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dc.contributor.authorGaggiotti, Oscar E.
dc.contributor.authorChao, Anne
dc.contributor.authorPeres-Neto, Pedro
dc.contributor.authorChiu, Chun-Huo
dc.contributor.authorEdwards, Christine
dc.contributor.authorFortin, Marie-Josée
dc.contributor.authorJost, Lou
dc.contributor.authorRichards, Christopher
dc.contributor.authorSelkoe, Kimberly
dc.date.accessioned2018-02-20T09:30:06Z
dc.date.available2018-02-20T09:30:06Z
dc.date.issued2018-07-17
dc.identifier.citationGaggiotti , O E , 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.12593en
dc.identifier.issn1752-4563
dc.identifier.otherPURE: 251827373
dc.identifier.otherPURE UUID: 1604e728-1724-4949-8ff5-b04994e35ccc
dc.identifier.otherScopus: 85042157403
dc.identifier.otherWOS: 000439505200011
dc.identifier.otherORCID: /0000-0003-1827-1493/work/61370124
dc.identifier.urihttp://hdl.handle.net/10023/12756
dc.descriptionThis 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).en
dc.description.abstractBiological 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.
dc.format.extent18
dc.language.isoeng
dc.relation.ispartofEvolutionary Applicationsen
dc.rights© 2018 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.en
dc.subjectBiodiversity indicesen
dc.subjectHill numbersen
dc.subjectSpecies diversityen
dc.subjectGenetic diversityen
dc.subjectHierarchical spatial structureen
dc.subjectGE Environmental Sciencesen
dc.subjectQH301 Biologyen
dc.subjectQH426 Geneticsen
dc.subjectDASen
dc.subjectBDCen
dc.subject.lccGEen
dc.subject.lccQH301en
dc.subject.lccQH426en
dc.titleDiversity from genes to ecosystems : a unifying framework to study variation across biological metrics and scalesen
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews.School of Biologyen
dc.contributor.institutionUniversity of St Andrews.Marine Alliance for Science & Technology Scotlanden
dc.contributor.institutionUniversity of St Andrews.Scottish Oceans Instituteen
dc.identifier.doihttps://doi.org/10.1111/eva.12593
dc.description.statusPeer revieweden
dc.date.embargoedUntil2018-02-20


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