Cross-tolerance evolution is driven by selection on heat tolerance in 1 Drosophila subobscura

11 The evolution of heat tolerance is a crucial mechanism for the adaptive response to 12 global warming, but it depends on the genetic variance carried by populations and on 13 the intensity of thermal stress in nature. Experimental selection studies have greatly 14 benefited research into heat tolerance, providing valuable insights into its evolutionary 15 process. However, the impact of varying levels of heat stress intensity on the associated 16 changes in resistance traits has not yet been explored. Here, the correlated evolution of 17 increasing knockdown temperature in Drosophila subobscura was evaluated on the 18 knockdown time at different stress temperatures (35, 36, 37, and 38 ºC), thermal death 19 time (TDT) curves, and desiccation and starvation resistance. The selection of heat 20 tolerance was performed using different ramping temperatures to compare the impact of 21 heat intensity selection on resistance traits. Correlated evolution was found for these 22 four resistance traits in D. subobscura , indicating that the evolutionary response to 23 tolerance of higher temperatures also confers the ability to tolerate other stresses such as 24 desiccation and starvation. However, these correlated responses depended on the 25


INTRODUCTION
Rising environmental temperatures are a major challenge for ectotherms (i.e., organisms whose body temperature depends on the ambient temperature) because their morphology, physiology, behavior, and performance depend on the thermal environment (Huey and Stevenson 1979;Cossins and Bowler 1987;Angilletta 2009).Furthermore, rising environmental temperatures increase the risk of extinction for many species living near their upper thermal limits (Deutsch et al. 2008;Huey et al. 2009;Hoffmann and Sgrò 2011).However, ectotherms can avoid the negative effects of heat through behavioral thermoregulation, evolutionary change, and/or phenotypic plasticity of the upper thermal limits (Visser 2008).
Evolutionary adaptation depends on the genetic variation exhibited by upper thermal limits; however, some studies have suggested that heat tolerance has a limited evolutionary potential to respond to increasing environmental temperatures (Chown et al. 2009;Mitchell and Hoffmann 2010;Kellermann et al. 2012).Yet, theoretical and empirical evidence suggests that heritability estimates for heat tolerance tend to be lower when heat tolerance is measured in longer assays (e.g., slow-ramping assays or static assays using sublethal temperatures) than in shorter assays (e.g., fast-ramping assays or static assays using extremely high temperatures) (Chown et al. 2009;Mitchell and Hoffmann 2010;Rezende et al. 2011;Blackburn et al. 2014;Heerwaarden et al. 2016;Castañeda et al. 2019).Thus, the intensity of heat stress may influence our predictions regarding the evolutionary potential of heat tolerance, but how do populations respond to variable selection driven by heat stress?Selection under laboratory conditions has a long history of providing information on the adaptive evolution of specific selective agents (Lenski and Bennett 1993;Garland Jr 2003;Fuller et al. 2005;Gibbs and Gefen 2009).In particular, the experimental evolution of heat tolerance has been assessed in several species, including fish, corals, and insects (Baer and Travis 2000;Kelly et al. 2012;Geerts et al. 2015;Esperk et al. 2016).Experimental evolution of heat tolerance has also been studied in several Drosophila species, including D. melanogaster (Gilchrist and Huey 1999;Folk et al. 2006), D. subobscura (Quintana and Prevosti 1990;Mesas et al. 2021;Mesas and Castañeda 2023), and D. buzzatti (Krebs and Loeschcke 1996).Most of these studies reported the evolution of heat tolerance using fast ramping protocols, ranging from 0.4 ºC/min in Folk et al. (Folk et al. 2006) to 1 °C/min in Gilchrist and Huey (Gilchrist and Huey 1999) or static hightemperature assays (40 °C), as in Bubliy and Loeschcke (2005).Recently, Mesas et al. (Mesas et al. 2021) reported that selected lines of D. subobscura evolved higher heat tolerance, regardless of the heating rate used during the selection experiments (slowramping rate: 0.08 °C/min and fast-ramping rate: 0.4 °C/min).

Interestingly, several of these selection experiments on heat tolerance in
Drosophila have found correlated responses in other traits such as starvation resistance, desiccation resistance, and heat shock proteins (Hoffmann et al. 1997;Feder et al. 2002;Bubliy and Loeschcke 2005).However, the intensity of thermal stress is expected to have important effects on the correlated responses of other traits to heat tolerance selection (Fragata and Simões 2022).For example, fast-ramping selected lines have evolved thermal performance curves with higher optimum temperatures and narrower thermal breadths than slow-ramping selected lines (Mesas et al. 2021).In addition, Mesas and Castañeda (Mesas and Castañeda 2023) reported that the evolution of heat tolerance was associated with reduced activity of the enzymes involved in the glucose-6-phosphate branch point and increased performance of life-history traits in slowramping selected lines.However, they did not observe any changes in the metabolic rate of the selected lines, as predicted by Santos et al. (2012).In summary, there is evidence that heat stress intensity determines the magnitude of the evolutionary responses of performance, metabolic, and life-history traits to heat tolerance selection; however, the correlated evolution of resistance traits has not yet been tested.This information should explain how thermal stress intensity might determine the cross-tolerance evolution to stressful environmental conditions.Natural populations are regularly subjected to multiple environmental stressors, and it is well-established that enhanced tolerance to one stressor can enhance tolerance to another (Rodgers and Gomez Isaza 2023).Crosstolerance induced by thermal stress has been widely studied in several arthropod species, increasing resistance to desiccation, insecticides, and pathogens (Kalra et al. 2017;Rodgers and Gomez Isaza 2021;Singh et al. 2022).However, the cross-tolerance patterns at the evolutionary level can be constrained or facilitated by genetic correlations among resistance traits depending on the environmental context (Lande and Arnold 1983;Bubliy and Loeschcke 2005;Gerken et al. 2016).
Previous research has examined the impact of varying levels of heat stress on the heat knockdown temperature of D. subobscura, as well as its associated impacts on thermal performance curves (Mesas et al. 2021), energy metabolism, and fitness-related traits (Mesas and Castañeda 2023).The evolutionary response of these traits was evaluated using two thermal selection protocols that differed in the rate of temperature increase (hereafter, ramping rate) to measure the heat knockdown temperature: slowramping selection (0.08ºC min -1 ) and fast-ramping selection (0.4ºC min -1 ).The present study investigates the effects of heat intensity selection for increasing knockdown temperature on the cross-tolerance evolution of four different resistance traits in D.
subobscura: knockdown time at different stress temperatures, thermal-death-time curves (TDT), desiccation resistance, and starvation resistance.In particular, TDT curves represent an integrative approach to assess how the probability of survival depends on the intensity and duration of heat stress, as they allow the estimation of the critical thermal maxima (CTmax) and thermal sensitivity using the thermal tolerance measurements obtained at different stress temperatures (Rezende et al. 2014).Here, it is expected that fast-ramping selected lines will exhibit higher knockdown time at highly stressful temperatures and higher CTmax because fast-ramping protocols reduce the confounding effects (e.g., hardening, rate of resource use) on heat tolerance associated with the assay length (see Rezende et al. 2011;Santos et al. 2012;Mesas et al. 2021).In contrast, slow-ramping selected lines should exhibit higher desiccation and starvation resistance because individuals with higher starvation and desiccation resistance exhibit higher thermal tolerance during long assays.

Sampling and maintenance
D. subobscura females were collected in the spring 2014 at the Botanical Garden of the Universidad Austral de Chile (Valdivia, Chile; 39º 48' S, 73º 14' W) using plastic traps containing banana/yeast baits.Two hundred females were collected and placed individually in plastic vials containing David's killed-yeast Drosophila medium to establish isofemale lines.In the next generation, 100 isofemale lines were randomly selected, and 10 females and 10 males per line were placed in an acrylic cage to establish a large, outbred population.In the next generation, the flies from this cage were divided into three population cages (R1, R2, and R3), attempting to assign the same number of flies to each cage.After three generations, the flies in each replicate cage were divided into four population cages, trying to assign the same number of flies to each cage.This procedure established 12 population cages assigned to each artificial selection protocol in triplicate: fast-ramping selection, fast-ramping control, slow-ramping selection, and slow-ramping control lines (Fig. S1).During the selection experiments, population cages were maintained at 18 °C (12:12 light-dark cycle) in a discrete generation, controlled larval density regime (Castañeda et al. 2015).Each population cage had a population size of 1000-1500 breeding adults.

Heat tolerance selection
For each replicate line, 120 four-day-old virgin females were randomly mated with two males for two days, after which the females were individually placed in a capped 5-mL glass vial, and the males were discarded.The vials were attached to a plastic rack and immersed in a water tank with an initial temperature of 28 °C, controlled by a heating unit (model ED, Julabo Labortechnik, Seelbach, Germany).After an equilibration period of 10 min, the temperature was increased to 0.08 ºC min -1 for the slow-ramping selection protocol or 0.4 ºC min -1 for the fast-ramping selection protocol.Assays were stopped when all flies collapsed.Each assay was recorded using a high-resolution camera (model D5100, Nikon, Tokyo, Japan) and then visualized to score the knockdown temperature for each fly, defined as the temperature at which each fly ceased to move.Flies were ranked by knockdown temperature, and four virgin females were selected from the progeny of the 40 flies with the highest knockdown temperature (top 30% of each assay) to establish the next generation.For the fast and slow control lines, the knockdown temperature was measured as described above, but the progeny was randomly selected to establish the next generation, regardless of the knockdown temperature of their mother.This artificial selection experiment was performed for 16 generations, after which flies from each selection treatment were placed in separate acrylic cages and maintained without selection (e.g., relaxed selection) at 18 °C and a 12:12 light-dark cycle.

Knockdown time in static assays
Eggs were collected from each population cage and transferred to vials at a density of 40 eggs/vial.At 4 days of age, ten females and ten males from each population cage were tested to measure their heat knockdown time at four different static temperatures: 35, 36, 37, and 38°C.This experimental design allowed the measurement of 960 flies (10 flies ´ 2 sexes ´ 4 static temperatures ´ 4 selection treatments ´ 3 replicated lines).
Static assays were performed similarly to knockdown temperature assays, but static temperatures were used instead of ramping temperatures.A total of 240 flies were measured for each static temperature, except for the assay at 35°C (178 flies) because two flies died before the start of the assay, and a video file of one assay was corrupted (data for 60 flies were lost).For the 37°C assay, four flies died before the assay began, and the collapse time could not be measured for six flies.Finally, for the 38ºC assay, three flies died before the start of the assay and the collapse time could not be measured for five flies.Heat knockdown assays were performed in generation 23 (Fig. S1).

Desiccation and starvation resistance
Eggs from each replicate cage were collected and maintained in vials at a density of 40 eggs/vial.Only fast control lines were measured as control lines.This decision was based on logistical reasons (i.e., the high number of vials) and statistical support because fast and slow control lines did not differ in their knockdown times and CTmax values (see the Results section).
For desiccation resistance assays, five flies from each sex were separately placed in a vial containing five desiccant droplets (Drierite) and sealed with parafilm (flies had no access to food or water during the assay).For starvation resistance assays, five flies from each sex were separately placed in a vial containing agar only (flies had access to water but no food).For both desiccation and starvation resistance assays, the number of live flies was counted every 3 h until all the flies were dead.Desiccation and starvation resistance were measured in 126 vials containing 10 flies each, respectively (7 vials ´ 2 sexes ´ 3 selection treatments ´ 3 replicate lines).These experiments were conducted at 18 °C using flies from generation 24 (Fig. S1).

Statistical analysis
Normality and homoscedasticity were tested for all variables, and the knockdown times were squared root transformed to meet the parametric assumptions.All analyses were performed with R software (R Development Core Team 2011).

Heat tolerance
For the knockdown temperature, control and selection lines were compared separately for the fast-and slow-ramping selection because it is well known that the knockdown temperature is higher in fast-ramping than in slow-ramping assays (Chown et al. 2009; see Mesas et al. 2021).For the knockdown time analysis, a mixed linear model with ramping selection (fixed effect with fast-control, slow-control, fast-selection, and slowselection lines as levels), sex (fixed effect with females and males as levels), and replicate lines nested within the thermal selection (random effect with replicates 1, 2 and 3 as levels) was performed using the library lme4 package for R (Bates et al. 2015).
Fixed effects were tested by a type III ANOVA and the random effect was tested by a likelihood ratio test comparing the model with and without the replicate lines.Both tests were performed using the library lmerTest package for R (Kuznetsova et al. 2017).If the selection effect was significant, a posteriori comparisons were performed using false discovery rate adjustment implemented in the emmeans package for R (Lenth et al. 2018).
Knockdown times were also used to plot the survival curves based on the Kaplan-Meier formula using the survfit function implemented in the survival package for R (Therneau 2023).

Thermal death time curves (TDT)
Average knockdown times were calculated for each sex, replicate lines, and selection treatment combination (Table S1).These values were regressed against the assay temperatures according to Equation 1 (Rezende et al. 2014): , where T is the assay static temperature (ºC), CTmax is the upper thermal limit (ºC), t is the knockdown time (min), and z is the thermal sensitivity.These curves allowed the estimation of CTmax as the extrapolated temperature that would result in a knockdown time of log10 t = 0 (i.e., knockdown time at 1 min) and the estimation of the thermal sensitivity (z = -1/slope), where the lower z values, the higher the thermal sensitivity.
Using equation 1, 24 TDT curves (2 sexes ´ 3 replicate lines ´ 4 selection protocols) were fitted, from which CTmax and z values were estimated as described above.A linear model with ramping selection treatment (levels: fast-control, slowcontrol, fast-selection, and slow-selection lines), sex (levels: females and males), and their interaction was performed to evaluate their effects on CTmax and z values.TDT curve analysis did not include replicate lines as a random effect because only one CTmax and z value was estimated by each replicate line.Additionally, a mixed linear mixed model with ramping selection (fixed effect with fast-control, slow-control, fastselection, and slow-selection lines as levels), sex (fixed effect with females and males as levels), and replicate lines nested within the thermal selection (random effect with replicates 1, 2 and 3 as levels), and assay temperatures (as covariate) was fitted on the knockdown time using the lmer package for R.

Desiccation and starvation resistance
To determine the lethal time at which 50% of flies of each vial were dead (LT50), a generalized linear model following a binomial distribution was fitted with the proportion of flies alive as the dependent variable and time as the predictor variable.
The generalized linear model was run using the glm function of the lme4 package for R (Bates et al. 2015).The LT50 of each vial was then estimated using the function dose.p from the MASS package for R (Venables and Ripley 2002).
To estimate the median LT50 and the 95% confidence intervals for each selection treatment and sex, each LT50 was transformed into a survival object using the Surv and survfit functions of the survival package for R (Therneau 2023).This procedure also allowed to estimate the survival curves in each vial.Finally, to test the effect of selection treatment (levels: control, fast-selection, and slow-selection lines) and sex (levels: females and males) on desiccation and starvation resistance, a Cox proportional regression model was fitted with LT50 as the dependent variable, and selection protocol and sex as predictor variables.The Cox model was run using the coxph function of the survival package (Therneau 2023).

Knockdown time evolution
As expected, the knockdown time decreased significantly as the assay temperatures increased (F1,877 = 649.1,P < 2´10 -16 ).The mean knockdown time and 95% CI for each Knockdown times differed significantly between selection treatments when flies were assayed at 36 and 37ºC (Table 1; Table S2; Fig. 1).At these temperatures, slow and fast selected lines showed higher heat tolerance than slow and fast control lines (Table S1-S3; Fig. 1C, E).Also, fast-selected lines showed a higher heat tolerance than slow-selected lines in flies assayed at 37ºC but not at 36ºC (Table S1-S3; Fig. 1C, E), whereas fast and slow control lines did not differ (Table S3; Fig 1).On the other hand, replicate lines had no significant effect on knockdown time, indicating consistent evolutionary responses within each selection and control treatment (Table S2).
Concerning sex, females showed a higher thermal tolerance than males but only when flies were assayed at 35 and 38ºC (Table 1; Fig. 1B, H).Finally, non-significant interactions between selection and sex were found for all assay temperatures (Table 1).

Desiccation resistance evolution
Survival analysis showed a significant effect of sex and selection treatment on desiccation resistance, but not for the interaction between selection treatments and sexof the two effects on desiccation resistance (LTR: c 2 5 = 83.55,P < 2´10 -16 Table S5).
Males showed a higher risk of desiccation than female flies (hazard ratio = 7.11, P < 2´10 -7 ; Fig. 3).Females showed a significant difference between selected and control lines (LTR: c 2 2 = 6.72,P = 0.03; Fig. 3A).Specifically, females of the slow-ramping selection lines showed a higher desiccation resistance than females of the control lines (hHazard ratio = 0.42, P = 0.009), whereas females of the fast-ramping selection and control lines showed similar desiccation risk (hazard ratio = 0.56, P = 0.072).On the other hand, males showed no differences in desiccation resistance between selected and control lines (LTR: c 2 2 = 1.88,P = 0.4; Fig. 3B).The desiccation survival analysis results testing the effect of selection protocol, sex, and their interaction are reported in the Table S5.

Starvation resistance evolution
A significant effect of sex, selection treatment, and the interaction between the two effects on starvation resistance was found in the survival analysis Survival analysis showed a significant interaction between selection treatments and sex on desiccation resistance (LTR5 = 94.89,P < 2´10 -16 Table S6).Males had a higher risk of starvation than female flies (hazard ratio = 22.75, P < 1´10 -16 ; Fig. 4).In female flies (Fig. 4A), fast-ramping selection and slow-ramping selection lines showed a higher starvation risk than control lines (hazard ratio = 2.37, P = 0.009; and hazard ratio = 2.20, P = 0.014, respectively).In contrast, male flies had an opposite pattern (Fig. 4B): slow-ramping selection lines had a lower starvation risk than control lines (hazard ratio = 0.50, P = 0.03), but nonsignificant differences were found between fast-ramping selection and control lines (hazard ratio = 0.64, P = 0.16).The starvation survival analysis results testing the effect of selection protocol, sex, and their interaction are reported in Table S6.

Discussion
Studying the evolutionary responses of thermal limits is key to understanding the adaptive responses and evolutionary constraints to global warming.Cross-tolerance studies can then provide valuable information on the evolutionary response to multiple environmental stressors.Cross-tolerance evolution has been reported among different resistance traits (Hoffmann and Parsons 1993;Bubliy and Loeschcke 2005;Stazione et al. 2020;Singh et al. 2022), but the magnitude of the evolutionary response could be explained by the trait under direct selection or the stress intensity (Gerken et al. 2016).
Here, artificial selection for heat tolerance (i.e., knockdown temperature) resulted in correlated responses in heat knockdown time, the thermal tolerance landscape (TDT curves), desiccation resistance, and starvation resistance.However, these responses depended on the intensity of thermal selection and sex, suggesting that the evolutionary response to tolerate higher temperatures also confers partial tolerance to other stresses such as desiccation and starvation.
Different approaches to measuring the upper thermal limit of ectotherms produce different genetic and phenotypic estimates.Fast-ramping assays generally estimate higher upper thermal limits and higher heritabilities than slow-rampingslow ramping assays (Chown et al. 2009;Rezende et al. 2011).For instance, the heritability of thermal tolerance was 0.13 for fast assays and 0.08 for slow assays in D. subobscura (Castañeda et al. 2019).Because heritability is commonly used as a predictor of the evolutionary response of a trait to natural or artificial selection, the evolutionary response of heat tolerance would be expected to depend on the ramping rate used during selection.However, previous work did not support this prediction for D. subobscura, finding that the evolution of heat tolerance was independent of the ramping rate (Mesas et al. 2021), but the correlated responses of the thermal performance curves or the energy metabolism depended on the intensity of the thermal selection (Mesas et al. 2021;Mesas and Castañeda 2023).In the present study, the evolution of knockdown temperature (e.g., heat tolerance measured in dynamic assays) induced a correlated response on the heat knockdown time (e.g., heat tolerance measured in static assays) when it was assayed at intermediate temperatures (36 and 37ºC), but not at less or more extreme assay temperatures (35 and 38ºC).These findings can be explained because stress tolerance at 35ºC should depend on the physiological state of the organism during prolonged thermal assays (e.g., availability of energy resources; see Rezende et al. 2011, but also see Overgaard et al. 2012) and not only on heat tolerance, whereas heat tolerance at 38ºC could be limited by physical properties of ectotherms (e.g., protein denaturation, membrane permeability).However, a previous study found a clinal pattern for heat tolerance in D. subobscura only for flies assayed in static assays (specifically at 38ºC), but this clinal pattern was not detected using ramping assays (Castañeda et al. 2015).Differences between these two studies could be explained by the number of generations under thermal selection, which could result in a different evolutionary response of heat tolerance.According to Begon (1976), D. subobscura can have between 4 and 6 generations per year, which makes it possible to estimate about 125 generations of selection from the introduction of D. subobcura in Chile until the study by Castañeda et al. (2015).On the other hand, the type of selection is completely different between the two studies (e.g., natural versus artificial selection), which could lead to various evolutionary outcomes.In any case, beyond these results from specific thermal assays, these findings support the idea that (1) the use of a single static temperature would miss genetic or phenotypic effects on heat tolerance, and (2) unifying several knockdown time estimates into a single approach (TDT curves) should be necessary to elucidate genetic and phenotypic patterns of heat tolerance in ectotherms (Rezende et al. 2014;Jørgensen et al. 2021).
TDT curves evolved in response to heat tolerance selection in D. subobscura.
TDT curves showed that fast-and slow-ramping selected lines evolved higher CTmax than control lines (DCTmax = 0.49 ºC).This differential CTmax value is slightly lower than the population differences (0.9ºC) observed between the lowest and highest latitude populations (~8 latitudinal degrees) of D. subobscura studied by Castañeda et al. (2015) and even lower than the CTmax variation reported among Drosophila species (Jørgensen et al. 2019;Alruiz et al. 2022).On the other hand, although CTmax and z (i.e., thermal sensitivity) are phenotypically correlated (see Castañeda et al. 2015;Molina et al. 2023), the evolutionary increase in CTmax was not associated with a correlated response in thermal sensitivity (z).This result suggests that both thermal parameters are not genetically constrained, but further evidence from quantitative genetic studies is needed to assess the genetic association between CTmax and z.A caveat for this finding could be related to the fact that thermal selection for heat tolerance was carried out over 16 generations, followed by 7 generations of relaxed selection (i.e., no selection).However, previous evidence suggests that differences in heat tolerance between control and selected lines were consistent between generations 16 and 25 (Mesas et al. 2021).Indeed, Passananti et al. (2004) also reported that phenotypic values did not change after 35 generations of relaxed selection in desiccation-selected populations of D.

melanogaster.
It was expected that flies selected for higher heat tolerance using slow-ramping rate protocols would exhibit greater desiccation and starvation resistance than flies selected using fast-ramping selection protocols.This is because flies assayed for heat tolerance in long assays are also exposed to desiccation and starvation stress (Santos et al. 2012) .This study provides partial support for this hypothesis.First, slow-ramping selected lines evolved a higher desiccation resistance than control and fast-ramping selected lines.However, this was only observed in female flies, while males of the different selection treatments did not show any difference in desiccation resistance.On the other hand, starvation resistance evolved in opposite directions depending on sex: females of the fast-ramping and slow-ramping selected lines showed lower starvation resistance than females of the control lines, whereas males of the slow-ramping selected lines showed higher starvation resistance than males of the control and fast-ramping selected lines.Differential evolutionary responses between the sexes could be due to heat thermal selection only being applied to females, which could have exacerbated the evolutionary responses of female flies.However, previous studies that artificially selected exaggerated male traits also found fitness consequences in females (Harano et al. 2010).Differential evolutionary responses between females and males can then be explained by sexually antagonistic selection on genetically correlated traits (Eyer et al. 2019;Fanara et al. 2023).Kwan et al. (2008) reported that desiccation-selected females had higher desiccation resistance than desiccation-selected males (see also Chippindale et al. 2004), which can be explained by males using resources at a faster rate than females (e.g., males lose weight, water, and metabolites faster than females).Sexual dimorphism in stress resistance traits has been mainly explained by differences in cuticular composition, resource storage, and energy conservation between the sexes (Schwasinger-Schmidt et al. 2012;Rusuwa et al. 2022).Although energy content was not measured here, Mesas and Castañeda (2023) found that body mass and metabolic rate were similar between control and heat-tolerance selected lines of D. subobscura, suggesting that neither resource storage nor energy conservation explains the sexdependent correlated response for stress resistance traits.However, the same study found that heat-tolerance selected lines had higher fecundity than control lines, whereas previous studies have found negative associations between fecundity and starvation resistance in D. melanogaster (Bubliy and Loeschcke 2005;Kalra et al. 2017).Then, the decrease in starvation resistance in females of the heat-selected lines could be related to increased fecundity, which is consistent with the reported trade-off between stress resistance traits and life-history traits (van Noordwijk and de Jong 1986;Rion and Kawecki 2007).
In conclusion, the present study shows that heat tolerance evolution is associated with evolutionary responses in other stress resistance traits, which could be explained by pleiotropic effects or linkage disequilibrium among the traits evaluated.However, further evidence (e.g., quantitative genetic or genome-wide analysis studies) is needed to elucidate the genetic basis of the cross-tolerance evolution in D. subobscura.In addition, this study provides evidence for rapid evolutionary responses in ectotherms mediated by thermal selection, but the evolutionary outcomes depend on the intensity of the thermal stress (Mesas and Castañeda 2023) and sex (Rogell et al. 2014;Rusuwa et al. 2022).This study also highlights the importance of D. subobscura as a suitable model to study thermal adaptation mediated by natural selection (Huey 2000;Gilchrist et al. 2008;Castañeda et al. 2013Castañeda et al. , 2015)), and laboratory selection (Santos et al. 2005, Santos et al. 2021;Simões et al. 2017;Mesas et al. 2021;Mesas and Castañeda 2023).
In addition, this study highlights the relevance of experimental evolutionary studies for understanding the adaptive responses to climate change (Mitchell and Whitney 2018;Brennan et al. 2022;Kelly 2022).Finally, these results suggest that ectotherms may evolve in response to climate warming, but evolutionary responses may differ between sexes and/or the warming rates experienced by natural populations, which may make it difficult to propose general trends in the fate of ectotherms in a changing world where temperature is not the only driver of climate change, but species are also expected to be exposed to changes in precipitation patterns and food availability.

Table 1 .
Mixed linear effect model for the knockdown time of Drosophila subobscura assayed at four static temperature assays.For simplicity, results for the random effect (replicate lines) are not shown because they were not statistically significant (see