Interpreting the replacement and richness difference components of beta diversity

By Pierre Legendre. 2014

1,009 citations recorded by the source corpus.

Subfields: Ecology, Evolution, Behavior and Systematics, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/8cbe48376b9338bec6cc5fcf154f14c7cbd3dff2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology, Evolution, Behavior and Systematics

1. Pierre Legendre
2. J. Heino
3. A. Baselga
4. Fabien Leprieur
5. J. Soininen
6. Pedro Cardoso
7. José Carlos Carvalho
8. János Podani

In Nature and Landscape Conservation

1. J. Heino
2. Pierre Legendre
3. J. Soininen
4. A. Baselga
5. Fabien Leprieur
6. János Podani
7. Pedro Cardoso
8. T. Erős

Citations in the corpus

• On some properties of the Bray-Curtis dissimilarity and their ecological meaning (2017, background): “…frequent characteristic of many dissimilarity coefficients is that they are formulated in terms of a ratio where the numerator summarizes the amount of plot-toplot dissimilarity depending on the purpose of the study, while the denominator scales the index to values between 0 and 1 (Legendre, 2014).”
• Does pollen-assemblage richness reflect floristic richness? A review of recent developments and future challenges (2016, neutral): “, 2002) suggests that an additive model of diversity 988 (alpha + beta = gamma) provides a more natural means of estimating beta diversity as an additive 989 concept (Ellison, 2010; Legendre, 2014).”
• Comparing methods to separate components of beta diversity (2015, methodology): “As already noted by Legendre (2014), the nestedness-resultant and richness-difference components of BAS and POD frameworks, respectively, account for different concepts.”
• Relationships between forest cover and fish diversity in the Amazon River floodplain (2018, methodology): “We also evaluated whether distinct land cover and environmental variables affected the relative contribution of the local habitats to β diversity (LCBD), which are comparative indicators of the ecological uniqueness of the sampled habitats for their contribution to β diversity (Legendre, 2014; Legen”
• Effects of dispersal mode on the environmental and spatial correlates of nestedness and species turnover in pond communities (2017, background): “Environmental variables were log10 transformed to eliminate their physical units (Legendre and Birks 2012).”
• Disentangling the correlates of species and site contributions to beta diversity in dung beetle assemblages (2018, methodology): “The richness difference measured here is not related to richness difference accounted by beta diversity partitioning into its process- related components (Legendre, 2014).”
• Partitioning abundance‐based multiple‐site dissimilarity into components: balanced variation in abundance and abundance gradients (2017, positive): “In both cases, the substitution and subset components of total dissimilarity can be separated (Baselga 2010, 2012, 2013b; Legendre 2014; Baselga & Leprieur 2015).”
• Box–Cox‐chord transformations for community composition data prior to beta diversity analysis (2018, methodology): “Clear demonstrations of the difficulties encountered when using the Euclidean distance, or methods that preserve it, for the analysis of community composition data have been given by Orlóci (1978), Legendre and Gallagher (2001) and Legendre and Legendre (2012). These authors based their demonstratio”
• Integrating dispersal proxies in ecological and environmental research in the freshwater realm (2017, background): “…to represent 464 dispersal, for instance, from headwaters to mainstreams and the latter accumulates more 465 species, a suitable dissimilarity index may be one that measures species turnover only and not 466 species richness differences (Lennon et al. 2001; Baselga 2010; Legendre 2014).”
• BAT – Biodiversity Assessment Tools, an R package for the measurement and estimation of alpha and beta taxon, phylogenetic and functional diversity (2015, background): “…these different components has been a field of much recent development (Baselga 2010, 2012; Podani & Schmera 2011; Carvalho, Cardoso & Gomes 2012; Carvalho et al. 2013; Legendre 2014), including when phylogenetic or functional relations between species are taken into account (Cardoso et al. 2014c).”
• Local environment and space drive multiple facets of stream macroinvertebrate beta diversity (2018, methodology): “In all db‐RDA analyses, the sqrt.dist correction for negative eigenvalues was added in the R script (Legendre, 2014).”