. Full article

Accurate characterization of closely related Ilex taxa is essential for the conservation, documentation, and utilization of plant genetic resources. In this study, five Ilex taxa from eastern China (Ilex rotunda Thunb., Ilex chinensis, Ilex cornuta Lindl. & Paxt., Ilex cornuta ‘Fortunei’, and Ilex latifolia Thunb.) were evaluated using an integrated framework combining fruit morphometric traits, CIELAB color parameters, and electronic-nose (E-nose) volatile fingerprints. Fruit transverse diameter, longitudinal diameter, single-fruit weight, fruit shape index, and peel color traits (L*, a*, b*, and chroma, C*) differed significantly among taxa (one-way ANOVA, all p < 0.001). I. cornuta produced the largest and heaviest fruits, I. chinensis showed the most elongated fruit shape, and I. rotunda exhibited the highest redness and chroma values. Chemometric analyses of E-nose responses further improved taxon discrimination and revealed clear divergence in volatile-response patterns. Trait-space relationships were broadly consistent with the preset phylogenetic framework, with I. rotunda showing the greatest divergence and I. cornuta and I. cornuta ‘Fortunei’ showing the closest similarity. These findings indicate that integrated fruit phenotyping and rapid volatile profiling provide a practical approach for Ilex germplasm identification, comparative evaluation, and resource documentation, with potential value for conservation planning and horticultural utilization. Full article

Biological invasions are a primary driver of biodiversity loss, with significant socio-economic repercussions. Therefore, understanding the factors influencing the assembly of invasive insect assemblages in Biodiversity Conservation Priority Areas is essential for formulating effective management strategies. This study examined the invasive alien insect fauna across three such regions in Guangxi, China, from April to November 2022, employing a systematic grid-based sampling design that encompassed 84 grids. A total of nineteen invasive alien insects from seven orders were identified, with Coleoptera (26.3%), Hymenoptera (21.1%), and Diptera (15.8%) being the most prevalent. Bactrocera cucurbitae Bezzi, 1913 (57.1% occurrence frequency) and Blattella germanica Linnaeus, 1767 (53.6%) were the most frequently observed species. Species richness exhibited significant variation among the three areas, peaking in the Western Guangxi and Southern Guizhou Limestone Area. The assemblages’ composition displayed high beta diversity, as indicated by a total Sørensen dissimilarity of 0.645, primarily driven by species turnover (0.474) rather than nestedness (0.171), which suggests the presence of distinct species assemblages across the areas. Generalized linear mixed models and Canonical Correspondence Analysis identified precipitation and temperature as the primary factors influencing species richness and assemblages’ composition, respectively. Hierarchical partitioning indicated that climatic variables, specifically precipitation (48.0%) and temperature (32.0%), collectively accounted for the majority of the variation in species richness, significantly surpassing the impact of local land cover (20.0%). In contrast, contemporary anthropogenic land use factors exhibited no significant effect. Our findings illustrate that while human activities serve as the ultimate drivers of species introductions, the subsequent assembly of invasive insect assemblages within these Biodiversity Conservation Priority Areas are predominantly shaped by climatic conditions. This highlights the essential role of climate suitability in determining the success of post-introduction establishment. Therefore, we recommend the incorporation of high-resolution climate-matching models into biosecurity screening and monitoring frameworks for Biodiversity Conservation Priority Areas, with targeted surveillance efforts directed toward regions exhibiting the highest climatic suitability. Full article

Walnut leaf necrosis causes leaf desiccation and premature abscission, substantially reducing photosynthetic efficiency, impairing fruit development, and ultimately leading to yield loss and quality deterioration. In severe cases, it accelerates branch senescence or even whole-tree mortality, resulting in considerable economic damage to the walnut industry. Rapid and accurate monitoring of this disease is therefore essential for sustainable production. This study aimed to characterize the different stages of walnut leaf necrosis using spectral analysis and develop classification models for stage-specific identification. Leaf samples representing healthy leaves and the early, middle, and late stages of necrosis were analyzed for spectral responses. Sensitive bands were identified using the variable importance in projection (VIP), successive projections algorithm (SPA), and the combined VIP-SPA method, and corresponding vegetation indices were constructed. The selected features were incorporated into classification models based on random forest (RF), extreme gradient boosting (XGBoost), and convolutional neural networks (CNNs). Results revealed that the red-edge (640–700 nm) and near-infrared (720–1000 nm) regions were identified as key diagnostic spectral ranges. Among the vegetation indices evaluated, the Simple Ratio Index (SRI) calculated from reflectance at 705.7 nm and 707.1 nm, the Normalized Difference Index (NDI) using the same band pair, and the Difference Index (DI) derived from 417.1 nm and 638.7 nm emerged as the most sensitive indicators of disease severity. Classification accuracies for different necrosis stages reached 0.9583, 0.9583, and 0.9333, respectively. These findings demonstrate that the identified spectral bands and vegetation indices provide robust tools for monitoring the progression of walnut leaf necrosis. Full article

The upper Permian Dalong Formation in western Hubei Province is a crucial strategic successor for shale gas development in South China. However, the geological controls on reservoir pore development, particularly the influence of organic–inorganic interactions on the pore system, remain poorly understood. This restricts the precise optimization of shale gas exploration targets in this formation. To investigate the pore development characteristics and main controlling factors of the Dalong Formation shale reservoirs, this study takes the DFS from the Shuanghe section in western Hubei as the research object. X-ray diffraction (XRD), argon-ion polishing-scanning electron microscopy (SEM), and N₂/CO₂ gas adsorption–desorption technologies were integrated to achieve qualitative characterization and quantitative assessment of the pore network, with analyses of pore size distribution. The results show that the pores of the DFSs are dominated by interparticle pores and organic matter pores, and the pore structures of organic-rich and organic-lean shales exhibit significant differentiation characteristics. The quartz in the DFSs are mainly of diagenetic origin, and authigenic quartz cementation blocks primary intergranular pores, exerting a significant negative effect on pore development. In contrast, the smectite-to-illite transformation promotes the development of interlayer micropores, leading to a good positive correlation between clay mineral content and micropore volume, as well as specific surface area. Organic matter abundance is the core controlling factor for the construction of micro–nano pore networks. This study clarifies the dominant mechanisms of pore development driven by organic–inorganic interactions in the DFS. Authigenic diagenetic quartz impedes pore development, while smectite-to-illite transformation promotes micropore formation. Organic matter abundance is the dominant control on the micro-nanopore system. This study lays a critical geological theoretical foundation for the exploration evaluation and target selection of shale gas in the Dalong Formation. Full article

Based on the characteristics of cities as organic entities, this paper constructs a five-dimensional evaluation framework encompassing economy, industry, society, population, and space. A three-stage process of “fuzzy comprehensive evaluation—bi-level K-means clustering—state stability correction” is adopted to identify the development stages and spatiotemporal evolution of 286 Chinese cities from 2008 to 2023. The study finds that China’s urban development has shifted from “universal growth” to “divergent evolution,” exhibiting multiple characteristics such as the decline in the initial-stage cities and differentiation in the growth stage. Significant regional spatial differentiation is observed, with notable development gaps among the eastern, central, western, and northeastern regions, as well as between the northern and southern regions. Furthermore, most urban agglomerations exhibit a “mature center–lagging periphery” structure. Full article

Deep coalbed methane (CBM) is a core exploration and development domain for increasing the reserves and production of unconventional natural gas in China. A systematic understanding has been established on the enrichment and accumulation mechanism of high-rank deep CBM in the southern section of the eastern margin of the Ordos Basin. However, the medium-rank deep CBM in the Mugua Area of the Shenfu Gas Field in the northern section of the eastern margin has essential differences from that in the southern section in terms of coal rank and hydrocarbon generation–occurrence mechanism, and its accumulation and enrichment regularity remain unclear. The core innovations of this study are as follows: aiming at the unclear accumulation regularity of medium-rank deep CBM in the northern section of the eastern margin of the Ordos Basin, we first reveal the spatiotemporal synergistic coupling reservoir-controlling mechanism of five factors (sedimentation–thermal evolution–temperature–pressure–preservation), determine the 1750 m critical transition zone of the deep CBM occurrence state, and establish two types of accumulation models adapted to the geological characteristics of medium-rank coal. Taking the No.8+9 coal seams of the Taiyuan Formation in the Mugua Area as the research object, based on the theoretical foundation of the dual properties of coal seams as the “source rock–reservoir”, this paper comprehensively adopted technical means such as core observation, drilling and logging data, and high-pressure isothermal adsorption experiments to carry out systematic multi-dimensional studies on sedimentary microfacies, coal reservoir characteristics, thermal evolution degree, and gas-bearing property; identified the main controlling factors of CBM accumulation; and constructed the accumulation model. The results show the following: ① The main burial depth of the coal seams is more than 1700 m, with a thickness ranging from 7.0 to 21.3 m and an average of 15.1 m, and the coal structure is dominated by the primary structure; maximum vitrinite reflectance (R_o,max) is generally distributed from 0.90% to 1.39% with an average of 1.08%, belonging to typical medium-rank coal; and the organic matter type is mainly Type III, with an average gas content of 10.01 m³/t, where the average proportion of desorbed gas in the total gas content is 83.91%, featuring superior source and reservoir conditions and a good foundation for CBM enrichment. ② The CBM accumulation in this area is jointly controlled by the coupling of four factors: sedimentation, thermal evolution degree, temperature–pressure effect, and preservation conditions. The tidal flat–lagoon facies control the development of high-quality coal seams; regional metamorphism dominates the hydrocarbon generation capacity and gas quality of coal seams; the temperature–pressure coupling forms a critical adsorption zone at 1750 m, defining the differentiation boundary of the occurrence state of deep CBM; and high-quality mudstone cap rocks, a stable structural environment, and closed hydrodynamic conditions constitute the three key guarantees for gas enrichment. ③ Two types of accumulation models are divided: “source–reservoir integration + multi-factor synergistic enrichment type” and “source–reservoir limited + insufficient accumulation condition type”. Among them, the four reservoir-controlling factors of the synergistic enrichment type are highly coupled, with excellent gas-bearing property and strong recoverability. This study systematically clarifies the enrichment and accumulation regularity of medium-rank deep CBM in the Mugua Area and improves the accumulation theory of medium-rank deep CBM in the northern section of the eastern margin of the Ordos Basin. Full article

Endangered montane endemic species face dual threats from unresolved taxonomic controversies and climate change. The genus Abies, a keystone component of alpine and subalpine ecosystems in the Northern Hemisphere, encompasses numerous species with controversial taxonomy and inadequately understood climatic response patterns. In this study, we integrated morphological and phylogenetic evidence and ecological niche modeling approaches to fill existing knowledge gaps regarding Abies ernestii, an endemic species found in southwest China. Key results are summarized below: (1) Morphological comparisons strongly support A. ernestii as a distinct species, with significant morphological differentiation from its congeneric species; phylogenetic analyses based on plastid sequences further corroborate its close phylogenetic relationship with A. kawakamii and A. beshanzuensis, rather than A. chensiensis. (2) The natural distribution range of A. ernestii is narrower than previously documented in the literature, and a newly discovered population in northern Yunnan extends its documented southern distribution boundary southward. (3) Current suitable habitats of this species are concentrated in the eastern Hengduan Mountains, where temperature seasonality-related variables (BIO11, BIO3, BIO4) exert dominant control over its distribution. (4) Future climate projections indicate a dynamic habitat shift characterized by initial expansion followed by contraction, accompanied by severe habitat fragmentation and inadequate protected area coverage. Collectively, these lines of evidence demonstrate that A. ernestii represents an endemic Fir with underestimated vulnerability, warranting immediate conservation prioritization. Full article

To clarify the compositional characteristics and functional mechanisms of gut microbial communities in wild earwigs (Dermaptera) and explore the potential of earwigs for development and utilization as natural enemies, this study conducted a comparative analysis of the gut microbial diversity and community structure of two earwig species, Timomenus komarovi (Semenov, 1901) and Eudohrnia metallica (Dohrn, 1865), which are widely distributed in mulberry orchards and cornfields of Guizhou Province, China. It also predicted the microbial functions based on the third-generation high-throughput sequencing technology targeting the 16S rRNA gene. The results showed that the two earwig species across different habitats and geographical regions harbored a similar core microbial flora. The dominant phyla of gut microbiota were Proteobacteria, Firmicutes. PICRUSt2 functional prediction analysis revealed that the functions of intestinal bacteria in earwigs were mainly concentrated in metabolism-related pathways. Through multi-dimensional analysis, it was confirmed that the gut microbial communities of earwigs were constructed following the “core-specialization” model. The core microbial communities exhibited high conservatism. Host species were the core factor shaping the composition of earwig gut microbial communities. Habitats could further regulate the commonness and diversity characteristics of the microbial communities, while geographical regions had an extremely weak impact on the gut microbial communities. Significant differences were observed in the gut microbial adaptation strategies between the two earwig species, which determined their distinct development potential and application scenarios as natural enemy insects: T. komarovi is suitable for development as a broad-spectrum natural enemy, while E. metallica is more appropriate for targeted development based on its microbial community characteristics. All data supporting the findings of this study are accessible in the NCBI database under BioProject accession number PRJNA1449822. This study provides a theoretical basis for exploring the functional mechanisms of intestinal microbes in dermapteran insects and supporting the development and utilization of these natural enemy resources. Full article

Cyclocarya paliurus (Batal.) Iljinsk is a multipurpose tree species with great potential for development. To identify indicators of grafting compatibility during the healing process, two cloned genotypes, CR4 and CR5, were used as scions, grafted onto seedling rootstocks derived from the Guangxi provenance. Following branch grafting, samples from the graft union were collected at 0, 20, 40, and 60 days. Physiological–biochemical indicators, including soluble sugars, soluble proteins, starch, peroxidase (POD) activity, polyphenol oxidase (PPO) activity, phenylalanine ammonia-lyase (PAL) activity, as well as flavonoid and phenylpropanoid contents, were analyzed. The graft survival rate of the CR4 combination (60%) was significantly higher than that of CR5 (35%). Significant differences in key physiological indicators were observed between the two scion–rootstock combinations. Analysis revealed that soluble sugar and soluble protein levels, along with POD and PAL activities in the scion during the early grafting stage, significantly influenced the final survival rate. Furthermore, lignans, lignin precursors, and several flavonoid compounds were found to accumulate preferentially at the graft union of the CR4 combination, which exhibited higher compatibility. These findings provide a physiological and biochemical foundation for selecting compatible scions and advancing clonal cultivation of C. paliurus. Full article

Soil salinity is a major environmental constraint limiting plant productivity and modulating secondary metabolism. Triterpenoid saponins play crucial roles in plant stress adaptation, yet their biosynthetic regulation in Cyclocarya paliurus under salt stress remains poorly understood. This research integrated transcriptomic and metabolomic analyses to investigate triterpenoid saponin metabolism in C. paliurus leaves at four NaCl concentrations and two sampling times. Salt stress altered ion homeostasis, suppressed growth, and induced distinct triterpenoid saponins accumulation patterns, with cyclocaric acid B and oleanolic acid showing significant increases. Weighted gene co-expression network analysis identified two modules significantly correlated with triterpenoid saponin accumulation and highlighted transcription factors including WRKY18, bHLH121, ERF4, and ERF1 as regulators of key biosynthetic genes (DXS, SQS, and HMGR). Molecular docking further validated these regulatory interactions, demonstrating that bHLH35, MYC2, ERF113, and MED26B form stable complexes with target gene promoters through extensive hydrogen-bond networks. These findings elucidate the regulatory framework of triterpenoid saponin metabolism under salinity and provide a foundation for molecular breeding and cultivation of C. paliurus in saline regions. 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