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Abrupt Climate Change and Extinction Events in Earth History

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Abstract

Slowly changing boundary conditions can sometimes cause discontinuous responses in climate models and result in relatively rapid transitions between different climate states. Such terrestrially induced abrupt climate transitions could have contributed to biotic crises in earth history. Ancillary events associated with transitions could disperse unstable climate behavior over a longer but still geologically brief interval and account for the stepwise nature of some extinction events. There is a growing body of theoretical and empirical support for the concept of abrupt climate change, and a comparison of paleoclimate data with the Phanerozoic extinction record indicates that climate and biotic transitions often coincide. However, more stratigraphic information is needed to precisely assess phase relations between the two types of transitions. The climate-life comparison also suggests that, if climate change is significantly contributing to biotic turnover, ecosystems may be more sensitive to forcing during the early stages of evolution from an ice-free to a glaciated state. Our analysis suggests that a terrestrially induced climate instability is a viable mechanism for causing rapid environmental change and biotic turnover in earth history, but the relation is not so strong that other sources of variance can be excluded.
... Tipping points (TPs) in complex systems are often assumed to obey the normal form of a saddlenode bifurcation, which gives rise to universal early warning signals (EWS) due to critical slowing down (CSD) [1][2][3][4]. In particular, when proceeding towards the bifurcation, saddle and node approach each other and eventually collide and disappear, at which point the largest Jacobian eigenvalue of the linearization around the node crosses the imaginary axis. ...
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Tipping points (TPs) are often described as low-dimensional bifurcations, and are associated with early warning signals (EWS) due to critical slowing down (CSD). CSD is an increase in amplitude and correlation of noise-induced fluctuations away from a reference attractor as the TP is approached. But for high-dimensional systems, it is not obvious which variables or observables would display the critical dynamics and carry CSD. Many variables may display no CSD, or show changes in variability not related to a TP. It is thus helpful to identify beforehand which observables are relevant for a given TP. Here we propose this may be achieved by knowledge of an unstable edge state that separates the reference from an alternative attractor that remains after the TP. This is because stochastic fluctuations away from the reference attractor are preferentially directed towards the edge state along a most likely path (the instanton). As the TP is approached the edge state and reference attractor typically become closer, and the fluctuations can evolve farther along the instanton. This can be exploited to find linear observables with substantial CSD, which we demonstrate using conceptual dynamical systems models and climate model simulations of a collapse of the Atlantic meridional overturning circulation.
... Again, the model predicts the same patterns as the total one (Supplementary Table 2) but with higher support. This is evident from the smaller credible intervals when comparing the models "without fossorial" vs. "with fossorial" (our total model) species across different habitats: Open (41% [35,44] vs. 41% [36,46]), Semi-Open (39% [36,41] vs. 39% [36,43]), and Closed (34% [29,37] vs. 36% [31,39]). These smaller credible intervals confirm the higher uncertainties of brightness prediction in fossorial species (Fig. 4). ...
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... In the field of climate science, the possibility of "abrupt climate change" and "critical points" was considered as early as the 1980s [31]. The notion that anthropogenic influence could also trigger sudden transitions in climate systems, slowly gained traction in the early 2000s [32,33]. ...
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Visual models play a crucial role in both science and science communication. However, the distinction between mere analogies and mathematically sound graphical representations is not easy and can be misunderstood not only by laypeople but also within academic literature itself. Moreover, even when the graphical representation exactly corresponds to the mathematical model, its interpretation is often far from obvious. In this paper we discuss the "potential landscape" visualization commonly used for tipping points in the context of nonlinear dynamics and reveal potential pitfalls, in particular when distinguishing bifurcation induced tipping (B-tipping) from noise-induced tipping (N-tipping). We propose new visualization techniques for tipping dynamics, carefully distinguishing between B- and N-tipping as well as between single systems and ensembles of systems. Explicitly, we apply these visualizations both to molecular cell biology and to climate science in order to reveal the crucial differences in the interpretation of the visual models. We find that it is crucial to explicitly discuss the assumptions made within the visual model and to be aware of the risk of misinterpretation. Based on these findings, we propose as a next step to investigate individual mental models induced by these visualizations in the framework of empirical research.
... waste) into the earth and atmosphere (Erdoğan et al. 2019;Kurniawan et al. 2021). The simple reason is that if growth is generated costing the natural environment quality in the long run, it can become a sign of environmental instability (Crowley and North 1988). Suppose such a situation continues to prevail over a more extended period. ...
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Chapter
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Chapter
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