SDMtoolbox 2.0: the next generation Python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses
Tóm tắt
Từ khóa
Tài liệu tham khảo
Anderson, 2003, Real vs. artefactual absences in species distributions: tests for Oryzomys albigularis (Rodentia: Muridae) in Venezuela, Journal of Biogeography, 30, 591, 10.1046/j.1365-2699.2003.00867.x
Anderson, 2011, Species-specific tuning increases robustness to sampling bias in models of species distributions: an implementation with MaxEnt, Ecological Modelling, 222, 2796, 10.1016/j.ecolmodel.2011.04.011
Anderson, 2010, The effect of the extent of the study region on GIS models of species geographic distributions and estimates of niche evolution: preliminary tests with montane rodents (genus Nephelomys) in Venezuela, Journal of Biogeography, 37, 1378, 10.1111/j.1365-2699.2010.02290.x
Barbet-Massin, 2012, Selecting pseudo-absences for species distribution models: how, where and how many?, Methods in Ecology and Evolution, 3, 327, 10.1111/j.2041-210X.2011.00172.x
Barve, 2011, The crucial role of the accessible area in ecological niche modeling and species distribution modeling, Ecological Modelling, 222, 1810, 10.1016/j.ecolmodel.2011.02.011
Boria, 2014, Spatial filtering to reduce sampling bias can improve the performance of ecological niche models, Ecological Modeling, 275, 73, 10.1016/j.ecolmodel.2013.12.012
Brown, 2014, SDMtoolbox: a python-based GIS toolkit for landscape genetic, biogeographic, and species distribution model analyses, Methods in Ecology and Evolution, 5, 694, 10.1111/2041-210X.12200
ESRI, 2017, ArcGIS desktop and spatial analyst extension: release 10.5
Hijmans, 2012, Cross-validation of species distribution models: removing spatial sorting bias and calibration with a null model, Ecology, 93, 679, 10.1890/11-0826.1
Laffan, 2010, Biodiverse, a tool for the spatial analysis of biological and related diversity, Ecography, 33, 643, 10.1111/j.1600-0587.2010.06237.x
Lobo, 2008, AUC: a misleading measure of the performance of predictive distribution models, Global Ecology & Biogeography, 17, 145, 10.1111/j.1466-8238.2007.00358.x
McRae, 2007, Circuit theory predicts gene flow in plant and animal populations, Proceedings of the National Academy of Sciences, 104, 19885, 10.1073/pnas.0706568104
Merow, 2013, A practical guide to MaxEnt for modeling species’ distributions: what it does, and why inputs and settings matter, Ecography, 36, 1058, 10.1111/j.1600-0587.2013.07872.x
Mishler, 2014, Phylogenetic measures of biodiversity and neo- and paleo-endemism in Australian Acacia, Nature Communications, 5, 4473, 10.1038/ncomms5473
Peterson, 2011, Ecological niches and geographic distributions, 49, 10.23943/princeton/9780691136868.001.0001
Phillips, 2006, Maximum entropy modeling of species geographic distributions, Ecological Modelling, 190, 231, 10.1016/j.ecolmodel.2005.03.026
Phillips, 2008, Modeling of species distributions with MaxEnt: new extensions and a comprehensive evaluation, Ecography, 31, 161, 10.1111/j.0906-7590.2008.5203.x
Phillips, 2017, MaxEnt software for modeling species niches and distributions
Radosavljevic, 2014, Making better MaxEnt models of species distributions: complexity, overfitting and evaluation, Journal of Biogeography, 41, 629, 10.1111/jbi.12227
Ray, 2005, PATHMATRIX: a geographical information system tool to compute effective distances among samples, Molecular Ecology Notes, 5, 177, 10.1111/j.1471-8286.2004.00843.x
Shcheglovitova, 2013, Estimating optimal complexity for ecological niche models: a jackknife approach for species with small sample sizes, Ecological Modeling, 269, 9, 10.1016/j.ecolmodel.2013.08.011
Veloz, 2009, Spatially autocorrelated sampling falsely inflates measures of accuracy for presence-only niche models, Journal of Biogeography, 36, 2290, 10.1111/j.1365-2699.2009.02174.x