This 2-credit course, taught at the University of Idaho, will cover core concepts in population analysis for wildlife biology, although it is by no means comprehensive. The course is structured around hands-on coding exercises that will allow students to grow a basic toolbox of population analytical techniques, as well as the skills to code such analyses rather than simply execute other people's pre-written R code. It will build on foundation courses in population biology, which all students should have completed, as well as basic statistical concepts. We will cover analyses related to modeling vital rates, population growth, abundance, and density.
This course is NOT comprehensive- there are so many analyses these days across population biology, and we will only be covering a handful. However, major types of analyses for different kinds of data will be covered during lecture, and an important version of that type of analysis then assigned as a coding exercise for that week.
- A very approachable primer of population parameter estimation: http://larkinpowell.wixsite.com/larkinpowell/estimation-of-parameters-for-animal-pop
- Michael Conroy's course website: https://sites.google.com/site/cmrsoftware/home
- Jay Rotella's course website: http://www.montana.edu/rotella/502/Schedule.html
- MARK program help book, includes info on analysis: http://www.phidot.org/software/mark/
- Good intro to R for wildlife students by USGS: https://sites.google.com/site/rforfishandwildlifegrads/
And many more...
- Skalski, John R., Kristin E. Ryding, and Joshua Millspaugh. Wildlife demography: analysis of sex, age, and count data. 2005.
- Williams, Byron K., James D. Nichols, and Michael J. Conroy. Analysis and management of animal populations. 2002.
- Doak, Dan, and Bill Morris. Quantitative conservation biology. 2002.
There are a huge number of books on specialty topics, from matrix models to survival, occupancy, capture-recapture, and integrated population models, and I encourage you to find and purchase those that are most beneficial to your research and learning.
- Week 1: August 24th: Introduction to population analysis
- Week 2: August 31: Survival analysis: CJS and MLE
- Week 3: September 7: Survival analysis: known fates
- Week 4: September 14: More survival bootstrapping
- Week 5: September 21: Estimating population growth, Leslie matrices
- Week 6: September 28: No class, TWS meeting
- Week 7: October 5: Leslie matrices 2
- Week 8: October 12: No class, Sophie in the field. Complete week 7 assignment, and distance sampling reading.
- Week 9: October 19: Distance sampling
- Week 10: October 29: Intro to spatial capture-recapture (SCR)
- Week 11: November 2: SCR continued (guest lecture Clayton Lamb)
- Week 12: November 9: No class, Sophie in the field. Complete Bayesian readings
- Week 13: November 16: Intro to Bayesian methods. Install JAGS on your computer ASAP.
- Week 14: November 23: No class, fall break
- Week 15: November 30: Integration of analytical techniques, IPMs (guest lecture Jon Horne, IDF&G)
- Week 15: Dec 7: Paper discussion and course feedback form/discussion.
- Week 16: Dec 14: No class, finals week
Grades will be based on weekly participation in coding exercises and code-sharing from previous coding exercises (10 pts per weekly meeting).