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EASTBIO Global spread of plant pests and diseases: projecting future threats to food security


Faculty of Natural Sciences

About the Project

Plant pests and pathogens reduce the yield from agriculture and forestry, as well as damaging natural ecosystems, presenting a major threat to food security globally. Staple crops are estimated to suffer 10-40% yield loss to pests and diseases, with the damage concentrated in developing economies with fast-growing human populations and food-deficits. Prevention is always better than cure, and so improving our understanding of the drivers of plant pest and disease emergence will be vital for anticipating and therefore preventing future threats to food security.



The aim of this PhD studentship is to develop predictive models for recent pest and disease emergence in countries around the globe, focusing on quarantine pests threatening Europe and the Mediterranean regions. These models must capture key drivers of plant disease spread such as increasing connectivity between countries and regions through trade and tourism, shifts in cropping patterns, climate change and other socio-economic factors. In a major step forward, the models will be used to project forwards in time and produce scenarios for future plant disease threats.



To do this the student will develop work on three related tasks:

Task 1: Assemble a database of plant pest and disease emergence and types of impact for a wide range of agricultural pests and diseases. This will involve mining published literature and existing databases.

Task 2: Use statistical and machine learning tools to model recent emergence events in the database and identify the most important drivers of emergence and impact. This will estimate the relative importance of drivers such as global trade, cropping, climatic and socio-economic factors, as well as key features of the pests and diseases such as their host range.

Task 3: Use the models to project disease threats into the future, based on alternative scenarios for global trade, climate and land use. This will be done using the statistical models for disease emergence from Task 2 and/or new agent-based simulations for global spread of pests or pathogens.



The student will receive training in database compilation, statistical modelling including machine learning using R or Python, and agent-based modelling. They will benefit from working in an interdisciplinary, diverse and supportive supervisory team and engaging with plant health stakeholders. We currently work on some of the most important plant health and invasive species threats (e.g. Xylella fastidiosa, Phytophthora, water hyacinth) and have strong links to plant health policy makers in the UK, Europe and beyond.

This is a full-time opportunity.


Candidates should have (or expect to achieve) a minimum of a 2:1 UK Honours degree, or the equivalent qualifications gained outside the UK, in a relevant subject.


We welcome applicants with a background in Ecology, Biology, Statistics or related fields. To enquire informally please contact Dr Daniel Chapman ().



References

Chapman, D.S. et al (2017) Global trade networks determine the distribution of invasive non‐native species. Global Ecology and Biogeography 26, 907-917.

Fones, H.N. et al. (2020) Threats to global food security from emerging fungal and oomycete crop pathogens. Nat Food 1, 332-342.

Savary, S., et al. (2019) The global burden of pathogens and pests on major food crops. Nature Ecology and Evolution 3, 430-439.

Funding Notes

This 4 year PhD project is part of a competition funded by EASTBIO BBSRC Doctoral Training Partnership View Website. This opportunity is open to UK and International students and provides funding to cover stipend and UK level tuition (Please state if your institution will provide funding to cover the difference in fees). Please refer to UKRI website and Annex B of the UKRI Training Grant Terms and Conditions for full eligibility criteria.


References

Please request an EASTBIO application and reference form by contacting the email address below. Completed references should also be sent to this address.

(pgr.ioa@stir.ac.uk)

Unfortunately due to COVID restrictions we cannot supply a telephone number for enquiries, in the first instance please email either Moira Maron at the address above or one of the supervisors listed above.

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