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

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.
Biological invasions, Context dependency, Invasion science, Invasive species
Novoa, A., Richardson, D.M., Pyšek, P., Meyerson, L.A., Bacher, S., Canavan, S., Catford, J.A., Čuda, J., Essl, F., Foxcroft, L.C., Genovesi, P., Hirsch, H., Hui, C., Jackson, M.C., Kueffer, C., Le Roux, J.J., Measey, J., Mohanty, N.P., Moodley, D., Müller-Schärer, H., Packer, J.G., Pergl, J., Robinson, T.B., Saul, W.C., Shackleton, R.T., Visser, V., Weyl, O.L.F., Yannelli, F.A. and Wilson, J.R.U. (2020). Invasion syndromes: a systematic approach for predicting biological invasions and facilitating effective management. Biological Invasions 22, 1801-1820.