Hostname: page-component-cd9895bd7-gvvz8 Total loading time: 0 Render date: 2024-12-18T07:45:04.196Z Has data issue: false hasContentIssue false
  • English
  • Français

Predicting the occurrence of nonindigenous species using environmental and remotely sensed data

Published online by Cambridge University Press:  20 January 2017

Lisa J. Rew ,
Bruce D. Maxwell  and
Richard Aspinall
Bruce D. Maxwell
Affiliation:
Department of Land Resources and Environmental Sciences, Montana State University, Bozeman, MT 59717
Richard Aspinall
Affiliation:
Geographic Information and Analysis Center, Montana State University, Bozeman, MT 59717
Get access Rights & Permissions [Opens in a new window]

Abstract

To manage or control nonindigenous species (NIS), we need to know where they are located in the landscape. However, many natural areas are large, making it unfeasible to inventory the entire area and necessitating surveys to be performed on smaller areas. Provided appropriate survey methods are used, probability of occurrence predictions and maps can be generated for the species and area of interest. The probability maps can then be used to direct further sampling for new populations or patches and to select populations to monitor for the degree of invasiveness and effect of management. NIS occurrence (presence or absence) data were collected during 2001 to 2003 using transects stratified by proximity to rights-of-way in the northern range of Yellowstone National Park. In this study, we evaluate the use of environmental and remotely sensed (LANDSAT Enhanced Thematic Mapper +) data, separately and combined, for developing probability maps of three target NIS occurrence. Canada thistle, dalmation toadflax, and timothy were chosen for this study because of their different dispersal mechanisms and frequencies, 5, 3, and 23%, respectively, in the surveyed area. Data were analyzed using generalized linear regression with logit link, and the best models were selected using Akaike's Information Criterion. Probability of occurrence maps were generated for each target species, and the accuracies of the predictions were assessed with validation data excluded from the model fitting. Frequencies of occurrence of the validation data were calculated and compared with predicted probabilities. Agreement between the observed and predicted probabilities was reasonably accurate and consistent for timothy and dalmation toadflax but less so for Canada thistle.

Keywords

Canada thistle, Cirsium arvense L. CIRARdalmation toadflax, Linaria dalmatica (L.) P. Mill. LINDAtimothy, Phleum pratense L. PHLPRGeneralized linear modelinvasive specieslogistic regressionnonnative speciespredictive mappingsurveystratified sampling
Type
Symposium
Information
Weed Science , Volume 53 , Issue 2 , April 2005 , pp. 236 - 241
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

Akaike, H. 1977. Likelihood of a model and information criteria. J. Econom 16:3–14.CrossRefGoogle Scholar
Burnham, K. P. and Anderson, D. R. 1998. Model Selection and Inference: A Practical Information-Theoretic Approach. New York: Springer-Verlag. 353 p.CrossRefGoogle Scholar
Franklin, J. 1995. Predictive vegetation mapping: geographical modelling of biospatial patterns in relation to environmental gradients. Prog. Phys. Geogr 19:474–499.CrossRefGoogle Scholar
Gelbard, J. L. and Belnap, J. 2003. Roads as conduits for exotic plant invasions in a semiarid landscape. Conserv. Biol 17:420–432.CrossRefGoogle Scholar
Grime, J. P. 1979. Plant Strategies and Vegetation Processes. Chichester, UK: J. Wiley. 222 p.Google Scholar
Guisan, A. and Zimmermann, N. E. 2000. Predictive habitat distribution models in ecology. Ecol. Model 135:147–186.CrossRefGoogle Scholar
Hirzel, A. and Guisan, A. 2002. Which is the optimal sampling strategy for habitat suitability modeling? Ecol. Model 157:331–341.CrossRefGoogle Scholar
Hitchcock, C. L. and Cronquist, A. 2001. Flora of the Pacific Northwest. 12th ed. Seattle, WA: University of Washington Press. 730 p.Google Scholar
Legleiter, C. J., Lawrence, R. L., Fonstad, M. A., Marcus, W. A., and Aspinall, R. J. 2003. Fluvial response a decade after wildfire in the northern Yellowstone ecosystem: a spatially explicit analysis. Geomorphology 54:119–136.CrossRefGoogle Scholar
Mack, R. N. and Thompson, J. N. 1982. Evolution in steppe with few, large, hooved mammals. Am. Nat 119:757–773.CrossRefGoogle Scholar
Maggini, R., Guisan, A., and Cherix, D. 2002. A stratified approach for modelling the distribution of a threatened ant species in the Swiss National Park. Biodivers. Conserv 11:2117–2141.CrossRefGoogle Scholar
National Park Service. 1996. Preserving our Natural Heritage—A Strategic Plan for Managing Invasive Non-Indigenous Plants on National Park System Lands. www.nature.nps.gov/biology/invasivespecies/strat_pl.htm.Google Scholar
Parendes, L. A. and Jones, J. A. 2000. Role of light availability and dispersal in exotic plant invasion along roads and streams in the H. J. Andrews Experimental Forest, Oregon. Conserv. Biol 14:64–75.CrossRefGoogle Scholar
Shafii, B., Price, W. J., Prather, T. S., Lass, L. W., and Thill, D. C. 2003. Predicting the likelihood of yellow starthistle (Centaurea solstitialis) occurrence using landscape characteristics. Weed Sci 52:748–751.CrossRefGoogle Scholar
Swift, L. W. 1976. Algorithm for solar radiation on mountain slopes. Water Res 12:108–112.CrossRefGoogle Scholar
Trombulak, S. C. and Frissell, C. A. 2000. Review of ecological effects of roads on terrestrial and aquatic communities. Conserv. Biol 14:18–30.CrossRefGoogle Scholar
Tyser, R. W. and Key, C. H. 1988. Spotted knapweed in natural area fescue grasslands: an ecological assessment. Northwest Sci 62:151–160.Google Scholar
Tyser, R. W. and Worley, C. A. 1992. Alien flora in grasslands adjacent to road and trail corridors in Glacier National Park, Montana (U.S.A). Conserv. Biol 6:253–262.CrossRefGoogle Scholar
Watkins, R. Z., Chen, J., Pickens, J., and Brosofske, K. D. 2003. Effects of forest roads on understory plants in a managed hardwood landscape. Conserv. Biol 17:411–419.CrossRefGoogle Scholar
Whipple, J. J. 2001. Annotated checklist of exotic vascular plants in Yellowstone National Park. West. N. Am. Nat 61:336–346.Google Scholar
Young, J. A., Evan, R. A., and Major, J. 1972. Alien plants in the Great Basin. J. Range Manag 25:194–201.CrossRefGoogle Scholar