Posted in | News | Remote Monitoring

AI Could Help Learn from Past Environmental Changes to Manage Biodiversity in Future

A team of researchers, led by the University of Birmingham’s School of Biosciences, has suggested a “time machine framework” that will assist decision-makers in successfully going back in time to explore the associations between pollution events, biodiversity and environmental changes, such as climate change, as they happened and scrutinize the effects they had on ecosystems.

AI Could Help Learn from Past Environmental Changes to Manage Biodiversity in Future.

Image Credit: University of Birmingham

The researchers demonstrate how these insights can be applied to estimate the future of ecosystem services such as food provisioning, climate change mitigation and clean water. Details of the study have been published in Trends in Ecology and Evolution.

Based on this information, stakeholders can line up actions that will provide the maximum impact.

Biodiversity sustains many ecosystem services. Yet these are declining at an alarming rate. As we discuss vital issues like these at the COP26 Summit in Glasgow, we might be more aware than ever that future generations may not be able to enjoy nature’s services if we fail to protect biodiversity.

Dr. Luisa Orsini, Principal Investigator and Associate Professor, University of Birmingham

Dr. Orsini is also a Fellow of The Alan Turing Institute.

Biodiversity loss takes place over a number of years and is frequently caused by the cumulative effect of numerous environmental threats. Only by assessing biodiversity before, during and after pollution events, can the causes of biodiversity and ecosystem service loss be detected, say the scientists.

It is a complex problem to manage biodiversity while confirming the delivery of ecosystem services because of competing objectives, limited resources and the drive for economic profitability. Safeguarding every species is impossible. The time machine framework provides a method to prioritize conservation techniques and mitigation interventions.

Dr. Orsini stated, “We have already seen how a lack of understanding of the interlinked processes underpinning ecosystem services has led to mismanagement, with negative impacts on the environment, the economy and on our wellbeing. We need a whole-system, evidence-based approach in order to make the right decisions in the future. Our time-machine framework is an important step towards that goal.”

We are working with stakeholders to make this framework accessible to regulators and policy makers. This will support decision-making in regulation and conservation practices.

Niamh Eastwood, Study Lead Author and PhD Student, University of Birmingham

The framework makes use of the expertise of environmental scientists, biologists, ecologists, computer scientists and economists.

The study is the outcome of a cross-disciplinary partnership among the University of Birmingham, the American University of Paris, the Alan Turing Institute, the University of California Berkeley, the University of Leeds, the University of Cardiff and the Goethe University Frankfurt.

Journal Reference:

Eastwood, N., et al. (2021) The Time Machine framework: monitoring and prediction of biodiversity loss. Trends in Ecology and Evolution.

Tell Us What You Think

Do you have a review, update or anything you would like to add to this news story?

Leave your feedback
Your comment type

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.