RESEARCH ARTICLE
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Optimal harvest strategy for even-aged stands with price uncertainty and risk of natural disturbances
Andres Susaeta,
Peichen Gong,
Corresponding Author
Andres Susaeta
Institute of Food and Agricultural Sciences, School of Forest Resources and Conservation, University of Florida, Gainesville, Florida
Correspondence School of Forest Resources and Conservation, University of Florida, 315 Newins Ziegler Hall, PO Box 110410, Gainesville, FL 32611. Email: asusaeta@ufl.edu
Search for more papers by this authorPeichen Gong
Department of Forest Economics, Centre for Environmental and Resource Economics, Swedish University of Agricultural Sciences, Umeå, Sweden
Search for more papers by this authorAndres Susaeta,
Peichen Gong,
Corresponding Author
Andres Susaeta
Institute of Food and Agricultural Sciences, School of Forest Resources and Conservation, University of Florida, Gainesville, Florida
Correspondence School of Forest Resources and Conservation, University of Florida, 315 Newins Ziegler Hall, PO Box 110410, Gainesville, FL 32611. Email: asusaeta@ufl.edu
Search for more papers by this authorPeichen Gong
Department of Forest Economics, Centre for Environmental and Resource Economics, Swedish University of Agricultural Sciences, Umeå, Sweden
Search for more papers by this authorAbstract
We present a reservation price model to examine the joint impacts of natural disturbances and stumpage price uncertainty on the optimal harvesting decision for even-aged forest stands. We consider a landowner who manages a loblolly pine stand to produce timber and amenities, under age-dependent risk of wildfires and uncertainty in future timber prices. We show that the incorporation of risk of wildfires decreases the optimal reservation prices. The inclusion of risk of wildfires leads to lower land values and reduces the mean harvest age compared with the case of no-risk of wildfires. Higher economic gains are obtained with the reservation price strategy compared with the deterministic rotation age model—a difference in the land value of $2,326 ha−1 (21%) between the two approaches.
Recommendations for Resource Managers
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Our adaptive harvest strategy shows that the incorporation of risk of wildfires decreases the optimal reservation prices compared with the case of no-risk of wildfires.
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Low reservation prices—a price that makes the landowner indifferent between harvesting or waiting longer—result in lower economic benefits for landowners and potential conversions of lands to nonforest use.
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Forest management practices oriented to reduce the effects of catastrophic disturbances, for example, creating a more complex forest structure with different stand densities, become imperative to ensure the sustainability of forestlands in the US South.
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Our analysis also suggests that the valuation of forestry investments should consider not only the risk of catastrophic events but also uncertainty in future timber prices. Higher appraisals of land value are obtained when timber price uncertainty is explicitly recognized, providing financial incentives for landowners to invest in forestry.
REFERENCES
- Amacher, G., Ollikainen, M., & Koskela, E. (2009). Economics of forest resources. London, UK: MIT Press.
- Amacher, G. S., Malik, A. S., & Haight, R. G. (2005a). Forest landowner decisions and the value of information under fire risk. Canadian Journal of Forest Research, 35(11), 2603–2615.
- Amacher, G. S., Malik, A. S., & Haight, R. G. (2005b). Not getting burned: The importance of fire prevention in forest management. Land Economics, 81(2), 284–302.
- Barlow, R., & Levendis, W. (September/October 2015). 2014 cost and cost trends for forestry practices in the South. Forest Landowner Magazine, 23–31.
- Brazee, R., & Bulte, E. H. (2000). Optimal harvesting and thinning with stochastic prices. Forest Science, 46(1), 23–31.
- Brazee, R., & Mendelsohn, R. (1988). Timber harvesting with fluctuating prices. Forest Science, 34(2), 359–372.
- Buongiorno, J., & Zhou, M. (2015). Adaptive economic and ecological forest management under risk. Forest Ecosystems, 2(4) https://doi.org/10.1186/s40663-015-0030-y
- Clarke, H. R., & Reed, W. J. (1989). The tree cutting problem in a stochastic environment: The case of age-dependent growth. Journal of Economic Dynamics and Control, 13(4), 569–595.
- Dale, V. H., Joyce, L. A., Mcnulty, S., & Neilson, R. P. (2000). The Interplay between climate change, forests, and disturbances. The Science of the Total Environment, 262(3), 201–204.
- Deegen, P., & Matolepszy, K. (2015). Economic balancing of forest management under storm risk, The case of the Ore Mountains (Germany). Journal of Forest Economics, 21(1), 1–13.
- Dickens, D., & Moorhead, D. D. (2015). A guide to thinning pine plantations. School of Forestry and Natural Resources, University of Georgia Warnell. Georgia Forest Productivity, Publication number 0010.
- Ecke, F., Löfgren, O., & Sörlin, D. (2002). Population dynamics of small mammals in relation to forest age and structural habitat factors in Northern Sweden. Journal of Applied Ecology, 39(5), 781–792.
- Englin, J., Boxall, P., & Hauer, G. (2000). An empirical examination of optimal rotations in a multiple-use forest in the presence of fire risk. Journal of Agricultural Resource Economics, 25(1), 14–27.
- Fina, M., Amacher, G. S., & Sullivan, J. (2001). Uncertainty, debt and forest harvesting: Faustmann revised. Forest Science, 47, 188–196.
- Gong, P. (1994). Adaptive optimization for forest-level timber harvest decision analysis. Journal of Environmental Management, 40(1), 65–90.
- Gong, P. (1998). Risk preferences and adaptive harvest policies for even-aged stand management. Forest Science, 44(4), 496–506.
- Gong, P. (1999). Optimal harvest policy with first-order autoregressive price process. Journal of Forest Economics, 5(3), 413–439.
- Gong, P., Boman, M., & Mattsson, L. (2005). Non-timber benefits, price uncertainty and optimal harvest of an even-aged stand. Forest Policy and Economics, 7(3), 283–295.
- Gong, P., & Löfgren, K. G. (2007). Market and welfare implications of the reservation price strategy for forest harvest decisions. Journal of Forest Economics, 13(4), 217–243.
- Grado, S. C., & Husak, A. L. (2005). Economic analyses of a sustainable agroforestry system in the Southeastern United States. In J. R. R. Alavalapati, & E. Mercer (Eds.), Valuing agroforestry systems: Methods and applications. Dordrecht, The Netherlands: Kluwer Academic Publishers.
10.1007/1-4020-2413-4_3 Google Scholar
- Haight, R. G., & Holmes, T. P. (1991). Stochastic price models and optimal tree cutting: Results for loblolly pine. Natural Resource Modeling, 5(4), 423–443.
10.1111/j.1939-7445.1991.tb00255.x Google Scholar
- Haight, R. G., Smith, D., & Straka, T. (1995). Hurricanes and the economics of loblolly pine plantations. Forest Science, 41(4), 675–688.
- Haight, R. G., & Smith, W. D. (1991). Harvesting loblolly pine plantations with hardwood competition and stochastic prices. Forest Science, 37(5), 1266–1282.
- Harrison, W. M., & Borders, B. E. (1996) Yield prediction and growth projection for site-prepared loblolly pine plantations in the Carolinas, Georgia, Alabama, and Florida ( PMRC Technical Report 1996-1). Athens, GA: School of Forestry and Natural Resources, University of Georgia Warnell.
- Howard, P. (2014). Flammable planet: Wildfires and the social cost of carbon. The cost of carbon project report. NYU Law School, New York: Institute for Policy Integrity. Retrieved from http://costofcarbon.org/files/Flammable_Planet__Wildfires_and_Social_Cost_of_Carbon.pdf
- Humphrey, J. W., Davey, S., Peace, A. J., Ferris, R., & Harding, K. (2002). Lichens and bryophyte communities of planted and semi-natural forests in Britain: The influence of site type, stand structure and deadwood. Biological Conservation, 107(2), 165–180.
- Johansson, P. O., & Löfgren, K. G. (1985). The economics of forestry and natural resources. New York, NY: Basil Blackwell.
- Keyser, T. L., Smith, F. W., & Shepperd, W. D. (2009). Short-term impact of post-fire salvage logging on regenration, hazardous fuel accumulation, and understorey development in ponderosa pine forests of the Black Hills, SD, USA. International Journal of Wildland Fire, 18(4), 451–458.
- Kinnucan, H. W. (2016). Timber price dynamics after a natural disaster: Hurricane Hugo revisited. Journal of Forest Economics, 25(1), 115–129.
- Kirilenko, A. P., & Sedjo, R. A. (2007). Climate change impacts on forestry. Proceeding of the National Academy of Sciences of the United States of America, 104(50), 19697–19702.
- Lauer, C. J., Montgomery, C. A., & Dietterich, T. G. (2017). Spatial interactions and optimal forest mangement on a fire-threathened landscape. Forest Policy and Economics, 83(October), 107–120.
- Li, J., Hong, Y., Thapa, R., & Burkhart, H. E. (2015). Survival analysis of loblolly pine trees with spatially correlated random effects. Journal of American Statistical Association, 110(510), 486–502.
- Liu, Y., Prestemon, J. P., Goodrick, S. L., Holmes, T. P., Stanturf, J. A., & Vose, J. M. (2014). Future wildfire trends, impacts, and mitigation options in the southern United States. In J. M. Vose & K. D. Klepzing (Eds.), Climate change adaptation and mitigation management options: A guide for natural resource managers in southern forest ecosystems. Boca Raton, FL: CRC Press.
- Lohmander, P. (1988). Pulse extraction under risk and a numerical forestry application. Systems Analysis Modelling Simulation, 5(4), 339–354.
- Loisel, P. (2011). Faustmann rotation and population dynamics in the presence of a risk of destructive events. Journal of Forest Economics, 17, 235–247.
- Loisel, P. (2014). Impact of storm risk on Faustman rotation. Forest Policy and Economics, 38(January), 191–198.
- Lu, F., Gong, P., & Lu, F. (2003). Optimal stocking level and final harvest age with stochastic prices. Journal of Forest Economics, 9(2), 119–136.
10.1078/1104-6899-00026 Google Scholar
- Martell, D. L. (1980). The optimal rotation of a flammable forest stand. Canadian Journal of Forest Research, 10(1), 30–34.
- Mengak, M. T. (2012). Tips for creating a hunting lease. School of Forestry, University of Georgia Warnell and Natural Resources Cooperative Extension Circular 91.
- National Interagency Fire Center. (2017). Historical wildland fire information: human-caused fires. Retrieved from http://www.nifc.gov/fireInfo/fireInfo_stats_human.html
- Nordhaus, W. D. (2010). Global warming economics. Science, 294(5545), 1283–1284.
- Pimentel, D., Zuniga, R., & Morrison, D. (2005). Update on the environmental and economic costs associated with alien-invasive species in the United States. Ecological Economics, 52(3), 273–288.
- Poudel, B. N., & Paudel, K. P. (2018). An integrated approach to analyzing risk in bioeconomic models. Natural Resource Modeling, 31, e12172. https://doi.org/10.1111/nrm.12172
- Prestemon, J. P., & Holmes, T. (2008). Timber salvage economics. In T. P. Holmes, J. P. Prestemon & K. Abt (Eds.), The economics of forest disturbances: Wildfires, storms and invasive species. Dordrecht, The Netherlands: Springer.
10.1007/978-1-4020-4370-3_9 Google Scholar
- Prestemon, J. P., Wear, D. N., Stewart, F. J., & Holmes, T. P. (2006). Wildfire, timber salvage, and the economics of expediency. Forest Policy and Economics, 8(3), 321–322.
- Pukkala, T., & Kellomaki, S. (2012). Anticipatory vs adaptive optimization of stand management when tree growth and timber prices are stochastic. Forestry: An International Journal of Forest Research, 85(4), 463–472.
10.1093/forestry/cps043 Google Scholar
- Rakotoarison, H., & Loisel, P. (2017). The Faustmann model under storm risk and price uncertainty: A case study of European beech in Northwestern France. Forest Policy and Economics, 81, 30–37.
- Reed, W. J. (1984). The effects of the risk of fire on the optimal rotation of a forest. Journal of Environmental Economics and Management, 11(2), 180–190.
- Reed, W. J., & Apaloo, J. (1991). Evaluating the effects of risk on the economics of juvenile spacing and commercial thinning. Canadian Journal of Forest Research, 21(9), 1390–1400.
- Rudolph, C., & Conner, R. (1991). Cavity Tree selection by red-cockaded woodpeckers in relation to tree age. The Wilson Bulletin, 103(3), 458–467.
- Schultz, R. P. (1997), Loblolly pine: The ecology and culture of loblolly pine (Pinus taeda L.) Agriculture Handbook 713. Washington, DC: US Department of Agriculture, Forest Service.
- Southern Regional Extension Forestry, 2014. The economic importance of forestry in the South-2013 (Technical Bulletin SREF-FE-001). Retrieved from http://www.southernforests.org/resources/publications/Forest_Econ_Fact_Sheet_2013.pdf
- Stanturf, J. A., Goodrick, S. L., & Outcalt, K. W. (2007). Disturbance and coastal forests: A strategic approach to forest management in hurricane impact zones. Forest Ecology and Management, 250(1–2), 119–135.
- Staupendahl, K., & Möhring, B. (2011). Integrating natural risks into silvicultural decision models: A survival function approach. Forest Policy and Economics, 13(6), 496–502.
- Straka, T. (2011). Contribution of wildlife to the value of U.S. Southern Forestland. Journal of the American Society of Farms Managers and Rural Appraisers, 74(1), 23–32.
- Susaeta, A., Carter, D. R., Chang, S. J., & Adams, D. C. (2016). A generalized Reed model with application to wildfire risk in even-aged Southern United States pine plantations. Forest Policy and Economics, 67(June), 60–69.
- Swallow, S. K., Parks, P. J., & Wear, D. N. (1990). Policy-relevant nonconvexities in the production of multiple forest benefits. Journal of Environmental Economics Management, 19(3), 264–280.
- Timber Mart South. (2017) Timber Mart South market newsletter: Annual stumpage prices 1982–2016. School of Forestry and Natural Resources, Center for Forest Business, University of Georgia Warnell and Frank W 2017, Athens, GA.
- US Department of Labor Bureau of Labor Statistics. (2017). Producer price index industry data. Retrieved from http://data.bls.gov/cgi-bin/dsrv?pc
- Ziegler, J. P., Hoffman, C., Battaglia, M., & Mell, W. (2017). Spatially explicit measurements of forest structure and fire behavior following restoration treatments uin dry forests. Forest Ecology and Management, 386, 1–12.
