mapping with community models

[Magdalena Salas]

Hi Juergen, I hope you're doing well. I was wondering if it's possible to map the occupancy predicted by the MOMS. I was able to get the table with predicted values for camera stations (mean and sd) but I don't know if it can estimate predicted values for points in a raster. I think this a key step, and the only way to generate this kind of map in R (with package raster and sf).

When working with single-season occupancy models, I used this predict function with the data frame being the points extracted from the raster (in this case, "alt" and " pend" are variables):

occ_predavg <- predict(MMod139,
                       newdata = as.data.frame (pred_surface_std[,c("alt",
                                                                    "Pend")]), type = "state")

Thank you very much in advance.

Best,

Magdalena

[Juergen Niedballa]

Hello,

yes, you can create prediction maps for multi-species occupancy models, using the predict() function (as defined by camtrapR), see:

 ?camtrapR::predict

It allows the creation of species occupancy and species richness maps (mean, SD, confidence intervals). For Royle-Nichols models it also calculates abundance. In addition it can calculate percentage of area occupied (PAO), which does not return maps though.

See the vignette under "Spatial predictions":

https://cran.r-project.org/web/packages/camtrapR/vignettes/camtrapr5.html

On a side note, in single species models from unmarked (and ubms) you can predict directly on rasters (or terra SpatRast objects), so no need to convert the raster to a data frame first.

Best regards,

Jürgen