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Multicriterial analyses CANOCO

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Course Unit Code546-0115/01
Number of ECTS Credits Allocated2 ECTS credits
Type of Course Unit *Choice-compulsory type B
Level of Course Unit *Second Cycle
Year of Study *Second Year
Semester when the Course Unit is deliveredWinter Semester
Mode of DeliveryFace-to-face
Language of InstructionCzech
Prerequisites and Co-Requisites Course succeeds to compulsory courses of previous semester
Name of Lecturer(s)Personal IDName
KRE71Ing. Hana Švehláková, Ph.D.
Within the course the students will be acquainted with basic methods of multidimensional data analysis in CANOCO 5 environment. Emphasis will be placed on the use of biocenological data, their collection, control, transformation, classification and ordination, studies design, hypothesis creation and their testing.
Learning Outcomes of the Course Unit
Students will be able to work in CANOCO 5 environment, especially analysis, synthesis and interpretation of data - ie. ecological data collection, control, transformation, classification and ordination of including visualization of results.
Course Contents
1. Working with data. Types of data. Data Collection. Primary data. Data transcription and control. EDA. CDA. Data transformation.
2. Ecological data and its use. Ecological similarity. Biodiversity indices. Ellenberg\'s indication values. Traits.
3. Basic terminology of multicriterial statistical methods.
4. Regression. Linear models. Regression curves.
5. Ordination analysis. Models of species response on environment gradient. Basic ordination techniques and methods.
6. Indirect gradient analysis. PCA (Principal Components Analysis). CA (Correspondence Analysis). DCA (Detrended Correspondence Analysis).
7. Direct gradient analysis. RDA (redundancy analysis). CCA (canonical correspondence ananlysis).
8. Null hypothesis. Monte Carlo permutation test. Testing statistics.
9. Case study.
10. Classification methods. Nonhierarchical classification.
11. Classification methods. Hierarchical classification. Divisive classification.
12. Case study.
13. Design of experiments - manipulation vs. natural experiments.
Recommended or Required Reading
Required Reading:
Šmilauer, P., Lepš, J. Multivariate analysis of Ecological Data using CANOCO 5.Cambridge University Press 2014.
teer BRAAK, C. J. F., ŠMILAUER, P: CANOCO 5. Reference manual and user’s guide to Canoco for Windows: Software for Ordination. Microcomputer Power, Ithaca, New York, USA.2012
Digby, P.G.N., Kempton, R.A Multivariate analysis of ecological communities. Chapman and Hall, London – New York. 1987
Legendre, P., Legendre, L. Numerical Ecology (Third English Edition). Elsevier 2012. Amsterdam.
Zuur, A.F., Ieno, E.N ,Smith, G.M. Analysing Ecological Data. Springer 2007
HEBÁK, P., HUSTOPECKÝ, J., PECÁKOVÁ, I., PRŮŠA, M., ŘEZANKOVÁ, H., SVOBODOVÁ, A. a P. VLACH. Vícerozměrné statistické metody 3. Praha: Informatorium, 2005. ISBN 80-7333-039-3
HERBEN, Tomáš a Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I: Data o druhovém složení, 2001;
HENDL, Jan. Přehled statistických metod zpracování dat. Praha: Portál, 2012. ISBN 978-80-262-0200-4
ŠMILAUER, Petr a Jan LEPŠ. Multivariate analysis of Ecological Data using CANOCO 5.Cambridge University Press, 2014. ISBN 978-11396-2706-1
LEGENDRE, Pierre a Louis LEGENDRE. Numerical Ecology, vol. 24. Elsevier, 2012. ISBN 978-0-444-53868-0
Recommended Reading:
McGarigal, K., Cushman, S. & Stafford, S.G., Multivariate Statistics for Wildlife and Ecology Research, Springer, New York. 2000.
Gotelli, N.J., Ellison, A.M. A Primer of Ecological Statistics. Sinauer Associates 2004.
Oksanen, J. Multivariate Analysis in Ecology, Lecture Notes. 2004.
Palmer, M. Ordination methods for ecologists.
Legendre, P., Legendre, L. Numerical Ecology, 2nd Engl. Ed., Elsevier, Amsterdam, ISBN 0444892494. 1998.
LEPŠ, Jan a Petr ŠMILAUER. Metody mnohorozměrné statistiky v analýze ekologických dat. Studijní materiál ke kursu. České Budějovice: Biologická fakulta Jihočeské university, 1994
JANOUŠOVÁ, Eva, Jiří HOLČÍK, Danka HARUŠTIAKOVÁ, Simona LITTNEROVÁ a Jiří JARKOVSKÝ. Vícerozměrné statistické metody v biologii. Brno: CERM, 2012. ISBN 978-80-7204-791-8
MARHOLD, Karol a Jan SUDA. Statistické zpracování mnohorozměrných dat v taxonomii (Fenologické metody). Praha: Karolinum, 2002. ISBN 80-246-0438-8
ZVÁRA, Karel. Biostatistika. Praha: Karolinum, 2008. ISBN 80-7184-773-9
Planned learning activities and teaching methods
Lectures, Tutorials
Assesment methods and criteria
Task TitleTask TypeMaximum Number of Points
(Act. for Subtasks)
Minimum Number of Points for Task Passing
CreditCredit100 51