Literature DB >> 28812627

Direct observation of increasing recovery length before collapse of a marine benthic ecosystem.

Luca Rindi1, Martina Dal Bello1, Lei Dai2, Jeff Gore2, Lisandro Benedetti-Cecchi1.   

Abstract

Ecosystems can experience catastrophic transitions to alternative states, yet recent results have suggested that slowing down in rates of recovery after a perturbation may provide advance warning that a critical transition is approaching. Perturbation experiments with microbial populations have supported this hypothesis under controlled laboratory conditions, but evidence from natural ecosystems remains rare. Here, we manipulated rocky intertidal canopy algae to test the hypothesis that the spatial scale at which the system recovers from a perturbation in space should increase as the system approaches the tipping point, marking the transition from a canopy-dominated to a turf-dominated state. Empirical estimates of recovery length, a recently proposed spatial indicator of an approaching tipping point, were obtained by comparing the spatial scale at which algal turfs propagated into canopy-degraded regions with decreasing canopy cover. We show that recovery length increased along the gradient in canopy degradation, providing field-based evidence of spatial signatures of critical slowing down in natural conditions.

Entities:  

Year:  2017        PMID: 28812627     DOI: 10.1038/s41559-017-0153

Source DB:  PubMed          Journal:  Nat Ecol Evol        ISSN: 2397-334X            Impact factor:   15.460


  11 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.  How one might miss early warning signals of critical transitions in time series data: A systematic study of two major currency pairs.

Authors:  Haoyu Wen; Massimo Pica Ciamarra; Siew Ann Cheong
Journal:  PLoS One       Date:  2018-03-14       Impact factor: 3.240

3.  Rate of recovery from perturbations as a means to forecast future stability of living systems.

Authors:  Amin Ghadami; Eleni Gourgou; Bogdan I Epureanu
Journal:  Sci Rep       Date:  2018-06-18       Impact factor: 4.379

4.  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

5.  Machine learning methods trained on simple models can predict critical transitions in complex natural systems.

Authors:  Smita Deb; Sahil Sidheekh; Christopher F Clements; Narayanan C Krishnan; Partha S Dutta
Journal:  R Soc Open Sci       Date:  2022-02-16       Impact factor: 2.963

6.  Robots as models of evolving systems.

Authors:  Gao Wang; Trung V Phan; Shengkai Li; Jing Wang; Yan Peng; Guo Chen; Junle Qu; Daniel I Goldman; Simon A Levin; Kenneth Pienta; Sarah Amend; Robert H Austin; Liyu Liu
Journal:  Proc Natl Acad Sci U S A       Date:  2022-03-17       Impact factor: 12.779

7.  Spatiotemporal variability in Swedish lake ecosystems.

Authors:  Tarsha Eason; Ahjond Garmestani; David G Angeler
Journal:  PLoS One       Date:  2022-03-21       Impact factor: 3.240

8.  Diversity of Molluscan Assemblage in Relation to Biotic and Abiotic Variables in Brown Algal Forests.

Authors:  Martina Orlando-Bonaca; Domen Trkov; Katja Klun; Valentina Pitacco
Journal:  Plants (Basel)       Date:  2022-08-16

9.  Ocean acidification conditions increase resilience of marine diatoms.

Authors:  Jacob J Valenzuela; Adrián López García de Lomana; Allison Lee; E V Armbrust; Mónica V Orellana; Nitin S Baliga
Journal:  Nat Commun       Date:  2018-06-13       Impact factor: 14.919

10.  Impairment of microbial and meiofaunal ecosystem functions linked to algal forest loss.

Authors:  Silvia Bianchelli; Roberto Danovaro
Journal:  Sci Rep       Date:  2020-11-17       Impact factor: 4.379

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