Autumn Phenology Research Articles

Greening‐Induced Biophysical Impacts Lead to Earlier Spring and Autumn Phenology in Temperate and Boreal Forests

AbstractTree phenology, the timing of periodic biological events in trees, is highly sensitive to climate change. Previous studies have indicated that forest greening can impact the local climate by modifying the seasonal surface energy budget. However, the understanding of tree phenological responses to forest greening at large spatial scales remains limited. Utilizing satellite‐derived phenological and leaf area index data spanning from 2001 to 2021, herein we show that forest greening led to earlier spring and autumn phenology in both temperate and boreal forests. Our findings demonstrated that forest greening during winter and spring contributed to a reduction in surface albedo, resulting in biophysical warming and consequently advancing spring leaf phenology. Conversely, forest greening in summer and autumn induced biophysical cooling through increased evapotranspiration, leading to an earlier onset of autumn leaf phenology. Our findings highlight the significant impact of forest greening‐induced local seasonal climate changes on shaping tree phenology in temperate and boreal forests. It is crucial to consider these greening‐induced alterations in microclimate conditions when modeling changes in tree phenology under future climate warming scenarios.

Influence of vegetation phenological carryover effects on plant autumn phenology under climate change

Vegetation phenological carryover effects refer to the influence of previous phenological events on the current or subsequent ones. These effects can modulate the responses of autumn phenology to climate change, but the magnitude and duration of this effect remain poorly understood. Therefore, we employed multiple remote sensing datasets from 1982 to 2018 in the Northern Hemisphere (> 30°N) and partial correlation to investigate the influence of the carryover effect and environmental factors on the end of the growing season (EOS) over time. The importance of the variables in the projection score was used to quantify their relative importance. Our results showed that the previous year's EOS had a robust positive impact on the EOS for 40.02 % of the study area during 1982–2015, which was mainly located in the northern 50°N region. In contrast, the start of the growing season (SOS) was the main contributor to the EOS during 2001–2018, mainly at 40°N-50°N and in northern Russia. The carryover effect persisted into the subsequent year, but its strength and positive impacts varied dramatically in the next year. Concurrently, the mean correlation coefficient between climate factors and EOS rose from 0.20 to 0.22. Notably, the correlation coefficient for frost day frequency increased significantly (P < 0.05) from 0.15 to 0.36, with its influence area expanding from 10.29 % to 11.85 % of the study area. Compared with climate factors, the phenological carryover effect was the dominant driver of the EOS for each vegetation type, accounting for 72.8 % and 44.23 % of the total pixels during 1982–2015 and 2001–2018, respectively. Our study reveals a cascade of ecological consequences that extend beyond the initial occurrence and emphasizes the interconnectedness of growth stages in the plant life cycle, providing valuable insights into the adaptability and vulnerability of plant communities.

Canopy structure regulates autumn phenology by mediating the microclimate in temperate forests

Canopy structure regulates autumn phenology by mediating the microclimate in temperate forests

From Delay to Advance: The Impact of Increasing Drought on Autumn Photosynthetic Phenology in Subtropical and Tropical Forests

AbstractDrought dramatically impacts the autumn phenology of vegetation. However, the underlying mechanisms of vegetation autumn phenology responses to drought in tropical and subtropical forests remain unclear. Here, we employed three fitting methods to extract the end‐of‐photosynthetic‐growing‐season (EOPS) dates and quantified their responses to drought intensity using ridge regression and correlation analysis. Our analysis revealed a general delay in the trend of EOPS at an average rate of 3.6 days per decade from 2001 to 2020 in southern China. The standardized precipitation evapotranspiration index (SPEI) emerged as the primary influencing predictor of EOPS processes, surpassing the impacts of temperature, precipitation, and radiation. Notably, our analysis highlighted a shift in the response of EOPS to drought from delay to advancement when drought intensity exceeded 0.38. Incorporating this reversal phenomenon into EOPS models is crucial for accurately predicting autumn phenology under future escalating drought conditions.

Factors and effects of inter-individual variability in silver birch phenology using dense LiDAR time-series

Comprehending and quantifying local variability in plant phenology, alongside its impacts on tree growth, is challenging due to spatially and temporally heterogeneous environmental factors that interact to affect phenological events and periods. Although previous studies have focused on the climatic factors driving phenological events at the stand level, the influences of competition, neighborhood characteristics, species richness, and water availability on plant phenology remain unclear. In the present paper, we used hourly terrestrial LiDAR surveys performed between April 2020 and April 2021 to investigate the influence of local factors (neighborhood and topography) on the phenology of silver birch trees (Betula pendula Roth.). We also examined how phenological events affect growth in tree height and crown area. All response and explanatory variables were estimated using LiDAR time-series data and a field survey campaign. Our findings demonstrate a high within-species variability in plant phenology that is controlled by biotic and abiotic characteristics of the ecosystem. We found that between tree variation in leaf burst, completion of the leaf growth and length of canopy growth period were affected by tree size, neighborhood species richness, level of suppression and competition, which potentially indicate plant responses to light availability. The beginning of senescence, completion of leaf drop, and length of autumn phenology were mostly affected by topographic water index, which reflects water availability and can be linked to nutrient availability and exposure to wind. Furthermore, we demonstrated that an earlier leaf burst, and delayed beginning of senescence were associated with larger absolute growth in canopy area but found no clear relationship between height growth and phenology. Our study highlights the capability of dense, high-quality LiDAR time-series to detect significant phenological variation among individuals of the same species within the same locality, demonstrating the potential of LiDAR time-series as a tool for understanding phenology and its impacts.

Effects of Extreme Climatic Events on the Autumn Phenology in Northern China Are Related to Vegetation Types and Background Climates

The increased intensity and frequency of extreme climate events (ECEs) have significantly impacted vegetation phenology, further profoundly affecting the structure and functioning of terrestrial ecosystems. However, the mechanisms by which ECEs affect the end of the growing season (EOS), a crucial phenological phase, remain unclear. In this study, we first evaluated the temporal variations in the EOS anomalies in Northern China (NC) based on the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) from 2001 to 2018. We then used event coincidence analysis (ECA) to assess the susceptibility of EOS to four ECEs (i.e., extreme heat, extreme cold, extreme wet and extreme dry events). Finally, we examined the dependence of the response of EOS to ECEs on background climate conditions. Our results indicated a slight decrease in the proportion of areas experiencing extreme heat and dry events (1.10% and 0.66% per year, respectively) and a slight increase in the proportion of areas experiencing extreme wet events (0.77% per year) during the preseason period. Additionally, EOS exhibited a delaying trend at a rate of 0.25 days/a during the study period. The susceptibility of EOS to ECEs was closely related to local hydrothermal conditions, with higher susceptibility to extreme dry and extreme hot events in drier and warmer areas and higher susceptibility to extreme cold and extreme wet events in wetter regions. Grasslands, in contrast to forests, were more sensitive to extreme dry, hot and cold events due to their weaker resistance to water deficits and cold stress. This study sheds light on how phenology responds to ECEs across various ecosystems and hydrothermal conditions. Our results could also provide a valuable guide for ecosystem management in arid regions.

Shifts in Plant Phenology and Its Responses to Climate Warming in Three Temperate Cities of China during 1963–2020

The advance of spring phenology and the delay of autumn phenology caused by global warming have been documented by many studies. However, most research has focused on natural areas, with limited studies conducted on phenological observations in urban environments. Here, we selected the first flowering date (FFD), first leaf date (FLD), and leaf coloring date (LCD) at three sites (Beijing, Harbin, and Mudanjiang) from the China Phenological Observation Network. We analyzed the phenological changes of 84 species between 1963–1991 and 1992–2020 to examine their response to urban warming. We then quantified the correlations and regressions between phenological events and preseason temperature. The results show the following: (1) Among the three sites, the mean FFD and FLD were earliest in Beijing, while the mean LCD occurred earliest in Harbin and latest in Beijing. (2) FFD and FLD exhibited a significant trend towards earlier occurrences at all three sites, while LCD showed a significant delay trend except for the Mudanjiang site. Specifically, at the Beijing, Harbin, and Mudanjiang sites, the mean FFD advanced by 8.32 days, 6.11 days, and 2.60 days in the latter period (p &lt; 0.05), whereas the mean FLD advanced by 11.30 days, 7.21 days, and 5.02 days (p &lt; 0.05), respectively. (3) In Beijing, Harbin, and Mudanjiang, both FFD and FLD were significantly negatively correlated with preseason temperature. However, no consistent relationship was observed between LCD and preseason temperature. These results enhance our understanding of the response of plant phenology to urban warming.

Disentangling the Effects of Atmospheric and Soil Dryness on Autumn Phenology across the Northern Hemisphere

In recent decades, drought has intensified along with continuous global warming, significantly impacting terrestrial vegetation. High atmospheric water demand, indicated by vapor pressure deficit (VPD), and insufficient soil moisture (SM) are considered the primary factors causing drought stress in vegetation. However, the influences of VPD and SM on the autumn phenology are still unknown. Using satellite observations and meteorological data, we examined the impacts of VPD and SM on the end of the growing season (EOS) across the Northern Hemisphere (&gt;30°N) from 1982 to 2022. We found that VPD and SM were as important as temperature, precipitation, and radiation in controlling the variations in the EOS. Moreover, the EOS was predominantly influenced by VPD or SM in more than one-third (33.8%) of the study area. In particular, a ridge regression analysis indicated that the EOS was more sensitive to VPD than to SM and the other climatic factors, with 25% of the pixels showing the highest sensitivity to VPD. In addition, the effects of VPD and SM on the EOS varied among biome types and climate zones. VPD significantly advanced the EOS in 25.8% of temperate grasslands, while SM had the greatest impact on advancing the EOS in 17.7% of temperate coniferous forests. Additionally, 27.7% of the midlatitude steppe (BSk) exhibited a significant negative correlation between VPD and the EOS, while 19.4% of the marine west coast climate (Cfb) showed a positive correlation between SM and the EOS. We also demonstrated that the correlation between VPD and the EOS was linearly affected by VPD and the leaf area index, while the correlation between SM and the EOS was affected by SM, precipitation, and the leaf area index. Our study highlights the importance of VPD and SM in regulating autumn phenology and enhances our understanding of terrestrial ecosystem responses to climate change.

Turning Points in Vegetation Phenology Trends and Their Relationship to Climate in Arid Central Asia

AbstractGrassland phenology is highly sensitive to climate change. Here, we investigate the spatiotemporal patterns of start (start of season (SOS)) and end (end of season (EOS)) dates of the growing season and quantify changes in their climatic controls over the arid Central Asian grassland ecosystems during 1982–2015, which may improve the model performance by considering shifts in primary drivers under ongoing climate change. Our results suggest that temperature played a positive role in advancing the SOS date, with the control of temperature on SOS getting stronger as preseason conditions become warmer but not drier. For autumn phenology, rapid increase in temperature after 1999 in combination with reductions in precipitation jointly contributed to a shift from delayed to advanced EOS. The areas that EOS regulated by either temperature or precipitation have changed between the two subperiods. Our findings suggest that the dynamic controls of temperature and precipitation on grassland phenology and the difference between spring and autumn phenology should be built into phenological models more accurately.

Enhanced autumn phenology model incorporating agricultural drought

The impacts of various drought types on autumn phenology have yet to be extensively explored. We address the influence of pre-season agricultural and meteorological droughts on autumn phenology in the Northern Hemisphere. To this end, enhanced autumn phenology models incorporating drought factors was developed, contributing to a deeper understanding of these complex interactions. The study reveals that there was no significant trend of advancement or delay in the End of Season (EOS) across the Northern Hemisphere based on SIF estimates from 2001 to 2020. The cumulative and delayed impacts of pre-season agricultural drought on EOS were found to be more pronounced than those associated with meteorological drought. The analysis of various evaluation indexes shows that the performance of the Cooling Degree Days (CDD) model incorporating the Standardized Soil Moisture Drought Index (CDDSSMI) in simulating EOS in the Northern Hemisphere is >14 % higher than that of the standard CDD model. Additionally, the performance of the CDD model with the Standardized Precipitation Index (CDDSPI) in simulating EOS in the Northern Hemisphere is improved by >5.6 % compared to the standard CDD model. A comparison of future EOS projections across various models reveals that the CDD model significantly overestimates EOS in different scenarios (SSP245 and SSP585). The CDDSSMI model projects EOS approximately 7 days earlier than the CDD model, and the CDDSPI model projects EOS approximately 5 days earlier than the CDD model. This study highlights the diverse impacts of drought types on plant autumn phenology and underscores the significance of parameterizing drought impacts in autumn phenology models.

Autumn phenology consistently delays in subtropical forests in China based on a new process-based model integrating temperature, photoperiod and precipitation

Abstract Climate warming has delayed vegetation autumn phenology, which in turn influences terrestrial carbon and water cycles and their feedback to the climate. However, the performance of autumn phenology models, especially for subtropical forests, remains poor. In this study, we extracted the end-of-photosynthetic-growing-season (EOPS) dates in subtropical China over the period 2001-2018 based on high-resolution solar-induced chlorophyll fluorescence (SIF) dataset using three fitting methods. We developed a new autumn phenology model (DMP model) that integrates precipitation and photoperiod into the classic cold-degree days model, and the new model outperformed the classic model reducing the RMSE by approximately 2 days. We found that the EOPS date was delayed by an average of 4.1 days per decade in the subtropical forests of China from 2001 to 2018, and the precipitation (partial correlation coefficient, r = 0.45), rather temperature (r = 0.29) determined the EOPS processes. We further studied future EOPS using the DMP model and found the EOPS will delay by 1.0 days per decade under the SSP2-4.5 scenario and 2.7 days per decade under the SSP5-8.5 scenario from 2030 to 2100. Our study highlighted the role of precipitation in regulating EOPS in the subtropical forests of China and provided valuable insight for integrating multiple climatic determinants into autumn phenology models.

No slowdown of growing season extension with warming in a permafrost‐affected meadow on the Tibetan Plateau

Abstract The Tibetan Plateau holds the world's largest alpine permafrost and is undergoing an acceleration of warming. Phenological shifts over alpine permafrost in a warmer world have been little studied and are greatly underrepresented in current syntheses. Here, we conducted seasonal and gradient temperature‐controlled experiments in a permafrost‐affected meadow to evaluate how warming drives shifts in spring and autumn phenology, and associated growing‐season length at both community and species levels. We found that there is no sign of slowdown in spring advance with warming under a higher year‐around warming treatment, aligning with a future medium warming scenario. Although spring advance led to an advance in autumn senescence according to spring‐only warming experiments, the advance could not offset the delay due to concurrent warming. As a result, year‐around warming significantly delayed autumn senescence, although there was a deceleration in delay with warming under high temperature treatment than under the low one. This finding can be attributed to the possibility that winter warming is insufficient to reduce chilling accumulation, which would not delay spring phenology and then lead to a non‐slowdown in spring phenological advancement. Taken together, there is no slowdown in an extension of growing season length with warming under a higher year‐around warming treatment, with an increase of length by 9 and 21 days at the end of this century under a CO2 stabilization and medium warming scenarios, respectively. Synthesis. Our results suggest that a continued growing season extension at least under the medium warming scenario would help permafrost‐affected meadow ecosystems to mitigate permafrost carbon release on the Tibetan Plateau.

Weakened connection between spring leaf-out and autumn senescence in the Northern Hemisphere.

Vegetation autumn phenology is critical in regulating the ecosystem carbon cycle and regional climate. However, the dominant drivers of autumn senescence and their temporal shifts under climate change remain poorly understood. Here, we conducted a multi-factor analysis considering both direct climatic controls and biological carryover effects from start-of-season (SOS) and seasonal peak vegetation activities on the end-of-season (EOS) to fill these knowledge gaps. Combining satellite and ground observations across the northern hemisphere, we found that carryover effects from early-to-peak vegetation activities exerted greater influence on EOS than the direct climatic controls on nearly half of the vegetated land. Unexpectedly, the carryover effects from SOS on EOS have significantly weakened over recent decades, accompanied by strengthened climatic controls. Such results indicate the weakened constraint of leaf longevity on senescence due to prolonged growing season in response to climate change. These findings underscore the important role of biological carryover effects in regulating vegetation autumn senescence under climate change, which should be incorporated into the formulation and enhancement of phenology modules utilized in land surface models.

Evaluating the effect of Multi-Scale droughts on autumn phenology of global land biomes with satellite observation

The end of the growing season (EOS), autumn phenology, is a significant indicator of vegetation health in terrestrial ecosystems. Higher frequency and intensity droughts are expected to have a greater impact on ecosystem homeostasis, and an urgent determination of the impact of temporal effects on autumn phenology is imperative to improve the understanding of ecosystem resilience and resistance and the stability of plant carbon sinks. This study aims to quantitatively assess the response of global autumn phenology to observed drought cumulative and lagged effects based on EOS and multi time-scales drought index (the Standardized Precipitation and Evapotranspiration Index, SPEI), and analyze the potential impact path of climate variables on EOS-SPEI relationship. Our results suggested that the cumulative and lagged effects of drought had a significant impact on the autumn phenology of approximately 27.00% and 48.73% of the vegetated area, respectively. The accumulated months were mostly concentrated on shorter time scales (1- to 3-month), and the lagged effect was mostly concentrated on 1 to 3 lagged months. These two effects on EOS were similar in different biomes and water availability, demonstrating that diverse biomes have different adaptation strategies to drought and the importance of water available for ecosystem drought mitigation. Precipitation and solar radiation had a direct negative impact on evaporation, whereas evaporation had a substantial directly positive impact on the intensity of drought effect on autumn phenology. The interaction between the climatic variables results in the accumulated months being directly positively regulated by thermal radiation, while the lagged months were directly positively influenced by precipitation, which indicates that the hydrothermal conditions at the onset of EOS occurrence govern the autumn phenology response to drought more than the occurrence time of EOS.

Autumn sunlight promotes aboveground carbon loss in a temperate mixed forest

BackgroundPhotodegradation of plant litter plays a pivotal role in the global carbon (C) cycle. In temperate forest ecosystems, the exposure of plant litter to solar radiation can be significantly altered by changes in autumn phenology and snow cover due to climatic change. How this will affect litter decomposition and nutrient dynamic interacting with forest canopy structure (understorey vs. gaps) is uncertain. In the present study, we conducted a field experiment using leaf litter of early-fall deciduous Betula platyphylla (Asian white birch) and late-fall deciduous Quercus mongolica (Mongolian oak) to explore the effect of change in autumn solar radiation on dynamics of litter decomposition in a gap and understorey of a temperate mixed forest.ResultsExposure to the full-spectrum of not only significantly increased the loss of mass, C, and lignin, but also modified N loss through both immobilization and mineralization during the initial decomposition during autumn canopy opening, irrespective of canopy structure and litter species. These effects were mainly driven by the blue-green spectral region of sunlight. Short-term photodegradation by autumn solar radiation had a positive legacy effect on the later decomposition particularly in the forest gap, increasing mass loss by 16% and 19% for Asian white birch and Mongolia oak, respectively.ConclusionsOur results suggest that earlier autumn leaf-fall phenology and/or later snow cover due to land-use or climate change would increase the exposure of plant organic matter to solar radiation, and accelerate ecosystem processes, C and nutrient cycling in temperate forest ecosystems. The study provides a reference for predictive research on carbon cycling under the background of global climate change.

Response of vegetation phenology to climate factors in the source region of the Yangtze and Yellow Rivers

Abstract Exploring the impact of climate factors on vegetation phenology is crucial to understanding climate–vegetation interactions as well as carbon and water cycles in ecosystems in the context of climate change. In this article, we extracted the vegetation phenology data from 2002 to 2021 based on the dynamic threshold method in the source region of the Yangtze and Yellow Rivers. Trend and correlation analyses were used to investigate the relationship between vegetation phenology and temperature, precipitation and their spatial evolution characteristics. The results showed that: (i) From 2002 to 2021, the multi-year average start of growing season (SOS), end of growing season (EOS) and length of growing season (LOS) for plants were concentrated in May, October and 4–6 months, with a trend of 4.9 days (earlier), 1.5 days (later), 6.3 days/10 a (longer), respectively. (ii) For every 100 m increase in elevation, SOS, EOS and LOS were correspondingly delayed by 1.8 days, advanced by 0.8 days and shortened by 2.6 days, respectively. (iii) The impacts of temperature and precipitation on vegetation phenology varied at different stages of vegetation growth. Influencing factors of spring phenology experienced a shift from temperature to precipitation, while autumn phenology experienced precipitation followed by temperature. (iv) The climate factors in the previous period significantly affected the vegetation phenology in the study area and the spatial variability was obvious. Specifically, the temperature in April significantly affected the spring phenology and precipitation in August widely affected the autumn phenology.

Temperature variations impacting leaf senescence initiation pathways alter leaf fall timing patterns in northern deciduous forests

Simulating the timing of leaf fall in large scale is crucial for accurate estimation of ecosystem carbon sequestration. However, the limited understanding of leaf senescence mechanisms often impedes the accuracy of simulation and prediction. In this study, we employed the advanced process-based models to fit remote sensing-derived end dates of the growing season (EOS) across deciduous broadleaf forests in the Northern Hemisphere, and revealed the spatial pattern associated with two leaf senescence pathways (i.e., either photoperiod- or temperature- initiated leaf senescence) and their potential effects on EOS prediction. The results show that the pixel-specific optimum models effectively fitted all EOS time series. Leaf senescence in 67.6 % and 32.4 % of pixels was initiated by shortening daylength and declining temperature, respectively. Shortening daylength triggered leaf senescence occurs mainly in areas with shorter summer daylength and/or warmer autumns, whereas declining temperature induced leaf senescence appears primarily in areas with longer summer daylength and/or colder autumns. The strong dependence of leaf senescence initiation cues on local temperature conditions implies that the ongoing increase in autumn temperature has the potential to alter the leaf senescence initiation, shifting from temperature cues to photoperiod signals. This shift would occur in 26.2–49.6 % of the areas where leaf senescence is initiated by declining temperature under RCP 4.5 and 8.5 scenarios, while forest areas where leaf senescence is induced by shortening daylength may expand northward. The overall delaying of the currently predicted EOS would therefore slow down by 4.5–10.3 % under the two warming scenarios. This implies that the adaptive nature of plants will reduce the overestimation of changes in carbon exchange capacity between ecosystems and atmosphere. Our study offers novel insights into understanding the mechanism of leaf senescence and improving the estimation of autumn phenology and ecosystem carbon balance in the deciduous broadleaf forests.

Earlier Spring-Summer Phenology and Higher Photosynthetic Peak Altered the Seasonal Patterns of Vegetation Productivity in Alpine Ecosystems

Carbon uptake of vegetation is controlled by phenology and photosynthetic carbon uptake capacity. However, our knowledge of the seasonal responses of vegetation productivity to phenological and physiological changes in alpine ecosystems is still weak. In this study, we quantified the spatio-temporal variations of vegetation phenology and gross primary productivity (GPP) across the source region of the Yellow River (SRYR) by analyzing MODIS-derived vegetation phenology and GPP from 2001 to 2019, and explored how vegetation phenology and maximum carbon uptake capacity (GPPmax) affected seasonal GPP over the region. Our results showed that the SRYR experienced significantly advanced trends (p &lt; 0.05) for both start (SOS) and peak (POS) of the growing season from 2001 to 2019. Spring GPP (GPPspr) had a significantly increasing trend (p &lt; 0.01), and the earlier SOS had obvious positive effects on GPPspr. Summer GPP (GPPsum) was significantly and negatively correlated to POS (p &lt; 0.05). In addition, GPPmax had a significant and positive correlation with GPPsum and GPPann (p &lt; 0.01), respectively. It was found that an earlier spring-summer phenology and higher photosynthetic peak enhanced the photosynthetic efficiency of vegetation in spring and summer and altered the seasonal patterns of vegetation productivity in the SRYR under warming and wetting climates. This study indicated that not only spring and autumn phenology but also summer phenology and maximum carbon uptake capacity should be regarded as crucial indicators regulating the carbon uptake process in alpine ecosystems. This research provides important information about how changes in phenology affect vegetation productivity in alpine ecosystems under global climate warming.

A new temperature–photoperiod coupled phenology module in LPJ-GUESS model v4.1: optimizing estimation of terrestrial carbon and water processes

Abstract. Vegetation phenological shifts impact the terrestrial carbon and water cycle and affect the local climate system through biophysical and biochemical processes. Dynamic global vegetation models (DGVMs), serving as pivotal simulation tools for investigating climate impacts on terrestrial ecosystem processes, incorporate representations of vegetation phenological processes. Nevertheless, it is still a challenge to achieve an accurate simulation of vegetation phenology in the DGVMs. Here, we developed and implemented spring and autumn phenology algorithms into one of the DGVMs, LPJ-GUESS. The new phenology modules are driven by temperature and photoperiod and are parameterized for deciduous trees and shrubs by using remotely sensed phenological observations and the reanalysis data from ERA5. The results show that the LPJ-GUESS with the new phenology modules substantially improved the accuracy in capturing the start and end dates of growing seasons. For the start of the growing season, the simulated RMSE for deciduous trees and shrubs decreased by 8.04 and 17.34 d, respectively. For the autumn phenology, the simulated RMSE for deciduous trees and shrubs decreased by 22.61 and 17.60 d, respectively. Interestingly, we have also found that differences in the simulated start and end of the growing season also alter the simulated ecological niches and competitive relationships among different plant functional types (PFTs) and subsequentially influence the terrestrial carbon and water cycles. Hence, our study highlights the importance of accurate phenology estimation to reduce the uncertainties in plant distribution and terrestrial carbon and water cycling.

Weak evidence of provenance effects in spring phenology across Europe and North America.

Forecasting the biological impacts of climate change requires understanding how species respond to warmer temperatures through interannual flexible variation vs through adaptation to local conditions. Yet, we often lack this information entirely or find conflicting evidence across studies, which is the case for spring phenology. We synthesized common garden studies across Europe and North America that reportedspring event dates for a mix of angiosperm and gymnosperm tree species in the northern hemisphere, capturing data from 384 North American and 101 European provenances (i.e. populations) with observations from 1962 to 2019, alongside autumn event data when provided. Across continents, we found no evidence of provenance effects in spring phenology, but strong clines with latitude and mean annual temperature in autumn. These effects, however, appeared to diverge by continent and species type (gymnosperm vs angiosperm), with particularly pronounced clines in North America in autumn events. Our results suggest flexible, likely plastic responses, in spring phenology with warming, and potential limits - at least in the short term - due to provenance effects for autumn phenology. They also highlight that, after over 250 yr of common garden studies on tree phenology, we still lack a holistic predictive model of clines across species and phenological events.