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 4.3-4-8
Maya Guéguen
biomod2: Ensemble Platform for Species Distribution Modeling
Functions for species distribution modelling, to calibrate, evaluate, and project species-environment relationships across space and time using multiple modelling algorithms and ensemble forecasting. It accommodates diverse ecological data types (presence-only, presence-absence, counts, multi-class abundance, or relative/absolute abundance) within a unified modelling workflow which includes cross-validation schemes, pseudo-absence selection strategies, expanded model parametrization options, a dozen of algorithms, and tools for exploring and visualizing outputs.
Authors:
biomod2_4.3-4-8.tar.gz
biomod2_4.3-4-8.zip(r-4.7-any)biomod2_4.3-4-8.zip(r-4.6-any)biomod2_4.3-4-8.zip(r-4.5-any)
biomod2_4.3-4-8.tgz(r-4.6-any)biomod2_4.3-4-8.tgz(r-4.5-any)
biomod2_4.3-4-8.tar.gz(r-4.7-any)biomod2_4.3-4-8.tar.gz(r-4.6-any)
biomod2_4.3-4-8.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:11a4c0fe41. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 418 | ||
| source / vignettes | OK | 382 | ||
| linux-release | OK | 374 | ||
| macos-release | OK | 353 | ||
| macos-oldrel | OK | 268 | ||
| windows-devel | OK | 399 | ||
| windows-release | OK | 354 | ||
| windows-oldrel | OK | 342 | ||
| wasm-release | OK | 204 |
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: 2026-10-09
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 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 |
