I don’t use glmmadmb either but I use both ADMB and R, so can see glmmadmb is just intercepting ADMB error trapping. I waited on answering, hoping somebody familiar with glmmadmb would respond. I’m stuck with guessing here. Normally I would diagnose the problem via familiar ADMB outputs, track the fitting progress, and output key estimates (but have to modify the tpl for that). In your case it looks the job was submitted with default settings, and the hessian was attempted, but I have no experience with either zero-inflated models or sparse estimation of the hessian (the –shess option). The error message is just the usual consequence of a failure to achieve convergence. When the model fails it (usually) won’t produce the file of standard deviations of estimated parameters. Not a syntax issue or anything wrong with handshaking between R and ADMB, but maybe not the most intuitive error message. My first guess is an inappropriate model, either type or particular specifications. A second guess is too little data per design partitions. I.e. just how many plants per block/treatment, and what sort of variance in seed counts do we see within these partitions. Sorry, best I can do.
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This might have
And if everything else
fails, try to get in touch with Ben Bolker