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.
Park Planning and Development Unit, South African National Parks, Port Elizabeth, South Africa;Department of Botany, Nelson Mandela Metropolitan University, Port Elizabeth, South Africa;Kirstenbosch Research Centre, South African National Biodiversity Institute, Private Bag X7, Claremont, Cape Town, South Africa;Statistics in Ecology, Environment and Conservation, Department of Statistical Sciences, University of Cape Town, Rondebosch, South Africa;Institute of Systematic Botany, University of Zurich, Zollikerstrasse 107, Zurich, Switzerland
Recommended Citation:
Peter L. Bradshaw,Jonathan F. Colville,H. Peter Linder. Optimising Regionalisation Techniques: Identifying Centres of Endemism in the Extraordinarily Endemic-Rich Cape Floristic Region[J]. PLOS ONE,2015-01-01,10(7)