ORIGINAL ARTICLE

A virtual “field test” of forest management carbon offsetprotocols: the influence of accounting

Christopher S. Galik & Megan L. Mobley &

Daniel deB. Richter

Received: 24 March 2009 /Accepted: 28 July 2009 /Published online: 18 August 2009# Springer Science + Business Media B.V. 2009

Abstract Of the greenhouse gas (GHG) mitigation options available from U.S. forests andagricultural lands, forest management presents amongst the lowest cost and highest volumeopportunities. A number of carbon (C) accounting schemes or protocols have recentlyemerged to track the mitigation achieved by individual forest management projects. Using50-year C cycling data from the Calhoun Experimental Forest in South Carolina, USA, Cstorage is estimated for a hypothetical forest management C offset project operating underseven of these protocols. After 100 years of project implementation, net C sequestrationamong the seven protocols varies by nearly a full order of magnitude. This variation stemsfrom differences in how individual C pools, baseline, leakage, certainty, and buffers areaddressed under each protocol. This in turn translates to a wide variation in the C pricerequired to match the net present value of the non-project, business-as-usual alternative.Collectively, these findings suggest that protocol-specific restrictions or requirements arelikely to discount the amount of C that can be claimed in “real world” projects, potentiallyleading to higher project costs than estimated in previous aggregate national analyses.

Keywords Carbon offsets . Carbon sequestration . Forest management . Offset markets

1 Introduction

The global forest sector is viewed as a key component in greenhouse gas (GHG) mitigationefforts (e.g., Pacala and Socolow 2004). In the United States, the forest sector comprises a

Mitig Adapt Strateg Glob Change (2009) 14:677–690DOI 10.1007/s11027-009-9190-9

C. S. GalikClimate Change Policy Partnership, Duke University, Box 90658, Durham, NC 27708-0658, USA

M. L. Mobley : D. deB. RichterNicholas School of the Environment and University Program in Ecology, Duke University, Box 90328,Durham, NC 27708-0328, USA

C. S. Galik (*)Duke University, Box 90658, Durham, NC 27712-0658, USAe-mail: csg9@duke.edu

significant carbon (C) sink, with U.S. forests and forest products sequestering over 700million metric tons (t) of carbon dioxide equivalents (CO2e) per year (U.S.Environmental Protection Agency 2008). With a sufficiently strong price signal,afforestation and forest management in the U.S. can sequester an additional 1.2 billiont CO2e per year (U.S. Environmental Protection Agency 2005). Beyond sheer mitigationpotential, the inclusion of forest and other biological C sequestration activities incomprehensive climate policy can provide a pool of low-cost mitigation options andlower the overall costs of meeting emission reductions (Amano and Sedjo 2006). Of theGHG mitigation options available from U.S. forests and agricultural lands, forestmanagement presents amongst the lowest cost and highest volume opportunities (U.S.Environmental Protection Agency 2005).

Numerous recent proposals in the United States Congress contemplate theparticipation of the forest sector in comprehensive climate policy (H.R. 2454, AmericanClean Energy and Security Act of 2009; S.3036, Lieberman-Warner Climate SecurityAct 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, theprimary opportunity for forests to participate under a cap-and-trade program would bein offset markets.

Buyers, sellers, and policy makers must all have confidence in the accounting systemused to track the GHG mitigation achieved by particular projects if forests are to fullyparticipate in offset markets. Unfortunately, forest management offset project accountingremains a difficult undertaking. This is largely due to the dynamic nature of C storage inforest systems and a lack of standardized management and land use practices across usersand landscapes. Owing to both the complexity of the issue and a conspicuous absence of asingle federal standard, a variety of forest management C offset accounting approacheshave emerged in recent years. This has created uncertainty for project developers andinvestors, alike. To allay this uncertainty, standardization of accounting methodology is alikely prerequisite to the full participation of forest management offsets in comprehensiveclimate policy.

An assessment of the lessons learned in early forest offset project implementation is, inturn, likely a necessary first step in the standardization process. The literature suggests thata great deal of variation in cost and net C sequestration exists across projects and projecttypes (Richards and Stokes 2004; Stavins and Richards 2005). Research also suggests thatproject 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 offorest management offset projects. The literature, however, contains few examples of thefinancial and/or environmental implications of forest management offset projects as viewedthrough the lens of the actual accounting schemes that will govern offset projectimplementation (e.g., Pearson et al. 2008).

In light of this critical research gap, work was initiated in early 2008 to provide a betterunderstanding of the real-world differences among the forest management offset projectaccounting protocols in use today. Here, long-term sequestration data from the CalhounExperimental Forest in South Carolina is used to conduct side-by-side virtual trials of sevendistinct forest management offset protocols. In the analysis that follows, particular attentionis paid to the accounting methods used and the implications for net creditable C, or theamount 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 marketdiscussed.

678 Mitig Adapt Strateg Glob Change (2009) 14:677–690

2 Methods1

2.1 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 age25), implemented for a period of 100 years. At project inception, there are two standseach of 0, 5, 10, 15, and 20 years old. To phase in the shift in rotation over time, onestand in each pair is managed on a 25-year rotation until the first harvest, and thenconverted to a 50-year rotation. The other stand in each pair is immediately converted to a50-year rotation.

The C sequestration data on which the hypothetical project is based is derived from Cinventories at the Calhoun Experimental Forest in Union County, South Carolina, USA. Basedon decades of observations and repeated sampling (Urrego 1993; Richter et al. 1994; Richter etal. 1999; Richter and Markewitz 2001), a spreadsheet model was created to simulate repeated25– and 50-year clearcut harvests at the Calhoun Forest, allowing an ex post monitoringperspective on the hypothetical project. In constructing the model, tree biomass was estimatedby a combination of allometric equations depending on age and tree component (Nelson andSwitzer 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).

Implementation of the hypothetical project is evaluated under seven distinct offsetaccounting schemes. This research focuses on those schemes in which distinct protocols ormethodologies were available for forest management projects. Collectively, the selectedaccounting schemes provide a representative sample of the breadth of U.S. voluntary andemerging state and region compliance registries and markets. Protocols or methodologiesspecifically examined here include:

1. U.S. Department of Energy (DOE) 1605(b) Technical Guidelines for VoluntaryReporting 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 WoodProducts Protocols (Chicago Climate Exchange 2007a, b);

4. California Climate Action Reserve (CAR) Forest Project Protocol (Climate ActionReserve 2007);

5. Voluntary Carbon Standard (VCS) Improved Forest Management Protocol (VoluntaryCarbon Standard 2007a, b);

6. a protocol derived from recommended concepts in Duke University’s Harnessing Farmsand Forests in the Low-Carbon Economy (HFF) (Willey and Chameides 2007); and

7. a draft recommendation for active forest management offset projects proposed by theState of Maine under the Regional Greenhouse Gas Initiative (RGGI) (State of Maineet al. 2008).

For each protocol, the C in both required and eligible (but optional) forest C pools istallied, 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

1 An expanded discussion of the methods employed here can be found in Galik et al. (2008).

Mitig Adapt Strateg Glob Change (2009) 14:677–690 679

nature of the project, a number of assumptions were necessary. To capture the full potentialrange of creditable C generated, three scenarios are considered: base-case, high C, and lowC. High and low C scenarios simply make use of those values described above and listed inTable 1 that generate the highest and lowest amounts of net creditable C, respectively. Base-case scenarios represent a “best estimate” of conditions as they would have existed on theground for the hypothetical project.

For all protocols, C accruing above the baseline (after all necessary deductions forbuffer, leakage, certainty and other components), is assumed to be eligible for crediting. Itis also assumed that credits are “bought back” from the market in years of negativesequestration. Baseline and wood product methodologies common to several protocols aredescribed below, followed by protocol-specific calculations or assumptions.

2.1.1 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’sstarting C stock to U.S. Forest Service Forest Inventory and Analysis (FIA) mean per hectare Cstorage for similar forest types in the area (see State of Maine et al. 2008).

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 notconsider that component, only that there are no mechanisms to adjust creditable C on the basis of it. Onlypools contributing significant amounts of C to sequestration totals at the Calhoun site are included; a givenprotocol may include more pools than those evaluated here

Entity Baseline Pools includeda Quantification ofwood products

Reversal Uncertainty Leakage

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) - 0-30%[10%]

-

PerformanceStandard

VCS Single-practice LT, BG*, DT*, L*,S*, WP*

100-Year 5–60%[10%]

- 10–40%[10%]

PerformanceStandard

HFF Cohort Group LT, BG, DT, L, S,WP*

(none specified) - - 33.5–44.5%[43%]

PerformanceStandard

RGGI ModifiedBase-year

LT, BG, DT*, WP* Regional Threshold 0–20%[20%]

- -

a C pools include: LT Live Tree, BG Belowground, DT Dead Tree, L Litter, S Soil, WP Wood Products

*Denotes optional pools

680 Mitig Adapt Strateg Glob Change (2009) 14:677–690

Single-practice performance standard Baseline under a single-practice performancestandard equals the estimated C sequestered under the management scenario that bestapproximates what would have been done in the absence of the project. Here, this isassumed 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 similarmethod using harvest probabilities is described in Murray and Brown (2007). Here, an ageclass distribution for privately-held planted loblolly forests in the South Carolina Piedmont isderived using FIA year-2006 data (U.S. Forest Service 2008), and then multiplied by the Cstock 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, anestimate of total C stocking. No creditable C is generated while a project’s stocking level isbelow the performance standard; all C above the standard is eligible for crediting.

2.1.2 Wood product methodologies

100-year method The 100-Year method implicitly assumes that all C remaining in woodproducts in use or in landfills after 100 years is permanently stored. To estimate this fractionof the harvested wood product stream, conversion factors listed in Smith et al. (2006) areused to derive harvested wood volume, fraction of this volume that is either softwood orhardwood, fraction that is either sawtimber or pulpwood, and fraction of the resulting woodproducts projected to remain in use and in landfills 100 years after harvest. A first step inthis process is to use estimates of Live Tree C at the time of harvest to generate harvestedvolumes for hardwood and softwood pulpwood and sawtimber. Because the data on whichthe project is based is not expressed in terms of timber volume but rather gross Csequestration, the following equation is used (derived from Smith et al. 2006) to solve forharvested volume in units of m3 ha-1 (V):

Live Tree C t ha�1� � ¼ 0:5 * V * FS * FT * SG

where FS is the fraction of the harvested stock that is either hardwood or softwood, FT isthe fraction of the harvested stock that is either sawtimber or pulpwood, SG is the specificgravity 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 andtype. The amount of C contained in harvested hardwood and softwood pulpwood andsawtimber is then multiplied by the fraction that is expected to remain in use or in landfillsfor 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 aregional threshold approach is dependent on the relationship between project harvests andregional removals. Average removals for the project are estimated as:

Project Removals ¼ V * 100ð Þ=50where V represents harvested volume in units of m3 ha-1, a constant of 100 scales theharvest up to the project area, and a constant of 50 converts single rotation harvests into

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annualized removals. After converting from cubic meters to cubic feet, the hypotheticalproject’s harvest rate is found to exceed average removals for loblolly in South Carolina asderived from U.S. Forest Service (2007). The difference between these two removal rates isscaled up to removals per-hectare, per-rotation, and then into fraction of wood productsprojected to remain in use and in landfills 100 years after harvest using the process outlinedunder the 100-year method above. Credit for this amount is taken in the year of harvest.

2.1.3 Protocol-specific notes and assumptions

U.S. DOE 1605(b) For the purposes of this analysis, all pools under the 1605(b) accountingmethodology are classified as “required.” It is perhaps technically more appropriate toclassify all pools as “optional,” but this would result in no creditable C being generatedunder the required pool scenario explored here, thus limiting comparison with otherprotocols.

Georgia Forestry Commission The GFC protocol was not explicitly designed forimplementation in South Carolina, but its evaluation here provides an opportunity fordirect comparison with other major protocols.

CCX sustainably managed forests/long-lived wood products protocols Wood products areconsidered 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 inventoriesto up to 20% for modeled C estimates. A base-case deduction of 20% is assumed here. Thesize 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 buffercredits returned to the project after the 100 year project lifespan.

CAR forest project protocol 2The CAR protocol was not explicitly designed forimplementation in South Carolina, but it is assumed that project meets all relevant CARadditionality and project eligibility requirements. Under current CAR guidelines, optionalpools cannot be certified, and therefore cannot generate “creditable C” as defined by thisanalysis. Consequently, optional pools are excluded here. Quantification of off-site leakageis not required and a methodology is not provided, so leakage is excluded as well. CARuncertainty discounts 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 allrelevant additionality and project eligibility requirements. Discounts for leakage range from10% to 40%; a base-case leakage rate of 10% is assumed as it is expected that the projectwould maintain consistent long-term timber supplies. Buffer set-asides range from 5% to60%; a base-case buffer of 10% is assumed based on a “low risk” project classification.

2 The CAR forest protocol is in the process of being revised as of the drafting of this article. The latest draftof the protocol available to the authors at the time of submission (version 3.0, June 22, 2009) represents asignificant shift from the CAR protocol evaluated herein. Preliminary analysis suggests that if implementedin its current form, an updated CAR forest management protocol all-pools scenario would generate averageannual creditable C values approximately midway between the HFF and current CAR protocol explored herebut with greater potential variability. Significantly less creditable C is generated by the draft version than thecurrent CAR protocol when limiting the analysis to only required pools, with the draft protocol againexhibiting greater variability than the current version.

682 Mitig Adapt Strateg Glob Change (2009) 14:677–690

Credits need not be replaced on a 1-for-1 basis if removed from the buffer in years ofnegative sequestration. Additional credits are “bought back” from the market if negativesequestration exceeds the amount in the buffer. A portion of buffer may be released back tothe 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 varybetween 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, thecohort group performance standard baseline ranges from 152.3 tC ha-1 (FIA SC SurveyUnit 3 – privately owned) to 166.2 tC ha-1 (FIA SC Survey Unit 3 – private and publicownership). No accounting methodology is outlined for wood products, so the pool isexcluded. Leakage is calculated based on an equation derived from Murray et al. 2004

Leakage ¼ 100 * e * CNð Þ= e� E * 1þ Φ½ �ð ÞCR

Price elasticities of supply (e) are assumed to range from 0.193 to 0.321 (Adams andHaynes 1996), and a value of –0.4 is assumed for price elasticity of demand (E) (Willey andChameides 2007). It is assumed that the project comprises a small portion of the timbermarket, so market share (Φ) drops from the equation. C emission intensities are assumed tobe equal both on-site (CR) and off-site (CN), and are likewise dropped. This yields leakagerates of 32.5% to 44.5%. A base-case leakage rate of 43% is estimated using 0.3 as theprice elasticity of supply and –0.4 for demand.

Draft recommendation, active forest management (RGGI) The modeled 25-year rotation isused to approximate pre-project conditions, yielding a total-project starting C stock of 60.2t ha-1 for both required and all pool scenarios. These values are achieved the year prior toproject initiation. Depending on ownership and geographic area selected, FIA mean Cvalues range between 51.6 and 56.7 t ha-1 for required pools and between 62.7 and 68.6t ha-1 for all eligible pools. The draft RGGI protocol does not require a calculation ofleakage, but does require that the forest on which the project exists either be certified or thatharvest rates not be exceptionally lower than the average removal rates for forests in thatarea. As described in Section 2.1.2., estimates of timber production from the project exceedaverage removals for loblolly in South Carolina. The draft protocol suggests that a buffermay be required if insurance is not secured, but an exact amount is not specified; a 20%buffer is assumed here as a base case.

2.2 Quantification of net creditable carbon

For each protocol and assumption scenario, net creditable C (NCC) for a given year t iscalculated as:

Net Creditable C NCCtð Þ ¼ Ct � Btð Þ * 1� Ltð Þ * 1� Utð Þ * 1� Rtð Þwhere Ct is the gross C storage in relevant pools in year t, Bt is the baseline, and Lt , Ut, andRt are the percentage deductions (if any) for leakage, uncertainty, and reserve set-asides,respectively. NCCt is then converted to net creditable CO2e (NCCet). Total GHG mitigationunder each protocol and scenario is calculated by summing annual estimates of NCCe

Mitig Adapt Strateg Glob Change (2009) 14:677–690 683

across 100 years of project implementation. This is recognized as a rough aggregatemeasure of C effects over time, one that does not explicitly account for the timing of Cstorage.

Timing is however accounted for in the determination of the C price necessary togenerate 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, netproject benefits (NB) for a given year t can be calculated:

Net Benefits NBtð Þ ¼ NCCet * Pcð Þ þ Tt * Pwð Þð Þ � NCCet * Fcð Þ þ Fm þ St * Cp

� �� �

where NCCe represents total net creditable C generated under each protocol or scenario, Pc

is the C price per metric ton, Fc is a per-metric ton C trading fee, and Fm is a flat projectregistration or maintenance fee (if any). Specific fees include those identified in The DeltaInstitute (2007), Voluntary Carbon Standard (2007a), and Climate Action Reserve (2008).Tt is the tonnage of timber produced in year t, Pw is the timber price, St is the size of thestand (in ha) being planted, and Cp represents per-hectare planting costs. Hardwood andsoftwood 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 areassumed to be static throughout the project. Once a stream of annual net benefits isgenerated, a basic net present value (NPV) is calculated for a BAU timber-only scenarioand for the hypothetical project operating under each protocol and assumption scenario:

Net Present Value NB0; . . . ;NB100ð Þ ¼X100

t¼0

NBtð Þ� 1þ rð Þt

A discount rate (r) of 0.05 is assumed for each scenario, and the C price at which theNPV of each protocol and assumption scenario equals the NPV of a BAU, timber-onlyscenario is determined using a simple “solver” spreadsheet tool.

3 Results

Considerable differences in creditable C storage between the seven protocols are foundwhen applying the Calhoun-derived sequestration data and base case assumptions describedin Table 1 (Fig. 1). Depending on the protocol applied, the range of total creditable Cgenerated by the project spans nearly an order of magnitude. Across all protocols, cycles ofharvest and growth are easily seen, as are the considerable differences in the trajectory andextent of creditable C generation under each protocol. Differences in net creditable C can beattributed to a wide variety of factors. In some approaches (e.g., VCS, RGGI), creditable Caccumulation is limited by the C pools included, even before factoring in baseline or othercomponents. In other protocols (e.g., HFF), it is not the included forest pools, but rather anaggressive 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 canbe clearly seen (Fig. 2). Base-year approaches allow creditable C to be generated theearliest and in the largest quantity. Projects using a cohort group performance standardbaseline do not begin to generate creditable C until they surpass average regional stockinglevels, or approximately 19 years after project inception. The gradual decline in creditableC seen in the single practice performance standard is attributable to the greater amount of

684 Mitig Adapt Strateg Glob Change (2009) 14:677–690

Fig. 1 Cumulative creditable C generated by the hypothetical 100 hectare project. The line graphs depict netC 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

Mitig Adapt Strateg Glob Change (2009) 14:677–690 685

wood products being produced in the BAU management scenario, resulting in negative netsequestration being reported in this pool.

The role of assumptions becomes apparent as low and high C assumption scenarios areapplied to the hypothetical project (Fig. 3). Potential overlap exists between the rangesgenerated under each protocol, but it is unlikely that the same conditions that generate thelowest possible amount of creditable C in one protocol will generate the highest underanother (i.e., simultaneous high deductions for leakage under CAR and low deductions forleakage under VCS). Break-even C prices within each protocol also vary, the extent ofvariation depending on the assumptions applied (Fig. 4). Furthermore, despite an apparentclustering of annualized sequestration in Fig. 1a, especially from 2,500 to 5,000 t C, suchsimilarities are not borne out when examining average annual C sequestration and the Cprice required for the project to match the non-project BAU alternative, metrics thatpotentially factor most heavily into project feasibility. It is also important to note that theapparent clustering in Fig. 1 covers a range of approximately 2,500 t C from highest tolowest 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 pricein which later storage is discounted relative to sequestration in the near-term.

4 Discussion and conclusion

Considerable differences are found in the amount of creditable C generated by ahypothetical forest management offset project operating under different protocols. These

Fig. 2 Total creditable C for the 100 hectare project, as influenced by baseline methodology. C pools areidentical under each baseline scenario, and include those described under the 1605(b) methodology (LiveTree, Dead Tree, Belowground, Litter, Soil, and Wood Products). No deductions are made for leakage,set-asides, or uncertainty

686 Mitig Adapt Strateg Glob Change (2009) 14:677–690

differences are compounded when factoring the impact of assumptions on baselines,leakage rates, certainty discounts, and buffer withholding schedules. A great deal ofvariation stems from the C pools included and the baseline approach employed. Includingmore C pools generally results in greater potential creditable C. Limiting pools lowers thestarting point from which a project developer must then make deductions for baseline,leakage, and other discounts. But including more pools does not always equal greatercreditable C generation. Under most baseline approaches evaluated here, wood productscomprise a substantial portion of total project creditable C. However, fully accounting forthe changes in the wood products pool, considering both the amount of C stored by theproject and under a BAU scenario, can result in negative sequestration being reported forthe pool. This is a primary cause of the diminishing total project storage seen in the case ofthe single project performance standard in Fig. 2.

These differences in approach translate directly into differences in project break-even Cprice (Fig. 4). Because forest landowners will likely pursue offset projects only if theyprovide financial benefits, these results suggest that offset protocol design can influence therole of forest management under a larger cap-and-trade policy framework. This hassignificant implications for emission mitigation and cost containment objectives, as forestmanagement offsets are expected to be one of the largest, lowest cost, and most rapidlydeployable contributors to forest and agricultural GHG mitigation efforts (U.S. Environ-mental Protection Agency 2005).

In addition to the range of break-even C prices found here, the magnitude of break-evenC prices also warrant examination. The choice of management regime is one factor in thehigh break-even C prices calculated here. Comparable optimal rotation studies often look atsmaller increments in the rotation age, which are less expensive on the margin. Despitephasing in the transition to 50-year rotations, a doubling of rotation lengths represents anextreme shift in management. Even so, the break-even price estimated here for one of theprotocols (1605(b)) falls within the range estimated for a majority of forest managementprojects in previous national assessments (U.S. Environmental Protection Agency 2005).This suggests that it may not be the choice of management regime that is whollyresponsible for the high break-even C prices. It is therefore possible that protocol-specificrestrictions or requirements (e.g., leakage, baseline) may lead to lower amounts of C beinggenerated in so-called “real world” projects than otherwise predicted by aggregate nationalanalyses.

Fig. 3 Range of mean annualper-hectare creditable CO2egenerated under each protocolfor both required pools and alleligible pools. The bar graphsindicate mean annual per-hectarenet sequestration under base caseassumptions for baseline,reversal, leakage, and uncertaintyexplored in this analysis; theerror bars reflect the meanannual per-hectare netsequestration under low andhigh C assumption scenarios

Mitig Adapt Strateg Glob Change (2009) 14:677–690 687

Although direct comparison between the present study and previous national analysesare difficult, these findings suggest that forest management offset projects, especially thoseincreasing C storage by extending rotations, may require higher C prices to be financiallyfeasible than previously estimated. A similar finding is echoed in other recent analysis(Sohngen and Brown 2008). The wide range in creditable C generation found here, both

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

688 Mitig Adapt Strateg Glob Change (2009) 14:677–690

among and within protocols under different assumption scenarios, also suggests thatpolicymakers must be deliberate in the standardization of offsets methodology. Creating anaccounting framework that makes it easier for landowners to participate may come at theexpense of system integrity. A system that is robust but exceedingly onerous maydiscourage landowner participation and reduce the role that forests can play in acomprehensive GHG mitigation strategy.

Further research is necessary to better characterize the full suite of factors influencingforest management offset project feasibility and sequestration potential. Immediate nextsteps in this ongoing research are to expand the current analysis to include other forestsystems and management treatments. It is also important to further examine the full suite oftransaction costs in offset project implementation, specifically those attributable tomeasurement, monitoring, and verification. The protocols examined here vary inmethodology and administrative requirements, factors that are likely to lead to a variationin 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 DukeUniversity. The authors also wish to thank the USDA Forest Service forest managers at Sumter NationalForest for their continued support of the long-term soil and ecosystem research being conducted at theCalhoun Experimental Forest.

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