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Description

Automated Tuning and Evaluations of Ecological Niche Models.

Runs ecological niche models over all combinations of user-defined settings (i.e., tuning), performs cross validation to evaluate models, and returns data tables to aid in selection of optimal model settings that balance goodness-of-fit and model complexity. Also has functions to partition data spatially (or not) for cross validation, to plot multiple visualizations of results, to run null models to estimate significance and effect sizes of performance metrics, and to calculate niche overlap between model predictions, among others. The package was originally built for Maxent models (Phillips et al. 2006, Phillips et al. 2017), but the current version allows possible extensions for any modeling algorithm. The extensive vignette, which guides users through most package functionality but unfortunately has a file size too big for CRAN, can be found here on the package's Github Pages website: <https://jamiemkass.github.io/ENMeval/articles/ENMeval-2.0-vignette.html>.

CRAN version downloads R-CMD-check

ENMeval version 2.0.4

R package for automated tuning and evaluations of ecological niche models

NOTE: ENMeval is a work in progress, changing slowly to fix bugs when users identify them. If you find a bug, please raise an Issue in this Github repo and I will resolve it as soon as I can. The CRAN version may lag behind the Github one, so please try the development version here first if you are having any issues. Install with: devtools::install_packages("jamiemkass/ENMeval")

ENMeval is an R package that performs automated tuning and evaluations of ecological niche models and species distribution models. Version >=2.0.0 represents an extensive restructure and expansion of version 0.3.1, and has many new features, including customizable specification of algorithms besides Maxent using the new ENMdetails object, comprehensive metadata output, null model evaluations, new visualization tools, a completely updated and extensive vignette with a complete analysis walkthrough, and more flexibility for different analyses and data types. Many of these new features were created in response to user requests -- thank you for your input!

ENMeval >=2.0.0 includes the functionality to specify any algorithm of choice, but comes out of the box with two implementations of Maxent: maxnet (Phillips et al. 2017) from the maxnet R package and the Java software maxent.jar (Phillips et al. 2006), available here, as well as BIOCLIM implemented with the dismo R package.

Model tuning refers to the process of building models with varying complexity settings, then choosing optimal settings based on some criteria. As it is difficult to predict in advance what level of complexity best fits your data and results in the most ecologically realistic response for your species, model tuning and evaluations are essential for ENM studies. This process helps researchers maximize predictive ability and avoid overfitting with models that are too complex.

For a more detailed description of version >=2.0.0, please reference the new publication in Methods in Ecology and Evolution:

Kass, J. M., Muscarella, R., Galante, P. J., Bohl, C., Pinilla-Buitrago, G. E., Boria, R. A., Soley-Guardia, M., & Anderson, R. P. (2021). ENMeval 2.0: redesigned for customizable and reproducible modeling of species’ niches and distributions. Methods in Ecology and Evolution, 12: 1602-1608.

For the original package version, please reference the 2014 publication in Methods in Ecology and Evolution:

Muscarella, R., Galante, P. J., Soley-Guardia, M., Boria, R. A., Kass, J. M., Uriarte, M. and Anderson, R. P. (2014), ENMeval: An R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models. Methods in Ecology and Evolution, 5: 1198–1205.

NOTES:

  1. The vignette is not included in the CRAN version of the package due to file size constraints, but is available on the package's Github Pages website.

  2. Please make sure to use the most recent version of maxent.jar (currently 3.4.4), as recent bug fixes were made.

  3. Note that as of version 0.3.0, the default implementation uses the 'maxnet' R package. The output from this differs from that of the original Java program and so some features are not compatible (e.g., variable importance, html output).

Metadata

Version

2.0.4

License

Unknown

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