Hi everyone,
I have a methodological question. I am working with a population of 9 animals and 4 environmental covariates. For each individual, I first fitted univariate habitat selection functions, and then I used ctmm:mean to estimate population-level coefficients.
Then, I wanted to adjust multivariate models. So, I fitted several candidate models for each individual (starting with 4 covariates, then 3, then 2…), and ranked them using AICc and BIC to identify the best-fitting models. This gave me multivariate models that best explained habitat selection at the individual level (each individual had different covariates associated with their movement).
My question is: is there a way to extend this approach to obtain a multivariate model estimated at the population level, rather than only at the individual level?
Thanks a lot for your help!
Best,
Victória