My research used camera surveys to estimate population density and detection probability of coyotes and other mesopredators. I also wanted to determine the influence of trap-specific covariates (e.g., building density, road density, patch size, etc) on population density and detection probability. Now I know that when modeling density, you need covariates values at each mask point (e.g. Mask Covariates). I know this can be done using addCovariates to extrapolate the trap-specific covariates included in a traps object to a mask, which takes values for each mask point from the nearest trap.
Now, I might be over thinking this, but before I do this it was my understanding that a traps object with trap-specific covariates had to be created using the read.traps function. I wrote the code for this:
- Code: Select all
traps <- read.traps("G:/R/Cameras/fall/FallCameras/CamsBinVars.txt", data = data.frame(trap), detector = "proximity", covnames = c("dH20", "dBLD", "dSE", "BLDensity", "PercPatch", "PatchArea", "RoadDensity"))
When the traps object was created, it only included the XY coordinates of each trap site and not the associated trap-specific covariate values. Due to my status as a beginner-level user of R, I am at a loss for how to add the data frame of the trap-specific covariates to the traps object, so I can then create mask covariates in order to model effects of density.
Any help or recommendations will be greatly appreciated as I cannot continue my analysis until this is figured out.
Sincerely,
Jason