Lecturer(s)
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Boukal David, doc. Ing. MgA. Ph.D.
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Course content
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Content of lectures: Introduction to evolutionary ecology. Evolutionary thinking in context of population ecology. Natural selection: fitness as a function of individual properties in a given environment. Population genetics, quantitative genetics and adaptive processes. Selection, mutation and genetic drift. Finding evolutionarily stable strategies: methods of optimization, adaptive dynamics and dynamical programming. Life-history evolution. Evolution in constant and varying environments. Phenotypic plasticity and reaction norms. Evolution of behavioural traits. Mating systems and sexual selection. Models of speciation.
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Work with text (with textbook, with book), Demonstration, Work with multi-media resources (texts, internet, IT technologies), Project-based learning
- Preparation for exam
- 60 hours per semester
- Class attendance
- 36 hours per semester
- Preparation for classes
- 40 hours per semester
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Learning outcomes
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Introduction to evolutionary ecology. Basic concepts of population genetics and review of fundamental problems in theoretical evolutionary ecology. Review of mathematical techniques available in evolutionary ecology. Emphasis on mathematical formulation of evolutionary problems and their solution.
The student will be able to applu basic methods to solve problems in theoretical evolutionary ecology, including analytical and numerical simulations of equations and numerical simulations of dynamical processes. He/she will gain insight into the basic concepts of theoretical evolutionary ecology and will be able to interpret scientific papers on the subject.
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Prerequisites
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Basic knowledge of dynamical systems and ordinary differential/difference equations.
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Assessment methods and criteria
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Combined exam
To pass the course, students need to pass a combined exam consisting of a written test of theoretical knowledge and a computer code demonstrating the ability to solve a selected problem. The student mus score at least 50% of total points to pass the test.
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Recommended literature
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Bulmer M.: Theoretical evolutionary ecology. Sinauer Associates, 1994.
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Freeman S., Herron J. C.: Evolutionary Analysis, 4th edition. Pearson Prentice Hall, 2007.
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Roughgarden J.: Theory of population genetics and evolutionary ecology. Prentice Hall, 1996.
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Roff D.A. Modeling Evolution: an introduction to numerical methods. New York, 2010. ISBN 978-0-19-957114-7.
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