Modelling the mechanisms of olive die back caused by Xylella fastidiosa biofilms

Project Rationale :
Plant health is crucially important for food production and the preservation of biodiversity. However, threats from human mediated drivers, such as climate change and increased globalisation, has led to an increase in the spread of novel plant diseases that can have significant impacts on food production and the economy.

Xylella fastidiosa is a globally important bacterial pathogen that attacks many plants of economic importance. Initially it was restricted to the Americas, but in 2013 it was detected in Lecce, Italy in 2013. Since the initial outbreak, it has invaded large swathes of olives in southern Italy [1], and is of great concern throughout Mediterranean basin and beyond. Currently, there is no known cure for this deadly disease of olives and the only approaches to control are to destroy the host trees and create buffer zones around them or to manage the insect vector population. Exploring the mechanisms by which the bacterium grows within the host plant, forming a biofilm, is critical for our understanding future control methods.

This project will develop mathematical models of biofilm and associated plant disease spread related to Xylella fastidiosa. These predictive process based models will be developed in close collaboration with CEH and CNR, Bari.

Methodology:
The aim of this studentship is to develop and analyse process based mathematical models, parameterised by existing datasets, to better understand seasonal X. fastidiosa biofilm growth in olive hosts. These models will not only lead to a better understanding of the disease and its spread, but they allow for optimisation of existing treatments and development of new ones. The specific aim of the project is to better predict the timing of dieback infection initiation and how this interacts with the environment. In particular, the student will:
1) Develop process based models for seasonal xylem flow of water and nutrients via evapotranspiration,
2) Develop models of seasonal biofilm growth and aggregation, including extracellular polymeric substances,
3) Combine the above models to understand the mechanisms of X. fastidiosa-induced dieback in olives in seasonal environments.
Model predictions will compared to field and laboratory observations of olive dieback (visits to CNR, Bari are part of this project), as well as remotely sensed canopy-level data (hyperspectral and thermal images).

Training:
The INSPIRE DTP program provides comprehensive personal and professional development training alongside extensive opportunities for students to expand their multi-disciplinary outlook through interactions with a wide network of academic, research and industrial/policy partners. The student will be registered at the UoS and hosted jointly by UoS and CEH. Specific training will
include:
• Process based modelling theory,
• Process based modelling simulation techniques,
• Plant water and nutrient transportation modelling,
• Biofilm modelling,
• Numerical analysis,
• Scientific programming,
• High performance computing,
• Scientific writing.

Furthermore, the student will have the opportunity to engage in national and international conferences, as well as present at X. fastidiosa specific workshops, policy engagement meetings and conferences throughout Europe.