EUROPEAN JOURNAL OF ENTOMOLOGYENTOMOLOGY ISSN (online): 1802-8829 Eur. J. Entomol. 113: 104–112, 2016 http://www.eje.cz doi: 10.14411/eje.2016.013 ORIGINAL ARTICLE

Climate-induced changes in the phenotypic plasticity of the , athalia (: )

EDIT JUHÁSZ 1, ZSOLT VÉGVÁRI 2, JÁNOS P. TÓTH 3, KATALIN PECSENYE 1 and ZOLTÁN VARGA1

1 Department of Evolutionary Zoology and Human Biology, University of Debrecen, Egyetem tér 1, Debrecen 4032, Hungary; e-mails: [email protected], [email protected], [email protected] 2 Department of Conservation Zoology, Hortobágy National Park Directorate, University of Debrecen, Sumen u. 2, Debrecen 4024, Hungary; e-mail: [email protected] 3 MTA-DE “Lendület” Behavioural Ecology Research Group, Department of Evolutionary Zoology, University of Debrecen, Egyetem tér 1, Debrecen 4032, Hungary; e-mail: [email protected]

Key words. Lepidoptera, Nymphalidae, Melitaea athalia, butterfl y, Carpathian Basin, morphology, Procrustes anova

Abstract. Recently a large number of studies have reported an increase in the variability in the climate, which affects behavioural and physiological adaptations in a broad range of organisms. Specifi cally, may be especially sensitive to climatic fl uctua- tions, as their physiology and life history traits, like those of other ectotherms, are predominantly affected by environmental factors. Here we aimed to investigate climate-induced changes in several morphometric measures of the Heath Fritillary in North-Eastern Hungary, which is a highly diverse transitional area. During this study we tested the following hypotheses: (i) climate affects genitalia and body size to various degrees (ii) increasing variability in climate induces higher levels of fl uctuating asymmetry and variance in all morphological characters. To our knowledge, this study is the fi rst to analyse simultaneously wing size and structure of genitalia of a butterfl y in response to variability in climate. Our fi ndings suggest that wing and genital traits may exhibit similar degrees of stability in response to a more variable climate, although the response in terms of forewing size differs from that of other body measurements and the structure of the genitalia. These fi ndings suggest that global climate change may affect lepidopteran body metrics over longer periods of time. Our fi ndings parallel the results of investigations showing that morphology might be modifi ed by environmental changes, which is especially the case for those body parts that are phenotypically very variable. However, we found no evidence that increasing variability in climate would induce higher levels of fl uctuating asymmetry and greater variability in morphological characters.

INTRODUCTION Characteristics of butterfl y wings are widely used as Evidence is accumulating that most habitat loss, frag- model system for studying development or phenotypic mentation and long-term changes in climate can be attrib- plasticity (Dennis & Shreeve, 1989; Berwaerts et al., 1998; uted to anthropogenic factors (Bellard et al., 2012; Man- Hill et al., 1999; Thomas & Van Dyck, 2006; Talloen et tyka-Pringle et al., 2012). It is of particular interest to know al., 2009; Gibbs et al., 2011). For example, coloration and how different organisms react to changes in climate and patterns on the wings of some of butterfl ies are weather over long periods of time, especially in terms of known to be very variable and show high levels of pheno- their phenology and morphological adaptations. Specifi - typic plasticity in response to different environmental fac- cally, insects may be especially sensitive to fl uctuations in tors (Shapiro, 1976; Brakefi eld et al., 1996; Brakefi eld & climate, as their physiology and life history traits are pre- French, 1999; Talloen et al., 2009) or food quality (Kooi dominantly affected by environmental factors as are those et al., 1996). Specifi cally, human-induced habitat frag- of other small ectotherms (Bale et al., 2002; Wilson et al., mentation has been shown to drive morphological modi- 2007). Thus, variation in food availability, predation pres- fi cations (Berwaerts et al., 1998). Furthermore, results of sure, temperature, length of the season, photoperiod and experimental studies support the hypothesis that changes humidity can affect the responses of organisms (Hughes et in climate drive morphological characters (Gibbs et al., al., 2003, 2007; Karlsson & Van Dyck, 2005). Heterogene- 2011): Xi et al. (2015) indicate that temperature increase ous environments provide opportunities for exploring the per se and its interaction with the direction of temperature role and limits of natural selection in shaping the response change should be primarily responsible for shifts in body of organisms to environmental change (Pigliucci, 2001). size at different times of the year. Therefore, seasonal pat- terns in temperature in temperate regions could be of gen-

Final formatted article © Institute of Entomology, Biology Centre, Czech Academy of Sciences, České Budějovice. An Open Access article distributed under the Creative Commons (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).

104 Juhász et al., Eur. J. Entomol. 113: 104–112, 2016 doi: 10.14411/eje.2016.013 eral importance for predicting changes in body size strained genetic control than body metrics, therefore we in respone to a warmer climate. In contrast, insect genital expect that changes in temperature will affect genitalia and characteristics differ greatly, even between sibling species, body measurements differently. Thirdly, we aim to test the and seem to be only slightly affected by environmental fac- hypothesis that with increase in climatic variability there tors (Cesaroni et al., 1994; Dapporto et al., 2009, 2011). is an increase in fl uctuating asymmetry and variance in all As a result of environmental perturbations, self-regu- morphological characters (Joubert & Bijlsma, 2010). latory mechanisms might be unable to stabilize develop- MATERIALS AND METHODS ment (Van Valen, 1962; Palmer & Strobeck, 1986, 1992). Fluctuating asymmetry, which consists of small random Climate data differences between left and right sides in bilaterally sym- We obtained meteorological data for 1967–2013 from the near- metrical structures of organisms, is a widely used meas- est meteorological station at Miskolc (48.1°N, 20.4°E), which is ure of developmental instability (Van Valen, 1962; Palmer, 60 km from the study site, and the only station for which there 1997). However, there is growing evidence from both ex- is long-term dataset necessary for determining trends in climate perimental and non-experimental studies that fl uctuating (Végvári et al., 2014). To assess temporal patterns in climatic pre- dictors relevant for larval development of the species studied, we asymmetry does not consistently predict stress or fi tness calculated (i) mean temperatures in March, April and May (ii) (Lens et al., 2002; Silva et al., 2009). temperature averaged across March to April and March to May Owing to their highly variable morphometric character- (iii) mean seasonal temperatures (iv) precipitation sums for the istics, members of the Melitaea (Lepidoptera: Nym- above periods, which is when the larvae are feeding. To calculate phalidae) provide opportunities for studying the effects of the same metrics for the pre-diapausal and diapausal periods, we climate change and variability on lepidopteran morpholo- repeated these analyses for July and August to February, respec- gy. In addition, butterfl ies are particularly well represented tively (Pöyry et al., 2011). Monthly and seasonal means of cli- in museum collections, thus morphometric studies can also matic proxies are widely used in insect studies (Altermatt, 2010a; be carried out on both wings and external genitalia of a Gibbs et al., 2011; Mega, 2014). Although climatic parameters may fl uctuate strongly within a month, we were interested in the number of lepidopterans using historical data. effects of the overall trend in climate. To detect temporal trends In the present study, we aim to investigate the effects of in weather proxies, we fi tted linear regressions to these variables changes in climate on the (i) wing size and (ii) genital char- as a function of years. acteristics of the Heath Fritillary butterfl y – Melitaea ath- Sample collection alia (Rottemburg, 1775), which is a threatened species in In total, 228 male individuals were analyzed all of which were Western Europe but not yet endangered in the eastern part captured in the Jósvafő area of the Aggtelek Karst region, East- of the continent (Van Swaay & Warren, 1999; Van Swaay Hungary. Specimens were collected between 1967–2013 only in et al., 2010). For example, this species is a priority species May and June and stored in the collection of the University of De- for butterfl y conservation in England, where its phenology brecen (Table 1). As only male individuals were available in suffi - and population structure have been studied in detail (War- ciently large numbers to carry out the analyses and morphometric ren, 1987a, b, c, 1991; Hodgson et al., 2009). In contrast, traits (measure and shape) showed marked sexual dimorphism, this species occurs in an astonishing variety of ecological we used only the data for male specimens. Further, to increase the situations in Hungary. The main object of the present work robustness of our results, we removed records for years when less is to determine whether climate-induced changes occur than four individuals were caught. in several morphometric measures of this butterfl y in the Aggtelek Karst area, which is a highly diverse transitional area where continental, mountain and Mediterranean spe- Table 1. Numbers of specimens caught each year that were used cies co-occur within a limited area (Varga, 1997). In addi- in the morphometric analyses. tion, this region has long been considered an important site Number of specimens for Number of specimens for Year for entomological studies (Varga & Szabó, 1997; Nagy et wing measurements genitalia measurements al., 1999; Pecsenye et al., 2007; Árnyas et al., 2009; Berec- 1967 22 24 zki et al., 2011; Bátori et al., 2012a, b), including some on 1975 7 15 the effect of climate change (Végvári et al., 2014). In our 1976 5 8 analyses we primarily focused on the relationships between 1981 16 10 climatic predictors and morphological traits. We choose 1983 – 1 this approach as relationships between temporal trends in 1984 – 2 environmental predictors and their effects on morphologi- 1986 1 2 cal metrics is rather complex (Parmesan & Yohe, 2003) 1988 5 6 and the absence of temporal trends in morphological traits 1999 22 25 does not exclude interrelationships between morphometry 2000 12 12 and climatic proxies. 2001 15 26 Our study is based on the following hypotheses. Firstly, 2007 14 24 high temperatures induce longer larval feeding periods, 2008 21 44 which results in larger body metrics. Secondly, theory 2011 14 15 predicts that genitalia measurements are under more con- 2012 13 14

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Fig. 1. Features measured on wings and genitalia. Black dots illustrate the two sliding landmarks on the forewing. A – wing; B – external genitalia; C – aedeagus.

Geometric morphometry Morphometric characteristics of wings and genitalia were cho- Male wings were fi xed on transparent fi lms and digitalised sen from a large set of characters for which the measurement er- using Canon CanoScreen 5200F scanner. Landmark-based geo- rors were estimated using a series of hierarchical ANOVA. The metric morphometric analyses were used to quantify the variation measurement errors of the characters used in this study accounted in the shape of wing and reveal any asymmetry. Accordingly, we for less than 10% of the total variance. recorded 14 landmarks on the forewing and 12 on the hindwing at All measurements were repeated three times on each individual characteristic meeting points of veins (Fig. 1A). Landmark points to control for measurement error. were assigned as interception points of the veins with insignifi - Statistical analyses cant topological variability, following the recommendations of In the fi rst step, we used Procrustes generalized least squares Sanzana et al. (2013) and Bereczki et al. (2014). (ProcGLS) to determine the shape of both fore- and hindwings The preparation procedure of male external genitalia was car- and male genitalia. Procrustes transformation aims to rescale co- ried out based on (Bátori, 2012b). Slides were digitalised using an ordinates to unit centroid size and rotate in order to minimize the Olympus C-4000 Zoom camera and a Canon stereomicroscope. sum of squared distances among corresponding landmarks. In the Landmark-based geometric morphometric analyses were used case of forewings we included two sliding landmarks to control to quantify the variation in the shape of processus posterior on for position variance of these unfi xed reference points, as indi- the valvae. We recorded 6 landmarks at the tips and origin of the cated by Fig. 1A (Adams & Otárola-Castillo, 2013). main processi (Fig. 1B). In both cases (wing and external geni- To assess measurement error, the data was subjected to Pro- talia) TpsDig 2.1 was used to digitalise landmarks (Zelditch et crustes ANOVA (Klingenberg & McIntyre, 1998), which indicate al., 2012). signifi cantly lower levels of measurement error (< 3.0% on aver- In the following analyses shape and size variables were treated age) than differences between individuals, and between left and as dependent metrics and calculated across individuals grouped right sides of individuals (p < 0.0001) (White & Searle, 2008). by year-of-catch: (i) degree of bilateral asymmetry of both wings In the following step we assessed the effect of climatic vari- and processus posterior by retrieving the Goodall’s F-statistic ables on all morphometric variables by formulating Procrustes provided by the component of fl uctuating asymmetry as a result full Linear Mixed Models (LMM) including all climate proxies of Procrustes ANOVA fi tted on shape variation (ii) centroid size added as fi xed factors and individual ID as a random factor. of both wings and processus posterior calculated by using Pro- After model fi tting, the relative importance of environmental crustes-transformed coordinates (iii) aedeagus length (henceforth variables was determined using an information-theoretic model- morphometric variables). For geometric morphometry we apply comparison, which provides robust measures of climatic respon- the frequently used centroid size, which is defi ned as the square siveness in in terms of body metrics independent of sample size root of the summed squared distances of each landmark to the and is thus a robust estimate of the importance of predictors un- centroid. biased by the signifi cance levels of a large number of covariates Traditional morphometry (Burnham & Anderson, 2002). This approach, therefore, excludes Traditional morphometry was used to detect changes in the the possibility of signifi cant relationships emerging from a large length of the aedeagus (Fig. 1C). Length of the aedeagus was set of predictors, since the importance of each predictor is de- measured using the Image J 1.36 program (Kizic & Borovac, termined by a subset of models with substantial support, based 2001). on their information content (Burnham & Anderson, 2002). The model selection procedure was as follows. First we obtained

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Table 2. Temporal trends in the climatic variables measured based on linear regressions as a function of years. Signifi cant relationships (p < 0.05) are indicated in bold. Climatic predictor Parameter estimate Adjusted R2 p Temperature mean March 4.0126 0.0593 0.0706 April 3.7312 0.1548 0.0058 May 2.2243 0.0434 0.0985 May to April 1.1768 0.0050 0.3771 March to April 5.5894 0.1961 0.0019 March to May 5.5894 0.1961 0.0019 July 2.2841 0.0511 0.0872 August to February 1.2370 0.0072 0.2190 Precipitation totals March 0.0055 0.0277 0.9613 April 0.1094 0.0186 0.1975 May –0.0010 –0.0270 0.9846 Complete life cycle (previous May to April) –0.0185 0.3914 < 0.0001 March to April –0.0169 0.3277 < 0.0001 March to May –0.0169 0.3277 < 0.0001 July 0.1770 0.0223 0.1218 August to February –0.0114 0.0212 0.8991 the values of Akaike’s information criterion corrected for small autumn and winter climatic variables, and those recorded sample size (AICc ) and the corresponding Akaike weight of each over the pre-diapausal and diapausal periods. model (ω). Second, we selected models with substantial support (Δ = AIC – AIC < 2.0) and calculated model-averaged param- Effects of changes in climate on the morphology i i min of wings and genitalia eter estimates (β) and unconditional standard errors (SEu; Burn- ham & Anderson, 2002) of each variable using the sums of their In the case of the relationship between forewing centroid Akaike weights across all the models containing the given predic- size and April mean temperature: forewing size increased tor that had substantial support. Akaike differences in the range with temperature (β = 16.446 ± 2.033, Table 3, Fig. 2, Ap- 0–2 indicate a substantial level of empirical support for a given pendix 1). In contrast, there was no correlation between model, whereas Δ > 7 implies very weak support (Burnham & i hindwing centroid size and processus posterior, and cli- Anderson, 2002). All statistical analyses were carried out in the R statistical matic predictors in the best supported models fi tted to both programming environment (R Development Core Team, 2013), these metrics. Similarly, aedeagus length was not associ- using the specifi c packages “geomorph” (Adams & Otárola-Cas- ated with any of the climatic variables. tillo, 2013), “shapes” (Dryden, 2007), “MuMIn” (Barton, 2011) Fluctuating asymmetry of both wing measurements and and “nlme” (Pinheiro et al., 2010). processus posterior was not associated with any of the cli- matic predictors measured as none of these climatic pre- RESULTS dictors were supported variables. In addition, there was no Climatic patterns correlation between the body metrics measured and climat- First we investigated the temporal trends in the predic- ic parameters recorded in the pre-diapausal and diapausal tors of climate change. Spring temperatures increased in all periods (Table 3, Appendix 1). periods: there were signifi cant positive temporal trends in DISCUSSION the mean temperatures of April, March to April and March to May (b = 3.731, p = 0.0058; b = 5.589, p = 0.002; b = Our study provides two main fi ndings. First, wing and 5.589, p = 0.002, respectively, Table 2). Signifi cant nega- genital traits exhibit similar degrees of stability in response tive temporal trends were recorded in the sum of the pre- to variations in climate, although with contrasting patterns cipitation from March to May (b = –0.161, p < 0.0001, between forewing size and other body measurements and Table 2). There were no clear temporal trends in summer, variation in genitalia. Second, our results suggest that glob-

Table 3. Model-averaged parameters calculated across best supported models fi tted to centroid size of forewing. Variable β SEu Adjusted SE Lower CI Upper CI Intercept 994.014 154.199 155.451 691.295 1296.733 Temperature means March –18.131 21.697 21.724 –60.710 24.449 April 16.446 8.621 8.645 9.133 51.030 March to April –1.322 28.605 28.645 –57.466 54.821 Cumulative temperature (March to April) 0.341 0.275 0.276 –0.200 0.881

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in climate are still unknown, further studies on the cascad- ing effects of climatic processes on trophic networks are needed (García-Barros, 2000). Due to this complexity the relationships between tempo- ral trends in climatic predictors and their effects on mor- phometry is not straightforward (Parmesan & Yohe, 2003). This might account for why we did not record temporal trends in various morphological traits that are known to be affected by changes in climate. The greater degree of plasticity in the size of the fore- wing than of the hindwing in response to changes in tem- perature is in line with the results of an experimental study that indicates the asymmetric resistance to aerodynamic twisting of the broad forewings of butterfl ies is a conse- quence of the curved section of the leading edge (Wootton, 1993). Another investigation indicates that hindwings are not necessary for fl ight but essential for the execution of evasive fl ight in butterfl ies (Jantzen & Eisner, 2008). Thus, the asymmetrical aerodynamic behaviour of the fore- and hindwings might require different allocations of a re- Fig. 2. Centroid size of forewing as a function of April mean tem- source, as these organs compete for a haemolymph-borne perature. resource, such as a nutrient or growth factor (Klingenberg & Nijhout, 1998). al changes in climate may affect lepidopteran body metrics Our fi nding that forewing size was associated with the over longer periods of time. temperatures during larval development in spring indicates Our study is in accordance with others in indicating that that environmental conditions experienced by caterpillars insect morphology might be modifi ed by environmental can affect adult morphology. Indeed, recent studies have changes, especially in terms of an increased variability shown that environmental conditions during a specifi c in phenotype (Dennis & Shreeve, 1989; Berwaerts, 1998; period in an individual’s life cycle are refl ected in fi tness Talloen et al., 2009; Gibbs et al., 2011). Indeed, the recent during the breeding season. For instance, a low availabil- work of Xi et al. (2015) support the hypothesis that there ity of food during the pre-hibernation period might result has been changes in morphology resulting from recent in reduced breeding success (Boggs, 2009; Harrison et changes in climate. However, the regional and taxonomic al., 2011). This result parallels that of a number of studies variance in the degree of climate-induced changes in body that demonstrate that for a large number of lepidopterans metrics is still not yet fully understood (Xi et al., 2015). warm springs accelerate larval development indirectly by Our fi nding that some characteristics of lepidopteran advancing food plant phenology (Altermatt, 2010b). As wings vary with the season and possibly with changes in the species studied is an oligophagous specialist feeding climate implies that they might be an important part of on plants that contain iridoid-glycosides, we assume that their adaptation to changes in their microclimates, which larval phenology of M. athalia is less constrained by the is confi rmed by a recent experimental study (Gibbs et al., responsiveness of its food plants to changes in climate than 2011). Changes in the shape and size of wings affect ther- lepidopterans that are more host specifi c (Warren, 1987a). moregulation in ectotherms (Willmer, 1991; De Keyser et However, as the effectiveness of insect digestion depends al., 2015). However, relationships between thermal prefer- on temporal changes in temperature (Bale et al., 2002), ences and body metrics are less clear in ectotherms than studies on food plant utilisation and nutrient cycle of host endotherms, as a recent study demonstrates that there is no specifi c species is required. evidence for Bergmann’s rule applying to insects (Shelo- Although the mechanisms underlying how the climatic mi, 2012). In contrast, increase in body size in lepidopter- conditions experienced early on in development can affect ans induced by high temperatures is predicted by various later stages of development are not fully understood, pos- hypotheses. Firstly, warmer and earlier springs may lead sible processes include phenotypic plasticity, microevolu- to the larvae spending more time feeding, which result in tionary processes and epigenetic modifi cations of morpho- increased forewing length (Mega, 2014). Secondly, larval logical traits (Scaven & Rafferty, 2013). More specifi cally, size might be indirectly affected by physical characteristics the variation in body size, growth rate and development of the food (Dennis, 1991; García-Barros, 2000). Specifi - time of dung fl ies remained the same after several genera- cally, warm springs might induce earlier and faster devel- tions of artifi cial selection for body size, indicating that the opment of food plants, which results in an early abundance largest fraction of the phenotypic variance is heritable or of food for the larvae, which thus grow larger. However, environmentally induced plasticity (Blanckerhorn et al., as the effects of seasonal changes in climate on larval de- 2009). Similarly, another experimental study shows that velopment via the effect on the food plants of the change morphological alterations might be linked to thermal con-

108 Juhász et al., Eur. J. Entomol. 113: 104–112, 2016 doi: 10.14411/eje.2016.013 ditions (Gibbs et al., 2011; Harper, 2011). Such a mecha- climate change research: direct effects of rising temperature on nism might account for the rapid changes in morphological insect herbivores. — Glob. Chang. Biol. 8: 1–16. characters in response to changes in climate recorded for BÁTORI E., PECSENYE K., BERECZKI J. & VARGA Z. 2012a: Patterns M. athalia in this study. of genetic and taxonomic differentiation in three Melitaea (subg. Mellicta) species (Lepidoptera, Nymphalidae, Nym- In contrast to forewing morphology, measurements of all phalinae). — J. Insect Conserv. 16: 647–656. other body parts, including hindwing, size of the proces- BÁTORI E., PECSENYE K., TÓTH J.P. & VARGA Z. 2012b: Patterns sus posterior and length of the aedeagus, were not associ- of genetic and morphometric differentiation in Melitaea (Mel- ated over the period of this study with any of the climatic licta) athalia (Lepidoptera: Nymphalidae). — Biol. J. Linn. predictors measured, probably because of their stricter Soc. 107: 398–413. genetic control (reviewed in e.g. Simmons, 2014). In ad- BARTON K. 2011: MuMIn: Multi-Model Inference. R Package Ver. dition, forewing dimensions are robust predictors of body 1.0.0. R Foundation for Statistical Computing, Vienna, http:// size (Miller, 1977; Noriyuki et al., 2010; Mega, 2014) and CRAN.R-project.org/package= MuMIn. are associated with changes in climate (Mega, 2014; Xi et BELLARD C., BERTELSMEIER C., LEADLEY P., THUILLER W. & COUR- CHAMP F. 2012: Impacts of climate change on the future of bio- al., 2015). diversity. — Ecol. Lett. 15: 365–377. Changes in climate did not affect fl uctuating asymme- BERECZKI J., TÓTH J.P., TÓTH A., BÁTORI E., PECSENYE K. & VARGA try and the variance in the morphology of both wings and Z. 2011: The genetic structure of phenologically differentiated genitalia. Our study did not reveal an increase in fl uctuat- Large Blue (Maculinea arion) populations (Lepidoptera: Ly- ing asymmetry with increase in the unfavourableness of caenidae) in the Carpathian Basin. — Eur. J. Entomol. 108: the environment. 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(eds): Phenotypic Plasticity of Insects: that microclimate has more direct effects on insect devel- Mechanisms and Consequences. Science Publishers, Enfi eld, opment than macroclimate. NH, pp. 369–422. In summary, our study highlights the importance of re- BOGGS C.L. 2009: Understanding insect life histories and senes- sponsiveness of various aspects wing morphology of a le- cence through a resource allocation lens. — Funct. Ecol. 23: 27–37. pi dopteran that is decreasing throughout Europe to chang- BRAKEFIELD P.M. & FRENCH V. 1999: Butterfl y wings: the evolu- es in climate, which might be important in determining its tion of development of colour patterns. — BioEssay 21: 391– ability to adapt to an acceleration in climate change. 401. BRAKEFIELD P.M., GATES J., KEYS D., KESBEKE F., WIJNGAARDEN P. ACKNOWLEDGEMENTS. 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Appendix 1. Table of full model selection of GLM-s fi tted to forewing centroid size as a function of climatic variables. Annual April mean March mean March–April March–April August–February July mean Model ID Intercept df logLik AICc ΔAICc weight precipitation temperature temperature mean temp. cumulative temp. mean temp. temperature 60 276893.45 10.118 –26.35 7.63 –24637.54 –196.58 8 –2960.13 5932.37 0 0.5721 124 287765.37 28.29 –2.75 –18.07 0.34 –24866.74 –527.39 9 –2959.73 5933.63 1.25 0.3058 28 282524.66 –36.29 25.12 –24451.46 –501.78 7 –2963.90 5937.89 5.52 0.0362 52 274728.47 14.20 –21.82 –25123.53 99.63 7 –2964.23 5938.54 6.16 0.0262 44 290577.93 30.36 –21.40 0.37 –24150.19 –949.08 7 –2963.84 5939.80 7.42 0.0140 64 272013.35 0.015 9.70 –20.64 10.46 –24347.86 –130.74 9 –2962.92 5940.00 7.62 0.0126 92 275363.68 17.20 –16.15 0.23 –24836.64 –48.07 8 –2964.25 5940.62 8.25 0.0093 108 235930.36 29.20 –29.62 –24092.87 1206.10 8 –2965.32 5940.72 8.35 0.0088 128 260075.76 0.001 27.20 –3.56 –16.32 0.32 –24096.01 240.70 10 –2962.57 5941.35 8.98 0.0064 116 265223.69 –35.68 25.73 0.04 –24953.18 404.39 8 –2964.68 5941.48 9.10 0.0060 56 272986.35 0.015 –30.00 27.28 –24929.76 82.28 8 –2966.67 5945.46 13.09 0.0008 48 270680.69 0.014 15.23 –14.86 –23944.81 –249.40 8 –2967.07 5946.27 13.89 0.0005 112 232489.42 0.022 22.40 –13.34 –24211.85 1396.09 9 –2967.44 5947.01 14.64 0.0004 32 252703.67 0.000 30.36 –21.40 0.37 –23691.66 355.63 8 –2966.81 5947.79 15.41 0.0003 120 291552.97 0.018 –30.04 26.60 –0.06 –25142.27 –566.37 9 –2967.30 5948.75 16.38 0.0002 76 262220.41 0.008 17.14 –13.55 0.18 –25635.24 826.34 7 –2967.30 5948.77 16.40 0.0002 96 261452.37 18.83 0.51 –24335.79 287.86 9 –2969.39 5948.87 16.50 0.0001 16 271433.33 0.032 15.45 –24253.50 –147.88 7 –2971.46 5953.00 20.62 0 12 263060.23 9.75 –25050.42 540.11 6 –2973.46 5954.97 22.60 0 58 273703.77 0.022 17.90 0.24 –24794.34 7 –2971.47 5955.06 22.69 0 80 255573.42 –13.34 –24814.08 731.74 8 –2974.39 5956.83 24.45 0 59 –21006.61 –21.62 –0.26 878.91 7 –2974.10 5958.29 25.92 0 122 274556.33 0.043 20.95 –24864.54 8 –2974.18 5958.45 26.08 0 123 –21457.38 4.79 900.15 8 –2976.62 5961.30 28.93 0 20 340179.25 0.045 20.33 –0.05 –27718.93 –1367.33 6 –2974.79 5961.70 29.32 0 84 328369.03 12.82 0.31 –26248.70 –1540.07 7 –2975.98 5962.05 29.67 0 40 286761.43 –0.006 –16.37 –26183.13 82.70 7 –2977.58 5965.24 32.87 0 51 –17187.04 721.89 6 –2979.61 5965.25 32.88 0 50 278267.08 0.010 –18.29 –0.32 –25218.79 6 –2977.10 5966.23 33.86 0 26 274098.93 0.06 –24825.89 6 –2980.64 5969.34 36.97 0 27 –14862.00 0.014 635.04 6 –2982.10 5972.26 39.88 0 36 318954.41 0.029 –0.27 –27233.03 –734.93 6 –2981.89 5973.86 41.49 0 104 272501.27 0.045 –0.05 8 –25747.51 461.89 8 –2950.14 5916.49 272501.27 0 100 299116.08 0.31 7 –27838.28 320.06 7 –2951.30 5916.76 299116.08 0 106 274344.35 30.35 0.37 7 –24843.91 7 –2951.47 5917.11 274344.35 0 62 271681.88 0.015 9.67 –20.65 8 –24614.86 8 –2950.55 5917.31 271681.89 0 63 –18902.32 0.015 9.70 –20.64 8 792.83 8 –2950.72 5917.65 –18902.32 0 91 –22400.17 17.20 –16.15 0.23 7 934.36 7 –2951.87 5917.90 –22400.17 0 90 276095.92 17.20 –16.14 0.23 7 –25012.46 7 –2951.88 5917.92 276095.92 0 42 263527.11 29.19 6 –23848.02 6 –2952.96 5918.04 263527.10 0 43 –11044.60 29.20 6 489.74 6 –2953.11 5918.33 –11044.60 0 107 –30322.75 30.36 0.37 7 1255.36 7 –2952.20 5918.56 –30322.75 0 126 277210.55 0.001 27.18 –3.57 0.32 9 –25106.67 9 –2950.20 5918.66 277210.55 0 114 282092.76 –35.67 0.04 7 –25567.66 7 –2952.30 5918.77 282092.76 0 127 –23703.63 0.001 27.20 –3.56 0.32 9 989.63 9 –2950.31 5918.88 –23703.63 0 115 –21605.69 –35.68 0.04 7 898.16 7 –2952.47 5919.11 –21605.69 0 4 299568.31 5 –27113.37 –10.14 5 –2954.88 5919.84 299568.31 0 24 332370.47 –0.006 –16.36 7 –27850.74 –996.62 7 –2952.91 5919.99 332370.47 0 88 315888.55 0.010 –18.28 –0.32 8 –25905.85 –1191.93 8 –2952.33 5920.86 315888.55 0 54 279769.29 0.015 –29.99 7 –25359.38 7 –2954.30 5922.76 279769.29 0 55 –17446.25 0.015 –30.00 7 730.48 7 –2954.33 5922.81 –17446.25 0 31 –13942.84 0.014 15.23 –14.86 7 597.15 7 –2954.69 5923.54 –13942.84 0 30 270854.87 0.014 15.22 –14.85 7 –24533.52 7 –2954.72 5923.60 270854.87 0 68 325781.37 0.06 6 –27829.57 –743.82 6 –2955.90 5923.92 325781.37 0 46 271195.07 0.022 22.38 7 –24558.34 7 –2955.07 5924.31 271195.07 0 47 –13201.69 0.022 22.40 7 570.17 7 –2955.08 5924.32 –13201.69 0 110 275514.19 0.000 30.35 0.37 8 –24950.25 8 –2954.44 5925.10 275514.19 0 111 –26910.22 0.000 30.36 0.37 8 1118.8622 8 –2954.67 5925.54 –26910.22 0 118 277780.98 0.018 –30.02 –0.06 8 –25177.48 8 –2954.92 5926.06 277780.98 0 94 276199.88 0.008 17.14 –13.54 0.18 8 –25022.25 8 –2954.93 5926.07 276199.89 0 74 291800.73 18.82 0.51 6 –26446.31 6 –2957.01 5926.14 291800.73 0 75 –33145.66 18.83 0.51 6 1361.47 6 –2957.06 5926.23 –33145.66 0 119 –19452.84 0.018 –30.04 –0.06 8 811.256 8 –2955.16 5926.52 –19452.841 0 95 –24751.41 0.008 17.14 –13.55 0.18 8 1028.26 8 –2955.17 5926.55 –24751.41 0 8 316805.57 0.015 6 –27575.076 –496.95 6 –2957.37 5926.87 316805.57 0 72 321442.43 0.030 –0.27 7 –26795.33 –1024.67 7 –2957.14 5928.43 321442.43 0 14 271730.53 0.032 15.44 6 –24616.62 6 –2959.09 5930.30 271730.53 0 15 –16177.16 0.032 15.45 6 684.99 6 –2959.11 5930.34 –16177.16 0 10 281186.88 9.74 5 –25470.76 5 –2961.09 5932.26 281186.88 0 11 –20325.76 9.75 5 853.36 5 –2961.11 5932.31 –20325.76 0 78 278806.29 0.022 17.89 0.24 7 –25263.12 7 –2959.10 5932.36 278806.29 0 57 966.04 10.12 –26.35 6 6 –2960.13 5932.37 966.04 0 79 –25398.24 0.022 17.90 0.24 7 1052.40 7 –2959.14 5932.44 –25398.24 0 121 1046.35 28.29 –2.75 0.34 7 7 –2959.73 5933.62 1046.35 0 18 306451.75 –13.34 5 –27760.37 5 –2962.01 5934.10 306451.75 0 19 4986.93 –13.34 5 –155.97 5 –2962.25 5934.58 4986.98 0 83 10698.68 –21.62 –0.26 6 –382.69 6 –2961.75 5935.61 10698.68 0 82 294752.23 –21.61 –0.26 6 –26692.78 6 –2961.76 5935.64 294752.23 0 38 291763.75 0.043 6 –26449.93 6 –2961.81 5935.73 291763.75 0 39 –20852.77 0.043 6 866.68 6 –2962.22 5936.56 –20852.77 0 49 860.09 –36.29 5 5 –2963.91 5937.89 860.10 0 25 1013.94 14.20 –21.82 5 5 –2964.23 5938.54 1013.94 0 34 298322.05 5 –27027.65 5 –2964.26 5938.60 298322.05 0 35 –8139.32 5 366.28 5 –2964.28 5938.65 –8139.32 0 103 –13171.24 0.045 –0.05 7 559.88 7 –2962.43 5939.02 –13171.23 0 102 288564.86 0.045 –0.05 7 –26158.09 7 –2962.46 5939.07 288564.86 0 99 –19352.05 0.31 6 809.93 6 –2963.60 5939.32 –19352.06 0 98 304864.91 0.31 6 –27633.50 6 –2963.61 5939.33 304864.91 0 105 1061.33 30.36 0.37 6 6 –2963.84 5939.80 1061.33 0 61 918.54 0.015 9.70 –20.64 7 7 –2962.92 5940.00 918.54 0 89 958.81 17.20 –16.15 0.23 6 6 –2964.25 5940.62 958.81 0 41 1198.84 29.20 5 5 –2965.32 5940.72 1198.83 0 125 1037.15 0.001 27.20 –3.56 0.32 8 8 –2962.57 5941.35 1037.15 0 113 848.37 –35.68 0.04 6 6 –2964.68 5941.48 848.37 0 22 312408.75 –0.006 –16.36 6 –28301.09 6 –2965.20 5942.53 312408.75 0 2 306715.41 4 –27786.15 4 –2967.24 5942.53 306715.41 0 23 5433.60 –0.006 –16.37 6 –173.48 6 –2965.26 5942.63 5433.60 0 3 –2468.65 4 141.45 4 –2967.35 5942.75 –2468.65 0 86 292471.45 0.010 –18.28 –0.32 7 –26485.95 7 –2964.68 5943.53 292471.45 0 87 12094.84 0.001 –18.29 –0.32 7 –438.75 7 –2964.91 5943.98 12094.84 0 53 815.84 0.015 –30.00 6 6 –2966.67 5945.46 815.84 0 29 985.99 0.014 15.23 –14.86 6 6 –2967.07 5946.27 985.99 0 66 312159.70 0.06 5 –28281.74 5 –2968.26 5946.60 312159.70 0 67 –1992.15 0.06 5 122.11 5 –2968.32 5946.73 –1992.15 0 45 1052.61 0.022 22.40 6 6 –2967.44 5947.01 1052.61 0 109 1061.34 0.000 30.36 0.37 7 7 –2966.81 5947.79 1061.34 0 117 828.56 0.018 –30.04 –0.06 7 7 –2967.30 5948.75 828.56 0 93 955.00 0.008 17.14 –13.55 0.18 7 7 –2967.30 5948.77 955.00 0 73 891.10 18.83 0.51 5 5 –2969.39 5948.87 891.10 0 6 308032.60 0.014 5 –27906.96 5 –2969.73 5949.54 308032.60 0 7 2341.94 0.014 5 –51.44 5 –2970.08 5950.24 2341.94 0 71 10037.28 0.030 –0.27 6 –358.41 6 –2969.50 5951.12 10037.28 0 70 297914.29 0.030 –0.27 6 –26985.19 6 –2969.52 5951.15 297914.29 0 13 947.57 0.032 15.45 5 5 –2971.46 5953.00 947.57 0 9 1008.31 9.75 4 4 –2973.46 5954.97 1008.31 0 77 911.84 0.022 17.90 0.24 6 6 –2971.49 5955.06 911.84 0 17 1087.56 –13.34 4 4 –2974.34 5956.83 1087.56 0 81 1131.55 –21.62 –0.26 5 5 –2974.10 5958.29 1131.55 0 37 814.24 0.043 5 5 –2974.18 5958.45 814.24 0 33 1017.69 4 4 –2976.62 5961.30 1017.67 0 101 825.68 0.045 –0.05 6 6 –2974.79 5961.70 825.68 0 97 896.32 0.31 5 5 –2975.98 5962.05 896.32 0 21 1096.59 –0.006 –16.37 5 5 –2977.58 5965.24 1096.59 0 1 1067.58 3 3 –2979.61 5965.25 1067.59 0 85 1125.98 0.010 –18.29 –0.32 6 6 –2977.06 5966.23 1125.98 0 65 1060.49 0.06 4 4 –2980.64 5969.34 1060.48 0 5 1055.91 0.014 4 4 –2982.10 5972.26 1055.91 0 69 1077.05 0.029 –0.27 5 5 –2981.89 5973.86 1077.05 0 112