Search Results (1,048)

Solidago canadensis L. is a regulated invasive alien species in China and was first recorded in the wild in Jiangsu Province. Despite widespread concern regarding its distribution and ecological associations, province-wide information on its current invasion status and associated plant community patterns in Jiangsu remains limited. To fill this gap, we conducted field surveys at 165 sites across Jiangsu Province and combined hierarchical clustering, plant-community diversity analysis, species-level analysis of accompanying-plant composition, redundancy analysis, and MaxEnt modeling to evaluate invasion-intensity patterns, associated environmental and anthropogenic factors, and plant-community responses in invaded communities. Solidago canadensis was recorded throughout the province, but invasion intensity was highest in southern Jiangsu. Hierarchical clustering classified the 165 sampling sites into three invasion-intensity groups. Group A (74 sites), concentrated in southern Jiangsu, was classified as the severe invasion group and showed generally lower plant diversity within the invaded-site dataset. Group B (60 sites) represented moderate invasion. Group C (31 sites), mainly distributed in northern and coastal Jiangsu, represented light invasion and retained relatively higher accompanying-plant diversity. Within S. canadensis-invaded communities, we documented 183 accompanying plant species from 43 families. Asteraceae and Poaceae were the most species-rich families, and annual or biennial herbs were the dominant life-form category. Species-level analysis further showed that accompanying-plant composition varied significantly along the invasion-intensity gradient (PERMANOVA, R² = 0.035), suggesting that differences in S. canadensis dominance were associated with detectable shifts in local plant assemblages. Redundancy analysis indicated latitude, transportation route density, and floating population density were closely associated with variation in S. canadensis invasion indicators and associated community variables, with soil pH, precipitation of the driest month, GDP, and motor vehicle ownership also contributing to the observed pattern. MaxEnt modeling identified southern and central Jiangsu as the main climatically suitable areas. This pattern was broadly consistent with the concentration of higher invasion intensity in southern Jiangsu. Nevertheless, field records in northern Jiangsu suggest that areas with lower predicted climatic suitability should also remain under continued monitoring. These findings suggest the need for coordinated management, particularly along major transportation corridors and in highly disturbed urban habitats. Control efforts should combine zoning management, source control, repeated removal, and habitat restoration tailored to local conditions. Full article

Rapid accumulation of soil lanthanum (La), cerium (Ce), and fluorine (F) caused by bastnasite mining development has increasingly become a concern worldwide in the past decades. However, the effects of the different chemical forms of these elements on the composition and diversity of soil dominant, moderate, and rare microorganisms are unclear. In this study, Planctomycetota was changed from dominant to moderate, caused by exchangeable and carbonate-bound forms of La and Ce. Both organic bound La (La_ORG) and water-soluble F (F_WS) were the crucial factors driving variations in the relative abundance of Patescibacteria and Bacteroidota from moderate to dominant, while the fungal phylum Chytridiomycota was changed from moderate to dominant, promoted by F_WS. La_ORG, the ferrum-manganese bound form of Ce, and F_WS displayed a negative correlation with the three rare bacterial phyla, i.e., Abditibacteriota, GAL15, and Deinococcota respectively. F_WS caused the disappearance of the rare fungal phylum Monoblepharomycota and the appearance of the rare bacterial phylum Fibrobacterota. Organic bound forms of both Ce and F showed a negative correlation with the bacterial Sobs and fungal Phylogenetic diversity indices, respectively. To summarize, the different chemical forms of La, Ce, and F showed varied effects on the composition and diversity of soil microbial communities. Full article

In the extremely arid Gobi environment, it remains unclear whether afforestation with saxaul (Haloxylon ammodendron) is an effective ecological restoration strategy or whether it may trigger ecological risks under severe water limitation. This study examined saxaul shelterbelts of different ages across precipitation gradients (0–50, 50–100, and 100–150 mm·yr⁻¹) in the Alxa Gobi based on 48 plots. It systematically assessed the effects of precipitation on stand growth, soil particle-size distribution, and nutrient dynamics inside and outside plantations, and used partial least squares path modeling (PLS-PM) to analyze the coupling mechanisms among precipitation, soil, and plant growth. The results showed that precipitation was the key factor controlling the survival and growth of saxaul, while planting density further regulated survival rates within different precipitation zones. Plant height, crown width, and basal diameter generally showed better performance in higher-precipitation zones, although differences among plantation ages may have been influenced by variation in initial planting density. Among the three precipitation zones, plants in the 100–150 mm zone exhibited the best growth performance. In low-precipitation areas (≤50 mm), the growth of saxaul was strongly limited, and afforestation disturbance was associated with disruption of the surface gravel layer, soil coarsening, and inadequate nutrient accumulation. In contrast, in medium- and high-precipitation areas (50–150 mm), saxaul plantations established at appropriate densities are more conducive to the accumulation of fine soil particles and nutrient enrichment. Correlation heatmaps and PLS-PM results further showed that precipitation gradient, soil texture, soil fertility, and plant growth were closely coupled. Moreover, the associations between soil and vegetation variables were stronger inside the shelterbelts than outside the shelterbelts, indicating that more pronounced local soil–vegetation feedbacks may have been formed after the establishment of artificial Haloxylon ammodendron stands. Overall, the suitability of saxaul plantations in the Alxa Gobi showed clear precipitation-dependent differentiation, with approximately 50 mm representing a practical lower limit for saxaul plantation establishment. Large-scale saxaul plantations is not recommended in areas with precipitation ≤ 50 mm, where low-disturbance restoration focused on gravel-layer protection should be prioritized; in contrast, areas receiving 50–150 mm precipitation are more suitable for plantation establishment under appropriate density control. These findings provide a scientific basis for sustainable afforestation, regional allocation, and low-disturbance management in extremely arid Gobi regions under the principle of matching vegetation restoration to water availability and site conditions. Full article

Accurate detection of plant leaf diseases is essential for enhancing crop productivity and supporting global food security. In addition to disease classification, understanding how environmental and soil conditions affect model performance is important for developing robust real-world agricultural monitoring systems. Although deep learning (DL) models achieve high accuracy on benchmark datasets, their performance in real-world settings is often limited by variations in illumination, background complexity, and environmental conditions. This study proposes a smart DL framework for detecting and classifying multiple leaf diseases in tomato, potato, and pepper plants. The framework combines U²-Net-based leaf segmentation with a Convolutional Neural Network–Bidirectional Gated Recurrent Unit (CNN–Bi-GRU) architecture. MobileNetV2 is employed as the feature extraction backbone to capture spatial characteristics, while Bi-GRU layers model sequential feature dependencies, forming a spatio-temporal network whose architectural design prioritizes parameter efficiency through depthwise separable convolutions and reduced gating complexity. The model was trained and validated using the PlantVillage benchmark dataset and achieved a classification accuracy of 99.8% with a macro-averaged F1-score of 94%, outperforming several state-of-the-art architectures. To assess robustness under real-world conditions, the trained model was further tested on leaf images collected from open-field environments near Eluru, South India. The field evaluation revealed a reduction in classification accuracy to 61.97%, indicating the impact of domain shift and environmental variability. To investigate potential contributing factors, soil parameters, including pH, temperature, moisture, and NPK levels, were monitored using an IoT-based Arduino sensing system over ten consecutive days. Rather than serving as direct inputs to the disease classification model, these environmental measurements were analyzed to assess their potential influence on disease symptom expression and the observed reduction in model performance under field conditions. The results suggest that environmental conditions may influence disease symptom expression and model transferability. This study highlights the importance of integrating DL-based disease recognition with environmental monitoring for reliable field-level agricultural applications. Nevertheless, computational complexity metrics, including inference latency and memory footprint, were not evaluated in the present work and are identified as a priority for future edge deployment studies. Full article

Global atmospheric N₂O concentrations have risen to 335 ppb, with agricultural soils serving as a major emission source and rice paddies accounting for approximately 11% of agricultural N₂O emissions. Rice–crab co-culture has been widely adopted because of its potential to increase and stabilize crop yields; however, the underlying mechanisms of N₂O mitigation and the synergistic effects of crab bioturbation with water and nitrogen management remain unclear. Therefore, in this study, we conducted a two-year field experiment in Zhaodong, Heilongjiang Province, China, to elucidate the N₂O mitigation effects of rice–crab co-culture under water and nitrogen regulation and the associated driving mechanisms. The results showed that rice–crab co-culture significantly reduced N₂O emissions. Specifically, the N₂O flux decreased by 19.9%, while cumulative N₂O emissions decreased by 19.8%. Under the combined regulation of water and nitrogen management, the mitigation effect on N₂O emissions was further enhanced, with a reduction of up to 30.8%. Regarding environmental factors, crab activity combined with shallow wet irrigation reduced soil water content and increased surface temperature. These changes promoted the transformation of nitrogen from inorganic forms to microbially assimilable forms, increasing the microbial nitrogen content by approximately 29.5%. Meanwhile, soil enzyme activities changed significantly: the activities of urease, sucrase, and protease increased, whereas nitrate reductase activity decreased. Structural equation modeling showed that the indirect effect of management practices was much greater than the direct effect, accounting for 63% of the total effect. Nitrogen transformation was the core mitigation pathway, characterized by the conversion of inorganic nitrogen into microbial biomass nitrogen, which reduced substrate availability for nitrification and denitrification. Enzyme activity regulation served as a secondary pathway, mainly through the inhibition of nitrate reductase activity. Overall, the rice–crab system achieved sustained N₂O reduction by improving soil aeration and jointly regulating substrate limitation and weakening nitrogen transformation capacity. Full article

Perennial alfalfa roots form a composite with the soil, contributing to intensified grassland degradation and reduced yields. Soil-loosening and root-cutting tools are effective in disrupting root–soil composites and reducing soil compaction. However, loosening and root-cutting operations commonly face challenges, such as high tillage resistance and disturbance. This study developed a simulation model of the alfalfa root–soil composite based on the coupled Finite Element Method (FEM) and Smoothed Particle Hydrodynamics (SPH) method when considering the biomechanical properties of roots. The validity of the model was verified using direct shear and cutting tests. The errors in both simulation and test results were less than 8%. Additionally, a vibration root-cutting shovel was designed. The factors of tillage speed, vibration frequency, amplitude, and direction were analyzed for their impact on tillage resistance and root shear displacement. Results indicated that the incorporation of vibration enhanced soil breaking and reduced root-cutting displacement. The optimal combination of parameters determined using the Response Surface Method (RSM) for minimizing tillage resistance and shear displacement were a tillage speed of 0.86 m·s⁻¹, vibration amplitude of 3.79 mm, vibration frequency of 45.05 Hz, and vibration parallel to the tillage direction. Field tests confirmed the effectiveness of the vibratory root-cutting shovel. The addition of vibration parallel to the tillage direction can reduce tillage resistance by 16.68% and penetration resistance by 26.80%. This study provides a methodology for modeling root–soil composite and improving the root-cutting shovel for grassland degradation restoration. Full article

Soil contamination around iron ore complexes in semiarid zones is usually described by total metal concentrations, which underestimate the labile mobile pool. At the Sokolovka-Sarbai mining and beneficiation complex (SSGPO, Northern Kazakhstan), total (EPA 3051A) and mobile (neutral NH₄OAc, pH 7) forms of ten heavy metals were analyzed in 87 site-horizon composites (29 sites × 3 pits × 3 horizons; 261 field samples). Descriptive indices flag Co as the only moderately contaminated element (I_geo 1.16) and Mn as the only one in persistent deficit (Kc_total 0.62); Co and Mn show the largest mobility-factor increments above background (Δ_MF +17.8 and +22.3 p.p.). The priority toxic elements As, Cd and Pb remain at or near depth-matched background in the total fraction (median Kc_total 0.98–1.09; I_geo < 0 for all three), although Pb shows a moderate mobile-fraction enrichment (median Kc_mobile 2.6); mercury was not among the ten metals analyzed. Factor analysis of mobile forms resolves two independent sources (F1-siderophile Cr-Ni-Fe-Mn-Co; F2-Zn-dominant, non-sphalerite) and a humus-driven sorption pool (F3), coherently localized in the dump2A-pit2 sector; mobile-fraction attribution greatly outperforms the total fraction (21 vs. 0 FDR-significant trends). The raw Mn-deficit-Co-mobility correlation (ρ = −0.54) is fully mediated by humus (partial ρ = +0.05). Total Mn deficit and enhanced Co lability are therefore interpreted as coupled consequences of a single humus-Ca-pH Kastanozem geochemistry rather than a causal “Mn-buffer depletion → Co mobilization” chain. Because the dataset is cross-sectional, this distinction remains correlational; sequential fractionation and mineralogical verification are priorities for future work. Full article

Astragalus root rot is a soil-borne disease primarily caused by Fusarium spp., which severely hampers the sustainable development of the Astragalus industry. F. acuminatum is a predominant pathogen causing this disease. To elucidate the genetic variation and adaptive evolutionary characteristics of F. acuminatum from different geographical origins, this study conducted whole-genome resequencing analysis on 28 isolates of F. acuminatum collected from four major Astragalus production regions. Approximately 124.9 Gb of high-quality sequencing data were obtained, and a large number of single-nucleotide polymorphisms (SNPs) were detected. Population genetic analysis revealed that strains from different regions did not form strictly geographically specific clusters, exhibiting a complex mixed distribution pattern. Nucleotide polymorphism analysis indicated that the Dingxi, Gansu (GD) population possessed the highest nucleotide diversity (π) value, reflecting the richest genetic diversity. Fixation index (Fst) analysis revealed significant genetic differentiation (Fst > 0.15) among populations from different provinces, suggesting that geographic isolation may be a contributing factor to restricted gene flow between pathogenic isolates in these regions. Tajima’s D positive values suggest a deviation from neutrality, consistent with balancing selection or population contraction. Ka/Ks analysis further revealed that the majority of genes exhibited Ka/Ks > 1, differing from the typical pattern of purifying selection dominance. This study revealed the genetic variation and selection signals of F. acuminatum isolates from different geographical origins, observed significant genetic differentiation between the Gansu and Ningxia populations, and identified a large number of genes that may be subject to positive selection. Full article

Soil–rock mixtures are composed of various constituents, including rock blocks, soil matrix, and pores. The stability of slopes formed by such materials is significantly affected by rock content, block location, and block gradation. However, most existing studies have used the overall rock content as the primary index to characterize the role of rock blocks. This index is essentially a global averaged parameter and therefore cannot accurately reflect the actual contribution of rock blocks to slope stability. To overcome this limitation, stochastic numerical models of soil–rock mixture slopes were established based on real rock-block contours, and the seismic stability of these slopes under pseudo-static horizontal seismic loading was investigated using the upper-bound finite element limit analysis method. On this basis, the concept of effective rock content was proposed to quantify the actual participation of rock blocks within the governing sliding zone. Comparative analyses based on selective rock-block removal further demonstrated the limitation of the overall rock content index. When the rear rock blocks were removed while the effective rock content remained unchanged, the safety factor changed only slightly from 0.882 to 0.881. In contrast, after removing the leading-edge rock blocks, the effective rock content of the slope decreased to 0. The safety factor dropped to 0.774, close to the safety factor of 0.772 for a homogeneous soil slope. Quantitative sensitivity analysis further showed that the effective rock content plays a controlling role in the slope safety factor. Compared with the overall rock content, it can more effectively characterize the actual contribution of rock blocks to the seismic stability of soil–rock mixture slopes and can be regarded as the governing structural parameter controlling slope stability. Furthermore, the effects of gradation and the spatial distribution of oversized rock blocks on the stability of soil–rock mixture slopes can both be interpreted through their regulation of the effective rock content and the rock-skeleton effect. In general, the beneficial influence of the spatial location of oversized rock blocks on slope stability follows the order: slope toe > slope face > slope crest > inside the slope > behind the slope. These findings indicate that effective rock content can serve as a key index for characterizing the seismic stability of soil–rock mixture slopes and provide a new analytical framework for the stability assessment of such slopes in seismic regions. Full article

Piles with continuous helix (referred to herein as “screw pile”) is a new configuration of helical piles. It features a continuous helix spiraling several pitches around a smooth shaft forming a “threaded shaft”. This study investigates the compressive capacity and behavior of helical and screw piles using 3D numerical models calibrated and validated against full-scale field testing. The bearing capacity factor, $N_c$, for helical piles is back-calculated from the numerical results and compared against standard theoretical assumptions to evaluate their accuracy in predicting ultimate capacity. Parametric studies are conducted considering screw piles configuration, including shaft diameter, pitch size, helix diameter, as well as soil strength. The results reveal that shaft resistance accounts for up to 89% of the total capacity. Analysis of load distribution, shear contours, and displacement contours at failure allowed for the identification of different failure modes of soil adjacent to the pile’s threaded shaft: Individual Bearing Mode (IBM), Cylindrical Shear Mode (CSM), and a combined mode. The study identifies specific parametric thresholds for these modes in both sand and clay layers. Furthermore, varying clay strength is found to alter the development of the shear surface, transitioning from localized bearing to continuous shearing along the threaded shaft. Finally, apparent shaft resistance factors, $\alpha$ and $\beta$, are back-calculated to provide practical parameters for evaluating the resistance of threaded shafts in layered soil. Full article

Evaluating resource and environmental carrying capacity (RECC) serves as a fundamental approach for assessing regional environmental baselines and is widely applied in territorial spatial planning. Focusing on Daye City—a characteristic resource-exhausted city in Hubei Province—this study developed a comprehensive RECC evaluation system. By integrating the obstacle degree model, hotspot analysis, and Geodetector, we investigated the spatial differentiation mechanisms of RECC and the resulting production–living–ecological (PLE) spatial conflicts, ultimately proposing targeted optimization pathways. The core findings are as follows: (1) The RECC of Daye City exhibits pronounced spatial polarization and a distinct north–south gradient. (2) The spatial stress of industrial/mining land emerges as the primary obstacle (36.47%). Together with geological hazard risk and soil erosion sensitivity, it forms a core constraint chain. The highly significant hotspots of these factors strongly overlap in the north-central mining districts. (3) Geodetector analysis reveals robust bivariate and nonlinear enhancement effects among these core obstacle factors. This indicates that the cascading vicious cycle of mining disturbance, ecological degradation, and declining carrying capacity fundamentally underlies the constrained RECC in mining regions. (4) PLE spatial conflicts across the study area are dominated by production–ecological conflicts (47.73%), presenting a spatial pattern that heavily couples with the polarized obstacle zones. Based on these findings, this study proposes differentiated regulation strategies centered on mitigating mining-induced stress and interrupting the cascading transmission of disaster risks. These strategies aim to restructure and optimize the territorial spatial pattern, providing robust quantitative decision support for the sustainable transformation of similar resource-exhausted cities. Full article

In this work, we present the Chernozem Soil Aggregates Micromorphometrical Parameters Dataset for specific areas located in the Central Russian Upland that can be utilized for the development of a digital twin of Chernozem. The present dataset represents a collection of soil aggregates’ micromorphometrical parameters (aggregate total area, minimal and maximal Feret diameters, form factor, elongation, unevenness, orientation) obtained through segmentation of soil thin sections’ digital images. Also, the dataset represents the data on physical and chemical properties of the studied soils (organic carbon content, inorganic carbon content, clay, silt, and sand fractions content, mean weight diameter of aggregates). Soil excavation and sampling were conducted in two stages: 24–25 April 2023 and 4 June 2024. Soil sampling sites were selected to provide a comparison of virgin Chernozem soils with plowed, non-eroded, and severely eroded ones. Soil sections were excavated at 9 key points. Laboratory analysis yielded 60 sets of data on physical and chemical properties and over 51,000 micromorphometric values for soil aggregates. Full article

Copper is an essential trace element for plant growth; however, in excessive amounts, it can cause severe toxicity by inducing bursts of reactive oxygen species and disrupting metabolic balance. As a root-based medicinal plant and food, Platycodon grandiflorus has its roots in direct contact with the soil. Its ability to accumulate copper is the most pronounced among various heavy metals; consequently, it is particularly susceptible to copper stress, which in turn affects its normal growth and medicinal quality. This paper focuses on the intrinsic stress potential and possible response pathways of Platycodon grandiflorus to copper stress. Drawing on existing research and relevant literature, it conducts an integrated analysis of its defence mechanisms across four levels: physical barriers, non-enzymatic antioxidants, conserved physiological and biochemical pathways, and transcriptional regulation. Regarding physical barriers, the cell wall forms the first line of defence through pectin adsorption and lignin deposition; in terms of endogenous antioxidant defence, secondary metabolites such as polysaccharides and saponins can directly participate in the scavenging of reactive oxygen species; regarding conserved pathways, the glutathione–phytochelate system acts in concert with antioxidant enzymes such as SOD and CAT to participate in copper ion chelation and the alleviation of oxidative stress, with hormone signalling regulation also playing a crucial coordinating role in this process; regarding transcriptional regulation, transcription factors such as PgWRKY may mediate the perception of stress signals and the expression of downstream genes. These pathways act in a coordinated and sequential manner, collectively forming a multi-level defence network through which Platycodon grandiflorus responds to copper stress. At the same time, this paper highlights the functional limitations of this defence system, summarises the shortcomings in current research, and proposes directions for future studies, with a view to guiding the safe cultivation and quality assurance of Platycodon grandiflorus in copper-polluted areas, as well as for the breeding of heavy-metal-tolerant medicinal plants. Full article

Sugarcane is a high-value crop in Egypt, yet weed communities in the understudied Upper Egypt region have not been systematically characterized. This study provides a comprehensive analysis of weed floristic composition, phytogeographical affinities, and the edaphic and canopy light factors governing vegetation structure across contrasting Nile Valley clay and reclaimed desert lands in Qena Governorate. Fourteen stands were surveyed during the 2024/2025 sugarcane growing season, recording 110 species from 33 families (68 annuals and 42 perennials), which were dominated by Poaceae, Asteraceae, Fabaceae, Euphorbiaceae, and Amaranthaceae (54.6% of the flora recorded). Therophytes were the most abundant life form (60.9%), and 51.8% of species belonged to Neotropical, Palaeotropical, Cosmopolitan, and Pantropical chorotypes. Diversity indices showed high and balanced species diversity, with no dominance by any single species. Seasonal variation showed that species richness peaked in spring, decreased through summer and autumn, and correlated with light intensity under the canopy. TWINSPAN identified four vegetation groups, which were merged into three primary vegetation groups (A, B, and C) via DCA and CCA ordinations and linked to microhabitats shaped by elevation and soil physicochemical properties. CCA revealed that Group C (stands in the Nile Riverbank lands) had the highest diversity, which was associated with organic matter, clay, and field capacity. In contrast, Group A (stands of reclaimed desert land) had low richness linked to high levels of Total Dissolved Solids (TDS), Electrical Conductivity (EC), Na, K, Mg, CaCO₃, and sandy soils. Group B (stands of Nile clay lands) was an intermediate transitional community between groups A and C. These findings establish edaphic factors as the primary determinant of weed community structure, with salinity as the critical constraint in reclaimed lands and seasonal light variation as a secondary diversity filter. Full article

Agricultural watersheds must simultaneously support multiple Ecosystem Services (ESs), yet the coordination between Ecosystem Service Value (ESV) growth and synergies of ESs remains poorly understood. Taking the Liaohe River mainstream Basin (LRMB), a typical agricultural watershed, as a case, this study investigates the spatiotemporal dynamics of ESV and trade-offs among ESs, along with their driving factors. Five key ESs—Food Production (FP), Water Conservation (WC), Water Purification (WP), Soil Conservation (SC), and Landscape Aesthetics (LA)—were selected. The InVEST model, Function-based Valuation Method, Root Mean Square Deviation (RMSD), and Coupling Coordination Degree (CCD) were comprehensively applied to assess the spatiotemporal variations in ESV, trade-off intensity, and their coupling coordination degree in the watershed from 2000 to 2023. Furthermore, the Optimal Parameters-based Geographical Detector (OPGD) and Multiscale Geographically Weighted Regression with Spatial Auto-correlation (MGWR-SAR) were employed to explore the driving mechanisms underlying changes in ESV and trade-off intensity, and to identify the major driving factors and their spatial heterogeneity. The results reveal the following: (1) From 2000 to 2023, total ESV in the LRMB increased by 69.5% from 77.66 to 131.59 billion yuan, with WC and FP accounting for 42.8% and 41.9% of this growth. Spatially, ESV shifted from a west-to-east increasing gradient to a U-shaped pattern, with high values concentrated in mountainous areas and low values along the mainstream. (2) Mean trade-off intensity remained stable at approximately 0.29, yet exhibited pronounced spatial polarisation. High trade-off zones shifted from the southwestern estuary toward the mainstream corridor, driven primarily by intensifying conflicts between FP and other ESs. (3) Despite a stable watershed-average CCD of 0.71–0.73, the CCD along the Liaohe River mainstream declined by over 15%, forming a corridor of coordination decay and revealing that ESV growth occurs at the expense of internal synergy. (4) Nonlinear interactions dominated ES dynamics, with the interaction of precipitation and human disturbance intensity exhibiting the highest explanatory power (q-values of 0.61 for ESV and 0.58 for RMSD). (5) Natural climatic factors (precipitation, temperature) predominantly enhanced synergy in mountainous areas, whereas human and landscape factors (human disturbance intensity, Shannon’s Diversity Index, PLAND of water) intensified trade-offs along the mainstream and central plains. This study establishes an integrated “ESV–trade-off–CCD” diagnostic framework and proposes a differentiated management strategy, offering a potentially transferable paradigm for sustainable governance in agricultural watersheds. Full article