GLS - Plotting Graphs with 95% conf interval

Hi, I am trying to plot the original data with the line of the model using
the predict function.  I want to add SE to the graph, but not sure how to
get them out as the predict function for gls does not appear to allow for
SE=TRUE argument.  

Here is my code so far:

f1<-formula(MaxNASC40_50~hu3+flcmax+TidalFlag)

vf1Exp<-varExp(form=~hu3)

B1D<-gls(f1,correlation=corGaus(form=Lat~Lon, nugget=TRUE),weights=vf1Exp
, data=ocean)

ochu3<-seq(from=2.9,to=4,length=120)
ocflc<-seq(from=0,to=0.8,length=120)
tidal1<-rep(c("1"),length=120)

mydata1<-data.frame(TidalFlag=factor(tidal1),hu3=ochu3,flcmax=ocflc)
lineNASC1<-predict(B1D,newdata=mydata1,type="response")
lineNASC1<-as.data.frame(lineNASC1)

plot(ocean$MaxNASC40_50[ocean$TidalFlag==1]~ocean$flcmax[ocean$TidalFlag==1)
lines(lineNASC1$lineNASC1~mydata1$flcmax)

Tidal Flag is a factor (so i assume i have to plot seperate graphs for
each level).

When I have tried to use the effects package I get the error:  Error in
x$formula : object of type 'symbol' is not subsettable.

Also when i have been trying to predict values from a zero inflated
negative binomial, I am getting the same line of fit regardless of what is
on my X axis (depsite different variables have positive and negative
relationships).

any imput on any of these problems would be appreciated.

Thanks