Combining hierarchical distance sampling with occupancy modeling to measure population density from indirect signs

Published: 31 July 2018| Version 1 | DOI: 10.17632/4s97scjk3g.1
Rhett M. Rautsaw, Scott A. Martin, M. Rebecca Bolt, Richard A. Seigel, Christopher L. Parkinson


Text S1. An R Markdown script in ‘html’ format complete with step-by-step data analysis, model results, and simulations. The script also includes comments and guidelines for researchers to fit their own data. Data S1. All data for the analysis of Gopher Tortoise burrow surveys. Data includes transect observations, transect covariates, survey covariates, and burrow occupancy data. Additionally, the 50 m x 50 m grid covariates used to predict Gopher Tortoise density is included. Table S1. Covariates used in modelling and their predicted effects. Check marks for each location correspond to whether the habitat was present in that location. Table S2. Estimates of signal and animal density and abundance. LCL, Lower Confidence Limits; UCL, Upper Confidence Limit; SE, Standard Error; CV, Coefficient of Variation



Towson University, Ohio State University, Clemson University, University of Central Florida


Ecology, Conservation, Conservation Management, Animal Ecology, Wildlife Management, Methodology, Population Density