Luíz Fernando Esser
caretSDM
is a under development R package that uses the
powerful caret
package as the main engine to obtain Species
Distribution Models. As caret
is a packaged turned to build
machine learning models, caretSDM
has a strong focus on
this approach.
You can install the development version of caretSDM from GitHub with:
install.packages("devtools")
::install_github("luizesser/caretSDM") devtools
The package is also available on CRAN. Users are able to install it using the following code:
install.packages("caretSDM")
caretSDM is vastly documented and has included some objects that can guide your data management. If some of your data or code seem to be wrong, try to take a look at those objects or the articles in the website:
Objects
bioc
Bioclimatic variables for current scenario in
stars class.
rivs
Hydrological variables for current scenario in
sf class.
occ
Araucaria angustifolia occurrence data
as a dataframe.
salm
Salminus brasiliensis occurrence data
as a dataframe.
parana
Shapefile to use in sdm_area
in
Simple Feature class.
scen
Bioclimatic variables for future scenarios in
stars class.
algorithms
Dataframe with characteristics from every
algorithm available in caretSDM.
Articles
caretSDM Workflow for Species Distribution Modeling
is the main vignette for terrestrial species modeling, where we model
the tree species Araucaria angustifolia.
Modeling Species Distributions in Continental Water Bodies
is the main vignette for continental aquatic species modeling, where we
model the fish species Salminus brasiliensis.
Concatenate functions in caretSDM
shows how to build
compact scripts, which is very useful to run your first tests.