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 OâHara (2020) <doi:10.1016/j.tree.2019.08.006>.
Version: 2.1.1 Depends: R (≥ 3.5), ggplot2, terra, sf, stats, PointedSDMs (≥ 2.1.0), methods Imports: R6, geodata, fmesher, inlabru (≥ 2.3.1), giscoR, blockCV, rgbif, tidyterra, units Suggests: viridis, INLA (≥ 21.08.31), R.utils, lwgeom, spatstat, RColorBrewer, knitr, rmarkdown, testthat (≥ 3.0.0) Published: 2025-01-13 DOI: 10.32614/CRAN.package.intSDM Author: Philip Mostert [aut, cre], Angeline Bruls [aut], Ragnhild {BjørkÃ¥s} [aut], Wouter Koch [aut], Ellen Martin [aut] Maintainer: Philip Mostert <philip.s.mostert at ntnu.no> License: GPL (≥ 3) NeedsCompilation: no Additional_repositories: https://inla.r-inla-download.org/R/testing/ Materials: README NEWS CRAN checks: intSDM results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=intSDM to link to this page.
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