Application of CORINE land-cover mapping to estimate carbon stored in the vegetation of Ireland

The CORINE land cover database for Ireland (in ARC/INFO) is used to estimate the amount of carbon stored (tonnes) by each land-cover (vegetation) type. Carbon store is the area of each CORINE land-cover type multiplied by its carbon density (t C ha⁻¹). Derivations of these carbon densities are described and limitations of data and other empirical evidence discussed. The total vegetation-carbon stores are calculated for Northern Ireland (3·81 Mt), the Republic of Ireland (19·27 Mt) and Ireland (23·08 Mt). Carbon densities are grouped into classes and their distributions across Ireland are mapped. The vegetation-carbon store is taken to include stems, branches, foliage and roots. It does not include litter, microbial biomass and organic carbon in the soil. Forests store 49% of the vegetation carbon on less than 5% of the total CORINE land area, with a further 22% in other semi-natural vegetation. In contrast, pastures account for 56% of the land-cover area, but only 19% of the carbon store. High carbon densities are found in the west and in uplands, reflecting the distribution of forests and semi-natural vegetation, particularly peatland and moors. The inventory of vegetation-carbon stores is an important first step in attempts to monitor changes in carbon sequestration from, and emissions to, the atmosphere by terrestrial vegetation. Greenhouse gas fluxes, including CO₂, and climate warming are global issues which require responses by all countries. Inventories of carbon stores and fluxes therefore need to be comparable between countries so that agreed reductions can be targetted. CORINE land-cover data are available for 19 European Union and adjacent countries and could be used to provide an inventory of carbon stores, and through updating of CORINE, changes in those stores. Commonality in determining the carbon densities of CORINE classes would be required. This study exemplifies how that was achieved in two countries using their national data.