Niche-based modelling as a tool for predicting the risk of alien plant invasions at a global scale

Authors

  • WILFRIED THUILLER,

    1. Climate Change Research Group, Kirstenbosch Research Centre, South African National Biodiversity Institute, P/Bag x7, Claremont 7735, Cape Town, South Africa,
    2. Laboratoire d'Ecologie Alpine, CNRS, Université Joseph Fourier, BP 53, 38041 Grenoble Cedex 9, France,
    Search for more papers by this author
  • DAVID M. RICHARDSON,

    1. Centre for Invasion Biology, Department of Botany and Zoology, University of Stellenbosch, Private Bag X1, Matieland 7602, South Africa,
    Search for more papers by this author
  • PETR PYŠEK,

    1. Institute of Botany, Academy of Sciences of the Czech Republic, CZ-252 43 Průhonice, Czech Republic,
    2. Department of Ecology, Charles University, Viničná 2, CZ-128 02 Praha 2, Czech Republic,
    Search for more papers by this author
  • GUY F. MIDGLEY,

    1. Climate Change Research Group, Kirstenbosch Research Centre, South African National Biodiversity Institute, P/Bag x7, Claremont 7735, Cape Town, South Africa,
    2. Center for Applied Biodiversity Conservation, Conservation International, 1919 M St., Washington, DC 20036, USA
    Search for more papers by this author
  • GREG O. HUGHES,

    1. Climate Change Research Group, Kirstenbosch Research Centre, South African National Biodiversity Institute, P/Bag x7, Claremont 7735, Cape Town, South Africa,
    Search for more papers by this author
  • MATHIEU ROUGET

    1. Climate Change Research Group, Kirstenbosch Research Centre, South African National Biodiversity Institute, P/Bag x7, Claremont 7735, Cape Town, South Africa,
    Search for more papers by this author

Wilfried Thuiller, e-mail: Thuiller@sanbi.org

Abstract

Predicting the probability of successful establishment of plant species by matching climatic variables has considerable potential for incorporation in early warning systems for the management of biological invasions. We select South Africa as a model source area of invasions worldwide because it is an important exporter of plant species to other parts of the world because of the huge international demand for indigenous flora from this biodiversity hotspot. We first mapped the five ecoregions that occur both in South Africa and other parts of the world, but the very coarse definition of the ecoregions led to unreliable results in terms of predicting invasible areas. We then determined the bioclimatic features of South Africa's major terrestrial biomes and projected the potential distribution of analogous areas throughout the world. This approach is much more powerful, but depends strongly on how particular biomes are defined in donor countries. Finally, we developed bioclimatic niche models for 96 plant taxa (species and subspecies) endemic to South Africa and invasive elsewhere, and projected these globally after successfully evaluating model projections specifically for three well-known invasive species (Carpobrotus edulis, Senecio glastifolius, Vellereophyton dealbatum) in different target areas. Cumulative probabilities of climatic suitability show that high-risk regions are spatially limited globally but that these closely match hotspots of plant biodiversity. These probabilities are significantly correlated with the number of recorded invasive species from South Africa in natural areas, emphasizing the pivotal role of climate in defining invasion potential. Accounting for potential transfer vectors (trade and tourism) significantly adds to the explanatory power of climate suitability as an index of invasibility.

The close match that we found between the climatic component of the ecological habitat suitability and the current pattern of occurrence of South Africa alien species in other parts of the world is encouraging. If species' distribution data in the donor country are available, climatic niche modelling offers a powerful tool for efficient and unbiased first-step screening. Given that eradication of an established invasive species is extremely difficult and expensive, areas identified as potential new sites should be monitored and quarantine measures should be adopted.

Ancillary