Assessing tree species diversity in forest ecosystems: A new approach

Abstract

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The significance of biodiversity research is to understand the structure and function of the community, and then to protect and monitor the community. The metric of biodiversity is the base of biodiversity conservation. Species richness and evenness are the most common descriptors of biodiversity. Whether it is diversity information measure, probability measure or geometric measure, they all express the combination of species richness and evenness in different ways. This study presents a new biologically meaningful measure of species diversity, which evaluates species richness and evenness independently, designated as DRE. The novelty of our method is to use “absolute discrepancy” to express the dissimilarity between the observed community and the uniform distribution community with the same species composition and same abundance of each species, and then measure the species evenness. The logarithmic transformation of the species number is used to measure species richness with values ranging between 0 and 1. We test the performance of this measure using simulated data and observations of natural and planted forests in different climatic zones. The results showed that the new diversity index (DRE) has superior statistical qualities compared with the traditional indices. Especially, in extremely uneven communities, the new measure describes the causes of diversity changes than the traditional DRE. In addition, DRE is more sensitive to the abundance changes of rare species in the simulated community, and the interpretation of the results is more intuitive and meaningful. It is an improved method to evaluate the species diversity of any ecosystem.

Keywords

• absolute discrepancy
• logarithmic transformation
• normalization
• relative abundances
• species diversity
• species evenness