I'm quite new to R and I need a little advise on whether multinomial logistic regression is right for what I'm hoping to do for my data. Basically, I've been given some camera trap data to work with. The data is non-normal and consists of 25 species documented over 30 different trap locations. I have environmental variables for each trap (e.g. canopy cover, distance to water source etc). I would like to see whether species abundance/diversity varies across different environmental variables. I initially thought a general linear model could work but reading around makes me think miltinomial logistic regression is the best option for me. I assume I can't do just logistic regression as that seems to need the dependent variable to be just 2 options e.g. presence vs absence of a particular species which is a bit limiting. So to do species diversity as the dependent variable with 3 or so environmental variables as independent variables would multinomial logistic regression be suitable? If so how do I perform one? (my book only covers linear and logistic regression).

I hope all that makes sense!

Thanks in advance