Soil freeze-thaw state influences multiple terrestrial ecosystem processes, such as soil hydrology and carbon cycling. However, knowledge of historical long-term changes in the timing, duration, and temperature of freeze-thaw processes remains insufficient, and studies exploring the combined or individual contributions of climatic factors-such as air temperature, precipitation, snow depth, and wind speed-are rare, particularly in current thermokarst landscapes induced by abrupt permafrost thawing. Based on ERA5-Land reanalysis, MODIS observations, and integrated thermokarst landform maps, we found that: 1) Hourly soil temperature from the reanalysis effectively captured the temporal variations of in-situ observations, with Pearson' r of 0.66-0.91. 2) Despite an insignificant decrease in daily freeze-thaw cycles in 1981-2022, other indicators in the Qinghai-Tibet Plateau (QTP) changed significantly, including delayed freezing onset (0.113 d yr- 1), advanced thawing onset (-0.22 d yr- 1), reduced frozen days (-0.365 d yr- 1), increased frozen temperature (0.014 degrees C yr- 1), and decreased daily freeze-thaw temperature range (-0.015 degrees C yr- 1). 3) Total contributions indicated air temperature was the dominant climatic driver of these changes, while indicators characterizing daily freeze-thaw cycles were influenced mainly by the combined effects of increased precipitation and air temperature, with remarkable spatial heterogeneity. 4) When regionally averaged, completely thawed days increased faster in the thermokarstaffected areas than in their primarily distributed grasslands-alpine steppe (47.69%) and alpine meadow (22.64%)-likely because of their stronger warming effect of precipitation. Locally, paired comparison within 3 x 3 pixel windows from MODIS data revealed consistent results, which were pronounced when the thermokarst-affected area exceeded about 38% per 1 km2. Conclusively, the warming and wetting climate has significantly altered soil freeze-thaw processes on the QTP, with the frozen soil environment in thermokarstaffected areas, dominated by thermokarst lakes, undergoing more rapid degradation. These insights are crucial for predicting freeze-thaw dynamics and assessing their ecological impacts on alpine grasslands.

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.

Snow amounts and duration are susceptible to climate change and may significantly affect plant diversity and biomass in grassland ecosystems. Yet, the combined effects of grassland use (type and intensity) and snow depth on plant diversity and productivity remain poorly understood. We established two complementary field experiments to explore the mechanisms driving the effects of grassland use (type and intensity) and snow manipulation on plant diversity and productivity in the meadow steppe. An experiment on grassland use type and snow manipulation showed that lower snow cover in winter reduced soil moisture in the snowmelt period, significantly increased the abundance of ammonia-oxidizing archaea and ammonia-oxidizing bacteria, and initiated nitrification earlier, resulting in the loss of soil available nitrogen, and then reduced the aboveground biomass of early grasses. An experiment on grassland mowing intensity and snow manipulation showed that moderate mowing intensity can restrain the loss of grass biomass and soil nutrients and maintain grassland sustainability in winters with less snow. Stochasticity has played a more important role in plant community assembly in higher intensity of grassland use. Based on our results, we recommend that optimal defoliation height can restrain the loss of grass biomass and soil nutrients and maintain grassland sustainability in winters with less snow. This study has potential benefits for optimizing sustainable production and maintaining ecosystem function under winter snowfall changes in the future across large regions of arid and semiarid grasslands. (c) 2024 The Society for Range Management. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

Due to the impact of climate change, significant alterations in snowmelt have already occurred, which have been demonstrated to play a crucial role in photosynthetic carbon sequestration processes in vegetation. However, the effect of changes in snowmelt on light use efficiency (LUE) of grassland remain largely unknown in the permafrost region of Qinghai-Tibetan Plateau (QTP). By utilizing remote sensing data from 2000 to 2017, we conducted an analysis on the spatial and temporal patterns of LUE for various types of permafrost and grassland on the QTP. The LUE of the growing season was 1.1588 g CMJ(-1), displaying variations among different ecosystems: alpine steppe of seasonally frozen ground (ASS) > alpine meadow of seasonally frozen ground (AMS) > alpine meadow of permafrost (AMP) > alpine steppe of permafrost (ASP). Furthermore, our study demonstrated that decreasing snowmelt during the growing season had a negative impact on LUE through meteorological factors, elucidating its influence on LUE for approximately 40.65%, 34.06%, 41.05%, and 32.68% of ecosystems studied. Reduced snowmelt indirectly affects LUE by lowering air temperatures, vapor pressure deficit and solar radiation, while replenishing soil moisture. Additionally, changes in snowmelt can directly affect LUE by reducing the insulating properties of snow cover. Therefore, when estimating gross primary productivity (GPP) using remote sensing data based on LUE, it is essential to consider the impact of snowmelt. This will better represent vegetation phenology's response to 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.

BackgroundGrasslands in drylands are increasingly influenced by human activities and climate change, leading to alterations in albedo and radiative energy balance among others. Surface biophysical properties and their interactions change greatly following disturbances. However, our understanding of these processes and their climatic impacts remains limited. In this study, we used multi-year observations from satellites and eddy-covariance towers to investigate the response of albedo to variables closely associated with human disturbances, including vegetation greenness (EVI) and surface soil volumetric water content (VWC), as well as snow cover and clearness index (Ta) for their potential relationships.ResultsEVI and VWC during the growing season were the primary factors influencing albedo. EVI and VWC were negatively correlated with albedo, with VWC's total direct and indirect impacts being slightly smaller than those of EVI. During the non-growing season, snow cover was the most influential factor on albedo. VWC and Ta negatively affected albedo throughout the year. We estimated the impact of variations in EVI and VWC on climate to be in the range of 0.004 to 0.113 kg CO2 m-2 yr-1 in CO2 equivalent.ConclusionsThis study indicates the significant impacts of climate change and human disturbances on vulnerable grassland ecosystems from the perspective of altered albedo. Changes in vegetation greenness and soil properties induced by climate change and human activities may have a substantial impact on albedo, which in turn feedback on climate change, indicating that future climate policies should take this factor into consideration.

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.