Scaling up our understanding of tipping points

Abstract

Anthropogenic activities are increasingly affecting ecosystems across the globe. Meanwhile, empirical and theoretical evidence suggest that natural systems can exhibit abrupt collapses in response to incremental increases in the stressors, sometimes with dramatic ecological and economic consequences. These catastrophic shifts are faster and larger than expected from the changes in the stressors and happen once a tipping point is crossed. The primary mechanisms that drive ecosystem responses to perturbations lie in their architecture of relationships, i.e. how species interact with each other and with the physical environment and the spatial structure of the environment. Nonetheless, existing theoretical work on catastrophic shifts has so far largely focused on relatively simple systems that have either few species and/or no spatial structure. This work has laid a critical foundation for understanding how abrupt responses to incremental stressors are possible, but it remains difficult to predict (let alone manage) where or when they are most likely to occur in more complex real-world settings. Here, we discuss how scaling up our investigations of catastrophic shifts from simple to more complex—species rich and spatially structured—systems could contribute to expanding our understanding of how nature works and improve our ability to anticipate the effects of global change on ecological systems. This article is part of the theme issue ‘Ecological complexity and the biosphere: the next 30 years’.

Ecological complexity and the biosphere: the next 30 years

“…Large-scale modelling of the challenges associated with the biodiversity crisis requires sensing global, spatio-temporal complexity across scales [ 68 ], using meta community approaches [ 69 , 70 ], incorporating humans into ecology [ 71 ] and adopting a network perspective [ 72 , 73 ]. Concerning the first, our perception of the state of the planet has much improved over the last 30 years as remote sensing methods and machine learning-based data analysis have been developed.…”

“…In order to tackle these tipping points, including their detection and prevention, a major challenge of this research concerns their occurrence in time [ 72 ]. Although most models support the likelihood of these transitions (see however [ 79 ]) there is no general method that consistently predicts when the shift will occur.…”

“…One of the big issues associated with the loss or introduction of keystone species is tied to network architecture. Any strategy aimed at protecting ecosystem resilience requires the identification of relevant species whose loss can trigger avalanches of change [ 72 , 88 – 91 ]. The potential for such downstream effects in food webs is illustrated by the effects of the loss of keystone predators in Barro Colorado Island [ 92 ] or in Yellowstone [ 87 , 93 , 94 ].…”

“…the identification of relevant species whose loss can trigger avalanches of change [72,[88][89][90][91]. The potential for such downstream effects in food webs is illustrated by the effects of the loss of keystone predators in Barro Colorado Island [92] or in Yellowstone [87,93,94].…”

A taxonomy of multiple stable states in complex ecological communities

“…The mechanisms generating multistability have been thoroughly described by single- or few-unit dynamical models that do not always capture the key ingredients at play in the complex system they aim at describing [13; 14; 15]. In ecology more specifically, the current understanding of multistability and related tipping points largely ignores the role of species diversity and the complexity of their interactions, potentially failing at characterizing species-rich dynamical processes [1; 14; 16; 17].…”