Hello everyone,

I am working on a conservation project with an endangered beetle and am trying to find a more accurate and reliable method for population modeling instead of just a Schnabel index.

The beetle is a strong flyer (regularly moving move then 1km in a night) so all of the local populations are open. They also go under ground multiple times a season to reproduce, making a model that can include the temporal aspect essential. The Robust Design model in MARK seemed to be perfect since it fits the biology of the beetle so well. We sampled 3 nights in a row then took 4 nights off, rinse and repeat though the summers.

However, I am getting bad AICs and total junk confidence intervals (if n is estimated at 7, the CI will be 7, if n is 21, the CI will be 21). I have played around with the models to the best of my ability (I have read the MARK book and have taken some ecology and population modeling classes...but I am an entomologist, not an ecologist or statistician).

My data is extremely 0 heavy since recapture rates are so low (~10% of beetles were recaptured) and we only caught individual beetles more then twice a few times. Is this a simple case of GIGO?

I have been reading through any forum posts that seem similar to my problem or have worked with Robust design over the last couple days with no success. You all seemed really helpful so I wanted to take a chance and ask before I tried to find a different option for my analysis.

Thanks for your time,

Kyle