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Determining the community structure of the coral Seriatopora hystrix from hydrodynamic and genetic networks

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dc.contributor Australian Institute Of Marine Science (aims) en
dc.contributor University Of Queensland
dc.contributor Univ Queensland
dc.contributor Australian Inst Marine Sci
dc.contributor Sch Integrat Biol
dc.contributor Australian Institute Of Marine Science
dc.contributor Ecol Ctr & Commonwealth Res Facil Appl Environm D
dc.contributor.author POSSINGHAM, HUGH P.
dc.contributor.author KININMONTH, STUART
dc.contributor.author VAN OPPEN, MADELEINE J. H.
dc.date.accessioned 2017-03-21T01:17:36Z
dc.date.accessioned 2017-03-21T01:17:36Z
dc.date.accessioned 2013-02-28T06:50:30Z
dc.date.accessioned 2018-11-01T03:22:38Z
dc.date.available 2013-02-28T06:50:30Z
dc.date.available 2013-02-28T06:50:30Z
dc.date.available 2017-03-21T01:17:36Z
dc.date.available 2018-11-01T03:22:38Z
dc.date.issued 2010-12-15
dc.identifier 8678 en
dc.identifier.citation Kininmonth SJ, van Oppen MJH and Possingham H (2010) Determining the community structure of the coral Seriatopora hystrix from hydrodynamic and genetic networks. Ecological Modelling. 221: 2870-2880. en
dc.identifier.issn 0304-3800
dc.identifier.uri http://epubs.aims.gov.au/11068/8678
dc.description Link to abstract/full text - http://dx.doi.org/10.1016/j.ecolmodel.2010.08.042 en
dc.description.abstract The exchange of genetic information between coral reefs through the transport of larvae can be described in terms of networks that capture the linkages between distant populations. A key question arising from these networks is the determination of the highly connected modules (communities). Communities can be defined using genetic similarity or distance statistics between multiple samples but due to limited specimen sampling capacity the boundaries of the communities for the known coral reefs in the seascape remain unresolved. In this study we use the microsatellite composition of individual corals to compare sample populations using a genetic dissimilarity measure (F-ST which is then used to create a complex network This network involved sampling 1025 colonies from 22 collection sites and examining 10 microsatellites loci. The links between each sampling site were given a strength that was created from the pair wise F-ST values. The result is an undirected weighted network describing the genetic dissimilarity between each sampled population. From this network we then determined the community structure using a leading eigenvector algorithm within graph theory. However, given the relatively limited sampling conducted, the representation of the regional genetic structure was incomplete. To assist with defining the boundaries of the genetically based communities we also integrated the communities derived from a hydrodynamic and distance based networks. The hydrodynamic network, though more comprehensive, was of smaller spatial extent than our genetic sampling. A Bayesian Belief network was developed to integrate the overlapping communities. The results indicate the genetic population structure of the Great Barrier Reef and provide guidance on where future genetic sampling should take place to complete the genetic diversity mapping. Crown Copyright (C) 2010 Published by Elsevier B.V. All rights reserved.
dc.description.uri http://dx.doi.org/10.1016/j.ecolmodel.2010.08.042 en
dc.language English
dc.language en en
dc.relation.ispartof Ecological Modelling - pages: 221: 2870-2880 en
dc.relation.ispartof Null
dc.subject Microsatellites
dc.subject Marine Reserves
dc.subject Hydrodynamics
dc.subject Ecology
dc.subject Building Corals
dc.subject Scales
dc.subject Australia
dc.subject Environmental Sciences & Ecology
dc.subject Genetic Communities
dc.subject Patterns
dc.subject Genotypic Diversity
dc.subject Population Connectivity
dc.subject Flow
dc.subject Bayesian Belief Networks
dc.subject Genetic Connectivity
dc.subject Seriatopora Hystrix
dc.subject Larval Dispersal
dc.subject Great-barrier-reef
dc.title Determining the community structure of the coral Seriatopora hystrix from hydrodynamic and genetic networks
dc.type journal article en
dc.identifier.doi 10.1016/j.ecolmodel.2010.08.042
dc.identifier.wos WOS:000284444300002


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