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A method to detect discontinuities in census data

Citation

Barichievy, C and Angeler, DG and Eason, T and Garmestani, AS and Nash, KL and Stow, CA and Sundstrom, S and Allen, CR, A method to detect discontinuities in census data, Ecology and Evolution, 8, (19) pp. 9614-9623. ISSN 2045-7758 (2018) [Refereed Article]


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Copyright Statement

Copyright 2018 The Authors. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/

DOI: doi:10.1002/ece3.4297

Abstract

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.

Item Details

Item Type:Refereed Article
Keywords:discontinuity analysis, resilience, Gap Rarity Index, scale-specific pattern
Research Division:Mathematical Sciences
Research Group:Statistics
Research Field:Biostatistics
Objective Division:Environment
Objective Group:Ecosystem Assessment and Management
Objective Field:Ecosystem Assessment and Management at Regional or Larger Scales
UTAS Author:Nash, KL (Dr Kirsty Nash)
ID Code:129672
Year Published:2018
Web of Science® Times Cited:4
Deposited By:Ecology and Biodiversity
Deposited On:2018-12-12
Last Modified:2019-02-19
Downloads:33 View Download Statistics

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