Community‐wide changes in intertaxonomic temporal co‐occurrence resulting from phenological shifts

Global climate change is known to affect the assembly of ecological communities by altering species' spatial distribution patterns, but little is known about how climate change may affect community assembly by changing species' temporal co‐occurrence patterns, which is highly likely given the widely observed phenological shifts associated with climate change. Here, we analyzed a 29‐year phenological data set comprising community‐level information on the timing and span of temporal occurrence in 11 seasonally occurring animal taxon groups from 329 local meteorological observatories across China. We show that widespread shifts in phenology have resulted in community‐wide changes in the temporal overlap between taxa that are dominated by extensions, and that these changes are largely due to taxa's altered span of temporal occurrence rather than the degree of synchrony in phenological shifts. Importantly, our findings also suggest that climate change may have led to less phenological mismatch than generally presumed, and that the context under which to discuss the ecological consequences of phenological shifts should be expanded beyond asynchronous shifts.     

Phenological indices of avian reproduction: cryptic shifts and prediction across large spatial and temporal scales

Climate change‐induced shifts in phenology have important demographic consequences, and are frequently used to assess species' sensitivity to climate change. Therefore, developing accurate phenological predictions is an important step in modeling species' responses to climate change. The ability of such phenological models to predict effects at larger spatial and temporal scales has rarely been assessed. It is also not clear whether the most frequently used phenological index, namely the average date of a phenological event across a population, adequately captures phenological shifts in the distribution of events across the season. We use the long‐tailed tit Aegithalos caudatus (Fig. 1) as a case study to explore these issues. We use an intensive 17‐year local study to model mean breeding date and test the capacity of this local model to predict phenology at larger spatial and temporal scales. We assess whether local models of breeding initiation, termination, and renesting reveal phenological shifts and responses to climate not detected by a standard phenological index, that is, population average lay date. These models take predation timing/intensity into account. The locally‐derived model performs well at predicting phenology at the national scale over several decades, at both high and low temperatures. In the local model, a trend toward warmer Aprils is associated with a significant advance in termination dates, probably in response to phenological shifts in food supply. This results in a 33% reduction in breeding season length over 17 years – a substantial loss of reproductive opportunity that is not detected by the index of population average lay date. We show that standard phenological indices can fail to detect patterns indicative of negative climatic effects, potentially biasing assessments of species' vulnerability to climate change. More positively, we demonstrate the potential of detailed local studies for developing broader‐scale predictive models of future phenological shifts.     

Shifts in frog size and phenology: Testing predictions of climate change on a widespread anuran using data from prior to rapid climate warming

Changes in body size and breeding phenology have been identified as two major ecological consequences of climate change, yet it remains unclear whether climate acts directly or indirectly on these variables. To better understand the relationship between climate and ecological changes, it is necessary to determine environmental predictors of both size and phenology using data from prior to the onset of rapid climate warming, and then to examine spatially explicit changes in climate, size, and phenology, not just general spatial and temporal trends. We used 100 years of natural history collection data for the wood frog, Lithobates sylvaticus with a range >9 million km², and spatially explicit environmental data to determine the best predictors of size and phenology prior to rapid climate warming (1901–1960). We then tested how closely size and phenology changes predicted by those environmental variables reflected actual changes from 1961 to 2000. Size, phenology, and climate all changed as expected (smaller, earlier, and warmer, respectively) at broad spatial scales across the entire study range. However, while spatially explicit changes in climate variables accurately predicted changes in phenology, they did not accurately predict size changes during recent climate change (1961–2000), contrary to expectations from numerous recent studies. Our results suggest that changes in climate are directly linked to observed phenological shifts. However, the mechanisms driving observed body size changes are yet to be determined, given the less straightforward relationship between size and climate factors examined in this study. We recommend that caution be used in “space‐for‐time” studies where measures of a species’ traits at lower latitudes or elevations are considered representative of those under future projected climate conditions. Future studies should aim to determine mechanisms driving trends in phenology and body size, as well as the impact of climate on population density, which may influence body size.     

Identifying potential evolutionary consequences of climate-driven phenological shifts

Climate change is shifting the phenology of many species throughout the world. While the interspecific consequences of these phenological shifts have been well documented, the intraspecific shifts and their resultant evolutionary consequences remain relatively unexplored. Here, we present a conceptual framework and overview of how phenological shifts within species can drive evolutionary change. We suggest that because the impacts of climate change are likely to vary across the range of a species and differentially impact individuals, phenological shifts may often be highly variable both within and among populations. Together these changes have the potential to alter existing patterns of gene flow and influence evolutionary trajectories by increasing phenological isolation and connectivity. Recent research examining the response of species to contemporary climate change suggests that both phenological isolation and connectivity may be likely responses to future climate change. However, recent studies also show mixed results on whether adaptive responses to climate change are likely to occur, as some populations have already shown adaptive responses to changing climate, while others have not despite fitness costs. While predicting the exact consequences of intraspecific phenological shifts may be difficult, identifying the evolutionary implications of these shifts will allow a better understanding of the effects of future climate change on species persistence and adaptation.     

植物物候学研究进展

植物物候变化在研究陆地生态系统对气候变化的响应时被誉为"矿井中的金丝雀",全球气候变化愈演愈烈,重新引起了人们对植物物候研究的广泛关注。随着观测技术的发展,在各种空间和生态尺度上收集到的物候观测数据迅速累积,尽管已经在多个尺度上（物种、群落和景观尺度）观察到物候变化,但物候变化的机理仍然没有得到很好的理解。回顾了国内外植物物候研究的发展历程;总结了物候数据收集技术进展和全球物候变化的主要趋势;归纳了植物物候变化的机理与驱动因素;探讨了物候模型研究及物候对气候变化响应研究的主要方向。随着物候观测技术在不同尺度上应用的增加,物候研究进入了一个新的阶段。未来物候研究需要制定跨区域标准化观测指南,融合所有相关学科,改进物候模型,拓展研究区域;同时融合有效的历史物候资料,采用新技术和长期收集的物候数据为大数据时代植物物候学研究提供基础。     

Impacts of climate change on avian populations

This review focuses on the impacts of climate change on population dynamics. I introduce the MUP (Measuring, Understanding, and Predicting) approach, which provides a general framework where an enhanced understanding of climate‐population processes, along with improved long‐term data, are merged into coherent projections of future population responses to climate change. This approach can be applied to any species, but this review illustrates its benefit using birds as examples. Birds are one of the best‐studied groups and a large number of studies have detected climate impacts on vital rates (i.e., life history traits, such as survival, maturation, or breeding, affecting changes in population size and composition) and population abundance. These studies reveal multifaceted effects of climate with direct, indirect, time‐lagged, and nonlinear effects. However, few studies integrate these effects into a climate‐dependent population model to understand the respective role of climate variables and their components (mean state, variability, extreme) on population dynamics. To quantify how populations cope with climate change impacts, I introduce a new universal variable: the ‘population robustness to climate change.’ The comparison of such robustness, along with prospective and retrospective analysis may help to identify the major climate threats and characteristics of threatened avian species. Finally, studies projecting avian population responses to future climate change predicted by IPCC‐class climate models are rare. Population projections hinge on selecting a multiclimate model ensemble at the appropriate temporal and spatial scales and integrating both radiative forcing and internal variability in climate with fully specified uncertainties in both demographic and climate processes.     

Mechanistic niche modelling: combining physiological and spatial data to predict species' ranges

Species distribution models (SDMs) use spatial environmental data to make inferences on species' range limits and habitat suitability. Conceptually, these models aim to determine and map components of a species' ecological niche through space and time, and they have become important tools in pure and applied ecology and evolutionary biology. Most approaches are correlative in that they statistically link spatial data to species distribution records. An alternative strategy is to explicitly incorporate the mechanistic links between the functional traits of organisms and their environments into SDMs. Here, we review how the principles of biophysical ecology can be used to link spatial data to the physiological responses and constraints of organisms. This provides a mechanistic view of the fundamental niche which can then be mapped to the landscape to infer range constraints. We show how physiologically based SDMs can be developed for different organisms in different environmental contexts. Mechanistic SDMs have different strengths and weaknesses to correlative approaches, and there are many exciting and unexplored prospects for integrating the two approaches. As physiological knowledge becomes better integrated into SDMs, we will make more robust predictions of range shifts in novel or non-equilibrium contexts such as invasions, translocations, climate change and evolutionary shifts.     

Phenological shifts and the fate of mutualisms

Climate change is altering the timing of life history events in a wide array of species, many of which are involved in mutualistic interactions. Because many mutualisms can form only if partner species are able to locate each other in time, differential phenological shifts are likely to influence their strength, duration and outcome. At the extreme, climate change‐driven shifts in phenology may result in phenological mismatch: the partial or complete loss of temporal overlap of mutualistic species. We have a growing understanding of how, when, and why phenological change can alter one type of mutualism–pollination. However, as we show here, there has been a surprising lack of attention to other types of mutualism. We generate a set of predictions about the characteristics that may predispose mutualisms in general to phenological mismatches. We focus not on the consequences of such mismatches but rather on the likelihood that mismatches will develop. We explore the influence of three key characteristics of mutualism: 1) intimacy, 2) seasonality and duration, and 3) obligacy and specificity. We predict that the following characteristics of mutualism may increase the likelihood of phenological mismatch: 1) a non‐symbiotic life history in which co‐dispersal is absent; 2) brief, seasonal interactions; and 3) facultative, generalized interactions. We then review the limited available data in light of our a priori predictions and point to mutualisms that are more and less likely to be at risk of becoming phenologically mismatched, emphasizing the need for research on mutualisms other than plant–pollinator interactions. Future studies should explicitly focus on mutualism characteristics to determine whether and how changing phenologies will affect mutualistic interactions.     

Links between plant species’ spatial and temporal responses to a warming climate

To generate realistic projections of species’ responses to climate change, we need to understand the factors that limit their ability to respond. Although climatic niche conservatism, the maintenance of a species’s climatic niche over time, is a critical assumption in niche-based species distribution models, little is known about how universal it is and how it operates. In particular, few studies have tested the role of climatic niche conservatism via phenological changes in explaining the reported wide variance in the extent of range shifts among species. Using historical records of the phenology and spatial distribution of British plants under a warming climate, we revealed that: (i) perennial species, as well as those with weaker or lagged phenological responses to temperature, experienced a greater increase in temperature during flowering (i.e. failed to maintain climatic niche via phenological changes); (ii) species that failed to maintain climatic niche via phenological changes showed greater northward range shifts; and (iii) there was a complementary relationship between the levels of climatic niche conservatism via phenological changes and range shifts. These results indicate that even species with high climatic niche conservatism might not show range shifts as instead they track warming temperatures during flowering by advancing their phenology.     

Temperature‐related shifts in butterfly phenology depend on the habitat

Many species are becoming active earlier in the season as the climate becomes warmer. In parallel to phenological responses to climate change, many species have also been affected by habitat changes due to anthropogenic land use. As habitat type can directly affect microclimatic conditions, concurrent changes in climate and habitat could have interacting effects on the phenology of species. Temperature‐related shifts in phenology, however, have mostly been studied independent of habitat types. Here, I used long‐term data from a highly standardized monitoring program with 519 transects to study how phenology of butterflies is affected by ambient temperature and habitat type. I compared forests, agricultural areas and settlements, reflecting three major land use forms, and considered butterfly species that were observed in all three of these habitats. Seasonal appearance of the butterflies was affected both by the ambient temperature and the habitat type. As expected, warmer temperatures led to an overall advancement of the appearance and flight period of most species. Surprisingly, however, phenology of species was delayed in settlement habitats, even though this habitat type is generally associated with higher temperatures. A possible explanation is dispersal among habitat types, such that source–sink effects affect local phenology. When there is little productivity in settlement areas, observed butterflies may have immigrated from forest or agricultural habitats and thus appear later in settlements. My findings suggest that a spillover of individuals among habitats may affect phenology trends and indicate that phenological studies need to be interpreted in the context of habitat types. This becomes especially important when defining strategies to prevent or mitigate effects of climate and land‐use changes on phenology and abundance of species.     

Predicting insect phenology across space and time

Many species appear to be undergoing shifts in phenology, arising from climate change. To predict the direction and magnitude of future changes requires an understanding of how phenology depends on climatic variation. Species show large‐scale spatial variation in phenology (affected by differentiation among populations) as well as variation in phenology from year‐to‐year at the same site (affected predominantly by local plasticity). Teasing apart spatial and temporal variation in phenology should allow improved predictions of phenology under climate change. This study is the first to quantify large‐scale spatial and temporal variation in the entire emergence pattern of species, and to test the relationships found by predicting future data. We use data from up to 33 years of permanent transect records of butterflies in the United Kingdom to fit and test models for 15 butterfly species. We use generalized additive models to model spatial and temporal variation in the distribution of adult butterflies over the season, allowing us to capture changes in the timing of emergence peaks, relative sizes of peaks and/or number of peaks in a single analysis. We develop these models using data for 1973–2000, and then use them to predict phenologies from 2001 to 2006. For six of our study species, a model with only spatial variation in phenology is the best predictor of the future, implying that these species have limited plasticity. For the remaining nine species, the best predictions come from a model with both spatial and temporal variation in phenology; for four of these, growing degree‐days have similar effects over space and time, implying high levels of plasticity. The results show that statistical phenology models can be used to predict phenology shifts in a second time period, suggesting that it should be feasible to project phenologies under climate change scenarios, at least over modest time scales.     

Forecasting phenology: from species variability to community patterns

Shifts in species' phenology in response to climate change have wide-ranging consequences for ecological systems. However, significant variability in species' responses, together with limited data, frustrates efforts to forecast the consequences of ongoing phenological changes. Herein, we use a case study of three North American plant communities to explore the implications of variability across levels of organisation (within and among species, and among communities) for forecasting responses to climate change. We show how despite significant variation among species in sensitivities to climate, comparable patterns emerge at the community level once regional climate drivers are accounted for. However, communities differ with respect to projected patterns of divergence and overlap among their species' phenological distributions in response to climate change. These analyses and a review of hypotheses suggest how explicit consideration of spatial scale and levels of biological organisation may help to understand and forecast phenological responses to climate change.     

Influence of spring and autumn phenological transitions on forest ecosystem productivity

We use eddy covariance measurements of net ecosystem productivity (NEP) from 21 FLUXNET sites (153 site-years of data) to investigate relationships between phenology and productivity (in terms of both NEP and gross ecosystem photosynthesis, GEP) in temperate and boreal forests. Results are used to evaluate the plausibility of four different conceptual models. Phenological indicators were derived from the eddy covariance time series, and from remote sensing and models. We examine spatial patterns (across sites) and temporal patterns (across years); an important conclusion is that it is likely that neither of these accurately represents how productivity will respond to future phenological shifts resulting from ongoing climate change. In spring and autumn, increased GEP resulting from an ‘extra’ day tends to be offset by concurrent, but smaller, increases in ecosystem respiration, and thus the effect on NEP is still positive. Spring productivity anomalies appear to have carry-over effects that translate to productivity anomalies in the following autumn, but it is not clear that these result directly from phenological anomalies. Finally, the productivity of evergreen needleleaf forests is less sensitive to phenology than is productivity of deciduous broadleaf forests. This has implications for how climate change may drive shifts in competition within mixed-species stands.     

Phenological Changes in the Southern Hemisphere

Current evidence of phenological responses to recent climate change is substantially biased towards northern hemisphere temperate regions. Given regional differences in climate change, shifts in phenology will not be uniform across the globe, and conclusions drawn from temperate systems in the northern hemisphere might not be applicable to other regions on the planet. We conduct the largest meta-analysis to date of phenological drivers and trends among southern hemisphere species, assessing 1208 long-term datasets from 89 studies on 347 species. Data were mostly from Australasia (Australia and New Zealand), South America and the Antarctic/subantarctic, and focused primarily on plants and birds. This meta-analysis shows an advance in the timing of spring events (with a strong Australian data bias), although substantial differences in trends were apparent among taxonomic groups and regions. When only statistically significant trends were considered, 82% of terrestrial datasets and 42% of marine datasets demonstrated an advance in phenology. Temperature was most frequently identified as the primary driver of phenological changes; however, in many studies it was the only climate variable considered. When precipitation was examined, it often played a key role but, in contrast with temperature, the direction of phenological shifts in response to precipitation variation was difficult to predict a priori. We discuss how phenological information can inform the adaptive capacity of species, their resilience, and constraints on autonomous adaptation. We also highlight serious weaknesses in past and current data collection and analyses at large regional scales (with very few studies in the tropics or from Africa) and dramatic taxonomic biases. If accurate predictions regarding the general effects of climate change on the biology of organisms are to be made, data collection policies focussing on targeting data-deficient regions and taxa need to be financially and logistically supported.     

Plant–pollinator interactions and phenological change: what can we learn about climate impacts from experiments and observations?

Climate change can affect plant–pollinator interactions in a variety of ways, but much of the research attention has focused on whether independent shifts in phenology will alter temporal overlap between plants and pollinators. Here I review the research on plant–pollinator mismatch, assessing the potential for observational and experimental approaches to address particular aspects of the problem. Recent, primarily observational studies suggest that phenologies of co‐occurring plants and pollinators tend to respond similarly to environmental cues, but that nevertheless, certain pairs of interacting species are showing independent shifts in phenology. Only in a few cases, however, have these independent shifts been shown to affect population vital rates (specifically, seed production by plants) but this largely reflects a lack of research. Compared to the few long‐term studies of pollination in natural plant populations, experimental manipulations of phenology have yielded relatively optimistic conclusions about effects of phenological shifts on plant reproduction, and I discuss how issues of scale and frequency‐dependence in pollinator behaviour affect the interpretation of these ‘temporal transplant’ experiments. Comparable research on the impacts of mismatch on pollinator populations is so far lacking, but both observational studies and focused experiments have the potential to improve our forecasts of pollinator responses to changing phenologies. Finally, while there is now evidence that plant–pollinator mismatch can affect seed production by plants, it is still unclear whether this phenological impact will be the primary way in which climate change affects plant–pollinator interactions. It would be useful to test the direct effects of changing climate on pollinator population persistence, and to compare the importance of phenological mismatch with other threats to pollination.     

Phenological plasticity is a poor predictor of subalpine plant population performance following experimental climate change

Phenological shifts, changes in the seasonal timing of life cycle events, are among the best documented responses of species to climate change. However, the consequences of these phenological shifts for population dynamics remain unclear. Population growth could be enhanced if species that advance their phenology benefit from longer growing seasons and gain a pre-emptive advantage in resource competition. However, it might also be reduced if phenological advances increase exposure to stresses, such as herbivores and, in colder climates, harsh abiotic conditions early in the growing season. We exposed subalpine grasslands to ~3 K of warming by transplanting intact turfs from 2000 m to 1400 m elevation in the eastern Swiss Alps, with turfs transplanted within the 2000 m site acting as a control. In the first growing season after transplantation, we recorded species’ flowering phenology at both elevations. We also measured species’ cover change for three consecutive years as a measure of plant performance. We used models to estimate species’ phenological plasticity (the response of flowering time to the change in climate) and analysed its relationship with cover changes following climate change. The phenological plasticity of the 18 species in our study varied widely but was unrelated to their changes in cover. Moreover, early- and late-flowering species did not differ in their cover response to warming, nor in the relationship between cover changes and phenological plasticity. These results were replicated in a similar transplant experiment within the same subalpine community, established one year earlier and using larger turfs. We discuss the various ecological processes that can be affected by phenological shifts, and argue why the population-level consequences of these shifts are likely to be species- and context-specific. Our results highlight the importance of testing assumptions about how warming-induced changes in phenotypic traits, like phenology, impact population dynamics.     

Macrophenology: insights into the broad-scale patterns,drivers, and consequences of phenology

Plant phenology research has surged in recent decades, in part due to interest in phenological sensitivity to climate change and the vital role phenology plays in ecology. Many local-scale studies have generated important findings regarding the physiology, responses, and risks associated with shifts in plant phenology. By comparison, our understanding of regional- and global-scale phenology has been largely limited to remote sensing of green-up without the ability to differentiate among plant species. However, a new generation of analytical tools and data sources—including enhanced remote sensing products, digitized herbarium specimen data, and public participation in science—now permits investigating patterns and drivers of phenology across extensive taxonomic, temporal, and spatial scales, in an emerging field that we call macrophenology. Recent studies have highlighted how phenology affects dynamics at broad scales, including species interactions and ranges, carbon fluxes, and climate. At the cusp of this developing field of study, we review the theoretical and practical advances in four primary areas of plant macrophenology: (1) global patterns and shifts in plant phenology, (2) within-species changes in phenology as they mediate species' range limits and invasions at the regional scale, (3) broad-scale variation in phenology among species leading to ecological mismatches, and (4) interactions between phenology and global ecosystem processes. To stimulate future research, we describe opportunities for macrophenology to address grand challenges in each of these research areas, as well as recently available data sources that enhance and enable macrophenology research.     

(A bit) Earlier or later is always better: Phenological shifts in consumer–resource interactions

Phenology is a crucial life history trait for species interactions and it can have great repercussions on the persistence of communities and ecosystems. Changes in phenology caused by climate change can disrupt species interactions causing decreases in consumer growth rates, as suggested by the match–mismatch hypothesis (MMH). However, it is still not clear what the long-term consequences of such phenological changes are. In this paper, we present models in which phenology and consumer–resource feedbacks determine long-term community dynamics. Our results show that consumer viability is constrained by limits in the amount of phenological mismatch with their resources, in accordance with the MMH, but the effects of phenological shifts are often nonmonotonic. Consumers generally have higher abundances when they recruit some time before or after their resources because this reduces the long-term effects of overexploitation that would otherwise occur under closer synchrony. Changes in the duration of recruitment phenologies also have important impacts on community stability, with shorter phenologies promoting oscillations and cycles. For small community modules, the effects of phenological shifts on populations can be explained, to a great extent, as superpositions of their effects on consumer–resource pairs. We highlight that consumer–resource feedbacks and overexploitation, which are not typically considered in phenological models, are important factors shaping the long-term responses to phenological changes caused by climate change.     

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.