This data bundle contains some of the inputs, all of the processing instructions and all outputs from a single VisTrails/SAHM workflow. This model specifically includes field data of thinned occurrence locations and random background locations and un-thinned occurrence locations and targeted background locations for three species of tegu lizards in South America. Predictors included bioclimatic, tree cover, season length, potential evapotranspiration and solar radiation index rasters. Details about both inputs are included in the associated manuscript. The three bundle documentation files are: 1) '_archive_bundle_metadata.xml' (this file) which contains FGDC metadata describing the archive bundle. 2) 'PredictorList.csv' and PredictorList_North America.csv' contain a list of the raster inputs that were used to generate these model results. The first list points to these rasters for South America, the second for North America. These are not included in the archive bundle due to size constraints but are identified in this file as well as the metadata document. 3) '_archive_workflow_<>' where <> is the name of the species being modeled (tume = Salvator merianae (Argentine black and white tegu), tute = Tupinambis teguixin sensu lato (gold tegu), saru = S. rufescens (red tegu) and combined = all three species together). Contains two VisTrails/SAHM workflow documents (.vt files) which contains the workflow that was used to create these outputs. The two files represent models created with targeted background method and random background method as described in the associated manuscript. The folder also includes the final ensemble raster outputs from the models and the input location data for the random background models. 4) 'template_cj' is the raster layer input to the TemplateRaster module in SAHM to create the South America models. The remaining data files are the intermediate workflow products as well as the complete spatial and diagnostic model outputs. 5) 'masterLocationDataFiles.csv' contains the location data used to develop the targeted background models.