Name of course: Quantitative Plant Ecology
ECTS credits: 5
Course parameters:
Language: English
Level of course: PhD course
Time of year: Fall 2014
No. of contact hours/hours in total incl. preparation, assignment or the like: 35/80
Capacity limits: 16 participants
Objectives of the course: The PhD students will be introduced to state-space models and structural equation
models, which are becoming increasingly popular for fitting ecological models to empirical data. The aim of the
course is to introduce the students to i) the applied use of likelihood functions and Bayesian statistics in plant
ecology, ii) setting up advanced statistical models with latent parameters, and iii) making quantitative
predictions with a known degree of uncertainty.
Learning outcomes and competences:
At the end of the course, the student should be able to:
- assess the possible value of using advanced Bayesian methods in the students own scientific work
- critically evaluate scientific literature using advanced statistical models
Compulsory programme: preparation, active participation, assignment
Course contents:
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Introduction to plant abundance data
Introduction to likelihood functions typically used in plant ecology
State-space and structural equation models
Fitting models to ecological data using Bayesian MCMC methods
Ecological prediction
Prerequisites: Plant ecology, population ecology, statistics
Name of lecturer: Christian Damgaard (http://pure.au.dk/portal/en/cfd@dmu.dk)
Type of course/teaching methods: seminars and exercises
Literature: Electronic notes and supplementary original literature. In the course the software Mathematica will
be used. Before the course the student should have installed Mathematica on his or her portable computer and
have followed some of the tutorials at “http://www.wolfram.com/broadcast/#Tutorials”. The software can be
bought from “www.wolfram.com” (student prize ca. 800 kr.), but it can also be downloaded as a free 15-day
trial version, which will be sufficient to follow the course (do not download the free trial-version before two days
prior to the start of the course).
Course homepage: None
Course assessment: Personalized reports (approximately 20-40 pages, corresponding to a work load of 20
hours outside, and in the week after the end of the scheduled classes) has to be completed and submitted for
approval (pass/fail).
Provider: Department of Bioscience
Special comments on this course: There is a small fee to cover lunch etc. All other expenses for
accommodation and travel are paid by the individual PhD student.
Time: Monday 27/10 to Friday 31/10 2014
Place: Department of Bioscience, Aarhus University, Vejlsøvej 25, DK-8600 Silkeborg, Denmark
Registration: Deadline for registration is 13/10.
For registration: Christian Damgaard, e-mail: cfd@dmu.dk
If you have any questions, please contact Christian Damgaard, e-mail: cfd@dmu.dk
Course Program
The topics of the 5 days are as detailed below, and each topic starts with a lecture followed by computer
exercises which are carried out in teams of two-three participants. Each participant has to produce a
personalized report of the exercises. During the course, the participants should be prepared to work outside the
scheduled classes in order to complete the computer exercises.
Monday, 27/10
10:00 – 10:15
10:15 – 12:00
12:00 – 13:00
13:00 – 15:00
15:00 – 15:15
15:15 – 16:00
19:00
Coffee
Lecture 1: Welcome, Introduction to Course and Mathematica
Lunch
Lecture 2: Plant abundance data
Coffee
Discussion
Course Dinner
Tuesday, 28/10
08:30 – 10:00
10:00 – 10:15
10:15 – 12:00
12:00 – 13:00
13:00 – 15:00
15:00 – 15:15
15:15 – 16:00
Lecture 3: Likelihood functions typically used in plant ecology
Coffee
Computer Exercises
Lunch
Lecture 4: Likelihood functions typically used in plant ecology
Coffee
Computer Exercises
Wednesday, 29/10
08:30 – 10:00
10:00 – 10:15
10:15 – 12:00
12:00 – 13:00
13:00 – 15:00
15:00 – 15:15
15:15 – 16:00
Lecture 5: State-space and structural equation models
Coffee
Computer Exercises
Lunch
Computer Exercises
Coffee
Computer Exercises
Thursday, 30/10
08:30 – 10:00
10:00 – 10:15
10:15 – 12:00
12:00 – 13:00
13:00 – 15:00
15:00 – 15:15
15:15 – 16:00
Lecture 6: Fitting models to ecological data using Bayesian MCMC methods
Coffee
Computer Exercises
Lunch
Computer Exercises
Coffee
Lecture 7: Ecological predictions
Friday, 31/10
08:30 – 10:00
10:00 – 10:15
10:15 – 12:00
12:00 – 13:00
13:00 – 14:00
Lecture 8: Presenting other cases
Coffee
Student Discussion of Papers
Lunch
Evaluation and departure
Monday, 10/11
Submission of final report by e-mail to Christian Damgaard (cfd@dmu.dk)
Til annoncering på webside – til boks i øverste højre hjørne:
PLEASE NOTE
Deadline for registration is 13/10.
If you have any questions, Christian Damgaard, e-mail: cfd@dmu.dk