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A comparative analysis of thermogenic capacity and cold tolerance in small birds
David L. Swanson, Eric T. Liknes
Journal of Experimental Biology 2006 209: 466-474; doi: 10.1242/jeb.02024
David L. Swanson
Eric T. Liknes
Small birds showing marked seasonal changes in cold tolerance also exhibit winter increases in summit metabolic rate (Msum=maximum cold-induced thermogenesis or thermogenic capacity) relative to summer birds. However, some birds show modest seasonal changes in cold tolerance without winter increases in Msum and others exhibit large seasonal changes in cold tolerance with only minor changes in Msum. Thus, the degree of correlation between cold tolerance and Msum is uncertain and no interspecific study has directly addressed this question. In this study, we measured cold tolerance and Msum in summer- (21 species) and winter- (11 species) acclimatized birds from southeastern South Dakota. Msum was measured as the maximum oxygen consumption attained during exposure of individual birds to a declining series of temperatures in 79% helium/21% oxygen (helox). Cold tolerance was measured as the temperature at cold limit (TCL), which is the helox temperature that induced hypothermia in individual birds. Residuals from allometric regressions of logMsum and logTCL were significantly and negatively related for summer (R2=0.34, P=0.006) and winter (R2=0.40, P=0.037) birds. Data were also subjected to a comparative analyses with phylogenetically independent contrasts to remove potential confounding effects of phylogeny, and results were similar to the non-phylogenetic analyses, with significant negative correlations in both summer (R2=0.47, P<0.001) and winter (R2=0.40, P=0.049). Thus, birds with high Msum tended to show reduced TCL (i.e. high cold tolerance), suggesting that cold tolerance and summit metabolism are phenotypically linked in small birds.
thermogenesis
acclimatization
Small birds wintering in temperate regions generally show markedly improved cold tolerance capabilities relative to summer-acclimatized birds (Marsh and Dawson, 1989; Swanson, in press). This winter acclimatization primarily results from an increased ability to sustain high levels of shivering thermogenesis over prolonged periods (Marsh and Dawson, 1989). In birds showing marked winter improvement of cold tolerance, this improvement is also associated with expanded Msum (summit metabolism or thermogenic capacity), typically measured by indirect calorimetry as the maximal rate of oxygen consumption under cold stress (Dawson and Smith, 1986; Marsh and Dawson, 1989; Swanson, 1990a; Cooper and Swanson, 1994; Liknes and Swanson, 1996; Liknes et al., 2002; Cooper, 2002). Furthermore, birds that show relatively minor seasonal differences in cold resistance also show no, or only minor, seasonal differences in Msum (Dawson et al., 1983a; Saarela et al., 1989, 1995; Swanson and Weinacht, 1997). Thus, during winter acclimatization the expanded Msum is closely associated with increased shivering endurance at submaximal levels of cold challenge. Indeed, Swanson (2001) demonstrated that shivering endurance under a standardized cold exposure was positively correlated with Msum in three species of small passerines. Moreover, expanded endurance is tied to enhanced maximal capacities for aerobic activity in vertebrate animals generally (Bennett, 1991).
Nevertheless, seasonal changes in shivering endurance and cold resistance in some species of small birds may occur without corresponding changes in Msum, and geographic variation in cold resistance is not always associated with variation in Msum (Dawson et al., 1983a; Swanson, 1993). Thus, cold tolerance and Msum do not always change in lockstep and the extent of their phenotypic correlation is uncertain. Shivering endurance and Msum are correlated intraspecifically in small birds (Swanson, 2001), but the interspecific relationship between cold tolerance and Msum has not been directly examined for birds. Intraspecific seasonal changes in cold tolerance in birds are concluded either when birds tolerate a static cold exposure longer in winter than in summer (e.g. Dawson and Carey, 1976; Dawson and Smith, 1986; Cooper and Swanson, 1994) or when colder temperatures are required to induce hypothermia in winter than in summer (Saarela et al., 1989, 1995; Liknes et al., 2002). Efforts to test the interspecific relationship between cold tolerance and Msum have not yet been undertaken, and are potentially confounded by body size effects on metabolic rates and heat loss. Testing the relationship between Msum and cold tolerance requires a standardized cold exposure among species and measurement of either shivering endurance or the temperature inducing hypothermia. Developing a standardized measure of shivering endurance requires a standardized cold challenge for all species measured, which is difficult, if not impossible, to attain because factors such as body size and thermal conductance vary among species and greatly impact heat loss to the environment (Aschoff, 1981). One way around this problem, however, is to hold shivering endurance essentially constant while measuring the temperature in helox (79% helium/21% oxygen) required to elicit hypothermia (or the temperature at the cold limit, TCL; after Saarela et al., 1989).
The objective of this study was to examine the interspecific relationship between cold tolerance (measured as TCL under a sliding helox cold exposure) and Msum in both summer and winter in a phylogenetically diverse sample of small birds. We used both standard and phylogenetically corrected methods to analyze the interspecific Msum/TCL relationship to determine whether phylogeny influenced any correlation between Msum and TCL. To our knowledge, this is the first study to directly examine, using relevant comparative techniques, whether an interspecific phenotypic correlation between cold tolerance and Msum exists for birds.
Birds and collection
We measured Msum and TCL for 21 species in summer and 11 species in winter (Table 1); these species ranged in body mass Mb from 9.2 to 62.6 g. All birds used in the present study were captured by mist net in summer (late April-August) or winter (December-February) near Vermillion, Clay County, South Dakota, USA (42°47′N, 97°0′W). The species used in this study are all common summer, winter or permanent residents in this area. Following capture, birds were transported to the laboratory where they were held at room temperature (22°C), with food (bird seed, mealworm larvae and/or mulberries) and water ad libitum, until cold exposure tests later on the day of capture. Body mass was measured to the nearest 0.1 g immediately prior to cold exposure tests, which were conducted from 09:00 h-20:00 h CST in summer and from 10:00 h-19:00 h CST in winter. Following cold exposure tests, birds were banded with a standard US Fish and Wildlife Service leg band and released at the site of capture. Msum and TCL were measured only once on individual birds.
Mass, summit metabolism and cold tolerance data for summer- and winter-acclimatized small birds
Measurement of cold tolerance and Msum
Standardized conditions for determining TCL must be delineated to use cold tolerance data for comparative analyses. Swanson et al. (1996) suggested standard methods for eliciting Msum in birds by sliding cold exposure in helox that we adapted for measurement of TCL. Using this method, we exposed an individual bird to a declining series of temperatures in 79% helium/21% oxygen (helox), where temperature was decreased by 3°C at 25 min after the initiation of cold exposure, and every 20 min thereafter, until hypothermia was induced. We concluded that hypothermia had occurred when oxygen consumption decreased steadily, without rebounding, over several minutes, reaching levels lower than those recorded over the preceding portion of the cold exposure test. To verify hypothermia, we removed birds from the metabolic chamber and measured body temperature with a Cole-Parmer Model 8500-40 Thermocouple Thermometer (Chicago, IL, USA) by inserting a lubricated 20-gauge copper-constantan thermocouple into the cloaca to a depth (approximately 1 cm) where further insertion did not alter the temperature reading. We considered birds with body temperature Tb<37°C as hypothermic, and birds were invariably hypothermic when the conditions noted above had been met. We defined the helox temperature at the beginning of this steady decline in oxygen consumption as TCL. One further matter in the standardization of TCL measurement involves the temperature at which the sliding helox cold exposure is initiated. Because TCL is affected by body mass, to keep thermogenic endurance roughly standardized among species, cold exposure tests must begin at higher temperatures for smaller birds.
Based upon previous studies using both sliding and static helox cold exposure in both summer- and winter-acclimatized birds (Dawson and Smith, 1986; Swanson, 1990a, 1993; Cooper and Swanson, 1994; O'Connor, 1995a; Dutenhoffer and Swanson, 1996; Liknes and Swanson, 1996; Swanson et al., 1996), we initially measured TCL by sliding helox cold exposure for nine species of summer-acclimatized passerines (Contopus virens, Tyrannus tyrannus, Vireo gilvus, Dumetella carolinensis, Troglodytes aedon, Carduelis tristis, Spizella pusilla, Dendroica petechia and Pheucticus ludovicianus) ranging from 9.6 to 40.7 g mean body mass, and for five species of winter-acclimated birds (Picoides pubescens, P. villosus, Sitta carolinensis, Cardinalis cardinalis and Passer domesticus) ranging from 21.8 to 62.6 g mean body mass. For TCL measurements on these species, sliding helox cold exposure was initiated either (1) at 6-8°C above temperatures producing hypothermia in a majority of individuals within 1 h in previous studies using static cold exposure, (2) at 6-8°C above TCL from previous studies using sliding cold exposure, or (3) if cold tolerance had not previously been measured for that species, from extrapolations based on body mass from previous studies on other species. From these TCL data, we calculated mean TCL for each of these species and generated an allometric equation predicting TCL for both summer- and winter-acclimatized birds:
where TCL is in °C and Mb is in g. For subsequent TCL experiments, sliding helox cold exposure was initiated at temperatures 6°C above the allometrically predicted TCL. The initial temperature was then modified for each species, as needed, so that hypothermia did not occur too rapidly (<45 min) or too slowly (>2 h) for comparative purposes.
In the current study, we measured TCL concurrently with Msum determination on individual birds. We measured summit metabolic rate by open-circuit respirometry using a sliding cold exposure in helox (Swanson et al., 1996). Briefly, we placed birds into 1.9 l or 3.8 l paint cans (depending on body size), with the inner surface painted flat black to provide emissivities near 1.0, which served as metabolic chambers. Mean effective volumes of these chambers, calculated according to Bartholomew et al. (1981), were 1917 ml and 4688 ml for the 1.9 l and 3.8 l chambers, respectively. We achieved temperature control within metabolic chambers by immersing them into a bath of water and propylene glycol (Forma Scientific Model 2095; Marietta, OH, USA), which regulated chamber temperature to ±0.5°C. Prior to immersion, we flushed the chamber for at least 5 min with helox to replace air with helox. We maintained flow rates of dry, CO2-free, helox at 1010-1030 ml min-1 over the course of the experiments using a Cole-Parmer Precision Rotameter (Model FM082-03ST; Chicago, IL, USA), previously calibrated to ±1% accuracy. We measured fractional oxygen content in excurrent gas leaving the chamber using an Ametek S-3A oxygen analyzer (Pittsburgh, PA, USA). We recorded fractional oxygen content every 60 s over the test period and computed oxygen consumption according to the instantaneous equations of Bartholomew et al. (1981). We then calculated consecutive 10 min means for oxygen consumption rates over the test period (1-10, 2-11, etc.) and considered the highest 10 min mean, excluding the initial 10 min of measurements), as Msum (Dawson and Smith, 1986). We corrected all values for oxygen consumption to STPD and converted oxygen consumption to metabolic rates (in W) by assuming an energy equivalent of 20.1 J ml-1 O2.
Phylogeny of bird species used in comparative analyses in this study. Tree topology and branch lengths represent genetic distances (ΔT50H values) from DNA/DNA hybridization data (Sibley and Ahlquist 1990). The total distance from the base node of the tree to the branch tips is 26.3 for the species in this study.
During cold exposure treatments, we exposed individual birds to a declining series of temperatures in helox (3°C every 20 min after 25 min at the initial test temperature) until a gradual decrease in oxygen consumption indicative of hypothermia occurred. These conditions have been shown to elicit Msum in birds (Dutenhoffer and Swanson, 1996; Swanson et al., 1996). For a few individuals in winter (three horned larks Eremophila alpestris, two northern cardinals Cardinalis cardinalis), birds did not become hypothermic after 3 h of cold exposure reaching the lowest temperatures the bath was capable of attaining (approximately -17.5°C), so it is not certain that these individuals attained Msum and they did not reach TCL. However, oxygen consumption in these individuals was essentially constant over at least the last hour of cold exposure, despite declining temperatures in helox, so it is likely that birds were very close to Msum. In addition, since some individuals of these species did become hypothermic at similar temperatures, it is likely that these individuals had also approached TCL. Although mean TCL was undoubtedly slightly underestimated for these species, this should make the interspecific Msum/TCL relationship conservative, as these two species had higher Msum than was allometrically predicted (Table 1).
We analyzed the relationship between Msum and TCL both by conventional statistical methods and by phylogenetically independent contrasts (Felsenstein, 1985; Garland et al., 1992). For conventional analyses, we performed least-squares regressions of logMb vs logMsum and logMb vs logTCL. We then calculated residuals from these allometric equations and performed least-squares regression of residuals of logTCL against residuals of logMsum. While this approach controls for the effects of mass on the Msum/TCL relationship, it does not account for possible phylogenetic influence on the relationship.
Consequently, we calculated phylogenetically independent contrasts (PIC) for logMb, logMsum and logTCL according to Garland et al. (1992, 1993). Calculation of phylogenetically independent contrasts requires knowledge of tree topology and branch lengths, which we garnered from Sibley and Ahlquist (1990) (Fig. 1). Most species for which we measured Msum in this study either have branch length data provided directly in the study of Sibley and Ahlquist (1990) or are closely related to species that are listed, so that branch lengths can be determined. We used arbitrary branch lengths of 1.0 in the summer analysis for divergences of chipping (Spizella passerina) and field (S. pusilla) sparrows and for Baltimore (Icterus galbula) and orchard (I. spurious) orioles (based, respectively, on divergence distances within Melospiza sparrows of 1.3 or less and a divergence distance of 1.2 for orioles and New World blackbirds; Sibley and Ahlquist, 1990). In addition, we used a branch length of 2.8 for the Bell's-warbling vireo divergence, because that is the divergence distance between congeneric blue-headed and white-eyed vireos (Sibley and Ahlquist, 1990). In addition, analyses using PIC are robust to actual branch length variation (Garland et al., 1999), so the few arbitrary branch lengths used in this study are unlikely to influence PIC results. We initially standardized contrasts by dividing by branch lengths, but absolute values of contrasts were potentially correlated with their branch lengths, so branch lengths were log-transformed after first increasing the scale of the entire phylogenetic tree by a factor of 10. This reduced correlations to non-significant levels so that contrasts were weighted equally in subsequent analyses. Standardized contrasts were positivized on Mb according to Garland et al. (1992). We then performed least-squares regression through the origin on positivized contrasts of logMb vs logMsum and on logMb vs logTCL. We calculated residuals from logMsum and logTCL PIC allometric regressions and performed least-squares regression on residuals of logTCL contrasts against residuals of logMsum contrasts to test for phenotypic correlation independent of body mass and phylogeny.
To analyze phylogenetic diversity in the relationship between Msum and TCL, we calculated 95% confidence intervals around allometric regression lines for raw data and PIC regressions for Msum and TCL. We considered values for species (raw data) or for ancestral nodes (PIC) falling outside these confidence intervals as having high or low Msum or TCL (for allometric regressions).
We generated Msum and TCL data for 21 species in summer and 11 species in winter that ranged in body mass from 9.2-62.6 g (Table 1). Mean time to hypothermia (thypo) for different species ranged from 33 to 99 min in summer, with most values between 45 and 90 min, and from 40-170 min in winter, with most values between 65 and 105 min, so the goal of inducing hypothermia between 45 and 120 min was met for most species (Table 1).
Regressions of logMsum (A) and logTCL (B) against logMb in summer (solid line) and winter (broken line). At both seasons, logMsum was significantly and positively associated with logMb and logTCL was significantly and negatively related to logMb. Winter equations were significantly elevated for logMsum and significantly lower for logTCL than summer equations, suggesting that winter increases in Msum are correlated with decreases in TCL. Msum, W; TCL,° K; Mb, g.
Least-squares regression yielded significant positive relationships between logMb (in g) and logMsum (in W) for both summer and winter birds (Fig. 2A). Regression equations were:
Slopes of logMsum vs logMb regressions did not differ significantly between seasons (F1,60=4.63, P>0.05), but the winter intercept was significantly higher than the summer intercept (F1,29=27.83, P<0.001). Similarly, logMb (in g) and logTCL (in °K) were significantly negatively related in both summer and winter birds (Fig. 2B). Regression equations were:
Slopes of logTCL vs logMb regressions did not differ significantly between seasons (F1,60=1.44, P>0.05), but the winter intercept was significantly lower than the summer intercept (F1,29=87.99, P<0.001). Residuals of logMsum/logMb and logTCL/logMb regressions were significantly negatively related in both summer (R2=0.34, P=0.006) and winter (R2=0.40, P=0.037) (Fig. 3).
Residuals from logMsum vs logMb regressions plotted against residuals from logTCL vs logMb regressions. Residuals of logMsum were significantly and negatively associated with residuals of logTCL at both seasons, indicating a phenotypic correlation between Msum and TCL.
Phylogenetically independent contrast analysis
Least-squares regression through the origin of phylogenetically independent contrasts of logMsum against logMb yielded significant positive relationships for both summer and winter birds. For summer birds, regression statistics were b=0.70, R2=0.66, P<0.001. Regression statistics for this relationship in winter were b=0.50, R2=0.73, P=0.001. Regressions through the origin for logMb and logTCL (°K) contrasts were significantly negatively related in summer birds and showed a similar non-significant trend for winter birds. Regression statistics for the summer equation were b=-0.029, R2=0.29, P=0.012. Regression statistics for the winter equation were b=-0.012, R2=0.25, P=0.124. Residuals from allometric equations for logMsum and logTCL contrasts were significantly negatively correlated in both summer (R2=0.47, P<0.001) and winter (R2=0.40, P=0.049) (Fig. 4).
Residuals from logMsum contrasts vs logMb contrasts regressions plotted against residuals from logTCL contrasts vs logMb contrasts regressions. Residuals of logMsum contrasts were significantly and negatively associated with residuals of logTCL contrasts at both seasons, indicating a phenotypic correlation between Msum and TCL independent of both body mass and phylogeny.
Phylogenetic diversity
Species exhibiting high Msum in summer included downy woodpecker, house wren, black-capped chickadee, house sparrow, American goldfinch and field sparrow (Fig. 5A). Species with low Msum in summer were eastern wood-pewee, Bell's vireo, gray catbird, white-breasted nuthatch, orchard oriole and rose-breasted grosbeak. Those species with high or low Msum also generally showed low or high TCL, respectively. Exceptions included gray catbird and rose-breasted grosbeak, which had low Msum but typical TCL, house wren and black-capped chickadee, which had high Msum but typical TCL, downy woodpecker, which had high Msum but high TCL, and house finch, which had typical Msum but low TCL.
Winter species with high Msum included black-capped chickadee and house sparrow, whereas those with low Msum were downy woodpecker and white-breasted nuthatch; these latter two species also showed high TCL (Fig. 5B). However, even though chickadees and house sparrows had high Msum, their TCL was typical for allometric predictions. American tree sparrows had low TCL, despite exhibiting typical Msum for their body size.
PIC analyses documented ancestral nodes showing high or low Msum or TCL (Fig. 5). For summer analyses, nodes with high Msum included the root node for the entire tree, the vireo node, the house sparrow-sister taxon node, the Spizella node, the warbler-oriole/cardinalid node, and the oriole node (Fig. 5A). Nodes with low Msum were the catbird node, the chickadee-nuthatch/wren node, the nuthatch-wren node, the Spizella-warbler/oriole/cardinalid node and the oriole-cardinalid node (Fig. 5B). Nodes showing high or low Msum also generally showed low or high TCL, respectively. Exceptions included the root node and the warbler-oriole/cardinalid node, which had high Msum but typical TCL, the oriole-cardinalid node, which had low Msum but typical TCL, and the woodpecker and nuthatch/wren/chickadee nodes, which had typical Msum but low TCL. The only winter node with high Msum was the house sparrow-finch/sparrow/cardinalid node, but this node showed typical TCL. The only winter node with low Msum was the nuthatch-chickadee node, which also showed high TCL. The nuthatch/chickadee-sister taxon and horned lark-sister taxon nodes both showed low TCL but typical Msum.
Cold tolerance and thermogenic capacity were positively correlated in both summer and winter on an interspecific basis for both standard and phylogenetically corrected analyses in this study. This indicates that species with higher thermogenic capacity also showed greater cold tolerance, as measured by lower TCL, suggesting that cold tolerance and thermogenic capacity are functionally linked. These data are consistent with intraspecific data on thermogenic capacity and cold tolerance in small birds. Swanson (2001) measured cold tolerance as shivering endurance under cold stress in black-capped chickadees Poecile atricapillus, dark-eyed juncos Junco hyemalis and American tree sparrows Spizella arborea, all of which showed positive correlations between shivering endurance and thermogenic capacity. Thus, both within and among species comparisons demonstrate a positive correlation between cold tolerance and thermogenic capacity, strongly suggesting a functional link between them.
Such a correlation is also generally consistent with previous data on seasonal acclimatization in small birds. A few birds exhibit seasonal changes in cold tolerance without accompanying seasonal changes in thermogenic capacity, and geographic variation in cold tolerance is not always associated with corresponding variation in thermogenic capacity (Dawson et al., 1983a; Swanson, 1993; Saarela et al., 1995). Such data have cast doubt on the generality of the correlation between thermogenic capacity and cold tolerance. However, most species of small birds do show a significant winter increment of thermogenic capacity that is associated with substantial improvements in capacity to tolerate cold temperatures (Hart, 1962; Swanson, 1990a; Cooper and Swanson, 1994; O'Connor, 1995a; Liknes and Swanson, 1996; Liknes et al., 2002; Cooper, 2002; Arens and Cooper, 2005a). Winter increments of thermogenic capacity documented in these studies range from 16-55%. If thermogenic capacity and cold tolerance are generally elevated in winter relative to summer in small birds, then regression equations of logMsum on logMb should be elevated, and regression equations of logTCL on logMb should be lower, in winter compared to summer. Such was indeed the case in this study, as slopes of these regressions did not differ significantly between seasons, but intercepts were significantly higher for Msum and significantly lower for TCL in winter than in summer. In general, therefore, winter birds had higher thermogenic capacity and tolerated colder temperatures in helox than summer birds. For example, according to the regression equations in this study, a 20 g bird would have a 28.2% higher Msum and would require a helox temperature 6.8°C lower to induce hypothermia in winter relative to summer. The seasonal temperature difference for hypothermia induction in helox substantially underestimates the actual seasonal temperature difference in air, as helox markedly increases thermal conductivity relative to air in small birds (Dawson and Smith, 1986; Swanson, 1993; Cooper, 2002), so seasonal differences in cold tolerance are quite marked for the species in this study.
Thus, winter increment of thermogenic capacity appears to be a common component of seasonal acclimatization in small birds. Taken together, data demonstrating concomitant seasonal variation in cold tolerance and thermogenic capacity and direct demonstration of correlations between cold tolerance and thermogenic capacity, both within and among species, strongly suggest that physiological adjustments promoting increased thermogenic capacity in small birds also promote elevated cold tolerance. This suggests that cold tolerance (i.e. thermogenic endurance) and thermogenic capacity are functionally linked, potentially through variation in muscle mass or by adjustments of mass-specific metabolic intensity or capacity to oxidize fuels, principally fat (Dawson et al., 1983b; Marsh and Dawson, 1989; Swanson, in press). Such a link is consistent with the general vertebrate pattern of coupled variation in endurance and aerobic capacity (Bennett, 1991).
Occurrence of high (solid bold lines) and low (broken lines) Msum for tips of phylogenies for summer and winter birds in this study. The numbers and letters at the ancestral nodes and branch tips refer to high Msum (1), low Msum (2), low TCL (good cold tolerance; A), high TCL (poor cold tolerance; B). Low and high Msum and TCL were determined from tips or nodes that fell outside of 95% confidence intervals from allometric regressions of logMsum and logTCL on logMb for both raw data and phylogenetically independent contrasts.
Because metabolic rates (M) in endotherms can be defined by:
where C is thermal conductance (a net measure of heat transfer between the animal and the environment), Tb is body temperature and Ta is ambient temperature, a link between Msum and TCL is perhaps not surprising. At temperatures eliciting maximum cold-induced metabolic rates in birds, Msum and TCL can potentially be substituted into the above equation, yielding, after rearrangement:
which suggests that Msum and TCL should be linked (e.g. Bozinovic and Rosenmann, 1989). However, two factors could influence this purported linkage. First, variation in Msum is not the only factor that influences TCL. Concurrent variation in C or Tb could offset any variation in Msum, such that Msum and TCL might not be correlated. In essence, testing for a correlation between Msum and TCL is akin to testing for how much variation in TCL is explained by variation in Msum, rather than by other factors that affect C or Tb. Second, substituting Msum and TCL into the above equation assumes that TCL always occurs concurrently with Msum, but this is often not the case, as the highest metabolic rates (Msum) during cold exposure treatments, such as those in this study, usually occur well before temperatures eliciting hypothermia (Swanson, 2001). Thus, substituting Msum and TCL into the equation describing metabolic rates in endotherms is probably not strictly appropriate.
R2 values for regressions of residuals from allometric equations for Msum and TCL ranged from 34-47% in this study, indicating that interspecific variation in thermogenic capacity explained a substantial portion of the interspecific variation in cold tolerance. However, substantial variation in cold tolerance still remains unexplained, which suggests a role for other factors in affecting differences in cold tolerance among species and seasons. Such factors could include differences in insulation, control over thermal conductance, circulatory and ventilatory differences (Swanson, 1990b; Breuer et al., 1995; Arens and Cooper, 2005a,b), or metabolic adjustments promoting shivering endurance without affecting thermogenic capacity (Marsh and Dawson, 1982; Yacoe and Dawson, 1983; Marsh et al., 1990).
Because seasonal acclimatization in birds is largely a metabolic process, with only a minor role played by seasonal changes in insulation (Dawson et al., 1983b; Marsh and Dawson, 1989; Swanson, 1991a), metabolic adjustments should play a prominent role in explaining both seasonal and interspecific variation in cold tolerance. Such metabolic adjustments could include those affecting fuel mobilization and supply to shivering muscles, as well as those promoting preferential use of lipid to fuel shivering (Marsh and Dawson, 1982; Yacoe and Dawson, 1983; Marsh et al., 1990; Swanson, 1991b; O'Connor, 1995b). These adjustments would not necessarily be reflected by increases in thermogenic capacity, but could increase cold tolerance by elevating the percentage of thermogenic capacity that could be sustained for prolonged periods. This model for seasonal variation in cold tolerance was posited by Marsh and Dawson (1989), largely from studies on American goldfinches and house finches. Liknes et al. (2002) termed this model the variable fraction model, because the model contends that it is the fraction of thermogenic capacity that is sustainable which varies seasonally, rather than the thermogenic capacity. In contrast to this model is the variable maximum model (Liknes et al., 2002), which posits that it is thermogenic capacity that varies seasonally. The winter increment of thermogenic capacity, in turn, increases thermogenic endurance in the cold, because as thermogenic capacity increases, the absolute rate of sustainable heat production also increases, even if the fraction of thermogenic capacity that is sustainable remains seasonally constant. Because the data in this study indicate a winter increment of thermogenic capacity and directly document a correlation between thermogenic capacity and cold tolerance in small birds, they are consistent with the variable maximum model. However, it is important to note that metabolic adjustments promoting maintenance of a higher sustained fraction of thermogenic capacity could further improve cold tolerance, and therefore might help account for some of the unexplained variation in cold tolerance in this study.
Some interesting general trends emerged from analyses of phylogenetic diversity in the relationship between Msum and TCL. For summer analyses, the root node had high Msum, but typical TCL based on allometric predictions, whereas in winter the root node was typical for both parameters. The summer data suggest that ancestral species had high thermogenic capacity, but were relatively poorly insulated, resulting in relatively poor cold tolerance for their metabolic abilities. However, in winter, where taxa not resident in cold climates were absent from the analyses, the root node was typical for both Msum and TCL, suggesting that it is taxa not resident in cold climates that were driving the uncoupling of Msum and TCL from summer analyses. Another factor likely influences this uncoupling, however, and that is the absence of a winter increase in Msum in downy woodpeckers in this study. Because downy woodpeckers had high Msum in summer and low Msum in winter, and woodpeckers were one of the sister taxa at this node, the nodal values were likely influenced by the absence of a seasonal difference in Msum in this species. The lack of a seasonal difference in Msum in downy woodpeckers differs from that previously documented for this species by Liknes and Swanson (1996), where Msum in winter was 52% greater than that in summer. The reason for the difference between these two studies is unknown, but may involve differences in winter weather among years, which can impact metabolic rates in birds (Swanson and Olmstead, 1999).
Another noteworthy finding from summer analyses was that high Msum and low TCL, as well as low Msum and high TCL, occurred in taxa composed solely of migrants, as well as taxa with members wintering in cold climates. This suggests that physiological capacities for heat production or cold tolerance are not the sole determinant of wintering strategy within a taxon. Finally, although deviations from allometric predictions for Msum and TCL were usually coupled for species and for ancestral nodes, this was not always the case. This again suggests that while thermogenic capacity is a prominent factor influencing cold tolerance, there is still room for factors other than thermogenic capacity in establishing differences in cold tolerance among species and seasons.
Funding for this study was provided by NSF EPSCoR grant 0091948, the American Philosophical Society, and the USD Office of Research. We thank Karen Olmstead for advice on statistical analyses. Birds were captured under federal collecting permit 758442 and South Dakota collecting permits. All procedures in the study approved by the University of South Dakota IACUC and were consistent with guidelines provided by the American Ornithologists' Union.
↵† Present address: Department of Biology, Augustana College, 2001 S. Summit Avenue, Sioux Falls, SD 57197, USA
Aschoff, J. (1981). Thermal conductance in mammals and birds: its dependence on body size and circadian phase. Comp. Biochem. Physiol. 69A,611 -619.
Arens, J. R. and Cooper, S. J. (2005a). Metabolic and ventilatory acclimatization to cold stress in house sparrows (Passer domesticus). Physiol. Biochem. Zool. 78,579 -589.
Arens, J. R. and Cooper, S. J. (2005b). Seasonal and diurnal variation in metabolism and ventilation in house sparrows. Condor 107,433 -444.
Bartholomew, G. A., Vleck, D. and Vleck, C. M. (1981). Instantaneous measurements of oxygen consumption during pre-flight warm-up and post-flight cooling in sphingid and saturniid moths. J. Exp. Biol. 90,17 -32.
Bennett, A. F. (1991). The evolution of activity capacity. J. Exp. Biol. 160, 1-23.
Bozinovic, F. and Rosenmann, M. (1989). Maximum metabolic rate of rodents: physiological and ecological consequences on distributional limits. Funct. Ecol. 3, 173-181.
Breuer, K., Lill, A. and Baldwin, J. (1995). Haematological and body-mass changes of small passerines overwintering in south-eastern Australia. Aust. J. Zool. 43, 31-38.
Cooper, S. J. (2002). Seasonal metabolic acclimatization in mountain chickadees and juniper titmice. Physiol. Biochem. Zool. 75,386 -395.
Cooper, S. J. and Swanson, D. L. (1994). Seasonal acclimatization of thermoregulation in the black-capped chickadee. Condor 96,638 -646.
Dawson, W. R. and Carey, C. (1976). Seasonal acclimatization to temperature in cardueline finches I. Insulative and metabolic adjustments. J. Comp. Physiol. 112,317 -333.
Dawson, W. R. and Smith, B. K. (1986). Metabolic acclimatization in the American goldfinch (Carduelis tristis). In Living in the Cold: Physiological and Biochemical Adaptations (ed. H. C. Heller, X. J. Musacchia and L. D. H. Wang), pp. 427-437. New York: Elsevier.
Dawson, W. R., Marsh, R. L., Buttemer, W. A. and Carey, C. (1983a). Seasonal and geographic variation of cold resistance in house finches. Physiol. Zool. 56,353 -369.
Dawson, W. R., Marsh, R. L. and Yacoe, M. E. (1983b). Metabolic adjustments of small passerine birds for migration and cold. Am. J. Physiol. 245,R755 -R767.
Dutenhoffer, M. S. and Swanson, D. L. (1996). Relationship of basal to summit metabolic rate in passerine birds and the aerobic capacity model for the evolution of endothermy. Physiol. Zool. 69,1232 -1254.
Felsenstein, J. (1985). Phylogenies and the comparative method. Am. Nat. 125, 1-15.
Garland, T., Jr, Harvey, P. H. and Ives, A. R. (1992). Procedures for the analysis of comparative data using phylogenetically independent contrasts. Syst. Biol. 41, 18-32.
Garland, T., Jr, Dickerman, A. W., Janis, C. M. and Jones. J. A. (1993). Phylogenetic analysis of covariance by computer simulation. Syst. Biol. 42,265 -292.
Garland, T., Jr, Midford, P. E. and Ives, A. R. (1999). An introduction to phylogenetically based statistical methods, with a new method for confidence intervals on ancestral values. Am. Zool. 39,374 -388.
Hart, J. S. (1962). Seasonal acclimatization in four species of small wild birds. Physiol. Zool. 35,224 -236.
Liknes, E. T. and Swanson, D. L. (1996). Seasonal variation in cold tolerance, basal metabolic rate, and maximal capacity for thermogenesis in white-breasted nuthatches Sitta carolinensis and downy woodpeckers Picoides pubescens, two unrelated arboreal temperate residents. J. Avian Biol. 27,279 -288.
Liknes, E. T., Scott, S. M. and Swanson, D. L. (2002). Seasonal acclimatization in the American goldfinch revisited: to what extent do metabolic rates vary seasonally? Condor 104,548 -557.
Marsh, R. L. and Dawson, W. R. (1982). Substrate metabolism in seasonally acclimatized American goldfinches. Am. J. Physiol. 242,R563 -R569.
Marsh, R. L. and Dawson, W. R. (1989). Avian adjustments to cold. In Advances in Comparative and Environmental Physiology 4, Animal Adaptation to Cold (ed. L. C. H. Wang), pp.206 -253. Berlin: Springer-Verlag.
Marsh, R. L., Dawson, W. R., Camilliere, J. J. and Olson, J. M. (1990). Regulation of glycolysis in the pectoralis muscles of seasonally acclimatized American goldfinches exposed to cold. Am. J. Physiol. 258,R711 -R717.
O'Connor, T. P. (1995a). Metabolic characteristics and body composition in house finches: effects of seasonal acclimatization. J. Comp. Physiol. B 165,298 -305.
O'Connor, T. P. (1995b). Seasonal acclimatization of lipid mobilization and catabolism in house finches (Carpodacus mexicanus). Physiol. Zool. 68,985 -1005.
Saarela, S., Klapper, B. and Heldmaier, G. (1989). Thermogenic capacity of greenfinches and siskins in winter and summer. In Physiology of Cold Adaptation in Birds (ed. C. Bech and R. E. Reinertsen), pp.115 -122. New York: Plenum.
Saarela, S., Klapper, B. and Heldmaier, G. (1995). Daily rhythm of oxygen consumption and thermoregulatory responses in some European winter- or summer-acclimatized finches at different ambient temperatures. J. Comp. Physiol. B 165,366 -376.
Sibley, C. G. and Ahlquist, J. E. (1990). Phylogeny and Classification of Birds: A Study in Molecular Evolution. New Haven: Yale University Press.
Swanson, D. L. (1990a). Seasonal variation in cold hardiness and peak rates of cold-induced thermogenesis in the dark-eyed junco (Junco hyemalis). Auk 107,561 -566.
Swanson, D. L. (1990b). Seasonal variation of vascular oxygen transport in the dark-eyed junco. Condor 92,62 -66.
Swanson, D. L. (1991a). Seasonal adjustments in metabolism and insulation in the dark-eyed junco. Condor 93,538 -545.
Swanson, D. L. (1991b). Substrate metabolism under cold stress in seasonally acclimatized dark-eyed juncos. Physiol. Zool. 64,1578 -1592.
Swanson, D. L. (1993). Cold tolerance and thermogenic capacity in dark-eyed juncos in winter: geographic variation and comparison with American tree sparrows. J. Therm. Biol. 18,275 -281.
Swanson, D. L. (2001). Are summit metabolism and thermogenic endurance correlated in winter acclimatized passerine birds? J. Comp. Physiol. B 171,475 -481.
Swanson, D. L. (in press). Seasonal metabolic variation in birds: functional and mechanistic correlates. Curr. Ornithol. 17.
Swanson, D. L. and Olmstead, K. L. (1999). Evidence for a proximate influence of winter temperature on metabolism in passerine birds. Physiol. Biochem. Zool. 72,566 -575.
Swanson, D. L. and Weinacht, D. P. (1997). Seasonal effects of metabolism and thermoregulation in northern bobwhite. Condor 99,478 -489.
Swanson, D. L., Drymalski, M. W. and Brown, J. R. (1996). Sliding vs. static cold exposure and the measurement of summit metabolism in birds. J. Therm. Biol. 21,221 -226.
Yacoe, M. E. and Dawson, W. R. (1983). Seasonal acclimatization in American goldfinches: the role of the pectoralis muscle. Am. J. Physiol. 245,R265 -R271.
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