Evidence for a Proximate Influence of Winter Temperature on Metabolism in Passerine Birds

Abstract

The roles of ultimate and proximate factors in regulating basal and summit metabolic rates of passerine birds during winter have received little study, and the extent to which winter temperatures affect these variables is unknown. To address this question, we measured basal and summit (maximum cold-induced) metabolic rates in black-capped chickadees (Poecile atricapillus), dark-eyed juncos (Junco hyemalis), and American tree sparrows (Spizella arborea) during winters from 1991/1992 to 1997 in southeastern South Dakota. Both temperature and these metabolic rates varied within and among winters. Least-squares regression revealed significant negative relationships for normalized basal and summit metabolism against mean winter temperature for all species pooled (R2=0.62 to 0.69, P</=0.001). Simple and multiple regressions were performed to analyze the influence of short-term (0-7 d preceding testing), medium-term (14-30 d before testing), and long-term (100-yr means for mean, minimum, and extreme low temperatures) temperature variables on whole-animal and mass-specific metabolic rates. Simple correlation coefficients for whole-animal metabolic rates were highest (r=-0.48 to -0.75, P<0.01) for 14-30-d temperature variables in chickadees and juncos and for 0-5-d temperature variables (r=-0. 54 to -0.68, P<0.01) in tree sparrows. For mass-specific metabolic rates, simple correlation coefficients were again highest (r=-0.45 to -0.70, P<0.01) for 14-30-d temperature variables in chickadees and juncos. Simple correlations for mass-specific metabolic rates were highest for 7-14-d temperature variables for tree sparrows (r=-0.67 to -0.68, P<0.01). Multiple regressions yielded model R2s ranging from 0.45 to 0.94 using a forward selection procedure and from 0.23 to 0.71 using a stepwise selection procedure. The partial R2 contributed from mass variation was small in all cases, ranging from 0.05 to 0.18, indicating that winter temperature was generally a good predictor of metabolic rate in these species. Metabolism was substantially correlated with short- and medium-term temperature variables for all species (cumulative partial R2=0.31 to 0.70 for forward selection and 0.13 to 0.57 for stepwise selection) but, at most, only weakly so with long-term temperature variables (cumulative partial R2=0-0.11 for forward selection and 0-0.06 for stepwise selection). Thus, short- to medium-term temperatures were better predictors of metabolic rates than long-term temperatures. These data suggest a proximate role for winter temperature in regulating metabolism in these birds.

Global patterns of seasonal acclimatization in avian resting metabolic rates

“…It is striking, for instance, that within both a north-temperate species (Black-capped Chickadee; Poecile atricapillus) and a southern subtropical species (White-browed Sparrow-weaver; Plocepasser mahali) the direction of winter changes in BMR varies among populations from winter decreases to winter increases ( A related question that remains largely unanswered, but which is potentially important for understanding observed patterns in intra-and interspecific variation in seasonal metabolic adjustments, concerns the extent to which seasonal changes within populations are flexible and are modulated by environmental conditions. Data for several north-temperate species reveal that Msum closely tracks short-term fluctuations in temperature, suggesting a proximate influence of temperature (Swanson and Olmstead 1999;Petit and Vezina 2014). But the intraspecific variation in seasonal BMR adjustments highlighted in the preceding paragraph raises the possibility that not just the magnitude, but also the direction of seasonal metabolic adjustments may vary among seasons.…”

“…Smit and McKechnie's (2010) winter data were collected following a relatively dry rainy season, whereas the more recent unpublished winter data were collected following a summer with aboveaverage rainfall. These contrasting results within a species raise questions about environmental drivers of seasonal metabolic adjustments (Swanson and Olmstead 1999), and it may be that the direction of seasonal changes within populations are modulated by year-to-year differences in temperature and/or food availability. The functional significance of these variable adjustments may reflect the continuum from energy conservation to enhanced cold tolerance proposed by (Smit and McKechnie 2010), a possibility that can be evaluated by examining correlations between metabolic adjustments and temporal variation in temperature and food availability.…”

Cold- and exercise-induced peak metabolic rates in tropical birds

“…Cold or seasonal acclimation greatly increases PMR C in many small mammals and in some species may also affect PMR E (28). Similarly, in some high-latitude birds, acclimatization to winter temperatures increases PMR C (6,55). Also, PMR C is higher in the migration season in some temperate species, presumably as a consequence of increased flight muscle mass associated with preparation for long-duration migratory flights (33).…”

Local Adaptation to Winter Conditions in a Passerine Spreading North: A Common-Garden Approach

“…Thus, basal MR appears to be a plastic character, because foster birds from the southern population strongly react to changes in the environment. The proximate mechanism triggering such differential response to the environment is open for speculation, with the most likely candidates including cues that vary on a latitudinal basis; for example, temperature (Swanson and Olmstead 1999), photoperiod (Wikelski et al 2003), or a combination of both. However, increasing the energy budget more than necessary is a risky strategy, especially when food supplies and the time available for foraging are decreasing.…”

“…Thus, variation among individuals may be determined by several factors at the same time. These can be genetic, developmental, or environmental and may also be due to strategic decisions (Dawson et al 1983; Burness et al 1998;Swanson and Olmstead 1999;Nilsson 2002;Wikelski et al 2003).…”