Running the analysis

Fit the models - Step 9/14

Now we are ready for projection at global scale under current climatic conditions. To do this we change the argument of new.env to “vars_proj” (the variable prepared or the projection at the start of module 3):

> myproj<-BIOMOD_Projection(modeling.output=mymodel,
+             new.env=vars_proj,
+             proj.name="current",
+             selected.models=”all”,
+             do.stack=T)

we plot the maps:

> source("../script/palette_MAXENT.R")
> map.current<-stack("krameri.1/proj_current/proj_current_krameri.1.gri")
> plot(map.current, col=palette_MAXENT(min=0, max=1000, interval=100)[[1]], breaks=palette_MAXENT(0, 1000, 100)[[2]])

As you can see in this figure there is a large variability of the projections among different models but also among the 3 runs of each model. This justify the use of an ensemble model for projection in space and time.
To do this we will use the function BIOMOD_EnsembleModeling().