Bi7550 Analysis of community ecology data in R program

Faculty of Science
Spring 2011 - only for the accreditation
Extent and Intensity
1/1/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. David Zelený, Ph.D. (lecturer)
Guaranteed by
Mgr. David Zelený, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. David Zelený, Ph.D.
Prerequisites
Bi7540 Data anal. commun. ecology
The class is focused on the use of R for analysis of multivariate ecological data. It is meant to be a continuation of Bi7540 Data analysis in community ecology, but oriented more practically and limited purely on the use of R (I expect, at least partially, students to gain their theoretical knowledge in Bi7540 or other courses). Before signing for this course, student should have also elementary experience with R program operation (gained by self-study or by attending other classes, such as Bi7560 Introduction to R, Bi8190 Visualization of biological data, Bi7920 Analysis of biological data etc.).
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 6 fields of study the course is directly associated with, display
Course objectives
At the end of the class, students should be able to analyze various types of ecological data using the R program. The class should also provide an inspiration for further individual improvements in using R program. R is not only substitution for PC-ORD or CANOCO - it offers much more, from almost unlimited selection of various statistical approaches up to the creative freedom, allowing one to handle any type of analysis and data.
Syllabus
  • 1. Introduction, basic data operations, libraries vegan and labdsv, recommended references 2. Betadiversity, similarity matrices, Mantel's test 3. Numerical classification methods 4. Unconstrained ordination 5. Constrained ordination 6. Classification and regression trees 7. Additional methods (e.g. Beals smoothing, diversity analysis such as rarefaction curves, etc.)
Literature
  • Oksanen J. (2010): Multivariate analysis of ecological communities in R: vegan tutorial. URL: http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf
  • Roberts, D.V. (2009): R labs for vegetation ecologists. URL: http://ecology.msu.montana.edu/labdsv/R/
  • CRAWLEY, Michael J. The R book. Hoboken, N.J.: Wiley, 2007, viii, 942. ISBN 9780470510247. URL info
Teaching methods
Lessons will combine theoretical parts, focused on theoretical background of particular methods, and practical parts, in which these methods will be applied on real datasets (practical part will be emphasized).
Assessment methods
Students will elaborate a final thesis, analysing their own (or borrowed) data using some of the methods tought in the class. Class will be concluded by oral examination, which will have form of discussion about the thesis with additional questions. During the class, student will elaborate several voluntary homeworks for training of selected methods.
Language of instruction
Czech
Further comments (probably available only in Czech)
The course can also be completed outside the examination period.
The course is taught once in two years.
Information on the per-term frequency of the course: jaro 2011, 2013, ...
The course is taught: every other week.
The course is also listed under the following terms Spring 2011, spring 2012 - acreditation, Spring 2013, Spring 2015, Spring 2017, Spring 2020, autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.