A mathematical investigation of Rao diversity coefficients among the communities according to species morphometry and species taxonomy

Kenneth Barroga

International Journal of Mathematics in Operational Research, 2018, vol. 12, issue 4, 542-564

Abstract: Although Rao diversity coefficient (Rao DIVC) is sensitive to the differences among species, a gap still remains in investigating how the communities are affected when the dissimilarity among the species are in terms of its morphometry and taxonomy. I studied the effect of using species taxonomic classification and species morphometrical traits in the computation of Rao DIVC in assessing diversity of ecological communities. I utlised the Mahalanobis distance for measuring the variation of species morphometry. As for species taxonomy, I employed the method by Warwick and Clarke (1995). When the calculated Rao DIVCs, double principal coordinate analysis and co-inertia analysis outputs were compared, I discovered that Rao DIVCs accounting species morphometry (R_sm) and species taxonomy (R_st) yielded different results and interpretation. R_sm clearly showed more the variation among communities but contributed less in the analysis, whereas R_st showed more clearly the clusters between the communities which make the interpretation easier.

Keywords: double principal coordinate analysis; DPCoA; Mahalanobis distance; Rao diversity coefficient; Rao DIVC; co-inertia analysis; COIA. (search for similar items in EconPapers)
Date: 2018
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