Determinants of inter-specific variation in basal metabolic rate
01 Jan 2013-Journal of Comparative Physiology B-biochemical Systemic and Environmental Physiology (Springer-Verlag)-Vol. 183, Iss: 1, pp 1-26
TL;DR: In this paper, the authors review explanations for size-related and mass-independent variation in the basal metabolic rate (BMR) of animals, and suggest ways that the various explanations can be evaluated and integrated.
Abstract: Basal metabolic rate (BMR) is the rate of metabolism of a resting, postabsorptive, non-reproductive, adult bird or mammal, measured during the inactive circadian phase at a thermoneutral temperature. BMR is one of the most widely measured physiological traits, and data are available for over 1,200 species. With data available for such a wide range of species, BMR is a benchmark measurement in ecological and evolutionary physiology, and is often used as a reference against which other levels of metabolism are compared. Implicit in such comparisons is the assumption that BMR is invariant for a given species and that it therefore represents a stable point of comparison. However, BMR shows substantial variation between individuals, populations and species. Investigation of the ultimate (evolutionary) explanations for these differences remains an active area of inquiry, and explanation of size-related trends remains a contentious area. Whereas explanations for the scaling of BMR are generally mechanistic and claim ties to the first principles of chemistry and physics, investigations of mass-independent variation typically take an evolutionary perspective and have demonstrated that BMR is ultimately linked with a range of extrinsic variables including diet, habitat temperature, and net primary productivity. Here we review explanations for size-related and mass-independent variation in the BMR of animals, and suggest ways that the various explanations can be evaluated and integrated.
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TL;DR: In this paper, the scaling law of organismal metabolic rate with organismal mass was examined, and it was shown that for mammals, a possible breakdown in scaling for larger masses reflected in a systematic increase in the metabolic rate.
Abstract: We examine the scaling law $B \propto M^{\alpha}$ which connects organismal metabolic rate $B$ with organismal mass $M$, where $\alpha$ is commonly held to be 3/4. Since simple dimensional analysis suggests $\alpha=2/3$, we consider this to be a null hypothesis testable by empirical studies. We re-analyze data sets for mammals and birds compiled by Heusner, Bennett and Harvey, Bartels, Hemmingsen, Brody, and Kleiber, and find little evidence for rejecting $\alpha=2/3$ in favor of $\alpha=3/4$. For mammals, we find a possible breakdown in scaling for larger masses reflected in a systematic increase in $\alpha$. We also review theoretical justifications of $\alpha=3/4$ based on dimensional analysis, nutrient-supply networks, and four-dimensional biology. We find that present theories for $\alpha=3/4$ require assumptions that render them unconvincing for rejecting the null hypothesis that $\alpha=2/3$.
481 citations
TL;DR: It is argued that a comprehensive understanding of the pace of life must include how biological activities depend on both energy and information and their environmentally sensitive interaction, supported by extensive evidence showing that hormones and other regulatory factors and signalling systems coordinate the processes of growth, metabolism and food intake in adaptive ways that are responsive to an organism's internal and external conditions.
Abstract: A common, long-held belief is that metabolic rate drives the rates of various biological, ecological and evolutionary processes. Although this metabolic pacemaker view (as assumed by the recent, influential 'metabolic theory of ecology') may be true in at least some situations (e.g. those involving moderate temperature effects or physiological processes closely linked to metabolism, such as heartbeat and breathing rate), it suffers from several major limitations, including: (i) it is supported chiefly by indirect, correlational evidence (e.g. similarities between the body-size and temperature scaling of metabolic rate and that of other biological processes, which are not always observed) - direct, mechanistic or experimental support is scarce and much needed; (ii) it is contradicted by abundant evidence showing that various intrinsic and extrinsic factors (e.g. hormonal action and temperature changes) can dissociate the rates of metabolism, growth, development and other biological processes; (iii) there are many examples where metabolic rate appears to respond to, rather than drive the rates of various other biological processes (e.g. ontogenetic growth, food intake and locomotor activity); (iv) there are additional examples where metabolic rate appears to be unrelated to the rate of a biological process (e.g. ageing, circadian rhythms, and molecular evolution); and (v) the theoretical foundation for the metabolic pacemaker view focuses only on the energetic control of biological processes, while ignoring the importance of informational control, as mediated by various genetic, cellular, and neuroendocrine regulatory systems. I argue that a comprehensive understanding of the pace of life must include how biological activities depend on both energy and information and their environmentally sensitive interaction. This conclusion is supported by extensive evidence showing that hormones and other regulatory factors and signalling systems coordinate the processes of growth, metabolism and food intake in adaptive ways that are responsive to an organism's internal and external conditions. Metabolic rate does not merely dictate growth rate, but is coadjusted with it. Energy and information use are intimately intertwined in living systems: biological signalling pathways both control and respond to the energetic state of an organism. This review also reveals that we have much to learn about the temporal structure of the pace of life. Are its component processes highly integrated and synchronized, or are they loosely connected and often discordant? And what causes the level of coordination that we see? These questions are of great theoretical and practical importance.
253 citations
Cites background from "Determinants of inter-specific vari..."
...…the geometry of resource-transport networks (claimed by the MTE to account for the effect of body size on metabolic rate) may develop or evolve to support, rather than dictate metabolic scaling (Darveau et al., 2002; Kozłowski & Konarzewski, 2004; Weibel & Hoppeler, 2005; White & Kearney, 2013)....
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...…2010; Vaca &White, 2010; Glazier et al., 2011; McFeeters et al., 2011; Müller et al., 2012; Ohlberger et al., 2012; Carey, Sigwart & Richards, 2013; White & Kearney, 2013), thus questioning the MTE’s assumption that the direction of causality is from metabolism to other processes, rather than the…...
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01 Jan 2014
TL;DR: This chapter provides a general historical background, with definitions and information of free radicals, antioxidants and oxidative stress and examines how mild doses of stress can have stimulatory effects on organismal performance through hormetic mechanisms and that this may significantly relate to evolutionary fitness and to the ecology of species.
Abstract: The transition from a reducing to an oxidising chemistry in the atmosphere and oceans paved the way for the diversification of life. Oxygen expanded metabolic and biochemical capacities of organisms. Over the incipient stages of evolution of oxidative metabolism, organisms also needed to develop mechanisms to mitigate the toxic effects of oxygen derivatives, such as free radicals and nonradical reactive species. This chapter provides a general historical background, with definitions and information of free radicals, antioxidants and oxidative stress. This chapter also examines how mild doses of stress can have stimulatory effects on organismal performance through hormetic mechanisms and that this may significantly relate to evolutionary fitness and to the ecology of species. Finally, the chapter explains the concept of life-history trade-offs and highlights how the need to manage oxidative stress in an optimal way may be an important mechanism driving the outcome of many of these trade-offs. 1.1 The Great Oxidation Event: From a Reducing to an Oxidising World The planet Earth is approximately 4.5 billion years old. The atmosphere of the primeval Earth was quite different from what we observe nowadays. It was mildly reducing, with large proportions of methane, ammonia and hydrogen and a low concentration of oxygen (Schopf and Klein 1992; Sessions et al. 2009). Around 2.45 billion years ago, atmospheric oxygen rose suddenly in what is now termed the Great Oxidation Event (Sessions et al. 2009). A second significant increase in atmospheric oxygen occurred at around 600–800 million years ago and was accompanied by the oxygenation of the deep oceans and emergence of multicellular animals (Sessions et al. 2009). The increase in oxygen concentration in the atmosphere and oceans paved the way for the diversification of life (Fig. 1.1). D. Costantini, Oxidative Stress and Hormesis in Evolutionary Ecology and Physiology, DOI: 10.1007/978-3-642-54663-1_1, Springer-Verlag Berlin Heidelberg 2014 1 The transition from a reducing to an oxidising atmosphere was characterised by the evolution of metabolic networks of increasing complexity (Raymond and Segrè 2006). Adaptation to molecular oxygen has also likely taken place independently in species from diverse lineages, even if it is unclear whether it contributed to shaping taxonomical diversity (Raymond and Segrè 2006). Certainly, oxygen expanded metabolic and biochemical capacities of organisms. The stimulatory effect of oxygen on the evolution of metabolic networks was not cost-free. Beyond diversification of mechanisms using oxygen to produce energy, organisms also needed to evolve mechanisms to mitigate the toxic effects of oxygen derivatives, such as free radicals and non-radical reactive species. 1.2 Reactive Species, Antioxidants and Oxidative Stress 1.2.1 On the Nature of Free Radicals and Other Reactive Species The discovery of organic free radicals dates back to over a century ago, when the scientist Gomberg (1900) at the University of Michigan identified the triphenylmethyl The primeval Earth’s atmosphere was mildly reducing. Photochemical reactions between simple gas elements 2H2 + CO2 → H2CO + H2O Evolution of anaerobic bacteria H2S + CO2 → (H2CO)n + S Evolution of photosynthetic organisms H2O + CO2 → (H2CO)n + O2 Evolution of aerobic eukaryotes; aerobic pathways produce much more energy than anaerobic pathways O2 + (H2CO)n → H2O + CO2 Aerobic pathways generate oxygen free radicals and non-radical species. Hence, evolution of antioxidant mechanisms to cope with oxidative stress. Fig. 1.1 Sequence of main transitions in energetic metabolism induced by changes in atmosphere and ocean chemistry (see Falkowski 2006) 2 1 Historical and Contemporary Issues of Oxidative Stress
229 citations
TL;DR: The aerobic capacity model of the evolution of endothermy is supported, suggesting elevated body temperatures evolved as correlated responses to selection for high activity levels and in pelagic species with higher trophic levels.
Abstract: Rates of aerobic metabolism vary considerably across evolutionary lineages, but little is known about the proximate and ultimate factors that generate and maintain this variability. Using data for 131 teleost fish species, we performed a large-scale phylogenetic comparative analysis of how interspecific variation in resting metabolic rates (RMRs) and maximum metabolic rates (MMRs) is related to several ecological and morphological variables. Mass- and temperature-adjusted RMR and MMR are highly correlated along a continuum spanning a 30- to 40-fold range. Phylogenetic generalized least squares models suggest that RMR and MMR are higher in pelagic species and that species with higher trophic levels exhibit elevated MMR. This variation is mirrored at various levels of structural organization: gill surface area, muscle protein content, and caudal fin aspect ratio (a proxy for activity) are positively related with aerobic capacity. Muscle protein content and caudal fin aspect ratio are also positively correlated with RMR. Hypoxia-tolerant lineages fall at the lower end of the metabolic continuum. Different ecological lifestyles are associated with contrasting levels of aerobic capacity, possibly reflecting the interplay between selection for increased locomotor performance on one hand and tolerance to low resource availability, particularly oxygen, on the other. These results support the aerobic capacity model of the evolution of endothermy, suggesting elevated body temperatures evolved as correlated responses to selection for high activity levels.
174 citations
Cites result from "Determinants of inter-specific vari..."
...Our findings generally agree with earlier work that shows positive interspecific relationships among RMR and MMR (e.g., Daan et al. 1990; Rezende et al. 2004; Raichlen et al. 2010; White and Kearney 2013; Wiersma et al. 2007)....
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References
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19 Jun 2013
TL;DR: The second edition of this book is unique in that it focuses on methods for making formal statistical inference from all the models in an a priori set (Multi-Model Inference).
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"Determinants of inter-specific vari..." refers background or methods in this paper
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...All models were compared on the basis of Akaike’s information criterion (AIC) as a measure of model fit (Burnham and Anderson 2001, 2002)....
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...Such ideas form the basis of information theoretic approaches to model comparison (Burnham and Anderson 2002; Johnson and Omland 2004; Hobbs and Hilborn 2006); in the case of metabolic scaling, such tests generally favour complex models over simple ones (Isaac and Carbone 2010), because the…...
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TL;DR: UNLABELLED Analysis of Phylogenetics and Evolution (APE) is a package written in the R language for use in molecular evolution and phylogenetics that provides both utility functions for reading and writing data and manipulating phylogenetic trees.
Abstract: Summary: Analysis of Phylogenetics and Evolution (APE) is a package written in the R language for use in molecular evolution and phylogenetics. APE provides both utility functions for reading and writing data and manipulating phylogenetic trees, as well as several advanced methods for phylogenetic and evolutionary analysis (e.g. comparative and population genetic methods). APE takes advantage of the many R functions for statistics and graphics, and also provides a flexible framework for developing and implementing further statistical methods for the analysis of evolutionary processes.
Availability: The program is free and available from the official R package archive at http://cran.r-project.org/src/contrib/PACKAGES.html#ape. APE is licensed under the GNU General Public License.
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"Determinants of inter-specific vari..." refers methods in this paper
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TL;DR: In this article, the authors discuss their experience designing and implementing a statistical computing language, which combines what they felt were useful features from two existing computer languages, and they feel that the new language provides advantages in the areas of portability, computational efficiency, memory management, and scope.
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9,446 citations
TL;DR: A method of correcting for the phylogeny has been proposed, which specifies a set of contrasts among species, contrasts that are statistically independent and can be used in regression or correlation studies.
Abstract: Recent years have seen a growth in numerical studies using the comparative method. The method usually involves a comparison of two phenotypes across a range of species or higher taxa, or a comparison of one phenotype with an environmental variable. Objectives of such studies vary, and include assessing whether one variable is correlated with another and assessing whether the regression of one variable on another differs significantly from some expected value. Notable recent studies using statistical methods of this type include Pilbeam and Gould's (1974) regressions of tooth area on several size measurements in mammals; Sherman's (1979) test of the relation between insect chromosome numbers and social behavior; Damuth's (1981) investigation of population density and body size in mammals; Martin's (1981) regression of brain weight in mammals on body weight; Givnish's (1982) examination of traits associated with dioecy across the families of angiosperms; and Armstrong's (1983) regressions of brain weight on body weight and basal metabolism rate in mammals. My intention is to point out a serious statistical problem with this approach, a problem that affects all of these studies. It arises from the fact that species are part of a hierarchically structured phylogeny, and thus cannot be regarded for statistical purposes as if drawn independently from the same distribution. This problem has been noticed before, and previous suggestions of ways of coping with it are briefly discussed. The nonindependence can be circumvented in principle if adequate information on the phylogeny is available. The information needed to do so and the limitations on its use will be discussed. The problem will be discussed and illustrated with reference to continuous variables, but the same statistical issues arise when one or both of the variables are discrete, in which case the statistical methods involve contingency tables rather than regressions and correlations.
8,833 citations
"Determinants of inter-specific vari..." refers methods in this paper
...When analysed using phylogenetic independent contrasts (Felsenstein 1985) the exponent of FMR for birds and mammals are 0....
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...When analysed using phylogenetic independent contrasts (Felsenstein 1985) the exponent of FMR for birds and mammals are 0.679 ± 0.032 and 0.576 ± 0.036, respectively (Speakman and Król 2010)....
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Book•
01 Jan 1996
TL;DR: This book discusses the genetic Basis of Quantitative Variation, Properties of Distributions, Covariance, Regression, and Correlation, and Properties of Single Loci, and Sources of Genetic Variation for Multilocus Traits.
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6,530 citations