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

 

Show simple item record

dc.contributor.author Bradshaw, Peter L en_ZA
dc.contributor.author Colville, Jonathan F en_ZA
dc.contributor.author Linder, H Peter en_ZA
dc.date.accessioned 2016-01-02T05:07:13Z
dc.date.available 2016-01-02T05:07:13Z
dc.date.issued 2015 en_ZA
dc.identifier.citation Bradshaw, 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.0132538 en_ZA
dc.identifier.uri http://dx.doi.org/10.1371/journal.pone.0132538 en_ZA
dc.identifier.uri http://hdl.handle.net/11427/16173
dc.description.abstract 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. en_ZA
dc.language.iso eng en_ZA
dc.publisher Public Library of Science en_ZA
dc.rights This 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.uri http://creativecommons.org/licenses/by/4.0 en_ZA
dc.source PLoS One en_ZA
dc.source.uri http://journals.plos.org/plosone en_ZA
dc.subject.other Biogeography en_ZA
dc.subject.other Plants en_ZA
dc.subject.other Species delimitation en_ZA
dc.subject.other Geographic information systems en_ZA
dc.subject.other Algorithms en_ZA
dc.subject.other Charts en_ZA
dc.subject.other Permutation en_ZA
dc.subject.other Conservation science en_ZA
dc.title Optimising regionalisation techniques: identifying centres of endemism in the extraordinarily endemic-rich Cape Floristic Region en_ZA
dc.type Journal Article en_ZA
dc.rights.holder © 2015 Bradshaw et al en_ZA
uct.type.publication Research en_ZA
uct.type.resource Article en_ZA
dc.publisher.institution University of Cape Town
dc.publisher.faculty Faculty of Science en_ZA
dc.publisher.department Department of Statistical Sciences en_ZA
uct.type.filetype Text
uct.type.filetype Image
dc.identifier.apacitation Bradshaw, 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/11427/16173 en_ZA
dc.identifier.chicagocitation Bradshaw, 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/11427/16173 en_ZA
dc.identifier.vancouvercitation Bradshaw 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.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


Files in this item

This item appears in the following Collection(s)

Show simple item record

This 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. Except where otherwise noted, this item's license is described as This 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.