Package: biomod2 4.2-6-2

Maya Gueguen

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 visualization tools are also available within the package.

Authors:Wilfried Thuiller [aut], Damien Georges [aut], Maya Gueguen [aut, cre], Robin Engler [aut], Frank Breiner [aut], Bruno Lafourcade [aut], Remi Patin [aut], Helene Blancheteau [aut]

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biomod2.pdf |biomod2.html✨
biomod2/json (API)

# Install 'biomod2' in R:
install.packages('biomod2', repos = c('https://biomodhub.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/biomodhub/biomod2/issues

Datasets:

On CRAN:

13.64 score 88 stars 7 packages 476 scripts 3.9k downloads 113 mentions 79 exports 48 dependencies

Last updated 2 hours agofrom:59fa1ead3a. Checks:OK: 1 NOTE: 5 ERROR: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 21 2024
R-4.5-winNOTENov 21 2024
R-4.5-linuxNOTENov 21 2024
R-4.4-winNOTENov 21 2024
R-4.4-macNOTENov 21 2024
R-4.3-winNOTENov 21 2024
R-4.3-macERRORNov 21 2024

Exports:.transform_model.as.col.transform.outputs.listBinaryTransformationBIOMOD_CrossValidationBIOMOD_EnsembleForecastingBIOMOD_EnsembleModelingBIOMOD_FormatingDataBIOMOD_LoadModelsBIOMOD_ModelingBIOMOD_ModelingOptionsBIOMOD_PresenceOnlyBIOMOD_ProjectionBIOMOD_RangeSizeBIOMOD_TuningBIOMOD.formated.dataBIOMOD.formated.data.PABIOMOD.options.datasetBIOMOD.options.defaultbm_BinaryTransformationbm_CalculateStatbm_CrossValidationbm_CrossValidation_blockbm_CrossValidation_envbm_CrossValidation_kfoldbm_CrossValidation_randombm_CrossValidation_stratbm_CrossValidation_user.definedbm_FindOptimStatbm_MakeFormulabm_ModelingOptionsbm_PlotEvalBoxplotbm_PlotEvalMeanbm_PlotRangeSizebm_PlotResponseCurvesbm_PlotVarImpBoxplotbm_PseudoAbsencesbm_PseudoAbsences_diskbm_PseudoAbsences_randombm_PseudoAbsences_srebm_PseudoAbsences_user.definedbm_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.levelsshowsresummaryvariables_importancezzz_bm

Dependencies:abindclicodetoolscolorspacedplyrfansifarverforeachgbmgenericsggplot2gluegtableisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigplyrPresenceAbsencepROCR6RColorBrewerRcppreshapereshape2rlangrpartscalesspstringistringrsurvivalterratibbletidyselectutf8vctrsviridisLitewithr

Cross-validation

Rendered fromvignette_crossValidation.Rmdusingknitr::knitron Nov 21 2024.

Last update: 2024-09-12
Started: 2024-02-14

Data preparation

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Last update: 2024-09-12
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Main functions

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Modeling Options

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News

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Presentation

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Pseudo-absences

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Secondary functions

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Variability in results

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Videos

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Vignette Abundance

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Readme and manuals

Help Manual

Help pageTopics
Bioclimatic variables for SDM based on current conditionbioclim_current
Bioclimatic variables for SDM based on future conditionbioclim_future
Project ensemble species distribution models onto new environmentBIOMOD_EnsembleForecasting
Create and evaluate an ensemble set of models and predictionsBIOMOD_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 modelsBIOMOD_Modeling
Project a range of calibrated species distribution models onto new environmentBIOMOD_Projection
Analyze the range size differences between projections of species distribution modelsBIOMOD_RangeSize BIOMOD_RangeSize,data.frame,data.frame-method BIOMOD_RangeSize,SpatRaster,SpatRaster-method
'BIOMOD_EnsembleModeling()' output object classBIOMOD.ensemble.models.out BIOMOD.ensemble.models.out-class show,BIOMOD.ensemble.models.out-method
'BIOMOD_FormatingData()' output object classBIOMOD.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 classBIOMOD.models.options BIOMOD.models.options-class print,BIOMOD.models.options-method show,BIOMOD.models.options-method
'BIOMOD_Modeling()' output object classBIOMOD.models.out BIOMOD.models.out-class show,BIOMOD.models.out-method
'bm_ModelingOptions' output object classBIOMOD.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 classBIOMOD.options.default BIOMOD.options.default,character,character-method BIOMOD.options.default-class
'BIOMOD_Projection()' output object classBIOMOD.projection.out BIOMOD.projection.out-class plot,BIOMOD.projection.out,missing-method show,BIOMOD.projection.out-method
'BIOMOD_Modeling' and 'BIOMOD_EnsembleModeling' output object classBIOMOD.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 EMmean_biomod2_model-class EMmedian_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 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 thresholdbm_BinaryTransformation bm_BinaryTransformation,data.frame-method bm_BinaryTransformation,matrix-method bm_BinaryTransformation,numeric-method bm_BinaryTransformation,SpatRaster-method
Build cross-validation tablebm_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 methodbm_CalculateStat bm_FindOptimStat get_optim_value
Standardized formula makerbm_MakeFormula
Configure the modeling options for each selected modelbm_ModelingOptions
Plot boxplot of evaluation scoresbm_PlotEvalBoxplot
Plot mean evaluation scoresbm_PlotEvalMean
Plot species range changebm_PlotRangeSize
Plot response curvesbm_PlotResponseCurves
Plot boxplot of variables importancebm_PlotVarImpBoxplot
Select pseudo-absencesbm_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
Loop to compute all single species distribution modelsbm_RunModel bm_RunModelsLoop
Sample binary vectorbm_SampleBinaryVector
Sample all levels of a factorial variablebm_SampleFactorLevels bm_SampleFactorLevels.data.frame bm_SampleFactorLevels.raster
Surface Range Envelopebm_SRE
Tune models parametersbm_Tuning
Variables' importance calculationbm_VariablesImportance
Presence-Absence data to build test SDMDataSpecies
Functions to extract informations from 'biomod2_model' objectsgetters.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' objectsfree 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' objectsload_stored_object load_stored_object,BIOMOD.stored.data-method load_stored_object,BIOMOD.stored.SpatRaster-method
Single models package and functionsModelsTable
Bigboss pre-defined parameter values for single modelsOptionsBigboss
'plot' method for 'BIOMOD.formated.data' object classplot,BIOMOD.formated.data,missing-method
Functions to get predictions from 'biomod2_model' objectspredict,biomod2_model-method predict.biomod2_model predict.bm
Functions to get predictions from 'biomod2_ensemble_model' objectspredict.em
'summary' method for 'BIOMOD.formated.data' object classsummary,BIOMOD.formated.data-method