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With the rapid accumulation of plant trait data, major opportunities have arisen for the integration of these data into predicting ecosystem primary productivity across a range of spatial extents. Traditionally, traits have been used to explain physiological productivity at cell, organ, or plant scales, but scaling up to the ecosystem scale has remained challenging. Here, we show the need to combine measures of community-level traits and environmental factors to predict ecosystem productivity at landscape or biogeographic scales. We show how theory can extend the production ecology equation to enormous potential for integrating traits into ecological models that estimate productivity-related ecosystem functions across ecological scales and to anticipate the response of terrestrial ecosystems to global change. ispartof: TRENDS IN PLANT SCIENCE vol:28 issue:1 pages:43-53 ispartof: location:England status: published

Half of all of China's lakes are on the Qinghai-Tibet Plateau (QTP), which are mainly distributed at altitudes above 4000 m asl. Being under conditions of progressively intensifying anthropogenic activities and climate change, the debate on whether QTP lakes act as carbon (C) sinks or sources remains unresolved. This study explores QTP lake C exchange processes and characteristics over the past two decades through field monitoring and data integration. Results reveal high lake carbon dioxide (CO

Photosynthetically carbon (C) allocation largely determines yield and C sequestration of agroecosystem. However, how C allocation of crops responses to climate change at the long-time scale is poorly defined. Combining thirteen years of eddy covariance and inventory measurements, we comprehensively investigated C allocation mechanism in a winter-wheat and summer-maize double cropping field. Significantly increased gross primary production (GPP) was benefited from CO2 fertilization, and 35% of increased GPP transferred to strengthening C sequestration. However, elevated temperature and drying surface soil moisture stimulated the partitioning of GPP to autotrophic respiration, resulted in conservative net primary production and grain yield. Maize faced a greater risk of C loss and yield reduction than wheat to warming and drying. By synthesizing published long-term data of agroecosystems, we further highlight that the GPP partitioning cannot be simply predicted by allometric theory, particularly for grains, which should be considered in predicting C budget and crop yield.

The Tibetan Plateau is generally referred to as the Chinese water tower, and evapotranspiration (ET) affects the water budget and stability of alpine meadows on the Tibetan Plateau. However, its variability and controlling mechanisms have not been well documented under the drier conditions induced by global warming. Therefore, this study aimed to clarify whether meteorological or biological factors primarily affected the variability in ET under contrasting water conditions in the alpine meadow ecosystem on the Tibetan Plateau. Based on 6-year (2013–2018) eddy covariance observations and the corresponding meteorological and biological data, linear perturbation analyses were employed to isolate the contributions of meteorological and biological factors to the variability in evapotranspiration (δET). The results showed that δET was mainly driven by meteorological factors in wet peak seasons (July and August), and was dominated by net radiation (Rn) and air temperature (Ta), indicating that the inadequate available energy is the factor limiting ET. However, the dominant factors affecting δET shifted from meteorological to biological in dry peak seasons when the canopy stomatal conductance (gs) and leaf area index were dominant. At this point, the ecosystem was limited by the water conditions. These results provide empirical insights into how meteorological and biological factors regulate variability in ET under contrasting water conditions. These findings can further improve our understanding of water cycle processes and can help effectively manage water resources in alpine meadow ecosystems under future climate change conditions.

The alpine meadow ecosystem in Tibet is fragile and sensitive, and its carbon sink function with respect to climate change has become a matter of widespread concern. Therefore, this study aims to clarify the inter-annual variations (IAVs) in the carbon fluxes in an alpine meadow and to further quantify the contributions of the driving factors to the IAVs. Based on 7 years of flux data (2012–2018) and the corresponding climatic and biotic data, a set of look-up tables was used to separate and quantify the IAV sources. Furthermore, linear perturbation analyses were employed to quantify the contributions of each key factor. During 2012–2018, the net ecosystem productivity (NEP), gross primary productivity (GPP) and ecosystem respiration (Re) of this alpine meadow were 3.31 ± 26.90, 210.18 ± 48.35 and 206.88 ± 28.45 g C m−2 y−1, respectively, which indicated relatively large IAVs. When the contributions of climatic and biotic effects were distinguished and quantified, the dominant effects of biotic factors emerged. Additionally, negative interactions between climatic and biotic effects were detected. Among the climatic factors, only soil water content contributed relatively more to the IAVs and played a role in regulating the interactions between climatic and biotic effects. These results suggest that biotic effects must be carefully considered to reduce the uncertainties associated with future carbon flux estimates.

Iron (Fe), molybdenum (Mo), and vanadium (V) are the main components of the three known biological nitrogenases, which constrain nitrogen fixation and affect ecosystem productivity. Atmospheric deposition is an important pathway of these trace metals into ecosystems. Here, we explored the deposition flux, spatiotemporal pattern, and influencing factors of atmospheric wet Fe, Mo, and V deposition based on China Wet Deposition Observation Network (ChinaWD) data from 2016 to 2020. Our results showed that atmospheric wet Fe, Mo, and V deposition was 7.77 ± 7.24, 0.16 ± 0.11, and 0.13 ± 0.12 mg m

Litter comprises a major nutrient source when decomposed via soil microbes and functions as subtract that limits gas exchange between soil and atmosphere, thereby restricting methane (CH4) uptake in soils. However, the impact and inherent mechanism of litter and its decomposition on CH4 uptake in soils remains unknown in forest. Therefore, to declare the mechanisms of litter input and decomposition effect on the soil CH4 flux in forest, this study performed a litter-removal experiment in a tropical rainforest, and investigated the effects of litter input and decomposition on the CH4 flux among forest ecosystems through a literature review. Cumulative annual CH4 flux was -3.30 kg CH4-C ha

Silicon (Si) is considered a "quasi-essential" nutrient element for plants and is also an essential nutrient for some phytoplankton. Except for the silicate provided by weathering, atmospheric deposition has gradually become an important supplementary method for Si nutrients to enter the ecosystem. However, national observational studies on atmospheric silicon deposition have not yet been reported. Herein, based on the China Wet Deposition Observation Network, we continuously collected monthly wet deposition samples from 43 typical ecosystems from 2013 to 2020 and measured the content of dissolved silica (dSi) in precipitation to quantify the spatiotemporal patterns of Si wet deposition in China. The results showed that the mean annual dSi wet deposition in China during 2013-2020 was approximately 2.07 ± 0.27 kg ha

Drylands play major roles in the terrestrial carbon cycle and mitigation of climate change. Understanding the dynamics of soil organic carbon (SOC) stocks under land use change and management is essential for achieving soil C sequestration through land-based solutions for drylands. In this paper, we briefly reviewed the literature to evaluate the impact of land use change and management on dryland SOC stocks. While the site-level field measurements of SOC stocks under different types of land use change and land management are remarkable, we found that the impact is hardly quantified at the regional level using selected soil datasets or process models and may be due to insufficient data quality, representativeness and information availability, which are among the major challenges of upscaling from field measurements to estimating regional SOC stocks. Therefore, we proposed a comprehensive framework following the IPCC inventory approach to improve future studies, which underlines the needs of data collection from multiple sources, meta-analysis for calculating SOC stock change factors, and matching land and soil datasets.

Chinese forests cover most of the representative forest types in the Northern Hemisphere and function as a large carbon (C) sink in the global C cycle. The availability of long-term C dynamics observations is key to evaluating and understanding C sequestration of these forests. The Chinese Ecosystem Research Network has conducted normalized and systematic monitoring of the soil-biology-atmosphere-water cycle in Chinese forests since 2000. For the first time, a reference dataset of the decadal C cycle dynamics was produced for 10 typical Chinese forests after strict quality control, including biomass, leaf area index, litterfall, soil organic C, and the corresponding meteorological data. Based on these basic but time-discrete C-cycle elements, an assimilated dataset of key C cycle parameters and time-continuous C sequestration functions was generated via model-data fusion, including C allocation, turnover, and soil, vegetation, and ecosystem C storage. These reference data could be used as a benchmark for model development, evaluation and C cycle research under global climate change for typical forests in the Northern Hemisphere., Measurement(s) photosynthetically active radiation • biomass • plant litter • leaf area index • soil organic carbon • CO2 flux • carbon cycling • temperature of air • rain • humidity of soil • humidity of air Technology Type(s) Sensor Device • forest inventory • litter trap • soil coring • eddy covariance • data assimilation Factor Type(s) plot Sample Characteristic - Environment forest biome Sample Characteristic - Location China Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.13348154

Food, energy, and water (FEW) systems have been recognized as an issue of critical global importance. Understanding the mechanisms that govern the FEW nexus is essential to develop solutions and avoid humanitarian crises of displacement, famine, and disease. The U.S. and China are the world's leading economies. Although the two nations are shaped by fundamentally different political and economic systems, they share FEW trajectories in several complementary ways. These realities place the U.S. and China in unique positions to engage in problem definition, dialogue, actions, and transdisciplinary convergence of research to achieve productive solutions addressing FEW challenges. By comparing the nexus and functions of the FEW systems in the two nations, this perspective aims to facilitate collaborative innovations that reduce disciplinary silos, mitigate FEW challenges, and enhance environmental sustainability. The review of experiences and challenges facing the U.S. and China also offers valuable insights for other nations seeking to achieve sustainable development goals.

Functional traits are frequently used to evaluate plant adaptation across environments. Yet, traits tend to have multiple functions and interactions, which cannot be accounted for in traditional correlation analyses. Plant trait networks (PTNs) clarify complex relationships among traits, enable the calculation of metrics for the topology of trait coordination and the importance of given traits in PTNs, and how they shift across communities. Recent studies of PTNs provide new insights into some important topics, including trait dimensionality, trait spectra (including the leaf economic spectrum), stoichiometric principles, and the variation of phenotypic integration along gradients of resource availability. PTNs provide improved resolution of the multiple dimensions of plant adaptation across scales and responses to shifting resources, disturbance regimes, and global change.

The high uncertainty associated with the response of terrestrial carbon (C) cycle to climate is dominated by ecosystem C turnover time (τeco). Although the relationship between τeco and climate has been extensively studied, significant knowledge gaps remain regarding the differential climate sensitivities of turnover time in major biomass (τveg) and soil (τsoil) pools, and their effects on vegetation and soil C sequestration under climate change are poorly understood. Here, we collected multiple time-series observations on soil and vegetation C from permanent plots in ten Chinese forests and used model-data fusion to retrieve key C cycle process parameters that regulate τsoil and τveg. Our analysis showed that 𝜏veg and 𝜏soil both decreased with increasing temperature and precipitation, and τsoil was more than twice as sensitive (1.27 yr/°C, 1.70 yr/100 mm) than τveg (0.53 yr/°C, 0.40 yr/100 mm). The higher climate sensitivity of τsoil caused a more rapid decrease in τsoil than in τveg with increasing temperature and precipitation, thereby significantly reducing the difference between τsoil and τveg (τdiff) under warm and humid conditions. τdiff, an indicator of the balance between the soil C input and exit rate, was strongly responsible for the variation (more than 50%) in soil C sequestration. Therefore, a smaller τdiff under warm and humid conditions suggests a relatively lower contribution from soil C sequestration. This information has strong implications for understanding forest C-climate feedback, predicting forest C sink distributions in soil and vegetation under climate change, and implementing C mitigation policies in forest plantations or soil conservation.

Most ecological and environmental issues faced by human society can only be solved at the ecosystem, watershed, regional and even global scale. Thus, ecological research is developing rapidly towards macro-scale studies. With the rapid development of observational networks and information technology, the spaceborne-aircraft-ground based observation system is becoming an important feature of ecosystem monitoring in the new era. With the gradual formation of the global new-generation observational systems and the rapid expansion of massive multi-source heterogeneous data, ecology has entered the era of big data, big science, and big theory. How to integrate ecological big data, discover valuable ecological laws and mechanisms, and further expand them to solve eco-environmental issues that closely relate to human development are the major opportunities and challenges in this field. In this paper, we systematically summarized the research progresses in ecological big data, reviewed the opportunity and demand of integrative ecology, and further discussed the main approaches of ecological big data integration by using meta-analysis, data mining, and data-model fusion. Finally, we proposed the prospects and research directions of in-tegrative ecology and suggested that future researches need to integrate big data into land models so as to improve the accuracy of ecological forecasting. It can be foreseen that under the background of global change and the rapid development of big data in the future, integrative ecology will be extensively applied and developed to serve the sustainable development of human society.

From a molecular level to an ecosystem scale, different coupling mechanisms take place during coupled carbon-nitrogen-water (C-N-H2O) cycles, of which essential are water flux and related biogeochemical processes through physicochemical reactions associated with terrestrial and aquatic ecosystems. Meanwhile, regional coupled C-N-H2O cycle will subsequently impact regional gross primary productivity (GPP) and C and N exchanges during air-water interactions that occur downstream of watersheds. This study aimed to first synthetically analyze the regional dynamics of C, N and H2O cycles in ecosystems and determine their interactional relationships; second, to specify regional C-N-H2O coupled relationships of ecosystems and their theoretical ecological principles; third, to classify coupled regional response and adaptation of the C-N-H2O cycle to climatic and environmental changes under anthropogenic activities, providing a theoretical basis to fully understand and make adjustments to interactional C, N and H2O cycling relationships at different ecosystem scales and under associated coupling processes.

Carbon (C) and nitrogen (N) are the primary elements involved in the growth and development of plants. The C:N ratio is an indicator of nitrogen use efficiency (NUE) and an input parameter for some ecological and ecosystem models. However, knowledge remains limited about the convergent or divergent variation in the C:N ratios among different plant organs (e.g., leaf, branch, trunk, and root) and how evolution and environment affect the coefficient shifts. Using systematic measurements of the leaf-branch-trunk-root of 2,139 species from tropical to cold-temperate forests, we comprehensively evaluated variation in C:N ratio in different organs in different taxa and forest types. The ratios showed convergence in the direction of change but divergence in the rate of change. Plants evolved toward lower C:N ratios in the leaf and branch, with N playing a more important role than C. The C:N ratio of plant organs (except for the leaf) was constrained by phylogeny, but not strongly. Both the change of C:N during evolution and its spatial variation (lower C:N ratio at midlatitudes) help develop the adaptive growth hypothesis. That is, plants with a higher C:N ratio promote NUE under strong N-limited conditions to ensure survival priority, whereas plants with a lower C:N ratio under less N-limited environments benefit growth priority. In nature, larger proportion of species with a high C:N ratio enabled communities to inhabit more N-limited conditions. Our results provide new insights on the evolution and drivers of C:N ratio among different plant organs, as well as provide a quantitative basis to optimize land surface process models.

Ecological restoration is essential to reverse land degradation worldwide. Most studies have assessed the restoration of ecosystem functions individually, as opposed to a holistic view. Here we developed a network-based ecosystem multifunctionality (EMF) framework to identify key functions in evaluating EMF restoration. Through synthesizing 293 restoration studies (2900 observations) following cropland abandonment, we found that individual soil functions played different roles in determining the restoration of belowground EMF. Soil carbon, total nitrogen, and phosphatase were key functions to predict the recovery of belowground EMF. On average, abandoned cropland recovered ~19% of EMF during 18 years. The restoration of EMF became larger with longer recovery time and higher humidity index, but lower with increasing soil depth and initial soil carbon. Overall, this study presents a network-based EMF framework, effectively helping to evaluate the success of ecosystem restoration and identify the key functions.

Precipitation-use efficiency (PUE) is an important ecosystem indicator of the efficiency of carbon–water conversion. The trend and interannual variation of precipitation-use efficiency (PUE) response to climatic factors provide a theoretical foundation for understanding how Eurasian grasslands adapt to climate change. However, the long-term trends and regulating factors of PUE in Eurasian grasslands at the continental scale are still unclear. Here, we integrated long-term Global Inventory Monitoring and Modeling System (GIMMS) Normalized Difference Vegetation Index (NDVI), field surveys of aboveground net primary production (ANPP) and meteorological datasets during 1982–2015 to reveal the temporal variations and controls of PUE in Eurasian grasslands. We found that there was an overall uptrend of PUE (3 × 10−3 g C m−2 mm−1/10 yr) in Eurasian grasslands. The greatest increasing trends of PUE was found in forest steppe at the rate of 13 × 10−3 g C m−2 mm−1/10 yr, while greatest decreasing trend presented in alpine steppe at the rate of −2.6 × 10−3 g C m−2 mm−1/10 yr. The PUE showed linearly decreasing patterns with precipitation at the biome and continental scales, while it was uncorrelated with temperature at the continental scale and showed diverse patterns of linear increase, concave-down and no correlation with temperature for different biomes. The temporal variation of PUE was mainly controlled by precipitation in Eurasian grasslands. This result further revealed that climatic factors shaped the temporal pattern of PUE by the cascading effects networks of climatic factors (precipitation and temperature) − vapor pressure deficit (VPD) – leaf area index (LAI) – ANPP – PUE (CVLP-CENet). This study identified the long-term trends, interannual variations and controls of PUE in Eurasian grasslands over the past three decades, and provided crucial insights into understanding grassland ecosystems dynamics and response to climate change.

Compared to the well-known drivers of spatial variability in gross primary productivity (GPP), the relative importance of climatic variables, soil properties and plant traits to the spatial variability in net ecosystem exchange of CO2 between terrestrial ecosystem and atmosphere (NEE) is poorly understood. We used principal component regression to analyze data from 147 eddy flux sites to disentangle effects of climatic variables, soil properties and plant traits on the spatial variation in annual NEE and its components (GPP and ecosystem respiration (RE)) across global forests and grasslands. Our results showed that the largest unique contribution (proportion of variance only explained by one class of variables) to NEE variance came from climatic variables for forests (24%-30%) and soil properties for grasslands (41%-54%). Specifically, mean annual precipitation and potential evapotranspiration were the most important climatic variables driving forest NEE, whereas available soil water capacity, clay content and cation exchange capacity mainly influenced grassland NEE. Plant traits showed a small unique contribution to NEE in both forests and grasslands. However, leaf phosphorus content strongly interacted with soil total nitrogen density and clay content, and these combined factors represented a major contribution for grassland NEE. For GPP and RE, the majority of spatial variance was attributed to the common contribution of climate, soil and plant traits (50% - 62%, proportion of variance explained by more than one class of variables), rather than their unique contributions. Interestingly, those factors with only minor influences on GPP and RE variability (e.g., soil properties) have significant contributions to the spatial variability in NEE. Such emerging factors and the interactions between climatic variables, soil properties and plant traits are not well represented in current terrestrial biosphere models, which should be considered in future model improvement to accurately predict the spatial pattern of carbon cycling across forests and grasslands globally.

Global warming has significantly altered the distribution and productivity of vegetation owing to shifts in plant functional traits. However, chlorophyll adaptations—good representative of plant production—in grasslands have not been investigated on a large scale, hindering ecological predictions of climate change. Three grassland transects with a natural temperature gradient were designed in the Tibetan, Mongolian, and Loess Plateau to describe the changes in chlorophyll under different warming scenarios for 475 species. In the three plateaus, variations and distributions of species chlorophyll concentration and composition were compared. The results showed that the means of chlorophyll concentration and composition (chlorophyll a/b) increased with the mean annual temperature. Still, their distributions shifted in opposite manners: chlorophyll concentration was distributed in a broader but more differential manner, while chlorophyll composition was distributed in a narrower but more uniform manner. Compared to chlorophyll concentration, chlorophyll composition was more conservative, with a slight shift in distribution. At the regional level, the chlorophyll concentration and composition depend on the limitations of the local climate or resources. The results implied that warming might drive shifts in grassland chlorophyll distribution mainly by alternations in species composition. Large-scale chlorophyll investigations will be useful for developing prediction techniques.

Drylands refer to regions with an aridity index lower than 0.65, and billions of people depend on services provided by the critically important ecosystems in these areas. How ecosystem carbon exchange in global drylands (CED) occurs and how climate change affects CED are critical to the global carbon cycle. Here, we performed a comprehensive bibliometric study on the fields of annual publications, marked journals, marked institutions, marked countries, popular keywords, and their temporal evolution to understand the temporal trends of CED research over the past 30 a (1991–2020). We found that the annual scientific publications on CED research increased significantly at an average growth rate of 7.93%. Agricultural Water Management ranked first among all journals and had the most citations. The ten most productive institutions were centered on drylands in America, China, and Australia that had the largest number and most citations of publications on CED research. “Climate change” and climate-related (such as “drought”, “precipitation”, “temperature”, and “rainfall”) research were found to be the most popular study areas. Keywords were classified into five clusters, indicating the five main research focuses on CED studies: hydrological cycle, effects of climate change, carbon and water balance, productivity, and carbon-nitrogen-phosphorous coupling cycles. The temporal evolution of keywords further showed that the areas of focus on CED studies were transformed from classical pedology and agricultural research to applied ecology and then to global change ecological research over the past 30 a. In future CED studies, basic themes (such as “water”, “yield”, and “salinity”) and motor themes (such as “climate change”, “sustainability”, and “remote sensing”) will be the focus of research on CED. In particular, multiple integrated methods to understand climate change and ecosystem sustainability are potential new research trends and hotspots.

Forestation is important for sequestering atmospheric carbon, and it is a cost-effective and nature-based solution (NBS) for mitigating global climate change. Here, under the assumption of forestation in the potential plantable lands, we used the forest carbon sequestration (FCS) model and field survey involving 3365 forest plots to assess the carbon sequestration rate (CSR) of Chinese existing and new forestation forests from 2010 to 2060 under three forestation and three climate scenarios. Without considering the influence of extreme events and human disturbance, the estimated average CSR in Chinese forests was 0.358 ± 0.016 Pg C a

Nitrogen (N) deposition is a component of global change that has considerable impact on belowground carbon (C) dynamics. Plant growth stimulation and alterations of fungal community composition and functions are the main mechanisms driving soil C gains following N deposition in N-limited temperate forests. In N-rich tropical forests, however, N deposition generally has minor effects on plant growth; consequently, C storage in soil may strongly depend on the microbial processes that drive litter and soil organic matter decomposition. Here, we investigated how microbial functions in old-growth tropical forest soil responded to 13 years of N addition at four rates: 0 (Control), 50 (Low-N), 100 (Medium-N), and 150 (High-N) kg N ha-1 year-1 . Soil organic carbon (SOC) content increased under High-N, corresponding to a 33% decrease in CO2 efflux, and reductions in relative abundances of bacteria as well as genes responsible for cellulose and chitin degradation. A 113% increase in N2 O emission was positively correlated with soil acidification and an increase in the relative abundances of denitrification genes (narG and norB). Soil acidification induced by N addition decreased available P concentrations, and was associated with reductions in the relative abundance of phytase. The decreased relative abundance of bacteria and key functional gene groups for C degradation were related to slower SOC decomposition, indicating the key mechanisms driving SOC accumulation in the tropical forest soil subjected to High-N addition. However, changes in microbial functional groups associated with N and P cycling led to coincidentally large increases in N2 O emissions, and exacerbated soil P deficiency. These two factors partially offset the perceived beneficial effects of N addition on SOC storage in tropical forest soils. These findings suggest a potential to incorporate microbial community and functions into Earth system models considering their effects on greenhouse gas emission, biogeochemical processes, and biodiversity of tropical ecosystems.

Grazing is the primary land use practice in alpine ecosystems on the Tibetan Plateau. However, it remains unclear how grazing regulates levels of carbon and the water cycle in this ecosystem. A paired set of eddy covariance systems were set in adjacent fenced (FM) and grazed meadows (GM) to explore the grazing effects on alpine meadows. Aboveground biomass removed by grazing caused declines in grass transpiration (T), whereas the evaporation (E) was enhanced because of greater exposure to radiation, which in turn led to higher evapotranspiration (ET) in GM. However, the deep-layer soil moisture remained high because of the effects of mattic epipedon, which worked as a water-resistant layer. Therefore, the deep-layer soil moisture in GM was higher than that in FM because of decreased water consumption caused by the grazing-induced reduction in leaf area in GM. As a consequence, the deep-layer soil in GM could provide more water to help plants endure droughts. Additionally, grazing enhanced the sensitivity of productivity to soil moisture during the wet season in drought years, which could restore grassland productivity more quickly after droughts. Therefore, grazing could help this fragile ecosystem to withstand droughts to some extent and maintain higher productivity. This may provide us with an ecological approach for confronting global climate change.

Aims Evapotranspiration (ET) is an important component of the terrestrial water cycle and is easily affected by external disturbances, such as climate change and grazing. Identifying ET responses to grazing is instructive for determining grazing activity and informative for understanding the water cycle. Methods This study utilized 2 years (2014 and 2017) of eddy covariance data to test how grazing regulated ET for an alpine meadow ecosystem on the Tibetan Plateau (TP) by path analysis. Important Findings Radiation dominated ET with a decision coefficient of 64–74%. The soil water content (SWC) worked as the limiting factor in the fenced site. However, in the grazing site, the limiting factor was the vapor pressure deficit (VPD). Grazing had large effects on ET because it greatly affected the water conditions. The SWC and VPD were enhanced by 14.63% and 4.36% in the grazing site, respectively. Therefore, sufficient water was supplied to ET, especially during drought, and strengthened the transpiration pull. As a result, a favorable micrometeorological environment was created for ET. Grazing shifted the limiting factor of ET from the SWC to VPD, which weakened the limiting effect of the water conditions on ET and advanced the ET peak time. In addition, grazing altered the compositions of ET by changing the community structure, which directly resulted in an increased ET. In summary, grazing enhanced ET through altering the community structure and micrometeorological environments. The findings of this study further improve our understanding of the driving mechanisms of grazing on ET and will improve our predictions for the global water cycle.