3.4.1.3 Learning challenges

Tipping points present a set of specific learning challenges that could undermine governance efforts. Nonlinear state changes are a feature of many complex Earth system components (Young, 2012; 2017), which require complex systems thinking, often involving a fundamental change in decision makers’ assumptions about reality and the nature of change (i.e. an ontological shift) from a mechanistic, linear and simple single-cause model to one centring emergence, nonlinearity and multi-causality. As Renn (2022) notes, tipping points are a type of systemic risk that render trial-and-error approaches to learning useless, demanding novel approaches to learning, such as immersive game-based techniques.

ESTPs occur at unusual spatial and temporal scales, for which common governance approaches are unsuitable. Tipping systems, including ocean circulation patterns or transboundary ecosystems, introduce a distinct spatial scale for governance that often cross national and even continental boundaries – for example, the Amazon basin, Atlantic Ocean or Arctic. In the absence of governance institutions or polities representing all relevant actors for this specific scale, knowledge development is challenging. For some tipping systems, such as ocean currents, scale-specific knowledge producers are scarce or disconnected from decision making. The multiple timescales of Earth system tipping, including extremely long time horizons, present profound challenges for learning, assessing and valuing potential future outcomes and for including timescale considerations in present-day decision making and governance.

The production of scientific knowledge involves dealing with uncertainties, some of which cannot be reduced through further research. This applies to ESTPs. We might detect signals that a system is approaching a tipping point, but not be able to predict when and under what specific conditions the threshold will be reached. For ‘slow’ tipping systems, science might not be able to state whether or not a tipping point has been crossed for decades, and given that there may be no clearly established or observable ‘event’ indicators at the time the threshold is crossed, tipping points may be passed with no notice. The limitations of scientific knowledge about tipping points in turn have significant implications for governance, dramatically elevating the need for precaution, an expanded toolbox for dealing with uncertainty, and processes to create anticipatory capacities such as decision makers’ abilities to engage in long-term thinking. At the same time, there is evidence that this kind of uncertainty inhibits cooperation and collective action (Barrett and Dannenberg, 2012; 2014; Schill, Lindahl, and Crépin, 2015).

Some of the key questions that remain to be clarified when co-producing knowledge about tipping points include:

• How can actors identify critical information? 
• What criteria should guide action priorities amidst an increasing number and severity of Earth system tipping processes? 
• How can we attend to long-term processes despite short-term political pressures?