Hostname: page-component-77c89778f8-m8s7h Total loading time: 0 Render date: 2024-07-17T08:59:34.581Z Has data issue: false hasContentIssue false
  • English
  • Français

Distributional Changes and Range Predictions of Downy Brome (Bromus tectorum) in Rocky Mountain National Park

Published online by Cambridge University Press:  20 January 2017

James E. Bromberg ,
Sunil Kumar ,
Cynthia S. Brown  and
Thomas J. Stohlgren
James E. Bromberg*
Affiliation:
Bioagricultural Science and Pest Management Department, Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO 80523
Sunil Kumar
Affiliation:
Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO 80523
Cynthia S. Brown
Affiliation:
Bioagricultural Science and Pest Management Department, Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO 80523
Thomas J. Stohlgren
Affiliation:
Fort Collins Science Center, U.S. Geological Survey, 2150 Building C, Fort Collins, CO 80526
*
Corresponding author's E-mail: jebromberg@yahoo.com
Get access Rights & Permissions [Opens in a new window]

Abstract

Downy brome (Bromus tectorum L.), an invasive winter annual grass, may be increasing in extent and abundance at high elevations in the western United States. This would pose a great threat to high-elevation plant communities and resources. However, data to track this species in high-elevation environments are limited. To address changes in the distribution and abundance of downy brome and the factors most associated with its occurrence, we used field sampling and statistical methods, and niche modeling. In 2007, we resampled plots from two vegetation surveys in Rocky Mountain National Park for presence and cover of downy brome. One survey was established in 1993 and had been resampled in 1999. The other survey was established in 1996 and had not been resampled until our study. Although not all comparisons between years demonstrated significant changes in downy brome abundance, its mean cover increased nearly fivefold from 1993 (0.7%) to 2007 (3.6%) in one of the two vegetation surveys (P = 0.06). Although the average cover of downy brome within the second survey appeared to be increasing from 1996 to 2007, this slight change from 0.5% to 1.2% was not statistically significant (P = 0.24). Downy brome was present in 50% more plots in 1999 than in 1993 (P = 0.02) in the first survey. In the second survey, downy brome was present in 30% more plots in 2007 than in 1996 (P = 0.08). Maxent, a species–environmental matching model, was generally able to predict occurrences of downy brome, as new locations were in the ranges predicted by earlier generated models. The model found that distance to roads, elevation, and vegetation community influenced the predictions most. The strong response of downy brome to interannual environmental variability makes detecting change challenging, especially with small sample sizes. However, our results suggest that the area in which downy brome occurs is likely increasing in Rocky Mountain National Park through increased frequency and cover. Field surveys along with predictive modeling will be vital in directing efforts to manage this highly invasive species.

Keywords

Downy brome, Bromus tectorum L.Cheatgrassinvasive species spreadMaxentniche modelingrange expansion
Type
Research
Information
Invasive Plant Science and Management , Volume 4 , Issue 2 , April 2011 , pp. 173 - 182
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

Barnett, D. T. and Stohlgren, T. J. 2003. A nested-intensity design for surveying plant diversity. Biodivers. Conserv 12:255–278.CrossRefGoogle Scholar
Baron, J. S., Rueth, H. M., Wolfe, A. M., Nydick, K. R., Allstott, E. J., Minear, T., and Moraska, B. 2000. Ecosystem responses to nitrogen deposition in the Colorado front range. Ecosystems 3:352–368.Google Scholar
Beatley, J. C. 1966. Ecological status of introduced brome grasses (Bromus spp.) in desert vegetation of southern Nevada. Ecology 47:548–554.Google Scholar
Beckstead, J. and Augspurger, C. K. 2004. An experimental test of resistance to cheatgrass invasion: limiting resources at different life stages. Biol. Invasions 6:417–432.Google Scholar
Booth, M. S., Caldwell, M. M., and Stark, J. M. 2003. Overlapping resource use in three Great Basin species: implications for community invisibility and vegetation dynamics. J. Ecol 91:36–48.Google Scholar
Bradford, J. B. and Lauenroth, W. K. 2006. Controls over the invasion of Bromus tectorum: the importance of climate, soil, disturbance and seed availability. J. Veg. Sci 17:693–704.Google Scholar
Bradley, B. A. 2009. Regional analysis of the impacts of climate change on cheatgrass invasion shows potential risk and opportunity. Global Change Biol 15:196–208.Google Scholar
Brooks, M. L. 2003. Effects of increased soil nitrogen on the dominance of alien annual plants in the Mojave Desert. J. Appl. Ecol 40:344–353.CrossRefGoogle Scholar
Chambers, J. C., Roundy, B. A., Blank, R. R., Meyer, S. E., and Whittaker, A. 2007. What makes Great Basin sagebrush ecosystems invasible by Bromus tectorum? Ecol. Monogr 77:117–145.Google Scholar
Daubenmire, R. 1968. Soil moisture in relation to vegetation distribution in the mountains of northern Idaho. Ecology 49:431–438.Google Scholar
Dietz, H. and Edwards, P. J. 2006. Recognition that causal processes change during plant invasion helps explain conflicts in evidence. Ecology 87:1359–1367.Google Scholar
Dukes, J. S. and Mooney, H. A. 1999. Does global change increase the success of biological invaders? Trends Ecol. Evol 14:135–139.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.CrossRefGoogle Scholar
Elith, J., Leathwick, J. R., and Hastie, T. 2008. A working guide to boosted regression trees. J. Anim. Ecol 77:802–813.CrossRefGoogle ScholarPubMed
Elzinga, C. L., Salzer, D. W., and Willoughby, J. W. 1998. Measuring and monitoring plant populations. BLM Tech. Reference 1730–1. National Business Center, Denver, CO. 477 p.Google Scholar
Evangelista, P. H., Kumar, S., Stohlgren, T. J., Jarnevich, C. S., Crall, A. W., Norman, J. B. III, and Barnett, D. T. 2008. Modelling invasion for a habitat generalist and a specialist plant species. Divers. Distrib 14:808–817.Google Scholar
Evans, R. D., Rimer, R., Sperry, L., and Belnap, J. 2001. Exotic plant invasion alters nitrogen dynamics in an arid grassland. Ecol. Appl 11:1301–1310.Google Scholar
Fenn, M. E., Baron, J. S., Allen, E. B., et al. 2003. Ecological effects of nitrogen deposition in the western United States. BioScience 53:404–420.Google Scholar
Friedman, J. H., Hastie, T., and Tibshirani, R. 2000. Additive logistic regression: a statistical view of boosting. Anal. Stat 28:337–407.Google Scholar
Getz, H. L. and Baker, W. L. 2008. Initial invasion of cheatgrass (Bromus tectorum) into burned pinon–juniper woodlands in western Colorado. Am. Midl. Nat 159:489–497.CrossRefGoogle Scholar
Harris, G. A. 1967. Some competitive effects between Agropyron spicatum and Bromus tectorum . Ecol. Monogr 37:89–111.Google Scholar
Hastie, T., Tibshirani, R., and Friedman, J. H. 2001. The Elements of Statistical Learning: Data Mining, Inference and Prediction. New York, NY Springer-Verlag. 552 p.Google Scholar
Hobbs, R. J. and Mooney, H. A. 1986. Community changes following shrub invasion of grassland. Oecologia 70:508–513.Google Scholar
Humphrey, L. D. and Schupp, E. W. 2004. Competition as a barrier to establishment of a native perennial grass (Elymus elymoides) in alien annual grass (Bromus tectorum) communities. J. Arid Environ 58:405–422.CrossRefGoogle Scholar
Hunter, R. 1991. Bromus invasions on the Nevada test site: present status of B. rubens and B. tectorum with notes on their relationship to disturbance and altitude. Great Basin Nat 51:176–182.Google Scholar
[IPCC] Intergovernmental Panel on Climate Change. 2001. Climate Change 2001: The Scientific Basis. New York, NY University Press. 94 p.Google Scholar
Jenkins, M. J., Hebertson, E., Page, W., and Jorgensen, C. A. 2008. Bark beetles, fuels, fires and implications for forest management in the intermountain west. Forest Ecol. Manag 254:16–34.CrossRefGoogle Scholar
Kao, R. H., Brown, C. S., and Hufbauer, R. A. 2008. High phenotypic and molecular variation in downy brome (Bromus tectorum). Invasive Plant Sci. Manag 1:216–225.Google Scholar
Knapp, P. A. 1996. Cheatgrass (Bromus tectorum L.) dominance in the Great Basin Desert: history, persistence, and influences to human activities. Global Environ. Change 6:37–52.Google Scholar
Kumar, S., Spaulding, S. A., Stohlgren, T. J., Hermann, K. A., Schmidt, T. S., and Bahls, L. L. 2009. Predicting habitat distribution for freshwater diatom Didymosphenia geminata in the continental United States. Front. Ecol. Environ 7:415–420.Google Scholar
Kumar, S. and Stohlgren, T. J. 2009. Maxent modeling for predicting suitable habitat for threatened and endangered tree Canacomyrica monticola in New Caledonia. J. Ecol. Nat. Environ 1:94–98.Google Scholar
Kumar, S., Stohlgren, T. J., and Chong, G. W. 2006. Spatial heterogeneity influences native and nonnative plant species richness. Ecology 87:3186–3199.Google Scholar
Lowe, P. N., Lauenroth, W. K., and Burke, I. C. 2003. Effects of nitrogen availability on competition between Bromus tectorum and Bouteloua gracilis . Plant Ecol 167:247–254.Google Scholar
Mack, R. N. 1981. Invasion of Bromus tectorum L. into western North America: an ecological chronicle. Agro-Ecosystems 7:145–165.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
Mack, R. N. and D'Antonio, C. M. 1998. Impacts of biological invasions on disturbance regimes. Trends Evol. Ecol 13:195–198.Google Scholar
Mack, R. N. and Pyke, D. A. 1983. The demography of Bromus tectorum: variation in time and space. J. Ecol 71:69–93.Google Scholar
McCarty, J. P. 2001. Ecological consequences of recent climate change. Conserv. Biol 15:320–331.Google Scholar
McLendon, T. and Redente, E. F. 1993. Vegetation Restoration Research, Rocky Mountain National Park: Anthropic Disturbance, Patterns of Secondary Succession, and Alternative Sources of Fill Material. National Park Service, Denver, CO. No.1268-1-9002. 45 p.Google Scholar
Melgoza, G., Nowak, R. S., and Tausch, R. J. 1990. Soil water exploitation after fire: competition between Bromus tectorum (cheatgrass) and two native species. Oecologia 83:7–13.Google Scholar
Morrow, L. A. and Stahlman, P. W. 1984. The history and distribution of downy brome (Bromus tectorum) in North America. Weed Science 32:2–6.Google Scholar
Mortensen, D. A., Rauschert, E. S. J., Nord, A. N., and Jones, B. P. 2009. Forest roads facilitate the spread of invasive plants. Invasive Plant Sci. Manag 2:191–199.CrossRefGoogle Scholar
Ortega-Huerta, M. A. and Peterson, A. T. 2008. Modeling ecological niches and predicting geographic distributions: a test of six presence-only methods. Rev. Mex. Biodivers 79:205–216.Google Scholar
Ostertag, R. and Verville, J. H. 2002. Fertilization with nitrogen and phosphorus increases abundance of non-native species in Hawaiian montane forests. Plant Ecol 162:77–90.Google Scholar
Pauchard, A., Kueffer, C., Dietz, H., et al. 2009. Ain't no mountain high enough: plant invasions reaching new elevations. Front. Ecol. Environ 7:479–486.Google Scholar
Pearson, R. G., Raxworthy, C. J., Nakamura, M., and Peterson, A. T. 2007. Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar. J. Biogeogr 34:102–117.Google Scholar
Peterson, A. T. 2003. Predicting the geography of species invasions via ecological niche modeling. Q. Rev. Biol 78:419–433.Google Scholar
Phillips, S. J., Anderson, R. P., and Schapire, R. E. 2006. Maximum entropy modeling of species geographic distributions. Ecol. Model 190:231–259.Google Scholar
Phillips, S. J., Dudik, M., Elith, J., Graham, C. H., Lehman, A., Leathwick, J., and Ferrier, S. 2009. Sample selection bias and presence-only distribution models: implication for background and pseudo-absence data. Ecol. Appl 19:181–197.Google Scholar
Pierson, E. A. and Mack, R. N. 1990. The population biology of Bromus tectorum in forests—effects of disturbance, grazing, and litter on seedling establishment and reproduction. Oecologia 84:526–533.Google Scholar
Pierson, E. A., Mack, R. N., and Black, R. A. 1990. The effect of shading on photosynthesis, growth, and regrowth following defoliation for Bromus tectorum. Oecologia 84:534–543.Google Scholar
Ramakrishnan, A. P., Meyer, S. E., Fairbanks, D. J., and Coleman, C. E. 2006. Ecological significance of microsatellite variation in western North American populations of Bromus tectorum . Plant Species Biol.l 21:61–73.Google Scholar
Randin, C. F., Dirnbock, T., Dullinger, S., Zimmermann, N. E., Zappa, M., and Guisan, A. 2006. Are niche-based species distribution models transferable in space? J. Biogeogr 33:1689–1703.Google Scholar
Rew, L. J., Maxwell, B. D., and Aspinall, R. 2005. Predicting the occurrence of nonindigenous species using environmental and remotely sensed data. Weed Sci 53:236–241.Google Scholar
Rice, K. J. and Mack, R. N. 1991a. Ecological genetics of Bromus tectorum: i. A hierarchical analysis of phenotypic variation. Oecologia 88:77–83.Google Scholar
Rice, K. J. and Mack, R. N. 1991b. Ecological genetics of Bromus tectorum: iii. The demography of reciprocally sown populations. Oecologia 88:91–101.Google Scholar
Richardson, D. M., Allsopp, N., D'Antonio, C. M., Milton, S. J., and Rejmanek, M. 2000. Plant invasions—the role of mutualisms. Biol. Rev 77:65–93.Google Scholar
Rummell, R. S. 1946. Some effects of competition from cheatgrass brome on crested wheatgrass and bluestem wheatgrass. Ecology 27:159–167.Google Scholar
Sala, O. E., Chapin, F. S. III, Armesto, J. J., et al. 2000. Global biodiversity scenarios for the year 2100. Science 287:1770–1774.Google Scholar
Sasek, T. W. and Strain, B. R. 1988. Effects of carbon dioxide enrichment on the growth and morphology of kudzu (Pueraria lobata). Weed Sci 36:28–36.Google Scholar
Sasek, T. W. and Strain, B. R. 1991. Effects of carbon dioxide enrichment on the growth and morphology of a native and an introduced honeysuckle vine. Am. J. Bot 78:69–75.Google Scholar
Sax, D. F., Stachowicz, J. J., Brown, J. H., et al. 2007. Ecological and evolutionary insights from species invasions. Trends Ecol. Evol 22:465–471.Google Scholar
Smith, S. D., Huxman, T. E., Zitzer, S. F., Charlet, T. N., Housman, D. C., Coleman, J. S., Fenstermaker, L. K., Seemann, J. R., and Nowak, R. S. 2000. Elevated CO2 increases productivity and invasive species success in an arid ecosystem. Nature 408:79–82.Google Scholar
Smith, S. D., Strain, B. R., and Sharkey, T. D. 1987. Effects of CO2 enrichment on four Great Basin grasses. Funct. Ecol 1:139–143.CrossRefGoogle Scholar
Sperry, L. J., Belnap, J., and Evans, R. D. 2006. Bromus tectorum invasion alters nitrogen dynamics in an undisturbed arid grassland ecosystem. Ecology 87:603–615.Google Scholar
Stockwell, D. and Nobel, I. R. 1992. Induction of sets of rules from animal distribution data: a robust and informative method of data analysis. Math. Comput. Simulation 33:385–390.Google Scholar
Stockwell, D. and Peters, D. 1999. The GARP modeling system: problems and solutions to automated spatial prediction. Int. J. Geogr. Inf. Sci 13:143–158.Google Scholar
Stohlgren, T. J., Crosier, C., Chong, G. W., et al. 2005. Life-history habitat matching in invading non-native plant species. Plant Soil 277:7–18.CrossRefGoogle Scholar
Stohlgren, T. J., Falkner, M. B., and Schell, L. D. 1995. A modified-Whittaker nested vegetation sampling method. Vegetatio 117:113–121.Google Scholar
Stohlgren, T. J., Owen, A. J., and Lee, M. 2000. Monitoring shifts in plant diversity in response to climate change: a method for landscapes. Biodivers. Conserv 9:65–86.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
Thomas, C. D., Cameron, A., Green, R. E., et al. 2004. Extinction risk from climate change. Nature 427:145–148.Google Scholar
Upadhyaya, M. K., Turkington, R., and McIlvride, D. 1986. The biology of Canadian weeds. 75. Bromus tectorum L. Can. J. Plant Sci 66:689–709.Google Scholar
Walther, G., Post, E., Convey, P., Menzel, A., Parmesan, C., Beebee, T. J. C., Fromentin, J., Hoegh-Gulberg, O., and Bairlein, F. 2002. Ecological responses to recent climate change. Nature 416:389–395.Google Scholar
Williams, M. W., Baron, J. S., Caine, N., Sommerfeld, R., and Sanford, R. Jr. 1996. Nitrogen saturation in the Rocky Mountains. Environ. Sci. Technol 30:640–646.Google Scholar
Wisz, M. S., Hijmans, R. J., Li, J., Peterson, A. T., Graham, C. H., and Guisan, A. NCEAS Predicting Species Distributions Working Group 2008. Effect of sample size on the performance of species distribution models. Divers. Distrib 14:763–773.Google Scholar
Yensen, D. L. 1981. The 1900 invasion of alien plants into southern Idaho. Great Basin Nat 41:176–183.Google Scholar
Young, J. 2000. Bromus tectorum . Pages 76–80. In Bossard, C. C., Randall, J. M., and Hoshovsky, M. C. Invasive Plants of California's Wildlands. Berkeley, CA University of California Press.Google Scholar
Zadeh, H. 2001. Successional patterns and rates of recovery of disturbed sites in Rocky Mountain National Park, Colorado. M.S. thesis. Fort Collins, CO Colorado State University. 63 p.Google Scholar