Quantifying the contributions of human activities and climate change to vegetation net primary productivity dynamics in China from 2001 to 2016

Vegetation change mechanism and key driving factors in complex terrains, China

Under global climate change, vegetation dynamics in complex terrains exhibit distinct response patterns to altered hydrological cycles, but the response mechanism and the driving factors are unclear in complex terrains. As most previous studies have underlying surface conditions simple, it is difficult to understand the mechanism in complex terrains. Therefore, this study taking the water conservation area of the Yellow River in China with complex terrains as an example, comprehensively integrated time-series analysis, wavelet transforms, and grey correlation modeling to decode vegetation change mechanisms. Further analyzes are made to explore the temporal trends and spatial patterns of the key driving factors. Our multi-method approach reveals that temperature and soil water content are the key factors driving the spatial and temporal vegetation change with temperature ranking the first. Climate change affected the changes of temperature and soil water content in the basin, resulting in the abrupt change of vegetation coverage in 2000-2005. Vegetation coverage fluctuated downward before 2000 then surged after 2000, aligning with soil water content increases and sustained temperature rises till 2020. Sub-watershed analyses identified consistent 6-7a precipitation cycles but temperature and soil water content are stable. We found that environmental policies and GDP growth emerged as key anthropogenic amplifiers, enhancing vegetation resilience through synergistic effects with climatic factors. These methodologies and findings provide scientific support for the ecological restoration of the Yellow River Basin and offer global implications for similar complex terrains, particularly in developing climate-adaptive vegetation restoration strategies.

Spatiotemporal changes of vegetation in the northern foothills of Qinling Mountains based on kNDVI considering climate time-lag effects and human activities

Vegetation is fundamental to regulating the climate system and ensuring carbon balance. Recognizing the effects of climate change (CC) and human activities (HA) is vital for understanding shifts in vegetation. However, climate time-lag effects are rarely measured, resulting in an inadequate assessment of CC's effects on vegetation dynamics. In this study, firstly, based on the Landsat image dataset, the spatiotemporal variations of the kernel Normalized Difference Vegetation Index (kNDVI) in the northern foothills of the Qinling Mountains (NQLM) from 1986 to 2022 were analyzed. Then, the multiple regression residuals method, accounting for time-lag effects, was employed to determine the effects of CC and HA on kNDVI change. Finally, six patterns of kNDVI change were obtained based on the kNDVI trend and the changes of CC and HA to kNDVI. Our research found: (1) Over the past 37 years, the vegetation has fluctuated upward at a rate of 0.0061/a, and most areas have experienced significant greening (84.82%) in the NQLM. Only 0.86% of the area has experienced vegetation degradation, and the stability of vegetation has been maintained. (2) The kNDVI exhibited a positive correlation with both precipitation and temperature, kNDVI response to precipitation with 1-month time lag and 0-month for temperature. (3) The contribution of CC to kNDVI change was 84%, temperature and precipitation drive kNDVI change rates with 0.0012/a and 0.0039/a, respectively. The contribution of HA to kNDVI change was only 16%. While the role of HA cannot be overlooked, these findings underscore the critical influence of CC on vegetation changes. (4) Among the six patterns of kNDVI change, CC and HA collectively contributed to kNDVI change, and the effect of CC alone was more significant than that of HA. These findings can help policymakers design more targeted interventions to enhance ecological resilience and support long-term environmental stability, which is critical for the development of informed, sustainable revegetation strategies in the NQLM.

Climate change enhances greening while human activities accelerate degradation in northern China's grasslands

Northern China's grasslands play a pivotal role in livestock production, energy utilization, and ecosystem balance, both domestically and globally. However, they exhibit pronounced temporal variability and marked spatial heterogeneity. Since most existing studies rely on single vegetation indices and regional-scale analyses, they may introduce biases in interpreting grassland dynamics and their underlying drivers. To address this gap, we integrated both functional and structural indices - Gross Primary Productivity (GPP), solar-Induced chlorophyll fluorescence (SIF), Normalized Difference Vegetation Index (NDVI), and Leaf Area Index (LAI) - to systematically investigate spatiotemporal trends across various grassland types in northern China. Using partial derivative analysis, we quantified the relative contributions of climate change and human activities to these observed vegetation trends. Results indicated that over 70 % of grassland areas, especially temperate grasslands, showed an overall increase in vegetation indices, while a decline was observed in the southwestern alpine grasslands. Climate change was the primary driver of grassland greening (56.55 %-63.83 %), primarily through increased precipitation in temperate grasslands and rising temperatures in alpine grasslands. Human activities contributed substantially to greening (36.17 %-43.45 %), especially in desertified temperate grasslands (e.g., Mu Us Sandy Land, Gansu, Ningxia, Xinjiang) and Qinghai alpine meadows, mainly through farmland restoration and desertification control. Conversely, human activities also served as the primary driver of grassland degradation (51.70 %-69.64 %) in certain alpine regions, where overgrazing and population growth - compounded by rising temperatures and declining soil moisture - led to significant vegetation losses. Moreover, 72.66 % of temperate grasslands demonstrated strong coupling between vegetation structure and function, whereas 57.59 % of alpine grasslands exhibited increasing GPP alongside declines in both LAI and SIF. Overall, these findings underscore the spatial heterogeneity of grassland responses to climatic and anthropogenic drivers, highlighting the necessity of employing multiple vegetation indices to guide targeted and effective grassland management strategies.

Forecasting for electricity demand utilizing enhanced inception-V4 using improved Osprey optimization

This research examines the impact of temperature, relative humidity, and wind speed on the electricity demand. It presents a unique method that combines an Enhanced Inception-V4 model with an Improved Osprey Optimizer to analyze weather-related factors. The combined model, which has been validated from 2003 to 2023, surpasses traditional forecasting techniques and significantly improves prediction accuracy. The Enhanced Inception-V4 model's ability to process data allows it to identify key factors that influence electricity demand patterns. Meanwhile, the Modified Osprey Optimizer fine-tunes the model's parameters, ensuring its adaptability to different weather scenarios. The study confirms the reliability of the OOI-Inception-V4 model in forecasting electricity demand and highlights the strong connection between weather conditions and energy usage, especially during extreme weather events. The projected increase in electricity demand from 2024 to 2030 emphasizes the importance of proactive energy policies, infrastructure upgrades, and sustainability initiatives. The research underscores the crucial role of temperature in driving electricity demand, with noticeable variations during winter and summer due to heightened usage of heating and cooling systems. In general, this study emphasizes the significant impact of climate on energy demand and demonstrates the potential of advanced predictive models in enhancing electricity demand forecasting.

Spatiotemporal variations and driving factors of crop productivity in China from 2001 to 2020

Human activities have altered the quantity and distribution of cropland, and climate change profoundly affects crop productivity. However, the spatiotemporal patterns and driving mechanisms of crop productivity remain unclear. Here, we analyze the spatiotemporal evolution of Chinese crop productivity using long-term satellite observation data. We employ the residual trend analysis method to separate the relative contributions of climate change and non-climate factors to crop productivity. Our results indicate the following: (1) from 2001 to 2020, China's crop productivity increased by approximately 0.11 kgCm-2yr-1, which compensated for the decline in crop yields caused by a reduction in cropland area. (2) Crop productivity exhibits significant spatial heterogeneity, with notable differences between the southern and northern regions of China. Both cropland and crop productivity show a northward shift, with the migration distance of the mean center of crop productivity exceeding that of cropland. (3) Agricultural production inputs are closely related to crop productivity, but climate change remains the primary factor influencing changes in Chinese crop productivity. Crop productivity in northern China is more sensitive to climate change, and the dominant factors vary among different agricultural districts. (4) Over the study period, long-term crop cultivation in northern China has benefited the net primary productivity of surface vegetation, though the sustainability of production faces challenges. This study is of great importance for maintaining food security and promoting sustainable agricultural development, offering guidance for cross-regional cropland compensation.

Threshold effects of vegetation cover on production-living-ecological functions coordination in Xiangyang City, China

Clarifying the nonlinear impacts of vegetation cover on production-living-ecological function (PLEF) coordination is essential to ecological restoration regulation and sustainable land use. However, the threshold effect of vegetation cover on PLEF coordination, particularly in major function-oriented zones (MFZs), has yet to receive attention. This study selected Xiangyang City, China, as the case area to identify the impact threshold of vegetation cover on PLEF coordination from the perspectives of the region as a whole and MFZ, respectively. The results showed that the PLEF coordination was high in the center and east while low in the west. For production-ecological function, 51.46% of the area was primarily coordinated and above, while for production-living function, 61.35% of the city area was severely uncoordinated. Vegetation cover was high in the west and low in the east. A negative correlation existed between vegetation cover and PLEF coordination. Urban built-up areas with lower vegetation cover showed higher levels of PLEF coordination, whereas western mountainous regions with higher vegetation cover demonstrated lower levels of PLEF coordination. Furthermore, vegetation cover exhibited a pronounced threshold effect on PLEF coordination, featuring conspicuous regional variations. The identified thresholds of vegetation cover for PLEF coordination in key development, agricultural production, and key ecological function zones were 0.3896, 0.2272, and 0.8161, respectively. Our study provides scientific references for the impact assessment of ecological restoration and the synergistic enhancement of land functions.

Influences of climatic variation and human activities on vegetation photosynthesis dynamics in Southwest China

Photosynthesis is a direct route for carbon sequestration in vegetation, and is influenced by climatic variation (CV) and human activities (HA). Therefore, a quantitative assessment of their influence on vegetation photosynthesis dynamics is pivotal for formulating effective carbon neutrality strategies. Herein, based on the solar-induced chlorophyll fluorescence index (SIF), which reflects the vegetation photosynthesis intensity, and TerraClimate meteorological data, we refined the residual trend approach by incorporating more climatic variables and their time effects on vegetation to assess the influences of CV and HA on SIF dynamics in Southwest China. Our results revealed that an increasing rate of vegetation SIF across Southwest China of 0.0312 Wm-2μm-1sr-1/10a (p < 0.001) from 2000 to 2019, and over 90% of the region exhibited an increase in SIF. The influence of CV on SIF dynamics had time effects, including time-cumulative and time-lag effects. Nevertheless, these effects varied by climatic variables and vegetation types. The variable importance in projection demonstrated that temperature was the primary factor influencing SIF dynamics, followed by precipitation, potential evapotranspiration, downward surface solar radiation, vapor pressure deficit, and wind speed. Furthermore, both CV and HA collectively enhanced the vegetation photosynthesis intensity in the region, HA was the main driver of the SIF increase, contributing 0.0239 Wm-2μm-1sr-1/10a, while CV accounted for 0.0073 Wm-2μm-1sr-1/10a. Overall, we refined the previous residual trend approach and provided a new way for quantitatively assessing the influences of CV and HA on vegetation photosynthetic intensity.

An improved framework for quantifying the contribution of climatic and anthropogenic factors to vegetation dynamics - A case study of China

Accurately quantifying the impact of climatic and anthropogenic factors on vegetation change is critical for developing and evaluating ecological management strategies. However, most presented studies typically ignore the climate temporal effects and assume that all pixels are affected by both climate change (CC) and human activities (HA), which often introduce uncertainties. In this study, Leaf area index (LAI), temperature, precipitation, solar radiation, and land cover data from 1982 to 2020 were used to detect and attribute vegetation dynamics in China. We used partial correlation analysis, generalize linear model, trend analysis, and improved RESTREND to analyze the spatiotemporal variation characteristics of vegetation LAI from 1982 to 2020 and to quantify the effects of CC and HA on vegetation dynamics since the implementation of the Grain for Green Project (GGP). The results indicate that significant vegetation greening appeared in most areas (66.2%) between 2000 and 2020. Both CC and HA have positive effects on vegetation greening. In arid and semi-arid regions, precipitation was the primary driver of vegetation change, while in high-latitude areas of southern and southwestern China, temperature was the primary determinant. After considering the temporal effects, the explanatory power of climate variables for vegetation dynamics increased by 4.0% compared to ignoring the temporal effects, accounting for 72.81%. After dividing the pixels into those affected by CC and those affected by both CC and HA, the contribution of HA was decreased from 31.19% to 25.96%. Although the contribution of HA is lower than that of CC, ecological engineering has effectively promoted vegetation greening. These research findings provide scientific data and theoretical basis for ecological environment protection and natural resource management.

Spatiotemporal variation and GeoDetector analysis of NDVI at the northern foothills of the Yinshan Mountains in Inner Mongolia over the past 40 years

The study of spatiotemporal variation and driving forces of the normalized difference vegetation index (NDVI) is conducive to regional ecosystem protection and natural resource management. Based on the 1982-2022 GIMMS NDVI data and 26 influencing variables, by using the Theil-Sen median slope analysis, Mann-Kendall (M - K) test method and GeoDetector model, we analyzed the spatial and temporal characteristics of vegetation cover and the driving factors of its spatial differentiation in the northern foothills of the Yinshan Mountains in Inner Mongolia. The NDVI showed a significantly increasing trend during 1982-2022, with a growth rate of 0.0091 per decade. It is further predicted that future change in NDVI will continue the 1982-2022 trend, and sustainable improvement will dominate in the future; however, 17.69 % of vegetation will degrade, that is, NDVI will degrade instead of improvement. The spatial distribution of the NDVI in the northern foothills of the study area was generally characterized by high in the east and low in the west. Annual precipitation (Pre), evapotranspiration (Evp), relative humidity (Rhu) and sunshine hours (Ssd) had >70 % explanatory power (73.5, 79.9, 79.0, and 74.9 %, respectively). The explanatory power of edaphic factors was >30 %, whereas anthropogenic and topographic factors had little influence on the spatial variation of NDVI, with an explanatory power of <30 %. Thus, climatic factors were the dominant factors influencing the spatial variability of NDVI in the study area. The results of the interaction detector analysis showed nonlinear strengthening for any two factors, and the interaction between Rhu and barometric pressure had the highest explanatory power. There were optimal ranges or characteristics of each factor that promoted vegetation growth. This study investigated the differences in the explanatory power of different factors on the NDVI and the optimal range of individual factors to promote vegetation growth, which can provide a basis for the development of vegetation resource management programs.

Impact of Natural and Human Factors on Dryland Vegetation in Eurasia from 2003 to 2022

Eurasian dryland ecosystems consist mainly of cropland and grassland, and their changes are driven by both natural factors and human activities. This study utilized the normalized difference vegetation index (NDVI), gross primary productivity (GPP) and solar-induced chlorophyll fluorescence (SIF) to analyze the changing characteristics of vegetation activity in Eurasia over the past two decades. Additionally, we integrated the mean annual temperature (MAT), the mean annual precipitation (MAP), the soil moisture (SM), the vapor pressure deficit (VPD) and the terrestrial water storage (TWS) to analyze natural factors' influence on the vegetation activity from 2003 to 2022. Through partial correlation and residual analysis, we quantitatively described the contributions of both natural and human factors to changes in vegetation activity. The results indicated an overall increasing trend in vegetation activity in Eurasia; the growth rates of vegetation greenness, productivity and photosynthetic capacity were 1.00 × 10-3 yr-1 (p < 0.01), 1.30 g C m-2 yr-2 (p < 0.01) and 1.00 × 10-3 Wm-2μm-1sr-1yr-1 (p < 0.01), respectively. Furthermore, we found that soil moisture was the most important natural factor influencing vegetation activity. Human activities were identified as the main driving factors of vegetation activity in the Eurasian drylands. The relative contributions of human-induced changes to NDVI, GPP and SIF were 52.45%, 55.81% and 74.18%, respectively. These findings can deepen our understanding of the impacts of current natural change and intensified human activities on dryland vegetation coverage change in Eurasia.

Night lights observations significantly improve the explainability of intra-annual vegetation growth globally

Understanding the underlying mechanism of vegetation growth is of great significance to improve our knowledge of how vegetation growth responds to its surrounding environment, thereby benefiting the prediction of future vegetation growth and guiding environmental management. However, human impacts on vegetation growth, especially its intra-annual variability, still represent a knowledge gap. Night Lights (NL) have been demonstrated as an effective indicator to characterize human activities, but little is known about the potential improvement of intra-annual vegetation growth using seasonal NL observations. To address this gap, we investigated and quantified the explainability improvement of intra-annual vegetation growth by establishing a multiple linear regression model for vegetation growth (indicated by Normalized Difference Vegetation Index, NDVI) with human factor (indicated by NL observations here) and three climatic factors, i.e., temperature, water availability, and solar radiation using the Principal Components Regression (PCR) method. Results indicate that NL observations significantly improve our understanding of intra-annual vegetation growth globally. Model explainability, i.e., adjusted R2 metric of the PCR model, was comparatively improved by 54 % on average with a median value of 11 % when taking NL observations into consideration. Such improvement occurred in 82 % of the whole investigation pixels. We found that the improvement of model explanatory power was significant in regions where both NL and NDVI trends were large, except for the case where both of their trends were negative. At the country-level, the improvement of model explanatory power increases as GDP decreases, illustrating a greater improvement in a lower middle-income country than that in a high-income country. Our findings emphasize the importance of considering human activities (indicated by NL here) in vegetation growth, offering novel insights into the explanation of intra-annual vegetation growth.

Vegetation resilience assessment and its climatic driving factors: Evidence from surface coal mines in northern China

Vegetation resilience is a key concept for understanding ecosystem responses to disturbances and is essential for maintaining ecosystem sustainability. However, assessing vegetation resilience remains challenging, especially for areas with significant disturbances and ecological restoration, such as surface coal mine ecosystems. Vegetation resilience assessment requires a combination of disturbance magnitude, recovery magnitude, and recovery time. In this study, we propose a vegetation resilience assessment method by integrating disturbance magnitude, recovery magnitude and recovery time. Forty-six surface coal mines in northern China were analysed as the study areas. A geographical detector model was used to explore the influence of climatic factors on vegetation resilience. The results indicated that the vegetation resilience curves included three shapes, inverted U-shaped, S-shaped, and monotonically decreasing, and the different disturbance-recovery relationships of the curves indicated that natural and social factors jointly changed the ecological restoration process. The vegetation resilience of the 46 surface coal mines varies widely, ranging from 0.87 to 7.22, showing a spatial decreasing trend from east to west. The explanatory power of different climatic factors on vegetation resilience by indirectly affecting hydrothermal conditions varies, with the effect of atmospheric pressure being the most significant and the superposition of the two climatic factors enhancing the effect on vegetation resilience. This study enriches the understanding of vegetation resilience assessment and provides important information to guide the differentiation of ecological restoration and resource development of surface coal mines in different regions.

The impact of extreme precipitation on water use efficiency along vertical vegetation belts in Hengduan Mountain during 2001 and 2020

In the context of climate change, extreme precipitation events are continuously increasing and impact the water‑carbon coupling of ecosystems. The vertical vegetation zonation, as a characteristic of mountain ecosystems, reflects the differences in vegetation response to climate change at different elevations. In this study, we used the water use efficiency (WUE) as an indicator to evaluate the water‑carbon relationship. By using MODIS data, we analyzed the spatiotemporal patterns of gross primary productivity (GPP), evapotranspiration (ET), and WUE from 2001 to 2020, as well as the responses of WUE to extreme wetness factor Number of precipitation days (R0.1), extreme dryness factor Consecutive dry days (CDD), and meteorological factors under the vertical vegetation zonation. Our results showed that annual GPP and ET displayed a significant increasing trend between 2001 and 2020, whereas WUE showed a weak decreasing trend. Spatially, GPP and WUE decreased with increasing elevation. Analyzing the WUE of mountainous ecosystems as a unified whole may not precisely capture the reactions of vegetation to severe rainfall occurrences. In fact, across different vegetation belts in mountainous areas, there exists a negative correlation between WUE and R0.1, and a positive correlation with CDD. In terms of meteorological factors, the temporal variation of GPP was primarily associated with vapor pressure deficit (VPD) and temperature (Ta), while those of ET was mainly related to soil water content (SWC). WUE was affected by a combination of meteorological factors and had a certain degree of variation between different altitude intervals. These findings contribute to a better understanding and prediction of the relationship between extreme rainfall climate and water‑carbon coupling in mountainous areas.

Assessment of vegetation net primary productivity variation and influencing factors in the Beijing-Tianjin-Hebei region

Exploring the spatiotemporal variations of vegetation net primary productivity (NPP) and analyzing the relationships between NPP and its influencing factors are vital for ecological protection in the Beijing-Tianjin-Hebei (BTH) region. In this study, we employed the CASA model in conjunction with spatiotemporal analysis techniques to estimate and analyze the spatiotemporal variations of NPP in BTH and different ecological function sub-regions over the past two decades. Subsequently, we established three scenarios (actual, climate-driven and land cover-driven) to assess the influencing factors and quantify their relative contributions. The results indicated that the overall NPP in BTH exhibited a discernible upward trend from 2000 to 2020, with a growth rate of 3.83 gC·m-2a-1. Furthermore, all six sub-regions exhibited an increase. The Bashang Plateau Ecological Protection Zone (BP) exhibited the highest growth rate (5.03 gC·m-2a-1), while the Low Plains Ecological Restoration Zone (LP) exhibited the lowest (2.07 gC·m-2a-1). Geographically, the stability of NPP exhibited a spatial pattern of gradual increase from west to east. Climate and land cover changes collectively increased NPP by 0.04 TgC·a-1 and 0.07 TgC·a-1, respectively, in the BTH region. Climate factors were found to have the greatest influence on NPP variations, contributing 40.49% across the BTH region. This influence exhibited a decreasing trend from northwest to southeast, with precipitation identified as the most influential climatic factor compared to temperature and solar radiation. Land cover change has profound effects on ecosystems, which is an important factor on NPP. From 2000 to 2020, 15.45% area of the BTH region underwent land cover type change, resulting in a total increase in NPP of 1.33 TgC. The conversion of grass into forest brought about the 0.89 TgC increase in NPP, which is the largest of all change types. In the area where land cover had undergone change, the land cover factor has been found to be the dominant factor influencing variations in NPP, with an average contribution of 49.37%. In contrast, in the south-central area where there has been no change in land cover, the residual factor has been identified as the most influential factor influencing variations in NPP. Our study highlights the important role of land cover change in influencing NPP variations in BTH. It also offers a novel approach to elucidating the influences of diverse factors on NPP, which is crucial for the scientific assessment of vegetation productivity and carbon sequestration capacity.

New Perspective to Evaluate the Carbon Offsetting by Urban Blue-Green Infrastructure: Direct Carbon Sequestration and Indirect Carbon Reduction

Urban blue-green infrastructure (BGI) offers a multitude of ecological advantages to residents, thereby playing a pivotal role in fortifying urban resilience and fostering the development of climate-resilient cities. Nonetheless, current research falls short of a comprehensive analysis of BGI's overall potential for carbon reduction and its indirect carbon reduction impact. To fill this research gap, we utilized the integrated valuation of ecosystem services and trade-offs model and remote sensing estimation algorithm to quantify the direct carbon sequestration and resultant indirect carbon reduction facilitated by the BGI within the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) (China). To identify the regions that made noteworthy contributions to carbon offsets and outliers, spatial autocorrelation analysis was also employed. The findings of this study reveal that in 2019, the BGI within the study area contributed an overall carbon offset of 1.5 × 108 t·C/yr, of which 3.5 × 107 and 11.0 × 107 t·C/yr were the result of direct carbon sequestration and indirect carbon reduction, respectively. The GBA's total CO2 emissions were 1.1 × 108 t in 2019. While the direct carbon sequestration offset 32.0% of carbon emissions, the indirect carbon reduction mitigated 49.9% of potential carbon emissions. These results highlight the critical importance of evaluating BGI's indirect contribution to carbon reduction. The findings of this study provide a valuable reference for shaping management policies that prioritize the protection and restoration of specific areas, thereby facilitating the harmonized development of carbon offset capabilities within urban agglomerations.

Pattern of cooling benefits from ecospaces during urbanization: A case study of the Yangtze River Economic Belt

Urban ecological spaces are effective thermoregulators under global warming. However, the cooling efficiency of urban ecological spaces during the urbanization has not been studied comprehensively. Here, we investigate the spatio-temporal dynamics of Urban Cold Island (UCI) intensity in 11 typical cities of the Yangtze River Economic Belt (YREB). We determined the impact of ecological landscape trends on these dynamics by using GlobalLand and MODIS 8 d mean land surface temperature (LST) data for three periods (2000, 2010, and 2020), and the landscape pattern index and diversity index. We found that in the past 20 years, the built-up area has increased by sixfold; 62.53 % and 37.47 % of YREB were warming or cooling, with 71.22 % of the daytime cooling and 93 % of the nighttime warming. The average UCI intensity of YREB has increased from 0.518 to 0.847 and is negatively correlated with LST with a decreasing slope. As the UCI intensity of green spaces increased, that of blue spaces decreased. Surface area and landscape pattern are the key determinants of UCI intensity in blue and green spaces, respectively, especially the landscape shape index (LSI). Therefore, maintaining ecological spaces, enriching the structural integrity of green spaces, and improving blue space connectivity can help cities at different development levels cope with heat stress during regional urbanization.

Mutual inhibition effects of elevated CO2 and climate change on global forest GPP

The impact of CO2 fertilization on enhancing global forest gross primary productivity (GPP) is acknowledged, but its interaction with climate factors-air temperature (Tem), precipitation (Pre), vapor pressure deficit (VPD), and radiation (Rad)-remains unclear. In this study, global forest GPP trends from 1982 to 2018 were examined using BEPS, NIRv, FLUXCOM, and revised EC-LUE datasets, with interannual trends of 5.618 (p < 0.01), 5.831 (p < 0.01), 0.227, and 6.566 g C m-2 yr-1 (p < 0.01), respectively. Elevated CO2 was identified as the primary driver of GPP trends, with the dominant area ranging from 51.11% to 90.37% across different GPP datasets. In the NIRv and revised EC-LUE datasets, the positive impact of CO2 on GPP showed a decrease of 0.222 g C m-2 yr-1, while the negative impact of Rad increased by 0.007 g C m-2 yr-1. An inhibitory relationship was found between the actual effects of elevated CO2 and climate change on GPP in most forest types. At lower latitudes, Tem primarily constrained CO2 fertilization, while at higher latitudes, VPD emerged as the key limiting factor. This was mainly attributed to the potential trade-off or competition between elevated CO2 and climate change in influencing GPP, with strategic resource allocation varying across different forest ecosystems. This study highlights the significant inhibitory effects of elevated CO2 and climate change on global forest GPP, providing insights into the dynamic responses of forest ecosystems to changing environments.

Temporal and spatial evolution simulation and attribution analysis of vegetation photosynthesis over the past 21 years based on satellite SIF data: a case study from Asia

Photosynthesis in vegetation is one of the key processes in maintaining regional ecological balance and climate stability, and it is of significant importance for understanding the health of regional ecosystems and addressing climate change. Based on 2001-2021 Global OCO-2 Solar-Induced Fluorescence (GOSIF) dataset, this study analyzed spatiotemporal variations in Asian vegetation photosynthesis and its response to climate and human activities. Results show the following: (1) From 2001 to 2021, the overall photosynthetic activity of vegetation in the Asian region has shown an upward trend, exhibiting a stable distribution pattern with higher values in the eastern and southern regions and lower values in the central, western, and northern regions. In specific regions such as the Turgen Plateau in northwestern Kazakhstan, Cambodia, Laos, and northeastern Syria, photosynthesis significantly declined. (2) Meteorological factors influencing photosynthesis exhibit differences based on latitude and vertical zones. In low-latitude regions, temperature is the primary driver, while in mid-latitude areas, solar radiation and precipitation are crucial. High-latitude regions are primarily influenced by temperature, and high-altitude areas depend on precipitation and solar radiation. (3) Human activities (56.44%) have a slightly greater impact on the dynamics of Asian vegetation photosynthesis compared to climate change (43.56%). This research deepens our comprehension of the mechanisms behind the fluctuations in Asian vegetation photosynthesis, offering valuable perspectives for initiatives in environmental conservation, sustainability, and climate research.

Evaluating net primary productivity dynamics and their response to land-use change in the loess plateau after the 'Grain for Green' program

Assessing net primary productivity (NPP) dynamics and the contribution of land-use change (LUC) to NPP can help guide scientific policy to better restore and control the ecological environment. Since 1999, the "Green for Grain" Program (GGP) has strongly affected the spatial and temporal pattern of NPP on the Loess Plateau (LP); however, the multifaceted impact of phased vegetation engineering measures on NPP dynamics remains unclear. In this study, the Carnegie-Ames-Stanford Approach (CASA) model was used to simulate NPP dynamics and quantify the relative contributions of LUC and climate change (CC) to NPP under two different scenarios. The results showed that the average NPP on the LP increased from 240.7 gC·m-2 to 422.5 gC·m-2 from 2001 to 2020, with 67.43% of the areas showing a significant increasing trend. LUC was the main contributor to NPP increases during the study period, and precipitation was the most important climatic factor affecting NPP dynamics. The cumulative amount of NPP change caused by LUC (ΔNPPLUC) showed a fluctuating growth trend (from 46.23 gC·m-2 to 127.25 gC·m-2), with a higher growth rate in period ΙΙ (2010-2020) than in period Ι (2001-2010), which may be related to the accumulation of vegetation biomass and the delayed effect of the GGP on NPP. The contribution rate of LUC to increased NPP in periods Ι and ΙΙ was 101.2% and 51.2%, respectively. Regarding the transformation mode, the transformation of grassland to forest had the greatest influence on ΔNPPLUC. Regarding land-use type, the increased efficiency of NPP was improved in cropland, grassland, and forest. This study provides a scientific basis for the scientific management and development of vegetation engineering measures and regional sustainable development.

Revealing climatic and groundwater impacts on the spatiotemporal variations in vegetation coverage in marine sedimentary basins of the North China Plain, China

The North China Plain (NCP) is one of the three great plains in China and also serves as a vital region for grain, cotton, and oil production. Under the influence of regional hydrothermal changes, groundwater overexploitation, and seawater intrusion, the vegetation coverage is undergoing continuous alterations. However, a comprehensive assessment of impacts of precipitation, temperature, and groundwater on vegetation in marine sedimentary regions of the NCP is lacking. Heilonggang Basin (HB) is located in the low-lying plain area in the east of NCP, which is part of the NCP. In this study, the HB was chosen as a typical area of interest. We collected a series of data, including the Normalized Difference Vegetation Index (NDVI), precipitation, temperature, groundwater depth, and Total Dissolved Solids (TDS) from 2001 to 2020. Then the spatiotemporal variation in vegetation was analyzed, and the underlying driving mechanisms of vegetation variation were explored in this paper. The results show that NDVI experiences a rapid increase from 2001 to 2004, followed by stable fluctuations from 2004 to 2020. The vegetation in the HB has achieved an overall improvement in the past two decades, with 76% showing improvement, mainly in the central and eastern areas, and 24% exhibiting deterioration in other areas. From 2001 to 2020, NDVI correlates positively with precipitation, whereas its relationship with temperature fluctuates between positive and negative, and is not statistically significant. There is a threshold for the synergistic change of NDVI and groundwater depth. When the groundwater depth is lower than 3.8 m, NDVI increases sharply with groundwater depth. However, beyond this threshold, NDVI tends to stabilize and fluctuate. In the eastern coastal areas, NDVI exhibits a strong positive correlation with groundwater depth, influenced by the surface soil TDS controlled by groundwater depth. In the central regions, a strong negative correlation is observed, where NDVI is primarily impacted by soil moisture under the control of groundwater. In the west and south, a strong positive correlation exists, with NDVI primarily influenced by the intensity of groundwater exploitation. Thus, precipitation and groundwater are the primary driving forces behind the spatiotemporal variability of vegetation in the HB, while in contrast, the influence of temperature is uncertain. This study has elucidated the mechanism of vegetation response, providing a theoretical basis for mitigating adverse factors affecting vegetation growth and formulating rational water usage regulations in the NCP.

Assessing the effects of climate and human activity on vegetation change in Northern China

Fractional vegetation cover (FVC) has changed significantly under various disturbances over northern China in recent decades. This research examines the dynamics of FVC and how it is affected by climate and human activity during the period of 1990-2018 in northern China. The effects of climate change (i.e., temperature, precipitation, solar radiation, and soil moisture) and human activity (socioeconomic data and land use) on vegetation coverage change in northern China from 1990 to 2018 were quantified using the Sen + Mann-Kendall test, partial correlation analysis, and structural equation modelling (SEM) methods. The findings of this research indicate the following: (1) From 1990 to 2018, the overall trend in FVC in northern China was increased. The areas with obvious increases were mainly situated on the northern slope of Tianshan Mountains, Xinjiang, the Loess Plateau, the Northeast China Plain, and the Sanjiang Plain, while the areas with distinct degradation were located in the Inner Mongolia Plateau, the Changbai Mountain and the eastern part of north China. (2) In the past 29 years, the FVC in northern China has been mainly affected by precipitation and soil moisture. (3) Based on structural equation modelling, we discovered that certain variables impacted the main factors influencing the amount of FVC in northern China. Human activity has had a larger impact on FVC than climate change. Our findings can accelerate the comprehension of vegetation dynamics and their underlying mechanisms and provide a theoretical basis for regional ecological environmental protection.

Vegetation cover dynamics and its constraint effect on ecosystem services on the Qinghai-Tibet Plateau under ecological restoration projects

Ecological restoration projects (ERPs) are implemented worldwide to restore degraded ecosystems and promote ecosystem sustainability. In recent years, a series of ERPs have been implemented to enhance vegetation cover in the unique alpine ecosystems of the Qinghai-Tibet Plateau (QTP). However, the current assessment of the ecological benefits of ERPs is relatively single, and the scale and extent of future ecological restoration project implementation cannot be determined. We quantified trends in normalized vegetation index (NDVI) since the implementation of ERPs. Changes in four major ecosystem services were assessed before and after ERPs implementation, including wind erosion protection, soil retention, water yield, and net primary productivity (NPP). The relationship between NDVI and ecosystem services was further explored using a constraint line approach to identify NDVI as a threshold reference for ERPs implementation. The results showed that: (1) since the implementation of ERPs, 21.80% of the regional NDVI of the QTP has increased significantly. (2) After the implementation of ERPs, the average total ecosystem services index (TES) increased from 0.269 in 2000 to 0.285 in 2020. The average soil retention and water yield increased but the NPP and sandstorm prevention decreased slightly. (3) NDVI had no significant constraint effect on soil retention and NPP, but there was a significant constraint effect on wind erosion prevention and water yield. (4) The constraint line of NDVI on TES was S-shaped. After the implementation of ERPs, the TES gradually reached a threshold value when NDVI was 0.65-0.75. Our findings identify significant contributions of ERPs and thresholds for the constraining effects of vegetation cover on ecosystem services, which can inform sustainable ERPs for governments.

Impact of aerosol concentration changes on carbon sequestration potential of rice in a temperate monsoon climate zone during the COVID-19: a case study on the Sanjiang Plain, China

The emission reduction of atmospheric pollutants during the COVID-19 caused the change in aerosol concentration. However, there is a lack of research on the impact of changes in aerosol concentration on carbon sequestration potential. To reveal the impact mechanism of aerosols on rice carbon sequestration, the spatial differentiation characteristics of aerosol optical depth (AOD), gross primary productivity (GPP), net primary productivity (NPP), leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FPAR), and meteorological factors were compared in the Sanjiang Plain. Pearson correlation analysis and geographic detector were used to analyze the main driving factors affecting the spatial heterogeneity of GPP and NPP. The study showed that the spatial distribution pattern of AOD in the rice-growing area during the epidemic was gradually decreasing from northeast to southwest with an overall decrease of 29.76%. Under the synergistic effect of multiple driving factors, both GPP and NPP increased by more than 5.0%, and the carbon sequestration capacity was improved. LAI and FPAR were the main driving factors for the spatial differentiation of rice GPP and NPP during the epidemic, followed by potential evapotranspiration and AOD. All interaction detection results showed a double-factor enhancement, which indicated that the effects of atmospheric environmental changes on rice primary productivity were the synergistic effect result of multiple factors, and AOD was the key factor that indirectly affected rice primary productivity. The synergistic effects between aerosol-radiation-meteorological factor-rice primary productivity in a typical temperate monsoon climate zone suitable for rice growth were studied, and the effects of changes in aerosol concentration on carbon sequestration potential were analyzed. The study can provide important references for the assessment of carbon sequestration potential in this climate zone.

Analysis of change process of NPP dominated by human activities in Northwest Hubei, China, from 2000 to 2020

Clarifying the spatial distribution of the impact of different human disturbance activities on the net primary productivity (NPP) in regions with single climatic conditions is of considerable importance to ecological protection. Time-series NPP from 2000 to 2020 was simulated in Northwest Hubei, China, and the effects of the climate and human activities on the NPP changes were separated. Research results showed that from 2000 to 2020, the NPP change with an area of 10,166.63 km2 in Northwest Hubei is influenced by climate and human activities. Among them, human activities account for as high as 84.53%. From 2000 to 2020, the NPP in Northwest Hubei showed a slight upward trend at a rate of 1.61 g C m-2 year-1. The significantly increased NPP accounted for 21.4% of the total, which was mainly distributed in north of Northwest Hubei. And the farming of cultivated land led to the increase of NPP in west as well as the reduced human distribution in cultivated land, which was scattered in forests. Only 6.67% of the total area demonstrated a significantly decreased NPP, which was distributed mainly in the central affected by the expansion of rural-urban land and change of broad-leaved forests to shrubs and in southeast regions of Northwest Hubei caused by the increase in potential evapotranspiration. This study refined the driving factors of spatial heterogeneity of NPP changes in Northwest Hubei, which is conducive to rational planning of terrestrial ecosystem protection measures.

Unraveling the enigma of NPP variation in Chinese vegetation ecosystems: The interplay of climate change and land use change

Global carbon emissions have exacerbated the greenhouse effect, exerting a profound impact on ecosystems worldwide. Gaining an understanding of the fluctuations in vegetation net primary productivity (NPP) is pivotal in the assessment of environmental quality, estimation of carbon source/sink potential, and facilitation of ecological restoration. Employing MODIS and meteorological data, we conducted a comprehensive analysis of NPP evolution in Chinese vegetation ecosystems (VESs), employing Theil-Sen median trend analysis and the Mann-Kendall test. Furthermore, utilizing scenario-based analysis, we quantitatively determined the respective contributions of climate change and land use change to NPP variations across various scales. The overall NPP exhibited a discernible upward trend from 2000 to 2020, with a growth rate of 5.83 gC·m-2·year-1. Forestland ecosystem (FES) displayed the highest rate of increase (9.40 gC·m-2·year-1), followed by cropland ecosystem (CES) (4.00 gC·m-2·year-1) and grassland ecosystem (GES) (3.40 gC·m-2·year-1). Geographically, NPP exhibited a spatial pattern characterized by elevated values in the southeast and diminished values in the northwest. In addition, climate change had elevated 76.39 % of CES NPP, 90.62 % of FES NPP, and 71.78 % of GES NPP. At the national level, climate change accounted for 83.14 % of the NPP changes, while land use change contributed 14.14 %. Notably, climate change emerged as the primary driving force behind NPP variations across all VEGs, with land use change exerting the most pronounced influence on CES. At the grid scale (2 km × 2 km), land use change played a substantial role in all VEGs, contributing 60.01 % in CES, 54.20 % in FES, and 55.61 % in GES of the NPP variations.

Temperate grassland vegetation restoration influenced by grazing exclusion and climate change

Grasslands are one of the most important terrestrial biomes, supporting a wide range of ecological functions and services. Grassland degradation due to overgrazing is a severe issue worldwide, especially in developing regions. However, observations from multiple sources have shown that temperate grasslands in China have significantly increased during the past two decades. It remains controversial what factors have driven the vegetation restoration in this region. In this study, we combined remote-sensing images and field survey datasets to quantify the contributions of different factors to vegetation restoration in six temperate grasslands in northern China. Across the six grasslands, the Normalized Difference Vegetation Index (NDVI) increased by 0.003-0.0319 year-1. The average contributions of grazing exclusion and climate change to the NDVI increase were 49.23 % and 50.77 %, respectively. Precipitation change was the primary climate factor driving vegetation restoration, contributing 50.76 % to the NDVI variance. By contrast, climate warming tended to slow vegetation restoration, and atmospheric CO2 concentration change contributed little to the NDVI increase in the temperate grasslands. These results emphasize the significant contributions of both climate change and human management to grassland vegetation restoration.

Study on the relationship between regional soil desertification and salinization and groundwater based on remote sensing inversion: A case study of the windy beach area in Northern Shaanxi

Soil desertification and salinization are important environmental concerns in arid regions, and their relationship with groundwater change must be further clarified. However, the relationships among soil desertification, salinization, and groundwater are difficult to investigate on a large spatiotemporal scale using traditional ground surveys. In the windy beach area in Northern Shaanxi (WBANS), desertification and salinization problems coexist; therefore, this area was selected as the study area. The feasibility of implementing large-scale remote sensing inversions to identify the degree of desertification and salinization was verified based on measured data, and the degree of influence of groundwater burial depth (GBD) on desertification and salinization was quantified using the geodetector and residual trend analysis methods. The results showed that the GBD in the WBANS presented an increasing trend and the degree of salinization showed a decreasing trend. Moreover, the joint influence of the unique natural environment and anthropogenic activities has led to increases in fractional vegetation cover and considerable improvements in the ecological environment. The intensity of desertification explained by GBD in the WBANS increased significantly (p < 0.01) at a rate of change of 0.0190/year, with high q-values above 0.66 for both Yuyang and Shenmu. The contribution rate of potential evapotranspiration and precipitation to salinization in Yuyang and Shenmu was >97 %, and the contribution rate of GBD to salinization in Dingbian, Jingbian, and Hengshan was 34.78 %, 31.15 %, and 29.41 %, respectively. Overall, the suitable GBD in the WBANS is 2-4 m. The study results provide a reference for research on the inversion, monitoring, and prevention of desertification and salinization dynamics on a large spatiotemporal scale and offer a scientific basis for rationally determining GBD.

Impacts of climate change on winter wheat net primary production: the regulatory role of crop management

BACKGROUND

The Huang-Huai-Hai Plain (3HP) is the main agricultural area in China. Although climate change (CC) and crop management (CM) are considered factors affecting the winter wheat net primary production (NPP) in this region, their effects remain unclear. In the present study, we evaluated the relative contributions of CC and CM to winter wheat aboveground NPP (ANPP) in the 3HP and the relationships between climatic factors and ANPP using the first-order difference method from 2000 to 2020.

RESULTS

CM had a greater influence on the ANPP of winter wheat than did CC. However, the relative contribution of CM to ANPP gradually decreased in humid and dry sub-humid regions with the development of winter wheat. Furthermore, in areas characterized by low temperatures and limited precipitation, CC became the dominant factor contributing to ANPP, indicating that varieties resilient to drought and cold should be selected in these regions. Minimum and average temperatures were the dominant factors driving spatiotemporal variations in ANPP during the early stage of winter wheat growth, whereas maximum temperature constrained growth throughout the winter wheat growth cycle. When winter wheat entered the vigorous growth stage, precipitation and solar radiation replaced temperature as the driving factors influencing winter wheat growth.

CONCLUSION

The results of the present study provide guidance for optimizing winter wheat crop management in the 3HP. © 2023 Society of Chemical Industry.

Trends and contribution of different grassland types in restoring the Three River Headwater Region, China, 1988-2012

Rapid greening of the Qinghai-Tibet Plateau had been confirmed, but the contributions to the overall change and its causes in various grassland types has been less studied. Previous research has focused on exogenous factors such as climate change and human activities, rather than on endogenous factors, such as grassland types. Using net primary productivity (NPP), precipitation and temperature data, we applied trend, contribution and pull contribution analysis to understand the spatiotemporal evolution and driving factors of six different grassland types at a pixel scale in the Three River Headwater Region (TRHR) of China from 1988 to 2012. The results showed that grassland NPP in the TRHR increased at an average growth amount of 3.46 gC m-2 yr-1 and an average growth rate of 2.26 %. The average growth amount of alpine desert and alpine steppe (0.42 gC m-2 yr-1, 1.74 gC m-2 yr-1, respectively) showed great potential improvement. The average growth rate (1.27 %, 1.87 %) of montane meadow and alpine meadow, respectively, presented a high potential to increase (P < 0.05). Alpine meadow, montane meadow and temperate steppe were positive pullers to the average growth amount. Alpine steppe and alpine desert were positive pullers to the average growth rate. In general, alpine meadow had the highest growth amount contribution (84.86 %), while alpine meadow and alpine steppe had the highest contribution to the growth rate (62.16 %, 34.24 %, respectively). The study implied that, in addition to external factors, differences in internal factors such as the community composition and structure of different grassland types could also affected the grassland recovery process. These results contribute to understanding the specific differences in the contribution of regional grassland restoration processes from vegetation composition. Assessing grasslands with the potential to increase productivity, we can provide scientific reference for implementing more precise and efficient measures in future grassland management restoration.

The impact of climate change and human activities on the change in the net primary productivity of vegetation-taking Sichuan Province as an example

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.

Past and projected future patterns of fractional vegetation coverage in China

With the intensifying climate change and the strengthening ecosystem management, quantifying the past and predicting the future influence of these two factors on vegetation change patterns in China need to be analyzed urgently. By constructing a framework model to accurately identify fractional vegetation coverage (FVC) change patterns, we found that FVC in China from 1982 to 2018 mainly showed linear increase (29.5 %) or Gaussian decrease (27.4 %). FVC variation was mainly affected by soil moisture in the Qi-North region and by vapor pressure deficit in other regions. The influence of environmental change on FVC, except for Yang-Qi region in the southwest (-2.0 %), played a positive role, and weakened from the middle (Hu-Yang region: 2.7 %) to the northwest (Qi-North region: 2.4 %) to the east (Hu-East region: 0.8 %). Based on five machine learning algorithms, it was predicted that under four Shared Socioeconomic Pathways (SSPs, including SSP126、SSP245、SSP370、SSP585) from 2019 to 2060, FVC would maintain an upward trend, except for the east, where FVC would rapidly decline after 2039. FVC in the eastern region experienced a transition from past growth to future decline, suggesting that the focus of future ecosystem management should be on this region.

Urbanization expands the fluctuating difference in gross primary productivity between urban and rural areas from 2000 to 2018 in China

Urban and rural vegetation are affected by both climate change and human activities, but the role of urbanization in vegetation productivity is unclear given the dual impacts. Here, we delineated urban area (UA) and rural area (RA), quantified the relative impacts of climate change and human activities on gross primary production (GPP) in 34 major cities (MCs) in China from 2000 to 2018, and analyzed the intrinsic impacts of urbanization on GPP. First, we found that the total urban impervious surface coverage (ISC) of the 34 MCs increased by 13.25 % and the mean annual GPP increased by 211 gC m-2 during the study period. GPP increased significantly in urban core areas, but decreased significantly in urban expansion areas, which was mainly due to a large amount of vegetation loss due to land use conversion. Second, the variability of GPP in UA was generally lower than in RA. Both climate change and human activities had a positive impact on GPP in UA and RA in the 34 MCs, of which the contribution was 49 % and 51 % in UA, and 76 % and 24 % in RA, respectively. Third, under climate change and human activities, the increase in GPP offset 4.96 % and 12.35 % of the impact of land use conversion on GPP in 2000 and 2018, respectively, which indicated that the offset strengthened over time. These findings emphasize the role of human activities in promoting carbon sequestration in urban vegetation, which is crucial for better understanding the processes and mechanisms of urban carbon cycles. Decision-makers can manage urban vegetation based on vegetation carbon sequestration potential as regions urbanize, aiding comprehensive decision-making.

Vegetation as the catalyst for water circulation on global terrestrial ecosystem

Global climate change is expected to further intensify the global water cycle, leading to more rapid evaporation and more intense precipitation. At the same time, the growth and expansion of natural vegetation caused by climate change and human activities create potential conflicts between ecosystems and humans over available water resources. Clarifying how terrestrial ecosystem evapotranspiration responds to global precipitation and vegetation facilitates a better understanding of and prediction for the responses of global ecosystem energy, water, and carbon budgets under climate change. Relying on the spatial and temporal distribution of evapotranspiration, precipitation, and solar-induced chlorophyll fluorescence (SIF) from remote sensing platforms, we decouple the interaction mechanism of evapotranspiration, precipitation, and vegetation in linear and nonlinear scenarios using correlation and partial correlation analysis, multiple linear regression analysis, and binning. Major conclusions are as follows: (1) As a natural catalyst of the global water cycle, vegetation plays a crucial role in regulating the relationship between climate change and the water‑carbon-energy cycle. (2) Vegetation, a key parameter affecting the water cycle, participates in the entire water cycle process. (3) The increase in vegetation productivity and photosynthesis plays a dominant role in promoting evapotranspiration in vegetated areas, while the increase in precipitation dominates the promotion of evapotranspiration in non-vegetated areas.

Short-term restoration effects of ecological projects detected using the turning point method in the Three River Headwater Region, China

The Three River Headwater Region (TRHR) is an important river source area providing important ecological functions. Decades ago, climate change and human activities severely degraded the ecosystem in the TRHR. To restore vegetation, a series of ecological projects have been implemented since 1989. Using net primary productivity (NPP) data from 1988 to 2012, a sequential Mann-Kendall trend test (SQ-MK) method was applied to identify the turning point of vegetation NPP. This approach was able to represent the critical response time of the vegetation to important disturbances. A 3-year time window was set after the implementation of one ecological project to detect and analyze its short-term effects. The ecological projects included the Yangtze River Basin Shelterbelt System Construction Project (YRCP), the TRHR Nature Reserve Construction Project (TNR), the Returning Grazing Land to Grassland Project (RGLGP), and the first phase of the Ecological Conservation and Restoration Project of the TRHR (ECRP). Our results showed that the vegetation in the TRHR responded positively to restoration: 89% of pixels showed an increasing trend and 54% of pixels underwent an abrupt change. The accelerated growth type accounted for the highest proportion among all types of detected turning points. In the ECRP's window, the positive turns rose rapidly, from 41% in 2005 to 86% in 2008, and it showed the most balanced restoration effects across grasslands. The alpine meadow and montane meadow restoration was largely influenced by the ECRP and the RGLGP (both >40%). The alpine steppe restoration was mainly attributed to the ECRP (68%). On the county scale, the positive turns in Yushu at the source of the Yangtze River mainly benefited from the RGLGP (56%), while the positive turns in Maduo at the source of the Yellow River benefited from the ECRP (77%). Nangqian, Tanggula and Zaduo County were still in need of intervention for restoration (< 3%). The results of the study can enhance our understanding of the spatio-temporal distribution of the short-term ecological benefits of different ecological projects, thus provide a scientific and timely reference for future planning and adjustment of the conservation and restoration projects.

Quantifying climate variability and regional anthropogenic influence on vegetation dynamics in northwest India

To explore the spatio-temporal dynamics and mechanisms underlying vegetation cover in Haryana State, India, and implications thereof, we obtained MODIS EVI imagery together with CHIRPS rainfall and MODIS LST at annual, seasonal and monthly scales for the period spanning 2000 to 2022. Additionally, MODIS Potential Evapotranspiration (PET), Ground Water Storage (GWS), Soil Moisture (SM) and nighttime light datasets were compiled to explore their spatial relationships with vegetation and other selected environmental parameters. Non-parametric statistics were applied to estimate the magnitude of trends, along with correlation and residual trend analysis to quantify the relative influence of Climate Change (CC) and Human Activities (HA) on vegetation dynamics using Google Earth Engine algorithms. The study reveals regional contrasts in trends that are evidently related to elevation. An annual increasing trend in rainfall (21.3 mm/decade, p < 0.05), together with augmented vegetation cover and slightly cooler (-0.07 °C/decade) LST is revealed in the high-elevation areas. Meanwhile, LST in the plain regions exhibit a warming trend (0.02 °C/decade) and decreased in vegetation and rainfall, accompanied by substantial reductions in GWS and SM related to increased PET. Linear regression demonstrates a strongly significant relationship between rainfall and EVI (R2 = 0.92), although a negative relationship is apparent between LST and vegetation (R2 = -0.83). Additionally, increased LST in the low-elevation parts of the study area impacted PET (R2 = 0.87), which triggered EVI loss (R2 = 0.93). Moreover, increased HA resulted in losses of 25.5 mm GSW and 1.5 mm SM annually. The relative contributions of CC and HA are shown to vary with elevation. At higher elevations, CC and HA contribute respectively 85% and 15% to the increase in EVI. However, at lower elevations, reduced EVI is largely (79%) due to human activities. This needs to be considered in managing the future of vulnerable socio-ecological systems in the state of Haryana.

Analysis of Net Primary Productivity Variation and Quantitative Assessment of Driving Forces-A Case Study of the Yangtze River Basin

Net primary productivity (NPP) can indirectly reflect vegetation's capacity for CO2 fixation, but its spatiotemporal dynamics are subject to alterations to some extent due to the influences of climate change and human activities. In this study, NPP is used as an indicator to investigate vegetarian carbon ability changes in the vital ecosystems of the Yangtze River Basin (YRB) in China. We also explored the NPP responses to climate change and human activities. We conducted a comprehensive analysis of the temporal dynamics and spatial variations in NPP within the YRB ecosystems from 2003 to 2020. Furthermore, we employed residual analysis to quantitatively assess the contributions of climate factors and human activities to NPP changes. The research findings are as follows: (1) Over the 18-year period, the average NPP within the basin amounted to 543.95 gC/m2, displaying a noticeable fluctuating upward trend with a growth rate of approximately 3.1 gC/m2; (2) The areas exhibiting an increasing trend in NPP account for 82.55% of the total study area. Regions with relatively high stability in the basin covered 62.36% of the total area, while areas with low stability accounted for 2.22%, mainly situated in the Hengduan Mountains of the western Sichuan Plateau; (3) NPP improvement was jointly driven by human activities and climate change, with human activities contributing more significantly to NPP growth. Specifically, the contributions were 65.39% in total, with human activities contributing 59.28% and climate change contributing 40.01%. This study provides an objective assessment of the contributions of human activities and climate change to vegetation productivity, offering crucial insights for future ecosystem development and environmental planning.

Increasing riverine export of dissolved organic carbon from China

River transport of dissolved organic carbon (DOC) to the ocean is a crucial but poorly quantified regional carbon cycle component. Large uncertainties remaining on the riverine DOC export from China, as well as its trend and drivers of change, have challenged the reconciliation between atmosphere-based and land-based estimates of China's land carbon sink. Here, we harmonized a large database of riverine in-situ measurements and applied a random forest model, to quantify riverine DOC fluxes (FDOC ) and DOC concentrations (CDOC ) in rivers across China. This study proposes the first DOC modeling effort capable of reproducing well the magnitude of riverine CDOC and FDOC , as well as its trends, on a monthly scale and with a much wider spatial distribution over China compared to previous studies that mainly focused on annual-scale estimates and large rivers. Results show that over the period 2001-2015, the average CDOC was 2.25 ± 0.45 mg/L and average FDOC was 4.04 ± 1.02 Tg/year. Simultaneously, we found a significant increase in FDOC (+0.044 Tg/year2 , p = .01), but little change in CDOC (-0.001 mg/L/year, p > .10). Although the trend in CDOC is not significant at the country scale, it is significantly increasing in the Yangtze River Basin and Huaihe River Basin (0.005 and 0.013 mg/L/year, p < .05) while significantly decreasing in the Yellow River Basin and Southwest Rivers Basin (-0.043 and -0.014 mg/L/year, p = .01). Changes in hydrology, play a stronger role than direct impacts of anthropogenic activities in determining the spatio-temporal variability of FDOC and CDOC across China. However, and in contrast with other basins, the significant increase in CDOC in the Yangtze River Basin and Huaihe River Basin is attributable to direct anthropogenic activities. Given the dominance of hydrology in driving FDOC , the increase in FDOC is likely to continue under the projected increase in river discharge over China resulting from a future wetter climate.

The influence of climate and population density on Buxus hyrcana potential distribution and habitat connectivity

Changes in environmental factors, human impact, and interactions between them accelerate the extinction of woody species. Therefore, conservation programs are needed to protect endangered taxa. However, the relationship between climate, habitat fragmentation, and anthropogenic activities and their consequences are still not well understood. In this work, we aimed to evaluate the impact of climate change and human population density on the Buxus hyrcana Pojark distribution range, as well as the phenomenon of habitat fragmentation. Based on species occurrence data throughout the Hyrcanian Forests (north of Iran), the MAXENT model was employed to estimate the potential distribution and suitability changes. Morphological-spatial analysis (MSPA) and CIRCUITSCAPE were used to assess habitat fragmentation and its connectivity. According to the main results obtained from future scenarios, the potential range will significantly decrease due to the lack of suitable climatic conditions. Meanwhile, B. hyrcana may not be able to shift in potentially suitable areas because of human influence and geographic barriers. Under RCP scenarios the extent of the core area would be reduced and the edge/core ratio significantly increased. Altogether, we found negative effects of the environmental change and the human population density on the continuity of habitats of B. hyrcana. The results of the presented work may improve our knowledge connected with in situ and ex situ protection strategies.

Comprehensive evaluation system for vegetation ecological quality: a case study of Sichuan ecological protection redline areas

Dynamic monitoring and evaluation of vegetation ecological quality (VEQ) is indispensable for ecological environment management and sustainable development. Single-indicator methods that have been widely used may cause biased results due to neglect of the variety of vegetation ecological elements. We developed the vegetation ecological quality index (VEQI) by coupling vegetation structure (vegetation cover) and function (carbon sequestration, water conservation, soil retention, and biodiversity maintenance) indicators. The changing characteristics of VEQ and the relative contribution of driving factors in the ecological protection redline areas in Sichuan Province (EPRA), China, from 2000 to 2021 were explored using VEQI, Sen's slope, Mann-Kendall test, Hurst index, and residual analysis based on the XGBoost (Extreme gradient boosting regressor). The results showed that the VEQ in the EPRA has improved over the 22-year study period, but this trend may be unsustainable in the future. Temperature was the most influential climate factor. And human activities were the dominant factor with a relative contribution of 78.57% to VEQ changes. This study provides ideas for assessing ecological restoration in other regions, and can provide guidance for ecosystem management and conservation.

Impact assessment of urbanization on vegetation net primary productivity: A case study of the core development area in central plains urban agglomeration, China

Rapid urbanization process has a negative or positive impact on vegetation growth. Net primary productivity (NPP) is an effective indicator to characterize vegetation growth status. Taking the core development area of the Central Plains urban agglomeration as the study area, we estimated the NPP and its change trend in the past four decades using the Carnegie-Ames-Stanford Approach (CASA) model and statistical analysis based on meteorological and multi-source remote sensing data. Meanwhile, combined with the urbanization impact framework, we further analyzed urbanization's direct and indirect impact on NPP. The results showed that the urban area increased by 2688 km² during a high-speed urbanization process from 1983 to 2019. As a result of the intense urbanization process, a continuous NPP decrease (direct impact) can be seen, which aggravated along with the acceleration of the urban expansion, and the mean value of direct impact was 130.84 g C·m^-2·a^-1. Meanwhile, urbanization also had a positive impact on NPP (indirect impact). The indirect impact showed an increasing trend during urbanization with a mean value of 10.91 g C·m^-2·a^-1. The indirect impact was mainly related to temperature in climatic factors. The indirect impact has a seasonal heterogeneity, and high-temperature environments of urban areas are more effective in promoting vegetation growth in autumn and winter than in summer. Among different cities, high-speed development cities have higher indirect impact values than medium's and low's because of better ecological construction. This study is of great significance for understanding the impact of urbanization on vegetation growth in the Central Plains urban agglomeration area, supporting urban greening plans, and building sustainable and resilient urban agglomerations.

Factors Limiting Radial Growth of Conifers on Their Semiarid Borders across Kazakhstan

The forests of Central Asia are biodiversity hotspots at risk from rapid climate change, but they are understudied in terms of the climate-growth relationships of trees. This classical dendroclimatic case study was performed for six conifer forest stands near their semiarid boundaries across Kazakhstan: (1-3) Pinus sylvestris L., temperate forest steppes; (4-5) Picea schrenkiana Fisch. & C.A. Mey, foothills, the Western Tien Shan, southeast; (6) Juniperus seravschanica Kom., montane zone, the Western Tien Shan, southern subtropics. Due to large distances, correlations between local tree-ring width (TRW) chronologies are significant only within species (pine, 0.19-0.50; spruce, 0.55). The most stable climatic response is negative correlations of TRW with maximum temperatures of the previous (from -0.37 to -0.50) and current (from -0.17 to -0.44) growing season. The strength of the positive response to annual precipitation (0.10-0.48) and Standardized Precipitation Evapotranspiration Index (0.15-0.49) depends on local aridity. The timeframe of climatic responses shifts to earlier months north-to-south. For years with maximum and minimum TRW, differences in seasonal maximal temperatures (by ~1-3 °C) and precipitation (by ~12-83%) were also found. Heat stress being the primary factor limiting conifer growth across Kazakhstan, we suggest experiments there on heat protection measures in plantations and for urban trees, alongside broadening the coverage of the dendroclimatic net with accents on the impact of habitat conditions and climate-induced long-term growth dynamics.

A novel framework for vegetation change characterization from time series landsat images

Understanding terrestrial ecosystem dynamics requires a comprehensive examination of vegetation changes. Remote sensing technology has been established as an effective approach to reconstructing vegetation change history, investigating change properties, and evaluating the ecological effects. However, current remote sensing techniques are primarily focused on break detection but ignore long-term trend analysis. In this study, we proposed a novel framework based on a change detection algorithm and a trend analysis method that could integrate both short-term disturbance detection and long-term trends to comprehensively assess vegetation change. With this framework, we characterized the vegetation changes in Zhejiang Province from 1990 to 2020 using Landsat and landcover data. Benefiting from combining break detection and long-term trend analysis, the framework showcased its capability of capturing a variety of dynamics and trends of vegetation. The results show that the vegetation was browning in the plains while greening in the mountains, and the overall vegetation was gradually greening during the study period. By comparison, detected vegetation disturbances covered 57.71% of the province's land areas (accounting for 66.92% of the vegetated region) which were mainly distributed around the built-up areas, and most disturbances (94%) occurred in forest and cropland. There were two peak timings in the frequency of vegetation disturbances: around 2003 and around 2014, and the proportions of more than twice disturbances in a single location were low. The results illustrate that this framework is promising for the characterization of regional vegetation growth, including long-term trends and short-term features. The proposed framework enlightens a new direction for the continuous monitoring of vegetation dynamics.

Effects of climate change and human activities on vegetation coverage change in northern China considering extreme climate and time-lag and -accumulation effects

Quantifying the contributions of climate change (CC) and human activities (HA) to vegetation change is crucial for making a sustainable vegetation restoration scheme. However, the effects of extreme climate and time-lag and -accumulation effects on vegetation are often ignored, thus underestimating the impact of CC on vegetation change. In this study, the spatiotemporal variation of fractional vegetation cover (FVC) from 2000 to 2019 in northern China (NC) as well as the time-lag and -accumulation effects of 15 monthly climatic indices, including extreme indices, on the FVC, were analyzed. Subsequently, a modified residual analysis considering the influence of extreme climate and time-lag and -accumulation effects was proposed and used to attribute the change in the FVC contributed by CC and HA. Given the multicollinearity of climatic variables, partial least squares regression was used to construct the multiple linear regression between climatic indices and the FVC. The results show that: (1) the annual FVC significantly increased at a rate of 0.0268/10a from 2000 to 2019 in all vegetated areas of NC. Spatially, the annual FVC increased in most vegetated areas (∼81.6 %) of NC, and the increase was significant in ∼54.6 % of the areas; (2) except for the temperature duration (DTR), climatic indices had no significant time-lag effects but significant time-accumulation effects on the FVC change. The DTR had both significant time-lag and -accumulation effects on the FVC change. Except for potential evapotranspiration and DTR, the main temporal effects of climatic indices on the FVC were a 0-month lag and 1-2-month accumulation; and (3) the contributions of CC and HA to FVC change were 0.0081/10a and 0.0187/10a in NC, respectively, accounting for 30.2 % and 69.8 %, respectively. HA dominated the increase in the FVC in most provinces of NC, except for the Qinghai and Neimenggu provinces.

Effects of drought and climate factors on vegetation dynamics in Central Asia from 1982 to 2020

Ecological security and ecosystem stability in Central Asia depend heavily on the local vegetation. Vegetation dynamics and the response and hysteresis relationships to climate factors and drought on multiple scales over long time series in the region still need to be further explored. Using the net primary productivity (NPP) values as the vegetation change index of interest, in this study, we analyzed vegetation dynamics in Central Asia from 1982 to 2020 and assessed the responses and time lags of vegetation to climate factors and drought. The results showed that NPP gradually decreased from north to south and from east to west. Vegetation was distributed along both sides of the mountains. The temperatures rose from northeast to southwest, while precipitation gradually increased from southwest to northeast. The proportion of dry and wet years was as follows: normal (56.41%) > slightly dry (28.2%) > slightly humid (15.39%). Precipitation and drought conditions were positively correlated with NPP during the growing season, while temperature was negatively correlated with NPP. Increased spring temperature, precipitation, and drought conditions positively affected vegetation, while sustained summer temperature resulted in suppressed vegetation growth. Autumn vegetation was positively affected by temperature and drought, and precipitation was negatively correlated with autumn vegetation. Increasing winter temperatures promoted vegetation growth. The time lag between NPP and temperature gradually increased from northeast to southwest, and the time lag between NPP and precipitation gradually increased from south to north. Spring temperatures had the greatest beneficial impact on forestlands; summer climatic factors and drought had little effect on shrublands; the autumn climate exhibited small differences in its influence of each plant type; and winter temperatures had the greatest positive effect on grasslands. No time lag effect was found between any of the four vegetation types and precipitation. A one-month lag was found between cultivated lands and temperature; a two-month lag was found between forestlands and temperature; and a one-month lag was found between forestlands and drought and between shrublands and drought. The results can provide a scientific foundation for the sustainable development and management of ecosystems.

Effects of climate change and human activities on gross primary productivity in the Heihe River Basin, China

As the primary source of carbon dioxide fixation, vegetation is critical to the carbon sink process. In this paper, the Net Primary Productivity (NPP) and the Gross Primary Productivity (GPP) were simulated using the Carnegie-Ames-Stanford Approach (CASA) model and the Vegetation Photosynthesis Model (VPM), respectively, and then the Potential Gross Primary Productivity (PGPP) and the GPP affected by human activities (AGPP) were simulated by combining Potential Net Primary Productivity (PNPP), and then the impact of climate change and human activities on GPP was assessed in the Heihe River Basin (HRB). The results showed that the GPP of grassland and Bare or Sparse Vegetation (BSV) exhibited a fluctuation rise, with increases of 0.709 gCm^-2 a^-1 and 0.115 gCm^-2 a^-1, respectively, whereas the GPP of cropland showed a fluctuation reduction, with a decline rate of -0.465 gCm^-2 a^-1. Climate change and human activity are both positive for vegetation growth, and human activity being the primary factor influencing GPP change. Human-dominated vegetation restoration accounted for 56.1% of the overall restoration area, with grassland GPP being the most visible response to human activities. The GPP changes in crop and grassland had a positive correlation with precipitation but a negative correlation with temperature among climate change factors, whereas the GPP changes in BSV had a negative correlation with both precipitation and temperature. Quantitative analyses of climate change and human activities' dynamic contributions to vegetation can give scientific and theoretical insight for dealing with global climate change.

Response of vegetation dynamic change to multi-scale drought stress in the high-latitude Nenjiang River basin in China

Vegetation is an integral part of terrestrial ecosystem and plays an important role in responding to climate change, with its dynamic characteristics reflecting the ecological environmental quality. Recently, the continually increasing frequency and intensity of droughts has greatly changed how vegetation growth and development respond to drought. In this study, using normalized difference vegetation index and standardized precipitation evapotranspiration index (SPEI), we studied the response characteristics of vegetation dynamics to multi-scale drought stress (SPEI-1, SPEI-3, and SPEI-12) in the Nenjiang River basin (NRB) via Pearson correlation analysis, along with further exploration of the vegetation stability under drought. The results showed that the same period effect of drought on vegetation growth in NRB mainly occurs during the early and middle stages of vegetation growth. Furthermore, the proportion of significant positive correlation between them is 15.3%–43.3%, mainly in the central and southern parts of the basin. The lagged period effect of drought on vegetation growth mainly occurred during autumn in the southeast and middle of the basin, with a significant positive correlation of 20.8%. Under drought stress, the forest vegetation stability in NRB was the highest, with the resilience of wetland and grassland vegetation being the best and worst, respectively. Our study results will not only deepen our understanding of the dynamic vegetation changes in the high-latitude semi-arid basin under global climate change, but also provide a scientific basis for the management and water resources allocation of “agriculture-wetland-forest” complex ecosystem in the future.

Processes and mechanisms of vegetation ecosystem responding to climate and ecological restoration in China

Vegetation is an essential component of the earth's surface system and its dynamics is a clear indicator of global climate change. However, the vegetation trends of most studies were based on time-unvarying methods, cannot accurately detect the long-term nonlinear characteristics of vegetation changes. Here, the ensemble empirical mode decomposition and the Breaks for Additive Seasonal and Trend algorithm were applied to reconstruct the the normalized difference vegetation index (NDVI) data and diagnose spatiotemporal evolution and abrupt changes of long-term vegetation trends in China during 1982-2018. Residual analysis was used to separate the influence of climate and human activities on NDVI variations, and the effect of specific human drivers on vegetation growth was obtained. The results suggest that based on the time-varying analysis, high vegetation browning was masked by overall vegetation greening. Vegetation growth in China experienced an abrupt change in the 1990s and 2000s, accounting for 50% and 33.6% of the whole China respectively. Of the area before the breakpoint, 45.4% showed a trend of vegetation decrease, which was concentrated mainly in east China, while 43% of the area after the breakpoint also showed vegetation degradation, mainly in northwest China. Climate was an important driving force for vegetation change in China. It played a positive role in south China, but had a negative effect in northwest China. The impact of human activities on vegetation growthchanged from an initial negative influence to a positive one. In terms of human activities, an inverted-U-shaped relation was detected between CO2 emissions and vegetation growth; that is, the fertilization effect of CO2 had a certain threshold. Once that threshold was exceeded, it would hinder vegetation growth. Population density had a slight constraint on vegetation growth, and the implementation of ecological restoration projects (e.g., the Grain for Green Program) can promote vegetation growth to a certain extent.

Spatiotemporal Evolution and Driving Forces of Vegetation Cover in the Urumqi River Basin

It is important to determine long-term changes in vegetation cover, and the associated driving forces, to better understand the natural and human-induced factors affecting vegetation growth. We calculated the fractional vegetation coverage (FVC) of the Urumqi River basin and selected seven natural factors (the clay and sand contents of surface soils, elevation, aspect, slope, precipitation and temperature) and one human factor (land use type). We then used the Sen-Man-Kendall method to calculate the changing trend of the FVC from 2000 to 2020. We used the optimal parameters-based geographical detector (OPGD) model to quantitatively analyze the influence of each factor on the change in vegetation coverage in the basin. The FVC of the Urumqi River basin fluctuated from 2000 to 2020, with average values between 0.22 and 0.33. The areas with no and low vegetation coverage accounted for two-thirds of the total area, whereas the areas with a medium, medium-high and high FVC accounted for one-third of the total area. The upper reaches of the river basin are glacial and forest areas with no vegetation coverage and a high FVC. The middle reaches are concentrated in areas of urban construction with a medium FVC. The lower reaches are in unstable farmland with a medium and high FVC and deserts with a low FVC and no vegetation. From the perspective of the change trend, the areas with an improved FVC accounted for 62.54% of the basin, stable areas accounted for 5.66% and degraded areas accounted for 31.8%. The FVC showed an increasing trend in the study area. The improvement was mainly in the areas of urban construction and desert. Degradation occurred in the high-elevation areas, whereas the transitional zone was unchanged. The analysis of driving forces showed that the human factor explained more of the changes in the FVC than the natural factors in the order: land use type (0.244) > temperature (0.216) > elevation (0.205) > soil clay content (0.172) > precipitation (0.163) > soil sand content (0.138) > slope (0.059) > aspect (0.014). Apart from aspect, the explanatory power (Q value) of the interaction of each factor was higher than that of the single factor. Risk detection showed that each factor had an interval in which the change in the FVC was inhibited or promoted. The optimum elevation interval of the study area was 1300-2700 m and the greatest inhibition of the FVC was seen above 3540 m. Too much or too little precipitation inhibited vegetation coverage.