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Assessing the externalities of timber production
Forest Policy and Economics ( IF 4 ) Pub Date : 2021-11-20 , DOI: 10.1016/j.forpol.2021.102646
Timo Pukkala 1
Affiliation  

Responsible forest policy promotes management that does not impair the multiple uses of forests or decrease their regulative effects and biological diversity. The most important regulative effect of boreal forests is their ability to remove carbon dioxide from the atmosphere. High biological diversity improves the resilience of forest ecosystems and forest-based economies, enhancing the long-term sustainability of forest production. This study developed a method for assessing the performance of forest management in terms of its effects on multiple uses, biodiversity, and carbon sequestration. These externalities were described with 11 indicator variables, which can be calculated for any Finnish forest stand from the current forest inventory data with currently available models and algorithms. The indicator variables were normalized based on the ranges of the indicator variables in Finnish forests on different sites. The forest-level averages of the normalized indicator variables were used to calculate a multiplicative externality score for the forest. The developed method for calculating the forest-wide externality score was used in two forest holdings for alternative silvicultural systems. The case study results suggested that continuous cover management enhances the positive externalities of timber production, as compared to even-aged rotation forestry. Green-tree retention improved the externality score in both silvicultural systems. Maximizing the net present value of timber production in rotation forestry decreased the externality score by about 50% compared to a non-managed forest. The decrease was about 30% smaller in continuous cover forestry.



中文翻译:

评估木材生产的外部性

负责任的森林政策促进不损害森林的多种用途或减少其调节作用和生物多样性的管理。北方森林最重要的调节作用是它们从大气中去除二氧化碳的能力。高度的生物多样性提高了森林生态系统和以森林为基础的经济的复原力,增强了森林生产的长期可持续性。本研究开发了一种方法,用于评估森林管理对多种用途、生物多样性和碳固存的影响。这些外部性用 11 个指标变量来描述,这些变量可以用当前可用的模型和算法从当前的森林清单数据中计算出任何芬兰林分。根据芬兰不同地点森林中指标变量的范围对指标变量进行了归一化处理。归一化指标变量的森林级平均值用于计算森林的乘法外部性得分。用于计算森林范围外部性得分的开发方法被用于替代造林系统的两个森林持有量。案例研究结果表明,与等龄轮作林业相比,连续覆盖管理增强了木材生产的正外部性。绿树保留提高了两种造林系统的外部性得分。与非管理森林相比,在轮作林业中最大化木材生产的净现值可使外部性得分降低约 50%。

更新日期:2021-11-20
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