Storage, patterns, and environmental controls of soil organic carbon stocks in the permafrost regions of the Northern Hemisphere

Total nitrogen levels as a key constraint on soil organic carbon stocks across Australian agricultural soils

Understanding how pedoclimatic drivers regulate soil organic carbon (SOC) stock is crucial for gaining insights into terrestrial carbon-climate feedback and thus adaptation to climate change. However, current data-driven SOC predictive models often neglect to incorporate total nitrogen (TN) data, thereby constraining our understanding of carbon-nitrogen interactions and their influences on SOC storage mechanisms across large scales. Utilizing an interpretable machine learning technique, we investigated how key drivers (TN, climate, elevation, land use, pH, SiO2) affect SOC stocks at different soil depths across Australian major agricultural production regions. Incorporating TN into data-based SOC predictive models enhanced the explained variation by approximately 11 %. TN was identified as the predominant factor influencing SOC stocks, accounting for over 47 % of observed variability across all depths and outweighing climate effects in subsurface soils. Furthermore, we identified depth-specific thresholds of TN levels that constrain SOC accumulation: 1.45 mg/g soil for 0-10 cm, 0.80 mg/g soil for 10-20 cm and 0.63 mg/g soil for 20-30 cm. Projections of SOC stocks under different scenarios suggest that achieving these TN thresholds can promote SOC accumulation and help offset SOC losses associated with a 1 °C increase in mean annual temperature. This study underscores TN levels as a key constraint on SOC stocks across Australian agricultural soils, and thus should be explicitly considered when predicting large-scale SOC dynamics and formulating soil carbon sequestration strategies.

Substantial Mercury Releases and Local Deposition from Permafrost Peatland Wildfires in Southwestern Alaska

Increasing wildfire activity at high northern latitudes has the potential to mobilize large amounts of terrestrial mercury (Hg). However, understanding implications for Hg cycling and ecosystems is hindered by sparse research on peatland wildfire Hg emissions. In this study, we used measurements of soil organic carbon (SOC) and Hg, burn depth, and environmental indices derived from satellite remote sensing to develop machine learning models for predicting Hg emissions from major wildfires in the permafrost peatland of the Yukon-Kuskokwim Delta (YKD) in southwestern Alaska. Wildfire Hg emissions during summer 2015─estimated as the product of Hg:SOC (0.38 ± 0.17 ng Hg g C1-), predicted SOC stores (mean [5th-95th] = 9.1 [5.3-11.2] kg C m-2), and burn depth (11.3 [8.2-13.9] cm)─were 556 [164-1138] kg Hg or approximately 6% of Hg emissions from wildfire activity >60°N. Modeling estimates suggest that wildfire nearly doubled summertime Hg deposition within 10 km, despite advection of more than 75% of total emissions beyond Alaska. YKD areal emissions combined with remote sensing estimates of burned area suggest that wildfire Hg emissions from northern peatlands (25.4 [14.9-33.6] Mg y-1) are an important component of the northern Hg budget. Additional research is needed to refine these estimates and understand the implications for Arctic and global Hg cycling.

Hydrological response to long-lasting dry spell at the southern edge of Siberian permafrost

Regions experiencing prolonged dry spell exhibit intensified land-atmosphere coupling, exacerbating dry conditions within the hydrological system. Yet, understanding the propagation of these processes within the context of permafrost degradation remains limited. Our study investigates concurrent hydro-climate variations in the semi-arid Selenga River basin in the southern edge of Siberian permafrost. Driven by the natural atmospheric circulations, this region experienced two distinct dry spells during 1954-2013. It enables comparative investigations into the role of warming-induced permafrost degradations in drought dynamics under land-atmosphere coupling. Based on a comprehensive analysis of observed borehole data from 1996 to 2009 and empirical methods, we identify widespread permafrost loss in the semi-arid Selenga region. Such large-scale landscape changes may increase the infiltration of water from the surface to the subsurface hydrological system, and significantly influence the dry conditions in landsurface. First, significant decreasing trends are observed in river runoff (-0.30mm/yr, p < 0.05) and TWS (-3.16 mm/yr, p = 0.1), despite the absence of an apparent trend in annual precipitation (0.009 mm/yr, p = 0.9). Furthermore, in comparison to the first dry spell (1974-1983, 10yrs), the hydro-climatic variables show prolonged and more severe water deficits in runoff and TWS during the second dry spell (1996-2012, 17 yrs), with a reduced runoff-generation efficiency from precipitation. Such exacerbated dry conditions are coincident with amplified positive anomalies observed in air temperature, PET, as well as low-level geopotential height. These concurrent "hot-dry" phenomena indicate an enhanced land-atmospheric interaction within the hydro-climate system, which is further evidenced by the negative relationship between permafrost thawing index and runoff deficits (regression coefficient = -3.8, p < 0.001). As climate warming continues, the ongoing permafrost degradation could reinforce water scarcity, triggering an irreversible shift in water availability in water-scarce regions. Our findings could support freshwater management for regional food supply, human health, and ecosystem functions in the regions undergoing large-scale permafrost degradation.

Soil organic carbon fractions in China: Spatial distribution, drivers, and future changes

Soil is the world's largest terrestrial carbon pool and plays an important role in the global carbon cycle, which may be greatly affected by global change. Recently, research frameworks have indicated that division of soil organic carbon (SOC) into two forms particulate organic carbon (POC) and mineral-associated organic carbon (MAOC) can help us better understand SOC cycle. However, there is a lack of the use of meta-analysis combined with machine learning models to explore the spatial distribution of SOC fractions at large scales. Based on 356 studies conducted in Chinese terrestrial ecosystems, we performed a meta-analysis of extracted data and measured data combined with machine learning models to reveal the spatial distribution of soil POC density (POCD) and MAOC density (MAOCD) and the main drivers of variations in POCD and MAOCD. Our study demonstrated that POCD and MAOCD in China's soil were 3.24 and 2.61 kg m-2, with stocks of 31.10 and 25.06 Pg, respectively. Climate, soil, and vegetation properties together explained 44.9 % and 27.2 % of the variation in POCD and MAOCD, respectively. Climate was more important than other variables in controlling the changes in POCD, with mean annual temperature being specifically the main driver. Soil, however, was more important than other variables in controlling changes in MAOCD, with soil clay content being the main driver. Compared to the other climate scenarios, the rate of change in POCD and MAOCD was higher with a 1.5 °C increase in temperature. In the future, we should pay more attention to the impact of climate change on POCD, which provides a theoretical basis for achieving the "dual-carbon" target. Our study contributes to the understanding of the potential mechanisms of the changes in SOC fractions under global change and provides useful information for future prediction models to simulate the impacts of global change.

Data-driven assessment of soil total nitrogen on the Qinghai-Tibet Plateau

The investigation of soil total nitrogen (STN) holds significant importance in the preservation and sustainability of Earth's ecosystems. The Qinghai-Tibet Plateau (QTP), renowned as the world's most expansive plateau and characterized by its exceptionally delicate ecosystem, demands an in-depth exploration of its STN content. In this study, we use a machine learning approach to extrapolate point-scale measured STN stocks to the entire QTP and calculated STN storage from 0 to 2 m. Our results show that the XGB algorithm performs well in modeling STN despite variations in simulation accuracy for specific depth ranges. The spatial distribution of STN across the QTP exhibits pronounced heterogeneity, especially for the 0-50 cm soil layer, with relatively higher STN stocks in the southeast and lower stocks in the northwest of QTP. The vertical distribution reveals a gradual decrease in STN storage with increasing depth. The 0-50 cm soil layer holds the highest STN stocks, averaging around 0.78 kg/m2, which is almost the sum of STN stocks in the 50-100 cm and 100-200 cm soil layers. Meanwhile, the STN stocks are smaller in permafrost zone than that in non-permafrost zone. We also investigate the impact factors that control the spatiotemporal distribution of STN. It indicates that vegetation, precipitation, temperature, and elevation are the major factors for STN distribution, while physical properties of the soil have a relatively smaller impact. These findings are crucial for understanding the distribution and evolution of STN on the QTP.

Changes in soil organic carbon stocks and its physical fractions along an elevation in a subtropical mountain forest

Soil microorganisms are the drivers of soil organic carbon (SOC) mineralization, and the activities of these microorganisms are considered to play a key role in SOC dynamics. However, studies of the relationship between soil microbial carbon metabolism and SOC stocks are rare, especially in different physical fractions (e.g., particulate organic carbon (POC) fraction and mineral-associated organic carbon (MAOC) fraction). In this study, we investigated the changing patterns of SOC stocks, POC stocks, MAOC stocks and microbial carbon metabolism (e.g., microbial growth, carbon use efficiency and biomass turnover time) at 0-20 cm along an elevational gradient in a subtropical mountain forest ecosystem. Our results showed that SOC and POC stocks increased but MAOC stocks remained stable along the elevational gradient. Soil microbial growth increased while microbial turnover time decreased with elevation. Using structural equation modeling, we found that heightened microbial growth is associated with elevated POC stocks. Moreover, MAOC stocks positively correlate with microbial growth but show negative associations with both POC stocks and soil pH. Overall, the increase in SOC stocks along the elevational gradient is primarily driven by changes in POC stocks rather than MAOC stocks. These findings underscore the importance of considering diverse soil carbon fractions and microbial activities in predicting SOC responses to elevation, offering insights into potential climate change feedbacks.

Effects of agricultural land use on soil nutrients and its variation along altitude gradients in the downstream of the Yarlung Zangbo River Basin, Tibetan Plateau

Agricultural development in alpine ecosystems can cause significant changes in soil nutrients. With large altitude spans, the combined effect of the two is still unclear in existing research. To answer this problem, this study took the downstream of the Yarlung Zangbo River Basin (YZRB) as the study area, and designed a comparative soil sampling scheme along the altitude gradient. We compared soil nutrient characteristics facility agricultural land (FA) and field cultivated land (FC), using grassland (GL), the main source of agriculture expansion, as a reference. A total of 44 sampling areas were designed within an altitude range of 800-3500 m to reveal the effects of agricultural land development along the altitude gradient on soil nutrients. Research found that the FA significantly improved soil nutrient levels, with most nutrient indicators higher than those of FC and GL (P < 0.05), while the above indicators of FC were only slightly higher than GL. Moreover, the effects of agricultural development decreased with soil depth, and mainly occurred within the 0-30 cm soil layer (P < 0.05). With increasing altitude, most of soil nutrients first decreased and then increased and differences in soil nutrients among different land use modes first expanded and then shrank. This may be related to differences in farmland management methods, vegetation coverage, and temperature under different altitude gradient constraints. Especially in middle-altitude areas, the FA not only breaks through the low-temperature limitations of the plateau, but also has the advantage of large-scale development, which is suggested for future agricultural intensification in the plateau.

Dramatic Carbon Loss in a Permafrost Thaw Slump in the Tibetan Plateau is Dominated by the Loss of Microbial Necromass Carbon

Thaw slumps can lead to considerable carbon loss in permafrost regions, while the loss of components from two major origins, i.e., microbial and plant-derived carbon, during this process remains poorly understood. Here, we provide direct evidence that microbial necromass carbon is a major component of lost carbon in a retrogressive permafrost thaw slump by analyzing soil organic carbon (SOC), biomarkers (amino sugars and lignin phenols), and soil environmental variables in a typical permafrost thaw slump in the Tibetan Plateau. The retrogressive thaw slump led to a ∼61% decrease in SOC and a ∼25% SOC stock loss. As evident in the levels of amino sugars (average of 55.92 ± 18.79 mg g^-1 of organic carbon, OC) and lignin phenols (average of 15.00 ± 8.05 mg g^-1 OC), microbial-derived carbon (microbial necromass carbon) was the major component of the SOC loss, accounting for ∼54% of the SOC loss in the permafrost thaw slump. The variation of amino sugars was mainly related to the changes in soil moisture, pH, and plant input, while changes in lignin phenols were mainly related to the changes in soil moisture and soil bulk density.

Permafrost degradation is accelerating beneath the bottom of Yanhu Lake in the Hoh Xil, Qinghai-Tibet Plateau

Lakes on the Qinghai-Tibet Plateau (QTP) have notably expanded over the past 20 years. Due to lake water level rise and lake area expansion, the permafrost surrounding these lakes is increasingly becoming submerged by lake water. However, the change process of submerged permafrost remains unclear, which is not conducive to further analyzing the environmental effects of permafrost change. Yanhu Lake, a tectonic lake on the QTP, has experienced significant expansion and water level rise. Field measurement results indicate that the water level of Yanhu Lake increased by 2.87 m per year on average from 2016 to 2019. Cold permafrost, developed in the lake basin, was partially submerged by lake water at the end of 2017. Based on the water level change and permafrost thermal regime, a numerical heat conduction permafrost model was employed to predict future changes in permafrost beneath the lake bottom. The simulated results indicate that the submerged permafrost would continuously degrade because of the significant thermal impact of lake water. By 2100, the maximum talik thicknesses could reach approximately 7, 12, 16, and 19 m under lake-bottom temperatures of +2.0, +4.0, +6.0, and +8.0 °C, respectively. Approximately 291 years would be required to completely melt 47 m of submerged permafrost under the lake-bottom temperature of +4 °C. Note that the permafrost table begins to melt earlier than does the permafrost base, and the decline in the permafrost table occurs relatively fast at first, but then the process is attenuated, after which the permafrost table again rapidly declines. Compared to climate warming, the degradation of the submerged permafrost beneath the lake bottom occurred more rapidly and notably.