Evolving Integrated Models From Narrower Economic Tools: the Example of Forest Sector Models


Integrated simulation models are commonly used to provide insight on the complex functioning of social-ecological systems, often drawing on earlier tools with a narrower focus. Forest sector models (FSM) encompass a set of simulation models originally developed to forecast economic developments in timber markets but now commonly used to analyse climate and environmental policy. In this paper, we document and investigate this evolution through the prism of the inclusion of several non-timber objectives into FSM. We perform a systematic, quantitative survey of the literature followed by a more in-depth narrative review. Results show that a majority of papers in FSM research today focuses on non-timber objectives related to climate change mitigation, namely carbon sequestration and bioenergy production. Habitat conservation, deforestation and the mitigation of disturbances are secondary foci, while aspects such as forest recreation and many regulation services are absent. Non-timber objectives closest to the original targets of FSM, as well as those for which economic values are easier to estimate, have been more deeply integrated to the models, entering the objective function as decision variables. Others objectives are usually modelled as constraints and only considered through their negative economic impacts on the forest sector. Current limits to a deeper inclusion of non-timber objectives include the models’ ability to represent local environmental conditions as well as the formulation of the optimisation problem as a maximisation of economic welfare. Recent research has turned towards the use of model couplings and the development of models at the local scale to overcome these limitations. Challenges for future research comprise extensions to other non-timber objectives, especially cultural services, as well as model calibration at lower spatial scales.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3


  1. 1.

    A co-occurrence link is formed between two keywords when they appear in the same publication. The more often keywords appear together, the stronger the link. Keywords and links are then represented on a network where distances between items indicate their level of relatedness, and items are further separated into clusters. Keywords whose spelling varies across publications are merged using a thesaurus.

  2. 2.

    A journal can belong to several categories, e.g., Forest Policy and Economics appears in both the agricultural and biological sciences and economics, econometrics and finance categories.

  3. 3.

    In some cases, all carbon sequestered is subsidized, and the \( {\Delta C}_t^{BAU} \) term equals 0.


  1. 1.

    Masson-Delmotte, V., et al. (2018). Global warming of 1.5°C an IPCC special report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty summary for policymakers edited by Science Officer Science Assistant Graphics Officer Working Group I Technical Support Unit. Geneva.

  2. 2.

    J. Rogelj et al., “Mitigation pathways compatible with 1.5°C in the context of sustainable development,” in Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, [Masson-Delmotte, S. C. V., P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, and and T. W. (eds. . J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, Eds. In press, 2018.

  3. 3.

    S. Diaz et al., “Summary for policymakers of the global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services-Advance Unedited Version-Members of the management committee who provide,” 2019.

    Google Scholar 

  4. 4.

    Hamilton, S. H., Elsawah, S., Guillaume, J. H. A., Jakeman, A. J., & Pierce, S. A. (2015). Environmental modelling & software integrated assessment and modelling : overview and synthesis of salient dimensions. Environmental Modelling and Software, 64, 215–229.

    Google Scholar 

  5. 5.

    Van Delden, H., Seppelt, R., White, R., & Jakeman, A. J. (2011). A methodology for the design and development of integrated models for policy support. Environmental Modelling and Software, 26(3), 266–279.

    Google Scholar 

  6. 6.

    Harris, G. (2002). Integrated assessment and modelling : an essential way of doing science 1. Environmental Modelling and Software, 17, 201–207.

    Google Scholar 

  7. 7.

    Aznar-Sánchez, L. J., Belmonte-Ureña, J. A., López-Serrano, M. J., & Velasco-Muñoz, J. F. (2018). Forest ecosystem services: an analysis of worldwide research. In forests (Vol. 9, pp. 1–19).

    Google Scholar 

  8. 8.

    Tian, H., Lu, C., Yang, J., Banger, K., Huntzinger, D. N., Schwalm, C. R., Michalak, A. M., Cook, R., Ciais, P., Hayes, D., Huang, M., Ito, A., Jain, A. K., Lei, H., Mao, J., Pan, S., Post, W. M., Peng, S., Poulter, B., Ren, W., Ricciuto, D., Schaefer, K., Shi, X., Tao, B., Wang, W., Wei, Y., Yang, Q., Zhang, B., & Zeng, N. (2015). Global patterns and controls of soil organic carbon dynamics as simulated by multiple terrestrial biosphere models: current status and future directions. Global Biogeochemical Cycles, 29(6), 775–792.

    CAS  Google Scholar 

  9. 9.

    Sedjo, R. A., & Sohngen, B. (2012). Carbon sequestration in forests and soils. Ssrn.

  10. 10.

    Eriksson, E., et al. (2007). Integrated carbon analysis of forest management practices and wood substitution. Canadian Journal of Forest Research, 37(3), 671–681.

    CAS  Google Scholar 

  11. 11.

    Sjølie, H. K., & Solberg, B. (2011). Greenhouse gas emission impacts of use of Norwegian wood pellets: a sensitivity analysis. Environmental Science & Policy, 14(8), 1028–1040.

    Google Scholar 

  12. 12.

    Sturrock, R. N., et al. (2011). Climate change and forest diseases. Plant Pathology, 60(1), 133–149.

    Google Scholar 

  13. 13.

    Broadmeadow, S., & Nisbet, T. R. (2010). The effects of riparian forest management on the freshwater environment: a literature review of best management practice. Hydrology and Earth System Sciences, 8(3), 286–305.

    Google Scholar 

  14. 14.

    Milcu, A. I., Hanspach, J., Abson, D., & Fischer, J. (2013). Cultural ecosystem services: a literature review and prospects for future research. Ecology and Society, 18(3), art44.

    Google Scholar 

  15. 15.

    Hernández-Morcillo, M., Plieninger, T., & Bieling, C. (2013). An empirical review of cultural ecosystem service indicators. In Ecological Indicators (Vol. 29, pp. 434–444). Amsterdam: Elsevier.

    Google Scholar 

  16. 16.

    Hanewinkel, M., Hummel, S., & Albrecht, A. (2011). Assessing natural hazards in forestry for risk management: a review. European Journal of Forest Research, 130(3), 329–351.

    Google Scholar 

  17. 17.

    Garcia, S., Abildtrup, J., & Stenger, A. (2018). How does economic research contribute to the management of forest ecosystem services? Annals of Forest Science, 75(2), 53.

    Google Scholar 

  18. 18.

    Duncker, P., et al. (2012). How forest management affects ecosystem services, including timber production and economic return: synergies and trade-offs. Ecology and Society, 17(4), art50.

    Google Scholar 

  19. 19.

    FAUSTMANN and M., “Berechnung des Werthes, welchen Waldboden, sowie noch nicht haubare Holzbestande fur die Waldwirthschaft besitzen [Calculation of the value which forest land and immature stands possess for forestry],” Allg. Fotst- und Jagd-Zeitung, vol. 25, pp. 441–455, 1849.

  20. 20.

    R. Hartman, “The harvesting decision when a standing forest has value,” Econ. Inq., vol. XIV, no. March, pp. 52–58, 1976.

  21. 21.

    Tardieu, L. (2017). The need for integrated spatial assessments in ecosystem service mapping. Rev. Agric. Food Environ. Stud., 98(3), 173–200.

    Google Scholar 

  22. 22.

    Maes, J., et al. (2012). Mapping ecosystem services for policy support and decision making in the European Union. Ecosystem Services, 1(1), 31–39.

    Google Scholar 

  23. 23.

    L. Diaz-Balteiro and C. Romero, “Making forestry decisions with multiple criteria: a review and an assessment,” Forest Ecology and Management, vol. 255, no. 8–9. Elsevier, Amsterdam, pp. 3222–3241, 2008.

  24. 24.

    Uhde, B., Hahn, A., Griess, V. C., & Knoke, T. (2015). Hybrid MCDA methods to integrate multiple ecosystem services in forest management planning: a critical review. Environmental Management, 56(2), 373–388.

    Google Scholar 

  25. 25.

    Buchy, M., & Hoverman, S. (2000). Understanding public participation in forest planning: a review. Forest Policy and Economics, 1(1), 15–25.

    Google Scholar 

  26. 26.

    A. Ficko, G. Lidestav, Á. Ní Dhubháin, H. Karppinen, I. Zivojinovic, and K. Westin, “European private forest owner typologies: a review of methods and use,” Forest Policy and Economics, vol. 99. Elsevier, pp. 21–31, 01-Feb-2019.

  27. 27.

    Adams, D. M., & Haynes, R. W. (2007). Resource and market projections for forest policy development: twenty-five years of experience with the U.S. RPA timber assessment. Berlin: Springer.

    Google Scholar 

  28. 28.

    Latta, G. S., Sjolie, H. K., & Solberg, B. (2013). A review of recent developments and applications of partial equilibrium models of the forest sector. Journal of Forest Economics, 19(4), 350–360.

    Google Scholar 

  29. 29.

    Northway, S., Bull, G. Q., & Nelson, J. D. (2013). Forest sector partial equilibrium models: processing components. Forest Science, 59(2), 151–156.

    Google Scholar 

  30. 30.

    Buongiorno, J. (2014). Global modelling to predict timber production and prices: the GFPM approach. Forestry, 88(3), 291–303.

    Google Scholar 

  31. 31.

    Toppinen, A., & Kuuluvainen, J. (2010). Forest sector modelling in Europe-the state of the art and future research directions. Forest Policy and Economics, 12(1), 2–8.

    Google Scholar 

  32. 32.

    Solberg, B. (1986). Forest sector simulation models as methodological. Silva Fennica, 20(4), 419–427.

    Google Scholar 

  33. 33.

    Lobianco, A., Delacote, P., Caurla, S., & Barkaoui, A. (2016). Accounting for active management and risk attitude in forest sector models an impact study on French forests. Environmental Modeling and Assessment, 21, 391–405.

    Google Scholar 

  34. 34.

    H. K. Sjølie, G. S. Latta, T. Gobakken, and B. Solberg, “NorFor - a forest sector model of Norway model overview and structure,” INA fagrapport 18. Department of Ecology and Natural Resource Management Norwegian University of Life Sciences. 2011.

  35. 35.

    C. Johnston and G. C. van Kooten, “Modelling bi-lateral forest product trade flows : experiencing vertical and horizontal chain,” no. August, 2014.

  36. 36.

    Kallio, A. M. I., Anttila, P., McCormick, M., & Asikainen, A. (2011). Are the Finnish targets for the energy use of forest chips realistic-assessment with a spatial market model. Journal of Forest Economics, 17(2), 110–126.

    Google Scholar 

  37. 37.

    W. F. Mustapha, E. Trømborg, and T. F. Bolkesjø, “Forest-based biofuel production in the Nordic countries: modelling of optimal allocation,” For. Policy Econ., no. September 2016, pp. 1–10, 2017.

  38. 38.

    Caurla, S., Delacote, P., Lecocq, F., Barthès, J., & Barkaoui, A. (2013). Combining an inter-sectoral carbon tax with sectoral mitigation policies: impacts on the French forest sector. Journal of Forest Economics, 19(4), 450–461.

    Google Scholar 

  39. 39.

    D. Adams, B. A. Mccarl, and B. C. Murray, “FASOMGHG conceptual structure, and specification: documentation,” 2005.

    Google Scholar 

  40. 40.

    Hänninen, R., & Kallio, A. M. I. (2007). Economic impacts on the forest sector of increasing forest biodiversity conservation in Finland. Silva Fenn., 41(3), 507–523.

    Google Scholar 

  41. 41.

    Rafal, C., Abt, R. C., Jonsson, R., Prestemon, J. P., & Cubbage, F. W. (2013). Modeling the impacts of EU bioenergy demand on the forest sector of the southeast U.S. J. Energy Power Eng., 7, 1073–1081.

    Google Scholar 

  42. 42.

    A. M. I. Kallio, A. Moiseyev, B. Solberg, and A M. I. Kallio, Moiseyev, A., Solberg, B., “The global forest sector model EFI-GTM. The model structure,” 2004.

  43. 43.

    Favero, A., Mendelsohn, R., & Sohngen, B. (2018). Can the global forest sector survive 11 °C warming? Journal of Agricultural and Resource Economics, 47(2), 388–413.

    Google Scholar 

  44. 44.

    Schwarzbauer, P., & Rametsteiner, E. (2001). The impact of SFM-certification on forest product markets in Western Europe - an analysis using a forest sector simulation model. Forest Policy and Economics, 2(3–4), 241–256.

    Google Scholar 

  45. 45.

    Samuelson, P. A. (1952). Spatial price equilibrium and linear programming. The American Economic Review, 42(3), 283–303.

    Google Scholar 

  46. 46.

    Kallio, A. M. I., Hänninen, R., Vainikainen, N., & Luque, S. (2008). Biodiversity value and the optimal location of forest conservation sites in southern Finland. Ecological Economics, 67(2), 232–243.

    Google Scholar 

  47. 47.

    Sjølie, H. K., Latta, G. S., Adams, D. M., & Solberg, B. (2011). Impacts of agent information assumptions in forest sector modeling. Journal of Forest Economics, 17(2), 169–184.

    Google Scholar 

  48. 48.

    Johnston, C. M. T., & van Kooten, G. C. (2016). Global trade impacts of increasing Europe’s bioenergy demand. Journal of Forest Economics, 23, 27–44.

    Google Scholar 

  49. 49.

    S. Caurla, F. Lecocq, P. Delacote, and A. Barkaoui, “The French forest sector model: version 1.0.,” 2010.

  50. 50.

    Lauri, P., Kallio, A. M. I., & Schneider, U. A. (2012). Price of CO2 emissions and use of wood in Europe. Forest Policy and Economics, 15, 123–131.

  51. 51.

    Buongiorno, J. (1996). Forest sector modeling: a synthesis of econometrics, mathematical programming, and system dynamics methods. International Journal of Forecasting, 12(3), 329–343.

    Google Scholar 

  52. 52.

    Bettinger, P., Boston, K., Siry, J. P., & Grebner, D. L. (2017). Management of forests and other natural resources. For. Manag. Plan., 1–20.

  53. 53.

    Carvalho-Ribeiro, S. M., Lovett, A., & O’Riordan, T. (2010). Multifunctional forest management in Northern Portugal: moving from scenarios to governance for sustainable development. Land Use Policy, 27(4), 1111–1122.

    Google Scholar 

  54. 54.

    Hall, G. R. (1963). The myth and reality of multiple use forestry. Natural Resources Journal, 2, 276–290.

    Google Scholar 

  55. 55.

    Mander, Ü., Wiggering, H., & Helming, K. (2007). Multifunctional land use: meeting future demands for landscape goods and services. Springer.

  56. 56.

    MCPEF, “RESOLUTION H1 General Guidelines for the Sustainable Management of Forests in Europe,” Second Minist. Conf. Prot. For. Eur. 16–17 June 1993, no. June, pp. 1–5, 1993.

  57. 57.

    FAO, “FRA 2015 - Terms and defintions,” 2012.

  58. 58.

    FAO, “Terms and definitions FRA 2020,” 2018.

  59. 59.

    Krieger, D. J. (2001). The economic values of forest ecosystem services: a review. The Wilderness Society.

  60. 60.

    TEEB, “The economics of ecosystems and biodiversity: mainstreaming the economics of nature: a synthesis of the approach, conclusions and recommendations of TEEB,” 2010.

    Google Scholar 

  61. 61.

    R. Haines-Young and M. B. Potschin, “Common International Classification of Ecosystem Services (CICES) V5.1 and Guidance on the Application of the Revised Structure,” 2018.

  62. 62.

    Mace, G. M., Norris, K., & Fitter, A. H. (2012). Biodiversity and ecosystem services: a multilayered relationship. Trends in Ecology & Evolution, 27(1), 19–26.

    Google Scholar 

  63. 63.

    Põllumäe, P., Korjus, H., & Paluots, T. (2014). Management motives of Estonian private forest owners. Forest Policy and Economics, 42, 8–14.

    Google Scholar 

  64. 64.

    Côté, M. A., Généreux-Tremblay, A., Gilbert, D., & Gélinas, N. (2017). Comparing the profiles, objectives and behaviours of new and longstanding non-industrial private forest owners in Quebec, Canada. Forest Policy and Economics, 78, 116–121.

    Google Scholar 

  65. 65.

    Kumer, P., & Štrumbelj, E. (2017). Clustering-based typology and analysis of private small-scale forest owners in Slovenia. Forest Policy and Economics, 80, 116–124.

    Google Scholar 

  66. 66.

    Hugosson, M., & Ingemarson, F. (2004). Objectives and motivations of small-scale forest owners; theoretical modelling and qualitative assessment. Silva Fennica, 38(2), 217–231.

    Google Scholar 

  67. 67.

    Kuuluvainen, J., Karppinen, H., & Ovaskainen, V. (1996). Landowner objectives and nonindustrial private timber supply. Forest Science, 42(3), 300–309.

    Google Scholar 

  68. 68.

    Wear, D. N., & Coulston, J. W. (2019). Specifying forest sector models for forest carbon projections. Journal of Forest Economics, 34(1–2), 73–97.

    Google Scholar 

  69. 69.

    N. J. Van Eck and L. Waltman, “VOSviewer Manual,” 2018.

    Google Scholar 

  70. 70.

    van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538.

    Google Scholar 

  71. 71.

    Lobianco, A., Delacote, P., Caurla, S., & Barkaoui, A. (2015). The importance of introducing spatial heterogeneity in bio-economic forest models: insights gleaned from FFSM++. Ecological Modelling, 309–310, 82–92.

    Google Scholar 

  72. 72.

    Petucco, C., Lobianco, A., & Caurla, S. (2019). Economic evaluation of an invasive forest pathogen at a large scale: the case of ash dieback in France. Environ. Model. Assess.

  73. 73.

    S. Härkönen et al., “Environmental Modelling & Software a climate-sensitive forest model for assessing impacts of forest management in Europe,” Environ. Model. Softw., vol. 115, no. August 2018, pp. 128–143, 2019.

  74. 74.

    Buongiorno, J., Zhu, S., Zhang, D., Turner, J., & Tomberlin, D. (2003). The global forest products model. Academic.

  75. 75.

    Abt, R. C., Cubbage, F. W., & Pacheco. (2000). Southern forest resource assessment using the subregional timber supply (SRTS) model. Forest Products Journal, 50(4), 25–25.

    Google Scholar 

  76. 76.

    Moiseyev, A., Solberg, B., Michie, B., & Kallio, A. M. I. (2010). Modeling the impacts of policy measures to prevent import of illegal wood and wood products. Forest Policy and Economics, 12(1), 24–30.

    Google Scholar 

  77. 77.

    Li, R., Buongiorno, J., Turner, J. A., Zhu, S., & Prestemon, J. (2008). Long-term effects of eliminating illegal logging on the world forest industries, trade, and inventory. Forest Policy and Economics, 10(7–8), 480–490.

    Google Scholar 

  78. 78.

    Mosnier, A., et al. (2014). Modeling impact of development trajectories and a global agreement on reducing emissions from deforestation on Congo Basin forests by 2030. Environmental and Resource Economics, 57(4), 505–525.

    Google Scholar 

  79. 79.

    X. Zhang, B. Xu, L. Wang, A. Yang, and H. Yang, “Eliminating illegal timber consumption or production: which is the more economical means to reduce illegal logging?,” Forests, vol. 7, no. 9, 2016.

  80. 80.

    P. M. Fernandes et al., “Prescribed burning in southern Europe: developing fire management in a dynamic landscape,” Frontiers in Ecology and the Environment, vol. 11, no. SUPPL. 1. 2013.

  81. 81.

    Lobianco, A., Caurla, S., Delacote, P., & Barkaoui, A. (2016). Carbon mitigation potential of the French forest sector under threat of combined physical and market impacts due to climate change. Journal of Forest Economics, 23, 4–26.

    Google Scholar 

  82. 82.

    E. Trømborg and H. K. Sjølie, “Data applied in the forest sector models NorFor and NTMIII,” Ina fagrapport. Dep. Ecol. Nat. Resour. Manag. Nor. Univ. Life Sci., vol. 17, 2011.

  83. 83.

    Kallio, A. M. I., Salminen, O., & Sievänen, R. (2013). Sequester or substitute-consequences of increased production of wood based energy on the carbon balance in Finland. Journal of Forest Economics, 19(4), 402–415.

    Google Scholar 

  84. 84.

    Sjolie, H. K., Latta, G. S., & Solberg, B. (2013). Potentials and costs of climate change mitigation in the Norwegian forest sector - does choice of policy matter? Can. J. For. Res. Can. Rech. For., 43(6), 589–598.

    Google Scholar 

  85. 85.

    Im, E. H., Adams, D. M., & Latta, G. S. (2007). Potential impacts of carbon taxes on carbon flux in western Oregon private forests. Forest Policy and Economics, 9(8), 1006–1017.

    Google Scholar 

  86. 86.

    Latta, G., Adams, D. M., Alig, R. J., & White, E. (2011). Simulated effects of mandatory versus voluntary participation in private forest carbon offset markets in the United States. Journal of Forest Economics, 17(2), 127–141.

    Google Scholar 

  87. 87.

    Lecocq, F., Caurla, S., Delacote, P., Barkaoui, A., & Sauquet, A. (2011). Paying for forest carbon or stimulating fuelwood demand? Insights from the French forest sector model. Journal of Forest Economics, 17(2), 157–168.

    Google Scholar 

  88. 88.

    Buongiorno, J., & Zhu, S. (2013). Consequences of carbon offset payments for the global forest sector. Journal of Forest Economics, 19(4), 384–401.

    Google Scholar 

  89. 89.

    Im, E. H., Adams, D. M., & Latta, G. S. (2010). The impacts of changes in federal timber harvest on forest carbon sequestration in western Oregon. Can. J. For. Res. Can. Rech. For., 40(9), 1710–1723.

    Google Scholar 

  90. 90.

    A. M. I. Kallio, B. Solberg, L. Käär, and R. Päivinen, “Forest policy and economics: economic impacts of setting reference levels for the forest carbon sinks in the EU on the European forest sector,” For. Policy Econ., vol. 92, no. May, pp. 193–201, 2018.

  91. 91.

    Kallio, A. M. I., & Solberg, B. (2018). Leakage of forest harvest changes in a small open economy: case Norway. Scandinavian Journal of Forest Research, 33(5), 502–510.

    Google Scholar 

  92. 92.

    Bolkesjø, T., Trømborg, E., & Solberg, B. (2006). Bioenergy from the forest sector: economic potential and interactions with timber and forest products markets in Norway. Scandinavian Journal of Forest Research, 21(2), 175–185.

    Google Scholar 

  93. 93.

    Moiseyev, A., Solberg, B., Kallio, A. M. I., & Lindner, M. (2011). An economic analysis of the potential contribution of forest biomass to the EU RES target and its implications for the EU forest industries. Journal of Forest Economics, 17(2), 197–213.

    Google Scholar 

  94. 94.

    White, E. M., Latta, G., Alig, R. J., Skog, K. E., & Adams, D. M. (2013). Biomass production from the U.S. forest and agriculture sectors in support of a renewable electricity standard. Energy Policy, 58, 64–74.

    Google Scholar 

  95. 95.

    Caurla, S., Delacote, P., Lecocq, F., & Barkaoui, A. (2013). Stimulating fuelwood consumption through public policies: an assessment of economic and resource impacts based on the French forest sector model. Energy Policy, 63, 338–347.

    Google Scholar 

  96. 96.

    Kangas, H. L., Lintunen, J., Pohjola, J., Hetemäki, L., & Uusivuori, J. (2011). Investments into forest biorefineries under different price and policy structures. Energy Economics, 33(6), 1165–1176.

    Google Scholar 

  97. 97.

    Sjølie, H. K., Trømborg, E., Solberg, B., & Bolkesjø, T. F. (2010). Effects and costs of policies to increase bioenergy use and reduce GHG emissions from heating in Norway. Forest Policy and Economics, 12(1), 57–66.

    Google Scholar 

  98. 98.

    J. M. Earles, A. Halog, P. Ince, and K. Skog, “Integrated economic equilibrium and life cycle assessment modeling for policy-based consequential LCA,” 2012.

    Google Scholar 

  99. 99.

    Böttcher, H., Frank, S., Havlík, P., & Elbersen, B. (2013). Future GHG emissions more efficiently controlled by land-use policies than by bioenergy sustainability criteria. Biofuels, Bioproducts and Biorefining, 7(2), 115–125.

    Google Scholar 

  100. 100.

    Havlík, P., et al. (2011). Global land-use implications of first and second generation biofuel targets. Energy Policy, 39(10), 5690–5702.

    Google Scholar 

  101. 101.

    S. U. Okoro, U. Schickhoff, and U. A. Schneider, “Impacts of bioenergy policies on land-use change in Nigeria,” Energies, vol. 11, no. 1, p. 152, 2018.

  102. 102.

    Costanza, J. K., Abt, R. C., McKerrow, A. J., & Collazo, J. A. (2017). Bioenergy production and forest landscape change in the southeastern United States. GCB Bioenergy, 9(5), 924–939.

    Google Scholar 

  103. 103.

    Duden, A. S., et al. (2017). Modeling the impacts of wood pellet demand on forest dynamics in southeastern United States. Biofuels, Bioproducts and Biorefining, 11(6), 1007–1029.

    CAS  Google Scholar 

  104. 104.

    Geijer, E., Andersson, J., Bostedt, G., Brännlund, R., & Hjältén, J. (2014). Safeguarding species richness vs. increasing the use of renewable energy—the effect of stump harvesting on two environmental goals. Journal of Forest Economics, 20, 111–125.

    Google Scholar 

  105. 105.

    Schleupner, C., & Schneider, U. A. (2010). Effects of bioenergy policies and targets on European wetland restoration options. Environmental Science & Policy, 13(8), 721–732.

    Google Scholar 

  106. 106.

    Geijer, E., Bostedt, G., & Brännlund, R. (2011). Damned if you do, damned if you do not-reduced climate impact vs. sustainable forests in Sweden. Resource and Energy Economics, 33(1), 94–106.

    Google Scholar 

  107. 107.

    Perez-Garcia, J., Joyce, L. A., & McGuire, A. D. (2002). Temporal uncertainties of integrated ecological/economic assessments at the global and regional scales. Forest Ecology and Management, 162(1), 105–115.

    Google Scholar 

  108. 108.

    Solberg, B., Moiseyev, A., & Kallio, A. M. I. (2003). Economic impacts of accelerating forest growth in Europe. Forest Policy and Economics, 5(2), 157–171.

    Google Scholar 

  109. 109.

    R. H. Beach et al., “Climate change impacts on US agriculture and forestry: benefits of global climate stabilization,” Environ. Res. Lett., vol. 10, no. 9, 2015.

  110. 110.

    G. C. van Kooten and C. Johnston, “The economics of forest carbon offsets,” Ssrn, no. April, pp. 1–20, 2016.

  111. 111.

    Adams, D. M., Alig, R., Latta, G., & White, E. M. (2011). Regional impacts of a program for private forest carbon offset sales. Journal of Forestry, 109(8), 444–461.

    Google Scholar 

  112. 112.

    Sjølie, H. K., Latta, G. S., & Solberg, B. (2014). Impacts of the Kyoto protocol on boreal forest climate change mitigation. Annals of Forest Science, 71(2), 267–277.

    Google Scholar 

  113. 113.

    Moiseyev, A., Solberg, B., & Kallio, A. M. I. (2014). The impact of subsidies and carbon pricing on the wood biomass use for energy in the EU. Energy, 76, 161–167.

    Google Scholar 

  114. 114.

    Tavoni, M., Sohngen, B., & Bosetti, V. (2007). Forestry and the carbon market response to stabilize climate. Energy Policy, 35(11), 5346–5353.

    Google Scholar 

  115. 115.

    Favero, A., & Mendelsohn, R. (2014). Using markets for woody biomass energy to sequester carbon in forests. Journal of the Association of Environmental and Resource Economists, 1(1/2), 75–95.

    Google Scholar 

  116. 116.

    Kallio, A. M. I., Moiseyev, A., & Solberg, B. (2006). Economic impacts of increased forest conservation in Europe: a forest sector model analysis. Environmental Science & Policy, 9(5), 457–465.

    Google Scholar 

  117. 117.

    Bolkesjø, T. F., Trømborg, E., & Solberg, B. (2005). Increasing forest conservation in Norway: consequences for timber and forest products markets. Environmental and Resource Economics, 31(1), 95–115.

    Google Scholar 

  118. 118.

    Merry, F., Soares-Filho, B., Nepstad, D., Amacher, G., & Rodrigues, H. (2009). Balancing conservation and economic sustainability: the future of the amazon timber industry. Environmental Management, 44(3), 395–407.

    Google Scholar 

  119. 119.

    Barbier, E. B., Bockstael, N., Burgess, J. C., & Strand, I. (1995). The linkages between the timber trade and tropical deforestation???Indonesia. World Economics, 18(3), 411–442.

    Google Scholar 

  120. 120.

    Sun, L., & Bogdanski, B. E. C. (2017). Trade incentives for importers to adopt policies to address illegally logged timber: the case of non-tropical hardwood plywood. Journal of Forest Economics, 27, 18–27.

    Google Scholar 

  121. 121.

    Schleupner, C., & Schneider, U. A. (2013). Allocation of European wetland restoration options for systematic conservation planning. Land Use Policy, 30, 604–614.

    Google Scholar 

  122. 122.

    Adams, D. M., & Latta, G. S. (2007). Timber trends on private lands in western Oregon and Washington: a new look. Western Journal of Applied Forestry, 22, 8–14.

    Google Scholar 

  123. 123.

    D. M. Adams and G. S. Latta, “Future prospects for private timber harvest in Eastern Oregon,” WEST.J.APPL.FOR., vol. 22, no. 3, 2007.

  124. 124.

    Adams, D. M., & Latta, G. S. (2005). Costs and regional impacts of restoration thinning programs on the national forests in eastern Oregon. Canadian Journal of Forest Research, 35(6), 1319–1330.

    Google Scholar 

  125. 125.

    Ince, P. J., Spelter, H., Skog, K. E., Kramp, A., & Dykstra, D. P. (2008). Market impacts of hypothetical fuel treatment thinning programs on federal lands in the western United States. Forest Policy and Economics, 10(6), 363–372.

    Google Scholar 

  126. 126.

    Prestemon, J. P., Abt, K. L., & Huggett, R. J. (2008). Market impacts of a multiyear mechanical fuel treatment program in the U.S. Forest Policy and Economics, 10(6), 386–399.

    Google Scholar 

  127. 127.

    Turner, J. A., Buongiorno, J., Zhu, S., Prestemon, J. P., Li, R., & Bulman, L. S. (2007). Modelling the impact of the exotic forest pest Nectria on the New Zealand forest sector and its major trading partners. New Zeal. J. For. Sci., 37(3), 383–411.

    Google Scholar 

  128. 128.

    Sun, C. (2016). Timber market recovery after a hurricane. Forest Science, 62(6), 600–612.

    Google Scholar 

  129. 129.

    Caurla, S., Garcia, S., & Niedzwiedz, A. (2015). Store or export? An economic evaluation of financial compensation to forest sector after windstorm. The case of hurricane Klaus. Forest Policy and Economics, 61, 30–38.

    Google Scholar 

  130. 130.

    Prestemon, J. P., Abt, K. L., Potter, K. M., & Koch, F. H. (2013). An economic assessment of mountain pine beetle timber salvage in the west. Western Journal of Applied Forestry, 28(4), 143–153.

    Google Scholar 

  131. 131.

    Pattanayak, S. K., et al. (2004). Forest forecasts: does individual heterogeneity matter for market and landscape outcomes? Forest Policy and Economics, 6(3–4), 243–260.

    Google Scholar 

  132. 132.

    Yu, C.-H., McCarl, B., Yu, C.-H., & McCarl, B. A. (2018). The water implications of greenhouse gas mitigation: effects on land use, land use change, and forestry. Sustainability, 10(7), 2367.

    Google Scholar 

  133. 133.

    Kallio, A. M. I. (2010). Accounting for uncertainty in a forest sector model using Monte Carlo simulation. Forest Policy and Economics, 12(1), 9–16.

    Google Scholar 

  134. 134.

    Chudy, R. P., Sjølie, H. K., & Solberg, B. (2016). Incorporating risk in forest sector modeling – state of the art and promising paths for future research. Scandinavian Journal of Forest Research, 31(7), 719–727.

    Google Scholar 

  135. 135.

    J. Buongiorno and C. Johnston, “Effects of parameter and data uncertainty on long-term projections in a model of the global forest sector,” For. Policy Econ., vol. 93, no. May, pp. 10–17, 2018.

  136. 136.

    Jåstad, E. O., Mustapha, W. F., Bolkesjø, T. F., Trømborg, E., & Solberg, B. (2018). Modelling of uncertainty in the economic development of the Norwegian forest sector. Journal of Forest Economics, 32(May 2017), 106–115.

    Google Scholar 

  137. 137.

    Morland, C., Schier, F., Janzen, N., & Weimar, H. (2018). Supply and demand functions for global wood markets: specification and plausibility testing of econometric models within the global forest sector. Forest Policy and Economics, 92, 92–105.

    Google Scholar 

  138. 138.

    Rougieux, P., & Damette, O. (2018). Reassessing forest products demand functions in Europe using a panel cointegration approach. Applied Economics, 50(30), 3247–3270.

    Google Scholar 

  139. 139.

    Kallio, A., Solberg, B., Kallio, A. M. I., & Solberg, B. (2018). On the reliability of international forest sector statistics: problems and needs for improvements. Forests, 9(7), 407.

    Google Scholar 

  140. 140.

    Trømborg, E., Bolkesjø, T. F., & Solberg, B. (2007). Impacts of policy means for increased use of forest-based bioenergy in Norway-a spatial partial equilibrium analysis. Energy Policy, 35(12), 5980–5990.

    Google Scholar 

  141. 141.

    Cai, Y., Newth, D., Finnigan, J., & Gunasekera, D. (2015). A hybrid energy-economy model for global integrated assessment of climate change, carbon mitigation and energy transformation. Applied Energy, 148, 381–395.

    CAS  Google Scholar 

  142. 142.

    Bosetti, V., et al. (2005). Change Hybrud model WITCH a world induced technical change hybrid model Emanuele Massetti. JSTOR.

  143. 143.

    Hourcade, J.-C., Jaccard, M., Bataille, C., & Ghersi, F. (2011). Hybrid modeling: new answers to old challenges introduction to the special issue of The Energy Journal. The Energy Journal, SI2006(01).

  144. 144.

    Shabani, N., Akhtari, S., & Sowlati, T. (2013). Value chain optimization of forest biomass for bioenergy production: a review. Renewable and Sustainable Energy Reviews, 23, 299–311.

    Google Scholar 

  145. 145.

    De Meyer, A., Cattrysse, D., Rasinmäki, J., & Van Orshoven, J. (2014). Methods to optimise the design and management of biomass-for-bioenergy supply chains: a review. Renewable and Sustainable Energy Reviews, 31, 657–670.

    Google Scholar 

  146. 146.

    P. J. Ince et al., “U.S. forest products module: a technical document supporting the Forest Service 2010 RPA Assessment,” 2011.

    Google Scholar 

  147. 147.

    Peter, B., & Niquidet, K. (2016). Estimates of residual fibre supply and the impacts of new bioenergy capacity from a forest sector transportation model of the Canadian Prairie Provinces. Forest Policy and Economics, 69, 62–72.

    Google Scholar 

  148. 148.

    Niquidet, K., & Friesen, D. (2014). Bioenergy potential from wood residuals in Alberta: a positive mathematical programming approach. Canadian Journal of Forest Research, 44(12), 1586–1594.

    Google Scholar 

  149. 149.

    Galik, C. S., & Abt, R. C. (2016). Sustainability guidelines and forest market response: an assessment of European Union pellet demand in the southeastern United States. GCB Bioenergy, 8(3), 658–669.

    Google Scholar 

  150. 150.

    Latta, G. S., Baker, J. S., & Ohrel, S. (2018). A Land Use and Resource Allocation (LURA) modeling system for projecting localized forest CO2effects of alternative macroeconomic futures. Forest Policy and Economics, 87(October 2017), 35–48.

    Google Scholar 

  151. 151.

    Perez-Garcia, J., Joyce, L. A., Binkley, C. S., & McGuire, A. D. (1997). Economic impacts of climatic change on the global forest sector: an integrated ecological/economic assessment. Critical Reviews in Environmental Science and Technology, 27(SPEC. ISS), S123–S138.

    CAS  Google Scholar 

  152. 152.

    Eriksson, L. O., et al. (2012). Climate change mitigation through increased wood use in the European construction sector-towards an integrated modelling framework. European Journal of Forest Research, 131(1), 131–144.

    Google Scholar 

  153. 153.

    Caurla, S., Bertrand, V., Delacote, P., & Le Cadre, E. (2018). Heat or power: how to increase the use of energy wood at the lowest cost? Energy Economics, 75, 85–103.

    Google Scholar 

  154. 154.

    Beaussier, T., Caurla, S., Bellon-Maurel, V., & Loiseau, E. (2019). Coupling economic models and environmental assessment methods to support regional policies: a critical review. Journal of Cleaner Production, 216, 408–421.

    Google Scholar 

  155. 155.

    Sievanen, L., Campbell, L. M., & Leslie, H. M. (2012). Challenges to interdisciplinary research in ecosystem-based management. Conservation Biology, 26(2), 315–323.

    Google Scholar 

  156. 156.

    Campbell, L. M. (2005). Diversity overcoming obstacles to interdisciplinary research. Conservation Biology, 19(2), 574–577.

    Google Scholar 

  157. 157.

    Tardieu, L., & Tuffery, L. (2019). From supply to demand factors: what are the determinants of attractiveness for outdoor recreation? Ecological Economics, 161, 163–175.

    Google Scholar 

  158. 158.

    Chan, K. M. A., Satterfield, T., & Goldstein, J. (2012). Rethinking ecosystem services to better address and navigate cultural values. In Ecological Economics (Vol. 74, pp. 8–18). Amsterdam: Elsevier.

    Google Scholar 

  159. 159.

    An, L. (2012). Modeling human decisions in coupled human and natural systems: review of agent-based models. Ecological Modelling, 229, 25–36.

    Google Scholar 

  160. 160.

    Heckbert, S., Baynes, T., & Reeson, A. (2010). Agent-based modeling in ecological economics. Annals of the New York Academy of Sciences, 1185, 39–53.

    Google Scholar 

  161. 161.

    M. Janssen and E. Ostrom, “Empirically based, agent-based models,” Ecol. Soc., vol. 11, no. 2, 2006.

  162. 162.

    Pohjola, J., Laturi, J., Lintunen, J., & Uusivuori, J. (2018). Immediate and long-run impacts of a forest carbon policy—a market-level assessment with heterogeneous forest owners. Journal of Forest Economics, 32, 94–105.

    Google Scholar 

  163. 163.

    Yousefpour, R., Augustynczik, A. L. D., Reyer, C. P. O., Lasch-Born, P., Suckow, F., & Hanewinkel, M. (2018). Realizing mitigation efficiency of European commercial forests by climate smart forestry. Scientific Reports, 8(1), 1–11.

    CAS  Google Scholar 

  164. 164.

    G. A. Mendoza and H. Martins, “Multi-criteria decision analysis in natural resource management: a critical review of methods and new modelling paradigms,” Forest Ecology and Management, vol. 230, no. 1–3. Elsevier, Amsterdam, pp. 1–22, 2006.

Download references


The authors want to thank the Climate Economics Chair for financial support. The authors want to thank Pr. Harold Levrel for his attentive help, as well as our anonymous reviewers for their insightful comments and suggestions.


This work was supported by the French Ministère de l’Agriculture et de l’Alimentation. The BETA contributes to the LabEX ARBRE ANR-11-LABX-0002-01. This research is part of the Agriculture and Forestry research program by the Climate Economics Chair.

Author information



Corresponding author

Correspondence to Miguel Riviere.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Riviere, M., Caurla, S. & Delacote, P. Evolving Integrated Models From Narrower Economic Tools: the Example of Forest Sector Models. Environ Model Assess 25, 453–469 (2020). https://doi.org/10.1007/s10666-020-09706-w

Download citation


  • Forest sector model
  • Forestry
  • Economics
  • Environmental modelling
  • Ecosystem services
  • Integrated assessment

JEL Codes

  • C61
  • L7
  • Q21
  • Q23
  • Q57