January 2018

Global Forest GHG Emissions Database and

Global FLR CO2 Removals Database Findings and Discussion

Prepared by Blanca Bernal, Lara Murray, Gabriel Sidman, and Timothy Pearson.

In partnership with the International Union for the Conservation of Nature (IUCN), Winrock International (WI)

conducted a comprehensive analysis of emissions from deforestation, forest degradation, and potential removals

from Forest Landscape Restoration (FLR) activities. The analysis was global in scale, and resulted in the creation

of two separate databases: The Global Forest GHG Emissions Database and The Global FLR CO2 Removals

Database.

A summary of the findings is offered in this document. Please see the accompanying Methods document for

detailed information on methods and data sources applied in the development of the databases.

Global Forest GHG Emissions Database

The Global Forest GHG Emissions Database provides estimates of forest emissions at the subnational level for

all countries, as shown in Figure 1. Depicted is the emissions intensity for deforestation (red scale, top right) and

forest degradation (purple scale, mid left), which includes emissions from logging (green scale, mid right),

fuelwood collection (blue scale, bottom left), and fire (orange scale, bottom right).

This analysis reveals that developing countries have the highest emissions, attributed mostly to deforestation

and logging degradation. Developed countries generally have less forest cover than tropical developing ones

but can still have high total emissions due to fire degradation, as it is seen in Australia, Canada, and Russia.

This trend is also apparent in Figure 2 which depicts the proportion of emissions by activity among the top 20

countries with highest forest emissions. The most significant emissions activities are deforestation, followed by

logging, fuelwood, and fire. Russia represents an exception where fire is the principal source of forest emissions.

Emissions from fire are also a significant portion of the total forest emissions in Angola, DRC, Argentina, and

Bolivia.

Figure 1. Global emissions (Mt CO2e yr-1).

A breakdown of total emissions from deforestation and degradation among the top 15 countries with highest total

forest emissions is detailed in Table 1.

Table 1. Emissions (Mt CO2e yr-1) from the top 15 emitting countries.

Country Emissions from degradation

(Mt CO2e yr-1)

Emissions from deforestation

(Mt CO2e yr-1)

Total emissions

(Mt CO2e yr-1)

Indonesia 313 1,656 1,970

Brazil 285 1,483 1,768

Malaysia 132 467 599

DRC 104 339 443

China 61 302 363

Mexico 66 150 216

Colombia 20 171 191

India 135 49 184

Argentina 14 148 162

Bolivia 23 129 152

Philippines 108 43 151

Paraguay 35 111 146

Myanmar 36 102 139

Russia 131 0.013 131

Angola 60 55 114

Figure 2. Composition of forest emission sources for top 20 emitting countries. The size of the pie charts is proportional to the total forest emissions of the countries, and the slices represent the contribution of each

source to the total.

Figure 3 depicts emissions by region and activity, on a proportional basis. Asia and the Americas have the

greatest emissions overall by a wide margin.

Figure 4 offers a different perspective on the top 15 forest emitting countries, whereby the size of the bubbles

reflects the relative size of the countries. This diagram demonstrates that the total amount of forest emissions

is not necessarily proportional to country size.

Figure 3. Proportional representation of emissions by activity and region.

Emissions from Forest Degradation

Emissions from forest degradation have been commonly overlooked, yet they represent a significant proportion

of the total annual carbon dioxide equivalents (CO2e) emissions to the atmosphere1. Emissions from degradation

are relevant for developed and developing countries (Figure 5). Brazil and Indonesia are the countries with

highest yearly forest degradation rates, due mostly to degradation from selective logging (Figure 1). Figure 5

shows that forest degradation emissions come for the most part from the tropical and subtropical regions,

followed by the northern hemiboreal zone (Canada and Russia) due to relatively high emissions from forest fires.

Europe, Western Africa, and the Caribbean are regions with consistently low emissions from forest degradation.

1 Pearson et al. 2017. Carbon Balance and Management 12:3.

caption + credit

Figure 4. Total forest emissions (t CO2e yr-1) from the 15 countries with highest emissions. The size of the bubble is proportional to the country area, and its color represents its region – green for countries in the

Americas, purple for countries in Africa, red for countries in Asia, and blue for countries in Europe.

Figure 6 shows the relative impacts of the three forest degradation activities included in the analysis among the

15 countries with highest emissions from forest degradation. Indonesia and Brazil represent the highest forest

degradation emitters due to logging, but this activity is also clearly an important source of emissions in Malaysia

and the Philippines. Again, fire is significant in Russia, DRC, Canada, and Angola, and emissions from fuelwood

collection are most relevant in India, Ethiopia, China, and Pakistan.

Figure 5. Global map showing country sizes proportional to total degradation emissions (Mt CO2e yr-1).

Figure 6. Comparison of forest degradation emissions by degrading activities in the top 15 degradation emitting countries. The size of the bubble is proportional to emissions for each activity, and its color

represents region – green the Americas, purple for Africa, red for Asia, and blue for Europe.

Global FLR CO2 Removals Database

The Global FLR CO2 Removals Database provides information on the rate of CO2 removals from Forest

Landscape Restoration (FLR) activities2 at the subnational level for every country: The specific FLR activities

includes are Plantations and Woodlots, Natural regeneration, Mangrove Restoration, and Agroforestry. The rate

of CO2 removals per FLR type was estimated through a review of over 144 studies on forest restoration and tree

growth.

Plantations and Woodlots

The rate at which commonly planted woody species in plantations and woodlots sequester CO2 from the

atmosphere was estimated, including in aboveground and belowground biomass. Where sufficient data were

available, specific growth rates for climatic zones were developed to best reflect the variations in biomass

accumulation for planted species. Species for which CO2 sequestration rates were estimated include: Teak

(Tectona spp.), grown in tropical climates; eucalyptus (Eucalyptus spp.), grown in temperate and tropical

climates; other broadleaf species, grown globally; Oak (Quercus spp.), grown in temperate and tropical climates;

pine (Pinus spp.), grown globally; and other conifer species, also grown globally. The growth rates developed of

these planted species per climatic zone are shown in Figure 7.

The highest removal rates were estimated for tropical climates, and the fastest growing species (removing the

most CO2 annually from the atmosphere) were conifers and eucalyptus. Plantations and woodlots are scarce in

the boreal or hemiboreal region, but both conifers and broadleaf species grow well in this area and can represent

significant CO2 removals.

2 IUCN and WRI 2014. ROAM Handbook.

Figure 7. Removals rates (t CO2e ha-1 yr-1) for plantation species per climate (tropical, temperate, and boreal) and forest type (dry and moist/wet forest), calculated for the first 20 years after establishment.

Natural Regeneration

Removals estimates were also estimated for naturally regenerated forests. Regional removals for Asia and

Oceania, Europe, North America, Central America and the Caribbean, South America, and Africa were divided

according to precipitation regimes (dry and moist/wet forests). These are represented in Figure 8.

Europe, North America, Asia and Oceania, and Central America and the Caribbean show small differences in

growth/removal rates between dry and moist/wet naturally regenerated forest compared to the larger differences

between precipitation regimes estimated for South America and Africa.

Figure 8. Natural regeneration removal rates (t CO2e ha-1 yr-1) per region, calculated for the first 20 years since establishment.

Mangrove Restoration

The removal rates for mangrove restoration were calculated for both mangrove trees (found along

tropical coasts) and shrubs (found along tropical and subtropical coasts). The total CO2 removals for

the first 20 years after restoration are represented in Figure 9.

Figure 9. Removal rates (t CO2e ha-1 yr-1) for mangrove restoration by mangrove type, calculated for the first

20 years after establishment.

Agroforestry

In the analysis of removals from a wide range of agroforestry practices, the highest potential for removals were

see in the Latin America and Caribbean region, followed by Asia & Oceania, and then Africa. This is show in

Figure 10 below.

Figure 10. Removal rates (t CO2e ha-1 yr-1) for agroforestry activities by region of the world, calculated for the

first 20 years after establishment.

Bonn Challenge Commitments

The Bonn Challenge is a global effort to bring 150 million hectares of the world’s deforested and degraded land

into restoration by 2020, and 350 million hectares by 2030.3 Restoration efforts under the Bonn Challenge seek

to realize long-term whole-landscape restoration4 by adapting FLR strategies to national contexts to abate

climate change by reducing greenhouse gas emissions while supporting well-being and biodiversity. To the date,

40 governments and over 150 million hectares have been committed to this restoration initiative.

To assess the potential contributions FLR activities pledged under the Bonn Challenge would have,

commitments were combined with corresponding removal rates from the FLR CO2 Removals Database. The 15

countries with the highest emissions are listed in table 2, along with the average national removal rates of each

FLR activity as well as Bonn Challenge Commitments. The table also demonstrates that only eight out of the 15

countries have committed to reduce emission under the Bonn Challenge.

Table 2. Potential FLR removals in the top 15 emitting countries and Bonn Challenge Commitments. N/a (not

applicable) is listed where no commitment has been pledged to date.

Country Average removal rate during the first 20 years (tC ha-1 yr-1) Commitment

(million ha) Plantations

Natural

Regeneration

Mangrove

Restoration Agroforestry

Indonesia 7.2 3.2 2.0 2.8 29.0

Brazil 5.9 4.5 2.0 4.2 12.0

Malaysia - - - - n/a

DRC 7.0 3.9 2.0 2.9 8.0

China 4.4 3.0 2.0 3.8 15.8

Mexico 5.9 2.9 2.0 4.2 8.5

Colombia 6.9 5.0 2.0 4.2 1.0

India 6.0 3.1 2.0 3.8 21.0

Argentina 4.1 4.7 0 4.2 1.0

Bolivia - - - - n/a

Philippines - - - - n/a

Paraguay - - - - n/a

Myanmar - - - - n/a

Russia - - - - n/a

Angola - - - - n/a

3 Details at: www.bonnchallenge.org, as of May 2017 4 See: https://infoflr.org/, as of May 2017

Information on Bonn Challenge5 and FLR Commitments6 was applied to estimate the total emission removals

potential over 20 years. This is demonstrated in Figure 11. Should Indonesia and Nigeria meet their

commitments to reforest 29 and 30 million hectares (respectively), they will realize the greatest removals based

on this analysis. The highest potential for removals based on Bonn Challenge Commitments is in India, whose

target is to restore 21 million hectares.

Figure 12 offers a comparison between commitment size and total emissions. All 53 countries with Bonn

Challenge commitments are shown, ranked by the size of their commitment (million ha). Bubble size represents

their total emissions from deforestation and forest degradation.

5 Available at: www.bonnchallenge.org/commitments 6 Listed in: https://infoflr.org/countries

Figure 11. Map of the potential removals (Mt CO2e) that participating countries can achieve after 20 years under the Bonn Challenge5 and the FLR6 Commitments.

Figure 12. Bonn Challenge and FLR Commitment compared to total emissions from deforestation and forest degradation (bubble size).