• Energy Research

SummaryClimate 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.

AbstractTemperature sensitivity—the magnitude of a biological response per °C—is a fundamental concept across scientific disciplines, especially biology, where temperature determines the rate of many plant, animal and ecosystem processes. Recently, a growing body of literature in global change biology has found temperature sensitivities decline as temperatures rise (Fuet al., 2015; Güsewell et al., 2017; Piao et al., 2017; Chen et al., 2019; Dai et al., 2019). Such observations have been used to suggest climate change is reshaping biological processes, with major implications for forecasts of future change. Here we present a simple alternative explanation for observed declining sensitivities: the use of linear models to estimate non-linear temperature responses. We show how linear estimates of sensitivities will appear to decline with warming for events that occur after a cumulative thermal threshold is met—a common model for many biological events. Corrections for the non-linearity of temperature response in simulated data and long-term phenological data from Europe remove the apparent decline. Our results show that rising temperatures combined with linear estimates based on calendar time produce 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.Significance statementRecently a growing body of literature has observed declining temperature sensitivities of plant leafout and other events with higher temperatures. Such results suggest that climate change is already reshaping fundamental biological processes. These temperature sensitivities are often estimated as the magnitude of a biological response per °C from linear regression. The underlying model for many events—that a critical threshold of warmth must be reached to trigger the event—however, is non-linear. We show that this mismatch between the statistical and biological models can produce the illusion of declining sensitivities with warming using current methods. We suggest simple alternative approaches that can better identify when and how warming will reshape biological processes.

Predicting spring phenology in temperate forests is critical for forecasting important processes such as carbon storage. One major forecasting method for phenology is the growing degree day (GDD) model, which tracks heat accumulation. Forecasts using GDD models typically assume that the GDD threshold for a species is constant across diverse landscapes, but increasing evidence suggests otherwise. Shifts in climate with anthropogenic warming may change the required GDD. Variation in climate across space may also lead to variation in GDD requirements, with recent studies suggesting that fine-scale spatial variation in climate may matter to phenology. Here, we combine simulations, observations from an urban and a rural site, and Bayesian hierarchical models to assess how consistent GDD models of budburst are across species and space. We built GDD models using two different methods to measure climate data: on-site weather stations and local dataloggers. We find that estimated GDD thresholds can vary up to 20% across sites and methods. Our results suggest our studied urban site requires fewer GDDs until budburst and may have stronger microclimate effects than the studied rural site, though these effects depend on the method used to measure climate. Further, we find that GDD models are less accurate for early-active species and may become less accurate with warming. Our results suggest that local-scale forecasts based on GDD models for spring phenology should incorporate these inherent accuracy issues of GDD models, alongside the variations we found across space, species and warming. Testing whether these issues persist at larger spatial scales could improve forecasts for temperate forests.

Summary 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.

This database uses data downloaded from Pan European Phenology network (PEP725, www.pep725.eu) on spring phenology (e.g., BBCH 11) of six temperate European tree species to understand (1) the effects of mean spring temperature, distance from the coast, elevation and the North Atlantic Oscillation (NAO) on false spring risk, and (2) how these major predictors have shifted with climate change across species.

SummaryClimate 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.

Summary 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.

AbstractTemperate plants are at risk of being exposed to late spring freezes. These freeze events—often called false springs—are one of the strongest factors determining temperate plants species range limits and can impose high ecological and economic damage. As climate change may alter the prevalence and severity of false springs, our ability to forecast such events has become more critical, and it has led to a growing body of research. Many false spring studies largely simplify the myriad complexities involved in assessing false spring risks and damage. While these studies have helped advance the field and may provide useful estimates at large scales, studies at the individual to community levels must integrate more complexity for accurate predictions of plant damage from late spring freezes. Here, we review current metrics of false spring, and how, when, and where plants are most at risk of freeze damage. We highlight how life stage, functional group, species differences in morphology and phenology, and regional climatic differences contribute to the damage potential of false springs. More studies aimed at understanding relationships among species tolerance and avoidance strategies, climatic regimes, and the environmental cues that underlie spring phenology would improve predictions at all biological levels. An integrated approach to assessing past and future spring freeze damage would provide novel insights into fundamental plant biology and offer more robust predictions as climate change progresses, which are essential for mitigating the adverse ecological and economic effects of false springs.