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First published online January 30, 2009
Journal of Experimental Biology 212, 483-493 (2009)
Published by The Company of Biologists 2009
doi: 10.1242/jeb.025262
Physiological variation in amethyst sunbirds (Chalcomitra amethystina) over an altitudinal gradient in winter
School of Biological and Conservation Sciences, University of KwaZulu-Natal, Private Bag X01, Pietermaritzburg, 3201, South Africa
* Author for correspondence (e-mail: downs{at}ukzn.ac.za)
Accepted 20 November 2008
 |
Summary |
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 TOP Summary INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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O2) using
flow-through respirometry, at 5 and 25°C. Birds were then acclimated at
25°C for 6 weeks on a 12 h:12 h L:D cycle.
O2 was measured
post-acclimation at eight different temperatures (15, 5, 10, 20, 30, 28, 25
and 33°C). We found little variation in winter
O2 between
individuals from the same locality, whereas significant variation was observed
in O2 at the
same temperatures between individuals from the different localities and thus
between altitudes. In particular, winter BMR decreased significantly with
decreasing altitude post-acclimation. This study emphasizes the need to
understand plasticity/flexibility in metabolic rates and to acknowledge
altitudinal differences within a species, to make accurate predictions about
the thermal physiology of a species and its responses to changes in ambient
temperatures.
Key words: altitudinal variation, amethyst sunbird, metabolic rates, phenotypic plasticity, phenotypic flexibility
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INTRODUCTION |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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; Kingsolver et al.,
2002; Piersma and Drent,
2003). However, instead of using the term `phenotypic plasticity',
Piersma and Drent (Piersma and Drent,
2003) proposed the use of the term `phenotypic flexibility' which
refers to variation within a characteristic of a single individual which is
reversible, and a function of both predictable and unpredictable fluctuations
in environmental conditions. Despite this the former is still used by some in
the literature, however, we will use the latter term.
The ability to employ flexibility to ensure regulation of maintenance
energy requirements is important within a species inhabiting locations over an
altitudinal and thus temperature gradient. Avian species have shown the
ability to enhance heat or cold resistance seasonally and in response to
experimental conditions (Dawson,
2003). At higher altitudes, the effect of reduced oxygen partial
pressure as well as decreasing ambient temperatures pose significant
challenges to avian gas exchange and thus metabolic parameters
(Clemens, 1988). Individuals
(and thus populations) that are able to adjust their thermal physiology in
response not only to their thermal environmental range, but to rapid
environmental changes (shorter than their lifetime), may enjoy a selective
advantage and thus higher fitness pay-offs than those that cannot
(DeWitt et al., 1998;
Piersma and Drent, 2003). Thus
the role of phenotypic flexibility relative to changing environmental
conditions needs to be evaluated, and the ecological factors leading to
inter-specific (as well as intra-specific) differences in response to climate
change need to be identified
(Møller et al.,
2004).
Birds are considered to be homeothermic endotherms, which implies the
ability to maintain a constant body temperature over a broad range of ambient
temperatures by adjusting their metabolism
(Chaui-Berlinck et al., 2002).
However small homeotherms have higher energetic demands at colder temperatures
and require physiological adjustments in metabolic rate or insulation to
counteract this (Downs and Brown,
2002; Soobramoney et al.,
2003). As a result of this many birds display phenotypic
flexibility in maintenance energy requirements, and are able to up- or
downregulate basal metabolic rate (BMR) over a period of time during thermal
acclimation (McKechnie et al.,
2007; Bush et al.,
2008a). Recent evidence suggests that winter BMR of species living
in highly seasonal environments reflects the conditions in which the animal
existed immediately prior to metabolic measurements being taken
(McKechnie, 2008) and thus it
becomes important to differentiate metabolic measurements made pre-acclimation
and those made post-acclimation (Bush et
al., 2008a; Smit et al.,
2008). Klaasen et al. (Klaasen
et al., 2004) suggested that it is important to recognize whether
seasonal changes in BMR represent a separate acclimation or acclimatization
response or merely variation in working capacity.
In avian comparative studies, much focus is placed on the origin of study
birds in terms of captive bred or wild caught populations and the effect of
this factor on BMR (e.g. Weathers et al.,
1983; McKechnie et al.,
2007; McKechnie,
2008), but this does not take into consideration the geographic
and consequent altitudinal origin of the wild caught species as a possible
source of variation. Previous studies of avian thermal biology have examined
metabolic adaptations along an aridity gradient (e.g.
Tieleman et al., 2002), the
effects of seasonal and environmental changes on BMR of a species (e.g.
Hart, 1962;
Dawson and Carey, 1976;
Weathers and Caccamise, 1978;
Ambrose and Bradshaw, 1988;
Maddocks and Geiser, 2000;
Bush et al., 2008b;
Smit et al., 2008), phenotypic
flexibility in BMRs of one population as a representative of a species (e.g.
McKechnie et al., 2007), or
have assessed population responses to climate change as a mean response at the
population level (e.g. Møller et
al., 2004). Published data often represents a single BMR or RMR
value per species, regardless of altitudinal origin, or alternatively data
from one population as a representative of an entire species (e.g.
Bech, 1980;
Cooper and Swanson, 1994;
Boix-Hinzen and Lovegrove,
1998; Maddocks and Geiser,
2000; McKechnie and Lovegrove,
2001; Downs and Brown,
2002; López-Calleja and
Bozinovic, 2003; Lovegrove and
Smith, 2003; McKechnie et al.,
2007), thus highlighting the need to acknowledge the role of
phenotypic flexibility within a species.
Very few avian studies, however, have looked at variation in the thermal
physiology of a species over an altitudinal gradient
(Soobramoney et al., 2003).
More specifically, in this case, few studies have looked at phenotypic
plasticity or flexibility within a subpopulation pre- and post-acclimation,
and over an altitudinal gradient, as well as examining altitudinal
intra-specific variation in BMR. Thus the fact that plasticity may exist in
phenotypic flexibility, with respect to physiological parameters, is not
acknowledged.
This is an oversight in metabolic studies. For example, McNab
(McNab, 2003) found that 99%
of the observed variation in the BMR of birds of paradise (Family
Paradisaeidae) was due to inter-specific variation in body mass, food habits
and distribution over an altitudinal gradient. Although McNab
(McNab, 2003) focused on
inter-species differences, one can assume that if inter-species differences
can be attributed to altitude, that subpopulations of the same species would
also display variation in certain bioenergetic parameters as a result of
existing in a non-migratory manner over an altitudinal gradient.
The amethyst sunbird, Chalcomitra amethystina (Shaw 1811), is a
relatively large African nectarivorous sunbird with a mean mass of
approximately 15 g (Cheke et al.,
2001; Tree, 2005).
Adult amethyst sunbirds exhibit sexual dimorphism. Adult males have
blackish-brown plumage with purplish-copper on the throat and shoulders and
silvery light green on their heads whereas females are grey-brown with pale
grey-brown underbellies (Cheke et al.,
2001; Tree, 2005).
Amethyst sunbirds occupy a broad geographical region within South Africa which
includes an altitudinal gradient from the Drakensberg mountain range to the
coast of KwaZulu-Natal (KZN) (Cheke et al.,
2001). Their populations in KZN are described as being sedentary,
with some localised winter movement (Tree,
2005).
The current knowledge of the effects of climate change on birds is
restricted to passerines from northern hemispheric temperate zones, and more
work is needed on their southern hemisphere counterparts
(Møller et al., 2004).
Thus this study aims to address this by examining how subpopulations of the
same species survive over an altitudinal gradient and thus a range of
temperatures, as well as how they adapt to changes in ambient temperature.
We predicted that the winter metabolic rates of subpopulations of amethyst sunbirds would vary over the altitudinal gradient as a result of acclimatization and adaptations to different temperatures, as well as pre- and post-acclimation resulting from innate physiological differences to acclimation to 25°C and the Pietermaritzburg altitude (660 m). BMR is generally thought to be species specific, but we predicted phenotypic flexibility between subpopulations, within a species, because of the temperature differences occurring over altitude.
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MATERIALS AND METHODS |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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). After capture, birds were transferred to the Animal House of the University of KwaZulu-Natal (UKZN) Pietermaritzburg, at an altitude of 660 m, where they were housed individually in cages (1 mx0.35 mx0.5 m) in a constant environment (CE) room. Room temperature was set at 25°C with a 12 h:12 h L:D photoperiod for the study duration (May to September 2006). Artificial nectar (20% sucrose plus Ensure®; Zwolle, Netherlands), as well as water, were available ad libitum to birds from nectar feeders in cages. Fruit flies were bred on rotting fruit in the room in which birds were housed, to supplement protein intake.
Birds were allowed to feed during the day prior to measurements of
metabolic rate because of their rapid food transit times
(Downs, 1997;
Downs and Brown, 2002), but
were deprived of food during trials. Thus it was assumed that birds were post
absorptive and that resting metabolic rate (RMR) was measured.
Metabolic measurements and protocol
Sunbirds were kept in the animal house for one night after capture before
pre-acclimation respirometry trials to reduce the effect of transport stress.
Acclimation is regarded as changes in the organism in response to changes in
any component in the environment of the laboratory
(Garland and Adolph, 1991;
Smit et al., 2008).
Metabolic rate was measured indirectly by quantifying oxygen consumption
(O2) using a
respirometer. Birds were weighed and then placed individually in respirometry
chambers (volume=3.96 l) between 16:30–17:00 h. Respirometry chambers
were placed in a sound-proof Conviron® (Winnipeg, Manitoba, Canada)
cabinet (1 m3). Photoperiods were set in synchronization with that
of the constant environment room where birds were housed (12 h:12 h L:D).
Conviron® cabinet temperature (Ta) was measured using
thermistor probes calibrated with a standard mercury thermometer (0.05°C)
in a water bath at temperatures between 5 and 45°C.
Air flow was controlled using a computerized open flow-through system
(Depocas and Hart, 1957;
Hill, 1972). Atmospheric air
was pumped in and partially dried using silica gel, before reaching the
Conviron® cabinet. Flow rate was maintained at a level that ensured <1%
change in oxygen concentration, between 0.5 and 0.6 l h–1
(Downs and Brown, 2002). The
flow rate of each chamber was measured using a Brooks thermal mass-flow meter
(Model 580E; Hatfield, PA, USA) factory calibrated to STP. A steady flow of
air through the chamber was ensured as air entered the bottom and was expelled
through the top of the respirometry chambers. Simultaneous measurements of six
chambers (five experimental and one control chamber) was achieved by using
solenoid valves and a separate pump for each chamber.
Excurrent air was passed through a water condenser (a copper tube in which
air was cooled to approximately 3°C, or below dew point) to remove water
vapour, and soda lime, to remove CO2. An oxygen analyser (Model
S-3A/1, Ametek, Pittsburgh, PA, USA) was used to determine the fractional
concentration of O2 in dry air samples. The fractional
concentration of O2 in the control chamber was measured at the
start of every 6 min. cycle, and the O2 values from the
experimental chambers were then subtracted from this value. The problem of
long-term drift in O2 analyser outputs was thus limited to that
which would occur in 5 min cycles. Measurements of the various parameters for
each chamber (Ta, flow rate and fractional O2
concentrations) were recorded at the end of each 45 s sampling interval, so as
to allow sufficient time for the flushing of air from the previous channel
from the ducting between relay valves and the sub sample tubing.
O2 was recorded
digitally every 6 min, corrected for standard temperature and pressure, and
expressed as a mass-specific value. Thus ten readings per individual were
recorded on an hourly basis.
Analogue signals from the thermistor probes, mass flow meter and oxygen analyser were recorded digitally using an A/D converter and software written by R. Van Zyl, UKZN.
The following equation was used to calculate mass-specific oxygen
consumption:
 | (1) |
O2 is the
metabolic rate (ml O2 g–1 h–1),
is the flow rate (ml
min–1), FIO2 is the incurrent
fractional O2 concentration and FEO2
is the excurrent fractional O2 concentration, and
Mb is body mass (g)
(Hill, 1972). At 07:00 h the following morning, birds were removed from the chambers, weighed and returned to their cages in the CE room in the animal house. Food and water were available to them ad libitum.
Pre-acclimation
O2 values were
measured at ambient temperatures of 25°C [assumed to be in the thermal
neutral zone (TNZ)] and 5°C (assumed to be at an extreme) within 4 days of
capture using an interspersed design within each subpopulation.
After the initial trials, birds were acclimated in the CE room for 6 weeks
as described. This long acclimation period was necessary to ensure that
sunbirds were all acclimated to the same conditions. After this time
O2 measurements
were repeated as in the earlier trials at randomly ordered ambient
temperatures of 15, 5, 10, 20, 30, 28, 25 and 33°C, to ensure the absence
of temperature acclimation. Birds were carefully monitored at 33°C and
removed at approximately 21:00 h.
Release
Birds were weighed and released back at the original capture site upon
completion of respirometry trials.
Statistical analyses
Descriptive statistics were calculated in STATISTICA (Statsoft, Tulsa, USA)
for each subpopulation of amethyst sunbirds. Hourly rates of winter
O2 for
individuals from each subpopulation of sunbirds were determined and plotted
against time for each Ta. The minimum RMR at each of these
temperatures for each individual was used in analysis to determine change with
temperature using generalized linear models (commonly called GLM) repeated
measures analysis of variance (RM ANOVA). BMR was calculated by taking the
lowest mean RMR per subpopulation. The TNZ was determined using
post-hoc Sheffé tests to determine over what range minimum RMR
did not differ significantly. GLM RM ANOVA was further used for the comparison
of winter O2
measurements between populations at different altitudes and between pre- and
post-acclimation data. Post-hoc Sheffé tests were done to
determine where significant interactions occurred (P<0.05) between
populations and within populations pre- and post-acclimation. Data were
presented as mean ± s.e.m. of the individuals measured (N).
Percentage change in winter MR (BMR or RMR) between populations was calculated
using the following equation: (higher altitude MR–lower altitude
MR)/(higher altitude MR)x100. Similarly, percentage change between pre-
and post-acclimation winter MR values were calculated using the following
equation: (pre-acclimation MR–post-acclimation MR)/(pre-acclimation
MR)x100.
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RESULTS |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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O2 values for
amethyst sunbird subpopulations at Ta=5°C when
compared within and between sites (Fig.
1A; RM ANOVA, F(2,8)=14.977,
P=0.002). Mean
O2 values at
5°C changed significantly between pre- and post-acclimation for the high
altitude Underberg (N=9) and low altitude Oribi Gorge (N=8)
subpopulations (post-hoc Sheffé test, P<0.05). The
high altitude Underberg subpopulation showed a 51.8% increase in
O2 from pre- to
post-acclimation at 5°C from 8.44±0.170 ml O2
g–1 h–1 (0.047 W) to 12.81±0.949 ml
O2 g–1 h–1 (0.071 W). The low
altitude Oribi Gorge sunbirds showed a 52.5% decrease in
O2 between
pre-and post-acclimation trails at 5°C, from 12.59±0.699 ml
O2 g–1 h–1 (0.070 W) to
5.98±0.499 ml O2 g–1 h–1
(0.033 W). The intermediate altitude Howick sunbirds did not show a
significant difference between pre- and post-acclimation
O2 at 5°C
(post-hoc Sheffé, P>0.05), with a marginal 7.2%
decrease in O2
between pre- and post-acclimation, from 15.94± 0.426 ml O2
g–1 h–1 (0.089 W) to 14.79±1.337 ml
O2 g–1 h–1 (0.083 W).
|
O2 values at
5°C (Fig. 1A) showed a
significant difference between Underberg and Howick (post-hoc
Sheffé, P<0.05), and Underberg and Oribi Gorge
(post-hoc Sheffé, P<0.05), but not between Howick
and Oribi Gorge subpopulations (post-hoc Sheffé,
P>0.05). However, post-acclimation subpopulation comparisons
indicated a significant difference between Underberg and Oribi Gorge
(post-hoc Sheffé, P<0.05), Howick and Oribi Gorge
(post-hoc Sheffé, P<0.05), but no significant
difference in O2
values between Underberg and Howick subpopulations
(Fig. 1A; post-hoc
Sheffé, P>0.05).
|
O2 values for
amethyst sunbird subpopulations at Ta=25°C when
compared within and between sites (Fig.
1B; RM ANOVA, F(2,10)=10.345,
P=0.004). Significant variation existed between Underberg and Howick,
and Underberg and Oribi Gorge subpopulations post-acclimation to 25°C, in
25°C trials (post-hoc Sheffé, P<0.05). The
high altitude Underberg subpopulation showed very little change between pre-
and post-acclimation trials at 25°C with a decrease of only 2.9% from
6.71±0.146 ml O2 g–1 h–1
(0.037 W) to 6.52±0.493 ml O2 g–1
h–1 (0.036 W; post-hoc Sheffé,
P>0.05).
O2 for Howick
and Oribi Gorge subpopulations decreased significantly between pre- and
post-acclimation trials (post-hoc Sheffé, P<0.05),
with the O2 of
Howick subpopulations decreasing by 58.4% [from 7.20±0.447 ml
O2 g–1 h–1 (0.040 W) to
3.00±0.386 ml O2 g–1 h–1
(0.017 W)] from pre- to post-acclimation, and the low altitude Oribi Gorge
sunbirds exhibiting a 48.7% decrease in
O2 (from
7.48±0.742 ml O2 g–1 h–1
or 0.042 W to 3.84±0.387 ml O2 g–1
h–1 or 0.021 W) from pre- to post-acclimation trials at
25°C. The high altitude Underberg subpopulation of amethyst sunbirds (Fig. 2), showed a much greater within individual variation post-acclimation at 5°C than pre-acclimation at the same temperature, however, very similar variation between pre-and post-acclimation at 25°C. At 5°C, Howick sunbirds showed greater between individual variation pre-acclimation, but a similar between individual variation pre- and post-acclimation at 25°C (Fig. 3). The low altitude Oribi Gorge pre- and post-acclimation subpopulation data (Fig. 4) showed more variation between individuals pre-acclimation at 5°C, but similar variation between pre- and post-acclimation at 25°C.
|
|
O2
of different altitudinal subpopulations of amethyst sunbirds (Figs
5,
6 and
7) levelled off to RMR between
19:00–05:00 h.
O2 increased
pre-dawn (06:00 h) starting at approximately 05:00 h, and
O2 started to
decrease pre-sunset (18:00 h). The low altitude Oribi Gorge sunbirds displayed
the lowest inter-individual variation (Fig.
7), and the high altitude Underberg sunbirds the highest
inter-individual variation (Fig.
5) over the range of ambient temperatures. Howick sunbirds
displayed a high inter-individual variation in
O2 at
Tas of 5–20 and 33°C
(Fig. 6), but a decrease in
individual variation between Ta=25–30°C, thus
corresponding to the TNZ. Inter-individual variation increased as altitude
increased.
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|
|
Winter mean resting metabolic rates for each of the different amethyst
sunbirds subpopulations over the range of ambient temperatures are summarised
in Fig. 8. There was little
variation in O2
between individuals from the same locality, whereas significant variation was
observed at the same temperatures between localities and thus between
altitudes. There was a significant effect of altitude and temperature when
comparing O2
values for the subpopulations of sunbirds (RM ANOVA,
F(14,70)=21.039, P<0.001). There was a
significant difference between the
O2 values of the
high altitude Underberg and low altitude Oribi Gorge subpopulations at 5, 10,
15, 20, 28, 30°C (post-hoc Sheffé, P<0.05),
and between Underberg and Howick subpopulations at 25 and 28°C
(post-hoc Sheffé, P<0.05), and finally between
Howick and Oribi Gorge subpopulations at 5, 10 and 15°C (post-hoc
Sheffé, P<0.05). BMR was determined for each subpopulation
by using the mean of the lowest hourly individual RMRs: Underberg
[5.71±0.402 ml O2 g–1 h–1
(0.032 W) at 33°C], Howick [2.46±0.299 ml O2
g–1 h–1 (0.014 W) at 28°C] and Oribi
Gorge [3.49±0.312 ml O2 g–1
h–1 (0.019 W) at 30°C].
|
Post-hoc Sheffé tests (P<0.05), rather than regression lines, were used to determine the winter thermal neutral zone (TNZ), and differences in the TNZ range between altitudinal subpopulations were evident (Underberg=15–33°C, Howick=25–30°C and Oribi Gorge=5–33°C), with the subpopulation at the lowest altitude having the broadest TNZ.
Body mass
There was no significant difference between winter mean pre- and
post-acclimation body mass (g) of amethyst sunbirds within sites, nor were
there significant differences between winter pre- and post-acclimation body
masses between altitudinal subpopulations of amethyst sunbirds
(Fig. 9; RM ANOVA,
F(2,22)=0.345, P=0.712).
|
Ambient temperature
Ambient temperatures for the three altitudinal locations (January
2004–May 2007), Underberg (Shaleburn), Howick (Cedara), and Oribi Gorge
(Paddock) are given in Table 1
as per data obtained from the South African Weather Service. Underberg
consistently had lower ambient temperatures over the winter months (May to
August) than the other altitudinal locations. Howick had higher mean ambient
temperatures than Oribi Gorge in the winter months.
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|
DISCUSSION |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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;
Cooper and Swanson, 1994;
Maddocks and Geiser, 2000;
McKechnie and Lovegrove, 2001;
López-Calleja and Bozinovic,
2003; Lovegrove and Smith,
2003; McKechnie et al.,
2007; Smit et al.,
2008). However, this winter study showed that populations respond
differently to acclimation, possibly as a result of persistent underlying
physiological differences, or persistent effects of altitudinal
acclimatization. Recent evidence suggests that winter BMRs of species living
in highly seasonal environments reflect the conditions that the animals were
in immediately prior to metabolic measurements being taken
(McKechnie, 2008). As a result
of this, after the 6 week acclimation period to 25°C and an altitude of
660 m, we would expect birds from all of the altitudinal subpopulations to
react similarly if not uniformly to the range of ambient temperatures of the
respirometry trials, and thus differently to pre-acclimation trials, thereby
displaying similar phenotypic flexibility. However, differences in winter MR,
and in particular winter BMR, between subpopulations in post-acclimation
trials indicate that this is not necessarily the case. Altitudinal
subpopulations still showed differences in MR post-acclimation, thus
indicating that captive-bred populations of birds would not represent the
entire species as well as might be assumed, unless altitudinal origin of the
original population is known, and laboratory populations represent
subpopulations over the entire altitudinal gradient occupied by the species.
It is also difficult to assess the end point of thermal acclimation
(Rezende et al., 2004;
Bush et al., 2008a) and thus it
is possible that this was merely a stage in the ability of amethyst sunbirds
to change their thermal phenotype over a longer period of time.
The fact that there was no significant difference between the winter
post-acclimation masses of the three subpopulations of amethyst sunbirds
showed that these differences in winter RMR and BMR were not a result of the
effects of body mass and thus may indicate a difference in acclimation
strategies, most likely as a result of adapting to life in different
altitudinal and thus thermal environments. This further emphasizes the need
for knowledge of the origin of study populations, and not just in terms or
captive versus wild-caught populations. In recent comparative avian
reviews, much focus is placed on whether study birds were captive bred or wild
caught (e.g. Weathers et al.,
1983; McKechnie et al.,
2007; McKechnie,
2008) and on phenotypic flexibility. However, changing views in
avian physiology as yet omit to recognize the altitudinal origin of the study
population. A review by McKechnie
(McKechnie, 2008) recognized
that the data in the literature often uses a single BMR value per species and
is assumed to represent a fixed species-specific value. Indeed, most studies
of avian thermoregulatory abilities have used a mean BMR from one population
as a representative for the entire species, which does not take into
consideration the altitudinal origin of the study animals, seasonal effects,
nor does it acknowledge the fact that phenotypic flexibility, with respect to
physiological parameters, may not be consistent throughout a species.
Amethyst sunbirds exhibited significant differences in winter
pre-acclimation metabolic rates at both 5 and 25°C, indicating that
altitudinal acclimatization plays a big role in sunbird physiology at any
point in time. The results also indicate that different subpopulations show
different responses to acclimation, and that differences in TNZ were evident
post-acclimation, which indicated that physiological differences were not just
a result of acclimation to the temperature and altitude of the acclimation
site. Post-acclimation results also showed significant differences in winter
O2 between
Underberg and Oribi Gorge subpopulations at 5, 10, 15, 20, 28, 30°C,
between Underberg and Howick amethyst sunbird subpopulations at 25, 28°C
and between Howick and Oribi Gorge subpopulations at 5, 10 and 15°C.
Similarly, Soobramoney et al. (Soobramoney
et al., 2003) found that there was a difference in metabolic rates
of the common fiscal (Lanius collaris) over an altitudinal
temperature gradient as colder temperatures at high altitudes require an
increase in metabolic heat production in homeotherms. However, common fiscals
showed higher metabolic rates in subpopulations from the warmer altitudes,
whereas amethyst sunbirds subpopulations from the warmer location (Oribi
Gorge, lowest altitude) showed lower winter metabolic rates. As winter
temperatures vary dramatically between the two habitats it would be expected
that individuals that could survive in that range of ambient temperatures
would be selected for over the generations and thus we would expect underlying
physiological differences between altitudinal subpopulations.
Our data, and that of other altitudinal studies, emphasizes the need to acknowledge altitudinal differences between populations and not just use species means, as species means do not fully incorporate the effect of phenotypic plasticity/flexibility. In this study variation in MR was only examined during winter.
Amethyst sunbirds exhibited high levels of phenotypic flexibility between the three different subpopulations studied. This variation reflects acclimatization at the population level, and indicates that geographic conditions (altitude and ambient temperature) play a major role in influencing animal physiology. It also indicates that amethyst sunbirds have the capacity to adapt to a range of climatic conditions, suggesting that the impact of climate change may not be as severe on bird distributional ranges as previously thought.
Conclusion
Variation exists in winter RMR, BMR and TNZ between populations of amethyst
sunbirds over an altitudinal gradient. Variation persisted, if not increased,
post-acclimation, indicating phenotypic flexibility within the species. Thus
acclimation time should be taken into account. Physiological phenotypic
flexibility within a species indicates differing abilities to adapt to climate
change and thus may lead to different survival predictions for each
population. Thus one subpopulation should not be used as a representative of a
species, and location and altitude of experimental subpopulations should be
taken into account when making species predictions or comparing species in
terms of BMR and RMR.
LIST OF ABBREVIATIONS
O2
|
Acknowledgments |
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|
References |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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