carbon sequestration in forests and soils

Carbon Sequestration inForests and Soils

Roger Sedjo1 and Brent Sohngen2

1Resources for the Future, Washington, DC 20036; email: [email protected]

2Department of Agricultural, Environmental, and Development Economics,

The Ohio State University, Columbus, Ohio 43210

Annu. Rev. Resour. Econ. 2012. 4:127–53

The Annual Review of Resource Economics is

online at resource.annualreviews.org

This article’s doi:

10.1146/annurev-resource-083110-115941

Copyright © 2012 by Annual Reviews.

All rights reserved

1941-1340/12/1010-0127$20.00

Keywords

climate change, GHGs, deforestation, biomass, policy,

permanence, forest management

Abstract

Forests can play a large role in climate change through the seques-

tration or emission of carbon, an important greenhouse gas; through

biological growth, which can increase forest stocks; or through

deforestation, which can increase carbon emissions. Carbon is cap-

tured not only in tree biomass but also in forest soils. Forest man-

agement and public policy can strongly influence the sequestration

process. Economic policies can provide incentives for both forest

expansion and contraction. Systems that provide prices for carbon

sequestration or taxes for emissions can have important effects on

emission and sequestration levels. Issues involve carbon additionality,

permanence, and leakage. Forest measurement, monitoring, and veri-

fication also provide serious challenges. Various economic models

are used to estimate the effects of various economic policies on

forest carbon stocks. Estimates from the literature of some actual

and potential levels of forest carbon are presented.

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INTRODUCTION

Concerns about climate change and global warming are focused extensively on the buildup

of atmospheric greenhouse gases (GHGs). Carbon is an important greenhouse gas with

respect to its global warming influences. Biological systems, including forests, can store,

capture, and release carbon. Biological growth draws carbon from the atmosphere.

Forests, due to their long life and potentially considerable mass, can and often do have

large volumes of carbon held in their cells. In essence, forests act as carbon silos, with net

biological growth increasing their held volumes of carbon. Biological decline or destruc-

tion, e.g., via decomposition or fire that destroys biological material, releases carbon—

generally back into the atmosphere. Soils can also be a vehicle to sequester and hold

captive carbon. Indeed, soils rich in carbon are often soils exceptionally suited to biological

growth, particularly in agriculture. This article discusses issues related to carbon seques-

tration by forests and soils, with a view to the global change issues, the role that forests

and soils play, and the activities that might affect that role in the future.

BIOLOGICAL BASIS FOR CARBON SEQUESTRATION IN SOILSAND FORESTS

Carbon sequestration is the process of capture (through photosynthesis) and long-term

storage of atmospheric carbon dioxide (CO2). Sequestration is possible through a range of

processes, including those occurring naturally in plants and soils. In recent years, carbon

sequestration and reduced emissions from avoided deforestation have received more atten-

tion as methods to help reduce the buildup of greenhouse gases in the atmosphere.

Biological growth involves the process of a plant utilizing CO2 from the atmosphere:

The plant draws the carbon into its cells and releases oxygen (O2) back into the atmo-

sphere. The destruction of biological matter essentially reverses this process: Carbon is

released back into the atmosphere, where carbon combines with two O2 atoms to form CO2.

Forests and soils sequester atmospheric CO2 within their biomass or in organic matter

that is stored in the ground. Oceans store most of the world’s carbon, but forests and soils

store most of the carbon sequestered within land. Worldwide, forests store approximately

47% of total global carbon (Malhi et al. 2002). The US Environmental Protection Agency

(EPA) reports that in 2008, US forestland stored approximately 75% of the net CO2

sequestered within US land (EPA 2010). Forestland includes aboveground biomass,

belowground biomass, dead wood, litter, and soil organic carbon. To break that percent-

age down on a finer scale, forests sequestered approximately 59% of the net CO2 stored

within US land, whereas soil sequestered approximately 16% of the net CO2 stored

within US land (EPA 2010).

Carbon Sequestration in Forests

In forests, carbon is sequestered within tree biomass. More than 50% of dry tree biomass is

carbon (Malhi et al. 2002). Biomass can be any part of living or nonliving tree tissue, for

example, the trunk, branches, leaves, or roots. In cells, carbon is stored within plants’ cell

walls. Plant cells, unlike animal cells, have cell walls that provide structure and support for

the organism. Cell walls are made of fibers of cellulose and/or lignin. Carbon is needed to

build cellulose and lignin compounds and therefore becomes sequestered within the plant tissue.

128 Sedjo � Sohngen

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But how does carbon get there? CO2 is necessary for photosynthesis, a biological

process critical for plant growth. Photosynthesis is the process of using sun, water, and

CO2 to create glucose and O2. Glucose, a simple sugar, is food for the plant and is necessary

for plant survival and growth. For photosynthesis to occur, CO2 is captured from the

atmosphere through stomata (singular: stoma), small openings that are on the plant’s epi-

dermis (specifically the leaves or stem) and that are used for gas exchange. Some of the

glucose produced by the plant is used to create cellulose to build up the plant’s tissue. As the

plant produces more sugar and grows, more carbon is sequestered within the plant’s tissue

(White 2010). Therefore, as trees within the forest grow, the forest sequesters more carbon

within tree biomass. Net carbon uptake of forests is greatest when the trees are still young

and growing.

Although forests are able to sequester a lot of carbon, they also release some CO2 back

into the atmosphere. CO2 is an end product of cellular respiration, a biological process that

occurs both in plants and in animals. During cellular respiration, glucose bonds are broken

down to release energy to produce adenosine-50-triphosphate (ATP). In plants, the CO2

from cellular respiration can be recycled for photosynthesis but is released into the atmo-

sphere at night, when no photosynthesis occurs.

CO2 is also released into the atmosphere when debris or a dead tree (or any other type

of vegetation) begins to decompose. As bacteria break down the tree biomass, the CO2 is

released. Decomposition can be slowed down if the forest canopy is thick enough to

prevent sunlight from reaching the forest floor. In addition to natural decomposition,

another source of released CO2 is tree harvesting. How quickly the carbon is released

depends on what the trees are harvested for. For example, trees cut down to make short-

lived products such as paper will release carbon very quickly. However, trees used to

make long-term products such as furniture or lumber will sequester the carbon for a long

time and will continue to act as a carbon sink until the wood decays (Ecological Society of

America 2000). The EPA (2010) estimates that in 2008, harvested wood products seques-

tered 9% of the net CO2 stored within US land.

Fires, as well as decomposition, can release a large amount of carbon sequestered

within forests. As fires burn, trees release CO2 back into the atmosphere. In 2008, the

total CO2 emitted from US fires—both wildfires and prescribed fires—was 189.7 teragrams

(1012 grams)1 (EPA 2010).

Figure 1 displays the various ways carbon can be released from forests. As Figure 1

shows, growth is the only way that CO2 is sequestered by forests. Although forests release

CO2 into the atmosphere, forests are carbon sinks. As seen in Figure 2, the net carbon

flux for forests and harvested wood has been negative.

Carbon Sequestration in Soils

Carbon is stored in soil as organic soil matter or humus. In addition to forests and forest

soils, agriculture soils are also a major carbon sink (Gonzales-Ramırez et al. 2012). Carbon

is sequestered within soil in two ways, both involving photosynthesis. The first is through

humification. As mentioned above, CO2 is captured, used by plants for photosynthesis,

and then stored within plant tissue. When plants die and begin to decompose, organic soil

matter is created from their biomass and is cycled into the soil. Organic soil matter is a mix

1This amount is included in net carbon sequestration by forests.

www.annualreviews.org � Carbon Sequestration in Forests and Soils 129

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of carbon compounds, decomposing plant and animal matter, and microbes. This organic

soil matter is then decomposed into a stable form known as humus. Humus stores carbon

and is a source of energy for microbes. The second way to sequester carbon is through

microphotosynthesis. Within the soil, photosynthetic bacteria up to 200 mm can sequester

CO2 from the atmosphere due to the fact that ultraviolet and infrared light rays are able

to reach these bacteria and power the photosynthesis process.

The carbon sequestered in soil can stay in the ground for a long period of time. Carbon

is released when microbes come in contact with humus and decompose it for energy.

Atmosphere

Livevegetation

Harvestedwood

Standing deadvegetation

Woody debris,litter, and

logging residue

Soil organicmaterial

Wood forfuel

Woodproducts

Carbon poolCarbon transfer or flux

Growth

MortalityHarvests

Harvestresidue

Consumption

Processing

DisposalIncineration

Decomposition

Decomposition

Decomposition

Decomposition

Combustion

Litterfallmortality

Treefall

Combustion from forest fires (carbon dioxide, methane)

Combustion from forest fires (carbon dioxide, methane)

Landfills

Methane flaring and utilization

Forest sector carbon pools and flows

Humification

Figure 1

Forest carbon sequestration cycle. From Inventory of US Greenhouse Gas Emissions and Sinks, EPA (2010).

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

50

0

–50

–100

–150

–200

–250

Harvested woodSoil

Forest, nonsoil

Total net change

Year

Fo

rest

sec

tor

net

car

bo

n f

lux

(Tg

yr–

1 )

Figure 2

Forest and soil net carbon flux. From Inventory of US Greenhouse Gas Emissions and Sinks, EPA (2010).


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How quickly microbes come in contact with undiscovered pockets of humus depends largely

on various conditions, including soil drainage, climate, natural vegetation, and soil texture.

Carbon Dioxide Effects on Tree and Plant Growth

Scientists are studying how plants are reacting to the increased amounts of atmosphere

CO2. Increased atmosphere CO2, sometimes termed the CO2 fertilization effect, increases

the plant’s growth rate and thus CO2 absorption, particularly for C3 plants, which include

trees and certain grasses. For example, Norby et al. (2005) find a sustained 23% response

in net primary productivity upon a doubling of CO2. However, it is not clear whether an

individual plant will absorb more total carbon or will absorb carbon only up to a certain

threshold (White 2010). Nevertheless, numerous studies show that trees can increase their

growth rate when they are not constrained by other environmental limitations. This is

particularly true for seedlings and saplings, which sequester more carbon per unit time

in a higher-CO2 environment. Most studies find accelerated growth for trees in recent

decades, when atmospheric CO2 levels have been higher than in the recent past (see review

by Boisvenue & Running 2006). Thus, faster growth resulting from CO2 fertilization

may become a tool in a program for mitigating atmospheric CO2 buildup. Finally, many

types of grasses are also of the C3 type. Such grasses increase biological growth rates in the

presence of higher CO2 levels and thereby increase the rates of carbon absorption and

soil carbon accumulation (e.g., Kummel & Johnson 2008).

PRACTICES TO PROMOTE CARBON SEQUESTRATION IN SOILSAND FORESTS

Both soils and forest are capable of sequestering large volumes of carbon. If the soil is used

for agriculture purposes, the soil management practices play a large role in the amount of

carbon sequestered. In agriculture, tilling is used to remove weeds, mix in fertilizers, and

prepare the surface for seeding. However, both tilling soil and adding fertilizer signifi-

cantly decrease the amount of carbon sequestered within soil. By soil tilling, microbes come

in contact with previously untouched humus that is quickly decomposed, and carbon is

released. In addition, limestone and dolomite are often added to soil to prevent acidification,

which in turn degrades the soil and releases CO2. Approximately 4 million tons of CO2

equivalents are released annually in the United States from the liming of soils (EPA 2010).

Forestry has a variety of options for capturing carbon. Approximately 50% of dry biomass

is carbon. Thus, any net increases in forest biomass result in increased sequestered carbon.

However, various agricultural practices can improve soil carbon sequestration (Ecological

Society of America 2000). These practices include conservation tillage, cover cropping, and

crop rotation. Conservation tillage involves minimizing the manipulation of the soils. Often

termed no-till agriculture, this approach forgoes the usual plowing phase of the planting and

harvesting process, thereby bypassing a process that disturbs the soil and promotes carbon

escape. The plowing phase is undertaken largely to reduce weeding, and under a no-till

regime, herbicides usually replace much of the plowing. Cover cropping involves planting

cover crops such as grass and clovers in between regular crop seasons to protect the soil.

The economics of no-till practices are often comparable in cost to that of traditional

approaches (e.g., Beck et al. 1998, Laukkanen & Nauges 2009). No-till practices may

ultimately benefit the farmer because maintaining adequate carbon in the soil promotes


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crop production. More carbon within the soil improves water quality, decreases nutrient

loss, and limits soil erosion. Finally, if compensation were to be provided for carbon

sequestered in soils, additional financial benefits could accrue to the farmer. However, a

study by Choi & Sohngen (2009) suggests that, although no till may be less costly, there

appear to be negative yield effects in corn. Emerging evidence about the nutrient losses

from conservation tillage also suggests that no till reduces attached phosphorous but

increases dissolved phosphorous emissions—an entirely different and potentially more

problematic problem.

FOREST OPTIONS TO SEQUESTER CARBON

The most obvious approach to sequestering carbon is afforestation: simply planting trees

on a previously unforested site. Early studies estimated the amount of carbon that could

be captured (Marland 1988) and the costs of such an activity (Sedjo & Solomon 1989).

Subsequently, a host of studies estimated the volumes and costs associated with planted

forests under a variety of situations. Literature reviews included those prepared by Sedjo

et al. (1995), Richards & Stokes (2004), and Stavins & Richards (2005). Early papers

were often crude and commonly did not consider the opportunity costs of the lands. Costs

per ton of carbon varied from low, sometimes negative values to $100 per ton of carbon

and often much more (Sedjo et al. 1995, Stavins & Richards 2005). Most of these studies

focused on carbon (as opposed to CO2, whose weight is 12/44 that of carbon). In addition

to questions of carbon sequestration costs by using forests, questions arose about the value

of the sequestration both for accounting purposes and for potential market payments.

Other approaches involved forest management. Since prior to the mid-nineteenth century,

foresters have been developing increasingly sophistical management regimes focusing on

timber volumes, quality, and market conditions and have been striving to obtain the optimum

revenues from each harvest (Faustmann 1968). These techniques consist of (a) adjusting

forestry practices to the costs and returns to various silvicultural prices and (b) considering

the price and time dimensions (discount rate) related to the length of harvest rotation.

Practices to increase timber growth rates generally increase sequestered forest carbon (Hyde

1976). These practices depend upon the site but often involve attention given to species

choice, the full stocking of the stand, replanting after harvest instead of relying on natural

regeneration, and perhaps fertilization under some circumstances (although fertilization

may involve some early GHG release). Of course, unforested land can be converted to

forestland, thereby adding to total forest carbon sequestration.

Other management adjustments sometimes involve the management of understory,

e.g., by a thinning regime that removes the smaller saplings. Although such an approach

is sometimes used to increase timber values by putting more of the growth on fewer trees,

such an approach may or may not increase the total carbon sequestered in the forest and

would need to be examined on a case-by-case basis.

Extending the harvest rotation will also allow for more carbon sequestration on the site.

Even if timber harvests occur, the average carbon held in the forest increases with an

extended rotation. Indeed, should carbon have value, forests could be managed profitably

for both timber and carbon. van Kooten et al. (1995) demonstrate that if carbon in a

standing tree has value, then the optimum financial rotation will be extended to the point

at which the carbon’s incremental value is equal to the value of the incremental tree

growth. Therefore, if forests are managed for the joint production of carbon and timber,


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the harvest will be delayed, and the forest will be managed for a longer periods of time.

In the extreme case, with sufficiently high relative values of carbon, the forest will never

be harvested for timber.

From a theoretical perspective, all the flows, positive and negative, should be mea-

sured. Empirically, however, the parameters are often difficult to determine. Furthermore,

the transactions costs of measuring all the flows may be too high to justify. Nonetheless,

these questions are not economic so much as they are policy related. Other current ques-

tions that are largely policy related include issues regarding credits for the amounts of

carbon sequestered by the forest. These questions may involve decisions as to how

various values are to be treated. For example, should the wood produced for carbon

subsequently also be used for industrial purposes? Does the forest get credit for carbon

that continues to be sequestered in its long-lived forest products? Should carbon credits

be given to wood products for their continued sequestration of carbon, even after they are

processed? Also, questions arise as to the forests’ life expectancy. How should a destroyed

forest be treated? Does temporary carbon storage that may be interrupted by a distur-

bance have value, even if it is ultimately lost? Also, which country should receive credits,

particularly when the products sold or are exported? These questions persist.

Finally, actions could be taken to reduce carbon emissions from forests directly by

reducing deforestation and degradation, particularly in the developing world, where defor-

estation is greatest. Reducing emissions from deforestation and degradation (REDD) was

part of the 2007 Bali Roadmap in the UN Framework Convention on Climate Change

(UNFCCC). An outcome of the 2010 UNFCCC conference was an agreement for devel-

oped nations to pledge financial aid for developing countries to mitigate GHG emissions,

deploy clean energy technologies, and manage forests. Programs are under way in devel-

oping countries to provide financial incentives via payments to landholders to maintain

existing forested areas that might otherwise be harvested and forestland that might other-

wise be converted to other uses. The gradually expanded REDD program (REDDþ) pro-

vides financial payments for investments in new forests and support for the development

of systems to better administer, manage, and protect existing forested areas. An area of

increasing interest is compensation for enhanced biodiversity.

A GENERAL ECONOMIC MODEL OF CARBON SEQUESTRATION

The value of land in forests has long been described with the Faustmann (1968) formula.

This formula shows the present value of future timber flows from forestland, starting

with bare land in the present. Hartman (1976) extends this to include general nonmarket

benefits associated with timber, and Englin & Callaway (1993) and van Kooten et al.

(1995) illustrate how the forest valuation problem could be augmented with carbon prices.

Sohngen & Brown (2008) use an approach similar to that of van Kooten et al. (1995), but

they rent carbon in the forest and pay for carbon stored in marketed products. Renting

carbon in forests assumes that landowners have the property right for the carbon stored

on their land and that they are able to sell the annual rental equivalent of holding the carbon

out of the atmosphere for each year they store it.2 When landowners harvest their forests,

2When bare land is considered, renting carbon stock and paying the carbon price for permanent storage in products

have a present value equivalent to paying the carbon price for annual sequestration and taxing emissions when they

occur if rental rates are calculated as rental rate ¼ rPC and under the assumption that carbon prices are constant.


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some dead wood remains on the site and is assumed to decompose immediately (this

scenario further assumes that the carbon from decomposing material does not enter soil

pools). The remaining wood is assumed to move into wood products. The augmented

Faustmann formula, which includes carbon rentals, is written as

Bare land valueW tð Þ ¼

PSfSt

� �Vt m0ð Þ 1þ rð Þ�t þ PCaVt m0ð Þ 1þ rð Þ�t þ rPC

Xt

n¼1

bnVn m0ð Þ 1þ rð Þ�n � CostP m0ð Þ

1� 1þ rð Þ�t� � ,

ð1Þwhere Vt(m0) is biomass yield or growing stock volume (cubic meters per hectare) at

age t given management inputs at planting time of m0; fSt is the proportion of biomass

used for wood products at age t; a is a factor for converting harvested biomass to

permanently stored carbon; bt is a conversion factor converting biomass yield to carbon;

CostP denotes planting costs; and r is the interest rate.

The first part of Equation 1— PSfSð ÞVt m0ð Þ 1þ rð Þ�t—represents the value of har-

vesting the stand and selling products in markets. The second part of Equation 1—

PCaVt m0ð Þ 1þ rð Þ�t—is the value of storing carbon permanently in markets at the time

of timber harvest. The term a is a parameter that can be calculated from data on how

long wood products remain utilized in markets and how long material is buried in land-

fills before decomposing. Permanent storage is valued at the market price for carbon

sequestration, PC.

The term rPCXt

n¼1

bnVn m0ð Þ 1þ rð Þ�n in Equation 1 accounts for the annual rental value

of carbon sequestered on the stump. Carbon on the stump is rented annually at the

rate of rPC.3 Because the volume of carbon on the stump grows over time, the annual value

of rental payments for carbon sequestration increases over time. The term bn converts

timber volume to carbon. As noted in Brown et al. (1999) and Smith et al. (2003), carbon

per unit of timber volume changes over time, so the carbon conversion factor for timber

on the stump is a function of time. We use conversion factors derived from Smith et al.

(2003) to determine the carbon content of stands. Equation 1 thus accounts for timber

value and carbon value, where carbon value is the sum of the present value of carbon

stored on the stump and the present value of permanent storage in marketed products

when harvests occur.

Equation 1 illustrates the value of forestland when carbon has value. Land converts

from agriculture to forests (e.g., afforestation) when the value of land in forests exceeds the

opportunity cost of land, which is the land value in other agricultural uses such as grazing

or crops. Land thus converts to forests when

W tð Þ > OppCost tð Þ. ð2ÞEquation 1 can also be used to show how improvements in management could be under-

taken to enhance carbon sequestration. One management change would be to alter the

3This rental rate is determined by assuming that the price of carbon, PC, is the present value of future damages

and that PC remains constant over time. Renting one ton of carbon stored in forests for one year is thus worth rPC.

The term can be adjusted if carbon prices are assumed to rise over time.


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rotation age (Sohngen & Brown 2008). Another change would be to increase the man-

agement level at the time of replanting, perhaps by better controlling competing species

the first few years the stand is growing. This effect could be assessed by altering the

parameter m0. Table 1 provides recent estimates of European land resources and car-

bon yields over various time periods through the use of different modeling approaches

(Ovando & Caparros 2009).

To assess deforestation, Equation 2 needs to be modified. Land is deforested if the value

of the land in the next-best use (i.e., the opportunity cost) plus the value of the timber that

could be harvested immediately when deforesting plus the value of the carbon in stored

forest products is greater than the value of the carbon stored in the stand. Because defores-

tation occurs mostly in mature forests, we assume that the decision to deforest can be

written as the carbon price times the carbon stored in the forest:

Deforest if PSjSt

� �Vt m0ð Þ þ PCaVt m0ð Þ þOppCost tð Þ > PCbtVt m0ð Þ. ð3Þ

As the value of carbon increases, the value of the standing stock of carbon rises. In most

tropical countries where deforestation occurs, timber is only a small part of the value

associated with deforestation. Therefore, the values in the first two parts of the left-hand

side of Equation 3 are relatively small and have a limited impact on the decision to hold

forest or to convert the land to agriculture.

Some estimates of the values in Equations 1–3 for various species are shown in Table 2.

Columns 1–3 are W(t), shown in Equation 1 above. Given a carbon price of $100 per ton

of carbon, the carbon values for most timber types (shown in columns 2 and 3) are sub-

stantially more than the value of the timber. Thus, carbon prices in this range could cause

substantial afforestation, given the importance of carbon on the stump. In areas where

mature forests are being cleared for agriculture, one must compare the value of timber

with the value of carbon in the mature forests, as shown in Equation 3. Mature forests

contain large amounts of carbon in aboveground stocks. For instance, mature tropical

rainforests in Brazil may contain 111 tons of carbon per hectare, and when this carbon is

valued at $100 per ton, the value of the standing carbon is $11,100 per hectare. This value

is likely to be substantially more than the value of agricultural activities on the same land.

Putting a price on carbon could strongly affect how land is used. Existing research

suggests that large areas of land will shift to forest if carbon is priced on the landscape.

For example, Lubowski et al. (2006) suggest that a carbon price of $100 per ton of carbon

could produce approximately 600 million tons of carbon abatement per year through

afforestation. Given that approximately 1.4 tons of carbon per hectare year can be stored

in US forests, this discussion suggests that approximately 400 million additional hectares

of land would be planted in US forests. For the same carbon price, the model by Murray

et al. (2005) suggests only approximately 25 million additional hectares, and the model

by Sohngen & Sedjo (2006) suggests approximately 41 million additional hectares.

ECONOMIC METHODS FOR MEASURING COSTSOF CARBON SEQUESTRATION

There are various methods for calculating the costs of carbon sequestration (e.g., Stavins &

Richards 2005). These methods are typically placed into one of three categories: bottom

up, econometric, and optimization. Bottom-up methods refer to studies that build estimates


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Table1

Landdem

andandpotentialquantities

ofcarbonsequesteredin

Europe.From

Ovando&

Caparros(2009)

Study

Region

considered

Landresources

(Mha)

Tim

ehorizon

orperiod

Carbonyields

(tCha�1year�

1)

Potentialmitigation

estimates(M

tCyear�

1)

Approach

a:models

Approach:

scenarios

Carbon

prices($

tC�1)

Klijn

etal.

(2005)

EU-25

6.7–14b

2010–2030

0.0–4.0

c24

IMAGE

2.2/CLUEGTAP

(IM

,RF,DD)

IPCC/SRES

Strengers

etal.(2008)

OECD

and

Western

Europed

�13

2025

2.2–3.4

�41e

IMAGE

2.2/G

TAP/FAIR

(IM

,RF,DD)

IPCC/SRES

<350

�20

2100

�160

<600

Sohngen

&

Mendelsohn

(2003)

Europe

(excluding

FSUStates)f

8.5

2010

Notspecified;

estimations:

1.5–2.1

g

200

Globaltimber

modeland

DIC

Emodel

(SEM

,RF,DD)

Expectedclim

ate

changedamage

(minim

um)

7.14

12.8

2050

700(12.5)

29.87

25.9

2100

1,700(20.0)cumulativeh

61.34

22.3

2010

300

Uncertain

clim

ate

changedamage

(maxim

um)

21.8

39.8

2050

1,300(25.0)

92.19

66

2100

4,300(60.0)cumulativeh

187.5

Tavoni

etal.(2007)

Europe(W

estern

Europeand

New

Europe:

EU-10)

14.1

2022

1.5–2.1

g45

Globaltimber

modeland

WITCH

(SEM

,RF,DD)

BaUCO

2

stabilization:

550ppm

57

42.7

2052

100

113

63.5

2092

151

271

aBaU,businessasusual;DD,dem

anddriven;IM

,integratedassessm

entmodel;RF,resource-focusedapproach;SEM,sectorialequilibrium

model;SOM,soilorganicmatter.

bNet

changein

forestareaisestimatedforA1andB1EURURALIS

implementationoftheIPCC/SRESscenariosin

2030(K

lijn

etal.2005).

cCarbonsequestrationestimatesofKlijn

etal.(2005)are

basedoncountry-specific

carbonyield

figuresofJanssenset

al.(2005).Theseestimatesrangefrom

0to

1.5

tC

ha�1year�

1)

insouthernandnorthernEuropeanforest

andrangefrom

1.6

to4.0

tC

ha�

1year�

1in

temperate

centralEuropeanforest.

dExcludingtheEuropeanmicrostates,OECD

andEasternEuropecover

autilizedagriculturallandareaclose

to211Mha(O

vando&

Caparros2009,table1).

eApproxim

ated(�

)values

are

taken

from

Strengerset

al.(2008)figuresfortheB2IPCC/SRESscenario.

f Europeanterritory

excludingform

erSovietUnioncountries(Estonia,Latvia,andLithuania)em

bracesclose

to204Mhaofutilizedagriculturallands.

gEstim

ates

from

Ovando&

Cap

arros(2009)arebased

ontheaveragean

nual

gross

increm

entsper

hectare

ofexploitab

leforestin

EuropeofKuusela

(1994,p.35),whichisthereference

that

Sohngenet

al.(1999)give

forEuropeancountriesdataforestimatingtimber

yieldfunctions.Thecarbonstorage

param

etersforEuropeanforestincludeatotalbiomass/merchan

tablebiomass

ratiothat

varies

from

1.6

to1.9,acarbon/biomassproportionof0.5,an

dawooddensity

of0.4

tm

�3(Sohngen&

Sedjo

2000).

hParentheticalestimatesofannualcarbonsequestrationare

from

Ovando&

Caparros(2009)andare

basedonSohngen

&M

endelsohn’s(2003)cumulativecarbonsequestration

values

by2010,2050,and2100.


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on the basis of inputs into economic production processes. Data on the inputs are combined

with price information from markets to determine how costly differently activities are.

With bottom-up studies, input and output prices are exogenous and given by markets.

Examples of bottom-up studies include Moulton & Richards (1990) and more recently

Sohngen & Brown (2008).

Econometric studies utilize statistical methods to estimate the costs of shifting from

one activity to another. Such studies rely on observations from historical land use or

land management and prices to determine how past price changes or policy shifts have

influenced land use or management. The statistical models are then used to infer

future changes on the basis of the model results. As with bottom-up studies, econo-

metric approaches most often assume that input prices are fixed or given. Examples of

econometric approaches include Plantinga et al. (1999), Stavins (1999), and Lubowski

et al. (2006).

Optimization approaches model markets by assuming that consumers and producers

make optimal decisions about land use and management. Often, optimization approaches

maximize the present value of welfare over time and are thus dynamic or forward looking.

Optimization approaches allow timber, crop, or carbon prices to be determined endoge-

nously. Examples of optimization approaches include Adams et al. (1999), Sohngen &

Mendelsohn (2003), Murray et al. (2005), and Sohngen & Sedjo (2006).

Each approach has pluses and minuses. Bottom-up studies can be fairly easily con-

ducted with limited data and can often provide a first-cut estimate of the costs. Such

estimates may prove vital for deciding whether specific actions in a given region are worth

investigating further or whether the costs of such actions are too high. However, because

prices are assumed to be fixed, bottom-up approaches may seriously underestimate the

aggregate costs of carbon mitigation activities.

Table 2 Value of forestland in timber and carbon with a carbon price of $100 per ton of carbon

Bare land values Old growth

(1) (2) (3) (4) (5)

Region Timber value

(NPVa)

Rental value

of carbon (NPV)

Value of market

storage of

carbon (NPV)

Value of mature

forest harvest

Value of carbon

in standing

mature forests

Southern pine plantation $3,157 $2,068 $1,298 $8,964 $11,053

Douglas fir plantation $2,715 $4,392 $1,923 $20,040 $22,789

Midwestern oak/hickory $291 $2,302 $566 $9,676 $11,595

Boreal forest (Canada) $155 $1,551 $341 $5,063 $9,439

Boreal forest (Russia) $10 $93 $133 $1,170 $3,169

European hardwoods $78 $325 $1,062 $33,819 $11,052

Tropical rainforest (Brazil) $197 $3,512 $172 $5,513 $11,172

Tropical rainforest

(Southeast Asia)

$175 $4,717 $168 $4,223 $23,263

aNPV denotes net present value.


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Econometric studies take substantially more effort than do bottom-up studies. Because

econometric studies rely on actual data and can be calibrated to historical outcomes, econo-

metric methods are widely considered to be the strongest and most appropriate methods for

calculating costs. However, econometric studies require access to good data and knowledge

of the statistical methods and may thus not be applicable in all circumstances. Furthermore,

like bottom-up studies, econometric studies assume that input and output prices are exoge-

nous, so if land use change or carbon sequestration becomes large, the parameter estimates

may no longer be applicable. Statistical methods have been used largely in the climate area to

assess potential land use change between agriculture and forestry, although some studies

have been used to assess agricultural management options. So far, econometric models have

not been used to assess management options in forestry.

Optimization studies, like econometric studies, require much more effort than do

bottom-up studies. Optimization studies are less data intensive than are econometric

models, but they require substantial programming and computing resources. Optimiza-

tion approaches can be applied in a broader set of areas than can econometric studies

because there are fewer data requirements, but optimization approaches require com-

puter programming and specialized software in many cases. Optimization approaches

account for price changes associated with different policy proposals and may thus be better

suited for larger-scale analysis that may have price effects. Such approaches have been used

to assess land use change and land management.

REVIEW OF CARBON SEQUESTRATION ESTIMATES

As noted above, numerous studies estimate the marginal cost of carbon sequestration.

There are a number of reviews of these estimates in the literature (e.g., Sedjo et al. 1995,

Richards & Stokes 2004, van Kooten & Sohngen 2007). Sohngen (2010) reviews the more

recent literature and compiles a current set of marginal-cost estimates (Table 3). These

results indicate that at $30 per ton of CO2, 6.8 billion tons of CO2, or approximately 15%

of the total emissions of CO2 and CO2 equivalents, can currently be sequestered. Perhaps

most surprising is that the economic estimates presented in Table 3 indicate that the largest

share of carbon potential is derived from avoided deforestation (REDD) and forest

management. The focus of policy over the past 10–15 years has been afforestation, and

although afforestation is important, it represents the smallest potential share of carbon.

THE TIMING AND BENEFITS OF FOREST CARBON SEQUESTRATION

One interesting issue to consider is when the different forestry options should be employed.

Economically, it makes sense to focus on the lowest-cost options first, but given the scale

of potential carbon sequestration, carbon prices are likely to adjust when forest carbon

sequestration is included in policy analysis. As a result, determining when different actions

should be employed becomes a fairly complex economic problem. Recent analysis by

Sohngen (2010) explicitly considers the timing of different activities through the use of a

model that integrates the forest sector with the energy sector.

This analysis finds that in the near term (over the next 20 years), reducing emissions

from deforestation could produce approximately 35% of total global carbon abatement,

whereas forest management could provide approximately 15% and afforestation could

provide an additional 15% of total abatement. By the middle of the twenty-first century


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(2050), reducing emissions from deforestation becomes a smaller portion of the global

total, providing only approximately 14% of global carbon abatement services. Forest

management and afforestation, however, increase in scale, providing 19% and 17% of

total global carbon abatement, respectively. Forest management and afforestation increase

in proportion, in part because they are higher-cost options and carbon prices will have

risen by the middle of the century but also because it takes time to put those actions in

place so that they result in carbon sequestration.

Forestry actions can substantially reduce the costs of meeting specific carbon objec-

tives. For example, many policy studies conduct cost-effectiveness analyses, whereby such

studies take the policy constraint as given and assess the least-cost options for achieving

that constraint. One such study by Tavoni et al. (2007) utilizes an integrated assessment

model that contains much detail on potential technologies to mitigate climate change to

assess a global carbon concentration limitation of 550 parts per million. Another study,

Table 3 Average annual potential net emissions reductions (in millions of tons of CO2)

through forestry for the period 2020–2050. From Sohngen (2010)a

Afforestation REDDb Management Total

TEMPERATE

United States 471 (325–2,267)c 33 291 (268–314)c 795

Canada 87d 0 148d 235

Europe 32d 0 132d 164

Russia 25d 0 414d 439

China 104d 0 348d 452

Japan 34d 0 25d 59

Oceania 24d 0 21d 45

Total (temperate) 777 33 1,379 2,189

TROPICS

South and

Central America

356d 1,209 (800–1,600)e 0 1,565

Southeast Asia 288d 402 (141–1,153)e 696d 1,386

Africa 258d 1,216 (884–1,407)e 0 1,474

India 168d 0 2d 170

Total (tropics) 1,070 2,827 698 4,595

Total (all) 1,847 2,860 2,077 6,784

aThe carbon price is assumed to be constant at $30 per ton of CO2. Data are from various studies. Cost estimates

include opportunity costs and implementation and management costs, but not MMVor other transactions costs.bREDD denotes reductions in emissions from deforestation and forest degradation.cRanges are from Adams et al. (1999), Plantinga et al. (1999), Stavins (1999), Murray et al. (2005), Lubowski et al.

(2006), and Sohngen & Mendelsohn (2007).dFrom the global timber model (Sohngen & Mendelsohn, 2003, 2007).eFrom Kindermann et al. (2008).


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Sohngen (2010), uses a less detailed integrated assessment model but examines a limit on

the overall temperature increase of 2�C. Both studies find that forest actions could reduce

carbon prices by 40–50%.

SPECIAL ISSUES AND POLICY LIMITATIONS REGARDINGCARBON SEQUESTRATION

Concerns regarding carbon sequestration in forests or soils include additionality, perma-

nence, and leakage. Also, there is the question of the feasibility and cost of measuring,

monitoring, and verification. Most proposals to assign credits to manage forest carbon

aim to reward actions that would not have happened otherwise—that is, actions that are

additional to business as usual.

Additionality commonly refers to the question of whether the incremental seques-

tered carbon under discussion is truly additional to what would be sequestered without

a program or whether that carbon would have been sequestered even without the pro-

gram. Thus, for example, if a forest were to be planted for commercial timber purposes,

the carbon captured as the forest grew would be captured without any special carbon

sequestration program or incentives. By contrast, if a forest were established strictly

to capture carbon, then this carbon would be viewed as additional and might, in some

systems, be eligible for carbon credits and compensation. Additionality requires an

initial measurement, or baseline inventory, as well as periodic monitoring to observe

inventory changes.

Permanence relates to the issue of whether the carbon is permanently sequestered or

whether it is only temporary. Most biological sequestration systems can be viewed as

temporary. For example, forests are susceptible to a wide range of natural disturbances

(e.g., fires and pests) and timber harvesting. For temporary sequestration, the payments

associated with carbon offset systems are typically less than payments associated with

permanent sequestration or emissions reductions. Moreover, carbon offset–related pay-

ments require repayments if the forests are harvested or destroyed.

Leakage refers to offsetting carbon releases related to a sequestration activity. For

example, if an area of forest is protected to prevent deforestation so as to maintain the

sequestered carbon already held captive in that forest, but if the deforestation is simply

deflected to another location, then no net sequestration is achieved, and leakage has

occurred. Indeed, the concept of leakage is quite broad. As another example, market-

generated leakage has occurred if by reducing harvest carbon continues to be sequestered

in one forest but the lower availability of timber increases the market price and results in

an increased harvest from other forests so that no net sequestration is achieved. Leakage is

particularly difficult to determine or contain because, in principle, it knows no geographic

bounds. Murray et al. (2004) estimate leakage at 10% to 90% for various activities within

the United States, and Sohngen & Brown (2004) examine leakage in an international con-

text (see also discussion in Sohngen 2010). Some forest carbon management proposals

allow discounting or rental of forest assets and transferability of the assets to account for

the possibility of their impermanence (Pfaff et al. 2000).

Taken together, leakage, permanence, and additionality require a means of measure-

ment and monitoring that provides for and maintains data in the form of a global time

series of information about global forests. Models that fail to account for these changes can

be misleading (even if contractual provisions ultimately accommodate these changes).


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Measuring, monitoring, and verification are integral parts of any carbon sequestra-

tion effort. Typically, researchers use sampling methods and regression models to estimate

volume in large, heterogeneous forests. On-the-ground inventorying approaches have been

developed and utilized for many decades, if not centuries, to estimate the volumes of the

forest stock. However, these approaches were typically undertaken to determine the avail-

ability of timber for harvests. Also, these approaches were applied largely locally to spe-

cific forest stands, although the US Forest Service used this approach for most of the

latter part of the twentieth century to estimate US forest stocks. After the 1980s, the UN

Food and Agricultural Organization periodically assessed global forestlands but relied

heavily upon information provided by the various countries. Recently developed various

remote sensing approaches use airborne or satellite approaches, usually in concert with

on-the-ground truthing (Fagan & DeFries 2009). Although these approaches are ade-

quate for many purposes, they are still limited for estimating carbon volumes in forests

(Macauley et al. 2009).

The usual approach to estimating carbon volumes and/or changes is to estimate the

forest biomass using an on-the-ground sampling procedure. The volume is converted to

biomass, which refers to the dry weight of the forest. Biomass is related to forest volume,

but the relation varies substantially, depending on tree species, forest elevation, and other

factors. Also, traditional approaches apply largely to trees suitable for commercial pur-

poses. Moreover, many forest volume-to-biomass models measure only the aboveground

biomass of growing stock volume (Fagan & DeFries 2009). However, for estimating

carbon volumes, more of the biomass is relevant. More comprehensive models for esti-

mating forest biomass by incorporating the biomass of standing dead trees, the biomass

of root systems, and differences in species are being developed (Smith et al. 2003). Never-

theless, these approaches estimate only biomass using conversion factors, and the carbon

component still needs to be estimated.

Dry woody biomass is consistently approximately 50% carbon, so rough estimates of

forest carbon content are obtained by multiplying the dry weight of a forest by 0.5 (Smith

et al. 2003). Improvements in the constituent factors for carbon estimation will lead to

better carbon measures. Until then, the default value of aboveground carbon in forests is

generally accepted to be 47% to 50% of aboveground dry biomass value, although carbon

values may vary between 43% and 55%, depending on the part of the trees and on the

forest climate (Metz et al. 2007, Brown et al. 2009, Fagan & DeFries 2009). The National

Research Council (2010) cites research reporting that the standing biomass of tropical

forests is uncertain by a factor of two. Thus, estimates of the annual flux of CO2 released

through forest clearing are uncertain by the same amount.

Estimating soil carbon is even more complicated than for aboveground forest vegeta-

tion. For soils, techniques for measuring soil carbon and changes in soil carbon though

time have not been well developed on a large scale. Hence, measuring soil carbon requires

a system of sample tests. For agriculture, soil carbon can vary depending on practices,

e.g., no till. Such practices require regular on-the-ground sampling and can be a relatively

expensive process (e.g., Mooney et al. 2004). Testing for forest soil carbon changes requires a

similar on-the-ground approach.

In sum, measuring, monitoring, and verification are currently not simple or low cost.

New technology offers the potential to substantially improve the process with the further

development of remote sensing approaches. Remote sensing, e.g., radar (which transmits

and receives pulses of energy), tends to give fairly accurate measurements of volume,


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but only in low-density forests (the radar saturates and may not be able to penetrate the

forest when it is too dense). A newer technique, LIDAR (light detection and ranging),

uses scattered light to find the distance to an object. LIDAR can penetrate the tree canopy

and provide data on the topography of the underlying terrain with reasonable accuracy

(Fagan & DeFries 2009). Although these approaches could improve approximate mea-

surement and substantially improve verification, conversions of forest volume estimates to

precise biomass measurements would remain problematical, and costs could remain high.

The first satellite-based LIDAR for observing land is not expected until 2015 or later. Even

then, the approach will be optimized for observing other types of resources (such as ice

formations or volcanic processes), not forest measurement (see http://desdyni.jpl.nasa.gov/

mission for a discussion of this approach).

DISCLOSURE STATEMENT

The authors are not aware of any affiliations, memberships, funding, or financial holdings

that might be perceived as affecting the objectivity of this review.

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viii

Annual Review of

Resource Economics

Volume 4, 2012 Contents

Prefatory

A Conversation with Arnold HarbergerArnold C. Harberger and Richard Just . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Environmental Economics and Public Policy

Adoption Versus Adaptation, with Emphasis on Climate ChangeDavid Zilberman, Jinhua Zhao, and Amir Heiman . . . . . . . . . . . . . . . . . 27

Including Jobs in Benefi t-Cost AnalysisTimothy J. Bartik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

Behavioral Economics and Environmental PolicyFredrik Carlsson and Olof Johansson-Stenman . . . . . . . . . . . . . . . . . . . . 75

Environmental Tax Reform: Principles from Theory and PracticeIan W.H. Parry, John Norregaard, and Dirk Heine . . . . . . . . . . . . . . . . 101

The Impact of Agricultural and Natural Resource Management on Global Warming

Carbon Sequestration in Forests and SoilsRoger Sedjo and Brent Sohngen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127

An Overview of Carbon Offsets from AgricultureJimena González-Ramírez, Catherine L. Kling, and Adriana Valcu . . . . 145

Measuring Indirect Land Use Change with Biofuels: Implications for PolicyMadhu Khanna and Christine L. Crago . . . . . . . . . . . . . . . . . . . . . . . . . 161

Agricultural Risks, Markets, and Trade

Commodity Prices over Two Centuries: Trends, Volatility, and ImpactJeffrey G. Williamson . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185

On the Value of Agricultural BiodiversitySalvatore Di Falco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207

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The Economics of the Food System RevolutionThomas Reardon and C. Peter Timmer . . . . . . . . . . . . . . . . . . . . . . . . . 225

Agricultural Trade: What Matters in the Doha Round?David Laborde and Will Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265

Resource Economics

(The Economics of) Discounting: Unbalanced Growth, Uncertainty, and Spatial ConsiderationsThomas Sterner and Efthymia Kyriakopoulou . . . . . . . . . . . . . . . . . . . . 285

Taking Stock of Malthus: Modeling the Collapse of Historical CivilizationsRafael Reuveny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 303

International Trade in Natural Resources: Practice and PolicyMichele Ruta and Anthony J. Venables. . . . . . . . . . . . . . . . . . . . . . . . . . 331

The Origins and Ideals of Water Resource Economics in the United StatesRonald C. Griffi n . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 353

The New Fisheries Economics: Incentives Across Many MarginsMartin D. Smith . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 379

Errata

An online log of corrections to Annual Review of Resource Economicsarticles may be found at http://resource.annualreviews.org

Contents ix

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AnnuAl Reviewsit’s about time. Your time. it’s time well spent.

AnnuAl Reviews | Connect with Our expertsTel: 800.523.8635 (us/can) | Tel: 650.493.4400 | Fax: 650.424.0910 | Email: [email protected]

New From Annual Reviews:

Annual Review of Statistics and Its ApplicationVolume 1 • Online January 2014 • http://statistics.annualreviews.org

Editor: Stephen E. Fienberg, Carnegie Mellon UniversityAssociate Editors: Nancy Reid, University of Toronto

Stephen M. Stigler, University of ChicagoThe Annual Review of Statistics and Its Application aims to inform statisticians and quantitative methodologists, as well as all scientists and users of statistics about major methodological advances and the computational tools that allow for their implementation. It will include developments in the field of statistics, including theoretical statistical underpinnings of new methodology, as well as developments in specific application domains such as biostatistics and bioinformatics, economics, machine learning, psychology, sociology, and aspects of the physical sciences.

Complimentary online access to the first volume will be available until January 2015. table of contents:•What Is Statistics? Stephen E. Fienberg•A Systematic Statistical Approach to Evaluating Evidence

from Observational Studies, David Madigan, Paul E. Stang, Jesse A. Berlin, Martijn Schuemie, J. Marc Overhage, Marc A. Suchard, Bill Dumouchel, Abraham G. Hartzema, Patrick B. Ryan

•The Role of Statistics in the Discovery of a Higgs Boson, David A. van Dyk

•Brain Imaging Analysis, F. DuBois Bowman•Statistics and Climate, Peter Guttorp•Climate Simulators and Climate Projections,

Jonathan Rougier, Michael Goldstein•Probabilistic Forecasting, Tilmann Gneiting,

Matthias Katzfuss•Bayesian Computational Tools, Christian P. Robert•Bayesian Computation Via Markov Chain Monte Carlo,

Radu V. Craiu, Jeffrey S. Rosenthal•Build, Compute, Critique, Repeat: Data Analysis with Latent

Variable Models, David M. Blei•Structured Regularizers for High-Dimensional Problems:

Statistical and Computational Issues, Martin J. Wainwright

•High-Dimensional Statistics with a View Toward Applications in Biology, Peter Bühlmann, Markus Kalisch, Lukas Meier

•Next-Generation Statistical Genetics: Modeling, Penalization, and Optimization in High-Dimensional Data, Kenneth Lange, Jeanette C. Papp, Janet S. Sinsheimer, Eric M. Sobel

•Breaking Bad: Two Decades of Life-Course Data Analysis in Criminology, Developmental Psychology, and Beyond, Elena A. Erosheva, Ross L. Matsueda, Donatello Telesca

•Event History Analysis, Niels Keiding•StatisticalEvaluationofForensicDNAProfileEvidence,

Christopher D. Steele, David J. Balding•Using League Table Rankings in Public Policy Formation:

Statistical Issues, Harvey Goldstein•Statistical Ecology, Ruth King•Estimating the Number of Species in Microbial Diversity

Studies, John Bunge, Amy Willis, Fiona Walsh•Dynamic Treatment Regimes, Bibhas Chakraborty,

Susan A. Murphy•Statistics and Related Topics in Single-Molecule Biophysics,

Hong Qian, S.C. Kou•Statistics and Quantitative Risk Management for Banking

and Insurance, Paul Embrechts, Marius Hofert

Access this and all other Annual Reviews journals via your institution at www.annualreviews.org.

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carbon sequestration in forests and soils

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