I am using SSfol in nlme to fit some data for the change of N concentration (N) in plant tissue over time (gdd). The model works nicely for 2 out of 3 treatments, so I would really like to use it, but it consistently has a bad fit for my third treatment. I am pasting the figure for the third treatment only. I feel that I have my fixed and random effects properly identified, but have also tried many combinations to see if I can improve the fit.
Are there any other ideas of what I can do to capture the highest point of N with the model?
Here is my code for the figure followed by a link to the dataset.
cna<-read.table("aboveground C and N, dates removed, zeros added.txt", header=TRUE)