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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...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2010
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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. |
format | Text |
id | pubmed-2898690 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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