Course Description
Recently developed statistical tools make it possible to fit models of population dynamics to field data while accounting for observation error. This course will examine how to use these tools for statistical inference and prediction about animal population parameters including abundance, occupancy, survival, recruitment, and dispersal.
Athena Title
Inference Pop Dynamics
Prerequisite
Permission of school
Semester Course Offered
Offered fall
Grading System
A - F (Traditional)
Course Objectives
Students will learn how to: (1) design studies of animal population dynamics; (2) fit statistical models to data collected in the field; (3) interpret results; and (4) make predictions useful for informing conservation decisions.
Topical Outline
Part I - Introductory principles Statistical inference and population dynamics Part II - Static models of abundance and distribution Occupancy models N-mixture models Distance sampling Mark-recapture Spatial capture-recapture Part III - Dynamic models Dynamic occupancy models Dynamic N-mixture models Survival models Cormack-Jolly-Seber models Jolly-Seber models Dynamic spatial capture-recapture models Part IV - Project presentations
Syllabus