Universität Wien
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300108 VU Macroecology and spatial phylogenetics of animals (2025S)

(Data Analysis and modelling)

5.00 ECTS (3.00 SWS), SPL 30 - Biologie
Continuous assessment of course work
We 05.03. 11:30-13:00 Hörsaal (Fakultätszentrum für Biodiversität) Rennweg EG

Details

max. 12 participants
Language: English

Lecturers

    Classes (iCal) - next class is marked with N

    • Monday 07.04. 10:00 - 17:00 Übungsraum 1 (Fakultätszentrum für Biodiversität) Rennweg 1.OG
    • Tuesday 08.04. 10:00 - 17:00 Übungsraum 1 (Fakultätszentrum für Biodiversität) Rennweg 1.OG
    • Wednesday 09.04. 10:00 - 17:00 Übungsraum 1 (Fakultätszentrum für Biodiversität) Rennweg 1.OG
    • Thursday 10.04. 10:00 - 17:00 Übungsraum 1 (Fakultätszentrum für Biodiversität) Rennweg 1.OG
    • Friday 11.04. 10:00 - 17:00 Übungsraum 1 (Fakultätszentrum für Biodiversität) Rennweg 1.OG

    Information

    Aims, contents and method of the course

    In this course students will learn how to use molecular phylogenies in conjunction with distributional data to tackle questions in the fields of macroecology and spatial phylogenetics. Species diversity and phylogenetic diversity measures will be combined with climate and topographic data in a geographic grid-based approach using GIS applications and subsequent analysis with custom R scripts. Students will be instructed how to interpret their results and extract the relevant conclusions. Issues in dealing with large and complex datasets will be discussed, practical solutions presented and applied. Target organisms are terrestrial arthropods (Lepidoptera) and vertebrates (birds and mammals).

    The following aspects will be treated in particular:

    1. Students will be introduced to basic concepts in the fields of macroecology and spatial phylogenetics.
    2. Strategies and methods for data acquisition (e.g. climate, topography, species distribution) from online databases will be discussed and applied
    3. Students will be introduced to the use of GIS applications for spatial analysis
    4. Results obtained in the course will be discussed and their interpretation and limitations explored.

    Students are asked to bring their own laptop computer to the course, since there is limited capacity to accommodate students unable to do so. Please approach the instructors at the initial meeting if you are unable to bring your own computer. Systems running under Windows, MacOS and Linux are equally suitable for this course. Prior knowledge of R or GIS applications is not required.

    Assessment and permitted materials

    Students will work in teams of two, with each group working on a different dataset provided by the instructors.

    Students are expected to actively participate in the course, show initiative in problem solving and search for literature relevant to their topic.

    Students are expected to show their ability to discern relevant aspects of the results obtained in the course and condense those into a written report where the results are presented and interpreted in relation to the published literature. The report is to be written in English; length approximately 4000 to 6000 words. Further instructions will be provided on the first course day.

    Minimum requirements and assessment criteria

    The following criteria apply in order to receive a passing grade:

    1. Active participation
    2. Submission of a written report; initial draft no later than May 26th 2025; final version no later than June 30th 2024
    3. Give a short, informal presentation outlining the results obtained in the course.
    4. Attendance is mandatory on all days including the initial meeting on March 5th. A maximum of one day of absence is permitted.

    Contribution to final grade:
    25% Active participation
    60% Written report
    15% Presentation

    Examination topics

    Reading list

    See the following publication for further clarification of the course’s content:

    Earl C, Belitz MW, Laffan SW, Barve V, Barve N, Soltis DE, Allen JM, Soltis PS, Mishler BD, Kawahara AY, Guralnick R 2020. Spatial phylogenetics of butterflies in relation to environmental drivers and angiosperm diversity across North America.
    bioRxiv 2020.07.22.216119; doi: https://doi.org/10.1101/2020.07.22.216119

    Association in the course directory

    MEC-9, MZO W2, MZO4, MNB6, MNB2, MES5

    Last modified: Fr 10.01.2025 00:02