a Climate Change Policy Partnership, Duke University b Nicholas School of the Environment and University Program in Ecology, Duke University

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1 A virtual field test of forest management carbon offset protocols: the influence of accounting Christopher S. Galik a,c Megan L. Mobley b Daniel deb. Richter b Mitigation and Adaptation Strategies for Global Change (2009) DOI /s Original publication available at Abstract Of the greenhouse gas (GHG) mitigation options available from U.S. forests and agricultural lands, forest management presents amongst the lowest cost and highest volume opportunities. A number of carbon (C) accounting schemes or protocols have recently emerged to track the mitigation achieved by individual forest management projects. Using 50-year C cycling data from the Calhoun Experimental Forest in South Carolina, USA, C storage is estimated for a hypothetical forest management C offset project operating under seven of these protocols. After 100 years of project implementation, net C sequestration among the seven protocols varies by nearly a full order of magnitude. This variation stems from differences in how individual C pools, baseline, leakage, certainty, and buffers are addressed under each protocol. This in turn translates to a wide variation in the C price required to match the net present value of the nonproject, business-as-usual alternative. Collectively, these findings suggest that protocol-specific restrictions or requirements are likely to discount the amount of C that can be claimed in real world projects, potentially leading to higher project costs than estimated in previous aggregate national analyses. Key Words: carbon offsets, carbon sequestration, forest management, offset markets 1. Introduction The global forest sector is viewed as a key component in greenhouse gas (GHG) mitigation efforts (e.g., Pacala and Socolow 2004). In the United States, the forest sector comprises a significant carbon (C) sink, with U.S. forests and forest products sequestering over 700 million metric tons (t) of carbon dioxide equivalents (CO 2 e) per year (U.S. Environmental Protection Agency 2008). With a sufficiently strong price signal, afforestation and forest a Climate Change Policy Partnership, Duke University b Nicholas School of the Environment and University Program in Ecology, Duke University c Corresponding author: (+1) ; csg9@duke.edu. 1

2 management in the U.S. can sequester an additional 1.2 billion t CO 2 e per year (U.S. Environmental Protection Agency 2005). Beyond sheer mitigation potential, the inclusion of forest and other biological C sequestration activities in comprehensive climate policy can provide a pool of low-cost mitigation options and lower the overall costs of meeting emission reductions (Amano and Sedjo 2006). Of the GHG mitigation options available from U.S. forests and agricultural lands, forest management presents amongst the lowest cost and highest volume opportunities (U.S. Environmental Protection Agency 2005). Numerous recent proposals in the United States Congress contemplate the participation of the forest sector in comprehensive climate policy (H.R. 2454, American Clean Energy and Security Act of 2009; S.3036, Lieberman-Warner Climate Security Act of 2008). In these proposals, forests are generally classified as an uncapped sector, one that is not directly regulated by an emissions cap. As an uncapped sector, the primary opportunity for forests to participate under a cap-and-trade program would be in offset markets. Buyers, sellers, and policy makers must all have confidence in the accounting system used to track the GHG mitigation achieved by particular projects if forests are to fully participate in offset markets. Unfortunately, forest management offset project accounting remains a difficult undertaking. This is largely due to the dynamic nature of C storage in forest systems and a lack of standardized management and land use practices across users and landscapes. Owing to both the complexity of the issue and a conspicuous absence of a single federal standard, a variety of forest management C offset accounting approaches have emerged in recent years. This has created uncertainty for project developers and investors, alike. To allay this uncertainty, standardization of accounting methodology is a likely prerequisite to the full participation of forest management offsets in comprehensive climate policy. An assessment of the lessons learned in early forest offset project implementation is, in turn, likely a necessary first step in the standardization process. The literature suggests that a great deal of variation in cost and net C sequestration exists across projects and project types (Richards and Stokes 2004; Stavins and Richards 2005). Research also suggests that project scale (Mooney et al. 2004), site quality (Huang and Kronrad 2006), forest type (Gutrich and Howarth 2007), and individual management decisions (Garcia-Gonzalo et al. 2007; Hoover and Stout 2007; van Kooten et al. 1995) can all impact the economics of forest management offset projects. The literature, however, contains few examples of the financial and/or environmental 2

3 implications of forest management offset projects as viewed through the lens of the actual accounting schemes that will govern offset project implementation (e.g., Pearson et al. 2008). In light of this critical research gap, work was initiated in early 2008 to provide a better understanding of the real-world differences among the forest management offset project accounting protocols in use today. Here, long-term sequestration data from the Calhoun Experimental Forest in South Carolina is used to conduct side-by-side virtual trials of seven distinct forest management offset protocols. In the analysis that follows, particular attention is paid to the accounting methods used and the implications for net creditable C, or the amount of stored C that may be reported, registered, or claimed by the project developer. The impacts of key assumptions are reviewed, and implications for an emerging C market discussed. 2. Methods Project Overview The analysis is based on the hypothetical extension of rotations of planted loblolly pine (Pinus taeda L.) from 25 to 50 years. The hypothetical project consists of ten 10-hectare (ha), even-aged stands of identical composition and site quality (site index 75, base age 25), implemented for a period of 100 years. At project inception, there are two stands each of 0, 5, 10, 15, and 20 years old. To phase in the shift in rotation over time, one stand in each pair is managed on a 25-year rotation until the first harvest, and then converted to a 50-year rotation. The other stand in each pair is immediately converted to a 50-year rotation. The C sequestration data on which the hypothetical project is based is derived from C inventories at the Calhoun Experimental Forest in Union County, South Carolina, USA. Based on decades of observations and repeated sampling (Urrego 1993; Richter et al. 1994; Richter et al. 1999; Richter and Markewitz 2001), a spreadsheet model was created to simulate repeated 25- and 50-year clearcut harvests at the Calhoun Forest, allowing an ex post monitoring perspective on the hypothetical project. In constructing the model, tree biomass was estimated by a combination of allometric equations depending on age and tree component (Nelson and Switzer 1975; Pehl et al. 1984; Shelton et al. 1984; Van Lear et al. 1986; Baldwin 1987; Kapeluck and Van Lear 1995). Further information regarding the treatment of specific pools, including the transfer of C between pools, can be found in Galik et al. (2008). 1 An expanded discussion of the methods employed here can be found in Galik et al. (2008). 3

4 Implementation of the hypothetical project is evaluated under seven distinct offset accounting schemes. This research focuses on those schemes in which distinct protocols or methodologies were available for forest management projects. Collectively, the selected accounting schemes provide a representative sample of the breadth of U.S. voluntary and emerging state and region compliance registries and markets. Protocols or methodologies specifically examined here include: 1. U.S. Department of Energy (DOE) 1605(b) Technical Guidelines for Voluntary Reporting of Greenhouse Gases (Office of Policy and International Affairs 2007); 2. Georgia Forestry Commission (GFC) Carbon Sequestration Registry Project Protocol (Georgia Forestry Commission 2007); 3. Chicago Climate Exchange (CCX) Sustainably Managed Forests/Long-Lived Wood Products Protocols (Chicago Climate Exchange 2007b; Chicago Climate Exchange 2007a); 4. California Climate Action Reserve (CAR) Forest Project Protocol (Climate Action Reserve 2007); 5. Voluntary Carbon Standard (VCS) Improved Forest Management Protocol (Voluntary Carbon Standard 2007a; Voluntary Carbon Standard 2007b); 6. a protocol derived from recommended concepts in Duke University s Harnessing Farms and Forests in the Low-Carbon Economy (HFF) (Willey and Chameides 2007); and 7. a draft recommendation for active forest management offset projects proposed by the State of Maine under the Regional Greenhouse Gas Initiative (RGGI) (State of Maine et al. 2008). For each protocol, the C in both required and eligible (but optional) forest C pools is tallied, baseline determined, and off-site leakage, uncertainty discounts, and reserve set-asides deducted as outlined in the relevant protocol (Table 1). Due to the hypothetical nature of the project, a number of assumptions were necessary. To capture the full potential range of creditable C generated, three scenarios are considered: base-case, high C, and low C. High and low C scenarios simply make use of those values described above and listed in Table 1 that generate the highest and lowest amounts of net creditable C, respectively. Base-case scenarios 4

5 Table 1. Overview of key components of the protocols examined in this analysis. Values in Reversal, Uncertainty, or Leakage columns indicate the range of possible values (base case estimates listed in brackets) for key components; the absence of values for a specific category does not imply that the protocol does not consider that component, only that there are no mechanisms to adjust creditable C on the basis of it. Only pools contributing significant amounts of C to sequestration totals at the Calhoun site are included; a given protocol may include more pools than those evaluated here. Entity Baseline Pools Included A Quantification Reversal Uncertainty Leakage of Wood Products 1605(b) Base-year LT, BG, DT, L, S, WP 100-Year GFC Base-year LT, BG, S*, WP* 100-Year CCX Base-year LT, BG, WP* 100-Year [20%] 0-20% - [20%] CAR Single-practice LT, BG, DT, L*, S*, WP* (optional) % - Performance Standard [10%] VCS Single-practice LT, BG*, DT*, L*, S*, WP* 100-Year 5-60% % Performance Standard [10%] [10%] HFF Cohort Group LT, BG, DT, L, S, WP* (none specified) % Performance Standard [43%] RGGI Modified Base-year LT, BG, DT*, WP* Regional 0-20% - - Threshold [20%] A C pools include: LT Live Tree; BG Belowground; DT Dead Tree; L Litter; S Soil; WP Wood Products. * denotes optional pools. 5

6 represent a best estimate of conditions as they would have existed on the ground for the hypothetical project. For all protocols, C accruing above the baseline (after all necessary deductions for buffer, leakage, certainty and other components), is assumed to be eligible for crediting. It is also assumed that credits are bought back from the market in years of negative sequestration. Baseline and wood product methodologies common to several protocols are described below, followed by protocol-specific calculations or assumptions Baseline Methodologies Base-year: Baseline under a base-year approach equals the total C onsite at project inception. Under 1605(b), GFC, and CCX, all C accruing above the baseline is assumed to be additional. The rate of C accumulation under the draft RGGI protocol is based on the relation of a project s starting C stock to U.S. Forest Service Forest Inventory and Analysis (FIA) mean per hectare C storage for similar forest types in the area (see State of Maine et al. 2008). Single-Practice Performance Standard: Baseline under a single-practice performance standard equals the estimated C sequestered under the management scenario that best approximates what would have been done in the absence of the project. Here, this is assumed to be 25-year rotations. Cohort Group Performance Standard: Under the cohort group performance standard, observed stand ages in the region are used to derive a baseline. A conceptually similar method using harvest probabilities is described in Murray and Brown (2007). Here, an age class distribution for privately-held planted loblolly forests in the South Carolina Piedmont is derived using FIA year data (U.S. Forest Service 2008), and then multiplied by the C stock at the midpoint of each age class as derived from a Carbon On-Line Estimator (COLE) 1605(b) query for planted loblolly forests in the area (The Carbon Online Estimator 2008). This yields average C storage for each age class, and upon summation across age classes, an estimate of total C stocking. No creditable C is generated while a project s stocking level is below the performance standard; all C above the standard is eligible for crediting Wood Product Methodologies 100-Year Method: The 100-Year method implicitly assumes that all C remaining in wood products in use or in landfills after 100 years is permanently stored. To estimate this fraction of 6

7 the harvested wood product stream, conversion factors listed in Smith et al. (2006) are used to derive harvested wood volume, fraction of this volume that is either softwood or hardwood, fraction that is either sawtimber or pulpwood, and fraction of the resulting wood products projected to remain in use and in landfills 100 years after harvest. A first step in this process is to use estimates of Live Tree C at the time of harvest to generate harvested volumes for hardwood and softwood pulpwood and sawtimber. Because the data on which the project is based is not expressed in terms of timber volume but rather gross C sequestration, the following equation is used (derived from Smith et al. 2006) to solve for harvested volume in units of m 3 ha 1 (V): Live Tree C (t ha 1 ) = 0.5 * V * FS * FT * SG where FS is the fraction of the harvested stock that is either hardwood or softwood, FT is the fraction of the harvested stock that is either sawtimber or pulpwood, SG is the specific gravity of the species harvested, and 0.5 approximates the C fraction of wood. Values of FS, FT, and SG for Southern loblolly-shortleaf pine forest types are derived from Smith et al. (2006), as are conversion factors to translate total C back into estimates for each species and type. The amount of C contained in harvested hardwood and softwood pulpwood and sawtimber is then multiplied by the fraction that is expected to remain in use or in landfills for 100 years after harvest. Credit for this amount is taken in the year of harvest. Regional Threshold: Eligibility to claim credit for C stored in wood products under a regional threshold approach is dependent on the relationship between project harvests and regional removals. Average removals for the project are estimated as: Project Removals = (V * 100) / 50 where V represents harvested volume in units of m 3 ha 1, a constant of 100 scales the harvest up to the project area, and a constant of 50 converts single rotation harvests into annualized removals. After converting from cubic meters to cubic feet, the hypothetical project s harvest rate is found to exceed average removals for loblolly in South Carolina as derived from U.S. Forest Service (2007). The difference between these two removal rates is scaled up to removals 7

8 per-hectare, per-rotation, and then into fraction of wood products projected to remain in use and in landfills 100 years after harvest using the process outlined under the 100-year method above. Credit for this amount is taken in the year of harvest Protocol-Specific Notes and Assumptions U.S. DOE 1605(b): For the purposes of this analysis, all pools under the 1605(b) accounting methodology are classified as required. It is perhaps technically more appropriate to classify all pools as optional, but this would result in no creditable C being generated under the required pool scenario explored here, thus limiting comparison with other protocols. Georgia Forestry Commission: The GFC protocol was not explicitly designed for implementation in South Carolina, but its evaluation here provides an opportunity for direct comparison with other major protocols. CCX Sustainably Managed Forests/Long-Lived Wood Products Protocols: Wood products are considered to be an optional pool here, as they are governed by a separate CCX protocol. Uncertainty discounts range from 0% for C storage estimated via annual in-field inventories to up to 20% for modeled C estimates. A base-case deduction of 20% is assumed here. The size of the buffer is assumed to remain a constant proportion relative to the project C stock. The buffer is not drawn upon in years where emissions exceed sequestration, nor are buffer credits returned to the project after the 100 year project lifespan. CAR Forest Project Protocol: 2 The CAR protocol was not explicitly designed for implementation in South Carolina, but it is assumed that project meets all relevant CAR additionality and project eligibility requirements. Under current CAR guidelines, optional pools cannot be certified, and therefore cannot generate creditable C as defined by this analysis. Consequently, optional pools are excluded here. Quantification of off-site leakage is not required and a methodology is not provided, so leakage is excluded as well. CAR uncertainty discounts 2 The CAR forest protocol is in the process of being revised as of the drafting of this article. The latest draft of the protocol available to the authors at the time of submission (version 3.0, June 22, 2009) represents a significant shift from the CAR protocol evaluated herein. Preliminary analysis suggests that if implemented in its current form, an updated CAR forest management protocol all-pools scenario would generate average annual creditable C values approximately midway between the HFF and current CAR protocol explored here but with greater potential variability. Significantly less creditable C is generated by the draft version than the current CAR protocol when limiting the analysis to only required pools, with the draft protocol again exhibiting greater variability than the current version. 8

9 range from 0% to 30% depending on the sampling error at the 90% confidence level. A base case error of 10% is assumed. VCS Improved Forest Management Protocol: It is assumed that the project satisfies all relevant additionality and project eligibility requirements. Discounts for leakage range from 10% to 40%; a base-case leakage rate of 10% is assumed as it is expected that the project would maintain consistent long-term timber supplies. Buffer set-asides range from 5% to 60%; a base-case buffer of 10% is assumed based on a low risk project classification. Credits need not be replaced on a 1-for-1 basis if removed from the buffer in years of negative sequestration. Additional credits are bought back from the market if negative sequestration exceeds the amount in the buffer. A portion of buffer may be released back to the project if risk ratings are maintained or reduced from one verification event to the next. Future withholdings may also be reduced. It is assumed that buffer reduction rates vary between 0 and 15% reduction, with subsequent verification taking place at 5 year intervals. No buffer reduction is assumed as a base case. Harnessing Farms and Forests: Depending on ownership and geographic area selected, the cohort group performance standard baseline ranges from tc ha -1 (FIA SC Survey Unit 3 privately owned) to tc ha -1 (FIA SC Survey Unit 3 private and public ownership). No accounting methodology is outlined for wood products, so the pool is excluded. Leakage is calculated based on an equation derived from Murray et al. 2004: Leakage = (100 * e * C N ) / (e E * [1 + Φ]) C R Price elasticities of supply (e) are assumed to range from to (Adams and Haynes 1996), and a value of 0.4 is assumed for price elasticity of demand (E) (Willey and Chameides 2007). It is assumed that the project comprises a small portion of the timber market, so market share (Φ) drops from the equation. C emission intensities are assumed to be equal both on-site (C R ) and off-site (C N ), and are likewise dropped. This yields leakage rates of 32.5% to 44.5%. A base-case leakage rate of 43% is estimated using 0.3 as the price elasticity of supply and 0.4 for demand. Draft Recommendation, Active Forest Management (RGGI): The modeled 25-year rotation is used to approximate pre-project conditions, yielding a total-project starting C stock of 60.2 t ha -1 9

10 for both required and all pool scenarios. These values are achieved the year prior to project initiation. Depending on ownership and geographic area selected, FIA mean C values range between 51.6 and 56.7 t ha -1 for required pools and between 62.7 and 68.6 t ha -1 for all eligible pools. The draft RGGI protocol does not require a calculation of leakage, but does require that the forest on which the project exists either be certified or that harvest rates not be exceptionally lower than the average removal rates for forests in that area. As described in Section , estimates of timber production from the project exceed average removals for loblolly in South Carolina. The draft protocol suggests that a buffer may be required if insurance is not secured, but an exact amount is not specified; a 20% buffer is assumed here as a base case Quantification of Net Creditable Carbon calculated as: For each protocol and assumption scenario, net creditable C (NCC) for a given year t is Net Creditable C (NCC t ) = ( C t B t ) * ( 1 L t ) * ( 1 U t ) * ( 1 RRt ) where C t is the gross C storage in relevant pools in year t, B t is the baseline, and L t, U t, and RRt are the percentage deductions (if any) for leakage, uncertainty, and reserve set-asides, respectively. NCC t is then converted to net creditable CO 2 e (NCCe t ). Total GHG mitigation under each protocol and scenario is calculated by summing annual estimates of NCCe across 100 years of project implementation. This is recognized as a rough aggregate measure of C effects over time, one that does not explicitly account for the timing of C storage. Timing is however accounted for in the determination of the C price necessary to generate the same net financial benefits as the timber-only, business-as-usual (BAU), non-project alternative. For both the hypothetical project and non-project (BAU) alternative, net project benefits (NB) for a given year t can be calculated: Net Benefits (NB t ) = ((NCCe t * P c ) + (T t * P w )) ((NCCe t * F c ) + F m + (S t * C p )) where NCCe represents total net creditable C generated under each protocol or scenario, P c is the C price per metric ton, F c is a per-metric ton C trading fee, and F m is a flat project registration or 10

11 maintenance fee (if any). Specific fees include those identified in The Delta Institute (2007), Voluntary Carbon Standard (2007a), and Climate Action Reserve (2008). T t is the tonnage of timber produced in year t, P w is the timber price, S t is the size of the stand (in ha) being planted, and C p represents per-hectare planting costs. Hardwood and softwood sawtimber and pulpwood prices are derived from Forest2Market (2008). A cost of $625 ha -1 is used for site preparation and regeneration (Sohngen and Brown 2008; pers. comm., Judd Edeburn, Duke Forest, January 6, 2009). Timber prices and planting costs are assumed to be static throughout the project. Once a stream of annual net benefits is generated, a basic net present value (NPV) is calculated for a BAU timber-only scenario and for the hypothetical project operating under each protocol and assumption scenario: Net Present Value (NB 0,,NB 100 ) = (NB t ) / (1 + r) t A discount rate (r) of 0.05 is assumed for each scenario, and the C price at which the NPV of each protocol and assumption scenario equals the NPV of a BAU, timber-only scenario is determined using a simple solver spreadsheet tool. 100 t=0 3. Results Considerable differences in creditable C storage between the seven protocols are found when applying the Calhoun-derived sequestration data and base case assumptions described in Table 1 (Figure 1). Depending on the protocol applied, the range of total creditable C generated by the project spans nearly an order of magnitude. Across all protocols, cycles of harvest and growth are easily seen, as are the considerable differences in the trajectory and extent of creditable C generation under each protocol. Differences in net creditable C can be attributed to a wide variety of factors. In some approaches (e.g., VCS, RGGI), creditable C accumulation is limited by the C pools included, even before factoring in baseline or other components. In other protocols (e.g., HFF), it is not the included forest pools, but rather an aggressive baseline and large deductions for leakage that are the primary drivers. Holding the choice of C pools and non-baseline accounting components (e.g., leakage, uncertainty, set-asides) constant, the role of project baseline in creditable C generation can be clearly seen (Figure 2). Base-year approaches allow creditable C to be generated the 11

12 Figure 1. Cumulative creditable C generated by the hypothetical 100 hectare project. The line graphs depict net C sequestration for (a) only required pools and (b) all eligible pools under base case assumptions for baseline, reversal, leakage, and uncertainty explored in this analysis. 12

13 earliest and in the largest quantity. Projects using a cohort group performance standard baseline do not begin to generate creditable C until they surpass average regional stocking levels, or approximately 19 years after project inception. The gradual decline in creditable C seen in the single practice performance standard is attributable to the greater amount of wood products being produced in the BAU management scenario, resulting in negative net sequestration being reported in this pool. Figure 2. Total creditable C for the 100 hectare project, as influenced by baseline methodology. C pools are identical under each baseline scenario, and include those described under the 1605(b) methodology (Live Tree, Dead Tree, Belowground, Litter, Soil, and Wood Products). No deductions are made for leakage, set-asides, or uncertainty. The role of assumptions becomes apparent as low and high C assumption scenarios are applied to the hypothetical project (Figure 3). Potential overlap exists between the ranges generated under each protocol, but it is unlikely that the same conditions that generate the lowest possible amount of creditable C in one protocol will generate the highest under another (i.e., simultaneous high deductions for leakage under CAR and low deductions for leakage under VCS). Break-even C prices within each protocol also vary, the extent of variation depending on the assumptions applied (Figure 4). Furthermore, despite an apparent clustering of annualized 13

14 sequestration in Figure 1a, especially from 2,500 to 5,000 t C, such similarities are not borne out when examining average annual C sequestration and the C price required for the project to match the non-project BAU alternative, metrics that potentially factor most heavily into project feasibility. It is also important to note that the apparent clustering in Figure 1 covers a range of approximately 2,500 t C from highest to lowest protocol, a range roughly equal to a doubling of the lowest sequestering approach. The timing of sequestration is another important factor, especially for the break-even price in which later storage is discounted relative to sequestration in the near-term. Figure 3. Range of mean annual per-hectare creditable CO 2 e generated under each protocol for both required pools and all eligible pools. The bar graphs indicate mean annual per-hectare net sequestration under base case assumptions for baseline, reversal, leakage, and uncertainty explored in this analysis; the error bars reflect the mean annual per-hectare net sequestration under low and high C assumption scenarios. 4. Discussion and Conclusion Considerable differences are found in the amount of creditable C generated by a hypothetical forest management offset project operating under different protocols. These differences are compounded when factoring the impact of assumptions on baselines, leakage rates, certainty discounts, and buffer withholding schedules. A great deal of variation stems from the C pools included and the baseline approach employed. Including more C pools generally results in greater potential creditable C. Limiting pools lowers the starting point from 14

15 Figure 4. Range of C prices necessary to match the Net Present Value of the non-project, timber-only alternative for (a) only required pools and (b) all eligible pools. High and low values under each protocol are generated by considering the highest and lowest sequestration estimates, respectively, generated by the range of values for baseline, reversal, leakage, and uncertainty explored in this analysis. 15

16 which a project developer must then make deductions for baseline, leakage, and other discounts. But including more pools does not always equal greater creditable C generation. Under most baseline approaches evaluated here, wood products comprise a substantial portion of total project creditable C. However, fully accounting for the changes in the wood products pool, considering both the amount of C stored by the project and under a BAU scenario, can result in negative sequestration being reported for the pool. This is a primary cause of the diminishing total project storage seen in the case of the single project performance standard in Figure 2. These differences in approach translate directly into differences in project break-even C price (Figure 4). Because forest landowners will likely pursue offset projects only if they provide financial benefits, these results suggest that offset protocol design can influence the role of forest management under a larger cap-and-trade policy framework. This has significant implications for emission mitigation and cost containment objectives, as forest management offsets are expected to be one of the largest, lowest cost, and most rapidly deployable contributors to forest and agricultural GHG mitigation efforts (U.S. Environmental Protection Agency 2005). In addition to the range of break-even C prices found here, the magnitude of break-even C prices also warrant examination. The choice of management regime is one factor in the high break-even C prices calculated here. Comparable optimal rotation studies often look at smaller increments in the rotation age, which are less expensive on the margin. Despite phasing in the transition to 50-year rotations, a doubling of rotation lengths represents an extreme shift in management. Even so, the break-even price estimated here for one of the protocols (1605(b)) falls within the range estimated for a majority of forest management projects in previous national assessments (U.S. Environmental Protection Agency 2005). This suggests that it may not be the choice of management regime that is wholly responsible for the high break-even C prices. It is therefore possible that protocol-specific restrictions or requirements (e.g., leakage, baseline) may lead to lower amounts of C being generated in so-called real world projects than otherwise predicted by aggregate national analyses. Although direct comparison between the present study and previous national analyses are difficult, these findings suggest that forest management offset projects, especially those increasing C storage by extending rotations, may require higher C prices to be financially feasible than previously estimated. A similar finding is echoed in other recent analysis (Sohngen 16

17 and Brown 2008). The wide range in creditable C generation found here, both among and within protocols under different assumption scenarios, also suggests that policymakers must be deliberate in the standardization of offsets methodology. Creating an accounting framework that makes it easier for landowners to participate may come at the expense of system integrity. A system that is robust but exceedingly onerous may discourage landowner participation and reduce the role that forests can play in a comprehensive GHG mitigation strategy. Further research is necessary to better characterize the full suite of factors influencing forest management offset project feasibility and sequestration potential. Immediate next steps in this ongoing research are to expand the current analysis to include other forest systems and management treatments. It is also important to further examine the full suite of transaction costs in offset project implementation, specifically those attributable to measurement, monitoring, and verification. The protocols examined here vary in methodology and administrative requirements, factors that are likely to lead to a variation in the costs of project implementation. Work to better characterize these costs is underway. Acknowledgments This analysis was largely supported by the Climate Change Policy Partnership at Duke University. The authors also wish to thank the USDA Forest Service forest managers at Sumter National Forest for their continued support of the long-term soil and ecosystem research being conducted at the Calhoun Experimental Forest. References Adams DM, Haynes RW (1996) The 1993 timber assessment market model structure, projections, and policy simulations. PNW-GTR-368. U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, Portland Amano M, Sedjo RA (2006) Forest sequestration: performance in selected countries in the Kyoto period and the potential role of sequestration in post-kyoto agreements. Resources for the Future, Washington DC Baldwin VC (1987) Green and dry-weight equations for above-ground components of planted loblolly pine trees in the West Gulf Region. Southern Journal of Applied Forestry 11:

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