Increased demands for timber products remove carbon from forests, however previous literature has suggested that higher resulting prices could spur forestland expansion, ameliorating the forest carbon impacts. We examine the impacts on forest carbon from harvest increases with an empirical forest sector model, coupled with an econometric model of endogenous land use change that differentiates the impacts of population, income, and pine plantation rents among forest management types and non-forest land uses. We explore the sensitivity of forest area and carbon to a suite of scenarios by varying timber product demands combined with a sensitivity analysis on pine plantation responses to pine plantation rents. The econometric results show that pine plantation rents lead to increases in pine plantation area and that all non-urban land uses are negatively related to both per capita income and population. Scenario projections show that (1) higher pulpwood demands driven by wood pellets lead to lower forest carbon outcomes; (2) higher sawtimber demands exacerbate the known cycles in sawtimber prices and result in corresponding cycles in forest area and carbon. All scenarios show increases in forest carbon over time, though some scenarios increase faster than others. Within the study period, the highest forest carbon level is achieved by the high sawtimber demand and low pulpwood demand scenario. Long term growth cycles over the course of the projection period, however, lead to alternating forest carbon outcomes, indicating that conclusions about forest carbon depend on the projection length.

中文翻译：

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美国东南部产品需求增加和土地利用变化下的森林碳


对木材产品的需求增加会去除森林中的碳，但以前的文献表明，由此产生的价格上涨可能会刺激林地扩张，从而减轻森林的碳影响。我们使用实证林业部门模型以及内生土地利用变化的计量经济学模型来研究采伐增加对森林碳的影响，该模型区分了森林管理类型和非林地利用之间人口、收入和松树种植园租金的影响。我们通过改变木材产品需求并结合松树种植园对松树人工林租金反应的敏感性分析，探讨了森林面积和碳对一系列情景的敏感性。计量经济学结果表明，松树人工林租金导致松树人工林面积增加，并且所有非城市土地利用都与人均收入和人口呈负相关。情景预测表明，（1） 木屑颗粒导致纸浆木材需求增加，导致森林碳含量降低;（2） 更高的锯材需求加剧了锯材价格的已知周期，并导致林面积和碳的相应周期。所有情景都显示森林碳随时间增加，尽管有些情景比其他情景增长得更快。在研究期间，高锯材需求和低纸浆木材需求情景实现了最高的森林碳水平。然而，预测期内的长期生长周期导致森林碳结果交替出现，这表明关于森林碳的结论取决于预测长度。