I've got a data about mammal body weight responses to increasing air temperature. I want to know whether there are some mammals that respond to the increasing air temperatures differently. Hence, I was going to preform a affinity propagation clustering method on the responses of body weight to temperature, which would get me a number of groups. Now, I want to know what influences whether a certain individual is assigned to a certain group - i.e. what influences the differences in mammal body weight responses to increasing air temperatures? I've got a lot of additional data to explain this, like longevity, habitat parameters, competition etc. So I thought to then construct a linear model to explain growth in each of the clusters (i.e. what are the predictors of mammal body response in each cluster).
Is this statistically sound? I feel like it may be a little bit of a weird way to do it, but I can't think of anything else. Any help would be greatly appreciated, thank you!