Analysis of ecological data, focusing on community-level data. Topics include distance measures, group comparison methods (Mantel test, permutational MANOVA), ordinations (PCA, DCA, NMS), methods of identifying groups (cluster analysis, classification trees), as well as Indicator Species Analysis, diversity measures, and related topics. Prerequisite: Q SCI 482, which may be taken concurrently. Offered: W.
This course focuses on current analytical techniques. Students will move beyond conventional statistics to specialized techniques that are applicable to ecological data, especially at the community level. Topics will include matrix algebra, distance measures, permutational MANOVA, indicator species analysis, and ordinations (DCA, CCA, NMS).
Student learning goals
General method of instruction
This course will involve a combination of lectures, demonstrations, and computer exercises. We will use R software throughout the course. Students should bring a thumb drive with at least 512 MB of free space to class to hold software and data files. Forestry and Biology students are welcome, along with students from other disciplines. Fisheries students are welcome but may prefer FISH 560.
A background in conventional statistics will serve as a springboard into these techniques. Therefore, QSCI 482 is a pre- or co-requisite.
Class assignments and grading
Most assignments will be computer-based. I will provide datasets for students to work on if they choose, though I strongly encourage students to analyze their own data where possible and appropriate.
Grading will be based on assignments and a detailed project. See course webpage for more details.