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Quantifying the Evolution of Early Life pp 23–48Cite as

Exploratory Multivariate Techniques and Their Utility for Understanding Ancient Ecosystems

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Part of the book series: Topics in Geobiology ((TGBI,volume 36))

Abstract

Elucidating the ecology and evolution of the early biosphere is a critical area of research in geobiology. Indeed, the number of described species and data sets from early ecosystems has increased rapidly in the last few decades. Such datasets lend themselves well to more complex multivariate analyses. The purpose of this contribution is to serve as a primer for commonly used multivariate ordinations. I review data characterization, as it is critical to selecting the proper ordination. Then I discuss principal components analysis, principal coordinates analysis, non-metric multidimensional scaling, detrended correspondence analysis, and canonical variate analysis. For each ordination I discuss the purpose of the procedure, how it manipulates the data, which types of data are appropriate, and examples of how these procedures have been used to better understand the ecology and evolution of ancient life.

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Author information

Authors and Affiliations

  1. GeoZentrum Nordbayern, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Bavaria, Germany

    John Warren Huntley

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  1. John Warren Huntley
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Correspondence to John Warren Huntley .

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Editors and Affiliations

  1. , Smithsonian Postdoctoral Fellow, Departm, Smithsonian Institution, National Museum, Washington, 20013-7012, Washington, USA

    Marc Laflamme

  2. , Department of Geosciences, Virginia Polytechnic Institute, Derring Hall 4044, Blacksburg, 24061, Virginia, USA

    James D. Schiffbauer

  3. , Department of Geosciences, University of Wisconsin-Milwaukee, Milwaukee, 53201-0413, Wisconsin, USA

    Stephen Q. Dornbos

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Huntley, J.W. (2011). Exploratory Multivariate Techniques and Their Utility for Understanding Ancient Ecosystems. In: Laflamme, M., Schiffbauer, J., Dornbos, S. (eds) Quantifying the Evolution of Early Life. Topics in Geobiology, vol 36. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0680-4_2

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