New insights on plant phenological response to temperature revealed from long‐term widespread observations in China

Constraints of temperature on spring plant phenology are closely related to plant growth, vegetation dynamics, and ecosystem carbon cycle. However, the effects of temperature on leaf onset, especially for winter chilling, are still not well understood. Using long‐term, widespread in situ phenology observations collected over China for multiple plant species, this study analyzes the quantitative response of leaf onset to temperature, and compares empirical findings with existing theories and modeling approaches, as implemented in 18 phenology algorithms. Results show that the growing degree days (GDD) required for leaf onset vary distinctly among plant species and geographical locations as well as at organizational levels (species and community), pointing to diverse adaptation strategies. Chilling durations (CHD) needed for releasing bud dormancy decline monotonously from cold to warm areas with very limited interspecies variations. Results also reveal that winter chilling is a crucial component of phenology models, and its effect is better captured with an index that accounts for the inhomogeneous effectiveness of low temperature to chilling rate than with the conventional CHD index. The impact of spring warming on leaf onset is nonlinear, better represented by a logistical function of temperature than by the linear function currently implemented in biosphere models. The optimized base temperatures for thermal accumulation and the optimal chilling temperatures are species‐dependent and average at 6.9 and 0.2°C, respectively. Overall, plants’ chilling requirement is not a constant, and more chilling generally results in less requirement of thermal accumulation for leaf onset. Our results clearly demonstrate multiple deficiencies of the parameters (e.g., base temperature) and algorithms (e.g., method for calculating GDD) in conventional phenology models to represent leaf onset. Therefore, this study not only advances our mechanistic and quantitative understanding of temperature controls on leaf onset but also provides critical information for improving existing phenology models.     

Changes in satellite‐derived spring vegetation green‐up date and its linkage to climate in China from 1982 to 2010: a multimethod analysis

The change in spring phenology is recognized to exert a major influence on carbon balance dynamics in temperate ecosystems. Over the past several decades, several studies focused on shifts in spring phenology; however, large uncertainties still exist, and one understudied source could be the method implemented in retrieving satellite‐derived spring phenology. To account for this potential uncertainty, we conducted a multimethod investigation to quantify changes in vegetation green‐up date from 1982 to 2010 over temperate China, and to characterize climatic controls on spring phenology. Over temperate China, the five methods estimated that the vegetation green‐up onset date advanced, on average, at a rate of 1.3 ± 0.6 days per decade (ranging from 0.4 to 1.9 days per decade) over the last 29 years. Moreover, the sign of the trends in vegetation green‐up date derived from the five methods were broadly consistent spatially and for different vegetation types, but with large differences in the magnitude of the trend. The large intermethod variance was notably observed in arid and semiarid vegetation types. Our results also showed that change in vegetation green‐up date is more closely correlated with temperature than with precipitation. However, the temperature sensitivity of spring vegetation green‐up date became higher as precipitation increased, implying that precipitation is an important regulator of the response of vegetation spring phenology to change in temperature. This intricate linkage between spring phenology and precipitation must be taken into account in current phenological models which are mostly driven by temperature.     

Functional differences between summer and winter season rain assessed with MODIS‐derived phenology in a semi‐arid region

Questions: We asked several linked questions about phenology and precipitation relationships at local, landscape, and regional spatial scales within individual seasons, between seasons, and between year temporal scales. (1) How do winter and summer phenological patterns vary in response to total seasonal rainfall? (2) How are phenological rates affected by the previous season rainfall? (3) How does phenological variability differ at landscape and regional spatial scales and at season and inter‐annual temporal scales? Location: Southern Arizona, USA. Methods: We compared satellite‐derived phenological variation between 38 distinct 625‐km² landscapes distributed in the northern Sonoran Desert region from 2000 to 2007. Regression analyses were used to identify relationships between landscape phenology dynamics in response to precipitation variability across multiple spatial and temporal scales. Results: While both summer and winter seasons show increases of peak greenness and peak growth with more precipitation, the timing of peak growth was advanced with more precipitation in winter, while the timing of peak greenness was advanced with more precipitation in summer. Surprisingly, summer maximum growth was negatively affected by winter precipitation. The spatial variations between summer and winter phenology were similar in magnitude and response. Larger‐scale spatial and temporal variation showed strong differences in precipitation patterns; however the magnitudes of phenological spatial variability in these two seasons were similar. Conclusions: Vegetation patterns were clearly coupled to precipitation variability, with distinct responses at alternative spatial and temporal scales. Disaggregating vegetation into phenological variation, spanning value, timing, and integrated components revealed substantial complexity in precipitation‐phenological relationships.     

Temperature and snowfall trigger alpine vegetation green‐up on the world's roof

Rapid temperature increase and its impacts on alpine ecosystems in the Qinghai–Tibetan Plateau, the world's highest and largest plateau, are a matter of global concern. Satellite observations have revealed distinctly different trend changes and contradicting temperature responses of vegetation green‐up dates, leading to broad debate about the Plateau's spring phenology and its climatic attribution. Large uncertainties in remote‐sensing estimates of phenology significantly limit efforts to predict the impacts of climate change on vegetation growth and carbon balance in the Qinghai–Tibetan Plateau, which are further exacerbated by a lack of detailed ground observation calibration. Here, we revealed the spatiotemporal variations and climate drivers of ground‐based herbaceous plant green‐up dates using 72 green‐up datasets for 22 herbaceous plant species at 23 phenological stations, and corresponding daily mean air temperature and daily precipitation data from 19 climate stations across eastern and southern parts of the Qinghai–Tibetan Plateau from 1981 to 2011. Results show that neither the continuously advancing trend from 1982 to 2011, nor a turning point in the mid to late 1990s as reported by remote‐sensing studies can be verified by most of the green‐up time series, and no robust evidence for a warmer winter‐induced later green‐up dates can be detected. Thus, chilling requirements may not be an important driver influencing green‐up responses to spring warming. Moreover, temperature‐only control of green‐up dates appears mainly at stations with relatively scarce preseason snowfall and lower elevation, while coupled temperature and precipitation controls of green‐up dates occur mostly at stations with relatively abundant preseason snowfall and higher elevation. The diversified interactions between snowfall and temperature during late winter to early spring likely determine the spatiotemporal variations of green‐up dates. Therefore, prediction of vegetation growth and carbon balance responses to global climate change on the world's roof should integrate both temperature and snowfall variations.     

Large‐scale prerain vegetation green‐up across Africa

Information on the response of vegetation to different environmental drivers, including rainfall, forms a critical input to ecosystem models. Currently, such models are run based on parameters that, in some cases, are either assumed or lack supporting evidence (e.g., that vegetation growth across Africa is rainfall‐driven). A limited number of studies have reported that the onset of rain across Africa does not fully explain the onset of vegetation growth, for example, drawing on the observation of prerain flush effects in some parts of Africa. The spatial extent of this prerain green‐up effect, however, remains unknown, leaving a large gap in our understanding that may bias ecosystem modelling. This paper provides the most comprehensive spatial assessment to‐date of the magnitude and frequency of the different patterns of phenology response to rainfall across Africa and for different vegetation types. To define the relations between phenology and rainfall, we investigated the spatial variation in the difference, in number of days, between the start of rainy season (SRS) and start of vegetation growing season (SOS); and between the end of rainy season (ERS) and end of vegetation growing season (EOS). We reveal a much more extensive spread of prerain green‐up over Africa than previously reported, with prerain green‐up being the norm rather than the exception. We also show the relative sparsity of postrain green‐up, confined largely to the Sudano‐Sahel region. While the prerain green‐up phenomenon is well documented, its large spatial extent was not anticipated. Our results, thus, contrast with the widely held view that rainfall drives the onset and end of the vegetation growing season across Africa. Our findings point to a much more nuanced role of rainfall in Africa's vegetation growth cycle than previously thought, specifically as one of a set of several drivers, with important implications for ecosystem modelling.     

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.     

Predicting bird phenology from space: satellite‐derived vegetation green‐up signal uncovers spatial variation in phenological synchrony between birds and their environment

Population‐level studies of how tit species (Parus spp.) track the changing phenology of their caterpillar food source have provided a model system allowing inference into how populations can adjust to changing climates, but are often limited because they implicitly assume all individuals experience similar environments. Ecologists are increasingly using satellite‐derived data to quantify aspects of animals' environments, but so far studies examining phenology have generally done so at large spatial scales. Considering the scale at which individuals experience their environment is likely to be key if we are to understand the ecological and evolutionary processes acting on reproductive phenology within populations. Here, we use time series of satellite images, with a resolution of 240 m, to quantify spatial variation in vegetation green‐up for a 385‐ha mixed‐deciduous woodland. Using data spanning 13 years, we demonstrate that annual population‐level measures of the timing of peak abundance of winter moth larvae (Operophtera brumata) and the timing of egg laying in great tits (Parus major) and blue tits (Cyanistes caeruleus) is related to satellite‐derived spring vegetation phenology. We go on to show that timing of local vegetation green‐up significantly explained individual differences in tit reproductive phenology within the population, and that the degree of synchrony between bird and vegetation phenology showed marked spatial variation across the woodland. Areas of high oak tree (Quercus robur) and hazel (Corylus avellana) density showed the strongest match between remote‐sensed vegetation phenology and reproductive phenology in both species. Marked within‐population variation in the extent to which phenology of different trophic levels match suggests that more attention should be given to small‐scale processes when exploring the causes and consequences of phenological matching. We discuss how use of remotely sensed data to study within‐population variation could broaden the scale and scope of studies exploring phenological synchrony between organisms and their environment.     

Chilling and forcing temperatures interact to predict the onset of wood formation in Northern Hemisphere conifers

The phenology of wood formation is a critical process to consider for predicting how trees from the temperate and boreal zones may react to climate change. Compared to leaf phenology, however, the determinism of wood phenology is still poorly known. Here, we compared for the first time three alternative ecophysiological model classes (threshold models, heat‐sum models and chilling‐influenced heat‐sum models) and an empirical model in their ability to predict the starting date of xylem cell enlargement in spring, for four major Northern Hemisphere conifers (Larix decidua, Pinus sylvestris, Picea abies and Picea mariana). We fitted models with Bayesian inference to wood phenological data collected for 220 site‐years over Europe and Canada. The chilling‐influenced heat‐sum model received most support for all the four studied species, predicting validation data with a 7.7‐day error, which is within one day of the observed data resolution. We conclude that both chilling and forcing temperatures determine the onset of wood formation in Northern Hemisphere conifers. Importantly, the chilling‐influenced heat‐sum model showed virtually no spatial bias whichever the species, despite the large environmental gradients considered. This suggests that the spring onset of wood formation is far less affected by local adaptation than by environmentally driven plasticity. In a context of climate change, we therefore expect rising winter–spring temperature to exert ambivalent effects on the spring onset of wood formation, tending to hasten it through the accumulation of forcing temperature, but imposing a higher forcing temperature requirement through the lower accumulation of chilling.     

Effects of growth temperature and chilling duration on leaf phenology of <Emphasis Type="Italic">Fauria crista</Emphasis>-<Emphasis Type="Italic">galli</Emphasis> subsp. <Emphasis Type="Italic">japonica</Emphasis>, an alpine snowbed geophyte

I examined the effects of growth temperature and winter duration on the leaf phenology of Fauria crista-galli plants, which have an indeterminate growth habit. After a 220-day chilling treatment, the leaf expansion and green periods of plants maintained at 25/20°C were much longer than those of plants maintained at 15/10°C and of plants at the natural habitat obtained in a previous study. The results indicate that early growth cessation and early leaf senescence in the natural habitat are not only due to endogenous rhythm but determined to some extent by cool summer temperatures. When grown at 15/10°C, the green period of individual leaves and plants was much shorter after a long chilling treatment (220 days) than after a short chilling treatment (110 days). The plants sprouted during or immediately after the termination of chilling treatment, suggesting that the decrease in the green period results partly from an advance of endogenous developmental stages during the chilling treatment and that the timing of snowmelt potentially affects the time of leaf senescence in the natural habitat.     

Precipitation impacts on vegetation spring phenology on the Tibetan Plateau

The ongoing changes in vegetation spring phenology in temperate/cold regions are widely attributed to temperature. However, in arid/semiarid ecosystems, the correlation between spring temperature and phenology is much less clear. We test the hypothesis that precipitation plays an important role in the temperature dependency of phenology in arid/semiarid regions. We therefore investigated the influence of preseason precipitation on satellite‐derived estimates of starting date of vegetation growing season (SOS) across the Tibetan Plateau (TP). We observed two clear patterns linking precipitation to SOS. First, SOS is more sensitive to interannual variations in preseason precipitation in more arid than in wetter areas. Spatially, an increase in long‐term averaged preseason precipitation of 10 mm corresponds to a decrease in the precipitation sensitivity of SOS by about 0.01 day mm^?1. Second, SOS is more sensitive to variations in preseason temperature in wetter than in dryer areas of the plateau. A spatial increase in precipitation of 10 mm corresponds to an increase in temperature sensitivity of SOS of 0.25 day °C^?1 (0.25 day SOS advance per 1 °C temperature increase). Those two patterns indicate both direct and indirect impacts of precipitation on SOS on TP. This study suggests a balance between maximizing benefit from the limiting climatic resource and minimizing the risk imposed by other factors. In wetter areas, the lower risk of drought allows greater temperature sensitivity of SOS to maximize the thermal benefit, which is further supported by the weaker interannual partial correlation between growing degree days and preseason precipitation. In more arid areas, maximizing the benefit of water requires greater sensitivity of SOS to precipitation, with reduced sensitivity to temperature. This study highlights the impacts of precipitation on SOS in a large cold and arid/semiarid region and suggests that influences of water should be included in SOS module of terrestrial ecosystem models for drylands.     

Extension of the growing season due to delayed autumn over mid and high latitudes in North America during 1982–2006

Aim We intend to characterize and understand the spatial and temporal patterns of vegetation phenology shifts in North America during the period 1982–2006. Location North America. Methods A piecewise logistic model is used to extract phenological metrics from a time‐series data set of the normalized difference vegetation index (NDVI). An extensive comparison between satellite‐derived phenological metrics and ground‐based phenology observations for 14,179 records of 73 plant species at 802 sites across North America is made to evaluate the information about phenology shifts obtained in this study. Results The spatial pattern of vegetation phenology shows a strong dependence on latitude but a substantial variation along the longitudinal gradient. A delayed dormancy onset date (0.551 days year^?1, P= 0.013) and an extended growing season length (0.683 days year^?1, P= 0.011) are found over the mid and high latitudes in North America during 1982–2006, while no significant trends in greenup onset are observed. The delayed dormancy onset date and extended growing season length are mainly found in the shrubland biome. An extensive validation indicates a strong robustness of the satellite‐derived phenology information. Main conclusions It is the delayed dormancy onset date, rather than an advanced greenup onset date, that has contributed to the prolonged length of the growing season over the mid and high latitudes in North America during recent decades. Shrublands contribute the most to the delayed dormancy onset date and the extended growing season length. This shift of vegetation phenology implies that vegetation activity in North America has been altered by climatic change, which may further affect ecosystem structure and function in the continent.     

Delayed autumn phenology in the Northern Hemisphere is related to change in both climate and spring phenology

The timing of the end of the vegetation growing season (EOS) plays a key role in terrestrial ecosystem carbon and nutrient cycles. Autumn phenology is, however, still poorly understood, and previous studies generally focused on few species or were very limited in scale. In this study, we applied four methods to extract EOS dates from NDVI records between 1982 and 2011 for the Northern Hemisphere, and determined the temporal correlations between EOS and environmental factors (i.e., temperature, precipitation and insolation), as well as the correlation between spring and autumn phenology, using partial correlation analyses. Overall, we observed a trend toward later EOS in ~70% of the pixels in Northern Hemisphere, with a mean rate of 0.18 ± 0.38 days yr^?1. Warming preseason temperature was positively associated with the rate of EOS in most of our study area, except for arid/semi‐arid regions, where the precipitation sum played a dominant positive role. Interestingly, increased preseason insolation sum might also lead to a later date of EOS. In addition to the climatic effects on EOS, we found an influence of spring vegetation green‐up dates on EOS, albeit biome dependent. Our study, therefore, suggests that both environmental factors and spring phenology should be included in the modeling of EOS to improve the predictions of autumn phenology as well as our understanding of the global carbon and nutrient balances.     

Local snow melt and temperature—but not regional sea ice—explain variation in spring phenology in coastal Arctic tundra

The Arctic is undergoing dramatic environmental change with rapidly rising surface temperatures, accelerating sea ice decline and changing snow regimes, all of which influence tundra plant phenology. Despite these changes, no globally consistent direction of trends in spring phenology has been reported across the Arctic. While spring has advanced at some sites, spring has delayed or not changed at other sites, highlighting substantial unexplained variation. Here, we test the relative importance of local temperatures, local snow melt date and regional spring drop in sea ice extent as controls of variation in spring phenology across different sites and species. Trends in long‐term time series of spring leaf‐out and flowering (average span: 18 years) were highly variable for the 14 tundra species monitored at our four study sites on the Arctic coasts of Alaska, Canada and Greenland, ranging from advances of 10.06 days per decade to delays of 1.67 days per decade. Spring temperatures and the day of spring drop in sea ice extent advanced at all sites (average 1°C per decade and 21 days per decade, respectively), but only those sites with advances in snow melt (average 5 days advance per decade) also had advancing phenology. Variation in spring plant phenology was best explained by snow melt date (mean effect: 0.45 days advance in phenology per day advance snow melt) and, to a lesser extent, by mean spring temperature (mean effect: 2.39 days advance in phenology per °C). In contrast to previous studies examining sea ice and phenology at different spatial scales, regional spring drop in sea ice extent did not predict spring phenology for any species or site in our analysis. Our findings highlight that tundra vegetation responses to global change are more complex than a direct response to warming and emphasize the importance of snow melt as a local driver of tundra spring phenology.     

Public Internet‐connected cameras used as a cross‐continental ground‐based plant phenology monitoring system

Plant phenology is highly sensitive to changes in environmental conditions and can vary widely across landscapes. Current observation methods are either manual for small‐scale, high precision measurements or by satellite remote sensing for large‐scale, low spatial resolution measurement. The development of inexpensive approaches is necessary to advance large scale, high precision phenology monitoring. The use of publicly available, Internet‐connected cameras, often associated with airports, national parks, and roadway conditions, for detecting and monitoring plant phenology at a continental scale can augment existing ground and satellite‐based methodologies. We collected twice‐daily images from over 1100 georeferenced public cameras across North America from February 2008 to 2009. Using a test subset of these cameras, we compared modeled spring ‘green‐up’ with that from co‐occurring remote sensing products. Although varying image exposure and color correction introduced noise to camera measurements, we were able to correlate spring green‐up across North America with visual validation from images and detect a latitudinal trend. Public cameras had an equivalent or higher ability to detect spring compared with satellite‐based data for corresponding locations, with fewer numbers of poor quality days, shorter continuous bad data days, and significantly lower errors of spring estimates. Manual image segmentation into deciduous, evergreen, and understory vegetation allowed detection of spring and fall onset for multiple vegetation types. Additional advantages of a public camera‐based monitoring system include frequent image capture (subdaily) and the potential to detect quantitative responses to environmental changes in organisms, species, and communities. Public cameras represent a relatively untapped and freely available resource for supporting large‐scale ecological and environmental monitoring.     

Experimental warming alters spring phenology of certain plant functional groups in an early successional forest community

Experimental study of the effects of projected climate change on plant phenology allows us to isolate effects of warming on life‐history events such as leaf out. We simulated a 2 °C temperature increase and 20% precipitation increase in a recently harvested temperate deciduous forest community in central Pennsylvania, USA, and observed the leaf out phenology of all species in 2009 and 2010. Over 130 plant species were monitored weekly in study plots, but due to high variability in species composition among plots, species were grouped into five functional groups: short forbs, tall forbs, shrubs, small trees, and large trees. Tall forbs and large trees, which usually emerge in the late spring, advanced leaf out 14–18 days in response to warming. Short forbs, shrubs, and small trees emerge early in spring and did not alter their phenology in response to warming or increased precipitation treatments. Earlier leaf out of tall forbs and large trees coincided with almost 3 weeks of increased community‐level leaf area index, indicating greater competition and a condensed spring green‐up period. While phenology of large trees and tall forbs appears to be strongly influenced by temperature‐based growth cues, our results suggest that photoperiod and chilling cues more strongly influence the leaf out of other functional groups. Reduced freeze events and warmer temperatures from predicted climate change will interact with nontemperature growth cues to have cascading consequences throughout the ecosystem.     

1982—2009年基于卫星数据的北半球中高纬地区植被春季物候动态及其与气候的关系

深入认识北半球植被物候在全球变暖背景下的动态变化特征,对于评估和预测生态系统结构和功能对气候变化的响应有重要的指示作用.遥感技术是获取北半球植被春季物候的最重要方法,但是由于物候提取算法的差异,目前还存在较大的不确定性.本文利用5种方法,基于卫星获取的归一化植被指数估算了北半球中高纬地区1982—2009年植被春季物候开始日期,分析了该日期的多年动态变化的时空特征,并探讨了气候变化对春季物候变化的影响.结果表明: 研究区植被春季物候开始日期呈现提前趋势,研究期间提前(4.0±0.8) d,其中,欧亚大陆提前速率为(0.22±0.04) d·a^-1,显著高于北美大陆的变化速率(0.03±0.02 d·a^-1);不同植被类型的变化趋势不同,5种方法都显示草地表现为显著提前趋势,而林地的提前趋势不显著.区域平均的植被春季物候开始日期的年际波动主要受春季温度的变化所驱动(r² =0.61,P<0.001), 温度每上升1 ℃,可以导致春季物候提前(3.2±0.5) d,而春季降水影响不显著(P>0.05).     

Temperature alone does not explain phenological variation of diverse temperate plants under experimental warming

Anthropogenic climate change has altered temperate forest phenology, but how these trends will play out in the future is controversial. We measured the effect of experimental warming of 0.6–5.0 °C on the phenology of a diverse suite of 11 plant species in the deciduous forest understory (Duke Forest, North Carolina, USA) in a relatively warm year (2011) and a colder year (2013). Our primary goal was to dissect how temperature affects timing of spring budburst, flowering, and autumn leaf coloring for functional groups with different growth habits, phenological niches, and xylem anatomy. Warming advanced budburst of six deciduous woody species by 5–15 days and delayed leaf coloring by 18–21 days, resulting in an extension of the growing season by as much as 20–29 days. Spring temperature accumulation was strongly correlated with budburst date, but temperature alone cannot explain the diverse budburst responses observed among plant functional types. Ring‐porous trees showed a consistent temperature response pattern across years, suggesting these species are sensitive to photoperiod. Conversely, diffuse‐porous species responded differently between years, suggesting winter chilling may be more important in regulating budburst. Budburst of the ring‐porous Quercus alba responded nonlinearly to warming, suggesting evolutionary constraints may limit changes in phenology, and therefore productivity, in the future. Warming caused a divergence in flowering times among species in the forest community, resulting in a longer flowering season by 10‐16 days. Temperature was a good predictor of flowering for only four of the seven species studied here. Observations of interannual temperature variability overpredicted flowering responses in spring‐blooming species, relative to our warming experiment, and did not consistently predict even the direction of flowering shifts. Experiments that push temperatures beyond historic variation are indispensable for improving predictions of future changes in phenology.     

Maternal winter body mass and not spring phenology determine annual calf production in an Arctic herbivore

Warming of the Arctic has resulted in earlier snowmelt and green‐up of plants in spring, potentially disrupting the synchrony between plant phenology and breeding phenology in herbivores. A negative relationship between offspring survival in West Greenland caribou and the timing of vegetation emergence was the first finding of such a mismatch in Arctic mammals. However, other studies indicate that the energy for foetal growth and early lactation is predominantly drawn from stored energy reserves typical of ‘capital’ breeders, suggesting that conditions well before spring influence calf production more than the timing of spring onset. Here we use 20 years of observations of marked Svalbard reindeer to evaluate determinants of annual recruitment, as measured by the presence of a calf at foot in mid‐summer. Spring temperatures and the enhanced vegetation index were used as proxies for spring onset, while data on body mass and pregnancy rates in late winter allowed us to determine maternal condition and the reproductive status before spring. Pregnancy rate, offspring survival and annual recruitment were all strongly correlated with average late winter adult female body mass (r = 0.87; r = 0.83; r = 0.92, respectively). Contrary to the findings in West Greenland, neither early calf survival nor annual recruitment were correlated with the two measures of annual variation in spring phenology (r = – 0.07, p = 0.8 and r = – 0.15, p = 0.6, respectively). We also revisit the Greenland data and reveal that the pattern of covariance between early and late measures of fecundity, as well as between early measures of fecundity and offspring survival, correspond with the results from Svalbard. Our results emphasize that conditions affecting maternal body mass during winter explain close to all the variation in recruitment, questioning the importance of the role of a mismatch between plant phenology and calving date.     

The North Atlantic Oscillation and regional phenology prediction over Europe

We present an integrated modeling study designed to investigate changes in ecosystem level phenology over Europe associated with changes in climate pattern, by the North Atlantic Oscillation (NAO). We derived onset dates from processed NDVI data sets and used growing degree day (GDD) summations from the NCEP re‐analysis to calibrate and validate a phenology model to predict the onset of the growing season over Europe. In a cross‐validation hindcast, the model (PHENOM) is able to explain 63% of the variance in onset date for grid cells containing at least 50% mixed and boreal forest. Using a model developed from previous work we performed climate change scenarios, generating synthetic temperature and GDD distributions under a hypothetically increasing NAO. These new distributions were used to drive PHENOM and project changes in the timing of onset for forested cells over Europe. Results from the climate change scenarios indicate that, if the current trend in the NAO continues, there is the potential for a continued advance to the start of the growing season by as much as 13 days in some areas.     

Temperature sensitivity of spring vegetation phenology correlates to within-spring warming speed over the Northern Hemisphere

The inter-annual shift of spring vegetation phenology relative to per unit change of preseason temperature, referred to as temperature sensitivity (days °C⁻¹), quantifies the response of spring phenology to temperature change. Temperature sensitivity was found to differ greatly among vegetation from different environmental conditions. Understanding the large-scale spatial pattern of temperature sensitivity and its underlying determinant will greatly improve our ability to predict spring phenology. In this study, we investigated the temperature sensitivity for natural ecosystems over the North Hemisphere (north of 30°N), based on the vegetation phenological date estimated from NDVI time-series data provided by the Advanced Very High Resolution Radiometer (AVHRR) and the corresponding climate dataset. We found a notable longitudinal change pattern with considerable increases of temperature sensitivity from inlands to most coastal areas and a less obvious latitudinal pattern with larger sensitivity in low latitude area. This general spatial variation in temperature sensitivity is most strongly associated with the within-spring warming speed (WWS; r = 0.35, p < 0.01), a variable describing the increase speed of daily mean temperature during spring within a year, compared with other factors including the mean spring temperature, spring precipitation and mean winter temperature. These findings suggest that the same magnitude of warming will less affect spring vegetation phenology in regions with higher WWS, which might partially reflect plants’ adaption to local climate that prevents plants from frost risk caused by the advance of spring phenology. WWS accounts for the spatial variation in temperature sensitivity and should be taken into account in forecasting spring phenology and in assessing carbon cycle under the projected climate warming.