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Diversity from genes to ecosystems: A unifying framework to study variation across biological metrics and scales
Biological diversity is a key concept in the life sciences and plays a fundamental role in many ecological and evolutionary processes. Although biodiversity is inherently a hierarchical concept covering different levels of organization (genes, population, species, ecological communities and ecosyste...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6050189/ https://www.ncbi.nlm.nih.gov/pubmed/30026805 http://dx.doi.org/10.1111/eva.12593 |
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author | Gaggiotti, Oscar E. Chao, Anne Peres‐Neto, Pedro Chiu, Chun‐Huo Edwards, Christine Fortin, Marie‐Josée Jost, Lou Richards, Christopher M. Selkoe, Kimberly A. |
author_facet | Gaggiotti, Oscar E. Chao, Anne Peres‐Neto, Pedro Chiu, Chun‐Huo Edwards, Christine Fortin, Marie‐Josée Jost, Lou Richards, Christopher M. Selkoe, Kimberly A. |
author_sort | Gaggiotti, Oscar E. |
collection | PubMed |
description | Biological diversity is a key concept in the life sciences and plays a fundamental role in many ecological and evolutionary processes. Although biodiversity is inherently a hierarchical concept covering different levels of organization (genes, population, species, ecological communities and ecosystems), a diversity index that behaves consistently across these different levels has so far been lacking, hindering the development of truly integrative biodiversity studies. To fill this important knowledge gap, we present a unifying framework for the measurement of biodiversity across hierarchical levels of organization. Our weighted, information‐based decomposition framework is based on a Hill number of order q = 1, which weights all elements in proportion to their frequency and leads to diversity measures based on Shannon's entropy. We investigated the numerical behaviour of our approach with simulations and showed that it can accurately describe complex spatial hierarchical structures. To demonstrate the intuitive and straightforward interpretation of our diversity measures in terms of effective number of components (alleles, species, etc.), we applied the framework to a real data set on coral reef biodiversity. We expect our framework will have multiple applications covering the fields of conservation biology, community genetics and eco‐evolutionary dynamics. |
format | Online Article Text |
id | pubmed-6050189 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-60501892018-07-19 Diversity from genes to ecosystems: A unifying framework to study variation across biological metrics and scales Gaggiotti, Oscar E. Chao, Anne Peres‐Neto, Pedro Chiu, Chun‐Huo Edwards, Christine Fortin, Marie‐Josée Jost, Lou Richards, Christopher M. Selkoe, Kimberly A. Evol Appl Original Articles Biological diversity is a key concept in the life sciences and plays a fundamental role in many ecological and evolutionary processes. Although biodiversity is inherently a hierarchical concept covering different levels of organization (genes, population, species, ecological communities and ecosystems), a diversity index that behaves consistently across these different levels has so far been lacking, hindering the development of truly integrative biodiversity studies. To fill this important knowledge gap, we present a unifying framework for the measurement of biodiversity across hierarchical levels of organization. Our weighted, information‐based decomposition framework is based on a Hill number of order q = 1, which weights all elements in proportion to their frequency and leads to diversity measures based on Shannon's entropy. We investigated the numerical behaviour of our approach with simulations and showed that it can accurately describe complex spatial hierarchical structures. To demonstrate the intuitive and straightforward interpretation of our diversity measures in terms of effective number of components (alleles, species, etc.), we applied the framework to a real data set on coral reef biodiversity. We expect our framework will have multiple applications covering the fields of conservation biology, community genetics and eco‐evolutionary dynamics. John Wiley and Sons Inc. 2018-02-20 /pmc/articles/PMC6050189/ /pubmed/30026805 http://dx.doi.org/10.1111/eva.12593 Text en © 2018 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Articles Gaggiotti, Oscar E. Chao, Anne Peres‐Neto, Pedro Chiu, Chun‐Huo Edwards, Christine Fortin, Marie‐Josée Jost, Lou Richards, Christopher M. Selkoe, Kimberly A. Diversity from genes to ecosystems: A unifying framework to study variation across biological metrics and scales |
title | Diversity from genes to ecosystems: A unifying framework to study variation across biological metrics and scales |
title_full | Diversity from genes to ecosystems: A unifying framework to study variation across biological metrics and scales |
title_fullStr | Diversity from genes to ecosystems: A unifying framework to study variation across biological metrics and scales |
title_full_unstemmed | Diversity from genes to ecosystems: A unifying framework to study variation across biological metrics and scales |
title_short | Diversity from genes to ecosystems: A unifying framework to study variation across biological metrics and scales |
title_sort | diversity from genes to ecosystems: a unifying framework to study variation across biological metrics and scales |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6050189/ https://www.ncbi.nlm.nih.gov/pubmed/30026805 http://dx.doi.org/10.1111/eva.12593 |
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