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Lastly, we used OLS simple regression to examine the relationship between MIBMR and latitude-independent range size at the among-families level using family mean trait values. All statistical analyses were performed in R 2. The representative number of species for the remaining families ranged from Thus, range size in squared area, and latitudinal and longitudinal extent provide very similar information.

We present only the results involving range area. Histograms of range size are shown in Figure S1. Range size in mammals varied from less than 1 km 2 for the murid rodent Melomys rubicola to 63 million km 2 for the red fox Vulpes vulpes. By contrast the distribution of range sizes of the species for which we had appropriate metabolic rate data ranged from 2, km 2 in the chipmunk Tamias palmeri to 63 million km 2 in the red fox.

Thus, our data set varied over 5 orders of magnitude compared to 12 orders of magnitude in PanTHERIA and was biased against species with small ranges. Both distributions were strongly right-skewed for untransformed data but less strongly left-skewed for log 10 transformed data. Similar results were found when the rodent data were analyzed separately Figure S1.

For all mammals, mass explained Residuals were normally distributed and MIBMR was not correlated with mass; species with both higher and lower than expected BMR for their body size occurred across the range of masses Figure S2. For rodents only, mass explained Again, residuals were normally distributed and not correlated with mass. Significant relationships are indicated by OLS regression lines-of-best-fit. Positive latitudes represent the Northern hemisphere; negative latitudes represent the Southern hemisphere.

MIBMR increased relatively strongly with latitude in the Northern hemisphere, where the data extend to MIBMR increased less strongly if at all with latitude in the Southern hemisphere, where the data extend only to We also divided the range size data into quartiles: average MIBMR decreased significantly from the highest to lowest quartile Figure 4a.

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When the correlation between latitude and range size was removed, the relationship between latitude-independent range size and MIBMR was not significant for OLS and marginally significant 0. Table 2. Dotted lines were drawn by eye to illustrate the hypothesized functional constraint see text. Table 3. For rodents, there was no significant relationship between range size and mass or between range size and BMR Table 2 ; Figure 3d,e.

However, again, these relationships changed when separated by region Table 3. Table 4. In the Tropics, there was no significant effect of any variable on range size. As described earlier, the low species-level resolution of mammalian relationships afforded weak tests of the impact of phylogeny upon the traits analyzed, so we opted to also examine these relationships at the family level where data permitted. Points without error bars are families represented by a single species. OLS regression lines are plotted where significant.

Geographic range size is codified as a key criterion for inferring vulnerability to extinction [ , ]. The underlying assumption is that narrow distribution or stenotopy is inherently risky and conversely that broad distribution or eurytopy confers resistance to stochastic extinction. We hypothesized that diversity in geographic range size in the assemblage of contemporary terrestrial mammals would be positively related to diversity in metabolic rate. Using the largest macrophysiological dataset yet assembled for mammals or any other major monophyletic radiation , we found evidence for this prediction in two dimensions: BMR, a measure of absolute minimal energy demand, and MIBMR, a measure of relative minimal energy demand, both of which are significantly positively correlated with range size.

Our analysis of the classic macroecological relationship between mass and range size showed that as body size increases, species occupy larger ranges, so there is a general lack of large-bodied stenotopic species Figure 3a,d , as previously known [ 18 , 63 , 65 , ]. Presumably, the operant constraints on minimum range size in both dimensions of energetics stem from per capita energy demand, in which an increase in either absolute mass, BMR or relative MIBMR energy demand increases the minimum area required for individuals and therefore species to support minimum viable populations to avoid extinction.

A recent refinement of the Energy Constraint Hypothesis modifies the classic view of the body size-range size relationship in mammals [ 65 ]. For larger species to the right of the mode, the pattern described above of progressively larger ranges with increasing body size was clearly evident in the expanded data set, consistent with the original Energy Constraint Hypothesis [ 18 ]. However, for smaller species to the left of the mode, the relationship between body size and range size was actually negative, prompting a modified Energy Constraint Hypothesis that includes a transition in the energetics of body size and its consequences for minimum space requirements as body size departs in either direction from the mode.

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Thus, the smallest mammals have the highest mass-specific energy demands, which may increase their space needs above those expected based solely on their small body size, as seen in the relationship between body size and home range size [ , ]. Thus, the negative relationship between body size and geographic range size in small mammals is now argued to be another constraint on minimum space requirements arising from progressively higher mass-specific energy demands at small body sizes [ 65 ]. It has long been assumed that energy demand underlies the relationship between mass and range size [ 18 ].

Our analysis of BMR and range size confirms this Figure 3b,e. Moreover, our analysis of MIBMR uncovers a second, previously unrecognized dimension to the energetics of range size diversity in mammals. In fact, MIBMR explained more variation in range size than mass, the most widely studied macroecological predictor of range size [ 7 , 14 , 17 , 64 , , ] Table 1. This pattern was amplified in the family-level analyses.

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However, the small amount of variation explained by the predictors we examined highlights the limited success that traditional regression approaches have had in resolving determinants of variation in range size, especially when large numbers of species are compared within a single set of statistical models [ 14 , 61 ]. A more informative perspective on macro-scale relationships between range size and species traits is the idea of a 2D trait-space bounded by mechanisms that restrict the combinations of values to fall within a constrained space Figure 1.

Further, the constraint space approach aims to decipher the functional constraints that correlate with parts of the trait-space in which particular types of species are under-represented or non-existent. From this perspective, we find that the shapes of the trait-spaces describing the relationships between range size and the predictor variables are highly similar Figure 3.

Each trait-space is roughly triangular and has a positive lower bound dotted lines in Figure 3 indicating a constraint on minimum range size as a function of absolute mass, BMR and relative MIBMR energy demand. The finding that trait-spaces involving metabolic rates as predictors reveal the same positive lower bound previously observed for mass provides the first direct macrophysiological evidence that energy limitation per se constrains the lower right portion of the trait-space, supporting the Energy Constraint Hypothesis [ 14 , 18 , 62 - 65 , ].

For BMR, this is not surprising because it is highly correlated with mass, which is what motivated the Energy Constraint Hypothesis to explain the body size-range size relationship in the first place [ 18 ]. Nevertheless, our analysis is apparently the first direct test using metabolic rate data. The discovery of the triangular trait-space and positive lower bound in the MIBMR-range size dimension is unexpected and, because BMR and MIBMR are not highly correlated with each other, it reveals a second dimension of energetic constraint on mammal distributions.

In the context of the Energy Constraint Hypothesis, the result that the positive lower bound is also evident for MIMBR indicates that species that have deviated towards higher metabolic rates are relatively rare and require among the largest ranges, above and beyond the increasing energy demands that accrue as an allometric consequence of evolutionary increases in body size. Figure 3c,f makes clear that low MIBMR does not necessarily restrict species to small ranges, but high MIBMR constrains species to large ranges, presumably to satisfy their sustained high per capita energy demands.

The hypothesis that energy demand per se restricts range size can be considered further by examining the distribution of range sizes for modal-sized mammals and how it varies as body size departs from the mode towards larger body size. First, consider two proxies of absolute energy demand, namely body size and non-mass-adjusted BMR. The modal body size in our data set occurs at log 10 1. Inspection of Figure 3a,d shows that as body size evolves away from this modal size range towards larger body size, a constraint on the minimum area needed to support the species appears to arise almost immediately, a point made in seminal macroecologcial analyses of birds [ 18 ] and mammals [ 63 ].

Thus, an apparent constraint arises as mammal body size, and by allometric consequence, its absolute energy demand increases from the modal body size. Second, from the perspective of relative energy demand, we can ask how departures above and below expected BMR influence range size. Relationships between species traits and measures of distribution and abundance, like those observed here, are generally weak in the traditional regression sense at large spatial and taxonomic scales for a variety of reasons [ 14 , 17 , ].

Two findings from our study help explain some of this unresolved variance, namely, that there are hemispheric and temperate—tropic differences in functional relationships Figure 2b , Figure 5 , Table 4 , Figure S3 , and that the strength of functional relationships depends on phylogenetic scale Figure 3 , Figure 6. Although this pattern has generally been found for terrestrial species in the Northern hemisphere, it is clearly not a rule because its existence is not taxonomically or geographically universal [ 7 , 27 , , ]. Our analysis was the first to use all available data 4, species from the PanTHERIA database [ 8 ] to examine the global latitudinal gradient in mammal range size and it revealed two notable patterns.

Second, and more apparent than the trends in average range size, the variance in range size decreased with latitude in both hemispheres, so that there was a general absence of stenotopic species whose geographic ranges are centered at high latitudes in both hemispheres Figure 2a. Thus, the global relationship between latitude and mammal range size can be summarized as: 1 few species with small ranges exist at high latitudes in both hemispheres, as predicted by the Climatic Variability Hypothesis but also by the idea that the gradient in range size is linked to the gradient in species richness [ 46 , , ] , but 2 range size tends to decrease with latitude in the Southern hemisphere and increase with latitude in the Northern hemisphere, as predicted if available land area acts as a constraint.

Indeed, land area decreases dramatically with latitude in the Southern hemisphere but increases with latitude in the Northern hemisphere [ ]. A similar global pattern between range size and latitude occurs in birds, which was found to be well-correlated with the global latitudinal gradient in total land area Figure 3 in [ ].

Both land area and average range size increase with latitude in the Northern hemisphere where there is more land overall, but decrease with latitude in the Southern hemisphere where there is less land overall. In contrast, the Climatic Variability Hypothesis predicts a pattern of increasing range size with latitude in both hemispheres. Along with latitudinal variation in range size, multiple regression indicated that significant predictors of range size can be region-specific Table 4.

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In this region, there was a significant positive relationship regardless of regression method OLS vs. PGLS or response variable range size vs. An obvious question is: why might the positive MIBMR-range size relationship be most evident at high latitudes in the North? The Climatic Variability Hypothesis predicts differences in physiological tolerances and, consequently, range sizes, between tropic versus temperate organisms [ 43 ].

MIBMR can be viewed as a proxy for thermal tolerance in endotherms because elevated metabolism increases the capacity for thermogenesis, which is needed to maintain body temperature at low environmental temperature see section Thermal Plasticity Hypothesis. Other aspects of metabolic capacity, such as nonshivering thermogenesis in rodents, also increase with latitude and decrease with environmental temperature [ ]. However, while MIBMR clearly increases with latitude in the Northern hemisphere, it is not clear from our data whether this also occurs in the Southern hemisphere.

Thus, the comparison of tropical species to northern species provides strong empirical support for the Climatic Variability Hypothesis. This pattern is both opposite that of northern mammals and not consistent with the prediction of the Climatic Variability Hypothesis, a discrepancy that may relate to the different historical and contemporary patterns of climatic variability and cold temperatures experienced at high latitudes in the Northern colder, more variable versus Southern warmer, less variable hemispheres [ 27 , 28 , 76 , ].

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Most macroecological and macrophysiological analyses to date ignore the biases that arise from phylogenetic relatedness, which are widely acknowledged in many other areas of comparative biology [ 23 , 24 ]. In part this is due to the general lack of resolved phylogenies for the very large groups of species for which physiological or distributional data are assembled from the literature, but also by some concerns about the utility and interpretation of phylogenetic comparative methods. Some have asserted that phylogenetic history should not be considered in the analysis of life historical or physiological traits because these traits must evolve rapidly and are under such strong adaptive constraint that it is not possible for phylogeny to constrain them [ - ].

However, these arguments have been mathematically falsified [ ] or are inconsistent with other empirical findings of substantial lineage effects on BMR and its allometric scaling in both mammals and birds [ 60 , 82 , , ]. A more credible issue is that, although phylogenetic comparative methods aim to statistically separate the component of trait variation explained by common descent from that which is typically viewed as the adaptive component i. Unfortunately, there is no current methodology for evaluating the contribution of adaptive stasis to phylogenetic signal, suggesting that phylogenetic comparative methods are overly conservative.

Nonetheless, relatedness clearly imposes some inertial constraint on adaptive evolution that must be considered, even if current methods are overly conservative. However, AICc scores from phylogenetic regression were consistently lower or comparable to AICc scores from non-phylogenetic regression, indicating that accounting for phylogeny generally provided as good or a better fit to the data than not doing so.

It must be noted that the overall poor resolution of the phylogeny means that the power of the phylogenetically-grounded analyses was weak. Thus, the lack of strong phylogenetic signal cannot be taken as a definitive indication that phylogeny does not play a role in character covariance among mammal species. This cautious view is reinforced by the additional analyses we conducted at the family level Figure 6. While the overall phylogenetically-structured analyses were not strikingly different from those not accounting for phylogeny, the analysis at the family level revealed much stronger functional relationships than the species-level analysis especially for rodents , which is a clear indication of covariance among species traits and range properties at the family level.

Physiological Ecology is the field concerned with understanding how organisms transduce abiotic environmental variance into the phenotypes that determine both individual fitness and demographic dynamics [ 53 - 57 , - ]. Although it had a central role in early-mid 20th century Ecology, Physiological Ecology was seconded to Community Ecology i.

Macrophysiology represents a conceptual reunification of physiology with ecology [ 36 ] and as such reintegrates these ideas into the ecological mainstream to address the fundamental ecological problem of understanding interspecific diversity in and functional constraints on the distribution and abundance of organisms. It also provides a theoretical platform for understanding mechanistically how abiotic factors influence distributions. Our analysis of PSTs as predictors of mammalian distributions explained more variance than previous studies that have used more tangential predictors such as body size Table 1 , especially at the family level Figure 6.

Moreover, we found neglected but meaningful ecological signals in the residuals of the BMR data, indicating that relative energy demand, above and beyond absolute energy demand, explains additional variance in mammalian range sizes.

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This finding of latent signal in the residuals MIBMR reflects functional divergence evolutionary excursions of mammal species above and below the constraint imposed by allometric scaling, and shows that our current grasp of how physiological constraints relate to distributions in mammals and other lineages is incomplete.

Neglected patterns in residuals of PST relationships deserve careful scrutiny in other systems and are fertile lines of inquiry for understanding species distributions [ 32 ]. Moreover, the macrophysiological signal emerging from the residuals invites caution in generalizations that have been advanced about how endotherms or ectotherms should respond to warming climates [ ] and how range size relates to vulnerability to extinction.

The assumption underlying geographic range size as a key criterion for extinction vulnerability [ , ] is that small ranges stenotopy are inherently risky while large ranges eurytopy confer resistance to stochastic extinction, an assumption that may be sound, all else equal. However, our analyses show that the degree to which stenotopy is risky in mammals likely depends on body size and comparative energetics. The previously recognized absence of large-bodied, stenotopic species has been argued to be due to a relatively higher likelihood of lethal energy limitation due to the higher spatio-temporal unpredictability of energy in small geographic areas Energy Constraint Hypothesis.

Our analyses demonstrate directly the link between allometric and non-allometric increases in energy demand estimated by BMR and MIBMR and variation in range size. From this, we infer that the degree to which stenotopy is risky is greatest in large mammals with high absolute energy demand. Furthermore, we infer that because this pattern also holds in the dimension of relative energy demand, those mammals with higher than expected BMR for their body size are at heightened vulnerability to range size reductions, above and beyond the vulnerability accrued as a result of large body size or small range size.

Hence, the mammal species most vulnerable to range size reductions and changes in energy landscapes e. Other recent findings further suggest that the smallest mammals those with the highest mass-specific BMR are also at heightened risk from range size reductions [ 65 ]. Put another way, the mammal species least at risk from range size reductions will approximate the modal-sized mammal and have a low MIBMR.

Macrophysiological approaches, which directly evaluate relationships between traits that are closely linked to organismal energetics and landscape-scale patterns of distribution, are useful for meeting this challenge, as shown here for analyses of the classic mammalian geographic range size distribution.

The dashed lines illustrate the bias in the data set used in this study c,f towards species with large ranges compared to the full distribution of range sizes found in the entire mammal assemblage b, e. Fenner Endowment of Wilkes University. This is contribution No. The aforementioned entities had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Browse Subject Areas? Click through the PLOS taxonomy to find articles in your field. Abstract Physiological processes are essential for understanding the distribution and abundance of organisms, and recently, with widespread attention to climate change, physiology has been ushered back to the forefront of ecological thinking. Funding: No current external funding sources for this study. Competing interests: The authors declared that no competing interests exist. Specifically, we wish to: 1 estimate the influence of phylogeny, ecology, and migratory tendency on their BMRs; and 2 compare BMR of tropical and temperate birds.

Birds were captured during 7—26 May , 10—18 April , and 15 March—11 May We weighed birds just after the capture. Juvenile birds and females with a strongly pronounced brood patch were released immediately after weighing and did not participate in BMR measurements. We housed birds in soft mesh cages and provided water and food ad libitum.

We obtained a total of BMR measurements equal to the number of individuals during 79 nights. The number of individuals per species ranged from 1 to 47 average of 5. BMR of birds was estimated during the night after capture by flow-through respirometry see Supplementary Materials for details about respirometry equipment, calibration, leak testing, etc.

We put metabolic chambers in boxes made from sound-proofing and heat-insulating foam plastic. The rates of gas exchange were measured until AM. We did not use thermostats because the ambient temperature in the laboratory during measurements was very stable recorded using type T thermocouple probe [Sable Systems International, USA].

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We used 8 independent membrane pumps AC, Resun, China to push the outdoor air through columns containing self-indicating granulated fine-pored silica gel to remove water vapor and then into metabolic chambers with birds. We used a custom built valve system, which alternately routed the air stream from each chamber with birds and an empty reference chamber for baselining to the FoxBox-C Respirometry System Sable Systems International, USA , which included build-in air filters, mass flowmeter, flow controller, membrane pump, O 2 and CO 2 analyzers.

Hammond Drierite Co. Birds were measured alternately in cycles. Baselining was performed 1—3 times during each cycle, depending on the number of measured birds. It was done in such a way that measurements of each bird or at least each second bird adjoined with baselining. Around AM, birds were removed from the chambers, weighed with a precision of 0.

We categorized species to ecological groups according to personal observations of our colleagues, I. Palko and M. Kalyakin Supplementary Table S1 , who conduct long-term observations on ecology and behavior of tropical birds in the study site. Exposed open habitat type did not always equal to feeding in the sun, as some species from exposed habitats feed in the shade of thick grass or shrub e. Migratory species only included migrants to temperate and high latitudes 54 species were residents and 12 were migrants.

All tropical breeders were categorized as residents sedentary birds , including Pitta moluccensis , which performs winter migration to the Malay Archipelago. All scaling exponents in allometric equations in our study were based on ordinary least squares OLS regressions, unless specifically mentioned. The body mass and BMR data were log 10 -transformed before analysis to account for allometric scale.

We tested the differences between observed and predicted values of BMR using a t -test predicted values were calculated using different allometric equations from Table 1. All analyses were conducted in R R Core Team Standard errors of intercepts and slopes are shown in equations in brackets.

Table 1 The average ratio of observed whole-organism BMR of tropical resident birds of different taxonomic groups from Vietnam to predicted BMR, estimated using allometric relationships between BMR and body mass from literature on corresponding groups. The average ratio of observed whole-organism BMR of tropical resident birds of different taxonomic groups from Vietnam to predicted BMR, estimated using allometric relationships between BMR and body mass from literature on corresponding groups. The phylogenetic relationships between studied species were extracted from the BirdTree.

A total of 1, trees were downloaded from BirdTree. We used phylogenetic generalized least squares model PGLS to take the phylogenetic signal into account in allometric analysis Grafen ; Freckleton et al. We did not find any phylogenetic signal in the residual variation of the regression of log BMR on log M i. We provided several phylogenetic regressions to show that regression coefficients from PGLS were very close to those that were obtained by OLS.

We found the mass exponent in the allometric relation between BMR and body mass in tropical birds to be very small Figure 1. The slope of the regression in the reduced sample was still significantly lower than 0. The relationship between BMR and body mass in tropical birds of Southern Vietnam black thick solid line. Red solid triangles indicate passerines; blue open squares indicate non-passerines. We did not find a phylogenetic signal in mass-independent BMR of tropical birds from our sample. We repeated analysis with all branches of the tree set to unity.

The differences in phylogenetic signal were negligible from the above results. The equation of the model, which took standard errors into account using Ives et al. Our results suggest that residential birds have a lower BMR than long-distance migrants on their wintering grounds in tropics. The influence of all other ecological and behavioral factors was not significant habitat, feeding in the shade or sun, diet, foraging substrate.

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To simplify the analysis, the categories of different factors were variously combined, but the adjusted R 2 increased only by 0. The relationship between BMR and body mass in resident red thick solid line, red solid triangles and migratory blue thick dashed line, blue open squares tropical birds of Southern Vietnam.

Among passerines, the BMR of long-distance migrants on their wintering grounds was intermediate between tropical and temperate residents Figure 3. We implemented some commonly used allometric equations to calculate the predicted BMR of our birds using their mean body weight Table 1. The considerable part of those equations especially the old ones were based on species from temperate areas, which allowed us to compare BMR of tropical birds with estimated BMR of temperate birds of the same body mass. Similarly, when comparing with raw data from other extensive studies on tropical birds Wiersma et al.

Wiersma et al. 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. 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 tropical species is more pronounced than in small species.

Moreover, during the lengthy rainy season they endure a very high temperature together with a very high humidity. This physiological constraint is readily apparent in some energetic models, which assume positive and proportional relationship between BMR and maximal aerobic capacity Bennett and Ruben or maximal rate of daily work output Gavrilov In the body of a large active animal, even a small portion of endogenous heat in addition to BMR may lead to overheating.

From this point of view, the gentle allometric slope may reflect the adaptive decrease of BMR in large birds, which are more vulnerable to hot conditions than small birds. That is one of the speculative explanations of the low scaling exponent in tropical birds, although we did not have data to test it. Contrary to some other studies on energetics of tropical birds Wiersma et al. We demonstrated that this trait has evolved independently of phylogeny, for example, close relatives are not more similar than distant relatives.

The different models of evolution demonstrated very close values of regression coefficients in our study, which is in agreement with special articles on this topic Jhwueng The lack of phylogenetic signal in BMR of our sample of birds may reflect their strong adaptation to constant environment in tropics: the body mass undertook the majority of BMR variation and leaved too little for the other traits, including phylogeny see below. Another reason why interspecific differences in mass-independent BMR were not predicted by phylogeny may be related to methodological problems.

One of them is possible inaccuracies in the phylogenetic tree, particularly in branch lengths. The phylogenetic regressions are also robust to errors in tree topology and branch lengths Stone The more plausible methodic cause of the lack of phylogenetic signal in BMR could be related to an insufficient sample size of different taxa. Our non-passerines were represented substantially by only Coraciiformes and Piciformes Supplementary Table S1. Of 66 species in our BMR database, 23 were represented only by 1 individual, 12 by 2 individuals, and 4 by 3 individuals.

One of the reasons why passerine birds are so widespread and numerous may be related to their high BMR in comparison with other taxa of endotherms Gavrilov , a , b , , Some studies attributed this energetic asymmetry to the phylogenetic relationships between species Reynolds and Lee ; Garland and Ives ; Rezende et al. In our study, tropical resident passerines did not show higher BMR than non-passerines. This result contradicts previous comparisons of BMR in these 2 groups of tropical birds Wiersma et al.

According to his conjecture, passerine birds had to reduce flight speed for settlement in forest habitats. Passerines of the temperate zone could not reduce speed by an increase in head resistance as tropical birds do, because it is not energetically compatible with long-distance migrations.

They used other means to reduce flight speed, namely adopting a new style of flight, which consists of the active work of wings in down-stroke only. Such flight requires more energy, and migrating passerines obtained it by increasing their metabolic capacity, which was reflected in their BMR. All these groups are also characterized by high mobility and seasonal long-distance migration. It is likely that natural selection does not act directly on BMR, but on correlated energetic traits.

Among those, the most ecologically important traits are daily energy expenditure, maximal aerobic metabolism, potential productive energy, and maximum rate of a daily locomotor activity Bennett and Ruben ; Gavrilov ; Nilsson ; White and Seymour Interspecific studies in birds generally support the aerobic capacity model [see references in Swanson et al.

He did not use phylogenetic methods in this comparison and pointed at several important aspects against the use of phylogenetic correction before factor analysis. Moreover, the PGLS analysis showed a difference in these groups in slopes as well.

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BMRs of all 4 suboscine species fell close to the general regression line. If tropical passerines had higher BMR than non-passerines, one could expect that more primitive Eurylaimides would have a lower BMR compared to oscines. Using a mixed sample of temperate and tropical birds, Swanson and Bozinovic found that oscines have higher summit metabolic rates maximum rate of thermogenesis than New World suboscines.

This result favors the hypothesis, which explains competitive superiority of oscines by their higher metabolic capacities Swanson and Bozinovic We did not find any ecological or behavioral factors to have an impact on BMR, with the exception of migratory tendency. Our data suggest that migratory passerines from temperate and high latitudes on their wintering grounds in tropics have a higher BMR than tropical residents.

This is in agreement with the results of a study comparing migrants and residents based on a global database Jetz et al. Intraspecific studies on captive-raised common stonechats Saxicola torquata also showed that BMR was lower in individuals from a sedentary tropical population than in individuals from a migratory temperate population Klaassen ; Wikelski et al. In addition, wintering passerine migrants from our study did not differ in BMR from passerine migrants on their breeding grounds in temperate and high latitudes.

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Jetz et al. But, since we measured BMR of migrants and residents at the same time and place, where representatives of both groups had been living for several months, we conclude that higher BMR of migrants could reflect the elevated maintenance costs of metabolic machinery for long-distance migration.

On the other hand, BMR of passerine migrants on their tropical wintering grounds in Vietnam was lower than that of passerine residents from temperate and high latitudes. This result suggests that migratory tendency is not the only driver of increased metabolic power. Following the notion of Jetz et al. McNab begins with an overview of thermal rates—much of our own energy is spent maintaining our F temperature—and explains how the basal rate of metabolism drives energy use, especially in extreme environments.

He then explores those variables that interact with the basal rate of metabolism, like body size and scale and environments, highlighting their influence on behavior, distribution, and even reproductive output.