The spatial scaling of beta diversity

Abstract

Beta diversity is an important concept used to describe turnover in species composition across a wide range of spatial and temporal scales, and it underpins much of conservation theory and practice. Although substantial progress has been made in the mathematical and terminological treatment of different measures of beta diversity, there has been little conceptual synthesis of potential scale dependence of beta diversity with increasing spatial grain and geographic extent of sampling. Here, we evaluate different conceptual approaches to the spatial scaling of beta diversity, interpreted from 'fixed' and 'varying' perspectives of spatial grain and extent. We argue that a 'sliding window' perspective, in which spatial grain and extent covary, is an informative way to conceptualize community differentiation across scales. This concept more realistically reflects the varying empirical approaches that researchers adopt in field sampling and the varying scales of landscape perception by different organisms. Scale dependence in beta diversity has broad implications for emerging fields in ecology and biogeography, such as the integration of fine-resolution ecogenomic data with large-scale macroecological studies, as well as for guiding appropriate management responses to threats to biodiversity operating at different spatial scales.

Global meta-analysis reveals low consistency of biodiversity congruence relationships

“…However, these differences are clearly attributable to methodological considerations: Mellin et al 31 use 4100 km 2 as their highest category of spatial extent, six orders of magnitude lower than our maximum recorded values, whereas Wolters et al 30 use analysis of grain size rather than spatial extent. These are independent metrics that-as we and others have shown-have differing effects on observed patterns of biodiversity 35,50 . These contrasts show that the choice of scales-and the metrics used in assessments of the effects of scale-can strongly influence the outcome of ecological studies and meta-analyses, and can thereby influence inferred patterns of biodiversity 35,50 .…”

“…These are independent metrics that-as we and others have shown-have differing effects on observed patterns of biodiversity 35,50 . These contrasts show that the choice of scales-and the metrics used in assessments of the effects of scale-can strongly influence the outcome of ecological studies and meta-analyses, and can thereby influence inferred patterns of biodiversity 35,50 . We found no evidence for an effect of higher-level phylogeny on cross-taxon congruence, a result that has several key implications.…”

“…In particular, we found that congruence in species composition was low below 10 3 km 2 (Fig. 1c), suggesting that at these fine spatial scales complementarity-based metrics applied to single taxa are unlikely to be broadly representative of biodiversity 50 . In contrast, species richness is a metric that is most commonly applied at landscape scales (B10 3 km 2 ), that is, at precisely those scales where observed patterns will be least well correlated with overall biodiversity 50,57 .…”

“…1c), suggesting that at these fine spatial scales complementarity-based metrics applied to single taxa are unlikely to be broadly representative of biodiversity 50 . In contrast, species richness is a metric that is most commonly applied at landscape scales (B10 3 km 2 ), that is, at precisely those scales where observed patterns will be least well correlated with overall biodiversity 50,57 . This implies that ecologists that monitor change in species richness over time (for example, as an indicator of ecological change) at landscape scales should strongly consider monitoring a number of functionally distinct taxonomic groups if their recommendations to managers are to be robust.…”

Local and regional influences over soil microbial metacommunities in the Transantarctic Mountains

“…We quantified local (alpha) and regional (gamma) diversity patterns to estimate multiplicative beta diversity (variation in community composition among assemblages) (Jost 2007, Chao et al 2012, which can also be related to scale of metacommunity mixing (Barton et al 2013). Using variation partitioning, we assessed the spatial scale of community composition heterogeneity in the metacommunity (spatial component of beta diversity) and the spatial scales at which community composition responds to environmental gradients (environmental component of beta diversity) (Borcard et al 1992, Van der Gucht et al 2007, Dumbrell et al 2009, Bru et al 2010, Logue and Lindströ m 2010, Caruso et al 2011, Logue et al 2011, De Bie et al 2012).…”