I am trying to analyze data I have on bird migration and am stuck on what I need to do. Basically, I have the maximum abundance of birds seen per week for 10 weeks for 4 sites within a location, for 5 different species, and over the course of 5 years.

So for one year, the abundance will start at 0 at week 1, then will follow a jagged line reaching a peak around week 7, then in most cases return back to 0. I want to figure out if there are any significant differences in terms of both the timing of migration (are birds arriving later in some years? are the peaks earlier or later?) and abundances (how high the peaks are) between sites, species, and years. For an example, are Dunlin using one site more than the others, are they arriving in the same numbers and around the same time year to year?

I originally thought I would fit a line to each species and compare them but these aren't linear trends. I'm not sure if I need to maybe use a smoother and then find a way to compare the trends that way? Is there a way to capture whether both the TIMING and the ABUNDANCES are significantly different year to year/site to site/species to species?

I can insert a picture of the types of graphs I'm working with if that would help.

In addition, I have a set of variables that might explain some of these differences (if there are any) - time of day of the observation, tide level, food levels, total area of the site, etc. I wanted to see if there's any correlation between bird abundances and timing and these variables (Especially the food levels). Would this require doing a GLM? And would this analysis be totally separate from what I'm trying to do above or would they be part of the same analysis? Once I know what to do I think I'll be able to figure it out in R, but I just don't know where to start!

Thanks for any help/suggestions!