PS 62-75 - A decision support model for buffelgrass management in southern Arizona

Thursday, August 11, 2011
Exhibit Hall 3, Austin Convention Center
Tracy R. Holcombe1, Leonardo Frid2, Aaryn Olsson3, Katy Bryan2, Alexander Hall2 and Jeffrey T. Morisette4, (1)Fort Collins Science Center, U.S. Geological Survey, Fort Collins, CO, (2)ESSA Technologies Ltd., Vancouver, BC, Canada, (3)Northern Arizona University, Flagstaff, AZ, (4)North Central Climate Science Center, U.S. Geological Survey, Fort Collins, CO
Background/Question/Methods

Buffelgrass (Pennisetum ciliare) is spreading throughout the southwestern United States creating a risk of fire in a system poorly adapted to it.  This fire risk threatens native ecosystems and human properties.  We created a decision support model for the wildland urban interface north of Tucson, AZ, to address the level of resources required to prevent buffelgrass spread and the allocation of these resources among inventory, treatment, and maintenance.  We used a spatial modeling framework, Tool for Exploratory Landscape Scenario Analyses (TELSA), to run our simulations.  Inputs to the model include a State and Transition Model to describe the succession and control of buffelgrass, a habitat suitability model, management planning zones, spread vectors, estimated dispersal kernels for buffelgrass and maps of its current distribution. 

Results/Conclusions

Our spatial simulations showed that without treatment, areas that started with as little as 80 hectares of buffelgrass could see spread to over 6,000 hectares by the year 2060.  In contrast, applying unlimited resources could limit 2060 infestation levels to only about 50 acres.  These results tell us that areas affected by buffelgrass may increase substantially over the next 50 years, but that a large upfront investment in buffelgrass control could reduce that area and overall management costs. The application of sufficient resources towards inventory is important as treatments can’t be applied to patches where buffelgrass is undetected.

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