The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Niche‐based modelling as a tool for predicting the risk of alien plant invasions at a global scale
Open accessAbstract
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.
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A new look at the statistical model identification
Akaike, H. (1974) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1974.1100705 · Cited by 51,879
Global Biodiversity Scenarios for the Year 2100
Sala, O. E., Stuart Chapin, F., III, Armesto, J. J., Berlow, E., Bloomfield, J., Dirzo, R., Huber-Sanwald, E., Huenneke, L. F., Jackson, R. B., et al. (2000) · Science · doi:10.1126/science.287.5459.1770 · Cited by 9,280
Terrestrial ecoregions of the world: a new map of life on Earth
Olson, D. M., Dinerstein, E., Wikramanayake, E. D., Burgess, N. D., Powell, G. V. N., Underwood, E. C., D'amico, J. A., Itoua, I., Strand, H. E., Morrison, J. C., et al. (2001) · BioScience · doi:10.1641/0006-3568(2001)051[0933:teotwa]2.0.co;2 · Cited by 8,488
Consequences of changing biodiversity
Chapin III, F. S., Zavaleta, E. S., Eviner, V. T., Naylor, R. L., Vitousek, P. M., Reynolds, H. L., Hooper, D. U., Lavorel, S., Sala, O. E., Hobbie, S. E., et al. (2000) · Nature · doi:10.1038/35012241 · Cited by 4,282
Effects of Invasive Alien Plants on Fire Regimes
BROOKS, M. L., D'ANTONIO, C. M., RICHARDSON, D. M., GRACE, J. B., KEELEY, J. E., DiTOMASO, J. M., HOBBS, R. J., PELLANT, M., & PYKE, D. (2004) · BioScience · doi:10.1641/0006-3568(2004)054[0677:eoiapo]2.0.co;2 · Cited by 1,634
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Species Distribution Models: Ecological Explanation and Prediction Across Space and Time
Elith, J., & Leathwick, J. R. (2009) · Annual Review of Ecology, Evolution, and Systematics · doi:10.1146/annurev.ecolsys.110308.120159 · Cited by 6,707
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Metadata
- Authors
- THUILLER, W., RICHARDSON, D. M., PYŠEK, P., MIDGLEY, G. F., HUGHES, G. O., & ROUGET, M.
- Venue
- Global Change Biology
- Publisher
- Wiley
- Published
- 2005-11-28
- Volume
- 11
- Issue
- 12
- Pages
- 2234-2250
- ISSN
- 1354-1013 (ISSN-L)
- 1365-2486
- OpenAlex
- W2140263047
- Cited by
- 927
- References
- 5
- FWCI
- 22.48
- Type
- journal article
- Language
- en
- Open access
- green
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- THUILLER, W., RICHARDSON, D. M., PYŠEK, P., MIDGLEY, G. F., HUGHES, G. O., & ROUGET, M. (2005). Niche‐based modelling as a tool for predicting the risk of alien plant invasions at a global scale. Global Change Biology. https://doi.org/10.1111/j.1365-2486.2005.001018.x
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