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. • Digital Twin for biodiversity research still grapples with some engineering challenges. • Digital Twin technology delivers real-time biodiversity insights and enables strategy testing in simulations. • Biodiversity digital twins illuminate the anthropogenic impact on biodiversity loss and identify intervention pathways. • Adaptable digital twins capture ecological relationships across different scales. • Hybrid biodiversity modelling with Digital Twin promotes FAIR, scalable solutions for ecological complexities. [ABSTRACT FROM AUTHOR]