Canoco 5.1 released with new methods

Published on
March 27, 2018

Canoco 5.1 implements new methods for trait-environment analysis and for micro-biome data analysis. Existing Canoco 5 customers can update to Canoco 5.1 with the usual update process from within Canoco 5.

The new method designed for micro-biome analysis is weighted log-ratio PCA (Greenacre and Lewi, 2009), and in similar vein, RDA. A fully worked example of the possibilities of Canoco for microbiome analysis is included in the new release.

Trait-environment analysis used to proceed via community weighted means (CWM) correlation or the fourth-corner correlation. These methods correlated a single trait to a single environmental variable. These analysis are now fully extended to the multi-trait multi-environmental variable case. The new method allows you to detect which traits show the highest correlation with the environment and, reversely, which environmental variables show the highest correlation with the traits. The method builds a regression model that allows you to quantify how much variation is explained by traits, by environment and by their combination.

The rationale for the new trait-environment methods has been summarized in a presentation and two published papers. The first paper links the fourth-corner GLM-based regression and gives the extension to the multi-trait multi-environmental variable case, which is simple double constrained correspondence analysis (dc-CA). The second paper gives a full description of dc-CA and the algorithm used by Canoco.

The linear-trait environment model of Cormont et al. (2011) has been extended similarly to double constrained principal component analysis (dc-PCA).

The new release has a reworked manual that comes with each new license. The free update comes with pdfs in the Canoco5/pdf folder containing the major changes in Canoco 5.1 (see details).