Disentangling climatic and anthropogenic contributions to nonlinear dynamics of alpine grassland productivity on the Qinghai-Tibetan Plateau

Soil carbon stocks in temperate grasslands reach equilibrium with grazing duration

Lost soil organic carbon (SOC) in degraded grasslands can be restored via the 'grazing exclusion' practice, but it was unknown how long (# of years) the restoration process can take. A synthesis of four decades of studies revealed that grazing exclusion increased SOC stocks in the topsoil (0-0.30 m) by 14.8 % (±0.8 Std Err), on average, compared to moderate-to-heavy grazing (MtH); During which SOC stock increased steadily, peaked in Year 18.5, and then declined. At peak, SOC stock was 42.5 % greater under grazing exclusion than under MtH due to 100.4 ± 4.2 % increase in aboveground biomass and 80.3 ± 33.5 % increase in root biomass. Grazing exclusion also increased soil C:N ratio by 7.6 % while decreasing bulk density by 9.4 %. Grazing exclusion could be ceased 18.5 years after initiation of grazing exclusion as plant biomass input balances carbon decomposition and SOC equilibrium occurs then additional benefits start diminishing.

Grazing affects ecosystem traits by regulating plateau pika activities at the landscape scale

The mechanism underlying the effects of livestock grazing on grassland ecosystem traits has been greatly discussed. However, as a common small burrowing mammal on the Tibetan Plateau grasslands, the plateau pika's (Ochotona curzoniae) influence on alpine grassland ecosystem traits has rarely been investigated, especially beyond the plot scale. In this study, we flew an unmanned aerial vehicle (UAV) over a grassland landscape under grazing and nongrazing treatments. Mounted visible spectral remote sensing, in combination with field surveys, was utilized to explore how livestock and pika grazing modify grassland ecosystem traits at the landscape scale on the Tibetan Plateau (TP). Using object-oriented classification and partial least squares regression, we retrieved the pika burrow distribution and grassland ecosystem traits. Then, the relationships among livestock grazing, pika burrowing and ecosystem traits were evaluated. The results indicated that livestock grazing reduces the alpine meadow community height by 0.13 cm and the species number by 0.25 while increasing the vegetation coverage by 9.69 % and the aboveground biomass (AGB) by 10.07 g/m2. A lower statue grassland community with greater coverage caused by livestock grazing promotes pika burrowing. Pika burrow density increases 100/ha per 1.70 % increase in vegetation coverage, a 1.87 g/m2 increase in AGB or a 0.08 m decrease in community height. Under livestock grazing, both community structure and nutrients are more strongly associated with pika burrow density. The structural equation model demonstrated that livestock grazing regulates pika burrow density by moderating structural value and subsequently affecting nutritional value. Pika burrowing activity explains 40 % of the total variation in nutritional value. Our findings revealed an intrinsic linkage between mammal activities and alpine grassland ecosystems, which can provide guidelines for grassland management through pika population control by adjusting grazing intensity on the TP.

Impacts of climate change on grassland fractional vegetation cover variation on the Tibetan Plateau

Climate change has profoundly impacted Tibetan Plateau grasslands, necessitating a comprehensive analysis of the historical and future responses across diverse grassland types, with the integration of an elevated atmospheric CO2 concentration (eCO2) and climatic factors. In this study, the response of the Tibetan Plateau grassland was investigated, with a focus on the fractional vegetation cover (FVC). By employing an enhanced ecohydrological model for the baseline (1985-2014) and future (2031-2070) periods under shared socioeconomic pathway (SSP) scenarios, the responses of FVC to climate change were predicted across all grassland types. The alpine steppe exhibited the most rapid growth, with average FVC increases projected to reach 37 ± 7 %-81 ± 15 % for alpine meadow, 82 ± 22 %-185 ± 55 % for alpine steppe, and 50 ± 8 %-95 ± 23 % for temperate grassland by the 2060s. During the baseline, eCO2 primarily caused the FVC increases in alpine meadow and temperate grassland, while warming governed alpine steppe growth. Interannual variability in the FVC of alpine grasslands was temperature-driven, while that of the temperate grasslands was driven by precipitation. An increase in the FVC of the alpine steppe was caused by warming under both low- and high-emissions scenarios. For the alpine meadow and temperate grasslands, precipitation was dominant for FVC changes in the SSP1-2.6 scenario, and eCO2 was dominant in the SSP3-7.0 and SSP5-8.5 scenarios. These findings provide a vital foundation for grassland management, carbon cycling comprehension, and vegetation feedback estimations on the Tibetan Plateau.

Nonlinear time effects of vegetation response to climate change: Evidence from Qilian Mountain National Park in China

Vegetation responses to climate change are typically nonlinear with varied time effects, yet current research lacks comprehensiveness and precise definitions, hindering a deeper understanding of the underlying mechanisms. This study focuses on the mountain-type Qilian Mountain National Park (QMNP), investigating the characteristics and patterns of these nonlinear time effects using a generalized additive model (GAM) based on MODIS-NDVI, growing season temperature, and precipitation data. The results show that 1) The time effects of climate change on vegetation exhibit significant spatial variations, differing across vegetation types and topographic conditions. Accounting for optimal time effects can increase the explanatory power of climate on vegetation change by 6.8 %. Precipitation responses are mainly characterized by time-lag and time-accumulation effects, notably in meadows and steppes, while temperature responses are largely cumulative, especially in steppes. The altitude and slope significantly influence the pattern of vegetation response to climate, particularly in areas with high altitudes and steep slopes. 2) There is a significant nonlinear relationship between vegetation growth and both precipitation and temperature, with the nonlinear relationship between precipitation and vegetation being stronger than that with temperature, particularly in the western and central regions of the park. Different vegetation types exhibit significant variations in their response to climate change, with deserts and steppes being more sensitive to precipitation. 3) Precipitation is the primary driver of vegetation change in the QMNP, particularly for high-elevation vegetation and herbaceous vegetation. The complex temporal patterns of vegetation response to climate change in the QMNP not only deepen the understanding of the intricate relationship between regional vegetation and climate variability but also provide a methodological reference for global studies on vegetation responses to climate change.

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.

The rising human footprint in the Tibetan Plateau threatens the effectiveness of ecological restoration on vegetation growth

Ecological restoration projects in the Tibetan Plateau aimed to reverse ecosystem degradation and safeguard the fragile alpine ecological environment. However, it is still being determined if the vegetation restoration is successful on a large scale or reaches the expected magnitude, restricting our ability to adapt practices to maximise the benefit. With multiple vegetation indices (VIs: NDVI, LAI, and GPP) from satellite observations and random forest machine-learning models, we performed an attribution study on vegetation growth trends caused by climate change and human activities. Then, we further explored the relationship between vegetation growth and ecological projects and human footprint without the influence of climate. The results showed that climatic change was a relatively strong driver of vegetation growth. The positive contributions of ecological restoration occurred only in half of the plateau due to the increased human footprint. Vegetation enhancement resulting from ecological restoration occurred in 13.1%-23.1% of the plateau. Among these values, ecological restoration counteracted the negative climate effects in 4.7%-8.3% of the plateau (about half of the negative climate effect area). In forest and grassland protection areas, the ecological restoration was more successful. The study provides a better understanding of the role of ecological projects in vegetation restoration and potential threats to its effectiveness. This is essential to improve future restoration projects.

Long-term ecological restoration increased plant diversity and soil total phosphorus content of the alpine flowing sand land in northwest Sichuan, China

The ecological restoration techniques that combine grazing, sand barriers with willows, fertilization, artificial planting, and continuous management are increasingly adopted in the management of flowing sandy land in high-altitude and cold regions. However, few studies have focused on the long-term ecological restoration effects of such technologies. This study systematically compared the vegetation and soil characteristics under different ecological restoration durations (0 (CK), 3 (F1), 14 (F2), 26 (F3), and 46 (F4) years) in the alpine sandy land of northwest Sichuan. The results showed that, with the increase of ecological restoration durations, (1) the aboveground and underground biomass of plants, and species number significantly increased, while the shannon-wiener index, margalef index, and simpson index dramatically decreased; (2) in the early stage of ecological restoration (0-3 yr), Cyperaceae accounted for the main groups, while in the late stage of ecological restoration (14-46 yr), Leguminosae and Forb groups predominated; (3) ecological restoration durations significantly influenced the total phosphorus (TP) content at a soil depth of 0-60 cm, but soil organic carbon and C/P ratio were only significantly impacted at 40-60 cm; (4) the plant and soil characteristics of F1, F2, and F3 treatments were more similar, and CK and F4 treatments were clearly distinguished on PC1 of principal component analysis; (5) there was no significant correlation between Leguminosae groups and environmental factors. Instead, a correlation between total nitrogen (TN) and Forb groups, Gramineae groups, and Cyperaceae groups was revealed. TN was very significantly positively correlated with species diversity and TP. Long-term ecological restoration improved plants biomass, plant species diversity, functional plant groups, and increased soil TP content in the alpine sandy land of northwest Sichuan.

Land use intensity controls the diversity-productivity relationship in northern temperate grasslands of China

Introduction

The diversity-productivity relationship is a central issue in maintaining the grassland ecosystem's multifunctionality and supporting its sustainable management. Currently, the mainstream opinion on the diversity-productivity relationship recognizes that increases in species diversity promote ecosystem productivity.

Methods

Here, we challenge this opinion by developing a generalized additive model-based framework to quantify the response rate of grassland productivity to plant species diversity using vegetation survey data we collected along a land-use intensity gradient in northern China.

Results

Our results show that the grassland aboveground biomass responds significantly positively to the Shannon-Wiener diversity index at a rate of 46.8 g m-2 per unit increase of the Shannon-Wiener index in enclosure-managed grasslands, under the co-influence of climate and landscape factors. The aboveground biomass response rate stays positive at a magnitude of 47.1 g m-2 in forest understory grassland and 39.7 g m-2 in wetland grassland. Conversely, the response rate turns negative in heavily grazed grasslands at -55.8 g m-2, transiting via near-neutral rates of -7.0 and -7.3 g m-2 in mowing grassland and moderately grazed grassland, respectively.

Discussion

These results suggest that the diversity-productivity relationship in temperate grasslands not only varies by magnitude but also switches directions under varying levels of land use intensity. This highlights the need to consider land use intensity as a more important ecological integrity indicator for future ecological conservation programs in temperate grasslands.

Using enzyme activities as an indicator of soil fertility in grassland - an academic dilemma

Grasslands play an important role in conserving natural biodiversity and providing ecosystem functions and services for societies. Soil fertility is an important property in grassland, and the monitoring of soil fertility can provide crucial information to optimize ecosystem productivity and sustainability. Testing various soil physiochemical properties related to fertility usually relies on traditional measures, such as destructive sampling, pre-test treatments, labor-intensive procedures, and costly laboratory measurements, which are often difficult to perform. However, soil enzyme activity reflecting the intensity of soil biochemical reactions is a reliable indicator of soil properties and thus enzyme assays could be an efficient alternative to evaluate soil fertility. Here, we review the latest research on the features and functions of enzymes catalyzing the biochemical processes that convert organic materials to available plant nutrients, increase soil carbon and nutrient cycling, and enhance microbial activities to improve soil fertility. We focus on the complex relationships among soil enzyme activities and functions, microbial biomass, physiochemical properties, and soil/crop management practices. We highlight the biochemistry of enzymes and the rationale for using enzyme activities to indicate soil fertility. Finally, we discuss the limits and disadvantages of the potential new molecular tool and provide suggestions to improve the reliability and feasibility of the proposed alternative.

Divergent seasonal responses of above- and below-ground to environmental factors in alpine grassland

INTRODUCTION

Under current global warming, the relationship between season changes of plants and environmental factors is focused on high-elevation and latitude regions. Due to the desynchronized growth of above- and below-ground and the buffering of soil, the driving factors in leaf and root show seasonal dynamics.

METHODS

We measured above- and below-ground intensity in the alpine steppe over the non-growing season (October-April) and growing season (May-September). Air temperature, precipitation, soil moisture, and soil temperature were used to analyze the correlation based on the growth rhythm.

RESULTS

Results showed that an earlier growth in spring and a delayed dormancy in autumn of root than leaf was observed. Our results strongly suggest that soil moisture plays a more important role in leaf unfolding while temperature is consistent with the withering of the shoots. Soil moisture comes from soil melt driving the spring phenology of roots, which derived from the storage of the subsoil layer in the last autumn.

DISCUSSION

Climate change will affect the strong seasonal patterns that characterized these precipitation-limited systems, especially in the spring and fall shoulder seasons. As seasonality changes in the alpine steppe, divergent responses of leaf and fine root would be explored.

Revealing the dominant factors of vegetation change in global ecosystems

In the context of climate change, revealing the causes of significant changes in ecosystems will help maintain ecosystem stability and achieve sustainability. However, the dominant influencing factors of different ecosystems in different months on a global scale are not clear. We used Ordinary Least Squares Model and Mann–Kendall test to detect the significant changes (p < 0.05) of ecosystem on a monthly scale from 1981 to 2015. And then multi-source data, residual analysis and partial correlation method was used to distinguish the impact of anthropogenic activities and dominant climate factors. The result showed that: (1) Not all significant green areas in all months were greater than the browning areas. Woodland had a larger greening area than farmland and grassland, except for January, May, and June, and a larger browning area except for September, November, and December. (2) Anthropogenic activities are the leading factors causing significant greening in ecosystems. However, their impact on significant ecosystem browning was not greater than that of climate change on significant ecosystem greening in all months. (3) The main cause of the ecosystem’s significant greening was temperature. Along with temperature, sunshine duration played a major role in the significant greening of the woodland. The main causes of significant farmland greening were precipitation and soil moisture. Temperature was the main factor that dominated the longest month of significant browning of grassland and woodland. Temperature and soil moisture were the main factors that dominated the longest month of significant browning of farmland. Our research reveals ecosystem changes and their dominant factors on a global scale, thereby supporting the sustainable ecosystem management.

Optimal ranges of social-environmental drivers and their impacts on vegetation dynamics in Kazakhstan

Kazakhstan is part of the Eurasian Steppes, the world's largest contiguous grassland system. Kazakh grassland systems are largely understudied despite being historically important for agropastoral practices. These grasslands are considered vulnerable to anthropogenic activities and climatic variability. Few studies have examined vegetation dynamics in Central Asia owing to the complex impacts of moisture, climatic and anthropogenic forcings. A comprehensive analysis of spatiotemporal changes of vegetation and its driving factors will help elucidate the causes of grassland degradation. Here, we investigated the individual and pairwise interactive influences of various social-environmental system (SES) drivers on greenness dynamics in Kazakhstan. We sought to examine whether there is a relationship between peak season greenness and its drivers - spring drought, preceding winter freeze-thaw cycles, percent snow cover and snow depth - for Kazakhstan during 2000-2016. As hypothesized, snow depth and spring drought accounted for 60 % and 52 % of the variance in the satellite-derived normalized difference vegetation index (NDVI) in Kazakhstan. The freeze-thaw process accounted for 50 % of NDVI variance across the country. In addition, continuous thawing during the winter increased vegetation greenness. We also found that moisture and topographic factors impacted NDVI more significantly than socioeconomic factors. However, the impacts of socioeconomic drivers on vegetation growth were amplified when they interacted with environmental drivers. Terrain slope and soil moisture had the highest q-values or power of determinant, accounting for ~70 % of the variance in NDVI across the country. Socioeconomic drivers, such as crop production (59 %), population density (48 %), and livestock density (26 %), had significant impacts on vegetation dynamics in Kazakhstan. We found that most of the pairwise interactive influences of the drivers exhibited bi-factor enhancement, and the interaction between soil moisture and elevation was the largest (q = 0.92). Our study revealed the optimal ranges and tipping points of SES drivers and quantified the impacts of various driving factors on NDVI. These findings can help us identify the factors causing grassland degradation and provide a scientific basis for ecological protection in semiarid regions.

Impacts of climate change and human activities on different degraded grassland based on NDVI

Grassland degradation has emerged as a serious socio-economic and ecological problem, endangering both long-term usage and the regional biogeochemical cycle. Climate change and human activities are the two leading factors leading to grassland degradation. However, it is unclear what the degradation level caused by these two factors is. Using the normalized difference vegetation index (NDVI) and coefficient of variation of NDVI (CV_NDVI), the spatial distribution features of grassland degradation or restoration were analyzed in Qilian County in the northeast of the Qinghai–Tibet Plateau. The dominant climate variables affecting NDVI variation were selected through the combination of random forest model and stepwise regression method to improve the residual trend analysis, and on this basis, twelve possible scenarios were established to evaluate the driving factors of different degraded grasslands. Finally, used the Hurst index to forecast the trend of grassland degradation or restoration. The results showed that approximately 55.0% of the grassland had been degraded between 2000 and 2019, and the area of slight degradation (NDVI_slope > 0; CV_{NDVI (slope)} > 0; NDVI_value > 0.2) accounted for 48.6%. These regions were centered in the northwest of Qilian County. Climate and human activities had a joint impact on grassland restoration or degradation. Human activities played a leading role in grassland restoration, while climate change was primarily a driver of grassland degradation. The regions with slight degradation or re-growing (NDVI_slope > 0; CV_{NDVI (slope)} > 0), moderate degradation (NDVI_slope < 0; CV_{NDVI (slope)} > 0), and severe degradation or desertification (NDVI_slope < 0; CV_{NDVI (slope)} < 0) were dominated by the joint effects of climate and anthropogenic activity accounted for 34.3%, 3.3%, and 1.3%, respectively, of the total grassland area. Grasslands in most areas of Qilian County are forecasted to continue to degrade, including the previously degraded areas, with continuous degradation areas accounting for 54.78%. Accurately identifying the driving factors of different degraded grassland and predicting the dynamic change trend of grassland in the future is the key to understand the mechanism of grassland degradation and prevent grassland degradation. The findings offer a reference for accurately identifying the driving forces in grassland degradation, as well as providing a scientific basis for the policy-making of grassland ecological management.

Quantifying the contributions of climate change and human activities to vegetation dynamic in China based on multiple indices

Distinguishing the respective roles of climate change and anthropogenic activities can provide crucial information for sustainable management of the environment. Here, using the residual trend method (RESTREND), which measures the residue of the actual and potential trends of vegetation, we quantified the relative contributions of human activities (e.g., ecological restoration, overgrazing, and urbanization) and climate change (the warmer and wetter trend) to vegetation dynamics in China during 1988-2018 based on multiple vegetation indices, including the vegetation optical depth (Ku-VOD, C-VOD), normalized difference vegetation index (NDVI), and gross primary productivity (GPP). The results showed that the VOD, NDVI, and GPP exhibited overall increasing trends during 1988-2018. Human activities contributed >70% to the increases in NDVI and GPP in China, whereas a counterbalanced contribution of human activities and climate change was identified for the VOD dynamics (51% vs. 49%). Regions with high contributions from human activities to NDVI, GPP, and VOD were located in northeastern, southern, central, and northwestern China. In northern China, the positive impacts of human activities on NDVI (78%) and BEPS-GPP (83%) were greater than those of climate change. In contrast, human activities contributed 96% to the decrease in Ku-VOD over the same period. Before 2000, climate change promoted increases in GPP and NDVI in most regions of southern China. The increasing rates of GPP and NDVI accelerated after 2000 due to afforestation. However, human activities like overgrazing and urbanization have led to decreases in Ku-VOD in northern and southwestern China, and in C-VOD in northeastern, eastern, central, southwestern, and southern China. In all, the relative roles of climate and human factors varied in different regions when NDVI, GPP, or VOD were individually considered. Our results highlighted that the regional-scale vegetation conditions should be taken into full account to achieve sustainable management of ecosystems.

Increasing Impact of Precipitation on Alpine-Grassland Productivity over Last Two Decades on the Tibetan Plateau

Understanding the importance of temperature and precipitation on plant productivity is beneficial, to reveal the potential impact of climate change on vegetation growth. Although some studies have quantified the response of vegetation productivity to climate change at local, regional, and global scales, changes in climatic constraints on vegetation productivity over time are not well understood. This study combines the normalized difference vegetation index (NDVI) and the net primary production (NPP) modeled by CASA during the plant-growing season, to quantify the interplay of climatic (growing-season temperature and precipitation, GST and GSP) constraints on alpine-grassland productivity on the Tibetan Plateau, as well as the temporal dynamics of these constraints. The results showed that (1) 42.2% and 36.3% of grassland NDVI and NPP on the Tibetan Plateau increased significantly from 2000 to 2019. GSP controlled grassland growth in dryland regions, while humid grasslands were controlled by the GST. (2) The response strength of the NDVI and NPP to precipitation (partial correlation coefficient RNDVI-GSP and RNPP-GSP) increased substantially between 2000 and 2019. Especially, the RNDVI-GSP and RNPP-GSP increased from 0.14 and 0.01 in the first 10year period (2000–2009) to 0.83 and 0.78 in the second 10-year period (2010–2019), respectively. As a result, the controlling factor for alpine-grassland productivity variations shifted from temperature during 2000–2009 to precipitation during 2010–2019. (3) The increase in precipitation constraints was mainly distributed in dryland regions of the plateau. This study highlights that the climatic constraints on alpine-grassland productivity might change under ongoing climate change, which helps the understanding of the ecological responses and helps predict how vegetation productivity changes in the future.

Distinguishing the Impacts of Human Activities and Climate Change on the Livelihood Environment of Pastoralists in the Qinghai Lake Basin

Grassland vegetation is the largest terrestrial ecosystem in the Qinghai Lake Basin (QLB), and it is also the most important means of production for herders’ livelihoods. Quantifying the impact of climate change and human activities on grassland vegetation changes is an essential task for ensuring the sustainable livelihood of pastoralists. To this end, we investigated vegetation cover changes in the QLB from 2000 to 2020 using the normalized difference vegetation index (NDVI), meteorological raster data, and digital elevation and used residual analysis of multiple linear regression to evaluate the residuals of human activities. The residual analysis of partial derivatives was used to quantify the contribution of climate change and human activities to changes in vegetation cover. The results showed that: (1) The vegetation coverage of the QLB increased significantly (0.002/a, p < 0.01), with 91.38% of the area showing a greening trend, and 8.62% of the area suffering a degrading trend. The NDVI decreased substantially along the altitude gradient (−0.02/a, p < 0.01), with the highest vegetation coverage at 3600–3700 m (0.37/a). The vegetation degraded from 3200–3300 m, vegetation greening accelerated from 3300–3500 m, and vegetation greening slowed above 3500 m. (2) The contribution of climate change, temperature (T), and precipitation (P) to vegetation cover change were 1.62/a, 0.005/a, and 1.615/a, respectively. Below 3500 m, the vegetation greening was more limited by P. Above 3500 m, the vegetation greening was mainly limited by T. (3) Residual analysis showed that the contribution of human activities to vegetation cover was −1.618/a. Regarding the altitude gradient, at 3300–3500 m, human activities had the highest negative contribution to vegetation coverage (−2.389/a), and at 3200–3300 m, they had the highest positive contribution (0.389/a). In the past 21 years, the impact of human activities on vegetation coverage changed from negative to positive. Before 2009, the annual average NDVIres value was negative; after 2010, the average yearly NDVIres value turned positive. In general, the vegetation greening of the QLB depends on climate warming and humidification. The positive impact of human activities over the past decade was also essential for vegetation greening. These findings deepen our understanding of the QLB vegetation changes under climate change and human activities.

The Relative Roles of Climate Variation and Human Activities in Vegetation Dynamics in Coastal China from 2000 to 2019

Vegetation in the terrestrial ecosystem, sensitive to climate change and human activities, exerts a crucial influence on the carbon cycles in land, ocean, and atmosphere. Discrimination between climate and human-induced vegetation dynamics is advocated but still limited, especially in coastal China, which is characterized by a developed economy, a large population, and high food production, but also by unprecedented climate change and warming. Taking coastal China as the research area, our study used the normalized difference vegetation index (NDVI) in growing seasons, as well as precipitation, temperature, and sunlight hours datasets, adopted residual trend analysis at pixel and regional scales in coastal China from 2000–2019 and aims to (1) delineate the patterns and processes of vegetation changes, and (2) separate the relative contributions of climate and human activities by adopting residual trend analysis. The results indicated that (1) coastal China experienced the most vegetation greening (83.04% of the whole region) and partial degradation (16.86% of the whole region) with significant spatial heterogeneity; (2) compared with climate change, human activities have a greater positive impact on NDVI, and the regions were mainly located in the north of the North China Plain and the south of southern China; (3) the relative contribution rates of climate change and human activities were detected to be 0–60% and 60–100%, respectively; (4) in the northern coastal areas, the improvement of cultivated land management greatly promoted the greening of vegetation and thus the increase of grain yield, while in southern coastal areas, afforestation and the restoration of degraded forest were responsible for vegetation restoration; and (5) similar results obtained by partial correlation between nighttime lights and NDVI indicated the reliability of the residual trend analysis. The linear relationships of precipitation, temperature, and radiation on NDVI may limit the accurate estimation of climate drivers on vegetation, and further ecosystem process-modeling approaches can be used to estimate the relative contribution of climate change and human activities. The findings in our research emphasized that the attribution for vegetation dynamics with heterogeneity can provide evidence for the designation of rational ecological conservation policies.

Ecological Engineering Projects Shifted the Dominance of Human Activity and Climate Variability on Vegetation Dynamics

Global greening and its eco-environmental outcomes are getting mounting international focus. The important contribution of China to the global greening is highly appreciated. However, the basic driving forces are still elusive. The Loess Plateau (LP) and Three-River Source Region (TRSR) were chased as study areas in Northern China. The prior one represents the region experiencing intensive human interventions from ecological engineering projects, while the latter is a typical region that is experiencing faster climate change. Hypothesized to be driven by a disproportionate rate of human activities and climates, also being regions of typical large-scale ecological engineering projects, the study goal is to identify the actual driving forces on vegetation dynamics in these two regions. Trend analysis, correlation analysis, and residual trend-based method (RESTREND) were utilized to understand the relationships between climate variability, human activities, and vegetation dynamics. The spatiotemporal variations of vegetation from 1982 to 2019 were evaluated and the respective impacts of climatic and anthropogenic factors on vegetation dynamics were disentangled. Indicating apparent vegetation restoration in LP and TRSR, the results depict that annual LAI has remarkably increased during the 38 years. Temperature and precipitation promoted vegetation growth, whereas the solar radiation and vapor pressure deficit hampered it. After implementing the ecological engineering projects, the primary climatic factor changed from temperature to precipitation. Meanwhile, human activities act as the major driving factor in vegetation greening in the entire study area, with a contribution rate exceeding 70%. This information highlights that ecological engineering can significantly reduce the risks of ecosystem degradation and effectively restore vegetation, especially in ecologically sensitive and vulnerable areas.

Evaluation of Reasonable Stocking Rate Based on the Relative Contribution of Climate Change and Grazing Activities to the Productivity of Alpine Grasslands in Qinghai Province

An accurate assessment of the stocking rate is crucial for maintaining the stable function and the sustainable use of the alpine grassland ecosystem. A new scenario design method to evaluate the reasonable stocking rate is presented in the current work. First, climate change is quantified by potential net primary productivity (NPPp) and measured by adopting the Zhou Guangsheng model, and the NPP generated by anthropogenic activities (NPPh) is estimated by the distinction between NPPp and actual NPP (NPPa) calculated with the application of the Carnegie–Ames–Stanford Approach (CASA) model. Second, using the NPPh and actual grassland productivity consumed by livestock (NPPac), the reasonable stocking rate is obtained. Finally, the driving factors of NPP change in alpine grassland and the reasonable stocking rate are clarified in Qinghai Province during 2005–2018. The results reveal that the temperature of alpine grassland in Qinghai Province has a slight upward trend from 2005 to 2018, and precipitation displays a downward trend. The overall NPPp of alpine grassland demonstrated a downward trend, and precipitation is regarded as the major influencing factor. In addition, the overall NPPh of alpine grassland exhibited a downward trend. The NPPa demonstrated an overall upward trend, where 58.32% of the regional NPPa is in a state of growth, and 41.68% of the regional NPPa is in a state of degradation. According to contribution analysis, anthropogenic activities provided the primary driving factor to promote the restoration of alpine grassland in Qinghai Province. Moreover, the stocking rate must be reduced in 60.77% of the alpine grasslands in Qinghai Province, mostly situated in the eastern and southwestern parts of Qinghai Province, and the other areas must not increase future stocking rates. The current study can theoretically and technically support the construction of Qinghai as the green organic agricultural and livestock product demonstration province and the creation of an ecological civilization highland.

A Multi-Perspective Assessment Method with a Dynamic Benchmark for Human Activity Impacts on Alpine Ecosystem under Climate Change

Intense human activities and rapid climate changes both have obvious impacts on alpine ecosystems. However, the magnitudes and directions of the impacts by these two drivers remain uncertain due to a lack of a reasonable assessment method to distinguish between them. The impact of natural resilience is also generally included in the dynamics of a disturbed ecosystem and is liable to be mixed into the impact of human activity. It is urgent that we quantitatively discriminate human activity impacts on the ecosystem under climate change, especially for fast-developing alpine regions. Here, we propose an assessment method to determine human activity impacts under a dynamic climate, taking the potential net primary production (NPP) of an ecosystem as a benchmark. The potential NPP (NPPP) series under the changing climate was retrieved by an improved integrated biosphere simulator based on the initial disturbed ecosystem status of the assessment period. The actual NPP (NPPA) series monitored by remote sensing was considered as the results derived from the joint impacts of climate change, natural resilience and human activity. Then, the impact of human activity was quantified as the difference between the NPPP and NPPA. The contributions of human activity and natural forces to ecosystem NPP dynamics were then calculated separately and employed to explore the dominant driver(s). This assessment method was demonstrated in a typical alpine ecosystem in Northwest China. The results indicate that this method capably revealed the positive impacts of local afforestation and land-use optimization and the negative impacts caused by grazing during the assessment period of 2001–2017. This assessment method provides a quantitative reference for assessing the performances of ecological protections or human damage to alpine ecosystems at the regional scale.

Tracking Sustainable Restoration in Agro-Pastoral Ecotone of Northwest China

Large-scale ecological restoration (ER) projects have been implemented in northwest China in recent decades as a means to prevent desertification and improve ecosystem services. However, previous studies have demonstrated adverse impacts in the form of widespread soil water deficit caused by intensive ER activities. Understanding the role of climate change and ER efforts in vegetation dynamics and soil moisture consumption is essential for sustainable ecosystem management. Here, we used the break for additive season and trend (BFAST) method to analyse spatial patterns in the normalized difference vegetation index (NDVI) variation over the agro-pastoral ecotone of northwest China (APENC) for 2000–2015. From the combined use of generalized additive modelling (GAM) and residual-trend analysis (RESTREND), we distinguished and quantified the effects of climate and human management on vegetation and soil water dynamics. Approximately 78% of the area showed vegetation variations representing a significant change in NDVI, of which more than 68% were categorized as abrupt changes. Large areas of the abrupt change type, interrupted increase and monotonic increase in NDVI were observed before 2006, and small areas of the change type of negative reversals were observed after 2012. Anthropogenic activity was found to be the major driving factor of variation in vegetation (contribution rate of 56%) and soil moisture (contribution rate of 78%). The vegetation expansion, which was mainly related to the large number of ER programs that started in 2000, was found to increase soil moisture depletion. By comparing areas where anthropogenic activities had a high contribution rate to vegetation increase and areas where soil moisture consumption was severely increased, we identify and discuss hotspot areas of soil moisture consumption caused by the ER programs. The current methodological workflow and results represent a novel foundation to inform and support water resource management and ecological-restoration-related policy making.