Digital twin challenges in biodiversity modelling

Digital Twin is a contemporary digital representation paradigm that is capable of encompassing the complex interactions within the natural environment. By building biodiversity Digital Twin solutions we may reveal anthropogenic effects that cause loss in biodiversity and discover the pathways that can better uncover, diminish or prevent these effects. Developing Digital Twin Applications for biodiversity has unique challenges, like the hybrid and heterogeneous nature of biodiversity modelling, model co-simulation, the demand for highly variable computational power and the incorporation of data and models to existing research infrastructures. In this paper a state of the art survey is provided with application to the field of biodiversity. We identify broad categories of challenges that need to be tackled to deliver reliable, sustainable and scalable Digital Twin solutions. Moreover, we propose a disciplined approach towards using the Digital Twin paradigm and related terminologies methodically and responsibly.

Automated summary

Digital Twin is a contemporary digital representation paradigm that encompasses complex interactions in the natural environment. Developing Digital Twin Applications for biodiversity can uncover anthropogenic effects causing biodiversity loss and identify ways to mitigate or prevent these effects. However, there are unique challenges in applying Digital Twin to biodiversity, such as heterogeneous modeling, model co-simulation, variable computational power, and integration with existing research infrastructures.