RTI uses cookies to offer you the best experience online. By clicking “accept” on this website, you opt in and you agree to the use of cookies. If you would like to know more about how RTI uses cookies and how to manage them please view our Privacy Policy here. You can “opt out” or change your mind by visiting: http://optout.aboutads.info/. Click “accept” to agree.
As the demand for forest products and carbon storage in standing timbers increases, intensive planting of forest resources will increase. As the use of plantation practices continues to increase, it is important to understand the effects that forest plot characteristics have on the likelihood of planting occurring. Depending on the goals of a policy or program, increasing forest planting could be a desirable outcome or something to avoid. While planted forests have been shown to be more productive in timber production and can sequester carbon at faster rates than naturally regenerated stands, planted forests have also been shown to limit biodiversity through the destruction of undergrowth during planting and thinning, and limit the variability in age class of standing timber. This study uses a logistical regression function to estimate the likelihood that forest plots will be intensively planted based on physical, climate, and economic factors. These results are then used to highlight how future expansion of planted forests may occur at both the intensive (planting on existing forests post-harvest) and extensive (planting on non-forestland) margins. These results can provide policymakers with information on the potential spatial extent of forest planting to aid in conservation planning, regional climate action strategies, or economic incentives designed to boost the local forest products industry. Furthermore, our results can also inform national or global land use models used to assess interactions between markets, policy, environmental change, and forest resource management.