Terrestrial Insects and Climate Change: Adaptive Responses in Key Traits

Home , Aporia (butterfly), Drosophila serrata, Vanessa (butterfly)

Physiological Entomology (2019), DOI: 10.1111/phen.12282

Terrestrial insects and climate change: adaptive responses in key traits

VANESSA KELLERMANN andBELINDA VAN HEERWAARDEN School of Biological Sciences, Monash University, Melbourne, Victoria, Australia

Abstract. Understanding and predicting how adaptation will contribute to species’ resilience to climate change will be paramount to successfully managing biodiversity for conservation, agriculture, and human health-related purposes. Making predictions that capture how species will respond to climate change requires an understanding of how key traits and environmental drivers interact to shape fitness in a changing world. Current trait-based models suggest that low- to mid-latitude populations will be most at risk, although these models focus on upper thermal limits, which may not be the most important trait driving species’ distributions and fitness under climate change. In this review, we discuss how different traits (stress, fitness and phenology) might contribute and interact to shape insect responses to climate change. We examine the potential for adaptive genetic and plastic responses in these key traits and show that, although there is evidence of range shifts and trait changes, explicit consideration of what underpins these changes, be that genetic or plastic responses, is largely missing. Despite little empirical evidence for adaptive shifts, incorporating adaptation into models of climate change resilience is essential for predicting how species will respond under climate change. We are making some headway, although more data are needed, especially from taxonomic groups outside of Drosophila, and across diverse geographical regions. Climate change responses are likely to be complex, and such complexity will be difficult to capture in laboratory experiments. Moving towards well designed field experiments would allow us to not only capture this complexity, but also study more diverse species.

Key words. Climate change, CTmax, evolutionary potential, fitness, heat, heritability, latitude, phenology, phenotypic plasticity, stress resistance, thermal performance curves, upper thermal limits.

Introduction frequency and duration of extreme events, will also have significant impacts on the vulnerability of many species (Parmesan Insects comprise the vast majority of animal diversity on this et al., 2000). planet and represent some of the most economically and eco- Making predictions that accurately capture how species will logically important species, such as bees, mosquitos and moths. respond to climate change requires an understanding of how Understanding how such an important and diverse group key traits and environmental drivers interact to shape fitness in of species will respond to climate change remains one of the a changing world. How a species responds to climate change biggest challenges in climate change biology. With respect is often considered within a response framework: species and to ectothermic species, climate is a key driver of insect distribu- populations can shift their distribution and track optimum tions, meaning that climate change will have a vast impact on fit- environments; however, in the absence of suitable habitat, or ness and current species’ ranges (Addo-Bediako et al., 2000). the capacity to migrate, species must adapt or go extinct. The Increasing temperature is the most frequently considered vari- capacity for species to adapt to climate change will depend on able, yet other attributes, such as changes in rainfall and the the rate of climate change itself, but also on the life-history characteristics of a species (i.e. short versus long generations), Correspondence: V. Kellermann, School of Biological Sciences, the underlying genetic architecture of key traits that will be Monash University, Clayton, Melbourne, Victoria 3800, Australia. Tel.: subjected to climate change selection (i.e. complex versus +61 3 9902 0158; e-mail: [email protected] simple genetic architecture) and the speed at which a species

© 2019 The Royal Entomological Society 1 2 V. Kellermann and B. van Heerwaarden can change these key traits in response to climate change (i.e. events (phenology) (Addo-Bediako et al., 2000; Deutsch et al., rapid/plasticity versus slow/genetic change). 2008; Diamond et al., 2012). Although phenological changes Evidence for adaptive responses to climate change generally have been well documented in response to recent warming (For- comes from correlational studies relating distributional shifts rest, 2016), the role of temperature in shaping thermal resistance to environmental change, and many species are keeping pace and fitness, by far, have been the most well studied variables with warming, as indicated by altitudinal and latitudinal shifts in insect climate change research and assessments of climate (Thomas et al., 2001; Konvicka et al., 2003; Parmesan & Yohe, change risk (Table 1) (Hoffmann & Sgro, 2011). Desiccation 2003; Chen et al., 2011; Kerr et al., 2015; Lenoir & Sven- resistance, which is closely associated with species’ distribu- ning, 2015). What underpins these range shifts? Are species tions, is another candidate trait that is likely to be important in simply moving into previously unsuitable habitat or are these shaping species’ resilience under climate change (Chown et al., range shifts typified by adaptive responses in key traits? There 2011; Kellermann et al., 2012a). is evidence that traits are changing alongside distributions, although very few examples can be explicitly attributed to adaptation (Schilthuizen & Kellermann, 2014) (but see also Upper thermal limits: acute and fitness-based Bradshaw & Holzapfel, 2001; Umina et al., 2005; Balanya et al., 2006) (Table 1). Alongside the successful range shifts, Assessments of climate change risk for species are frequently there are many examples of failures to adapt; as ranges shift measured from thermal performance curves (TPCs), tolerance to meet new suitable climates, range contractions at the lower and lethal assays (tolerance/lethal CTmin and CTmax) (Angilletta, latitudes/elevations are typical and highlight a failure to adapt 2009; Chown et al., 2009; Sinclair et al., 2016) (for a description to warmer more variable climates (Wiens, 2016). What traits of these predictors, see Box 1). Whether climate change pre- underpin failures to adapt? Are they the same across species, dictors, derived from tolerance and lethal assays or TPCs, are or are they typically idiosyncratic and complex? Successful good proxies for climate change resilience will depend on how predictions of the response of species to climate change requires well these estimates correlate with fitness and survival in natu- an understanding of which environmental variables will be most ral populations under climate change. The underlying premise important, which traits will be vital for withstanding changes of TPCs is that the measured fitness trait is linked to intrinsic in climate, and the extent to which different species can track rate of increase (R ), although rarely is an association between changes via adaptive changes in these traits. 0 traits and R0 investigated (Huey & Berrigan, 2001). Single traits Current methods for predicting how a species will respond to represent a component of fitness but not absolute fitness and thus climate change rely heavily on correlative species’ distributional some fitness traits may capture climate change sensitivity better models. These models relate environmental variables to species’ than others. For example, two commonly estimated fitness traits distributions, making predictions about habitat suitability under in Drosophila, namely fecundity and viability, both produce a climate change (Evans et al., 2015; Bush et al., 2016). However, standard TPC shape (Fig. 1a), where fitness begins to decline at the niche of a species is not static and is in part defined by its warmer temperatures. If fitness, however, is estimated in only physiology. As such, mechanistic models that integrate the one of these traits, then it cannot be ignored that these traits biology of the organism will generate more robust predictions have different thermal sensitivities and that increasing tempera- of the response of species to climate change obtained from these tures will have an accumulative effect on absolute fitness. That models (Kearney et al., 2009; Evans et al., 2015). Even current is, as fecundity declines, so does the viability of the eggs being mechanistic models have their limitations, they rarely account laid (Fig. 1b). To circumvent this issue, Overgaard et al. (2014) for the potential for traits to evolve to changing climates. Recent generated a composite fitness curve from estimates of fecun- work by Bush et al. (2016) has demonstrated how predictions of dity, viability and development time. However, this still assumes climate change responses can vastly change if adaptation in key that these traits capture the thermal sensitivity of R .Butif traits is considered. Incorporating adaptation into mechanistic 0 other fitness traits or life stages are more temperature sensitiv- models would improve their utility but models are only as good ity, then absolute fitness may be overestimated. For example, as the data we provide. Some of the fundamental questions in the male sperm of Drosophila is highly temperature sensitive climate change biology remain largely unknown. What will an and their CT is below the temperature thresholds for fecun- adaptive response to climate change look like? Which traits and max et al. life-history characteristics are going to be the most important dity, viability and other fitness-related traits (David , 2005; for adapting to climate change? Will this differ across species Nguyen et al., 2013; Porcelli et al., 2017) (Fig. 1b). Male steril- and life stages? And how well do we capture these traits in the ity is also likely to be an important trait for understanding fitness laboratory? effects under climate change. In the neotropical pseudoscorpion, males produced 45% less sperm at temperatures mimicking 3.5 ∘C of warming (Zeh et al., 2012). The temperature sensitivity Trait-based approaches: can we predict of male sperm and the extent to which species can shift male the responses of species to climate change sterility remains a poorly understood phenomenon (David et al., and which traits are the most important? 2005; Zeh et al., 2012; Saxon et al., 2018). Thermal sensitivities may also differ across life stages (Sinclair et al., 2016; Zhao Trait-based approaches for understanding the response et al., 2017) and Kingsolver et al. (2011) have shown that larvae of species to climate change focus on stress resistance, the tem- and pupae of Manduca sexta have different thermal sensitivities perature sensitivity of fitness traits and the timing of life cycle and differ in their TPC. Different life stages may be more or

Table 1. Examples of studies linking variation in traits to responses (genetic or plastic) to climate and latitude.

Common Climate (C)/ Genetic (G)/ Population (P)/ garden (CG)/ Trait Taxa latitude (L) plasticity (P) species (S) field (F) Reference

Gene frequencies Drosophila melanogaster, + L G P CG Umina et al. (2005) Drosophila subobscura + L G P CG Balanya et al. (2006) TPC Drosophila – L G S CG Overgaard et al. (2014)

TPC- RO Insects – L/+C G S CG/F Deutsch et al. (2008)

CTmax Insects – L G S CG/F Addo-bediako et al. (2000) CTmax Drosophila + C G S CG Kellermann et al. (2012a, b) + C G S CG Kellermann & Sgro (2018) + C G S CG Overgaard et al. (2014) + L G P CG Sgro et al. (2010) + L G P CG Ranga et al. (2017) + C P P CG Kellermann et al. (2017) Voltinsm Lepidoptera + C P/G S F Altermatt (2010) Development time Drosophila melanogaster + L G P CG James et al. (1995) Diapause Drosophila melanogaster + L G P CG Schmidt et al. (2005) + L G P CG Lee et al. (2011) Diapause Wyeomyia smithii + C G P F Bradshaw & Holzapfel (2001) Voltinsm Operophtera + CG P F+ CG Van Asch et al. 2013) brumata Photoperiodism response Aedes albopictus + CG P CGUrbanskiet al. (2012) Emergence times/rate Lepidoptera + C P P/S F Hodgson et al. (2011) Developmental rate/timing Insects + CP S F Buckleyet al. (2017)

+, A significant association between environment/latitude and trait variation was detected. –, No association between environment/latitude and trait variation was detected.

less sensitive to climate change and good predictors of climate biological reasons to explain why CTmax is largely invariant change resilience will depend on understanding the thermal sen- across environments and insects. One reason is that estimates sitivities of the most vulnerable life stage. of CTmax are often performed on individuals collected from One way of testing the predictive power of thermal limits is the field, meaning previous thermal history (acclimatization) to look for an association between environmental variables and may influence estimates (Hoffmann & Sgro, 2017; Kellermann thermal limits. This would suggest traits are under selection. et al., 2017) (Box 1.). When thermal history is controlled,

A study in Drosophila found tolerance CTmin and CTmax to be CTmax, derived from tolerance assays but not TPCs was associ- better predictors of current species’ distributions and climate ated with the environment (Sgro et al., 2010; Overgaard et al., change risk than fitness traits (Overgaard et al., 2014). Sim- 2014; Kellermann & Sgro, 2018), although common garden ilarly, in D. melanogaster, a significant association between studies are predominately limited to Drosophila. tolerance CTmax and latitude was found, although there was An alternate hypothesis for low variation in CTmax,across no relationship between latitude and fitness traits (Sgro et al., species, is that species have the capacity to seek out micro- 2010). By contrast, Penick et al. (2017) reported a positive climates, and essentially avoid heat stress and selection correlation between tolerance CTmax and fitness, in ants. These (behavioural thermoregulation) (Huey et al., 2012). Tracking studies suggest that at least in Drosophila, fitness and tol- the behaviour of insects in the field is not without its challenges, erance thermal limits may quantify different components of although there is indirect evidence for behavioural thermoreg- temperature resilience, although more work explicitly linking ulation in insects (Jakobs et al., 2015; Yin et al., 2018). For

TPC descriptors to environments, across diverse insect taxa, is example, the CTmax of ants is lower than the maximum temper- needed. Despite intraspecific studies suggesting a relationship ature observed in the field (Hemmings & Andrew, 2017). Anda between CTmax and the environment (Sgro et al., 2010; Ranga stronger association between CTmax and environment, in areas et al., 2017), two interspecific studies found no association with low precipitation, is considered to be linked to a reduction between latitude (proxy for environment) and CTmax, derived in canopy cover and the ability to behaviourally thermoregulate from tolerance assays (Addo-Bediako et al., 2000) and TPCs in Drosophila species (Kellermann et al., 2012b). Research (Deutsch et al., 2008). However, tropical regions (–20∘ to 20∘) also suggests that the inclusion of microclimates can have large were poorly represented in both studies, limiting the broad gen- effects on the calculations of warming tolerance (Pincebourde eralizations that can be made. Although, a more comprehensive & Suppo, 2016) (for a definition of warming tolerance, see assessment in approximately 100 species of Drosophila also Box 1). Whether or not behavioural thermoregulation will be found a weak relationship between environment and tolerance important for climate change responses will also depend on

CTmax (Kellermann et al., 2012b). There may be a number of the availability of microclimates (Huey et al., 2012). Tropical

© 2019 The Royal Entomological Society, Physiological Entomology, doi: 10.1111/phen.12282 4 V. Kellermann and B. van Heerwaarden environments tend to be more thermally homogeneous than that of Kearney et al. (2009). Parametrizing their model with subtropical and temperate environments and are predicted to physiological variables from the literature, their work demon- become increasingly so under climate change (Caillon et al., strated precipitation as a key driver of Aedes aegypti distri- 2014). This means that behaviour can only buffer species for butions. In some circumstances, sufficient data to parametrize so long before adaptive shifts in fitness and stress resistance models may exist (Kearney et al., 2009), although a directive will be required to maintain the persistence of species. Whether between ecologist, physiologists and modellers to collect the behaviour might then constrain adaptive responses to climate data required for better models is urgently needed. Although change by generating large mismatches between traits and the study by Kearney et al. (2009) was published 10 years ago, environments is worthy of further exploration. only one other paper that we could find integrated mechanistic effects of precipitation into distributional models (de la Vega & Schilman, 2017). Precipitation predictors: desiccation resistance

Most studies examining climate change impacts on the fitness Phenology of species focus on the consequences of increasing temperatures. However, changes in precipitation will also play a significant Changes in phenological responses, such as seasonal tim- role (Chown et al., 2011). Precipitation has been closely associ- ing of migration, development, reproduction and diapause (dor- ated with insect distributions (Bonebrake & Mastrandrea, 2010; mancy) induction, are predicted under climate change, and their Olfert et al., 2018) and, across diverse taxa, has been implicated disruption is likely to have a large impact on fitness. For in generating stronger selection gradients than temperature example, the development time of many insects decreases (Siepielski et al., 2017). Extinction events have been related to at warmer temperatures, leading to the prediction of earlier drought events in the checkerspot butterfly (McLaughlin et al., emergence times and increases in the number of generations 2002), whereas Cohen et al. (2018) found precipitation to be per year (voltinsm) (Altermatt, 2010; Forrest, 2016). Since the equally as important as temperature with respect to predicting 1980s, a number of central European Lepidoptera species have phenology at lower latitudes. Changes in precipitation will also increased the number of generations per year, with some uni- have large effects on plant biomass, which in turn will influence or bivoltine species shifting to bi- and multivoltine life cycles, their associated insect herbivores (Zhu et al., 2014; Wade et al., respectively (Altermatt, 2010). Reproductive diapause and qui- 2017). Precipitation patterns are expected to become more escence are also photoperiod and climate sensitive, and enable variable under climate change, meaning that species will have individuals to escape stressful climatic conditions such as low to endure longer periods between precipitation events and the and high temperatures and drought (Masaki, 1980; Schmidt events themselves may be more extreme (Adler et al., 2008). For et al., 2005). Changes in voltinism and diapause under climate insects, with highly permeable membranes and a high surface change might increase fitness in some instances via increases area to volume ratio, maintaining water balance under climate in population growth rates and survival, although they might change will be vital (Edney, 1977; Chown et al., 2011). Desic- also have cascading effects on interactions between host species, cation resistance and the mechanisms that underpin desiccation prey, predators, parasites and/or disease, especially if interact- resistance (e.g. water loss rates, dehydration tolerance and ing species respond differently to changes in climate, leading water storage) are frequently used to understand how species to asynchronies between interacting species (Thackeray et al., will survive dry environments (Gibbs et al., 2003). Desiccation 2016; Kharouba et al., 2018). Furthermore, phenological shifts resistance has also been linked to species’ distributions and in diapause induction and emergence time may expose sensitive precipitation, suggesting desiccation resistance to be a key trait life stages to thermal stress and decrease survival and reproduc- under selection (Kellermann et al., 2012a; Bujan et al., 2016; tion (Forrest, 2016). For example, warmer winter/spring condi- Weldon et al., 2016). Although we know that the ability to toler- tions increase developmental rates in bark beetles, allowing a ate dry periods will be key for species’ climate change responses, second generation, although those emerging are immature stages there is a missing link between studies examining water balance that are poorly adapted to winter conditions (Dworschak et al., mechanisms and the effects of altered precipitation on fitness 2014). Although there have been many studies suggesting shifts (Chown et al., 2011). A recent study by Klockmann & Fischer in phenology with recent warming, few of these studies have (2017) showed desiccation stress significantly reduced hatching been able to directly show changes that are adaptive (Bradshaw success in butterflies, more so than temperature stress. & Holzapfel, 2001; Altermatt, 2010; Thackeray et al., 2016). The framework for successfully incorporating desiccation stress into mechanistic models and examples of how to do so could be taken from the heat literature (Bush et al., 2016). Adaptive responses to climate change For some species, the data may already exist. Kleynhans & Terblanche (2011) extensive work on desiccation stress across Models of climate change resilience, based on traits, assume different temperatures and varying humidity levels provides an that estimates are static and do not change over time. However, excellent framework for explicitly untangling the role of tem- species can adjust their physiology and fitness over short time perature and humidity, although a direct link between desic- scales (i.e. phenotypic plasticity) and longer time scales (i.e. cation resistance and fitness is missing. A rare example of evolutionary responses). To examine the capacity for species incorporating precipitation changes into mechanistic models is to adapt to climate change, researchers can employ a number

Fig. 1. (a) A hypothetical thermal performance curve (TPC) showing the relationship between performance (fitness) and temperature. The most commonly used descriptors are outlined including: the temperature where fitness is maximized opt(T ), the thermal breadth (Tbreadth) and critical thermal limits (CTmin/CTmax). (b) Thermal performance curves for fecundity and viability in Drosphila melanogaster and the temperatures at which male sterility is induced and tolerance CTmin and CTmax (data from Petavy et al., 2001; David et al., 2005; Kellermann et al., 2012a, b; Clemson et al., 2016). [Colour figure can be viewed at wileyonlinelibrary.com]. of methods. Direct estimates of genetic variance and heritability 2016). Point estimates of heritability for heat resistance are (h2) allow researchers to estimate the predicted response to not always low, with a recent meta-analysis, predominately in selection under climate change and can be estimated directly Drosophila (Diamond, 2017), suggesting significant heritability 2 2 via pedigree data: h = VA/VP,whereVA is the additive genetic (h ∼0.28). However, point estimates of heritability may not 2 variance and VP is the phenotypic variance, or h can be always provide an accurate representation of long-term selection estimated indirectly from selection experiments: h2 = R/S if responses because strong directional selection will change allele both the response to selection R and the selection intensity S frequencies and erode genetic variation (Roff, 1997). As such, are known. Significant genetic variation can also be inferred it is not clear whether standing levels of genetic variation for from experimental evolution studies, common garden studies heat resistance are adequate for sustained responses to selection. of population variation linked to environmental differences in For example, significant h2 = 0.24, calculated from the response the field (clinal studies) and transplant experiments looking for to selection, was found in D. melanogaster, yet, after eight to signatures of local adaptation (Nooten & Hughes, 2017; O’Brien 10 generations, a selection plateau was reached (Hangartner & et al., 2017). Hoffmann, 2016). Significant selection responses to increased heat resistance have been demonstrated in the whitefly Cernisia tabaci, although only five to seven generations were selected for Evolutionary responses to rising temperatures and it is possible that further generations of selection could have resulted in a plateau (Munoz-Valencia et al., 2016). Direct estimates of evolutionary potential can be difficult Another reason why point estimates of heritability may be an to estimate in non-model organisms. Consequently, most of the unreliable predictor of evolutionary responses is because these work looking at genetic variation in heat resistance in insects, estimates may be environmentally sensitive (Hoffmann & Mer- particularly direct estimates from family studies and selection ila, 1999; Husby et al., 2011; Chirgwin et al., 2015). Whether experiments, comes from Drosophila. Significant intraspecific heritability will increase or decrease under unfavourable condi- variation in heat resistance has been detected for a number tions is debated and likely to be trait and species specific (Hoff- of insect species (Sgro et al., 2010; Fallis et al., 2011; Alford mann & Merila, 1999). The genetic architecture of traits may et al., 2012; Ranga et al., 2017) but not always (Ragland & differ depending on the environment that they are measured in Kingsolver, 2008). Despite significant intraspecific variation (Bubliy et al., 2012a). For example, in rainforest Drosophila, in D. melanogaster (Sgro et al., 2010), selection for heat heritability for heat resistance was significant under projected resistance has been shown to rapidly plateau in a number summer but not winter or constant thermal regimes (van Heer- of studies and low genetic variation has been demonstrated waarden et al., 2016b), although it did not change for desiccation for one measure of heat resistance: CTmax (Gilchrist & Huey, resistance (van Heerwaarden & Sgro, 2014). Laboratory her- 1999; Mitchell & Hoffmann, 2010; Hangartner & Hoffmann, itabilities also tend to be higher than when estimated in the

© 2019 The Royal Entomological Society, Physiological Entomology, doi: 10.1111/phen.12282 6 V. Kellermann and B. van Heerwaarden field and are likely to over-estimate the response to selection surviving heat stress (Sgro et al., 2016). Determining how in the wild (Anderson et al., 2014). Changing population size these species have adapted to extreme heat environments will might also influence heritability and evolutionary responses to provide critical insight into the potential costs and mechanisms climate change. Low population sizes driven by intense selec- for insects to acquire high heat resistance. Given that only a tion and habitat fragmentation under climate change will reduce handful of Drosophila species from the 100 measured have standing genetic variation and heritability, which may limit the evolved high heat resistance and this was closely associated capacity for species to respond to further selection (Bijlsma & with phylogenetic position, ants may be the exception and Loeschcke, 2012). Estimating evolutionary potential under con- many insect species may face constraints to shifting their heat ditions that do not reflect future environmental conditions may resistance (Kellermann et al., 2012b). It is possible that the provide limited insight into evolutionary responses to climate evolutionary transitions to high heat resistance are costly and change. Whether current standing variation will allow species to require large mechanistic shifts (Hoffmann et al., 2013). survive climates not yet experienced is unlikely to be measurable Transplanting species within or beyond their current range can via estimates of evolutionary potential alone. be a powerful tool for examining patterns of local adaptation Experimental evolution studies, where populations/species and the potential for adaptive shifts beyond the current range of evolve under warmer conditions reflecting climate change, can a species (Etterson & Shaw, 2001). Not extensively utilized in be a powerful tool for predicting adaptive responses to climate insects (Nooten & Hughes, 2017), most insect transplant experi- change. In line with previous experiments directly selecting for ments are short-term, generally comprising one generation, with heat resistance (Gilchrist & Huey, 1999; Hangartner & Hoff- species transplanted within their current range (Forrest & Thom- mann, 2016), D. melanogaster failed to increase their heat resis- son, 2011; O’Brien et al., 2017). This means these studies are tance over 20 generations of slowly increasing temperatures assessing short-term impacts of transplantation on fitness, mak- and significant population declines were recorded at only31 ing it difficult to infer adaptive capacity under climate change. ∘C (Schou et al., 2014; Schou et al., 2017), a temperature well One example, from the black veined white butterfly (Aporia below their tolerance and TPC CTmax but close to the tempera- crategi) showed that eggs transplanted to lower elevations had ture at which males become sterile (David et al., 2005) (Fig. 1b). lower viability (Merrill et al., 2008). It was concluded that Experimental evolution created divergence in heat resistance warmer temperatures driving lower viability were responsible in the dung fly Sepsis punctum and D. melanogaster selected for observed range contractions in this species. However, further under warm and cold conditions for 15 years, suggesting some work explicitly testing species outside their current range and capacity for heat resistance to increase (Cavicchi et al., 1985; thus mimicking climate change is needed. Studies tend to focus Esperk et al., 2016). However, determining whether observed on cooler range margins as warmer range margins are assumed responses are ecologically meaningful or a consequence of a to be driven by biotic interactions (Thomas et al., 2001). Stud- specific response driven by laboratory experimental manipula- ies focusing on the warmer range margin could provide critical tion is difficult (Kellermann et al., 2015). Because selection will insights into what limits or promotes evolutionary responses to act on the entire organism, replicating selection patterns in a lab- climate change. Insect range contractions also offer the perfect oratory setting is virtually impossible. Kellermann et al. (2015) testing ground to determine what underpins extinction events attempted to replicate patterns of selection in D. melanogaster, and transplant experiments may be the perfect tool. reproducing a well-studied natural latitude temperature gradi- Explicit consideration of the evolution of fitness traits in ent in the laboratory. The study failed to produce clinal patterns response to climate change is limited. Consequently, it is unclear of trait evolution observed in the field. Similar mismatches in whether species have the capacity to increase their fitness or laboratory evolution versus natural populations have also been shift their thermal optimum (Topt) as climates change. In more shown in Drosophila subobscura (Fragata et al., 2018). A major than one study, thermal optimum, calculated from the TPC limitation to experimental evolution studies is that the way selec- for fecundity, did not differ between highly divergent population acts on a trait can never be truly replicated. For example, tions of D. melanogaster (Klepsatel et al., 2013; Clemson et al., studies often fail to capture the role of behavioural thermoregu- 2016). Other studies have found significant genetic variation for lation in buffering selection, as well as how extreme temperature thermal optima in activity and growth rate, in Drosophila ser- events may shape genetic variance in key traits. rata and Pieris rapae, respectively (Izem & Kingsolver, 2005; Although laboratory selection and evolution experiments Latimer et al., 2011). Outside of the TPC framework, signif- show limited capacity for heat resistance to evolve, there are icant intraspecific variation in fitness traits suggests that they examples of extreme heat resistance in insects. Thermophilic are generally underpinned by genetic variation in a number of ants can withstand temperatures upwards of 48 ∘C(Gehring& insects (Mitrovski & Hoffmann, 2001; Sgro & Blows, 2003; Wehner, 1995; Hemmings & Andrew, 2017), with some species Sarup et al., 2009; Roy et al., 2018) and point estimates of her- foraging through the hottest part of the day to avoid predators itabilites are around ∼0.12, although much of the work has and competition (Schultheiss & Nooten, 2013). Rapid shifts been performed under constant conditions (Mousseau & Roff, in heat resistance in response to urbanization have also been 1987). In Drosophila, egg-to-adult viability and thus reproduc- documented, suggesting some capacity for ants to increase tive success is lower under high temperatures, with declines in their heat resistance (Diamond et al., 2017). Spider beetles can h2 often being associated with high temperatures (Kristensen also tolerate extreme temperatures upwards of 50 ∘C, although, et al., 2015; Saxon et al., 2018) but not always (van Heerwaar- unlike ants, hot temperatures induce a period of quiescence den & Sgro, 2014). Drosophila experimental evolution studies (Yoder et al., 2009), an under-appreciated mechanism for found no evolutionary responses in fecundity or egg to adult

© 2019 The Royal Entomological Society, Physiological Entomology, doi: 10.1111/phen.12282 Adaptive responses to climate change in insects 7 viability under warm temperatures (Schou et al., 2014; Keller- in Drosophila melanogaster (Kellermann et al., 2015), in line mann et al., 2015), whereas positive selection responses for heat with clinal studies in Australian populations (James et al. 1995). resistance, in the whitefly Bemisia tabaci, did not translate into This pattern is opposite to the observed plastic decreases in correlated increases in fecundity and viability under heat stress development time at warmer temperatures both in the laboratory (Munoz-Valencia et al., 2016). Observed fitness declines under and in the field, highlighting that evolutionary responses may hot temperatures are not surprising and the limited empirical differ based on expectations from plasticity alone. Studies in studies suggest that these traits do not readily evolve (Schou other organisms also suggest that development time is heritable et al., 2014; Kellermann et al., 2015; Munoz-Valencia et al., (Bradshaw et al., 1997), although it was low and nonsignificant, 2016). Further studies examining the adaptive capacity for regardless of thermal regimes, in the beetle Tribolium casta- species to increase their fitness to higher temperatures beyond neum (Kramarz et al., 2016). Diapause occurrence in insects has point estimates are needed, as is an explicit consideration of the also found to be heritable in a number of species (Roff, 1996; potential for evolutionary shifts in thermal optima. Begin & Roff, 2002; Han & Denlinger, 2009; Chen et al., 2014) (but see also Piiroinen et al., 2011) and may be an important adaptive response for insects to avoid stressful temperatures Evolutionary responses in desiccation resistance with climate change. Significant intraspecific variation and associations with latitude and temperature (Schmidt et al., Although our understanding of how changes in precipitation 2005; Lee et al., 2011) suggest that evolution in diapause traits alter fitness is limited, data on the capacity for species toadapt may be possible. to dry environments are increasing. Intra- and interspecific Only a handful of studies, on phenological traits, provide variation in desiccation resistance suggests an underlying direct evidence for genetic responses to climate change (Brad- genetic basis (Parkash & Munjal, 1999; Kellermann et al., shaw & Holzapfel, 2001; Urbanski et al., 2012; van Asch et al., 2012a; Bujan et al., 2016), and rapid selection responses to dry 2013). One of the best examples is the shift in the timing of dia- environments have been demonstrated a number of times in D. pause in the pitcher plant mosquito, which is heritable and clines melanogaster and other Drosophila species (Blows & Hoff- with latitude along eastern North America, suggesting that this mann, 1993; Hoffmann & Parsons, 1993; Telonis-Scott et al., trait is under climatic selection (Bradshaw & Holzapfel, 2001). 2006). However, not all species have the capacity to increase Since 1972, the latitudinal cline in the timing of diapause induc- their desiccation resistance, with many tropical species of tion has been shifting, with populations from the north showing Drosophila showing low evolutionary potential when assessed a genetic shift towards a southern shorter day length form as at extreme levels of desiccation stress (relative humidity in the growing seasons have become longer as a result of warmer tem- range 5–10%) (Kellermann et al., 2009). The future of tropical peratures (Bradshaw & Holzapfel, 2001). There is evidence that Drosophila species is not quite so bleak if we examine more winter moths have adjusted their phenology to match the bud ecologically relevant measures of desiccation stress (relative burst date of their host species, which has shifted in response humidity > 35%) (van Heerwaarden & Sgro, 2014), although a to recent climate change (van Asch et al., 2013). Using both lack of evolutionary potential at extreme measures of desicca- long-term observational data and laboratory experiments, van tion stress for tropical but not widespread species suggests that Asch et al. (2013) demonstrated that the egg hatching date of there is a fundamental difference in the way tropical species the winter moth, which has shifted in response to recent cli- respond to dry environments. Beyond Drosophila, positive mate change faster than the bud burst date of its oak host, has selection responses for increased desiccation resistance have changed genetically, resulting in closer synchrony with its host. been found in the tephritid fly (Tejeda et al., 2016) and in the Although there is evidence for evolutionary potential for a num- eggs of the mosquito Aedes albopictus (Sota, 1993). Whether ber of phenological traits, there are not many examples of these other species share similar limitations similar to the tropical traits responding adaptively to climate change. The fact that Drosophila species remains to be determined. Given that envi- many insects are not shifting their phenology in pace with plants ronments are predicted to become hotter and drier, explicit may suggest there are constraints (Thackeray et al., 2016). consideration of the effects of temperature, precipitation and humidity is needed, particularly given that the genetic architecture of heat resistance can differ depending on relative humidity Phenotypic plasticity: responses to climate change (Bubliy et al., 2012a). The ability to adapt to climate change is likely to be the most important predictive factor for the long-term survival of species. Evolutionary responses in phenology traits However, the capacity to respond rapidly via phenotypic plasticity may be an important predictor of short-term survival. Here, Throughout the literature, there are many examples of insects we define phenotypic plasticity as an environmentally induced adjusting their phenology in response to recent climate change change in phenotype with no underlying change in genotype, (Forrest, 2016). Whether phenological traits are underpinned generally measured within generations (Sgro et al., 2016). by genetic variation and the degree to which these responses are Treatments used to induce phenotypic plasticity can be divided driven by phenotypic plasticity or evolution remains unclear. into long-term exposures (days to weeks) to temperatures that In the laboratory, experimental evolution studies showed fall at the lower or upper end of the viable range of a species slower development time evolved under warmer temperatures (acclimation) and can include exposure to only the adults (adult

© 2019 The Royal Entomological Society, Physiological Entomology, doi: 10.1111/phen.12282 8 V. Kellermann and B. van Heerwaarden acclimation) or during development and the adult life stage acclimation responses could compensate for increases in tem- (developmental acclimation), whereas short-term (minutes to perature by an average of 0.2 ∘Cper1∘C of warming. There hours) exposure to sublethal temperatures is termed hardening is also some evidence that plastic responses in upper thermal (Cossins & Bowler, 1987). Long-term exposures of temperature tolerance might be linked to a trade-off between innate/basal (i.e. during development) are expected to induce irreversible CTmax and plasticity. High levels of heat resistance corresponds effects, whereas short-term exposures such as hardening are to low levels of plasticity at higher temperatures (Stillman, 2003; assumed to be reversible (Piersma & Drent, 2003) and this has van Heerwaarden et al., 2016a), suggesting that the most heat been shown for heat resistance in Drosophila (Telonis-Scott tolerant species may have the lowest capacity to increase their et al., 2014; Kellermann et al., 2017). Plasticity can be exam- upper thermal limit. The evolution of plasticity in heat resis- ined using a reaction norm approach, where a trait is measured tance might also come at a cost to other fitness traits. For across a broad environmental gradient and descriptors such as example, in pea leaf miners, hardening at higher temperatures the slope and/or curvature of the reaction norm are then used to assess plasticity (Murren et al., 2014). However, the shape of a increased heat survival but decreased fecundity (Huang et al., reaction norm may differ depending on the type of trait that is 2007). Similar to heat resistance, for some Drosophila species, a assessed. For example, a fitness trait under stabilizing selection trade-off between basal desiccation resistance and plasticity has with high fitness favoured across a broad range of temperatures been observed, where species with the highest basal tolerance might show a quadratic relationship with temperature, whereas also have the lowest capacity to respond plastically to the envi- tolerance traits, where increases in tolerance are favoured under ronment (Kellermann et al., 2018). The presence of trade-offs increasingly stressful environments, might show a linear rela- suggests fundamental limits in plastic capacity, thus highlight- tionship. Reaction norm shape might also differ depending on ing that plastic responses are unlikely to be endless. Determining the range of environments examined (e.g. a reaction norm might the mechanisms that underpin plastic responses will provide key be linear across a small temperature gradient but quadratic insight into future responses. across the entire viable temperature range) (Fig. 1a). The predictability of plastic responses in phenological traits Because plastic responses can occur rapidly, plasticity has and whether plasticity will be adequate to maintain fitness under been proposed as a mechanism to buffer species from rapid climate change remains an important challenge (Visser, 2008). changes (Chevin et al., 2010) and many of the traits that are Similar to heat and desiccation resistance, predicting pheno- linked to climate change, in insects, are temperature sensitive logical responses to climate change requires an understanding and show a degree of plasticity (Sgro et al., 2016). The upper of how current and future climatic variables influence pheno- thermal tolerance of many insects is generally plastic, increasing logical responses and their cascading effects on community with warmer temperatures (Hoffmann et al., 2003; Gunderson & interactions. Studies have attempted to do this by examining Stillman, 2015), although this will begin to decline as damage accumulates (Kellermann & Sgro, 2018). Desiccation resistance year-to-year variation in phenological responses with respect to is also plastic in Drosophila and a short adult pre-treatment of emergence date and then correlating these responses back to desiccation stress, as well as developing larvae at lower relative temperature (Roy & Sparks, 2000; Hodgson et al., 2011). For humidity, increases resistance (Hoffmann, 1990; Hoffmann, example, Hodgson et al. (2011) found that nine of 15 species 1991; Parkash et al., 2012; Bubliy et al., 2012b; Aggarwal et al., of butterflies shifted their phenology over time, suggesting plas- 2013; Bubliy et al., 2013). Plasticity of thermal tolerance during ticity in phenological traits for these species. Studies have also other life stages and in other traits sensitive to climate (e.g. examined whether traits such as developmental thresholds, diet reproductive diapause, reproductive timing/peak reproductive breadth, overwintering stage and range size underlie recent phe- output) may also be important (Sgro et al., 2016). Although nological shifts in insects and whether patterns change across plasticity has been implicated in shifts in phenology and body latitude and different insect groups (Buckley et al., 2017). Dia- size in birds, mammals and fish (Merila & Hendry, 2014), to mond et al. (2011) found that butterfly species with a nar- date, there is no explicit study linking plasticity to an adaptive rower larval diet breadth, more advanced overwintering stages response to climate change in insects. Although plasticity has and smaller range sizes have experienced greater phenological the potential to buffer phenotypes from rapid climate change, advancement in first appearance dates, whereas Buckley et al. it is unlikely to be a sustained response and may even reduce (2017) reported that the lower temperature threshold for devel- selection pressures and limit longer-term selection responses opment could explain advances in phenology and increases in (Oostra et al., 2018). the numbers of generations per year, particularly at high lat- Although there is ample evidence for plasticity in insects, itudes. Studies have also found mismatches in phenological whether these responses will be sufficient to keep pace with predicted increases in temperature is less certain. There is grow- responses across trophic levels, with primary consumers changing evidence that many species have only a small capacity to ing their phenology more than other trophic levels (Thackeray et al., 2016), which might create resource mismatches. Indeed, shift their CTmax via plasticity (Gunderson & Stillman, 2015; Sorensen et al., 2016; Kellermann & Sgro, 2018). For example, in a meta-analysis, Kharouba et al. (2018) found significant in Drosophila, a combination of developmental acclimation and changes in the synchrony of phenological timing among pair- hardening only increased heat resistance by a maximum of wise species interactions over recent decades. This suggests that 0.6–1.0 ∘C (van Heerwaarden et al., 2016a). Similarly, across a changes in the synchrony of species might be widespread with range of insect species, Gunderson & Stillman (2015) found that future warming.

Fig. 2. The relationship between plasticity and latitude, in Drosophila species, overlaid on seasonality in temperature (red) and precipitation (blue), two important predictors of plasticity under the climatic variability hypothesis, for (a) CTmax and (b) desiccation hardening. The environmental variables that are the strongest predictor of plasticity for (c) CTmax and (d) desiccation hardening. [Colour figure can be viewed at wileyonlinelibrary.com].

The potential for plasticity to buffer climate change (Calosi et al., 2010; Overgaard et al., 2014; Gunderson & Still- man, 2015; Seebacher et al., 2015) (Fig. 2a). Although the the- The leading hypothesis to explain the evolution of plasticity oretical predictions for the evolution of plasticity are centred across habitats is the climatic variability hypothesis (Ghalam- around temperature, this theory can also be applied to precipita- bor et al., 2006; Gunderson & Stillman, 2015). This hypoth- tion. There is some evidence that the climatic variability hypothesis stems from theoretical models that predict that plasticity esis may explain plasticity in desiccation resistance in some should evolve when populations experience spatial and/or tem- Drosophila species (Kellermann et al., 2018). However, the pat- poral environmental heterogeneity (Via & Lande, 1985; Gabriel terns are not simple, implicating a complex interplay between & Lynch, 1992; Gilchrist, 1995), the environmental cues influ- climate, physiological trade-offs and phylogeny (Fig. 2b). The encing plasticity are strong and predictable (Gabriel & Lynch, tendency for higher plasticity in tropical species however sug- 1992; Tufto, 2000) and the cost of plasticity is low (van Tien- gests all hope is not lost. deren, 1991; Moran, 1992; Auld et al., 2010; Murren et al., Perhaps the lack of consistent results for the climatic vari- 2015). By contrast, plasticity will be lost when the environment is stable, primarily because maintaining a plastic phe- ability hypothesis is because temperature variability may not notype is presumed to be costly (DeWitt et al., 1998). Based capture how organisms experience their environment (Fig. 2). on these theoretical expectations, temperate organisms are pre- Microclimatic variation and behavioural thermoregulation could dicted to evolve broad thermal tolerances and high plasticity play an important role in buffering species from extremes to counter large seasonal/daily fluctuations in climate, whereas (Grant et al., 2017). There is also an underlying assumption tropical organisms should evolve narrow thermal tolerance and that temperature variability equals temperature predictability. reduced plasticity, in response to exposure to a less variable A predictable environment is central to theoretical models, climate (Ghalambor et al., 2006); however, the empirical evi- where predictability decreases mismatches between plastic dence for these patterns for plasticity in CTmax is equivocal responses (fitness) and the environment (Gabriel & Lynch,

Fig. 3. (Box 1). Thermal safety margins calculated as the difference between CTmax and the environment for (a) the annual mean temperature and (b) the maximum temperature (data from Kellermann et al., 2012b; Bennett et al., 2018). [Colour figure can be viewed at wileyonlinelibrary.com].

Box 1. Using CTmax to estimate warming tolerance Estimates of upper thermal limits have been used to assess species’ climate change risk (Deutsch et al., 2008; Diamond et al., 2012; Kellermann et al., 2012b). Thermal limits have been measured using thermal performance curves (TPCs), tolerance assays

estimating critical thermal limits (CTmin and CTmax) and static assays estimating thermal lethal temperatures (LLT and ULT) or a combination of each (Angilletta, 2009; Chown et al., 2009; Sinclair et al., 2016). Tolerance CTmin and CTmax represent the lower and upper operational temperature of a species and are typically estimated using dynamic/ramping tolerance assays, where temperature is gradually decreased/increased until the insect loses its righting response or activity (Chown et al., 2009) (Fig. 4).

Alternatively, CTmin and CTmax can be estimated from TPCs. TPCs are reaction norms that describe the relationship between temperature and fitness, withmin CT and CTmax calculated as the temperature at which fitness (e.g. egg production) declines to zero (Angilletta, 2009) (Fig. 1). LLT and ULT are the lower and upper lethal temperature at which mortality occurs (usually estimated

from the temperature at which LT50 or LT100 occurs) after a fixed duration of time (Bennett et al., 2018) (Fig. 4). The distinction between these different methods for estimating temperature sensitivities is important because they are likely to measure different components of thermal resilience (Hoffmann et al., 2013). To estimate which geographical areas are most of risk at climate change, studies have calculated warming tolerance (the difference

between CTmax and habitat temperature) or thermal safely margins (the difference between the temperature where fitness is optimized (Topt) (Fig. 3) and habitat temperature (Kellermann et al., 2012b). The main conclusions from these studies is that low latitude insects will be at greatest risk (Deutsch et al., 2008; Diamond et al., 2012). This is because these insects already live in above average temperatures and only a small increase in temperature will push these species beyond their thermal limits

(Deutsch et al., 2008; Dillon et al., 2010). The problem with these models, not-withstanding whether CTmax is a good proxy for climate change resilience, is that they often consider average mean temperature; but see Kellermann et al. (2012b). Temperature fluctuations may be more important in shaping fitness than average temperature per se (Hoffmann et al., 2013). If temperature fluctuations, by considering maximum temperature, are taken into consideration, then both mid and low latitude species areat high risk (Fig. 3b). The critical thermal limits data are also problematic. Focusing on data from insects, 95% of the data are from Drosophila, Coleoptera and ants. Although there is a good representation across latitudes from Drosophila, there is little data available from low latitudes in ants and beetles, making broad generalizations of insect climate change risk, particularly at lower latitudes, difficult (Fig. 4). The extent to which these measures reflect accurate and comparable measures of upper thermal toleranceis

also not clear. Studies estimating tolerance CTmax often use different starting temperatures and different rates of ramping, which, combined, will influence both duration of exposure to higher temperatures and upper thermal tolerance (Terblanche et al., 2011)

(Fig. 4). By gradually increasing temperatures in dynamic measures of CTmax, these estimates may include beneficial effects of hardening and/or the detrimental effects of cumulative heat damage incurred when the temperature is increased (Terblanche et al., 2011), whereas estimates of ULT will not. Hoffmann et al. (2013) compared these two measures and found small differences

between CTmax and ULT, although CTmin estimates were larger than LLT. Another important consideration is that some studies use wild caught individuals, whereas others acclimate individuals in the laboratory or use laboratory reared individuals. This may influence thermal tolerance as a result of plastic effects (Kellermann et al., 2017), although the extent to which thermal history might influence spatial patterns in upper thermal limits has not been investigated. These assessments of warming tolerance donot take into account phenotypic plasticity or future evolutionary responses. Furthermore, they have predominately used data collected from adult life stages, which might not accurately encompass the vulnerability of different species.

studies suggest that low to mid latitude populations will be most at risk but ignore adaptive responses and the contribution of other traits, such as desiccation resistance and phenology, to climate change responses (Deutsch et al., 2008; Diamond et al., 2012). Beyond these limitations, traits are often measured in highly controlled constant conditions, unlike anything experienced by species in natural environments. Studies compar- ing the results from constant environments with those of more ecologically relevant fluctuating thermal regimes find that the results often differ (Bozinovic et al., 2011; Ketola et al., 2014; Colinet et al., 2015; Bozinovic et al., 2016). Positive effects of temperature fluctuations are often documented within the permissible range of species but, outside this, negative effects on fitness begin to accumulate (Colinet et al., 2015; Bozinovic et al., 2016; Saxon et al., 2018). Mimicking temperature fluctuations in the laboratory is also complicated because species

Fig. 4. (Box 1). Common methods for estimating CTmax. Upper ther- are unable to buffer extreme temperatures by seeking out micro- mal limits (ULT) are estimated by calculating the temperature that climates (Duffy et al., 2015; Buckley & Huey, 2016), meaning induces 50% or 100% of mortality, whereas dynamic ramping assays that the accumulation of temperature effects is likely to be larger slowly increase temperature at different rates and measure the tempera- in laboratory experiments than that experienced in wild pop- ture at which an individual succumbs to heat. ulations. Laboratory environments can never truly mimic the complex selection patterns that organisms will experience in 1992). Although the climatic variability hypothesis was devel- the field (Kristensen et al., 2008; Kristensen et al., 2015; Zhu oped around temperature, it is also possible temperature may not et al., 2015; O’Brien et al., 2017). For example, Kristensen et al. be the most important environmental driver (Kellermann et al., (2008) showed cold acclimation in flies came at no cost in 2018). Precipitation is emerging as an important variable that the laboratory but, in the field, cold acclimated flies performed shapes the distributions of species and adaptive responses in the worse at warm temperatures. field (Kellermann et al., 2012a; Siepielski et al., 2017). Precip- Climate change will induce a combination of environmental itation tends to be more variable in tropical environments that stressors, including changes in precipitation, nutrition environ- experience distinct wet and dry seasons (Fig. 2a). If precipita- ment, disease and competition, which may have inconceivable tion, rather than temperature, is the most important driver of effects on trait fitness, evolution and, ultimately, species per- plasticity, we would expect the opposite pattern to the climatic sistence (Zhu et al., 2014). These combined effects will be variability hypothesis (i.e. higher plasticity at lower latitudes). virtually impossible to study in laboratory designs and require In reality, variation in temperature and precipitation, amongst moving beyond single species and single trait approaches. Thus, other factors (Kellermann et al., 2018), is likely to create a com- understanding the true effects of climate change on the adaptive plex environmental landscape making it difficult to predict the potential of species requires a field-based approach. Repeated evolution of plasticity across species. measures of key traits across time and space, as well as trans- Evidence from interspecific studies suggest that plastic plant experiments, are needed to increase our understanding of responses in upper thermal limits are generally small and may the range of genetic and plastic responses in field individuals. not be adequate to keep up with warming (Gunderson & Still- Such a design would not only explicitly incorporate the com- man, 2015; Kellermann & Sgro, 2018). Whether plasticity has plex range of climatic and nonclimatic drivers, but also permit the capacity to buffer species in general is debatable (Sorensen the study of more diverse species. Increasingly more complex et al., 2016) and requires a better understanding of the drivers systems for testing effects of climate change in field based envi- of plasticity evolution. No consistent patterns in plasticity with ronments are available (Couture & Lindroth, 2012; Lindroth & latitude and environmental variation means that broad scale Raffa, 2017) and this will allow us to examine these complex predictions about plastic responses are unlikely. Some studies interactions and the utility of current climate change predictors. suggest that plastic responses might be lower in species adapted Although trait-based approaches have provided some impor- to warmer and drier environments (Stillman, 2003; van Heer- tant insight into how species may respond to climate change, waarden et al., 2016a; Kellermann et al., 2018; Kellermann & ultimately, the predictive power of trait based approaches Sgro, 2018). Certainly, plasticity is unlikely to maintain species depends on the traits themselves. Are the commonly estimated and population fitness indefinitely, and evolutionary responses traits the true proxies for climate change resilience or are to climate change will be necessary. they simply the easiest to measure in laboratory and field experiments? Adults have been the primary focus, although other life stages may be more sensitive, particularly as the Improving climate change predictors capacity to behaviourally thermoregulate may vary across life stages (Kingsolver et al., 2011). An understanding of which life Our current methods for assessing the responses of species stages and which traits are the most temperature sensitive and to climate change rely heavily on a trait-based approach. These contribute to climate change resilience is needed. Species that

© 2019 The Royal Entomological Society, Physiological Entomology, doi: 10.1111/phen.12282 12 V. Kellermann and B. van Heerwaarden are failing to maintain their current distribution may hold the and longer timescales (1979-2006). Journal of Geophysical key to understanding which traits will limit species’ capacity to Research – Atmospheres, 113, D22104. respond to climate change. Aggarwal, D.D., Ranga, P., Kalra, B. et al. (2013) Rapid effects of humidity acclimation on stress resistance in Drosophila melanogaster. Comparative Biochemistry and Physiology A – Molecular & Integrative Physiology, 166, 81–90. Conclusions Alford, L., Blackburn, T.M. & Bale, J.S. (2012) Effects of acclimation and latitude on the activity thresholds of the aphid Myzus persicae in Whether species have the capacity to increase their resilience Europe. Journal of Applied Entomology, 135, 332–346. to climate change via genetic or plastic responses is unclear. Altermatt, F. 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