To R users,

I am new to R and would appreciate any suggestions to my questions. I am 
modeling factors that influence point counts. My question is regarding the 
use and command lines of lmer. First, I have repeated measures per site 
(10-20 per site),  multiple years, and multiple spatial scales of each 
factor. The counts by day are different within each site but the 
explanatory data are the same and therefore do not vary (e.g., % cover). I 
have few sites with no overlap, even at the largest scales. I followed an 
example of mixed model use with longitudinal data from Faraway 2005 and 
modeled site and year as random effects. Example of my formula was: 
log(response) ~ hab1 + hab2 + (1 | year) + (1 | site). The models 
converged, no warnings, etc. Was this an appropriate model for these data? 
Also, do you suggest including a time component (e.g., timing of surveys 
partitioned into grouped days) , even though I am not necessarily 
interested in timing effects? If so, is it correct to model it as 
(time|site) instead of (1|time) and does time need to be additionally 
included as a fixed effect? Thank you very much for suggestions.

Models and output are:

Without including time (date of survey):

r mixed-effects model fit by REML 
Formula: log(response) ~ hab1 + hab2 + (1 | year) + (1 | site) 
   Data: data 
 AIC   BIC logLik MLdeviance REMLdeviance
 177 192.1  -83.5      148.1          167
Random effects:
 Groups   Name        Variance  Std.Dev.
 site     (Intercept) 0.1378352 0.371262
 year     (Intercept) 0.0023579 0.048558
 Residual             0.1180495 0.343583


Fixed effects:
              Estimate Std. Error t value
(Intercept)  8.666e+00  1.031e+00   8.402
hab1        -4.213e+00  1.194e+00  -3.527
hab2        -3.100e-05  4.463e-05  -0.695

Correlation of Fixed Effects:
     (Intr) hab1 
hab1 -0.992 
hab2 -0.229  0.149

With time (no time fixed effect):

r mixed-effects model fit by REML 
Formula: log(response) ~ hab1 + hab2 + (1 | year) + (time | site) 
   Data: data 
   AIC   BIC logLik MLdeviance REMLdeviance
 168.1 189.2 -77.07      134.9        154.1
Random effects:
 Groups   Name        Variance   Std.Dev. Corr 
 site     (Intercept) 0.16295061 0.403671 
          time        0.02118839 0.145562 -0.523 
 year     (Intercept) 0.00055594 0.023578 
 Residual             0.09299733 0.304955 


Fixed effects:
              Estimate Std. Error t value
(Intercept)  8.079e+00  1.006e+00   8.028
hab1        -3.643e+00  1.162e+00  -3.136
hab2        -2.391e-05  4.331e-05  -0.552

Correlation of Fixed Effects:
     (Intr) hab1 
hab1 -0.993 
hab2 -0.243  0.163
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