Skip to main content

Projection Systems in Europe and North America: Concepts and Approaches

  • Chapter
  • First Online:
Forest Inventory-based Projection Systems for Wood and Biomass Availability

Part of the book series: Managing Forest Ecosystems ((MAFE,volume 29))

Abstract

Many scenario analyses have been conducted to assess woody biomass availability, although the variety of projection systems used in different countries makes the comparison of results difficult. Understanding the projection systems used for scenario analysis and their limitations is crucial for better interpretations of results. This chapter presents an analysis of the structure of the projection systems from Europe and North America that are described in the second part of the book. The chapter describes these projection systems in terms of the applicable ranges of the tools, the modelling philosophies and model types, the temporal scales, and the external variables that drive the systems. A detailed description of each projection system is found in Part II.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Alvarez-Marty S (1989) La méthode des générations dans l’étude de la ressource d’une forêt équienne. Afocel-Armef, Informations Forêt 3:135–146

    Google Scholar 

  • Barreiro S, Tomé M (2011) SIMPLOT: simulating the impacts of fire severity on sustainability of eucalyptus forests in Portugal. Ecol Indic 11:36–45

    Article  Google Scholar 

  • Barreiro S, Tomé M (2012) Analysis of the impact of the use of eucalyptus biomass for energy on wood availability for eucalyptus forest in Portugal: a simulation study. Ecol Soc 17(2):14

    Article  Google Scholar 

  • Bento JMRS (1994) Oferta sustentada de material lenhoso de pinheiro bravo – uma aplicação a nível nacional. PhD dissertation Universidade de Trás-os-Montes e Alto Douro, 274 p

    Google Scholar 

  • Burkhart HE, Tomé M (2012) Modeling forest trees and stands. Springer, Dordrecht/New York, 446 p

    Google Scholar 

  • Dixon GE (2002) Essential FVS: a user’s guide to the Forest Vegetation Simulator. Internal Report. US Department of Agriculture, Forest Service, Forest Management Service Center, Fort Collins, 226 p (Revised: November 2, 2015)

    Google Scholar 

  • Eid T, Hobbelstad K (2000) AVVIRK-2000: a large-scale forestry scenario model for long-term investment, income and harvest analyses. Scand J For Res 15:472. doi:10.1080/028275800750172736

    Article  Google Scholar 

  • Franklin JF, Spiesb TA, van Pelta R, Careyc AB, Thornburghd DA, Berge DR, Lindenmayerf DB, Harmong ME, Keetona WS, Shawh DC, Biblea K, Cheni J (2002) Disturbances and structural development of natural forest ecosystems with silvicultural implications, using Douglas-fir forests as an example. For Ecol Manag 155:399–423

    Article  Google Scholar 

  • Garegnani G, Geri F, Zambelli P, et al. (2015) A new open source DSS for assessment and planning of renewable energy: r.green. In: Proceedings of FOSS4G Europe, Como 2015, 14–17 June 2015. Geomatics Workbooks, pp 39–50. ISSN: 1591-092X

    Google Scholar 

  • Hofer P, Altwegg J, Schoop A et al (2011) Holznutzungspotenziale im Schweizer Wald. Auswertung von Nutzungsszenarien und Waldwachstumsentwicklung. Umwelt-Wissen Nr. 1116:80 S. Bundesamt für Umwelt, Bern.

    Google Scholar 

  • Jonsson B (1974) The thinning response of Scots pine (Pinus sylvestris) in northern Sweden. Skogshögskolan, Inst för skogsproduktion, Rapp o upps no 28, 41pp

    Google Scholar 

  • Kaufmann E (2001) Prognosis and management scenarios. In: Brassel P, Lischke H (eds) Swiss national forest inventory: methods and models of the second assessment. Swiss Federal Research Institute (WSL), Birmensdorf, pp 197–206

    Google Scholar 

  • Kaufmann E (2011) Nachhaltiges Holzproduktionspotenzial im Schweizer Wald. Schweiz Z Forstwes 162(9):300–311. doi:10.3188/szf.2011.0300

    Article  Google Scholar 

  • Kimmins JP, Blanco JA, Seely B, Welham C, Scoullar K (2010) Forecasting forest futures: a hybrid modelling approach to the assessment of sustainability of forest ecosystems and their values. Earthscan, London. doi:10.1080/00207233.2011.552232

    Google Scholar 

  • Kindermann G (2010a) Weiterentwicklung eines Kreisflächenzuwachsmodells – Refining a basal area increment model. In: Deutscher Verband Forstlicher Forschungsanstalten Sektion Ertragskunde. Jahrestagung vom 17–19 Mai 2010, Möhnesee, pp 82–95

    Google Scholar 

  • Kindermann G (2010b) Eine klimasensitive Weiterentwicklung des Kreisflächenzuwachsmodells aus PrognAus – A climate sensitive refining of the basal area increment model in PrognAus. Centralblatt für das gesamte Forstwesen. Austrian J For Sci 127(3–4):147–178

    Google Scholar 

  • Kostov G (1993) The Bulgarian Forest Resources Assessment Model – some base data and results. SUAS. Department of Operational Efficiency, College of Forestry, Garpenberg

    Google Scholar 

  • Kramer K, van der Werf DC (2010) Equilibrium and non-equilibrium concepts in forest genetic modelling: population- and individually-based approaches. For Syst 19:100–112. doi:10.5424/fs/201019S-9312

    Google Scholar 

  • Kramer K, Degen B, Buschbom J, Hickler J, Thuiller W, Sykes MT, Winter WD (2010) Modelling exploration of the future of European beech (Fagus sylvatica L.) under climate change--range, abundance, genetic diversity and adaptive response. For Ecol Manag 259:2213–2222. doi:10.1016/j.foreco.2009.12.023

    Article  Google Scholar 

  • Kull SJ, Rampley GJ, Morken S et al (2011) Operational-scale carbon budget model of the Canadian forest sector (CBM-CFS3) version 1.2: user’s guide. Canadian Forest Service, Edmonton

    Google Scholar 

  • 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 220:480–504

    Article  Google Scholar 

  • Landsberg J (2003) Modelling forest ecosystems: state of the art, challenges, and the future directions. Can J For Res 26:1174–1186

    Google Scholar 

  • Ledermann T (2006) Description of PrognAus for Windows 2.2. In: Hasenauer H (ed) Sustainable forest management – growth models for Europe. Springer, Berlin/Heidelberg, pp 71–78

    Google Scholar 

  • Liski J, Palosuo T, Peltoniemi M, Sievänen R (2005) Carbon and decomposition model Yasso for forest soils. Ecol Model 189:168–182. doi:10.1016/j.ecolmodel.2005.03.005

    Article  CAS  Google Scholar 

  • Lundström A, Söderberg U (1996) Outline of the Hugin system for long-term forecasts of timber yields and possible cut. In: Päivinen R, Roihuvuo L, Siitonen M (eds) Proceedings no. 5: in large-scale forestry scenario models: experiences and requirements. European Forest Institute, Joensuu, pp 63–77

    Google Scholar 

  • Mäkelä A (2009) Hybrid models of forest stand growth and production. In: Dykstra DP, Monserud RA (eds) Forest growth and timber quality: crown models and simulation methods for sustainable forest management. Proceedings of an international conference. U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, Portland, pp 43–47

    Google Scholar 

  • McMahan AJ, Milner KS, Smith EL (2002) FVS-BGC: a process-model extension to the Forest Vegetation Simulator. U.S. Department of Agriculture, Forest Service, Forest Health Technology Enterprise Team, Fort Collins, 51p

    Google Scholar 

  • Medema EL, Hatch CR (1982) Computerized help for economic analysis of Prognosis Model outputs: a user’s manual. Contribution no. 227. University of Idaho, Forest, Wildlife, and Range Experiment Station, Moscow, 72 p

    Google Scholar 

  • Milner KS, Coble DW (1995) The ground surface vegetation model: a process-based approach to modeling vegetative interactions. Unpublished manuscript

    Google Scholar 

  • Monserud RA (2003) Evaluating forest models in a sustainable forest management context. FBMIS 1:35–47

    Google Scholar 

  • Munro D (1974) Forest growth models – a prognosis. In: Fries J (ed) Growth models for tree and stand simulation. Royal College of Forestry Res Notes 30, Stockholm, pp 7–21

    Google Scholar 

  • Nord-Larsen T, Suadicani MK (2010) Træbrændselsressourcer fra danske skove over ½ ha: opgørelse og prognose 2010. Skov & Landskab, Københavns Universitet. Arbejdsrapport / Skov & Landskab, no. 113

    Google Scholar 

  • Peng C (2000) Growth and yield models for uneven-aged stands: past, present and future. For Ecol Manag 132:259–279

    Article  Google Scholar 

  • Perera AH, Sturtevant BR, Buse LJ (2015) Simulation modeling of forest landscape disturbances: an overview. In: Perera AH, Sturtevant BR, Buse LJ (eds) Simulation modeling of forest landscape disturbances. Springer, Geneva, pp 1–15

    Chapter  Google Scholar 

  • Petrauskas E, KulieÅ¡is A (2004) Scenario-based analysis of possible management alternatives for Lithuanian forests in the 21st century. Balt For 10:72–82

    Google Scholar 

  • Phillips H (2011) All Ireland roundwood production forecast 2011–2028. COFORD, Dublin

    Google Scholar 

  • 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 266:144–171

    Article  CAS  Google Scholar 

  • Redsven V, Hirvelä H, Härkönen K, Salminen O, Siitonen M (2013) MELA2012 reference manual, 2nd edn. The Finnish Forest Research Institute. ISBN: 978-951-40-2451-1

    Google Scholar 

  • Reed D (1999) Ecophysiological models of forest growth: uses and limitations. In: Amaro A, Tomé M (eds) Empirical and process based models for forest tree and stand growth simulation. Edições Salamandra, Novas Tecnologias, Lisboa, pp 305–311

    Google Scholar 

  • Reed DD, Amaro A, Amateis R, Huang S, Tomé M (2003) Emerging trends and future directions: a workshop synthesis. In: Amaro A, Reed D, Soares P (eds) Modelling forest systems. CAB International, Oxford, pp 389–394

    Google Scholar 

  • Rennolls K, Tomé M, McRoberts RE, Vanclay JK, LeMay V, Guan BT, Gertner GZ (2007) Potencial contributions of statistics and modelling to sustainable forest management: review and synthesis. In: Reynolds KM, Thomson AJ, Kohl M, Shannon MA, Ray D, Rennolls K (eds) Sustainable forestry: from monitoring and modeling to knowledge management & policy science. CABI, Wallingford/Cambridge, pp 314–341

    Chapter  Google Scholar 

  • Rock J, Bösch B, Kändler G (2013). WEHAM 2012 – Waldentwicklungs- und Holzaufko-mmensmodellierung für die dritte Bundeswaldinventur. In: Klädtke J, Kohnle U (eds) Deutscher Verband Forstlicher Forschungsanstalten. Sektion Ertragskunde. Jahrestagung, Rychnov nad Kneznou/Tschechien, pp 127–133. ISSN: 1432-2609. http://sektionertragskunde.fvabw.de/2013/Beitrag_13_17.pdf. Accessed 14 May 2016

  • Sallnäs O (1990) A matrix growth model of the Swedish forest. Studia Forestalia Suecica. Sveriges lantbruksuniversitet, Uppsala. ISBN: 91-576-4174-9

    Google Scholar 

  • Schelhaas MJ, Eggers J, Lindner M, Nabuurs GJ, Pussinen A, Päivinen R, Schuck A, Verkerk PJ, van der Werf DC, Zudin S, (2007) Model documentation for the European Forest Information Scenario model (EFISCEN 3.1.1). Wageningen, Alterra, Alterra report 1559, EFI technical report 26, Joensuu, 118p. http://www.efi.int/files/attachments/publications/alterrarapport1559.pdf. Accessed 5 July 2015

  • Siitonen M, Härkönen K, Hirvelä H, Jämsä J, Kilpeläinen H, Salminen O, Teuri M (1996) MELA Handbook—1996 edn. Metsäntutkimuslaitoksen tiedonantoja 622, p 452

    Google Scholar 

  • Snorrason A (2006) Langtímaspá um kolefnisbindingu nýskógræktar. Skógræktarritið 58–64 (in Icelandic)

    Google Scholar 

  • Stage AR (1973) Prognosis Model for stand development. Res. Paper INT-137. U. S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station, Ogden, 32p

    Google Scholar 

  • Sterba H, Moser M, Monserud RA (1995) PROGNAUS – Ein Waldwachstumssimulator für Rein- und Mischbestände. Österreichische Forstzeitung 106(5):19–20

    Google Scholar 

  • Thürig E, Palosuo T, Bucher J, Kaufmann E (2005) The impact of windthrow on carbon sequestration in Switzerland: a model-based assessment. For Ecol Manag 210:337–350. doi:10.1016/j.foreco.2005.02.030

    Article  Google Scholar 

  • Tomé M, Faias S (2011) Report describing the regional simulators and the European simulator. EFI Technical Report 69. European Forest Institute, Finland, 65pp

    Google Scholar 

  • Vanclay JK (1994) Modelling forest growth and yield – applications to mixed tropical forests. CAB International, Oxon

    Google Scholar 

  • Wernsdörfer H, Colin A, Bontemps J-D, Chevalier H, Pignard G, Caurla S, Leban J-M, Herve J-C, Fournier M (2012) Large scale dynamics of a heterogeneous forest resource are driven jointly by geographically varying growth conditions, tree species composition and stand structure. Ann For Sci 69:829–844

    Article  Google Scholar 

  • Wilson FG (1946) Numerical expression of stocking in term of height. J For 44(10):758–761

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Susana Barreiro .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this chapter

Cite this chapter

Barreiro, S., Tomé, M. (2017). Projection Systems in Europe and North America: Concepts and Approaches. In: Barreiro, S., Schelhaas, MJ., McRoberts, R., Kändler, G. (eds) Forest Inventory-based Projection Systems for Wood and Biomass Availability. Managing Forest Ecosystems, vol 29. Springer, Cham. https://doi.org/10.1007/978-3-319-56201-8_3

Download citation

Publish with us

Policies and ethics