Global responses of wetland methane emissions to extreme temperature and precipitation.

As global warming continues, events of extreme heat or heavy precipitation will become more frequent, while events of extreme cold will become less so. How wetlands around the globe will react to these extreme events is unclear yet critical, because they are among the greatest natural sources of methane(CH4). Here we use seven indices of extreme climate and the rate of methane emission from global wetlands(WME) during 2000-2019 simulated by 12 published models as input data. Our analyses suggest that extreme cold (particularly extreme low temperatures) inhibits WME, whereas extreme heat (particularly extreme high temperatures) accelerates WME. Our results also suggest that daily precipitation >10 mm accelerates WME, while much higher daily precipitation levels can slow WME. The correlation of extreme high temperature and precipitation with rate of WME became stronger during the study period, while the correlation between extreme low temperature and WME rate became weaker.

Observational constraints reduce model spread but not uncertainty in global wetland methane emission estimates.

The recent rise in atmospheric methane (CH4 ) concentrations accelerates climate change and offsets mitigation efforts. Although wetlands are the largest natural CH4 source, estimates of global wetland CH4 emissions vary widely among approaches taken by bottom-up (BU) process-based biogeochemical models and top-down (TD) atmospheric inversion methods. Here, we integrate in situ measurements, multi-model ensembles, and a machine learning upscaling product into the International Land Model Benchmarking system to examine the relationship between wetland CH4 emission estimates and model performance. We find that using better-performing models identified by observational constraints reduces the spread of wetland CH4 emission estimates by 62% and 39% for BU- and TD-based approaches, respectively. However, global BU and TD CH4 emission estimate discrepancies increased by about 15% (from 31 to 36 TgCH4 year-1 ) when the top 20% models were used, although we consider this result moderately uncertain given the unevenly distributed global observations. Our analyses demonstrate that model performance ranking is subject to benchmark selection due to large inter-site variability, highlighting the importance of expanding coverage of benchmark sites to diverse environmental conditions. We encourage future development of wetland CH4 models to move beyond static benchmarking and focus on evaluating site-specific and ecosystem-specific variabilities inferred from observations.

Methane emissions respond to soil temperature in convergent patterns but divergent sensitivities across wetlands along altitude.

Among the global coordinated patterns in soil temperature and methane emission from wetlands, a declining trend of optimal soil temperature for methane emissions from low to high latitudes has been witnessed, while the corresponding trend along the altitudinal gradient has not yet been investigated. We therefore selected two natural wetlands located at contrasting climatic zones from foothill and mountainside of Nepal Himalayas, to test: (1) whether the optimal temperature for methane emissions decreases from low to high altitude, and (2) whether there is a difference in temperature sensitivity of methane emissions from those wetlands. We found significant spatial and temporal variation of methane emissions between the two wetlands and seasons. Soil temperature was the dominant driver for seasonal variation in methane emissions from both wetlands, though its effect was perplexed by the level of standing water, aquatic plants, and dissolved organic carbon, particularly in the deep water area. When integrative comparison was conducted by adding the existing data from wetlands of diverse altitudes, and the latitude-for-altitude effect was taken into account, we found the baseline soil temperatures decrease whilst the altitude rises with respect to a rapid increase in methane emission from all wetlands, however, remarkably higher sensitivity of methane emissions to soil temperature (apparent Q10 ) was found in mid-altitude wetland. We provide the first evidence of an apparent decline in optimal temperature for methane emissions with increasing elevation. These findings suggest a convergent pattern of methane emissions with respect to seasonal temperature shifts from wetlands along altitudinal gradient, while a divergent pattern in temperature sensitivities exhibits a single peak in mid-altitude.

Critical land change information enhances the understanding of carbon balance in the United States.

Large-scale terrestrial carbon (C) estimating studies using methods such as atmospheric inversion, biogeochemical modeling, and field inventories have produced different results. The goal of this study was to integrate fine-scale processes including land use and land cover change into a large-scale ecosystem framework. We analyzed the terrestrial C budget of the conterminous United States from 1971 to 2015 at 1-km resolution using an enhanced dynamic global vegetation model and comprehensive land cover change data. Effects of atmospheric CO2 fertilization, nitrogen deposition, climate, wildland fire, harvest, and land use/land cover change (LUCC) were considered. We estimate annual C losses from cropland harvest, forest clearcut and thinning, fire, and LUCC were 436.8, 117.9, 10.5, and 10.4 TgC/year, respectively. C stored in ecosystems increased from 119,494 to 127,157 TgC between 1971 and 2015, indicating a mean annual net C sink of 170.3 TgC/year. Although ecosystem net primary production increased by approximately 12.3 TgC/year, most of it was offset by increased C loss from harvest and natural disturbance and increased ecosystem respiration related to forest aging. As a result, the strength of the overall ecosystem C sink did not increase over time. Our modeled results indicate the conterminous US C sink was about 30% smaller than previous modeling studies, but converged more closely with inventory data.

Global vegetation biomass production efficiency constrained by models and observations.

Plants use only a fraction of their photosynthetically derived carbon for biomass production (BP). The biomass production efficiency (BPE), defined as the ratio of BP to photosynthesis, and its variation across and within vegetation types is poorly understood, which hinders our capacity to accurately estimate carbon turnover times and carbon sinks. Here, we present a new global estimation of BPE obtained by combining field measurements from 113 sites with 14 carbon cycle models. Our best estimate of global BPE is 0.41 ± 0.05, excluding cropland. The largest BPE is found in boreal forests (0.48 ± 0.06) and the lowest in tropical forests (0.40 ± 0.04). Carbon cycle models overestimate BPE, although models with carbon-nitrogen interactions tend to be more realistic. Using observation-based estimates of global photosynthesis, we quantify the global BP of non-cropland ecosystems of 41 ± 6 Pg C/year. This flux is less than net primary production as it does not contain carbon allocated to symbionts, used for exudates or volatile carbon compound emissions to the atmosphere. Our study reveals a positive bias of 24 ± 11% in the model-estimated BP (10 of 14 models). When correcting models for this bias while leaving modeled carbon turnover times unchanged, we found that the global ecosystem carbon storage change during the last century is decreased by 67% (or 58 Pg C).

Rainfall manipulation experiments as simulated by terrestrial biosphere models: Where do we stand?

Changes in rainfall amounts and patterns have been observed and are expected to continue in the near future with potentially significant ecological and societal consequences. Modelling vegetation responses to changes in rainfall is thus crucial to project water and carbon cycles in the future. In this study, we present the results of a new model-data intercomparison project, where we tested the ability of 10 terrestrial biosphere models to reproduce the observed sensitivity of ecosystem productivity to rainfall changes at 10 sites across the globe, in nine of which, rainfall exclusion and/or irrigation experiments had been performed. The key results are as follows: (a) Inter-model variation is generally large and model agreement varies with timescales. In severely water-limited sites, models only agree on the interannual variability of evapotranspiration and to a smaller extent on gross primary productivity. In more mesic sites, model agreement for both water and carbon fluxes is typically higher on fine (daily-monthly) timescales and reduces on longer (seasonal-annual) scales. (b) Models on average overestimate the relationship between ecosystem productivity and mean rainfall amounts across sites (in space) and have a low capacity in reproducing the temporal (interannual) sensitivity of vegetation productivity to annual rainfall at a given site, even though observation uncertainty is comparable to inter-model variability. (c) Most models reproduced the sign of the observed patterns in productivity changes in rainfall manipulation experiments but had a low capacity in reproducing the observed magnitude of productivity changes. Models better reproduced the observed productivity responses due to rainfall exclusion than addition. (d) All models attribute ecosystem productivity changes to the intensity of vegetation stress and peak leaf area, whereas the impact of the change in growing season length is negligible. The relative contribution of the peak leaf area and vegetation stress intensity was highly variable among models.

Modelling the impacts of climate and land use changes on soil water erosion: Model applications, limitations and future challenges.

The world is experiencing serious soil losses. Soil erosion has become an important environmental problem in certain regions and is strongly affected by climate and land use changes. By selecting and reviewing 13 extensively used soil water erosion models (SWEMs) from the published literature, we summarize the current model-based knowledge on how climate factors (e.g., rainfall, freeze-thaw cycles, rainstorms, temperature and atmospheric CO2 concentrations) and land use change impact soil erosion worldwide. This study also provides a critical review of the application of these 13 SWEMs. By comparing model structures, features, prediction accuracies, and erosion processes, we recommend the most suitable SWEMs for different regions of the globe (Asia, Europe, Africa and the America) based on the evaluations of 13 SWEMs. Future soil erosion could be simulated using the RUSLE, LISEM, WEPP v2010.1, SWAT, EPIC, KINEROS and AGNPS models in Asia; the RUSLE, WEPP v2010.1, SWAT, EPIC, WATEM-SEDEM, MEFIDIS, AGNPS and AnnAGNPS models in Europe; the RUSLE, LISEM, SWAT, and AGNPS models in Africa; and the WEPP v2010.1, SWAT, EPIC, KINEROS, AGNPS and AnnAGNPS models in America. Finally, the limitations and challenges of the 13 SWEMs are highlighted.

Interannual variation in methane emissions from tropical wetlands triggered by repeated El Niño Southern Oscillation.

Methane (CH4 ) emissions from tropical wetlands contribute 60%-80% of global natural wetland CH4 emissions. Decreased wetland CH4 emissions can act as a negative feedback mechanism for future climate warming and vice versa. The impact of the El Niño-Southern Oscillation (ENSO) on CH4 emissions from wetlands remains poorly quantified at both regional and global scales, and El Niño events are expected to become more severe based on climate models' projections. We use a process-based model of global wetland CH4 emissions to investigate the impacts of the ENSO on CH4 emissions in tropical wetlands for the period from 1950 to 2012. The results show that CH4 emissions from tropical wetlands respond strongly to repeated ENSO events, with negative anomalies occurring during El Niño periods and with positive anomalies occurring during La Niña periods. An approximately 8-month time lag was detected between tropical wetland CH4 emissions and ENSO events, which was caused by the combined time lag effects of ENSO events on precipitation and temperature over tropical wetlands. The ENSO can explain 49% of interannual variations for tropical wetland CH4 emissions. Furthermore, relative to neutral years, changes in temperature have much stronger effects on tropical wetland CH4 emissions than the changes in precipitation during ENSO periods. The occurrence of several El Niño events contributed to a lower decadal mean growth rate in atmospheric CH4 concentrations throughout the 1980s and 1990s and to stable atmospheric CH4 concentrations from 1999 to 2006, resulting in negative feedback to global warming.

Soil properties and species composition under different grazing intensity in an alpine meadow on the eastern Tibetan Plateau, China.

As the main form of land use and human disturbance of grassland, livestock grazing has great influences on the soil resources and plant communities. This study observed the variation of soil properties and community characteristics of four treatments of different grazing intensity (no grazing, UG; light grazing, LG; moderate grazing, MG; and heavy grazing, HG) in an alpine meadow of Sichuan Province on the northeastern margin of the Tibetan Plateau. The results showed that grazing increased the pH, soil bulk density (BD), and contents of total carbon (TC) and total nitrogen (TN), and the BD increased while the others decreased with the grazing intensity. At the community level, with the increase of the grazing intensity, the vegetation coverage (R 2 = 0.61, P < 0.001), mean height of community (R 2 = 0.37, P < 0.001), aboveground biomass (R 2 = 0.54, P < 0.001), litter biomass (R 2 = 0.84, P < 0.001), and percentage of aboveground biomass of palatable grasses to total biomass (R 2 = 0.74, P < 0.001) significantly decreased, while the belowground biomass (R 2 = 0.72, P < 0.001) and the root/shoot (R/S) ratio (R 2 = 0.65, P < 0.001) increased. The species richness was the greatest at LG and the total biomass at UG. With grazing, the dominant species of the plant community shifted from palatable grasses (Gramineae and Cyperaceae) to unpalatable grasses (Compositae and Ranunculaceae). Based on the results, LG may be the optimal grassland management mode to be used in the long time in the alpine meadow of the Tibetan Plateau.

Carbon accumulation and sequestration of lakes in China during the Holocene.

Understanding the responses of lake systems to past climate change and human activity is critical for assessing and predicting the fate of lake carbon (C) in the future. In this study, we synthesized records of the sediment accumulation from 82 lakes and of C sequestration from 58 lakes with direct organic C measurements throughout China. We also identified the controlling factors of the long-term sediment and C accumulation dynamics in these lakes during the past 12 ka (1 ka = 1000 cal yr BP). Our results indicated an overall increasing trend of sediment and C accumulation since 12 ka, with an accumulation peak in the last couple of millennia for lakes in China, corresponding to terrestrial organic matter input due to land-use change. The Holocene lake sediment accumulation rate (SAR) and C accumulation rate (CAR) averaged (mean ± SE) 0.47 ± 0.05 mm yr(-1) and 7.7 ± 1.4 g C m(-2)  yr(-1) in China, respectively, comparable to the previous estimates for boreal and temperate regions. The SAR for lakes in the East Plain of subtropical China (1.05 ± 0.28 mm yr(-1) ) was higher than those in other regions (P < 0.05). However, CAR did not vary significantly among regions. Overall, the variability and history of climate and anthropogenic interference regulated the temporal and spatial dynamics of sediment and C sequestration for lakes in China. We estimated the total amount of C burial in lakes of China as 8.0 ± 1.0 Pg C. This first estimation of total C storage and dynamics in lakes of China confirms the importance of lakes in land C budget in monsoon-influenced regions.

Regional drought-induced reduction in the biomass carbon sink of Canada's boreal forests.

The boreal forests, identified as a critical "tipping element" of the Earth's climate system, play a critical role in the global carbon budget. Recent findings have suggested that terrestrial carbon sinks in northern high-latitude regions are weakening, but there has been little observational evidence to support the idea of a reduction of carbon sinks in northern terrestrial ecosystems. Here, we estimated changes in the biomass carbon sink of natural stands throughout Canada's boreal forests using data from long-term forest permanent sampling plots. We found that in recent decades, the rate of biomass change decreased significantly in western Canada (Alberta, Saskatchewan, and Manitoba), but there was no significant trend for eastern Canada (Ontario and Quebec). Our results revealed that recent climate change, and especially drought-induced water stress, is the dominant cause of the observed reduction in the biomass carbon sink, suggesting that western Canada's boreal forests may become net carbon sources if the climate change-induced droughts continue to intensify.

An optimized water table depth detected for mitigating global warming potential of greenhouse gas emissions in wetland of Qinghai-Tibetan Plateau.

Climate change and human activities have intensified variations of water table depth (WTD) in wetlands around the world, which may strongly affect greenhouse gas emissions. Here, we analyzed how emissions of CO2, CH4, and N2O from the Zoige wetland on the Qinghai-Tibetan Plateau (QTP) vary with the WTD. Our data indicate that the wetland shows net positive global warming potential (11.72 tCO2-e ha-1 yr-1), and its emissions of greenhouse gases are driven primarily by WTD. Our analysis suggests that an optimal WTD exists, which at our study site was approximately 18 cm, for mitigating increases in global warming potential from the wetland. Our study provides insights into how climate change and human acitivies affect greenhouse gas emissions from alpine wetlands, and they suggest that water table management may be effective at mitigating future increases in emissions.

Estimating wetland CH4 emissions on the Qinghai-Tibetan Plateau based on a processed model coupled with inundation dynamics between 1960 and 2100.

Quantifying the impacts of climate change and wetland area dynamics on methane (CH4) emissions in the Qinghai-Tibetan Plateau (QTP) is crucial for enhancing our understanding of regional and global CH4 budgets. However, a major source of uncertainty in estimating wetland methane emissions stems from the limited delineation of wetland area dynamics. In this study, we integrated dynamic wetland inundation schemes into a process-based model to quantify the contributions of wetland area variations to natural wetland CH4 emissions on the QTP, both historically and in the future. The results revealed that climate change significantly influenced the spatiotemporal distribution of wetland CH4 emissions, with wetland inundation dynamics contributing between 21.84 % and 27.18 % of the increase in CH4 emissions from 1960 to 2020. Under future climate change scenarios, wetland CH4 emissions are projected to exhibit a more pronounced increasing trend, with wetland inundation dynamics projected to contribute 18.94 % to 21.80 % of the increase in CH4 emissions in the QTP under seven Shared Socioeconomic Pathways scenarios.

The impacts of climate change and human activities on biogeochemical cycles on the Qinghai-Tibetan Plateau.

With a pace of about twice the observed rate of global warming, the temperature on the Qinghai-Tibetan Plateau (Earth's 'third pole') has increased by 0.2 °C per decade over the past 50 years, which results in significant permafrost thawing and glacier retreat. Our review suggested that warming enhanced net primary production and soil respiration, decreased methane (CH(4)) emissions from wetlands and increased CH(4) consumption of meadows, but might increase CH(4) emissions from lakes. Warming-induced permafrost thawing and glaciers melting would also result in substantial emission of old carbon dioxide (CO(2)) and CH(4). Nitrous oxide (N(2)O) emission was not stimulated by warming itself, but might be slightly enhanced by wetting. However, there are many uncertainties in such biogeochemical cycles under climate change. Human activities (e.g. grazing, land cover changes) further modified the biogeochemical cycles and amplified such uncertainties on the plateau. If the projected warming and wetting continues, the future biogeochemical cycles will be more complicated. So facing research in this field is an ongoing challenge of integrating field observations with process-based ecosystem models to predict the impacts of future climate change and human activities at various temporal and spatial scales. To reduce the uncertainties and to improve the precision of the predictions of the impacts of climate change and human activities on biogeochemical cycles, efforts should focus on conducting more field observation studies, integrating data within improved models, and developing new knowledge about coupling among carbon, nitrogen, and phosphorus biogeochemical cycles as well as about the role of microbes in these cycles.

An early warning signal for grassland degradation on the Qinghai-Tibetan Plateau.

Intense grazing may lead to grassland degradation on the Qinghai-Tibetan Plateau, but it is difficult to predict where this will occur and to quantify it. Based on a process-based ecosystem model, we define a productivity-based stocking rate threshold that induces extreme grassland degradation to assess whether and where the current grazing activity in the region is sustainable. We find that the current stocking rate is below the threshold in ~80% of grassland areas, but in 55% of these grasslands the stocking rate exceeds half the threshold. According to our model projections, positive effects of climate change including elevated CO2 can partly offset negative effects of grazing across nearly 70% of grasslands on the Plateau, but only in areas below the stocking rate threshold. Our analysis suggests that stocking rate that does not exceed 60% (within 50% to 70%) of the threshold may balance human demands with grassland protection in the face of climate change.

Integrating major agricultural practices into the TRIPLEX-GHG model v2.0 for simulating global cropland nitrous oxide emissions: Development, sensitivity analysis and site evaluation.

Nitrous oxide (N2O) emissions from croplands are one of the most important greenhouse gas sources while the estimation of which remains large uncertainties globally. To simulate N2O emissions from global croplands, the process-based TRIPLEX-GHG model v2.0 was improved by coupling the major agricultural activities. Sensitivity experiment was used to measure the impact of the integrated processes to modeled N2O emission found chemical N fertilization have the highest relative effect sizes. While the coefficient of the NO3- consumption rate for denitrification (COEdNO3), controlling the first step of the denitrification process was identified to be the most sensitive parameter based on sensitivity analysis of model parameters. The model performed well when simulating the magnitude of the daily N2O emissions for 39 calibration sites and the continental mean of the parameters were used to producing reasonable estimations for the means of the measured daily N2O fluxes (R2 = 0.87, slope = 1.07) and emission factors (EFs, R2 = 0.70, slope = 0.72) during the experiment periods. The model reliability was further confirmed by model validation. General trend of modeled daily N2O emissions were reasonably consistent with the observations of selected validated sites. In addition, high correlations between the results of modeled and observed mean N2O emissions (R2 = 0.86, slope = 0.82) and EFs (R2 = 0.66, slope = 0.83) from 68 validation sites were obtained. Further improvement on more detailed estimations for the variation of the environmental factors, management effects as well as accurate model input model driving data are required to reduce the uncertainties of model simulations. Consequently, our simulation results demonstrate that the TRIPLEX-GHG model v2.0 can reliably estimate N2O emissions from various croplands at the global scale, which contributes to closing global N2O budget and sustainable development of agriculture.

The Effects of Drought and Re-Watering on Non-Structural Carbohydrates of Pinus tabulaeformis Seedlings.

Intense and frequent drought events strongly affect plant survival. Non-structural carbohydrates (NSCs) are important "buffers" to maintain plant functions under drought conditions. We conducted a drought manipulation experiment using three-year-old Pinus tabulaeformis Carr. seedlings. The seedlings were first treated under different drought intensities (i.e., no irrigation, severe, and moderate) for 50 days, and then they were re-watered for 25 days to explore the dynamics of NSCs in the leaves, twigs, stems, and roots. The results showed that the no irrigation and severe drought treatments significantly reduced photosynthetic rate by 93.9% and 32.6% for 30 days, respectively, leading to the depletion of the starch storage for hydraulic repair, osmotic adjustment, and plant metabolism. The seedlings under moderate drought condition also exhibited starch storage consumption in leaves and twigs. After re-watering, the reduced photosynthetic rate recovered to the control level within five days in the severe drought group but showed no sign of recovery in the no irrigation group. The seedlings under the severe and moderate drought conditions tended to invest newly fixed C to starch storage and hydraulic repair instead of growth due to the "drought legacy effect". Our findings suggest the depletion and recovery of starch storage are important strategies for P. tabulaeformis seedlings, and they may play key roles in plant resistance and resilience under environmental stress.

Global response of terrestrial gross primary productivity to climate extremes.

Extreme climate events undoubtedly have essential impacts on ecosystem gross primary productivity (GPP), but the global spatio-temporal patterns of GPP responses to climate extremes are unclear. In this study, we analyzed the responses of GPP to temperature and precipitation extremes during historical (1901-2016) and future (2006-2100) periods using climate extreme indices (CEIs) developed by the Expert Team on Climate Change Detection and Indices. Eight temperature-related CEIs and eight precipitation-related CEIs were used for this analysis, along with three future greenhouse gas concentration trajectory scenarios generated by the IPCC: RCP 2.6, RCP 4.5, and RCP 8.5. Our results show that under RCP 4.5 and RCP 8.5, most climate extremes are increasing from the historical period into the future, indicating a warming globe with more frequent and more intense extreme climate events. But the increasing rate is only persistently enhanced with time under scenario RCP 8.5. GPP shows a continuous negative relationship with cold CEIs and positive relationship with wet CEIs from the historical period into the future. In all zonal scales, the changed magnitude of GPP responds strongly to extreme value-related temperature extremes under different scenarios. However, the precipitation-related extremes with the strongest GPP response are various in different regions. In the future, GPP is most sensitive to temperature extremes in upper northern latitudes and in high-altitude regions (e.g., Qinghai-Tibet Plateau) and to precipitation extremes in the tropical zone. This study may provide a basis for predicting how GPP responds to climate extremes and explaining the underlying changes in the carbon cycle.

The significant contribution of lake depth in regulating global lake diffusive methane emissions.

Global lakes have been identified as an important component of natural methane (CH4) sources. Given that lake CH4 emissions involve multiple, complex processes influenced by various environmental factors, estimates of global lake CH4 emissions are largely uncertain. In this study, we compiled global CH4 emission data on 744 lakes from published studies, and found a significantly negative correlation (R2 = 0.50, p < 0.01) between diffusive CH4 flux and lake maximum depth. Further analysis indicated that no significant differences in global sediment CH4 production were found for the different maximum depths investigated. Owing to the longer oxidation pathway, presence of oxycline layer, and the lower nutrient environment, deeper lakes yield less diffusive CH4 efflux compared to shallower lakes. Additionally, we also found that lake area was negatively correlated (R2 = 0.13, p < 0.01) to diffusive CH4 flux. Therefore, based on empirical correlations between lake morphometry (maximum depth and area) and diffusive CH4 emission, as well as the combination of two lake databases, we estimated that the annual diffusive CH4 emission from global lakes is approximately 11.2 (6.2-19.5) Tg CH4/yr, and greater than 84% is emitted from lakes with a mean depth of less than 5 m. Furthermore, two regions, 40-70° N (30.4%) and 20° S∼10° N (37.4%), were found to be the dominant contributors of global lake diffusive CH4 emissions, resulting from the considerable total lake area and the extensive shallow lakes in these regions. This study highlights the significance of the 'depth-effect' which controls the spatial distribution of lake diffusive CH4 flux and allows for the quantification of global lake diffusive CH4 emissions.

Progressive nitrogen limitation across the Tibetan alpine permafrost region.

The ecosystem carbon (C) balance in permafrost regions, which has a global significance in understanding the terrestrial C-climate feedback, is significantly regulated by nitrogen (N) dynamics. However, our knowledge on temporal changes in vegetation N limitation (i.e., the supply of N relative to plant N demand) in permafrost ecosystems is still limited. Based on the combination of isotopic observations derived from a re-sampling campaign along a ~3000 km transect and simulations obtained from a process-based biogeochemical model, here we detect changes in ecosystem N cycle across the Tibetan alpine permafrost region over the past decade. We find that vegetation N limitation becomes stronger despite the increased available N production. The enhanced N limitation on vegetation growth is driven by the joint effects of elevated plant N demand and gaseous N loss. These findings suggest that N would constrain the future trajectory of ecosystem C cycle in this alpine permafrost region.