Choose timezone
Your profile timezone:
Powered by Indico
v3.3.5
We are delighted to invite you to the upcoming symposium “Science: To Be Determined”, taking place on 3–4 March 2026 at the German Centre for Integrative Biodiversity Research (iDiv), Leipzig.
Science plays a central role in addressing today’s global challenges. Researchers are increasingly called upon to be innovative, collaborative, and socially engaged, while navigating structural and ethical challenges such as balancing productivity with integrity. These dynamics are amplified by rapid advances in AI and rising public skepticism toward science.
In this symposium, we aim to establish a shared understanding of what responsible and rigorous science entails, fostering better collaboration and strengthening both our individual and collective research practices. While rooted in biodiversity research, these questions resonate far beyond disciplinary boundaries — making this an event for all who care about the future of science.
About the event
📅 When: 3–4 March 2026
📍 Where: German Centre for Integrative Biodiversity Research (iDiv), Leipzig
☕ What to expect: Keynote talks, interactive workshops, and open discussions
👩🔬 Who should attend: Master and PhD students, postdocs, as well as early-career researchers from all disciplines interested in scientific integrity, reproducibility, and responsible innovation.
A Livestream Registration will be open until 21 February 2026. A small participation fee of 10 € is required to help cover event organisation costs.
In my talk I will discuss the Open Science movement and its concerted efforts to reform science from the ground up, highlighting its discourse culture, forms of organising, and the implications of their proposed reforms. My own sociological research on the transdisciplinary community forming around replications will be one focus of the talk, delineating potential advantages and pitfalls of opening up collaborations on science reforms to private as well as political actors and their (less than scientific) interests. Another focus will be the narrative side of their advocacy, explicating common narrative elements and ideas present within the Open Science discourse. One point of reflection will be the implications for the epistemic diversity of the sciences. (preliminary)
Practicing the principles of good and open science does not always align with career advancements in academia. In contrast, there is a tension between what guidelines for research integrity tell us and what we are rewarded for. This is a structural problem that deeply affects research culture. We will start this workshop by simulating how individuals decisions on scientific practices may affect career success through an interactive board game. Afterwards, we will engage in structured reflection on the dilemmas that arise during the simulation and relate them to the challenges you face in your research. We will brainstorm options for how to act in this competitive environment as early career researcher, influence research culture, and turn good practices into career advantages. By the end of this workshop, you will have a better understanding of the dilemmas in research integrity and open science, and will gain practical strategies to navigate these challenges.
About:
Ilona Lipp is the Open Science Officer at the Leipzig University, promoting and supporting transparency and integrity in research. She has over 12 years of research experience in interdisciplinary neuroscience in Austria, the UK, and Germany. With additional training in coaching, mediation and didactics, she now helps scientists navigate academia and optimize their research practices. Her workshops cover a wide range of topics, from effective communication and self-confident presentations to data analysis, good scientific practice and responsible use of generative AI.
In this 90-minute workshop, we will dive into the basic principles of generative artificial intelligence systems such as ChatGPT and learn what these systems can do and what not. We go through the most important best-practices, e.g. in prompt-engineering and quality assurance so that we can get the most out of this technology for our daily work in scientific research.
Good science is more than rigid methodology, solid statistical analyses and transparency. It’s about people, the systems they operate in and the history that shaped them. Increasingly, researchers are striving to make science more equitable, diverse and inclusive. But changing the workplace and academia on a day-to-day basis is an ongoing challenge. In this workshop, we will highlight key equity, diversity and inclusivity (EDI) issues that scientists
face in their working life to increase awareness. Next, we will discuss different ways in which common EDI issues can be addressed. Meaningful solutions often require understanding the root of the problem: from the historical marginalization of certain identities, to self-reflection of your own cultural background, and an understanding of biased systemic structures. We will demonstrate how researchers at any career stage can rethink science through an EDI lens and facilitate critical thinking among participants to put the materials to practice by discussing solutions to these problems.
About:
Rebecca Chen [she/her] is a molecular and behavioural ecologist, currently finishing her PhD at Bielefeld University. She uses genomic and epigenetic tools to understand the proximate mechanisms shaping fitness variation in wild animals. In her PhD, she predicted deleterious mutations in black grouse to understand the genetic architecture of fitness traits, inbreeding depression, purging and the honesty of sexual traits. Over the years, she’s become more interested in open science practices, addressing justice, equity, diversity and inclusivity issues in academia, and finding other ways of improving science.
Ane Liv Berthelsen [she/her] is a final year PhD student in molecular ecology at the Evolutionary Population Genetics group at Bielefeld University, Germany. Her work aims at disentangling phenotypic trait variation in Antarctic fur seals and exploring the effects of density on pup development using image-based, physiological and transcriptomic data. She is further interested in finding sustainable solutions, implementing open science practices, and advocating for equity, diversity and inclusivity in Academia. In her personal life, she tests her physical limits on the bouldering wall and enjoys reading a good book. She probably holds a record of daily black tea consumption.
Statistical models are essential tools for understanding data and drawing scientific conclusions. Despite the adoption of modern statistical methods (hierarchical models, structural equation models, Bayesian inference, …) in many disciplines, using these tools responsibly can be challenging. Classical issues, such as model assumptions, uncertainty, and experimental design remain and intersect with new developments, including unprecedented data volumes, complex model structures, and the temptation to replace classical statistical methodology with AI-based methods.
We invite participants to reflect on old and emerging statistical challenges to scientific understanding. Which challenges are the most urgent in everyday research practice? Which ones could be addressed through, for example, better statistical training, more rigorous analyses, improved study design, or increased computational power? Topics may include model generality versus model complexity, correlation versus causation, or statistical inference versus forecasting.
About:
Benjamin is a Computational Ecologist with a PhD in Applied Mathematics, based in iDiv’s ‘Theory in Biodiversity Science’ group. Here, his research focuses on statistical methods for population dynamics, species interactions and food webs. Through his work as a statistical advisor, he has been involved in many biodiversity-related projects. He regularly teaches Bayesian statistics and also offers statistical consulting for the whole iDiv community.
This workshop is aimed at early career researchers who want to develop workflows that allow collaborators, peers and their future selves to reliably run and understand their code. We will explore common sources of irreproducibility, such as lack of documentation, inconsistent project structure, errors derived from copy-paste, among others.
Participants will learn practical strategies for organizing R projects, documenting analyses, managing dependencies, testing code, and writing clear, reusable code, and how to make it openly available. The workshop emphasizes realistic, day-to-day practices rather than
idealized solutions.
My presentation will cover the main causes that have led to a reliability crisis in science, as well as the most-promising solutions towards overcoming the crisis. I will emphasize the utility of p-values in hypothesis testing, and the necessity to control for pseudo-replication and overdispersion in the data. Further, I will explain the problem of multiple hypothesis testing combined with “HARKing” (i.e. hypothesizing after the results are known), as well as the problem of “researcher degrees of freedom” in data analysis. Both issues can be overcome by preregistration, and the latter also by multiverse analysis. The concept of “directed acyclical graphs” (DAGs) will be introduced as a key tool to mastering multiverse analysis.
About:
Wolfgang Forstmeier is an evolutionary biologist and ornithologist with a special interest in promoting rigorous science and data analysis. Since 2004, he has been working in the Department of Ornithology (formerly Behavioural Ecology & Evolutionary Genetics) at the Max Planck Institute in Seewiesen. There he studies the mating behaviour of captive zebra finches and ruff sandpipers, with a focus on understanding behaviour through the most parsimonious mechanisms. He is best known for his methodological publications that not only point out problematic practices in statistical analysis but also offer pragmatic solutions to those problems.
Meta-analyses are critical for evidence synthesis and policy-making, yet they often suffer from the same transparency and methodological issues they criticize in primary studies. This workshop explores common problems in meta-analyses, including low transparency and reporting, poor reproducibility, inadequate handling of heterogeneity and publication bias, and lack of risk of bias assessments, and discuss practical solutions.
Participants will engage in hands-on exercises to assess the transparency of published meta-analyses and evaluate their shared data. While examples focus on ecology and evolution, the principles apply across disciplines.
This 90-minute workshop focuses on authorship in the context of good scientific practice. Participants will reflect on general aspects of research integrity and scientific misconduct and examine the roles and responsibilities associated with authorship. Based on international and institutional guidelines (e.g. DFG, Leipzig University, COPE, ICMJE), the workshop compares authorship criteria and discusses their different interpretations and applications. Problematic practices such as honorary authorship, author and citation cartels will be identified and critically assessed. Participants will be encouraged to develop practical strategies and recommendations for fair and transparent authorship attribution and to reflect on how to prevent authorship conflicts in collaborative research settings. The workshop combines short inputs with interactive elements to promote critical thinking and peer exchange.
About:
Dr. habil. Nadja Walter works at Leipzig University since 2015 at the Faculty of Sport Science, Sport Psychology. Her research focus is on behavior change and mental health in the competitive sport context. She also investigates the ´dark side` of physical activity and coach-athlete-relationship. Nadja Walter teaches in all study programs, is the coordinator of the master in Sport and Exercise Psychology and it‘s double degree, and works as an applied sport psychological consultant. In 2020, Nadja Walter was appointed as arbitrator for Leipzig University. In this position she is contact person for PhD students or post-doctoral researchers regarding conflicts.
Democracies face a dual challenge. On the one hand, democratic institutions are increasingly under pressure from authoritarian, right-wing populist, and extremist actors. On the other hand, socio-ecological transformation in response to climate change requires decisive action, social solidarity, and trust in democratic institutions. These processes are intertwined: ecological crises - particularly extreme weather events - may foster democratic resilience but can also intensify authoritarian backlash, thereby undermining transformation efforts. Given that the entire scientific enterprise has come under attack, the question is what role should or could academics play to fight the backlash and to resist the onslaught on intellectualism and facts?Here we analyse the status quo. What has the academic response to Trumpism and authoritarianism been so far? How do we deal with bad-faith actors and how are we identifying them to begin with? How do we change our way to communicate and embrace said challenge? How do we regain ground, get organised and bring about the necessary discomfort? In order to understand the dynamics, we dissect critical factors such as emotions, biases, neurological and psychological disorders. We discuss social shifts from a current and historical perspective. We shed light on the role of the media (legacy as well as social media). And ultimately, we offer solutions for how to communicate more effective and goal-oriented. In a climate as well as societal context.'
About:
Karsten is a Research Associate at the Meteorological Institute of Leipzig University. He is linking extreme weather events, biodiversity loss and human-induced climate change. One key question he is trying to answer is to what extent the observed changes are attributable to anthropogenic causes. For example, he helped developing the rapid event attribution framework, now widely known as World Weather Attribution. He also has a keen interest in climate change communication and is currently involved in a project which aims at accelerating the transfer of science knowledge into society.
Scientific challenges such as biodiversity loss demand research that crosses disciplinary boundaries and knowledge systems. Addressing them often requires not only interdisciplinary collaboration, but also meaningful engagement with stakeholders and other knowledge holders beyond academia.
That’s the core idea of transdisciplinary research: starting from real-world problem settings and aiming for co-creation of knowledge - bringing scientific expertise into dialogue with practical, professional, local, and experiential perspectives. Rather than treating these as ‘inputs’ to science, transdisciplinary work emphasizes joint problem framing, shared learning, and shared ownership of both questions and solutions.
But what does this kind of work actually entail in practice? What are the motivations and potential benefits - and what are the common challenges, tensions, and trade-offs (e.g., differing expectations, timelines, vocabularies, or ideas of what counts as evidence)?
In this World Café–style workshop on inter- and transdisciplinary research, participants will rotate through small-group discussions with three researchers who have hands-on experience in both interdisciplinary and transdisciplinary projects. Each table will focus on a guiding question related to transdisciplinary synthesis—such as integrating diverse knowledge systems, navigating interdisciplinary teamwork, shaping and using data infrastructures, or rethinking ecological research practices. The format is interactive and reflective: the facilitators will share their experiences, invite questions, and discuss openly with participants.
About:
Cristina A. de la Vega-Leinert is a senior researcher at the German Institute for Integrative Biodiversity Research. Her work is grounded in exchange with stakeholders at different levels, with a particular focus on synergies and trade-offs between conservation and land use, particularly on Europe’s (coastal) agricultural peatlands and forest frontiers in Latin America.
Thore Engel is an interdisciplinary ecologist and Postdoc at the German Centre for Integrative Biodiversity Research. Beside his research and initiated an artist-in-residence series that brought artists and scientists together to foster collaboration and open up new ways of exploring research questions.
Maya Bosch is a doctoral candidate at the German Institute for Integrative Biodiversity Research. She has experience working with school students, particularly through citizen science projects and participatory research formats.
This workshop designed for Early Career Researchers (ECR) and students focus on research assessment and the work of the Coalition for Advancing Research Assessment (CoARA). It is based on the observation that current research assessment relies on quantitative indicators and often misses to acknowledge the wide array of contributions made by researchers. In a world café like setting we will discuss first the state of play with the aim to determine when researchers are evaluated and what are the forms of evaluation. We will particularly highlight the case of students and ECR, accounting for international variations and also bringing out the explicit and the implicit forms of assessment. In a second part, the propositions of reforms and the work of CoARA will be examined. We will confront it with participants' ideas with the intention to foster a rich conversation.
About:
Magali Weissgerber (she/her) works at the German Institute for Integrative Biodiversity Research as a postdoctoral researcher. Her main research topics are land-use changes, ecosystem restoration and rewilding. She has been involved in local, national, and European NGOs advocating for better living and working conditions for early career researchers since 2018. She is currently a general board member of Eurodoc, the European Council for Doctoral Candidates and Junior Researchers.
In recent decades science has increasingly demanded scientists write more, be cited more, and produce more. This creates a quandary, scientists, entering the profession either in order to “make a difference’ or driven by curiosity are focused on a narrow track of writing papers. Furthermore, we have entered an age of distrust, where a scientist dedicating a lifetime to their topic can be hounded online, and countered by fallacies and misinformation. In this challenging landscapes scientists face difficult choices, how can they continue to conduct work with impact and integrity, maintain an academic position, and be seen as impartial?
Here we discuss this challenging landscape, and how we might walk the difficult line between “surviving publish or perish” whilst maintaining curiosity and impact driven research. We explore different forms of impact, and how we can communicate them honestly in increasingly challenging landscapes, and how we can translate our science into policy. Lastly we discuss how this landscape is evolving, and how we can at least attempt to prepare ourselves for the future, for increasingly interdisciplinary research, and a landscape with new tools, challenges and opportunities to contend with.
About:
Alice is a Professor at the University of Melbourne, and previously led research groups at the University of Hong Kong and the Chinese Academy of Sciences following positions in Thailand, the CSIRO in Canberra, and a PhD at the University of Bristol. She is the author of over 200 papers and was in the top 2% of most cited researchers in Ecology in 2023 and 2024. She is President of INTECOL, Co-Chair of GEOBON, Chief editor of Climate Change Ecology and on various task forces for the UN, and a Coordinating Lead Author for the IPBES assessment on the monitoring framework. She has also worked with various science Ministries, drafted policy briefs, and worked with UN missions to inform more effective science driven policy. Through these roles she seeks to better mobilise and translate data to enable change in policy and practice.
Alices research covers a wide array of topics pertaining to understanding patterns of biodiversity and the drivers of biodiversity change with an aim of informing more effective conservation at all scales. Her work focuses on the interface between conservation ecology and conservation action, with an additional special focus on bats, including ecology, biogeography and OneHealth. She and her team collect and utilise diverse data to enable the development of new methods and frameworks, then integrate the outcomes into policy and practice through her various roles. Her research is driven by the need for better data and understanding to empower evidence informed change. By providing a bridge between science and filling key data and knowledge gaps she hopes to facilitate a transition to a more sustainable, and biosecure future.
Taking inspiration from guerilla warfare, I will introduce a framework for managing scientific research that addresses the complexity of research while advancing goals of transparency and reliability. Real science is complex, and there is no single scientific method. It is a chaotic network of theories, data, models, graphs, comparisons, summaries, and narratives. A flaw in any part can ruin everything. How can small teams of researchers challenge this complexity and emerge victorious? More statistical training is not enough. More resources is not enough. Lawrence of Arabia once said, "Guerrilla warfare is more intellectual than a bayonet charge." And this is how we too will proceed. Instead of confronting the complexity directly, with more money and more people and more data and more meta-analyses, we must develop a SCIENTIFIC WORKFLOW that subdivides, analyzes, and transparently justifies our individual research projects. The tools to do this already exist, and individual researchers can become scientific guerillas today to improve their chances of victory.
Correlation does not imply causation – but then, what does it tell us about the world out there? In my talk, I will provide a non-technical introduction to directed acyclic graphs (DAGs) as a tool to understand the relationship between correlation and causation. Three simple fundamental causal structures can go a long way to improve how we reason about the world, both in everyday life and in research, which I will illustrate with various examples. For example, does caffeine during pregnancy cause miscarriages? Isn’t it surprising that hunter-gatherers live nearly as long as we do, once they have survived infancy? And what was up with those claims that children with COVID-19 are just as infectious as adults?
About:
Julia Rohrer is a personality psychologist by training whose work covers a broad range of topics, including the effects of birth order, age patterns in personality, and the determinants of subjective well-being. Her methodological interests include all things causal inference, as well as research transparency and, more generally, how we can improve psychological science. She received her doctoral degree as a fellow of the International Max Planck Research School on the Life Course in 2019 and has since then been an academic assistant at Leipzig University.
Getting the first research articles published can feel like navigating the waters of a stormy ocean. The academic publishing system is designed to ensure quality, transparency, and equity in disseminating scientific knowledge. However, its processes may not be immediately intuitive to everyone. In this workshop, we will start from real examples of published research articles and demystify the intricate journey of scientific publication. From crafting a well-prepared manuscript to submitting it, undergoing peer review, and ultimately achieving publication, you will gain insights into the entire process.
The goal is to empower the participants with the knowledge needed to confidently navigate the academic publishing landscape. The workshop will also touch on important related topics, including literature research, science metrics, open science, ethics and integrity in publishing, and more. It is tailored for students and early-career scientists preparing their inaugural scientific publication but everyone is welcome.
Scientific practice is shaped not only by formal methods and standards but also by shared norms that are often implicit and rarely examined. This workshop invites participants to critically explore how such norms influence everyday research decisions, the production of evidence, and the credibility of scientific knowledge. Using examples from evidence synthesis, meta-analysis, and open research practices, the session examines how biases such as publication bias, selective reporting, and confirmation bias can emerge from common research practices and systemic pressures. The focus is not on assigning blame, facilitating policing or prescribing a single correct approach but on understanding how transparency, reproducibility, and research integrity depend on the norms that govern scientific practice. Participants will leave with a deeper appreciation of how questioning these norms can be a productive and necessary scientific act.
About:
I am an ecologist and meta-analyst leading the Biodiversity and Ecosystem Services (BIOECOS) research group at the Helmholtz Centre for Environmental Research – UFZ in Leipzig, Germany. My research focuses on cross-scale data syntheses and evidence-based approaches to study organism–environment relationships and landscape-level biodiversity patterns, with applications in conservation and sustainable land use. I apply open science and transparent research practices throughout my work and have published on ecological synthesis methods, individual variation in ecological niches, and meta-analysis databases. I earned my PhD in behavioural ecology from Friedrich-Schiller University Jena and collaborate widely to bridge quantitative synthesis with ecological understanding.
Transparency and reproducibility are essential to good research practice. Although replicating scientific findings can be challenging, achieving full computational reproducibility for the outputs reported in a manuscript, is both necessary and achievable. This workshop will introduce participants to creating a reproducible workflow for a publication-ready manuscript that integrates data, analyses, text, figures, and references. Using Quarto with R or Python, we will discuss what Quarto is, why it is useful, and how to organise a project for reproducible workflows. I will briefly cover Markdown, inline code, code chunks for figures and tables, managing references with Zotero or BibTeX, and rendering manuscripts to multiple formats. The session includes a presentation and short live demonstration. Participants familiar with R, Python and Markdown are encouraged to follow along using their own laptops with Quarto and RStudio installed.
About:
I am a PhD student using evidence synthesis i.e. systematic reviews and meta-analyses to understand broad questions in behavioural ecology and evolution but I am especially interested in understanding sources of variation in traits. I am a strong advocate of open science and strive to incorporate open science practices into my work to make it transparent and reproducible. I’m also passionate about meta-research, particularly questions about how we conduct and evaluate science.
Biomedical research is celebrated as a driver of innovation and patient benefit — yet much of what we produce is unreliable, unpublished, or irrelevant. Preclinical work still struggles with basic internal validity: missing blinding and randomization, small samples, flexible analyses, and a storytelling culture that turns exploratory findings into “discoveries.” Publication bias remains so pervasive that major research areas rest on untested assumptions.
Clinical research once had similar problems but confronted them directly: preregistration, randomized trials, a separation of exploratory and confirmatory work, evidence-based medicine, systematic reviews, meta-analysis, and conflict-of-interest disclosure. The result was not perfection, but clear progress.
Why is broader biomedicine slower to change? Structural pressures: large financial stakes, heavy clinical and teaching loads, limited training in research methods, rigid hierarchies, and incentive systems that reward impact factors, grants, and flashy claims over truth. Even in clinical research, waste persists through underpowered studies, marginally novel questions, industry-shaped biases, and unpublished results.
Still, momentum for reform is growing in preclinical science: preregistration, open data, preprints, transparent reporting, and funded confirmatory studies are slowly reshaping norms. The core lesson is uncomfortable: improving research quality is not mainly a technical problem but an incentive problem. If institutions reward rigor, transparency, and reproducibility, we can reduce waste, improve quality, and build a research enterprise worthy of public trust.
About:
In both preclinical and clinical studies, Ulrich Dirnagl’s research has uncovered pathobiological mechanisms that influence outcomes after stroke. Several of these mechanisms are therapeutically targetable, and clinical trials are underway. In addition, his meta-research has identified opportunities to improve research practices and has generated evidence for the effectiveness of interventions designed to increase the value of biomedical research. Until his retirement in 2025 from Charité – Universitätsmedizin Berlin, Ulrich Dirnagl was Professor of Clinical Neuroscience and served as the founding director of the Department of Experimental Neurology from 1999 to 2022. From 2017 to 2025, he also served as the founding director of the QUEST Center for Responsible Biomedical Research at the Berlin Institute of Health. QUEST seeks to overcome roadblocks in translational medicine by increasing the value and impact of biomedical research through enhanced quality, reproducibility, generalizability, and validity.
Public trust in science is fracturing along partisan lines—a gap that has widened dramatically over the past two decades. This polarization is not simply a misinformation problem to be solved by better fact-checking. Algorithmically curated platforms sort audiences by ideology, reinforce existing beliefs, and undermine shared deliberation. Drawing on recent research, this talk examines why traditional deficit-model approaches to science communication are failing in these new information ecologies, and outlines an evidence-based agenda for engaging diverse publics that acknowledges the role of values and meets audiences where they are.
About:
Dietram A. Scheufele is an Investigator and Vilas Distinguished Achievement Professor in the Morgridge Institute for Research and a Distinguished Research Fellow at the University of Pennsylvania's Annenberg Public Policy Center. His most recent work has focused on mis- and disinformation, open science, and the societal impacts of emerging technologies like AI and human brain organoids.
He is an elected member of the American Academy of Arts and Sciences and the German National Academy of Science and Engineering, and a fellow of the American Academy of Political & Social Science, the American Association for the Advancement of Science, and the International Communication Association.