Intrapopulational variation in the standard metabolic rate of insects: repeatability, thermal dependence and sensitivity (Q10) of oxygen consumption in a cricket
1 Instituto de Ecología y Evolución, Facultad de Ciencias,
Universidad Austral de Chile, Casilla 567, Valdivia, Chile
2 Center for Advanced Studies in Ecology and Biodiversity and Departamento
de Ecología, Facultad de Ciencias Biológicas, Pontificia
Universidad Católica de Chile, Santiago 6513677, Chile
* Author for correspondence (e-mail: rnespolo{at}genes.bio.puc.cl)
Accepted 27 August 2003
![]() |
Summary |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Individual Q10 values revealed important interindividual variation, which reflects the existence of intrapopulational variability in the thermal sensitivity of MR. In addition, individual Q10 values were negatively correlated between temperature ranges. This means that crickets having low Q10 at low temperatures, presented high Q10 at high temperatures, and vice versa. Our results suggest that MR could be of selective value in insects, showing consistency over time and intrapopulational variability in its thermal dependence. Nevertheless, its heritability remains to be determined.
Key words: standard metabolic rate, cricket, Hophlosphyrum griseus, Q10, oxygen consumption, repeatability, ectotherm, evolution
![]() |
Introduction |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
The most immediate determinants of MR in insects are body mass and ambient
temperature (Ta). Secondarily, MR changes with mode of
locomotion (Rogowitz and Chappell,
2000), gender (Rogowitz and
Chappell, 2000
), altitude
(Rourke, 2000
), parasitic
infestation (Kolluru et al.,
2002
), water scarcity (Davis
et al., 1999
), climate
(Nielsen et al., 1999
), and
reproduction (Prestwich and Walker,
1981
). Several adaptive hypotheses have been proposed to explain
general patterns and magnitudes of MR in insects. Two of the most popular, but
at the same time highly debated, are discontinuous gas exchange and metabolic
cold adaptation. The former makes use of a known respiratory pattern in
insects (i.e. a burst of CO2 release between periods of low
CO2 production) to explain water economy or adaptations to hypoxia
(Lighton, 1996
). The second
hypothesis states that insects inhabiting geographic areas with low mean
Ta will present elevated MR (after controlling for body
mass, temperature and phylogeny), as a thermoregulatory adaptation to confront
heat loss (Reinhold, 1999
;
Addo-Bediako et al., 2002
).
These studies make it clear that the ecological and physiological patterns and
processes that account for observed variation in MR in insects are not yet
fully understood, especially in regard to its adaptive significance.
Comparative physiological ecology is a discipline that largely focuses on
inferring adaptations (McNab,
2002). Physiological ecologists analyse morphological,
physiological and behavioural traits patterns, in order to explain how such
traits originated, and whether or not their presence increases survival and
reproduction. However, probably for historical reasons, only the first two
tasks have been successful (Bennett,
1987
). New physiological adaptations are currently occurring in
populations, but interest in studying evolutionary processes at this level has
only just begun (Kingsolver et al., 2000; Hoeckstra et al., 2001). Such
processes need to be addressed in the context of natural selection and
intraspecific variability. A trait can be the target of natural selection only
if it is consistent over time, that is, the trait must be repeatable
(Hayes and Jenkins, 1997
). In
fact, quantitative geneticists have demonstrated that repeatability is related
to heritability, in the sense that the former sets the upper limit of the
latter (Falconer and Mackay,
1997
; Dohm, 2002
).
Hence, the demonstration of significant repeatability in a trait necessarily
precedes any attempt to demonstrate its selective significance. Metabolic rate
has been shown to be repeatable in vertebrates, both in endotherms
(Hayes et al., 1998
;
Bech et al., 1999
) and
ectotherms (Garland and Else,
1987
; Garland and Bennett,
1990
), and recently, Rogowitz and Chappell
(2000
) have reported
significant repeatability in activity metabolism of a beetle. However,
although MR appear to be closely related to fitness in crickets
(Crnokrak and Roff, 2002
), as
far as we know there is no published study that reports repeatability of MR in
an insect, which is the first aim of this paper.
Our second aim concerns the thermal sensitivity of MR, termed
Q10 (i.e. the magnitude of change in MR for a 10°C change in
Ta) (Schmidt-Nielsen,
1995). There is a great deal of information on the Q10
of MR in insects, values ranging from 1.5 to 3, with a mode of 2.5
(Prestwich and Walker, 1981
;
Ashby, 1997
;
Davis et al., 1999
;
Rourke, 2000
;
Rogowitz and Chappell, 2000
).
However, Q10, like MR, can be considered to be an individual
attribute. Since it reflects the capacity of change in MR relative to changes
in temperature, it could also be considered a measure of organismal
performance. Hence, it is interesting to explore how much variability exists
in Q10 within a population, and how this variability is related to
the same variables that determine MR: temperature and body mass. As far as we
know, this approach has been never attempted. We chose for our study model a
small cricket species from central Chile, Hophlosphyrum griseus,
since these insects are naturally exposed to a wide range of environmental
temperatures, are available in large numbers and are easy to handle and
measure.
![]() |
Materials and methods |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Maintenance and acclimation
All specimens were kept in individual containers (i.e. perforated plastic
Petri dishes) to ensure uniformity of acclimation conditions prior to
measurements. Water was periodically added to a cotton swab placed at the end
of the cage to provide a source of moisture. Food was supplied weekly, in the
form of rabbit food pellets. The photoperiod was kept at 12 h:12 h dark:light.
After an initial 1 week period of acclimation to laboratory conditions, and
prior to each metabolic measurement, crickets were maintained for 2 weeks at
either 7±1°C, 17±1°C or 27±1°C in
environmental chambers. These temperatures were offered in a random order to
avoid sequential training. We chose these acclimation temperatures since they
are close to the average extremes of the natural temperature range in the
habitat where the sample organisms were captured (see
Di Castri and Hajek, 1976;
Jaksic, 2001
). Following each
thermal acclimation, metabolic rate was measured at the same temperature as
acclimation.
We collected additional individuals to increase sample size for the repeatability analysis. All of these specimens were maintained at 17°C since at this temperature mortality was minimal. Both metabolic measurements were performed 1 month apart (see below).
Metabolic rate measurements
All metabolic trials were performed during the day, which corresponds to
the rest phase in this species. Rates of oxygen consumption
(V.O) were used as a measure of MR.
V.O was determined using `closed system' metabolic
chambers (Vleck, 1987),
consisting of disposable 10 ml hermetic syringes fitted with three-way valves
(see also Chappell, 1983
;
Ashby, 1997
;
Chown, 1997
). All measurements
were made during the day, when crickets are inactive, and thus they serve as
measures of 'standard rates of metabolism' (MR)
(Schmidt-Nielsen, 1995
;
McNab, 2002
). Animals were
weighed (body mass = Mb) to the nearest mg in an
analytical balance and then placed, individually, inside the syringes. Small
granules of CO2-absorbent BaralymeTM and DrieriteTM were
added to each syringe in a compartment isolated from the cricket. The syringes
were sealed from the atmosphere and placed in a temperature controlled, dark
incubator for the duration of the measurement period (ca. 36 h,
depending on the Ta at which measurements were made). In
no case did the O2 within the syringe decrease by more than 10%
(usually less than 5%) between the start and the end of each measurement
period. Three blank syringes served as controls for each series of
measurements. We injected the air of the syringe into a TygonTM tube (1.5
m long) connected to the O2 analyzer after passing through
CO2-absorbent granules of BaralymeTM and DrieriteTM. At
the end of the measurement interval, O2 concentrations were
determined using a Fox Field Oxygen Analysis System (Sable System
International, Henderson, NV, USA) supplied with barometric pressure
compensation. Output from the O2 analyzer was recorded by a
computer using the DATACAN program. Rates of oxygen consumption (in µl
O2 h1) were calculated for each syringe, using
the following equation modified from Vleck
(1987
):
![]() | (1) |
This system was not intended to measure the instantaneous rate of
metabolism, nor to resolve discontinuous gas exchange (e.g.
Chappell and Rogowitz, 2000),
since each measurement is an average of oxygen consumption over several hours.
However, technical errors associated with this measurement method are small
(see Anderson et al., 1989
),
and its simplicity allows simultaneous measurements of a large number of
individuals, which are needed for statistical analyses of repeatability.
Statistics
Our design included three predictor variables: two categorical variables
(sex and Ta), and one continuous variable
(Mb). Dependent variables were MR and Q10. We
performed an analysis of covariance (ANCOVA), with Mb as
the a covariate, to test the effects of each categorical variable on
O2. We checked
analysis of variance (ANOVA) assumptions using KolmogorovSmirnov and
Cochran tests for normality, and Hartley and Bartlett tests for homogeneity of
variances. The parallelism assumption (i.e. interaction with the covariate)
was checked using an ANCOVA homogeneity-of-slopes model (Statistica 6.0), and
was found to be significant in all cases. Consequently, we performed a
separate slopes model ANCOVA (Statistica 6.0), which accounts for the absence
of parallelism. Common linear regressions of Mb and MR
were performed between each temperature. Although, formally repeatability is
the intraclass correlation coefficient between two measurements
(Lessels and Boag, 1987
),
several authors have adopted the Pearson productmoment correlation
(Huey and Dunham, 1987
;
Chappell et al., 1995
) since
it is statistically easier to manage, and theoretically it represents the same
quantity (Lynch and Walsh,
1998
). We then used the Pearson productmoment correlation
(residuals from Mb) performed on the same individuals, 1
month apart. Values of Q10 were computed for each individual as
MR(T2)/MR(T1), where
T2 and T1 were either 17°C and
7°C, or 27°C and 17°C, respectively. Since MR strongly covaries
with Mb, a prerequisite to treating individual
Q10 as independent data points (and using them in statistical
analyses) is that the ratio of
Mb(T2):Mb(T1)
must be approximately equal to unity (i.e. Mb does not
change between Ta values). We tested this assumption prior
to any statistical treatment of individual Q10 values
[Mb(17°C)/Mb(7°C)=0.97±0.10
and Mb(27°C)/Mb(17°C)=
1.08±0.16 (mean ± S.E.M.)].
We obtained two samples of individual Q10 values at different temperatures (low: 717°C and high: 1727°C, Ta). These values were compared by ANCOVA, using mean Mb, [Mb(T2)+Mb(T1)]/2 as the covariate. To explore the effect of Ta on individual Q10 values, we correlated residuals of Q10 with Mb, between Tas (i.e. Q10 residuals from low Ta versus Q10 residuals from high Ta), in those crickets where V.O could be measured at the three Tas (N=38 individuals).
![]() |
Results |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
|
|
|
|
Residuals of V.O were significantly repeatable between measurements made 1 month apart (r=0.53; P<0.0001, Fig. 3), which reflects trait consistency over time. Individual Q10 values were significantly correlated with Mb only in the low Ta range, but this correlation was weak (r2=0.08, P<0.0001; high Ta: r2=0.03, NS, Fig. 4). Individual Q10 presented substantial variability, with coefficients of variation of 22% and 30% in the low and high temperature range, respectively. However, Q10 values from the different temperature ranges were not significantly different (Q10,717°C=2.43±0.53; Q10,1727°C= 2.63±0.80, t37=1.07, NS), although residuals of Q10 were significantly and negatively correlated between Ta values (r=0.59, P=0.0001; Fig. 5).
|
|
|
![]() |
Discussion |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Metabolic rate
Our values of metabolic rate are very similar to those reported for other
species of similarly sized crickets
(Prestwich and Walker, 1981),
or values that have been allometrically standardized by body size
(Reinhold, 1999
; see also
Ashby, 1997
). Assuming a
respiratory quotient of 0.84 (Addo-Bediako
et al., 2002
), and taking into account each test temperature, our
MR values are above those reported by other authors using open
flow-V.CO respirometry for crickets (46 µl
O2 h1, Ta=30°C;
Kolluru et al., 2002
),
harvestmen (2.6 µl O2
h1,Ta=25°C;
Lighton, 2002
), and some
beetle species (5.9 µl O2 h1,
Ta=28°C; Davis et
al., 1999
), and are similar to some grasshopper species
(7.1411.9 µl O2 h1,
Ta=25°C; Rourke,
2000
). Metabolic rate increased with Ta, as
expected in an ectotherm species. However, the rate of increase was different
at different temperatures. Such a pattern has been described in crickets
(Prestwich and Walker, 1981
),
grasshoppers (Rourke, 2000
),
beetles (Rogowitz and Chappell,
2000
), ants (Nielsen et al.,
1999
), and several other species of terrestrial and aquatic
invertebrates (Rao and Bullock,
1954
). In addition to Mb and
Ta, some authors have reported significant effects of sex
on MR (Rogowitz and Chappell,
2000
). This is not the case here since the main effects of sex on
V.O were not significant when controlling for
Mb.
Repeatability of metabolic rate
Our results suggest that standard MR in Hophlosphyrum griseus is
significantly repeatable after controlling for Mb. A
potential drawback of our estimation is that we did not control for activity,
which influences MR, although individuals were measured during the rest phase.
If the same individuals in the sample were more active during both periods of
MR measurement, the repeatability result could be high since individuals
conserve their activity ranking across measurements. However, this does not
apply to the relationship between body mass and MR, where these were high and
significant. This means that larger individuals consistently presented higher
MR values than smaller individuals, which is clearly a biological effect and
not an artefact. Activity would be `noise' in the sense of residual error,
which reduces the power of the analysis. In our case, this would yield a small
and probably nonsignificant correlation, which was not the case. Another
factor that could affect the repeatability analysis is that individuals were
growing during the experimental period. This is very hard to avoid since
H. griseus is a yearly species (i.e. individuals reproduce seasonally
and live no more than a year; Lamborot,
1985). On the other hand, a shorter measurement period would have
been less informative since repeatability is the consistency of a trait over
relatively long periods of time. Thus, to minimize the effect of growth, we
controlled by body mass by using residuals and excluded individuals that
molted during this period (approximately three crickets).
Previous attempts to determine the repeatability of
O2 or
CO2 in insects
suffer from serious biases. For example, Ashby
(1997
) reported a
V.O productmoment correlation of 0.85 for a
grasshopper, but N=6 and, furthermore, no significance value was
provided, nor body size controlled for. This result is, therefore trivial,
since apparent repeatability of MR without correction for
Mb, or computed over mass-specific MR, would be very high,
given that Mb is known to be a highly repeatable trait
(Chappell et al., 1995
).
Actually, if we reanalyze our data using V.O values
obtained per individual (i.e. ml O2 h1), our
repeatability would be 0.72 (P<0.01), compared with repeatability
for mass-specific V.O (i.e. ml O2
g1 h1), where r=0.55
(P<0.01). These inflated values are only due to effects of
Mb. On the other hand, Rourke
(2000
) concluded that
repeatability of water loss rate is high because three measurements made 2
weeks apart in 15 individuals did not show significant differences. The
problem with this reasoning is that statistical tests are designed to avoid
type I error, but not type II. In other words, the absence of significant
differences among means is not evidence for their similarity
(Parkhurst, 2001
). Thus,
Rourke (2000
) can only
conclude that there is not enough evidence to decide whether the water loss
rate is different between samples. The only study we found where accurate
estimations of repeatability in an insect were provided was for the metabolic
rate of forced terrestrial exercise in a beetle
(Rogowitz and Chappell, 2000
).
These authors reported significant values of repeatability, some as high as
0.75 between trials, but with all measurements made over a time period of 5
days. This value was higher than our findings and, together, both studies
report considerably higher repeatability values than any previously reported
values for physiological traits in vertebrates
(Chappell et al., 1995
;
Berteaux et al., 1996
;
Bech et al., 1999
). The fact
that standard MR in insects is repeatable is interesting, since it suggests
that this trait could respond to natural selection
(Falconer and Mackay, 1997
).
To address this key question, which is a second step directed towards
addressing adaptive hypotheses of physiological traits in insects, researchers
should attempt to answer the more specific question: is standard metabolic
rate heritable? Studies in vertebrates yielded mixed results
(Calvo et al., 2002
;
Nespolo et al., 2003
) but the
fact that metabolic rate appear as important determinant of fitness in some
species of cricket (Crnokrak and Roff,
2002
) along with the results of this paper suggest that insect
metabolism could be of selective importance.
Thermal sensitivity of metabolic rate
We assessed the metabolic response to Ta using
Q10 values computed for each individual at two temperature ranges.
There are plenty of studies reporting the Q10 of metabolic rate for
insects, and for invertebrates in general. It appears that in most insects MR
presents a Q10 ranging from 2.0 to 2.5, with extreme values of 1.0
and 4.6 (Forlow and MacMahon,
1988; Hadley and Massion,
1985
; Cooper,
1993
; Chown et al.,
1997
), which are in agreement with our results.
From thermodynamic considerations for general biochemical reactions,
Q10 is predicted to be higher at lower temperatures
(Schmidt-Nielsen, 1995).
However, in insects this pattern is rather variable. For example, the results
of Harrison and Fewell (1995
)
were in agreement with this theoretical prediction for a grasshopper, since
Q10 values of digestive processes were always negatively correlated
with temperature. These authors found that Q10 was quite variable,
depending on the specific process being tested, with extreme values such as
5.3 for excretion rate. However, for MR, these authors found that
Q10 did not change with temperature, and, in fact, reported
remarkably high magnitudes (Q10=3.63.7). Hadley and Massion
(1985
), on the other hand,
found that altitude had inverse effects on Q10 and
Ta. Low-altitude populations presented low Q10
at low Ta and high-altitude populations presented high
Q10 over the same temperature range. However, the pattern was
completely reversed at a higher temperature range: low-altitude populations
presented high Q10, and so on. Our results suggest a similar, but
perhaps more surprising, outcome: first, there is intrapopulation variation in
individual Q10 values of around 30%; second, this variation shows a
significant dependence on Ta; third, the dependence is
negative, which suggests a trade-off, where individuals with low
Q10 at high Ta present high Q10 at
low Ta, and the contrary for individuals with high
Q10 at high Ta.
What could be the explanation for such an unusual outcome? We recomputed
individual Q10 values several times and the results remained
unchanged, so we believe that this finding is not an artefact. The following
mechanism, modified from Heinrich
(1977), and applied by Casey
and Knapp (1987
) to explain
their results with caterpillars, provides a good explanation. Metabolic rate,
as well as its thermal sensitivity, depends on biochemical reactions inside
cells and tissues. These reactions are organized in metabolic pathways, whose
efficiency depends primarily on limiting pathways which, in turn, depend on
enzyme complexes. Enzymes in different individuals have different thermal
optima. The point is that perhaps a polymorphism in such enzyme complexes
could exist in a population. Then, if a key metabolic pathway is unique for an
individual, it could be that such an animal with a low optimum would perform
better (i.e. present higher Q10) at low temperatures but
not at high temperatures. Other individuals, stocked with an enzyme
complex with a higher thermal optimum, would present higher Q10 at
higher Ta, but not at low Ta.
Such a trade-off polymorphism would produce a response to selection, if
sensitivity to temperature influences fitness.
![]() |
Acknowledgments |
---|
![]() |
References |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Addo-Bediako, A., Chown, S. L. and Gaston, K. J. (2002). Metabolic cold adaptation in insects: a large-scale perspective. Funct. Ecol. 16,332 -338.[CrossRef]
Alexander, R. M. (1999). Energy for Animal Life. New York: Oxford University Press.
Anderson, J. F., Lanciani, C. A. and Giesel, J. T. (1989). Diel cycles and metabolic rates in Drosophila. Comp. Biochem. Physiol. 94A,269 -271.[CrossRef]
Ashby, P. D. (1997). Conservation of mass-specific metabolic rate among high- and low- elevation populations of the acridid grasshopper Xanthippus corallipes. Physiol. Biochem. Zool. 70,701 -711.
Bech, C., Langseth, I. and Gabrielsen, G. W. (1999). Repeatability of basal metabolism in breeding female kittiwakes. Proc. R. Soc. Lond. B 266,2161 -2167.[CrossRef]
Bennett, A. F. (1987). Inter-individual variability: an under utilized resource. New Directions in Ecological Physiology (ed. M. E. Feder, A. F. Bennett, W. R. Burggren and R. B. Huey), pp. 147-169. Cambridge: Cambridge University Press.
Berteaux, D., Thomas, D. W., Bergeron, J. M. and Lapierre, H. (1996). Repeatability of daily field metabolic rate in female meadow voles (Microtus pennsilvanicus). Funct. Ecol. 10,751 -759.
Blouin-Demers, G. and Weatherhead, P. J. (2001). An experimental test of the link between foraging, habitat selection and thermoregulation in black rat snakes Elaphe obsoleta obsoleta. J. Anim. Ecol. 70,1006 -1013.[CrossRef]
Calvo, M., Rodas, G., Vallejo, M., Estruch, A., Arcas, A., Javierre, C., Viscor, G. and Ventura, J. L. (2002). Heritability of explosive power and anaerobic capacity in humans. Eur. J. Appl. Physiol. 86,218 -225.[CrossRef][Medline]
Casey, T. M. and Knapp, R. (1987). Caterpillar thermal adaptation: behavioral differences reflect metabolic thermal sensitivities. Comp. Biochem. Physiol. 86A,679 -682.[CrossRef]
Chappell, M. A. (1983). Metabolism and thermoregulation in desert and montane grasshoppers. Oecologia (Berlin) 56,126 -131.
Chappell, M. A., Bachman, G. C. and Odell, J. P. (1995). Repeatability of maximal aerobic performance in Belding's ground squirrels, Spermophilus beldingi. Funct. Ecol. 9, 498-504.
Chappell, M. A. and Rogowitz, G. L. (2000).
Mass, temperature and metabolic effects on discontinuous gas exchange cycles
in eucalyptus-boring beetles (Coleoptera: Cerambycidae). J. Exp.
Biol. 203,3809
-3820.
Chown, S. L., van der Merwe, M. and Smith, V. R. (1997). The influence of habitat and altitude on oxygen uptake in sub-Antarctic weevils. Physiol. Biochem. Zool. 70,116 -124.
Chown, S. L. (1997). Thermal sensitivity of oxygen uptake of Diptera from sub-Antarctic South Georgia and Marion Island. Polar Biol. 17,81 -86.[CrossRef]
Cooper, P. D. (1993). Field metabolic rate and cost of activity in two tenebrionid beetles from the Mojave Desert of North America. J. Arid Environ. 24,165 -175.[CrossRef]
Cossins, A. R. and Bowler K. (1987). Temperature Biology of Animals. London: Chapman and Hall.
Crnokrak, P. and Roff, D. A. (2002). Trade-offs to flight capability in Grillus firmus: the influence of whole-organism respiration rate on fitness. J. Evol. Biol. 15,388 -398.[CrossRef]
Davis, A. L. V., Chown, S. L. and Scholtz, C. H. (1999). Discontinuous gas exchange cycles in Scarabelus dung beetles (Coleoptera: Scarabaeidae): mass-scaling and temperature dependence. Physiol. Biochem. Zool. 72,555 -565.[CrossRef][Medline]
Di Castri, F. and Hajek, E. R. (1976). Bioclimatología de Chile. Santiago: Editorial Universidad Católica.
Dohm, M. R. (2002). Repeatability estimates do not always set an upper limit to heritability. Funct. Ecol. 16,273 -280.[CrossRef]
Falconer, D. S. and Mackay, T. F. C. (1997). Introduction to Quantitative Genetics. Edinburgh: Longman.
Forlow, L. J. and MacMahon, J. A. (1988). A seasonal comparison of metabolic and water loss rates of three species of grasshoppers. Comp. Biochem. Physiol. 89A, 51-60.[CrossRef]
Garland, T. and Bennett, A. F. (1990). Quantitative genetics of maximal oxygen consumption in a garter snake. Am. J. Physiol. 259,R986 -R992.[Medline]
Garland, T. and Else, P. L. (1987). Seasonal, sexual and individual variation in endurance and activity metabolism in lizards. Am. J. Physiol. 252,R439 -R449.[Medline]
Gibert, P., Huey, R. B. and Gilchrist, G. W. (2001). Locomotor performance of Drosophila melanogaster: interactions among developmental and adult temperatures, age, and geography. Evolution 55,205 -209.[Medline]
Hadley, N. F. and Massion, D. D. (1985). Oxygen consumption, water loss and cuticular lipids of high and low elevation populations of the grasshopper Aeropedellus clavatus (Orthoptera: Acrididae). Comp. Biochem. Physiol. 80A,307 -311.[CrossRef]
Harrison, J. F. and Fewell, J. H. (1995). Thermal effects on feeding behavior and net energy intake in a grasshopper experiencing large diurnal fluctuations in body temperature. Physiol. Zool. 68,453 -473.
Hayes, J. P. and Jenkins, S. H. (1997). Individual variation in mammals. J. Mammal. 78,274 -293.
Hayes, J. P., Bible, C. A. and Boone, J. D. (1998). Repeatability of mammalian physiology: evaporative water loss and oxygen consumption of Dipodomys merriami. J. Mammal. 79,475 -485.
Huey, R. B. and Berrigan, D. (2001). Temperature, demography, and ectotherm fitness. Am. Nat. 158,204 -210.[CrossRef]
Huey, R. B. and Dunham, A. E. (1987). Repeatability of locomotor performance in natural populations of the lizard Sceloporus merriami. Evolution 41,1116 -1120.
Heinrich, B. (1977). Why have some animals evolved to regulate a high body temperature? Am. Nat. 111,623 -640.[CrossRef]
Hoekstra, H. E., Hoekstra, J. M., Berrigan, D., Vignieri, S. N.,
Hoang, A., Hill, A. V. S., Beerli, P. and Kingsolver, J. G.
(2001). Strength and tempo of directional selection in the wild.
Proc. Natl. Acad. Sci. USA
98,9157
-9160.
Jaksic, F. (2001). Spatiotemporal variation patterns of plants and animals in San Carlos de Apoquindo, central Chile. Rev. Chil. Hist. Nat. 74,459 -484.
Kingsolver, J. G., Hoekstra, H. E., Hoekstra, J. M., Berrigan, D., Vignieri, S. N., Hill, C. E., Hoang, A., Gibert, P. and Beerli, P. (2001). The strength of phenotypic selection in natural populations. Am. Nat. 157,245 -261.[CrossRef]
Kolluru, G. R., Zuk, M. and Chappell, M. A.
(2002). Reduced reproductive effort in male field crickets
infested with parasitoid fly larvae. Behav. Ecol.
13,607
-614.
Lamborot, X. (1985). Hoplosphyrum griseus (Phillipi) y Microgryllus pallipes Phillipi, dos especies de grillos escamosos en Chile. Publicación Ocasional No 42. Santiago: Museo Nacional de Historia Natural.
Lessels, C. M. and Boag, P. T. (1987). Unrepeatable repeatabilities: a common mistake. Auk 104,116 -121.
Lighton, J. R. B. (1996). Discontinuous gas exchange in insects. Annu. Rev. Entomol. 41,309 -324.[CrossRef][Medline]
Lighton, J. R. B. (2002). Lack of discontinuous gas exchange in a tracheate arthropod, Leiobunum townsendi (Arachnida, Opiliones). Physiol. Entomol. 27,170 -174.[CrossRef]
Lynch, M. and Walsh, B. (1998). Genetics and Analysis of Quantitative Traits. Sunderland: Sinauer. 980 pp.
Madsen, T. and Shine, R. (1999). Life history consequences of nest-site variations in tropical pythons (Liasis fuscus). Ecol. 80,989 -997.
McNab, B. K. (2002). The physiological ecology of vertebrates. A View from Energetics, 1st edition, Vol. 1. Cornell: Comstock.
Nespolo, R. F., Bacigalupe, L. D. and Bozinovic, F. (2003). Heritability of energetics in a wild mammal, the leaf-eared mouse (Phyllotis darwini). Evolution 57,1679 -1688.[Medline]
Nielsen, M. G., Elmes, G. W. and Kipyatkov, V. E. (1999). Respiratory Q10 varies between populations of two species of Myrmica ants according to the latitude of their sites. J. Insect Physiol. 45,559 -564.[CrossRef][Medline]
Parkhurst, D. F. (2001). Statistical significance tests: equivalence and reverse tests should reduce misinterpretation. BioSci. 51,1051 -1057.
Prestwich, K. N. and Walker, T. J. (1981). Energetics of singing in crickets: effect of temperature in three trilling species (Orthoptera: Gryllidae). Oecologia (Berlin) 143,199 -212.
Rao, K. P. and Bullock, T. H. (1954). Q10 as a function of size and habitat temperature in poikilotherms. Am. Nat. 88,33 -44.[CrossRef]
Reinhold, K. (1999). Energetically costly behaviour and the evolution of resting metabolic rate in insects. Funct. Ecol. 13,217 -224.[CrossRef]
Rogowitz, G. L. and Chappell, M. A. (2000).
Energy metabolism of eucalyptus-boring beetles at rest and during locomotion:
gender makes a difference. J. Exp. Biol.
203,1131
-1139.
Rourke, B. (2000). Geographic and altitudinal
variation in water balance and metabolic rate in a California grasshopper,
Melanoplus sanguinipes. J. Exp. Biol.
203,2699
-2712.
Schmidt-Nielsen, K. (1995). Animal Physiology. New York: Cambridge University Press.
Sibly, R. M. and Atkinson, D. (1994). How rearing temperature affects optimal adult size in ectotherms. Funct. Ecol. 8,486 -493.
Vleck, D. (1987). Measurement of O2
consumption, CO2 production, and water vapor production in a closed
system. J. Appl. Physiol.
62,2103
-2106.