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This paper discusses the measurement of taxonomic diversity of a given community or set of species. First, given D, the matrix of pairwise distances between species, I propose to summarize taxonomic diversity through Rényi.s information-theoretical parametric formalism on D. In this way, a family of taxonomic diversity indices is obtained which shows different sensitivity to the presence of species with different levels of taxonomic distinctness. The adequacy of information-theoretical indices for quantifying taxonomic diversity is discussed.

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Due to its nonlinearity with respect to species addition, some applications of the Rao quadratic diversity are meaningful only if they are first transformed into their equivalent number of species, which is the theoretical species richness of a maximally distinct and perfectly even community with the same diversity as the original community. In this paper, relaxing the requirement of maximal distinction among species, we generalize the notion of the equivalent number of species for the Rao diversity to partially distinct species. The biological meaning of this proposal is illustrated with one dedicated case study in sand dune communities in Italy. According to our results, the proposed approach proved appropriate for comparing the functional diversity of different plant communities with varying levels of environmental constraints.

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Plant communities are generally spatially structured. Therefore, in order to enhance the interpretation of distance-dependent community patterns, spatially explicit measures of β-diversity are needed that, besides simple species turnover, are able to account for the rate at which biological similarity decays with increasing distance. We show that a multivariate semivariogram computed from species presence and absence data can be considered as a space-dependent alternative to existing definitions of β-diversity. To illustrate how the proposed method works, we used a classical data set from a second-growth piedmont hardwood forest.

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There are many different metrics for expressing the dissimilarity between two samples or plots. The large majority of these dissimilarity measures attempt to summarize different aspects of plot-to-plot dissimilarity based either on species presences and absences within plots or on species abundances. Here, we propose a new parametric measure of plot-to-plot functional dissimilarity that incorporates information about the degree of functional dissimilarity between species. This measure is obtained from the combination of Hurlbert’s ‘expected species diversity’ with one dissimilarity coefficient of the ‘Bray-Curtis family’ and calculates the expected functional dissimilarity between the species in plot A and their functional nearest neighbors in plot B if m individuals are chosen randomly with replacement from each of the two plots. Due to its parametric nature, the proposed measure has a different sensitivity to the presence of rare and abundant species within plots as a function of the selected parameter value.

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Recently, a number of measures of functional diversity have been proposed for data on species presences and absences. One of the most fashionable methods uses cluster analysis of species computed from a matrix of functional characters. Functional diversity is then summarized as the sum of branch lengths of the dendrogram (FDD). Like other graph-theoretical measures of functional diversity, FDD is an increasing function of species richness. This makes FDD inadequate for comparative studies if we want to quantify a component of functional diversity that is not directly related to differences in species counts. The aim of this paper is thus to develop a graph-theoretical measure of functional diversity that does not depend of species richness. The edges of the minimum spanning tree, calculated from the pair-wise inter-species dissimilarity matrix based on functional traits, are ranked and then a power law relationship is established with the cumulative distances. We empirically demonstrate that the exponent of this relationship is independent of species richness and is therefore a suitable measure of functional diversity.

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Abstract

To avoid the problems associated with the Euclidean distance for the calculation of plot-to-plot dissimilarity, a variety of alternative measures have been proposed. Among them, the chord and the Hellinger distances are both obtained by first transforming separately the species abundances in each plot vector and then by calculating the Euclidean distance on the chord-transformed or the Hellinger-transformed data. However, although both measures are routinely used by ecologists as substitutes for the Euclidean distance, they have very different properties. In this paper, using a modified version of Dalton's principle of transfers, I will show that, unlike the Euclidean distance, the chord and the Hellinger distances are not monotonic to changes in absolute abundances. Therefore, they are not interchangeable with the Euclidean distance. The moral of this story is that although dissimilarity may appear an intuitively simple concept, the properties of even the best-known indices are not fully understood. Therefore, a clear understanding of old and new coefficients is needed to evaluate their ability to highlight relevant aspects of compositional dissimilarity among plots.

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Connectivity determines a large number of ecological functions of the landscape, including seed and animal dispersal, gene flow and disturbance propagation, and is therefore a key to understanding fluxes of matter and energy within land mosaics. Several approaches to quantifying landscape connectivity are possible. Among these, graph theory may be used to represent a landscape as a series of interconnected patches, where flows occur as a result of structural and/or functional patch connectivity. Within this context, we propose the use of a graph-theoretic index (i.e., the Harary index) as a measure of landscape connectivity. Results derived from the analysis of the vegetation map of Palmarola (central Italy) show that, from a statistical and ecological viewpoint, the Harary index may be a better measure of landscape connectivity than more traditional indices derived from transportation geography.

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Community Ecology
Authors: C. Ricotta, E. De Zuliani, A. Pacini, and et al.

Several evenness measures have been proposed for quantifying the distribution of abundance among community species, but none seems to be generally preferred. Since these measures have the common objective of summarizing community structure, they may be expected to be intercorrelated. In this paper, seven standard measures of evenness were calculated for 65 sample plots of ruderal vegetation within the archaeological sites of Paestum and Venosa (southern Italy). Principal component analysis was used to identify the primary aspects of community structure being characterized by these seven indices. The first two principal components explained 96% of total variance. A comparison of the first two principal components with the analyzed measures of evenness provides insight into what aspects of community structure they are expressing. While the first principal component is most sensitive to the relative abundances of rare species, the second principal component is clearly associated to changes in the abundance of the dominant community species.

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Community ecologists have become increasingly interested in analyzing the phylogenetic diversity of species assemblages. Species that co-occur in the same habitats often share a common phylogenetic history such that at coarse spatial scales a species assemblage with a locally clustered phylogenetic structure is usually associated with the presence of habitat filtering mechanisms. However, more recently it has been hypothesized that environmental filters act primarily on the relative abundance of species rather than on their simple presences and absences, reducing the species’ probabilities to persist in given environmental conditions. This process may produce a non-random distribution of species abundances in the regional phylogeny even in the absence of a locally clustered phylogenetic structure. In this paper, using data from the urban flora of Brussels (Belgium) we tested for the presence of non-randomness in the distribution of abundances among the species phylogenetic structure. We argue that the observed pattern of low species phylogenetic distinctiveness at increasing species abundances is compatible with environmental filtering processes.

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