Predictions of biodiversity trajectories under climate change are crucial in order to act effectively in maintaining the diversity of species. We propose an interpretable and flexible two-step methodology to measure the similarity between predicted species range maps and to cluster the future scenario predictions utilizing a spectral clustering technique. Clustering based on predicted species range maps is mainly driven by the amount of warming rather than climate model or future scenario.