Beta diversity metrics and the estimation of niche width via species co‐occurrence data: reply to Zeleny

Abstract

Summary 1. Zeleny (2008) demonstrated that the co-occurrence based assessment of species habitat specialization (introduced by Fridley et al . 2007) depends on the size of the species pool. To correct for the effect of the species pool on the estimation of species niche width, Zeleny suggested a modification of the original algorithm by replacing additive partitioning as a measure of beta diversity with Whittaker's beta. 2. We used simulated data to show that the alternative index proposed by Zeleny (2008) will poorly represent the niche widths of species inhabiting a set of plots with a highly skewed distribution of local richness values. We therefore expand on Zeleny's (2008) analysis by considering two additional metrics of beta diversity based on compositional similarity and by testing the performance of these indices under different local-regional richness relationships. 3. Synthesis. None of the four tested metrics of beta diversity produced unbiased estimates of niche width under curvilinear local-regional richness relationships. In this context, we provide additional guidance to potential users of co-occurrence based niche width estimates by specifying the conditions under which certain indices of beta diversity best represent niche width information.

Building relevant ecological indicators with basic data: Species and community specialization indices derived from atlas data

“…In fact, a common though unwanted property of these alternative similarity metrics is to be correlated to species richness (Koleff et al, 2003). In Fridley's algorithm, these other metrics tend to be highly sensitive to species occurring in species-poor habitats, which have strongly skewed richness distributions (Manthey and Fridley, 2009). The Simpson's pairwise index (b sim ) is among the less biased metric of similarity (Baselga, 2010) so we used it as a good index of betadiversity.…”

Linking small-scale topography with microclimate, plant species diversity and intra-specific trait variation in an alpine landscape

“…This method estimates realised niche width as the beta diversity, in this case the multisite Simpson dissimilarity index, among a random sample of plots in which the focal species occurs. The multi-site Simpson index was chosen because it has been shown to be robust against variation in species richness and plot abundances (Manthey and Fridley 2009). Higher values of this index for a given species indicate a greater turnover in co-existing species among plots.…”

“…Hence, this represents an estimate of the microclimatic preferences of each species. Second, as a biotic approach, we used recently developed methods (Fridley et al 2007;Manthey and Fridley 2009) to estimate the width of each species' realised niche based on co-occurrence data. This method estimates realised niche width as the beta diversity, in this case the multisite Simpson dissimilarity index, among a random sample of plots in which the focal species occurs.…”

Beta Diversity of Demersal Fish Assemblages in the North-Eastern Pacific: Interactions of Latitude and Depth

“…Scientific conservation strategies can use measures of beta diversity to maintain a patchwork of heterogeneous habitats that can host a variety of species and community types, rather than focusing efforts on simply preserving high values of species richness, per se [16], [17]. Sites might have high conservation value not because of the absolute number of species they contain, but because of the variety of different types of niches present, which tends to be strongly reflected by measures of beta diversity [18].…”