BIOMOD2: invalid term in model formula

While trying out BIOMOD2 for species distribution modeling I encountered the following error when trying to create a random forest (RF) model:

Error in terms.formula(formula, data = data) : 
  invalid term in model formula
Error in predict(model.bm, Data[, expl_var_names, drop = FALSE], on_0_1000 = TRUE) : 
  error in evaluating the argument 'object' in selecting a method for function 'predict': Error: object 'model.bm' not found

After lots of digging in the source code of BIOMOD I discovered what happened and how to fix it.

The line where the error was occurring looked like this:

model.sp <- try(randomForest(formula = makeFormula(resp_name, 
    head(Data), "simple", 0), data = Data[calibLines, 
    ], ntree = Options@RF$ntree, importance = FALSE, 
    norm.votes = TRUE, strata = factor(c(0, 1)), 
    nodesize = Options@RF$nodesize, maxnodes = Options@RF$maxnodes))

As you can see a formula is created from our data. The generated formula looked like this:

654987634 ~ 1 + nitrate_mean + par_mean + sst_mean + sst_range

The number 654987634 is my response variable name that I set when calling BIOMOD_FormatingData which apparently has been added to the Data data.frame as the first column. 

Solution: adding a letter prefix to my response variable name fixed my issue.

Lessons learned:

1. It's incredibly useful that you can take a look at external source code in an RSession by typing its name, for iternals you add the package name and 3 double dots e.g. biomod2:::.Biomod.Models. Generics functions can be fetched with getMethod e.g. getMethod(biomod2::predict, signature="RF_biomod2_model")
2. Read the docs very carefully: this is the description for resp.name: response variable name (character). The species name.
3. An assertion in BIOMOD_FormatingData would have saved me an hour or two. But note that a naive check like is.character(resp.name) wouldn't work in this case, because once the formula is made it isn't a character anymore.
4. Adding more diagnostic information in your error messages saves people time. If the generated formula would have been printed as well then I would probably have noticed the issue directly.
5. Libraries make you win time, but you lose some as well.

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