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Aim Location Time periods Major taxa studied Methods Results Main conclusions Controlled experiments are increasingly important for investigating how and to what degree plant phenology responds to global climate change. Current experiments underline that chilling and forcing temperatures are two major environmental cues shaping the budburst date of temperate species, but whether experiments could reflect the observed responses to chilling has rarely been examined.Europe and North America.1951–2021.Temperate trees and shrubs.Using an experimental database of budburst dates for 50 species derived from previous literature and observational data of the same species at 12,579 stations in Europe and 1469 stations in the USA, we compared the response of forcing requirement (FR) of the budburst date to chilling accumulation (CA) between observations and experiments using a common measure of FR and CA.The median, variance and probability distribution of CA‐FR curves differed significantly between experiments and observations in most cases. The distinction in chilling effects between experiments and observations could be attributed to the difference in thermal space, heat stress, genetic variation among provenances, different forcing treatments adopted and plant materials used in the experiments.Our results suggest that the uncertainty of phenological models based solely on the experimental data needs to be re‐evaluated when predicting future spring phenological responses across broad spatial scales. [ABSTRACT FROM AUTHOR]

Plant phenology refers to cyclic plant growth events, and is one of the most important indicators of climate change. Integration of plant phenology information is crucial for understanding the ecosystem response to global change and modeling the material and energy balance of terrestrial ecosystems. Utilizing 24 552 in situ phenological observations of 24 representative woody plant species from the Chinese Phenology Observation Network (CPON), we have developed maps delineating species phenology (SP) and ground phenology (GP) of forests over China from 1951 to 2020. These maps offer a detailed spatial resolution of 0.1 ∘ and a temporal resolution of 1 d. Our method involves a model-based approach to upscale in situ phenological observations to SP maps, followed by the application of weighted average and quantile methods to derive GP maps from the SP data. The resulting SP maps for the 24 woody plants exhibit a high degree of concordance with in situ observations, manifesting an average deviation of 6.9 d for spring and 10.8 d for autumn phenological events. Moreover, the GP maps demonstrate robust alignment with extant land surface phenology (LSP) products sourced from remote sensing data, particularly within deciduous forests, where the average discrepancy is 8.8 d in spring and 15.1 d in autumn. This dataset provides an independent and reliable phenology data source for China on a long-time scale of 70 years, and contributes to more comprehensive research on plant phenology and climate change at both regional and national scales. The dataset can be accessed at 10.57760/sciencedb.07995 (Zhu and Dai, 2023). [ABSTRACT FROM AUTHOR]

Winter temperature‐related chilling and spring temperature‐related forcing are two major environmental cues shaping the leaf‐out date of temperate species. To what degree insufficient chilling caused by winter warming would slow phenological responses to spring warming remains unclear. Using 27,071 time series of leaf‐out dates for 16 tree species in Europe, we constructed a phenological model based on the linear or exponential function between the chilling accumulation (CA) and forcing requirements (FR) of leaf‐out. We further used the phenological model to quantify the relative contributions of chilling and forcing on past and future spring phenological change. The results showed that the delaying effect of decreased chilling on the leaf‐out date was prevalent in natural conditions, as more than 99% of time series exhibited a negative relationship between CA and FR. The reduction in chilling linked to winter warming from 1951 to 2014 could offset about one half of the spring phenological advance caused by the increase in forcing. In future warming scenarios, if the same model is used and a linear, stable correlation between CA and FR is assumed, declining chilling will continuously offset the advance of leaf‐out to a similar degree. Our study stresses the importance of assessing the antagonistic effects of winter and spring warming on leaf‐out phenology. [ABSTRACT FROM AUTHOR]

Spring warming could induce earlier leaf-out or flowering of temperate plant species, and decreased chilling in winter has a delaying effect on spring phenology. However, the relative contribution of the decreased chilling and increased forcing on spring phenological change is unclear. Here, we analyzed the experimental data for 14 temperate woody species in Beijing, China and quantified the forcing requirements (FR) of spring phenology and chilling sensitivity (the ratio of the FR at the low chilling condition to the FR at the high chilling condition) for each species. Furthermore, using species-specific functions between the amount of chilling and FR, we established a phenological model to simulate the annual onset dates of spring events during the past 69 years (1952–2020) and in the future (2021–2099) under RCP 4.5 and RCP 8.5 climate scenarios. We also developed a novel method to quantitatively split the predicted phenological change into the effects caused by changes in forcing and those caused by changes in chilling. The results show that the FR of spring events decreased with the increase in the amount of chilling, and this relationship could be described as an exponential decay function. The basic FR (the FR at the high chilling condition) and chilling sensitivity varied greatly among species. In the 1952–2020 period, the advancing effect of increased forcing was stronger than the effect of chilling, leading to earlier spring events with a mean trend of −1.96 days/decade. In future climate scenarios, the spring phenology of temperate species would continue to advance but will be limited by the decreased chilling. The species with lower chilling sensitivities showed stronger trends than those with high chilling sensitivities. Our results suggested that the delaying effect of declining chilling could only slow down the spring phenological advance to a certain extent in the future. [ABSTRACT FROM AUTHOR]

Mountain ecosystems are sensitive to climate change, and vegetation phenology provides one of the best signals to exemplify ecosystem responses to climate change. Vegetation phenology of mountain ecosystems is usually characterized with an elevational pattern, with the growing season starts earlier and ends later in lower versus higher elevations. With climate change, this elevational gradient of vegetation phenology is likely to shift as well. However, both the patterns and the underlying driving forces for potential changes in this elevational gradient of vegetation phenology are still unclear. Here, we used 500‐m resolutioned normalized difference vegetation index (NDVI) data from Moderate Resolution Imaging Spectroradiometer (MODIS) for the period of 2001 to 2017 to investigate changes in the start of growing season (SOS) along the elevational gradient for six mountains in northern China dominated by broadleaf deciduous forests. We found that while SOS consistently advanced for most of the pixels, the elevational lapse rate of SOS (SE) showed various trends for different mountains. Specifically, SE showed a significant (p‐value <.05) decreasing trend for the two southernmost mountains, indicating an increasing elevational synchronization in SOS. However, such phenological synchronization was not found in other temperate mountains. As warming has caused relatively consistent increases in heat forcing across different elevations and among different mountains but has led to highly various changes in chilling hours between high and low elevations, we suggested that the distinctive pattern in elevational synchronicity of spring phenology between southern and northern mountains in temperate China was primarily due to their different recent changes in chilling hours. Our work provides a novel key hypothesis for explaining the divergent changes in elevational gradients of vegetation phenology that can be tested in other regions for mountain ecosystems. [ABSTRACT FROM AUTHOR]

Autumn phenology variation in temperate grassland is a direct indicator of land degradation, and a phenology‐based model has been used to simulate human‐induced land degradation. It is important to reveal how environmental factors influence autumn phenology of herbaceous plants. In this study, we examined the effects of temperature, photoperiod, and soil moisture on the leaf withering date (LWD) of four herbaceous species (Xanthium sibiricum, Plantago asiatica, Iris lactea, and Taraxacum mongolicum) at 15 sites in the Inner Mongolian steppe from 1981 to 2012. Then, we developed two process‐based models coupling the effects of the three factors based on an existing cold degree–days (CDD)‐based model for predicting the LWD of the four species. The new models showed better accuracy than CDD model during validation. The model structure and parameters suggested that soil moisture likely influenced LWD nonlinearly and presented a multiplicative interaction with temperature and photoperiod. In addition, photoperiod had divergent effects on the accumulation of cold temperature for different species and sites. For X. sibiricum, the photoperiod only determined the start of cold temperature accumulation. Considering the carryover effect of spring phenology did not improve model performance. Our study also showed that local adaptation of plants was commonly ignored when using same parameters in model calibration with observation data from multiple sites; however, model calibrations using site‐specific data were less stable, and the parameters could not be extrapolated across space. It will be necessary to establish a generalized regional model driven by both climatic and genotypic factors in future research. [ABSTRACT FROM AUTHOR]

Phenological records in historical documents have been proven to be of unique value for reconstructing past climate changes. As a literary genre, poetry reached its peak in the Tang and Song dynasties (618–1279 CE) in China. Sources from this period could provide abundant phenological records in the absence of phenological observations. However, the reliability of phenological records from poems, as well as their processing methods, remains to be comprehensively summarized and discussed. In this paper, after introducing the certainties and uncertainties of phenological information in poems, the key processing steps and methods for deriving phenological records from poems and using them in past climate change studies are discussed: (1) two principles, namely the principle of conservatism and the principle of personal experience, should be followed to reduce uncertainties; (2) the phenological records in poems need to be filtered according to the types of poems, background information, rhetorical devices, spatial representations, and human influence; (3) animals and plants are identified at the species level according to their modern distributions and the sequences of different phenophases; (4) phenophases in poems are identified on the basis of modern observation criteria; (5) the dates and sites for the phenophases in poems are confirmed from background information and related studies. As a case study, 86 phenological records from poems of the Tang Dynasty in the Guanzhong region in China were extracted to reconstruct annual temperature anomalies in specific years in the period between 600 and 900 CE. Following this, the reconstruction from poems was compared with relevant reconstructions in published studies to demonstrate the validity and reliability of phenological records from poems in studies of past climate changes. This paper reveals that the phenological records from poems could be useful evidence of past climate changes after being scientifically processed. This could provide an important reference for future studies in this domain, in both principle and methodology, pursuant of extracting and applying phenological records from poems for larger areas and different periods in Chinese history. [ABSTRACT FROM AUTHOR]

Climate change could affect botanical tourism by altering the plant phenology (e.g., flowering and leaf coloring date) and the physical comfort of tourists. To date, few studies have simultaneously considered the influence of plant phenology and physical comfort on the travel suitability of botanical tourism. Taking Beijing as an example, this study used phenological data of 73 species from 1963 to 2017 to construct a phenological ornamental index (POI) according to the flowering and leaf coloring date of ornamental plant. The climate comfort index (CCI) of tourism was calculated by using meteorological data of the corresponding periods. Finally, the travel suitability index (TSI) was constructed by integrating the two indices (POI and CCI). The POI showed that the best period for spring flower viewing was from April 4 to May 10, while the best period for autumn leaves viewing was from October 11 to November 6 on average. According to the variation of the CCI within the year, the most comfortable period for spring tourism was matched with the best period for spring flower viewing (April 4 to June 1), but the most comfortable period for autumn tourism (September 4 to October 19) was earlier than the best period for autumn leaves viewing. The TSI indicated that the best periods for spring and autumn botanical tourism were April 7 to May 10 and October 10 to November 7, respectively. Based on the climate data under different scenarios (representative concentration pathways 4.5 and 8.5), we simulated the climate and phenological suitability for botanical tourism in the next thirty years. The results showed that the best period for spring botanical tourism during 2040–2050 was earlier and the period for autumn botanical tourism was later than that in the past 55 years. Meanwhile, the duration would shorten by 2–7 days for both seasons. This study provided a reference for assessing the impact of global climate change on the best season of botanical tourism. [ABSTRACT FROM AUTHOR]

Changes in crop phenology may reflect crop responses and adaptation to climate change. In this study, we used observational data (1981–2010) of maize (Zea mays L.) phenology from agricultural meteorological stations in the major maize-growing regions of China to examine spatiotemporal changes in the phenologies and growth periods and associated sensitivities to changes in major climatic factors. The results showed that, during the study period, sowing, tasseling, and maturity dates for maize were delayed in most maize growth regions. The lengths of vegetative growth period (VGP, from emergence to tasseling) were increased in spring and spring-summer maize growth regions and decreased in summer maize growth regions; the lengths of the maize reproductive growth period (RGP, from tasseling to maturity) and whole growth period (WGP, from emergence to maturity) were mostly extended (except NWMR_SU). Overall, sensitivity of maize VGP, RGP, and WGP was negatively related to average temperature (P < 0.01) and positively related to precipitation and sunshine hours (P < 0.01); there were variations in sensitivity among regions and data station locations. Precipitation was a driver of growth period length in the northwest inland maize region, whereas mean temperature and sunshine hours were drivers in the southwest hilly region. [ABSTRACT FROM AUTHOR]

In a natural ecosystem or as climatic climax community, grassland is relatively dry with a strongly seasonal climate, and sensitive to climatic changes. Most of the previous studies used remote sensing data to investigate the phenological response of grassland to climate change, while ground‐based studies covering a large geographic area were limited. In this study, using the long‐term phenological data (1981–2012) of 16 herbaceous species observed at 20 stations in Inner Mongolia, China, we first investigated the trends in three spring phenophases, including the dates of bud‐burst, first leaf unfolding, and 50% of leaf unfolding. Subsequently, multiple linear regressions between phenophases and four climatic factors (spring temperature, soil moisture, chilling temperature, and insolation) were performed to determine the relative importance of each factor on the spring phenology. To validate the resulted regression coefficients, we developed a controlled environment to investigate the factors regulating the leaf unfolding time of one dominant species (Leymus chinensis). The results showed that the study area became warmer and drier from 1981 to 2012. However, the overall changes in spring phenophases were not apparent, as there was a similar proportion of significant earlier or later trends. Such phenological changes were driven by multiple climatic factors. The warmer temperature would advance the spring phenophases, while lower soil moisture would delay them. The impact of soil moisture was significant in the experimental data, but not significant in the observation data. In addition, leaf unfolding became faster when L. chinensis experienced more chilling days, but this effect was difficult to be detected in observation data due to the weak sensitivity of the leaf unfolding time to chilling days. These findings can help us to understand how the spring phenology of typical herbaceous species responds to multiple climatic factors under the background of climate change. [ABSTRACT FROM AUTHOR]

• We used three machine learning (ML) algorithms to simulate leaf senescence date. • The ML-based models outperformed process-based models for six tree species. • Interpretable ML algorithms could decipher the effects of multiple driving factors. Predicting tree phenology accurately is essential for assessing the impact of climate change on ecosystems. However, the current process-based models are still hard to fully explain and quantify the effects of multiple biotic and environmental factors (e.g., spring phenology, local adaptation, productivity, climatic variables) on autumn phenology. Using leaf senescence data (1980-2015) of 232766 site-year records (3020 sites and 6 deciduous tree species) in Europe, we first calibrated and evaluated 4 process-based models developed by previous studies. Subsequently, by using different machine learning (ML) algorithms (RF, EBM, and GAMI-Net), we developed 3 ML-based models for predicting the leaf senescence date of the same species and quantifying the importance and response function of 63 biotic or environmental variables. We found that the root mean square error (RMSE) of process-based models (averaged from all species) for the test dataset ranged from 11.97 to 12.91 days. The ML-based models outperformed process-based models for all species, with RMSE ranging from 10.01 to 10.58 days. For most species, the recently developed ML algorithms (EBM and GAMI-Net) are more effective than the classical RF algorithm developed in the early 21th century. Besides the temperature and photoperiod in autumn, the geographic factors (especially elevation, longitude, and latitude) were identified as the most important variables in the ML-based models, implying that leaf senescence date is an adaptive trait. Furthermore, for most species investigated, earlier leaf-out dates tended to advance the leaf senescence date. Our results highlight that the ML algorithms not only could effectively improve the performance of the process-based models for predicting the leaf senescence date, but also help to understand the nonlinear and interactive effects of multiple driving factors on autumn phenology. [ABSTRACT FROM AUTHOR]

Existing evidence demonstrates that the first flowering date (FFD) of most plant species became earlier in response to temperature increase over the past several decades. However, the studies on changes in flowering duration (FD) were limited. By using the non-parametric Theil–Sen estimator, this study investigated the temporal trends in 127 time series of FFD, end of flowering date (EFD), and FD of 97 woody plants from 1963 to 2014 at three sites (Harbin, Beijing, and Xi'an) in North China. The relationship between flowering phenophases and temperature was analyzed using two phenological models. The results showed that most of FFD and EFD time series exhibited an apparent advancing trend. Among them, trends of 52.0% (40.9%) of FFD (EFD) time series were significant (P < 0.05). FFD and EFD time series (95.3 and 89.8%, respectively) responded negatively and significantly to preseason temperature (P < 0.05). The direction of FD changes varied among sites and species. On average, a shortening trend of FD was observed at Harbin (−0.51 days decade−1), with 7.5% of species significantly. However, FD on average extended by 0.42 and 0.93 days decade−1 at Beijing (24.5% significantly) and Xi'an (28.9% significantly), respectively. The regression models could simulate the interannual changes in FFD and EFD with the mean goodness of fit (R2) ranging from 0.37 to 0.67, but fail to simulate the changes in FD accurately (R2 ranging from 0.09 to 0.18). The growing degree day model could improve the R2 for simulating FFD and EFD except for FD. Therefore, more phenological models need to be tested, and more drivers of FD need to be further investigated. [ABSTRACT FROM AUTHOR]

Autumn phenology plays a critical role in terrestrial ecosystem circulations. However, the changes in autumn phenology and their correlation with temperature remain uncertain because mean temperature alone was not able to determine the changes in autumn phenology at various sites. Here, the leaf coloring season (LCS) was defined as the period when the leaves of more than half of the species had recognized changes in color. We systematically studied the changes in peak, start, end, and duration of LCS and their correlations with five temperature parameters (mean temperature, accumulated cold temperature, day temperature, night temperature, and temperature difference between day and night) in four periods. Similarly to previous findings, the start date of LCS advanced and the end of LCS delayed over the past 50 years, which consequently led to a lengthened duration of LCS in Xi'an, Harbin, Minqin, and Shenyang. In general, the rise in mean temperature, day temperature, and night temperature would delay the peak, start, and end of LCS and lengthen the duration of LCS in most cases. We also proved that the changes in LCS metrics not only could completely be explained by mean temperature but also were influenced by day temperature, night temperature, temperature difference, and even other climatic factors such as precipitation, at different sites. [ABSTRACT FROM AUTHOR]

Temperature sensitivity (ST) of phenology, defined as the shift of phenophase with per unit change of preseason temperature, has been widely used to quantify phenological response to climate change. The spatial variation in ST of spring phenology has been well studied for several woody plants, but how to explain it became a challenge. Several hypotheses to explain the spatial variation in ST have been proposed, but studies examining all potential factors together were very limited. In this study, using first flowering date (FFD) data for five widespread woody plants at 47 stations in China and the other five species at 421 stations in central Europe during 1964–2014, we calculated ST by using the Sen's slope of FFD on mean preseason temperature for each species at each station. Subsequently, multiple regression analysis was applied to examining whether ST followed the geographical (latitudinal, longitudinal, or vertical) gradients. At last, four potential influencing factors of ST were tested by Spearman partial correlation analysis. We found that ST of FFD was higher at lower latitude for most species in China. However, in central Europe, the variation of ST did not follow the geographical gradient for most species. Only one species (Fraxinus excelsior) showed a latitudinal gradient, and one (Betula pendula) showed a longitudinal gradient. For most species in both regions, the strength of FFD–temperature relationship and the preseason length could account for the spatial variation of ST to a more considerable extent compared to preseason temperature variance and chilling conditions. Our results suggest that we need to consider the effects of multiple factors on phenological response to temperature when simulating future phenological change. The spatial patterns of the temperature sensitivity (ST) of first flowering date (FFD) for five woody plants in China. [ABSTRACT FROM AUTHOR]

Autumn phenology can regulate climate-biosphere interactions and net primary production within the ecosystem. However, studies modeling spatiotemporal variations in leaf coloring date (LCD) remain limited, especially for species-specific phenology on a continental scale. Aiming to simulate spatiotemporal variations in LCD in three widespread tree species ( Ulmus pumila , Fraxinus chinensis, and Robinia pseudoacacia ) across China, we used phenological observation records acquired from the China Phenology Observation Network (CPON) during 1963–2010 to establish and compare three LCD models (multiple regression (MA), temperature-photoperiod (TP), spring-influenced autumn (SIA)). Subsequently, we simulated the mean LCD of the three species using the most effective model and examined the effect of geographical factors (i.e., latitude, longitude, and altitude) on LCD through multiple regression analysis. Empirical Orthogonal Function (EOF) analysis was applied to identifying the most extensive and influential spatial modes of LCD variability and how they changed with time. The results showed that: (1) The LCD of F. chinensis was fitted better with the statistical model using monthly temperature as the independent variables (MR model). The LCD of F. chinensis was delayed by a temperature rise in August and September, but advanced by a temperature rise in May and June. The LCD of U. pumila and R. pseudoacacia was fitted better with the TP and SIA models, in which the photoperiod determined the date when the cold temperature started to accumulate. (2) The simulated mean LCD of U. pumila , F. chinensis, and R. pseudoacacia was October 6, October 16 and October 22, respectively. Latitude, longitude, and altitude had a significant influence on mean LCD of the three tree species. With increasing latitude and altitude, the LCD of all three species became earlier. However, the impact of longitude on the mean LCD varied among species. (3) For all the three species, the first EOF mode presented a consistent pattern of LCD variability across space, suggesting that an earlier or later LCD occurred simultaneously in the whole China. Meanwhile, the second EOF mode exhibited contrary signals of LCD variability in the north and south for F. chinensis and R. pseudoacacia . Over the past 50 years, the LCD of all the three species has delayed. The delaying trend revealed by the first EOF mode was 1.25 ( p < 0.01), 0.21 ( p < 0.01), and 0.53 days/decade (not significant) for U. pumila , F. chinensis and R. pseudoacacia , respectively. These results provide the basis for a better understanding of the phenology process in autumn and how it responds to climate change. [ABSTRACT FROM AUTHOR]

Plant phenology is influenced by various climatic factors such as temperature, precipitation, insolation, and humidity, etc. Among these factors, temperature and precipitation are proved to be the most important. However, the relative importance of these two factors is different among various phenophases and regions and is seldom discussed along environmental gradients. Based on normalized difference vegetation index (NDVI) data from the NDVI3g dataset and using the mid-point method, we extracted the start date of the growing season (SOG) and the end date of the growing season (EOG) in northern China during 1982–2012. To determine which climate factor was more influential on plant phenology, partial correlation analysis was applied to analyse the spatial difference between the response of SOG and EOG to temperature and precipitation. Finally, we calculated the temperature and precipitation sensitivities of the SOG and EOG. The results showed that: (1) SOG displayed an advancing trend in most regions, while EOG was delayed for all the vegetation types during 1982–2012. (2) SOG was mainly triggered by preseason temperature. The increase in temperature caused an overall advance in SOG. However, the relationship between SOG and precipitation varied among different vegetation types. Regarding EOG, precipitation had greater impacts than temperature in relatively arid environments, such as deserts, steppes and meadow biomes. (3) The response of vegetation phenology (both SOG and EOG) to temperature became stronger with increasing preseason precipitation across space. The response of EOG to precipitation became weaker from arid regions to relatively humid regions. These results provide a better understanding of the spatial pattern of the phenological response along the precipitation gradient and a reference for assessing impacts of future climate change on vegetation phenology, especially in transitional and fragile zones. [ABSTRACT FROM AUTHOR]

The impact of spring temperature forcing on the timing of leaf unfolding of plants (temperature sensitivity, S) is one important indicator of how and to what degree plant species track climate change. Fu et al. (Nature 526:104-107, 2015) found that S has significantly decreased from the 1980-1994 to the 1999-2013 period for seven mid-latitude tree species in Europe. However, long-term changes in S over the past 60 years are still not clear. Here, using in situ observations of leaf unfolding for seven dominant European tree species, we analyze the temporal change in S over decadal time scales extending the data series back to 1951. Our results demonstrate that S shows no statistically significant change within shifting 30-year windows from 1951 to 2013 and remains stable between 1951-1980 and 1984-2013 (3.6 versus 3.7 days °C). This result suggests that the significant decrease in S over the past 33 years could not be sustained when examining the trends of phenological responses in the long run. Therefore, we could not conclude that tree spring phenology advances will slow down in the future, and the S changes in warming scenarios are still uncertain. [ABSTRACT FROM AUTHOR]

ABSTRACT Phenology can be used to track plant responses to climate change. In China, several studies have found the earlier trends of spring phenophases over the past 50 years. However, few studies put these phenological changes into historical perspective. Based on specific phenophases records from historical diaries and Chinese Phenological Observation Network, we developed spring phenology index ( SPI) time series in temperate and subtropical regions of eastern China from 1850 to 2009. We firstly compare the temporal change of SPI and seasonal temperature anomaly. Subsequently, we search for common shifts in phenological and temperature time series by applying the moving t-test method, and discuss temperature sensitivity of SPI by using the moving linear regression method for both regions. Results show that the SPI in temperate region revealed lower interannual variability than in subtropical region, while the seasonal temperature variability was higher in temperate region. In temperate region, the timing of significant shift towards earlier SPI (in 1979) coincides with the timing of shift in spring temperature time series. The temperature sensitivities of SPI differ among the two regions. The mean sensitivity of SPI to spring temperature in subtropical region (−3.7 days °C−1) is stronger than in temperate region (−2.5 days °C−1). The temperature sensitivity of SPI varies among consecutive 30-year periods. In recent three decades, temperature sensitivity of spring phenophases became stronger in both regions. [ABSTRACT FROM AUTHOR]

Temperature sensitivity of plant phenology (S) is a determining factor of as to what degree climate change impacts on plant species. Fu et al . (Int J Biometeorol 60:1611-1613, 2016) claimed that long long-term linear trends mask phenological shifts. However, the decreased and increased S was both found in warming scenarios. The conceptual scheme telling the nonlinear relationship between spring temperature and leaf unfolding date proposed by Fu et al . (Int J Biometeorol 60:1611-1613, 2016) cannot be supported by observation data across Europe. Therefore, linking declined S to climate warming is misleading, and future S changes are more uncertain than they suggested. [ABSTRACT FROM AUTHOR]

Recent shifts in phenology reflect the biological response to current climate change. Aiming to enhance our understanding of phenological responses to climate change, we developed, calibrated and validated spatio-temporal models of first leaf date (FLD) for 20 broadleaved deciduous plants in China. Using daily meteorological data from the Chinese Meteorological Administration and the Community Climate System Model, version 3 (CCSM3) created using three IPCC scenarios (A2, A1B and B1), we described the FLD time series of each species over the past 50 years, extrapolating from these results to simulate estimated FLD changes for each species during the twenty-first century. Model validation suggests that our spatio-temporal models can simulate FLD accurately with R (explained variance) >0.60. Model simulations show that, from 1952 to 2007, the FLD in China advanced at a rate of −1.14 days decade on average. Furthermore, changes in FLD showed noticeable variation between regions, with clearer advances observed in the north than in the south of the country. The model indicates that the advances in FLD observed from 1952-2007 in China will continue over the twenty-first century, although significant differences among species and different climate scenarios are expected. The average trend of FLD advance in China during the twenty-first century is modeled as being −1.92 days decade under the A2 scenario, −1.10 days decade under the A1B scenario and −0.74 days decade under the B2 scenario. The spatial pattern of FLD change for the period 2011-2099 is modeled as being similar but showing some difference from patterns in the 1952-2007 period. At the interspecific level, early-leafing species were found to show a greater advance in FLD, while species with larger distributions tended to show a weaker advance in FLD. These simulated changes in phenology may have significant implications for plant distribution as well as ecosystem structure and function. [ABSTRACT FROM AUTHOR]

Leaf phenology has been shown to be one of the most important indicators of the effects of climate change on biological systems. Few such studies have, however, been published detailing the relationship between phenology and climate change in Asian contexts. With the aim of quantifying species' phenological responsiveness to temperature and deepening understandings of spatial patterns of phenological and climate change in China, this study analyzes the first leaf date (FLD) and the leaf coloring date (LCD) from datasets of four woody plant species, Robinia pseudoacacia, Ulmus pumila, Salix babylonica, and Melia azedarach, collected from 1963 to 2009 at 47 Chinese Phenological Observation Network (CPON) stations spread across China (from 21° to 50° N). The results of this study show that changes in temperatures in the range of 39-43 days preceding the date of FLD of these plants affected annual variations in FLD, while annual variations in temperature in the range of 71-85 days preceding LCD of these plants affected the date of LCD. Average temperature sensitivity of FLD and LCD for these plants was −3.93 to 3.30 days °C and 2.11 to 4.43 days °C, respectively. Temperature sensitivity of FLD was found to be stronger at lower latitudes or altitude as well as in more continental climates, while the response of LCD showed no consistent pattern. Within the context of significant warming across China during the study period, FLD was found to have advanced by 5.44 days from 1960 to 2009; over the same period, LCD was found to have been delayed by 4.56 days. These findings indicate that the length of the growing season of the four plant species studied was extended by a total of 10.00 days from 1960 to 2009. They also indicate that phenological response to climate is highly heterogeneous spatially. [ABSTRACT FROM AUTHOR]

• Chilling accumulation (CA) and heat requirement (HR) are determined for 14 species. • An inconsistent CA-HR relationship between years was found. • Using one-year experimental data to simulate spring phenology is inappropriate. • Current chilling models need to be improved by performing more experiments. The controlled experiments are increasingly used to examine the effect of chilling on the spring phenology of temperate woody plants. Previous studies demonstrated a delaying effect of lack of chilling on spring events due to a negative relationship between chilling accumulation (CA) and heat requirement (HR). However, most experiments only lasted for one year, and limited studies examined the consistency of the CA-HR relationship between years. Here, we conducted a twig experiment with 14 temperate woody species in two winter seasons (2018/2019 and 2019/2020) to assess the between-year difference in the impact of chilling on HR of flowering or leaf-out. The CA and HR for each species in each year were estimated based on the common-used chilling and forcing model. The results showed that 8 of 14 species exhibited a significantly different slope or intercept of the linear function of HR against CA between two winter seasons. Using the first-year CA-HR function to simulate the second-year spring events would result in large uncertainties with root-mean-square errors ranging from 1.3 to 9.9 days. In addition to the original chilling model, we further selected an optimal one for each species from another 8 chilling models. The optimal chilling models varied among species and could reduce the RMSE of phenological simulation of 10 species by 0.1–3.7 days. Our results suggest that using one-year experimental data to develop the phenological model or estimate the chilling and heat requirement of spring events is unsuitable. Further studies are still needed to better quantify the rate of chilling under different temperature conditions for various species. [ABSTRACT FROM AUTHOR]

Confirming the results of previous regional studies on changes in first bloom dates (FBD) in China, this study provides evidence that complements conclusions drawn from studies of phenological changes in other dynamic climate systems in the Northern Hemisphere. Furthermore, increased occurrences of yearly second blooms (YSB) further reinforce results derived from other studies indicating a recent trend of generalized climate warming across China. Additionally, ascertaining changes in FBD and YSB against a recent background not only provides a hitherto poorly formulated autumnal equivalent to the well-studied shifts in FBD, but also formulates both spring and autumn flowering changes in recent years. Data in this study are derived from observations made from 1963 to 2006 by the Chinese Phenological Observation Network (CPON)-a nationwide system of monitoring stations that has made observations of over 173 species from across China since 1963. At each site, the mean value of each species' annual deviation and spring mean surface temperatures were calculated. For each species, years and locations were also recorded for species in which second blooms (YSB) occurred. Of the 46 FBD samples, 31 showed advances from the mean, blooming earlier over the course of the study period. Notably, although only 8 of the 46 FBD samples showed significance levels of 0.1 or better, the average FBD did advance by 5.3 days. After the 1980s, the frequency of YSB occurrence remained steady, declining a little from the peak in the 1980s, but still exhibiting occurrences far more than were observed earlier. The data from this study clearly indicate that both the phenological advance of FBD in spring and the increased occurrence of YSB are consistent with climate warming. [ABSTRACT FROM AUTHOR]

Spring warming substantially advances leaf unfolding and flowering time for perennials. Winter warming, however, decreases chilling accumulation (CA), which increases the heat requirement (HR) and acts to delay spring phenology. Whether or not this negative CA-HR relationship is correctly interpreted in ecosystem models remains unknown. Using leaf unfolding and flowering data for 30 perennials in Europe, here we show that more than half (7 of 12) of current chilling models are invalid since they show a positive CA-HR relationship. The possible reason is that they overlook the effect of freezing temperature on dormancy release. Overestimation of the advance in spring phenology by the end of this century by these invalid chilling models could be as large as 7.6 and 20.0 days under RCPs 4.5 and 8.5, respectively. Our results highlight the need for a better representation of chilling for the correct understanding of spring phenological responses to future climate change. Climate warming is advancing spring leaf unfolding, but it is also reducing the cold periods that many trees require to break winter dormancy. Here, the authors show that 7 of 12 current chilling models fail to account for the correct relationship between chilling accumulation and heat requirement, leading to substantial overestimates of the advance of spring phenology under climate change. [ABSTRACT FROM AUTHOR]

Existing evidence of plant phenological change to temperature increase demonstrates that the phenological responsiveness is greater at warmer locations and in early-season plant species. Explanations of these findings are scarce and not settled. Some studies suggest considering phenology as one functional trait within a plant's life history strategy. In this study, we adapt an existing phenological model to derive a generalized sensitivity in space (SpaceSens) model for calculating temperature sensitivity of spring plant phenophases across species and locations. The SpaceSens model have three parameters, including the temperature at the onset date of phenophases (Tp), base temperature threshold (Tb) and the length of period (L) used to calculate the mean temperature when performing regression analysis between phenology and temperature. A case study on first leaf date of 20 plant species from eastern China shows that the change of Tp and Tb among different species accounts for interspecific difference in temperature sensitivity. Moreover, lower Tp at lower latitude is the main reason why spring phenological responsiveness is greater there. These results suggest that spring phenophases of more responsive, early-season plants (especially in low latitude) will probably continue to diverge from the other late-season plants with temperatures warming in the future. [ABSTRACT FROM AUTHOR]

The global climate change-induced advanced spring green-up dates (GUDs) of vegetation in the past decades have been well documented. However, anthropogenic effects on GUDs are still unclear, and the impacts of widespread cropland expansion on GUDs are rarely quantified. Here, we examine the differences in GUDs between agroecosystems and natural ecosystems using both satellite and in-situ observations across China's ecosystems with a latitude ≥ 30°N and explore the potential effects of cropland expansion on vegetation spring phenology. We find that agroecosystems had significantly later GUDs than adjacent natural ecosystems according to satellite observations, with a delay of 22.26 ± 16.32 (Mean ± 1STD) days and 18.11 ± 11.75 days compared with woodland and grassland ecosystems, respectively. The later GUDs for agroecosystems is more distinct in the Northeast China Plain and Xinjiang Oasis region (>30 days), where land reclamation was remarkable. We also find a distinct delayed GUD trend (> 5 day/yr, p < 0.001) during 2001–2014 in a cropland expansion region in Xinjiang Province, which is much higher than the usual advancement of GUDs due to warming (usually ≤ 1 day/yr). In-situ and satellite observations of delayed GUDs agree better in agroecosystems than in forest and grassland ecosystems. More attention is needed to better understand the important role of cropland expansion in driving inter-annual change of vegetation spring phenology in addition to climate change, and integration of realistic crop green-up timing into climate models is also needed for accurate climate simulations. • Differences in the vegetation green-up dates (GUDs) between agroecosystems and natural ecosystems are quantified. • Cropland expansion delayed vegetation GUDs greatly according to satellite and in-situ observations. • Effects of cropland expansion on spring phenology change trends cannot be overlooked. [ABSTRACT FROM AUTHOR]

• Spring phenological traits of plant species in Northeast China are analyzed. • Spring phenological traits of plants are phylogenetically conserved. • Reproductive phenology is more phylogenetically conserved than vegetative phenology. • Native climate has a stronger effect than phylogeny on spring phenological traits. The effects of climate change on plant phenology have been widely recognized around the world. However, the effect of plant internal factors (such as phylogeny) on the variations in phenology among plant species remains unclear. In this study, we investigated the phylogenetic conservatism in spring phenological traits using phylogenetic signal and evolutionary models, including Brownian motion (BM) model, Ornstein–Uhlenbeck (OU) model and white noise (WN) model, based on the phenological data of 48 temperate plant species in Northeast China. We also explored the relative contributions of phylogeny and adaptation to native climate (i.e., the climate in native range of species) to the variations in the phenological traits among species using phylogenetic eigenvector regression and variance partitioning analysis. The results showed thatspring phenological traits conformed to the OU model, indicating thatspring traits were phylogenetically conserved. The effect of phylogeny on flowering traits was stronger than that on leaf-out traits. Additionally, the adaptation to native climate contributed more to the variations in spring phenological traits among species than phylogeny, and adaptation to native climate explained more variations in leaf-out traits than in flowering traits. Our results suggested that the spring phenological traits were constrained by both phylogeny and adaptation to native climate. However, the adaptation to native climate had a stronger effect on the variations in phenological traits than phylogeny. Therefore, the degree of similarity in spring phenological traits across closely related species depends on the degree of similarity in the environmental conditions where these close relatives are distributed. [ABSTRACT FROM AUTHOR]