REM Density Estimation Using Delta Method for Large Mammals in Golestan National Park, Iran (R Script)

This R script implements the Random Encounter Model (REM) combined with the delta method to estimate the population density and associated uncertainty (standard deviation and variance) of three large mammal species — red deer (Cervus elaphus) , roe deer (Capreolus capreolus) , and wild boar (Sus scrofa) — in Golestan National Park, Iran. The method integrates field data (camera trap detections, animal movement speed, detection parameters) with statistical error propagation to produce robust density estimates across different years (2011 and 2023). The script includes: A custom function REM_density() for density estimation and variance calculation via the delta method. Species-specific input data for red deer, roe deer, and wild boar. Output printing of density, standard deviation, and variance per species and year. This code supports transparent and reproducible wildlife monitoring, suitable for conservation research and management programs using camera trap data. Usage Notes: Requires R and the emdbook package. Results are printed directly to the console. Custom inputs can be added by modifying the species_data list.