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E4 DTP - Assessment of diet, gut microbiome, and plant detoxification in roe deer as a tool for forest management

Project Description


This project will take an omics approach to assess diet composition, gut microbiota, and secretion of tannin-binding salivary proteins in woodland roe deer populations to inform forest management strategies in Scotland

Project background

The increase in distribution and numbers of wild ungulates in Europe in the last decades pose great challenges in wildlife management, with roe deer being one of the species that has more rapidly increased in range and density. In Scotland, roe deer occur throughout the mainland and on some of the islands after a notable recent range expansion. Although roe deer are an important and iconic woodland species and provides revenue as game species, browsing by roe deer incurs damage to forestry and agriculture. Previous studies have indicated seasonal shifts in roe deer diet and that plant food availability can influence the level of damage in woodlands. Furthermore, an increasing number of studies are showing the importance of diet and gut microbiota to satisfy the nutritional requirements of large mammal herbivores in their seasonal environments. Insights about the diet, gut microbiome, secretion of saliva proteins aiding plant detoxification, and body condition in roe deer populations will further our understanding of adaptive strategies of this species to their environment. Robust information on summer diet in expanding roe deer populations will help devise management strategies to decrease the impact of browsing in protected woodlands and commercial forest stands.

Research questions

1. How habitat characteristics and food availability influences the diet of roe deer populations?
2. What are the associations between diet, gut microbiome, secretion of salivary plant detoxification proteins, and body condition in roe deer populations?
3. What deer and forestry management strategies could be implemented to decrease browsing damage in commercial forestry stands and natural protected areas whilst safeguarding roe deer welfare?


This project will adopt an interdisciplinary approach using traditional (botany, zoology) with novel approaches (spatial analyses, genomics, and proteomics). Representative samples of available plant food for roe deer in summer and winter from a selection of adjacent woodland estates in Scotland will be collected to build a DNA reference database for the diet analyses. Samples from rumen contents from 400 legally hunted and culled roe deer will be analysed to identify plant material ingested and microbiome composition in summer and winter following a DNA metabarcoding approach. The barcoding of plant material will be conducted using a chloroplast-specific primer cocktail that would enable identification at the species level. DNA sequences will be compared to the DNA reference database representing food availability in the study area. Microbiome analyses will be conducted using established protocols for sequencing of the ribosomal RNA marker 16S. Bioinformatic pipelines will be applied for qualitative and semi-quantitative analyses of the resulting plant and gut microbiome sequences. Identification and quantification of secretion of salivary glycoproteins binding plant secondary metabolites will be conducted by proteome analyses of samples of saliva and/or salivary glands tissue using mass spectrometry (MALDI-TOF/TOF). Diet, gut microbiome, and secretion of glycoproteins will be compared with body condition data collected for each individual during the sampling period.

Year 1. Plant identification and G.I.S. training. Mapping of food availability in the study area, DNA plant reference database, sample collection and body condition data measurements.
Year 2. Metabarcoding and bioinformatics training. Diet and gut microbiome analyses.
Year 3. Protein assays and proteomics training. Identification and quantification of secretion of glycoproteins to bind plant secondary metabolites.


A comprehensive training programme will be provided comprising both specialist scientific training and generic transferable and professional skills. Specialised skills will include fieldwork, spatial data analyses, genomics, bioinformatics, and proteomics. The student will also acquire a suite of other transferable skills including data management, effective communication with stakeholders, and the application of scientific evidence to inform deer and forestry management.

Funding Notes


The successful candidate will have an interest in deer biology and management, a degree in a related biological subject, experience in molecular biology, and excellent communication skills to interact with different stakeholders. A valid full UK driving license will be needed at the start of the project. Relevant fieldwork experience and some knowledge of G.I.S. analyses will also be advantageous.

Application process - View Website

Apply by Thu Jan 09 2020 at 12:00


Hu X., Liu G., Li Y., Wei Y., Lin S., Liu S., Zheng Y., Hu D. (2018). High-throughput analysis reveals seasonal variation of the gut microbiota composition within forest mush deer (Moschus berezovskii). Frontiers in Microbiology 9:1674
De Jong C.B., Gill R.M.A., van Wieren S.E., Burlton F.W.E. (1995). Diet selection by roe deer Capreolus capreolus in Kielder Forest in relation to plant cover. Forest Ecology and Management 79: 91-97.
Latham J., Staines B.W., Gorman M.L. (1999). Comparative feeding ecology of red (Cervus elaphus) and roe deer (Capreolus capreolus) in Scottish plantation forests. Journal of Zoology, London 247: 409-418.
Putman R., Langbein J., Green P., Watson P. (2011). Identifying threshold densities for wild deer in the UK above which negative impacts may occur. Mammal Review 41 (3): 175-176.
Ward A.I. (2005). Expanding ranges of wild and feral deer in Great Britain. Mammal Review 35: 1104-1120.
CASE partner: British Deer Society & Forest Research

Application process -

Apply by Thu Jan 09 2020 at 12:00

How good is research at University of Edinburgh in Biological Sciences?

FTE Category A staff submitted: 109.70

Research output data provided by the Research Excellence Framework (REF)

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