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https://github.com/jamiemkass/ENMeval

R package for automated runs and evaluations of ecological niche models.
https://github.com/jamiemkass/ENMeval

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R package for automated runs and evaluations of ecological niche models.

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[![CRAN version](https://www.r-pkg.org/badges/version/ENMeval)](https://CRAN.R-project.org/package=ENMeval) [![downloads](https://cranlogs.r-pkg.org:443/badges/grand-total/ENMeval?color=orange)](https://cranlogs.r-pkg.org:443/badges/grand-total/ENMeval?color=orange)

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# 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`](https://jamiemkass.github.io/ENMeval/index.html) 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](https://jamiemkass.github.io/ENMeval/articles/ENMeval-2.0-vignette.html) 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)](https://onlinelibrary.wiley.com/doi/full/10.1111/ecog.03049) from the [maxnet R package](https://cran.r-project.org/package=maxnet) and the Java software maxent.jar [(Phillips *et al.* 2006)](https://doi.org/10.1016/j.ecolmodel.2005.03.026), available [here](http://biodiversityinformatics.amnh.org/open_source/maxent/), as well as BIOCLIM implemented with the [dismo R package](https://cran.r-project.org/package=dismo). 



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.](https://doi.org/10.1111/2041-210X.13628)



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.](https://doi.org/10.1111/2041-210X.12261)



NOTES:



1. The vignette is not included in the CRAN version of the package due to file size constraints, but is [available](https://jamiemkass.github.io/ENMeval/articles/ENMeval-2.0.0-vignette.html) on the package's Github Pages website. 



2. Please make sure to use the most recent version of [maxent.jar](https://biodiversityinformatics.amnh.org/open_source/maxent/) (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](https://cran.r-project.org/package=maxnet). 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).