Overview

Project Highlights:

  • Will contribute to addressing significant knowledge gaps in tropical peatland geochemistry and contemporary functioning for a large, newly discovered peatland in the Congo Basin; opportunity for field work.
  • Multi-disciplinary supervisory team, including with British Geological Survey; all supervisors have a strong publication track record in high impact journals.
  • Opportunity to gain training and experience of a range of cutting-edge field, analytical and data synthesis techniques.

Tropical peatlands are dense, long-term stores of carbon (C) that are vital components of global C soil-atmosphere exchange processes. They contain ~130 Gt C (20% of global peat C; Page et al. 2011, Dargie et al. 2017) but are very vulnerable to destabilisation through human- and climate-induced changes, including deforestation, drainage, drought and fire, which enhance peat oxidation and convert long- term CO2 sinks into globally significant CO2 sources. The peatlands of the Cuvette Centrale in the Congo Basin have only recently been discovered; they are the largest peatland complex in the tropics, occupying some 145,500 km2, an area slightly larger than England, and storing 30.6 Pg C (Dargie et al. 2017). These peatlands appear to form shallow domes with a well-marked zonation of different vegetation types from dome edge to centre. Controls on peat and carbon accumulation rates will likely depend on factors that limit the decomposition rates of organic matter, i.e. waterlogging, low pH, as well as those that limit the availability of resources for decomposer microorganisms, i.e. poor quality plant litter, deficiency of nutrient elements. Initial measurements indicate that Congo peats have a higher C density than other tropical peats, possibly due to low net accumulation rates, and indicating that these peatlands may be vulnerable to even modest changes in environmental conditions that could cause the system to transition from a C sink to a C source. This project will investigate surface peat and peat water geochemistry in relation to vegetation, hydrology and geomorphological setting in order to explore the relative importance of environmental controls on peat formation, decomposition and contemporary ecosystem functioning, including production of greenhouse gases (CO2, CH4). A range of geochemical techniques could be employed (including stable isotopes and organic geochemical analyses). The data will provide an improved knowledge of the controls on peat and GHG production rates, as well as delivering inputs for parameterisation of models of peatland development, and the formulation of practical and policy-focused measures aimed at ensuring responsible peatland management.

 

Location of the Cuvette peatlands. They are estimated to have a peat carbon store of 30 Gt (billion tonnes)  (image source: Nature)

Methodology

Samples for this project are available and additional samples can be collected as part of our ongoing Large NERC grant; CongoPeat, Past, Present and Future of the Peatlands of the Central Congo Basin (see: https://congopeat.net)

The proposed methodology is based on well-established organic geochemical procedures. We will study the nature of the organic matter using pyrolysis gas chromatography mass spectrometry (py- GC/MS), RockEval and Fourier transform infra red (FTIR) spectroscopy. This will result in detailed knowledge of the structure of the organic matter and will allow us to explore the driving factors behind spatial variation. In order to further understand biogeochemical processes such as methane oxidation we will extract lipids, which we will analyse using GC/MS and compound specific stable isotope measurements.

Training and Skills

The student will acquire a wide range of biogeochemical, hydrological, ecological and modelling skills, including the possibility for field work in a tropical setting. They will gain training and experience of research design and planning, writing peer-reviewed articles and presenting at conferences. They will benefit from a collaboration with the BGS, where additional training in complementary techniques can be obtained. Research objectives will be met using a mix of fieldwork, physical and chemical analyses, including cutting edge geochemical techniques, and modelling. The student will benefit from joining a multidisciplinary team with a strong track record of publication and end-user engagement.

Timeline

Year 1: Undertake literature searches; define research plan & research questions; undertake basic research training; research and define methodologies; design analytical framework; visit field sites; carry out a relevant work placement (e.g. with a knowledge end-user organisation).

Year 2: Undertake range of analyses to provide initial results; carry out data analysis and interpretation; use models as a framework for data interpretation; undertake iterative changes to research design, as required, and design additional analyses to address follow-on questions. Present initial results at a conference.

Year 3: Complete research programme, data collection, analysis and modelling; start writing research chapters & first journal paper; present results at an international conference; complete thesis.

Partners and collaboration (including CASE)

The student will be part of the NERC funded Congo Peat NERC-funded CongoPeat project (2018-2023) research community and will attend project seminars and meetings. The research will be a carried out in close collaboration with the scientists collaborating on the project and, in particular, with Dr Sofie Sjogersten and Dr Nick Girkin at the University of Nottingham and our external partner Dr. Chris Vane from the BGS. The student will also interact with other field scientists (UK and international) who are using the same study sites, e.g. to investigate the developmental history of the Congo peatlands.

Further Details

Contact details: Prof Susan Page (sep5@le.ac.uk); Dr Arnoud Boom (ab269@le.ac.uk), both in School of Geography, Geology & the Environment, University of Leicester (https://www2.le.ac.uk/departments/geoggeolenv)