Do early warning signals lead to better decisions?
Florian Diekert and colleagues have developed a theoretical model that shows how an early warning system can influence the management of complex socio-ecological systems under stress. The concept complements the development of resilience indicators for complex human-nature systems by providing a better understanding of how, when, and why these indicators lead to improved decisions. However, the authors also demonstrate that the potential to receive a warning about tipping could lead to riskier behaviour, which in some circumstances could mean that tipping points are exceeded even more quickly.
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Key Messages
- Abrupt changes in complex socio-ecological systems can sometimes be predicted by observing their behaviour under increasing stress conditions.
- The authors develop a theoretical model of an early warning system (EWSys).
- The EWSys consists of a tipping indicator, whose value increases as the system approaches the tipping point, and a trigger value at which a warning is issued.
- Such early warning systems can help to better understand and assess tipping points.
- Early warning systems help navigate the trade-off between improved information and the risk of exceeding the tipping point and may, under certain circumstances, suggest increased risk acceptance.
Tipping points and early warning systems
Decision-making in socio-ecological systems can benefit significantly from observing the underlying behavioural patterns of the system. These observations can be used to identify statistical indicators of impending tipping points. Suitable indicators can be used as early warning systems to inform decision-makers about the risks of their actions. This study investigated the effects that such an early warning system can have on optimal decision-making in the event of a potential tipping risk. The theoretical results suggest that the mere existence of an early warning system for detecting the tipping point leads to more cautious initial actions. If an early warning signal (EWS) is actually received, this confirms that caution was justified, while the absence of an EWS implies that a tipping point is unlikely (or, to put it simply, ‘no news is good news’). However, this may encourage decision-makers to take riskier actions in the future, which could even lead to a higher overall risk of tipping – compared to a situation where no early warning system is available.
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Risk reduction or maximum value enhancement?
However, the study shows that an EWS analysis can still be economically valuable. The most important finding is that an early warning system reveals a trade-off between the highest increase in economic value and the greatest risk reduction. In other words, there is a Pareto frontier, which indicates that the trigger value should always lie between the maximum economic value increase and the maximum risk reduction. The model thus provides a useful framework for considering the consequences of the availability of an early warning system in a situation where action brings additional benefits but also carries the risk of tipping.
A key feature of the model presented is the direct relationship between human action and the occurrence of the tipping point. This means that the functioning of the system along the critical transition and the relevant time scales is clearly understood here – causes and effects can be assigned to each other. In other situations, however, human control is less direct and tipping may depend on additional factors. A better understanding of such uncontrollable processes, their interaction with human actions and the reliability of early warning systems is an important task for future research.
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Related literature:
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Shayegh, S., Proverbio, D., Alibakhshi, S., Dakos, V., Diekert, F., Heyen, D., Nesje, F., Richter, A., Schreuder, M., and Weinans, E. (2024). Operationalizing early warning signals for effective decision-making. Mimeo, European Institute on Economics and the Environment Sustainable Earth Modelling.
Worth knowing
An early warning system is a mechanism or method used to identify potential problems or risks at an early stage before they lead to major difficulties. Such systems are often used in various areas, such as:
- Economy: To predict financial crises or market fluctuations.
- Environmental protection: To monitor natural disasters such as earthquakes or floods.
- Healthcare: To identify disease outbreaks at an early stage.
