The role of temperature variability on insect performance and population dynamics in a warming world

Despite the amount of research on the consequences of global warming on ecological systems, most studies examine the impact of increases in average temperature. However, there are few studies concerning the role of thermal variability on ecological processes. Based on insect thermal and population ecology, we propose a theoretical framework for organizing the study of the role that thermal mean and variability plays in individual performance, and how it may affect population dynamics. Starting with three predictions of global warming scenarios, we develop null models of the expected changes in individual physiological performance and population dynamics. Ecological consequences in each scenario may range from simple changes in performance to drastic changes in population fluctuations and geographic ranges. In particular, our null models show that potential changes in the intrinsic population growth rate (R_m) will depend on the interaction of mean temperature and thermal variability, and that the net effect of the interaction could be synergistic or antagonistic. To evaluate these null models, we fit performance curves to compiled data from the literature on measurements of R_m at several constant and fluctuating temperatures. The fitted models showed that several of the qualitative characteristics predicted by the null model may be found in the fitted curves. We expect that this framework will be useful as a guide to study the influence of thermal changes on the dynamics of natural populations. Synthesis Despite the common assertion that global warming impacts depend on not only the mean temperatures but also on thermal variability, theoretical approaches to explain how the interaction of thermal mean and variability determines fitness are lacking. Here we propose a framework for studying the role of thermal mean and variability on individual performance and population dynamics. We developed null models that show how changes in the intrinsic population growth rate (R_m) will depend on the interaction of mean temperature and thermal variability, and that the net effect could be synergistic or antagonistic. We expect that this framework will be useful to study the influence of thermal changes on natural populations.     

Tree growth-climate relationship in the Azorean holly in a temperate humid forest with low thermal amplitude

Dendroclimatic records in areas with high relative humidity and low thermal amplitude are manifestly scarcer and only a few studies are applied to species that are present in areas with weak seasonality. The Azores archipelago with temperate climate, with low thermal amplitude, has unique biodiversity, including the Azorean holly, Ilex azorica Gand., that is dominant in most extant natural forests. Hence, the importance of understanding its behavior and relation with climate. In this study, we try to understand tree-ring patterns of this species and examine the relationship between radial tree growth and main climatic drivers. For this purpose, we sampled four populations from São Miguel Island and two from Terceira Island. We found a diffuse-ring porous wood with a common layer of vessels associated to the ring boundary, which was critical to identify annual tree-rings. Generalized linear models were used to relate different variations of temperature and precipitation parameters, resulting into a diverse climate-growth relationships of different populations, while the composite population exhibited pronounced effect of temperature. We conclude that, I. azorica forms reliable annual tree-rings, which can be statistically related to climate, mostly temperature. However, there are differences among specific sites, thus the climate sensitivity depends on other site characteristics, such as soil and slope, but probable also to other ecological drivers, such as the competition, water drainage, among others.     

Trade‐offs and evolution of thermal adaptation in the Irish potato famine pathogen Phytophthora infestans

Temperature is one of the most important environmental parameters with crucial impacts on nearly all biological processes. Due to anthropogenic activity, average air temperatures are expected to increase by a few degrees in coming decades, accompanied by an increased occurrence of extreme temperature events. Such global trends are likely to have various major impacts on human society through their influence on natural ecosystems, food production and biotic interactions, including diseases. In this study, we used a combination of statistical genetics, experimental evolution and common garden experiments to investigate the evolutionary potential for thermal adaptation in the potato late blight pathogen, Phytophthora infestans, and infer its likely response to changing temperatures. We found a trade‐off associated with thermal adaptation to heterogeneous environments in P. infestans, with the degree of the trade‐off peaking approximately at the pathogen's optimum growth temperature. A genetic trade‐off in thermal adaptation was also evidenced by the negative association between a strain's growth rate and its thermal range for growth, and warm climates selecting for a low pathogen growth rate. We also found a mirror effect of phenotypic plasticity and genetic adaptation on growth rate. At below the optimum, phenotypic plasticity enhances pathogen's growth rate but nature selects for slower growing genotypes when temperature increases. At above the optimum, phenotypic plasticity reduces pathogen's growth rate but natural selection favours for faster growing genotypes when temperature increases further. We conclude from these findings that the growth rate of P. infestans will only be marginally affected by global warming.     

Increasing temperature weakens the positive effect of genetic diversity on population growth

Genetic diversity and temperature increases associated with global climate change are known to independently influence population growth and extinction risk. Whether increasing temperature may influence the effect of genetic diversity on population growth, however, is not known. We address this issue in the model protist system Tetrahymena thermophila. We test the hypothesis that at temperatures closer to the species’ thermal optimum (i.e., the temperature at which population growth is maximal, or T _opt), genetic diversity should have a weaker effect on population growth compared to temperatures away from the thermal optimum. To do so, we grew populations of T. thermophila with varying levels of genetic diversity at increasingly warmer temperatures and quantified their intrinsic population growth rate, r. We found that genetic diversity increases population growth at cooler temperatures, but that as temperature increases, this effect weakens. We also show that a combination of changes in the amount of expressed genetic diversity (G) in r, plastic changes in population growth across temperatures (E), and strong G × E interactions underlie this temperature effect. Our results uncover important but largely overlooked temperature effects that have implications for the management of small populations with depauperate genetic stocks in an increasingly warming world.     

Does growth irradiance affect temperature dependence and thermal acclimation of leaf respiration? Insights from a Mediterranean tree with long‐lived leaves

Understanding the response of leaf respiration (R) to changes in irradiance and temperature is a prerequisite for predicting the impacts of climate change on plant function and future atmospheric CO2 concentrations. Little is known, however, about the interactive effects of irradiance and temperature on leaf R. We investigated whether growth irradiance affects the temperature response of leaf R in darkness (Rdark) and in light (Rlight) in seedlings of a broad-leaved evergreen species, Quercus ilex. Two hypotheses concerning Rdark were tested: (1) the Q10 (i.e. the proportional increase in R per 10 degrees C rise in temperature) of leaf Rdark is lower in shaded plants than in high-light-grown plants, and (2) shade-grown plants exhibit a lower degree of thermal acclimation of Rdark than plants exposed to higher growth irradiance. We also assessed whether light inhibition of Rlight differs between leaves exposed to contrasting temperatures and growth irradiances, and whether the degree of thermal acclimation of Rlight is dependent on growth irradiance. We showed that while growth irradiance did impact on photosynthesis, it had no effect on the Q10 of leaf Rdark. Growth irradiance had little impact on thermal acclimation when fully expanded, pre-existing leaves were exposed to contrasting temperatures for several weeks. When Rlight was measured at a common irradiance, Rlight/Rdark ratios were higher in shaded plants due to homeostasis of Rlight between growth irradiance treatments and to the lower Rdark in shaded leaves. We also showed that Rlight does not acclimate to the same degree as Rdark, and that Rlight/Rdark decreases with increasing measuring and growth temperatures, irrespective of the growth irradiance. Collectively, we raised the possibility that predictive carbon cycle models can assume that growth irradiance and photosynthesis do not affect the temperature sensitivity of leaf Rdark of long-lived evergreen leaves, thus simplifying incorporation of leaf R into such models.     

Thermal performance curves of Paramecium caudatum: a model selection approach

The ongoing climate change has motivated numerous studies investigating the temperature response of various organisms, especially that of ectotherms. To correctly describe the thermal performance of these organisms, functions are needed which sufficiently fit to the complete optimum curve. Surprisingly, model-comparisons for the temperature-dependence of population growth rates of an important ectothermic group, the protozoa, are still missing. In this study, temperature reaction norms of natural isolates of the freshwater protist Paramecium caudatum were investigated, considering nearly the entire temperature range. These reaction norms were used to estimate thermal performance curves by applying a set of commonly used model functions. An information theory approach was used to compare models and to identify the best ones for describing these data. Our results indicate that the models which can describe negative growth at the high- and low-temperature branch of an optimum curve are preferable. This is a prerequisite for accurately calculating the critical upper and lower thermal limits. While we detected a temperature optimum of around 29 °C for all investigated clonal strains, the critical thermal limits were considerably different between individual clones. Here, the tropical clone showed the narrowest thermal tolerance, with a shift of its critical thermal limits to higher temperatures.     

Predicting the growth of the amphibian chytrid fungus in varying temperature environments

Environmental temperature is a crucial abiotic factor that influences the success of ectothermic organisms, including hosts and pathogens in disease systems. One example is the amphibian chytrid fungus, Batrachochytrium dendrobatidis (Bd), which has led to widespread amphibian population declines. Understanding its thermal ecology is essential to effectively predict outbreaks. Studies that examine the impact of temperature on hosts and pathogens often do so in controlled constant temperatures. Although varying temperature experiments are becoming increasingly common, it is unrealistic to test every temperature scenario. Thus, reliable methods that use constant temperature data to predict performance in varying temperatures are needed. In this study, we tested whether we could accurately predict Bd growth in three varying temperature regimes, using a Bayesian hierarchical model fit with constant temperature Bd growth data. We fit the Bayesian hierarchical model five times, each time changing the thermal performance curve (TPC) used to constrain the logistic growth rate to determine how TPCs influence the predictions. We then validated the model predictions using Bd growth data collected from the three tested varying temperature regimes. Although all TPCs overpredicted Bd growth in the varying temperature regimes, some functional forms performed better than others. Varying temperature impacts on disease systems are still not well understood and improving our understanding and methodologies to predict these effects could provide insights into disease systems and help conservation efforts.     

To aggregate or not? Capturing the spatio-temporal complexity of the thermal regime

Freshwater stream systems are under immense pressure from various anthropogenic impacts, including climate change. Stream systems are increasingly being altered by changes to the magnitude, timing, frequency, and duration of their thermal regimes, which will have profound impacts on the life-history dynamics of resident biota within their home range. Although temperature regimes have a significant influence on the biology of instream fauna, large spatio-temporal temperature datasets are often reduced to a single metric at discrete locations and used to describe the thermal regime of a system; potentially leading to a significant loss of information crucial to stream management. Models are often used to extrapolate these metrics to unsampled locations, but it is unclear whether predicting actual daily temperatures or an aggregated metric of the temperature regime best describes the complexity of the thermal regime. We fit spatial statistical stream-network models (SSNMs), random forest and non-spatial linear models to stream temperature data from the Upper Condamine River in QLD, Australia and used them to semi-continuously predict metrics describing the magnitude, duration, and frequency of the thermal regime through space and time. We compared both daily and aggregated temperature metrics and found that SSNMs always had more predictive ability than the random forest models, but both models outperformed the non-spatial linear model. For metrics describing thermal magnitude and duration, aggregated predictions were most accurate, while metrics describing the frequency of heating events were better represented by metrics based on daily predictions generated using a SSNM. A more comprehensive representation of the spatio-temporal thermal regime allows researchers to explore new spatio-temporally explicit questions about the thermal regime. It also provides the information needed to generate a suite of ecologically meaningful metrics capturing multiple aspects of the thermal regime, which will increase our scientific understanding of how organisms respond to thermal cues and provide much-needed information for more effective management actions.     

Physiology in ecological niche modeling: using zebra mussel's upper thermal tolerance to refine model predictions through Bayesian analysis

Climate change and human-mediated dispersal are increasingly influencing species’ geographic distributions. Ecological niche models (ENMs) are widely used in forecasting species’ distributions, but are weak in extrapolation to novel environments because they rely on available distributional data and do not incorporate mechanistic information, such as species’ physiological response to abiotic conditions. To improve accuracy of ENMs, we incorporated physiological knowledge through Bayesian analysis. In a case study of the zebra mussel Dreissena polymorpha, we used native and global occurrences to obtain native and global models representing narrower and broader understanding of zebra mussel’ response to temperature. We also obtained thermal limit and survival information for zebra mussel from peer-reviewed literature and used the two types of information separately and jointly to calibrate native models. We showed that, compared to global models, native models predicted lower relative probability of presence along zebra mussel's upper thermal limit, suggesting the shortcoming of native models in predicting zebra mussel's response to warm temperature. We also found that native models showed improved prediction of relative probability of presence when thermal limit was used alone, and best approximated global models when both thermal limit and survival data were used. Our result suggests that integration of physiological knowledge enhances extrapolation of ENM in novel environments. Our modeling framework can be generalized for other species or other physiological limits and may incorporate evolutionary information (e.g. evolved thermal tolerance), thus has the potential to improve predictions of species’ invasive potential and distributional response to climate change.     

Modeling greenup date of dominant grass species in the Inner Mongolian Grassland using air temperature and precipitation data

This work was undertaken to examine the combined effect of air temperature and precipitation during late winter and early spring on modeling greenup date of grass species in the Inner Mongolian Grassland. We used the traditional thermal time model and developed two revised thermal time models coupling air temperature and precipitation to simulate greenup date of three dominant grass species at six stations from 1983 to 2009. Results show that climatic controls on greenup date of grass species were location-specific. The revised thermal time models coupling air temperature and precipitation show higher simulation parsimony and efficiency than the traditional thermal time model for five of 11 data sets at Bayartuhushuo, Xilinhot and Xianghuangqi, whereas the traditional thermal time model indicates higher simulation parsimony and efficiency than the revised thermal time models coupling air temperature and precipitation for the other six data sets at E’ergunayouqi, Ewenkeqi and Chaharyouyihouqi. The mean root mean square error of the 11 models is 4.9 days. Moreover, the influence of late winter and early spring precipitation on greenup date seems to be stronger at stations with scarce precipitation than at stations with relatively abundant precipitation. From the mechanism perspectives, accumulated late winter and early spring precipitation may play a more important role as the precondition of forcing temperature than as the supplementary condition of forcing temperature in triggering greenup. Our findings suggest that predicting responses of grass phenology to global climate change should consider both thermal and moisture scenarios in some semiarid and arid areas.     

Half the story: Thermal effects on within‐host infectious disease progression in a warming climate

Immune defense is temperature dependent in cold‐blooded vertebrates (CBVs) and thus directly impacted by global warming. We examined whether immunity and within‐host infectious disease progression are altered in CBVs under realistic climate warming in a seasonal mid‐latitude setting. Going further, we also examined how large thermal effects are in relation to the effects of other environmental variation in such a setting (critical to our ability to project infectious disease dynamics from thermal relationships alone). We employed the three‐spined stickleback and three ecologically relevant parasite infections as a “wild” model. To generate a realistic climatic warming scenario we used naturalistic outdoors mesocosms with precise temperature control. We also conducted laboratory experiments to estimate thermal effects on immunity and within‐host infectious disease progression under controlled conditions. As experimental readouts we measured disease progression for the parasites and expression in 14 immune‐associated genes (providing insight into immunophenotypic responses). Our mesocosm experiment demonstrated significant perturbation due to modest warming (+2°C), altering the magnitude and phenology of disease. Our laboratory experiments demonstrated substantial thermal effects. Prevailing thermal effects were more important than lagged thermal effects and disease progression increased or decreased in severity with increasing temperature in an infection‐specific way. Combining laboratory‐determined thermal effects with our mesocosm data, we used inverse modeling to partition seasonal variation in Saprolegnia disease progression into a thermal effect and a latent immunocompetence effect (driven by nonthermal environmental variation and correlating with immune gene expression). The immunocompetence effect was large, accounting for at least as much variation in Saprolegnia disease as the thermal effect. This suggests that managers of CBV populations in variable environments may not be able to reliably project infectious disease risk from thermal data alone. Nevertheless, such projections would be improved by primarily considering prevailing thermal effects in the case of within‐host disease and by incorporating validated measures of immunocompetence.     

A Theoretical Analysis of the Effects of Tumor-Treating Electric Fields on Single Cells

Tumor-treating fields (TTFields) are low-intensity and intermediate-frequency alternating electric fields that have been found to inhibit tumor cell growth. While effective, the mechanism by which TTFields affect cell growth is not yet clearly understood. Although numerous mathematical studies on the effects of electromagnetic fields on single cells exist, the effect of TTFields on single cells have been analyzed less frequently. The goal of this study is to explore through a mathematical analysis the effects of TTFields on single cells, with particular emphasis on the thermal effect. We examine herein two single-cell models, a simplified spheroidal model and a simulation of a U-87 MG glioblastoma cell model obtained from microscopic images. A finite element method is used to analyze the electric field distribution, electromagnetic loss, and thermal field distribution. The results further prove that the electric field in the cytoplasm is too weak and its thermal damage can be excluded as a mechanism for cell death in TTFields. Bioelectromagnetics. 2020;41:438–446. © 2020 Bioelectromagnetics Society.     

A cost‐effective method of assessing thermal habitat quality for endotherms

The conservation of many endothermic species depends critically on the availability of suitable retreat sites, yet we know little about the variation in thermal quality of such microhabitats. Studies of thermal habitat suitability for birds and mammals must account for the effect of endothermic heat production on their microclimates. For example, endotherms may significantly raise the air temperature in their retreat sites and this effect must be considered when assessing retreat site quality. We devised an inexpensive means by which to construct pseudo‐endothermic ‘environmental temperature’ models with the use of disposable heat pads. We applied this technique to investigate thermal aspects of nest box design, illustrating the potential positive and negative effects of nest box insulation depending on the environmental context. We suggest that, from a thermal perspective, the avoidance of heat stress is an important and underappreciated issue in the retreat site selection of endotherms.     

Growth and development rates have different thermal responses

Growth and development rates are fundamental to all living organisms. In a warming world, it is important to determine how these rates will respond to increasing temperatures. It is often assumed that the thermal responses of physiological rates are coupled to metabolic rate and thus have the same temperature dependence. However, the existence of the temperature-size rule suggests that intraspecific growth and development are decoupled. Decoupling of these rates would have important consequences for individual species and ecosystems, yet this has not been tested systematically across a range of species. We conducted an analysis on growth and development rate data compiled from the literature for a well-studied group, marine pelagic copepods, and use an information-theoretic approach to test which equations best describe these rates. Growth and development rates were best characterized by models with significantly different parameters: development has stronger temperature dependence than does growth across all life stages. As such, it is incorrect to assume that these rates have the same temperature dependence. We used the best-fit models for these rates to predict changes in organism mass in response to temperature. These predictions follow a concave relationship, which complicates attempts to model the impacts of increasing global temperatures on species body size.     

Predictions of response to temperature are contingent on model choice and data quality

The equations used to account for the temperature dependence of biological processes, including growth and metabolic rates, are the foundations of our predictions of how global biogeochemistry and biogeography change in response to global climate change. We review and test the use of 12 equations used to model the temperature dependence of biological processes across the full range of their temperature response, including supra‐ and suboptimal temperatures. We focus on fitting these equations to thermal response curves for phytoplankton growth but also tested the equations on a variety of traits across a wide diversity of organisms. We found that many of the surveyed equations have comparable abilities to fit data and equally high requirements for data quality (number of test temperatures and range of response captured) but lead to different estimates of cardinal temperatures and of the biological rates at these temperatures. When these rate estimates are used for biogeographic predictions, differences between the estimates of even the best‐fitting models can exceed the global biological change predicted for a decade of global warming. As a result, studies of the biological response to global changes in temperature must make careful consideration of model selection and of the quality of the data used for parametrizing these models.     

Thermal acclimation of photosynthesis: on the importance of adjusting our definitions and accounting for thermal acclimation of respiration

While interest in photosynthetic thermal acclimation has been stimulated by climate warming, comparing results across studies requires consistent terminology. We identify five types of photosynthetic adjustments in warming experiments: photosynthesis as measured at the high growth temperature, the growth temperature, and the thermal optimum; the photosynthetic thermal optimum; and leaf-level photosynthetic capacity. Adjustments of any one of these variables need not mean a concurrent adjustment in others, which may resolve apparently contradictory results in papers using different indicators of photosynthetic acclimation. We argue that photosynthetic thermal acclimation (i.e., that benefits a plant in its new growth environment) should include adjustments of both the photosynthetic thermal optimum (T _opt) and photosynthetic rates at the growth temperature (A _growth), a combination termed constructive adjustment. However, many species show reduced photosynthesis when grown at elevated temperatures, despite adjustment of some photosynthetic variables, a phenomenon we term detractive adjustment. An analysis of 70 studies on 103 species shows that adjustment of T _opt and A _growth are more common than adjustment of other photosynthetic variables, but only half of the data demonstrate constructive adjustment. No systematic differences in these patterns were found between different plant functional groups. We also discuss the importance of thermal acclimation of respiration for net photosynthesis measurements, as respiratory temperature acclimation can generate apparent acclimation of photosynthetic processes, even if photosynthesis is unaltered. We show that while dark respiration is often used to estimate light respiration, the ratio of light to dark respiration shifts in a non-predictable manner with a change in leaf temperature.     

Diurnal variation around an optimum and near‐critically high temperature does not alter the performance of an ectothermic aquatic grazer

The growing threat of global climate change has led to a profusion of studies examining the effects of warming on biota. Despite the potential importance of natural variability such as diurnal temperature fluctuations, most experimental studies on warming are conducted under stable temperatures. Here, we investigated whether the responses of an aquatic invertebrate grazer (Lymnaea stagnalis) to an increased average temperature differ when the thermal regime is either constant or fluctuates diurnally. Using thermal response curves for several life‐history and immune defense traits, we first identified the optimum and near‐critically high temperatures that Lymnaea potentially experience during summer heat waves. We then exposed individuals that originated from three different populations to these two temperatures under constant or fluctuating thermal conditions. After 7 days, we assessed growth, reproduction, and two immune parameters (phenoloxidase‐like activity and antibacterial activity of hemolymph) from each individual. Exposure to the near‐critically high temperature led to increased growth rates and decreased antibacterial activity of hemolymph compared to the optimum temperature, whilst temperature fluctuations had no effect on these traits. The results indicate that the temperature level per se, rather than the variability in temperature was the main driver altering trait responses in our study species. Forecasting responses in temperature‐related responses remains challenging, due to system‐specific properties that can include intraspecific variation. However, our study indicates that experiments examining the effects of warming using constant temperatures can give similar predictions as studies with fluctuating thermal dynamics, and may thus be useful indicators of responses in nature.     

A parametric study of thermal therapy of skin tissue

A thermal therapy for cancer in skin tissue is numerically investigated using three bioheat conduction models, namely Pennes, thermal wave and dual-phase lag models. A laser is applied at the surface of the skin for cancer ablation, and the temperature and thermal damage distributions are predicted using the three bioheat models and two different modeling approaches of the laser effect. The first one is a prescribed surface heat flux, in which the tissue is assumed to be highly absorbent, while the second approach is a volumetric heat source, which is reasonable if the scattering and absorption skin effects are of similar magnitude. The finite volume method is applied to solve the governing bioheat equation. A parametric study is carried out to ascertain the effects of the thermophysical properties of the cancer on the thermal damage. The temperature distributions predicted by the three models exhibit significant differences, even though the temperature distributions are similar when the laser is turned off. The type of bioheat model has more influence on the predicted thermal damage than the type of modeling approach used for the laser. The phase lags of heat flux and temperature gradient have an important influence on the results, as well as the thermal conductivity of the cancer. In contrast, the uncertainty in the specific heat and blood perfusion rate has a minor influence on the thermal damage.     

Modelling Bacterial Growth of Lactobacillus curvatus as a Function of Acidity and Temperature

Models that describe the effect of acidity, temperature, and the combined effect of these variables on the growth parameters of Lactobacillus curvatus are developed and validated. Growth parameters (lag time, specific growth rate, and maximum population density) were calculated from growth data at different temperature-acidity combinations. Experiments were set up to assess the quantitative effects of temperature and acidity on the growth parameters rather than for parameter estimation solely. The effect of acidity is monitored at several constant temperature values. Models are set up and fitted to the data. The same procedure is used at constant acidity values to model the effect of temperature. For lag time, specific growth rate, and maximum population density, the effect of temperature could be multiplied with the effect of acidity to obtain combinatory models that describe the effect of both controlling factors on the growth parameters. Lag time measurements showed large deviations, and therefore the lag time models developed can only be used to estimate the order of magnitude of lag time.     

Climatic Stress during Stand Development Alters the Sign and Magnitude of Age-Related Growth Responses in a Subtropical Mountain Pine

The modification of typical age-related growth by environmental changes is poorly understood, In part because there is a lack of consensus at individual tree level regarding age-dependent growth responses to climate warming as stands develop. To increase our current understanding about how multiple drivers of environmental change can modify growth responses as trees age we used tree ring data of a mountain subtropical pine species along an altitudinal gradient covering more than 2,200 m of altitude. We applied mixed-linear models to determine how absolute and relative age-dependent growth varies depending on stand development; and to quantify the relative importance of tree age and climate on individual tree growth responses. Tree age was the most important factor for tree growth in models parameterised using data from all forest developmental stages. Contrastingly, the relationship found between tree age and growth became non-significant in models parameterised using data corresponding to mature stages. These results suggest that although absolute tree growth can continuously increase along tree size when trees reach maturity age had no effect on growth. Tree growth was strongly reduced under increased annual temperature, leading to more constant age-related growth responses. Furthermore, young trees were the most sensitive to reductions in relative growth rates, but absolute growth was strongly reduced under increased temperature in old trees. Our results help to reconcile previous contrasting findings of age-related growth responses at the individual tree level, suggesting that the sign and magnitude of age-related growth responses vary with stand development. The different responses found to climate for absolute and relative growth rates suggest that young trees are particularly vulnerable under warming climate, but reduced absolute growth in old trees could alter the species’ potential as a carbon sink in the future.