Abstract

National Forest Inventories (NFIs) provide quantitative information on forest area, volume, growing stock and composition at national level but in most cases these data cannot be directly linked with geographical or climatic data sources, such as temperature and precipitation. Assuming that NFIs represent the most useful source of data to evaluate area, volume, age class distribution and composition of forests, the objective of this work was to combine these data with the geo-referenced data provided by CORINE (Coordination of Information on the Environment) and with other data on local climatic conditions. This is a necessary prerequisite for a long-term project aimed at the application of a full carbon accounting approach at European level. The approach was applied to the Italian NFI, assumed as a representative example at European level.Maps of temperature and precipitation classes were projected over a CORINE map and over the Italian administrative units defined at Nuts 2 level. The resulting combinations of precipitation and mean temperature values were used to define 24 climatic land units (CLUs). The results were validated against data provided by 111 weather stations in 3 different administrative regions.The proportion of NFI forest area associated with each CLU at regional level, divided into broadleaved, coniferous and mixed forests, was estimated on the basis of CORINE data.Because this approach maintained all the information reported by NFI linking them to climatic data, both the final forest area and the distribution of forest types at national level were also maintained, avoiding any inconsistency with data directly provided by CORINE. This also ensured full consistency with the forest threshold parameters applied at national level and with the application of these data to international reporting documents (i.e. the UNFCCC report on LULUCF).The approach can easily be applied to every other European country, linking data reported by NFI with other land use geo-referenced data and with climatic data. In the meantime, maintaining the supra-national classification system proposed by CORINE, the results could be more consistently compared across national borders.

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