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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]

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]

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]

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]

Continuous long-term temperature sensitivity (ST) 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 ST 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 ST 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 ST of LUD, with 55% showing significant increases (P < 0.05). ST for the other 25% exhibited a decreasing trend, with 17% showing significant decreases (P < 0.05). On average, ST 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, ST tended to increase more, while species with earlier LUD and shorter OP tended to display a decreasing ST. The standard deviation of preseason temperature impacted the temporal variation in ST. Chilling conditions influenced ST for some species, but photoperiod limitation did not have significant or coherent effects on changes in ST. [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]

Phenological data obtained from historical documents constitute highly important ecological evidence for the pre-instrumental period, and can be used in analyzing climatic change in history. In this study, 87 phenological records about seasonality of non-biological events (e.g., first frost date), agriculture and ornamental plants (e.g., first flowering date) over 77 years were extracted from historical documents from the Sui and Tang dynasties in China to reconstruct the winter half-year (from October to next April) temperatures in the Guanzhong Area (located in central China) from 600 to 902 AD. Transfer functions between temperature and phenophases with significant correlations were established by using modern observation data. Temperatures from the study period were reconstructed by applying the transfer functions to historical phenological data. The reconstruction indicates that the winter half-year temperatures during 600-902 AD were 0.23°C higher than the reference period (1961-1990). The temperature changed with two distinct stages. During the 600s-800s, temperatures were approximately 0.38°C higher than at present but then temperatures decreased in the subsequent period (800-902 AD). These results are similar to ones from previous studies on the mean temperature and the divisions between warm and cold periods during the study period, though differences were found in the degree of warmness/coldness. This reconstruction provides a valuable contribution to a better understanding of climatic variability during the Sui and Tang dynasties in China. [ABSTRACT FROM AUTHOR]

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). [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]

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]

Land surface phenology (LSP) is beneficial to understand ecosystem response to climate change, vegetation and crop type discrimination, and ecological modeling. However, the existing efforts based on coarse resolution data (≥500 m) cannot perform well in regions with higher spatial heterogeneity and multi-cropping system, such as China. Given that the majority of 10 m/30 m-based phenological research has focused on North America and Europe, developing spatiotemporally explicit LSP data in China is imperative. More importantly, the existing 30 m LSP products are mainly suitable for vegetation types with a single vegetation cycle, but cannot work well for biomes with complex seasonality (e.g., multiple growth cycles). Here we first harmonized three vegetation indices, i.e., the normalized difference vegetation index (NDVI), two-band enhanced vegetation index (EVI2), and land surface water index (LSWI) from Landsat-7/8 and Sentinel-2 imagery on the Google Earth Engine (GEE) platform. We then developed a new 30 m LSP algorithm that unified different phenological cycle-seeking processes per vegetation type and improved the existing algorithm. Furthermore, we used the algorithm to estimate the LSP product (LSP30CHN) for 2016–2019 across China, suitable for all vegetation types. The validation results showed a reasonably high accuracy (R2 > 0.6, RMSE < 15 days, mostly) of the LSP30CHN data against multi-sources in-situ observational (e.g., PhenoCam) and satellite-retrieved vegetation phenology data. Moreover, LSP30CHN data showed a consistent pattern but finer spatial details with the 500 m Moderate Resolution Imaging Spectroradiometer (MODIS) phenology product (MCD12Q2) at the homogenous area. We also found that phenological differences between LSP30CHN and MCD12Q2 increased with surface fragmentation, suggesting the potential of LSP30CHN to delineate phenological information on more fragmented landscapes. In contrast, the 500 m LSP data cannot provide such details in the regions with mixed cropping structures (e.g., corn, rice, and soybean) and multiple cropping index (e.g., single- and double-cropping systems). This study offers high accuracy of the LSP map for China, valuable for finer phenology-based services such as field-level crop management and agricultural phenology monitoring. It opens up new insights about exploring large-scale refined agricultural management and ecological assessment for other regions with complicated, fragmented landscapes and vegetation seasonality. [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]