Dr. Matthew Saunders

The primary objective of this project is to develop an inter-disciplinary approach to assess the impact of anthropogenic management of peatlands, through drainage and land use conversion, on carbon and greenhouse gas emissions. This project will utilise high-resolution hyperspectral and Copernicus Sentinel-2 satellite based imagery to identify peatland land use and drainage extent, and combine this information with land-atmosphere and fluvial C/GHG emission measurements to derive a habitat condition and peatland drainage map that can be aligned to a GHG emission factor.

Population growth, demographic shifts, climate change and the need for increased food production are placing new and increased pressures and demands on our natural resources, highlighting the need for adopting more sustainable life-styles. Now, more than ever, we need high-quality, timely information about our farms, forests, natural wetlands and cities in order to better understand the interdependencies and interactions between the human activities and natural processes that create these complex environments. Terrain-AI will tackle this challenge through the innovative fusion of multi-thematic data-sources captured from spaceborne satellites, aerial/drone platforms, in-field instruments, in-situ sensor networks and mobile devices with existing databases, on land use and population, using highly automated Machine Learning workflows to extract terrestrial features, patterns and processes " essential to understanding and managing these environments. Integrated land-surface models, capable of handling uncertainty, will utilise these AI outputs together with land-cover type, biomass and environmental variables to produce improved estimates of Carbon Stocks and Exchanges. The big research opportunity here is building a state-of-the-art digital terrestrial monitoring and modelling platform based on Terrain-AI"s 14 instrumented real-world test-sites together with the latest Earth Observation, Robotics and Sensing technologies that will enable the collaborative research and development of scalable ML and integrated modelling workflows with a team of over 45 dedicated research specialists. There are big commercial and societal opportunities including, developing next generation digital Agri-tech products and services through to making real changes in how we manage Carbon on our farms, forests, peatlands and urban spaces, in support of sustainable land use.

Agriculture contributes over one-third of national greenhouse gas (GHG) emissions, with the majority arising from livestock production. Both Food Wise 2025 and Origin Green initiatives aim to simultaneously increase agricultural production, whilst also reducing the carbon footprint and enhancing sustainability associated with that production. Conversely EU Climate and Energy Framework targets require a 30% reduction in emissions. Carbon (C) sequestration associated with pastures and improved grassland management could provide a mitigation option without impacting on agricultural production. In addition, improved soil carbon should lead to better nutrient cycling and soil nutrient availability. More accurate quantification of C sequestration in grasslands is essential to allow reporting to Tier 2 and 3 levels and to provide information that allows for both effective reduction and mitigation of C emissions at both the field and national level. Management practices that can increase SOC stocks to mitigate climate change will provide the basis for inclusion of grassland soils into both carbon trading schemes and LCA's, which will assist the sector both in terms of carbon credits and a reduced carbon footprint on agricultural produce. This project will integrate with various other projects quantifying and/or modelling C and nitrogen (N) processes to provide costed toolkit of potential management of C associated with grasslands.

Peatlands are distinctive ecosystems that develop at the interface between terrestrial and aquatic biospheres, they cover only between 2-6% of the earth's surface but play a significant role in global carbon (C), water and greenhouse gas (GHG) dynamics1,2. These ecosystems store approximately 15 x 102 Pg of C representing ~33% of the global soil C pool1,3, and contribute up to 30% of the global methane (CH4) emissions4, which has a global warming potential 26 times greater than carbon dioxide (CO2) over a 100-year timeframe. In Ireland, peatlands cover between 14-20% of the land area and sequester an estimated 72,000 t C yr-1, however much of this area has been modified by anthropogenic activities such as extraction for energy, horticulture or domestic purposes or through drainage for agriculture or forestry5. Such land management activities have significant implications for the C sequestration potential and GHG dynamics of these ecosystems, and the restoration of degraded areas is required to enhance the C sink strength of these ecosystems and further offset national GHG emissions. Of particular national significance is the occurrence of peat-forming raised bogs, such as Clara Bog, Co Offaly, an annex II habitat under the EU Habitats Directive (92/43/EEC), which while degraded is one of the best examples of active raised bog in Western Europe. Restoration activities are currently underway at Clara as part of a NPWS EU-funded LIFE project, and this project will enhance this work by investigating the impacts of peatland restoration on the C and GHG dynamics of this ecosystem.

Nitrous oxide emissions comprise over one-third of all agricultural emissions, with the majority arising from livestock production. Both Food Wise 2025 and Origin Green initiatives aim to simultaneously increase agricultural production, whilst also reducing the carbon footprint and enhancing sustainability associated with that production. Conversely EU Climate and Energy Package targets require reductions in absolute emissions. Current nitrous oxide mitigation research attempts to reduce N2O emissions via various means which may increase other reactive N losses (from leached N or ammonia volatilisation). Converting excess soil N to N2 (via the process of total and co-denitrification) offers the prospect of diverting excess N away from environmentally damaging N forms (N2O, NH3, NO3-) to environmentally benign N2. In addition, most N2O research is principally focussed on manipulation at the plot scale, with little or no temporal or spatial verification of measures. This makes verifying the carbon and nitrogen footprint of farms use default emission factors difficult, with no empirical verification of these emissions.