The storage of significant amounts of timber from thrown or dead trees after natural disturbances is an established practice for forest enterprises. Timber storage mitigates economic losses caused by supply-driven timber price falls after natural disturbances. We use a forest accounting database to explore the controls of residence times of coniferous timber stocks in storage following severe storm events. We characterize forest enterprises’ timber stock outflow distributions from storage over several years by mean residence times and their variances. We conduct regression analyses on the expected residence times and their variances. We assess the significance of several explanatory variables representing economic, institutional and tree species-related factors on these metrics using multiple linear regression analyses. Illustrating the effect of these variables on timber storage residence time distributions we reanalyze the database by grouping the FADN data sets with regard to the identified control variables and determine their mean timber storage outflow distributions after the storm events as well as associated expected residence times and their variances. Applying the resulting parameters with the continuous gamma distribution to simulate TSO residence time distributions clearly illuminates the effect of the control variables on storage management. We show that besides market price dynamics, species groups, ownership categories and forest worker capacities are statistically significant controls for mean residence times of timber stock in storage and their variances. We find that stronger timber price falls correlate with shorter mean residence times of timber stocks in storage. We relate this to liquidity maintenance of forest enterprises. We model duration times parameterizing the Gamma distribution. The application of the Gamma distribution to characterize storage management behavior offers the potential to describe differences in timber stock quantities even on shorter timescales than the mean storage residence times. According to our results, we propose to assess timber stocks in storage over a multi-year period in order to improve related national and international accounting schemes.

中文翻译：

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探索严重风暴事件后木材库存在储存中的停留时间控制

在自然扰动之后，大量来自被抛树或死树的木材的储存是林业企业的既定做法。木材储存减轻了自然干扰后供应驱动的木材价格下跌造成的经济损失。我们使用森林会计数据库来探索在严重风暴事件后对存储中的针叶材库存的停留时间的控制。我们通过平均停留时间及其差异来表征森林企业在几年内从储存中流出的木材库存分布。我们对预期停留时间及其方差进行回归分析。我们使用多元线性回归分析评估代表经济、制度和树种相关因素的几个解释变量对这些指标的重要性。为了说明这些变量对木材储存停留时间分布的影响，我们通过将 FADN 数据集与已识别的控制变量相关联并确定它们在风暴事件后的平均木材储存流出分布以及相关的预期停留时间和它们的差异。应用具有连续伽马分布的结果参数来模拟 TSO 停留时间分布，清楚地阐明了控制变量对存储管理的影响。我们表明，除了市场价格动态之外，物种组、所有权类别和森林工人能力是对储存木材库存的平均停留时间及其方差的统计显着控制。我们发现，木材价格下跌幅度越大，木材库存在储存中的平均停留时间越短。我们将此与林业企业的流动性维护联系起来。我们对参数化 Gamma 分布的持续时间进行建模。应用 Gamma 分布来表征存储管理行为，即使在比平均存储停留时间更短的时间尺度上，也可以描述木材库存量的差异。根据我们的结果，我们建议评估多年储存的木材库存，以改进相关的国家和国际会计计划。应用 Gamma 分布来表征存储管理行为，即使在比平均存储停留时间更短的时间尺度上，也可以描述木材库存量的差异。根据我们的结果，我们建议评估多年储存的木材库存，以改进相关的国家和国际会计计划。应用 Gamma 分布来表征存储管理行为，即使在比平均存储停留时间更短的时间尺度上，也可以描述木材库存量的差异。根据我们的结果，我们建议评估多年储存的木材库存，以改进相关的国家和国际会计计划。