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Plasticity of cold-hardiness in the eastern spruce budworm, Choristoneura fumiferana Butterson, Skye 2020

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PLASTICITY OF COLD-HARDINESS IN THE EASTERN SPRUCE BUDWORM, CHORISTONEURA FUMIFERANA by  Skye Butterson  B.Sc. (Honours), Stellenbosch University, 2015  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Zoology)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  June 2020  © Skye Butterson, 2020 ii  The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, a thesis entitled:  PLASTICITY OF COLD-HARDINESS IN THE EASTERN SPRUCE BUDWORM, CHORISTONEURA FUMIFERANA  submitted by Skye Butterson in partial fulfillment of the requirements for the degree of Master of Science in Zoology  Examining Committee: Katie E. Marshall, Zoology Supervisor  Patricia M. Schulte, Zoology Supervisory Committee Member Michelle Tseng, Zoology Additional Examiner   Additional Supervisory Committee Members: Amy L. Angert, Botany Supervisory Committee Member iii  Abstract  Of all abiotic factors that drive range boundaries, temperature is the best studied because of its pervasive influence on biological processes. For populations at high-latitudes, extreme cold and the populations’ cold-hardiness set the range boundary. Phenotypic plasticity, where a single genotype results in differentiated phenotypes under differential environmental conditions, can assist populations in managing changing temperatures. Local adaptation in phenotypic plasticity, which results in different responses in different populations, can assist with the variability in temperature a species can experience across its range, especially at range boundaries. I used the eastern spruce budworm, Choristoneura fumiferana (Lepidoptera: Tortricidae) as a model system for exploring local adaptation and phenotypic plasticity of insect cold-hardiness. The species is one of the most destructive forest pests in North America, therefore accurately predicting its range and population growth is essential for management. In this thesis, I show that there is no transgenerational plasticity in cold-hardiness. However, I found a fitness cost associated with repeated cold exposures. Additionally, across the species’ range, I found both local adaptation of seasonal cold-hardiness and short-term plasticity of this trait. Therefore, the findings of this thesis provide evidence for including phenotypic plasticity and local adaptation when modelling species distributions under climate change.  iv  Lay Summary  For terrestrial insects enduring extreme temperatures is essential to survival. If insects encounter extreme temperatures, they can either migrate to more suitable areas, evolve increased tolerance to those temperatures, or exhibit phenotypic plasticity, which is the ability to change your response to environmental conditions without genetic change. The eastern spruce budworm is one of Canada’s most destructive forest pest species. It has a wide geographic range therefore populations are exposed to a variety of temperatures. In this thesis, I have tested for transgenerational plasticity (when the parental environment influences offspring responses) and local adaptation of phenotypic plasticity (different responses to environmental change in different populations) of cold-hardiness in the species. I found no evidence for transgenerational plasticity. However, I found evidence that northerly populations exhibit increased capacity for cold-hardiness when repeatedly cold-exposed compared to southerly populations. These results are important for accurately modelling population growth and species distributions. v  Preface  The research presented in this thesis is my original work. Under the guidance of my supervisor, Dr. Katie E. Marshall, I designed the experiments, collected the data, performed relevant analyses and summarized the findings here. Additional suggestions and feedback were given by Drs Amy L. Angert, Amanda D. Roe, Patricia M. Schulte and Michelle Tseng.          vi  Table of Contents  Abstract ...................................................................................................................... iii Lay Summary ............................................................................................................. iv Preface .......................................................................................................................... v Table of Contents ...................................................................................................... vi List of Figures ............................................................................................................ ix Acknowledgements ................................................................................................... xi Chapter 1: General Introduction ............................................................................ 1 1.1 The limits to species ranges ............................................................................ 1 1.2 Evolved responses to temperature .................................................................. 3 1.3 Insect cold tolerance ........................................................................................ 7 1.4 The eastern spruce budworm .......................................................................... 9 1.5 Thesis objectives ............................................................................................ 11 1.5.1 Chapter 2 objectives ............................................................................... 12 1.5.2 Chapter 3 objectives ............................................................................... 13 Chapter 2: Transgenerational Plasticity of Cold-hardiness ........................... 14 2.1 Introduction ................................................................................................... 14 2.2 Materials and methods .................................................................................. 17 2.2.1 Experimental animals ............................................................................ 17 2.2.2 Treatments ............................................................................................. 17 2.2.3 Measures of cold-hardiness .................................................................... 19 vii  2.2.3.1 Supercooling point (SCP) .................................................................... 19 2.2.3.2 Biochemical assays ............................................................................. 20 2.2.3.3 Lower lethal temperature (LLT) ........................................................ 21 2.2.4 F1: Mating and rearing ........................................................................... 22 2.2.5 Statistical analyses ................................................................................ 23 2.3 Results ........................................................................................................... 25 2.3.1 Life history.............................................................................................. 25 2.3.2 Mortality and supercooling point........................................................... 26 2.3.3 Metabolites ............................................................................................. 28 2.4 Discussion ...................................................................................................... 33 Chapter 3: Local Adaptation in Phenotypic Plasticity of Cold-hardiness .. 38 3.1 Introduction ................................................................................................... 38 3.2 Materials and methods .................................................................................. 41 3.2.1 Experimental animals ............................................................................ 41 3.2.2 Treatments ............................................................................................. 42 3.2.3 Measures of cold-hardiness .................................................................... 43 3.2.4 Statistical analyses ................................................................................ 44 3.3 Results ........................................................................................................... 45 3.4 Discussion ...................................................................................................... 55 Chapter 4: Conclusion ............................................................................................. 60 4.1 Chapter 2 summary ....................................................................................... 60 4.2 Chapter 3 summary ....................................................................................... 62 viii  4.3 Limitations and future work ......................................................................... 62 4.4 Implications ................................................................................................... 63 References.................................................................................................................. 65 Appendix .................................................................................................................... 79   ix  List of Figures  Figure 2.1 Design of cold exposures conducted in a programmable refrigerated circulating bath. ........................................................................................................... 19 Figure 2.2 Number of offspring. .................................................................................. 25 Figure 2.3 Supercooling points (SCP) (°C) as a result of cold exposures and generation in second-instar IPQL Choristoneura fumiferana larvae. ....................... 27 Figure 2.4 LT50 of F0 second-instar IPQL (Choristoneura fumiferana) larvae after different treatments shown in colour assessed at four different times during development. ................................................................................................................ 28 Figure 2.5 Total carbohydrate per larva (μmol) across the different treatments and two generations in second-instar IPQL Choristoneura fumiferana larvae. .............. 30 Figure 2.6 Glycogen per larva (μmol) across the different treatments and two generations in second-instar IPQL Choristoneura fumiferana larvae. ..................... 31 Figure 2.7 Glycerol per larva (μmol) across the different treatments and two generations in second-instar IPQL Choristoneura fumiferana larvae ...................... 32 Figure 3.1 Map of population sampling localities. ..................................................... 41 Figure 3.2 Basal SCP (°C) of second-instar Choristoneura fumiferana across different populations tested at either early (6 weeks) or late (12 weeks) into diapause. ...................................................................................................................... 46 x  Figure 3.3 Basal total carbohydrate per larva (μmol) of second-instar Choristoneura fumiferana across different populations tested at either early (6 weeks) or late (12 weeks) into diapause.................................................................................................... 47 Figure 3.4 Basal glycogen per larva (μmol) of second-instar Choristoneura fumiferana across different populations tested at either early (6 weeks) or late (12 weeks) into diapause.................................................................................................... 48 Figure 3.5 Basal glycerol per larva (μmol) of second-instar Choristoneura fumiferana across different populations tested at either early (6 weeks) or late (12 weeks) into diapause.................................................................................................... 49 Figure 3.6 Supercooling point (°C) of second-instar Choristoneura fumiferana before (“basal”) and after (“induced”) five exposures to -15 °C. ............................................ 51 Figure 3.7 Total carbohydrate (μmol) of second-instar Choristoneura fumiferana before (“basal”) and after (“induced”) five exposures to -15 °C. ................................. 52 Figure 3.8 Glycogen (μmol) of second-instar Choristoneura fumiferana before (“basal”) and after (“induced”) five exposures to -15 °C. ............................................ 53 Figure 3.9 Glycerol (μmol) of second-instar Choristoneura fumiferana before (“basal”) and after (“induced”) five exposures to -15 °C. ............................................ 54  xi  Acknowledgements A thesis is the film you watch, all polished in its artistic glory. The acknowledgements section is your closing credits. I know that I can’t convey all the emotions, work, support in my closing credits… its impossible. But I’m thankful for the ride. I would like to acknowledge the immense support and mentorship I’ve received from my supervisor. Katie – it is through your guidance that this work exists. There are so many ways in which you’ve supported me throughout these three years, academically and not. Thank you for responding to that first email. Thank you for teaching me. Thank you for nurturing discussion. Thank you for allowing me the space to struggle and share. Thank you for looking out for me when I needed it most. This work was greatly improved by thoughtful feedback from my committee members, Amy and Trish. I didn’t think I would be lucky enough that two of the most amazing scientists would agree to be on my committee, but I was. Thank you, Michelle, for making my Zoom defense a little bit more kind. None of this work would have been possible if it wasn’t for Amanda, Ashlyn and everyone else tirelessly raising budworm babies in Sault St. Marie. Your knowledge and passion for budworm is infectious, I’ve had a great time being on the budworm crew. I would also like to thank the members of Marshall (OU and UBC)~Schulte labs, and of course Derek, for fruitful lab meeting discussions. As for COMPHY and the xii  rest of the Zoology department, it was a pleasure to be a part of such an overachieving, caring, rowdy bunch. I look forward to the day that it becomes more colourful. I would also like to thank all the undergrads I’ve been lucky enough to teach. I didn’t think teaching would be such an important thing to me, but it was. Sharing a space in learning with you was my constant reminder of bigger things. Thank you for being patient with me. Being in a foreign land doing all kinds of foreign things has been so much better with the help of friends. Thank you for hanging, chatting, dancing, eating, biking, hugging and everything in-between with me. A special thank you to Ben, Ed, Isa, Javier, Jeroen, Melissa, Michelle, Olivia and Tyler. Ya’ll the MVPs.  Lastly, a thank you to the most important people in my life. Thank you for never questioning that I could successfully move to another country and do my masters. Selfs toe niemand anders dit gedoen het nie, selfs waneer julle vir my bang was, selfs toe ons dit nie kon bekostig nie. Dankie dat julle my liefde vir natuur gekoester het. Thank you Mommy, Daddy, Lee, Chad, Sage and Willow.  As we let our own light shine, we unconsciously give other people the permission to do the same.    1  Chapter 1: General Introduction  1.1 The limits to species ranges All species have a distinct geographical range. Range boundaries can be determined by a broad array of factors (Spicer & Gaston, 1999; Price & Kirkpatrick, 2009), including abiotic factors like temperature (Tomanek, 2008) and biotic factors like predation (Holt & Barfield, 2009). The North-South hypothesis (reviewed in Cahill et al., 2014) is that equatorward range limits are more often set by biotic factors, whereas abiotic factors (particularly climate) play a bigger role at poleward limits. However, it is more likely that a combination of factors limits ranges (Harley, 2000; Merrill, 2007). In addition, historical and spatial aspects like past glaciation and mountain ranges may also play a role in the boundaries of current ranges (Gaston, 2000). Range boundaries have been extensively studied but the mechanisms that set those limits are still poorly understood. Of all abiotic factors that drive range boundaries, temperature is the best studied because of its pervasive influence on biological structures and functions. Temperature drives biochemical reaction rates due to direct Arrhenius effects (Somero et al., 2017). It can influence protein stability, therefore changing both binding affinity and catalytic rate (Somero et al., 2017), further influencing reaction rates. In addition, changing temperatures alter membrane fluidity, where decreasing temperature decreases membrane fluidity, in turn, decreasing 2  the reaction rate for membrane-bound proteins (Somero et al., 2017). Extreme temperatures can result in macromolecule denaturation, apoptosis and consequently, mortality of the organism. For example, mussel hemocytes experience DNA damage after acute temperature exposure (Yao & Somero, 2012), which decreased genome integrity and initiated apoptosis. This stress can also activate downstream molecular responses important for dealing with stress, such as heat shock or antifreeze proteins, which can further contribute to whole-organism thermal tolerance (Somero et al., 2017). For ectotherms, whose body temperature closely matches their environmental temperature, temperature effects integrate from biochemical reactions up to the whole organism.  Some species have broad geographic ranges such that different populations experience substantially different thermal regimes. For populations at high latitudes, extreme cold temperature is an integral temperature stress limiting their distribution. Small ectotherms in these environments are especially at risk of freezing their body fluids due to their relatively lower thermal inertia (Rubalcaba et al., 2019). Freezing is deadly for most species because of the mechanical damage in cells caused by ice crystal formation and cellular dehydration, which can result in an accumulation of solutes and altered biochemical gradients (Lee, 2010). By comparison, populations at lower latitudes experience on average warmer temperatures and less variability in thermal conditions (Sunday et al., 2011a). Therefore, high latitude populations potentially 3  experience much higher selection pressure on cold tolerance than low latitude populations.  1.2 Evolved responses to temperature The ability to survive stressful temperatures can come from two evolved responses: phenotypic plasticity and local adaptation. Plasticity is the altered phenotypic expression of a single genotype induced by different environmental conditions and can also integrate from molecular to whole-organism scale (Pigliucci, 2001). For example, fathead minnows can increase their critical thermal maxima (CTmax) when acclimated to warmer water temperatures (Salinas et al., 2019), and similarly, they are able to seasonally increase heat shock protein (Hsp70) expression as water temperatures increase (Feder et al., 1994). By contrast, local adaptation occurs because of spatial differences in forces associated with natural selection. This results in a population evolving traits that increase fitness in its local habitat, regardless of its impact in other habitats (Kawecki & Ebert, 2004). For example, damselflies (Ischnura elegans) show strong allelic turnover along their range associated with climatic variables such as maximum summer temperature (Dudaniec et al., 2018). Consequently, we might expect that high latitude populations exhibit either local adaptation in cold tolerance or higher phenotypic plasticity of cold tolerance. In addition, phenotypic plasticity can undergo local adaptation (Kawecki & Ebert, 2004; Calosi et al., 2008), resulting in differentiated responses in different 4  populations. For example, Yampolsky et al. (2014) tested for both local adaptation and adaptive plasticity in high temperature tolerance in the widely distributed zooplankton, Daphnia magna. Individuals from sites with higher average temperature had higher heat tolerance suggesting local adaptation. Acclimation to warmer temperatures also increased heat tolerance in all populations (but to different degrees) suggesting adaptive plasticity. Therefore, local adaptation in phenotypic plasticity can assist in driving range edges by providing locally-suited capacities for tolerance shifts. Phenotypic plasticity can occur on multiple timescales: hardening, acclimation and over development. Stress hardening occurs rapidly after short exposures to sublethal conditions and is usually reversible (Mitchell et al., 2011). Rapid cold-hardening (RCH) occurs after cold exposures on the scale of minutes to hours (Lee et al., 1987; Lee & Denlinger, 2010). Marshall & Sinclair (2012) differentiate between a change in response after a single compared to repeated cold shocks, which are more common in nature. In contrast, acclimation such as seasonal cold-hardening occurs over longer timescales of days to months (Lee, 2010). Since both hardening and acclimation result in a similar response of increased cold tolerance, they might share biochemical underpinnings such cryoprotectants and membrane modifications. In addition, there is also evidence that they can layer on top of each other (Kawarasaki et al., 2013), which suggests there might also be non-shared mechanisms, although the degree of reliance on these mechanisms are unknown (Teets & Denlinger, 2013). Across developmental 5  stages, individuals can be plastic in their responses. As an example, Jensen et al. (2007) showed large variation in cold tolerance of Drosophila melanogaster depending on the lifestage tested. Additionally, Drosophila showed the capacity to undergo RCH across all lifestages, however, some lifestages had negative or neutral effects of RCH. This provides evidence for the interaction between the timescales of plasticity and the costs associated with them. Apart from intragenerational plasticity, there is also transgenerational plasticity. This occurs when parental environmental conditions influence offspring phenotype. Transgenerational plasticity (TGP) is most commonly studied as maternal effects (reviewed in Fox & Mousseau, 1998), but also include paternal, grandparental, and potentially earlier generations’ effects. For example, in the cabbage beetle, Colaphellus bowringi, the incidence of diapause in offspring is influenced by the temperature and photoperiod conditions parents are exposed to. He et al. (2018) showed that parental and offspring diapause incidence are negatively related, where if parents are exposed to conditions that increase entering diapause, when offspring are exposed to similar conditions, they decrease entering diapause. Therefore, the conditions prior generations are exposed to can have large effects on subsequent generations. Transgenerational plasticity acts through two known mechanisms: epigenetic and non-epigenetic. Epigenetic mechanisms do not directly influence base pair sequences, instead they include chemical modifications that increase or decrease transcription and translation rates. They include chromatin remodelling 6  (DNA methylation or acetylation and histone modifications) and RNA-mediated modifications (non-coding RNA and microRNA; Ho & Burggren, 2010; Gladstad et al., 2019). Non-epigenetic mechanisms of transgenerational plasticity include shifts in egg size or provisioning (Gibbs et al., 2010). Although maternal effects like changes in egg size can influence offspring fitness (Benton et al., 2005), it is unclear whether it is a direct response to different environmental conditions or a consequence of reproduction (e.g. egg size is temperature-dependent, influencing total yolk in each egg; Ernsting & Isaaks, 2000). Therefore, TGP has multiple mechanisms and can provide a rapid response to rapidly changing thermal conditions. Local adaptation does not occur in every population because there are factors that can inhibit the accumulation of differentiated characters. Dispersal can result in the sharing and mixing of characters through mating (Bohonak, 1999). Migration between geographically isolated populations could either hinder or enhance local adaption (Hoffman & Sgrò, 2011) through the homogenization of alleles or through the introduction of new alleles. At the individual level, dispersal to new environments is risky but at the population level, it is necessary to track changing environments. Smaller population sizes could result in less genetic variation within a population which can lead to less differentiated ways of dealing with local conditions (Kirkpatrick & Barton, 1997). All these drivers limit evolution broadly as well. 7  Local adaptation at range edges should encourage range expansion. There is evidence that these locally adapted range-edge populations might not be the best suited for expansion via an accumulation of detrimental traits from high incidence of inbreeding and genetic drift (Pironon et al., 2017). However, along a continuous environmental gradient, locally adapted populations at the edge could be primed for areas beyond the range, which might facilitate range shifts. Hargreaves & Eckert (2019) provide some evidence for both ideas, although high edge populations had higher lifetime fitness in comparison to lower elevation plants, this benefit disappeared under climate warming. Therefore, under projected climatic changes, there is no evidence that edge populations are better suited for range expansion. Climate change is expected to alter the already variable climatic landscape. Climatic conditions have already changed faster than ever before (IPCC, 2014). In Canada, winter and higher latitudes have experienced the most change in temperature (Zhang et al., 2019). Therefore, populations are experiencing novel thermal environments across their ranges and understanding the responses of populations across a species’ range is necessary for predicting the changes in population growth and range that may occur in the future.  1.3 Insect cold tolerance Climate extremes or thermal limits for insects are important to determining range boundaries because they set the absolute absence or presence 8  of a species with regards to the temperature in that area. Insects survive cold temperatures with cold-hardiness adaptations usually associated with diapause. Diapause is an endocrine-mediated state of metabolic arrest that usually occurs during a certain developmental stage (reviewed in Tauber et al., 1986). Diapausing insects are either obligate (independent of environmental factors) or facultative (programmed by environmental conditions like temperature and diurnal cycles) diapausers (Koštál, 2006). Diapause is a very common example of seasonal phenotypic plasticity in insects. During the diapausing lifestage cold-hardiness enhances survival at lower temperatures through physical or metabolic changes. Cold-hardiness can occur without undergoing diapause, however cold-hardiness is a component of diapause (Denlinger, 1991). Among cold-hardy insects, cold-hardiness strategies can be divided into freeze avoidance and freeze tolerance (Bale, 1993). Freeze-avoidance is the tolerance of a larger range of low temperatures through the depression of the supercooling point (SCP; the temperature at which their internal fluid freeze; Lee, 2010). The SCP is depressed through the dehydration of body water content (Holmstrup et al., 2002), expressing cryoprotectants like glycerol (Lee & Baust, 1987) or sorbitol (Duman et al., 1985), and antifreeze proteins (AFPs; Block & Duman, 1989). By contrast, freeze-tolerant animals can survive internal ice formation by deploying a similar suite of macromolecules, but also initiating freezing using ice-nucleating proteins (INPs; Duman et al., 1985).  9  1.4 The eastern spruce budworm Here I used the eastern spruce budworm, Choristoneura fumiferana (Lepidoptera: Tortricidae) as a model system for exploring local adaptation in plasticity and TGP of insect cold-hardiness. The species is considered one of the most destructive forest pests in North America and has been well-studied (Régnière & Duval, 1998; Royama et al., 2005; Gray, 2008; Pureswaran et al., 2016) primarily due to its large economic and ecological impacts (MacLean, 2004). It outbreaks in cycles of 30 – 40 years and in the past, three major outbreaks in eastern Canada (1910-20s, 1940-50s and 1970-80s) have caused defoliation on the scale of 11, 15 and 58 million hectares, respectively (Kettela, 1983). Additionally, there is spatial variation in the severity and duration of outbreaks (Candau et al., 1998). Therefore, apart from large-scale impacts on forest dynamics and carbon-sink potential, the economic cost associated with managing outbreaks compared to no management is significant (Chang et al., 2012a; Chang et al., 2012b). Using this species as a model therefore allows testing theoretical questions while producing tangible applied answers. The eastern spruce budworm has a wide distribution across Canada and the northern United States (DuPuis et al., 2017). The ecology of spruce budworm is well-understood, including larval feeding strategies, extensive moth dispersion and outbreak patterns associated with climate (Greenbank, 1956; Royama, 1984; Thomson et al., 1984; Nealis, 2015). They are univoltine and overwinter as second-instar larvae. No larval feeding occurs from hatching until the end of 10  diapause, therefore larvae rely fully on yolk provisioning to survive overwintering. At the end of winter, they feed and rapidly grow, and moult to sixth-instar larvae before pupating and eclosing into an adult moth (Sanders, 1991). The overwintering mortality when in hibernacula and the two dispersal events associated with it (into and out of the hibernacula) are the dominant sources of mortality as larvae (Miller, 1958). There is spatial as well as temporal variation in the overwintering conditions across the species’ large geographic range. The species is predicted to shift its range poleward as a response to warming winters (Gray 2008; Régnière et al., 2012). This suggests that the current northern range boundary is set by cold temperatures. The eastern spruce budworm survives winter by undergoing obligate diapause for approximately six months, from August to February (Régnière, 1990, Han & Bauce, 1993). During this period, they become more cold-hardy. They are freeze-avoidant animals and are able to depress their SCP to ~-35°C (Han & Bauce, 1995a), by accumulating ~ 0.8 M glycerol (Han & Bauce, 1995b), expressing AFPs (Tyshenko et al., 1997; Qin et al., 2007) and decreasing their water content (Han & Bauce, 1998; Bauce & Han, 2001).  While capable of surviving very brief exposures to just about their SCP, exposure to -15 °C for more than ten days can result in mortality (Han & Bauce, 1995a). Their basic mechanisms of cold-hardiness are well-understood, making them an excellent model organism for studying plasticity in cold-hardiness. 11  The role of plasticity and local adaptation in how this species survives different environmental conditions across its range is still poorly understood. Offspring fitness is influenced by parents’ nutritional status within the sixth-instar (Carisey & Bauce, 2002). They showed that parents that are fed on low quality diets result in reduced egg hatching success and early instar survival, but that surviving offspring have an increased tolerance to starvation compared to offspring with parents fed on high quality diets. Harvey (1983a, 1983b & 1985) showed that there is a geographical cline in egg weight, where northwestern populations have fewer, large eggs and southwest populations produce many, small eggs. Additionally, the work in this thesis stems from a Natural Resources Canada project (see interim report Candau et al., 2018) intended to validate predicted species distribution models. This project has showed that development times differ across the populations tested, where northern populations (Inuvik and Alberta) have faster larval development compared to more southern populations. Therefore, this thesis aims to further increase our current understanding of plasticity and local adaptation, specifically with regards to cold-hardiness measures, in this species.  1.5 Thesis objectives This thesis takes a macrophysiological approach to testing the influence of plasticity on setting range boundaries. I’ve used the eastern spruce budworm because understanding plasticity of cold-hardiness during overwintering is useful 12  for better predicting population dynamics and consequently, mapping potential range shifts and future outbreaks. Since we know mortality associated with overwintering is an important driver of C. fumiferana population size and distribution, and that winters in Canada are changing, improving our understanding of the current and predicted range of this species on all fronts is necessary.  1.5.1 Chapter 2 objectives The objective of this chapter was to determine the extent of TGP of cold-hardiness in the F1 after parental cold exposure.  Chapter 2 hypotheses 1. Repeated cold exposure drives physiological and fitness costs 2. F1 second-instar larvae’s cold-hardiness is influenced by the parental thermal environment. Chapter 2 predictions 1. F1 whose parents have been repeatedly cold exposed will have higher cold-hardiness, 2. There is a fitness cost associated with increasing offspring cold-hardiness, such parents would have smaller clutch sizes to increase offspring cold-hardiness. 13  3. Repeated cold exposures in parents will result in increased cold-hardiness measures in offspring  1.5.2 Chapter 3 objectives The objective of this chapter was to determine if there is local adaptation in C. fumiferana 1) basal cold-hardiness and 2) inducible cold-hardiness in populations across the species’ range.  Chapter 3 hypotheses 1. There is local adaptation in basal cold-hardiness, 2. Populations will exhibit local adaptation in phenotypic plasticity of cold-hardiness. Chapter 3 predictions 1. Northern populations will exhibit higher levels of measures of cold-hardiness, 2. Northern populations will exhibit higher phenotypic plasticity. 14  Chapter 2: Transgenerational Plasticity of Cold-hardiness  2.1  Introduction Climate change is exerting strong selective pressure on species. There are three potential adaptive responses to this pressure: migrate to suitable areas, adaptively evolve in place or use phenotypic plasticity (Hoffmann & Sgrò, 2011). Phenotypic plasticity, because it results in shifts in phenotype without changing genotype after exposure to different environmental conditions, can result in rapid responses to climate change (Pigliucci, 2001). Therefore, it is often the first response to changing environmental conditions both for species who have the geographical and dispersal capacity to migrate and those who do not. While phenotypic plasticity can act within generations, it can also act across generations. Across generation plasticity, or transgenerational plasticity (TGP), include the most commonly studied maternal effects (Mousseau & Fox, 1998). It is when parents alter their offspring’s responses to changing conditions (often associated with stress; Allen et al., 2008). These effects can be adaptive if prior environment conditions are good predictors for future generations’ environments (Uller, 2008; Uller et al., 2013). This alteration in offspring response can be induced through epigenetic mechanisms such as changing DNA methylation patterns (Ho & Burggren, 2010; Gladstad et al., 2019) or non-epigenetic mechanisms like altering egg sizes and therefore, offspring energetic reserves (Gibbs et al., 2010). Therefore, the occurrence of TGP is usually 15  associated with predictable stress events between parental and offspring environments, and at lifestages that occur before offspring have a chance to mediate the stress (e.g. before feeding lifestages). There is significant potential for TGP in overwintering eastern spruce budworm (Choristoneura fumiferana). The larvae overwinter as second-instar that do not feed after hatching, therefore the reserves that keep caterpillars alive through a seven-month obligate diapause is entirely dependent on parental investment (Sanders, 1991). During diapause, offspring cease development and increase cold-hardiness through the production of a suite of antifreeze proteins and the cryoprotectant glycerol synthesized from glycogen reserves (Han & Bauce, 1995b; Tyshenko et al., 1997; Qin et al., 2007). These large energetic costs are funded completely by parentally-invested reserves. Cold-hardiness can also be plastic on short timescales, responding to brief temperature fluctuations (Marshall & Sinclair, 2012). However, fluctuating temperatures also often induce additional stress in insects, including spruce budworm. For example, repeated exposures to sub-zero temperatures cause short-term increases in glycerol content in overwintering insects, but also long-term decreases in survival or reproductive output (Marshall & Sinclair, 2015). Therefore, responding to variable thermal environments with phenotypic plasticity could induce a cost to long-term survival and fitness. With climate change, C. fumiferana is predicted to increase population growth and shift its range poleward (Gray, 2008; Régnierè et al., 2012), however 16  phenotypic plasticity has not been incorporated into these models. There is some evidence in plants that not including measures of plasticity in species distribution models underestimates predicted range shifts (Benito-Garzón et al., 2011; Valladares et al., 2014). In terrestrial insects broadly, currently poleward distributions are underpredicted by the most commonly used measures of cold-hardiness, and plasticity might explain this gap (Sunday et al., 2012). Current spruce budworm species distribution models use basal thermal tolerance and do not account for plasticity (Régnière et al., 2012). By including TGP, if it exists, in species distribution models for spruce budworm, we may produce more accurate models of population growth and range. Therefore, in this chapter I hypothesized that C. fumiferana would display TGP of cold-hardiness. Using the IPQL lab strain, I exposed second-instar larvae to repeated cold exposures to test if short-term cold stress cause altered investment in cold-hardiness or energetic reserves in the offspring.   17  2.2 Materials and methods 2.2.1 Experimental animals Animals used in all experiments and measures were sourced from a colony established in 1961 at the Insect Production and Quarantine Laboratories (“IPQL”, Great Lakes Forestry Centre, Sault Ste. Marie, Canada; Roe et al., 2018). I ordered pre-diapausing caterpillars from Insect Production and Quarantine Laboratories (Sault St. Marie, Ontario, Canada) and they were shipped to the University of British Columbia with ice packs to maintain cool conditions. Once received, I left caterpillars in an incubator (MIR-154, Sanyo, Bensenville, USA) held at 2 °C in constant darkness for six weeks to induce diapause.  2.2.2 Treatments After six weeks, I separated caterpillars into “control”, “single T1” (a single cold exposure to -10 °C for 12 hours including a ramping rate of 0.05 °C/minute), “single T2” (a single exposure cold exposure to -10 °C for 12 hours the same ramping rate, but keeping them at 2°C for 152 hours (~ 6 days and 8 hours) to account for differences in time since first cold exposure between “single T1” and “repeated”) and “repeated” (five exposures to -10 °C and 2 °C for 12 hours with the same ramping rate) (Figure 2.1). When separating experimental groups, I removed larvae from their hibernacula and put 20 caterpillars in individual 0.2 18  mL microcentrifuge tubes (for SCP measures), five sets of 10 caterpillars (for biochemical assays), five sets of 20 caterpillars (for LLT measures) or 10 sets of 10 caterpillars in 0.2 mL microcentrifuge tubes (mating group), the two latter groups being held in the gauze in the tubes (Table A1). The single and repeated animal tubes were then put into a milled aluminium block (as in Sinclair et al., 2015) connected to a programmable refrigerated circulating bath (Lauda Proline RP 3530, Wurzburg, Germany) containing 50:50 ethylene glycol:water. Ten 36 AWG Type T (copper-constantan) thermocouples (Omega Engineering Inc., Laval, Canada) were placed into the block to monitor temperature. These thermocouples were interfaced with PicoTech TC-08 thermocouple interfaces connected to a computer running PicoLog software (Pico Technology, Cambridge, U.K.) taking temperature measurements in the block every 0.5 seconds. The refrigerated circulating bath was set to cycle between 2 and -10 °C for 12 hours each including ramping rates between these temperatures of 0.05 °C/min once (single) or for five full cycles (repeated). I put caterpillars back into the diapausing conditions in the incubator for 24 h recovery after this exposure. I exposed LLT caterpillars a week later due to capacity constraints on the circulating baths.  19  2.2.3 Measures of cold-hardiness 2.2.3.1 Supercooling point (SCP) SCPs were measured as in Strachan et al. (2010). I attached individual caterpillars to 36 AWG Type T copper-constantan thermocouples with a thin layer of vacuum grease. These thermocouples were threaded through the pierced top of the 0.2 mL microcentrifuge tubes and held in place with adhesive putty.  Figure 2.1 Design of cold exposures conducted in a programmable refrigerated circulating bath. A refers to timepoint control was assessed, B is single T1, black dashed line refers to trajectory of single T2 and C is the timepoint both repeated and single T2 was assessed at.  Tubes were floated on 60:40 methanol: water in a programmable refrigerated circulating bath (Lauda ECO RE 1050, Wurzburg, Germany). The refrigerated circulating bath was cooled from 2 to -52 °C at a rate of 0.09 20  °C/minute. SCP was recorded as the point before the onset of the exotherm (Lee, 2010).  2.2.3.2 Biochemical assays I homogenized groups of 10 caterpillars with approximately 90 0.5 mm Zirconium oxide beads (Next Advance Inc., Averill Park, USA) in a Bullet Blender (Storm 24, Next Advance Inc., Averill Park, USA) for two minutes at the highest speed. I added 50 µL of 0.05% Tween 20 and repeated blending. I added an additional 250 µL 0.05% Tween 20 and mixed the sample using a vortexer (Vortex-Genie 2, Scientific Industries Inc., Bohemia, USA). I then centrifuged (Allegra 64R, Beckman Coulter Canada Inc., Mississauga, Canada) the sample for 10 min at 15 000 × g. The supernatant was removed into two aliquots and stored at -80 °C for later assays.  I measured glycerol, glucose, glycogen and protein content using spectrophotometric assays following Gefen et al. (2006) using glycerol, glucose and Type II glycogen from oyster and bovine serum albumin as standards, respectively. Briefly, glycerol was measured using a Free Glycerol kit (MAK117, Sigma-Aldrich Canada Co., Oakville, Canada). Glucose was measured using a hexokinase-based Glucose assay kit (GAHK20, Sigma-Aldrich Canada Co.). Glycogen content was measured using the same kit following an 8-hour amyloglucosidase (A9228, Sigma-Aldrich Canada Co.) digestion in a dark drawer at room temperature. Soluble protein was measured using a Bicinchronicinc acid 21  kit (BCA1, Sigma-Aldrich Canada Co.). Absorbance of each reaction was measured in a spectrophotometer (Spectra Max M2, Molecular Devices, San Jose, USA) and calculated concentrations are reported in µmol/individual.  2.2.3.3 Lower lethal temperature (LLT) To estimate LLT, I exposed five groups of 20 caterpillars from each treatment group to either -15, -20, -25, -30, or -35 °C, as described in Sinclair et al. (2015).  Groups of larvae were exposed to their corresponding temperature treatment for 4 hours, by placing the pierced 0.2 mL microcentrifuge tubes into a milled aluminium block. This block was connected to a programmable refrigerated circulating bath (Lauda Proline RP 3530, Wurzburg, Germany) with 50:50 ethylene glycol:water. Ten 36 AWG Type T (copper-constantan) thermocouples (Omega Engineering Inc., Laval, Canada) were placed in the block to monitor temperature. These thermocouples were interfaced with PicoTech TC-08 thermocouple interfaces connected to a computer running PicoLog software (Pico Technology, Cambridge, UK) recording temperature in the block every 0.5 seconds. After exposure, I transferred them to Petri dishes to avoid stress when doing mortality assessment. Mortality was assessed under the microscope (MEB126, Leica, Wetzlar, Germany) by checking if caterpillars were dehydrated, out of their hibernaculum or immobile, one week after exposure, at the end of 22  diapause, at thinning (10 days after ending diapause) and at pupation. Dead caterpillars were removed at each time point.  2.2.4 F1: Mating and rearing After the exposures, I put the mating group back into an incubator at diapausing conditions (2 °C in constant darkness) for a total of 20 diapausing weeks. At this point, I removed them and put them into feeding/developing conditions (24 °C, with a 16: 8 light: dark cycle). I followed the rearing methods as described in the standard operating procedure (Great Lakes Forest Centre Insect Production Services, 2015). Briefly, groups of 10 caterpillars were put onto diet cups with artificial diet (McMorran, 1965; purchased through Insect Production and Quarantine Services). Diet cups were changed once a week to avoid the accumulation of microbes and mould. Ten days later (thinning), I put one caterpillar in each cup. At pupation, I sterilized caterpillars with a 10% bleach solution under a fume hood, rinsed them with deionized water and left them to dry on paper towels. They were then sexed under a microscope and the first 40 were weighed on a microbalance (CP 124 S, Sartorius, Göttingen, Germany). Males and females were moved to separate ventilated plastic containers to emerge. These emergence chambers were checked daily for emerged adult moths. I put the first 20 male and female moths (total of 40 moths) that emerged into 20 L clear plastic bags with 5 × 5 cm strips of waxed paper stapled together. I maintained a 50:50 female 23  and male ratio in each bag. I sprayed each treatment’s mating chamber with deionized water before and after take-down. The three mating chambers were then kept in environmental chambers (23 ± 3°C, 55 ± 10% RH, 16L:8D) in the Faculty of Forestry at the University of British Columbia. Mating chambers were set-up for a week, after which moths died and egg masses were collected. I set up emergence pans using 30 × 25 × 5 cm baking trays lined with gauze and sealed with Parafilm and electrical tape to avoid larval escape. Once second-instar caterpillars began spinning their hibernacula, I opened the emergence pans, counted how many larvae had emerged and spun their hibernacula. I then removed the gauze, wrapped it with parafilm, and put it in an incubator held at 2 °C in constant darkness. After six weeks into diapause, I repeated all measures of cold hardiness with F1 second-instar larvae.  2.2.5 Statistical analyses All statistical tests and data plots were conducted in RStudio (version 1.1.463, 2018). I fitted a Type II ANOVA model using aov function in the car package (Fox & Weisberg, 2019) with generation and treatment as predictors, after testing the model assumptions. For biochemical assays, I set protein concentration as a covariate in the model. LT50s were calculated using a generalized linear model with binomial error distribution and the dose.p function with p set to 0.5 from the MASS package (Venables & Ripley, 2002). Alpha was 24  set to 0.05 and p-values less than 0.01 are reported as such. All significant interactions were further investigated using TukeyHSD posthoc tests.   25  2.3 Results 2.3.1 Life history F0 pupae had a mean weight of 0.098 g (± 0.034) and cold exposures had no effect on pupal weight (Treatment: F(2,119)=1.11, p=0.34). After rearing out F0 exposed to no (control), a single, or five repeated cold treatments, I counted first-instar larvae in each group. Repeated cold exposures resulted in the smallest number of offspring number in comparison to control (51% more) or singly exposed F0 parents (45% more; Figure 2.2). Since rearing was conducted as mass matings, I am unable to estimate the variability in offspring number per mating.   Figure 2.2 Number of offspring. F1 first-instar IPQL (Choristoneura fumiferana) larvae following parental (F0) exposure to -10 °C once (“Single”) or five times (“Repeated”). 26  2.3.2 Mortality and supercooling point Cold exposure did not significantly change SCP of either generation, although SCP was higher in F1 generation (Generation: F(1,139)=63.77, p=p<0.01; Figure 2.3). Mortality in F0 generation was assessed after a cold exposure to five different temperatures at four different timepoints: one week after exposure, at the end of diapause (20 weeks from the onset of diapause), thinning (between instar 3 and 4) and pupation to understand the long-term effect of cold exposures (Figures A1-4). The effect of cold exposure on LT50 depended on the timepoint mortality was assessed at and treatment (Timepoint: F(3,15)=58.63, p<0.001; Treatment: F(3,15)=4.18, p=0.047). Individuals exposed to cold once (but sampled at the same time as the repeated group) died at higher temperatures at every timepoint assessed, except at the end of diapause, compared to other cold exposures (Figure 2.4). Additionally, calculated LT50 increased with time as mortality effects accrued through development. Larvae that received repeated cold exposures had the lowest calculated LT50 at every timepoint which suggests increased cold-hardiness after repeated cold exposure. 27   Figure 2.3 Supercooling points (SCP) (°C) as a result of cold exposures and generation in second-instar IPQL Choristoneura fumiferana larvae. Bold line inside box shows median, lower and upper box boundaries show 25th and 75th percentile, respectively, lower and u upper error lines show 10th and 90th percentile, respectively. Treatment groups are Single1 (larvae exposed to a single cold exposure of -10 °C for 12 hrs and assessed 24 hours after), Single2 (larvae exposed to a single cold exposure of -10 °C for 12 hrs and assessed at the same time as the repeated group) and Repeated (larvae exposed to five cold exposures of -10 °C for 12 hrs and assessed 24 hours after). Different letters indicate statistically significant comparisons (p≤α).  28   Figure 2.4 LT50 of F0 second-instar IPQL (Choristoneura fumiferana) larvae after different treatments shown in colour assessed at four different times during development. Treatment groups are Single1 (larvae exposed to a single cold exposure of -10 °C for 12 hrs a and assessed 24 hours after), Single2 (larvae exposed to a single cold exposure of -10 °C for 12 hrs and assessed at the same time as the repeated group) and Repeated (larvae exposed to five cold exposures of -10 °C for 12 hrs and assessed 24 hours after). Times assessed are 1 week (one week after the treatment), end diapause (20 weeks after the induction of diapause), thinning (ten days after ending diapause) and pupation. Error bars show standard error.  2.3.3 Metabolites Cold exposure and generation had a significant effect on energetic reserves and metabolites. Total carbohydrate significantly differed among treatments (Treatment: F(3,34)=5.42, p=0.0047). Post-hoc tests indicated single timepoint 2 29  and repeatedly exposed larvae had significantly higher than total carbohydrate content the control and single timepoint 1 (Figure 2.5). There was no significant interaction between treatment and protein mass (Treatment × Protein mass: F(3,34)=2.03 p=0.13). Similarly, glycogen content significantly differed among treatments (Treatment: F(3,34)=7.60, p<0.001), following the same trend with control and single timepoint 1 being significantly lower than single timepoint 2 and repeatedly cold exposed larvae (Figure 2.6). Protein mass also differed with glycogen concentrations (Total protein: F(1,34)=43.81, p<0.001). Cold exposure caused no significant differences in glycerol content (Treatment: F(3,34)=1.039, p=0.39). This can be attributed to the large variance (sd=0.08) compared to the other treatment groups in F0 (sd<0.01; Figure 2.7).   30  Figure 2.5 Total carbohydrate per larva (μmol) across the different treatments and two generations in second-instar IPQL Choristoneura fumiferana larvae. Refer to figure 2 caption for explanation of boxplot display. Treatment groups are Single1 (larvae exposed to a single cold exposure of -10 °C for 12 hrs and assessed 24 hours after), Single2 (larvae exposed to a single cold exposure of -10 °C for 12 hrs and assessed at the same time as the repeated group) and Repeated (larvae exposed to five cold exposures of -10 °C for12 hrs and assessed 24 hours after). Different letters indicate statistically significant comparisons (p≤α).   31   Figure 2.6 Glycogen per larva (μmol) across the different treatments and two generations in second-instar IPQL Choristoneura fumiferana larvae. Refer to figure 2 caption for explanation of boxplot display. Treatment groups are Single1 (larvae exposed to a single cold exposure of -10 °C for 12 hrs and assessed 24 hours after), Single2 (larvae exposed to a single cold exposure of -10 °C for 12 hrs and assessed at the same time as the repeated group) and Repeated (larvae exposed to five cold exposures of -10 °C for 12 hrs and assessed 24 hours after). Different letters indicate statistically significant comparisons (p≤α).    32   Figure 2.7 Glycerol per larva (μmol) across the different treatments and two generations in second-instar IPQL Choristoneura fumiferana larvae. Refer to figure 2 caption for explanation of boxplot display. Treatment groups are Single1 (larvae exposed to a single cold exposure of -10 °C for 12 hrs and assessed 24 hours after), Single2 (larvae exposed to a single cold exposure of -10 °C for 12 hrs and assessed at the same time as the repeated group) and Repeated (larvae exposed to five cold exposures of -10 °C for 4 hrs and assessed 24 hours after). Different letters indicate statistically significant comparisons (p≤α).     33  2.4 Discussion Here I show that, despite inducing a significant reduction in F0 fitness, repeated cold exposures do not induce transgenerational plasticity in C. fumiferana. I found that repeated cold exposure reduces the number of offspring a parent can produce, but there is no difference in realized or potential cold-hardiness of those offspring. Therefore, repeated cold exposures in C. fumiferana might not result in TGP, however could decrease population size over time. While this experiment was not designed to test differences in reproductive output, there was a large (>50%) decrease in the number of offspring produced by parents who had experienced repeated cold exposure. However, whether the decrease was due to some individuals being sterile or clutch sizes being small because of repeated cold exposure is untestable with the present data. The decrease in the number of first-instar offspring of parents who received repeated cold exposures could be attributed to trade-offs between the energetic costs of surviving repeated cold stress and reproductive output. For example, there are priority effects associated with trade-offs, such that some processes take energetic precedent over others (Zera & Harshman, 2001). One explanation for lack of TGP after repeated cold exposure could be that post-diapause feeding could mask the effect stress-induced TGP (Tauber et al., 1986). However, I showed that the reproductive cost occurred after the sole feeding opportunity in this species. There are then two possibilities for the lowered reproductive output: either an inability to replenish depleted energetic 34  reserves or long-term damage. The absence of a difference in pupal weights suggests that individuals were likely able to replenish themselves, and instead it is more likely that long-term damage was incurred.  In general, cold exposures negatively influence reproductive behaviour and output (Coulson & Bale, 1992; Shreve et al., 2004; Basson et al., 2011). In addition, similar trade-offs between reproductive output and cold-hardiness have been found in flies (Drosophila melanogaster) and the goldenrod gall fly (Eurosta solidaginis). Both species demonstrate reduced population growth after being repeatedly exposed to cold events in a fluctuating thermal regime even when total duration and intensity of cold exposure was matched (Marshall & Sinclair, 2010; Marshall & Sinclair, 2018). Therefore, the trade-offs between life-history traits due to energetic limitations can be detrimental to population growth. Contrary to my expectations, there was no significant increase in cryoprotectant glycerol concentration after being repeatedly exposed to cold. Marshall & Sinclair (2015) found that five exposures to -10 °C was enough to induce increased investment in glycerol content through increased glycerol synthesis from glycogen. By contrast, I found increased carbohydrate content in larvae that received repeated or a single cold exposure the matched timepoint. It could be that they are utilizing lipid reserves, however this is not well understood in C. fumiferana (Marshall & Sinclair, 2018). While I found that SCP did not change among the F0 treatment groups, there was a decrease in LT50 in caterpillars that received repeated cold 35  exposures, which indicates increased cold-hardiness. Additionally, mortality increases at over time, and is different for different treatment groups. Although I did not observe a significant increase in glycerol content as a result of cold exposure, it is possible that other cold-hardiness mechanisms (e.g. heat shock proteins or antifreeze proteins) that I didn’t measure may be responsible for increased cold-hardiness. Previous work has shown that second-instar larvae in the middle of diapause had increased survival to sub-zero exposures and that acclimation can increase survival to cold exposures (Han & Bauce, 1995a). Therefore, although tolerance to acute temperatures is very high as measured by SCP, the resultant chilling injury resulting from temperatures above the SCP is still significant.  In general, I found no difference in cold-hardiness in F1 offspring. Therefore, although I was able induce fitness costs in parents, there was no evidence of differential investment as a result of parental experience. Due to lower than expected F1 offspring numbers, I was unable to test LT50 as done in F0, however SCP as an acute measure of cold-hardiness did not change. In addition, no difference in glycerol or glycogen (source of glycerol) was found. There was a difference in cold-hardiness between the F0 and F1 generations. Although I followed the standard operating procedure for rearing spruce budworm as set by the Insect Production and Quarantine Laboratory, it is assumed that there are differences in the control of these practices between IPQL and myself. The differences between the two generations are attributed to this. 36  TGP can only be adaptive when environmental conditions are predictable between parent and offspring lifecycles. Larval C. fumiferana don’t disperse far, they are capable of dispersing between a few trees by “ballooning” on silken threads or walking to different parts of the tree crown (Johns & Eveleigh, 2013; Nealis, 2014). By comparison, adult moths disperse much larger distances, sometimes 100s of kms (Sturtevant et al., 2013). Therefore, it could be that the probability of shared environmental conditions between generations is low, and TGP of cold-hardiness in second-instars is not favoured by selection. It is also possible that TGP occurs in other winter-related traits rather than in absolute cold-hardiness or supplied energetic reserves. For example, Harvey (1961) found that some fourth-instar C. fumiferana undergo a second diapause. It could be that the occurrence of second diapause could be a plastic trait. Therefore, since it is likely that the predictability between second- and fourth-instar larvae environmental conditions is higher than between generations, it is possible that TGP could occur in the occurrence of second diapause. The lack of TGP in cold-hardiness could also be due to using a lab-selected strain. The IPQL strain has been in culture for over 70 years and has gone without the addition of wild allelles for the past 20 of those years (Roe et al., 2018). Therefore, the relaxed selection of cold-hardiness under lab conditions could have resulted in a very different response compared to wild populations (Hoffmann & Ross, 2018). So perhaps wild populations would demonstrate TGP. 37  The absence of evidence for TGP in IPQL strain diapausing cold-hardiness suggests that TGP does not need to be considered for population growth or species range models in C. fumiferana. However, it does provide further evidence that repeated cold exposure is more complicated and that fitness trade-offs in overwintering insects exist. Further work should focus on untangling the potential mechanisms of these trade-offs, and future modelling should include fitness effects of repeated cold exposure.38  Chapter 3: Local Adaptation in Phenotypic Plasticity of Cold-hardiness  3.1 Introduction Temperature has ubiquitous effects on all organisms. In small ectotherms, it both directly and indirectly drives the rates of physiological and biochemical processes (Somero et al., 2017). In addition, there is variability on multiple, interacting timescales in the thermal environments that animals are exposed to (Marshall & Sinclair, 2012). Therefore, it is likely that selective pressure exists on animals to adjust their thermal tolerance rapidly. Evolved responses to this selection include phenotypic plasticity and local adaptation. Phenotypic plasticity is altering phenotype without changing genotype as a response to environmental change (Pigliucci, 2001). In contrast, populations that are locally adapted have genetic differences that increase fitness in their location-specific environments (Kawecki & Ebert, 2004; Barrett et al., 2011). Although they are thought of two different responses, they can evolve together (Jensen et al., 2008) as there can also be local adaptation of phenotypic plasticity (Ghalambor et al., 2007). The eastern spruce budworm, Choristoneura fumiferana is a boreal defoliating caterpillar native to North America. The species has a large geographical range from Newfoundland to British Columbia, with populations as 39  far north as Inuvik, Northwest Territories. Therefore, populations across its range are exposed to a wide range of temperatures. In addition, C. fumiferana is predicted to move poleward with climate change (Gray, 2008; Régnierè et al., 2012) as winters warm, particularly in the north (Zhang et al., 2019). The eastern spruce budworm survives cold temperature during a seven-month long diapause as a second-instar larvae. As part of the diapause programme, it increases its cold-hardiness by accumulating low molecular weight cryoprotectant glycerol (Han & Bauce, 1995b) and antifreeze proteins (Tyshenko et al., 1997; Qin et al., 2007), and by decreasing body water content (Han & Bauce, 1998) to suppress its supercooling point (the temperature at which internal fluids freeze). It therefore invests a substantial amount of energy to survive this lifestage.  Cold-hardiness can be phenotypically plastic. Cold developmental acclimation can decrease CTmin (critical thermal minimum, lowest temperature before losing locomotory function; Overgaard et al., 2011; Schou et al., 2016). Crosthwaite et al. (2011) showed significant seasonal plasticity in cold-hardiness in the emerald ash borer (Agrilus planipennis) with increased glycerol content and supressed SCPs in winter. In spruce budworm, repeated cold exposure of second-instar larvae resulted in rapidly increased glycerol content (Marshall & Sinclair, 2015). Therefore, plasticity in cold-hardiness is common in insects. Most of the work on local adaptation of cold-hardiness in insects does not explicitly include the possibility of local adaptation in plasticity of cold-hardiness. 40  Sinclair et al. (2012) reviews examples of local adaptation in thermal performance measures, e.g. metabolic rate, feeding rates and locomotion, across insect populations. In Drosophila melanogaster, basal cold-hardiness varies across populations (Schmidt et al., 2005). Local adaptation in cold tolerance limits (CTmin) of natural populations was found in Eldana saccharina (Kleynhans et al., 2014). Therefore, while local adaptation of cold-hardiness occurs frequently, local adaptation of plasticity is less well-understood. Much of the work on cold-hardiness in C. fumiferana has been conducted on the IPQL strain, which has been in culture for more than 70 years. Recently, to validate the population growth/species distribution models, Candau et al. (2018) showed that the IPQL strain is not reflective of wild populations of C. fumiferana. They found that wild populations differ vastly in developmental rate, compared to the IPQL. Additionally, Harvey (1983a) showed that genetically based phenotypic differentiation exists in this species. Number and egg size vary across C. fumiferana range; with fewer, larger eggs in the northwest and more, smaller eggs in the southeast of its range when in common-garden. Therefore, testing for local adaptation in wild populations of C. fumiferana is a logical next step. Therefore, in this chapter I tested two questions using representative populations of C. fumiferana from across its range: 1) is there local adaptation in seasonal plasticity of cold-hardiness, and 2) is there local adaptation in short-term plasticity of cold-hardiness? 41  3.2 Materials and methods 3.2.1 Experimental animals I used second-instar diapausing Choristoneura fumiferana caterpillars in all experiments and measures. These cultures were originally sampled from wild populations as reported in Candau et al. (2018). Populations used in this study were originally sampled around Campbellton, New Brunswick (47°59'13.1"N 66°40'37.8"W), Fermont, Quebec (52°51'07.1"N 67°06'35.5"W), High Level, Alberta (58°50'71" N 117°14'03" W), Inuvik, Northwest Territories (68°21'56.2"N 133°42'04.9"W) and a laboratory strain that has been in culture for over 70 years (“IPQL”, see Roe et al., 2018; Figure 3.1). Wild populations were kept in culture for 1 (late diapause measures) or 2 generations (all other measures) before use.   Figure 3.1 Map of population sampling localities.  42  Diapausing larvae in newly-spun hibernacula in gauze were shipped from Insect Production and Quarantine Laboratories (Great Lakes Forestry Centre, Sault Ste. Marie, Canada) to the University of British Columbia with ice packs to maintain cool diapausing conditions. Once received, larvae were placed into an incubator (MIR-154, Sanyo, Bensenville, USA) held at 2 °C in constant darkness.  3.2.2 Treatments I removed larvae from the incubator at either six or twelve weeks into diapause, constituting the “early” and “late” diapause groups, respectively. Early diapause groups were further separated into “basal” (individuals immediately tested) or “inducible” (first exposed to a cold exposure, described below, before being tested). No caterpillars from the New Brunswick population were exposed to the inducible treatment due to limited sample numbers. I divided larvae in the inducible group into groups of approximately 10 individuals each by cutting pieces of gauze (to avoid disturbing or stressing caterpillars) and putting them into pierced 0.2 mL microcentrifuge tubes. These tubes were then placed into a milled aluminium block (as in Sinclair et al., 2015) connected to a programmable refrigerated circulating bath (Lauda Proline RP 3530, Wurzburg, Germany) containing 50:50 ethylene glycol:water. I placed ten 36 AWG Type T (copper-constantan) thermocouples (Omega Engineering Inc., Laval, Canada) in the block to monitor temperature. These thermocouples were interfaced with PicoTech TC-08 thermocouple interfaces connected to a computer 43  running PicoLog software (Pico Technology, Cambridge, U.K.) taking temperature samples in the block every 0.5 seconds. The bath was set to cycle between 2 and -15 °C for 12 hours each including ramping rates between these temperatures of 0.051 °C/min for five full cycles. I put the caterpillars back into an incubator in diapausing conditions for 24 hours to recover after the exposure.   3.2.3 Measures of cold-hardiness I extracted caterpillars from their hibernacula in the gauze and placed into 0.2 mL microcentrifuge tubes before all measurements. I separated them into 20 replicates of one caterpillar per pierced tube for SCP measures or five microcentrifuge tubes with 10 caterpillars for biochemical assays. I measured SCPs as in Strachan et al. (2010) and as described in Chapter 2 SCP methods. Late diapausing Inuvik caterpillars could not be frozen by the previous method. In this case, I estimated SCPs by placing thermocouples attached to individual caterpillars in microcentrifuge tubes in Styrofoam freezer boxes and then into a -80 °C freezer. The cooling rate for this exposure can only be estimated in this case as 9 °C/minute. I conducted biochemical assays as described in Chapter 2 biochemical assay methods.  44  3.2.4 Statistical analyses All statistical tests and data plots were conducted in RStudio (version 1.1.463, 2018). I fitted a Type II ANOVA model using aov function in the car package (Fox and Weisberg, 2019) with population, diapause stage and treatment as predictors, after testing the model assumptions. For biochemical assays, I set protein concentration as a covariate in the model. Alpha was set to 0.05. p-values less than 0.01 will be reported as such. Significant interactions were further investigated using TukeyHSD posthoc tests. Means and SE are reported in results.   45  3.3 Results Population and time in diapause had a significant effect on SCP, where the Inuvik late diapause individuals had a significantly lower SCP compared to other populations and times tested (Population: F(2,119)=4.87, p<0.001; Time: F(1,119)=16.06, p<0.001; Population × Time: F(2,119)=5.43, p<0.01; Figure 3.2).  Population and time in diapause both had a significant effect on basal total carbohydrate concentrations (Population: F(2, 29)=3.196, p=0.020; Time: F(1, 29)=15.96, p<0.001). This was driven by New Brunswick larvae in early diapause having lower total carbohydrate content than the Inuvik and Quebec early diapause larvae (Figure 3.3). Glycogen concentrations were significantly affected by time only (Time: F(1,29)=11.27, p<0.01; Figure 3.4). Population had a significant effect on basal glycerol content (Population: F(2,29)=13.85, p<0.001; Figure 3.5). In this case, larvae from Inuvik in early diapause significantly increased their glycerol at late diapause, whereas larvae from New Brunswick significantly decreased glycerol throughout diapause.    46   Figure 3.2 Basal SCP (°C) of second-instar Choristoneura fumiferana across different populations tested at either early (6 weeks) or late (12 weeks) into diapause. Different letters indicate statistically significant comparisons (p≤α).  47   Figure 3.3 Basal total carbohydrate per larva (μmol) of second-instar Choristoneura fumiferana across different populations tested at either early (6 weeks) or late (12 weeks) into diapause. Different letters indicate statistically significant comparisons (p≤α).  48   Figure 3.4 Basal glycogen per larva (μmol) of second-instar Choristoneura fumiferana across different populations tested at either early (6 weeks) or late (12 weeks) into diapause. Different letters indicate statistically significant comparisons (p≤α).   49   Figure 3.5 Basal glycerol per larva (μmol) of second-instar Choristoneura fumiferana across different populations tested at either early (6 weeks) or late (12 weeks) into diapause. Different letters indicate statistically significant comparisons (p≤α).  When I examined the effects of repeated cold exposure on measures of cold-hardiness, I found that there was a significant interaction between population and cold exposure frequency on SCP (Population: F(3,169)=10.32, p<0.001; Treatment: F(1,169)=15.80, p<0.001; Population × Treatment: F(3,169)=3.654, p=0.014; Figure 3.6). Alberta and Inuvik decreased their SCP after exposure, 50  whereas Quebec and the IPQL remained the same. For total carbohydrate, there were no significant effect of population or treatment (Population: F(3,39)=2.765, p=0.058; Treatment: F(1,39)=0.88, p=0.35; Figure 3.7). The same is true for glycogen; there was no effect of population or treatment (Population: F(3,39)=0.123, p=0.12; Treatment: F(1,39)=0.534, p=0.47; Figure 3.8). However, a significant effect of population and treatment was found on glycerol concentrations (Population: F(3,39)=36.47, p<0.001; Treatment: F(1,39)=31.31, p<0.001; Population × Treatment: F(3,39)=7.24, p<0.001; Figure 3.9).    51   Figure 3.6 Supercooling point (°C) of second-instar Choristoneura fumiferana before (“basal”) and after (“induced”) five exposures to -15 °C. Different letters indicate statistically significant comparisons (p≤α). 52   Figure 3.7 Total carbohydrate (μmol) of second-instar Choristoneura fumiferana before (“basal”) and after (“induced”) five exposures to -15 °C. Different letters indicate statistically significant comparisons (p≤α).  53   Figure 3.8 Glycogen (μmol) of second-instar Choristoneura fumiferana before (“basal”) and after (“induced”) five exposures to -15 °C. Different letters indicate statistically significant comparisons (p≤α).  54   Figure 3.9 Glycerol (μmol) of second-instar Choristoneura fumiferana before (“basal”) and after (“induced”) five exposures to -15 °C. Different letters indicate statistically significant comparisons (p≤α).   55  3.4 Discussion I found evidence for seasonal plasticity of cold-hardiness and local adaptation in the short-term plasticity of cold-hardiness in the C. fumiferana second-instar diapausing larvae. In particular, I found local adaptation in plasticity in SCP and glycerol content as individuals from the most northerly population (Inuvik) significantly decreased their SCP and increased their glycerol content at late-stage diapause, and a similar response was found in both Inuvik and Alberta (the next most northerly population tested) caterpillars after repeated cold exposure.  Populations did not differ in their basal SCP in early diapause; however, when tested at late diapause, Inuvik had a significantly lower SCP compared to other populations tested (Figure 3.2). This could be related to winters in this area, which are significantly longer and colder than the conditions from the collection localities of the other populations (Government of Canada, 2020). However, early in the experiment, the method of measuring SCP using a -80 °C freezer could have influenced this result. There is evidence that shows that cooling rates can influence absolute thermal limits (Salt, 1966; Terblanche et al., 2007). Since the cooling rate used in the -80 °C freezer was very fast (9 °C/min), this might have resulted in a much lower SCP. However, the switch in methods was due to the inability to freeze any Inuvik larvae at temperatures that were sufficient for the other populations.  In addition, following repeated cold exposures and using a refrigerated circulating bath method, the measured SCP of 56  the Inuvik population was also much lower than the other populations (Figure 3.2), suggesting that the lower SCP late in diapause is accurate. The reductions in SCP were also matched by increases in glycerol content. By accumulating low-molecular weight solutes like glycerol, insects can increase their body fluid osmolality, thereby depressing their SCP (Zachararissen, 1985). Late diapausing Inuvik individuals had significantly higher glycerol content compared to other populations tested. At early diapause, individuals from Alberta had significantly higher glycerol content than all other populations tested besides Inuvik. This could be also explained by comparatively colder and longer winters in Alberta and Inuvik. Williams et al. (2015) similarly showed evidence for local adaptation in seasonal plasticity in fall webworms (Hyphantria cunea). They showed that populations from more northerly compared to more southerly locations had differential cold-hardiness across seasons, driven by different rates of energy use, growth and development. Therefore, depending on local temperature conditions, the expression of cold-hardiness might differ over time. In comparison, I found no differences in energy content across the population comparisons in early or late diapause. Most populations had lower carbohydrate contents later in diapause, since they are actively using these reserves throughout diapause. As mentioned in the previous chapter, it could be that spruce budworm is utilizing lipid reserves, however this is not well understood in the species (Marshall & Sinclair, 2018). 57  All the populations I tested showed some evidence for local adaptation in short-term phenotypic plasticity of cold-hardiness. This was clustered into two groups, Inuvik and Alberta, and Quebec and IPQL. Given the long culture duration of the IPQL strain, it may have adapted to laboratory conditions (Hoffmann & Ross, 2018) although it still maintained similar cold-hardiness to the Quebec population. Individuals from Alberta and Inuvik were able to significantly increase their cold-hardiness after being repeatedly exposed to -15 °C, compared to both Quebec and the IPQL which could not. This clustering is supported by Lumley et al., (2020) who showed that there are three C. fumiferana genetic subgroups: eastern (which would include the Quebec and IPQL populations), central (eastern Alberta and Manitoba) and western (which would include the northern Alberta and Inuvik populations). These subgroups are hypothesized to have been created and maintained through the Wisconsin continental ice sheet and proglacial lakes that formed on the southern border of the Laurentide ice sheet as it melted, and the western boundary is further maintained through prevailing westerly winds. This validates the separation and clustering of Alberta and Inuvik because it provides evidence for geographical isolation from the eastern and central subgroups. Although the IPQL strain has been used extensively for understanding overwintering in C. fumiferana, further evidence is provided here on the importance of considering wild populations when determining range-wide responses. I do not have measures of cold-hardiness in the IPQL at late diapause, 58  however the evidence that I do have shows that short-term plasticity is comparatively lower in the IPQL compared to other wild populations compared here. The climate variability hypothesis (CVH) states that populations in areas with high thermal variability (i.e. higher latitudes) should display stronger clines for phenotypic plasticity (Janzen, 1967; Stevens, 1989). I found evidence in support of this hypothesis with short-term plasticity of cold-hardiness in Alberta and Inuvik, which experience comparatively more thermal variability than the other populations tested (Government of Canada, 2020).  Local adaptation and phenotypic plasticity can and should be included in species distribution models for C. fumiferana. Diamond (2018) highlights the use of hybrid species distribution models, which uses trait mean, variability, heritability and the plasticity of the trait to determine range shifts, therefore incorporating both plasticity and evolution. Bush et al., (2016) tested this AdaptR model and found that range loss for 17 species of Drosophila decreased by 33% in 2105 when incorporating these additional traits. For C. fumiferana, accurately modelling species distributions with these spatiotemporal adaptive models could prove useful for species management in future climates.  In summary, this chapter corroborates evidence found in Harvey (1983a) and Candau et al. (2018) of local adaptation in eastern spruce budworm. In addition, it provides novel evidence for local adaptation in seasonal and short-term phenotypic plasticity in cold-hardiness in C. fumiferana. Therefore, it gives 59  evidence for the use of these types of data in the building of species distribution and population growth models. 60  Chapter 4: Conclusion  The objective of this thesis was to assess the role of plasticity and local adaptation in overwintering survival of Choristoneura fumiferana. I specifically tested for transgenerational plasticity, local adaptation in seasonal plasticity and local adaptation in short-term phenotypic plasticity of cold-hardiness. These questions arose out of an attempt to understand the importance of these mechanisms to further improve the species distribution and population growth models for the species. The latter has implications for applied pest management under future climate change scenarios. I found no evidence for TGP in overwintering C. fumiferana; however, I found that repeated cold exposures have significant reproductive consequences. In addition, I found significant evidence for local adaptation in phenotypic plasticity, both short-term and seasonally, of cold-hardiness across C. fumiferana’s range.  4.1 Chapter 2 summary Transgenerational plasticity could evolve from selection on managing variability in temperature or could be a by-product from selection acting on a different suite of traits. Since C. fumiferana’s survival of extreme cold temperatures throughout overwintering is fully dependent on energetic provisioning of eggs, it was hypothesized that TGP was used to prime offspring to 61  manage harsh winters. The results from Chapter 2 do not support this hypothesis. I found evidence for a significant fitness cost associated with experiencing repeated cold exposures in F0 parents, but no TGP in cold-hardiness in overwintering spruce budworm was found. This is attributed to two potential reasons: 1) long-term lab selection in the IPQL strain used relaxed selection for TGP, and 2) low predictability in environmental conditions between generations due to high dispersive capabilities of adult moths. It is also possible that TGP effects can persist across multiple generations (Shama & Wegner, 2014), however, this study did not have the resolution to pick up effects from prior generations excluding F0. Martin et al. (2019) similarly found no TGP in thermal tolerance in acorn ants (Temnothorax curvispinosus). Evidence for TGP of cold-hardiness has been found in other invertebrates. For example, marine polychaete (Ophryotocha labronica) mothers increase cold tolerance corresponding to parental environments when temperatures were experienced in late oogenesis but not early oogenesis (Massamba-N’Siala et al., 2014) and blow fly (Calliphora vicina) parents exposed to warmer conditions during diapause produced larvae with decreased cold-hardiness (Coleman et al., 2014). This suggests that while TGP in temperature tolerance is certainly possible in insects, it is not always the case.  62  4.2 Chapter 3 summary The eastern spruce budworm has a large range in North America, and consequently, populations are exposed to very different temperature regimes across this range. It was hypothesized that populations would exhibit local adaptation in seasonal as well as short-term plasticity. The results from Chapter 3 provide evidence in support of this hypothesis. Two populations tested, Alberta and Inuvik, showed similar levels of short-term plasticity, which is attributed to geographical connectivity between the populations. Generally, there were no differences in basal cold-hardiness among the populations tested, however seasonal and repeated cold exposures revealed evidence for local adaptation of plasticity in the populations. The chapter results have direct implications for the predicted population growth, range shifts, and current species distribution modelling for the species. The IPQL lab strain, which forms the basis of our current understanding of cold-hardiness in the species, shows comparatively low plasticity. Therefore, increased climate extremes that select for plasticity, and altered thermal regimes in local environments as a consequence of climate change, will mean that different populations across the species’ large range will respond very differently.   4.3 Limitations and future work In my experiment testing for TGP in cold-hardiness, I used the IPQL lab strain. This strain has been used in most of the studies that form the basis of our 63  understanding of C. fumiferana cold-hardiness (Han & Bauce, 1993, 1995a, 1995b, 1998). However, since this strain has been in culture for over 70 years, it is likely that lab selection has removed much of the natural variation in this population (Hoffmann & Ross, 2018). Since we know now that local adaptation of phenotypic plasticity exists in wild populations, the existence of TGP of cold-hardiness should be tested in wild populations as well.   4.4 Implications The results from this thesis have three broad implications. The first implication is for modelling C. fumiferana population growth and ranges. The current models do not consider phenotypic plasticity or local adaptation of cold-hardiness (Régnière et al., 2012). Overwintering in this species is a significant lifestage taking up over half of their lifetime (Sanders, 1991). Therefore, differences in overwintering survival across the species’ range may account for substantial differences between projected models and realized population growth. However, I showed that TGP in cold-hardiness for second-instars is absent, therefore changes in these traits are not predictive across generations. However, evidence for local adaptation in phenotypic plasticity was found, and should be considered in future species distribution models (Diamond, 2018). This will strongly improve these models, with specific improvement in the northern range of the species.  64  The second major implication of my work is for understanding insect low temperature physiology. I show that repeated cold exposures have significant reproductive costs. Impacts of thermal stress is often only assessed after a single cold exposure (Nedvĕd et al., 1998; Chown & Terblanche, 2007). Here I show that this might not be fully reflective of the trade-offs in insect cold tolerance. We know that in nature, insects are exposed to multiple bouts of cold temperatures at varying degrees (Gaines & Denny, 1993). Although a regime of five predictable cold exposures is also not truly reflective of natural thermal regimes, Marshall & Sinclair (2015) show that although simplified, this frequency results in similar impact to more intensive regimes. The final implication of my work is for species range limits and species thermal tolerance. We are moving towards the synthesizing our understanding of thermal tolerances (Sunday et al., 2019). However, this provides evidence that although northern species might be suited for range expansion into areas of climate-suitability, depending on the type of climate, it won’t necessarily be so straightforward. Thermal limits are clearly only one part of the story: reproduction and population growth, biotic interactions (Harley, 2003), and other abiotic factors might play a role in range shifts.    65  References Allen R. M., Buckley Y. M., & Marshall D. J. 2008. Offspring size plasticity in response to intraspecific competition: An adaptive maternal effect across life‐history stages. American Naturalist 171: 225-237. Bale, J. S. 1993. Classes of insect cold hardiness. Functional Ecology 7: 751-753. Barrett, R. D., Paccard, A., Healy, T. M., Bergek, S. & Schulte, P. M. 2011. Rapid evolution of cold tolerance in stickleback. Proceedings of the Royal Society B 278: 233-238. Basson, C. H., Nyamukondiwa, C. & Terblanche, J. S. 2011. Fitness costs of rapid cold-hardening in Ceratitis capitata. Evolution 66: 296-304.  Bauce, É. & Han, E. 2001. Desiccation resistance in pre‐diapause, diapause and post‐diapause larvae of Choristoneura fumiferana (Lepidoptera: Tortricidae). Bulletin of Entomological Research 91: 321-326. Benito‐Garzón, M., Alía, R., Robson, T. M. & Zavala, M. A. 2011. Intra‐specific variability and plasticity influence potential tree species distributions under climate change. Global Ecology and Biogeography 20(5): 766-778. Benton, T. G., Plaistow, S. J., Beckerman, A. P., Lapsley, C. T. & Littlejohns, S. 2005. Changes in maternal investment in eggs can affect population dynamics. Proceedings of the Royal Society of London Series B 272: 1351-356.  Block, W. & Duman, J. G. 1989. Presence of thermal hysteresis producing antifreeze proteins in the Antarctic mite, Alaskozetes antarcticus. Journal of Experimental Zoology 250: 29-231. Bohohak, A. J. 1999. Dispersal, gene flow, and population structure. The Quarterly Review of Biology 74: 21-45. Bush, A., Mokany, K., Catullo, R., Hoffmann, A., Kellerman, V., Sgrò, C., McEvey, S. & Ferrier, S. 2016. Incorporating evolutionary adaptation in species 66  distribution modelling reduces projected vulnerability to climate change. Ecology Letters 19(12): 1468-1478. Cahill, A. E., Aiello-Lammens, M. E., Fisher-Reid, M. C., Hua, X., Karanewsky, C. J., Ryu, H. Y., Sbeglia, G. C., Spagnolo, F., Waldron, J. B. & Wiens, J. J. 2014. Causes of warm‐edge range limits: systematic review, proximate factors and implications for climate change. Journal of Biogeography 14(3): 429-442.  Calosi, P., Bilton, D. T. & Spicer, J. I. 2008. Thermal tolerance, acclimatory capacity and vulnerability to global climate change. Biology Letters 4: 99-102. Candau, J. N., Fleming, R. A. & Hopkin, A. 1998. Spatiotemporal patterns of large-scale defoliation caused by the spruce budworm in Ontario since 1941, Canadian Journal of Forest Research 28(11): 1733-1741. Candau, J., Dedes, J., Macquarrie, C. J. K., Perrault, K., Roe, A. & Wardlaw, A. 2018. Validation of a spruce budworm phenology model across environmental and genetic gradients: applications for budworm control and climate change predictions. Interim Report, Natural Resources Canada. Carisey, N. & Bauce, É. 2002. Does nutrition-related stress carry over to spruce budworm, Choristoneura fumiferana (Lepidoptera: Tortricidae) progeny? Bulletin of Entomological Research 92(2):101-108. Chang, W., Lantz, V. A., Hennigar, C. R. & MacLean, D. A. 2012a. Benefit-cost analysis of spruce budworm (Choristoneura fumiferana Clem.) control: incorporating market and non-market values. Journal of Environmental Management 93: 104-112. Chang, W., Lantz, V. A., Hennigar, C. R. & MacLean, D. A. 2012b. Economic impacts of forest pests: a case study of spruce budworm outbreaks and control in New Brunswick, Canada. Canadian Journal of Forest Research 42: 490-505. Chown, S. L. & Terblanche, J. S. 2007. Physiological diversity in insects: ecological and evolutionary contexts. Advances in Insect Physiology 33: 50-152. 67  Coleman, P. C., Bale, J. S. & Hayward, S. A. L. 2014. Cross-generation plasticity in cold hardiness is associated with diapause, but not the non-diapause developmental pathway, in the blow fly Calliphora vicina. Journal of Experimental Biology 217: 1454-1461. Coulson, S. C. & Bale, J. S. 1992. Effect of rapid cold hardening on reproduction and survival of offspring in the housefly Musca domestica. Journal of Insect Physiology 38: 421-424. Crosthwaite, J. C., Sobek, S., Lyons, D. B., Bernards, M. A. & Sinclair, B. J. 2011. The overwintering physiology of the emerald ash borer, Agrilus planipennis fairmaire (Coleoptera: Buprestidae). Journal of Insect Physiology 57(1): 166-173. Denlinger, D. L. 1991. Relationship between cold hardiness and diapause. In Insects at Low Temperature. Lee & Denlinger. Diamond, S. E. 2018. Contemporary climate‐driven range shifts: Putting evolution back on the table. Functional Ecology 32(7): 1652-1665. Dowd, W. W., King, F. A. & Denny, M. W. 2015. Thermal variation, thermal extremes and the physiological performance of individuals. Journal of Experimental Biology 218: 1956-1967. Dudaniec, R. Y., Yong, C. J., Lancaster, L. T., Svensson, E. I. & Hansson, B. 2018. Signatures of local adaptation along environmental gradients in a range-expanding damselfly (Ischnura elegans). Molecular Ecology 27(11): 2576-2593. Duman, J. G., Neven, L. G., Beals, J. M., Olson, K. R. & Castellino, F. J. 1985. Freeze-tolerance adaptations, including haemolymph protein and lipoprotein nucleators, in the larvae of the cranefly Tipula trivittata. Journal of Insect Physiology 31: 1-8. Dupuis, J. R., Brunet, B. M. T., Bird, H. M., Lumley, L. M., Fagua, G., Boyle, B., Levesque, R., Cusson, M., Powell, J. A. & Sperling, F. A. H. 2017. Genome-wide SNPs resolve phylogenetic relationships in the North American 68  spruce budworm (Choristoneura fumiferana) species complex. Molecular Phylogenetics and Evolution 111: 158-168.  Ernsting, G. & Isaaks, J. A. 2000. Ectotherms, temperature, and trade-offs: size and number of eggs in a carabid beetle. American Naturalist 155: 804-813. Feder, S. C., Yu, Z. & Spotila, J. R. 1994. Seasonal variation in heat shock proteins (hsp70) in stream fish under natural conditions. Journal of Thermal Biology 19(5): 335-341. Fox, C. W. & Mousseau, T. A. 1998. Maternal effects as adaptations for transgenerational phenotypic plasticity in insects. Maternal effects as adaptations. Oxford University Press, USA. Fox, J. & Weisberg, S. 2019. An R Companion to Applied Regression, Third edition. Sage, Thousand Oaks CA. Gaines, S. D. & Denny, M. W. 1993. The largest, smallest, highest, lowest, longest, and shortest: extremes in ecology. Ecology 74: 1677-1692. Gaston, K. J. 2000. Global patterns in biodiversity. Nature 405: 220-227. Gefen, E., Marlon, A. J. & Gibbs, A. G. 2006. Selection for desiccation resistance in adult Drosophila melanogaster affects larval development and metabolite accumulation. Journal of Experimental Biology 212: 753-760. Ghalambor, C. K., McKay, J. K., Carrol, S. P. & Reznick, D. N. 2007. Adaptive versus non‐adaptive phenotypic plasticity and the potential for contemporary adaptation in new environments. Functional Ecology 21(3): 394-407. Gibbs, M., van Dyck, H. & Karlsson, B. 2010. Reproductive plasticity, ovarian dynamics and maternal effects in response to temperature and flight in Pararge aegeria. Journal of Insect Physiology. 56: 1275-1283. Gladstad, K. M., Hunt, B. G. & Goodisman, M. A. D. 2019. Epigenetics in insects: genome regulation and the generation of phenotypic diversity. Annual Review of Entomology 64: 185-203. 69  Government of Canada. 2020. Historical climate data. Gray, D. R. 2008. The relationship between climate and outbreak characteristics of the spruce budworm in eastern Canada. Climatic Change 87: 361-383. Great Lakes Forest Centre Insect Production Services. 2015. Standard operating procedure IPS/003/003. Greenbank, D. O. 1956. The role of climate and dispersal in the initiation of outbreaks of the spruce budworm in New Brunswick I. The role of climate. Canadian Journal of Zoology 34, 453-476. Han, E.‐N. & Bauce, É. 1993. Physiological changes and cold hardiness of spruce budworm larvae, Choristoneura fumiferana (Clem.), during pre-diapause and diapause development under laboratory conditions. The Canadian Entomologist 125(6): 1043-1053. Han, E.‐N. & Bauce, É. 1995a. Non-freeze survival of spruce budworm larvae, Choristoneura fumiferana, at sub-zero temperatures during diapause. Entomologia Experimentalis et Applicata 75: 67-74. Han, E.‐N. & Bauce, É. 1995b. Glycerol synthesis by diapausing larvae in response to the timing of low temperature exposure, and implications for overwintering survival of the spruce budworm, Choristoneura fumiferana. Journal of Insect Physiology 41, 981-985. Han, E.‐N. & Bauce, É. 1998. Timing of diapause initiation, metabolic changes and overwintering survival of the spruce budworm, Choristoneura fumiferana. Ecological Entomology 23: 160-167. Hargreaves, A. L. & Eckert, C. G. 2019. Local adaptation primes cold-edge populations for range expansion but not warming-induced range shifts. Ecology Letters 22: 78-88. Harley, C. 2000. Abiotic stress and herbivory interact to set range limits across a two-dimensional stress gradient. Ecology 84(6): 1477-1488. 70  Harvey, G. T. 1961. Second diapause in spruce budworm from eastern Canada. Canadian Entomologist 93: 594-602. Harvey, G. T. 1983a. A geographical cline in egg weights in Choristoneura fumiferana (Lepidoptera: Tortricidae) and its significance in population dynamics. The Canadian Entomologist 115: 1103-1108. Harvey, G. T. 1983b. Environmental and genetic effects on mean egg weights in spruce budworm (Lepidoptera: Tortricidae). The Canadian Entomologist 115: 1109-1117. Harvey, G. T. 1985. Egg weight as a factor in the overwintering survival of spruce budworm (Lepidoptera: Tortricidae) larvae. The Canadian Entomologist 117: 1451-1461. He, H. M., Xiao, H. J. & Xue, F. S. 2018. Parental effect of diapause in relation to photoperiod and temperature in the cabbage beetle, Colaphellus bowringi (Coleoptera: Chrysomelidae). Bulletin of Entomological Research 108(6): 773-780. Hoffmann, A. A. & Ross, P. A. 2018. Rates of patterns of laboratory adaptation in (mostly) insects. Journal of Economic Entomology 111(2): 501-509. Hoffmann, A. A. & Sgrò, C. M. 2011. Climate change and evolutionary adaptation. Nature 470: 479-485. Ho, D. H. & Burggren, W. W. 2010. Epigenetics and transgenerational transfer: a physiological perspective. Journal of Experimental Biology 213: 3-16. Holmstrup, M., Bayley, M. & Ramløv, H. 2002. Supercool or dehydrate? An experimental analysis of overwintering strategies in small permeable artic invertebrates. Proceedings of the National Academy of Sciences of the United States of America 99(8): 5716-5720.  Holt, R. D. & Barfield, M. 2009. Trophic interactions and range limits: the diverse roles of predation. Proceedings of the Royal Society B 276: 1435-1442. IPCC. 2014. Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the 71  Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and L.A. Meyer (eds.)]. IPCC, Geneva, Switzerland, 151 pp. Janzen, D. H. 1967. Why mountain passes are higher in the tropics. The American Naturalist 101(919): 233-249. Jensen, D., Overgaard, J. & Sørensen, J. G. 2007. The influence of developmental stage on cold shock resistance and ability to cold-harden in Drosophila melanogaster. Journal of Insect Physiology 53(2): 179-186. Jensen, L. F., Hansen, M. M., Pertoldi, C., Holdensgaard, G., Mensberg, K. L. & Loeschcke, V. 2008. Local adaptation in brown trout early life-history traits: implications for climate change adaptability. Proceedings of the Royal Society B 275: 2859-2868. Johns, R. C. & Eveleigh, E. S. 2013. Ontogeny and stand condition influence the dispersal behaviour of a defoliating specialist caterpillar. Environmental Ecology 42(6): 1329-1337. Kawarasaki, Y., Teets, N. M., Denlinger, D. L. & Lee, R. H. 2013. The protective effect of rapid cold-hardening develops more quickly in frozen versus supercooled larvae of the Antarctic midge, Belgica antarctica. Journal of Experimental Biology 216: 3937-3945. Kawecki, T. & Ebert, D. 2004. Conceptual issues in local adaptation. Ecology Letters 7: 1225-1241. Kettela, E. G., 1983. A cartographic history of spruce budworm defoliation 1967 to 1981 in eastern North America. Canadian Forestry Service, Maritime Forest Research Centre, Fredericton, N.B., Canada. Information Report DPC-X-14. Kirkpatrick, M. J. & Barton, N. H. 1997. Evolution of a species’ range. The American Naturalist 150: 1-23. Kleynhans, E., Mitchell, K. A., Conlong, D. E. & Terblanche, J. S. 2014. Evolved variation in cold tolerance among populations of Eldana saccharina 72  (Lepidoptera: Pyralidae) in South Africa. Journal of Evolutionary Biology 27(6): 1149-1159. Koštál, V. 2006. Eco-physiological phases of insect diapause. Journal of Insect Physiolsiology 52:113–127. Lee, R.E. 2010. Low temperature biology of insects. Cambridge, UK. Lee, R. E. & Baust, J. G. 1987. Cold-hardiness in the Antarctic tick, Ixodes uriae. Physiological Zoology 60: 499-506. Lee, R. E., Chen, C. P. & Denlinger, D. L. 1987. A rapid cold-hardening process in insects. Science 238: 1415-1417. Lee, R. E. & Denlinger, D. L. 2010. Rapid cold-hardening: ecological significance and underpinning mechanisms. Low Temperature Biology of Insects (eds. D. L. Denlinger and R. E. Lee). 35-28. Cambridge University Press, U.K. Lumley, L. M., Pouliot, E., Laroche, J., Boyle, B., Brunet, B. M. T., Levesque, R. C., Sperling, F. A. H. & Cusson, M. 2020. Continent‐wide population genomic structure and phylogeography of North America’s most destructive conifer defoliator, the spruce budworm (Choristoneura fumiferana). Ecology & Evolution 10(2): 914-927. MacLean, D. A. 2004. Predicting forest insect disturbance regimes for use in emulating natural disturbance. In: Perera, A. H., Buse, L. J., Weber, M. G. (Eds.). Emulating Natural Forest Landscape Disturbances: Concepts and Applications. Columbia University Press, New York, pp. 69-82. Marshall, K. E., & B. J. Sinclair. 2010. Repeated stress exposure results in a survival-reproduction trade-off in Drosophila melanogaster. Proceedings of the Royal Society B 277: 963-969. Marshall, K. E. & Sinclair, B. J. 2012. The impacts of repeated cold exposure on insects. Journal of Experimental Biology 215: 1607-1613 Marshall, K. E., & Sinclair, B. J. 2015. The relative importance of number, duration and intensity of cold stress events in determining survival and energetics of an overwintering insect. Functional Ecology 29(3): 357-366. 73  Marshall, K. E., & Sinclair, B. J. 2018. Repeated freezing induces a trade-off between cryoprotection and egg production in the goldenrod gall fly, Eurosta solidaginis. Journal of Experimental Biology 221: 1-13. Martin, R. A., Chick, L. D., Yilmaz, A. R. & Diamond, S. E. 2019. Evolution, not transgenerational plasticity, explains the adaptive divergence of acorn ant thermal tolerance across an urban-rural temperature cline. Evolutionary Applications 12: 1678-1687. Massamba-N’Siala, G., Prevedelli, D. & Simonini, R. 2014. Trans-generational plasticity in physiological thermal tolerance is modulated by maternal pre-reproductive environment in the polychaete Ophryotrocha labronica. Journal of Experimental Biology 217: 2004-2012. McMorran, A. 1965. A synthetic diet for the spruce budworm, Choristoneura fumiferana (Clem.) (Lepidoptera: Tortricidae). The Canadian Entomogist 97: 58-62. Merrill, R. M., Gutiérrez, D., Lewis, O. T., Gutiérrez, J., Díez, S. B., Wilson, R. J. 2007. Combined effects of climate and biotic interactions on the elevational range of a phytophagous insect. Journal of Animal Ecology 77: 145-155. Miller, C. A. 1958. The measurement of spruce budworm populations and mortality during the first and second larval instars. Canadian Journal of Zoology 36: 409-422. Mitchell, K. A., Sgrò, C. M., Hoffmann, A. A. 2011. Phenotypic plasticity in upper thermal limits is weakly related to Drosophila species distributions. Functional Ecology 25: 661-70. Nedvĕd, O., Lavy, D. & Verhoef, H. 1998. Modelling the time–temperature relationship in cold injury and effect of high temperature interruptions on survival in a chill-sensitive collembolan. Functional Ecology 12: 816-824. Nealis, V. G. 2016. Comparative ecology of conifer‐feeding spruce budworms. The Canadian Entomologist 148: S33-S57. 74  Overgaard, J., Kristensen, T. N., Mitchell, K. A. & Hoffmann, A. A. 2011 Thermal tolerance in widespread and tropical Drosophila species: does phenotypic plasticity increase with latitude? The American Naturalist 178: S80-S96. Pigliucci, M. 2001. Phenotypic plasticity: beyond nature and nurture. John Hopkins University Press, USA. Pironon, S., Papuga, G., Villellas, J., Angert, A. L., García, M. B. & Thompson,  J. D.  2017.  Geographic variation in genetic and demographic performance: new insights from an old biogeographical paradigm. Biological Reviews 92: 1877-1909. Price, T. D. & Kirkpatrick, M. 2009. Evolutionary stable range limits set by interspecific competition. Proceedings of the Royal Society B 276: 1429-1434. Pureswaran, D. S., Johns, R., Heard, S. B. & Quiring, D. 2016. Paradigms of eastern spruce budworm (Lepidoptera: Tortricidae) population ecology: a century of debate. Environmental Entomology 45(6): 1333-1342. Qin, W., Doucet, D., Tyshenko, M. G. & Walker, V. K. 2007. Transcription of antifreeze protein genes in Choristoneura fumiferana. Insect Molecular Biology 16: 423-434. Régnière, J. 1990. Diapause termination and changes in thermal responses during postdiapause development in larvae of the spruce budworm, Choristoneura fumiferana (Clem.) (Lepidoptera: Tortricidae). Journal of Insect Physiology 36: 727-735. Régnierè, J. & Duval, P. 1998. Overwintering mortality of spruce budworm, Choristoneura fumiferana (Clem.) (Lepidoptera: Tortricidae), populations under field conditions. The Canadian Entomologist 130: 13-26.  Régnierè, J., St-Amant, R. & Duval, P. 2012. Predicting insect distributions under climate change from physiological responses: spruce budworm as an example. Biological Invasions 14: 1571-1586. 75  Roe, A. D., Demidovich, M. & Dedes, J. 2018. Origins and history of laboratory insect stocks in a multispecies insect production facility, with the proposal of standardized nomenclature and designation of formal standard names. Journal of Insect Science 18(3): 1-9. Royama, T. 1984. Population dynamics of the spruce budworm Choristoneura fumiferana. Ecological Monographs 54: 429-461. Royama, T., MacKinnon, W. E. Kettela, E. G. Carter, N. E. & Hartling, L. K. 2005. Analysis of spruce budworm outbreak cycles in New Brunswick, Canada, since 1952. Ecology 86(5): 1212-1224. Rubalcaba, J. G., Gouveia, S. F. & Olalla-Tárraga, M. A. 2019. A mechanistic model to scale up biophysical processes into geographical size gradients in ectotherms. Global Ecology and Biogeography 28(6): 793-803. Salinas, S., Irvine, S. E., Schertzing, C. L., Golden, S. Q. & Munch, S. M. 2019. Trait variation in extreme thermal environments under constant and fluctuating temperatures. Proceedings of the Royal Society 374: 20180177. Salt, R. W. 1966. Effect of cooling rate on the freezing temperatures of supercooled insects. Canadian Journal of Zoology 44: 654-659. Sanders, C. J. 1991. Biology of North American spruce budworms. Tortricid pests, their biology, natural enemies and control. Elsevier Science Publishers, Amsterdam, The Netherlands. Schou, M. F., Mouridsen, M. B., Sørensen, J. G. & Loeschcke, V. 2016. Linear reaction norms of thermal limits in Drosophila: predictable plasticity in cold but not in heat tolerance. Functional Ecology 31(4): 934-945. Schmidt, P. S., Matzkin, L., Ippolito, M. & Eanes, W. F. 2005. Geographic variation in diapause incidence, life-history traits, and climatic adaptation in Drosophila melanogaster. Evolution 59:1721-1732. Shama, L. N. S. & Wegner, K. M. 2014. Grandparental effects in marine sticklebacks: transgenerational plasticity across multiple generations. Journal of Evolutionary Biology 27(11): 2297-2307. 76  Shreve, S. M., Kelty, J. D. & Lee, R. E. 2004. Preservation of reproductive behaviors during modest cooling: rapid cold-hardening fine-tunes organismal response. Journal of Experimental Biology 207:1797-1802. Sinclair, B. L., Coello Alvarado, L. E. & Ferguson, L. V. 2015. An invitation to measure insect cold tolerance: methods, approaches, and workflow. Journal of Thermal Biology 53: 180-197. Sinclair, B. J., Williams, C. M. & Terblanche, J. S. 2012. Variation in thermal performance among insect populations. Physiological and Biochemical Zoology 85(6): 594-606. Somero, G. N. 2010. The physiology of climate change: how potentials for acclimatization and genetic adaptation will determine ‘winners’ and ‘losers’. Journal of Experimental Biology 213: 912-920. Somero, G. N., Lockwood, B. L. & Tomanek, L. 2017. Biochemical adaptation: response to environmental challenges from life’s origin to the Anthropocene. Sunderland, Massachusetts, USA. Spicer, J. I. & Gaston, K. J. 1999. Physiological diversity and its ecological implications. Blackwell Science, Oxford, UK. Stevens, G. C. 1989. Geographical range: how so many species coexist in the tropics. The American Naturalist 133(2): 240-256. Strachan, L. A., Tarnowski-Garner, H. E., Marshall, K. E. & Sinclair, B. J. 2010. The evolution of cold tolerance in Drosophila. Physiological Chemistry & Zoology 84: 43-53. Sturtevant, B. R., Achtemeier, G. L., Charney, J. J., Anderson, D. P., Cooke, B. J. & Townsend, P. A. 2013. Long-distance dispersal of spruce budworm (Choristoneura fumiferana Clemens) in Minnesota (USA) and Ontario (Canada) via the atmospheric pathway. Agricultural and Forest Meteorology 168: 186-200. Sunday, J. M., Bates, A. E. & Dulvey, N. K. 2011a. Global analysis of thermal tolerance and latitude in ectotherms. Proceedings of the Royal Society B 278: 1823-1830. 77  Sunday, J. M., Bates, A. E. & Dulvey, N. K. 2011b. Thermal tolerance and the global redistribution of animals. Nature Climate Change 2: 686-690. Sunday, J., Bennett, J., Calosi, P., Clusella-Trullas, S., Gravel, S., & Hargreaves, A. et al. 2019. Thermal tolerance patterns across latitude and elevation. Philosophical Transactions of the Royal Society B 374(1778): 1-10. M. J., Tauber, C. A. & Masaki, S. 1986. Seasonal Adaptations of Insects. Oxford University Press, New York. Teets, N. M. & Denlinger, D. L. 2013. Physiological mechanisms of seasonal and rapid cold-hardening in insects. Physiological Entomology 38(2): 105-116. Terblanche, J. S., Deere, J. A., Clusella-Trullas, S., Janion, C. & Chown, S. L. 2007. Critical thermal limits depend on methodological context. Proceedings of the Royal Society B 274: 2935-2942. Thomson, A. J., Shepherd, R. F., Harris, J. W. E. & Silversides, R. H. 1984. Relating weather to outbreaks of western spruce budworm, Choristoneura occidentalis (Lepidoptera: Tortricidae), in British Columbia. The Canadian Entomologist 116: 375-381. Tomanek, L. 2008. The importance of physiological limits in determining biogeographical range shifts due to global climate change: the heat-shock response. Physiological and Biochemical Zoology 81(6): 709-717.  Tyshenko, M. G., Doucet, D., Davies, P. L. & Walker, V. K. 1997. The antifreeze potential of the spruce budworm thermal hysteresis protein. Nature Biotechnology, 15, 887-890. Uller, T. 2008. Developmental plasticity and the evolution of parental effects. Trends in Ecology & Evolution 23: 432-8. Uller, T., Nakagawa, S. & English, S. 2013. Weak evidence for anticipatory parental effects in plants and animals. Journal of Evolutionary Biology 26: 2161-70.  78  Valladares, F., Matesanz, S., Guilhaumon, F., Araújo, M. B., Balaguer, L., Benito‐Garzón, M., Cornwell, W., Gianoli, E., van Kleunen, M., Naya, D. E., Nicotra, A. B., Poorter, H. & Zavala, M. A. 2014. The effects of phenotypic plasticity and local adaptation on forecasts of species range shifts under climate change. Ecology Letters 17: 1351-1364. Venables, W. N. & Ripley, B. D. 2002. Modern Applied Statistics with S, Fourth edition. Springer, New York. Williams, C. M., Chick, W. D. & Sinclair, B. J. 2015. A cross‐seasonal perspective on local adaptation: metabolic plasticity mediates responses to winter in a thermal‐generalist moth. Functional Ecology 29(4): 549-561. Yampolsky, L. Y., Schaer, T. M. M. & Ebert, D. Adaptive phenotypic plasticity and local adaptation for temperature tolerance in freshwater zooplankton. Proceedings of the Royal Society B 281: 1-9. Yao, C. & Somero, G. 2012. The impact of acute temperature stress on hemocytes of invasive and native mussels (Mytilus galloprovicialis and Mytilus californianus): DNA damage, membrane integrity, apoptosis and signaling pathways. The Journal of Experimental Biology 215: 4267-4277. Zacharariassen, K. E. 1985. Physiology of cold tolerance in insects. Physiological Reviews 65(4): 799-832. Zera, A. J. & Harshman, L. G. 200. The physiology of life history trade-offs in animals. Annual Review of Ecology, Evolution, and Systematics 32: 95-126. Zhang, X., Flato, G., Kirchmeier-Young, M., Vincent, L., Wan, H., Wang, X., Rong, R., Fyfe, J., Li, G. & Kharin, V.V. 2019. Changes in Temperature and Precipitation Across Canada; Chapter 4 in Bush, E. and Lemmen, D.S. (Eds.) Canada’s Changing Climate Report. Government of Canada, Ottawa, Ontario, 112-119.  79  Appendix  Table A1. Sample sizes for all measures assessed. Measures assessed per treatment taken as: supercooling point, 20 caterpillars; metabolites, 5 biological replicates of 10 caterpillars; lower lethal temperature, 5 tubes with 20 caterpillars each per temperature treatment; mating, 100 caterpillars. Measurement Sample size (n) Supercooling point 20 Metabolites 5  Lower lethal temperature 100 Mating 100      80   Figure A1. Proportion of survival of Control F0 second-instar IPQL (Choristoneura fumiferana) larvae  assessed at different developmental times after 4-hour exposures to lower lethal temperature treatments (n=100 per treatment). Times assessed are A) 1 week, B) the end of diapause, C) thinning, and D) pupation.     81   Figure A2. Proportion of survival of Single T1 F0 second-instar IPQL (Choristoneura fumiferana) larvae assessed at different developmental times after 4-hour exposures to lower lethal temperature treatments (n=100 per treatment). Times assessed are A) 1 week, B) the end of diapause, C) thinning, and D) pupation.    82   Figure A3. Proportion of survival of Single T2 F0 second-instar IPQL (Choristoneura fumiferana) larvae assessed at different developmental times after 4-hour exposures to lower lethal temperature treatments (n=100 per treatment). Times assessed are A) 1 week, B) the end of diapause, C) thinning, and D) pupation.    83   Figure A4. Proportion of survival of Repeated F0 second-instar IPQL (Choristoneura fumiferana) larvae assessed at different developmental times after 4-hour exposures to lower lethal temperature treatments (n=100 per treatment). Times assessed are A) 1 week, B) the end of diapause, C) thinning, and D) pupation.    

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