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Algorithmic approaches to aid species' delimitation in multidimensional morphospace

BACKGROUND: The species is a fundamental unit of biological pattern and process, but its delimitation has proven a ready source of argument and disagreement. Here, we discuss four key steps that utilize statistical thresholds to describe the morphological variability within a sample and hence assess...

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Autores principales: Ezard, Thomas HG, Pearson, Paul N, Purvis, Andy
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2898690/
https://www.ncbi.nlm.nih.gov/pubmed/20540735
http://dx.doi.org/10.1186/1471-2148-10-175
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author Ezard, Thomas HG
Pearson, Paul N
Purvis, Andy
author_facet Ezard, Thomas HG
Pearson, Paul N
Purvis, Andy
author_sort Ezard, Thomas HG
collection PubMed
description BACKGROUND: The species is a fundamental unit of biological pattern and process, but its delimitation has proven a ready source of argument and disagreement. Here, we discuss four key steps that utilize statistical thresholds to describe the morphological variability within a sample and hence assess whether there is evidence for one or multiple species. Once the initial set of biologically relevant traits on comparable individuals has been identified, there is no need for the investigator to hypothesise how specimens might be divided among groups, nor the traits on which groups might be separated. RESULTS: Principal components are obtained using robust covariance estimates and retained only if they exceed threshold amounts of explanatory power, before model-based clustering is performed on the dimension-reduced space. We apply these steps in an attempt to resolve ongoing debates among taxonomists working on the extinct Eocene planktonic foraminifera Turborotalia, providing statistical evidence for two species shortly before the lineage's extinction near the Eocene/Oligocene boundary. CONCLUSION: By estimating variance robustly (samples containing incipient species are unlikely to be scaled optimally by means and standard deviations) and identifying thresholds relevant to a particular system rather than universal standards, the steps of the framework aim to optimize the chances of delineation without imposing pre-conceived patterns onto estimates of species limits.
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spelling pubmed-28986902010-07-08 Algorithmic approaches to aid species' delimitation in multidimensional morphospace Ezard, Thomas HG Pearson, Paul N Purvis, Andy BMC Evol Biol Methodology article BACKGROUND: The species is a fundamental unit of biological pattern and process, but its delimitation has proven a ready source of argument and disagreement. Here, we discuss four key steps that utilize statistical thresholds to describe the morphological variability within a sample and hence assess whether there is evidence for one or multiple species. Once the initial set of biologically relevant traits on comparable individuals has been identified, there is no need for the investigator to hypothesise how specimens might be divided among groups, nor the traits on which groups might be separated. RESULTS: Principal components are obtained using robust covariance estimates and retained only if they exceed threshold amounts of explanatory power, before model-based clustering is performed on the dimension-reduced space. We apply these steps in an attempt to resolve ongoing debates among taxonomists working on the extinct Eocene planktonic foraminifera Turborotalia, providing statistical evidence for two species shortly before the lineage's extinction near the Eocene/Oligocene boundary. CONCLUSION: By estimating variance robustly (samples containing incipient species are unlikely to be scaled optimally by means and standard deviations) and identifying thresholds relevant to a particular system rather than universal standards, the steps of the framework aim to optimize the chances of delineation without imposing pre-conceived patterns onto estimates of species limits. BioMed Central 2010-06-11 /pmc/articles/PMC2898690/ /pubmed/20540735 http://dx.doi.org/10.1186/1471-2148-10-175 Text en Copyright ©2010 Ezard et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology article
Ezard, Thomas HG
Pearson, Paul N
Purvis, Andy
Algorithmic approaches to aid species' delimitation in multidimensional morphospace
title Algorithmic approaches to aid species' delimitation in multidimensional morphospace
title_full Algorithmic approaches to aid species' delimitation in multidimensional morphospace
title_fullStr Algorithmic approaches to aid species' delimitation in multidimensional morphospace
title_full_unstemmed Algorithmic approaches to aid species' delimitation in multidimensional morphospace
title_short Algorithmic approaches to aid species' delimitation in multidimensional morphospace
title_sort algorithmic approaches to aid species' delimitation in multidimensional morphospace
topic Methodology article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2898690/
https://www.ncbi.nlm.nih.gov/pubmed/20540735
http://dx.doi.org/10.1186/1471-2148-10-175
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