“…These include choice of modelling algorithm, required sample size, optimal model complexity, choice of study area from which data are drawn, the exclusion of outliers and selection of environmental predictors, among others (Acevedo, Jimenez-Valverde, Lobo, & Real, 2012;Boria, Olson, Goodman, & Anderson, 2014;Domisch, Kuemmerlen, Jahnig, & Haase, 2013;Garcia-Callejas & Araujo, 2016;Guisan, Graham, Elith, Huettmann, & Distri, 2007;van Proosdij, Sosef, Wieringa, & Raes, 2016;Soley-Guardia et al, 2016;Varela, Anderson, Garcia-Valdes, & Fernandez-Gonzalez, 2014;Wisz et al, 2008). Many of the measurable phenomena that are potentially related to suitability (e.g., population density [Carrascal, Aragon, Palomino, & Lobo, 2015], upper limit of local abundance [VanDerWal, Shoo, Johnson, & Williams, 2009, Gomes et al, 2018 have not been quantified in detail for many real species and as such are unavailable for model validation. Decisions about how best to model species are typically made using metrics that test discrimination accuracy on subsets of species occurrence data that have been withheld during model construction (Elith et al, 2006;Radosavljevic & Anderson, 2014); for a recent literature review and summary see Appendices S1 and S2.…”