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Diversity from genes to ecosystems: a unifying framework to study variation across biological metrics and scales

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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; Selkoe, Kimberly.

In: Evolutionary Applications, Vol. 11, No. 7, 01.08.2018, p. 1176-1193.

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Gaggiotti, OE, Chao, A, Peres-Neto, P, Chiu, C-H, Edwards, C, Fortin, M-J, Jost, L, Richards, C & Selkoe, K 2018, 'Diversity from genes to ecosystems: a unifying framework to study variation across biological metrics and scales' Evolutionary Applications, vol. 11, no. 7, pp. 1176-1193. https://doi.org/10.1111/eva.12593

APA

Gaggiotti, O. E., Chao, A., Peres-Neto, P., Chiu, C-H., Edwards, C., Fortin, M-J., ... Selkoe, K. (2018). Diversity from genes to ecosystems: a unifying framework to study variation across biological metrics and scales. Evolutionary Applications, 11(7), 1176-1193. https://doi.org/10.1111/eva.12593

Vancouver

Gaggiotti OE, Chao A, Peres-Neto P, Chiu C-H, Edwards C, Fortin M-J et al. Diversity from genes to ecosystems: a unifying framework to study variation across biological metrics and scales. Evolutionary Applications. 2018 Aug 1;11(7):1176-1193. https://doi.org/10.1111/eva.12593

Author

Gaggiotti, Oscar E. ; Chao, Anne ; Peres-Neto, Pedro ; Chiu, Chun-Huo ; Edwards, Christine ; Fortin, Marie-Josée ; Jost, Lou ; Richards, Christopher ; Selkoe, Kimberly. / Diversity from genes to ecosystems : a unifying framework to study variation across biological metrics and scales. In: Evolutionary Applications. 2018 ; Vol. 11, No. 7. pp. 1176-1193.

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@article{1604e728172449498ff5b04994e35ccc,
title = "Diversity from genes to ecosystems: a unifying framework to study variation across biological metrics and scales",
abstract = "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 organisation (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 organisation. 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 dataset on coral reef biodiversity. We expect our framework will have multiple applications covering the fields of conservation biology, community genetics, and eco-evolutionary dynamics.",
keywords = "Biodiversity indices, Hill numbers, Species diversity, Genetic diversity, Hierarchical spatial structure",
author = "Gaggiotti, {Oscar E.} and Anne Chao and Pedro Peres-Neto and Chun-Huo Chiu and Christine Edwards and Marie-Jos{\'e}e Fortin and Lou Jost and Christopher Richards and Kimberly Selkoe",
note = "This work was assisted through participation in “Next Generation Genetic Monitoring” Investigative Workshop at the National Institute for Mathematical and Biological Synthesis, sponsored by the National Science Foundation through NSF Award #DBI-1300426, with additional support from The University of Tennessee, Knoxville. Hawaiian fish community data were provided by the NOAA Pacific Islands Fisheries Science Center's Coral Reef Ecosystem Division (CRED) with funding from NOAA Coral Reef Conservation Program. O.E.G. was supported by the Marine Alliance for Science and Technology for Scotland (MASTS). A. C. and C. H. C. were supported by the Ministry of Science and Technology, Taiwan. P.P.-N. was supported by a Canada Research Chair in Spatial Modelling and Biodiversity. K.A.S. was supported by National Science Foundation (BioOCE Award Number 1260169) and the National Center for Ecological Analysis and Synthesis. All data used in this manuscript are available in DRYAD (https://doi.org/dx.doi.org/10.5061/dryad.qm288) and BCO-DMO (http://www.bco-dmo.org/project/552879).",
year = "2018",
month = "8",
day = "1",
doi = "10.1111/eva.12593",
language = "English",
volume = "11",
pages = "1176--1193",
journal = "Evolutionary Applications",
issn = "1752-4571",
publisher = "Wiley-Blackwell",
number = "7",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Diversity from genes to ecosystems

T2 - Evolutionary Applications

AU - Gaggiotti, Oscar E.

AU - Chao, Anne

AU - Peres-Neto, Pedro

AU - Chiu, Chun-Huo

AU - Edwards, Christine

AU - Fortin, Marie-Josée

AU - Jost, Lou

AU - Richards, Christopher

AU - Selkoe, Kimberly

N1 - This work was assisted through participation in “Next Generation Genetic Monitoring” Investigative Workshop at the National Institute for Mathematical and Biological Synthesis, sponsored by the National Science Foundation through NSF Award #DBI-1300426, with additional support from The University of Tennessee, Knoxville. Hawaiian fish community data were provided by the NOAA Pacific Islands Fisheries Science Center's Coral Reef Ecosystem Division (CRED) with funding from NOAA Coral Reef Conservation Program. O.E.G. was supported by the Marine Alliance for Science and Technology for Scotland (MASTS). A. C. and C. H. C. were supported by the Ministry of Science and Technology, Taiwan. P.P.-N. was supported by a Canada Research Chair in Spatial Modelling and Biodiversity. K.A.S. was supported by National Science Foundation (BioOCE Award Number 1260169) and the National Center for Ecological Analysis and Synthesis. All data used in this manuscript are available in DRYAD (https://doi.org/dx.doi.org/10.5061/dryad.qm288) and BCO-DMO (http://www.bco-dmo.org/project/552879).

PY - 2018/8/1

Y1 - 2018/8/1

N2 - 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 organisation (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 organisation. 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 dataset on coral reef biodiversity. We expect our framework will have multiple applications covering the fields of conservation biology, community genetics, and eco-evolutionary dynamics.

AB - 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 organisation (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 organisation. 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 dataset on coral reef biodiversity. We expect our framework will have multiple applications covering the fields of conservation biology, community genetics, and eco-evolutionary dynamics.

KW - Biodiversity indices

KW - Hill numbers

KW - Species diversity

KW - Genetic diversity

KW - Hierarchical spatial structure

U2 - 10.1111/eva.12593

DO - 10.1111/eva.12593

M3 - Article

VL - 11

SP - 1176

EP - 1193

JO - Evolutionary Applications

JF - Evolutionary Applications

SN - 1752-4571

IS - 7

ER -

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