|Title of Project|
|Ash dieback: analysis and modelling of the Realising Ash Potential field trials|
|This project going to be…|
|Experimental (lab/field), remote/virtual, Computational, on site|
|Full Name of Supervisor|
|Prof. Adam Kleczkowski|
|Institution Department and Address|
|Dept. Mathematics and Statistics, University of Strathclyde, 26 Richmond Street
Glasgow, Glasgow G1 1XH
|Full name of the day to day supervisor and/or arrangements for supervision|
|The project will be jointly supervised by Prof. A Kleczkowski (Strathclyde) and Dr J Clark (Future Trees Trust). The data analysis and modelling will be carried out in Glasgow, Scotland, but there is a possibility of carrying out the work entirely remotely. The student will also have an opportunity to travel to Oxfordshire to take part in collecting the 2022 data. The student will be given appropriate training by Dr Clark and the Future Trees Trust; transport and accommodation will be covered from the project budget.|
|Date of Project Commencement|
|Brief Description of Project|
|Ash dieback, Hymenoscyphus fraxineus, is a fungal disease that has been inflicting devastating impacts on the UK landscapes and biodiversity since its first detection in 2012; it is expected to have a £15b impact to the UK economy. It is now widespread in Europe, with up to 85% mortality rates recorded in plantations and 69% in woodlands. It is estimated that a large proportion of ash trees in the UK are already affected. As there is no promising treatment or prevention measure, the best hope for the long-term future of the UK’s ash trees lies in identifying tolerant or resistant trees for breeding new generations.
This project combines unique field data sets collected during in the Realising Ash Potential trials and supplied by Dr Clark from the Future Trees Trust, and Prof. Kleczkowski modelling approaches. The student will also benefit from collaboration with a PhD student jointly supervised by Kleczkowski and Dr Cavers from the Centre of Ecology and Hydrology (CEH). Data on 4,212 trees collected for different provenances, consisting of budburst, senescence and infection levels assessed yearly since 2013, will be analysed statistically to uncover a relationship between tree provenance and disease resistance. An epidemiological model, based on a survival (Cox) model, will be constructed and fitted to data using appropriate statistical approaches. Depending on student interests, a Bayesian approach will be considered, allowing estimation of survival probabilities. An extension to an epidemiological, Susceptible-Infected-Removed, model will also be considered.
The student will also have an opportunity to travel to Oxfordhshire to take part in collecting the 2022 data and to subsequently analyse them and incorporate into the model. The student will be given appropriate training and support in travelling to the site.
The project suits a student of quantitative subjects, or a Biology student who wants to expand their portfolio by including advanced epidemiological modelling. The student will learn about ash biology and Ash Dieback impact, including the ability to identify disease in the field and the principles of field trials. They will also study basic spatial statistics and disease modelling, before progressing to using R to construct a model. Time permitting, the student will also explore how climate change is impacting spread of disease by combining epidemiological data with weather records.
The student will have the opportunity to present their work to members of CEH and Future Trees. They will also benefit from participation in a large NERC Treescape grant NE/V019988/1 “ Learning to adapt to an uncertain future: linking genes, trees, people and processes for more resilient treescapes (newLEAF)” with Kleczkowski leading one of the work packages. The student will participate in regular project meetings and will present the results of the project for the consortium.
|Attach the recommended reading for the project|
• Kleczkowski A, Gilligan CA. 2007 Parameter estimation and prediction for the course of a single epidemic outbreak of a plant disease. Journal of The Royal Society Interface 4, 865–877. (doi:10.1098/rsif.2007.1036)
• Kleczkowski A, Hoyle A, McMenemy P. 2019 One model to rule them all? Modelling approaches across OneHealth for human, animal and plant epidemics. Phil. Trans. R. Soc. B 374, 20180255. (doi:10.1098/rstb.2018.0255)Literature (ash dieback):• Forest Research: Pest and disease resources, Ash dieback (Hymenoscyphus fraxineus) https://www.forestresearch.gov.uk/tools-and-resources/fthr/pest-and-disease-resources/ash-dieback-hymenoscyphus-fraxineus/ [Accessed 01/03/2022]
• McKinney LV, Nielsen LR, Collinge DB, Thomsen IM, Hansen JK, Kjær ED. 2014 The ash dieback crisis: genetic variation in resistance can prove a long-term solution. Plant Pathology 63, 485–499. (doi:10.1111/ppa.12196)
• Landolt J, Gross A, Holdenrieder O, Pautasso M. 2016 Ash dieback due to Hymenoscyphus fraxineus: what can be learnt from evolutionary ecology? Plant Pathology 65, 1056–1070. (doi:10.1111/ppa.12539)
• Plumb WJ, Coker TLR, Stocks JJ, Woodcock P, Quine CP, Nemesio-Gorriz M, Douglas GC, Kelly LJ, Buggs RJA. 2020 The viability of a breeding programme for ash in the British Isles in the face of ash dieback. PLANTS, PEOPLE, PLANET 2, 29–40. (doi:10.1002/ppp3.10060)
• Mitchell RJ et al. 2014 Ash dieback in the UK: A review of the ecological and conservation implications and potential management options. Biological Conservation 175, 95–109. (doi:10.1016/j.biocon.2014.04.019)
• Whittet R, Cottrell J, Cavers S, Pecurul M, Ennos R. 2016 Supplying trees in an era of environmental uncertainty: Identifying challenges faced by the forest nursery sector in Great Britain. Land Use Policy 58, 415–426. (doi:10.1016/j.landusepol.2016.07.027)