Early warning of critical transitions in biodiversity from compositional disorder

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Documents

DOI

  • C. Patrick Doncaster, University of Southampton, United Kingdom
  • Vasthi Alonso Chávez, University of Southampton, United Kingdom
  • Clément Viguier, Institute for Complex Systems Simulation, University of Southampton, Southampton, UK, University of Nice Polytech Nice-Sophia, Sophia-Antipolis, United Kingdom
  • Rong Wang, University of Southampton, State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, United Kingdom
  • Enlou Zhang, State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, China
  • Xuhui Dong
  • ,
  • John A. Dearing, Geography and Environment, University of Southampton, Southampton, UK, United Kingdom
  • Peter G. Langdon, University of Southampton, United Kingdom
  • James G. Dyke, Institute for Complex Systems Simulation, University of Southampton, Southampton, UK, University of Southampton, United Kingdom
Global environmental change presents a clear need for improved leading indicators of critical transitions, especially those that can be generated from compositional data and that work in empirical cases. Ecological theory of community dynamics under environmental forcing predicts an early replacement of slowly replicating and weakly competitive “canary” species by slowly replicating but strongly competitive “keystone” species. Further forcing leads to the eventual collapse of the keystone species as they are replaced by weakly competitive but fast-replicating “weedy” species in a critical transition to a significantly different state. We identify a diagnostic signal of these changes in the coefficients of a correlation between compositional disorder and biodiversity. Compositional disorder measures unpredictability in the composition of a community, while biodiversity measures the amount of species in the community. In a stochastic simulation, sequential correlations over time switch from positive to negative as keystones prevail over canaries, and back to positive with domination of weedy species. The model finds support in empirical tests on multi-decadal time series of fossil diatom and chironomid communities from lakes in China. The characteristic switch from positive to negative correlation coefficients occurs for both communities up to three decades preceding a critical transition to a sustained alternate state. This signal is robust to unequal time increments that beset the identification of early-warning signals from other metrics.
Original languageEnglish
JournalEcology
Volume97
Issue11
Pages (from-to)3079-3090
Number of pages12
ISSN0012-9658
DOIs
Publication statusPublished - 2016

    Research areas

  • critical slowing down, early warning signal, ecosystem canary, lake sediment, leading indicator, nestedness temperature, regime shift, tipping point

See relations at Aarhus University Citationformats

Download statistics

No data available

ID: 104674406