response curves and variable contributions from R session code

[Danielle Del Castillo]

Hello,

I have run wallace using the GUI web interface, but I cannot run/visualize the model predictions here due to computational constraints. Therefore, I have downloaded the R session code .Rmd file and running it this way.

This generates the models as an ENMevaluation object. I see in the @results slot that I can use these data to generate evaluation plots/tables for choosing the appropriate model. But where can I find data to generate variable response curves, or determine the variable contributions? Is there an R script I can modify my session code with to extract this information?

Another unrelated issue is that whenever I used categorical environmental layers (Ex: EVI or soil), the wallace GUI web interface greys out and stops running. So I cannot get this to work for generating an R session code using categorical layers. Therefore, I don't know how to modify my R code to prompt the use of categorical environmental layers in my modeling. Can someone please provide the R script that I can incorporate to model with categorical layers?

This is my model script so far, and has been running well:

model_Cc <- model_maxent(
    occs = occs_Cc,
    bg = bgEnvsVals_Cc,
    user.grp = groups_Cc,
    bgMsk = bgMask_Cc,
    rms = c(1, 10),
    rmsStep =  1,
    fcs = c('L', 'LQ', 'H', 'LQH'),
    clampSel = TRUE,
    algMaxent = "maxnet",
    parallel = FALSE,
  numCores = 19)

Thank you for your help!!

Danielle