Biological Invasions

, Volume 18, Issue 3, pp 631–645 | Cite as

Identifying hotspots of alien plant naturalisation in Australia: approaches and predictions

  • Aaron J. Dodd
  • Michael A. McCarthy
  • Nigel Ainsworth
  • Mark A. Burgman
Original Paper


The early detection of newly naturalised alien species is vital to ensuring the greatest chance of their successful eradication. Understanding where species naturalise most frequently is the first stage in allocating surveillance effort. Using Australia’s Virtual Herbarium, we compiled the collection records for all plant species in Australia. We controlled for potential spatial biases in collection effort to identify areas that have an elevated rate of first records of alien species’ occurrence in Australia. Collection effort was highly variable across Australia, but the most intense collection effort occurred either close to herbaria (located in cities) or in remote natural environments. Significant clusters of first records of occurrence were identified around each state’s capital city, coinciding with higher collection effort. Using Poisson point process modelling, we were able to determine the relative influence of environmental and anthropogenic factors on the spatial variation in the risk of species naturalisation. Effort-corrected naturalisation risk appeared to be strongly related to land use, road and human population densities, as well as environmental factors such as average temperature and rainfall. Our paper illustrates how the risk of naturalisation at a location can be estimated quantitatively. Improved understanding of factors that contribute to naturalisation risk enhances allocation of surveillance effort, thereby detecting novel species sooner, and increasing the likelihood of their eventual eradication.


Alien flora Herbarium Invasive plants Pathway analysis Sampling bias Surveillance 



The authors would like to acknowledge Jane Catford, Jane Elith, Frith Jarrad, Petr Pysek, John Wilson and an additional anonymous reviewer for their insightful comments on earlier versions of this manuscript. Alison Vaughan, Niels Klazenga and Anna Monro helped us understand the nuances of both AVH and APC. Jane Elith provided advice regarding point process models. This research was supported by a Victorian Life Sciences Computation Initiative (VLSCI) Grant [VR0284] on its Peak Computing Facility at the University of Melbourne, an initiative of the Victorian Government, Australia. This research was also supported by an Australian Research Council (ARC) Future Fellowship to M.M. and the ARC Centre of Excellence for Environmental Decisions.

Supplementary material

10530_2015_1035_MOESM1_ESM.r (70 kb)
Supplementary material 1 (R 70 kb)


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Copyright information

© Her Majesty the Queen in Right of Australia as represented by: Sally Salmon 2015

Authors and Affiliations

  1. 1.Centre of Excellence for Biosecurity Risk Analysis, School of BioSciencesThe University of MelbourneParkvilleAustralia
  2. 2.Victorian Department of Economic Development, Jobs, Transport and ResourcesAttwoodAustralia
  3. 3.Centre of Excellence for Environmental Decisions, School of BioSciencesThe University of MelbourneParkvilleAustralia
  4. 4.Victorian Department of Economic Development, Jobs, Transport and ResourcesMelbourneAustralia

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