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首页> 外文期刊>Journal of paleolimnology >Fourier-transform infrared spectroscopy (FTIRS), a new method to infer past changes in tree-line position and TOC using lake sediment
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Fourier-transform infrared spectroscopy (FTIRS), a new method to infer past changes in tree-line position and TOC using lake sediment

机译：傅里叶变换红外光谱（FTIRS），一种利用湖沉积物推断树线位置和TOC过去变化的新方法

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摘要

This study tests the hypothesis that Fourier-transform infrared spectroscopy (FTIRS) of lake sediments can be used to infer past changes in tree-line position and total organic carbon (TOC) content of lake water. A training set of 100 lakes from northern Sweden spanning a broad altitudinal and TOC gradient from 0.7 to 14.9 mg/l was used to assess whether vegetation zones and TOC can be modelled from FTIR spectra of surface sediments (0-1 cm) using principal component analysis (PCA) and partial least squares (PLS) regression. Preliminary results show that FTIRS of lake sediments can be used to reconstruct past changes in tree line and the TOC content of lake water, which is hardly surprising since FTIRS registers the properties of organic and minerogenic material derived from the water mass and the drainage area. The FTIRS model for TOC gives a root mean squared error (RMSECV) of calibration of 1.4 mg/l (10% of the gradient) assessed by internal cross-validation (CV) yielding an R-cv(2) of 0.64. This should be compared with a near-infrared spectroscopy (NIRS) and diatom transfer function for TOC from the same set of lakes, which have a R-cv(2) of 0.61 and 0.31, and RMSECV of 1.6 and 2.3 mg/l, respectively. The FTIRS-TOC model was applied to a Holocene sediment core from a tree-line lake and the results show similar trends as inferences from NIRS and pollen from the same core. Overall, the results indicate that changes in FTIR spectra from lake sediments reflect differences in catchment vegetation and TOC, and that FTIRS-models based on surface-sediment samples can be applied to sediment cores for retrospective analysis.
机译：这项研究检验了以下假设：湖沉积物的傅里叶变换红外光谱（FTIRS）可用于推断过去树线位置和湖水中总有机碳（TOC）含量的变化。瑞典北部的一个100个湖泊的训练集跨越了0.7至14.9 mg / l的高海拔和TOC梯度，用于评估是否可以使用主要成分通过表面沉积物（0-1 cm）的FTIR光谱模拟植被区和TOC分析（PCA）和偏最小二乘（PLS）回归。初步结果表明，湖泊沉积物的FTIRS可用于重构树木线和湖水中TOC含量的过去变化，这并不令人惊讶，因为FTIRS记录了源自水体和流域的有机和成矿物质的特性。通过内部交叉验证（CV）评估的TOC的FTIRS模型给出的校准均方根误差（RMSECV）为1.4 mg / l（梯度的10％），得出R-cv（2）为0.64。这应该与来自同一组湖泊的TOC的近红外光谱（NIRS）和硅藻传递函数进行比较，R-cv（2）分别为0.61和0.31，RMSECV为1.6和2.3 mg / l，分别。 FTIRS-TOC模型被应用于一个树线湖泊的全新世沉积岩心，结果显示出与来自NIRS和来自同一岩心的花粉推断相似的趋势。总体而言，结果表明，湖泊沉积物的FTIR光谱变化反映了集水区植被和TOC的差异，并且基于表面沉积物样本的FTIRS模型可以应用于沉积物芯进行回顾性分析。

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