Impact of Harvest-Level Changes on Carbon Accumulation and Timber Stumpage Prices in Mississippi

increased demand for carbon offsets leading to higher carbon prices and, therefore, encourage forest landowners to enter into forest carbon offset contracts. As a result, qualifying forest tracts might be withdrawn from harvest during the contract leading to decreased timber supply in the short term. Timber markets will respond to such a situation with increased timber stumpage prices (Sohngen and Mendelsohn 2003, Stainback and Alavalapati 2002). However, in the long term, timber harvests might increase as carbon contracts are completed allowing landowners to harvest their forests. Consequently, timber stumpage prices would then decrease (Sohngen et al. 2008) assuming that other factors related to timber supply remain unchanged. Potential impacts of implementing carbon policies and programs on timber supply and timber stumpage prices were demonstrated by several studies. Sohngen et al. (2008) analyzed the effect of carbon policy on carbon accumulation and timber supply at the global level using the Dynamic Timber Supply Model. They showed that carbon policy would induce owners of hardwood forests in the southern United States to withhold their forests from harvest in the short term, which would result in increased timber prices. However, they also showed that additional land supply, longer rotations, and improved forest management would increase timber supply in the long term, causing timber prices eventually to fall. In another study, Sohngen and Mendelsohn (2003) indicated that implementation of the least cost strategy (minimizing the present value of the total costs of greenhouse gas damage and its abatement) to control greenhouse gases would result in global carbon sequestration of 102 billion metric tons. During the same time, global timber supply would increase by up to 785 million cubic meters (m) resulting in lower global timber prices in the long term. Other studies indicated that payments for carbon sequestered by forests will lead to longer forest rotations (Nepal et al. 2009, Sohngen et al. 2008, Gutrich and Howarth 2007, Stainback and Alavalapati 2002, van Kooten et al. 1995) and reduced timber supply in the short term (Sohngen et al. 2008, Sohngen and Mendelsohn 2003, Stainback and Alavalapati 2002). Several studies have indicated that current US carbon prices do not pay enough to make forest-based carbon sequestration financially viable (Nepal et al. 2012, Latta et al. 2011, Malmsheimer et al. 2008). Consequently, under current carbon market conditions, landowners are more likely to retain their right to sell timber rather than enroll their forest stands into carbon contracts. However, if the United States implements a mandatory carbon policy, it is expected that demand for carbon will increase leading to higher carbon prices (Green Assets 2012, US EPA 2009) and improved financial viability of forestry-based carbon sequestration strategies (Malmsheimer et al. 2008). This study investigated how future carbon accumulation in Mississippi’s forests and harvested wood products will be impacted by changes in future harvest levels during 2006–2051. In addition, the study examined the impact of such changes in harvest levels on timber stumpage prices and quantified the resulting changes in timber and carbon revenues in Mississippi. Mississippi was selected as the study area because it is considered to have a great potential to increase carbon sequestration both in standing trees and harvested wood products due to its large area under timberland (8 million ha) and a large quantity of annual timber harvest (30 million m) (USDA Forest Service 2010). Other neighboring states in the southern United States, including Alabama, Arkansas, and Louisiana, share similar forest sector characteristics such as timberland area and ownership, timber inventory, harvest levels, and timber products output (Smith et al. 2009). Therefore, we expect that our analysis of statewide impacts of harvest-level changes in Mississippi can provide useful benchmark information, not only for Mississippi, but also for these neighboring states as well as other states in the southern United States. Methods and Materials The Model The Subregional Timber Supply (SRTS) model (Abt et al. 2009) was used to examine a business-as-usual (BAU) and four alternative timber-harvest scenarios in terms of carbon accumulation, timber stumpage prices, and timber and carbon revenues in Mississippi during 2006–2051. The year 2006 was selected as a starting point for the analysis because it was the most recent year for which forest inventory data were available for Mississippi, whereas the year 2051 represents the end of harvest projection available for the BAU scenario. The SRTS is a partial market equilibrium model that combines economic and forest inventory information to determine impacts of changes in timber demand and supply on timber inventory and timber stumpage markets (Abt et al. 2009). The original version of the model was designed to simulate market for only one single product of two species groups and estimating the total timber volume for softwoods and hardwoods. The model has been updated and can be used to project timber supply for multiple products and subregions (Abt et al. 2009). The earlier versions of this timber market model were used to project timber supply in the US South and Northeast (e.g., Bingham et al. 2003, Sendak et al. 2003, Prestemon and Abt 2002, Abt et al. 2000, Pacheco et al. 1997, Abt et al. 1993). The model has also been used to project impacts of climate change on timber supply in the US South (Abt and Murray 2001) and analyze impacts of nonmarket forest values on timber supply decisions of nonindustrial private forestland (NIPF) landowners (Pattanayak et al. 2002). Modeling Timber Demand and Supply Demand for timber was modeled as a function of stumpage price and a demand shifter, whereas supply of timber was modeled as a function of stumpage price, forest inventory, and a supply shifter using the SRTS market module. The statewide equilibrium harvest in year t was determined by interaction of the following timber demand and supply functions (Abt et al. 2000):