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Predicting the Distribution of Perennial Pepperweed (Lepidium latifolium), San Francisco Bay Area, California

Published online by Cambridge University Press:  20 January 2017

Melanie Vanderhoof ,
Barbara A. Holzman  and
Chris Rogers
Melanie Vanderhoof*
Affiliation:
Department of Geography and Human Environmental Studies, San Francisco State University, 1600 Holloway Ave., San Francisco, CA 94132
Barbara A. Holzman
Affiliation:
Department of Geography and Human Environmental Studies, San Francisco State University, 1600 Holloway Ave., San Francisco, CA 94132
Chris Rogers
Affiliation:
ESA, 350 Frank H. Ogawa Plaza, Suite 300, Oakland, CA 94612
*
Corresponding author's E-mail: mvanderhoof@mbakercorp.com
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Abstract

Perennial pepperweed is an invasive plant species that occurs throughout the western United States. This study develops a predictive model for perennial pepperweed distribution for the San Francisco Bay Area, based on spatial variables. Distribution data were developed by mapping perennial pepperweed along the shoreline of the South San Francisco Bay, using geographic positioning system units. Spatial relationships between its distribution and spatial variables were tested using binomial logistic regression. Predictive models were mapped using geographic information systems (GIS), and high risk areas within the San Francisco Bay Area were identified. Perennial pepperweed was found to occur within marsh habitats with full tidal action and near open water. This study demonstrates that habitat variables from widely available GIS layers can be used to predict distribution patterns for perennial pepperweed. The model results were compared to land ownership within the study area to demonstrate a management application of the model.

Keywords

Perennial pepperweed, Lepidium latifolium L. LEPLAPredictive modelinvasivedistributionriskSan Francisco BayGIS
Type
Research
Information
Invasive Plant Science and Management , Volume 2 , Issue 3 , July 2009 , pp. 260 - 269
Copyright
Copyright © Weed Science Society of America 

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