CONSERVATION & BIODIVERSITY - Biodiversity in ecosystems

Three metrics of species diversity -species richness, the Shannon index and the Simpson index -are still widely used in ecology, despite decades of valid critiques leveled against them. Developing a robust diversity metric has been challenging because, unlike many variables ecologists measure, the diversity of a community often cannot be estimated in an unbiased way based on a random sample from that community. Over the past decade, ecologists have begun to incorporate two important tools for estimating diversity: coverage and Hill diversity. Coverage is a method for equalizing samples that is, on theoretical grounds, preferable to other commonly used methods such as equal-effort sampling, or rarefying datasets to equal sample size. Hill diversity comprises a spectrum of diversity metrics and is based on three key insights. First, species richness and variants of the Shannon and Simpson indices are all special cases of one general equation. Second, richness, Shannon and Simpson can be expressed on the same scale and in units of species. Third, there is no way to eliminate the effect of relative abundance from estimates of any of these diversity metrics, including species richness. Rather, a researcher must choose the relative sensitivity of the metric towards rare and common species, a concept which we describe as 'leverage.' In this paper we explain coverage and Hill diversity, provide guidelines for how to use them together to measure species diversity, and demonstrate their use with examples from our own data. We show why researchers will obtain more robust results when they estimate the Hill diversity of equal-coverage samples, rather than using other methods such as equaleffort sampling or traditional sample rarefaction.

2008

Several indices have been created to measure diversity, and the most frequently used are the Shannon-Wiener (H) and Simpson (D) indices along with the number of species (S) and evenness (E). Controversies about which index should be used are common in literature. However, a generalized entropy (Tsallis entropy) has the potential to solve part of these problems. Here we explore a family of diversity indices (S q ; where q is the Tsallis index) and evenness (E q ), based on Tsallis entropy that incorporates the most used indices. It approaches S when q 00, H when q 01 and gives D when q 0 2. In general, varying the value of the Tsallis index (q), S q varies from emphasis on species richness (qB1) to emphasis on dominance (q 1). Similarly, E q also works as a tool to investigate diversity. In particular, for a given community, its minimum value represents the maximum deviation from homogeneity (E q

The Open Conservation Biology Journal, 2009

The concept of biodiversity can be simply defined as the sum of all biotic variation from the level of genes to ecosystems. Biodiversity at the species level, frequently called "species diversity", is a core concept of ecological community and conservation research. To date, however, no single number can fully capture such a concept without loss of information, although many attempts have been made to quantitatively express species diversity. Three aspects of species diversity have received considerable attention in the literature: species richness, evenness and abundance. Current diversity indices often emphasize evenness at the expense of richness or abundance. In this paper, we propose to express species diversity of communities as their position in a three-dimensional volume along the axes of richness, abundance, and evenness. With hypothetical as well as actual examples from our own studies, we discuss the usefulness of this threedimensional approach. We believe that expressing species diversity as a volume is biologically intuitive, easy to interpret numerically and ecologically, and very useful in the assessment and management of biodiversity at the species level.

Ecological Indicators, 2009

Twenty-four measures of species diversity, richness and equitability were compared using both real species abundance data (bird censuses on a standard study plot) and simple simulation tests. Based on 20 criteria, the most ecommendable measures for the estimation of alpha diversity of species have been Fager’s “number of moves per specimen”, exponential Shannon’s information (or H’), reciprocal Simpson’s lambda, and species richness (number of species). However, the last index is only appropriate when sample sizes are approximately equal otherwise it can be misleading and Hurlbert’s rarefaction method should be applied. The other measures tested, especially all equitability indices, have been shown to be problematic and should not be used regularly for the measurement of species diversity.

Oecologia, 2009

Almost half a century after Whittaker (Ecol Monogr 30:279–338, 1960) proposed his influential diversity concept, it is time for a critical reappraisal. Although the terms alpha, beta and gamma diversity introduced by Whittaker have become general textbook knowledge, the concept suffers from several drawbacks. First, alpha and gamma diversity share the same characteristics and are differentiated only by the scale at which they are applied. However, as scale is relative––depending on the organism(s) or ecosystems investigated––this is not a meaningful ecological criterion. Alpha and gamma diversity can instead be grouped together under the term “inventory diversity.” Out of the three levels proposed by Whittaker, beta diversity is the one which receives the most contradictory comments regarding its usefulness (“key concept” vs. “abstruse concept”). Obviously beta diversity means different things to different people. Apart from the large variety of methods used to investigate it, the main reason for this may be different underlying data characteristics. A literature review reveals that the multitude of measures used to assess beta diversity can be sorted into two conceptually different groups. The first group directly takes species distinction into account and compares the similarity of sites (similarity indices, slope of the distance decay relationship, length of the ordination axis, and sum of squares of a species matrix). The second group relates species richness (or other summary diversity measures) of two (or more) different scales to each other (additive and multiplicative partitioning). Due to that important distinction, we suggest that beta diversity should be split into two levels, “differentiation diversity” (first group) and “proportional diversity” (second group). Thus, we propose to use the terms “inventory diversity” for within-sample diversity, “differentiation diversity” for compositional similarity between samples, and “proportional diversity” for the comparison of inventory diversity across spatial and temporal scales.

2010

Background: The number of species of terrestrial vertebrate in one of the world's great zoological regions fits a linear combination of area (A) and one climatic variable -either annual actual evapotranspiration (AE) or mean annual temperature (T) -with an R 2 of 0.97. The same is true of species diversity in the four separate classes of terrestrial vertebrate; their R 2 -values range from 0.90 to 0.95.

Quantifying and interpreting functional diversity of natural communities: practical considerations matter. -Preslia 78: 481-501 .

World Journal of Advanced Research and Reviews, 2024

The concept of segregation has received less attention in ecology. Species diversity is a concept that includes the number of species (the total number of possible species) in the community, their abundance, and the individuals who are divided among the species, for which biodiversity is generally considered in three dimensions: within communities (αdiversity), between or among communities (β-diversity), and in the total dataset (γ-diversity). Recently, Shamia proposed using an improved generalized diversity index, which includes special cases of MacArthur's and Hill's indices. Such an index is easy to interpret when all species have equal even abundances resulting in an equivalent number to refer to the output in the community. index, when community weights are unequal relative abundances, has been applied to real data to compare the index's performance under the segregation concept. Such measures for different sites give meaningful results in multiplicative partitioning.