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Drivers of stem radial variation and its pattern in peatland Scots pines: A pilot study

机译:茎径向变异的驱动因素及其在泥炭地苏格兰松树中的模式:试验研究

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Dendrometers are useful tools to analyze intra-annual variation of radial growth in trees, but have rarely been applied in marginal environments. Our aim in this study was to explore stem radial variation (SRV) of Scots pines (Pinus sylvestrisL.) growing in a marginal environment on top of a peatland and compare it with stem radial variation of Scots pines growing in a nearby forest. We compared high-resolution (30?min) tree-growth of the peatland and forest pines in two consecutive years in two ways. First, we modeled raw SRV using site and weather parameters as predictors, to determine if and in what way stem radial variation depends on the site type. Second, we split the SRV signal into sub-series of varying length to test for differences between the time-series pattern of peatland and forest SRV with clustering methods and classifier models. We found indications that site type is influencing raw stem radial variation as: 1) an intercept, i.e. forest trees tended to grow more than peatland trees (as expected); 2) an interaction factor with structural and weather parameters, i.e. response of the forest trees to changing environmental parameters was different than the response of the peatland trees. Conversely, with regard to the temporal pattern of the stem radial variation, we found that the conditions within one year, e.g. weather patterns, were more important than site conditions, especially at short time scales. However, with increasing length of the sub-series the relative accuracy of the classifier models increased. Our results indicate that the site type was important for the raw SRV (amplitude) but not for the SRV pattern, which might be important to consider when comparing intra-annual signals from multiple sites.
机译:树枝状仪是分析树木中径向生长的年内变化的有用工具,但很少应用于边际环境。我们本研究的目的是探索苏格兰污水松树(Pinus Sylvestrisl的SRV)的茎径向变异(SRV)在泥炭地顶部的边缘环境中生长,并与在附近森林中生长的苏格兰松树的茎径向变化进行比较。我们以两种方式在连续两年中比较了泥炭地和森林松树的高分辨率(30?分钟)树 - 生长。首先,我们使用站点和天气参数作为预测器建模原始SRV,以确定阀辐射变化是否依赖于站点类型。其次,我们将SRV信号分成不同长度的子系列,以测试泥炭地和森林SRV的时间序列模式与聚类方法和分类器模型之间的差异。我们发现迹象表明,现场类型影响原始茎径向变化为:1)拦截,即林木往往比泥炭地树木(如预期)更长; 2)具有结构和天气参数的相互作用因子,即森林树木改变环境参数的响应不同于泥炭地树的响应。相反,关于茎径向变异的时间图案,我们发现一年内的条件,例如,天气模式,比现场条件更重要,特别是在短时间尺度。然而,随着子系列的增加而增加,分类器模型的相对精度增加。我们的结果表明,站点类型对于原始SRV(幅度)很重要,但不适用于SRV模式,在比较来自多个站点的年内信号时可能很重要。

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