Energetics of diving in macaroni penguins
1
School of Biosciences, University of Birmingham, Edgbaston, Birmingham,
B15 2TT, UK
2
British Antarctic Survey, High Cross, Madingley Road, Cambridge, CB3 0ET,
UK
Present address: Sea Mammal Research Unit, Gatty Marine Laboratory, University
of St Andrews, St Andrews, Fife KY16 8LB, Scotland
* Author for correspondence (e-mail: p.j.butler{at}bham.ac.uk)
Accepted 1 October 2002
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Summary |
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Key words: energetics, diving, macaroni penguin, heart rate, abdominal temperature, rate of oxygen consumption, calculated aerobic dive limit
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Introduction |
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Further investigations examined how physiological and behavioural
adjustments might permit such impressive diving behaviour
(Butler and Jones, 1997;
Kooyman and Ponganis, 1998
).
The extent to which diving animals balance the use of aerobic and anaerobic
metabolism during natural dives is unclear. The majority of evidence suggests,
however, that most dives are essentially aerobic
(Butler and Jones, 1997
).
Anaerobic metabolism may be used in some circumstances
(Kooyman et al., 1980
;
Ydenberg and Clark, 1989
;
Carbone and Houston, 1996
;
Mori, 1998
;
Butler, 2001
), but within any
dive there must be oxygen available for the central nervous system (CNS),
heart and active muscles, even after lactate begins to accumulate.
Observations of diving behaviour confirm that most dives are within bouts of
repeated diving with relatively low ratios of post-dive surface interval
duration to dive duration (dive:pause ratio).
The aerobic dive limit (ADL), the diving duration beyond which post-dive
blood lactate levels increase above resting values, was first determined
experimentally in Weddell seals (Kooyman
et al., 1980) and defined by Kooyman et al.
(1983
). Since then, ADL or
diving lactate threshold (DLT; Butler and
Jones, 1997
) has been determined in two more species of seal
(Ponganis et al.,
1997a
,c
)
under captive conditions and in freely diving emperor penguins
(Ponganis et al., 1997b
) and
bottlenose dolphins (Williams, T. M. et
al., 1999
). In emperor penguins the DLT was 5-7 min, which agreed
quite closely with an ADL of 8 min estimated from observations of natural
diving behaviour (behavioural ADL; Kooyman
and Kooyman, 1995
). This behavioural ADL was calculated as the
dive duration above which recovery times at the surface were proportionately
longer in duration, suggesting that dives had a substantial anaerobic
component. Only 4% of natural dives exceeded this behavioural ADL, therefore
it was concluded that most diving was aerobic.
ADL has also been calculated (cADL) for many diving animals, including
several penguin species, by dividing an estimate of usable body oxygen stores
by an estimate of the rate of oxygen consumption
(O2) while
submerged (Butler and Jones,
1997
). When compared to observed patterns of diving in different
penguin species, these studies have found that 2-50% of dives exceed the cADL
(Culik et al., 1994
,
1996a
;
Boyd and Croxall, 1996
;
Bethge et al., 1997
;
Bevan et al., 2002
;
Wilson et al., 2002
). In these
studies, examination of the dive:pause ratio suggests that it is unlikely that
so many dives use predominantly anaerobic metabolism. In order for a large
proportion of natural dives by many species of penguins to be aerobic, the
cADL must be greater. Both usable oxygen stores and
O2 are difficult
to measure while submerged, and other pathways such as the metabolism of
phosphocreatine might provide energy under these conditions
(Butler and Jones, 1997
).
Submerged
O2 is
particularly difficult to measure (Costa,
1988
). If estimates of the usable oxygen stores for penguins are
approximately correct, then
O2 during diving
needs to be as low as that recorded from penguins at rest on the water surface
for most dives to be within the cADL
(Butler, 2000
).
In the present study we measured heart rate (fH), abdominal
temperature (Tab) and depth in macaroni penguins
Eudyptes chrysolophus diving freely while foraging in their natural
environment, using purpose-built implantable data loggers
(Woakes et al., 1995). Heart
rate can be used to estimate
O2 in diving
animals (Fedak, 1986
;
Bevan et al., 1992
;
Butler, 1993
) and a
relationship between heart rate and
O2 has been
established for macaroni penguins (Green,
J. A. et al., 2001
). This approach allows us to consider the
effects of the suite of physiological and behavioural adaptations that have
been found to contribute to the maximising of cADL while submerged. These
adaptations include variation of heart rate and circulation
(Butler and Woakes, 1979
;
Fedak et al., 1988
;
Kooyman et al., 1992b
;
Davis and Kanatous, 1999
),
regional hypothermia (Bevan et al.,
1997
,
2002
;
Handrich et al., 1997
) and the
use of passive gliding during the ascent and descent phases of dives
(Williams, T. M. et al., 1999
,
2000
). Thus these measurements
enabled us to relate the energetic costs and physiological responses to diving
with the observed patterns of diving behaviour.
The present study, therefore, had four main aims: (1) to estimate from
heart rate the energy cost of free-ranging diving behaviour in macaroni
penguins, (2) to determine if macaroni penguins dive within their cADL and
establish therefore whether they predominantly use aerobic respiration, (3) to
examine heart rate changes on a fine scale (measured every 2 s) in order to
assess whether circulatory adjustments made during diving might extend dive
duration (Butler and Jones,
1997; Davis and Kanatous,
1999
), (4) to measure abdominal temperature and investigate the
hypothesis that lowered body temperature contributes to the extension of
diving duration (Culik et al.,
1996b
; Handrich et al.,
1997
; Bevan et al.,
2002
).
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Materials and methods |
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Implantation procedure
Implantation of the data logger into the abdominal cavity allows data to be
recorded without compromising the swimming, foraging and breeding performance
of animals, as has been observed with the use of externally mounted devices on
the morphometrically identical royal penguin
(Hull, 1997). The implantation
procedure was basically the same as described for similar studies
(Bevan et al., 1995a
). Briefly,
the sterilised data logger was implanted into the abdominal cavity
via a mid-line incision made in the skin and body wall muscle in the
brood patch while the bird was anaesthetised with halothane. The logger design
incorporates a low power radio frequency transmitter, which emits a short
pulse on each QRS wave of the electrocardiogram (ECG). Detection of this
signal on a radio receiver was used to indicate when the data logger was in
the correct position. Once in position, the body wall and skin were sutured,
antibiotic powder (Woundcare, Animalcare Ltd, York, UK) applied to the wound
and a long-acting antibiotic (LA Terramycin, Pfizer, Sandwich, UK) and
analgesic (Vetergesic, Reckitt and Colman Products Ltd, Hull, UK) injected
intramuscularly. Aseptic conditions were maintained wherever possible. The
time at which the data logger was implanted was noted to the nearest
second.
All birds were weighed immediately before surgery using a spring balance (10±0.1 kg, Pesola, Switzerland) and a passive implantable transponder (PIT) tag, mounted on a plastic cable tie, was secured around their ankle. Birds were put into a large darkened box to recover from the surgery. Once the birds were alert and responsive, usually after 1-2h, they were returned to the colony where behaviour varied between individuals. Some would go swimming within a few hours, whereas others made their way to the nest site or stood alone elsewhere in the colony. Around the time at which the data logger memory was predicted to be full, implanted birds were recaptured after returning from a foraging trip and having fed their chicks. The data logger was removed using the same procedure as during implantation, and the bird was released back in to the colony once it had recovered.
Heart rate data loggers
The data loggers could record heart rate, hydrostatic pressure (diving
depth) and abdominal temperature every 2s and, at this sampling rate, could
store data over 30.3 days. Before use, the devices were encased in paraffin
wax and encapsulated in silicon rubber to provide waterproofing and
biocompatability. The hydrostatic pressure sensor in the data logger could
detect diving depth to within 1.2m. The temperature sensor of the encapsulated
data logger was calibrated by immersing the device in water baths of known
temperature. This procedure was also used to determine the time constant
() of the temperature sensor, which was 74s. Unfortunately, given the
relatively short dive durations of macaroni penguins, this meant that changes
in abdominal temperature could only be analysed within diving bouts, not
within individual dives. The time of removal of the data logger was noted and
the precise times of implantation and removal were later used to establish the
time base of the data downloaded from the data logger. The heart rate,
abdominal temperature and depth data from within the data logger memory were
downloaded onto a computer (Acorn RISC PC) using purpose-designed
software.
Data analysis
The data were prepared and analysed using purpose-written computer programs
within the SAS statistical package (version 6.11, SAS institute) on a UNIX
workstation. Further analyses were performed with the statistical packages
Minitab 12 (Minitab Inc.), SPSS 10.0.8 (SPSS) and Excel 97 (Microsoft). The
recovery period following the implantation procedure
(Bevan et al., 2002) was
excluded from the analysis by ignoring data collected during the period from
implantation to the start of the first foraging trip. In the present study the
duration of this period was 55.5±5h (mean ± S.E.M.).
Time at-sea on foraging trips was estimated from the depth data, supported with data from field observations and a PIT tag recorder (FSI Ltd, Cambridge, UK) situated in a gate at the edge of the colony. Each record of heart rate, abdominal temperature and dive depth was also marked with the daylight conditions (light or dark). These were calculated using the times for civil sunrise and sunset calculated for the longitude and latitude of Bird Island (54°00'S, 38°02'W). In examining dive records, dives with maximum depths of <2.4m were ignored during analyses, since wave action and recorder noise degraded depth accuracy for shallower dives. In all analyses, dives were treated as independent events. While accepting that this assumption may not be strictly correct, it is necessary in order to perform further statistical analyses.
A dive cycle was defined as a dive and the following interval spent at the
water surface prior to the next dive. Bouts of dives were defined following
the iterative statistical method of Boyd et al.
(1994), which relies on
searching the dive sequence for a change in behaviour that differs
significantly from the previous set of behaviours since the last significant
change. A minimum dive bout was formally defined as a group of at least three
dives occurring within a period of 10min. The dive record for each penguin was
searched sequentially from the start, and once a group of dives had satisfied
this minimum requirement, a search was made through the subsequent dives to
find the end of the diving bout. This was done by calculating the mean and
standard deviation (S.D.) of the surface intervals between dives, within the
diving bout, and comparing these with the next surface interval in the
sequence. If the next surface interval was significantly greater than the
previous surface intervals in the bout (t-test, P<0.01)
then the bout was deemed to have ended. If the duration of the surface
interval was not significantly different from those in the current bout, then
the dive was included within the bout, the mean ± S.D. of the surface
intervals for the bout were recalculated, and the analysis then moved onto the
next dive in the sequence.
The fH data were used to estimate mass specific rate of oxygen
consumption, O2,
using the relationship obtained from macaroni penguins walking on a treadmill
(Green, J. A. et al., 2001
).
For breeding female penguins, which were the subjects of the present study,
the equation was:
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This technique is normally calibrated when the animals' metabolism is in
steady state and hence cannot be used to estimate
O2 while the
animal is submerged. However, if fH and
O2 are averaged
over a number of complete dive/surface cycles, then fH is an accurate
and reliable predictor of
O2 in aquatic
birds and mammals (Fedak,
1986
; Bevan et al.,
1992
; Butler,
1993
). The S.D. of an estimate made using Equation 1 was
calculated using equation 11 of Green et al.
(2001
), which includes the
variability within and between calibration and field animals, and is quoted in
the text where estimates have been made.
Oxygen stores have not been measured in macaroni penguins, or indeed any of
the crested penguins, but have been calculated for other species of penguins
(Kooyman, 1989;
Kooyman and Ponganis, 1990
;
Chappell et al., 1993
;
Bethge et al., 1997
), usually
following the assumptions of Stephenson et al.
(1989
) and Croll et al.
(1992
). These studies have
detected differences between species and within species between different
studies. However, the range of estimates is not large, varying from 45ml
O2 kg-1 in little blue penguins
(Bethge et al., 1997
) to 63ml
O2 kg-1 for Adélie penguins
(Culik et al., 1994
). In the
present study it was not possible to collect the data necessary to calculate
oxygen stores for macaroni penguins, so a value of 58 ml O2
kg-1 was used, which is in the middle of the range of most of the
calculated values for other species and has been used previously as an
estimate to compare different penguin species
(Butler, 2000
). Stephenson et
al. (1989
) discuss the
influence of training on the composition of oxygen stores but there is no
reason to assume that the birds in the present study were not fit and
acclimated for intensive diving.
Data were analysed using analysis of variance (ANOVA) with Tukey
post-hoc testing, linear regression and stepwise multiple linear
regression. Results were considered significant at P<0.05 and the
significance level is quoted in the text. Unless stated otherwise, mean values
are the grand mean of the mean value for each penguin and are ± 1
S.E.M. Percentage values were arcsinetransformed before comparisons were made
(Zar, 1999). All times are
given in local time (GMT -3h) unless otherwise stated.
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Results |
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When dives were classified into bouts, 98% of all dives were part of a bout consisting of at least three dives (Table 2). Only dives within bouts were considered for further analyses. When considering post-dive surface intervals, the last dive of a bout was discarded. Individual distributions of both dive depth and duration were not normal, so KruskalWallis tests with Dunn's multiple comparisons were used to examine differences between individuals. There were significant differences between individuals in both dive depth (KruskalWallis statistic(13)=964.3, P<0.001) and duration (KruskalWallis statistic(13)=1088, P<0.001) (Table 2). Fig. 2 shows the mean frequency distributions of dive depth and duration, calculated by taking an average of the individual frequencies of occurrence of each dive depth or duration interval from all 13 penguins. These distributions were not substantially different from those of all dives from all penguins but this approach treats all individuals equally, despite large differences in the number of dives recorded from individual penguins (Table 2). 21% of all dives were to a maximum depth of 4.8m (Fig. 2A), with declining frequencies to 94.8m, the maximum dive depth recorded. This dive was recorded by penguin H79, which was responsible for most of the deeper and longer dives, including all those deeper than 70m. Dive durations were more normally distributed (Fig. 2B), though slightly negatively skewed.
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Abdominal temperature during diving
The mean Tab while on-shore was 40.1±0.9°C,
and the mean Tab during diving bouts and while at-sea but
not diving were 34.8±1.2°C and 38.2±1.0°C, respectively.
Two-way analysis of variance with Tukey post-hoc testing
(F2,38=31.6, P<0.001) revealed significant
differences between all three measurements of Tab. Further
analyses were performed to investigate the decrease in Tab
associated with diving and what effect it might have in improving diving
performance. Average diving temperature (DTab) was
calculated for each dive as the mean temperature while submerged. Linear
regressions were used to determine whether DTab, dive
duration and mean diving fH varied progressively during the course of
each diving bout (Table 3). 63.4% of all dive bouts showed a significant change in
DTab through the course of the bout and 76.2% of these
(i.e. 48.3% of all dive bouts) were significant declines, with a mean
r2 of 0.76 (Table
3). However, only 35.0% and 35.4% of bouts showed a significant
change in dive duration and fH, respectively, over the course of the
bout, and the average r2 of these relationships was only
0.37 and 0.34, respectively. The decline in Tab
(Tab) during each dive bout was calculated as the
difference between the maximum and minimum values of DTab
from that bout. Mean
Tab from all 13 penguins was
2.32±0.20°C, range 0-13.51±1.1°C.
Tab increased with the duration of the diving bout
for each individual (mean r2=0.55, all
P<0.001) and for all diving bouts pooled
(r2=0.46, P<0.001,
Fig. 3).
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Heart rate and rate of oxygen consumption while diving
Mean heart rates while the penguins were on-shore and at-sea were
116±6 and 148±7 beats min-1, respectively. While the
penguins were at-sea, mean heart rate during diving bouts (DfH) was
147±6 beats min-1, whereas mean heart rate while the birds
were at-sea but not diving (NDfH), calculated from fH
between diving bouts, was 154±8 beats min-1. Two-way ANOVA
with Tukey post-hoc testing (F2,38=38.1,
P<0.001) showed that DfH was not significantly different
from NDfH, but both were significantly greater than fH while
on-shore. During the dive cycle, macaroni penguins showed increases and
decreases in fH associated with dives of all durations. The extent of
these changes in fH associated with diving were related to dive
duration. Table 4 shows mean,
maximum and minimum fH at different stages of the diving cycle for
dives of different durations and for dives of all durations, while
Fig. 4 shows how heart rate
varied during dives lasting 102-110 s, the most frequently observed category
of dive duration (Fig. 2B). A
similar pattern was observed in dives of both longer and shorter durations and
can be described as follows. (1) Prior to diving, fH was elevated
above DfH and started to decrease just before submergence. (2) Upon
submerging, fH immediately decreased before recovering slightly.
fH then decreased more slowly to a level below
DfH. (3) At the bottom of the dive fH tended to
stabilise. (4) As the penguin started to ascend to the surface, fH
increased slowly. (5) After the penguin surfaced, fH then increased
more rapidly to a level above DfH. (6) This high heart
rate was usually followed immediately by another dive, if the dive was part of
a dive bout, otherwise fH declined to DfH. ANOVA showed that
if dives of all durations were averaged together, there were significant
differences between DfH and fH at different stages of the
dive cycle (two-way ANOVA, F4,64=97.8,
P<0.001). Further Tukey post-hoc tests showed that mean
pre-dive and post-dive fH values were significantly higher than mean
DfH, mean fH while submerged and minimum
fH while submerged. Furthermore, minimum fH while submerged
was significantly lower than DfH and mean fH while
submerged. There was no significant difference between mean fH while
submerged and DfH.
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In order to investigate further how the marked changes in heart rate during the dive cycle might be related to dive duration, stepwise multiple linear regression analysis was used. Two multiple regressions were performed. In the first analysis, the dependent variable was dive duration and the independent variables were measurements of fH made during the corresponding dive cycle, thought to be those that characterised the major features of the fH changes during a dive. These variables were: mean diving fH, minimum diving fH, minimum fH within the first 10 s of submersion, pre-dive mean fH, pre-dive maximum fH, post-dive mean fH and post-dive maximum fH. The analysis was performed for each penguin using all of its dives, and for all dives from all the penguins pooled (Table 5). The analysis indicated that, on average, 36% of the variation in dive duration could be predicted by the adjustments in fH. There was considerable variation between individuals but, as shown in Table 5, the most consistent influences on dive duration of the individual penguins were minimum fH while submerged, followed by minimum fH shortly after submersion and mean post-dive fH. When all the dives from all penguins were pooled, the three most important influences were minimum fH when submerged, mean pre-dive fH and minimum fH shortly after submersion.
|
The second analysis used differences in fH between different phases of the dive cycle, as the magnitude of these changes also appeared to vary with changes in dive duration. In this regression, the dependent variable was again dive duration and the independent variables were: the difference in fH from mean pre-dive to mean during diving, the difference in fH from maximum pre-dive to minimum during diving and the difference in fH from maximum pre-dive to minimum within 10 s of submersion. Again, the analysis was performed for each penguin using all of its dives, and for all dives from all the penguins pooled (Table 6). This analysis explained on average 22% of the variation in dive duration, and for each individual and all dives pooled the r2 value was lower than in the corresponding first analysis. This analysis was clearly of less value than the first and was not considered further.
|
The resulting multiple regression equations for each individual penguin (Table 5) could be used to predict dive duration from measurements of heart rate for that animal. Though all of the individual relationships were significant (Table 5), the reliability of such a prediction would vary considerably from individual to individual as there was considerable variation in the r2 values of the relationships (0.05-0.71). The relationship for all of the penguins pooled could be used to predict dive duration for an individual from outside this study, from measurements of fH. However, the r2 value of this relationship was relatively low (0.20, Table 5), meaning that the confidence intervals around such a prediction would be large and the prediction of limited value.
O2 while
on-shore and at-sea, estimated using Equation 1, was 16.9±1.4 and
26.3±1.4 ml min-1 kg-1, respectively.
O2 was not
calculated from DfH and NDfH since these were not
significantly different from each other or fH while at-sea. Equation
1 was, however, used to estimate
O2 and the 95%
confidence limits of these estimates, using fH from completed dive
cycles. Since fH varied with dive duration
(Table 4), it was necessary to
estimate
O2 and
the confidence limits at each different dive duration for the full range
observed by macaroni penguins (Table
7). As mean fH decreased with dive duration, then so did
estimated
O2
(Table 7).
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Discussion |
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In all four of the above studies, macaroni penguins tended to dive
predominantly in daylight. Dives at night were less frequent, to shallower
depths and of shorter duration (Fig.
1). For macaroni penguins foraging in waters around Bird Island, a
suggested cause for this is the diurnal migration of Antarctic krill
(Croxall et al., 1993). Krill
are found near the top of the water column at night but are more widely
dispersed through the water column during daylight. For penguins feeding near
Heard Island, the reasons are less clear, though little is known about the
myctophid icefish on which the penguins feed and a reliance on visual foraging
was suggested as the explanation for decreased diving at night
(Green et al., 1998
). Such a
reliance on daylight for successful foraging has also been proposed in other
penguin species feeding on a variety of prey in different locations
(Wilson et al., 1993
).
Heart rate changes within dives
Fig. 4 shows the average
change in heart rate associated with dives of 102-110 s duration. Heart rate
during diving has been recorded previously in diving birds, but only within
laboratory conditions (Butler and Woakes,
1979,
1984
;
Stephenson et al., 1986
),
semi-natural conditions (Culik,
1992
; Kooyman et al.,
1992b
) or in the field at a lower resolution (Bevan et al.,
1997
,
2002
). These studies showed
similar patterns in the change of heart rate to those of the present study,
with fH higher than the resting level before and after dives, then
falling to a level close to or lower than the resting level during dives. Such
a response is now widely accepted to be a trade-off between the `classic dive
response', which conserves oxygen stores while the animal is deprived of
access to air, and the `exercise response', which prioritises blood flow and
oxygen uptake to active muscles when exercising
(Butler, 1988
).
In the present study, the mean NDfH was not significantly
different from the mean heart rate during bouts of diving (DfH). It
is not possible to state exactly what activities the penguins were engaged in
when not diving, but it seems likely that they were travelling between the
feeding sites and the colony. Swimming or porpoising while travelling is
energetically more expensive than resting either in water or air
(Culik and Wilson, 1991;
Bevan et al., 1995b
), and hence
NDfH cannot necessarily be considered to be the fH while
resting on water. In gentoo penguins, fH while resting on the water
in a respirometer was the same as fH averaged over complete
free-ranging dive cycles (Bevan et al.,
1995b
), and we have assumed that the same is true for macaroni
penguins.
Adjustments in fH allow dive duration to be extended by ensuring
full loading of oxygen stores before the dive, then by reducing aerobic
metabolism during the dive (Butler and
Jones, 1997) and ensuring the full and effective use of oxygen
stores while submerged (Davis and
Kanatous, 1999
). Changes in heart rate, blood flow and perfusion
during diving have been proposed ever since the early physiological
experiments on forcibly submerged animals
(Scholander, 1940
) and have
subsequently been observed in freely diving penguins
(Millard et al., 1973
) and
other diving birds (Bevan and Butler,
1992
). Data on these circulatory adjustments are limited
(Kooyman and Ponganis, 1998
),
but they could have a very great effect on reducing aerobic metabolism and
maximising the effective use of oxygen stores
(Davis and Kanatous, 1999
).
The stepwise multiple linear regression showed that minimum fH had
the strongest relationship to dive duration followed by minimum fH
during the first 10 s of the dive and mean fH after the dive. Since
the minimum heart rate occurs relatively early in the dive
(Fig. 4), this might suggest
that the penguins are to some extent setting the duration of the dive when the
minimum fH is reached, though the importance of mean fH
post-dive suggests that penguins adjust fH as a response to the
previous dive rather than to prepare for the next one. This idea would
contradict the apparent prediction of the duration and depth of the following
dive and adjustment of the volume of inhaled air
(Sato et al., 2002
;
Wilson et al., 2002
) and
clearly this subject requires further investigation. Currently the multiple
regression analysis is instructive, but it is difficult to determine whether,
within the penguin, dive duration is dependent on the cardiac and circulatory
adjustments or vice versa. What can be stated with certainty is that
in macaroni penguins, the cardiac adjustments become more exaggerated as dive
duration increases.
Rate of oxygen consumption during diving
Heart rate cannot be used to estimate
O2 while
submerged. In tufted ducks Aythya fuligula, estimation of submerged
O2 using values
for mean submerged fH at mean dive duration, actually underestimated
mean submerged
O2 at mean dive
duration, as calculated from a multiple linear regression
(Woakes and Butler, 1983
).
However, if fH is averaged over complete dive cycles, then it is an
accurate and reliable predictor of
O2 for the dive
cycle (Fedak, 1986
;
Bevan et al., 1992
;
Butler, 1993
). This approach
was adopted in the present study and
O2 during dive
cycles was estimated using mean fH recorded from completed dive
cycles. If we assume that
O2 while
submerged is equivalent to this mean value, then it is possible to determine
the cADL for macaroni penguins. As the observed dive duration increased,
O2 decreased and
hence cADL increased (Table 7).
For all dive durations up to 138 s (95.3%) of dives), the cADL was greater
than the observed dive duration (Fig.
5). The 95% confidence limits can also be used to calculate cADLs
for the potential minimum and maximum estimates of
O2. If the upper
confidence limit is used, then for a given dive duration, cADL will be lower
and only dives up to 126 s (89.2% of dives) would be within the cADL. In
contrast, at the lower confidence interval, for a given dive duration the cADL
will be higher and all dives would be within the cADL. These results imply
that most natural dives within diving bouts by macaroni penguins are aerobic.
O2 calculated
from DfH of 147 beats min-1 would be 26.2±1.4 ml
min-1 kg-1, with upper and lower confidence limits of
28.9 and 23.5 ml min-1 kg-1, respectively. The resultant
cADL would be 133 s with limits of 120-148 s. This would translate to 92.8% of
observed dives being within the cADL with 95% confidence limits of 84.5-97.6%.
This approach demonstrates the importance of including the variation in heart
rate associated with dives of different durations. Calculating cADL at
different durations suggests that 95.3% of observed dives used aerobic
metabolism, whereas the more straightforward approach using overall mean
DfH to calculate cADL suggests that only 92.8% of observed dives used
aerobic metabolism.
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cADL has been calculated using
O2 while resting
on water for three other penguin species
(Butler, 2000
), though in each
case,
O2 was
measured using respirometry, rather than estimated from the field. In emperor
penguins, 96% of foraging dives in the field would be within the cADL, whereas
in king penguins Aptenodytes patagonicus and gentoo penguins
Pygoscelis papua, only 80% of dives in the field would be within the
cADL. Given that the oxygen stores are assumed to be the same for these four
species, there must be a difference in diving behaviour or
O2 while
submerged between species. Food density, availability and location will
fluctuate, causing variation in ecological conditions between populations and
species, which are more likely to be the causes of variability in diving
performance than differences in physiology. Ecological differences between
gentoo and macaroni penguins breeding at Bird Island have been described
previously (Croxall et al.,
1997
), and the breeding success of gentoo penguins is far more
vulnerable than macaroni penguins to variations in their food availability
(Croxall et al., 1999
).
Perhaps gentoo penguins are under greater pressure to gather enough food to
provision their two chicks, leading to a higher proportion of anaerobic
diving.
Similarly, emperor penguins are substantially larger than king penguins
(approx. 25-30 and 10-15 kg, respectively)
(Pütz et al., 1998), yet
their diving performance is similar
(Kooyman and Ponganis, 1990
;
Kooyman et al., 1992a
;
Kooyman and Kooyman, 1995
). As
would be expected, with their greater size and oxygen stores, emperor penguins
are capable of superior maximum dive depth and duration than king penguins,
but a large proportion of the foraging dives of both species are to 100-200 m
depth and up to 5-6 min duration (Kooyman
et al., 1992a
; Kooyman and
Kooyman, 1995
). This implies that emperor penguins operate well
within their physiological limits, whereas king penguins dive to depths and
for durations that are close to the maximum of their capabilities.
Abdominal temperature changes during dive bouts
Abdominal temperature showed a progressive decline during most dive bouts.
Similar decreases in body temperature have been observed in other diving birds
including king penguins (Culik et al.,
1996b; Handrich et al.,
1997
), gentoo penguins (Bevan
et al., 2002
), king cormorants
(Kato et al., 1996
) and
blue-eyed shags (Bevan et al.,
1997
) as well as in marine mammals
(Hill et al., 1987
). The mean
decrease during a diving bout (
Tab) in macaroni
penguins was 2.32±0.2°C, similar to that in gentoo penguins of
2.6°C (Bevan et al., 2002
).
Mean
Tab was considerably less than the mean maximum
Tab of 13.5±1.1°C, as most individuals
performed many short diving bouts where
Tab was low.
This also explains why the mean Tab during diving bouts
was 4.7°C lower than the mean Tab while not diving, as
long bouts with large values of
Tab account for a
large proportion of the time spent within diving bouts.
The decline in Tab may be the inevitable consequence of
the ingestion of cold food or of conduction to cold seawater from exposed
surfaces on the feet and flippers. Local changes in circulation may effect the
dissipation of heat from the abdominal region. Animals may attempt to reduce
this heat loss or simply allow it to continue. Alternatively, in an effort
intentionally to lose or `dump' heat, animals may increase blood flow to the
abdomen and/or exposed surfaces. These alternative mechanisms for heat loss,
and determination of whether this an active or passive process, are still
subject to investigation (Kooyman et al.,
1980; Hill et al.,
1987
; Kooyman,
1989
; Handrich et al.,
1997
; Ponganis et al.,
2001
). However, studies of the barnacle goose Branta
leucopsis, a non-diving bird, have shown that it is possible for birds to
experience anapyrexia (Cabanac and
Brinnel, 1987
), a resetting of their body temperature to a lower
level when conservation of energy may be important, even if the animal is
active and food is not scarce (Butler and
Woakes, 2001
).
Data from king penguins suggest that the decrease in
Tab is in some way facilitated and not just the
consequence of ingesting cold food, as the Tab of foraging
king penguins was lower than that in the stomach
(Handrich et al., 1997). It
has been proposed that this reduction in Tab leads to
lowered metabolic rates in diving birds
(Boyd and Croxall, 1996
;
Culik et al., 1996b
;
Butler, 2000
), through the
effect of cold temperatures on metabolically active tissues
(Heldmaier and Ruf, 1992
) and
reduced thermoregulatory costs. Barnacle geese engaged in a long,
energetically costly migration were found to allow their
Tab to fall progressively by 4.4°C, and it is proposed
that if this hypothermia extended to the whole body, an amount of fat could be
saved equivalent to up to 25% of that used for migration
(Butler and Woakes, 2001
). In
diving birds, a lowering of Tab and metabolic rate is
suggested to be sufficient to bring most natural dives observed in the field
within the cADL (Boyd and Croxall,
1996
; Butler,
2000
). This is not the only mechanism that might account for the
discrepancies between observed diving behaviour and cADL. For example,
phosphocreatine may be a source of energy that animals use while submerged
(Butler and Jones, 1997
) and
further research into this possibility should be a priority.
In the present study, it was not possible to detect variation in
Tab within dives. In king penguins, fluctuations in
temperature in localised parts of the body were found to vary between
consecutive dives (Culik et al.,
1996b). Similar experiments investigating changes in
Tab of emperor penguins diving from man-made holes in
sea-ice using a thermistor with a much smaller time constant (0.2 s) showed
that Tab can drop quite considerably within individual
dives (Ponganis et al., 2001
).
However, in the same study (Ponganis et
al., 2001
), another thermistor placed in the inferior vena cava,
which receives blood drained from core organs such as the kidneys, liver and
gastrointestinal tract, registered no significant changes in temperature
during diving. The authors concluded that there was no evidence to suggest
that reduction in Tab facilitates diving durations greater
than the cADL or DLT, as core temperature did not vary during diving and there
was no relationship between the magnitude of Tab
fluctuation and dive duration. Further work, involving more sensitive and
faster responding temperature sensors at multiple locations around the body,
may cast more light on the extent of this regional hypothermia and its
possible importance in extending dive durations in different species.
Though it was not possible to detect differences in Tab
within individual dives in the present study, Tab did
decline progressively during diving bouts. The shape and gradient of this
temperature decline varied between individuals (which may be attributable to
the position of the data logger) and between diving bouts performed by the
same individual. However, in each case the decline was progressive throughout
the bout, and abdominal temperature only increased after or at the very end of
the bout. The magnitude of the temperature drop did increase consistently with
the duration of diving bouts (Fig.
3). If diving behaviour was determined only by physiological
capacity, and lowered abdominal temperature was essential to facilitate
increased diving duration, then we might expect to see dive duration
increasing and/or mean fH decreasing progressively through bouts as
abdominal temperature decreases. However, as
Table 4 shows, nearly as many
diving bouts showed a progressive decrease in dive duration during bouts as
showed a progressive increase, and over 64% showed no significant change at
all. In addition, nearly all dives were within the cADL. This supports the
suggestion that, for macaroni penguins, factors other than physiological ones
are likely to be more important in determining average diving behaviour. Such
factors could include progressive satiation during dive bouts and the location
and density of patches of food within the water column, especially since
Antarctic krill are found in swarms
(Everson, 2000). In gentoo and
king penguins, which may be pushing the physiological limits of aerobic diving
more than macaroni penguins, patterns of increasing dive duration within bouts
might be observed.
The progressive decrease in Tab of macaroni penguins is
likely to be the result of many smaller decreases associated with individual
dives. The abdomen may not have sufficient time to return to its initial
temperature during the surface interval between dives, and the overall
decrease in temperature may be the result of an accumulation of these cycles.
This pattern was found to occur in diving emperor penguins
(Ponganis et al., 2001) where
Tab started to decrease as soon as a dive commenced and
continued to decrease until the animal surfaced. Upon surfacing,
Tab immediately increased until the next dive commenced.
However, the increase while at the surface was not sufficient to match the
decrease while diving and the net effect was a progressive decline in
Tab during diving bouts.
Conclusions
The present study suggests that most dives by macaroni penguins are likely
to be aerobic. Circulatory adjustments and the associated reduction of heart
rate during dives permit a sufficiently low level of oxygen consumption such
that even the longest observed dives performed by these animals may be
supported by aerobic metabolism. Bouts of repeated diving are also associated
with a reduction in abdominal temperature, which is probably a result of the
accumulation of many smaller decreases during individual dive/surface cycles.
Decreased temperature in the abdomen will further contribute to a reduction in
metabolic rate, but further work would be required to determine the extent of
cooling in the penguins' bodies and to what extent this might lead to a
significant reduction in metabolic rate during dives.
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References |
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