Jennifer L. Firn1, Tracy M. Rout2, Hugh P. Possingham1, and Yvonne M. Buckley1. (1) University of Queensland, (2) University of Melbourne
The prolific spread of exotic plants is a serious global management concern because of the high socio-economic, and environmental impacts associated with their invasion. In response to this concern, ecological studies have focused on isolating the causal mechanisms behind invasion and a number have identified disturbance. To link science to practice, we explored the benefit of incorporating actions that reduce the frequency of disturbance into weed management regimes. First we developed a simple metapopulation model that describes the dynamics of weed invasion, including the likelihood that alternative control measures will kill or remove adult plants, and stimulate germination from the seed bank. Then, we used a decision theory tool, stochastic dynamic programming, to find the optimal control measure depending on the probability of disturbance, and current state of the invasion. To illustrate the utility of this approach, we applied it to a case study - management of Mimosa pigra, an invasive perennial legume shrub, and a pantropical weed. We show that if disturbance levels are high then the optimal control measure is that with the highest likelihood of reducing the size of the weed seed bank. This complicates control efforts, as seed bank size is difficult to measure and reducing it requires intensive actions such as the removal of adult plants and stimulation of germination. If, however, disturbance is unlikely then practitioners can use more straightforward management actions, such as the application of herbicides that aim to control adult populations without the complexity of managing seed bank size.