Supplement 1. R code and data to run spatial mark–resight model for raccoon camera trap and telemetry data.

File List Raccoon_data.R: R list object with following slots $n: matrix with unmarked photo-counts for each trap (rows) and sampling period (columns) $yknown: 3-dimensional array with individual photographic encounter histories (counts) of all tagged and radio-collared individuals (rows) at each camera (columns) and each sampling period (3rd dimension) $X: matrix with X and Y coordinates (columns) of each camera trap (rows), in UTM scaled to km $mi: vector with total number of photos of marked individuals that could be identified to individual level for each sampling period $mall: vector with total number of photos of marked individuals, identified and unidentified, for each sampling period $M: size of the augmented data set $Eff: 3-dimensional array with information on how many days each camera trap (column) was functional during each sampling period (3rd dimension), expanded to hold the same information for each individual in the augmented data set (row), for easier array multiplication in the MCMC algorithm $collar: vector of length M with “TRUE” for individuals with radio-collars and “FALSE” for individuals without collars, tagged or unmarked $locs: list of length sum(collar) with 2-dimensional matrices containing X and Y coordinates of radio telemetry locations for each of the collard individuals SSp.dbf, SSp.shp, SSp.shx: Shapefile with outline of South Core Banks (which comprises the state-space for the raccoon analysis) Rscript_Raccoons.R: R code to load data and run raccoon analysis MCMC_algorithm.txt: R code for MCMC algorithm for spatial mark-resight analysis of raccoon data Description Data files and code are set up to repeat the spatial mark–resight analysis of raccoon camera trapping and telemetry data from South Core Bank, NC, as presented in the Application example in the manuscript.