Forest Resource Projection Tools at the European Level

  • Mart-Jan Schelhaas
  • Gert-Jan Nabuurs
  • Pieter Johannes Verkerk
  • Geerten Hengeveld
  • Tuula Packalen
  • Ola Sallnäs
  • Roberto Pilli
  • Giacomo Grassi
  • Nicklas Forsell
  • Stefan Frank
  • Mykola Gusti
  • Petr Havlik
Part of the Managing Forest Ecosystems book series (MAFE, volume 29)


Many countries have developed their own systems for projecting forest resources and wood availability. Although studies using these tools are helpful for developing national policies, they do not provide a consistent assessment for larger regions such as the European Union or Europe as a whole. Individual national-scale studies differ considerably in timing, underlying methodology and scenarios, and reports are not issued for all countries in the region. However, a clear demand for consistent projections at European scale still remains. This chapter describes the resource simulators and forest sector models EFISCEN, EFDM, CBM-CFS3, and GLOBIOM/G4M that can all be applied to individual European countries, as well as to Europe as a whole.


  1. Böttcher H, Verkerk PJ, Gusti M et al (2012) Projection of the future EU forest CO2 sink as affected by recent bioenergy policies using two advanced forest management models. GCB Bioenergy 4:773–783CrossRefGoogle Scholar
  2. Boudewyn P, Song X, Magnussen S, Gillis MD (2007) Model-based, volume-to-biomass conversion for forested and vegetated land in Canada. Canadian Forest Service, Victoria, Canada (Inf. Rep. BC-X-411) Accessed 20 Sept 2016
  3. Cramer W, Kicklighter DW, Bondeau A et al (1999) Comparing global models of terrestrial net primary productivity (NPP): overview and key results. Glob Chang Biol 5:1–15CrossRefGoogle Scholar
  4. Crouzat E, Mouchet M, Turkelboom F et al (2015) Assessing bundles of ecosystem services from regional to landscape scale: insights from the French Alps. J Appl Ecol 52:1145–1155CrossRefGoogle Scholar
  5. Edwards DM, Jay M, Jensen FS et al (2012) Public preferences across Europe for different forest stand types as sites for recreation. Ecol Soc 17(1):27. doi: 10.5751/ES-04520-170127 CrossRefGoogle Scholar
  6. Eggers T (2002) The impacts of manufacturing and utilisation of wood products on the European carbon budget. European Forest Institute, JoensuuGoogle Scholar
  7. Elbersen B, Staritsky I, Hengeveld GM et al (2012) Atlas of EU biomass potentials. Deliverable 3.3: Spatially detailed and quantified overview of EU biomass potential taking into account the main criteria determining biomass availability from different sources. Biomass Futures Accessed 20 Sept 2016
  8. European Commission (2013) EU energy, transport and GHG emissions: trends to 2050. Scenario, ReferenceGoogle Scholar
  9. FOREST EUROPE (2011) State of Europe’s Forests 2011Google Scholar
  10. FOREST EUROPE (2015) State of Europe’s Forests 2015Google Scholar
  11. Forsell N, Korosuo A, Havlík P et al (2016) Study on impacts on resource efficiency of future EU demand for bioenergy. Task 3: modelling of impacts of an increased EU bioenergy demand on biomass production, use and prices, 109pGoogle Scholar
  12. Frank S, Schmid E, Havlík P et al (2015) The dynamic soil organic carbon mitigation potential of European cropland. Glob Environ Chang 35:269–278CrossRefGoogle Scholar
  13. Global Forest Resources Assessment (2010) Global Forest Resources Assessment, main report. Food and Agricultural Organization of the United Nations, RomeGoogle Scholar
  14. Groen TA, Verkerk PJ, Böttcher H et al (2013) What causes differences between national estimates of forest management carbon emissions and removals compared to estimates of large-scale models? Environ Sci Pol 33:222–232CrossRefGoogle Scholar
  15. Gusti M (2010) An algorithm for simulation of forest management decisions in the global forest model. Artif Intell N4:45–49Google Scholar
  16. Gusti M, Kindermann G (2011) An approach to modeling landuse change and forest management on a global scale. In: Kacprzyk J, Pina N, Filipe J (eds) SIMULTECH-2011. Proceedings of 1st international conference on simulation and modeling methodologies, technologies and applications, Noordwijkerhout, 29–31 July 2011: SciTePress – Science and Technology Publications, Setúbal, pp 180–185Google Scholar
  17. Hanewinkel M, Cullmann DA, Schelhaas MJ et al (2013) Climate change may cause severe loss in the economic value of European forest land. Nat Clim Chang 3:203–207CrossRefGoogle Scholar
  18. Havlík P, Schneider UA, Schmid E et al (2011) Global land-use implications of first and second generation biofuel targets. Energ Policy 39:5690–5702CrossRefGoogle Scholar
  19. Havlík P, Valin H, Herrero M et al (2014) Climate change mitigation through livestock system transitions. Proc Natl Acad Sci 111:3709–3714CrossRefPubMedPubMedCentralGoogle Scholar
  20. Herrero M, Havlík P, Valin H et al (2013) Biomass use, production, feed efficiencies, and greenhouse gas emissions from global livestock systems. Proc Natl Acad Sci 110(52):20888–20893CrossRefPubMedPubMedCentralGoogle Scholar
  21. Kindermann G, Obersteiner M, Sohngen B et al (2008a) Global cost estimates of reducing carbon emissions through avoided deforestation. PNAS 105:10302–10307CrossRefPubMedPubMedCentralGoogle Scholar
  22. Kindermann GE, McCallum I, Fritz S, Obersteiner M (2008b) A global forest growing stock, biomass and carbon map based on FAO statistics. Silva Fenn 42(3):387CrossRefGoogle Scholar
  23. Kindermann G, Schorghuber S, Linkosalo T et al (2013) Potential stocks and increments of woody biomass in the European Union under different management and climate scenarios. Carbon Balance Manag 8:2CrossRefPubMedPubMedCentralGoogle Scholar
  24. Kull S, Kurz WA, Rampley G et al. (2011) Operational-scale carbon budget model of the Canadian Forest Sector (CBM-CFS3) Version 1.2: User’s guide. Canadian Forest Service, Northern Forestry CentreGoogle Scholar
  25. Kurz WA, Apps MJ (1999) A 70-year retrospective analysis of carbon fluxes in the Canadian forest sector. Ecol Appl 9:526–547CrossRefGoogle Scholar
  26. Kurz WA, Dymond CC, White TM et al (2009) CBM-CFS3: a model of carbon-dynamics in forestry and land-use change implementing IPCC standards. Ecol Model 220:480–504CrossRefGoogle Scholar
  27. Lauri P, Havlík P, Kindermann G et al (2014) Woody biomass energy potential in 2050. Energ Policy 66:19–31CrossRefGoogle Scholar
  28. Li Z, Kurz WA, Apps MJ, Beukema SJ (2003) Belowground biomass dynamics in the Carbon Budget Model of the Canadian Forest Sector: recent improvements and implications for the estimation of NPP and NEP. Can J For Res 33:126–136CrossRefGoogle Scholar
  29. Liski J, Palosuo T, Peltoniemi M, Sievänen R (2005) Carbon and decomposition model Yasso for forest soils. Ecol Model 189:168–182CrossRefGoogle Scholar
  30. McCollum D, Krey V, Kolp P et al (2014) Transport electrification: a key element for energy system transformation and climate stabilization. Clim Chang 123(3):651–664CrossRefGoogle Scholar
  31. Meyer J, Vilén T, Peltoniemi M et al. (2005) Uncertainty estimate of the national level biomass and soil carbon stock and stock change. CarboInvent Project Deliverable 6.3Google Scholar
  32. Nabuurs GJ, Schelhaas MJ, Pussinen A (2000) Validation of the European Forest Information Scenario Model (EFISCEN) and a projection of Finnish forests. Silva Fenn 34(2):167–179. CrossRefGoogle Scholar
  33. Nabuurs GJ, Goede DM, Michie B et al (2002) Long term international impacts of nature oriented forest management on European forests – an assessment with the EFISCEN model. J World Forest Resource Manag 9:101–129Google Scholar
  34. Nabuurs GJ, Pussinen A, van Brusselen J, Schelhaas MJ (2007) Future harvesting pressure on European forests. Eur J For Res 126:391–400CrossRefGoogle Scholar
  35. Nabuurs GJ, Schelhaas MJ, Hendriks CMA, Hengeveld GM (2014) Can European forests meet the demands of the bioeconomy in the future? Wood supply alongside environmental services. In: Innes J, Nikolakis W (eds) Forests and globalization: challenges and opportunities for sustainable development. The Earthscan Forest Library, Routledge, Oxon/New-YorkGoogle Scholar
  36. Nilsson S, Sallnäs O, Duinker P (1992) A report on the IIASA forest study: future forest resources of Western and Eastern Europe. The Parthenon Publishing Group, CarnforthGoogle Scholar
  37. Nuutinen T, Kellomäki S (2001) A comparison of three modelling approaches for largescale forest scenario analysis in Finland. Silva Fenn 35(3):299–308CrossRefGoogle Scholar
  38. Oosterbaan A, van den Berg CA, Schelhaas MJ (2007) Ontwikkelingen in vraag en aanbod van rondhout in Nederland en aangrenzend gebied en mogelijke knelpunten en kansen voor de bos- en houtsector in de periode 2005–2025. Alterra rapport 1510, WageningenGoogle Scholar
  39. Packalen T, Sallnäs O, Sirkiä S et al (2014) The European Forestry Dynamics Model: concept, design and results of first case studies. Publications Office of the European Union, EUR 27004. doi: 10.2788/153990 Google Scholar
  40. Pilli R, Grassi G, Kurz WA et al (2013) Application of the CBM-CFS3 model to estimate Italy’s forest carbon budget, 1995–2020. Ecol Model 266:144–171CrossRefGoogle Scholar
  41. 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) – in Italian, with summary in English. Forest@ 11:20–35CrossRefGoogle Scholar
  42. 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 8:410–421CrossRefGoogle Scholar
  43. Pilli R, Grassi G, Kurz WA et al (2016a) Modelling forest carbon stock changes as affected by harvest and natural disturbances. I. Comparison with countries’ estimates for forest management. Carbon Balance Manag 11:5CrossRefPubMedPubMedCentralGoogle Scholar
  44. Pilli R, Grassi G, Kurz WA et al (2016b) Modelling forest carbon stock changes as affected by harvest and natural disturbances II. EU-level analysis. Carbon Balance Manag 11:20CrossRefPubMedPubMedCentralGoogle Scholar
  45. Pussinen A, Nabuurs GJ, Wieggers HJJ et al (2009) Modelling long-term impacts of environmental change on mid- and high-latitude European forests and options for adaptive forest management. Forest Ecol Manag 258:1806–1813CrossRefGoogle Scholar
  46. Reisinger A, Havlik P, Riahi K et al (2013) Implications of alternative metrics for global mitigation costs and greenhouse gas emissions from agriculture. Clim Chang 117(4):677–690CrossRefGoogle Scholar
  47. Sallnäs O (1990) A matrix growth model of the Swedish forest. Stud For Suec 183:1–23Google Scholar
  48. Sallnäs O, Berger A, Räty M, Trubins M (2015) An area-based matrix model for uneven-aged forests. Forests 6:1500–1515. doi: 10.3390/f6051500 CrossRefGoogle Scholar
  49. Särkkä S (2013) Bayesian filtering and smoothing (PDF). Cambridge University Press.
  50. Schelhaas MJ, Eggers J, Lindner M et al. (2007) Model documentation for the European Forest Information Scenario model (EFISCEN 3.1). Alterra report 1559, Wageningen, EFI technical report 26, JoensuuGoogle Scholar
  51. Schelhaas MJ, Hengeveld G, Moriondo M et al (2010) Assessing risk and adaptation options to fires and windstorms in European forestry. Mitig Adapt Strateg 15:681–701. doi: 10.1007/s11027-010-9243-0 CrossRefGoogle Scholar
  52. Schelhaas MJ, Nabuurs GJ, Hengeveld GM et al (2015) Alternative forest management strategies to account for climate change-induced productivity and species suitability changes in Europe. Reg Environ Chang 15:1581–1594CrossRefGoogle Scholar
  53. Stinson G, Kurz WA, Smyth CE et al (2011) An inventory-based analysis of Canada’s managed forest carbon dynamics, 1990 to 2008. Glob Chang Biol 17:2227–2244CrossRefPubMedCentralGoogle Scholar
  54. Takayama T, Judge GG (1971) Spatial and temporal price and allocation models. North-Holland Publishing Company, Amsterdam/LondonGoogle Scholar
  55. UNECE/FAO (1953) European timber trends and prospects. FAO, GenevaGoogle Scholar
  56. UNECE/FAO (2005) European Forest Sector Outlook Study: main report. United Nations, Geneva, ECE/TIM/SP/20Google Scholar
  57. UNECE/FAO (2011). The European Forest Sector Outlook Study II (EFSOS II). 2010–2030. UNECE/FAOGoogle Scholar
  58. Verkerk PJ, Antilla P, Eggers J et al (2011) The realisable potential supply of woody biomass from forests in the European Union. Forest Ecol Manag 261:2007–2015CrossRefGoogle Scholar
  59. Verkerk H, Lindner M, Helming J et al (2014) Identification of pathways to consolidated visions of future land use in Europe. VOLANTE Deliverable 11:3Google Scholar
  60. Zamolodchikov DG, Grabovsky VI, Korovin GN, Kurz WA (2008) Assessment and projection of carbon budget in forests of Vologda Region using the Canadian model CBM-CFS Lesovedenie 6:3–14 (in Russian, with summary in English)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Mart-Jan Schelhaas
    • 1
  • Gert-Jan Nabuurs
    • 1
    • 2
  • Pieter Johannes Verkerk
    • 3
  • Geerten Hengeveld
    • 1
  • Tuula Packalen
    • 4
  • Ola Sallnäs
    • 5
  • Roberto Pilli
    • 6
  • Giacomo Grassi
    • 6
  • Nicklas Forsell
    • 7
  • Stefan Frank
    • 7
  • Mykola Gusti
    • 7
  • Petr Havlik
    • 7
  1. 1.Wageningen Environmental Research (Alterra)WageningenThe Netherlands
  2. 2.Forest Ecology and Forest Management GroupWageningen University and ResearchWageningenThe Netherlands
  3. 3.European Forest InstituteJoensuuFinland
  4. 4.Natural Resources Institute FinlandJoensuuFinland
  5. 5.Swedish University of Agricultural SciencesUpsalaSweden
  6. 6.European Commission, Joint Research Centre, Directorate D – Sustainable Resources – Bio-Economy UnitIspraItaly
  7. 7.International Institute for Applied Systems Analysis (IIASA), Ecosystems Services and Management Program (ESM)LaxemburgAustria

Personalised recommendations