Snow cover variation significantly impacts alpine vegetation dynamics on the Tibetan Plateau (TP), yet this effect under climate change remains underexplored. This study uses a survival analysis model to assess the influence of snow on vegetation green-up dynamics, while controlling for key temperature and water availability factors. This analysis integrates multi-source data, including satellite-derived vegetation green-up dates (GUDs), snow depth, accumulated growing degree days (AGDD), downward shortwave radiation (SRAD), precipitation, and soil moisture. Our survival analysis model effectively simulated GUD on the TP, achieving an R of 0.62 (p < 0.01), a root mean square error (RMSE) of 11.20 days, and a bias of -1.41 days for 2020 GUD predictions. It outperformed both the model excluding snow depth and a linear regression model. By isolating snow's impact, we found it exerts a stronger influence on vegetation GUD than precipitation in snow-covered areas of the TP. Furthermore, snow depth effects varied seasonally: a 1-cm increase in preseason snow depth reduced green-up rates by 8.48% before 156(th) day but increased them by 4.74% afterward. This indicates that deeper preseason snow cover delays GUD before June, but advances it from June onward, rather than having a uniform effect. These findings highlight the critical role of snow and underscore the need to incorporate its distinct effects into vegetation phenology models in alpine regions.

Environmental changes, such as climate warming and higher herbivory pressure, are altering the carbon balance of Arctic ecosystems; yet, how these drivers modify the carbon balance among different habitats remains uncertain. This hampers our ability to predict changes in the carbon sink strength of tundra ecosystems. We investigated how spring goose grubbing and summer warming-two key environmental-change drivers in the Arctic-alter CO2 fluxes in three tundra habitats varying in soil moisture and plant-community composition. In a full-factorial experiment in high-Arctic Svalbard, we simulated grubbing and warming over two years and determined summer net ecosystem exchange (NEE) alongside its components: gross ecosystem productivity (GEP) and ecosystem respiration (ER). After two years, we found net CO2 uptake to be suppressed by both drivers depending on habitat. CO2 uptake was reduced by warming in mesic habitats, by warming and grubbing in moist habitats, and by grubbing in wet habitats. In mesic habitats, warming stimulated ER (+75%) more than GEP (+30%), leading to a 7.5-fold increase in their CO2 source strength. In moist habitats, grubbing decreased GEP and ER by similar to 55%, while warming increased them by similar to 35%, with no changes in summer-long NEE. Nevertheless, grubbing offset peak summer CO2 uptake and warming led to a twofold increase in late summer CO2 source strength. In wet habitats, grubbing reduced GEP (-40%) more than ER (-30%), weakening their CO2 sink strength by 70%. One-year CO2-flux responses were similar to two-year responses, and the effect of simulated grubbing was consistent with that of natural grubbing. CO2-flux rates were positively related to aboveground net primary productivity and temperature. Net ecosystem CO2 uptake started occurring above similar to 70% soil moisture content, primarily due to a decline in ER. Herein, we reveal that key environmental-change drivers-goose grubbing by decreasing GEP more than ER and warming by enhancing ER more than GEP-consistently suppress net tundra CO2 uptake, although their relative strength differs among habitats. By identifying how and where grubbing and higher temperatures alter CO2 fluxes across the heterogeneous Arctic landscape, our results have implications for predicting the tundra carbon balance under increasing numbers of geese in a warmer Arctic.

The Arctic has warmed nearly four times faster than the global average since 1979, resulting in rapid glacier retreat and exposing new glacier forelands. These forelands offer unique experimental settings to explore how global warming impacts ecosystems, particularly for highly climate-sensitive arthropods. Understanding these impacts can help anticipate future biodiversity and ecosystem changes under ongoing warming scenarios. In this study, we integrate data on arthropod diversity from DNA gut content analysis-offering insight into predator diets-with quantitative measures of arthropod activity-density at a Greenland glacier foreland using Structural Equation Modelling (SEM). Our SEM analysis reveals both bottom-up and top-down controlled food chains. Bottom-up control, linked to sit-and-wait predator behavior, was prominent for spider and harvestman populations, while top-down control, associated with active search behavior, was key for ground beetle populations. Bottom-up controlled dynamics predominated during the early stages of vegetation succession, while top-down mechanisms dominated in later successional stages further from the glacier, driven largely by increasing temperatures. In advanced successional stages, top-down cascades intensify intraguild predation (IGP) among arthropod predators. This is especially evident in the linyphiid spider Collinsia holmgreni, whose diet included other linyphiid and lycosid spiders, reflecting high IGP. The IGP ratio in C. holmgreni negatively correlated with the activity-density of ground-dwelling prey, likely contributing to the local decline and possible extinction of this cold-adapted species in warmer, late-succession habitats where lycosid spiders dominate. These findings suggest that sustained warming and associated shifts in food web dynamics could lead to the loss of cold-adapted species, while brief warm events may temporarily impact populations without lasting extinction effects.

Daurian Pika ( Ochotona dauurica) are steppe-dwelling burrowing mammals with the potential to have large effects on central Asian grasslands due to their extensive range, propensity to occur at extremely high density, and roles as ecosystem engineers and important prey species. The few studies that have been done are mostly from northern China and Russia, while little research has been done in the majority of their range in Mongolia. We studied a population of Daurian Pika in the Darhad Valley of northern Mongolia, near the southern edge of the permafrost, where climate change is progressing rapidly. We evaluated pika populations at 87 random plots across a large 40 x 125 km area and assessed the impact of factors related to vegetation cover, grazing, and soils that predicted their occupancy and an index of their density (number of active burrows). We found that pikas were more likely to occur in areas with taller grass and higher forb cover, and burrow densities were higher in areas with low or moderate grazing and lower soil moisture. In summer, pikas mainly foraged on grass compared with forbs-while in fall, forbs appeared to be selected for in haypiles. Dense pika burrow systems had taller grasses and forbs in their immediate vicinity, suggesting that in some cases, pika could help promote plant growth for other grazers. Long-tailed Ground Squirrel (Urocitellus undulatus) was the second most abundant small mammal in our study sight and selected for areas with high cover of overgrazing indicator species and for short forbs, providing little evidence for competition with Daurian Pika. Our results suggest that shorter grass (similar to 1 cm) can decrease pika occupancy by 75%, while heavy grazing may decrease burrow density by 66% in dry soils. With grazing pressure in Mongolia increasing dramatically since the 1990s, future research is strongly needed to assess the impacts of grazing on this keystone species.

In Central Asia, the ground thermal regime is strongly affected by the interplay between topographic factors and ecosystem properties. In this study, we investigate the governing factors of the ground thermal regime in an area in Central Mongolia, which features discontinuous permafrost and is characterized by grassland and forest ecosystems. Miniature temperature dataloggers were used to measure near-surface temperatures at c. 100 locations throughout the 6 km2 large study area, with the goal to obtain a sample of sites that can represent the variability of different topographic and ecosystem properties. Mean annual near-surface ground temperatures showed a strong variability, with differences of up to 8 K. The coldest sites were all located in forests on north-facing slopes, while the warmest sites are located on steep south-facing slopes with sparse steppe vegetation. Sites in forests show generally colder near-surface temperatures in spring, summer and fall compared to grassland sites, but they are warmer during the winter season. The altitude of the measurement sites did not play a significant role in determining the near-surface temperatures, while especially solar radiation was highly correlated. In addition, we investigated the suitability of different hyperspectral indices calculated from Sentinel-2 as predictors for annual average near-surface ground temperatures. We found that especially indices sensitive to vegetation properties, such as the Normalized Difference Vegetation Index (NDVI), show a strong correlation. The presented observations provide baseline data on the spatiotemporal patterns of the ground thermal regime which can be used to train or validate modelling and remote sensing approaches targeting the impacts of climate change.

Global warming has caused the gradual degradation of permafrost, which may affect the vegetation water uptake from different depths. However, the water utilization strategies of different vegetation species during the thawing stages of permafrost regions need further study. To elucidate these differences, we selected the permafrost region in Northeast China as study area. We analyzed the water uptake from different depths of Larix gmelinii, a deciduous coniferous tree, Pinus sylvestris var. mongolica, an evergreen tree, and Betula platyphylla, a deciduous broadleaf tree, using stable isotopes of xylem water, soil water, and precipitation from June to October 2019. The results showed that L. gmelinii primarily used shallow soil water (0-40 cm) with the highest proportion at 64.1%, B. platyphylla generally used middle soil water (40-110 cm) with the highest proportion at 55.7%, and P. sylvestris mainly used middle (40-110cm) and deep soil water (110-150 cm) with the highest proportion at 40.4% and 56.9%. The water sources from different depths exhibited more frequent changes in P. sylvestris, indicating a higher water uptake capacity from different soil depths. L. gmelinii mainly uptakes water from shallow soils, suggesting that the water uptake of this species is sensitive to permafrost degradation. This study revealed the water uptake strategies from different depths of three tree species in a permafrost region, and the results suggested that water uptake capacity of different tree species should be considered in the prediction of vegetation changes in permafrost regions under a warming climate.

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.

Modeling Arctic-Boreal vegetation is a challenging but important task, since this highly dynamic ecosystem is undergoing rapid and substantial environmental change. In this work, we synthesized information on 18 dynamic vegetation models (DVMs) that can be used to project vegetation structure, composition, and function in North American Arctic-Boreal ecosystems. We reviewed the ecosystem properties and scaling assumptions these models make, reviewed their applications from the scholarly literature, and conducted a survey of expert opinion to determine which processes are important but lacking in DVMs. We then grouped the models into four categories (specific intention models, forest species models, cohort models, and carbon tracking models) using cluster analysis to highlight similarities among the models. Our application review identified 48 papers that addressed vegetation dynamics either directly (22) or indirectly (26). The expert survey results indicated a large desire for increased representation of active layer depth and permafrost in future model development. Ultimately, this paper serves as a summary of DVM development and application in Arctic-Boreal environments and can be used as a guide for potential model users, thereby prioritizing options for model development.

Snow is an important factor controlling vegetation functions in high latitudes/altitudes. However, due to the lack of reliable in -situ measurements, the effects of snow on vegetation phenology remains poorly understood. Here, we examine the effects of snow cover duration (SCD) on the start of growing season (SOS) for different vegetation types. SOS and SCD were extracted from in -situ carbon flux and albedo data, respectively, at 51 eddy covariance flux sites in the northern mid -high latitudes. The effects of SCD on SOS vary substantially among different vegetation types. For grassland, preseason SCD outperforms other factors controlling grassland SOS. However, for forests and cropland, the preseason air temperature is the dominant factor in controlling SOS. Preseason SCD mainly influences the SOS by regulating preseason air and soil temperature rather than soil moisture. The CMIP6 Earth system models (ESMs) fail to capture the effect of SCD on SOS. Thus, Random Forest (RF) models were established to predict future SOS changing trends considering the effect of SCD. For grassland and evergreen needleleaf forest, the projected SOS advance rate is slower when SCD is considered. These findings can help us better understand impacts of snow on vegetation phenology and carbon -climate feedbacks in the warming world.

Svalbards permafrost is thawing as a direct consequence of climate change. In the Low Arctic, vegetation has been shown to slow down and reduce the active layer thaw, yet it is unknown whether this also applies to High Arctic regions like Svalbard where vegetation is smaller, sparser, and thus likely less able to insulate the soil. Therefore, it remains unknown which components of High Arctic vegetation impact active layer thaw and at which temporal scale this insulation could be effective. Such knowledge is necessary to predict and understand future changes in active layer in a changing Arctic. In this study we used frost tubes placed in study grids located in Svalbard with known vegetation composition, to monitor the progression of active layer thaw and analyze the relationship between vegetation composition, vegetation structure and snow conditions, and active layer thaw early in summer. We found that moss thickness, shrub and forb height, and vascular vegetation cover delayed soil thaw immediately after snow melt. These insulating effects attenuated as thaw progressed, until no effect on thaw depth was present after 8 weeks. High Arctic mosses are expected to decline due to climate change, which could lead to a loss in insulating capacity, potentially accelerating early summer active layer thaw. This may have important repercussions for a wide range of ecosystem functions such as plant phenology and decomposition processes. Temperatures are rising in the Arctic, causing increased thaw of the layer of soil located above the permanently frozen ground. In Low Arctic regions vegetation cools the soil, which reduces the thawing. So far, we do not know whether the small plants growing in the High Arctic may be able to slow or reduce thaw. We measured soil thaw throughout the summer in High Arctic Svalbard in locations where vegetation composition is known. We also measured thickness of the moss layer, height of plants and snow depth. We found that moss thickness was the strongest factor in insulating the soil. Also the cover of plants, height of shrubs and forbs, and height of grass-like plants slowed soil thaw in the early summer. The insulating effects became less over time and no effects were found 8 weeks after onset of thaw. As climate change is causing changes in the Arctic vegetation, mosses and small shrubs are expected to decrease. As we found these to be the most important factors in insulating the soil, a future decrease in mosses and small shrubs may cause accelerated soil thaw at the start of summer. High Arctic vegetation slows active layer thaw in early summer after snow melt Mosses show a stronger negative relation with thaw depth than vascular vegetation Factors influencing active layer thaw change over time in early summer