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| Funder | Engineering and Physical Sciences Research Council |
|---|---|
| Recipient Organization | Newcastle University |
| Country | United Kingdom |
| Start Date | Feb 25, 2021 |
| End Date | Aug 23, 2023 |
| Duration | 909 days |
| Number of Grantees | 3 |
| Roles | Co-Investigator; Principal Investigator |
| Data Source | UKRI Gateway to Research |
| Grant ID | EP/V048511/1 |
The spread of contagious tree diseases threatens woodlands and urban trees in the UK and globally, and recent UK epidemics of ash and chestnut trees have been covered extensively in the news.
The decimation of entire tree populations leads to dramatic ecological changes, and can also pose profound socio-economic challenges.
Defra, the government Department for Environmental, Food and Rural Affairs have identified a lack of realistic models to describe and predict tree disease spread as a key gap in their ability to manage pests and diseases effectively. This could have a major influence on the planning and management of trees in both woodlands and urban settings.
The proposed research will combine cutting edge techniques from applied mathematical modelling and statistical inference to develop a comprehensive modelling approach to predict tree disease in the UK.
The framework we propose will allow the model to be trained on data of past outbreaks before being used to predict emerging pathogens such as sweet chestnut blight.
Newcastle University; Durham University
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