
Dear readers,
 
I have a basic question about how to use lme for my design. I haven't been able to find an example in r-help that made it clear to me how to tackle this problem and unfortunately I also cannot get hold of Pinheiro & Bates 2000. I hope someone can help.
 
Data for the response variable "foan" were collected in:
·       60 plots
·       plots were re-sampled yearly for 15 years (certain years are missing for certain plots)
·       plots are divided over 4 reserves (but not equally, so the design is unbalanced)
·       rain is a continuous covariate, which has the same value for all plots within one year.
 
Since plots are random within reserves, but reserves can be seen as fixed factors, it seems I should use a mixed-model and so I have come up with the following models:
 
model.1 <- lme(foan ~ year * reserve, data=data, random= ~1 | plot)
 
model.2 <- lme(foan ~ year * reserve, data=data, random= ~year | plot)
 
Model.2 does not provide a better fit than model.1, so apparently the slope of the relationship between "foan" and "year" does not vary for plots. 
 
I want to know if (and how) the response variable changes over the years, while correcting for variance explained by rain. My question is how to incorporate "rain" in this model. Can I simply use:
 
model.3 <- lme(foan ~ year * reserve * rain, data=data, random= ~ 1 | plot)
 
This somehow seems wrong (forgive my ignorance) since rain has the same value within each year. On the other hand it has different values within each plot. I hope someone can point me in the right direction.
 
 
Thanks in advance,
 
Robert Buitenwerf
 
South African Environmental Observation Network
Phalaborwa
South Africa
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