The GFPM tracks 14 wood product groups (Table …...Shared Socioeconomic Pathways (SSPs) The Shared Socioeconomic Pathways (SSPs) describe plausible development of socioeconomic futures,

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Supporting Information

The Global Forest Products Model (GFPM)

The Global Forest Products Model (GFPM) is available freely upon request from http://labs.russell.wisc.edu/buongiorno/welcome/gfpm/.

The GFPM tracks 14 wood product groups (Table S1) across 180 individual countries (Table S2), and is calibrated to the most recent data reported by FAOSTAT by estimating input-output coefficients, and costs associated with manufacturing transportation - the GFPM solution for 2015 closely replicated the observations for the same year on production, consumption, prices, and net trade according to FAOSTAT.

The GFPM is solved by calculating successive yearly market equilibriums by maximizing a quasi-welfare function, as given by the sum of consumer and producer surpluses net of transaction costs: Z= 𝑃"# 𝐷"#

%&'("# 𝑑𝐷"# − 𝑃"# 𝑆"#

,&'("# 𝑑𝑆"# − 𝑚"# 𝑦"#

/&'("# 𝑑𝑌"# − 𝑐"2#𝑇"2#"2# , (S1)

where i and j refer to countries, with k wood product markets of price P as determined through end product demand D and wood supply S. The manufactured quantity of wood is denoted by Y at marginal cost m, and the quantity traded T at transaction cost (including tariffs) c. In other words, the first portion of equation (S1) is the area under the demand curve for consuming end products, while the second and third components measure the cost of production and manufacturing respectively. Finally, the last portion of equation (S1) measures the total cost of shipments. The model computes the market equilibrium subject to a number of economic and biophysical constraints, including a market clearing condition which states the sum of imports, production, and manufactured supply of a given product in a given country must equal the sum of end product consumption, exports and demand for inputs in downstream manufacturing: 𝑇2"# + 𝑆"# + 𝑌"# = 𝐷"# +2 𝑎"#7𝑌"77 + 𝑇"2#2 , (S2)

where aikn is the input of upstream product k required in the manufacture of a given unit of downstream product n.

Changes in resource efficiency are operationalized through changes in the input-output coefficients, and evolve exogenous over time according to: 𝑎"#7,9 = 𝑎"#7,9:;(1 − 𝜂"#7,9), (S3)

where ∆𝑎"#7,9 is the periodic rate of change in input-output coefficient. The demand in country i for final product k is assumed to follow a constant elasticity of

substitution:

𝐷"#,9 = 𝐷"#,9∗ B&',CB&',CDE

F&', (S4)

where 𝑃"#,9:; is last periods price, 𝛿"# is the price elasticity of demand for product k in region i, and current consumption at last periods price is given by: 𝐷"#,9∗ = 𝐷"#,9:; 1 + 𝛼"I𝑔"I,9 + 𝛼"( , (S5)

www.pnas.org/cgi/doi/10.1073/pnas.1904231116

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which is a function of last periods demand, the growth rate of GDP at time t, 𝑔"I,9, the elasticity of demand with respect to GDP, 𝛼"I, and a period trend, 𝛼"(.

The cost of shipping product k from region i to region j in any given year is assumed to be a constant elasticity of substitution form:

𝑐"2#,9 = 𝑐"2#,9∗ K&',CK&',CDE

L&', (S6)

where 𝑇"#,9:; is last periods quantity traded, and 𝜏"# is the elasticity of transport costs with respect to quantity traded. The base period transaction cost 𝑐"2#,9 is calibrated to estimated freight costs, observed export taxes and import ad-valorem tariffs, and endogenously determined product prices.

Supply is also described through a constant elasticity of substitution supply curve:

𝑆"#,9 = 𝑆"#,9∗ B&',CB&',CDE

N&', (S7)

where 𝜆"# is the price elasticity of supply for product k in region i, and current production at last periods price is given by: 𝑆"#,9∗ = 𝑆"#,9:; 1 + 𝛽"Q𝑔"9Q + 𝛽"R𝑔"9R , (S8)

where 𝑔"9Q is the periodic rate of change of forest stock in region i at time t, 𝑔"9R is the periodic rate of change of forest area, and β’s indicated respective elasticities.

Land use change enters the model through changes to forest area; assumed to be a function of evolving demographics and economic growth. An environmental Kuznets curve relationship associates changes in income per capita (Y/N) to the forest area annual growth rate, 𝑔"9R : 𝑔"9R = (𝛼"( + 𝛼;(𝑌/𝑁)"9)𝑒VW(//X)&C. α1>0 and α2<0. (S9)

With parameter estimates of α1, and α2 estimated from historical data, and αi0 calibrated such that in the base year (2015) equation (S9) predicted the observed forest area growth rate, 𝑔"9R , given the observed level of income per capita, (Y/N)it. Equation (S9) predicts negative growth rates of forest area for low income countries, which increase and become positive at higher income, and decrease progressively to zero at the highest income levels. The annual rate of change of biomass stock due to tree growth and mortality is inversely related to the forest density (residual stock level, Sit, per unit area, Ait).

For more detailed information on the model structure refer to (1), including the formulations of constraints related to trade inertia, prices, manufacturing costs, transport costs, market dynamics, linear approximations of certain constraints, and annual allowable cut constraints.

Shared Socioeconomic Pathways (SSPs)

The Shared Socioeconomic Pathways (SSPs) describe plausible development of socioeconomic futures, which focus on different challenges to climate change mitigation and adaptation (ref. (2); Table S3). While the SSPs were originally intended for climate change-related research and policy analysis, they have subsequently been used to establish indicators of alternative futures for forecasting by many non-climate related assessments (3), including downscaled SSPs that have been developed for the forest sector (Table S4). We operationalize SSPs within the GFPM to reflect country-specific demographic and economic growth using publicly available data from the

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International Institute for Applied Systems Analysis found here (https://tntcat.iiasa.ac.at/SspDb/dsd?Action=htmlpage&page=about). The aggregated evolution of population and GDP is depicted in Fig. S1. Consistent with the forest sector SSPS from Table S4, we further operationalize the SSPs within the GFPM by adjusting parameters related to openness of trade and resource efficiency (e.g. improved product recovery rates and recycling) (Table S5).

Following (4), we modeled country specific land use change assumptions under different SSPs as a function of evolving demographics and economic growth represented through an environmental-Kuznets-curve relationship with forest area. Other SSP parameters are captured within GDP and population projections, and operationalized within the GFPM modeling framework through shifts in demand, supply, technological change, transportation and shipping costs, and freedom of trade (see (4) for details).

SSP1 describes a world which gradually shifts towards a more sustainable future, with low levels of population growth that levels off around 2050. Consumption preferences trend towards products which are more sustainably minded, implying lower reliance on natural resources and emission intensive manufacturing. At the same time, the global economy experiences sustained economic growth where commodities (including forest products) are freely traded.

SSP2 describes a business as usual scenario where social, economic, and technological trends do not change significantly from current patterns. Population continues to rise moderately, and begins to level off near 2065. Economic development and income growth rises globally on its current pace, but consequently, continued inequality persists. International trade patterns are expected to be regionally focused, and bilateral and multilateral trade agreements continue.

SSP3 describes a future that is domestically focused, causing slow and unequal economic development. Global population is expected to rise rapidly, although population growth in developing countries is modest, further exacerbating the issue of income inequality. Due to the nationalist focus, policies on trade create a market where goods are not freely traded, as concerns about domestic manufacturing competitiveness are central components to domestic policy.

SSP4 describes a future of continued inequality, with specific challenges to low income countries. GDP rises modestly, and population growth plateaus around 2065. Social and economic progress is descried for middle- and high-countries only, while low income countries will continue to experience relatively low income per capita. Low income countries will have challenges in accessing an increasingly global market, with wood production increasing for rich timber producing regions.

SSP5 describes a world with few limitations to development. GDP rises exponentially through 2065, and population growth tapers off around 2050, leading to high income per capita. The global economy is strong connected through free trade, leading to rapid development in forest products markets.

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Forest Sector System Boundary

The IPCC views the harvested wood product carbon flux as part of a comprehensive picture of the forest ecosystem (Fig. S3). As the forest grows, it absorbs CO2 and converts it to carbon through photosynthesis. This carbon may remain sequestered within the tree, or within a harvested wood product, or is released when older products reach the end of their useful life and are burned, potentially offsetting fossil emissions or sent to SWDS where they decompose to varying rates. Additional atmospheric carbon benefits may arise when wood products are used to substitute away from emissions intensive products like steel, concrete, and bricks, or when used to produce energy (e.g. biofuels).

The IPCC presents four broad mitigation options available to increase removals by sinks within the forest sector system boundary, of which the first three are primarily focused within the forest ecosystem. First, a country may maintain or increase the forest area within their national boundary, and this may be achieved by reducing deforestation, degradation, or through afforestation/reforestation efforts. Second, a country may maintain or increase the carbon density within existing forests by engaging in carbon friendly forest management techniques like planting, silviculture, uneven-aged management, and tree-improvement. Third, a country may maintain or increase the carbon density within existing forests by improving forest conservation efforts including longer rotations, fire suppression, and activities that discourage invasive species and pests. Finally, carbon benefits may be achieved outside the forest ecosystem through the production and utilization of long-lived wood products, substitution for emissions intensive products, and increasing the use of biomass for energy to substitute away from fossil fuels.

Our study focuses only on the production and utilization of end-use HWPs, but the full mitigation potential of the forested ecosystem depends on the scope of the system boundary identified (5, 6). Other aspects related to substitution effects are challenging to quantify (7), but could alter the carbon benefits of HWPs somewhat if fully accounted for (8). References

1. Buongiorno, J., S. Zhu, D. Zhang, J. Turner, D. Tomberlin. 2003. The Global Forest Products Model, Structure, Estimation, and Appplications. Academic Press, Elsevier, San Diego, 301p.

2. O’Neill, B.C., E. Kriegler, K.L. Ebi, E. Kemp-Benedict, K. Riahi, D.S. Rothman, B.J.van Ruijven, D.P. van Vuuren, J. Birkmann, K. Kok, M. Levy, and W. Solecki. 2017. The roads ahead. Narratives for shared socioeconomic pathways describing world futures in the 21st century. Global Environmental Change 42: 169-180.

3. Riahi K., van Vuuren D. P., Kriegler E., Edmonds J., O’Neill B., Fujimori S., Bauer N., Calvin K., Dellink R., Fricko O., Lutz W., Popp A., Cuaresma J. C., Leimbach M., Kram T., Rao S., Emmerling J., Hasegawa T., Havlik P., Humpenöder F., Aleluia Da Silva L., Smith S., Stehfest E., Bosetti V., Eom J., Gernaat D., Masui T., Rogelj J., Strefler J., Drouet L., Krey V., Luderer G., Harmsen M., Takahashi K., Wise M., Baumstark L., Doelman J., Kainuma M., Klimont Z., Marangoni G., Moss R., Lotze-Campen H., Obersteiner M., Tabeau A. and Tavoni M. 2017. The Shared Socioeconomic Pathways and their Energy, Land Use, and Greenhouse Gas Emissions Implications: An Overview. Global Environmental Change 42:153-168.

4. Buongiorno, J. 2015a. Global modelling to predict timber production and prices: the GFPM approach. Forestry 88: 291-303.

5. van Kooten, G.C., and Johnston C. 2016. The Economics of Forest Carbon Offsets. Annual Review of Resource Economics 8: 227-246.

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6. Jasinevičius G., Linder M., Verkek P.J., and Aleinikovas M. 2017. Assessing Impacts of Wood Utilization Scenarios for a Lithuanian Bioeconomy: Impacts on Carbon in Forests and Harvested Wood Products and on the Socio-Economic Performance of the Forest-Based Sector. Forests 8(4): 133.

7. Valade, A., Bellassen V., Magand C., and Luyssaert S. 2017. Sustaining the Sequetration Efficiency of the European Forest Sector. Forest Ecology and Management 405(1). 44-55.

8. Leskinen P., Cardellini G., Gonzalez-Garcia S., Hurmekoski E., Sathre R., Seppälä J., Smyth C., Stern T., Verker P.J. 2018. Substitution Effects of Wood-Based Products in Climate Change Mitigation. From Science to Policy 7.

9. Daigneault. A., Johnston C., Korosuo A., Baker J., Forsell N., Prestemon J., and Abt R. 2019. Developing Detailed Shared Socioeconomic Pathway (SSP) Narratives for the Global Forest Sector. Journal of Forest Economics. In Press.

10. [IPCC] Intergovernmental Panel on Climate Change. 2006. Chapter 12: Harvested Wood Products. Contribution to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Vol. 4 Agriculture, Forestry and Other Land Use. Pingoud, K., Skog, K., Martino, D., Tonosaki, M., Xiaoquan, Z. http://www.ipcc-nggip.iges.or.jp/public/2006gl/pdf/4_Volume4/V4_12_Ch12_HWP.pdf [accessed April 8, 2019].

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Table S1. Forest sector commodities and market data predicted by the GFPM Commodity Production Import Export Price Fuelwood x x x x Industrial roundwood x Other industrial roundwood x x x x Sawnwood x x x x Veneer and plywood x x x x Paticleboard x x x x Fibreboard x x x x Mechanical pulp x x x x Chemical pulp x x x x Other fibre pulp x x x x Waste paper x x x x Newsprint x x x x Printing & writing paper x x x x Other paper & paperboard x x x x

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Table S2. Countries within the GFPM Country Country Country Country AFRICA N/C AMERICA ASIA EUROPE Algeria Bahamas Afghanistan Albania Angola Barbados Bahrain Austria Benin Belize Bangladesh Belgium Botswana Canada Bhutan Bosnia and Herzegovina Burkina Faso Saint Lucia Brunei Darussalam Bulgaria Burundi Costa Rica Cambodia Croatia Cameroon Cuba China Czech Republic Cape Verde Dominica Cyprus Denmark Central African Republic Dominican Republic Maldives Finland Chad El Salvador India France Congo, Republic of Guatemala Indonesia Germany Côte d'Ivoire Haiti Iran, Islamic Rep of Greece Djibouti Honduras Iraq Hungary Egypt Jamaica Israel Luxembourg Equatorial Guinea Martinique Japan Ireland Ethiopia Mexico Jordan Italy Gabon Netherlands Antilles Korea, Dem People's Rep Macedonia, The Fmr Yug Rp Gambia Nicaragua Korea, Republic of Montenegro Ghana Panama Kuwait Netherlands Guinea Saint Vincent/Grenadines Laos Norway Guinea-Bissau Trinidad and Tobago Lebanon Poland Kenya United States of America Timor-Leste Portugal Lesotho SOUTH AMERICA Malaysia Romania Liberia Argentina Mongolia Slovakia Libyan Arab Jamahiriya Bolivia Myanmar Slovenia Madagascar Brazil Nepal Spain Malawi Chile Oman Sweden Mali Colombia Pakistan Switzerland Mauritania Ecuador Philippines United Kingdom Mauritius French Guiana Qatar Serbia Morocco Guyana Saudi Arabia FORMER USSR Mozambique Paraguay Singapore Armenia Niger Peru Sri Lanka Azerbaijan, Republic of Nigeria Suriname Syrian Arab Republic Belarus Réunion Uruguay Thailand Estonia Rwanda Venezuela, Boliv Rep of Turkey Georgia Sao Tome and Principe United Arab Emirates Kazakhstan Senegal Viet Nam Kyrgyzstan Sierra Leone Yemen Latvia Somalia OCEANIA Lithuania South Africa Australia Moldova, Republic of Sudan Cook Islands Russian Federation Swaziland Fiji Islands Tajikistan Tanzania, United Rep of French Polynesia Turkmenistan Togo New Caledonia Ukraine Tunisia New Zealand Uzbekistan Uganda Papua New Guinea Congo, Dem Republic of Samoa Dummy Region Zambia Solomon Islands World Zimbabwe Tonga Vanuatu

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Table S3. Overview of key components of the shared socioeconomic pathways (SSPs) as described in O’Neill et al. (2017)

Component SSP1 SSP2 SSP3 SSP4 SSP5

Population growth Relatively Low Medium

Low in OECD, high in other countries

Low in OECD, relatively high in other countries

High in OECD, low in other countries

Economic growth High in LICs, MICs; medium in HICs

Medium, uneven Slow Low in LICs, medium in other countries

High

International trade Moderate Moderate Strongly constrained Moderate

High, with regional specialization in production

Globalization Connected markets, regional production

Semi-open globalized economy

De-globalizing, regional security

Globally connected elites

Strongly globalized, increasingly connected

Consumption & diet

Low growth in material consumption, low-meat diets, first in HICs

Material-intensive consumption, medium meat consumption

Material-intensive consumption

Elites: high consumption lifestyles; Rest: low consumption, low mobility

Materialism, status consumption, tourism, mobility, meat-rich diets

International cooperation Effective Relatively weak Weak, uneven

Effective for globally connected economy, not for vulnerable populations

Effective in pursuit of development goals, more limited for environmental goals

Environmental policy

Improved management of local and global issues; tighter regulation of pollutants

Concern for local pollutants but only moderate success in implementation

Low priority for environmental issues

Focus on local environment in MICs, HICs; little attention to vulnerable areas or global issues

Focus on local environment with obvious benefits to well-being, little concern with global problems

Policy orientation Toward sustainable development

Weak focus on sustainability

Oriented toward security

Toward the benefit of the political and business elite

Toward development, free markets, human capital

Institutions

Effective at national and international levels

Uneven, modest effectiveness

Weak global institutions/natl. govts. dominate societal decision-making

Effective for political and business elite, not for rest of society

Increasingly effective, oriented toward fostering competitive markets

Technology development Rapid Medium, uneven Slow

Rapid in high-tech economies and sectors; slow in others

Rapid

Environment Improving conditions over time

Continued degradation

Serious degradation

Highly managed and improved near high/middle-income living areas, degraded otherwise

Highly engineered approaches, successful management of local issues

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Table S4. Overview of key components of forest sector pathways corresponding to each shared socioeconomic pathway (SSP) as described in Daigneault et al. (2019)

Component SSP1 SSP2 SSP3 SSP4 SSP5

Land-use change regulation*

Strong regulation to avoid damages to the environment.

Medium regulation; slow decline in the rate of deforestation

Limited regulation; continued deforestation

Highly regulated in MICs and HICs; lack of regulation in LICs lead to high deforestation rates

Medium regulation; slow decline in the rate of deforestation

Forest productivity growth

High improvements in forest plantation productivity and forest management; rapid diffusion of best practices

Medium increase of productivity in managed forests and plantations

Very low productivity development

Forest productivity high in HICs, low in LICs

Highly managed, resource-intensive; rapid increase in productivity

Environmental impact of forestry activities

Reduced harvest intensity in non-plantation forests, emphasis on conservation of environmental values. Increased areas set aside from forestry activities

Medium environmental impacts from forestry activities

Intensive harvests increase the stress on biodiversity and other environmental values

HICs: strong regulation ensures adequate set-asides and environmental considerations; MICs and LICs: negative impacts on the environment through poor control

Intensive harvests cause more stress to the environment, but moderate level of regulation and set-asides reduces the harmful impacts

International trade* Moderate Moderate Strongly

constrained Moderate

High, with regional specialization in production

Globalization* Connected markets, regional production

Semi-open globalized economy

De-globalizing, regional security

Globally connected elites

Strongly globalized

Land-based mitigation policies*

No delay in international cooperation for climate change mitigation. Full participation of the land use sector

Delayed international cooperation for climate change mitigation. Partial participation of the land use sector

Heavily delayed international cooperation for climate change mitigation. Limited participation of the land use sector

No delay in international cooperation for climate change mitigation. Partial participation of the land use sector

Delayed international cooperation for climate change mitigation. Full participation of the land use sector

Efficiency of wood use (cascading, recycling, new materials, technical development)

High, with rapid development of new bio-based materials

Medium

Strongly constrained development, focus on local solutions only

Moderate in HICs; poor efficiency of wood use in LICs

Rapid development of new technologies, with countries specializing heavily. Moderate levels of cascading and recycling

Forest Product Consumption

Decreased overall consumption, with a high share of wood-based materials

Medium, following historical trends

High total consumption, emphasis on conventional products

Medium, following historical trends with LICs relying heavily on firewood as an energy source

High overall consumption, with moderate share of wood-based materials and fuel

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Table S5. Parameters to operationalize Shared Socioeconomic Pathway within the Global Forest Products Model

Component SSP1 SSP2 SSP3 SSP4 SSP5 GDP (Y) 2.16%/yr 2.11%/yr 1.43%/yr 1.68%/yr 2.76%/yr Population (N) 0.01%/yr 0.28%/yr 0.62%/yr 0.31%/yr 0.07%/yr International trade (𝜆ik) 1.0 1.0 1.2 1.0 0.8

Resource efficiency (𝜂ikn,t) 0.3%/yr 0.2%/yr 0.1%/yr 0.3%/yr HIC/ 0.1%/yr LIC 0.3%/yr

Note: High income countries (HIC), low income countries (LIC)

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Table S6. Forest product half-life’s, and factors to convert from product units to carbon Product j

Sawnwood Wood-based panels

Paper & paperboard

Half-life in use (years); 𝐻𝐿2 35 25 2

Carbon factor (tC m-3); 𝜂2 0.229 0.269 0.3861 1 tC (air-dry tonne)-1

, tC=tonne of carbon. Data are default recommendations in Table 2.8.1 and Table 2.8.2 in Chapter 2: 2013 Revised Supplementary Methods and Good Practice Guidance Arising from the Kyoto Protocol (IPCC, 2014a)

Table S7. Estimated Annual Rates of Increase for Industrial Roundwood Production (Harvested) by World Region for the Period of 1900 – 1961. Region Annual Rate of Increase World Total 0.0148 Europe 0.0151 USSR 0.0160 North America 0.0143 Latin America 0.0220 Africa 0.0287 Asia 0.0217 Oceania 0.0231 Data are default recommendations in Table 12.3 in Chapter 12; IPCC report on GPG- LULUCF (IPCC, 2006)

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Table S8. Historical and projected production of roundwood for select regions and countries. Historic data for 1992 to 2015 from FAOSTAT, projections for 2065 from the GFPM for SSP1-5.

(106 m3) Historical Projection to 2065 1992 2015 SSP1 SSP2 SSP3 SSP4 SSP5

AFRICA 431.8 711.1 411.8 422.2 442.3 430.8 408.5 Egypt 14.7 17.9 18.6 18.8 18.7 18.8 18.6 Nigeria 61.1 71.9 0.0 0.0 0.0 0.0 0.0 South Africa 27.9 26.1 42.9 42.2 39.4 38.9 45.6 NORTH/CENTRAL AMERICA 739.7 652.7 796.1 774.7 695.9 684.1 901.2 Canada 169.9 154.1 151.6 146.4 127.8 126.1 176.4 Mexico 42.0 44.2 43.7 44.0 44.0 42.2 45.0 United States of America 483.8 403.3 573.1 556.6 496.9 488.6 651.8 SOUTH AMERICA 288.3 393.6 403.4 399.7 381.8 373.2 426.4 Argentina 11.7 16.3 17.4 17.2 15.4 15.0 18.8 Brazil 202.5 257.0 279.3 275.6 262.5 254.9 297.0 Chile 28.4 58.2 46.6 46.2 43.8 43.2 49.7 ASIA 1160.7 1240.3 1215.0 1207.4 1170.8 1173.7 1261.9 China 366.2 445.8 483.5 479.8 461.6 456.0 502.4 India 320.1 350.7 342.4 341.6 338.4 348.1 348.3 Indonesia 158.8 115.6 107.8 106.1 98.3 96.7 115.0 Japan 27.3 21.4 20.1 19.1 16.3 17.0 23.5 Korea, Republic of 3.7 5.2 18.1 16.9 15.4 15.8 21.1 Malaysia 48.9 20.3 30.0 28.5 24.9 24.6 35.2 OCEANIA 44.2 72.3 65.3 63.3 54.0 55.9 74.4 Australia 20.7 29.8 29.5 28.6 22.9 25.2 33.9 New Zealand 14.3 29.6 25.3 24.6 21.6 21.4 29.1 EUROPE 555.1 713.8 1026.5 1008.6 951.1 925.5 1113.2 Austria 12.8 17.4 19.9 19.5 18.3 18.0 21.6 Finland 38.5 58.3 69.4 69.0 67.3 66.3 72.0 France 62.8 52.3 78.0 76.6 74.3 70.6 85.1 Germany 33.0 55.5 105.1 102.1 90.7 88.0 119.1 Italy 8.4 5.7 9.5 9.3 9.2 8.7 10.2 Russian Federation 227.9 196.4 269.8 265.2 247.9 243.7 287.9 Spain 13.9 16.4 24.8 24.4 25.8 22.2 27.1 Sweden 53.5 72.9 79.7 79.2 76.6 75.4 83.5 United Kingdom 6.4 11.1 9.3 9.2 8.9 8.1 10.2 WORLD 3219.8 3783.7 3918.1 3875.7 3696.0 3643.2 4185.6

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Table S9. Historical and projected production of industrial roundwood for select regions and countries. Historic data for 1992 to 2015 from FAOSTAT, projections for 2065 from the GFPM for SSP1-5.

(106 m3) Historical Projection to 2065 1992 2015 SSP1 SSP2 SSP3 SSP4 SSP5

AFRICA 56.7 72.1 71.9 68.5 61.8 61.8 78.3 Egypt 0.1 0.3 0.5 0.5 0.4 0.4 0.5 Nigeria 8.3 10.0 0.0 0.0 0.0 0.0 0.0 South Africa 15.3 13.5 30.2 29.4 26.5 26.1 33.0 NORTH/CENTRAL AMERICA 577.2 515.9 685.4 663.9 586.2 573.8 789.2 Canada 163.5 151.4 148.6 143.5 125.0 123.1 173.2 Mexico 7.0 5.4 5.8 5.9 5.9 4.5 6.9 United States of America 403.1 354.7 526.7 510.3 451.4 442.4 604.3 SOUTH AMERICA 120.5 215.3 229.0 224.7 208.0 200.6 251.0 Argentina 7.8 10.9 12.7 12.5 10.7 10.5 14.1 Brazil 79.3 136.3 163.2 159.0 146.7 140.0 180.1 Chile 19.4 42.6 30.0 29.6 27.3 26.9 33.0 ASIA 277.9 399.7 623.5 610.1 556.4 549.1 680.4 China 92.4 167.2 316.0 311.7 292.6 287.7 334.3 India 36.3 49.5 97.4 95.1 79.8 79.3 111.9 Indonesia 43.1 74.0 62.8 60.9 53.4 52.1 69.8 Japan 27.1 21.3 20.1 19.0 16.3 17.0 23.4 Korea, Republic of 1.1 4.5 17.3 16.1 14.6 15.0 20.3 Malaysia 45.0 17.8 27.3 25.9 22.2 21.9 32.6 OCEANIA 34.3 63.5 55.8 53.8 44.6 46.3 64.9 Australia 16.7 27.4 24.4 23.5 18.1 20.1 28.7 New Zealand 14.3 28.9 25.3 24.6 21.6 21.4 29.1 EUROPE 416.8 578.1 866.7 849.0 794.1 766.7 951.0 Austria 9.9 12.6 15.9 15.5 14.3 13.9 17.6 Finland 35.6 51.4 61.2 60.8 59.4 58.2 63.6 France 29.3 25.0 48.2 46.9 44.9 41.0 54.8 Germany 29.2 45.1 92.5 89.6 78.4 75.5 106.2 Italy 3.5 2.0 4.3 4.2 4.2 3.7 5.0 Russian Federation 164.0 190.5 254.8 250.2 232.9 229.0 272.6 Spain 11.6 13.0 21.0 20.6 22.0 18.4 23.2 Sweden 49.7 67.3 75.9 75.3 72.8 71.5 79.7 United Kingdom 6.2 8.6 7.8 7.7 7.4 6.5 8.7 WORLD 1483.4 1844.6 2532.3 2469.9 2251.1 2198.4 2814.8

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Table S10. Historical and projected production of wood pulp for select regions and countries. Historic data for 1992 to 2015 from FAOSTAT, projections for 2065 from the GFPM for SSP1-5.

(106 mt) Historical Projection to 2065 1992 2015 SSP1 SSP2 SSP3 SSP4 SSP5

AFRICA 1.9 1.5 2.7 2.5 2.1 2.0 3.0 Egypt 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Nigeria 0.0 0.0 0.0 0.0 0.0 0.0 0.0 South Africa 1.4 1.3 2.1 2.0 1.8 1.6 2.4 NORTH/CENTRAL AMERICA 80.9 64.9 73.2 70.0 58.0 58.8 86.8 Canada 22.6 16.6 8.5 8.0 6.2 6.9 9.7 Mexico 0.3 0.1 0.0 0.0 0.0 0.0 0.0 United States of America 58.0 48.2 64.7 62.0 51.8 51.9 77.0 SOUTH AMERICA 7.7 25.9 11.2 10.8 9.7 9.3 13.0 Argentina 0.6 0.8 0.4 0.3 0.1 0.1 0.6 Brazil 5.2 17.4 9.9 9.6 8.8 8.2 11.2 Chile 1.7 5.1 0.4 0.4 0.4 0.4 0.4 ASIA 15.9 30.1 28.0 27.3 24.0 23.6 31.6 China 2.0 10.0 0.0 0.0 0.0 0.0 0.0 India 0.8 2.1 16.5 16.2 14.3 13.2 17.8 Indonesia 1.0 6.7 2.9 2.8 2.4 3.0 3.4 Japan 11.0 8.7 5.8 5.4 4.6 4.7 7.2 Korea, Republic of 0.3 0.5 2.0 1.9 1.9 1.9 2.1 Malaysia 0.0 0.2 0.0 0.0 0.0 0.0 0.0 OCEANIA 2.3 2.9 2.3 2.1 1.6 1.7 3.2 Australia 1.0 1.4 1.5 1.2 0.7 0.8 2.3 New Zealand 1.3 1.5 0.8 0.8 0.9 0.9 0.9 EUROPE 38.9 44.0 43.3 43.2 40.1 42.1 46.9 Austria 1.4 1.4 1.7 1.8 1.7 1.9 1.5 Finland 8.5 10.3 2.0 1.9 1.5 1.7 2.9 France 2.7 1.6 0.1 0.1 0.1 0.1 0.1 Germany 2.3 2.6 3.3 3.6 3.5 3.8 1.8 Italy 0.4 0.4 0.9 0.8 0.7 0.5 1.1 Russian Federation 6.2 8.1 24.3 24.2 22.5 23.3 25.9 Spain 1.5 1.6 0.0 0.0 0.0 0.0 0.1 Sweden 9.6 11.1 3.4 3.1 2.2 2.6 4.3 United Kingdom 0.6 0.2 0.0 0.0 0.0 0.0 0.0 WORLD 147.7 169.2 160.7 155.8 135.4 137.5 184.4

15

Table S11. Historical and projected production of sawnwood for select regions and countries. Historic data for 1992 to 2015 from FAOSTAT, projections for 2065 from the GFPM for SSP1-5.

(106 m3) Historical Projection to 2065 1992 2015 SSP1 SSP2 SSP3 SSP4 SSP5

AFRICA 8.1 9.9 9.2 8.9 8.0 8.2 7.9 Egypt 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Nigeria 2.7 2.0 0.0 0.0 0.0 0.0 0.0 South Africa 1.8 1.9 2.9 2.9 2.7 2.6 0.9 NORTH/CENTRAL AMERICA 129.7 127.3 136.8 135.2 125.1 134.2 124.7 Canada 40.1 47.1 23.2 22.8 20.4 22.2 24.8 Mexico 2.7 2.5 0.2 0.0 0.0 0.0 0.8 United States of America 85.2 76.4 111.7 110.7 103.1 110.4 97.4 SOUTH AMERICA 24.0 30.6 40.3 39.6 37.4 37.0 40.3 Argentina 1.5 2.8 3.9 3.9 3.8 3.5 4.0 Brazil 15.9 15.2 24.4 23.2 21.2 21.6 24.3 Chile 3.0 8.4 6.2 6.3 6.0 5.8 6.6 ASIA 97.2 125.9 75.4 73.6 64.0 84.2 90.8 China 19.8 74.3 9.2 11.2 15.1 36.5 12.8 India 17.5 6.9 11.4 11.3 11.1 10.4 11.8 Indonesia 8.4 4.2 5.4 5.3 4.5 5.2 5.6 Japan 27.3 9.6 0.0 0.0 0.0 0.0 0.0 Korea, Republic of 3.5 2.4 4.6 4.4 4.2 4.4 5.0 Malaysia 9.4 4.5 14.4 12.6 8.0 7.0 21.6 OCEANIA 5.9 9.5 5.9 5.3 7.1 5.1 10.0 Australia 3.0 5.2 1.5 0.9 0.0 0.0 5.5 New Zealand 2.5 4.1 3.7 3.6 6.1 4.1 4.1 EUROPE 134.1 150.8 301.2 297.7 284.1 263.4 332.4 Austria 7.0 8.7 45.1 45.6 45.2 35.8 48.0 Finland 7.3 10.6 41.5 41.0 40.5 40.2 42.4 France 10.5 7.5 11.7 11.5 9.7 11.2 12.0 Germany 13.5 21.5 55.0 52.7 44.5 39.6 73.3 Italy 1.8 1.5 0.0 0.0 0.0 0.0 0.1 Russian Federation 53.4 34.5 24.5 24.1 22.7 22.3 26.4 Spain 2.5 2.5 0.0 0.0 0.0 0.0 0.0 Sweden 12.1 18.2 66.1 66.5 67.6 65.6 66.0 United Kingdom 2.1 3.5 4.2 3.5 4.0 2.0 5.0 WORLD 398.9 454.0 568.9 560.3 525.8 532.0 606.3

16

Table S12. Historical and projected production of wood-panels for select regions and countries. Historic data for 1992 to 2015 from FAOSTAT, projections for 2065 from the GFPM for SSP1-5.

(106 m3) Historical Projection to 2065 1992 2015 SSP1 SSP2 SSP3 SSP4 SSP5

AFRICA 1.5 3.1 9.2 8.0 6.3 6.1 11.1 Egypt 0.1 0.1 0.7 0.7 0.7 0.6 0.7 Nigeria 0.1 0.1 0.0 0.0 0.0 0.0 0.0 South Africa 0.4 1.2 2.8 2.6 2.0 1.7 3.6 NORTH/CENTRAL AMERICA 45.2 48.3 37.5 35.4 27.6 30.1 62.5 Canada 6.6 12.8 9.5 8.9 6.5 7.2 14.7 Mexico 0.6 1.2 3.5 3.6 3.7 2.7 3.8 United States of America 37.7 33.9 23.9 22.5 17.0 19.9 43.4 SOUTH AMERICA 4.6 17.7 41.0 40.4 36.2 31.6 49.1 Argentina 0.3 1.1 1.6 1.6 0.9 1.0 1.9 Brazil 2.9 11.1 32.1 32.0 29.4 25.9 39.3 Chile 0.5 3.3 2.8 2.6 2.5 1.6 2.9 ASIA 32.4 246.2 416.5 395.8 343.8 293.7 517.5 China 4.9 200.7 334.6 319.0 280.3 239.2 420.3 India 0.4 3.1 15.5 15.3 12.5 10.2 17.8 Indonesia 10.6 7.1 13.9 13.4 11.7 9.6 15.8 Japan 8.3 4.7 6.9 6.3 5.1 6.0 8.6 Korea, Republic of 1.6 3.4 5.9 5.2 4.2 4.3 7.7 Malaysia 3.5 6.8 6.4 6.3 5.3 4.3 7.8 OCEANIA 1.7 3.8 3.5 3.2 2.7 2.6 4.2 Australia 0.9 1.8 0.0 0.0 0.0 0.0 0.0 New Zealand 0.8 1.9 3.0 2.7 2.3 2.2 3.7 EUROPE 40.6 82.4 224.2 217.1 188.7 187.8 249.9 Austria 1.9 3.1 4.1 3.9 3.4 3.3 5.0 Finland 0.9 1.3 6.9 6.9 6.6 6.7 7.2 France 3.6 5.2 10.5 9.8 6.7 7.9 12.6 Germany 8.9 12.2 26.6 24.5 20.7 21.5 30.0 Italy 3.4 3.6 8.1 7.7 4.4 7.2 10.3 Russian Federation 7.4 14.3 50.2 48.0 42.8 38.9 54.6 Spain 2.3 3.9 4.6 4.3 2.7 3.9 5.9 Sweden 0.8 0.7 2.2 2.1 1.3 2.0 2.7 United Kingdom 1.9 3.1 2.4 3.3 2.3 3.8 2.3 WORLD 126.0 401.5 731.8 699.9 605.4 551.9 894.2

17

Table S13. Historical and projected production of paper and paperboard for select regions and countries. Historic data for 1992 to 2015 from FAOSTAT, projections for 2065 from the GFPM for SSP1-5.

(106 mt) Historical Projection to 2065 1992 2015 SSP1 SSP2 SSP3 SSP4 SSP5

AFRICA 2.7 3.6 9.4 8.9 7.6 7.2 10.7 Egypt 0.2 0.7 2.0 1.9 1.8 1.7 2.1 Nigeria 0.0 0.0 0.2 0.2 0.2 0.1 0.2 South Africa 1.8 2.2 4.6 4.4 3.7 3.5 5.2 NORTH/CENTRAL AMERICA 94.7 88.7 95.9 93.6 82.5 87.6 109.6 Canada 16.6 10.3 6.6 6.1 4.2 5.9 7.7 Mexico 2.8 5.3 12.2 12.6 13.0 10.5 12.8 United States of America 75.2 72.4 76.0 73.8 64.3 70.3 87.9 SOUTH AMERICA 8.1 15.8 24.7 23.7 21.1 19.0 29.0 Argentina 1.0 1.2 1.5 1.3 1.0 0.9 2.0 Brazil 4.9 10.4 16.9 16.2 14.6 13.2 20.2 Chile 0.5 1.2 0.0 0.0 0.0 0.0 0.0 ASIA 63.2 190.6 349.9 341.0 317.0 306.5 385.4 China 20.0 111.2 213.9 209.7 201.0 192.2 232.7 India 2.5 15.0 38.6 37.8 33.2 30.5 42.0 Indonesia 2.3 10.2 20.5 20.0 18.0 16.8 22.6 Japan 28.3 26.2 25.6 24.1 20.7 21.8 30.8 Korea, Republic of 5.5 11.6 13.3 13.0 12.6 14.4 14.7 Malaysia 0.6 1.8 4.0 4.0 3.8 3.4 4.4 OCEANIA 2.7 3.9 6.7 6.1 3.5 4.4 9.4 Australia 2.0 3.2 6.1 5.5 2.9 3.7 8.7 New Zealand 0.7 0.7 0.6 0.6 0.6 0.6 0.7 EUROPE 72.8 104.2 145.9 141.9 114.0 127.6 168.0 Austria 3.3 5.0 9.4 9.5 6.5 7.6 9.3 Finland 9.2 10.3 3.2 3.0 2.5 2.8 4.2 France 7.7 8.0 16.1 15.6 11.3 14.5 18.3 Germany 13.2 22.6 30.6 30.1 28.4 29.8 33.8 Italy 6.0 8.8 20.0 19.3 13.7 15.4 22.3 Russian Federation 5.8 8.1 11.5 11.6 8.7 8.2 12.5 Spain 3.4 6.2 10.4 10.1 8.3 9.3 11.6 Sweden 8.4 10.3 5.2 4.8 3.1 4.1 7.4 United Kingdom 5.2 4.0 11.9 11.7 10.2 11.7 12.7 WORLD 244.1 406.7 632.6 615.1 545.7 552.4 712.2

18

Table S14. Historical and projected annual carbon flux in harvested wood products for select regions and countries according to IPCC 2013 Good Practice Guidance. Historic data for 1992 to 2015 from FAOSTAT, projections for 2065 from the GFPM for SSP1-5.

(Mt CO2e) Historical Projection to 2065 1992 2015 SSP1 SSP2 SSP3 SSP4 SSP5

AFRICA 4.6 4.9 4.4 3.6 2.2 2.1 4.7 Egypt 0.0 0.0 0.1 0.1 0.1 0.1 0.1 Nigeria 1.6 0.6 -0.6 -0.6 -0.6 -0.6 -0.7 South Africa 1.0 1.0 1.8 1.7 1.3 1.0 1.0 NORTH/CENTRAL AMERICA 79.1 36.4 12.0 10.1 1.1 6.1 19.1 Canada 21.7 17.2 -5.3 -5.9 -8.4 -7.3 -1.3 Mexico 1.0 1.3 0.1 0.1 0.3 -0.4 0.6 United States of America 55.8 17.0 16.9 15.5 8.9 13.7 19.2 SOUTH AMERICA 14.2 21.6 24.1 23.6 19.8 16.4 30.6 Argentina 0.9 1.9 1.4 1.4 0.9 0.9 1.7 Brazil 9.2 9.8 19.7 19.0 16.2 14.0 25.2 Chile 2.1 6.8 0.3 0.2 0.1 -0.5 0.7 ASIA 52.2 181.8 79.1 71.9 44.4 41.8 119.1 China 12.3 150.5 64.6 61.7 48.5 44.1 80.3 India 10.7 3.4 5.4 5.3 3.3 3.3 7.8 Indonesia 14.4 3.7 2.4 2.4 1.3 1.1 3.7 Japan -4.0 -5.8 -3.0 -3.4 -4.0 -3.8 -1.9 Korea, Republic of 0.1 1.8 4.4 3.8 3.1 3.3 5.9 Malaysia 8.5 3.8 5.7 4.6 1.4 0.1 11.8 OCEANIA 2.8 4.9 -1.4 -1.9 -0.7 -2.1 1.7 Australia 1.1 2.4 -2.8 -3.2 -3.1 -3.3 -0.1 New Zealand 1.5 2.3 0.9 0.7 1.9 0.6 1.5 EUROPE 47.2 62.2 119.7 114.2 94.8 82.2 148.1 Austria 1.1 1.0 2.2 2.1 1.7 1.5 2.9 Finland 1.1 1.9 9.5 9.4 9.3 8.8 9.8 France 5.0 0.8 5.8 5.2 2.8 3.7 7.3 Germany 7.0 5.7 28.5 26.5 19.9 17.8 35.9 Italy 0.2 0.0 1.0 1.0 0.7 0.8 1.4 Russian Federation 20.4 11.8 18.1 16.2 11.7 8.0 21.8 Spain 1.2 2.7 -0.1 -0.3 -1.2 -0.4 0.6 Sweden 3.1 4.7 10.6 10.5 10.3 9.7 11.2 United Kingdom 2.5 2.6 -0.2 0.0 0.0 -0.5 0.1 WORLD 205.4 334.6 237.3 219.8 158.0 142.2 328.3

19

Table S15. Country level GHG emissions by select sector (Mt CO2e) for most recent year of data availability reported by UNFCCC. Emissions from harvested wood products for matching year.

2015 in Mt CO₂ equivalent

Party

Harvested Wood

Products Energy Industrial Processes Agriculture

Total (without

LULUCF) Year Afghanistan 0.1 2.9 0.3 3.2 2005 Albania -0.1 4.3 1.6 5.9 2009 Algeria 0.0 66.4 5.2 71.6 2000 Angola 0.0 27.5 0.4 27.8 2005 Argentina 1.9 173.5 14.7 188.3 2012 Armenia 0.0 4.2 0.2 4.5 2010 Australia 2.4 421.9 33.8 70.1 537.6 2015 Austria 1.0 53.4 16.7 7.2 78.9 2015 Azerbaijan, Republic of 0.0 27.9 2.0 29.8 2012 Bahamas 0.0 0.7 0.7 2000 Bahrain 0.0 16.0 2.2 18.2 2000 Bangladesh 0.1 37.9 2.9 40.9 2005 Barbados 0.0 2.0 0.2 2.2 1997 Belarus 3.1 54.0 6.4 23.1 90.2 2015 Belgium 0.9 86.2 19.7 10.1 117.6 2015 Belize 0.0 0.0 0.0 2009 Benin 0.1 1.4 1.4 2000 Bhutan 0.0 0.3 0.2 0.5 2000 Bolivia 0.3 9.0 0.8 9.8 2004 Bosnia and Herzegovina 0.7 19.5 2.2 21.7 2014 Botswana 0.0 4.0 4.0 2000 Brazil 9.8 395.2 88.2 483.6 2012 Brunei Darussalam 0.0 5.9 5.9 2010 Bulgaria 0.7 45.5 5.8 6.2 61.7 2015 Burkina Faso 0.0 1.3 0.3 1.6 2007 Burundi 0.0 0.2 0.0 0.2 2005 Cambodia 0.0 2.1 2.1 2000 Cameroon 0.5 2.8 0.2 3.0 2000 Canada 17.2 585.2 51.4 58.6 713.8 2015 Cape Verde 0.0 Central African Republic 0.0 0.3 0.0 0.3 2010 Chad 0.0 4.1 4.1 2003 Chile 6.8 65.8 4.1 70.1 2010 China 150.5 8688.3 1193.2 9893.3 2012 Colombia 0.0 57.0 6.9 63.9 2004 Congo, Dem Republic of 0.0 2.5 0.2 2.6 2003 Congo, Republic of 0.3 1.3 1.3 2000 Cook Islands 0.0 0.0 0.0 1994 Costa Rica 0.1 5.5 0.5 6.0 2005 Côte d'Ivoire 0.6 60.4 0.0 60.4 2000 Croatia 0.7 16.7 2.8 2.9 24.2 2015 Cuba 0.1 23.6 1.3 24.9 2002 Cyprus 0.0 6.1 1.2 0.5 8.3 2015 Czech Republic 0.0 99.0 15.0 8.2 127.6 2015 Denmark -0.1 36.0 2.1 10.4 49.6 2015 Djibouti 0.0 0.3 0.3 2000 Dominica 0.0 0.1 0.1 2005 Dominican Republic 0.0 10.8 1.8 12.6 2010 Ecuador 0.6 36.5 4.6 41.1 2012 Egypt 0.0 148.8 20.4 169.2 2005 El Salvador 0.0 5.6 0.4 6.1 2005 Equatorial Guinea 0.0 Estonia 1.2 15.9 0.5 1.3 18.0 2015 Ethiopia 0.1 8.4 1.8 10.1 2013 Fiji Islands 0.1 1.6 1.6 2004 Finland 1.9 40.9 5.9 6.5 55.3 2015 France 0.8 324.9 44.2 78.1 464.6 2015 French Guiana 0.0 French Polynesia 0.0

20

Gabon 0.7 5.1 0.1 5.2 2000 Gambia 0.0 0.2 0.0 0.2 2000 Georgia 0.0 7.3 2.2 9.5 2013 Germany 5.7 768.1 60.9 66.7 906.8 2015 Ghana 0.3 7.6 0.2 7.8 2006 Greece -0.1 71.0 11.9 7.8 95.3 2015 Guatemala 0.1 11.0 1.5 12.6 2005 Guinea 0.0 1.4 0.1 1.6 1994 Guinea-Bissau 0.0 0.3 2.5 2010 Guyana 0.0 1.7 1.7 2004 Haiti 0.0 1.4 1.4 2000 Honduras -0.1 3.2 0.7 4.2 2000 Hungary 0.1 43.3 7.4 6.7 61.0 2015 India 3.4 1441.9 132.5 1574.4 2010 Indonesia 3.7 247.5 40.3 289.5 2000 Iran, Islamic Rep of 1.1 337.4 28.6 365.9 2000 Iraq 0.0 54.0 6.4 60.4 1997 Ireland 0.8 36.6 3.1 18.7 59.4 2015 Israel 0.0 64.7 2.4 67.0 2015 Italy 0.0 352.5 32.3 29.4 432.9 2015 Jamaica 0.0 8.2 0.4 8.6 1994 Japan -5.8 1173.1 92.8 33.6 1321.1 2015 Jordan 0.0 20.9 2.2 23.1 2006 Kazakhstan 0.1 262.5 23.7 32.2 323.7 2015 Kenya 0.1 11.8 2.1 13.9 2010 Korea, Dem People's Rep 0.0 68.4 5.3 73.8 2002 Korea, Republic of 1.8 589.4 33.3 628.8 2014 Kuwait 0.0 28.9 0.7 29.5 1994 Kyrgyzstan 0.1 6.0 0.4 6.4 2010 Laos 0.9 1.0 0.0 1.1 2000 Latvia 1.9 7.2 0.8 2.7 11.3 2015 Lebanon 0.0 20.6 2.5 23.1 2013 Lesotho 0.0 0.8 0.8 2000 Liberia 0.0 3.6 3.6 2000 Libyan Arab Jamahiriya 0.0 Lithuania 0.9 11.1 3.5 4.6 20.2 2015 Luxembourg 0.0 8.8 0.6 0.7 10.3 2015 Macedonia,The Fmr Yug Rp 0.0 Madagascar 0.0 1.9 0.2 2.1 2010 Malawi 0.0 0.7 0.1 0.7 1994 Malaysia 3.8 188.6 17.2 205.8 2011 Maldives 0.0 1.1 1.2 2011 Mali 0.2 2.7 0.1 2.7 2010 Martinique 0.0 Mauritania 0.0 1.1 0.0 1.1 2000 Mauritius 0.0 4.2 0.0 4.3 2013 Mexico 1.3 432.2 34.4 468.2 2013 Moldova, Republic of 0.0 Mongolia -0.2 9.8 0.1 10.0 2006 Montenegro 0.2 2.5 0.2 2.7 2011 Morocco 0.0 52.2 9.9 62.1 2012 Mozambique 0.0 1.5 0.1 1.6 1994 Myanmar 1.0 8.0 0.3 8.3 2005 Nepal 0.3 2.8 0.1 2.9 2000 Netherlands -0.1 161.4 10.9 18.8 194.6 2015 Netherlands Antilles 0.0 New Caledonia 0.0 New Zealand 2.3 32.4 5.3 39.1 80.7 2015 Nicaragua -0.1 3.5 0.3 3.8 2000 Niger 0.0 1.8 0.0 1.8 2008 Nigeria 0.6 114.7 2.1 116.8 2000 Norway 0.4 39.6 8.5 4.5 53.9 2015 Oman 0.0 10.6 0.6 11.2 1994 Pakistan 1.0 77.2 11.3 88.4 1994 Panama 0.0 4.6 0.6 5.2 2000 Papua New Guinea 0.1 2.4 0.1 4.4 2000

21

Paraguay 0.3 5.0 0.7 5.7 2012 Peru 0.1 42.1 6.1 48.2 2012 Philippines -0.4 62.5 8.6 82.7 2000 Poland 5.1 316.1 28.5 29.5 385.2 2015 Portugal 0.3 48.3 7.8 6.7 69.4 2015 Qatar 0.0 0.4 0.2 0.5 2005 Réunion 0.0 Romania 5.5 79.0 12.8 18.6 116.2 2015 Russian Federation 11.8 2162.1 218.8 135.8 2629.9 2015 Rwanda 0.1 Saint Lucia 0.0 0.5 0.5 2010 Saint Vincent/Grenadines 0.0 0.2 0.2 2004 Samoa 0.0 0.1 0.1 1994 Sao Tome and Principe 0.0 0.1 0.1 2005 Saudi Arabia 0.0 444.5 53.7 498.9 2012 Senegal 0.0 4.5 0.5 5.1 2005 Serbia 0.5 47.4 3.2 50.6 1998 Sierra Leone 0.0 0.1 0.1 2005 Singapore 0.3 46.8 46.8 2012 Slovakia 1.4 27.7 9.1 2.6 40.9 2015 Slovenia 0.2 13.4 1.1 1.8 16.9 2015 Solomon Islands 0.0 Somalia 0.0 South Africa 1.0 287.9 28.1 316.0 1994 Spain 2.7 254.6 32.3 34.5 335.8 2015 Sri Lanka 0.1 10.4 0.5 10.9 2000 Sudan 0.0 6.1 0.1 6.2 2000 Suriname 0.1 2.4 0.1 2.5 2003 Swaziland 0.1 Sweden 4.7 39.0 6.5 6.9 53.8 2015 Switzerland 0.2 37.1 4.0 6.0 47.8 2015 Syrian Arab Republic 0.0 Tajikistan 0.0 1.3 0.7 1.9 2010 Tanzania, United Rep of 0.0 Thailand 5.2 223.3 18.6 242.0 2013 Timor-Leste 0.0 0.2 0.3 2010 Togo 0.0 1.1 0.8 1.9 2005 Tonga 0.0 0.1 0.1 2000 Trinidad and Tobago 0.0 9.9 5.1 15.0 1990 Tunisia 0.1 19.0 3.6 22.7 2000 Turkey 8.1 339.7 59.6 53.7 469.9 2015 Turkmenistan 0.0 36.3 1.0 37.3 2010 Uganda 0.3 1.2 0.2 1.4 2000 Ukraine 1.3 210.5 56.5 39.8 319.0 2015 United Arab Emirates 0.0 149.8 8.6 158.4 2005 United Kingdom 2.6 416.3 33.8 41.9 511.3 2015 United States of America 17.0 5567.8 367.8 566.9 6638.1 2015 Uruguay 0.4 8.2 0.4 8.6 2012 Uzbekistan 0.0 99.6 5.9 105.5 2012 Vanuatu 0.0 0.1 0.1 2000 Venezuela, Boliv Rep of 0.6 105.1 9.0 114.1 1999 Viet Nam 8.7 126.9 29.8 157.0 2013 Yemen 0.0 16.8 0.7 17.5 2000 Zambia 0.1 1.5 0.2 1.7 2000 Zimbabwe 0.0 10.3 0.7 11.0 2006

22

Fig. S1. Population and GDP projections under the Shared Socioeconomic Pathways for the Period of 1960 – 2065. (a) Population (a) GDP

Source: IIASA Note: Population and GDP projections are aggregated for illustrative purposes based on country level data. SSP2 and SSP4 population appear to overlap in panel (a).

3

4

5

6

7

8

9

10

11

1960 1975 1990 2005 2020 2035 2050 2065

Bill

ion

Historic until 2015SSP1SSP2SSP3SSP4SSP5

0

100

200

300

400

500

600

1960 1975 1990 2005 2020 2035 2050 2065

PPP

US$

2005

trill

ion

23

Fig. S2. Proportion of unaccounted feedstock according to IPCC Good Practice Guidance

24

Fig. S3. Forest Sector System Boundary

Adapted from the IPCC 4th Working Group Assessment Report. Climate Change 2007: Mitigation of Climate Change. Chapter 9: Forestry. https://www.ipcc.ch/site/assets/uploads/2018/02/ar4-wg3-chapter9-1.pdf