I am looking at whether abundance is related to size. Size is (of course) continuous, however, abundance is recorded on a scale such that 

    A = 0-10
    B = 11-25
    C = 26-50
    D = 51-100
    E = 101-250
    F = 251-500
    G = 501-1000
    H = 1001-2500
    I = 2501-5000
    J = 5001-10,000
    etc... 

A through Q... 17 levels. I was thinking one possible approach would be to assign each letter a number: either the minimum, maximum, or median (ie A=5, B=18, C=38, D=75.5...). 

What are the potential pitfalls -- and as such, would it better to treat this data as categorical?

I have read through [this question][1] which provides some thoughts -- but one of the keys of this data set is that the categories are not even -- so treating it as categorical would assume the difference between A and B is the same as the difference between B and C... (which can be rectified by using logarithm - thanks Anonymouse)

Ultimately, I would like to see whether size can be used as a predictor for abundance after taking other environmental factors into consideration. The prediction will also be in a range: Given size X and factors A, B, and C we predict that Abundance Y will fall between Min and Max (which I suppose could span one or more scale points: More than Min D and less than Max F... though the more precise the better).



  [1]: http://stats.stackexchange.com/questions/539/does-it-ever-make-sense-to-treat-categorical-data-as-continuous