Ecological drivers of flower-leaf sequences: aridity and proxies for pollinator attraction select for flowering-first in the American plums.

Across temperate forests, many tree species produce flowers before their leaves emerge. This flower-leaf phenological sequence, known as hysteranthy, is generally described as an adaptation for wind pollination. However, this explanation does not address why hysteranthy is also common in biotically pollinated taxa. We quantified flower-leaf sequence variation in the American plums (Prunus, subg. Prunus sect. Prunocerasus), a clade of insect-pollinated trees, using herbaria specimens and Bayesian hierarchical modeling. We tested two common, but rarely interrogated hypotheses - that hysteranthy confers aridity tolerance and/or pollinator visibility - by modeling the associations between hysteranthy and related traits. To understand how these phenology-trait associations were sensitive to taxonomic scale and flower-leaf sequence classification, we then extended these analyses to all Prunus species in North America. Our findings across two taxonomic levels support the hypotheses that hysteranthy may help temporally partition hydraulic demand to reduce water stress and increase pollinator visibility - thereby reducing selective pressure on inflorescence size. Our results provide foundational insights into the evolution of flower-leaf sequences in the genus Prunus, with implications for understanding these patterns in biotically pollinated plants in general. Our approach suggests a path to advance these hypotheses to other clades, but teasing out drivers fully will require new experiments.

Weak evidence of provenance effects in spring phenology across Europe and North America.

Forecasting the biological impacts of climate change requires understanding how species respond to warmer temperatures through interannual flexible variation vs through adaptation to local conditions. Yet, we often lack this information entirely or find conflicting evidence across studies, which is the case for spring phenology. We synthesized common garden studies across Europe and North America that reported spring event dates for a mix of angiosperm and gymnosperm tree species in the northern hemisphere, capturing data from 384 North American and 101 European provenances (i.e. populations) with observations from 1962 to 2019, alongside autumn event data when provided. Across continents, we found no evidence of provenance effects in spring phenology, but strong clines with latitude and mean annual temperature in autumn. These effects, however, appeared to diverge by continent and species type (gymnosperm vs angiosperm), with particularly pronounced clines in North America in autumn events. Our results suggest flexible, likely plastic responses, in spring phenology with warming, and potential limits - at least in the short term - due to provenance effects for autumn phenology. They also highlight that, after over 250 yr of common garden studies on tree phenology, we still lack a holistic predictive model of clines across species and phenological events.

The role of genotypic and climatic variation at the range edge: A case study in winegrapes.

PREMISE: Changes in habitat suitability due to climate change are causing range shifts, with new habitat potentially available at cold range edges. We must predict these range shifts, but forecasters have limited knowledge of how genetic differences in plant physiological tolerances influence range shifts. Here, we focus on a major determinant of species ranges-physiological tolerance to extreme cold-to ask how warming over recent decades and genetic variation shape expansion across complex landscapes. METHODS: We examined how genotypes vary in maximum cold tolerance from 9 years of cold hardiness data across 18 genotypes from 13 sites, using winegrapes (Vitis vinifera subsp. vinifera) as a case study. Combining a Bayesian hierarchical dose-response model with gridded climate data, we then project changes in climatic suitability near winegrapes' current cold range-edge between 1949 and 2016. RESULTS: Plants increased maximum cold hardiness non-linearly with decreasing air temperature (maximum cold hardiness: -23.6°C), but with substantial (by 2°C) variation across genotypes. Our results suggest, since the 1980s, decreasing freeze injury risk has made conditions more favorable for all genotypes at the cold range-edge, but conditions remained more favorable for more cold hardy genotypes and in warmer areas. There was substantial spatial variation in habitat suitability, with the majority of suitably warm habitat located in a narrow north-south oriented strip. CONCLUSIONS: We highlight the importance of genotypic differences in physiological tolerances when assessing range shift potential with climate change. Habitat improvements were unevenly distributed over the spatially complex landscape, though, emphasizing the importance of dispersal in range expansion.

Lack of evidence for the match-mismatch hypothesis across terrestrial trophic interactions.

Climate change has led to widespread shifts in the timing of key life history events between interacting species (phenological asynchrony) with hypothesized cascading negative fitness impacts on one or more of the interacting species-often termed 'mismatch'. Yet, predicting the types of systems prone to mismatch remains a major hurdle. Recent reviews have argued that many studies do not provide strong evidence of the underlying match-mismatch hypothesis, but none have quantitatively analysed support for it. Here, we test the hypothesis by estimating the prevalence of mismatch across antagonistic trophic interactions in terrestrial systems and then examine whether studies that meet the assumptions of the hypothesis are more likely to find a mismatch. Despite a large range of synchrony to asynchrony, we did not find general support for the hypothesis. Our results thus question the general applicability of this hypothesis in terrestrial systems, but they also suggest specific types of data missing to robustly refute it. We highlight the critical need to define resource seasonality and the window of 'match' for the most rigorous tests of the hypothesis. Such efforts are necessary if we want to predict systems where mismatches are likely to occur.

Flowering phenology influences butterfly nectar foraging on non-native plants in an oak savanna.

The negative impacts of non-native species have been well documented, but some non-natives can play a positive role in native ecosystems. One way that non-native plants can positively interact with native butterflies is by provisioning nectar. Relatively little is known about the role of phenology in determining native butterfly visitation to non-native plants for nectar, yet flowering time directly controls nectar availability. Here we investigate the phenological patterns of flowering by native and non-native plants and nectar foraging by native butterflies in an oak savanna on Vancouver Island, British Columbia, Canada. We also test whether native butterflies select nectar sources in proportion to their availability. We found that non-native plants were well integrated into butterfly nectar diets (83% of foraging observations) and that visitation to non-natives increased later in the season when native plants were no longer flowering. We also found that butterflies selected non-native flowers more often than expected based on their availability, suggesting that these plants represent a potentially valuable resource. Our study shows that non-native species have the potential to drive key species interactions in seasonal ecosystems. Management regimes focused on eradicating non-native species may need to reconsider their aims and evaluate resources that non-natives provide.

Integrating experiments to predict interactive cue effects on spring phenology with warming.

Climate change has advanced plant phenology globally 4-6 d °C-1 on average. Such shifts are some of the most reported and predictable biological impacts of rising temperatures. Yet as climate change has marched on, phenological shifts have appeared muted over recent decades - failing to match simple predictions of an advancing spring with continued warming. The main hypothesis for these changing trends is that interactions between spring phenological cues - long-documented in laboratory environments - are playing a greater role in natural environments due to climate change. Here, we argue that accurately linking shifts observed in long-term data to underlying phenological cues is slowed by biases in observational studies and limited integration of insights from laboratory studies. We synthesize seven decades of laboratory experiments to quantify how phenological cue-space has been studied and how treatments compare with shifts caused by climate change. Most studies focus on one cue, limiting our ability to make accurate predictions, but some well-studied forest species offer opportunities to advance forecasting. We outline how greater integration of controlled-environment studies with long-term data could drive a new generation of laboratory experiments, built on physiological insights, that would transform our fundamental understanding of phenology and improve predictions.

A simple explanation for declining temperature sensitivity with warming.

Recently, multiple studies have reported declining phenological sensitivities (∆ days per ℃) with higher temperatures. Such observations have been used to suggest climate change is reshaping biological processes, with major implications for forecasts of future change. Here, we show that these results may simply be the outcome of using linear models to estimate nonlinear temperature responses, specifically for events that occur after a cumulative thermal threshold is met-a common model for many biological events. Corrections for the nonlinearity of temperature responses consistently remove the apparent decline. Our results show that rising temperatures combined with linear estimates based on calendar time produce the observations of declining sensitivity-without any shift in the underlying biology. Current methods may thus undermine efforts to identify when and how warming will reshape biological processes.

How phenological tracking shapes species and communities in non-stationary environments.

Climate change alters the environments of all species. Predicting species responses requires understanding how species track environmental change, and how such tracking shapes communities. Growing empirical evidence suggests that how species track phenologically - how an organism shifts the timing of major biological events in response to the environment - is linked to species performance and community structure. Such research tantalizingly suggests a potential framework to predict the winners and losers of climate change, and the future communities we can expect. But developing this framework requires far greater efforts to ground empirical studies of phenological tracking in relevant ecological theory. Here we review the concept of phenological tracking in empirical studies and through the lens of coexistence theory to show why a community-level perspective is critical to accurate predictions with climate change. While much current theory for tracking ignores the importance of a multi-species context, basic community assembly theory predicts that competition will drive variation in tracking and trade-offs with other traits. We highlight how existing community assembly theory can help understand tracking in stationary and non-stationary systems. But major advances in predicting the species- and community-level consequences of climate change will require advances in theoretical and empirical studies. We outline a path forward built on greater efforts to integrate priority effects into modern coexistence theory, improved empirical estimates of multivariate environmental change, and clearly defined estimates of phenological tracking and its underlying environmental cues.

Late spring freezes coupled with warming winters alter temperate tree phenology and growth.

Spring phenology is advancing with warming but late spring freezes may not advance at the same rate, potentially leading to an increase in freezes after trees initiate budburst. Research suggests warming winters may delay budburst through reduced chilling, which may cause plants to leafout more slowly, thus decreasing spring freeze tolerance. Here, we assessed the effects of late spring freezes and reduced over-winter chilling on sapling phenology, growth and tissue traits, across eight temperate tree and shrub species in a laboratory experiment. We found that spring freezes delayed leafout - extending the period of greatest risk for freeze damage - increased damage to the shoot apical meristem, and decreased leaf toughness and leaf thickness. Longer chilling accelerated budburst and leafout, even under spring freeze conditions. Thus, chilling compensated for the adverse effects of late spring freezes on phenology. Despite the effects of spring freezes and chilling on phenology, we did not see any major reordering in the sequence of species leafout. Our results suggest climate change may impact forest communities not through temporal reassembly, but rather through impacts on phenology and growth from the coupled effects of late spring freezes and decreased over-winter chilling under climate change.

Spatial and temporal shifts in photoperiod with climate change.

Climate change causes both temporal (e.g. advancing spring phenology) and geographic (e.g. range expansion poleward) species shifts, which affect the photoperiod experienced at critical developmental stages ('experienced photoperiod'). As photoperiod is a common trigger of seasonal biological responses - affecting woody plant spring phenology in 87% of reviewed studies that manipulated photoperiod - shifts in experienced photoperiod may have important implications for future plant distributions and fitness. However, photoperiod has not been a focus of climate change forecasting to date, especially for early-season ('spring') events, often assumed to be driven by temperature. Synthesizing published studies, we find that impacts on experienced photoperiod from temporal shifts could be orders of magnitude larger than from spatial shifts (1.6 h of change for expected temporal vs 1 min for latitudinal shifts). Incorporating these effects into forecasts is possible by leveraging existing experimental data; we show that results from growth chamber experiments on woody plants often have data relevant for climate change impacts, and suggest that shifts in experienced photoperiod may increasingly constrain responses to additional warming. Further, combining modeling approaches and empirical work on when, where and how much photoperiod affects phenology could rapidly advance our understanding and predictions of future spatio-temporal shifts from climate change.

Reconciling competing hypotheses regarding flower-leaf sequences in temperate forests for fundamental and global change biology.

Phenology is a major component of an organism's fitness. While individual phenological events affect fitness, there is growing evidence to suggest that the relationship between events could be equally or more important. This could explain why temperate deciduous woody plants exhibit considerable variation in the order of reproductive and vegetative events, or flower-leaf sequences (FLSs). There is evidence to suggest that FLSs may be adaptive, with several competing hypotheses to explain their function. Here, we advance existing hypotheses with a new framework that accounts for quantitative FLS variation at multiple taxonomic scales using case studies from temperate forests. Our inquiry provides several major insights towards a better understanding of FLS variation. First, we show that support for FLS hypotheses is sensitive to how FLSs are defined, with quantitative definitions being the most useful for robust hypothesis testing. Second, we demonstrate that concurrent support for multiple hypotheses should be the starting point for future FLS analyses. Finally, we highlight how adopting a quantitative, intraspecific approach generates new avenues for evaluating fitness consequences of FLS variation and provides cascading benefits to improving predictions of how climate change will alter FLSs and thereby reshape plant communities and ecosystems.

Climate change reshapes the drivers of false spring risk across European trees.

Temperate forests are shaped by late spring freezes after budburst - false springs - which may shift with climate change. Research to date has generated conflicting results, potentially because few studies focus on the multiple underlying drivers of false spring risk. Here, we assessed the effects of mean spring temperature, distance from the coast, elevation and the North Atlantic Oscillation (NAO) using PEP725 leafout data for six tree species across 11 648 sites in Europe, to determine which were the strongest predictors of false spring risk and how these predictors shifted with climate change. All predictors influenced false spring risk before recent warming, but their effects have shifted in both magnitude and direction with warming. These shifts have potentially magnified the variation in false spring risk among species with an increase in risk for early-leafout species (i.e. Aesculus hippocastanum, Alnus glutinosa, Betula pendula) compared with a decline or no change in risk among late-leafout species (i.e. Fagus sylvatica, Fraxinus excelsior, Quercus robur). Our results show how climate change has reshaped the drivers of false spring risk, complicating forecasts of future false springs, and potentially reshaping plant community dynamics given uneven shifts in risk across species.

How do climate change experiments alter plot-scale climate?

To understand and forecast biological responses to climate change, scientists frequently use field experiments that alter temperature and precipitation. Climate manipulations can manifest in complex ways, however, challenging interpretations of biological responses. We reviewed publications to compile a database of daily plot-scale climate data from 15 active-warming experiments. We find that the common practices of analysing treatments as mean or categorical changes (e.g. warmed vs. unwarmed) masks important variation in treatment effects over space and time. Our synthesis showed that measured mean warming, in plots with the same target warming within a study, differed by up to 1.6  ∘ C (63% of target), on average, across six studies with blocked designs. Variation was high across sites and designs: for example, plots differed by 1.1  ∘ C (47% of target) on average, for infrared studies with feedback control (n = 3) vs. by 2.2  ∘ C (80% of target) on average for infrared with constant wattage designs (n = 2). Warming treatments produce non-temperature effects as well, such as soil drying. The combination of these direct and indirect effects is complex and can have important biological consequences. With a case study of plant phenology across five experiments in our database, we show how accounting for drier soils with warming tripled the estimated sensitivity of budburst to temperature. We provide recommendations for future analyses, experimental design, and data sharing to improve our mechanistic understanding from climate change experiments, and thus their utility to accurately forecast species' responses.

Phenological sequences: how early-season events define those that follow.

PREMISE OF THE STUDY: Plant phenology is a critical trait, as the timings of phenophases such as budburst, leafout, flowering, and fruiting, are important to plant fitness. Despite much study about when individual phenophases occur and how they may shift with climate change, little is known about how multiple phenophases relate to one another across an entire growing season. We test the extent to which early phenological stages constrain later ones, throughout a growing season, across 25 angiosperm tree species. METHODS: We observed phenology (budburst, leafout, flowering, fruiting, and senescence) of 118 individual trees across 25 species, from April through December 2015. KEY RESULTS: We found that early phenological events weakly constrain most later events, with the strongest constraints seen between consecutive stages. In contrast, interphase duration was a much stronger predictor of phenology, especially for reproductive events, suggesting that the development time of flowers and fruits may constrain the phenology of these events. CONCLUSIONS: Much of the variation in later phenological events can be explained by the timing of earlier events and by interphase durations. This highlights that a shift in one phenophase may often have cascading effects on later phases. Accurate forecasts of climate change impacts should therefore include multiple phenophases within and across years.

Temperature and photoperiod drive spring phenology across all species in a temperate forest community.

Accurate predictions of spring plant phenology with climate change are critical for projections of growing seasons, plant communities and a number of ecosystem services, including carbon storage. Progress towards prediction, however, has been slow because the major cues known to drive phenology - temperature (including winter chilling and spring forcing) and photoperiod - generally covary in nature and may interact, making accurate predictions of plant responses to climate change complex and nonlinear. Alternatively, recent work suggests many species may be dominated by one cue, which would make predictions much simpler. Here, we manipulated all three cues across 28 woody species from two North American forests. All species responded to all cues examined. Chilling exerted a strong effect, especially on budburst (-15.8 d), with responses to forcing and photoperiod greatest for leafout (-19.1 and -11.2 d, respectively). Interactions between chilling and forcing suggest that each cue may compensate somewhat for the other. Cues varied across species, leading to staggered leafout within each community and supporting the idea that phenology is a critical aspect of species' temporal niches. Our results suggest that predicting the spring phenology of communities will be difficult, as all species we studied could have complex, nonlinear responses to future warming.

Temporal ecology in the Anthropocene.

Two fundamental axes - space and time - shape ecological systems. Over the last 30 years spatial ecology has developed as an integrative, multidisciplinary science that has improved our understanding of the ecological consequences of habitat fragmentation and loss. We argue that accelerating climate change - the effective manipulation of time by humans - has generated a current need to build an equivalent framework for temporal ecology. Climate change has at once pressed ecologists to understand and predict ecological dynamics in non-stationary environments, while also challenged fundamental assumptions of many concepts, models and approaches. However, similarities between space and time, especially related issues of scaling, provide an outline for improving ecological models and forecasting of temporal dynamics, while the unique attributes of time, particularly its emphasis on events and its singular direction, highlight where new approaches are needed. We emphasise how a renewed, interdisciplinary focus on time would coalesce related concepts, help develop new theories and methods and guide further data collection. The next challenge will be to unite predictive frameworks from spatial and temporal ecology to build robust forecasts of when and where environmental change will pose the largest threats to species and ecosystems, as well as identifying the best opportunities for conservation.

Warming experiments underpredict plant phenological responses to climate change.

Warming experiments are increasingly relied on to estimate plant responses to global climate change. For experiments to provide meaningful predictions of future responses, they should reflect the empirical record of responses to temperature variability and recent warming, including advances in the timing of flowering and leafing. We compared phenology (the timing of recurring life history events) in observational studies and warming experiments spanning four continents and 1,634 plant species using a common measure of temperature sensitivity (change in days per degree Celsius). We show that warming experiments underpredict advances in the timing of flowering and leafing by 8.5-fold and 4.0-fold, respectively, compared with long-term observations. For species that were common to both study types, the experimental results did not match the observational data in sign or magnitude. The observational data also showed that species that flower earliest in the spring have the highest temperature sensitivities, but this trend was not reflected in the experimental data. These significant mismatches seem to be unrelated to the study length or to the degree of manipulated warming in experiments. The discrepancy between experiments and observations, however, could arise from complex interactions among multiple drivers in the observational data, or it could arise from remediable artefacts in the experiments that result in lower irradiance and drier soils, thus dampening the phenological responses to manipulated warming. Our results introduce uncertainty into ecosystem models that are informed solely by experiments and suggest that responses to climate change that are predicted using such models should be re-evaluated.