Quantitative Ecology - MB162QM01
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Opinion survey results Schedule
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This course provides an integrated introduction to the quantitative foundations of ecological research. Students will explore how statistical thinking, rigorous study design, and modern analytical tools can be used to address fundamental ecological questions and interpret complex biodiversity patterns. The course begins by examining the opportunities and challenges of applying quantitative approaches in biodiversity, guiding students through the process of planning a research program from formulating hypotheses and designing sampling strategies to implementing reverse planning and understanding the role of uncertainty in ecological inference. A central component of the course is the application of multivariate statistical methods to ecological data. Students will learn how to uncover structure and variation in communities using techniques such as cluster analysis, principal component analysis (PCA), redundancy analysis (RDA), canonical correlation, and related ordination methods. These tools will be complemented by core inferential approaches including analysis of variance (ANOVA), regression models, and an introduction to generalized linear models (GLMs), enabling students to analyse different types of ecological responses and experimental designs. A further module focuses on sampling and survey techniques widely used in biodiversity (plant and wildlife) studies. Students will be introduced to sampling theory and methods such as transects, abundance indices, and capture–mark–recapture approaches, developing an understanding of how sampling design influences data quality and ecological interpretation.
Course coordinator: Prof. Dr. Roberto Ambrosini Last update: Gáliková Kristýna, Mgr. et Mgr., DiS. (21.11.2025)
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