Improving National forest inventory-based carbon stock change estimates for greenhouse gas inVENTories
Forest land in Europe annually sequesters atmospheric carbon comparable to the emissions from the agricultural or industrial process sectors. Despite its importance, the full potential of carbon sequestration on forest land in climate change mitigation strategies is not utilized. In large part, this is due to the high uncertainty of carbon stock change estimates of living biomass and forest mineral soil using current national-level methods. New estimation methods, which increase the spatial resolution of estimates by incorporating existing auxiliary data sources, are required to further mobilize the mitigation potential of forest land in Europe. INVENT will use national forest inventory, spatially-explicit remote sensing, and local forest harvest data to increase the precision and spatial resolution of living biomass estimates. INVENT will use forest and soil inventory data, spatially-explicit remote sensing data, and modeling procedures to increase the accuracy and spatial resolution of forest mineral soil carbon stock change estimates. INVENT will apply the developed methods to quantify the effects of forest mitigation measures at the national and sub-national scales. The derived methods and their application will be demonstrated in national greenhouse gas inventories and in case-studies that strengthen the trans-national exchange of knowledge within the consortium countries of Denmark, Latvia, Norway, and Sweden. The results will demonstrate the general applicability of the derived methods to reduce the uncertainty in living biomass and forest mineral soil carbon estimates in greenhouse gas reporting on forest land.
Norwegian Institute of Bioeconomy Research (NIBIO), Norway
Prof. Lise Dalsgaard
Latvian State Forest Research Institute (SILAVA), Latvia University of Copenhagen (UCPH), Denmark Swedish University of Agricultural Sciences, Sweden
Total requested funding
NEWS from INVENT
A study showing that estimates of land-use categories (activity data) can be considerably improved when using national maps in addition to national forest inventory (NFI) data (preprint: https://arxiv.org/abs/2004.07503) was recently submitted. Another INVENT study on the improvement of activity data is already published (https://doi.org/10.15159/AR.19.195)
The INVENT-project was represented at the EGU2020 (#shareEGU20) with the poster “Predicting the spatial distribution of soil organic carbon stock in Swedish boreal forest using remotely sensed and site-specific variables”.
The soil carbon model Yasso is now supplemented with Latvian above ground litter input data for birch, pine, and spruce. These data will be integrated in forest growth model AGM, which is used in elaboration of GHG projections including the National Forest Reference Level. Publications on this and further INVENT results are currently in the making.