This paper uses Monte Carlo methods and regression analysis to assess the role of uncertainty in yield function and land supply elasticity parameters on land use, carbon, and market outcomes in a long-term dynamic model of the global forest sector. The results suggest that parametric uncertainty has little influence on projected future timber prices and global output, but it does have important implications for regional projections of outputs. A wide range of outcomes are possible for timber outputs, depending on growth and elasticity parameters. Timber output in the U.S., for instance, could change by -67 to +98 million m3 per year by 2060. Despite uncertainty in the parameters, our analysis suggests that the temperate zone may sequester +30 to +79 Pg C by 2060 and +58 to +114 Pg C by 2090 while the tropics are projected to store -35 to +70 Pg C and -33 to +73 Pg C for the same time periods, respectively. Attributional analysis shows that uncertainty in the parameters regulating forest growth has a more important impact on projections of future carbon storage than uncertainty in the land supply elasticity parameters. Moreover, the results suggest that understanding growth parameters in regions with large current carbon stocks is most important for making future projections of carbon storage.

本文使用蒙特卡罗方法和回归分析来评估不确定性在全球森林部门长期动态模型中对土地利用、碳和市场结果的产量函数和土地供应弹性参数的作用。结果表明，参数不确定性对预计的未来木材价格和全球产量影响不大，但对区域产量预测具有重要影响。取决于生长和弹性参数，木材产出可能会产生广泛的结果。例如，到 2060 年，美国的木材产量可能每年变化 -67 至 +9800 万立方米。尽管参数存在不确定性，我们的分析表明，到 2060 年，温带地区可能会隔离 +30 至 +79 Pg C，到 2090 年将隔离 +58 至 +114 Pg C，而预计热带地区将储存 -35 至 +70 Pg C 和 -33 至 +73 Pg C分别在相同的时间段内。归因分析表明，调节森林生长的参数的不确定性对未来碳储量的预测比土地供应弹性参数的不确定性具有更重要的影响。此外，结果表明，了解当前碳储量较大的地区的增长参数对于未来预测碳储量至关重要。归因分析表明，调节森林生长的参数的不确定性对未来碳储量的预测比土地供应弹性参数的不确定性具有更重要的影响。此外，结果表明，了解当前碳储量较大的地区的增长参数对于未来预测碳储量至关重要。归因分析表明，调节森林生长的参数的不确定性对未来碳储量的预测比土地供应弹性参数的不确定性具有更重要的影响。此外，结果表明，了解当前碳储量较大的地区的增长参数对于未来预测碳储量至关重要。