The behavior of multiple independent managers and ecological traits interact to determine prevalence of weeds.

Management of damaging invasive plants is often undertaken by multiple decision makers, each managing only a small part of the invader's population. As weeds can move between properties and re-infest eradicated sites from unmanaged sources, the dynamics of multiple decision makers plays a significant role in weed prevalence and invasion risk at the landscape scale. We used a spatially explicit agent-based simulation to determine how individual agent behavior, in concert with weed population ecology, determined weed prevalence. We compared two invasive grass species that differ in ecology, control methods, and costs: Nassella trichotoma (serrated tussock) and Eragrostis curvula (African love grass). The way decision makers reacted to the benefit of management had a large effect on the extent of a weed. If benefits of weed control outweighed the costs, and either net benefit was very large or all agents were very sensitive to net benefits, then agents tended to act synchronously, reducing the pool of infested agents available to spread the weed. As N. trichotoma was more damaging than E. curvula and had more effective control methods, agents chose to manage it more often, which resulted in lower prevalence of N. trichotoma. A relatively low number of agents who were intrinsically less motivated to control weeds led to increased prevalence of both species. This was particularly apparent when long-distance dispersal meant each infested agent increased the invasion risk for a large portion of the landscape. In this case, a small proportion of land mangers reluctant to control, regardless of costs and benefits, could lead to the whole landscape being infested, even when local control stopped new infestations. Social pressure was important, but only if it was independent of weed prevalence, suggesting that early access to information, and incentives to act on that information, may be crucial in stopping a weed from infesting large areas. The response of our model to both behavioral and ecological parameters was highly nonlinear. This implies that the outcomes of weed management programs that deal with multiple land mangers could be highly variable in both space and through time.