In recent decades, the carbon sink provided by the U.S. forest sector has offset a sizable portion of domestic greenhouse gas (GHG) emissions. In the future, the magnitude of this sink has important implications not only for projected U.S. net GHG emissions under a reference case but also for the cost of achieving a given mitigation target. The larger the contribution of the forest sector towards reducing net GHG emissions, the less mitigation is needed from other sectors. Conversely, if the forest sector begins to contribute a smaller sink, or even becomes a net source, mitigation requirements from other sectors may need to become more stringent and costlier to achieve economy wide emissions targets. There is acknowledged uncertainty in estimates of the carbon sink provided by the U.S. forest sector, attributable to large ranges in the projections of, among other things, future economic conditions, population growth, policy implementation, and technological advancement. We examined these drivers in the context of an economic model of the agricultural and forestry sectors, to demonstrate the importance of cross-sector interactions on projections of emissions and carbon sequestration. Using this model, we compared detailed scenarios that differ in their assumptions of demand for agriculture and forestry products, trade, rates of (sub)urbanization, and limits on timber harvest on protected lands. We found that a scenario assuming higher demand and more trade for forest products resulted in increased forest growth and larger net GHG sequestration, while a scenario featuring higher agricultural demand, ceteris paribus led to forest land conversion and increased anthropogenic emissions. Importantly, when high demand scenarios are implemented conjunctively, agricultural sector emissions under a high income-growth world with increased livestock-product demand are fully displaced by substantial GHG sequestration from the forest sector with increased forest product demand. This finding highlights the potential limitations of single-sector modeling approaches that ignore important interaction effects between sectors.

近几十年来，美国森林部门提供的碳汇抵消了相当大一部分国内温室气体 (GHG) 排放。在未来，这种汇的大小不仅对参考案例下预计的美国温室气体净排放量具有重要影响，而且对实现给定缓解目标的成本也有重要影响。森林部门对减少温室气体净排放量的贡献越大，其他部门所需的减排量就越少。相反，如果森林部门开始贡献较小的汇，甚至成为净源，其他部门的减排要求可能需要变得更加严格和成本更高，以实现经济范围内的排放目标。美国林业部门提供的碳汇估算存在公认的不确定性，这归因于对未来经济状况、人口增长、政策实施和技术进步等预测的大范围变化。我们在农业和林业部门的经济模型背景下研究了这些驱动因素，以证明跨部门互动对排放和碳固存预测的重要性。使用该模型，我们比较了对农林产品需求、贸易、（郊区）城市化率和受保护土地上木材采伐限制的假设不同的详细情景。我们发现，假设对林产品的更高需求和更多贸易的情景导致森林增长增加和温室气体净封存量增加，而以农业需求增加为特征的情景，在其他条件不变的情况下，导致林地转变和人为排放增加。重要的是，当同时实施高需求情景时，在高收入增长世界和畜产品需求增加的情况下，农业部门的排放完全被森林部门的大量温室气体封存和林产品需求的增加所取代。这一发现凸显了忽略部门间重要相互作用效应的单部门建模方法的潜在局限性。