Much beyond Mantel: bringing Procrustes association metric to the plant and soil ecologist's toolbox

PLoS One. 2014 Jun 27;9(6):e101238. doi: 10.1371/journal.pone.0101238. eCollection 2014.

Abstract

The correlation of multivariate data is a common task in investigations of soil biology and in ecology in general. Procrustes analysis and the Mantel test are two approaches that often meet this objective and are considered analogous in many situations especially when used as a statistical test to assess the statistical significance between multivariate data tables. Here we call the attention of ecologists to the advantages of a less familiar application of the Procrustean framework, namely the Procrustean association metric (a vector of Procrustean residuals). These residuals represent differences in fit between multivariate data tables regarding homologous observations (e.g., sampling sites) that can be used to estimate local levels of association (e.g., some groups of sites are more similar in their association between biotic and environmental features than other groups of sites). Given that in the Mantel framework, multivariate information is translated into a pairwise distance matrix, we lose the ability to contrast homologous data points across dimensions and data matrices after their fit. In this paper, we attempt to familiarize ecologists with the benefits of using these Procrustean residual differences to further gain insights about the processes underlying the association among multivariate data tables using real and hypothetical examples.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biodiversity*
  • Ecology / methods
  • Models, Statistical*
  • Multivariate Analysis
  • Plant Physiological Phenomena*
  • Soil*

Substances

  • Soil

Grants and funding

This work was carried out with the aid of a grant from Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq - 563304/2010-3 and 562955/2010-0), Fundação de Amparo à Pesquisa de Minas Gerais (FAPEMIG CRA - APQ-00001-11), and the Inter-American Institute for Global Change Research (IAI-CRN II-021). Francy Lisboa greatly acknowledges a research scholarship from CAPES/EMBRAPA (Carbioma) and Dr. Beata Madari. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.