Alpine grassland ecosystems play a crucial role in the global carbon (C) balance by contributing to the soil organic carbon (SOC) pool; thus, quantifying SOC stocks in these ecosystems is essential for understanding potential gains or losses in soil C under the threat of climate change and anthropogenic activities. Remote sensing plays a vital role in estimating SOC stocks; however, identifying reliable remote sensing proxies to enhance SOC prediction remains a challenge. Information on soil C cycling proxies can reveal how the balance between C inputs and outputs affects SOC. Therefore, these proxies could be effective indicators of SOC variations. In this study, we explored the potential of satellite-derived attributes related to soil C cycling proxies for predicting SOC stocks. We derived remote sensing indices such as gross primary production, soil respiration, soil moisture, land surface temperature, radiation, and soil disturbance and assessed the relationships between these indices and SOC stocks via partial least squares structural equation modeling (PLS-SEM). We evaluated the effectiveness of these indices in predicting SOC stocks, we compared PLS-SEM and quantile regression forest (QRF) models across different variable combinations, including static, intra-annual, and inter-annual information. The PLS-SEM results demonstrated the suitability of the derived remote sensing indices and their interactions in reflecting processes related to soil C balance. The QRF models, using these indices, achieved promising prediction accuracies, with a coefficient of determination (R2) of 0.54 and a root mean square error (RMSE) of 0.79 kg m-2 at the topmost 10 cm of soil. However, the prediction performance generally decreased with increasing soil depth, up to 30 cm. The results also revealed that adding intra- and inter-annual information to remotely sensed proxies did not increase the prediction accuracy. Our study revealed that gross primary production, soil respiration, soil moisture, land surface temperature, radiation, and soil disturbance are effective proxies for representing factors influencing soil C balance and mapping SOC stocks in alpine grasslands.

Wildfire strongly influences permafrost environment and soil organic carbon (SOC) pool. In this study, we reviewed the effects of fire severity, time after a fire, and frequency on SOC in boreal permafrost regions. This review highlighted several key points: the effect of wildfires on SOC increased with an increase of fire severity, and the amount of vegetation returned and surface organic matter replenished was less in a short term, which resulted in a significantly lower SOC content compared to that of before the fire. Within a short period after fire, the SOC in near-surface permafrost and the active layer decreased significantly due to the loss of above ground biomass, permafrost thaw, and increased microbial decomposition; as the years pass after a fire, the SOC gradually accumulates due to the contributions of litter layer accumulation and rooting systems from different stages of succession. The increase in fire frequency accelerated permafrost thawing and the formation of thermokarst, resulting in the rapid release of a large amount of soil carbon and reduced SOC storage. Therefore, the study on the effects of wildfires on SOC in the boreal permafrost region is of great significance to understanding and quantifying the carbon balance of the ecosystem.

Soil organic carbon (SOC) plays a vital role in the global carbon cycle and soil quality assessment. The Qinghai-Tibet Plateau is one of the largest plateaus in the world. Therefore, in this region, SOC density and the spatial distribution of SOC are highly sensitive to climate change and human intervention. Given the insufficient understanding of the spatial distribution of SOC density in the Qinghai-Tibet Plateau, this study utilized machine learning (ML) algorithms to estimate the density and distribution pattern of SOC density in the region. In this study, we first collected multisource data, such as optical remote sensing data, synthetic aperture radar) (SAR) data, and other environmental variables, including socioeconomic factors, topographic factors, climate factors, and soil properties. Then, we used ML algorithms, namely random forest (RF), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM), to estimate the topsoil SOC density and spatial distribution patterns of SOC density. We also aimed to investigate any driving factors. The results are as follows: (1) The average SOC density is 5.30 kg/m(2). (2) Among the three ML algorithms used, LightGBM showed the highest validation accuracy (R-2 = 0.7537, RMSE = 2.4928 kgC/m(2), MAE = 1.7195). (3) The normalized difference vegetation index (NDVI), valley depth (VD), and temperature are crucial in predicting the spatial distribution of topsoil SOC density. Feature importance analyses conducted using the three ML models all showed these factors to be among the top three in importance, with contribution rates of 14.08%, 12.29%, and 14.06%; 17.32%, 20.73%, and 24.62%; and 16.72%, 11.96%, and 20.03%. (4) Spatially, the southeastern part of the Qinghai-Tibet Plateau has the highest topsoil SOC density, with recorded values ranging from 8.41 kg/m(2) to 13.2 kg/m(2), while the northwestern part has the lowest density, with recorded values ranging from 0.85 kg/m(2) to 2.88 kg/m(2). Different land cover types showed varying SOC density values, with forests and grasslands having higher SOC densities compared to urban and bare land areas. The findings of this study provide a scientific basis for future soil resource management and improved carbon sequestration accounting in the Qinghai-Tibet Plateau.

Patchiness acts as an indicator of terrestrial ecosystem degradation and can lead to considerable loss of soil organic carbon and total nitrogen. However, quantitative assessments of the effects of patchiness on soil organic carbon and total nitrogen stocks and their associated mechanisms remain limited. This study aimed to explore the influence mechanisms of patchiness on soil organic carbon and total nitrogen stocks and to project the quantitative contribution of the further expansion of patchiness and vegetation recovery. Soil properties, soil organic carbon and total nitrogen stocks were investigated using a combination of field sampling and aerial photography in four grassland types, alpine meadow, alpine steppe, temperate grassland, and desert grassland, at 47 sites in northwestern China. Soil organic carbon and total nitrogen densities in the bare patches were 34 - 54 % and 23 - 41 % lower, respectively, compared to the original vegetation. At the plot-scale, current soil organic carbon and total nitrogen stocks ranged from 30.85 to 77.80 T/ha and 3.26 to 10.19 T/ha, respectively, across grassland types; with a 10 - 27 % and 7 - 24 % potential loss of soil organic carbon and total nitrogen stocks, respectively, from the further expansion of patchiness but a 10 - 50 % and 9 - 37 % potential increase in soil organic carbon and total nitrogen stocks, respectively, from vegetation recovery. Soil organic carbon and total nitrogen stocks were positively correlated with vegetation biomass, soil clay content, and precipitation (p < 0.001), whereas they were negatively correlated with patchiness (p < 0.001). In summary, patchiness reduced soil organic carbon and total nitrogen stocks by decreasing vegetation inputs and increasing erosion outputs, while vegetation recovery showed potential for increasing carbon and nitrogen stocks. Our results highlight that maintaining intact vegetation cover is critical for preserving terrestrial ecosystem carbon and nitrogen storage.

Seasonally frozen ground (SFG) significantly contributes to global carbon sinks. Global warming and anthropogenic-induced disturbances threaten the carbon storage capacity of SFG. Challenges in evaluating the SFG carbon storage potential include the lack of understanding of the control mechanisms of soil organic carbon (SOC) variations and timely spatial estimates of SOC. In this study, we investigated SOC stocks in SFG in the Tibet Autonomous Region, China, in 2020 and 2021. We employed partial least squares structural equation modeling (PLS-SEM) to explore the effect of complex processes (interacting roles of climate, plant physiology and phenology, freeze-thaw cycle, soil environment, and C inputs) on SOC and mapped SOC stocks in the topmost 30 cm. We identified four causal pathways: (1) an indirect pathway representing the effect of climate on plant physiology and phenology through changes in freeze-thaw cycles and soil environment, (2) an indirect pathway representing the effect of climate on C inputs through changes in freeze-thaw cycles, soil environment and plant physiology and phenology, (3) an indirect pathway representing the effect of climate on freeze-thaw cycles, and (4) an indirect pathway representing the effect of climate on the soil environment through changes in freeze--thaw cycles. C inputs exerted the greatest control on SOC. The effect of these factors decreased with increasing soil depth. We used PLS-SEM to generate maps of SOC stocks in SFG at a 500 m resolution with a moderate accuracy. The estimated mean SOC stocks in the 0-30 cm layer reached 6.87 kg m(-2), with a 95% confidence interval ranging from 6.2 to 7.5 kg m(-2). Our results indicated that it is critical to consider the depth dependence of the direct and indirect effects of environmental factors when assessing the control mechanisms of SOC vari-ations. In this work, we also demonstrated that spatially explicit SOC estimates based on timely investigations are important for assessing C stocks against the background of considerable environmental changes across the Ti-betan Plateau.

The increase in deciduous shrub growth in response to climate change throughout the Arctic tundra has uncertain implications, in part due to a lack of field observations. Here we investigate how increasing alder shrub growth in alpine tundra in Interior Alaska corresponds to active layer thickness and soil physical properties. We documented increased alder growth by combining biomass harvests and dendrochronology with the analysis of remotely sensed Normalized Difference Vegetation Index and fire history. Active layer thickness was measured with a tile probe and carbon and nitrogen pools were assessed via elemental analysis. Shallower organic layers under increasing alder growth indicate that nitrogen-rich, deciduous litter inputs may play a role in accelerating decomposition. Despite the observed reduction in organic carbon stocks, active layer thickness was the same under alder and adjacent graminoid tundra, implying deeper thaw of the underlying mineral soil. This study provides further evidence that the widely observed expansion of deciduous shrubs into graminoid tundra will reduce ecosystem carbon stocks and intensify soil-atmosphere thermal coupling. Two consequences of rapid climate warming in the Arctic, where grass-like plants dominate under very cold conditions, are an increased growth and occurrence of shrubs and associated thaw of frozen ground. This exposes organic matter in soils to microbes that can decompose it into carbonaceous greenhouse gases, but some of this carbon loss may be offset by the increased plant growth. Here, we investigate the impacts of greater shrub presence on soil properties at five sites in Alaska. We documented shrub growth by analyzing satellite images, which can help us understand the productivity and/or leaf coverage at each site back in time, and annual growth rings in shrub stems, which show how old the shrubs are and how much they grow each year. We also measured the depth of soil thaw in the field and its organic matter content in a laboratory. Where shrubs were more common, we found a thinner layer of organic matter at the soil surface. Thaw depth remained the same, which may indicate that the presence of shrubs results in deeper thaw of the mineral soil. Our findings support the hypothesis that shrub expansion will further enhance warming-driven increases of greenhouse gas emissions from Arctic landscapes. Trends in dendrochronology and Normalized Difference Vegetation Index reveal increasing growth of alder shrubs in Interior Alaska.More alder cover results in the loss of the soil organic layer and thus soil C and N that is not offset by more shrub biomass.Increasing alder growth may promote permafrost thaw not captured by tile probe active layer thickness monitoring.

Large stocks of soil organic carbon (SOC) accumulated in the Northern Hemisphere permafrost regions may be vulnerable to climatic warming, but global estimates of SOC distribution and magnitude in permafrost regions still have large uncertainties. Based on multiple high-resolution environmental variables and a compiled soil sample dataset (>3000 soil profiles), we used machine-learning methods to estimate the size and spatial distribution of SOC for the top 3 m soils in the Northern Hemisphere permafrost regions. We also identified key environmental predictors of SOC. The results showed that the SOC storage for the top 3 m soil was 1079 +/- 174 Pg C across the Northern Hemisphere permafrost regions (20.8 x 10(6) km(2)), including 1057 +/- 167 Pg C in the northern permafrost regions and 22 +/- 7 Pg C in the Third Pole permafrost regions. The mean annual air temperature and NDVI are the main controlling factors for the spatial distribution of SOC stocks in the northern and the Third Pole permafrost regions. Our estimations were more accurate than the existing global SOC stock maps. The results improve our understanding of the regional and global permafrost carbon cycle and their feedback to the climate system.

Anticipated permafrost thaw in upcoming decades may exert significant impacts on forest soil nitrogen (N) dynamics. The rate of soil N mineralization (Nmin) plays a crucial role in determining soil N availability. Nevertheless, our understanding remains limited regarding how biotic and abiotic factors influence the Nmin of forest soil in response to permafrost thaw. In this study, we investigated the implications of permafrost thaw on Nmin within a hemiboreal forest based on a field investigation along the degree of permafrost thaw, having monitored permafrost conditions for eight years. The results indicate that permafrost thaw markedly decreased Nmin values. Furthermore, Nmin demonstrated positive associations with soil substrates (namely, soil organic carbon and soil total nitrogen), microbial biomass carbon and nitrogen, and soil moisture content. The decline in Nmin due to permafrost thaw was primarily attributed to the diminished quality and quantity of soil substrates rather than alterations in plant community composition. Collectively, our results underscore the pivotal role of soil substrate and microbial biomass in guiding forest soil N transformations in the face of climate-induced permafrost thaw.

As an active ecological agent in the boreal forest, wildfires have many important impacts on the underlying permafrost. However, investigations of post-fire changes in the features of ecosystem-protected permafrost are extremely limited in the patchy permafrost regions, Northeast China. Additionally, the impacts of wildfires on patchy permafrost are complicated in this region. In this paper, based on field surveys and observations, permafrost features and their influencing factors were analyzed in the area burned in 2006. The results showed notably lower soil temperatures in shrub-wetland (NWH1, unburned and NWH2, light burn) in comparison with those in the birch-larch forest (NWH3, light burn and NWH4, moderate burn). Changes in shallow ground temperatures (0-4 m in depth) were significant. Mean annual soil temperatures (MAST) and annual maximum soil temperature at the light-burn NWH2 site were 0.3-5.2 degrees C higher than those of unburned NWH1, but annual minimum soil temperatures, 0.3-2.1 degrees C lower. MASTs at the moderately burned NWH4 were 0.6-1.6 degrees C higher than those at the light-burn NWH3. The active layer thickness (ALT) was greater at burned sites, and; at the moderately burned site, only seasonal frost was found when 13 years after the burn. The contents of soil organic carbon and total nitrogen were the highest at the unburned NWH1 from 0.0 to 0.4 m in depth, followed by those at the lightly-burned NWH2 and NWH3, and the lowest at the moderately-burned NWH4. Climate warming, forest fires, and changing local factors (e.g., soil moisture contents, snow cover, soil texture and drainage conditions) worked together to increase ground temperature and ALT. These research results could provide important scientific basis for the protection of boreal forest and wetlands and the ecosystem-protected permafrost under a warming climate.

Aims Quantitatively assess the foraging and burrowing effects of plateau pikas (Ochotona curzoniae, hereafter pikas) on vegetation biomass and soil organic carbon at plot scale. Methods Combining field surveys and aerial photographing, we investigated pikas density, vegetation biomass, soil organic carbon and total nitrogen at quadrat-scale in 82 grassland sites of the Qinghai-Tibetan Plateau. We then upscaled these variables to plot-scale and eventually quantified pikas' foraging and burrowing effects on aboveground biomass and soil organic carbon. Results Pikas have a wide distribution, with densities ranging from 40.29 to 71.40 ha(-1). Under this density level, pikas consume approximate 21% to 40% of the total vegetation biomass, while their burrowing activity causes less than 1% vegetation biomass reduction. However, pikas burrowing transfers 1 to 5 T ha(-1)of soil to the ground surface, which contains approximate 20 to 70 kg ha(-1)of soil organic carbon and 2 to 5 kg ha(-1)of total nitrogen. Conclusions Vegetation biomass is susceptible to the foraging influence of pikas. Pikas burrowing activity has a potential impact on soil organic carbon loss and thus vegetation growth. These results are conducive to improve our understanding of the effects of pikas on regulating alpine grasslands. Unmanned aerial vehicle is a feasible and efficient tool to perform the monitoring extensiveness plots and study the role of pikas.