Developing a statistical methodology for the assessment and management of peatland (StAMP)

Lead Research Organisation: University of Nottingham
Department Name: Faculty of Engineering


In good condition, peatlands are the most efficient carbon store of all soils. They regulate freshwater supply (peatlands are 95% water) and quality, mitigate climate change by storing greenhouse gases, and maintain biodiversity. Land use management interventions (e.g. use of peat for agriculture, drainage, forestry, burning for game management and recreation) can compromise the delivery of all these services by destabilising the vast carbon store that peat has locked away over thousands of years. The UK has 2 Mha of peatlands (10% land area), however, up to 80% of these peatlands are damaged to some degree. It is estimated that degraded UK peatlands emit 10 Mt C a-1, a similar magnitude to oil refineries or landfill sites, placing the UK among the top 20 countries for emissions of carbon from degrading peat.

Restoring degraded peatlands to halt carbon losses is an essential part of a global strategy to fight climate change. However, to date, we do not have a tool to help us assess how land use affects peatland condition in a cost effective manner over large and often remote areas, making it difficult to identify which areas should be prioritised for management intervention. In the UK, several millions of pounds of public money have already been invested in large-scale peatland restoration projects yet we do not have a reliable and robust way to evaluate the effectiveness of restoration. These are important gaps in our knowledge that prevent us from being able to make cost-effective choices when it comes to peatland management

With this project, we will develop new statistical methods to detect change in the condition of peatland landscapes from data collected by satellites. In a previous research project, we showed that peatland condition can be found from satellite data that measures surface motion of the peat. A wet peat in good condition displays very different characteristics to dry peat in poor condition. However, our satellite-based approach produces too much complex data that cannot be reliably and consistently analysed by eye.

We aim to inform peatland management decisions by developing a new statistical method that can robustly and consistently quantify the changes in the peatland landscape from the satellite data. This requires methods capable of handling extremely large and complex structured datasets. In statistics, a new framework, known as Object-Oriented Data Analysis (OODA), is ideally suited to achieve this purpose by building models based on suitable choices of data objects. OODA can be used for developing parsimonious models for detecting change, and for quantifying uncertainty in predictions. OODA of the satellite data as functions of space and time will enable the modelling of trends and variability in the different regions, and the detection of reg change in the peatland.

Our project will develop the OODA method further than its current capabilities and apply this method to the satellite datasets of peat surface motion. The result will be a series of maps that illustrate the change in peatland landscape over time that are designed to be used by land managers and policy makers to guide decision making. This will help reduce unnecessary spending and prioritise the most urgent and strategic areas for peat restoration. Our novel approach combining state-of-the-art statistical methods with satellite data will provide a reliable tool to evaluate investments in peat restoration and report to funding bodies. The ability to quantify changes in the peat landscape using statistics should provide confidence to peatland managers and to those who fund and invest in peatland restoration, enabling them to make better choices for peatlands.

Planned Impact

Peatlands account for a third of Earth's soil carbon and provide a full spectrum of ecosystem services. Globally, they are under pressure from land-use, climate change, and erosion. Carbon losses associated with these disturbances are economically and ecologically costly. Large-scale restoration of peatlands is being implemented globally through industry or government funding, and peatlands feature with increasing prominence in national strategies for biodiversity and greenhouse gas mitigation. However, in all instances, funding, resources and evaluations are limited in their spatial application and therefore, there is a critical and urgent need to develop tools that will aid the cost-effective management of peatland landscapes. The statistical methods, data outputs and provisioning for a decision support tool from this project will address this need and benefit peatland landscape and environmental management via public, private, third sector landowners and regulators in the UK with potential international transfer to global peatlands.
The impacts of this research are:
To provide quantitative statistical evidence of changing peatland condition to support land managers by highlighting which management strategies are most effective and predicting the future impact of land-use decision making. Such quantification will enhance mandatory reports to funding agencies, provide robust justification for continued investment in peatland restoration and encourage joined up thinking between landscape managers.
Supply policy maker, third sector organisations and practitioners with evidence that could support better restoration practices over existing drain blocking, forestry removal, brash management and rewetting programmes.
Influence public policies and legislation at a local, regional, national and international level in relation to peatland management by transforming the current land use decision-process and providing a statistical assessment of the impact of extreme events (e.g. drought) and climate change on peatland landscapes.
Create new knowledge and services that may be attractive to research and development investors from global businesses, especially in the development of satellite products through our project partner (Geomatic Ventures Ltd)
More specifically, key stakeholder groups that this research will impact include:
Peatland owning and management community, including project partner Forest and Land Scotland but also crofters, private landowners, sporting estates.
Policy stakeholders with a direct interest in peatland, including the devolved administrations, agencies such as Scottish Natural Heritage (project partner), SEPA, DEFRA, Climate Change Adaptation Sub-committee, Scottish Forestry.
Third sector organisations with active involvement in peatland management, including landowning NGOs and NGOs that manage and work on peatland-rich areas, including RSPB, PlantLife, John Muir Trust, National Trust.
Water industry (Scottish Water in particular) who need to manage peatland catchments and associated water quality.
World Heritage Site (WHS) working group, facilitating associated businesses in the tourism & recreation sector. Co-I Andersen sits on the WHS working group.
- Public, including youth, with interests in climate change, conservation, biodiversity. This would also include artists with who the research team has interacted in the past to create work informed by the science and inspired by the peatlands.
- Professional Bodies and associations interested in peatlands, including project partner Food and Agriculture Organisation (UN body), Global Peatland Initiative, International Peatland Society. The team has members or key contacts in all these bodies.
Finally, a wide dissemination of our results will contribute to increasing public awareness of the key role of peatlands in climate and water regulation, catalysing environmentally aware attitudes and behavioural change.


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