Resilience in complex systems through adaptive spatial pattern formation.

In the current Anthropocene, there is a need to better understand the effects of climate and land use change on ecosystems and earth system components, or ‘earth systems’. The fundamental concept of critical transitions, or tipping points, contributes to such understanding. In this context, the important search for early warning signals for imminent critical transitions is ongoing. Spatial self-organization, such as the spontaneous formation of regular vegetation patterns, is thought to be one of such prominent early warning signals. However, recent findings indicate that spatial self-organization should not necessarily be interpreted as early warning signal for forthcoming critical transitions, but as a signal of resilience instead, avoiding tipping points through adaptive spatial pattern formation. Further analysis indicates that such avoiding may be very common for many ecosystems and earth systems that until now are identified as sensitive to tipping. Therefore, we hypothesize that there is a broad range of conditions for which tipping points are circumvented in ecosystems and earth systems that are so far known as prone to tipping. We will investigate universal conditions for circumventing tipping points by mathematical analyses. We will develop a unifying spatial model and analyze the conditions for avoiding tipping points, using savannas as a model system. We will validate this model by exploring adaptive spatial patterns for avoidance of tipping points using satellite data of savannas worldwide. This is imperative for our fundamental understanding and prediction of critical transitions in nature, and how these can be avoided at local to global scales, relevant for ecosystem restoration and mitigating climate and land use change.