Forest cannot be a repeated measure because you don't expect any forest to be affected by other forests. Forest is just a random effect reflecting the fact that the rates of whatever you're measuring randomly vary from one forest to the next. The repeated measures effect is the Year with Subject=Forest. Your Age effect has nothing to do with Year but I don't understand why you have Year in the model. What is your research question about changes from the first Year bugs to the second Year bugs or do you even have one? As long as the samples were collected in the same time-frame in all forests, you can assume that the year effects apply equally to all forests and they don't seem to need to be in the model. If you don't have a cross-sectional design as far as the years of collection, then Year may be important. Year could also be important if you expect some kind of interaction between year and forest or year and the other two predictors. Seems like for your model you only need to consider Type|Age effects and for your random statement you need a simple RANDOM Forest; statement. Whether or not the outcomes change from the first year to the second is irrelevant, unless your samples in the two years are not equal. ... View more