Iron (Fe) minerals possess a huge specific surface area and high adsorption affinity, usually considered as rust tanks of organic carbon (OC), playing an important role in global carbon storage. Microorganisms can change the chemical form of Fe by producing Fe-chelating agents such as side chains and form a stable complex with Fe(III), which makes it easier for microorganisms to use. However, in seasonal frozen soil thawing, the succession of soil Fe-cycling microbial communities and their coupling relationship with Fe oxides and Fe-bound organic carbon (Fe-OC) remains unclear. We characterized changes in the Fe phase, Fe-OC, Fe-oxidizing bacteria (FeOB), and Fe-reducing bacteria (FeRB) in the subsoil and analyzed the microbial mechanism underlying Fe-OC changes in alpine grassland by constructing a composite structural equation model (SEM). We found that the Fe(III) content consistently exceeded that of Fe(II). Among the three types of Fe oxides, organically complex Fe (Fe-p) decreased from 2.54 to 2.30 gkg(-1), whereas the opposite trend was observed for poorly crystalline Fe (Fe-o). The Fe-OC content also decreased (from 10.31 to 9.47 gkg(-1); p < 0.05). Fe-cycling microorganisms were markedly affected by the thawing of frozen soil (except FeRB). Fe-p and Feo directly affected changes in Fe-OC. Soil moisture (SM) and FeOB were significant indirect factors affecting Fe-OC changes. Freeze-thaw changes in the subsoil of alpine grassland in Central Asia significantly affected FeOB and Fe oxides, thus affecting the Fe-OC content. To the best of our knowledge, this was the first study to examine the influence of Fe-cycling microorganisms on the Fe phase and Fe-OC in the soil of alpine grassland in Central Asia. Overall, our findings provide scientific clues for exploring the biogeochemical cycle process in future climate change.

The burrowing activity of plateau pikas (Ochotona curzoniae; hereafter, pikas) may profoundly influence vegetation species composition on the Qinghai-Tibetan Plateau (QTP). Although significant efforts have been made to examine the relationship between vegetation species composition and pikas disturbance, our knowledge regarding the direct influence of pikas activity on vegetation species diversity is still limited. We conducted field observations on pikas burrows and surrounding vegetation patches at 23 alpine grassland sites to investigate this effect. When compared to vegetation patches, pikas burrowing activity decreased soil hardness, thus improving water infiltration, while caused the less reduction of soil nutrition and soil moisture when compared to adjacent vegetation patches. Vegetation species composition on pikas burrows significantly differed from that on vegetation patches. Common plant species between pikas burrows and vegetation patches were fewer than three in all types of grasslands, and ten species were found exclusively on pikas burrows. The total species richness, including both pikas burrows and vegetation patches, was approximately 1.3-2.5 times higher than that on each single patch type (pikas burrows or vegetation patches). A conceptual framework was proposed to synthesize the evolution of vegetation species composition under a disturbance regime resulting from pika's burrowing. Overall, we concluded that pika's burrowing activity enhanced vegetation species richness by loosening the soil, creating safe sites for seed settling and germination, which provided a novel habitat for vegetation invasion.

Study region: The source region of the Yangtze River in the Qinghai-Tibet Plateau, China. Study focus: In the context of global warming, conducting a comprehensive study on the hydrothermal processes and their influencing factors in the permafrost active layer of the Tibetan Plateau is crucial for gaining a better understanding of the ecohydrological processes in alpine grasslands. In this study, we analyzed differences in soil temperature and humidity change patterns in the active layer of four alpine grassland types in the Totuohe Basin of the Yangtze River source area. We aimed to discuss the influence of vegetation, soil, and other factors on the hydrothermal mechanism of the active layer. The main research results are as follows: (1) Significant differences in the active layer's hydrothermal regime, with higher vegetation cover correlating to lower thaw indices and better moisture conditions. (2) Vegetation and water content strongly influence thermal conditions and active layer thickness. In high-cover alpine meadows, ground surface temperature is lower with a 200 cm active layer, while swamp meadows have a shallowest layer at 160 cm. (3) Deeper active layer moisture is influenced by freezing and thawing, while shallower layers are affected by warm-season precipitation and soil texture. (4) Negative heat fluxes in the topsoil of alpine swamp and high-cover meadows indicate substantial heat release, likely contributing to permafrost preservation due to high active layer water content. New hydrological insights for the region: (1) Vegetation cover significantly influences the thermal and moisture conditions of the active layer, with higher vegetation associated with lower thaw indices and better moisture conditions. (2) Soil moisture distribution within the active layer is controlled by both freeze-thaw cycles and warm-season precipitation, indicating complex interactions between seasonal processes and soil properties.

Permafrost temperature is a vital indicator of climate and permafrost changes, benefiting ecosystem development and informing local climate strategies. Alpine grasslands impact moisture and heat exchange between the surface and atmosphere, thereby affecting the thermal state of underlying permafrost. This study analyzed permafrost temperatures (2004-2019) from various alpine grasslands (including alpine meadow, alpine steppe, alpine desert grassland, and barren land) in the Beiluhe region of the Tibetan Plateau and revealed their connections to climate change and controlling factors, using time-frequency analysis. The findings revealed that in the time-frequency domain, permafrost temperatures exhibited multiple time scales characteristics, driven by climate fluctuations. Changes in the active layer closely followed monthly climate variations, while permafrost dynamics responded to annual climate changes. Significant oscillations with periods of 10-11, 8-9, and 14 years were observed in the surface, permafrost table, and deep permafrost layers, respectively. Among the different types of alpine grasslands, alpine meadows proved to be the most sensitive to climate change, with the intensity of periodic fluctuations initially decreasing and then increasing with depth in alpine meadows, while it consistently decreased with depth in the other three alpine grasslands. The impact of air temperature, precipitation, and wind speed on permafrost dynamics exhibited depth-dependent variations in the time-frequency domain, contrasting with the time domain where permafrost temperature changes were predominantly associated with air temperature across all depths.

As the largest and highest plateau in the world, ecosystems on the Tibetan Plateau (TP) imply fundamental ecological significance to the globe. Among the variety, alpine grassland ecosystem on the TP forms a critical part of the global ecosystem and its soil carbon accounts over nine tenths of ecosystem carbon. Revealing soil carbon dynamics and the underlying driving forces is vital for clarifying ecosystem carbon sequestration capacity on the TP. By selecting northern TP, the core region of the TP, this study investigates spatiotemporal dynamics of soil total carbon and the driving forces based on two phases of soil sampling data from the 2010s and the 2020s. The research findings show that soil total carbon density (STCD) in total-surface (0-30 cm) in the 2010s (8.85 +/- 3.08 kg C m(- 2)) significantly decreased to the 2020s (7.15 +/- 2.90 kg C m(-2)), with a decreasing rate (Delta STCD) of -0.17 +/- 0.39 kg C m(-2) yr(-1). Moreover, in both periods, STCD exhibited a gradual increase with soil depth deepening, while Delta STCD loss was more apparent in top-surface and mid-surface than in sub-surface. Spatially, Delta STCD loss in alpine desert grassland was - 0.41 +/- 0.48 kg C m(- 2) yr(-1), which is significantly higher than that in alpine grassland (-0.11 +/- 0.31 kg C m(- 2) yr(- 1)) or alpine meadow (-0.04 +/- 0.28 kg C m(- 2) yr(- 1)). The STCD in 2010s explained >30 % of variances in Delta STCD among the set of covariates. Moreover, rising temperature aggravates Delta STCD loss in alpine desert grassland, while enhanced precipitation alleviates Delta STCD loss in alpine meadow. This study sheds light on the influences of climate and background carbon on soil total carbon loss, which can be benchmark for predicting carbon dynamics under future climate change scenarios.

Aboveground biomass (AGB) serves as a crucial measure of ecosystem productivity and carbon storage in alpine grasslands, playing a pivotal role in understanding the dynamics of the carbon cycle and the impacts of climate change on the Qinghai-Xizang Plateau. This study utilized Google Earth Engine to amalgamate Landsat 8 and Sentinel-2 satellite imagery and applied the Random Forest algorithm to estimate the spatial distribution of AGB in the alpine grasslands of the Beiliu River Basin in the Qinghai-Xizang Plateau permafrost zone during the 2022 growing season. Additionally, the geodetector technique was employed to identify the primary drivers of AGB distribution. The results indicated that the random forest model, which incorporated the normalized vegetation index (NDVI), the enhanced vegetation index (EVI), the soil-adjusted vegetation index (SAVI), and the normalized burn ratio index (NBR2), demonstrated robust performance in regards to AGB estimation, achieving an average coefficient of determination (R2) of 0.76 and a root mean square error (RMSE) of 70 g/m2. The average AGB for alpine meadows was determined to be 285 g/m2, while for alpine steppes, it was 204 g/m2, both surpassing the regional averages in the Qinghai-Xizang Plateau. The spatial pattern of AGB was primarily driven by grassland type and soil moisture, with q-values of 0.63 and 0.52, and the active layer thickness (ALT) also played a important role in AGB change, with a q-value of 0.38, demonstrating that the influences of ALT should not be neglected in regards to grassland change.

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.

The growth of vegetation on the Qinghai Tibet Plateau (QTP) is experiencing significant changes due to climate change. There is still a lack of high -precision simulation methods for alpine grassland cover (AGC), and the climate feedback mechanisms of AGC remain unclear, which poses challenges for the production of highprecision AGC products and the formulation of ecological conservation policies. In this study, a transferable stacking deep learning (Stacking -DL) model is proposed based on a CNN, a DNN, and a GRU for AGC time series simulation. The applicability of deep learning models for AGC simulation is evaluated based on long time series of measured data, MODIS data, and environmental factors. Finally, the AGC spatiotemporal changes and controlling environmental factors in the alpine region were analyzed based on Sen 's slope and structural equation modeling (SEM). The results showed that feature selection and parameter optimization improved the applicability of the deep learning models in AGC simulations, and the DNN (R 2 = 0.899, RMSE = 0.078) model performed best among the base deep learning models. The Stacking -DL model combines the advantages of multiple models and achieves high transfer accuracy. In the YRSR, the AGC increase area (20.34 %) is greater than the AGC decrease area (3.34 %), the increase area is mainly located in the northeast, and the decrease area is mainly located in the southwest. AGC changes in the YRSR are mainly controlled by permafrost and climate. This study provides a high -precision and transferable vegetation monitoring model for alpine mountain regions based on advanced deep learning models and clarifies the response mechanism of AGC under climate change.

Plateau pika (Ochotona curzoniae, hereafter pika) is considered to exert a profound impact on vegetation species diversity of alpine grasslands. Great efforts have been made at mound or quadrat scales; nevertheless, there is still controversy about the effect of pika. It is vital to monitor vegetation species composition in natural heterogeneous ecosystems at a large scale to accurately evaluate the real role of pika. In this study, we performed field survey at 55 alpine grassland sites across the Shule River Basin using combined methods of aerial photographing using an unmanned aerial vehicle (UAV) and traditional ground measurement. Based on our UAV operation system, Fragmentation Monitoring and Analysis with aerial Photography (FragMAP), aerial images were acquired. Plot-scale vegetation species were visually identified, and total pika burrow exits were automatically retrieved using the self-developed image processing software. We found that there were significant linear relationships between the vegetation species diversity indexes obtained by these two methods. Additionally, the total number of identified species by the UAV method was 71, which was higher than the Quadrat method recognition, with the quantity of 63. Our results indicate that the UAV was suitable for long-term repeated monitoring vegetation species composition of multiple alpine grasslands at plot scale. With the merits of UAV, it confirmed that pika's disturbance belonged to the medium level, with the density ranging from 30.17 to 65.53 ha(-1). Under this density level, pika had a positive effect on vegetation species diversity, particularly for the species richness of sedge and forb. These findings conclude that the UAV was an efficient and economic tool for species monitoring to reveal the role of pika in the alpine grasslands.

Soil thermal regime in permafrost regions is sensitive to climate change and may cause vast ecological consequences under future warming scenarios. However, there still lacks a systematic evaluation on the effect of warming on soil thermodynamics in the different ecosystems of permafrost regions. This study investigated the alterations of soil thermodynamics in alpine swamp meadow and alpine steppe under experimental warming by open-top chambers in permafrost regions of the central Tibetan Plateau. The results showed that air temperature increased significantly with an annual mean increase of 1.4 degrees C under warming. Compared to alpine swamp meadow, soil thermodynamics represented by soil temperature, soil thermal parameters, soil freeze-thaw process and active layer thickness in alpine steppe was more susceptible to warming. Specifically, soil temperature at 5-40 cm depths increased more in alpine steppe than alpine swamp meadow under warming, especially at topsoil (5-20 cm). Moreover, the increase in soil temperature at topsoil was greater during cold season than warm season. Greater alterations of soil thermal parameters were likely because soil moisture content reduced more in alpine steppe. Regarding soil freeze-thaw process, warming significantly postponed the onset of completely frozen stage and reduced the completely frozen days in alpine steppe. Active layer thickness in alpine steppe distinctly increased by 46 cm on average and showed an increasing trend under warming from 2009 to 2011. Overall, vegetation coverage and soil moisture content were responsible for the different responses of soil thermodynamics to experimental warming. The study has important implications for future scenarios as permafrost and grassland degradation may intensify under climate warming.