Errata Acesso aberto Revisado por pares

Erratum

2014; Wiley; Volume: 6; Issue: 1 Linguagem: Estoniano

10.1111/2041-210x.12305

ISSN

2041-210X

Tópico(s)

Malaria Research and Control

Resumo

Methods in Ecology and EvolutionVolume 6, Issue 1 p. 119-120 ErratumFree Access Erratum This article corrects the following: ENMeval: An R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models Robert Muscarella, Peter J. Galante, Mariano Soley-Guardia, Robert A. Boria, Jamie M. Kass, María Uriarte, Robert P. Anderson, Jana McPherson, Volume 5Issue 11Methods in Ecology and Evolution pages: 1198-1205 First Published online: September 25, 2014 First published: 17 December 2014 https://doi.org/10.1111/2041-210X.12305AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat The first version of ENMeval (version 0.1.0) contained a bug in the ‘calc.aicc’ function used to calculate AICc and related values (i.e. delta AICc and AICc weights). We have since released an updated version of the package (ENMeval version 0.1.1), which is now available on CRAN (http://cran.r-project.org/web/packages/ENMeval/index.html). Users should update to this version, and AICc calculations based on version 0.1.0 should not be used. The main conclusions of our original paper (Muscarella et al. 2014) remain unaffected. However, for five of the eight species included in our case study, the settings chosen as ‘optimal’ based on AICc changed with the corrected calculations. These changes are reflected in the new versions of Fig. 2, Fig. 3 and Table 3 included here. Table 3. Evaluation metrics of Maxent ENMs generated by ENMeval (version 0.1.1) for eight species of Coccoloba trees in Puerto Rico. Results are based on the ‘checkerboard2’ method for data partitioning and are shown for settings that gave minimum AICc values (i.e. ΔAICc = 0) as well as for Maxent default settings. Number of occurrence records used for each species is given by n. Schoener's D statistic (Schoener 1968; Warren et al. 2009) – a measure of model similarity in geographic space – compares the predictions of AICc-selected models with those based on default settings. Values of D range from zero to one, with higher values indicating more similar models Species N Model FC RM AUCTEST AUCDIFF ORMTP OR10 ΔAICc D C. costata (C. Wright) 48 AICc LQHPT 1·5 0·823 0·070 0·039 0·175 0·0 0·932 Default LQH 1 0·829 0·069 0·062 0·175 20·9 C. diversifolia (Jacq.) 69 AICc LQ 2·5 0·760 0·080 0·081 0·222 0·0 0·810 Default LQH 1 0·776 0·078 0·056 0·250 95·8 C. krugii (Lindau) 24 AICc L 0·5 0·954 0·022 0·071 0·117 0·0 0·886 Default LQH 1 0·945 0·030 0·071 0·242 19·9 C. microstachya (Willd.) 58 AICc H 1·5 0·783 0·074 0·111 0·214 0·0 0·898 Default LQH 1 0·785 0·073 0·023 0·251 15·0 C. pyrifolia (Desf.) 71 AICc LQ 1·5 0·685 0·053 0·040 0·178 0·0 0·862 Default LQH 1 0·690 0·083 0·010 0·170 36·4 C. sintenisii (Urb.) 27 AICc LQ 1·5 0·797 0·091 0·069 0·188 0·0 0·822 Default LQH 1 0·813 0·097 0·091 0·272 NA C. swartzii (Meisn.) 42 AICc L 1 0·708 0·097 0·019 0·170 0·0 0·911 Default LQH 1 0·697 0·133 0·128 0·300 29·8 C. venosa (L.) 44 AICc LQH 2·5 0·712 0·113 0·095 0·312 0·0 0·860 Default LQH 1 0·707 0·145 0·115 0·312 53·9 Figure 2Open in figure viewerPowerPoint Occurrences and predictions of Maxent models shown in selected portions of Puerto Rico for Coccoloba microstachya (a, b) and C. pyrifolia (c, d). Models shown here correspond to those producing the minimum AICc (a, c) and those built with default settings (b, d). Occurrence localities are indicated with an x. Scale bars show Maxent logistic output (used here only for visualization purposes); higher values (warmer colours) indicate higher predicted suitability. Figure 3Open in figure viewerPowerPoint Three evaluation metrics for Coccoloba microstachya (a–c) and C. pyrifolia (d–f) resulting from Maxent models made across a range of feature-class combinations and regularization multipliers. Left panels show ΔAICc, centre panels show the omission rate of testing localities at the 10% training threshold (OR10), and right panels show AUCTEST. Dotted horizontal line in ΔAICc plots represents ΔAICc = 2, which delimits models that are generally considered to have substantial support relative to others examined – that is those below the line (Burnham & Anderson 2004). Default settings and settings that yielded minimum AICc are indicated with arrows. Legends denote feature classes allowed (L = linear, Q = quadratic, H = hinge, P = product and T = threshold). Note that for one of these two species (C. microstachya), AICc-selected settings (based on all localities) resulted in substantially lower omission rates (in the models run with the partitioned data;’checkerboard2’ method) than were achieved by the default settings. However, maximal AUCTEST showed low correspondence with either the AICc-chosen or default settings. For these species, AICc consistently selected regularization multipliers higher than the default value. Results for all eight species (including estimates of variance) are provided in Appendix 1. References Burnham, K.P. & Anderson, D.R. (2004) Multimodel inference: understanding AIC and BIC in Model Selection. Sociological Methods and Research, 33, 261– 304. Muscarella, R., Galante, P.J., Soley-Guardia, M., Boria, R.A., Kass, J.M., Uriarte, M. & 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. Schoener, T.W. (1968) The Anolis lizards of Bimini: resource partitioning in a complex fauna. Ecology, 49, 704– 726. Warren, D.L., Glor, R.E., Turelli, M. & Funk, D. (2009) Environmental niche equivalency versus conservatism: quantitative approaches to niche evolution. Evolution, 62, 2868– 2883; Erratum: Evolution 2865: 1215. Volume6, Issue1January 2015Pages 119-120 FiguresReferencesRelatedInformation

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