Suchergebnis: Katalogdaten im Herbstsemester 2017

Biologie Master Information
Wahlvertiefungen
Wahlvertiefung: Ökologie und Evolution
Wahlpflicht Masterkurse
NummerTitelTypECTSUmfangDozierende
751-4801-00LSystembezogene Bekämpfung herbivorer Insekten IW2 KP2GD. Mazzi
KurzbeschreibungIm Zentrum steht das Erwerben von Fähigkeiten zur Beurteilung von Strategien zur Lenkung von Schädlingspopulationen im Spannungsfeld Ökonomie-Ökologie-Gesellschaft. Agrarwissenschaftlich bedeutende Verfahren werden erklärt und an Beispielen vertieft, wie Prävention mittels natürlicher Ressourcen, Überwachung und Prognose, Resistenz-Management, sowie Mittelzulassung samt Ökotoxikologie.
LernzielDie Studierenden erreichen ein gutes Verständnis über gundlegende Aspekte der Schädlingsbekämpfung in Agrarökosystemen und können Handlungsoptionen im Spannungsfeld Ökologie - Ökonomie - Gesellschaft beurteilen. Sie gewinnen zusätzlich die Fähigkeit, Recherchen über relevante Fragen der Schädlingsbekämpfung durchzuführen und Fallbeispiele kritisch zu beurteilen.
701-1409-00LResearch Seminar: Ecological Genetics
Minimum number of participants is 4.
W2 KP1SA. Widmer, S. Fior
KurzbeschreibungIm Forschungsseminar werden aktuelle Themen aus der Ökologischen Genetik an Hand neuester Publikationen kritisch diskutiert.
LernzielUnser Ziel ist es, dass die Teilnehmenden einen Einblick in den aktuellen Forschungs- und Wissensstand in Ökologischer Genetik erhalten und lernen neue, wissenschaftliche Publikationen kritisch zu diskutieren und zu würdigen.
Skriptkeines
Literaturwird verteilt
Voraussetzungen / BesonderesEine aktive Teilnahme an den Diskussionen ist Voraussetzung für diesen Kurs.
551-1703-00LÖkologie anthropogen geprägter StandorteW2 KP1VD. Ramseier
KurzbeschreibungDer Fokus liegt auf der Agrarökolgie und der Ökologie urbaner Standorte. Beide sind geprägt durch häufige Störungen, spezielle chemische Einflüsse und extreme klimatische Bedingungen. Bei urbanen Standorten herrschen ausserdem häufig schwierige edaphische Verhältnisse. Die Artenvielfalt und das Artenset variieren räumlich und zeitlich stärker als bei entsprechenden natürlichen Verhältnissen.
LernzielKenntnisse von Agrarökosystemen und urbanen Oekosytemen, deren Entstehung, Funktionen („ecosystem services“), Mechanismen und Bedeutung für den Erhalt der Biodiversität.
701-1441-00LAlpine Ecology and Environments Information W2 KP2GS. Dietz, D. Ramseier
KurzbeschreibungThe online course ALPECOLe provides a global overview of the complex ecosystems of mountain regions, and of their great diversity of habitats and organisms. The course is interdisciplinary and the various approaches are designed to help understand the past, present and future of mountain ecosystems.
LernzielKnowledge of alpine environments worldwide and their ecology
InhaltThe online course is subdivided into
- 5 lessons on abiotic factors: geology, soils and their forming processes, climate, and disturbance factors
- 12 lessons on plants: diversity, patterns and processes, treelines, water & nutrients, carbon cycle, atmospheric influences, sexual and clonal reproduction, and one specific lesson on aquatic environments
- 5 lessons on animals: habitats and adaptations, origin of species, food ecology and impact of domestic livestock
- 3 lessons on landscape evolution: quarternary paleoenvironments, methods like radiocarbon dating, pollen records, dendrochronology, stable isotopes, and historical data
- 1 lesson on global change

Students can also follow a virtual walk through alpine areas where context-based information on alpine environments can be accessed. Moreover, all mayor alpine areas of the world can be selected on a map and then informative pictures of those landscapes and faunistic and floristic inhabitants will be shown.
Online exercises and tests allow to test the learned matter.
Voraussetzungen / BesonderesOnline course and seminar
Students prepare for the seminar by working through particular lessons. Each student has to present some special aspects of one lesson. The seminar contribution is part of the performance assessment.
Course language is English
751-5121-00LInsect EcologyW2 KP2VC. De Moraes, M. Mescher, N. Stanczyk
KurzbeschreibungThis is an introductory course in insect ecology. Students will learn about the ways in which insects interact with and adapt to their abiotic & biotic environments and their roles in diverse ecosystems. The course will entail lectures, outside readings, and critical analysis of contemporary literature.
LernzielStudents completing this course should become familiar with the application of ecological principles to the study of insects, as well as major areas of inquiry in this field. Highlighted topics will include insect behavior, chemical and sensory ecology, physiological responses to biotic and abiotic stressors, plant-insect interactions, community and food-web dynamics, and disease ecology. The course will emphasize insect evolution and adaptation in the context of specific interactions with other organisms and the abiotic environment. Examples from the literature incorporated into lectures will highlight the methods used to study insect ecology.
SkriptProvided to students through ILIAS
LiteraturSelected required readings (peer reviewed literature, selected book chapters). Optional recommended readings with additional information.
401-0625-01LApplied Analysis of Variance and Experimental Design Information W5 KP2V + 1UL. Meier
KurzbeschreibungPrinciples of experimental design, one-way analysis of variance, contrasts and multiple comparisons, multi-factor designs and analysis of variance, complete block designs, Latin square designs, random effects and mixed effects models, split-plot designs, incomplete block designs, two-series factorials and fractional designs, power.
LernzielParticipants will be able to plan and analyze efficient experiments in the fields of natural sciences. They will gain practical experience by using the software R.
InhaltPrinciples of experimental design, one-way analysis of variance, contrasts and multiple comparisons, multi-factor designs and analysis of variance, complete block designs, Latin square designs, random effects and mixed effects models, split-plot designs, incomplete block designs, two-series factorials and fractional designs, power.
LiteraturG. Oehlert: A First Course in Design and Analysis of Experiments, W.H. Freeman and Company, New York, 2000.
Voraussetzungen / BesonderesThe exercises, but also the classes will be based on procedures from the freely available, open-source statistical software R, for which an introduction will be held.
401-0649-00LApplied Statistical RegressionW5 KP2V + 1UM. Dettling
KurzbeschreibungThis course offers a practically oriented introduction into regression modeling methods. The basic concepts and some mathematical background are included, with the emphasis lying in learning "good practice" that can be applied in every student's own projects and daily work life. A special focus will be laid in the use of the statistical software package R for regression analysis.
LernzielThe students acquire advanced practical skills in linear regression analysis and are also familiar with its extensions to generalized linear modeling.
InhaltThe course starts with the basics of linear modeling, and then proceeds to parameter estimation, tests, confidence intervals, residual analysis, model choice, and prediction. More rarely touched but practically relevant topics that will be covered include variable transformations, multicollinearity problems and model interpretation, as well as general modeling strategies.

The last third of the course is dedicated to an introduction to generalized linear models: this includes the generalized additive model, logistic regression for binary response variables, binomial regression for grouped data and poisson regression for count data.
SkriptA script will be available.
LiteraturFaraway (2005): Linear Models with R
Faraway (2006): Extending the Linear Model with R
Draper & Smith (1998): Applied Regression Analysis
Fox (2008): Applied Regression Analysis and GLMs
Montgomery et al. (2006): Introduction to Linear Regression Analysis
Voraussetzungen / BesonderesThe exercises, but also the classes will be based on procedures from the freely available, open-source statistical software package R, for which an introduction will be held.

In the Mathematics Bachelor and Master programmes, the two course units 401-0649-00L "Applied Statistical Regression" and 401-3622-00L "Regression" are mutually exclusive. Registration for the examination of one of these two course units is only allowed if you have not registered for the examination of the other course unit.
701-0301-00LAngewandte SystemökologieW3 KP2VA. Gessler
KurzbeschreibungDieser Kurs vertieft das ökologische Systemwissen, das nötig ist, um angewandte Lösungen für aktuelle Umweltprobleme zu hinterfragen. Unser zentrales Anliegen ist es, den Respekt der Teilnehmer vor Komplexität mit einem Sinn für Möglichkeiten zu balancieren, indem wir Beispiele aus dem weiten Lösungsraum ökologischer Systeme darstellen, wie z.B. grüne Infrastruktur im Wassermanagement.
LernzielAm Ende der Vorlesung...
...können Sie Ihre Recherche strukturieren und Sie wissen, wie Sie ein komplexes Umweltproblem analysieren können. Sie können die lösungs-relevanten Fragen formulieren und Antworten finden (unterstützt durch Diskussionen, Input der Dozenten und aus der Literatur), und Sie können Ihre Schlussfolgerungen klar und sorgfältig darstellen.
...verstehen Sie die Komplexität der Interaktionen und Strukturen in Ökosystemen. Sie wissen wie Ökosystemprozesse, Funktionen und Dienste interagieren und sich über vielfältige Raum- und Zeitskalen hinweg beeinflussen (im Allgemeinen, und im Detail für einige ausgewählte Beispiele).
...verstehen Sie, dass Biodiversität und die Interaktionen zwischen Organismen ein integraler Bestandteil von Ökosystemen sind. Ihnen ist bewusst, dass die Verbindung zwischen Biodiversität und Prozess/Funktion/Dienst selten vollständig verstanden ist. Sie wissen wie man aufrichtig mit diesem Verständnismangel umgeht und können dennoch Lösungswege finden, kritisch analysieren und darstellen.
...verstehen Sie die Wichtigkeit von Ökosystemdiensten für die Gesellschaft.
...haben Sie einen Überblick über die Methoden in der Ökosystemforschung und einen tieferen Einblick in einige ausgewählte Techniken z.B. in die ökologische Beobachtung, Manipulation und Modellierung.
...haben Sie sich mit der Ökologie als junge und zentrale Disziplin für drängende angewandte Gesellschaftsfragen auseinandergesetzt.
InhaltDieser Kurs vertieft das ökologische Systemwissen, das nötig ist um angewandte Lösungen für aktuelle Umweltprobleme zu hinterfragen. Wir werden die Komplexität aktueller Umweltprobleme kritisch erfassen, und dabei grundlegende ökologische Konzepte und Prinzipien illustrieren. Unser zentrales Anliegen ist es, den Respekt der Teilnehmer vor Komplexität mit einem Sinn für Möglichkeiten zu balancieren, indem wir Beispiele aus dem weiten Lösungsraum ökologischer Systeme darstellen, wie z.B. grüne Infrastruktur im Wassermanagement.

Der Kurs ist in vier grössere Themengebiete untergliedert: (1) Integriertes Wassermanagement -- Grüne Infrastruktur (Optionen im Landschaftsmanagement) als Alternativen zu technischen Lösungen (z.B. Staudämme) im Umgang mit Überflutungen und Dürren; (2) Feuerdynamik, der Wasserkreislauf und Biodiversität -- Die überraschende Dynamik der Lebenszyklen einzelner Arten und Populationen in trockenen Landschaften; (3) "Rückverwilderung", z.B. die Wiedereinführung grosser Räuber (z.B. Wölfe) oder grosser Weidetiere (z.B. Bisons) in Schutzgebieten -- ein Naturschutztrend mit überraschenden Effekten; (4) Die Kopplung von aquatischen und terrestrischen Systemen: Kohlenstoff-, Stickstoff- und Phosphorflüsse von globaler Wichtigkeit auf Landschaftsebene.
SkriptFallbeschreibungen, ein kommentiertes Glossar, und eine Liste der Literatur und weiter Quellen pro Fall.
LiteraturEs ist nicht unbeding notwendig die folgenden Bücher zu leihen/kaufen. Wir stellen immer wieder Auszüge und weiterführende Literatur während des Kurses bereit.

Agren GI and Andersson FO (2012) Principles of Terrestrial Ecosystem Ecology, Cambridge University Press.

Chapin et al. (2011), Principles of Terrestrial Ecosystem Ecology, Springer.

Schulze et al. (2005) Plant Ecology; Springer.
Voraussetzungen / BesonderesDer Kurs kombiniert Elemente des klassischen Vorlesungsformats, Gruppendiskussionen und Problem Based Learning. Es ist hilfreich, aber nicht zwingend notwendig, wenn Sie mit der Methode des "Siebensprung" (siehe z.B. Veranstaltung 701-0352-00L "Analyse und Beurteilung der Umweltverträglichkeit" von Christian Pohl et al.) vertraut sind.
401-6215-00LUsing R for Data Analysis and Graphics (Part I) Information W1.5 KP1GA. Drewek, M. Mächler
KurzbeschreibungThe course provides the first part an introduction to the statistical software R for scientists. Topics covered are data generation and selection, graphical and basic statistical functions, creating simple functions, basic types of objects.
LernzielThe students will be able to use the software R for simple data analysis.
InhaltThe course provides the first part of an introduction to the statistical software R for scientists. R is free software that contains a huge collection of functions with focus on statistics and graphics. If one wants to use R one has to learn the programming language R - on very rudimentary level. The course aims to facilitate this by providing a basic introduction to R.

Part I of the course covers the following topics:
- What is R?
- R Basics: reading and writing data from/to files, creating vectors & matrices, selecting elements of dataframes, vectors and matrices, arithmetics;
- Types of data: numeric, character, logical and categorical data, missing values;
- Simple (statistical) functions: summary, mean, var, etc., simple statistical tests;
- Writing simple functions;
- Introduction to graphics: scatter-, boxplots and other high-level plotting functions, embellishing plots by title, axis labels, etc., adding elements (lines, points) to existing plots.

The course focuses on practical work at the computer. We will make use of the graphical user interface RStudio: www.rstudio.org

Note: Part I of UsingR is complemented and extended by Part II, which is offered during the second part of the semester and which can be taken independently from Part I.
SkriptAn Introduction to R. http://stat.ethz.ch/CRAN/doc/contrib/Lam-IntroductionToR_LHL.pdf
Voraussetzungen / BesonderesThe course resources will be provided via the Moodle web learning platform
Please login (with your ETH (or other University) username+password) at
https://moodle-app2.let.ethz.ch/enrol/users.php?id=1145
Choose the course "Using R for Data Analysis and Graphics" and follow the instructions for registration.
401-6217-00LUsing R for Data Analysis and Graphics (Part II) Information W1.5 KP1GA. Drewek, M. Mächler
KurzbeschreibungThe course provides the second part an introduction to the statistical software R for scientists. Topics are data generation and selection, graphical functions, important statistical functions, types of objects, models, programming and writing functions.
Note: This part builds on "Using R... (Part I)", but can be taken independently if the basics of R are already known.
LernzielThe students will be able to use the software R efficiently for data analysis.
InhaltThe course provides the second part of an introduction to the statistical software R for scientists. R is free software that contains a huge collection of functions with focus on statistics and graphics. If one wants to use R one has to learn the programming language R - on very rudimentary level. The course aims to facilitate this by providing a basic introduction to R.

Part II of the course builds on part I and covers the following additional topics:
- Elements of the R language: control structures (if, else, loops), lists, overview of R objects, attributes of R objects;
- More on R functions;
- Applying functions to elements of vectors, matrices and lists;
- Object oriented programming with R: classes and methods;
- Tayloring R: options
- Extending basic R: packages

The course focuses on practical work at the computer. We will make use of the graphical user interface RStudio: www.rstudio.org
SkriptAn Introduction to R. http://stat.ethz.ch/CRAN/doc/contrib/Lam-IntroductionToR_LHL.pdf
Voraussetzungen / BesonderesBasic knowledge of R equivalent to "Using R .. (part 1)" ( = 401-6215-00L ) is a prerequisite for this course.

The course resources will be provided via the Moodle web learning platform
Please login (with your ETH (or other University) username+password) at
https://moodle-app2.let.ethz.ch/enrol/users.php?id=1145
Choose the course "Using R for Data Analysis and Graphics" and follow the instructions for registration.
751-4504-00LPlant Pathology IW2 KP2GB. McDonald
KurzbeschreibungPlant Pathology I will focus on pathogen-plant interactions, epidemiology, disease assessment, and disease development in agroecosystems. Themes will include: 1) how pathogens attack plants and; 2) how plants defend themselves against pathogens; 3) factors driving the development of epidemics in agroecosystems.
LernzielStudents will understand: 1) how pathogens attack plants and; 2) how plants defend themselves against pathogens; 3) factors driving the development of epidemics in agroecosystems as a basis for implementing disease management strategies in agroecosystems.
InhaltCourse description: Plant Pathology I will focus on pathogen-plant interactions, epidemiology, disease assessment, and disease development in agroecosystems. Themes will include: 1) how pathogens attack plants and; 2) how plants defend themselves against pathogens; 3) factors driving the development of epidemics in agroecosystems. Topics under the first theme will include pathogen life cycles, disease cycles, and an overview of plant pathogenic nematodes, viruses, bacteria, and fungi. Topics under the second theme will include plant defense strategies, host range, passive and active defenses, and chemical and structural defenses. Topics under the third theme will include the disease triangle and cultural control strategies.

Lecture Topics and Tentative Schedule

Week 1 No Lecture: First day of autumn semester

Week 2 The nature of plant diseases, symbiosis, parasites, mutualism, biotrophs and necrotrophs, disease cycles and pathogen life cycles. Nematode attack strategies and types of damage.

Week 3 Viral pathogens, classification, reproduction and transmission, attack strategies and types of damage. Examples TMV, BYDV, plum pox virus. Bacterial pathogens and phytoplasmas, classification, reproduction and transmission. Bacterial attack strategies and symptoms. Example bacterial diseases: fire blight, Agrobacterium crown gall, soft rots.

Week 4 Fungal pathogens, classification, growth and reproduction, sexual and asexual spores, transmission. Fungal life cycles, disease cycles, infection processes, colonization, phytotoxins and mycotoxins. Attack strategies of fungal necrotrophs and biotrophs.

Week 5 Symptoms and signs of fungal infection. Example fungal diseases: potato late blight, wheat stem rust, grape powdery mildew, wheat Septoria leaf blotch.

Week 6 Plant defense mechanisms, host range and non-host resistance. Passive structural and chemical defenses, preformed chemical defenses. Active structural defense, papillae, active chemical defense, hypersensitive response, pathogenesis-related (PR) proteins, phytoalexins and disease resistance.

Week 7 Pisatin and pisatin demethylase. Local and systemic acquired resistance, signal molecules.

Week 8 Pathogen effects on food quality and safety.

Week 9 Epidemiology: historical epidemics, disease pyramid, environmental effects on epidemic development. Plant effects on development of epidemics, including resistance, physiology, density, uniformity.

Week 10 Disease assessment: incidence and severity measures, keys, diagrams, scales, measurement errors. Correlations between incidence and severity.

Week 11 Molecular detection and diagnosis of pathogens. Host indexing, serology, monoclonal and polyclonal antibodies. ELISA, PCR, rDNA and rep-PCR.

Week 12 Strategies for minimizing disease risks: principles of disease control and management.

Week 13 Disease control strategies: economic thresholds, physical control methods.

Week 14 Cultural control methods: avoidance, tillage practices, crop sanitation, fertilizers, crop rotation.
SkriptDetailed lecture notes (~160 pages) will be available for purchase at the cost of reproduction at the start of the semester.
636-0017-00LComputational Biology Information W6 KP3G + 2AC. Magnus, T. Stadler, T. Vaughan
KurzbeschreibungThe aim of the course is to provide up-to-date knowledge on how we can study biological processes using genetic sequencing data. Computational algorithms extracting biological information from genetic sequence data are discussed, and statistical tools to understand this information in detail are introduced.
LernzielAttendees will learn which information is contained in genetic sequencing data and how to extract information from this data using computational tools. The main concepts introduced are:
* stochastic models in molecular evolution
* phylogenetic & phylodynamic inference
* maximum likelihood and Bayesian statistics
Attendees will apply these concepts to a number of applications yielding biological insight into:
* epidemiology
* pathogen evolution
* macroevolution of species
InhaltThe course consists of four parts. We first introduce modern genetic sequencing technology, and algorithms to obtain sequence alignments from the output of the sequencers. We then present methods for direct alignment analysis using approaches such as BLAST and GWAS. Second, we introduce mechanisms and concepts of molecular evolution, i.e. we discuss how genetic sequences change over time. Third, we employ evolutionary concepts to infer ancestral relationships between organisms based on their genetic sequences, i.e. we discuss methods to infer genealogies and phylogenies. Lastly, we introduce the field of phylodynamics. The aim of phylodynamics is to understand and quantify the population dynamic processes (such as transmission in epidemiology or speciation & extinction in macroevolution) based on a phylogeny. Throughout the class, the models and methods are illustrated on different datasets giving insight into the epidemiology and evolution of a range of infectious diseases (e.g. HIV, HCV, influenza, Ebola). Applications of the methods to the field of macroevolution provide insight into the evolution and ecology of different species clades. Students will be trained in the algorithms and their application both on paper and in silico as part of the exercises.
SkriptLecture slides will be available on moodle.
LiteraturThe course is not based on any of the textbooks below, but they are excellent choices as accompanying material:
* Yang, Z. 2006. Computational Molecular Evolution.
* Felsenstein, J. 2004. Inferring Phylogenies.
* Semple, C. & Steel, M. 2003. Phylogenetics.
* Drummond, A. & Bouckaert, R. 2015. Bayesian evolutionary analysis with BEAST.
Voraussetzungen / BesonderesBasic knowledge in linear algebra, analysis, and statistics will be helpful. Programming in R will be required for the "Central Element". We provide an R tutorial and help sessions during the first two weeks of class to learn the required skills.
701-1419-00LAnalysis of Ecological DataW3 KP2GS. Güsewell
KurzbeschreibungThis class provides students with an overview of techniques for data analysis used in modern ecological research, as well as practical experience in running these analyses with R and interpreting the results. Topics include linear models, generalized linear models, mixed models, model selection and randomization methods.
LernzielStudents will be able to:
- describe the aims and principles of important techniques for the analysis of ecological data
- choose appropriate techniques for given problems and types of data
- evaluate assumptions and limitations
- implement the analyses in R
- represent the relevant results in graphs, tables and text
- interpret and evaluate the results in ecological terms
Inhalt- Linear models for experimental and observational studies
- Model selection
- Introduction to likelihood inference and Bayesian statistics
- Analysis of counts and proportions (generalised linear models)
- Models for non-linear relationships
- Grouping and correlation structures (mixed models)
- Randomisation methods
SkriptLecture notes and additional reading will be available electronically a few days before the course
LiteraturSuggested books for additional reading (available electronically)
Zuur A, Ieno EN & Smith GM (2007) Analysing ecological data. Springer, Berlin.
Zuur A, Ieno EN, Walker NJ, Saveliev AA & Smith GM (2009) Mixed effects models and extensions in ecology with R. Springer, New York.
Faraway JJ (2006) Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models. Taylor & Francis.
Voraussetzungen / BesonderesTime schedule
The course takes place on Mondays 12:45-15:00 from 25 September until 27 November, with the final exam on Monday 4 December. The last two weeks of the semester are free.

Prerequisites
- Basic statistical training (e.g. Mathematik IV in D-USYS): Data distributions, descriptive statistics, hypothesis testing, linear regression, analysis of variance
- Basic experience in data handling and data analysis in R

Individual preparation
Students without the required knowledge are asked to contact the lecturer before the first lecture date for support with individual preparation.
701-1471-00LEcological Parasitology Belegung eingeschränkt - Details anzeigen
Number of participants limited to 20. A minimum of 6 students is required that the course will take place.

Waiting list will be deleted on September 29th, 2017.
W3 KP1V + 1PO. E. Seppälä, H. Hartikainen, J. Jokela
KurzbeschreibungCourse focuses on the ecology and evolution of macroparasites and their hosts. Through lectures and practical work, students learn about diversity and natural history of parasites, adaptations of parasites, ecology of host-parasite interactions, applied parasitology, and human macroparasites in the modern world.
Lernziel1. Identify common macroparasites in aquatic organisms.
2. Understand ecological and evolutionary processes in host-parasite interactions.
3. Conduct parasitological research
InhaltLectures:
1. Diversity and natural history of parasites (i.e. systematic groups and life-cycles).
2. Adaptations of parasites (e.g. evolution of life-cycles, host manipulation).
3. Ecology of host-parasite interactions (e.g. parasite communities, effects of environmental changes).
4. Applied parasitology (e.g. aquaculture and fisheries).
5. Human macroparasites (schistosomiasis, malaria).

Practical exercises:
1. Examination of parasites in fish (identification of species and description of parasite communities).
2. Examination of parasites in molluscs (identification and examination of host exploitation strategies).
3. Examination of parasites in amphipods (identification and examination of effects on hosts).
Voraussetzungen / BesonderesThe three practicals will take place at the 10.10.2017, the 24.10.2017 and the 7.11.2017 at Eawag Dübendorf from 08:15 - 12:00.
701-1427-00LExperimental EvolutionW4 KP2SG. Velicer, A. Hall, S. Wielgoss, Y.‑T. N. Yu
KurzbeschreibungStudents will analyze experimental evolution literature covering a wide range of questions, species and types of analysis and will lead discussions of this literature. Students will develop a written project proposal for a novel evolution experiment (or a novel analysis of a published experiment) to address an unanswered question and will also deliver an oral presentation of the project proposal.
LernzielCourse objectives:
i) become familiar with a diverse sample of experimental evolution literature,
ii) gain understanding of the strengths and limitations of experimental evolution for addressing evolutionary questions relative to other forms of evolutionary analysis, and
iii) gain the ability to effectively design and analyze evolution experiments that address fundamental or applied questions in evolutionary biology.
InhaltExperimental evolution is a powerful and increasingly prominent approach to investigating evolutionary processes. Students will analyze experimental evolution literature covering a diverse range of topics, species and types of analysis and will lead discussions of this literature. Students will develop a written project proposal for a novel evolution experiment (or a novel analysis of a published experiment) to address an unanswered question and will also deliver an oral presentation of the project proposal. Evaluation will be based on a combination of participation in and leadership of literature discussions, in-class exams, and oral and written presentations of the project proposal.
LiteraturPrimary research papers and review articles.
Voraussetzungen / Besonderes701-0245-00 Introduction to Evolutionary Biology (or equivalent).
701-1703-00LEvolutionary Medicine for Infectious DiseasesW3 KP2GA. Hall
KurzbeschreibungThis course explores infectious disease from both the host and pathogen perspective. Through short lectures, reading and active discussion, students will identify areas where evolutionary thinking can improve our understanding of infectious diseases and, ultimately, our ability to treat them effectively.
LernzielStudents will learn to (i) identify evolutionary explanations for the origins and characteristics of infectious diseases in a range of organisms and (ii) evaluate ways of integrating evolutionary thinking into improved strategies for treating infections of humans and animals. This will incorporate principles that apply across any host-pathogen interaction, as well as system-specific mechanistic information, with particular emphasis on bacteria and viruses.
InhaltWe will cover several topics where evolutionary thinking is relevant to understanding or treating infectious diseases. This includes: (i) determinants of pathogen host range and virulence, (ii) dynamics of host-parasite coevolution, (iii) pathogen adaptation to evade or suppress immune responses, (iv) antimicrobial resistance, (v) evolution-proof medicine. For each topic there will be a short (< 20 minutes) introductory lecture, before students independently research the primary literature and develop discussion points and questions, followed by interactive discussion in class.
LiteraturThe focus is on primary literature, but for some parts the following text books provide good background information:

Schmid Hempel 2011 Evolutionary Parasitology
Stearns & Medzhitov 2016 Evolutionary Medicine
Voraussetzungen / BesonderesA basic understanding of evolutionary biology, microbiology or parasitology will be advantageous but is not essential.
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