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

由于树木疾病和有害入侵害虫在我们的原生森林内的传播而造成的生物多样性的丧失正在产生巨大的环境、经济和社会影响。近年来，由于意外的国际进口增加以及气候变化为许多病原体和害虫创造了更有利的环境，这一威胁一直在升级。在《25年环境计划》中，英国政府强调，通过控制现有的疾病和害虫，并通过培养森林对新的疾病的适应能力，加强生物安全是一个关键的优先事项。一种令人担忧的关键入侵害虫是橡树过程蛾(OPM)，这是一种对橡树和人类都有害的破坏性害虫。尽管作出了很大努力将疫情控制在英格兰东南部最初流行的地区，但OPM仍在继续传播。公园和城市地区内的树木受到的影响最大，有可能进一步加剧在获得优质绿地方面的社会经济和种族鸿沟。对OPM人口未来动态的预测和控制是政府OPM控制方案(OPM-CP：包括来自环境、食品和农村事务部(DEFRA)、林业委员会(FC)和南安普敦地理数据公司等的研究人员)的优先事项。增加使用计算模型和统计流行病学是DEFRA确定的优先措施，以保护环境和社会福利的植物健康。尽管这种跨学科方法的潜在影响，但在将这些理论技术转化为环境组织制定强有力的林业管理和保护计划的广泛使用方面仍存在差距。该奖学金旨在弥合这一差距，通过与OPM-CP.p成员的动态合作，为OPM的传播开发数学模型。与NERC通过保护当前林地健康和通过告知战略确保未来的林地弹性来实现‘健康环境’的优先交付领域相一致，该奖学金将推动基于本地主体的模型和用于OPM传播的国家随机微分连续模型的发展。这些模型将以OPM-CP共享的真实数据的严格统计分析和参数推断为基础，并用于为控制OPM的政策提供信息，特别是在有高感染风险的贫困城市地区。这些成果不仅将为管理OPM的控制提供洞察力，而且还将为数学家和林业合作伙伴之间的知识交流建立一个框架，可用于管理未来的病虫害。

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.