Random intercept and slope after model Averaging

Hello All,

I did model averaging for a mixed model, and now i want to find the
estimates of Random variable after model averaging,
my random variable is Dry and Wet season.
My models are
1)model1<- glmmadmb(Birds~DO+evap+precipitation+Turbidity
+(1|season),data=a,"nbinom")
2)model2<-glmmadmb(Birds~DO+temp+precipitation+Turbidity
+(1|season),data=a,"nbinom")
then i did model averaging as under
Avgmodel<-model.avg(model1,model2)

Here is the summary.
Component model call:
glmmadmb(formula = <2 unique values>, data = a, family = nbinom)

Component models:
df logLik AICc delta weight
1245 7 -539.36 1093.56 0.00 0.7
1345 7 -540.23 1095.30 1.74 0.3

Term codes:
DO evap temp preci Turb
1 2 3 4 5

Model-averaged coefficients:
(full average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) -3.2065 3.2864 3.2968 0.973 0.33075
DO 1.1228 0.4082 0.4119 2.726 0.00641 **
evap 0.9174 0.6821 0.6836 1.342 0.17961
preci -1.6303 0.5586 0.5636 2.893 0.00382 **
Turb 1.2183 0.4086 0.4122 2.955 0.00312 **
temp 0.3124 0.5135 0.5140 0.608 0.54335

(conditional average)
Estimate Std. Error Adjusted SE z value Pr(>|z|)
(Intercept) -3.2065 3.2864 3.2968 0.973 0.33075
DO 1.1228 0.4082 0.4119 2.726 0.00641 **
evap 1.3021 0.3994 0.4029 3.232 0.00123 **
preci -1.6303 0.5586 0.5636 2.893 0.00382 **
Turb 1.2183 0.4086 0.4122 2.955 0.00312 **
temp 1.0574 0.3236 0.3265 3.238 0.00120 **
---
Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1

Relative variable importance:
DO preci Turb evap temp
Importance: 1.0 1.0 1.0 0.7 0.3
N containing models: 2 2 2 1 1


If i want to get random effects of model 1 or model 2 specifically i can
get them through
ranef(model1)
But how to get random effects after model averaging.
I can get the estimates of fixed parameters by summary(Avgmodel),
but how to get intercept and slopes for random variable?

any help will be appreciated.

Regards