Search Results (141)

Extreme climate events can disturb vegetation dynamics and alter ecosystem stability. This study investigated the evolution of extreme climatic conditions and vegetation greenness across the Yangtze River Basin during 1982–2022 by integrating CN05.1 daily meteorological records with the PKU-GIMMS NDVI V1.2 dataset. Using the index framework of the ETCCDI, fifteen extreme weather-related climate indices were calculated. Trend magnitudes were quantified using Sen’s slope estimation, while the Mann–Kendall trend test was used to determine the direction and significance of long-term changes. Both standard correlation and lagged cumulative correlation were used to assess NDVI–climate relationships; the latter tested ten predefined windows formed from climate conditions between the current month and three months before each NDVI observation, with the largest absolute correlation defining the optimal window. The basin experienced a distinct warming signal in temperature extremes during 1982–2022, characterized by reduced occurrences of TN10p and TX10p, together with more frequent TN90p and TX90p events. Precipitation extremes showed an overall intensification, with R95p and R99p increasing by 9.2 mm per decade and 5.6 mm per decade. NDVI also increased throughout the analysis period, with a basin-wide rate of 0.0038 per decade and the fastest greening in the middle reaches at 0.0069 per decade. Vegetation NDVI was generally positively associated with warm-related temperature indices and negatively associated with cold-related indices. The lagged cumulative analysis identified the strongest NDVI–climate associations within windows combining current and antecedent climate conditions, with marked differences among subregions and vegetation types. Because the analyses are correlation-based and did not quantify non-climatic drivers such as land-use change or ecological restoration, the results should be interpreted as statistical associations rather than causal attribution. Overall, these findings characterize how vegetation greenness covaries with extreme climate indices across the Yangtze River Basin. Full article

Studies on the association between green spaces and childhood allergic diseases are limited and have yielded inconsistent results across different regions. Furthermore, this relationship remains underexplored in Chengdu, China. In this study, we aimed to investigate the association between the residential greening rate, Normalized Difference Vegetation Index (NDVI), proportion of allergenic plants (proportion of allergenic woody plants, proportion of allergenic herbaceous plants), the closeness-to-nature characteristics of children’s playgrounds, and childhood allergic diseases in Chengdu. Seven representative neighborhoods were selected based on a 2018 database of pediatric patients from West China Hospital of Sichuan University. Through questionnaires in 2025, data on allergic diseases (e.g., atopic dermatitis and allergic rhinitis) were collected for 210 children aged 0–6 years. Logistic regression models were employed to analyze the data. The results indicate that in the overall sample, residential greening rate, NDVI, proportion of allergenic plants and closeness-to-nature characteristics of children’s playgrounds showed no significant association with allergic diseases. However, subgroup analyses revealed that greening rate was positively associated with allergy risk among children aged 0–3 years, whereas the proportion of allergenic woody plants was negatively associated with allergy risk in this age group; residential NDVI was significantly negatively associated with allergy risk in low-to-medium-housing-price neighborhoods (<19,000 CNY/m²), but positively associated in high-housing-price neighborhoods (≥19,000 CNY/m²); the proportion of allergenic herbaceous plants was significantly negatively associated with allergy risk in children only in high-housing-price neighborhoods. The presence of children’s playgrounds, accessibility of natural elements, integration of sites and facilities into the landscape, and use of natural materials in playgrounds and facilities showed a negative trend with allergy risk in low-to-medium-housing-price neighborhoods; the integration of sites and facilities into the landscape was significantly positively associated with allergy risk in high-rise neighborhoods. Collectively, these associations vary based on individual and neighborhood characteristics. Targeted green space planning and design interventions should be context-specific, synergistically optimizing vegetation coverage and plant composition, while enhancing the closeness-to-nature characteristics of children’s playgrounds within neighborhoods. Our results provide empirical evidence that may offer insights into the development of healthy and child-friendly cities. Full article

Aridification and hotter droughts are triggering forest die-off events characterized by high mortality rates and declines in forest productivity. The western Mediterranean Basin is a climate change hotspot where many of these die-off events have affected several tree and shrub species in recent decades. Yet, the responses of canopy greenness and cover, radial growth, and gross primary productivity (GPP) to climate in these die-off sites remain poorly understood across species and biomes. Here, we examined 44 sites across Spain, covering humid, dry sub-humid, and semi-arid biomes, and including nine tree and one shrub species. We obtained and correlated monthly climate data, satellite-derived vegetation indices (Normalized Difference Vegetation Index, Enhanced Vegetation Index), tree-ring metrics (basal area increment, ring-width indices), and GPP. We assessed climate trends and relationships between climate, vegetation indices, growth, GPP, and resilience after five extreme drought years in the period 1984–2023. Climate warming impacted all sites, increasing vapor pressure deficit and reducing soil moisture availability, with semi-arid sites warming the most. Vegetation indices and growth showed the largest declines during extreme droughts in dry sub-humid and semi-arid sites. Correlations with climate variables highlighted strong sensitivity to drought stress, particularly regarding growth metrics. During die-off events, GPP significantly declined in the growing season, but no legacy effects were observed afterwards. Vegetation indices and growth partially recovered one year after drought, with resilience peaking for GPP in semi-arid sites. Hotter droughts constrain GPP and growth, especially in dry sub-humid and semi-arid forests. Forests and shrublands experiencing die-off are diagnostic monitors of drought-induced thresholds in ecosystem productivity. Full article

Accurately assessing and predicting vegetation dynamics is of great significance for evaluating regional hydrological and ecological environments. This study focuses on the climate-sensitive Qinghai-Tibetan Plateau (QTP), aiming to reveal the spatiotemporal patterns, underlying driving mechanisms, and future trends of vegetation dynamics. The historical turning points of greening trends were identified using the running slope difference method, and the SHapley Additive exPlanations (SHAP) method was employed to analyze the key driving factors. An Xtreme Gradient Boosting (XGBoost) prediction model was constructed and validated, and then coupled with Coupled Model Intercomparison Project Phase 6 (CMIP6) multi-model ensemble data to project seasonal vegetation changes under different Shared Socioeconomic Pathways (SSP). The main conclusions are as follows: (1) Vegetation on the QTP showed an overall greening trend with significant spatial heterogeneity. Approximately 47.25% of the area exhibited no trend shift (NS), while 29.42% experienced a shift from greening to browning (GB), with most shifts occurring between 1990 and 2010. (2) Soil moisture and precipitation were the dominant driving factors, with contributions significantly higher than those of temperature, wind speed, and other variables, and they exhibited nonlinear interactive effects with the Normalized Difference Vegetation Index (NDVI). (3) In the future, vegetation is projected to show an overall increasing trend, with stronger responses in spring and autumn. The regional average rate of change is highest in spring, especially under the SSP5-8.5 scenario (17.8% for 2030–2060 and 26.4% for 2061–2100); in autumn, although the regional average rate of change is small, the internal spatial variability is significant. The humid regions in the eastern and southeastern parts of the QTP demonstrated more active greening across all seasons except winter, and high-emission scenarios are expected to exacerbate regional and seasonal differences. This study systematically reveals the adaptive dynamics and future scenarios of vegetation dynamics on the QTP, providing scientific support for the adaptation of alpine ecosystems to global change and the management of regional ecological security barriers. Full article

The construction of green mines is a core strategy for promoting ecological civilization in China’s mining sector, yet its long-term ecological effects require quantitative assessment. Using a cement-grade limestone mine operated by Linyi Zhonglian Cement Co., Ltd. in Shandong Province as an illustrative case, we employed Landsat 8 OLI/TIRS imagery acquired in 2015, 2020, and 2025 to develop a five-indicator framework for assessing ecological environment quality. The selected indicators comprised greenness (NDVI), wetness, dryness (NDBSI), land surface temperature (LST), and dust concentration (MECDI). These five indicators were subsequently integrated via principal component analysis to generate the Mine Ecological Quality Index (Mine-EQI). Using this index, we applied the Theil–Sen median slope estimator alongside zonal statistics to examine ecological change trajectories across the full study area and three functional zones—the industrial square, haul roads, and active mining area—over the 2015–2025 period. The ecological outcomes attributable to the green mine policy were then quantified. The results show that (1) the mean Mine-EQI of the study area decreased from 0.3713 in 2015 to 0.3460 in 2025, exhibiting a slight overall decline. However, the rate of decline decreased from −6.1% during 2015–2020 to −0.7% during 2020–2025, yielding a Temporal Change Intensity index (TCI) of +88.5%, indicating that the ecological degradation trend has been effectively curbed. (2) Significant spatial heterogeneity was observed. The industrial square showed substantial improvement (Theil–Sen slope = +0.0726), while the haul roads (slope = −0.0705) and mining area (slope = −0.0408) continued to exhibit degradation trends. The improved areas (9.7% of the study area) were spatially coincident with green mine engineering projects. (3) The dust indicator (MECDI) decreased by 24.7% during 2020–2025, and the vegetation index (NDVI) increased by 19.5% over the decade, representing the dominant contributors to ecological improvement. This study reveals that China’s green mine policy has yielded remarkable ecological improvements in relatively stable functional zones such as industrial squares. In contrast, ecological restoration within persistently disturbed areas, including haul roads and mining pits, demands long-term sustained investment and governance. By integrating remote sensing techniques with policy analysis, this research establishes a replicable framework for evaluating progress toward sustainable mining practices. The findings directly support the monitoring of SDG 12 (Responsible Consumption and Production) and SDG 15 (Life on Land), providing a quantitative pathway to balance mineral resource extraction with ecological protection—a core sustainability challenge for resource-dependent regions. Full article

Amidst global urbanization and rising psychological stress, urban green spaces are increasingly recognized as critical infrastructure for sustainable urban development and public health. However, the mechanisms by which summer vegetation structure mediates both physiological and psychological restoration, and the interplay between these two dimensions, remain poorly understood. Understanding these mechanisms is essential for designing sustainable, health-promoting urban environments that can support growing urban populations in a warming climate. This study employed a controlled field experiment in Xi’an during summer to examine the effects of five vegetation structure types (Single-Layer Grassland, single-layer woodland, tree–shrub–grass composite woodland, tree–grass composite woodland, and a non-vegetated square) on university students’ physiological (heart rate variability) and psychological (perceived restorativeness and affective states) restoration. Following stress induction, 300 participants engaged with the green spaces through both quiet sitting and walking. The results revealed three key findings: (1) the tree–shrub–grass composite woodland consistently showed the most favorable trends other vegetation types across all psychological restoration dimensions, while also showing favorable trends in physiological recovery, underscoring the importance of structural complexity for restorative quality; (2) walking significantly enhanced physiological recovery compared to seated observation across all settings, confirming the role of physical activity as a critical activator of green space benefits; (3) correlation analysis identified a specific cross-system association: the R-R interval recovery value showed a weak but significant correlation with positive affect (PA) scores, suggesting that physiological calmness and positive emotional experience are linked, yet their weak coupling under short-term exposure indicates they may operate as parallel processes with distinct temporal dynamics. These findings indicate that the restorative potential of summer green spaces emerges from an integrated framework combining vegetation complexity and activity support. We propose that future sustainable landscape design should prioritize multi-layered vegetation structures as nature-based solutions that simultaneously enhance human well-being and urban resilience. These findings provide empirical evidence for integrating health-promoting green infrastructure into sustainable urban planning frameworks, supporting multiple Sustainable Development Goals (SDGs), including SDG 3 (Good Health and Well-being), SDG 11 (Sustainable Cities and Communities), and SDG 13 (Climate Action). Full article

Spring vegetation phenology is highly sensitive to climate change; however, climate drivers and their threshold responses at the urban scale remain insufficiently and systematically quantified. Focusing on 31 provincial capitals and municipalities in mainland China, this study integrated MODIS MCD12Q2-derived start-of-season (SOS) for spring green-up and TerraClimate climate data (2001–2023) at a 500 m grid resolution. SOS trends were characterized using the Mann–Kendall test and the Theil–Sen slope estimator. Building on these trend metrics, we developed an XGBoost–SHAP framework using the interannual rate of temperature change (tem_slope) and the interannual rate of precipitation change (pre_slope) as input features, to quantify the nonlinear contributions of climate-change rates to SOS trends and to identify key thresholds. Results indicate that the multi-year mean SOS across China’s provincial capitals and municipalities is primarily distributed between approximately DOY 74 and 138, exhibiting a clear spatial pattern of earlier green-up in the south, later green-up in the north, and delayed green-up on plateaus, with pronounced shifts in distribution centers and dispersion among climatic zones and cities. At the city level, the mean SOS trend shows an overall advancing rate of 0.81 d·year⁻¹ (i.e., the average of city-mean Sen slopes across the 31 cities). Pixel-level trend analyses show that advancing and delaying trends commonly coexist within most cities; among pixels with significant or marginally significant SOS trends identified by the Mann–Kendall test (MK p < 0.10) across all cities, advancing and delaying SOS pixels account for 75.02% and 24.98%, respectively. At the city scale, the proportions of advancing versus delaying pixels vary markedly among cities, forming directional structures characterized by advance-dominant, delay-dominant, or bidirectional coexistence patterns. SHAP dependence relationships further reveal that the effects of tem_slope and pre_slope on SOS trends are generally nonlinear and piecewise, with substantial heterogeneity across climate zones and cities. The identified tipping points and associated sensitive ranges collectively delineate spatially differentiated climate-sensitive intervals, which define the nonlinear response boundaries of spring SOS to sustained warming and precipitation changes. This study provides quantitative evidence for regional differences in urban spring phenological responses to climate change across major Chinese cities and offers a methodological reference for identifying actionable climate thresholds in urban greening design and climate-adaptive management. Full article

Mountain ecosystems are susceptible to climate change, and alpine treeline ecotones (ATEs) represent one of the significant responsive indicators of climate-driven environmental change. This study examines long-term spatiotemporal dynamics of the ATE across the Eastern Slopes of the Canadian Rocky Mountains (ESCR) from 1984 to 2023, with the objective of assessing whether regional climate warming has influenced ATE extent and elevation across different aspects and watersheds. Multi-decadal Landsat imagery, ERA5-Land temperature data, and topographic variables were integrated within a Google Earth Engine (GEE) framework to map ATEs using the Alpine Treeline Ecotone Index (ATEI), a probabilistic approach designed to capture transitional vegetation zones. Temporal trends were evaluated using non-parametric statistics, correlation analyses, and watershed- and aspect-based comparisons. Results indicate that the total alpine treeline ecotone (ATE) area in the ESCR was approximately 13.3% larger in 2023 than in 1984. However, the temporal evolution of ATE extent and elevation was non-monotonic, and linear trend analyses did not detect statistically significant increasing or decreasing trends over the full study period. ATE elevation and expansion exhibited pronounced spatial heterogeneity, with greater changes occurring on north- and northwest-facing slopes and within selected watersheds. In contrast, summer (July–September) temperatures increased significantly (+2.84 °C), exceeding global land-only warming rates, and vegetation greenness (NDVI) showed a strong, statistically significant positive relationship with temperature. These findings show that while climate warming has clearly increased vegetation productivity, elevational ATE dynamics remain spatially heterogeneous and temporally non-synchronous with summer temperature trends. Full article

Solanum torvum is an important medicinal and culinary vegetable with poor seed propagation, characterized by low germination and limited seed longevity. This study examined the effects of fruit maturity stage, storage temperature, duration, and endogenous hormonal profiles on seed germination. Fruits were harvested at three physiological maturity stages: matured green, ripe yellow, and overripe brown. Extracted seeds were stored in ambient (24–26 °C) and cold (3–8 °C) conditions for 24 weeks, with subsequent germination testing with 3 replicates per treatment. Endogenous abscisic acid (ABA) and gibberellic acid (GA) were quantified using HPLC-DAD to assess their association with germination behaviour. Seeds from ripe yellow fruits achieved the highest germination (95%), with a mean germination time of 12 days and a mean germination rate of 8%, identifying this stage as the optimal maturity stage for harvest. While total germination percentage was enhanced by an after-ripening effect during the first 16 weeks of ambient storage, other vigour parameters, including mean germination time and rate and synchronization began to decline thereafter. ABA and GA concentrations displayed treatment-dependent variation across maturity stages and storage conditions, with hormonal trends showing complex associations with dormancy release rather than consistent main effects. These findings indicate that harvesting Solanum torvum fruits at the ripe yellow stage and storing seeds under ambient conditions for up to 16 weeks, under the conditions evaluated in this study, provides a practical balance between dormancy alleviation and seed vigour, thereby improving short-term propagation efficiency. Full article

Leaf area index (LAI) is a key vegetation structural parameter widely used to quantify vegetation dynamics. A thorough understanding of its spatiotemporal characteristics and driving mechanisms is essential for sustainable ecosystem management. This study combines LAI and climate remote sensing data with socioeconomic statistics, and uses the Geographically and Temporally Weighted Regression (GTWR) model and geographic detector to identify the key drivers of LAI changes and their spatial differentiation characteristics. The results indicate a significant upward trend in the LAI across the basin, with a markedly higher growth rate after 2000 (0.0123/year) compared to the period before 2000 (0.0028/year). Spatially, before 2000, 57% of the regions showed an increasing trend in LAI, while after 2000, 69% of the regions exhibited an increasing trend in LAI. In terms of temporal LAI dynamics, in the eastern region, the positive promotion effect of the Grain for Green policy (GRGR) was the most significant factor affecting LAI changes. In the central region, the employed population ratio (EPR) emerged as the dominant factor driving LAI increase. In the western region, the negative effect of the urban–rural income ratio (IR) served as the primary driver of LAI change. Regarding the spatial distribution of LAI, both natural and policy factors were statistically significant. Mean precipitation (MP) and mean slope (MS) exerted the most pronounced influences, followed by mean temperature (MT) and GRGR, whereas mean elevation (MD) showed the weakest effect. Notably, socioeconomic factors did not demonstrate statistically significant impacts on the spatial distribution of LAI. This study provides a theoretical foundation for understanding the driving mechanisms of LAI dynamics in the Yellow River Basin and offers scientific support for ecological restoration and sustainable management in the region. Full article

To effectively manage and conserve ecosystems, it is crucial to understand how vegetation changes over time and space and what drives these changes. The Normalized Difference Vegetation Index (NDVI) is a key measure of plant growth that is highly sensitive to climate variations. Despite its importance, there has been limited research on vegetation changes in the upper sections of the Irtysh River. In our study, we combined various datasets, including NDVI, temperature, precipitation, soil moisture, elevation, and land cover. We conducted several analyses, such as Theil–Sen median trend analysis, Mann–Kendall trend and mutation tests, partial correlation analysis, the geographical detector model, and wavelet analysis, to reveal the region’s pronounced warming and moistening trend in recent years, the response relationship between NDVI and the climate, and the primary drivers influencing NDVI variations. We also delved into the spatiotemporal evolution of NDVI and identified key factors driving these changes by analyzing atmospheric circulation patterns. Our main findings are as follows: (1) Between 1901 and 2022, the area’s temperature rose by 0.018 °C/a, with a noticeable increase in the rate of warming around 1990; precipitation increased by 0.292 mm/a. From 1950 to 2022, soil moisture exhibited a steady increase of 0.0002 m³ m⁻³/a. Spatial trend distributions indicated that increasing trends in temperature and precipitation were evident across the entire region, while trends in soil moisture showed significant spatial variation. (2) During 1982 to 2022, the vegetation greening trend was 0.002/10a, indicating a gradual improvement in vegetation growth in the study area. The spatial distribution of monthly average NDVI values revealed that the main growing season of vegetation spanned April to November, with peak NDVI values occurring in June–August. Combined with serial partial correlation and spatial partial correlation analysis, temperatures during April to May effectively promoted the germination and growth of vegetation, while soil moisture accumulation from June to August (or January to August) effectively met the water demand of vegetation during its growth process, with a significant promoting effect. Geographical detector results demonstrate that temperature exhibits the strongest explanatory power for NDVI variation, whereas land cover has the weakest. The synergistic promotional effect of multiple climatic factors is highly pronounced. (3) Wavelet analysis revealed that the periodic characteristics of NDVI and climate variables over a 2–15-year timescale may have been associated with the impacts of atmospheric circulation. Taking NDVI and climatic factors from June to August as an example, before 2000, temperature was the dominant influencing factor, followed by precipitation and soil moisture; after 2000, precipitation and soil moisture became the primary drivers. The North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) were the primary atmospheric circulation patterns influencing vegetation variability in the region. Their effects were reflected in the inverse relationship observed between NAO/AO indices and NDVI, with typical phases of high and low NDVI closely corresponding to shifts in NAO and AO activity. This study helps us to understand how plants have been changing in the upper parts of the Irtysh River. These insights are critical for guiding efforts to develop the area in a way that is sustainable and beneficial for the environment. Full article

In response to the urgent demands of global climate governance, China has systematically integrated the green transition into its “dual-carbon” goals. The practical exploration of cultivated land emission reduction is not only crucial for promoting green transition but also embodies the synergistic effects of emission reduction and carbon sequestration in high-carbon-emission pressure areas. Existing studies have paid relatively less attention to high-carbon-emission pressure areas, necessitating more systematic research. In this study, we selected Henan Province as the study area and quantitatively analyzed the spatial-temporal differentiation of cultivated land net carbon sink from 2000 to 2023 along with their driving factors using an integrated methodological framework including Intergovernmental Panel on Climate Change (IPCC)-based carbon accounting, spatial autocorrelation analysis, and trajectory modeling. Analysis of the results indicates that the total net carbon sink of cultivated land in Henan Province showed a fluctuating yet overall upward trend with an average annual growth rate of 2.51%. The spatial distribution exhibits a pattern of “higher in the south and lower in the north” and “higher in the east and lower in the west”. This spatial pattern was significantly shaped by the cultivation area and fertilizer application intensity of three major crops—wheat, maize, and vegetables. Specifically, the net carbon sink contributions from these crops increased from 82.12% in 2000 to 85.93% in 2023, while the share of carbon emissions attributable to fertilizer use in the net carbon sink increased from 4.61% in 2000 to 5.22% in 2023, representing the activity with the largest contribution ratio among carbon emission activities. These findings provide valuable scientific evidence for further optimizing the green transition in high-carbon-emission areas and promoting the synergistic effects of emission reduction and carbon sequestration. Full article

In the context of global climate change and intensified water resource constraints, studying the evolution of the urban–agricultural–ecological spatial structure and the water–heat–vegetation responses driven by large-scale irrigation and drainage projects in arid and semi-arid regions is of great significance. Based on multitemporal remote sensing data from 1985 to 2015, this study takes the Inner Mongolia Hetao Plain as the research area, constructs a “multifunctionality–dynamic evolution” dual-principle classification system for urban–agricultural–ecological space, and adopts the technical process of “separate interpretation of each single land type using the maximum likelihood algorithm followed by merging with conflict pixel resolution” to improve the classification accuracy to 90.82%. Through a land use transfer matrix, a standard deviation ellipse model, surface temperature (LST) inversion, and vegetation fractional coverage (VFC) analysis, this study systematically reveals the spatiotemporal differentiation patterns of spatial structure evolution and surface parameter responses throughout the project’s life cycle. The results show the following: (1) The spatial structure follows the path of “short-term intense disturbance–long-term stable optimization”, with agricultural space stability increasing by 4.8%, the ecological core area retention rate exceeding 90%, and urban space expanding with a shift from external encroachment to internal filling, realizing “stable grain yield with unchanged cultivated land area and improved ecological quality with controlled green space loss”. (2) The overall VFC shows a trend of “central area stable increase (annual growth rate 0.8%), eastern area fluctuating recovery (cyclic amplitude ±12%), and western area local improvement (key patches increased by 18%)”. (3) The LST-VFC relationship presents spatiotemporal misalignment, with a 0.8–1.2 °C anomalous cooling in the central region during the construction period (despite a 15% VFC decrease), driven by irrigation water thermal inertia, and a disrupted linear correlation after completion due to crop phenology changes and plastic film mulching. (4) Irrigation and drainage projects optimize water resource allocation, constructing a hub regulation model integrated with the Water–Energy–Food (WEF) Nexus, providing a replicable paradigm for ecological effect assessment of major water conservancy projects in arid regions. Full article

Global soil moisture has undergone significant changes in recent decades due to climate change and vegetation greening. However, the seasonal and climate zonal variations in soil moisture dynamics at different depths, driven by both climate and vegetation, remain insufficiently explored. This study provides a comprehensive analysis of the global patterns in rootzone and surface soil moisture and leaf area index (LAI) across different seasons and climate zones, utilizing satellite observations from 1982 to 2020. We investigate how climatic factors and LAI influence soil moisture variations and quantify their dominant contributions. Furthermore, by employing key vegetation phenological indicators, namely the peak of growing season (POS) and the corresponding maximum LAI (LAI_MAX), we assess the feedback effects of vegetation phenology on soil moisture dynamics. The results indicate that the greening trend (as reflected by LAI increases) from 2000 to 2020 was significantly stronger than that observed during 1982–1999 across all seasons and climate zones. Both rootzone and surface soil moisture shifted from a decreasing (drying) trend (1982–1999) to an increasing (wetting) trend (2000–2020). From 1982 to 2020, the LAI induced moistening trends in both surface and rootzone soil moisture. In arid and temperate zones, precipitation drove rootzone soil moisture increases only during the summer. Among all seasons and climate zones, solar radiation induced the strongest surface soil drying in tropical summers, with a rate of −0.04 × 10⁻³ m³m⁻³/Wm⁻². For rootzone soil moisture, LAI dominated over individual climatic factors in winter and spring globally. In contrast, solar radiation became the primary driver during summer and autumn, followed by precipitation. For surface soil moisture, precipitation exhibited the strongest control in winter, but solar radiation surpassed it as the dominant factor from spring through autumn. In the tropical autumn, the sensitivity of rootzone and surface soil moisture to POS (and LAI_MAX) was highest, at 0.059 m³m⁻³·d⁻¹ (0.256 m³m⁻³/m²m⁻²) and 0.052 m³m⁻³·d⁻¹ (0.232 m³m⁻³/m²m⁻²), respectively. This research deepens the understanding of how climate and vegetation regulate soil moisture across different climate zones and seasons. It also provides a scientific basis for improving global soil moisture prediction models and managing water resource risks in the context of climate change. Full article

Vegetation dynamics in the Hulun Lake Basin (HLB), a vulnerable grassland–wetland–forest transition zone in Northeastern Inner Mongolia, North China, are sensitive to climate change, but traditional greenness metrics like the normalized difference vegetation index (NDVI) lack process-level insights. Using the GIMMS NDVI3g dataset (1982–2015) and meteorological data, this study analyzed the spatiotemporal dynamics of the NDVI and vegetation NDVI change rate (VNDVI)—a metric quantifying greening and browning speeds via NDVI temporal variation—employing linear regression and partial correlation analyses. The NDVI exhibited an overall significant upward trend of +0.0028 yr⁻¹ (p < 0.05) across more than 70% of the basin, indicating a persistent greening tendency. The VNDVI revealed an accelerated spring greening rate of +0.8% yr⁻¹ (p < 0.05) and a slowed autumn browning rate of −0.6% yr⁻¹ (p < 0.05), reflecting an extended growing season. Spatial correlation analysis showed that the temperature dominated spring greening (r = 0.52), precipitation governed summer growth (r = 0.64), and solar radiation modulated autumn senescence (r = 0.38). Compared with the NDVI, the VNDVI was more sensitive to both climatic fluctuations and anthropogenic disturbances, highlighting its utility in capturing process-level vegetation dynamics. These findings provide quantitative insights into the mechanisms of vegetation change in the HLB and offer scientific support for ecological conservation in North China’s grassland–forest ecotone. Full article