few data appropriate for Huggins?

[JH_UW]

I have small mammal mark-recapture data from 2 field seasons, captured in two stand types, among a gradient of patch sizes. I would like to examine the differences in population estimates between stand types and among patch sizes. Since I trapped at each grid once, and a few grids twice (once each season), and since I have relatively few data, I used Closed Captures full model. However, I would like to add the categorical variable stand type, and continuous variable patch size to MARK analyses, instead of adding these to subsequent GLMs, so that I can directly use the confidence intervals MARK provides.

So far, with full Closed Captures, I've input the data by: PIT tag, capture history (4 occasions), and trapping grid ID. MARK gives me a population estimate and Upper Lower CI. After I divided the Formal N by effective trapping area, I brought those values into a GLM and added covariates stand type and patch size. The only problem with that is that I'm not sure how to use the original CI MARK provided.

Would you recommend that I use the Huggins Closed Captures model? Since I have relatively few data and low recapture rate: (508) total vole captures and (101) recaptures, and (95) total chipmunk captures and (31) recaptures, the capture histories are full of zeros.

Thanks so much for your advice!

- J

[bacollier]

J,
A statement rather than a recommendation, but yes, you can use a Huggin's model, but you might spend some time looking into some of the spatially explicit CMR methods (Murray Efford's work) as it may be applicable to your study.

bret

[JH_UW]

Thanks for your advice, Bret.