This dissertation aims to develop the economics of even-aged Scots pine (Pinus sylvestris L.) management. In our economic-ecological model, a detailed process-based forest growth model is connected to an economic description of stand management. The process-based growth model is able to describe forest growth in management regimes and climate conditions previously not experienced, because it applies causal relationships and feedbacks instead of statistical correlations. Optimization is carried out with an effective general pattern search algorithm. The optimized variables include rotation length, initial stand density, and the timing, type, intensity, and number of thinnings. Essential model details include the quality pricing of timber and detailed harvesting cost functions. Integration of carbon subsidy systems into the model enables the determination of the economically optimal carbon storage with various carbon price levels. Finally, the growth model is extended to include a direct link between climate change and tree growth, to optimize stand management in a changing climate. The dissertation thesis is composed of a summary section and three articles, which produce a coherent and comprehensive picture on the optimal stand management of Scots pine in the relevant growth conditions of Fennoscandia. The results demonstrate the necessity to simultaneously optimize all stand management variables, and the advantages of having a detailed model. Optimal stand management is shown to be sensitive to growth conditions, interest rate, and management objective, along with the design of the carbon subsidy system and the subsidy level. The stand-level analysis is additionally extended to the national level, and adapting forest management was found to potentially be a cost-efficient method for carbon abatement in Finland. Furthermore, the optimal adaptation of stand management in a changing climate remarkably improves the economic surplus from forestry.
|Tilldelningsdatum||15 dec 2017|
|Status||Publicerad - 15 dec 2017|
|MoE-publikationstyp||G5 Doktorsavhandling (artikel)|
- 4112 Skogsvetenskap