scholarly journals Variance and Rate-of-Change as Early Warning Signals for a Critical Transition in an Aquatic Ecosystem State: A Test Case From Tasmania, Australia

2018 ◽  
Vol 123 (2) ◽  
pp. 495-508 ◽  
Author(s):  
Kristen K. Beck ◽  
Michael-Shawn Fletcher ◽  
Patricia S. Gadd ◽  
Henk Heijnis ◽  
Krystyna M. Saunders ◽  
...  
Keyword(s):  
Early Warning ◽  
Aquatic Ecosystem ◽  
Rate Of Change ◽  
Test Case ◽  
Critical Transition ◽  
Warning Signals ◽  
Early Warning Signals ◽  
Ecosystem State

Flickering gives early warning signals of a critical transition to a eutrophic lake state

Nature ◽  
2012 ◽  
Vol 492 (7429) ◽  
pp. 419-422 ◽  
Author(s):  
Rong Wang ◽  
John A. Dearing ◽  
Peter G. Langdon ◽  
Enlou Zhang ◽  
Xiangdong Yang ◽  
...  
Keyword(s):  
Early Warning ◽  
Eutrophic Lake ◽  
Critical Transition ◽  
Warning Signals ◽  
Early Warning Signals

Seizures Start without Common Signatures of Critical Transition

2016 ◽  
Vol 26 (08) ◽  
pp. 1650053 ◽  
Author(s):  
Piotr Milanowski ◽  
Piotr Suffczynski
Keyword(s):  
Ocean Circulation ◽  
Early Warning ◽  
Human Subjects ◽  
Epileptic Seizures ◽  
Critical Transition ◽  
Warning Signals ◽  
Early Warning Signals ◽  
Human Epilepsy ◽  
Critical Transitions ◽  
Eeg Recordings

Complex dynamical systems may exhibit sudden autonomous changes from one state to another. Such changes that occur rapidly in comparison to the regular dynamics have been termed critical transitions. Examples of such phenomena can be found in many complex systems: changes in climate and ocean circulation, changes in wildlife populations, financial crashes, as well as in medical conditions like asthma attacks and depression. It has been recognized that critical transitions, even if they arise in completely different contexts and situations, share several common attributes and also generic early-warning signals that indicate that a critical transition is approaching. In the present study, we review briefly the general characteristics that have been observed in systems prior to critical transitions and apply these general indicators to nearly 300 epileptic seizures collected from human subjects using invasive EEG. Only in about 8% of the patients was evidence of critical transitions found. In the remaining majority of cases no early warning signals that behaved consistently prior to seizures were observed. These results do not rule out the possibility of critical transitions to seizure but point to limited relevance of their early warning signals in the context of human epilepsy observed using intracranial EEG recordings.

scholarly journals Early warning signals and the prosecutor's fallacy

2012 ◽  
Vol 279 (1748) ◽  
pp. 4734-4739 ◽  
Author(s):  
Carl Boettiger ◽  
Alan Hastings
Keyword(s):  
Early Warning ◽  
Spatial Scales ◽  
Experimental Studies ◽  
Statistical Error ◽  
Warning Signal ◽  
Experimental Manipulation ◽  
Critical Transition ◽  
Natural Experiments ◽  
Warning Signals ◽  
Early Warning Signals

Early warning signals have been proposed to forecast the possibility of a critical transition, such as the eutrophication of a lake, the collapse of a coral reef or the end of a glacial period. Because such transitions often unfold on temporal and spatial scales that can be difficult to approach by experimental manipulation, research has often relied on historical observations as a source of natural experiments. Here, we examine a critical difference between selecting systems for study based on the fact that we have observed a critical transition and those systems for which we wish to forecast the approach of a transition. This difference arises by conditionally selecting systems known to experience a transition of some sort and failing to account for the bias this introduces—a statistical error often known as the prosecutor's fallacy. By analysing simulated systems that have experienced transitions purely by chance, we reveal an elevated rate of false-positives in common warning signal statistics. We further demonstrate a model-based approach that is less subject to this bias than those more commonly used summary statistics. We note that experimental studies with replicates avoid this pitfall entirely.

Early-Warning Signals for a Critical Transition in the Coupled Amazon Rainforest-South American Monsoon System

2021 ◽  
Author(s):  
Nils Bochow
Keyword(s):  
Early Warning ◽  
Amazon Rainforest ◽  
South American ◽  
Critical Transition ◽  
The South ◽  
Warning Signals ◽  
Early Warning Signals ◽  
South American Monsoon ◽  
Monsoon System ◽  
South American Monsoon System

<p>The Amazon rainforest is widely recognised as a potential tipping element in the Earth's climate system. While several studies suggest a sudden dieback of the rainforest ecosystem after partial deforestation [e.g., 1, 2], there is still a lack of understanding where to search for early-warning signals that might precede such a dieback. In this work we employ a non-linear model of the moisture transport across the Amazon Basin to propose several statistical and physical early warning signals for a critical transition in the coupled dynamics of the Amazon rainforest and the atmospheric circulation of the South American monsoon. </p><p>Widespread deforestation and its effects on evapotranspiration and radiation have been shown to potentially trigger a collapse of the positive feedback related to latent heat release over the rainforest [3], resulting in substantially reduced rainfall amounts. The model includes a nonlinear contribution representing the acceleration of low-level moisture flow caused by condensational latent heating.  </p><p>Guided by our modelling results, we associate characteristic changes in the hydrological cycle as well as statistical indicators in observed data with deforestation-induced circulation changes that are consistent with the identified early-warning signals. Our findings indicate that in response to deforestation, the coupled atmosphere-vegetation system is destabilising and that further deforestation could trigger a transition of the Amazon rainforest to a savanna state. </p><p>[1] Nobre, C. A., & Borma, L. D. S. (2009). “Tipping points” for the Amazon forest. Current Opinion in Environmental Sustainability. https://doi.org/10.1016/j.cosust.2009.07.003</p><p>[2] Hirota, M., Holmgren, M., Van Nes, E. H., & Scheffer, M. (2011). Global resilience of tropical forest and savanna to critical transitions. Science, 334(6053), 232–235. https://doi.org/10.1126/science.1210657</p><p>[3] Boers, N., Marwan, N., Barbosa, H. M. J., & Kurths, J. (2017). A deforestation-induced tipping point for the South American monsoon system. Scientific Reports, 7. https://doi.org/10.1038/srep41489</p>

scholarly journals Catching Critical Transition in Engineered Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Jin Huang ◽  
Tianchuang Meng ◽  
Yangdong Deng ◽  
Fanling Huang
Keyword(s):  
Early Warning ◽  
Multiple Scales ◽  
Stable State ◽  
Critical Threshold ◽  
Supporting Evidence ◽  
Critical Transition ◽  
Warning Signals ◽  
Early Warning Signals ◽  
Critical Transitions ◽  
Engineered Systems

A variety of engineered systems can encounter critical transitions where the system suddenly shifts from one stable state to another at a critical threshold. The critical transition has aroused vital concerns for its potentially disastrous impacts. We validate an often taken-for-granted hypothesis that the failure of engineered systems can be attributed to the respective critical transitions and show how early warning signals are closely associated with critical transitions. We demonstrate that it is feasible to use early warning signals to predict system failures. Our findings open a new path to forecast failures of engineered systems with a generic method and provide supporting evidence for the universal existence of critical transition in dynamical systems at multiple scales.

scholarly journals Remotely-Sensed Early Warning Signals of a Critical Transition in a Wetland Ecosystem

2017 ◽  
Vol 9 (4) ◽  
pp. 352 ◽  
Author(s):  
Sara Alibakhshi ◽  
Thomas Groen ◽  
Miina Rautiainen ◽  
Babak Naimi
Keyword(s):  
Early Warning ◽  
Remotely Sensed ◽  
Critical Transition ◽  
Wetland Ecosystem ◽  
Warning Signals ◽  
Early Warning Signals
Sign in / Sign up

Export Citation Format

Share Document