Analysis of ecological data, focusing specifically 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. Pre- or corequisite: QSCI 482. Offered: W.

Professor: Dr. Jon Bakker

Office: Room 036, Merrill Hall, Center for Urban Horticulture

Phone: 206-221-3864

Email: jbakker@u.washington.edu

Office Hours: Please make an appointment via email

The goals of this course are:

1. To introduce students to the range of techniques available for analyzing community-level ecological data.

2. To provide students with the ability to evaluate and choose appropriate statistical techniques, and the opportunity to apply them to their own data.

3. To expose students to the variety of ecological questions to which these statistical techniques have been applied.

Classes are held on Wednesdays and Fridays from 9:00 to 10:20 am in FSH 136.

This course is extensively computer-based. In-class demonstrations will use example datasets so that we can detect and address procedural errors that might otherwise confound analyses. Assignments and student projects will provide opportunities to apply techniques. Readings will provide background material to techniques and examples of their application.

Participation / Discussion - 10%

Assignments (equally weighted) - 40%

Project (see here for details) - 50%

Assignments and projects are due at the beginning of the class period on the due date. Late assignments will be penalized 10% per day.

Final grades will be assigned based on the UW standard grading system.

Required:McCune, B., and J.B. Grace. 2002. Analysis of ecological communities. MjM Software Design, Gleneden Beach, OR. ISBN 0-9721290-0-6. Call number QH541.15.S72 M33 2002

Recommended: Dalgaard, P. 2002. Introductory statistics with R. Springer, New York, NY. ISBN 0-387-95475-9. Call number QA276.4 .D33 2002

Various articles from the primary literature. Articles are available on the website through the course schedule.

A large number of texts about R have been published recently. A partial list of these, and other statistical resources, is available here. Note: The text and many of the recommended resources are on reserve at the circulation desk in the Natural Sciences Library.

Data should be stored and manipulated in Microsoft Excel or, if data quantities are large, Microsoft Access. These programs are part of Microsoft Office, and are available on most UW computers.

Most of our analyses will be conducted in the R statistical language. R is an open source system, and can be downloaded (free!) from http://cran.r-project.org/. The base system is updated frequently; the current version as of 091114 is v.2.10.0. Packages that conduct specific types of analyses in R have been written by folks around the world and can be downloaded from the same site. Packages that are directly applicable to this course are labdsv and vegan, among others. However, you can also write your own code to conduct, summarize, and graph your results - and we'll do so during the course!

Some analytical techniques may also be demonstrated in PC-ORD and/or PRIMER. PC-ORD is produced by MjM Software (http://home.centurytel.net/~mjm/pcordwin.htm). The current version as of 090102 is v.5.18. PRIMER is produced by PRIMER-E, a UK company (http://www.primer-e.com/index.htm). The current version as of 090102 is 6.1.11. However, I am aware of few copies of PRIMER on the UW campus.

Our classroom is FSH 136, a SAFS computer lab. This lab contains 24 student computers and one instructor computer. R and PC-ORD are installed on all machines. Students may also bring their own laptop into FSH 136 if they prefer. Required internet resources (course website, R packages, etc) may be accessed via the wireless network available in FSH 136.

Students who are using the lab computers will require their own thumb drive (USB drive) on which to store data files. R can be installed, and run, from a thumb drive. Doing so will require a drive with at least 500 MB of storage space.

FSH 136 is not available for use outside of classtime, but several other labs are available:

• FSH 207. Available for all UW students. R and PC-ORD are installed on all computers.
• BLD 156 (Bloedel Hall). Requires a CFR NetID to log on. R and PC-ORD are installed on all computers.
• MER 020 (Merrill Hall). Requires a CFR NetID to log on. R and PC-ORD are installed on all computers.

In addition, since R is free, assignments can be conducted on your home computer or laptop.

One way to organize the anticipated course topics is as follows:

1. Introductory Materials
1. Data adjustments
2. Matrix algebra
3. Distance measures
2. Group Comparisons (comparing a priori groups)
1. Mantel tests
2. ANOSIM
3. MRPP
4. Permutational MANOVA
3. Ordinations (visualizations; data reduction)
1. PCA
2. CA and variants (DCA, CCA)
3. NMS
4. Identifying Groups (creating new groupings based on data)
1. Cluster analysis
2. Discriminant analysis
3. Regression trees
5. Other Common Techniques in Community Ecology
1. Indicator Species Analysis
2. Diversity Measures

In addition, several class periods will be devoted to topics that students select on the basis of their interest and utility. Potential topics include:

-Bray-Curtis (Polar) ordination

-Discriminant Analysis

-Manova (Hotelling's T²)

-Structural equation modeling

-Bayesian statistics

-Monte Carlo techniques

-Species accumulation curves

-Spatial analysis *+

-Repeated measures / time series analysis *+

-Meta-analytic techniques

-other??

Note: Items chosen by students in Winter 2007 and 2008 are indicated by '*' and '+', respectively.

Academic Integrity

Plagiarism, cheating, and other misconduct are serious violations of your contract as a student. I expect that you will know and follow the University's policies on cheating and plagiarism. Any suspected cases of academic misconduct will be handled according to University regulations. More information, including definitions and examples, can be found at: http://depts.washington.edu/grading/issue1/honesty.htm.

Disability Accommodations

To request academic accommodations due to a disability, please contact Disabled Student Services, 448 Schmitz, (206)543-8924 (V/TTY). If you have a letter from Disabled Student Services indicating that you have a disability which requires academic accommodations, please present the letter to me so we can discuss the accommodations needed for this class.