Bi7540 Data analysis in community ecology

Faculty of Science
Autumn 2008
Extent and Intensity
2/0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Milan Chytrý, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Milan Chytrý, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: prof. RNDr. Milan Chytrý, Ph.D.
Timetable
Wed 8:00–9:50 BR2
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Při výkladu místy navazuji na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a proto budu raději, když studenti tento předmět zapíší až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení předmětu (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
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
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomical delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using standard software packages such as PC-ORD, CANOCO, Statistica etc.
Syllabus
  • 1. Introduction to community ecology methods.
  • 2. Field sampling design.
  • 3. Data handling: computer programs.
  • 4. Data standardizations and transformations.
  • 5. Resemblance coefficients
  • 6. Numerical classification - cluster analysis and TWINSPAN. Supervised classification with artificial neural networks (ANN).
  • 7. Theory of gradient analysis.
  • 8. Regression models including regression trees (CART).
  • 9. Calibration and bioindication.
  • 10. Ordination - principal components analysis (PCA), correspondence analysis (CA), detrended correspondence analysis (DCA).
  • 11. Constrained ordination - redundancy analysis (RDA), canonical correspondence analysis (CCA), evaluation of ecological experiments with RDA and CCA, partial ordinations.
  • 12. Computer programs PC-ORD, CANOCO, Statistica.
  • 13. Case studies.
Literature
  • LEPŠ, Jan and Petr ŠMILAUER. Multivariantní analýza ekologických dat. 2001. info
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Assessment methods
Lessons include explanation of theory and demonstration of computer programs. For exam students prepare classification and ordination analyses of their own data or data obtained from the teacher, which they summarize in a brief report. The exam is oral discussion about this report. Students are required to know the theory in the background of individual methods. For more detailed requirements see http://www.sci.muni.cz/botany/chytry/zpradat/uloha.htm.
Language of instruction
Czech
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
Listed among pre-requisites of other courses
Teacher's information
http://www.sci.muni.cz/botany/chytry/zpradat/
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.
  • Enrolment Statistics (Autumn 2008, recent)
  • Permalink: https://is.muni.cz/course/sci/autumn2008/Bi7540