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282
Coadaptation: A Unifying Principle in Evolutionary Thermal Biology*
Michael J. Angilletta Jr.
1,⫹
Albert F. Bennett
2
Helga Guderley
3
Carlos A. Navas
4
Frank Seebacher
5
Robbie S. Wilson
6
1
Department of Ecology and Organismal Biology, Indiana
State University, Terre Haute, Indiana 47809;
2
Department of
Ecology and Evolutionary Biology, University of California,
Irvine, California 92697;
3
De´partement de Biologie,
Universite´ Laval, Que´bec, Que´bec G1K 7P4, Canada;
4
Departamento de Fisiologia, Instituto de Biocieˆncias,
Universidade de Sa˜o Paulo, Sa˜o Paulo 05508-900, Brasil;
5
School of Biological Sciences, Heydon Laurence Building
A08, University of Sydney, Sydney, New South Wales 2006,
Australia;
6
School of Life Sciences, Goddard Building, St.
Lucia Campus, University of Queensland, Brisbane,
Queensland 4072, Australia
Accepted 4/25/2005; Electronically Published 2/3/2006
ABSTRACT
Over the last 50 yr, thermal biology has shifted from a largely
physiological science to a more integrated science of behavior,
physiology, ecology, and evolution. Today, the mechanisms that
underlie responses to environmental temperature are being
scrutinized at levels ranging from genes to organisms. From
these investigations, a theory of thermal adaptation has
emerged that describes the evolution of thermoregulation, ther-
mal sensitivity, and thermal acclimation. We review and inte-
grate current models to form a conceptual model of coadap-
tation. We argue that major advances will require a quantitative
theory of coadaptation that predicts which strategies should
evolve in specific thermal environments. Simply combining
current models, however, is insufficient to understand the re-
sponses of organisms to thermal heterogeneity; a theory of
coadaptation must also consider the biotic interactions that
influence the net benefits of behavioral and physiological strat-
* This paper was prepared as an overview of a symposium session presented at
“Animals and Environments,” the Third International Conference for Com-
parative Physiology and Biochemistry, Ithala Game Reserve, KwaZulu-Natal,
South Africa, 2004 (http://www.natural-events.com/ithala/default-follow_2.asp).
⫹
Corresponding author; e-mail: m-angilletta@indstate.edu.
Physiological and Biochemical Zoology 79(2):282–294. 2006. 䉷 2006 by The
University of Chicago. All rights reserved. 1522-2152/2006/7902-4148$15.00
egies. Such a theory will be challenging to develop because each
organism’s perception of and response to thermal heterogeneity
depends on its size, mobility, and life span. Despite the chal-
lenges facing thermal biologists, we have never been more
pressed to explain the diversity of strategies that organisms use
to cope with thermal heterogeneity and to predict the conse-
quences of thermal change for the diversity of communities.
Introduction
Forty years after Heath (1964) placed beer cans in the sun to
caution against a simplistic approach to the study of thermo-
regulation, thermal biology has become a thriving area of re-
search based on mathematical theories, sophisticated technol-
ogies, and model organisms. Much of this research is still
designed to help us understand the causes and consequences
of thermoregulation, but the evolution of thermal reaction
norms (for definitions of this and other thermal biology terms,
see Table 1) has also become a major focus. The core assump-
tions of thermal biology are (1) temperature is one of the most
pervasive state variables affecting biological processes, and (2)
the laws of thermodynamics define the direction and rate of
biochemical processes that underlie the performance of whole
organisms (Haynie 2001; Brown et al. 2004). Given these core
assumptions, thermal biologists have concluded that the en-
vironment exerts strong selective pressures on all organisms
and that knowledge of thermal biology is the key to explaining
many physiological, ecological, and evolutionary patterns.
Adaptive responses to thermal heterogeneity involve all levels
of biological organization from the expression of genes to the
behavior of the organism, but these responses occur on different
temporal scales (Fig. 1). We think of the interactions among
levels of organization that link these responses as a mechanistic
cascade, which flows from the biochemical to the organismal
levels and is nested within a feedback loop. In other words, the
expression of genes shapes the behavior of the organism, but
this behavior causes a change in physiological state that deter-
mines subsequent gene expression. Thus, the relationships
among thermal responses at various levels of organization are
likely to be complex, and thermal responses at biochemical
levels cannot be used to predict changes at higher levels of
organization (Huey and Stevenson 1979; Chaui-Berlinck et al.
2004). The challenge for biologists is to define the mechanistic
links between thermal responses at different levels and to iden-
tify their impact on fitness—in other words, to understand the
evolution of the mechanistic cascade.
Evolutionary Thermal Biology 283
Table 1: Definition of terms in thermal biology
Term Definition
Coadaptation The coevolution of traits within a population via natural selection
Developmental acclimation Irreversible plasticity of a physiological trait in response to an isolated environ-
mental variable, such as temperature, which is experienced during ontogeny
Eurythermy The ability to function over a broad range of body temperatures
Operative temperature The temperature of an inanimate object of zero heat capacity with the same
size, shape, and color as the animal
Seasonal acclimation Reversible plasticity of a physiological trait in response to a seasonal change in
an isolated environmental variable, such as temperature
Stenothermy The restriction of function to a narrow range of body temperatures
Thermal reaction norm A mathematical function relating environmental temperature (or body temper-
ature) to the phenotype expressed by a given genotype; includes thermal per-
formance curves, which describe the thermal sensitivities of behavioral or
physiological rates, and thermal tolerance curves, which describe thermal
sensitivities of fitness
Thermal sensitivity The slope (or derivative) of a thermal reaction norm
Thermoregulation The maintenance of a mean or variance of body temperature that differs from
the mean or variance of operative environmental temperatures, by means of
behavioral, physiological, or morphological strategies
Note. See Mercer (2001) for additional clarification of terminology.
At the organismal level, strategies for coping with thermal
heterogeneity vary along a continuum with two dimensions.
The first dimension describes the strategy of thermoregulation,
from organisms that maintain a nearly constant body temper-
ature despite thermal heterogeneity to those that conform to
environmental temperature. The second dimension describes
the strategy of thermal sensitivity, from organisms whose per-
formance is very sensitive to temperature (stenotherms) to
those whose performance is relatively insensitive to temperature
(eurytherms). All organisms fall somewhere within the contin-
uum bounded by these axes. Many endotherms, such as mam-
mals and birds, are thermoregulators that are stenothermic, but
many ectotherms also regulate their body temperature using
somewhat different mechanisms. Certain fish, such as carp, are
good examples of thermoconformers that are eurythermic. The
position of an organism along this continuum can be altered
by acclimation; in fact, an individual can be stenothermic dur-
ing specific seasons but eurythermic over the course of a year.
Finally, evolution by natural selection alters both acute and
acclimatory responses to temperature. Thus, ecological re-
sponses involve reversible or nonreversible forms of phenotypic
plasticity, and evolutionary responses involve a change in the
reaction norms of genotypes in a population (see Levins 1963
for a generalized discussion of these strategies).
Given that organisms have many options for dealing with
thermal heterogeneity, why does each species adopt certain
strategies over others? To answer this question, we must con-
sider the costs and benefits of each strategy in a range of en-
vironments; such considerations range from purely verbal mod-
els to complicated mathematical ones. Levins (1962, 1963) was
the first to advance models of evolution in heterogeneous en-
vironments, and many models of thermal adaptation were un-
doubtedly inspired by the work described in his classic book
(Levins 1968). Here, we review current models and draw on
recent studies of fish, reptiles, and amphibians to evaluate them.
We then combine the ideas generated from these models to
form a conceptual model of coadaptation that predicts the
optimal suite of strategies given mean, variance, and predict-
ability of environmental temperature. We argue that coadap-
tation is a unifying principle of thermal biology because it
emphasizes the simultaneous evolution of thermoregulation
and thermal sensitivities.
Adaptive Responses to Thermal Heterogeneity:
Theory and Evidence
When the temperature of the environment varies spatially and
temporally, one of four conditions must occur: (1) body tem-
perature is regulated by behavior and physiology; (2) body
temperature fluctuates, but performance is not impaired; (3)
body temperature fluctuates, and performance is initially im-
paired but is restored later by acclimation; or (4) body tem-
perature fluctuates, and performance is impaired and is not
restored by acclimation. As we shall discuss, any of these out-
comes could be adaptive in certain environments. Because each
outcome results from a combination of behavioral and phys-
iological strategies, natural selection should produce organisms
with suites of traits that are coadapted to the environment.
284 M. J. Angilletta Jr., A. F. Bennett, H. Guderley, C. A. Navas, F. Seebacher, and R. S. Wilson
Figure 1. A cascade of mechanisms operating from cellular to organismal
levels is responsible for adaptive responses to thermal heterogeneity.
These mechanisms alter commonly measured properties of organisms,
from gene expression to behavior, on different temporal scales.
Given the complexity of this process, how can we develop a
theory of coadaptation to explain the diversity of strategies that
are manifested in nature? To answer this question, we must
first consider existing theories of thermal adaptation and their
empirical support.
Thermoregulation
What factors determine the degree to which an individual
should thermoregulate and the mechanisms it should use to
do so? Huey and Slatkin (1976) modeled the optimal degree
of thermoregulation given energetic costs and benefits. They
assumed that the rate of energy gain was a unimodal function
of temperature. Although they modeled an energetic cost of
thermoregulation, they noted that other costs are certainly plau-
sible; for example, thermoregulators might incur a greater risk
of predation and fewer opportunities for territorial defense or
courtship, reducing fitness via survival and fecundity, respec-
tively. The model makes several predictions: (1) thermoregu-
lation should be greater in patchy environments, where thermal
heterogeneity enables heating and cooling with a low cost of
shuttling; (2) stenotherms should thermoregulate more care-
fully than eurytherms; and (3) individuals in colder environ-
ments should have a lower mean body temperature than in-
dividuals in hotter environments when all other factors are
equal.
Reptiles provide ample evidence that the costs and benefits
of thermoregulation influence the body temperatures of ani-
mals. Many species of diurnal lizards maintain relatively high
and constant body temperatures during activity, which tend to
maximize capacities for performance (Huey 1982; Hertz et al.
1983; Adolph 1990; Angilletta et al. 2002a). Anyone who
watched these lizards could appreciate the tremendous signif-
icance of behavioral mechanisms of thermoregulation, which
include shuttling between microhabitats, perching on objects,
and orienting the body toward solar radiation (Heath 1965;
Hertz and Huey 1981; Christian et al. 1983; Adolph 1990; Bau-
wens et al. 1996). Because solar radiation is the primary source
of heat for ectotherms, thermoregulation is presumably more
costly for species that are nocturnal or inhabit dense forests
(Huey 1974, 1982; Huey and Slatkin 1976). Indeed, body tem-
peratures of nocturnal geckos during activity are significantly
lower than those of diurnal lizards, even though these low
temperatures impede locomotor performance (Huey et al.
1989). For some species of geckos, relatively low body tem-
peratures during activity are undoubtedly caused by costs or
constraints imposed by nocturnal activity because the same
species maintain relatively high and constant body temperatures
in artificial thermal gradients (Huey et al. 1989; Angilletta and
Werner 1998). Some nocturnal geckos thermoregulate as ac-
curately and effectively during the day as diurnal lizards, par-
ticularly in late spring and summer, when considerable thermal
heterogeneity exists within and among sites of retreat (Kearney
and Predavec 2000; Rock et al. 2002). Transplant experiments
also reveal the influence of costs and constraints on thermo-
regulation. For example, Chamaeleo schubotzi, which inhabits
the foggy slopes of Mount Kenya (3,300 m), maintained its
preferred body temperature (33⬚C) for only an hour on clear
days and never approached this body temperature on most days
(Bennett 2005); yet, individuals transplanted to a lower ele-
vation near Nairobi (1,700 m) maintained body temperatures
above 30⬚C throughout the day (Fig. 2). These examples dem-
onstrate the profound flexibility of thermoregulatory behavior
in reptiles.
As predicted by theory, comparative studies over space and
time indicate that mean body temperatures of ectotherms are
lower in colder environments. Within species, this phenome-
non is manifested in one of two ways: individuals in colder
environments (1) maintain lower body temperatures while they
are active (Hertz 1981; Hertz et al. 1983; Van Damme et al.
1989; Adolph 1990; Grant and Dunham 1990; Christian and
Weavers 1996) or (2) maintain elevated body temperatures for
shorter durations each day (Angilletta 2001; Sears and Angilletta
2004). Despite these differences in behavior in natural envi-
ronments, preferred body temperatures measured in artificial
thermal gradients often do not differ among populations when
field body temperatures do (Van Damme et al. 1989; Angilletta
2001). Interspecific comparative analyses have provided mixed
support for the hypothesis that body temperatures will be lower
in colder environments. Among species of Chamaeleo, mean
body temperature decreased with decreasing minimal and max-
imal air temperatures (Bennett 2005). Among tropical species
of Sceloporus and Liolaemus, mean body temperature during
activity decreases by 1⬚C per 1,000 m of elevation (Andrews
1998; Navas 2002). Tropical anurans exhibit more pronounced
Evolutionary Thermal Biology 285
Figure 2. Thermoregulation by (A) native and (B) transplanted cha-
meleons (Chamaeleo schubotzi) in Kenya. Data are mean body tem-
peratures and mean operative temperatures measured in the sun and
shade; operative temperatures in the sun were measured with hollow
copper tubes painted white or black. A, Individuals in the native habitat
of Mount Kenya ( ) never attained body temperatures aboveN p 4
23⬚C. B, Individuals transplanted to Nairobi ( ) maintained bodyN p 6
temperatures above 30⬚C most of the day. Data are from A. F. Bennett
(unpublished manuscript).
elevational clines, with mean body temperature decreasing by
5⬚C per 1,000 m of elevation (Navas 2002). Yet, no elevational
trend in body temperature was evident among temperate spe-
cies of Sceloporus (Andrews 1998); this observation does not
necessarily contradict the prediction of theory because tem-
perate species in colder environments usually maintain pre-
ferred body temperatures for shorter durations per day (Sears
and Angilletta 2004). Thus, lizards in colder environments
maintain lower mean body temperatures over the course of
their lives.
Experimental studies of thermoregulation under perceived
risks of predation also support a model of thermoregulation
based on costs and benefits. Downes (2001) used chemical cues
to alter the perception of risk by garden skinks (Lampropholis
guichenoti) in experimental enclosures. Skinks surrounded by
a high density of scent markings became active later and became
inactive earlier than lizards surrounded by a low density of
scent markings. Consequently, the mean body temperature of
these skinks was lower and their growth was slower. Addition-
ally, velvet geckos (Oedura lesueurii) preferred warm retreats
in the absence of predators but chose cool retreats when warm
retreats were marked by the chemical cues of a predator
(Downes and Shine 1998). Clearly, the risk of predation and
its effect on body temperature depend on the specific mech-
anisms of thermoregulation. Behavioral mechanisms (e.g., shut-
tling and posturing) might make an individual more conspic-
uous to predators, whereas physiological mechanisms (e.g.,
shunting blood and changing color) might not increase risk.
Large reptiles can effectively exploit physiological mechanisms
of thermoregulation, but small reptiles could be forced to rely
largely on behavioral mechanisms (Bartholomew 1982; Dzi-
alowski and O’Connor 2004). Furthermore, the relationship
between thermoregulation and predation risk is complicated
because the ability of prey to escape predators probably depends
on body temperature (reviews in Hertz et al. 1988; Angilletta
et al. 2000b).
Thermal Sensitivity
When body temperature varies, natural selection is expected to
shape the thermal sensitivity of performance. The direction of
evolution should depend greatly on the manner in which an
individual’s performance contributes to its fitness. If perfor-
mance contributes additively to fitness (i.e., the sum of per-
formance over time determines fitness), stenotherms are fa-
vored under most patterns of temporal variation; eurytherms
are more fit than stenotherms only if environmental temper-
ature varies greatly among generations and little within gen-
erations (Gilchrist 1995). A greater degree of eurythermy, how-
ever, would be favored if environmental temperature changed
systematically with time (Huey and Kingsolver 1993). Thus,
the relative magnitude of variation within and among gener-
ations determines the optimal thermal sensitivity when per-
formance contributes additively to fitness. If performance con-
tributes multiplicatively to fitness (i.e., the product of
performance over time determines fitness), optimal thermal
sensitivities are determined more by variation within genera-
tions than by variation among generations; stenothermy is fa-
vored in constant environments, and eurythermy is favored in
variable environments (Lynch and Gabriel 1987). The generality
of these conclusions depends on the validity of a critical as-
sumption: an increase in performance at one or more tem-
peratures necessitates a decrease in performance at other tem-
peratures. In other words, a jack-of-all-temperatures is assumed
to be a master of none (Huey and Hertz 1984). This trade-off
between specialization and generalization, originally proposed
286 M. J. Angilletta Jr., A. F. Bennett, H. Guderley, C. A. Navas, F. Seebacher, and R. S. Wilson
Figure 3. Maximal growth rates (V
max
) of ancestral (filled circles) and
selected (open circles) populations of E. coli. Selected populations were
maintained at 37⬚C for 20,000 generations. Error bars are 95% con-
fidence intervals. Adapted from Cooper et al. (2001).
by Levins (1968), is a common assumption of evolutionary
theories in general.
Both comparative and experimental studies have shown that
eurythermy evolves far more often than predicted by theory.
Thermal sensitivities of growth rate have been compared among
populations of marine fish distributed along latitudinal clines.
If we assume that growth contributes additively to fitness, cur-
rent theory predicts that natural selection should produce
stenotherms that perform best at the mean water temperature.
In most cases, however, genetic divergence along latitudinal
clines has produced eurytherms that perform equally well or
better than stenotherms at any temperature (review in Angil-
letta et al. 2002b). These genetic differences among populations
persist despite considerable gene flow among populations
(Conover 1998), which suggests that natural selection can pro-
duce jacks-of-all-temperatures that are masters of all. Semi-
natural selection of E. coli under various thermal regimes has
provided mixed support for the theory of thermal adaptation.
Selection at 37⬚C during 20,000 generations improved fitness
at 27⬚–39⬚C but reduced fitness at extreme temperatures (Fig.
3). Nevertheless, a series of selection experiments with E. coli
(Bennett and Lenski 1999; Po¨rtner et al. 2006) and a compar-
ative study of Daphnia pulicaria (Palaima and Spitze 2004) have
shown that a trade-off between fitnesses at high and low tem-
peratures is not a necessary outcome of evolution. These com-
parative and experimental results cast doubt on the generality
of current theory.
One possible explanation for the lack of thermal speciali-
zation within natural populations is that physiological perfor-
mances contribute both additively and multiplicatively to
fitness. Consider the number of genes that must underlie a
complex trait such as growth rate. Some fraction of these genes
could also code for proteins that enhance maintenance, repair,
and, hence, survival. Such genes would cause growth rate to
evolve in correlation with thermal tolerance. Because environ-
mental temperature tends to vary more at higher latitudes,
natural selection should produce broader thermal tolerances at
these locations (e.g., van Berkum 1988). Thus, correlated evo-
lution of thermal sensitivities of growth rate and thermal tol-
erance might explain the countergradient variation observed in
fish (Conover and Schultz 1995). Selection experiments can be
used to explore potential genetic correlations between the tol-
erance of extreme temperatures and performance at less ex-
treme temperatures (Mongold et al. 1999). The identification
of mechanistic cascades that produce variation in organismal
performances would shed light on the network of genes shared
between performance and tolerance.
Acclimation of Thermal Sensitivity
Many ectotherms modify thermal sensitivities of performance
throughout their lifetimes. These modifications can be non-
reversible responses to temperatures experienced during on-
togeny (developmental acclimation) or reversible responses to
gradual changes in temperature among seasons (seasonal ac-
climation). The distinction between developmental and sea-
sonal responses is important when discussing the evolutionary
significance of phenotypic plasticity (Kingsolver and Huey
1998). Both developmental and seasonal acclimation involve a
cascade of processes, which can include the detection of en-
vironmental signals, a signal transduction pathway (or path-
ways), and the activation of the production machinery of the
cell (e.g., structural genes, polymerases, ribosomes) leading to
a change in physiology. During developmental acclimation, the
process involves morphogenesis that is irreversible. Small effects
of developmental temperature early in ontogeny can lead in-
directly to larger effects on the phenotype later in ontogeny.
Thus, developmental acclimation can produce changes that are
distinct from those observed during seasonal acclimation of the
same physiological systems (I. A. Johnston and R. S. Wilson,
unpublished data).
Precht (1958) divided patterns of acclimation into five cat-
egories based on the degree to which the rate of performance
is maintained during environmental change; these categories
are overcompensation, perfect compensation, partial compen-
sation, no compensation, and inverse compensation. All of
these responses have been interpreted as adaptive strategies for
coping with thermal fluctuations (Huey and Berrigan 1996).
For example, when faced with seasonal cooling, an ectotherm
can (1) slow physiological capacity by submitting to Q
10
effects
(e.g., O’Steen and Bennett 2003); (2) depress physiological ca-
pacity by enhancing thermal effects (e.g., St. Pierre and Boutilier
2001); or (3) offset Q
10
effects by maintaining capacities through
partial compensation, perfect compensation, or overcompen-
sation (e.g., Rome et al. 1984; Guderley and St. Pierre 1999).
Evolutionary Thermal Biology 287
Patterns of acclimation are enriched by nature’s complexity;
for example, when environmental warming is accompanied by
a depletion of resources (e.g., food, oxygen), some ectotherms
initiate a metabolic depression that alleviates Q
10
effects (Hand
and Hardewig 1996; de Souza et al. 2004; review in Guppy and
Withers 1999). The presumption that these compensatory re-
sponses enhance the fitness of an organism is known as the
beneficial acclimation hypothesis (Leroi et al. 1994).
Critics of the adaptationist program noted alternatives to
adaptive explanations for acclimatory responses (Garland and
Carter 1994; Feder et al. 2000), and others argued that the
evolutionary significance of such responses has rarely been es-
tablished (Huey and Berrigan 1996; Kingsolver and Huey 1998;
Huey et al. 1999). Huey et al. (1999) encouraged the application
of strong inference (Platt 1964) and advanced four hypotheses
as alternatives to the beneficial acclimation hypothesis. Al-
though we agree that strong inference is a powerful approach,
we contend that current hypotheses have limited power to in-
crease our understanding of the evolution of acclimation. First,
these hypotheses stem from verbal models that consider isolated
mechanisms rather than quantitative models that consider mul-
tiple causality; for example, the hypothesis that “colder is
better” is based on the common observation that organisms
reach larger body sizes at lower temperatures, whereas the hy-
pothesis of developmental buffering is based on a mechanism
that is independent of body size (Huey et al. 1999). Because
these hypotheses are not mutually exclusive and neither leads
to quantitative predictions about the magnitude of acclimation,
one cannot easily design crucial experiments to distinguish be-
tween them (see Quinn and Dunham 1983). More importantly,
these hypotheses do not stem from an explicit consideration
of the variance and predictability of environmental tempera-
ture. A quantitative model, however, would provide the explicit
analysis of costs and benefits that is needed to predict the
optimal capacity for acclimation given the mean, variance, and
predictability of environmental temperature. Furthermore,
such a model would enable investigators to make a priori pre-
dictions about the acclimation of thermal sensitivity when mul-
tiple mechanisms (or constraints) are involved.
Currently, only one quantitative model can be used to infer
the optimal acclimation of thermal sensitivity. This model, con-
structed by Gabriel and Lynch (1992), describes the evolution
of an environmental tolerance curve, which can be thought of
as the relationship between temperature and fitness. As with a
performance curve, a tolerance curve can be characterized by
an optimum and a breadth. The model predicts that the net
benefit of acclimation increases with increasing variation in
body temperature among generations and decreasing variation
in body temperature within generations. This result, however,
follows from the fact that fitness is zero if body temperature
falls outside of the tolerance curve at any point during the life
of an organism (i.e., once you’re dead, you’re dead). The op-
timal acclimation of performance curves would differ quali-
tatively from that of tolerance curves if performance contributes
additively to fitness rather than multiplicatively (see “Thermal
Sensitivity”).
Despite the limitations of current theory, experimental stud-
ies of acclimation have generally rejected the beneficial accli-
mation hypothesis (Leroi et al. 1994; Zamudio et al. 1995; Huey
and Berrigan 1996; Bennett and Lenski 1997; Huey et al. 1999;
Gibert et al. 2001). Given that these studies used rigorous ex-
perimental designs to test and reject a long-held assumption
within evolutionary physiology, they confirm the need to crit-
ically evaluate adaptive explanations for phenotypic plasticity.
Much of the rigorous nature of these experiments was afforded
by the careful selection of model organisms, such as E. coli and
Drosophila melanogaster. Huge numbers of replicates, short
generation times, and comparatively simple procedures of
maintenance were all important advantages of using these spe-
cies. In the majority of these studies, however, organisms were
raised at different temperatures for one or more generations.
A consequence of this experimental design was that reversible
and irreversible forms of acclimation might have been con-
founded (Wilson and Franklin 2002).
Our understanding of acclimation comes mostly from hun-
dreds of descriptions of seasonal acclimation and its underlying
mechanisms (Prosser 1979). Although recent experiments have
focused on developmental acclimation in organisms with short
generations, the benefits of seasonal acclimation still remain to
be investigated (Guderley and St. Pierre 2002; Wilson and
Franklin 2002). This gap in our understanding of acclimation
is surprising when one considers that many model organisms
in thermal biology have generations that span one or more
years and are therefore routinely exposed to seasonal changes
in temperature. One key to better understanding the evolution
of either developmental or seasonal acclimation will be the
careful selection of a trait that has a clear connection to survival
or reproduction. For example, Wilson and Johnston (2005)
studied the thermal acclimation of mating success of males of
Gambusia holbrooki. Males of this species copulate entirely
through sneaky encounters because females always resist mat-
ing. When tested at 18⬚C, males acclimated to this temperature
swam faster, maneuvered better, and had greater mating success
than males acclimated to 30⬚C; the converse was true for tests
conducted at 30⬚C (Fig. 4). Because mating success is likely to
correlate strongly with fitness, this experiment provides some
evidence for the benefits of seasonal acclimation.
Even when compensation would seem beneficial, failure to
compensate perfectly could reflect costs of acclimation (Hoff-
mann 1995; Guderley 2004). Acclimation of thermal perfor-
mance curves would seem beneficial if (1) fluctuations in tem-
perature within generations are predictable, (2) the time lag
required for compensation is short relative to the rate of change
in temperature, and (3) the energetic or survival cost of com-
pensation is less than the loss of energy or reduction of sur-
vivorship that is caused by a failure to compensate (see DeWitt
288 M. J. Angilletta Jr., A. F. Bennett, H. Guderley, C. A. Navas, F. Seebacher, and R. S. Wilson
Figure 4. Effect of thermal acclimation on the number of copulations
obtained by males of Gambusia holbrooki at 18⬚ and 30⬚C. Copulations
were recorded during 5 min of exposure to two females in an aquarium.
Significant differences were detected between groups at both test tem-
peratures ( for each group). Data are . AdaptedN p 20 means Ⳳ SE
from Wilson and Johnston (2005).
et al. 1998). Perfect compensation of performance is costly
because of the time and energy required to synthesize new
enzymes, modify membranes, and redistribute resources. For
example, compensation of muscular function during exposure
to low temperature can involve increases in the concentrations
of enzymes (Sa¨nger 1993), the expression of myosin isoforms
(Johnston and Temple 2002), the fluidity of cellular membranes
(Hazel 1995), and the oxidative capacity or volume of mito-
chondria (Guderley and St. Pierre 1999). These changes require
time as well as energy; for example, the compensatory response
of rainbow trout (Oncorhynchus mykiss) is biphasic and requires
a minimum of 6 wk to stabilize (Bouchard and Guderley 2003).
Beyond the obvious costs of producing these changes, the en-
ergetic cost of “primed” mitochondria and the deleterious ef-
fects of the reactive oxygen species generated during electron
transport are additional costs of compensation (review in Gud-
erley 2004). Furthermore, natural covariation between tem-
perature and other resources can enhance the costs of com-
pensation. A seasonal decrease in temperature is usually
accompanied by a reduction in the availability of food, which
could favor reverse compensation rather than partial or perfect
compensation (Clarke 1993). Indeed, the nutritional state of
an animal has marked effects on the aerobic and glycolytic
capacities of its muscles (Pelletier et al. 1993a, 1993b; Dutil et
al. 1998). More effort must be expended to determine the net
benefits of acclimation in natural environments (Huey and Ber-
rigan 1996), and cooperation between physiologists and ecol-
ogists will be invaluable in this undertaking (Kingsolver and
Huey 1998).
A Theory of Coadaptation
Although the coadaptation of thermoregulation and thermal
reaction norms has been appreciated for over 20 yr (Huey and
Slatkin 1976; Huey and Bennett 1987), this appreciation has
not led to an understanding of why some organisms modify
behavior, physiology, and biochemistry in certain combina-
tions. Consider the two most commonly tested hypotheses re-
garding thermal coadaptation: (1) the mean (or preferred) body
temperature of an organism should match the thermal opti-
mum for performance, and (2) the variance in body temper-
ature should correlate with the thermal performance breadth.
These predictions deal with covariation between phenotypes
but say nothing about which phenotypes should be observed
in a given environment. Do some organisms, such as tropical
anurans (Navas 1996), use mainly biochemical modifications
of thermal sensitivity because the cost of thermoregulation is
too high? Are other organisms, such as temperate lizards (Sears
and Angilletta 2004), more likely to use thermoregulation be-
cause its costs are lower in their environments? And what are
the causes of variation along this continuum within major
groups of ectotherms?
Currently, no theory of coadaptation links phenotypic strat-
egies to thermal environments because models of thermoreg-
ulation assume a thermal reaction norm and models of thermal
reaction norms assume a profile of body temperatures. Optimal
thermal reaction norms depend on temporal variation in body
temperature (Huey and Kingsolver 1993; Gilchrist 1995). The
benefit of thermoregulation depends on thermal reaction
norms for all phenotypes that contribute to fitness; benefits are
high for thermal specialists and low for thermal generalists
(Huey and Slatkin 1976; Huey 1982). Each body of theory
makes assumptions about the other; therefore, one must view
the evolution of thermoregulation and thermal sensitivities of
performance as a coadaptive process (Huey and Bennett 1987).
Current theories enable us to understand the covariation be-
tween thermoregulation and thermal physiology, but they do
not enable us to predict which suites of traits will evolve in
particular environments.
How can one unify current theories of thermal adaptation
to produce a more powerful theory of coadaptation? We start
by offering a conceptual model, which can be further developed
quantitatively. Two assumptions pervade current theories
(Huey and Kingsolver 1989): (1) a jack-of-all-temperatures is
a master of none (i.e., a trade-off exists between performance
at a given temperature and the thermal breadth of perfor-
mance), and (2) hotter is better (i.e., performance at the ther-
mal optimum is greater when the thermal optimum is higher).
If the first assumption is valid, a stenotherm with a constant
body temperature that is equal to its thermal optimum should
have a higher fitness than a eurytherm with any distribution
of body temperatures (Gilchrist 1995). If the second assump-
tion is valid, a stenotherm with a high and constant body
Evolutionary Thermal Biology 289
Figure 5. Conceptual model illustrating how thermoregulation and the thermal sensitivity of performance coevolve in ectotherms.
temperature should have a higher fitness than a stenotherm
with a low and constant body temperature. Using these two
assumptions, we can predict the strategies produced by coad-
aptation. In the simplest case, an organism in a stable envi-
ronment obviously must thermoconform and should be a spe-
cialist for the modal temperature (see Janzen 1967). But what
about organisms in variable environments? Here, the cost of
thermoregulation might be the primary driver of coadaptation
(Fig. 5). Environments in which the cost of thermoregulation
is low will favor specialists that thermoregulate precisely. The
preferred body temperature (or preferred range of body tem-
peratures) should depend on the cost-benefit ratio of ther-
moregulation, the effect of temperature on absolute perfor-
mance (i.e., whether hotter truly is better), and physical
constraints on the stability of cellular and molecular structures.
Alternatively, environments in which the cost of thermoregu-
lation is high will favor either specialists or generalists that
thermoconform; organisms whose generation is long should be
specialists, whereas organisms whose generation is short should
be generalists. This conclusion follows from the fact that the
optimal thermal sensitivity is determined by the relative mag-
nitude of within-generation versus among-generation variation
in temperature (see “Adaptive Responses to Thermal Hetero-
geneity”). Note that eurythermy on a generational scale might
be achieved by developmental plasticity or acclimatization,
which would appear to be stenothermy on a shorter temporal
scale. If a trade-off between specialization and generalization
is not universal, the process of coadaptation might be more
complex. Yet, our current understanding of biochemical ad-
aptation (Hochachka and Somero 2002; Guderley 2004) leads
us to conclude that this trade-off must occur at the biochemical
level, even if it can be masked at the organismal level (see
Angilletta et al. 2003).
Putting the Game into Theories of Thermal Adaptation
Evolutionary thermal biologists have made great strides in dis-
covering the processes that operate at or below the organismal
level but have generally underappreciated the biotic arena in
which organisms employ their behavioral and physiological
strategies. This oversight is hardly punishable, considering that
ecologists have only just begun to appreciate the role of en-
vironmental temperature in shaping the dynamics of com-
munities (Panikov 1999; Rooney and Kalff 2000; Al-Rabai’ah
et al. 2002; Garvey et al. 2003; McClanahan and Maina 2003;
Genner et al. 2004). In nature, temperature is likely to influence
the quantity and quality of competitors, predators, and mu-
tualists. These other players must also find strategies for coping
with thermal heterogeneity while dealing with their own set of
competitors, predators, and mutualists. The result is a rich web
of interactions among species that must ultimately shape the
process of thermal coadaptation within species (see Magnuson
et al. 1979).
This game-theoretic perspective offers more than a macro-
scopic view of thermal adaptation. Indeed, the interactions
among species are likely to produce emergent phenomena that
differ qualitatively from the predictions of current theories (e.g.,
Davis et al. 1998). In other words, one cannot understand
thermal adaptation in a community of species by studying the
evolution of each species in isolation. We draw this conclusion
for two reasons: (1) the net benefits of thermoregulation and
thermal acclimation depend on the strategies adopted by other
290 M. J. Angilletta Jr., A. F. Bennett, H. Guderley, C. A. Navas, F. Seebacher, and R. S. Wilson
Figure 6. Variation in environmental temperature is perceived differently by each species in a community. Species that live one or more years
experience more variation within generations than they do among generations, whereas those that live only a few weeks experience more
variation among generations than within generations. This point is illustrated by data from Oak Ridge, Tennessee (36⬚00⬘05⬙N, 84⬚14⬘56⬙ W;
elevation 266 m), recorded by the National Oceanic and Atmospheric Administration. The effect of generation time is shown by expanding
several periods of the year 1999, ranging from 6 wk (oval frame) to the entire year (rectangular frame).
organisms, and (2) species within a community are expected
to have different thermal sensitivities of performance. The first
point should be obvious from studies of thermoregulation un-
der perceived risks of predation (see “Adaptive Responses to
Thermal Heterogeneity”). Whether predators are capable of
activity under a thermal condition affects the cost of ther-
moregulation by their prey (Huey and Slatkin 1976; Huey
1982). The same coevolutionary dynamic applies to seasonal
acclimation; whether a species should compensate for seasonal
changes or submit to a decrease in physiological function de-
pends on whether their predators and prey are doing so because
the net benefit of compensation depends on the availability of
resources (Clarke 1993). The expectation that species in a com-
munity will have different thermal sensitivities of performance
follows from the recognition that all species perceive the ther-
mal environment differently. For example, consider an envi-
ronment in which temperature cycles daily and annually (Fig.
6). Species with generations of a few weeks (or less) will ex-
perience less variation within generations and more variation
among generations; moreover, variation among generations will
be unpredictable because temperature fluctuates stochastically
within seasons (hence the terms “cold snap” and “heat wave”).
Species with generations of a few months will experience mod-
erate variation within and among generations; however, vari-
ation among generations will be caused by predictable changes
in season. Finally, species with generations of a year or more
will see more variation within generations than among gen-
erations; much of the variation within generations will be
caused by predictable changes in season. Spatial variation is
also perceived differently because small and large species at the
same location can have very different body temperatures (Ste-
venson 1985); this problem is exacerbated by differences in
mobility between small and large species (or between plants
and animals; Bradshaw 1972; Huey et al. 2002). These differ-
ences in the perception of temporal and spatial variation among
species should influence the evolution of thermal sensitivities
and acclimatory responses and hence should have consequences
for the ecological and evolutionary dynamics of communities.
The Need for Immediate Progress in Evolutionary
Thermal Biology
A theory of thermal coadaptation should have impacts beyond
the realm of basic science. Over 99% of all organisms are ec-
tothermic, and global climate change has and will continue to
pose thermal challenges to these organisms. On a regional basis,
some environments have warmed by as much as 2⬚Cinthe
last 30 yr, while other environments have cooled by a similar
degree (Walther et al. 2002). These thermal changes have altered
the growth, phenology, and distribution of many plants and
animals (Atrill and Power 2002; Beaugrand et al. 2002; Walther
et al. 2002; Parmesan and Yohe 2003). Because temperature
Evolutionary Thermal Biology 291
affects many traits that determine the interactions among spe-
cies (Garvey et al. 2003; Jiang and Morin 2004), the structure
and dynamics of communities will likely be perturbed by global
climate change. These perturbations will be particularly prob-
lematic when responses to thermal change are asynchronous
among species whose interactions are normally in a dynamic
equilibrium (e.g., Fitter and Fitter 2002).
The development of a game theory of thermal coadaptation
could offer a major advantage to applied ecologists. Although
great effort has been expended to understand the ecological
consequences of global climate change, the evolutionary con-
sequences remain less clear. Yet, evolutionary responses will
determine the interactions among organisms in future ecosys-
tems. This interplay between ecological and evolutionary re-
sponses will be complex because certain species will evolve more
rapidly than others. Knowledge of the rates and magnitudes of
potential evolutionary responses could help us to assess the
long-term consequences of global climate change. Thus, a game
theory of thermal coadaptation might ultimately lead to insights
that will enable us to manage biodiversity successfully in the
coming decades.
Acknowledgments
We thank S. Morris and A. Vosloo for organizing the Third
International Congress of Comparative Physiology and Bio-
chemistry. Participation by M.J.A. was made possible by an
international travel grant from Indiana State University. A.F.B.,
H.G., and C.A.N. were supported by grants from the National
Science Foundation (IBN0091308), Natural Sciences and En-
gineering Research Council, and Fundac¸a˜o de Amparo a`
Pesquisa do Estado de Sa˜o Paulo (03-01577-8), respectively.
R.S.W. was supported by a grant from the University of Queens-
land and a discovery grant from the Australian Research Coun-
cil. We thank R. Huey for providing thoughtful comments on
a previous version of the manuscript.
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