scen

A <code>stars</code> object with bioclimatic variables (bio1, bio4 and bio12) and four future scenarios for
the Parana state in Brazil. Data from MIROC6 GCM from WorldClim 2.1 at 10 arc-min resolution.

datasets

Use machine learning algorithms and advanced geographic information system tools to
build Species Distribution Modeling in a extensible and modern fashion.

Luíz Esser

caretSDM

Build Species Distribution Modeling using 'caret'

Dayani Bailly

Edivando Couto

José Hilário Delconte Ferreira

Reginaldo Ré

Valéria Batista

Luíz Fernando Esser

scen function

## `scen`
A <code>stars</code> with 4 attribute and 3 bands:<dl>
 <dt>ca_ssp245_2090</dt>
<dd>Intermediate scenario for the year 2090 and GCM CanESM5</dd> <dt>ca_ssp585_2090</dt>
<dd>Extreme scenario for the year 2090 and GCM CanESM5</dd> <dt>mi_ssp245_2090</dt>
<dd>Intermediate scenario for the year 2090 and GCM MIROC6</dd> <dt>mi_ssp585_2090</dt>
<dd>Extreme scenario for the year 2090 and GCM MIROC6</dd> <dt>bio1</dt>
<dd>Annual Mean Temperature</dd> <dt>bio4</dt>
<dd>Temperature Seasonality</dd> <dt>bio12</dt>
<dd>Annual Precipitation</dd>
</dl>

Format

Bioclimatic Variables — scen

## `scen`
A <code>stars</code> with 4 attribute and 3 bands:<dl>
 <dt>ca_ssp245_2090</dt>
<dd>Intermediate scenario for the year 2090 and GCM CanESM5</dd>

 <dt>ca_ssp585_2090</dt>
<dd>Extreme scenario for the year 2090 and GCM CanESM5</dd>

 <dt>mi_ssp245_2090</dt>
<dd>Intermediate scenario for the year 2090 and GCM MIROC6</dd>

 <dt>mi_ssp585_2090</dt>
<dd>Extreme scenario for the year 2090 and GCM MIROC6</dd>

 <dt>bio1</dt>
<dd>Annual Mean Temperature</dd>

 <dt>bio4</dt>
<dd>Temperature Seasonality</dd>

 <dt>bio12</dt>
<dd>Annual Precipitation</dd>


</dl>

scen: Bioclimatic Variables

Description

Usage

Arguments

Format