Computational Approaches to 19th-century Thuringian Ecosystems

Historical ecology offers vital baselines for assessing present‑day biodiversity and climate policy by revealing how past societies shaped—and were shaped by—their environments. Moreover, it is clear that many sustainability and biodiversity challenges of the 21^st century can trace their dynamics and trajectories into the past, even if some of the driving factors are more recent in scope. Here, the emergence of digital tools (including AI) has the potential to mobilize vast quantities of archival data for studies of biodiversity and ecological change. Thuringia, now at the crossroads of ambitious rewilding schemes, sustainable‑forestry reforms, and debates regarding supports for agricultural land use provides an ideal proving ground for testing the ability of these tools to utilized historical data to aid understanding of contemporary contexts.

Historically, the area nowadays known as Thuringia (“Thüringen”) had been governed by multiple political entities until the unification of the seven so-called “Thüringische Freistaaten” into the Free State of Thuringia following the German Revolution after World War I. Given the complexity inherent in examining ecological conditions across all of Thuringia, this pilot study concentrates on the historical Principality of Reuss Junior Line (Fürstentum Reuß jüngerer Linie)—a compact, clearly bounded polity whose mix of upland forests, river valleys, and early industrial centres around its capital Gera makes it a revealing case-study for the reconstruction of Thuringia’s ecological situation around 1870.

The full-scale study of the historical-ecological conditions in the region of Thuringia requires the discovery, digitization, datafication and analytic assessment of numerous archival records from several institutions. The primary source for our pilot investigation is the systematically structured volume "Landes- und Volkskunde des Fürstenthums Reuß j.L.", published in 1870 and written by Georg Brückner (1800-1881), a local historian, archivist, geographer and high school professor on behalf of the Reuss j.L. sovereign of the time, Prince Henry XIV (1832–1913) shortly after he took office in 1867. This historical text, circa 840 pages in total, includes chapters covering a variety of ecological themes, such as geognostic overviews, hydrology, climate, fauna and flora, agriculture, forestry and mining.

The project has the following scientific objectives:

• Extraction and Categorization of relevant Ecological Information: the project aims to systematically and reliably extract ecological information from the historical text. The process involves the identification and classification of references to flora, fauna, climatic conditions, patterns of land use, agricultural and forestry practices, as well as human-environment interactions explicitly recorded or implied in the source document from 1870. Through LLM- based text annotation, we will identify ecological entities and thereby enrich the text source with annotations, allowing for an analysis of the entities themselves and the text context around them. The Named Entity Recognition Tagset includes:
  • Animal: Animal species
  • Plant: Plant species
  • Environment: Biotopes or ecosystems
  • Human: Named entity tag Person
  • Natural Object: Objects in nature, e.g. specific river, forest, mountain
  • Environmental Impact: Influences on environments, fauna, flora or climate
  • Resource: Natural resources used by humans, e.g. wood, oil, coal
  • Climate: Mention of climate factors like weather, seasons, temperature

• Analysis and Spatial Mapping of Historical Ecological Data: Following data extraction, a comprehensive analytical framework will be employed to interpret and spatially map the retrieved ecological information. Utilizing Geographic Information Systems (GIS), the project aims to visualize the ecological conditions in 1870 within the territory of the Principality of Reuss Junior Line. The maps will serve as a resource for interpreting ecological changes over time and enhancing our understanding of historical environmental dynamics within the Reuss Junior Line.
• Development and Validation of Computational Methods: This project also seeks to advance methodological knowledge by evaluating the effectiveness, accuracy, and reproducibility of leveraging the capabilities of Large Language Models (LLMs) in historical ecological research. Through critical assessment and validation of computational techniques employed for entity recognition, annotation accuracy, and data extraction reliability, the study aims to establish standardized practices and guidelines for future interdisciplinary historical- ecological studies employing artificial intelligence.

By integrating traditional historical research with state-of-the-art computational methods, this study aims to deliver significant contributions to historical ecological scholarship, facilitating broader discussions on ecological history, environmental transformations, and the role of digital innovations in historical analysis.