Overdispersion parameter in R's glmmTMB I am using R's glmmTMB for modeling negative binomial mixed effects. In the output, I see the following line : Overdispersion parameter for nbinom2 family (): 9.28e+06. 
How do I interpret such a large overdispersion? Please help.
 A: I think a value of 
Overdispersion parameter for nbinom2 family (): 9.28e+06
actually means no overdispersion. This is the theta parameter of a NB2 model, see also
What is theta in a negative binomial regression fitted with R?
That is, the right thing in this case would be fitting a Poisson mixed model.
A: I'm not 100% but I don't think it's a normal value even with a negative binomial distribution. And I think it requires model improvement. I had a similar problem and managed to almost solve it.
The final code gave me a much lower overdispersion, though it was still overdispersed when checked with the DHARMa test for dispersion (p < 0.05).
Here it is:
glmmTMB(count ~ distance_to_pond * rainfall + distance_to_river * rainfall + (1|cell) * (1|date) + offset(log(area)), ziformula = ~1, family = nbinom2)
I initially had the random effects as nested so (1|date/cell) and shifting to crossed effect almost solved my issue. These random effects are for mitigating spatial and temporal autocorrelation (and it worked according to DHARMa tests for autocorrelation, though it is mentionned in the guidelines not to fully rely on them and perform further tests).
