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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).
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