Suchergebnis: Katalogdaten im Herbstsemester 2021
Agrarwissenschaften Master ![]() | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Nummer | Titel | Typ | ECTS | Umfang | Dozierende | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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751-2903-00L | Evaluation of Agricultural Policies | W | 3 KP | 2G | R. Huber, R. Finger, C. Schader | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kurzbeschreibung | In this course, students get an overview of agricultural policy evaluations and their societal and political relevance. They learn to understand and apply the principles of scientific based evaluations of agricultural policies. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Lernziel | The course has four major learning objectives: 1) Students know the conceptual background of evaluations and can relate concepts in agricultural economics to the evaluation of policies. 2) They know the basics of how to design and implement a policy evaluation study. 3) Students can transfer their methodological knowledge from other agricultural economics courses to the context of agricultural policy evaluations (econometrics, modelling etc.). They make hands-on experiences of methodological challenges. 4) They can critically assess the science-policy interface of policy evaluations. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Inhalt | The course consists of two blocks: First, students will learn the basics of how to design, implement and interpret agricultural policy evaluations. In this block, the conceptual embedding, the design and methodological tools as well as case studies are presented. Secondly, the students make hands-on experience using econometric and modelling tools in the context of agricultural policy evaluations. They apply their theoretical and empirical knowledge to Swiss case studies. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Skript | Handouts and reading assignments | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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751-2205-00L | Management für Unternehmen der Agrar- und Ernährungswirtschaft II | W | 2 KP | 2G | M. Weber | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kurzbeschreibung | Advanced Management in the Agri-Food Chain: Framework und Managementmodelle für den Umgang mit Komplexität in Organisationen der Agri-Food Chain | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Lernziel | Nach der Vorlesung ... ... kennen die Studierenden die wichtigsten Charakteristiken und Konsequenzen der aktuellen Probleme in der Organisationswelt, ... kennen wichtige Managementmodelle und -konzepte für das heutige organisatorische Umfeld, ... kennen ausgewählte praktische Anwendungen und Beispiele der behandelten Inhalte und ... sind in der Lage, ihre Kenntnisse selbständig weiter zu vertiefen. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Inhalt | In der Vorlesung werden folgende Inhalte behandelt: - Zustand, Gründe und Wirkungen von Komplexität in der Organisationswelt. - Framwork für die Gestaltung, Lenkung und Entwicklung intelligenter Organisationen. - Ausgewählte aktuelle Managementmodelle für eine komplexe Organisationswelt. - Transfer und Anwendung der Modelle auf Organisationen in der Agri-Food Chain. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Skript | Foliensatz mit ausgewählten Inhalten. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Voraussetzungen / Besonderes | - Vorlesung "Management für Unternehmen der Agrar- & Ernährungswirtschaft I" in D-USYS Vorlesung wird in deutscher Sprache abgehalten | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kompetenzen![]() |
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751-2103-00L | Socioeconomics of Agriculture ![]() | W | 2 KP | 2V | S. Mann | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kurzbeschreibung | The main part of this lecture will examine constellations where hierarchies, markets or cooperation have been observed and described in the agricultural sector. On a more aggregated level, different agricultural systems will be evaluated in terms of main socioeconomic parameters like social capital or perceptions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Lernziel | Students should be able to describe the dynamics of hierarchies, markets and cooperation in an agricultural context. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Inhalt | Introduction to Sociology Introduction to Socioeconomics Agricultural Administration: Path dependencies and efficiency issues Power in the Chain The farming family Occupational Choices Consumption Choices Locational Choices Common Resource Management in Alpine Farming Agricultural Cooperatives Societal perceptions of agriculture Perceptions of farming from within Varieties of agricultural systems and policies | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Skript | http://www.springer.com/gp/book/9783319741406 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Literatur | see script | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Voraussetzungen / Besonderes | Basic economic knowledge is expected. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
751-1573-00L | Dynamic Simulation in Agricultural and Regional Economics | W | 2 KP | 2V | B. Kopainsky | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kurzbeschreibung | In dieser Vorlesung lernen die Studierenden die Grundzüge der Systemdynamik und deren Anwendung auf agrar- und regionalwirtschaftliche Fragestellungen. In der zweiten Vorlesungshälfte entwickeln die Studierenden ein eigenes Simulationsmodell, anhand dessen sie mögliche Interventionen zur Steigerung der ökonomischen als auch ökologischen Nachhaltigkeit von Ernährungssystemen evaluieren. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Lernziel | - Die Studierenden erlernen die Grundzüge der dynamischen Simulation. - Die Studierenden können angeleitet ein einfaches dynamisches Simulationsmodell aufbauen, analysieren, weiter entwickeln und Simulationsergebnisse interpretieren. - Über die Anwendung des entwickelten dynamischen Simulationsmodells gewinnen die Studierenden einerseits einen fundierten Einblick in Fragen der Ernährungsproblematik. Andererseits erkennen sie die Grenzen und das Potenzial der dynamischen Simulation, letzteres insbesondere auch in einem anwendungsorientierten Kontext. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Skript | Folien (werden während der Vorlesung zur Verfügung gestellt) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Literatur | Artikel (werden während der Vorlesung zur Verfügung gestellt) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
751-0423-00L | Risk Analysis and Risk Management in Agriculture | W | 3 KP | 2G | R. Finger | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kurzbeschreibung | Agricultural production is exposed to various risks and risk management is indispensable. This course introduces modern concepts on farmers' decision making under risk and risk management. We present innovative insights, emprical example from European agriculture. You gain hands-on experience using R. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Lernziel | -to develop a better understanding of decision making under uncertainty and risk; - gain hands-on experience in risk analysis and management using R -to gain experience in different approaches to analyze risky decisions; -to develop an understanding for different sources of risk in agricultural production; -to understand the crucial role of subjective perceptions and preferences for risk management decisions; -to get an overview on risk management in the agricultural sector, with a particular focus on insurance solutions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Inhalt | - Quantification and measurement of risk - Risk preferences, Expected Utility Theory, Cumulative Prospect Theory - Production and input use decisions under risk - Portfolio Theory and Farm Diversification - Forwards, Futures, Crop Insurance - Weather Index Insurance and Satellite Imagery - Empirical Applications using R | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Skript | Handouts will be distributed in the lecture and available on the moodle. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Voraussetzungen / Besonderes | knowledge of basic concepts of probability theory and microeconomics | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
363-0305-00L | Empirical Methods in Management | W | 3 KP | 2G | S. Tillmanns | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kurzbeschreibung | In this class, students learn how to understand and conduct empirical research. It will enable them to manage a business based on evident-based decision-making. The class includes group assignments, where students will cover small parts of the lecture content in self-created videos. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Lernziel | The general objective of the course is to enable students to understand the basic principles of empirical studies. After successfully passing the class, they will be able to formulate research questions, design empirical studies, and analyze data by using basic statistical approaches. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Inhalt | Data has become an important resource in today’s business environment, which can be used to make better management decisions. However, evidence-based decision-making comes along with challenges and requires a basic understand of statistical approaches. Therefore, this class introduces problems and key concepts of empirical research, which might be qualitative or quantitative in its nature. Concerning qualitative research, students learn how to conduct and evaluate interviews. In the area of quantitative research, they learn how to apply measurement and scaling methods and conduct experiments. In addition, basic statistical analyses like a variance analysis and how to conduct it in a standard statistical software package like SPSS are also part of the lecture. The lessons learned from the lecture will empower students to critically assess the quality and outcomes of studies published in the media and scientific journals, which might form a basis auf their decision-making. We recommend the lecture also to students without basic statistical skill, who plan to attend more advanced lectures in the field of artificial intelligence such as Marketing Analytics. The lecture will be taught online this fall semester. Therefore, it involves group work, where students form groups in order to create small learning videos, which cover small parts of the lecture. These videos will be shown and discussed in the online lecture and will make up 30% of the final grade. Part of this assignment will be the evaluation of videos from other students. The preparation of the videos will also prepare students for the final exam. In addition to that, there will be some non-mandatory online exercises as an additional opportunity to prepare for the exam. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Literatur | Literature and readings will be announced. For a basic undertanding we recommend the Handbook of Good Research by Jürgen Brock and Florian von Wangenheim. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Voraussetzungen / Besonderes | The course includes out-of-class assignments and projects to give students some hands-on experience in conducting empirical research in management. Projects will focus on one particular aspect of empirical research, like the formulation of a research question or the design of a study. Students will form groups and create a learning video regarding one specific topic. Assignments will be graded and need to be turned-in on time as they will be shown and discussed in class. Students will also have to evaluate the videos of other student groups. Online class participation is encouraged and can greatly improve students' learning. In this spirit, students are expected to attend class regularly and come to class prepared. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
851-0626-01L | International Aid and Development ![]() Maximale Teilnehmerzahl: 60 Voraussetzung: Verständnis der Grundlagen der Volkswirtschaftslehre. | W+ | 2 KP | 2V | K. Harttgen, I. Günther | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kurzbeschreibung | Die Veranstaltung vermittelt grundlegende ökonomische und empirische Kenntnisse um die Möglichkeiten und Grenzen internationaler Entwicklungszusammenarbeit zu verstehen und zu analysieren. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Lernziel | Ziel der Veranstaltung ist es, den Teilnehmenden ein wissenschaftlich fundiertes Verständnis von den Möglichkeiten und Grenzen internationaler Entwicklungszusammenarbeit zu vermitteln. Die Teilnehmer sollen aktuelle Instrumente der Entwicklungszusammenarbeit verstehen und kritisch diskutieren können. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Inhalt | Einführung: Ursachen von Unterentwicklung; Geschichte der Entwicklungszusammenarbeit (EZ); Zusammenhang EZ und Entwicklung: theoretische und empirische Perspektiven; Politische Ökonomie der EZ; Auswirkungen von EZ; Aktuelle Instrumente der EZ: z.B. Mikro-Finanzierung, Budget-Hilfe, Fair-Trade. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Literatur | Artikel und Auszüge aus Büchern, die elektronisch zur Verfügung gestellt werden. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Nummer | Titel | Typ | ECTS | Umfang | Dozierende | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
751-5101-00L | Biogeochemistry and Sustainable Management ![]() Findet dieses Semester nicht statt. | W | 2 KP | 2G | W. Eugster, V. Klaus | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kurzbeschreibung | 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Lernziel | Students will analyse and understand the complex and interacting processes of ecology, biogeochemistry and management of agroecosystems, be able to analyze large meteorological and flux data sets, and evaluate the impacts of weather events and management practices, based on real-life data. Moreover, students will be able to coordinate and work successfully in small (interdisciplinary) teams. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Inhalt | 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. Responses of agroecosystems to the environment, i.e., to climate and weather events, but also to management will be studied. 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 about the complex interactions of a coupled human-environmental system. Students will work with real-life data 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Skript | Handouts will be available on the webpage of the course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Literatur | Will be discussed in class. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Voraussetzungen / Besonderes | 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
751-3405-00L | Chemical Nature of Nutrients and their Availability to Plants: The Case of Phosphorus ![]() Number of participants limited to 15. Priority will be given to students in Agricultural Sciences | W | 4 KP | 4G | E. Frossard, L. P. Schönholzer, M. Wiggenhauser | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kurzbeschreibung | The course discusses the mechanistic relationships between nutrient speciation in fertilizer and nutrient uptake by plants using phosphorus as an example. The course involves theoretical aspects of nutrient cycling, laboratory work, data analysis and presentation, and the use of advanced methods in plant nutrition studies. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Lernziel | At the end of this course, participants will obtain a mechanistic understanding of why and how the speciation of phosphorus in fertilizer can affect its release to the soil solution and subsequent uptake by plants. Students will be able to use this information for the development of fertilization schemes that maximize the nutrient uptake and fertilizer efficiency of crops or pastures. During the course, participants will become familiar with the use of radioisotopes and nuclear magnetic resonance as approaches to measure nutrient availability and forms, respectively and they will know the limits of these techniques. Students will also have the opportunity to improve their laboratory and communication skills. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Skript | Documents will be distributed during the lecture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Literatur | Documents will be distributed during the lecture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Voraussetzungen / Besonderes | The lecture will take place at the ETH experimental station in Eschikon Lindau. See the location of the station at: http://www.plantnutrition.ethz.ch/the-group/how-to-find-us.html We strongly advise students who are planning to be absent for more than one week during the semester NOT to visit this course. Students must have visited the plant nutrition lectures in the 3rd and 6th semesters and the lecture pedosphere in the 3rd semester of the agricultural study program of the ETH (or bring an equivalent knowledge). This knowledge is indispensable for this 7th semester. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
751-5125-00L | Stable Isotope Ecology of Terrestrial Ecosystems ![]() ![]() Number of participants limited to 20. | W | 2 KP | 2G | R. A. Werner, N. Buchmann, A. Gessler, M. Lehmann | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kurzbeschreibung | This course provides an overview about the applicability of stable isotopes (carbon 13C, nitrogen 15N, oxygen 18O and hydrogen 2H) to process-oriented ecological research. Topics focus on stable isotopes as indicators for the origin of pools and fluxes, partitioning of composite fluxes as well as to trace and integrate processes. In addition, students carry out a small project during lab sessions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Lernziel | Students will be familiar with basic and advanced applications of stable isotopes in studies on plants, soils, water and trace gases, know the relevant approaches, concepts and recent results in stable isotope ecology, know how to combine classical and modern techniques to solve ecophysiological or ecological problems, learn to design, carry out and interpret a small IsoProject, practice to search and analyze literature as well as to give an oral presentation. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Inhalt | The analyses of stable isotopes often provide insights into ecophysiological and ecological processes that otherwise would not be available with classical methods only. Stable isotopes proved useful to determine origin of pools and fluxes in ecosystems, to partition composite fluxes and to integrate processes spatially and temporally. This course will provide an introduction to the applicability of stable isotopes to ecological research questions. Topics will focus on carbon (13C), nitrogen (15N), oxygen (18O) and hydrogen (2H) at natural isotope abundance and tracer levels. Lectures will be supplemented by intensive laboratory sessions, short presentations by students and computer exercises. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Skript | Handouts will be available on the webpage of the course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Literatur | Will be discussed in class. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Voraussetzungen / Besonderes | This course is based on fundamental knowledge about plant ecophysiology, soil science, and ecology in general. Course will be taught in English. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Nummer | Titel | Typ | ECTS | Umfang | Dozierende | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
751-4104-00L | Alternative Crops | W | 2 KP | 2V | A. Walter, K. Berger Büter | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kurzbeschreibung | Few crops dominate the crop rotations worldwide. Following the goal of an increased agricultural biodiversity, species such as buckwheat but also medicinal plants might become more important in future. The biology, physiology, stress tolerance and central aspects of the value-added chain of the above-mentioned and of other alternative crops will be depicted. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Lernziel | Im Verlauf des Kurses lernen die Studierenden, das Potential verschiedenster Kulturpflanzenarten im Vergleich zu den Hauptkulturarten auf der Basis ihrer biologischen und agronomischen Eigenschaften zu beurteilen. Jeder Studierende nimmt die Beurteilung einer von ihm oder ihr selbst ausgewählten alternativen Kulturart vor und stellt diese den anderen Kursteilnehmern dar. Dabei werden Fachartikel sowie Einträge in Wikipedia zu Hilfe gezogen und selbst bearbeitet. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
751-3603-00L | Current Challenges in Plant Breeding ![]() Maximale Teilnehmerzahl: 15 | W | 2 KP | 2G | B. Studer, A. Hund | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kurzbeschreibung | The seminar 'Current challenges in plant breeding' aims to bring together national and international experts in plant breeding to discuss current activities, latest achievements and future prospective of a selected topic/area in plant breeding. The topic this year will be: 'Plant Breeding a(nd) Data Science'. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Lernziel | The educational objectives cover both thematic competences and soft skills: Thematic competences: - Deepening of scientific knowledge in plant breeding - Critical evaluation of current challenges and new concepts in plant breeding - Promotion of collaboration and Master thesis projects with practical plant breeders Soft skills: - Independent literature research to get familiar with the selected topic - Critical evaluation and consolidation of the acquired knowledge in an interdisciplinary team - Establishment of a scientific presentation in an interdisciplinary team - Presentation and discussion of the teamwork outcome - Establishing contacts and strengthening the network to national and international plant breeders and scientist | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Inhalt | Interesting topics related to plant breeding will be selected in close collaboration with the working group for plant breeding of the Swiss Society of Agronomy (SSA). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Skript | None | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Literatur | Peer-reviewed research articles, selected according to the topic. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Voraussetzungen / Besonderes | Participation in the BSc course 'Pflanzenzüchtung' is strongly recommended, a completed course in 'Molecular Plant Breeding' is highly advantageous. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Nummer | Titel | Typ | ECTS | Umfang | Dozierende | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
751-5121-00L | Insect Ecology ![]() The number of participants is limited to 30. | W | 2 KP | 2V | C. De Moraes, M. Mescher, N. Stanczyk | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kurzbeschreibung | This is an introductory class on insect ecology. During the course you will learn about insect interactions with, and adaptations to, their environment and other organisms, and the importance of insect roles in our ecosystems. This course includes lectures, small group discussions and outside readings. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Lernziel | The aim of the course is to gain an understanding of how insects have specialised and adapted to occupy diverse environmental niches and become vital to ecosystem processes. Important topics include: insect-plant interactions, chemical ecology, predator-prey interactions, vectors of disease, social insects, mutual and parasitic interactions and examining insect ecology in an evolutionary context. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Skript | Provided to students through Moodle | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Literatur | Selected required readings (peer reviewed literature). Optional recommended readings with additional information. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
751-4811-00L | Alien Organisms in Agriculture ![]() Number of participants limited to 30. | W | 2 KP | 2G | J. Collatz, M. Meissle | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kurzbeschreibung | The course focuses on alien organisms in agriculture as well as the scientific assessment and regulatory management of their effects on the environment and agricultural production. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Lernziel | Students will understand the consequences arising from the unintentional or deliberate introduction of alien organisms into agricultural systems. They will be able to understand the concept of environmental risk assessment and be able to evaluate risk management options. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Inhalt | Alien organisms in agriculture is a topic that receives an increasing awareness among farmers, agricultural scientists, regulators and the general public. Students of this course will learn about the nature of alien organisms such as invasive species, biocontrol organisms and genetically modified organisms. With a particular focus on arthropods, plants and their interactions we will look at the potential threats the novel organisms pose, the benefits they provide and how both of these effects can be scientifically assessed. Students will learn how the topic of alien organisms in agriculture is intrinsically tied to policy making and regulation and get to know current examples and future challenges in research. In the last part of the course students will be able to apply the acquired knowledge in a practical exercise (case study). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Skript | Material will be distributed during the course | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Voraussetzungen / Besonderes | A part of the course will take place in flipped classroom mode, i.e. the lectures on 28.9., 5.10., 19.10., 16.11. and 23.11. will be available as podcasts. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
701-0263-01L | Seminar in Evolutionary Ecology of Infectious Diseases ![]() | W | 3 KP | 2G | R. R. Regös, S. Bonhoeffer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kurzbeschreibung | 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Lernziel | 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Inhalt | 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Skript | Publications and class notes can be downloaded from a web page announced during the lecture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Literatur | Papers will be assigned and downloaded from a web page announced during the lecture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
751-4506-00L | Pflanzenpathologie III ![]() Number of participants limited to 20. | W | 2 KP | 2G | M. Maurhofer Bringolf | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kurzbeschreibung | Identifikation der wichtigsten Krankheiten und ihrer pilzlichen Erreger von ein- und mehrjährigen, landwirtschaftlich wichtigen Pflanzenarten, basierend auf der Symptomatologie sowie den Mikro-Strukturen. Die zugehörigen Kontrollmassnahmen einiger wichtiger Schaderreger werden anhand ihrer Lebenszyklen erklärt. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Lernziel | - Erkennen der wichtigsten Pflanzenkrankheiten, d.h. deren Symptome (makroskopisch) - Präpariertechnik, Umgang mit Lupe und Mikroskop - Kenntnisse über die Biologie (Sporulationsorgane, Zyklus) der Erreger und ihre systematische Zuordnung - sichere DIAGNOSE - allgemeine sowie spezifische Kontrollmassnahmen (aus der Biologie abgeleitet) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Inhalt | Eine Lektion der LV wird als e-learning Uebung (computergestützt) durchgeführt. Dies gilt auch als Vorbereitung auf das e-exam (Schlussprüfung). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Skript | Es wird mit einem Skript (die Kulturen und ihre wichtigsten Krankheiten) gearbeitet. Dieses wird schrittweise aktualisiert. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Voraussetzungen / Besonderes | Der Kurs wird in deutscher Sprache geführt (spez. Terminologie) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Nummer | Titel | Typ | ECTS | Umfang | Dozierende | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
701-3001-00L | Environmental Systems Data Science ![]() | W+ | 3 KP | 2G | L. Pellissier, J. Payne, B. Stocker | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kurzbeschreibung | Students are introduced to a typical data science workflow using various examples from environmental systems. They learn common methods and key aspects for each step through practical application. The course enables students to plan their own data science project in their specialization and to acquire more domain-specific methods independently or in further courses. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Lernziel | The students are able to ● frame a data science problem and build a hypothesis ● describe the steps of a typical data science project workflow ● conduct selected steps of a workflow on specifically prepared datasets, with a focus on choosing, fitting and evaluating appropriate algorithms and models ● critically think about the limits and implications of a method ● visualise data and results throughout the workflow ● access online resources to keep up with the latest data science methodology and deepen their understanding | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Inhalt | ● The data science workflow ● Access and handle (large) datasets ● Prepare and clean data ● Analysis: data exploratory steps ● Analysis: machine learning and computational methods ● Evaluate results and analyse uncertainty ● Visualisation and communication | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Voraussetzungen / Besonderes | 252-0840-02L Anwendungsnahes Programmieren mit Python 401-0624-00L Mathematik IV: Statistik 401-6215-00L Using R for Data Analysis and Graphics (Part I) 401-6217-00L Using R for Data Analysis and Graphics (Part II) 701-0105-00L Mathematik VI: Angewandte Statistik für Umweltnaturwissenschaften | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
401-6215-00L | Using R for Data Analysis and Graphics (Part I) ![]() | W+ | 1.5 KP | 1G | M. Mächler | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kurzbeschreibung | The course provides the first part an introduction to the statistical software R (https://www.r-project.org/) for scientists. Topics covered are data generation and selection, graphical and basic statistical functions, creating simple functions, basic types of objects. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Lernziel | The students will be able to use the software R for simple data analysis and graphics. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Inhalt | The 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Skript | An Introduction to R. http://stat.ethz.ch/CRAN/doc/contrib/Lam-IntroductionToR_LHL.pdf | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Voraussetzungen / Besonderes | The course resources will be provided via the Moodle web learning platform. As from FS 2019, subscribing via Mystudies should *automatically* make you a student participant of the Moodle course of this lecture, which is at https://moodle-app2.let.ethz.ch/course/view.php?id=15518 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
401-6217-00L | Using R for Data Analysis and Graphics (Part II) ![]() | W+ | 1.5 KP | 1G | M. Mächler | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kurzbeschreibung | The 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Lernziel | The students will be able to use the software R efficiently for data analysis, graphics and simple programming | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Inhalt | The course provides the second part of an introduction to the statistical software R (https://www.r-project.org/) 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Skript | An Introduction to R. http://stat.ethz.ch/CRAN/doc/contrib/Lam-IntroductionToR_LHL.pdf | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Voraussetzungen / Besonderes | Basic 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. As from FS 2019, subscribing via Mystudies should *automatically* make you a student participant of the Moodle course of this lecture, which is at https://moodle-app2.let.ethz.ch/course/view.php?id=15522 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
751-5510-00L | Introduction to Agricultural Robotics ![]() Number of participants limited to 20. | W+ | 3 KP | 2G | S. Mintchev | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kurzbeschreibung | In this course, students will learn theoretical and practical aspects of robotics. Lectures will give an introduction to how robots operate in the real world. Students will apply the concepts learned in class on educational robots to simulate a weeding task. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Lernziel | After the course, students will be able to critically examine and select appropriate robotic solutions for agricultural applications. The learning objectives of the course are: (i) illustrate the principle of operation of the main components of a robotic system, (ii) analyse how the different robotic components are integrated and contribute to the functioning of a robotic system, and (iii) solve problems in the field of agriculture using robotic principles. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Inhalt | Robots are becoming a key technology in the transition to smart farming and in supporting the agricultural needs of the 21st century. For example, robots enable site-specific fertilization, automated weeding, or livestock herding. The course gives an overview of robotic systems, beginning with their fundamental components (e.g., sensors, actuators, locomotion strategies) and gradually scaling up to the system level, illustrating the concepts of perception, robot control, obstacle avoidance and navigation. Exercises performed with an educational robot (Thymio) will complement the theoretical lectures providing a hands-on practical experience of the challenges of using these machines. During the course, students will gradually apply the theoretical and practical knowledge they are learning. To this end, students will work in small teams (2 to 3 members) to develop a robotic solution for an agricultural task of their choice. Students will learn to translate the task into meaningful requirements for a robotic system and critically select the most appropriate components to achieve the required robotic functions. Students will periodically present and discuss the development of this "robot design" exercise during presentations and in a journal report. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Skript | Copies of the slides and exercises will be provided on the course web page | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Literatur | S. Asseng and F. Asche, “Future farms without farmers,” Sci. Robot., vol. 4, no. 27, p. eaaw1875, Feb. 2019. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Voraussetzungen / Besonderes | No mandatory prerequisites, but it is preferable that students have a basic knowledge of computer programming. Class size limitation to 20 students. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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