Human societies are embedded in complex social-ecological systems (SESs) that are composed of interconnected physical, biological and socio-economic processes, cycles and networks. Understanding these systems and their interconnection, is vital to tackling the grand challenges and “wicked problems” facing society in the 21st century, such as those related to climate change, biodiversity, human demographics and economic disruption.

Future Horizons:

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5-yearhorizon

Digital modelling achieves wider take-up

Greater use is made of digital modelling techniques to assess individual development and infrastructure projects, as well as greater integration with decision-making processes. Research continues into how immersive models can best allow stakeholders to more intuitively yet rigorously understand the context for decision-making, and achieve low-cost, low-risk simulation of different solutions to development and environmental challenges.

10-yearhorizon

Better data and computational resources create better models

High-resolution models for physical processes, initially demonstrated for select locations, become both more accurate and more widely available, thanks to increases in computational power and well-categorised and contextualised data. Integrated models of the built environment are created for some urban environments and coupled social-ecological avatars are created for especially tractable and well-studied locales, such as oceanic islands.

25-yearhorizon

Local and global models merge

Local digital twins and avatars that allow predictive management and decision-making at city and island scales join up with regional and global avatars, such as physical climate models that increasingly include biological and social feedbacks. They become interconnected at nested scales, creating a global “intelligent fabric” that can be utilised in politics and diplomacy.

These challenges are now becoming tractable thanks to expansion of our ability to collect and analyse data about SESs through satellite imagery,¹¹ in situ networks of ecosystem¹² ¹³ and urban¹⁴ sensors, and automated aggregation of economic and social data.¹⁵ This in turn makes it possible to build computer models that simulate processes taking place in a wide variety of systems and at a wide variety of scales.

Initially, these models were confined to physical processes, with climate modelling being by far the best-known example,¹⁶ but as our data-gathering capabilities have expanded, we have now started to model ecosystems¹⁷ and various dimensions of societies such as urban planning¹⁸ and health¹⁹ as well. Research is under way into the use of these models as decision-support tools for policy-makers. ²⁰

Technology vendors have put forward the idea of integrated “digital twins” that span physical, biological, social and economic dimensions from local to global scales, and particularly integrated models of cities. However, the case for these has yet to be proven, especially with regards to less wealthy communities, where the focus is more on using digital tools at more granular levels, such as buildings-information management.²¹

World simulation - Anticipation Scores

The Anticipation Potential of a research field is determined by the capacity for impactful action in the present, considering possible future transformative breakthroughs in a field over a 25-year outlook. A field with a high Anticipation Potential, therefore, combines the potential range of future transformative possibilities engendered by a research area with a wide field of opportunities for action in the present. We asked researchers in the field to anticipate:

The uncertainty related to future science breakthroughs in the field
The transformative effect anticipated breakthroughs may have on research and society
The scope for action in the present in relation to anticipated breakthroughs.

This chart represents a summary of their responses to each of these elements, which when combined, provide the Anticipation Potential for the topic. See methodology for more information.