Output argument “explained” from pca() gives the percentage of the total variance explained by each principal component. Explained value returned for the first one is 100 this means 100 percentage of the total variance(i.e total variance) is explained by the first component itself hence you are getting only first eigenvector.
Since the first component explains 100% of all variability, plotting even the second component won’t give wrong results but you will see only the first component displayed.