Widespread dieback of natural Mongolian pine (Pinus sylvestris var. mongolica) forests in Hulunbuir sandy land since 2018 has raised concerns about their sustainability in afforestation programs. We hypothesized that this dieback is driven by two interrelated mechanisms: (1) anthropogenic fire suppression disrupting natural fire regime, and (2) climate change-induced winter warming reducing snow cover duration and depth. To test these, we quantified dieback using Green Normalized Difference Vegetation Index (GNDVI) across stands with varying fire histories via UAV-based multispectral imagery, alongside long-term climatic observations (1960-2024) of temperature, precipitation, and snow dynamics from meteorological stations combined with remote sensing datasets. Results showed that an abrupt change point in 2018 for both annual precipitation and mean temperature was identified, coinciding with dieback. Significant negative linear relationship between GNDVI (forest health) and last fire interval indicated prolonged fire exclusion exacerbating dieback, possibly via pathogen/pest accumulation. Winter temperature rose significantly during 1960-2023, with notable acceleration following abrupt change point in 1987. Concurrently, winters during 2018-2023 exhibited pronounced warming, with snow cover duration reduced by 23 days and snow depth diminished by 7.6 cm. These conditions reduced snowmelt -derived soil moisture (critical water source) recharge in early spring, exacerbating drought stress during critical growth periods and predisposing trees to pest and disease infestations. Our results support both hypotheses, demonstrating that dieback is synergistically driven by fire regime alteration and climate-mediated snowpack reductions. Converting pure pine forests into mixed pine-broadleaf forests via differentiated water sources was proposed to restore ecological resilience in sandy ecosystems.

Understanding soil organic carbon (SOC) distribution and its environmental controls in permafrost regions is essential for achieving carbon neutrality and mitigating climate change. This study examines the spatial pattern of SOC and its drivers in the Headwater Area of the Yellow River (HAYR), northeastern Qinghai-Xizang Plateau (QXP), a region highly susceptible to permafrost degradation. Field investigations at topsoils of 86 sites over three summers (2021-2023) provided data on SOC, vegetation structure, and soil properties. Moreover, the spatial distribution of key permafrost parameters was simulated: temperature at the top of permafrost (TTOP), active layer thickness (ALT), and maximum seasonal freezing depth (MSFD) using the TTOP model and Stefan Equation. Results reveal a distinct latitudinal SOC gradient (high south, low north), primarily mediated by vegetation structure, soil properties, and permafrost parameters. Vegetation coverage and above-ground biomass showed positive correlation with SOC, while soil bulk density (SBD) exhibited a negative correlation. Climate warming trends resulted in increased ALT and TTOP. Random Forest analysis identified SBD as the most important predictor of SOC variability, which explains 38.20% of the variance, followed by ALT and vegetation coverage. These findings likely enhance the understanding of carbon storage controls in vulnerable alpine permafrost ecosystems and provide insights to mitigate carbon release under climate change.

The retreat of glaciers due to climate change is reshaping mountain landscapes and biodiversity. While previous research has documented vegetation succession after glacier retreat, our understanding of functional diversity dynamics is still limited. In this case study, we address the effects of glacier retreat on plant functional diversity by integrating plant traits with ecological indicator values across a 140-year chronosequence in a subalpine glacier landscape. We reveal that functional richness and functional dispersion decrease with glacier retreat, while functional evenness and functional divergence increase, suggesting a shift toward more specialized and competitive communities. Our findings highlight the critical role of ecological factors related to soil moisture, soil nutrients and light availability in shaping plant community dynamics. As years since deglaciation was a key factor in regression and machine learning models, encapsulating time-lagged, spatial and historical processes, we highlight the need of including time into phenomenological or mechanistic models predicting biodiversity change following glacier retreat. The integrative approach of this case study provides novel insights into the potential response of alpine plant communities to climate change, offering a deeper understanding of how to predict and anticipate the effects of glacier extinction on biodiversity in rapidly changing environments. (sic)(sic): (sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)140(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).

Aims Human disturbances and environmental changes significantly influence riparian vegetation composition and dynamics by altering hydrological regimes. In high-altitude river systems, snowmelt-driven water-level fluctuations add further complexity to these processes. However, little is known about how riparian plant functional strategies-competitor (C), stress-tolerator (S), and ruderal (R)-respond to dam-induced water-level fluctuations. This study aimed to assess the effects of water-level fluctuations and climatic factors on riparian vegetation functional strategies along the Nyang River, Qinghai-Tibet Plateau.Location This study was conducted along the Nyang River, Qinghai-Tibet Plateau, China. A total of 33 sites were surveyed, spanning upstream, reservoir, and downstream zones, which were categorized based on water-level fluctuation gradients.Methods We classified riparian vegetation functional strategies using Grime's CSR framework based on species trait data. Hydrological and climatic variables, including water-level fluctuations, temperature, precipitation, and snow cover, were derived from the Global Surface Water Mapping Layers and the FLDAS dataset. Soil properties were measured in the field. Redundancy analysis and partial least squares path modeling were applied to identify key drivers of CSR variation across different river zones.Results Riparian vegetation exhibited significant differences in stress tolerance and ruderal strategies across the Nyang River. Plants in the reservoir and upstream zones had higher S-strategy values, whereas downstream vegetation was predominantly characterized by high competitiveness. The primary drivers of CSR variation across the catchment were temperature, precipitation, and snow cover. In reservoir zones, water-level fluctuations (e.g., retention time, river width) were the dominant influences, whereas downstream vegetation was mainly governed by climate variables. In upstream zones, precipitation, water-level fluctuations, and snow cover jointly influenced CSR strategies. Water-level fluctuations directly regulated functional strategies, whereas snow cover had both direct effects and indirect effects via soil moisture changes.Conclusions This study highlights the interactive effects of climate change and flow regulation on riparian vegetation functional strategies in high-altitude river systems. The findings provide critical insights into how water-level fluctuations and climatic factors shape riparian plant strategies, offering valuable information for ecosystem-based river management and conservation in alpine regions.

Substantial nitrous oxide (N2O) emissions from permafrost-affected regions could accelerate climate warming, given that N2O exhibits approximately 300 times greater radiative forcing potential than carbon dioxide. Pronounced differences exist in N2O emissions between freeze and thaw periods (FP and TP), but the mechanisms by which environmental factors regulate the production and emission of N2O during these two periods have not been thoroughly examined. We therefore combined static chamber gas chromatography, in-situ soil temperature (ST) and moisture (SM) monitoring, and 16S rRNA sequencing to investigate seasonal N2O variations in the Qinghai-Tibet Plateau (QTP) alpine meadow ecosystem, and assess the relative contributions of environmental and microbial drivers. Our findings indicate that N2O fluxes (-3.15 to 6.10 mu g m-2 h-1) fluctuated between weak sources and sinks, peaking during FP, particularly at its late stage with initial surface soil thawing. Soil properties affect N2O emissions by regulating denitrification processes and altering microbial community diversity. During the FP, ST fluctuations control N2O release by modifying mineral nutrient availability. During TP, soil texture modulates denitrification-driven N2O production through its effect on SM. Spring N2O pulses likely originate from microbial reactivation in thawed soil. N2O accumulated in frozen soil may gradually release during vertical profile thawing. On the QTP, a warmer and wetter climate scenario may alter N2O emissions by modifying the duration of the FP and TP and phase-specific hydrothermal allocation. This study provides mechanistic insights for predicting climate change impacts on N2O flux in fragile alpine meadow ecosystems.

Highlights What are the main findings? Permafrost in the Muri area responded to human disturbance without significant spatial expansion during 2000-2024. The semi-arid climate, rough terrain, thin root zone and gappy vertical structure underneath were the major factors. What are the implications of the main findings? Annual ALT estimated from 2000 to 2024 filled the data gap of high-resolution ALT in the Muri area. Knowledge was provided for a better understanding of alpine permafrost development.Highlights What are the main findings? Permafrost in the Muri area responded to human disturbance without significant spatial expansion during 2000-2024. The semi-arid climate, rough terrain, thin root zone and gappy vertical structure underneath were the major factors. What are the implications of the main findings? Annual ALT estimated from 2000 to 2024 filled the data gap of high-resolution ALT in the Muri area. Knowledge was provided for a better understanding of alpine permafrost development.Abstract Alpine permafrost plays a vital role in regional hydrology and ecology. Alpine permafrost is highly sensitive to climate change and human disturbance. The Muri area, which is located in the headwaters of the Datong River, northeast of the Tibetan Plateau, has undergone decadal mining, and the permafrost stability there has attracted substantial concerns. In order to decipher how and to what extent the permafrost in the Muri area has responded to the decadal mining in the context of climate change, daily MODIS land surface temperatures (LSTs) acquired during 2000-2024 were downscaled to 30 m x 30 m. The active layer thickness (ALT)-ground thaw index (DDT) coefficient was derived from in situ ALT measurements. An annual ALT of 30 m x 30 m spatial resolution was subsequently estimated from the downscaled LST for the Muri area using the Stefan equation. Validation of the LST and ALT showed that the root of mean squared error (RMSE) and the mean absolute error (MAE) of the downscaled LST were 3.64 degrees C and -0.1 degrees C, respectively. The RMSE and MAE of the ALT estimated in this study were 0.5 m and -0.25 m, respectively. Spatiotemporal analysis of the downscaled LST and ALT found that (1) during 2000-2024, the downscaled LST and estimated ALT delineated the spatial extent and time of human disturbance to permafrost in the Muri area; (2) human disturbance (i.e., mining and replantation) caused ALT increase without significant spatial expansion; and (3) the semi-arid climate, rough terrain, thin root zone and gappy vertical structure beneath were the major controlling factors of ALT variations. ALT, estimated in this study with a high resolution and accuracy, filled the data gaps of this kind for the Muri area. The ALT variations depicted in this study provide references for understanding alpine permafrost evolution in other areas that have been subject to human disturbance and climate change.

Surface soil moisture (SSM) is a key limiting factor for vegetation growth in alpine meadow on the Qinghai-Tibetan Plateau (QTP). Patches with various sizes and types may cause the redistribution of SSM by changing soil hydrological processes, and then trigger or accelerate alpine grassland degradation. Therefore, it is vital to understand the effects of patchiness on SSM at multi-scales to provide a reference for alpine grassland restoration. However, there is a lack of direct observational evidence concerning the role of the size and type of patches on SSM, and little is known about the effects of patches pattern on SSM at plot scale. Here, we first measured SSM of typical patches with different sizes and types at patch scale and investigated their patterns and SSM spatial distribution through unmanned aerial vehicle (UAV)-mounted multi-type cameras at plot scale. We then analyzed the role of the size and type of patchiness on SSM at both patch and plot scales. Results showed that: (1) in situ measured SSM of typical patches was significantly different (P < 0.01), original vegetation patch (OV) had the highest SSM, followed by isolate vegetation patch (IV), small bare patch (SP), medium bare patch (MP) and large bare patch (LP); (2) the proposed method based on UAV images was able to estimate SSM (0-40 cm) with a satisfactory accuracy (R-2 = 0.89, P < 0.001); (3) all landscape indices of OV, with the exception of patch density, were positively correlated with SSM at plot scale, while most of the landscape indices of LP and IV showed negative correlations (P < 0.05). Our results indicated that patchiness intensified the spatial heterogeneity of SSM and potentially accelerated the alpine meadow degradation. Preventing the development of OV into IV and the expansion of LP is a critical task for alpine meadow management and restoration.

Alpine tundra ecosystems, like their arctic counterparts, have historically been the sites of considerable soil organic carbon (SOC) storage due to climatic factors that suppressed microbial activity. While climatic factors are important, heterotopic soil respiration (and SOC storage) may be influenced by a range of soil characteristics. In this study, we measured soil respiration, soil temperature, soil moisture, soil nutrient concentrations, soil pH, and soil texture in 4 alpine tundra sites located in Rocky Mountain National Park, Colorado, USA from June 2015 - September 2021. We also used geospatial modeling to visualize predicted climate changes in this system over the 21st century. Finally, we measured SOC concentrations over the seven-year study. We found that soil respiration was significantly correlated with soil temperature, soil moisture, and soil texture. All other parameters were not significantly correlated with soil respiration. We also found that SOC concentrations did not change significantly over the course of the seven-year study. The predictive models show that by the end of the century, over the majority of the park, the mean maximum air temperature will increase, the amount of snowfall will decrease, soil moisture will decrease, and the number of snow-free days will increase. These results suggest that SOC is not currently being lost from this system at a high rate. In addition, it appears that with a changing climate, soil respiration may increase with warming, but the overall increase may be limited by decreased soil moisture and in some cases, high soil temperatures.

The spatial distribution of saturated hydraulic conductivity (Ks) is controlled by soil processes at multiple scales, and this spatial variability is crucial to simulating soil moisture movement. Nevertheless, few studies focus on the spatial variability of Ks and how changes through alpine meadow degradation or the specific scales at which the controlling factors function. This study therefore examines the scale-dependent relationships between Ks and several primary driving factors. Soil samples were collected at an interval of 3 m along three transects on a slope in the Qinghai-Tibet Plateau (QTP) and Ks, bulk density (BD), above-ground biomass (AGB), soil organic carbon content (SOC), sand content (SAND), silt content (SILT) and clay content (CLAY) were analysed. Ks showed strong spatial dependency and irregular distribution due to alpine meadow degradation. Pearson correlation analysis revealed a significant correlation between BD, AGB and Ks (p < 0.001). Furthermore, cross-semivariograms showed that Ks exhibited strong spatial correlation with AGB and SAND. Using the state space method, we determined that BD, SOC, AGB and CLAY are the main factors that control the spatial distribution of Ks on the slope. A two-factor state-space equation based on CLAY and BD provides a good representation of Ks, enabling the prediction and estimation of Ks distribution characteristics. These findings enhance our understanding of the crucial parameters that govern hydrological processes at the slope-scale of alpine grassland on the QTP, thereby helping to elucidate permafrost-related hydrological processes related to climate change.

Background and aimsAlpine swamp meadows play a vital role in water conservation and maintaining ecological balance. However, the response mechanisms of its area and hydrological functions under global climate change remain unclear, particularly the impact of permafrost degradation on water storage capacity, which urgently requires quantification.MethodsWe integrated multi-temporal Landsat data (2000-2023) and phenological features to construct a classification framework for alpine swamp meadows. A multi-source remote sensing-based water balance assessment method was developed. Random forest importance evaluation and piecewiseSEM were employed to quantify the impacts and pathways of multidimensional driving factors on changes in alpine swamp meadow area and water storage.ResultsThe phenology-based classification method effectively extracted alpine swamp meadows with a mean producer's accuracy of 92.84%, user's accuracy of 92.14%, and a Kappa coefficient of 0.95. The study found that the spatial expansion of alpine swamp meadows in the watershed showed an initial decrease followed by an increase trend, while the water storage capacity continued to decline, indicating a significant decoupling between the two.ConclusionUnder climate change, increased precipitation and reduced snow cover albedo have led to the expansion of alpine swamp meadows, while enhanced evapotranspiration and the degradation of permafrost aquicludes have caused a systematic decline in their water storage capacity. These findings provide a scientific basis for assessing the health of alpine ecosystems and managing water resources under climate change.