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A method to detect discontinuities in census data

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

Publikation: Bidrag till tidskriftArtikel i vetenskaplig tidskriftPeer review

Sammanfattning

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.
OriginalspråkEngelska
Sidor (från-till)9614-9623
Antal sidor10
TidskriftEcology and Evolution
Volym8
Nummer19
DOI
StatusPublicerad - 2018

FN:s SDG:er

Detta resultat bidrar till följande hållbara utvecklingsmål:

  1. SDG 15 – Ekosystem och biologisk mångfald
    SDG 15 – Ekosystem och biologisk mångfald

Nyckelord

  • discontinuities
  • discontinuity detector
  • ecosystem management
  • resilience

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