Introduction | Reading and plotting data | Generating block CV folds | Evaluating SDMs with block cross-validation: examples | Using blockCV with Random Forest model | Using blockCV in biomod2 package | References:

Introduction | Installation | Package data | Block cross-validation strategies | Spatial blocks | Spatial and environmental clustering | Leave-group-out cross-validation | Buffering LOO (also known as Spatial LOO) | Nearest Neighbour Distance Matching (NNDM) LOO | k-fold Nearest Neighbour Distance Matching (kNNDM) | Visualising the folds | Next steps | References:

Introduction | Prepare data and folds | Fold-quality summary | Environmental similarity diagnostics | Nearest-neighbour distance diagnostics | Choosing a candidate block size | References:

Introduction | Prepare the data | Create spatial folds | Fit a caret model | References

Correlation matrix | Density plots | Nearest-neighbour distance | Mapping species data | Plotting static map | Plotting interactive map

Introduction | Modeling all species with one modeling method - example | Evaluating the models | Creating target group background (TGB) sample | TGB example | References

Prepare the training data | Fit a down-sampled random forest | Plot univariate and bivariate response curves | Ensemble response curves