Changes in timing of seasonal peak photosynthetic activity in northern ecosystems

Earlier peak photosynthesis timing potentially escalates global wildfires

More intense fire weather due to climate change is implicated as a key driver of recent extreme wildfire events. As fuel stock, the role of vegetation and its phenology changes in wildfire dynamics, however is not fully appreciated. Using long-term satellite-based burned areas and photosynthesis observations, we reveal that an earlier peak photosynthesis timing (PPT) potentially acts to escalate subsequent wildfires, with an increase in the global average burned fraction of 0.021% (∼2.20 Mha) for every additional day of PPT advancement. Satellite observations and Earth System modeling consistently show that this fire escalation is likely due to intensified drought conditions and increased fuel availability associated with the climate feedback arising from earlier PPT. Current fire-enabled dynamic global vegetation models can reproduce the observed negative correlation between PPT and burned area but underestimate the strength of the relationship notably. Given the continued PPT advancement owing to climate change, the bioclimatic effects of vegetation phenology change suggest a potentially pervasive upward pressure on future wildfires.

Consistent time allocation fraction to vegetation green-up versus senescence across northern ecosystems despite recent climate change

Extended growing season lengths under climatic warming suggest increased time for plant growth. However, research has focused on climatic impacts to the timing or duration of distinct phenological events. Comparatively little is known about impacts to the relative time allocation to distinct phenological events, for example, the proportion of time dedicated to leaf growth versus senescence. We use multiple satellite and ground-based observations to show that, despite recent climate change during 2001 to 2020, the ratio of time allocated to vegetation green-up over senescence has remained stable [1.27 (± 0.92)] across more than 83% of northern ecosystems. This stability is independent of changes in growing season lengths and is caused by widespread positive relationships among vegetation phenological events; longer vegetation green-up results in longer vegetation senescence. These empirical observations were also partly reproduced by 13 dynamic global vegetation models. Our work demonstrates an intrinsic biotic control to vegetation phenology that could explain the timing of vegetation senescence under climate change.

Why do avian responses to change in Arctic green-up vary?

Global climate change has altered the timing of seasonal events (i.e., phenology) for a diverse range of biota. Within and among species, however, the degree to which alterations in phenology match climate variability differ substantially. To better understand factors driving these differences, we evaluated variation in timing of nesting of eight Arctic-breeding shorebird species at 18 sites over a 23-year period. We used the Normalized Difference Vegetation Index as a proxy to determine the start of spring (SOS) growing season and quantified relationships between SOS and nest initiation dates as a measure of phenological responsiveness. Among species, we tested four life history traits (migration distance, seasonal timing of breeding, female body mass, expected female reproductive effort) as species-level predictors of responsiveness. For one species (Semipalmated Sandpiper), we also evaluated whether responsiveness varied across sites. Although no species in our study completely tracked annual variation in SOS, phenological responses were strongest for Western Sandpipers, Pectoral Sandpipers, and Red Phalaropes. Migration distance was the strongest additional predictor of responsiveness, with longer-distance migrant species generally tracking variation in SOS more closely than species that migrate shorter distances. Semipalmated Sandpipers are a widely distributed species, but adjustments in timing of nesting relative to variability in SOS did not vary across sites, suggesting that different breeding populations of this species were equally responsive to climate cues despite differing migration strategies. Our results unexpectedly show that long-distance migrants are more sensitive to local environmental conditions, which may help them to adapt to ongoing changes in climate.

Vegetation canopy structure mediates the response of gross primary production to environmental drivers across multiple temporal scales

Gross primary production (GPP) is a critical component of the global carbon cycle and plays a significant role in the terrestrial carbon budget. The impact of environmental factors on GPP can occur through both direct (by influencing photosynthetic efficiency) and indirect (through the modulation of vegetation structure) pathways, but the extent to which these mechanisms contribute has been seldom quantified. In this study, we used structural equation modeling and observations from the FLUXNET network to investigate the direct and indirect effects of environmental factors on terrestrial ecosystem GPP at multiple temporal scales. We found that canopy structure, represented by leaf area index (LAI), is a crucial intermediate factor in the GPP response to environmental drivers. Environmental factors affect GPP indirectly by altering canopy structure, and the relative proportion of indirect effects decreased with increasing LAI. The study also identified different effects of environmental factors on GPP across time scales. At the half-hourly time scale, radiation was the primary driver of GPP. In contrast, the influences of temperature and vapor pressure deficit took on greater prominence at longer time scales. About half of the total effect of temperature on GPP was indirect through the regulation of canopy structure, and the indirect effect increased with increasing time scale (GPPNT-based models: 0.135 (half-hourly) vs. 0.171 (daily) vs. 0.189 (weekly) vs. 0.217 (monthly); GPPDT-based models: 0.139 vs. 0.170 vs. 0.187 vs. 0.215; all values were reported in gC m-2 d-1 °C-1, P < 0.001); while the indirect effect of radiation on GPP was comparatively lower, accounting for less than a quarter of the total effect. Furthermore, we observed a direct, negative-to-positive impact of precipitation on GPP across timescales. These findings provide crucial information on the interplay between environmental factors and LAI on GPP and enable a deeper understanding of the driving mechanisms of GPP.

Physiological and phenological adjustments in water and carbon fluxes of Aleppo pine forests under contrasting climates in the Eastern Mediterranean

The ability of plants to adjust to the adverse effects of climate change is important for their survival and for their contribution to the global carbon cycle. This is particularly true in the Mediterranean region, which is among the regions that are most vulnerable to climate change. Here, we carried out a 2-year comparative ecophysiological study of ecosystem function in two similar Eastern Mediterranean forests of the same tree species (Pinus halepensis Mill.) under mild (Sani, Greece) and extreme (Yatir, Israel) climatic conditions. The partial effects of key environmental variables, including radiation, vapor pressure deficit, air temperature and soil moisture (Rg, D, T and soil water content (SWC), respectively), on the ecosystems' CO2 and water vapor fluxes were estimated using generalized additive models (GAMs). The results showed a large adjustment between sites in the seasonal patterns of both carbon and water fluxes and in the time and duration of the optimal period (defined here as the time when fluxes were within 85% of the seasonal maximum). The GAM analysis indicated that the main factor influencing the seasonal patterns was SWC, while T and D had significant but milder effects. During the respective optimal periods, the two ecosystems showed strong similarities in the fluxes' responses to the measured environmental variables, indicating similarity in their underlying physiological characteristics. The results indicate that Aleppo pine forests have a strong phenotypic adjustment potential to cope with increasing environmental stresses. This, in turn, will help their survival and their continued contribution to the terrestrial carbon sink in the face of climate change in this region.

Diminishing carryover benefits of earlier spring vegetation growth

Spring vegetation growth can benefit summer growth by increasing foliage area and carbon sequestration potential, or impair it by consuming additional resources needed for sustaining subsequent growth. However, the prevalent driving mechanism and its temporal changes remain unknown. Using satellite observations and long-term atmospheric CO2 records, here we show a weakening trend of the linkage between spring and summer vegetation growth/productivity in the Northern Hemisphere during 1982-2021. This weakening is driven by warmer and more extreme hot weather that becomes unfavourable for peak-season growth, shifting peak plant functioning away from earlier periods. This is further exacerbated by seasonally growing ecosystem water stress due to reduced water supply and enhanced water demand. Our finding suggests that beneficial carryover effects of spring growth on summer growth are diminishing or even reversing, acting as an early warning sign of the ongoing shift of climatic effects from stimulating to suppressing plant photosynthesis during the early to peak seasons.

Drivers of contemporary and future changes in Arctic seasonal transition dates for a tundra site in coastal Greenland

Climate change has had a significant impact on the seasonal transition dates of Arctic tundra ecosystems, causing diverse variations between distinct land surface classes. However, the combined effect of multiple controls as well as their individual effects on these dates remains unclear at various scales and across diverse land surface classes. Here we quantified spatiotemporal variations of three seasonal transition dates (start of spring, maximum normalized difference vegetation index (NDVImax ) day, end of fall) for five dominating land surface classes in the ice-free Greenland. Using a distributed snow model, structural equation modeling, and a random forest model, based on ground observations and remote sensing data, we assessed the indirect and direct effects of climate, snow, and terrain on seasonal transition dates. We then presented new projections of likely changes in seasonal transition dates under six future climate scenarios. The coupled climate, snow cover, and terrain conditions explained up to 61% of seasonal transition dates across different land surface classes. Snow ending day played a crucial role in the start of spring and timing of NDVImax . A warmer June and a decline in wind could advance the NDVImax day. Increased precipitation and temperature during July-August are the most important for delaying the end of fall. We projected that a 1-4.5°C increase in temperature and a 5%-20% increase in precipitation would lengthen the spring-to-fall period for all five land surface classes by 2050, thus the current order of spring-to-fall lengths for the five land surface classes could undergo notable changes. Tall shrubs and fens would have a longer spring-to-fall period under the warmest and wettest scenario, suggesting a competitive advantage for these vegetation communities. This study's results illustrate controls on seasonal transition dates and portend potential changes in vegetation composition in the Arctic under climate change.

Climatic limitations on grassland photosynthesis over the Tibetan Plateau shifted from temperature to water

Plant photosynthesis plays an essential role in regulating the global carbon cycle. Therefore, it is essential to understand the limitations imposed by climate on plant photosynthesis to comprehend the impacts of climate change on land carbon dynamics. In this study, taking gross primary productivity as a direct representation of photosynthesis, we employed a light use efficiency model (i.e., the revised EC-LUE) and factorial analysis method to quantify the spatiotemporal variation of temperature- and water-limitations on plant photosynthesis over the Tibetan Plateau (TP) grasslands during growing season (May to October) in 1983-2018. Results revealed a clear spatiotemporal pattern of the temperature- and water-limitations: temperature is the primary climatic limiting factor in the eastern TP, while water is the primary climatic limiting factor in the western TP; the water- and temperature-limitations prevail in summer and spring/autumn, respectively. The water- and temperature-limitations intensified and alleviated, respectively, during 1983 through 2018. There also was a widespread shift from temperature-limitation to water-limitation in the TP, particularly in midsummer (August). Our findings demonstrated the shifting relative importance of climatic limitations on plant photosynthesis under changing climate, which is crucial for predicting future terrestrial carbon cycle dynamics.

Nitrogen addition enhances tree radial growth but weakens its recovery from drought impact in a temperate forest in northern China

Forest growth in the majority of northern China is currently limited by drought and low nitrogen (N) availability. Drought events with increasing intensity have threatened multiple ecosystem services provided by forests. Whether N addition will have a detrimental or beneficial moderation effect on forest resistance and recovery to drought events was unclear. Here, our study focuses on Pinus tabulaeformis, which is the main plantation forest species in northern China. We investigated the role of climate change and N addition in driving multi-year tree growth with an 8-year soil nitrogen fertilization experiment and analyzing 184 tree ring series. A moderate drought event occurred during the experiment, providing an opportunity for us to explore the effects of drought and N addition on tree resistance and recovery. We found that N addition was beneficial for increasing the resistance of middle-aged trees, but had no effect on mature trees. The recovery of trees weakened significantly with increasing N addition, and the reduction in fine root biomass caused by multiyear N addition was a key influencing factor limiting recovery after moderate drought. Our study implies that the combined effect of increasing drought and N deposition might increase the risk of pine forest mortality in northern China.

Vapour pressure deficit was not a primary limiting factor for gas exchange in an irrigated, mature dryland Aleppo pine forest

Climate change is often associated with increasing vapour pressure deficit (VPD) and changes in soil moisture (SM). While atmospheric and soil drying often co-occur, their differential effects on plant functioning and productivity remain uncertain. We investigated the divergent effects and underlying mechanisms of soil and atmospheric drought based on continuous, in situ measurements of branch gas exchange with automated chambers in a mature semiarid Aleppo pine forest. We investigated the response of control trees exposed to combined soil-atmospheric drought (low SM, high VPD) during the rainless Mediterranean summer and that of trees experimentally unconstrained by soil dryness (high SM; using supplementary dry season water supply) but subjected to atmospheric drought (high VPD). During the seasonal dry period, branch conductance (gbr ), transpiration rate (E) and net photosynthesis (Anet ) decreased in low-SM trees but greatly increased in high-SM trees. The response of E and gbr to the massive rise in VPD (to 7 kPa) was negative in low-SM trees and positive in high-SM trees. These observations were consistent with predictions based on a simple plant hydraulic model showing the importance of plant water potential in the gbr and E response to VPD. These results demonstrate that avoiding drought on the supply side (SM) and relying on plant hydraulic regulation constrains the effects of atmospheric drought (VPD) as a stressor on canopy gas exchange in mature pine trees under field conditions.

Greening of human-dominated ecosystems in India

Satellite data show the Earth has been greening and identify croplands in India as one of the most prominent greening hotspots. Though India's agriculture has been dependent on irrigation enhancement to reduce crop water stress and increase production, the spatiotemporal dynamics of how irrigation influenced the satellite observed greenness remains unclear. Here, we use satellite-derived leaf area data and survey-based agricultural statistics together with results from state-of-the-art Land Surface Models (LSM) to investigate the role of irrigation in the greening of India's croplands. We find that satellite observations provide multiple lines of evidence showing strong contributions of irrigation to significant greening during dry season and in drier environments. The national statistics support irrigation-driven yield enhancement and increased dry season cropping intensity. These suggest a continuous shift in India's agriculture toward an irrigation-driven dry season cropping system and confirm the importance of land management in the greening phenomenon. However, the LSMs identify CO2 fertilization as a primary driver of greening whereas land use and management have marginal impacts on the simulated leaf area changes. This finding urges a closer collaboration of the modeling, Earth observation, and land system science communities to improve representation of land management in the Earth system modeling.

Lagged feedback of peak season photosynthetic activities on local surface temperature in Inner Mongolia, China

Increased vegetation peak growth and phenological shifts toward spring have been observed in response to climate warming in the temperate regions. Such changes have the potential to modify warming by perturbing land‒atmosphere energy exchanges; however, the signs and magnitudes of biophysical feedback on surface temperature in different biomes are largely unknown. Here, we synthesized information from vegetation growth proxies, land surface temperature (LST), and surface energy balance factors (surface evapotranspiration (ET), albedo, and broadband emissivity (BBE)) to investigate the variations in timing (PPT) and productivity (PPmax) of seasonal peak photosynthesis and their time-lagged biophysical feedbacks to the post-season LST in Inner Mongolia (IM) during 2001-2020. We found that increased PPmax, rather than advanced PPT, exhibited a significant impact on LST, with divergent signs and magnitudes across diurnal periods and among different biomes. In the grassland biome, increased PPmax cooled both LST during daytime (LSTday) and nighttime (LSTnight) throughout the post-season period, with a more pronounced response during daytime and diminishing gradually from July to September. This cooling effect on LST was primarily attributed to enhanced ET, as evidenced by the greater effect of ET cooling than that of albedo warming and BBE cooling based on a structural equation model (SEM). In the forest biome, increased PPmax led to a symmetrical warming effect on LSTday and LSTnight, and none of the surface energy balance factors were identified as significant intermediate explanatory factors for the observed warming effect. Moreover, the responses of average LST (LSTmean) and diurnal temperature range of LST (LSTDTR) to variations in PPmax were consistent with those of LSTday at two biomes. The observations above elucidate the divergent feedback mechanisms of vegetation peak growth on LST among different biomes and diurnal cycles, which could facilitate the improvement of the realistic parameterization of surface processes in global climate models.

Dryness limits vegetation pace to cope with temperature change in warm regions

Climate change leads to increasing temperature and more extreme hot and drought events. Ecosystem capability to cope with climate warming depends on vegetation's adjusting pace with temperature change. How environmental stresses impair such a vegetation pace has not been carefully investigated. Here we show that dryness substantially dampens vegetation pace in warm regions to adjust the optimal temperature of gross primary production (GPP) (T opt GPP ) in response to change in temperature over space and time.T opt GPP spatially converges to an increase of 1.01°C (95% CI: 0.97, 1.05) per 1°C increase in the yearly maximum temperature (Tmax ) across humid or cold sites worldwide (37o S-79o N) but only 0.59°C (95% CI: 0.46, 0.74) per 1°C increase in Tmax across dry and warm sites.T opt GPP temporally changes by 0.81°C (95% CI: 0.75, 0.87) per 1°C interannual variation in Tmax at humid or cold sites and 0.42°C (95% CI: 0.17, 0.66) at dry and warm sites. Regardless of the water limitation, the maximum GPP (GPPmax ) similarly increases by 0.23 g C m-2 day-1 per 1°C increase inT opt GPP in either humid or dry areas. Our results indicate that the future climate warming likely stimulates vegetation productivity more substantially in humid than water-limited regions.

Increasing temperature regulates the advance of peak photosynthesis timing in the boreal ecosystem

The shift in vegetation phenology is an essential indicator of global climate change. Numerous researches based on reflectance-based vegetation index data have explored the changes in the start (SOS) and end (EOS) of vegetation life events at long time scales, while a huge discrepancy existed between the phenological metrics of vegetation structure and function. The peak photosynthesis timing (PPT), which is crucial in regulating terrestrial ecosystem carbon balance, has not received much attention. Using two global reconstructed solar-induced chlorophyll fluorescence data (CSIF and GOSIF) directly associated with vegetation photosynthesis, the spatio-temporal dynamics in PPT as well as the key environmental controls across the boreal ecosystem during 2001-2019 were systematically explored. Multi-year mean pattern showed that PPT mainly appeared in the first half of July. Compared to the northern Eurasia, later PPT appeared in the northern North America continent for about 4-5 days. Meanwhile, spatial trend in PPT exhibited an advanced trend during the last two decades. Especially, shrubland and grassland were obvious among all biomes. Spatial partial correlation analysis revealed that preseason temperature was the dominant environmental driver of PPT trends, occupying 81.32% and 78.04% of the total pixels of PPT_CSIF and PPT_GOSIF, respectively. Attribution analysis by ridge regression again emphasized the largest contribution of temperature to PPT dynamics in the boreal ecosystem by 52.22% (PPT_CSIF) and 46.59% (PPT_GOSIF), followed by radiation (PPT_CSIF: 24.44%; PPT_GOSIF: 28.66%) and precipitation (PPT_CSIF: 23.34%; PPT_GOSIF: 24.75%). These results have significant implications for deepening our understanding between vegetation photosynthetic phenology and carbon cycling with respect to future climate change in the boreal ecosystem.

Experimental warming causes mismatches in alpine plant-microbe-fauna phenology

Long-term observations have shown that many plants and aboveground animals have changed their phenology patterns due to warmer temperatures over the past decades. However, empirical evidence for phenological shifts in alpine organisms, particularly belowground organisms, is scarce. Here, we investigate how the activities and phenology of plants, soil microbes, and soil fauna will respond to warming in an alpine meadow on the Tibetan Plateau, and whether their potential phenological changes will be synchronized. We experimentally simulate an increase in soil temperature by 2-4 °C according to future projections for this region. We find that warming promotes plant growth, soil microbial respiration, and soil fauna feeding by 8%, 57%, and 20%, respectively, but causes dissimilar changes in their phenology during the growing season. Specifically, warming advances soil faunal feeding activity in spring and delays it in autumn, while their peak activity does not change; whereas warming increases the peak activity of plant growth and soil microbial respiration but with only minor shifts in their phenology. Such phenological asynchrony in alpine organisms may alter ecosystem functioning and stability.

Shifting from a thermal-constrained to water-constrained ecosystem over the Tibetan Plateau

Introduction

Understanding the seasonality of vegetation growth is important for maintaining sustainable development of grassland livestock systems over the Tibetan Plateau (TP). Current knowledge of changes in the seasonality of TP grasslands is restricted to spring and autumn phenology, with little known about the date of peak vegetation growth, the most relevant quantity for grassland productivity.

Methods

We investigate the shifts of the date of peak vegetation growth and its climatic controls for the alpine grasslands over the TP during 2001-2020 using a framework based on the law of minimum, which is based on the assumption that peak vegetation growth would be consistent with the peak timing of the most limiting climatic resource.

Results

The date of peak vegetation growth over the TP advanced by 0.81 days decade-1 during 2001-2020. This spring-ward shift mainly occurs in the semi-humid eastern TP, where the peak growth date tracks the advancing peak precipitation, and shifted towards the timing of peak temperature. The advancing peak growth over the eastern TP significantly stimulated the ecosystem production by 1.99 gCm-2 year-1 day-1 during 2001-2020, while this positive effect weakened from 3.02 gCm-2 year-1 day-1 during 2000s to 1.25 gCm-2 year-1 day-1 during 2010s.

Discussion

Our results highlighted the importance of water availability in vegetation growth over the TP, and indicated that the TP grassland is moving towards a tipping point of transition from thermal-constrained to water-constrained ecosystem under the rapid warming climate.

New tree-ring data from Canadian boreal and hemi-boreal forests provide insight for improving the climate sensitivity of terrestrial biosphere models

Understanding boreal/hemi-boreal forest growth sensitivity to seasonal variations in temperature and water availability provides important basis for projecting the potential impacts of climate change on the productivity of these ecosystems. Our best available information currently comes from a limited number of field experiments and terrestrial biosphere model (TBM) simulations of varying predictive accuracy. Here, we assessed the sensitivity of annual boreal/hemi-boreal forest growth in Canada to yearly fluctuations in seasonal climate variables using a large tree-ring dataset and compared this to the climate sensitivity of annual net primary productivity (NPP) estimates obtained from fourteen TBMs. We found that boreal/hemi-boreal forest growth sensitivity to fluctuations in seasonal temperature and precipitation variables changed along a southwestern to northeastern gradient, with growth limited almost entirely by temperature in the northeast and west and by water availability in the southwest. We also found a lag in growth climate sensitivity, with growth largely determined by the climate during the summer prior to ring formation. Analyses of NPP sensitivity to the same climate variables produced a similar southwest to northeast gradient in growth climate sensitivity for NPP estimates from all but three TBMs. However, analyses of growth from tree-ring data and analyses of NPP from TBMs produced contrasting evidence concerning the key climate variables limiting growth. While analyses of NPP primarily indicated a positive relationship between growth and seasonal temperature, tree-ring analyses indicated negative growth relationships to temperature. Also, the positive effect of precipitation on NPP derived from most TBMs was weaker than the positive effect of precipitation on tree-ring based growth: temperature had a more important limiting effect on NPP than tree-ring data indicated. These mismatches regarding the key climate variables limiting growth suggested that characterization of tree growth in TBMs might need revision, particularly regarding the effects of stomatal conductance and carbohydrate reserve dynamics.

Seasonal peak photosynthesis is hindered by late canopy development in northern ecosystems

The seasonal dynamics of the vegetation canopy strongly regulate the surface energy balance and terrestrial carbon fluxes, providing feedbacks to climate change. Whether the seasonal timing of maximum canopy structure was optimized to achieve a maximum photosynthetic carbon uptake is still not clear due to the complex interactions between abiotic and biotic factors. We used two solar-induced chlorophyll fluorescence datasets as proxies for photosynthesis and the normalized difference vegetation index and leaf area index products derived from the moderate resolution imaging spectroradiometer as proxies for canopy structure, to characterize the connection between their seasonal peak timings from 2000 to 2018. We found that the seasonal peak was earlier for photosynthesis than for canopy structure in >87.5% of the northern vegetated area, probably leading to a suboptimal maximum seasonal photosynthesis. This mismatch in peak timing significantly increased during the study period, mainly due to the increasing atmospheric CO₂, and its spatial variation was mainly explained by climatic variables (43.7%) and nutrient limitations (29.6%). State-of-the-art ecosystem models overestimated this mismatch in peak timing by simulating a delayed seasonal peak of canopy development. These results highlight the importance of incorporating the mechanisms of vegetation canopy dynamics to accurately predict the maximum potential terrestrial uptake of carbon under global environmental change.

Photosynthetic capacity dominates the interannual variation of annual gross primary productivity in the Northern Hemisphere

Annual gross primary productivity (AGPP) of terrestrial ecosystems is the largest carbon flux component in ecosystems; however, it's unclear whether photosynthetic capacity or phenology dominates interannual variation of AGPP, and a better understanding of this could contribute to estimation of carbon sinks and their interactions with climate change. In this study, observed GPP data of 494 site-years from 39 eddy covariance sites in Northern Hemisphere were used to investigate mechanisms of interannual variation of AGPP. This study first decomposed AGPP into three seasonal dynamic attribute parameters (growing season length (CUP), maximum daily GPP (GPP_max), and the ratio of mean daily GPP to GPP_max (α_GPP)), and then decomposed AGPP into mean leaf area index (LAI_m) and annual photosynthetic capacity per leaf area (AGPP_lm). Furthermore, GPP_max was decomposed into leaf area index of DOY_max (the day when GPP_max appeared) (LAI_max) and photosynthesis per leaf area of DOY_max (GPP_lmax). Relative contributions of parameters to AGPP and GPP_max were then calculated. Finally, environmental variables of DOY_max were extracted to analyze factors influencing interannual variation of GPP_lmax. Trends of AGPP in 39 ecosystems varied from -65.23 to 53.05 g C m^-2 yr^-2, with the mean value of 6.32 g C m^-2 yr^-2. Photosynthetic capacity (GPP_max and AGPP_lm), not CUP or LAI, was the main factor dominating interannual variation of AGPP. GPP_lmax determined the interannual variation of GPP_max, and temperature, water, and radiation conditions of DOY_max affected the interannual variation of GPP_lmax. This study used the cascade relationship of "environmental variables-GPP_lmax-GPP_max-AGPP" to explain the mechanism of interannual variation of AGPP, which can provide new ideas for the AGPP estimation based on seasonal dynamic of GPP.

Exploring the relative contribution of flood regimes and climatic factors to Carex phenology in a Yangtze River-connected floodplain wetland

Hydrological regimes can combine with climatic factors to affect plant phenology; however, few studies have attempted to quantify their complex influences on plant phenology in floodplain wetlands. We obtained phenological information on Carex vegetation through MODIS normalized difference vegetation index (NDVI) data during 2001-2020, and monthly field investigation during 2011-2020. We then explored how these data were correlated with climatic factors and flood regimes in a Yangtze River-connected floodplain wetland (Dongting Lake, China). Our results showed that warmer temperature tended to advance the start of the pre-flooding growing season (SOS1), with a relative contribution of 76.1 %. Flood rising time strongly contributed to controlling the end of the pre-flooding growing season. Flood recession time and inundation duration were dominant factors determining the start of the post-flooding growing season (SOS2). Earlier flood recession time and shortened inundation duration tended to advance the SOS2. Shortened inundation duration, earlier flood recession time, and lower solar radiation tended to advance the end of the post-flooding growing season. The phenology of Carex distributed at high-elevation areas was more affected by hydrology than that of Carex distributed at low-elevation areas. Thus, climatic factors strongly affect the phenology of Carex during the pre-flooding growing season, whereas flood regimes play a dominant role in determining the phenology in the post-flooding growing season. The different responses of Carex phenology to climatic and flooding factors may provide insights for the conservation and management of floodplain wetlands in Yangtze River because Carex are primary food source and habitat for herbivorous waterfowls.

Climate Controls on the Spatial Variability of Vegetation Greenup Rate across Ecosystems in Northern Hemisphere

Variations in individual phenological events in response to global change have received considerable attentions. However, the development of phenological stages is relatively neglected, especially based on in situ observation data. In this study, the rate of vegetation greenup (Vgreenup) across the Northern Hemisphere was examined for different plant functional types (PFTs) by using eddy covariance flux data from 40 sites (417 site-years). Then, the controls of climatic variables on the spatial distribution of Vgreenup across PFTs were further investigated. The mean Vgreenup was 0.22 ± 0.11 g C m^-2 day^-2 across all sites, with the largest and lowest values observed in cropland and evergreen needle-leaf forest, respectively. A strong latitude dependence by Vgreenup was observed in both Europe and North America. The spatial variations of Vgreenup were jointly regulated by the duration of greenup (Dgreenup) and the amplitude of greenup (Agreenup). However, the predominant factor was Dgreenup in Europe, which changed to Agreenup in North America. Spring climatic factors exerted significant influences on the spatial distribution of Vgreenup across PFTs. Specifically, increasing temperature tended to shorten Dgreenup and promote Agreenup simultaneously, resulting in an acceleration of Vgreenup. Dryness had a depression effect on Vgreenup for the whole study area, as exhibited by a lower Vgreenup with increasing vapor pressure deficit or decreasing soil moisture. However, Vgreenup in North America was only significantly and positively correlated with temperature. Without the limitation of other climatic factors, the temperature sensitivity of Vgreenup was higher in North America (0.021 g C m^-2 day^-2 °C^-1) than in Europe (0.015 g C m^-2 day^-2 °C^-1). This study provides new cognitions for Vgreenup dynamics from in situ observations in complement to satellite observations, which can improve our understanding of terrestrial carbon cycles.

Impacts of climate change on vegetation phenology over the Great Lakes Region of Central Asia from 1982 to 2014

Dryland ecosystems in the Great Lakes Region of Central Asia (GLRCA) are highly sensitive to climate change due to the climate of spring precipitation. Although shifts in vegetation phenology have been widely attributed to rising temperature, the effects of solar radiation and drought on phenology remain largely unknown. Understanding the mechanisms of vegetation phenology response to climatic factors is essential for assessing the impact of climate change on dryland ecosystems. In this study, we investigated the spatial and temporal variations of vegetation phenology across the GLRCA using a long-term series of Normalized Difference Vegetation Index (NDVI), and then examined the response of vegetation phenology to climate change within different climate zones by combining with climate data (surface temperature, soil moisture, short-wave radiation, and standardized precipitation evapotranspiration index (SPEI)). The results suggested that the start of growing season (SGS) and the end of growing season (EGS) were significantly earlier regionally by -0.143 days/year and -0.363 days/year, respectively. Because of changes in SGS and EGS, length of growing season (LGS) across the GLRCA was shortened at a rate of -0.442 days/yr, which was mainly attributed to advanced EGS. Additionally, SGS of vegetation was negatively correlated with surface temperature but positively correlated with soil moisture and SPEI. These results indicated that surface temperature was a major determinant of advanced spring phenology, while increased soil moisture and mitigated drought would delay spring phenology. The response of autumn phenology to surface temperature and short-wave radiation varied across different climate zones. In arid climate zone, autumn phenology was obviously advanced with the increase of surface temperature and short-wave radiation. In cold climate zone, higher surface temperature and short-wave radiation postponed autumn phenology. Meanwhile, the thermal growing season did not accurately characterize the actual vegetation growing season because GLRCA phenology was different from most of Northern Hemisphere.

Warming and spring precipitation addition change plant growth pattern but have minor effects on growing season mean gross ecosystem productivity in an alpine meadow

Gross ecosystem productivity (GEP) plays an important role in global carbon cycling. However, how plant phenology and growth rate regulate GEP under climate change is unclear. Based on an in situ manipulative experiment using open top chambers from 2015 to 2018, we measured whole year warming and spring precipitation addition effects on plant phenology, plant growth rate and GEP. Our results showed that warming delayed plant green up (4 days) and withering (5 days), while spring precipitation addition advanced green up 13 days and did not change withering. Warming delayed the timing of the fast-growing phase 7 days, shortened length of the fast-growing phase 7 days and marginally increased the growth rate. Spring precipitation addition advanced the timing of the fast-growing phase 6 days, but did not change the length of the fast-growing phase or the growth rate. Both whole year warming and spring precipitation addition have not significantly affected growing season mean GEP. GEP is positively correlated with plant growth rate and negatively correlated with the length of the fast-growing phase. We provide an evidence that although warming did not change growing season mean productivity, it delayed plant fast-growing phase. Our findings suggest that management approaches for increasing water availability before the fast-growing phase should be intensified to increase ecosystem carbon uptake and grass supply for animal husbandry in spring.

Mismatch of N release from the permafrost and vegetative uptake opens pathways of increasing nitrous oxide emissions in the high Arctic

Biogeochemical cycling in permafrost-affected ecosystems remains associated with large uncertainties, which could impact the Earth's greenhouse gas budget and future climate policies. In particular, increased nutrient availability following permafrost thaw could perturb the greenhouse gas exchange in these systems, an effect largely unexplored until now. Here, we enhance the terrestrial ecosystem model QUINCY (QUantifying Interactions between terrestrial Nutrient CYcles and the climate system), which simulates fully coupled carbon (C), nitrogen (N) and phosphorus (P) cycles in vegetation and soil, with processes relevant in high latitudes (e.g., soil freezing and snow dynamics). In combination with site-level and satellite-based observations, we use the model to investigate impacts of increased nutrient availability from permafrost thawing in comparison to other climate-induced effects and CO₂ fertilization over 1960 to 2018 across the high Arctic. Our simulations show that enhanced availability of nutrients following permafrost thaw account for less than 15% of the total Gross primary productivity increase over the time period, despite simulated N limitation over the high Arctic scale. As an explanation for this weak fertilization effect, observational and model data indicate a mismatch between the timing of peak vegetative growth (week 26-27 of the year, corresponding to the beginning of July) and peak thaw depth (week 32-35, mid-to-late August), resulting in incomplete plant use of nutrients near the permafrost table. The resulting increasing N availability approaching the permafrost table enhances N loss pathways, which leads to rising nitrous oxide (N₂ O) emissions in our model. Site-level emission trends of 2 mg N m^-2  year^-1 on average over the historical time period could therefore predict an emerging increasing source of N₂ O emissions following future permafrost thaw in the high Arctic.

A long-term reconstructed TROPOMI solar-induced fluorescence dataset using machine learning algorithms

Photosynthesis is a key process linking carbon and water cycles, and satellite-retrieved solar-induced chlorophyll fluorescence (SIF) can be a valuable proxy for photosynthesis. The TROPOspheric Monitoring Instrument (TROPOMI) on the Copernicus Sentinel-5P mission enables significant improvements in providing high spatial and temporal resolution SIF observations, but the short temporal coverage of the data records has limited its applications in long-term studies. This study uses machine learning to reconstruct TROPOMI SIF (RTSIF) over the 2001-2020 period in clear-sky conditions with high spatio-temporal resolutions (0.05° 8-day). Our machine learning model achieves high accuracies on the training and testing datasets (R2 = 0.907, regression slope = 1.001). The RTSIF dataset is validated against TROPOMI SIF and tower-based SIF, and compared with other satellite-derived SIF (GOME-2 SIF and OCO-2 SIF). Comparing RTSIF with Gross Primary Production (GPP) illustrates the potential of RTSIF for estimating gross carbon fluxes. We anticipate that this new dataset will be valuable in assessing long-term terrestrial photosynthesis and constraining the global carbon budget and associated water fluxes.

Responses of Vegetation Autumn Phenology to Climatic Factors in Northern China

Understanding the dynamics of vegetation autumn phenology (i.e., the end of growing season, EOS) is crucial for evaluating impacts of climate change on vegetation growth. Nevertheless, responses of the EOS to climatic factors were unclear at the regional scale. In this study, northern China was chosen for our analysis, which is a typical ecologically fragile area. Using the Enhanced Vegetation Index (EVI) and climatic data from 1982 to 2016, we extracted the EOS and analyzed its trends in northern China by using the linear least-squares regression and the Bayesian change-point detection method. Furthermore, the partial correlation analysis and multivariate regression analysis were used to determine which climatic factor was more influential on EOS. The main findings were as follows: (1) multi-year average of EOS mainly varied between 275 and 305 day of year (DOY) and had complicated spatial differences for different vegetation types; (2) the percentage of the pixel showing delaying EOS (65.50%) was larger than that showing advancing EOS (34.50%), with a significant delaying trend of 0.21 days/year at the regional scale during the study period. As for different vegetation types, their EOS trends were similar in sign but different in magnitude; (3) temperature showed a dominant role in governing EOS trends from 1982 to 2016. The increase in minimum temperature led to the delayed EOS, whereas the increase in maximum temperature reversed the EOS trends. In addition to temperature, the impacts of precipitation and radiation on EOS trends were more complex and largely depended on the vegetation types. These findings can provide a crucial support for developing vegetation dynamics models in northern China.

An earlier start of the thermal growing season enhances tree growth in cold humid areas but not in dry areas

Climatic warming alters the onset, duration and cessation of the vegetative season. While previous studies have shown a tight link between thermal conditions and leaf phenology, less is known about the impacts of phenological changes on tree growth. Here, we assessed the relationships between the start of the thermal growing season and tree growth across the extratropical Northern Hemisphere using 3,451 tree-ring chronologies and daily climatic data for 1948-2014. An earlier start of the thermal growing season promoted growth in regions with high ratios of precipitation to temperature but limited growth in cold-dry regions. Path analyses indicated that an earlier start of the thermal growing season enhanced growth primarily by alleviating thermal limitations on wood formation in boreal forests and by lengthening the period of growth in temperate and Mediterranean forests. Semi-arid and dry subalpine forests, however, did not benefit from an earlier onset of growth and a longer growing season, presumably due to associated water loss and/or more frequent early spring frosts. These emergent patterns of how climatic impacts on wood phenology affect tree growth at regional to hemispheric scales hint at how future phenological changes may affect the carbon sequestration capacity of extratropical forest ecosystems.

Estimation of China’s Contribution to Global Greening over the Past Three Decades

China’s contribution to global greening is regulated by increasing atmospheric CO2 concentrations, climate change, and land use. Based on TRENDY project data, this study identified that the shifts in China’s contribution to the global leaf area index (LAI) trend strongly reduced during the warming hiatus, translating from 13.42 ± 26.45% during 1982–1998 into 7.91 ± 25.45% during 1999–2012. First, significant negative sensitivities of LAI to enhanced vapor pressure deficit (VPD), when only considering the climate effect derived from TRENDY models in China, were found to have shifted substantially after the late 1990s. However, globally, LAI had positive rather than negative responses to enhanced VPD. These opposing shifts in the response of LAI to enhanced VPD reduced the national contribution to global vegetation greening. Second, shifts in land-use change and their effects on the LAI trends in the two periods in China were accompanied by major changes in land cover and land management intensity, including forestry. Consequently, the contribution of land use in China reduced by −47.68% during the warming hiatus period, as compared with the warming period. Such a shift in the impact of land-use change on LAI simulated by ecosystem models might result from the models’ lack of consideration of conserving and expanding forests with the goal of mitigating climate change for China. Our results highlight the need for ecosystem models to reproduce the enhanced negative impact on global LAI and consider the shifts in man-made adaptation policies (e.g., forest management) to improve terrestrial ecosystem models in the future.

Worldwide impacts of atmospheric vapor pressure deficit on the interannual variability of terrestrial carbon sinks

Interannual variability of the terrestrial ecosystem carbon sink is substantially regulated by various environmental variables and highly dominates the interannual variation of atmospheric carbon dioxide (CO₂) concentrations. Thus, it is necessary to determine dominating factors affecting the interannual variability of the carbon sink to improve our capability of predicting future terrestrial carbon sinks. Using global datasets derived from machine-learning methods and process-based ecosystem models, this study reveals that the interannual variability of the atmospheric vapor pressure deficit (VPD) was significantly negatively correlated with net ecosystem production (NEP) and substantially impacted the interannual variability of the atmospheric CO₂ growth rate (CGR). Further analyses found widespread constraints of VPD interannual variability on terrestrial gross primary production (GPP), causing VPD to impact NEP and CGR. Partial correlation analysis confirms the persistent and widespread impacts of VPD on terrestrial carbon sinks compared to other environmental variables. Current Earth system models underestimate the interannual variability in VPD and its impacts on GPP and NEP. Our results highlight the importance of VPD for terrestrial carbon sinks in assessing ecosystems’ responses to future climate conditions.

Time-Series of Cloud-Free Sentinel-2 NDVI Data Used in Mapping the Onset of Growth of Central Spitsbergen, Svalbard

The Arctic is a region that is expected to experience a high increase in temperature. Changes in the timing of phenological phases, such as the onset of growth (as observed by remote sensing), is a sensitive bio-indicator of climate change. In this paper, the study area was the central part of Spitsbergen, Svalbard, located between 77.28°N and 78.44°N. The goals of this study were: (1) to prepare, analyze and present a cloud-free time-series of daily Sentinel-2 NDVI datasets for the 2016 to 2019 seasons, and (2) to demonstrate the use of the dataset in mapping the onset of growth. Due to a short and intense period with greening-up and frequent cloud cover, all the cloud-free Sentinel-2 data were used. The onset of growth was then mapped by a NDVI threshold method, which showed significant correlation (r2 = 0.47, n = 38, p < 0.0001) with ground-based phenocam observation of the onset of growth in seven vegetation types. However, large bias was found between the Sentinel-2 NDVI-based mapped onset of growth and the phenocam-based onset of growth in a moss tundra, which indicates that the data in these vegetation types must be interpreted with care. In 2018, the onset of growth was about 10 days earlier compared to 2017.

Assessing model performance via the most limiting environmental driver in two differently stressed pine stands

Climate change will impact forest productivity worldwide. Forecasting the magnitude of such impact, with multiple environmental stressors changing simultaneously, is only possible with the help of process-based models. In order to assess their performance, such models require careful evaluation against measurements. However, direct comparison of model outputs against observational data is often not reliable, as models may provide the right answers due to the wrong reasons. This would severely hinder forecasting abilities under unprecedented climate conditions. Here, we present a methodology for model assessment, which supplements the traditional output-to-observation model validation. It evaluates model performance through its ability to reproduce observed seasonal changes of the most limiting environmental driver (MLED) for a given process, here daily gross primary productivity (GPP). We analyzed seasonal changes of the MLED for GPP in two contrasting pine forests, the Mediterranean Pinus halepensis Mill. Yatir (Israel) and the boreal Pinus sylvestris L. Hyytiälä (Finland) from three years of eddy-covariance flux data. Then, we simulated the same period with a state-of-the-art process-based simulation model (LandscapeDNDC). Finally, we assessed if the model was able to reproduce both GPP observations and MLED seasonality. We found that the model reproduced the seasonality of GPP in both stands, but it was slightly overestimated without site-specific fine-tuning. Interestingly, although LandscapeDNDC properly captured the main MLED in Hyytiälä (temperature) and in Yatir (soil water availability), it failed to reproduce high-temperature and high-vapor pressure limitations of GPP in Yatir during spring and summer. We deduced that the most likely reason for this divergence is an incomplete description of stomatal behavior. In summary, this study validates the MLED approach as a model evaluation tool, and opens up new possibilities for model improvement.

The Shrinking Resource Base of Pastoralism: Saami Reindeer Husbandry in a Climate of Change

The productive performance of large ungulates in extensive pastoral grazing systems is modulated simultaneously by the effects of climate change and human intervention independent of climate change. The latter includes the expansion of private, civil and military activity and infrastructure and the erosion of land rights. We used Saami reindeer husbandry in Norway as a model in which to examine trends in, and to compare the influence of, both effects on a pastoral grazing system. Downscaled projections of mean annual temperature over the principal winter pasture area (Finnmarksvidda) closely matched empirical observations across 34 years to 2018. The area, therefore, is not only warming but seems likely to continue to do so. Warming notwithstanding, 50-year (1969–2018) records of local weather (temperature, precipitation and characteristics of the snowpack) demonstrate considerable annual and decadal variation which also seems likely to continue and alternately to amplify and to counter net warming. Warming, moreover, has both positive and negative effects on ecosystem services that influence reindeer. The effects of climate change on reindeer pastoralism are evidently neither temporally nor spatially uniform, nor indeed is the role of climate change as a driver of change in pastoralism even clear. The effects of human intervention on the system, by contrast, are clear and largely negative. Gradual liberalization of grazing rights from the 18th Century has been countered by extensive loss of reindeer pasture. Access to ~50% of traditional winter pasture was lost in the 19th Century owing to the closure of international borders to the passage of herders and their reindeer. Subsequent to this the area of undisturbed pasture within Norway has decreased by 71%. Loss of pasture due to piecemeal development of infrastructure and to administrative encroachment that erodes herders' freedom of action on the land that remains to them, are the principal threats to reindeer husbandry in Norway today. These tangible effects far exceed the putative effects of current climate change on the system. The situation confronting Saami reindeer pastoralism is not unique: loss of pasture and administrative, economic, legal and social constraints bedevil extensive pastoral grazing systems across the globe.

Mapping Spatiotemporal Changes in Vegetation Growth Peak and the Response to Climate and Spring Phenology over Northeast China

Global climate change has led to significant changes in seasonal rhythm events of vegetation growth, such as spring onset and autumn senescence. Spatiotemporal shifts in these vegetation phenological metrics have been widely reported over the globe. Vegetation growth peak represents plant photosynthesis capacity and responds to climate change. At present, spatiotemporal changes in vegetation growth peak characteristics (timing and maximum growth magnitude) and their underlying governing mechanisms remain unclear at regional scales. In this study, the spatiotemporal dynamics of vegetation growth peak in northeast China (NEC) was investigated using long-term NDVI time series. Then, the effects of climatic factors and spring phenology on vegetation growth peak were examined. Finally, the contribution of growth peak to vegetation production variability was estimated. The results of the phenological analysis indicate that the date of vegetation green up in spring and growth peak in summer generally present a delayed trend, while the amplitude of growth peak shows an increasing trend. There is an underlying cycle of 11 years in the vegetation growth peak of the entire study area. Air temperature and precipitation before the growing season have a small impact on vegetation growth peak amplitude both in its spatial extent and magnitude (mainly over grasslands) but have a significant influence on the date of the growth peak in the forests of the northern area. Spring green-up onset has a more significant impact on growth peak than air temperature and precipitation. Although green-up date plays a more pronounced role in controlling the amplitude of the growth peak in forests and grasslands, it also affects the date of growth peak in croplands. The amplitude of the growth peak has a significant effect on the inter-annual variability of vegetation production. The discrepant patterns of growth peak response to climate and phenology reflect the distinct adaptability of the vegetation growth peak to climate change, and result in different carbon sink patterns over the study area. The study of growth peak could improve our understanding of vegetation photosynthesis activity over various land covers and its contribution to carbon uptake.

Asymmetry of Daytime and Nighttime Warming in Typical Climatic Zones along the Eastern Coast of China and Its Influence on Vegetation Activities

In this dissertation, the author adopted the normalized difference vegetation index (NDVI) and meteorological data from 1982 to 2016 of the typical climate zones in coastal areas of China to analyze the influence of daytime and nighttime warming asymmetric changes in different seasons on vegetation activities during the growing season period according to the copula function theory optimized based on Markov chain Monte Carlo (MCMC). The main conclusions are as follows: (1) The seasonal daytime and nighttime warming trends of Guangdong, Jiangsu and Liaoning over the past 35 years were significant, and the daytime and nighttime warming rates were asymmetric. In spring and summer of Guangdong province, the warming rate in the daytime was higher than that at night, while, in autumn, the opposite law was observed. However, the warming rate in the daytime was lower than that at night in Jiangsu and Liaoning provinces. There were latitude differences in diurnal and nocturnal warming rate. (2) The daytime and nighttime warming influences on vegetation showed significant seasonal differences in these three regions. In Guangdong, the influence of nighttime warming on vegetation growth in spring is greater than that in summer, and the influences of daytime warming on vegetation growth from strong to weak were spring, summer and autumn. In Jiangsu, both the influences of daytime and nighttime warming on vegetation growth in summer were less than that in autumn. In Liaoning, both the influences of daytime and nighttime warming on vegetation growth from strong to weak were autumn, spring and summer. (3) In Guangdong, Jiangsu and Liaoning provinces, their maximum temperature (Tmax) and minimum temperature (Tmin) and the joint probability distribution functions of NDVI, all had little effect on NDVI when Tmax and Tmin respectively reached their minimum values, but their influences on NDVI were obvious when Tmax and Tmin respectively reached their maximum values. (4) The smaller the return period, the larger the range of climate factor and NDVI, which has indicated that when the climate factor is certain, the NDVI is more likely to have a smaller return period, and the frequency of NDVI over a certain period is higher. In addition, the larger the climate factor, the greater the return period is and NDVI is less frequent over a certain period of time. This research can help with deep understanding of the dynamic influence of seasonal daytime and nighttime asymmetric warming on the vegetation in typical coastal temperature zones of China under the background of global climate change.

Accelerated rate of vegetation green-up related to warming at northern high latitudes

Mid- to high-latitude vegetation are experiencing changes in their seasonal cycles as a result of climate change. Although the rates of seasonal growth from winter dormancy to summer maturity have accelerated because of changes in environmental conditions, less attention has been paid to the rate of vegetation green-up (RVG) and its dynamics, which could advance vegetation maturity. We analyzed the long-term changes in RVG and the drivers at high northern latitudes for 35 years (1982-2016) using satellite-retrieved leaf area index data based on partial correlation analyses and multivariable linear regression. The rates tended to increase significantly with time, particularly at high latitudes above 60°N in North America (1.8% mon^-1 decade^-1 , p < .01) and Eurasia (1.0% mon^-1 decade^-1 , p < .01). The increasing trend in North America was mostly because of increased heat accumulation in spring (1.2% mon^-1 decade^-1 ), that is, more rapid green-up owing to warming, with an increased carbon dioxide concentration (0.6 mon^-1 decade^-1 ). The trend in Eurasia, however, was induced by warming, increased carbon dioxide concentration, and stronger radiation, 1.0%, 0.7%, and 0.5% mon^-1 decade^-1 , respectively, but was partly counteracted by earlier pregreen-up dates of -1.2% mon^-1 decade^-1 , that is, earlier initiation of growth which counteracted green-up rate acceleration. The results suggested that warming was the predominant factor influencing the accelerated RVG at high latitudes; however, Eurasian vegetation exhibited different green-up dynamics, mitigating the influence of warming with the earlier pregreen-up. Our findings imply that high-latitude warming will drive vegetation seasonality toward rapid green-up and early maturity, leading to the reinforcement of climate-vegetation interactions; however, the consequences will be more distinct in North America owing to the absence of alleviation by earlier pregreen-up.

Research challenges and opportunities for using big data in global change biology

Global change biology has been entering a big data era due to the vast increase in availability of both environmental and biological data. Big data refers to large data volume, complex data sets, and multiple data sources. The recent use of such big data is improving our understanding of interactions between biological systems and global environmental changes. In this review, we first explore how big data has been analyzed to identify the general patterns of biological responses to global changes at scales from gene to ecosystem. After that, we investigate how observational networks and space-based big data have facilitated the discovery of emergent mechanisms and phenomena on the regional and global scales. Then, we evaluate the predictions of terrestrial biosphere under global changes by big modeling data. Finally, we introduce some methods to extract knowledge from big data, such as meta-analysis, machine learning, traceability analysis, and data assimilation. The big data has opened new research opportunities, especially for developing new data-driven theories for improving biological predictions in Earth system models, tracing global change impacts across different organismic levels, and constructing cyberinfrastructure tools to accelerate the pace of model-data integrations. These efforts will uncork the bottleneck of using big data to understand biological responses and adaptations to future global changes.

Alpine grassland plants grow earlier and faster but biomass remains unchanged over 35 years of climate change

Satellite data indicate significant advancement in alpine spring phenology over decades of climate warming, but corresponding field evidence is scarce. It is also unknown whether this advancement results from an earlier shift of phenological events, or enhancement of plant growth under unchanged phenological pattern. By analyzing a 35‐year dataset of seasonal biomass dynamics of a Tibetan alpine grassland, we show that climate change promoted both earlier phenology and faster growth, without changing annual biomass production. Biomass production increased in spring due to a warming‐induced earlier onset of plant growth, but decreased in autumn due mainly to increased water stress. Plants grew faster but the fast‐growing period shortened during the mid‐growing season. These findings provide the first in situ evidence of long‐term changes in growth patterns in alpine grassland plant communities, and suggest that earlier phenology and faster growth will jointly contribute to plant growth in a warming climate.

Climatic Drivers of Greening Trends in the Alps

Since the 1980s, vegetated lands have experienced widespread greening at the global scale. Numerous studies have focused on spatial patterns and mechanisms of this phenomenon, especially in the Arctic and sub-Arctic regions. Greening trends in the European Alps have received less attention, although this region has experienced strong climate and land-use changes during recent decades. We studied the rates and spatial patterns of greening in an inner-alpine region of the Western Alps. We used MODIS-derived normalized difference vegetation index (NDVI) at 8-day temporal and 250 m spatial resolution, for the period 2000–2018, and removed areas with disturbances in order to consider the trends of undisturbed vegetation. The objectives of this study were to (i) quantify trends of greening in a representative area of the Western Alps; and (ii) examine mechanisms and causes of spatial patterns of greening across different plant types. We show that 63% of vegetated areas experienced significant trends during the 2000–2018 period, of which only 8% were negative. We identify (i) a climatic control on spring and autumn phenology with contrasting effects depending on plant type and elevation, and (ii) land-use change dynamics, such as shrub encroachment on abandoned pastures and colonization of new surfaces at high elevation. Below 1500 m, warming temperatures promote incremental greening in the transition from spring to summer, but not in fall, suggesting either photoperiod or water limitation. In the alpine and sub-alpine belts (>1800 m asl), snow prevents vegetation development until late spring, despite favorable temperatures. Instead, at high elevation greening acts both in summer and autumn. However, photoperiod limitation likely prevents forested ecosystems from fully exploiting warmer autumn conditions. We furthermore illustrate two emblematic cases of prominent greening: recent colonization of previously glaciated/non vegetated areas, as well as shrub/tree encroachment due to the abandonment of agricultural practices. Our results demonstrate the interplay of climate and land-use change in controlling greening dynamics in the Western Alps.