Thermolimit respirometry: an objective assessment of critical thermal maxima in two sympatric desert harvester ants, Pogonomyrmex rugosus and P. californicus
1 Department of Biological Sciences, University of Nevada at Las Vegas, 4505
Maryland Parkway, Las Vegas, NV 89154-4004 USA
2 SpanLabs Inc., 8445 Westwind Road, Las Vegas, NV 89139, USA
* Author for correspondence at address 1 (e-mail: john{at}johnlighton.org)
Accepted 9 March 2004
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Summary |
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Key words: CTmax, temperature, heat shock, thermal stress, Pogonomyrmex, thermolimit respirometry
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Introduction |
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What CTmax metric is best suited for assessing the
whole-organism temperature tolerance of a small animal such as an insect?
CTmax metrics are reliant on a specific endpoint marker
such as the onset of spasms, capsizing or heat paralysis, which are monitored
visually. The marker is variably noted as `knockdown'
(Berrigan and Hoffmann, 1998),
`loss of righting response' (LRR), `onset of spasms' (OS), or other
descriptive terms, and is followed finally by heat paralysis (see review by
Lutterschmidt and Hutchinson,
1997
, and references therein).
Which endpoint marker is most appropriate? Lutterschmidt and Hutchinson
(1997) favor OS. LRR or
knockdown generally precedes OS and can also be defined as motor coordination
failure. It determines ecological perdition the point beyond which
escape from further temperature stress is improbable as distinguished
from OS and heat paralysis, the physiological walls of final mortality [it
being understood that perdition is ecological and evolutionary while death is
physiological and that perdition, in this case, precedes death], and as such
is probably more ecologically and evolutionarily relevant. But as
Lutterschmidt and Hutchison
(1997
) admit, these
observationally determined `...end points are not definitive, are
difficult to determine and are seldom described fully'.
An objective, operationally defined endpoint that is unambiguous and low in measurement variance (mostly arising from human interpretive error) is desirable. Such an objective endpoint for CTmax determination will allow small signals to be teased from measurement noise. Low measurement noise is especially important in evolutionary studies where the noise of genetic variation may be an important part of the signal.
Investigators mostly use two dissimilar techniques for manifesting
CTmax, however defined, in their experimental organisms
(for extended discussions, see the review by
Lutterschmidt and Hutchison,
1997). Either method may include induction and acclimation
variations. The first technique exposes the organism to an acute temperature.
It may employ an LD50-type assessment. The time taken to achieve
LRR or OS at a fixed temperature is noted and employed as a metric of
thermotolerance. Usually a succession of temperatures is employed (with new
subjects for each), and CTmax is operationally defined as
the temperature at which LRR or OS occur. Lutterschmidt and Hutchison
(1997
) refer to this as the
`static method'. We refer to this method as the `total immersion method'.
The total immersion method has the following drawbacks: (a) the organism requires time to thermally equilibrate to the experimental temperature, and this must be measured and accounted for; (b) the choice of test temperature(s) is to a large extent arbitrary, and (c) the duration of normal behavior at any given temperature is thus, necessarily, also an arbitrary metric even if it is replicable. For example, is 54°C the CTmax if an insect undergoes LRR or OS at that temperature after 5 or after 2 min, after 1 min, after 0.5 min or after 10 min? Why not 55°C for 2 min rather than 54°C for 3 min? By using a single temperature and comparing times to LRR or OS, comparisons within a group of animals of similar masses can be made. However, the arbitrary nature of the temperature choice and thus of the associated survival time gives this method a clumsy affect and complicates comparisons between studies. In addition, in the field and in the final analysis it may be even more relevant that high resolution of CTmax using this method requires a large number of temperatures and animals.
The second technique is to expose the animal to a ramped temperature and
note the temperature at which it displays LRR or OS. We refer to this method
as the `temperature ramp method'. Lutterschmidt and Hutchison
(1997) refer to it as the
`dynamic method'. The temperature ramp method has the virtue that it yields a
hard number for CTmax. However, that number's meaning can
be difficult to interpret. This is primarily because the temperature ramp
method has a strong historical component, easily revealed by conducting a
thought experiment. Imagine that the ramping rate is infinitely slow or
infinitely high; in either case the temperature ramp method effectively
becomes the total immersion method. If the ramp starts out at a low enough
temperature, the animal risks dehydration or starvation before it succumbs to
the experimental temperature. On the other hand, an infinite temperature ramp
rate will cause immediate death. Between these two extremes lies a thermal
landscape where the animal at any given moment has endured all of the
temperatures from the start of the ramp up to its present temperature. At high
temperatures, each preceding temperature has an associated lethal exposure
time yet moment by moment the animal is no longer at that temperature
but at a higher one with a shorter lethal exposure time. The slower the ramp,
the more extensive will be the animal's exposure to the physiological integral
of its previous thermal exposures. Slow ramps may effect step-wise
preconditioning and induce heat shock effects (see references in
Lutterschmidt and Hutchinson,
1997
). But the faster the ramp, the more the animal's body
temperature may lag behind that of its environment, yielding misleading
overestimates of CTmax.
Thus, to sum up, the disadvantages of the temperature ramp technique are (a) that the animal's body temperature will lag behind the ramp temperature if the ramp rate is too rapid, and (b) the temperature at which the animal succumbs to heat stress is a strong function of its recent thermal history, and thus of the rate at which temperature is ramped. Obviously (a) interacts negatively with (b).
We can see from the above that the total immersion method is unsatisfactory because it has a strong arbitrary component. The temperature ramp method is unsatisfactory because it is sensitive to summed historical effects over the ramp duration; and, being thus sensitive to ramping rates, likewise has an arbitrary component. The two techniques are not easily or directly interconvertible and so their results cannot be readily compared. Furthermore, each technique requires skilled visual observation, which may have to be augmented by manipulation that may, in turn, alter the temperature challenging the organism.
Given the choice between two evils, we believe the temperature ramp
technique to be the lesser, especially for comparative work involving species
within moderate ranges (ca. two- to fourfold) of body mass. This is because
the ramping rate can be objectivized by standardizing it to the maximum at
which optimal thermal equilibration occurs in any given body mass range. Thus
the maximum ramping rate will scale to the 0.33 power of body mass,
determined by the ratio of body surface area (L2) to mass
(L3). It will also vary with body surface conductance,
medium conductance (air or water), the animal's radiative environment, the
convective characteristics of the medium, and other factors. To some degree
ramp rate will depend on the taxonomic or physiological resolution sought by
the researcher (see especially Stevenson,
1985). We suggest that the ramp rate appropriate for mass and
phylogeny (RRAMP) is therefore usually best determined empirically by trial
and if comparative measurements are made, that the ramping rate be constant
across groups and determined by adequate equilibration of the largest
animals.
In the course of studying the thermal biology of two sympatric Mojave desert harvester ants, Pogonomyrmex rugosus and Pogonomyrmex californicus, we have developed a ramped metric that utilizes two independent and objective measures of loss of muscular control, i.e. cessation of coordinated voluntary and involuntary activity. Neither measure is dependent on visual observation, facilitating automated objective analysis of CTmax. The technique also yields valuable metabolic data. We refer to this technique as `thermolimit respirometry'.
Measurements of CTmax are particularly relevant to ant
biology. As central place foragers
(Hölldobler and Wilson,
1990), most diurnal ant species in warm regions are forced by
rising temperatures to cease foraging at some point in the day. Because of
selective pressures that include maximizing net energy intake to the colony
(Lighton and Duncan, 2002
and
references therein), and a reduction in competition and predation combined
with the presence of heat-stressed prey at high temperatures
(Cerdá et al., 1998
;
Wehner et al., 1992
;
Marsh, 1985
), many ant species
(in Rüdiger Wehner's words) `walk a thermal tightrope'
(ibid.)
Pogonomyrmex californicus and Pogonomyrmex rugosus are
common sympatric seed-harvesting ants in the Mojave Desert, southwestern USA.
P. californicus forages at high substrate (though not necessarily ant
body) temperatures; up to 53°C
(Bernstein, 1974), 54.4°C
(Bernstein, 1979
) or even,
supposedly, 60°C (Whitford et al., 1976). In contrast, P. rugosus
ceases foraging at approximately 46°C (Bernstein
1974
,
1979
). Bernstein's estimates
are similar to those made at our location (J. Dorn, M. Feder and J.R.B.L.,
unpublished data). Behavioral observations (J.R.B.L. and R.T.U., unpublished)
show that P. californicus is a rapidly moving and (in the milieu in
which we find them) mostly solitary forager, making extensive use of thermal
refuges such as small sticks or stones that allow it to enter a cooler layer
of air and dump heat. P. rugosus forages more frequently in columns,
although it also forages individually (see also
Hölldobler and Wilson,
1990
, and references therein; Davidson,
1977a
,1977b
;
Gordon, 1984
;
Traniello, 1989
). Its
movements are slower and more directed, and its thermal refuge behavior is
less marked. It is reasonable to predict that the CTmax of
P. californicus would be higher than that of P. rugosus. We
developed the techniques outlined here (see also
Lighton and Turner, 2003
) to
address that question, as well as to characterize metabolic responses to
extreme temperature stress. Our null hypothesis was that P.
californicus would display the same CTmax as P.
rugosus.
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Materials and methods |
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Respirometry, activity monitoring and temperature control
We used a Sable Systems International (SSI; Las Vegas, NV, USA) TR-2 flow
through respirometry system and DATACAN V data acquisition software
(www.sablesystems.com),
supplemented with activity detection monitoring and temperature measurement
and control (Fig. 1). In more
detail, each ant we studied was placed in a glass respirometer chamber sealed
at each end by an aluminum cap with double Viton O-rings (SSI RC-M). Air
scrubbed of CO2 and H2O flowed through the chamber
via 2.5 mm i.d. metal barbs in the end caps. The chamber entry and
exit were secured against ant escape with stainless steel mesh (6 mm diameter,
<50 µm openings, Dutch weave). At one end the mesh was pushed aside
enough to allow a thin (ca. 0.5 mm diameter, type T) thermocouple wire to
penetrate about 2 cm into the chamber through the barb.
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The thermocouple wire left the chamber via the barb, traveled through a 3 cm length of 3 mm i.d. PharMed tubing, and then through the long axis of a HDPE T-adapter inserted into the other end of the tubing. The wire exit was sealed with silicone RTV cement and leak-tested. The flow path entered the respirometer chamber via the orthogonal axis of the T-adapter. Finally, the wire left the temperature-controlled chamber and was attached to a SSI TC1000 thermocouple meter. The accuracy of this meter is better than 0.2°C over the range 75 to +125°C. The 16-bit analog output of the TC1000 was attached to a 16-bit data acquisition interface (SSI UI2, basic accuracy 0.03%), which was connected to a laptop computer. The temperature of the air within the cabinet, as controlled and reported by the controller (see below) was simultaneously monitored.
The respirometer chamber rested on the cradle of an open activity detector (SSI AD-1), which detected the activity of the ant by monitoring fluctuations in reflected infrared light at ca. 900 nm. The infrared radiation was too weak to affect the temperature of nearby objects to any measurable extent. The output of the AD-1 was likewise monitored via the UI2.
Incurrent air was pulled from outside the building by a SSI TR-SS1 subsampler pump through a Drierite/Ascarite/Drierite column that scrubbed CO2 and H2O from the air. The air was then pushed through a 200 ml min-1 mass flow control valve controlled at 50 ml min-1 by a SSI MFC-1 mass flow control electronics unit. After entering the controlled-temperature cabinet, but prior to entering the respirometer chamber, the incurrent air flow traveled through 350 mm of coiled 3 mm i.d. aluminum tubing placed next to the respirometer chamber in the temperature cabinet. This ensured that air entering the respirometer chamber had thermally equilibrated with the interior of the controlled-temperature cabinet. Finally, the air entered the respirometer chamber, and then entered the TR-2 CO2 respirometry system, which was also monitored by the UI2 and data acquisition system. Fig. 1 shows a diagram of the system.
Our experimental design required flexible control of temperature. We used a SSI PTC-1 miniature temperature control cabinet attached to a SSI PELT-4 temperature controller. This cabinet and controller combination regulates temperature with an absolute accuracy of 0.2°C over the range 560°C. We attached the PELT-4 controller to a laptop computer running SSI Pelt-C1 temperature control software. We generated a temperature profile that began with 10 min at 45°C (similar to the temperatures at which the ants had been foraging), followed by a ramp at a rate of 0.25°C min-1 to a temperature of 55°C. That final temperature was maintained for 10 min. Finally the program reset the cabinet temperature to 45°C. The PELT-4 controller was updated with new values every 5 s during the ramping period. The ramping temperature of 0.25°C min-1 was the fastest ramp that did not produce a lag effect (see Discussion).
Equilibration for 10 min probably does not allow for biochemical
acclimation to high temperatures, and indeed, this experimental design was
intentional. The aim of the 10 min equilibration phase at 45°C was to
allow for thermal equilibration, behavioral acclimation, and measurement of
initial rate of CO2 production
(CO2) before
starting the upward ramp. 10 min of exposure to 45°C is not a challenge
for these species. Both species can survive for >90 min at this
temperature, which is typical of substrate temperatures while they are
actively foraging (J. Dorn, M. Feder, J.R.B.L., M.J.T., unpublished data; see
also Bernstein 1974
,
1979
).
Experimental protocol
The ant was weighed to 0.1 mg on an analytical balance (Mettler AG-245,
Columbus, OH, USA). Meanwhile, baseline air (zero CO2) was pushed
through the respirometry system and the recording initiated. After at least 1
min of plateau baseline had been recorded (baseline drift from run to run was
<0.5 p.p.m.), the recording was paused, the ant was placed in the
respirometry chamber, and the recording was re-started after 23 min.
Simultaneously, the temperature profile (starting with the 10 min
equilibration phase at 45°C) was initiated. CO2 concentration
in p.p.m., temperature in °C within the respirometer chamber, activity
(arbitrary units, recorded as volts), and temperature of the air within the
temperature-controlled cabinet, were recorded at intervals of 1 s until the
recording was manually terminated. The ant was then decanted into a 0.75 ml
Eppendorf-type vial, labeled and stored.
Data analysis
Data analysis was performed with a beta release of SSI ExpeData scientific
data analysis software. For each recording, data analysis was a two-step
process, starting out with transformations of the original data and moving to
data reduction. During transformation, the CO2 trace was baseline
corrected and converted to
CO2 in µl
h-1, then copied to an empty channel. The copy was transformed for
later determination of Q10 by taking its base-10 logarithm. The
original was copied again, into another empty channel, and its absolute
difference sum (ADS) was calculated.
The ADS of a given data channel, such as
CO2 or activity,
is the cumulative sum of the absolute difference between all of that channel's
adjacent data points. It is a useful measure of cumulative dynamic variability
in a measured variable. Thus, expressed in pseudocode, where ADS is the ADS
accumulator, ADSData() is the 0-based ADS destination vector, and the data to
be calculated as ADS are in the 0-based vector Data() with Samples being the
number of samples, the algorithm is simply:
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The file was then saved under a new name for data reduction. The original data were preserved. All of the transformations listed above were implemented as a macro so that the transformed files could be recreated from the raw data files at any time. The macro could also be edited to add other transformations, if desired. We now describe the analytical steps in detail to facilitate replication.
For data reduction, the transformed file was loaded and the
CO2 and
respirometer chamber temperatures were displayed simultaneously.
S.D. refers here to standard deviation. (1) The equilibration
section was selected, and the identity of the ant, start and end of the
selection, mean
CO2 and
S.D.,
CO2 ADS rate of
change (slope) vs. time in min, mean temperature and S.D.,
and activity ADS slope and S.D. were written to an internal
spreadsheet. The reader may wish to consult the Results for explanations of
each of the post-equilibration phases that will now be described. (2)
Approximately the first half of the temperature ramp was selected. The start
and end of the selection, the slope of log10-transformed
CO2 vs.
respirometer temperature,
CO2 ADS slope
vs. time in min, temperature slope vs. time in min (=
ramping rate), and activity ADS slope vs. time in min were written.
(3) The pre-mortal plateau
CO2 was
selected. The start and end of the selection, the mean
CO2 and
S.D., the slope of log10-transformed
CO2 vs.
respirometer temperature,
CO2 ADS slope
vs. time in min, temperature slope vs. time in min (=
ramping rate), and activity ADS slope vs. time in min were written.
(4) The end of the plateau to the lowest post-mortal
CO2 (`postmortal
valley') was selected. The start and end of the selection, the minimum and
maximum
CO2, the
slope of log10-transformed
CO2 vs.
respirometer temperature,
CO2 ADS slope
vs. time in min, the minimum and maximum respirometer temperature
over the selected interval, and activity ADS slope vs. time in min
were written. (5) The
CO2 ADS was
viewed and a ca. 5 min interval around its breakpoint selected. The linear
regression of
CO2 ADS over
this interval was obtained and its residuals inspected. The breakpoint of the
regression, i.e. the transition from high short-term variability to minimal
short-term variability in
CO2, was visible
as a sharp peak in the residual graph (see Results). The graph of the
residuals could act as a selection mechanism by clicking on two points on the
graph with a mouse, and then activating the selection. An interval just to
either side of the residuals peak was selected. The start and end of the
selection, the mean temperature within the respirometer chamber and its
S.D., and the mean
CO2 and its
S.D. were written. Sixth, an exactly analogous technique was used
to select the interval immediately around the breakpoint of the activity ADS
trace. The start and end of the selection, the mean temperature within the
respirometer chamber and its S.D., and the mean
CO2 and its
S.D. were written. (7) The highest 20 points in the large
post-mortal rise in
CO2 were found
via a zenith search algorithm, and the start and end of the selection
and the mean
CO2
and its S.D. were written. (8) The linear downward slope of the
post-mortal-peak
CO2
(log10 transformed) vs. time in min was written, followed
by
CO2 ADS slope
vs. time in min, and activity ADS slope vs. time in min. (9)
Finally the mass of each ant was determined by scanning the remarks saved with
the file for a number followed by `mg', yielding a final column of data.
Each of the steps outlined above was implemented as a separate macro so that the possibility of mistaken analyses was eliminated after each area was manually selected and the appropriate analysis steps initiated. Each file that was analyzed also yielded a log file that detailed all of the steps taken in analyzing it, allowing the analysis of any file to be reconstructed in full detail. The log files could also be edited to add further analysis steps and played back to automate the re-analysis of any or all of the files, if desired.
Statistics
Means are accompanied by standard deviations (S.D.). Regression
analysis is by least squares, with axis transformation where noted. Means are
compared using Student's t-test, and/or by analysis of variance
(ANOVA) where noted. P<0.05 was considered significant.
Regressions were compared by analysis of covariance (ANCOVA). All statistical
tests were performed with RudeStat, a DOS-based statistical package written by
J.R.B.L., validated against Systat IV, and available by e-mail from him on
request
(john{at}johnlighton.org).
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Results |
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A typical recording at a ramp rate of 0.25°C min-1 is shown
in Fig. 2. The two species
reacted to a ramp-based temperature challenge almost identically, with seven
distinct phases. Following (1) the equilibration phase during which
CO2 was
constant, (2) ramping began, and the ants'
CO2 increased
exponentially. The exponential rise in
CO2 terminated
in (3) a `premortal plateau' phase, during which
CO2 did not
increase with temperature. A steep decline in
CO2 then
occurred (4) during the course of which `mortal fall' both spiracular control
(as measured by
CO2 ADS) and
activity (as measured by activity ADS) abruptly ceased (which we call the
`theta point', shown in detail in Fig.
3; see Discussion); this was followed by (5) `postmortal valley',
a low point in post-mortal
CO2. After this,
CO2 rose again,
into (6) the `postmortal peak', before slowly declining (7) with a classic
exponential decay which progressed, if the recording was allowed to continue
for long enough, back to baseline levels. It is worth re-emphasizing that
CTmax occurs during phase 4.
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The results are summarized in Table 1. Some supplemental information is provided below, divided among the seven phases described above.
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Equilibration phase
The nominal temperature during the equilibration phase was 45°C. The
actual measured temperature at the ants' location was 44.78±0.14°C,
which does not differ significantly from 45°C (P>0.12). During
equilibration, both species were consistently active, with activity ADS slopes
vs. time being 912x postmortal levels. (Postmortal ADS
slopes served as zero-activity controls).
Ramping phase
The nominal ramping rate was 0.25°C min-1. The actual
measured ramping rate, measured at the ants' location using a fine-gauge
thermocouple, was not significantly different at 0.249±0.003°C
min-1 (t=0.12; P>0.4). Activity levels, as
measured by the slope of the activity ADS vs. time, increased
relative to equilibration levels. Because of the elevated activity levels,
CO2 increased
more rapidly with temperature than would be expected from measurements made on
inactive ants, which yield a Q10 near 2 (see
Lighton and Bartholomew,
1988
). The slope of log10-transformed
CO2 on
temperature corresponded to a Q10 of 34, which did not
differ between species (P=0.15).
Premortal plateau phase
Both species reached plateau values of
CO2 prior to
achieving CTmax. During this plateau,
CO2 did not vary
with temperature. The slope of log10-transformed
CO2 vs.
temperature during the plateau was 0.026±0.055 for Pogonomyrmex
rugosus, which did not differ significantly from the value for
Pogonomyrmex californicus of 0.021±0.037 (P>0.4).
Neither slope differed significantly from 0 (P>0.4). In terms of
temperature, the plateau was nearly 1°C wide in both species, and
therefore lasted on average for just under 4 min. Even over this rather narrow
range of variance in start and end plateau temperatures, the higher the
temperature at which an ant entered the plateau phase, the higher the
temperature at which it left it. This consistency in the duration of the
plateau phase thus shows no evidence for a proscribed or absolute exit
temperature. Plateau entry temperature explained 64% of plateau exit
temperature variance in a positive direction
(Fig. 4). Neither species
differed from each other in this relationship (ANCOVA:
F[1,35]=0.72; P[same slope]=0.4;
F[1,36]=0.05; P[same
intercepts]=0.4).
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A huge increase in the activity ADS slope vs. time occurred during the premortal plateau phase, elevating activity ADS slopes over 50-fold above inactive control (postmortal) levels. In P. rugosus the activity ADS slope was 57.6±29.2, while in P. californicus it was 54.6±29.4. These figures do not differ significantly (P>0.3). However, both figures are highly significantly greater than each species' activity ADS slope during the ramp (P<0.0001). The change in spiracular ADS slope, however, was not as marked. In P. rugosus spiracular ADS slope was 4.3±1.5, while in P. californicus it was 3.9±1, not significantly different (P>0.3). Only in the case of P. californicus was the spiracular ADS slope significantly elevated relative to ramp levels (P<0.01).
An unexpected finding was the constant magnitude of
CO2 across
species during the plateau. Even though P. rugosus weighs 84% more
than P. californicus, and although its equilibrium
CO2 at 45°C
was significantly higher, the
CO2 values of
the two species during the plateau were not significantly different
(Table 1).
Mortal fall phase
At the termination of the premortal plateau,
CO2 fell
steeply. Within 2 min, control of the spiracles and voluntary motor control
ceased, operationally constituting CTmax. Whether measured
via activity ADS or spiracular ADS, the CTmax of
P. californicus was slightly, but not significantly, higher than that
of P. rugosus. Because neither the activity nor
CO2 ADS
estimates of CTmax differed significantly between species,
it was possible to pool data across species and compare the two independent
estimates of CTmax directly. In that case the pooled
CTmax as determined by the activity ADS breakpoint was
51.66±0.33°C. For the spiracular or
CO2 ADS
breakpoint, the CTmax was 51.68±0.37°C. The two
means are only 0.02°C apart, an insignificant difference
(t=0.33, P>0.4). To put it another way, the mean
difference between activity and
CO2-based
estimates of CTmax was only 0.02±0.24°C, which
does not differ significantly from zero (P>0.4). Thus our null
hypothesis was not disproved.
In any given ant of either species, even given the restricted range of
CTmax values, a high activity ADS-derived
CTmax predicted a high
CO2 ADS-derived
CTmax. By regression analysis, either measure explained
59% of the variance in the other (Fig.
5). The relation between activity ADS-derived
CTmax and
CO2 ADS-derived
CTmax did not differ between species (ANCOVA:
F[1,35]=0.48; P[same slope]=0.4;
F[1,36]=0.40; P[same
intercepts]=0.4).
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The CO2 at
CTmax of an ant of either species was 10.5 µl
h-1 lower than its maximal
CO2 (as
determined by plateau
CO2). By
regression analysis, plateau
CO2 explained
46% of the variance in
CO2 at
CTmax (Fig.
6). The relation between plateau
CO2 and
CTmax did not differ between species (ANCOVA:
F[1,35]=0.33; P[same slope]=0.4;
F[1,36]=1.51; P[same intercepts]=0.2).
The slope of the consensus relation was 1.0 (0.998±0.177) while the
intercept was 10.5.
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Valley phase
During this phase,
CO2 declined to
a minimum in both species (Table
1).
Post-mortal peak phase
After declining to the valley values shown in
Table 1,
CO2 increased to
a well-defined peak (see Fig.
2) that reached its highest value approximately 10 min after
CTmax (10.4±2.4 min in P. rugosus and
10.1±1.4 min in P. californicus). As with premortal plateau
CO2 values,
these
CO2 values
are not mass dependent. However, an ant that displayed a high premortal
plateau
CO2
value also tended to display a high postmortal peak
CO2 value. The
premortal plateau
CO2 value
explained 28% of the variance of postmortal peak
CO2, with the
two species having equivalent slopes (ANCOVA; P>0.4; shared slope
1.01) and equivalent intercepts (ANCOVA; P>0.4; shared intercept
22.2 µl h-1).
Exponential decay phase
After reaching a peak of CO2 output, each ant displayed a
classic e-kt decay curve of CO2 output vs. time
(Fig. 2; see
Table 1). The fit of the
experimental data to this model was >95% in all cases. The larger time
constant in P. californicus is to be expected in view of the smaller
mass of P. californicus, and thus larger ratio of internal volume to
surface area.
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Discussion |
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One area in which we have respectfully parted from standard terminology is
to use the term theta point (from ANATO
, death, brother
of sleep) for the operationally defined, objective endpoint that marks
CTmax. This reflects its distinct methodological origin
from conventional endpoints determined by subjective inspection. We
nevertheless consider the theta point to be broadly congruent with
observationally determined LRR/OS CTmax.
Standardization issues
As mentioned in the Results, we found a significant lag between chamber and
ant temperatures at a ramping rate of 0.5°C min-1. We are
therefore forced to conclude that because of this lag effect, data obtained
using fast temperature ramps (e.g. Wehner
et al., 1992; 1°C min-1) may overestimate
CTmax. As noted in the Introduction, ramp rates should be
appropriate to mass and phylogeny (RRAMP); phylogenetic considerations are of
themselves inclusive of anatomical differences and their thermal qualities. We
suggest that ramp rates be standardized to the extent that differing organism
masses allow acceptable thermal equilibration to occur without imposing an
unacceptable water loss penalty. Of course, this means that the organisms may
be exposed to stressful temperatures for a longer time (see Introduction),
further reducing measured CTmax. Yet this apparent
shortcoming may yield useful data if CTmax values at
different ramp rates are compared within a single study, provided that
acceptable thermal equilibration of the experimental organism is achieved. In
particular, we anticipate that thermolimit respirometry will be a useful tool
for examining the induction of thermoprotective mechanisms.
The post-mortal valley and peak
The post-mortal peak is an unexpected phenomenon. The ants lost spiracular
control during the mortal fall (at the theta point =
CTmax). The spiracles in insects are open by default
unless held closed by spiracular closer muscles. It was therefore expected
that CO2 should
continue to fall after CTmax was reached, but unexpectedly
it then not only rose, but also slowly increased to levels 50% greater than
those maintained at the plateau phase. In other words, after death the ants
were capable of a greater effective
CO2 than while
alive. But from whence did this CO2 come? The excess CO2
in the portmortal peak is obviously not from CO2 stored in the
trachea, because such stores would have been released as soon as spiracular
control was lost. The two other alternatives are the release of dissolved or
bound CO2 in the hemolymph and tissues, and a short-lived burst of
mitochondrial activity. The former alternative at first appears unlikely,
because such a release of bound CO2 would surely have occurred
immediately after spiracular control was lost and would (it is reasonable to
assume) not have increased in magnitude, but merely fallen gradually after
death.
It is likely, however, that intracellular [ATP] plummets in the minutes following the theta point because of ATP-demanding cellular processes. Once [ADP] reaches high enough levels, [ADP]-modulated reactions will accelerate if they are still capable of doing so and if metabolic substrates remain available. If these reactions are primarily anaerobic, a downward shift in hemolymph and/or intracellular pH, as the result of lactate accumulation caused by anaerobic metabolism, could be responsible for `blowing off' the CO2 by shifting the bicarbonate/CO2 equilibrium towards CO2. (This may also explain the post-mortal valley, during which reserves of ATP may not yet be depleted to the point where [ADP]-modulated reactions begin to increase CO2 flux.)
Oxygen was freely available through the open spiracles, however, so this
anaerobic explanation is only valid if the mitochondria were unable to process
the end products of glycolysis (see also
Denlinger and Yokum, 1998;
Pörtner, 2001
,
2002
). This raises the second
possibility namely, that mitochondrial respiration is able to take
place at a rapid rate in the brief period during which ATP demand is high,
respiratory substrates remain available, and the subcellular machinery remains
intact. Distinguishing between the anaerobic blowoff and accelerated
mitochondrial respiration hypotheses should not be difficult; it merely
requires manipulation of external oxygen partial pressure.
Comparative critical thermal maxima
Within animals
The activity ADS and
CO2 ADS
estimates of CTmax, measures of motor control and
spiracular control, respectively, gave almost identical results. [Pooled
value: CTmax ADS activity breakpoint:
51.66±0.33°C; CTmax spiracular or
CO2 ADS
breakpoint: 51.68±0.37°C.] This interchangeability of independent,
activity-based and metabolic-based measures shows that our methodology for
determining CTmax is robust. It might also be mentioned
for the ecological context that this CTmax is lower than
the observed maximal foraging temperatures noted in the Introduction, which
are substrate, not animal, temperatures.
The low coefficient of variation (CV) of our observations (<1%) is
unusual in thermal biology. For example, Gehring and Wehner
(1995), using the ramp method,
report CV values of 23% in Cataglyphis bicolor and Formica
polyctena (assuming that their unspecified variance statistics are
standard deviations; if they are standard errors, the reported CV values
increase to 1218%). In a comprehensive study of domesticated
vs. feral honeybees, Atmowidjojo et al.
(1997
), also using the ramp
method, reported CV values ranging from 1221%. Using the total
immersion method, Berrigan and Hoffmann
(1998
) report CV values of 30%
and 28% for Drosophila birchii and D. serrata,
respectively.
A further line of evidence emphasizes the robustness of the `physiological
democracy' correlation between voluntary motor activity and spiracular-control
measures of thermal stress. Even though the variability in
CTmax was minor (CV<1%), activity and
CO2 ADS values
were strongly correlated (Fig.
4). Thus ants in either species with high
CTmax values in one measure tended to have high
CTmax values in the other (for a different example, see
also Berrigan, 2000
).
The almost complete congruence between CTmax values
derived from locomotor and spiracular effectors suggests that control of the
two disparate effector systems is lost via the failure of a common
heat-sensitive mechanism in the CNS. It is worth noting that although the
spiracular closer muscles may be inactivated directly by hypercapnia, they are
under direct CNS control as well (see reviews by
Kestler, 1985;
Lighton, 1996
, and references
therein).
It follows that a sub-set of thermolimit respirometry, i.e. simple optical activity detection along with temperature ramping, may yield CTmax values equivalent to those obtained when using flow-through respirometry in addition or by itself. Therefore, unless gas exchange data are required, investigators may obtain equivalent data using a simpler `thermolimit activity' system. That being said, obtaining two independent measures of CTmax does add confidence to the result.
Between species
The only significant differences found in this study between these two
sympatric and congeneric harvester ant species were, for P.
californicus, (a) much smaller mass, (b) higher mass-specific rate of
CO2 emission as measured during the premortal plateau and (c)
greater degree of spiracular control (as measured by
CO2 ADS slope)
during the premortal plateau; it may also exhibit greater variability in its
plateau entry/exit point temperatures. The more thermophilic behavior of
P. californicus relative to P. rugosus is thus not explained
by CTmax. It is, however, supported at least in part by
the above physiological adaptations and/or exaptations. The biophysical
criteria separating the two congeners facilitate the observed behavioral
divergence in the field by allowing more rapid dumping of heat during thermal
refuge behavior (a), and by allowing higher mass-specific rates of metabolic
flux (b, c) thus permitting the more intense motor activity required to
exploit thermal refuges, especially when laden. Phenomena such as biochemical
induction of thermotolerance or behavioral frequency of achieving thermal
refuges should be considered in further studies.
To summarize, the mass-specific maximum aerobic capacity of P. californicus is higher than that of P. rugosus, serving its ability to seek out thermal refuges under heat-stressed conditions, while its lower mass allows it to dump heat more rapidly. The result is a suite of characteristics that raise its maximum foraging temperature by about 78°C relative to P. rugosus in spite of an equivalent CTmax under the conditions of our experiments. Our null hypothesis that P. californicus would display the same CTmax as P. rugosus was not disproved.
Was the higher aerobic capacity of P. californicus an exaptation
(along with smaller body size) that facilitated solitary foraging and the
athletic exploitation of thermal refuges, or did that higher aerobic capacity
(and smaller body size) evolve in response to niche separation pressures and
accompanying behavioral selection? We are aware that assigning a direction to
the arrow of causation is problematic and rife with potential phylogenetic
complications. Our study reminds us again (see
Huey and Stevenson, 1979) that
ecological and evolutionary divergences do not always have simple biophysical
explanations.
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