Hi all:Hope you understand I'm not an statistician and hope my question is not very basic. I did have a deep look to old posts but could not find an appropriate response. So, let me ask my question!
I'm doing some lmer and glmer (poisson) models, but I noticed that for glmer there is not residual variance for the random effects. So, how do variance values should be interpreted in a glmer? What does the 6.8578 e-06 mean in the example below? I understand the "Subject" factor is explaining 6.8 e-06 of the variance, but what is the total or the residual variance? This number does not say many to me. 
Additionally, is it possible to fit a glmer with maximum likelihood? or is Laplace approximation the only option?

Thanks for your help and comprehension   

> summary(glmer1)
Generalized linear mixed model fit by the Laplace approximation 
Formula: Response ~ Treatment + (1 | Subject) 
   AIC  BIC logLik deviance
 788.8 1052 -345.4    690.8
Random effects:
 Groups Name        Variance   Std.Dev. 
Subject    (Intercept) 6.8578e-06 0.0026187
Number of obs: 1604, groups: NNo, 555

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