Spring Vegetation Phenology Research Articles

Accelerating urban warming effects on the spring phenology in cold cities but decelerating in warm cities

Urban is regarded as the ideal natural laboratory for predicting vegetation growth response to future warming, as urban warming promotes the growth of urban vegetation and advances spring phenology. However, the effects of daytime and nighttime warming on the spring phenology of natural vegetation remain unclear under global warming. Here, we used urbanization intensity (UI) as a proxy for future warming, then investigated the start dates of the growing season (SOS) response to daytime and nighttime warming across different levels of UI. We found both nighttime and daytime temperature sensitivities increased significantly from rural to urban centers in cold cities, decreasing in warm cities. It indicated that the advancement in spring phenology of urban vegetation accelerates along with UI in cold cities but slows down in warm cities. Because in cold cities, urban warming and increased humidity accelerate vegetation growth, while in warm cities urban warming and decreased humidity decelerate growth. Therefore, in future we should consider not only the asymmetrical responses of urban vegetation spring phenology to daytime and nighttime warming, but also the disparate responses in different background climate regions under future warming.

Interactions of climate, topography, and soil factors can enhance the effect of a single factor on spring phenology in the arid/semi-arid grasslands of China

Understanding the interactions among climate, topography, and soil factors on vegetation spring phenology can help reveal the feedback mechanisms of vegetation ecosystems in response to environmental conditions and climate change. Nonetheless, the coupling effects of these environmental elements on vegetation start of season (SOS) are still poorly understood. We took Xinjiang Province, a typical arid/semi-arid region, as the research area and quantitatively analyzed the explanatory power and interactions of climate, topography, and soil factors on grassland SOS through the geographical detector model based on the data extracted by Timesat 3.3 software. The results showed that: (1) From 2001 to 2020, early SOS predominantly occurred from 75 to 105 days in Northern Xinjiang. While later SOS was widespread in Southern Xinjiang from 105 to 135 days. The area of the SOS advanced region was larger than that of the delayed region; (2) There was obvious spatial hierarchical heterogeneity between SOS and climate, topography, and soil factors. Altitude, maximum temperature, and soil type were the primary drivers of SOS changes in the study area (P < 0.001); (3) The interactions among environmental factors strengthened the explanatory power of individual factors, either through mutual reinforcement or non-linear effects. The interactions between elevation and climate factors were particularly significant, with an explanatory power above 0.3. This study highlighted the importance of the coupling effects of environmental variables on SOS and suggested that drives should be considered more comprehensively in future analyses.

Matching Spring Phenology Indicators in Ground Observations and Remote-Sensing Metrics

Accurate monitoring of leaf phenology, from individual trees to entire ecosystems, is vital for understanding and modeling forest carbon and water cycles, as well as assessing climate change impact. However, the accuracy of many remote-sensing phenological products remains difficult to directly corroborate using ground-based monitoring, owing to variations in the observed indicators and the scales used. This limitation hampers the practical implementation of remote-sensing phenological metrics. In our study, the start of growing season (SOS) from 2016 to 2021 was estimated for the continental USA using Sentinel-2 images. The results were then matched with several ground-based spring vegetation phenology metrics obtained by the USA National Phenology Network (USA-NPN). In this study, we focused on the relationships between the leaf-unfolding degree (LUD), the SOS, and the factors that drive these measures. Our results revealed that: (1) the ground-based leaves and increasing leaf size stages were significantly correlated with the SOS; (2) with the closest match being observed for a leaf spread of 13%; (2) the relationship between the SOS and LUD varied according to the species and ecoregion, and the pre-season cumulative radiation was found to be the main factor affecting the degree of matching between the ground observations and the metrics derived from the Sentinel-2 data. Our investigations provide a ground-based spring phenology metric that can be used to verify or evaluate remote-sensing spring phenology products and will help to improve the accuracy of remote-sensing phenology metrics.

Asymmetrical Impact of Daytime and Nighttime Warming on the Interannual Variation of Urban Spring Vegetation Phenology

AbstractUrban warming significantly advances spring vegetation phenology. However, the potential effect of daytime and nighttime warming on the start of the urban vegetation growing season (SOS) remains to be determined. Here, we characterized the interannual response of SOS to daytime and nighttime warming from 2003 to 2020 using remotely sensed phenological observations across cities in the Northern Hemisphere (&gt;30°N). We implemented the partial correlation analysis and the process‐based phenology model to quantify the effects of daytime and nighttime warming on vegetation. We found that either daytime or nighttime warming can promote an earlier urban spring SOS for Northern Hemisphere cities, while the phenological response varies across cities. Additionally, the response of SOS to daytime and nighttime urban warming (ST, expressed in advance days of SOS per °C warming) offset each other at an average rate of 0.08 days/°C per decade. Our results suggest that daytime warming predominates the temporal variation of SOS for high‐latitude cities, whereas nighttime warming is the primary driver of SOS change in low‐latitude cities. By revealing the effect and contributions of daytime and nighttime warming on the urban SOS, our results highlight the importance of considering daytime and nighttime temperatures separately in the response of vegetation phenology to urban thermal warming and climate variability.

Co-influence of the start of thermal growing season and precipitation on vegetation spring green-up on the Tibetan Plateau

The climate in the Tibetan Plateau (TP) has undergone significant change in recent decades, mainly in thermal and water conditions, which plays a crucial role in phenological changes in vegetation spring phenology. However, how the start of the thermal growing season (SOS-T) and the start of the rainy season (SORS) as key climatic factors affect vegetation green-up remains unclear. Given that these factors characterize thermal and water conditions required for vegetation green-up, this study investigated changes in the SOS-T and SORS from 1961 to 2022, using observation-based datasets with long time series. We found that the SOS-T and SORS have advanced across the TP in 1961–2022 and have shown a spatial pattern of advancement in the east and delay in the west in 2000–2022. Further, the co-effect of temperature and precipitation change on the start of vegetation growing season (SOS-V) in 2000–2022 was observed. Averaged across TP, the SOS-V had an early onset of 1.3 d per decade during 2000–2022, corresponding to advanced SOS-T and SORS. Regionally, the SOS-V generally occurred nearly at the same time as the SOS-T in the high-altitude meadow region. A substantial delay in the SOS-V relative to the SOS-T was observed in the desert, shrub, grassland and forest regions and generally kept pace with the SORS. Furthermore, for 50% of the vegetated regions on the TP, inter-annual variation in the delay in the SOS-V relative to the SOS-T was dominated by precipitation change, which was profound in warm-climate regions. This study highlights the co-regulation of precipitation and temperature change in the SOS-V in different vegetation cover regions in the TP, offering a scientific foundation for comprehending the impact of climate change and prospects for vegetation phenology on the TP.

The Advancement in Spring Vegetation Phenology in the Northern Hemisphere Will Reverse After 2060 Under Future Moderate Warming Scenarios

AbstractGlobal warming has largely advanced spring vegetation phenology, which has subsequently affected terrestrial carbon and water cycles. However, further shifts in vegetation phenology under future climate change remain unclear. We estimated the start of the growing season (SOS) by applying multiple extraction methods based on the NDVI3g data set, and then parameterized and evaluated 11 spring vegetation phenology models that included chilling, forcing, and the photoperiod. Based on scenario data from three Shared Socioeconomic Pathways (SSP126, SSP245, and SSP585) derived from eight climate models, future vegetation phenology was predicted using the phenology models. Results showed that all the phenology models performed better than the NULL model (mean of the SOS), with the performance of one‐phase models broadly matching that of two‐phase models, although the best models varied by vegetation type. The spatial pattern of simulated SOS was similar among the models, and it explained &gt;75% of the variation. Based on the mean predicted SOS, we found that spring vegetation phenology will continue to advance under strong warming conditions (SSP245 and SSP585), but that the trend of advance will reverse at around 2060 under the SSP126 scenario. The continued trend in SOS advance is likely related to rapid forcing fulfillment under stronger warming conditions. However, under moderate warming, chilling might be reduced and it might require longer to compensate for higher forcing, which ultimately would result in SOS delay. Our findings highlight that trends will likely change under different warming conditions, potentially causing widespread impact on species interaction, biodiversity, and ecosystem function.

Response of spring vegetation phenology to soil freeze–thaw state in the Northern Hemisphere from 2016 to 2022

IntroductionThe research on spring vegetation phenology is crucial to the investigation of terrestrial ecosystems and climate change. Changes in the soil freeze–thaw (F/T) lead to variations in soil moisture, directly impacting vegetation activity. The start of the season (SOS) is the initial and important phenophase for vegetation activity, and thus, this highlights the need to understand the response of spring vegetation phenology to soil F/T state.MethodsThis study first comprehensively investigates the consistency of the SOS and three soil F/T state indexes, i.e., the start day of the F/T state (SFT), the end day of the F/T state (EFT), and the length of days of the F/T state (LFT) via satellite data source.ResultsResults reveal that: (1) All 3 F/T state indexes impact SOS values, and the EFT outperforms others. The correlation coefficients between EFT and SOS gain around 3.07%. (2) A temporal overlap between SOS and EFT occurs in May, suggesting that parts of the plants begin active growth before average temperatures reach above 0°. (3) Small differences of SOS and EFT exist between savannas, and croplands, with an average difference of less than 10 days; in contrast, the largest differences occur in broadleaf evergreen forests. The results can fill the knowledge gap on the response of spring vegetation phenology to soil F/T state, and help to investigate the reasons for the nonlinear dynamics of SOS under global warming.

Urbanization effects on the spatial patterns of spring vegetation phenology depend on the climatic background

Cities have been considered ideal surrogates for evaluating ecological responses to climate warming. Although research has revealed that the urban heat island effect is not the only determinant that drives the rural-urban difference in spring phenology, limited attempts further explore the effect of complex interactions between urbanization and climates on the start of the season (SOS). Here, we employed the percentage of impervious surface area as an indicator of urbanization levels, incorporating the urban heat island (UHI) effect and climates to decipher the multiple effects on the temporal shift in SOS. Our results suggest that urbanization, the UHI effect, and climates jointly drive the phenological timing in cities. The SOS is highly linearly correlated with urbanization levels and UHI effects (p<0.001) in the zones with warm and humid climates, whereas relatively warmer, cooler, or arid climates break down the linearity. Geographically, the SOS is north-south symmetrical for the rural-urban ecosystem at the national scale, which initiates at the mid-latitudes (around 30 °N, 67.58 DOY ± 2.23 days) first and then towards the low (around 20 °N, 105.25 DOY ± 1.31 days) and high-latitudes (45 °N, 123.01 DOY ± 1.45 days). Chilling accumulation and spring temperature jointly contribute to this phenomenon. As the UHI effect is similar to the projected global warming in the future, understanding the phenological responses to urbanization in various climates is insightful for evaluating the impact of future warming on plants' phenological behavior in the global ecosystem.

Forage senescence and disease influence elk pregnancy across the Greater Yellowstone Ecosystem

AbstractFor various temperate ungulate species, recent research has highlighted the potential for spring vegetation phenology (“green‐up”) to influence individual condition, with purported benefits to population productivity. However, few studies have been able to measure the benefit on vital rates directly, and fewer still have investigated the comparative influence of other phenological periods on ungulate vital rates. In this study, we tracked phenological changes throughout the duration of the growing season and examined how their timing affected the probability of pregnancy in an ungulate population. We did this for elk (Cervus canadensis) across the Greater Yellowstone Ecosystem (GYE) by sampling 1106 adult females in winter at 25 sites over a 13‐year period and assessing sources of variation in pregnancy using a Bayesian hierarchical model. Pregnancy rates were generally high across the GYE (82.4%), and the primary influences on probability of pregnancy were the timing of vegetation senescence (“brown‐down”) in autumn and exposure to the reproductive disease brucellosis. Earlier forage brown‐down in fall negatively influenced the probability of pregnancy of elk aged 6–9 years by an estimated 17.2% within the range (ca. 32 days) of observed brown‐down end dates. While summer habitat quality has been inferred to influence elk pregnancy previously, our findings specify the key influence of foraging conditions later in the seasonal cycle, immediately before the breeding season. The reproductive disease brucellosis was also an important factor, reducing the probability of pregnancy by 12.4% in elk in the 6‐ to 9‐year age class. Because pregnancy was tested before most disease‐induced abortions occur, the apparent mechanism for this effect is a prolonged reduction in fertility beyond the period of initial exposure in which fetal mortality is typically expected. Our results prompt greater scrutiny of the combined effects of late‐season phenology and disease on reproductive rates and population productivity in temperate ungulates.

Unraveling Effect of Snow Cover on Spring Vegetation Phenology across Different Vegetation Types in Northeast China

Snow cover has significantly changed due to global warming in recent decades, causing large changes in the vegetation ecosystem. However, the impact of snow cover changes on the spring phenology of different vegetation types in Northeast China remains unclear. In this study, we investigated the response of the start of the growing season (SOS) to different snow cover indicators using partial correlation analysis and stepwise regression analysis in Northeast China from 1982 to 2015 based on multiple remote sensing datasets. Furthermore, we revealed the underlying mechanisms using a structural equation model. The results show that decreased snow cover days (SCD) and an advanced snow cover end date (SCED) led to an advanced SOS in forests. Conversely, an increased SCD and a delayed SCED led to an advanced SOS in grasslands. The trends of SCD and SCED did not exhibit significant changes in rainfed cropland. The maximum snow water equivalent (SWEmax) increased in most areas. However, the proportion of the correlation between SWEmax and SOS was small. The impact of snow cover changes on the SOS varied across different vegetation types. Snow cover indicators mainly exhibited positive correlations with the SOS of forests, including deciduous broadleaf forests and deciduous coniferous forests, with positive and negative correlations of 18.61% and 2.58%, respectively. However, snow cover indicators mainly exhibited negative correlations in the SOS of grasslands and rainfed croplands, exhibiting positive and negative correlations of 4.87% and 13.06%, respectively. Snow cover impacted the SOS through the “temperature effect” in deciduous broadleaf forests, deciduous coniferous forests, and rainfed croplands, while it affected SOS through the “moisture effect” in grasslands. These results provide an enhanced understanding of the differences in snow cover changes affecting SOS in different vegetation types under climate change in Northeast China.

The Sensitivity of Green-Up Dates to Different Temperature Parameters in the Mongolian Plateau Grasslands

The rise in global average surface temperature has promoted the advancement of spring vegetation phenology. However, the response of spring vegetation phenology to different temperature parameters varies. The Mongolian Plateau, one of the largest grasslands in the world, has green-up dates (GUDs) with unclear sensitivity to different temperature parameters. To address this issue, we investigated the responses of GUDs to different temperature parameters in the Mongolian Plateau grasslands. The results show that GUDs responded significantly differently to changes in near-surface temperature (TMP), near-surface temperature maximum (TMX), near-surface temperature minimum (TMN), and diurnal temperature range (DTR). GUDs advanced as TMP, TMX, and TMN increased, with TMN having a more significant effect, whereas increases in DTR inhibited the advancement of GUDs. GUDs were more sensitive to TMX and TMN than to TMP. The sensitivity of GUDs to DTR showed an increasing trend from 1982 to 2015 and showed this parameter’s great importance to GUDs. Our results also show that the spatial and temporal distributions of temperature sensitivity are only related to temperature conditions in climatic zones instead of whether they are arid.

Cropland expansion delays vegetation spring phenology according to satellite and in-situ observations

The global climate change-induced advanced spring green-up dates (GUDs) of vegetation in the past decades have been well documented. However, anthropogenic effects on GUDs are still unclear, and the impacts of widespread cropland expansion on GUDs are rarely quantified. Here, we examine the differences in GUDs between agroecosystems and natural ecosystems using both satellite and in-situ observations across China’s ecosystems with a latitude ≥ 30°N and explore the potential effects of cropland expansion on vegetation spring phenology. We find that agroecosystems had significantly later GUDs than adjacent natural ecosystems according to satellite observations, with a delay of 22.26 ± 16.32 (Mean ± 1STD) days and 18.11 ± 11.75 days compared with woodland and grassland ecosystems, respectively. The later GUDs for agroecosystems is more distinct in the Northeast China Plain and Xinjiang Oasis region (>30 days), where land reclamation was remarkable. We also find a distinct delayed GUD trend (> 5 day/yr, p < 0.001) during 2001–2014 in a cropland expansion region in Xinjiang Province, which is much higher than the usual advancement of GUDs due to warming (usually ≤ 1 day/yr). In-situ and satellite observations of delayed GUDs agree better in agroecosystems than in forest and grassland ecosystems. More attention is needed to better understand the important role of cropland expansion in driving inter-annual change of vegetation spring phenology in addition to climate change, and integration of realistic crop green-up timing into climate models is also needed for accurate climate simulations.

Effects of Snow Cover on Spring Vegetation Phenology Vary With Temperature Gradient Across the Pan‐Arctic

AbstractExtensive and complex changes in spring vegetation phenology have occurred in the Pan‐Arctic over the last several decades. However, the role of snow cover at the start of the growing season (SOS) under different climatic conditions remains unclear. Therefore, we compare the effects of four snow indicators on SOS from 1982 to 2015 based on long‐term remote sensing data and found that snow cover end date (SCED) is the main snow indicator affecting SOS, with SOS advancing 0.56 days for each 1‐day advance in SCED, explaining 12%–90% of SOS variability in 63% of the Pan‐Arctic region. The results also demonstrate that SCED is the dominant factor on SOS in 13% of the Pan‐Arctic region and the effects of SCED on SOS vary with temperature gradient rather than precipitation gradient. In cold areas, the positive effect of SCED on SOS diminished with increasing temperature, while in warm areas, the positive effect of SCED on SOS increased with increasing temperature. As the climate warms, the impact of SCED on SOS is expected to weaken in cold areas and increase in warm areas. The findings have crucial implications for understanding future vegetation phenological responses to climate change across the Pan‐Arctic.

Effects of Climate Extremes on Spring Phenology of Temperate Vegetation in China

The response of vegetation spring phenology to climate warming has received extensive attention. However, there are few studies on the response of vegetation spring phenology to extreme climate events. In this study, we determined the start of the growing season (SOS) for three vegetation types in temperate China from 1982 to 2015 using the Global Inventory Modeling and Mapping Study’s third-generation normalized difference vegetation index and estimated 25 extreme climate events. We analyzed the temporal trends of the SOS and extreme climate events and quantified the relationships between the SOS and extreme climate events using all-subsets regression methods. We found that the SOS was significantly advanced, with an average rate of 0.97 days per decade in China over the study period. Interestingly, we found that the SOS was mainly associated with temperature extremes rather than extreme precipitation events. The SOS was mainly influenced by the frost days (FD, r = 0.83) and mean daily minimum temperature (TMINMEAN, r = 0.34) for all three vegetation types. However, the dominant influencing factors were vegetation-type-specific. For mixed forests, the SOS was most influenced by TMINMEAN (r = 0.32), while for grasslands and barren or sparsely vegetated land, the SOS was most influenced by FD (r &gt; 0.8). Our results show that spring phenology was substantially affected by extreme climate events but mainly by extreme temperature events rather than precipitation events, and that low temperature extremes likely drive spring phenology.

A stronger advance of urban spring vegetation phenology narrows vegetation productivity difference between urban settings and natural environments

Climate change is posing dramatic effects on terrestrial vegetation dynamics. The links between vegetation phenology or vegetation activity (growth) and climate change have been widely reported, yet, less is known about the impacts of phenological shifts on vegetation growth. Urban settings characterized by urban heat island and CO2 dome are often used as ideal natural laboratories to understand how vegetation responds to global climate change. Here we assessed the impacts of phenology changes on vegetation growth in China using satellite phenology metrics and gross primary production (GPP) data from 2003 to 2018 and urban-natural contrast analysis. Compared with natural environments, phenological metrics (e.g., start/end of growing season (SOS/EOS), and the length of growing season (GSL), etc.) were observed to change more dramatically in urban environments. Furthermore, we found that GPP in both settings increased over time but with a higher increment in the urban environments, and the urban-natural vegetation productivity gap had been diminishing at a rate of 16.9 ± 6.76 g C m−2 y−1. The narrowing of the urban-natural GPP difference over time can be attributed to a more advanced SOS and extended GSL in urban settings than their natural counterparts, particularly SOS shift. These findings suggested that the distinct urban phenological shifts would become increasingly important in offsetting the loss of vegetation productivity induced by urbanization.

Assessment of Climatic Impact on Vegetation Spring Phenology in Northern China

Spring phenology is often considered the start of season (SOS) for vegetation, which can affect ecosystem photosynthesis, respiration, and evapotranspiration. However, the long-run variation of SOS remains unclear at the regional scale. In this research, the long-term variation of SOS in northern China was explored by using the updated normalized difference vegetation index and monthly climatic data during 1982–2014. Furthermore, the relative importance of climatic factors on SOS was analyzed through partial correlation and multivariate regression methods. The main results were as follows: (1) average SOS largely ranged between day 120 and 165 of the year and varied widely for different vegetation types; (2) SOS during 1982–2014 showed an advancing trend, but it appeared to be reversed after 1998; (3) preseason minimum temperature was a dominant factor controlling SOS in most pixels in northern China, followed by maximum temperature (Tmx). However, impacts of radiation and precipitation on the trend of SOS primarily depended on vegetation types; (4) impacts of climatic factors on SOS declined in the period after 1998, especially for Tmx. These findings provide important support for modeling vegetation phenology and growth in northern China.

Soil moisture determines the effects of climate warming on spring phenology in grasslands

Spring vegetation phenology is highly sensitive to global change. However, the effects of ongoing climate warming and N deposition on grassland spring phenology and how abiotic and biotic factors modulate such effects remain unclear. Here, we conducted a factorial field experiment of warming and N addition in three types of grasslands with varying aridity indices (0.20–0.39) in Inner Mongolia, China. Our results showed that warming and the combination of warming plus N addition had similar effects on start of season (SOS). These treatments delayed SOS by 3–5 weeks in low-, moderate and high-aridity grasslands in both wet (2018) and dry (2019) years, except that they advanced SOS by ∼1 week in low-aridity grassland in the wet year. N addition alone slightly advanced or delayed SOS by 2–5 days depending on the grassland type. The magnitude and direction of SOS response to warming and warming plus N addition were closely and linearly correlated to grassland soil moisture, but not to air temperature or soil N availability. Warming-induced reduction in soil moisture drove SOS by affecting species richness and/or functional group composition. By contrast, N addition–induced changes in species richness and functional group composition did not alter the SOS. These combined results indicate that temperature and soil water availability are primary factors regulating SOS in semiarid grasslands. Our findings suggest that annual variation and spatial distribution in soil moisture should be considered in future studies of climate warming and environmental effects on grassland phenology.

Urban warming increases the temperature sensitivity of spring vegetation phenology at 292 cities across China

Urban spring phenology changes governed by multiple biological and environmental factors significantly impact urban ecosystem functions and services. However, the temporal changes in spring phenology (i.e., the start of the vegetation growing season, SOS) and the magnitude of SOS sensitivity to temperature in urban settings are not well understood compared with natural ecosystems. Therefore, we explored warming impacts on SOS across 292 rural and urban areas from 2001 to 2016. We found that warming occurred in 79.9% of urban areas and 61.3% of rural areas. This warming advanced SOS in 78.3% of the urban settings and 72.8% of the rural areas. The accelerated rate of SOS in urban settings was significantly higher (−0.52 ± 0.86 days/year) than in rural areas (−0.09 ± 0.69 days/year). Moreover, SOS was significantly more sensitive to warming in urban areas (−2.86 ± 3.57 days/°C) than in rural areas (−1.57 ± 3.09 days/°C), driven by urban-rural differences in climatic (precipitation, temperature, and warming speed) and vegetation factors. Precipitation contributed the most had the highest relative importance for controlling SOS, at 45% and 63% for urban and rural areas, respectively. These findings provide a new understanding of the impacts of urbanization and climate change on vegetation phenology. Moreover, our results have implications for urban environment impacts on ecosystems and human health.

Earlier snowmelt predominates advanced spring vegetation greenup in Alaska

Snow is considered a vital component in the northern climate system, however, our understanding of the impacts of snowmelt on spring phenological shifts is still limited for high-latitude ecosystems. In this study, we analyzed the start of growing season (SOS) and its response to the process of snowmelt over 2000–2019 using multiple ground observations, satellite data products, and climate datasets in Alaska and part of Canada Yukon among five ecoregions. We found that the earlier snowmelt resulting from warming spring dominates the advanced spring vegetation phenology in the region. Spring vegetation greenup follows the start of snowmelt (SOM). During 2000–2019, the SOM and SOS advanced in a similar spatial pattern across the ecoregions, and SOS experienced further advancement than SOM. On average, SOS advanced about 0.49 days per day of SOM advancement. The impacts of snowmelt on vegetation phenology are largely driven by the snowmelt-induced synergistic changes in soil temperature and soil water content. As snowmelt starts, the infiltration of snowmelt water and insulation of the remaining snow cover stimulate the vegetation activities below the snow. The responses of SOS to the snowmelt phenology varied among the different ecoregions are associated with the varied climate backgrounds and vegetation types. Greater SOS and SOM advancements were found in the taiga-tundra ecotone, while lower changes were detected over the tundra. This study suggests that the snow cover and snowmelt phenology should be considered to better understand the vegetation seasonality under climate change in the high latitudes.

Vegetation green-up date is more sensitive to permafrost degradation than climate change in spring across the northern permafrost region.

Global climate change substantially influences vegetation spring phenology, that is, green-up date (GUD), in the northern permafrost region. Changes in GUD regulate ecosystem carbon uptake, further feeding back to local and regional climate systems. Extant studies mainly focused on the direct effects of climate factors, such as temperature, precipitation, and insolation; however, the responses of GUD to permafrost degradation caused by warming (i.e., indirect effects) remain elusive yet. In this study, we examined the impacts of permafrost degradation on GUD by analyzing the long-term trend of satellite-based GUD in relation to permafrost degradation measured by the start of thaw (SOT) and active layer thickness (ALT). We found significant trends of advancing GUD, SOT, and thickening ALT (p<0.05), with a spatially averaged slope of -2.1days decade-1 , -4.1days decade-1 , and +1.1cm decade-1 , respectively. Using partial correlation analyses, we found more than half of the regions with significantly negative correlations between spring temperature and GUD became nonsignificant after considering permafrost degradation. GUD exhibits dominant-positive (37.6% vs. 0.6%) and dominant-negative (1.8% vs. 35.1%) responses to SOT and ALT, respectively. Earlier SOT and thicker ALT would enhance soil water availability, thus alleviating water stress for vegetation green-up. Based on sensitivity analyses, permafrost degradation was the dominant factor controlling GUD variations in 41.7% of the regions, whereas only 19.6% of the regions were dominated by other climatic factors (i.e., temperature, precipitation, and insolation). Our results indicate that GUDs were more sensitive to permafrost degradation than direct climate change in spring among different vegetation types, especially in high latitudes. This study reveals the significant impacts of permafrost degradation on vegetation GUD and highlights the importance of permafrost status in better understanding spring phenological responses to future climate change.