Optimising regionalisation techniques: identifying centres of endemism in the extraordinarily endemic-rich Cape Floristic Region

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dc.contributor.authorBradshaw, Peter Len_ZA
dc.contributor.authorColville, Jonathan Fen_ZA
dc.contributor.authorLinder, H Peteren_ZA
dc.date.accessioned2016-01-02T05:07:13Z
dc.date.available2016-01-02T05:07:13Z
dc.date.issued2015en_ZA
dc.description.abstractWe used a very large dataset (>40% of all species) from the endemic-rich Cape Floristic Region (CFR) to explore the impact of different weighting techniques, coefficients to calculate similarity among the cells, and clustering approaches on biogeographical regionalisation. The results were used to revise the biogeographical subdivision of the CFR. We show that weighted data (down-weighting widespread species), similarity calculated using Kulczinsky's second measure, and clustering using UPGMA resulted in the optimal classification. This maximized the number of endemic species, the number of centres recognized, and operational geographic units assigned to centres of endemism (CoEs). We developed a dendrogram branch order cut-off (BOC) method to locate the optimal cut-off points on the dendrogram to define candidate clusters. Kulczinsky's second measure dendrograms were combined using consensus, identifying areas of conflict which could be due to biotic element overlap or transitional areas. Post-clustering GIS manipulation substantially enhanced the endemic composition and geographic size of candidate CoEs. Although there was broad spatial congruence with previous phytogeographic studies, our techniques allowed for the recovery of additional phytogeographic detail not previously described for the CFR.en_ZA
dc.identifier.apacitationBradshaw, P. L., Colville, J. F., & Linder, H. P. (2015). Optimising regionalisation techniques: identifying centres of endemism in the extraordinarily endemic-rich Cape Floristic Region. <i>PLoS One</i>, http://hdl.handle.net/11427/16173en_ZA
dc.identifier.chicagocitationBradshaw, Peter L, Jonathan F Colville, and H Peter Linder "Optimising regionalisation techniques: identifying centres of endemism in the extraordinarily endemic-rich Cape Floristic Region." <i>PLoS One</i> (2015) http://hdl.handle.net/11427/16173en_ZA
dc.identifier.citationBradshaw, P. L., Colville, J. F., & Linder, H. P. (2015). Optimising regionalisation techniques: identifying centres of endemism in the extraordinarily endemic-rich Cape Floristic Region. PloS one, 10(7), e0132538. doi:10.1371/journal.pone.0132538en_ZA
dc.identifier.ris TY - Journal Article AU - Bradshaw, Peter L AU - Colville, Jonathan F AU - Linder, H Peter AB - We used a very large dataset (>40% of all species) from the endemic-rich Cape Floristic Region (CFR) to explore the impact of different weighting techniques, coefficients to calculate similarity among the cells, and clustering approaches on biogeographical regionalisation. The results were used to revise the biogeographical subdivision of the CFR. We show that weighted data (down-weighting widespread species), similarity calculated using Kulczinsky's second measure, and clustering using UPGMA resulted in the optimal classification. This maximized the number of endemic species, the number of centres recognized, and operational geographic units assigned to centres of endemism (CoEs). We developed a dendrogram branch order cut-off (BOC) method to locate the optimal cut-off points on the dendrogram to define candidate clusters. Kulczinsky's second measure dendrograms were combined using consensus, identifying areas of conflict which could be due to biotic element overlap or transitional areas. Post-clustering GIS manipulation substantially enhanced the endemic composition and geographic size of candidate CoEs. Although there was broad spatial congruence with previous phytogeographic studies, our techniques allowed for the recovery of additional phytogeographic detail not previously described for the CFR. DA - 2015 DB - OpenUCT DO - 10.1371/journal.pone.0132538 DP - University of Cape Town J1 - PLoS One LK - https://open.uct.ac.za PB - University of Cape Town PY - 2015 T1 - Optimising regionalisation techniques: identifying centres of endemism in the extraordinarily endemic-rich Cape Floristic Region TI - Optimising regionalisation techniques: identifying centres of endemism in the extraordinarily endemic-rich Cape Floristic Region UR - http://hdl.handle.net/11427/16173 ER - en_ZA
dc.identifier.urihttp://dx.doi.org/10.1371/journal.pone.0132538en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/16173
dc.identifier.vancouvercitationBradshaw PL, Colville JF, Linder HP. Optimising regionalisation techniques: identifying centres of endemism in the extraordinarily endemic-rich Cape Floristic Region. PLoS One. 2015; http://hdl.handle.net/11427/16173.en_ZA
dc.language.isoengen_ZA
dc.publisherPublic Library of Scienceen_ZA
dc.publisher.departmentDepartment of Statistical Sciencesen_ZA
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.rightsThis is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en_ZA
dc.rights.holder© 2015 Bradshaw et alen_ZA
dc.rights.urihttp://creativecommons.org/licenses/by/4.0en_ZA
dc.sourcePLoS Oneen_ZA
dc.source.urihttp://journals.plos.org/plosoneen_ZA
dc.subject.otherBiogeographyen_ZA
dc.subject.otherPlantsen_ZA
dc.subject.otherSpecies delimitationen_ZA
dc.subject.otherGeographic information systemsen_ZA
dc.subject.otherAlgorithmsen_ZA
dc.subject.otherChartsen_ZA
dc.subject.otherPermutationen_ZA
dc.subject.otherConservation scienceen_ZA
dc.titleOptimising regionalisation techniques: identifying centres of endemism in the extraordinarily endemic-rich Cape Floristic Regionen_ZA
dc.typeJournal Articleen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceArticleen_ZA
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