The interdisciplinary project From Historical Sources to Ecological Data builds on the rich tradition of environmental and nature associations, which have been publishing observations of fauna, flora and ecosystems in magazines, newsletters and reports since the nineteenth century. These historical sources – recently digitised by the Flanders Marine Institute (VLIZ) and the Institute of Social History (Amsab-ISG), among others – contain crucial data for reconstructing ecological baselines. The emphasis is on bird and fish populations, and both aquatic and terrestrial indicator species, with a focus on the Scheldt Valley (cfr. Artemis) and the Belgian coast, where an exceptionally rich continuity of sources allows us to analyse the interaction between nature and human intervention over two centuries.
The project aims to unlock historical data, and to answer fundamental ecological questions, such as how have key species within bird and fish populations evolved under the influence of human interventions in river and coastal ecosystems, which long-term patterns are visible in the biodiversity of the Scheldt valley and the Belgian coast and how can historical reference points contribute to contemporary nature restoration and policy strategies in light of the European Biodiversity and Nature Restoration Regulation?
Central to the project is the application of semi-automatic extraction methods in a human-in-the-loop approach, technically developed and supported by the Ghent Centre for Digital Humanities. By combining text and data mining with domain expertise in ecology and biology, species observations, population trends and environmental problems are reliably extracted from the sources. In this way, we develop energy-efficient, controlled, validated datasets that provide both scientific insights and offer policymakers and citizens long-term perspectives on the development of nature and the environment. To this end, we also collaborate with the Research Institute for Nature and Forest (INBO) and the Meise Botanical Garden.
Project team: Prof.dr. Christophe Verbruggen, Prof. dr. Thijs Lambrecht and Prof.dr. Sander Govaerts.