Huang, Jin ; Sujit K. Ghosh, Committee Member,Barry K. Goodwin, Committee Member,Robert C. Abt, Committee Chair,Brian. C. Murray, Committee Member,Subhrendu K. Pattanayak, Committee Member,Huang, Jin ; Sujit K. Ghosh ; Committee Member ; Barry K. Goodwin ; Committee Member ; Robert C. Abt ; Committee Chair ; Brian. C. Murray ; Committee Member ; Subhrendu K. Pattanayak ; Committee Member
This dissertation provides a quantitative analysis of the adaptability in forest management to future risks using existing data describing pine growth and management across a range of conditions in the southern U.S. Future risks include gradual climatic change, catastrophic events, price and yield risks. The adaptive options considered include rotation ages, thinning ages, thinning intensity and frequency, planting density and stand stocking. Using a bio-economic model approach, two empirical yield models based on U.S. Forest Service FIA data are integrated with an extended Faustmann and a Real Options optimization models respectively. Simulation results are obtained across risk categories and model types. Marginal and joint effects of risk are derived and comparisons between different integrated models are made. Forest managers' optimal decisions in response to risk are found to be sensitive to the set of adaptive options. The “standardâ€Âoptimal rotation results do not necessarily hold if stand density control and thinning options are considered. The impacts of discrete catastrophic events on forest management adaptation and welfare are found to be more important than the gradual climate change impact. Gradual climate change within the range of Hadley 3 scenarios does not lead to significant changes in optimal rotation age, stand density or thinning ages but the change in forest rents may be significant. Depending on the impact of climate change on agriculture rent, we would expect more adaptations at the extensive margin (land use change) than the intensive margin (silvicultural intensity).
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An Empirical Analysis of Adaptability to Climate Change and Risk in Forest Management