Package: intSDM 2.1.1.9000

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>.

Authors:Philip Mostert [aut, cre], Angeline Bruls [aut], Ragnhild {Bjørkås} [aut], Wouter Koch [aut], Ellen Martin [aut]

intSDM_2.1.1.9000.tar.gz
intSDM_2.1.1.9000.zip(r-4.7-any)intSDM_2.1.1.9000.zip(r-4.6-any)intSDM_2.1.1.9000.zip(r-4.5-any)
intSDM_2.1.1.9000.tgz(r-4.6-any)intSDM_2.1.1.9000.tgz(r-4.5-any)
intSDM_2.1.1.9000.tar.gz(r-4.7-any)intSDM_2.1.1.9000.tar.gz(r-4.6-any)
intSDM_2.1.1.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
intSDM/json (API)

# Install 'intSDM' in R:
install.packages('intSDM', repos = c('https://philipmostert.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/philipmostert/intsdm/issues

On CRAN:

Conda:

5.99 score 7 stars 31 scripts 460 downloads 5 exports 92 dependencies

Last updated from:796f76984d. Checks:8 OK, 1 ERROR. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK333
source / vignettesOK326
linux-releaseOK300
macos-releaseOK235
macos-oldrelERROR191
windows-develOK281
windows-releaseOK274
windows-oldrelOK279
wasm-releaseOK176

Exports:getPriorsobtainRichnesssdmWorkflowspecies_modelstartWorkflow

Dependencies:abindaskpassautomapbase64encblockCVclassclassIntclicountrycodecowplotcpp11crulcurldata.tableDBIdplyre1071farverfmesherFNNgenericsgeodataggplot2giscoRgluegstatgtablehttpcodehttrhttr2inlabruintervalsisobandjsonliteKernSmoothlabelinglatticelazyevallifecyclemagrittrMatrixMatrixModelsmimeoaiopensslpillarpkgconfigplyrPointedSDMsproxypurrrR.devicesR.methodsS3R.ooR.utilsR6rappdirsrasterRColorBrewerRcppreshapergbifrlangs2S7scalessfsftimespspacetimesplancsstarsstringistringrsysterratibbletidyrtidyselecttidyterratriebeardunitsurltoolsutf8vctrsviridisLitewhiskerwithrwkxml2xtszoo

intSDM: R package to produce species distribution models in a reproducible framework
Introduction | Workflow setup | Select area | Adding occurrence data | Adding covariate data | Metadata | Creating an fm_mesh_2d object | Specify priors | Bias field | Model options | Running workflow | Maps

Last update: 2026-06-10
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