Biological Invasions

, Volume 13, Issue 1, pp 153–163

Challenges of predicting the potential distribution of a slow-spreading invader: a habitat suitability map for an invasive riparian tree

Original Paper


Understanding the potential spread of invasive species is essential for land managers to prevent their establishment and restore impacted habitat. Habitat suitability modeling provides a tool for researchers and managers to understand the potential extent of invasive species spread. Our goal was to use habitat suitability modeling to map potential habitat of the riparian plant invader, Russian olive (Elaeagnus angustifolia). Russian olive has invaded riparian habitat across North America and is continuing to expand its range. We compiled 11 disparate datasets for Russian olive presence locations (n = 1,051 points and 139 polygons) in the western US and used Maximum entropy (Maxent) modeling to develop two habitat suitability maps for Russian olive in the western United States: one with coarse-scale water data and one with fine-scale water data. Our models were able to accurately predict current suitable Russian olive habitat (Coarse model: training AUC = 0.938, test AUC = 0.907; Fine model: training AUC = 0.923, test AUC = 0.885). Distance to water was the most important predictor for Russian olive presence in our coarse-scale water model, but it was only the fifth most important variable in the fine-scale model, suggesting that when water bodies are considered on a fine scale, Russian olive does not necessarily rely on water. Our model predicted that Russian olive has suitable habitat further west from its current distribution, expanding into the west coast and central North America. Our methodology proves useful for identifying potential future areas of invasion. Model results may be influenced by locations of cultivated individuals and sampling bias. Further study is needed to examine the potential for Russian olive to invade beyond its current range. Habitat suitability modeling provides an essential tool for enhancing our understanding of invasive species spread.


Biological invasions Exotic plant species Habitat suitability model Maxent Riparian Russian olive 


  1. Araujo MB, Luoto M (2007) The importance of biotic interactions for modelling species distributions under climate change. Glob Ecol Biogeogr 16:743–753CrossRefGoogle Scholar
  2. Billerbeck R (2003) Colorado state parks weed data. Colorado State ParksGoogle Scholar
  3. Bradley BA, Oppenheimer M and Wilcove DS (2009) Climate change and plant invasions: restoration opportunities ahead? Global Change BiologyGoogle Scholar
  4. Bradley BA, Blumenthal DM, Wilcove DS and Ziska LH (2010) Predicting plant invasions in an era of global change. Tree (in press)Google Scholar
  5. Cooper DJ, Merritt DM, Andersen DC, Chimner RA (1999) Factors controlling the establishment of Fremont cottonwood seedlings on the upper Green River, USA. Reg Rivers Res Manage 15:419–440CrossRefGoogle Scholar
  6. Crosier CS (2004) Synergistic methods to generate predictive models at large spatial extents and fine resolution, Graduate Degree Program in Ecology. Colorado State University, Fort Collins, p 119Google Scholar
  7. DAYMET (2006) Climatological summaries for the conterminous United States, 1980–1997. Daily surface weather and climatological summaries (DAYMET;
  8. DeCant JP (2008) Russian Olive, Elaeagnus Angustifolia, alters patterns in soil nitrogen pools along The Rio Grande River, New Mexico, USA. Wetlands 28:896–904CrossRefGoogle Scholar
  9. Evangelista PH, Kumar S, Stohlgren TJ, Jarnevich CS, Crall AW, Norman JB, Barnett DT (2008) Modelling invasion for a habitat generalist and a specialist plant species. Divers Distrib 14:808–817CrossRefGoogle Scholar
  10. Freeman EA, Moisen GG (2008) A comparison of the performance of threshold criteria for binary classification in terms of predicted prevalence and kappa. Ecol Modell 217:48–58CrossRefGoogle Scholar
  11. Friedman JM, Auble GT, Shafroth PB, Scott ML, Merigliano MF, Preehling MD, Griffin EK (2005) Dominance of non-native riparian trees in western USA. Biol Invasions 7:747–751CrossRefGoogle Scholar
  12. Gochis DJ, Brito-Castillo L, Shuttleworth WJ (2006) Hydroclimatology of the North American Monsoon region in northwest Mexico. J Hydrol 316:53–70CrossRefGoogle Scholar
  13. Heikkinen RK, Luoto M, Araujo MB, Thuiller W, Sykes MT (2006) Methods and uncertainties in bioclimatic envelope modelling under climate change. Prog Phys Geogr 30:751–777CrossRefGoogle Scholar
  14. Hijmans RJ (2006) MkBCvars.AML version 2.3.
  15. Hirzel AH, Le Lay G, Helfer V, Randin C, Guisan A (2006) Evaluating the ability of habitat suitability models to predict species presences. Ecol Modell 199:142–152CrossRefGoogle Scholar
  16. Hood WG, Naiman RJ (2000) Vulnerability of riparian zones to invasion by exotic vascular plants. Plant Ecol 148:105–114CrossRefGoogle Scholar
  17. HR2720 (2006) Salt Cedar and Russian Olive Control Demonstration Act. United States CongressGoogle Scholar
  18. Jarnevich CS, Stohlgren TJ, Barnett D, Kartesz J (2006) Filling in the gaps: modelling native species richness and invasions using spatially incomplete data. Divers Distrib 12:511–520CrossRefGoogle Scholar
  19. Jimenez-Valverde A, Lobo JM (2007) Threshold criteria for conversion of probability of species presence to either-or presence-absence. Acta Oecologica Int J Ecol 31:361–369CrossRefGoogle Scholar
  20. Katz GL, Shafroth PB (2003) Biology, ecology and management of Elaeagnus angustifolia L. (Russian olive) in western North America. Wetlands 23:763–777CrossRefGoogle Scholar
  21. Katz GL, Friedman JM, Beatty SW (2005) Delayed effects of flood control on a flood-dependent riparian forest. Ecol Appl 15:1019–1035CrossRefGoogle Scholar
  22. Lesica P, Miles S (1999) Russian olive invasion into cottonwood forests along a regulated river in northcentral Montana. Canadian Journal of Botany—Revue Canadienne De Botanique 77:1077–1083Google Scholar
  23. Liu CR, Berry PM, Dawson TP, Pearson RG (2005) Selecting thresholds of occurrence in the prediction of species distributions. Ecography 28:385–393CrossRefGoogle Scholar
  24. Naiman RJ, Decamps H, Pollock M (1993) The role of Riparian corridors in maintaining regional biodiversity. Ecol Appl 3:209–212CrossRefGoogle Scholar
  25. NPS (2003) Data and Information: Data Clearinghouse. National Park ServiceGoogle Scholar
  26. Phillips SJ (2008) Transferability, sample selection bias and background data in presence-only modelling: a response to Peterson et al. (2007). Ecography 31:272–278Google Scholar
  27. Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecol Modell 190:231–259CrossRefGoogle Scholar
  28. Phillips SJ, Dudik M, Elith J, Graham CH, Lehmann A, Leathwick J, Ferrier S (2009) Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data. Ecol Appl 19:181–197CrossRefPubMedGoogle Scholar
  29. Quinn JF, Thorne J (2007) California invasive plant dataGoogle Scholar
  30. Reynolds LV, Cooper DJ (2010) Environmental tolerance of an invasive riparian tree and its potential for continued spread in the Southwestern US. J Veg Sci 1–11. doi:10.1111/j.1654-1103.2010.01179.x
  31. Richard SH, White P (2001) Horticulture as a pathway of invasive plant introductions in the United States. Bioscience 51:103–113CrossRefGoogle Scholar
  32. Richardson DM, Holmes PM, Esler KJ, Galatowitsch SM, Stromberg JC, Kirkman SP, Pysek P, Hobbs RJ (2007) Riparian vegetation: degradation, alien plant invasions, and restoration prospects. Divers Distrib 13:126–139CrossRefGoogle Scholar
  33. Sabo JL, Sponseller R, Dixon M, Gade K, Harms T, Heffernan J, Jani A, Katz G, Soykan C, Watts J, Welter A (2005) Riparian zones increase regional species richness by harboring different, not more, species. Ecology 86:56–62CrossRefGoogle Scholar
  34. Shafroth PB, Auble GT, Scott ML (1995) Germination and establishment of the native plains cottonwood (Populus-Deltoides Marshall Subsp Monilifera) and the exotic Russian-olive (Elaeagnus-Angustifolia L). Conserv Biol 9:1169–1175CrossRefGoogle Scholar
  35. Shafroth PB, Beauchamp VB, Briggs MK, Lair K, Scott ML, Sher AA (2008) Planning riparian restoration in the context of Tamarix control in western North America. Restor Ecol 16:97–112CrossRefGoogle Scholar
  36. Stohlgren TJ, Bull KA, Otsuki Y, Villa CA, Lee M (1998) Riparian zones as havens for exotic plant species in the central grasslands. Plant Ecol 138:113–125CrossRefGoogle Scholar
  37. Stohlgren TJ, Schell LD, Bull KA, Otsuki Y, Newman G, Bashkin M, Son Y, Binkley D, Chong GW, Kalkhan MA (1999) Exotic plant species invade hot spots of native plant diversity. Ecol Monogr 69:25–46CrossRefGoogle Scholar
  38. Strayer DL, Eviner VT, Jeschke JM, Pace ML (2006) Understanding the long-term effects of species invasions. Trends Ecol Evol 21:645CrossRefPubMedGoogle Scholar
  39. Swets JA (1988) Measuring the accuracy of diagnostic systems. Science 240:1285–1293CrossRefPubMedGoogle Scholar
  40. Thomas K, Guertin P (2007) Southwest non-native invasive plant database (SWEMP07). U.S. Geological Survey, Southwest Biological Science Center (USGS-SBSC)Google Scholar
  41. USDA (2009) The PLANTS Database, National Plant Data Center, NRCS onGoogle Scholar
  42. Utah BLM (2006) Utah noxious weeds. Bureau of Land ManagementGoogle Scholar
  43. Vieira J (2003) Royal Gorge area weed mapping data. Bureau of Land ManagementGoogle Scholar
  44. Wilson JRU, Richardson DM, Rouget M, Proches S, Amis MA, Henderson L, Thuiller W (2007) Residence time and potential range: crucial considerations in modelling plant invasions. Divers Distrib 13:11–22CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  1. 1.US Geological Survey, Fort Collins Science CenterFort CollinsUSA
  2. 2.Department of Forest, Rangeland and Watershed Stewardship and Graduate Degree Program in EcologyColorado State UniversityFort CollinsUSA

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