The ranksum test ignores the sequential order of scores, so for example ranksum(x,y) will give you the same answer no matter how you randomly permute the orders of the scores within x and y. This essentially means that the test ignores any systematic temporal fluctuations (e.g., seasonal) that might affect both x and y similarly. The reviewers might be objecting to ranksum on that basis, if some seasonal or similar factor might affect your x and y values similarly.
It's a little hard to say what test would be right without more specifics about your data and research question. If you have x and y measurements at exactly the same time points, you might start by seeing what % of time points have x>y, which is one way to control for systematic fluctuations due to time. If your x and y are measured at different time points, then it would be more complicated to remove seasonal effects.