Integrating Thermal Physiology and Ecology of Ectothenns:
A Discussion of Approaches
Department of Zoology NJ-15, University of Washington, Seattle, Washington 981 95
AND
Centerfor Quantitative Science in Forestry, Fisher2e.r and WildlifP HR-20, Universlty of
Washington, Seattle, Washington 98 195
SYNOPSIS. An understanding of interactions between the thermal physiology and ecology
of ectotherms remains elusive, partly because information on the relative performance of
whole-animal physiological systems at ecologically relevant body temperatures is limited.
After discussing physiological systems that have direct links to ecology (e.g., growth,
locomotor ability), we review analytical methods of describing and comparing certain aspects of performance (including optimal temperature range, thermal performance
breadth), apply these techniques in a n example o n the thermal sensitivity of locomotion in
frogs, and evaluate potential applications.
INTRODUCTION
Body tetnperature (Th) profoundly affects the ecology of ectotherms by influencing both physiology and behavior. T h e
effects of temperature on many physiological systems are known (Dawson, 1975),
and the responses used by amphibians and
reptiles in regulating Th a r e well established (Cowles a n d Bogert, 1944; Bratts t r o m , 1963; H e a t h , 1965; Lillywhite,
1970). An understanding of the interactions between physiological performance
and ecology is, however, still elusive (Huey
and Slatkin, 1976). This gap partly results
from a surprising lack of information on
whole-animal physiological systems (e.g.,
growth, locomotion, reproductive output)
that have direct links to ecology and from
the difficulty of defining a n d estimating
statistics (e.g., optimal temperature range,
thermal perfortnance breadth) that characterize the thermal sensitivity of these responses. In this paper we enumerate some
ecologically relevant physiological systems,
review methods of describing their therand dismal sensitivity with an examile.
,
cuss ecological problems that can be attacked by similar approaches.
O u r interest in iliermal physiology and
ecology evolved from field studies o n temp e r a t u r e regulation in lizards. Certain
species regulated precisely only in habitats
where the potential costs (time a n d energy)
or risks (predation) of' raising T, appear
low (Ruibal, 1961; DeWitt, 1967; Regal,
1967; Hertz, 1974; Huey, 1974; L,ister,
1976), suggesting that the behavior of
lizards cannot be understood solelv from
physiological considerations.
Huey and Slatkin (1976) formalized the
'
We thank A. F. Bennett, M. E. Feder, S. S. Hillman,
A. R. Kiester, P. Licht, E. P. Smith, S. C. Stearns, C. R.
Tracy, D. B. Wake, and E. E. Williams for discussions.
We thank P. E. Hertz, W. W. Reynolds, S. C. Stearns,
F. van Berkum, a n d reviewers f o r constructive
suggestions o n the manuscript. H. B. Lillywhite and
0. E. Greenwald kindly provided original data. R. B.
H. thanks W. W. Reynolds for the opportunity to
participate in the symposium on Thermoregulation
in Ectotherms. Page charges were supported by
N.S.F. Grant PCM 78-05691 to W. W. Reynolds. Research supported by N.S.F. Grant GB 3773 1X to E. E.
Williams, by the Miller Institute for Basic Research in
Science, t h e Museum of Vertebrate Zoology, t h e
GI-aduate School Research Fund, and N.S.F. Grant
DEB 78-12024 to R.B.H.. and by the College of Forest
Resources toR.D.S.
view that thermoregulatory behavior
should reflect a com~romisebetween the
benefits and the associated costs or risks of
temperature regulation and then derived a
cost-benefit model with three Darameters
(the benefit at various Tb, the frequency
distribution of environmental temperatures in a habitat at a given time, and the
cost to achieve particular T,). This model
predicts, for example, the extent of temperature regulation that maximizes energy
gain or the relative advantages of thermal
generalists us. thermal specialists (eurytherms, stenotherrns).
In attempting to esti~natethe physiological benefits of Tb, these or related analyses
confront serious proble~ns.First, the available data on physiological effects of T b ,
which have been gathered to determine
the physiological significance of the preferred Tb (the Tb selected in a laboratory
thermal gradient; Licht et al., 1966), are
usually focused on tissue or cellular systems (Dawson, 1975) rather than on
whole-animal systems, which are ecologically more relevant (Bartholornew, 1958).
Second, important descriptive statistics
such as the physiologically "optimal" T,
(herein defined as the best-performance
Tb; Fig. 1) or the "thermal performance
breadth" (herein defined as the range of
Tb over which an animal performs well;
Fig. 1) are normally estimated indirectly
(e.g., inferring optimal Tb from preferred
Tb). These estimates can be useful as first
approximations, but have limitations
(Huey and Slatkin, 1976; Reynolds, 1977;
Beitinger and Fitzpatrick, 1979): most importantly, such estimates convey no information on the relative physiological disadvantage of activity at other Tb.
A 1~ a r t i asolution
l
to these difficulties was
pioneered by several biologists (Moore,
1939; Fry and Hart, 1948; Brett, 1971).
Basicallv. one measures an animal's Derformance over a broad spectrum of T, and
then fits a curve to these performance
data. One can then estimate o~tirnalT,..,,
thermal performance breadth, or relative
performance at any Tb from these curves.
These procedures and their applications
are the subjects of this discussion.
i
ECOLOGICALLY INTERPRETABLE PHYSIOLOGICAL
SYSTEMS
Although ecologists and physiologists
are keenly interested in thermal biology,
they usually have different goals. Consider
their contrasting approaches to studies on
locomotion. T o an ecologist, the thermal
sensitivity of locomotion is critical for
evaluating an animal's ability to capture
prey, escape predators, and interact socially. T o a physiologist, the thermal sensitivity of this whole-animal activity provides a baseline for focusing ever sharper
on the mechanisms of thermal adaptations
at the tissue, cellular, and biochemical
levels.
Our contention here is that attempts to
integrate physiology and ecology should
usually rely o n studies of whole-anzmal
functions rather than of tissue or cellular
activities (Bartholomew, 1958). In other
words, a study on acceleration is more di"op/~'rna/"fernperafore
7
rectly related to ecological performance
than is a study on the rapidity of muscle
contraction (the latter is, of course, appropriate for mechanistic evaluations). Licht
(1967) discovered, for example, a classic
case where biochemical data appear
ecologically misleading: the "optimal"
temperatures for alkaline-phosphatase activity were above the lethal temperatures
for some of the lizards he studied!
From this intentionally restricted perBody T e m p e r a t u r e
spective, examples of whole-animal acFIG. 1 . Hypothetical performance curve of an ec- tivities that should make significant contributions to fitness include growth rates
totherm as a function of body temperature.
Body Temperature,
OC
FIG. 2. A. Growth (g/wk) of HuJo boreus juvenile>
during third week since metamcrrphosis (from Lillywhite el nl., 1973). B . Percentage o f strikes b!
Body Temperature, OC
gopher snakes (Pituophis melarroleuci~~)
that resulted in
caprure of a mouse (from Greenwald, 1974). Curves
fur both graphs fitted by eye.
(Fig. 2A), digestive efticierlcies and rates, (or degree of thermal specialization), and
healing from injury, surviving disease, pre- the tolerance range (Fry et nl., 1946), with
dation success (Fig. 2B) and avoidance, associated upper and lower threshold o r
maximum acceleration or velocity, agility, lethal temperatures. When completeness is
metabolic scope, rate of egg PI-oduction, required, fitting a curve to performance
and social dominance. Desvite the irnvres- data allows specification of predicted persive variety and quality of studies on the formance at any Tb (Huey, 1975).
These measures differ in physiological
physiological significance of temperature
regulation at tissue or lower levels (Dawson, significance. Optimal temperatures a n d
1975), information on whole-animal per- thermal performance breadth describe
formance is scattered and [-are (p.g., ~ o o r e , temperatures a t which animals perform
1939; Awry, 197 1; Lillywhite ~ tal., 1973; ''he~t''
or ' L ~ ~ ~respectively,
lI,"
and are closely
Greenwald, 1974; Huey, 1975; Kluger, related to the physiological concept of
1978; Bennett, 1978, unpublished data; capacity adaptation (Precht (jt al., 1973). In
Waldschmidt. 1978: Tracy. u n ~ u h l i s h e d contrast, the tolerance range estimates the
data). A major and immediate goal of re- range of temperatures over which uny activity or survival is possible, and is thus research in this area rnust be to fill this gap.
lated to thc concept of resistance adaptation
(Precht rt al., 1973).
DESCRIBING THERMAL SENSITIVITY
These measures differ in ecological
significance as well. Thermal performance
breadth is relevant to the i m p o r t a n t
Many physiological systerns show maxi- ecological concept of niche width (Roughmum resDonse at intermediate Th and re- garden, 1972). Threshold or lethal temduced response at higher or lower T, (Figs. peratures set absolute limits on where or
1, 2. 3). Similar responsc curves approxi- when animals can survive (Porter a n d
mate the performance of many systems Gates, 1969; Heatwole, 1970; Spellerberg,
(Brett. 197 1 ).
1972c~,1973). Flowever, lizards are rarely
To characterize the thermal sensitivity of active a t near-threshold TI,, except in
such systems, we need at least three de- emergencies (DeWitt, 1967). For example,
scriptive measures (Fig. 1): the "optimal" the difference between the maxirnurrl Th
t e m p e r a t u r e ( o r optirrlal t e m p e r a t u r e ever recorded for active individuals and the
range), the therrnal performance breadth upper T, at loss of coordination (Critical
'
1
360
Y R. D. STEVENSON
R. B. H ~ J EAND
their optimal T, was altered by the subsequent realization that field Tb9sreflect a
compromise between physiology and ecology (SoulC, 1963; Licht et al., 1966; DeWitt,
1967; Regal, 1967; Huey, 1974). Workers
then often substituted the "preferred" Tb
of lizards in laboratory thermal gradients
(Licht et al., 1966). With some exceptions,
many tissue and cellular functions do proceed fastest near the preferred Tb (Dawson, 1975). Nevertheless, preferred Tb
may be altered by time, hormonal o r
B o d y lernperolure. ' C
physiological state, and behavioral context
(Huey and Slatkin, 1976; Reynolds, 1977),
FIG. 3. Distance jumped by Rana clamitans as a
function of T b (from Huey, 1975; see Appendix I).
suggesting that the preferred Tb is someThe fitted curve is a product exponential (see Apwhat labile and may also reflect a compendix 11).
promise between physiology and ecology.
More importantly, as noted above, preThermal Maximum) for 33 species of ferred T, conveys no information about
lizards is 6.0&0.58"C, range = 1.O0- 19.4"C the actual disadvantages to an animal of
(calculated from Heatwole, 1970) and the being active at any other Tb. However,
difference between the minimum T b ever when direct measures of physiological perrecorded for active lizards and the lower Tb formance are unavailable or impractical,
at loss of coordination (=Critical 'Thermal preferred Tb is probably the most meanMinimum) for 4 species of lizards is even ingful measure of thermal behavior
larger (12.8-t1.21°C, range = 10.2" - (Reynolds, 1977) and may also provide
15.3"C: calculated from Spellerberg, important insight into the nature of be1972a,b). Because activity Tbare thus very havioral integration.
different from threshold T,, the cessation
In contrast, tolerance range can be diof activity before reaching near-threshold rectly measured by calculating the differtemperatures is probably not a result of ence between the Critical Thermal Maxiavoiding such temperatures. We believe mum and Minimum (Moore, 1939; Kour
that this cessation is instead related to the and Hutchinson, 1970; Spellerberg,
general decline in physiological perform1972a, Snyder and Weathers, 1975). Fewer
ance at non-optimal T b (Fig. 1). [Extremely measures of performance breadth as imhigh-temperature ectotherms like Dip- plied herein have been suggested, partly
sosaurus dorsalis may, however, be excep- because perf.ormance breadth is intions.] Thus tolerance limits seemingly frequently distinguished from tolerance
have less relevance to temperature regula- range and partly because the renewed attion per se or to the day-to-day activities of tention to the theoretical significance of
ectotherms than d o optimal temperatures niche width is recent (Janzen, 1967;
or thermal performance breadths (Bar- Brattstrom, 1968; Levins, 1969; Kour and
tholomew, 1958: Warren, 1971; Huey, Hutchison, 1970; Ruibal and Philibosian,
1970; Huey and Slatkin, 1976; Lister,
1975; Feder, 1978; Humphreys, 1978: but
1976; Hertz, 1977; Huey, 1978; Feder,
see Spellerberg, 1973).
1978). Most field or laboratory measures
are imprecise or rely o n untested assumptions (Huey and Slatkin, 1976, p. 370). The
use of tolerance range to estimate performance breadth not only confounds the
The a priori assumption of early workers important physiological and ecological
(e.g., Cowles and Bogert, 1944) that the distinctions between these measures
mean T, of field-active lizards represents (above), hut may also be unreliable. For
tions, o n e can c o m p a r e t h e relative
breadth of ranges among populations.
Methods fbr estimating whether one range
is hotter than another will be suggested
below in the discussion on comparing optimal temperature ranges.
@timn( terr~fieratureus. optirnnl tenzperature
mnge. While many of' us casually refer to
"the optimal temper-ature" of an animal, we
should probably I-eferinstead to its optimal
temperature I-ange (see Heath, 1965). 'l'he
continuity of Inany physiological systems
strongly implies a zone of temperatures
within which perfornlance does not
change substantially (Fig. 1). T h e width of
this temperature-insensitivc zone has profound implications for- ecological and behavioral analyses (Huey and Slatkin, 1976)
and even for selection of an appropriate
statistical method for comparing optima.
We should therefore initially determine
whether an individual has an optimal temperature or- an optimal temperature range.
First, we might determinc the mean and
variance of' the anirnal's performance at
each of several test temperatures (Fig. 3).
Then we might determine the number of
test temperatures in the maximal perforrnance range that are statistically identical. A consistent pattern of insignificant
differences
among three o r more intervals
Direct ntrnszires of descrifiiiz~~
.rtcltistics
implies a broad optimal t e m p e r a t u r e
Optimal temperatures and thermal per- range. Statistical identity of only two temformance widths can be estimated bv peratures, which could indicate either that
measuring the performance of arl animal an optimal range exists or that the optimal
over a spectrum of Tband fitting a curve to temperature is intermediate between the
the data. T o exemplify this procedure, we two test temperatures, is ambiguous. For
use some preliminary data (Fig. 3, frorn Rana claniita?z.r (Fig. 3),jumps at 15°C and
Huey, 1975) on the acute effect of T,, on 20°C d o not diff'er significantly. T h e temdistance jumped (Appendix I) by a green peratur-e intervals (5°C) in this study were
frog (Rnna clnrnita7z.c) and fit these data to a large, so thesc data are somewhat ambiguproduct-exponential equation (Appendix ous. Nonetheless, the general jumping
11). [When possible, data should be fitted pattern suggests a broad optimal temperto a theoretical cur-ve. In the absence of ature range.
When an optimal temperature exists,
such a curve, as is the case here, standard
curve-fitting procedures should be fol- one can esti~natcthe optimal 'I,,> by I )
selecting tlle single best performance TI,
lowed. I
The1-ma1 tol~rnnrrm n g e . C:urvc fitting is (c..g., by ANOVA); 2) selecting the midnot reclirired; ~nerelycorripute the differ- point betwccn tlte .two best performance
ence between t h e u p p e r ant1 lower Th;ur 3) fitting a curve to the data arrtl
threshold T,,. For Rann clan~itciri.\ (Fig. 3), solving for the optimal TI,.Solution of' the
this range is 3O.O0C. By calculating this product-cxporrential (Fig. 3, Appendix 11)
range for individuals in several popula- yields an estimate of 16.8'C, wher-eas the
example, the known toler-ance ranges of
amphibians and reptiles d o not in fact corI-elate directly with intuitive predictio~isby
herpetologists of performance breadths.
Most her-petologists that we have informally queried believe that frogs have wider
perfbrmancc breaclths than d o lizards-Yet
sample tolerance ranges of lizards (X =
36.7?..52"C, N = 29; calculated from
Spellerberg, 1972a) are actually broader
than those of frogs (X= 30.1 5 .91°C, N =
5 ; calculated f r o m Br.attstrom, 1963).
Moreove1-, a correlation between tolerance
range and performance breadth is seemingly possible only to a limited extent: a
precise correlation would imply that
physiological performance curves a r e
geo~netricallysimilar -an improbable occurrence in biology! Therefore, uritil a
s t r o n g correlation is actually d e m o n strated, it seems appropriate to maintain a
distinction between tolerance range and
performance breadth.
Of the traditional measures o f descr-ibing thermal performance, only tolerance
range can be easily and directly estimated.
Estimates of other measures are less suitable for detailed analyses of physiology and
ecology.
i
midpoint estimate is 175°C.
When the object of curve fitting is for a
comparison of populations, data for individuals must be examined separately.
Lumping data for individuals, while decreasing the experimental load considerably, has two serious drawbacks. First,
unless data are normalized. individual differences in magnitude of performance increase the variance at each test temperature. Second, if' optimal Th is genetically
polymorphic o r is affected by age, season,
time of day, o r acclimation (see Reynolds,
1977), one might co~lcludethat individuals
have broad <ptimal temperature ranges
when instead the population is merely heterogeneous for optilhal Th(Roughga;den,
1972).
~hermalfi~rforrnancebreadth. T o estimate
thermal performance breadth, select a n
arbitrary performance level (e.g., 80% of
maximum performance) and then solve
the curve to determine the range of Th
over which that perf'ormance standard is
equalled o r exceeded (Huey, 1975). For
example, the estimate from the productexponential curve for Rana clamitans is
2 1.7"C (Fig. 3). T h e choice of performance
level is arbitrary, of course; and the estimate for thermal performance breadth
will vary between the estimates for tolerance range and the optimal temperature
range, depending o n t h e selected pertbrmance level. [Because performance
breadth is measured in degrees Celsius,
one can compare performance breadths of
animals having very different forms of
locomotion (P.R.,j u ~ n p i n gby frogs us.
sprinting by lizards).]
Comparing p/acemen,t of tolernn,ce rnnges
and optimal tenlfierrcltur~ran,ges. When an optimal temperature range exists (or when
comparing tolerance ranges), the above
methods, which compare optimal temperatures, would be biologically misleading.
I n this case, we rephrase the problem to
determine whether the optimal temperature range of population A is higher than
that of' population B. T h e simplest method
is to compare midpoints ( e . ~ . 17.5"C
,
f0s
Rann r1amita~l.s)f o r individuals a m o n g
populations. A more general techniclue
that has greater information content can
also be derived. After determining the optimal temperature range (e.g., 15°C to
20°C, Fig. 3) fbr each individual, compare
average "lower bound" t e m p e r a t u r e s
(15"C, Fig. 3) among populations. Next, set
criteria f o r differential placement of
ranges. For example, specify that range A
is higher than range B only if the lower
bound anti the upper bound of A are both
significantly higher than those of B. [Alternatively, one could specify that A is
higher than R if at least one bound is
significantly higher in A.] Although this
"bound" method is more complex than a
"midpoint" approach, more information is
gained. T h u s we determine not only that A
is higher than B "on average," but also the
basis for this average difference. Moreover, the bound approach would alert us to
situations where the range of B is entirely
contained within the range of A.
INTEGRATING THERMAL PHYSIOLOGY AND
ECOLOGY
T h e above m e t h o d s can be used t o
quantify the sensitivity of physiological
performarlce to Tb, a prerequisite for integrating thermal physiology and ecology.
Knowledge of optimal Thalone may suffice
for many analyses, but curve fitting permits further analytical power. It can be
useful, for examble. to- know that Rana
clamitans should jump about twice as far at
Th= 16.8OC than it shoulti at T, = 5.0°C o r
3 1.5"C.
.
,
Measures of optimal ITt,
are particular.ly
appropriate to analyses of geographic distributions of animals (Spellerberg, 1973;
Huey and Slatkin, 1976; see also <:lark and
Kroll, 1974), of times of activity and ot'
habltats (Kanti, 1964; Corn, 197 1; Huey
and Webstel., 1976: Huey and Pianka,
1977), a n d of competitive interactions
(Inger, 1959; Kuibal, 1961; Rand, 1964;
Huey and Webster, 1976; Lister., 15176;
Schoener, 1977). Optimal .I',, could be used
to estimate patterns of geographic: variation
(Moore, 1949) anti even to measure rates
of evolution of' phenotypic characters (see
B o g e r t , 1 9 4 9 ; Brown a n d F e l d m e t h ,
1971).
'Thermal performance br.eadth is relevant to discussions of' habitat occupancy
a n d competition (Ruibal anti Philibosian,
1970; Huey, 1974; Huey a n d Webster,
1976; Huey a n d Slatkin, 1976; I,ister,
1976; Hertz, 1977) as well as of' the precision of tenlper.atur-e regulation in various
ecological a n d behavioral contexts (DeWitt, 1 9 6 7 ; H u e y a n d Slatkin, 1976;
Greenl>e~.g,1976). Moreover, selection
pressure for thermal per.fornlance breadth
may difler between constant and Huctuating envir-onments (Levins, 1969; Kour and
Hutchison, 1970; Huey and Slatkin, l976),
and knowledge of thermal perfi~rmance
breadths is necessar-y for certain zoogeogr a p h i c analyses (Janzen, 1967; Fedel-,
1978; Huey, 1978).
As we have argued, toler-ance range and
associated threshold o r critical temperatures have restr-icted ecological significance
(Warren, 1971; Feder, 1978; I l u n ~ p h r e y s ,
1978). They relate primarily to analyses of'
" t h e r m a l safety margins" ( H e a t w o l e ,
1970), to aclaptations to extreme conditions, a ~ i dto understanding why animals
avoid extreme temperatures.
width (see Levins, 1969; Hertz, 1977) than
the acute estimates discussed here.
A more specific application concerns
analyses of differences in pr-ef'er-red Th
among sanlplcs. Mayhew and Weintraub
(1971 ) demonstrated seasonal changes in
preferreti Thof Scelopo~usorc~rtti.This shif't
can be interpreted as evidence of seasonal
acclimatization of optimal body temperature. Alternatively, perhaps the physiological optimum is unaffected by season,
but instead only the preferred -rh,
which is
a behavior (Reynolds, 1977), is changing.
Given a constant, physiologically "optimal"
T,,,a lower PI-ef'el-redThduring w'
linter can
be adaptive by reducing costs associated
with attempting to maintain n high 'Ti,
(see
Huey and Slatkin, 1976). A direct comparison of' optimal Tb f'or growth o r
locomotion for. lizards at different seasons
might discriminate by strong inl'el-ence
(Platt, 1964) between these competing (but
non-exclusive) hypotheses.
CONC1.UDlNC REMARKS-UNSOLVED PROBLEMS
T h e above discussion implicitly assu~ncs
that different physiological systems of' an
ectotherm have similarly shaped and positioned wr-fi)rn~ancecurves. 'I'his is undoubtedly
an oversin~plification(Dawson,
Extensions
1975). If' optimal t e m p e r a t u r e s vary
An irnrnediate extension of this methoti- among physiological systems (or with age,
ology involves increasing the dimension- sex, o r tirne), then n o single 'TI,simultaality. May ( 1 97.5) d e m o n s t r a t e d i n t e r - neously optimizes all systems. O n e potenactions be'tween salinity and temper-ature tial a p p r o a c h to sol;.ing this c o h p l e x
o n embryonic development of' the fish problem would he to order physiological
Bairdirlla ici.ctin. C;. R. 'Tracv, (\! ~ e r s o n a l svstelns bv their immortance to the animal:
communication) is sirnilal-ly examining the thus (it'optimal 'TI,
for locon~otionis higher
effects of T, and hydr-ation state o n jump- than that for growth) an animal might select
a hiah T, only when the abilitv to r u n
ing ahility o f a frog.
A seco~rdextension involves the dimen- quickly is of more immediate (or long term)
sion of' time. Acc.lirnation results in a importance than is the ability to grow
tirne-dependcnt shif't (pr.esurnably adap- quickly. [Why selection might have resulted
optima rather than converging
tive) in the perf01-1na11cectrr\.e (Fry and in rr~~lltiple
seems a funHart, 1948). [Holding an anirnal at con- systems to a single
" ovti~nurn
,
stant, 'moderately high T,, may produce a damental question. Not all systcms are used
ti111e-dependent impairment in per-fbnn- simultaneously: perhaps optimal 'r, of' a
a n c e : t h u s not all shif'ts a r e a d a p t i \ , e system is related to its temporal activity
(Hutchison a n d Ferrance, 1070).] T h e ex- pattern (see Brett, 197 I).]
A second proble~nis that physiological
tent and rate of acclimation. which can easily be quantified with the a b o ~ emethods, a n d ecological pertbrmancc probably d o
also gives a longer term estimate of' niche not scale directly. Greenwald's (1974)
L,
unique data on gopher snakes (Pituophi.~ before repeating the test. T e n sets of
mrlanol~ucus)provide a suggestive example. jumps were measured at 5"C:, and then at
Relative velocity of strikes at mice were cor- 5°C intervals between 10" and 30°C folrelated with percentage of strikes that were lowing the above protocol. At a TI) ot'
successful (r = .SO), but major changes in 33.5"C, the frog was again unable to jump
percent success were associated with minor when prodded. T o test for fatigue effects
changes in relative strike velocity (slope = o r possible acclimation during the experi1.8 1, calculated from data, courtesy of 0.E. ment, the frog was cooled to 20°C and
Greenwald). T h u s a 50% improvement in another series of jumps recorded (b in Fig.
physiological performance (strike velocity) 3). Mean distance jumped for the two
does not necessarily imply a 50% increase in series at 20°C did not differ significantly
ecological performance (predation suc- suggesting that the decrease in distance at
cess). Extrapolation f r o m tissue o r high Th (Fig. 3) was unrelated to fatigue
biochemical systems to ecological perform- and that acclimation did not occur.
ance must also be very sensitive to this scaling problem: This is a n additional reason
APPENDIX 11
why such systems a r e unsuitable f o r
Various curves were tit to the frog jumpecological analyses.
Because metabolism remesents an im- ing data (Fig. 3, Appendix I). T h e bestportant a n d constant d r a i n of energy, fitting curve was the product of 2 exponenmetabolic costs may also inHuence the out- tial equations (see Thornton and Lessem,
come of interactions between physiology 1978, for a similar model that uses the
a n d ecology a n d f u r t h e r complicate product of 2 logistic equations):
analyses. Very likely, animals sometimes
select Th that are suboptimal for certain
physiological systems but that maximize where P is performance, SC is the scale
growth rate (Brett, 197 1; Warren, 197 1) or parameter (estimated value = 87.50 cm),
that minimize metabolic losses o r risk of -K1 is the initial slope for the lower (left)
predation (Regal, 1967; Huey and Slatkin, side of the curve (.44"CP1),This body tem1976; Hainsworth and Wolf, 1978; Hum- perature, TI is the lower threshold temp h r e y ~ 1978).
,
perature (3.45"C), K, is the initial slope for
T h e existence of these and other sig- the upper (right) side (.34"CP1),and T, is
nificant complications suggests that at- t h e u p p e r threshold t e m p e r a t u r e
tempts to integrate physiology a n d ecology (33.50"C). T h e product exponential was
a r e a t a nascent stage of development. estimated using the SPSS nonlinear regresNevertheless, this is a stage that appears to sion (Marquarclt's method) subprogram.
promise rapid gains in the immediate future.
APPENDIX 1
T o determine the thermal dependence
of distance jumped by a 45 g, adult male
Runn clarnita?~,.~
(acclimated for 2 weeks at
about 7 0 ~ 1 ,H~~~ (1975) coolecl the frog
it was
t O j u l nwhen
~
prodded
(3.5"C). T h e f r o g was transferred to a
water bath (5°C). After 30 min, the frog
was placed on the floor
induced to
j u m p by l i g h t l ~tapping its u r ~ s t y l e(the average of 3 jumps was recorded). T h e f r o g
was returned to the water bath for 5 min
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