Detecting spatial regimes in ecosystems

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

Research output: Contribution to journalArticlepeer-review

52 Scopus citations


Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory-based method, on both terrestrial and aquatic animal data (U.S. Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps and multivariate analyses such as nMDS and cluster analysis. We successfully detected spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change.

Original languageEnglish (US)
Pages (from-to)19-32
Number of pages14
JournalEcology Letters
Issue number1
StatePublished - Jan 1 2017


  • Boundary detection
  • Fisher information
  • community change
  • regime shifts
  • spatial regimes
  • spatial resilience

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics


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