Basal metabolic rate in free-living tropical birds: the influence of phylogenetic, behavioral, and ecological factors

Basal metabolic rate in free-living tropical birds: the influence of phylogenetic, behavioral,... The majority of our knowledge of avian energetics is based on studies of birds from temperate and high latitudes. Using the largest existing sample of wild-caught Old World tropical species, we showed that birds from Southern Vietnam had lower basal metabolic rate (BMR) than temperate species. The strongest dissimilarity between tropical and temperate species was the low scaling exponent in the allometric relation between BMR and body mass in tropical birds (the regression slope was 0.573). The passerine migrants to temperate and high latitudes had higher BMR than tropical sedentary passerines. Body mass alone accounted for 93% of the variation in BMR (body mass ranged from 5 to 252 g). Contrary to some other studies, we did not find evidence besides the above mentioned that phylogeny, taxonomy, behavior, or ecology have a significant influence on BMR variation among tropical birds. Key words: allometry, BMR, body mass, energy metabolism, tropical birds. The notable differences in numerous life-history and other traits be- The most commonly examined comparative measure of the tween tropical and temperate birds led to the notion that tropical metabolic rate of endotherms is basal metabolic rate (BMR), which birds have a “slow pace of life”: they live longer, have fewer off- is the minimum metabolic rate of an adult normothermic animal in spring, and invest more resources in self-maintenance, whereas tem- postabsorptive state and in nonreproductive phase, at rest and at perate birds have high rates of mortality and invest more resources temperatures within the thermoneutral zone (TNZ; McNab 1997). in reproduction (Williams et al. 2010; Jimenez et al. 2014a). The di- BMR is the lowest cost of body maintenance and, therefore, an im- versification of life histories in animals is limited by physiological portant characteristic of physiological heterogeneity of communities mechanisms (Ricklefs and Wikelski 2002). Physiological differences and separate populations of endotherms. To date, there is much evi- between birds of high and low latitudes remain insufficiently dence supporting the dependence of the variation in avian BMR on known, although some recent studies have made great progress in many factors, such as season, temperature, habitat, phylogeny, this respect (Tieleman et al. 2005, 2006; Wiersma et al. 2007a, behavior, etc. (McNab 2012). However, the importance of each fac- 2007b; Williams et al. 2010; Wiersma et al. 2012; Jimenez et al. tor with respect to the others often is not clear. For example, it is 2013, 2014b; Jimenez and Williams 2014). hard to separate the effects of temperature and pace of life V C The Author (2017). Published by Oxford University Press. 33 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com Downloaded from https://academic.oup.com/cz/article-abstract/64/1/33/3084522 by Ed 'DeepDyve' Gillespie user on 16 March 2018 34 Current Zoology, 2018, Vol. 64, No. 1 (London ~o et al. 2015; Bech et al. 2016) or temperature and migra- We predict that long-distance migration requires higher metabolic tory tendency (Jetz et al. 2008). capacity (e.g., based on higher mass of metabolically active tissues), Several physiological characteristics, which may relate to BMR which should be reflected in higher BMR of tropical migrants com- variation, are different in tropical and temperate species. In particular, pared to residents. Since most of the temperate passerines are migra- tropical birds have a smaller organ size, lower flight muscle, and fea- tory species, we think that one of the main reasons of increased ther mass (Williams et al. 2010; Wiersma et al. 2012), smaller muscle BMR in the temperate passerines is their migratory style of life. fiber size, and increased costs of maintaining muscle mass (Jimenez Therefore, we hypothesized that the energetic asymmetry between and Williams 2014), lower daily metabolized energy in nestlings passerines and non-passerines should be less pronounced in tropical residents than in breeding birds of higher latitudes. (Bryant and Hails 1983), lower summit metabolism and field meta- Together with migratory tendency and taxonomy, some ecolo- bolic rate (Wagner et al. 2013), lower peak metabolic rate (Wiersma gical factors may have a great impact on animal energetics (McNab et al. 2007a, 2007b), and cellular metabolic rate (Jimenez et al. 1988, 2009, 2015b). Among these factors we tested those that were 2014b). At least some of these features may be considered as the rea- shown to have influence on BMR in tropical birds: diet (arthropods, sons for BMR reduction in tropical birds. Although avian BMR was seeds, nectar, etc.) and some characteristics of behavior, which are studied in many works over the last century (Downs and Brown important in terms of risk of overheating (habitat, foraging in the 2012), the number of studies on free-living birds in tropics is much sun or shade, etc.). smaller compared to temperate zone. There are only 3 studies on In this study, we use the largest original dataset on BMR of Old BMR of tropical birds containing adequate sample sizes of individuals World wild-caught tropical birds to reveal features of tropical birds. and/or species. Two of them were done in the Neotropical region: the Specifically, we wish to: (1) estimate the influence of phylogeny, study by Wiersma et al. (2007b), based on 69 species from a lowland ecology, and migratory tendency on their BMRs; and (2) compare rainforest in Panama, and the very recent work by Londono ~ et al. BMR of tropical and temperate birds. (2015), based on 253 species from forests in Peru. The only compre- hensive study of energetics in tropical birds of the Old World is the re- cent monograph by McNab (2013), based on 45 free-living New Materials and Methods Guinea species and 32 species obtained from captivity. Capturing birds Some studies on avian energetics have found a reduced rate of me- We caught birds using mist nets in Cat Tien National park (Vu’o ’n tabolism in tropical birds (Weathers 1977; Hails 1983; Klaassen 0  0 quu’cgia C at Ti^ en), Southern Vietnam (11 25 N, 107 25 E; elevation 1995; Wikelski et al. 2003; Tieleman et al. 2006; McNab 2009), but 120–140 m) in a deciduous tropical forest with strongly degraded some have found it to be similar to the metabolic rate of birds from vegetation (Vandekerkhove et al. 1993; Blanc et al. 2000). Birds were higher latitudes or that the difference depends on species and their captured during 7–26 May 2011, 10–18 April 2012, and 15 March– ecology (Scholander et al. 1950; MacMillen 1974; Vleck and Vleck 11 May 2013. We weighed birds just after the capture. Juvenile birds 1979; Weathers 1979,1997; Pettit et al. 1985; Bennett and Harvey 1987; McNab 2013). Nevertheless, all phylogenetically controlled and females with a strongly pronounced brood patch were released multispecies studies have confirmed low metabolic rate in tropical immediately after weighing and did not participate in BMR measure- birds (Wiersma et al. 2007a, 2007b; London ~o et al. 2015; Bech et al. ments. We housed birds in soft mesh cages and provided water and 2016). The substantial studies by Wiersma et al. (2007a, 2007b)dem- food ad libitum. Birds were kept in cages for 10 h at maximum (mean onstrated lower basal and peak metabolic rates in Neotropical birds, is 5.5 h). Some birds (such as broadbills, pittas, doves, kingfishers, which perfectly fit the concept of slow “intensity of life” in tropical woodpeckers, and drongos) refused to eat and were force-fed every species. London ~o et al. (2015) found that BMR of temperate breeders 2 h with zophobas, mealworms, crickets, mango fruits, and dry feed Padovan (Valman s.r.l., Italy). The last feeding was done before 5 PM. is on average 16.4% higher than that of Neotropical species. At the We weighed all captured birds every 1–2 h, depending on the size of same time, McNab (2013) has showed that lowland tropical passer- species. If a bird’s weight had dropped noticeably (10% of body- ines from his and Wiersma et al. (2007b) datasets, on average, had a weight loss), we immediately released that individual. higher BMR than expected from a general avian-scaling curve. We obtained a total of 368 BMR measurements (equal to the However, unlike studies on Neotropical birds, McNab (2013) inten- number of individuals) during 79 nights. The number of individuals tionally did not correct his analyses for phylogeny. In our study, we per species ranged from 1 to 47 (average of 5.6). Our BMR database wanted to investigate whether the Old World birds follow the trend includes 66 species from 29 families belonging to 9 orders observed in the New World. (Supplementary Table S1). Latin and common names of species The higher BMR of passerines was one of the main taxonomic were taken from IOC World Bird Names v. 7.1 (http://www.world differences observed in the energetics of endotherms (e.g., Lasiewski birdnames.org/). and Dawson 1967; Aschoff and Pohl 1970; Kendeigh et al. 1977; Bennett and Harvey 1987; Gavrilov 1997; Jetz et al. 2008; McNab 2009, 2015a; Bech et al. 2016). However, with the exceptions of Measurements of BMR Wiersma et al. (2007b), McNab (2013), London ~o et al. (2015), and BMR of birds was estimated during the night after capture by flow- Bech et al. (2016), all comparisons between passerines and non- through respirometry (see Supplementary Materials for details about passerines were done using datasets substantially amassed on meta- respirometry equipment, calibration, leak testing, etc.). At 6 PM, bolic rates of temperate species. On the other hand, a comprehensive after sunset, we placed up to 7 (average of 4.8) birds inside cylin- phylogenetically controlled analysis by Jetz et al. (2008) revealed drical polypropylene chambers (1.3–2.7 L). We put metabolic cham- that BMR in migrants is much higher than in nonmigrant birds. bers in boxes made from sound-proofing and heat-insulating foam These researchers partially explained high BMR in long-distance mi- plastic. We used 20 L chambers for the largest species (Amaurornis grants with lower temperatures on their breeding grounds, but the phoenicurus, Arborophila chloropus, and Centropus sinensis). The BMR data for migrants on their tropical wintering grounds are too rates of gas exchange were measured until 6:00 AM. We did not scarce to test their hypothesis. In our study, we partly fill this gap. use thermostats because the ambient temperature in the laboratory Downloaded from https://academic.oup.com/cz/article-abstract/64/1/33/3084522 by Ed 'DeepDyve' Gillespie user on 16 March 2018 Bushuev et al.  Basal metabolic rate in free-living tropical birds 35 during measurements was very stable (recorded using type T thick grass or shrub (e.g., Acrocephalus sp., Locustella lanceolata, thermocouple probe [Sable Systems International, USA]). The tem- Phragmaticola aedon, Timalia pileata). Migratory species only perature inside the chambers was within 28–30 C (recorded every included migrants to temperate and high latitudes (54 species were 20 min with iButton thermologgers), which should be within the residents and 12 were migrants). All tropical breeders were catego- TNZ of most tropical birds (McNab 2013). rized as residents (sedentary birds), including Pitta moluccensis, We used 8 independent membrane pumps (AC-500, Resun, which performs winter migration to the Malay Archipelago. China) to push the outdoor air through columns containing self- indicating granulated fine-pored silica gel to remove water vapor and Statistical analysis then into metabolic chambers with birds. The flow rate was set at All scaling exponents in allometric equations in our study were based 250–1,200 mL/min (depending on the size of measured species). We on ordinary least squares (OLS) regressions, unless specifically men- used a custom built valve system, which alternately routed the air tioned. The body mass and BMR data were log -transformed before stream from each chamber with birds and an empty reference cham- analysis to account for allometric scale. To test for difference in inter- ber (for baselining) to the FoxBox-C Respirometry System (Sable cepts of log(BMR)  log(M) regressions in different groups of birds Systems International, USA), which included build-in air filters, mass (categorical predictor, e.g., residents/migrants), we used ANCOVA flowmeter, flow controller, membrane pump, O and CO analyzers. 2 2 with log(BMR) as dependent variable and log(M) as covariate. We After the air left the valve system, it was routed through a small col- tested the differences between observed and predicted values of BMR umn (V¼ 45–70 mL) with DrieriteV 10–20 mesh absorbent (W.A. using a t-test (predicted values were calculated using different allomet- Hammond Drierite Co. Ltd, USA) and then through mass flowmeter ric equations from Table 1). The differences between observed slopes into O /CO gas analyzers. Birds were measured alternately in cycles. 2 2 and theoretical slopes of 2/3 and 3/4 were tested with Welch’s t-test. The time of measurement for each bird within a cycle and the length To test for difference in slopes of 2 regression lines, we tested the of each cycle depended on the number of birds within a night session model with the interaction term of log(M) and the grouping factor and were at average of 25 and 139 min, correspondingly. Baselining versus the model without interaction using function “ANOVA.” All was performed 1–3 times during each cycle, depending on the number regression residuals were normally distributed, which was checked of measured birds. It was done in such a way that measurements of using Shapiro–Wilk test. All analyses were conducted in R (R Core each bird or at least each second bird adjoined with baselining. Team 2016). The significance level was set as a ¼ 0.05. Standard Around 6:00 AM, birds were removed from the chambers, weighed errors of intercepts and slopes are shown in equations in brackets. with a precision of 0.1 g, and released. To estimate BMR we selected the lowest stable part of the curve Phylogenetic analysis (average of 11 min) over the entire night. We rejected data from in- The phylogenetic relationships between studied species were ex- dividuals that did not become quiescent. The volume of consumed tracted from the BirdTree.org database (http://www.birdtree.org) oxygen was calculated from fractional concentrations of O and using the study by Hackett et al. (2008) as the backbone for phylo- CO according to the principle of Haldane transformation (Luft genetic reconstruction. A total of 1,000 trees were downloaded from et al. 1973; Wagner et al. 1973; Wilmore and Costill 1973): BirdTree.org, which is enough to obtain robust phylogenies E E (Rubolini et al. 2015). The resultant MCC consensus tree 1  F O  F CO 2 2 E I E VO ¼ V   F O  F O ; 2 2 2 I I (Supplementary Figure S1) was obtained by Treeannotator of 1  F O  F CO 2 2 BEAST 1.8.2 (Drummond et al. 2012). where V is the flow of dry air out of the animal chamber in volume Phylogenetic signal in traits was estimated with Pagel’s k (Pagel per time unit, F is volume fractional concentration of respective gas 1999; Freckleton et al. 2002) using function “phylosig” from pack- in dry inlet air, F is volume fractional concentration of respective age “phytools” (Revell 2012). We used phylogenetic generalized gas in dry outlet air. We calculated the respiratory quotient (VCO 2 least squares model (PGLS) to take the phylogenetic signal into ac- produced/VO consumed) and used it to convert the volume of oxy- 2 count in allometric analysis (Grafen 1989; Freckleton et al. 2002). gen consumption (VO ) to the values of energy expenditure (kJ/day) 2 We did not find any phylogenetic signal in the residual variation of using the equation 5 from Lusk (1924). Nevertheless, the mean the regression of log(BMR) on log(M) (i.e., mass-independent BMR was less than 0.01% different from the value calculated BMR). Consequently, the OLS method was more suitable for fitting through commonly used coefficient 19.8 J/mL O (Gessaman and 2 the regression models than PGLS (Revell 2010). We provided several Nagy 1988). phylogenetic regressions to show that regression coefficients from PGLS were very close to those that were obtained by OLS. We fit Categorization of ecological and behavioral factors PGLS via maximum likelihood (ML) approach using the function Following McNab (2009, 2013, 2015b), we used analysis of cova- “gls” from package “nlme” (Pinheiro et al. 2014). We specified 4 riance (ANCOVA) to determine which factors had an impact on different ways in which the tree structure is expected to affect the co- BMR. We used the following taxonomic, ecological, and behavioral variance in trait values across species (Brownian motion [BM], rankings: passerine/non-passerine and oscine/suboscine dichotomies, Grafen’s q, Pagel’s k, and Ornstein–Uhlenbeck [OU] models of evo- migratory behavior (migrant/resident), habitat type (exposed, forest lution) using package “ape” (Paradis et al. 2004). or intermediate), foraging substrate, feeding in the shade or sun, food We estimated the effect of within-species sampling (intraspecific habits (diet). We categorized species to ecological groups according to variation) on the strength of phylogenetic signal using function personal observations of our colleagues, I.V. Palko and M.V. “phylosig” from package “phytools” (Revell 2012). We also used function “pgls.Ives” from the same package (BM is assumed) to in- Kalyakin (Supplementary Table S1), who conduct long-term observa- tions on ecology and behavior of tropical birds in the study site. corporate sampling error in the estimation of species means by fit- Exposed (open) habitat type did not always equal to feeding in ting the phylogenetic reduced major axis (RMA) regression of Ives the sun, as some species from exposed habitats feed in the shade of et al. (2007). Downloaded from https://academic.oup.com/cz/article-abstract/64/1/33/3084522 by Ed 'DeepDyve' Gillespie user on 16 March 2018 36 Current Zoology, 2018, Vol. 64, No. 1 Table 1. The average ratio of observed whole-organism BMR of tropical resident birds of different taxonomic groups from Vietnam to pre- dicted BMR, estimated using allometric relationships between BMR and body mass from literature on corresponding groups Literature source ab Avian group Ratio (%) This study 195.75 0.573 Tropical (including migrants) 98.8 This study 200.18 0.581 Tropical (including migrants) (PC) 99.4 This study 267.49 0.622 Tropical migrants 84.9** This study 202.80 0.589 Tropical residents 100.0 Brody and Proctor (1932) 372.63 0.640 Temperate 65.6** King and Farner (1961) 335.36 0.659 Temperate 78.0** King and Farner (1961) 311.08 0.744 Large temperate (M > 125 g) 80.9* Lasiewski and Dawson (1967) 361.74 0.668 Temperate 74.7** Lasiewski and Dawson (1967) 540.10 0.724 Temperate passerines 64.6** Lasiewski and Dawson (1967) 327.83 0.723 Temperate non-passerines 90.8* Zar (1969) 324.06 0.739 Temperate 107.7 Zar (1969) 473.11 0.632 Temperate passerines 51.2** Zar (1969) 319.03 0.743 Temperate non-passerines 98.8 Aschoff and Pohl (1970) 480.64 0.726 Temperate passerines 73.2** Aschoff and Pohl (1970) 307.73 0.734 Temperate non-passerines 99.8 Bennett and Harvey (1987) 240.93 0.670 All 112.9** Daan et al. (1990) 361.32 0.677 All 77.2** Reynolds and Lee (1996) 343.17 0.670 All 79.3** Reynolds and Lee (1996) 339.25 0.635 All (PC) 70.8** Gavrilov (1997) 435.08 0.700 Passerines in summer 72.9** Gavrilov (1997) 349.65 0.710 Non-passerines in summer 82.0** Tieleman and Williams (2000) 308.32 0.638 All 78.8** Tieleman and Williams (2000) 279.90 0.677 All (PC) 99.7 Frappell et al. (2001) 471.39 0.680 Basically temperate 59.8** Frappell et al. (2001) 445.36 0.680 Basically temperate (PC) 63.3** Rezende et al. (2002) 329.64 0.635 All 72.9** Rezende et al. (2002) 399.98 0.721 All (PC) 81.7** McKechnie and Wolf (2004) 303.75 0.669 All 89.3** McKechnie and Wolf (2004) 243.51 0.677 All (PC) 114.6** Speakman (2005) 350.41 0.671 All 77.9** McKechnie et al. (2006) 315.1 0.744 All wild-caught birds (PC) 114.6* White et al. (2006) 243.35 0.640 All 100.5 Wiersma et al. (2007b) 307.97 0.644 Tropical passerines 82.4** Wiersma et al. (2007b) 262.73 0.644 Tropical non-passerines 90.7* McNab (2009) 314.47 0.652 All 81.2** McNab (2009) 429.69 0.713 Passerines 77.7** McNab (2009) 317.40 0.724 Non-passerines 94.1 McNab (2009) 451.02 0.708 Temperate passerines 71.6** McNab (2013) 234.97 0.581 Tropical (including non-residents) 84.7** McNab (2013) 245.39 0.634 Tropical residents 97.6 McNab (2013) 293.61 0.686 Tropical passerines 102.1 McNab (2013) 167.36 0.686 Tropical non-passerines 160.1** Londono ~ et al. (2015) 220.73 0.551 Tropical residents 82.3** Londono ~ et al. (2015) 193.95 0.543 Tropical residents (PC) 91.2** Londono ~ et al. (2015) 300.48 0.644 Tropical resident passerines 86.0** Londono ~ et al. (2015) 283.25 0.644 Tropical resident non-passerines 84.1** Londono ~ et al. (2015) 298.51 0.627 Tropical resident passerines (PC) 81.0** Londono ~ et al. (2015) 277.73 0.701 Tropical resident non-passerines (PC) 100.7 Notes: a is the allometric coefficient and b is the scaling exponent from equation BMR ¼ aM , where BMR is basal metabolic rate in kJ/day and M is body mass in kg. PC means “phylogenetically corrected.” Temperate birds here include also species from high latitudes. Marks recalculations based on equation 1 L of O ¼ 20.083 kJ of energy (Schmidt-Nielsen 1997). *P < 0.05; **P < 0.001. Results slope value (b¼ 0.57) differed from the theoretical slopes b¼ 0.75 (Kleiber’s law) and b¼ 0.67 (Rubner’s rule) (P < 0.001). If we included The relation between BMR and body mass in the analysis only species with more than 3 individuals [n 3isre- We found the mass exponent in the allometric relation between quirement from McKechnie and Wolf (2004)], the equation was BMR and body mass in tropical birds to be very small (Figure 1). log(BMR)¼ 0.598[0.040]þ 0.546[0.030]*log(M) (R ¼ 0.928). The adj The OLS regression between log(BMR) and log(M) was slope of the regression in the reduced sample was still significantly lower log(BMR)¼ 0.573[0.029]þ 0.573[0.019]*log(M) (R ¼ 0.930). The adj than 0.67 (P < 0.001). Downloaded from https://academic.oup.com/cz/article-abstract/64/1/33/3084522 by Ed 'DeepDyve' Gillespie user on 16 March 2018 Bushuev et al.  Basal metabolic rate in free-living tropical birds 37 1.0 1.5 2.0 1.0 1.5 2.0 log [body mass], g log [body mass], g Figure 1. The relationship between BMR and body mass in tropical birds of Figure 2. The relationship between BMR and body mass in resident (red thick Southern Vietnam (black thick solid line). Red solid triangles indicate passer- solid line, red solid triangles) and migratory (blue thick dashed line, blue ines; blue open squares indicate non-passerines. Green thin solid lines indi- open squares) tropical birds of Southern Vietnam. Thin dashed lines indicate cate theoretical slopes b ¼ 0.75 (Kleiber’s law) and b ¼ 0.67 (Rubner’s rule). 95% confidence intervals of the corresponding regressions. Black thin dashed lines indicate 95% confidence interval of the regression. The influence of taxonomy on BMR of tropical birds Phylogenetic analysis We did not find differences in BMR between tropical passerine and The coefficients of log(BMR)  log(M) regression did not change non-passerine birds: log(BMR)  log(M) regression lines of passer- significantly after taking phylogeny into account. We did not find a ines and non-passerines did not differ in slopes (P > 0.5), nor in phylogenetic signal in mass-independent BMR of tropical birds from intercepts (P > 0.7). The corresponding OLS regressions were our sample. log(BMR) ¼ 0.555[0.043] þ 0.588[0.033]*log(M) and log(BMR)¼ The Pagel’s k for log(M), log(BMR), and mass-independent 0.596[0.060] þ 0.559[0.032]*log(M). When we excluded migratory BMR were 0.989 (P < 0.001), 0.943 (P < 0.001), and 0.00007 species (all of them were passerines) from the analysis, absence of (P ¼ 1.00), respectively (P values indicate the significance of the dif- significant differences between passerines and non-passerines re- ference from zero). The Pagel’s k for log(M) and log(BMR) were not mained, and the equation for passerines changed to log(BMR)¼ significantly different from unity (P > 0.3), for example, we cannot 0.513[0.040] þ 0.609[0.029]*log(M). confidently distinguish our estimated phylogenetic signal in those Oscine passerines did not differ from suboscines in both regres- traits from BM. sion coefficients (P > 0.3 for the slopes, P > 0.5 for the intercepts), Comparison of different evolutionary models using the general although suboscines were represented by only 4 species with similar sample of migrant and resident species revealed that the best fit was body weights (52.7–115.3 g). the model with Pagel’s covariance structure (AIC¼172.32). It was followed by the OU model (AIC¼155.59) and covariance under The influence of ecology and behavior on BMR BM (AIC¼137.20). The phylogenetic regression from the model, Our results suggest that residential birds have a lower BMR than which finds and fits the ML value for Pagel’s k,was long-distance migrants on their wintering grounds in tropics. The in- log(BMR)¼ 0.557[0.047]þ 0.581[0.025]*log(M) (R ¼ 0.956). The fluence of all other ecological and behavioral factors was not signifi- best-fit value of k was determined to be very close to zero by ML and cant (habitat, feeding in the shade or sun, diet, foraging substrate). not different from zero (P¼ 1). The phylogenetic regression from the To simplify the analysis, the categories of different factors were vari- OU model was log(BMR)¼ 0.573[0.030]þ 0.573[0.020]*log(M), a (strength of the evolutionary constraint) was equal to 1.00. Assuming ously combined, but the adjusted R increased only by 0.011 at the BM model of evolution (Pagel’s k fixed to unity), the phylogenetic maximum. There was also no correlation between mean capture day regression was log(BMR)¼ 0.529[0.089]þ 0.589[0.034]*log(M). and BMR (Spearman’s q: P > 0.8). We repeated analysis with all branches of the tree set to unity. The There was no difference between resident (n¼ 54) and migratory (n¼ 12) species in slopes (P¼ 0.75) of log(BMR)  log (M) regressions, differences in phylogenetic signal were negligible from the above re- but migratory birds had a higher intercept (P¼ 0.014) (Figure 2). sults. The best-fit model (with Pagel’s covariance structure) gave the The OLS regressions for resident and migratory birds were phylogenetic regression log(BMR)¼ 0.541[0.045]þ 0.588[0.024]* log(BMR)¼ 0.539[0.028]þ 0.589[0.018]*log(M) and log(BMR)¼ log(M) (R ¼ 0.952). Incorporating the standard errors for each spe- 0.563[0.160]þ 0.622[0.145]*log(M), correspondingly. The difference cies into the model led to considerable reduction of sample size, as 23 of 66 species were presented only by a single individual; however, the in intercepts between migrants and residents only tended to be signifi- estimates of Pagel’s k did not change substantially for all traits. The cant after removal of the barn swallow from the analysis (P¼ 0.077). equation of the model, which took standard errors into account using We also compared our raw BMR data with those from McNab’s Ives et al. (2007) regression method, was log(BMR)¼ 0.580þ 0.564* (2009) comprehensive database (533 species) using ANCOVA. We log(M). found that tropical residents in our study had a lower BMR than both Downloaded from https://academic.oup.com/cz/article-abstract/64/1/33/3084522 by Ed 'DeepDyve' Gillespie user on 16 March 2018 log [BMR], kJ/day 1.0 1.2 1.4 1.6 1.8 2.0 log [BMR], kJ/day 1.0 1.2 1.4 1.6 1.8 2.0 38 Current Zoology, 2018, Vol. 64, No. 1 [calculated from Hails (1983)], b ¼ 0.508 [calculated from Tieleman *** et al. (2005)], b ¼ 0.581 (McNab 2013), and b ¼ 0.551 (Londono ~ et al. 2015). Wiersma et al. (2007b) reported a steeper slope, *** b ¼ 0.644, for birds breeding in tropics. The low scaling exponent relating BMR to body mass in tropical birds could be of a heritable nature or could be an effect of phenotypic plasticity in response to different environmental conditions. For instance, McKechnie et al. (2006) found substantial differences in scaling coefficients for BMR in captive-raised and wild-caught birds, which most likely reflect phenotypic adjustments, and not genotypic divergence. The allometric coefficient (a) in our study was also lower than reported in all allometric equations for temperate species (Table 1). Together with the very low scaling exponent (b), this indicates that both small and large tropical birds had lower BMR than temperate birds, but the difference in BMR between large temperate and trop- Figure 3. Mean BMRs of resident and migratory passerines in tropics and ical species is more pronounced than in small species. Tropical birds middle/high latitudes. TrRes and TrMig denote tropical residents and mi- of Southern Vietnam spend a considerable portion of their lives at grants, correspondingly (original data); TeMig and TeRes denote migrants ambient temperatures that exceed 30 C in the shade, which is close and residents on their breeding grounds at middle/high latitudes [data from to their body temperature. Moreover, during the lengthy rainy sea- McNab (2009)]. Current effect of the ANCOVA model was F ¼ 23.55, P < 3, 129 son they endure a very high temperature together with a very high 0.001 [log(body mass) was used as a covariate]. Vertical bars denote 95% humidity. Such conditions hamper heat dissipation both through confidence intervals (sample sizes are shown above them). *P < 0.05; ***P < 0.001. nonevaporative and evaporative thermoconductance, especially in large animals due to their unfavorable surface/volume ratio (Schmidt-Nielsen 1997). This physiological constraint is readily ap- residents and migrants from middle/high latitudes on their breeding parent in some energetic models, which assume positive and propor- grounds (P < 0.001). That was true also for passerines (P < 0.001) tional relationship between BMR and maximal aerobic capacity and non-passerines (P < 0.01) separately. The migrants in our study (Bennett and Ruben 1979) or maximal rate of daily work output did not differ in BMR from both migrants and residents on their (Gavrilov 1997). In the body of a large active animal, even a small breeding grounds in middle/high latitudes (P > 0.24). Among passer- portion of endogenous heat in addition to BMR may lead to over- ines, the BMR of long-distance migrants on their wintering grounds heating. From this point of view, the gentle allometric slope may re- was intermediate between tropical and temperate residents (Figure 3). flect the adaptive decrease of BMR in large birds, which are more vulnerable to hot conditions than small birds. That is one of the BMR of tropical versus temperate birds speculative explanations of the low scaling exponent in tropical We implemented some commonly used allometric equations to cal- birds, although we did not have data to test it. culate the predicted BMR of our birds using their mean body weight (Table 1). The considerable part of those equations (especially the Phylogenetic analysis of BMR old ones) were based on species from temperate areas, which Contrary to some other studies on energetics of tropical birds allowed us to compare BMR of tropical birds with estimated BMR (Wiersma et al. 2007b; Londono ~ et al. 2015), we did not find a sig- of temperate birds of the same body mass. On average, BMR of resi- nificant phylogenetic signal in mass-independent BMR. We demon- dent birds from Vietnam was 23% lower than the BMR of temper- strated that this trait has evolved independently of phylogeny, for ate species. Using raw data from McNab’s (2009) database, we example, close relatives are not more similar than distant relatives. found that resident birds from Vietnam had a 17.5% lower BMR The best-fit phylogenetic regression of BMR on body mass was the than residents from middle/high latitudes (P < 0.001). Similarly, model with Pagel’s covariance structure, but this result should be when comparing with raw data from other extensive studies on treated with caution. Due to the low values of a and k, there was not tropical birds (Wiersma et al. 2007b; McNab 2013; Londono ~ et al. enough power to adequately distinguish between BM and other evo- 2015), we found that BMR of our tropical residents was lower than lution models. The different models of evolution demonstrated very that in the cited works (P < 0.001). close values of regression coefficients in our study, which is in agree- ment with special articles on this topic (Jhwueng 2013). Although our number of species (n ¼ 66) is sufficient for phylogenetic analysis Discussion (Boettiger et al. 2012), the taxonomical and mass range was too lim- The relation between BMR and body mass ited to reliably extend this conclusion for all Southeast Asian trop- We found that the slope of relation between BMR and body mass in ical birds. tropical birds is very gentle (b ¼ 0.573) relative to temperate-zone The lack of phylogenetic signal in BMR of our sample of birds birds (b > 0.63 in all studies, see Table 1). The slope of the may reflect their strong adaptation to constant environment in log(BMR)  log(body mass) regression did not change significantly tropics: the body mass undertook the majority of BMR variation in different ecological and taxonomic groups of birds, when sample and leaved too little for the other traits, including phylogeny (see size was reduced to exclude species presented only by few individ- below). Another reason why interspecific differences in mass- uals, or after the inclusion of phylogeny into the model. The slopes independent BMR were not predicted by phylogeny may be related of the BMR regressions of tropical birds in other studies were simi- to methodological problems. One of them is possible inaccuracies in larly gentle, at least within the range of body weights up to 1–2 kg: the phylogenetic tree, particularly in branch lengths. However, the b ¼ 0.527 [calculated from Vleck and Vleck (1979)], b ¼ 0.542 effect of incorporating branch length information is negligible for Downloaded from https://academic.oup.com/cz/article-abstract/64/1/33/3084522 by Ed 'DeepDyve' Gillespie user on 16 March 2018 Bushuev et al.  Basal metabolic rate in free-living tropical birds 39 most of phylogenetic tests, including our main test, Pagel’s k We did not find any differences in BMR in Old World suboscines (Freckleton et al. 2002; Mu ¨ nkemu ¨ ller et al. 2012). The phylogenetic comparing to oscine passerines. BMRs of all 4 suboscine species fell regressions are also robust to errors in tree topology and branch close to the general regression line. If tropical passerines had higher lengths (Stone 2011). The more plausible methodic cause of the lack BMR than non-passerines, one could expect that more primitive of phylogenetic signal in BMR could be related to an insufficient Eurylaimides would have a lower BMR compared to oscines. Using sample size of different taxa. Our non-passerines were represented a mixed sample of temperate and tropical birds, Swanson and substantially by only Coraciiformes and Piciformes (Supplementary Bozinovic (2011) found that oscines have higher summit metabolic Table S1). Another possible bias could be an insufficient intraspe- rates (maximum rate of thermogenesis) than New World suboscines. cific sample size, which is known to have a great impact on phylo- This result favors the hypothesis, which explains competitive super- genetic analysis (Harmon and Losos 2005; Garamszegi and Møller iority of oscines by their higher metabolic capacities (Swanson and 2010; Mu ¨ nkemu ¨ ller et al. 2012). Of 66 species in our BMR data- Bozinovic 2011). base, 23 were represented only by 1 individual, 12 by 2 individuals, and 4 by 3 individuals. The influence of ecology and behavior on BMR We did not find any ecological or behavioral factors to have an im- The influence of taxonomy on BMR of tropical birds pact on BMR, with the exception of migratory tendency. Our data One of the reasons why passerine birds are so widespread and nu- suggest that migratory passerines from temperate and high latitudes merous may be related to their high BMR in comparison with other on their wintering grounds in tropics have a higher BMR than trop- taxa of endotherms (Gavrilov 1994, 1999a, 1999b, 2011, 2014). ical residents. This is in agreement with the results of a study com- Some studies attributed this energetic asymmetry to the phylogenetic paring migrants and residents based on a global database (Jetz et al. relationships between species (Reynolds and Lee 1996; Garland and 2008). Moreover, relatively high BMR was observed in several spe- Ives 2000; Rezende et al. 2002; McKechnie and Wolf 2004; cies of migratory shorebirds (Kersten and Piersma 1987; Lindstro¨m Wiersma et al. 2007b), although all of them were based on outdated 1997; Lindstro ¨ m and Klaassen 2003). Sedentary New Zealand and inaccurate phylogeny from Sibley and Ahlquist (1990). In our ducks have a lower BMR than migratory species from the same gen- study, tropical resident passerines did not show higher BMR than era (McNab 2003b). Intraspecific studies on captive-raised common non-passerines. This result contradicts previous comparisons of stonechats Saxicola torquata also showed that BMR was lower in BMR in these 2 groups of tropical birds (Wiersma et al. 2007b; individuals from a sedentary tropical population than in individuals McNab 2013; Londono ~ et al. 2015), but is in agreement with from a migratory temperate population (Klaassen 1995; Wikelski Gavrilov’s (2011, 2014) hypothesis. According to his conjecture, et al. 2003). passerine birds had to reduce flight speed for settlement in forest In addition, wintering passerine migrants from our study did not habitats. Passerines of the temperate zone could not reduce speed by differ in BMR from passerine migrants on their breeding grounds in an increase in head resistance as tropical birds do, because it is not temperate and high latitudes. Our results on BMR of migrants in energetically compatible with long-distance migrations. They used tropics support the aforementioned Gavrilov’s (2011, 2014) hypoth- other means to reduce flight speed, namely adopting a new style of esis about migratory tendency as an important cause of high BMR flight, which consists of the active work of wings in down-stroke in passerines. Jetz et al. (2008) found no significant difference in only. Such flight requires more energy, and migrating passerines ob- summer BMR between migrants and nonmigrants after accounting tained it by increasing their metabolic capacity, which was reflected for temperature, and concluded that higher BMR of migrants is in their BMR. Besides passerines there are 3 orders of birds with determined in part by temperature effects through phenotypic flexi- a similarly high BMR: Anseriformes, Procellariiformes, and bility. But, since we measured BMR of migrants and residents at the Charadriiformes (McNab 2015a). All these groups are also charac- same time and place, where representatives of both groups had been terized by high mobility and seasonal long-distance migration. It is living for several months, we conclude that higher BMR of migrants likely that natural selection does not act directly on BMR, but on could reflect the elevated maintenance costs of metabolic machinery correlated energetic traits. Among those, the most ecologically im- for long-distance migration. On the other hand, BMR of passerine portant traits are daily energy expenditure, maximal aerobic metab- migrants on their tropical wintering grounds in Vietnam was lower olism, potential productive energy, and maximum rate of a daily than that of passerine residents from temperate and high latitudes. locomotor activity (Bennett and Ruben 1979; Gavrilov 1997; This result suggests that migratory tendency is not the only driver of Nilsson 2002; White and Seymour 2004). Interspecific studies in increased metabolic power. Following the notion of Jetz et al. birds generally support the aerobic capacity model [see references in (2008), we consider low ambient temperatures at high latitudes as Swanson et al. (2012)], although the positive relationship between another obvious factor of BMR elevation (see next section). BMR and work output rate was not found in some studies (Ricklefs In contrast to our study, some researchers found BMR to be et al. 1996; Wiersma 2003; Welcker et al. 2015). lower in tropical birds that forage in the sun, than in those that for- Wiersma et al. (2007b) have found that tropical passerines had age in the shade (Weathers 1979, 1997; Hails 1983). Additionally, higher BMR than tropical non-passerines, but this difference was we did not find any relation between BMR and characteristics of not significant in phylogenetic models. McNab (2013) had found habitat, diet, and foraging substrates. Of the variation in BMR of 13 that passerines in his sample of tropical birds had a mean BMR that species of birds of paradise, 99% can be accounted for by interspe- is 75% greater than non-passerines of the same mass. He did not use cific variation in body mass, food habits, and altitudinal distribution phylogenetic methods in this comparison and pointed at several im- (McNab 2003a, 2005). The frugivorous birds of paradise had the portant aspects against the use of phylogenetic correction before fac- lowest BMR compared to omnivores and insectivores (McNab tor analysis. Using OLS models, Londono ~ et al. (2015) have found 2005). In contrast to birds of paradise, the BMR of New Guinean that passerine BMR averaged 12% higher than that of non- herbivores was 23% higher than in those with an animal diet passerines. Moreover, the PGLS analysis showed a difference in (McNab 2013). At the same time, there was no effect of food habits these groups in slopes as well. on BMR of honeyeaters (McNab 2016). The habitat type did not Downloaded from https://academic.oup.com/cz/article-abstract/64/1/33/3084522 by Ed 'DeepDyve' Gillespie user on 16 March 2018 40 Current Zoology, 2018, Vol. 64, No. 1 affect BMR of tropical birds from New Guinea, whereas foraging and provides support in favor of the “slow life history” hypothesis. substrate did: the highest BMR was found in species that forage on On the other hand, low BMR in tropical birds, as well as similarity trees compared to species that use aerial/ground feeding substrates ~ of avian BMR across altitudes in Peru (Londono et al. 2015), may (McNab 2013). be explained not by average ambient temperatures, but by seasonal Body mass on its own accounted for 93.0% of the variation of stability in tropics (Bech et al. 2016). In summary, the relative roles avian BMR in our study (94.2% if we excluded the barn swallow of temperature and life histories in latitudinal variation of BMR re- from the analysis, which was represented by a single individual with main unclear. exceptionally high BMR). The inclusion of any other factors did not In conclusion, using our sample of 54 sedentary and 12 migra- improve the model. In a similar analysis, McNab (2013) found that tory avian species from Southern Vietnam, we showed that tropical body mass accounted for 86.6% of the variation in BMR of tropical birds have 17.5–23% lower BMR than temperate birds. Also, the birds. Londono ~ et al. (2015) reported R 80% in a similar model most pronounced difference between tropical and temperate species and R 74% in phylogenetic analysis. McNab (2013) found at was the low scaling exponent in the allometric relation between least 9 significant factors of BMR variation, but with the exception BMR and body mass in tropical birds. This indicates that the differ- of migratory tendency, these factors increased R by 2.8% at most. ence in BMR between large temperate and tropical species is more Bringing passerine/nonpasserine dichotomy into analysis, McNab pronounced than in small species. Furthermore, we found evidence 2 2 (2013) increased R to 94.7%. Wiersma et al. (2007b) reported R that tropical migrants to temperate and high latitudes on their win- 93% for the same model. tering grounds might have higher BMR than tropical resident spe- Our inability to find significant ecological and behavioral factors cies. Apart from this observation, we did not find any evidence that of BMR variation may reflect the homogeneity of our sample of spe- phylogeny, taxonomy, behavior, and ecology have a significant in- cies and individuals: all birds were captured in roughly the same sea- fluence on BMR variation among birds of Southern Vietnam. Body son within a very confined territory without much difference in mass alone accounted for 93% of the variation in BMR in our biotopes and altitude. McNab (2013) had a much more diverse sam- study, which is higher than in other studies on tropical birds despite ple: birds from altitude up to 3,000 m, species with torpor, birds the narrower range of body mass in our sample of species. One of from small islands, flightless species, etc. the possible reasons for the poor correlations we observed between ecological factors and BMR, contrary to other studies on tropical BMR of tropical versus temperate birds birds, could be related to the uniformity of our study area with re- The BMR of tropical birds in our study was on average 23% lower spect to climate conditions and biotopes. The revealed absence of than predicted by most allometric equations for temperate species or differences in BMR between tropical passerines and non-passerines 17.5% lower than BMR of temperate birds from extensive McNab’s as well as the increased BMR in migratory species are consistent (2009) database. The common explanation of reduced BMR in trop- with the predictions of Gavrilov’s (2011, 2014) hypothesis. ical birds is the conformity of their life-history traits together with a slow pace of life (Wiersma et al. 2007b). However, besides life his- tory, there is another possible explanation for the latitudinal trend Acknowledgments in basal and field metabolic rates—temperature on breeding grounds We are grateful to the directorate of main and south divisions of the Joint (Anderson and Jetz 2005; Jetz et al. 2008; Bech et al. 2016). The Russian-Vietnamese Tropical and Technological Center for providing rooms heritable nature of BMR was shown in free-living birds (Bushuev ~ ~ and facilities (A.N. Kuznetsov, V.L. Trunov, Nguy^ en Thi Nga, Nguy^ en V an et al. 2011, 2012). If there is an impact of ambient temperature on Khu^ e). We are much obliged to V.V. Rozhnov for acquisition of respirometry energetics, the lower BMR of tropical birds is not necessarily evi- ~ equipment and to Nguy^ en V an Di^ e n, the director of C at Ti^ en National Park, dence for heritable differences in BMR. It could simply reflect the for permission to work there. We thank A.E. Anichkin, Nguy^ en V an Thi nh, high phenotypic plasticity of the energetics of birds (McKechnie VuM ~ a nh, and Nguy^ en BaœoNgoc for arranging our experiments; our col- leagues I.V. Palko and S.S. Gogoleva for help in the field; I.V. Palko and M.V. 2008; Swanson 2010; Kerimov et al. 2014). Kalyakin for expert categorization of ecological factors for our avian species; The low BMR of tropical species could result from the absence E.N. Rakhimberdiev for help in statistics; E.A. Ershova for corrections in of costly long-distance migrations and, in particular, the low de- English; A.B. Savinetsky for providing the original software used to control mands for thermogenesis in warm stable climate. Wiersma et al. the multi-channel system; and L.P. Korzun for the help on all preliminary (2007b) have found that tropical migrants breeding in temperate stages of our research. habitats had a lower BMR than temperate residents. Jetz et al. (2008) proposed that higher BMR of migrants is partly the result of the negative effects of temperature on BMR. White et al. (2007) Ethical note have concluded that low BMR of birds from hot arid environments The design of our study was approved by the ethics committee of Lomonosov results mainly from extreme temperatures. They found that BMR Moscow State University [resolution of the committee no 26(6)]. We have was negatively associated with ambient temperature and annual exerted every effort to carry out our work in compliance with present interna- temperature range, but was not correlated with low annual net pri- tional ethical standards. All our experiments were intravital and did not re- mary productivities. Bech et al. (2016) have showed that “slow pace quire prolonged treatment and handling of birds. None of the species from of life” in Australian old-endemic passerine birds was not accompa- our study were included in “Threatened” category of the IUCN Red List of nied by low BMR. On the other hand, Londono ~ et al. (2015) have Threatened Species. found no difference in BMR across a 2.6-km altitude gradient in tropical Peru. According to Jetz et al. (2008),a 20 C decrease in Funding temperature was associated with a 50% increase in BMR. Taking into account that the high-altitude site was on average 12 C colder Field work and initial data analysis was supported by the Tropical Center than the lowland site, the result of London ~o et al. (2015) argues (project Ekolan E-1.2) and partially by the Russian Foundation for Basic against the “temperature” explanation of low BMR in tropical birds Research (RFBR Grant nos 12-04-01440, 15-04-07407, and 15-04-08407). Downloaded from https://academic.oup.com/cz/article-abstract/64/1/33/3084522 by Ed 'DeepDyve' Gillespie user on 16 March 2018 Bushuev et al.  Basal metabolic rate in free-living tropical birds 41 The maintenance of the database and final data analysis was financially sup- Gavrilov VM, 1999b. Energy responses of passerine and non–passerine birds to their thermal environment: differences and ecological effects. Avian Ecol ported by the Russian Science Foundation (RSF Grant no. 14-50-00029). Behav 3:1–21. Gavrilov VM, 2011. Energy expenditures for flight, aerodynamic quality, and colonization of forest habitats by birds. Biol Bull 38:779–788. Supplementary Material Gavrilov VM, 2014. Ecological and scaling analysis of the energy expenditure of rest, activity, flight, and evaporative water loss in Passeriformes and non- Supplementary material can be found at https://academic.oup.com/cz. Passeriformes in relation to seasonal migrations and to the occupation of boreal stations in high and moderate latitudes. Q Rev Biol 89:107–150. Gessaman JA, Nagy KA, 1988. Energy metabolism: errors in gas-exchange References conversion factors. Physiol Zool 61:507–513. Anderson KJ, Jetz W, 2005. The broad-scale ecology of energy expenditure of Grafen A, 1989. The phylogenetic regression. Philos Trans R Soc B endotherms. Ecol Lett 8:310–318. 326:119–157. Aschoff J, Pohl HJ, 1970. Der Ruheumsatz von Vo ¨ geln als Funktion der Hackett SJ, Kimball RT, Reddy S, Bowie RCK, Braun EL et al., 2008. A phylo- Tageszeit und der Ko ¨ rpergro ¨ ße. J Ornith 111:38–47. genomic study of birds reveals their evolutionary history. Science Bech C, Chappell MA, Astheimer LB, Londono ~ GA, Buttemer WA, 2016. A 320:1763–1768. ‘slow pace of life’ in Australian old-endemic passerine birds is not accompa- Hails CJ, 1983. The metabolic rate of tropical birds. Condor 85:61–65. nied by low basal metabolic rates. J Comp Physiol B 186:503–512. Harmon LJ, Losos JB, 2005. The effect of intraspecific sample size on type I Bennett AF, Ruben JA, 1979. Endothermy and activity in vertebrates. Science and type II error rates in comparative studies. Evolution 59:2705–2710. 206:649–654. Ives AR, Midford PE, Garland T Jr, 2007. Within-species variation and meas- Bennett PM, Harvey PH, 1987. Active and resting metabolism in birds: allom- urement error in phylogenetic comparative methods. Syst Biol 56:252–270. etry, phylogeny and ecology. J Zool 213:327–344. Jetz W, Freckleton RP, McKechnie AE, 2008. Environment, migratory ten- Blanc L, Maury-Lechon G, Pascal J-P, 2000. Structure, floristic composition dency, phylogeny and basal metabolic rate in birds. PLoS ONE 3:e3261. and natural regeneration in the forests of Cat Tien National Park, Vietnam: Jhwueng D-C, 2013. Assessing the goodness of fit of phylogenetic comparative an analysis of the successional trends. J Biogeogr 27:141–157. methods: a meta-analysis and simulation study. PLoS ONE 8:e67001. Boettiger C, Coop G, Ralph P, 2012. Is your phylogeny informative? Jimenez AG, Cooper-Mullin C, Calhoon EA, Williams JB, 2014a. Measuring the power of comparative methods. Evolution 66:2240–2251. Physiological underpinnings associated with differences in pace of life and Brody S, Proctor RC, 1932. Growth and development, with special reference metabolic rate in north temperate and neotropical birds. J Comp Physiol B to domestic animals. XXIII. Relation between basal metabolism and mature 184:545–561. body weight in different species of mammals and birds. Univ Miss Agr Exp Jimenez AG, Harper JM, Queenborough SA, Williams JB, 2013. Linkages be- Sta Res Bull 166:89–101. tween the life-history evolution of tropical and temperate birds and the re- Bryant DM, Hails CJ, 1983. Energetics and growth patterns of three tropical sistance of cultured skin fibroblasts to oxidative and non–oxidative bird species. Auk 100:425–439. chemical injury. J Exp Biol 216:1373–1380. Bushuev AV, Husby A, Sternberg H, Grinkov VG, 2012. Quantitative genetics Jimenez AG, Van Brocklyn J, Wortman M, Williams JB, 2014b. Cellular meta- of basal metabolic rate and body mass in free-living pied flycatchers bolic rate is influenced by life-history traits in tropical and temperate birds. Ficedula hypoleuca. J Zool 288:245–251. PLoS ONE 9:e87349. Bushuev AV, Kerimov AB, Ivankina EV, 2011. Estimation of heritability and Jimenez AG, Williams JB, 2014. Differences in muscle fiber size and associated repeatability of resting metabolic rate in birds by the example of free-living energetic costs in phylogenetically paired tropical and temperate birds. Pied Flycatchers Ficedula hypoleuca (Aves: Passeriformes). Biol Bull Rev Physiol Biochem Zool 87:752–761. 1:26–46. Kendeigh SC, Dolnik VR, Gavrilov VM, 1977. Avian energetics. In: Pinowski Daan S, Masman D, Groenewold A, 1990. Avian basal metabolic rates: their J, Kendeigh SC, editors. Granivorous Birds in Ecosystem. Cambridge: association with body composition and energy expenditure in nature. Am J Cambridge University Press, 127–204. Physiol 259:R333–R340. Kerimov AB, Grinkov VG, Ivankina EV, Ilyina TA, Bushuev AV, 2014. The Downs CT, Brown M, 2012. Is respirometry a standardized technique? A re- influence of spring temperature on the intensity of advertising behavior and view of measurement of avian resting metabolic rates. J Therm Biol basal metabolic rate in bright and pale pied flycatcher Ficedula hypoleuca 37:531–536. males. Zool Zhurn 93:1288–1302. In Russian with English summary. Drummond AJ, Suchard MA, Xie D, Rambaut A, 2012. Bayesian phylogen- Kersten M, Piersma T, 1987. High levels of energy expenditure in shorebirds: etics with BEAUti and the BEAST 1.7. Mol Biol Evol 29:1969–1973. metabolic adaptations to an energetically expensive way of life. Ardea Frappell PB, Hinds DS, Boggs DF, 2001. Scaling of respiratory variables and 75:175–187. the breathing pattern in birds: an allometric and phylogenetic approach. King JR, Farner DS, 1961. Energy metabolism, thermoregulation and body Physiol Biochem Zool 74:75–89. temperature. In: Marshall AJ, editor. Biology and Comparative Physiology Freckleton RP, Harvey PH, Pagel M, 2002. Phylogenetic analysis and com- of Birds. New York: Academic Press, 215–288. parative data: a test and review of evidence. Am Nat 160:712–726. Klaassen M, 1995. Molt and basal metabolic costs in males of 2 subspecies of Garamszegi LZ, Møller AP, 2010. Effects of sample size and intraspecific vari- stonechats - the European Saxicola torquata rubicula and the east-African ation in phylogenetic comparative studies: a meta-analytic review. Biol Rev Saxicola torquata axillaris. Oecologia 104:424–432. Camb Philos Soc 85:797–805. Lasiewski RC, Dawson WR, 1967. A re-examination of the relation between Garland T Jr, Ives AR, 2000. Using the past to predict the present: confidence standard metabolic rate and body weight in birds. Condor 69:13–23. intervals for regression equations in phylogenetic comparative methods. Am Lindstro¨m A, 1997. Basal metabolic rates of migrating waders in the Eurasian Nat 155:346–364. Arctic. J Avian Biol 28:87–92. Gavrilov VM, 1994. Migrations and evolution of metabolism in birds. Ring Lindstro¨m A, Klaassen M, 2003. High basal metabolic rates of shorebirds 16:22–37. while in the Arctic: a circumpolar view. Condor 105:420–427. Gavrilov VM, 1997. Energetics and avian behavior. In: Turpaev TM, editor. Londono ~ GA, Chappell MA, Castaneda ~ MR, Jankowski JE, Robinson SK, Physiology and General Biology Reviews. Vol. 11. Amsterdam: Harwood 2015. Basal metabolism in tropical birds: latitude, altitude, and the “pace of Academic Publishers, 1–225. life”. Funct Ecol 29:338–346. Gavrilov VM, 1999a. Ecological phenomena of Passeriformes as a derivative Luft UC, Myhre LG, Loeppky JA, 1973. Validity of Haldane calculation for of their energetics. Acta Ornithol 34:165–172. estimating respiratory gas exchange. J Appl Physiol 34:864–865. Downloaded from https://academic.oup.com/cz/article-abstract/64/1/33/3084522 by Ed 'DeepDyve' Gillespie user on 16 March 2018 42 Current Zoology, 2018, Vol. 64, No. 1 Lusk G, 1924. Animal calorimetry: twenty-fourth paper. Analysis of the oxi- Schmidt-Nielsen K, 1997. Animal Physiology: Adaptation and Environment. New York: Cambridge University Press. dation of mixtures of carbohydrate and fat. J Biol Chem 59:41–42. Scholander PF, Walters V, Hock R, Irving L, 1950. Adaptation to cold in arctic MacMillen RE, 1974. Bioenergetics of Hawaiian honeycreepers: the Amakihi and tropical mammals and birds in relation to body temperature, insulation, Loxops virens and the Anianiau L. parva. Condor 76:62–69. and basal metabolic rate. Biol Bull 99:259–271. McKechnie AE, 2008. Phenotypic flexibility in basal metabolic rate and the changing view of avian physiological diversity: a review. J Comp Physiol B Sibley CG, Ahlquist JE, 1990. Phylogeny and Classification of Birds: A Study in Molecular Evolution. New Haven (CT): Yale University Press. 178:235–247. Speakman JR, 2005. Body size, energy metabolism and lifespan. J Exp Biol McKechnie AE, Freckleton RP, Jetz W, 2006. Phenotypic plasticity in the scal- 208:1717–1730. ing of avian basal metabolic rate. Proc R Soc B 273:931–937. Stone EA, 2011. Why the phylogenetic regression appears robust to tree mis- McKechnie AE, Wolf BO, 2004. The allometry of avian basal metabolic rate: specification. Syst Biol 60:245–260. good predictions need good data. Physiol Biochem Zool 77:502–521. Swanson DL, 2010. Seasonal metabolic variation in birds: functional and McNab BK, 1988. Food habits and the basal rate of metabolism in birds. mechanistic correlates. Curr Ornithol 17:75–129. Oecologia 77:343–349. Swanson DL, Bozinovic F, 2011. Metabolic capacity and the evolution of bio- McNab BK, 1997. On the utility of uniformity in the definition of basal rate of geographic patterns in oscine and suboscine passerine birds. Physiol metabolism. Physiol Zool 70:718–720. Biochem Zool 84:185–194. McNab BK, 2003a. Ecology shapes bird bioenergetics. Nature 426:620–621. Swanson DL, Thomas NE, Liknes ET, Cooper SJ, 2012. Intraspecific correl- McNab BK, 2003b. The energetics of New Zealand’s ducks. Comp Biochem ations of basal and maximal metabolic rates in birds and the aerobic cap- Physiol A 135:229–247. acity model for the evolution of endothermy. PLoS ONE 7:e34271. McNab BK, 2005. Food habits and the evolution of energetics in birds of para- Tieleman BI, Dijkstra TH, Lasky JR, Mauck RA, Visser GH et al., 2006. dise (Paradisaeidae). J Comp Physiol B 175:117–132. Physiological and behavioural correlates of life-history variation: a compari- McNab BK, 2009. Ecological factors affect the level and scaling of avian son between tropical and temperate zone house wrens. Funct Ecol BMR. Comp Biochem Physiol A 152:22–45. 20:491–499. McNab BK, 2012. Extreme Measures: The Ecological Energetics of Birds and Tieleman BI, Williams JB, 2000. The adjustment of avian metabolic rates and Mammals. Chicago (IL): University of Chicago Press. water fluxes to desert environments. Physiol Biochem Zool 73:461–479. McNab BK, 2013. The ecological energetics of birds in New Guinea. Bull Tieleman BI, Williams JB, Ricklefs RE, Klasing KC, 2005. Constitutive innate Florida Mus Nat Hist 52:95–159. immunity is a component of the pace-of-life syndrome in tropical birds. McNab BK, 2015a. Avian energetics: the passerine/non-passerine dichotomy. Proc R Soc B 272:1715–1720. Comp Biochem Physiol A 191:152–155. Vandekerkhove K, De Wulf R, Chin NN, 1993. Dendrological composition McNab BK, 2015b. Behavioral and ecological factors account for variation in and forest structure in Nam Bai Cat Tien National Park, Vietnam. Silva the mass-independent energy expenditures of endotherms. J Comp Physiol Gandavensis 58:41–83. B 185:1–13. Vleck CM, Vleck D, 1979. Metabolic rate in five tropical bird species. Condor McNab BK, 2016. Analysis of factors that influence energy expenditure in 81:89–91. honeyeaters (Meliphagidae). New Zeal J Zool 43:179–190. Wagner DN, Mineo PM, Sgueo C, Wikelski M, Schaeffer PJ, 2013. Does low Mu ¨ nkemu ¨ ller T, Lavergne S, Bzeznik B, Dray S, Jombart T et al., 2012. How daily energy expenditure drive low metabolic capacity in the tropical robin, to measure and test phylogenetic signal. Methods Ecol Evol 3:743–756. Turdus grayi? J Comp Physiol B 183:833–841. Nilsson JA, 2002. Metabolic consequences of hard work. Proc R Soc B Wagner JA, Horvath SM, Dahms TE, Reed S, 1973. Validation of open-circuit 269:1735–1739. method for the determination of oxygen consumption. J Appl Physiol Pagel M, 1999. Inferring the historical patterns of biological evolution. Nature 34:859–863. 401:877–884. Weathers WW, 1977. Temperature regulation in the dusky munia Lonchura Paradis E, Claude J, Strimmer K, 2004. APE: analyses of phylogenetics and fuscans (Cassin) (Estrildidae). Aust J Zool 25:193–199. evolution in R language. Bioinformatics 20:289–290. Weathers WW, 1979. Climatic adaptation in avian standard metabolic rate. Pettit TN, Ellis HI, Whittow GC, 1985. Basal metabolic rate in tropical sea- Oecologia 42:81–89. birds. Auk 102:172–174. Weathers WW, 1997. Energetics and thermoregulation by small passerines of Pinheiro J, Bates D, DebRoy S, Sarkar D, R Core Team, 2014. nlme: linear the humid, lowland tropics. Auk 114:341–353. and nonlinear mixed effects models. R package version 3.1-118. [cited 2017 Welcker J, Speakman JR, Elliott KH, Hatch SA, Kitaysky AS, 2015. Resting March 26]. Available from: https://CRAN.R-project.org/package¼nlme. and daily energy expenditures during reproduction are adjusted in opposite R Core Team, 2016. A language and environment for statistical computing. directions in free–living birds. Funct Ecol 29:250–258. Vienna (Austria): R Foundation for Statistical Computing [cited 2017 White CR, Blackburn TM, Martin GR, Butler PJ, 2007. Basal metabolic rate March 26]. Available from: https://www.R-project.org/. of birds is associated with habitat temperature and precipitation, not pri- Revell LJ, 2010. Phylogenetic signal and linear regression on species data. mary productivity. Proc R Soc B 274:287–293. Methods Ecol Evol 1:319–329. White CR, Phillips NF, Seymour RS, 2006. The scaling and temperature de- Revell LJ, 2012. phytools: an R package for phylogenetic comparative biology pendence of vertebrate metabolism. Biol Lett 2:125–127. (and other things). Methods Ecol Evol 3:217–223. White CR, Seymour RS, 2004. Does basal metabolic rate contain a useful sig- Reynolds PS, Lee IIIRM, 1996. Phylogenetic analysis of avian energetics: pas- nal? Mammalian BMR allometry and correlations with a selection of serines and nonpasserines do not differ. Am Nat 147:735–759. physiological, ecological, and life-history variables. Physiol Biochem Zool Rezende EL, Swanson DL, Novoa FF, Bozinovic F, 2002. Passerines versus 77:929–941. nonpasserines: so far, no statistical differences in the scaling of avian ener- Wiersma P, 2003. Working for a living: physiological and behavioural trade- getics. J Exp Biol 205:101–107. offs in birds facing hard work [PhD dissertation]. Zoological Laboratory, Ricklefs RE, Konarzewski M, Daan S, 1996. The relationship between basal Groningen, The Netherlands: University of Groningen. metabolic rate and daily energy expenditure in birds and mammals. Am Nat Wiersma P, Chappell MA, Williams JB, 2007a. Cold- and exercise-induced 147:1047–1071. peak metabolic rates in tropical birds. Proc Natl Acad Sci USA Ricklefs RE, Wikelski M, 2002. The physiology/life-history nexus. Trends 104:20866–20871. Ecol Evol 17:462–468. Wiersma P, Munoz- ~ Garcia A, Walker A, Williams JB, 2007b. Tropical birds Rubolini D, Liker A, Garamszegi LZ, Møller AP, Saino N, 2015. Using the have a slow pace of life. Proc Natl Acad Sci USA 104:9340–9345. BirdTree.org website to obtain robust phylogenies for avian comparative Wiersma P, Nowak B, Williams JB, 2012. Small organ size contributes to the studies: a primer. Curr Zool 61:959–965. slow pace of life in tropical birds. J Exp Biol 215:1662–1669. Downloaded from https://academic.oup.com/cz/article-abstract/64/1/33/3084522 by Ed 'DeepDyve' Gillespie user on 16 March 2018 Bushuev et al.  Basal metabolic rate in free-living tropical birds 43 Wikelski M, Spinney L, Schelsky W, Scheuerlein A, Gwinner E, 2003. Slow Wilmore JH, Costill DL, 1973. Adequacy of the Haldane transformation in pace of life in tropical sedentary birds: a common-garden experiment on four the computation of exercise VO in man. J Appl Physiol 35:85–89. stonechat populations from different latitudes. Proc R Soc B 270:2383–2388. Zar JH, 1969. The use of the allometric model for avian standard metabolism- Williams JB, Miller RA, Harper JM, Wiersma P, 2010. Functional linkages for the body weight relationships. Comp Biochem Physiol 29:227–234. pace of life, life-history, and environment in birds. Integr Comp Biol 50:855–868. 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Basal metabolic rate in free-living tropical birds: the influence of phylogenetic, behavioral, and ecological factors

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Abstract

The majority of our knowledge of avian energetics is based on studies of birds from temperate and high latitudes. Using the largest existing sample of wild-caught Old World tropical species, we showed that birds from Southern Vietnam had lower basal metabolic rate (BMR) than temperate species. The strongest dissimilarity between tropical and temperate species was the low scaling exponent in the allometric relation between BMR and body mass in tropical birds (the regression slope was 0.573). The passerine migrants to temperate and high latitudes had higher BMR than tropical sedentary passerines. Body mass alone accounted for 93% of the variation in BMR (body mass ranged from 5 to 252 g). Contrary to some other studies, we did not find evidence besides the above mentioned that phylogeny, taxonomy, behavior, or ecology have a significant influence on BMR variation among tropical birds. Key words: allometry, BMR, body mass, energy metabolism, tropical birds. The notable differences in numerous life-history and other traits be- The most commonly examined comparative measure of the tween tropical and temperate birds led to the notion that tropical metabolic rate of endotherms is basal metabolic rate (BMR), which birds have a “slow pace of life”: they live longer, have fewer off- is the minimum metabolic rate of an adult normothermic animal in spring, and invest more resources in self-maintenance, whereas tem- postabsorptive state and in nonreproductive phase, at rest and at perate birds have high rates of mortality and invest more resources temperatures within the thermoneutral zone (TNZ; McNab 1997). in reproduction (Williams et al. 2010; Jimenez et al. 2014a). The di- BMR is the lowest cost of body maintenance and, therefore, an im- versification of life histories in animals is limited by physiological portant characteristic of physiological heterogeneity of communities mechanisms (Ricklefs and Wikelski 2002). Physiological differences and separate populations of endotherms. To date, there is much evi- between birds of high and low latitudes remain insufficiently dence supporting the dependence of the variation in avian BMR on known, although some recent studies have made great progress in many factors, such as season, temperature, habitat, phylogeny, this respect (Tieleman et al. 2005, 2006; Wiersma et al. 2007a, behavior, etc. (McNab 2012). However, the importance of each fac- 2007b; Williams et al. 2010; Wiersma et al. 2012; Jimenez et al. tor with respect to the others often is not clear. For example, it is 2013, 2014b; Jimenez and Williams 2014). hard to separate the effects of temperature and pace of life V C The Author (2017). Published by Oxford University Press. 33 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com Downloaded from https://academic.oup.com/cz/article-abstract/64/1/33/3084522 by Ed 'DeepDyve' Gillespie user on 16 March 2018 34 Current Zoology, 2018, Vol. 64, No. 1 (London ~o et al. 2015; Bech et al. 2016) or temperature and migra- We predict that long-distance migration requires higher metabolic tory tendency (Jetz et al. 2008). capacity (e.g., based on higher mass of metabolically active tissues), Several physiological characteristics, which may relate to BMR which should be reflected in higher BMR of tropical migrants com- variation, are different in tropical and temperate species. In particular, pared to residents. Since most of the temperate passerines are migra- tropical birds have a smaller organ size, lower flight muscle, and fea- tory species, we think that one of the main reasons of increased ther mass (Williams et al. 2010; Wiersma et al. 2012), smaller muscle BMR in the temperate passerines is their migratory style of life. fiber size, and increased costs of maintaining muscle mass (Jimenez Therefore, we hypothesized that the energetic asymmetry between and Williams 2014), lower daily metabolized energy in nestlings passerines and non-passerines should be less pronounced in tropical residents than in breeding birds of higher latitudes. (Bryant and Hails 1983), lower summit metabolism and field meta- Together with migratory tendency and taxonomy, some ecolo- bolic rate (Wagner et al. 2013), lower peak metabolic rate (Wiersma gical factors may have a great impact on animal energetics (McNab et al. 2007a, 2007b), and cellular metabolic rate (Jimenez et al. 1988, 2009, 2015b). Among these factors we tested those that were 2014b). At least some of these features may be considered as the rea- shown to have influence on BMR in tropical birds: diet (arthropods, sons for BMR reduction in tropical birds. Although avian BMR was seeds, nectar, etc.) and some characteristics of behavior, which are studied in many works over the last century (Downs and Brown important in terms of risk of overheating (habitat, foraging in the 2012), the number of studies on free-living birds in tropics is much sun or shade, etc.). smaller compared to temperate zone. There are only 3 studies on In this study, we use the largest original dataset on BMR of Old BMR of tropical birds containing adequate sample sizes of individuals World wild-caught tropical birds to reveal features of tropical birds. and/or species. Two of them were done in the Neotropical region: the Specifically, we wish to: (1) estimate the influence of phylogeny, study by Wiersma et al. (2007b), based on 69 species from a lowland ecology, and migratory tendency on their BMRs; and (2) compare rainforest in Panama, and the very recent work by Londono ~ et al. BMR of tropical and temperate birds. (2015), based on 253 species from forests in Peru. The only compre- hensive study of energetics in tropical birds of the Old World is the re- cent monograph by McNab (2013), based on 45 free-living New Materials and Methods Guinea species and 32 species obtained from captivity. Capturing birds Some studies on avian energetics have found a reduced rate of me- We caught birds using mist nets in Cat Tien National park (Vu’o ’n tabolism in tropical birds (Weathers 1977; Hails 1983; Klaassen 0  0 quu’cgia C at Ti^ en), Southern Vietnam (11 25 N, 107 25 E; elevation 1995; Wikelski et al. 2003; Tieleman et al. 2006; McNab 2009), but 120–140 m) in a deciduous tropical forest with strongly degraded some have found it to be similar to the metabolic rate of birds from vegetation (Vandekerkhove et al. 1993; Blanc et al. 2000). Birds were higher latitudes or that the difference depends on species and their captured during 7–26 May 2011, 10–18 April 2012, and 15 March– ecology (Scholander et al. 1950; MacMillen 1974; Vleck and Vleck 11 May 2013. We weighed birds just after the capture. Juvenile birds 1979; Weathers 1979,1997; Pettit et al. 1985; Bennett and Harvey 1987; McNab 2013). Nevertheless, all phylogenetically controlled and females with a strongly pronounced brood patch were released multispecies studies have confirmed low metabolic rate in tropical immediately after weighing and did not participate in BMR measure- birds (Wiersma et al. 2007a, 2007b; London ~o et al. 2015; Bech et al. ments. We housed birds in soft mesh cages and provided water and 2016). The substantial studies by Wiersma et al. (2007a, 2007b)dem- food ad libitum. Birds were kept in cages for 10 h at maximum (mean onstrated lower basal and peak metabolic rates in Neotropical birds, is 5.5 h). Some birds (such as broadbills, pittas, doves, kingfishers, which perfectly fit the concept of slow “intensity of life” in tropical woodpeckers, and drongos) refused to eat and were force-fed every species. London ~o et al. (2015) found that BMR of temperate breeders 2 h with zophobas, mealworms, crickets, mango fruits, and dry feed Padovan (Valman s.r.l., Italy). The last feeding was done before 5 PM. is on average 16.4% higher than that of Neotropical species. At the We weighed all captured birds every 1–2 h, depending on the size of same time, McNab (2013) has showed that lowland tropical passer- species. If a bird’s weight had dropped noticeably (10% of body- ines from his and Wiersma et al. (2007b) datasets, on average, had a weight loss), we immediately released that individual. higher BMR than expected from a general avian-scaling curve. We obtained a total of 368 BMR measurements (equal to the However, unlike studies on Neotropical birds, McNab (2013) inten- number of individuals) during 79 nights. The number of individuals tionally did not correct his analyses for phylogeny. In our study, we per species ranged from 1 to 47 (average of 5.6). Our BMR database wanted to investigate whether the Old World birds follow the trend includes 66 species from 29 families belonging to 9 orders observed in the New World. (Supplementary Table S1). Latin and common names of species The higher BMR of passerines was one of the main taxonomic were taken from IOC World Bird Names v. 7.1 (http://www.world differences observed in the energetics of endotherms (e.g., Lasiewski birdnames.org/). and Dawson 1967; Aschoff and Pohl 1970; Kendeigh et al. 1977; Bennett and Harvey 1987; Gavrilov 1997; Jetz et al. 2008; McNab 2009, 2015a; Bech et al. 2016). However, with the exceptions of Measurements of BMR Wiersma et al. (2007b), McNab (2013), London ~o et al. (2015), and BMR of birds was estimated during the night after capture by flow- Bech et al. (2016), all comparisons between passerines and non- through respirometry (see Supplementary Materials for details about passerines were done using datasets substantially amassed on meta- respirometry equipment, calibration, leak testing, etc.). At 6 PM, bolic rates of temperate species. On the other hand, a comprehensive after sunset, we placed up to 7 (average of 4.8) birds inside cylin- phylogenetically controlled analysis by Jetz et al. (2008) revealed drical polypropylene chambers (1.3–2.7 L). We put metabolic cham- that BMR in migrants is much higher than in nonmigrant birds. bers in boxes made from sound-proofing and heat-insulating foam These researchers partially explained high BMR in long-distance mi- plastic. We used 20 L chambers for the largest species (Amaurornis grants with lower temperatures on their breeding grounds, but the phoenicurus, Arborophila chloropus, and Centropus sinensis). The BMR data for migrants on their tropical wintering grounds are too rates of gas exchange were measured until 6:00 AM. We did not scarce to test their hypothesis. In our study, we partly fill this gap. use thermostats because the ambient temperature in the laboratory Downloaded from https://academic.oup.com/cz/article-abstract/64/1/33/3084522 by Ed 'DeepDyve' Gillespie user on 16 March 2018 Bushuev et al.  Basal metabolic rate in free-living tropical birds 35 during measurements was very stable (recorded using type T thick grass or shrub (e.g., Acrocephalus sp., Locustella lanceolata, thermocouple probe [Sable Systems International, USA]). The tem- Phragmaticola aedon, Timalia pileata). Migratory species only perature inside the chambers was within 28–30 C (recorded every included migrants to temperate and high latitudes (54 species were 20 min with iButton thermologgers), which should be within the residents and 12 were migrants). All tropical breeders were catego- TNZ of most tropical birds (McNab 2013). rized as residents (sedentary birds), including Pitta moluccensis, We used 8 independent membrane pumps (AC-500, Resun, which performs winter migration to the Malay Archipelago. China) to push the outdoor air through columns containing self- indicating granulated fine-pored silica gel to remove water vapor and Statistical analysis then into metabolic chambers with birds. The flow rate was set at All scaling exponents in allometric equations in our study were based 250–1,200 mL/min (depending on the size of measured species). We on ordinary least squares (OLS) regressions, unless specifically men- used a custom built valve system, which alternately routed the air tioned. The body mass and BMR data were log -transformed before stream from each chamber with birds and an empty reference cham- analysis to account for allometric scale. To test for difference in inter- ber (for baselining) to the FoxBox-C Respirometry System (Sable cepts of log(BMR)  log(M) regressions in different groups of birds Systems International, USA), which included build-in air filters, mass (categorical predictor, e.g., residents/migrants), we used ANCOVA flowmeter, flow controller, membrane pump, O and CO analyzers. 2 2 with log(BMR) as dependent variable and log(M) as covariate. We After the air left the valve system, it was routed through a small col- tested the differences between observed and predicted values of BMR umn (V¼ 45–70 mL) with DrieriteV 10–20 mesh absorbent (W.A. using a t-test (predicted values were calculated using different allomet- Hammond Drierite Co. Ltd, USA) and then through mass flowmeter ric equations from Table 1). The differences between observed slopes into O /CO gas analyzers. Birds were measured alternately in cycles. 2 2 and theoretical slopes of 2/3 and 3/4 were tested with Welch’s t-test. The time of measurement for each bird within a cycle and the length To test for difference in slopes of 2 regression lines, we tested the of each cycle depended on the number of birds within a night session model with the interaction term of log(M) and the grouping factor and were at average of 25 and 139 min, correspondingly. Baselining versus the model without interaction using function “ANOVA.” All was performed 1–3 times during each cycle, depending on the number regression residuals were normally distributed, which was checked of measured birds. It was done in such a way that measurements of using Shapiro–Wilk test. All analyses were conducted in R (R Core each bird or at least each second bird adjoined with baselining. Team 2016). The significance level was set as a ¼ 0.05. Standard Around 6:00 AM, birds were removed from the chambers, weighed errors of intercepts and slopes are shown in equations in brackets. with a precision of 0.1 g, and released. To estimate BMR we selected the lowest stable part of the curve Phylogenetic analysis (average of 11 min) over the entire night. We rejected data from in- The phylogenetic relationships between studied species were ex- dividuals that did not become quiescent. The volume of consumed tracted from the BirdTree.org database (http://www.birdtree.org) oxygen was calculated from fractional concentrations of O and using the study by Hackett et al. (2008) as the backbone for phylo- CO according to the principle of Haldane transformation (Luft genetic reconstruction. A total of 1,000 trees were downloaded from et al. 1973; Wagner et al. 1973; Wilmore and Costill 1973): BirdTree.org, which is enough to obtain robust phylogenies E E (Rubolini et al. 2015). The resultant MCC consensus tree 1  F O  F CO 2 2 E I E VO ¼ V   F O  F O ; 2 2 2 I I (Supplementary Figure S1) was obtained by Treeannotator of 1  F O  F CO 2 2 BEAST 1.8.2 (Drummond et al. 2012). where V is the flow of dry air out of the animal chamber in volume Phylogenetic signal in traits was estimated with Pagel’s k (Pagel per time unit, F is volume fractional concentration of respective gas 1999; Freckleton et al. 2002) using function “phylosig” from pack- in dry inlet air, F is volume fractional concentration of respective age “phytools” (Revell 2012). We used phylogenetic generalized gas in dry outlet air. We calculated the respiratory quotient (VCO 2 least squares model (PGLS) to take the phylogenetic signal into ac- produced/VO consumed) and used it to convert the volume of oxy- 2 count in allometric analysis (Grafen 1989; Freckleton et al. 2002). gen consumption (VO ) to the values of energy expenditure (kJ/day) 2 We did not find any phylogenetic signal in the residual variation of using the equation 5 from Lusk (1924). Nevertheless, the mean the regression of log(BMR) on log(M) (i.e., mass-independent BMR was less than 0.01% different from the value calculated BMR). Consequently, the OLS method was more suitable for fitting through commonly used coefficient 19.8 J/mL O (Gessaman and 2 the regression models than PGLS (Revell 2010). We provided several Nagy 1988). phylogenetic regressions to show that regression coefficients from PGLS were very close to those that were obtained by OLS. We fit Categorization of ecological and behavioral factors PGLS via maximum likelihood (ML) approach using the function Following McNab (2009, 2013, 2015b), we used analysis of cova- “gls” from package “nlme” (Pinheiro et al. 2014). We specified 4 riance (ANCOVA) to determine which factors had an impact on different ways in which the tree structure is expected to affect the co- BMR. We used the following taxonomic, ecological, and behavioral variance in trait values across species (Brownian motion [BM], rankings: passerine/non-passerine and oscine/suboscine dichotomies, Grafen’s q, Pagel’s k, and Ornstein–Uhlenbeck [OU] models of evo- migratory behavior (migrant/resident), habitat type (exposed, forest lution) using package “ape” (Paradis et al. 2004). or intermediate), foraging substrate, feeding in the shade or sun, food We estimated the effect of within-species sampling (intraspecific habits (diet). We categorized species to ecological groups according to variation) on the strength of phylogenetic signal using function personal observations of our colleagues, I.V. Palko and M.V. “phylosig” from package “phytools” (Revell 2012). We also used function “pgls.Ives” from the same package (BM is assumed) to in- Kalyakin (Supplementary Table S1), who conduct long-term observa- tions on ecology and behavior of tropical birds in the study site. corporate sampling error in the estimation of species means by fit- Exposed (open) habitat type did not always equal to feeding in ting the phylogenetic reduced major axis (RMA) regression of Ives the sun, as some species from exposed habitats feed in the shade of et al. (2007). Downloaded from https://academic.oup.com/cz/article-abstract/64/1/33/3084522 by Ed 'DeepDyve' Gillespie user on 16 March 2018 36 Current Zoology, 2018, Vol. 64, No. 1 Table 1. The average ratio of observed whole-organism BMR of tropical resident birds of different taxonomic groups from Vietnam to pre- dicted BMR, estimated using allometric relationships between BMR and body mass from literature on corresponding groups Literature source ab Avian group Ratio (%) This study 195.75 0.573 Tropical (including migrants) 98.8 This study 200.18 0.581 Tropical (including migrants) (PC) 99.4 This study 267.49 0.622 Tropical migrants 84.9** This study 202.80 0.589 Tropical residents 100.0 Brody and Proctor (1932) 372.63 0.640 Temperate 65.6** King and Farner (1961) 335.36 0.659 Temperate 78.0** King and Farner (1961) 311.08 0.744 Large temperate (M > 125 g) 80.9* Lasiewski and Dawson (1967) 361.74 0.668 Temperate 74.7** Lasiewski and Dawson (1967) 540.10 0.724 Temperate passerines 64.6** Lasiewski and Dawson (1967) 327.83 0.723 Temperate non-passerines 90.8* Zar (1969) 324.06 0.739 Temperate 107.7 Zar (1969) 473.11 0.632 Temperate passerines 51.2** Zar (1969) 319.03 0.743 Temperate non-passerines 98.8 Aschoff and Pohl (1970) 480.64 0.726 Temperate passerines 73.2** Aschoff and Pohl (1970) 307.73 0.734 Temperate non-passerines 99.8 Bennett and Harvey (1987) 240.93 0.670 All 112.9** Daan et al. (1990) 361.32 0.677 All 77.2** Reynolds and Lee (1996) 343.17 0.670 All 79.3** Reynolds and Lee (1996) 339.25 0.635 All (PC) 70.8** Gavrilov (1997) 435.08 0.700 Passerines in summer 72.9** Gavrilov (1997) 349.65 0.710 Non-passerines in summer 82.0** Tieleman and Williams (2000) 308.32 0.638 All 78.8** Tieleman and Williams (2000) 279.90 0.677 All (PC) 99.7 Frappell et al. (2001) 471.39 0.680 Basically temperate 59.8** Frappell et al. (2001) 445.36 0.680 Basically temperate (PC) 63.3** Rezende et al. (2002) 329.64 0.635 All 72.9** Rezende et al. (2002) 399.98 0.721 All (PC) 81.7** McKechnie and Wolf (2004) 303.75 0.669 All 89.3** McKechnie and Wolf (2004) 243.51 0.677 All (PC) 114.6** Speakman (2005) 350.41 0.671 All 77.9** McKechnie et al. (2006) 315.1 0.744 All wild-caught birds (PC) 114.6* White et al. (2006) 243.35 0.640 All 100.5 Wiersma et al. (2007b) 307.97 0.644 Tropical passerines 82.4** Wiersma et al. (2007b) 262.73 0.644 Tropical non-passerines 90.7* McNab (2009) 314.47 0.652 All 81.2** McNab (2009) 429.69 0.713 Passerines 77.7** McNab (2009) 317.40 0.724 Non-passerines 94.1 McNab (2009) 451.02 0.708 Temperate passerines 71.6** McNab (2013) 234.97 0.581 Tropical (including non-residents) 84.7** McNab (2013) 245.39 0.634 Tropical residents 97.6 McNab (2013) 293.61 0.686 Tropical passerines 102.1 McNab (2013) 167.36 0.686 Tropical non-passerines 160.1** Londono ~ et al. (2015) 220.73 0.551 Tropical residents 82.3** Londono ~ et al. (2015) 193.95 0.543 Tropical residents (PC) 91.2** Londono ~ et al. (2015) 300.48 0.644 Tropical resident passerines 86.0** Londono ~ et al. (2015) 283.25 0.644 Tropical resident non-passerines 84.1** Londono ~ et al. (2015) 298.51 0.627 Tropical resident passerines (PC) 81.0** Londono ~ et al. (2015) 277.73 0.701 Tropical resident non-passerines (PC) 100.7 Notes: a is the allometric coefficient and b is the scaling exponent from equation BMR ¼ aM , where BMR is basal metabolic rate in kJ/day and M is body mass in kg. PC means “phylogenetically corrected.” Temperate birds here include also species from high latitudes. Marks recalculations based on equation 1 L of O ¼ 20.083 kJ of energy (Schmidt-Nielsen 1997). *P < 0.05; **P < 0.001. Results slope value (b¼ 0.57) differed from the theoretical slopes b¼ 0.75 (Kleiber’s law) and b¼ 0.67 (Rubner’s rule) (P < 0.001). If we included The relation between BMR and body mass in the analysis only species with more than 3 individuals [n 3isre- We found the mass exponent in the allometric relation between quirement from McKechnie and Wolf (2004)], the equation was BMR and body mass in tropical birds to be very small (Figure 1). log(BMR)¼ 0.598[0.040]þ 0.546[0.030]*log(M) (R ¼ 0.928). The adj The OLS regression between log(BMR) and log(M) was slope of the regression in the reduced sample was still significantly lower log(BMR)¼ 0.573[0.029]þ 0.573[0.019]*log(M) (R ¼ 0.930). The adj than 0.67 (P < 0.001). Downloaded from https://academic.oup.com/cz/article-abstract/64/1/33/3084522 by Ed 'DeepDyve' Gillespie user on 16 March 2018 Bushuev et al.  Basal metabolic rate in free-living tropical birds 37 1.0 1.5 2.0 1.0 1.5 2.0 log [body mass], g log [body mass], g Figure 1. The relationship between BMR and body mass in tropical birds of Figure 2. The relationship between BMR and body mass in resident (red thick Southern Vietnam (black thick solid line). Red solid triangles indicate passer- solid line, red solid triangles) and migratory (blue thick dashed line, blue ines; blue open squares indicate non-passerines. Green thin solid lines indi- open squares) tropical birds of Southern Vietnam. Thin dashed lines indicate cate theoretical slopes b ¼ 0.75 (Kleiber’s law) and b ¼ 0.67 (Rubner’s rule). 95% confidence intervals of the corresponding regressions. Black thin dashed lines indicate 95% confidence interval of the regression. The influence of taxonomy on BMR of tropical birds Phylogenetic analysis We did not find differences in BMR between tropical passerine and The coefficients of log(BMR)  log(M) regression did not change non-passerine birds: log(BMR)  log(M) regression lines of passer- significantly after taking phylogeny into account. We did not find a ines and non-passerines did not differ in slopes (P > 0.5), nor in phylogenetic signal in mass-independent BMR of tropical birds from intercepts (P > 0.7). The corresponding OLS regressions were our sample. log(BMR) ¼ 0.555[0.043] þ 0.588[0.033]*log(M) and log(BMR)¼ The Pagel’s k for log(M), log(BMR), and mass-independent 0.596[0.060] þ 0.559[0.032]*log(M). When we excluded migratory BMR were 0.989 (P < 0.001), 0.943 (P < 0.001), and 0.00007 species (all of them were passerines) from the analysis, absence of (P ¼ 1.00), respectively (P values indicate the significance of the dif- significant differences between passerines and non-passerines re- ference from zero). The Pagel’s k for log(M) and log(BMR) were not mained, and the equation for passerines changed to log(BMR)¼ significantly different from unity (P > 0.3), for example, we cannot 0.513[0.040] þ 0.609[0.029]*log(M). confidently distinguish our estimated phylogenetic signal in those Oscine passerines did not differ from suboscines in both regres- traits from BM. sion coefficients (P > 0.3 for the slopes, P > 0.5 for the intercepts), Comparison of different evolutionary models using the general although suboscines were represented by only 4 species with similar sample of migrant and resident species revealed that the best fit was body weights (52.7–115.3 g). the model with Pagel’s covariance structure (AIC¼172.32). It was followed by the OU model (AIC¼155.59) and covariance under The influence of ecology and behavior on BMR BM (AIC¼137.20). The phylogenetic regression from the model, Our results suggest that residential birds have a lower BMR than which finds and fits the ML value for Pagel’s k,was long-distance migrants on their wintering grounds in tropics. The in- log(BMR)¼ 0.557[0.047]þ 0.581[0.025]*log(M) (R ¼ 0.956). The fluence of all other ecological and behavioral factors was not signifi- best-fit value of k was determined to be very close to zero by ML and cant (habitat, feeding in the shade or sun, diet, foraging substrate). not different from zero (P¼ 1). The phylogenetic regression from the To simplify the analysis, the categories of different factors were vari- OU model was log(BMR)¼ 0.573[0.030]þ 0.573[0.020]*log(M), a (strength of the evolutionary constraint) was equal to 1.00. Assuming ously combined, but the adjusted R increased only by 0.011 at the BM model of evolution (Pagel’s k fixed to unity), the phylogenetic maximum. There was also no correlation between mean capture day regression was log(BMR)¼ 0.529[0.089]þ 0.589[0.034]*log(M). and BMR (Spearman’s q: P > 0.8). We repeated analysis with all branches of the tree set to unity. The There was no difference between resident (n¼ 54) and migratory (n¼ 12) species in slopes (P¼ 0.75) of log(BMR)  log (M) regressions, differences in phylogenetic signal were negligible from the above re- but migratory birds had a higher intercept (P¼ 0.014) (Figure 2). sults. The best-fit model (with Pagel’s covariance structure) gave the The OLS regressions for resident and migratory birds were phylogenetic regression log(BMR)¼ 0.541[0.045]þ 0.588[0.024]* log(BMR)¼ 0.539[0.028]þ 0.589[0.018]*log(M) and log(BMR)¼ log(M) (R ¼ 0.952). Incorporating the standard errors for each spe- 0.563[0.160]þ 0.622[0.145]*log(M), correspondingly. The difference cies into the model led to considerable reduction of sample size, as 23 of 66 species were presented only by a single individual; however, the in intercepts between migrants and residents only tended to be signifi- estimates of Pagel’s k did not change substantially for all traits. The cant after removal of the barn swallow from the analysis (P¼ 0.077). equation of the model, which took standard errors into account using We also compared our raw BMR data with those from McNab’s Ives et al. (2007) regression method, was log(BMR)¼ 0.580þ 0.564* (2009) comprehensive database (533 species) using ANCOVA. We log(M). found that tropical residents in our study had a lower BMR than both Downloaded from https://academic.oup.com/cz/article-abstract/64/1/33/3084522 by Ed 'DeepDyve' Gillespie user on 16 March 2018 log [BMR], kJ/day 1.0 1.2 1.4 1.6 1.8 2.0 log [BMR], kJ/day 1.0 1.2 1.4 1.6 1.8 2.0 38 Current Zoology, 2018, Vol. 64, No. 1 [calculated from Hails (1983)], b ¼ 0.508 [calculated from Tieleman *** et al. (2005)], b ¼ 0.581 (McNab 2013), and b ¼ 0.551 (Londono ~ et al. 2015). Wiersma et al. (2007b) reported a steeper slope, *** b ¼ 0.644, for birds breeding in tropics. The low scaling exponent relating BMR to body mass in tropical birds could be of a heritable nature or could be an effect of phenotypic plasticity in response to different environmental conditions. For instance, McKechnie et al. (2006) found substantial differences in scaling coefficients for BMR in captive-raised and wild-caught birds, which most likely reflect phenotypic adjustments, and not genotypic divergence. The allometric coefficient (a) in our study was also lower than reported in all allometric equations for temperate species (Table 1). Together with the very low scaling exponent (b), this indicates that both small and large tropical birds had lower BMR than temperate birds, but the difference in BMR between large temperate and trop- Figure 3. Mean BMRs of resident and migratory passerines in tropics and ical species is more pronounced than in small species. Tropical birds middle/high latitudes. TrRes and TrMig denote tropical residents and mi- of Southern Vietnam spend a considerable portion of their lives at grants, correspondingly (original data); TeMig and TeRes denote migrants ambient temperatures that exceed 30 C in the shade, which is close and residents on their breeding grounds at middle/high latitudes [data from to their body temperature. Moreover, during the lengthy rainy sea- McNab (2009)]. Current effect of the ANCOVA model was F ¼ 23.55, P < 3, 129 son they endure a very high temperature together with a very high 0.001 [log(body mass) was used as a covariate]. Vertical bars denote 95% humidity. Such conditions hamper heat dissipation both through confidence intervals (sample sizes are shown above them). *P < 0.05; ***P < 0.001. nonevaporative and evaporative thermoconductance, especially in large animals due to their unfavorable surface/volume ratio (Schmidt-Nielsen 1997). This physiological constraint is readily ap- residents and migrants from middle/high latitudes on their breeding parent in some energetic models, which assume positive and propor- grounds (P < 0.001). That was true also for passerines (P < 0.001) tional relationship between BMR and maximal aerobic capacity and non-passerines (P < 0.01) separately. The migrants in our study (Bennett and Ruben 1979) or maximal rate of daily work output did not differ in BMR from both migrants and residents on their (Gavrilov 1997). In the body of a large active animal, even a small breeding grounds in middle/high latitudes (P > 0.24). Among passer- portion of endogenous heat in addition to BMR may lead to over- ines, the BMR of long-distance migrants on their wintering grounds heating. From this point of view, the gentle allometric slope may re- was intermediate between tropical and temperate residents (Figure 3). flect the adaptive decrease of BMR in large birds, which are more vulnerable to hot conditions than small birds. That is one of the BMR of tropical versus temperate birds speculative explanations of the low scaling exponent in tropical We implemented some commonly used allometric equations to cal- birds, although we did not have data to test it. culate the predicted BMR of our birds using their mean body weight (Table 1). The considerable part of those equations (especially the Phylogenetic analysis of BMR old ones) were based on species from temperate areas, which Contrary to some other studies on energetics of tropical birds allowed us to compare BMR of tropical birds with estimated BMR (Wiersma et al. 2007b; Londono ~ et al. 2015), we did not find a sig- of temperate birds of the same body mass. On average, BMR of resi- nificant phylogenetic signal in mass-independent BMR. We demon- dent birds from Vietnam was 23% lower than the BMR of temper- strated that this trait has evolved independently of phylogeny, for ate species. Using raw data from McNab’s (2009) database, we example, close relatives are not more similar than distant relatives. found that resident birds from Vietnam had a 17.5% lower BMR The best-fit phylogenetic regression of BMR on body mass was the than residents from middle/high latitudes (P < 0.001). Similarly, model with Pagel’s covariance structure, but this result should be when comparing with raw data from other extensive studies on treated with caution. Due to the low values of a and k, there was not tropical birds (Wiersma et al. 2007b; McNab 2013; Londono ~ et al. enough power to adequately distinguish between BM and other evo- 2015), we found that BMR of our tropical residents was lower than lution models. The different models of evolution demonstrated very that in the cited works (P < 0.001). close values of regression coefficients in our study, which is in agree- ment with special articles on this topic (Jhwueng 2013). Although our number of species (n ¼ 66) is sufficient for phylogenetic analysis Discussion (Boettiger et al. 2012), the taxonomical and mass range was too lim- The relation between BMR and body mass ited to reliably extend this conclusion for all Southeast Asian trop- We found that the slope of relation between BMR and body mass in ical birds. tropical birds is very gentle (b ¼ 0.573) relative to temperate-zone The lack of phylogenetic signal in BMR of our sample of birds birds (b > 0.63 in all studies, see Table 1). The slope of the may reflect their strong adaptation to constant environment in log(BMR)  log(body mass) regression did not change significantly tropics: the body mass undertook the majority of BMR variation in different ecological and taxonomic groups of birds, when sample and leaved too little for the other traits, including phylogeny (see size was reduced to exclude species presented only by few individ- below). Another reason why interspecific differences in mass- uals, or after the inclusion of phylogeny into the model. The slopes independent BMR were not predicted by phylogeny may be related of the BMR regressions of tropical birds in other studies were simi- to methodological problems. One of them is possible inaccuracies in larly gentle, at least within the range of body weights up to 1–2 kg: the phylogenetic tree, particularly in branch lengths. However, the b ¼ 0.527 [calculated from Vleck and Vleck (1979)], b ¼ 0.542 effect of incorporating branch length information is negligible for Downloaded from https://academic.oup.com/cz/article-abstract/64/1/33/3084522 by Ed 'DeepDyve' Gillespie user on 16 March 2018 Bushuev et al.  Basal metabolic rate in free-living tropical birds 39 most of phylogenetic tests, including our main test, Pagel’s k We did not find any differences in BMR in Old World suboscines (Freckleton et al. 2002; Mu ¨ nkemu ¨ ller et al. 2012). The phylogenetic comparing to oscine passerines. BMRs of all 4 suboscine species fell regressions are also robust to errors in tree topology and branch close to the general regression line. If tropical passerines had higher lengths (Stone 2011). The more plausible methodic cause of the lack BMR than non-passerines, one could expect that more primitive of phylogenetic signal in BMR could be related to an insufficient Eurylaimides would have a lower BMR compared to oscines. Using sample size of different taxa. Our non-passerines were represented a mixed sample of temperate and tropical birds, Swanson and substantially by only Coraciiformes and Piciformes (Supplementary Bozinovic (2011) found that oscines have higher summit metabolic Table S1). Another possible bias could be an insufficient intraspe- rates (maximum rate of thermogenesis) than New World suboscines. cific sample size, which is known to have a great impact on phylo- This result favors the hypothesis, which explains competitive super- genetic analysis (Harmon and Losos 2005; Garamszegi and Møller iority of oscines by their higher metabolic capacities (Swanson and 2010; Mu ¨ nkemu ¨ ller et al. 2012). Of 66 species in our BMR data- Bozinovic 2011). base, 23 were represented only by 1 individual, 12 by 2 individuals, and 4 by 3 individuals. The influence of ecology and behavior on BMR We did not find any ecological or behavioral factors to have an im- The influence of taxonomy on BMR of tropical birds pact on BMR, with the exception of migratory tendency. Our data One of the reasons why passerine birds are so widespread and nu- suggest that migratory passerines from temperate and high latitudes merous may be related to their high BMR in comparison with other on their wintering grounds in tropics have a higher BMR than trop- taxa of endotherms (Gavrilov 1994, 1999a, 1999b, 2011, 2014). ical residents. This is in agreement with the results of a study com- Some studies attributed this energetic asymmetry to the phylogenetic paring migrants and residents based on a global database (Jetz et al. relationships between species (Reynolds and Lee 1996; Garland and 2008). Moreover, relatively high BMR was observed in several spe- Ives 2000; Rezende et al. 2002; McKechnie and Wolf 2004; cies of migratory shorebirds (Kersten and Piersma 1987; Lindstro¨m Wiersma et al. 2007b), although all of them were based on outdated 1997; Lindstro ¨ m and Klaassen 2003). Sedentary New Zealand and inaccurate phylogeny from Sibley and Ahlquist (1990). In our ducks have a lower BMR than migratory species from the same gen- study, tropical resident passerines did not show higher BMR than era (McNab 2003b). Intraspecific studies on captive-raised common non-passerines. This result contradicts previous comparisons of stonechats Saxicola torquata also showed that BMR was lower in BMR in these 2 groups of tropical birds (Wiersma et al. 2007b; individuals from a sedentary tropical population than in individuals McNab 2013; Londono ~ et al. 2015), but is in agreement with from a migratory temperate population (Klaassen 1995; Wikelski Gavrilov’s (2011, 2014) hypothesis. According to his conjecture, et al. 2003). passerine birds had to reduce flight speed for settlement in forest In addition, wintering passerine migrants from our study did not habitats. Passerines of the temperate zone could not reduce speed by differ in BMR from passerine migrants on their breeding grounds in an increase in head resistance as tropical birds do, because it is not temperate and high latitudes. Our results on BMR of migrants in energetically compatible with long-distance migrations. They used tropics support the aforementioned Gavrilov’s (2011, 2014) hypoth- other means to reduce flight speed, namely adopting a new style of esis about migratory tendency as an important cause of high BMR flight, which consists of the active work of wings in down-stroke in passerines. Jetz et al. (2008) found no significant difference in only. Such flight requires more energy, and migrating passerines ob- summer BMR between migrants and nonmigrants after accounting tained it by increasing their metabolic capacity, which was reflected for temperature, and concluded that higher BMR of migrants is in their BMR. Besides passerines there are 3 orders of birds with determined in part by temperature effects through phenotypic flexi- a similarly high BMR: Anseriformes, Procellariiformes, and bility. But, since we measured BMR of migrants and residents at the Charadriiformes (McNab 2015a). All these groups are also charac- same time and place, where representatives of both groups had been terized by high mobility and seasonal long-distance migration. It is living for several months, we conclude that higher BMR of migrants likely that natural selection does not act directly on BMR, but on could reflect the elevated maintenance costs of metabolic machinery correlated energetic traits. Among those, the most ecologically im- for long-distance migration. On the other hand, BMR of passerine portant traits are daily energy expenditure, maximal aerobic metab- migrants on their tropical wintering grounds in Vietnam was lower olism, potential productive energy, and maximum rate of a daily than that of passerine residents from temperate and high latitudes. locomotor activity (Bennett and Ruben 1979; Gavrilov 1997; This result suggests that migratory tendency is not the only driver of Nilsson 2002; White and Seymour 2004). Interspecific studies in increased metabolic power. Following the notion of Jetz et al. birds generally support the aerobic capacity model [see references in (2008), we consider low ambient temperatures at high latitudes as Swanson et al. (2012)], although the positive relationship between another obvious factor of BMR elevation (see next section). BMR and work output rate was not found in some studies (Ricklefs In contrast to our study, some researchers found BMR to be et al. 1996; Wiersma 2003; Welcker et al. 2015). lower in tropical birds that forage in the sun, than in those that for- Wiersma et al. (2007b) have found that tropical passerines had age in the shade (Weathers 1979, 1997; Hails 1983). Additionally, higher BMR than tropical non-passerines, but this difference was we did not find any relation between BMR and characteristics of not significant in phylogenetic models. McNab (2013) had found habitat, diet, and foraging substrates. Of the variation in BMR of 13 that passerines in his sample of tropical birds had a mean BMR that species of birds of paradise, 99% can be accounted for by interspe- is 75% greater than non-passerines of the same mass. He did not use cific variation in body mass, food habits, and altitudinal distribution phylogenetic methods in this comparison and pointed at several im- (McNab 2003a, 2005). The frugivorous birds of paradise had the portant aspects against the use of phylogenetic correction before fac- lowest BMR compared to omnivores and insectivores (McNab tor analysis. Using OLS models, Londono ~ et al. (2015) have found 2005). In contrast to birds of paradise, the BMR of New Guinean that passerine BMR averaged 12% higher than that of non- herbivores was 23% higher than in those with an animal diet passerines. Moreover, the PGLS analysis showed a difference in (McNab 2013). At the same time, there was no effect of food habits these groups in slopes as well. on BMR of honeyeaters (McNab 2016). The habitat type did not Downloaded from https://academic.oup.com/cz/article-abstract/64/1/33/3084522 by Ed 'DeepDyve' Gillespie user on 16 March 2018 40 Current Zoology, 2018, Vol. 64, No. 1 affect BMR of tropical birds from New Guinea, whereas foraging and provides support in favor of the “slow life history” hypothesis. substrate did: the highest BMR was found in species that forage on On the other hand, low BMR in tropical birds, as well as similarity trees compared to species that use aerial/ground feeding substrates ~ of avian BMR across altitudes in Peru (Londono et al. 2015), may (McNab 2013). be explained not by average ambient temperatures, but by seasonal Body mass on its own accounted for 93.0% of the variation of stability in tropics (Bech et al. 2016). In summary, the relative roles avian BMR in our study (94.2% if we excluded the barn swallow of temperature and life histories in latitudinal variation of BMR re- from the analysis, which was represented by a single individual with main unclear. exceptionally high BMR). The inclusion of any other factors did not In conclusion, using our sample of 54 sedentary and 12 migra- improve the model. In a similar analysis, McNab (2013) found that tory avian species from Southern Vietnam, we showed that tropical body mass accounted for 86.6% of the variation in BMR of tropical birds have 17.5–23% lower BMR than temperate birds. Also, the birds. Londono ~ et al. (2015) reported R 80% in a similar model most pronounced difference between tropical and temperate species and R 74% in phylogenetic analysis. McNab (2013) found at was the low scaling exponent in the allometric relation between least 9 significant factors of BMR variation, but with the exception BMR and body mass in tropical birds. This indicates that the differ- of migratory tendency, these factors increased R by 2.8% at most. ence in BMR between large temperate and tropical species is more Bringing passerine/nonpasserine dichotomy into analysis, McNab pronounced than in small species. Furthermore, we found evidence 2 2 (2013) increased R to 94.7%. Wiersma et al. (2007b) reported R that tropical migrants to temperate and high latitudes on their win- 93% for the same model. tering grounds might have higher BMR than tropical resident spe- Our inability to find significant ecological and behavioral factors cies. Apart from this observation, we did not find any evidence that of BMR variation may reflect the homogeneity of our sample of spe- phylogeny, taxonomy, behavior, and ecology have a significant in- cies and individuals: all birds were captured in roughly the same sea- fluence on BMR variation among birds of Southern Vietnam. Body son within a very confined territory without much difference in mass alone accounted for 93% of the variation in BMR in our biotopes and altitude. McNab (2013) had a much more diverse sam- study, which is higher than in other studies on tropical birds despite ple: birds from altitude up to 3,000 m, species with torpor, birds the narrower range of body mass in our sample of species. One of from small islands, flightless species, etc. the possible reasons for the poor correlations we observed between ecological factors and BMR, contrary to other studies on tropical BMR of tropical versus temperate birds birds, could be related to the uniformity of our study area with re- The BMR of tropical birds in our study was on average 23% lower spect to climate conditions and biotopes. The revealed absence of than predicted by most allometric equations for temperate species or differences in BMR between tropical passerines and non-passerines 17.5% lower than BMR of temperate birds from extensive McNab’s as well as the increased BMR in migratory species are consistent (2009) database. The common explanation of reduced BMR in trop- with the predictions of Gavrilov’s (2011, 2014) hypothesis. ical birds is the conformity of their life-history traits together with a slow pace of life (Wiersma et al. 2007b). However, besides life his- tory, there is another possible explanation for the latitudinal trend Acknowledgments in basal and field metabolic rates—temperature on breeding grounds We are grateful to the directorate of main and south divisions of the Joint (Anderson and Jetz 2005; Jetz et al. 2008; Bech et al. 2016). The Russian-Vietnamese Tropical and Technological Center for providing rooms heritable nature of BMR was shown in free-living birds (Bushuev ~ ~ and facilities (A.N. Kuznetsov, V.L. Trunov, Nguy^ en Thi Nga, Nguy^ en V an et al. 2011, 2012). If there is an impact of ambient temperature on Khu^ e). We are much obliged to V.V. Rozhnov for acquisition of respirometry energetics, the lower BMR of tropical birds is not necessarily evi- ~ equipment and to Nguy^ en V an Di^ e n, the director of C at Ti^ en National Park, dence for heritable differences in BMR. It could simply reflect the for permission to work there. We thank A.E. Anichkin, Nguy^ en V an Thi nh, high phenotypic plasticity of the energetics of birds (McKechnie VuM ~ a nh, and Nguy^ en BaœoNgoc for arranging our experiments; our col- leagues I.V. Palko and S.S. Gogoleva for help in the field; I.V. Palko and M.V. 2008; Swanson 2010; Kerimov et al. 2014). Kalyakin for expert categorization of ecological factors for our avian species; The low BMR of tropical species could result from the absence E.N. Rakhimberdiev for help in statistics; E.A. Ershova for corrections in of costly long-distance migrations and, in particular, the low de- English; A.B. Savinetsky for providing the original software used to control mands for thermogenesis in warm stable climate. Wiersma et al. the multi-channel system; and L.P. Korzun for the help on all preliminary (2007b) have found that tropical migrants breeding in temperate stages of our research. habitats had a lower BMR than temperate residents. Jetz et al. (2008) proposed that higher BMR of migrants is partly the result of the negative effects of temperature on BMR. White et al. (2007) Ethical note have concluded that low BMR of birds from hot arid environments The design of our study was approved by the ethics committee of Lomonosov results mainly from extreme temperatures. They found that BMR Moscow State University [resolution of the committee no 26(6)]. We have was negatively associated with ambient temperature and annual exerted every effort to carry out our work in compliance with present interna- temperature range, but was not correlated with low annual net pri- tional ethical standards. All our experiments were intravital and did not re- mary productivities. Bech et al. (2016) have showed that “slow pace quire prolonged treatment and handling of birds. None of the species from of life” in Australian old-endemic passerine birds was not accompa- our study were included in “Threatened” category of the IUCN Red List of nied by low BMR. On the other hand, Londono ~ et al. (2015) have Threatened Species. found no difference in BMR across a 2.6-km altitude gradient in tropical Peru. According to Jetz et al. (2008),a 20 C decrease in Funding temperature was associated with a 50% increase in BMR. Taking into account that the high-altitude site was on average 12 C colder Field work and initial data analysis was supported by the Tropical Center than the lowland site, the result of London ~o et al. (2015) argues (project Ekolan E-1.2) and partially by the Russian Foundation for Basic against the “temperature” explanation of low BMR in tropical birds Research (RFBR Grant nos 12-04-01440, 15-04-07407, and 15-04-08407). Downloaded from https://academic.oup.com/cz/article-abstract/64/1/33/3084522 by Ed 'DeepDyve' Gillespie user on 16 March 2018 Bushuev et al.  Basal metabolic rate in free-living tropical birds 41 The maintenance of the database and final data analysis was financially sup- Gavrilov VM, 1999b. Energy responses of passerine and non–passerine birds to their thermal environment: differences and ecological effects. Avian Ecol ported by the Russian Science Foundation (RSF Grant no. 14-50-00029). Behav 3:1–21. Gavrilov VM, 2011. Energy expenditures for flight, aerodynamic quality, and colonization of forest habitats by birds. Biol Bull 38:779–788. Supplementary Material Gavrilov VM, 2014. Ecological and scaling analysis of the energy expenditure of rest, activity, flight, and evaporative water loss in Passeriformes and non- Supplementary material can be found at https://academic.oup.com/cz. Passeriformes in relation to seasonal migrations and to the occupation of boreal stations in high and moderate latitudes. Q Rev Biol 89:107–150. Gessaman JA, Nagy KA, 1988. Energy metabolism: errors in gas-exchange References conversion factors. Physiol Zool 61:507–513. Anderson KJ, Jetz W, 2005. The broad-scale ecology of energy expenditure of Grafen A, 1989. The phylogenetic regression. Philos Trans R Soc B endotherms. Ecol Lett 8:310–318. 326:119–157. Aschoff J, Pohl HJ, 1970. Der Ruheumsatz von Vo ¨ geln als Funktion der Hackett SJ, Kimball RT, Reddy S, Bowie RCK, Braun EL et al., 2008. A phylo- Tageszeit und der Ko ¨ rpergro ¨ ße. J Ornith 111:38–47. genomic study of birds reveals their evolutionary history. Science Bech C, Chappell MA, Astheimer LB, Londono ~ GA, Buttemer WA, 2016. A 320:1763–1768. ‘slow pace of life’ in Australian old-endemic passerine birds is not accompa- Hails CJ, 1983. The metabolic rate of tropical birds. Condor 85:61–65. nied by low basal metabolic rates. J Comp Physiol B 186:503–512. Harmon LJ, Losos JB, 2005. The effect of intraspecific sample size on type I Bennett AF, Ruben JA, 1979. Endothermy and activity in vertebrates. Science and type II error rates in comparative studies. Evolution 59:2705–2710. 206:649–654. Ives AR, Midford PE, Garland T Jr, 2007. Within-species variation and meas- Bennett PM, Harvey PH, 1987. Active and resting metabolism in birds: allom- urement error in phylogenetic comparative methods. Syst Biol 56:252–270. etry, phylogeny and ecology. J Zool 213:327–344. Jetz W, Freckleton RP, McKechnie AE, 2008. Environment, migratory ten- Blanc L, Maury-Lechon G, Pascal J-P, 2000. Structure, floristic composition dency, phylogeny and basal metabolic rate in birds. PLoS ONE 3:e3261. and natural regeneration in the forests of Cat Tien National Park, Vietnam: Jhwueng D-C, 2013. Assessing the goodness of fit of phylogenetic comparative an analysis of the successional trends. J Biogeogr 27:141–157. methods: a meta-analysis and simulation study. PLoS ONE 8:e67001. Boettiger C, Coop G, Ralph P, 2012. Is your phylogeny informative? Jimenez AG, Cooper-Mullin C, Calhoon EA, Williams JB, 2014a. Measuring the power of comparative methods. Evolution 66:2240–2251. Physiological underpinnings associated with differences in pace of life and Brody S, Proctor RC, 1932. Growth and development, with special reference metabolic rate in north temperate and neotropical birds. J Comp Physiol B to domestic animals. XXIII. Relation between basal metabolism and mature 184:545–561. body weight in different species of mammals and birds. Univ Miss Agr Exp Jimenez AG, Harper JM, Queenborough SA, Williams JB, 2013. Linkages be- Sta Res Bull 166:89–101. tween the life-history evolution of tropical and temperate birds and the re- Bryant DM, Hails CJ, 1983. Energetics and growth patterns of three tropical sistance of cultured skin fibroblasts to oxidative and non–oxidative bird species. Auk 100:425–439. chemical injury. J Exp Biol 216:1373–1380. Bushuev AV, Husby A, Sternberg H, Grinkov VG, 2012. Quantitative genetics Jimenez AG, Van Brocklyn J, Wortman M, Williams JB, 2014b. Cellular meta- of basal metabolic rate and body mass in free-living pied flycatchers bolic rate is influenced by life-history traits in tropical and temperate birds. Ficedula hypoleuca. J Zool 288:245–251. PLoS ONE 9:e87349. Bushuev AV, Kerimov AB, Ivankina EV, 2011. Estimation of heritability and Jimenez AG, Williams JB, 2014. Differences in muscle fiber size and associated repeatability of resting metabolic rate in birds by the example of free-living energetic costs in phylogenetically paired tropical and temperate birds. Pied Flycatchers Ficedula hypoleuca (Aves: Passeriformes). Biol Bull Rev Physiol Biochem Zool 87:752–761. 1:26–46. Kendeigh SC, Dolnik VR, Gavrilov VM, 1977. Avian energetics. In: Pinowski Daan S, Masman D, Groenewold A, 1990. Avian basal metabolic rates: their J, Kendeigh SC, editors. Granivorous Birds in Ecosystem. Cambridge: association with body composition and energy expenditure in nature. Am J Cambridge University Press, 127–204. Physiol 259:R333–R340. Kerimov AB, Grinkov VG, Ivankina EV, Ilyina TA, Bushuev AV, 2014. The Downs CT, Brown M, 2012. Is respirometry a standardized technique? A re- influence of spring temperature on the intensity of advertising behavior and view of measurement of avian resting metabolic rates. J Therm Biol basal metabolic rate in bright and pale pied flycatcher Ficedula hypoleuca 37:531–536. males. Zool Zhurn 93:1288–1302. In Russian with English summary. Drummond AJ, Suchard MA, Xie D, Rambaut A, 2012. Bayesian phylogen- Kersten M, Piersma T, 1987. High levels of energy expenditure in shorebirds: etics with BEAUti and the BEAST 1.7. Mol Biol Evol 29:1969–1973. metabolic adaptations to an energetically expensive way of life. Ardea Frappell PB, Hinds DS, Boggs DF, 2001. Scaling of respiratory variables and 75:175–187. the breathing pattern in birds: an allometric and phylogenetic approach. King JR, Farner DS, 1961. Energy metabolism, thermoregulation and body Physiol Biochem Zool 74:75–89. temperature. In: Marshall AJ, editor. Biology and Comparative Physiology Freckleton RP, Harvey PH, Pagel M, 2002. Phylogenetic analysis and com- of Birds. New York: Academic Press, 215–288. parative data: a test and review of evidence. Am Nat 160:712–726. Klaassen M, 1995. Molt and basal metabolic costs in males of 2 subspecies of Garamszegi LZ, Møller AP, 2010. Effects of sample size and intraspecific vari- stonechats - the European Saxicola torquata rubicula and the east-African ation in phylogenetic comparative studies: a meta-analytic review. Biol Rev Saxicola torquata axillaris. Oecologia 104:424–432. Camb Philos Soc 85:797–805. Lasiewski RC, Dawson WR, 1967. A re-examination of the relation between Garland T Jr, Ives AR, 2000. Using the past to predict the present: confidence standard metabolic rate and body weight in birds. Condor 69:13–23. intervals for regression equations in phylogenetic comparative methods. Am Lindstro¨m A, 1997. Basal metabolic rates of migrating waders in the Eurasian Nat 155:346–364. Arctic. J Avian Biol 28:87–92. Gavrilov VM, 1994. Migrations and evolution of metabolism in birds. Ring Lindstro¨m A, Klaassen M, 2003. High basal metabolic rates of shorebirds 16:22–37. while in the Arctic: a circumpolar view. Condor 105:420–427. Gavrilov VM, 1997. Energetics and avian behavior. In: Turpaev TM, editor. Londono ~ GA, Chappell MA, Castaneda ~ MR, Jankowski JE, Robinson SK, Physiology and General Biology Reviews. Vol. 11. Amsterdam: Harwood 2015. Basal metabolism in tropical birds: latitude, altitude, and the “pace of Academic Publishers, 1–225. life”. Funct Ecol 29:338–346. Gavrilov VM, 1999a. Ecological phenomena of Passeriformes as a derivative Luft UC, Myhre LG, Loeppky JA, 1973. Validity of Haldane calculation for of their energetics. Acta Ornithol 34:165–172. estimating respiratory gas exchange. J Appl Physiol 34:864–865. Downloaded from https://academic.oup.com/cz/article-abstract/64/1/33/3084522 by Ed 'DeepDyve' Gillespie user on 16 March 2018 42 Current Zoology, 2018, Vol. 64, No. 1 Lusk G, 1924. Animal calorimetry: twenty-fourth paper. Analysis of the oxi- Schmidt-Nielsen K, 1997. Animal Physiology: Adaptation and Environment. New York: Cambridge University Press. dation of mixtures of carbohydrate and fat. J Biol Chem 59:41–42. Scholander PF, Walters V, Hock R, Irving L, 1950. Adaptation to cold in arctic MacMillen RE, 1974. Bioenergetics of Hawaiian honeycreepers: the Amakihi and tropical mammals and birds in relation to body temperature, insulation, Loxops virens and the Anianiau L. parva. Condor 76:62–69. and basal metabolic rate. Biol Bull 99:259–271. McKechnie AE, 2008. Phenotypic flexibility in basal metabolic rate and the changing view of avian physiological diversity: a review. J Comp Physiol B Sibley CG, Ahlquist JE, 1990. Phylogeny and Classification of Birds: A Study in Molecular Evolution. New Haven (CT): Yale University Press. 178:235–247. Speakman JR, 2005. Body size, energy metabolism and lifespan. J Exp Biol McKechnie AE, Freckleton RP, Jetz W, 2006. Phenotypic plasticity in the scal- 208:1717–1730. ing of avian basal metabolic rate. Proc R Soc B 273:931–937. Stone EA, 2011. Why the phylogenetic regression appears robust to tree mis- McKechnie AE, Wolf BO, 2004. The allometry of avian basal metabolic rate: specification. Syst Biol 60:245–260. good predictions need good data. Physiol Biochem Zool 77:502–521. Swanson DL, 2010. Seasonal metabolic variation in birds: functional and McNab BK, 1988. Food habits and the basal rate of metabolism in birds. mechanistic correlates. Curr Ornithol 17:75–129. Oecologia 77:343–349. Swanson DL, Bozinovic F, 2011. Metabolic capacity and the evolution of bio- McNab BK, 1997. On the utility of uniformity in the definition of basal rate of geographic patterns in oscine and suboscine passerine birds. Physiol metabolism. Physiol Zool 70:718–720. Biochem Zool 84:185–194. McNab BK, 2003a. Ecology shapes bird bioenergetics. Nature 426:620–621. Swanson DL, Thomas NE, Liknes ET, Cooper SJ, 2012. Intraspecific correl- McNab BK, 2003b. The energetics of New Zealand’s ducks. Comp Biochem ations of basal and maximal metabolic rates in birds and the aerobic cap- Physiol A 135:229–247. acity model for the evolution of endothermy. PLoS ONE 7:e34271. McNab BK, 2005. Food habits and the evolution of energetics in birds of para- Tieleman BI, Dijkstra TH, Lasky JR, Mauck RA, Visser GH et al., 2006. dise (Paradisaeidae). J Comp Physiol B 175:117–132. Physiological and behavioural correlates of life-history variation: a compari- McNab BK, 2009. Ecological factors affect the level and scaling of avian son between tropical and temperate zone house wrens. Funct Ecol BMR. Comp Biochem Physiol A 152:22–45. 20:491–499. McNab BK, 2012. Extreme Measures: The Ecological Energetics of Birds and Tieleman BI, Williams JB, 2000. The adjustment of avian metabolic rates and Mammals. Chicago (IL): University of Chicago Press. water fluxes to desert environments. Physiol Biochem Zool 73:461–479. McNab BK, 2013. The ecological energetics of birds in New Guinea. Bull Tieleman BI, Williams JB, Ricklefs RE, Klasing KC, 2005. Constitutive innate Florida Mus Nat Hist 52:95–159. immunity is a component of the pace-of-life syndrome in tropical birds. McNab BK, 2015a. Avian energetics: the passerine/non-passerine dichotomy. Proc R Soc B 272:1715–1720. Comp Biochem Physiol A 191:152–155. Vandekerkhove K, De Wulf R, Chin NN, 1993. Dendrological composition McNab BK, 2015b. Behavioral and ecological factors account for variation in and forest structure in Nam Bai Cat Tien National Park, Vietnam. Silva the mass-independent energy expenditures of endotherms. J Comp Physiol Gandavensis 58:41–83. B 185:1–13. Vleck CM, Vleck D, 1979. Metabolic rate in five tropical bird species. Condor McNab BK, 2016. Analysis of factors that influence energy expenditure in 81:89–91. honeyeaters (Meliphagidae). New Zeal J Zool 43:179–190. Wagner DN, Mineo PM, Sgueo C, Wikelski M, Schaeffer PJ, 2013. Does low Mu ¨ nkemu ¨ ller T, Lavergne S, Bzeznik B, Dray S, Jombart T et al., 2012. How daily energy expenditure drive low metabolic capacity in the tropical robin, to measure and test phylogenetic signal. Methods Ecol Evol 3:743–756. Turdus grayi? J Comp Physiol B 183:833–841. Nilsson JA, 2002. Metabolic consequences of hard work. Proc R Soc B Wagner JA, Horvath SM, Dahms TE, Reed S, 1973. Validation of open-circuit 269:1735–1739. method for the determination of oxygen consumption. J Appl Physiol Pagel M, 1999. Inferring the historical patterns of biological evolution. Nature 34:859–863. 401:877–884. Weathers WW, 1977. Temperature regulation in the dusky munia Lonchura Paradis E, Claude J, Strimmer K, 2004. APE: analyses of phylogenetics and fuscans (Cassin) (Estrildidae). Aust J Zool 25:193–199. evolution in R language. Bioinformatics 20:289–290. Weathers WW, 1979. Climatic adaptation in avian standard metabolic rate. Pettit TN, Ellis HI, Whittow GC, 1985. Basal metabolic rate in tropical sea- Oecologia 42:81–89. birds. Auk 102:172–174. Weathers WW, 1997. Energetics and thermoregulation by small passerines of Pinheiro J, Bates D, DebRoy S, Sarkar D, R Core Team, 2014. nlme: linear the humid, lowland tropics. Auk 114:341–353. and nonlinear mixed effects models. R package version 3.1-118. [cited 2017 Welcker J, Speakman JR, Elliott KH, Hatch SA, Kitaysky AS, 2015. Resting March 26]. Available from: https://CRAN.R-project.org/package¼nlme. and daily energy expenditures during reproduction are adjusted in opposite R Core Team, 2016. A language and environment for statistical computing. directions in free–living birds. Funct Ecol 29:250–258. Vienna (Austria): R Foundation for Statistical Computing [cited 2017 White CR, Blackburn TM, Martin GR, Butler PJ, 2007. Basal metabolic rate March 26]. Available from: https://www.R-project.org/. of birds is associated with habitat temperature and precipitation, not pri- Revell LJ, 2010. Phylogenetic signal and linear regression on species data. mary productivity. Proc R Soc B 274:287–293. Methods Ecol Evol 1:319–329. White CR, Phillips NF, Seymour RS, 2006. The scaling and temperature de- Revell LJ, 2012. phytools: an R package for phylogenetic comparative biology pendence of vertebrate metabolism. Biol Lett 2:125–127. (and other things). Methods Ecol Evol 3:217–223. White CR, Seymour RS, 2004. Does basal metabolic rate contain a useful sig- Reynolds PS, Lee IIIRM, 1996. Phylogenetic analysis of avian energetics: pas- nal? Mammalian BMR allometry and correlations with a selection of serines and nonpasserines do not differ. Am Nat 147:735–759. physiological, ecological, and life-history variables. Physiol Biochem Zool Rezende EL, Swanson DL, Novoa FF, Bozinovic F, 2002. Passerines versus 77:929–941. nonpasserines: so far, no statistical differences in the scaling of avian ener- Wiersma P, 2003. Working for a living: physiological and behavioural trade- getics. J Exp Biol 205:101–107. offs in birds facing hard work [PhD dissertation]. Zoological Laboratory, Ricklefs RE, Konarzewski M, Daan S, 1996. The relationship between basal Groningen, The Netherlands: University of Groningen. metabolic rate and daily energy expenditure in birds and mammals. Am Nat Wiersma P, Chappell MA, Williams JB, 2007a. Cold- and exercise-induced 147:1047–1071. peak metabolic rates in tropical birds. Proc Natl Acad Sci USA Ricklefs RE, Wikelski M, 2002. The physiology/life-history nexus. Trends 104:20866–20871. Ecol Evol 17:462–468. Wiersma P, Munoz- ~ Garcia A, Walker A, Williams JB, 2007b. Tropical birds Rubolini D, Liker A, Garamszegi LZ, Møller AP, Saino N, 2015. Using the have a slow pace of life. Proc Natl Acad Sci USA 104:9340–9345. BirdTree.org website to obtain robust phylogenies for avian comparative Wiersma P, Nowak B, Williams JB, 2012. Small organ size contributes to the studies: a primer. Curr Zool 61:959–965. slow pace of life in tropical birds. J Exp Biol 215:1662–1669. Downloaded from https://academic.oup.com/cz/article-abstract/64/1/33/3084522 by Ed 'DeepDyve' Gillespie user on 16 March 2018 Bushuev et al.  Basal metabolic rate in free-living tropical birds 43 Wikelski M, Spinney L, Schelsky W, Scheuerlein A, Gwinner E, 2003. Slow Wilmore JH, Costill DL, 1973. Adequacy of the Haldane transformation in pace of life in tropical sedentary birds: a common-garden experiment on four the computation of exercise VO in man. J Appl Physiol 35:85–89. stonechat populations from different latitudes. Proc R Soc B 270:2383–2388. Zar JH, 1969. The use of the allometric model for avian standard metabolism- Williams JB, Miller RA, Harper JM, Wiersma P, 2010. Functional linkages for the body weight relationships. Comp Biochem Physiol 29:227–234. pace of life, life-history, and environment in birds. Integr Comp Biol 50:855–868. Downloaded from https://academic.oup.com/cz/article-abstract/64/1/33/3084522 by Ed 'DeepDyve' Gillespie user on 16 March 2018

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