ENMeval v0.3.0

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Automated Runs and Evaluations of Ecological Niche Models

Automatically partitions data into evaluation bins, executes ecological niche models across a range of settings, and calculates a variety of evaluation statistics. Current version only implements ENMs with Maxent (Phillips et al. 2006) or maxnet (Phillips et al. 2017).

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ENMeval

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

ENMeval is an R package that performs automated runs and evaluations of ecological niche models, and currently implements Maxent using the either (now by default) the 'maxnet' algoritm developed by Phillips et al. (2017) using the 'maxnet' R package or [the original java program (http://biodiversityinformatics.amnh.org/open_source/maxent/). ENMeval was made for those who want to "tune" their models to maximize predictive ability and avoid overfitting, or in other words, optimize model complexity to balance goodness-of-fit and predictive ability. The primary function, ENMevaluate, does all the heavy lifting and returns several items including a table of evaluation statistics and, for each setting combination, a model object and a raster layer showing the model prediction across the study extent. There are also options for calculating niche overlap between predictions, running in parallel to speed up computation, and more. For a more detailed description of the package, check out the open-access publication:

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.

Also see the vignette for examples of implementation.

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, the old html output). Our team has done some fairly extensive testing to ensure this implementation gives the expected results but the maxnet implementation is relatively new (at the time of writing this) and we encourage users to scrutinize their results.

Functions in ENMeval

Name Description
get.evaluation.bins Methods to partition data for evaluation
calc.aicc Calculate AICc from Maxent model prediction
var.importance Extract percent contribution and permutation importance from a Maxent model
enmeval_results An object of class "ENMevaluation"
eval.plot Generate Basic Plot for ENMevaluate Output
calc.niche.overlap Calculate Similarity of ENMs in Geographic Space
corrected.var Calculate variance corrected for non-independence of k-fold iterations
ENMevaluate Tuning and evaluation of ENMs with Maxent
ENMeval-package Automated runs and evaluations of ecological niche models
make.args Generate arguments for Maxent
maxnet.functions Functions for compatability with maxnet package
eval2 An object of class "ENMevaluation"
ENMevaluation-class Class "ENMevaluation"
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Vignettes of ENMeval

Name
ENMeval-vignette.Rmd
ENMeval-vignette.md
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Details

Type Package
Date 2018-07-23
License GPL
Encoding UTF-8
VignetteBuilder knitr
RoxygenNote 6.0.1
NeedsCompilation no
Packaged 2018-08-14 19:10:12 UTC; au529793
Repository CRAN
Date/Publication 2018-08-15 08:10:03 UTC

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