Digital Twins: From Industry to Ecology
From: https://www.nature.com/articles/d41586-025-03314-y
Digital twin technology, traditionally an industrial tool, is now proving valuable in ecological research and wildlife management. This marks a positive shift for a technology that has previously faced scepticism regarding its practical delivery.
“Digital twins can be particularly useful for studying systems that are changing outside historical norms… That includes how ecosystems react to anthropogenic climate change.”
The Nature article details how virtual representations are simulating animal behaviour, predicting environmental changes, and informing conservation efforts.
The Rise of Digital Twins
A digital twin is a virtual model that accurately reflects a physical entity, continuously updated with real-time data. This allows for simulations, monitoring, and analysis. Its accelerated adoption stems from:
- Increased data availability.
- Prevalence of Internet of Things (IoT) devices.
- Advancements in artificial intelligence (AI) and cloud computing.
Ecological Applications
Ecologists are using digital twins to address complexities and data gaps in biodiversity research:
- Crane Radar: Developed by Wageningen University & Research, this twin forecasts common crane migration across Western Europe. It integrates migration data, birdwatcher sightings, and environmental factors. Ecologist Koen de Koning noted its personal benefit: “This model really helped me, personally, to see them more often.”
- Doñana National Park: A complex model is being built to simulate interactions between vegetation, rabbits, and the Iberian lynx, understanding how various factors affect the ecosystem.
- River Management: Digital twins for rivers like the Stiffkey (England) and Mara (Kenya) aid in habitat improvement, flood prevention, and community alerts.
Challenges
Despite their potential, ecological digital twins face hurdles:
- Data Reliability: High-quality, real-time data is crucial; inaccurate citizen observations can affect model accuracy.
- Data Storage Costs: The large data volumes required can lead to significant cloud storage expenses.
- Funding & Awareness: As a new application in ecology, educating potential users and securing sustainable funding for long-term maintenance are essential.
My experience with digital twins has primarily been in industrial contexts, where they often faced scepticism due to initial over-promising. It is encouraging to see this technology find positive and impactful application in ecology, moving beyond its previous reputation to deliver tangible benefits in wildlife management and environmental conservation. This shift demonstrates a maturing of the technology, where practical applications are now outweighing earlier hype. The Crane Radar, engaging the public as data providers, illustrates the potential for digital twins to foster a more connected approach to environmental stewardship.
