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First published online November 1, 2006
Journal of Experimental Biology 209, 4566-4573 (2006)
Published by The Company of Biologists 2006
doi: 10.1242/jeb.02536
Seasonal adjustment of energy budget in a large wild mammal, the Przewalski horse (Equus ferus przewalskii) II. Energy expenditure
Research Institute of Wildlife Ecology, University of Veterinary Medicine, Vienna, Savoyenstraße 1, 1160 Vienna, Austria
* Author for correspondence (e-mail: walter.arnold{at}vu-wien.ac.at)
Accepted 8 September 2006
| Summary |
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|
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fH varied periodically throughout the year with a twofold increase from a mean of 44 beats min-1 during December and January to a spring peak of 89 beats min-1 at the beginning of May. LA increased from 23% per day during December and January to a mean level of 53% per day during May, and declined again thereafter. Daily mean subcutaneous body temperature (Ts) declined continuously during winter and reached a nadir at the beginning of April (annual range was 5.8°C), well after the annual low of air temperature and LA.
Lower Ts during winter contributed considerably to the reduction in fH. In addition to thermoregulation, fH was affected by reproduction, LA, HI and unexplained seasonal variation, presumably reflecting to some degree changes in organ mass. The observed phase relations of seasonal changes indicate that energy expenditure was not a consequence of energy uptake but is under endogenous control, preparing the organism well in advance of seasonal energetic demands.
Key words: hypometabolism, hypothermia, metabolic rate, winter adaptation, body temperature regulation.
| Introduction |
|---|
|
|
|---|
Nevertheless, pronounced seasonal fluctuations in metabolic rate (MR) are
known to occur in ruminants with a winter nadir in northern species
(Arnold et al., 2004
;
Nilssen et al., 1984a
;
Renecker and Hudson, 1985
) and
with a summer nadir in desert species
(Ostrowski et al., 2006
;
Williams et al., 2001
). It has
been argued that this seasonal variation in MR does not reflect a change in
BMR but results from different levels of LA or of the heat increment of
feeding (HI) (Mautz et al.,
1992
; Mesteig et al.,
2000
; Jiang and Hudson,
1993
; Worden and Pekins,
1995
). However, a recent study of red deer (Cervus
elaphus) identified a previously unknown mechanism in ungulates -
nocturnal hypometabolism - that contributed significantly to reduced energy
expenditure, mainly during late winter
(Arnold et al., 2004
).
It is unknown whether this type of hypometabolism is also used by other
large ungulates. Furthermore, it is unclear as to what degree these different
mechanisms determine MR; up until now, the crucial physiological and
behavioural parameters have never been measured simultaneously over a
sufficient period of time. In this study, we quantified for the first time the
independent contribution of thermoregulation, LA and HI to MR in a
free-roaming large ungulate, the Przewalski horse or Takhi (Equus ferus
przewalskii Poljakow). As an indicator for field MR that can be measured
over long periods of time, we recorded heart rate (fH)
(Butler et al., 2004
). Like
northern ruminants, Przewalski horses reduce voluntary food intake during
winter, suggesting that energy expenditure is also decreased
(Kuntz et al., 2006
). We
hypothesized that the same reactions that decrease winter MR of ruminants also
exist in Przewalski horses and enable this species to cope with severe
energetic bottlenecks.
The Przewalski horse is a typical steppe herbivore
(Van Dierendonck and Wallis de Vries,
1996
) and its original distribution probably covered the whole
Eurasian steppe belt. However, in the 1960s the species became extirpated in
the wild (Boyd and Houpt,
1994
). Przewalski horses have been successfully saved from total
extinction by breeding in captivity, and since the middle of the 1990s they
have been reintroduced into their natural habitat in Mongolia. The species'
recent natural refuge, the Dzungarian Gobi, is a desert or semi-desert with a
continental climate. Rain falls mostly during the summer months, but mean
rainfall amounts to not more than 100 mm per year, and temperatures are
extreme with a maximum of 40°C in summer and a minimum of -40°C in
winter (Volf, 1996
). The
reintroduction of an almost extinct species into such an extraordinary
seasonal environment requires in-depth knowledge of its physiological
capabilities, seasonal adjustments and factors governing these changes. Only
this knowledge allows us to identify suitable habitats or the reasons for
fluctuations in the mortality or reproductive success of released horses.
Hence, the results of our study will not only help to better understand
over-wintering strategies of large ungulates but also to develop the most
appropriate strategy for a successful reintroduction of the Takhi.
| Materials and methods |
|---|
|
|
|---|
Telemetric measurements
For remote measurements of physiological parameters and LA, a
self-constructed telemetry system was used. The system consisted of an
implanted transmitter and a receiver and storage unit located in a collar. The
microprocessor-controlled transmitter (50 g, 65x35x11 mm) was
encapsulated in physiologically inert medical-grade silicone rubber and
surgically implanted under the skin in the ventro-lateral neck region.
fH was extracted from the QRS complexes of the
electrocardiogram (ECG) detected by two subcutaneously implanted electrode
plates (surgical steel, 8 mm diameter). Electrodes were subcutaneously
connected to the transmitter with a coiled silicone rubber-insulated wire of
multi-stranded stainless steel fitted in silicone rubber tubing to form an
elastic and flexible lead. Subcutaneous temperature (Ts)
was recorded in the implant by a thermistor. Prior to surgical implantation of
the device, the temperature dependence of the sensor output was calibrated in
a waterbed between 20°C and 40°C at 5°C intervals. Recalibration
after explantation of the transmitters yielded virtually identical results
(drift over the measurement period <0.1°C).
Data were collected at two-minute intervals. During each of these measurement periods fH was determined for 60 s, Ts once. Both parameters were transmitted at 100 KHz via a short-range telemetry data link to the receiver in the collar. Resolution of Ts measurements was 0.1°C, and resolution of the fH measurements was 1 beat min-1. Furthermore, movements of experimental animals were detected by a vibration sensor that was located in the collar and which measured accelerations in three axes. The proportion of time with LA during a two-minute measurement cycle was defined as the proportion of seconds with sensor activation, counted by a built-in microcontroller. All measured values were stored in the collar and retrieved at the end of the experiment.
Anaesthesia and surgery
Przewalski horses were immobilized by intramuscular injection of a mixture
of 2.45 mg etorphine and 10 mg azepromazine (1 ml Immobilon®; Novartis,
Herts, UK), plus 10 mg butorphanol (1 ml Butomidor®; Richter Pharma AG,
Wels, Austria), plus 10 mg detomidine (1 ml Domosedan®; Pfizer Co.,
Vienna, Austria) per adult animal with dart projectors. Immobilized animals
were carried to the open shelter where a field surgical facility had been
established. After fixation with ropes on an inflatable surgery bed the
animals were intubated. Anaesthesia was maintained with a mixture of 1000 mg
ketamin, 15 mg midazolam and 1 mg detomidin in 500 ml NaCl, administered
intravenously, at a dosage of 1.2 ml h-1 and kg body mass. Body
mass was estimated or measured to the closest kg using a portable balance.
|
Estimating the heat increment of feeding
From July 2002 until January 2004 information on the daily dry matter
intake (DMI) and its nutrient content was available for approximately every
other month for some of the study horses
(Kuntz et al., 2006
).
Furthermore, information regarding the annual course of body condition was
available from a visually obtained body-score index that correlated
significantly with body mass (Kuntz et
al., 2006
). HI was estimated from these data to explore the
energetic consequences of seasonal variation in DMI and fattening. The period
from April to October, with a trend of increasing mean body condition, was
considered as a time of above-maintenance metabolism, and the period from
November to March with decreasing mean body condition as a time of
below-maintenance metabolism. For each DMI measurement (kg), we assumed a
digestibility of 50% [table 3.5 in Blaxter
(Blaxter, 1989
)] and estimated
HI (MJ) from the proportions of various nutrients, their gross energy content
and the proportions of metabolizable energy converted to HI by non-ruminant
herbivores [table 12.1 in Blaxter (Blaxter,
1989
)]:
![]() | (1) |
![]() | (1) |
For 17 estimates of HI, daily means of fH,
Ts and LA of the respective horses were available for
exactly the same day. For 5 further estimates of HI, daily mean
fH, Ts and LA were measured close
enough to justify the inclusion of these data in the analysis (
12 days
apart; mean=6, s.e.m.=1.7).
Data analyses
Telemetrically obtained raw data contained obviously false values because
of electronic noise during the transmission. We therefore removed all values
outside of the physiological range for horses, i.e. subcutaneous temperatures
of 0-42°C and fHs of 10-250 beats min-1
from the database. Ts remained slightly elevated for 8-14
days after transmitter implantation. These days were discarded from
statistical analyses. For calculating daily means of fH,
LA and Ts, only days with at least 60 datasets (i.e. two
sampling hours) within each quartile of a day were used to obtain the means of
these parameters that were unbiased by circadian changes. Altogether, 29 046 h
of telemetric measurements remained for final analyses, representing 29 days
of measurement from the stallion, 224, 251, 289 and 322 days from the four
adult mares, and 33 and 253 days from the two young mares, respectively.
|
|
10% represented two-minute intervals of
continuous lying or standing motionless and were categorized as intervals
spent at rest. Intervals with LA >10% were categorized as intervals with
LA.
Statistics
Statistical tests were performed using S-Plus 6.2 for Windows (Insightful
Corporation, Seattle, WA, USA). Linear mixed-effect models with the random
effect `individual' were used to analyse data repeatedly sampled from the same
individuals (Pinheiro and Bates,
2000
). To compare regression models, we used Akaike's Information
Criterion (AIC) (Akaike, 1973
),
which is proportional to the residual sum of squares penalized by the number
of parameters in the model.
Significance of seasonal variation was tested by entering a sine
(t) and cosine (t) term into the linear model, with
t representing the day of the year in radians. Sums of squares and
the degrees of freedom of these terms were added to obtain a single
F- and P-value for the periodic function. Coefficients of
the sine and cosine term were then used to algebraically compute the amplitude
(A) and phase (
) of the periodic function. Phase differences
between two periodic fits were tested for significance by determining
for the first fit and recalculating both models with sine (t-
)
and cosine (t-
). This transformation of the x-axis
results in a parameter estimate of 0 for either sin (t-
) or cos
(t-
) for the first model. Both periodic fits have a
significantly different if
the term with a parameter estimate of 0 in
the first model significantly deviates from zero in the second model.
| Results |
|---|
|
|
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Reproducing mares had significantly higher fHs during late gestation and early lactation (Table 1A). A pronounced peak of fH occurred in spring, coinciding with the time of parturition by two of the study mares (9 May 2003 and 10 May 2003, Fig. 2). However, during the same time period a peak in fH was observed in the mare that delivered only on 4 August 2003, although at a much lower level. In contrast to the situation in spring, the fH of this mare was only slightly higher when foaling in early August compared with the two mares nursing foals now already three months old (Fig. 2).
|
Locomotor activity
Daily mean LA also varied considerably throughout the year, with a more
than twofold change (Fig. 1B).
LA increased from a mean of 23% per day during December and January to a mean
level of 53% per day during May and declined again thereafter. The annual
pattern of LA closely resembled seasonal variation of fH,
and LA had, after the factor `reproduction', the secondstrongest influence on
daily mean fH (Table
1A). Nevertheless, LA only explained the profound seasonal change
in fH to some degree. A clear seasonality was also evident
in fH measured in horses at rest. Mean
fH at rest was 15.6% lower (s.e.m.=0.25) than during LA,
but showed a similar seasonal change (Fig.
3).
Body temperature
Daily mean Ts increased rapidly during April and May
from the late-winter low and remained high and roughly constant from June to
October with a mean of 36.2°C (s.e.m.=0.03). The annual range of variation
in daily means was 5.8°C. From early November onwards,
Ts decreased continuously to reach the annual nadir at the
beginning of April, long after the annual low of daily mean air temperature
(Ta) and LA (Fig.
1C). Nevertheless, the overall correlation between
Ts and Ta was relatively high
(r=0.55, F1,1303=458.6, P<0.001). In
contrast, the correlation of the daily minimum of Ts
(Tmin) with Ta was considerably weaker
(r=0.13, F1,1303=6.6, P=0.010).
Tmin was lower from June to October when the horses had a
summer fur. However, Tmin was more variable than daily
mean and maximum Ts throughout the year and was
distributed with a strong skew towards lower temperatures (the median was
34°C; interquartile range was from 32.7°C to 34.9°C). This skew
arose from bouts of particularly low Ts (<32°C)
lasting for up to 570 min. Tmin during these bouts reached
values as low as 24.4°C. Bouts with Ts<32°C
usually started in the early morning hours (median onset time was 04.42,
s.e.m.=0.015) and principally occurred at any time of the year. However, in
August these bouts lasted for a mean of 91 min (s.e.m.=18.6, N=29)
but for a mean of 181 min during April (s.e.m.=25.9, N=32).
Altogether, the energetic consequences of thermoregulation and weather conditions contributed significantly to the seasonal changes in fH (Table 1A). Daily mean fH decreased with daily mean Ts with an effect size comparable to that of LA. The independent effect of Ta on fH was relatively small and negative, indicating a slightly increasing energetic cost of defending a high body temperature at lower Ta. Similarly, fH increased slightly with daily mean wind speed (Table 1A).
Previous studies of thermoregulatory reactions to cold exposure of
winter-acclimatized domestic horses found a zone of thermoneutrality between
10°C and -15°C and an increase in MR to 142% of BMR during periods of
acute cold exposure (up to -40°C)
(McBride et al., 1985
). In
contrast to this result, we found the same correlations as reported in
Table 1A when calculating the
regression model for Ta only in the range -15°C to
+10°C.
Heat increment of feeding
Although all of the above mentioned energetically relevant factors
contributed independently and significantly to the seasonal variation of
fH, much of this variation remained unexplained. A
periodic term added to the multiple regression model further improved the fit
(AIC decrease=300, P<0.001) and turned out to be the most
important predictor (Table 1A).
We hypothesized that this unexplained periodic variation of
fH was because of a seasonally changing HI and tested this
hypotheses with data from Kuntz et al.
(Kuntz et al., 2006
).
Indeed, HI varied periodically throughout the year {test for difference to
zero for the amplitude of the periodic fit {[cos(Julian
day/365x2
-
)], F2,17=70.3,
P<0.001, Fig. 4,
lower graph}. However, predicting fH with HI resulted in a
poorer regression model (F1,18=27.8, P<0.001)
than using a periodic fit to fH
(F2,17=94.0, P<0.001, AIC difference between
both models=17, P<0.001). The acrophase of the periodic fit to
fH was on 9 July, and that of the periodic fit to HI on 2
August, representing a significant phase delay
(Fig. 4;
F1,17=11.9, P=0.003; see Materials and methods
for details). Furthermore, in a multiple-regression model containing HI in
addition to the factors considered so far, a periodic fit remained a strong
predictor of fH, together with Ts,
Ta and HI, despite the considerably smaller sample size
(Table 1B). The other
predictors in this model did not achieve or maintain statistical significance,
either because of low-effect size or, as in the case of the factor
`reproduction', because this time period of high MR was insufficiently
represented in this smaller sample.
|
| Discussion |
|---|
|
|
|---|
Among endotherms, low MR during winter and resumption of high metabolic
activity in spring are well known from hibernators and species exhibiting
daily torpor. The reduction is mainly achieved by a dramatic decrease in
endogenous heat production and tolerance of substantially lower body
temperatures (Geiser and Ruf,
1995
; Kayser,
1964
; Ruf and Heldmaier,
1992
). Earlier reports regarding a similar reduction in BMR in
ungulates during winter were initially refuted on experimental grounds, but
found new support with the discovery of nocturnal hypometabolism in Cervus
elaphus during winter (Arnold et al.,
2004
). Disentangling the relative contribution of energetically
relevant factors to the seasonal changes in MR is only possible with long-term
measurement of MR together with simultaneous measurement of critical variables
influencing MR. It further seems necessary to study animals in the wild, or
kept under almost natural conditions, in order to see undisturbed reactions.
Our study with Equus ferus przewalskii fulfilled these
preconditions.
Reproduction
The most likely candidate causing a spring peak in MR is reproduction. As
is typical for precocial mammals, reproducing mares have highest energy
expenditure during the last part of gestation and during the first weeks of
lactation (Boyd and Houpt,
1994
). Wild horses foal predominantly in spring when the growing
vegetation provides optimal nutrition
(Duncan, 1992
). However, high
energy expenditure for reproduction does not entirely explain the pronounced
increase in daily mean fH found in spring. Comparison of
the fH courses of the three reproducing mares revealed
that the mare that foaled in August 2003 had peak fH at
the same time as the two mares foaling in May 2003, albeit at a lower level
(Fig. 2). Nevertheless,
reproduction in spring apparently increased daily mean fH
considerably during the most energetically demanding weeks around foaling.
Interestingly, the increase in fH around birth in the mare
that foaled on 4 August 2003 was much smaller. This result is compatible with
a reduced ability to increase energy expenditure later in the year. It might
well be that mothers foaling late in the year are unable to adequately provide
for their offspring. Indeed, foals born outside of the main foaling season are
known to grow more slowly and are less likely to survive
(Duncan, 1992
), a phenomenon
also reported for red deer calves
(Clutton-Brock et al.,
1982
).
Physical activity
Lower levels of LA during winter contributed to a halving of
fH during winter. LA increased in spring by as much as
fH and simultaneously with fH
(Fig. 1). During a typical day
in December, 56% of all available two-minute data sets represented resting
behaviour, but at the beginning of June only 3% of the data sets had an
activity level
10%, which was typical for uninterrupted lying or standing
motionless (Kuntz et al.,
2006
). Furthermore, the intensity of LA might also have increased
but remained undetected. The sensor in the collar would have been constantly
activated and hence have recorded the maximum of 100% LA if a horse walked
slowly throughout a 2 min measurement interval, but also if it fought
furiously with a conspecific. There is no doubt that the latter is
energetically more costly as indicated by higher fH
(Kubalek, 2005
), but this
difference could not be detected with our measurement of LA. Since agonistic
interactions are comparatively rare during winter
(Kubalek, 2005
), the increase
in energy expenditure because of changes in the intensity and type of various
activities in spring is presumably higher than indicated by the increase in
our measure of LA. Nevertheless, the rapid increase in fH
in spring was also found during periods at rest
(Fig. 3), corroborating the
existence of other energetically relevant changes occurring in spring.
Thermoregulation
The horses showed a distinct seasonal rhythm of peripheral body temperature
with considerably lower Ts during winter.
Ts and Ta correlated closely, as to be
expected from the classical model of thermoregulation
(Scholander et al., 1950b
;
Scholander et al., 1950a
).
Peripheral vasoconstriction lowers Ts and attenuates heat
loss from the body core and should therefore occur more at lower
Ta. However, several lines of evidence from our data are
incompatible with the classical model. Ts continued to
decline during late winter but Ta had already increased
(Fig. 1C). At the same time,
lowest Tmin were observed. Ts
correlated positively with fH independent of all other
thermoregulatory-relevant factors considered
(Table 1), and the same
correlation was found at Ta within the thermal-neutral
zone of winter-acclimatized domestic horses
(McBride et al., 1985
). These
results indicate that a reduction in endogenous heat production accompanied by
a reduction in the set point of body temperature regulation was the major
reason for lower Ts. Apparently, this strategy to reduce
energy expenditure was increasingly employed by the horses as body energy
reserves became depleted as the course of Ts during winter
matched the decline of body mass with coinciding annual nadirs in April [cf.
fig. 6 from Kuntz et al. (Kuntz et al.,
2006
) with Fig.
1C].
Low Tmin during summer might also have reflected a
strategy to reduce the energetic cost of thermoregulation. A larger decrease
in body temperature during the night increases the capacity to store heat
during the hot day and reduces the amount of heat that must be dissipated
through evaporation. This reaction is a well-known strategy of desert
ungulates to reduce their water requirements
(Ostrowski et al., 2003
;
Ostrowski and Williams, 2006
;
Schmidt-Nielsen et al., 1957
).
It could well be that during hot summer days our study animals showed a
similar thermoregulatory reaction despite having water available ad
lib., because such a reaction is adaptive in their natural desert
habitat.
Fasting and fattening
All northern ungulates studied so far eat less during winter, even when
provided with food ad lib., and fuel metabolism to some degree with
body fat reserves accumulated during the previous summer (reviewed in
Kuntz et al., 2006
).
Przewalski horses also reduce food intake during winter and deplete body fat
reserves (Kuntz et al., 2006
;
Scheibe and Streich, 2003
).
Processing and metabolizing food is energetically costly. This cost is mostly
determined by the amount of food intake, the crude protein content of food
plants and is higher during metabolism above maintenance level
(Blaxter, 1989
). Thus,
considerably higher HI is to be expected during summer. Therefore, the
argument that higher MR of large herbivores during the summer months just
reflects the intense use of abundantly available protein-rich food and the
cost of building up body energy stores rests on solid grounds
(Jiang and Hudson, 1993
;
Mautz et al., 1992
;
Mesteig et al., 2000
;
Nilssen et al., 1984b
;
Pekins et al., 1992
;
Worden and Pekins, 1995
).
However, direct measurements and a quantification of the contribution of HI to
MR in wild ungulates were lacking so far.
At first glance, our data support the view that there was no seasonal
change in BMR but only an HI-induced increase in MR in summer. However, the
increase in MR in spring clearly preceded the increase in estimated HI
(Fig. 4), possibly reflecting
preparation by the organism for the upcoming task of processing large amounts
of high-quality food. In line with this interpretation, residual
fH still varied periodically after adding HI to the
regression model (Table 1B). To
some degree, a likely cause of this residual variation in MR could be a
seasonal change in the size and energy requirements of the gut and visceral
organs. Atrophy of the digestive tract and splanchnic organs during phases of
low or absent use is a widespread phenomenon (e.g.
Hume et al., 2002
;
Hume and Biebach, 1996
;
Kamler, 2001
;
Karasov and McWilliams, 2005
;
Piersma and Drent, 2003
;
Piersma and Lindström,
2000
; Secor and Diamond,
1998
; Starck,
1999
). Rebuilding the capability to take up energy at a higher
rate requires the synthesis of enzymes of the intermediary metabolism, growth
of the gut, its absorption capacity, of splanchnic organs, and most
importantly, maintenance of a higher mass of metabolically active tissue, i.e.
high MR.
An endogenous seasonal cycle of MR
Like many northern mammals, during winter Equus ferus przewalskii
showed a bundle of reactions known as physiologic adaptation to starvation
(Hoffer, 2006
). In order to
cope with lower food intake during winter, MR was throttled by the absence of
advanced gestation or peak lactation, by reduced physical activity, presumably
by reduced body mass and organ size and by tolerating lower body temperature.
Metabolic heat production was a major factor contributing to
fH and our data support the view that its reduction is a
ubiquitous adaptation of endotherms to cope with the energetic challenge of
winter (Arnold et al., 2004
).
However, the reactions found differ in one important aspect from the classical
starvation syndrome. They were not merely the result of an inadequate energy
uptake, as corroborated by the phase relations of the annual cycles of
fH, LA, Ts and HI. Thus, the seasonal
changes in physiological and behavioural parameters found in Przewalski horses
are evidently under endogenous control, preparing the organism well in advance
for predictable seasonal changes of climate and of availability and quality of
food.
| Acknowledgments |
|---|
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