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TemporalModelR: Temporally Explicit Species Distribution Modelling

Increases the ease of implementing a temporally-explicit modeling methodology when building ecological niche and species distribution models. Provides functions to assist with three major steps of temporally-explicit models: (i) preprocessing species and environmental data and generating suitable background or pseudoabsence data, (ii) building a niche model and generating temporally-explicit predictions from that model, and (iii) model postprocessing to explore spatiotemporal trends in model predictions. Methodological and theoretical foundations are described in Ingenloff and Peterson (2021) <doi:10.1111/2041-210X.13564>, Franklin (2010, ISBN:9780521700023), Peterson et al. (2011, ISBN:9780691136882), Blonder (2018) <doi:10.1111/ecog.03187>, Senay et al. (2013) <doi:10.1371/journal.pone.0071218>, and Li and Zhang (2024) <doi:10.48550/arXiv.2404.05933>.

Version: 0.2.0
Depends: R (≥ 4.1)
Imports: deldir, graphics, grDevices, sf, stats, terra, tools, utils, exactextractr
Suggests: fastcpd, ggplot2, hypervolume, knitr, mgcv, randomForest, RColorBrewer, rmarkdown, scatterpie
Published: 2026-06-30
DOI: 10.32614/CRAN.package.TemporalModelR (may not be active yet)
Author: Connor Hughes ORCID iD [aut, cre], Mariana Castaneda-Guzman ORCID iD [aut], Luis E. Escobar ORCID iD [aut]
Maintainer: Connor Hughes <connorhughes926 at gmail.com>
BugReports: https://github.com/CJHughes926/TemporalModelR/issues
License: MIT + file LICENSE
URL: https://github.com/CJHughes926/TemporalModelR, https://cjhughes926.github.io/TemporalModelR/
NeedsCompilation: no
Language: en-US
Materials: README, NEWS
CRAN checks: TemporalModelR results

Documentation:

Reference manual: TemporalModelR.html , TemporalModelR.pdf
Vignettes: About the Example Dataset (source, R code)
Preprocessing temporally explicit data (source, R code)
Modeling with a GLM (source, R code)
Modeling with a GAM (source, R code)
Modeling with a Random Forest (source, R code)
Modeling with a Hypervolume (source, R code)
Post-processing predictions (source, R code)

Downloads:

Package source: TemporalModelR_0.2.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): TemporalModelR_0.2.0.tgz, r-oldrel (arm64): TemporalModelR_0.2.0.tgz, r-release (x86_64): TemporalModelR_0.2.0.tgz, r-oldrel (x86_64): TemporalModelR_0.2.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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