[R] strange logLik results in gls (nlme)

[Wilhelm B. Kloke]

I am trying to analyse a data with gls/lm using the following set of models

prcn.0.lm <- lm( log10(Y)~(cond-1)+(cond-1):t ,prcn)
prcn.1.gls <- gls( log10(Y)~(cond-1)+(cond-1):t ,prcn,cor=corAR1())
prcn.0.gls <- gls( log10(Y)~(cond-1)+(cond-1):t ,prcn)
prcn.1m.gls <- gls( log10(Y)~(cond-1)+(cond-1):t ,prcn,cor=corAR1(),method="ML")

I get the following AICs for these models:
> AIC(prcn.1m.gls)
[1] -78.3
> AIC(prcn.1.gls)
[1] -46.3
> AIC(prcn.0.gls)
[1] -24.7
> AIC(prcn.0.lm)
[1] -59.8
It is the difference between the last two, which puzzles me. They are
the same models. So I can't compare the AICs of prcn.0.lm and prcn.1.gls
directly. When using anova() for the comparison, I get a sensible result:
> anova(prcn.1.gls,prcn.0.lm)
           Model df   AIC    BIC logLik   Test L.Ratio p-value
prcn.1.gls     1  6 -46.3 -28.62   29.1                       
prcn.0.lm      2  5 -24.7  -9.97   17.3 1 vs 2    23.6  <.0001

Multiple arguments in AIC() give:

> AIC(prcn.1.gls,prcn.0.lm)
           df   AIC
prcn.1.gls  6 -46.3
prcn.0.lm   5 -59.8

How can I be sure to make it right?