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Sizing Up Allometric Scaling Theory

Overview of attention for article published in PLoS Computational Biology, September 2008
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Title
Sizing Up Allometric Scaling Theory
Published in
PLoS Computational Biology, September 2008
DOI 10.1371/journal.pcbi.1000171
Pubmed ID
Authors

Van M. Savage, Eric J. Deeds, Walter Fontana

Abstract

Metabolic rate, heart rate, lifespan, and many other physiological properties vary with body mass in systematic and interrelated ways. Present empirical data suggest that these scaling relationships take the form of power laws with exponents that are simple multiples of one quarter. A compelling explanation of this observation was put forward a decade ago by West, Brown, and Enquist (WBE). Their framework elucidates the link between metabolic rate and body mass by focusing on the dynamics and structure of resource distribution networks-the cardiovascular system in the case of mammals. Within this framework the WBE model is based on eight assumptions from which it derives the well-known observed scaling exponent of 3/4. In this paper we clarify that this result only holds in the limit of infinite network size (body mass) and that the actual exponent predicted by the model depends on the sizes of the organisms being studied. Failure to clarify and to explore the nature of this approximation has led to debates about the WBE model that were at cross purposes. We compute analytical expressions for the finite-size corrections to the 3/4 exponent, resulting in a spectrum of scaling exponents as a function of absolute network size. When accounting for these corrections over a size range spanning the eight orders of magnitude observed in mammals, the WBE model predicts a scaling exponent of 0.81, seemingly at odds with data. We then proceed to study the sensitivity of the scaling exponent with respect to variations in several assumptions that underlie the WBE model, always in the context of finite-size corrections. Here too, the trends we derive from the model seem at odds with trends detectable in empirical data. Our work illustrates the utility of the WBE framework in reasoning about allometric scaling, while at the same time suggesting that the current canonical model may need amendments to bring its predictions fully in line with available datasets.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 279 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 12 4%
United Kingdom 6 2%
France 2 <1%
Portugal 2 <1%
Spain 2 <1%
Brazil 2 <1%
South Africa 1 <1%
Germany 1 <1%
Chile 1 <1%
Other 4 1%
Unknown 246 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 62 22%
Researcher 62 22%
Professor 29 10%
Student > Master 20 7%
Professor > Associate Professor 18 6%
Other 60 22%
Unknown 28 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 98 35%
Environmental Science 22 8%
Medicine and Dentistry 21 8%
Physics and Astronomy 17 6%
Engineering 17 6%
Other 63 23%
Unknown 41 15%