[R-sig-ME] lme for split-plot

[Etienne Laliberté]

I'm analyzing experimental data from a split-plot design, with two
blocks, each block containing five whole plots, and each whole plot
containing three subplots.

The multilevel structure of the design dictates the following random
structure (in the case of a random intercept model):

lme(...., random = ~ 1 | block / wholeplot, ...)

However, if, for a given model, the random effects end up being
incredibly small, e.g.

Random effects:
 Formula: ~1 | block
         (Intercept)
StdDev: 4.639022e-06

 Formula: ~1 | wholeplot %in% block
         (Intercept)  Residual
StdDev: 2.256742e-09 0.1911715

Is it still better to leave them in the model, or should I exclude them
and use gls() instead?

Many thanks,

Etienne