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kuenm2: Detailed Development of Ecological Niche Models

A new set of tools to help with the development of detailed ecological niche models using multiple algorithms. Pre-modeling analyses and explorations can be done to prepare data. Model calibration (model selection) can be done by creating and testing models with several parameter combinations. Handy options for producing final models with transfers are included. Other tools to assess extrapolation risks and variability in model transfers are also available. Methodological and theoretical basis for the methods implemented here can be found in: Peterson et al. (2011) <https://www.degruyter.com/princetonup/view/title/506966>, Radosavljevic and Anderson (2014) <doi:10.1111/jbi.12227>, Peterson et al. (2018) <doi:10.1111/nyas.13873>, Cobos et al. (2019) <doi:10.7717/peerj.6281>, Alkishe et al. (2020) <doi:10.1016/j.pecon.2020.03.002>, Machado-Stredel et al. (2021) <doi:10.21425/F5FBG48814>, Arias-Giraldo and Cobos (2024) <doi:10.17161/bi.v18i.21742>, Cobos et al. (2024) <doi:10.17161/bi.v18i.21742>.

Version: 0.1.2
Depends: R (≥ 3.5)
Imports: doSNOW, enmpa (≥ 0.2.1), foreach (≥ 1.5), fpROC (≥ 0.1.0), glmnet (≥ 4.1), grDevices, graphics, mgcv (≥ 1.9), mop (≥ 0.1.3), parallel, stats, terra (≥ 1.6), utils
Suggests: knitr, rmarkdown, spelling
Published: 2026-03-29
DOI: 10.32614/CRAN.package.kuenm2
Author: Weverton C. F. Trindade ORCID iD [aut, cre], Luis F. Arias-Giraldo ORCID iD [aut], Luis Osorio-Olvera ORCID iD [aut], A. Townsend Peterson ORCID iD [aut], Marlon E. Cobos ORCID iD [aut]
Maintainer: Weverton C. F. Trindade <wevertonf1993 at gmail.com>
BugReports: https://github.com/marlonecobos/kuenm2/issues
License: GPL (≥ 3)
URL: https://marlonecobos.github.io/kuenm2/
NeedsCompilation: no
SystemRequirements: GDAL (>= 2.2.3), GEOS (>= 3.4.0), PROJ (>= 4.9.3)
Language: en-US
Materials: README, NEWS
CRAN checks: kuenm2 results

Documentation:

Reference manual: kuenm2.html , kuenm2.pdf
Vignettes: 1. Basic Data Cleaning (source, R code)
3. Model Calibration (source, R code)
4. Fit and Explore Selected Models (source, R code)
5. Project Models to a Single Scenario (source, R code)
6. Project Models to Multiple Scenarios (source, R code)
2. Prepare Data for Model Calibration (source, R code)
8. Example of Projections Using CHELSA Data (source, R code)
7. Exploring Model Uncertainty and Variability (source, R code)

Downloads:

Package source: kuenm2_0.1.2.tar.gz
Windows binaries: r-devel: kuenm2_0.1.2.zip, r-release: kuenm2_0.1.2.zip, r-oldrel: kuenm2_0.1.2.zip
macOS binaries: r-release (arm64): kuenm2_0.1.2.tgz, r-oldrel (arm64): not available, r-release (x86_64): kuenm2_0.1.2.tgz, r-oldrel (x86_64): kuenm2_0.1.2.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=kuenm2 to link to this page.

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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