Studying beta diversity: ecological variation partitioning by multiple regression and canonical analysis

By Pierre Legendre. 2008

516 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/76d79a9c1a681ad2e55af82c68685cd5550c50f6

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In Ecology

In Ecology, Evolution, Behavior and Systematics

In Nature and Landscape Conservation

Citations in the corpus

Local environment and space drive multiple facets of stream macroinvertebrate beta diversity (2018, methodology): “According to Legendre (2008), negative values should be interpreted as zeros and “they correspond to cases where the explanatory variables explain less variation than random normal variables would”.”
Beta diversity of stream fish assemblages: partitioning variation between spatial and environmental factors (2017, methodology): “Here, we address variation between local assemblages (Anderson et al., 2011; Tuomisto, 2010b) using canonical analysis to determine how species composition is a function of environmental and spatial factors, both together and separately (Legendre, 2008; Legendre et al., 2005).”
Botanical richness and endemicity patterns of Borneo derived from species distribution models (2009, methodology): “As spatial predictors we used the nine terms of the third order polynomial trend-surface regression equation of latitude and longitude (Borcard et al. 1992, Lobo and Martin-Piera 2002, Legendre 2008).”
Does pollen-assemblage richness reflect floristic richness? A review of recent developments and future challenges (2016, unknown): “1067 Just as variation partitioning in canonical ordination and multiple regression (Borcard et al., 1068 1992; Legendre, 2008; Legendre and Legendre, 2012) has become a standard data-analytical tool in 1069 ecology and palaeoecology (e.g. Legendre and Birks, 2012; Simpson and Hall, 2012),…”
Navigating the multiple meanings of β diversity: a roadmap for the practicing ecologist. (2011, background): “Added to the perplexing array of potential measures (e.g. Tuomisto 2010a) are a variety of statistical approaches for analysing patterns in b diversity (Legendre et al. 2005; Anderson et al. 2006; Tuomisto & Ruokolainen 2006; Qian & Ricklefs 2007; Legendre 2008).”
Factors controlling decomposition rates of fine root litter in temperate forests and grasslands (2014, methodology): “We used partial linear regression to determine the amounts of variations explained by land use and the other environmental variables on decomposition of standardized fine root litter in grasslands (Legendre 2008).”