Bi7540 Data analysis in community ecology

Faculty of Science
Spring 2017
Extent and Intensity
2/1/0. 3 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
Timetable
Mon 20. 2. to Mon 22. 5. Mon 9:00–12:50 B09/316, Mon 17:00–18:50 D32/329
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Přednáška navazuje na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a bylo by proto lepší, aby si studenti tento předmět zapsali až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může si předmět zapsat a na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení (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 taxonomic 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 CANOCO and CanoDraw).
Syllabus
  • Pre-analysis data preparation (data cleaning, outliers, transformation, standardization, exploratory data analysis), types of data (categorical vs quantitative, abundances, frequencies)
  • Ecological similarity (indices of ecological similarity and distance between samples)
  • Ordination (linear vs unimodal, constrained vs unconstrained, ordination diagrams, permutation tests, variance partitioning, forward selection, case studies)
  • Numerical classification (hierarchical vs nonhierarchical, agglomerative vs divisive, supervised vs unsupervised)
  • Use of species functional traits or species indicator values in multivariate analysis (functional traits, Ellenberg indicator values, community-weighted mean, fourth-corner)
  • Diversity indices (alpha, beta and gamma diversity, accumulation curves and rarefaction curves)
  • Case studies demonstrating the use of particular analytical methods
  • Design of ecological experiments (manipulative vs natural experiments)
    Computer labs will provide opportunity to improve practical software knowledge with programs CANOCO 5 and to apply acquired theoretical knowledge about analytical methods on real ecological data.
Literature
    recommended literature
  • LEPŠ, Jan a Petr ŠMILAUER. Mnohorozměrná analýza ekologických dat. 2001. http://regent.jcu.cz/skripta.pdf
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Teaching methods
theoretical lessons with additional computer labs (three to four blocks in computer lab)
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper - more details about its structure will be published on the class website. The exam is oral discussion about the study, with additional questions targeting theoretical background of used methods.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
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://vitsyrovatka.info/doku.php?id=zpradat:cs:start
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, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.
  • Enrolment Statistics (Spring 2017, recent)
  • Permalink: https://is.muni.cz/course/sci/spring2017/Bi7540