Scientists have developed a novel method to reconstruct the past changes in biodiversity and environmental conditions of a freshwater lake using artificial intelligence (AI) and environmental DNA (eDNA).
Their approach, which they call a "biodiversity time machine", could help us understand the causes and consequences of the ongoing loss of biodiversity in the face of global warming and pollution.
What is the biodiversity time machine and how does it work?
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The biodiversity time machine is a technique that uses sediment cores from the bottom of a lake to extract eDNA, which is genetic material left behind by plants, animals, and bacteria that lived in the lake.
By analyzing the eDNA sequences, the researchers can identify the species that were present in the lake at different points in time, spanning from the present to the past 100 years or more.
The eDNA data can then be combined with climate and pollution data to create a comprehensive picture of the biological and environmental changes that occurred in the lake over time.
The researchers used AI to help them interpret the complex and noisy eDNA data, and to identify the factors that best explained the changes in biodiversity.
They applied machine learning algorithms to find patterns and correlations among the eDNA, climate, and pollution data, and to infer the causal relationships among them.
The AI also helped them to prioritize the conservation of species that provide important ecosystem services, such as water purification, nutrient cycling, and food production.
What did the biodiversity time machine reveal about a century of environmental change in a Danish lake?
The researchers tested their biodiversity time machine on a lake in Denmark, called Lake Esrum, which has a history of well-documented shifts in water quality, making it a perfect natural experiment.
They published their findings in the journal eLife.
They found that the lake experienced a dramatic loss of biodiversity over the past century, especially in the last 50 years.
They identified insecticides and fungicides, along with increases in minimum temperature, as the main drivers of biodiversity decline.
Furthermore, they found that some species, such as diatoms (a type of algae), were more sensitive to environmental changes than others, and that some species, such as cyanobacteria (a type of bacteria), increased in abundance as the water quality deteriorated.
According to the researchers, biodiversity loss was potentially irreversible, as some species that disappeared from the lake did not return even after the water quality improved.
They warned that the loss of biodiversity could have negative impacts on the ecosystem services and functions that the lake provides, such as water clarity, oxygen production, and fish production.
Why is the biodiversity time machine important for conservation and restoration?
The researchers hope that their biodiversity time machine can be applied to other lakes and ecosystems and that it can help regulators and policymakers to protect and restore the biodiversity that sustains our life on Earth.
They argue that the biodiversity time machine can provide valuable insights into the historical baselines and trajectories of biodiversity, and the factors that influence them.
This can help to identify the most vulnerable and valuable species, and the most effective interventions to prevent or reverse their decline.
The researchers also suggest that the biodiversity time machine can be used to monitor the progress and outcomes of conservation and restoration efforts and to evaluate their cost-effectiveness and sustainability.
They believe that the biodiversity time machine can be a powerful tool to inform and inspire the public and the stakeholders about the importance and the benefits of preserving and enhancing the biodiversity of our planet.
