Search Results (79)

Biological invasions driven by climate change and human activities pose a serious threat to biodiversity and ecosystem stability in global biodiversity hotspot regions. Lantana camara is a globally recognized aggressive invasive plant that has rapidly spread in southwest China and caused significant ecological risks. To clarify its potential geographic distribution, key driving factors, and future invasion dynamics under climate change, this study applied an MaxEnt model with feature-class optimization, integrating occurrence points, bioclimatic variables, topographic data, and the human footprint index to simulate habitat suitability in southwest China for the current period (1970–2000) and the future (2050s and 2070s) under three shared socioeconomic pathways (SSP1-2.6, SSP2-4.5, SSP5-8.5). The results show that the current high-suitability area for L. camara is 1.21 × 10⁴ km², mainly distributed in central Yunnan and the Chengdu Plain. Human activity (human footprint index, 52.3%) is the dominant driver, and the mean temperature of the coldest month (28.5%) is the primary natural limiting factor. Future suitable areas exhibit a remarkable scenario-dependent nonlinear response. By the 2070s, the high-suitability area expands most sharply under SSP2-4.5 (3.27 × 10⁴ km², an increase of about 170%), revealing that moderate warming facilitates northward expansion. Under SSP5-8.5, the high-suitability area contracts compared with the 2050s, indicating that extreme high temperatures restrain optimal habitats. Spatially, L. camara displays a “retreat south, advance north” pattern under high-emission scenarios, with its distribution centroid continuously shifting northeast, reflecting climate-driven niche changes. This study verifies that the invasion risk of L. camara does not rise linearly with climate warming. Moderate warming boosts its spread, whereas extreme warming reshapes its distribution, offering a scientific basis for risk assessment, early warning, and targeted control strategies against L. camara invasion in southwest China and worldwide. Full article

The North China Plain (NCP) has entered a “New Water Regime” driven by water diversions, stringent groundwater management, and climatic fluctuations, resulting in the widespread recovery of regional groundwater levels. How land subsidence has responded spatiotemporally to these interventions remains unclear. To quantify the regional hydrogeological responses, we integrated Time-Series Interferometric Synthetic Aperture Radar (TS-InSAR) observations spanning 2016–2023 with weighted centroid tracking and Emerging Hot Spot Analysis (EHA) based on a Space-Time Cube. Centroid tracking indicated that the regional subsidence center remained spatially stable without significant directional drift. In the western and southern regions, Persistent and Intensifying Cold Spots dominated, corresponding to ground stabilization and rebound. In the central-eastern centers, 26.80% and 6.47% of the statistically significant clustering area were Persistent and Intensifying Hot Spots, reflecting continuous localized compaction, with Mann–Kendall and Sen’s slope analyses indicating a decelerating trend within these clusters. A further 4.92% and 9.63% were Diminishing and Historical Hot Spots, indicating reduced clustering after 2019. Overall, subsidence has decelerated markedly across most of the plain, yet compaction inertia in thick clay layers sustains localized hot spots despite rebounding groundwater levels. This time-lag response implies that short-term water-level recovery cannot immediately reverse subsidence, necessitating sustained groundwater management across the NCP. Full article

Flash drought, an abruptly intensifying meteorological anomaly, poses a growing threat to agricultural production, ecosystem stability, and regional carbon cycling, particularly in croplands of monsoon regions. Existing studies have largely focused on point-scale identification or conventional vegetation indices, whereas the regional spatiotemporal evolution of flash droughts and crop-specific differences in photosynthetic recovery remain poorly understood. Using multi-source remote sensing data for the North China Plain and the Middle–Lower Yangtze Plain during 2001–2024, this study integrated triple-collocation error assessment, root-zone soil-moisture percentile identification, connected-component tracking, and Random Forest–SHAP analysis to characterize flash drought trajectories and their vegetation impacts. The results showed that the southern Middle–Lower Yangtze Plain exhibited a high-frequency but low-intensity pattern, whereas the central North China Plain was characterized by lower frequency yet higher intensity and longer duration. Rice-based systems were more vulnerable to frequent flash drought shocks, whereas rainfed and rotation systems faced stronger cumulative risks. Solar-induced chlorophyll fluorescence (SIF) responded to flash droughts 6–9 days earlier than gross primary productivity (GPP), and all cropping systems displayed a “rapid physiological response–lagged carbon-assimilation recovery” pattern. The month of occurrence, drought duration, and decline rate were identified as the dominant factors governing photosynthetic recovery. These findings extend the flash drought monitoring framework to incorporate regional connectivity and crop recovery mechanisms, providing a remote-sensing basis for agricultural early warning, drought mitigation, and food-security management. Full article

Shallow aquifers in intensively managed alluvial plains worldwide are increasingly impacted by inorganic nitrogen, yet the simultaneous occurrence and interconversion of nitrate (NO₃⁻–N), nitrite (NO₂⁻–N) and ammonium (NH₄⁺–N) often confound source attribution when single indicators are used. Here, we present a transferable, process-linked framework for diagnosing “tri-nitrogen” (tri-N) pollution that integrates hydrogeochemical evolution, data-driven pattern discovery and receptor-model apportionment. We analyzed 409 shallow-groundwater samples from Shijiazhuang City (central North China Plain) for major ions and tri-N species, interpreted within Piper facies and salinization gradients, and then applied a Gaussian mixture model (GMM) to resolve multivariate hydrochemical–nitrogen end-members. Six clusters (I–VI) depict an interpretable progression from background Ca–HCO₃/Ca·Mg–HCO₃ waters to agricultural NO₃⁻–N enrichment under oxic conditions and a distinct NH₄⁺–N-rich point-source end-member under reducing conditions. An attention-based attribution model indicates that total tri-N, Na⁺, NO₃⁻–N, the NO₂⁻ fraction and SO₄²⁻ are the primary discriminators of cluster structure. Species-resolved positive matrix factorization (US EPA PMF 5.0) quantifies dominant controls, with agricultural leaching–nitrification explaining most NO₃⁻–N (Factor 6, 87.9%) and sewage/manure inputs dominating NH₄⁺–N (Factor 3, 95.3%), while NO₂⁻–N reflects mixed contributions consistent with redox-interface transitions. Beyond this case study, the combined GMM–interpretability–PMF workflow provides a general template for separating non-point versus point tri-N inputs and for prioritizing management actions in shallow aquifers where isotope or tracer data are limited. Full article

With the rapid advancement of urbanization in China, the issue of imbalanced regional distribution of EFI has become increasingly prominent, given its role as a core component of ecological civilization construction. To scientifically identify spatial disparities in environmental facility development across China’s urban agglomerations, this study examines 138 cities within China’s ten major urban agglomerations. By constructing a multidimensional comprehensive evaluation index system, and employing entropy weighting, the Dagum Gini coefficient, kernel density estimation, and the spatial β-convergence model, this study systematically analyzes regional differences in China’s EFI development levels from 2014 to 2024. This study found that the overall level of EFI in China exhibits a gradient pattern, characterized by “higher in the east and lower in the west, stronger in the south and weaker in the north.” The Pearl River Delta and Yangtze River Delta regions consistently rank in the top tier, while the Central Plains and Guanzhong regions lag significantly behind. Regional disparities follow an inverted U-shaped trend, widening initially and then narrowing, with the gaps primarily stemming from interregional interactions. Spatial agglomeration is evident among urban agglomerations, and late-developing regions such as Chengdu–Chongqing and the Middle Yangtze River region are converging at a relatively rapid pace. Based on these findings, it is recommended to strengthen cross-regional coordination mechanisms, implement differentiated development strategies, and accelerate the transition to smart infrastructure to promote the balanced and coordinated development of EFI, thereby supporting high-quality, green, and low-carbon regional development. Full article

Cultivated land fragmentation has become a critical constraint on regional agricultural sustainable development. Revealing its spatial patterns and driving mechanisms is of great significance for optimizing the utilization and management of cultivated land resources and enhancing regional agricultural productivity. This study focuses on the main grain-producing areas in the middle and lower reaches of the Yangtze River Basin. It constructs a Cultivated Land Fragmentation Index (CLFI) using an integrated method that combines landscape index analysis with an entropy-weighted approach, based on 2023 land-use data. The optimal analytical grain size and extent were determined before employing geographic detectors to identify dominant factors influencing cultivated land fragmentation. The key findings include the following: (1) The appropriate spatial resolution for fragmentation analysis was identified as 330 m, with an optimal analysis extent of 8910 m. (2) CLFI values ranged from 0.001 to 0.973, exhibiting significant spatial heterogeneity. The central plains and northeastern regions demonstrated low fragmentation levels and better contiguous cultivated land distribution, while the western and peripheral areas showed higher fragmentation. A provincial-scale comparison revealed that Jiangxi Province had the highest fragmentation level (0.255), whereas Jiangsu Province had the lowest (0.146). The topographic gradient analysis indicated a decreasing trend from the Guizhou Plateau (0.503) to the North China Plain (0.125), with plateaus and basins showing significantly higher fragmentation than hilly and plain regions. (3) Dominant controlling factors varied among provinces: In provinces with greater topographic relief (Anhui, Hubei, Hunan, Jiangxi), natural factors like elevation, slope gradient, and NDVI primarily controlled fragmentation patterns; in contrast, socioeconomic factors such as nighttime light intensity dominated in Jiangsu Province, characterized by flat terrain and high urbanization. Multi-factor interactions generally enhanced explanatory power regarding spatial patterns, confirming that cultivated land fragmentation is a result of comprehensive multi-factor interactions. This study reveals the spatial distribution characteristics of cultivated land fragmentation at the pixel scale in the study region, providing theoretical foundations and decision-making references for the efficient utilization of cultivated land resources and rural land system reforms. Full article

Shallow groundwater in saline soils creates a self-reinforcing cycle where waterlogging-induced root hypoxia impairs the ATP-dependent sodium exclusion mechanisms that plants rely on for salt tolerance. We conducted a two-year field experiment to test whether subsurface drainage must precede root-zone aeration for oxygen delivery to be effective. The experimental site was located in Heyang County, Weinan City, on the Guanzhong Plain of Shaanxi Province, north-central China—a major alluvial agricultural region representative of shallow-groundwater-induced salinization. The site had saturated paste electrical conductivity of 6.0 dS m⁻¹ and groundwater depth fluctuating between 0.5 and 1.4 m. A randomized complete block design with 2 × 2 factorial arrangement compared four treatments: control (CK), subsurface drainage only (SD), root-zone aeration only (RA), and both interventions combined (SD + RA). Drainage increased air-filled porosity from 5.8% to 13.5%, crossing the 10.2% threshold (95% CI: 9.1–11.3%) where gas-phase continuity emerges according to segmented regression analysis. Without drainage, aeration achieved only 4.2 mg L⁻¹ dissolved oxygen with high spatial variability (CV 12.5%), while the combined treatment reached 6.8 mg L⁻¹ (CV 6.8%). Root ATP content increased by 89% in SD + RA compared to control, accompanied by 56% lower root Na⁺ and 185% higher K⁺/Na⁺ ratio. These physiological changes correlated with 31% higher grain yield (7580 vs. 5798 kg ha⁻¹). The synergy index of 1.40 (95% CI: 1.28–1.52) indicated that combined effects exceeded the sum of individual treatments by 40%. Methane emissions declined by 62%, and the system achieved a 2.9-year payback period with a benefit–cost ratio of 4.08. These results establish drainage as a physical prerequisite for effective oxygenation, providing a mechanistic explanation for the variable performance of aeration systems reported in previous studies. Full article

In the North China Plain (NCP), wind and rain during the grain-filling period of winter wheat can cause lodging. The second basal internode (I2), a key load-bearing structure, plays a central role in yield stability. This study, under a constant nitrogen (N) application rate of 270 kg ha⁻¹, aimed to clarify how nitrogen basal-to-topdressing ratios regulate I2 characteristics to balance lodging resistance and yield increase. Field experiments were conducted across two seasons with three cultivars and three nitrogen split ratios (5:5, CK; 3:7, N1; and 7:3, N2). Dynamic measurements of I2 mechanical properties, morphology, anatomy, and composition were taken, and structural equation modeling (SEM) was used for analysis. Results showed that the culm lodging resistance index (CLRI) decreased by 41.8% from flowering to milk stage under all treatments, with CLRI at the milk stage of lodging treatments between 0.11 and 0.15. SEM supported a composition–structure–lodging resistance–yield chain, with CLRI as the key mediator. The N1 treatment significantly improved CLRI at all stages and increased yield by 12.2% compared to CK, making it a recommended nitrogen strategy for improving both yield and lodging resistance. These findings provide agronomically applicable nitrogen management guidelines for high-yield winter wheat systems. Full article

This study is based on isotope (δ¹⁸O, δ²H, ¹⁴C), hydrochemical, and groundwater-level data from the past 47 years in the central North China Plain (NCP). It uses methods such as mathematical statistics, Piper diagrams, Gibbs models, and ion ratios to investigate the characteristics of changes in the groundwater flow field, hydrochemistry, and isotopes across various aquifers in the Hengshui funnel area before and after the implementation of groundwater exploitation reduction measures (GWER). Furthermore, it reveals the driving mechanisms of these measures’ effects on hydrochemical characteristics and isotopic variations. The results show the following: (1) The hydrochemical type of shallow groundwater (SG) before GWER was primarily Cl▪SO₄-Na▪Ca, which diversified to Cl▪SO₄-Na and SO₄▪Cl-Na types after GWER; the deep groundwater (DG) type changed from Cl▪SO₄-Na to Cl-Na. (2) Before GWER, the hydrochemical composition of SG and DG was primarily controlled by the dissolution of silicates, salt rocks, and evaporites. After GWER, the hydrochemical composition of DG primarily originated from the dissolution of evaporites and salt rocks, accompanied by enhanced cation exchange. (3) The δ¹⁸O of SG was affected by the recharge of irrigation return water, changing from enrichment to depletion before and after the GWER. The δ¹⁸O value in DG changed from depletion to enrichment, and the groundwater age changed from older to younger after the GWER. The GWER altered the hydrodynamics, weakened the hydraulic connectivity, and led to changes in the evolution of the hydrochemistry. The findings have direct implications for water quality and promoting the sustainable utilization of deep groundwater in the NCP’s central funnel area. Full article

The Zhang–Wei River served as the Yongji Canal section of the Beijing–Hangzhou Grand Canal in Chinese history, with its watershed rich in agricultural land and vegetation resources. Rapid urbanization in China has led to a reduction in the natural landscape base, alterations in landscape patterns, and increased habitat fragmentation within the basin. These changes have resulted in a diminished capacity landscape ecological regulation and an increase in landscape ecological risk levels. Therefore, exploring the mechanisms of landscape ecological risk evolution in the Zhang–Wei River Basin is of great theoretical and practical significance for optimizing land resource allocation in the North China Plain and promoting the restoration of ecological functions in the basin. This study utilizes land use data from the Zhang–Wei River Basin for the years 2000, 2010, 2020, and 2023. Employing the ecological risk index model and the OPGD optimal discretization method, it reveals the spatiotemporal dynamics of landscape ecological risk evolution within the basin and examines the trends and driving factors of this spatiotemporal evolution. The research indicates the following findings: (1) The Zhang–Wei River Basin is primarily characterized by cultivated land and grassland land types. Between 2000 and 2023, both cultivated land and water body areas exhibited negative growth trends, decreasing by 3.6% and 0.05%, respectively. Cultivated land conversion shows the most significant change. The predominant conversion type was construction land. (2) Landscape ecological risks in the Zhang–Wei River Basin have progressively increased over time, exhibiting spatial clustering effects. High-risk zones are concentrated in the southern and eastern parts of the Wei River Basin, while low-risk zones are found in the northern and central–southern regions of the Zhang River Basin and the central section of the Wei River Basin. (3) Human activity intensity, land use change, annual precipitation, and population density are the primary single drivers of spatiotemporal differentiation in ecological risks within the Zhang–Wei River Basin. The interactions among these influencing factors within the basin have intensified annually. Notably, in 2020, the interaction between annual precipitation and the Enhanced Vegetation Index shifted from a dual-factor enhancement to a nonlinear enhancement. These results provide scientific basis for land security planning in the Zhang–Wei River Basin and offer valuable insights for safeguarding ecological security in the North China Plain. Full article

Harvest-disrupting rain events (HDREs) are prolonged cloudy–rainy spells during winter wheat maturity that impede harvesting and drying, induce pre-harvest sprouting and grain mould, and threaten food security in the Huang–Huai–Hai Plain (HHHP), China’s core winter wheat region. Using daily meteorological records (1960–2019), remote sensing-derived land-use data and topography, we develop a hazard–exposure–vulnerability framework to quantify HDRE risk and its drivers at 1 km resolution. Results show that HDRE risk has increased markedly over the past six decades, with the area of medium-to-high risk rising from 26.9% to 73.1%. The spatial pattern evolved from a “high-south–low-north” structure to a concentrated high-risk belt in the central–northern HHHP, and the risk centroid migrated from Fuyang (Anhui) to Heze (Shandong), with an overall displacement of 124.57 km toward the north–northwest. GeoDetector analysis reveals a shift from a “humidity–temperature dominated” mechanism to a “sunshine–humidity–precipitation co-driven” mechanism; sunshine duration remains the leading factor (q > 0.8), and its interaction with relative humidity shows strong nonlinear enhancement (q = 0.91). High-risk hot spots coincide with low-lying plains and river valleys with dense winter wheat planting, indicating the joint amplification of meteorological conditions and underlying surface features. The results can support regional decision-making for harvest-season early warning, risk zoning, and disaster risk reduction in the HHHP. Full article

The spatiotemporal heterogeneity of hydrothermal conditions during the spring sowing period profoundly shapes cropping layouts and sowing strategies. Using NASA’s GLDAS remote sensing reanalysis, we developed a continuous agricultural climate risk index that integrates three remotely driven indicators—spring sowing window days (SWDs) derived from a “continuous suitable-day” logic, the hydrothermal coordination degree (D value), and a comprehensive suitability index (SSH_SI)—thus advancing risk assessment from single metrics to a multidimensional framework. Methodologically, dominant periodic structures of spring sowing hydrothermal risk were extracted via a combination of wavelet power spectra and the global wavelet spectrum (GWS), while spatial trend-surface fitting and three-dimensional directional analysis captured spatial non-stationarity. The index’s spatial migration trajectories and centroid-evolution paths were then quantified. Results reveal pronounced gradients along the Great Wall Belt: SWD displays a “central-high, terminal-low” pattern, with sowing windows restricted to only 3–6 days in northeastern Inner Mongolia and western Liaoning but extending to 11–13 days in the central plains of Inner Mongolia and Shanxi; SSH_SI and D values form an overall “south-west high, north-east low” pattern, indicating more favorable hydrothermal coordination in southwestern areas. Temporally, although SWD and SSH_SI show no significant downward trend, their interannual variability has increased, signaling rising instability, whereas the D value declines markedly in most regions, reflecting intensified hydrothermal imbalance. The integrated risk index identifies high-risk hotspots in eastern Inner Mongolia and northern North China, and low-risk zones in western provinces such as Gansu and Ningxia. Centroid-shift analysis further uncovers a dynamic regional adjustment in optimal sowing patterns, offering scientific evidence for addressing spring sowing climate risks. These findings provide a theoretical foundation and decision support for optimizing regional cropping structures, issuing climate risk warnings, and precisely regulating spring sowing schedules. Full article

The pepper weevil Anthonomus eugenii is a devastating pest native to Central America that can cause severe damage to over 35 pepper varieties. Global trade in peppers has significantly increased the risk of its spread and expansion. Moreover, future climate change may add more uncertainty to its distribution, resulting in considerable ecological and economic damage globally. Therefore, we employed an ensemble model combining Random Forests and CLIMEX to predict the potential global distribution of A. eugenii in historical and future climate scenarios. The results indicated that the maximum temperature of the warmest month is an important variable affecting global A. eugenii distribution. Under the historical climate scenario, the potential global distribution of A. eugenii is concentrated in the Midwestern and Southern United States, Central America, the La Plata Plain, parts of the Brazilian Plateau, the Mediterranean and Black Sea coasts, sub-Saharan Africa, Northern and Southern China, Southern India, Indochina Peninsula, and coastal area in Eastern Australia. Under future climate scenarios, suitable areas in the Northern Hemisphere, including North America, Europe, and China, are projected to expand toward higher latitudes. In China, the number of highly suitable areas is expected to increase significantly, mainly in the south and north. Contrastingly, suitable areas in Central America, northern South America, the Brazilian Plateau, India, and the Indochina Peninsula will become less suitable. The total land area suitable for A. eugenii under historical and future low- and high-emission climate scenarios accounted for 73.12, 66.82, and 75.97% of the global land area (except for Antarctica), respectively. The high-suitability areas identified by both models decreased by 19.05 and 35.02% under low- and high-emission scenarios, respectively. Building on these findings, we inferred the future expansion trends of A. eugenii globally. Furthermore, we provide early warning of A. eugenii invasion and a scientific basis for its spread and outbreak, facilitating the development of effective quarantine and control measures. Full article

As China’s first systematic assessment of high-risk Amaranthaceae invaders, this study addresses a critical knowledge gap identified in the National Invasive Species Inventory, in which four invasive Amaranthaceae species (Dysphania ambrosioides, Celosia argentea, Amaranthus palmeri, and Amaranthus spinosus) are prioritized due to CNY 2.6 billion annual ecosystem damages in China. By coupling multi-species comparative analysis with a parameter-optimized Maximum Entropy (MaxEnt) model integrating climate, soil, and topographical variables in China under Shared Socioeconomic Pathways (SSP) 126/245/585 scenarios, we reveal divergent expansion mechanisms (e.g., 247 km faster northward shift in A. palmeri than D. ambrosioides) that redefine invasion corridors in the North China Plain. Under current conditions, the suitable habitats of these species span from 92° E to 129° E and 18° N to 49° N, with high-risk zones concentrated in central and southern China, including the Yunnan–Guizhou–Sichuan region and the North China Plain. Temperature variables (Bio: Bioclimatic Variables; Bio6, Bio11) were the primary contributors based on permutation importance (e.g., Bio11 explained 56.4% for C. argentea), while altitude (e.g., 27.3% for A. palmeri) and UV-B (e.g., 16.2% for A. palmeri) exerted lower influence. Model validation confirmed high accuracy (mean area under the curve (AUC) > 0.86 and true skill statistic (TSS) > 0.6). By the 2090s, all species showed net habitat expansion overall, although D. ambrosioides exhibited net total contractions during mid-century under the SSP126/245 scenarios, C. argentea experienced reduced total suitability during the 2050s–2070s despite high-suitability growth, and A. palmeri and A. spinosus expanded significantly in both total and highly suitable habitat. All species shifted their distribution centroids northward, aligning with warming trends. Overall, these findings highlight the critical role of temperature in driving range dynamics and underscore the need for latitude-specific monitoring strategies to mitigate invasion risks, providing a scientific basis for adaptive management under global climate change. Full article

China’s National Famous, Special, Excellent, and New Agricultural Products are key rural economic assets, yet their spatial patterns and sustainability drivers remain underexplored. Based on the geospatial data of 1932 National Famous, Special, Excellent and New Agricultural Products in China, this study systematically analyzes their spatial distribution pattern by using GIS spatial analysis techniques, including the standard deviation ellipse, kernel density estimation, geographic concentration index and Lorenz curve, and quantitatively explores the driving factors of sustainable development by using geographic detectors. The research results of this paper are as follows. (1) The spatial distribution shows a significant non-equilibrium characteristic of “high-density concentration in the central and eastern part of the country and low-density sparseness in the western part of the country” and the geographic concentration index (G = 22.95) and the standard deviation ellipse indicate that the center of gravity of the distribution is located in the North China Plain (115° E–35° N), and the main direction extends along the longitude of 110° E–120° E. (2) Driving factor analysis showed that railroad mileage (X10) (q = 0.5028, p = 0.0025 < 0.01), highway mileage (X11) (q = 0.4633, p = 0.0158 < 0.05), and population size (X3) (q = 0.4469, p = 0.0202 < 0.05) are the core drivers. (3) Three-dimensional kernel density mapping reveals that the eastern coast and central plains (kernel density > 0.08) form high-density clusters due to the advantages of the transportation network and market, while the western part shows a gradient decline due to the limitation of topography and transportation conditions. The study suggests that the sustainable development of National Famous, Special, Excellent, and New Agricultural Products should be promoted by strengthening transportation and digital logistics systems, enhancing cold-chain distribution for perishable goods, tailoring regional branding strategies, and improving synergy among local governments, thereby providing actionable guidance for policymakers and producers to increase market competitiveness and income stability. The study provides a quantitative, policy-oriented assessment of China’s branded agricultural resource allocation and its sustainability drivers, offering specific recommendations to guide infrastructure investment, e-commerce logistics enhancement, and targeted subsidy design for balanced regional development. The study highlights three key contributions: (1) an innovative integration of geospatial analytics and geographical detectors to reveal spatial patterns; (2) clear empirical evidence for policymakers to prioritize transport and digital logistics investments; and (3) practical guidance for producers and brand managers to enhance product market reach, optimize supply chains, and strengthen regional competitiveness in line with sustainable development goals. Full article