Hostname: page-component-78c5997874-j824f Total loading time: 0 Render date: 2024-11-10T15:56:44.208Z Has data issue: false hasContentIssue false
  • English
  • Français

Predicting Invasive Plants in Florida Using the Australian Weed Risk Assessment

Published online by Cambridge University Press:  20 January 2017

Doria R. Gordon ,
Daphne A. Onderdonk ,
Alison M. Fox ,
Randall K. Stocker  and
Crysta Gantz
Doria R. Gordon*
Affiliation:
The Nature Conservancy, and Courtesy Professor
Daphne A. Onderdonk
Affiliation:
Department of Botany, P.O. Box 118526, University of Florida, Gainesville, FL 32611
Alison M. Fox
Affiliation:
Department of Agronomy, Center for Aquatic and Invasive Plants, IFAS, P.O. Box 110500, University of Florida, Gainesville, Florida 32611-0500
Randall K. Stocker
Affiliation:
Department of Agronomy, Center for Aquatic and Invasive Plants, IFAS, P.O. Box 110500, University of Florida, Gainesville, Florida 32611-0500
Crysta Gantz
Affiliation:
Department of Agronomy, Center for Aquatic and Invasive Plants, IFAS, P.O. Box 110500, University of Florida, Gainesville, Florida 32611-0500
*
Corresponding author's E-mail: dgordon@tnc.org
Get access Rights & Permissions [Opens in a new window]

Abstract

Screening tools that effectively predict which nonnative species are likely to become invasive are necessary because of the disproportionate ecological and economic costs associated with invaders. We tested the effectiveness of the Australian Weed Risk Assessment system (WRA) in distinguishing plant species that are major invaders, minor invaders, and noninvaders in Florida. The test included 158 annuals and perennials in six growth forms from 52 families in 27 orders. The WRA with a secondary screen met all hypothesized accuracy levels: it correctly rejected 92% of test species that have been documented to be invasive in Florida and correctly accepted 73% of the noninvaders. The incorrect rejection of noninvaders was 8% with the remaining 19% of noninvaders falling into the “evaluate further” outcome. Only 10% of the 158 species required further evaluation. Invaders of natural areas and agricultural systems were identified with equal accuracy. Receiver operating characteristic analysis demonstrated high separation of invaders from noninvaders. The degree to which the WRA is precautionary may be adjusted by altering the cutoff scores that define the “accept, evaluate further,” and “reject” outcomes. This approach could be adopted in Florida as a screening mechanism to reduce importation of new invaders.

Keywords

Alien invasive speciesnonnativepredictive screening
Type
Research Articles
Information
Invasive Plant Science and Management , Volume 1 , Issue 2 , April 2008 , pp. 178 - 195
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

Biosecurity Australia 2007. The Weed Risk Assessment System. http://www.daffa.gov.au/ba/reviews/weeds/system. Accessed: August 8, 2007.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
Carter-Finn, K., Hodges, A. W., Lee, D. J., and Olexa, M. T. 2006. The History and Economics of Melaleuca Management in South Florida. Gainesville, FL Food and Resource Economics Department, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida. Electronic Data Information Source Publication FE670. http://edis.ifas.ufl.edu/pdffiles/FE/FE67000.pdf. Accessed: August 7, 2007.CrossRefGoogle Scholar
Daehler, C. and Carino, D. A. 2000. Predicting invasive plants: prospects for a general screening system based on current regional models. Biol. Invasions 2:93–102.Google Scholar
Daehler, C. C., Denslow, J. L., Ansari, S., and Kuo, H. 2004. A risk assessment system for screening out harmful invasive pest plants from Hawaii's and other Pacific islands. Conserv. Biol 18:360–368.CrossRefGoogle Scholar
DeLong, E. R., DeLong, D. M., and Clarke-Pearson, D. L. 1988. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44:837–845.CrossRefGoogle ScholarPubMed
Ewel, J. J. 1986. Invasibility: lessons from South Florida. Pages 214–230. in Mooney, H. A. and Drake, J. A., editors. Ecology of Biological Invasions of North America and Hawaii. New York Springer-Verlag.Google Scholar
[FAO] Food and Agriculture Organization of the United Nations 2005. Procedures for Weed Risk Assessment. Rome, Italy Plant Production and Protection Divison, FAO. ftp://ftp.fao.org/docrep/fao/009/y5885e/y5885e00.pdf. Accessed: November 28, 2007.Google Scholar
[FDACS] Florida Department of Agriculture and Consumer Services 2007. Florida Noxious Weed List. http://www.doacs.state.fl.us/pi/enpp/botany/noxweed.html. Accessed: August 9, 2007.Google Scholar
Florida Invasive Species Working Group 2003. Statewide Invasive Species Strategic Plan for Florida. http://www.iswgfla.org/. Accessed: August 9, 2007.Google Scholar
Fox, A. M., Gordon, D. R., Dusky, J. A., Tyson, L., and Stocker, R. K. 2005. IFAS Assessment of the Status of Non-Native Plants in Florida's Natural Areas. http://plants.ifas.ufl.edu/assessment. Accessed: August 9, 2007.Google Scholar
Gordon, D. R. 1998. Effects of invasive, non-indigenous plant species on ecosystem processes: lessons from Florida. Ecol. Appl 8:975–989.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. doi: 10.1111/j.1472-4642.2007.00460.x.Google Scholar
Gordon, D. R. and Thomas, K. P. 1997. Introduction of invasive non-indigenous plants into Florida: history, screening and regulatory approaches. Pages 21–37. in Simberloff, D., Schmitz, D. C., and Brown, T. C., editors. Strangers in Paradise: Impact and Management of Nonindigenous Species in Florida. Washington, DC Island Press.Google Scholar
Hall, C. R., Hodges, A. W., and Haydu, J. J. 2006. The economic impact of the green industry in the United States. Hort. Technol 16:345–353.Google Scholar
Hobbs, R. J. and Humphries, S. E. 1995. An integrated approach to the ecology and management of plant invasions. Conserv. Biol 9:761–770.CrossRefGoogle Scholar
Hodges, A. W. and Mulkey, W. D. 2006. Economic Impacts of Agricultural and Natural Resources Industries in Florida, 2003. Gainesville, FL Food and Resource Economics Department, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida. Electronic Data Information System publication FE627 http://edis.ifas.ufl.edu/FE627. Accessed: August 7, 2007.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.CrossRefGoogle Scholar
Jefferson, L., Havens, K., and Ault, J. 2004. Implementing invasive screening procedures: the Chicago Botanic Garden model. Weed Technol 18:1434–1440.CrossRefGoogle Scholar
Johnson, D. 1999. Floriculture and Environmental Horticulture: Situation and Outlook Report. Washington, DC USDA-Economic Research Service. FLO-1999. 107.Google Scholar
Kato, H., Hata, K., Yamamoto, H., and Yoshioka, T. 2006. Effectiveness of the weed risk assessment system for the Bonin Islands. Pages 65–72. in Koike, F., Clout, M. N., Kawamichi, M., De Poorter, M., and Iwatsuki, K., editors. Assessment and Control of Biological Invasion Risk. Kyoto, Japan and Gland, Switzerland Shoukadoh Book Sellers and IUCN.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. U. S. A. 104:203–207.CrossRefGoogle ScholarPubMed
Kitajima, K., Fox, A. M., Sato, T., and Nagamatsu, D. 2006. Cultivar selection prior to introduction may increase invasiveness: evidence from Ardisia crenata. Biol. Invasions 8:1471–1482.CrossRefGoogle Scholar
Kowarik, I. 1995. Time lags in biological invasion with regard to the success and failure of alien species. Pages 15–38. in Pysek, P., Rejmánek, M., and Wade, M., editors. Plant Invasions—General Aspects and Special Problems. Amsterdam, The Netherlands SPB Academic Publishing.Google Scholar
Křivánek, M. and Pyšek, P. 2006. Predicting invasions by woody species in a temperate zone: a test of three risk assessment schemes in the Czech Republic (Central Europe). Divers. Distrib 12:319–327.Google Scholar
Leung, B., Lodge, D. M., Finnoff, D., Shorgren, J. F., Lewis, M. A., and Lamberti, G. 2002. An ounce of prevention or a pound of cure: bioeconomic risk analysis of invasive species. Proc. R. Soc. Lond., Biol. Sci 269:2407–2413.Google Scholar
Mack, R. N. 1996. Predicting the identity and fate of plant invaders: emergent and emerging approaches. Biol. Conserv 78:107–121.Google Scholar
McNeely, J. A., Mooney, H. A., Neville, L. E., Schei, P., and Waage, J. K., editors. 2001. Global Strategy on Invasive Alien Species. Gland, Switzerland IUCN on behalf of the Global Invasive Species Programme. 50.Google Scholar
Mooney, H. A., Mack, R. N., McNeely, J. A., Neville, L. E., Schei, P. J., and Waage, J. K., editors. 2005. Invasive Alien Species: A New Synthesis. Washington, DC Island Press. 368.Google Scholar
National Invasive Species Council 2001. Management Plan: Meeting the Invasive Species Challenge. http://www.invasivespeciesinfo.gov/docs/council/mpfinal.pdf. Accessed: August 8, 2007.Google Scholar
Nishida, T. 2006. Towards a weed risk assessment model for Japan. Pages 73–76. in. Proceedings of the NIAES International Symposium. Tsukuba, Japan Epochal Tsukuba.Google Scholar
Panetta, F. D. 1993. A system for assessing proposed plant introductions for weed potential. Plant Prot. Q 8:10–14.Google Scholar
Parker, C., Caton, B. P., and Fowler, L. 2007. Ranking nonindigenous weed species by their potential to invade the United States. Weed Sci 55:386–397.Google Scholar
Perrins, C., Williamson, M., Barbier, E. B., Delfino, D., Dalmazzone, S., Shogren, J., Simmons, P., and Watkinson, A. 2002. Biological invasion risks and the public good: an economic perspective. Conserv. Ecol 6/1:1. http://www.consecol.org/vol6/iss1/art1. Accessed: August 8, 2007.Google Scholar
Perrins, J., Williamson, M., and Fitter, A. 1992. A survey of differing views of weed classification—implications for regulation of introductions. Biol. Conserv 60:47–56.Google Scholar
Pest Exclusion Advisory Committee 2001. Pest Exclusion Advisory Committee Report. Tallahassee, FL Florida Department of Agriculture and Consumer Services. 88.Google Scholar
Pheloung, P. C., Williams, P. A., and Halloy, S. R. 1999. A weed risk assessment model for use as a biosecurity tool evaluating plant introductions. J. Environ. Manage 57:239–251.Google Scholar
Pimentel, D., Zuniga, R., and Morrison, D. 2005. Update on the environmental and economic costs associated with alien-invasive species in the United States. Ecol. Econ 52:273–288.CrossRefGoogle Scholar
Reichard, S. H. and Hamilton, C. W. 1997. Predicting invasions of woody plants introduced into North America. Conserv. Biol 11:193–203.Google Scholar
Reichard, S. H. and White, P. 2001. Horticulture as a pathway of invasive plant introductions in the United States. Bioscience 51:103–113.CrossRefGoogle Scholar
Rejmánek, M., Richardson, D. M., Higgins, S. I., Pitcairn, M., and Grotkopp, E. 2005. Ecology of invasive plants: state of the art. Pages 104–161. in Monney, H. A., McNeely, J. A., Neville, L., Schei, P. J., and Waage, J., editors. Invasive Alien Species: A New Synthesis. Washington, DC Island Press.Google Scholar
Richardson, D. M., Pyšek, P., Rejmánek, M., Barbour, M. G., Panetta, F. D., and West, C. J. 2000. Naturalization and invasion of alien plants: concepts and definitions. Divers. Distrib 6:93–107.Google Scholar
Smith, C. S., Lonsdale, W. M., and Fortune, J. 1999. When to ignore advice: invasion predictions and decision theory. Biol. Invasions 1:89–96.Google Scholar
[SWSS] Southern Weed Science Society 1990 to 2005. Annual Research Reports of Common and Troublesome Weeds in Agriculture. Raleigh, NC Southern Weed Science Society Publications.Google Scholar
Stohlgren, T. J. and Schnase, J. L. 2006. Risk analysis for biological hazards: what we need to know about invasive species. Risk Anal 26:163–173.Google Scholar
Thuiller, W., Richardson, D. M., Pyšek, P., Midgley, G. F., Hughes, G. O., and Rouget, M. 2005. Niche-based modeling as a tool for predicting the risk of alien plant invasions at a global scale. Glob. Chang. Biol 11:2234–2250.CrossRefGoogle ScholarPubMed
[USDA-APHIS] U.S. Department of Agriculture Animal and Plant Health Inspection Service 2004. Weed-Initiated Pest Risk Assessment Guidelines for Qualitative Assessments. Raleigh, NC USDA-APHIS Center for Plant Health Science and Technology, Plant Epidemiology and Risk Analysis Laboratory. http://www.aphis.usda.gov/plant_health/plant_pest_info/weeds/downloads/wra.pdf. Accessed: August 9, 2007.Google Scholar
[USDA, NRCS] U.S. Department of Agriculture Natural Resources Conservation Service 2007. The PLANTS Database. Baton Rouge, LA National Plant Data Center. http://plants.usda.gov. Accessed: August 8, 2007.Google Scholar
Widrlechner, M. P., Thompson, J. R., Iles, J. K., and Dixon, P. M. 2004. Models for predicting the risk of naturalization of non-native woody plants in Iowa. J. Environ. Hort 22:23–31.Google Scholar
Wilcove, D. S., Rothstein, D., Dubow, J., Phillips, A., and Losos, E. 1998. Quantifying threats to imperiled species in the United States. Bioscience 48:607–615.Google Scholar
Williams, J. A. and West, C. J. 2000. Environmental weeds in Australia and New Zealand: issues and approaches to management. Austral Ecol 25/5:425–444.CrossRefGoogle Scholar
Williamson, M. and Fitter, A. 1996. The varying success of invaders. Ecology 77:1661–1665.Google Scholar
Wunderlin, R. P. and Hansen, B. F. 2003. Guide to the Vascular Plants of Florida, 2nd ed. Gainesville, FL University Press of Florida. 787.Google Scholar
Wunderlin, R. P. and Hansen, B. F. 2004. Online Atlas of Florida Vascular Plants. http://www.plantatlas.usf.edu/. Accessed: August 9, 2007.Google Scholar
Zhang, Z. and Pepe, M. S. 2005. A linear regression framework for receiver operating characteristic (ROC) curve analysis. Berkeley, CA University of Washington Biostatistics Working Paper Series. Paper 253. 22.Google Scholar