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Measuring β-diversity with species abundance data.

Louise J Barwell1,2, Nick J B Isaac2, William E Kunin1

  • 1Institute of Integrative and Comparative Biology, University of Leeds, LC Miall Building, Leeds, LS2 9JT, UK.

The Journal of Animal Ecology
|March 4, 2015
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Summary

This study evaluates abundance-based beta-diversity metrics, finding many redundancies and trade-offs. Abundance metrics are less biased with undersampling, but new metrics are needed to estimate unseen species.

Keywords:
community compositiondifferentiationmetricsrank abundance distributionsimilaritysimulated assemblagespatial turnoverβ-diversity indices

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Area of Science:

  • Ecology
  • Spatial Ecology
  • Biodiversity Science

Background:

  • Beta-diversity is crucial for understanding spatial ecology.
  • Numerous metrics exist to quantify beta-diversity, necessitating careful selection.
  • A previous review identified trade-offs and redundancies among presence-absence metrics.

Purpose of the Study:

  • To investigate the performance of abundance-based beta-diversity metrics.
  • To test 16 conceptual and 2 sampling properties of beta-diversity metrics.
  • To identify redundancies and performance trade-offs among existing metrics.

Main Methods:

  • Evaluated 29 abundance-based beta-diversity metrics against 16 conceptual and 2 sampling properties.
  • Assessed metric performance based on independence from alpha-diversity, monotonicity with turnover, and behavior with nestedness.
  • Compared abundance-based metrics to presence-absence metrics like betaSim.

Main Results:

  • Thirteen of the tested metrics were outperformed or equaled by others across all properties.
  • Abundance-based metrics generally show less bias with undersampling, aiding rare species detection.
  • Only betaBaselga R turn, betaBaselga B-C turn, and betaSim purely measured species turnover and were independent of nestedness.

Conclusions:

  • Significant redundancy exists among current beta-diversity metrics.
  • A performance trade-off exists between sample size bias and detecting rare species turnover.
  • Future abundance-based metrics should address the estimation of unseen shared and unshared species.