When a new pathogen or insect pest is detected, rapid response is critical to maximise the chance of containment and eradication and minimise the threat to relevant industries. However, inappropriate response can be extremely costly. For example, we might waste resources on trying to eradicate a pest that has already spread too far to be contained or use a management strategy that has a lower chance of success than another possibility and thus allow the pest to escape and become permanently established.

Simulation modelling is a tool that can be used to evaluate different management options in light of available knowledge about the pest’s dispersal and population dynamics and its new environment. However, simulation models typically take a long time to develop, parameterise, test, run and analyse. How then can modelling be used to provide valuable predictions when rapid response is critical?

We present an approach for meta-modelling of biological invasions. Meta-models, or emulators, are relatively simple and empirical models that capture the important characteristics of more complex and realistic process-based simulation models, and thus ‘emulate’ their predictions. However, the meta-model is much simpler than the simulation model being emulated, making it much quicker to run and analyse. It can also be used to make predictions for a wide range of organisms, environments, and management options, and to evaluate which characteristics of these organisms and environments are most important to the final outcome. This allows expensive and time-consuming collection of new data to be focussed on areas where it is most needed.