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Letters to Nature
Nature 432, 747-750 (9 December 2004) | doi:10.1038/nature03034; Received 10 August 2004; Accepted 14 September 2004
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Spatial scaling of microbial eukaryote diversity
Jessica L. Green1,4, Andrew J. Holmes2, Mark Westoby1, Ian Oliver3, David Briscoe1, Mark Dangerfield1, Michael Gillings1 & Andrew J. Beattie1
- Key Centre for Biodiversity and Bioresources, Department of Biological Sciences, Macquarie University, New South Wales 2109, Australia
- School of Molecular and Microbial Biosciences, The University of Sydney, New South Wales 2006, Australia
- New South Wales Department of Infrastructure, Planning and Natural Resources, P.O. Box U245, University of New England, Armidale, New South Wales 2351, Australia
- Present address: School of Natural Sciences, University of California, Merced, P.O. Box 2039, Merced, California 95344, USA
Correspondence to: Jessica L. Green1,4 Email: jgreen@ucmerced.edu
Abstract
Patterns in the spatial distribution of organisms provide important information about mechanisms that regulate the diversity of life and the complexity of ecosystems1, 2. Although microorganisms may comprise much of the Earth's biodiversity3, 4 and have critical roles in biogeochemistry and ecosystem functioning5, 6, 7, little is known about their spatial diversification. Here we present quantitative estimates of microbial community turnover at local and regional scales using the largest spatially explicit microbial diversity data set available (> 106 sample pairs). Turnover rates were small across large geographical distances, of similar magnitude when measured within distinct habitats, and did not increase going from one vegetation type to another. The taxa–area relationship of these terrestrial microbial eukaryotes was relatively flat (slope z = 0.074) and consistent with those reported in aquatic habitats8, 9. This suggests that despite high local diversity, microorganisms may have only moderate regional diversity. We show how turnover patterns can be used to project taxa–area relationships up to whole continents. Taxa dissimilarities across continents and between them would strengthen these projections. Such data do not yet exist, but would be feasible to collect.
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