COS 76-1
Spatial prioritization for management of Andropogon gayanus (Gamba grass) invasions: accounting for social, economic and environmental values

Wednesday, August 7, 2013: 1:30 PM
L100G, Minneapolis Convention Center
Vanessa M. Adams, Northern Australia National Environmental Research Program Hub, Research Institute for the Environment and Livelihoods, Charles Darwin University, Darwin, Australia
Samantha A. Setterfield, Research Institute for Environment and Livelihoods, Charles Darwin University, Darwin, Australia
Background/Question/Methods

The social, economic and environmental impacts of invasive plants are well recognized.  However, the social and economic costs of managing and eradicating invasive plants are rarely accounted for in the spatial prioritization of funding for weed management.    

We examine how current spatially explicit prioritization methods can be extended to identify optimal budget allocations to both eradication and control measures of invasive species to minimize the costs and likelihood of reinvasion. Our framework extends recent approaches to systematic prioritization of weed management to account for spatially variable environmental, social and cultural assets that are threatened by weed invasions.

We apply our method to the Daly catchment in the Northern Territory which has significant conservation and development values which are threatened by gamba grass (Andropogon gayanus), a highly invasive species recognized by the Australian government as a Weed of National Significance (WONS).  We integrate the current distribution and density of gamba grass, modelled spread, cost of eradication and control, mapped biodiversity assets and mapped cultural assets to optimally allocate funds to eradication and control programs under an annual $1.5 million budget comparing maxgain and minloss optimization approaches. 

Results/Conclusions

The prioritizations support previous findings that a minloss approach is a better strategy when threats are more variable than biodiversity.  Over a ten year simulation period we find that a minloss approach reduces future infestations by 15% compared to maxgain.  We find that due to the extensive current invasion and rapid rate of spread, allocating the annual budget to control efforts is more efficient than funding eradication efforts (reduces spread by up to 20%).  Applying the most efficient optimization scenario (control, minloss), a budget of $1.5 million a year reduces spread by ~30% compared to no control.  A budget of $7.5 million a year would allow control of all current invasions in the region and avoid a 400% increase in infestations.