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The goal of intSDM is to assist users in creating a reproducible workflow for large-scale integrated species distribution models. The package does this by providing the tools and methods to obtain species’ occurrence data from GBIF and environmental covariates from WorldClim. The package then estimates the integrated species distribution model using a Bayesian framework with the integrated nested Laplace approximation method.


You can install the development version of this package from GitHub with:


or directly through CRAN:



The package contains two main functions: startWorkflow which initializes the workflow, and sdmWorkflow, which estimates one of the specified outcomes of the workflow. startWorkflow produces an R6, which has a multitude of different slot functions to help customize the workflow. These include:

Function name Function use
.$plot() Plot data and other objects required for the model.
.$addStructured() Add data not available on GBIF.
.$addMesh() Create an inla.mesh object.
.$addGBIF() Add data from GBIF.
.$addArea() Specify sampling domain.
.$addCovariates() Add spatial covariates.
.$crossValidation() Specify the cross-validation method.
.$modelOptions() Add R-INLA, inlabruand PointedSDMs options.
.$specifySpatial() Add penalizing complexity priors to the spatial effects.
.$biasFields() Specify an additional spatial effect for a dataset.
.$workflowOutput() Specify the output of the workflow.
.$obtainMeta() Obtain metadata for the occurrence records.

An example of the package in-use is provided as a vignette within the package.