Were raster stack for cov.file.type should be?

[rogerio-bio]

Hi Rachel,

I'm trying to generate an abundance map with static variables, following your advice from weeks ago. Well, in the cov.file.type argument, where should my rasters go in? Following what is written in the help, the recommended option is cov.file.type = "tif". Where do my variables go? I'll put the script below to see what I'm doing wrong, I can't understand where the file should go.

Edit: The extracted values of the static raster are inside the tapir data

#Importing data and rasters
tapir = read.csv(file.choose(), header=TRUE, sep=",")

predictor_filenames = list.files("TIF_2", pattern = ".tif", all.files = T, full.names = T)
predictors = rast (predictor_filenames)

predi = rast <-c (predictors$bio12,predictors$class02,predictors$rios)
plot (predi)

#Extracting static coords
tapir <- extract_static_coords(tapir, 
                      varnames = c("bio12", "class02","rios"),
                      extraction.method = "bilinear",
                      predi)

sample <- rast("sample_categorical.tif")

model_variables <- c("bio12", "class02","rios")

#Blocking
tapir_blocked<-spatiotemp_block(occ.data = tapir,
                                vars.to.block.by = model_variables[1:3],
                                spatial.split.degrees = 3,
                                temporal.block = "month",
                                n.blocks = 4,
                                iterations = 5000)

tapir_abund_blocked<-tapir_blocked[!tapir_blocked$individualCount==0,]
tapir_abund_blocked<-tapir_blocked[tapir_abund_blocked$individualCount>0,]
tapir_abund_blocked$logabund<-log10(1+tapir_abund_blocked$individualCount)
tapir_abund_blocked <- na.omit(tapir_abund_blocked)

#Abundance model
tapir_SAM_models <- brt_fit(occ.data = tapir_abund_blocked,
                            response.col = "logabund",
                            varnames = model_variables,
                            distribution = "gaussian",
                            block.col = "BLOCK.CATS",
                            n.trees = 5000)

dynamic_proj(dates = "2020-01-01",
             projection.method = "abundance",
             local.directory = "E:/abundance_teste/projection_covariates",
             user.email = user.email,
             sam.mod =  tapir_SAM_models,
             #sam.weight =  tapir_sam_weights,
             cov.file.type = "tif",
             save.directory = workingdirectory)
**Error: [rast] filename is empty. Provide a valid filename**

[r-a-dobson]

Hi Rogerio,

Thank you for attaching your code. I recommend that you use the dynamic_proj_covariates() function to generate either rasterstacks or data frames that contain the data you wish to project onto using dynamic_proj(). Take a look at the documentation for this function. Also, the package vignettes contained a detailed walk-through example of dynamicSDM functions!

Best of luck with your modelling!

Rachel

[rogerio-bio]

Thank you Rachel, sorry for my dumb question.

Best,
Rogério.