Forecasting phenology under global warming

As a consequence of warming temperatures around the world, spring and autumn phenologies have been shifting, with corresponding changes in the length of the growing season. Our understanding of the spatial and interspecific variation of these changes, however, is limited. Not all species are responding similarly, and there is significant spatial variation in responses even within species. This spatial and interspecific variation complicates efforts to predict phenological responses to ongoing climate change, but must be incorporated in order to build reliable forecasts. Here, we use a long-term dataset (1953–2005) of plant phenological events in spring (flowering and leaf out) and autumn (leaf colouring and leaf fall) throughout Japan and South Korea to build forecasts that account for these sources of variability. Specifically, we used hierarchical models to incorporate the spatial variability in phenological responses to temperature to then forecast species'' overall and site-specific responses to global warming. We found that for most species, spring phenology is advancing and autumn phenology is getting later, with the timing of events changing more quickly in autumn compared with the spring. Temporal trends and phenological responses to temperature in East Asia contrasted with results from comparable studies in Europe, where spring events are changing more rapidly than are autumn events. Our results emphasize the need to study multiple species at many sites to understand and forecast regional changes in phenology.     

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.     

Landscape controls on the timing of spring,autumn, and growing season length in mid‐Atlantic forests

The timing of spring leaf development, trajectories of summer leaf area, and the timing of autumn senescence have profound impacts to the water, carbon, and energy balance of ecosystems, and are likely influenced by global climate change. Limited field‐based and remote‐sensing observations have suggested complex spatial patterns related to geographic features that influence climate. However, much of this variability occurs at spatial scales that inhibit a detailed understanding of even the dominant drivers. Recognizing these limitations, we used nonlinear inverse modeling of medium‐resolution remote sensing data, organized by day of year, to explore the influence of climate‐related landscape factors on the timing of spring and autumn leaf‐area trajectories in mid‐Atlantic, USA forests. We also examined the extent to which declining summer greenness (greendown) degrades the precision and accuracy of observations of autumn offset of greenness. Of the dominant drivers of landscape phenology, elevation was the strongest, explaining up to 70% of the spatial variation in the onset of greenness. Urban land cover was second in importance, influencing spring onset and autumn offset to a distance of 32 km from large cities. Distance to tidal water also influenced phenological timing, but only within ~5 km of shorelines. Additionally, we observed that (i) growing season length unexpectedly increases with increasing elevation at elevations below 275 m; (ii) along gradients in urban land cover, timing of autumn offset has a stronger effect on growing season length than does timing of spring onset; and (iii) summer greendown introduces bias and uncertainty into observations of the autumn offset of greenness. These results demonstrate the power of medium grain analyses of landscape‐scale phenology for understanding environmental controls on growing season length, and predicting how these might be affected by climate change.     

The influence of life history traits on the phenological response of British butterflies to climate variability since the late‐19th century

Many species of plants and animals have advanced their phenology in response to climate warming in recent decades. Most of the evidence available for these shifts is based on data from the last few decades, a period coinciding with rapid climate warming. Baseline data is required to put these recent phenological changes in a long‐term context. We analysed the phenological response of 51 resident British butterfly species using data from 83 500 specimens in the collections of the Natural History Museum, London, covering the period 1880–1970. Our analysis shows that only three species significantly advanced their phenology between 1880 and 1970, probably reflecting the relatively small increase in spring temperature over this period. However, the phenology of all but one of the species we analysed showed phenological sensitivity to inter‐annual climate variability and a significant advancement in phenology in years in which spring or summer temperatures were warm and dry. The phenologies of butterfly species were more sensitive to weather if the butterfly species was early flying, southerly distributed, and a generalist in terms of larval diet. This observation is consistent with the hypothesis that species with greater niche breadth may be more phenologically sensitive than species with important niche constraints. Comparison of our results with post‐1976 data from the UK Butterfly Monitoring Scheme show that species flying early in the year had a greater rate of phenological advancement prior to the mid‐1970s. Additionally, prior to the mid‐1970s, phenology was influenced by temperatures in March or April, whereas since 1976, February temperature had a stronger influence on the phenology. These results suggest that early flying species may be approaching the limits of phenological advancement in response to recent climate warming.     

Climatic change is advancing the phenology of moth species in Ireland

Recent increases in global temperatures have contributed to advancing phenology of plants and animals. These increases in temperature have been shown to affect the phenological phases (phenophases) of plants and birds in Ireland, but less is known about the effect on the phenophases of Irish insects. Records of the flight periods of 59 species of Irish moths over the past 35 years (1974–2009) were obtained from a public monitoring group. Observations were analysed across the country using generalized additive models (GAMs) weighted by total yearly population numbers for each species. The results of the statistical analyses showed that 45 of the 59 species studied have a significantly earlier first sighting date now than when observations began. With this earlier emergence, 44 of the 59 species also have a significantly longer flight season over the same 35‐year period. The extent of these changes varies across the country and by species life history. In particular, species emerging in spring are advancing at a much faster rate than species emerging during the summer. Many of these changes in first sighting are negatively correlated with rising temperatures in Ireland, particularly in late spring and early summer (May and June). The variation in phenological advancement in the moth species of Ireland is extremely complex and may be influenced more by species life history than by the phenology of interacting species, such as host plants.     

Multiscale modeling of spring phenology across Deciduous Forests in the Eastern United States

Phenological events, such as bud burst, are strongly linked to ecosystem processes in temperate deciduous forests. However, the exact nature and magnitude of how seasonal and interannual variation in air temperatures influence phenology is poorly understood, and model‐based phenology representations fail to capture local‐ to regional‐scale variability arising from differences in species composition. In this paper, we use a combination of surface meteorological data, species composition maps, remote sensing, and ground‐based observations to estimate models that better represent how community‐level species composition affects the phenological response of deciduous broadleaf forests to climate forcing at spatial scales that are typically used in ecosystem models. Using time series of canopy greenness from repeat digital photography, citizen science data from the USA National Phenology Network, and satellite remote sensing‐based observations of phenology, we estimated and tested models that predict the timing of spring leaf emergence across five different deciduous broadleaf forest types in the eastern United States. Specifically, we evaluated two different approaches: (i) using species‐specific models in combination with species composition information to ‘upscale’ model predictions and (ii) using repeat digital photography of forest canopies that observe and integrate the phenological behavior of multiple representative species at each camera site to calibrate a single model for all deciduous broadleaf forests. Our results demonstrate variability in cumulative forcing requirements and photoperiod cues across species and forest types, and show how community composition influences phenological dynamics over large areas. At the same time, the response of different species to spatial and interannual variation in weather is, under the current climate regime, sufficiently similar that the generic deciduous forest model based on repeat digital photography performed comparably to the upscaled species‐specific models. More generally, results from this analysis demonstrate how in situ observation networks and remote sensing data can be used to synergistically calibrate and assess regional parameterizations of phenology in models.     

Detecting nonlinear response of spring phenology to climate change by Bayesian analysis

The impact of climate change on the advancement of plant phenological events has been heavily studied in the last decade. Although the majority of spring plant phenological events have been trending earlier, this is not universally true. Recent work has suggested that species that are not advancing in their spring phenological behavior are responding more to lack of winter chill than increased spring heat. One way to test this hypothesis is by evaluating the behavior of a species known to have a moderate to high chilling requirement and examining how it is responding to increased warming. This study used a 60‐year data set for timing of leaf‐out and male flowering of walnut (Juglans regia) cultivar ‘Payne’ to examine this issue. The spring phenological behavior of ‘Payne’ walnut differed depending on bud type. The vegetative buds, which have a higher chilling requirement, trended toward earlier leaf‐out until about 1994, when they shifted to later leaf‐out. The date of male bud pollen shedding advanced over the course of the whole record. Our findings suggest that many species which have exhibited earlier bud break are responding to warmer spring temperatures, but may shift into responding more to winter temperatures (lack of adequate chilling) as warming continues.     

Impact of climate change on plant phenology in Mediterranean ecosystems

Plant phenology is strongly controlled by climate and has consequently become one of the most reliable bioindicators of ongoing climate change. We used a dataset of more than 200 000 records for six phenological events of 29 perennial plant species monitored from 1943 to 2003 for a comprehensive assessment of plant phenological responses to climate change in the Mediterranean region. Temperature, precipitation and North Atlantic Oscillation (NAO) were studied together during a complete annual cycle before phenological events to determine their relative importance and potential seasonal carry‐over effects. Warm and dry springs under a positive phase of NAO advance flowering, leaf unfolding and fruiting dates and lengthen the growing season. Spatial variability of dates (range among sites) was also reduced during warm and dry years, especially for spring events. Climate during previous weeks to phenophases occurrence had the greatest impact on plants, although all events were also affected by climate conditions several months before. Immediate along with delayed climate effects suggest dual triggers in plant phenology. Climatic models accounted for more than 80% of variability in flowering and leaf unfolding dates, and in length of the growing season, but for lower proportions in fruiting and leaf falling. Most part of year‐to‐year changes in dates was accounted for temperature, while precipitation and NAO accounted for <10% of dates' variability. In the case of flowering, insect‐pollinated species were better modelled by climate than wind‐pollinated species. Differences in temporal responses of plant phenology to recent climate change are due to differences in the sensitivity to climate among events and species. Spring events are changing more than autumn events as they are more sensitive to climate and are also undergoing the greatest alterations of climate relative to other seasons. In conclusion, climate change has shifted plant phenology in the Mediterranean region.     

Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982–2006

Shifts in the timing of spring phenology are a central feature of global change research. Long‐term observations of plant phenology have been used to track vegetation responses to climate variability but are often limited to particular species and locations and may not represent synoptic patterns. Satellite remote sensing is instead used for continental to global monitoring. Although numerous methods exist to extract phenological timing, in particular start‐of‐spring (SOS), from time series of reflectance data, a comprehensive intercomparison and interpretation of SOS methods has not been conducted. Here, we assess 10 SOS methods for North America between 1982 and 2006. The techniques include consistent inputs from the 8 km Global Inventory Modeling and Mapping Studies Advanced Very High Resolution Radiometer NDVIg dataset, independent data for snow cover, soil thaw, lake ice dynamics, spring streamflow timing, over 16 000 individual measurements of ground‐based phenology, and two temperature‐driven models of spring phenology. Compared with an ensemble of the 10 SOS methods, we found that individual methods differed in average day‐of‐year estimates by ±60 days and in standard deviation by ±20 days. The ability of the satellite methods to retrieve SOS estimates was highest in northern latitudes and lowest in arid, tropical, and Mediterranean ecoregions. The ordinal rank of SOS methods varied geographically, as did the relationships between SOS estimates and the cryospheric/hydrologic metrics. Compared with ground observations, SOS estimates were more related to the first leaf and first flowers expanding phenological stages. We found no evidence for time trends in spring arrival from ground‐ or model‐based data; using an ensemble estimate from two methods that were more closely related to ground observations than other methods, SOS trends could be detected for only 12% of North America and were divided between trends towards both earlier and later spring.     

Similarities in butterfly emergence dates among populations suggest local adaptation to climate

Phenology shifts are the most widely cited examples of the biological impact of climate change, yet there are few assessments of potential effects on the fitness of individual organisms or the persistence of populations. Despite extensive evidence of climate‐driven advances in phenological events over recent decades, comparable patterns across species' geographic ranges have seldom been described. Even fewer studies have quantified concurrent spatial gradients and temporal trends between phenology and climate. Here we analyse a large data set (~129 000 phenology measures) over 37 years across the UK to provide the first phylogenetic comparative analysis of the relative roles of plasticity and local adaptation in generating spatial and temporal patterns in butterfly mean flight dates. Although populations of all species exhibit a plastic response to temperature, with adult emergence dates earlier in warmer years by an average of 6.4 days per °C, among‐population differences are significantly lower on average, at 4.3 days per °C. Emergence dates of most species are more synchronised over their geographic range than is predicted by their relationship between mean flight date and temperature over time, suggesting local adaptation. Biological traits of species only weakly explained the variation in differences between space‐temperature and time‐temperature phenological responses, suggesting that multiple mechanisms may operate to maintain local adaptation. As niche models assume constant relationships between occurrence and environmental conditions across a species' entire range, an important implication of the temperature‐mediated local adaptation detected here is that populations of insects are much more sensitive to future climate changes than current projections suggest.     

Alpine grassland plants grow earlier and faster but biomass remains unchanged over 35 years of climate change

Satellite data indicate significant advancement in alpine spring phenology over decades of climate warming, but corresponding field evidence is scarce. It is also unknown whether this advancement results from an earlier shift of phenological events, or enhancement of plant growth under unchanged phenological pattern. By analyzing a 35‐year dataset of seasonal biomass dynamics of a Tibetan alpine grassland, we show that climate change promoted both earlier phenology and faster growth, without changing annual biomass production. Biomass production increased in spring due to a warming‐induced earlier onset of plant growth, but decreased in autumn due mainly to increased water stress. Plants grew faster but the fast‐growing period shortened during the mid‐growing season. These findings provide the first in situ evidence of long‐term changes in growth patterns in alpine grassland plant communities, and suggest that earlier phenology and faster growth will jointly contribute to plant growth in a warming climate.     

Elevational trends in butterfly phenology: implications for species responses to climate change

1. Impacts of global change on the distribution, abundance, and phenology of species have been widely documented. In particular, recent climate change has led to widespread changes in animal and plant seasonality, leading to debate about its potential to cause phenological mismatches among interacting taxa. 2. In mountainous regions, populations of many species show pronounced phenological gradients over short geographic distances, presenting the opportunity to test for effects of climate on phenology, independent of variation in confounding factors such as photoperiod. 3. Here we show for 32 butterfly species sampled for five years over a 1700 m gradient (560–2260 m) in a Mediterranean mountain range that, on average, annual flight period is delayed with elevation by 15–22 days per kilometre. Species mainly occurring at low elevations in the region, and to some extent those flying earlier in the year, showed phenological delays of 23–36 days per kilometre, whereas the flight periods of species that occupy high elevations, or fly in late summer, were consistently more synchronised over the elevation gradient. 4. Elevational patterns in phenology appear to reflect a narrowing phenological window of opportunity for larval and adult butterfly activity of high elevation and late‐flying species. 5. Here, we speculate as to the causes of these patterns, and the consequences for our ability to predict species responses to climate change. Our results raise questions about the use of space–time substitutions in predicting phenological responses to climate change, since traits relating to flight period and environmental associations may influence the capacity of species to adapt to changing climates.     

The roles of shifting and filtering in generating community‐level flowering phenology

Plant phenologies are key components of community assembly and ecosystem function, yet we know little about how phenological patterns differ among ecosystems. Community‐level phenological patterns may be driven by the filtering of species into communities based on their phenology or by intraspecific responses to local conditions that shift when species flower. To understand the relative roles of filtering and shifting on community‐level phenological patterns we compared patterns of first flowering dates (FFD) for herbaceous species at Konza Prairie, KS, USA with those from the colder Fargo, ND, USA area and from Chinnor, England, which has a less continental climate. Comparing patterns of FFD supports that Konza's flowering patterns are potentially influenced both by filtering species that flower early in the growing season and by phenological shifting. Konza species flowering dates were earlier in the spring and later in the fall compared to Fargo, but were not shifted compared to Chinnor, which had a unique suite of early‐flowering species. In all, comparing flowering phenology among three sites reveals that intraspecific responses to climate can generate phenological shifts that compress or stretch community‐level phenological patterns, while novel niches in phenological space can also alter community‐level patterns. Community flowering patterns related to climate suggest that climatic warming has the potential to further distribute flowering of the Konza flora over a longer period, but also could further open it to introductions of non‐native species that have evolved to flower early in the season.     

Contrasting effects of warming and increased snowfall on Arctic tundra plant phenology over the past two decades

Recent changes in climate have led to significant shifts in phenology, with many studies demonstrating advanced phenology in response to warming temperatures. The rate of temperature change is especially high in the Arctic, but this is also where we have relatively little data on phenological changes and the processes driving these changes. In order to understand how Arctic plant species are likely to respond to future changes in climate, we monitored flowering phenology in response to both experimental and ambient warming for four widespread species in two habitat types over 21 years. We additionally used long‐term environmental records to disentangle the effects of temperature increase and changes in snowmelt date on phenological patterns. While flowering occurred earlier in response to experimental warming, plants in unmanipulated plots showed no change or a delay in flowering over the 21‐year period, despite more than 1 °C of ambient warming during that time. This counterintuitive result was likely due to significantly delayed snowmelt over the study period (0.05–0.2 days/yr) due to increased winter snowfall. The timing of snowmelt was a strong driver of flowering phenology for all species – especially for early‐flowering species – while spring temperature was significantly related to flowering time only for later‐flowering species. Despite significantly delayed flowering phenology, the timing of seed maturation showed no significant change over time, suggesting that warmer temperatures may promote more rapid seed development. The results of this study highlight the importance of understanding the specific environmental cues that drive species’ phenological responses as well as the complex interactions between temperature and precipitation when forecasting phenology over the coming decades. As demonstrated here, the effects of altered snowmelt patterns can counter the effects of warmer temperatures, even to the point of generating phenological responses opposite to those predicted by warming alone.     

Climate change impacts on mismatches between phytoplankton blooms and fish spawning phenology

Substantial interannual variability in marine fish recruitment (i.e., the number of young fish entering a fishery each year) has been hypothesized to be related to whether the timing of fish spawning matches that of seasonal plankton blooms. Environmental processes that control the phenology of blooms, such as stratification, may differ from those that influence fish spawning, such as temperature‐linked reproductive maturation. These different controlling mechanisms could cause the timing of these events to diverge under climate change with negative consequences for fisheries. We use an earth system model to examine the impact of a high‐emissions, climate‐warming scenario (RCP8.5) on the future spawning time of two classes of temperate, epipelagic fishes: “geographic spawners” whose spawning grounds are defined by fixed geographic features (e.g., rivers, estuaries, reefs) and “environmental spawners” whose spawning grounds move responding to variations in environmental properties, such as temperature. By the century's end, our results indicate that projections of increased stratification cause spring and summer phytoplankton blooms to start 16 days earlier on average (±0.05 days SE) at latitudes >40°N. The temperature‐linked phenology of geographic spawners changes at a rate twice as fast as phytoplankton, causing these fishes to spawn before the bloom starts across >85% of this region. “Extreme events,” defined here as seasonal mismatches >30 days that could lead to fish recruitment failure, increase 10‐fold for geographic spawners in many areas under the RCP8.5 scenario. Mismatches between environmental spawners and phytoplankton were smaller and less widespread, although sizable mismatches still emerged in some regions. This indicates that range shifts undertaken by environmental spawners may increase the resiliency of fishes to climate change impacts associated with phenological mismatches, potentially buffering against declines in larval fish survival, recruitment, and fisheries. Our model results are supported by empirical evidence from ecosystems with multidecadal observations of both fish and phytoplankton phenology.     

Disentangling the paradox of insect phenology: are temporal trends reflecting the response to warming?

The strength and direction of phenological responses to changes in climate have been shown to vary significantly both among species and among populations of a species, with the overall patterns not fully resolved. Here, we studied the temporal and spatial variability associated with the response of several insect species to recent global warming. We use hierarchical models within a model comparison framework to analyze phenological data gathered over 40 years by the Japan Meteorological Agency on the emergence dates of 14 insect species at sites across Japan. Contrary to what has been predicted with global warming, temporal trends of annual emergence showed a later emergence day for some species and sites over time, even though temperatures are warming. However, when emergence data were analyzed as a function of temperature and precipitation, the overall response pointed out an earlier emergence day with warmer conditions. The apparent contradiction between the response to temperature and trends over time indicates that other factors, such as declining populations, may be affecting the date phenological events are being recorded. Overall, the responses by insects were weaker than those found for plants in previous work over the same time period in these ecosystems, suggesting the potential for ecological mismatches with deleterious effects for both suites of species. And although temperature may be the major driver of species phenology, we should be cautious when analyzing phenological datasets as many other factors may also be contributing to the variability in phenology.     

Phenology model from surface meteorology does not capture satellite-based greenup estimations

Seasonal temperature change in temperate forests is known to trigger the start of spring growth, and both interannual and spatial variations in spring onset have been tied to climatic variability. Satellite dates are increasingly being used in phenology studies, but to date that has been little effort to link remotely sensed phenology to surface climate records. In this research, we use a two‐parameter spring warming phenology model to explore the relationship between climate and satellite‐based phenology. We employ daily air temperature records between 2000 and 2005 for 171 National Oceanographic and Atmospheric Administration weather stations located throughout New England to construct spring warming models predicting the onset of spring, as defined by the date of half‐maximum greenness (D₅₀) in deciduous forests as detected from Moderate Resolution Imaging Spectrometer. The best spring warming model starts accumulating temperatures after March 20th and when average daily temperatures exceed 5°C. The accumulated heat sums [heating degree day (HDD)] required to reach D₅₀ range from 150 to 300 degree days over New England, with the highest requirements to the south and in coastal regions. We test the ability of the spring warming model to predict phenology against a null photoperiod model (average date of onset). The spring warming model offers little improvement on the null model when predicting D₅₀. Differences between the efficacies of the two models are expressed as the ‘climate sensitivity ratio’ (CSR), which displays coherent spatial patterns. Our results suggest that northern (beech‐maple‐birch) and central (oak‐hickory) hardwood forests respond to climate differently, particularly with disparate requirements for the minimum temperature necessary to begin spring growth (3 and 6°C, respectively). We conclude that spatial location and species composition are critical factors for predicting the phenological response to climate change: satellite observations cannot be linked directly to temperature variability if species or community compositions are unknown.     

The influence of local spring temperature variance on temperature sensitivity of spring phenology

The impact of climate warming on the advancement of plant spring phenology has been heavily investigated over the last decade and there exists great variability among plants in their phenological sensitivity to temperature. However, few studies have explicitly linked phenological sensitivity to local climate variance. Here, we set out to test the hypothesis that the strength of phenological sensitivity declines with increased local spring temperature variance, by synthesizing results across ground observations. We assemble ground‐based long‐term (20–50 years) spring phenology database (PEP725 database) and the corresponding climate dataset. We find a prevalent decline in the strength of phenological sensitivity with increasing local spring temperature variance at the species level from ground observations. It suggests that plants might be less likely to track climatic warming at locations with larger local spring temperature variance. This might be related to the possibility that the frost risk could be higher in a larger local spring temperature variance and plants adapt to avoid this risk by relying more on other cues (e.g., high chill requirements, photoperiod) for spring phenology, thus suppressing phenological responses to spring warming. This study illuminates that local spring temperature variance is an understudied source in the study of phenological sensitivity and highlight the necessity of incorporating this factor to improve the predictability of plant responses to anthropogenic climate change in future studies.     

Predicting the sensitivity of butterfly phenology to temperature over the past century

Studies to date have documented substantial variation among species in the degree to which phenology responds to temperature and shifts over time, but we have a limited understanding of the causes of such variation. Here, we use a spatially and temporally extensive data set (ca. 48 000 observations from across Canada) to evaluate the utility of museum collection records in detecting broad‐scale phenology‐temperature relationships and to test for systematic differences in the sensitivity of phenology to temperature (days °C^?1) of Canadian butterfly species according to relevant ecological traits. We showed that the timing of flight season predictably responded to temperature both across space (variation in average temperature from site to site in Canada) and across time (variation from year to year within each individual site). This reveals that collection records, a vastly underexploited resource, can be applied to the quantification of broad‐scale relationships between species' phenology and temperature. The timing of the flight season of earlier fliers and less mobile species was more sensitive to temperature than later fliers and more mobile species, demonstrating that ecological traits can account for some of the interspecific variation in species' phenological sensitivity to temperature. Finally, we found that phenological sensitivity to temperature differed across time and space implying that both dimensions of temperature will be needed to translate species' phenological sensitivity to temperature into accurate predictions of species' future phenological shifts. Given the widespread temperature sensitivity of flight season timing, we can expect long‐term temporal shifts with increased warming [ca. 2.4 days °C^?1 (0.18 SE)] for many if not most butterfly species.     

Delayed phenological timing of dragonfly emergence in Japan over five decades

Recent increases in air temperature have affected species phenology, resulting in the earlier onset of spring life-cycle events. Trends in the first appearance of adult dragonflies across Japan were analysed using a dataset consisting of observations from 1953 to 2005. Dynamic factor analysis was used to evaluate underlying common trends in a set of 48 time series. The appearance of the first adult dragonfly has significantly shifted to later in the spring in the past five decades. Generalized linear mixing models suggested that this is probably the result of increased air temperatures. Increased summer and autumn temperatures may provide longer bivoltine periods and a faster growth rate; thus, the second generation, which previously hatched in summer, can emerge in the autumn causing the size of the population of dragonflies that emerge in spring to decrease. It is also possible that reduced dragonfly populations along with human development are responsible for a delay in the first observed dragonflies in the spring. However, human population density did not appear to strongly affect the appearance date. This study provides the first evidence of a delay in insect phenological events over recent decades.