Multivariate methods for ecologists

Last changed: 04 October 2019
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The Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences invites PhD students to attend the course Multivariate methods for ecologists, 2019.

The deadline for application has passed and the course is fully booked.

Time

The course is given in two parts: The first part involves lectures and supervised computer exercises, and the second involves supervised individual work with own data at your own office. Course participants may register for either the first or both parts of the course.

Part 1: 1 week. 14-18 October 2019. At Ultuna campus, Uppsala.

Part 2: 2 weeks, directly after part 1, i.e. 21-31 October 2019. At your own office except the last day, which will be at Ultuna.

Attendants

The course is open for PhD students. We cannot accept undergraduate students. Post Doc researches are welcome only if there is place.

Prerequisites

A basic course in ordinary statistics is recommended. Students taking part 2 of the course must have their own data to work with.

Aims

The course aims to illustrate the application of number of multivariate methods on ecological data. Following the course, participants should be familiar with different multivariate techniques, and how they can be applied on various types of data. The course will focus on developing an understanding of the application of multivariate techniques, with only a minimum amount of effort placed on comprehending the underlying mathematical details.

After the course, the students should be able to analyse multivariate ecological data using any of the major software for this kind of analyses, including R.

Contents

A number of ordination and classification procedures will be demonstrated, such as cluster analysis, correspondence analysis (CA), canonical correspondence analysis (CCA), redundancy analysis (RDA), principle components analysis (PCA), partial least square-analysis (PLS) e. The course literature consists of 10 papers that will be available on the course web page. 

Requirements for examination and Credits

For part 1: Pass on all exercises during the first course week and pass on the home assignment. Presence at least at 80% of the lectures.

For part 2: Approved oral and written report from the project.

Swedish PhD students will receive 3 ECTS credits for the first (lecture) part and 4.5 ECTS credits for completing the whole course.

Location

The first part of the course will be given at the SLU campus, Uppsala. The second part of the course should be completed at your home department, with frequent contact with the teachers. The last day (31 October) is a seminar and discussion day where students taking part 2 will present the results of the individual project. This will be at Ultuna.

Software

We will mainly use the commercial software CANOCO v.5. SLU affiliated students can have the program installed on their own computers. Talk with the IT people at your department. 

For non-SLU students: a trial version can be requested from MicroComputer Power by sending a mail to Dr. Richard Furnas asking for a trial version to be used for this course. NOTE: do not send requests for the trial version until after 1 October (else you will get a trial version that expires before the end of the course).

We will also demonstrate how the programs R, PAST and Simca are used for selected multivariate methods.

Computers

We will do all exercises during part 1 at a computer lab. You may use your own laptop, provided that you have installed (at least the trail version of) CANOCO (see above).

Teachers

Ulf Grandin, Martyn Futter, Lars Sonesten, Hanna Fried-Petersen, James Weldon.

Course secretary

Sara Sandström (e-mail: sara.sandstrom@slu.se)

Accommodation

There are several lodging alternatives in Uppsala. The hostel/hotel Sunnersta herrgård is located within walking distance from the SLU campus. In the city centre, you can find many hotels and hostels, see e.g. destination Uppsala.

For more information contact

Ulf Grandin (course content etc.), e-mail: ulf.grandin@slu.se

or

Sara Sandström (application, practical matters, etc.), e-mail: sara.sandstrom@slu.se

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Last update of information: 7 May 2019

Page editor: simon.hallstan@slu.se