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News3 days ago
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
Auxiliary functions2 months ago
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
Main functions: abundance data2 months ago
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
Main functions: binary data2 months ago
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
Videos - biomod24 months ago
biomod2 team videos | Tutorial 2 - v4.3-4 - part 1 | Tutorial 1 - v4.2-6
Videos - ENM 20204 months ago
2020: Ecological Niche Modeling course | Introduction to biomod2 package | Modeling single species | Modeling multiple species | biomod2 specificities (pseudo-absences, variability) | Interface (package ShinyBiomod)
Cross-validation6 months ago
Definition | How to split data ? - Methods | Calibration / Validation - Evaluation | Specifications | References
Modeling Options6 months ago
How it works ? | Model ID name | Set modeling options | Default | Bigboss | Tuned | User-defined
Presentation6 months ago
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
Pseudo-absences6 months ago
Definition | How to select them ? - Methods | How to select them ? - Barbet-Massin et al. 2012
Data preparation2 years ago
Small preliminary questions | Observations & Explanatory variables | Geographical distribution | Environmental distribution | Modeling choices
Variability in results2 years ago
Definition | Variability - within the evaluation / importance of variables | Variability - within the predictions