Hostname: page-component-78c5997874-ndw9j Total loading time: 0 Render date: 2024-11-19T11:49:37.372Z Has data issue: false hasContentIssue false
  • English
  • Français

Risk Assessment of Potential Biofuel Species: An Application for Trait-Based Models for Predicting Weediness?

Published online by Cambridge University Press:  20 January 2017

Roger Cousens
Roger Cousens*
Affiliation:
Department of Resource Management and Geography, The University of Melbourne, Burnley Campus, 500 Yarra Boulevard, Richmond, Victoria 3121, Australia
*
Corresponding author's E-mail: rcousens@unimelb.edu.au
Get access Rights & Permissions [Opens in a new window]

Abstract

To avoid major negative impacts of the widespread adoption of biofuel species, whether they are exotic species, natives, or novel constructs, we need a system for screening their weed potential. Australia is an important global center of biodiversity and also has major cropping industries to protect. Prevention of the entry of further weeds is therefore a major national priority. The Weed Risk Assessment (WRA) system was developed and implemented for importation decisions in 1997; it has since been introduced into other countries and is probably as good as any system currently in operation. However, we need to be aware of the limitations of any system, to address these, and to work toward improved or alternative systems. WRA is a very simple spreadsheet requiring answers to questions about a species' life-history traits, dispersal, habitat suitability, impacts on other species, and history overseas, which are then added together and compared with numerical decision criteria. Its predictive powers are limited by this simplicity and by the complexity of human attitudes toward risk and impact. Alternative risk-management methods are available but, even so, the capacity for improvement is limited. It is quite possible, therefore, that in using any trait-based system to assess the negative risks of importation or interstate translocation of biofuel species, we will wrongly reject a valuable species or approve a species that turns out to be a major weed. It is suggested that, rather than attempting to improve a single-tiered decision-support system (the quarantine “sieve”), a multitiered system (nested sieves) would lead to a more effective system and greater cost-effectiveness. The key to this would be a postentry screening process for those species that have successfully passed through the WRA system.

Keywords

Invasive speciesweedinessquarantinerisk assessmentlife historyimpactbiofuel
Type
Symposium
Information
Weed Science , Volume 56 , Issue 6 , December 2008 , pp. 873 - 882
Copyright
Copyright © Weed Science Society of America 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Literature Cited

Baker, H.G. 1965. Characteristics and modes of origin of weeds. Pages 147–172. in Baker, H.G. and Stebbins, G.L. The Genetics of Colonizing Species. New York Academic.Google Scholar
Baker, H.G. 1974. The evolution of weeds. Annu. Rev. Ecol. Syst. 5:1–24.Google Scholar
Barlow, B.A. 1994. Phytogeography of the Australian region. Pages 3–35. in Groves, R.H. Australian Vegetation. 2nd ed. Cambridge, UK Cambridge University Press.Google Scholar
Caley, P. and Kuhnert, P.M. 2006. Application and evaluation of classification trees for screening unwanted plants. Austral Ecol. 31:647–655.Google Scholar
Caley, P., Lonsdale, W.M., and Pheloung, P.C. 2006. Quantifying uncertainty in predictions of invasiveness, with emphasis on weed risk assessment. Biological Invasions. 8:1595–1604.Google Scholar
Cook, G.D. and Dias, L. 2006. It was no accident: deliberate plant introductions by Australian government agencies during the 20th century. Aust. J. Bot. 54:601–625.Google Scholar
Cooney, R. 2005. Introduction. Pages 3–17. in Cooney, R. and Dickson, B. Biodiversity and the Precautionary Principle: Risk and Uncertainty in Conservation and Sustainable Use. London Earthscan.Google Scholar
Cousens, R. 1985. A simple model relating yield loss to weed density. Ann. Appl. Biol. 107:239–252.Google Scholar
Cousens, R., Dytham, C., and Law, R. 2008. Dispersal in Plants: A Population Perspective. Oxford Oxford University Press.Google Scholar
Crawley, M.J. 1997. Biodiversity. Pages 595–632. in Crawley, M.J. Plant Ecology. 2nd ed. Oxford Blackwell Science.Google Scholar
Crooks, J.A. 2002. Characterizing ecosystem-level consequences of biological invasions: the role of ecosystem engineers. Oikos. 97:153–166.Google Scholar
Daehler, C.C., Denslow, J.S., Ansari, S., and Kuo, H.C. 2004. A risk-assessment system for screening out invasive pest plants from Hawaii and other Pacific islands. Conserv. Biol. 18:360–368.CrossRefGoogle Scholar
Denslow, J.S. and DeWalt, S.J. 2008. Plant invasions in tropical forests: patterns and mechanisms. Pages 409–426. in Carson, W.P. and Schnitzer, S.A. Tropical Forest Community Ecology. Oxford, UK Blackwell Scientific. In press.Google Scholar
Elith, J., Graham, C.H., Anderson, R.P., et al. 2006. Novel methods improve prediction of species' distributions from occurrence data. Ecography. 29:129–151.Google Scholar
Forcella, F. 1985. Final distribution is related to rate of spread in alien weeds. Weed Res. 25:181–191.Google Scholar
Gordon, D.R., Onderdonk, D.A., Fox, A.M., and Stocker, R.K. 2008. Consistent accuracy of the Australian weed risk assessment system across varied geographies. Divers. Distrib. 14:234–242.Google Scholar
Groves, R.H. 1991. A short history of biological invasions of Australia. Pages 59–63. in Groves, R.H. and Di Castri, F. Biogeography of Mediterranean Invasions. Cambridge, UK Cambridge University Press.Google Scholar
Groves, R.H. 2002. Robert Brown and the naturalized flora of Australia. Cunninghamia. 7:623–629.Google Scholar
Groves, R.H. and Hosking, J.R. 1997. Recent incursions of weeds to Australia 1971–1995. Technical Series No. 3. Adelaide, Australia CRC for Weed Management Systems.Google Scholar
Groves, R.H. and Willis, A.J. 1999. Environmental weeds and loss of native plant biodiversity: some Australian examples. Aust. J. Environ. Manag. 6:164–171.Google Scholar
Hazard, W.H.L. 1988. Introducing crop, pasture and ornamental species into Australia—the risk of introducing new weeds. Austr. Plant Intro. Rev. 19:19–36.Google Scholar
Holm, L.G., Plunknett, D.L., Pancho, J.V., and Herberger, H.P. 1977. The World's Worst Weeds: Distribution and Biology. Honolulu University Press of Hawaii.Google Scholar
Hughes, G. and Madden, L.V. 2003. Evaluating predictive models with application in regulatory policy for invasive weeds. Agric. Syst. 76:755–774.Google Scholar
Keeler, K.H. 1989. Can genetically engineered crops become weeds. Bio/Technology. 7:1134–1139.Google Scholar
Keller, R.P., Lodge, D.M., and Finnoff, D.C. 2007. Risk assessment for invasive species produces net bioeconomic benefits. Proc. Natl. Acad. Sci. 104:203–207.Google Scholar
Kot, M., Lewis, M.A., and van den Driessche, P. 1996. Dispersal data and the spread of invading organisms. Ecology. 77:2027–2042.Google Scholar
Kriticos, D.J. and Randall, R.P. 2001. A comparison of systems to analyze potential weed distributions. Pages 61–79. in Groves, R.H., Panetta, F.D., and Virtue, J.G. Weed Risk Assessment. Collingwood, Australia CSIRO.Google Scholar
Lonsdale, W.M. 1994. Inviting trouble: introduced pasture species in northern Australia. Aust. J. Ecol. 19:345–354.Google Scholar
Low, T. and Booth, C. 2007. The Weedy Truth About Biofuels. Melbourne Invasive Species Council.Google Scholar
MacArthur, R.H. and Wilson, E.O. 1967. The Theory of Island Biogeography. Princeton, NJ Princeton University Press.Google Scholar
Mack, R.N. 1996. Predicting the identity and fate of plant invaders: emergent and emerging approaches. Biological Conservation. 78:107–121.Google Scholar
Maguire, L.A. 2004. What can decision analysis do for invasive species management. Risk Analysis. 24:859–868.Google Scholar
Maillet, J. and Lopez-Garcia, C. 2000. What criteria are relevant for predicting the invasive capacity of a new agricultural weed. The case of invasive American species in France. Weed Res. 40:11–26.Google Scholar
Morfe, T.A., Weiss, J., and McLaren, D.A. 2002. Economics of serrated tussock and Mexican feather grass in Victoria: Why we need to act now. Plant Prot. Q. 17:86–94.Google Scholar
National Weed Risk Assessment System (NWRAS) 2006. Review of the National Weed Risk Assessment System. Canberra, Australia Natural Resource Management Standing Committee/Primary Industries Standing Committee Sub-Committee.Google Scholar
Nix, N.H. 1986. A biogeographic analysis of Australian elapid snakes. Pages 4–15. in Longmore, R. Atlas of the Australian Elapid Snakes. Canberra, Australia Bureau of Flora and Fauna.Google Scholar
Noble, I.R. 1989. Attributes of invaders and the invading process: terrestrial and vascular plants. Pages 301–313. in Drake, J.A., Mooney, H.A., do Castri, F., Groves, R.H., Kruger, F.J., Rejmánek, M., and Williamson, M. Biological Invasions: A Global Perspective. New York Wiley.Google Scholar
Panetta, F.D. 1993. A system of assessing proposed plant introductions for weed potential. Plant Prot. Q. 8:10–14.Google Scholar
Panetta, F.D., Mackey, A.P., Virtue, J.G., and Groves, R.H. 2001. Weed risk assessment: core issues and future directions. Pages 231–240. in Groves, R.H., Panetta, F.D., and Virtue, J.G. Weed Risk Assessment. Collingwood, Australia CSIRO.Google Scholar
Parker, I.M., Simberloff, D., Lonsdale, W.M., et al. 1999. Biol. Invasions. 1:3–19.Google Scholar
Parker, P., Caton, B.P., and Fowler, L. 2007. Ranking nonendigenous weed species by their potential to invade the United States. Weed Sci. 55:386–397.Google Scholar
Perrins, J., Williamson, M., and Fitter, A. 1992. Do annual weeds have predictable characters. Acta Oecol. 13:517–533.Google Scholar
Pheloung, P.C. 2001. Weed risk assessment for plant introductions to Australia. Pages 83–92. in Groves, R.H., Panetta, F.D., and Virtue, J.G. Weed Risk Assessment. Collingwood, Australia CSIRO.Google Scholar
Pheloung, P.C., Scott, J.K., and Randall, R.P. 1996. Predicting the distribution of Emex in Australia. Plant Prot. Q. 11:138–140.Google Scholar
Pheloung, P.C., Williams, P.A., Halloy, S.R., and S. R. 1999. A weed risk assessment model for use as a biosecurity tool evaluating plant introductions. Journal of Environmental Management. 57:239–251.CrossRefGoogle Scholar
Pianka, E.R. 1970. On r- and K-selection. Am. Nat. 104:592–597.Google Scholar
Radford, I.J. and Cousens, R.D. 2000. A comparative ecological study of Senecio madagascariensis (fireweed) and S. lautus (variable groundsel) (Asteraceae). Oecologia. 125:531–542.Google Scholar
Raghu, S., Anderson, R.C., Daehler, C.C., Davis, A.S., Wiedenmann, R.N., Simberloff, D., and Mack, R.N. 2006. Adding biofuels to the invasive species fire. Science. 313:1742.Google Scholar
Randall, R.P. 2007. The introduced flora of Australia. Adelaide, Australia CRC for Australian Weed Management.Google Scholar
Regan, H.M., Colyvan, M., and Burgman, M.A. 2002. A taxonomy and treatment of uncertainty for ecology and conservation biology. Ecol. Appl. 12:618–628.Google Scholar
Reichard, S.H. and Hamilton, C.W. 1997. Predicting invasions of woody plants introduced into North America. Conservation Biology. 11:193–203.Google Scholar
Rejmánek, M. 1996. A theory of seed plant invasiveness: The first sketch. Biol. Conserv. 78:171–181.Google Scholar
Rejmánek, M. 2001. What tools do we have to detect invasive plant species. Pages 3–9. in Groves, R.H., Panetta, F.D., and Virtue, J.G. Weed Risk Assessment. Collingwood, Australia CSIRO.Google Scholar
Rejmánek, M. and Richardson, D.M. 1996. What makes some plant species more invasive. Ecology. 77:1655–1661.CrossRefGoogle Scholar
Roy, J. 1990. In search of characteristics of plant invaders. Pages 335–352. in di Castri, J., Hansen, A.J., and Debussche, M. Biological Invasions in Europe and the Mediterranean Basin. Dordrecht Kluwer.Google Scholar
Scott, J.K. and Panetta, F.D. 1993. Predicting the Australian weed status of southern African plants. Journal of Biogeography. 20:87–93.Google Scholar
van Kleunen, M. and Johnson, S.D. 2007. South African Iridaceae with rapid and profuse seedling emergence are more likely to become naturalized in other regions. J. Ecol. 95:675–681.Google Scholar
Wainger, L.A. and King, D.M. 2001. Priorities for weed risk assessment: using a landscape context to assess indicators of functions, services and values. Pages 34–51. in Groves, R.H., Panetta, F.D., and Virtue, J.G. Weed Risk Assessment. Collingwood, Australia CSIRO.Google Scholar
Walton, C.S. 2001. Implementation of a permitted list approach to plant introductions in Australia. Pages 93–99. in Groves, R.H., Panetta, F.D., and Virtue, J.G. Weed Risk Assessment. Collingwood, Australia CSIRO.Google Scholar
Weber, J., Panetta, F.D., Virtue, J., and Pheloung, P. In press. An evaluation of eight years' data from the Australian border weed risk assessment system. J. Environ. Manag.Google Scholar
Williams, P.A. 2003. Guidelines for weed-risk assessment in developing countries. Pages 37–59. in Labrada, R. FAO Plant Production and Protection Paper 120 Addendum 1, Weed Management for Developing Countries. Rome Food and Agriculture Organization of the United Nations.Google Scholar
Williamson, M. 1993. Invaders, weeds and the risk from genetically modified organisms. Experientia. 49:219–224.Google Scholar