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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.

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&#95;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.

Continuous long-term temperature sensitivity (S T ) of leaf unfolding date (LUD) and main impacting factors in spring in the period 1978-2014 for 40 plant species in Mudanjiang, Heilongjiang Province, Northeast China, were analyzed by using observation data from the China Phenological Observation Network (CPON), together with the corresponding meteorological data from the China Meteorological Data Service Center. Temperature sensitivities, slopes of the regression between LUD and mean temperature during the optimum preseason (OP), were analyzed using 15-year moving window to determine their temporal trends. Major factors impacting S T were then chosen and evaluated by applying a random sampling method. The results showed that LUD was sensitive to mean temperature in a defined period before phenophase onset for all plant species analyzed. Over the period 1978-2014, the mean S T of LUD for all plant species was - 3.2 ± 0.49 days °C -1 . The moving window analysis revealed that 75% of species displayed increasing S T of LUD, with 55% showing significant increases (P < 0.05). S T for the other 25% exhibited a decreasing trend, with 17% showing significant decreases (P < 0.05). On average, S T increased by 16%, from - 2.8 ± 0.83 days °C -1 during 1980-1994 to - 3.30 ± 0.65 days °C -1 during 2000-2014. For species with later LUD and longer OP, S T tended to increase more, while species with earlier LUD and shorter OP tended to display a decreasing S T . The standard deviation of preseason temperature impacted the temporal variation in S T . Chilling conditions influenced S T for some species, but photoperiod limitation did not have significant or coherent effects on changes in S T .

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 (R 2 ) ranging from 0.37 to 0.67, but fail to simulate the changes in FD accurately (R 2 ranging from 0.09 to 0.18). The growing degree day model could improve the R 2 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.

Temperature sensitivity of plant phenology (S T ) 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 T 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 T to climate warming is misleading, and future S T changes are more uncertain than they suggested.

Advance in spring plant phenology over the last several decades has been found in all continents of the Northern Hemisphere. Compared to the studies detecting phenological trends, the studies investigating the geographical pattern of phenological variability (including mean date and magnitude of variability) are rather limited. In this study, we analyzed spatial pattern of mean date and standard deviation (SD) of first bloom date (FBD) time series (≥15 years) for black locust (Robinia pseudoacacia) at 22 stations in China, common lilac (Syringa vulgaris) at 79 stations in the Western US and Chinese lilac (Syringa chinensis) at 45 stations in the Eastern US. Subsequently, the impact of geographical factors (latitude, longitude, and altitude) on the mean date and SD was quantified by using the multiple regression analysis method. Meanwhile, the relationship between FBD variability and temperature sensitivity of FBD was examined. Results showed that the mean FBD highly depended on geographical factors for all the three species. Compared to the mean date, the dependence of SD of FBD time series on geographical factors was weaker. The geographical factors could only explain 13 to 31 % of spatial variance in SD of FBD. The negative regression coefficients of latitude (P < 0.05 except black locust) indicated that FBD is more variable at lower latitude. At most of stations, significant and negative correlations between FBD and preseason temperature on interannual scale were found, but the temperature sensitivity varied among different stations. The magnitude of temperature sensitivity decreased with increasing latitude. In general, the locations at lower latitude had earlier and more variable spring phenophase and showed stronger phenological response to climate change than the locations at higher latitude.

The change in the phenology of plants or animals reflects the response of living systems to climate change. Numerous studies have reported a consistent earlier spring phenophases in many parts of middle and high latitudes reflecting increasing temperatures with the exception of China. A systematic analysis of Chinese phenological response could complement the assessment of climate change impact for the whole Northern Hemisphere. Here, we analyze 1263 phenological time series (1960-2011, with 20+ years data) of 112 species extracted from 48 studies across 145 sites in China. Taxonomic groups include trees, shrubs, herbs, birds, amphibians and insects. Results demonstrate that 90.8% of the spring/summer phenophases time series show earlier trends and 69.0% of the autumn phenophases records show later trends. For spring/summer phenophases, the mean advance across all the taxonomic groups was 2.75 days decade(-1) ranging between 2.11 and 6.11 days decade(-1) for insects and amphibians, respectively. Herbs and amphibians show significantly stronger advancement than trees, shrubs and insect. The response of phenophases of different taxonomic groups in autumn is more complex: trees, shrubs, herbs and insects show a delay between 1.93 and 4.84 days decade(-1), while other groups reveal an advancement ranging from 1.10 to 2.11 days decade(-1) . For woody plants (including trees and shrubs), the stronger shifts toward earlier spring/summer were detected from the data series starting from more recent decades (1980s-2000s). The geographic factors (latitude, longitude and altitude) could only explain 9% and 3% of the overall variance in spring/summer and autumn phenological trends, respectively. The rate of change in spring/summer phenophase of woody plants (1960s-2000s) generally matches measured local warming across 49 sites in China (R=-0.33, P<0.05)., (© 2014 John Wiley & Sons Ltd.)

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 R² (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⁻¹) 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⁻¹ under the A2 scenario, -1.10 days decade⁻¹ under the A1B scenario and -0.74 days decade⁻¹ 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.

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(-1) and 2.11 to 4.43 days °C⁻¹, 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.

Phenological data of 42 woody plants in a temperate deciduous forest from the Chinese Phenological Observation Network (CPON) and the corresponding meteorological data from 1963 to 2011 in Xi'an, Shaanxi Province, China were collected and analyzed. The first leaf date (FLD), leaf coloring date (LCD) and first flower date (FFD) are revealed as strong biological signals of climatic change. The FLD, LCD and FFD of most species are sensitive to average temperature during a certain period before phenophase onset. Regional precipitation also has a significant impact on phenophases of about half of the species investigated. Affected by climate change, the FLD and FFD of these species have advanced by 5.54 days and 10.20 days on average during 2003-2011 compared with the period 1963-1996, respectively. Meanwhile, the LCD has delayed by 10.59 days, and growing season length has extended 16.13 days. Diverse responses of phenology commonly exist among different species and functional groups during the study period. Especially for FFD, the deviations between the above two periods ranged from -20.68 to -2.79 days; biotic pollination species showed a significantly greater advance than abiotic pollination species. These results were conducive to the understanding of possible changes in both the structure of plant communities and interspecific relationships in the context of climate change.

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]

A comparative assessment of bud and wood phenology could aid a better understanding of tree growth dynamics. However, the reason for asynchronism or synchronism in leaf and cambial phenology remains unclear. To test the assumption that the temporal relationship between the budburst date and the onset date of wood formation is due to their common or different responses to environmental factors, we constructed a wood phenology dataset from previous literature, and compared it with an existing bud phenology dataset in Europe. We selected three common conifers (Larix decidua Mill. Picea abies (L.) H. Karst. and Pinus sylvestris L.) in both datasets and analyzed 909 records of the onset of wood formation at 47 sites and 238,720 records of budburst date at 3051 sites. We quantified chilling accumulation (CA) and forcing requirement (FR) of budburst and onset of wood formation based on common measures of CA and FR. We then constructed negative exponential CA–FR curves for bud and wood phenology separately. The results showed that the median, variance and probability distribution of CA–FR curves varied significantly between bud and wood phenology for three conifers. The different FR under the same chilling condition caused asynchronous bud and wood phenology. Furthermore, the CA–FR curves manifested that wood phenology was more sensitive to chilling than bud phenology. Thus, the FR of the onset of wood formation increases more than that of budburst under the same warming scenarios, explaining the stronger earlier trends in the budburst date than the onset date of woody formation simulated by the process-based model. Our work not only provides a possible explanation for asynchronous bud and wood phenology from the perspective of organ-specific responses to chilling and forcing, but also develops a phenological model for predicting both bud and wood phenology with acceptable uncertainties. [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]

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]

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]

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]

This case study of the Hexi Corridor, Northwestern China, utilizes statistical methods to estimate quantitatively the interaction at a regional level between climate change, ancient social developments, and political coping strategies over the past 2000 years. The data is sourced from high-resolution reconstructions of climate series (temperature and precipitation), and historical records of cultivated land, war, population, and changes in regional administrative systems. The results show that moisture conditions played a more significant role than temperature in driving land reclamation in the Hexi Corridor. Analysis also showed a negative correlation between war frequency and the area of cultivated land in the Corridor over 20-year time intervals. Population growth was found to have a significant positive correlation with the cultivated land area during the study period. The results indicate that a climate-induced decline in agricultural production and the subsequent fluctuations in population could act as a trigger for social unrest, which is especially true at the mutual decadal time-scales. However, the interaction with administrative reform also suggests that, in the face of social and economic turmoil, a reasonable administrative hierarchy could strengthen the social governance of regional government, and promote social stability and economic development at a regional level. The study substantiates this notion with empirical quantitative evidence. [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]

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]

Abstract: The responses of plant phenology to temperature variability have many consequences for ecological processes, agriculture, forestry, and human health. Temperature sensitivity (ST) of phenology could measure how and to what degree plant could phenologically track climate change. The long‐term trends and spatial patterns in ST have been well studied for vegetative phenology such as leaf unfolding, but trends to be expected for reproductive phenology in the future remain unknown. Here we investigate trends and factors driving the temporal variation of ST of first bloom date (FBD). Using the long‐term FBD records during 1963–2013 for common lilac (Syringa vulgaris) from 613 stations in Europe, we compared changes in ST from the beginning to the end of the study period. The Spearman partial correlations were used to assess the importance of four influencing factors. The results showed that the temporal changes in ST of FBD varied considerably among time scales. Mean ST decreased significantly by 0.92 days °C−1 from 1963–1972 to 2004–2013 (P < 0.01), but remained stable from 1963–1987 to 1989–2013. The strength of FBD and temperature relationship, the spring temperature variance, and winter chill all impact ST in an expected way at most stations. No consistent responses of ST on photoperiod were found. Our results imply that the trends and variability in ST of flowering phenology are driving by multiple factors and impacted by time scales. Continued efforts are still needed to further examine the flowering‐temperature relationship for other plant species in other climates and environments using similar methods to our study. [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]

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]

• 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]