# PCA/ordination/Correspondence analysis for data with two groupings

I am working with a data set on plant presence-absence within 40 plots. For two years, the presence-absence of all plants were noted in each plot. I would now like to investigate whether the plant community is more alike within a given year or within a given plot.

My immediate thought is to run a PCA or other kind of ordination in R. But I am unsure of what kind of PCA/ordination is the most suitable when I have not one, but two grouping variables along with my presence absence data? I have loooked at the PCoA analysis and the MCA analysis. My goal in using the PCA is to give a visual interpretation of potential shift en species within and between plots.

My goal is to be able to create a plot where I can color according to year and link the dots corresponding to the same plot. I have tried drawing what I envision and inserted it below:

My data has the following structure:

Species 1; Species 2; Species 3; ...; Species n; Year; Plot

1;         0;         1; ...;          1; 2017; 1

0;         0;         1; ...;          0; 2018; 1

1;         1;         1; ...;          1; 2017; 2

1;         0;         0; ...;          1; 2018; 2