Development updates | 2026 | Bugfix | 4.3-4-4 Clean version (2026-01-22) | 2025 | 4.3-4 DNN model (2025-06-04) | 4.3-3 Multiclass datatype (2025-05-20) | Major Changes | 4.3-2 Report (2025-03-11) | 4.3-1 RangeSize (2025-03-03) | 4.3-0 Abundance (2025-01-30) | Minor Changes | 2024 | 4.2-6 RFd and some tuning (2024-07-22) | 4.2-5 Modeling options and Tuning (2024-05-02) | 2023 | 4.2-5 Modeling options and Tuning (2023-09-12) | 4.2-4 XGBOOST (2023-06-21) | 4.2-3 Cross-Validation and Pseudo-Absences (2023-05-09) | Internal | 4.2-2 Improvement patch (2023-01-13) | Internal Changes | 2022 | 4.2-1 Bugfix patch | 4.2-0 Terra Update | 4.1-3 | 4.1-2 (2022-09-29) | Major changes | Minor changes | Bug Fix | Miscellaneous | 4.1-1 (2022-08-30) | 4.1 (2022-07-12) | 4.0 (2022-03-01) | 2021 | 3.5-3 (2021-11-02) | 3.5-2 (2021-10-18) | 2018-2019 | 3.3-20 (2019-03-05) | 3.3-18 (2018-07-04) | 3.3-17 (2018-04-23) | 2016 | 3.3-6 (2016-01-14) | 3.3-5 (2016-01-04) | 2015 | 3.3-4 (2015-11-04) | 3.3-3 (2015-10-27) | 3.3-00 (2015-10-05) | 3.2-00 (2015-07-28) | 2014 | 3.1-59 (2014-10-23) | 3.1-53 (2014-08-06) | 3.1-44 (2014-05-20) | 3.1-43 (2014-05-20) | 3.1-42 (2014-05-19) | 2013 | 3.1-17 (2013-10-23) | 3.1-1 (2013-09-04) | 3.0.2 (2013-07-23) | 3.0.0 (2013-07-01) | 2.1.37 (2013-06-12) | 2.1.32 (2013-05-30) | 2.1.13 (2013-03-06) | 2.1.12 (2013-03-04) | 2.1.9 (2013-02-28) | 2.1.9 (2013-02-27) | 2.1.8 (2013-02-25) | 2.1.0 (2013-02-21) | 2.0.11 (2013-02-18) | 2.0.9 (2013-02-15) | 2.0.8 (2013-02-14) | 2.0.7 (2013-02-12) | 2.0.3 (2013-01-18) | 2.0.0 (2013-01-17) | Year 0 | 1.x.x
Package: biomod2 4.3-4-7
Maya Guéguen
biomod2: Ensemble Platform for Species Distribution Modeling
Functions for species distribution modeling, calibration and evaluation, ensemble of models, ensemble forecasting and visualization. The package permits to run consistently up to 10 single models on a presence/absences (resp presences/pseudo-absences) dataset and to combine them in ensemble models and ensemble projections. Some bench of other evaluation and visualisation tools are also available within the package.
Authors:
biomod2_4.3-4-7.tar.gz
biomod2_4.3-4-7.zip(r-4.7)biomod2_4.3-4-7.zip(r-4.6)biomod2_4.3-4-7.zip(r-4.5)
biomod2_4.3-4-7.tgz(r-4.6-any)biomod2_4.3-4-7.tgz(r-4.5-any)
biomod2_4.3-4-7.tar.gz(r-4.7-any)biomod2_4.3-4-7.tar.gz(r-4.6-any)
biomod2_4.3-4-7.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
biomod2/json (API)
| # Install 'biomod2' in R: |
| install.packages('biomod2', repos = c('https://biomodhub.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/biomodhub/biomod2/issues
Pkgdown/docs site:https://biomodhub.github.io
Datasets:
- bioclim_current - Bioclimatic variables for SDM based on current condition
- bioclim_future - Bioclimatic variables for SDM based on future condition
- DataSpecies - Presence-Absence data to build test SDM
- DataSTOC - Abundance to build test SDM
- ModelsTable - Single models package and functions
- ODMAP - ODMAP empty table
- OptionsBigboss - Bigboss pre-defined parameter values for single models
Last updated from:32fa1f3fa4. Checks:7 WARNING, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | WARNING | 476 | ||
| source / vignettes | OK | 415 | ||
| linux-release-x86_64 | WARNING | 471 | ||
| macos-release-arm64 | WARNING | 208 | ||
| macos-oldrel-arm64 | WARNING | 273 | ||
| windows-devel | WARNING | 357 | ||
| windows-release | WARNING | 357 | ||
| windows-oldrel | WARNING | 338 | ||
| wasm-release | OK | 291 |
Exports:.transform_model.as.col.transform.outputs.listBinaryTransformationBIOMOD_CrossValidationBIOMOD_EnsembleForecastingBIOMOD_EnsembleModelingBIOMOD_FormatingDataBIOMOD_LoadModelsBIOMOD_ModelingBIOMOD_ModelingOptionsBIOMOD_PresenceOnlyBIOMOD_ProjectionBIOMOD_RangeSizeBIOMOD_ReportBIOMOD_TuningBIOMOD.formated.dataBIOMOD.formated.data.PABIOMOD.options.datasetBIOMOD.options.defaultbm_BinaryTransformationbm_CalculateStatAbunbm_CalculateStatBinbm_CrossValidationbm_CrossValidation_blockbm_CrossValidation_envbm_CrossValidation_kfoldbm_CrossValidation_randombm_CrossValidation_stratbm_CrossValidation_user.definedbm_FindOptimStatbm_MakeFormulabm_ModelAnalysisbm_ModelingOptionsbm_PlotEvalBoxplotbm_PlotEvalMeanbm_PlotRangeSizebm_PlotResponseCurvesbm_PlotVarImpBoxplotbm_PseudoAbsencesbm_PseudoAbsences_diskbm_PseudoAbsences_randombm_PseudoAbsences_srebm_PseudoAbsences_user.definedbm_RangeSizebm_RunModelbm_RunModelsLoopbm_SampleBinaryVectorbm_SampleFactorLevelsbm_SREbm_Tuningbm_VariablesImportancecalculate.statFind.Optim.Statfreeget_built_modelsget_calib_linesget_eval_dataget_evaluationsget_formal_dataget_formal_modelget_kept_modelsget_optim_valueget_optionsget_predictionsget_projected_modelsget_scaling_modelget_species_dataget_variables_importancegetStatOptimValueload_stored_objectmakeFormulamodels_scores_graphplotpredictprintProbDensFuncresponse.plot2sample.factor.levelsset_new_dirnameshowsresummaryvariables_importancezzz_bm
Dependencies:abindclicodetoolscpp11dplyrfarverforeachgbmgenericsggplot2gluegtableisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixpillarpkgconfigplyrPresenceAbsencepROCR6RColorBrewerRcppreshapereshape2rlangrpartS7scalesspstringistringrsurvivalterratibbletidyselectutf8vctrsviridisLitewithr
News
Last update: 2026-07-01
Started: 2022-03-01
Auxiliary functions
Small code examples | Prepare data | Vector data | Explanatory variables & Observations | Auxiliary functions : vector data | Generate calibration / evaluation datasets | Find optimal threshold for a specific evaluation metric | From continuous to binary / filtered vector | Auxiliary functions : explanatory variables | Generate automatic formula | Sample all factor levels | Compute Species Range Envelop model | Compute variables importance | Auxiliary functions : biomod2 data | Generate pseudo-absence datasets | Retrieve modeling options
Last update: 2026-05-07
Started: 2025-12-03
Main functions: abundance data
Complete code example | Load dataset and variables | Prepare data & parameters | Format data (observations & explanatory variables) | Cross-validation datasets | Retrieve modeling options | Run modeling | Single models | Ensemble models | Project models | Compare range sizes | Export a report
Last update: 2026-05-07
Started: 2025-12-03
Main functions: binary data
Complete code example | Load dataset and variables | Prepare data & parameters | Format data (observations & explanatory variables) | Pseudo-absences extraction | Cross-validation datasets | Retrieve modeling options | Run modeling | Single models | Ensemble models | Project models | Compare range sizes | Export a report
Last update: 2026-05-07
Started: 2025-12-03
Videos - biomod2
biomod2 team videos | Tutorial 2 - v4.3-4 - part 1 | Tutorial 1 - v4.2-6
Last update: 2026-02-27
Started: 2026-02-27
Videos - ENM 2020
2020: Ecological Niche Modeling course | Introduction to biomod2 package | Modeling single species | Modeling multiple species | biomod2 specificities (pseudo-absences, variability) | Interface (package ShinyBiomod)
Last update: 2026-02-27
Started: 2026-02-27
Cross-validation
Definition | How to split data ? - Methods | Calibration / Validation - Evaluation | Specifications | References
Last update: 2026-01-15
Started: 2024-02-14
Modeling Options
How it works ? | Model ID name | Set modeling options | Default | Bigboss | Tuned | User-defined
Last update: 2026-01-15
Started: 2024-02-14
Presentation
Data formatting : BIOMOD_FormatingData | Single models : BIOMOD_Modeling | Ensemble models : BIOMOD_EnsembleModeling | Exploring outputs | Projecting models : BIOMOD_Projection, BIOMOD_EnsembleForecasting | Species range change : BIOMOD_RangeSize | Report : BIOMOD_Report
Last update: 2026-01-15
Started: 2024-05-06
Pseudo-absences
Definition | How to select them ? - Methods | How to select them ? - Barbet-Massin et al. 2012
Last update: 2026-01-15
Started: 2022-03-01
Data preparation
Small preliminary questions | Observations & Explanatory variables | Geographical distribution | Environmental distribution | Modeling choices
Last update: 2024-09-12
Started: 2023-09-12
Variability in results
Definition | Variability - within the evaluation / importance of variables | Variability - within the predictions
Last update: 2024-09-12
Started: 2022-07-13
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Bioclimatic variables for SDM based on current condition | bioclim_current |
| Bioclimatic variables for SDM based on future condition | bioclim_future |
| Project ensemble species distribution models onto new environment | BIOMOD_EnsembleForecasting |
| Create and evaluate an ensemble set of models and predictions | BIOMOD_EnsembleModeling |
| Format input data, and select pseudo-absences if wanted, for usage in 'biomod2' | BIOMOD_FormatingData |
| Load species distribution models built with 'biomod2' | BIOMOD_LoadModels |
| Run a range of species distribution models | BIOMOD_Modeling |
| Project a range of calibrated species distribution models onto new environment | BIOMOD_Projection |
| Analyze the range size differences between projections of species distribution models | BIOMOD_RangeSize |
| Produce summary outputs from a simulation folder | BIOMOD_Report |
| 'BIOMOD_EnsembleModeling()' output object class | BIOMOD.ensemble.models.out BIOMOD.ensemble.models.out-class show,BIOMOD.ensemble.models.out-method |
| 'BIOMOD_FormatingData()' output object class | BIOMOD.formated.data BIOMOD.formated.data,data.frame,ANY-method BIOMOD.formated.data,numeric,data.frame-method BIOMOD.formated.data,numeric,matrix-method BIOMOD.formated.data,numeric,SpatRaster-method BIOMOD.formated.data-class show,BIOMOD.formated.data-method |
| 'BIOMOD_FormatingData()' output object class (with pseudo-absences) | BIOMOD.formated.data.PA BIOMOD.formated.data.PA,numeric,data.frame-method BIOMOD.formated.data.PA,numeric,SpatRaster-method BIOMOD.formated.data.PA-class |
| 'bm_ModelingOptions' output object class | BIOMOD.models.options BIOMOD.models.options-class print,BIOMOD.models.options-method show,BIOMOD.models.options-method |
| 'BIOMOD_Modeling()' output object class | BIOMOD.models.out BIOMOD.models.out-class show,BIOMOD.models.out-method |
| 'bm_ModelingOptions' output object class | BIOMOD.options.dataset BIOMOD.options.dataset,character-method BIOMOD.options.dataset-class print,BIOMOD.options.dataset-method show,BIOMOD.options.dataset-method |
| 'bm_ModelingOptions' output object class | BIOMOD.options.default BIOMOD.options.default,character,character-method BIOMOD.options.default-class |
| 'BIOMOD_Projection()' output object class | BIOMOD.projection.out BIOMOD.projection.out-class plot,BIOMOD.projection.out,missing-method show,BIOMOD.projection.out-method |
| 'BIOMOD_RangeSize()' output object class | BIOMOD.rangesize.out BIOMOD.rangesize.out-class |
| 'BIOMOD_Modeling' and 'BIOMOD_EnsembleModeling' output object class | BIOMOD.stored.data BIOMOD.stored.data-class BIOMOD.stored.data.frame-class BIOMOD.stored.files-class BIOMOD.stored.formated.data-class BIOMOD.stored.models.out-class BIOMOD.stored.options-class BIOMOD.stored.SpatRaster-class |
| Ensemble model output object class (when running 'BIOMOD_EnsembleModeling()') | biomod2_ensemble_model biomod2_ensemble_model-class EMca_biomod2_model-class EMci_biomod2_model-class EMcv_biomod2_model-class EMfreq_biomod2_model-class EMmean_biomod2_model-class EMmedian_biomod2_model-class EMmode_biomod2_model-class EMwmean_biomod2_model-class show,biomod2_ensemble_model-method |
| Single model output object class (when running 'BIOMOD_Modeling()') | ANN_biomod2_model-class biomod2_model biomod2_model-class CTA_biomod2_model-class DNN_biomod2_model-class FDA_biomod2_model-class GAM_biomod2_model-class GBM_biomod2_model-class GLM_biomod2_model-class MARS_biomod2_model-class MAXENT_biomod2_model-class MAXNET_biomod2_model-class RFd_biomod2_model-class RF_biomod2_model-class show,biomod2_model-method SRE_biomod2_model-class XGBOOST_biomod2_model-class |
| Convert probability values into binary values using a predefined threshold | bm_BinaryTransformation bm_BinaryTransformation,data.frame-method bm_BinaryTransformation,matrix-method bm_BinaryTransformation,numeric-method bm_BinaryTransformation,SpatRaster-method |
| Build cross-validation table | bm_CrossValidation bm_CrossValidation_block bm_CrossValidation_block,BIOMOD.formated.data-method bm_CrossValidation_block,BIOMOD.formated.data.PA-method bm_CrossValidation_env bm_CrossValidation_env,BIOMOD.formated.data-method bm_CrossValidation_env,BIOMOD.formated.data.PA-method bm_CrossValidation_kfold bm_CrossValidation_kfold,BIOMOD.formated.data-method bm_CrossValidation_kfold,BIOMOD.formated.data.PA-method bm_CrossValidation_random bm_CrossValidation_random,BIOMOD.formated.data-method bm_CrossValidation_random,BIOMOD.formated.data.PA-method bm_CrossValidation_strat bm_CrossValidation_strat,BIOMOD.formated.data-method bm_CrossValidation_strat,BIOMOD.formated.data.PA-method bm_CrossValidation_user.defined bm_CrossValidation_user.defined,BIOMOD.formated.data-method bm_CrossValidation_user.defined,BIOMOD.formated.data.PA-method |
| Calculate the best score according to a given evaluation method | bm_CalculateStatAbun bm_CalculateStatAbund bm_CalculateStatBin bm_FindOptimStat get_optim_value |
| Standardized formula maker | bm_MakeFormula |
| Analyze the residuals of the single models | bm_ModelAnalysis |
| Configure the modeling options for each selected model | bm_ModelingOptions |
| Plot boxplot of evaluation scores | bm_PlotEvalBoxplot |
| Plot mean evaluation scores | bm_PlotEvalMean |
| Plot species range change | bm_PlotRangeSize |
| Plot response curves | bm_PlotResponseCurves |
| Plot boxplot of variables importance | bm_PlotVarImpBoxplot |
| Select pseudo-absences | bm_PseudoAbsences bm_PseudoAbsences_disk bm_PseudoAbsences_disk,ANY,SpatRaster-method bm_PseudoAbsences_disk,ANY,SpatVector-method bm_PseudoAbsences_random bm_PseudoAbsences_random,ANY,SpatRaster-method bm_PseudoAbsences_random,ANY,SpatVector-method bm_PseudoAbsences_sre bm_PseudoAbsences_sre,ANY,SpatRaster-method bm_PseudoAbsences_sre,ANY,SpatVector-method bm_PseudoAbsences_user.defined bm_PseudoAbsences_user.defined,ANY,SpatRaster-method bm_PseudoAbsences_user.defined,ANY,SpatVector-method |
| Analyze the range size differences between projections of species distribution models | bm_RangeSize bm_RangeSize,data.frame,data.frame-method bm_RangeSize,SpatRaster,SpatRaster-method |
| Loop to compute all single species distribution models | bm_RunModel bm_RunModelsLoop |
| Sample binary vector | bm_SampleBinaryVector |
| Sample all levels of a factorial variable | bm_SampleFactorLevels bm_SampleFactorLevels.data.frame bm_SampleFactorLevels.raster |
| Surface Range Envelope | bm_SRE |
| Tune models parameters | bm_Tuning |
| Variables' importance calculation | bm_VariablesImportance |
| Presence-Absence data to build test SDM | DataSpecies |
| Abundance to build test SDM | DataSTOC |
| Functions to extract informations from 'biomod2_model' objects | getters.bm get_formal_model get_formal_model,biomod2_model-method get_scaling_model get_scaling_model,biomod2_model-method |
| Functions to extract informations from 'BIOMOD.models.out', 'BIOMOD.projection.out' or 'BIOMOD.ensemble.models.out' objects | free free,BIOMOD.projection.out-method getters.out get_built_models get_built_models,BIOMOD.ensemble.models.out-method get_built_models,BIOMOD.models.out-method get_calib_lines get_calib_lines,BIOMOD.models.out-method get_evaluations get_evaluations,BIOMOD.ensemble.models.out-method get_evaluations,BIOMOD.models.out-method get_eval_data get_eval_data,BIOMOD.formated.data-method get_formal_data get_formal_data,BIOMOD.ensemble.models.out-method get_formal_data,BIOMOD.models.out-method get_kept_models get_kept_models,BIOMOD.ensemble.models.out-method get_options get_options,BIOMOD.models.out-method get_predictions get_predictions,BIOMOD.ensemble.models.out-method get_predictions,BIOMOD.models.out-method get_predictions,BIOMOD.projection.out-method get_projected_models get_projected_models,BIOMOD.projection.out-method get_species_data get_species_data,BIOMOD.formated.data-method get_species_data,BIOMOD.formated.data.PA-method get_variables_importance get_variables_importance,BIOMOD.ensemble.models.out-method get_variables_importance,BIOMOD.models.out-method |
| Functions to load 'BIOMOD.stored.data' objects | load_stored_object load_stored_object,BIOMOD.stored.data-method load_stored_object,BIOMOD.stored.SpatRaster-method |
| Single models package and functions | ModelsTable |
| ODMAP empty table | ODMAP |
| Bigboss pre-defined parameter values for single models | OptionsBigboss |
| 'plot' method for 'BIOMOD.formated.data' and 'BIOMOD.formated.data.PA' object class | plot,BIOMOD.formated.data,missing-method |
| Functions to get predictions from 'biomod2_model' objects | predict,biomod2_model-method predict.biomod2_model predict.bm |
| Functions to get predictions from 'biomod2_ensemble_model' objects | predict.em |
| Functions to change the place of the different biomod2 objects | setters set_new_dirname set_new_dirname,BIOMOD.ensemble.models.out-method set_new_dirname,BIOMOD.models.out-method set_new_dirname,BIOMOD.projection.out-method |
| 'summary' method for 'BIOMOD.formated.data' object class | summary,BIOMOD.formated.data-method |
