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13 - The consequences of body size in model microbial ecosystems

Published online by Cambridge University Press:  02 December 2009

Owen L. Petchey
Affiliation:
University of Sheffield
Zachary T. Long
Affiliation:
University of North Carolina at Chapel Hill; Virginia Institute of Marine Science
Peter J. Morin
Affiliation:
Rutgers University
Alan G. Hildrew
Affiliation:
Queen Mary University of London
David G. Raffaelli
Affiliation:
University of York
Ronni Edmonds-Brown
Affiliation:
University of Hertfordshire
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Summary

Introduction

Patterns in the sizes of coexisting organisms have always intrigued ecologists (Hutchinson, 1961). Some kinds of regularities are well known for some systems (Sheldon, Prakash & Sutcliffe, 1972), and are less appreciated or rediscovered for others (Enquist & Niklas, 2001; Cohen, Jonsson & Carpenter, 2003). One example of this kind of pattern is the apparent constancy of total biomass within different size fractions of organisms living in aquatic communities (Sheldon, et al. 1972; Cyr, 2000; Kerr & Dickie, 2001; Cohen et al., 2003; Sheldon, Sutcliffe & Paranjape, 1977; Tilman et al., 2001; Mulder et al., 2005). Essentially, over many orders of magnitude of organism size, any particular size class holds about the same total biomass of organisms per unit volume. The result is an inverse relationship between the log of organism size and the log of organism abundance per unit volume, with a slope of − 1. The apparent constancy of this relationship has even led some workers to suggest, tongue in cheek, that it could be used to estimate the population size of some organisms that have proven to be notoriously difficult to observe, once assumptions about their average size were made (Sheldon & Kerr, 1972, 1973). Whether or not the elusive Loch Ness Monster (to which these calculations were rather whimsically applied) actually exists, it appears that the total biomass of organisms in some habitats is fixed by certain features of the habitat, most likely the abundance of incoming energy and nutrients that drive productivity (Sheldon et al., 1977; Cyr, 2000; Kerr & Dickie, 2001; Cohen et al., 2003; Mulder et al., 2005).

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Publisher: Cambridge University Press
Print publication year: 2007

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