Canonical Correspondence Analysis

method

Canonical Correspondence Analysis (CCA) is a constrained multivariate ordination used to explore relationships between species abundance data and environmental variables when unimodal responses are expected.

Published

February 2, 2024

Modified

January 29, 2024

Description

Canonical Correspondence Analysis (CCA) is a multivariate statistical method widely used in ecological research to explore the relationships between species abundance data and environmental variables. CCA is an extension of CA and aims to maximize the covariance between species abundances and environmental gradients while respecting the constraints of linear ordination.

Example

wetlands <- readRDS("wetlands.rds")

library(vegan)

cca_ord <- cca(wetlands$cross, wetlands$env[ , c(
            "groundwater",
            "tmean",
            "tseason",
                        "prsum",
            "prseason")])
plot(cca_ord)