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Biophysical and Economic Analysis of Black Spruce Regeneration in Eastern Canada using Global Climate Model Productivity Outputs

This study explores the biophysical potential and economic attractiveness of black spruce (Picea mariana) regeneration in eastern Canada under future climate changes. It integrates process-based ecosystem model simulated forest productivities from three major global climate models (GCMs), growth and yield formulations specific to black spruce and economic analyses to determine the overall investment value of black spruce, both including and excluding carbon sequestration benefits. Net present value (NPV) was estimated to represent the financial attractiveness of long-rotation forest plantations through time. It was assumed that stands would not be harvested at volumes less than 80 m3 ha-1. The price of stumpage was set to $20 m-3, stand establishment cost was set to $500 ha-1, and the discount rate was considered at 4%, with sensitivity analyses conducted around these assumptions. The growth and yield of black spruce was simulated for an extreme future climate scenario – IPCC-RCP 8.5. The results suggested a general North-South gradient in forest productivity where gross merchantable wood volumes increased with decreasing latitudes. This pattern was also observed in NPVs, with higher values projected for the southern portion of the study area. Based on the base economic assumptions and sensitivity analyses, study results suggested that black spruce plantations are not economically attractive, unless carbon sequestration benefits of at least $5 ton-1 CO2 are realized. Further sensitivity analyses showed that discount rate plays a significant role in determining the optimal harvest age and value. Furthermore, the optimal harvest rotation age increases with increasing carbon price by approximately 9 to 18 years. / Thesis / Master of Science (MSc)

Identiferoai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/19435
Date January 2016
CreatorsLee, Jung Kuk
ContributorsArain, Altaf, Environmental Science
Source SetsMcMaster University
LanguageEnglish
Detected LanguageEnglish
TypeThesis

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