Skip to main content

Advertisement

SpringerLink
Log in

A compromise programming model for developing the cost of including carbon pools and flux into forest management

  • Published:
Annals of Operations Research Aims and scope Submit manuscript

Abstract

Policy makers need research based decision analysis models that include carbon sequestration and forest products in order to make policies that are both economically viable and effective. Forests and wood products have been identified as important mechanisms for carbon sequestration and storage. Policies often cover carbon sequestration but not product storage and substitution. Furthermore, many researchers have developed and published models on carbon management. However, a gap exists in operational level models that include product substitution. We developed a model to investigate optimal stand level management with competing objectives of maximizing soil expectation value, carbon storage in the forest, and carbon dioxide emission savings from product storage and substitution. Our purpose was to produce an accurate and usable analytical product for Southeastern U.S. foresters growing loblolly pine (Pinus taeda) in the presence of carbon policies. The decision variables were traditional stand level management variables: planting density, thinning timing and density, and rotation length. Over time these variables influence the proportion of wood going into pulp, chip-n-saw, and sawtimber where each of these classes has an expected use (carbon storage) life. Compromise programming was employed to solve the multiple-objective problem and to demonstrate the tradeoffs between the competing objectives. This type of model demonstrates a practical method for comparing tradeoffs associated with adjusting forest management for a carbon market. The difference in costs among objectives is important for decision makers considering climate change policies, as it represents the minimum value a rational landowner would accept to sequester a unit of carbon.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Backeus, S., Wikstrom, P., & Lamas, T. (2005). A model for regional analysis of carbon sequestration and timber production. Forest Ecology and Management, 216, 28–40.

    Article  Google Scholar 

  • Bergman, R., & Bowe, S. (2010). Environmental impact of manufacturing softwood lumber in the Northeastern and North central United States. Wood and Fiber Science, 42, 67–78.

    Google Scholar 

  • Briggs, D. (1994). Forest product measurements conversion factors. Washington: College of Forest Resources, University of Washington.

    Google Scholar 

  • Buford, M. (1991). Performance of four yield models for predicting stand dynamics of a 30-year-old loblolly pine spacing study. Forest Ecology and Management, 46, 23–38.

    Article  Google Scholar 

  • Buford, M., & Hafley, W. (1985). Probability distributions as models for mortality. Forest Science, 31, 331–341.

    Google Scholar 

  • Cao, T., Valsta, L., & Makela, A. (2010). A comparison of carbon assessment methods for optimizing timber production and carbon sequestration in Scots pine stands. Forest Ecology and Management, 260, 1726–1734.

    Article  Google Scholar 

  • Davis, L., Johnson, K., Bettinger, P., & Howard, T. (2001). Forest management (4th ed.). New York: McGraw Hill.

    Google Scholar 

  • Del Lungo, A., Ball, J. & Carle, J. Global planted forests thematic study: results and analysis, FAO planted forests and trees working paper 38, Rome.

  • Dwivedi, P., Alavalapati, J., Susaeta, A., & Stainback, A. (2009). Impact of carbon value on the profitability of slash pine plantations in the Southern United States: an integrated life cycle and Faustmann analysis. Canadian Journal of Forest Research, 39, 990–1000.

    Article  Google Scholar 

  • Dwivedi, P., Bailis, R., Bush, T., & Mainescu, M. (2011). Quantifying GWI of wood pellet production in the Southern United states and its subsequent utilization for electricity production in the Netherlands/Florida. Bioenergy Research, 4, 180–192.

    Article  Google Scholar 

  • EC (2009). Directive 2009/28/EC of the European Parliament and of the Council. Official Journal of the European Union, 140, 16–47.

    Google Scholar 

  • Eriksson, E., Gillespie, A., Gustavsson, L., Langvall, O., Olsson, M., Sathre, R., & Stendahl, J. (2007). Integrated carbon analysis of forest management practices and wood substitution. Canadian Journal of Forest Research, 37, 671–681.

    Article  Google Scholar 

  • FAO (2010). Global forest resources assessment 2010 main report. FAO forestry paper 163, Rome.

  • Franklin Associates, a division of ERG (2011). Life cycle inventory of foam polystyrene, paper-based, and PLA foodservice products. Accessed via web 4 August 2011. http://plasticfoodservicefacts.com/Life-Cycle-Inventory-Foodservice-Products

  • Fylstra, D., Lasdon, L., Watson, J., & Waren, A. (1998). Design and use of the microsoft excel solver. Interfaces, 28, 29–55.

    Article  Google Scholar 

  • Galik, C., Mobley, M., & Richter, D. (2009). A virtual “field test” of forest management carbon offset protocols: the influence of accounting. Mitigation and Adaptation Strategies for Global Change, 14, 677–690.

    Article  Google Scholar 

  • Gershon, M. (1982). The role of weights and scales in the application of multiobjective decision making. European Journal of Operational Research, 15, 244–250.

    Article  Google Scholar 

  • GGLS8 (2010). Green house gasses and energy balance calculation standard. Green Gold Label Program, web.

  • Hafley, W., & Buford, M. (1985). A bivariate model for growth and yield prediction. Forest Science, 31, 237–247.

    Google Scholar 

  • Hafley, W., Smith, W., & Buford, M. (1982). A new yield prediction model for unthinned loblolly pine plantations. Technical report No. 1, Bioeconomic modeling project, Southern Forest Research Center, School of Forest Resources, North Carolina State University, Raleigh, NC.

  • Heath, L., Hansen, M., Smith, J., Smith, W., & Miles, P. (2008). Investigation into calculating tree biomass and carbon in the FIADB using a biomass expansion factor approach. Fort Collins: U.S. Department of Agriculture (RMRS-P-56CD).

    Google Scholar 

  • Hennigar, C., MacLean, D., & Amos-Binks, L. (2008). A novel approach to optimize management strategies for carbon stored both in forests and wood products. Forest Ecology and Management, 256, 786–797.

    Article  Google Scholar 

  • Huang, C., & Kronrad, G. (2006). The effect of carbon revenues on the rotation and profitability of loblolly pine plantations in East Texas. Southern Journal of Applied Forestry, 30, 21–29.

    Google Scholar 

  • Hyytiainen, K., Tahvonen, O., & Valsta, L. (2005). Optimum juvenile density, harvesting, and stand structure in even-aged Scots pine stands. Journal of Forest Economics, 51, 120–133.

    Google Scholar 

  • IPCC (2006). 2006 IPCC guidelines for national greenhouse gas inventories. Prepared by the National greenhouse gas inventories programme, Eggleston H. S., Buendia L., Miwa K., Ngara T. and Tanabe K. (eds). IGES, Japan.

  • IPCC (2007). Nabuurs G., Masera O., Andrasko K., Benitez-Ponce P., Boer R., Dutschke M., Elsiddig E., Ford-Robertson J., Frumhoff P., Karjalainen T., Krankina O., Kurz W., Matsumoto M., Oyhantcabal W., Ravindranath N., Sanz Sanchez J., Zhang X. Forestry in climate change 2007: mitigation. Contribution of working group III to the fourth assessment report of the intergovernmental panel on climate change [B. Metz, O.R. Davidson, P.R. Bosch, R. Dave, L.A. Meyer (eds.)], Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

  • IPCC (2011). Summary for policymakers. In O. Edenhofer, R. Pichs-Madruga, Y. Sokona, K. Seyboth, P. Matschoss, S. Kadner, T. Zwickel, P. Eickemeier, G. Hansen, S. Schlömer, & C. von Stechow (Eds.), IPCC special report on renewable energy sources and climate change mitigation. Cambridge: Cambridge University Press.

    Google Scholar 

  • Jimenez, J., Rattan, L., Russo, R., & Leblanc, H. (2008). The soil organic carbon in particle-size separates under different regrowth forest stands of North Eastern Costa Rica. Ecological Engineering, 34, 300–310.

    Article  Google Scholar 

  • Kaipainen, T., Liski, J., Pussinen, A., & Karjalainen, T. (2004). Managing carbon sinks by changing rotation length in European forests. Environmental Science & Policy, 7, 205–219.

    Article  Google Scholar 

  • Krcmer, E., van Kooten, G., & Vertinsky, I. (2005). Managing forest and marginal agricultural land for multiple tradeoffs: compromising on economic, carbon and structural diversity objectives. Ecological Modelling, 185, 451–468.

    Article  Google Scholar 

  • Lee, H. (1996). Supporting rural telecommunications: a compromise solutions approach. Annals of Operations Research, 68, 33–45.

    Article  Google Scholar 

  • Lippke, B., Wilson, J., Meil, J., & Taylor, A. (2010). Characterizing the importance of carbon stored in wood products. Wood and Fiber Science, 42, 5–14.

    Google Scholar 

  • Liski, J., Pussinen, A., Pingoud, K., Makipaa, R., & Karjalainen, T. (2001). Which rotation length is favorable to carbon sequestration? Canadian Journal of Forest Research, 31, 2004–2013.

    Article  Google Scholar 

  • Meng, F., Bourgque, C., Oldford, S., Swift, D., & Smith, H. (2003). Combining carbon sequestration objectives with timber management planning. Mitigation and Adaptation Strategies for Global Change, 8, 371–403.

    Article  Google Scholar 

  • Milota, M., West, C., & Hartley, I. (2005). Gate to gate life-cycle inventory of softwood lumber production. Wood and Fiber Science, 37, 47–57.

    Google Scholar 

  • NC Extension Forestry. Wood energy. May 2011. Web.

  • NCASI (2004). Critical review of forest product decomposition in municipal solid waste landfills. Technical bulletin No. 0872. Triangle Park: National Council for Air and Stream Improvement, Inc.

    Google Scholar 

  • Nepal, P., Grala, R., & Grebner, D. (2012). Financial feasibility of increasing carbon sequestration in harvested wood products in Mississippi. Forest Policy and Economics, 14, 99–106.

    Article  Google Scholar 

  • Peng, C., Jiang, H., Apps, M., & Zhang, Y. (2002). Effects of harvesting regimes on carbon and nitrogen dynamics of boreal forests in central Canada: a process model simulation. Ecological Modeling, 155, 177–189.

    Article  Google Scholar 

  • Pohjola, J., & Valsta, L. (2007). Carbon credits and management of Scots pine and Norway spruce stands in Finland. Forest Policy and Economics, 9, 789–798.

    Article  Google Scholar 

  • Prodanovic, P., & Simonovic, S. (2003). Fuzzy compromise programming for group decision making. IEEE Transactions on Systems, Man and Cybernetics. Part A. Systems and Humans, 33(3), 358–365.

    Article  Google Scholar 

  • Puettmann, M., & Wilson, J. (2005). Life-cycle analysis of wood products: cradle-to-gate LCI of residential wood building materials. Wood and Fiber Science, 37, 18–29.

    Google Scholar 

  • Rawlings, J., Pantula, S., & Dickey, D. (1998). Applied regression analysis: a research tool (2nd ed.). New York: Springer.

    Book  Google Scholar 

  • Sanchez, F., Carter, E., & Klepac, J. (2003). Enhancing the soil organic matter pool through biomass incorporation. Biomass & Bioenergy, 24, 337–349.

    Article  Google Scholar 

  • Sarkhot, D., Comerford, N., Jokela, E., & Reeves, J. (2007). Effects of forest management intensity on carbon and nitrogen content in different soil size fractions of a North Florida Spodosol. Plant and Soil, 294, 291–303.

    Article  Google Scholar 

  • Skog, K. (2008). Sequestration of carbon in harvested wood products for the United States. Forest Products Journal, 58, 56–72.

    Google Scholar 

  • Smith, B., Miles, P., Vissage, J., & Pugh, S. (2003). Forest resources of the United States. Gen. tech. rep. NC-241, St. Paul, U.S. Department of Agriculture, Forest Service, North Central Research Station, 137 p.

  • Smith, B., Miles, P., Perry, C., & Pugh, S. (2009). Forest resources of the U.S. Gen. tech. rep. WO-78, Washington, U.S. Department of Agriculture, 2007, Forest Service, Washington Office, 336 p. Available at. http://www.fs.fed.us/nrs/pubs/gtr/gtr_wo78.pdf.

  • Smith, J., Heath, L., Skog, K., & Birdsey, R. (2006). Methods for calculating forest ecosystem and harvested carbon with standard estimates for forest types in the United States. General technical report NE-343, Newtown Square, U.S. Department of Agriculture, Forest Service, North Eastern Research Station, 216 p.

  • Sohngen, B., & Brown, S. (2008). Extending timber rotations: carbon and cost implications. Climate Policy, 8, 435–451.

    Article  Google Scholar 

  • Talbert, J., & Jett, J. (1981). Regional specific gravity values for plantation grown loblolly pine in the Southeastern United States. Forest Science, 27, 801–807.

    Google Scholar 

  • UNFCCC Secretariat (2011). News. Accessed via web 4 August 2011. http://unfccc.int/2860.php.

  • Upton, B., Miner, R., Spinney, M., & Heath, L. (2008). The greenhouse gas and energy impacts of using wood instead of alternatives in residential construction in the United States. Biomass & Bioenergy, 32, 1–10.

    Article  Google Scholar 

  • van Kooten, G., Binkley, C., & Delcourt, G. (1995). Effect of carbon taxes and subsidies on optimal forest rotation age and supply of carbon services. American Journal of Agricultural Economics, 77, 365–374.

    Article  Google Scholar 

  • White, M., Gower, S., & Ahl, D. (2005). Life cycle inventories of roundwood production in Northern Wisconsin: inputs into an industrial forest carbon budget. Forest Ecology and Management, 219, 13–28.

    Article  Google Scholar 

  • Winston, W. (2004). Operations research: applications and algorithms (4th ed.). Belmont: Brooks/Cole.

    Google Scholar 

  • Woodbury, P., Smith, J., & Heath, L. (2007). Carbon sequestration in the U.S. forest sector from 1990–2010. Forest Ecology and Management, 241, 14–27.

    Article  Google Scholar 

Download references

Acknowledgements

A portion of this research has been funded by a grant from the U.S. EPA’s P3 Program. Laurie Gharis was supported by a National Needs Fellowship co-sponsored by North Carolina State University’s Department of Forestry and Environmental Resources and the USDA-CSREES. The authors would also like to thank Richard Bergman, Puneet Dwivedi, Peter Lohmander, and Maureen Puettmann for their help.

Author information

Authors and Affiliations

  1. Department of Forestry and Environmental Resources, North Carolina State University, 3120 Jordan Hall, Campus Box 8008, Raleigh, NC, 27695, USA

    L. Gharis, J. Roise & J. McCarter

Authors
  1. L. Gharis
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. J. Roise
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. J. McCarter
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to L. Gharis.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Gharis, L., Roise, J. & McCarter, J. A compromise programming model for developing the cost of including carbon pools and flux into forest management. Ann Oper Res 232, 115–133 (2015). https://doi.org/10.1007/s10479-013-1519-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10479-013-1519-9

Keywords

Search

Navigation