CCA Rscript and datasets

This folder contained a R script and datasets to perform a Canonical correspondence analysis (CCA) in R. CCA was used to infer the underlying relationship between the benthic harmful dinoflagellate assemblages and benthic substrate characteristics, depths and irradiances. CCA is a constrained multivariate ordination technique that extracts major gradients among combinations of explanatory variables in a dataset and requires samples to be both random and independent. Data for cell abundances were Hellinger-transformed prior to CCA to ensure the data met the statistical assumptions of normality and linearity. The analysis was performed using vegan. The significance of variation in benthic harmful dinoflagellates assemblages explained by the explanatory variables was tested using an ANOVA-like Monte Carlo permutation test as implemented in vegan.