Distance-based multivariate analyses confound location and dispersion effects

作者：Warton, David I.^*; Wright, Stephen T.; Wang, Yi

来源：Methods in Ecology and Evolution, 2012, 3(1): 89-101.

DOI：10.1111/j.2041-210X.2011.00127.x

• Bray-Curtis distance
• community composition
• generalised linear models
• mean-variance relationship
• multi-dimensional scaling
• multivariate analysis
• PERMANOVA
• SIMPER
• species-by-site data

1. A critical property of count data is its meanvariance relationship, yet this is rarely considered in multivariate analysis in ecology. @@@ 2. This study considers what is being implicitly assumed about the mean-variance relationship in distance-based analyses-multivariate analyses based on a matrix of pairwise distances -and what the effect is of any misspecification of the mean-variance relationship. @@@ 3. It is shown that distance-based analyses make implicit assumptions that are typically out-of-step with what is observed in real data, which has major consequences. @@@ 4. Potential consequences of this mean-variance misspecification are: confounding location and dispersion effects in ordinations; misleading results when trying to identify taxa in which an effect is expressed; failure to detect a multivariate effect unless it is expressed in high-variance taxa. @@@ 5. Data transformation does not solve the problem. @@@ 6. A solution is to use generalised linear models and their recent multivariate generalisations, which is shown here to have desirable properties.

• 出版日期2012-2