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Biases in RCS tree ring chronologies due to sampling heights of trees

机译:由于树的采样高度,RCS树年轮时序中的偏差

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The Regional Curve Standardization (RCS) is one of the most employed standardization methods to remove biological signals in long tree ring chronologies. The approach assumes that an overall age-related growth trend typify all tree ring series to be included in a standardized tree ring chronology. Although several potential problems of the method have been examined, the influence of varying the sampling height along tree stems has not been evaluated. Considering that age-related growth trends may vary with stem height, biases may arise when combining samples from unknown or variable sampling heights, a frequent situation with subfossil logs. In this study we perform a detailed stem analysis of 15 lakeshore black spruce (Picea mariana Mill. B.S.P.) trees in the taiga of eastern Canada to describe how the age-related growth trend varies with stem height and evaluate associated biases in RCS chronologies built from living and subfossil trees. Results show that the age-related growth trends vary markedly and systematically along stems, potentially generating large methodological biases in RCS chronologies, especially near the recent chronology end. These biases may lead to erroneous reconstructions of recent climatic trends and cause false divergence between tree ring and climate series. We have developed a correction procedure that appears efficient in removing these biases from chronologies built with the lakeshore trees and associated subfossil logs. (C) 2015 Elsevier GmbH. All rights reserved.
机译:区域曲线标准化(RCS)是在长树年轮年代中去除生物信号的最常用的标准化方法之一。该方法假设与年龄相关的总体增长趋势代表了所有要归入标准化树年轮年表的树年轮系列。尽管已经研究了该方法的几个潜在问题,但尚未评估沿树茎改变采样高度的影响。考虑到与年龄相关的生长趋势可能随茎高而变化,将来自未知或可变采样高度的样品合并在一起时可能会出现偏差,这是亚化石测井的常见情况。在这项研究中,我们对加拿大东部针叶林的15个湖岸黑云杉(Picea mariana Mill。BSP)树进行了详细的茎分析,以描述与年龄相关的生长趋势如何随茎高变化,并评估了从活体和亚化石树。结果表明,与年龄相关的生长趋势沿茎明显而系统地变化,可能在RCS年表中产生较大的方法学偏差,尤其是在最近的年表末期。这些偏见可能导致错误地重建最近的气候趋势,并导致树木年轮与气候系列之间出现错误的分歧。我们已经开发出一种纠正程序,该纠正程序看起来很有效,可以消除湖岸树木和相关的化石记录所建立的年代学中的这些偏差。 (C)2015 Elsevier GmbH。版权所有。

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