Search result: Catalogue data in Autumn Semester 2023
Environmental Sciences Master  | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
 Major in Ecology and Evolution | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| B. Concept Courses and Applications | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Advanced Concept Classes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Number | Title | Type | ECTS | Hours | Lecturers | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 701-0263-01L | Seminar in Evolutionary Ecology of Infectious Diseases  | W | 3 credits | 2G | R. R. Regös, S. Bonhoeffer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Students of this course will discuss current topics from the field of infectious disease biology. From a list of publications, each student chooses some themes that he/she is going to explain and discuss with all other participants and under supervision. The actual topics will change from year to year corresponding to the progress and new results occuring in the field. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | This is an advanced course that will require significant student participation. Students will learn how to evaluate and present scientific literature and trace the development of ideas related to understanding the ecology and evolutionary biology of infectious diseases. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | A core set of ~10 classic publications encompassing unifying themes in infectious disease ecology and evolution, such as virulence, resistance, metapopulations, networks, and competition will be presented and discussed. Pathogens will include bacteria, viruses and fungi. Hosts will include animals, plants and humans. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Publications and class notes can be downloaded from a web page announced during the lecture. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Papers will be assigned and downloaded from a web page announced during the lecture. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 701-1409-00L | Research Seminar: Ecological Genetics Minimum number of participants is 5. | W | 2 credits | 1S | S. Fior | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | In this research seminar we will critically discuss recent publications on current topics in Ecological Genetics. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | It is our aim that participants gain insight into current research topics and approaches in Ecological Genetics and learn to critically assess and appreciate scientific publications in this field. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | none | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | will be distributed | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Active and regular participation in the discussions, together with the presentation of a scientific paper are required to successfully pass this course. It is strongly recommended that participants have in advance successfully participated in the course Evolutionary Genetics (701-2413-00) or Ecological Genetics (701-1413-01). | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 701-1471-00L | Ecological Parasitology A minimum of 6 students is required that the course will take place. | W | 3 credits | 1V + 1P | F. Feijen, J. Jokela, C. Vorburger | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Course 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. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | 1. Identify common macroparasites in invertebrates. 2. Understand ecological and evolutionary processes in host-parasite interactions. 3. Conduct parasitological research | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Lectures: 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. Ecology and evolution of parasitoids and their applications in biocontrol 5. Human macroparasites (schistosomiasis, malaria). Practical exercises: 1. Examination of parasites in molluscs (identification and examination of host exploitation strategies). 2. Examination of parasites in amphipods (identification and examination of effects on hosts). 3. Examination of parasitoids of aphids. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | The three practicals will take place at the 03.10.2023, the 17.10.2023 and the 07.11.2023 at Eawag Dübendorf from 08:15 - 12:00. Note that each practical takes 2 hours longer than the weekly lecture. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 701-1676-01L | Genomics of Environmental Adaptation Prerequisites: good knowledge in population genetics and some experience in using GIS and R is required. | W | 2 credits | 3G | R. Holderegger, F. Gugerli, C. Rellstab | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This five-day winter school aims at teaching advanced Master students, PhD students and postdoctoral researchers on aspects of the genomics of environmental adaptation. It provides both theoretical background and hands-on exercises on major topics of contemporary environmental genomics such as signatures of selection, outlier analysis, genotype-environment associations, or GWAS. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The genomics of environmental adaptation is an evolving scientific field of both basic and applied interest. Researchers make increasing use of diverse methodological approaches built on concepts from ecology, evolutionary biology and population genomics. This five-day winter school introduces students to some major concepts and methods of environmental genomics, i.e., (i) how the environment and adaptive genetic variation are related and (ii) how signatures of genomic adaptation can be detected in natural populations. The winter school focuses on current methods and hands-on exercises, emphasizing an understanding of the underlying concepts and a discussion of benefits, limitations and pitfalls of environmental genomics. It is specifically aimed at the needs of advanced Master students, PhD students and early postdoctoral researchers. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Topics: (1) Molecular markers and next generation sequencing techniques; neutral and adaptive genetic variation, genetic drift and genetic population structure. (2) Outlier analysis: concept, methodology and types of outlier analyses. (3) Environmental data: which environmental data are available and used to identify signatures of adaptation; data limitations; collinearity. (4) Genotype-environment associations (landscape genomics): concept and types of genotype-environment associations; false discovery rates; genomic offset. (5) Genotypes and phenotypes: GWAS; follow-up analyses. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Hand-outs will be distributed. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | The course requires 4 hours of preparatory reading of selected papers on the genomics of environmental adaptation. The papers will be distributed by e-mail. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Grading will be according to a written report (8-10 pages), in which students will have to design a complete study in environmental genomics, and according to student contributions during the course. Prerequisites: students must have good knowledge in population genetics and evolutionary biology and some experience with R and GIS. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 701-1703-00L | Evolutionary Medicine for Infectious Diseases | W | 3 credits | 2G | A. Hall | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This 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. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Students 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. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | We 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. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | The 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 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | A basic understanding of evolutionary biology, microbiology or parasitology will be advantageous but is not essential. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 636-0017-00L | Computational Biology | W | 6 credits | 3G + 2A | T. Vaughan, C. Magnus, T. Stadler | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | The 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. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Attendees 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 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The 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 which is to understand and quantify 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. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Lecture slides will be available on moodle. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | The 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. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Basic knowledge in linear algebra, analysis, and statistics will be helpful. Programming in R will be required for the project work (compulsory continuous performance assessments). In case you do not have any previous experience with R, we strongly recommend to get familiar with R prior to the semester start. For the D-BSSE students, we highly recommend the voluntary course „Introduction to Programming“, which takes place in Basel before the start of the semester. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 751-5101-00L | Biogeochemistry and Sustainable Management | W | 2 credits | 2G | I. Feigenwinter, N. Buchmann | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course focuses on the interactions between ecology, biogeochemistry and management of agro- and forest ecosystems, thus, coupled human-environmental systems. Students learn how human impacts on ecosystems via management or global change are mainly driven by effects on biogeochemical cycles and thus ecosystem functioning, but also about feedback mechanisms of terrestrial ecosystems. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Students will analyse and understand the complex and interacting processes of ecology, biogeochemistry and management of agroecosystems, set up a small weather station and program a data logger to collect meteorological variables, analyze large meteorological and flux data sets, and evaluate the impacts of weather events and management practices, based on real-life data. Thus, students will expand their computational competences. Moreover, students will be able to coordinate and work successfully in small (interdisciplinary) teams. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Agroecosystems play a major role in all landscapes, either for production purposes, ecological areas or for recreation. The human impact of any management on the environment is mainly driven by effects on biogeochemical cycles. Effects of global change impacts will also act via biogeochemistry at the soil-biosphere-atmosphere-interface. Thus, ecosystem functioning, i.e., the interactions between ecology, biogeochemistry and management of terrestrial systems, is the science topic for this course. Students will gain profound knowledge about biogeochemical cycles and greenhouse gas fluxes in managed grassland and/or cropland ecosystems as well as expand their computational competences. Responses of agroecosystems to the environment, i.e., to climate and weather events, but also to management will be studied. Campbell dataloggers will be programmed and a small weather station will be set up. Different meteorological and greenhouse gas flux data will be analysed (using R) and assessed in terms of production, greenhouse gas budgets and carbon sequestration. Thus, students will learn how to collect, analyse and interpret data about the complex interactions of a coupled human-environmental system. Students will work in groups (3-4 persons per group) with real-life data from a small weather station (dedicated to the course) and from the long-term measurement network Swiss FluxNet. Data from the intensively managed grassland site Chamau will be used to investigate the biosphere-atmosphere exchange of CO2, H2O, N2O and CH4. Functional relationships will be identified, greenhouse gas budgets will be calculated for different time periods and in relation to management over the course of a year. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Handouts will be available in moodle. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Prerequisites: Attendance of introductory courses in plant ecophysiology, ecology, and grassland or forest sciences. Knowledge of data analyses in R and statistics. Course will be taught in English. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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