Table of Contents of Volume 51 - 2003

Table of Contents

Table of Contents of Volume 51 - 2003     

An information-theoretical measure of taxonomic diversity

Traditional diversity indices are computed from the abundances of species present and are insensitive to taxonomic differences between species. However, a community in which most species belong to the same genus is intuitively less diverse than another community with a similar number of species distributed more evenly between genera. In this paper, we propose an information-theoretical measure of taxonomic diversity that reflects both the abundances and taxonomic distinctness of the species. Unlike previous measures of taxonomic diversity, such as Rao's quadratic entropy, in this new measure the analyzed taxonomic properties are associated with the single species instead of species pairs.     

Parametric scaling from species to growth-form diversity: an interesting analogy with multifractal functions

We propose a measure of divergence from species to life-form diversity aimed at summarizing the ecological similarity among different plant communities without losing information on traditional taxonomic diversity. First, species and life-form relative abundances within a given plant community are determined. Next, using Rényi's generalized entropy, the diversity profiles of the analyzed community are computed both from species and life-form relative abundances. Finally, the speed of decrease from species to life-form diversity is obtained by combining the outcome of both profiles. Interestingly, the proposed measure shows some formal analogies with multifractal functions developed in statistical physics for the analysis of spatial patterns. As an application for demonstration, a small data set from a plant community sampled in the archaeological site of Paestum (southern Italy) is used.     

Remotely sensed spectral heterogeneity as a proxy of species diversity: Recent advances and open challenges

Environmental heterogeneity is considered to be one of the main factors associated with biodiversity given that areas with highly heterogeneous environments can host more species due to their higher number of available niches. In this view, spatial variability extracted from remotely sensed images has been used as a proxy of species diversity, as these data provide an inexpensive means of deriving environmental information for large areas in a consistent and regular manner. The aim of this review is to provide an overview of the state of the art in the use of spectral heterogeneity for estimating species diversity. We will examine a number of issues related to this theme, dealing with: i) the main sensors used for biodiversity monitoring, ii) scale matching problems between remotely sensed and field diversity data, iii) spectral heterogeneity measurement techniques, iv) types of species taxonomic diversity measures and how they influence the relationship between spectral and species diversity, v) spectral versus genetic diversity, and vi) modeling procedures for relating spectral and species diversity. Our review suggests that remotely sensed spectral heterogeneity information provides a crucial baseline for rapid estimation or prediction of biodiversity attributes and hotspots in space and time.     

Assessing the functional turnover of species assemblages with tailored dissimilarity matrices

It is often suggested that community functional diversity is an appropriate predictive measure of ecosystem functioning, particularly if relevant species traits for the ecological property of interest are carefully selected. However, methods for selecting traits are often based on expert knowledge or on theoretical models of ecosystem functioning, but usually do not include explicitly developed quantitative procedures. Here we propose to construct a so‐called ‘tailored dissimilarity matrix’ between species assemblages to emphasize their functional turnover in response to some user‐defined ecological property. First, a subset of community weighted mean trait values (CWM) is selected by stepwise regression on the ecological process of interest. The selected CWM values are then replaced by the residuals of the least‐squares regressions of each single CWM on the ecological process of interest and pairwise Euclidean distances between the residual values at each sampling site are calculated. We illustrate the advantages of the tailored approach using two distinct plant and bee communities under contrasting fire regimes in temperate forests of southern Switzerland. Our results demonstrated that, unlike for the original CWM values, the tailored approach optimized the degree of functional differentiation among bee and plant species assemblages, i.e. the species functional turnover, with respect to different fire regimes.     

Measuring beta‐diversity from taxonomic similarity

Question: The utility of beta (β‐) diversity measures that incorporate information about the degree of taxonomic (dis)similarity between species plots is becoming increasingly recognized. In this framework, the question for this study is: can we define an ecologically meaningful index of β‐diversity that, besides indicating simple species turnover, is able to account for taxonomic similarity amongst species in plots? Methods: First, the properties of existing measures of taxonomic similarity measures are briefly reviewed. Next, a new measure of plot‐to‐plot taxonomic similarity is presented that is based on the maximal common subgraph of two taxonomic trees. The proposed measure is computed from species presences and absences and include information about the degree of higher‐level taxonomic similarity between species plots. The performance of the proposed measure with respect to existing coefficients of taxonomic similarity and the coefficient of Jaccard is discussed using a small data set of heath plant communities. Finally, a method to quantify β‐diversity from taxonomic dissimilarities is discussed. Results: The proposed measure of taxonomic β‐diversity incorporates not only species richness, but also information about the degree of higher‐order taxonomic structure between species plots. In this view, it comes closer to a modern notion of biological diversity than more traditional measures of β‐di‐versity. From regression analysis between the new coefficient and existing measures of taxonomic similarity it is shown that there is an evident nonlinearity between the coefficients. This nonlinearity demonstrates that the new coefficient measures similarity in a conceptually different way from previous indices. Also, in good agreement with the findings of previous authors, the regression between the new index and the Jaccard coefficient of similarity shows that more than 80% of the variance of the former is explained by the community structure at the species level, while only the residual variance is explained by differences in the higher‐order taxonomic structure of the species plots. This means that a genuine taxonomic approach to the quantification of plot‐to‐plot similarity is only needed if we are interested in the residual system's variation that is related to the higher‐order taxonomic structure of a pair of species plots.     

A Recipe for Unconventional Evenness Measures

The degree to which abundances are evenly divided among the species of a given community is a basic property of any biological community. Several evenness indices have thus far been proposed in ecological literature. However, despite their vast potential applicability in ecological research, none seems to be generally preferred. In this paper, I first summarize the basic requirements that evenness measures should meet to adequately behave in ecological studies. Then, I discuss the major drawbacks of these requirements and propose an alternative family of measures that are based on the notion of specificity used in fuzzy set theory for measuring the uncertainty associated with a fuzzy set.     

Testing for differences in beta diversity from plot-to-plot dissimilarities

The central role of beta diversity in describing biodiversity patterns has been investigated in many fields of ecology and biogeography. While a variety of measures of beta diversity have been proposed over the past five decades, the question of how to test for differences in beta diversity among different sets of sampling plots has been addressed only rarely. Here, we describe a simple analytical procedure to test for differences in beta diversity among distinct sets of plots. The advantage of this approach compared to methods that have been previously proposed lies in its randomization procedure. Such a procedure creates a distribution of null values of the test statistic that is compatible with the null hypothesis of no significant difference in multivariate dispersion between the groups. The proposed test was illustrated using a large dataset of plant and water beetle (Coleoptera) assemblages collected from 45 farmland ponds in Ireland.     

Computing diversity from dated phylogenies and taxonomic hierarchies: does it make a difference to the conclusions?

Recently, dated phylogenies have been increasingly used for ecological studies on community structure and conservation planning. There is, however, a major impediment to a systematic application of phylogenetic methods in ecology: reliable phylogenies with time-calibrated branch lengths are lacking for a large number of taxonomic groups and this condition is likely to continue for a long time. A solution for this problem consists in using undated phylogenies or taxonomic hierarchies as proxies for dated phylogenies. Nonetheless, little is known on the potential loss of information of these approaches compared to studies using dated phylogenies with time-calibrated branch lengths. The aim of this study is to ask how the use of undated phylogenies and taxonomic hierarchies biases a very simple measure of diversity, the mean pairwise phylogenetic distance between community species, compared to the diversity of dated phylogenies derived from the freely available software Phylomatic. This is illustrated with three sets of data on plant species sampled at different scales. Our results show that: (1) surprisingly, the diversity computed from dated phylogenies derived from Phylomatic is more strongly related to the diversity computed from taxonomic hierarchies than to the diversity computed from undated phylogenies, while (2) less surprisingly, the strength of this relationship increases if we consider only angiosperm species.