USDA Forest Service Northern Research Station, United States
Background/Question/Methods
Reducing the arrival and spread of harmful invasive species is a challenge facing governments worldwide. Despite efforts to prevent their introduction or eradicate nascent populations, many invasive species continue to become established and threaten food production, human health, and natural biodiversity. In these cases, slowing or stopping the spread of these species may be a preferred strategy; however there have been relatively few efforts made to accomplish this. Part of the problem with managing invasion spread is that it is unclear how to cost-effectively distribute management efforts over space to accomplish this. Here we consider a continuous space bioeconomic model, and we develop and apply a novel algorithm to find the optimal allocation of population suppression efforts along a spatial gradient.
Results/Conclusions
We show that, if the amount abated per investment does not depend on population density (e.g., physical removal of large weeds), the optimal management comprises only surveillance and eradication in the uninvaded area (into which individuals disperse from previously invaded areas). But the optimal strategy is different if removal is proportional to population density (e.g., using pesticides to suppress insect populations), the dispersal rate is sufficiently large, and Allee effects are not too strong. In these cases, the optimal strategy also comprises treatment in a specific area, a “suppression zone,” located between the invaded and the uninvaded areas, where treatment reduces the invading population but without eliminating it, thereby reducing the cost of eradication in the uninvaded area. Implementation of such a suppression zone and identification of its optimal size hold considerable promise for cost-effective containment of invasive species and subsequent mitigation of their impacts.
