Running performance with emphasis on low temperatures in a Patagonian lizard, Liolaemus lineomaculatus

Abstract

Lizard activity and endurance of cold climate is regulated by several factors such as evolutionary potential, acclimatization capacity, physiological tolerance, and locomotion among thermally advantageous microenvironments. Liolaemus lineomaculatus, a lizard inhabiting a wide range of cold environments in Patagonia, provides an excellent model to test interpopulation variability in thermal performance curves (TPCs) and usage of microhabitats. We obtained critical thermal minima and maxima, and performed running trials at eight temperatures using lizards from both a temperate-site (high-altitude) population at 42° S and a cold-site population at 50° S. The availability of environmental temperatures for running performance in open ground and in potential lizard refuges were recorded, and showed that lizards in the temperate site had a greater availability of thermal environments offering temperatures conducive to locomotion. Generalized additive mixed models showed that the two populations displayed TPCs of different shapes in 0.15 m runs at temperatures near their optimal temperature, indicating a difference in thermal sensitivity at high temperatures. However, the rest of the locomotor parameters remained similar between Liolaemus lineomaculatus from thermal and ecological extremes of their geographic distribution and this may partly explain their ability to endure a cold climate.

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Running performance
with emphasis on low
temperatures in a Patagonian
lizard, Liolaemus lineomaculatus
N. R. Cecchetto1*, S. M. Medina2 & N. R. Ibargüengoytía1
Lizard activity and endurance of cold climate is regulated by several factors such as evolutionary
potential, acclimatization capacity, physiological tolerance, and locomotion among thermally
advantageous microenvironments. Liolaemus lineomaculatus, a lizard inhabiting a wide range of
cold environments in Patagonia, provides an excellent model to test interpopulation variability
in thermal performance curves (TPCs) and usage of microhabitats. We obtained critical thermal
minima and maxima, and performed running trials at eight temperatures using lizards from both a
temperate-site (high-altitude) population at 42° S and a cold-site population at 50° S. The availability
of environmental temperatures for running performance in open ground and in potential lizard refuges
were recorded, and showed that lizards in the temperate site had a greater availability of thermal
environments oering temperatures conducive to locomotion. Generalized additive mixed models
showed that the two populations displayed TPCs of dierent shapes in 0.15 m runs at temperatures
near their optimal temperature, indicating a dierence in thermal sensitivity at high temperatures.
However, the rest of the locomotor parameters remained similar between Liolaemus lineomaculatus
from thermal and ecological extremes of their geographic distribution and this may partly explain
their ability to endure a cold climate.
In ectotherms, the range of temperatures that allow an individual to roam (thermal tolerance breadth (TTB),
sensu Feldmeth etal.1) provides an indication of upper and lower limits, outside of which tness is reduced. For
example, individuals may be less able to escape predators, nd refuges, or use thermal microenvironments. e
TTB for a species restricts the potential hours of activity2–4 and is oen correlated with its thermal environment5–8,
varying among populations due to phenotypic plasticity9 or natural selection10. Within the range of the TTB, the
eects of temperature on some performance proxies such as sprint speed, endurance, and digestion, establish
the thermal performance curves (TPCs; Figs.1 and 2). TPCs tend to form a general shape: a sigmoidal increase
in performance with temperature, then either a clear peak or a variable plateau at the optimal temperature (Topt;
sensu Waldschmidt and Tracy, Huey and Bennett)11,12, depending on the measured performance trait, and nally
an exponential or quadratic decrease13–17.
e thermal performance curve (TPC) can vary among populations at dierent locations, given that it is
expected that natural selection will favour those phenotypes that maximise performance within their local
thermal regime18–20. Environmental variability can cause variation in the maximum performance value of the
population’s TPC, the Topt, or the performance breadth (such as 80% or 95% of maximal performance and
TTB16,17,21–23). us, a population’s relationship to temperature can deviate from the species’ average or thermal
reaction norm, being best characterized by dierent mathematical functions (e.g., quadratic, exponential, Gauss-
ian). Low environmental temperatures can be detrimental to vital activities and compromise survival4,24–26, unless
the population modies its TPC, its TTB, or makes behavioural adjustments via thermoregulation, modication
of the daily hours of activity, or by choosing appropriate refuges to spend inactive time27,28.
OPEN
Ecophysiology and Life History of Reptiles: Research Laboratory, Instituto de Investigaciones en Biodiversidad
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 Centro de Investigación Esquel de
         
 *
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Lizards from high-elevation or high-latitude environments brumate in winter and, during their behavioural
transition during autumn and spring, they frequently experience temperatures near the critical thermal minimum
(CTMin). To avoid low temperatures, lizards can choose microenvironments (e.g., burrows, crevices, vegetative
cover) where temperatures are warmer than air temperature, and this behavior may extend the hours of activity
during transitions. Nevertheless, in temperate and cold environments lizards would still greatly benet from
mechanisms that allow them to be active at low temperatures, even at suboptimal levels of performance, to take
advantage of the scant and irregularly available thermal resources in harsh, cold environments. In this regard,
lizards can widen their thermal tolerance breadths, modify thermoregulatory behaviour and activity patterns,
and be as active at lower body temperatures as are populations in warmer environments10,29–33.
e genus Liolaemus shows an ability to adapt to a broad range of environments, from Peru, in the northern
extreme of their geographic range (12° S), south to Tierra del Fuego, in Argentina (54° S34,35), thus providing a
very interesting model for testing intraspecic variation in performance. Liolaemids living in the temperate-
cold climate of Patagonia showed a remarkable capacity to endure low temperatures, being active at suboptimal
temperatures and modifying thermoregulatory behaviour according to the availability of microenvironments for
thermoregulation (e.g. Liolaemus pictus argentinus36, L. bibronii, L. boulengeri37, L. sarmientoi, L. magellanicus38).
Nevertheless, the long period of brumation that reptiles experience in Patagonia in contrast to warmer loca-
tions, reduces the hours of activity which in turn aects multiple aspects of their life history39,40, and makes it
crucial for lizards to nd and use the scant warm-temperature resources whenever they are available. Liolaemus
lizards show slow growth and late sexual maturity (i.e. L. pictus argentinus, 6–8years41) in comparison with
other Lacertids living in warmer environments42–44, and they can adjust their thermoregulation behaviour to
compensate for the low environmental temperatures and short periods of activity37,45,46. Liolaemus lineomaculatus
is a viviparous species with a broad distribution from the high-Andean in north-western Patagonia, Argentina,
in Neuquén province (39° S), at elevations up to 1,800m a.s.l., to the lowlands in Santa Cruz province (400m
a.s.l. 51° S34,35).
Figure1. Velocities of 0.15m runs of Liolaemus lineomaculatus individuals from the temperate site (Esquel,
triangles) and the cold site (Calafate, circles), and the global smoothing line from the Generalized Additive
Mixed Model for each site for (a) all temperatures and (b) suboptimal temperatures.
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In this study, we evaluated the locomotor performance of Liolaemus lineomaculatus in laboratory trials at sev-
eral temperatures, with emphasis on the low-temperature portion of the thermal tolerance breadth. We selected
two populations located at the extremes of the species eco-geographic range: a northern one in the high-Andean
steppe, at 1,800m a.s.l. in Esquel (42° S), and a southern one in the lowland steppe, in Calafate (50° S), Argen-
tina. Results of the thermal performance of Liolaemus lineomaculatus are discussed in relation to the ecological
implications of locomotor capacities at low temperatures (near CTMin) in harsh environments of Patagonia.
Given that Patagonian Liolaemus lineomaculatus populations are living in the extremes of the species distri-
bution, we hypothesize that:
(1) Patagonian lizard populations live in environments of relatively dierent “thermal quality” (i.e., micro-
habitats with dierent ecologically relevant temperatures for the species, sensu Huey47).
From this hypothesis, we predict wider variability of thermal microenvironments with temperatures
within thermal parameters of eco-physiological relevance (thermal optima or thermal tolerance breadths
for running performance) at the high-elevation site in Esquel than at the lowlands in Calafate, probably
aecting the hours of activity in both populations.
(2) e individuals from these two populations have adapted their locomotor performance capacities, particu-
larly at suboptimal temperatures, and dierent thermal sensitivities, according to the thermal quality of the
environment. From this hypothesis, we predict that lizards from the population with low thermal quality
will run at higher speed at suboptimal temperatures than the population that inhabits the environment
with higher thermal quality. Additionally, we predict that the shapes of the thermal performance curves
of these two populations will be dierent, indicative of dierent sensitivities to temperature (wider or nar-
rower thermal performance breaths, dierent maximum speeds, or dierent slopes).
Figure2. Velocities of 1.05m runs of Liolaemus lineomaculatus individuals from the temperate site (Esquel,
triangles) and the cold site (Calafate, circles), and the global smoothing line from the Generalized Additive
Mixed Model for each site for (a) all temperatures and (b) suboptimal temperatures.
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Results
Parameters of the thermal performance curves for the 0.15 m runs and the 1.05 m runs for liz-
ards from the temperate population (Esquel) and from the cold population (Calafate). er-
mal tolerance breadth (TTB) was wider (Table1) and notably CTMin was lower (t1,27 = 7.27, p < 0.01) in lizards
from the temperate-site population (Esquel, mean = 2.67 ± 0.48) than in lizards from the cold-site population
(Calafate, mean = 4.18 ± 0.72). ere was no signicant population dierence in CTMax (t1,27 = 0.98, p = 0.33).
For both types of runs, we calculated the performance breadth as the ranges of Tb at which performance
is greater than or equal to 80% and 95% of maximum speed, respectively (B80 and B95). For the 0.15m runs
(Fig.1a), the higher and lower bounds of B80 were signicantly higher for individuals from the temperate
site (meanlower bound = 24.43 ± 0.21; meanhigher bound = 35.10 ± 0.26) compared to individuals from the cold site
(meanlower bound = 23.70 ± 0.38; meanhigher bound = 34.50 ± 0.30; t-test, t1,36 lower bound = 7.73, p < 0.01; and t1,36 higher bound
= 8.73, p < 0.01). ere were no signicant dierences in maximum speed (Vmax), maximum speed at subop-
timal temperatures (Vsuboptimal), or optimal temperature (Topt) between populations (F1,36 Vma x = 0.23, p = 0.64;
F1,34 Vsuboptimal = 1.89, p = 0.18; and F1,36 Topt = 0.65, p = 0.43). For the 1.05m runs (Fig.2a), individuals from the
temperate site (meanlower bound = 21.80 ± 0.51) showed lower values for the lower bound of B80 (t1,36 lower bound = 4.59,
p < 0.01) than individuals from the cold site (meanlower bound = 22.60 ± 0.60). ere were no dierences in the upper
bound of B80, nor in Vmax, Vsuboptimal or Topt between populations (Table2). Individual performance curves for
0.15m and 1.05m runs are in the Supplementary Information section (Supplementary Figs.2–5).
Proportion of individuals running within B80 and B95 in the 0.15 m and the 1.05 m runs. A
higher proportion of lizards from the temperate population (Esquel) than lizards from the cold population
Table 1. Temperature range for Liolaemus lineomaculatus from the temperate (Esquel) and the cold (Calafate)
populations’ locomotor performance parameters. ermal tolerance breadth represents the dierence between
CTMax and CTMin, while the B80 and B95 ranges are the ranges of temperatures within which the populations
can achieve 80 and 95% of their maximum speed, respectively.
Population parameter
Temperature range (°C)
Esquel Calafate
Lower bound Upper bound Lower bound Upper bound
ermal tolerance breadth 1.46 42.06 2.97 42.40
0.15m runs
B80 range 24.43 35.09 23.70 34.46
B95 range 27.71 32.63 26.89 31.93
1.05m runs
B80 range 21.15 34.68 21.29 34.83
B95 range 24.84 31.40 25.67 31.65
Table 2. Comparison of mean performance parameters of 0.15m and 1.05m runs, and critical thermal
minima and maxima (°C) including the lower and upper values of the performance breadth (B80 lower and
B80 upper, °C), maximum speed (Vmax, m/s), maximum speed at suboptimal temperatures (Vmax suboptimal, m/s),
and thermal optimum (Topt, °C). Statistical parameters for t-tests (T), Fischer’s test (F), and probabilities (p)
are shown. Performance parameters were obtained as the means of the estimates of each individual thermal
performance curve. Bold letters indicate signicance values of p < 0.01.
Population parameter Esquel mean Calafate mean Statistic p
CTMin 2.67 4.18 T1,27 = 7.27 < 0.01
CTMax 41.1 41.3 T1,27 = 0.98 0.33
0.15m runs
B80 upper 35.1 34.5 T1,16 = 8.73 < 0.01
B80 lower 24.4 23.7 T1,16 = 7.73 < 0.01
Vmax 1.41 1.74 F1,36 = 0.23 0.64
Vsuboptimal 1.27 1.10 F1,34 = 1.89 0.18
Topt 30.17 29.66 F1,36 = 0.65 0.43
1.05m runs
B80 upper 33.99 34.18 T1,16 = 0.13 0.89
B80 lower 21.81 22.65 T1,16 = 4.59 < 0.01
Vmax 0.52 0.63 F1,36 = 3.46 0.07
Vsuboptimal 0.45 0.44 F1,34 = 0.05 0.83
Topt 28.12 28.86 F1,36 = 1.16 0.22
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(Calafate) ran at speeds above their respective B80 and B95 parameters, in the 0.15m runs, while for the 1.05m
runs no signicant population dierences were found.
For the 0.15m runs, 86% of individuals from the temperate site (18 of 21) and 53% of individuals from the
cold site (9 of 17) ran at a speed within the B80 (Fisher’s exact test; odds ratio = 5.08, p = 0.03). Furthermore, 62%
of individuals from the temperate site (13 of 21) and 29% of individuals (5 of 17) from the cold site ran at a speed
within the B95 (Fisher’s exact test; odds ratio = 3.75, p = 0.04).
For the 1.05m runs, 67% of individuals from the temperatesite (14 of 21) and 59% of individuals from the
cold site (10 of 17) ran at a speed within the B80 (Fisher’s exact test; odds ratio = 1.39, p = 0.43). Additionally,
52% of individuals from the temperate site (11 of 21) and 41% of individuals from the coldsite (7 of 17) ran at
a speed within the B95 (Fisher’s exact test; odds ratio = 1.55, p = 0.36).
Models testing and comparison of the thermal performance curves (TPC) between popula-
tions. An AIC comparison of the models with and without “individual” as a random eect showed a signi-
cant improvement when including the random eect in the 0.15m and the 1.05m runs models (Supplementary
Information section, Supplementary Table).
e GAMMs ts on the TPC showed a signicant eect of the smoothing term on temperature (F1,7.33 = 43.9,
p < 0.01 for the 0.15m runs and F1,6.76 = 84.3, p < 0.01 for the 1.05m runs), and signicantly dierent trends in
0.15m run between individuals from the temperate site and the cold site (F1,4.29 = 2.54, p = 0.03, Fig.1a). In the
1.05m runs, we did not nd a signicant dierence in shape between the TPCs (Fig.2a). e random eect of
“individuals” was signicant for both models (F1,24.14 = 2.72, p < 0.01 for the 0.15m run and F1,27.58 = 5.15, p < 0.01
for the 1.05m runs), and the covariables BCI and sex did not have signicant eects on any of the models. Devi-
ance explained by the 0.15m run model was 73.3%, while the 1.05m runs model explained 74.1% of deviance.
Meanwhile, the GAMM ts for the suboptimal temperatures TPC (i.e. below Topt) showed a signicant eect
of the smoothing term on temperature (F1,2.66 = 131.03, p < 0.01 for 0.15m runs, and F1,2.73 = 96.56, p < 0.01 for the
1.05m runs), but the model did not detect a signicant dierence in shape between the TPCs in 0.15m runs or
1.05m runs (Figs.1b, 2b). e random eect of “individuals” was again signicant in both models (F1,23.97 = 2.63,
p < 0.01 for 0.15m runs and F1,26.28 = 3.96, p < 0.01 for the 1.05m runs), and the covariables BCI and sex did not
have a signicant eect on any of these models either. Deviance explained by the 0.15m runs model was 81%,
while the 1.05m runs model explained 80% of deviance (Table3).
Environmental temperatures and its relationship with running performance in Liolaemus
lineomaculatus. e environmental temperatures recorded by data-loggers obtained from the PVC lizard
models of potential overwintering refuges and exposed microenvironments on the ground at each sampling site
showed that, in the temperate site (Esquel), lizards can spend longer time at favourable temperatures for run-
ning performance than in the cold site (Calafate). Lizards in the temperate site have longer time of availability
of environmental temperatures within the thermal tolerance breadth (TTB), the B80, the B95, and longer time to
attain the Topt, than lizards from the cold site (Table4). Degree-days within TTB were almost four times higher
for the potential refuges in the temperate site than for potential refuges in the cold site (Fig.3).
Discussion
Despite the high elevation, the population of Liolaemus lineomaculatus at Esquel (temperate site) experiences
more degree-days at optimal locomotor performance temperatures than the population living in the cold site,
in Calafate, particularly during spring and autumn. Lizards in Esquel experience more of their activity span at
temperatures within their thermal tolerance breadth than lizards in Calafate. In particular, during the coldest
seasons when lizards are starting or nishing brumation and still in intermittent activity (autumn and spring) the
degree-days at the potential refuges were four times higher in the temperate site than in the cold site. We found
that these environmental dierences are associated with changes in sensitivity to temperature, represented by a
Table 3. Generalized additive models (GAMs) t to sprint-runs and long-runs, in individuals from Esquel
(temperate site) and Calafate (cold site). For each thermal performance curve (TPC), the parametric
coecients are the intercepts of the models estimated for each population. An Analysis of Variance (ANOVA)
with an F-test was used to evaluate changes in the shape of TPC between populations, for the 0.15m runs and
for the 1.05m runs. SE standard error, N number of observations, edf eective degrees of freedom. Bold letters
indicate signicance values of p < 0.01.
Estimation of parametric coecients
(SE)Approximate signicance of the elevation smoothing term (s) and
interactions
Deviance explained (N)Intercept Esquel Intercept Calafate
s (temperature) s (temperature:Calafate) s (individual)
F-value (edf) p F-value (edf ) p F-value (edf) p
0.15m runs 0.49 (0.15) 0.43 (0.17) 43.9 (7.33) < 0.01 2.54 (4.29) 0.03 2.72 (24.14) < 0.01 73.3% (358)
1.05m runs 0.16 (0.07) 0.07 (0.07) 84.3 (6.76) < 0.01 0.01 (1) 0.95 5.15 (27.58) < 0.01 74.1% (356)
0.15m runs at Suboptimal
temperatures 0.48 (0.15) 0.45 (0.17) 131.03 (2.66) < 0.01 0.46 (1.33) 0.69 2.63 (23.97) < 0.01 81% (213)
1.05m runs at Suboptimal
temperatures 0.09 (0.07) −0.06 (0.08) 96.55 (2.73) < 0.01 0.16 (1) 0.69 3.96 (26.28) < 0.01 80% (212)
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dierence in thermal tolerance breadth and a dierent shape of the thermal performance curves in the 0.15m
runs. While both populations show exponential decreases for values above optimal temperature, the population
from the cold site has a steeper exponential drop for values above ~ 30°C (Topt) for 0.15m runs and for values
above ~ 28°C (Topt) for 1.05m runs in comparison with the population from the temperate site.
e thermal tolerance breadths for individuals from Esquel were wider, with lower critical thermal mini-
mums than for individuals from Calafate. e lower bound of B80 for the 1.05m runs was almost 1°C lower in
lizards from Esquel as well. is is not surprising, since many studies show that CTMin can vary across latitudes
and elevations for many terrestrial ectotherms33,48. However, the lower and upper bounds of B80 for the 0.15m
runs was almost 1°C lower for individuals from the cold site than for individuals from the temperate site. is
dierence suggests an adaptive shi or plasticity of the performance curve to colder temperatures in Calafate,
which would allow lizards living in a harsher environment to perform at the same speed at lower temperatures.
However, although this potential advantage was observed in 0.15m runs, there were no dierences when lizards
had to run longer distances (1.05m runs). e great importance of sprint speed for many ectotherms’ tness
and survival is evident in events such as eeing predators49,50 and capturing prey51. erefore, it is not surprising
that the 0.15m run speed might have population-level dierences in thermal sensitivities in comparison with
other locomotor parameters such as the 1.05m run speed. is dierence in thermal sensitivity might also be
explained by ecological factors such as a dierence in predation pressure52,53 or dierences in the landscape and
type of substrate used for most vital activities such as feeding, reproduction and exploration. For example, the
high-Andean steppes in Esquel feature small areas of variable steepness between potential refuges and irregular
distances between refuges, a characteristic not present in the steppes of Calafate, which are mostly open plains
with more-uniform distances between shrubs (Fig.4b,c).
Table 4. Hours of activity spent within the range of the locomotor performance parameters for each
population and the percentage of the total hours of activity they represent.
Active time (hours) spent in the range (percentage of
total)
Population parameter Esquel Calafate
ermal tolerance breadth 2,262 (95%) 1,693 (71%)
0.15m runs
B80 range 329 (14%) 123 (5%)
B95 range 135 (6%) 51 (2%)
Topt 28 (1%) 11 (1%)
1.05m runs
B80 range 615 (26%) 188 (8%)
B95 range 243 (10%) 67 (3%)
Topt 44 (2%) 11 (1%)
Tot al 2,378
Figure3. ermal quality of the potential refuges (degree-day) in the temperate site (Esquel, dark grey) and the
cold site (Calafate, light grey). Values for degree-days within each population’s thermal tolerance breadth (TTB)
are represented for each potential refuge. Vector art obtained or modied from https ://svgsi lh.com; https ://pixab
ay.com; https ://www.clean png.com.
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Figure4. (a) A photograph of a Liolaemus lineomaculatus individual, scale in cm. (b) A photograph of the
sampling site in Esquel (temperate site). (c) A photograph of the sampling site in Calafate (cold site).
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In the eld, we found several dierences in the thermal quality of the environments exposed (out of poten-
tial refuges) and in the thermal quality of the potential refuges that Liolaemus lineomaculatus could use in the
intermittent and opportunistic activities during the hours of activity in autumn and spring. In the high-Andean
steppes from the temperate site, in Esquel, lizards spent the majority (95%) of autumn, spring and the begin-
ning of summer within their thermal tolerance breadth (TTB). In contrast, in the steppes of Calafate, the cold
site, lizards spent only 71% of activity time during the same months within their TTB. e same pattern can
be observed for the B80 and B95 ranges and for Topt in both the 0.15m runs and the 1.05m runs. erefore,
Esquel lizards might inhabit an environment that provides a better thermal quality for running performance. It
should be noted that the sampling of potential refuges did not take into account relative frequency of all avail-
able potential refuges nor were we able to deploy enough models to obtain replicas of each potential refuge at
each site, so certain types of refuges might be overrepresented and others underrepresented. Nevertheless, the
homogeneity of the environment allowed us to cover the most representative microenvironments even with few
models (Fig.4b,c). A more extensive study with more models per site, as recommended by some authors54 would
be necessary to describe more accurately their thermal environments.
e variance in thermal quality and physiognomy of the landscape did not result in dierences in maximal
velocities of the 0.15m runs or the 1.05m runs between populations. We expected the lower thermal quality of
partially exposed and potential refuges models in the cold site to be correlated with a better running performance
by those individuals, to compensate for having less time available with temperatures within the TTB, as seen in
many terrestrial ectotherms such as insects, amphibians and reptiles55. Additionally, daily temperature amplitude
is more variable at high elevations and, when daily variation is situated near the most thermally sensitive areas of
the TPC (such as values near Topt or near the critical thermal minima or maxima), it can reduce performance56,
which could aect individuals from the temperate site. Nevertheless, none of these factors seems to be correlated
with dierences in maximal velocities between the populations. Physiological limitations, such as mechanical
power output of the muscle bres in relation to temperature26,57, might be favouring conservation in speed-related
traits such as Vmax despite environmental dierences.
In spite of the mentioned dierences in the thermal quality of the environments, we did not detect signicant
dierences in the optimal temperature between populations, even though optimal temperatures for running are
considered to be lower in lizards in colder temperate environments24,38. Mean optimal temperatures of liolaemids
seem variable among species, particularly in lizards of the lineomaculatus section (from 27 to 36°C38,58). However,
we found that between populations of Liolaemus lineomaculatus in dierent environments, Topt for the 0.15m
and the 1.05m runs remains consistent and within the range of values found for other liolaemids58,59. Some of
the factors that could be keeping optimal temperatures similar among populations within a species, as is the
case for Zootoca vivipara25 and Sceloporus undulatus60, are behavioural adjustments such as thermoregulation61
and microhabitat selection62. Additionally, optimal temperatures could be similar among populations within a
species because of changes in predation strategies, or because of dierences in selection pressure at the dierent
locations that maintain the optimal temperature at a similar value, as was proposed by van Damme25. Values of
both populations Topt are below Liolaemus lineomaculatus’ preferred laboratory temperatures (Tsel)63, as is the
case for L. pictus argentinus59, L. sarmientoi and L. magellanicus38, and the gecko Homonota darwini64. Patagon-
ian lizards are able to obtain maximal performance output even below preferred laboratory temperatures, which
could be another cold-environment adaptation in the suite of traits composing their life histories typied by late
sexual maturity, longevity, and low mean annual reproductive output65,66.
e Generalized Additive Mixed-eects Models showed that the mixed structure, considering individuals
as a random eect, signicantly improved all models. Interindividual variation in the populations’ life history
traits has been proved to be an important source of variability67,68, which could have key relevance in the species’
plasticity, expansion and distribution69, and is sometimes more important than interpopulation variability70. We
provide further evidence that studies of thermal performance curves should include interindividual variability
while modelling for population trends with a statistical model that contemplates this very complex structure of
individuals with variable tendencies.
e GAM approach allowed us to see some marginal dierences in the shape of the TPC between individuals
from the temperate site, Esquel, and those from the cold site, Calafate, in the 0.15m runs (Fig.1a), but we did
not nd dierences in the 1.05m runs (Figs.1b, 2a,b). is is interesting because even though traditionally it
has been considered that TPCs tend to take the same general shape13,71, there seems to be value in allowing the
model to consider population-specic shapes and allowing for variability per individual (see the Supplemen-
tary Information section for individual performance curves, Supplementary Figs.2–5). However, that for some
species thermal physiology is evolutionarily conservative and thus relatively insensitive to directional selection,
following the “static thermoregulation view” (sensu Hertz etal.72), such as Psammodromus algirus, where high-
elevation lizards did not perform better than mid- and low-elevation lizards at suboptimal body temperatures,
despite inhabiting a low-quality thermal environment73.
Lizards in Esquel seem able to attain more of their locomotor potential than lizards in Calafate, since a higher
proportion of the population ran at speeds above the B80 and B95 parameters in the 0.15m runs. Perhaps this is
due to living in a more heterogeneous environment with better opportunities for thermoregulation, as seen by
the potential refuges analysis74–77.
Evidence suggests that the state of the surrounding environment can have a profound eect on the perception
of “fear” by prey animals in predatory encounters; there is a strong eect of distance to the refuge in most spe-
cies, and more species-specic evidence of eects of group size, habitat type and patch quality78. In the foraging
literature, the environmental stochasticity (in this case, considering the temperature resource) is usually referred
to as “risk”, and the daily energy budget rule79 states that a forager on a positive budget should be risk-averse
while a forager on a negative budget, risk-prone80. Following this logic, if lizards from the cold site in Calafate
were living on a negative thermal budget, they would be more risk-prone in comparison to lizards from the
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temperate site in Esquel. In Calafate, lizards might be forced to leave their refuges to thermoregulate in risky
situations where speed might factor in their survival81, making speed an important trait to develop. Meanwhile,
the potential refuges in Esquel might allow lizards to avoid unnecessary risks since they showed four times the
amount of degree-days in the thermal tolerance breadth in comparison to potential refuges in Calafate, providing
the lizards enough temperature to move without having to leave the refuge (Fig.3). Additionally, the high-Andean
steppes in Esquel provide more variability in types of microsites to use as provisional refuges, such as rocks
and burrows dug by small mammals, absent in the steppes in Calafate. Microsite selection might play a larger
role than mean ambient temperature or even latitude in shaping TPC parameters8. erefore, this dierence in
potential refuges may be even more important than the dierence in temperature observed between exposed
model temperatures, especially since presence or vulnerability to predation might act against continuous activity
even during favourable weather53,82.
In the cold weather and great seasonal thermal variations of Patagonia, at the high elevation of the Andean
steppes of Esquel and in the southern latitude steppes of Calafate, Liolaemus lineomaculatus manages to survive
and display an array of behaviours related to temperature and locomotion. In our study, we have seen that L.
lineomaculatus is able to function at environments of dierent thermal quality with similar performance. Regard-
ing 0.15m runs, the species modied the shape of their thermal performance curves between populations, and
there was a shi to colder temperatures in the population from Calafate. No such changes were found regarding
1.05m runs, or considering only temperatures below Topt. Future studies could inquire into the genetic compo-
nent that explains this interindividual variability in performance and the variability among populations of a same
species in relatively similar environments with common garden experiments or translocations, to dierentiate
between adaptation and plasticity. Future studies could also investigate the characteristics of potential refuges
based on behavioural observations in the eld and on the use of tracking technology to disclose which refuges
lizards actually use in the eld, particularly during winter.
Materials and methods
Study areas and eld methods. Liolaemus lineomaculatus is a small (SVL = 62mm; Fig.4a), insectivo-
rous, psammophilous, viviparous lizard34,35. We captured adults at two extreme locations of the species’ eco-
geographic range: one in the Andes near Esquel, Argentina (42° 49′ S, 71° 15′ W; 1,800m a.s.l.; March 2017;
N = 21, 13 males and 8 females, Fig.4b), and the other in the steppes of Calafate (50° 15′ S, 71° 29′ W; 450m a.s.l.;
February 2018, N = 17, 7 males and 10 females, Fig.4c). We captured lizards by hand or loop, and individuals
were handled by the head and hips at time of capture to avoid heat transfer.
In the high-Andean steppe, lizards can nd refuge under boulders, bushes, tussocks or in the many aban-
doned burrows of small mammals (such as rodents from the Ctenomys genera), and the terrain is composed of
small areas of variable steepness. Meanwhile, in the steppes near Calafate, the terrain is a plain, open eld with
numerous bushes and tussocks, but there are almost no boulders or rocks to hide under or use as heat sources
(N. Cecchetto, personal observation).
Eects of body temperature on speed. Immediately aer capture, we brought lizards to the laboratory
in individual cloth bags to minimize stress, and housed them in individual open-top terraria (15 × 20 × 20cm).
We carried out the locomotor performance trials (running trials) within 96h of capture between 09:00 and
19:00h, when lizards are active in their natural environment and at least 16h aer feeding. Lizards were fed and
had water adlibitum daily aer completing the trials.
Running trials were conducted on a racetrack 0.07m wide and leading to a shelter. Eight photocells positioned
at 0.15-m intervals along the track and connected to a computer sensed the lizard’s motion, and thereby, the
speed over each 0.15-m section and the full 1.05m length. During analysis, each run was broken into a sprint-
run component (rst 0.15m, henceforth referred to as “0.15m run”), and a long-run component (henceforth
referred to as “1.05m run”), both runs indicative of locomotor capacity of the lizard. e 0.15m runs represent
the rst burst or escape response from a predator since the top velocity is usually reached in the rst milliseconds
of the response58 and represent the distance between two immediatelycontiguous shrubs. Meanwhile, the 1.05m
runs represent the longer distances lizards oen use to activities such as foraging, territorial defence, escaping
predators, and courtship, considering that in this population lizards run in general from one shrub to the other,
which are 1 to 2m apart (Fig.4c).
e 0.15m and 1.05m running trials were carried out at eight temperatures: 12, 14, 18, 22, 24, 31, 35, 38°C,
included in the range of eld active temperatures of L. lineomaculatus (10–40°C63). Lizards were placed in a
thermal chamber at stable temperatures for at least 30min aer equilibrium with target temperature before trials.
We performed only two temperature trials per day, one in the morning and the other in the aernoon, leaving
lizards enough time to rest between trials. Order of temperatures was haphazardly chosen for lizards (not follow-
ing any particular randomization system), avoiding two contrasting temperatures (e.g. a very low temperature
followed by a high temperature) on the same day, which could unnecessarily stress the lizards, following the
methods of Angilletta etal.83, Fernández etal.38, Ibargüengoytía etal.84. Before each run, we measured the body
temperature (Tb) using the same methodology used for eld Tb.
Each lizard ran three consecutive times in each of the eight temperature trials, and then, we selected only the
fastest non-stop run for the analyses.
We measured body mass before and aer each trail using an Ohaus balance Scot Pro (± 0.01g) and we did not
nd dierences between them (Paired t-test, t1,37 = 0.711, p = 0.48 for Esquel individuals; t1,32 = 0.416, p = 0.68 for
Calafate individuals). We considered the thermal tolerance breadth (TTB) as the dierence between the critical
thermal minimum (CTMin) and the critical thermal maximum (CTMax; methods for the estimation of CTMin
and CTMax can be found in Supplementary Information on Materials and Methods) for each individual85.
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Environmental temperatures and potential lizard refuges. To measure environmental tempera-
tures, we placed six models emulating a lizard’s shape in the temperate site (Esquel) and four models in the cold
site (Calafate) connected by thermistors to data loggers (HOBO Temp H8, four-channel external data logger),
between March 2017 and January 2018. e models were placed in potential refuges in which the species might
seek temporary shelter (e.g., buried ~ 10–15cm underground; beneath rocks; under tussocks) and in microenvi-
ronments outside of potential refuges (on the ground, under small bushes) partially exposed to environmental
temperatures. At the site near Calafate, rocks suitable for refuging were very infrequent. is is relevant because
rocks have been shown to be quite ecient as winter refuges in similar environments36, and as corridors and
thermal buers in low thermal quality environments86.
Temperatures were recorded every 30min. e models were made of PVC pipe (1.5 × 8.0cm section) which
were then sealed at the ends with silicone (Fastix) to mimic body size, reectance, thermodynamics, and shape
of lizard’s bodies. We validated the models simultaneous temperature data from a live Liolaemus lineomaculatus
individual and a model next to each other, exposing them to a sequence of temperatures. For the calibration,
we used a heating lamp and a small terrarium, adjusting the model to mimic the position of the lizard (see
Supplementary Fig.1). Given that PVC models equilibrated too slowly with a live lizard during calibration to
be considered representative of “operative temperature distributions” (sensu87), the term “operative tempera-
tures” will not be employed in this study in relation to neither potential refuges nor the models set outside of
potential refuges. Instead, we are considering the data as environmental temperatures recorded by data-loggers.
Aer this calibration, we performed a regression between the model and the body temperature of the lizard
(Tb = 2.82 + 0.912 × physical model; Adjusted R2 = 0.92; n = 2,510; Condence Interval 0.88–0.94) and amended
the values accordingly.
For the models’ data, we considered the active time for lizards as the period 09:00 to 19:00h, using as refer-
ence the times of captures for the species from previous studies on L. lineomaculatus63,88. We discarded data from
winter, given that lizards brumate during that season due to consistently low temperatures, snowfall and shorter
days88. However, we included in the analyses data from the cold seasons of autumn and spring. We wanted to test
whether lizards could run (or walk) during the infrequent warm days in autumn and spring, when temperature
might allow for intermittent hours of activity.
In order to compare the “thermal quality” of potential refuges, we applied the concept of degree-days (sensu
Lindsey and Newman89), using as reference the values of the mean CTMin for each location. Degree-days are
the summation of temperature dierences to a reference value over time. In this way, degree-days explain both
the magnitude and duration that lizards would experience temperatures in relation to a reference chosen value.
is metric allows a direct comparison of thermal regimes among dierent sites for many species or species
populations90–95.
Statistical analyses. We analysed the variability in body sizes and weights using body condition index
(BCI), calculated as:
where Mi and SVLi are the mass and SVL of the individual, SVL0 is the arithmetic mean SVL of the population,
and bSMA is the standardized major axis slope from the regression of ln body mass on ln SVL for the population
(sensu Peig and Green96). e bSMA exponent was calculated using the package ‘lmodel2’97 in R98.
Regarding 0.15m runs and 1.05m runs, we calculated the maximum speed achieved for each lizard (Vmaxi),
the maximum speed achieved for the population (Vmax), and the thermal optimum (Topt), as the Tb at which speed
is maximal for each individual. Additionally, we calculated the performance breadth (B80 and B95), the ranges
of Tb at which performance is greater than or equal to 80% and 95% of the Vmax, respectively, following Hertz
etal.72 and Angilletta etal.83 methodologies. Finally, we wanted to detect dierences in performance consider-
ing only suboptimal temperatures (i.e., values below Topt), so we calculated maximum velocity at suboptimal
temperatures (Vsuboptimal).
To estimate the Vmaxi, Vmax, B80 and B95 parameters for each population, we tted a Generalized Additive
Mixed-eects Model (GAMM) to the data obtained from the runs of all individuals using the “mcgv” package99.
e GAMM approach100 allowed tting the nonlinear relationship between temperature and speed with a
smoother function, while also evaluating interindividual variability. We considered “individuals” (each lizard’s
curve, obtained from all its temperature trials) as a grouping factor random eect, the BCI and sex as covariables,
and the eect of temperature on speed as a xed eect (one model for the 0.15m runs and one for the 1.05m
runs). e model is further explained in the Supplementary Information on Materials and Methods.
Reported parameter estimates for both xed and random eects were obtained with restricted maximum
likelihood. All statistical analyses were performed with the R statistical soware, version 3.5.398 and the “mgcv”
package, version 1.8-2899.
Ethical statement. Captures were carried out with authorization from the Wildlife Service of the Province
of Chubut (Permit # 0460/16 MP; Law XI N°10, Decree 686/90, Disposition #11/2016), signed by F. Bersano,
Director of the Wildlife Service of the Province of Chubut, E-mail: direccionfaunayorachubut@gmail.com.
We followed the ASIH/HL/SSAR Guidelines for Use of Live Amphibians and Reptiles as well as the regulations
detailed in Argentinean National Law #14,346.
BCI
=M
i
∗[
(
SVL
0)/(
SVL
i)
]
bSMA
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Data availability
Data used for these analyses are available as a Supplementary Table and atFigshare(10.6084/m9.figsh
are.12857804).
Received: 15 April 2020; Accepted: 19 August 2020
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Acknowledgements
We would like to thank F. Duran and J. Boretto for their help in the eld, capturing lizards. We would also like
to thank F. Baudino for her help and company during the experiments. Finally, we want to thank Dr M. Gómez
Berisso and I. Artola for the design and construction of the racetrack for the running trials and Dr J. Krenz for
reviewing the manuscript and providing insights.
Author contributions
N.R.C., S.M.M. and N.R.I. were involved in the conception and design of the study, captured the lizards, and
performed the experiments. N.R.C., S.M.M. and N.R.I. performed the data analyses. N.R.C. wrote the manu-
script, and S.M.M. and N.R.I. revised the manuscript.
Competing interests
e authors declare no competing interests.
Additional information
Supplementary information is available for this paper at https ://doi.org/10.1038/s4159 8-020-71617 -3.
Correspondence and requests for materials should be addressed to N.R.C.
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