On resemblance measures for ecological studies, including taxonomic dissimilarities and a zero-adjusted Bray–Curtis coefficient for denuded assemblages

By K. Robert Clarke, P. Somerfield, M. Chapman. 2006

1,166 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/42ce6db901ca6815dc027c2faac2d1626205faad

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In Ecological Modeling

In Ecology

In Nature and Landscape Conservation

Citations in the corpus

Average functional distinctness as a measure of the composition of assemblages (2008, background): “There is a range of possibilities here, depending on how one considers the multivariate structure within the matrix (Clarke et al., 2006).”
Linking variability in species composition and MODIS NDVI based on beta diversity measurements (2009, background): “Empirical evidence suggests that regional variability in community structure, productivity, and biodiversity is related to spatial environmental heterogeneity shaped by climate, latitude, elevation, historical processes, as well as interactions among species (Rosenzweig, 1995; Gaston, 2000).”
A generalised analysis of similarities (ANOSIM) statistic for designs with ordered factors (2021, methodology): “…appropriate pre-treatment of the data (Clarke et al. 2014b), to display patterns among samples as determined by appropriate resemblance measures (Clarke et al. 2006) using clustering (Clarke et al. 2016) and ordination, and to analyse these patterns using a range of hypothesis tests and…”
Diel movements of fishes linked to benthic seascape structure in a Caribbean coral reef ecosystem (2011, methodology): “Ordination by non-metric multidimensional scaling (nMDS) was applied to matrices of Bray-Curtis pairwise similarities (Clarke et al. 2006) to examine between-sample patterns of seascape structure in a 2-dimensional plot.”
Response of soil microbial communities to contrasted histories of phosphorus fertilisation in pastures (2012, methodology): “The similarity in community composition among samples was calculated using the Bray–Curtis method, which has general suitability for biological data sets (Clarke et al., 2006).”
The non-native solitary ascidian Ciona intestinalis (L.) depresses species richness (2007, neutral): “The Bray–Curtis coefficient behaves erratically under these circumstances (Clarke et al., 2006), so we excluded these four panels from the multivariate analyses to prevent distortion of the results.”
Habitat structure and complexity as determinants of biodiversity in blue mussel beds on sublittoral rocky shores (2010, methodology): “To test whether the species composition and the abundance of functional groups in the diVerent types of treatments diVered, the treatment types were subjected to a nonmetric multidimensional scaling (nMDS) ordination based on Bray–Curtis dissimilarity with the PRIMER-6 package ( Clarke et al. 2006 )”
Global diversity and distribution of arbuscular mycorrhizal fungi (2011, neutral): “While the Euclidian distance metric equally weighs presence and absence in the community, because our distributions were highly localized (i.e., many more 0s than 1s), other methods such as Bray-Curtis dissimilarities were not appropriate (Clarke et al., 2006).”
Navigating the multiple meanings of β diversity: a roadmap for the practicing ecologist. (2011, methodology): “Measures in this class include Bray–Curtis, one of the most popular abundance-based metrics (Bray & Curtis 1957; Clarke et al. 2006), along with modified Gower (Anderson et al. 2006), chi squared (having a kinship with correspondence analysis, ter Braak 1985; Legendre & Legendre 1998) and Hellinger…”
Animal-sediment relationships re-visited: Characterising species' distributions along an environmental gradient using canonical analysis and quantile regression splines (2008, methodology): “The approach is based on a suitable resemblance measure among samples (such as Bray-Curtis, Clarke et al., 2006), thus generally avoiding explicit assumptions regarding the distributions of original variables.”