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The use of MSR (Minimum Sample Richness) for sample assemblage comparisons

Published online by Cambridge University Press:  08 April 2016

Kenny J. Travouillon ,
Gilles Escarguel ,
Serge Legendre ,
Michael Archer  and
Suzanne J. Hand
Kenny J. Travouillon
Affiliation:
Laboratoire de Géologie de Lyon: Terre, Planètes, Environnement UMR 5276 CNRS/Université Lyon, 1/ENS-Lyon; Université Claude Bernard Lyon 1, 27-43 Boulevard du 11 Novembre 1918, F-69622 Villeurbanne Cedex, France School of Biological, Earth and Environmental Sciences, University of New South Wales, New South Wales 2052, Australia. E-mail: kennytravouillon@hotmail.com
Gilles Escarguel
Affiliation:
Laboratoire de Géologie de Lyon: Terre, Planètes, Environnement UMR 5276 CNRS/Université Lyon, 1/ENS-Lyon; Université Claude Bernard Lyon 1, 27-43 Boulevard du 11 Novembre 1918, F-69622 Villeurbanne Cedex, France
Serge Legendre
Affiliation:
Laboratoire de Géologie de Lyon: Terre, Planètes, Environnement UMR 5276 CNRS/Université Lyon, 1/ENS-Lyon; Université Claude Bernard Lyon 1, 27-43 Boulevard du 11 Novembre 1918, F-69622 Villeurbanne Cedex, France
Michael Archer
Affiliation:
School of Biological, Earth and Environmental Sciences, University of New South Wales, New South Wales 2052, Australia
Suzanne J. Hand
Affiliation:
School of Biological, Earth and Environmental Sciences, University of New South Wales, New South Wales 2052, Australia
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Abstract

Minimum Sample Richness (MSR) is defined as the smallest number of taxa that must be recorded in a sample to achieve a given level of inter-assemblage classification accuracy. MSR is calculated from known or estimated richness and taxonomic similarity. Here we test MSR for strengths and weaknesses by using 167 published mammalian local faunas from the Paleogene and early Neogene of the Quercy and Limagne area (Massif Central, southwestern France), and then apply MSR to 84 Oligo-Miocene faunas from Riversleigh, northwestern Queensland, Australia. In many cases, MSR is able to detect the assemblages in the data set that are potentially too incomplete to be used in a similarity-based comparative taxonomic analysis. The results show that the use of MSR significantly improves the quality of the clustering of fossil assemblages. We conclude that this method can screen sample assemblages that are not representative of their underlying original living communities. Ultimately, it can be used to identify which assemblages require further sampling before being included in a comparative analysis.

Type
Articles
Information
Paleobiology , Volume 37 , Issue 4 , Fall 2011 , pp. 696 - 709
Copyright
Copyright © The Paleontological Society 

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