• A new University of Sheffield project utilises methods successful in predicting COVID-19 spread to better understand and combat the significant economic and environmental impact of forest diseases in the UK

• Developed in partnership with Forest Research, the advanced mathematical models will integrate factors like tree distribution and seasonality, initially focusing on Dothistroma needle blight to inform management strategies

• The project includes an interactive web-based tool to make the research accessible to educators, students and the public, empowering wider understanding and contribution to forest protection

• Ash dieback is predicted to kill over 100 million trees in the UK and cost our economy up to £15 billion

Harnessing methods used to successfully predict and understand the spread of COVID-19 during the pandemic, a new University of Sheffield project aims to combat the impact of forest diseases that can cost the UK economy billions.

Tree diseases such as Ash dieback, Dutch elm disease and Dothistroma needle blight pose significant economic and environmental threats to UK forests. Their impact hinders forests' vital carbon dioxide absorption, causes biodiversity loss and habitat destruction, and affects the survival of other plant species, significantly impacting the fight against climate change.

The associated financial costs, such as surveying, felling, implementing control measures and replanting, can cost billions, with Ash dieback alone predicted to kill off 80% of the UK’s Ash trees and estimated to cost the UK economy £15 billion. Scientists are now turning to sophisticated mathematical models to better understand and combat these challenges.

A new partnership between the University of Sheffield and Forest Research, the UK Government’s agency for applied forest science and part of the Forestry Commission, will see the development of advanced models that capture the complex interplay of disease spread, the arrangement and distribution of trees within a forest and seasonal changes in ecosystems.

“We have all seen how mathematical models can be an important tool to understanding, predicting and managing disease spread during the COVID-19 pandemic,” said project leader Dr Alex Best, from the University of Sheffield’s School of Mathematical and Physical Sciences

“This project will apply similar methods to tree diseases, but with the additional challenge of understanding how the spatial arrangement of trees in forests is a crucial element in how diseases spread through groups of trees.

“By working closely with colleagues at Forest Research, we can use these models to produce advice to growers on how best to manage their stocks if they find disease.”

The partnership with Forest Research, the UK's leading tree research agency, will enable the models to be practically applied in the real world. The initial focus will be on Dothistroma needle blight, a growing threat to pine trees. The goal is to develop management strategies for forest nurseries and create an interactive web-based tool to help nursery managers and the public understand disease spread.

Dr Katherine Tubby, Senior Scientist in the Pathology team, said: “Dothistroma needle blight significantly threatens UK pine woodlands. A decline in eastern England forests began in the early 2000s, with the pathogen, Dothistroma septosporum, rapidly spreading across the UK over the next two decades.

“Despite ongoing research, much remains unknown. Molecular studies indicate some populations may be native, while others show close links to European and even western Canadian populations, highlighting just how far the pathogen can travel.

“Trees grown in nurseries for our commercial forests are subject to strict biosecurity measures, but movement of the pathogen within and outside these environments presents a very real risk to our forests. This study should give us a better understanding of the key drivers behind pathogen dissemination and disease outbreaks, and will play a critical role in helping us protect our forests.”

The project faces the challenge of combining spatial structure – the rooted nature of trees and localised disease spread – with seasonality, which involves the climatic changes affecting both trees and pathogens. While these factors have been studied separately, the new project will integrate them into a single, comprehensive model.

The development of an interactive web-modeller will further broaden the project's impact, making the research accessible to educators, students and the general public. This will empower a wider audience to understand the challenges facing our forests, enabling them to contribute to their protection and ensure their sustainability for future generations.