Spatially explicit output for occupancy models

[Manuel Spínola]

Dear group members,

I am trying to get spatially explicit output for occupancy models.
How can I do it using the output from occupancy model from unmarked?
or there is another way to do it?
I am using dismo package and yoy can get spatially explicit
predictions for glm, but it uses glm class objects.
Best,

Manuel Spínola

[Jeffrey Royle]

hi Manuel,
I assume you mean things like spatially correlated random effects or
autologistic type models? If so, unmarked doesn't have any spatially
explicit capabilities so you're on your own there. I would suggest
WinBUGS
regards
andy

[Manuel Spínola]

Thank you very much Andy.
I wasn't thinking on such complex models, I was thinking how to predict occupancy for an area based on an occupancy model.  The output will be a map, like the one that you have in your book.  I am attaching a map that I got for a species distribution model using maxent (a species distribution algorithm) from the package dismo (there are others in R, like BIOMOD).
If I understand correctly, occupancy models could be used to model species distribution, but the people working on species distribution models are not considering (to my knowledge) occupancy models like one of the alternatives.
Best,

Manuel

--
Manuel Spínola, Ph.D.
Instituto Internacional en Conservación y Manejo de Vida Silvestre
Universidad Nacional
Apartado 1350-3000
Heredia
COSTA RICA
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Teléfono: (506) 2277-3598
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[Richard Chandler]

Hi Manuel,

There are a couple of options for making maps using models fit in unmarked. If you have a map of the covariates used in the model, then you can simply use the predict function to get an estimate of Pr(occurrence) for each cell. Then you would plot the predictions using one of the many functions available in R such as image or levelplot. Here's a fake example:

fm <- occu(~date ~ elevation, data)
E <- predict(fm, type="state", newdata = someSpatiallyReferencedCovariateData, appendData=TRUE)
require(lattice)
levelplot(Predicted ~ x.coord + y.coord, data=E)

The object "someSpatiallyReferencedCovariateData" would be a data.frame with columns x.coord and y.coord for your coordiantes and other columns for your covariates (eg elevation).

Hope this helps.

Richard

[Manuel Spínola]

Thank you very much Richard.

I will try that.
Best,

Manuel