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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]

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]

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

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]

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]

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]

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]

• 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 soil water content and temperature determined the maximum photosynthesis. • Sufficient soil water elevated the optimal temperature and maximum photosynthesis. • The optimal environmental configuration for the alpine meadow was detected. • If soil water is high, higher temperature and VPD are beneficial for carbon uptake. The changes in the carbon sink function of sensitive and fragile alpine ecosystems under climate change are widely concerned. Radiation, temperature, and water resources play important roles in regulating carbon assimilation. Therefore, it is important to detect the optimal configuration of environmental factors for the photosynthesis of alpine meadow ecosystems. In this study, based on 10-year flux and corresponding environmental observations in a typical alpine meadow ecosystem, the optimal environmental configuration that could realistically occur in the natural world for photosynthesis was detected. The results indicated that the temperature and water conditions were the primary limiting factors, as radiation resources are abundant on the Tibetan Plateau. The optimal temperature for photosynthesis (TA opt) was determined to be 11.92 ℃ based on the entire observation dataset, with a maximum photosynthetic capacity (GPP max) of 0.20 mg CO 2 m−2 s−1. However, the TA opt and the corresponding GPP max could be elevated when the soil water content (SWC) was abundant. When SWC exceeded 0.26 m3 m−3, TA opt increased to 13.41 ℃, and the corresponding GPP max reached as high as 0.30 mg CO 2 m−2 s−1, which is the maximum the ecosystem could reach. Thus, the optimal environmental configuration for photosynthesis that could realistically occur in the natural world in this alpine meadow was air temperature (TA)=13.41 ℃, SWC=0.28 m3 m−3, vapor pressure deficit (VPD)=0.61 kPa, net radiation (RN)=411.53 J m−2 s−1. According to this study, it could be inferred that within a reasonable range, higher temperatures and VPD would benefit photosynthesis in this alpine meadow as long as the soil water supply is sufficient. The climate on the Tibetan Plateau is arid with high VPD and is experiencing warming due to climate change. Consequently, alpine ecosystems situated in relatively humid regions with sufficient soil water resources may exhibit greater potential for carbon sequestration than previously estimated. [ABSTRACT FROM AUTHOR]

The alpine ecosystems on the Qinghai-Tibetan Plateau are quite sensitive to climate change. The increasing temperature and changing precipitation patterns greatly affect the gross primary productivity (GPP) and disturb the carbon balances of these alpine ecosystems. To clarify the impacts of future climate change across the Qinghai-Tibetan Plateau, it is important to address the scientific issue "Which factor would dominate interannual variability (IAV) in GPP and through which path does it work?" To clarify this issue, two key processes, growing season length (GSL) and maximum photosynthetic capacity (GPP max), were introduced to reveal the underlying mechanisms, and which of the environmental factors dominated their variations were studied specifically based on the flux and corresponding environmental observation data obtained in different types of alpine ecosystems across the Qinghai-Tibetan Plateau in this study. The results indicated that across the temperature- and water-limited alpine ecosystems, the temperature controlled the GSL, but the water conditions dominated the variations in GPP max. The soil water content (SWC) dominated GPP max , which could explain 89% of the variation in GPP max. The GSL alone was incapable of explaining IAV in GPP. Conversely, GPP max is robust in explaining IAV in GPP, which could explain 94% of the annual GPP. Therefore, climate change would probably drive IAV in GPP through the path of "SWC → GPP max → annual GPP" on the Qinghai-Tibetan Plateau. In addition, GPP max together with GSL (GSL × GPP max) could explain 99% of IAV in GPP, as they indicated the length of the carbon uptake time and the capacity of carbon sequestration, respectively. This study provides a new perspective on the predominant causes of IAV in GPP in alpine ecosystems, indicating that the changing precipitation patterns under future climate change will play a dominant role in affecting the carbon sink function of the Qinghai-Tibetan Plateau. [Display omitted] • Temperature dominated the growing season length (GSL) in alpine ecosystems. • Soil water content (SWC) dominated the maximum photosynthetic capacity (GPP max). • GPP max rather than GSL dominated the annual GPP. • GSL and GPP max coexplained 99% of the interannual variability in annual GPP. • Climate change drove GPP through two key underlying processes: GSL and GPP max. [ABSTRACT FROM AUTHOR]