Course information + schedule
HT 2014
BL 8056: Master course in
‘Marine population and ecosystem dynamics’
Welcome to the course in Marine population and ecosystem dynamics (MPED)! The course starts on Mon 3th
Nov 2014 at 9:15h in Room 105 at Frescati Backe (the Department of Ecology, Environment and Plant Sciences
building) and will be given in English. Below is a preliminary schedule and some information about the course.
This course is a slight modification of the formally called course ‘Marine Environmental Monitoring and Risk
Assessment’. The course takes a broad approach to theoretical, practical and applied aspect of ecosystem
dynamics in the marine environment, and will focus on:
•
•
•
•
•
data handling and statistical analysis of experimental and field data, including long-term observational
data
field work and lab analysis ourselves
theoretical ecological questions of long-term processes
the use of monitoring data in research and human society
interactions between marine ecosystems and global change
The first three weeks (wk 45-47) will mainly focus on basic data handling and statistics (lectures and computer
exercises). This is an important part of the course and the goal is to give a basic statistical understanding and
provide useful tools that we will use later in the course to analyse our field data and “real” datasets from the
national marine environmental monitoring programs and for designing environmental control programs and field
studies.
The fourth week (wk 48) will be fieldwork at Askö marine biological laboratory in the Trosa Archipelago south
of Stockholm. We will go there by minibuses/cars to “Stora Utterviks brygga” on Monday morning, from where
we take the boat and home again on Friday afternoon. If you have not been at Askö before, you can read more at
www.smf.su.se. Prepare for being away from home that week!
After the fieldwork we will spend time (wk 49-51) on processing and analyzing both field data and “real” data
from monitoring programs provided by researchers at the Department of Ecology, Environment and Plant
Sciences. During this period we will also have lectures about dynamics of marine populations by researchers
working on ecosystem dynamics and the use of ecological data in the society. Following, there will be one
individual examination task related to handling and analysis of observational data (handed in 19 Dec) and one
written examination (9 Jan).
The last course week (wk 3) will focus on population and ecosystem dynamics, where we will link statistical
data analyses to modelling and theory. This week will be structured with lectures, basic modelling exercises,
individual readings and presentations.
This is a preliminary schedule and changes might occur depending on student’s background knowledge and the
results of the fieldwork to use the time efficiently.
Literature
Is provided at the end of this document.
Computer software
We will mainly use the statistical software R, that can be downloaded free of charge from http://cran.rproject.org/. I also recommend using R studio, a free and open source integrated development environment for R
(http://rstudio.org/).
1 SU-account
We will have computer exercises (especially during the first three weeks) in BIG’s computer room D406. You
will need your SU-account to login on the computers, so make sure you have a working username and keyword,
otherwise contact BIG.
Assignments & Evaluation:
Students will be evaluated based on a final exam, individual analysis examination, fieldwork exercise, and
presentation.
• Exams: there will be one written examination (60 % of final grade).
• Individual analysis examination: students will use a dataset and complete specific analysis tasks (20 % of
final grade)
• Field work exercise: based on field work summary and presentation (10 % of final grade)
• Presentation: students must attend all classes during the final week (wk 3) and present a paper (10 % of final
grade)
• Computer exercises: all exercises have to be turned in (no grading)
Note: Students are required to complete all components of this course to receive a passing grade.
Teaching rooms:
Frescati backe FB 105
BIG’s computer room D 406, D 406A
Course leader:
MW = Monika Winder
Place of work
EMB, SU
Phone
08-16 1741
E-mail
[email protected]
Assistant course leaders
JN = Jens Nielsen
KK = Konrad Karlsson
EMB, SU
EMB, SU
[email protected]
[email protected]
Other teachers
DA = David Angeler
AB = Anders Bignert
NC = Nastassja Capetillo
JG = Jennifer Griffiths
OH = Olle Hjerne
HK = Hans Kautsky
SK = Susanne Kratzer
OS = Oleg Svachuk
JW = Jakob Walve
SLU; EMB, SU
NH Riksmuséet
SMF, SU
EMB, SU
EMB, SU
EMB, SU
EMB, SU
Baltic Nest, SU
EMB, SU
[email protected]
[email protected]
[email protected]
[email protected]
[email protected]
[email protected]
[email protected]
[email protected]
[email protected]
Please contact me if you have any questions about the course or other practical details.
Best regards,
Monika Winder,
Assoc. Prof, Course leader
Department of Ecology, Environment and Plant Sciences
Stockholm University
106 91 Stockholm
Phone: 08-16 1741, Mobile: 0709-988566, E-mail: [email protected]
2 Schedule for Marine population and ecosystem dynamics, 2014
Day
w 45
Mo
Date
Time
Room
Introduction + Applied statistics
3/11 09:15-12:00 FB 105
Activity (L:Lecture, C:Computer lab, G:Group activity)
Teacher
L
L
Course introduction: Roll call, Welcome
Why data analysis? Statistical challenges in
experiments and sampling
Data processing and graphics in Excel
Descriptive statistics & hypothesis testing
Introduction to R
Computer exercise (R)
Data exploration and graphical methods in R
Computer exercise (R)
Individual reading and computer exercises
t-test & one-way ANOVA
Computer exercise (R)
MW, JN, KK
MW
Correlation & Regression
Computer exercise (R)
Multiple regression
Computer exercise (R)
Two-way ANOVA
Computer exercise (R)
Individual reading and computer exercises
Multivariate analysis
Computer exercise (R)
MW
JN, KK
MW
JN, KK
MW
JN, KK
Tu
3/11 4/11 13:00-16:00
09:15-12:00
FB 105
FB 105
L
L
We
4/11 5/11 13:00-16:00
09:15-12:00
13:00-16:00
All day
09:15-12:00
13:00-16:00
D 406
FB 105
C
L
C
Th
Fr
w 46
Mo
Tu
We
Th
Fr
w 47
Mo
Tu
We
Th
Fr
w 48
Mo
Tu
We
Th
Fr
6/11 7/11 Applied statistics
10/11
09:15-12:00
13:00-16:00
11/11
09:15-12:00
13:00-16:00
12/11
09:15-12:00
13:00-16:00
13/11
All day
14/11
09:15-12:00
13:00-16:00
D 406
FB 105
D 406
FB 105
D 406
FB 105
D 406
FB 105
D 406
D 406
FB 105
D 406
L
C
L
C
L
C
L
C
L
C
Applied statistics + Field work preparations
17/11
09:15-12:00 FB 105 L Multivariate analysis, Nonparametric tests
13:00-16:00 D 406
C Multivariate analysis exercise (R)
18/11
09:15-12:00 FB 105 L Power analysis, Selecting test
13:00-16:00 D 406
C Computer exercise (R)
19/11
09:15-12:00 FB 105 L Sampling strategies for environmental monitoring
13:00-16:00 D 406
C Computer exercise – catch up opportunity (R)
20/11
All day
D 406
Individual reading and computer exercises
21/11
09:15-12:00 FB 105 L Environmental Monitoring; Plankton monitoring
13:00-13:45 FB 105 L Information and history about Askö
14:00-16:00 FB 105 L Field work planning
Field work at Askö
24/11
07:00
09:00-09:15
10:0025/11
all day
26/11
all day
27/11
all day
28/11
all day
15:00
FB
Uttervik
Askö
Askö
Askö
Askö
Askö
Departure towards Utterviks brygga
Boat transportation Uttervik-Askö
Field work and analysis
Field work and analysis
Field work and analysis
Field work and analysis
Field work and analysis
Boat transportation Askö-Uttervik
JN, KK
MW
JN, KK
MW
JN, KK
MW
JN, KK
DA
JN, KK
MW
JN, KK
MW
JN, KK
AB
JN, KK
MW, JW
NC
MW, JN, KK
JN, KK
JN, KK
MW, JN, KK
JN, KK
JN, KK
3 w 49
Mo
Tu
We
Th
Fr
w 50
Mo
Tu
We
Tu
Fr
w 51
Mo
Tu
We
Th
Fr
Group work + Lectures
1/12
09:15-12:00
afternoon
2/12
09:15-12:00
afternoon
3/12
09:15-12:00
afternoon
4/12
morning
afternoon
5/12
09:15-12:00
afternoon
FB 105
D 406
FB 105
D 406
FB 105
D 406
D 406
D 406
FB 105
D 406
Lectures + Oral presentation
8/12
09:15-12:00 FB 105
13:00-16:00
D 406
9/12
09:15-12:00 FB 105
afternoon
D 406
10/12
09:15-12:00 FB 105
13:00-16:00 FB 105
11/12
09:15-12:00
D 406
12/12
09:15-12:00 FB 105
13:00-16:00 FB127/
D 406
G
G
L
G
L
G
G
G
L
G
Field data analysis – status check
Field data analysis
Long-term ecological research (time series) I
Field data analysis
Long-term ecological research (time series) II
Field data analysis
Field data analysis
Field data analysis
Dynamics of fish populations
Field data analysis
MW, JN, KK
L
G
L
Dynamics of vegetative bottom
Field data analysis
Dynamics of salmon populations
Field data analysis
Oral field work presentation + discussion
Oral field work presentation + discussion
Individual work and reading
Dynamics of plankton communities
Introduction to individual examination task
HK
JN
JG
JN
MW, JN, KK
MW, JN, KK
Statistical summary
Individual work and reading
Observing Marine Ecosystem Processes from Space
Individual work and reading
The use of monitoring data for society and policy
Individual work and reading
Individual work and reading
Individual work and reading
Deadline for individual analysis examination task
MW
JN, KK
SK
JN, KK
OS
JN, KK
W
W
L
L
G
Lectures + individual examination task
15/12
09:15-12:00 FB 105 L
afternoon
D 406 L
16/12
09:15-12:00 FB 105 L
afternoon
D 406
17/12
09:15-12:00 FB 105 L
afternoon
D 406
18/12
all day
D 406
19/12
all day
D 406
17:00
MW
JN, KK
MW
JN, KK
JN
OH
JN, KK
JW
MW
w 52 + w 1 Christmas holiday
w2
Mo
Tu
We
Th
Fr
Examination
5/1
all day
6/1
all day
7/1
all day
8/1
all day
9/1
09:15-12:00
w3
Mo
Combining data with models and theory
12/1
09:15-12:00 FB 105 L
13:00-16:00
D 406 C
13/1
09:15-12:00 FB 105 L
13:00-16:00
D 406 C
14/1
09:15-12:00 FB 105 L
afternoon
D 406
15/1 09:15-15:00 FB 105
16/1 09:15-15:00 FB 105
Tu
We
Th
Fr
FB 105
Individual work and reading
Individual work and reading
Individual work and reading
Individual work and reading
Written examination
Population dynamics modelling I
Exercise
Population dynamics modelling II
Exercise
Alternative states
Individual work and reading
Individual work and reading
Student presentations
JN, KK
JG
JN
JG
JN
MW
MW, JN, KK
4 Course literature (MPED 2014, BL8043)
The course is to a large extent based on lectures about data analysis and statistics, marine monitoring
and ecosystem dynamics. There is no single book that covers these topics well, so we will use different
sources to complement the messages from the lectures and exercises. However, the most important
source of information will be the lectures themselves, including lecture handouts, copies/articles, and
exercises. Lecture handouts are available at the Mondo website: https://mondo.su.se/portal/site/
Marine monitoring
Two small documents that can be downloaded from the Swedish Environmental Protection Agency
(SEPA, Naturvårdsverket) give an overview of long-term observations of the Sea. They are available
both in English and Swedish:
• Monitoring the sea (http://www.naturvardsverket.se/Documents/publikationer/978-91-6208388-5.pdf),
Vi övervakar havet (http://www.naturvardsverket.se/Documents/publikationer/978-91-6208383-0.pdf)
• The Health of the Sea (http://www.naturvardsverket.se/Documents/publikationer/978-91-6208382-3.pdf),
Så mår havet (http://www.naturvardsverket.se/Documents/publikationer/978-91-620-83816.pdf)
Data handling and statistics
We won’t have one single compulsory book about statistics because we don’t follow a specific book.
Below are some book recommendations. You will get material as lecture handouts and exercises, but I
recommend that you get (at least) one statistical reference literature, as suggested below or something
comparable that you might already have. It is often good to have the same statistical concepts explained
in more than one way.
Statistical literature with an ecological perspective (without references to R):
• Statistics Explained – An introductory Guide for Life Scientist. Steve McKillup 2005. 267 pages.
 Comment: Relatively easy to read and a pedagogic introduction to statistics that unfortunately
do not bring up everything we will cover in the course (e.g. multiple regression), but by
attending the lectures you will do alright anyway. Very much recommended especially if you
have little statistical background and need simple explanations at the basic level.
 Price example: 233 SEK at Bokus
(http://www.bokus.com/b/9780521543163.html?pt=search_result&search_term=statistics%20ex
plained)
• The analysis of biological data. Whitlock, M. and D. Schluter. 2009.
 Comment: An easy readable introduction to analysing data in biology and a good book to
refresh your memories. This book covers basic principles in statistics and touches on some more
advances methods.
 Price example: 567 SEK at Bokus (http://www.bokus.com/bok/9780981519401/the-analysis-ofbiological-data/)
• Experimental Design and Data Analysis for Biologist. Gerry P. Quinn and Michale J. Keough.
2002. 537 pages.
 Comment: A rather extensive book that gives a good overview of a large number of statistical
methods used by ecologists. It contains more than we will cover on the course, but could be of
good use if you are going to use statistics in the future.
 Price example: 403 SEK at Bokus
(http://www.bokus.com/b/9780521009768.html?pt=search_result&search_term=experimental%
20desogn%20and)

5 Statistical literature with reference to R:
• The R Book. Crawley, Michael J. (2012). 960 pages.
 Comments: This book is a good introduction to analysing and understanding your data and is
easy to follow. The book guides you through how statistics works and what the output from R
mean. This book will be used in the Advanced Statics Course, so if you intend to take that
course this is a good investment. Recommended.
 This book is available for download at the library
(http://www.sub.su.se/search/soktraff.aspx?librisid=13967494)
 Price example: 541 SEK at Bokus (http://www.bokus.com/bok/9780470973929/the-r-book-2ndedition/).
• Discovering Statistics Using R. Field, Miles, Field. 2012. 992 pages.
 Comments: This book is a good investment if you plan to continue working with R for statistical
analysis and is a good resource from statistical novice to working researchers. The book gives a
good overview of the concepts of diverse statistical tests we use in the course, and more
advanced and keeps mathematics at a minimum, and gives good working examples. Although
the material is presented in an easy-going manner, it is quite comprehensive.
 Price example: 537 SEK at Bokus (http://www.bokus.com/bok/9781446263914/discoveringstatistics-using-ibm-spss-statistics/)
• Analysing Ecological Data. Zuur, Ieno & Smith. 2007. 698 pages.
 Comment: This book presents a wide range of approaches for analyzing data using case studies.
The books gives step by step analysis, discusses alternative approaches, and interpretation of
outputs and plots. Mathematics and theory are described lightly and it doesn’t explain basic
statistical concepts very detailed. R scripts for the analysis are available on the books webpage.
This book covers some more advanced topics than we are going to deal with at the course but I
can highly recommend it if you want to develop statistical skills further in the future.
 This book is available for download at the library (http://www.springerlink.com/content/978-0387-45967-7/#section=292216&page=1&locus=3)
 Price example: 817 SEK at Bokus (http://www.bokus.com/bok/9781441923578/analysingecological-data/)
Introduction to R:
There is a lot of information available on the internet about R (e.g. http://www.r-project.org/ under
“Documentation > Books” or “Documentation > Other > Contributed documentation”), that could be
used. An excellent introduction to learn R efficiently (without much statistics) that is available
electronically at Stockholm University library (http://www.sub.su.se/ > e-books (e-böcker) > Springer
eBooks >) is:
• The R Book. Crawley, Michael J. (2012). 960 pages. See above.
• A beginner’s Guide to R. Alain F. Zuur, Elena N. Ieno and Erik H. W. G. Meesters. 2009
 Comment: Explains how to use R, without going into statistical theory and supply many useful
examples and R code.
 Available for download (chapter by chapter unfortunately) from the SU library if you have an
SU account (http://www.springerlink.com/content/978-0-387-938363/#section=79195&page=1&locus=2)
 There are also useful R code and datasets available at (http://www.highstat.com/book3.htm)
I recommend that you order the statistics literature you want as soon as possible, and if you have never
studied statistics at all before you will benefit from taking a look in MacKillup (2005) or The R Book
before the course.
/Monika Winder
6