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Digital twins as a tool for ecosystem research
Marcel E Visser1, Geerten M Hengeveld1, Jelske de Kraker2
1Netherlands Institute of Ecology (NIOO-KNAW), Wageningen, The Netherlands.
Trends in Ecology & Evolution
|June 22, 2026
Summary
Digital twins offer an innovative approach to ecosystem analysis by integrating diverse data and models. These dynamic tools capture species interactions and biodiversity, enabling crucial scenario studies for conservation and climate resilience.
Area of Science:
- Ecology
- Environmental Science
- Computational Biology
Background:
- Understanding ecosystem functioning is crucial for forecasting environmental changes.
- Integrating diverse research fields is necessary for comprehensive ecosystem analysis.
- Biodiversity loss and climate change necessitate advanced analytical tools.
Purpose of the Study:
- To introduce digital twins as an innovative approach for integrated ecosystem analysis.
- To outline the key characteristics and capabilities of ecosystem digital twins.
- To highlight the potential of digital twins in addressing biodiversity loss and enhancing climate resilience.
Main Methods:
- Developing digital twins tailored to specific ecosystems.
- Establishing dynamic interactions between digital twins and physical ecosystems.
- Integrating diverse data sources and complementary models within digital twins.
- Utilizing digital twins for scenario studies to forecast ecosystem changes.
Main Results:
- Digital twins can accurately represent specific ecosystems and their dynamics.
- The integration of diverse data and models enhances analytical capabilities.
- Digital twins facilitate scenario studies for predicting ecosystem responses.
- Ecosystem digital twins capture species interactions, biodiversity dynamics, and carrying capacity.
Conclusions:
- Digital twins are powerful tools for understanding and managing ecosystems.
- Their development is timely due to advances in digital technologies.
- Ecosystem digital twins are instrumental in combating biodiversity loss and improving climate resilience.
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