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300007 UE Species distribution modelling (2021S)
Prüfungsimmanente Lehrveranstaltung
Labels
DIGITAL
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Do 11.02.2021 08:00 bis Do 25.02.2021 18:00
- Abmeldung bis Mi 31.03.2021 18:00
Details
max. 16 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine
First meeting: 04/03/2021, 9 - 10.00, online
The course will be 19 - 23/04, 9 - 17.00. Ideally in our seminar room at Rennweg 14, but, given the current COVID situation most likely as an online-course. More on this during the first meeting.Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
Participants will work in groups of two. Each group will have its own 'project' including the full sequence of modelling, projection and analysis work. Evaluation will be based on work during the course and on a final 15-min presentation of the groups' results.
Mindestanforderungen und Beurteilungsmaßstab
The course requires basic familiarity with R. As there will be groups of two, knowledge of partners may be complementary.
Positive evaluation requires regular presence, active work during the course and doing at least part of the final presentation.
Positive evaluation requires regular presence, active work during the course and doing at least part of the final presentation.
Prüfungsstoff
Literatur
Guisan A. & Zimmermann N. E. 2000: Predictive habitat distribution models in ecology. Ecological Modelling 135: 147- 86.Guisan, A. & Thuiller, W. 2005: Predicting species distributions: offering more than simple habitat models. Ecology Letters 8: 993-1009.Thuiller, W. et al. 2009: BIOMOD - A platform for ensemble forecasting of species distributions. Ecography: 32, 369-373.Franklin, J. 2010: Mapping species distributions. Cambridge University Press.Guisan, A., Thuiller, W. & Zimmermann, N.E. 2017: Habitat suitability and distribution models. Cambridge University Press.
Zuordnung im Vorlesungsverzeichnis
MEC-6, MBO 7
Letzte Änderung: Fr 14.05.2021 11:08
The course will combine introductory lectures with pratical work. Practical work will include all main steps from data preparation, model parameterization & evaluation to projection, mapping and analysis of projection results. All practical work will be done in R.