Can we detect a nonlinear response to temperature in European plant phenology?

Transport capacity is uncoupled with endodormancy breaking in sweet cherry buds: physiological and molecular insights

Introduction

To avoid the negative impacts of winter unfavorable conditions for plant development, temperate trees enter a rest period called dormancy. Winter dormancy is a complex process that involves multiple signaling pathways and previous studies have suggested that transport capacity between cells and between the buds and the twig may regulate the progression throughout dormancy stages. However, the dynamics and molecular actors involved in this regulation are still poorly described in fruit trees.

Methods

Here, in order to validate the hypothesis that transport capacity regulates dormancy progression in fruit trees, we combined physiological, imaging and transcriptomic approaches to characterize molecular pathways and transport capacity during dormancy in sweet cherry (Prunus avium L.) flower buds.

Results

Our results show that transport capacity is reduced during dormancy and could be regulated by environmental signals. Moreover, we demonstrate that dormancy release is not synchronized with the transport capacity resumption but occurs when the bud is capable of growth under the influence of warmer temperatures. We highlight key genes involved in transport capacity during dormancy.

Discussion

Based on long-term observations conducted during six winter seasons, we propose hypotheses on the environmental and molecular regulation of transport capacity, in relation to dormancy and growth resumption in sweet cherry.

Climate warming shifts the time interval between flowering and leaf unfolding depending on the warming period

The timing of flowering (FL) and leaf unfolding (LU) determine plants' reproduction and vegetative growth. Global warming has substantially advanced FL and LU of temperate and boreal plants, but their responses to warming differ, which may influence the time interval between FL and LU (∆LU-FL), thereby impacting plant fitness and intraspecific physiological processes. Based on twigs collected from two flowering-first tree species, Populus tomentosa and Amygdalus triloba, we conducted a manipulative experiment to investigate the effects of winter chilling, spring warming and photoperiod on the ∆LU-FL. We found that photoperiod did not affect the ∆LU-FL of Amygdalus triloba, but shortened ∆LU-FL by 5.1 d of Populus tomentosa. Interestingly, spring warming and winter chilling oppositely affected the ∆LU-FL of both species. Specifically, low chilling accumulation extended the ∆LU-FL by 3.8 and 9.4 d for Populus tomentosa and Amygdalus triloba, but spring warming shortened the ∆LU-FL by 4.1 and 0.2 d °C^-1. Our results indicate that climate warming will decrease or increase the ∆LU-FL depending on the warming periods, i.e., spring or winter. The shifted time interval between flowering and leaf unfolding may have ecological effects including affecting pollen transfer efficiency and alter the structure and functioning of terrestrial ecosystem.

The growing and vital role of botanical gardens in climate change research

Botanical gardens make unique contributions to climate change research, conservation, and public engagement. They host unique resources, including diverse collections of plant species growing in natural conditions, historical records, and expert staff, and attract large numbers of visitors and volunteers. Networks of botanical gardens spanning biomes and continents can expand the value of these resources. Over the past decade, research at botanical gardens has advanced our understanding of climate change impacts on plant phenology, physiology, anatomy, and conservation. For example, researchers have utilized botanical garden networks to assess anatomical and functional traits associated with phenological responses to climate change. New methods have enhanced the pace and impact of this research, including phylogenetic and comparative methods, and online databases of herbarium specimens and photographs that allow studies to expand geographically, temporally, and taxonomically in scope. Botanical gardens have grown their community and citizen science programs, informing the public about climate change and monitoring plants more intensively than is possible with garden staff alone. Despite these advances, botanical gardens are still underutilized in climate change research. To address this, we review recent progress and describe promising future directions for research and public engagement at botanical gardens.

Maps, trends, and temperature sensitivities-phenological information from and for decreasing numbers of volunteer observers

Phenology serves as a major indicator of ongoing climate change. Long-term phenological observations are critically important for tracking and communicating these changes. The phenological observation network across Germany is operated by the National Meteorological Service with a major contribution from volunteering activities. However, the number of observers has strongly decreased for the last decades, possibly resulting in increasing uncertainties when extracting reliable phenological information from map interpolation. We studied uncertainties in interpolated maps from decreasing phenological records, by comparing long-term trends based on grid-based interpolated and station-wise observed time series, as well as their correlations with temperature. Interpolated maps in spring were characterized by the largest spatial variabilities across Bavaria, Germany, with respective lowest interpolated uncertainties. Long-term phenological trends for both interpolations and observations exhibited mean advances of -0.2 to -0.3 days year^-1 for spring and summer, while late autumn and winter showed a delay of around 0.1 days year^-1. Throughout the year, temperature sensitivities were consistently stronger for interpolated time series than observations. Such a better representation of regional phenology by interpolation was equally supported by satellite-derived phenological indices. Nevertheless, simulation of observer numbers indicated that a decline to less than 40% leads to a strong decrease in interpolation accuracy. To better understand the risk of declining phenological observations and to motivate volunteer observers, a Shiny app is proposed to visualize spatial and temporal phenological patterns across Bavaria and their links to climate change-induced temperature changes.

How did the characteristics of the growing season change during the past 100 years at a steep river basin in Japan?

The effects of climate change on plant phenological events such as flowering, leaf flush, and leaf fall may be greater in steep river basins than at the horizontal scale of countries and continents. This possibility is due to the effect of temperature on plant phenology and the difference between vertical and horizontal gradients in temperature sensitivities. We calculated the dates of the start (SGS) and end of the growing season (EGS) in a steep river basin located in a mountainous region of central Japan over a century timescale by using a degree-day phenological model based on long-term, continuous, in situ observations. We assessed the generality and representativeness of the modelled SGS and EGS dates by using phenological events, live camera images taken at multiple points in the basin, and satellite observations made at a fine spatial resolution. The sensitivity of the modelled SGS and EGS dates to elevation changed from 3.29 days (100 m)⁻¹ (−5.48 days °C⁻¹) and −2.89 days (100 m)⁻¹ (4.81 days °C⁻¹), respectively, in 1900 to 2.85 days (100 m)⁻¹ (−4.75 days °C⁻¹) and −2.84 day (100 m)⁻¹ (4.73 day °C⁻¹) in 2019. The long-term trend of the sensitivity of the modelled SGS date to elevation was −0.0037 day year⁻¹ per 100 m, but the analogous trend in the case of the modelled EGS date was not significant. Despite the need for further studies to improve the generality and representativeness of the model, the development of degree-day phenology models in multiple, steep river basins will deepen our ecological understanding of the sensitivity of plant phenology to climate change.

A Phenological Model for Olive (Olea europaea L. var europaea) Growing in Italy

The calibration of a reliable phenological model for olive grown in areas characterized by great environmental heterogeneity, like Italy, where many varieties exist, is challenging and often suffers from a lack of observations, especially on budbreak. In this study, we used a database encompassing many phenological events from different olive varieties, years, and sites scattered all over Italy to identify the phases in which site-enlarged developmental rates can be well regressed against air temperature (Developmental Rate function, DR) by testing both linear and nonlinear functions. A K-fold cross-validation (KfCV) was carried out to evaluate the ability of DR functions to predict phenological development. The cross-validation showed that the phases ranging from budbreak (BBCH 01 and 07) to flowering (BBCH 61 and 65) and from the beginning of flowering (BBCH 51) to flowering can be simulated with high accuracy (r² = 0.93-0.96; RMSE = 3.9-6.6 days) with no appreciable difference among linear and nonlinear functions. Thus, the resulting DRs represent a simple yet reliable tool for regional phenological simulations for these phases in Italy, paving the way for a reverse modeling approach aimed at reconstructing the budbreak dates. By contrast, and despite a large number of phases explored, no appreciable results were obtained on other phases, suggesting possible interplays of different drivers that need to be further investigated.

Comparison of chilling and heat requirements for leaf unfolding in deciduous woody species in temperate and subtropical China

Climate warming has advanced the spring phenology of many plant species by accelerating heat accumulation. However, delayed phenophases due to insufficient chilling have also been reported. Based on phenological observation data (1963-2010), we compared the effects of preseason chill and heat accumulation on leaf unfolding dates of four deciduous woody species (Lagerstroemia indica, Robinia pseudoacacia, Sophora japonica, and Ulmus pumila) in temperate and subtropical regions of China. Daily chill and heat accumulation were calculated by two chilling models (the Positive Utah Model and the Dynamic Model) and the Growing Degree Hour (GDH) Model. We determined the temporal trends in chill and heat accumulations for leaf unfolding of the four species. The results showed that there were shorter chilling periods in the subtropics than in temperate sites because the chilling period typically started later and ended earlier. There was no significant difference in the length of the forcing period in the different regions. The chilling requirements for leaf unfolding were higher in temperate regions (1344.9-1798.9 chilling units (CU) or 64.7-79.4 chilling portions (CP)) than in the subtropics (1145.9-1828.1 CU or 47.9-75.2 CP). Plants in the subtropics needed higher forcing temperatures (4135.8-10084.8 GDH) than those in temperate regions (3292.0-8383.6 GDH). The earlier-leafing species (e.g., U. pumila) had a lower heat requirement for leaf unfolding than the later-leafing species (e.g., L. indica). A significant increase in heat accumulation was found at all sites except Guiyang, while chill accumulation only increased in Beijing.

Varying temperature sensitivity of bud-burst date at different temperature conditions

The relationship between the rate of development (DR) of bud-burst and temperature may be nonlinear, which could lead to varying temperature sensitivity (TS) of budburst date under different climate conditions. In order to determine the functional form between DR/TS and temperature, we gathered twigs with flower buds of five woody plants (Malus halliana, Forsythia suspense, Crataegus pinnatifida, Prunus cerasifera F. atropurpurea, and Berberis thunbergii var. atropurpurea Chenault) in early spring of 2017 at Beijing, and placed them in six growth chambers at same daylength but different temperature conditions (5, 10, 15, 20, 25, and 30 °C). The proportion of bud- burst was recorded every 2 or 3 days for each species at each temperature condition. The results showed that the proportion of bud-burst followed the logistic function over time at a given temperature. Subsequently, we developed a mathematical model to simulate the proportion of bud-burst at any temperature and date. The DR and TS were parameterized using a differential method. The simulation results showed that the DR increased monotonically with the rise in temperature, but only two species could reach the maximum value at 30 °C. The TS decreased with the increase in temperature, but this effect was weak when the temperature was high enough. These findings suggested that the predicted warming in the future may result in a slowdown in the advance of spring phenology of woody plants.

Effects of temperature variability and extremes on spring phenology across the contiguous United States from 1982 to 2016

Warming climate and its impact on vegetation phenological trends have been widely investigated. However, interannual variability in temperature is considerably large in recent decades, which is expected to trigger an increasing trend of variation in vegetation phenology. To explore the interannual phenological variation across the contiguous United States (CONUS), we first detected the onset of vegetation greenup using the time series of the daily two-band Enhanced Vegetation Index (EVI2) observed from the AVHRR Long-Term Data Record (1982–1999) and the MODIS Climate Modeling Grid (2000–2016). We then calculated the interannual variation in greenup onset during four decadal periods: 1982–1989, 1990–1999, 2000–2009 and 2010–2016. Further, the trend of interannual variation in greenup onset from 1982 to 2016 was analyzed at pixel and state levels. Extreme phenological events were also determined using a greenup onset anomaly for each pixel. Similar approaches were applied to spring temperatures to detect extreme years and to the temporal trend of interannual variation to explain the phenological variation. The results revealed that 62% of pixels show an increasing interannual variation in greenup onset, and in 44% of pixels, this variation could be explained by the temperature. Although extreme phenology occurred locally in different years, three nationwide extreme phenological years were distinguished. The extreme warm spring that occurred in 2012 resulted in the occurrence of greenup onset as much as 20 days earlier than normal in large parts of the CONUS. In contrast, greenup onset was much later (up to 30 days) in 1983 and 1996 due to cool spring temperatures. These findings suggest that interannual variation in spring phenology could be much stronger in the future in response to climate variation, which could have more significant impacts on terrestrial ecosystems than the regular long-term phenological trend.

Climate change fingerprints in recent European plant phenology

A paper published in Global Change Biology in 2006 revealed that phenological responses in 1971-2000 matched the warming pattern in Europe, but a lack of chilling and adaptation in farming may have reversed these findings. Therefore, for 1951-2018 in a corresponding data set, we determined changes as linear trends and analysed their variation by plant traits/groups, across season and time as well as their attribution to warming following IPCC methodology. Although spring and summer phases in wild plants advanced less (maximum advances in 1978-2007), more (~90%) and more significant (~60%) negative trends were present, being stronger in early spring, at higher elevations, but smaller for nonwoody insect-pollinated species. These trends were strongly attributable to winter and spring warming. Findings for crop spring phases were similar, but were less pronounced. There were clearer and attributable signs for a delayed senescence in response to winter and spring warming. These changes resulted in a longer growing season, but a constant generative period in wild plants and a shortened one in agricultural crops. Phenology determined by farmers' decisions differed noticeably from the purely climatic driven phases with smaller percentages of advancing (~75%) trends, but farmers' spring activities were the only group with reinforced advancement, suggesting adaptation. Trends in farmers' spring and summer activities were very likely/likely associated with the warming pattern. In contrast, the advance in autumn farming phases was significantly associated with below average summer warming. Thus, under ongoing climate change with decreased chilling the advancing phenology in spring and summer is still attributable to warming; even the farmers' activities in these seasons mirror, to a lesser extent, the warming. Our findings point to adaptation to climate change in agriculture and reveal diverse implications for terrestrial ecosystems; the strong attribution supports the necessary mediation of warming impacts to the general public.

Variations in the temperature sensitivity of spring leaf phenology from 1978 to 2014 in Mudanjiang, China

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.

How to analyse plant phenotypic plasticity in response to a changing climate

Contents Summary 1235 I. Introduction 1235 II. The many shapes of phenotypic plasticity 1236 III. Random regression mixed model framework 1237 IV. Conclusions 1240 Acknowledgements 1240 References 1240 SUMMARY: Plant biology is experiencing a renewed interest in the mechanistic underpinnings and evolution of phenotypic plasticity that calls for a re-evaluation of how we analyse phenotypic responses to a rapidly changing climate. We suggest that dissecting plant plasticity in response to increasing temperature needs an approach that can represent plasticity over multiple environments, and considers both population-level responses and the variation between genotypes in their response. Here, we outline how a random regression mixed model framework can be applied to plastic traits that show linear or nonlinear responses to temperature. Random regressions provide a powerful and efficient means of characterising plasticity and its variation. Although they have been used widely in other fields, they have only recently been implemented in plant evolutionary ecology. We outline their structure and provide an example tutorial of their implementation.

The breadth of climate change impacts on biological systems

Human activity is driving climate change. This is affecting and will affect many aspects of life on earth. The breadth of its impacts is very wide and covers human, animal and plant health, and also the planet's biodiversity and the services that deliver benefits to people from natural capital. Finding solutions to the challenge of climate change will require multidisciplinary action in which the life sciences have a major role to play as this issue of Emerging Topics in Life Sciences indicates. More process and mechanistic knowledge could underpin solutions or even provide early warning of impacts. Any solutions will need to be developed and deployed in ways that gain and maintain public support.

Getting ahead of the curve: cities as surrogates for global change

Urbanization represents an unintentional global experiment that can provide insights into how species will respond and interact under future global change scenarios. Cities produce many conditions that are predicted to occur widely in the future, such as warmer temperatures, higher carbon dioxide (CO2) concentrations and exacerbated droughts. In using cities as surrogates for global change, it is challenging to disentangle climate variables-such as temperature-from co-occurring or confounding urban variables-such as impervious surface-and then to understand the interactive effects of multiple climate variables on both individual species and species interactions. However, such interactions are also difficult to replicate experimentally, and thus the challenges of cities are also their unique advantage. Here, we review insights gained from cities, with a focus on plants and arthropods, and how urban findings agree or disagree with experimental predictions and historical data. We discuss the types of hypotheses that can be best tested in cities, caveats to urban research and how to further validate cities as surrogates for global change. Lastly, we summarize how to achieve the goal of using urban species responses to predict broader regional- and ecosystem-level patterns in the future.

Machine learning modeling of plant phenology based on coupling satellite and gridded meteorological dataset

Changes in the timing of plant phenological phases are important proxies in contemporary climate research. However, most of the commonly used traditional phenological observations do not give any coherent spatial information. While consistent spatial data can be obtained from airborne sensors and preprocessed gridded meteorological data, not many studies robustly benefit from these data sources. Therefore, the main aim of this study is to create and evaluate different statistical models for reconstructing, predicting, and improving quality of phenological phases monitoring with the use of satellite and meteorological products. A quality-controlled dataset of the 13 BBCH plant phenophases in Poland was collected for the period 2007-2014. For each phenophase, statistical models were built using the most commonly applied regression-based machine learning techniques, such as multiple linear regression, lasso, principal component regression, generalized boosted models, and random forest. The quality of the models was estimated using a k-fold cross-validation. The obtained results showed varying potential for coupling meteorological derived indices with remote sensing products in terms of phenological modeling; however, application of both data sources improves models' accuracy from 0.6 to 4.6 day in terms of obtained RMSE. It is shown that a robust prediction of early phenological phases is mostly related to meteorological indices, whereas for autumn phenophases, there is a stronger information signal provided by satellite-derived vegetation metrics. Choosing a specific set of predictors and applying a robust preprocessing procedures is more important for final results than the selection of a particular statistical model. The average RMSE for the best models of all phenophases is 6.3, while the individual RMSE vary seasonally from 3.5 to 10 days. Models give reliable proxy for ground observations with RMSE below 5 days for early spring and late spring phenophases. For other phenophases, RMSE are higher and rise up to 9-10 days in the case of the earliest spring phenophases.

Pan European Phenological database (PEP725): a single point of access for European data

The Pan European Phenology (PEP) project is a European infrastructure to promote and facilitate phenological research, education, and environmental monitoring. The main objective is to maintain and develop a Pan European Phenological database (PEP725) with an open, unrestricted data access for science and education. PEP725 is the successor of the database developed through the COST action 725 "Establishing a European phenological data platform for climatological applications" working as a single access point for European-wide plant phenological data. So far, 32 European meteorological services and project partners from across Europe have joined and supplied data collected by volunteers from 1868 to the present for the PEP725 database. Most of the partners actively provide data on a regular basis. The database presently holds almost 12 million records, about 46 growing stages and 265 plant species (including cultivars), and can be accessed via http://www.pep725.eu/ . Users of the PEP725 database have studied a diversity of topics ranging from climate change impact, plant physiological question, phenological modeling, and remote sensing of vegetation to ecosystem productivity.

Trends and uncertainties in budburst projections of Norway spruce in Northern Europe

Budburst is regulated by temperature conditions, and a warming climate is associated with earlier budburst. A range of phenology models has been developed to assess climate change effects, and they tend to produce different results. This is mainly caused by different model representations of tree physiology processes, selection of observational data for model parameterization, and selection of climate model data to generate future projections. In this study, we applied (i) Bayesian inference to estimate model parameter values to address uncertainties associated with selection of observational data, (ii) selection of climate model data representative of a larger dataset, and (iii) ensembles modeling over multiple initial conditions, model classes, model parameterizations, and boundary conditions to generate future projections and uncertainty estimates. The ensemble projection indicated that the budburst of Norway spruce in northern Europe will on average take place 10.2 ± 3.7 days earlier in 2051–2080 than in 1971–2000, given climate conditions corresponding to RCP 8.5. Three provenances were assessed separately (one early and two late), and the projections indicated that the relationship among provenance will remain also in a warmer climate. Structurally complex models were more likely to fail predicting budburst for some combinations of site and year than simple models. However, they contributed to the overall picture of current understanding of climate impacts on tree phenology by capturing additional aspects of temperature response, for example, chilling. Model parameterizations based on single sites were more likely to result in model failure than parameterizations based on multiple sites, highlighting that the model parameterization is sensitive to initial conditions and may not perform well under other climate conditions, whether the change is due to a shift in space or over time. By addressing a range of uncertainties, this study showed that ensemble modeling provides a more robust impact assessment than would a single phenology model run.

The rise of phenology with climate change: an evaluation of IJB publications

In recent decades, phenology has become an important tool by which to measure both the impact of climate change on ecosystems and the feedback of ecosystems to the climate system. However, there has been little attempt to date to systematically quantify the increase in the number of scientific publications with a focus on phenology and climate change. In order to partially address this issue, we examined the number of articles (original papers, reviews and short communications) containing the terms 'phenology' and 'climate change' in the title, abstract or keywords, published in the International Journal of Biometeorology in the 60 years since its inception in 1957. We manually inspected all issues prior to 1987 for the search terms and subsequently used the search facility on the Web of Science online database. The overall number of articles published per decade remained relatively constant (255-378) but rose rapidly to 1053 in the most recent decade (2007-2016), accompanied by an increase (41-172) in the number of articles containing the search terms. A number of factors may have contributed to this rise, including the recognition of the value of phenology as an indicator of climate change and the initiation in 2010 of a series of conferences focusing on phenology which subsequently led to two special issues of the journal. The word 'phenology' was in use from the first issue, whereas 'climate change' only emerged in 1987 and peaked in 2014. New technologies such as satellite remote sensing and the internet led to an expansion of and greater access to a growing reservoir of phenological information. The application of phenological data included determining the impact of warming of phenophases, predicting wine quality and the pollen season, demonstrating the potential for mismatch to occur and both reconstructing and forecasting climate. Even though this analysis was limited to one journal, it is likely to be indicative of a similar trend across other scientific publications.

Cold Tolerance of the Male Gametophyte during Germination and Tube Growth Depends on the Flowering Time

In temperate climates, most plants flower during the warmer season of the year to avoid negative effects of low temperatures on reproduction. Nevertheless, few species bloom in midwinter and early spring despite severe and frequent frosts at that time. This raises the question of adaption of sensible progamic processes such as pollen germination and pollen tube growth to low temperatures. The performance of the male gametophyte of 12 herbaceous lowland species flowering in different seasons was examined in vitro at different test temperatures using an easy to handle testing system. Additionally, the capacity to recover after the exposure to cold was checked. We found a clear relationship between cold tolerance of the activated male gametophyte and the flowering time. In most summer-flowering species, pollen germination stopped between 1 and 5 °C, whereas pollen of winter and early spring flowering species germinated even at temperatures below zero. Furthermore, germinating pollen was exceptionally frost tolerant in cold adapted plants, but suffered irreversible damage already from mild sub-zero temperatures in summer-flowering species. In conclusion, male gametophytes show a high adaptation potential to cold which might exceed that of female tissues. For an overall assessment of temperature limits for sexual reproduction it is therefore important to consider female functions as well.

A collection of European sweet cherry phenology data for assessing climate change

Professional and scientific networks built around the production of sweet cherry (Prunus avium L.) led to the collection of phenology data for a wide range of cultivars grown in experimental sites characterized by highly contrasted climatic conditions. We present a dataset of flowering and maturity dates, recorded each year for one tree when available, or the average of several trees for each cultivar, over a period of 37 years (1978-2015). Such a dataset is extremely valuable for characterizing the phenological response to climate change, and the plasticity of the different cultivars' behaviour under different environmental conditions. In addition, this dataset will support the development of predictive models for sweet cherry phenology exploitable at the continental scale, and will help anticipate breeding strategies in order to maintain and improve sweet cherry production in Europe.