Knowledge Exchange Fellowship: developing and sharing mathematical tools to protect urban trees and woodland from invasive pests

The loss of biodiversity due to the spread of tree diseases and harmful invasive pests within our native forests is having an enormous environmental, economic, and social impact. The threat has been escalating in recent years due to increased accidental international imports and climate change creating a more favourable environment for many pathogens and pests. In the '25 Year Environment Plan' the UK government highlights enhancing biosecurity as a key priority, through the control of existing diseases and pests, and by building forest resilience against new ones.

A key invasive pest of concern is the oak processionary moth (OPM), a destructive pest harmful to both oak trees and humans. Despite great efforts to contain the outbreak to the original infested area of south-east England, OPM continues to spread. Trees within public parks and urban areas are most affected, risking further exacerbating both the socio-economic and ethnic divides in the access to quality green space. The prediction and control of the future dynamics of the OPM population is the priority of the governmental OPM Control Programme (OPM-CP: including researchers from the Department for Environment, Food and Rural Affairs (DEFRA), the Forestry Commission (FC), and Southampton GeoData, among others).

Increasing the use of computational modelling and statistical epidemiology are priority measures identified by DEFRA to protect plant health for environmental and social wellbeing. Despite the potential impact of such interdisciplinary methods, there is a gap in translating these theoretical techniques into widespread usage by environmental organisations for developing robust forestry management and protection plans. This Fellowship aims to bridge this gap to develop mathematical models for the spread of OPM through dynamic collaboration with members of the OPM-CP.

Aligned with NERC's priority delivery areas of 'healthy environment' through protecting current woodland health and 'resilient environment' through informing strategies to ensure future woodland resilience, this Fellowship will drive the development of both a local agent-based model, and a national stochastic differential continuum model for the spread of OPM. The models will be underpinned by rigorous statistical analysis and parameter inference of real data shared by OPM-CP and used to inform policies to control OPM, particularly in deprived urban areas at high risk of infestation. The results will not only provide an insight into managing the control of OPM but also establish a framework for knowledge exchange between mathematicians and forestry partners transferable to the management of future pests and diseases.