Conditional occupancy? or other co-occurrence analyses?

[Miguel Silva]

I'm working on some community occupancy models with msPGOcc(), and was wondering if there is a good way of assessing the effect that one species might have on another. I know in unmarked there are some ways to set up conditional occupancy measures for one species when another is present or absent in relation to a predictor. 

I'm curious if something similar can be done in spOccupancy, or if there might be a better way to look into spatial differences in the occupancy of two species or species groups. 

I'm specifically trying to evaluate how two different carnivore species are distributed to see if they avoid each other or if they mostly co-occur, etc. Is there also a way to set this up with species groupings (say small and large carnivores) from the species in the community model?

Thank you all for any insight you can provide!

Miguel

[Marc Kéry]

Dear Miguel,

I think spOcc/spAbu does not (yet ?) have any models for species co-occurrence of the kind that you mention, e.g., like the models developed by Chris Rota and colleagues around 2016. For this, you would have to go to unmarked or code them up in JAGS/NIMBLE/Stan.

However, one might still learn something about co-occurrence patterns from a model fit in spOccupancy, based on posterior draws of z, i.e. the presence and absence of each species. You can get z for each site in your analysis in R, by calling the function rbinom with sample size equal to 1 (for a Bernoulli) and with prob = the predicted occupancy probability (psi) obtained from a call to spOccupancy:: predict. Doing this once for each posterior draw of psi at every pixel gives you the posterior distribution of z for every pixel. Then, you can summarize these for two or also more species in a tabulation that gives you the number of pixels where only one species occurs, only the other, both, or none. This will be more descriptive than what the Rota et al-type of models can teach you, but inspecting such patterns may still give you a lot of insight into community structure.

Best regards  --- Marc

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Marc Kéry
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marc...@vogelwarte.ch
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Swiss Ornithological Institute | Seerose 1 | CH-6204 Sempach | Switzerland
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*** Hierarchical modeling in ecology ***

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