Patterns and dynamics of rest-phase hypothermia in ...

J Comp Physiol B (2009) 179:737–745 DOI 10.1007/s00360-009-0357-1

ORIGINAL PAPER

Patterns and dynamics of rest-phase hypothermia in wild and captive blue tits during winter Andreas Nord · Johan F. Nilsson · Maria I. Sandell · Jan-Åke Nilsson

Received: 21 January 2009 / Revised: 5 March 2009 / Accepted: 19 March 2009 / Published online: 8 April 2009 © Springer-Verlag 2009

Abstract We evaluated biotic and abiotic predictors of rest-phase hypothermia in wintering blue tits (Cyanistes caeruleus) and also assessed how food availability inXuences nightly thermoregulation. On any given night, captive blue tits (with unrestricted access to food) remained largely homeothermic, whereas free-ranging birds decreased their body temperature (Tb) by about 5°C. This was not an eVect of increased stress in the aviary as we found no diVerence in circulating corticosterone between groups. Nocturnal Tb in free-ranging birds varied with ambient temperature, date and time. Conversely, Tb in captive birds could not be explained by climatic or temporal factors, but diVered slightly between the sexes. We argue that the degree of hypothermia is controlled predominantly by birds’ ability to obtain suYcient energy reserves during the day. However, environmental factors became increasingly important for thermoregulation when resources were limited. Moreover, as birds did not enter hypothermia in captivity when food was abundant, we suggest that this strategy has associated costs and hence is avoided whenever resource levels permit. Keywords Body temperature regulation · Corticosterone · Energy conservation · Food availability · Heterothermy · Life history trade-oVs

Communicated by G. Heldmaier. A. Nord (&) · J. F. Nilsson · M. I. Sandell · J.-Å. Nilsson Department of Animal Ecology, Lund University, Ecology Building, 223 62 Lund, Sweden e-mail: [email protected]

Introduction Spending the winter at high latitudes is an energetically demanding task for most organisms. The situation is especially problematic for small birds that must cope with a large surface area to volume ratio and high sustained mass speciWc metabolic rates but still have to maintain high body temperatures (Tb) (passerine average: 41.6°C; Prinzinger et al. 1991). This is especially challenging during times of low ambient temperatures, short day lengths and restricted access to food due to snow or ice cover, often experienced during winters at high latitudes. These diYculties are ampliWed by the fact that due to their high metabolic demands, small birds need more energy to survive than is contained in food carried in their gut. Instead, these birds utilize subcutaneous fat deposits built up on a daily basis as overnight metabolic fuel (reviewed by Pravosudov and Grubb 1997). These fat reserve dynamics results in small birds (body mass 12 ng (ml plasma)¡1; naviary = 3,

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nWeld = 1] were omitted from the data. Inclusion of these observations in the analyses did not aVect the results. Statistical analyses All statistical tests were performed using SAS 9.2 for Windows. Tb of day- and night-time free-living birds and captive birds were compared with a linear mixed model (PROC MIXED) Wtted using restricted maximum likelihood (REML) methods, with Tb as the dependent variable, origin as a Wxed eVect and bird identity nested within origin as a random factor. DiVerences between groups were compared using calculated least squares means, with P-values adjusted for unbalanced multiple comparisons using the Tukey–Kramer method (Littell et al. 2006). We analysed factors that could explain the variation in Tb in free-living and captive birds, respectively, using similar linear mixed models. Independent factors included all biometric measures and fat score as well as climatic and linear and squared temporal (date, minutes from sunset) variables as covariates and bird identity as a random factor. However, because of sample bias (see above), we did not include bird age in the aviary models. Furthermore, to avoid loss of predictive power of the captive bird model (that was based on a considerably smaller data set), we did not allow for squared eVects of date and time of the day in the saturated model. We included all two-way interactions with age and sex in the full models of free-living birds and all two-way interactions with sex in the full model of aviary birds, but as interaction eVects did not explain any of the variation in Tb (P > 0.10 in all cases) they are not presented in the Wnal models. Because measurements were performed by two persons (A. N., J. F. N.), we included “observer” as a Wxed factor in all analyses, but it did not explain any variation in the dependent variable (P > 0.8 in all cases) and was accordingly excluded from the Wnal models. Full models were reduced by backward elimination (Seber and Lee 2003) until only signiWcant variables remained in the model. Repeatability of within-individual measurements was calculated following Lessells and Boag (1987), using the estimates from a one-way general linear model (PROC GLM) with Tb as the dependent variable and bird identity as a grouping factor. SigniWcances of random factors were assessed by comparing the restricted log likelihood ratio of the reduced and the saturated model to a Chi square distribution with one degree of freedom (Sokal and Rohlf 1995). For all analyses, denominator degrees of freedom for Wxed eVects were calculated using the Satterthwaite approximation (Littell et al. 2006). Because of multicollinearity between climatic variables, we Wtted and subsequently reduced full models in both the aviary and the free-living bird data set with one randomly

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chosen climatic variable, using REML methods. When only signiWcant variables remained, we re-Wtted the model with maximum likelihood (ML) methods, including each climatic variable in turn. We compared model Wt using the Akaike Information Criterion, AIC (Seber and Lee 2003) and used the model with the lowest value of AIC as the Wnal model. Plasma corticosterone level between groups was compared using a general linear model (PROC GLM) with hormone levels as dependent, origin (i.e. free-living or captive) as a Wxed factor and handling time as a covariate. We included “observer” (A. N., J.-Å. N.) in the full model, but it did not explain any variation in plasma corticosterone levels (P > 0.7). All means and intercepts () are reported with their standard errors (mean/ § SE) and all signiWcances, except those for the log-likelihood ratio tests, are two-tailed.

Results General There were large diVerences in Tb between day and night and also between free-living and aviary birds (PROC MIXED: F2,120 = 604.10, P < 0.0001; Fig. 1). Post hoc comparisons revealed that daytime Tb in free-living birds ( = 42.6 § 0.2°C) was signiWcantly higher than night-time Tb in both free-living ( = 37.8 § 0.1°C; t237 = 25.1, P < 0.0001) and captive birds ( = 41.9 § 0.1°C; t161 = ¡3.0, P = 0.0092). Furthermore, nocturnal Tb was signiWcantly lower in free-living compared to captive birds (t77.9 = 29.2, P < 0.0001). We found no signiWcant diVerence in body mass between captive (mean = 11.76 § 0.11 g) and free-ranging birds (mean = 11.65 § 0.06 g; t test: t154 = 0.77, P = 0.19). However, captive birds had somewhat larger subcutaneous fat reserves (mean = 3.26 § 0.15) than did free-ranging birds (mean = 2.60 § 0.09; Mann–Whitney U test: U = 841.0, P = 0.001). Plasma corticosterone levels did not diVer between free-living and captive birds (PROC GLM: F1,25 = 0.94, P = 0.65; mean = 2.43 § 0.67 ng (ml plasma)¡1 and 2.67 § 0.63 ng (ml plasma)¡1 for captive and free-living birds, respectively). Handling time did not aVect plasma corticosterone concentration (PROC GLM: F1,27 = 2.68, P = 0.11). Field birds Using backward elimination of non-signiWcant main eVect terms on a saturated linear mixed model (PROC MIXED) with Tb as the dependent variable, we excluded, in turn, tarsus length (F1,147 = 0.14, P = 0.71), minutes from sunset2 (F1,151 = 0.33, P = 0.57), mass (F1,122 = 0.21, P = 0.65), sex

J Comp Physiol B (2009) 179:737–745

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44.0

body temperature (°C)

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42.0

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142

38.0

41 40 39 38 37 36

0

2

4

6

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10

ambient temperature (°C) 36.0

*** *** 34.0

Field (day)

Aviary (night)

Field (night)

Fig. 1 DiVerences in core body temperature between free-living blue tits during the day (Weld day), free-living blue tits during the night (Weld night) and birds from the same population kept in outdoor aviaries and measured during the night (aviary night). In cases of more than one sample for an individual, the mean of these was used for the illustrations. Boxes show medians, 1st and 3rd quartiles. Whiskers extend to the last observation within 1.5 £ the interquartile range, IQR. Open circles denote observations occurring between 1.5 and 3 IQR. Filled circles denote points greater than 3 IQR

(F1,104 = 0.10, P = 0.76), fat score (F5,160 = 0.76, P = 0.58) and age (F1,123 = 0.67, P = 0.42) from the model. However, Tb was strongly dependent on date (F1,185 = 8.52, P = 0.0039) and date2 (F1,186 = 11.63, P = 0.0008), reaching its minimum in mid winter and being relatively higher in late fall and late winter (Fig. 2). Moreover Tb increased with mean temperature during the night prior to sampling (F1,191 = 10.48, P = 0.0014; Fig. 3) and decreased with minutes from sunset (F1,172 = 4.74, P = 0.0309; Fig. 4).

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body temperature (°C)

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35 -2

Fig. 3 Nocturnal core body temperature of free-living blue tits (n = 142) as a function of mean ambient temperature one night before the sampling night. In cases of multiple measurements on a single individual, the sample from the coldest night of the study period is shown in the Wgure. The relationship is signiWcant at P = 0.001; Y = 0.0915x + 37.717; R2 = 0.066

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body temperature (°C)

body temperature (°C)

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42 41 40 39 38 37 36 35

2

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time (h) Fig. 4 Nocturnal core body temperature of free-living blue tits (n = 142) in relation to hours from sunset. In cases of multiple measurements on a single individual, the sample from the coldest night of the study period is shown in the Wgure. The relationship is signiWcant at P = 0.03; Y = ¡0.0022x + 38.577; R2 = 0.045

The random eVect term for bird identity was not signiWcant (Likelihood ratio test:  = 1.4, P = 0.23). Nor was Tb within an individual signiWcantly repeatable between sampling events (r = 0.10; PROC GLM: F55,142 = 1.15, P = 0.27).

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Aviary birds

37 36 35 20

40

60

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date Fig. 2 Nocturnal core body temperature of wintering free-living blue tits (n = 142) in relation to date (days after 1 October). In cases of multiple measurements on a single individual, the sample from the coldest night of the study period is shown in the Wgure. The line represents a quadratic Wt to the data. The relationship is signiWcant at P = 0.004; Y = 0.0002x2 ¡ 0.0247x + 38.581; R2 = 0.081

As for free-living birds, variation in Tb in captive birds was not explained by tarsus length (PROC MIXED: F1,20.8 = 0.23, P = 0.63), mass (F1,37.7 = 1.06, P = 0.31) and subcutaneous fat score (F3,37.2 = 1.74, P = 0.18). Furthermore, we found no eVect of date (F1,34.3 = 0.15, P = 0.70), mean temperature during the night prior to sampling (F1,36.9 = 1.24, P = 0.27) and minutes from sunset (F1,26.3 = 0.67, P = 0.42) on nightly Tb in aviary birds. However, Tb was signiWcantly dependent on sex of captive

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742 44.0

43.0

body temperature (°C)

Fig. 5 Nocturnal core body temperature (Tb) during winter of male (n = 7) and female (n = 19) blue tits kept in outdoor aviaries. Illustrations are based on one to six observations per individual and each box represents one bird. Boxes show medians, 1st and 3rd quartiles. Whiskers extend to the last observation within 1.5 £ the interquartile range, IQR. Open circles denote observations occurring between 1.5 and 3 IQR. Dashed lines show Tb means for females and males, respectively. DiVerences are signiWcant at P = 0.03

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42.0

41.0

40.0

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birds (F1,17.3 = 6.02, P = 0.025; Fig. 5) with males, on average, maintaining their Tb 0.7°C higher than females (male = 42.5 § 0.24°C, female = 41.8 § 0.14°C). The random eVect term for bird identity was not signiWcant (Likelihood ratio test:  = 3.0, P = 0.083). However, Tb was weakly but signiWcantly repeatable within individuals between sampling events (r = 0.23; PROC GLM: F26,65 = 1.97, P = 0.014).

Discussion We have shown that free-ranging blue tits decreased Tb almost 5°C compared to daytime levels, whereas birds from the same population temporarily kept in outdoor aviaries remained more or less homeothermic throughout the night (Fig. 1). Since free-ranging and captive birds were of the same origin and experienced identical ambient conditions and photoperiods, the main remaining diVerence between the groups was the amount of available food. It is widely recognized that patterns and dynamics of heterothermy often diVer between free-ranging and captive birds (Geiser et al. 2000). The discrepancy results from a lower amplitude of diurnal body temperature oscillation in captive individuals in some species (Buttemer et al. 2003; Cooper et al. 2008) and a much reduced propensity to enter hypothermia in others (Bech and Nicol 1999; Körtner et al. 2001). Consequently, it has been argued that because of stress, birds in captivity appear reluctant to use hypothermia, and that the resulting increased nightly energy expenditure is made possible by the access to food in captivity (Körtner et al. 2001).

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However, we found no diVerences in plasma corticosterone levels between free-ranging and captive blue tits, implying that stress levels did not diVer between the groups. We thus feel conWdent that the observed diVerence in the use of nocturnal hypothermia was attributable to eVects of food availability per se. There is good reason to assume that food availability is instrumental in the use of nocturnal hypothermia, because food deprivation is often necessary to induce hypothermia in captive birds otherwise fed ad libitum (Reinertsen and Haftorn 1986; McKechnie and Lovegrove 2003; Laurila and Hohtola 2005). Incidental evidence for the importance of food resources in body temperature dynamics is also provided by the fact that species with a capacity for substantial decreases in Tb generally are those that rely predominantly on food sources that are ephemeral, weather-dependent or diYcult to store endogenously (McKechnie and Lovegrove 2002). Accordingly, we expected that birds feeding mainly on predictable resources or in non-Xuctuating environments would be less prone to enter hypothermia, as they would have a higher relative probability of replenishing energy reserves the subsequent day (Schleucher 1999, 2001). The fact that birds seem to avoid hypothermia when food is abundant suggests that, even though potentially beneWcial for energy conservation purposes (e.g. Maddocks and Geiser 1997; Sharbaugh 2001; Cooper and Gessaman 2005), using heterothermy at night incurs a cost. The risk of predation has been suggested to be such a cost, inXuencing optimal nightly Tb in birds as a trade-oV between energetic constraints and predation risks (Laurila and Hohtola (2005). We, therefore, argue that captive blue tits in the current

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study actively maintained Tb close to daytime levels to minimize nightly predation risk and that this was possible as a result of ad libitum food. Conversely, free-ranging birds were probably exposed to an omnipresent energetic constraint, which made hypothermia more beneWcial regardless of predation risks. Hence, birds should avoid costs by keeping Tb at high levels whenever possible. However, this is probably possible only under certain conditions (such as benign ambient conditions or abundant food resources) which might never occur during winter in the temperate region. Nocturnal Tb varied predictably with date in freeranging birds (Fig. 2), reaching an overall minimum in mid winter and being relatively higher in late fall and late winter. Changes in Tb regulation with season occur in free-ranging populations of some species (Carpenter 1974; Chaplin 1976; Reinertsen and Haftorn 1983; Waite 1991; Brigham et al. 2000; Maddocks 2001) and may reXect a response to variation in day length (Reinertsen 1996). During the short days of mid winter at high latitudes, birds have little choice but to forage intensively to replenish energy reserves (Haftorn 1992). As days become longer, more time for foraging is available and the need for energy conservation at night decreases (Welton et al. 2002). However, ambient conditions are also subjected to stochasticity and can change rapidly from one day to the next. In accordance with previous studies (Merola-Zwartjes 1998; MerolaZwartjes and Ligon 2000; Dolby et al. 2004; McKechnie et al. 2004; Lane et al. 2004), we found Tb to be positively related to ambient temperature (Fig. 3), which might reXect a response to such environmental stochasticity. We thus argue that, although Tb regulation in blue tits may vary seasonally (see above), birds also adjust Tb in relation to ambient temperature. This allows wintering blue tits to Wne tune energy management and optimize the trade-oV between energy expenditure and predation risk on a nightly basis. On a smaller temporal scale, Tb also varied as a function of progression of the night. More speciWcally, Tb decreased slowly (0.12°C h¡1) after sunset throughout the sampling period (Fig. 4). Because we did not sample for more than about 8 h past sunset, we have no data on arousal. However, considering the relatively long period of constant decrease, there is reason to expect the nocturnal hypothermic response in wintering free-ranging blue tits does not show the distinct “entry-maintenance-arousal”-pattern (McKechnie and Lovegrove 2002) which occurs in other parid species (Willow tit Poecile montanus: Reinertsen and Haftorn 1983, 1986; Juniper titmouse Baeolophus ridgwayi, Mountain chickadee Poecile gambeli: Cooper and Gessaman 2005). Rather, our results suggest that in blue tits there is a slow continuous decrease during the Wrst half of

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the night (see e.g. McKechnie and Lovegrove 2001a, b, 2002; Cooper et al. 2008 for examples of such Tb traces). The low amplitude daily cycles in Tb in aviary birds was well within the range of the 1–2°C variation ascribed to the circadian rhythm (Reinertsen and Haftorn 1986). Because these birds probably did not enter hypothermia, it is no surprise that variation in nocturnal Tb could not be explained by any of the predictors known to inXuence Tb variation in free-ranging birds. The absence of a hypothermic response in captive birds diVers markedly from data in similar studies, in which nocturnal Tb not only shows pronounced daily cycles but also varies predictably with both ambient temperature (Mayer et al. 1982; Reinertsen and Haftorn 1984, 1986; Maddocks and Geiser 1997; Sharbaugh 2001; McKechnie and Lovegrove 2001b; Downs and Brown 2002; Cooper and Gessaman 2005; Maddocks and Geiser 2007) and season (Carpenter 1974; Chaplin 1976; Reinertsen and Haftorn 1983; Waite 1991; Maddocks and Geiser 2007). However, the majority of these studies were performed over larger temperature ranges, at higher latitudes or in colder ambient temperatures than our study. It, therefore, seems likely that even though captive conditions might aVect patterns and use of facultative hypothermia, this is to some extent dependent on ambient conditions. If true, ad libitum access to food might suYce to preclude a hypothermic response during the comparatively mild winters in southern Sweden, but not during more energetically demanding winters. Even though our sample was small and heavily skewed, nocturnal Tb diVered signiWcantly between sexes in the captive birds (Fig. 5). Testosterone appears to play a signiWcant role in explaining sex-speciWc variation in thermoregulation in several mammals (Ruby et al. 1993; McKechnie and Lovegrove 2002 and references therein; Mzilikazi and Lovegrove 2002). Even though comparable data for birds are lacking, Merola-Zwartjes and Ligon (2000) found that torpor in breeding individuals of the Puerto Rican tody (Todus mexicanus) was restricted to females and proposed that higher testosterone levels of males might preclude torpor. The observed sex diVerences in our captive birds could potentially be explained if male testosterone production during winter depends on food levels. This would also explain the lack of sex diVerences in free-ranging birds.

Conclusions We have shown that hypothermia in free-ranging blue tits is a dynamic process that is regulated to ensure an optimal trade-oV between energy management and costs (e.g. predation risk) during winter nights. This is supported by the lack of repeatability of Tb within free-ranging individuals. Blue tits seem to respond both to predictable factors, such

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as day length and to short-term variation in e.g. ambient temperature. Furthermore, the trade-oV nature of hypothermia is consistent with the fact that blue tits remained largely homeothermic at night in situations with high food availability. Thus, when hypothermia is not needed to reduce risks of overnight starvation, blue tits do not pay the cost of potentially increased predation risk during the night (Pravosudov and Lucas 2000). Our results, therefore, stress the overall importance of energetic limitations in regulating the dynamics of nocturnal hypothermia in overwintering birds. Surprisingly, in spite of convincing evidence that food related energetic stress can be a major determinant of Tb dynamics in birds, experimental evidence from natural populations is scant (but see Woods and Brigham 2004). Thus, studies of patterns, dynamics and consequences of Tb regulation in wild populations are critically needed. Acknowledgments We are grateful to Charlotta Borell Lövstedt for supplying climatic data from the study area. Comments from Indrikis Krams and three anonymous reviewers improved a previous version of the manuscript. This study was supported by grants from the Swedish Research Council (to J.-Å. N.). All experimental protocols adhere to the guidelines of the Swedish Animal Welfare Agency and were approved by the Malmö/Lund Animal Care Committee, Sweden (permit nos. M53-06, M237-07).

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