How to extract the quasi-BIC (QBIC) from a Quasipoisson model?

Question

I would like to use GLMULTI for feature-selection by fitting a Quasipoisson model using quasi-BIC (QBIC) as information criterion. I use the following code:

glmulti(y ~ ., data=data,
               level=2, fitfunction=glm, family = quasipoisson, crit="useBIC", confsetsize=128, 
               method = "g", plotty = T)

Where useBIC comes from the AICcmodavg package. I then receive the error messages:

Mean crit= NA
Error in plot.window(...) : need finite 'xlim' values
In addition: Warning messages:
1: In min(x) : no non-missing arguments to min; returning Inf
2: In max(x) : no non-missing arguments to max; returning -Inf
3: In min(x) : no non-missing arguments to min; returning Inf
4: In max(x) : no non-missing arguments to max; returning -Inf

To me, this suggests that the function attempts to calculate a regular BIC, which won't work because the model does not have a likelihood. I think so because when I call useBIC on a quasipoisson model, I receive NA.

What I ultimately would like to do is to select features (variables) using GLMULTI and a quasipoisson model. I have used GLMULTI fitting negative-binomial models with BIC which works well but I would like to see whether fitting a quasipoisson model will yield a different set of features.