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Predicting the likelihood of yellow starthistle (Centaurea solstitialis) occurrence using landscape characteristics

Published online by Cambridge University Press:  20 January 2017

Bahman Shafii ,
William J. Price ,
Timothy S. Prather ,
Lawrence W. Lass  and
Donald C. Thill
William J. Price
Affiliation:
Statistical Programs, College of Agricultural and Life Sciences, University of Idaho, Moscow, ID 83844
Timothy S. Prather
Affiliation:
Department of Plant, Soil, and Entomological Sciences, College of Agricultural and Life Sciences, University of Idaho, Moscow, ID 83844
Lawrence W. Lass
Affiliation:
Department of Plant, Soil, and Entomological Sciences, College of Agricultural and Life Sciences, University of Idaho, Moscow, ID 83844
Donald C. Thill
Affiliation:
Department of Plant, Soil, and Entomological Sciences, College of Agricultural and Life Sciences, University of Idaho, Moscow, ID 83844
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Abstract

Yellow starthistle is an invasive plant species common in the semiarid climate of central Idaho and other western states. Early detection of yellow starthistle and estimation of its infestation potential in semiarid grasslands have important scientific and managerial implications. Weed detection and delineation of infestations are often carried out by using ground survey techniques. However, such methods can be inefficient and expensive in detecting sparse infestations. The distribution of yellow starthistle over a large region may be affected by various landscape variables such as elevation, slope, and aspect. These exogenous variables may be used to develop prediction models to estimate the potential for yellow starthistle invasion into new areas. A nonlinear prediction model has been developed using a polar coordinate transformation of landscape characteristics to predict the likelihood of yellow starthistle occurrence in north-central Idaho. The study region included the lower Snake River and parts of the Salmon and Clearwater basins encompassing various land-use (range, pasture, and forest) categories. The model provided accurate estimates of yellow starthistle incidence within each specified land-use category and performed well in subsequent statistical validations. This prediction model can assist land managers in focusing their efforts by identifying specific areas for survey.

Keywords

Yellow starthistle, Centaurea solstitialis L. CENSOEstimationlandscape variablesnonlinear regressionvalidation
Type
Weed Biology
Information
Weed Science , Volume 51 , Issue 5 , October 2003 , pp. 748 - 751
Copyright
Copyright © Weed Science Society of America 

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