Towards the integration of spread and economic impacts of biological invasions in a landscape of learning and imitating agents

We develop an agent-based model integrated with a spatial stochastic simulation harmful non-indigenous species (NIS) spread model in which farmers have learning and imitation capabilities. The model is applied to the western corn rootworm (WCR) invasion in the UK. The invasion is never eradicated due to the high dispersal capacity of WCR, particularly under climate change conditions. The lowest expected welfare losses arise with a laissez faire policy against the invasion. The effectiveness of NIS control programmes that require participation by land managers is shown to depend greatly on their learning and imitation dynamics. Control programmes might fail completely if there is global knowledge of the burdens of compliance – e.g. through the media – and the land managers can foresee the future consequences of new actions. This is due to coordinated noncompliance occurring across the landscape. If the agents need to experience compliance to learn its consequences or communicate only locally, potential noncompliant behaviour spreads more slowly than the invasion front and trails behind it. In conclusion, negative opinions of land managers over NIS control programmes and their media coverage can strongly undermine programmes. Identification and management of these factors may increase the odds of success of the programmes.