Course: Desing and Analysis of Ecological Experiments

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Course title Desing and Analysis of Ecological Experiments
Course code KBO/332
Organizational form of instruction Lecture + Lesson
Level of course Master
Year of study not specified
Frequency of the course In academic years starting with an even year (e.g. 2016/2017), in the winter semester.
Semester Winter
Number of ECTS credits 6
Language of instruction English
Status of course 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: Observation and experiment, limitation of experiments in ecology, general rules of hypothesis testing, confirmatory and exploratory data analysis. Experimental designs and corresponding ANOVA models: Latin square design, nested designs, split plot, repeated measurements. General linear model and its implications as a basis of ordination methods. Multivariate methods in ecological research resemblance function, classification, gradient analysis. Ordination methods basics, techniques (CANOCO). Constrained, unconstrained, partial ordination in evaluation of designed experiments. Graphical display of results, ordination diagrams. Numerical classification. Content of practicals: Practical application of statistical methods introduced during the lectures, using Canoco 5 software, TWINSPAN, and cluster analysis and ANOVA in R software.

Learning activities and teaching methods
Monologic (reading, lecture, briefing), Projection, Skills training, E-learning
  • Preparation for classes - 28 hours per semester
  • Preparation for credit - 16 hours per semester
  • Semestral paper - 32 hours per semester
  • Preparation for exam - 24 hours per semester
  • Class attendance - 52 hours per semester
Learning outcomes
The course provides basic principles of experimental and sampling design in ecology, and of the analysis of resulting data. The practical problems resulting from work in the field are stressed. A special attention is paid to understanding the difference between causal and statistical relationships and the role of experiments in revealing the causal relationships. Whereas in Biostatistics course the main emphasis was on the univariate statistical methods, in this course we focus on the more complex ANOVA models, and mainly on the multivariate statistical methods. The multivariate statistics will be demonstrated using the CANOCO and TWINSPAN software packages. In the presented framework, the multivariate methods are seen not only as the methods of exploratory data analysis, but mainly as a tool of hypothesis testing and analysis of designed ecological experiments.
Student will acquire the abilities to: (1) correctly plan and evaluate experiments in the fields of theoretical as well as applied ecology and taxonomy, particularly at the level of populations and communities, but also experiments producing multivariate data of molecular biology (2) distinguish research questions answerable using unconstrained and constrained ordination methods and correctly choose the corresponding methodology (3) interpret the results of permutation tests of multivariate hypotheses and also to correctly interpret graphical representation of ordination methods (ordination diagrams) (4) choose and apply appropriate methods of cluster analysis or TWINSPAN method
Prerequisites
Students need expertise corresponding to the course of Biostatistics (KBE/012 or KBO/012), particularly in the area of hypothesis testing, analysis of variance, and linear models.

Assessment methods and criteria
Essay, Combined exam, Interim evaluation

Students solve homeworks during the term (5-7 times), which are then scored by the lecturer. At the end of term, students submit a written essay, representing analysis of own (or provided-by-lecturer) dataset, using the methods introduced during the course.
Recommended literature
  • Jongman R. H. et al. (1987): Data analysis in community and landscape ecology. - Pudoc, Wageningen.
  • P. Legendre, L. Legendre. Numerical Ecology. Third English Edition. Elsevier, Amsterdam, 2012. ISBN 978-0-444-53868-0.
  • Šmilauer P., Lepš J. Multivariate analysis of ecological data using Canoco 5. Cambridge University Press, Cambridge, UK, 2014. ISBN 978-1-107-69440-8.


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): Mathematics for future teachers (1) Category: Mathematics courses 3 Recommended year of study:3, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Botany (1) Category: Biology courses - Recommended year of study:-, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Mathematics for future teachers (1) Category: Mathematics courses 3 Recommended year of study:3, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Ecosystem Biology (1) Category: Ecology and environmental protection - Recommended year of study:-, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Ecosystem Biology (1) Category: Ecology and environmental protection - Recommended year of study:-, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Secondary Schools Teacher Training in Mathematics (2012) Category: Pedagogy, teacher training and social care - Recommended year of study:-, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Applied Mathematics (2010) Category: Mathematics courses 3 Recommended year of study:3, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Mathematics for future teachers (1) Category: Mathematics courses 3 Recommended year of study:3, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Mathematics for future teachers (1) Category: Mathematics courses 3 Recommended year of study:3, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Botany (1) Category: Biology courses - Recommended year of study:-, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Botany (1) Category: Biology courses - Recommended year of study:-, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Secondary Schools Teacher Training in Mathematics (1) Category: Pedagogy, teacher training and social care - Recommended year of study:-, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Secondary Schools Teacher Training in Mathematics (1) Category: Pedagogy, teacher training and social care - Recommended year of study:-, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Secondary Schools Teacher Training in Mathematics (1) Category: Pedagogy, teacher training and social care - Recommended year of study:-, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Botany (1) Category: Biology courses - Recommended year of study:-, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Ecosystem Biology (1) Category: Ecology and environmental protection - Recommended year of study:-, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Ecosystem Biology (1) Category: Ecology and environmental protection - Recommended year of study:-, Recommended semester: Winter
Faculty: Faculty of Science Study plan (Version): Zoology (1) Category: Biology courses - Recommended year of study:-, Recommended semester: Winter