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Keyword

MaxEnt

Description: MaxEnt is a maximum-entropy machine-learning method commonly used to model species distributions from environmental data.
OpenAlex ID: keywords/maxent
Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation
2008 · Steven J. Phillips, Miroslav Dudík · Ecography · 6,840
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A statistical explanation of MaxEnt for ecologists
2010 · Jane Elith, Steven J. Phillips, et al. · Diversity and Distributions · 6,681
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A practical guide to MaxEnt for modeling species' distributions: what it does, and why inputs and settings matter
2013 · Cory Merow, Matthew J. Smith, et al. · Ecography · 3,806
ORIGINAL ARTICLE: Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar
2006 · Richard G. Pearson, Christopher J. Raxworthy, et al. · Journal of Biogeography · 3,140
Sample selection bias and presence‐only distribution models: implications for background and pseudo‐absence data
2009 · Steven J. Phillips, Miroslav Dudík, et al. · Ecological Applications · 2,987
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Opening the black box: an open‐source release of Maxent
2017 · Steven J. Phillips, Robert P. Anderson, et al. · Ecography · 2,880
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The art of modelling range-shifting species
2010 · Jane Elith, Michael Kearney, et al. · Methods in Ecology and Evolution · 2,806
The effect of sample size and species characteristics on performance of different species distribution modeling methods
2006 · Pilar A. Hernandez, Catherine H. Graham, et al. · Ecography · 2,538
Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria
2010 · Dan L. Warren, Stephanie N. Seifert · Ecological Applications · 2,304
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ENM eval: An R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models
2014 · Robert Muscarella, Peter J. Galante, et al. · Methods in Ecology and Evolution · 2,099
ENMTools: a toolbox for comparative studies of environmental niche models
2010 · Dan L. Warren, Richard E. Glor, et al. · Ecography · 2,061
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Making better M axent models of species distributions: complexity, overfitting and evaluation
2013 · Aleksandar Radosavljevic, Robert P. Anderson · Journal of Biogeography · 1,716
Spatial filtering to reduce sampling bias can improve the performance of ecological niche models
2014 · Robert A. Boria, Link E. Olson, et al. · Ecological Modelling · 1,534
The importance of correcting for sampling bias in MaxEnt species distribution models
2013 · Stephanie Kramer‐Schadt, Jürgen Niedballa, et al. · Diversity and Distributions · 1,314
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SDM toolbox: a python‐based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses
2014 · Jason L. Brown · Methods in Ecology and Evolution · 1,254
The ability of climate envelope models to predict the effect of climate change on species distributions
2006 · ROBERT J. HIJMANS, CATHERINE H. GRAHAM · Global Change Biology · 1,179
Mapping Species Distributions with MAXENT Using a Geographically Biased Sample of Presence Data: A Performance Assessment of Methods for Correcting Sampling Bias
2014 · Yoan Fourcade, Jan O. Engler, et al. · PLoS ONE · 1,172
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kuenm: an R package for detailed development of ecological niche models using Maxent
2019 · Marlon E. Cobos, A. Townsend Peterson, et al. · PeerJ · 1,009
SDMtoolbox 2.0: the next generation Python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses
2017 · Jason L. Brown, Joseph R. Bennett, et al. · PeerJ · 1,009
bioclim : the first species distribution modelling package, its early applications and relevance to most current MaxEnt studies
2013 · Trevor H. Booth, Henry A. Nix, et al. · Diversity and Distributions · 989
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Transferability and model evaluation in ecological niche modeling: a comparison of GARP and Maxent
2007 · A. Townsend Peterson, Monica Papeş, et al. · Ecography · 973
How much does climate change threaten European forest tree species distributions?
2017 · Marcin K. Dyderski, Sonia Paź, et al. · Global Change Biology · 933
Selecting pseudo-absence data for presence-only distribution modeling: How far should you stray from what you know?
2009 · Jeremy VanDerWal, Luke P. Shoo, et al. · Ecological Modelling · 885
Predictive performance of presence‐only species distribution models: a benchmark study with reproducible code
2021 · Roozbeh Valavi, Gurutzeta Guillera‐Arroita, et al. · Ecological Monographs · 858
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ENMeval 2.0: Redesigned for customizable and reproducible modeling of species’ niches and distributions
2021 · Jamie M. Kass, Robert Muscarella, et al. · Methods in Ecology and Evolution · 764
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Works count: 8,868
Citation count: 164,900
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