This study examined optimal harvesting decisions of multiple age-class private forests that maximize private forest owners’ utility. For this analysis, we developed two scenarios. One scenario was to maintain the harvest level currently performed in the Republic of Korea (ROK) (baseline scenario), and the other was to harvest according to the harvest prescription derived from the discrete-time utility model with a multiple age-class forest (optimization scenario). For the baseline scenario, the cohort component approach was applied to predict changes in the forest’s age structure under the given harvest level. For the optimization scenario, we applied a discrete-time utility model that can describe the consumption and cutting behavior of private forest owners who manage a multiple age-class forest. Then, we compared the changes of the timber supply level and forest structure dynamic by scenarios. The results showed that current harvesting in ROK is not at its optimal level. The baseline scenario results showed that if the current level of harvesting is maintained, a total of 1,315,000 m³ of soft wood will be supplied annually. However, the average annual wood supply will increase to 11,522,000 m³ under the maximized utility scenario. In terms of timber self-sufficiency, if all domestic wood produced is supplied as materials, the supply level from the optimization scenario will meet the government’s policy goal of a 30% timber self-sufficiency rate. However, if the baseline scenario is maintained, supply shortages can be expected by 2050.

中文翻译：

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大韩民国私有针叶林实用最大化采伐决策模型

这项研究检查了多个年龄级私有林的最佳采伐决策，这些决策可以最大程度地发挥私有林所有者的效用。对于此分析，我们开发了两种方案。一种方案是维持大韩民国（ROK）当前执行的采伐水平（基准方案），另一种方案是根据具有多个年龄级森林的离散时间效用模型得出的采伐处方进行采伐（优化方案）。对于基准情景，采用了同类群组方法来预测在给定采伐水平下森林年龄结构的变化。对于优化方案，我们应用了离散时间效用模型，该模型可以描述管理多个年龄级森林的私有林所有者的消耗和采伐行为。然后，我们通过情景比较了木材供应水平和森林结构动态的变化。结果表明，韩国目前的收割未达到最佳水平。基准情景的结果表明，如果维持目前的收割水平，则总计1,315,000 m每年将供应³软木。但是，在最大程度利用效用的情况下，年平均木材供应量将增加到11,522,000 m ³。在木材自给自足方面，如果将所有生产的家用木材都作为原料供应，那么优化方案的供应水平将满足政府设定的30％木材自给率的政策目标。但是，如果维持基准情景，到2050年将出现供应短缺。