Theory, R functions & Examples
Section: Ordination analysis
Use vegetation data from an experimental study on wet meadow, which tried to answer the question how are abundance and species composition of seedlings of herb species on wet meadow influenced by experimental removal of dominant clonal plant species (Nardus stricta), plant litter (remnants of plant biomass from the previous season in case that the meadow was not mown) and removal of litter+mosses (by raking). Before analysis, please get familiar with the data you will be using. Data are from completely randomized block design with four blocks, each with four plots (one per treatment, including control). The block design will need to be taken into consideration when testing the significance of explained variation using Monte Carlo permutation test.
seedlings.env- the first containing species composition of seedlings per plot, the second contain an assignment of the plot to the block and experimental treatment.
seedlings.env$blocksas a covariable in the model (the vegetation within individual blocks may slightly differ because the experimental site (meadow) is not perfectly homogeneous, but for us, this variation is not relevant - we are not interested in it, so we will remove it as covariable).
decoranaresults. If over 4, use CCA, if less then 3, use RDA, 3-4 -both are fine;
seedlings.spe ~ treatment + Condition (block), data = seedlings.env;
anovawithout any other arguments; since the
blocksare defined as covariable, the function will test the significance of variation after removal of their variation;
by = “axis”.