Do digital twins need people? Integration of the human dimension into digital twins of the natural environment

Digital Twins (DTs) are dynamic digital representations of physical objects and systems, including their associated processes and environments. Using real-time data analytics, modelling, simulation and 'what-if' scenarios, they can enable valuable understanding and decision-support for managing a system. One potential application of DTs is the management of natural landscapes. However, despite the critical impact of humans on the natural environment, none of the DTs of the natural environment found in the literature include the human systems in that environment. We propose a modular framework for integrating human systems within a DT of the natural environment, to facilitate simulation and modelling of a range of management contexts, objectives and stakeholders across time and space. We then propose four principles as the theoretical basis for modelling the socio-ecological governance systems that underpin DTs of human systems for managing the natural environment. We also provide a use case related to area-wide integrated pest management as an example of the potential application of the proposed framework for collectively managing the natural landscape. The composition and characteristics of this use case as a DT and examples of user engagement at multiple spatial and temporal scales are also described. Finally, we identify some methods such as agent-based modelling, reinforcement learning, and graph neural networks that could be used to incorporate human systems in a DT, along with some examples of their use for similar tasks from the literature. Integrating human systems in DTs of the natural environment will facilitate the development of novel digital decision-support tools that provide stakeholders with different perspectives of the shared natural environment and enable them to understand the impact of various management methods and actions.