Alternative to multi-season occupancy model for count data

[Vatsal Parikh]

Hi all, I have a data for which I want to have different site covariates each season (land cover, population, etc.). I think that this could work well with a multi-season occupancy model (colext in unmarked), but I want to use count values (poisson distribution) rather than presence/absence. Is there a model in unmarked that could be used to achieve this goal? 

[Marc Kery]

Dear Vatsal,

the count-data analogue to the dynamic occupancy model is the Dail-Madsen model, or dynamic Nmix model. This is implemented in unmarked in the pcountOpen function. Can be VERY hard to fit models there when you have covariates. An alternative would be a year-stratified, static model (a.k.a., the "stacked data" approach), i.e., use function pcount() for stacked data and fit a random site effect to account for possible non-independence of the data in different years at the same site. Unless you are particularly interested in the parameters that govern the dynamics, this may be your best choice.

Best regards  --- Marc

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From: unma...@googlegroups.com <unma...@googlegroups.com> on behalf of Vatsal Parikh <vat...@umich.edu>
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Subject: [unmarked] Alternative to multi-season occupancy model for count data

 

Hi all, I have a data for which I want to have different site covariates each season (land cover, population, etc.). I think that this could work well with a multi-season occupancy model (colext in unmarked), but I want to use count values (poisson distribution) rather than presence/absence. Is there a model in unmarked that could be used to achieve this goal? 

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