Hostname: page-component-cd9895bd7-7cvxr Total loading time: 0 Render date: 2024-12-25T18:39:06.541Z Has data issue: false hasContentIssue false

Biophysical Correlates with the Distribution of the Invasive Annual Red Brome (Bromus rubens) on a Mojave Desert Landscape

Published online by Cambridge University Press:  20 January 2017

Scott R. Abella*
Affiliation:
Department of Environmental and Occupational Health, University of Nevada, Las Vegas, NV 89154-3064
Teague M. Embrey
Affiliation:
Department of Environmental and Occupational Health, University of Nevada, Las Vegas, NV 89154-3064
Sarah M. Schmid
Affiliation:
Department of Environmental and Occupational Health, University of Nevada, Las Vegas, NV 89154-3064
Kathryn A. Prengaman
Affiliation:
Department of Environmental and Occupational Health, University of Nevada, Las Vegas, NV 89154-3064
*
Corresponding author's E-mail: scott.abella@unlv.edu

Abstract

Because of its ability to transform ecosystems by increasing the prevalence of fire, the invasive annual red brome is a priority exotic species for management in arid lands of the southwestern United States. By sampling red brome presence and 97 environmental (climatic, topographic, and soil) and native vegetation (e.g., perennial species richness) variables on 126 sites, we assessed biophysical correlates with red brome distribution on a 755,000-ha (1.9 million ac) Mojave Desert landscape. Brome occupied 55 of 126 (44%) 0.09-ha plots. The simplest models (i.e., those containing the fewest or most easily obtained variables) in multivariate (classification trees and nonparametric multiplicative regression) and univariate (χ2) models often portrayed red brome distribution as well, or nearly as well, as more complicated models containing more variables harder to obtain. The models varied, however, in their abilities for describing brome presence compared with absence. For example, a simple classification tree using only elevation, soil great group, parent material, and vegetation type improved estimates of brome presence for 55% of sites, absences for 87%, and overall for 73% of sites compared with a naïve model containing the observed frequency of brome in the data. Conversely, a more complicated model, including soil boron and sulfur, performed better for presences (96%) than for absences (73%; 83% overall). Results also showed variable support for two general postulates in invasive species science. Red brome distribution was not correlated with soil N, which is inconsistent with the supposition that nutrient-rich soils are more prone to invasion. Brome was correlated with native perennial species richness to support the postulate that exotic species abundance is correlated with species-rich habitats, but the correlation was weak (r = 0.38) and similar in strength to correlations with many other environmental variables. On this relatively low-elevation landscape, the areas currently most invaded by red brome include the higher elevations (> 777 m [2,549 ft]), limestone–sandstone soils, and burrobush and mixed perennial communities. Areas least inhabited by brome are the lowest elevations (< 491 m), gypsum soils, and creosotebush and saltbush communities.

Type
Research
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

Abella, S. R., Craig, D. J., Chiquoine, L. P., Prengaman, K. A., Schmid, S. M., and Embrey, T. M. 2011. Relationships of native desert plants with red brome (Bromus rubens): toward identifying invasion-reducing species. Invasive Plant Sci. Manag. 4:115124.Google Scholar
Abella, S. R., Spencer, J. E., Hoines, J., and Nazarchyk, C. 2009. Assessing an exotic plant surveying program in the Mojave Desert, Clark County, Nevada, USA. Environ. Monit. Assess. 151:221230.Google Scholar
Abella, S. R., Prengaman, K. A., Embrey, T. M., Schmid, S. M., Newton, A. C., and Merkler, D. J. 2012. A hierarchical analysis of vegetation on a Mojave Desert landscape, USA. J. Arid Environ. 78:135143.Google Scholar
Arim, M., Abades, S. R., Neill, P. E., Lima, M., and Marquet, P. A. 2006. Spread dynamics of invasive species. Proc. Natl. Acad. Sci. U. S. A. 103:374378.Google Scholar
Bashkin, M., Stohlgren, T. J., Otsuki, Y., Lee, M., Evangelista, P., and Belnap, J. 2003. Soil characteristics and plant exotic species invasions in the Grand Staircase-Escalante National Monument, Utah, USA. Appl. Soil Ecol. 22:6777.Google Scholar
Beatley, J. C. 1966. Ecological status of introduced brome grasses (Bromus spp.) in desert vegetation of southern Nevada. Ecology 47:548554.Google Scholar
Beatley, J. C. 1974. Phenological events and their environmental triggers in Mojave Desert ecosystems. Ecology 55:856863.Google Scholar
Beers, T. W., Dress, P. E., and Wensel, L. C. 1966. Aspect transformation in site productivity research. J. Forestry 64:691692.Google Scholar
Bowers, M. A. 1987. Precipitation and the relative abundances of desert winter annuals: a 6-year study in the northern Mojave Desert. J. Arid Environ. 12:141149.Google Scholar
Bradley, B. A. and Mustard, J. F. 2006. Characterizing the landscape dynamics of an invasive plant and risk of invasion using remote sensing. Ecol. Appl. 16:11321147.Google Scholar
Breiman, L., Friedman, J. H., Olshen, R. A., and Stone, C. J. 1984. Classification and Regression Trees. Belmont, CA Wadsworth. 358 p.Google Scholar
Brooks, M. L. 1999. Habitat invasibility and dominance by alien annual plants in the western Mojave Desert. Biol. Invasions 1:325337.Google Scholar
Brooks, M. L. 2000. Bromus madritensis ssp. rubens (L.) Husnot. Page 7276 in Bossard, C. C., Randall, J. M., and Hoshovsky, M. C., eds. Invasive Plants of California's Wildlands. Berkeley, CA University of California Press.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. 40:344353.Google Scholar
Brooks, M. L. 2009. Spatial and temporal distribution of non-native plants in upland areas of the Mojave Desert. Page 101124 in Webb, R. H., Fenstermaker, L. F., Heaton, J. S., Hughson, D. L., McDonald, E. V., and Miller, D. M., eds. The Mojave Desert: Ecosystem Processes and Sustainability. Reno, NV University of Nevada Press.Google Scholar
Brooks, M. L. and Matchett, J. R. 2006. Spatial and temporal patterns of wildfires in the Mojave Desert, 1980–2004. J. Arid Environ. 67:148164.Google Scholar
Brooks, M. L. and Berry, K. H. 2006. Dominance and environmental correlates of alien annual plants in the Mojave Desert, USA. J. Arid Environ. 67:100124.Google Scholar
Brooks, M. L. and Lair, B. M. 2009. Ecological effects of vehicular routes in a desert ecosystem. Page 168195 in Webb, R. H., Fenstermaker, L. F., Heaton, J. S., Hughson, D. L., McDonald, E. V., and Miller, D. M., eds. The Mojave Desert: Ecosystem Processes and Sustainability. Reno, NV University of Nevada Press.Google Scholar
Brooks, M. L., Esque, T. C., and Duck, T. 2007. Creosotebush, blackbrush, and interior chaparral shrublands. Page 97110 in Hood, S. M. and Miller, M., eds. Fire Ecology and Management of the Major Ecosystems of Southern Utah. Fort Collins, CO U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station General Technical Report RMRS-GTR-202.Google Scholar
Burt, R., ed. 2004. Soil Survey Laboratory Methods Manual. Soil Survey Investigations Report No. 42, Version 4.0. Washington, DC U.S. Department of Agriculture, Natural Resources Conservation Service. 700 p.Google Scholar
Chambers, J. C., Roundy, B. A., Blank, R. R., Meyer, S. E., and Whitaker, A. 2007. What makes Great Basin sagebrush ecosystems invasible by Bromus tectorum? Ecol. Monogr. 77:117145.Google Scholar
Craig, D. J., Craig, J. E., Abella, S. R., and Vanier, C. H. 2010. Factors affecting exotic annual plant cover and richness along roadsides in the eastern Mojave Desert, USA. J. Arid Environ. 74:702707.Google Scholar
Crooks, J. A. 2002. Characterizing ecosystem-level consequences of biological invasions: the role of ecosystem engineers. Oikos 97:153166.Google Scholar
Daly, C., Halbleib, M., Smith, J. I., Gibson, W. P., Doggett, M. K., Taylor, G. H., Curtis, J., and Pasteris, P. P. 2008. Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States. Int. J. Climatol. 28:20312064.Google Scholar
Davis, M. A., Grime, J. P., and Thompson, K. 2000. Fluctuating resources in plant communities: a general theory of invasibility. J. Ecol. 88:528534.Google Scholar
Ellis, C. J., Coppins, B. J., Dawson, T. P., and Seaward, M. R. D. 2007. Response of British lichens to climate change scenarios: trends and uncertainties in the projected impact for contrasting biogeographic groups. Biol. Conserv. 140:217235.Google Scholar
Floyd, M. L., Hanna, D., Romme, W. H., and Crews, T. E. 2006. Predicting and mitigating weed invasions to restore natural post-fire succession in Mesa Verde National Park, Colorado, USA. Int. J. Wildland Fire 15:247259.Google Scholar
Gilbert, B. and Lechowicz, M. J. 2005. Invasibility and abiotic gradients: the positive correlation between native and exotic plant diversity. Ecology 86:18481855.Google Scholar
Hunter, R. B. 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. 51:176182.Google Scholar
Kass, R. E. and Raftery, A. E. 1995. Bayes factors. J. Am. Statis. Assoc. 90:773795.Google Scholar
Kent, M. and Coker, P. 1992. Vegetation Description and Analysis. New York J. Wiley. 363 p.Google Scholar
Knapp, A. K., Beier, C., Briske, D. D., et al. (2008). Consequences of more extreme precipitation regimes for terrestrial ecosystems. Bioscience 58:811821.Google Scholar
Lato, L. J. 2006. Soil Survey of Clark County Area, Nevada. Washington, DC U.S. Department of Agriculture, Natural Resources Conservation Service. 1801 p.Google Scholar
Levine, J. M. and D'Antonio, C. M. 1999. Elton revisited: a review of evidence linking diversity and invasibility. Oikos 87:1526.Google Scholar
McCune, B. 2006. Non-parametric habitat models with automatic interactions. J. Veg. Sci. 17:819830.Google Scholar
McCune, B. 2007. Improved estimates of incident radiation and heat load using non-parametric regression against topographic variables. J. Veg. Sci. 18:751754.Google Scholar
McCune, B. and Mefford, M. J. 2004. Hyperniche. Multiplicative Habitat Modeling: User's Booklet. Version 1.0. Gleneden Beach, OR MjM Software.Google Scholar
McCune, B., Berryman, S. D., Cissel, J. H., and Gitelman, A. I. 2003. Use of a smoother to forecast occurrence of epiphytic lichens under alternative forest management plans. Ecol. Appl. 13:11101123.Google Scholar
Meyer, S. E. 1986. The ecology of gypsophile endemism in the eastern Mojave Desert. Ecology 67:13031313.Google Scholar
Miller, M. E., Belnap, J., Beatty, S. W., and Reynolds, R. L. 2006. Performance of Bromus tectorum L. in relation to soil properties, water additions, and chemical amendments in calcareous soils of southeastern Utah, USA. Plant Soil 288:118.Google Scholar
Rao, L. E., Allen, E. B., and Meixner, T. 2010. Risk-based determination of critical nitrogen deposition loads for fire spread in southern California deserts. Ecol. Appl. 20:13201335.Google Scholar
Salo, L. F. 2005. Red brome (Bromus rubens subsp. madritensis) in North America: possible modes for early introductions, subsequent spread. Biol. Invasions 7:165180.Google Scholar
SAS Institute. 1999. SAS/STAT User's Guide. Version 8. Cary, NC SAS Institute. 1464 p.Google Scholar
SAS Institute. 2004. JMP User's Guide. Cary, NC SAS Institute. 402 p.Google Scholar
Saxton, K. E. and Rawls, W. J. 2006. Soil water characteristic estimates by texture and organic matter for hydrologic solutions. Soil Sci. Soc. Am. J. 70:15691578.Google Scholar
Seager, R., Ting, M. F., Held, I. M., et al. 2007. Model projections of an imminent transition to a more arid climate in southwestern North America. Science 316:11811184.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 408:7982.Google Scholar
Soil Survey Division. 1993. Soil Survey Manual. Washington, DC U.S. Department of Agriculture Handbook No. 18. 437 p.Google Scholar
Strait, R. K. 2006. Soil Survey of Mohave County, Arizona, Central Part. Washington, DC Department of Agriculture, Natural Resources Conservation Service. 945 p.Google Scholar
Suazo, A. A., Spencer, J. E., Engel, E. C., and Abella, S. R. 2011. Responses of native and non-native Mojave Desert winter annuals to soil disturbance and water additions. Biol. Invasions. In press. DOI: 10.1007/s10530-011-9998-6.Google Scholar
Tan, K. H. 2005. Soil Sampling, Preparation, and Analysis. Boca Raton, FL CRC. 680 p.Google Scholar
Williamson, J. and Harrison, S. 2002. Biotic and abiotic limits to the spread of exotic revegetation species. Ecol. Appl. 12:4051.Google Scholar
[WRCC] Western Regional Climate Center. 2011. Western U.S. Historical Climate Summaries. Reno, NV Western Regional Climate Center, http://www.wrcc.dri.edu/ Accessed: March 22, 2011.Google Scholar
Wu, K. K. and Jain, S. K. 1979. Population regulation in Bromus rubens and B. mollis: life cycle components and competition. Oecologia 39:337357.Google Scholar
Yost, A. C. 2008. Probabilistic modeling and mapping of plant indicator species in a Northeast Oregon industrial forest, USA. Ecol. Indic. 8:4656.Google Scholar