Literature DB >> 34143719

When and Where We Can Expect to See Early Warning Signals in Multispecies Systems Approaching Tipping Points: Insights from Theory.

Amy Chian Patterson, Alexander G Strang, Karen C Abbott.   

Abstract

AbstractEarly warning signals (EWSs) have the potential to predict tipping points where catastrophic changes occur in ecological systems. However, EWSs are plagued by false negatives, leading to undetected catastrophes. One reason may be because EWSs do not occur equally for all species in a system, so whether and how strongly EWSs are detected depends on which species is being observed. Here, we illustrate how the strength of EWSs is determined by each species' relationship to properties of the noise, the system's response to that noise, and the occurrence of critical slowing down (the dynamical phenomenon that gives rise to EWSs). Using these relationships, we present general rules for maximizing EWS detection in ecological communities. We find that for two-species competitive and mutualistic systems, one should generally monitor the species experiencing smaller intraspecific effects to maximize EWS performance, while in consumer-resource systems, one should monitor the species imposing the smaller interspecific effects. These guidelines appear to hold for at least some larger communities as well. We close by extending the theoretical basis for our rules to systems with any number of species and more complex forms of noise. Our findings provide important guidance on how to monitor systems for EWSs to maximize detection of tipping points.

Entities:  

Keywords:  critical slowing down; early warning signal; fold bifurcation; stochasticity; tipping point

Year:  2021        PMID: 34143719     DOI: 10.1086/714275

Source DB:  PubMed          Journal:  Am Nat        ISSN: 0003-0147            Impact factor:   3.926


  3 in total

Review 1.  Scaling up our understanding of tipping points.

Authors:  Sonia Kéfi; Camille Saade; Eric L Berlow; Juliano S Cabral; Emanuel A Fronhofer
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2022-06-27       Impact factor: 6.671

2.  Structure-based identification of sensor species for anticipating critical transitions.

Authors:  Andrea Aparicio; Jorge X Velasco-Hernández; Claude H Moog; Yang-Yu Liu; Marco Tulio Angulo
Journal:  Proc Natl Acad Sci U S A       Date:  2021-12-21       Impact factor: 12.779

3.  Anticipating the direction of symptom progression using critical slowing down: a proof-of-concept study.

Authors:  Marieke J Schreuder; Johanna T W Wigman; Robin N Groen; Els Weinans; Marieke Wichers; Catharina A Hartman
Journal:  BMC Psychiatry       Date:  2022-01-21       Impact factor: 3.630

  3 in total

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