Decomposition of the Leinster-Cobbold Diversity Index

TL;DR

This paper presents a method to decompose the Leinster-Cobbold diversity index into contributions from richness, evenness, and similarity, providing unbiased estimates and a new concept of taxonomic tree equilibration for community analysis.

Contribution

It introduces a novel scheme for decomposing the Leinster-Cobbold index, improving estimation accuracy and incorporating community structure via taxonomic tree equilibration.

Findings

Unbiased estimation of evenness and similarity in non-homogeneous communities

A new scheme for decomposing the Leinster-Cobbold index

Introduction of taxonomic tree equilibration concept

Abstract

The Leinster and Cobbold diversity index possesses a number of merits; in particular, it generalises many existing indices and defines an effective number. We present a scheme to quantify the contribution of richness, evenness, and taxonomic similarity to this index. Compared to the work of van Dam (2019), our approach gives unbiased estimates of both evenness and similarity in a non-homogeneous community. We also introduce a notion of taxonomic tree equilibration which should be of use in the description of community structure.