I have a field study in which the abundance of insects is measured in 4 nests (
NestID) at 32 Sites (
Site) 5 times (
Round). Each round was one month apart, but I am missing data from Round #4, so virtually I have only 4 rounds with uneven spacing between them. The average abundance across rounds is hump-shaped:
My interest is the environmental factors (
x) that might affect abundance.
I am unsure how to proceed. I want to account for the autocorrelation at the
Site level with
(1|Site), and also for the temporal aspect. On forums proposed solution is usually:
y ~ Round + (1 + Round|NestID), and since my
NestID is nested in
Site I thought of doing :
m1 <- bf(y ~ x + Round + (Round|Site/NestID))
m2 <- bf(y ~ x + Round + (Round|NestID) + (1|Site) + (1|NestID:Site))
m3 <- bf(y ~ x + s(Round, k = 4) + (1|Site/NestID))
but I am not sure if this is what I want exactly and if including both
Round is not redundant.
I actually wondered if, given I am not interested in temporal effects,
y ~ x + (1|Site/NestID) would be the appropriate model, since it averages over different nests, so no need to add the
Round to the model?
y ~ x + Round + (Round|Site) (or equivalent with a spline) if I am interested in the temporal effect on the abundance.
I am also not sure if I should treat
Round as numerical or categorical predictor.
Any advice would be appreciated!