- Value: This project is eligible for funding from the PANORAMA NERC Doctoral Training Partnership in an open competition.
- Number of awards: Approximately 24 awards across the Panorama programme.
- Deadline: 7 January 2019
Peatlands form an important terrestrial carbon store, comprising 30-50% of all carbon stored in soils worldwide (Gorham, 1991) much of which is at risk of degradation through climate change (Gallego-Sala and Prentice, 2013), increasing its susceptibility to erosion. When peat is eroded, this carbon is released into the atmosphere and contributes to global greenhouse gas emissions. Blanket peat in the British Isles makes up a highly significant 15% of the global total and recent efforts have been directed towards mapping the extent of peat erosion in Britain from satellites and aircraft. These surveys can detect large changes over the course of decades. In contrast, many studies focus on studying short-term erosion rates at the field scale, using point measurements of erosion. Although recent studies have shown that peat erosion and transport is an important component of the carbon budget, this process is rarely investigated in detail. In general, there are few direct measurements of peat erosion processes.
Recent advances in geomatics present exciting new opportunities by offering unprecedented resolution topographic data. We now have the opportunity to observe mm to cm-scale changes in bare peat surfaces and quantify erosion and carbon loss over small scales. High resolution topographic data contain a wealth of hitherto untapped information; the fine-scale topographic variability acts as a ‘roughness signature’ of the dominant processes operating on peat (demonstrated recently by Smith & Warburton, 2018). By integrating detailed small-scale observations of erosion processes as a connected mosaic within the larger catchment erosion and sediment yield models can be developed.
The aim of this project is to couple event-scale monitoring of surface change using Structure-from-Motion photogrammetry with observations of meteorological and hydrological drivers of that erosion. Using roughness analysis and machine-learning algorithms, the project will identify roughness signatures of peat weathering and erosion processes, thereby attributing volumetric peat and carbon losses to a particular driving process. Finally, for a broader impact, the project will seek to upscale this mechanistic quantification of peat erosion to larger catchment scales to inform and help target future restoration practices.
In this project, you will work with scientists in both the University of Leeds and Durham University with close ties to peatland managers and restoration practitioners of the North Pennines AONB Peatland Programme. The exact nature of the project can be adjusted to suit your individual research interests (including experiments in the environmental laboratory and potentially modelling); however, the studentship will involve the following core objectives:
- To quantify peat erosion volumes and carbon loss estimates at the plot and small catchment scale over a range of surface types;
- To measure fine scale peat topographic roughness using Structure-from-Motion photogrammetry over a range of surface types;
- To establish quantitative ‘roughness signatures’ of different peat surface processes using machine learning techniques;
- To produce the first mechanistic segregation of peat erosion volumes and carbon loss through application of these roughness signatures;
- To upscale these relationships to the management scale and inform targeted peatland restoration campaigns.
While the majority of the research is planned for UK uplands, the methods are transferrable to other areas of eroding peatland and the supervision team has extensive experience studying peatlands worldwide. Furthermore, the members of the supervision team were recently awarded a research grant to investigate geomorphological responses to the Saddleworth Moor wildfires; the successful candidate may wish to interrogate the high spatial and temporal resolution topographic dataset to investigate peatland responses to wildfire and/or investigate any further such fires should they arise.
Minimum 2:1 UK bachelor (honours) degree or equivalent. Applicants from other EU countries will need to meet the University's English language requirements before starting the PhD in October 2019.
How to apply
If you require any further information about the application process, please contact Jacqui Manton.