I just posted a question to you and the phidot community about incorporating sex successfully, but I wanted to start another thread to ask you an additional question about whether there is a way to unpack how each covariate within the script contributes to the ultimate density result.
Don't want to sound like a broken record, but to add context to THIS thread... My script is currently using 21 anthropogenic an environmental covariates including human footprint, anthropogenic biomes, veg coverage, land cover, human population density, bioclims, etc. in an effort to create a comprehensive leopard density that illustrates how leopard density is affected by various land use, land cover and edge effects across a highly modified landscape in the Cape.
Unfortunately I haven't gotten a D lately as a result of the error:
- Code: Select all
Error in secr.fit(PP_ALLregionsCH_allCov_sex, model = g0 ~ 1, trace = FALSE, :
'verify' found errors in 'capthist' argument
Sometimes I get this error for script that had been previously running perfectly fine with no issue!?
But for WHEN I do get the script to run and generate a D, are there script tricks that will allow me to look at each covariate independently within the analysis so that I may be able to see which covariates are the most significant, as well as the weight/influence of each within the generated D? Its one thing to get a D=__ result, but I want to understand this number and breakdown (if possible) how the chosen model and covariates affect leopard density overall for a density. I'm not sure what the R options for this are since I'm still new to all this. Hopefully this is possible with some crafty pro R skills that you can share!?
Appreciate your help with this (and any thoughts you have on what is going on to for me to keep getting the error in capthist argument?)
All the best,
Carolyn