4.4 Article

Invasion syndromes: a systematic approach for predicting biological invasions and facilitating effective management

Journal

BIOLOGICAL INVASIONS
Volume 22, Issue 5, Pages 1801-1820

Publisher

SPRINGER
DOI: 10.1007/s10530-020-02220-w

Keywords

Biological invasions; Context dependency; Invasion science; Invasive species

Funding

  1. DSI-NRF Centre of Excellence for Invasion Biology (CIB) in Stellenbosch, South Africa
  2. office of the Vice Rector: Research and Postgraduate Studies at Stellenbosch University
  3. DSI-NRF Centre of Excellence for Invasion Biology
  4. Centre of Excellence PLADIAS (Czech Science Foundation) [14-36079G]
  5. EXPRO Grant (Czech Science Foundation) [19-28807X]
  6. Czech Academy of Sciences [RVO 67985939]
  7. South African Department of Environment, Forestry, and Fisheries (DEFF)
  8. National Research Foundation of South Africa [89967, 109244]
  9. Australian Research Council [DP150103017]
  10. National Research Foundation [85417, 110507, 85412]
  11. Working for Water Programme through their collaborative research project: Research for Integrated Management of Invasive Alien Species
  12. Austrian Science Foundation FWF [I2086-B16]
  13. Czech Science Foundation [17-19025S]

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Our ability to predict invasions has been hindered by the seemingly idiosyncratic context-dependency of individual invasions. However, we argue that robust and useful generalisations in invasion science can be made by considering invasion syndromes which we define as a combination of pathways, alien species traits, and characteristics of the recipient ecosystem which collectively result in predictable dynamics and impacts, and that can be managed effectively using specific policy and management actions. We describe this approach and outline examples that highlight its utility, including: cacti with clonal fragmentation in arid ecosystems; small aquatic organisms introduced through ballast water in harbours; large ranid frogs with frequent secondary transfers; piscivorous freshwater fishes in connected aquatic ecosystems; plant invasions in high-elevation areas; tall-statured grasses; and tree-feeding insects in forests with suitable hosts. We propose a systematic method for identifying and delimiting invasion syndromes. We argue that invasion syndromes can account for the context-dependency of biological invasions while incorporating insights from comparative studies. Adopting this approach will help to structure thinking, identify transferrable risk assessment and management lessons, and highlight similarities among events that were previously considered disparate invasion phenomena.

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