Search

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]

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]

• 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]