AI Time Machine Reveals Species Decline in Lake
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An AI model developed by a team of scientists from Goethe University of Frankfurt and the University of Birmingham, led by Niamh Eastwood and Prof. Luisa Orsini, shows how water pollution, extreme weather and rising temperatures can change the ecosystem of a freshwater spring and irreversibly damaged. more for decades. The model uses weather and climate data and data from a lake sediment core and could be used in the future to predict how ecosystems respond to complex environmental changes. As such, it could serve as a ‘biodiversity time machine’, so to speak, explaining past processes while simultaneously pointing to future ecological dangers.
The sediments of lakes and rivers form the long-term memory of water bodies: it is here where layer by layer of mineral, organic and chemical particles and substances are deposited over time. Using a sediment core from the “Ring Lake”, located near the town of Braedstrup in Denmark, the team of German and British scientists analyzed the DNA residues of plants, animals and bacteria, as well as environmental toxins such as pesticides and herbicides that entered the water came. more over time and is deposited in the sediments. This allowed them to reconstruct the changes that have taken place in the lake’s ecological community, as well as the pollution caused by, for example, nitrates and biocides over the past 100 years.
“The subject of our research, the ‘Ring Lake’ in Denmark, is a body of water that was hardly polluted at the beginning of the 20th century. However, over the course of the century the lake was exposed to significant environmental pollution. In the last years of the 20th century, water quality improved significantly,” explains Prof. Henner Hollert, environmental toxicologist at Goethe University Frankfurt, Fraunhofer IME and the LOEWE Center TBG for Translational Biodiversity Genomics. Combined with the undisturbed sedimentation, which makes the years visible in a way that seems on that of annual rings of a tree trunk, this made it more of an interesting research topic.
The scientific team then set out to link the drill core analysis data to climate records, with a particular focus on extreme temperatures and precipitation levels. Using artificial intelligence, they developed a model that explains the influence of environmental changes on the composition of the freshwater community and resolves it in terms of time and space. Their finding: 90 percent of the changes in Ring Lake’s functional biodiversity were due to the introduction of insecticides and fungicides combined with extreme temperatures and precipitation events.
Although nearby agricultural activity declined at the end of the century, leading to an improvement in water quality, the German-British team of scientists found that this did not restore the lake’s original ecological condition.
Henner Hollert: “We have been able to demonstrate that the loss of biodiversity in an ecosystem is not completely reversible: Biocenosis no longer functions as before, because species that provide certain services within the ecosystem are missing. We will now test our AI system – which we call our ‘biodiversity time machine’ – on other lakes, including as part of an ongoing interdisciplinary project of the German Research Foundation (DFG) on the interaction between humans and the environment in late Middle Ages. the latter are the Technical University of Darmstadt, Helmholtz Center Potsdam – GFZ German Research Center for Geosciences, the State Service for Heritage Protection and Management Baden-Wuerttemberg, and the universities of Tübingen and Braunschweig. Lessons from the past can help us for the future: We aim to provide governments with a warning system that can assess ecologically threatening developments at an early stage, allowing countermeasures to be taken, for example limiting the use of certain biocides in the environment of an ecotope.”
Ecotoxicologist Professor Luisa Orsini, who also holds a Hückmann Endowed Visiting Professorship at Goethe University Frankfurt and is a member of the RobustNature network of excellence, underlines the benefits of the new AI-based method: “The high-throughput analyzes we use allow us able to observe the totality of living organisms in an ecosystem and relate them to their environment. With this in hand, we can estimate the long-term trends in the development of an ecosystem much better than with previous monitoring methods, which focus only on one or a few species and identify the factors with the greatest impact on biodiversity.”
Publication: Niamh Eastwood, Jiarui Zhou, Romain Derelle, Mohamed Abou-Elwafa Abdallah, William A Stubbings, Yunlu Jia, Sarah E Crawford, Thomas A Davidson, John K Colbourne, Simon Creer, Holly Bik, Henner Hollert, Luisa Orsini: 100 years of anthropogenic impact causes changes in functional freshwater biodiversity. eLife (2023) https://elifesciences.org/articles/86576
About the RobustNature research cluster: https://www.robustnature.de/en/
More information:
Professor Henner Hollert
Institute for Ecology, Evolution and Diversity
Goethe University Frankfurt
and Fraunhofer Institute for Molecular Biology and Applied Ecology (IME), Schmallenberg, and LOEWE-Center for Translational Biodiversity Genomics (LOEWE-TBG), Frankfurt
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