j of Supplement

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This Issue:

Forest Carbon Stocks and Flows

Climate–Forest Interactions

Biomass Use and Feedstock Issues

Wood–Fossil Fuel SubstitutionEffects

Forest Carbon Policies

ntegrating Forests into a RationalPolicy Framework

Managing Forests because Carbon Matters:Integrating Energy, Products, and Land Management Policy

A Society of American Foresters Task Force Report

SUPPLEMENT TO

Journal of

FORESTRYOctober/November 2011 Volume 109, Number 7S

www.jofonline.org

Society of merican Foresters



COMMENTARY

S5 Publisher’s Note M.T. Goergen Jr.

SAF TASK FORCE REPORT

Managing Forests because Carbon Matters:Integrating Energy, Products, and Land Management PolicyR.W. Malmsheimer, J.L. Bowyer, J.S. Fried, E. Gee, R.L. Izlar, R.A. Miner,

I.A. Munn, E. Oneil, and W.C. Stewart

S7 Abstract

S8 Preface

S9 Executive Summary

section 1

S13 Introduction

section 2

S14 Forest Carbon Stocks and Flows

section 3

S21 Climate–Forest Interactions

section 4

S24 Biomass Use and Feedstock Issues

section 5

S27 Wood–Fossil Fuel Substitution Effects

section 6

S35 Forest Carbon Policies

Journal of

FORESTRYOctober/November 2011 (supplement) Volume 109, Number 7S

ditorW. Keith Moser, CF, [email protected]

Managing EditorMatthew Walls, [email protected]

Associate Editorstanley T. Asah, recreation • Keith A. Blatner, education & ommunication • Don Bragg, forest ecology • Stephen Bratk-vich, utilization & engineering • Russell Briggs, CF, soils &

hydrology • Dean Coble, measurement • Dean Current, international forestry • Robert Deal, silviculture • John Groninger,ilviculture • Sean Healey, geospatial technologies • Shibuose, forest ecology • Michael Kilgore, economics • Mee-Sook

Kim, entomology & pathology • Jeffrey Kline, economics •Karen Kuers, silviculture • David Kulhavy, entomology & pathology • James G. Lewis, history • Valerie Luzadis, social ciences • Michael G. Messina, silviculture • Cassandra Mose-ey, policy • Michael J. Mortimer, policy • David Nowak, urban & community forestry • Jay O’Laughlin, policy • Brian Oswald,fire • John G. Peden, recreation • Barry Rosen, international forestry • Kevin Russell, wildlife management • Terry Sharik,education & communication • John Shaw, silviculture • Susantewart, social sciences • Thomas A. Waldrop, fire • Pattephens Williams, human dimensions • Michael Wing,

geospatial technologies

Book Review Editor

ames E. Coufal, [email protected] Managerinda Edelman, [email protected]

Production Editorynthia Owens, [email protected]

PublisherMichael T. Goergen Jr., [email protected]

Director, Advertisingcott Oser, [email protected]

ditorial Offices and Advertising Sales5400 Grosvenor Lane, Bethesda, MD 20814-2198301) 897-8720 • fax (301) 897-3690 • www.safnet.org

Correspondence: Address all letters to the editor to Jour- nal of Forestry Editor or e-mail [email protected]. Ad-

ress correspondence relating to manuscripts to the Man-ging Editor. Address all advertising queries to theAdvertising Manager.

Permission to reprint: Individuals, and nonprofit librar-es acting for them, may make fair use of the material in thisournal, for example, copying an article or portion of anrticle for use in teaching or research. Individuals may alsouote from the publication if the customary acknowledge-

ment of the source accompanies the quotation. To requestermission to make multiple or systematic reproductions orepublish material (including figures and article excerpts)ontact the Copyright Clearance Center, Customer Service

Department, 222 Rosewood Dr., Danvers, MA 01923; (978)750-8400; fax (978) 750-4470; www.copyright.com. A feeor commercial use will be determined depending on use.

Subscriptions: Subscription options and prices are avail-ble at www.jofonline.org. Subscription price to members ofhe Society of American Foresters is included in annual dues.

Single Issues: $12 (individuals), $24 (institutions). Con-act [email protected] to determine availability.

he Journal of Forestry (ISSN 0022-1201) (IPM # 115308) is published in January/February, March, April/

May, June, July/August, September, October/November,nd December by the Society of American Foresters, 5400

Grosvenor Lane, Bethesda, MD 20814-2198. ©2011 (sup-lement) by the Society of American Foresters. Periodicalsostage paid at Bethesda, MD, and at additional mailingffices. Printed in the USA.

POSTMASTER: Send address changes to Journal of Forestry, 5400GrosvenorLane,Bethesda,MD 20814-2198;[email protected].

Journal of

FORESTRYJoF



conclusion

S40 Integrating Forests into a Rational Policy Framework

S41 Literature Cited

S49 About the Task Force

S51 Subject Index

DEPARTMENTS

S52 Journal of Forestry Quiz

On the cover: Composite image design by US Forest Service, Pacific Northwest Research Station. Photo

credits: “Carbon Smart”: top, Tom J. Iraci; middle, m.o.daby design LLC; bottom, Stephen M. Jolley.

“Not So Much”: top, Daniel G. Brown; middle, Tom J. Iraci; bottom, unknown.

Society of American Foresters

residentoger A. Dziengeleski, CF, Gansevoort, NY, [email protected]

Vice-President. William RockwellJr., CF/FCA, St.Johns,MI, [email protected]

mmediate Past-President

Michael B. Lester, CF, Mechanicsburg, PA, [email protected]

xecutive Vice-President and Chief Executive OfficerMichael T. Goergen Jr., Bethesda, MD, [email protected]

ouncilobert L. Alverts, CF, Tigard, OR •Michael J. DeLasaux, Quincy, CAMark P. Elliott, Daphne, AL • George F. Frame, CF, Bristol, NH •

rnest A. Houghton, Gladstone, MI • Kenneth W. Jolly, Annapolis,MD • Charles W. Lorenz, CF, Turnwater, WA • Ian A. Munn, CF,Mississippi State, MS • G. Lynn Sprague, Garden City, ID • Thomas

Straka, CF/FCA, Pendleton, SC • William David Walters, CF,Murfreesboro, TN

orest Science and Technology Boardurt W. Gottschalk, CF, chair • Andrew Sanchez Meador, forest esources •William F. Elmendorf,nonindustrial forestry •Matthew

McBroom, forest ecology & biology • David Shaw, forest manage-

ment & utilization •

Sayeed Mehmood, decision sciences •

Phillipmartt, social & related sciences • Paul F. Doruska, CF, northern egional representative • David B. South, southern regional repre- entative • Guy Pinjuv, western regional representative

House of Society Delegates. Lynn Burkett, chair • Andrew J. Hayes, CF, vice-chair

National Office Department DirectorsMichael T. Goergen Jr., executive vice-president & chief executive fficer • Jorge Esguerra, senior director , finance & administration Louise Murgia, CF,senior director,field services •Matthew Walls,

enior director, publications • Christopher Whited, senior director,marketing& membership • ScottOser,director, advertising • Carol. Redelsheimer, CF, director, science & education

SAF Mission

The Society of American Foresters (SAF) is the nationalscientific and educational organization representing theforestry profession in the United States. Founded in 1900by Gifford Pinchot, it is the largest professional society forforesters in the world. The mission of the Society of Amer-icanForesters is to advance thescience,education, technol-ogy,andpracticeofforestry;toenhancethecompetencyofits members; to establish professional excellence; and, touse the knowledge, skills, and conservation ethic of theprofessionto ensure the continuedhealthand useof forestecosystemsand thepresentand future availability offorestresourcesto benefit society.SAF is a nonprofitorganizationmeeting the requirements of 501 (c) (3). SAF membersinclude natural resource professionals in public and privatesettings, researchers, CEOs, administrators, educators, andstudents.

SAF Core Values1. Forests are a fundamental source of global health and

human welfare,2. Forests mustbe sustainedthroughsimultaneouslymeet-

ing environmental, economic, and community aspira-tions and needs,

3. Forestersarededicatedto soundforestmanagementandconservation, and

4. Foresters serve landowners and society by providingsound knowledge and professional management skills.

Journal of

FORESTRY JoFEditorial Policy The Journal of Forestry welcomes scientific and editorial manuscripts that advance the profession of forestry by presenting s ignificant developments andideas of general interest to natural resource and forestry professionals. Articles published in the Journal present, in a readable style, new andstate-of-the-art knowledge, research, practices, ideas, and policies. Mini-reviews on topics of special interests are also published at the discretion of theeditorial board. Manuscripts must not have been published previously and must not be under consideration for publication elsewhere. Acceptance forpublication is based on both editorial criteria and peer review. Manuscripts are evaluated for methodology, technical accuracy, breadth of appeal, clarity,contribution, and merit. The Journal reserves the right to publish countering or supplemental articles to promote discussion.

Submission GuidelinesLetters to the Editor—Letters should directly address ideas or facts presented in the Journal. Priority is given to letters no longer than 250 words that referto material published within the past six months. Letters may be faxed to (301) 897-3690, attention Editor, e-mailed to [email protected], or mailedto Editor, Journal of Forestry , 5400 Grosvenor Lane, Bethesda, MD 20814-2198.

Exploring the Roots— These short introductions revisit seminal articles previously published by SAF and discuss topics of historical import to the field offorestry, as well as explore the historical basis for issues currently affecting forestry. Maximum length is 1,000 words. Proposals for Exploring the Rootscolumns may be e-mailed to [email protected], faxed to (301) 897-3690, attention Editor, or mailed to Editor, Journal of Forestry , 5400 GrosvenorLane, Bethesda, MD 20814-2198.

Perspectives— These short opinion pieces are not formally reviewed but are evaluated for content and style by the editors and/or editorial board.Maximum length is 1,000 words. The contributor of a “Perspective” must be a member of the Society of American Foresters. Submit the manuscript,complete contact information, and a head-and-shoulders photograph online at www.rapidreview.com/SAF/author.html.

Full-Length Articles—Maximum length is 4,500 words, plus a 150-word abstract. Footnotes should be incorporated into the text wherever possible or bepresented as endnotes. Full guidelines can be found online at www.jofonline.org. Submit your manuscript online at www.rapidreview.com/SAF/ author.html.Becausethereviewprocessisdouble-blind,pleaseensurethatauthorsarenotidentifiedanywhereinthemanuscript(includingrunningheadsand feet).

Review Articles—Maximum length is 6,000 words, plus a 150-word abstract. Footnotes should be incorporated into the text wherever possible or bepresented as endnotes. There is no limit to the number of literat ure citations in a review article. Full guidelines can be found online at www.jofonline.org.Submit your manuscript online at www.rapidreview.com/SAF/author.html. Because the review process is double-blind, please ensure that authors arenot identified anywhere in the manuscript (including running heads and feet).



Managing Forests because Carbon Matters:Integrating Energy, Products, and LandManagement Policy

Robert W. Malmsheimer, James L. Bowyer, Jeremy S. Fried, Edmund Gee, Robert L. Izlar,Reid A. Miner, Ian A. Munn, Elaine Oneil, and William C. Stewart

The United States needs many different types of forests: some managed for wood products plus other benefits, and some managed for nonconsumptiveuses and benefits. The objective of reducing global greenhouse gases (GHG) requires increasing carbon storage in pools other than the atmosphere. Growing

more forests and keeping forests as forests are only part of the solution, because focusing solely on the sequestration benefits of the forests misses the important(and substantial) carbon storage and substitution GHG benefits of harvested forest products, as well as other benefits of active forest management.

Forests and global climate are closely linked in terms of carbon storage and releases, water fluxes from the soil and into the atmosphere, and solar energycapture. Understanding how carbon dynamics are affected by stand age, density, and management and will evolve with climate change is fundamental toexploiting the capacity for sustainably managed forests to remove carbon dioxide from the atmosphere. For example, even though temperate forests continueto be carbon sinks, in western North America forest fires and tree mortality from insects are converting some forests into net carbon sources.

Expanding forest biomass use for biofuels and energy generation will compete with traditional forest products, but it may also produce benefits throughcompetition and market efficiency. Short-rotation woody crops, as well as landowners’ preferences—based on investment-return expectations and environmentalconsiderations, both of which will be affected by energy and environmental policies—have the potential to increase biomass supply.

Unlike metals, concrete, and plastic, forest products store atmospheric carbon and have low embodied energy (the amount of energy it takes to makeproducts), so there is a substitution effect when wood is used in place of other building materials. Wood used for energy production also provides substitutionbenefits by reducing the flow of fossil fuel–based carbon emissions to the atmosphere.

The value of carbon credits generated by forest carbon offset projects differs dramatically, depending on the sets of carbon pools allowed by the protocoland baseline employed. The costs associated with establishing and maintaining offset projects depend largely on the protocols’ specifics. Measurement challengesand relatively high transaction costs needed for forest carbon offsets warrant consideration of other policies that promote climate benefits from forests and forestproducts but do not require project-specific accounting.

Policies can foster changes in forest management and product manufacture that reduce carbon emissions over time while maintaining forests for environmental andsocietal benefits. US policymakers should take to heart the finding of the Intergovernmental Panel on Climate Change in its Fourth Assessment Report when it concludedthat “In the long term, a sustainable forest management strategy aimed at maintaining or increasing forest carbon stocks, while producing an annual sustained yield oftimber, fibre, or energy from the forest, will generate the largest sustained mitigation benefit.” A rational energy and environmental policy framework must be basedon the premise that atmospheric greenhouse gas levels are increasing primarily because of the addition of geologic fossil fuel–based carbon into the carbon cycle.Forest carbon policy that builds on the scientific information summarized in this article can be a significant and important part of a comprehensive energy policythat provides for energy independence and carbon benefits while simultaneously providing clean water, wildlife habitat, recreation, and other uses and values.

Keywords: forest management, forest policy, forest carbon dynamics, carbon accounting, carbon offsets, life cycle assessment, building products substitution,bioenergy

Robert W. Malmsheimer is task force chair, and professor of Forest Policy and Law, SUNY College of Environmental Science and Forestry, Syracuse, NY. James L.Bowyer is professor emeritus, Department of Bioproducts and Biosystems Engineering, University of Minnesota, Minneapolis, MN, president of Bowyer & Associates,Inc., Minneapolis, MN, and director of the Responsible Materials Program in Minneapolis-based Dovetail Partners, Inc., Minneapolis, MN. Jeremy S. Fried is research forester, Resource Monitoring and Assessment Program, US Forest Service, Pacific Northwest Research Station, Portland, OR. Edmund Gee is team leader,US Forest Service National Woody Biomass Utilization Team and coordinator, National Partnership, Washington, DC. Robert L. Izlar is director, University of Georgia Center for Forest Business, Athens, GA. Reid A. Miner is vice president for Sustainable Manufacturing, National Council for Air and Stream Improvement,Research Triangle Park, NC. Ian A. Munn is professor of Forestry Economics and Management, Mississippi State University, Mississippi State, MS. Elaine Oneil is research scientist, University of Washington, and executive director, Consortium for Research on Renewable Industrial Materials, Seattle, WA. William C. Stewart is forestry specialist, Environmental Science, Policy, and Management Department, University of California–Berkeley, Berkeley, CA.

Copyright © 2011 by the Society of American Foresters.

Journal of Forestry • October/November 2011 (supplement) S7

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S T R

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Preface

Forest Management Solutions for Mitigating Climate Change inthe United States (Malmsheimer et al. 2008), by the ClimateChange and Carbon Sequestration Task Force of the Society

of American Foresters (SAF), evaluated the implications of globalclimate change for forests and addressed the role of forestry andforests in mitigating climate change. Since that task force issued itsreport, the science and policies involving forests’ roles in climatechange policies have evolved rapidly. Moreover, questions havearisen regarding how changes in the amount of forest biomass usedfor energy and the trading of forest carbon for pollution credits(offsets), motivated in part by climate change concerns, will affectglobal climate benefits related to forests, forest ecosystems, and tra-ditional forest products industries.

In May 2010, SAF created a new task force to address thoseissues and analyze United States’ forests, climate change, and energy policies. This article summarizes and examines our current under-standing of forest carbon stocks and flows; climate–forest interac-tions; biomass use and feedstock issues; wood–fossil fuel substitu-tion effects; and forest carbon policies. Our analysis focuses on USrather than international forests and forest policies, although we doexamine pertinent international developments.

This article and the task force’s other products are the result of hundreds of hours by dedicated SAF volunteers. Many individualsassisted with the preparation of this article. We would especially liketo thank Kelsey Delaney (SAF) for her administrative assistance and

support of the task force, Sally Atwater (Editorial Arts) for editingthe article, Ken Skog (US Forest Service) for his assistance with dataclarification in Section 5, Brad Smith (USFS Program Manager,Forest Inventory Analysis) for providing Figure 1 in Section 4, andDavid Cleaves, Elizabeth Reinhardt, and David Wear (US ForestService) for their assistance coordinating the review of this article by agency experts.

Three individuals initially drafted small sections of this article.Dr. Jeffery Hatten (Mississippi StateUniversity) contributed the soilcarbon dynamics in Section 2, Dr. Demetrios Gatziolis (USFSPNW Research Station) assisted on section 6’s assessment of carbonvia remote sensing, and Dr. Marcia Patton-Mallory (USFS PNW Research Station) contributed to Section 6’s discussion of the stra-

tegic balance in managing carbon risk. In addition, this article wasreviewed, in whole or in part, by the reviewers listed here and by otherswho wished to remainanonymous. To all of these individuals,the authors express their sincere thanks. Their efforts significantly increased the article’s accuracy and scope.

We have arranged this article topically. We believe that thisorganization will be useful to most readers. However, one conse-quence of this arrangement is that we discuss topics at variousspatial and temporal scales in each section. We have attempted toalert readers to these scale changes throughout the article.

Reviewers

Dennis BaldocchiUniversity of Californiaat Berkeley

Brooks MendellForisk Consulting LLC

Marilyn BufordUS Forest Service

Jay O’LaughlinUniversity of Idaho

Laura DrauckerWorld Resources Institute

Marcia Patton-Mallory US Forest Service

Chris Farley US Forest Service

John Perez-GarciaUniversity of Washington

Christopher Galik Duke University Naomi Pena Joanneum Research

Robert Fledderman MeadWestvacoCorporation

Gary RynearsonGreen Diamond Resource Company

Andrew Gray US Forest Service

Roger SedjoResources for the Future

Dale GreeneUniversity of Georgia

Roger Sherman MeadWestvaco Corporation

Thomas HarrisUniversity of Georgia

Jacek Siry University of Georgia

Randall KolkaUS Forest Service Kenneth SkogUS Forest Service

Alan LucierNational Council for Air and Stream Improvement

Timothy Volk SUNY Environmental Science and Forestry

Margaret MannNational Renewable Energy Laboratory

Shira YoffeUS Forest Service International Programs

Cite this article as:

Malmsheimer, R.W., J.L. Bowyer, J.S. Fried, E. Gee, R.L.

Izlar, R.A. Miner, I.A. Munn, E. Oneil, and W.C. Stewart.

2011. Managing Forests because Carbon Matters: Integrat-

ing Energy, Products, and Land Management Policy. Jour-

nal of Forestry 109(7S):S7–S50.

S8 Journal of Forestry • October/November 2011 (supplement)



Executive Summary

The United States needs many differ-ent types of forests: some managedfor wood products plus other bene-

fits and some managed for nonconsumptiveuses and benefits. Management decisionsmust account for local conditions; landown-ers’ objectives; and a broad set of environ-mental, economic, and societal values. Thisarticle considers how various forest and

wood use strategies can reduce accumulationof greenhouse gases (GHG) in the atmo-sphere.

The global carbon system stores carbonin various pools (stocks). Oceans and bothforested and nonforested lands emit carbonto and absorb carbon from the atmospherein a two-way flow (flux). In contrast, carbonremoved from fossil fuel reserves acts as aone-way flow because regardless of whetheremissions from fossil fuel combustion areultimately taken up by land, ocean, or for-ests, they are not returned to fossil fuel re-serves on anything less than a geologic time-scale. Although there are many uncertaintiesin measuring carbon stocks and flows glob-ally, the objective of reducing global GHGssuggests the importance of increasing car-bon storage in pools other than the atmo-sphere. Growing more forests and keepingforests as forests are only part of the solu-tion. Focusing solely on forests’ sequestra-tion benefits misses the important (andsubstantial) carbon storage and substitu-tion GHG benefits of harvested forest prod-ucts, as well as other benefits of active forestmanagement.

An assessment of the consequences of managing forests as part of a carbon mitiga-tion strategy needs to consider all those ele-ments as an integrated whole across spatialand temporal scales.Policies that ignorehow forests fit into the broader economic, envi-ronmental, and social framework can fall farshort of the possible reductions in carbonemissions and lead to counterproductivemitigation strategies that are environmen-tally and economically unsustainable. Effec-tive solutions require a wider perspectivethat consider among many other things, the

role of forests as a source of products forsociety and the effects of those products onGHG concentrations.

US environmental and energy policiesneed to be linked or at least be based onmutual recognition and should be based onfour basic premises grounded in the sciencesummarized in this article:

1. Sustainably managed forests can providecarbon storage and substitution benefits

while delivering a range of environmen-tal and social benefits, such as timber andbiomass resources, clean water, wildlifehabitat, and recreation.

2. Energy produced from forest biomass re-turns to the atmosphere carbon thatplants absorbed in the relatively recentpast; it essentially results in no net releaseof carbon as long as overall forest inven-tories are stable or increasing (as is thecase with US forests).

3. Forest products used in place of energy-intensive materials such as metals, con-

crete and plastics (a) reduce carbon emis-sions (because forest products require lessfossil fuel-based energy to produce), (b)store carbon (for a length of time basedon products’ use and disposal), and (c)provide biomass residuals (i.e., waste

wood) that can be substituted for fossilfuels to produce energy.

4. Fossil fuel–produced energy releases car-bon into the atmosphere that has residedin the Earth for millions of years; forestbiomass–based energy uses far less of the

carbon stored in the Earth thereby reduc-ing the flow of fossil fuel–based carbonemissions to the atmosphere.

US policies can encourage managementof forests for all the carbon and energy ben-efits of forests and forest products while sus-taining ecosystem health and traditional for-est biomass uses. The scientific informationin this article can be used as the basis fordeveloping sound forest carbon policies.

Forest Carbon Stocks and FlowsTracking the allocation of forest carbon

across live and dead trees, understory shruband herbaceous vegetation, the forest floor,forest litter, soils, harvested wood products,and energy wood is far more difficult thanconducting traditional inventories of com-mercially valuable wood volume. Under-standing the dynamics of these allocations;how they are affected by stand age, density,and management; and how they will evolve

with climate change is fundamental to ex-ploiting the capacity for sustainably man-aged forests to remove carbon dioxide(CO2) from the atmosphere.

Carbon flux is usually estimated aschange in carbon stocks. Several compli-cations—deciding what comparisons or“pools” to include and what models, equa-tions, and coefficients to rely on, accountingfor uncertainty and error, and even defini-tions of “tree” and “forest”—conspire tomake consistent, universally accepted esti-mates grounded in objective science very

scarce. On average, carbon in the boles of live trees, the best-sampled and most easily modeled component of forest carbon inven-tories, represents less than half the carbon inthe forest.

Unmanaged forests do not provide ad-ditional climate benefits indefinitely. Theage when annual forest carbon storage incre-ments begin to decline varies but generally occurs in the first 100–150 years as treemortality losses increase. In most of the

American West, fire and insects pose a very immediate threat of catastrophic loss of livetree carbon, turning affected forests into car-bon emitters. In the rest of the UnitedStates, insect, disease, and storm-relatedconversion of live carbon to dead carboneventually slows, stops, and sometimes re-verses net sequestration.

Old forests have some of the largest car-bon densities but typically low or near-zerorates of additional carbon sequestration andhigher probabilities of loss. For example,85% of the woody biomass–based carbon




storage in ponderosa pine forests in centralOregon is in stands older than 100 years

where annual accumulation is slowing andthe risks of carbon loss due to wildfire arehigh and often increasing. Regeneration har-vest in high-volume old-growth could re-lease carbon that would not be used forproducts or energy. However, these stands

are found almost exclusively on public landsand are rarely harvested or even actively managed in the United States today.

Soil carbon can have residence times aslong as thousands of years, as long as it isdeep in the soil profile or associated withminerals. The effect of harvest and replant-ing on soil carbon is difficult to generalize, asmuch depends on the initial soil depth, thedepth to which soil is sampled, and posthar-vest site preparation. The measured effectstend to be slight in the short term, with car-bon decreases concentrated in the forest

floor and near the soil surface and carbonincreases occurring in the deep mineral soillayers. Whole-tree harvesting for biomassproduction has little long-term effect on soilcarbon stocks if surface soil layers containingorganic material (O horizon) are left on site,nutrients are managed, and the site is al-lowed to regenerate. Converting agriculturaland degraded lands to forests or short-rota-tion woody crops increases abovegroundcarbon stocks as well as soil carbon stocks.

Fuel treatments designed to reduce firehazard and other stand manipulation that

promotes resilience by reducing potentiallosses due to insects, diseases, or storms can-not eliminate risk but can reduce the scale of tree mortality and associated carbon emis-sions. The carbon losses from disturbancesaccrue over time as the live biomass is con-verted to dead biomass that slowly releasescarbon dioxide via enhanced microbial res-piration.

Including the boreal forests of Alaskaand the tropical island forests, 53% of thearea of US forests is timberland (i.e., foreststhat are available for periodic harvesting) of

naturally regenerated origin, much of whichis managed; 7% is forest plantations; and40% is reserved or low-productivity forest.The carbon dynamics of each forest type arestrongly influenced by the long-term sus-tainability of the forests, the types of woodproducts that are harvested, and the life-cycle carbon consequences of the variousproducts.

After accounting for the wood used forenergy in sawmills and paper mills, the an-nual growth of forest carbon is split among

growth in live-tree inventories (28%), har-vested wood products (23%), energy (18%),and natural mortality and logging residues(31%). These enduses each have unique car-bon storage characteristics and trajectories.The distribution of total forest growth variesconsiderably among regions, with the Southproducing more products, the North and

Pacific Coast harvesting a smaller fraction of new growth while still producing consider-able products, and the Rocky Mountainregion having the highest fraction of totalgrowth converting into deadwood.

Since 1985, annual US wood produc-tion has stayed roughly constant, at 420 mil-lion m3, while consumption increased to550 million m3 by 2005. Counting the in-creased forest carbon sequestration in theUnited States as new global carbon seques-tration overstates the benefits, however, be-cause of the substitution of Canadian for US

wood products.

Climate–Forest Interactions With forests covering approximately

30% of Earth’s land surface and storingabout 45% of terrestrial carbon, forests andglobal climate are closely linked in terms of carbon storage and releases, water fluxesfrom the soil and into the atmosphere, andsolar energy capture. Estimates of the car-bon, water, and energy balances of forestsdiffer, however, depending on the atmo-spheric model or forest cover and forest in-

ventory model used.Not all the carbon captured by treesends up as stored carbon. Approximately three-quarters of the carbon fixed by photo-synthesis is immediately released throughecosystem respiration. In forests, about one-half of the respiration comes from above-ground vegetation and one-half from theforest floor and forest soils. The increase inforest floor and soil respiration is pro-portional to how much woody debris—

whether from natural mortality or loggingresidues—is decomposing on site.

Temperate forests continue to increaseas carbon sinks even though large quantitiesof wood products are removed from theseforests annually. The current rate of carbonaccumulation in temperate forests may de-cline, however, if the average age of forestscontinues to increase. Changing climatemay also adversely impact carbon seques-tration rates. Significant increases in theshift from live-tree to dead-tree biomassfrom fires and beetles in western North

America have generated interest in changing

forest management approaches to respondto climate-related stresses. Some researchersbelieve that seed sources and silviculturalmethods must be matched to predict cli-matic conditions to maintain or increaseproductivity.

Recent data on tropical forest coverhave significantly lowered the estimates of

net GHG emissions related to tropical de-forestation overall and suggest a need for agreater focus on deforestation in areas wherecarbon-rich peat soils are disturbed. Whenthe broad range of feedbacks is considered,tropical forests are considered by most ob-servers to be the most effective forests interms of overall climate benefits providedper unit of area or biomass.

Links between water and carbon fluxare seen in all forest types but most strongly in the tropics. The most significant waterflux link between forests and the atmosphere

is the evaporative cooling from tropical for-est canopies, which has a positive relation-ship with cloud formation and rainfall pat-terns. In semi-arid areas in tropical andtemperate regions, research has pointed to atradeoff between increased carbon storage innew trees and reductions in streamflow available to other plants and animals.

A significant energy flux related to for-ests at the global level is the drop in the al-bedo when dark-colored trees expand at theexpense of snow-covered areas with little orno tree cover. A lower albedo decreases the

fraction of solar energy that is reflected intothe atmosphere. The albedo effect is mostimportant on the northern edge of the bo-real region; it is measurable but less signifi-cant in temperate regions.


Feedstock supply depends not just onsupply-and-demand curves but also on bio-mass availability; harvesting, delivery, andother costs; landowner objectives; and na-tional, regional, state, and local laws, regula-tions, and policies. Forest biomass includesresidues from forest stand improvements,timber harvests, hazardous-fuel reductiontreatments, forest health restoration proj-ects, energy wood plantations, and othersimilar activities. Regional variations influ-ence the United States’ potential feedstock supply of biomass and ultimately the loca-tion of bioenergy facilities. Readily availableforest biomass supply encompasses woody biomass by type and US region that is eco-




nomically available based on standard andexisting logging configurations.

Expanding forest biomass use for eitherbiofuels or energy generation may compete

with traditional forest products, but it may also produce benefits through competitionand market efficiency. Changes in feedstock use are controversial and a point of conten-

tion for competing industries (paper andpulp versus bioenergy), environmental andother nongovernmental organizations (whoare concerned about industrial-scale bio-mass production), private landowners (whosee opportunities for additional revenuestreams), and public land managers (whoneed markets for low-quality material re-moved from overgrown forests).

Biomass feedstock supply will be af-fected by landowners’ preferences based onprice, investment-backed expectations, andenvironmental considerations, all of which

are affected by government energy and envi-ronmental policies. Short-rotation woody crops, such as shrub willow, hybrid poplar,southern pine, and eucalyptus, have the po-tential to increase woody biomass feedstocksfrom both forestlands and converted agri-cultural lands.

Energy, Products, andSubstitution

Forests store carbon, and so do woodproducts. Evaluation of carbon flows showsthat conversion of wood to useful products

can significantly reduce overall societal car-bon emissions. To arrive at a cogent pictureof the overall forest sector effect on atmo-spheric carbon, we need to understand thematerial and energy flows as inputs and out-puts within well-defined system boundaries.Then, we need to integrate the effects acrosssystem boundaries to understand the many

ways in which substitution of harvested wood products for fossil fuels andfossilfuel–intensive products can offset the flow of car-bon dioxide from fossil carbon reserves tothe atmosphere.

Forest products have lower embodiedenergy (the amount of energy it takes tomake products) than comparable buildingproducts, so there is a substitution effect

when wood is used in place of steel, alumi-num, concrete, or plastic. That substitutioneffect varies by use and comparable productbut on average, every 1 tonne (t) of woodused removes 2.1 t of carbon from the atmo-sphere.

Wood products store carbon for the life

of the product. At the end of their lives, wood products can be reused, recycled,burned for energy, or landfilled. If they are landfilled, the carbon contained withinthem can be stored for a long periodof time,but there can also be a substantial GHGcost because of methane emissions, particu-larly from paper decomposition. This sug-

gests that incentives should be high to reusepaper and wood, recycle it, or burn it to re-cover at least its heating value.

A sustainably managed forest can pro-duce a continual flow of wood products andbiomass for energy while at the same timemaintaining or increasing carbon stocks.Determining the effects of forest harvestingfor wood products or bioenergy productionrequires a landscape-level analysis over time.For instance, in harvesting woody biomassfor use in generating energy, carbon is re-moved from the forest, reducing forest car-

bon stocks, and that carbon is liberated asbiomass is converted to energy. However, aslong as harvests and mortality do not exceednet growth across the forest, carbon stocksremain stable or increase through time andthe total carbon sequestration potential of the forests is maintained. In addition, theproducts removed from the forest provide along-term carbon benefit equal to theavoided emissions from fossil fuels less any fossil energy used to harvest and transportthe biomass feedstock.

Sustainable forest management helps

ensure a neutral carbon cycle on the forest-land base. Carbon storage in wood productsand wood use for energy from material har-vested from that land base is an additionalcarbon benefit beyond the forest.

Forest Carbon Policies At the national level, increasing net car-

bon sequestration rates in forests, using wood products rather than fossil fuel–inten-sive products, and using forest residues forenergy will reduce GHG emissions. How-ever, project-based accounting rules that ig-

nore or undercount nonproject benefits andrisks can result in project-based conclusionsthat differ from a more comprehensive na-tional or international accounting.

Forestry offset protocols have been cre-ated to serve different purposes. Some werecreated as part of cap-and-trade programs,either mandatory or voluntary, or as part of emissions reduction schemes. Others weredeveloped independently but have been ad-opted by one or more programs. Althoughthe concept of offsets is the same, the

amount of carbon credits generated for thesame project can differ dramatically depend-ing on the sets of carbon pools allowed andthe baseline approach employed.

Protocols for forestry offset projectsusually include the following elements: eli-gibility, carbon sequestration calculationprocedures, baseline requirements, carbon

pools, crediting period, leakage, perma-nence, and reversals. The costs associated with establishing and maintaining forestry offset projects depend largely on the pro-tocols’ specifics. Because protocols differgreatly in their requirements for monitoringand verification, carbon measurement, andthird-party certification, the transactioncosts per hectare also vary substantially, by asmuch as a factor of five.

Forestry offset projects generally can beclassified as afforestation, reforestation, for-est management, forest conservation, or for-

est preservation. The estimates of net cli-mate benefits from forest management,conservation, or preservation projects de-pend largely on the assumptions about thecarbon storage and substitution benefits of

wood products; this is less true for afforesta-tion and reforestation projects. For an offsetproject to have any effect on net GHG emis-sions to the atmosphere, the net amount of carbon sequestered must be additional to

what would have occurred anyway. For for-est projects, additionality is relatively easy toestablish when new trees are planted and

maintained but considerably more difficultto demonstrate when based on what did notor will not happen (e.g., “I was going to har-vest in 10 years but instead will wait 30years”). If forest carbon credits are used topermanently offset industrial emissions, theforest project must show permanence by en-suring that initial emissions are balanced by an equivalent amount of new carbon storageover time. However, strict project-levelguarantees or insurance increase the cost of forest carbon credits. Also, US forestry proj-ects that increase in-forest carbon sequestra-

tion through a short-term reduction in har-vests may have national market leakage ratesthat approach 100% if harvests from non-project forests meet consumer demand.

Modeled benefits of forest carbon offsetprojects are highly variable and dependenton assumptions, including estimates of for-est carbon flux. Determining with precision

whether a threshold flux for a given area hasbeen or will be achieved is difficult with thetechnology available today.

The measurement challenges and rela-




tively high transaction costs inherent in for-est carbon offset systems motivate consider-ation of other policies that can promoteclimate benefits from forests without requir-ing project-specific accounting. For exam-ple, market prices for building and energy products that reflect emissions, economicincentives for treeplanting, and credible in-

formation disclosure on the relative climateimpacts of different products could provemore effective at a national scale.

Integrating Forests into aRational Policy Framework

Forests are an integral component of the global carbon cycle and may change inresponse to climate change. US forest poli-cies can foster changes in forest managementthat will provide measurable reductions incarbon emissions over time while maintain-ing forests for environmental and societal

benefits, such as timber and nontimber for-est products, vibrant rural communities,clean water, and wildlife habitat. Policiesfounded on three tenets reflecting the stocksand flows of woody biomass can ensure thatUS forests will produce sustainable carbon,and environmental and societal benefits.

1. Keep Forests as Forests and Man-age Appropriate Forests for Carbon

For more than 70 continuous years, USforest cover has increased andnet growthhasexceeded removals and mortality. Therefore,

carbon storage is increasing in the UnitedStates. In some forests (e.g., old-growth),other considerations and other benefits willoutweigh carbon benefits. However, forests

will change with or without management,and choosing not to manage has its own car-bon consequences. Young, healthy forestsare carbon sinks. As forests mature, they generally become carbon-cycle neutral oreven carbon emission sources because netprimary productivity declines and the decay of trees killed by natural disturbances—

windstorms, fire, ice storms, hurricanes, and

insect and disease infestations—emits car-

bon without providing the carbon benefitsavailable through product and energy substi-tution.

2. Recognize that Substantial Quanti-ties of Carbon Are Stored in WoodProducts for Long Periods of Time

Wood is one-half carbon by weight,and it lasts a long time in service—often fora long time after being retired from service.Substantial volumes of wood go into con-struction products and structures: evenduring the midst of the recent “Great Reces-sion” (2007–2009), US housing starts ex-ceeded 440,000 annually. Additional woodis used for furniture and other products,

which at the end of their useful lives may beconverted to energy. Paper may go intolong-term use (e.g., books) or be recoveredfrom the waste stream for energy produc-tion. Other wood—construction debris,yard waste, and unrecycled paper—windsup in landfills, where it often deterioratesmore slowly than is generally assumed. Intotal, the rate of carbon accumulation from

wood products in use and in landfills wasabout 88 million tonnes of carbon dioxideequivalents (CO

2e) in 2008, about 12% of the rate of sequestration in forests.

3. The Substitution Effect Is Real, Irre- versible, and Cumulative

Compared with steel, aluminum, con-crete, or plastic products, considerably lessenergy, and vastly less fossil fuel– derived en-

ergy, is required to make wood products.The low embodied energy of wood buildingproducts, structures, furniture, cabinets, andother products has been well documentedthrough life-cycle assessments. Not only isthe quantity of energy used in manufactur-ing wood products low compared with othermaterials, but the quantity of fossil energy iscomparatively very low: one-half to two-thirds of the energy used by the North

American wood products industry is bioen-ergy. For instance, compared with steelframing with an average recycled content,

the manufacture of wood framing requires

one-half or less the total energy and one-fourth to one-fifth the fossil energy.

Conserving forests for recreational, aes-thetic, and wildlife habitat goals has been astrongpolicy driver in the UnitedStatesoverthe past few decades, especially in the PacificCoast and Northeast regions. Evidence of increasing losses to disturbances that are

not captured in forest growth modeling anddecreasing rates of carbon accumulation inmaturing forests suggests that a strong con-servation-oriented strategy may not alwaysproduce significant global climate benefits.The climate benefits of active forest manage-ment are most apparent when the substitu-tion benefits that occur in the consumer sec-tor are included. As we move forward withpolicy discussions regarding the many posi-tive roles of US forests at local, national, andglobal scales, it will be imperative that ob-

jective, science-based analysis and interpre-

tations are used and that particularly closeattention is paid to the assumptions under-lying the analyses.

US policymakers should take to heartthe finding of the Intergovernmental Panelon Climate Change (IPCC) in its Fourth

Assessment Report when it concluded that“In the long-term, a sustainable forest man-agement strategy aimed at maintaining orincreasing forest carbon stocks, while pro-ducing an annual sustained yield of timber,fibre or energy from the forest, will generatethe largest sustained mitigation benefit”

(IPCC 2007a, p. 543). A rational energy andenvironmental policy framework must bebased on the premise that atmosphericGHG levels are increasing primarily becauseof the addition of geologic fossil fuel–basedcarbon into the carbon cycle. Forest carbonpolicy that builds on the scientific informa-tion summarized in this article can be animportant part of a comprehensive energy policy that promotes energy independenceand delivers carbon benefits while providingessential environmental and social benefits,including clean water, wildlife habitat, and

recreation.




Introduction

The United States needs many differ-ent types of forests: some managedfor wood products plus other bene-

fits and some managed for nonconsumptiveuses. Management decisions must accountfor local conditions; landowners’ objectives;and a broad set of environmental, economic,and societal values. This article considershow various forest and wood use strategiescan reduce accumulation of greenhousegases (GHG) in the atmosphere.

Carbon Framework A simplified representation of the

global carbon system shows that carbon isstored in various pools (stocks) with dy-namic flows (fluxes) between the pools (Fig-ure 1-1). The oceans, and lands, both for-ested and nonforested, emit carbon to andabsorb carbon from the atmosphere in atwo-way flow. In contrast, carbon removedfrom fossil fuel reserves acts as a one-way flow because regardless of whether emissionsfrom fossil fuel combustion are ultimately taken up by land, ocean, or forests, they arenot returned to fossil fuel reserves on any-thing less than a geologic timescale. Al-though there are many uncertainties in mea-suring carbon stocks and flows globally, theobjective of reducing global GHGs suggeststhe importance of increasing carbon stor-age in pools other than the atmosphere.Growing more forests and keeping forestsas forests are only part of the solution be-cause focusing solely on the sequestrationbenefits of the forests misses the important

(and substantial) carbon storage and sub-stitution GHG benefits of harvested forestproducts.

An assessment of forest management aspart of a carbon mitigation strategy needs toconsider all of those elements as an inte-grated whole across spatial and temporalscales. Policies that ignore how forests fitinto the broader economic, environmental,and social framework can fall far short of

possible reductions in carbon emissionsand lead to counterproductive mitigationstrategies that are environmentally and eco-nomically unsustainable. Effective solutionsrequire a wider perspective that considers,among many other things, the role of forestsas a source of products for society and theeffects of those products on GHG concen-trations.

Forest Carbon PoliciesUS environmental and energy policies

need to be linked or at least be based onmutual recognition and should be based onfour basic premises grounded in the sciencesummarized in this article:

1. Sustainably managed forests can providecarbon storage and substitution benefits

while delivering a range of environmen-tal and social benefits, such as timber andbiomass resources, clean water, wildlifehabitat, and recreation.

2. Energy produced from forest biomass re-turns to the atmosphere carbon thatplants absorbed relatively recently fromthe atmosphere; it essentially results in

no net release of carbon as long as overallforest inventories are stable or increasing(as is the case with US forests).

3. Forest products used in place of energy-intensive materials, such as metals, con-crete, andplastic, (a) reduce carbonemis-sions (because forest products require lessfossil fuel–based energy to produce), (b)store carbon (for a length of time basedon products’ use and disposal); and (c)provide biomass residuals (i.e., waste

wood) that can be substituted for fossilfuels to produce energy.4. Fossil fuel–produced energy releases car-

bon into the atmosphere that has residedin the Earth for millions of years; forestbiomass–based energy uses far less of thecarbon stored in Earth thereby reducingthe flow of fossil fuel–based carbon emis-sions to the atmosphere.

US policies canencourage managementof forests for all the carbon and energy ben-efits of forests and forest products while

sustaining ecosystem health and traditionalforest biomass users. The scientific informa-tion in this article can be used as the basis fordeveloping sound forest carbon policies.

Figure 1–1. Major global carbon pools, their interactions, and forest and fossil fuelproducts. (Source: Adapted from Lippke et al. 2011.)


section 1



Forest Carbon Stocks and Flows

US forests were in carbon balance

with the atmosphere (emissionsapproximately equal to sequestra-

tion) from the beginning of Euro-Americansettlement to 1800. Subsequently, forests

were cleared for agriculture and construc-tion, resulting in significant emissions of carbon until 1950. These same forests arenow significant carbon sinks (Pacala et al.2001) because of forest regrowth in areas

whereagriculture was abandoned (Birdsey etal. 2006), fire suppression in western forests,increased productivity of planted forests,and forest management activity. These fac-tors were responsible for a carbon flux aslarge as 390 teragrams (Tg; trillion grams)/year as recently as the 1990s (Houghton et al.2000). (By convention, carbon sequestra-tion is represented as negative flux and car-bon emissions as positive flux.)

US forests today are known to functionas a substantial carbon store, with woody biomass carbon stocks averaging nearly 58Mg (million grams)/ha, estimated via re-mote sensing (Myneni et al. 2001), andnearly 84 Mg/ha, estimated via inventory statistics (US Environmental Protection

Agency [EPA] 2010). Carbon flux reportedfor the entire forested area of the UnitedStates ranges from 141 (Myneni et al.2001) to183 (Birdsey et al. 2000) to –192(US EPA 2010) Tg of C/year, not account-ing for storage in harvested wood products.Both stocks and flux vary greatly by region,forest type, site class, owner group, and re-serve status. For example, inventoriedaboveground live and deadwood averagecarbon stocks in California range from 13Mg/ha for pinyon-juniper to 360 Mg/ha forredwood (Christensen et al. 2008). Carbonflux on highly productive national forestlands in California averages 1.25 Mg/haper year versus 0 Mg/ha per year for low-productivity (nontimberland) forests (Fried2010). Han et al. (2007) report a sink sizefor an 11-state region in the southernUnited States as 130 Tg of C/year andassert that this is sufficient to capture 23% of greenhouse gas (GHG) emissions in that re-

gion. Across the whole United States, car-bon removed from the atmosphere by forestgrowth or stored in harvested wood prod-ucts is equal to 12–19% of fossil fuel emis-sions (Ryan et al. 2010, EPA 2010).

Forest Carbon TrajectoriesForest carbon constitutes about one-

half of the bone-dry forest biomass. When we consider the temporal dynamics of car-bon in the forest, therefore, it can be helpfulto think of how forest biomass fluctuatesover time at the stand level. In forest typesthat are predominantly even-aged, either be-cause of management choice or natural dis-turbance regimes, a stand is initiated (viaafforestation or reforestation after a fire, har-vest, or other stand-replacing disturbance),grows (using photosynthesis to extract car-bon from the atmosphere and distribute it toleaves, stem, and roots), and ultimately dies(via harvest or other stand-replacing distur-bance or conversion to a nonforestland use).Management activities, such as thinning,

fertilization, and hazardous fuel removal,may occur along the way. Where stand-replacing disturbance is rare or managementemphasizes selection harvest, the birth anddeath of trees in a stand is continuous orepisodic, resulting in a stand-level trajectory of forest carbon without pronounced peaksand valleys. In such forests, gross primary productivity and allocation of forest car-bon among live and dead trees, understory shrub and herbaceous vegetation, forestfloor, litter and soils are ever changing. Un-derstanding these dynamics and how alloca-

tions change with stand age, density, andmanagement is essential to identifying op-portunities to manage forests to increasetheir capacity to remove carbon dioxide(CO2) from the atmosphere (Litton et al.2004).

Stand-Scale Trajectories A newly regenerating forest behaves as a

net carbon source to the atmosphere becausethe above- and belowground remains of

woody plants in the antecedent forest are

subject to decay and heterotrophic (micro-bial) respiration. In a study of disturbancetypes in evergreen forests in seven disparateregions of the United States, Thornton et al.(2002) found that peak emissions related todisturbance occurred 2 years after the distur-bance, and that emissions could exceed se-questration for up to 16 years—until thelive trees grew to a size at which their absorp-tion of carbon exceeded the onsite lossesfrom decomposition of the predisturbanceforest. If an old-growth stand, in whichdisturbance or harvest leaves behind highvolumes of large-diameter deadwood, theperiod in which emissions exceed sequestra-tion could be as long as 20–30 years (Har-mon and Marks 2002). Assuming sufficientstocking, a stand of pole-sized trees is wellpositioned to accumulate woody biomasscarbon at an increasing rate for several de-cades, barring excessive disturbance, but atsome point, growth decelerates.

Because carbon sequestration ratespeak in the first 100 –150 years in most even-agedstands as tree mortality losses increase, olderstands tend to be weak sinks at best. None-theless, analysis of forest inventory plotsshows that in rare cases (e.g., very wet forestson Washington’s Olympic Peninsula), for-est carbon stores may continue to increasefor as long as 800 years. A few old-growthforests can achieve truly massive (more than1,100-Mg of C/ha) carbon stocks (Smith-

wick et al. 2002), and researchers areincreas-ingly documenting that some old-growthforests can continue to have greater seques-tration than respiration as long as they arenot affected by stand-terminating distur-bances. Luyssaert et al. (2008) also foundpositive net ecosystem productivity in for-ests as old as 800 years in the boreal region,but they noted that many stands had experi-enced, and will continue to experience,stand-terminating disturbances.

Growth decline is ultimately inevitable,however, as gross primary productivity is re-duced by nutrient and other resource limi-tations and carbon allocation shifts from

wood production to respiration (Ryan et al.


section 2



2004). Ponderosa pine forests older than190 years in central Oregon remain weak carbon sinks, with a mean flux of 0.35 Mgof C/ha per year (Law et al. 2003). From alandscape perspective, 85% of the woody biomass-based carbon storage in ponderosapine forests in this area is found in standsolder than 100 years and faces a significant

risk of carbon loss from wildfire. Dimin-ished sink strength at even younger ages hasbeen widely documented. In Swiss alpineforests, storage capacity was found to peak at100 years, after which forests were net emit-ters of carbon (Schmid et al. 2006). An Aus-trian study that also accounted for woodproducts and bioenergy offsets found thatoverall carbon storage was greatest in un-managed stands over a 100-year horizon,but that the effective storage could well bemuch less because the standing carbon wasvulnerable to unforeseen disturbances

(Seidl et al. 2007). The Tongass NationalForest, where fire is unlikely, holds 8% of the forest carbon in the United States butis approaching a state of no additional car-bon sequestration because carbon emissionsvia microbial respiration will soon equalnewly sequestered carbon via photosynthesis(Leighty et al. 2006).

At some point, reduction of carbonstocks in any individual stand is also inevita-ble. Carbon may be emitted through naturaldisturbance or harvesting. Typically, a largefraction of forest carbon from a harvested

stand is sequestered in long-lived forestproducts or converted to bioenergy. Al-though carbon emissions from producingbioenergy may be the same as emissionsfrom natural disturbance, the latter achievesno carbon benefit. An accurate portrayal of forest carbon and the carbon benefits andcosts of any harvested products requireslooking at a large number of forests stands of different ages, the amount of carbon seques-tered in products, and the likely effects of disturbances.

Forest-Scale Trajectories Whereas forest carbon dynamics at

stand scale are driven by growth, harvest,and mortality, at the forest scale they are af-fected at least as much by the distribution of forest area by age class or successional stateand management regime. More than one-third of the forest area of Yellowstone Park,e.g., is of a single age class, bornafter the firesof 1988. Now undergoing a period of rapidgrowth and accumulating carbon, theseforests still have 91–99% of their carbon in

coarse woody debris and mineral soil; themature lodgepole pine forests elsewhere inthe park have 64% of their carbon in livetrees (Litton et al. 2004). The carbon lost inthe 1988 fires may not be recovered for 230years (Kashian et al. 2006). In this and lessextreme cases, the carbon implications of disturbance are greatly influenced by the

amount of the previous stand used in har-vested wood products and bioenergy; inthe Yellowstone case, this was zero. Late-successional forests, like the federally pro-tected wilderness and parks in the West,hold tremendous carbon stores but have low rates of carbon accumulation compared

with younger forests. The carbon stores of very large forest areas—those consisting of thousands of stands spanning a broadrange of age and successional developmentclasses—have achieved an approximately steady-state plateau (Harmon et al. 2001).

However, this “carbon plateau” may trendup or down with changes in growth ratesand natural and human disturbance fre-quency and magnitude, all of which may re-sult from climate change (Latta et al. 2010,Smithwick et al. 2007).

Management and Forest Carbon Capture

Eventually, all trees die, and when they do, their carbon moves quickly (e.g., fire,

windthrow, or harvest) or slowly (e.g., insectattack or disease infestation) into other pools

(e.g., deadwood, soil, products, or atmo-sphere). The process of forest renewal andtree growth, competition, aging, and, even-tually, death is ongoing. Environmentally sensitive use of forest mortality offers the op-portunity to capture some permanent car-bon benefits via long-term storage in prod-ucts and/or substitution for fossil fuelenergy. Depending on other objectives,these benefits can be captured using a widevariety of management-driven removals, in-cluding sanitation, mechanical fuel treat-ment, thinning, selection harvest, regenera-tion harvest, and salvage logging, albeit withvarying implications for economic feasibility and residual stand conditions. Such benefitsdo not accrue when dead and dying trees areleft in the woods to emit carbon via hetero-trophic respiration, and when capture op-portunities are missed, there are no secondchances. The timing of removals, however,can be important.

Regeneration harvest in a high-volumeold-growth stand releases a great deal of car-

bon—so much, in fact, that it may take de-cades before the new stand establishesgreater net uptake of carbon (after account-ing for storage in wood products, slash dis-posal, emissions from deadwood and otherharvest-killed vegetation, and soil carbonemissions) than if the old-growth had beenleft alone (Janisch and Harmon 2002).

However, such stands, which are found al-most exclusively on public lands, are rarely harvested or even actively managed in theUnited States today, and in any case, are un-likely to be considered candidates for bio-energy feedstocks because their value as en-ergy feedstock is low compared with thehigh social values placed on old-growth for-ests. Where catastrophic losses are likely (e.g., in drier forest types where fire or in-sects drive shorter disturbance intervals), thecarbon calculus is different. In this case,management that involves periodic harvest

provides a range of societal benefits. Regen-erated young stands continue to sequesternew forest carbon, and products derivedfrom the harvested wood store carbon forvarious lengths of time and provide substi-tution benefits that show up in nationalGHG accounts in lower emissions from fos-sil fuel burning.

Forests can be managed to maximizecarbon sequestration. Even-aged rotationssynchronized to culmination of mean an-nual increment* lengthen the period during

which current annual increment (1 year’s

addition to the live-tree carbon pool) ex-ceeds the maximum MAI. Across an owner-ship, shorter rotations may reduce maxi-mum sequestration on currently managedsites but can generate additional discountednet revenue that could be invested to in-crease growth in other forests. Rotationslonger than maximum MAI reduce the ca-pacity for long-term storage in harvested

wood products and, at least in some systems,increase the risk of catastrophic carbon loss.Reducing stocks in forests managed forcommercial products may reduce the finan-

cial and carbon risks of losses to episodicdisturbances, such as wildfires or severestorms, and potentially increase the averagevalue of the products produced; increasingstocks may increase the rate of carbon accu-mulation but also increase loss risk. Al-though any kind of harvest releases at least

* MAI; i.e., the point at which average annual woody carbon accumulation, calculated as totalcarbon divided by stand age, peaks and begins tofall.




some carbon to the atmosphere, thinningand selection harvests typically have a loweremissions density per unit area because they produce less slash and residual organic mat-ter (e.g., down wood and dead roots). Com-pared with regeneration harvests, thinningand selection also result in a farshorter delay before net carbon uptake is restored, becausethe residual stand maintains greater carbonsequestration capacity than does a clearcut.Even-aged harvests have a somewhat longer-lasting effect on net carbon flux because

there is no residual stand to sequester car-bon, and seedlings must grow for severalyears before they become a significant car-bon sink.

Estimates of US Carbon Flux by PoolTable 2-1 shows the estimated US for-

estry sector annual flux in teragrams of car-bon dioxide equivalent (CO2e) for 2008, themost current year available (US EPA 2010),as reported under international carbonprotocols. This framework calculates netchanges between consecutive, annual esti-

mates for five forest pools and two harvested wood pools. Note that only one-half of theflux is estimated to occur in the above-ground, live-tree pool—the pool that ismost commonly considered in carbon ac-counting analyses. Of the aboveground for-est carbon, current measurement proceduresare more accurate for the boles of trees of thespecies and sizes that have typically beenused to produce products, and considerably less accurate for noncommercial species andfor the branches, tops, and roots of all trees.

As currently reported, estimates for all otherforest pools are derived from models, in

which their assumptions may lead to inaccu-racies. For example, deadwood is modeledasa fraction of live wood, and soil carbon den-sity is assigned by forest type. Although de-finitive conclusions are elusive because of changes in inventory measurements and

protocols since 1990, the US forest carbonsink has been reported as weakening due toincreasing forest age and time since farm-land abandonment, climate variability, andincreasing frequency and severity of naturaldisturbances (some resulting from many years of fire suppression). Moreover, it ap-pears that climate change will increase thefrequency of disturbance in forest ecosys-tems (e.g., Hurtt et al. 2002, Dore et al.2008, Pan et al. 2008).

Carbon Trajectories in Forest SoilsSoil carbon, both in litter layers and as-

sociated with soil minerals, occurs in a het-erogeneous mix of organic materials(Hedges et al. 2000). Soil carbon is the larg-est actively cycled terrestrial carbon pool(Schlesinger 1997, Hedges et al. 2000, Job-bagy and Jackson 2000) and can have resi-dence times of hundreds to thousands of years (Gaudinski et al. 2000, Trumbore2000). These attributes imply that soils may be an attractive pool to sequester carbon forlong periods (Oldenburg et al. 2008). Forestmanagement and disturbances affect soilcarbon stocks through changes in carbonfluxes and carbon quality, and the magni-tude and direction of these changes tend tobe highly variable by region and situation.

The simplest conceptual model of soilcarbon is that of two pools of labile and re-calcitrant carbon that have short and longresidence times, respectively. Generally, themost labile carbon is organic (e.g., O hori-zons and belowground particulate organicmatter) and represents about 1–12% of for-est soil carbon (Schlesinger 1997, Fisher etal. 2000, Sollins et al. 2006). Mineral-asso-ciated carbon represents more than 90% of all soil carbon and has the longest residencetime (i.e., oldest 14C age) (Fisher et al. 2000,Gaudinski et al. 2000, Jobbagy and Jackson2000). Mineral-associated carbon is pro-tected from mineralization through itschemical stabilization with mineral surfaces(particularly reactive minerals such as ironoxides) (Kleber et al. 2005, Mikutta et al.2006) and physical protection within soilaggregates (Six et al. 2002). Additionally,36 – 41% of all soil carbon can be found be-

low 1 m in depth (Jobbagy and Jackson2000), where it has been found to have very long residence times (thousands of years;Trumbore et al. 1995).

Litterfall and root turnover (rhizodepo-sition) are the major inputs of carbon to soilcarbon pools and are closely related to netprimary productivity (Schlesinger 1997).

Root inputs of carbon account for 56–71%of mineral soil carbon (Rasse et al. 2005).Most carbon entering soil pools in forestedsystems decomposes and is emitted throughheterotrophic soil respiration (Hanson et al.2000, Subke et al. 2006). An increase in thisheterotrophic soil respiration caused by global warming may be a positive feedback mechanism of climate change (Raich andSchlesinger 1992). Stabilization of carbonentering the soil system depends on the car-bon content of the soil horizon it enters.Carbon entering a carbon-rich or carbon-

saturated surface horizon may accumulate ata constant rate but have a very short resi-dence time. On the other hand, carbon en-tering a carbon-poor soil horizon has morepotential to be stabilized in a mineral-asso-ciated recalcitrant pool because of the largerproportion of reactive mineral surface area.Because surface soil horizons in forest soilsare near saturation, an increase in carbonstores here is unlikely. Mineral soil at depth(e.g., more than 50 cm) has much lower car-bon concentrations and therefore may havethe capacity to stabilize carbon; however, in-

puts of carbon to this depth are also low.Harvesting and thinning operations al-ter soil carbon cycling by cutting the supply of root and litter inputs, disturbing the soilsurface, and changing temperature andmoisture regimes, all of which tend to in-crease heterotrophic respiration rates; how-ever, they also move some forest floor carboninto deeper, mineral soil layers. A few meta-analyses and review articles conclude thatthe net effect of harvest is a reduction in soilcarbon, with forest and soil type determin-ing the magnitude of carbon loss (Johnson

and Curtis 2001, Jandl et al. 2007, Nave etal. 2010). Nave et al. (2010) reported an 8%average reduction in soil carbon stocks afterharvesting over all forest and soil types stud-ied. However, most of the studies coveredsampled only the top 20 cm of soil, or even

just the forest floor, so these losses are pri-marily the result of a reduction in litter layermass and organic matter inputs from grow-ing trees; they may also reflect the samplingchallenges of accurately tracking forest floorcarbon over time (Federer 1982, Yanai et al.

Table 2-1. Carbon flux in the US forestry sector in 2008, excluding energy sectorand product substitution benefits.

Carbon pool

2008 fluxa

Tg CO2eb

Percentageof total

Forest 704 89c

Aboveground biomass 397 50Belowground biomass 79 10Deadwood 26 3Litter 56 7Soil organic carbon 146 18

Harvested wood 88 11

Products in use 24 3 Wood in landfills 64 8

Total net flux 792 100

a Carbonsequestrationis negative flux; carbon emissionsis pos-itive flux.b Tg CO2e, teragrams of carbon dioxide equivalent; to obtainteragrams of C from Tg CO2e, divide the latter by 3.667.Source: US EPA (2010).c Percentages of forest carbon pool do not add up to 89 due torounding.




2003). Harvesting either has no effect onmineral soil carbon or leads to increases(Slesak et al. 2011). Harrison et al. (2011)report that for a variety of ecosystems andtreatments, valid estimation of changes inecosystem carbon was not even possible

without sampling soil deeper than 20 cm.Even whole-tree harvesting for biomass pro-

duction may have little long-term effects onsoil carbon stocks if O horizons are leftundisturbed and nutrients are managed(Powers et al. 2005). Forest thinning andcompetition control have a much smallerdisturbance on soil characteristics and there-fore affect soil carbon stocks less. In addi-tion, by reducing the likelihood of stand-replacing wildfire and fire severity at the soilsurface, thinning and fuel reduction treat-ments may reduce future losses of soil car-bon.

Forest fertilization may increase or de-

crease soil carbon stores by increasing netprimary production (), shifting produc-tion to aboveground vegetation components(), increasing soil carbon mineralization(), and depressing some enzyme activity () (Jandl et al. 2007, Van Miegroet and

Jandl 2007). Effects of forest fertilization onsoil carbon have been found to be site-spe-cific, but most studies show an increase insoil carbon stock (Johnson and Curtis2001). However, fertilization of forests hasbeen linked to increased soil emissions of nitrous oxide (N2O, a GHG 300 times

stronger than CO2), so this must be factoredin when selecting the best managementstrategy to mitigate GHG concentrations(Matson et al. 1992, Castro et al. 1994). Theproduction of fertilizer itself also results incarbon emissions because the productionprocesses are energy intensive.

The influence of short-rotation woody crops and afforestation on soil carbon stocksappears to depend primarily on previousland use, management practices, and soilcharacteristics (Tolbert et al. 1997, 2002,Guo and Gifford 2002, Post and Kwon

2000, Sartori et al. 2006). Conversion of ag-ricultural and degraded lands to forest orshort-rotation woody crops is likely to in-crease soil carbon stocks. Lands used for pe-rennial crops or pasture typically have highercarbon concentrations than annually tilledlands, so afforestation may or may not in-crease soil carbon stocks. Depending onthe aforementioned factors, short-rotation

woody crops may increase soil carbon up to0 –1.6 Mg/ha per year for decades before thesoil reaches a new equilibrium (Guo and

Gifford 2002, Post and Kwon 2000, Sartoriet al. 2006).

Fire can be a major cause of carbon lossfrom forests, but the magnitude of loss de-pends on fire severity. Low-severity wildfiresand prescribed fires have little effect on soilcarbon and may even increase mineral soilcarbon through deposition and mixing of

partially burned or residual organic matterinto the surface mineral soil (Johnson andCurtis 2001, Hatten et al. 2005, 2008).Conversely, high-severity wildfire decreasessoil carbon stocks by 10–60% (Baird et al.1999, Bormann et al. 2008, Hatten et al.2008). Recovery rates after moderate- tohigh-severity fire may be similar to a post-harvest scenario, provided soil productivity is not damaged. Although high-severity

wildfire can release significant amounts of carbon from soil pools, the loss can be re-duced through well-designed fuel reduction

programs based on mechanical thinning andprescribed fire.

Given the variable properties of soils,determining soil carbon stores is more ex-pensive (many samples are required) thaninventory-based accounting for above-ground, live-tree carbon stores. The highvariability of soils and inability to take re-peated measures on exactly the same soilmake accounting for soil carbon flux overtime even more challenging. Many research-ers have developed sampling protocolsfor soil carbon stores (e.g., Shaw et al. 2008)

or the effects of different treatments (e.g.,Homann et al. 2001). The magnitude andspatial dependence of soil variability differamong soil types, so a one-size-fits-all ap-proach to soil sampling does not work (Ay-res et al. 2010). The Forest Inventory and

Analysis (FIA) (US Forest Service 2011)program of the US Forest Service collectssoil carbon data to a depth of 20 cm acrossthe United States on phase 3 plots (one per96,000 ac). This sampling intensity and lim-ited sampling depth are insufficient to ac-count for soil carbon across the United

States; however, it may help in refining asampling system that characterizes soils for agiven region, forest type, and soil type tosupport a targeted soil carboninventory pro-gram.

Carbon Flux from Forest Disturbances

As the average age of trees in forests in-creases, both carbon inventories and carbonlosses to mortality increase (Stinson et al.

2011). In the West, where public forestspredominate, the average stand age is 90years; for private forests in the East, it is 47years. In Canada, the average stand age formanaged forests is 92 years, and in Europe itis 48 years (Bottcher et al. 2008). US west-ern forests are similar to those of westernCanada (Kurz et al. 2008a, Stinson et al.

2011) in their high carbon inventories as well as current high losses to mortality fromfires and insects. The younger European for-ests are estimated to have much higher netcarbon sequestration rates and much lowerlosses to mortality (Luyssaert et al. 2010).The fraction of total growth in merchant-able volume that ends up as mortality is now nearly twice as high on national forests (0.33in the East and 0.36 in the West) as on tim-berlands outside the national forests (0.19 inthe East and 0.22 in the West; Smith et al.2009). Thus, management that anticipates

disturbance is a more compelling idea for western forests than for forests elsewhere. If carbon values rise and more efficient recov-ery technologies develop, natural distur-bances may be seen as opportunities to cap-ture carbon benefits via bioenergy from deadtrees that would otherwise emit carbon withno compensating benefits. Understandingthe disturbance processes that drive mor-tality and the fate of the dead biomass—

whether it is left in the forest to emit carbonover time or collected and used—is a signif-icant but often overlooked component of

forest carbon dynamics.

FireIncreased reliance on in-forest carbon

storage usually increases carbon emissions when fire does occur (Hurteau et al. 2008).In the West, fire poses the greatest risk of forest carbon emissions, which are very dif-ficult to quantify because of spatial and tem-poral heterogeneity: extreme interannualvariability has stymied efforts to determineeven the existence of a trend in emissions(Liu et al. 2005). Over the long term, assum-ing no trend in fire return intervals, emis-sions from fires are balanced against carbonsequestration by the growing forest. Ontimescales relevant to forest carbon offsets,fires can release truly massive quantities of carbon (averaging 293 Tg of C/year in2002–2006, a period of high fire activity),adding significant uncertainty to projectionsof likely reductions in carbon emissions(Wiedinmyer and Neff 2007). In part be-cause of a century of fire suppression (Ageeand Skinner 2005), combined with climatic




factors (McKenzie et al. 2004, 2008, Littellet al. 2009b), fire is now the dominant dis-turbance agent in most of the West and isimportant to consider in virtually every for-est management strategy. Even in wet forestsalong the Pacific Coast, catastrophic fireshave occurred (e.g., the Tillamook Fire inOregon’s Coast Range).

Intense, stand-replacing fires in heavily stocked stands can be so severe that substan-tial soil carbon stores are lost and soil struc-ture and nutrient capital are destroyed, de-laying regeneration and/or leading to slowerregrowth. Treatments that reduce ladder fu-els and understory vegetation in general arefrequently recommended to reduce fire se-verity and the probability of crown fire(Brown et al. 2004, Agee and Skinner2005). Numerous studies have attempted toassess various combinations of thinning,prescribed fire, and understory and down

wood removal for their capacity to maximizestored carbon and reduce the risk of cata-strophic forest carbon loss (e.g., Lee et al.2002, Li et al. 2007, Boerner et al. 2008,Chiang et al. 2008, Hurteau and North2010). Most of these studies have not ac-counted for the carbon stored in harvested

wood products and the carbon benefits of offsetting fossil fuel–generated energy, letalone the substitution benefits of using

wood instead of building materials whichare more fossil fuel intensive. Counting allremovals as instantaneous emissions, they

generally conclude that fuel treatments in-crease carbon emissions. Counting fire-in-duced mortality in untreated stands as forestecosystem carbon (e.g., Reinhardt and Hol-singer 2010) provides an accurate estimateimmediately after a fire but neglects the sig-nificant differences in photosynthesis andrespiration between live and dead trees overthe next few decades.

Such omissions preclude meaningfulinterpretation of study results because fueltreatments reduce the likelihood of cata-strophic carbon loss via wildfire and, analo-

gous to portfolio diversification, capturesome portion of the forest carbon for prod-ucts and energy (and associated carbon ben-efits) well before a stand reaches full rotationage (or experiences a stand-terminating dis-turbance). Carrying less in-forest volume(and carbon) is thus a desirable objective of such treatments. Finkral and Evans (2008)show how wood use can tip the balance to-

ward net carbon benefits. In a retrospective,model-based analysis of four large westernfires, Hurteau et al. (2008) found that had

the forests been thinned before the fire, car-bon emissions could have been significantly reduced. Stephens et al. (2009) accountedfor storage in harvested wood products anddocumented emissions from prescribed fire,mechanical treatment, and a combination of both, with and without a subsequent fire.Relative to the control, mechanical treat-

ment produced less emissions for almost any plausible assumption of fire probability, andthe other options produced less emissions asthe likelihood of fire increased (they resultedin much greater treatment emissions butmuch less posttreatment wildfire emissions).

In some cases, frequent fuel treatments(thinning combined with prescribed fire)have been known to reduce site quality (Gough et al. 2007). Over the past 10 years,a comprehensive literature on fuel treat-ments (e.g., Graham et al. 2009, Cathcart etal. 2010, Reinhardt et al. 2010) has specifi-

cally addressed the effects of biomass re-moval treatments on fire behavior and theconsequent carbon benefits. Fire and forestmanagers increasingly understand that suchtreatments rarely prevent fire but, when suc-cessful, tend to change fire type from crownto surface and reduce both fire intensity andcarbon emissions. When natural regenera-tion after fire is unlikely to occur, artificialregeneration can increase carbon storageover time.

Insects and DiseaseMortality wrought by insects and dis-

ease can rival that of fire and is a significantfactor in carbon emissions over time in for-ests across the United States. These agentstend not to reduce dead biomass and soilcarbon pools (as does fire); e.g., bark beetleoutbreaks generate considerable quantitiesof deadwood but may cause no change insoil respiration rates (Morehouse et al.2008). Their effect on forest carbon overtime depends in part on whether the agentattacks all tree species in a stand or only afew. As long as unaffected treesare present insignificant numbers, leaf area and growthpotential of the site “transfer” to the surviv-ing trees, at least some of which claim accessto the growing space vacated by trees thatsuccumb. If the dead-tree carbon can be re-covered (e.g., via sanitation harvest for woodproducts or energy), the effect on stand car-bon trajectories would be little differentthan a thinning. However, if the stand is amonoculture or the agent attacks all tree spe-cies, reversals in carbon storage may be sig-nificant, especially if salvage is not an option.

Some exotic invasive pests may prevent pre-infestation tree species from becoming rees-tablished, essentially changing the capacity of a site to store carbon unless alternativespecies with equivalent growth potential areavailable. Given the cost of fighting inva-sions and infestations, managing forests forresilience—such as by encouraging species

diversity and managing stand density—may be the most feasible approach.Insect infestations can heighten the

risks of severe crown fire (and thus the po-tential for large emissions of carbon from thelive-tree pool) not because they create dead-

wood but because the resulting change instand structure tends to promote ladder fuels(Bigler et al. 2005, Lynch et al. 2006). De-creased susceptibility to surface fire afterspruce beetle infestation (Kulakowski et al.2003) is possibly caused by increased forestfloor moisture. The prodigious amounts of

deadwood produced by infestations elevatethe potential for high-severity fire and sub-stantial carbon emissions when fires do oc-cur.

Weather-Related Disturbances Windthrow, hurricanes, and ice storms

can be locally significant. A study of ice dam-age under climate change found thatthinned stands were more susceptible to icedamage but that ice damage became lesslikely under a changed climate (McCarthy etal. 2006). A single Katrina-sized hurricane

has the potential to convert the live-treeequivalent of 10% of US annual carbon se-questration into deadwood, much of which

would be inaccessible and unrecoverable.Longer-term carbon losses result from thedelay in reestablishing full leaf area in hurri-cane-damaged stands (McNulty 2002).

Whether and how such disturbances mightbe managed to reduce carbon emissions isunknown.

Land-Use ChangeIn contrast with tropical forests, where

land-use change is the leading driver of change in carbon stores and sequestrationcapacity, the forested area in the UnitedStates is essentially stable, with recentchanges being well within the margin of er-ror(USDA 2009). Smith et al. (2009) reportFIA estimates of 337,000 ha added to for-ested area each year between 1997 and2007,on a base of 302 million ha. Statistics com-piled by US EPA (2010, Chapter 7) fromFIA, USDA’s Natural Resources Inventory,and the Multi-Resolution Land Cover Con-




sortium suggest substantial, bidirectionalflux in area between grass and cropland andforest, with more area entering than leavingforest. Moreover, a relatively small share(35%) of the area reported to have left forestends up in agricultural use, whereas 65%goes to settlements. Thus, the FIA-reportednet annual increase in forestland area likely

underestimates the carbon storage gainsbecause many of the forests converted tosettlements retain all or most of their forestbiomass. For example, in the western andnorthern states, the growth in the area of the

wildland–urban intermix (where homes arescattered within a matrix of wildland vegeta-tion) dwarfs that of the wildland–urban in-terface (where areas of high housing density abut areas of undeveloped wildland vegeta-tion; Hammer et al. 2007). Even urban for-ests can retain as much as 30–50% of thestanding forest carbon storage of their ante-

cedent wildland forest and may grow fasterbecause of the wider tree spacing, better con-trol of competing vegetation in landscapedyards, and irrigation and fertilization by homeowners. Urban forests cannot dupli-cate all the functions of theirwildland coun-terparts. The mere presence of humans re-duces habitat quality for many species, butsuch forests can accumulate substantialquantities of carbon. However, eventualcapture of that carbon in harvested woodproducts or as bioenergy (which would en-able urban forests to sequester yet more car-

bon via tree growth) is a nascent opportunity at best. Kline et al. (2004) found reducedincidence of forest management activity, in-cluding thinning and other harvest activity,in forests near settlements. Some micromillsalready glean timber supplies from urbantree removal (e.g., Urban Hardwood Recov-ery 2010), and wood removed in urban set-tings has been used for bioenergy produc-tion and district heating in St. Paul,Minnesota, but it is doubtful that urbantrees’ carbon benefits (of in situ storage,long-term product storage, and substitu-

tion) will ever approach what is possible onundeveloped but managed forests.

Forest Carbon AccountingMinimizing net emissions to the atmo-

sphere requires paying attention to sourcesand sinks both within the forest (net inven-tory growth and mortality) and in the con-sumer sector, where wood products can sub-stitute for energy- and emissions-intensivematerials such as concrete, steel, aluminum,plastic, heating oil, and coal (see Section 5).

The summary here provides national andregional context on the patterns of themovement of forest carbon from forests andinto wood products and energy.

Across the United States, forests differin how they are managed and how muchcarbon is removed to make products and en-ergy. Table 2-2 presents the area of forest-

land across six major regions. We focus ontimberland, the more productive forest, inthe first four regions (i.e., excluding interior

Alaska and the tropical islands, where tim-berland is scarce) because the data comefrom a common, contemporary database(the assessments for the Resources Planning

Act). This provides a more regionally nu-anced view of US forests and their potentialto generate climate benefits. These timber-lands represent about 60% of all US forestarea and approximately 90% of the nation’s

productive forests (the remainder is gener-ally in parks, wilderness, or other reservedareas typically off-limits to active manage-ment and considered inaccessible). Al-though all forests may be subject to signifi-cant disturbances spawned by climatechange, mitigation via vegetation manage-ment is most likely feasible only on accessi-

ble timberland.Since 1980, domestic production of roundwood has fluctuated around 300 mil-lion m3 of wood products while consump-tion has increased by more than 20% (Fig-ure 2-1). Most of this gap has been filled

with imports from Canada and other coun-tries. Because harvesting in Canada had toincrease to fill this gap, Canadian forest car-bon stocks are lower than they would havebeen otherwise. As a result, counting the in-creased forest carbon sequestration in the

Figure 2-1. Trends in US industrial roundwood, 1965–2005 (million cubic meters). (Source:Howard (2007).)

Table 2-2. Area of US forestland, timberland, reserved forest, and low-productivity forest, by region (million hectares).

RegionTotal

forestland

Timberland Reservedforest

Low-productivity forestTotal Natural Planted

South 87 83 64 18 1 3North 70 66 64 2 2 1Pacific Coast 86 30 26 4 18 38

Rocky Mountains 61 29 28 0 8 24Interior Alaska 46 3 3 0 11 32Tropical Islands 2 NA NA NA NA NA

Source: Smith et al (2009).




United States as new global climate carbonsequestration benefits overstates the globalbenefits.

Figure 2-2 combines forest inventory and forest product data to illustrate the netflux in wood volume on US timberlands in2006. The measurements include changes inboth growing inventory and dead trees in

the forest. Each flux has a very different car-bon trajectory over the next 100 years. Saw-logs can be used to create long-lasting woodproducts but account for only about one-half of the wood products used by consum-

ers. The conversion of harvested volumeinto consumer products is determined at themills as they respond to market price anddemand. About one-third of harvested vol-ume goes into lumber products, with the re-mainder going into structural compositelumber, oriented strandboard, structuraland nonstructural panels, paper products,

and fuelwood (Smith et al. 2009). Tradi-tional forest inventory statistics focus on thelive-tree inventory and apply no value to log-ging residues and mortality left in the forest.From a GHG perspective, both natural mor-

tality and logging residues will add to respi-ration-based carbon emissions even if they appear to be “storage” (in deadwood) in theyear that a tree dies. At a smaller scale, near

wood energy facilities, more of the net car-bon flux commonly goes to fuelwood andother energy uses, and less of the carbon isleft in the forest as logging residues or new

mortality. Although the proportions vary across regions, nationally, a third of the totalflux is taken out as products, a third adds togrowing trees, and third goes into dead anddown wood that will decompose over time.The annual flux from live trees into mortal-ity from natural causes or logging is signifi-cant. In terms of new carbon storage, thedeadwood is a “leaky bucket” because de-composition rates and eventual CO2 releaseare high. Harmon et al. (2001) estimateddecomposition rates for deadwood of 3%/year for coniferous forests and 8%/year for

deciduous forests, based on a review of morethan 20 published and unpublished studiesfrom temperate forests.

Table 2-3 summarizes the total forestand forest product carbon flux by region af-ter estimating the portion of harvested vol-ume of sawlogs and pulpwood used as en-ergy in mills and counting this as energy.

Wood used for energy in the industrial sec-tor accounts for 67% of the total energy

wood category; residential (21%), electricity generation (8%), and commercial uses (3%)made up the rest (US EPA 2010).

Carbon fluxes from US forests vary by region and ownership. Forests in the Southare more intensively managed and have thelowest level of emissions related to naturalmortality, and more of their gross growth isconverted into products and energy feed-stocks. Along the North and Pacific Coasts,the proportions of forest biomass going intoproducts and energy, new growing inven-tory, and mortality is approximately equal.Forests in the Rocky Mountains have a largeratio of new inventory to harvested prod-ucts, because there is little harvest activity in

that region, but also have high flux into nat-ural mortality. Recognizing the regionalvariations in where forest carbon accumu-lates is the key to interpreting national andsector-specific accounting.

Figure 2-2. Annual flux on timberlands in 2006, by region (million cubic meters of woody biomass). (Source: Smith et al. (2009).)

Table 2-3. Total estimated annual biomass flux into products, new inventory, andmortality as a percentage of gross annual growth on US timberlands.

Out-of-mills flux andin-forest flux South North

PacificCoast

Rocky Mountains

TotalUnited States

Final products 30% 15% 24% 12% 23%Energy 23 17 11 8 18

New growing inventory 19 36 35 36 28Logging residues 13 13 10 4 11Natural mortality 15 19 21 40 19

Source: Calculated from Smith et al. (2009).




Climate–Forest Interactions

Because forests cover approximately 30% of the Earth’s land surface andstore about 45% of terrestrial car-

bon (Sabine et al. 2004), forests and globalclimate are closely linked. Recent empiricalresults (Baldocchi 2008) and climate modelsthat now link the biosphere and atmosphere(Bonan 2008) indicate that the interactionsbetween forests and the atmosphere arehighly complex. Climatic changes can affectexisting forests, for example, though inci-

dence of drought, fire, and reproductive cy-cles of forest pests. Conversely, forests canaffect climate in ways other than carbonstorage. An overview of the three major for-est biomes (tropical, temperate, and boreal)and the three major processes that connectforests with the climate (carbon, energy, and

water fluxes) helps puts US forests in a globalcontext.

Forest Biomes andForest–Atmosphere Fluxes

The three major forest biomes have very

different biophysical dynamics with signifi-cant consequences for the atmosphere (Ta-ble 3-1). The United States has all threetypes: 3.03 million km2 of temperate forests,0.46 million km2 of boreal forests, and 0.02million km2 of tropical forests (Smith et al.2009). Total carbon storage is similar foreach biome, even though photosynthesis ishighest in the tropics and declines towardthe poles. Only a fraction of the carboncaptured by photosynthesis is added tocarbon storage. A global review of net eco-system carbon exchange concluded that“in general, 77 gC m2 year1 of carbon islost by ecosystem respiration for every 100gC m2 year1 gained by gross photosyn-thesis when an ecosystem has not experi-enced recent and significant disturbance”(Baldocchi 2008). A synthesis of 10 car-bon flux studies (Misson et al. 2007) con-cluded that forest floor and soil respirationmade up around one-half of the total siterespiration. The increase in forest floor andsoil respiration is proportional to how much

residue is left on site to decompose (Amiro2006a). Although the carbon contained inlogging residues and dead trees is not con-sidered as part of the growing stock in for-ests, the deadwood has a significant effect onforest respiration and the net carbon flux atthe forest level.

Carbon flux dynamics differ signifi-cantly among the three forest biomes. Forinstance, because most solar energy enter-ing the atmosphere is absorbed by theland and then transferred to the atmo-sphere (McGuire and Chapin 2006), therole of forests in energy fluxes has consider-able relevance. A significant energy flux isthe drop in the albedo (and the reflection of solar energy back through the atmosphere)

when dark-colored trees expand at the ex-pense of snow-covered areas (Bonan 2008,

Jackson et al. 2008, Anderson et al. 2011). A lower albedo decreases the fraction of solarenergy that is immediately reflected. The ex-pansion of boreal forests into areas that arecurrently tundra has been noted in many northern latitudes. The energy feedbacks re-lated to decreased albedo from the naturalmovement of forests into tundra regions canhave local as well as global impacts (Eu-skirchen et al. 2010).

Links between water and carbon fluxare seen most strongly in the tropics. Themost significant water flux linkage betweenforests and the atmosphere is the evaporativecooling from tropical forest canopies, whichhas a positive relationship with cloud for-mation and rainfall patterns (Fung et al.2005). Other research has pointed to a

tradeoff between increased carbon storageand reductions in streamflow from affores-tation in semiarid locations (Jackson et al.2005). In boreal forest regions, warming hasalso been associated with more fresh-waterrunoff into the Arctic Ocean and more areaof wetlands and water bodies that can be asignificant source of methane (Chapin etal. 2000). Some researchers have esti-mated that the climate implications of thebiogeophysical effects related to energy and

water fluxes are of a similar order of magni-tude as aboveground carbon sequestration(Arneth et al. 2010).

Climate-Related Characteristicsof Forest Biomes

New data on changes in tropical forestcover have lowered the estimates of netgreenhouse gas emissions from tropical de-forestation and suggest an emphasis on de-forestation where carbon-rich peat soils aredisturbed (van der Werf et al. 2009,Friedlingstein et al. 2010). Nevertheless, a

review of numerous studies shows that whenall feedbacks are considered, tropical forestsare generally seen as the most effective for-ests for providing climate benefits per unit of area or biomass (Jackson et al. 2008).

Although temperate forests cover theleast area of the three biomes, they are thesource of most of the sustainably produced

wood products. Temperate forests continueto increase as carbon sinks (Friedlingstein etal. 2010) even though large quantities of

wood are removed annually. The current

Table 3-1. Area, storage, and gross photosynthesis of global forest biomes.

BiomeForest area

(million km2)Total carbon

storage (kg C/m2)

Gross primary productivity

(photosynthesis;kg C/m2 per yr)

Tropical forests 17.5 31.6 2.322Temperate forests 10.4 28.1 0.954Boreal forests 13.7 28.8 0.605

Note: Total carbon storage includes vegetation and soil organic matter.Sources: Grace (2004), Anderson et al. (2011), and Beer et al. (2010).


section 3



rate of carbon accumulation may decline,however, if the average age of the trees in USforests continues to increase (Albani et al.2006). Some researchers believe that man-

agement can enhance forest productivity even under changing climatic conditions.The key, they suggest, is matching seedsources and silvicultural methods to futurerather than historical climatic conditions(Lindner and Karjalainen 2007, Nabuurs etal. 2007).

Boreal forests constitute 77% of Cana-dian forests (Natural Resources Canada2005) and 13% of US forests (Smith et al.2009). These forests have already experi-enced significant changes due to warming

climates (Randerson 2006, Kurz et al.2008b, Chapin et al. 2010). Outside the in-tensively managed boreal forests in Scandi-navia, the natural forests in most other bo-

real regions may experience changes that arestill only poorly understood (Amiro et al.2006b, Euskirchen et al. 2009, Chapin et al.2010). Such forests are believed to be lessamenable to cost-effective management in-terventions than temperate forests.

Figure 3-1 highlights the relative mag-nitudes of the three major fluxes (carbon,

water, and energy) for the three major forestbiomes. Focusing on only one or two of these fluxes as guidance for forest climatepolicy may give a biased perspective.

Atmospheric models and forest coverand forest inventory models give very dif-ferent estimates of the carbon, water, andenergy balances of forests (Houghton 2003)

and, therefore, policy inferences drawn fromany single model type may be highly mis-leading. Our understanding of forest dy-namics continues to improve with the devel-opment of more accurate models that couplethe carbon in atmosphere with the carbon invegetation (Bonan 2008, Tjoelker et al.2008, Beer et al. 2010, Yuan et al. 2010),make use of better field-based measurements(Baldocchi 2008), and more effectively link process models and experimental field data(Vargas et al. 2010). Better understanding

Figure 3-1. Forest biomes’ atmospheric interactions and geographic distribution. (Source: Bonan (2008).)




of the influence of nitrogen depositions ongrowth and soil respiration in temperateforests (Magnani et al. 2007) and global ni-trogen fluxes (Thornton et al. 2009) is alsoclarifying the relevant feedbacks.

Climate Induces Disturbancesand Mortality

Climate change will bring disturbancesthat affect tree mortality and forest regen-eration. Drought and species range shiftsare mentioned as critical processes associated

with climate change, but in western North America two processes dominate the discus-sion: wildfire and bark beetle outbreaks.

Wildfire is the dominant natural dis-turbance regime in western forests (Agee1993). Changes in wildfire behavior, extent,frequency, and impact in the past 10 yearsare notable (Calkin et al. 2005) and highly correlated with changing temperature pat-terns and drought (McKenzie et al. 2004,Gedalof et al. 2005, Westerling et al. 2006,Littell et al. 2009b). Although fuel buildup

from fire suppression plays a role in increas-ing fire extent and intensity, Littell et al.(2009b) found that the predictors for largefire years are all related to climate. Research-ers predict at least a doubling of the areaburned annually for western forests (Mc-Kenzie et al. 2004, Gedalof et al. 2005,

Westerling et al. 2006, Littell et al. 2009a)

under moderate climate change scenarios.Massive and ongoing mountain pinebeetle (Dendroctonus ponderosae ; MPB) out-breaks have affected the entire range of sus-ceptible pine in the West from New Mexicoto Alaska, and outbreaks of spruce bark beetles (Dendroctonus rufipennis ) have beensignificant in northern British Columbiaand Alaska. Bark beetle outbreaks are a nat-ural part of the western forest ecosystem, buttheir severity and extent have dramatically increased in the past 10 years as a result of climate change (Logan and Powell 2001,

Carroll et al. 2004, Logan et al. 2003, Gib-son 2006, Oneil 2006). In more northerly regions, MPB outbreaks have been corre-lated with warmer winters (Carroll et al.

2004), whereas outbreaks to the South havebeen correlated with hotter, drier summers(Oneil 2006). In southern Alaska, sprucebark beetle outbreaks have been substantial(Berg et al. 2006), causing 90% or highermortality in mature forest stands. Theseoutbreaks are associated with warm sum-mers that permit bark beetles to change

from a 2-year to a 1-year life cycle. For the western United States, summer tempera-ture extremes and/or extended droughtsare predicted under regional climatechange scenarios. Both conditions in-crease tree mortality, either directly throughdie-off (Adams et al. 2009, Breshears et al.2009) or indirectly by increasing stress com-plexes (McKenzie et al. 2008) that collec-tively cause large-scale mortality. The mostlikely scenarios involve greater water deficitsacross drier areas of the West, leading tospecies die-offs (Littell et al. 2009a). These

effects are not limited to western North America: Allen et al. (2010) found that cli-mate change–related mortality driven by

water stress affects forests globally.





The supply of biomass as feedstock for energy production depends not

just on supply and demand but alsoon the physical amounts from differentsources; delivered costs; and national, re-gional, state, and local laws, regulations, andpolicies. Regional variations influence theUnited States’ potential biomass supply andultimately the placement of bioenergy facil-ities. Whether biomass is removed and usedfor energy affects ecological systems and in-

fluences long-term climate change mitiga-tion measures.

Availability of BiomassBiomass feedstocks for bioenergy and

biofuel include forest and agricultural re-sources, residuals from forest product milloperations, and municipal solid and urban

waste wood (Perlack et al. 2005). Althougheach source is important, this article focuseson forest resources—residues from timberharvest, hazardous fuel reduction, foresthealth restoration projects, and energy wood

plantations—based on forest growth, re-movals, and mortality (Figure 4-1).

The “Billion Ton Report” projected thepotential amount of biomass to be as muchas 1.2 billion tons of biomass availability annually in the United States (Perlack et al.2005). It is now recognized, however, thatthe actual amount, given social, political,and market constraints, will be less (Sampleet al. 2010, US DOE 2011).

Five types of biomass have been defined(White 2010):

• Potentially available biomass is all the

woody biomass reported to be available.• Technically available biomass is the

amount of woody biomass that can actually be used, determined as a percentage of po-tentially available biomass and representingthe amount expected to be recoverable usingcurrent or expected technology (e.g., Perlack et al. 2005). Updated estimates of these vol-umes are also provided as available suppliesbased on accessibility and operability foreach US region (Greene et al. 2010).

• Market price biomass is the amount of woody biomass that could be available at agiven market price (e.g., Biomass Researchand Development Initiative [BRDI] 2008,

Walsh et al. 2003).• Supply curve biomass is the amount of

woody biomass available over a range of bio-mass prices (White 2010).

• Performance-based biomass is theamount of woody biomass available via afield verification of a coordinated resourceoffering protocol (CROP). Developed forthe US Forest Service, CROP is a tool for as-sessingbiomasssupply fromland managementagencies, based on “ability to perform” re-moval (versus potential to remove based pri-marily on inventory) (Mater and Gee 2011).

The use of energy fuels has changedslowly over time. Wood served as the mainform of energy for about half of the UnitedStates’ history. Coal surpassed wood in thelate 19th century and was in turn overtakenby petroleum products in the mid-1900s.Natural gas consumption experienced rapidgrowth in the second half of the 20th cen-tury, and coal use also began to expand as theprimary source of electric power generation

(Energy Information Administration 2010).The majority of bioenergy produced from

woody biomass is consumed currently by theindustrial sector—mostly at pulp and papermills that use heat and electricity produced onsite from mill residues (White 2010). But thatis changing. As of January 2011, there were445 (nonpulp and paper mill) operating andannounced wood-using bioenergy projects inthe United States, ranging from wood pelletmills and wood-to-electricity plants to pilot

projects for cellulosic ethanol (Forisk Con-sulting 2010).

Factors that Affect Feedstock Supply

Changes in feedstock supply are con-troversial and a point of contention for com-peting industries (paper and pulp versus bio-energy), environmental groups, privatelandowners, and public land managers. Thecontroversy is amplified by uncertaintiessurrounding the effects of climate change onforests and the best mix of mitigation andadaptation strategies to use across foresttypes and landowner categories. Research

Figure 4-1. US forest growth, removals, and mortality, 1952–2006. (Source: Based onSmith et al. 2009.)


section 4



has begun to analyze the perceived competi-tion conflicts between traditional consum-ing forest products mills and new wood en-ergy plants. For example, Ince et al. (2011,142) modeled US forest sector market andtrade impacts of expansion in domestic

wood energy consumption under hypothet-ical future US wood biomass energy policy

scenarios. Bowyer (2011) also examined pol-icy implications for bioenergy development,as well as the likely impact of global energy trends on biomass demand.

Environmental Consequencesand Constraints

The ecological effects on soils, wildlife,fire regimes, and water quality of using bio-mass for bioenergy depends on the existingcondition of the foreststand and the amountof biomass to be removed over a specific pe-riod. The results depend on such factors as

the timing of removal and the nature of thebiomass (e.g., logging residues or short-rota-tion woody crops; Pan et al. 2008, 2010,Hurteau et al. 2008).

There are concerns that if too many bioenergy and biofuel plants are establishedover time they will not be sustainable. How-ever, sustainable forest management prac-tices are well known and widely practicedand can protect forests’ environmental andecological values. States such as Minnesota,

Wisconsin, and Pennsylvania, are develop-ing woody biomass removal guidelines to

ensure small-scale and sustainable bioenergy plants can meet long-term environmental,ecological, and economic needs. Use of for-estry best management practices and certifi-cation systems such as the American TreeFarm System, Sustainable Forestry Initia-tive, and Forest Stewardship Council is also

widespread.There can be environmental tradeoffs

involved in removing harvesting residuals where the residuals have value in maintain-ing site productivity and biodiversity. Siteresponses to residue removal and retention

depend on site conditions and limiting fac-tors. Scientific evidence from sites acrossNorth America suggests that the productiv-ity of most sites is largely resilient to remov-ing harvesting residuals (Powers et al. 2005).For instance, Westbrook et al. (2007) foundthat even with removal of all harvesting res-idues and all nonmerchantable woody bio-mass between 1- and 4-in. dbh, nutrientlosses from a Georgia pine plantation wereexpected to be replaced by precipitation in 5

years. Overall, documentation of negativeeffects on site productivity due to biomassremoval is rare.

Two recent meta-analyses of the scien-tific literature suggest that effects of biomassharvest on biodiversity can vary by forestharvesting practice and other factors. Stud-ies of forest thinning have generally reported

positive or neutral effects on diversity andabundance of terrestrial vertebrates and in-vertebrates across all taxa, although thinningintensity and the type of thinning may influ-ence the magnitude of response (Verschuylet al. 2011). Studies that document biodi-versity response to harvest of coarse woody debris and/or standing snags report substan-tially and consistently lower diversity andabundance of cavity- and open-nesting birdsand reduced invertebrate biomass in treat-ments with lower amounts of downed coarse

woody debris and/or standing snags (Riffell

et al. 2011). Effects of harvesting coarse andparticularly fine woody debris on other taxado not appear to be great, although therehave been few studies of these practices (Rif-fell et al. 2011). With scientificsupport lack-ing for significant project level impacts, har-vesting guideline provisions should allow managers the flexibility to tailor prescriptionsto site conditions and limitingfactors andpro-mote analysis of the impacts across a scale thatincludes numerous ownerships and projects.

Genetic Improvement and

Woody CropsGenetic tree improvementprogramshave

focused on improving phenotypic characteris-tics, predominantly to increase volume fortimber production. Today, mostly privatecompanies are investing in poplar and willow to increase feedstocks through advanced ge-netics in tree selection. Mass control polli-nated and varietal pine seedlings that exhibitgenetic gains are now available (Dougherty 2007).

Poplar breeders in the United Stateshave focused on increasing adaptability,

growth rates, and pest and stress resistance.Significant increases have been achievedthrough traditional selection and breedingalong with intensified cultural practices. Ef-ficiencies have also been gained in harvestingand handling. Opportunities for manipulat-ing feedstock quality have long been recog-nized but have gone largely unrealized be-cause of uncertainties over which traits tomodify for what process and because of some social resistance to genetic modifica-

tion of trees. Quality changes can affect pro-cess efficiency in numerous ways, but reli-able information concerning the effects issparse (Dinus 2000, BRDI 2008, Sample etal. 2010, White 2010).

Short-rotation woody crops, such asshrub willow, hybrid poplar, southern pine,and eucalyptus, have the potential to increase

biomass feedstocks, but large-scale productionof these crops has yet to occur (Volk et al. inpress). Hybrid poplars grown in the Midwest,South, and Pacific Northwest under intensivesilviculture can provide biomass for energy as

well as sawlogs, veneer logs, and fiber for thepulp and paper industry (Volk et al. in press).Coppice systems are still under development,but yields from commercial plantations rangefrom 9 to 10 oven-dry tonnes(odt)/ha peryearin the Midwest to 18 odt/ha per year in thePacific Northwest (Netzer et al. 2002). Withadditional research, including breeding and

genetic advances, sustainable yields of 16,24, and 36 odt/ha peryearare possible in theMidwest, South, and Pacific Northwest, re-spectively (Volk et al. in press).

Pine and eucalyptus grown in the Southalso have the potential to supply biomass as

well as sawlogs and fiber. Loblolly pine’s widespread cultivation and high growthrates make it a likely candidate for short-rotation culture (Dickmann 2006), but ex-tensive development is required. Eucalyptushas been called an ideal species for biofuelsand bioenergy (Volk et al. in press), and in

the South, it can be produced and deliveredat a cost competitive with grasses and otherhardwoods. Under the right growing condi-tions, it can produce more than 29 odt/ha peryear for either biomass feedstock or ethanol(Gonzalez et al. 2009, 2010, 2011a, 2011b).

EconomicsTraditional forest products such as saw-

timber and pulpwood are more or less com-plementary uses, because pulpwood can bemanaged to become sawtimber. Forest bio-mass, at least for energy generation, cancome from pulpwood-size trees, which areeasily substituted: established markets,silvicultural systems, and harvesting andlogistics supply chains already exist. Al-though traditional pulpwood harvestingcan accommodate small woody biomassand forest residue collection, there is apoint at which production efficiency suf-fers (Westbrook et al. 2007). Price to thelandowner will invariably be a determin-ing factor of end use. The traditional for-est products industry, particularly the pulp




and paper sector, has already seen pricecompetition for pulpwood to be turned intopellets (Greene et al. 2010).

Government Policy The Biomass Research and Develop-

ment Act of 2000 authorized an interagency board (representing USDA, Department of Energy, Department of the Interior, and theEnvironmental Protection Agency) to pro-mote development of biofuels in the UnitedStates. The Board recently issued an eight-point strategic plan focused on this goal.

Agency coordination was recognized asimportant given often conflicting agency initiatives and guidance from Congress. Forinstance, the Energy Policy Act of 2005 dis-allowed the use of federal woody biomassfor the renewable energy credit. In contrast,Section 203 of the Healthy Forests Restora-tion Act of 2003 (PL 108-148, codified at 16

US Code Section 6531) provided authority for the Biomass Commercial UtilizationGrants Program, which emphasizes the useof woody biomass especially from wildfire-affected areas in the wildland–urban in-terface. The Food, Conservation, and En-ergy Act of 2008 (PL 110-234; Farm Bill2008), under Title IX, Section 9011-9013,promotes the use of woody biomass for re-search and development of biofuels, wood-to-energy programs for states and local com-

munities, and includes the Biomass Crop Assistance Program (BCAP).

Differing and often conflicting defini-tions of renewable biomass in current federalenergy policies hinders policy implementa-tion and the development of biomass mar-kets. A universal definition of renewablebiomass that includes renewable, sustainable

forest biomass—and does not confound thisdefinition by attempting to address otherpolicy goals—would promote the develop-ment of sustainable energy and environmen-tal policies on appropriate lands.

A further problem is that policies de-signed to promote the use of forest biomassenergy have focused on development of transportation fuels despite public concernsabout this direction. As Caputo (2009) de-scribes the situation:

… federal incentives have largely focusedon the production of renewable transporta-tion fuels and co-products. Input from

stakeholders indicates that future policiesshould focus on improving forest sustain-ability, increasing research capabilities, andimproving the economics of biomass utili-zation. Additionally, many feel that theproduction of heat and power should begiven similar attention to the production of liquid transportation fuels as an importantuse for woody biomass.

Landowner PreferencesThe availability of biomass feedstocks

will also depend on landowner preferences,

which vary based on the type of owner-ship. Numerous studies have documentedthat for nonindustrial private forest land-owners, harvesting is often a secondary objec-tive (e.g., Butler 2008). Even industrial andthose nonindustrial private forest landownersinterested in harvesting forest biomass are of-ten reluctant to engage in the long-term con-

tracts necessary to participate in forest carbonoffset projects.

Nonindustrial forest landowners whoseek maximum revenue, may plant short-rotation woody crops, such as hybrid popu-lar or willow, in response to the incentivescreated by BCAP. For example, Gan et al.(in press) found that without financial in-centives and technical assistance, fewer than6% of landowners would be willing to thinforest stands for energy production even if itreduced fire hazard, but with governmentcost sharing and technical assistance forgrowing biomass, two-thirds of timberlandlandowners would consider producing bio-mass for bioenergy purposes. The most rea-sonable expectation about biomass produc-tion by private landowners is that they willbe guided by economic reality and sustain-ability. High transaction costs can preventinterested nonindustrial landowners withsmall acreage from participating in biomassprojects.




Wood–Fossil Fuel Substitution Effects

W hen trees are harvested, carbonis removed from the forest. It istempting to conclude that forest

harvesting should be avoided to reduce car-bon emissions and maximize carbon storage.However, careful consideration of carbonflows reveals that conversion of wood to use-ful products can significantly reduce overallsocietal carbon emissions. Major consider-ations are the low carbon emissions associ-ated with wood products manufacture, car-bon storage in long-lasting wood products,avoided emissions that result when wood isused in place of energy-intensive materialsand products, and the efficient use of woodresidues for energy.

To arrive at a cogent picture of the for-est sector’s overall effects on atmosphericcarbon, we need to understand the materialand energy flows as inputs and outputs

within well-defined system boundaries. Analysis using attributional life-cycle assess-ment (LCA) methods that measure inputsand outputs within a system boundary ex-plains the interactions at that scale. We thenneed to integrate these effects across systemboundaries to see how substitution of har-vested wood products for fossil fuels and fos-sil fuel–intensive products can offset theflow of carbon dioxide from fossil fuel re-serves to the atmosphere.

Product Flows of Harvested Wood

Carbon makes up a considerable pro-portion of wood volume, amounting toabout 50% of the moisture-free weight.

Within forests, significant quantities of car-bon are stored (or sequestered) in the twigs,branches, boles, and roots of trees. Addi-tional carbon is stored in forest litter andforest soils. In 2005–2009, some 24–25 bil-lion tonnes of carbon was stored in standingtrees, forest litter, and other woody debris inUS forests, and another 20–21 billiontonnes was in forest soils and roots (US En-vironmental Protection Agency [EPA]2010). Carbon is also found within har-vested wood products. The carbon in wood

products in use and in landfills during2005–2007 was estimated at 2.3–2.4 billiontonnes—equivalent to 5.2–5.7% of forestcarbon pools.

Carbon was sequestered in US forestsduring 2005–2007 at a rate of 192 milliontonnes/year. The annual rate of carbon ac-cumulation within wood products in useand in landfills was estimated at about28–29 million tonnes—14.8% of the rate of sequestration within forests and 22–23% of the annual additions to nonsoil forest car-bon stocks (US EPA 2010). Rates of accu-mulation in harvested wood products werenotably lower in 2008–2010 because of thesharp decrease in overall economic activity and home construction.

Much of the carbon in wood productsresides in the nation’s housing, as well as incommercial, industrial, public, and otherstructures. Wood-framed buildings make upabout 90% of homes in the United States,and in all homes, whether wood framed ornot, wood furniture, cabinets, flooring, andtrim are dominant.

Emissions from Wood ProductsManufacture

The carbon dioxide that is removedfrom the air as a tree grows is combined with

water and converted to simple sugars withinthe leaves, conveyed downward throughthe branches and bole in the form of sap,and then converted into complex polymersthat combine to form an intricately struc-tured polymeric material that has a higherstrength-to-weight ratio than structural

steel. That this natural process uses freely available solar energy largely explains why the energy embodied in wood products islower than for any other construction mate-rial (Glover et al. 2002, Perez-Garcia et al.2005, Gustavsson and Sathre 2006, Lippkeet al. 2010). “Embodied energy” refers to thequantity of energy required by all the activ-ities associated with a production process,including gathering, transporting, and pri-mary processing of raw materials. Lumber,in particular, requires little energy to pro-

duce, because only minimal processing isneeded to convert the naturally produced

wood to desired shapes (Milota et al. 2005,Puettmann et al. 2010). Wood products,such as furniture, require more steps in pro-cessing and therefore more energy (e.g., Pu-ettmann and Wilson 2005, Wilson 2010)but still significantly less energy than non-

wood materials (Lippke et al. 2010).Not only does production of lumber

and wood products require relatively littleadditional energy beyond the solar energy used in tree growth and wood production,but very little of that additional energy comes from fossil fuels. In the United Statesin 2008, renewable energy produced fromtree bark, sawdust, manufacturing and har-vest residuals, and byproducts of pulping inpapermaking processes provided 65% of theenergy used in manufacturing paper prod-ucts and more than 73% of the energy usedin manufacturing wood products (AmericanForest and Paper Association 2010). In thesame year, the wood and paper industries of the United States accounted for 94% of themanufacturing sector’s derived renewablefuel use, and they generated 37% of the totalenergy produced by cogeneration-capablesystems within all manufacturing sectors.

Because wood is produced using solarenergy, the manufacture of lumber andother wood products requires little addi-tional energy. Moreover, only one-quarterto one-third of the energy consumed is fossilenergy. The result is that total emissionsfrom wood products manufacture, includ-ingemissions of carbon dioxide, are typically

lower than for potential wood substitutes ona weight or mass basis (Table 5-1). For ex-ample, carbon emissions for the manufac-ture of a tonne of lumber are markedly lessthan for a tonne of steel, plastic, or alumi-num.

Product SubstitutionFor every use of wood there are substi-

tutes: wood studs can be replaced by steelstuds, wood joists by steel I-joists, wood

walls by concrete walls, wood floors by con-


section 5



crete slab floors, and biofuel by fossil fuel.Every product use has its own life-cycle car-bon footprint (Perez-Garcia et al. 2005,Lippke and Edmonds 2009). Using life-cycle inventory (LCIs), which include thecarbon stored in wood as well as the process-ing emissions to harvest, transport, andmake the product, one can compare the netcarbon consequences of substituting oneproduct for another.

Life-cycle analyses have shown marked

differences in energy requirements and car-bon emissions associated with differentbuilding materials and the structures madefrom them (Glover et al. 2002, Gustavssonand Sathre 2006, 2011, Perez-Garcia et al.2005, Buchanan 2007, Gerilla et al. 2007,Salazar and Meil 2009, Lippke et al. 2010).Comparisons of structures having compara-ble heating and cooling requirements show that wood products and structures requirethe least energy to produce and conse-quently have the lowest greenhouse gas(GHG) emissions profile. Thus, substitut-

ing wood for more energy-intensive, non-renewable materials produces a substantialnet reduction in carbon emissions, called thesubstitution effect. In addition, wood storescarbon for the useful life of the product, en-hancing the benefits of wood relative toother building materials.

The comparisons in Table 5-1 are pertonne of product. More appropriate com-parisons, which reflect the functions thatproducts perform, have been made between

wood and nonwood assemblies for walls,

floors, and sheathing. Wood fares well insuch comparisons because of its highstrength relative to weight, its low embodiedenergy, and carbon stored in the product it-self. Lippke and Edmonds (2009) show therelative process emissions and stored carbonper functional unit for wood and nonwoodproducts (Figure 5-1). In Figure 5-1 the ver-tical zero line is where process emissionsequal carbon stored. A component (black bars) or assembly (green bars) to the right of the zero line produces more emissions than

it stores, and one to the left of the line storesmore carbon than it takes to produce (i.e., isa carbon sink) as long as the product remainsin use. Longer useful life, recycling, and re-use extend the period of this offset. Similarcharts for wall assemblies (not shown) show the same patterns, with wood products stor-ing more carbon than is emitted during theirharvest and manufacturing.

Another study compared wood andsteel houses built to Minneapolis code stan-dards and wood and concrete houses built to

Atlanta code standards (Meil et al. 2010).

The two designs shared many of the samestructural assemblies (i.e., foundation foot-ings and basement block wall, supportbeams and jack posts, and roof), and there-fore the differences in the environmental ef-fects can be traced to their respective walland floor assemblies. For the Minneapolishouse, the steel design was found to embody 66% more energy (measured in megajoulesper square foot of assembly) and generated49% more global warming potential thanthe wood design. Focusing on only the

assembly groups affected by changes inmaterial use (i.e., walls, floors, and roofs)revealed more pronounced differences.For instance, compared with the wood de-sign, the steel design’s floors and roof werefound to embody 245% more energy andproduce a corresponding increase in global

warming potential. In the Atlanta compari-son, increases in embodied energy andglobal warming potential were determinedto be 41% and 65% higher for concreteconstruction than for wood houses, re-

spectively. Comparisons of building com-ponents made to specified codes using wood, steel, and concrete options show that wood designs produce not only the lowestglobal warming potential, but also providethe lowest emissions to air and water. (See,for example, Table 3-1, Malmsheimer et al.2008). Only in the solid waste category does

wood fare worse than steel, a result thatarises because steel is precut and wood is cuton site during construction (Lippke and Ed-monds 2006). Further examination of fossilfuel consumption and associated carbon

emissions, linked to construction of entirestructures, reveals that differences in global warming potential for the various designsare in nearly direct proportion to the differ-ences in fossil fuel consumption (Tables 5-2and 5-3).

An analysis of carbon storage andavoided emissions for wood versus steelconstruction in a large wood structure alsoillustrates the carbon-related advantages of

wood (Table 5-4). The completed structure,in Anaheim, California, comprises five sto-

Figure 5-1. Process emissions less carbon stored in floor structure components andassemblies. Notes: EWP engineered wood product, OSB oriented-strand board,Dim dimension lumber. (Source: Adapted from Lippke and Edmonds (2009).)

Table 5-1. Net carbon emissions inmanufacture per tonnes.

MaterialNet emissions

(tCe)

Framing lumber 0.033Concrete 0.034Concrete block 0.038Medium-density fiberboard (virgin fiber) 0.088

Brick 0.088Glass 0.154Recycled steel (100% from scrap) 0.220Cement (Portland, masonry) 0.265Recycled aluminum (100% recycled

content)0.309

Steel (virgin) 0.694Molded plastic 2.502

Aluminum (virgin) 4.529

Notes: Values are based on life-cycle assessment and includegathering and processing of raw materials, primary and second-ary processing, and transportation; a 10% increase in energy consumption is assumed for the production of concrete block.tC, tonnes of carbon equivalent.Sources: Based on US EPA (2006, Exhibit 2–3); data for con-crete is from Flower and Sanjayan (2007).




ries of wood frame construction over a con-crete parking garage and first level and in-cludes 251 luxury apartment units and13,000 ft2 (1,208 m2) of retail space. Thestructure incorporates 5,201 m3 of wood,

with resulting long-term storage of 3,970tonnes of equivalent carbon (CO

2e), with

twice that level of avoided GHG emissionsresulting from selection of wood rather thantraditional steel construction.

The effect of substitution on a per hect-are basis is illustrated in Figure 5-2, whichcompares substitution of wood for concrete

in construction and its carbon implicationsover a timeline of two rotations of a forestinitially planted on bare land. Carbon storedin products (designated as “products car-bon”) is significant relative to the carbonstored in the live- and dead-tree biomass(designated as “forest carbon”). Further-more, well before the end of two rotations,overall sequestration of carbon (forest car-bon plus products carbon plus substitutioncarbon) far exceeds carbon sequestration inan unmanaged forest (i.e., a forest managed

without timberextraction, shown as the dot-

ted line designated as “no-harvest carbon”).The figure includes the carbon emissions as-sociated with generation of bioenergy fromshort-lived product pools, taking into ac-count that the efficiency of the conversion of

wood to energy is lower than forgas-or coal-fired boilers. A net benefit in this case ap-pears about 30 years after stand establish-ment, with benefits increasing over time.The managed and no-harvest forest scenar-ios both use growth trends in Douglas-fir, aspecies that is known to maintain growth

well into advanced years (Curtis and Mar-shall 1993). Other species with growth ratesthat peak sooner show even larger differ-ences in the relative carbon sequestration be-tween managed and unmanaged forests.These trajectories show the relative carbonconsequences assuming a change in manage-ment intent at the point when the first thin-ning was implemented. In practice, a no-harvest forest scenario would more often

than not have a lower forest growth trajec-tory because the investment in regeneratingthe forest from bare land would not haveoccurred without the expectation of a returnon the investment in later years.

As the examples illustrate, substitutionvalues vary with the wood product or assem-bly in question and its alternative. Sathreand O’Connor (2010) conducted a meta-analysis to estimate average substitution

rates for common building products. They arrived at a value of 2.1 tonnes of carbondisplaced per tonne of wood carbon used.This is a more general characterization of substitution across all wood uses than thespecific examples shown in Figures 5-1 and5-2 and Tables 5-3 and 5-4.

End-of-Life ConsiderationsBased on census data, the half-life of the

US housing stock is approximately 80 years

(Table 5-5; Winistorfer et al. 2005). First-order decay functions have often been usedto estimate losses of wood in use over time(e.g., Intergovernment Panel on ClimateChange [IPCC] 2007b), but they greatly overestimate early losses because they as-sume the highest decay (loss) rate when thereis the most stock, with a declining rate there-after. Because houses are rarely demolishedin their first 10 years, first-order decay func-

Figure 5-2. Carbon (tonnes per hectare) stored in forests (designated as “forest carbon”) inproducts (designated as “products carbon”), and retained in the lithosphere because ofsubstitution for concrete and fossil fuel energy (designated as “substitution carbon”),compared with carbon stored in an unmanaged forest (dotted line designated as “no-harvest carbon”), per hectare of forest. Notes: Douglas-fir forest, 80-year rotation, withintermediate thinnings at years 30 and 60; portion of wood harvested at rotation age usedfor long-lived construction products; dotted line indicates unmanaged forest. (Sources:Perez-Garcia et al. (2005), Wilson (2006).)

Table 5-2. Consumption of fossil fuelsassociated with exterior wall designs in

warm climate home.

Fossil fuel energy (MJ/ft2)

Lumber-framed wall

Concrete wall

Structural componentsa 6.27 75.89

Insulationb

8.51 8.51Claddingc 22.31 8.09

Totald 37.09 92.49

a Includes studs and plywood sheathing for the lumber-framed wall design and concrete blocks and studs (used in a furred-out wood stud wall) for the concrete wall design.b Includes fiberglass and six-mil polyethylene vapor barrier forboth designs.c Includes interior and exterior wall coverings. Exterior wallcoverings are vinyl (lumber-framed wall design) and stucco(concrete wall design). Interior wall coverings gypsum for bothdesigns.d Includes subtotals from structural, insulation, and claddingcategories.Source: Edmonds and Lippke (2004).

Table 5-3. Consumption of fossil fuelsassociated with floor designs (excludinginsulation).

Fossil fuel energy (MJ/ft2)

Dimension wood joist floor 9.93Concrete slab floor 24.75Steel joist floor 48.32

Source: Edmonds and Lippke (2004).

Table 5-4. Carbon storage and avoidedemissions from wood versus steelcommercial/residential complex.

Carbon sequestered and stored (CO2e) 3,970 tonnes Avoided greenhouse gases (CO2e) 8,440 tonnes

Total potential carbon benefit (CO2e) 12,410 tonnes

Source: This case study is based on use of the Forintek WoodCarbon Calculator for Buildings based on research by Sathre

and O’Connor (2010) and is described by WoodWorks(2011).




tions fail to capture the carbon storage po-tential of long-lived materials. An alternative

approach has been proposed by Marland etal. (2010), who applied gamma functions todistributed product pools so that short-livedproducts, such as paper, decay quickly butlong-lived products, such as oriented strand-board and lumber, decay more slowly. Re-finement of the parameters used by Marlandet al. (2010) to reflect actual decay rates on aregional, national, or wood basket basis isneeded, but the functional form improveson previous estimates of decay rates.

The collection efficiencies of landfillinghave carbon storage implications (Skog

2008). Of the wood products that entersolid waste disposal sites, more than three-quarters of the carbon in solid wood andalmost one-half of the carbon in paper isnever released to the atmosphere (Table5-6). The carbon that is released during de-cay takes many years to reach the atmo-sphere. For example, the 23% of the solid

wood that does decay has a half-life of 29years. Skog (2008) found that when paper islandfilled, the nonlignin component (56%)decays, leaving the lignin component (44%)as a long-term store in the landfill (Table

5-6). This nondegradable fraction varies by grade, from approximately 10% forbleached chemical pulp fibers to 85% formechanical pulp fibers (US EPA 2006).

Methane emissions from wood degra-dation in a landfill can offset any benefits of carbon stored there. Heath et al. (2010)found that with current landfill design andoperating practices, US landfills appear to bea net long-term sink for carbon in woodproducts but a long-term source of GHGemissions from paper products, particularly

paper that contains a large fraction of carbonthat is degradable under anaerobic condi-tions. This suggests that incentives should behigh to reuse paper and wood, recycle it, orburn it to recover its heating value, and thatlandfills should be managed to recapture theenergy value of methane emissions. Collec-tion systems are evolving rapidly. For exam-ple, US EPA (2007b) reported that the re-covery or oxidization of methane increased

from 20 to 50% between 1990 and 2006.Methane capture from landfills is one of themost cost-effective investments for atmo-spheric GHG reduction because of the dualbenefit stream of reducing methane release(methane has 25 times the global warmingpotential of CO2; Forster et al. 2007) andconverting the methane into usable energy that offsets fossil fuel emissions.

Wood Energy The US Department of Energy (DOE)

estimatesthatin2009,about8%(7.75quad-

rillion Btu) of the energy consumed in theUnited States came from renewable sources(excluding ethanol; US DOE 2010). For2004 –2008, about 30% (2.1 quadrillionBtu) of this renewable energy was suppliedfrom woody biomass, equivalent to about2% of annual energy consumption from allsources and the largest source of renewableenergy after hydropower (US DOE 2009).Renewable energy consumption (excludingethanol) is projected to increase to 8.4 quad-rillion Btu by 2015 and to 9.7 quadrillionBtu by 2030. Assuming the current share of

renewable energy coming from woody bio-mass remains static, woody biomass wouldbe the source of about 2.5 quadrillion Btu of energy in 2015 and 2.9 quadrillion Btu of energy in 2030. At present, wood energy consumption requires about 111 millionoven-dry tonnes (odt) of woody materialannually (assuming 17.2 million Btu/odt of

wood). Under DOE’s reference projection,approximately 132 million odt of wood willbe used for energy in 2015 and 152 millionodt will be used in 2030 (White 2010).

Using biomass instead of fossil fuels formeeting energy needs has several advan-tages. Specific benefits depend on the sourceof the wood (and its alternative fate if notused for energy) and the intended use. Ben-efits can include reduction of GHG emis-sions (particularly CO

2) and other air pol-lutants, energy cost savings, local economic

development, reduction in waste sent tolandfills, and the security of a domestic fuelsupply. In comparison with other renewableenergy sources, such as wind and solarpower, biomass is more flexible (e.g., cangenerate both power and heat) and reliable,because it is a nonintermittent energy source

whereas the alternatives rely on the weather.In the United States, the potential role

of forest bioenergy is readily accepted by pri-vate parties in regions where relatively low value pulp is the major output (Galik et al.2009a). It is more controversial in the con-

text of public forests. As in Europe, the pur-suit of aggressive bioenergy targets in theUnited States could affect traditional usersof industrial roundwood, especially pulpproducers in the southeast region of thecountry (Abt et al. 2010), but in other areasof the country it could create opportunitiesfor synergy. Increasing the use of managedforests for biomass could enhance forestresiliency and productivity without usingscarce high-quality agricultural land or irri-gation water.

Heat and Power (Combustionand Gasification)

Of the 9,709 megawatts (MW) of bio-mass electric capacity in the United States in2004, about 5,891 MW (61%) was gener-ated from wood and wood wastes. Another3,319 MW of generating capacity was frommunicipal solid waste and landfill gas, and499 MW of capacity was attributable toother biomass, such as agricultural residues,sludge, and anaerobic digester gas (US EPA 2007a).

Much of the biomass used for energy,especially the biomass burned in pulp mills,is burned in combined heat and power(CHP) systems. CHP is not a single technol-ogy but an integrated energy system that canbe modified depending on the needs of theenergy end user. The hallmark of all well-designed CHP systems is an increase in theefficiency of fuel use. By using waste heatrecovery technology to capture a signifi-cant proportion of heat created as a byprod-uct in electricity generation, CHP typically achieves total system efficiencies of 60– 80%

Table 5-5. Projected half-lives for end usesof wood.

UseHalf-life

(yr)

Single-family home (1920 and before) 78.0Single-family home (1921–1939) 78.8Single-family home (1939–) 85.0a

Multifamily home (as fraction of half-life

for single-family home)

52.3b

Housing alteration and repair (as fractionof half-life for single-family home)

25.7c

All other uses for solidwood products 38.0Paper 2.5

a Based on half-life increase per 20 yr for post-1939 period.b Based on half-life of multifamily home that is 0.61 of single-family home.c Based on half-life of repair and remodel that is 0.30 of single-family home.Source: Based on Skog (2008).

Table 5-6. Fate of material in solid wastedisposal sites.

Fractionpermanently sequestered

Fractionthat decays

Half-lifeof

decayingportion

Solid wood 77% 23% 29.0 yrPaper 44% 56% 14.5 yr

Source: Based on Skog (2008).




for producing electricity and thermal en-ergy. These efficiency gains improve the eco-nomics of using biomass fuels, as well as pro-duce other environmental benefits. Morethan 60% of all biomass-powered electricity generation in the United States is in theform of CHP (US EPA 2007a).

Energy Balance and Benefits ofBiomass Energy

A small amount of fossil fuel is used toproduce bioenergy—approximately 1 U of fossil fuel for every 25–50 U of bioenergy (Borjesson 1996, Boman and Turnbull1997, McLaughlin and Walsh 1998, Mat-thews and Mortimer 2000, Malkki andVirtanen 2003, Matthews and Robertson2005). Biofuels (transportation fuels) typi-cally require more input energy, so the en-ergy balance for producing biofuels is lessfavorable, as well as more variable—approx-imately 1 U of fossil energy for every 4 –5 Uof bioenergy (Gustavsson et al. 1995). Netcarbon emissions from generation of a unitof electricity from bioenergy can be 10–30 times lower than emissions from fossil-based electricity generation, depending onthe systems and fuel types being compared(Boman and Turnbull 1997, Matthews andMortimer 2000, Spath and Mann 2000,Mann and Spath 2001, Matthews and Rob-ertson 2005, Cherubini et al. 2009).

Although energy self-sufficiency is onereason for pursuing the development of

woody biomass-to-energy initiatives (En-ergy Independence and Security Act 2007),there are other reasons to use woody biomassas an energy source. In the West, wildfirerisk is high and increasing, and removingexcess biomass to reduce risks is desirable inmany cases. Reducing fire risk while main-taining other forest values often entails re-moving low-value material while retaininghigher-value trees for other purposes. With-out a viable economic return for woody bio-mass that is removed, the costs are prohibi-tive and the likelihood of action is low.

Wildfire emissions are equal to 5% of total GHG emissions in the continentalUnited States (Wiedinmyer et al. 2006).

Avoiding wildfire emissions by thinning sus-ceptible forests and using the harvested ma-terial as a woody biomass feedstock is a po-tentially valuable side benefit that is oftenignored in the assessment of the carbon con-sequences of bioenergy. Oneil and Lippke(2010) calculated the GHG forcing pertonne of biomass burned during wildfiresusing default emission and consumption

values from Wiedinmyer et al. (2006) tocompare the implications of thinning to re-duce fire risk versus stand-replacing wild-fires. Because open burning generates meth-ane and nitrous oxides, two potent GHGs,burning a tonne of biomass in a wildfire gen-erates more emissions in CO

2e than the car-bon content of the wood burned. Burning

the same wood under controlled conditionsin a boiler reduces non-CO2

emissionsby upto 98% while generating energy. The substi-tution of woody biomass for fossil fuel en-ergy provides a GHG offset because the fos-sil fuel remains underground and the flow of fossil carbon to the atmosphere is reduced.

Thus, harvesting woody biomass to re-duce wildfire risk, damage, and, ultimately,emissions delivers an additional atmo-spheric benefit beyond the substitution of fossil fuel (Mason et al. 2006, Hurteau et al.2008, Stephens et al. 2009, Reinhardt and

Holsinger 2010). That additional benefit isconstrained, however, by the number of treatments and their spatial extent: limitedtreatments may not be sufficient at the land-scape scale (Reinhardt and Holsinger 2010).The effectiveness of the benefit is also con-strained by the ecology of the forests in ques-tion. For example, in a detailed analysis of fire risk reduction treatments for PacificNorthwest coastal western hemlock–Doug-las-fir and western hemlock–sitka spruceforests with 500-year fire return intervals,Mitchell et al. (2009) found that the treat-

ments would be ineffective at reducing car-bon dioxide emissions and that leaving theforests untreated would be a better option.This result is not unexpected in a region

where fire is rare andfire risk reduction treat-ments are highly unlikely.

Energy SubstitutionThe substitution effect noted in con-

junction with production and use of woodproducts rather than metals, plastics, or con-crete also applies to use of wood in produc-tion of energy. Using wood to produce elec-tricity, heat, liquid fuels, or other forms of energy avoids the flow of fossil carbon to theatmosphere, provided that energy offsets theuse of fossil fuels. Although a CO

2 moleculeis a CO

2molecule, regardless of source,

crediting biofuel use as a fossil fuel offsetrecognizes the reduction of the flow of fossilcarbon. Consistent carbon accountingcounts the emissions and takes credit for theoffset value (i.e., the amount of fossil fuelcarbon that was not emitted, net of the fossilfuel used to produce the biomass energy).

Current protocols and policies generally donot allow this credit (see Section 6).

Potential biofuel feedstock that burnsordecays in the woods is a net decrease in thecarbon stock—the equivalent of an emis-sion. The loss of carbon from the forest isalready accounted for in the forest carbonstock change, but care must be taken when

extrapolating the results from a single standto a wider context (Figure 5-3). For a singlestand under sustainable management, theforest carbon cycles around some averagevalue that is contingent on inherent site pro-ductivity, rotation age, and species mix, andthere is a time interval between uptake andrelease of carbon (Figure 5-3a). However, noprocessing facility relies on a single stand toprovide feedstock, so extrapolating the time-dependent dimension of a single stand anal-ysis to the emissions profile of a facility isinappropriate and leads to incorrect conclu-

sions (O’Laughlin 2010). A more correct characterization of theeffectsof harvesting biofuel uses a landscape-level analysis to determine whether the har-vest needed to sustain processing facilities

within an economic haul distance increasesor decreases average carbon stores on theland. If harvesting results in a stable averageof carbon across the total forest throughtime (Figure 5-3b), the forest itself is car-bon-cycle neutral. If forest carbon stocks areunaffected by the choice between forest bio-mass and fossil fuels, the products removed

from the forest provide a carbon benefit tothe atmosphere equal to the avoided emis-sions from fossil fuels less any fossil energy ittook to produce energy from the biomassfeedstock. To meet this condition, it is nec-essary to ensure that harvests and mortality do not exceed net growth across the forestand that soil conditions and carbon seques-tration potential are maintained.

An analysis using publicly available datafrom the US LCI database (National Re-newable Energy Lab 2011) and the EPA TRACI Impact method found that the

global warming potential for a cradle-to-grave analysis was greater for coal than for woody biomass (Figure 5-4; Lippke et al.2011). The comparison in Figure 5-4 is forthe cleanest coal type (bituminous); othercoal types produce more emissions andtherefore produce an even larger differentialbetween the fuel types. Results show that if the uptake of CO

2in the forest is ignored,

disregarding the fundamental difference be-tween renewable and nonrenewable fuels,emissions from using biomass as a feedstock




are 82% of coal-fired emissions per mega- joule of electricity produced. If biomass isconsidered a renewable resource such thatemissions represent prior uptake, burningbiomass to generate electricity produces 4%of the emissions of a coal-fired power plant.

The net biomass bar in Figure 5-4 as-sumes that the biomass was produced in anarea where forest carbon stocksremain stableover the long term. Some assume that har-

vesting causes a reduction in forest carbonstocks, and particularly soil carbon, relativeto a scenario where the biomass is not usedfor energy, creating a carbon debt that mustbe overcome before the forest biomass–based system yields net benefits (e.g.,Schlamadinger et al. 1995, Searchinger et al.2009). Such thinking is based on initia-tion of measurement and comparison at thepoint of harvest.

Whether and how biomass is includedin emissions accounting affects policies aimed

at reducing overall GHG emissions. Ac-counting should (1) accurately characterizeatmospheric consequences of reducing theflow of fossil fuel emissions by using biofuelsand (2) measure the effects on the forestlandbase in terms of growing stock and soil car-bon. The assumptions and boundaries foranalyzing the GHG emissions of bioenergy are critical to the resulting conclusions andmust be clearly understood when studies are

used to justify policies or regulations.

Determination of CarbonNeutrality

Analyses of the benefits of forest-basedproducts and systems should incorporatespatial and temporal boundaries appropriatefor forestry and forest products. Forest man-agement practices may be applied at the in-dividual stand or project level, but woodsupply systems involve large areas managed

for long periods of time. Using a single standor project to model a wood supply systemcan severely distort systemwide outcomes(Lucier 2010).

At the scale of a wood supply area, sus-tained-yield forestry and sustainable man-agement systems keep growth and removalsin balance, and the loss of carbon from har-

vests in any given year is equal to gains incarbon elsewhere in the area. The net changein carbon stocks in all years is then zero; i.e.,net removals of carbon from the atmosphereequal the amount of carbon in wood re-moved from the forest, and the system iscarbon neutral. The variation in definitionsof carbon neutral (Table 5-7), however, sug-gests the need for elaboration when usingthe term.

Even if forestland is maintained as for-estland, deviations from carbon-cycle neu-trality can occur in both directions. Climate

change, more frequent insect and diseaseoutbreaks, exotic and/or invasive distur-bance agents, failure to regenerate, and se-vere wildfires that reduce soil productivity can affect long-term carbon storage poten-tial. Ensuring continued carbon benefitsfrom the forest sector requires maintaininglong-term site productivity. Given adequatenitrogen supplies to maintain carbon storesin dynamic equilibrium, average forest car-bon stores can increase concurrent withecological protections, such as riparian buf-fers and habitat requirements. Incorporating

most ecological sustainability criteria intothis forest management framework doesnot affect a forest’s carbon-cycle neutral-ity, but overall carbon benefits will be un-derestimated if harvested wood productsand their substitution effects are not takeninto account. LCI and LCA occur withindefined system boundaries. Substitution oc-curs when one product is replaced by an-other product and the comparison is be-tween the LCIs within each boundary. Anexample would be the comparison betweensteel joists and engineered I-joists that are

functionally equivalent. There are alsodisplacement factors when biofuel is usedinstead of fossil fuel for manufacturing thatoccurs inside the system boundary. The dis-placement occurs inside the system bound-ary of a particular product and forms part of its LCI.

Figure 5-5 integrates harvested woodproducts and substitution benefits for theforest management regime in Figure 5-3b toprovide the landscape context. It is based oncurrent patterns of wood use from harvested

Figure 5-3. Forest carbon under sustainable management, by (a) single hectare and (b)

landscape. (Source: Oneil et al. 2011.)




sites across a landscape that support a viableforest industry. It does not include increasedrecovery of forest residuals for bioenergy use,

which would offset more fossil fuel and in-crease the slope of the graph. In Figure 5-5the displacement is the amount of carbonbenefit that accrues from using biofuel inplace of natural gas for drying of the long-

lived products produced in the InlandNorthwest. Displacement can be larger inother regions where fossil fuels comprise agreater share of the energy used to generateelectricity or where more wood waste is usedfor energy. In this case from the InlandNorthwest, the analysis incorporates LCIdata on mill drying and the high percentageof nonfossil electricity generation in the re-gion caused by extensive hydroelectric re-sources. Note that the total emissions (in-cluding biofuel emissions) resulting fromproduction of these products shows up as a

negative benefit in Figure 5-5, depicting theemissions associated with generating the to-tal positive carbon benefits shown in this fig-ure. The displacement factor above the lineis the amount of equivalent fossil fuel emis-sions that were avoided by using biomass inplace of natural gas fordrying. The displace-ment factor takes into account the differen-tial in burning efficiencybetween natural gasand biomass.

As this example shows, where forest op-erations do not exceed the forest’s ability toregenerate, the gains from forest manage-

ment are seen in carbon pools and offsetsoutside the forest, without a decline in forestcarbon storage. The forest is carbon-cycleneutral in its own right; all products re-moved from it are additional carbon sinks aslong as they are in use, and the substitutionbenefits of using wood in place of compara-ble building products or energy sources alsoaccrue. If a change in forest operations (e.g.,shorter rotations, high natural mortality

without salvage, and reduced stocking be-cause of climate shifts) causes a decline inforest carbon storage, the slope of the graph

changes and the forest itself is no longercarbon-cycle neutral. Maintaining or en-hancing forest productivity so that a contin-uous flow of products can come from theforest provides the greatest carbon mitiga-tion benefit.

The forest is only the first tier. Makingproducts that displace fossil fuel–intensiveproducts provides a cumulative offset by re-ducing fossil fuel emissions and delivers thelargest carbon benefit (Eriksson et al. 2007,Lippke et al. 2010). Discussions about base-

Figure 5-4. Comparison of GHG emissions from electric power plants. (Source: Adaptedfrom Lippke et al. 2011.)

Table 5-7. Definitions of carbon neutrality.

Type Definition Example

Inherent carbon neutrality Biomass carbon was only recently removed from the atmosphere;returning it to the atmospheremerely closes the cycle

All biomass is “inherently carbonneutral”

Carbon-cycle neutrality If uptake of carbon (in CO2) by plantsover a given area and time is equal toemissions of biogenic carbonattributable to that area, biomassremoved from that area is carbon-cycle neutral

Biomass harvested from regions where forest carbon stocks arestable is “carbon-cycle neutral”

Life-cycle neutrality If emissions of all greenhouse gases

from the life cycle of a productsystem are equal to transfers of CO2

from the atmosphere into thatproduct system, the product systemis life-cycle neutral

Wood products that store

atmospheric carbon in long-termand permanent storage equal to(or greater than) life-cycleemissions associated withproducts are (at least) “life-cycleneutral”

Offset neutrality If emissions of greenhouse gases arecompensated for by using offsetsrepresenting removals that occuroutside of a product system, thatproduct or product system is offsetneutral

Airline travel by passengers whopurchase offset credits equal toemissions associated with theirtravels is “offset neutral”

Substitution neutrality If emissions associated with the lifecycle of a product are equal to (orless than) those associated with likely substitute products, that product orproduct system is (at least)

substitution neutral

Forest-based biomass energy systems with life-cycle emissionsequal to (or less than) thoseassociated with likely substitutesystems are (at least)

“substitution neutral” Accounting neutrality If emissions of biogenic CO2 are

assigned an emissions factor of zerobecause net emissions of biogeniccarbon are determined by calculatingchanges in stocks of stored carbon,that biogenic CO2 is accountingneutral

The US government calculatestransfers of biogenic carbon tothe atmosphere by calculatingannual changes in stocks of carbon stored in forests and forestproducts; emissions of CO2 frombiomass combustion are notcounted as emissions from theenergy sector nor are emissionsfrom decay of dead trees in theforest counted as emissions in theforest sector

Source: NCASI (2011).




lines and additionality are about who gets

the credit. Likewise, discussions about leak-age are about where it occurs in the globaleconomy. These concepts are relevant in themarketplace but irrelevant for climatechange mitigation because if, for example, aconstruction company does not use wood, it

will likely use a competing product with ahigher carbon footprint. These market fac-tors are explored in Section 6.

Even where growth and removals are inlong-term balance, carbon stocks can fluctu-ate across the wood supply area. Althoughthe timing of year-to-year carbon fluxes can

affect the radiative forcing of the atmo-

spheric system, focusing on these transient

conditions instead of the long-term balancebetween growth and removals can lead todifferent conclusions about the costs andbenefits of harvested biomass and woodproducts.

The temporal scale of an analysis can beimportant in several other ways, especially asit affects biomass carbon accounting. Thetime period for accounting may be expandedto include flows of CO

2 into trees; CO2

emissions from decomposing biomass in theforest; and emissions associated with estab-lishing, growing, or regenerating the forest

(including land-use change and other activ-

ities that alter long-term average carbonstocks). The end point for the accountingmay extend through the end of life of theproduct (World Resources Institute/WorldBusiness Council for Sustainable Develop-ment 2011).

Life-cycle studies often combine allflows of GHGs to and from the atmosphere

into a single number reflecting the total ef-fects over a product’s life cycle. It may beimportant, however, to understand the tim-ing of removals and emissions, particularly if comparing forest-based and substitute prod-ucts or comparing alternative uses for land.Such comparisons may show short-termbenefits attributable to delayed harvesting,but over time, these benefits diminish andeventually cease as forests age and naturalemissions approach uptake. The benefits as-sociated with using products from forest-based systems, however, often continue to

accumulate (Schlmadinger and Marland1996, Lippke et al. 2010, 2011). Extendingthe period of analysis through multiple rota-tions can be critical to understanding theshort-term and long-term implications of using forest-based products.

Temporal considerations can also beimportant when discounting is used to re-flect the time value of emissions and reduc-tions (Levasseur et al. 2010). Such studiesare the norm in the physical models used inclimate modeling but are relatively uncom-mon in life-cycle studies and policy-related

work.

Figure 5-5. Carbon trajectories under sustainable management of a forested landscape (asshown in Figure 5-3b). (Source: Oneil and Lippke 2010.)




Forest Carbon Policies

Policies to increase the benefits of for-est carbon can use a range of strate-gies. At the national level, the quan-

tity of greenhouse gases (GHG) emitted canbe reduced by:

• increasing net carbon sequestrationrates in forests,

• using wood products rather than en-ergy- and emissions-intensive buildingproducts, and

• converting forest residues into energy.

Voluntary carbon management pro-grams for individuals and groups of land-owners have been promoted in the UnitedStates, and countries that ratified the KyotoProtocol have introduced their own pro-grams. Although the Chicago Climate Ex-change (CCX) suspended activity in No-vember 2010 and no federal cap-and-tradelegislation that would include forest carbonprojects was enacted in 2010, there are vol-untary systems, regional programs (North-east Regional Greenhouse Gas Initiative and

Western Climate Initiative), and a state pro-gram (in California) that could evolve intomore significant schemes. In other countries

with temperate forests, increased demandand prices for woody biomass used for en-ergy across Europe (European Union 2009)and the creation of carbon property rightsfor post-1990 plantations in New Zealand(New Zealand Government 2011) could in-spire US incentive programs for landownersto manage for forest-based climate benefits.

Forest Carbon Offset ProjectsForest carbon offset projects started as a

way to finance projects to reduce tropicaldeforestation with voluntary investmentsfrom electric utilities (Dixon et al. 1993).Many US consumers interested in mitigat-ing climate change also preferred forest-based projects offered by voluntary offsetschemes (Niemeier and Rowan 2009). Theconcept of offsets is that individual emitterscan compensate for their carbon emissions

with carbon sequestered by qualifying proj-ects. The protocols for forestry carbon offsetprojects vary; most offset sales have been for

projects where the value was based on mea-surable increases in forest carbon stockscompared with a no-project scenario.

Forestry offset projects generally can beclassified into one of the following five cate-gories based on adaptations of Helms’s (1998)andtheFloridaDepartmentof EnvironmentalProtection’s (Stevens et al. 2010) definitions.Notall categories are recognized by thevariousprotocols governing forestry offset projects,and in some cases the definitions overlap.

• Afforestation—establishing forests

where the preceding vegetation or land use was not forests.

• Reforestation—the reestablishmentof forest cover after the previous forest wasremoved.

• Forest management—managementof existing forests to meet specified goals andobjectives while maintaining forest produc-tivity.

• Forest conservation—managementand protection of existing forests to avoidconversion to nonforested land uses.

• Forest preservation—management

and protection of existing forests to avoiddegradation into less productive conditions.

Protocols for those project types typi-cally include the following elements, but therequirements may differ significantly (Pear-son et al. 2008):

• Eligibility—for forestry offset proj-ects, many of the eligibility criteria (e.g.,landownership, commercial harvesting, anduse of pesticides) are not directly related toclimate benefits.

• Carbon sequestration calculation pro-cedures—methods to determine the num-ber and timing of carbon credits earnedthroughout the life of an offset project in-clude volume equations, growth-and-yieldtables, and direct measurements of standingforest biomass.

• Baseline requirements—carbon cred-its are earned for carbon sequestered aboveand beyond a baseline, which may be fixedto a certain year, based on the national trend,or defined as the “without project” scenarioor business-as-usual (BAU) case.

• Carbon pools—protocols typically credit carbon sequestered in one or morecarbon pools. The definitions and requiredmeasurement method of these carbon poolsdiffer greatly among protocols. Typical car-bon pools include measurable abovegroundbiomass, estimated belowground biomass andsoil carbon, and some harvested wood prod-ucts. Most project protocols do not credit

wood biomass initially used for energy or thefuture storage of woody biomass in landfills,even though these uses are calculated as cli-

mate benefits in national emissions reports.• Crediting period—the crediting pe-

riod specifies the time frame within whichcredits for sequestered carbon may be issuedfrom a specific project.

• Leakage—a project’s carbon benefitscan be canceled out by activities elsewhere.Internal leakage occurs if an owner increasesharvests on portions of its lands to replacetimber restricted from harvest under the off-set project. External leakage occurs outsidethe firm’s sphere of operations and occurs ata regional, national, or global scale.

• Permanence and reversals—carbonsequestered by an offset project, particularly if credits are issued, should remain seques-tered long enough to equal the atmosphericeffect of an emission. Based on IPCC defi-nitions (Forster et al. 2007), 100 years of new terrestrial carbon storage is considered apermanent offset for an emission of an equalquantity of carbon dioxide. A reversal occursif carbon sequestered and credited during aproject’s lifetime is lost, typically to naturaldisasters such as wildfires or storms but alsoto deliberate acts such as timber theft.

Forestry offset protocols (see Box nextpage) have been created to serve severaldifferent purposes. Some are part of cap-and-trade programs, whether mandatory orvoluntary. Others are part of emissions re-duction schemes. Still others were developedindependently but have been adopted by one or more programs:

• Mandatory GHG reduction pro-grams—caps are imposed on GHG emis-sions. If emissions are tradable, polluters can


section 6



purchase benefits from certified projects orother polluters that have reduced their emis-sions more than required. Among countries

that ratified the KyotoProtocol, NewZealandand New South Wales (Australia) have creditsgenerated from plantation forestry, and somedeveloping countries host Clean Develop-ment Mechanism afforestation projects.

• Voluntary cap-and-trade systems—participation is voluntary; however, partici-pants are obligated to reduce their GHGemissions. As in mandatory cap-and-trade sys-tems, unused quotas or credits from offsetprojects can be purchased to meet thecap. Thedemise of the CCX means that as of 2011,there are no voluntary systems in operation.

• Voluntary emissions offset proto-cols—various organizations have developedrigorous standards for offset projects. Theseprotocols are usually independent of any re-quirement to reduce GHGs.

Variation among ProtocolsThe amount of carbon credits gener-

ated under protocols used in the UnitedStates can differ dramatically for the sameproject (Galik et al. 2009c), depending onthe sets of carbon pools allowed by the pro-

tocol and its baseline approach. Differencescan be further compounded by leakage, per-manence, and buffer requirements. The sub-stantial ranges in creditable carbon gener-ated have a dramatic effect on the financialviability of carbon offset projects compared

with BAU timber management scenarios. When six different protocols were applied to

the same southern pine plantation in a study by Galik et al. (2009c), break-even carbonprices ($/tCO

2e) had a 20-fold range de-

pending on the protocol’s rules about base-line values, reversals, leakage, and uncer-tainty. Most of the break-even prices werefar above the best 2010 value for voluntary carbon offsets, $10/tonne of CO

2(equiva-

lent to $8/green tonne of stumpage).The costs associated with establishing

and maintaining forestry offset projects alsovary depending on verification requirements,carbon measurement procedures, monitor-

ing frequencies, and third-party certifica-tion. Per hectare, costs for the high-costprotocol may be five times greater than for thelow-cost protocol (Galik et al. 2009b). Trans-actioncosts forsmall ownerships(less than100ha) were 10–20 times more costly per offsetcredit than for larger ownerships. Differencesin transaction costs for large ownerships(greater than 10,000 ha) are still large but areminor in absolute terms (less than $1.20/ha)because of economies of scale.

Under regional and state programs, thenumber of voluntary projects exceeds the

number of projects with sales. As of the endof 2010, no afforestation or reforestationforestry projects had been registered withthe Northeast Regional Greenhouse GasInitiative (RGGI), Inc. (RGGI 2011), and

just three conservation-based forest manage-ment and improved forest managementprojects had offset sales following protocolsapproved by the California Air ResourcesBoard (Climate Action Reserve [CAR]2011). Since less than 20% of credits in Cal-ifornia have been retired after offsetting anemission (CAR 2010), it would appear that

many purchasers are assuming that some of the credits will be grandfathered in futuremandatory systems. This pattern has alsobeen noted in international carbon markets(United Nations Economic Commission forEurope/Food and Agriculture Organization2010). As of 2011, uncertainty about ac-ceptable methodologies for measuring forestcarbon and related climate benefits has sig-nificantly limited interest in developing for-est carbon projects that involve large up-front costs (Waage and Hamilton 2011).

Accounting Issues Additionality and Baseline Set-

tings. With reduction in GHG emissions tothe atmosphere as the goal, the net amountof carbon sequestered must be additional to

what would have occurred without the offsetproject. For forest projects, additionality is rel-atively easy to establish when new trees are

planted and maintained but considerably more difficult to establish when based on acounterfactual assertion (e.g., “I was going toharvest in 10 years but instead will wait 30years”). Thisis furthercomplicatedwhenproj-ect guidelines are designed by the project pro-ponent, and the underlying documentation isnot audited by any official regulator, as wouldbe required for a real estate or stock transac-tion. A carbon baseline must be establishedagainst which the net change in carbon stocksis measuredso thatemissions reduction creditscan be quantified, verified, and registered.

Baseline carbon values of forest inventories aredetermined through standardforestry biomet-ric methods that include direct and statisti-cally designed and modeled measurementtechniques, but projections into the futuremay require numerous assumptions. Thebaseline carbon value of wood products and

wood energy that are used outside the proj-ect are typically based on a study by Smith etal. (2006). However, the Smith et al. (2006)estimates of the amount of wood still in useare considerably lower than the sawmill effi-ciency estimates of Smith et al. (2009) and

the product lifetime estimates of Skog(2008). The practical effect of using theSmith et al. (2006) estimates is to increasethe apparent carbon benefits of reducingcurrent harvests. The potential to exaggeratethe net climate benefits of a forest offsetproject will be increased if it is assumed that

wood used for energy results in a direct lossof carbon without any fossil fuel substitu-tion benefit.

Additionality can be controversial be-cause new activities earn credits whereas iden-tical activities initiated in the past do not.

Thus, additionality sometimes rewards lateentrants while appearing to punish those whohave historically engaged in the desired be-havior. Additionality is also controversial be-cause determining the counterfactual oftenrequires judgments regarding motivation.

US registries and programs use BAUand base-year approaches. The BAU base-line is the emission that would have hap-pened without any new technologies oractions. This scenario works well for com-paring existing and improved technologies

Examples of Offset Programs

Mandatory cap-and-trade systems• Clean Development Mechanism(CDM),

www.cdm.unfccc.int• New South Wales Greenhouse Gas Re-

duction Scheme, www.greenhousegas.nsw.gov.au/default.asp

• New Zealand Emission Trading Scheme,

www.climatechange.govt.nz/emissions-trading-scheme/

• Regional Greenhouse Gas Initiative(RGGI), www.rggi.org.

• California AB 32 Scoping Plan’s Cap-and-Trade Program (2012 start date)

Voluntary cap-and-trade systems• Chicago Climate Exchange (CCX), www.chicagoclimatex.com (suspended in2010)

Voluntary emissions offset protocols• American Carbon Registry (ACR), www.americancarbonregistry.org

• Climate Action Reserve (CAR), www.

climateactionreserve.org• The GHG Protocol for Project Accounting and the Land Use, Land-UseChange, and Forestry Guidance forGHG Project Accounting, www.ghgprotocol.org

• Voluntary Carbon Standard (VCS)Program, www.v-c-s.org




but is often less useful for land-based seques-tration practices, where natural ecosystemdynamics and future market-based actionsincrease the uncertainty of any projection.Changing forest management objectives,markets for alternative land uses, timberprices, and ecosystem service prices (e.g., theprice of sequestered carbon, wildlife habitat

acres, and water yields) all contribute to ahigh level of inherent uncertainty when aBAU baseline is defined. Unlike the baselineemissions of a direct emitter of CO2 (e.g., acoal-fired power plant), which can be pre-cisely measured and operationally con-trolled, forest BAU baselines are difficult toestablish at the project level.

In the base-year approach, an inventory is taken at the beginning of the project pe-riod, and a second inventory is conductedsome years later, using the same inventory design. The net change in carbon stocks (of

all allowable carbon pools within the forestoffset project) represents the carbon seques-tration related to the forest for that periodand is the basis for the number of carboncredits issued. In a sustainably managedforest, this net change in carbon stocks willreflect forest management actions, such asharvesting, treeplanting, and fertilizing. It

will also reflect effects of natural events suchas weather, wildfire, insects, and disease.

Reversals and Permanence. If forestcarbon credits are used to permanently offsetindustrial emissions, the forest project must

establish permanence by ensuring an equiv-alent amount of new carbon storage overtime. Because of the unpredictability of

wildfires, insect infestations, and weather,permanence is typically achieved throughinsurance mechanisms to guarantee that any losses will be compensated. Some registriesand programs require that any released car-bon be included in the net change calcula-tions so that credits previously issued can bepaid back; no additional credits can then beissued until the net change in carbon stocksis again positive. Various mechanisms are

typically used to address permanence forland use, including deed restrictions on landuse, long-term or permanent conservationeasements, buffers, and reserve pools (whereby portions of the carbon sequestered are held inreserve to offset potential losses). Insurance isanother approach to guaranteeing that thepromised climate benefits materialize.

Market Leakage. In the forest climateproject literature, meeting consumer de-mand with new purchases from outside theproject boundary is referred to as market

leakage. Market leakage is often underesti-mated at the project or regional level in theUnited States because alternative wood sup-plies may come from other regions or na-tions. As noted in Section 2, domestic pro-duction has fluctuated around 300 millionm3 of wood products since 1980 while con-sumption continued to increase (Smith et al.

2009). When Murray et al. (2004) modeledthe large reduction in timber harvests frompublic lands in the Pacific Northwest in the1990s, they estimated a market leakage rateof more than 80% as timber demand wasmet through harvests elsewhere in North

America. Underestimating market leakagerates will proportionally overestimate theglobal climate benefits of forest offset proj-ects. However, most project-based forestoffset protocols ignore market leakage alto-gether, allow the project proponent tochoose the leakage rate, or set a maximum

market leakage rate of 20%.Temporal and Spatial Boundaries.

The spatial and temporal boundaries forcarbon accounting in offset programs arevery program-specific. In offset programs,selection of these boundaries is closely relatedto the leakage andpermanence issues discussedpreviously and based on a combination of sci-entific and policy considerations. Because pro-grams have different policy priorities, theseboundaries vary considerably, even for seem-ingly similar project types.

Spatial boundaries are usually deter-

mined based on the scale of the offset proj-ect, the jurisdiction of the program author-ity, and, to some extent, the need to preventleakage. Accordingly, spatial boundariesvary considerably. In principle, the bound-aries of the accounting should extend to allareas potentially affected by the offset proj-ect activity, but as a practical matter, spatialboundaries are usually extended only tothose areas directly affected by the project.Under normal circumstances, therefore,boundaries extend only as far as needed toaddress direct benefits and internal leakage.Limiting the boundaries in this manner risksmissing important indirect benefits andlarge-scale leakage.

Temporal boundaries in offset pro-grams also vary significantly. For forest-based projects, however, the temporalboundaries are especially significant, e.g., inselecting and modeling baseline conditions;as noted previously, the baseline can havedramatic effects on the estimated benefits of offset projects. Temporal boundaries are

also critical in addressing concerns about re-versals and permanence.

Estimates of Forest Carbon Flux. Car-bon stocks in the forest sector do not directly affect atmospheric GHG levels; rather, car-bon flux, typically assessed as a change incarbon stocks, is what matters in evaluatingthe contribution of forests. The change in

carbon flux, relative to a baseline or BAUscenario, is therefore the relevant metric. Fortracking flux at broad (state and regional)scales and for generating baseline referencevalues, comprehensive forest inventories basedon remeasured, permanent, sample plots pro-vide the most accurate and precise estimates.However, such inventories do not measure

woody carbon, biomass, or even volume. In-stead, they assess forest area, enumerate andtrack live and dead trees, and measure treecircumference and assess tree height. Someinventories also sample down wood, litter,

soils, and understory vegetation.Getting from those data to estimated

carbon stock involves several sources of er-ror: measurement, sampling, model, andmodel selection. Commitment to quality assurance—as practiced, for example, by theForest Inventory Analysis Program (Pollard2005)—can control measurement error.Sampling error can be controlled by increas-ing sample size, which typically does not in-troduce bias as long as the sample is repre-sentative. Model error, the uncertainty notexplained by the variables included in a

model, can be accounted for when modelingerror propagation (e.g., Phillips et al. 2000)as long as model authors report error infor-mation. However, model selection error canintroduce substantial bias and cannot be re-solved without investing in improved inven-tory technology and/or models on a scale notpreviously contemplated.

Model selection error arises from theneed to estimate carbon stores for each livetree by selecting from thousands of arguably plausible, analytically defensible computa-tion pathways generated from differentcombinations of published biomass, vol-ume, and density equations for whole trees,boles, branches, and bark, based on dbhalone or dbh and height. Under the mostoptimistic scenario of a sensitivity analysis of live-tree carbon stores in northwest Oregon,model selection error (half the predictionrange expressed as a percentage of the pre-diction envelope midpoint) was 37%(Melson et al. 2011). Given that samplingerror for the same analysis implied a 95%




confidence interval of 6%, model selectionaccountsfor mostuncertainty in carbonstores.

In most cases, carbon flux is a smallfraction of carbon stocks and can be farsmaller than the error of estimated carbonstocks. When flux is calculated as a differ-ence in carbon stocks, the error of the differ-ence can exceed the estimate of flux. An

analysis of Canada’s managed forests esti-mated annual net forest carbon fluxes of 2 20 teragrams (Tg) of C/year from1990 to 2008 (Stinson et al. 2011). A study of carbon balance in European forests thatused estimates based on ecological site stud-ies, national forest inventories, and vegeta-tion models calculated standard errors, notaccounting for model selection error, rang-ing from 21 to 133% of estimated flux(Luyssaert et al. 2010). The current “sys-tems” in place for estimating forest carbonflux are grossly inadequate and do not fully

use the data that is available. The error esti-mates are generated via an entirely ad hocapproach that omits what is likely the great-est component of error (model selection).For example, a US EPA (2010) report founduncertainty of 20% in estimates of forestecosystem carbon flux and 25% in esti-mates of harvested wood products carbonflux. However, the Monte Carlo–based er-ror simulation used to predict uncertainty accounted primarily for sampling and modelerror and did not address model selectionerror (Smith and Heath 2000).

Especially under disturbance regimes, itcan be important to understand carbon fluxfrom pools other than live trees, becausethese other pools contain 65–100% (for anonstocked stand) of total ecosystem carbon(Van Miegroet et al. 2007). Obtaining accu-rate estimates of nonlive tree pools, however,can be especially challenging. For instancetracking down wood over long time intervalsin an extensive forest inventory still is notfeasible because no system of accountingfor components of change, analogous togrowth, removals, and mortality of standing

trees, has been developed; the few studies, todate, have involved only small areas andshort time intervals and required substantialeffort (e.g., Vanderwel et al. 2008). More-over, the density of standing and down

wood is unpredictable, and questions re-main about the ability to develop estimatesof flux from estimates of deadwood for thesame plot at two points in time (Woodalland Monleon 2008). The difficulties are il-lustrated by Westfall and Woodall (2007)

who found that measurements of fine wood

pieces taken by two inventory crews even inthe same season agreed only 26–57% of thetime, and the lengths of coarse wood piecesagreed only 72% of the time; in both cases,“agreement” was defined as within a 20%tolerance. Estimating carbon flux from soilcan be problematic due to sampling andmeasurement costs as well as horizontal and

vertical variability, even at the plot scale; ac-curate flux is not possible because the soilsample is removed from the ground andtherefore cannot be remeasured the way atree can be remeasured.

These challenges to obtaining accurateestimates of forest carbon flux at broad scaleapply equally to obtaining estimates at thestand or project scale, e.g., to establish aproject baseline or show a change in carbonstores or flux. Additional challenges includeensuring a representative sample, obtainingsufficient sample size to control sampling er-

ror, and the need to model the carbon im-pacts of prospective management alterna-tives (e.g., BAU versus an offset project).Unless vigorous effort is invested in avoidingsubjectivity in plot placement (both in termsof which stands are selected for samplingand where the samples are collected fromsampled stands) and in assuring that standedges are sampled with appropriate proba-bility, inventories built on stand or compart-ment “exams” often exhibit sample locationbias that compromises representativeness.This is especially true when the stakes in the

outcome of the inventory are high (such asrefunding carbon offset payments if prom-ised sequestration cannot be proven): sam-pling results could easily be manipulated by plot placement or, conversely, by manage-ment activity being different at plot loca-tions than elsewhere. Given the large num-ber of plausibly valid carbon calculationpathways, there is ample opportunity for“equation shopping” to generate the greatestoffset value.

The considerable cost of implementinga comprehensive, systematic inventory de-

sign at project scale has driven some to pro-pose relying instead on remotely sensed esti-mates of forest carbon flux for monitoring(e.g., Ahern et al. 1998, Running et al.1999). Carbon storage has been estimatedvia spectral imagery (Law et al. 2006, Black-ard et al. 2008, Powell et al. 2010) and syn-thetic aperture RADAR (SAR) (Bergen andDobson 1999) from satellite and airborneplatforms. These approaches have relied on“ground truth” of the same carbon estimatesmodeled from vegetation assessed on field

plotsas described previously. Sampling erroris not a factor, because remote sensing takesa census rather than a sample of the forestedlandscape. Nevertheless, modeling carbonstores directly from spectral imagery or SAR has limitations: (1) saturation of the re-sponse signal in stands with dense canopiesand high biomass (Lefsky et al. 2002); (2)

little if any direct response signal from treeboles, the vegetation component containingthe most biomass; and (3) inability to consis-tently detectchangesin understorytrees, down

wood, and herbaceous cover under dense can-opy. These deficiencies partly explain recententhusiasm over using LiDAR (Light Detec-tion and Ranging systems) (e.g., Wulder etal. 2010); unfortunately, LiDAR acquisitionat a coverage density suitable for character-izing forest carbon is prohibitively costly.

Remote-sensing estimates of carbonstocks remains attractive because of its ap-

parently low cost, spatially comprehensivecoverage, and perhaps the deterministic re-sult—uncertainty information is essentially never carried along with pixel-level or ag-gregated estimates (for example, as standarderrors incorporating measurement, model,andmodel selection errors); indeed, it wouldbe hard to know how to do so in a meaning-ful way, but this does not mean that the un-certainty does not exist. When no uncer-tainty is recognized, however, it is easy toassume that stock change can be legitimately computed by comparing modeled stocks at

different times. In fact, even seemingly largedifferences may not be real, and even thebest validation results (typically for over-story trees) show models explaining barely 70% of the variation; for subcanopy carboncomponents, such as down deadwood andsnags, there is virtually no relationship be-tween model predictions and field-observedvalues (e.g., Wimberly et al. 2003).

Clearly, numerous challenges exist indeveloping suitably accurate estimates of carbon flux in forest-based carbon offsetprojects for supporting investment decisions

(e.g., McKinley et al. in press). Offset pro-grams must recognize these limitations, pro-viding mechanisms that protect againstclaims of benefits or assignments of liabili-ties that are artifacts of uncertainties in esti-mates of carbon stocks and flux.

Improvements in measurement andsampling methods are needed. Althoughmeasurement and sampling error are rela-tively manageable for generating estimatesof live-tree carbon stocks and fluxes at broadscale, there are important opportunities to




improve the models that transform inven-tory measurements into estimates of carbonflux. Existing allometric equations (volumeand biomass of all tree components) need tobe evaluated for their validity for differentpopulations of trees (e.g., across geography,species, site classes, and diameter ranges)and, undoubtedly, many more need to be

developed. The transportability of modelsand model forms across forest types alsoneeds evaluating, because a poor match be-tween models and actual trends could over-predict the level of benefits and promote du-bious projects (Bottcher et al. 2008). A critical question will be whether it is possibleto achieve these and other improvements inmeasurement and sampling methods andquantitative risk assessments at a sufficiently low cost to avoid the situation where achiev-ing levels of accuracy comparable with thoserequired for regulated financial transactions

exceeds the total financial value of forestmanagement projects. Policy alternatives tooffsets that avoid the expensive imperativefor high accuracy measurement of flux whilestill achieving climate benefits include, forexample, “bonus payments” for treeplantingor carrying higher tree stocking or permit

waivers for sanitation/salvage prescriptionsaimed at capturing carbon benefits frommortality via substitution.

Policy Alternatives to OffsetsScience-based forest carbon policies

should be part of a comprehensive energy policy to achieve energy independence anddeliver carbon benefits while providing en-vironmental and social benefits, includingclean water, wildlife habitat, and recreation.Economic incentives—in the form of taxcredits, subsidies on required reforestationinputs, or direct payments for easily measur-able attributes (e.g., forest cover)—can en-courage forest landowners to retain their for-ests as forests and manage their forests forcarbon benefits.Marketsand economicincen-tives are powerful tools; however, two other

effective policy mechanisms have promise.• Information disclosure—The ToxicRelease Inventory, Green Energy purchas-ing programs, and the Safe Drinking Water

Act have shown that information disclosure, whether required by government or by pri-vate entities, can motivate firms to changetheir behavior. Easily understood programsrequiring companies to disclose their GHGemissions for processes or products couldencourage the use of forest products, espe-

cially if these disclosures differentiate be-tween emissions that recirculate atmo-spheric carbon and emissions that add toatmospheric carbon. Importantly, informa-tion disclosure requirements are often polit-ically and socially more acceptable than reg-ulatory programs that mandate behaviormodifications.

• Building codes and procurementpolicies—substituting wood products forsteel, aluminum, concrete, plastic, and othermaterials permanently reduces GHG emis-sions (see Section 5). Local government pol-icies, such as building codes and procure-ment policies, which encourage or requirethe use of life-cycle assessments on the car-bon consequences of material choices, canhave significant climate change and energy benefits.

Those alternative policy approaches donot require the precision in forest carbon

accounting needed in offset programs. Us-ing life-cycle analyses, numerous scientificstudies have already determined the rela-tive carbon benefits of various products andprocesses, including forest biomass–basedproducts; thus there is no need to quantify the carbon benefits in each application of those products.

Managing Forest CarbonBenefits and Risks

The capacity of US forests to sequestercarbon over the next 100 years is subject to

powerful, disruptive forces: climate change;development pressure; conversion of forest-land to nonforest uses; and likely expansionof exotic plants, insects, and pathogens. Atthe same time, political imperatives for cleanenergy will drive production of energy frombiomass, including forest biomass. We canexpect concerted efforts to mitigate climatechange by increasing the carbon in US for-ests and using wood-based energy and prod-ucts. All this will occur against a backdrop of intense international competition amongcompanies that make traditional and non-

traditional forest products.That presents several challenges for theforestry sector. First, we cannot simply ex-trapolate past forest and wood use trends toforecast likely futures or even apply models

without accounting for the many uncertain-ties. For instance, carbon accumulation rates

will likely change with a different climateand species mix, and mortality relationshipscould be quite different than in the past.Second, a rational management response en-

tails adaptation to and mitigation of theseeffects (Malmsheimer et al. 2008). Changesin planted species selection, silviculturaltreatments, fire regimes, and insect damagemust be accounted for when projecting for-est carbon dynamics. Third, the uncertain-ties present risk management problems. A central question is how to strike a smart

balance between in-forest sequestration by managing for increased carbon density across all forest carbon pools, and use forbioenergy that offsets fossil fuel use and theremoval of carbon to long-term sequestra-tion in harvested wood products and landfillstorage (Matthews and Robertson 2005).The near certainty of eventual disturbancemakes dependence on in situ carbon storagesinks a high-risk alternative in many areas(Galik and Jackson 2009).

The most effective management strate-gies to satisfy multiple economic, environ-mental, and societal objectives will vary from site to site. There is substantial litera-ture developing around management andmitigation practices that maximize land-scape-level ecosystem carbon stocks whileconsidering uncontrollable disturbances andsustain or increase carbon sequestration in

wood and bioenergy products that achievefossil fuel substitution benefits (Hines et al.2010). Other approaches could maximizeproduct and energy benefits while puttingless emphasis on the levels of ecosystem car-

bon stocks. A major challenge for the future will be ensuring policy and market environ-ments that promote the application of strat-egies best suited to specific circumstances.

If bioenergy is to contribute to climatemitigation, the bioenergy sector will need toexpand. How this changes demand forforestproducts depends on renewable energy pol-icies, the treatment of bioenergy in climatepolicies, and the relative cost of producingenergy from forest biomass versus other re-newable energy sources and fossil fuels. De-veloping more efficient forms of bioenergy,

such as combined heat and power, will alsobe important. Emissions reduction benefitsofwoodenergyuse will varyby woodsource,forest condition, the extent of forest distur-bance, and geographic region. Markets andpolicies will determine how much new forestbiomass is purpose grown to meet energy goals and whether harvest residues can beredirected to produce energy that offsets fos-sil fuel use (Morris 2008).




Integrating Forests into a Rational PolicyFramework

Forests are an integral component of the global carbon cycle and may changein response to climate change.

US forest policies can fosterchanges in forestmanagement that will provide measurablereductions in carbon emissions over time

while maintaining forests for environmentaland societal benefits, such as timber andnontimber forest products, vibrant ruralcommunities, clean water, and wildlife hab-itat. Policies founded on three tenets reflect-ing the stocks and flows of woody biomass inUS forests can ensure that our forests willproduce sustainable carbon, environmental,and societal benefits.

1. Keep Forests as Forests andManage Appropriate Forestsfor Carbon

For more than 70 years, US forest coverhas increased and net growth has exceeded

removals and mortality. Therefore, carbonstorage is increasing in the United States. Insome forests (e.g., old-growth), other con-siderations and other benefits will usually outweigh carbon benefits. However, forests

will change with or without management,and choosing not to manage has its own car-bon consequences. Young, healthy forestsare carbon sinks. As forests mature, they generally become carbon-cycle neutral oreven carbon emission sources. Net primary productivity declines and the decay of treeskilled by natural disturbances—wind-

storms, fire, ice storms, hurricanes, insectand disease infestations— emits carbon without providing the carbon benefits avail-able through product and energy substitution.

2. Recognize that SubstantialQuantities of Carbon AreStored in Wood Products forLong Periods of Time

Wood is one-half carbon by weight,and it lasts a long time in service—and often

for a long time after being retired from ser-vice. Substantial volumes of wood go intoconstruction products and structures: evenduring the midst of the recent “Great Reces-sion” (2007–2009), US housing starts ex-ceeded 440,000 annually. Additional woodis used for furniture and other products,

which at the end of their useful lives may beconverted to energy. Paper may go intolong-term use (e.g., books) or be recoveredfrom the waste stream for energy produc-tion. Other wood—construction debris,yard waste, unrecycled paper—winds up inlandfills, where it often deteriorates moreslowly than is generally assumed. In total,the rate of carbon accumulation from woodproducts in use and in landfills was about 88million tonnes of carbon dioxide equivalents(CO

2e) in 2008, about 12% of the rate of

sequestration in forests.

3. The Substitution Effect Is

Real, Irreversible, andCumulative

Compared with steel, aluminum, con-crete, or plastic products, considerably lessenergy, and vastly less fossil fuel– derived en-ergy, is required to make wood products.The low embodied energy of wood buildingproducts, structures, furniture, cabinets, andother products has been well documentedthrough life-cycle assessments. Not only isthe quantity of energy used in manufactur-ing wood products low compared with other

materials, but the quantity of fossil energy iscomparatively very low: one-half to two-thirds of the energy used by the North

American wood products industry is bioen-ergy. For instance, compared with steelframing with an average recycled content,the manufacture of wood framing requiresone-half or less the total energy, and one-fourth to one-fifth the fossil energy.

Conserving forests for recreational, aes-thetic, and wildlife habitat goals has been a

strongpolicy driver in the UnitedStatesoverthe past few decades, especially in the PacificCoast and Northeast regions. Evidence of increasing losses to disturbances that are notcaptured in forest growth modeling anddecreasing rates of carbon accumulation inmaturing forests suggests that a strong con-servation-oriented strategy may not always

produce significant global climate benefits.The climate benefits of active forest manage-ment are most apparent when substitutionbenefits that occur in the consumer sectorare included. As we move forward with pol-icy discussions regarding the many positiveroles of US forests at local, national, andglobal scales, it will be imperative that objec-tive, science-based analysis and interpreta-tions are used, and that particularly closeattention is paid to assumptions underlyingthe analyses.

US policymakers should take to heart

the finding of the Intergovernmental Panelon Climate Change in its FourthAssessmentReport when it concluded that “In the longterm, a sustainable forest management strat-egy aimed at maintaining or increasing for-est carbon stocks, while producing an an-nual sustained yield of timber, fibre orenergy from the forest, will generate the larg-est sustained mitigation benefit” (IPCC2007a, 543). An integrated rational energy and environmental policy framework mustbe based on the premise that atmospheric

greenhouse gas levels are increasing primar-ily because of the addition of geologic fossilfuel–based carbon into the carbon cycle.Forest carbon policy that builds on the sci-entific information summarized in this arti-cle can be an important part of a compre-hensive energy policy that promotes energy independence and delivers real carbon ben-efits while providing essential environmen-tal and social benefits, including clean water,

wildlife habitat, and recreation.


conclusion



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About the Task Force

Robert W. Malmsheimer Task Force Chair, and Professor of Forest Pol-icy and Law, SUNY College of Environmental Science and Forestry, Syracuse, New York

Malmsheimer, a professor at SUNY ESF since 1999, teaches courses in naturalresources policy and environmental and nat-ural resources law. His research focuses onhow laws and the legal system affect forestand natural resources management, includ-ing how climate change and carbon seques-tration policies affect forest and natural re-sources. Before becoming a professor,Malmsheimer practiced law for 6 years. Hehas a PhD in forest policy from SUNY ESF,a JD from Albany Law School, and a BLA from SUNY ESF. He is a SAF Fellow andthe chair of the SAF Committee on ForestPolicy. He cochaired the 2007–2008 SAFTask Force on Climate Change and CarbonSequestration, and he has chaired and servedon numerous national and state SAF com-mittees and task forces.

James L. Bowyer Professor Emeritus, University of MinnesotaDepartment of Bioproducts and Biosystems Engineering, President of Bowyer & Associates,Inc., and Director of the Responsible Materials Program in Minneapolis-based Dovetail Part-ners, Inc.

Bowyer is president of Bowyer & Asso-ciates, Inc., a business-oriented environ-mental consulting firm, and director of theResponsible Materials Program in Minne-apolis-based Dovetail Partners, Inc., a non-profit focused on the effects and trade-offsof environmental decisions, including con-sumption choices, land use, and policy alter-natives. Bowyer is a 27-year member of SAFand an elected fellow of the International

Academy of Wood Science. He has served aspresident of the Forest Products Society andof the Society of Wood Science and Tech-nology, vice president of the Consortium forResearch on Renewable Industrial Materi-als, and chairman of the Tropical ForestFoundation. He was head of the University of Minnesota’s Department of Wood and

Paper Science and founder and director of the Forest Products Management Develop-ment Institute at the University of Minne-sota. Bowyer has a BS in forest managementfrom Oklahoma State University, an MS in

wood science from Michigan State Univer-sity, and a PhD in wood science and tech-nology from the University of Minnesota.

Jeremy S. Fried Research Forester, Resource Monitoring and Assessment Program, Pacific Northwest Re-search Station, US Forest Service, Portland,Oregon

Fried has been with the PNW ResearchStation’s Forest Inventory and Analysis unitsince 1999, serving as California FIA analystsince 2000 and as team leader from 1999 to2009. His research focus is interdisciplinary application of systems analysis and geo-graphic information science to contempo-rary natural resource management issues.Current and recent examples include eco-nomic feasibility of landscape-scale fueltreatments, forest carbon accounting, ini-tial attack simulation and optimization,impacts of climate change on wildlandfire, and building inventory-based modelsof fire effects. Before joining the PNW Research Station, he served on the forestry faculties at Michigan State and Helsinkiuniversities. He has a PhD in forest manage-ment and economics from the University of California–Berkeley and an MS in forestecology and soils from Oregon State Univer-sity. Fried served as the resource measure-ments subject area representative on SAF’s

Forest Science and Technology Board andasan officer (secretary, chair-elect, and chair)of both the Management Science/Opera-tions Research and GIS working groups.

Edmund Gee USDA Forest Service National Woody Bio-mass Utilization Team Leader and National Partnership Coordinator

Gee is the past chair of the Interagency Woody Biomass Utilization Group. He wasone of the coauthors of the SAF task force

report, “Forest Management Solutions inMitigating Climate Change in the UnitedStates.” He has a BS in natural resourcemanagement from the University of Califor-nia–Berkeley and an MBA in internationalbusiness from the University of Phoenix; healso completed graduate work in silvicultureand fire ecology at the University of Wash-ington. He has more than 35 years of diverseexperience as a line and staff officer with theUS Forest Service in the Washington Office,

two regions, six national forests, and inter-national programs.

Robert L. Izlar Director, University of Georgia Center for For-est Business, Athens, Georgia

Izlar has been director of the University of Georgia Center for Forest Business since1998, and he teaches courses on renewablenatural resources policy and consulting. Hehas 26 years’ experience in private forest in-dustry, including stints as head of the Geor-gia and Mississippi forestry associations. Hehas a bachelor’s and a master’s in forest re-sources from the University of Georgia andan MBA from Georgia Southern University.He served as SAF Georgia Division chair in1995 and Oconee Chapter chair in 2010,and was elected a Fellow in 2003. He is afellow of the Royal Swedish Academy of

Agriculture and Forestry and is a SAF Cer-tified Forester and a Registered Forester inGeorgia.

Reid A. Miner Vice President for Sustainable Manufacturing,National Council for Air and Stream Im- provement (NCASI), Research Triangle Park,North Carolina

Miner has workedfor National Councilfor Air and Stream Improvement since1974. For the past 15 years, he has focusedon sustainability topics, including theconnections between the forest productsindustry and the global carbon cycle. His

work has involved collaborations with arange of organizations, including the UnitedNations Food and Agriculture Organiza-




tion, the International Finance Corpora-tion of the World Bank Group, the Inter-governmental Panel on Climate Change(IPCC), the US Forest Service, the Environ-mental Defense Fund, the Council for Sus-tainable Biomass Production, the WorldResources Institute, and the World BusinessCouncil for Sustainable Development. He

was a contributing author to IPCC’s Fourth Assessment Report and is on US EPA’s andIPCC’s lists of expert reviewers on carbonaccounting. Miner has BS and MS degreesin chemical engineering from the University of Michigan.

Ian A. Munn Professor of Forestry Economics and Manage-ment, Mississippi State University, Mississippi

Munn has been a professor in the De-partment of Forestry at Mississippi StateUniversity since 1993. He teaches the de-partment’s capstone course in professionalpractices, as well as a course in advanced for-est management. He also coordinates stu-dent internships for academic credit. His re-search focuses on nonindustrial privateforest landowner issues, including land-owners’ willingness to provide ecosystemservices, recreational opportunities, and log-ging residues and short-rotation woody crops for biofuels. Before pursuing his PhDdegree, Munn was a timberland manager fora forest products firm for 10 years. He has a

PhD in forestry and economics from NorthCarolina State University, an MBA fromLouisiana Tech University, an MS in resourcemanagement from SUNY ESF, and an AB inbiology from the University of North Caro-lina. He is a SAF Fellow, a councilman fromDistrict 11, editor of the Southern Journal of Applied Forestry , and has served as a chair of

the Mississippi state society and local SAFchapter. Munn is a SAF Certified Foresterand a Mississippi Registered Forester.

Elaine Oneil Research Scientist, University of Washington,and Executive Director, Consortium for Re-search on Renewable Industrial Materials (CORRIM), Seattle

Oneil is a research scientist at the Uni-versity of Washington and the executive di-rector of the Consortium for Research onRenewable Industrial Materials, a 17-uni-versity research consortium that conductslife-cycle inventory and life-cycle assess-ments on wood products from cradle tograve. She has a BS in forestryfrom the Uni-versity of British Columbia and MSc andPhD degrees from the University of Wash-ington. Her focus is on forest managementoperational research: the effects of harvest-ing on bald eagle nesting, management of Douglas-fir at the edge of its climatic range,climate change impacts on forest health inInland West forests, integration of forest

carbon accounting into a forest manage-ment framework, ecological and economicconstraints to biomass feedstock availability,life-cycle analysis, and timber supply analy-sis. Before her midcareer return to academia,she worked as a Registered Professional For-ester in both consulting and governmentforestry positions in several central British

Columbia areas devastated by the mountainpine beetle epidemic.

William C. Stewart Forestry Specialist, Environmental Science,Policy and Management Department, Univer-sity of California–Berkeley

Stewart is a Cooperative Extension for-estry specialist who has been based at UCBerkeley since 2007. He is also the directorof the Center for Forestry and co-directorfor the Center for Fire Research and Out-reach at UC Berkeley. His current areas of research and extension focus on the linkagesbetween managed forests and climate change,the economic aspects of fire-adapted silvi-culture in California, and succession plan-ning with family forest owners. He has anMS and PhD in forest economics and policy from the University of California–Berkeley and a BS in environmental earth sciencesfrom Stanford University. He is active ontechnical committees of the Northern Cali-fornia SAF and has served on numerous na-tional and state scientific review task forces.




Subject Index Accounting neutrality, S33t Afforestation, S35

Baseline requirements, forest offset projects, S35

Billion Ton Report, S24Bioenergy, managing forests, S7

Biomass Commercial Utilization Grants Program, S26

Biomass Crop Assistance Program (BCAP), S26Biomass energy production, S30–S32

balance and benefits, S31

Biomass feedstocks, S24–S26availability, S24

economics, S25–S26

environmental consequences and constraints, S25

factors that affect supply, S24–S25government policy, S26

landowner preferences, S26

use and issues, S10Biomass Research and Development Act of 2000, S26

Bituminous coal, comparison of GHG emissions, S32 f

Boreal forests, S21–S23, S22 f

Building codes and procurement policies, S39Business-as-usual case (BAU), S35–S39

California Air Resources Board (Climate Action Re-serve CAR), S36

Carbon, see also Forest carbon

Carbon accounting, S7

Carbon-cycle neutrality, S33t Carbon emissions

determination of neutrality, S32, S33t

floor structure, S28 f from manufacture of wood products, S27, S28t

Carbon flux

estimates by pool, US, S16–S17from forest disturbances, S17–S19

US forestry sector in 2008, S16t

Carbon framework, S11, S13, S13 f Carbon pools

forest offset projects, S35

sustainable management, S32 f

Carbon sequestration calculation procedures, forest off-set projects, S35

Chicago Climate Exchange (CCX), S35–S36

Climate change, disturbances and mortality, S22–S23Climate-forest interactions, S10, S21–S23

Combined heat and power systems (CHP), S30–S31

Combustion, S30–S31Coordinated resource offering protocol (CROP), S24

Crediting period, forest offset projects, S35

Disease, forest mortality, S18Electric power plants, comparison of GHG emissions,

S32 f Eligibility, forest offset projects, S35

Energy, wood, S30–S32combustion and gasification, S30–S31

substitution, S10, S31

Energy fluxes, climate-forest interactions, S22–S23Energy Policy Act of 2005, S26

Environment, consequences of biomass use, S25

Food, Conservation, and Energy Act of 2008, S26

Forest, management, S35

Forest biomass

energy from, S13

total estimated annual flux, S20t Forest biomes

area, storage, and gross photosynthesis, S21t

climate-related characteristics, S21–S22

forest-atmosphere fluxes and, S21, S22 f

Forest carbon offset projects, S7, S35–S39

additionality and baseline settings, S36

estimates of forest carbon flux, S37

market leakage, S37

policy alternatives to, S39

reversals and permanence, S37

temporal and spatial boundaries, S37

variation among protocols, S36

Forest carbon, see also Carbon

accounting, S19

atmosphere fluxes, S22–S23dynamics, S7

fire effects, S17–S18

flux from disturbances, S17–S19

flux in US sector in 2008, S16t

insects and disease, S18

land-use change, S18–S19

management and capture, S15–S17

managing benefits and risks, S39

policies, S7, S10, S13, S35–S39

stocks and flows, S9, S14–S20

storage in wood products, S11, S27, S29 f

sustainably managed, S13

total estimated annual flux, S20t

trajectories, S14–S15, S16trajectories under sustainable management, S34 f

weather-related disturbances, S18

Forest conservation, S35

Forest growth, removals, and mortality, US, S24 f

Forest Inventory and Analysis (FIA), S17–S19

Forest Offset Programs, examples, S36

Forest preservation, S35

Forest products, versus energy-intensive materials, S13

Forests

integrating into a rational policy framework, S11,

S40

management, S7

US area of land, S19t

Forest-scale trajectories, S15

Forest soils, carbon trajectories, S16–S17Fossil fuel-produced energy, S13

Fossil fuels, S27–S34

consumption, entire structures, S28

exterior wall designs, S29t

floor design, S29t

Gasification, S30–S31

G i i S25

Greenhouse gases (GHG)

comparison of emissions, S32 f

executive summary, S9forest carbon policies and, S13, S35–S39

Health Forests Restoration Act of 2003, S26

Inherent carbon neutrality, S33t Insects, forest mortality, S18

Intergovernmental Panel on Climate Change (IPCC),

forest carbon policies and, S35–S39Kyoto Protocol, forest carbon policies, S35–S39

Land-use change, effects on forest carbon, S18–S19

Leakage, forest offset projects, S35Life-cycle assessment methods (LCA), S7, S27

Life-cycle neutrality, S33t

MAI, definition, S15

Mandatory GHG reduction programs, forest offsetprojects, S36

Market price biomass, S24

Methane emissions, from wood degradation, S30Northeast Regional Greenhouse Gas Initiative, S35–

S36Offset neutrality, S33t Performance-based biomass, S24

Permanence and reversals, forest offset projects, S35

Potentially available biomass, S24Reforestation, S35

Renewable biomass, definitions, S26

Resources Planning Act, S19–S20

Roundwood, US industrial, S19 f Safe Drinking Water Act, S39

Stand-scale trajectories, S14

Substitution effect, S10, S11, S40Substitution neutrality, S33t

Supply curve biomass, S24

Sustainable management

carbon trajectories under, S34 f forest carbon pools, S32 f

Technically available biomass, S24Temperate forests, S21–S23, S22 f Tillamook Fire, Oregon Coast Range, S18

Timberlands, annual flux, 2006, S20 f

Tongass National Forest, S15Toxic Release Inventory, S39

Tropical forests, S21–S23, S22 f

Voluntary cap-and-trade systems, forest offset projects,S36

Voluntary emissions offset protocols, forest offset proj-

ects, S36 Water fluxes, climate-forest interactions, S22–S23

Weather, effects on forest carbon, S18

Western Climate Initiative, S35 Wood energy, S30–S32

Wood-fossil fuel substitution effects, S27–S34

Wood products

carbon storage in, S11, S27, S40emissions from manufacture, S27, S28t

end-of-life considerations, S28–S29

fate of in solid waste sites, S30t d h lf l f d

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