For each principal component you can see which variables contribute
most to that component. Depending on what you used to do PCA in R, you
can use loadings() function. Loadings function gives a matrix that
shows how each variable contribute to the principal components. You
can do barplots for each principal component. That will visualize what
contributes to which principal component. You should do the barplots
for absolute values in the loadings matrix.
Take a look at the sources below, especially the second one
check here basic usage of PCA function in R
check here for detailed explanation on loadings()
especially check the section : "How do we know which species
contribute to which axes? We look at the component loadings (or
"factor loadings"): "