add comma

15-eco.Rmd

@@ -456,7 +456,7 @@ task = mlr3spatiotempcv::as_task_regr_st(
 ```
 
 Using an `sf` object as the backend automatically provides the geometry information needed for the spatial partitioning later on.
-Additionally, we got rid of the columns `id` and `spri` since these variables should not be used as predictors in the modeling.
+Additionally, we got rid of the columns `id` and `spri`, since these variables should not be used as predictors in the modeling.
 Next, we go on to construct the a random forest\index{random forest} learner from the **ranger** package [@wright_ranger_2017].
 
 ```{r 15-eco-21}