Managing Forests for Carbon and Timber: A Markov Decision Model of Uneven-aged Forest Management With Risk

Abstract

This paper calculates steady state management decisions that, if followed indefinitely, provide an adaptive strategy that maximizes the value from timber and carbon sequestration when risk is present. By including carbon offsets directly in the objective function of a Markov decision process (MDP) model, we find long-term trade-offs exist between economic and ecological outcomes. An economic supply schedule is provided, which shows an exponential increase in the cost of sequestration. Moderate carbon prices effectively sequester additional CO 2 from the atmosphere while having a positive impact on ecological indicators such as size and species diversity. In contrast, high carbon prices promote more of a monoculture in order to maximize expected forest value in the long run from carbon sequestration. This study finds evidence that the optimal adaptive decisions are sensitive to the magnitude of carbon prices, and consequently, so too are ecological outcomes. While some governments acknowledge the influence carbon markets have on the ecological integrity of the forest, fluctuations in carbon prices within a cap-and-trade market likely influence the optimal decision making of the forest manager, and thus, the ecological landscape of the forest itself.

Developing Detailed Shared Socioeconomic Pathway (SSP) Narratives for the Global Forest Sector

“…However, uncertainties associated with natural disturbance can significantly affect forest planning (Kurz et al, 2008;Lindroth et al, 2009). Furthermore, placing value on forest carbon offsets may lead to altered long-term ecological outcomes of the forest (Johnston and Withey, 2017). The role of forest management in mitigating CO 2 extends beyond the forest as governments increasingly turn to wood biomass energy as a substitute for fossil-fuels (McDermott et al, 2015).…”

Carbon Uptake and Forest Management under Uncertainty: Why Natural Disturbance Matters

“…Simulation allows for more complex and realistic analyses. Early papers employing this approach include Routledge (1980), van Kooten et al (1992), Asante et al (2011), and Johnston and Withey (2017), and Buongiorno et al (2017). Routledge argues that the optimal rotation age can increase under uncertainty, but finds a tendency for uncertainty to reduce rotation age, which corresponds to the finding by van Kooten et al using stochastic dynamic programming (SDP).…”

Prices of raw-wood assortments in selected markets of central Europe and their development in the future

“…They are, however, influenced by various factors, which need to be identified and quantified if possible. These factors and their influence result in a certain extent of risk or uncertainty in managing the forest land, arising from a huge variability of forest ecosystems and natural conditions and global climate change (Holécy and Hanewinkel 2006;Brunette and Couture 2013;Hanewinkel et al 2013;Brunette et al 2015;Johnston and Withey 2017). Predicting the extent of these factors and their effect is possible only by following the information on their previous development and using a mathematical model based on such development.…”