Permafrost thawing puts the frozen carbon at risk over the Tibetan Plateau

A review on mathematical modeling of microbial and plant induced permafrost carbon feedback

This review paper analyses the significance of microbial activity in permafrost carbon feedback (PCF) and emphasizes the necessity for enhanced modeling tools to appropriately predict carbon fluxes associated with permafrost thaw. Beginning with an overview of experimental findings, both in situ and laboratory, it stresses the key role of microbes and plants in PCF. The research investigates several modeling techniques, starting with current models of soil respiration and plant-microorganism interactions built outside of the context of permafrost, and then moving on to specific models dedicated to PCF. The review of the current literature reveals the complex nature of permafrost ecosystems, where various geophysical factors have considerable effects on greenhouse gas emissions. Soil properties, plant types, and time scales all contribute to carbon dynamics. Process-based models are widely used for simulating greenhouse gas production, transport, and emissions. While these models are beneficial at capturing soil respiration complexity, adjusting them to the unique constraints of permafrost environments often calls for novel process descriptions for proper representation. Understanding the temporal coherence and time delays between surface soil respiration and subsurface carbon production, which are controlled by numerous parameters such as soil texture, water content, and temperature, remains a challenge. This review highlights the need for comprehensive models that integrate thermo-hydro-biogeochemical processes to understand permafrost system dynamics in the context of changing climatic circumstances. Furthermore, it emphasizes the need for rigorous validation procedures to reduce model complexity biases.

Escalating Carbon Export from High-Elevation Rivers in a Warming Climate

High-elevation mountains have experienced disproportionately rapid warming, yet the effect of warming on the lateral export of terrestrial carbon to rivers remains poorly explored and understood in these regions. Here, we present a long-term data set of dissolved inorganic carbon (DIC) and a more detailed, short-term data set of DIC, δ13CDIC, and organic carbon from two major rivers of the Qinghai-Tibetan Plateau, the Jinsha River (JSR) and the Yalong River (YLR). In the higher-elevation JSR with ∼51% continuous permafrost coverage, warming (>3 °C) and increasing precipitation coincided with substantially increased DIC concentrations by 35% and fluxes by 110%. In the lower-elevation YLR with ∼14% continuous permafrost, such increases did not occur despite a comparable extent of warming. Riverine concentrations of dissolved and particulate organic carbon increased with discharge (mobilization) in both rivers. In the JSR, DIC concentrations transitioned from dilution (decreasing concentration with discharge) in earlier, colder years to chemostasis (relatively constant concentration) in later, warmer years. This changing pattern, together with lighter δ13CDIC under high discharge, suggests that permafrost thawing boosts DIC production and export via enhancing soil respiration and weathering. These findings reveal the predominant role of warming in altering carbon lateral export by escalating concentrations and fluxes and modifying export patterns.

Distribution characteristics of soil carbon density and influencing factors in Qinghai-Tibet Plateau region

The Qinghai-Tibet Plateau has low anthropogenic carbon emissions and large carbon stock in its ecosystems. As a crucial region in terrestrial ecosystems responding to climate change, an accurate understanding of the distribution characteristics of soil carbon density holds significance in estimating the soil carbon storage capacity in forests and grasslands. It performs a crucial role in achieving carbon neutrality goals in China. The distribution characteristics of carbon and carbon density in the surface, middle, and deep soil layers are calculated, and the main influencing factors of soil carbon density changes are analyzed. The carbon density in the surface soil ranges from a minimum of 1.62 kg/m2 to a maximum of 52.93 kg/m2. The coefficient of variation for carbon is 46%, indicating a considerable variability in carbon distribution across different regions. There are substantial disparities, with geological background, land use types, and soil types significantly influencing soil organic carbon density. Alpine meadow soil has the highest carbon density compared with other soil types. The distribution of soil organic carbon density at three different depths is as follows: grassland > bare land > forestland > water area. The grassland systems in the Qinghai-Tibet Plateau have considerable soil carbon sink and storage potential; however, they are confronted with the risk of grassland degradation. The grassland ecosystems on the Qinghai-Tibet Plateau harbor substantial soil carbon sinks and storage potential. However, they are at risk of grassland degradation. It is imperative to enhance grassland management, implement sustainable grazing practices, and prevent the deterioration of the grassland carbon reservoirs to mitigate the exacerbation of greenhouse gas emissions and global warming. This highlights the urgency of implementing more studies to uncover the potential of existing grassland ecological engineering projects for carbon sequestration.

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.

Simulation and prediction of changes in maximum freeze depth in the source region of the Yellow River under climate change

The source region of the Yellow River (SRYR) is located at the edge of the Qinghai-Tibet Plateau (QTP), which is completely covered by frozen ground. Due to relatively higher temperatures, the frozen ground in the SRYR is particularly fragile and susceptible to the impacts of global climate change. This study discusses the maximum freeze depth (MFD) of frozen ground in the SRYR, including analysis of measured data at the stations, comparison of simulation models, and projection of future changes. The MFD of frozen ground recorded at nine meteorological stations within the SRYR ranged from a few tens of centimeters to more than two meters. The decreasing trend of MFD was recorded except for a few stations from 1997 to 2017, with a maximum rate of -22.8 cm/10a. The decreasing rate of MFD for the whole SRYR from 1997 to 2017 is -10.8 cm/10a. Furthermore, we assessed the performance of three simulation methods: Stefan equation, multiple linear regression, and BP neural network predicting the MFD using the measured data. The Stefan equation exhibited limited accuracy in simulating the MFD, while the BP neural network demonstrated remarkable performance, with a correlation coefficient R of 0.949. In addition, we evaluated the applicability of different global climate models (GCMs) in the SRYR, identified the optimal model, and combined it with the BP neural network model to predict future MFD change. Among the five climate models, the BCC-CSM2-MR model and ensemble model fit the measured precipitation and air temperature well. The projected results based on the BCC-CSM2-MR model and ensemble model indicate that the MFD of different stations in the SRYR and the whole region will still tend to decrease in the future. Our results contribute to understanding the response of cold region frozen ground to climate change and provide available data.

Characterising baseflow signature variability in the Yellow River Basin

Baseflow is pivotal in maintaining catchment ecological health and improving sustainable economic development. The Yellow River Basin (YRB) is northern China's most important water supplier. However, it faces water shortage due to synergistic effects between natural conditions and anthropogenic activities. Investigating baseflow characteristics quantitively is, therefore, beneficial to promoting the sustainable development of the YRB. In this study, daily ensemble means baseflow data derived from four revised baseflow separation algorithms (i.e., the United Kingdom Institute of Hydrology (UKIH), Lyne-Hollick, Chapman-Maxwell, and Eckhardt methods) - was obtained from 2001 to 2020. Thirteen baseflow dynamics signatures were extracted to investigate baseflow spatiotemporal variations and their determinants across the YRB. The main findings were: (1) There were significant spatial distribution patterns of baseflow signatures, and most signatures had higher values in upstream and downstream reaches than in the middle reaches. There were also mixing patterns with higher values in middle and downstream reaches simultaneously. (2) The magnitude of temporal variation in baseflow signatures was most strongly correlated with catchment terrain (r = -0.4), vegetation growth (r > 0.3), and cropland coverage (r > 0.4). (3) There was a strong synergistic effect of multiple factors (e.g., soil textures, precipitation and vegetation conditions) on baseflow signature values. This study provided a heuristic evaluation of baseflow characteristics in the YRB, contributing to water resources management in the YRB and similar catchments.

Changing microbiome community structure and functional potential during permafrost thawing on the Tibetan Plateau

Large amounts of carbon sequestered in permafrost on the Tibetan Plateau (TP) are becoming vulnerable to microbial decomposition in a warming world. However, knowledge about how the responsible microbial community responds to warming-induced permafrost thaw on the TP is still limited. This study aimed to conduct a comprehensive comparison of the microbial communities and their functional potential in the active layer of thawing permafrost on the TP. We found that the microbial communities were diverse and varied across soil profiles. The microbial diversity declined and the relative abundance of Chloroflexi, Bacteroidetes, Euryarchaeota, and Bathyarchaeota significantly increased with permafrost thawing. Moreover, warming reduced the similarity and stability of active layer microbial communities. The high-throughput qPCR results showed that the abundance of functional genes involved in liable carbon degradation and methanogenesis increased with permafrost thawing. Notably, the significantly increased mcrA gene abundance and the higher methanogens to methanotrophs ratio implied enhanced methanogenic activities during permafrost thawing. Overall, the composition and functional potentials of the active layer microbial community in the Tibetan permafrost region are susceptible to warming. These changes in the responsible microbial community may accelerate carbon degradation, particularly in the methane releases from alpine permafrost ecosystems on the TP.

Remotely sensed lake area changes in permafrost regions of the Arctic and the Tibetan Plateau between 1987 and 2017

Both gradual and abrupt changes in lake surface area in permafrost regions are crucial for understanding the water cycles in cold regions under climate change. However, seasonal changes in lake area in permafrost regions are not available, and their occurrence conditions are still unclear. Based on remotely sensed water body products at a 30 m resolution, this study provides a detailed comparison of lake area changes across seven basins characterized by clear gradients in climatic, topographic and permafrost conditions in the Arctic and Tibetan Plateau between 1987 and 2017. The results show that the maximum surface area of all lakes net increased by 13.45 %. Among them, the seasonal lake area net increased by 28.66 %, but there was also a 2.48 % loss. The permanent lake area net increased by 6.39 %, and the area loss was approximately 3.22 %. The total permanent lake area generally decreased in the Arctic but increased in the Tibetan Plateau. At lake region scale (0.1° grid), the changes in permanent area of contained lakes were divided into four types including no change, homogeneous changes (only expansion or only shrinkage), heterogeneous changes (expansion neighboring shrinkage) and abrupt changes (newforming or vanishing). The lake regions with heterogeneous changes accounted for over one-quarter of all lake regions. All types of changes in lake regions, especially the heterogeneous changes and abrupt changes (e.g., vanishing), occurred more extensively and intensely on low and flat terrain, in high-density lake regions and in warm permafrost regions. These findings indicate that, considering the increase in surface water balance in these river basins, surface water balance alone cannot fully explain changes in permanent lake area in the permafrost region, and the thawing or disappearance of permafrost plays a tipping point effect on the lake changes.

Characteristics of methane emissions from alpine thermokarst lakes on the Tibetan Plateau

Understanding methane (CH₄) emission from thermokarst lakes is crucial for predicting the impacts of abrupt thaw on the permafrost carbon-climate feedback. However, observational evidence, especially from high-altitude permafrost regions, is still scarce. Here, by combining field surveys, radio- and stable-carbon isotopic analyses, and metagenomic sequencing, we present multiple characteristics of CH₄ emissions from 120 thermokarst lakes in 30 clusters along a 1100 km transect on the Tibetan Plateau. We find that thermokarst lakes have high CH₄ emissions during the ice-free period (13.4 ± 1.5 mmol m^-2 d^-1; mean ± standard error) across this alpine permafrost region. Ebullition constitutes 84% of CH₄ emissions, which are fueled primarily by young carbon decomposition through the hydrogenotrophic pathway. The relative abundances of methanogenic genes correspond to the observed CH₄ fluxes. Overall, multiple parameters obtained in this study provide benchmarks for better predicting the strength of permafrost carbon-climate feedback in high-altitude permafrost regions.

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.

Changes in permafrost spatial distribution and active layer thickness from 1980 to 2020 on the Tibet Plateau

The Tibetan Plateau (TP) is experiencing extensive permafrost degradation due to climate change, which seriously threatens sustainable water and ecosystem management in the TP and its downstream areas. Understanding the evolution of permafrost is critical for studying changes in the water cycle, carbon flux, and ecology of the TP. In this study, we mapped the spatial distribution of permafrost and active layer thickness (ALT) at 1 km resolution for each decade using empirical models and machine learning methods validated with borehole data. A comprehensive comparison of model results and validation accuracy shows that the machine learning method is more advantageous in simulating the permafrost distribution, while the ALT simulated by the empirical model (i.e., Stefan model) better reflects the actual ALT distribution. We further evaluated the dynamics of permafrost distribution and ALT from 1980 to 2020 based on the results of the better-performing models, and analyzed the patterns and influencing factors of the changes in permafrost distribution and ALT. The results show that the permafrost area on the TP has decreased by 15.5 %, and the regionally average ALT has increased by 18.94 cm in the 2010s compared to the 1980s. The average decreasing rate of permafrost area is 6.33 × 10⁴ km² decade^-1, and the average increasing rate of ALT is 6.31 cm decade^-1. Permafrost degradation includes the decreasing permafrost area and the thickening active layer mainly related to the warming of the TP. Spatially, permafrost area decrease is more susceptible to occur at lower latitudes and lower altitudes, while ALT increases more dramatically at lower latitudes and higher altitudes. In addition, permafrost is more likely to degrade to seasonally frozen ground in areas with deeper ALT.

Contribution of Tibetan Plateau ecosystems to local and remote precipitation through moisture recycling

The ecosystems of the Tibetan Plateau (TP) provide multiple important ecosystem services that benefit both local populations and those beyond, such as through climate regulation services on precipitation for East Asia and China. However, the precipitation regulation service of the TP ecosystems for supplying moisture and maintaining precipitation is yet to be evaluated. In this study, we used the moisture recycling framework and a moisture tracking model to quantify the precipitation regulation services of TP ecosystems for their contribution to precipitation. We found TP ecosystems contributed substantially to local and downwind precipitation, with a contribution of 221 mm/year for the TP and neighboring areas through evapotranspiration (ET) (104 mm/year through transpiration), declined to <10 mm/year for eastern China and other surrounding countries. Among ecosystem types, grassland contributed most to precipitation, followed by barren and snow lands, forests, and shrublands. In terms of seasonality, precipitation contribution from TP ecosystems was greater in summer months than in non-summer months for western China, while the opposite was true for eastern China-although the magnitude was much smaller. Over the past two decades, the significant ET increases in TP translated to a widespread increase in precipitation contribution for TP and downwind beneficiary regions from 2000 to 2020. Our study provides a quantitative way to understand the precipitation regulation services of TP ecosystems through moisture recycling, substantiating their key role to maintain precipitation and the water cycle for downwind regions-effectively acting as an ecological safeguard that could be perceived by the public.

Photolithography-Based Microfabrication of Biodegradable Flexible and Stretchable Sensors

Biodegradable sensors based on integrating conductive layers with polymeric materials in flexible and stretchable forms have been established. However, the lack of a generalized microfabrication method results in large-sized, low spatial density, and low device yield compared to the silicon-based devices manufactured via batch-compatible microfabrication processes. Here, a batch fabrication-compatible photolithography-based microfabrication approach for biodegradable and highly miniaturized essential sensor components is presented on flexible and stretchable substrates. Up to 1600 devices are fabricated within a 1 cm² footprint and then the functionality of various biodegradable passive electrical components, mechanical sensors, and chemical sensors is demonstrated on flexible and stretchable substrates. The results are highly repeatable and consistent, proving the proposed method's high device yield and high-density potential. This simple, innovative, and robust fabrication recipe allows complete freedom over the applicability of various biodegradable materials with different properties toward the unique application of interests. The process offers a route to utilize standard micro-fabrication procedures toward scalable fabrication of highly miniaturized flexible and stretchable transient sensors and electronics.

Interannual and seasonal variations of permafrost thaw depth on the Qinghai-Tibetan Plateau: A comparative study using long short-term memory, convolutional neural networks, and random forest

An accurate estimation of thaw depth is critical to understanding permafrost changes due to climate warming on the Qinghai-Tibetan Plateau (QTP). However, previous studies mainly focused on the interannual changes of active layer thickness (ALT) across the QTP, and little is known about the changes in the seasonal thaw depth. Machine learning (ML) is a critical tool to accurately estimate the ALT of permafrost, but a direct comparison of ML with deep learning (DL) in ALT projection regarding the model performance is still lacking. Here, ML, namely random forest (RF), and DL algorithms like convolutional neural networks (CNN) and long short-term memory (LSTM) neural networks were compared to estimate the interannual changes of ALT and seasonal thaw depth on the QTP. Meteorological series, in-situ collected ALT observations, and geospatial information were used as predictors. The results show that both ML and DL methods are capable of estimating ALT and seasonal thaw depth in permafrost areas. The CNN and LSTM models developed using longer lagging times exhibit better performance in thaw depth prediction while the RF models are either mediocre or sometimes even worse as the lagging time increases. The results show that the ALT from 2003 to 2011 on the QTP exhibits an increasing trend, especially in the northern region. In addition, 68.8%, 88.7%, 52.5%, and 47.5% of the permafrost regions on the QTP have deepened seasonal thaw depth in spring, summer, autumn, and winter, respectively. The correlation between air temperature and permafrost thaw depth ranges from 0.65 to 1 with the time lag ranging from 1 to 32 days. This study shows that ML and DL can be effectively used in retrieving ALT and seasonal thaw depth of permafrost, and could present an efficient way to figure out the interannual and seasonal variations of permafrost conditions under climate warming.

Substantial non-growing season carbon dioxide loss across Tibetan alpine permafrost region

One of the major uncertainties for projecting permafrost carbon (C)-climate feedback is a poor representation of the non-growing season carbon dioxide (CO₂ ) emissions under a changing climate. Here, combining in situ field observations, regional synthesis and a random forest model, we assessed contemporary and future soil respired CO₂ (i.e., soil respiration, R_s ) across the Tibetan alpine permafrost region, which has received much less attention compared with the Arctic permafrost domain. We estimated the regional mean R_s of 229.8, 72.9 and 302.7 g C m^-2  year^-1 during growing season, non-growing season and the entire year, respectively; corresponding to the contemporary losses of 296.9, 94.3 and 391.2 Tg C year^-1 from this high-altitude permafrost-affected area. The non-growing season R_s accounted for a quarter of the annual soil CO₂ efflux. Different from the prevailing view that temperature is the most limiting factor for cold-period CO₂ release in Arctic permafrost ecosystems, precipitation determined the spatial pattern of non-growing season R_s on the Tibetan Plateau. Using the key predictors, model extrapolation demonstrated additional losses of 38.8 and 74.5 Tg C from the non-growing season for a moderate mitigation scenario and a business-as-usual emissions scenario, respectively. These results provide a baseline for non-growing season CO₂ emissions from high-altitude permafrost areas and help for accurate projection of permafrost C-climate feedback.

Divergent changes in particulate and mineral-associated organic carbon upon permafrost thaw

Permafrost thaw can stimulate microbial decomposition and induce soil carbon (C) loss, potentially triggering a positive C-climate feedback. However, earlier observations have concentrated on bulk soil C dynamics upon permafrost thaw, with limited evidence involving soil C fractions. Here, we explore how the functionally distinct fractions, including particulate and mineral-associated organic C (POC and MAOC) as well as iron-bound organic C (OC-Fe), respond to permafrost thaw using systematic measurements derived from one permafrost thaw sequence and five additional thermokarst-impacted sites on the Tibetan Plateau. We find that topsoil POC content substantially decreases, while MAOC content remains stable and OC-Fe accumulates due to the enriched Fe oxides after permafrost thaw. Moreover, the proportion of MAOC and OC-Fe increases along the thaw sequence and at most of the thermokarst-impacted sites. The relatively enriched stable soil C fractions would alleviate microbial decomposition and weaken its feedback to climate warming over long-term thermokarst development.

Based on observations from thermokarst-impacted sites on the Tibetan Plateau, the authors find substantial particulate organic carbon loss but stable mineral-associated organic carbon and enriched iron-bound organic carbon upon permafrost thaw.

Simulation of regional groundwater levels in arid regions using interpretable machine learning models

Regional groundwater level forecasting is critical to water resource management, especially for arid regions which require effective management of groundwater resources to meet human and ecosystem needs. In this study Machine Learning and Deep Learning approaches - Support Vector Machine, Generalized Regression Neural Network, Decision Tree, Random Forest (RF), Convolutional Neural Network, Long Short Term Memory and Gated Recurrent Network- have been used to simulate the groundwater levels in the lower Tarim River basin (LTRB) which is an extreme dryland. The results showed that models developed here with easily available input data such as relative humidity, flow volume and distance to the riverbank can fully utilize spatiotemporally inconsistent groundwater monitoring data to predict the spatiotemporal variation of the groundwater system in arid regions where exist intermittent flow. The shapely additive explanations method was used to interpret the RF model and discover the effect of meteorological, hydrological and environmental variables on the regional groundwater. These explanations showed that the flow volume, the distance to the river channel and reservoir have a critical impact on groundwater changes. Within 300 m distance to the riverbank, groundwater would mainly be influenced by the flow volume and the distance to the reservoir. While far from the riverbank, these effects decreased gradually further away from the river course. The RF prediction results showed that in the next three years (2021-2023), the groundwater level on average may decline to -6.4 m, and the suitable areas for natural vegetation growth would be limited to 39% if no water conveyance in the LTRB. To guarantee the stability of ecosystems in the LTRB, it is necessary to convey the water annually. These results can support spatiotemporal predictions of groundwater levels predominantly recharged by intermittent flow, and form a scientific basis for sustainable water resources management in arid regions.

Sedimentary organic carbon storage of thermokarst lakes and ponds across Tibetan permafrost region

Sedimentary soil organic carbon (SOC) stored in thermokarst lakes and ponds (hereafter referred to as thaw lakes) across high-latitude/altitude permafrost areas is of global significance due to increasing thaw lake numbers and their high C vulnerability under climate warming. However, to date, little is known about the SOC storage in these lakes, which limits our better understanding of the fate of these active carbon in a warming future. Here, by combining large-scale field observation data and published deep (e.g., 0-300 cm) permafrost SOC data with a random forest (RF) machine learning technique, we provided the first comprehensive estimation of thaw lake SOC stocks to 3 m depth on the Tibetan Plateau. This study demonstrated that combining multiple environmental factors with the RF model could effectively predict the spatial distributions of the thaw lake SOC density values (SOCDs). The model results revealed that the soil respiration, normalized difference vegetation index (NDVI), and mean annual precipitation (MAP) were the most influential factors for predicting thaw lake SOCDs. In total, the sedimentary SOC stocks in the thaw lakes were approximately 52.62 Tg in the top 3 m, with 53% of the SOC stored in the upper layers (0-100 cm). The SOCDs generally exhibited high values in eastern Tibetan Plateau, and low values in mid- and western Tibetan Plateau, which were similar to the patterns of the land cover types that affected the SOCDs. We further found that the SOCDs of thaw lakes were generally higher than those of their surrounding permafrost soils at different layer depths, which could be ascribed to the erosion of soil particles or leaching solution from the thawing permafrost soils to lakes and/or enhanced vegetation growth at the lake bottom. This research highlights the necessity of explicitly considering the thaw lake SOC stocks in Earth system models for more comprehensive future projections of the carbon dynamics on the plateau.

Divergent Trajectory of Soil Autotrophic and Heterotrophic Respiration upon Permafrost Thaw

Warming-induced permafrost thaw may stimulate soil respiration (Rs) and thus cause a positive feedback to climate warming. However, due to the limited in situ observations, it remains unclear about how Rs and its autotrophic (Ra) and heterotrophic (Rh) components change upon permafrost thaw. Here we monitored variations in Rs and its components along a permafrost thaw sequence on the Tibetan Plateau, and explored the potential linkage of Rs components (i.e., Ra and Rh) with biotic (e.g., plant functional traits and soil microbial diversity) and abiotic factors (e.g., substrate quality). We found that Ra and Rh exhibited divergent responses to permafrost collapse: Ra increased with the time of thawing, while Rh exhibited a hump-shaped pattern along the thaw sequence. We also observed different drivers of thaw-induced changes in the ratios of Ra:Rs and Rh:Rs. Except for soil water status, plant community structure, diversity, and root properties explained the variation in Ra:Rs ratio, soil substrate quality and microbial diversity were key factors associated with the dynamics of Rh:Rs ratio. Overall, these findings demonstrate divergent patterns and drivers of Rs components as permafrost thaw prolongs, which call for considerations in Earth system models for better forecasting permafrost carbon-climate feedback.

Spatial and Temporal Variability of Key Bio-Temperature Indicators and Their Effects on Vegetation Dynamics in the Great Lakes Region of Central Asia

Dryland ecosystems are fragile to climate change due to harsh environmental conditions. Climate change affects vegetation growth primarily by altering some key bio-temperature thresholds. Key bio-temperatures are closely related to vegetation growth, and slight changes could produce substantial effects on ecosystem structure and function. Therefore, this study selected the number of days with daily mean temperature above 0 °C (DT0), 5 °C (DT5), 10 °C (DT10), 20 °C (DT20), the start of growing season (SGS), the end of growing season (EGS), and the length of growing season (LGS) as bio-temperature indicators to analyze the response of vegetation dynamics to climate change in the Great Lakes Region of Central Asia (GLRCA) for the period 1982–2014. On the regional scale, DT0, DT5, DT10, and DT20 exhibited an overall increasing trend. Spatially, most of the study area showed that the negative correlation between DT0, DT5, DT10, DT20 with the annual Normalized Difference Vegetation Index (NDVI) increased with increasing bio-temperature thresholds. In particular, more than 88.3% of the study area showed a negative correlation between annual NDVI and DT20, as increased DT20 exacerbated ecosystem drought. Moreover, SGS exhibited a significantly advanced trend at a rate of −0.261 days/year for the regional scale, while EGS experienced a significantly delayed trend at a rate of 0.164 days/year. Because of changes in SGS and EGS, LGS across the GLRCA was extended at a rate of 0.425 days/year, which was mainly attributed to advanced SGS. In addition, our study revealed that about 53.6% of the study area showed a negative correlation between annual NDVI and LGS, especially in the north, indicating a negative effect of climate warming on vegetation growth in the drylands. Overall, the results of this study will help predict the response of vegetation to future climate change in the GLRCA, and support decision-making for implementing effective ecosystem management in arid and semi-arid regions.

The Outburst of a Lake and Its Impacts on Redistribution of Surface Water Bodies in High-Altitude Permafrost Region

The lakes distributed in permafrost areas on the Tibetan Plateau (TP) have been experiencing significant changes during the past few decades as a result of the climate warming and regional wetting. In September 2011, an outburst occurred on an endorheic lake (Zonag Lake) in the interior of the TP, which caused the spatial expansion of three downstream lakes (Kusai Lake, Haidingnor Lake and Salt Lake) and modified the four independent lake catchments to one basin. In this study, we investigate the changes in surficial areas and water volumes of the outburst lake and related downstream water bodies 10 years after the outburst. Based on the meteorological and satellite data, the reasons for the expansion of downstream lakes were analyzed. Additionally, the importance of the permafrost layer in determining hydrological process on the TP and the influence of from lake expansion on engineering infrastructures were discussed. The results in this study showed the downstream lakes increased both in area and volume after the outburst of the headwater. Meanwhile, we hope to provide a reference about surface water changes and permafrost degradation for the management of lake overflow and flood on the TP in the background of climate warming and wetting.

Uncertainties of soil organic carbon stock estimation caused by paleoclimate and human footprint on the Qinghai Plateau

BACKGROUND

Quantifying the stock of soil organic carbon (SOC) and evaluating its potential impact factors is important to evaluating global climate change. Human disturbances and past climate are known to influence the rates of carbon fixation, soil physiochemical properties, soil microbial diversity and plant functional traits, which ultimately affect the current SOC storage. However, whether and how the paleoclimate and human disturbances affect the distribution of SOC storage on the high-altitude Tibetan Plateau remain largely unknown. Here, we took the Qinghai Plateau, the main component of the Tibetan Plateau, as our study region and applied three machine learning models (random forest, gradient boosting machine and support vector machine) to estimate the spatial and vertical distributions of the SOC stock and then evaluated the effects of the paleoclimate during the Last Glacial Maximum and the mid-Holocene periods as well as the human footprint on SOC stock at 0 to 200 cm depth by synthesizing 827 soil observations and 71 environmental factors.

RESULTS

Our results indicate that the vegetation and modern climate are the determinant factors of SOC stocks, while paleoclimate (i.e., paleotemperature and paleoprecipitation) is more important than modern temperature, modern precipitation and the human footprint in shaping current SOC stock distributions. Specifically, the SOC stock was deeply underestimated in near natural ecosystems and overestimated in the strongly human disturbance ecosystems if the model did not consider the paleoclimate. Overall, the total SOC stock of the Qinghai Plateau was underestimated by 4.69%, 12.25% and 6.67% at depths of 0 to 100 cm, 100 to 200 cm and 0 to 200 cm, respectively. In addition, the human footprint had a weak influence on the distributions of the SOC stock. We finally estimated that the total and mean SOC stock at 200 cm depth by including the paleoclimate effects was 11.36 Pg C and 16.31 kg C m^-2, respectively, and nearly 40% SOC was distributed in the top 30 cm.

CONCLUSION

The paleoclimate is relatively important for the accurate modeling of current SOC stocks. Overall, our study provides a benchmark for predicting SOC stock patterns at depth and emphasizes that terrestrial carbon cycle models should incorporate information on how the paleoclimate has influenced SOC stocks.

Domino effect of a natural cascade alpine lake system on the Third Pole

Third Pole natural cascade alpine lakes (NCALs) are exceptionally sensitive to climate change, yet the underlying cryosphere-hydrological processes and associated societal impacts are largely unknown. Here, with a state-of-the-art cryosphere-hydrology-lake-dam model, we quantified the notable high-mountain Hoh-Xil NCALs basin (including Lakes Zonag, Kusai, Hedin Noel, and Yanhu, from upstream to downstream) formed by the Lake Zonag outburst in September 2011. We demonstrate that long-term increased precipitation and accelerated ice and snow melting as well as short-term heavy precipitation and earthquake events were responsible for the Lake Zonag outburst; while the permafrost degradation only had a marginal impact on the lake inflows but was crucial to lakeshore stability. The quadrupling of the Lake Yanhu area since 2012 was due to the tripling of inflows (from 0.25 to 0.76 km³/year for 1999 to 2010 and 2012 to 2018, respectively). Prediction of the NCALs changes suggests a high risk of the downstream Qinghai-Tibet Railway, necessitating timely adaptions/mitigations.

Microbial functional changes mark irreversible course of Tibetan grassland degradation

The Tibetan Plateau’s Kobresia pastures store 2.5% of the world’s soil organic carbon (SOC). Climate change and overgrazing render their topsoils vulnerable to degradation, with SOC stocks declining by 42% and nitrogen (N) by 33% at severely degraded sites. We resolved these losses into erosion accounting for two-thirds, and decreased carbon (C) input and increased SOC mineralization accounting for the other third, and confirmed these results by comparison with a meta-analysis of 594 observations. The microbial community responded to the degradation through altered taxonomic composition and enzymatic activities. Hydrolytic enzyme activities were reduced, while degradation of the remaining recalcitrant soil organic matter by oxidative enzymes was accelerated, demonstrating a severe shift in microbial functioning. This may irreversibly alter the world´s largest alpine pastoral ecosystem by diminishing its C sink function and nutrient cycling dynamics, negatively impacting local food security, regional water quality and climate.

The Tibetan Kobresia pastures store 2.5% of the world’s soil organic carbon. Here the authors show that soil degradation and microbial shifts may irreversibly diminish the carbon sink function and accelerate nutrient losses.

Influence of Open-Pit Coal Mining on Ground Surface Deformation of Permafrost in the Muli Region in the Qinghai-Tibet Plateau, China

The Qinghai-Tibet Plateau (QTP) is the largest mid-to low latitude and high-altitude permafrost. Open-pit coal mining and other activities have caused serious damage to the alpine ecological environment and have accelerated the degradation of permafrost on the QTP. In this study, the influence of open-pit coal mining on the time series ground surface deformation of the permafrost in the Muli region of the QTP was analyzed from 19 January 2018 to 22 December 2020 based on Landsat, Gaofen, and Sentinel remote sensing data. The primary methods include human-computer interactive visual interpretation and the small baseline subsets interferometric synthetic aperture radar (SBAS-InSAR) method. The results showed that the spatial distribution of displacement velocity exhibits a considerably different pattern in the Muli region. Alpine meadow is the main land use/land cover (LULC) in the Muli region, and the surface displacement was mainly subsidence. The surface subsidence trend in alpine marsh meadows was obvious, with a subsidence displacement velocity of 10–30 mm/a. Under the influence of changes in temperature, the permafrost surface displacement was characteristics of regular thaw subsidence and freeze uplift. Surface deformation of the mining area is relatively severe, with maximum uplift displacement velocity of 74.31 mm/a and maximum subsidence displacement velocity of 167.51 mm/a. Open-pit coal mining had resulted in the destruction of 48.73 km2 of natural landscape in the Muli region. Mining development in the Muli region had increased the soil moisture of the alpine marsh meadow around the mining area, resulting in considerable cumulative displacement near the mining area and the acceleration of permafrost degradation.

Decipher soil organic carbon dynamics and driving forces across China using machine learning

The dynamics of soil organic carbon (SOC) play a critical role in modulating global warming. However, the long-term spatiotemporal changes of SOC at large scale, and the impacts of driving forces remain unclear. In this study, we investigated the dynamics of SOC in different soil layers across China through the1980s to 2010s using a machine learning approach and quantified the impacts of the key factors based on factorial simulation experiments.Our results showed that the latest (2000-2014) SOC stock in the first meter soil (SOC₁₀₀ ) was 80.68 ± 3.49 Pg C, of which 42.6% was stored in the top 20 cm, sequestrating carbon with a rate of 30.80 ± 12.37 g C m^-2  yr^-1 since the 1980s. Our experiments focusing on the recent two periods (2000s and 2010s) revealed that climate change exerted the largest relative contributions to SOC dynamics in both layers and warming or drying can result in SOC loss. However, the influence of climate change weakened with soil depth, while the opposite for vegetation growth. Relationships between SOC and forest canopy height further confirmed this strengthened impact of vegetation with soil depth and highlighted the carbon sink function of deep soil in mature forest. Moreover, our estimates suggested that SOC dynamics in 71% of topsoil were controlled by climate change and its coupled influence with environmental variation (CE). Meanwhile, CE and the combined influence of climate change and vegetation growth dominated the SOC dynamics in 82.05% of the first meter soil. Additionally, the national cropland topsoil organic carbon increased with a rate of 23.6 ± 7.6 g C m^-2  yr^-1 since the 1980s, and the widely applied nitrogenous fertilizer was a key stimulus. Overall, our study extended the knowledge about the dynamics of SOC and deepened our understanding about the impacts of the primary factors.

Significant loss of soil inorganic carbon at the continental scale

Widespread soil acidification due to atmospheric acid deposition and agricultural fertilization may greatly accelerate soil carbonate dissolution and CO₂ release. However, to date, few studies have addressed these processes. Here, we use meta-analysis and nationwide-survey datasets to investigate changes in soil inorganic carbon (SIC) stocks in China. We observe an overall decrease in SIC stocks in topsoil (0–30 cm) (11.33 g C m^–2 yr^–1) from the 1980s to the 2010s. Total SIC stocks have decreased by ∼8.99 ± 2.24% (1.37 ± 0.37 Pg C). The average SIC losses across China (0.046 Pg C yr^–1) and in cropland (0.016 Pg C yr^–1) account for ∼17.6%–24.0% of the terrestrial C sink and 57.1% of the soil organic carbon sink in cropland, respectively. Nitrogen deposition and climate change have profound influences on SIC cycling. We estimate that ∼19.12%–19.47% of SIC stocks will be further lost by 2100. The consumption of SIC may offset a large portion of global efforts aimed at ecosystem carbon sequestration, which emphasizes the importance of achieving a better understanding of the indirect coupling mechanisms of nitrogen and carbon cycling and of effective countermeasures to minimize SIC loss.

Indoor heterogeneous photochemistry of molds and their contribution to HONO formation

To better understand the impact of molds on indoor air quality, we studied the photochemistry of microbial films made by Aspergillus niger species, a common indoor mold. Specifically, we investigated their implication in the conversion of adsorbed nitrate anions into gaseous nitrous acid (HONO) and nitrogen oxides (NO_x ), as well as the related VOC emissions under different indoor conditions, using a high-resolution proton transfer reaction-time of flight-mass spectrometer (PTR-TOF-MS) and a long path absorption photometer (LOPAP). The different mold preparations were characterized by the means of direct injection into an Orbitrap high-resolution mass spectrometer with a heated electrospray ionization (ESI-Orbitrap-MS). The formation of a wide range of VOCs, having emission profiles sensitive to the types of films (either doped by potassium nitrate or not), cultivation time, UV-light irradiation, potassium nitrate concentration and relative humidity was observed. The formation of nitrous acid from these films was also determined and found to be dependent on light and relative humidity. Finally, the reaction paths for the NO_x and HONO production are proposed. This work helps to better understand the implication of microbial surfaces as a new indoor source for HONO emission.

Exceptional increases in fluvial sediment fluxes in a warmer and wetter High Mountain Asia

[Figure: see text].

Spatiotemporal variations and regional differences in air temperature in the permafrost regions in the Northern Hemisphere during 1980-2018

Surface air temperature is an important factor for the permafrost thermal state in the Northern Hemisphere. It is therefore necessary to understand the variations and regional differences in air temperature to determine the interactions between permafrost degradation and climate change. In this study, we used observational data from the National Centers for Environmental Information, the China Meteorological Administration, and the World Data Centre for Meteorology to quantitatively analyze the variations and regional differences in air temperature from 1980 to 2018. The results demonstrated that the annual mean air temperatures were low in continuous permafrost regions and high in sporadic and isolated permafrost regions, with a significant warming rate of 0.371 ± 0.086 °C/decade. Air temperatures warmed the slowest during the winter and fastest during the spring, and no "warming hiatus" was observed in the permafrost regions of the Northern Hemisphere. The spatial patterns of freezing degree-days (FDDs) and thawing degree-days (TDDs) had different spatial characteristics. The decreasing rate of FDDs was -6.97 °C·days/year, while the increasing rate of TDDs was 6.4 °C·days/year. The air temperatures and warming trends had largely regional differences with respect to high latitude, transitional, and high altitude permafrost regions. Air temperature and its warming trend was the highest in high altitude regions. In addition, air temperature warming trends gradually decreased from the continuous permafrost zone to the island permafrost zone. The FDDs had a significant decreasing trend from the continuous permafrost zone to the island permafrost zone, whereas TDDs exhibited the opposite trend. The results indicate that the air temperature warming rate in the permafrost regions was approximately 2.0 times that of the global warming rate, and 1.3 times the global land warming rate from 1980 to 2018. These findings offer a perspective on the differences in permafrost and its thermal state across different regions under climate change.

Greening of the Qinghai–Tibet Plateau and Its Response to Climate Variations along Elevation Gradients

The vegetation of the Qinghai–Tibet Plateau (QTP) is vital to the global climate change and ecological security of China. However, the impact of climate variation on the spatial pattern and zonal distribution of vegetation in the QTP remains unclear. Accordingly, we used multisource remote-sensing vegetation indices (GIMMS-LAI, GIMMS NDVI, GLOBMAP LAI, MODIS EVI, MODIS NDVI, and MODIS NIRv), climate data, a digital elevation model, and the moving window method to investigate the changes in vegetation greenness and its response to climate variations in the QTP from 2001 to 2016. Results showed that the vegetation was greening in the QTP, which might be attributed to the increases in temperature and radiation. By contrast, the browning of vegetation may be caused by drought. Notably, the spatial patterns of vegetation greenness and its variations were linearly correlated with climate at low altitudes, and vegetation greenness was non-linearly correlated with climate at high altitudes. The Northwestern QTP needs to be focused on in regard to positive and decreased VGEG (vegetation greenness along the elevation gradient). The significantly positive VGEG was up to (34.37 ± 2.21) % of the QTP, which indicated a homogenization of vegetation greenness on elevation. This study will help us to understand the spatial distribution of vegetation greenness and VGEG in the QTP under global warming, and it will benefit ecological environment management, policymaking, and future climate and carbon sink (source) prediction.

Plant uptake of CO2 outpaces losses from permafrost and plant respiration on the Tibetan Plateau

High-latitude and high-altitude regions contain vast stores of permafrost carbon. Climate warming may result in the release of CO2 from both the thawing of permafrost and accelerated autotrophic respiration, but it may also increase the fixation of CO2 by plants, which could relieve or even offset the CO2 losses. The Tibetan Plateau contains the largest area of alpine permafrost on Earth. However, the current status of the net CO2 balance and feedbacks to warming remain unclear, given that the region has recently experienced an atmospheric warming rate of over 0.3 °C decade-1 We examined 32 eddy covariance sites and found an unexpected net CO2 sink during 2002 to 2020 (26 of the sites yielded a net CO2 sink) that was four times the amount previously estimated. The CO2 sink peaked at an altitude of roughly 4,000 m, with the sink at lower and higher altitudes limited by a low carbon use efficiency and a cold, dry climate, respectively. The fixation of CO2 in summer is more dependent on temperature than the loss of CO2 than it is in the winter months, especially at higher altitudes. Consistently, 16 manipulative experiments and 18 model simulations showed that the fixation of CO2 by plants will outpace the loss of CO2 under a wetting-warming climate until the 2090s (178 to 318 Tg C y-1). We therefore suggest that there is a plant-dominated negative feedback to climate warming on the Tibetan Plateau.

Revealing the community and metabolic potential of active methanotrophs by targeted metagenomics in the Zoige wetland of the Tibetan Plateau

The Zoige wetland of the Tibetan Plateau is one of the largest alpine wetlands in the world and a major emission source of methane. Methane oxidation by methanotrophs can counteract the global warming effect of methane released in the wetlands. Understanding methanotroph activity, diversity and metabolism at the molecular level can guide the isolation of the uncultured microorganisms and inform strategy-making decisions and policies to counteract global warming in this unique ecosystem. Here we applied DNA stable isotope probing using ¹³ C-labelled methane to label the genomes of active methanotrophs, examine the methane oxidation potential and recover metagenome-assembled genomes (MAGs) of active methanotrophs. We found that gammaproteobacteria of type I methanotrophs are responsible for methane oxidation in the wetland. We recovered two phylogenetically novel methanotroph MAGs distantly related to extant Methylobacter and Methylovulum. They belong to type I methanotrophs of gammaproteobacteria, contain both mxaF and xoxF types of methanol dehydrogenase coding genes, and participate in methane oxidation via H₄ MPT and RuMP pathways. Overall, the community structure of active methanotrophs and their methanotrophic pathways revealed by DNA-SIP metagenomics and retrieved methanotroph MAGs highlight the importance of methanotrophs in suppressing methane emission in the wetland under the scenario of global warming.

Temperature sensitivity of permafrost carbon release mediated by mineral and microbial properties

Temperature sensitivity (Q 10) of permafrost carbon (C) release upon thaw is a vital parameter for projecting permafrost C dynamics under climate warming. However, it remains unclear how mineral protection interacts with microbial properties and intrinsic recalcitrance to affect permafrost C fate. Here, we sampled permafrost soils across a 1000-km transect on the Tibetan Plateau and conducted two laboratory incubations over 400- and 28-day durations to explore patterns and drivers of permafrost C release and its temperature response after thaw. We find that mineral protection and microbial properties are two types of crucial predictors of permafrost C dynamics upon thaw. Both high C release and Q 10 are associated with weak organo-mineral associations but high microbial abundances and activities, whereas high microbial diversity corresponds to low Q 10 The attenuating effects of mineral protection and the dual roles of microbial properties would make the permafrost C-climate feedback more complex than previously thought.

Characteristics of dissolved organic carbon and nitrogen in precipitation in the northern Tibetan Plateau

Dissolved organic carbon (DOC) and nitrogen (N) play essential roles in global C and N cycles. To address the possible role of DOC and N in precipitation and enrich the related global database, the characteristics of DOC and N in precipitation were investigated in a typical remote permafrost region (upper Heihe River Basin) of the northern Tibetan Plateau (TP) from February 2019 to March 2020. The results demonstrated that the average DOC and total dissolved N (TDN) concentrations in the precipitation were 1.41 ± 1.09 μg mL^-1 and 0.84 ± 0.48 μg mL^-1, respectively, with relatively lower concentrations in the summer. The annual DOC and TDN fluxes were estimated to be 6.42 kg ha^-1 yr^-1 and 3.39 kg ha^-1 yr^-1, respectively, indicating that precipitation was a significant factor in C and N deposition. The light-absorbing properties of precipitation DOC from the SUVA₂₅₄ and spectral slope revealed that precipitation DOC containing more aromatic components and lower molecular weights mostly was present during the summer; the mass cross-section (at the wavelength of 365 nm) ranged 0.26-1.84 m² g^-1, suggesting the potential impact of DOC on climatic forcing in the area. The principal component analysis combined with air mass backward trajectories indicated that the air masses from west Siberia, Central Asia, and northwestern China most significantly influenced the precipitation C and N in the study area. The WRF-Chem simulations and aerosol vertical distributions further illustrated the air mass transport pathways, demonstrating that dust and anthropogenic emissions could be transported over the studied area by westerlies and monsoonal winds. In the study basin, the precipitation deposition of DOC and N contributed largely to the riverine DOC and N exportation during the summer and had potential ecological effects. These results highlight the importance of DOC and N deposition from precipitation in the northern TP.

Reduced microbial stability in the active layer is associated with carbon loss under alpine permafrost degradation

Permafrost degradation may induce soil carbon (C) loss, critical for global C cycling, and be mediated by microbes. Despite larger C stored within the active layer of permafrost regions, which are more affected by warming, and the critical roles of Qinghai-Tibet Plateau in C cycling, most previous studies focused on the permafrost layer and in high-latitude areas. We demonstrate in situ that permafrost degradation alters the diversity and potentially decreases the stability of active layer microbial communities. These changes are associated with soil C loss and potentially a positive C feedback. This study provides insights into microbial-mediated mechanisms responsible for C loss within the active layer in degraded permafrost, aiding in the modeling of C emission under future scenarios.

Loss of NO(g) to painted surfaces and its re-emission with indoor illumination

Heterogeneous surface reactions play a key role in the chemistry of the indoor environment because of the large indoor surface-to-volume ratio. The presence of photocatalytic material in indoor paints may allow photochemical reactions to occur at wavelengths of light that are present indoors. One such potential reaction is the heterogeneous photooxidation of NO to HONO. NO(g) is commonly found indoors, originating from combustion sources, ventilation and infiltration of outdoor air. We studied the interaction of NO(g) with painted surfaces illuminated with indoor fluorescent and incandescent lighting. There is a loss of NO(g) to painted surfaces in the dark at both 0 and 50% RH. At 50% RH, there is a re-release of some of that NO(g) under illumination. The same behavior is observed for illumination of different colored paints. This is in contrast to what is seen with TiO₂ as the substrate, where photoenhanced uptake of NO(g) and formation of NO₂ (g) are observed. We hypothesize that the loss of NO(g) is due to adsorption and diffusion into the paint. The re-release of NO under illumination is thought to be due to photooxidation of NO to HONO on the painted surface at higher relative humidities and subsequent HONO photolysis.

Mapping Frozen Ground in the Qilian Mountains in 2004–2019 Using Google Earth Engine Cloud Computing

The permafrost in the Qilian Mountains (QLMs), the northeastern margin of the Qinghai–Tibet Plateau, changed dramatically in the context of climate warming and increasing anthropogenic activities, which poses significant influences on the stability of the ecosystem, water resources, and greenhouse gas cycles. Yet, the characteristics of the frozen ground in the QLMs are largely unclear regarding the spatial distribution of active layer thickness (ALT), the maximum frozen soil depth (MFSD), and the temperature at the top of the permafrost or the bottom of the MFSD (TTOP). In this study, we simulated the dynamics of the ALT, TTOP, and MFSD in the QLMs in 2004–2019 in the Google Earth Engine (GEE) platform. The widely-adopted Stefan Equation and TTOP model were modified to integrate with the moderate-resolution imaging spectroradiometer (MODIS) land surface temperature (LST) in GEE. The N-factors, the ratio of near-surface air to ground surface freezing and thawing indices, were assigned to the freezing and thawing indices derived with MODIS LST in considerations of the fractional vegetation cover derived from MODIS normalized difference vegetation index (NDVI). The results showed that the GEE platform and remote sensing imagery stored in Google cloud could be quickly and effectively applied to obtain the spatial and temporal variation of permafrost distribution. The area with TTOP < 0 °C is 8.4 × 104 km2 (excluding glaciers and lakes) and accounts for 46.6% of the whole QLMs, the regional mean ALT is 2.43 ± 0.44 m, while the regional mean MFSD is 2.54 ± 0.45 m. The TTOP and ALT increase with the decrease of elevation from the sources of the sub-watersheds to middle and lower reaches. There is a strong correlation between TTOP and elevation (slope = −1.76 °C km−1, p < 0.001). During 2004–2019, the area of permafrost decreased by 20% at an average rate of 0.074 × 104 km2·yr−1. The regional mean MFSD decreased by 0.1 m at a rate of 0.63 cm·yr−1, while the regional mean ALT showed an exception of a decreasing trend from 2.61 ± 0.45 m during 2004–2005 to 2.49 ± 0.4 m during 2011–2015. Permafrost loss in the QLMs in 2004–2019 was accelerated in comparison with that in the past several decades. Compared with published permafrost maps, this study shows better calculation results of frozen ground in the QLMs.

Stream Dissolved Organic Matter in Permafrost Regions Shows Surprising Compositional Similarities but Negative Priming and Nutrient Effects

Permafrost degradation is delivering bioavailable dissolved organic matter (DOM) and inorganic nutrients to surface water networks. While these permafrost subsidies represent a small portion of total fluvial DOM and nutrient fluxes, they could influence food webs and net ecosystem carbon balance via priming or nutrient effects that destabilize background DOM. We investigated how addition of biolabile carbon (acetate) and inorganic nutrients (nitrogen and phosphorus) affected DOM decomposition with 28-day incubations. We incubated late-summer stream water from 23 locations nested in seven northern or high-altitude regions in Asia, Europe, and North America. DOM loss ranged from 3% to 52%, showing a variety of longitudinal patterns within stream networks. DOM optical properties varied widely, but DOM showed compositional similarity based on Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) analysis. Addition of acetate and nutrients decreased bulk DOM mineralization (i.e., negative priming), with more negative effects on biodegradable DOM but neutral or positive effects on stable DOM. Unexpectedly, acetate and nutrients triggered breakdown of colored DOM (CDOM), with median decreases of 1.6% in the control and 22% in the amended treatment. Additionally, the uptake of added acetate was strongly limited by nutrient availability across sites. These findings suggest that biolabile DOM and nutrients released from degrading permafrost may decrease background DOM mineralization but alter stoichiometry and light conditions in receiving waterbodies. We conclude that priming and nutrient effects are coupled in northern aquatic ecosystems and that quantifying two-way interactions between DOM properties and environmental conditions could resolve conflicting observations about the drivers of DOM in permafrost zone waterways.