We use the dynamic global timber model (GTM) to assess how bio-energy demand affects the forestry sector, forestland, and carbon sequestration (4, 30). GTM compares timber harvesting and management in more than 200 managed and natural forest ecosystems across 16 world regions (fig. S1) under different bioenergy demand scenarios to a no-bioenergy demand scenario (22). The model used the Shared Socioeconomic Pathway (SSP) 2 marker scenario projections of gross domestic product (GDP) and population (31–33) to simulate forest product demand, while bioenergy demand projections [following the assumptions presented in Lauri et al. (34) that 9% to 12% of total bioenergy demand is sourced by dedicated forest plantation; bioenergy is converted from gigajoules (GJ) to cubic meters (m3) of forest biomass using constant conversion factors of 7.2 GJ/m3] and carbon price paths under the same SSP2 scenario for each Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathway (RCP) are used to simulate the future demand for woody biomass and the value of CO2 (fig. S2).

centration Pathway (RCP) are used to simulate the future demand for woody biomass and the value of CO2 (fig. S2).

In general, bioenergy consumption is expected to increase with the stringency of the RCP target. For reference, under RCP 1.9—the scenario most consistent with a 1.5circC target—about 30% of the total energy supply through 2100 is estimated to be sourced from bioenergy with carbon capture and storage (BECCS) (33). Because bioenergy demand is expected to come from a variety of sources, we assume about one-third of the supply is provided by forests, which is consistent with other global analyses (34). The model assumes a homogenous form of woody biomass energy demand without distinguishing types of woody biomass production. From the perspective of our model, this means that each type of wood that could be used as an input into biomass energy production is paid the same price.

Increasing demand for woody biomass will have noticeable impacts on the global forest sector compared with a no-policy baseline case (tables S2 to S4). Timber prices could more than triple if woody biomass consumption reaches 4.3 billion m3/year by the end of this century, as in the RCP 1.9 scenario (Fig. 1A). The model does account for the substitution between wood products and biomass, and the increasing demand for woody bioenergy negatively affects the industrial timber market. That is, there is a decline of between 30 and 80% in the production of industrial timber over the century projected across the RCPs, with the largest reduction under RCP 1.9.

Higher timber prices incentivize afforestation across the globe (Fig. 1B). However, higher timber prices also encourage harvesting of natural forest areas (forest types are defined as follows: “plantation” = intensively managed plantations; “managed” = extensively managed, often naturally regenerating forests; “natural” = inaccessible, unmanaged natural forests) (Fig. 1C), which are replanted as a mix of low-managed forests and intensive plantations (Fig. 1D). Total global forest carbon sequestration is projected to increase only when the demand for woody biomass is large enough to encourage consumption greater than 1.1 billion m3/year by 2100, i.e., an RCP of less than 4.5 (Fig. 1E). When biomass demand is lower than this level, it does not generate high enough timber prices to generate enough investments in forests or plantations to offset carbon losses that occur when forests are harvested. The carbon losses occur primarily in regions dominated by large areas of remaining inaccessible forests, namely, Latin America, Southeast Asia, Canada, and Russia. Older forests have substantial carbon stocks that are not compensated. Eventually, if biomass energy demand is strong enough, investments in forests will outweigh losses, and carbon turns positive. The expenditure on forest management, as measured by dollars per hectare invested in replanting, also matters, as it increases with more stringent climate policy (Fig. 1F).

The model accounts for carbon stored in four different pools. The increase in carbon stocks is primarily driven by improvements in aboveground carbon, while more forestland marginally increases soil carbon due to afforestation relative to the baseline scenario. Carbon stored in harvested wood products is projected to decline under all policy scenarios because the increasing demand for woody biomass reduces the quantity of noncombusted wood products (fig. S4).

Expanding woody biomass energy could result in a 286 (RCP 6.0) to 1931 (RCP 1.9) m3/year increase in total timber harvesting compared with the baseline scenario. Increases in harvests are not equally distributed across the globe though (Fig. 2), with the largest harvest increases expected in places where industrial wood harvesting is already an important part of the landscape and regional economy. For instance,

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to the price changes induced by bioenergy policy. If models include management responses, higher prices invariably encourage more management and forest area, and thus, biomass energy policies reduce net emissions over time. Alternatively, if forest land area and forest management do not change or decline with biomass energy policies, and there is additional harvesting of unmanaged stocks, then the policies typically result in net emissions. It is, thus, important to isolate the role of management on forest carbon stocks.

Second, studies suggesting that biomass energy should be taxed have ignored the literature showing the efficient economic treatment of carbon fluxes between the atmosphere and forests in the broader carbon cycle (4). From the perspective of the atmosphere, a ton of CO2 in forests is a ton not in the atmosphere, suggesting that the social cost of carbon can be used to value carbon exchanges, or fluxes, between the atmosphere and ecosystems (24). Two equally efficient schemes have been proposed in the literature to credit carbon fluxes between the atmosphere and forests: a carbon rental approach (4) and a carbon tax and subsidy approach (25). Under both approaches, the efficient climate policy counts emissions when forests are used for energy or wood products as an increase in atmospheric carbon, but they also count sequestration that occurs when forests grow. Bioenergy emissions can be taxed like other GHGs under an efficient approach to credit carbon fluxes, but only if the benefits of storing carbon in forested ecosystems are also recognized and subsidized (25). That is, a policy that taxes forest-based bioenergy without recognizing that forests also sequester carbon through growth [the Schlesinger proposition (26)] is inefficient and will lead to too little carbon in forests and too much carbon in the atmosphere.

Third, there are concerns that ecosystem services and biodiversity provided by primary forests could be affected if harvests are diverted from traditional wood products to bioenergy (13, 14) or the level and quality of standing biomass on managed forests are diminished due to higher levels of residue removals (27), shorter rotations (28, 29), or more land moved from no/low management to more intensive management. Concerns with ecosystem services, however, tend to focus on the effects of biomass harvests at individual sites (13, 14). While more intensive harvesting will be a consequence of any biomass energy policy that increases the demand for wood, intensification will not occur at a few selected sites, but across forests, especially under widespread biomass energy or carbon neutrality mandates. To gauge the full impacts of policies, models must be able to analyze the full spatial and temporal consequences on the global forest ecosystem.