[R] lme4 and false convergence

[Ben Zuckerberg]

Dear R-users,

I am using the most updated package of lme4 (lme4_0.999375-2).  I have a 
data set consisting of ~900 observations at ~440 independent survey 
sites.  There are an unbalanced number of surveys at each site.  I am 
attempting to develop several models evaluating the presence/absence of 
a species (PRES) at these random sites (SITE) using a number of 
predictor variables.  The response variable (PRES) is binomial and the 
included predictor variables are either proportions (e.g., AG, FOR, 
OPEN, LDEV,or DEV) or numerical (COUNT[min. 1 to max. 37,mean = 10]). 
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PROBLEM 1:
 
I have developed the following GLMM:
 
mix.1<-glmer(PRES~AG+FOR+OPEN+LDEV+DEV+COUNT+(1|SITE),family=binomial,data=merge1) 

 
I receive the following error:
Warning message:
In mer_finalize(ans) : false convergence (8)
 
There is model output, but I am worried it might be biased. 
 
I have tried:
-Data transformation of the predictor variables (e.g., log(COUNT)), 
which does seem successful in some simpler models, but does not work 
consistently.
-The most updated version of lme4
 
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PROBLEM #2:
In addition, I am interested in visualizing the predicted probabilities 
from this output using the fixed effect function, but receive the 
following message:
 
fixef(mix.1)
Error in UseMethod("fixef") : no applicable method for "fixef"
 
Any suggestions would be greatly appreciated!