Background and aimsUnderstanding of the influences of soil moisture changes on plant phenological shifts on the Qinghai-Tibetan Plateau (QTP) is insufficient mainly because previous studies focused on the climatic factors. We explored the role of soil moisture in regulating plant autumn phenology on the QTP.MethodsBased on long-term ground observations of soil moisture, plant phenology, and meteorology, temporal and spatial changes in soil moisture and leaf senescence dates (LSD) were analyzed using ordinary least squares regression and a meta-analysis procedure. Influences of soil moisture changes on the LSD shifts were assessed through correlation analysis and support vector machine, and also compared with those of air temperature and precipitation.ResultsNonsignificant interannual changes in soil moisture were observed, and LSD significantly delayed at a rate of 2.7 days/decade. Spatial changes of LSD were more correlated with site elevation and air temperature, and soil moisture and precipitation showed insignificant negative impacts. However, correlations between annual LSD and average soil moisture were mainly positive. Soil moisture and precipitation showed greater importance in regulating the LSD of sedges and grasses, whereas temperature exerted a larger influence on the LSD of forbs. Precipitation showed higher importance in regulating the interannual shifts in LSD, while temperature played a more important role in determining the spatial variations.ConclusionSoil moisture had divergent influences on the temporal and spatial shifts in LSD of different plant functional groups on the QTP. Overall, soil moisture was outweighed by temperature and precipitation in regulating autumn phenological shifts. However, soil moisture may become increasingly important in the future and forbs are expected to be more competitive if the QTP becomes warmer and drier, which will bring challenges in grassland management and utilization on the QTP.

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.

The more insects there are, the more food there is for insectivores and the higher the likelihood for insect-associated ecosystem services. Yet, we lack insights into the drivers of insect biomass over space and seasons, for both tropical and temperate zones. We used 245 Malaise traps, managed by 191 volunteers and park guards, to characterize year-round flying insect biomass in a temperate (Sweden) and a tropical (Madagascar) country. Surprisingly, we found that local insect biomass was similar across zones. In Sweden, local insect biomass increased with accumulated heat and varied across habitats, while biomass in Madagascar was unrelated to the environmental predictors measured. Drivers behind seasonality partly converged: In both countries, the seasonality of insect biomass differed between warmer and colder sites, and wetter and drier sites. In Sweden, short-term deviations from expected season-specific biomass were explained by week-to-week fluctuations in accumulated heat, rainfall and soil moisture, whereas in Madagascar, weeks with higher soil moisture had higher insect biomass. Overall, our study identifies key drivers of the seasonal distribution of flying insect biomass in a temperate and a tropical climate. This knowledge is key to understanding the spatial and seasonal availability of insects-as well as predicting future scenarios of insect biomass change.

Climate change has significantly impacted vegetation phenology across the globe with vegetation experiencing an advance in the spring green-up phases and a delay in fall senescence. However, some studies from high latitudes and high elevations have instead shown delayed spring phenology, owing to a lack of chilling fulfillment and altered snow cover and photoperiods. Here we use the MODIS satellite-derived view-angle corrected surface reflectance data (MCD43A4) to document the four phenological phases in the high elevations of the Sikkim Himalaya and compared the phenological trends between below-treeline zones and above-treeline zones. This analysis of remotely sensed data for the study period (2001-2017) reveals considerable shifts in the phenology of the Sikkim Himalaya. Advances in the spring start of the season phase (SOS) were more pronounced than delays in the dates for maturity (MAT), senescence (EOS), and advanced dormancy (DOR). The SOS significantly advanced by 21.3 days while the MAT and EOS were delayed by 15.7 days and 6.5 days respectively over the 17-year study period. The DOR showed an advance of 8.2 days over the study period. The region below the treeline showed more pronounced shifts in phenology with respect to an advanced SOS and a delayed EOS and DOR that above treeline. The MAT, however, showed a greater delay in the zone above the treeline than below. Lastly, unlike other studies from high elevations, there is no indication that winter chilling requirements are driving the spring phenology in this region. We discuss four possible explanations for why vegetation phenology in the high elevations of the Eastern Himalaya may exhibit trends independent of chilling requirements and soil moisture due to mediation by snow cover.

Mt. Everest (Qomolangma or Sagarmatha), the highest mount on Earth and located in the central Himalayas between China and Nepal, is characterized by highly concentrated glaciers and diverse landscapes, and is considered to be one of the most sensitive area to climate change. In this paper, we comprehensively synthesized the climate and environmental changes in the Mt. Everest region, including changes in air temperature, precipitation, glaciers and glacial lakes, atmospheric environment, river and lake water quality, and vegetation phenology. Historical temperature reconstruction from ice cores and tree rings revealed the distinct features of 20th century warming in the Mt. Everest region. Meteorological observations further proved that the Mt. Everest region has been experiencing significant warming (approximately 0.33 degrees C/decade) but relatively stable precipitation during 1961-2018 AD. Projected results (during 2006-2099 AD) under different representative concentration pathway scenarios showed a general warming trend in the region, with larger warming occurring in winter than in summer. Meanwhile, the precipitation projections varied spatially with no significant trends over the region. Intensive glacier shrinkage was characterized by decreasing glacier areas, while glacier-fed river runoff increased. Glacial lakes expanded with increasing glacial lake areas and numbers. These findings indicated a clear regional hydrological response to climate warming. Owing to the remote location of Mt. Everest, the present atmospheric environment remained relatively clean; however, long-range transport of atmospheric pollutants from South Asia and West Asia may have substantially influenced the Mt. Everest region, resulting in increasing concentrations of pollutants since the Industrial Revolution. Anthropogenic activities have been shown to influence river and lake water quality in this remote region, especially in the downstream. The end of the vegetation growing season advanced in the northern slope and did not change in southern slope region of the Mt. Everest, and there was no significant change in start date of the growing season in the region. This review will enhance our understanding of climate and environmental changes in the Mt. Everest region under global warming.

The snowbed habitats represent a relevant component of the alpine tundra biome, developing in areas characterized by a long-lasting snow cover. Such areas are particularly sensitive to climate changes, because small variations in air temperature, rain, and snowfall may considerably affect the pedoclimate and plant phenology, which control the soil C and N cycling. Therefore, it is fundamental to identify the most sensitive abiotic and biotic variables affecting soil nutrient cycling. This work was performed at seven permanent snowbed sites belonging to Salicetum herbaceae vegetation community in the northwestern Italian Alps, at elevations between 2,686 and 2,840 m.a.s.l. During a four-year study, we investigated climate, pedoclimate, floristic composition, phenology, and soil C and N dynamics. We found that lower soil water content and earlier melt-out day decreased soil N-NH4 (+), N-NO3 (-), dissolved organic carbon (DOC), dissolved organic nitrogen (DON), total dissolved nitrogen (TDN), microbial nitrogen (Nmicr), microbial carbon (Cmicr), and C:Nmicr ratio. The progression of the phenological stages of Salix herbacea reduced soil N-NH4 (+) and increased DOC. Our results showed that the snow melt-out day, soil temperature, soil water content, and plant phenological stages were the most important factors affecting soil biogeochemical cycles, and they should be taken into account when assessing the effects of climate change in alpine tundra ecosystems, in the framework of long-term ecological research.

The Tibetan Plateau (TP), also known as the world's Third Pole, is underlain by frozen ground and is highly sensitive to climate change. However, it remains unclear how the variations in soil freeze-thaw could affect vegetation dynamics across the TP. In this study, we adopted the latest datasets for vegetation, climate and soil freeze-thaw in the past two decades to explore the possible impacts of changes in soil freeze-thaw on vegetation greenness and phenology on the TP. According to the satellite-based observations, the TP showed an overall greening trend during 2001-2020, and the growing season length increased significantly at a rate of 3.6 days/ 10a, mainly contributed by the advances of the start of the growing season (2.7 days/10a). Based on ridge regression and partial correlation analysis, air temperature and precipitation were found to be the major dominant factors of vegetation dynamics on the TP, and precipitation played a dominant role in the relatively warm-dry southwestern TP where vegetation browning and spring phenology delays were observed. In the relatively cold regions, earlier soil thaw onset generally facilitated spring phenology, and longer soil thaw duration tended to increase the growing season soil moisture content, which could in turn enhance vegetation greenness. In the relatively warm regions, however, earlier thaw onset and longer thaw duration could possibly exacerbate the growing season water stress and limit vegetation growth. The negative impacts were more evident in the regions with unstable and completely degraded permafrost according to the results in the source region of Yellow and Yangtze rivers. Our findings highlight the spatially varying role of soil freeze-thaw changes in vegetation dynamics, which have important implications for the carbon budget of the TP in a warming future climate as frozen ground continues to degrade.

As an important part of the cryosphere, lake ice is a sensitive indicator of climate change. Remote sensing technology can quickly and accurately monitor the process of its formation and decay, among which Moderate Resolution Imaging Spectroradiometer (MODIS) images are the most widely used data in the remote sensing monitoring of lake ice. The reasonable selection of monitoring methods is of great significance to grasp the dynamic process and response to climate change of lake ice. In this study, five commonly used remote sensing monitoring methods of lake ice based on MODIS MOD09GA data, including the single band threshold method (SBT), reflectance difference threshold method (RDT), normalized difference snow index method (NDSI), modified normalized difference snow index method (MNDSI) and lake ice index method (LII), were selected to compare their accuracies in extracting lake ice extent by combining them with four evaluation metrics of accuracy, precision, recall and mean inter over union (MIoU). In addition, the ability of the high-precision LII method for extracting long time series lake ice phenology and its applicability to multiple types of lakes were verified. The results showed that compared with the NDSI method, the other four methods more easily distinguished between lake ice and lake water by setting thresholds. The SBT method and the RDT method had better extraction effects in the freezing process and the melting process, respectively. Compared with the NDSI and MNDSI methods, the LII method showed a significant improvement in lake ice extraction over the entire freeze-thaw cycle, with the smallest mean monitoring error of 1.53% for the percentage of lake ice area in different periods. Meanwhile, the LII method can be used to determine long term lake ice phenology dates and had good performance in extracting lake ice for different types of lakes on the Qinghai-Tibet Plateau with the optimal threshold interval of 0.05 similar to 0.07, which can be used for lake ice monitoring and long-term phenological studies in this region.

Changes in food availability may act as a major mechanism by which global change impacts populations of birds, especially in seasonal environments at high elevations or latitudes. Systematic sampling of invertebrates, which constitute the diet of many bird species during the breeding season, is however largely missing in mountain ecosystems and is overall very rare for soil-dwelling species or stages. Here, we repeatedly sampled earthworms (Lumbricidae), the staple prey of the Ring Ouzel Turdus torquatus, over a whole breeding season in a study area in the Swiss Alps. Our main goal was to finely characterise spatio-temporal patterns of food availability for this declining bird species, in relation to elevation, habitat type and snowmelt stage. In 24 sampling plots, we extracted two soil cores every week for 6-10 weeks and hand-sorted soil invertebrates separately for two 5-cm soil layers. We then analysed the abundance of earthworms in those two layers in relation to various environmental parameters. We show that within our study area, edaphic and topographical parameters are poor predictors of the mean abundance of earthworms over the breeding season. Ground vegetation cover and soil moisture, however, are suitable predictors for the number of earthworms within the soil profile at each sampling time, i.e., of their availability for Ring Ouzels. Moreover, we provide evidence for a clear seasonal peak in earthworm availability, which was more pronounced in open grasslands compared to forested areas and happened later in the season where snow lingered. This study, by improving our understanding of the factors driving food availability for a mountain bird species, provides insights into how shifts in land-use and climate might lead to altered predator-prey interactions.

The accumulation and ablation processes of seasonal snow significantly affect the land surface phenology in a mountainous ecosystem. However, the ability of snow to regulate the alpine land surface phenology in the arid regions is not well described in the context of climate change. The impact of snowpack changes on land surface phenology and its driving factors were investigated in the Tianshan Mountains using the land surface phenology metrics derived from satellited products and a snow dataset from downscaled regional climate model simulations covering the period from 1983 to 2015. The results demonstrated that the annual mean start of growing season (SOS) and length of growing season (LOS) experienced a significant (p < 0.05) decrease and increase with a rate of -2.45 days/decade and 2.98 days/decade, respectively. The significantly advanced SOS and increased LOS were mainly seen in the Western Tianshan Mountains and Ili Valley regions with elevations from 2500 to 3500 m a.s.l and below 3000 m a.s.l, respectively. During the early spring, the significant decline in snow cover fraction (SCF) could advance the SOS. In contrast, snowmelt amount and annual maximum snow water equivalent (SWE) have an almost equally substantial positive correlation with annual maximum vegetation greenness. In particular, the SOS of grassland was the most sensitive to variations of snow cover fraction during early spring than that of other vegetation types, and their strong relationship was mainly located at elevations from 1500 to 2500 m a.s.l. Its greenness was significantly controlled by the annual maximum snow water equivalent in all elevation bands. Both decreased SCF and increased temperature in the early spring caused a significant advance of the SOS, consequently prolonging the LOS. Meanwhile, more SWE and snowmelt amount could significantly promote vegetation greenness by regulating the soil moisture. The results can improve the understanding of the snow ecosystem services in the alpine regions under climate change.