Literature DB >> 23092014

Regime shift indicators fail under noise levels commonly observed in ecological systems.

Charles T Perretti1, Stephan B Munch.   

Abstract

Ecological regime shifts are rapid, potentially devastating changes in ecosystem state that last for extended periods of time. Previous theoretical work has generated numerous early-warning indicators of regime shifts, some of which have been empirically demonstrated in closed ecological systems. Here we evaluated a suite of indicators using a previously studied three-species model under conditions likely to be observed in field studies of open ecological systems. Simulations included large correlated fluctuations in extrinsic noise and a rapidly changing driving variable, while indicators were calculated using sparsely sampled time series. All indicators performed poorly under these conditions, particularly during the beginning of the regime shift. Overall, the best performing indicator was a rise in variance. Future research should focus on methods for setting benchmark values of early warning indicators and for identifying indicators that work for sparsely sampled data sets.

Mesh:

Year:  2012        PMID: 23092014     DOI: 10.1890/11-0161.1

Source DB:  PubMed          Journal:  Ecol Appl        ISSN: 1051-0761            Impact factor:   4.657


  11 in total

1.  Critical slowing down as early warning for the onset of collapse in mutualistic communities.

Authors:  Vasilis Dakos; Jordi Bascompte
Journal:  Proc Natl Acad Sci U S A       Date:  2014-11-24       Impact factor: 11.205

2.  Detecting spatial regimes in ecosystems.

Authors:  Shana M Sundstrom; Tarsha Eason; R John Nelson; David G Angeler; Chris Barichievy; Ahjond S Garmestani; Nicholas A J Graham; Dean Granholm; Lance Gunderson; Melinda Knutson; Kirsty L Nash; Trisha Spanbauer; Craig A Stow; Craig R Allen
Journal:  Ecol Lett       Date:  2017-01       Impact factor: 9.492

3.  Evaluating early-warning indicators of critical transitions in natural aquatic ecosystems.

Authors:  Alena Sonia Gsell; Ulrike Scharfenberger; Deniz Özkundakci; Annika Walters; Lars-Anders Hansson; Annette B G Janssen; Peeter Nõges; Philip C Reid; Daniel E Schindler; Ellen Van Donk; Vasilis Dakos; Rita Adrian
Journal:  Proc Natl Acad Sci U S A       Date:  2016-11-22       Impact factor: 11.205

4.  Forecasting resilience profiles of the run-up to regime shifts in nearly-one-dimensional systems.

Authors:  Matthew W Adamson; Jonathan H P Dawes; Alan Hastings; Frank M Hilker
Journal:  J R Soc Interface       Date:  2020-09-16       Impact factor: 4.118

5.  Teaching machines to anticipate catastrophes.

Authors:  Marcus Lapeyrolerie; Carl Boettiger
Journal:  Proc Natl Acad Sci U S A       Date:  2021-10-05       Impact factor: 11.205

6.  No evidence of critical slowing down in two endangered Hawaiian honeycreepers.

Authors:  Jessica C Rozek; Richard J Camp; J Michael Reed
Journal:  PLoS One       Date:  2017-11-13       Impact factor: 3.240

7.  An information theory-based approach to assessing spatial patterns in complex systems.

Authors:  Tarsha Eason; Wen Ching-Chuang; Shana Sundstrom; Heriberto Cabezas
Journal:  Entropy (Basel)       Date:  2019-02-15       Impact factor: 2.524

8.  Global assessment of early warning signs that temperature could undergo regime shifts.

Authors:  Mathieu Chevalier; Gaël Grenouillet
Journal:  Sci Rep       Date:  2018-07-03       Impact factor: 4.379

9.  Detecting critical slowing down in high-dimensional epidemiological systems.

Authors:  Tobias Brett; Marco Ajelli; Quan-Hui Liu; Mary G Krauland; John J Grefenstette; Willem G van Panhuis; Alessandro Vespignani; John M Drake; Pejman Rohani
Journal:  PLoS Comput Biol       Date:  2020-03-09       Impact factor: 4.475

10.  Detecting and distinguishing tipping points using spectral early warning signals.

Authors:  T M Bury; C T Bauch; M Anand
Journal:  J R Soc Interface       Date:  2020-09-30       Impact factor: 4.118

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.