Dynamics of carbon and water vapor fluxes in three typical ecosystems of Heihe River Basin, Northwestern China.

Understanding the dynamics of carbon and water vapor fluxes in arid inland river basin ecosystems is essential for predicting and assessing the regional carbon-water budget amid climate change. However, studies aiming to unravel the mechanisms driving the variations and coupling process of regional carbon-water budget in a changing environment in arid regions are limited. Here, we used the eddy covariance technique to analyze the relationship between CO2 and H2O fluxes in three typical ecosystems across the upper, middle, and lower reaches of an arid inland river basin in Northwestern China. Our results showed that all ecosystems acted as carbon sinks, with the alpine swamp meadow, cropland, and desert shrubland sequestrating -300.2 ± 0.01, -644.8 ± 2.9, and - 203.7 ± 22.5 g C m-2 yr-1, respectively. Air temperature (Ta) primarily controlled daily gross primary productivity (GPP) and net ecosystem CO2 exchange (NEE) in the irrigated cropland during the growing season, while soil temperature (Ts) and vapor pressure deficit (VPD) regulated these parameters in the alpine swamp meadow and desert shrubland. Additionally, Ta and net radiation (Rn) controlled daily evapotranspiration (ET) in cropland, while Ts and Rn regulated ET at other sites. Consequently, carbon and water vapor fluxes of all three ecosystems tended to be energy-limited during the growing season. The differential responses of carbon and water vapor fluxes in the upper, middle, and lower reaches of these ecosystems to biophysical factors determined their distinct coupling and variations in water use efficiency. Notably, the desert shrub ecosystem in the lower reach of the basin maintained a stable balance between carbon gain and water loss, indicating adaptation to aridity. This study provides valuable insights into the underlying mechanisms behind the changes in carbon and water vapor fluxes and water-use efficiency in arid river basin ecosystems.

Projected soil carbon loss with warming in constrained Earth system models.

The soil carbon-climate feedback is currently the least constrained component of global warming projections, and the major source of uncertainties stems from a poor understanding of soil carbon turnover processes. Here, we assemble data from long-term temperature-controlled soil incubation studies to show that the arctic and boreal region has the shortest intrinsic soil carbon turnover time while tropical forests have the longest one, and current Earth system models overestimate intrinsic turnover time by 30 percent across active, slow and passive carbon pools. Our constraint suggests that the global soils will switch from carbon sink to source, with a loss of 0.22-0.53 petagrams of carbon per year until the end of this century from strong mitigation to worst emission scenarios, suggesting that global soils will provide a strong positive carbon feedback on warming. Such a reversal of global soil carbon balance would lead to a reduction of 66% and 15% in the current estimated remaining carbon budget for limiting global warming well below 1.5 °C and 2 °C, respectively, rendering climate mitigation much more difficult.

Optimal design of surface CO2 observation network to constrain China's land carbon sink.

Accurate estimate of the size of land carbon sink is essential for guiding climate mitigation actions to fulfill China's net-zero ambitions before 2060. The atmospheric inversion is an effective approach to provide spatially explicit estimate of surface CO2 fluxes that are optimally consistent with atmospheric CO2 measurements. But atmospheric inversion of China's land carbon sink has enormous uncertainties, with one major source arising from the poor coverage of CO2 observation stations. Here we use a regional atmospheric inversion framework to design an observation network that could minimize uncertainties in inverted estimate of China's land carbon sink. Compared with the large spread of inverted sink (∼1PgCa-1) from state-of-the-art inversions using existing CO2 observations, the uncertainty is constrained within 0.3PgCa-1 when a total of 30 stations were deployed, and is further reduced to approximately 0.2PgCa-1 when 60 stations were deployed. The proposed stations are mostly distributed over areas with high biosphere productivity during the growing season, such as Southeast China, Northeast China, North China, and the Tibetan Plateau. Moreover, the proposed stations can cover areas where existing satellites have limited coverage due to cloud shadowing in the monsoon season or over complex topography. Such ground-based observation network will be a critical component in the future integrated observing system for monitoring China's land carbon fluxes.

Asymmetry of carbon sequestrations by plant and soil after forestation regulated by soil nitrogen.

Forestation is regarded as an effective strategy for increasing terrestrial carbon sequestration. However, its carbon sink potential remains uncertain due to the scarcity of large-scale sampling data and limited knowledge of the linkage between plant and soil C dynamics. Here, we conduct a large-scale survey of 163 control plots and 614 forested plots involving 25304 trees and 11700 soil samples in northern China to fill this knowledge gap. We find that forestation in northern China contributes a significant carbon sink (913.19 ± 47.58 Tg C), 74% of which is stored in biomass and 26% in soil organic carbon. Further analysis reveals that the biomass carbon sink increases initially but then decreases as soil nitrogen increases, while soil organic carbon significantly decreases in nitrogen-rich soils. These results highlight the importance of incorporating plant and soil interactions, modulated by nitrogen supply in the calculation and modelling of current and future carbon sink potential.

Persistent and enhanced carbon sequestration capacity of alpine grasslands on Earth's Third Pole.

The carbon sequestration capacity of alpine grasslands, composed of alpine meadows and steppes, in the Tibetan Plateau has an essential role in regulating the regional carbon cycle. However, inadequate understanding of its spatiotemporal dynamics and regulatory mechanisms restricts our ability to determine potential climate change impacts. We assessed the spatial and temporal patterns and mechanisms of the net ecosystem exchange (NEE) of carbon dioxide in the Tibetan Plateau. The carbon sequestration of the alpine grasslands ranged from 26.39 to 79.19 Tg C year-1 and had an increasing rate of 1.14 Tg C year-1 between 1982 and 2018. While alpine meadows were relatively strong carbon sinks, the semiarid and arid alpine steppes were nearly carbon neutral. Alpine meadow areas experienced strong increases in carbon sequestration mainly because of increasing temperatures, while alpine steppe areas had weak increases mainly due to increasing precipitation. Carbon sequestration capacity of alpine grasslands on the plateau has undergone persistent enhancement under a warmer and wetter climate.

Observation-based global soil heterotrophic respiration indicates underestimated turnover and sequestration of soil carbon by terrestrial ecosystem models.

Soil heterotrophic respiration (Rh ) refers to the flux of CO2 released from soil to atmosphere as a result of organic matter decomposition by soil microbes and fauna. As one of the major fluxes in the global carbon cycle, large uncertainties still exist in the estimation of global Rh , which further limits our current understanding of carbon accumulation in soils. Here, we applied a Random Forest algorithm to create a global data set of soil Rh , by linking 761 field observations with both abiotic and biotic predictors. We estimated that global Rh was 48.8 ± 0.9 Pg C year-1 for 1982-2018, which was 16% less than the ensemble mean (58.6 ± 9.9 Pg C year-1 ) of 16 terrestrial ecosystem models. By integrating our observational Rh with independent soil carbon stock data sets, we obtained a global mean soil carbon turnover time of 38.3 ± 11 year. Using observation-based turnover times as a constraint, we found that terrestrial ecosystem models simulated faster carbon turnovers, leading to a 30% (74 Pg C) underestimation of terrestrial ecosystem carbon accumulation for the past century, which was especially pronounced at high latitudes. This underestimation is equivalent to 45% of the total carbon emissions (164 Pg C) caused by global land-use change at the same time. Our analyses highlight the need to constrain ecosystem models using observation-based and locally adapted Rh values to obtain reliable projections of the carbon sink capacity of terrestrial ecosystems.

Carbon turnover times shape topsoil carbon difference between Tibetan Plateau and Arctic tundra.

The Tibetan Plateau (TP) and Arctic permafrost constitute two large reservoirs of organic carbon, but processes which control carbon accumulation within the surface soil layer of these areas would differ due to the interplay of climate, soil and vegetation type. Here, we synthesized currently available soil carbon data to show that mean organic carbon density in the topsoil (0-10 cm) in TP grassland (3.12 ± 0.52 kg C m-2) is less than half of that in Arctic tundra (6.70 ± 1.94 kg C m-2). Such difference is primarily attributed to their difference in radiocarbon-inferred soil carbon turnover times (547 years for TP grassland versus 1609 years for Arctic tundra) rather than to their marginal difference in topsoil carbon inputs. Our findings highlight the importance of improving regional-specific soil carbon turnover and its controlling mechanisms across permafrost affected zones in ecosystem models to fully represent carbon-climate feedback.

The driving factors of mercury storage in the Tibetan grassland soils underlain by permafrost.

Soils, especially permafrost in the Arctic and the Tibetan Plateau, are one of the largest reservoirs of mercury (Hg) in the global environment. The Hg concentration in the grassland soils over the Tibetan Plateau and its driving factors have been less studied. This study analyzes soil total mercury (STHg) concentrations and its vertical distribution in grassland soil samples collected from the Tibetan Plateau. We adopt a nested-grid high-resolution GEOS-Chem model to simulate atmospheric Hg deposition. The relationship between STHg and soil organic carbon (SOC), as well as atmospheric deposition, are explored. Our results show that the STHg concentrations in the Tibetan Plateau are 19.8 ± 12.2 ng/g. The concentrations are higher in the south and lower in the north in the Tibetan Plateau, consistent with the previous results. Our model shows that the average deposition flux of Hg is 3.3 µg m-2 yr-1, with 57% contributed by dry deposition of elemental mercury (Hg0), followed by dry (19%) and wet (24%) deposition of divalent mercury. We calculate the Hg to carbon ratio (RHg:C) as 5.6 ± 6.5 µg Hg/g C, and the estimated STHg is 86.6 ± 101.2 Gg in alpine grasslands in the Tibetan Plateau. We find a positive relationship between STHg and SOC in the Tibetan Plateau (r2 = 0.36) and a similar positive relationship between STHg and atmospheric total Hg deposition (r2 = 0.24). A multiple linear regression involving both variables better model the observed STHg (r2 = 0.42). We conclude that SOC and atmospheric deposition influence STHg simultaneously in this region. The data provides information to quantify the size of the soil Hg pool in the Tibetan Plateau further, which has important implications for the Hg cycles in the permafrost regions as well as on the global scale.

The paleoclimatic footprint in the soil carbon stock of the Tibetan permafrost region.

Tibetan permafrost largely formed during the late Pleistocene glacial period and shrank in the Holocene Thermal Maximum period. Quantifying the impacts of paleoclimatic extremes on soil carbon stock can shed light on the vulnerability of permafrost carbon in the future. Here, we synthesize data from 1114 sites across the Tibetan permafrost region to report that paleoclimate is more important than modern climate in shaping current permafrost carbon distribution, and its importance increases with soil depth, mainly through forming the soil's physiochemical properties. We derive a new estimate of modern soil carbon stock to 3 m depth by including the paleoclimate effects, and find that the stock ([Formula: see text] PgC) is triple that predicted by ecosystem models (11.5 ± 4.2 s.e.m PgC), which use pre-industrial climate to initialize the soil carbon pool. The discrepancy highlights the urgent need to incorporate paleoclimate information into model initialization for simulating permafrost soil carbon stocks.

Spatially-explicit estimate of soil nitrogen stock and its implication for land model across Tibetan alpine permafrost region.

Permafrost soils store a large amount of nitrogen (N) which could be activated under the continuous climate warming. However, compared with carbon (C) stock, little is known about the size and spatial distribution of permafrost N stock. By combining measurements from 519 pedons with two machine learning models (supporting vector machine (SVM) and random forest (RF)), we estimated the size and spatial distribution of N stock across the Tibetan alpine permafrost region. We then compared these spatially-explicit N estimates with simulated N stocks from the Community Land Model (CLM). We found that N density (N amount per area) in the top three meters was 1.58 kg N m-2 (interquartile range: 1.40-1.76) across the study area, constituting a total of 1802 Tg N (interquartile range: 1605-2008), decreasing from the southeast to the northwest of the plateau. N stored below 1 m accounted for 48% of the total N stock in the top three meters. CLM4.5 significantly underestimated the N stock on the Tibetan Plateau, primarily in areas with arid/semi-arid climate. The process of biological N fixation played a key role in the underestimation of N stock prediction. Overall, our study highlights that it is imperative to improve the simulation of N processes and permafrost N stocks in land models to better predict ecological consequences induced by rapid and widespread permafrost degradation.

Distinct microbial communities in the active and permafrost layers on the Tibetan Plateau.

Permafrost represents an important understudied genetic resource. Soil microorganisms play important roles in regulating biogeochemical cycles and maintaining ecosystem function. However, our knowledge of patterns and drivers of permafrost microbial communities is limited over broad geographic scales. Using high-throughput Illumina sequencing, this study compared soil bacterial, archaeal and fungal communities between the active and permafrost layers on the Tibetan Plateau. Our results indicated that microbial alpha diversity was significantly higher in the active layer than in the permafrost layer with the exception of fungal Shannon-Wiener index and Simpson's diversity index, and microbial community structures were significantly different between the two layers. Our results also revealed that environmental factors such as soil fertility (soil organic carbon, dissolved organic carbon and total nitrogen contents) were the primary drivers of the beta diversity of bacterial, archaeal and fungal communities in the active layer. In contrast, environmental variables such as the mean annual precipitation and total phosphorus played dominant roles in driving the microbial beta diversity in the permafrost layer. Spatial distance was important for predicting the bacterial and archaeal beta diversity in both the active and permafrost layers, but not for fungal communities. Collectively, these results demonstrated different driving factors of microbial beta diversity between the active layer and permafrost layer, implying that the drivers of the microbial beta diversity observed in the active layer cannot be used to predict the biogeographic patterns of the microbial beta diversity in the permafrost layer.

Warming effects on permafrost ecosystem carbon fluxes associated with plant nutrients.

Large uncertainties exist in carbon (C)-climate feedback in permafrost regions, partly due to an insufficient understanding of warming effects on nutrient availabilities and their subsequent impacts on vegetation C sequestration. Although a warming climate may promote a substantial release of soil C to the atmosphere, a warming-induced increase in soil nutrient availability may enhance plant productivity, thus offsetting C loss from microbial respiration. Here, we present evidence that the positive temperature effect on carbon dioxide (CO2 ) fluxes may be weakened by reduced plant nitrogen (N) and phosphorous (P) concentrations in a Tibetan permafrost ecosystem. Although experimental warming initially enhanced ecosystem CO2 uptake, the increased rate disappeared after the period of peak plant growth during the early growing season, even though soil moisture was not a limiting factor in this swamp meadow ecosystem. We observed that warming did not significantly affect soil extractable N or P during the period of peak growth, but decreased both N and P concentrations in the leaves of dominant plant species, likely caused by accelerated plant senescence in the warmed plots. The attenuated warming effect on CO2 assimilation during the late growing season was associated with lowered leaf N and P concentrations. These findings suggest that warming-mediated nutrient changes may not always benefit ecosystem C uptake in permafrost regions, making our ability to predict the C balance in these warming-sensitive ecosystems more challenging than previously thought.

Grassland restoration reduces water yield in the headstream region of Yangtze River.

Large-scale ecological restoration programs are considered as one of the key strategies to enhance ecosystem services. The Headstream region of Yangtze River (HYZR), which is claimed to be China's Water Tower but witnessed the rapid grassland deterioration during 1970s-2000, has seen a series of grassland restoration programs since 2000. But few studies have thoroughly estimated the hydrological effect of this recent grassland restoration. Here we show that restoration significantly reduces growing-season water yield coefficient (WYC) from 0.37 ± 0.07 during 1982-1999 to 0.24 ± 0.07 during 2000-2012. Increased evapotranspiration (ET) is identified as the main driver for the observed decline in WYC. After factoring out climate change effects, vegetation restoration reduces streamflow by 9.75 ± 0.48 mm from the period 1982-1999 to the period 2000-2012, amounting to 16.4 ± 0. 80% of climatological growing-season streamflow. In contrary to water yield, restoration is conducive to soil water retention - an argument that is supported by long-term in-situ grazing exclusion experiment. Grassland restoration therefore improves local soil water conditions but undercuts gain in downstream water resources associated with precipitation increases.

Determinants of carbon release from the active layer and permafrost deposits on the Tibetan Plateau.

The sign and magnitude of permafrost carbon (C)-climate feedback are highly uncertain due to the limited understanding of the decomposability of thawing permafrost and relevant mechanistic controls over C release. Here, by combining aerobic incubation with biomarker analysis and a three-pool model, we reveal that C quality (represented by a higher amount of fast cycling C but a lower amount of recalcitrant C compounds) and normalized CO2-C release in permafrost deposits were similar or even higher than those in the active layer, demonstrating a high vulnerability of C in Tibetan upland permafrost. We also illustrate that C quality exerts the most control over CO2-C release from the active layer, whereas soil microbial abundance is more directly associated with CO2-C release after permafrost thaw. Taken together, our findings highlight the importance of incorporating microbial properties into Earth System Models when predicting permafrost C dynamics under a changing environment.

The permafrost carbon inventory on the Tibetan Plateau: a new evaluation using deep sediment cores.

The permafrost organic carbon (OC) stock is of global significance because of its large pool size and the potential positive feedback to climate warming. However, due to the lack of systematic field observations and appropriate upscaling methodologies, substantial uncertainties exist in the permafrost OC budget, which limits our understanding of the fate of frozen carbon in a warming world. In particular, the lack of comprehensive estimates of OC stocks across alpine permafrost means that current knowledge on this issue remains incomplete. Here, we evaluated the pool size and spatial variations of permafrost OC stock to 3 m depth on the Tibetan Plateau by combining systematic measurements from a substantial number of pedons (i.e. 342 three-metre-deep cores and 177 50-cm-deep pits) with a machine learning technique (i.e. support vector machine, SVM). We also quantified uncertainties in permafrost carbon budget by conducting Monte Carlo simulations. Our results revealed that the combination of systematic measurements with the SVM model allowed spatially explicit estimates to be made. The OC density (OC amount per unit area, OCD) exhibited a decreasing trend from the south-eastern to the north-western plateau, with the exception that OCD in the swamp meadow was substantially higher than that in surrounding regions. Our results also demonstrated that Tibetan permafrost stored a large amount of OC in the top 3 m, with the median OC pool size being 15.31 Pg C (interquartile range: 13.03-17.77 Pg C). 44% of OC occurred in deep layers (i.e. 100-300 cm), close to the proportion observed across the northern circumpolar permafrost region. The large carbon pool size together with significant permafrost thawing suggests a risk of carbon emissions and positive climate feedback across the Tibetan alpine permafrost region.

Monitoring plant response to phenanthrene using the red edge of canopy hyperspectral reflectance.

To investigate the mechanisms and potential for the remote sensing of phenanthrene-induced vegetation stress, we measured field canopy spectra, and associated plant and soil parameters in the field controlled experiment in the Yellow River Delta of China. Two widely distributed plant communities, separately dominated by reed (Phragmites australis) and glaucous seepweed (Suaeda salsa), were treated with different doses of phenanthrene. The canopy spectral changes of plant community resulted from the decreases of biomass and foliar projective coverage, while leaf photosynthetic pigment concentrations showed no significance difference among treatments. The spectral response to phenanthrene included a flattened red edge, with decreased first derivative of reflectance. The red edge slope and area consistently responded to phenanthrene, showing a strong relationship with aboveground biomass, coverage and canopy pigments density. These results suggest the potential of remote sensing and the importance of field validation to correctly interpret the causes of the spectral changes.

Increased topsoil carbon stock across China's forests.

Biomass carbon accumulation in forest ecosystems is a widespread phenomenon at both regional and global scales. However, as coupled carbon-climate models predicted, a positive feedback could be triggered if accelerated soil carbon decomposition offsets enhanced vegetation growth under a warming climate. It is thus crucial to reveal whether and how soil carbon stock in forest ecosystems has changed over recent decades. However, large-scale changes in soil carbon stock across forest ecosystems have not yet been carefully examined at both regional and global scales, which have been widely perceived as a big bottleneck in untangling carbon-climate feedback. Using newly developed database and sophisticated data mining approach, here we evaluated temporal changes in topsoil carbon stock across major forest ecosystem in China and analysed potential drivers in soil carbon dynamics over broad geographical scale. Our results indicated that topsoil carbon stock increased significantly within all of five major forest types during the period of 1980s-2000s, with an overall rate of 20.0 g C m(-2) yr(-1) (95% confidence interval, 14.1-25.5). The magnitude of soil carbon accumulation across coniferous forests and coniferous/broadleaved mixed forests exhibited meaningful increases with both mean annual temperature and precipitation. Moreover, soil carbon dynamics across these forest ecosystems were positively associated with clay content, with a larger amount of SOC accumulation occurring in fine-textured soils. In contrast, changes in soil carbon stock across broadleaved forests were insensitive to either climatic or edaphic variables. Overall, these results suggest that soil carbon accumulation does not counteract vegetation carbon sequestration across China's forest ecosystems. The combination of soil carbon accumulation and vegetation carbon sequestration triggers a negative feedback to climate warming, rather than a positive feedback predicted by coupled carbon-climate models.

Soil TPH concentration estimation using vegetation indices in an oil polluted area of eastern China.

Assessing oil pollution using traditional field-based methods over large areas is difficult and expensive. Remote sensing technologies with good spatial and temporal coverage might provide an alternative for monitoring oil pollution by recording the spectral signals of plants growing in polluted soils. Total petroleum hydrocarbon concentrations of soils and the hyperspectral canopy reflectance were measured in wetlands dominated by reeds (Phragmites australis) around oil wells that have been producing oil for approximately 10 years in the Yellow River Delta, eastern China to evaluate the potential of vegetation indices and red edge parameters to estimate soil oil pollution. The detrimental effect of oil pollution on reed communities was confirmed by the evidence that the aboveground biomass decreased from 1076.5 g m(-2) to 5.3 g m(-2) with increasing total petroleum hydrocarbon concentrations ranging from 9.45 mg kg(-1) to 652 mg kg(-1). The modified chlorophyll absorption ratio index (MCARI) best estimated soil TPH concentration among 20 vegetation indices. The linear model involving MCARI had the highest coefficient of determination (R(2) = 0.73) and accuracy of prediction (RMSE = 104.2 mg kg(-1)). For other vegetation indices and red edge parameters, the R(2) and RMSE values ranged from 0.64 to 0.71 and from 120.2 mg kg(-1) to 106.8 mg kg(-1) respectively. The traditional broadband normalized difference vegetation index (NDVI), one of the broadband multispectral vegetation indices (BMVIs), produced a prediction (R(2) = 0.70 and RMSE = 110.1 mg kg(-1)) similar to that of MCARI. These results corroborated the potential of remote sensing for assessing soil oil pollution in large areas. Traditional BMVIs are still of great value in monitoring soil oil pollution when hyperspectral data are unavailable.