October 2017 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). Figure 1. Global emissions (Mt CO 2e yr -1 ). 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 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. 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 CO 2e yr -1 ) Emissions from deforestation (Mt CO 2e yr -1 ) Total emissions (Mt CO 2e 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 3. Proportional representation of emissions by activity and region. 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.
caption + credit Figure 4. Total forest emissions (t CO 2e 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. 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 (CO 2e) emissions to the atmosphere 1. 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.
Figure 5. Global map showing country sizes proportional to total degradation emissions (Mt CO 2e yr -1 ). 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 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) activities 2 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 CO 2e 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 CO 2e 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 CO 2e 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 CO 2e 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 restoration 4 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 (tco 2e ha -1 yr -1 ) Plantations Natural Regeneration Mangrove Restoration Agroforestry Commitment (million ha) 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 Challenge 5 and FLR Commitments 6 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 11. Map of the potential removals (Mt CO 2e) that participating countries can achieve after 20 years under the Bonn Challenge 5 and the FLR 6 Commitments. 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 12. Bonn Challenge and FLR Commitment compared to total emissions from deforestation and forest degradation (bubble size).