about 80% above baseline investment. Demand for wood products in general will stimulate investment as landowners are expected to accrue a higher return. However, a forest carbon rental and increased biomass demand policy could double investment compared with the biomass penalty approach (Fig. 3F). Management decisions affect the amount of carbon stored in forests in different ways. First, GTM controls rotation ages, which influences carbon stocks on sites, with higher rotation ages leading to greater timber supply and more carbon, and vice versa. Second, under high bioenergy demand and/or carbon prices, the model projects more replanting, which, compared with natural regeneration, will increase average carbon on a site over a rotation. Third, GTM shifts species types over time in response to prices and land rental values. Fourth, the model shifts species from no management to modest management (harvesting with natural regeneration or harvesting with replanting in some cases, depending on value). In nearly all cases, this conversion of older forests to younger forests leads to more timber output but less carbon. Last, GTM includes management intensity on replanted land. This type of management intensity, which could include genetic selection, fertilizing, density controls, and other approaches, increases both carbon stocks and the value of timber. This type of management intensity is monitored in the model by the expenditure per hectare of forestland, with higher expenditures leading to more timber and more carbon.
We tested the effects of bioenergy demand on forestland and carbon sequestration and the efficiency of the rental approach relative to the penalty approach under a scenario in which forestland additions are limited to 0.9 billion ha, following Bastin et al. (36). Even under this constrained scenario, our findings are confirmed: Bioenergy demand will increase total forestland and forest carbon sequestration compared with a no-bioenergy (baseline) scenario (Fig. 6, A and C), and the carbon rental policy provides an efficient approach to regulate the increasing demand for bioenergy by protecting natural forestland while providing woody biomass for energy at the same time (Fig. 6B). Although forest area does not expand as much with the tighter constraint, it is around 50% lower; forest carbon storage declines by only 20 to 30%. Carbon declines proportionally less than forest area because forests are managed more intensively to increase timber production, and this in turn enhances carbon storage. Any time there is a conversion in natural forest areas from inaccessible to accessible and lightly managed forests, there is lower total carbon stored over time. Thus, the efficient carbon rental climate policy leads to more carbon by protecting more natural forests from conversion.
Additional sensitivity analysis that adjusts key model parameters such as the land supply elasticity, management response to forest investment, and the cost of accessing and clearing natural forests to half and double their original values indicates that our general findings still hold (fig. S8). That is, higher biomass demand will increase the value of timberland, incentivize additional investment in forest management and afforestation, and result in greater forest carbon stocks over time, even if our model includes more pessimistic (i.e., less responsive) parameter values. However, the relative impact that each parameter has on the estimates varies. For example, a low land supply elasticity results in about half the afforestation rate of the high land supply elasticity case, simulating the potential effect if landowners are more resistant to converting their agricultural lands to forests. As a result, forest carbon stocks would still increase over time.
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lowers investment in forest management (Fig. 3F), and, thus, leads to lower forest carbon stocks (Fig. 3E) compared with the efficient approach (carbon rental scenario). That is, under any given demand for woody biomass, an approach that only penalizes emissions will deliver less carbon sequestration than the efficient rental approach. Moreover, timber prices are higher under the rental scenario because there are additional benefits associated with holding carbon in forests, thereby potentially reducing the annual timber supply.
Critically, the penalty approach, as suggested by Searchinger et al. (13), could cause a large reduction in the area of natural inaccessible forests of up to 200 Mha under the strong biomass energy demand of RCP 1.9 or 2.6 (Figs. 3C and 4). Without valuing standing stocks of forests through a subsidy for forest carbon sequestration, higher timber prices (Fig. 3A) provide a substantial incentive to convert natural forests to other forest types (Fig. 3B). The tax cannot avoid this outcome. The largest declines in natural forest areas under a penalty approach will occur under biomass demand higher than 1.5 billion m3/year, mainly in the tropics, followed by the temperate zone (Fig. 4). In contrast, a carbon rental approach encourages protection of standing natural forests by valuing the standing stock, such as old growth harvests in boreal regions and unmanaged forests in the tropics. In particular, a combination of the high carbon prices and bioenergy demands (RCPs 2.6 and 1.9) will avoid future deforestation of tropical natural forests relative to the baseline. That is, opportunity costs of land are relatively low in the tropics, so there is a reduction in forestland conversion to cropland. Second, the carbon gains in the tropics are relatively fast and large, such that the rental values encourage substantial carbon sequestration comparing to temperate and boreal forests.
Each of the policy approaches leads to more forestland globally over the next century, but estimates vary at the regional level (Fig. 5). In the cases where there is a penalty imposed on harvesting biomass, even with the relatively low carbon prices of RCPs 6.0 and 4.5, there could be 10 to 25% less forest cover in parts of the tropics by 2100 compared with the forest carbon rent policy. The forest carbon rental payment approach is expected to increase forest cover across the globe, with the more stringent mitigation scenarios leading to increases of 50% or more in many parts of the world.
A forest carbon rental approach has sometimes been considered an infeasible climate change mitigation policy option because of the complexities with measuring and verifying changes in carbon stocks and possible governance issues in developing countries (35, 38). However, placing a tax on woody bioenergy could exacerbate one of the issues the policy is intended to prevent, namely, the loss of natural forests and associated ecosystem services. Despite this, we find that increasing the demand for wood-based bioenergy, regardless of the policy approach, will increase the total forest carbon in nearly all scenarios (Fig. 3E). Under the penalty scenario, average stocks could increase by 34 gigatonnes carbon dioxide equivalent (GtCO2e) or about 1% compared with the baseline. This is equivalent to 0.4 GtCO2e/year or 1.1% of 2018 global CO2 emissions (39). Including payments for forest carbon sequestration has additional benefits. Forest area could expand by 500 Mha or more, and total carbon stocks could increase by an average of 2.3 GtCO2e/year, offsetting 7.1% of current annual emissions (Fig. 3E). In nearly all scenarios, a majority of this net increase in carbon stocks is due to increases in aboveground carbon, while the substitution of some timber to bioenergy has a somewhat negative effect (fig. S7).
Growing wood-based bioenergy demand will positively affect forest management investment regardless of the policy approach, averaging about 80% above baseline investment. Demand for wood products in general will stimulate investment as landowners are expected to accrue a higher return. However, a forest carbon rental and increased biomass demand policy could double investment compared with the biomass penalty approach (Fig. 3F). Management decisions affect the amount of carbon stored in forests in different ways. First, GTM controls rotation ages, which influences carbon stocks on sites, with higher rotation ages leading to greater timber supply and more carbon, and vice versa. Second, under high bioenergy demand and/or carbon prices, the model projects more replanting, which, compared with natural regeneration, will increase average carbon on a site over a rotation. Third, GTM shifts species types over time in response to prices and land rental values. Fourth, the model shifts species from no management to modest management (harvesting with natural regeneration or harvesting with replanting in some cases, depending on value). In nearly all cases, this conversion of older forests to younger forests leads to more timber output but less carbon. Last, GTM includes management intensity on replanted land. This type of management intensity, which could include genetic selection, fertilizing, density controls, and other approaches, increases both carbon stocks and the value of timber. This type of management intensity is monitored in the model by the expenditure per hectare of forestland, with higher expenditures leading to more timber and more carbon.