zero Inflation in glmmadmb

I'm going to take the liberty of replying by way of r-sig-mixed-models,
as this is a generally useful question ...

Dear professor Bolker,

I have applied the glmmadmb command to apply a zero-inflated
negative binomial model. The outcome is different to zero-inflated
models using the pscl package. Why is there only one set
coefficients in the summary instead of two for each of the
component models and how can the coefficients be interpreted? I
suspected that glmmadmb may apply a model similar to this one: 
http://hosho.ees.hokudai.ac.jp/~kubo/Rdoc/library/VGAM/html/zinegbinomial.html

At present glmmadmb fits only a constant-zero-inflation model,
corresponding
to a zeroinfl model of y~...|1 (zeroinfl's default is to make the
conditional mean and zero-inflation models the same). This is the
same as VGAM's default (i.e., with the 'zero' parameter excluded:
'zero=NULL' fits a model where conditional mean, dispersion, _and_
zero-inflation all use the same covariates).

  The results (see below) seem to be perfectly consistent.

but the results are neither consistent. Also I am uncertain about
the alpha-value in the negative binomial component of the hurdle
models. It seems to be the same as theta (or k). I thought alpha is
1/k. For the example data they are nearly identical but for my own
data they differ. Could you please clarify this?

The terminology is highly variable.  In this case alpha is indeed
the same as theta/k/size ...

library(pscl)
library(glmmADMB)
library(VGAM)

Owls <- transform(Owls,
                  Nest=reorder(Nest,NegPerChick),
                  logBroodSize=log(BroodSize),
                  NCalls=SiblingNegotiation)

## compare all three models, with constant zero-inflation probability
##  (default for VGAM and glmmADMB)
fit_zinb <- zeroinfl(NCalls~(FoodTreatment+ArrivalTime)*SexParent|1,
                     data=Owls, dist="negbin")
fit_zinbadmb <- glmmadmb(NCalls~(FoodTreatment+ArrivalTime)*SexParent,
                         data=Owls,
                         family="nbinom", zeroInfl=TRUE)
fit_zinegbinomial <- vglm(NCalls~(FoodTreatment+ArrivalTime)*SexParent,
                          data=Owls, zinegbinomial())

summary(fit_zinb)
summary(fit_zinbadmb)
summary(fit_zinegbinomial)

## glmmADMB fits zero-inflation and alpha on non-transformed scales
qlogis(fit_zinbadmb$pz)
log(fit_zinbadmb$alpha)

## 'alpha' (glmmADMB) = 'theta' (zeroinfl) = 'size' (VGAM)
## 'zero-inflation' = 'zero-inflation' = 'pstr0' (VGAM)