---
title: "Presentation"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Presentation}
  %\VignetteEngine{knitr::knitr}
  %\VignetteEncoding{UTF-8}
---

<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css" />


*To follow **biomod2** evolution of organization and features, the presentation below details the different steps and modules of the package.*

<br/><br/>

<div style="text-align:center;">
<embed src="pictures/biomod2_presentation.workflow_05_2024.pdf" width="900" height="700" type="application/pdf" allowfullscreen webkitallowfullscreen>
</embed>
</div>

<br/><br/>

<div align="center">
<p><a href="https://biomodhub.github.io/biomod2/articles/pictures/SCHEMA_BIOMOD2_WORKFLOW_functions.pdf">Download pdf of WORKFLOW GRAPHIC <i class="fas fa-download"></i></a></p>
<p><a href="https://biomodhub.github.io/biomod2/articles/pictures/biomod2_presentation.workflow_05_2024.pdf">Download pdf of PRESENTATION <i class="fas fa-download"></i></a></p>
</div>



#### <i class="fa-solid fa-list-check"></i> Data formatting : [BIOMOD_FormatingData](../reference/BIOMOD_FormatingData.html)

- **Formatting data** : combine observations, coordinates and explanatory variables, <br/>and sample pseudo-absences for presence-only data (*through [bm_PseudoAbsences](../reference/bm_PseudoAbsences.html)*)

- **Cross-validation** : create calibration / validation datasets (*through [bm_CrossValidation](../reference/bm_CrossValidation.html)*)

- **Modeling options** (*with the help of [ModelsTable](../reference/ModelsTable.html) and [OptionsBigboss](../reference/OptionsBigboss.html) datasets*)
    + Define specific options for single models (*through [bm_ModelingOptions](../reference/bm_ModelingOptions.html)*)
    + And tune with your own data (*through [bm_Tuning](../reference/bm_Tuning.html)*)

#### <i class="fa-solid fa-virus"></i> Single models : [BIOMOD_Modeling](../reference/BIOMOD_Modeling.html)

- **Evaluation** : transform predicted probabilities in binary values (*through [bm_BinaryTransformation](../reference/bm_BinaryTransformation.html)*), <br/>and compute evaluation metrics (*through [bm_FindOptimStat](../reference/bm_FindOptimStat.html)*)

- **Variables' importance** : estimate the impact of each explanatory variable on predictions (*through [bm_VariablesImportance](../reference/bm_VariablesImportance.html)*)
    
#### <i class="fa-solid fa-viruses"></i> Ensemble models : [BIOMOD_EnsembleModeling](../reference/BIOMOD_EnsembleModeling.html)

- Filter single models based on one evaluation metric
- Combine them according to different combinations
- And build ensemble models
    
#### <i class="fas fa-chart-bar"></i> Exploring outputs

- Evaluation : [bm_PlotEvalMean](../reference/bm_PlotEvalMean.html), [bm_PlotEvalBoxplot](../reference/bm_PlotEvalBoxplot.html)
- Variables' importance : [bm_PlotVarImpBoxplot](../reference/bm_PlotVarImpBoxplot.html)
- Response curves : [bm_PlotResponseCurves](../reference/bm_PlotResponseCurves.html)

#### <i class="fa-solid fa-earth-europe"></i> Projecting models : [BIOMOD_Projection](../reference/BIOMOD_Projection.html), [BIOMOD_EnsembleForecasting](../reference/BIOMOD_BIOMOD_EnsembleForecasting.html)

- Project models onto new conditions
- Transform predicted probabilities in binary values (*through [bm_BinaryTransformation](../reference/bm_BinaryTransformation.html)*)

#### <i class="fa-solid fa-ruler-combined"></i> Species range change : [BIOMOD_RangeSize](../reference/BIOMOD_RangeSize.html)