Prof. Dr. Carsten F. Dormann

Telefon: +49 761 203-3749
Telefax: +49 761 203-3751
eMail: carsten.dormann@biom.uni-freiburg.de 




Frau Eva Meier

Telefon: +49 761 203-3749 
Telefax: +49 761 203-3751 
eMail: eva.meier@biom.uni-freiburg.de 




Biometrie und Umweltsystemanalyse

Albert-Ludwigs-Universität Freiburg

Tennenbacher Straße 4 
79106 Freiburg i. Br.


Sie sind hier: Startseite Lehre / Teaching Themen für Abschlussarbeiten / Offers for bachelor or master projects Computer-based work (strong literature review component)

Computer-based work (strong literature review component)


1.   Individual-based models vs mean-field approach: what do we need?

Topic: In ecology and sociology, the huge variability in behaviour and the large variability in any trait of relevance among individuals has led to a strong push for so-called "individual-based" models, aka "agent-based models". These represent individuals, with fixed traits, but large variation among individuals. Such IBM/ABMs contrast with traditional, "theoretical" models, which are referred to as "mean-field approaches" (MFA).

It can be easily shown, for hypothetical situations, that IBM and MFAs may differ substantially in population dynamics. But does this potential difference actually matter in real systems?

Methods: Literature review of all studies comparing IBM and MFA. In google scholar, "("individual-based model" or "agent-based model") AND "mean field"" yields just over 200 papers, most probably irrelevant.

Suitable as: BSc or MSc thesis project

Time: A start is possible at any time.

Requirements: Interests in rather abstract system descriptions and model behaviour; meta-analysis.

Contact: Carsten Dormanncarsten.dormann@biom.uni-freiburg.de


2.   Are arthropod communities on trees more strongly determined by tree age or tree species identity? [Literature review with strong quantitative analysis component; multivariate statistics in R]

Topic: Tree diversity experiments, such as the IDENT site in Freiburg, allow clear conclusions about effects of biodiversity and tree species combinations on ecosystem functions, and the underlying mechanisms. But given the relatively small scale of such experiments, it can be challenging how to transfer results to real-world forests.
In the tree diversity experiment IDENT-Freiburg, we have sampled arboreal arthropods over several years now, revealing how biodiversity affects herbivory and arthropod communities.

Aim / Methods: The aim of this thesis is to compile arthropod community data from the literature for the same tree species as planted in the experiment, and compare community composition between the data from the IDENT experiment and data from literature sources with varying tree age. This involves literature search, data extraction and data analysis.

Interest in community ecology and entomology. Some experience with R, ideally with analysis of biodiversity / community data.

Time: project can start anytime. Suitable as BSc or MSc project.

Contact: Jochen Fründ (jochen.fruend@biom.uni-freiburg.de)


3.   Author networks and 'kinship' in meta-analyses

anne-mupepele author networks

Background: In meta-analyses the results of primary studies are synthesized to improve and generalize knowledge. Primary studies included in a meta-analysis have to address the same or at least a similar question, for example the relationship between agroforestry and biodiversity. Authors of primary studies addressing questions that would be subsumed in one meta-analysis often come from a handful of labs only. It is not rare to have the same first or last author in several primary studies which are all included in one meta-analysis.

With this thesis we want to test if such an author network, similar to a phylogeny, influences the results of the meta-analysis, for example with results more similar to each other if they come from the same lab or an otherwise closely related author network.

Aim / Methods: Use of various R-packages, such as ‘bib2df’, ‘statnet’ or ‘igraph’ to extract data from existing meta-analysis and to compute author networks; ‘vegan’ to calculate distances between authors and ‘brms’ for mixed-effect models with a correlation structure.

Requirements: Interest in quantitative ecology.

Language: English or German.

Data: Existing and published meta-analyses (of any topic of interest).

Time: Project can start anytime. Suitable as MSc project..


 Carsten Dormanncarsten.dormann@biom.uni-freiburg.de

 Anne Mupepele, anne-christine.mupepele@nature.uni-freiburg.de

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