A method to detect discontinuities in census data

Chris Barichievy, David G. Angeler, Tarsha Eason, Ahjond S. Garmestani, Kirsty L. Nash, Craig A. Stow, Shana Sundstrom, Craig R. Allen

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


The distribution of pattern across scales has predictive power in the analysis of complex systems. Discontinuity approaches remain a fruitful avenue of research in the quest for quantitative measures of resilience because discontinuity analysis provides an objective means of identifying scales in complex systems and facilitates delineation of hierarchical patterns in processes, structure, and resources. However, current discontinuity methods have been considered too subjective, too complicated and opaque, or have become computationally obsolete; given the ubiquity of discontinuities in ecological and other complex systems, a simple and transparent method for detection is needed. In this study, we present a method to detect discontinuities in census data based on resampling of a neutral model and provide the R code used to run the analyses. This method has the potential for advancing basic and applied ecological research.

Original languageEnglish (US)
Pages (from-to)9614-9623
Number of pages10
JournalEcology and Evolution
Issue number19
StatePublished - Oct 2018


  • discontinuities
  • discontinuity detector
  • ecosystem management
  • resilience

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Ecology
  • Nature and Landscape Conservation


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