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Policies to Reduce Emissions from Deforestation and Degradation ...

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2008; Strassburg et al. 2008). The studies use different methodologies <strong>and</strong> underlying assumptions,<br />

making direct comparison difficult. Some studies focus on the one-time benefits of a specific<br />

forestry project (Osborne <strong>and</strong> Kiker 2005). Other studies use models based on local opportunity<br />

costs aggregated <strong>to</strong> a national or multinational level (Greig-Gran 2006, Nepstad et al. 2007; Strassburg<br />

et al. 2008). Other studies use global models that construct REDD carbon supply curves at different<br />

carbon prices (Sohngen <strong>and</strong> Beach 2006; Anger <strong>and</strong> Sathaye 2008; Sathaye et al. 2005; Kinderman<br />

et al. 2006). The results of these studies are summarized in Table 2.3. Although the results<br />

vary, all but one study support the conclusion that substantial carbon benefits can be realized<br />

through REDD activities at low initial carbon prices ($10/tC or less); the exception is the McKinsey<br />

report by Enkvist et al. (2007).<br />

The McKinsey report found that reducing deforestation by 50 percent in Africa <strong>and</strong> 75 percent<br />

in Latin America could be achieved for about $183.50/tC ($50/tCO2) <strong>and</strong> abate 3 GtCO2 emissions<br />

(Enkvist et al. 2007). Enkvist et al. (2007) found that abating deforestation rates in Asia would<br />

be more expensive because of higher opportunity costs for forests. Additionally, they found that<br />

avoiding deforestation was more expensive than other forest mitigation measures.<br />

Osafo (2005), Osborne <strong>and</strong> Kiker (2005), <strong>and</strong> Silva-Chavez (2005) calculate the break-even price<br />

for carbon based on the opportunity cost of forested l<strong>and</strong> in the regions studied. Greig-Gran (2006)<br />

calculates the discounted return per hectare <strong>and</strong> not the price of l<strong>and</strong>, explaining that l<strong>and</strong> prices<br />

do not reflect avoided deforestation costs because of l<strong>and</strong> tenure issues surrounding tropical<br />

forests. These studies draw on information about current drivers of deforestation, such as the percentage<br />

of l<strong>and</strong> cleared for soy farming, cattle ranching, timber harvest, <strong>and</strong> the like <strong>to</strong> calculate<br />

the opportunity cost. Osafo (2005) accounts for revenues <strong>from</strong> agriculture but not the production<br />

costs <strong>and</strong> thus may overestimate the opportunity cost (Greig-Gran 2006). Greig-Gran (2006) includes<br />

transaction costs estimated <strong>from</strong> the administrative costs of payment-for-ecosystem-services<br />

(PES) programs in place in other countries. Specifically, Greig-Gran (2006) uses<br />

$4–$15/ha/year based on PES programs in place in Costa Rica, Mexico, <strong>and</strong> Ecuador. It is not clear<br />

how appropriate it is <strong>to</strong> extrapolate worldwide transaction costs based on these estimates. Greig-<br />

Gran (2006) does not include moni<strong>to</strong>ring costs in her calculations. However, she estimates that<br />

moni<strong>to</strong>ring costs would add $2 million/year for each of the eight countries studied. None of the<br />

other studies explicitly account for administrative <strong>and</strong> transaction costs. Osborne <strong>and</strong> Kiker (2005)<br />

note that costs for REDD pilot projects range <strong>from</strong> $0.10 <strong>to</strong> $15 per <strong>to</strong>n carbon worldwide <strong>and</strong> $1 <strong>to</strong><br />

$6 per <strong>to</strong>n carbon in Latin America, though they do not include this in their cost calculations.<br />

Sathaye et al. (2005) use a dynamic partial equilibrium model <strong>to</strong> examine the response of the<br />

forestry sec<strong>to</strong>r <strong>to</strong> carbon prices. Kindermann et al. (2006) use a spatially explicit integrated biophysical<br />

<strong>and</strong> socioeconomic l<strong>and</strong>-use model. Sohngen <strong>and</strong> Beach (2006) use a global timber model<br />

<strong>to</strong> calculate the carbon supply curves for REDD activities at different carbon prices. Sohngen <strong>and</strong><br />

Beach’s (2006) results are broken out by region, as shown in Figures 2.4 <strong>and</strong> 2.5.<br />

In regions where forests are relatively abundant, carbon s<strong>to</strong>cks are high, <strong>and</strong> deforestation rates<br />

are high, avoiding deforestation may offer the highest potential for CO2 mitigation (Trines et al.<br />

2006; Nabuurs et al. 2007; Stern 2007). Other forest mitigation measures include AR, forest management<br />

<strong>to</strong> increase the carbon s<strong>to</strong>cks of a forest, <strong>and</strong> bioenergy as a substitute for fossil fuel use.<br />

Trines et al. (2006) identify reducing deforestation in the three tropical regions (Central <strong>and</strong> South<br />

America, Africa, <strong>and</strong> tropical Asia) as three of the four forest mitigation measures with “large” potential<br />

<strong>to</strong> mitigate CO2. The fourth is forest management in North America.<br />

24 <strong>Policies</strong> <strong>to</strong> <strong>Reduce</strong> <strong>Emissions</strong> <strong>from</strong> <strong>Deforestation</strong> <strong>and</strong> <strong>Degradation</strong> in Developing Countries

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