Bi7550 Analysis of community ecology data in R program

Faculty of Science
Spring 2017
Extent and Intensity
1/1/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. Vít Syrovátka, Ph.D. (lecturer)
Guaranteed by
Mgr. Vít Syrovátka, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. Vít Syrovátka, Ph.D.
Supplier department: Department of Botany and Zoology – Biology Section – Faculty of Science
Prerequisites
Bi7540 Data anal. commun. ecology ||NOW( 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 (both classes could be taken in one semester, although from formal reason you need to apply for exception - this will be automatically granted), 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.). In case that enrolled students have no experience with using of R program, I will at the beginning insert one class devoted to "simple guide to R", which should ensure that everybody will have basic ability to master R program for the purpose of this class.
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
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
  • Introduction, data import, vegan library, recommended references, details about final examination.
  • Unconstrained ordination (CA, PCA, DCA, PCoA, NMDS, drawing ordination diagrams, environmental variables in unconstrained ordination).
  • Constrained ordination (RDA, CCA, db-RDA).
  • Monte Carlo permutation test, forward selection, variance partitioning.
  • Numerical classification (hierarchical and non-hierarchical classification, dendrogram, evaluation of classification results, indicator species).
  • Optional: Analysis of diversity (alpha and beta diversity, rarefaction curves). Note: optional topics will be inserted in case that participants are interested and there is enough time for it.
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/
  • BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. 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). The class will be held once per two weeks in Bohunice computer room.
Assessment methods
Students will elaborate a final thesis, analysing their own (or borrowed) data using some of the methods introduced 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
English
Further comments (probably available only in Czech)
Study Materials
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 - only for the accreditation, Spring 2011, spring 2012 - acreditation, Spring 2013, Spring 2015, Spring 2020, autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.
  • Enrolment Statistics (Spring 2017, recent)
  • Permalink: https://is.muni.cz/course/sci/spring2017/Bi7550