Biological Invasions

, Volume 18, Issue 4, pp 971–983 | Cite as

Defining invasiveness and invasibility in ecological networks

  • Cang Hui
  • David M. Richardson
  • Pietro Landi
  • Henintsoa O. Minoarivelo
  • Jeff Garnas
  • Helen E. Roy
Insect Invasions


The success of a biological invasion is context dependent, and yet two key concepts—the invasiveness of species and the invasibility of recipient ecosystems—are often defined and considered separately. We propose a framework that can elucidate the complex relationship between invasibility and invasiveness. It is based on trait-mediated interactions between species and depicts the response of an ecological network to the intrusion of an alien species, drawing on the concept of community saturation. Here, invasiveness of an introduced species with a particular trait is measured by its per capita population growth rate when the initial propagule pressure of the introduced species is very low. The invasibility of the recipient habitat or ecosystem is dependent on the structure of the resident ecological network and is defined as the total width of an opportunity niche in the trait space susceptible to invasion. Invasibility is thus a measure of network instability. We also correlate invasibility with the asymptotic stability of resident ecological network, measured by the leading eigenvalue of the interaction matrix that depicts trait-based interaction intensity multiplied by encounter rate (a pairwise product of propagule pressure of all members in a community). We further examine the relationship between invasibility and network architecture, including network connectance, nestedness and modularity. We exemplify this framework with a trait-based assembly model under perturbations in ways to emulate fluctuating resources and random trait composition in ecological networks. The maximum invasiveness of a potential invader (greatest intrinsic population growth rate) was found to be positively correlated with invasibility of the recipient ecological network. Additionally, ecosystems with high network modularity and high ecological stability tend to exhibit high invasibility. Where quantitative data are lacking we propose using a qualitative interaction matrix of the ecological network perceived by a potential invader so that the structural network stability and invasibility can be estimated from the literature or from expert opinion. This approach links network structure, invasiveness and invasibility in the context of trait-mediated interactions, such as the invasion of insects into mutualistic and antagonistic networks.


Biological invasions Fluctuating resource hypothesis Invasiveness Invasibility Ecological networks Interaction matrix Network stability Interaction strength 



This paper had its origin at a workshop on “Drivers, impacts, mechanisms and adaptation in insect invasions” hosted by the DST-NRF Centre of Excellence for Invasion Biology in Stellenbosch, South Africa, in November 2014. Additional financial support was provided by HortGro, the National Research Foundation of South Africa, Stellenbosch University, and SubTrop. We are grateful to participants at the workshop and to Marc Kenis, Wolfgang Rabitsch, Michael Pocock, Ulf Dieckmann and Åke Brännström for discussions on the concepts presented in this paper. CH is supported by the South African Research Chair Initiative (SARChI), the National Research Foundation of South Africa (Grant nos. 81825 and 76912), and the Australian Research Council (Discovery Project DP150103017). HOM receives a PhD Scholarship from the German Academic Exchange Service (DAAD). HER receives co-funding from the Natural Environment Research Council (NERC) and the Joint Nature Conservation Committee (JNCC). HER also acknowledges the COST Action TD1209. DMR acknowledges support from the National Research Foundation of South Africa (Grant 85417).

Supplementary material

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Supplementary material 1 (DOCX 20 kb)


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Cang Hui
    • 1
    • 2
  • David M. Richardson
    • 3
  • Pietro Landi
    • 1
    • 4
  • Henintsoa O. Minoarivelo
    • 1
  • Jeff Garnas
    • 5
  • Helen E. Roy
    • 6
  1. 1.Centre for Invasion Biology, Department of Mathematical SciencesStellenbosch UniversityMatielandSouth Africa
  2. 2.BioMath GroupAfrican Institute for Mathematical SciencesCape TownSouth Africa
  3. 3.Centre for Invasion Biology, Department of Botany and ZoologyStellenbosch UniversityMatielandSouth Africa
  4. 4.Evolution and Ecology ProgramInternational Institute for Applied Systems AnalysisLaxenburgAustria
  5. 5.Department of Zoology and Entomology, Forestry and Agricultural Biotechnology InstituteUniversity of PretoriaPretoriaSouth Africa
  6. 6.Centre for Ecology and HydrologyWallingfordUK

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