Recent Advances in Analysis of Multivariate Ecological Data: Theory and Practice

International Centre for Theoretical Physics (ICTP)

Trieste, Italy

24-28 October 2016

Pierre Legendre and Daniel Borcard

Université de Montréal

Course page

Official Website

Day 1

  1. Short introduction to the course [PL].
  2. Ordination in reduced space: principal component analysis (PCA) [PL].
  3. Transformation of species abundance data tables prior to linear analyses [DB].
  4. Ordination in reduced space: correspondence analysis (CA), principal coordinate analysis (PCoA) [DB].

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Day 2

  1. Measures of similarity and distance, especially for community composition data [PL].
  2. Multiple linear regression. R-square, adjusted R-square, AIC, tests of significance [PL].
  3. Polynomial regression [DB].
  4. Partial regression and variation partitioning [DB].

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Day 3

  1. Statistical testing by permutation [PL].
  2. Canonical redundancy analysis (RDA) and canonical correspondence analysis (CCA) [PL].
  3. Multivariate analysis of variance by canonical analysis [DB].
  4. Selection of environmental variables in RDA [DB].

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Day 4

  1. Beta diversity partitioning and LCBD indices [PL].
  2. Replacement and richness difference components of beta diversity [PL].
  3. Spatial modelling: origin of spatial structures [PL].
  4. Mantel correlogram [DB].

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Day 5

  1. Multi-scale modelling of the spatial structure of ecological communities: dbMEM [DB], generalized MEM, and AEM methods [PL].
  2. Community surveys through space and time: testing the space-time interaction in repeated surveys [DB].
  3. Is the Mantel test useful for spatial analysis in ecology and genetics? [PL].

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