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W1 En-ROADS Simulator

W2 Group Model Building as a form of Participatory Modeling for a holistic representation of complex adaptive systems

W3 Participatory explorative stakeholder modeling

W4 Towards unified principles for movement modelling

W5 Differences and Similarities between Social-ecological and Ecological-economic Models for Land-based Biodiversity Conservation

W6 Effective digital note taking: How to organize your knowledge and streamline your workflow

W7 Computational notebooks for more openness, reproducibility, and productivity in research

W8 Ecological modelling for environmental risk assessment – exploring career opportunities outside of academia

W9 Designing Dynamic Data-Driven Digital Twin Systems in Ecology

W10 Talking about models

W11 Reducing ambiguities and increasing efficiency – introducing (semi-)formal approaches into ecological modeling and simulation studies

W1 En-ROADS Simulator

Hans Dieter Kasperidus, Helmholtz Centre for Environmental Research – UFZ / Department Conservation Biology and Social-Ecological Systems

Monday, Sept 4, 2 p.m., Saal 1A

The interactive workshop introduces the En-ROADS simulator, which is a cutting-edge modelling tool developed by Climate Interactive, a leading nonprofit climate & energy think tank, in partnership with the MIT Sloan Sustainability Initiative. En-ROADS is a complex  System Dynamics model that is transformed into a freely accessible online simulation tool. The simulation model represents key processes in the energy system and its connections to climate, economy, and environment for a single, global region.

Participants will learn the basic features that are necessary to test solutions and build scenario for addressing climate change issues, proposing global actions in the fields of energy efficiency, carbon pricing, fossil fuel taxes, reducing deforestation, and carbon dioxide removal and others. Participants can see the impacts of proposes actions on global temperature and other environmental, social and economic factors in real-time. The goal of the workshop is to create a scenario that limits global warming to well below 2°C and aims for 1.5°C above pre-industrial levels according to the Paris 2015 climate agreement.

W2 Group Model Building as a form of Participatory Modeling for a holistic representation of complex adaptive systems

Christoph Schünemann, Leibniz Institute of Ecological Urban and Regional Development (IOER), Dresden, Germany

Monday, Sept 4, 2 p.m., Saal 1B

Ecological modelling of (social) adaptive complex system often requires inter- and transdisciplinary knowledge to capture in a holistic representation system knowledge that exceeds the limited mental model of the modeler or modelling team. Involving non-scientific stakeholders and experts in a participatory modeling format is a suitable solution to address this problem and in addition to strengthen the stakeholder ownership and thus the use of the model in practice. Group Model Building (GMB), a form of Participatory Modeling that has emerged from the field of System Dynamics, provides both a framework and a toolbox of building blocks for adaptive planning of participatory modelling sessions.

The GMB workshop offered will introduce the participants to the process of a participatory modeling exercise addressing an example of a complex problem. The knowledge of the participants is translated into a graphical causal model by the modeling team. The model goes beyond linear causality to depict the interdependencies of feedbacks that govern both ecological and social systems (Causal Loop Diagrams). The agenda will be divided into the following points:

  1. Introduction into Group Model Building
  2. Dynamic problem definition (Reference mode)
  3. Joint identification of the main variables of the complex problem
  4. Creating a joint Causal Loop Diagram
  5. Identification and discussion of feedback loops
  6. Implementation of interventions and policies
  7. Summary, discussion and outlook

W3 Participatory explorative stakeholder modeling

Kai Neumann

Tuesday, Sept 5, 6:15 p.m., Saal 1A

Using the web based software iMODELER for qualitative cause and effect modeling and the know-why-method as a technique for facilitation is an effective way to work with stakeholders from various fields. The direct translation of arguments into cause and effect relations works as a lingua franca between the different fields. Within the workshop the participants will experience the ease of this approach on a freely chosen environmental topic. The first step is to collect arguments, the second to qualitatively weight the connections and identify the levers and hinderances through an analysis using the insight matrix (the concept is comparable to fuzzy cognitive maps, FCM), and finally the third step to interpret and communicate the insights.

Participants can use their devices (smartphone, tablet, laptop) to join the web based modeling. For this kind of qualitative modeling the tool comes as a freeware.


The approach is widely used not just on environmental topics. To name some examples on environmental topics e.g. to explore the SDGs:

„Participatory, explorative, qualitative modeling: application of the iMODELER software to assess trade-offs among the SDGs“ by Kai Neumann , Carl Anderson and Manfred Denich from the journal Economics https://doi.org/10.5018/economics-ejournal.ja.2018-25

Or to explore with stakeholders along the whole value chain of biomass in subsaharan Africa the potentials for food security from food and non-food use of biotic resources. Or the various models on know-why.net that address climate change, horizon scanning, etc..

W4 Towards unified principles for movement modelling

Pernille Thorbeka,*, Thomas G. Preussb, Joachim Kleinmannc

a BASF SE, Speyerer Str. 2, 67117 Limburgerhof, Germany

b Bayer AG, Alfred Noble Str 50, 40789 Monheim am Rhein, Germany

Tuesday, Sept 5, 6:15 p.m., Saal 1B

This workshop proposal is accompanying the session: Movement modelling: underlying principles and processes

In this workshop different approaches to movement modelling will be discussed with the purpose of exploring possibilities for establishing a unified framework for movement modelling. Such a framework will outline which factors drive the decision making of movement speed and direction and how to represent them. This should include intrinsic factors which may depend on physiology and morphology and specific needs like shelter or food, but also extrinsic factors like responses to habitat, disturbances and landscape heterogeneity, response to physiological status, adaption to a changing environment and more.

W5 Differences and Similarities between Social-ecological and Ecological-economic Models for Land-based Biodiversity Conservation

Martin Drechsler, Helmholtz Centre for Environmental Research – UFZ, Leipzig

Frank Wätzold, Brandenburg University of Technology Cottbus-Senftenberg – BTU

Tuesday, Sept 5, 6:15 p.m., Saal 1C/D

In the field of land-based biodiversity conservation, both Social-Ecological Models (SEM) and Ecological-Economic Models (EEM) address coupled human-environment systems, typically with the aims to better understand their interaction and develop recommendations for improved conservation. According to a review by Drechsler (2020), SEM appear to have a stronger focus on human behaviour and system complexity, while EEM focus more on the analysis of conservation policy instruments. Related to this, SEM tend to be more “positive” by analysing system dynamics, while EEM are more “normative” by focusing on ecological effectiveness, cost-effectiveness and efficiency. Differences might exist also with respect to the researchers’ scientific backgrounds (such as ecology, economics, geography or mathematics) and the organisation in different communities (such as environmental economics, ecological economics, agricultural sciences or environmental modelling). However, the boundaries between the two approaches are fuzzy. Often one and the same model structure can be found under different labels, while different model structures and purposes can be found under the same label. This workshop will be organised as a panel discussion with much room for contributions from the audience. It will bring together representatives from the SEM and EEM community in order to better understand differences and similarities of methods, scope and aims of the two approaches. It will also enhance communication between the communities and enable mutual learning.


Drechsler, M., 2020. Model-based integration of ecology and socio-economics for the management of biodiversity and ecosystem services: state of the art, diversity and current trends. Environmental Modelling & Software 134, 104892.

W6 Effective digital note taking: How to organize your knowledge and streamline your workflow

Selina Baldauf, Theoretical Ecology Group, Freie Universität Berlin

Anne Lewerentz, Institute of Geography and Geoecology, Karlsruhe Institute of Technology

Monday, Sept 4, 2 p.m., Saal 1C/D

Effective note-taking is an important skill for any modeler, as it allows you to keep track of the tasks you need to complete, key learnings from papers you’ve read, the design of your models, and any new ideas that come up while you’re working. There are many different ways to take notes, including using pen and paper, post-its, digital documents, and even printed out papers with notes written on them. This often results in scattered notes on different media that are difficult to extend, connect, search or archive. Having all of your different notes in one place allows you to keep your thoughts organized and interconnected and helps you to always find your notes again and to streamline your workflow.

In this interactive workshop, we will explore the various methods of note-taking, discuss what we require good notes to look like and introduce a powerful tool called Obsidian. Obsidian is a markdown-based note-taking tool that can help modelers stay organized and on track with their work. It provides an easy-to-use interface for creating and organizing notes, as well as a system for linking notes with each other to create a web of interconnected thoughts and ideas. Obsidian is very flexible and can be customized and optimized for your specific workflow and thought process. This flexibility and adaptability make it a valuable tool for any modeler looking to improve their note-taking and stay organized.

To get started, we will provide a Demo-Notebook for academic note-taking with a lot of useful functionality (e.g. daily notes, literature notes connected to Zotero, designing model flowcharts, organizing to-dos and projects) on Github.

Every participant should ideally bring his / her laptop.

W7 Computational notebooks for more openness, reproducibility, and productivity in research

Ludmilla Figueiredo, German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig; Department of Informatics Friedrich- Schiller-University Jena

Monday, Sept 4, 2 p.m., Saal 2A

The ubiquitous use of computational work for data generation, processing, and modeling increased the importance of digital documentation in improving research quality and impact. Computational notebooks are files that contain descriptive text, as well as code and its outputs, in a single, dynamic, and visually appealing file that is easier to understand by non-specialists.

Traditionally used by data scientists when producing reports and informing decision-making, the use of this tool in research publication is not every day. For a single study, the content of such documentation partially overlaps with that of classical lab notebooks and that of the scientific manuscript reporting the study. Therefore, to minimize the work required to manage all the files related to a project’s documentation and report, we present a starter kit (Figueiredo et al. 2022) to facilitate the implementation of computational notebooks in the research process, including publication.

The kit contains the template of a computational notebook integrated into a research project that employs R, Python, or Julia. Over the course of one hour, participants will get a hands-on, in-depth introduction to the kit and be able to apply it to their own projects. In the end, we will discuss how to scale this approach for computationally heavy projects.

Requirements: Basic knowledge of how to work with RMarkdown, Pluto and Quarto files (or willingness to learn).

Equipment needed from participants: Notebook with (depending on user’s preference) R, Python, Julia, RMarkdown, or Pluto installed.


Figueiredo L, Scherer C, Cabral JS (2022) A simple kit to use computational notebooks for more openness, reproducibility, and productivity in research. PLOS Computational Biology 18(9): e1010356. https://doi.org/10.1371/journal.pcbi.1010356

W8 Ecological modelling for environmental risk assessment – exploring career opportunities outside of academia

Nika Galic, Syngenta Crop Protection Ag, Switzerland, nika.galic@syngenta.com

Oliver Jakoby, RIFCON GmbH, Germany, oliver.jakoby@rifcon.de

Tuesday, Sept 5, 6:15 p.m., Saal 2A

Quantitative and predictive methods, like ecological models, that can be used for decision-making are increasingly sought after in a range of sectors including private business, governmental agencies, and non-governmental organizations. For instance, European regulation of plant protection products (pesticides) explicitly recommends the use of mechanistic models to assessing risks on different levels of biological organization. This includes the development, implementation, application, communication, and evaluation of suitable models and model frameworks such as quantitative adverse outcome pathway models (qAOP) models, toxicokinetic-toxicodynamic (TKTD) models, population or community models, and landscape models. However, no set of ready-to-use models is available yet and a clear guidance of how to develop, apply and evaluate such models is still under discussion. Hence, there is great potential for research and development in this field in the coming years.

Despite many interesting and promising opportunities that exist for ecological modellers beyond the walls of academia, often these are not known to promising researchers which stifles their own personal development possibilities, as well as hampers the much-needed use of modelling methods for decision-making in various fields of application. In this workshop, we aim to provide information about some of the possibilities in sectors beyond academia, including the agrochemical industry, consulting businesses in contract research organizations (CRO) and regulatory authorities. For the format of the workshop, we suggest several presentations which will showcase interesting modeling developments as well as highlight the needs and career opportunities. We aim to leave ample time for questions and discussions.

W9 Designing Dynamic Data-Driven Digital Twin Systems in Ecology

Taimur Khan, Helmholtz-UFZ (Community Ecology)

Monday, Sept 4, 2 p.m., Saal 2B

Today’s ecological modelling and simulation code typically only support static workflows. Users can only interact with the running code to terminate a run when input data and parameter files have been produced in advance and are read by the code at startup. If data re-integration is necessary, it is typically done manually using static, sanitised input files produced from data sources to interact with observation systems, data archives, and experiments. This presents a challenge in using legacy ecological models and simulations in Digital Twins.

Dynamic Data Driven Application Systems (or DDDAS, http://1dddas.org) is a conceptual framework that synergistically combines models and data in order to facilitate the analysis and prediction of physical phenomena. DDDAS is an emerging systems design approach that enables to measure physical processes more effectively and consequently update models and simulations. DDDAS and Digital Twins are a natural pairing that improve the combined capabilities of sensors, data, models, and choices. DDDAS incorporates additional data into an executing Digital Twin, and in reverse, enhance a Digital Twin to dynamically steer the decision on its physical asset.

In this workshop, participants will get the chance to dive into what DDDAS is and what possibilities it allows for designing Digital Twin systems in Ecology. Furthermore, examples of DDDAS in Digital Twin design will be presented.

W10 Talking about models

Katrin M. Meyer; Ecosystem Modelling, University of Göttingen, Göttingen

Tuesday, Sept 5, 6:15 p.m., Saal 2B

We are talking about our models to conference audiences, colleagues, students, professors, stakeholders, policy makers, friends, and our grandmother. Each audience requires a different level of information, language and illustration. In this workshop, I will give an interactive presentation followed by a plenum discussion on questions such as: How many equations should I mention (if any) or where can I use interactive elements? The workshop is targeted at early-career modellers and everybody else interested in the topic. The focus will be on slide-based talks, but other communication will briefly be addressed, too. My main suggestion will be: Let the audience design your talk.

W11 Reducing ambiguities and increasing efficiency – introducing (semi-)formal approaches into ecological modeling and simulation studies

Adelinde M. Uhrmacher, University of Rostock

Tuesday, Sept 5, 6:15 p.m., Room 101 in Building 4.0

Modeling and simulation studies are knowledge and data-intensive processes in which various products are generated and refined. (Semi-)formal approaches allow a succinct representation of the diverse activities and products of a simulation study and relate those with each other. In addition, due to their clearly defined semantics, the information can be exploited by computational interpretation and inference processes.

For example, a formal domain-specific modeling language facilitates the interpretation and communication of a simulation model due to its concise and unambiguous representation.  Based on the precise semantics, a model can be executed by different simulators ensuring an efficient execution in a specific situation. Approaches for specifying simulation experiments lend structure to these experiments, facilitate their specification and reuse, and may even further their automatic generation.  Hypotheses, expressed in formal language, allow checking a simulation model automatically and fitting its parameters. The expectation regarding simulation results complements data traditionally used for validation and calibration. Suppose that how simulation studies shall be conducted is formally specified in terms of activities and products and their constraints.  This information can guide the modeler, ensure adherence to specific standards in developing a simulation model, and automatically generate and document the steps of the study.

The first part of the 1-hour workshop will show examples of semi-formal modeling and simulation approaches and their application. In the second part, we will discuss promises, crucial ingredients, and challenges to further the use of semi-formal approaches for modeling and simulation studies in ecology.