Using bioeconomic models to assess research priorities: a case study on afforestation as a carbon sequestration tool

Abstract

We have developed a spatial cost–benefit afforestation model that includes the tracking of five carbon pools. In this application we represent three possible afforestation strategies that could be implemented in Canada using plantations of hybrid poplar, hardwoods, and softwoods with average expected growth rates of 12–14, 5–7, and 5–7 m3· ha–1·year–1 respectively. The model provides spatially explicit insights into the cost effectiveness of afforestation as a carbon sequestration tool. Here we develop an elasticity metric and experiment to assess model sensitivity and use the results to make recommendations about research priorities. The most important biological variables across all scenarios include site suitability, which is related to refining the spatial estimates of potential yields, biomass to carbon ratios, and wood density. The most important economic variables include refinement and lowering of establishment costs and agricultural opportunity costs. Parameters that have a low impact on the break-even carbon price, suggesting refinements in knowledge in these areas would be relatively less beneficial, include decay rates for forest products, stand senescence age (the age when stand mortality reaches its maximum), bioenergy and pulpwood prices, and mean residual time for leaf litter. Less importance was also placed on the proportions of forest products in the total harvest and refining a fossil fuel substitution coefficient.