GfÖ workshop-series

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GfÖ Workshop Series 2023

Introduction to Workshops:

Costs: The workshops are free of charge! Accommodation, travel costs and food expenses have to be covered by every participant themselves.
Requirements for participation: GfÖ Membership! (Non-members cannot be considered). No member yet? Here you can join the GfÖ family and gain the chance to register for our workshops for free (as long as there are places left, first come, first serve)!
Target group: early career researchers in Ecology (mainly PhD level)

Please find our registration form here: GfÖ workshop registration form!


Workshop 1

Scientific writing in the field of Ecology

Lecturer: Prof. Dr. Anne Mupepele, University of Marburg, and Prof. Dr. Roland Brandl, University of Marburg

Date:  19.-21. June 2023

Number of course places: 20

Language: English

Course format: hybrid: in person and online block course

Location: Marburg

Short description: The ‘science of scientific writing’ was the name of an article published by Gopen and Swan in the American Scientist already in 1990. Scientific writing can be seen as a science on its own, which means that they are rules and techniques that can be learnt to improve in scientific writing.

We are going to address these rules and critically analyse what are the criteria for a good article and practice how you can compose one on your own. It will also help you to get started with your own writing projects and we are going to look at how to structure a text into paragraphs before starting the real writing. Requirements: A notbeook, ideally you already use and are familiar with a citation program that is installed, such as Zotero, JabRef, Mendeley, Citavi, Endnote

Record of participation: Signed GfÖ-Workshop 2023 certificate


Workshop 2

Statistics: Advanced regression models

Lecturer: Prof. Dr. Florian Hartig, University of Regensburg

Date: 22.05-26.05.2023

Number of course places: 10

Number of other participants: ~ 20 joined course of University of Regensburg

Language: English

Course format: online block course

Short description: The aim of this course is to introduce participants to modern statistical methods beyond what is typically covered in a first statistics class. We will cover commonly used advanced regression models (GLS, GAM, LMM, GLMM), resampling methods (cross-validation, bootstrapping), and some machine-learning applications, as well as guidance to deal with typical regression problems, such as heteroscedasticity or spatial autocorrelation. Teaching will consist of short theoretical instructions, demonstrations in R, and exercises in R.


  • Reminder: basic regression methods (LM and GLM)
  • Fundamentals of statistical model choice (predictive, causal), causal inference, SEMs
  • Modeling Spatial, temporal and phylogenetic correlation structures (GLS and GLMMs, R package nlme and glmmTMB)
  • Mixed models (LMM und GLMM, R packages nlme, lme4, glmmTMB)
  • Model selection and regularization methods (AIC, ridge and lasso regression)
  • Resampling methods (bootstrap, cross-validation)
  • Generalized additive models (GAM)
  • Principles and applications of machine learning

All methods will be taught with biological applications, in particular: Analysis of blocked experiments, Species distribution models, Analysis of trait data

Requirements: Minimum requirement for this course is an introductory statistics lecture, an introductory R course and being able to comfortably operate in R / RStudio.

Record of participation: Signed GfÖ-Workshop 2023 certificate; Written final project (take home) after the course.


Workshop 3

[ waiting-list ]

Machine learning and AI

Lecturer: Prof. Dr. Florian Hartig, University of Regensburg

Date: 03.07. - 07.07.2023 (changed date)

Number of course places: 10

Number of other participants: ~ 20 joined course of University of Regensburg

Language: English

Course format: online block course

Short description: This course provides a practical and general introduction into machine learning / predictive models with Google TensorFlow and Keras in R. We will cover the standard task in a practical data project, as well as todays's standard methods in machine learning and AI.

Topics covered include:

  • Data cleaning and preparation
  • The TensorFlow / Keras framework
  • Principles of machine learning - training, (cross)validation, predictions, regularization methods
  • Standard algorithm: SVM, RF, KNN, BRT, single-layer NNs
  • Regression and image classification with deep learning (DNNs, CNNs)
  • Advanced algorithms (RNN, GAN, VAE, reinforcement-learning, Auto-ML)

Methods will be shortly explained, but the course will mostly concentrate on the practical aspects of running these algorithms in R. It is therefore highly recommended to participants to get some prior information on the methods (what the idea is, what they do) in advance of the course, either via studying the recommended readings, or through taking the recommended lectures on machine learning.

Requirements: Prior knowledge of R and stats required for this course. Minimum requirement for this course is an introductory statistics lecture, an introductory R course and being able to comfortably operate in R / RStudio. Prior knowledge in statistical learning is also recommented.

Record of participation: Signed GfÖ-Workshop 2023 certificate; Successful completion of a data analysis project after the course.


Workshop 4

[ waiting-list ]

Experimental design in different fields of ecology

Lecturer: to be announced

Date: to be announced

Number of course places: to be announced

Language: to be announced

Course format: to be announced

Short description: This course will give an overview over commonly used experimental design methods in ecological (field) experiments, their advantages and disadvantages and how to carry them out. During the excursion day we will visit different existing (field) experiments to get an impression of the in-situ realization of presented experimental designs.


Record of participation: Signed GfÖ-Workshop 2023 certificate


Workshop 5

Modern Data Management against the background of FAIR

Lecturer: Dr. Jens Nieschulze

Date: 25.-27. Sept. 2023

Time: 9:00 - 13:00 CEST 

Number of course places: tba

Short description:

  • Mobile data capture (ODK) 
  • Data cleaning (OpenRefine) 
  • Version control/collaborative working (Git) 

Record of participation: Signed GfÖ-Workshop 2023 certificate


Workshop 6

Exploring Agent-Based Modeling with NetLogo: Fundamentals and Applications

Lecturers: Dr. Cara Gallagher, University of Potsdam, and Dr. Viktoriia Radchuk, Leibniz Institute for Zoo and Wildlife Research, Berlin

Date: 16.10-19.10.2023
Number of course places: 15
Language: English
Course format: in person, first lecture day online
Location: Berlin, Leibniz Institute for Zoo and Wildlife Research, 
Lecture hall

Short description: This course introduces the fundamentals of object-oriented and agent-based modeling using the NetLogo platform. The conceptual background of agent-based modeling will be discussed, along with a variety of real-world applications to demonstrate the potential of this approach. Hands-on activities include developing simple models to represent behavior, thermoregulation, and population dynamics of a species.

A large part of the course will be devoted to learning how to test, debug, and analyse models, specifically focusing on sensitivity analysis. A theory of how to find the appropriate level of model complexity will also be covered. 

The course is structured in a way that integrates short lecture sessions, walk-throughs in NetLogo, and hands-on NetLogo exercises. The lecture sessions will provide the theoretical background for the concepts covered, the walk-throughs will demonstrate how these concepts are implemented in NetLogo, and the hands-on exercises will give students the opportunity to apply what they have learned and gain practical experience with the software.

Requirements: This course is designed for beginners with no prior experience in modeling or programming. However, individuals with prior modeling experience in other languages who are interested in learning NetLogo or those with some NetLogo experience looking to further develop their skills are also welcome to enroll.

Record of participation: Signed GfÖ-Workshop 2023 certificate


Species Identification skills

Species Identification skills (“Artenkennerzertifikate”)

Would you like to improve your species identification skills? Here's the way to do it for free in 2023! To meet the high demand for diverse species identification courses, the GfÖ supports its members financially in acquiring species identification certificates in 2023.

Thus, members can submit their costs for a species identification certificate in 2023 and receive a refund up to the maximum amount of 200€ per member. The procedure is based on the principle of first come, first serve.

This enables covering significantly more species groups and members can obtain individual species identification certificates for their preferred species groups. The request for covering certificate costs for 2023 can be sent directly to Subsequently the member will recieve a confimation for the coverage of costs as long as the financial resources are sufficient.