Determining optimal forest rotation ages and carbon offset credits: Accounting for post-harvest carbon storehouses

Sequestering carbon in forest ecosystems is important for mitigating climate change. A major policy concern is whether forests should be left unharvested to avoid carbon dioxide (CO2) emissions and store carbon, or harvested to take advantage of potential carbon storage in post-harvest wood product sinks and removal of CO2 from the atmosphere by new growth. The issue is addressed in this paper by examining carbon rotation ages that consider commercial timber as well as carbon values. A discrete-time optimal rotation age model is developed that employs data on carbon fluxes stored in both living and dead biomass as opposed to carbon as a function of timber growth. Carbon is allocated to several ecosystem and post-harvest product pools that decay over time at different rates. In addition, the timing of carbon fluxes is taken into account by weighting future carbon fluxes as less important than current ones. Using simple formulae for determining optimal rotation ages, we find that: (1) Reducing the price of timber while increasing the price of carbon will increase rotation age, perhaps to infinity (stand remains unharvested). (2) An increase in the rate used to discount physical carbon generally reduces the rotation age, but not in all cases. (3) As a corollary, an increase in the price of carbon increases or reduces rotation age depending on the weight chosen to discount future carbon fluxes. (4) Site characteristics and the mix of species on the site affect conclusions (2) and (3). (5) A large variety of carbon offset credits from forestry activities could be justified, which makes it difficult to accept any.

Automated summary

Sequestering carbon in forest ecosystems is crucial for mitigating climate change. This study explores whether forests should be left unharvested or harvested to maximize the storage of carbon and removal of CO2. A model is developed, considering carbon fluxes and decay rates, to determine optimal rotation ages. The findings suggest that carbon price, discount rate, site characteristics, and species mix all influence the optimal rotation age, making it difficult to determine the best approach.