Suppose that I have a data set of three variables, Calcium, Iron, and Uranium.

Suppose also that I run PCA and obtain the following principal components:

$$\begin{array}{cccc}&PC\_1&PC\_2&PC\_3\\Calcium&0.6729&0.1021&-0.6771\\Iron&0.5331&0.2554&0.5402\\Uranium&0.1123&-0.8007&-0.0432\end{array}$$

The first PC shows Calcium as having the largest importance and Iron as being the second highest correlation. The second PC shows Uranium as having the largest correlation. But, the third PC then again denotes Calcium as having the largest correlation with the response, then Iron second. 

My main question is how such a PCA outcome can be interpreted. It makes no sense to say that Calcium is the most explanatory of the variance, **as well as also** being the third most explanatory variable for the variance.