I have a 4-year dataset of zooplankton biomass that was sampled three times a summer (i.e. June, July, August) for all four years. There are 6 sites that were sampled in triplicate (took 3 reps): two sites in Treatment A, two sites in Treatment B, and two sites in Treatment C. There are 72 data points per zooplankton functional group once I average the reps for each site giving one measurement of biomass per site for a given month and year.
I want to see if there are differences in biomass between treatments controlling for year and monthly variation. What was suggested to me was the following model:
Bbos.model <- lmer(log(Bos.Biomass+1) ~ Treatment + Year + (1|Site), data=mydata)
However, as I understand it, this treats the monthly sampling events as independent events which I don't think I can do. Is the correct analysis of this data a repeated measures analysis? Or would a mixed model approach be more appropriate?