Numerical Methods in Community Ecology
群聚生態學分析方法
EEB5083 (B44 U1950)
群聚生態學分析方法
EEB 5083, spring semester 109-2
The course focused on the analysis of community ecology data in R, organized by Institute of Ecology and Evolutionary Biology, College of Life Science, National Taiwan University
When: every Thursday 9:10-12:10
Where: 3A Life Science building (生科3A), National Taiwan University
Instructor: David Zelený (澤大衛), Vegetation Ecology Lab
TA: Po-Yu Lin (林柏佑), r07b44005@ntu.edu.tw
Language of the course: English
Course content: analysis of community ecology data, including ordination and cluster analysis, diversity analysis and analysis of species attributes. We will use real community ecology data (mostly vegetation and zoological datasets) and practice the analysis using the R project.
Link to CEIBA (NTU study system): https://ceiba.ntu.edu.tw/1092EEB5083_numecol
Private Facebook Group (consider joining!): To be announced
Target audience: senior undergraduate and graduate ecology students focused on botany and zoology, who are planning to do a study at the community level (i.e. not on a single species, but on the multiple species occurring at multiple localities). The class may be useful also for other disciplines handling multivariate data (e.g. microbiology), but the main focus is on ecological data. If you study PhD and want to join, you are welcome but expect that some of the teaching materials will cover rather basic things.
Teaching strategy: The class includes an introduction to the theory, application of methods using R program, solving individual exercise during the class, homework assignments, test of knowledge (analogy of midterm and final test) and preparation of individual projects and their presentation (in English).
Location: Life Science Building, National Taiwan University, Taipei.
Disclaimer: this is rather an intensive course, focused on a theory of community data analysis, and practical exercise using R on real community ecology datasets. In addition to lectures taught in the classroom, you need to also complete homework assignments, midterm quiz, final test and prepare (and present in English) the final project focused on the analysis of community data. This is not an R course for advanced use of R program - I expect that you have a basic knowledge of R before you enter the class, but the main focus is on learning the theory behind the methods and their use, not advanced R programming. If you want to learn basics of R, consider taking my other class Introduction to R for Ecologists (regular 3 credit class taught every winter semester).