A unified approach for quantifying invasibility and degree of invasion

Abstract

Habitat invasibility is a central focus of invasion biology, with implications for basic ecological patterns and processes and for effective invasion management. ‘‘Invasibility’’ is, however, one of the most elusive metrics and misused terms in ecology. Empirical studies and meta-analyses of invasibility have produced inconsistent and even conflicting results. This lack of consistency, and subsequent difficulty in making broad cross-habitat comparisons, stem in part from (1) the indiscriminant use of a closely related, but fundamentally different concept, that of degree of invasion (DI) or level of invasion; and (2) the lack of common invasibility metrics, as illustrated by our review of all invasibility-related papers published in
2013. To facilitate both cross-habitat comparison and more robust ecological generalizations, we clarify the definitions of invasibility and DI, and for the first time propose a common metric for quantifying invasibility based on a habitat’s resource availability as inferred from relative resident species richness and biomass. We demonstrate the feasibility of our metric using empirical data collected from 2475 plots from three forest ecosystems in the eastern United States. We also propose a similar metric for DI. Our unified, resource-based metrics are scaled from 0 to 1, facilitating cross-habitat comparisons. Our proposed metrics clearly distinguish invasibility and DI from each other, which will help to (1) advance invasion ecology by allowing more robust testing of generalizations and (2) facilitate more effective invasive species control and management.

  • Citation: Guo, Qinfeng; Fei, Songlin; Dukes, Jeffrey S.; Oswalt, Christopher M.; III, Basil V. Iannone; Potter, Kevin M. 2015. A unified approach for quantifying invasibility and degree of invasion. Ecology, Vol. 96(10): 9 pages.: 2613-2621.  10.1890/14-2172.1
  • Keywords: abundance; community ecology theory; competition; invasion theory; niche availability; prediction; resources.
  • Posted Date: January 6, 2016
  • Modified Date: January 7, 2016
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