zero-inflation in glmmADMB

Hello,

I am investigating impacts of forest fragmentation due to gas development
on songbirds, and have run mixed effects models using lme4.  My response
variables are species abundances (count data), fixed effects are landscape
metrics (forest edge density, percent gas cover, percent forest cover), and
random effects are year and survey point (repeated measures over an 8-yr
period).

However -- having recently realized that I need to better account for the
high numbers of zeros in my count data, I decided to try zero-inflated
poisson models in glmmADMB.

(1) Although many of the species I'm looking at have high numbers of zeros,
the results of my ordinary poisson models and zeroInflation=TRUE poisson
models appear to be identical, which seems odd:

*Ex.*:
CERW.pois <- glmmadmb(CERW.50m ~ Edge.100m + pGAS.100m + pFOR.500m
+ (1|Year) + (1|Point), family="poisson")

CERW.zipois <- glmmadmb(CERW.50m ~ Edge.100m + pGAS.100m + pFOR.500m
+ (1|Year) + (1|Point), zeroInflation=TRUE, family="poisson")

Am I doing something wrong here, or is it common for outputs to look nearly
identical, with or without zero-inflation?

(2)  I am also trying to incorporate offsets for detection probability
(calculated using the QPAD approach outlined in Solymos et al., 2013) --
but the offset term doesn't appear to be recognized ("unused argument"
error)

*Ex.*:
(.... family="poisson", offset=offset(CERW.offs))

*For what it's worth, here is the offset code that works in lme4 (doesn't
work in glmmADMB):
(.... family="poisson", offset=*corrections2offset*(CERW.offs))

Any suggestions or advice would be greatly appreciated.

Thanks,
Laura Farwell
West Virginia University

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