23553c
PC-based Seminar
SoSe 26: S II Quantitative Community Ecology in R
Oksana Buzhdygan, Felix May
Information for students
Additional module information: Quantitative Community Ecology
Additional information / Pre-requisites
Please use the computer not a tablet because R is difficult to install on a tablet.
Prior knowledge in R is required.
Prior knowledge in R is required.
Comments
Content:
In the seminars on the PC, students practically apply the topics and methods, learned during the lectures and seminars. Using a number of worked examples from the published ecological literature, students develop, evaluate, modify and solve the community analysis exercises using the R software under supervision and later independently. Students practice the selection of data analysis strategies for different datasets (e.g., chose appropreate methods for different multivariate datasets). Students learn how to interpret the results in the ecologically meaningful contexts.
Learning objectives:
In this module the students acquire the following knowledge and skills:
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In the seminars on the PC, students practically apply the topics and methods, learned during the lectures and seminars. Using a number of worked examples from the published ecological literature, students develop, evaluate, modify and solve the community analysis exercises using the R software under supervision and later independently. Students practice the selection of data analysis strategies for different datasets (e.g., chose appropreate methods for different multivariate datasets). Students learn how to interpret the results in the ecologically meaningful contexts.
Learning objectives:
In this module the students acquire the following knowledge and skills:
- to analyze ecological communities using taxonomic and functional approaches (total and relative abundances, biodiversity indicators, functional traits, functional diversity, taxonomic and functional community composition)
- to graphicaly visualize the variation within and between communities
- to apply statistics for multivariate data including Principal Component Analysis (PCA ), Redundancy Analysis (RDA), Canonical Correspondence Analysis (CCA), Nonparametric Multidimensional Scaling (NMDS) and other ordination methods and cluster analysis
- to test the effects of environmental variables on community diversity and changes in community composition
- to analyse the scale-dependence of biodiversity and approaches for standardized biodiversity comparisons
- to analyse community similarity and dissimilarity in species composition and in species functional traits
- to present statistical methods and results in oral and written form to a specialist audience.
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Suggested reading
De Bello, F., Carmona, C.P., Dias, A.T., Götzenberger, L., Moretti, M. and Berg, M.P., 2021. Handbook of trait-based ecology: from theory to R tools. Cambridge University Press.
Swenson, N.G., 2014. Functional and phylogenetic ecology in R. New York: Springer.
Borcard, D., Gillet, F. and Legendre, P., 2011. Numerical ecology with R. New York: Springer. close
10 Class schedule
Regular appointments
Mon, 2026-05-18 13:30 - 15:30
Tue, 2026-05-19 13:30 - 15:30
Wed, 2026-05-20 13:30 - 15:30
Thu, 2026-05-21 13:30 - 15:30
Wed, 2026-05-27 13:30 - 15:30
Thu, 2026-05-28 13:30 - 15:30
Fri, 2026-05-29 13:30 - 15:30
Mon, 2026-06-01 13:30 - 15:30
Tue, 2026-06-02 13:30 - 15:30
Wed, 2026-06-03 13:30 - 15:30