ESSM 689 Quantitative Methods in Ecology, Evolution, and Biogeography, SPRING 2015 [Download Syllabus | Online Schedule and Materials]
Course Instructor
Dr. Michelle Lawing, Department of Ecosystem Science and Management
Office: 223 Centeq Building B (Research Park)
Office Hours: R 9:00am – 11:00am or by appointment
Office Phone: 979-845-2748
Meeting Time and Place
Day and Time: Tuesday 1:00 – 3:40 pm
Lecture: Room 126, HSFB
Course Description and Prerequisites
Quantitative Methods in Ecology, Evolution, and Biogeography is a survey course for data analysis and modeling applications using the R Statistical Programing Language. We will cover linear models, likelihood, model selection, randomization, meta-analysis, multivariate ordination, species distribution modeling, phylogenetic comparative methods, and geometric morphometrics. Prerequisites: graduate classification.
Suggested Books
Crawley, M. J. 2012, The R book. 2nd edition. Chichester, England; Hoboken, N.J.,Wiley.
Dalgaard, P. 2008, Introductory statistics with R. 2nd. ed. New York,Springer.
Gotelli, N. J. and A. M. Ellison. 2004. A primer of ecological statistics. Sunderland, Mass., Sinauer Associates Publishers.
Paradis, E. 2006. Analysis of phylogenetics and evolution with R. New York, Springer.
Stevens, M. H. H. 2009. A primer of ecology with R. New York,Springer.
**Whitlock, M. and D. Schluter. 2015. 2nd edition. The analysis of biological data. Greenwood Village, Colo., Roberts and Co. Publishers.
Zuur, A. F., E. N. Ieno, N. J. Walker, A. A. Saveliev and G. M.Smith. 2009. Mixed effects models and extensions in ecology with R.
Course Grading and Composition
Grading (A: 90-100%, B: 80-89%, C: 70-79%, D: 60-69%, F: <60%)

Presentation – 20; Discussion – 20; Demonstration – 20; Tutorial – 20; Proposal and Final Project – 20

Each class will be structured in four components in the order of 1) student presentation of topic (15 minutes), 2) student-led class discussion (30-45 minutes), 3) demonstration in R (15 minutes), and 4) tutorial in R (90 minutes). Two students will be responsible for each component and sign-up will be the first day of class.

Topic Presenters: Structure an introductory presentation to a topic. Define important terminology, explain the quantitative approach (e.g., what type of data are used?, what are the assumptions of the approach?, what do we do if the assumptions are violated? what are the inferences you can draw from the results?), explain how this approach can be used in ecology, evolution or biogeography research, and finally briefly introduce the paper(s) that are selected for discussion. You have 15 minutes for this presentation.

Discussion Leaders: Choose one or two papers that use the quantitative method associated with your discussion, that is in a disciplinary specific journal, and that you would like to discuss. Send your choice paper(s) to me the Friday (or as close to it as possible) before your discussion for approval. I will then distribute to the class by Sunday evening. You are responsible for leading the class discussion in whatever way you decide. The class is rather large, so be creative and think of ways that would maximize learning, participation, and interest (e.g., break into smaller groups, forced debate, name that figure, and so forth). You have 30 to 45 minutes for your discussion.

Demonstrators: Present a walk through of the quantitative method in R. You will have up to 15 minutes to walk through your example. Plan for interruptions and questions during your demo. There are a number of example data sets already in R for your disposal. Use the function data() to see a list of those. TIP: You can run the examples at the bottom of each R help page by using the function example().

Tutorial builders: There are literally hundreds of tutorials available online for many (if not all) of the topics we will be covering. Your job is to find one or more, tweak or combine if needed, make sure it works, cite your source(s), and deliver it to me by Sunday night before our Tuesday session. The tutorial should take around 2 hours or so to complete if student is a novice R user.

Proposals are due Tuesday, March 24th. Format the proposal in accordance with a grant application for which you plan to apply. Presentations of final projects will be April 28th and May 5th. Presentations should be fifteen minutes in length followed by a few minutes of questions. Final project manuscripts are due Tuesday, May 12th. Format your manuscript in accordance with a journal in which you plan to submit your work.

Course Learning Objectives
  1. Explain the concepts of inference and modeling applications in ecology, evolution, and biogeography.
  2. Apply statistical concepts and methods to collect, analyze, and interpret data in ecology, evolution, and biogeography.
    1. Demonstrate competence in data manipulation and analysis in R.
    2. Design, collect and analyze data for a final project.
  3. Illustrate critical thinking and demonstrate problem-solving skills
    1. Write a research proposal based on problems in ecology, evolution, and biogeography.
    2. Write a paper that requires project development, analysis, interpretation, and implications.
  4. Demonstrate an ability to acquire, interpret, and present conclusions orally and in writing.
    1. Write a final paper that demonstrates acquisition, quality assessment, and retention of metadata specifications with data acquisition.
    2. Write a paper that requires project development, analysis, interpretation, and implications.
    3. Present the final paper with visual aid in the form of a fifteen-minute conference style talk.
Attendance Policy
Attendance is required. If the student must miss a class due to a university excused absence, then the student will be allowed to make up the work. The student must discuss this excused absence with the instructor and determine a make-up plan. Refer also to student rule 7:
The Americans with Disabilities Act (ADA) is a federal anti-discrimination statute that provides comprehensive civil rights protection for persons with disabilities. Among other things, this legislation requires that all students with disabilities be guaranteed a learning environment that provides for reasonable accommodation of their disabilities. If you believe you have a disability requiring an accommodation, please contact the Office of Support Services for Students with Disabilities in Room 126 of the Student Services Building. The phone number is 845-1637.
Honor Code
“An Aggie does not lie, cheat or steal, or tolerate those who do.” (
Tentative Class Schedule