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31 There is considerable interest in understanding how the energy budget of an endotherm is 32 modulated from a physiological and ecological point of view. In this paper, we used daily 33 (24 h) heart rate (DHR), as a proxy of DEE across seasons, to test the effect of 34 locomotion activity and water temperature on the energy budget of a large diving bird. 35 DHR was monitored continuously in common eiders (Somateria mollissima) during 36 seven months together with measures of time spent flying and time spent feeding. DHR 37 varied substantially during the recording period with numerous increases and decreases 38 that occurred across seasons, although we could not find any relationship between DHR 39 and the time spent active (feeding and flying). However, inactive heart rate (IHR) 40 decreased as locomotion activity increases suggesting that common eiders were using 41 some form of compensation when under a high work load. We were also unable to detect 42 a negative relationship between water temperature and resting heart rate, a proxy of 43 resting metabolic rate. This was unexpected based on the assumption that high 44 thermoregulation costs would be associated with cold waters. We showed instead that 45 high level of energy expenditure coincided with feather moult and warm waters, which 46 suggest that the observed variable pattern of seasonal DEE was driven by these two 47 factors. Nevertheless, our results indicate that compensation and possibly the timing of 48 moult may be used as mechanisms to reduce seasonal variation in energy expenditure. 49 50 INTRODUCTION 51 How animals deal with their intrinsic needs and environmental variability is a fundamental 52 question in physiology and ecology. Energy expenditure is thought to vary considerably in 53 birds during the annual cycle as they need to reproduce, thermoregulate, grow feathers or 54 even migrate. At the same time, food resources may vary seasonally in quantity and quality, 55 while predation pressure may force animals to move and seek safer habitats. For these 56 reasons, we expect the energy cost of life of birds to vary considerably in the course of the 57 T he J ou rn al o f E xp er im en ta l B io lo gy – A C C E PT E D A U T H O R M A N U SC R IP T 3 annual cycle. This reasoning has been labelled the increased demand hypothesis (ID) 58 (Weathers and Sullivan 1993). Recent studies on energetics of diving birds during the annual 59 cycle support the ID hypothesis where peaks of EE are associated with productive costs just 60 like during pre-breeding and feather moult (Guillemette et al. 2007, Green et al. 2009, White 61 et al. 2011). 62 63 However, metabolic ceilings may impose a limit to the level of energy expenditure ( 64 Kirkwood 1983, Daan et al. 1990; Peterson et al. 1990; Weiner 1992). In such a case, we 65 might expect daily energy expenditure (DEE) to stay relatively constant despite variation in 66 activity level, thermoregulation and productive costs (Guillemette et al. 2012). Despite large 67 and sophisticated efforts devoted recently to the study of metabolic ceilings in endotherms 68 (reviewed by Bacigalupe and Bozinovic. 2002, Speakman and Król. 2011), it appears that the 69 identification of such limits to DEE are at best difficult. Perhaps, such a difficulty is related to 70 the possibility that an animal uses an array of behavioural or physiological strategies in order 71 to maintain itself below a metabolic ceiling or to minimise energy expenditure, thus making 72 the identification of such a ceiling elusive (Guillemette 2012). This is the energy budget 73 limitation hypothesis (EBL), which predicts that when facing such limits to DEE, the time74 energy budget will be re-organised whether it is by the means of behavioural or physiological 75 compensation (Pelletier et al. 2008). These authors found that a high level of flight, a costly 76 activity for most wing-propelled diving birds like the common eider Somateria mollissima , 77 was associated with a reduction of the rest of the energy budget. However, Pelletier et al. 78 (2008) could not discriminate if this was the effect of EBL from the lack of any requirement 79 to move rapidly by flight. In a recent paper, Guillemette et al. (2012) selected a period of high 80 energy turnover and compared DEE before and after moult migration and found that DEE was 81 similar despite a large increase in foraging costs occurring before migration. Although, this 82 latter study supports the EBL hypothesis, we do not know if such an hypothesis would be 83 upheld during a longer time scale like the annual cycle. 84 85 The heart rate method using data loggers (DLs) implanted in the body cavity of birds 86 allows the investigator to estimate the rate of energy expenditure continuously over a 87 relatively long period of time, often in excess of a year (reviewed by Butler et al. 2004; 88 T he J ou rn al o f E xp er im en ta l B io lo gy – A C C E PT E D A U T H O R M A N U SC R IP T 4 Green 2011). The heart rate (HR) method has been largely used for wild and farm 89 animals, in addition to human beings (reviewed respectively by Green 2011, Brosh 2007; 90 Atchen and Jeukendrup 2003). With this method, HR is calibrated against 2 O V& in the 91 laboratory and HR measured in the field. Studies using this method have shown that 92 variation in HR of wild birds is the major circulatory adjustment observed in relation to 93 changes in oxygen demand and thus, any sustainable response to that demand should be 94 reflected by variation of HR. 95 96 In the present paper, we test the two hypotheses stated above by quantifying seasonal 97 variation of energy expenditure in a large sea duck, the common eider. Daily heart rate 98 (DHR, in beats min), the total number of heart beats occurring in one day divided by 99 1440 (the total number of minutes in 24 h) was converted into energy expenditure 100 (Hawkins et al. 2000) and used as an index of DEE in this study. We determine if average 101 DHR varies on a seasonal basis to test the ID hypothesis. Seasonal DHR was 102 characterised by various oscillations during the recording period (seven months) and was 103 related to seasonal water temperature in an effort to interpret these variations. We also 104 examine the influence of locomotor activity (LA = time spent flying and feeding) to test 105 the EBL hypothesis by partitioning DHR into feeding heart rate (FeHR), flight heart rate 106 (FHR) and "inactive" heart rate (IHR). The analysis was performed first within (intra-) 107 individuals and then conducted on the data from all the birds to examine how the pattern 108 of seasonal variation in DHR is correlated with LA. 109 110 METHODS 111 The study was performed on Christiansø Island (5519'N, 15 12'E), an old Danish 112 fortress located in the southern Baltic Sea, 18 km from the Danish island of Bornholm. 113 The general approach of our work involved the monitoring and deployment of data 114 loggers on breeding females, partitioning of heart rate data, and using heart rate to 115 estimate the daily energy expenditure (DEE). 116 Deployment of data loggers 117 T he J ou rn al o f E xp er im en ta l B io lo gy – A C C E PT E D A U T H O R M A N U SC R IP T 5 We studied the breeding biology of common eiders by monitoring about 100 nests on the 118 study plot every year (1999–2005). Nests of banded females were identified by numbered 119 wooden sticks. In spring 2003, 20 females were surgically implanted with heart rate and 120 pressure data loggers (DLs, as manufactured by Anthony J. Woakes from U.K.). We 121 obtained a licence from Dyreforsøgtilsynet (Royal Veterinarian Corporation) in Denmark 122 and birds were cared for in accordance with the principles and guidelines of the Canadian 123 Council on Animal Care. All surgical procedures were conducted indoors 100 m from the 124 experimental plot. The 20 DLs were 36 mm long (± SD = 0.5) x 28 mm (0.2) wide x 11 125 mm thick (0.3) and weighed 21 g (0.3), that is 1.2% of body mass at implantation 126 (Guillemette et al. 2002). Hydrostatic pressure and heart rate were sampled every 2 s. 127 Eighteen (90%) of the experimental females returned to the study area one year later, 128 which is similar to the previously reported survival rate in this species (Coulson 1984). 129 This is most likely related to the fact that implanted DLs do not alter aerodynamic or 130 hydrodynamic properties of the instrumented individuals (Guillemette et al. 2002). 131 However, the number of days per bird for which we had available information in the 132 present study was variable (ranging from 45 to 220 days), most likely due of battery 133 failure of the DLs. We analysed data from thirteen individuals, as these birds had loggers 134 that recorded continually for about 7 months (n = 186-220 days), which covered the 135 summer and the beginning of winter (mid-December). 136 Time activity budget and partitioning of heart rate data 137 The time budget data involved calculating the daily time spent: (1) flying, (2) feeding 138 and (3) being inactive. The partitioning of heart rate data involved calculating the number 139 of heart beats associated with each of these categories of behavior and subsequently 140 counting the number of heart beats occurring in one day (daily number of heart beats). 141 Flight schedules (number and duration of flights) were compiled for each bird following 142 the method described by Pelletier et al. (2007). This method is based on the dramatic 143 increases and decreases of heart rate upon take-offs and landings respectively, and a 144 plateau phase during flight where heart rate is typically 3–4 times the resting level. For 145 T he J ou rn al o f E xp er im en ta l B io lo gy – A C C E PT E D A U T H O R M A N U SC R IP T 6 every female, the daily time spent flying (TSF) was obtained by summing the duration of 146 all flights that occurred during one day. 147 In birds, dives are usually performed in a series, where time spent submerged 148 alternates with time breathing at the surface, which constitute a dive cycle. A feeding 149 bout (> 1 dive) is defined as the succession of dive cycles and the daily time spent 150 feeding (TSFe) was obtained by summing all feeding bouts occurring in one day. Finally, 151 the daily time spent “inactive” (TSI) was obtained for each day and each female sampled 152 by subtracting the time spent active (feeding + flying) from 1440 min. From visual 153 observations, we know that “inactive” behavior is composed of swimming, preening and 154 resting (Guillemette 2001). 155 The heart rate data were partitioned into useful quantities like feeding heart rate 156 (FeHR), flight heart rate (FHR) and inactive heart rate (IHR). Thus, for every category of 157 behavior and for every female, we summed the total number of heart beats associated 158 with that behavior and divided this by the number of minutes the bird spent engaged in 159 that activity each day. Thus, we obtained averages of FHR, FeHR and IHR for the 160 thirteen females. A similar procedure was followed for the total (daily) heart rate by 161 dividing the total number of heart beats obtained in one day by 1440 minutes. 162 A customized computer program (written by J.M. Grandbois) was run to calculate 163 all these quantities from the raw data. Finally, we estimated the minimum heart rate for 164 each bird during each day of sampling and took this to be the resting heart rate (RHR). To 165 do so, we wrote a computer program in order to find the minimum average value within 166 an interval of 5 min which was then compared with similar 5 min intervals obtained 167 through the day. This time interval was a compromise between smaller intervals, 168 incompatible with the observed decrease in heart rate during diving, and larger intervals 169 that compose a larger portion of the day. Since each new 5 min interval was searched 20 s 170 later than the one before, we obtained 4,306 such intervals for each day of sampling. The 171 end result of that procedure was the selection of the 5 min interval with the lowest mean 172 heart rate. We used that quantity as an estimate of the resting heart rate (RHR) for that 173 day and for a specific bird. 174 T he J ou rn al o f E xp er im en ta l B io lo gy – A C C E PT E D A U T H O R M A N U SC R IP T 7 Conversion into rate of energy expenditure 175 We used the calibration study of Hawkins et al. (2000) to convert HR data into mass176 specific metabolic rate (sMR). Hawkins et al. (2000, Table 4) related HR (beats min) 177 and mass-specific rate of oxygen consumption, s 2 O V & (ml O2 kg -1 min) for six common 178 eiders that were monitored continuously for two days on a water flume, exercised at 179 various speeds for up to 6 h per day and fed with waterfowl diet pellets. The functional 180 (reduced major axis) relationship was: s 2 O V & = 0.146HR + 9.677 (r = 0.753, p = 0.023). 181 One liter of oxygen consumed was multiplied by 20.083 kJ (Schmidt-Nielsen 1997) to 182 obtain sMR of birds. 183