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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]

Aim Carbon use efficiency [net primary production ( NPP)/gross primary production ( GPP) ratio] is a parameter related to the allocation of photosynthesized products by plants and is commonly used in many biogeochemical cycling models. But how this parameter changes with climates is still unknown. Faced by an aggravated global warming, there is a heightened necessity in unravelling the dependence of the NPP/ GPP ratio on climates. The objective of this study was to examine how ongoing climate change is regulating global patterns of change in the NPP/ GPP ratio. The study finding would elucidate whether the global vegetation ecosystem is becoming more or less efficient in terms of carbon storage under climatic fluctuation. Location The global planetary ecosystem. Methods The annual NPP/ GPP ratio of the global terrestrial ecosystem was calculated over a 10-year period based on Moderate Resolution Imaging Spectroradiometer data and an ecosystem productivity model. The temporal dynamics of the global NPP/ GPP ratio and their dependence on climate were investigated. Results The global NPP/ GPP ratio exhibited a decreasing trend from 2000 to 2009 due to decreasing NPP and stable GPP over this period. The temporal dynamics of the NPP/ GPP ratio were strongly controlled by temperature and precipitation. Increased temperature lowered the NPP/ GPP ratio, and increased precipitation led to a higher NPP/ GPP ratio. Conclusions The NPP/ GPP ratio exhibits a clear temporal pattern associated with climatic fluctuations at a global scale. The associations of the NPP/ GPP ratio with climatic variability challenge the conventional assumption that the NPP/ GPP ratio should be consistent independent of environmental conditions. More importantly, the findings of this study have fundamental significance for our understanding of ongoing global climatic change. In regions and time periods experiencing drought or increased temperatures, plant ecosystems would suffer a higher ecosystem respiration cost and their net productivity would shrink. [ABSTRACT FROM AUTHOR]

Wildfires, a common disturbance in ecosystems, can be an immediate and dominant source of interannual carbon variability. In this study, we used an instantaneous Moderate Resolution Imaging Spectroradiometer (MODIS) global disturbance index algorithm to explore continuous spatiotemporal patterns of forest fires in Northeast China. The forest fires that were sensed remotely were then validated by field records. The findings suggest that the disturbance index is effective in locating forest fires in Northeast China, as evidenced by a close match with field fire records. We found that the incidence of forest fires was closely linked to extreme conditions of climate warming and drought, and more fires occurred in dry years than in wet years. Among different forest types, shrublands, mixed forest, and deciduous needleleaf forests were more prone to wildfires because of their fire regime characteristics. The study demonstrates that the algorithm was effective in detecting forest fires from 2003 to 2011 in Northeast China, providing fundamental data for forest inventory and large-scale ecological applications. [ABSTRACT FROM AUTHOR]

Aim To test two predictions of the phylogenetic niche conservatism hypothesis for the latitudinal diversity gradient: (1) species in colder regions tend to be more phylogenetically related to each other (i.e. greater phylogenetic clustering) than those in warmer regions, and (2) clades are younger in colder regions. Location North America. Methods Correlation analysis was used to relate richness, mean clade age and phylogenetic relatedness (measured as phylogenetic species variability and net relatedness index) of angiosperm trees in 1175 regional assemblages (each with 12100 km2) to latitude and minimum temperature. The analysis was conducted for North America north of Mexico as a whole as well as for each of the three longitudinal bands (eastern, central and western) of North America. Results Species richness and mean clade age are negatively correlated with latitude and positively correlated with minimum temperature. Tree species in regional assemblages tend to be more phylogenetically related (clustered) in regions at higher latitudes with lower temperatures. Main conclusions The results of this study support two of the major predictions of the phylogenetic niche conservatism hypothesis for the latitudinal diversity gradient: species tend to be more phylogenetically clustered and ages of clades tend to be younger in colder regions, compared with those in warmer regions. [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]

Using historical General Land Office record as a reference, this study employed a landscape-scale disturbance and succession model to estimate the future cumulative effects of six alternative management plans on the tree species composition for various physiographic settings for the Mark Twain National Forest in Missouri. The results indicate that over a 200-year horizon, the relative abundance of black oak and pine species groups will decrease and the relative abundance of the white oak species group will increase, regardless of management strategy. General Land Office witness tree records provide a measure of tree species composition in the period from 1800 to 1850, prior to the large-scale influx of European settlers. Compared to the tree species composition described in the General Land Office records, the six contemporary management alternatives considered all would lead to a lower abundance of pine species, a higher abundance of red/black oak species, and a slightly higher abundance of white oak species after 200 years. Impacts of management on tree species composition varied with physiographic settings. The projected relative abundance of pine differed significantly across the five physiographic classes over the first 40 years of the simulation. In the medium term (simulation years 41–100) the projected relative pine abundance differed significantly among only four physiographic classes. In the long term (simulation years 100–200) the projected relative pine abundance differed for only one physiographic class. In contrast, differences among physiographic classes in the relative abundance of black oaks and white oaks increased over time. In general, the expected long-term differences in relative tree species abundance among six proposed alternative management plans are small compared to shifts in tree species composition that have occurred from 1850 to the present. [Copyright &y& Elsevier]

There is a widespread belief that warmer climate forests suffer more folivory, as a proportion of leaf area, than cooler climate forests. However, there is a need for closely standardized studies to test this assumption. In this study, we estimated total folivory as percentage area damaged in freshly fallen, undecayed autumn leaves from the forest floor during the lifetime of deciduous tree leaves, using scanner-linked software. Over a period of 2 years, 154 samples were taken at 96 forested localities in eastern North America, spanning 17° of latitude. In terms of percentage area damage per leaf, the results in both years sampled suggest that there is significantly more damage in warmer, lower latitude areas of eastern North America. The decreasing folivory rate is higher in northern than in southern regions. The observations of a latitudinal trend may suggest that 'biotic' interaction is indeed more important in warmer temperate climates compared to cool temperate climates. [ABSTRACT FROM AUTHOR]

Prior research on tree line dynamics has primarily been based on field inventory data, and little is known about the potential for using remotely sensed imagery to detect change. The present study developed a new methodology by combining remote sensing and field survey data to examine dynamics of the pristine forest in the tree line area on Changbai Mountain in Northeast China over the past two decades. The new method normalized remote sensing data by using the adjacent old-growth coniferous forest (close to climax) below the tree line as the reference (assuming steady state) to eliminate various potential errors associated with different satellite sensors, atmospheric conditions and seasonal vegetation changes. Specifically, we used a ratio of normalised difference vegetation index (NDVI) between the tree line forest (birch) and the referenced old-growth coniferous forest, as well as a ratio between the interface forest against the referenced coniferous forest, to investigate growth dynamics of the tree line forest from 1977 to 1999. The interface forest is distributed between the tree line forest and non-forest zone. Compared with traditional methods using remote sensing data, the new method has higher sensitivity to tree line dynamics. We found that the tree line delineated from satellite imagery had shown no shift in the past decades. However, the NDVI ratio of tree line forest against the reference forest increased from 0.9 to 1.2 from 1977 to 1999, and the ratio of interface forest against the reference forest increased from 0.83 to 0.98, indicating that growth of the tree line forest apparently exceeded that of the reference coniferous forest and had grown denser. Field surveys also supported the conclusion from remote sensing results that the tree line forest on Changbai Mountain has grown denser in the past decades. From 1980 to 2002, basal area of the tree line forest increased 35% (from 18.8 to 25.3 m2 ha-1); at the same time the NDVI ratio increased about 33%. This study suggests that it is possible to monitor growth of the tree line forest based on multi-temporal remote sensing images. We speculate that global warming may have contributed to the observed rapid growth of the tree line forest because temperature is a major limiting factor among climatic variables in the tree line forest and effect from other factors, such as fire, harvesting and snow and wind damage, were not evident in this protected area in the past decades. [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]

Abstract: Previous research addressing the unequal distribution of locally desirable land (LDL) has mainly ignored their associated environments (i.e., rural or urban). However, this study proposed a new framework that treats rural and urban regions separately. In rural areas, the LDLs included all public lands. In urbanized areas, the LDLs were defined as green open spaces. Potential inequities in the distribution of LDL were assessed with respect to socioeconomic characteristics of residents in the State of Georgia. Using US Census Bureau Data (2000), Census Block Groups (CBGs) adjacent to LDLs were compared to CBGs outside of LDLs on four socioeconomic variables (per capita income, occupation, education, and race) in urban, suburban and rural environments. Results showed that CBGs adjacent to LDLs were composed of statistically significant upper-class communities containing fewer blue-collar workers, more whites, and higher income and higher educated people in rural, suburban and urban areas. [Copyright &y& Elsevier]

Abstract: A novel manufacturing process for catalyst coated membrane (CCM) was utilized to fabricate the membrane electrode assemblies (MEA) for solid polymer electrolyte (SPE) water electrolysis. The properties and performance of the modified CCM were analyzed and evaluated by SEM, electrochemistry impedance spectroscopy (EIS) and I–V curves. The characterizations reveal that the sprayed Nafion layers are very effective for increasing the reaction interface between SPE and the electrode catalyst layer. The test experiments show that the SPE water electrolyzer with new MEA structure can lower about 0.1V of water electrolysis voltage at atmosphere pressure and 2Acm−2. [Copyright &y& Elsevier]

Abstract: A bifunctional RuO2–IrO2/Pt electrocatalyst for the unitized regenerative fuel cell (URFC) was synthesized by colloid deposition and characterized by analytical methods like TEM, XRD, etc. The result reveals that RuO2–IrO2 was well dispersed and deposited on the surface of Pt black. With deposited RuO2–IrO2/Pt as the catalyst of oxygen electrode, the performance of fuel cell/water electrolysis of unitized regenerative fuel cell (URFC) was studied in detail. URFC with deposited RuO2–IrO2/Pt shows better performance than that of URFC with mixed RuO2–IrO2/Pt catalyst. Cyclic performance of URFC with deposited RuO2–IrO2/Pt is very stable during 10 cyclic tests. [Copyright &y& Elsevier]

Abstract: Nano-sized SnO2 particles were prepared by the fusion of SnCl2·2H2O with sodium nitrate. X-ray diffraction and TEM were used to study the samples. According to XRD and TEM results, the average particle size/crystal sizes of SnO2 increase from 2.9 nm/2.5 nm to 8.6 nm/8.4 nm. The experiments reveal that the effects of synthesis temperature and synthesis time on the crystalline size are significant but the influence of reaction mixture composition on the particle size is rather small. Nano-sized SnO2 with advisable crystalline size can be obtained by the control of reaction mixture composition, synthesis temperature and synthesis time. [Copyright &y& Elsevier]

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]