Ruijin Ma, Ph.D.
Mark P. Kumler, Ph.D.
Invasive plant species are aggressively spreading and threatening the Joshua Tree National Park (JOTR) ecosystem. Uncontrolled invasives will crowd out native plants and disrupt the natural habitat for desert animal species. JOTR needed a geographic information system (GIS) that can provide support for developing weed control plans against the Sahara mustard threat. This project addressed this need by developing a geodatabase for analysis, compiling required GIS feature layers, developing a mustard weed data model and a predictive spread model to aid in tracking the invasive weed. The data model identifies the essential data to collect for assessing and monitoring mustard weed observations. The compiled GIS feature layers consists of human activity factors (road network, trail, disturbed areas) and land factors (soil type, elevation, slope, vegetation cover, etc.). Human activity is a strong predictor of weed spread and these feature classes are the main element in one tool, the Predict Weed Spread Model. Land assessment analysis helps identify JOTR areas that are potentially high risk to mustard weed infestation. Results showed that a fundamental understanding of the Sahara mustard dynamics is required to model weed habitats and to predict weed spread that contributed to its existence and spread.
Cullors, V. M. (2013). A Geographic Information System for Invasive Species: Sahara Mustard Weed (Master's thesis, University of Redlands). Retrieved from http://inspire.redlands.edu/gis_gradproj/205