I am trying to detect evidence of warming in a monthly temperature time series over a 20-year period by testing for a trend. I have precisely followed the method of Crawley (2013) The R Book, 2nd Edition pgs 798-799. In his linear mixed effects model for monthly temperatures he treats the explanatory variables time and linear trend as fixed effects, and year as a categorical random effect allowing for different intercepts for the different years. He then uses ANOVA to compare the full model (with trend explanatory variable) with a reduced version (i.e. without the trend explanatory variable).
A reviewer has questioned why year has been treated as a random effect and suggested that by doing so this would essentially remove a long-term trend. Can anyone clarify why it is correct to include year as a random effect and if by doing so this does or does not remove a trend?