Course: Advanced ordination methods

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Course title Advanced ordination methods
Course code KBE/052E
Organizational form of instruction Lecture + Lesson
Level of course Doctoral
Year of study not specified
Frequency of the course n academic years starting with an even year (e.g. 2016/2017), in the summer semester.
Semester Summer
Number of ECTS credits 3
Language of instruction English
Status of course Compulsory-optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Šmilauer Petr, doc. RNDr. Ph.D.
  • Lepš Jan, prof. RNDr. CSc.
Course content
Content of lectures: Working with Canoco software (recap). Advanced ANOVA models for repeated measurements plus corresponding multivariate methods (3 weeks); principal response curves; co-correspondence analysis, distance-based ordination methods (PCoA, NMDS), working with spatial data (dbMEM, 2 weeks), analysis relationships between functional traits and environment (2 weeks) Content of practicals: Complement lecture contents, last 2 weeks for work on miniprojects plus their presentation

Learning activities and teaching methods
Monologic (reading, lecture, briefing), Work with text (with textbook, with book), Demonstration, Projection, E-learning
  • Preparation for classes - 14 hours per semester
  • Preparation for exam - 16 hours per semester
  • Semestral paper - 16 hours per semester
  • Class attendance - 28 hours per semester
Learning outcomes
Students are acquainted with the theory of more advanced methods of multivariate analysis and lear how to apply those methods to their own data. The methods discussed in more detail include multivariate analysis of repeated measures data, principal response curves (PRC) method, co-correspondence analysis and Procrustes analysis, as well as ordination including data on spatial variation (db-MEM), as well as various methods of analysing the functional traits - environment relationship. Concluding week(s) (depending on student number) are devoted to work on student mini-projects to be presented in the final week, so that the students might demonstrate their ability to use at least one of the methods.
Students will be able to analyse multivariate data even if they harbour temporal correlations among observations (repeated measures) and/or spatial autocorrelation. They will be also able to analyse the relations between two kinds of biotic communities using co-correspondence analysis and to quantify and test the relations between functional traits of species and the properties of the environment.
Prerequisites
This course assumes knowledge and technical skills for using simple ordination methods (unconstrained, constrained and partial ordination) and the basic manipulation of data. Minimum of B+C students: 5
KBO/332
----- or -----
KBO/332E

Assessment methods and criteria
Analysis of student's language skills, Seminar work

Towards the end of term, students analyze a dataset with some of the method(s) introduced in this course and in the last practicals they present the results.
Recommended literature
  • P. Legendre & L. Legendre (2012): Numerical ecology. Elsevier, Amsterdam..
  • P. Šmilauer & J. Lepš (2014): Multivariate analysis of ecological data using Canoco 5..


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Science Study plan (Version): Zoology (1) Category: Biology courses - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Botany (1) Category: Biology courses - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Hydrobiology (1) Category: Biology courses - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Ecosystem Biology (1) Category: Ecology and environmental protection - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Entomology (1) Category: Biology courses - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Ecosystem Biology (1) Category: Ecology and environmental protection - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Hydrobiology (1) Category: Biology courses - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Ecosystem Biology (1) Category: Ecology and environmental protection - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Entomology (1) Category: Biology courses - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Hydrobiology (1) Category: Biology courses - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Entomology (1) Category: Biology courses - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Zoology (1) Category: Biology courses - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Botany (1) Category: Biology courses - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Botany (1) Category: Biology courses - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Zoology (1) Category: Biology courses - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Zoology (1) Category: Biology courses - Recommended year of study:-, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Botany (1) Category: Biology courses - Recommended year of study:-, Recommended semester: Summer