The demand for forest biomass has significantly increased due to renewable energy and climate policies, and this trend is projected to continue. While forest bioenergy holds potential as a climate solution, its sustainability and effect on forest carbon balance remain debated. Some studies suggest that using forest biomass for energy leads to a terrestrial carbon debt taking decades to repay, focusing on individual forest stands and assuming constant prices. These single-site models are criticized for ignoring market dynamics and the capacity of forest managers to respond to price signals. Conversely, other studies, using market-scale models, show that increased bioenergy demand can boost forest carbon storage, dependent on private forest investments, policies, and land use changes. A key methodological difference lies in how price expectations are incorporated. Static equilibrium models often assume a fixed forested land base and limited landowner response to market signals. Dynamic models, however, account for landscape-level decisions and allow adjustments in management response to prices. A crucial question is whether carbon debt is an appropriate measure of carbon neutrality at the market level, especially considering spatial and temporal aspects. Single-site models, lacking a comprehensive view of carbon flux across a region, do not fully capture the complexities of carbon neutrality. Finally, the treatment of forest investments clearly differentiates static and dynamic forest sector models (FSMs). Static models assume constant replanting post-harvest, while dynamic models account for endogenous land use and management responses to changing market prices. Historical data support the forward-looking nature of timber markets, indicating adjustments in planting and management intensity based on price expectations. This study uses a dynamic global economic FSM (GTM) to assess forest carbon debt and payback periods, focusing on economic factors influencing their size and duration, expanding the definition of carbon debt to measure an aggregate global outcome.

The literature on forest bioenergy's impact on carbon emissions is divided. Some studies, using stand-level life cycle analyses (LCA), show a significant carbon debt due to the delay in regrowth after harvest, assuming constant market conditions and disregarding the opportunity cost of land. These models often predict long repayment periods and question bioenergy's short-term climate benefits. Other studies, employing market-scale models, suggest that increased bioenergy demand can stimulate forest management and expansion, leading to higher overall carbon sequestration. These models incorporate economic factors like timber prices and landowner responses to market incentives. A key difference between these contrasting views lies in the methodological treatment of market dynamics and the adaptive capacity of forest management. Single-stand models generally assume static conditions, while market-scale models capture land-use change and the dynamic interactions between markets and management decisions. Existing literature often neglects the holistic picture of regional carbon fluxes and fails to account for alternative land-use scenarios. Static FSMs typically underestimate the impact of increasing timber prices on replanting and intensification efforts, leading to underestimation of long-term carbon storage gains.

This study utilizes the Global Timber Model (GTM), a dynamic partial equilibrium model that maximizes timber market welfare over time across approximately 350 global regions. GTM incorporates forest stand age, composition, management intensity, acreage, production costs, and land rental costs over a 200-year timeframe. Land classes are linked to vegetation types from ecosystem models like BIOME/LPX-Bern and MC2. The model's baseline scenario includes historical climate change effects, but excludes future climate change impacts. Demand-side factors are modeled via exogenous changes in population, income, consumer preferences, and technology. The supply side features forestland with varying biological yield functions, influenced by management, harvest, processing costs, and regional agricultural land rents. The model optimizes an objective function that incorporates demand for industrial wood products (sawtimber and pulpwood), demand for forest biomass for bioenergy (Q_b), harvesting and transportation costs (C_H), management costs (C_G), costs of new forestland (C_N), and opportunity costs of land (R(X_iat)). The total quantity of wood is determined by the harvested area and yield function which incorporates ecological productivity and management intensity. The model endogenously determines the optimal land allocation among timber and agriculture through a rental supply function that considers competition for land. An international timber market is assumed, leading to a global market-clearing price. Forest carbon stock is calculated by summing four pools: aboveground carbon, soil carbon, market carbon (harvested wood products), and slash carbon. Aboveground carbon is linked to total biomass, market carbon tracks carbon in wood products accounting for decay, and soil carbon captures changes due to land-use change and management. Slash carbon accounts for residual biomass after harvest and its decomposition. The model assesses 51 biomass demand pathways with varying initial quantities and growth rates. Forest carbon debt is the difference between forest carbon stock in a biomass demand scenario and the baseline scenario, and the payback period is the time it takes for the scenario stock to surpass the baseline stock. The analysis explores the impact of supply constraints, such as limitations on natural forests or plantations.

The GTM simulations reveal that the introduction of biomass demand causes an initial reduction in forest carbon stock across all scenarios, resulting in forest carbon debt. The magnitude of this debt varies, ranging from modest to approximately 1 GtCO2e yr⁻¹, particularly evident in low-demand growth scenarios. Scenarios with biomass demand growth below 3% generally do not fully recover this debt and may show further increases over time. In contrast, scenarios with growth rates above 3% consistently recover the initial debt, some showing significant increases in long-term carbon storage. A low biomass demand growth rate (<1% yr⁻¹) and low relative price growth are identified as primary contributors to sustained carbon debt. Higher growth rates (>3%) lead to full carbon debt recovery within 20 to 70 years, depending on demand levels. The decomposition of carbon stock into pools shows that much of the carbon debt stems from reduced carbon in long-lived wood products, rather than directly from reduced forest carbon stocks. The effect of forest product substitution is highlighted; constant demand primarily leads to substitution among products, not overall value increases, causing a decline in carbon sequestered in products. Aboveground carbon gains are crucial for debt recovery, driven by forest area expansion and increased management intensity. Higher demand growth rates (>3%) result in greater investments in land conversion and forest management, offsetting the substitution effect. Low average management intensity and forest area expansion are associated with carbon debt scenarios. Excluding market carbon from the calculation changes the outcome; fewer scenarios experience carbon debt, and those that do see shorter payback periods. Supply regulations, limiting natural forest use or plantation expansion, reduce the payback period but do not eliminate initial carbon debt, leaving scenarios with growth rates below 3% to still exhibit debt even with constraints.

The findings suggest that stand-level analyses may not adequately project the emissions implications of bioenergy policies, neglecting the role of markets and investment decisions. The timing of bioenergy production and consumption is critical. A positive net change in total forest carbon storage after the initial debt can be interpreted as net negative emissions, even without carbon capture and storage, assuming full emissions from biomass energy. Alternative market expansion pathways for forest biomass, beyond bioenergy, could enhance carbon storage in both terrestrial and wood product pools but might reduce emissions displacement potential. The study suggests that policies aimed at increasing managed forest productivity can complement bioenergy's climate goals. The results highlight the need for holistic assessments encompassing various economic and ecological factors. Further research could explore detailed life cycle assessments of bioenergy pathways and the potential tradeoffs of alternative demand-side policies.

This study demonstrates the critical influence of economic factors on the carbon implications of forest bioenergy expansion. The findings highlight the limitations of stand-level assessments and underscore the importance of dynamic models that incorporate market interactions and forest management responses. Sustained carbon debt is more likely under low-growth demand scenarios, while higher growth rates facilitate debt recovery. Supply regulations can shorten payback periods but may not completely avoid initial debt. The research emphasizes the need for integrated policies that consider economic incentives, forest management practices, and the broader implications of biomass use on ecosystems.

The study uses a global model, which may not capture the nuances of regional variations in forest ecosystems and economic conditions. The model focuses on carbon sequestration, neglecting the impact on other ecosystem services. The baseline scenario doesn't include future climate change impacts, which could affect forest growth and carbon dynamics. The analysis doesn't explicitly incorporate details of carbon capture and storage (CCS) technologies or emissions from biomass transport and processing.