# Feeding status impacts thermoregulation and its repeatability across day and night in a diurnal lizard

Constant Perry, Fabien Aubret, Alexis Chaine, Matthew Gifford, Ethan Livingston, Maya Moore, Shala Hankison, Eric Gangloff

► To cite this version:

Constant Perry, Fabien Aubret, Alexis Chaine, Matthew Gifford, Ethan Livingston, et al.. Feed-
ing status impacts thermoregulation and its repeatability across day and night in a diurnal lizard.
Behavioral Ecology, 2025, 36 (4), pp.araf045. 10.1093/beheco/araf045. hal-05388323

HAL Id: hal-05388323

https://cnrs.hal.science/hal-05388323v1

Submitted on 4 Dec 2025

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Distributed under a Creative Commons Attribution 4.0 International License
Title: Feeding impacts thermoregulatory behavior and patterns of among-
individual variation across day and night in a diurnal lizard.

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5 Constant Perry¹,⁵, Fabien Aubret¹,³, Alexis S. Chaine¹, Matthew E. Gifford⁴, Ethan
6 Livingston², Maya Moore², Shala Hankison², Eric J. Gangloff²

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8 ¹Station d'Ecologie Théorique et Expérimentale du CNRS – UAR 2029, Moulis, France

9 ²Department of Biological Sciences, Ohio Wesleyan University, Delaware, OH 43015,
10 USA

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11 ³School of Agriculture, Environmental and Veterinary Sciences, Charles Sturt
12 University, Port Macquarie, NSW 2444, Birpai Country, Australia

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13 ⁴Department of Biology, University of Central Arkansas, Conway, AR 72035, USA

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14 ⁵Corresponding author, E-mail address: constant.perry.contact@gmail.com

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18 **Lay summary:** Lizards must behaviorally regulate their body temperature based on their
19 current physiological state, such as whether they are digesting food. Our study followed
20 lizards over continuous day and night cycles, observing how fed and unfed lizards move
21 to adjust their body temperatures. Lizards were consistent in their temperature choices
22 over time, shifted their thermoregulation if they were digesting, and daytime and
23 nighttime behaviors are correlated. This study highlights the importance of considering

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24 both daytime and nighttime behaviors to characterize how lizards might cope with
25 environmental changes.

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30 Abstract:

31 Thermoregulatory decisions impact nearly every aspect of the physiology, performance,
32 and ecology of ectotherms. Thus, understanding the factors which influence ectotherm
33 thermoregulatory behaviors across ecological contexts and environmental conditions is
34 essential in predicting responses to novel or changing environments. Specifically,
35 quantifying such behaviors across the entire diel cycle – day and night – is key to
36 understanding the impact on physiological processes that happen during periods of
37 inactivity, such as digestion. Utilizing high-resolution time-series data, we quantified
38 the diel-cycle of thermoregulatory behaviors in fed and unfed common wall lizards
39 (*Podarcis muralis*) over five consecutive days. We first tested the hypothesis that
40 feeding status affects diurnal and nocturnal thermoregulation. Second, we quantified the
41 impact of feeding status on patterns of consistency and correlation within and among
42 individuals in diurnal and nocturnal thermal behaviors. Lizards modulated their
43 thermoregulatory behavior in response to feeding status, conserving energy by choosing
44 lower temperatures when unfed and by seeking higher temperatures when fed. We
45 observed consistent among-individual differences (repeatability) in thermoregulatory
46 behaviors across diurnal and nocturnal periods. Furthermore, diurnal and nocturnal
47 thermoregulatory behaviors were positively correlated within individuals. We
demonstrate that this diurnal ectotherm actively thermoregulate during the night, a finding particularly pertinent in urban environments, where artificial light and heat can prolong the active thermoregulatory behaviors of lizards. Overall, this research provides valuable insight into the flexible thermoregulation strategies of a species highly successful in expanding its range, demonstrating the importance of considering both diurnal and nocturnal activity.

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**Keywords:** Ectotherm, thermoregulatory behavior, feeding status, diel cycle, Common Wall Lizard (*Podarcis muralis*), repeatability, urban ecology.

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59

## INTRODUCTION

The thermal environment significantly influences the biological processes of organisms and is thus an integral component in defining ecological niche and distributions (Angilletta et al. 2002; Deutsch et al. 2008; Martin and Huey 2008). In ectotherms, available environmental temperatures determine body temperature, which in turn affects the rates of physiological processes and behavior (Huey 1982; Angilletta 2009). Extreme temperatures can be harmful or limiting, whereas moderately high temperatures can increase performance or enhance physiological processes, such as metabolic rate, digestion, and locomotor performance (Huey and Kingsolver 1989; Navas et al. 1999; Angilletta et al. 2002). Therefore, ectotherms often actively maintain stable and relatively high body temperatures through various behavioral strategies, including basking, postural changes, and regulating activity during periods of optimal
temperature availability (Žagar et al. 2023). The thermoregulatory behavior of an
organism can be defined as the suite of thermoregulatory decisions and setpoints that
encompass its ability to behaviorally regulate body temperatures. Studies of variation in
thermoregulatory behaviors, including thermoregulatory preferences in a controlled
setting and thermoregulatory efficiency in natural habitats, have been conducted across
various ectotherm groups, with squamate reptiles being one of the most thoroughly
investigated. For example, thermoregulatory behaviors and strategies vary among lizard
species based on differences in their habitat (Žagar 2016; Sagonas et al. 2017), patterns
of daily activity (Avery 1978; Hatano et al. 2001; Filogonio et al. 2010; Gordon et al.
2010; Atencia et al. 2020), seasonal shifts (Giacometti et al. 2023; Karameta et al.
2023), and geographical location (Rutschmann et al. 2020; Rozen-Rechels et al. 2021;
Chabaud et al. 2022). Intrinsic factors may also affect thermoregulatory setpoints,
including life-history stage, digestive status, or gravidity (Rock et al. 2000; Arnold and
Peterson 2002; Le Galliard et al. 2003; Lin et al. 2008; Li et al. 2010; Bodensteiner et
al. 2021). Further, individual differences may arise due to genetically-determined
differences and/or developmental conditions (Mathies and Andrews 1997; Xu and Ji
2006).

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To survive and successfully reproduce, organisms must achieve a positive nutritional
energy balance, where energy intake from feeding at the minimum is equal to that used
for growth, activities, and reproduction (Schneider 2004; Kooijman 2010; Brewster et
al. 2021). Energy assimilation is influenced by food availability, capture efficiency, and
rates of digestion, which in ectotherms is temperature-dependent (Van Damme et al.
1991; Angilletta 2001; Pafilis et al. 2007; Brewster et al. 2021; Wehrle and German
2023; Litmer and Beaupre 2024). In environments with abundant prey, faster digestion due to higher body temperatures can boost food consumption and growth (Gangloff et al. 2015; Addis et al. 2017). In particular, many studies have shown that the thermoregulatory behaviors of ectotherms can be influenced by feeding status, altering preferred temperatures after ingestion to aid digestion and absorption. Several ectothermic vertebrates keep their bodies warmer after eating to speed up digestion, a practice known as post-prandial thermophily (Huey 1982; Andrade et al. 2005). For example, studies in lizards (Brown and Griffin 2005; Van Berkel and Clusella-Trullas 2018; Padilla Perez et al. 2021) and snakes demonstrate that animals select warmer temperatures in both controlled thermal gradient experiments and in natural environments following feeding (Beck, 1996; Blouin-Demers and Weatherhead 2001).

Furthermore, feeding status may impact the precision and stability of thermoregulation over time, with lizards elevating their body temperature through thermophilic behavioral responses post-digestion and metabolic reactions associated with digestion (Brown and Au 2009). Over the long term, precise and consistent thermoregulation may be advantageous for optimizing digestion. Despite these reported shifts, at least one study has documented that feeding status did not influence the consistency of body temperature selection in a lizard species, the Southern rock agama (Agama atra; Van Berkel and Clusella-Trullas 2018).

Importantly, diurnally active ectotherms spend the majority of digestion time during periods of inactivity, such as during the night for lizards (Rutschmann et al., 2023).

Despite this, most studies of ectotherm thermoregulation have concentrated on diurnal thermoregulation rather than nocturnal thermoregulation, resulting in a scarcity of
research regarding the selection of retreat sites (Rutschmann et al., 2023). For ectotherms, choosing suitable retreat and resting sites is crucial for optimizing temperature-dependent physiological processes (e.g., metabolism, digestion, assimilation, and growth). Unsuitable retreat site temperatures can negatively impact fitness if they are either too low or too high for both diurnal (Huey et al. 1989; Lelièvre et al. 2010) and nocturnal (Kearney 2002; Chukwuka et al. 2020) species. A limited number of studies have examined nocturnal retreat site choice and diel variation in thermoregulation in diurnal species (Rutschmann et al., 2023). Indeed, the majority of our understanding of nocturnal retreat-site selection by diurnal ectotherms derives from studies on thermoconformers rather than lizards that actively regulate their body temperature. For instance, a study on unfed snakes revealed that diurnal species choose higher temperatures both during the day and night compared to nocturnal species, and interestingly, all species tended to select higher body temperatures at night than during the day (Llewelyn et al. 2005). The Tuatara (*Sphenodon punctatus*), known for its slow life history and imprecise thermoregulation, displayed a contrasting behavior: they preferred higher body temperatures during the day than at night, while feeding status did not affect the temperature of selected retreat sites (Corkery et al. 2014). Moreover, Chinese green tree vipers (*Trimeresurus s. stejnegeri*) did not differ in temperatures selected during the day and the night, but snakes in a post-prandial condition chose higher temperatures (Tsai and Tu 2005). In other studies, snakes selected body temperatures carefully in their retreat sites after feeding, putatively to optimize digestive processes (Blouin-Demers and Weatherhead 2001). It is crucial to recognize that the ectotherm species referenced in this paragraph are generally considered
thermoconformers and thus differ significantly in their thermal biology from actively thermoregulating and heliothermic lizards.

Although differences in thermoregulatory behaviors across species and populations have received considerable attention, there has been less focus on exploring patterns of variation within and among individuals, such as plasticity and consistency among individuals (Peterson and Arnold 1986; Clusella Trullas et al. 2007; Goulet et al. 2017; Van Berkel and Clusella-Trullas 2018) or within- and among-individual correlations between diurnal and nocturnal thermoregulatory traits. Such information is critical to assess the evolutionary context that may produce variation in thermoregulation both within and among species. For example, characterizing the repeatability of these behaviors is an essential first step in understanding how they may respond to natural selection (Boake 1989; Bell et al. 2009). In fact, some authors have demonstrated the low repeatability of diurnal preferred body temperature in four Cordylid lizard species (with the exception of one species after acclimatation, Clusella Trullas et al. 2007; Goulet et al. 2017) whereas others studies show higher repeatability for the Common lizard (Lacertidae: Zootoca vivipara; the range of repeatability estimates for mean selected temperature: 0.37-0.66, Le Galliard et al. 2003; Artacho et al. 2013; Bestion et al. 2015). Additionally, the thermal preference of five species of nocturnal geckos did not differ between two consecutive days and showed consistency among individuals (Angilletta et al. 1999). However, to our knowledge, none have examined repeatability across daytime and nighttime periods or have they coupled these studies with tests of feeding status. Our study aims to elucidate the implications of individual variation in thermoregulatory behaviors, while also exploring how feeding status affects
167 repeatability of thermoregulatory behaviors. By examining the correlation and
168 repeatability of diurnal and nocturnal thermoregulatory traits, we can assess whether
169 these traits can independently shift through plasticity or response to selection, which
170 bears important implications for their evolutionary potential to respond to
171 environmental challenges.

172
173 To test these hypotheses, we utilize lizards from recently-established urban populations
174 outside their native range, the common wall lizards (*Podarcis muralis*), a species
175 renowned for its exceptional success in colonizing novel and urban environments. First,
176 we tested the hypothesis that lizards will adjust their diurnal and nocturnal
177 thermoregulatory decisions dependent on feeding status. Second, we examine patterns
178 of consistency and correlation between diurnal and nocturnal thermal traits within and
179 among individuals, testing the hypothesis that traits representing aspects of the
180 thermoregulatory behavior are repeatable and uncorrelated, thereby highlighting the
181 possibility for independent evolutionary trajectories through responses to selection. To
182 achieve these aims, we quantified a comprehensive suite of thermoregulatory
183 parameters during day and night over five consecutive days in fed and unfed common
184 wall lizards in a repeated-measures design with individuals measured in both
185 conditions. We predicted that unfed lizards would adjust their thermoregulatory
186 behavior and will mirror the behavior of other Squamates and especially *Lacertidae*
187 (Van Damme et al. 1991) by lowering its body temperature to take advantage of
188 metabolic depression, thereby conserving energy during periods of fasting. Further, we
189 predicted that the strength of this response would increase over time (i.e., lizards will
190 choose cooler temperatures the longer they have been fasting to conserve energy). We
further predicted that fed lizards will demonstrate more precise and consistent thermoregulatory behaviors over time compared to unfed lizards, selecting higher temperatures to increase digestive capacity, thereby reducing among-individual variation and repeatability (Van Berkel and Clusella-Trullas 2018). We further predicted that lizards which select higher temperatures during the day are likely to also prefer higher temperatures at night as part of a thermophilic phenotype (Goulet et al. 2017; Michelangeli et al. 2018). Studying the diurnal and nocturnal thermoregulatory behaviors of lizards based on their feeding status is key to understanding how ectotherms adjust their body temperature to presumable optimize thermally-dependent performance and increase fitness.

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## 202 MATERIALS AND METHODS

203 *Ethics*

All research was conducted under Ohio Division of Wildlife Wild Animal Permit (23-014) and all procedures were approved by Ohio Wesleyan University IACUC (12-2020-06).

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208 *Study Species, Collection, and Husbandry*

The Common Wall Lizard, *Podarcis muralis* (Laurenti 1768), is a heliothermic, diurnal lizard conspicuous and widespread in Central Europe and the Iberian Peninsula (Speybroeck et al., 2016), and can be found at elevations between 0 and 2600 m ASL (Sillero et al. 2014; Pottier 2020). Lizards are active generally from March to November, though they can be found out on sunny days throughout the year (Pers. Obs). This species is small [adult snout-vent length (SVL) 45-75 mm], has colonized a
variety of habitat types including urban environments including in North America (Schulte et al. 2012; Michaelides et al. 2015; Engelstoft et al. 2020; Kolenda et al. 2020; Oskyrko et al. 2020; Davis et al. 2021). We collected adult Common Wall Lizards (minimum SVL 58.5mm) from introduced populations in Cincinnati and Columbus, Ohio, USA between June 2021 and May 2022. Lizards were maintained in captivity for 8-19 months before the start of experiments. For the experiment, 20 lizards (11 males and 9 females) were maintained in same-sex groups of 3-4 in plastic enclosures (60 cm × 42 cm × 34 cm) containing a thin layer of wood shaving substrate, a water container, and two plastic hides also used as thermoregulation platforms (20 cm × 15 cm × 3 cm). Lizards were fed mealworms (*Tenebrio larvae*) or crickets (*Acheta domesticus*) 3 times/week, at which time cages were also misted. Ambient light (via four ceiling-mounted fluorescent lights, length 92.5 cm) and UV lamp (ReptiSun 10.0 UV, ZooMed, San Luis Obispo, CA, USA) were provided for 12 h/day. Ambient room temperature was a constant 20°C and enclosures were heated with incandescent heat lamps (42 W), which provided a gradient of 20 to 45°C, for 6 h per day in 1 h intervals. From November 2022 – January 2023, lizards were hibernated in the dark at cold temperatures fluctuating from 4°C-15°C, with lizards warmed and provided basking opportunities approximately every four weeks to mimic natural conditions.

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## Experimental design

Our experiment was conducted in January and February 2023, two weeks after lizards were returned to normal husbandry conditions following the hibernation period (see above) and before females were reproducing. Because we could conduct measures on only 10 animals at a time (experimental arena described below), we first randomly
assigned 10 animals, a mix of males and females, to each of two blocks. The blocks did not differ in body mass or body size (SVL) at the start of the experiment (Mass: t₁₈ = 0.11, p = 0.91; SVL: t₁₈=0.13, p = 0.89). We conducted measures on the blocks in consecutive weeks, with five lizards in each block randomly assigned to their first trial in the fed or unfed treatment. Animals were isolated individually for 3 days before the experiment in order to control feeding status for both groups (digestion passage time for lizards from these populations is ~25-60 hours, A. Litmer et al. unpublished data, see also Pafilis et al. 2007). Animals in the unfed group were fasted (food withheld) for the 3 days before the experiment and throughout the experiment. The fed group was provided with 5 crickets daily (mean weight ± SD of 5 crickets: 0.34 ± 0.06 g) during both the three days before the trials and the five days of measurements (see details below). We recorded the number of crickets consumed and replaced them to provide five available crickets each morning between 8h00 and 9h00. All lizards in the fed group ate before the experimental trials. We further randomized the individual lane assignment in the thermal gradients (see below). Immediately following the measurements on the first block we conducted identical measures on the second block. Following the first trial with the second block, we conducted the second trial with animals in the first block, with each animal experiencing the alternative treatment (lizards first tested under the fed condition were tested unfed and vice-versa). Finally, we conducted the second trial with animals in the second block. This design resulted in animals receiving six days under normal husbandry conditions between trials.

260

261 **Thermoregulation trials**
To measure selected body temperatures in uniform laboratory conditions without confounding factors such as weather fluctuation or predation, we utilized a thermal gradient (Huey 1982; Camacho and Rusch 2017). Following the acclimation period, 10 lizards (5 from each treatment group) were placed at the same time (8h00) in individual lanes of a thermal preference arena (each lane 120 x 15 cm). Lizards were maintained for five consecutive days with an ambient light diel cycle 12:12 (from 8h00 to 20h00).

On one side of this arena, we suspended four ceramic lamps (100 W, infrared heating source) to create a thermal gradient ranging from 20 to 45°C and used 3D printed *P. muralis* operative temperature models to establish the body temperatures available in the gradient (Alujević et al., 2024; Figure S2). A shelter (a PVC pipe 120 cm long and 4 cm diameter with 8 openings placed every 15 cm) was provided along the entire length of the thermal gradient to prevent any bias in positioning with shelter use. We utilized a temperature sensor/transmitter to continuously record lizard body temperature. We adhered a CubiSens data logger (0.5 g; CubiSens TS100; CubeWorks, Ann Arbor, Michigan, USA) to the dorsal scales just posterior to the scapula with double-sided tape.

Placement of the logger in this position did not appear to constrain lizard movement, consistent with similar methodology in natural systems (Refsnider et al. 2018; Warner et al. 2006). Loggers were programmed to transmit temperature data every 15 minutes.

We conducted an additional experiment to validate this method, demonstrating that temperatures recorded with the dorsally-attached logger closely match those of a probe inserted into the cloaca in lizards thermoregulating in an identical gradient (R² = 0.97; P < 0.0001, slope ± SD: 0.99 ± 0.01; Fig. S1). We did not analyze the data for the first hour after placing the animals into the gradient. Each morning thereafter at 8h00 (after the light turned on), we sprayed the substrate, checked the number of remaining
crickets, and verified the position of the loggers on every lizard. To avoid confounding our thermoregulatory data with this period of disturbance, we did not analyze data collected each day 8h00-9h00. The day was categorized as running from 8h00 to 20h00, and the night from 20h00 to 8h00. To ensure consistent experimental conditions, we monitored temperatures in the gradient with iButtons placed at the extreme temperatures ends of two gradients, programmed to record temperature every 15 minutes. Lizards were kept in these conditions for 5 consecutive days. From the body temperature data recorded every 15 minutes over the duration of the trial, we calculated seven variables: the median body temperature ($T_{med}$), the preferred body temperature ($T_{pref}$) as the mean of the central 50% of body temperatures (mean of interquartile range), the preferred temperature range ($T_{sel}$) as the range of the central 50% of selected body temperatures (interquartile range), the lower preferred temperature (Lower $T_{sel}$) as the lower limit of the interquartile range, the upper preferred temperature (Upper $T_{sel}$) as the upper limit of the interquartile range, and the minimum and the maximum voluntary temperature ($VT_{min}$ and $VT_{max}$) as the minimum and maximum body temperatures experienced, respectively (Taylor et al. 2021).

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## Morphological measurements

We measured body size (snout to vent length: SVL) with digital calipers to the nearest 0.01 mm (Model CD-6, Mitutoyo, Japan) and body mass to the nearest 0.01 g using a digital scale (Weigh Gram Top-100, Pocket Scale, Tulelake, California, USA) before and after each trial. From length and mass data, we calculated the scaled mass index (SMI: Peig and Green, 2009) as an index of body condition, calculated separately for each sex (Amer et al. 2023). This approach effectively addresses the allometric scaling
310 of growth and offers the benefit of yielding an index in the same units as the observed
311 mass (Brodeur et al. 2020).

312

313 **Statistical Methods**

314 *Trait Repeatability and Correlations*

315 Data were processed and analyzed in the programming language R (version 4.1.2, R
316 Core Team, 2021). In order to assess the potential response to selective pressures of
317 thermoregulatory behaviors in *Podarcis muralis*, we calculated the repeatability, 95%
318 confidence intervals, and the associated p-values (via likelihood ratio test) for the seven
319 thermoregulatory traits (*T*<sub>med</sub>, *T*<sub>pref</sub>, *T*<sub>sel</sub>, Lower *T*<sub>sel</sub>, Upper *T*<sub>sel</sub>, *VT*<sub>min</sub> and *VT*<sub>max</sub>)
320 independently for each diel period (day and night) and feeding status (fed or unfed)
321 using the rptR package (Stoffel et al. 2017). *T*<sub>sel</sub> was log<sub>10</sub>-transformed before analysis
322 to meet the assumption of normality of model residuals. We calculated repeatability for
323 each diel period (day or night) including all data and separately by feeding status (fed or
324 unfed), resulting in seven different repeatability estimates (day including both treatment
groups, day fed, day unfed, night including both treatment groups, night fed, and night
325 unfed). We also calculated uncertainty of estimates, including standard errors and
326 confidence intervals derived through parametric bootstrapping (1000 permutations).
327

328

329 We then characterized phenotypic correlations among the seven traits comprising the
330 thermoregulatory behavior (*T*<sub>med</sub>, *T*<sub>pref</sub>, *T*<sub>sel</sub>, Lower *T*<sub>sel</sub>, Upper *T*<sub>sel</sub>, *VT*<sub>min</sub> and *VT*<sub>max</sub>).

331 First, we used parametric correlations (Pearson correlations) on traits from only day one
332 of the trials to provide a comparison with other studies (which almost exclusively
333 include only one day of trials) and to eliminate the effect of changes in behavior over
the duration of the experiment (Table S3). Second, we used data from all five days of each trial to assess the within-individual and among-individual covariation of the thermoregulatory traits using bivariate linear mixed models, creating separate models for the two feeding treatment groups (fed and unfed). As above, $T_{sel}$ was log₁₀-transformed before analysis. We implemented bivariate mixed models in a Bayesian framework using the MCMCglmm package (Hadfield 2010) to estimate within- and among-individual trait variances, covariances and correlations (Dingemanse and Dochtermann 2013). We conducted three different correlation tests for each pairwise trait combination: all the data together, only fed lizards and then only unfed lizards. We included the fixed effect of the day of the experiment (from 1 to 5) to account for temporal changes in traits and the state of digestion (fed or unfed) of the lizards, except in analyses that stratified datasets based on feeding status. We employed parameter-expanded priors with no specific information, utilizing a Gaussian distribution. The models were executed for 5 × 10⁶ iterations, incorporating a burn-in phase of 5 × 10³ and a thinning interval of 500. This approach resulted in models with minimal autocorrelation, well-mixed MCMC chains, and a satisfactory effective sample size (N = 9,990). Our findings are presented as point estimates (the mode of the posterior distribution) with 95% credible intervals.

## Description of the Thermoregulatory Behavior

We described a composite of the thermoregulatory behavior for each individual under each treatment (fed and unfed) and during each diel period (day and night) utilizing the seven thermoregulatory traits ($T_{med}$, $T_{pref}$, $T_{sel}$, Lower $T_{sel}$, Upper $T_{sel}$, $VT_{min}$ and $VT_{max}$). We reduced the dimensionality of our data while accounting for covariance among traits via
principal component analysis (PCA) implemented with the *prcomp* function in the stats package (RC Team et al. 2018). For analysis, we retained the first two axes of variation, which explained a large portion of variance (80.1%) and exhibited eigenvalues > 1 (remaining axis exhibited eigenvalues < 0.6, see Table S3).

Linear mixed model analysis of thermoregulatory behavior and mass change between feeding status

First, to test for changes in thermoregulatory behavior between diel periods, due to feeding status, and across days we built linear models with PC scores from the first two axes of variation as the dependent variables. Models included the categorical fixed effects of period (day or night) and feeding status (fed or unfed); the predictors of day of experiment (1-5, as continuous), the sex of lizards, body size (SVL), and SMI; and a random intercept for individual. Then to test for changes in mass of the lizards during the experiment, we built linear models of the percent mass change from the beginning to the end of each trial. Models included the categorical fixed effects of feeding status (fed or unfed); the sex of lizards; the continuous predictors of body size (SVL) and scaled mass index (SMI); and a random intercept for individual. We fit linear mixed models using the lme4 (Bates et al. 2015) and lmerTest packages (Kuznetsova et al. 2017). All Variance Inflation Factors (VIFs) were calculated with the package car (Fox and Weisberg 2019) and were lower than 2, indicating little risk of multicollinearity between the predictors (Zuur et al. 2010). Initial models included the three-way interaction of diel period, feeding status, and day of the experiment as well as all possible two-way interactions of these terms. We performed backward selection and sequentially removed non-significant (P > 0.05) interactions, resulting in no significant
interactions in any of the models. We visually assessed distributions of model residuals, which indicated only a slight skew (likely due to skew in the raw nocturnal data), which should minimally affect parameter estimates and interpretation (Zuur et al. 2010; Schielzeth et al. 2020). We determined the relative importance of fixed effects using type III sums of squares with corrected denominator degrees of freedom (Kenward and Roger 1997). Univariate analyse of each separate trait is available in the supplementary information (Table S2 & Figure S3). All data figures were created with the ggplot2 package (Wickham 2016).

## 391 RESULTS

*Repeatability and Trait Correlations*

We first assessed patterns of among-individual variation in the thermoregulatory behavior across both diurnal and nocturnal periods with a repeated-measures design. Our repeatability estimates of thermoregulatory traits ranged from 0.014 - 0.646. We found evidence (confidence intervals exclude zero) for consistent among-individual variation in $T_{\text{pref}}$, $T_{\text{sel}}$, Lower $T_{\text{sel}}$, Upper $T_{\text{sel}}$ and $VT_{\text{max}}$ during the day and $T_{\text{med}}$, $T_{\text{pref}}$, $T_{\text{sel}}$, Lower $T_{\text{sel}}$, Upper $T_{\text{sel}}$, $VT_{\text{min}}$ and $VT_{\text{max}}$ at night (Figure 1, Table 1). Repeatability estimates for $T_{\text{pref}}$, Upper $T_{\text{sel}}$, and $VT_{\text{min}}$ were higher during the night than during the day (as determined by non-overlapping confidence intervals; Figure 1, Table 1). Further, estimates of $T_{\text{med}}$ and $VT_{\text{min}}$ were significantly greater than zero during the night, but not during the day. Additionally, repeatability for $T_{\text{med}}$ is higher at night and estimates of $T_{\text{sel}}$ and $VT_{\text{max}}$ at night were significantly greater than zero for unfed lizards compared to fed lizards (Figure 1, Table 1). We then assessed patterns of correlations both within- and among-individuals for traits measured during the day and during the
406 night. When considering only data from the first day in the thermal gradient, diurnal and
407 nocturnal T<sub>pref</sub> and Lower T<sub>sel</sub> were weakly positively correlated for unfed lizards and
408 there was no correlation for fed lizards (Pearson test for T<sub>pref</sub>: Fed lizards: r = -0.099, P
409 = 0.685; Unfed lizards: r = 0.51, P = 0.020; for Lower T<sub>sel</sub>: Fed lizards: r = -0.052, P =
410 0.833; Unfed lizards: r = 0.461, P = 0.040). No correlations between diurnal and
411 nocturnal values for any other traits were found when analyzing data from the first day
412 of the experiment (Figure 2, Table 2). When considering repeated measures across the
413 five days of each measurement period, there was no evidence of among-individual
414 correlations. When including data from both treatments, we found evidence for positive
415 within-individual correlations between diurnal and nocturnal T<sub>pref</sub>, T<sub>sel</sub> and Lower T<sub>sel</sub>
416 (Figure 2, Table 2): On days when lizards selected higher temperatures during the day
417 they also did so at night and when their thermoregulation was more precise during the
418 day it was also more precise at night. When data were parsed by feeding status group
419 (fed or unfed) measurements, we found evidence of within-individual correlation
420 between between diurnal and nocturnal T<sub>sel</sub> in fed lizards and T<sub>pref</sub>, T<sub>sel</sub>, Lower T<sub>sel</sub>,
421 Upper T<sub>sel</sub> in unfed lizards (Figure 2, Table 2).
422

422

423 Thermoregulatory behavior analysis

424 We described the thermoregulatory behavior of 20 lizards during the day and the night
425 for five days in a fed state and five days in an unfed state (total of 10 days for each
426 individual). The first two principal component axes account for 80.1% of the total
427 variation (Table 3, Table S3). PC1, accounting for 59.78% of the variation, described a
428 continuum of individuals which generally thermoregulate to high temperatures (high
429 values of T<sub>med</sub>, T<sub>pref</sub>, Lower T<sub>sel</sub>, Upper T<sub>sel</sub>, VT<sub>min</sub> and VT<sub>max</sub>) in contrast with less
thermophilic lizards that thermoregulated to lower temperatures (Table 3). PC2 accounts for 20.29% of total variation and contrasts lizards with a broad range of selected temperatures (wide T<sub>sel</sub>, low VT<sub>min</sub> and high VT<sub>max</sub>), so less precise thermoregulators, with lizards exhibiting a narrower range of selected termfeatures (Table 3). PC1 differed between feeding status groups, such that unfed lizards decreased PC1 scores (meaning they exhibited lower overall body temperature) (Figure 3, Table 4). PC1 scores were higher during the day (Figure 3, Table 4) and increase across the days of the experiment, meaning that selected temperatures were higher overall during the day and decreased across the days in the thermal gradient (Table 4). PC2 does not differ between feeding status groups and the diel period (Figure 3, Table 4). PC2 increased linearly in response to the day in the thermal gradient, indicating that the thermoregulatory precision decreases over days in the thermal gradient (Table 4). Finally, PC2 scores were lower in larger lizards, indicating that larger lizards thermoregulated more precisely (Table 4). When traits were analyzed individually, differences during the day and night were qualitatively similar to the multivariate analysis, though the differences between treatment groups was less clear. Specifically, T<sub>pref</sub>, T<sub>sel</sub>, Lower T<sub>sel</sub>, Upper T<sub>sel</sub>, VT<sub>min</sub> and VT<sub>max</sub> were lower at night (Table S2). Further, T<sub>med</sub>, T<sub>pref</sub>, Lower T<sub>sel</sub>, Upper T<sub>sel</sub>, VT<sub>min</sub> and VT<sub>max</sub> decreased across day in the experiment (Table S2). Only T<sub>med</sub> and VT<sub>min</sub> differed between treatment groups, with both traits increasing when lizards were fed. We found no evidence of a response to feeding in the other traits (Table S2). Finally, larger lizards exhibited higher values of T<sub>pref</sub>, lower T<sub>sel</sub>, and lower VT<sub>min</sub> (Table S2).

452

Mass change between feeding status
454 Lizards in the unfed treatment group lost more mass than lizards in the fed treatment group (Figure 4, Table S4) and lizards with high SMI lost more mass than lizards with lower SMI (Table S4).

457

458

459 DISCUSSION

460 Digestion is an essential temperature-dependent physiological process which plays a
461 central role in shaping thermoregulatory behavior in ectotherms (Huey 1982). In our
462 study, we observed that both male and female common wall lizards modified their
463 diurnal and nocturnal thermoregulatory behavior according to feeding status,
464 specifically by selecting lower body temperatures when the digestive tract was empty,
465 as represented by changes in the first PC axis of the thermoregulatory behavior (Fig 1,
466 Table 2). This result is primarily driven by 2.6°C lower values of T<sub>med</sub> and 0.9°C lower
467 values of V<sub>Tmin</sub> when unfed (Table S3). This finding aligns with previous work on
468 squamate reptiles showing that ectotherms reduce their body temperature when not
469 digesting (Brown and Griffin 2005; Van Berkel and Clusella-Trullas 2018). Reducing
470 body temperature when food is scarce might benefit animals by reducing maintenance
471 costs (Huey and Slatkin 1976; Huey 1982; Angilletta 2009). Conversely, increasing
472 postprandial body temperature is common in ectotherms and is hypothesized to enhance
473 digestive performance and facilitate energy assimilation (Angilletta 2001; Pafilis et al.
474 2007; Wehrle and German 2023) and metabolic heat production could be an additional
475 factor (Brown and Au 2009). The relationship between thermoregulation and digestion
476 plays a crucial role in how energy is acquired and allocated, ultimately affecting life-
477 history and fitness of individuals (Congdon and Tinkle 1982; Dunham et al. 1989;
Jordan and Snell 2002). In addition, parallel patterns between diurnal and nocturnal thermoregulation suggest that this shift to selecting higher temperatures while digesting also operates at night during the inactivity phase for diurnal species, a pattern seldom quantified in squamate reptiles (but see Tsai and Tu, 2005, for similar results in Chinese green tree vipers, *Trimeresurus s. stejnegeri*). Furthermore, lizards selected progressively lower temperatures over time in a thermal gradient (on average, 1.3°C lower Tpref on day five compared with day one; Table 2). All lizards lost mass during the experiment, though those for which food was withheld lost more mass despite adjusting their thermoregulatory behaviors (Figure 4, Table S4). This suggests that all individuals may thermoregulate to sub-optimally high temperatures at night when novel warm temperatures, which have likely not been experienced frequently in recent evolutionary history, become available (Carretero and Rato 2013; Afşar et al. 2018; Yakın et al. 2019; Oda et al. 2020). Observations of wall lizards opportunistically using artificial light to be active at night demonstrate that nocturnal behaviors can be flexible in response to the immediate environment and specifically anthropogenic alterations (e.g., Carretero et al. 2012). This situation could become increasingly probable and detrimental for individuals as rising nighttime temperatures may result in the counter-selection of this excessive thermoregulation during the day and the night (Rutschmann et al. 2023). However, the range of temperatures utilized for thermoregulation (as described by the second axis of variation in the thermal behavior, PC2) remains consistent between fed and unfed lizards (Fig 1, Table 2), demonstrating consistency and low plasticity for thermoregulatory precision. Our study sheds light on the potential adaptability of these behaviors across the diel cycle, highlighting the significant yet understudied patterns of individual consistency and variation. By examining how
lizards modulate their thermoregulation in response to daily cycles and feeding, we
502
503 unveil insights into the range and accuracy of their thermoregulatory choices, as well as
504 correlations among traits, emphasizing their evolutionary implications.

505

Investigating thermoregulatory behaviors across the diel cycle in diurnal ectotherms is
506
crucial for quantifying the potential to adapt to environmental shifts, including the
507
poorly understood aspect of nocturnal thermoregulation in diurnal squamates
508
(Rutschmann et al. 2023). This exploration is hindered by the difficulty in documenting
509
nocturnal activities, resulting in a significant gap in our knowledge. Nocturnal
510
thermoregulatory behaviors, influenced by daily activities, food consumption, and
511
available night temperature, are particularly vital to understand in the context of global
512
warming, where the effects of nocturnal warming on ectotherms remain under-
513
researched and potentially underestimated (Rutschmann et al. 2023). In our experiment
514
we found that nocturnal thermoregulatory behaviors differ from those measured during
515
the day (Fig 1, Table 2). In fact, lizards select an overall lower temperature during the
516
night compared to the day while also increasing the range of selected temperatures
517
(Table 2). This result suggests that lizards need to maintain a sufficient body
518
temperature for a physiological performance that may vary across the diel cycle. Such
519
variation in the timing of physiological processes may explain why studies on the
520
predicted theoretical relationship between selected temperature and optimal temperature
521
('co-adaptation hypothesis', Huey and Bennett, 1987) for performance during the active
522
phase of ectotherms have yielded inconsistent evidence (Angilletta et al. 2002; Aparicio
523
Ramirez et al. 2021). Different physiological processes are occurring during the day and
524
night, each of which may have different optimum temperatures. Our results suggest that lizards are adjusting selected temperatures depending on the physiological processes occurring during specific periods of the diel cycle.

On one hand, our findings support the notion that organisms require a metabolic shift through a reduction in body temperature during rest periods, which is essential for regenerating physiological pathways in preparation for subsequent active phases (Rutschmann et al. 2023). On the other hand, our results support the idea that lower temperatures selected by lizards at night may enhance physiological processes occurring during rest, such as digestion, growth, and healing. In addition, a higher range of selected temperatures observed during the night (less precise thermoregulation) suggests that lizards may be actively searching a nocturnal refuge site in order to cool down and to rest as cited above. For example, the Tuatara (*Sphenodon punctatus*) was also observed selecting lower temperature at night to rest, even if this species is characterized by a slow life history and less precise thermoregulation (Corkery et al. 2014). Throughout our experiment, *P. muralis* body temperature data demonstrate that the majority of individuals actively thermoregulated at night when presented with a thermal gradient, as indicated by activity with body temperature fluctuations throughout the night. This thermoregulatory behavior at night was also observed in other lizards species, indicating that diurnal species extend their period of activity when environmental conditions allow, based on the environmental temperature (Sperry et al. 2013; Levy et al. 2019; Lara Resendiz 2020).
Our findings highlight the importance of measuring thermoregulatory patterns across the diel cycle and examining the differences in patterns of consistency and correlation between diurnal and nocturnal thermal traits within and among individuals. This approach illuminates the potential for independent evolutionary pathways via selective responses. First, the question of repeatability in thermoregulatory behaviors and how it varies between day and night among vertebrate ectotherms has received minimal attention. Overall, the higher repeatability observed in nocturnal T<sub>pref</sub>, Upper T<sub>sel</sub> and VT<sub>min</sub> was unexpected, considering that the demand for higher rates of physiological processes is likely lower at night than during the day (Rutschmann et al. 2023). Conversely, feeding status does not significantly impact the among-individual consistency of diurnal thermoregulatory traits, corroborating one of the few other studies to examine this (Van Berkel and Clusella-Trullas 2018). In fact, we had expected higher repeatability in fed lizards because unfed lizards are not faced with the requirement to optimize digestive processes and so may be free to exhibit more flexibility in thermoregulation. However, we found a higher consistency for nocturnal T<sub>med</sub> in unfed lizards compared to fed lizards (Table 1). Moreover, the discrepancy found between diurnal and nocturnal thermoregulatory behavior repeatability challenges the expectation that digestive status would predominantly affect behavior during active periods. The absence of among-individual correlations between diurnal and nocturnal thermoregulatory behavior indicates no distinct 'thermoregulatory type' or 'personality,' suggesting independent evolution or changes in these behaviors. Describing thermoregulatory behavior throughout the diel cycle is vital for comprehending the selection pressures on these traits and their potential adaptive responses to environmental changes.
572

573 The diurnal and nocturnal thermoregulatory behaviors of lizards in relation to their
574 feeding status has important implications for energy balance, and by extension fitness,
575 particularly in the context of urbanization and introduced populations (Buckley 2008).

576 The urban *Podarcis muralis* population in Ohio is an introduced group originated from
577 a small founding population of about ten individuals 70 years ago (Deichsel and Gist
578 2001; Davis et al. 2021). Thus, this population has experienced a significant founder
579 effect (Deichsel and Gist 2001; Lescano et al. 2021). This effect might impact the
580 current phenotypes of these lizards and especially their thermoregulatory behavior.

581 Despite a genetic bottleneck, the population has managed to survive in introduced
582 regions (Lescano 2010; Homan 2013). Notwithstanding its origin from a small founding
583 group, there is evidence that some genetic diversity has been maintained in Ohio wall
584 lizards, as indicated by the presence of genetically-determined color morphs (Andrade
585 et al. 2019; Amer et al. 2023). Our findings reveal that lizards from this urban
586 population in Ohio select higher diurnal and nocturnal body temperatures (Tpref: mean
587 ± SD; Day: 34.71°C ± 0.78°C; Night: 31.56°C ± 3.26°C) compared to their counterparts
588 in the original populations in South Europe (Greece; Tpref: Day: 32.61°C ± 1.13°C
589 (Sagonas et al. 2017) / South of France; Tpref: Day: 32.83°C ± 2.46°C (Bodensteiner et
590 al. 2021); Tpref: Day: 31.97°C ± 0.95°C; Night: 30.86°C ± 1.78°C, C. Perry
591 unpublished data). Importantly, thermal preferences in lizards from these same Ohio
592 populations were much higher when measured during midsummer (Tpref: mean ± SD:
593 36.61 ± 0.59 °C; (Spears et al. 2024), suggesting that seasonality may play a strong role
594 in determining thermoregulatory behaviors. The artificial lighting in urban environment
595 enhances the opportunity for nocturnal thermoregulation and extends the daily activity
period of diurnal species (Perry and Fisher 2006; Perry et al. 2008; Moule et al. 2016; Baxter- Gilbert et al. 2021). This setting allows certain species to feed more than they would in natural areas (Amadi et al. 2021). First, the tendency of *P. muralis* populations to choose high temperatures both during the day and at night could indicate a specific physiological strategy (e.g., reduce gut passage times to permit higher feeding rate). On the other hand, physiological evolution may have occurred either in response to selection to tolerate higher urban temperatures or due to drift following the founder effects of a small initial propagule. Alternatively, an increased preference for warmer environments could reflect adaptation to greater food availability, a change potentially rooted in evolutionary adjustments or broad plasticity. This potentially adaptive plasticity in thermoregulatory strategy may be a testament to the species' robust adaptability to diverse environments, contributing to its high rate of colonization success across the globe.

Biotic and abiotic factors critically influence thermoregulatory behaviors in terrestrial ectotherms, impacting physiological processes, life-history strategies, and population dynamics. This study investigated how feeding status affects thermoregulatory decisions in *P. muralis*, a diurnal, heliothermic lizard with a temperate thermal niche, emphasizing its successful adaptation and colonization. Our findings show that lizard thermoregulatory behaviors are flexible and dependent on internal physiological status, opening avenues for future research and revealing ecological and evolutionary implications. Importantly, additional extrinsic factors such as seasonality (Giacometti et al., 2023; Karameta et al., 2023; Rock et al., 2000; Sanders et al., 2015; C. Perry, unpublished data), predator presence (Huey and Slatkin 1976; Downes 2001; Herczeg et
al. 2008; Broeckhoven and Mouton 2015; Chabaud et al. 2023), hydration status (Rozen-Rechels et al. 2019; Sannolo and Carretero 2019), ultraviolet radiation (Conley and Lattanzio 2022) and wind (Spears et al. 2024) should figure into future research on thermoregulatory behavior across the entire diel cycle. Future studies should also consider measuring factors affecting variation in nocturnal retreat site selection of diurnal ectotherms, given our limited understanding of these behaviors. Exploring variations in thermoregulatory behaviors within and among individuals provides a foundation for predicting evolutionary responses to climate change, urbanization, and other anthropogenic alterations of habitats. Assessing the impact of available and selected nocturnal temperatures on temperature-dependent physiological processes, such as digestion and energy assimilation, is particularly relevant due to the insufficient understanding of nocturnal warming effects on ectotherms (Rutschmann et al. 2023).
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**Figure 1.** Repeatability and 95% of confidence interval of thermoregulatory traits for fed lizards (dots) and unfed lizards (triangles). Repeatability was estimated on seven thermal traits: median body temperature ($T_{med}$), thermal preference ($T_{pref}$), preferred temperature range ($T_{sel}$), lower selected temperature (Lower $T_{sel}$), upper selected temperature (Upper $T_{sel}$), voluntary minimum temperature ($VT_{min}$) and the voluntary maximum temperature ($VT_{max}$) measured in a thermal gradient across five consecutive days for fed and unfed adult male and female common wall lizards (*Podarcis muralis*) including measurements made both during the day and at night. Repeatability estimates were considered statistically significant if the 95% confidence interval did not include zero.

**Figure 2.** Among- and within-individual correlation estimates and 95% credible intervals for diurnal and nocturnal thermoregulatory traits in fed lizards (dots) and unfed (triangles) lizards. Correlations were estimated on seven thermal traits: median body temperature ($T_{med}$), thermal preference ($T_{pref}$), preferred temperature range ($T_{sel}$), lower selected temperature (Lower $T_{sel}$), upper selected temperature (Upper $T_{sel}$), voluntary minimum temperature ($VT_{min}$) and the voluntary maximum temperature ($VT_{max}$). Traits were measured in a thermal gradient across five consecutive days in adult male and female common wall lizards (*Podarcis muralis*).

**Figure 3.** Mean and 95% confidence interval of the first two principal components (explaining 80.1% of the variance) during the day or the night measured in a thermal gradient across five consecutive days for fed (dots) and unfed (triangles) adult male and female common wall lizards (*Podarcis muralis*). Feeding status significantly impacts PC1 and there is no interaction between feeding status and period (day or night) (see Table 4). PC loadings are described in Table 3: PC1 represents a continuum of lizards generally preferring cool to warm temperatures while PC 2 represents a continuum of imprecise to precise thermoregulation.

**Figure 4.** Percentage of body mass loss during the experiment with adult male and female *Podarcis muralis*. Plots are violin plots showing the mean and the 95% of confidence interval. The green color with the circular symbol represents the Fed group and the orange color with the triangle symbol represents the Unfed group. Lizards in the unfed treatment group lost more mass than lizards in the fed treatment group (p < 0.001; see Table S2) and lizards in “better condition” (as indicated by scaled mass index, SMI) lost more mass (p = 0.001; see Table S4).
1067 **Table 1.** Repeatability estimates and 95% bootstrapped confidence intervals for thermoregulatory traits: median body temperature ($T_{med}$), preferred temperature ($T_{pref}$), preferred temperature range ($T_{sel}$), lower selected temperature (Lower $T_{sel}$), upper selected temperature (Upper $T_{sel}$), voluntary minimum temperature ($VT_{min}$) and the voluntary maximum temperature ($VT_{max}$) measured in a thermal gradient across five consecutive days for fed and unfed adult male and female common wall lizards (*Podarcis muralis*) including measurements made both during the day and at night. Significant estimates shown in bold with one ($P < 0.05$) or two ($P < 0.01$) or three ($P < 0.001$) asterisks as determined by likelihood ratio tests. See text for statistical details.

<table><thead><tr><th rowspan="2"></th><th colspan="2">All</th><th colspan="2">Fed</th><th colspan="2">Unfed</th></tr><tr><th>Day</th><th>Night</th><th>Day</th><th>Night</th><th>Day</th><th>Night</th></tr></thead><tbody><tr><td>T<sub>med</sub></td><td>R = 0.039 [0, 0.131]<br>P = 0.179</td><td>R = 0.312 [0.115, 0.47]<br><b>P < 0.001***</b></td><td>R = 0.152 [0, 0.355]<br><b>P = 0.043*</b></td><td>R = 0.094 [0, 0.284]<br>P = 0.179</td><td>R = 0.119 [0.012, 0.401]<br><b>P = 0.010*</b></td><td>R = 0.617 [0.381, 0.773]<br><b>P < 0.001***</b></td></tr><tr><td>T<sub>pref</sub></td><td>R = 0.140 [0.023, 0.274]<br><b>P < 0.001***</b></td><td>R = 0.474 [0.285, 0.637]<br><b>P < 0.001***</b></td><td>R = 0.167 [0, 0.383]<br><b>P = 0.0286*</b></td><td>R = 0.404 [0.17, 0.595]<br><b>P < 0.001***</b></td><td>R = 0.339 [0.1, 0.543]<br><b>P < 0.001***</b></td><td>R = 0.646 [0.431, 0.785]<br><b>P < 0.001***</b></td></tr><tr><td>T<sub>sel</sub> (log<sub>10</sub>)</td><td>R = 0.235 [0.086, 0.389]<br><b>P < 0.001***</b></td><td>R = 0.106 [0.001, 0.23]<br><b>P < 0.01**</b></td><td>R = 0.336 [0.115, 0.546]<br><b>P < 0.001***</b></td><td>R = 0.027 [0, 0.198]<br>P = 0.403</td><td>R = 0.302 [0.099, 0.501]<br><b>P < 0.001***</b></td><td>R = 0.156 [0, 0.365]<br><b>P = 0.0402*</b></td></tr><tr><td>Lower T<sub>sel</sub></td><td>R = 0.202 [0.057, 0.349]<br><b>P < 0.001***</b></td><td>R = 0.445 [0.232, 0.608]<br><b>P < 0.001***</b></td><td>R = 0.237 [0.024, 0.441]<br><b>P < 0.01**</b></td><td>R = 0.314 [0.08, 0.53]<br><b>P < 0.001***</b></td><td>R = 0.38 [0.155, 0.587]<br><b>P < 0.001***</b></td><td>R = 0.657 [0.416, 0.794]<br><b>P < 0.001***</b></td></tr><tr><td>Upper T<sub>sel</sub></td><td>R = 0.1 [0, 0.228]<br><b>P = 0.011*</b></td><td>R = 0.452 [0.229, 0.619]<br><b>P < 0.001***</b></td><td>R = 0.198 [0, 0.391]<br><b>P = 0.016*</b></td><td>R = 0.389 [0.143, 0.595]<br><b>P < 0.001***</b></td><td>R = 0.308 [0.077, 0.508]<br><b>P < 0.001***</b></td><td>R = 0.574 [0.343, 0.735]<br><b>P < 0.001***</b></td></tr><tr><td>VT<sub>min</sub></td><td>R = 0.035 [0, 0.144]<br>P = 0.201</td><td>R = 0.381 [0.193, 0.545]<br><b>P < 0.001***</b></td><td>R = 0.014 [0, 0.19]<br>P = 0.466</td><td>R = 0.404 [0.146, 0.597]<br><b>P < 0.001***</b></td><td>R = 0.141 [0, 0.334]<br>P = 0.053</td><td>R = 0.365 [0.129, 0.574]<br><b>P < 0.001***</b></td></tr><tr><td>VT<sub>max</sub></td><td>R = 0.081 [0, 0.203]<br><b>P = 0.028*</b></td><td>R = 0.144 [0.027, 0.283]<br><b>P < 0.01**</b></td><td>R = 0.247 [0.026, 0.452]<br><b>P < 0.01**</b></td><td>R = 0.088 [0, 0.278]<br>P = 0.182</td><td>R = 0.27 [0.057, 0.47]<br><b>P < 0.001***</b></td><td>R = 0.308 [0.084, 0.512]<br><b>P < 0.001***</b></td></tr></tbody></table>
**Table 2.** Within-individual and among-individual correlations between diurnal and nocturnal measures of thermoregulatory traits: median body temperature ($T_{med}$), thermal preference ($T_{pref}$), preferred temperature range ($T_{sel}$), lower selected temperature (Lower $T_{sel}$), upper selected temperature (Upper $T_{sel}$), voluntary minimum temperature ($VT_{min}$) and the voluntary maximum temperature ($VT_{max}$) measured in a thermal gradient during 5 consecutive days for fed and unfed adult male and female common wall lizards (*Podarcis muralis*) including measurements made both during the day and at night. Values are the mode of the posterior distribution with 95% credible intervals estimated from all day, fed trials only, and unfed trials only. Correlations with 95% credible intervals that do not overlap zero are shown in bold. See text for statistical details.

<table><thead><tr><th rowspan="2"></th><th colspan="2">All</th><th colspan="2">Fed</th><th colspan="2">Unfed</th></tr><tr><th>Among Individual</th><th>Within Individual</th><th>Among Individual</th><th>Within Individual</th><th>Among Individual</th><th>Within Individual</th></tr></thead><tbody><tr><td>T<sub>med</sub></td><td>0.356<br>[-0.306, 0.772]</td><td>0.017<br>[-0.121, 0.192]</td><td>-0.019<br>[-0.488, 0.531]</td><td>0.092<br>[-0.147, 0.310]</td><td>0.510<br>[-0.223, 0.905]</td><td>0.003<br>[-0.254, 0.229]</td></tr><tr><td>T<sub>pref</sub></td><td>0.161<br>[-0.236, 0.677]</td><td><strong>0.223</strong><br><strong>[0.081, 0.378]</strong></td><td>0.169<br>[-0.422, 0.630]</td><td>0.091<br>[-0.160, 0.317]</td><td>0.334<br>[-0.236, 0.751]</td><td><strong>0.335</strong><br><strong>[0.100, 0.525]</strong></td></tr><tr><td>T<sub>sel</sub> (log<sub>10</sub>)</td><td>0.012<br>[-0.438, 0.417]</td><td><strong>-0.171</strong><br><strong>[-0.323, -0.020]</strong></td><td>-0.029<br>[-0.433, 0.407]</td><td><strong>-0.157</strong><br><strong>[-0.310, -0.012]</strong></td><td>-0.042<br>[-0.408, 0.439]</td><td><strong>-0.169</strong><br><strong>[-0.317, -0.010]</strong></td></tr><tr><td>Lower T<sub>sel</sub></td><td>0.111<br>[-0.422, 0.563]</td><td><strong>0.157</strong><br><strong>[0.003, 0.312]</strong></td><td>0.208<br>[-0.533, 0.629]</td><td>-0.081<br>[-0.316, 0.165]</td><td>0.169<br>[-0.527, 0.610]</td><td><strong>0.301</strong><br><strong>[0.015, 0.469]</strong></td></tr><tr><td>Upper T<sub>sel</sub></td><td>0.358<br>[-0.110, 0.747]</td><td>0.133<br>[-0.052, 0.261]</td><td>0.284<br>[-0.331, 0.684]</td><td>0.039<br>[-0.197, 0.282]</td><td>0.334<br>[-0.249, 0.720]</td><td><strong>0.266</strong><br><strong>[0.008, 0.458]</strong></td></tr><tr><td>VT<sub>min</sub></td><td>0.562<br>[-0.243, 0.861]</td><td>-0.046<br>[-0.215, 0.095]</td><td>-0.632<br>[-0.882, 0.298]</td><td>0.192<br>[-0.0651, 0.389]</td><td>0.629<br>[-0.320, 0.929]</td><td>-0.159<br>[-0.383, 0.070]</td></tr><tr><td>VT<sub>max</sub></td><td>0.425<br>[-0.136, 0.753]</td><td>-0.016<br>[-0.163, 0.144]</td><td>0.402<br>[-0.366, 0.750]</td><td>-0.040<br>[-0.281, 0.190]</td><td>0.250<br>[-0.370, 0.696]</td><td>0.104<br>[-0.172, 0.312]</td></tr></tbody></table>
<table><caption>Table 3. Variable loadings from a principal component (PC) analysis of seven thermoregulatory traits measured on adult male and female common wall lizards (*Podarcis muralis*), including measurements made both during the day and at night.</caption><thead><tr><th rowspan="2">Definition</th><th>Thermophilic gradient PC1</th><th>Thermoregulatory precision PC2</th></tr><tr><th>% Variance explained</th><th>59.78%</th><th>20.29%</th></tr><tr><th>Eigenvalue</th><th>4.18</th><th>1.42</th></tr></thead><tbody><tr><td>Median temperature selected, calculated as the median value of all body temperature measurements</td><td>T<sub>med</sub></td><td>0.336</td><td>-0.043</td></tr><tr><td>Preferred body temperature as the mean of the central 50% of body temperatures (mean of interquartile range)</td><td>T<sub>pref</sub></td><td>0.474</td><td>0.033</td></tr><tr><td>Lower preferred temperature (Lower T<sub>sel</sub>) as the lower limit of the interquartile range</td><td>Lower T<sub>sel</sub></td><td>0.456</td><td>-0.222</td></tr><tr><td>Upper preferred temperature (Upper T<sub>sel</sub>) as the upper limit of the interquartile range</td><td>Upper T<sub>sel</sub></td><td>0.456</td><td>0.246</td></tr><tr><td>Preferred temperature range (T<sub>sel</sub>) as the range of the central 50% of selected body temperatures (interquartile range)</td><td>T<sub>sel</sub></td><td>-0.035</td><td>0.796</td></tr><tr><td>Minimum voluntary temperature as the minimum body temperatures experienced</td><td>VT<sub>min</sub></td><td>0.327</td><td>-0.356</td></tr><tr><td>Maximum voluntary temperature as the maximum body temperatures experienced</td><td>VT<sub>max</sub></td><td>0.371</td><td>0.356</td></tr></tbody></table>
**Table 4.** Linear mixed-effects model results for factors affecting principal components describing the thermoregulatory behavior of adult male and female common wall lizards (*Podarcis muralis*), including measurements made both during the day and at night. Individuals were included as a random intercept. Significant p-values are in bold with one (P < 0.05), two (P < 0.01), or three (P < 0.001) asterisks.

<table><thead><tr><th>Source of Variation</th><th>PC1 (59.78%)</th><th>PC2 (20.29%)</th></tr></thead><tbody><tr><td><strong>Feeding status</strong></td><td></td><td></td></tr><tr><td>Estimate ± SE (Unfed)</td><td>-1.84 ± 0.17</td><td>-0.23 ± 0.12</td></tr><tr><td>Test statistic: F (df<sub>m</sub>, df<sub>d</sub>)</td><td>122.05 (1, 365.37)</td><td>3.63 (1, 364.70)</td></tr><tr><td>P-value</td><td><strong>&lt;0.001</strong> ***</td><td>0.057</td></tr><tr><td><strong>Period</strong></td><td></td><td></td></tr><tr><td>Estimate ± SE (Night)</td><td>-0.59 ± 0.17</td><td>0.10 ± 0.12</td></tr><tr><td>Test statistic: F (df<sub>m</sub>, df<sub>d</sub>)</td><td>12.72 (1, 360.51)</td><td>0.72 (1, 361.35)</td></tr><tr><td>P-value</td><td><strong>&lt;0.001</strong> ***</td><td>0.396</td></tr><tr><td><strong>Day in experiment</strong></td><td></td><td></td></tr><tr><td>Estimate ± SE</td><td>-0.19 ± 0.06</td><td>0.08 ± 0.04</td></tr><tr><td>Test statistic: F (df<sub>m</sub>, df<sub>d</sub>)</td><td>10.92 (1, 360.50)</td><td>3.96 (1, 361.22)</td></tr><tr><td>P-value</td><td><strong>&lt;0.01</strong> **</td><td><strong>0.047</strong> *</td></tr><tr><td><strong>SMI</strong></td><td></td><td></td></tr><tr><td>Estimate ± SE</td><td>-0.21 ± 0.28</td><td>-0.08 ± 0.14</td></tr><tr><td>Test statistic: F (df<sub>m</sub>, df<sub>d</sub>)</td><td>0.50 (1, 62.28)</td><td>0.30 (1, 27.45)</td></tr><tr><td>P-value</td><td>0.481</td><td>0.586</td></tr><tr><td><strong>SVL</strong></td><td></td><td></td></tr><tr><td>Estimate ± SE</td><td>0.32 ± 0.18</td><td>-0.18 ± 0.07</td></tr><tr><td>Test statistic: F (df<sub>m</sub>, df<sub>d</sub>)</td><td>2.98 (1, 16.75)</td><td>5.95 (1, 16.78)</td></tr><tr><td>P-value</td><td>0.103</td><td><strong>0.026</strong> *</td></tr><tr><td><strong>Sex</strong></td><td></td><td></td></tr><tr><td>Estimate ± SE (Male)</td><td>0.35 ± 0.41</td><td>-0.31 ± 0.17</td></tr><tr><td>Test statistic: F (df<sub>m</sub>, df<sub>d</sub>)</td><td>0.73 (1, 19.96)</td><td>3.49 (1, 18.54)</td></tr><tr><td>P-value</td><td>0.404</td><td>0.078</td></tr></tbody></table>
<figure><img src="image_2.png" /></figure>
<figure><img src="image_3.png" /></figure>
<figure><img src="image_4.png" /></figure>
<figure><img src="image_5.png" /><figcaption>Figure 4.</figcaption></figure>
1102 SUPPORTING INFORMATION

1103 Validation of the logger used for the experiment

1104 In order to confirm the method that we used to measure the temperature of the lizards
1105 with micro temperature loggers (0.5 g; CubiSens TS100; CubeWorks, Ann Arbor,
1106 Michigan, USA), we let five lizards first acclimate and the cool end of the thermal
1107 gradient (20°C) for one hour then thermoregulate in the thermal gradient (the same
1108 gradient as the experiment). We recorded body temperature every 5 min for 2 hours
1109 (between 10h00 and 12h00, producing n = 257 recordings of body temperature)
1110 simultaneously with the loggers on the back of the lizard and with a thermocouple that
1111 was inserted ~1 cm into the cloaca (Type T, 36 gauge, Omega Engineering, ± 0.1°C,
1112 connected to a digital temperature logger HH806AU, Omega) following the protocol
1113 from Bodensteiner et al. (2021). These results indicate a strong correlation without bias
1114 in body temperatures measured via cloacal probe and via temperature loggers (R² =
1115 0.97; P < 0.0001, slope estimate ± SD: 0.99 ± 0.01), so we analyzed data from the

loggers directly without correction
(Fig. S1).

**Figure S1.** Relationship between dorsal logger temperature and lizard cloaca temperature of adult male and female common wall lizards (*Podarcis muralis*). Orange line represents linear regression and the black line the 1:1 ratio (R² = 0.97; P < 0.0001, slope ± SD: 0.99 ± 0.01).

<figure><img src="image_6.png" /></figure>

$$
\text{Slope} = 0.99
$$

$$
R^2 = 0.97
$$

$$
Sd = 0.28
$$
1130

1131
Figure S2. Temperature in the gradient represented with a spline fit and shaded area represents the 95% confidence envelope for the fit, from 0 cm (where bulbs are placed) to 120 cm, using common wall lizard (*Podarcis muralis*) 3D printed operative temperature models (Alujević et al. 2024) with a type-T thermocouple inside.

<figure><img src="image_7.png" /><figcaption>Table S1. Summary of mean, standard deviation, and range for thermoregulatory traits at day and night for fed and unfed adult male and female common wall lizards (*Podarcis muralis*).</figcaption></figure>

<table><thead><tr><th rowspan="2">Thermoregulation traits</th><th colspan="2">Fed</th><th colspan="2">Unfed</th></tr><tr><th>Day</th><th>Night</th><th>Day</th><th>Night</th></tr></thead><tbody><tr><td>T<sub>med</sub> (°C)</td><td>34.04 ± 0.95 [31.02, 36.75]</td><td>33.78 ± 1.32 [29.00, 37.17]</td><td>31.56 ± 2.65 [22.51, 37.93]</td><td>31.03 ± 4.13 [21.44, 36.89]</td></tr><tr><td>T<sub>pref</sub> (°C)</td><td>33.99 ± 0.94 [31.40, 36.59]</td><td>31.41 ± 2.64 [22.51, 37.92]</td><td>33.76 ± 1.25 [30.47, 36.96]</td><td>31.04 ± 3.97 [21.44, 36.83]</td></tr><tr><td>T<sub>sel</sub> (°C)</td><td>2.58 ± 1.10 [0.97, 5.96]</td><td>2.46 ± 1.81 [0.15, 8.60]</td><td>2.65 ± 1.36 [0.59, 7.78]</td><td>2.52 ± 2.27 [0.06, 11.12]</td></tr><tr><td>Lower T<sub>sel</sub> (°C)</td><td>32.65 ± 1.33 [28.47, 35.12]</td><td>30.14 ± 2.72 [22.35, 37.81]</td><td>32.35 ± 1.85 [26.32, 36.14]</td><td>29.78 ± 4.02 [21.41, 36.43]</td></tr><tr><td>Upper T<sub>sel</sub> (°C)</td><td>35.23 ± 0.83 [32.89, 37.48]</td><td>32.60 ± 2.85 [22.63, 37.96]</td><td>35.04 ± 0.97 [32.50, 37.58]</td><td>32.30 ± 3.94 [21.48, 37.68]</td></tr><tr><td>VT<sub>min</sub> (°C)</td><td>29.38 ± 2.34 [18.38, 33.23]</td><td>27.38 ± 2.48 [21.92, 34.00]</td><td>28.41 ± 3.38 [16.17, 33.62]</td><td>26.69 ± 3.66 [20.70, 34.94]</td></tr><tr><td>VT<sub>max</sub> (°C)</td><td>37.53 ± 1.11 [34.41, 40.89]</td><td>35.29 ± 2.44 [24.61, 40.72]</td><td>37.24 ± 0.86 [35.28, 39.41]</td><td>34.93 ± 3.31 [21.53, 38.80]</td></tr></tbody></table>

1141

1142
<figure><img src="image_8.png" /><figcaption>**Figure S3.** Scatterplot matrix of the seven thermoregulatory traits of adult male and female common wall lizards (*Podarcis muralis*): median body temperature (T<sub>med</sub>), thermal preference (T<sub>pref</sub>), selected temperature range (T<sub>sel</sub>), lower selected temperature (Lower T<sub>sel</sub>), upper selected temperature (Upper T<sub>sel</sub>), voluntary minimum temperature (VT<sub>min</sub>), voluntary maximum temperature (VT<sub>max</sub>). The diagonal represents the distribution of each variable, above diagonal provides the Pearson correlation coefficients between pairs of variables and below diagonal provides scatter plots of each pair of variables with the best linear regression line.</figcaption></figure>
Table S2. Linear mixed-effects model results for factors affecting seven thermal traits of adult male and female common wall lizards (*Podarcis muralis*): median body temperature (T<sub>med</sub>), thermal preference (T<sub>pref</sub>), selected temperature range (T<sub>sel</sub>), lower selective temperature (Lower T<sub>sel</sub>), upper selective temperature (Upper T<sub>sel</sub>), voluntary minimum temperature (VT<sub>min</sub>), voluntary maximum temperature (VT<sub>max</sub>) during the day and the night. Individuals were included as a random intercept. Significant p-values are in bold with one (P < 0.05), two (P < 0.01), or three (P < 0.001) asterisks.

1158

<table><thead><tr><th>Source of Variation</th><th>T<sub>med</sub></th><th>T<sub>pref</sub></th><th>Lower T<sub>sel</sub></th><th>Upper T<sub>sel</sub></th><th>T<sub>sel</sub> (log<sub>10</sub>)</th><th>VT<sub>min</sub></th><th>VT<sub>max</sub></th></tr></thead><tbody><tr><td><strong>Feeding status</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Estimate ± SE (Unfed)</td><td>-2.612 ± 0.244</td><td>-0.355 ± 0.2197</td><td>-0.378 ± 0.238</td><td>-0.283 ± 0.222</td><td>-0.025 ± 0.032</td><td>-0.886 ± 0.285</td><td>-0.353 ± 0.208</td></tr><tr><td>Test statistic: F (df<sub>m</sub>, df<sub>d</sub>)</td><td>115.524 (1, 365)</td><td>2.609 (1, 365)</td><td>2.522 (1, 365)</td><td>1.630 (1, 365)</td><td>0.625 (1, 364)</td><td>9.663 (1, 365)</td><td>2.887 (1, 365)</td></tr><tr><td>P-value</td><td><strong>&lt;0.001***</strong></td><td>0.107</td><td>0.113</td><td>0.203</td><td>0.429</td><td><strong>0.002**</strong></td><td>0.090</td></tr><tr><td><strong>Period</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Estimate ± SE (Night)</td><td>-0.373 ± 0.242</td><td>-2.632 ± 0.218</td><td>-2.521 ± 0.237</td><td>-2.667 ± 0.220</td><td>-0.136 ± 0.032</td><td>-1.847 ± 0.283</td><td>-2.262 ± 0.207</td></tr><tr><td>Test statistic: F (df<sub>m</sub>, df<sub>d</sub>)</td><td>2.371 (1, 361)</td><td>145.593 (1, 360)</td><td>113.47 (1, 360)</td><td>146.507 (1, 360)</td><td>18.088 (1, 360)</td><td>42.528 (1, 361)</td><td>119.653 (1, 361)</td></tr><tr><td>P-value</td><td>0.124</td><td><strong>&lt;0.001***</strong></td><td><strong>&lt;0.001***</strong></td><td><strong>&lt;0.001***</strong></td><td><strong>&lt;0.001***</strong></td><td><strong>&lt;0.001***</strong></td><td><strong>&lt;0.001***</strong></td></tr><tr><td><strong>Day in experiment</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Estimate ± SE</td><td>-0.362 ± 0.085</td><td>-0.346 ± 0.077</td><td>-0.454 ± 0.083</td><td>-0.262 ± 0.077</td><td>0.020 ± 0.011</td><td>-0.334 ± 0.099</td><td>-0.227 ± 0.073</td></tr><tr><td>Test statistic: F (df<sub>m</sub>, df<sub>d</sub>)</td><td>18.052 (1, 361)</td><td>20.423 (1, 360)</td><td>29.772 (1, 360)</td><td>11.452 (1, 360)</td><td>3.127 (1, 360)</td><td>11.248 (1, 361)</td><td>9.802 (1, 361)</td></tr><tr><td>P-value</td><td><strong>&lt;0.001***</strong></td><td><strong>&lt;0.001***</strong></td><td><strong>&lt;0.001***</strong></td><td><strong>&lt;0.001***</strong></td><td>0.078</td><td><strong>&lt;0.001***</strong></td><td><strong>0.002**</strong></td></tr><tr><td><strong>SMI</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Estimate ± SE</td><td>-0.108 ± 0.229</td><td>0.179 ± 0.392</td><td>0.179 ± 0.401</td><td>0.045 ± 0.400</td><td>-0.041 ± 0.043</td><td>0.261 ± 0.457</td><td>0.260 ± 0.323</td></tr><tr><td>Test statistic: F (df<sub>m</sub>, df<sub>d</sub>)</td><td>0.211 (1, 50)</td><td>0.196 (1, 76)</td><td>0.186 (1, 60)</td><td>0.012 (1, 80)</td><td>0.859 (1, 33)</td><td>0.307 (1, 51)</td><td>0.612 (1, 47)</td></tr><tr><td>P-value</td><td>0.648</td><td>0.659</td><td>0.667</td><td>0.913</td><td>0.348</td><td>0.582</td><td>0.438</td></tr><tr><td><strong>SVL</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Estimate ± SE</td><td>0.244 ± 0.240</td><td>0.140 ± 0.056</td><td>0.151 ± 0.054</td><td>0.113 ± 0.058</td><td>-0.005 ± 0.005</td><td>0.127 ± 0.059</td><td>0.041 ± 0.041</td></tr><tr><td>Test statistic: F (df<sub>m</sub>, df<sub>d</sub>)</td><td>1.028 (1, 17)</td><td>6.211 (1, 17)</td><td>7.764 (1, 17)</td><td>3.745 (1, 17)</td><td>1.093 (1, 17)</td><td>4.674 (1, 17)</td><td>1.018 (1, 17)</td></tr><tr><td>P-value</td><td>0.325</td><td><strong>0.023*</strong></td><td><strong>0.013*</strong></td><td>0.070</td><td>0.310</td><td><strong>0.045*</strong></td><td>0.327</td></tr><tr><td><strong>Sex</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Estimate ± SE (Male)</td><td>0.459 ± 0.539</td><td>0.105 ± 0.591</td><td>-0.030 ± 0.574</td><td>0.382 ± 0.610</td><td>0.088 ± 0.054</td><td>-0.389 ± 0.631</td><td>0.146 ± 0.438</td></tr><tr><td>Test statistic: F (df<sub>m</sub>, df<sub>d</sub>)</td><td>0.715 (1, 20)</td><td>0.031 (1, 20)</td><td>0.003 (1, 20)</td><td>0.388 (1, 20)</td><td>2.632 (1, 19)</td><td>0.37 (1, 20)</td><td>0.110 (1, 20)</td></tr><tr><td>P-value</td><td>0.408</td><td>0.862</td><td>0.959</td><td>0.540</td><td>0.118</td><td>0.547</td><td>0.744</td></tr></tbody></table>
1159 **Table S3.** Variable loadings from a principal component (PC) analysis of seven

1160 thermoregulatory traits measured on adult male and female common wall lizards

1161 (*Podarcis muralis*), including measurements made both during the day and at night.

1162

<table><thead><tr><th>Response variable</th><th>PC1</th><th>PC2</th><th>PC3</th><th>PC4</th><th>PC5</th><th>PC6</th><th>PC7</th></tr></thead><tbody><tr><td>% Variance explained</td><td>59.78%</td><td>20.29%</td><td>8.63%</td><td>6.82%</td><td>4.29%</td><td>0.18%</td><td>0.98e-15%</td></tr><tr><td>Eigenvalue</td><td>4.18</td><td>1.42</td><td>0.60</td><td>0.48</td><td>0.30</td><td>0.01</td><td>&lt; 0.0001</td></tr><tr><td>T<sub>med</sub></td><td>-0.336</td><td>-0.043</td><td>-0.916</td><td>0.132</td><td>0.165</td><td>-0.027</td><td>0</td></tr><tr><td>T<sub>pref</sub></td><td>-0.474</td><td>0.033</td><td>0.066</td><td>-0.170</td><td>-0.325</td><td>0.797</td><td>0</td></tr><tr><td>Lower T<sub>sel</sub></td><td>-0.456</td><td>-0.222</td><td>0.115</td><td>-0.281</td><td>-0.191</td><td>-0.410</td><td>0.667</td></tr><tr><td>Upper T<sub>sel</sub></td><td>-0.456</td><td>0.246</td><td>0.099</td><td>-0.054</td><td>-0.342</td><td>-0.441</td><td>-0.639</td></tr><tr><td>T<sub>sel</sub></td><td>0.035</td><td>0.796</td><td>-0.034</td><td>0.400</td><td>-0.237</td><td>-0.020</td><td>0.383</td></tr><tr><td>VT<sub>min</sub></td><td>-0.327</td><td>-0.356</td><td>0.274</td><td>0.824</td><td>0.107</td><td>0.017</td><td>0</td></tr><tr><td>VT<sub>max</sub></td><td>-0.371</td><td>0.356</td><td>0.238</td><td>-0.177</td><td>0.804</td><td>0.035</td><td>0</td></tr></tbody></table>
1163 **Table S4.** Linear mixed-effects model results of effects on percenta mass change of the
1164 lizards in Fed and Unfed treatments (N = 20) with adult male and female common wall
1165 lizards (*Podarcis muralis*). Significant p-values are in bold with one (P < 0.05), two (P
1166 < 0.01), or three (P < 0.001) asterisks. SMI: scaled mass index; SVL: snout-vent-length.

<table><thead><tr><th>Factors</th><th>Estimate</th><th>SE</th><th>F<sub>ndf, ddf</sub></th><th>p</th></tr></thead><tbody><tr><td>Feeding status<br>(Fed/Unfed)</td><td>-3.58</td><td>0.88</td><td>16.40<sub>1, 18.24</sub></td><td><strong>&lt;0.001***</strong></td></tr><tr><td>Sex</td><td>2.97</td><td>1.78</td><td>2.78<sub>1, 19.19</sub></td><td>0.111</td></tr><tr><td>SVL</td><td>-0.31</td><td>0.16</td><td>12.57<sub>1, 32.70</sub></td><td>0.075</td></tr><tr><td>SMI</td><td>-4.75</td><td>1.34</td><td>3.60<sub>1, 16.51</sub></td><td><strong>&lt;0.01**</strong></td></tr></tbody></table>