FITTING MULTIVARIATE MODELS TO COMMUNITY DATA: A COMMENT ON DISTANCE‐BASED REDUNDANCY ANALYSIS

By Brian McArdle, Marti J. Anderson. 2001

3,931 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/8411990557bb74a5df3cbee40a95b0100abad31a

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Citations in the corpus

Interaction of ocean acidification and temperature; the high cost of survival in the brittlestar Ophiura ophiura (2010, methodology): “The remaining carbonate parameters were calculated using CO2SYS (Pierrot and Wallace 2006) with the constants supplied by Mehrbach et al. (1973) refitted by Dickson and Millero (1987) and the KSO4 dissociation constant from Dickson (1990).”
Animal-sediment relationships re-visited: Characterising species' distributions along an environmental gradient using canonical analysis and quantile regression splines (2008, methodology): “The inherent role-change in the consideration of species-environment relationships is the main difference between CAP and the related technique of distance-based (or dissimilarity-based) redundancy analysis (dbRDA, Legendre and Anderson, 1999; McArdle and Anderson, 2001).”
Microbial richness and composition independently drive soil multifunctionality (2017, methodology): “…of bacteria (Alpha-, Beta- and Gammaproteobacteria, Actinobacteria, Bacteroidetes and Fimicutes) as drivers of multifunctionality, we used a multi- model inference approach based on information theory and nonparametric distance- based linear regressions (DISTLM; McArdle & Anderson, 2001).”
Effects of tropical forest fragmentation on aerial insectivorous bats in a land-bridge island system. (2010, methodology): “Differences in species composition among site categories were assessed with a permutational multivariate analysis of variance (e.g. McArdle and Anderson, 2001) based on Bray–Curtis dissimilarity matrices and 1000 permutations using the ‘adonis’ function as implemented in the ‘vegan’ package…”
Carbon content and climate variability drive global soil bacterial diversity patterns (2016, methodology): “Data in panel (a) represent means ± SE; different letters in this panel indicate significant differences among latitudinal ranges (P < 0.05, post- hoc test after PERMANOVA).”
Navigating the multiple meanings of β diversity: a roadmap for the practicing ecologist. (2011, methodology): “…be measured directly using the sum of squared interpoint dissimilarities: r̂2 ¼ 1 N ðN 1Þ P i; j<i d 2 ij (e.g. Legendre & Anderson 1999; Anderson 2001; McArdle & Anderson 2001), the average interpoint dissimilarities 2010 Blackwell Publishing Ltd/CNRS d ¼ 1 m P i; j<i dij (e.g. Whittaker 1960,…”
The application of predicted habitat models to investigate the spatial ecology of demersal fish assemblages (2010, methodology): “We used a distance-based multivariate analysis for a linear model (DISTLM) to measure the relationship between the Wsh assemblage structure and the physical and biological environment (Anderson 2001; McArdle and Anderson 2001; Anderson 2004).”
Multivariate analysis of ecotoxicological data using ordination: demonstrations of utility on the basis of various examples (2003, result): “The results of the RDA and CCA analyses show that ordination successfully detected both absolute and compositional (or relative) differences in levels of PCB congeners between the samples taken in the three periods.”
Exotic plants increase and native plants decrease with loss of foundation species in sagebrush steppe (2010, methodology): “…analyzed with a non-parametric multivariate analysis of variance (PERMANOVA) using the vegan library (10,000 random permutations; Anderson 2001; McArdle and Anderson 2001; Oksanen et al. 2008) in R (R Development Core team 2007) to ensure that there were no pre-treatment differences in…”
Disease-specific Alterations in the Enteric Virome in Inflammatory Bowel Disease (2015, methodology): “001, 999 permutations) (McArdle and Anderson, 2001).”
Structure of cryptic reef fish assemblages: relationships with habitat characteristics and predator density (2003, positive): “…systematic changes in the habitat structural complexity inside versus outside the reserve, which might confound interpretation of any effects of Status, using non-parametric multivariate regression (McArdle & Anderson 2001) of the assemblage data versus Status, treating complexity as a covariable.”