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Shi, Xiaoying

Publications and source records attributed to Shi, Xiaoying.

At least 37 records · Page 2
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DOE OSTI2021

Evaluation and modification of ELM seasonal deciduous phenology against observations in a southern boreal peatland forest

Phenological transitions determine the timing of changes in land surface properties and the seasonality of exchanges of biosphere-atmosphere energy, water, and carbon. Accurate mechanistic modeling of phenological processes is therefore critical to understand and correctly predict terrestrial ecosystem feedbacks with changing atmospheric and climate conditions. However, the phenological components in the land model of the US Department of Energy's (DOE) Energy Exascale Earth System Model (ELM of E3SM) were previously unable to accurately capture the observed phenological responses to environmental conditions in a well-studied boreal peatland forest. In this research, we introduced new seasonal-deciduous phenology schemes into version 1.0 of ELM and evaluated their performance against the PhenoCam observations at the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment in northern Minnesota from 2015 to 2018. We found that phenology simulated by the revised ELM (i.e., earlier spring onsets and stronger warming responses of spring onsets and autumn senescence) was closer to observations than simulations from the original algorithms for both the deciduous conifer (Larix laricina) and mixed shrub layers. Moreover, the revised ELM generally produced higher carbon and water fluxes (e.g., photosynthesis and evapotranspiration) during the growing season and stronger flux responses to warming than the default ELM. A parameter sensitivity analysis further indicated the significant contribution of phenology parameters to uncertainty in key carbon and water cycle variables, underscoring the importance of precise phenology parameterization. Furthermore, this phenological modeling effort demonstrates the potential to enhance the E3SM representation of land-climate interactions at broader spatiotemporal scales, especially under anticipated elevated CO 2 and warming conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

An Integrative Model for Soil Biogeochemistry and Methane Processes. II: Warming and Elevated CO 2 Effects on Peatland CH 4 Emissions

Peatlands are one of the largest natural sources for atmospheric methane (CH 4 ), a potent greenhouse gas. Climate warming and elevated atmospheric carbon dioxide (CO 2 ) are two important environmental factors that have been confirmed to stimulate peatland CH 4 emissions; however, the mechanisms underlying enhanced emissions remain elusive. A data-model integration approach was applied to understand the CH 4 processes in a northern temperate peatland under a gradient of warming and doubled atmospheric CO 2 concentration. We found that warming and elevated CO 2 stimulated CH 4 emissions through different mechanisms. Warming initially stimulated but then suppressed vegetative productivity while stimulating soil organic matter (SOM) mineralization and dissolved organic carbon (DOC) fermentation, which led to higher acetate production and enhanced acetoclastic and hydrogenotrophic methanogenesis. Warming also enhanced surface CH 4 emissions, which combined with warming-caused decreases in CH 4 solubility led to slightly lower dissolved CH 4 concentrations through the soil profiles. Elevated CO 2 enhanced ecosystem productivity and SOM mineralization, resulting in higher DOC and acetate concentrations. Higher DOC and acetate concentrations increased acetoclastic and hydrogenotrophic methanogenesis and led to higher dissolved CH 4 concentrations and CH 4 emissions. Both warming and elevated CO 2 had minor impacts on CH 4 oxidation. A meta-analysis of warming and elevated CO 2 impacts on carbon cycling in wetlands agreed well with a majority of the modeled mechanisms. Finally, this mechanistic understanding of the stimulating impacts of warming and elevated CO 2 on peatland CH 4 emissions enhances our predictability on the climate-ecosystem feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Unusual characteristics of the carbon cycle during the 2015–2016 El Niño

The 2015–2016 El Niño was one of the strongest on record, but its influence on the carbon balance is less clear. Using Northern Hemisphere atmospheric CO 2 observations, we found both detrended atmospheric CO 2 growth rate (CGR) and CO 2 seasonal-cycle amplitude (SCA) of 2015–2016 were much higher than that of other El Niño events. The simultaneous high CGR and SCA were unusual, because our analysis of long-term CO 2 observations at Mauna Loa revealed a significantly negative correlation between CGR and SCA. Atmospheric inversions and terrestrial ecosystem models indicate strong northern land carbon uptake during spring but substantially reduced carbon uptake (or high emissions) during early autumn, which amplified SCA but also resulted in a small anomaly in annual carbon uptake of northern ecosystems in 2015–2016. This negative ecosystem carbon uptake anomaly in early autumn was primarily due to soil water deficits and more litter decomposition caused by enhanced spring productivity. Furthermore, our study demonstrates a decoupling between seasonality and annual carbon cycle balance in northern ecosystems over 2015–2016, which is unprecedented in the past five decades of El Niño events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Evaluation of the Large-Scale and Regional Climatic Response Across North Africa to Natural Variability in Oceanic Modes and Terrestrial Vegetation Among the CMIP5 Models

Hydrologic variability is a serious threat to the poverty-stricken regions of North Africa. Meanwhile, the scientific community struggles to attribute these extreme climatic episodes to specific oceanic and land drivers. Prior modeling studies have not assessed simulated feedbacks over North Africa against an established observational benchmark, so their results are considered as untested, model-specific findings. The Coupled Model Intercomparison Project Phase Five (CMIP5) archive represents the state-of-the-art in climate projections, with most CMIP5 models now containing interactive vegetation phenology; however, there have been no studies to date of their simulated vegetation feedbacks. The capability of CMIP5 models at accurately simulating the forcing of both sea-surface temperature (SST) and regional leaf area index (LAI) anomalies on North African climate needs to be a key consideration in assessing the models’ overall credibility and determining appropriate model weighting for developing climate projections. The Generalized Equilibrium Feedback Assessment (GEFA) is a promising statistical method, which can be applied to either model output or observations, for isolating the local and remote impacts of individual oceanic or terrestrial forcings on regional climate. We performed a combined observational and modeling assessment of land-ocean-atmosphere interactions across the distinct ecological and moisture gradients of North Africa. We evaluated and demonstrated the reliability of the GEFA statistical method over North Africa using the Community Earth System Model (CESM), applied GEFA to observational data to quantify the observed forcing of ocean basin SST anomalies and regional LAI anomalies on North African climate, evaluated the CMIP5 models’ performance in terms of representing these key observed feedbacks, and formulated CMIP5 feedback performance metrics for weighting North African climate projections. Our study represented the first attempt to separate the observed roles of oceanic and vegetation feedbacks across North Africa, the first systematic assessment and intercomparison of land-ocean-atmosphere feedbacks in CMIP5, and the first exploration of vegetation feedbacks among CMIP5 models. The following work was accomplished. (1) The team generated 14 scientific publications and 30 presentations based on the DOE-funded research. (2) A stepwise version of the GEFA statistical method was developed in which unimportant forcings were dropped to increase the reliability of the results. (3) SGEFA was successfully validated through experiments with CESM in terms of its ability to isolate the atmospheric responses to individual oceanic or land forcings. (4) Observational evidence was revealed for the Sahel’s positive vegetation-rainfall feedback on the seasonal to interannual time scale, and it was attributed to a moisture recycling mechanism rather than an albedo mechanism. (5) An approach with SGEFA was developed in which the individual contributions of soil moisture versus vegetation forcings could be separated, revealing that the former forcing outweighed the latter for sub-Saharan Africa. (6) Tropical ocean temperatures were found to be key regulators of pan-tropical vegetation variability, especially for arid and semi-arid regions, including sub-Saharan Africa. (7) The CMIP5 models largely underestimated the importance of land feedbacks across the Sahel. (8) The general consensus among CMIP5 models indicates, for the late 21st century, a diminished seasonal predictability of sub-Saharan African regional climate and an elevated role of the land surface compared to oceanic drivers in regulating regional climate variability. (9) Land-ocean-atmosphere interactions were demonstrated to be key contributors to the seasonal predictability of African wildfire activity. (10) The El Djouf was determined to be of greater importance than the Bodélé depression in terms of providing trans-Atlantic dust transport to the Americas.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Quantifying the drivers and predictability of seasonal changes in African fire

Africa contains some of the most vulnerable ecosystems to fires. Successful seasonal prediction of fire activity over these fire-prone regions remains a challenge and relies heavily on in-depth understanding of various driving mechanisms underlying fire evolution. Here, we assess the seasonal environmental drivers and predictability of African fire using the analytical framework of Stepwise Generalized Equilibrium Feedback Assessment (SGEFA) and machine learning techniques (MLTs). The impacts of sea-surface temperature, soil moisture, and leaf area index are quantified and found to dominate the fire seasonal variability by regulating regional burning condition and fuel supply. Compared with previously-identified atmospheric and socioeconomic predictors, these slowly evolving oceanic and terrestrial predictors are further identified to determine the seasonal predictability of fire activity in Africa. Our combined SGEFA-MLT approach achieves skillful prediction of African fire one month in advance and can be generalized to provide seasonal estimates of regional and global fire risk.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Initial Land Use/Cover Distribution Substantially Affects Global Carbon and Local Temperature Projections in the Integrated Earth System Model

Initial land cover distribution varies among Earth system models, an uncertainty in initial conditions that can substantially affect carbon and climate projections. We use the integrated Earth System Model to show that a 3.9 M km2 difference in 2005 global forest area (9–14% of total forest area) generates uncertainties in initial atmospheric CO2 concentration, terrestrial carbon, and local temperature that propagate through a future simulation following the Representative Concentration Pathway 4.5. By 2095, the initial 6 ppmv uncertainty range increases to 9 ppmv and the initial 26 PgC uncertainty range in terrestrial carbon increases to 33 PgC. The initial uncertainty range in annual average local temperature of -0.74 to 0.96 °C persists throughout the future simulation, with a seasonal maximum in Dec-Jan-Feb. These results highlight the importance of accurately characterizing historical land use and land cover to reduce overall initial condition uncertainty.

Di Vittorio, Alan↗
DOE OSTI2020

Spatiotemporal dynamics of ecosystem fires and biomass burning-induced carbon emissions in China over the past two decades

Fire is a major type of disturbance that has important influences on ecosystem dynamics and carbon cycles. Yet our understanding of ecosystem fires and their carbon cycle consequences is still limited, largely due to the difficulty of large-scale fire monitoring and the complex interactions between fire, vegetation, climate, and anthropogenic factors. Here, using data from satellite-derived fire observations and ecosystem model simulations, we performed a comprehensive investigation of the spatial and temporal dynamics of China's ecosystem fire disturbances and their carbon emissions over the past two decades (1997–2016). Satellite-derived results showed that on average about 3.47 - 4.53 x 10 4 km 2 of the land was burned annually during the past two decades, among which annual burned forest area was about 0.81 - 1.25 × 10 4 km 2 , accounting for 0.33-0.51% of the forest area in China. Biomass burning emitted about 23.02 TgC per year. Compared to satellite products, simulations from the Energy Exascale Earth System Land Model (ELM) strongly overestimated China's burned area and fire-induced carbon emissions. Annual burned area and fire-induced carbon emissions were high for boreal forest in Northeast China's Daxing'anling region and subtropical dry forest in South Yunnan, as revealed by both the satellite product and the model simulations. Our results suggest that climate and anthropogenic factors play critical roles in controlling the spatial and seasonal distribution of China's ecosystem fire disturbances. Our findings highlight the importance of multiple complementary approaches in assessing ecosystem fire disturbance and its carbon consequences. Further studies are required to improve the methods of observing and modelling China's ecosystem fire disturbances, which will provide valuable information for fire management and ecosystem sustainability in an era when both human activities and the natural environment are rapidly changing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Impacts of land use change and elevated CO 2 on the interannual variations and seasonal cycles of gross primary productivity in China

Climate change, rising CO 2 concentration, and landuse and land cover change (LULCC) are primary driving forces for terrestrialgross primary productivity (GPP), but their impacts on the temporal changesin GPP are uncertain. In this study, the effects of the three main factorson the interannual variation (IAV) and seasonal cycle amplitude (SCA) of GPPin China were investigated using 12 terrestrial biosphere models from theMulti-scale Synthesis and Terrestrial Model Intercomparison Project. Thesimulated ensemble mean value of China's GPP between 1981 and 2010, drivenby common climate forcing, LULCC and CO 2 data, was found to be7.4±1.8 Pg C yr -1 . In general, climate was the dominant controlfactor of the annual trends, IAV and seasonality of China's GPP. Theoverall rising CO2 led to enhanced plant photosynthesis, thusincreasing annual mean and IAV of China's total GPP, especially innortheastern and southern China, where vegetation is dense. LULCC decreasedthe IAV of China's total GPP by ~7%, whereas rising CO 2 induced an increase of 8 %. Compared to climate change andelevated CO 2 , LULCC showed less contributions to GPP's temporalvariation, and its impact acted locally, mainly in southwestern China.Furthermore, this study also examined subregional contributions to thetemporal changes in China's total GPP. Southern and southeastern Chinashowed higher contributions to China's annual GPP, whereas southwestern andcentral parts of China explained larger fractions of the IAV in China's GPP.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Investigating controls on sea ice algal production using E3SMv1.1-BGC

We present the analysis of global sympagic primary production (PP) from 300 years of pre-industrial and historical simulations of the E3SMv1.1-BGC model. The model includes a novel, eight-element sea ice biogeochemical component, MPAS-Seaice zbgc, which is resolved in three spatial dimensions and uses a vertical transport scheme based on internal brine dynamics. Modeled ice algal chlorophyll-a concentrations and column-integrated values are broadly consistent with observations, though chl-a profile fractions indicate that upper ice communities of the Southern Ocean are underestimated. Simulations of polar integrated sea ice PP support the lower bound in published estimates for both polar regions with mean Arctic values of 7.5 and 15.5 TgC/a in the Southern Ocean. However, comparisons of the polar climate state with observations, using a maximal bound for ice algal growth rates, suggest that the Arctic lower bound is a significant underestimation driven by biases in ocean surface nitrate, and that correction of these biases supports as much as 60.7 TgC/a of net Arctic PP. Simulated Southern Ocean sympagic PP is predominantly light-limited, and regional patterns, particularly in the coastal high production band, are found to be negatively correlated with snow thickness.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Urban warming advances spring phenology but reduces the response of phenology to temperature in the conterminous United States

Urbanization has caused environmental changes, such as urban heat islands (UHIs), that affect terrestrial ecosystems. However, how and to what extent urbanization affects plant phenology remains relatively unexplored. Here, we investigated the changes in the satellite-derived start of season (SOS) and the covariation between SOS and temperature (R T ) in 85 large cities across the conterminous United States for the period 2001–2014. We found that 1) the SOS came significantly earlier (6.1 ± 6.3 d) in 74 cities and R T was significantly weaker (0.03 ± 0.07) in 43 cities when compared with their surrounding rural areas (P < 0.05); 2) the decreased magnitude in R T mainly occurred in cities in relatively cold regions with an annual mean temperature <17.3 °C (e.g., Minnesota, Michigan, and Pennsylvania); and 3) the magnitude of urban–rural difference in both SOS and R T was primarily correlated with the intensity of UHI. Simulations of two phenology models further suggested that more and faster heat accumulation contributed to the earlier SOS, while a decrease in required chilling led to a decline in R T magnitude in urban areas. Furthermore, these findings provide observational evidence of a reduced covariation between temperature and SOS in major US cities, implying the response of spring phenology to warming conditions in nonurban environments may decline in the warming future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Modelling tree stem-water dynamics over an Amazonian rainforest

A novel tree stem-water model was developed to capture the dynamics of stem-water storage and its contribution to daily transpiration. The module was incorporated into the Community Land Model (CLM), where it was used to test model sensitivity to stem-water content for an evergreen rainforest site in Amazonia, that is, the BR-Sa3 eddy covariance site. With the inclusion of the stem-water storage, CLM produced greater dry-season latent heat flux that was closer to observations, facilitated by easier canopy access to a nearby stem-water source, rather than solely dependent on soil water. The simulated stem-water content also showed seasonal variations in magnitude, along with the seasonal variations in sap flow rate. Stored stem-water of a single mature tree was estimated to contribute 20–80 kg/day of water to transpiration during the wet season and 90–110 kg/day during the dry season, thereby partially replacing soil water and maintaining plant transpiration during the dry season. Diurnally, stem-water content declined as water was extracted for transpiration in the morning and then was refilled from soil water beginning in the afternoon and through the night. The dynamic discharge and recharge of stem storage was also shown to be regulated by multiple environmental drivers. Furthermore, our study indicates that the inclusion of stem capacitance in CLM significantly improves model simulations of dry-season water and heat fluxes, in terms of both magnitude and timing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Evaluating Carbon Extremes in a Coupled Climate-Carbon Cycle Simulation

Gross primary production (GPP) measures the photosynthetic update of carbon by terrestrial ecosystems. Accurately quantifying and simulating GPP and its extremes remains a challenge in global carbon cycle sciences. Here, we evaluate GPP extremes in a coupled biogeochemistry (BGC) simulation by the Department of Energy's Energy Exascale Earth System Model (E3SMv1.1) using the Generalized Extreme Value (GEV) distribution statistical model. The simulation is evaluated against the Global Bio-Atmosphere Flux (GBAF) data. Temporal trends and ENSO dependence are also investigated by using GEV models where time and the Niño3.4 index are introduced as linear covariates. The E3SMv1.1 model simulation generally predicts stronger negative and positive GPP extremes as compared to GBAF data. It also tends to simulate stronger temporal trends of GPP extremes than GBAF data. While negative GPP extreme trends are not significant in either E3SM or GBAF, positive GPP trends are statistically significant over several regions only for the E3SMv1.1 model simulation. ENSO dependence is generally stronger in the E3SMv1.1 model simulation, but ENSO dependence is found not to be significant for the time period analyzed (1980-2006) to match GBAF data. For the longer simulation period of 1900-2006, ENSO dependence is found to be statistically significant over Amazon, the maritime continent and Northern Australia for both negative and positive extremes.

Xu, Min↗
DOE OSTI2019

Field-experiment constraints on the enhancement of the terrestrial carbon sink by CO2 fertilization

How much elevated atmospheric CO2 concentration (eCO2) contributes to the terrestrial carbon sink (NEP) is a debated issue (Friedlingstein et al., 1995; Field & Raupach, 2004; Schimel et al., 2015; Keenan et al., 2016; Huntzinger et al., 2017). The results from Free-Air CO2-Enrichment (FACE) experiments at the site scale show that eCO2 generally increase plant growth and net ecosystem CO2 uptake for a few years after exposure to eCO2, but the effects were highly variable across sites (Jastrow et al., 2005; De Graaff et al., 2006), which poses a challenge for scaling up these local observations. Here, we extract the simulated short-term responses of NEP to eCO2 from global carbon models using a substitute pulse-response approach, and compare them with site-scale responses from FACE experiments in temperate ecosystems. In 12 gridded terrestrial ecosystem models examined, the large-scale NEP sensitivity to eCO2 across the Northern Hemisphere (NH) temperate region is linearly related to the site-scale sensitivity across different ecosystems. We use this emergent relationship, together with the observed response to eCO2 in the FACE site-scale data to estimate a data constrained effect of eCO2 on the NH temperate NEP of 0.73 ± 0.22 Pg C yr-1 per hundred parts per million (ppm) of CO2 increase during the past five decades. This is 26% higher than the mean of the model ensemble. Among the models, those with carbon-nitrogen interactions underestimate the sensitivity of NEP to eCO2, suggesting overly strong nitrogen-limitations on carbon uptake. We further identify that the NEP sensitivity to eCO2 at NH temperate scale is linearly correlated with that at global scale across the models. Extrapolating the constrained NH eCO2 effect to the global terrestrial carbon sink provides an estimate of 4.1 ± 1.5 Pg C yr-1 [100 ppm]-1. Large uncertainties remain regarding the global response broadly inferred from temperate FACE data, due to the lack of observations in boreal and tropical regions, emphasizing the importance of deploying new FACE experiments in those regions.

Liu, Yongwen↗
DOE OSTI2019

The Effects of Phosphorus Cycle Dynamics on Carbon Sources and Sinks in the Amazon Region: A Modeling Study Using ELM v1

Tropical forests play a crucial role in the global carbon cycle, accounting for one third of the global net primary productivity and containing about 25% of global vegetation biomass and soil carbon. This is particularly true for tropical forests in the Amazon region, as these comprise approximately 50% of the world's tropical forests. It is therefore important for us to understand and represent the processes that determine the fluxes and storage of carbon in these forests. In this study, we show that the implementation of phosphorus (P) cycle and P limitation in the version 1 of the Energy Exascale Earth System Model land model (ELM v1) improves simulated spatial pattern of wood productivity. The P-enabled ELM v1 is able to capture the declining west-to-east gradient of productivity, consistent with field observations. We also show that by improving the representation of mortality processes using soils data, ELMv1 is able to reproduce the observed spatial pattern of above ground biomass. Our model simulations show that the consideration of P availability leads to a smaller carbon sink associated with CO 2 fertilization effect and lower carbon emissions due to land use and land cover change. Our simulations suggest P limitation would significantly reduce the carbon sink associated with CO 2 fertilization effects through the 21st century. We conclude that P cycle dynamics affect both sources and sinks of carbon in the Amazon region, and the effects of P limitation would become increasingly important as CO 2 increases. Finally, P limitation must be considered for projecting future carbon dynamics in tropical ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Carbon and Water Use Efficiencies: A Comparative Analysis of Ten Terrestrial Ecosystem Models under Changing Climate

Terrestrial ecosystems carbon and water cycles are tightly coupled through photosynthesis and evapotranspiration processes. The ratios of carbon stored to carbon uptake and water loss to carbon gain are key ecophysiological indicators essential to assess the magnitude and response of the terrestrial plant to the changing climate. Here, we use estimates from 10 terrestrial ecosystem models to quantify the impacts of climate, atmospheric CO 2 concentration, and nitrogen (N) deposition on water use efficiency (WUE), and carbon use efficiency (CUE). We find that across models, WUE increases over the 20th Century particularly due to CO 2 fertilization and N deposition and compares favorably to experimental studies. Also, the results show a decrease in WUE with climate for the last 3 decades, in contrasts with up-scaled flux observations that demonstrate a constant WUE. Modeled WUE responds minimally to climate with modeled CUE exhibiting no clear trend across space and time. The divergence between simulated and observationally-constrained WUE and CUE is driven by modeled NPP and autotrophic respiration, nitrogen cycle, carbon allocation, and soil moisture dynamics in current ecosystem models. We suggest that carbon-modeling community needs to reexamine stomatal conductance schemes and the soil-vegetation interactions for more robust modeling of carbon and water cycles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Global vegetation biomass production efficiency constrained by models and observations

Typically, 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. In this work, we introduce 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).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

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 ( 36 .6 &#x2212;<!-- - --> 2 .4 + 2 .3 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.

54 ENVIRONMENTAL SCIENCES↗