This is the report from a BSPP MSc/MRes Bursary.
Click here to read more/apply for one yourself.
I undertook the MRes in Applied Sciences at UWE, Bristol. I was co-supervised by Joel Allainguillaume and Jim Vafidis, specialists in qPCR analysis and unmanned aerial vehicle (UAV) imaging respectively. My project investigated the potential of novel technologies such as UAVs and qPCR to detect Ash Dieback and assess disease severity. To assist me in my studies, I was granted a BSPP masters bursary which was an invaluable source of financial support.
Ash dieback is caused by the invasive ascomycete Hymenoscyphus fraxineus and it is projected that up to 95% of F. excelsior trees in the UK will be lost to the disease which will have significant ecological and economic consequences. The cost to woodland ecosystems will be severe and will have the most pronounced impact on taxonomic groups dependant on F. excelsior, such as native invertebrates and microfungi. Therefore, a research priority is to find economical and efficient ways of detecting the disease and of assessing the severity of disease in individual woodlands. By efficiently monitoring the disease throughout the landscape, accurate predictions can be made regarding the extent of tree loss, which will in turn allow conservationists to prepare for the subsequent ecological impacts.
The first phase of this project was using a multispectral UAV to photograph canopies of mixed broadleaf woodlands. Multispectral photography captures the spectral signature of foliage, which gives insights into foliar health which would not otherwise be achieved with conventional aerial photography. For this stage of the project, a multispectral UAV was flown above woodland canopies at a height of 80m on a clear day. The drone was programmed to fly in a grid pattern, taking photos every 2 seconds. The photos were then stitched together and visualised using PIX4D and ArcGIS Pro software. See Figure 1 for a multispectral photograph of one of the study sites. Capturing multispectral photographs of canopies allowed me to quickly identify the location of diseased F. excelsior crowns, which paved the way for the next stage of the project.
The second stage of the project was using qPCR to test wood samples of unhealthy F. excelsior trees identified by UAV photography. Most of these trees did suffer from foliage loss typical of H. fraxineus, yet crucially none of them suffered from the hallmark ‘lesions’ commonly associated with the disease. Therefore, this part of the project was particularly interesting as it tested the ability of qPCR to detect this pathogen in visually healthy wood. A tree boror was used to take samples from trees internal vascular tissues, as vascular tissue in infected trees is usually host to H. fraxineus hyphae. DNA were extracted using the Qiagen DNEasy Plant Mini Kit and underwent qPCR analysis using an established assay. It was found that 56% of wood samples generated a positive result for H. fraxineus. As all the trees tested were confirmed by visual surveying to have H. fraxineus, this result did not necessarily demonstrate qPCR to reliably diagnose the disease every time. However, as all the wood samples were taken from visually healthy wood without lesions, this result showed that qPCR had some modest potential to detect the disease in asymptomatic wood.
The potential ability to detect H. fraxineus in visually healthy wood should be further investigated. The current study found that when testing visually healthy tree trunks of infected trees, only 56% of samples delivered a positive result. It is recommended that other anatomical locations on trees are investigated as locations for diagnostic qPCR sampling, such as stems and branches. If future research finds that a particular anatomical location in diseased trees delivers a very high success rate in pathogen detection, such a sampling location could be used to test for the disease in asymptomatic trees. This would have promising potential in detecting the disease before obvious symptoms appear, which would be useful to those trying to monitor and track the progression of the disease throughout woodlands and tree nurseries. This capability would be a valuable tool in the fight against ash dieback.
Overall, this course was a significant learning experience for me. I was able to improve my knowledge of plant pathology and was also given the opportunity to develop new skills in field monitoring, qPCR testing, statistical analysis and project management. I would like to thank the BSPP again for the financial support granted to me.
Scarlet Maguire
TOP IMAGE. A multispectral photograph of one of the study sites, Coed-Y-Bedw in South Wales, UK. Red pixels indicate healthy foliage while paler pixels indicate unhealthy foliage.
This is the report from a BSPP MSc/MRes Bursary.
Click here to read more/apply for one yourself.
