EU Science Hub

The EU Archive Index Database customised for the Carbon Budget Model (CBM-CFS3)

Modelling the forest carbon budget is an essential prerequisite to assess the climate change mitigation impact of different forest management scenarios. For this reason, the JRC has been applying and testing the Carbon Budget Model (CBM-CFS3) of the Canadian Forest Sector, developed by Natural Resources Canada’s (NRCan) Canadian Forest Service (CFS), since 2009.

The CBM-CFS3 is an inventory-based, yield-data-driven model that simulates the stand- and landscape-level carbon (C) dynamics of above- and belowground biomass, dead wood, litter and mineral soil (Kurz et al., 2009).

The model, its user’s guide, and supporting technical documentation are all available free-of-charge online, and technical support and training is available from the CFS. Click here to access NRCan's CBM-CFS3 web page

The model has been adapted and used by the JRC to simulate forest C dynamics in 26 EU Member States (Pilli et al., 2016b). This included modelling specific characteristics of European forests, including, for example, (i) uneven-aged forest management (Pilli et al., 2013); (ii) a large variety of other management systems (e.g. coppice, coppice with standards, shelterwood, etc.), and (iii) the use of national standing volume and annual increment data.

The basic structure of the CBM-CFS3 includes three tools (Kull et al., 2016):

  1. the MAKELIST preprocessing program, used to format the inventory information and initialise the dead organic matter (DOM) pools;
  2. the CBM processing program, used during the simulation period to calculate the C stocks of each pool and spatial unit (SPU) annually, over the simulation period, according to the input data provided by the user;
  3. the Archive Index Database (AIDB), a Microsoft Access database that tracks the relationship between the model inputs and the results, tracks the status of the simulations, and stores all of the default information and parameters applied by model when creating a new project.

Both MAKELIST and the CBM are executable files which process the information provided by the user. The CBM-CFS3 has a user-friendly interface, permitting the user to modify the default (Canadian) data and parameters assigned to a specific project. However, to efficiently apply local data and parameters (i.e. non-default) to all projects that use the model, particularly when it will be applied frequently to forest ecosystems outside of Canada, modifying the content of the AIDB is the best path to follow.

Application and customisation of the Archive Index Database for European Union countries

In addition to preparing model input data reflecting various management and disturbance scenarios for CBM-CFS3 projects, an essential step was to update the original Archive Index Database (AIDB) with information specific to the EU context, and create an EU-AIDB. The EU-AIDB incorporates 1 034 spatial units resulting from the intersection of 204 European administrative regions (defined at the NUTS 1 and NUTS 2 levels for most of the EU countries), and 35 ecological boundaries representing climatic units, as defined by Pilli (2012). It also contains updated parameters for 192 of the main tree species reported by the National Forest Inventories of each EU country. The release of this database ensures a transparent documentation of the parameterisation behind the JRC’s runs with CBM. Furthermore, it provides ecological parameters specific to the EU context, potentially useful for greenhouse gas (GHG) inventory or research communities interested in applying the CBM-CFS3.

/jrc/en/file/archive/172018EU Archive Index Database(EU AIDB)

/jrc/en/file/document/172017Main tables modified in the EU AIDB - Excel file

/jrc/en/file/archive/172020Geographical distribution of the climatic units identified at European level - Shape file

/jrc/en/file/document/177243Volume and Increment Data derived by the CBM Output


Kull SJ, Rampley G, Morken S, Metsaranta J, Neilson ET, Kurz WA (2016) Operational-scale Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) version 1.2: user’s guide. Nat. Resour. Can., Can. For. Serv., North. For. Cent., Edmonton, AB.

Kurz WA, Dymond CC, White TM, Stinson G, Shaw CH, Rampley GJ, Smyth C, Simpson BN, Neilson ET, Trofymow JA, Metsaranta J, Apps MJ (2009) CBM-CFS3: A model of carbon-dynamics in forestry and land-use change implementing IPCC standards. Ecol. Model. 220(4): 480-504.

Pilli R (2012) Calibrating CORINE Land Cover 2000 on forest inventories and climatic data: an example for Italy. Int. J. Appl. Earth Obs. 9: 59-71.

Pilli R, Grassi G, Cescatti A (2014a). Historical analysis and modeling of the forest carbon dynamics using the Carbon Budget Model: an example for the Trento Province (NE, Italy). Forest@, 11: 20-35. (published in Italian with summary in English).

Pilli R, Grassi G, Kurz WA, Smyth CE, Blujdea V (2013) Application of the CBM-CFS3 to estimate Italy’s forest carbon budget, 1995 to 2020. Ecol. Model. 266: 144-171.

Pilli R, Grassi G, Moris JV, Kurz WA (2014b) Assessing the carbon sink of afforestation with the Carbon Budget Model at the country level: an example for Italy. iForest - Biogeosciences and Forestry 8: 410-421.

Pilli R, Grassi G, Kurz WA, Fiorese G, Cescatti A (2017) The European forest sector: past and future carbon budget and fluxes under different management scenarios. Biogeosciences, 14, 2387-2405.

Pilli R, Fiorese G, Grassi G, Abad Viñas R, Rossi S, Priwitzer T, Hiederer R, Baranzelli C, Lavalle C, Grassi G (2016c) LULUCF contribution to the 2030 EU climate and energy policy. EUR 28025, Luxembourg, Publication Office of the European Union.

Pilli R, Grassi G, Kurz WA, Moris JV, Viñas RA (2016b) Modelling forest carbon stock changes as affected by harvest and natural disturbances. II. EU-level analysis. Carbon Balance and Management, 11:20.

Pilli R, Grassi G, Kurz WA, Viñas RA, Guerrero N (2016a) Modelling forest carbon stock changes as affected by harvest and natural disturbances. I. Comparison with countries’ estimates for forest management. Carbon Balance and Management, 11:5.