Tropical rainforests are complex and varied environments found around the globe in tropical and subtropical regions. They hold a large biodiversity but also present multiple challenges, both for their human occupations and archaeological studies. In recent decades, we have learned that our ancestors lived in these environments much earlier than we thought and continuously over tens of thousands of years. Using stable isotope analyses, we hope to better understand how hunter-gatherers lived there in the past and if they perhaps gradually started using them differently before the introduction of agriculture.
Tropical rainforests are complex and varied environments found around the globe in tropical and subtropical regions. They hold a large biodiversity but also present multiple challenges, both for their human occupations and archaeological studies. In recent decades, we have learned that our ancestors lived in these environments much earlier than we thought and continuously over tens of thousands of years. Using stable isotope analyses, we hope to better understand how hunter-gatherers lived there in the past and if they perhaps gradually started using them differently before the introduction of agriculture.
Urbanization, forestry, and agriculture are readily associated with contemporary human land use, but how we use the land around us has changed greatly through our species' long history. The availability of food, seasonality, or the concentration of a particularly abundant rich food source are all examples of concerns that prehistoric populations would have faced, all of which would have been managed through land use strategies.
Directly and systematically assessing how past populations utilized their ecosystems, especially as far back as the Pleistocene, remains particularly challenging because pre-urban hunter-gatherer societies may not have left us with large-scale or significant traces. However, such studies are important to identify and assess drivers of long-term land changes and dynamics and to provide baselines for subsequent changes.
Dr. Nicolas Bourgon is carrying out zinc isotope analyses using a multi-collector mass spectrometer with inductively coupled plasma (MC-ICP-MS). The isotope analysis is carried out on fossil tooth enamel samples dissolved in acid from which the element zinc was previously separated using ion chromatography. The results obtained can help us distinguish between diets that rely more heavily on plants or meat, for example.
Dr. Nicolas Bourgon is carrying out zinc isotope analyses using a multi-collector mass spectrometer with inductively coupled plasma (MC-ICP-MS). The isotope analysis is carried out on fossil tooth enamel samples dissolved in acid from which the element zinc was previously separated using ion chromatography. The results obtained can help us distinguish between diets that rely more heavily on plants or meat, for example.
Using a systematic comparison of multi-isotopic data of δ66Zn, δ13C, and δ18O, we seek to quantify hunter-gatherers' dietary reliance on different resource types (e.g., plant, animal, and aquatic). Although the choice of food consumed may not have left visible traces in the landscape or the archeological records, these geochemical tracers can help us explore whether gradual dietary transitions were already underway even before the introduction of agriculture or animal husbandry.
This project is co-funded by an ongoing Walter Benjamin funding program of the Deutsche Forschungsgemeinschaft, with the project specifically looking into omnivory and how zinc isotopes can help us detect this dietary behaviour. This project is also being conducted in collaboration with the Bundesanstalt für Materialforschung und -prüfung (Berlin, Germany), the University of Sri Jayewardenepura (Gangodawila, Nugegoda, Sri Lanka), and the Australian National University (Canberra, Australia).
Several artificial intelligence techniques, such as large language models, are being developed for applications in historical research and their contributions to contemporary policymaking. This includes a collaboration with the Max Planck Library to automate the process of tracking and extracting expert evidence from written publications. This AI system can efficiently locate expert statements on a selected topic and generate a concise summary review.
The Anthropocene Curriculum (AC) began in 2013 as a long-term initiative exploring frameworks for critical knowledge and education in our ongoing transition into a new, human-dominated geological epoch—the Anthropocene. The project has drawn together heterogeneous knowledge practices, inviting academics, artists, and activists from around the world to co-develop curricular experiments that collectively respond to this crisis of the customary.
Analyzing narratives between science and policy involves examining the complex interplay and communication strategies that bridge the gap between scientific research and policy-making.
The ERC funded IslandLab project will document long-term legacies and feedbacks between ecological changes, societal responses and ecosystem resilience on the island of Malta.
The project aims to create an AI assistant to support research in the emerging, highly interdisciplinary field of geoanthropology. The new generation of generative AI is starting to transform scientific practice across all disciplines. In particular, large language models (LLMs) are rapidly becoming better at understanding text and quickly generating accurate responses, making this technology broadly applicable across many domains, including science.
The project explores the innovative approach of utilizing games as educational tools to enhance understanding and skills in complex system thinking. Complex systems, characterized by their intricate and interdependent components, pose significant challenges in comprehension and analysis. Games, with their interactive and engaging nature, offer a unique platform for learners to experiment with and understand the dynamics of such systems in a risk-free environment.
An effective understanding of past historical dynamics under a systems approach requires large volumes of diverse data. This should be structured as linked open data so that different systems’ components can be efficiently connected. To achieve this, we developed the Pandora data platform in collaboration with the Max Planck Computing and Data Facility and the Max Planck Library plus c. 60 international partners. Pandora is a grassroots initiative promoting the creation of independently managed data communities and wider collaborative data networks.
