Physiologically-based demographic modelling approach for invasive alien species: their contribution for quantitative pest risk assessment

Invasive alien species (IAS) represent an important threat for biodiversity and ecosystem services. They have also an important impact on plant, animal and human health and well-being. There is a growing need to develop methodologies for the quantitative assessment of risks posed by IAS to the environment as well as to plant, animal and human health, based on realistic scenarios of entry, establishment, spread and impact. Quantitative risk assessment can benefit from the contribution of population-based modelling approaches which are able to provide scenarios on the potential distribution and the dynamics of spread of IAS in newly invaded areas. We explore the use of a Physiologically-Based Demographic Model for the development of scenarios supporting quantitative risk assessment of invasive pests. Demographic models can describe spatio-temporal patterns of pests’ population abundance which is considered the main driver influencing their impact. The physiologically-based approach accounts for nonlinear relationships between environmental variables and biological responses at individual level. The invasion dynamics in Europe of the American grapevine leafhopper (Scafoideus titanus) and the Mediterranean fruit fly (Ceratitis capitata) are considered as case studies. For the two species we investigated the area of potential establishment and derived the spatial distribution through an index of their potential abundance in Europe. The possibility to mechanistically represent the influence of the environmental variables on demographic processes is used to explore the impact of climate change on distribution and abundance of the two species. Model outputs were compared with data showing actual presence of the specie in Europe. The modelling approach proposed provides the information necessary to perform quantitative risk assessment and might be suitable for (i) exploring consequences of different management scenarios for the control of IAS, (ii) comparing and prioritising IAS, (iii) supporting the prevention, early detection, rapid response and long-term control of IAS