intSDM: Reproducible Integrated Species Distribution Models Across Norway using 'INLA'

Integration of disparate datasets is needed in order to make efficient use of all available data and thereby address the issues currently threatening biodiversity. Data integration is a powerful modeling framework which allows us to combine these datasets together into a single model, yet retain the strengths of each individual dataset. We therefore introduce the package, 'intSDM': an R package designed to help ecologists develop a reproducible workflow of integrated species distribution models, using data both provided from the user as well as data obtained freely online. An introduction to data integration methods is discussed in Issac, Jarzyna, Keil, Dambly, Boersch-Supan, Browning, Freeman, Golding, Guillera-Arroita, Henrys, Jarvis, Lahoz-Monfort, Pagel, Pescott, Schmucki, Simmonds and O’Hara (2020) <doi:10.1016/j.tree.2019.08.006>.

Version: 2.0.2
Depends: R (≥ 3.5), ggplot2, terra, sf, stats, PointedSDMs, methods
Imports: R6, geodata, inlabru (≥ 2.3.1), giscoR, blockCV, rgbif, tidyterra
Suggests: viridis, INLA (≥ 21.08.31), ggpolypath, R.utils, lwgeom, spatstat, RColorBrewer, knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2023-10-20
Author: Philip Mostert [aut, cre], Angeline Bruls [aut], Ragnhild {Bjørkås} [aut], Wouter Koch [aut], Ellen Martin [aut]
Maintainer: Philip Mostert <philip.s.mostert at>
License: GPL (≥ 3)
NeedsCompilation: no
Materials: README NEWS
CRAN checks: intSDM results


Reference manual: intSDM.pdf
Vignettes: PennsylvaniaWarbler
Example creating a reproducible workflow for red listed vascular plants


Package source: intSDM_2.0.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): intSDM_2.0.2.tgz, r-oldrel (arm64): intSDM_2.0.2.tgz, r-release (x86_64): intSDM_2.0.2.tgz, r-oldrel (x86_64): intSDM_2.0.2.tgz
Old sources: intSDM archive


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