The package ‘SSDM’ offers a user-friendly interface built with the
web application framework for R Shiny. The graphical user interface is
launched with the function gui
.
The interface has three tabs on the left, appearring successively:
Load
to load datasets or previous models and preview the
data, Modelling
to specify, train/test and save models, and
Results
to view the results and compare the
performances.
The Load
tab allows to load a new dataset or a
previously saved model. Pop-up windows for data selection
contains a link toward example raw data in the drop down
menu.
Top-left panel allows to load environmental variables through rasters. Don’t forget to specify which variable should be considered as a categorical variable.
Second panel allows to load occurrences through csv or txt files. Don’t forget to specify raw data formatting.
The Modelling
tab proposes three types of models:
individual species distribution model (SDM), ensemble species
distribution model (ESDM), or stacked species distribution model (SSDM).
The Modelling
tab contains three sub-tabs offering
different levels of parameterization according to the user’s level of
expertise: (1) Basic
to select the model algorithm(s), the
number of runs per model algorithm, the model evaluation metric(s), and
the methods to be used to map diversity and endemism; (2)
Intermediate
to set pseudo-absence selection (number and
strategy), the cross-validation method, the metric used to estimate the
relative contribution of environmental variables, the ESDM consensus
method, and the SSDM stacking method; and (3) Advanced
to
set algorithm parameters.
The Results
tab gives maps and graphs summurizing the
results at stack and species levels: model maps (species habitat
suitability, species richness and endemism), relative contribution of
environmental variables, model accuracy assessment, and
between-algorithms correlation.
The interface includes a panel to save result maps in GeoTIFF format (.tif) compatible with most GIS softwares, and other numerical results as comma separated values (.csv) files.