Early Warnings for State Transitions

Caleb P. Roberts, Dirac Twidwell, Jessica L. Burnett, Victoria M. Donovan, Carissa L. Wonkka, Christine L. Bielski, Ahjond S. Garmestani, David G. Angeler, Tarsha Eason, Brady W. Allred, Matthew O. Jones, David E. Naugle, Shana M. Sundstrom, Craig R. Allen

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


New concepts have emerged in theoretical ecology with the intent to quantify complexities in ecological change that are unaccounted for in state-and-transition models and to provide applied ecologists with statistical early warning metrics able to predict and prevent state transitions. With its rich history of furthering ecological theory and its robust and broad-scale monitoring frameworks, the rangeland discipline is poised to empirically assess these newly proposed ideas while also serving as early adopters of novel statistical metrics that provide advanced warning of a pending shift to an alternative ecological regime. We review multivariate early warning and regime shift detection metrics, identify situations where various metrics will be most useful for rangeland science, and then highlight known shortcomings. Our review of a suite of multivariate-based regime shift/early warning indicators provides a broad range of metrics applicable to a wide variety of data types or contexts, from situations where a great deal is known about the key system drivers and a regime shift is hypothesized a priori, to situations where the key drivers and the possibility of a regime shift are both unknown. These metrics can be used to answer ecological state-and-transition questions, inform policymakers, and provide quantitative decision-making tools for managers.

Original languageEnglish
Pages (from-to)659-670
Number of pages12
JournalRangeland Ecology and Management
Issue number6
StatePublished - Nov 2018


  • early warning
  • rangeland monitoring
  • regime shift
  • resilience
  • spatial regimes
  • state-and-transition model


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