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Lecturer(s)
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Duchoslav Martin, RNDr. Ph.D.
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Course content
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1. Introduction. Types of ecological researches, terminology, historical overview. 2. Data sampling - objectivity, design of an experiment, results interpretation. 3. Characteristics of vegetation data - data matrices, data manipulation. Software Juice. Evaluation of similarities among species and relevés. Diversity, species richness, dominance. 4. Calibration. Ecological Analysis. Indicators. 5. Biosystematical data - sampling, types of variables, multicollinearity problems 6. Methods of multidimensional analyses. (i) Direct and indirect gradient analysis (ordination), software CANOCO, R. (ii) Classification methods (nonhierarchical classification, cluster and divisive analyses, discrimination analysis, regression trees), software JUICE. 7. Spatial and temporal aspect of ecological data. Numerical methods in ecology: study examples.
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Learning activities and teaching methods
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Lecture, Dialogic Lecture (Discussion, Dialog, Brainstorming), Projection (static, dynamic), Laboratory Work
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Learning outcomes
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The course focuses on methodology of design, sampling, analysis and interpretation of data from observational and experimental studies in community ecology and biosystematics.
Student should be able to (after attending the course): - Explain the terms of Plant Ecology Research. - Collect properly ecological data, design an experiment. - Analyse collected data using statistical software (JUICE, CANOCO, TWINSPAN, STATISTICA, R) and properly interpret obtained results. - Project, collect and statistically assess biosystematical data, using multivariate procedures.
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Prerequisites
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Basic knowledge of ecology and biostatistics.
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Assessment methods and criteria
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Mark, Written exam
Combined exam in extent of the lectures: written test and calculating some numerical examples on PC
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Recommended literature
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Jongman, R.H., Braak ter, C.J.F., Tongeren van, O.F.R. (1995). Data analysis in community and landscape ecology.. Cambridge University Press.
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Kent, M., Coker, P. (1992). Vegetation Description and Analysis.. Belhaven Press, London.
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Legendre P., Legendre L. (2012). Numerical Ecology. 3rd edition. Elsevier, Amsterdam.
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Lepš, J., & Šmilauer, P. (2003). Multivariate analysis of ecological data using CANOCO. Cambridge: Cambridge University Press.
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Magurran, A. E., McGill, B. J. (2011). Biological diversity: Frontiers in measurement and assessment. Oxford Univ. Press.
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Schneiner SM., Gurevitch J. (2001). Design and analysis of ecological experiments. Oxford University Press.
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ter Braak C.J.F, Šmilauer P. (2012). Canoco reference manual and users guide. České Budějovice.
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Wildi, O. (2013). Data analysis in vegetation ecology. Hoboken, N.J: Wiley-Blackwell.
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