Biological Invasions

, Volume 12, Issue 3, pp 463–476 | Cite as

Predicting plant invaders in the Mediterranean through a weed risk assessment system

  • Núria Gassó
  • Corina Basnou
  • Montserrat Vilà
Original Paper


Risk assessment schemes have been developed to identify potential invasive species, prevent their spread and reduce their damaging effects. One of the most promising tools for detecting plant invaders is the weed risk assessment (WRA) scheme developed for Australia. Our study explores whether the Australian WRA can satisfactorily predict the invasion status of alien plants in the Mediterranean Basin by screening 100 invasive and 97 casual species in Spain. Furthermore, we analysed whether the factors taken into account in the WRA are linked to invasion likelihood (i.e., invasion status) or to impacts. The outcome was that 94% of the invasive species were rejected, 50% of the casual species were rejected and 29% of them required further evaluation. The accuracy for casuals is lower than in other studies that have tested non-invasive (i.e., casuals or non-escaped) alien species. We postulate that low accuracy for casual species could result from: (1) an incorrect “a priori” expert classification of the species status, (2) a high weight of the WRA scores given to potential impacts, and (3) casual species being prone to becoming invasive when reaching a minimum residence time threshold. Therefore, the WRA could be working as a precaution early-warning system to identify casual species with potential to become invasive.


Alien plants Casual plants Mediterranean region Species traits Weed risk assessment 



We thank I. Kühn and P. Pyšek for providing the WRA excel application; and C. Daehler and three anonymous reviewers for comments on an early version of the manuscript. This study has been partially financed by the 6th Framework Programme of the European Commission projects ALARM (Assessing large-scale environmental risks for biodiversity with tested methods. GOCE-CT-2003-506675; and DAISIE (Delivering alien invasive species inventories for Europe. SSPI-CT-2003-511202; and the Spanish Ministerio de Ciencia e Innovación CONSOLIDER project MONTES (Spanish woodlands and global change: threats and opportunities. CSD2008-00040).


  1. Andersen MC, Adams H, Hope B, Powell M (2004) Risk assessment for invasive species. Risk Anal 24(4):787–793. doi: 10.1111/j.0272-4332.2004.00478.x CrossRefPubMedGoogle Scholar
  2. Baker HG (1965) Characteristics and modes of origin of weeds. In: Baker HG, Stebbins GL (eds) The genetics of colonizing species. Academic Press, New YorkGoogle Scholar
  3. Blackburn TM, Duncan RP (2001) Determinants of establishment success in introduced birds. Nature 414:195–197. doi: 10.1038/35102557 CrossRefPubMedGoogle Scholar
  4. Bolòs O, Vigo J, Masalles RM, Ninot JM (2005) Flora manual dels Països Catalans, 3rd edn. Ketrès, BarcelonaGoogle Scholar
  5. Brändle M, Stadler J, Klotz S, Brandl R (2003) Distributional range size of weedy plant species is correlated to germination patterns. Ecology 84:136–144. doi: 10.1890/0012-9658(2003)084[0136:DRSOWP]2.0.CO;2 CrossRefGoogle Scholar
  6. Caley P, Kuhnert PM (2006) Application and evaluation of classification trees for screening unwanted plants. Austral Ecol 31:647–655. doi: 10.1111/j.1442-9993.2006.01617.x CrossRefGoogle Scholar
  7. Caley P, Lonsdale WM, Pheloung PC (2006) Quantifying uncertainty in predictions of invasiveness. Biol Invasions 8:277–286. doi: 10.1007/s10530-004-6703-z CrossRefGoogle Scholar
  8. Caley P, Groves RH, Barker R (2008) Estimating the invasion success of introduced plants. Divers Distrib 14:196–203. doi: 10.1111/j.1472-4642.2007.00440.x CrossRefGoogle Scholar
  9. Callaway RM, Ridenour WM (2004) Novel weapons: invasive success and the evolution of increased competitive ability. Front Ecol Environ 2:436–443CrossRefGoogle Scholar
  10. Castroviejo S, Laínz M, López G, Montserrat P, Muñoz F, Paiva J, Villar L (eds) (1986–2000) Flora Ibérica. Real Jardín Botánico, CSIC, MadridGoogle Scholar
  11. Colautti RI, Ricciardi A, Grigorovich IA, Maclsaac HJ (2004) Is invasion success explained by the enemy release hypothesis? Ecol Lett 7:721–733. doi: 10.1111/j.1461-0248.2004.00616.x CrossRefGoogle Scholar
  12. Crawley MJ (2002) Statistical computing: an introduction to data analysis using S-Plus. Wiley, ChichesterGoogle Scholar
  13. Crooks JA (2005) Lag times and exotic species: the ecology and management of biological invasions in slow-motion. Ecoscience 12:316–329. doi: 10.2980/i1195-6860-12-3-316.1 CrossRefGoogle Scholar
  14. Crosti R, Cascone C, Testa W (2007) Towards a weed risk assessment for the Italian peninsula: preliminary validation of a scheme for the central Mediterranean region in Italy. In: Rokich D, Wardell-Johnson G, Yates C, Stevens J, Dixon K, McLellan R, Moss G (eds) Proceedings, International Mediterranean Ecosystems Conference, Perth, Australia, 2–5 September 2007, pp 53–54Google Scholar
  15. Daehler CC (1998) Variation in self-fertility and the reproductive advantage of self-fertility for an invading plant (Spatina alterniflora). Evol Ecol 12:553–568. doi: 10.1023/A:1006556709662 CrossRefGoogle Scholar
  16. Daehler CC (2003) Performance comparisons of co-occurring native and alien invasive plants: implications for conservation and restoration. Annu Rev Ecol Evol Syst 34:183–211. doi: 10.1146/annurev.ecolsys.34.011802.132403 CrossRefGoogle Scholar
  17. Daehler CC, Carino DA (2000) Predicting invasive plants: prospects for general screening system based on current regional models. Biol Invasions 2:93–102. doi: 10.1023/A:1010002005024 CrossRefGoogle Scholar
  18. Daehler CC, Denslow J, Ansari S, 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. doi: 10.1111/j.1523-1739.2004.00066.x CrossRefGoogle Scholar
  19. DeLong ER, DeLong DM, Clarke-Pearson DL (1988) Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44:837–845. doi: 10.2307/2531595 CrossRefPubMedGoogle Scholar
  20. Di Castri F (1989) History of biological invasions with special emphasis on the Old Word. In: Drake JA (ed) Biological invasions: a global perspective. Wiley, ChichesterGoogle Scholar
  21. Goodwin BJ, Mcallister AJ, Fahrig L (1999) Predicting invasiveness of plant species based on biological information. Conserv Biol 13:422–426. doi: 10.1046/j.1523-1739.1999.013002422.x CrossRefGoogle Scholar
  22. Gordon DR, Onderdonk DA, Fox AM, Stocker RK (2008) Consistent accuracy of the Australian weed risk assessment system across varied regions. Divers Distrib 14:234–242. doi: 10.1111/j.1472-4642.2007.00460.x CrossRefGoogle Scholar
  23. Harvey PH, Pagel MD (1991) The comparative method in evolutionary biology. Oxford University Press, OxfordGoogle Scholar
  24. Heger T, Trepl L (2003) Predicting biological invasions. Biol Invasions 5:313–321. doi: 10.1023/B:BINV.0000005568.44154.12 CrossRefGoogle Scholar
  25. Hughes G, Madden LV (2003) Evaluating predictive models with application in regulatory policy for invasive weeds. Agric Syst 76:755–774. doi: 10.1016/S0308-521X(02)00164-6 CrossRefGoogle Scholar
  26. Kato H, Hata K, Yamamoto H, Yoshioka T (2006) Effectiveness of the weed risk assessment system for the Bonin Islands. In: Koike F, Clout MN, Kawamichi M, De Poorter M, Iwatsuki K (eds) Assessment and control of biological invasion risk. Shoukadoh Book Sellers, Kyoto, Japan and IUCN, Gland, Switzerland pp 65–72Google Scholar
  27. Keller RP, Drake JM, Lodge DM (2007a) Fecundity as a basis for risk assessment of nonindigenous freshwater Molluscs. Conserv Biol 21:191–200. doi: 10.1111/j.1523-1739.2006.00563.x CrossRefPubMedGoogle Scholar
  28. Keller RP, Lodge DM, Finnoff DC (2007b) Risk assessment for invasive species produces net bioeconomic benefits. Proc Natl Acad Sci USA 104:203–207. doi: 10.1073/pnas.0605787104 CrossRefPubMedGoogle Scholar
  29. Kolar CS, Lodge DM (2001) Progress in invasion biology: predicting invaders. Trends Ecol Evol 16:199–204. doi: 10.1016/S0169-5347(01)02101-2 CrossRefPubMedGoogle Scholar
  30. Křivánek M, 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. doi: 10.1111/j.1366-9516.2006.00249.x CrossRefGoogle Scholar
  31. Lasko TA, Bhagwat JG, Zou KH, Ohno-Machado L (2005) The use of receiver operating characteristic curves in biomedical informatics. J Biomed Inform 38:404–415. doi: 10.1016/j.jbi.2005.02.008 CrossRefPubMedGoogle Scholar
  32. Lepš J, Šmilauer P (2006) Multivariate analysis of ecological data using CANOCO. Cambridge University Press, CambridgeGoogle Scholar
  33. Leung B, Lodge DM, Finnoff D, Shogren JF, Lewis MA, Lamberti G (2002) An ounce of prevention or a pound of cure: bioeconomic risk analysis of invasive species. Biol Sci 269:2407–2413. doi: 10.1098/rspb.2002.2179 CrossRefGoogle Scholar
  34. Lloret F, Médail F, Brundu G, Camarda I, Moragues E, Rita J, Lambdon P, Hulme PE (2005) Species attributes and invasion success by alien plants on Mediterranean islands. J Ecol 93:512–520. doi: 10.1111/j.1365-2745.2005.00979.x CrossRefGoogle Scholar
  35. Lockwood JL, Cassey P, Blackburn TM (2005) The role of propagule pressure in explaining species invasions. Trends Ecol Evol 20:223–228. doi: 10.1016/j.tree.2005.02.004 CrossRefPubMedGoogle Scholar
  36. McNeely JA, Mooney HA, Neville LE, Schei PJ, Waage JK (eds) (2001) A global strategy on invasive alien species. IUCN, GlandGoogle Scholar
  37. Medail F, Quezel P (1997) Hot-spots analysis for conservation of plant biodiversity in the Mediterranean basin. Ann Mo Bot Gard 84:112–127. doi: 10.2307/2399957 CrossRefGoogle Scholar
  38. National Invasive Species Council (2001) Management plan: meeting the invasive species challenge. Washington, DC. Available from Accessed August 2007
  39. Pheloung PC (1995) Determining the weed potential of new plant introductions to Australia. Agriculture Protection Board Report. West Australian Department of Agriculture, PerthGoogle Scholar
  40. Pheloung PC, Williams PA, Halloy SR (1999) A weed risk assessment model for use as a biosecurity tool evaluating plant introductions. J Environ Manag 57:239–251. doi: 10.1006/jema.1999.0297 CrossRefGoogle Scholar
  41. Pyšek P (2001) Past and future of predictions in plant invasions: a field test by time. Divers Distrib 7:145–151. doi: 10.1046/j.1366-9516.2001.00107.x CrossRefGoogle Scholar
  42. Pyšek P, Jarosík V (2005) Residence time determines the distribution of alien plants. In: Inderjit (ed) Invasive plants: ecological and agricultural aspects. Birkhauser Verlag, SwitzerlandGoogle Scholar
  43. Pyšek P, Richardson DM, Rejmánek M, Webster GL, Williamson M, Kirschner J (2004) Alien plants in checklists and floras: towards better communication between taxonomists and ecologists. Taxon 53:131–143. doi: 10.2307/4135498 CrossRefGoogle Scholar
  44. R Development Core Team (2006) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. Available from
  45. Reichard SH, Hamilton CW (1997) Predicting invasions of woody plants introduced into North America. Conserv Biol 11:193–203. doi: 10.1046/j.1523-1739.1997.95473.x CrossRefGoogle Scholar
  46. Rejmánek M (2000) Invasive plants: approaches and predictions. Austral Ecol 25:497–506Google Scholar
  47. Rejmánek M, Richardson DM (1996) What attributes make some plant species more invasive? Ecology 77:1655–1661. doi: 10.2307/2265768 CrossRefGoogle Scholar
  48. Richardson DM, Pyšek P (2006) Plant invasions: merging the concepts of species invasiveness and community invasibility. Prog Phys Geogr 30:409–431. doi: 10.1191/0309133306pp490pr CrossRefGoogle Scholar
  49. Richardson DM, Thuiller W (2007) Home away from home—objective mapping of high-risk source areas for plant introductions. Divers Distrib 13:299–312CrossRefGoogle Scholar
  50. Richardson DM, Pyšek P, Rejmánek M, Barbour MG, Panetta FD, West CJ (2000a) Naturalization and invasion of alien plants: concepts and definitions. Divers Distrib 6:93–107. doi: 10.1046/j.1472-4642.2000.00083.x CrossRefGoogle Scholar
  51. Richardson DM, Allsopp N, D’Antonio CM, Milton SJ, Rejmánek M (2000b) Plant invasions—the role of mutualisms. Biol Rev Camb Philos Soc 75:65–93. doi: 10.1017/S0006323199005435 CrossRefPubMedGoogle Scholar
  52. Sanz-Elorza M, Dana ED, Sobrino E (2004) Atlas de las plantas alóctonas invasoras de España. Dirección General para la Biodiversidad, MadridGoogle Scholar
  53. Smith CS, Lonsdale WM, Fortune J (1999) When to ignore advice: invasion predictions and decision theory. Biol Invasions 1:89–96. doi: 10.1023/A:1010091918466 CrossRefGoogle Scholar
  54. Sol D, Vilà M, Kühn I (2008) The comparitive analysis of historical alien introductions. Biol Invasions 10:1119–1129. doi: 10.1007/s10530-007-9189-7 CrossRefGoogle Scholar
  55. Thuiller W, Richardson DM, Pyšek P, Midgley GF, Hughes GO, Rouget M (2005) Niche-based modelling as a tool for predicting the risk of alien plant invasions at a global scale. Glob Chang Biol 11:2234–2250CrossRefGoogle Scholar
  56. Thuiller W, Richardson DM, Rouget M, Proches S, Wilson JRU (2006) Interactions between environment, species traits, and human uses describe patterns of plant invasions. Ecology 87:1755–1769. doi: 10.1890/0012-9658(2006)87[1755:IBESTA]2.0.CO;2 CrossRefPubMedGoogle Scholar
  57. Union of Concerned Scientists (2001) The science of invasive species. An information update by the Union of Concerned Scientists, Accessed 27 July 2006
  58. Venables WN, Ripley BD (2002) Modern applied statistics with S, 4th edn. Springer, New YorkGoogle Scholar
  59. Vilà M, Weber E, D’Antonio CM (2000) Conservation implications of invasion by plant hybridization. Biol Invasions 2:207–217. doi: 10.1023/A:1010003603310 CrossRefGoogle Scholar
  60. Westbrooks R (1981) Introduction of foreign noxious plants into the United States. Weeds Today 14:16–17Google Scholar
  61. Williamson M (1996) Biological invasions. Chapman and Hall, LondonGoogle Scholar
  62. Wittenberg R, Cock MJW (eds) (2001) Invasive Alien species: a toolkit of best prevention and management practices. CAB International, WallingfordGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Núria Gassó
    • 1
  • Corina Basnou
    • 1
  • Montserrat Vilà
    • 2
  1. 1.CREAF (Centre for Ecological Research and Forestry Applications)Universitat Autònoma de BarcelonaBellaterraSpain
  2. 2.Estación Biológica de Doñana-Centro Superior de Investigaciones Científicas (EDB-CSIC)SevillaSpain

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