Functional Ecology 2009, 23, 989–995
doi: 10.1111/j.1365-2435.2009.01588.x
Thermal acclimation of swimming performance in newt
larvae: the influence of diel temperature fluctuations
during embryogenesis
Eva Měráková and Lumı´r Gvoždı´k*
Department of Population Biology, Institute of Vertebrate Biology AS CR, Studenec 122, 67502 Koněšı´n, Czech Republic
Summary
1. Thermal acclimation is one of the basic strategies by which organisms cope with thermal heterogeneity of the environment. Under predictable variation in environmental temperatures, theory
predicts that selection favours acclimation of thermal performance curves over fixed phenotypes.
2. We examined the influence of diel fluctuations in developmental temperatures on the thermal
sensitivity of the maximal swimming capacity in larvae of the alpine newt, Triturus alpestris.
3. We incubated newt eggs under three thermal regimes with varying daily amplitudes (1, 5 and
9 C) and similar means (17Æ6–17Æ9 C), and accordingly we measured the swimming speed of
hatched larvae at three experimental temperatures (12, 17 and 22 C), which they would normally experience in their natural habitat.
4. Embryonic development under low and middle temperature fluctuations produced larvae
with similar swimming speeds across experimental temperatures. In contrast, the most fluctuating regime induced development of phenotypes, which at 12 C swam faster than larvae developed under moderate diel fluctuations.
5. Our results provide evidence that diel temperature fluctuations induce acclimation of thermal
dependence of locomotor performance. In ectotherms experiencing diel cycles in environmental
temperatures, this plastic response may act as an important pacemaker in the evolution of thermal sensitivity.
Key-words: acclimation, amphibians, locomotor performance, phenotypic plasticity, thermal
biology, thermal reaction norms
Introduction
Many organisms possess the ability to modify phenotypic
traits in response to environmental variation. This plastic
response encompasses various behavioural, physiological,
morphological and life history modifications (Pigliucci
2001; West-Eberhard 2003; DeWitt & Scheiner 2004), and
consequently it has a profound impact on population demographic parameters and interactions with the biotic and abiotic environment (Miner et al. 2005). In addition, plasticity
of fitness-related traits, especially whole-animal performance (locomotion, feeding, growth), may also play an
important role in accelerating or retarding adaptation to
newly colonized or rapidly changing environments (Ancel
2000; Price, Qvarnstrom & Irwin 2003; Ghalambor et al.
2007). Hence, information about the direction, magnitude,
adaptive significance of performance plasticity is necessary
*Correspondence author. E-mail: [email protected]
to predict the ecological and evolutionary consequences of
environmental change.
Temperature is one of the major abiotic factors inducing
plastic responses in ectotherms. Within their normal temperature range, these responses comprise of three types of thermally induced plasticity: acute, irreversible and reversible.
Acute plasticity represents a response to actual temperatures
and it is depicted by a thermal reaction norm, also referred to
as a thermal performance curve (Huey & Stevenson 1979).
Thermal sensitivity of performance (a slope or derivative of
the thermal reaction norm, Angilletta et al. 2006) can be
modified either by an irreversible response induced during
early stages of ontogeny, or by a reversible (diel or seasonal)
change that occurs during an individual lifetime. Because irreversible and reversible responses are hardly distinguishable
during early stages of ontogeny, they are jointly referred to as
thermal acclimation (Angilletta 2009). Issues concerning the
adaptive significance of thermal acclimation have received
considerable attention both theoretically and empirically
2009 The Authors. Journal compilation 2009 British Ecological Society
990 E. Meˇráková & L. Gvozˇdı´k
(Leroi, Bennett & Lenski 1994; Kingsolver & Huey 1998;
Huey et al. 1999; Gibert, Huey & Gilchrist 2001; Wilson &
Franklin 2002; Woods & Harrison 2002; Stillwell & Fox
2005). However, most researchers on thermal acclimation
until now considered only constant developmental temperatures, despite the fact that embryos of oviparous taxa are frequently exposed to substantial diel temperature fluctuations
(DTF; Shine & Harlow 1996; Bradshaw, Zani & Holzapfel
2004; Kaplan & Phillips 2006). In addition, the exposure
either to constant or fluctuating thermal regimens alters gene
expression (Podrabsky & Somero 2004), which may differently affect proximate mechanisms underlying thermal sensitivity of performance traits (Hochachka & Somero 2002;
Angilletta et al. 2003). It is therefore likely that fluctuating
and constant temperatures induce disparate plastic responses
in thermal sensitivity of whole-animal performance.
What can be predicted about the shape and direction
of an adaptive acclimation response under varying DTF
experienced in natural populations? Increasing amonggeneration variation, with respect to within-generation
variation in environmental temperatures, provides a selective advantage for irreversible acclimation (Gabriel &
Lynch 1992; see also Angilletta 2009). Theory predicts
that selection should favour increased acclimation capacity of the thermal optimum over performance breadth,
which closely follows the extent of the within-generation
variation (e.g. DTF). In contrast, selection will strongly
favour the reversible acclimation of the performance
breadth under high within-generation, relative to amonggeneration variation if DTF occurs faster than the physiological response (Gabriel 2005). Furthermore, both
theory (Huey & Kingsolver 1989; Autumn et al. 1999;
Kingsolver, Gomulkiewicz & Carter 2001; Angilletta et al.
2003) and comparative data sets (Kingsolver, Izem & Ragland 2004; Gvoždı́k & Van Damme 2008) suggest that
the widening of the performance curve primarily results
from either the change in the thermal dependence of performance or the increase in overall performance across
temperatures.
The present study examines the thermal acclimation of
maximal swimming capacity in the larvae of the alpine newt,
Triturus alpestris (Laurenti, 1768). Because alpine newts have
a relatively long generation time (mostly 3–4 years; Miaud,
Guyetant & Faber 2000), they presumably experience higher
DTF variation within than among generations (Angilletta,
Niewiarowski & Navas 2002), and thereby they are subjected
to selection for a reversible plastic response (see above).
Accordingly, we aimed to test whether (i) diel fluctuations
during embryogenesis induces an acclimation response in
swimming performance of hatched larvae and whether (ii) the
predicted response primarily involves change in the thermal
dependence of swimming capacity, or in overall performance
across a range of temperatures which normally occur in the
natural habitat of newt larvae. In addition, we obtained temperature time-series from a newt breeding habitat to obtain
information about spatiotemporal heterogeneity and predictability of DTF.
Materials and methods
STUDY SPECIES AND MAINTENANCE
Triturus alpestris (Fig. 1) is a medium-sized newt (total length up to
12 cm) widely distributed from Western Europe to the Balkans (Griffiths 1996). It usually has a biphasic lifestyle with an aquatic and terrestrial period. In Central Europe, the aquatic breeding period
typically lasts from April until June. A gravid female produces several
hundred eggs and the oviposition period lasts for several weeks. Eggs
are deposited a few centimetres below the water surface (Miaud
1995), at which depth temperatures are subjected to substantial diel
fluctuations. The oviposition occurs shortly after fertilization, e.g.
after the first or second cleavage (Griffiths & de Wijer 1994), and thus
embryogenesis is predominantly influenced not by maternal body
temperatures but by thermal conditions at oviposition sites. Larvae
usually metamorphose during summer but they sometimes overwinter and finish metamorphosis during the next season. The major
source of larval mortality is desiccation and predation (Griffiths
1997). Swimming capacity is associated with survival in various
amphibian larvae (Watkins 1996; Kaplan & Phillips 2006), therefore
this trait seems an ecologically relevant measure of their whole-animal
performance.
To obtain newt eggs for plasticity experiments, reproductive
females (mean ± SE snout to vent length = 48Æ3 ± 0Æ7 mm) were
captured from a population near Jihlava, Czech Republic, in April
2007. Females were placed in aquaria (40 · 26 · 18 cm3) with equal
amounts (3 g of wet mass) of aquatic vegetation (Vesicularia dubyana). Each aquarium was filled with 5 L of reconstituted soft
water (CaSO4Æ2H2O, 30 mg L)1; KCl, 2 mg L)1; MgSO4Æ7H2O,
61Æ37 mg L)1; NaHCO3, 48 mg L)1; Laugen, Laurila & Merilä 2003)
and it was placed in an environmental room to maintain aquarium
water temperatures at 17 ± 0Æ5 C and an equal 12 h light : dark
regime. The mean temperature was chosen with respect to modal temperatures in natural breeding sites during 2005 and 2006 (J. Dvořák
and L. Gvoždı́k, unpublished data). Newts were fed with live chironomid larvae and Tubifex worms twice per week. Water was regularly
changed in 3 day intervals. Eggs laid by a female during the first 12 h
could be influenced by previous thermal conditions and were therefore discarded from experiments. Newts were kept under these conditions up to a maximum of 7 days to obtain the required number of
eggs (n = 45) from each female (n = 10). After egg collection all
newts were released at the site of their capture.
Fig. 1. Alpine newt, Triturus alpestris. Male during aquatic period.
2009 The Authors. Journal compilation 2009 British Ecological Society, Functional Ecology, 23, 989–995
Thermal acclimation in newt larvae 991
EGG INCUBATION
We equally divided re-wrapped eggs from each female into nine plastic bowls. Each bowl was filled with 0Æ5 L of the reconstituted water,
provided with an aeration stone to prevent creation of hypoxic conditions, and the eggs were randomly placed into one of nine water baths
(60 · 46 · 15 cm3). Each bath was equipped with a thermostatic heater (50 W; Eheim ⁄ Jäger, Wüstenrot, Germany), and a mini pump
(5 W; Eheim, Deizisau, Germany) to enable equal heat distribution
throughout the cage. Water baths were evenly distributed into three
environmental rooms with air temperatures set to maintain equilibrium water temperatures at 13, 15 and 17 C. A max–min thermometer was placed in each room to assure that the target temperature did
not deviate unpredictably during incubation, e.g. in the case of a
power failure. The water baths were switched on for 10, 10 and 12 h
to reach 22, 20 and 18 C respectively. Hourly water temperatures
were recorded in one bath per room using a thermocouple probe connected to a datalogger (resolution 0Æ1 C; HOBO, Onset Computer,
Bourne, MA). Under these conditions three fluctuating regimes were
obtained with various daily amplitudes, 9, 5 and 1 C, and similar
means, 17Æ8, 17Æ9 and 17Æ6 C respectively (Fig. 2). Water baths were
checked everyday for the presence of dead eggs and newly hatched
larvae. Evaporated water was carefully replaced (i.e. to not whirl the
eggs) with deionized water during incubation.
SWIMMING PERFORMANCE TRIALS
We randomly transferred hatched larvae and placed them individually in Petri dishes (20 mL of water) in three environmental walkin rooms, maintaining water temperatures at 12, 17 and 22 C. Test
temperatures were chosen with respect to the range of temperatures
that hatched larvae experience in the field (J. Dvořák and L. Gvoždı́k,
unpublished data). When water temperature in the Petri dishes equilibrated with experimental temperature a larva was placed in the middle of squared arena (30 · 30 · 5 cm3) filled with the reconstituted
water up to 1 cm. The arena was illuminated through the semi-transparent bottom of the dish to obtain accurate outlines of experimental
animals. A larva was stimulated to move by the gentle touch of its tail
tip using a fine stainless steel probe. Each larva was stimulated four
times at one temperature only to obtain a mean thermal performance
curve for individuals developed under a particular temperature
regime. Swimming bouts were recorded using a digital camera (frame
frequency 50 Hz; Panasonic NV-GS500, Matsushita Electric Industrial, Osaka, Japan) mounted perpendicularly above the arena. After
swimming trials, larvae were digitally photographed from a dorsal
view. The total length of larvae, i.e. from the tip of snout to the tip of
tail, was later measured from the digital images by E. Měráková using
the tpsDIG software (F. J. Rohlf, Stony Brook University, Stony
Brook, NY), and then used as a proxy for hatchling size.
Video records were processed using motion analysis software
(MaxTraq; Innovision Systems, Columbiaville, MI). The maximal
distance travelled by each larva during 0Æ02 s was used for the calculation of the maximum swimming speed. Each swimming trial was subjectively judged as good or bad. Bad trials (2–4% per experimental
group), e.g. swimming along the walls of arena, were discarded from
further analyses.
ENVIRONMENTAL TEMPERATURES
To obtain information about the availability of water temperatures in
the wild, we chose three pools occupied by newts from our study population during three consecutive seasons (2005–2007). All water
bodies were located on the unpaved forest roads at maximum distance
of 200 m from each other. The maximum depth varied from 15 to
80 cm among pools. Water bodies used in one season were either
dried off or were destroyed by logging activities, therefore different
pools had to be measured between seasons. Four water-proofed (i.e.
vacuum-sealed in plastic bags) dataloggers (resolution 0Æ5 C;
DS1921G-F5, Maxim Integrated Products, Sunnyvale, CA) were
used to characterize the range of available water temperatures in each
pool. Two dataloggers were fixed to Styrofoam desks and anchored
approximately in the middle of the pool just under the water surface.
The remaining dataloggers were placed at the maximum depth on the
bottom. Pools were checked every week for the presence of aquatic
females and freshly hatched larvae from March till July. This ensures
that temperature data were obtained during the whole oviposition
and egg incubation period. Due to the non-detectable differences
between temperatures recorded by dataloggers within a given
pool-position category, their pooled time series were used for further
analyses.
STATISTICAL ANALYSES
Fig. 2. An example of temperature fluctuations in three temperature
regimes used for plasticity experiments. Hours are numbered from
the beginning of experiment.
We used generalized linear mixed-effect models for factorial randomized designs to evaluate the effect of incubation temperature regime
on embryonic survival, developmental time, hatchling size and swimming speed (Quinn & Keough 2002). Because the incubation regime
was considered an ordinal categorical variable, orthogonal polynomial contrasts were used for the analyses. Consequently, the model
for testing speed plasticity consisted of four fixed factors – linear (L)
and quadratic (Q) contrasts of developmental temperature regime
(Tdev), experimental temperature (Texp) and blocks (water baths)
nested within the incubation regime. The statistically significant Tdev
(L) indicates the increase in overall performance across temperatures,
whereas the presence of Tdev · Texp interactions supports the shift in
thermal dependence of swimming speed. The female identity and the
female · Tdev interaction were added as random factors. Due to the
fact that temperature affects hatchling size in newts (Griffiths & de
Wijer 1994), and body size may in turn influence prey catchability
(Van Damme & Van Dooren 1999), swimming speed was analysed
with and without total length as the covariate. Prior to data analysis,
2009 The Authors. Journal compilation 2009 British Ecological Society, Functional Ecology, 23, 989–995
992 E. Meˇráková & L. Gvozˇdı´k
swimming speed and total length were log10-transformed to improve
their linear relationship. The statistical significance of random factors
was tested using the likelihood ratio approach (Faraway 2006).
To evaluate both variation and predictability of DTF, we first
transformed the original time series into DTF (nfluctuations =
ntotal ) 24) defined as the temperature range during the previous
24 h. Autocorrelation patterns in transformed time series during
168 h (1 week) were examined for the presence of trend, cyclic and
random variation (Chatfield 1996). The values of autocorrelation
pffiffiffi
coefficients 2ð nÞ1 , where n is the number of values and were considered significantly different from zero. After visual examination,
time series were tested for the presence of a linear trend using the
general linear model with an autoregressive error structure. The
proportion of explained variance (PEV; Quinn & Keough 2002) by
each factor was calculated as PEV = r2model ⁄ r2total, where r2model is
the variance explained by the model, and r2total is the total variance in
a given time series. Due to large sample sizes, we considered the bias
in the estimated variance of water temperatures due to time dependence as negligible (Brown & Rothery 1993). A significance level of
a = 0Æ05 was used for all statistical tests. All means are reported ± 1
SE. Analyses were performed using the R statistical package
(R Foundation for Statistical Computing, Vienna, Austria).
speed. Specifically, this response nullified the acute effect of
temperature between 12 and 17 C in larvae developed under
high temperature fluctuations (Fig. 3).
NATURAL TEMPERATURE FLUCTUATIONS
We obtained temperature time series from six out of the nine
pools because of pool destruction by logging activities, early
drying off or loss ⁄ failure of dataloggers. For simplicity, we
present results from pools with the most extreme and the most
moderate DTF. The deepest pool (maximal depth 80 cm)
monitored in 2005 was characterized by extreme differences
between mean bottom and surface temperature fluctuations (0Æ59 ± 0Æ01 and 9Æ72 ± 0Æ09 C 24 h)1 respectively;
Fig. 4a). In contrast, newt eggs experienced more similar
DTF across water column (4Æ11 ± 0Æ03–5Æ19 ± 0Æ04 C
24 h)1) in the shallow pool (maximal depth 15 cm) monitored in 2007 (Fig. 4b). Autocorrelation coefficients of DTF
slowly decreased in time indicating the presence of linear
trend in the time series (Fig. 4c,d). In fact, linear trends were
confirmed in three out of the four time series (Fig. 4a,b;
Results
ACCLIMATION EXPERIMENTS
In total, we obtained estimates of maximal swimming speed
from 394 larvae out of 427 eggs (10 females). Embryonic survival was high (0Æ94–0Æ97; z = 1Æ17, P = 0Æ242) across all
temperature regimes. High and middle temperature fluctuations accelerated embryonic development in comparison with
embryos developed under low-fluctuating regime (14Æ5 ± 0Æ2
and 14Æ9 ± 0Æ2 days vs. 17Æ3 ± 0Æ2 days; F2,18 = 195Æ98,
P < 0Æ001). Temperature fluctuations during embryogenesis
had minor effects on hatchling size (10Æ23 ± 0Æ11–10Æ34 ±
0Æ11 mm; F2,18 = 0Æ90, P = 0Æ425), and consequently analyses of absolute and size-corrected swimming speed yielded the
same results (Table 1). Swimming speed was influenced with
experimental temperature and linear contrast of the temperature developmental regime. The presence of Tdev(L) · Texp
interaction showed that thermal conditions during embryonic
development shaped the thermal dependence of swimming
Absolute speed
Fig. 3. Thermal dependence of maximum swimming speed
(mean ± SE) in newt larvae developed at three varying temperature
regimes. See Table 1 for statistical details.
Size-corrected speed
Fixed factor
d.f.
t
P
d.f.
t
P
Tdev(L)
Tdev(Q)
Texp
Tdev(L) · Texp
Tdev(Q) · Texp
Block [Tdev]
Total length
18
18
360
360
360
360
2Æ32
0Æ11
11Æ37
2Æ16
0Æ02
1Æ03
0Æ032
0Æ914
<0Æ001
0Æ031
0Æ984
0Æ306
18
18
359
359
359
359
359
3Æ01
0Æ43
11Æ91
2Æ88
0Æ28
1Æ89
6Æ61
0Æ008
0Æ672
<0Æ001
0Æ004
0Æ780
0Æ060
<0Æ001
Random factor
Variance
v2
P
Variance
v2
P
Female
Female · Tdev
0Æ20 ± 0Æ45
0Æ00
0Æ25
0Æ00
0Æ617
1Æ000
0Æ34 ± 0Æ59
0Æ00
1Æ40
0Æ00
0Æ237
1Æ000
Table 1. General linear mixed-effect model
for the effect of developmental temperature
regime (Tdev), experimental temperature
(Texp) and female identity on the maximal
swimming speed without (absolute speed)
and with total length (size-corrected speed) as
the covariate in newt larvae
L, linear contrast; Q quadratic contrast. Statistically significant results are in bold.
2009 The Authors. Journal compilation 2009 British Ecological Society, Functional Ecology, 23, 989–995
Thermal acclimation in newt larvae 993
Fig. 4. Time series (a, b) and correlograms
(c, d) of water surface and bottom temperature fluctuations (over 24 h) recorded in temporary pools during the newt reproductive
period. Graphs represent pools with the most
extreme (a, c) and most moderate (b, d) temperature fluctuations recorded during 2005–
2007. Time series are fitted using the least
squares model with an autocorrelated error
structure (see Table 2 for statistical details).
Dotted lines in correlograms denote minimal
values as significantly different from zero.
Table 2). Despite statistically significant results, the amplitude of DTF changed very slowly during newt reproductive
period at rates of 0Æ08–0Æ24 C per week.
Discussion
Environmental temperatures are not usually stable but vary
both spatially and temporally. Surprisingly, whether diel fluctuations in developmental temperatures affect the thermal
sensitivity of whole-animal performance remains virtually
unknown. Consistent with predictions based on existing theory (see Introduction), our results showed that DTF during
embryogenesis induce acclimation response in the swimming
speed of newt larvae. The response affected thermal sensitivity at lower temperatures but not overall performance across
temperatures. In addition, high spatiotemporal heterogeneity
and predictability of DTF in natural breeding pools met the
assumptions of the adaptive thermal acclimation.
While our results clearly demonstrated the acclimation of
the thermal sensitivity of swimming speed, the effect of the
developmental temperature regime was surprisingly nonlin-
Table 2. Parameters of the general least
squares model with an autocorrelated error
structure describing linear dependence of
24-h temperature fluctuations on time in
temporary pools during newt reproductive
periods 2005–2007. Selected pools represent
examples of the most extreme and most
moderate temperature fluctuations measured
during this period
ear, suggesting the existence of a threshold for triggering a
plastic response between 5 and 9 C 24 h)1. The same result
can also be produced by constant temperatures (Cohet &
David 1978; Zamudio, Huey & Crill 1995; Huey et al. 1999).
However, it remains unclear as to what extent these responses
represent beneficial acclimation or simply the passive consequence of choosing ecologically unrealistic high and ⁄ or low
developmental temperatures (Huey et al. 1999; Loeschcke &
Hoffmann 2002; Woods & Harrison 2002). In the present
study, amplitudes of laboratory temperature regimes did not
exceed field maxima (see Fig. 4), suggesting that other mechanisms (e.g. developmental conversion or regulatory plasticity;
Smith-Gill 1983; Schlichting & Pigliucci 1995) behind detrimental acclimation are responsible for the phenotypic
outcome.
In the present study, embryogenesis under high DTF provided swimming advantage to hatched larvae at the lower end
of the DTF amplitude. The plastic response was, however,
beneficial only if swimming capacity was related to fitness in
newt larvae. Although direct evidence is lacking, some
published results support this assumption indirectly. In the
Temperature fluctuation (C 24 h)1) = a + b (hour)
Microhabitat a ± SE
Pool A1
Bottom
Surface
Pool B2
Bottom
Surface
t
b ± SE
P
t
2Æ36 ± 0Æ64 3Æ68 <0Æ001 )0Æ0005 ± 0Æ0002 2Æ80
6Æ42 ± 8Æ51 0Æ75
0Æ451
0Æ0009 ± 0Æ0023 0Æ42
)0Æ46 ± 1Æ11 0Æ41
0Æ70 ± 1Æ52 0Æ46
0Æ681
0Æ644
PEV (%)
P
0Æ005 27
0Æ675 2
0Æ0014 ± 0Æ0003 4Æ24 <0Æ001 44
0Æ0014 ± 0Æ0005 3Æ00
0Æ003 31
PEV, proportion of explained variance. Statistically significant results are in bold.
1
n = 1578; 2 n = 3192.
2009 The Authors. Journal compilation 2009 British Ecological Society, Functional Ecology, 23, 989–995
994 E. Meˇráková & L. Gvozˇdı´k
presence of a typical predator, i.e. dragonfly larva, newt larvae with relatively longer tails survive better than short-tailed
individuals (Van Buskirk & Schmidt 2000). Because tail area
is positively associated with swimming acceleration in similarly shaped salamander larvae (Fitzpatrick, Benard & Fordyce 2003), it is likely that swimming speed also influences
larval survival (see also Kaplan & Phillips 2006).
Theory predicts that the adaptive reversible acclimation
to the variation in DTF primarily involves thermal performance breadth (Gabriel 2005). The use of only three experimental temperatures precluded us from estimating this
parameter, which may be considered as a drawback of the
present study. However, an important assumption of the
model is that the optimal temperature of performance curve
follows a phenotypic optimum (i.e. modal temperature,
Kingsolver & Gomulkiewicz 2003) in a given environment.
This is not valid in our case, because the modal surface
temperatures were about 17 C and a mean thermal optimum for maximal swimming speed was 26 C (Gvoždı́k &
Van Damme 2008). In addition, only 0–12% of hourly
surface temperatures surpassed 22 C (J. Dvořák and L.
Gvoždı́k, unpublished data). Selection using thermal performance curves should be strongest at the modal temperature
(Kingsolver & Gomulkiewicz 2003), and thus we assumed
that the adaptive acclimation response would primarily act
on the shape of the ascending part of thermal performance
curve, which was sufficiently characterized by carefully chosen experimental temperatures. The estimation of the performance breadth would have been misleading in this
situation because swimming performance at biologically
unrealistic temperatures may result from a cryptic genetic
variation (Ghalambor et al. 2007) that could mask the
potential adaptive shift.
The boom of plasticity studies under fluctuating temperature regimes largely comes from an assumption that constant
temperatures provide ecologically unrealistic or even detrimental conditions, and consequently may produce misleading
results (Huey 1982; Brakefield & Mazzotta 1995; Woods &
Harrison 2002). Present findings, however, diverged from
these expectations. Clearly, there is no sign that nearly constant developmental temperature (17Æ6 ± 0Æ5 C) impairs
swimming capacity, hatchling size and embryonic survival. In
addition, data from natural habitats show that newt embryos
may develop under temperature fluctuations lying below the
threshold triggering the plastic response (Fig. 4b). Hence, low
fluctuations of daily temperatures need not necessarily represent a confounding factor in performance plasticity experiments.
Analyses of environmental temperatures showed both variation and partial predictability in DTF. Substantial spatiotemporal (i.e. between pools ⁄ seasons) variation in DTF
seems consistent with the assumption of beneficial reversible
acclimation in alpine newts (see Introduction). Spatial predictability stems from the fact that temperature fluctuations
were, especially in deeper pools, consistently more extreme on
the water surface than at the bottom of the pool. This provides newt females, whose oviposition decisions are influ-
enced by temperature (Dvořák & Gvoždı́k 2009), with
qualitative information about future thermal conditions for
their developing embryos. Temporal variation in DTF was
similar or slightly increased during the whole reproductive
period. It represents a reliable environmental cue for all ontogenetic stages. Hence, it seems likely that DTF variation in
natural breeding habitats of newts met assumptions not only
for the evolution of thermal acclimation (see Introduction)
but also for transgenerational phenotypic plasticity (Marshall
& Uller 2007).
In conclusion, our results demonstrated that fluctuating
temperatures during embryogenesis induce a plastic response
in thermal sensitivity of swimming performance in the direction of a new phenotypic optimum, i.e. the relative thermal
insensitivity under increased temporal variation of environmental temperatures. In the light of the recent theory (Ghalambor et al. 2007), the adaptive but fully compensatory
plasticity should effectively buffer selection pressure on thermal sensitivity of performance, whereas partial compensation
accelerates adaptive genetic change. The evolution of thermal
sensitivity varies considerably both within and among species
(Angilletta, Niewiarowski & Navas 2002). Diverse factors
have been proposed to explain this pattern, for example
thermoregulatory behaviour, heritability, trade-offs or the
relationship between performance and fitness (Bogert 1949;
Angilletta, Niewiarowski & Navas 2002; Huey, Hertz &
Sinervo 2003). This study indicates that thermal acclimation
to varying DTF represents another candidate for retarding or
accelerating evolutionary rates of thermal sensitivity in our
study system.
Acknowledgements
We thank R. Van Damme, S.L. Chown and three anonymous reviewers for useful comments on this manuscript, M.J. Angilletta for comments and chapters
from his book, J. Dvořák for help with obtaining newts and field temperature
data; D. Havelka for solving technical issues; L. Kratochvı́l for helpful discussion. This work was funded by the grant from the Czech Science Foundation
(206 ⁄ 06 ⁄ 0953) and the Czech Ministry of Education (LC06073). The Ministry
of the Environment of the Czech Republic issued the permission to capture
newts (8812 ⁄ 04-620 ⁄ 1483 ⁄ 04). All experimental procedures were approved by
the Expert Committee for Animal Conservation of the Institute of Vertebrate
Biology AS CR (research protocol no. 44 ⁄ 2005).
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Received 6 November 2008; accepted 5 May 2009
Handling Editor: Michael Angilletta
2009 The Authors. Journal compilation 2009 British Ecological Society, Functional Ecology, 23, 989–995