Widespread decline in winds delayed autumn foliar senescence over high latitudes.

The high northern latitudes (>50°) experienced a pronounced surface stilling (i.e., decline in winds) with climate change. As a drying factor, the influences of changes in winds on the date of autumn foliar senescence (DFS) remain largely unknown and are potentially important as a mechanism explaining the interannual variability of autumn phenology. Using 183,448 phenological observations at 2,405 sites, long-term site-scale water vapor and carbon dioxide flux measurements, and 34 y of satellite greenness data, here we show that the decline in winds is significantly associated with extended DFS and could have a relative importance comparable with temperature and precipitation effects in contributing to the DFS trends. We further demonstrate that decline in winds reduces evapotranspiration, which results in less soil water losses and consequently more favorable growth conditions in late autumn. In addition, declining winds also lead to less leaf abscission damage which could delay leaf senescence and to a decreased cooling effect and therefore less frost damage. Our results are potentially useful for carbon flux modeling because an improved algorithm based on these findings projected overall widespread earlier DFS than currently expected by the end of this century, contributing potentially to a positive feedback to climate.

Poleward shifts in the maximum of spring phenological responsiveness of Ginkgo biloba to temperature in China.

Global warming is advancing the timing of spring leaf-out in temperate and boreal plants, affecting biological interactions and global biogeochemical cycles. However, spatial variation in spring phenological responsiveness to climate change within species remains poorly understood. Here, we investigated variation in the responsiveness of spring phenology to temperature (RSP; days to leaf-out at a given temperature) in 2754 Ginkgo biloba twigs of trees distributed across subtropical and temperate regions in China from 24°N to 44°N. We found a nonlinear effect of mean annual temperature on spatial variation in RSP, with the highest response rate at c. 12°C and lower response rates at warmer or colder temperatures due to declines in winter chilling accumulation. We then predicted the spatial maxima in RSP under current and future climate scenarios, and found that trees are currently most responsive in central China, which corresponds to the species' main distribution area. Under a high-emission scenario, we predict a 4-degree latitude shift in the responsiveness maximum toward higher latitudes over the rest of the century. The identification of the nonlinear responsiveness of spring phenology to climate gradients and the spatial shifts in phenological responsiveness expected under climate change represent new mechanistic insights that can inform models of spring phenology and ecosystem functioning.

Radiation-constrained boundaries cause nonuniform responses of the carbon uptake phenology to climatic warming in the Northern Hemisphere.

Climatic warming has lengthened the photosynthetically active season in recent decades, thus affecting the functioning and biogeochemistry of ecosystems, the global carbon cycle and climate. Temperature response of carbon uptake phenology varies spatially and temporally, even within species, and daily total intensity of radiation may play a role. We empirically modelled the thresholds of temperature and radiation under which daily carbon uptake is constrained in the temperate and cold regions of the Northern Hemisphere, which include temperate forests, boreal forests, alpine and tundra biomes. The two-dimensionality of the temperature-radiation constraint was reduced to one single variable, θ, which represents the angle in a polar coordinate system for the temperature-radiation observations during the start and end of the growing season. We found that radiation will constrain the trend towards longer growing seasons with future warming but differently during the start and end of season and depending on the biome type and region. We revealed that radiation is a major factor limiting photosynthetic activity that constrains the phenology response to temperature during the end-of-season. In contrast, the start of the carbon uptake is overall highly sensitive to temperature but not constrained by radiation at the hemispheric scale. This study thus revealed that while at the end-of-season the phenology response to warming is constrained at the hemispheric scale, at the start-of-season the advance of spring onset may continue, even if it is at a slower pace.

Global warming is increasing the discrepancy between green (actual) and thermal (potential) seasons of temperate trees.

Over the past decades, global warming has led to a lengthening of the time window during which temperatures remain favorable for carbon assimilation and tree growth, resulting in a lengthening of the green season. The extent to which forest green seasons have tracked the lengthening of this favorable period under climate warming, however, has not been quantified to date. Here, we used remote sensing data and long-term ground observations of leaf-out and coloration for six dominant species of European trees at 1773 sites, for a total of 6060 species-site combinations, during 1980-2016 and found that actual green season extensions (GS: 3.1 ± 0.1 day decade-1 ) lag four times behind extensions of the potential thermal season (TS: 12.6 ± 0.1 day decade-1 ). Similar but less pronounced differences were obtained using satellite-derived vegetation phenology observations, that is, a lengthening of 4.4 ± 0.13 and 7.5 ± 0.13 day decade-1 for GS and TS, respectively. This difference was mainly driven by the larger advance in the onset of the thermal season compared to the actual advance of leaf-out dates (spring mismatch: 7.2 ± 0.1 day decade-1 ), but to a less extent caused by a phenological mismatch between GS and TS in autumn (2.4 ± 0.1 day decade-1 ). Our results showed that forest trees do not linearly track the new thermal window extension, indicating more complex interactions between winter and spring temperatures and photoperiod and a justification of demonstrating that using more sophisticated models that include the influence of chilling and photoperiod is needed to accurately predict spring phenological changes under warmer climate. They urge caution if such mechanisms are omitted to predict, for example, how vegetative health and growth, species distribution and crop yields will change in the future.

Winter warming offsets one half of the spring warming effects on leaf unfolding.

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.

Soil moisture regulates warming responses of autumn photosynthetic transition dates in subtropical forests.

Autumn phenology plays a key role in regulating the terrestrial carbon and water balance and their feedbacks to the climate. However, the mechanisms underlying autumn phenology are still poorly understood, especially in subtropical forests. In this study, we extracted the autumn photosynthetic transition dates (APTD) in subtropical China over the period 2003-2017 based on a global, fine-resolution solar-induced chlorophyll fluorescence (SIF) dataset (GOSIF) using four fitting methods, and then explored the temporal-spatial variations of APTD and its underlying mechanisms using partial correlation analysis and machine learning methods. We further predicted the APTD shifts under future climate warming conditions by applying process-based and machine learning-based models. We found that the APTD was significantly delayed, with an average rate of 7.7 days per decade, in subtropical China during 2003-2017. Both partial correlation analysis and machine learning methods revealed that soil moisture was the primary driver responsible for the APTD changes in southern subtropical monsoon evergreen forest (SEF) and middle subtropical evergreen forest (MEF), whereas solar radiation controlled the APTD variations in the northern evergreen-broadleaf deciduous mixed forest (NMF). Combining the effects of temperature, soil moisture and radiation, we found a significantly delayed trend in APTD during the 2030-2100 period, but the trend amplitude (0.8 days per decade) was much weaker than that over 2003-2017. In addition, we found that machine learning methods outperformed process-based models in projecting APTD. Our findings generate from different methods highlight that soil moisture is one of the key players in determining autumn photosynthetic phenological processes in subtropical forests. To comprehensively understand autumn phenological processes, in-situ manipulative experiments are urgently needed to quantify the contributions of different environmental and physiological factors in regulating plants' response to ongoing climate change.

Impact of microclimatic conditions and resource availability on spring and autumn phenology of temperate tree seedlings.

Microclimatic effects (light, temperature) are often neglected in phenological studies and little information is known about the impact of resource availability (nutrient and water) on tree's phenological cycles. Here we experimentally studied spring and autumn phenology in four temperate trees in response to changes in bud albedo (white-painted vs black-painted buds), light conditions (nonshaded vs c. 70% shaded), water availability (irrigated, control and reduced precipitation) and nutrients (low vs high availability). We found that higher bud albedo or shade delayed budburst (up to +12 d), indicating that temperature is sensed locally within each bud. Leaf senescence was delayed by high nutrient availability (up to +7 d) and shade conditions (up to +39 d) in all species, except oak. Autumn phenological responses to summer droughts depended on species, with a delay for cherry (+7 d) and an advance for beech (-7 d). The strong phenological effects of bud albedo and light exposure reveal an important role of microclimatic variation on phenology. In addition to the temperature and photoperiod effects, our results suggest a tight interplay between source and sink processes in regulating the end of the seasonal vegetation cycle, which can be largely influenced by resource availability (light, water and nutrients).

Divergent responses of phenology and growth to summer and autumnal warming.

Plant phenology is highly sensitive to climate change, and shifts in autumnal foliar senescence are critical for plant productivity and nutrient cycling. Global warming has delayed the timing of foliar senescence, but the response of autumnal foliar senescence to nonuniform seasonal warming remains poorly understood, with experimental evidence in trees especially scarce. We therefore conducted a field experiment on seasonally asymmetric warming on 2-year-old larch (Larix principis-rupprechtii) seedlings in two hydrologically contrasting years (wet 2018 and dry 2019). Autumnal and year-round warming significantly delayed the timing of foliar senescence by 6 and 7 d in 2018, the wet year, with corresponding temperature sensitivities of 6.73 ± 1.47 and 8.26 ± 1.00 d/°C, respectively. Interestingly, the dates of senescence did not change across the warming treatments in 2019, the dry year. However, there was no significant effect of summer warming on the timing of foliar senescence neither in the wet nor dry year. The delayed autumnal foliar senescence was responsible for an increase in biomass only in the wet year, 2018. In contrast, summer warming, but not autumnal warming, increased the mortality of the seedlings in both 2018 and 2019. These results suggest that the hydrological conditions substantially modify the response of autumnal phenology and growth to seasonal warming. Autumnal warming increases growth, whereas summer warming could cause carbon starvation/hydraulic failure, reduce growth, and lead to higher mortality. Our results suggest that the functioning, ecosystem services, and sustainability of forests in the future depend on the strength and pattern of nonuniform seasonal warming. This study can inspire new research in phenology and tree growth in experiments with asymmetric warming.

Photoperiod decelerates the advance of spring phenology of six deciduous tree species under climate warming.

Vegetation phenology in spring has substantially advanced under climate warming, consequently shifting the seasonality of ecosystem process and altering biosphere-atmosphere feedbacks. However, whether and to what extent photoperiod (i.e., daylength) affects the phenological advancement is unclear, leading to large uncertainties in projecting future phenological changes. Here we examined the photoperiod effect on spring phenology at a regional scale using in situ observation of six deciduous tree species from the Pan European Phenological Network during 1980-2016. We disentangled the photoperiod effect from the temperature effect (i.e., forcing and chilling) by utilizing the unique topography of the northern Alps of Europe (i.e., varying daylength but uniform temperature distribution across latitudes) and examining phenological changes across latitudes. We found prominent photoperiod-induced shifts in spring leaf-out across latitudes (up to 1.7 days per latitudinal degree). Photoperiod regulates spring phenology by delaying early leaf-out and advancing late leaf-out caused by temperature variations. Based on these findings, we proposed two phenological models that consider the photoperiod effect through different mechanisms and compared them with a chilling model. We found that photoperiod regulation would slow down the advance in spring leaf-out under projected climate warming and thus mitigate the increasing frost risk in spring that deciduous forests will face in the future. Our findings identify photoperiod as a critical but understudied factor influencing spring phenology, suggesting that the responses of terrestrial ecosystem processes to climate warming are likely to be overestimated without adequately considering the photoperiod effect.

Declining global warming effects on the phenology of spring leaf unfolding.

Earlier spring leaf unfolding is a frequently observed response of plants to climate warming. Many deciduous tree species require chilling for dormancy release, and warming-related reductions in chilling may counteract the advance of leaf unfolding in response to warming. Empirical evidence for this, however, is limited to saplings or twigs in climate-controlled chambers. Using long-term in situ observations of leaf unfolding for seven dominant European tree species at 1,245 sites, here we show that the apparent response of leaf unfolding to climate warming (ST, expressed in days advance of leaf unfolding per °C warming) has significantly decreased from 1980 to 2013 in all monitored tree species. Averaged across all species and sites, ST decreased by 40% from 4.0 ± 1.8 days °C(-1) during 1980-1994 to 2.3 ± 1.6 days °C(-1) during 1999-2013. The declining ST was also simulated by chilling-based phenology models, albeit with a weaker decline (24-30%) than observed in situ. The reduction in ST is likely to be partly attributable to reduced chilling. Nonetheless, other mechanisms may also have a role, such as 'photoperiod limitation' mechanisms that may become ultimately limiting when leaf unfolding dates occur too early in the season. Our results provide empirical evidence for a declining ST, but also suggest that the predicted strong winter warming in the future may further reduce ST and therefore result in a slowdown in the advance of tree spring phenology.

Global warming leads to more uniform spring phenology across elevations.

One hundred years ago, Andrew D. Hopkins estimated the progressive delay in tree leaf-out with increasing latitude, longitude, and elevation, referred to as "Hopkins' bioclimatic law." What if global warming is altering this well-known law? Here, based on ∼20,000 observations of the leaf-out date of four common temperate tree species located in 128 sites at various elevations in the European Alps, we found that the elevation-induced phenological shift (EPS) has significantly declined from 34 d⋅1,000 m-1 conforming to Hopkins' bioclimatic law in 1960, to 22 d⋅1,000 m-1 in 2016, i.e., -35%. The stronger phenological advance at higher elevations, responsible for the reduction in EPS, is most likely to be connected to stronger warming during late spring as well as to warmer winter temperatures. Indeed, under similar spring temperatures, we found that the EPS was substantially reduced in years when the previous winter was warmer. Our results provide empirical evidence for a declining EPS over the last six decades. Future climate warming may further reduce the EPS with consequences for the structure and function of mountain forest ecosystems, in particular through changes in plant-animal interactions, but the actual impact of such ongoing change is today largely unknown.

Modeling leaf senescence of deciduous tree species in Europe.

Autumnal leaf senescence signals the end of photosynthetic activities in temperate deciduous trees and consequently exerts a strong control on various ecological processes. Predicting leaf senescence dates (LSD) with high accuracy is thus a prerequisite for better understanding the climate-ecosystem interactions. However, modeling LSD at large spatial and temporal scales is challenging. In this study, first, we used 19972 site-year records (848 sites and four deciduous tree species) from the PAN European Phenology network to calibrate and evaluate six leaf senescence models during the period 1980-2013. Second, we extended the spatial analysis by repeating the procedure across Europe using satellite-derived end of growing season and a forest map. Overall, we found that models that considered photoperiod and temperature interactions outperformed models using simple temperature or photoperiod thresholds for Betula pendula, Fagus sylvatica and Quercus robur. On the contrary, no model displayed reasonable predictions for Aesculus hippocastanum. This inter-model comparison indicates that, contrary to expectation, photoperiod does not significantly modulate the accumulation of cooling degree days (CDD). On the other hand, considering the carryover effect of leaf unfolding date could promote the models' predictability. The CDD models generally matched the observed LSD at species level and its interannual variation, but were limited in explaining the inter-site variations, indicating that other environmental cues need to be considered in future model development. The discrepancies remaining between model simulations and observations highlight the need of manipulation studies to elucidate the mechanisms behind the leaf senescence process and to make current models more realistic.

Climate warming increases spring phenological differences among temperate trees.

Climate warming has substantially advanced spring leaf flushing, but winter chilling and photoperiod co-determine the leaf flushing process in ways that vary among species. As a result, the interspecific differences in spring phenology (IDSP) are expected to change with climate warming, which may, in turn, induce negative or positive ecological consequences. However, the temporal change of IDSP at large spatiotemporal scales remains unclear. In this study, we analyzed long-term in-situ observations (1951-2016) of six, coexisting temperate tree species from 305 sites across Central Europe and found that phenological ranking did not change when comparing the rapidly warming period 1984-2016 to the marginally warming period 1951-1983. However, the advance of leaf flushing was significantly larger in early-flushing species EFS (6.7 ± 0.3 days) than in late-flushing species LFS (5.9 ± 0.2 days) between the two periods, indicating extended IDSP. This IDSP extension could not be explained by differences in temperature sensitivity between EFS and LFS; however, climatic warming-induced heat accumulation effects on leaf flushing, which were linked to a greater heat requirement and higher photoperiod sensitivity in LFS, drove the shifts in IDSP. Continued climate warming is expected to further extend IDSP across temperate trees, with associated implications for ecosystem function.

Scaling Effects on Chlorophyll Content Estimations with RGB Camera Mounted on a UAV Platform Using Machine-Learning Methods.

Timely monitoring and precise estimation of the leaf chlorophyll contents of maize are crucial for agricultural practices. The scale effects are very important as the calculated vegetation index (VI) were crucial for the quantitative remote sensing. In this study, the scale effects were investigated by analyzing the linear relationships between VI calculated from red-green-blue (RGB) images from unmanned aerial vehicles (UAV) and ground leaf chlorophyll contents of maize measured using SPAD-502. The scale impacts were assessed by applying different flight altitudes and the highest coefficient of determination (R2) can reach 0.85. We found that the VI from images acquired from flight altitude of 50 m was better to estimate the leaf chlorophyll contents using the DJI UAV platform with this specific camera (5472 × 3648 pixels). Moreover, three machine-learning (ML) methods including backpropagation neural network (BP), support vector machine (SVM), and random forest (RF) were applied for the grid-based chlorophyll content estimation based on the common VI. The average values of the root mean square error (RMSE) of chlorophyll content estimations using ML methods were 3.85, 3.11, and 2.90 for BP, SVM, and RF, respectively. Similarly, the mean absolute error (MAE) were 2.947, 2.460, and 2.389, for BP, SVM, and RF, respectively. Thus, the ML methods had relative high precision in chlorophyll content estimations using VI; in particular, the RF performed better than BP and SVM. Our findings suggest that the integrated ML methods with RGB images of this camera acquired at a flight altitude of 50 m (spatial resolution 0.018 m) can be perfectly applied for estimations of leaf chlorophyll content in agriculture.

Modified Red Blue Vegetation Index for Chlorophyll Estimation and Yield Prediction of Maize from Visible Images Captured by UAV.

The vegetation index (VI) has been successfully used to monitor the growth and to predict the yield of agricultural crops. In this paper, a long-term observation was conducted for the yield prediction of maize using an unmanned aerial vehicle (UAV) and estimations of chlorophyll contents using SPAD-502. A new vegetation index termed as modified red blue VI (MRBVI) was developed to monitor the growth and to predict the yields of maize by establishing relationships between MRBVI- and SPAD-502-based chlorophyll contents. The coefficients of determination (R2s) were 0.462 and 0.570 in chlorophyll contents' estimations and yield predictions using MRBVI, and the results were relatively better than the results from the seven other commonly used VI approaches. All VIs during the different growth stages of maize were calculated and compared with the measured values of chlorophyll contents directly, and the relative error (RE) of MRBVI is the lowest at 0.355. Further, machine learning (ML) methods such as the backpropagation neural network model (BP), support vector machine (SVM), random forest (RF), and extreme learning machine (ELM) were adopted for predicting the yields of maize. All VIs calculated for each image captured during important phenological stages of maize were set as independent variables and the corresponding yields of each plot were defined as dependent variables. The ML models used the leave one out method (LOO), where the root mean square errors (RMSEs) were 2.157, 1.099, 1.146, and 1.698 (g/hundred grain weight) for BP, SVM, RF, and ELM. The mean absolute errors (MAEs) were 1.739, 0.886, 0.925, and 1.356 (g/hundred grain weight) for BP, SVM, RF, and ELM, respectively. Thus, the SVM method performed better in predicting the yields of maize than the other ML methods. Therefore, it is strongly suggested that the MRBVI calculated from images acquired at different growth stages integrated with advanced ML methods should be used for agricultural- and ecological-related chlorophyll estimation and yield predictions.

Daylength helps temperate deciduous trees to leaf-out at the optimal time.

Global warming has led to substantially earlier spring leaf-out in temperate-zone deciduous trees. The interactive effects of temperature and daylength underlying this warming response remain unclear. However, they need to be accurately represented by earth system models to improve projections of the carbon and energy balances of temperate forests and the associated feedbacks to the Earth's climate system. We studied the control of leaf-out by daylength and temperature using data from six tree species across 2,377 European phenological network (www.pep725.eu), each with at least 30 years of observations. We found that, in addition to and independent of the known effect of chilling, daylength correlates negatively with the heat requirement for leaf-out in all studied species. In warm springs when leaf-out is early, days are short and the heat requirement is higher than in an average spring, which mitigates the warming-induced advancement of leaf-out and protects the tree against precocious leaf-out and the associated risks of late frosts. In contrast, longer-than-average daylength (in cold springs when leaf-out is late) reduces the heat requirement for leaf-out, ensuring that trees do not leaf-out too late and miss out on large amounts of solar energy. These results provide the first large-scale empirical evidence of a widespread daylength effect on the temperature sensitivity of leaf-out phenology in temperate deciduous trees.

Plant phenology and global climate change: Current progresses and challenges.

Plant phenology, the annually recurring sequence of plant developmental stages, is important for plant functioning and ecosystem services and their biophysical and biogeochemical feedbacks to the climate system. Plant phenology depends on temperature, and the current rapid climate change has revived interest in understanding and modeling the responses of plant phenology to the warming trend and the consequences thereof for ecosystems. Here, we review recent progresses in plant phenology and its interactions with climate change. Focusing on the start (leaf unfolding) and end (leaf coloring) of plant growing seasons, we show that the recent rapid expansion in ground- and remote sensing- based phenology data acquisition has been highly beneficial and has supported major advances in plant phenology research. Studies using multiple data sources and methods generally agree on the trends of advanced leaf unfolding and delayed leaf coloring due to climate change, yet these trends appear to have decelerated or even reversed in recent years. Our understanding of the mechanisms underlying the plant phenology responses to climate warming is still limited. The interactions between multiple drivers complicate the modeling and prediction of plant phenology changes. Furthermore, changes in plant phenology have important implications for ecosystem carbon cycles and ecosystem feedbacks to climate, yet the quantification of such impacts remains challenging. We suggest that future studies should primarily focus on using new observation tools to improve the understanding of tropical plant phenology, on improving process-based phenology modeling, and on the scaling of phenology from species to landscape-level.

Short photoperiod reduces the temperature sensitivity of leaf-out in saplings of Fagus sylvatica but not in horse chestnut.

Leaf phenology is one of the most reliable bioindicators of ongoing global warming in temperate and boreal zones because it is highly sensitive to temperature variation. A large number of studies have reported advanced spring leaf-out due to global warming, yet the temperature sensitivity of leaf-out has significantly decreased in temperate deciduous tree species over the past three decades. One of the possible mechanisms is that photoperiod is limiting further advance to protect the leaves against potential damaging frosts. However, the "photoperiod limitation" hypothesis remains poorly investigated and experimentally tested. Here, we conducted a photoperiod- and temperature-manipulation experiment in climate chambers on two common deciduous species in Europe: Fagus sylvatica (European beech, a typically late flushing species) and Aesculus hippocastanum (horse chestnut, a typically early flushing species). In agreement with previous studies, we found that the warming significantly advanced the leaf-out dates by 4.3 and 3.7 days/°C for beech and horse chestnut saplings, respectively. However, shorter photoperiod significantly reduced the temperature sensitivity of beech only (3.0 days/°C) by substantially increasing the heat requirement to avoid leafing-out too early. Interestingly, the photoperiod limitation only occurs below a certain daylength (photoperiod threshold) when the warming increased above 4°C for beech trees. In contrast, for chestnut, no photoperiod threshold was found even when the ambient air temperature was warmed by 5°C. Given the species-specific photoperiod effect on leaf phenology, the sequence of the leaf-out timing among forest tree species may change under future climate warming conditions. Nonphotoperiodic species may benefit from warmer springs by starting the growing season earlier than photoperiodic sensitive species, modifying forest ecosystem structure and functions, but this photoperiod limitation needs to be further investigated experimentally in numerous species.

Shortened temperature-relevant period of spring leaf-out in temperate-zone trees.

Temperature during a particular period prior to spring leaf-out, the temperature-relevant period (TRP), is a strong determinant of the leaf-out date in temperate-zone trees. Climatic warming has substantially advanced leaf-out dates in temperate biomes worldwide, but its effect on the beginning and length of the TRP has not yet been explored, despite its direct relevance for phenology modeling. Using 1,551 species-site combinations of long-term (1951-2016) in situ observations on six tree species (namely, Aesculus hippocastanum, Alnus glutinosa, Betula pendula, Fagus sylvatica, Fraxinus excelsior, and Quercus robur) in central Europe, we found that the advancing leaf-out was accompanied by a shortening of the TRP. On average across all species and sites, the length of the TRP significantly decreased by 23% (p < .05), from 60 ± 4 days during 1951-1965 to 47 ± 4 days during 2002-2016. Importantly, the average start date of the TRP did not vary significantly over the study period (March 2-5, DOY = 61-64), which could be explained by sufficient chilling over the study period in the regions considered. The advanced leaf-out date with unchanged beginning of the TRP can be explained by the faster accumulation of the required heat due to climatic warming, which overcompensated for the retarding effect of shortening daylength on bud development. This study shows that climate warming has not yet affected the mean TRP starting date in the study region, implying that phenology modules in global land surface models might be reliable assuming a fixed TRP starting date at least for the temperate central Europe. Field warming experiments do, however, remain necessary to test to what extent the length of TRP will continue to shorten and whether the starting date will remain stable under future climate conditions.

Simulating the onset of spring vegetation growth across the Northern Hemisphere.

Changes in the spring onset of vegetation growth in response to climate change can profoundly impact climate-biosphere interactions. Thus, robust simulation of spring onset is essential to accurately predict ecosystem responses and feedback to ongoing climate change. To date, the ability of vegetation phenology models to reproduce spatiotemporal patterns of spring onset at larger scales has not been thoroughly investigated. In this study, we took advantage of phenology observations via remote sensing to calibrate and evaluated six models, including both one-phase (considering only forcing temperatures) and two-phase (involving forcing, chilling, and photoperiod) models across the Northern Hemisphere between 1982 and 2012. Overall, we found that the model that integrated the photoperiod effect performed best at capturing spatiotemporal patterns of spring phenology in boreal and temperate forests. By contrast, all of the models performed poorly in simulating the onset of growth in grasslands. These results suggest that the photoperiod plays a role in controlling the onset of growth in most Northern Hemisphere forests, whereas other environmental factors (e.g., precipitation) should be considered when simulating the onset of growth in grasslands. We also found that the one-phase model performed as well as the two-phase models in boreal forests, which implies that the chilling requirement is probably fulfilled across most of the boreal zone. Conversely, two-phase models performed better in temperate forests than the one-phase model, suggesting that photoperiod and chilling play important roles in these temperate forests. Our results highlight the significance of including chilling and photoperiod effects in models of the spring onset of forest growth at large scales, and indicate that the consideration of additional drivers may be required for grasslands.