Fieberg, John RForester, James DStreet, Garrett MJohnson, Douglas HArchMiller, Althea AMatthiopoulos, Jason2016-11-212016-08-112016-11-212016-08-11https://hdl.handle.net/11299/181607Each example.html file (“example_”) uses various uhcplot functions (html files with description “code for function”). The example with the MN moose data (example_4_moose.html) also uses data for one Minnesota moose from 2013 and 2014 (in moose12687.csv). The tables (tables.html) are created with regression output files created and saved with the codes provided in the example.html files. The zipped folder (UHCPlotsPaper_R.zip) contains all of the Program R files (.R extension) for each of the html files. MNmoose_Arrowhead.pdf details the location of the moose from dataset. See the readme.txt for more information.Species distribution models (SDMs) are one of a variety of statistical methods that link individuals, populations, and species to the habitats they occupy. In Fieberg et al. "Used-habitat calibration plots: A new procedure for validating species distribution, resource selection, and step-selection models", we introduce a new method for model calibration, which we call Used-Habitat Calibration plots (UHC plots) that can be applied across the entire spectrum of SDMs. Here, we share the Program R code and data necessary to replicate all three of the examples from the manuscript that together demonstrate how UHC plots can help with three fundamental challenges of habitat modeling: identifying missing covariates, non-linearity, and multicollinearity.Attribution-NonCommercial-ShareAlike 3.0 United Stateshttp://creativecommons.org/licenses/by-nc-sa/3.0/us/animal movementcalibrationlogistic regressionpredictionpresence-onlyresource-selectionspatial point processuse-availabilityuhcplots packageProgram RDatasethttp://doi.org/10.13020/D6T590