ENMeval: An R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models

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ENMeval: An R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models is …
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scholarly articleQ13442814

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P356DOI10.1111/2041-210X.12261

P50authorRobert MuscarellaQ49452776
Jamie M. KassQ56446658
María UriarteQ88767813
Robert A. BoriaQ104479787
P2093author name stringMariano Soley-Guardia
Peter J. Galante
Robert P. Anderson
P2860cites workThe meaning and use of the area under a receiver operating characteristic (ROC) curveQ29547182
Environmental niche equivalency versus conservatism: quantitative approaches to niche evolutionQ29616175
A framework for using niche models to estimate impacts of climate change on species distributionsQ30840927
Finite-Sample Equivalence in Statistical Models for Presence-Only DataQ30876908
Uses and misuses of bioclimatic envelope modelingQ31087201
Integrating GIS-based environmental data into evolutionary biologyQ31147400
Sample selection bias and presence-only distribution models: implications for background and pseudo-absence dataQ33422416
The effects of sampling bias and model complexity on the predictive performance of MaxEnt species distribution modelsQ34606307
Cross-validation of species distribution models: removing spatial sorting bias and calibration with a null modelQ45716155
Equivalence of MAXENT and Poisson point process models for species distribution modeling in ecology.Q51167138
Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria.Q51172584
Mapping the climate of Puerto Rico, Vieques and CulebraQ56058849
Multimodel Inference: Understanding AIC and BIC in Model SelectionQ56390541
AUC: a misleading measure of the performance of predictive distribution modelsQ56445156
Species-specific tuning increases robustness to sampling bias in models of species distributions: An implementation with MaxentQ56746639
The art of modelling range-shifting speciesQ56765761
Spatially autocorrelated sampling falsely inflates measures of accuracy for presence-only niche modelsQ56769867
Predicting species distribution: offering more than simple habitat modelsQ56785411
Assessing transferability of ecological models: an underappreciated aspect of statistical validationQ56924631
Incorporating model complexity and spatial sampling bias into ecological niche models of climate change risks faced by 90 California vertebrate species of concernQ57003039
Five (or so) challenges for species distribution modellingQ57014216
Novel methods improve prediction of species’ distributions from occurrence dataQ57014231
Correlation and process in species distribution models: bridging a dichotomyQ57019842
A statistical explanation of MaxEnt for ecologistsQ57062660
Presence-only modelling using MAXENT: when can we trust the inferences?Q57878008
ORIGINAL ARTICLE: Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in MadagascarQ58006257
P4510describes a project that usesR packageQ73539779
P433issue11
P407language of work or nameEnglishQ1860
P921main subjectR packageQ73539779
ecological modelingQ114110264
ecological complexityQ123741291
model complexityQ124734398
P6104maintained by WikiProjectWikiProject Invasion BiologyQ56241615
P1104number of pages8
P304page(s)1198-1205
P577publication date2014-09-25
P1433published inMethods in Ecology and EvolutionQ15710059
P1476titleENMeval: An R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models
P478volume5

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