ROOM: Room 120 – Dona Ana
Estimating the number of individuals within a population across time and space is a fundamental task in wildlife research and management. Distance sampling (often implemented as line-transect or point-count surveys) is a popular method of abundance (or density) estimation that corrects for imperfect detection based on the distribution of distances to observed individuals. Conventional distance-sampling approaches (e.g., Buckland et al. 2001, and basic models in Program Distance) have a rich history in wildlife ecology; however, recent developments have produced a growing number of methods available for analyzing distance-sampling, many of which rely solely on Program R, a free software environment for statistical computing and graphics. The goal of this workshop is to familiarize participants with methods to analyze distance-sampling data using Program R, and to equip participants with the ability to identify and implement appropriate methods for a given study design. Participants will gain hands-on exposure to options for conventional distance-sampling analysis (i.e., the R packages Rdistance, distance, and mrds), hierarchical distance-sampling analysis (i.e., the R package unmarked), and a Bayesian individual-covariate model implemented using free JAGS software. We will compare the consistency of results and the availability of analysis features (e.g., ability to handle covariates, automated model selection, etc.) across methods, helping participants determine which method may be most appropriate for common study designs and goals. The workshop will conclude with time reserved for participants to analyze real-world data (either their own or instructor-provided), with help from the instructors and fellow participants.
Organizers: Trent L. McDonald, Western Ecosystems Technology, Inc., Laramie, WY; Jason D. Carlisle, Western Ecosystems Technology, Inc., Laramie, WY
Supported by: Western Ecosystems Technology, Inc.