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There is growing evidence that land‐use management practices such as livestock grazing can strongly impact the local diversity, functioning, and stability of grassland communities. However, whether these impacts depend on environmental condition and propagate to larger spatial scales remains unclear. Using an 8‐year grassland exclosure experiment conducted at nine sites in the Tibetan Plateau covering a large precipitation gradient, we found that herbivore exclusion increased the temporal stability of alpine grassland biomass production at both the local and larger (site) spatial scales. Higher local community stability was attributed to greater stability of dominant species, whereas higher stability at the larger scale was linked to higher spatial asynchrony of productivity among local communities. Additionally, sites with higher mean annual precipitation had lower dominant species stability and lower grassland stability at both the spatial scales considered. Our study provides novel evidence that livestock grazing can impair grassland stability across spatial scales and climatic gradients. [ABSTRACT FROM AUTHOR]

Despite the mounting attention being paid to vegetation growth and their driving forces for water-limited ecosystems, the relative contributions of atmospheric and soil moisture dryness stress on vegetation growth are an ongoing debate. Here we comprehensively compare the impacts of high vapor pressure deficit (VPD) and low soil water content (SWC) on vegetation growth in Eurasian drylands during 1982–2014. The analysis indicates a gradual decoupling between atmospheric dryness and soil dryness over this period, as the former has expanded faster than the latter. Moreover, the VPD–SWC relation and VPD–greenness relation are both non-linear, while the SWC–greenness relation is near-linear. The loosened coupling between VPD and SWC, the non-linear correlations among VPD–SWC-greenness and the expanded area extent in which SWC acts as the dominant stress factor all provide compelling evidence that SWC is a more influential stressor than VPD on vegetation growth in Eurasian drylands. In addition, a set of 11 Earth system models projected a continuously growing constraint of SWC stress on vegetation growth towards 2100. Our results are vital to dryland ecosystems management and drought mitigation in Eurasia. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) is one of the most important areas for the study of the carbon budgets of terrestrial ecosystems. However, the estimation of the net ecosystem productivity (NEP) remains uncertain in this region due to its complex topographic properties and climatic conditions. Using CO2-eddy-covariance-flux data from 1982 to 2018 at 18 sites distributed around the TP grassland, we analyzed the spatial–temporal patterns of the grassland NEP and its driving factors from 1982 to 2018 using a random forest (RF) model. Our results showed that the RF model captured the size of the carbon sink (R2 = 0.65, p < 0.05) between the observed and simulated values for the validation samples. During the observation period, the grassland acted as a carbon sink of 26.2 Tg C yr−1 and increased significantly, by 0.4 g C m−2 yr−1. On a regional scale, the annual NEP gradually increased from the northwest to the southeast, and a similar pattern was also observed in the long-term trends. Furthermore, the moisture conditions, such as the specific humidity and precipitation, were proven to be the main driving factors of the carbon flux in the southeastern areas, while the temperature predominantly controlled the carbon flux in the northwest. Our results emphasize the net carbon sink of the TP and provide a reliable way to upscale NEP from sites. [ABSTRACT FROM AUTHOR]

Wet sieving is a common practice used to treat soil samples before analyses. However, slaking might occur during wet sieving, and this significantly affects analytical accuracy. To minimize side effects caused by slaking, we treated soils with ethanol and investigated the resulting efficiencies. Soil aggregates from the black soil zone of northeast China were selected as the study objects. In combination with Yoder's traditional wet‐sieving method, ethanol‐soaked aggregates were exposed to air under three different conditions (no exposure, brief exposure, and long‐term exposure) to assess whether slaking could be eliminated during wet sieving and to clarify whether slaking would reoccur when ethanol‐soaked aggregates were exposed to air. The results showed that soaking aggregates in ethanol fully eliminated the entrapped air and that the slaking effect was completely prevented during wet sieving. Compared with Yoder's wet‐sieving method, ethanol soaking increased the mass percentages of aggregates sized >2 and 2–1 mm by 51.06 and 3.67%, respectively. Regardless of whether the sample was exposed to air, patterns of the size distributions of ethanol‐soaked aggregates remained unchanged after wet sieving. When ethanol‐soaked aggregates were briefly exposed to air, there was no apparent slaking effect. Nevertheless, because the aggregates were soaked in ethanol, the internal structure of the aggregates was reinforced and the aggregates were not evidently dispersed and broken despite slight slaking during wet sieving. These findings provide a reference for studying water‐stable aggregates and improving measurement accuracies. Core Ideas: Soaking aggregates in alcohol eliminates slaking effects during wet sieving.Compared with Yoder's wet sieving method, alcohol soaking increased aggregates >1 mm.With or without exposure to air, size distributions of aggregates remained unchanged.The study provides a reference for improving accuracy in measurement of water‐stable aggregates. [ABSTRACT FROM AUTHOR]

• Elevated CO 2 significantly advanced spring phenology in kobresia pygmaea. • Alpine plants on the tibetan plateau are more sensitive to elevated CO 2. • Elevated CO 2 reduced overlapping flowering between species. • Advancement in K. pygmaea's phenology was linked to higher water-use efficiency. Phenological changes in global vegetation are often attributed to climate warming. However, climate warming and elevated atmospheric CO 2 concentration (e CO 2) are two co-occurring global change factors, and how e CO 2 would affect vegetation phenology has received less attention. The partial pressure of atmospheric CO 2 on the Tibetan Plateau (TP) is lower than that in regions of lower altitudes. Consequently, the growth and phenology of alpine plants in this region could be more sensitive to e CO 2 , but this hypothesis is not yet supported by empirical evidence. Here we explored the effect of e CO 2 on plant phenology (including phenophases of green-up, budding, and flowering) through a 5-year field manipulation experiment in a high-altitude (4600 m above sea level) alpine grassland on the TP. Our results showed that e CO 2 significantly advanced the spring phenology of an early-flowering species (Kobresia pygmaea), while it had no impact on the phenology of two mid-flowering species (Potentilla saundersiana and Potentilla cuneata). Compared to other low-altitude regions, plant phenology on the TP underwent greater alterations under e CO 2 , which supports our hypothesis that the growth of high-altitude plants is more sensitive to e CO 2. Furthermore, we found that e CO 2 significantly reduced the overlapping of flowering between contrasting plant species, mainly due to the phenological advancement of the K. pygmaea induced by e CO 2. The observed advancement of the spring phenology in K. pygmaea under e CO 2 was associated with increasing ecosystem water-use efficiency (WUE), thereby advancing its subsequent phenological development, such as budding and flowering. Our findings provide experimental evidence that atmospheric CO 2 enrichment can accelerate plant growth processes in high-altitude regions, and suggest that large-scale model simulations should consider the effects of elevated atmospheric CO 2 concentration on plant growth and phenology. [Display omitted] [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

It is hard for current time series reconstruction methods to achieve the balance of high-precision time series reconstruction and explanation of the model mechanism. The goal of this paper is to improve the reconstruction accuracy with a well-explained time series model. Thus, we developed a function-based model, the CCTM (Continuous Change Tracker Model) model, that can achieve high precision in time series reconstruction by tracking the time series variation rate. The goal of this paper is to provide a new solution for high-precision time series reconstruction and related applications. To test the reconstruction effects, the model was applied to four types of datasets: normalized difference vegetation index (NDVI), gross primary productivity (GPP), leaf area index (LAI), and MODIS surface reflectance (MSR). Several new observations are as follows. First, the CCTM model is well explained and based on the second-order derivative theorem, which divides the yearly time series into four variation types including uniform variations, decelerated variations, accelerated variations, and short-periodical variations, and each variation type is represented by a designed function. Second, the CCTM model provides much better reconstruction results than the Harmonic model on the NDVI, GPP, MSR, and LAI datasets for the seasonal segment reconstruction. The combined use of the Savitzky–Golay filter and the CCTM model is better than the combinations of the Savitzky–Golay filter with other models. Third, the Harmonic model has the best trend-fitting ability on the yearly time series dataset, with the highest R-Square and the lowest RMSE among the four function fitting models. However, with seasonal piecewise fitting, the four models all achieved high accuracy, and the CCTM performs the best. Fourth, the CCTM model should also be applied to time series image compression, two compression patterns with 24 coefficients and 6 coefficients respectively are proposed. The daily MSR dataset can achieve a compression ratio of 15 by using the 6-coefficients method. Finally, the CCTM model also has the potential to be applied to change detection, trend analysis, and phenology and seasonal characteristics extractions. [ABSTRACT FROM AUTHOR]

Forest height inversion with Polarimetric SAR Interferometry (PolInSAR) has become a research hotspot in the field of radar remote sensing. In this paper, we systematically studied a modified two-step, three-stage inversion simulating the L-band (L = 23 cm) full-polarization interferometric SAR data with an average forest height of 18 m using ESA PolSARpro-SIM software. We applied this method to E-SAR L-band single-baseline full PolInSAR data in 2003. In the first step, we modified the three-stage inversion algorithm based on phase diversity (PD)/maximum coherence difference (MCD) coherence optimization methods, corresponding to PD, MCD, respectively. In the second step, we introduced the coherence amplitude inversion term and modified the fixed weight to the variable of ε times the ground scattering ratio, which improved the accuracy of forest height inversion. The mean of forest height inversion by the HV method was the lowest (15.83 m) and the RMSE was the largest (4.80 m). The PD method was superior to the HV method with RMSE (4.60 m). The MCD method was slightly better than using the PD method with the smallest RMSE (4.43 m). After adding the coherence amplitude term, the RMSE was improved by 0.15 m, 0.14 m, and 0.08 m, respectively. The smallest RMSE was obtained by MCD, followed by the PD and HV methods. Although the robustness of the forest height inversion algorithm was reduced, the underestimation was improved and the RMSE was reduced. Due to the complexity of the real SAR E-SAR L-band single-baseline full PolInSAR data and the small sample sizes, the three-stage inversion methods based on coherent optimization were lower than the three-stage in-version method. After introducing the coherent magnitude term, the overestimation of the forest height was significantly weakened in HVWeight, PDweight, and MCDWeight, and PDWeight was optimal. The modified two-step, three-stage inversion algorithm had significant effects in alleviating forest height underestimation and overestimation, improving the accuracy of forest height inversion, and laying a foundation for the upcoming L-band SAR satellite generation, new SAR and LIDAR systems combined with RPAs (remotely piloted aircrafts)/UAVs (unmanned aerial vehicles) for small areas mapping initiatives, and promoting the depth and breadth of the SAR applications of the new SAR system. [ABSTRACT FROM AUTHOR]

Aim: Ecosystem carbon use efficiency (CUEe) is a core parameter of ecosystem process models, but its relationships with climate are still uncertain, especially for ecosystems with harsh environments. Large inconsistencies in climate impacts on the CUEe have been reported among various spatial scales. The goal of this study was to examine whether warming promotes or restricts the CUEe and whether the CUEe responds to a warming gradient in a linear or nonlinear manner. Location: Tibetan Plateau. Time period: 2000–2018. Major taxa studied: Alpine grassland ecosystem. Methods: We integrated multiple‐source data of carbon fluxes and CUEe, including warming experiments at a site scale, eddy covariance observations at a landscape scale and synthesized warming experiments and ecosystem process models at a regional scale. Next, we deployed a statistical model to examine the warming impacts on the CUEe across scales; the effects of biotic and abiotic factors on the CUEe and its components were summarized based on the results of standardized major axis tests and routines, structural equation modelling and nonlinear models. Results: This study reported a suppressive warming impact on the CUEe, which followed a nonlinear curve with severe inhibition in the high‐level warming treatment. With a warming threshold of 1.5–2.0°C, CUEe response patterns transitioned from no change to a significant decrease. The restriction effects can be ascribed to the joint adverse and asymmetric effects of warming on CUEe components under multiple‐level warming. Warming‐modified relationships among CUEe components and the nonlinear effects of biotic and abiotic factors led to the nonlinear responses of CUEe to warming. Main conclusions: This study revealed suppressive and nonlinear effects of warming on the CUEe, including especially dramatic CUEe decreases with high‐level warming. These findings are critical for optimizing model parameters and improving predictions of the carbon sequestration capacity of alpine grasslands. [ABSTRACT FROM AUTHOR]

• Vegetation greening slows land surface warming in Chinese drylands. • Biogeophysical feedback of vegetation greening to climate is seasonally asymmetric. • Land use change amplifies the greening-induced cooling effects. Vegetation change can provide strong feedback to climate system, but there is a severe shortage of understanding regarding how biogeophysical (BGP) processes related to vegetation changes and their impact on local temperature in arid and semi-arid regions of China (ASAC), a unique region where large-scale ecological engineering projects have been implemented. To address this knowledge gap, this study is aims to investigate the BGP effects of vegetation changes (including growth change and type conversion) and elucidate the BGP mechanisms that link vegetation and surface temperature (T s) through integrating the Intrinsic Biophysical Mechanism (IBM) method and pairwise comparison analysis. The findings reveal that vegetation change slows down climate warming rate of T s in ASAC, with a cooling magnitude of -0.0096 K/year (Non-radiative forcing: -0.0114 K/year; Radiative forcing: 0.0018 K/year) from 2000 to 2018, embodied as cooling in summer-autumn and warming in winter-spring. Vegetation-induced BGP effects in ASAC are dominated by non-radiative mechanisms. During the study period, compared to the stable land use/land cover (LULC), cropland expansion and grassland restoration usually led to cooling exceeding -0.05 K and -0.01 K, respectively. However, afforestation and urbanization generally cause warming about 0.02 K and 0.04 K, respectively. From a BGP point of view, avoiding large-scale afforestation in extremely arid regions is an effective strategy. This study highlights the importance of land use/ land cover change (LULCC) in regulating regional climates, and emphasizes the necessity of fully considering the multiple effects of LULCC in the formulation or evaluation of climate change mitigation policies. [ABSTRACT FROM AUTHOR]

Summary: Global environmental change is altering the Earth's ecosystems. However, much research has focused on ecosystem‐level responses, and we know substantially less about community‐level responses to global change stressors.Here we conducted a 6‐yr field experiment in a high‐altitude (4600 m asl) alpine grassland on the Tibetan Plateau to explore the effects of nitrogen (N) addition and rising atmospheric CO2 concentration on plant communities.Our results showed that N and CO2 enrichment had synergistic effects on alpine grassland communities. Adding nitrogen or CO2 alone did not alter total community biomass, species diversity or community composition, whereas adding both resources together increased community biomass, reduced species diversity and altered community composition. The observed decline in species diversity under simultaneous N and CO2 enrichment was associated with greater community biomass and lower soil water content, and driven by the loss of species characterised simultaneously by tall stature and small specific leaf area.Our findings point to the co‐limitation of alpine plant community biomass and structure by nitrogen and CO2, emphasising the need for future studies to consider multiple aspects of global environmental change together to gain a more complete understanding of their ecological consequences. [ABSTRACT FROM AUTHOR]

Climate change is known to affect many facets of the Earth's ecosystems. However, little is known about its impacts on phylogenetic and functional properties of ecological communities.Here we studied the responses of plant communities in an alpine grassland on the Tibetan Plateau to environmental warming across taxonomic, phylogenetic and functional levels in a 6‐year multiple‐level warming experiment.While low‐level warming did not alter either plant species richness or phylogenetic/functional community structure, high‐level warming significantly decreased species richness. Higher level warming more strongly reduced soil moisture and caused stronger environmental filtering, consequently changing species composition and community structure. At the plant functional trait level, high‐level warming promoted species turnover through altering the effects of traits such as plant height on species extinction and SLA on species colonization. As a result, high‐, but not low‐level warming drove phylogenetic/functional community structure from overdispersion to randomness, by filtering out species that were functionally dissimilar and distantly related to the resident species.Synthesis. Our study provides evidence that the responses of plant phylogenetic and functional community structure to low warming differ from those in the future scenarios of increasing temperature. Importantly, the extinction of species that was functionally dissimilar and distantly related to the resident species contributed to alterations in plant community structure under high warming. Our study underscores the need to incorporate the phylogenetic and functional perspectives to gain a more complete understanding of community responses to climate warming. [ABSTRACT FROM AUTHOR]

• Discrepancies exist with different data in phenology extractions. • High temporal resolution data has higher accuracies in capturing SOS. • Double logistic method can minimize the extraction difference. The vegetation phenology is a commonly used indicator signaling vegetation responses to global changes. Monitoring vegetation phenology at a regional and global scale needs to rely to remote sensing data, for which multiple sources of datasets and extraction methods have been developed. To be efficient, remote sensing data with coarse temporal resolution is conventionally preferred in exploring vegetation phenology patterns at the continental or global scale. As fine temporal resolution data is increasingly available, effects of their temporal resolution on our analysis are still elusive. In this study, we applied several commonly utilized vegetation phenology extraction methods on two different temporal resolution MODIS NDVI data and compared their performances on the Tibetan Plateau (TP). The results showed there were certain discrepancies in the magnitude, trends and spatial patterns of extracted phenological parameters between the two datasets and among the different extraction methods. Generally, the phenological parameters derived from fine temporal resolution NDVI (MOD09A1) displayed later start of growing season (SOS), earlier end of growing season (EOS), shorter length of growing season (LOS), and were more accurate in capturing vegetation SOS compared with the coarse temporal resolution NDVI data (MOD13A2). The double logistic method can minimize the differences of extracted SOS or EOS between the two temporal resolution datasets. The findings of this study would improve accuracies of applying remote sensing data on monitoring vegetation dynamics and advance our understanding on vegetation responses to climate changes. [ABSTRACT FROM AUTHOR]

Effects of climate warming and changing precipitation on ecosystem carbon fluxes have been intensively studied. However, how they co‐regulate carbon fluxes is still elusive for some understudied ecosystems. To fill the gap, we examined net ecosystem productivity (NEP), gross ecosystem productivity (GEP,) and ecosystem respiration (ER) responses to multilevel of temperature increments (control, warming 1, warming 2, warming 3, warming 4) in three contrasting hydrological growing seasons in a typical semiarid alpine meadow. We found that carbon fluxes responded to precipitation variations more strongly in low‐level warming treatments than in high‐level ones. The distinct responses were attributable to different soil water conditions and community composition under low‐level and high‐level warming during the three growing seasons. In addition, carbon fluxes were much more sensitive to decreased than to increased precipitation in low‐level warming treatments, but not in high‐level ones. At a regional scale, this negative asymmetry was further corroborated. This study reveals that future precipitation changes, particularly decreased precipitation would induce significant change in carbon fluxes, and the effect magnitude is regulated by climate warming size. [ABSTRACT FROM AUTHOR]

Asymmetric daytime and nighttime warming broadly affects terrestrial ecosystem carbon cycling in the Northern Hemisphere. Photosynthesis mostly occurs in the daytime and respiration occurs during the whole day. Then AW D-N will certainly affect the ratio between net primary productivity (NPP) against gross primary productivity (GPP), i.e. vegetation carbon use efficiency (CUE). However, how night and daytime warming differentially affects CUE remains unclear on a global scale. Using long-term productivity datasets from MODIS and terrestrial biosphere models, we investigated spatiotemporal patterns of CUE response to daytime (Tmax) and nighttime (Tmin) temperature changes across the Northern Hemisphere (>30°N) spanning 2000–2019. Regions exhibiting a negative correlation between Tmax and CUE were extensive throughout the growing season in most northern ecosystems, with a stronger correlation magnitude in summer than in spring and autumn. Tmin warming tended to cause a positive impact on CUE in spring and autumn, while being correlated negatively with summer CUE, resulting in an overall weak positive relationship between CUE and Tmin. Divergences in the strength and direction of productivity and respiratory responses to AW D-N lead to spatial and seasonal patterns between CUE and Tmax or Tmin, and this pattern is regulated by soil moisture. Our findings provide an in-depth understanding on how the interactions between AW D-N and water limitations regulate the spatiotemporal variations of vegetation gross primary product allocation, which is vital for improving model performance. • Daytime warming has decreased CUE, while night warming has weakly increased CUE. • The net effect is a modest CUE decreasing in response to asymmetric diurnal warming. • The response pattern is regulated by regional moisture conditions. [ABSTRACT FROM AUTHOR]

As the recent global warming hiatus and the warming on high elevations are attracting worldwide attention, this study examined the robustness of the warming slowdown over the Tibetan plateau (TP) and its related driving forces. By integrating multiple-source data from 1982 to 2015 and using trend analysis, we found that the mean temperature (Tmean), maximum temperature (Tmax) and minimum temperature (Tmin) showed a slowdown of the warming trend around 1998, during the period of the global warming hiatus. This was found over both the growing season (GS) and non-growing season (NGS) and suggested a robust warming hiatus over the TP. Due to the differences in trends of Tmax and Tmin, the trend of diurnal temperature range (DTR) also shifted after 1998, especially during the GS temperature. The warming rate was spatially heterogeneous. The northern TP (NTP) experienced more warming than the southern TP (STP) in all seasons from 1982 to 1998, while the pattern was reversed in the period from 1998 to 2015. Water vapour was found to be the main driving force for the trend in Tmean and Tmin by influencing downward long wave radiation. Sunshine duration was the main driving force behind the trend in Tmax and DTR through a change in downward shortwave radiation that altered the energy source of daytime temperature. Water vapour was the major driving force for temperature change over the NTP, while over the STP, sunshine duration dominated the temperature trend. [ABSTRACT FROM AUTHOR]

Abstract The carbon use efficiency (CUE) is a core ecosystem parameter that determines the proportion of gross primary productivity (GPP) kept by an ecosystem after self-consumption. Its patterns along climates have been investigated to some extents. However, large uncertainty still exists, especially regarding its relationships with soil nutrients. The objective of this study was to evaluate the CUE variations along soil nutrient gradients by utilizing multi-sources of data for the global terrestrial ecosystem. The global terrestrial ecosystem CUE was calculated based on remote sensing modeled ecosystem productivity data, as well as in-situ observation data. The pattern analysis showed that global croplands and grasslands are distributed in nutrient-richer regions than forests. Along waning nutrients, GPP and net primary productivity (NPP) exhibit an overall increasing trend, while CUE declines. Within each biome, GPP and NPP decrease along enhanced nutrients for forests and grasslands, while CUE exhibits an opposite pattern. Based on worldwide collected field plot data, CUE also decreases along a weakened nutrient gradient. The strengthened ecosystem CUE pattern along enhanced nutrients as resulted from both model and field measurements data underscores the foremost significances of nutrients for ecosystem efficiency, also entails more comprehensive incorporations of nutrients in the future modeling studies. Highlights • The global remote sensing modeled results show that along decreasing nutrient, GPP and NPP exhibit an overall increasing trend while CUE decreases. Within the biome, GPP and NPP decrease along enhanced nutrient for forests and grassland. • The worldwide collected field plot data shows that the CUE of global terrestrial ecosystems also decreases along a weakened nutrient gradient. • This study integrated remote sensing and field measurements data and simultaneously concludes that the global terrestrial ecosystem CUE has a strengthened pattern along enhanced nutrients. [ABSTRACT FROM AUTHOR]

Climate change is receiving mounting attentions from various fields and phenology is a commonly used indicator signaling vegetation responses to climate change. Previous phenology studies have mostly focused on vegetation greening-up and its climatic driving factors, while autumn phenology has been barely touched upon. In this study, vegetation phenological metrics were extracted from MODIS NDVI data and their temporal and spatial patterns were explored on the Tibetan Plateau (TP). The results showed that the start of season (SOS) has significantly earlier trend in the first decade, while the end of season (EOS) has slightly (not significant) earlier trend. In the spatial dimension, similar patterns were also identified. The SOS plays a more significant role in regulating vegetation growing season length than EOS does. The EOS and driving effects from each factor exhibited spatially heterogeneous patterns. Biological factor is the dominant factor regulating the spatial pattern of EOS, while climate factors control its inter-annual variation. [ABSTRACT FROM AUTHOR]

Temperature is conventionally considered as the dominant factor regulating carbon fluxes of the alpine meadow on the Tibetan Plateau, while contribution from water availability is composed of large uncertainty. In this study, eddy covariance (EC) data were used to assess the relative contribution of temperature and water availability to carbon fluxes of the alpine meadow ecosystem. The results showed that soil water content (SWC) was the most important factor controlling carbon fluxes – Net Ecosystem Productivity (NEP), Gross Primary Productivity (GPP) and Ecosystem Respiration (Re). The GPP and Re increased with strengthened SWC under any temperature conditions, indicating the dominant control of water availability on carbon fluxes. In addition, water availability regulated the response size of ecosystem to temperature, and could alleviate the stress caused by low temperature. The photosynthesis capacity of alpine plants at noon was depressed by water stress rather than by high temperature. The structural equation modeling (SEM) analysis further confirmed the dominance of SWC on the carbon fluxes. This study implies that effects of climatic change on this alpine ecosystem might be more induced by changes in water pattern than increased temperature, which provides new insights into the climate controls of carbon fluxes over alpine meadow, and adds to our understanding on climate change impacts on carbon cycling on the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

The relationships between cover and AGB for the dominant and widely distributed alpine grasslands on the northern Tibetan Plateau is still not fully examined. The objectives of this study are to answer the following question: (1) How does aboveground biomass (AGB) of alpine grassland relate to plant cover at different spatial scales? (2) What are the major biotic and abiotic factors influencing on AGB-cover relationship? A community survey (species, cover, height, and abundance) was conducted within 1 m × 1 m plots in 70 sites along a precipitation gradient of 50-600 m. Ordinary linear regression was employed to examine AGB-cover relationships of both community and species levels at regional scale of entire grassland and landscape scale of alpine meadow, alpine steppe, and desert steppe. Hierarchical partitioning was employed to estimate independent contributions of biotic and abiotic factors to AGB and cover at both scales. Partial correlation analyses were used to discriminate the effects of biotic and abiotic factors on AGB-cover relationships at two spatial scales. AGB and community cover both exponentially increased along the precipitation gradient. At community level, AGB was positively and linearly correlated with cover for all grasslands except for alpine meadow. AGB was also linearly correlated with cover of species level at both regional and landscape scales. Contributions of biotic and abiotic factors to the relationship between AGB and cover significantly depended on spatial scales. Cover of cushions, forbs, legumes and sedges, species richness, MAP, and soil bulk density were important factors that influenced the AGB-cover relationship at either regional or landscape scale. This study indicated generally positive and linear relationships between AGB and cover are at both regional and landscape scales. Spatial scale may affect ranges of cover and modify the contribution of cover to AGB. AGB-cover relationships were influenced mainly by species composition of different functional groups. Therefore, in deriving AGB patterns at different spatial scales, community composition should be considered to obtain acceptable accuracy. [ABSTRACT FROM AUTHOR]

Questions (1) What are the primary factors determining the precipitation-use efficiency ( PUE) in northern Tibet; (2) how does PUE respond to the gradients of biotic and abiotic factors; and (3) how do the composition and structure of plant functional groups ( PFGs) affect PUE? Location Northern Tibet, China. Methods A community survey of species composition, cover and above-ground net primary productivity ( ANPP) was conducted within 1 m × 1 m plots in 62 slightly disturbed sites. The effects of community features (total cover, cover of PFGs and species richness) and environmental factors [mean annual precipitation ( MAP), mean annual temperature, surface soil bulk density, pH and C and N content] on PUE were identified through Pearson's correlation analyses, hierarchical partitioning and ordinary regressions. Results Along the precipitation gradient, ANPP and PUE increased exponentially. Among the community features, total cover and cover of PFGs, including forbs and sedges, were the primary factors that determined PUE. The three cover variables, together with species richness, positively affected PUE and accounted for 47.6% of the total variation in PUE. Among the environmental factors, MAP, surface soil pH and N content were the most significantly related to PUE and accounted for 29.9% of the total contribution. Conclusion Communities with high cover, species richness and nutrient content, but low soil bulk density, presented the highest PUE. At a regional scale, PUE depended mainly on plant cover, especially the cover of PFGs, namely, forbs and sedges. Environmental factors, including MAP and surface soil N and C content, positively affected PUE, whereas soil pH and bulk density negatively affected PUE. Our results highlight the importance of considering community structure to understand PUE variations in natural alpine grasslands. [ABSTRACT FROM AUTHOR]

Soil moisture is a key limiting factor in grass growth and restoration in alpine meadow ecosystems on the northern Tibetan Plateau. In the deeper layers, soil moisture influences the processes of freeze-thaw, erosion and water cycle. Cosmic-ray neutron probe (CRNP) is a new method for continuously monitoring mean soil water content (SWC) at hectometer scale, which has been applied in an alpine meadow at a high accuracy. However, with CRNP measuring depth of only 30 cm, depth-scaling is needed for sufficient insight into deep-layer soil moisture. This study evaluated the accuracy of CRNP measurement of SWC in the 2015 and 2016 growing seasons and the performance of temporal stability (TS) analysis in depth-scaling CRNP-estimated SWC. During the study period, 11 field samplings were done for calibration of CRNP-estimated SWC. Using 22 occasions of neutron probe measurements for each of 113 investigated locations, the TS of SWC was analyzed and its performance in depth-scaling CRNP-estimated SWC at five soil depths (10, 20, 30, 40 and 50 cm) was evaluated. The results showed that the mean SWCs to the depth of 50 cm were 12.9 and 17.0%, respectively in 2015 and 2016 growing seasons and were temporally influenced by precipitation and spatially by soil depth. The accuracy of the CRNP-measured SWC was high, with root mean square error and Nash-Sutcliffe efficiency coefficient (NSE) of 2.1% and 0.832, respectively. Representative locations for TS existed in all the soil layers, which increased with increasing soil depth. For the various soil layers, TS-estimated SWC was close to field-measured value. Only a relatively small error and high NSE were noted, suggesting that TS was reliable in application in CRNP depth-scaling. The study provided further scientific basis for the application of CRNP and an effective way of depth-scaling CRNP-estimated mean SWC in alpine meadow ecosystems. [ABSTRACT FROM AUTHOR]

The effects of warming-shifted plant phenology on ecosystem carbon (C) cycling have received increasing attention in recent years. However, there is a lack of evidence and mechanistic understanding of how warming-shifted plant phenology influences ecosystem C cycling. In this study, we conducted a field experiment to investigate the effects of warming on phenology and ecosystem C exchange in a Tibetan alpine meadow during the 2014 and 2015 growing seasons. Our results indicated that warming led to later green-up in spring by aggravating water limitation but little change in autumn phenology, resulting in shortened growing season length. Interestingly, we found warming caused a seasonal shift of ecosystem C exchange. During the early summer monsoon, ecosystem C uptake was suppressed by warming due to the delay of phenological development. However, warming accelerated ecosystem C uptake and promoted ecosystem C uptake under ample water conditions during the late summer monsoon. As a result, although warming shortened the growing season length, it had no significant effects on gross primary production (GPP) and net ecosystem production (NEP). Our results will improve our understanding of the mechanisms of how warming-shifted plant phenology influences ecosystem C cycling in semiarid alpine ecosystems. [ABSTRACT FROM AUTHOR]

The inter-annual variability (IAV) of net ecosystem productivity (NEP) may be caused by both climatic factors and ecosystem responses. In this study, we used eddy covariance (EC) measurements over three typical grasslands in China to investigate the dynamics of NEP and its two components − gross primary productivity (GPP) and ecosystem respiration (Re) and their driving forces. We found that climatic factors and ecosystem response simultaneously influence the IAV of ecosystem carbon fluxes, with a dominant effect arising from an ecosystem response. On a daily scale, carbon fluxes were driven primarily by climatic factors, but effects from an ecosystem response strengthened when the period of analysis was extended. On an annual scale, ecosystem responses weakened the effects of climatic variability on ecosystem carbon fluxes for the three grasslands. This negative feedback demonstrated that ecosystem acclimatization to climate variability can constrain the IAV of carbon fluxes induced by such variability. [ABSTRACT FROM AUTHOR]

• Cold environment suppressed the accumulation of microbial-derived C in the soil. • Warming increased microbial residues in the soil, but N addition decreased it. • Warming weakened the N-driven negative effect on soil C stability. Microbial-derived soil organic carbon has attracted increased attention as an important source of soil organic matter that may affect soil carbon persistence. Ecosystems at high elevation and latitude contain massive amounts of soil organic carbon that is potentially vulnerable to rapid climate change. However, little is known about the mechanisms that govern the production and accumulation of carbon derived from microbes in the context of global changes for these regions. Here, we investigate soil biomarkers from membrane lipids and microbial residues in an experiment with six-year warming and nitrogen (N) addition treatments in an alpine meadow of the Tibetan Plateau. The results showed low accumulation of amino sugars in soil (167.51 to 297.36 μg·g−1) for this alpine meadow. After the six-year manipulative experiment, warming promoted accumulation of microbial-derived carbon in soil with both increased bacterial (increased by 53.56%) and fungal carbon (increased by 25.60%). Nitrogen addition inhibited microbial-derived carbon accumulation (decreased by 25.37%) and significantly decreased the fungal carbon content relative to bacterial carbon content. Climate warming tended to weaken this N-driven negative effect. As microbial residues relate closely with soil organic matter stability, these results highlight the potential of global change factors (warming and N addition) to alter the structure and persistence of soil organic matter, with important implications in refining carbon cycle-climate models. [ABSTRACT FROM AUTHOR]

• Correlation between albedo and LAI varies with vegetation type and growth stage. • Greening dominates albedo change in arid and semi-arid areas of China. • Land use change affects albedo change under greening by altering canopy structure. Land surface albedo (LSA) is a key parameter in the process of vegetation feedback to climate due to its decisive role in land surface radiation budget. However, our current knowledge on the relationship between LSA and vegetation changes is limited by one-sided attention to sole vegetation growth change or land use/land cover change (LULCC). How vegetation growth or LULCC respectively contributes to LSA change under their interactions remains poorly quantified. In this study, the arid and semi-arid areas of China (ASAC) with profound vegetation changes were selected to tackle this problem. The LSA showed a general downward trend (-0.00009 year−1) during 2000-2018 in response to ASAC's wide-range greening (0.0086 m2m−2year−1). Pairwise comparison analysis revealed that under the same unit of vegetation coverage change, the LSA change magnitude was contracted when grassland was converted to cultivated land or forest land, while the conversions of forest land to other vegetations led to an amplified change magnitude of LSA. Vegetation type directly leads to a difference in LSA change magnitude under greening due to their distinct canopy spectral characteristics. Grassland possesses lower LAI and its pixel-level LSA is more prone to be contaminated by background coverage, while LSA of forest land contains more vegetation canopy signal. In most areas where vegetation type converted, greening dominated LSA change with a contribution rate up to 98.14 %, except for the conversion of grassland to forest land, where LULCC accounted for about 66.38 % of LSA change. This study could improve the estimation of LSA from LAI, which is useful for optimizing vegetation-climate interaction models. [ABSTRACT FROM AUTHOR]

• Correlation between albedo and LAI varies with vegetation type and growth stage. • Greening dominates albedo change in arid and semi-arid areas of China. • Land use change affects albedo change under greening by altering canopy structure. Land surface albedo (LSA) is a key parameter in the process of vegetation feedback to climate due to its decisive role in land surface radiation budget. However, our current knowledge on the relationship between LSA and vegetation changes is limited by one-sided attention to sole vegetation growth change or land use/land cover change (LULCC). How vegetation growth or LULCC respectively contributes to LSA change under their interactions remains poorly quantified. In this study, the arid and semi-arid areas of China (ASAC) with profound vegetation changes were selected to tackle this problem. The LSA showed a general downward trend (-0.00009 year−1) during 2000-2018 in response to ASAC's wide-range greening (0.0086 m2m−2year−1). Pairwise comparison analysis revealed that under the same unit of vegetation coverage change, the LSA change magnitude was contracted when grassland was converted to cultivated land or forest land, while the conversions of forest land to other vegetations led to an amplified change magnitude of LSA. Vegetation type directly leads to a difference in LSA change magnitude under greening due to their distinct canopy spectral characteristics. Grassland possesses lower LAI and its pixel-level LSA is more prone to be contaminated by background coverage, while LSA of forest land contains more vegetation canopy signal. In most areas where vegetation type converted, greening dominated LSA change with a contribution rate up to 98.14 %, except for the conversion of grassland to forest land, where LULCC accounted for about 66.38 % of LSA change. This study could improve the estimation of LSA from LAI, which is useful for optimizing vegetation-climate interaction models. [ABSTRACT FROM AUTHOR]

• Higher spring GPP induced by earlier spring compensated for its summer reductions. • Earlier spring cost soil water earlier, and then strengthened summer heat effects. • These heat effects were offset due to the region-specific characteristics. • Lower temperature alleviated the decreases in summer GPP through decreasing VPD. The knock-on effects between earlier vegetation activities and summer droughts may have important consequences for broad ecological processes. To date, little is known about how the chained effects drive the carbon and water cycles on the Tibetan Plateau (TP). Using the naturally occurring above-mentioned sequential events in spring and summer in 2015 and 2017, we applied the observations at the site, landscape, and regional scales to evaluate the chained effects on the TP. Our findings indicated that higher spring vegetation productivity is caused by early vegetation activities, partially compensated for summer drought-induced loss. Concurrently, increased spring evapotranspiration induced by earlier spring may drain soil water resources earlier, exacerbating summer water restrictions caused mainly by sparse precipitation. This lagged effect of early spring, accompanied by summer drought, significantly increased summer sensible heat flux by 23.2%. Remarkably, the mean air temperature (Ta) was lower than the baseline during drought. This decrease was contributed mainly by lower nighttime Ta, indicating that the region-specific characteristics of the TP could offset the heating effects as mentioned above. The characteristics of high altitude, low air pressure, and thin air could strongly weaken the cloud insulations. More substantial decreases in cloud amount during drought further decreased atmospheric counter radiations, leading to lower mean/nighttime Ta. The simulation results showed that lower mean Ta alleviated the decreases in gross primary productivity by 4.3% through reducing vapor pressure deficit by 5.1%. In conclusion, the present study highlighted the need to comprehensively consider the buffering effects of lower temperature during summer drought to precisely assess the chained effects on the TP. [ABSTRACT FROM AUTHOR]

ABSTRACT As one of the most sensitive regions to climate change, the Qinghai-Xizang Plateau has been widely investigated as one unity for impacts of climate change on alpine grassland. However, previous findings might be confounded by distinct climate sensitivities at different elevations and different regional climates between Qinghai Province and Xizang Province, which lie at the two sides of Tanggula Mountains. In this study, we explored change trends of grassland vegetation, temperature and precipitation in growing season from 1982 to 2011, and elevation-dependent effects of climate change on grassland vegetation in the two provinces separately. The plateau grassland greenness gained improvement under climate warming and wetting during the past 30 years, especially in Qinghai Province. Temperature increased significantly with a warming magnitude of more than 1.5 °C over the plateau grassland. The interannual change of precipitation showed contrary trends between the two provinces. The main climate factor driving the grassland vegetation variation varied between the two provinces, with temperature being the main factor in Qinghai Province and precipitation being the main factor in Xizang Province. In particular, a more significant correlation between climate change and grassland vegetation variation was found at higher elevations, which reveals higher climate sensitivity in higher elevation areas of the plateau. [ABSTRACT FROM AUTHOR]

As the world's highest and largest plateau, the Qinghai-Xizang Plateau has experienced a greater warming than the Northern Hemisphere and global averages. This warming has been reported to exhibit an elevation-dependent pattern. However, the finding involved plenty of uncertainties caused by the spatially limited datasets and complex topography. Here, we explored an approach integrating satellite-derived LST data and ground records to generate a spatially continuous air temperature dataset for the plateau grasslands from 2003 to 2012, and then examined influences of elevation/topography on temperature change trends. The derived temperature dataset was validated to be closely correlated with field-station records. Based on the derived spatially continuous temperature datasets, we found an opposite change trend of annually average temperature between Qinghai and Xizang Province. The contrasted trend was obvious in daytime and more so in summer season. By analyzing the temperature trend in relation to elevation, we found an enhanced temperature change trend in higher elevation than in lower elevation for autumn nights and winter temperatures, while the temperature change trends for other seasons were more evident in lower elevation areas. The varying temperature change trends as regulated by elevation implies that temperate grasslands have experienced a more rapid temperature change than alpine grasslands during the past decade. [ABSTRACT FROM AUTHOR]

• Temporal change in relationship between NDVI and diurnal temperature was explored. • R NDVI-TMX and R NDVI-TMN showed distinct variations between mid- and high latitudes. • Weakening effect of TMX on vegetation growth was more apparent than that of TMN. • TRENDY models didn't capture dynamic relation of vegetation growth to TMX or TMN. Global warming has boosted vegetation growth to a large extent, but this stimulation effect has significantly weakened in recent years. Among the set of possible driving forces, the asymmetric daytime and nighttime warming effect has been largely neglected. To improve our understanding on the relationship between vegetation growth and global warming, this study tries to attribute the respective effects of daytime and nighttime temperature on vegetation growth and reveal their temporal trends in the extratropical Northern Hemisphere (30–90 °N). The results showed there had been significant warming trends in growing season maximum (TMX, 0.37 °C per decade) and minimum temperatures (TMN, 0.38 °C per decade) during 1982–2015, especially in high latitudes of the NH. Under the asymmetric diurnal warming, the effects of TMX and TMN on normalized difference vegetation index (NDVI) exhibited distinct temporal variations between mid- (<55 °N) and high latitudes (>55 °N). The positive correlation between NDVI and TMX (R NDVI-TMX) weakened in high latitudes, as well as the negative correlation between NDVI and TMN (R NDVI-TMN). However, the R NDVI-TMX and R NDVI-TMN changed little in mid-latitudes. Moreover, the weakening effect of TMX on NDVI was more apparent than that of TMN in high latitudes. The area with significantly (p < 0.1) positive R NDVI-TMX and significantly (p < 0.1) negative R NDVI-TMN both shrank from 1982–1998 to 1999–2015, with prior (15.97%) twice the latter one (7.09%) in shrunk area in high latitudes. With regard to vegetation type, decline in area with significantly (p < 0.1) positive R NDVI-TMX and negative R NDVI-TMN was extremely obvious in savannas, deciduous broadleaf forests and deciduous needleleaf forests. Besides, we also disclosed the poor performance of ecosystem process models in capturing the dynamic relationship between vegetation growth and diurnal temperature, which might be caused by their totally relying on diurnal mean temperature, instead of daytime and nighttime temperature, in forcing the models. This study can further advance our understandings on ecosystem responses to climate warming, and efficiently improve performance of ecosystem models. [ABSTRACT FROM AUTHOR]

• This is the CO 2 enrichment field experiment conducted on the highest elevation. • Elevated CO 2 (eCO 2) stimulates both GEP and ER, and causes a neutral effect on NEP. • Simultaneous N addition and eCO 2 stimulate carbon sink. • Excessive precipitation suppresses the eCO 2 effects on carbon fluxes. It's generally believed that elevated CO 2 (eCO 2) could stimulate plant growth and the ecosystem carbon (C) sink. However, great uncertainties exist in terms of the CO 2 fertilization effect (CFE) magnitude, and how it is regulated by other global change factors. The lack of experimental evidence from the Alpine Region also limits our cognition on the CFE. By conducting a five-year manipulative field experiment in a semi-arid grassland of the Tibetan Plateau, we are aimed to explore the behavior of ecosystem C exchange in response to eCO 2 and N availability under contrasting natural precipitation regimes. The experiment showed that eCO 2 stimulated both gross ecosystem productivity (GEP) and ecosystem respiration (ER), and resulted in a neutral effect on net ecosystem productivity (NEP). The reduction of leaf N concentration under eCO 2 constrained the eCO 2 effects on C fluxes, especially on GEP and NEP. As N addition replenishes N availability in soil and leaf, GEP benefited more from the N addition than the ER. The eCO 2 strengthened the C sink when exogenous N was added simultaneously. Furthermore, precipitation variability played an importance role in mediating the eCO 2 effect among growing seasons. The eCO 2 effects on C fluxes tended to decline with increased water availability. The CFE was suppressed with excessive precipitation when the water-use efficiency (WUE) response was weak and eCO 2 -induced water-saving disappeared. The negative impact of precipitation on the CFE may also be attributed to the short precipitation intervals and insufficient radiation caused by high-frequency precipitation. Our study demonstrates that eCO 2 only stimulates net C uptake under conditions of N addition or during drier periods. Given the widespread N limitation, the efficacy of terrestrial ecosystems in mitigating climate change under rising CO 2 may be weaker than projected and is closely related to the precipitation variability. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau is the highest and largest plateau in the world, hosting unique alpine grassland and having a much higher snow cover than any other region at the same latitude, thus representing a "climate change hot-spot". Land surface phenology characterizes the timing of vegetation seasonality at the per-pixel level using remote sensing systems. The impact of seasonal snow cover variations on land surface phenology has drawn much attention; however, there is still no consensus on how the remote sensing estimated start of season (SOS) is biased by the presence of preseason snow cover. Here, we analyzed SOS assessments from time series of satellite derived vegetation indices and solar-induced chlorophyll fluorescence (SIF) during 2003–2016 for the Tibetan Plateau. We evaluated satellite-based SOS with field observations and gross primary production (GPP) from eddy covariance for both snow-free and snow covered sites. SOS derived from SIF was highly correlated with field data (R2 = 0.83) and also the normalized difference phenology index (NDPI) performed well for both snow free (R2 = 0.77) and snow covered sites (R2 = 0.73). On the contrary, normalized difference vegetation index (NDVI) correlates only weakly with field data (R2 = 0.35 for snow free and R2 = 0.15 for snow covered sites). We further found that an earlier end of the snow season caused an earlier estimate of SOS for the Tibetan Plateau from NDVI as compared to NDPI. Our research therefore adds new evidence to the ongoing debate supporting the view that the claimed advance in land surface SOS over the Tibetan Plateau is an artifact from snow cover changes. These findings improve our understanding of the impact of snow on land surface phenology in alpine ecosystems, which can further improve remote sensing based land surface phenology assessments in snow-influenced ecosystems. Unlabelled Image • Four satellite indicators are tested to estimate spring phenology trends over the Tibetan Plateau. • The confounding effect of snow cover is evaluated. • The Normalized Difference Phenology Index provides best results for snow conditions. • Normalized Difference Vegetation Index SOS trends are biased by snow trends. [ABSTRACT FROM AUTHOR]

Aims: Vegetation in high-altitude regions is hypothesized to be more responsive to increasing atmospheric CO2 concentrations due to low CO2 partial pressure. However, the underlying mechanisms driving this response at an ecosystem scale are poorly understood. We aimed to explore the plant carbon (C) and nitrogen (N) relationships and biomass allocation in response to elevated CO2 and N addition in a Tibetan meadow. Methods: A 5-year manipulation experiment was conducted in an alpine meadow (4585 m above sea level) to explore the responses of plant carbon (C), nitrogen (N), and biomass dynamics, as well as their allocation schemes, to elevated CO2 (from 380 ppm to 480 ppm) and N fertilization. Results: Elevated CO2 alone significantly enhanced aboveground plant biomass by 98%, exhibiting a stronger CO2 fertilization effect than the global average level (20%) for grasslands. Elevated CO2 favored N accumulation in aboveground parts despite the declined concentration. Nitrogen fertilization alleviated the N constraints on CO2 fertilization effects, which strengthened C sequestration capacity for the aboveground plant tissues. Moreover, our results indicate a decoupling between C and N cycles in alpine ecosystems under elevated CO2, especially in the N-enrichment environments. Conclusions: Overall, this study shows a high sensitivity of aboveground plant biomass and decoupled C-N relationships under elevated CO2 and N fertilization for high-elevation alpine ecosystems, highlighting the need to incorporate altitude effects into Earth System Models in predicting C cycle feedbacks to climate changes. [ABSTRACT FROM AUTHOR]

• Alpine grasslands on the tibetan plateau possess low resistance to drought;. • The alpine ecosystems exhibit strong post-drought regrowth;. • Post-drought regrowth compensates for the prior loss to a certain extent;. • Observations across varied spatial scales turned out consistent conclusions. One-third of the global fossil fuel CO 2 emissions is offset by carbon uptake of terrestrial ecosystems, while its strength is highly sensitive to drought events. It is predicted that frequencies of drought events would increase under a changing climate, which entails improving our understanding about their effects. Here, we combined direct observations at plot (experiment sites) and landscape (eddy-covariance, EC) scales with remote sensing observations at a regional scale, and evaluated the linkages between ecological resistance (summer drought loss, SDL) and resilience (post-drought regrowth, PDR). The study was conducted for an alpine grassland ecosystem on the Tibetan Plateau, which is highly vulnerable to climate changes. The results showed that alpine grasslands possess low resistance to drought. A summer drought of 2015 reduced net primary productivity (NPP) or net ecosystem productivity (NEP) by 25.4 g C m −2, 48.6 g C m −2 and 14.2 Tg C at the plot, landscape and regional scale relative to the baseline, respectively. In another dry summer of 2017, NEP was 11.0 g C m −2 and 7.5 g C m −2 lower than the baseline at the landscape and plot scale, respectively. To be noted, NEP or NPP completely recovered and exceeded the baseline due to rewetting induced PDR, compensating for the prior SDL to a certain extent. In 2015, the SDL of NEP or NPP was compensated by 39.0%, 17.3% and 10.6% due to the PDR effects at the plot, landscape and regional scale, respectively. The PDR of NEP in 2017 offset 23.6% and 70.7% of the prior SDL at the landscape and plot scale, respectively. Overall, these results demonstrated that weakened ecosystem function due to drought (e.g., low resistance) does not preclude rapid ecosystem recovery and regrowth (e.g., high resilience), which compensates for the prior loss to a certain degree. [ABSTRACT FROM AUTHOR]

• The first study to use high-resolution images to survey pika hole size and area. • The first study to explore pika hole distribution pattern at a landscape scale. • Effects of pika hole on plant growth in the surrounding varies with pika hole size. • Vegetation coverage affects pika hole density in alpine meadow. The pika (Ochotona curzoniae) hole is an important landscape feature in the Tibetan Plateau (TP) grasslands, and it indicates grassland degradation levels due to the destruction caused by pika burrowing activities on grasslands. However, no studies have ever explored landscape patterns of pika holes and their effects on adjacent vegetation coverage. Taking meadow grasslands in Northern Tibet as an example, this study gathered unmanned aerial vehicle (UAV) images and explored landscape patterns of pika holes and their effects on grass coverage in the surroundings. The performances of two classification methods, including the decision tree classification based on Fully Constrained Least Squares (FDC) and the object-oriented classification (OBC) were compared in recognizing sizes and shapes of pika holes. The results showed that: (1) The object-oriented classification exhibits higher classification accuracy in identifying pika holes. (2) The average size of pika holes in the study area is 0.01 m2 and they exhibit clustered distribution patterns. The average distance between any two nearest pika hole patches is 0.79 m. (3) It presents a significant quadratic relationship between the number of pika holes and grass coverage. (4) The average effective distance of pika holes on the surrounding grass coverage is 20 cm. The findings of this study can provide guidelines for pika control and improve grassland management on the TP. [ABSTRACT FROM AUTHOR]

Plant phenology, as an indicator of environmental variation and climate change impacts, has vital effects on ecosystem biogeochemical cycles. As another major land cover type, snow cover plays an important role in influencing on ecosystem geo-biophysical processes and water availability. For Tibetan Plateau, snow cover and the alpine vegetation are more sensitive to climate change than other regions in China. In situ and regional studies provide evidence for the warming effect on phenology in the plateau. However, the understanding of how seasonal dynamic of snow cover affect the phenology by modulating soil water availability or other environmental factors, are still very limited. In our research, we use a 16-year time-series cloud-free MODIS daily snow cover MODIS dataset to extract the FSCD(Freezing of Snow Cover Date),MSCD(Melt of Snow Cover Date) and SCD(Snow Cover Duration). We also extract the spring phenology based on three vegetation indexes (NDVI, NDPI and PPI) to eliminate the snow cover's contamination. An overall enhanced spring phenology as well as a shorter SCD are observed. Snow cover area exhibited two separate peaks during autumn and late winter over the plateau. MSCD and FSCD do not show significant trend during research period. Extended SCD regions mainly distributed in middle-east of the plateau, while shrunken SCD distributed in other regions of the plateau. For the semi-arid meadow region, the autumn SCD and slightly postponed FSCD have positive effect on advancing the spring phenology along with lag effects. For the arid steppe region, the slightly postponed MSCD and the shrunken SCD have negative effect on the non-significant delay of spring phenology. The non-growing season freezing degree days(FDD) also can modify the effect of MSCD, FSCD and SCD on the spring phenology. Overall, our results suggest that for the alpine vegetation in Tibetan Plateau show distinct react to the snow cover change in different seasons. In further studies, with these effect considered, the predictions on the Tibetan Plateau's spring phenology could be improved.keywords: alpine vegetation, snow cover, phenology,Tibetan Plateau [ABSTRACT FROM AUTHOR]

Anthropogenic environmental changes are influencing the structure and function of many ecological communities, but their underlying mechanisms are often poorly understood. We conducted a 7‐year field experiment to explore the ecological consequences of nitrogen (N) and phosphorous (P) enrichment in a high‐altitude Tibetan alpine grassland. We found that the enrichment of both N and P, but not either alone, increased plant above‐ and belowground biomass. In contrast, N, but not P, enrichment reduced species richness and altered plant phylogenetic diversity and structure. Whereas plant species loss and changes in phylogenetic structure were mainly driven by higher soil manganese levels under N addition, they were mainly driven by increased plant belowground biomass under the addition of both N and P. Our study highlights the resource co‐limitation of community biomass but not the structure of the study grassland, while also identifying soil metal toxicity and belowground competition as important mechanisms driving community changes following nutrient amendment. [ABSTRACT FROM AUTHOR]

[Display omitted] Structural information of grassland changes on the Tibetan Plateau is essential for understanding alterations in critical ecosystem functioning and their underlying drivers that may reflect environmental changes. However, such information at the regional scale is still lacking due to methodological limitations. Beyond remote sensing indicators only recognizing vegetation productivity, we utilized multivariate data fusion and deep learning to characterize formation-based plant community structure in alpine grasslands at the regional scale of the Tibetan Plateau for the first time and compared it with the earlier version of Vegetation Map of China for historical changes. Over the past 40 years, we revealed that (1) the proportion of alpine meadows in alpine grasslands increased from 50% to 69%, well-reflecting the warming and wetting trend; (2) dominances of Kobresia pygmaea and Stipa purpurea formations in alpine meadows and steppes were strengthened to 76% and 92%, respectively; (3) the climate factor mainly drove the distribution of Stipa purpurea formation, but not the recent distribution of Kobresia pygmaea formation that was likely shaped by human activities. Therefore, the underlying mechanisms of grassland changes over the past 40 years were considered to be formation dependent. Overall, the first exploration for structural information of plant community changes in this study not only provides a new perspective to understand drivers of grassland changes and their spatial heterogeneity at the regional scale of the Tibetan Plateau, but also innovates large-scale vegetation study paradigm. [ABSTRACT FROM AUTHOR]

Highlights • Grazing could preserve the deep-layer soil moisture by reducing transpiration. • Higher productivity was maintained in grazed alpine meadow during droughts. • Younger leaves in grazed meadow could restore productivity quickly after droughts. Abstract 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. [ABSTRACT FROM AUTHOR]

Global warming exerts profound impacts on terrestrial carbon cycles and feedback to climates. Ecosystem respiration (ER) is one of the main components of biosphere CO2 fluxes. However, knowledge regarding how ER responds to warming is still lacking. In this study, a manipulative experiment with five simulated temperature increases (+0℃ [Control], +2.1℃ [warming 1, W1], +2.7℃ [warming 2, W2], +3.2℃ [warming 3, W3], +3.9℃ [warming 4, W4]) was conducted to investigate ER responses to warming in an alpine meadow on the Tibetan Plateau. The results showed that ER was suppressed by warming both in dry and wet years. The responses of ER to warming all followed a nonlinear pattern. The nonlinear processes can be divided into three stages, the quick‐response stage (W1), stable stage (W1–W3), and transition stage (W4). Compared with the nonlinear model, the linear model maximally overestimated the response ratios of ER to warming 2.2% and 3.2% in 2015 and 2016, respectively, and maximally underestimated the ratio 7.0% and 2.7%. The annual differences in ER responding to warming were mainly attributed to the distinct seasonal distribution of precipitation. Specially, we found that the abrupt shift response of ER to warming under W4 treatment in 2015, which might be regulated by the excitatory effect of precipitation after long‐term drought in the mid‐growing season. This study highlights the importance of the nonlinearity of warming effects on ER, which should be taken into the global‐C‐cycling models for better predicting future carbon–climate feedbacks. The responses of ER to warming all followed a nonlinear pattern. The nonlinear processes can be divided into three stages, the quick‐response stage (W1), stable stage (W1–W3), and transition stage (W4). The annual differences in ER responding to warming were mainly attributed to the distinct seasonal distribution of precipitation. Specially, we found that the distinct abrupt shift response of ER to warming under W4 treatment in 2015, which might be regulated by the excitatory effect of precipitation after long‐term drought in the mid‐growing season. [ABSTRACT FROM AUTHOR]

To explore grazing effects on carbon fluxes in alpine meadow ecosystems, we used a paired eddy-covariance (EC) system to measure carbon fluxes in adjacent fenced (FM) and grazed (GM) meadows on the Tibetan plateau. Gross primary productivity (GPP) and ecosystem respiration (Re) were greater at GM than FM for the first two years of fencing. In the third year, the productivity at FM increased to a level similar to the GM site. The higher productivity at GM was mainly caused by its higher photosynthetic capacity. Grazing exclusion did not increase carbon sequestration capacity for this alpine grassland system. The higher optimal photosynthetic temperature and the weakened ecosystem response to climatic factors at GM may help to facilitate the adaption of alpine meadow ecosystems to changing climate. [ABSTRACT FROM AUTHOR]

Climate warming is predicted to considerably affect variations in soil organic carbon (SOC), especially in alpine ecosystems. Microbial necromass carbon (MNC) is an important contributor to stable soil organic carbon pools. However, accumulation and persistence of soil MNC across a gradient of warming are still poorly understood. An 8‐year field experiment with four levels of warming was conducted in a Tibetan meadow. We found that low‐level (+0–1.5°C) warming mostly enhanced bacterial necromass carbon (BNC), fungal necromass carbon (FNC), and total MNC compared with control treatment across soil layers, while no significant effect was caused between high‐level (+1.5–2.5°C) treatments and control treatments. The contributions of both MNC and BNC to soil organic carbon were not significantly affected by warming treatments across depths. Structural equation modeling analysis demonstrated that the effect of plant root traits on MNC persistence strengthened with warming intensity, while the influence of microbial community characteristics waned along strengthened warming. Overall, our study provides novel evidence that the major determinants of MNC production and stabilization may vary with warming magnitude in alpine meadows. This finding is critical for updating our knowledge on soil carbon storage in response to climate warming. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau has experienced higher-than-global-average climate warming in recent decades, resulting in many significant changes in ecosystem structure and function. Among them is albedo, which bridges the causes and consequences of land surface processes and climate. The plateau is covered by snow/ice and vegetation in the non-growing season (nGS) and growing season (GS), respectively. Based on the MODIS products, we investigated snow/ice cover and vegetation greenness in relation to the spatiotemporal changes of albedo on the Tibetan Plateau from 2000 through 2013. A synchronous relationship was found between the change in GSNDVI and GSalbedo over time and across the Tibetan landscapes. We found that the annual average albedo had a decreasing trend, but that the albedo had slightly increased during the nGS and decreased during the GS. Across the landscapes, the nGSalbedo fluctuated in a synchronous pattern with snow/ice cover. Temporally, monthly snow/ice coverage also had a high correspondence with albedo, except in April and October. We detected clear dependencies of albedo on elevation. With the rise in altitude, the nGSalbedo decreased below 4000 m, but increased for elevations of 4500–5500 m. Above 5500 m, the nGSalbedo decreased, which was in accordance with the decreased amount of snow/ice coverage and the increased soil moisture on the plateau. More importantly, the decreasing albedo in the most recent decade appeared to be caused primarily by lowered growing season albedo. [ABSTRACT FROM AUTHOR]

Cold biome ecosystems, extensively distributed on our planet, are highly sensitive to global changes. Fluctuations caused by climate change would inevitably affect the ecosystems' structure and functions. However, the linkage between cold biome ecosystems and global changes demonstrates high spatial heterogeneity, especially between high-latitude ecosystems (HL) and high-altitude alpine ecosystems (HA). A comparative analysis of their response patterns would provide deeper insight into the underlying mechanisms at play. We used meta-analysis to synthesize ecosystems' response to warming and altered precipitation performed in HL and HA. Warming and enhanced precipitation increases ecosystem biomass and carbon fluxes in HL and HA. Warming significantly stimulates aboveground biomass (AGB), root biomass (RB), total biomass (TB), aboveground net primary productivity, gross ecosystem productivity (GEP), soil respiration (SR), and net ecosystem productivity (NEP) in HL and HA. Similarly, AGB, GEP, and NEP increase significantly with enhanced precipitation. Respondent of ecosystem carbon storage and fluxes in HL and HA showed diverse results to warming treatment. Warming increases AGB and RB in HA while RB remains unaltered in HL. GEP and ER exhibit a positive response to warming in HL but an insignificant response in HA. In general, HL is sensitive to warming, and HA is sensitive to precipitation. The differential responses of HL and HA to climate change imply specific ecosystem traits and particular environmental constraining factors. Future cold biome ecosystem studies should further consider specific conditions like microtopography, soil moisture, and local climate unique to high-latitude and high-altitude ecosystems. [ABSTRACT FROM AUTHOR]

Elucidating the response mechanism of soil respiration (Rs) to silvicultural practices is pivotal to evaluating the effects of management practices on soil carbon cycling in planted forest ecosystems. However, as common management practices, how thinning, understory plant removal, and their interactions affect Rs and its autotrophic and heterotrophic components (Ra and Rh) remains unclear. Therefore, we investigated Rs, Ra and Rh by the trenching method from 2011 to 2015 in a Pinus tabuliformis plantation in northern China, subjecting to four treatments (intact control plots [CK], thinning [T], understory removal [UR], and thinning with understory removal [TUR]). Mean annual Rs was significantly increased by thinning (by 15.3%), whereas decreased by UR (by 17.4%), compared with CK. These variations in Rs were mainly attributed to changes in Ra. The increments of Ra were caused by the enhanced growth of fine root biomass after thinning. However, UR led to lower Ra compared with CK (p <.05), indicating that understory growth is inadequate to compensate for the decreased respiring root biomass induced by understory removal. Rs was unchanged between TUR and the intact control plot due to the opposite effects of thinning and UR on the Ra. Changes in Rh exhibited no significant differences among the treatments, partly because of the stable microbial biomass carbon (MBC) and forest floor mass (litter and fine woody debris). No interaction effect between thinning and understory removal was detected on Rs, Ra, and Rh. The lowest temperature sensitivity (Q10) value of Ra was found in CK. This study highlights the necessity of incorporating understory plant effects on soil CO2 efflux in assessing forest management practices on soil carbon cycling. [ABSTRACT FROM AUTHOR]