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Partitioning soil water balance (SWB) is an effective approach for deciphering the impacts of vegetation change on soil hydrological processes. Growing apple trees on the Loess Plateau, China, leads to a substantial deep soil water deficit, posing a serious threat to the sustainable development of apple production. However, the impact of deep-rooted apple trees on SWB remains poorly understood. In this study, we conducted a "Paired Plot" experiment to achieve this objective by decoupling SWB components using water stable isotopes, tritium, and soil water contents from deep soil cores (up to 25 m) under apple orchards with a stand age gradient of 8–23 years. The results showed that deep soil water storage under apple orchards was notably reduced compared to nearby farmland, showing a stand age-related pattern of deep soil water deficit (R2 = 0.91). By analyzing the changing patterns of SWB components, we found that the main factor driving this deficit is the water uptake process controlled by the deep root system. This process is triggered by the increased transpiration demand of apple trees and short-term water scarcity. These findings have implications for understanding soil water dynamics, sustainable agroforestry management, and soil water resources' protection in this region and other similar water-limited areas. [ABSTRACT FROM AUTHOR]

Comprehending the underlying mechanisms governing the dynamics of vegetation alteration constitutes a fundamental prerequisite for the effective implementation of ecological construction. In this study, the spatial heterogeneity of vegetation coverage in the Liaohe River Basin (LHRB) in China from 2000 to 2019 was analyzed using the Normalized Difference Vegetation Index (NDVI) derived from MOD13Q1 product. It proposed to combine factor regression and factor interaction to jointly explore the effects of factors on the NDVI. The results showed that: (1) The NDVI in the LHRB showed an overall increasing trend from 2000 to 2019; (2) Precipitation emerged as the predominant factor exerting influence on vegetation change across the basin, and the change trend of NDVI was synchronized with precipitation; (3) The interactions between two environmental factors had a greater influence on NDVI than any single factor. The interactions of natural factors played a dominant role; (4) The gradient changes in precipitation affected the explanatory power of other factors for NDVI. With the increase of precipitation, the activity of other factors kept getting stronger, and the fit of other factors to NDVI improved; (5) The human activities have generally been dominated by positive effects in the LHRB over the past 20 years. [ABSTRACT FROM AUTHOR]

The Southwest Alpine Canyon Area (SACA), a well-known ecological vulnerability region, plays a very important role in China. Identifying the driving force of the spatial heterogeneity of vegetation and the response of interannual vegetation changes to climate change and human activities would be helpful for ecosystem management. Based on the NDVI dataset, the study analyzed the trend of NDVI change from 2000 to 2019 using the Theil–Sen trend analysis and the Mann–Kendal significance test, detected the driving forces of the spatial heterogeneity of NDVI by the means of the geographical detector, and analyzed the relative contribution of climate change and human activities to interannual NDVI changes using residual analysis model. The results showed that, in terms of the spatial distribution, the pattern of NDVI showed that it is higher in the southeast and lower in the northwest region of the SACA. Elevation was the dominant factor influencing the spatial heterogeneity of NDVI, with the explanatory power of 64%, much larger than other factors, and vegetation type, temperature, precipitation, land use type, and soil type were the main factors. In addition, the explanatory power of the dual factor interaction was higher than that of the single factor effect, which showed two kinds of interaction relationships: bivariate enhancement and nonlinear enhancement. In terms of the temporal variation, 85.59% of the study area showed an increasing trend, and only 14.41% of the area showed a decreasing trend. The main factor affecting NDVI changes was human activities, and climate change was the secondary factor, with relative contributions of 71.35% and 28.65%, respectively. The study will promote a better understanding of the complex mechanisms of vegetation changes and provide scientific recommendations for the prevention of vegetation degradation and vegetation restoration in the SACA. [ABSTRACT FROM AUTHOR]

Sediment connectivity is a valuable metric that characterizes the relationship between sediment transport from the source to the sink, and the ease of sediment erosion. Over the past four decades, changes in land use types and vegetation cover have significantly altered sediment dynamics in the Wei River basin. In this study, we used the index of connectivity (IC) to assess the temporal changes in sediment connectivity at a watershed scale. We employed Landsat images to analyse the relationship between changes in vegetation cover or land use type and sediment connectivity. We used factor detector and interaction detector in Geodetector to analyse the importance and impact of vegetation and slope on IC changes. We assessed the correlation of sediment yield and connectivity to validate our results and it shows that IC has strong or moderate positive correlation with sediment yield from eight out of nine stations in the Wei River Basin. Our findings demonstrate that soil and water conservation measures, as well as the grain for green project, have led to the transformation of cropland and grassland into woodland. This change is reflected in the decrease of the maximum IC value from 6.24 to 5.72 in the Beiluo sub‐basin, indicating a decreasing trend in sediment connectivity. Although the maximum IC value increased from 5.76 to 5.08 in the Jing sub‐basin, driven by human activity, showing an increasing trend. Furthermore, the IC value decreased in the western part of the Wei sub‐basin. Overall, sediment connectivity exhibits a weak decreasing trend in most regions of the Wei River basin, while it shows an increasing trend slightly in the Jing sub‐basin. The correlation coefficients ranged from 0.47 to 0.86, with sediment yield being moderately or strongly correlated with IC. Our study identified vegetation, human activity, and slope as the main influencing factors of IC. The results of factor detector showed that the q value of vegetation was 0.63 and the slope was 0.1, Vegetation played a major role in the change of IC. The results of interaction detector showed that interaction between vegetation and slope was greater than the single factor. The temporal variability of sediment connectivity in the basin provides valuable insights for sediment transport management. Our research highlights the importance of studying sediment connectivity and offers proposals for measures that can be taken to address sediment transport challenges in the Wei River basin. [ABSTRACT FROM AUTHOR]

How to distinguish the relative role of climate change and human activities in vegetation dynamics has attracted increasing attention. However, most of the current studies concentrate on arid and semiarid regions, while the relative contributions of climate change and human activities to vegetation changes remain unclear in warm-humid regions. Based on the normalized difference vegetation index (NDVI) and climatic variables (temperature, precipitation, radiation) during 2001–2020, this study used the Theil–Sen median trend analysis, partial correlation analysis, and residual trend analysis to analyze the spatiotemporal pattern of vegetation trends, the response of vegetation to climate variations, and the climatic and anthropogenic contributions to vegetation dynamics in the warm and humid Guangdong Province of south China. Results showed that the NDVI in most areas exhibited an increasing trend. Changes in climatic variables displayed different spatial variations which, however, were not significant in most areas. Vegetation responded diversely to climate change with temperature as the most important climatic factor for vegetation improvement in most areas, while precipitation was the dominant climatic factor in the southern edge region and radiation was the dominant climatic factor in the central and western regions. Vegetation in most areas was influenced by both climate change and human activities, but the contribution rate of human activities was commonly much higher than climate change. The findings of this study are expected to enhance our understanding of the relative climatic and anthropogenic contributions to vegetation changes in warm-humid regions and provide a scientific basis for future ecological policies and ecosystem management in highly urbanized regions. [ABSTRACT FROM AUTHOR]

Reconstructing the Holocene megaflood history is a key component of understanding the mechanism of past climate change and assessing the potential impact of future catastrophic events. The Pearl River is the longest watercourse in southern China, and its lower reach has been identified as one of the world's most vulnerable regions for flood exposure. However, there is a complete lack of millennial-scale geological records of paleomegafloods for the future prediction of once-in-a-hundred (even once-in-a-thousand) year floods in southern China. Here, we identified a series of paleomegaflood deposits interbedded with wood-rich peat layers in the lower West Pearl River area. All paleoflood layers have been well dated using AMS 14C dating method. According to the regional correlation of the flood sequence, sediment characteristics and provenance analysis, there have been at least 7 megafloods corresponding to once-in-a-thousand-year events in the lower reaches of the West Pearl River during the past 6000 years, with an average return period of approximately 855 years. The identified paleomegafloods were coeval with periods of strong El Niño-Southern Oscillation (ENSO), indicating that weakening of the Asian summer monsoon, associated with enhanced ENSO variability, may have triggered abnormally high precipitation leading to flooding of exceptional magnitude in southern China. In addition, the most prominent paleomegafloods identified in the lower Pearl River coincided with intervals of lower precipitation and fewer storms in central-eastern China, indicating the intensification of the meridional "tripole" pattern of precipitation across eastern China during the latter half of the Holocene. Increased land use and deforestation over the last 2000 years have resulted in soil loss and rapid degradation of local primeval forest ecosystems, leading to more catastrophic flooding. Large amounts of rice pollen in the uppermost flood layer during the Song Dynasty indicate that this megaflood may have inundated a large area of cultivated land. The periodic occurrence of Holocene megafloods not only caused damage to human existence, but also affected the evolution of local civilization. This study reveals for the first time a series of Holocene millennial-scale megafloods and sheds new light on the importance of atmosphere-ocean interactions in the tropical Pacific and monsoon subtropical climate dynamics for precipitation anomalies in East Asia. Our data yield valuable information for future research into climate extremes and hazard prevention. [ABSTRACT FROM AUTHOR]

The UN Decade of Ecosystem Restoration (2021–2030) provides a new momentum for scaling up ecosystem restoration efforts to landscape restoration. China's recent experience with transformative investment in landscape restoration provides invaluable guidance for the world. We retrospectively reviewed the scientific evidence on the responses of physical, ecological, and social processes to China's landscape restoration under geographic heterogeneity and obtained four experiences and lessons. First, China's forest landscape restoration has successfully promoted vegetation growth and enlarged the carbon sink. Second, landscape restoration has reduced the local water yield, while the regional responses of rainfall are still not clear. Third, the local conditions of soil erosion and habitat quality were largely improved by landscape restoration, while the decreases in soil moisture and streamflow demonstrated significant trade-offs among ecosystem services. Last, geographical differentiation existed in the local responses of livelihoods to landscape restoration strategies, and the win‒win solutions between human development and nature improvement under different landscape contexts were still uncertain. We summarize three additional questions as future prospects: what is the scale of the thresholds to prevent overshoot and cascading negative ecological effects? what are people's prior needs from nature? considering that there may be no universal win‒win pathways, how to promote co-benefits based on regional human–nature relationships? [ABSTRACT FROM AUTHOR]

Water resources management and planning traditionally focus on visible liquid or blue water. However, green water also maintains social development and ecosystem services. Therefore, blue and green water should be incorporated into the watershed management system for evaluating water resources. To analyze the water resources of the Hanjiang River Basin, the SWAT model was set up using long-term and high-precision geographic data. The methods of wavelet analysis and Pearson's correlation analysis were used to explore the influence mechanism of climate and vegetation changes on the blue and green water flow (BWF and GWF) of the main ecosystems in the basin. The results showed that: (1) The spatial–temporal distribution of the BWF and GWF in the main ecosystems of the basin over the past 50 years was uneven. Forest ecosystems and farmland ecosystems have a greater concentration of water resources in the south, while grassland ecosystems have a greater concentration of water resources in the east. (2) Climate dominates the BWF and GWF changes in the main ecosystems of the basin. The BWF and the precipitation change cycle are synergistic, and the GWF and the temperature change cycle are synergistic. (3) The correlation between vegetation and BWF and GWF in the farmland ecosystem is significant. Vegetation affects the hydrological change process of the BWF and GWF at the microscale. This study can provide data support and scientific rules for ecosystem water resource management in the basin. [ABSTRACT FROM AUTHOR]

Ecological protection and high-quality development of the Yellow River Basin (YRB), China, aroused remarkable concerns from China's Central Government, and has been a major national strategy. The Inner Mongolia reach of the Yellow River Basin (IM-YRB) is a typical dryland with pervasive vegetation restoration through the actions of the ecological projects that have been conducted in recent years. However, how climate changes and human activities, such as land use and land cover (LULC) changes, jointly impact vegetation variations in this region remains poorly understood. Here, using an explainable machine learning technique, we evaluated linkages between the kernel normalized difference vegetation index (kNDVI) and air temperature, precipitation, soil moisture, and LULC changes, and relevant marginal contributions of these four drivers to the observed vegetation changes. The grassland fraction on a pixel level was selected as the quantitative LULC variable due to its key role in regional LULC. We found that interannual kNDVI changes in most areas of this study region were negatively sensitive to temperature, but positively sensitive to precipitation and soil moisture, with area fractions of 71.74%, 96.93%, and 89.33%, respectively. The area fraction of negative kNDVI sensitivity to LULC was roughly equivalent to that of positive kNDVI sensitivity. The contributions of air temperature, precipitation, soil moisture, and LULC to overall kNDVI changes were 21.54%, 33.32%, 32.19%, and 12.95%, respectively. Moisture conditions also play a critical role in vegetation changes, which was reflected by the fluctuating growth of kNDVI as interannual changes in precipitation. Nonetheless, kNDVI changes are also affected by LULC, and LULC became the dominant factor behind the kNDVI anomalies over the grassland restoration regions from barren over the IM-YRB. This research provides theoretical support for dryland vegetation restoration under the influence of climate change. [ABSTRACT FROM AUTHOR]

How land use changes and geomorphologic zones impact on vegetation nonlinear trends remains unclear in economically developed areas with complicated terrain. This paper explores the nonlinear trends of vegetation changes with normalized vegetation index (NDVI) in the Yangtze River basin, China, and further analyzes the effect of geomorphologic zones and land use changes on the nonlinear trend. The results show that: (1) Although monotonic increasing is the main trend type of vegetation NDVI (32.46%), reversal trends from decreasing to increasing and from increasing to decreasing account for 11.87% and 24.95%, respectively. (2) The vegetation change is mainly monotonically increasing in low altitude and relief zones, while that is mainly a reversal trend in high altitude and relief zones, indicating an increased risk of vegetation degradation with altitude and relief increasing. (3) The trends in most land use types are mainly monotonically increasing, but those in urban, forest, and grassland are mainly from increasing to decreasing, with area percentages as high as 32.29%, 27.25%, and 35.97%, indicating degradation risk. (4) The conversion of cropland and wetland to forestland has greatly promoted the vegetation restoration. However, a risk of vegetation degradation exists in land conversions between grassland and other land use types, especially the afforestation of grassland. Over all, considering the effects of both geomorphic zones and land use changes can help us better explore the driving of the nonlinear trends of vegetation changes and understand the process of vegetation dynamics. [ABSTRACT FROM AUTHOR]

• The evolution of vegetation during the Holocene period was reconstructed in Central China. • The reduction of trees by human activity during the middle to late Holocene has been revealed in Central China. • The regional evolution of prehistoric houses closely corresponded to the decline in the tree population. The interaction between climate, hydrological environment, and human activities in prehistoric times has consistently attracted significant interest. However, the process and mechanism of this interaction remain unclear due to a lack of detailed materials that provide information on both human activity and environmental evolution. Here we present a comprehensive dataset of optically stimulated luminescence (OSL) dating and pollen analysis derived from lacustrine facies deposits in the vicinity of the Dongzhao Site in Central China, which is a key region for the origin and development of Chinese civilization. These data have revealed the existence of multiple cycles of environment-human interaction during prehistoric periods. The gradual improvement in the climate and minor fluctuations facilitated the settlement of prehistoric populations in the region, fostering uninterrupted cultural development for millennia since the early Holocene. The increase in population and intensification of human activities significantly affected regional vegetation, resulting in a decrease in the number of trees around 4.0 ka BP. Environmental changes influenced the prehistoric architectural style, resulting in a decrease in houses with "wood bone and mud walls" that were prevalent during the Yangshao periods (7.0–5.0 ka BP) due to a lack of trees. Our research once again highlights the perpetual cycle of interdependence and interaction between natural environments and human activities. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) is a key component of water cycle and is strongly modulated by below‐ground (e.g., dynamic effective rooting depth, Zr) and above‐ground (e.g., LAI and canopy height, CH) vegetation dynamics. Existing studies mainly focus on the effect of above‐ground vegetation dynamics on ET, while it is still unclear how Zr affects ET. Moreover, it is challenging to parameterize Zr dynamically in large‐scale hydrological and biogeochemical models due to data scarcity. Here, we estimate Zr in China from 1982 to 2015 based on Guswa's carbon cost‐benefit model, and update ET partitioning algorithm by replacing CH with Zr in PT‐JPLsm model to form the PT‐JPLzr model. We find that root mean square error (RMSE) between modeled (based on PT‐JPLzr model) and observed ET is 8.25% lower than that of PT‐JPLsm model at 16 in‐situ ET observation sites. Comparing with T/ET from the satellite‐based products, our results highlight the improved performance of PT‐JPLzr (R2 = 0.66) due to incorporated Zr, which is superior to that of PT‐JPLsm model (R2 = 0.62). Transpiration (T) limited by changes in soil moisture (SM) is more sensitive to Zr than CH. Thus, Zr improves the PT‐JPL model performance by affecting the sensitivity of T to soil moisture deficit. Moreover, SM and LAI are main drivers of T/ET spatial variability in drier and wetter regions, respectively. These findings highlight the critical role of Zr in regulating the effects of soil moisture deficit on ET. Key Points: We extend the static plant rooting depth to estimate the dynamic effective rooting depth (Zr) across ChinaZr is incorporated into evapotranspiration (ET) model to simultaneously consider the joint effects of canopy structure and rooting depth on ETTranspiration limited by soil moisture deficit is more sensitive to changes in Zr than canopy height (CH) [ABSTRACT FROM AUTHOR]

Climate change and human activities significantly affected environmental changes in drylands. However, the relative roles remain unclear regarding these factors' effects on environment changes in drylands. Herein, we analyzed vegetation change trends using remote-sensing datasets to determine the interactions of vegetation, climate, and anthropogenic activities in an arid region of China, Kubuqi Desert. Our study showed that 67.64% of the pixels of fractional vegetation coverage (FVC) increased in 2020 in comparison with those of 1986. The FVC exhibited a significant greening trend (0.0011/yr, p < 0.05) in 1986–2020 as a whole. This greening trend revealed two distinct periods separated by a turning point in 2001. There was no clear trend of FVC before 2001, and then there was a dramatically greening trend since 2001 in most regions of the study area. The increasing rate (0.0036/yr) in the later period was three times higher than the entire period. The accelerated increasing trend was due to the variable compound effects of climate and human activities. The correlation between FVC and precipitation was mainly positive, which outweighs the significantly negative correlation between vegetation and temperature. However, both climatic factors cannot well explain the trends of vegetation dynamics, implying a possible role for human activities. Generally, climate change and anthropogenic activities contributed 42.15% and 57.85% to the overall vegetation variations in 1986–2020. Specifically, the relative role of the two factors was vastly different in two distinct periods. Climate change led the dominant roles (58.68%) in the vegetation variations in 1986–2001, while anthropogenic activities dominated (86.79%) in driving vegetation recovery in the period after 2001. Due to the massive ecological conservation programs such as the Grain for Green Project launched in 2001, substantial deserts have been transformed into grasslands and forests. This analysis highlights the ecological policies largely responsible for vegetation restoration and provides references for ecological protection and sustainable development in eco-fragile ecosystems. [ABSTRACT FROM AUTHOR]

The vegetation is known to be sensitive to both climate change and anthropogenic disturbance. However, the relationship between changes in vegetation and climate is unclear in karst regions. The nonlinear characteristics of vegetation change and its possible relationships with driving factors in the karst region of southwest China are revealed, using methods of Ensemble Empirical Mode Decomposition, Mann-Kendall, and Partial Least Squares Regression. The results show that: (1) vegetation changes demonstrate an increasing trend with an abrupt change in 2002. Multiple time scales of 3, 6, 10, and 25-year are observed in vegetation variations, dominated by long-term trend and the short time scale of 3-year with variance contributions of 58.10% and 28.63%. (2) The relationship of climate indexes with vegetation changes shows r 2 = 0.78 (p < 0.01) based on the reconstruction of characteristic scales, indicating significant great relationship. In space, the area percentage with relationship of climate to vegetation is more than 50%, and the impact is much greater after the abrupt change of vegetation in 2002 (r 2 are 0.24–0.91 and 0.42–0.99, respectively). In addition, the correlation between vegetation change and ecological engineering is 0.15 (p < 0.01). The results indicate that climate change is the main impact factor of vegetation change, ecological engineering has positive influences in improving vegetation condition, and methods of scales decomposition and abrupt detection could reveal some hidden information for better understanding ecosystems in karst regions. [ABSTRACT FROM AUTHOR]

Soil organic carbon (SOC) detachment and transport, especially in the eroded areas, has a profound influence on the global carbon cycling and climate. However, soil organic carbon erosion still has a high uncertainty on land C balance components for lack of a detailed capture of local topography and quantitative factors. Here, aimed at the Loess Plateau (LP) area with undulating terrain, we presented an unprecedentedly high resolution (90 × 90 m) soil erosion model, Revised Universal Soil Loss Equation and the contributions of vegetation to SOC erosion changes were quantified through factorial simulation. Our findings demonstrate soil organic carbon which induced a substantial lateral redistribution by soil erosion was 10.46 Tg C yr−1 over the period 2000–2017, which was a decrease of 21% compared with that before 2000. In the fixed‐NDVI scenario, after 2000, SOC erosion increased by around 7% compared with that before 2000. Agriculture and shrub are the primary source of regional soil erosion and SOC erosion. These findings highlight the importance of lateral transport of SOC as an important process in soil and carbon cycles for future regional carbon cycle assessment. Plain Language Summary: Erosion‐induced soil transport and deposition change the spatial distribution of soil organic carbon, which has a profound influence on global carbon balance and climate environment. As a common focus of climate change and soil degradation, the impact of soil erosion on soil organic carbon has attracted wide attention. Generally, researches on soil organic carbon erosion lack detailed capture of local topography and quantitative factors. We provide quantitative, thorough and detailed estimates of soil erosion in Loess Plateau by means of a high‐resolution, spatially distributed, Revised Universal Soil Loss Equation‐based modeling approach. Unlike previous studies that dealt with soil erosion as a static process, here we shed light on the impacts of land use change on soil erosion. The contributions of vegetation to SOC erosion changes were quantified through factorial simulation. Our results indicated that the simulation model with a resolution of 90 m can detailly describe the local soil erosion and SOC erosion. The importance of the use of high precision data in erosional key areas is revealed, and continuous high precision data are also provided for modeling of hydrological models. Key Points: Based on a high‐resolution, continuous spatially distributed landuse, Revised Universal Soil Loss Equation was used to estimate quantitative, detailed soil erosionSoil organic carbon (SOC) erosion displayed a similar spatial pattern with soil erosionSOC erosion in the Loess Plateau was 10.46 Tg C yr−1 over the period 2000–2017, which was a decrease of 21% compared with that before 2000 [ABSTRACT FROM AUTHOR]

Understanding the impact of climate change and human activities on vegetation dynamics is crucial for ecosystem management. Employing the Residual Trend method and integrating Normalized Difference Vegetation Index (NDVI) data with land use/cover, this study assesses the impacts of climate change and human activities on vegetation dynamics across China from 2000 to 2018. The findings indicate a consistent upward trend of China's Growing Season NDVI (GSN), averaging a change rate of 0.0032/yr. Human activities are the primary drivers of this change, contributing 82.47% to GSN in China, while climate change accounts for 17.53%. The effect of human activities on vegetation dynamics showed considerable variation across different river basins, with the Huaihe River Basin experiencing the highest human impact (93.53%) and the Continental Basin the lowest (76.27%). Conversely, the Continental Basin experienced the greatest impact from climate change (23.73%), compared to the minimal influence in the Huaihe River Basin (6.47%). The study results offer contribution rates for each type of changed and unchanged land use, with persistent forestland, persistent grassland, persistent cropland, and grassland to forest conversion contributing 28.65%, 22.09%, 13.76%, and 4.61%, respectively. Persistent forestland emerges as the most efficacious land use type for facilitating vegetation restoration. Within the persistent forestlands of the Yangtze, Pearl, and Southeast River Basins, human activities accounted for 26.99%, 42.18%, and 43.50% of the vegetation alterations, respectively. These findings provide a scientific basis for formulating effective ecosystem management and protection strategies. • China's vegetation shows a rising trend, at an average rate of 0.0032/yr • Unchanged land use/cover impacts GSN more than changed land use/cover • Human activity drives 82.47% of vegetation change, climate change at 17.53% • Persistent forestland tops for vegetation restoration with a 28.65% contribution [ABSTRACT FROM AUTHOR]

• NO X inhibits the growth of forests, causing vegetation browning of urban green space. • Urbanization and climate change are positive with NO X , co-limiting forest production. • The responses of forest understory layers to environmental changes are different. • Urbanization increases leaf herbivory and lead to severe pests of urban green space. Nowadays, atmospheric concentrations of nitrogen oxides (NO X) have increased rapidly and exceeded the threshold of ecosystems, inevitably affecting the plant growth and community stability, especially in urban green space. The increase of atmospheric NO X is also accompanied by natural and anthropogenic environmental change, which also bring severe environmental stresses on green vegetation. To better understand drivers that contribute to the vegetation changes, this study explored the interaction among atmospheric NO X , climate, terrain, and urbanization, and its impact on the tree leaf and forest community traits, using a dataset with 118 plots of tree communities composed of 5781 trees across distinct types of urban green space in Tianjin, a highly urbanized metropolis in China. The results indicated that atmospheric NO X concentration showed a positive association with urbanization and temperature, which co-limited the tree growth and resulted in the vegetation browning of urban green space. The responses of coniferous and broadleaved forests were different, whose understory herbaceous diversity and height had contrary tendencies to environmental change. Meanwhile, urbanization intensified atmospheric N deposition and heat island effect, increasing the leaf chlorophyll contents of tree species in urban green spaces. While leaf herbivory showed positive correlation with urbanization, temperature, and evaporation only in the high NO X regime. Overall, this study found that atmospheric NO X could be used as a good indicator of urbanization. These findings also advanced our recognition of the environmental driving factors of green vegetation dynamics, and provided references for the research of elsewhere. [ABSTRACT FROM AUTHOR]

Climate and vegetation are important components of a changing environment that have synergistic effects on surface runoff. To date, few researchers have included the synergistic effects of changes in climate and vegetation in runoff simulation studies. In this study, a water-heat balance model based on the Budyko hypothesis was established, and an empirical formula for estimating model parameters based on the Normalized Difference Vegetation Index was proposed. This Normalized Difference Vegetation Index-climate relationship model allowed the synergistic effects of changes in climate and vegetation on runoff trends to be analyzed. The model was tested in the Fen River Basin, China. The results showed that the annual runoff would be 15.4%–39.5% (between 2020 and 2100) higher under two climate change scenarios than in the baseline period (2006–2015). Climate-driven change in the vegetation cover accounted for 8.0%–19.6% of the total variation in the runoff. The change in the vegetation cover inhibited the increase in runoff. To improve the accuracy of models and avoid overestimates, synergistic changes in vegetation and climate should be included in model simulations. [ABSTRACT FROM AUTHOR]

In arid-semiarid regions, understanding the mechanisms by which vegetation change and climate change affect the regional water balance is important for the development of effective measures and for guiding vegetation restoration and adapting to climate change. In this study, we utilize the Budyko equation and dual-source evapotranspiration models to assess the impacts of vegetation change and climate change on the runoff in China's Yellow River Basin (YRB). The aims of the study are as follows: (1) Apply a well-formulated Budyko framework-dual-source evapotranspiration model to explore the eco-hydrological controls of the regional water balance. (2) Precisely assess the contribution of vegetation change, precipitation change, temperature change, wind speed change, the relative humidity change, and radiation change to the decreased runoff. The results indicated that vegetation change was the dominant factor affecting the reduction of runoff in the upper reaches above Lanzhou, Toudaoguai, Longmen, Sanmenxia, and Huayuankou, and the contributions were −80.4%, −58.4%, −52.5%, −46.9%, −39.7%, and −41.6% respectively. In Lanzhou, Taodaoguai, Longmen, and Sanmenxia, the precipitation change was the second affecting factor, and the contributions were −20.8%, −31.6%, −30.0%, and −35.2%, respectively. In Huayuankou and Lijin, the relative humidity change was the second affecting factor, and the contributions were –26.8% and −35.0%, respectively. (3) As the vegetation coverage or the leaf area index (LAI) increased, the runoff decreased linearly. [ABSTRACT FROM AUTHOR]

As the source of the Yellow River, Yangtze River, and Lancang River, the Three-River Source Region (TRSR) in China is very important to China's ecological security. In recent decades, TRSR's ecosystem has degraded because of climate change and human disturbances. Therefore, a range of ecological projects were initiated by Chinese government around 2000 to curb further degradation. Current research shows that the vegetation of the TRSR has been initially restored over the past two decades, but the respective contribution of ecological projects and climate change in vegetation restoration has not been clarified. Here, we used the Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) to assess the spatial-temporal variations in vegetation and explore the impact of climate and human actions on vegetation in TRSR during 2001–2018. The results showed that about 26.02% of the TRSR had a significant increase in EVI over the 18 yr, with an increasing rate of 0.010/10 yr (P < 0.05), and EVI significantly decreased in only 3.23% of the TRSR. Residual trend analysis indicated vegetation restoration was jointly promoted by climate and human actions, and the promotion of human actions was greater compared with that of climate, with relative contributions of 59.07% and 40.93%, respectively. However, the degradation of vegetation was mainly caused by human actions, with a relative contribution of 71.19%. Partial correlation analysis showed that vegetation was greatly affected by temperature (r = 0.62, P < 0.05) due to the relatively sufficient moisture but lower temperature in TRSR. Furthermore, the establishment of nature reserves and the implementation of the Ecological Protection and Restoration Program (EPRP) improved vegetation, and the first stage EPRP had a better effect on vegetation restoration than the second stage. Our findings identify the driving factors of vegetation change and lay the foundation for subsequent effective management. [ABSTRACT FROM AUTHOR]

Reconstruction of past vegetation changes is critical for sustainable development in the fragile and highly eroded ecosystems on the Chinese Loess Plateau (CLP) under global change, particularly in light of future warming events. In this study, we collected fossil pollen data from 40 sites to reconstruct the Holocene (since 11 ka) vegetation pattern of the CLP using the biomization method. The results demonstrate that the CLP vegetation during the entire Holocene was dominated by grassland landscapes in most areas and periods, whereas the forest landscape only developed in some areas during certain periods. Steppe vegetation rather than forest vegetation was distributed in the central region of the CLP. Six forest biomes were primarily distributed in the southwestern and northeastern plateau high-altitude areas, showing notable expansion toward low latitudes and longitudes during the early to mid-Holocene. The steppe biome showed a rather wide distribution, primarily in the center and south, and especially in the expanded western region during the Early Holocene. Minor variations were observed for the widely distributed steppe biomes that shifted to high longitudes and latitudes during the Holocene. The desert biome was identified in the relatively restricted western and northern regions of China. Reconstructed biome spatial distributions showed a large vegetation gradient on the CLP. This suggests that variations in forest biomes on the CLP were potentially influenced by changes in precipitation. Different topographies within the same area led to different biomes. In addition, increased human activity may cause vegetation destruction. • Reconstructing vegetation changes is key for sustainable development on the CLP. • Fossil pollen data were used to reconstruct Holocene vegetation using biomization. • Dominant biomes on the CLP during the Holocene were deduced. • Results highlight spatial and temporal variability of fragile ecosystems on the CLP. [ABSTRACT FROM AUTHOR]

The Early Jurassic Jenkyns Event (or Toarcian Oceanic Anoxic Event T-OAE) was an episode of global warming and C-cycle perturbation that affected both marine and terrestrial ecosystems, but the interplay between climate change and vegetation is not established in detail from sections outside of Europe. Here, abundance changes in spore-pollen assemblages from the lacustrine Anya succession in the Ordos Basin (North China) reveal a unique record of vegetation dynamics during the Jenkyns Event. Plant communities responded to the event with biodiversity losses and the reorganization of gymnosperm-dominated forests. Community-level shifts are observed from the Pliensbachian–Toarcian boundary, but the onset of the negative carbon excursion (NCIE) that marks the event is coeval with the most significant turnover: a switch from a high-diversity vegetation with conifers, seed ferns, cycads, bennettites and ferns to drought-adapted low-diversity flora with Cheirolepidiaceae. The demise of forests and lowland mire biomes resulted in deforestation with increased weathering and soil erosion that exacerbated the terrestrial ecosystem crisis already under stress from rising temperatures. Terrestrial recovery was initiated before the end of the Jenkyns Event with the resurgence of pioneer ferns and lycopsids that colonized disturbed habitats. Plant assemblages signal aridification at the onset of the event with frequent climatic oscillations and extreme weather patterns during the event itself. The main NCIE phase was preceded by a short-lived cooling phase in the earliest Toarcian. In the aftermath of the NCIE, Cheirolepidiaceae forests declined and a more stable biome developed with seed ferns and various conifers. This was contemporaneous with delta development and shallowing of the lake surrounded by lowland mires with ferns, clubmosses and horsetails. Comparison of floral patterns across the Jenkyns Event show that, although Cheirolepidiaceae dominated the event globally, there were differences in vegetation response between coastal and inland areas, and recovery patterns might differ regionally. • Early Jurassic vegetation and climate from the Ordos Basin across the Jenkyns Event. • Floral changes across the Jenkyns Event with diversity and functional losses. • Classopollis dominace during the Event with spatially hetrogen floral patterns. • Aridification at the onset of the Event with climatic oscillations during the event. • Colder climate precedes Toarcian NCIE and temperate post Jenkyns Event climate. [ABSTRACT FROM AUTHOR]

[Display omitted] • Coupling PT-JPL into DTVGM improved the hydrological simulation accuracy in UHRB. • Except for Pr, which had a high positive correlation with BW, other climatic factors correlated relatively weakly with BW and GW. • Vegetation showed a significant greening trend in UHRB, facilitating the transformation of BW to GW. • Vegetation greening will alter the original correlation between climatic factors and hydrological processes. The characteristics of water fluctuations within the basin have remained ambiguous in recent years due to climate and vegetation changes, posing a challenge to the planning and utilization of regional water resources. This study coupled the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model, which can consider vegetation dynamics information and evapotranspiration physical mechanisms, into the Distributed Time Variant Gain Model (DTVGM) to improve the hydrological simulation accuracy under changing environments. Based on different simulation scenarios of the coupled model, the effects of climate and vegetation changes on hydrological processes were fully investigated using blue and green water (BW and GW) as assessment metrics. The upper Han River Basin (UHRB), as water source for the Central Line Project of China's South-North Water Diversion (CSNWD), was selected as a typical basin for the study, results indicated that: (1) The DTVGM coupled with PT-JPL could better reflect the spatiotemporal patterns of major hydrological processes (runoff, evapotranspiration, and soil moisture) in UHRB from 2001 to 2019; (2) The BW in UHRB exhibited decreasing trend from 2001 to 2019, while the GW on the contrary. Surface runoff (Rs), vegetation transpiration (Et), and soil moisture (W) contributed most in the components of BW and GW; (3) Vegetation change dominated by greening in UHRB, which facilitated the transformation of BW to GW in the basin, and it increased the proportion of GW mainly by promoting Et. BW was mainly influenced by precipitation, but vegetation change altered the original correlation between climatic factors and hydrological processes. This study can support the management of water resources in the basin under changing environments. [ABSTRACT FROM AUTHOR]

Grassland vegetation changes can be assessed based on vegetation growth dynamics and spatial characteristics of vegetation growth or land cover patches. However, previous studies have focused mainly on assessing changes in grasslands based only on vegetation growth condition, with limited consideration of spatial characteristics, which may lead to inaccurate identification of grassland dynamics. Here, a decision tree approach was developed to classify changes in grassland vegetation based on remote sensing data considering not only temporal variation in vegetation cover at the grid cell scale but also temporal variation in both spatial heterogeneity of vegetation cover and spatial configuration of bare land patches at the local landscape scale. The decision tree approach was verified using field and historical data and used to classify vegetation changes in the Xilingol League, Inner Mongolia, China, during the 2000–2019 period. According to the results, the study area was occupied mainly by grasslands with an insignificant change in vegetation growth, followed by those with significant improvement, and it was least occupied by those with significant decrease (but still covering 344 km2). Compared to vegetation cover, a combination of spatial characteristics was more effective in identifying changes in vegetation, including improvement, fragmentation, and degradation, and subtle changes within each process. A slight change in spatial heterogeneity of vegetation cover (such as the spatial coefficient of variation of the normalized difference vegetation index) may have overall impacts on the grassland. Each state during grassland retrogression, from moderate degradation through severe degradation to desertification, can be inferred by changes in spatial configuration (such as connectivity) of bare land patches, as well as the current bare land area. Overall, spatial characteristics can provide important theoretical information to facilitate assessment of grassland ecosystem dynamics and stability and serve as a critical early warning indicator for potential desertification. • An approach for grassland vegetation change classification is developed. • The approach was reliable in classifying vegetation changes in Inner Mongolia. • Considering spatial characteristics is critical to identify vegetation changes. • A slight change in spatial heterogeneity of vegetation may have overall effects. • Changes in connectivity of bare lands can indicate state shifts in grassland. [ABSTRACT FROM AUTHOR]

Direct effects of climate change (i.e. temperature rise, changes in seasonal precipitation, wind patterns and atmospheric stability) affect fire regimes of boreal forests by altering fire behaviour, fire seasons and fuel moisture. Climate change also alters species composition and fuel characteristics, which subsequently alter fire regimes. However, indirect effects of climate change are often simplified or neglected in the direct climate–fire relationship models and dynamic global vegetation models. This may result in high uncertainties associated with existing projections of fire regimes for climate change scenarios. Moreover, few studies have examined fire regime predictions beyond the 21st century, and consequently, how the fire regimes of boreal forests would respond to climate change at the long term (>100 years) are not clear.We develop a coupled modelling framework integrating direct and indirect effects of climate change to predict fire occurrence probability and burned area for boreal forests in northeastern China. We applied repeated measures ANOVA to quantify direct and indirect effects of climate change on fire regimes in the short (0–50 years), medium (60–100 years) and long term (150–200 years).Results showed that for the 21st century, direct effects of climate change are likely to exert a stronger influence on fire regimes than indirect effects. However, increases in fire occurrence probability and burned area will accelerate the transition of boreal forests to temperate forests in the period 2100–2200, and thereby reduce fire occurrence probability and burned area. This suggests that vegetation change will mediate direct effects of climate change on fire regimes of boreal forests at the long term.Synthesis and applications. Vegetation change will mediate direct effects of climate change on fire regimes of boreal forests at the long term. This finding suggested that policymakers may consider adaptive management by planting deciduous species to reduce fire occurrence probability and resistant management by reducing competition to promote boreal species under changing climate conditions. [ABSTRACT FROM AUTHOR]

Understanding the influences of climate change and human activities on vegetation change is the foundation for effective ecosystem management. Based on the 250 m MODIS-NDVI data from 2002 to 2020, we employed Theil-Sen Median trend analysis and the Mann-Kendall test to quantify vegetation change in Hunan Province. By combining with meteorological, nighttime light index, land cover and other data, residual analysis and correlation analysis, we examined the impacts of human activities and climate change on vegetation dynamics at both the pixel level and the county level. The results showed that the normalized difference vegetation index (NDVI) in Hunan Province exhibited a spatial pattern of "overall improvement with localized degradation" during 2002-2020. Approximately 64.9% of the study area experienced significant vegetation improvement, mainly occurring in the western and central-southern parts of Hunan Province. 1.4% of the study area experienced significant vegetation degradation, mostly in the newly developed urban areas and the farmland in the Dongting Lake Plain. Human activities and climate change jointly promoted vegetation improvement in 67.9% of the study area. Human activities and climate contributed to 96% and 4% of the NDVI change, respectively. At the county level, human activities contributed to over 80% of the NDVI change in each district or county. The impacts of human activities on vegetation change exhibited significant spatial heterogeneity. Urban expansion led to vegetation degradation in the newly developed areas, while vegetation growth appeared in the old developed urban areas. The ecological restoration projects promoted vegetation restoration in the western part of Hunan Province. This study could help us better understand the spatiotemporal variations of vegetation and their responses to climate change and human activities, which would offer scientific basis for effective ecological restoration policy.

Question: The impact of ants on the vegetation and soil seed bank of alpine meadows on the Qinghai‐Tibetan Plateau is largely unknown. We questioned how the mound‐building ant, Camponotus herculeanus, affects the above‐ground vegetation, the soil seed bank and physico‐chemical properties of the soil. Location: An alpine meadow in the northeast margin of the Qinghai‐Tibetan Plateau (37°40′ N, 102°32′ E), China. Methods: We used field and greenhouse studies to determine the above‐ground vegetation parameters and soil physico‐chemical properties, and the soil seed bank composition under the mound (UM), the herbage circle at about 10 cm width around the outside of the mound (mound edge, ME) and the area 1 m from the center of the mound (control). Results: (a) The mound edge had higher vegetation height, greater above‐ground biomass, lower vegetation coverage and lower plant richness than controls; (b) Gramineae had a higher total importance value, which was based on the height, coverage and biomass of each plant species, and composed a higher biomass proportion in the mound edge than in controls (68% vs. 38%), while most of the perennial dicotyledons were restricted to the controls; (c) dicotyledons were the main seed group in the 0–8 cm layer of soilUM (43%), soilME (51%) and soilcontrol (60%), while Gramineae had a significantly higher seed density and percentage of total seeds in the soilUM (16,507 ± 2,882.7 seeds/m3, 28.1%) than in the soilcontrol (4,200 ± 799.5 seeds/m3, 10.2%); and (d) soil in the 0–8 cm layer under the mound had lower water content and lower bulk density than soil on the mound edge and in controls. Conclusions: Mound‐building activity of Camponotus herculeanus increased the proportion of Gramineae and decreased the proportion of dicotyledons at the site of the study indicating, that mound building could enhance the transformation of a grass and sedges community to mainly a grass community in the alpine meadow. [ABSTRACT FROM AUTHOR]

• Ten indicators assessed the ecological health of the Taitema Lake wetland. • The result witnessed a 15.6-fold area increase and a twentyfold vegetation increase. • The wetland health has improved since 2000 but achieved a Good status in 2021. • Wetness increase and water body expansions promote the wetland recovery. The Taitema Lake wetland in the lower reaches of the Tarim River (northwest China) is sensitive to hydrological changes and provides necessary ecosystem functions for biodiversity conservation. Monitoring and evaluating the long-term dynamics of the Taitema Lake wetland is essential for conserving and restoring regional wetland ecosystems. This paper used a dense time series of Landsat images from 1986 to 2021 to map the Taitema Lake wetlands. It analyzed the annual and seasonal variations of the wetlands by ten ecological indicators, which include area extent, vegetation, hydrology, and landscape features. A systematic assessment of the ecological quality of the wetlands over the past 36 years, along with their influencing factors, was conducted from the perspective of wetland health. The results showed that (1) the recovered water areas and the wetlands showed a clear trend of ecological restoration since 2000, accompanied by an increased fragmentation. The total wetland area increased from 69.95 km2 in 1986 to 1164.47 km2 in 2021, with a 15.6-fold increase, and the vegetation area increased twentyfold to 639.84 km2. (2) The wetness in the core zone increased consistently across seasons, coupled with a simultaneous vegetation expansion surrounding the core zone. The areas with increasing wetness levels account for 48 % during winter and spring, and the areas with vegetation expansion account for 81 % and 72 % in summer and autumn, respectively. (3) The wetland ecological health status recovered to a "Good" level in 2021 and has not reached the "Excellent" status. The expansion of the water body is the primary driver behind the promotion of wetland ecological recovery. Small water bodies within the area range of 0.05 to 0.1 km2 notably exhibited the most stimulating effects on the wetlands. Thus, increasing the count of smaller water bodies helps rehabilitate vegetation growth and mitigating the water supply's stress to sustain large lacustrine bodies. [ABSTRACT FROM AUTHOR]

Afforestation‐induced changes in water resources have attracted worldwide attention. However, a clear picture of quantitative attribution of terrestrial water storage (TWS) variation from hydroclimatic and anthropogenic factors is still lacking. In this study, a quantitative analysis of TWS variation was conducted in the Yellow River basin of China under the Grain for Green project with consideration of irrigation. The results showed that the TWS has decreased (increased) more and more quickly (slowly) in the Loess Plateau (headwater region). The TWS increase corresponded to increased runoff and soil moisture in the headwaters, and the TWS depletion corresponded to decreased runoff and groundwater in the Loess Plateau and downstream regions. Regarding the TWS change (TWSC), it exhibited a negative trend across the basin. The increase in evapotranspiration (ET) dominated the basin‐averaged TWSC reduction, while the increase in ET was highly related to the increases in vegetation cover and irrigation water use. For spatial TWSC variations, the value of precipitation minus ET could account for most changes in TWSC, except for those in the headwater region and a region near the internally drained area. The increased vegetation coverage, which can affect multiple hydrological processes, played an important role in these two excluded regions. Importantly, the irrigation‐induced TWSC was considerable and varied with different irrigation water sources (i.e., surface water and groundwater). Overall, the impacts of afforestation and irrigation on TWS are sufficiently important. The research in this study can provide guidance for the water resource management during revegetation efforts. Key Points: A quantitative attribution of terrestrial water storage variation was conducted under the Grain for Green project and intensive irrigationIn regions where P and ET could not explain the terrestrial water storage change, the contribution of afforestation was importantIrrigation‐induced terrestrial water storage change was considerable and varied with different irrigation water sources [ABSTRACT FROM AUTHOR]

[Display omitted] • Annual streamflow sensitivities to climate variability and vegetation change are compared. • Annual streamflow is more sensitive to vegetation change than to climate variability in most watersheds. • Annual streamflow sensitivities vary among climate gradients. • Watershed properties considerably affect annual streamflow sensitivities to vegetation change and climate variability. Extensive studies have revealed the impacts of climate variability and vegetation change on annual streamflow. However, the response intensity of annual streamflow varies among watersheds owing to differences in climate and watershed properties, which have rarely been assessed, especially for streamflow sensitivity to forest change. This calls for studies to evaluate annual streamflow sensitivity, defined as the annual streamflow response intensity (%) per unit of external change (%), to better interpret variations in annual streamflow responses among watersheds as well as their associated driving mechanisms. In this study, we estimated and compared annual streamflow sensitivities to vegetation change (S v) and climate variability (S c) by applying a five-step framework in 14 large watersheds in China and disentangled the contributions of their associated key drivers. We found that S v was significantly greater than S c , suggesting that annual streamflow was more sensitive to vegetation change than to climate variability in 11 watersheds. Alpine watersheds have the lowest S v because of water plays a minor supportive role in vegetation growth under low effective precipitation and leaf area index, whereas higher topsoil salinity, which largely promotes water movement, contributes to a high S v in temperate watersheds. Temperate watersheds also have a large S c because their climate is dry and the resilience of their topography to climate variability is low. The relative contributions of the associated key drivers showed that S v was determined by topography (36.35%), soil (33.68%), landscape patterns (12.22%), vegetation background (9.26%), and climatic conditions (8.49%). In contrast, S c was mostly controlled by topography (54.39%) and climatic conditions (33.08%), followed by vegetation background (12.53%). This study highlights that the management paradigm for maintaining sustainable water resources should focus on both climate and vegetation changes considering the differences in watershed properties in a changing environment. [ABSTRACT FROM AUTHOR]

• Ten factors were chosen for assessing the risk of vegetation change. • The random forest model was employed to invert above-ground biomass. • The Mann-Kendall method was utilized to compute above-ground biomass trends, indicating vegetation degradation. • Bayesian Network enhanced the reliability and efficiency of vegetation change risk assessment. • The spatial and temporal distribution and trend of vegetation change risk in Xilin Gol League were analyzed. As an essential ecological barrier in the north of China, the grassland degradation situation in the Xilin Gol League of Inner Mongolia has remained severe in recent years. Based on data spanning from 2010 to 2022, this study utilizes a set of ten indicators, encompassing altitude, temperature, precipitation, wind speed, FVC, LAI, FRAR, NPP, ET, and above-ground biomass, to construct a Bayesian model for assessing ecological risks associated with vegetation change in the Xilin Gol League. In the case of the most crucial parameter, above-ground biomass, we integrate spectral bands, vegetation indices, and ground-truth data, employing the Random Forest algorithm to estimate the above-ground biomass in the Xilin Gol League. The study further applies the Mann-Kendall trend test and Sen's slope estimation to analyze changes in this parameter and employs it as an indicator for assessing grassland degradation. The results showed that (1) Overall, the risk level decreases gradually from the west to the east and aligns with the grassland types of the Xilin Gol League. (2) In terms of spatial and temporal distribution, medium and high-risk areas are primarily located in the western region of the Xilin Gol League, showing a distinct westward shift from 2010 to 2022. (3) Areas with higher grassland degradation risk are characterized by lower altitudes, higher temperatures, less precipitation, lower vegetation coverage, and reduced potential evapotranspiration. (4) Under the pressures of both climate warming and vegetation change, there has been a significant shift in grassland degradation risk levels in the Xilin Gol League. The application of the Bayesian model effectively reveals intricate causal relationships among various variables, such as climate, terrain, and vegetation dynamics. This study could provide guidance for the prevention and control of grassland degradation in the Xilin Gol League. [ABSTRACT FROM AUTHOR]

Holocene vegetation change is a complex process driven by climate and human activity, distinguishing their relative contributions is important to understand and adapt to the changing planet. Southeast China has a long history of human occupation and the evergreen broadleaved forests of the region have been strongly affected by human activity and replaced widely by anthropogenic vegetation in the last millennium. Pines exist both in natural and anthropogenic vegetation, therefore the interrelationship between pine and other species offers a means of differentiating natural from anthropogenic vegetation changes. Both climate and population in southeast China have undergone substantial change during the late Holocene, but the response of vegetation at centennial scale has not been fully resolved. In this study, we present a palynological analysis of a sediment core obtained from a high-elevation wetland on the Huangshan Mountain, which is known for its remarkably steep topography. The core provides evidence of vegetation history since the onset of the Little Ice Age. Results show that Huangshan vegetation shifted from montane mixed forest to upper montane grassland at the beginning of the Little Ice Age and that, although forest recovery thereafter was gradual, the coexistence of forest and grassland has been maintained since 1800 CE. Climate is shown to be the main driver of Huangshan vegetation change over the last six centuries as a whole, although the expansion of pines into broadleaved forests under the pressure of population growth, commonly reported at other sites in southeast China, is also observed in the Huangshan record from 1800 CE onward. Nevertheless, vegetation on the mountain appears to have been less impacted by human activity than in other parts of the region, possibly as result of the unique topography of Huangshan that restricts its accessibility. In conclusion, the study reveals climate still played an important role in driving last-millennium vegetation change. • Population growth over last six centuries created favorable conditions for pines to invade into broadleaved forests. • Climate was the main driver of the 600-year vegetation change at Huangshan. • Topography plays an important role in postponing human impact on vegetation. [ABSTRACT FROM AUTHOR]

Vegetation is an essential component of terrestrial ecosystems, influenced by climate change and human activities. Quantifying the relative contributions of climate change and human activities to vegetation dynamics is crucial for addressing global climate change. Sichuan Province is one of the essential ecological functional areas in the upper reaches of the Yangtze River, and its vegetation change is of great significance to the environmental function and ecological security of the Yangtze River Basin and southwest China. In this paper, the modified Carnegie-Ames-Stanford Approach(CASA) model was used to estimate the monthly NPP (Net Primary Productivity) of vegetation in Sichuan Province from 2000 to 2018, and the univariate linear regression analysis was used to analyze the temporal and spatial variation of vegetation NPP in Sichuan Province from 2000 to 2018. In addition, taking vegetation NPP as an index, Pearson correlation analysis, partial correlation analysis, and second-order partial correlation analysis were carried out to quantitatively analyze the contribution of climate change and human activities to vegetation NPP. Finally, the Hurst index and nonparametric Man-Kendall significance test were used to predict the future change trend of vegetation NPP in Sichuan Province. The results show that (1) from 2000 to 2018, the NPP of vegetation in Sichuan Province has a significant increasing trend (Slope = 6.09gC·m -2 ·a -1 ), with a multi-year average of 438.72 gC·m -2 ·a -1 , showing a trend of low in the east and high in the middle. The response of vegetation NPP to altitude is different at different elevations; (2) the contribution rates of climate change and human activities to vegetation NPP change are 4.12gC·m -2 ·a -1 and 1.97gC·m -2 ·a -1 , respectively. In contrast, the impact of human activities on NPP is more significant than climate change. Human activities are the main factors affecting vegetation restoration and degradation in Sichuan Province. However, the positive contribution to NPP change is less than climate change; (3) the future vegetation NPP change trend in Sichuan Province is mainly rising, and the same direction change trend is much larger than the reverse change trend. The areas with an increasing trend in the future account for 89.187% of the total area. This research helps understand the impact of climate change and human activities on vegetation change in Sichuan Province. It offers scientific bases for vegetation restoration and ecosystem management in Sichuan and the surrounding areas., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The Huaihe River Basin is located in-between the north-south climate transitional zone in China and is China's important congested area and production base. The land-use of the environment was occupied by the land-use for social and economics. This paper aims to have a comprehensive understanding about land-use and vegetation evolution of the basin over the past 30 years. In view of 5 years (1985, 1990, 2000, 2005, and 2014) land-use data and remote sensing data about NDVI, land-use dynamic degree, and land-use transfer matrix were used to analyze the dynamics of land use. Spatial overlay was used to study vegetation change characteristics of the basin. The present study investigates the evolution trend of vegetation coverage based on spatial overlay analysis. We found that water bodies and urban lands of the basin increased during 1985-2014. On the other hand, the area of artificial vegetation, natural vegetation, and wetland were reduced. The impact was gradually increased by human intervention on various land use types. Overall vegetation coverage level shows deteriorative development, and distribution areas were discrete. The excellent vegetation coverage of natural vegetation and wetland didn't have obvious changes, but the high coverage significantly decreased. Taken as a whole, the natural vegetation coverage was reduced. The vegetation coverage level of artificial water in the land-use for social and economics had greatly increased, but the overall trend of vegetation coverage level of artificial vegetation and resident construction land showed a decreasing trend. [ABSTRACT FROM AUTHOR]

• The impact of vegetation type change on ESs was explored. • Restoration of forest land had the most significant improvement in ESs. • Vegetation area restoration did not enhance all ESs. • A new method to identify vegetation damage was discussed. Vegetation change has a non-negligible role in the impact of ecosystem services (ESs). Quantitative assessment of vegetation ecosystem services is the basis for sustainable regional development. Using the Chinese Loess Plateau (LP) as the study area, this study firstly analysed the spatial and temporal characteristics of vegetation change and used a Geodetector model to reveal the driving mechanism. Next, this study applied the InVEST model to quantitatively assess the four services of carbon storage, habitat quality, soil conservation and water yield, and explored the vegetation ecosystem service balance through vegetation type transfer. The results showed that (1) there was a trend towards an increase in the area of all vegetation types, with sparse vegetation being the most pronounced. Areas of damaged vegetation were concentrated in urban and peripheral areas, as well as wasteland and bare ground. (2) Annual precipitation, soil types and cumulative afforestation area ratio were the main drivers of vegetation change on the LP. (3) Restoration of woodland enhanced carbon storage, habitat quality and soil retention services for vegetation on the LP, while water yield decreased by 31.66%. The restoration of vegetation area did not enhance all ecosystem services. This study may provide a reference and basis for the sustainable management of regional ecosystems. [ABSTRACT FROM AUTHOR]

• The urbanization level need specific attention in ecologically fragile regions. • The urbanization level and vegetation index experienced an obvious increase trend. • Vegetation decreased before 2011 but increased in the urban area. • Vegetation decreased along with increasing urbanization development intensity. Rapid urbanization significantly affects vegetation growth in urban environments. Responses of vegetation to urbanization at high spatial resolutions and long temporal ranges are still unclear, especially in ecologically fragile areas. Here, we explored urbanization impacts on vegetation across China's Loess Plateau (CLP) from 2000 to 2020 at a spatial resolution of 30 m. Urbanization and annual maximum Normalized Difference Vegetation Index (NDVI) in urban agglomerations, provincial capital cities, also the whole CLP experienced a rapid increase over this period; the annual maximum NDVI (NDVI max) in urban areas decreased before 2011 but increased afterward to reach its maximum value in 2018, and in non-urban areas, a significant increase was found between 2000 and 2020. NDVI max with significant reduction areas were mostly distributed in the urbanization area. A total of 97.56%, 53.66%, 80.49%, and 100% of all cities' urban core, urbanization, urban, and non-urban areas, respectively, indicated an increase in NDVI max during 2000–2020. For 97.56% (40/41) of the cities in the CLP, the increases in NDVI max in the non-urban areas were stronger than the NDVI max increases detected in the urban areas of these cities. In general, the urban areas of most cities (29/41) in the CLP had positive NDVI trends of greater than 50%. The NDVI max generally decreased with increasing urbanization development intensity (UDI) in 2000 and 2020 in the CLP along with five urban agglomerations. These findings have important implications for understanding urbanization impacts on vegetation, urbanization management, and development in ecologically fragile areas. [ABSTRACT FROM AUTHOR]

[Display omitted] • Vegetation change dominated by inter-annual variation and long-term trend. • Variation increases with increasing relief, decreases with increasing timescale. • Vegetation change is positive for maximum, negative for minimum temperature. • Maximum temperature mainly controls inter-annual vegetation variation. Despite numerous studies on the response of vegetation change to climate variation, they have mainly been based on annual mean temperature and annual mean precipitation, and have failed to reveal the impact of climate on the inter-annual variation of vegetation in different geomorphic zones based on non-linear methods and considering daily low and high temperature. In this study, the effect of climate variation on the inter-annual variation of vegetation in different geomorphic zones along the area of t the Yangtze River Basin, China from 1982 to 2015 is revealed using Ensemble Empirical Mode Decomposition method. The results show that the inter-annual variation of vegetation is frequently fluctuating, mainly on a short time scale (3-year time scale), and its contribution gradually increases from 62.35% to 73.57% with increasing relief (from plain to high undulating mountain). The vegetation change of more than 75% of the areas is dominated by inter-annual variations, moreover, the vegetation change of the low relief areas is dominated by the 3-year timescale along with the long-term trend, while that of the other geomorphic zones is dominated by the 3-year timescale only. Inter-annual vegetation variation is positively related to precipitation and maximum temperature, but negatively related to mean temperature and minimum temperature in most areas, with area percentages of 67.20%, 86.55%, 65.38% and 75.02%. Inter-annual variation is mainly controlled by maximum temperature in most areas (54.77%). These results will deepen our understanding of the vegetation-climate relationship, suggesting that the responses of inter-annual variation in vegetation to climate vary not only on different time scales, but also in indifferent geomorphic zones. [ABSTRACT FROM AUTHOR]

Secondary forests account for a large amount of subtropical forest due to persistent anthropogenic disturbance in China. The interaction between vegetation and soil during recovery process is rather complex and dependent on forest conditions. Understanding how vegetation and soil properties changes and how their relationship develops in secondary forests is key to effective forest restoration and management. Here we explored the patterns of vegetation and soil properties as well as their correlations during forest recovery process in a subtropical forest in south China. Plots of three forest types, i.e., broadleaf-conifer mixed forest, broadleaved forest and old growth stand, were established to represent the recovery stages. The results showed that diversity patterns in the tree, shrub and herb layers were different: in the tree layer the species diversity peaked at the intermediate stage, while in the understory layers it decreased chronologically. Most of the soil factors showed an increasing trend, and different effects of soil factors were found for the three layers as well as for the two spatial scales. Together, our results suggested that vegetation and soil might be interdependent during the recovery course. Further studies are needed on exploring how vegetation interplays with soil at different scales and how nutrient limitations affects the vegetation development in a chronosequence. [ABSTRACT FROM AUTHOR]

Attributing vegetation changes can provide fundamental information for environmental resources management, especially for those regions with vulnerable ecosystems. The vegetation on China’s Loess Plateau has been reported to be greatly changed especially due to the Grain for Green Program launched in 1999; however, its attribution has rarely been quantitatively investigated. This study analyzed the temporal changes in vegetation coverage in terms of Normal Difference Vegetation Index (NDVI) over 1982–2015, introduced topographical factors to interpret the spatial patterns of vegetation, and quantified the contributions of human activities to vegetation changes. Vegetation greening trend exhibits in the southeast part, and the greening rates over 2000–2015 are greater than those for 1982–1999. The overall spatial pattern does not change much; however, the low-value NDVI is moving to higher elevations while the high-value NDVI to lower elevations, and most types of NDVI to smaller slopes. Climate variability and human activities both contribute to vegetation change, among which human activities account for 55% of vegetation changes over 2000–2015 for the whole study area. [ABSTRACT FROM AUTHOR]

• Regional-scale water storage capacity (S) of four city clusters in China was estimated based on a four-source evapotranspiration (ET) model and a method for inferring S using daily ET recession. • The relative contribution of LAI to the spatial pattern of regional S in the four city clusters ranged from 11.59% to 27.56%, with an average of 19.68%. • The increase in vegetation dominated the change in urban Eb (soil evaporation) more than non-urban Eb. • Urban areas in Beijing–Tianjin–Hebei, the Yangtze River Delta, Pearl River Delta, and Chengdu–Chongqing would need to increase existing vegetation by 10%, 32%, 32%, and 28%, respectively, to store additional precipitation (above the mean annual precipitation) in high-precipitation years. Increasing the effective urban water storage capacity is one of a range of solutions to mitigate heat issues and flooding in urban areas and vegetation plays an important role in it. In this study, the regional-scale water storage capacity of four city clusters in China during the period 2009–2018 was estimated based on a four-source evapotranspiration (ET) model incorporated with urban water storage capacity (S) estimated on the basis of daily ET recession. Our results showed that simulated ET was consistent with four flux towers (R2 = 0.57, RMSE = 1.45 mm/d). The spatial distribution of S was similar to that of ET , and ranged from 2 to 28 mm. The influence of environmental drivers on the spatial pattern of S was explored using a machine learning technique, and the relative contribution of LAI (leaf area index) to the spatial pattern of S ranged from 11.59% to 27.56%. The effect of vegetation change on S in urban and non-urban areas showed an opposite relationship to the LAI change. However, the effect on S in urban and non-urban areas was reversed when vegetation was expanded to 1.25 times the existing mean, owing to the increase in vegetation dominating the change in urban Eb (soil evaporation) to a greater degree than for non-urban Eb. Urban areas in Beijing–Tianjin–Hebei, the Yangtze River Delta, Pearl River Delta, and Chengdu–Chongqing would need to increase existing vegetation by 10%, 32%, 32%, and 28%, respectively, to store additional precipitation (above the mean annual precipitation) in high-precipitation years. This study provides a new mechanistic understanding of the effects of vegetation change on water consumption in urban ecosystems, allowing the role of urban ecological planning in urban flood mitigation to be quantified. [ABSTRACT FROM AUTHOR]

Anthropogenic impacts on weathering processes in the late Holocene have been widely demonstrated in recent studies, but the mechanism by which enhanced chemical weathering is linked to human activity remains unclear. In this study, we present a comprehensive reconstruction of sediment provenance, chemical weathering, vegetation type and evidence of human activity in core ZK20 in the estuary of the Pearl River during the last 7 ka to investigate the interactions of weathering, climate, and human activity. Evidence from major elements and clay minerals indicates an abrupt increase in chemical weathering intensity since ∼3.0 cal ka BP. This result cannot be explained by changes in provenance, climate or other natural factors but agrees well with the stronger human activity, confirming the significance of anthropogenic impacts on silicate weathering. The nearly synchronous increase in C4 plant abundance since 3.0 ka BP, as reflected by the sediment records from the upper reach and river mouth of the Pearl River, implies that the intensified weathering signal was mainly derived from contemporaneous minerals alteration (less than millennium timescale) rather than reworked old soils. We propose that the varied weathering conditions in response to agricultural activity and vegetation change intensified the alteration degree of minerals. The farming-induced biogeochemical effects, such as the releasing of acids, regulation of hydrology and uptake of cations, played a significant role in intensifying chemical weathering. This study highlights the importance of farming-related biogeochemical effects, which have been largely neglected in previous studies, in the process of chemical weathering. • We present high-resolution Holocene records of weathering, vegetation and human activity at the Pearl River Basin. • Increasing anthropogenic impact on chemical weathering in the Pearl River Basin occurred since ∼3.0 ka BP. • Farming-related biogeochemical effects might intensify chemical weathering since the late Holocene. [ABSTRACT FROM AUTHOR]

To explore the responses of vegetation growth to change in terrestrial water storage in Southwest China, we analyzed the change trend and relationship between vegetation and terrestrial water storage anomaly (TWSA) in Southwest China from January 2003 to December 2021 by using TWSA data of Gravity Recovery and Climate Experi-ment (GRACE) satellite and normalized differential vegetation index (NDVI) data. The results showed that NDVI in Southwest China during the study period showed an overall upward trend. Meanwhile, TWSA showed a significant downward trend in central and southern Tibet, and a significant upward trend in northwest Tibet and southeast region of Southwest China. Results of Pearson correlation analysis showed that there were significant spatial differences in responses of NDVI to TWSA changes in Southwest China. NDVI had a significant negative response to TWSA changes in most regions of Tibet, but a significant positive response to TWSA changes in most regions of southeast region of Southwest China. Such differences were driven by climate change and topography.

Desertification is a serious environmental problem in north China that should be urgently addressed and prevented. Identifying the causes of vegetation trends that are closely related to desertification is prerequisite for a better control of desertification processes. In this study, the Xiliao River basin, a typical desertified watershed in northeast China, was selected as a case study. To partition the vegetation trends into climate-induced and human-induced trends, a linear regression model, piecewise regression model and a binary nonlinear regression analysis were employed, based on the long-term remote measures of the Normalized Difference Vegetation Index (NDVI) and climate data. The results showed that the spatial pattern of the vegetation trends in the basin was highly heterogonous, although the climatic factors varied similarly. In the north, where natural vegetation dominates, the vegetation exhibited significant browning (−0.0015 year−1), and a significant changing point was observed in 2000. In the south, where cropland dominates, the vegetation exhibited significant greening (0.002 year−1). Approximately 82.7% of the area with a decreasing NDVI was attributed to climate variability. The main reason for the vegetation degradation was because of a multiyear reduction in precipitation from 1999 to 2011 rather than from an increase in the grazing size. Approximately 67.0% of the area with an increasing NDVI could be attributed to irrigation, which overexploited a large amount of water resources, even though significantly increasing air temperatures can promote vegetation greenness. Our findings have important management implications for grazing and agriculture in the context of controlling desertification and sustaining environment. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Vegetation change reflects sensitive responses of ecosystem environment to global climate change as well as land use. It is well known that land use type and its transformation affect vegetation change. However, how the changes in land use intensity (LUI) within different land use types impact vegetation and the interactions with other drivers remain poorly understood. We measured the LUI of Jiangsu Province, China, within the main land use types in 1995, 2000, 2005, 2010, 2015 and 2018 by combining remote sensing-based land use data with representative county scale economic and social indicators. Structural equation models (SEMs) were built to quantify the influences of long term LUI on vegetation change interacting with economic development, climate change and topographical conditions in transformed land, cropland, rural settlements and urbanized land, respectively. Seventy percent of significant vegetation change existed in non-transformed land use types. Although the area with a vegetation greening trend is larger than that with a vegetation browning trend, the vegetation browning areas is prominent in urbanized lands and some croplands in south basins. The constructed SEMs suggested the dominant negative effect of fast economic development regardless of land use types, while LUI played important and different direct and indirect effects on affecting vegetation change significantly interacting with economic development and climate change in different land use types. The LUI increasing led a vegetation greening in cropland, and stronger than climate warming with both positive direct and indirect effects for influencing climate change. The LUI change took negative effects on vegetation change in rural and urban areas, while a positive indirect effect of LUI increasing in urbanized land signaled the positive results of human managements. We then provided some land use-specific suggestions on basin scale for land management in Jiangsu. Our results highlight the necessity of long-term LUI quantification and promote the understanding of its effects on vegetation change interacted with other drivers within different land use types. This can be very helpful for sustainable land use and managements in regions with fast economic development. • Seventy percent of significant vegetation change was without land use type change. • The interactive effects among drivers were examined by structural equation model. • Land use intensity (LUI) explains vegetation change better than climate in cropland. • Climate has larger effects on vegetation change than LUI both in urban and rural. • Diverse effects of dynamic LUI urge the sustainable land-specific management. [ABSTRACT FROM AUTHOR]

Understanding the changes in hydrological process is a key subject for water resource management of a high-diversity watershed. In this paper, through an establishment of a SWAT-based model, the effects of climate change and its induced vegetation change on hydrological process were analyzed in the East River Basin. The model could well simulate the hydrological processes of the basin including surface runoff (SURQ), groundwater (GWQ), lateral flow (LATQ), total water yield (WYLD), actual evapotranspiration (ET), and groundwater recharge (PERC). Under the vegetation change induced by temperature increase, the effects of the vegetation change on hydrological process were larger than that of the temperature change. Under the vegetation change caused by the increase of temperature and precipitation, the vegetation change enhanced the effects of climate change on annual SURQ, LATQ, GWQ, WYLD, and PERC of the basin. Under spatial scale, when the temperature and precipitation changed simultaneously, the increase of precipitation could promote the increase of annual ET in sub-watersheds. Also, the annual SURQ, WYLD, GWQ and ET in western sub-watersheds were more sensitive to the cumulative changes of vegetation and climate. This work can provide useful information to decision makers in water resource management of watersheds. • A SWAT-based model was established for a multi-level simulation. • Response of hydrological process to a climate-driven vegetation change was explored. • Effect of climate and vegetation changes on hydrological process was quantified. [ABSTRACT FROM AUTHOR]

Volatiles erupted from large-scale explosive volcanic activities have a significant impact on climate and environmental changes. As an important ecological factor, the occurrence of fire is affected by vegetation cover, and fire can feed back into both vegetation and climatic change. The causes of fire events are diverse; and can include volcanic eruptions. The amount of charcoal in sediment sequences is related to the frequency and intensity of fire, and hence under good preservation conditions fire history can be reconstructed from fossil charcoal abundance. Until now, little research on the role of fire has been carried out in northeastern China. In this study, through research on charcoal and tephra shards from Gushantun and Hanlongwan, Holocene vegetation change in relation to fire and volcanic events in Jilin, Northeastern China, was investigated. Where tephra shards are present in Gushantun it is associated with low level of both conifers and broadleaved trees, and is also associated with a pronounced charcoal peak. This suggests forest cover was greatly reduced from a fire caused by an eruption of the Tianchi volcano. We also detected one tephra layer in Hanlongwan, which also has the almost same depth with low level forest pollen values and one charcoal peak. This was caused probably by an eruption of the Jinlongdingzi volcano. [ABSTRACT FROM AUTHOR]

Vegetation is essential for ecosystem function and sustainable urban development. In the context of urbanization, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), as the typical urban-dominated region, has experienced a remarkable increase in social and economic activities. Their impact on vegetation is of great significance but unclear, as interannual flow data and linear methods have limitations. Therefore, in this study, we used human and vehicle flow data to build and simulate the indices of mobile human activity. In addition, we used partial least squares regression (PLSR), random forest (RF), and geographical detector (GD) models to analyze the impact of mobile human activities on vegetation change. The results showed that indices of mobile human and vehicle flow increased by 1.43 and 7.68 times from 2000 to 2019 in the GBA, respectively. Simultaneously, vegetation increased by approximately 64%, whereas vegetation decreased mainly in the urban areas of the GBA. Vegetation change had no significant linear correlation with mobile human activities, exhibiting a regression coefficient below 0.1 and a weight of coefficients of PLSR less than 40 between vegetation change and all the factors of human activities. However, a more significant nonlinear relationship between vegetation change and driving factors were obtained. In the RF regression model, vegetation decrease was significantly affected by mobile human activity of vehicle flow, with an importance score of 108.11. From the GD method, vegetation decrease was found to mainly interact with indices of mobile human and vehicle inflow, and the highest interaction force was 0.82. These results may support the attainment of sustainable social-ecological systems and global environmental change.

Fossil pollen records from 45 sites across China were evaluated and synthesized to document vegetation and climate change during Marine Isotope Stage 3 (MIS 3) at 60-27 ka and to understand the large-scale controls. During MIS3, vegetation type was dominantly forest in eastern China, forest steppe/meadow in the north and Tibetan Plateau, and steppe desert in northwestern arid China. We developed a semi-quantitative vegetation index to reflect change in plant abundance (by inferring the general climate conditions), with a vegetation score from 1 to 3 based on the different vegetation types inferred from pollen data at individual sites at intervals of 2,000 years. The reconstructed vegetation index shows higher values during MIS 3, especially during the period 53-40 ka, than at the Last Glacial Maximum. Our results also suggest that climate on the basis of vegetation change was cooler and drier during MIS 3 than during the Holocene optimum; however, MIS 3 vegetation was probably similar to modern vegetation. The close relationship between vegetation change, insolation and Asian summer monsoon strength suggests that climate variations, probably in both temperature and precipitation, are the primary drivers of regional vegetation change. Additional well-dated, high-resolution palaeoclimate records from many locations across China will be needed to understand the vegetation change and climate forcings on millennial and centennial scales within MIS 3. [ABSTRACT FROM AUTHOR]