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Inferring Past Trends in Lake Water Organic Carbon Concentrations in Northern Lakes Using Sediment Spectroscopy

机译:使用沉积光谱推断北湖湖水有机碳浓度的过去趋势

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摘要

Changing lake water total organic carbon (TOC)concentrations are of concern for lake management because of corresponding effects on aquatic ecosystem functioning, drinking water resources and carbon cycling between land and sea. Understanding the importance of human activities on TOC changes requires knowledge of past concentrations; however, water-monitoring data are typically only available for the past few decades, if at all. Here, we present a universal model to infer past lake water TOC concentrations in northern lakes across Europe and North America that uses visible-near-infrared (VNIR) spectroscopy on lake sediments. In the orthogonal partial least squares model, VNIR spectra of surface-sediment samples are calibrated against corresponding surface-water TOC concentrations (0.5–41 mg L-1) from 345 Arctic to northern temperate lakes in Canada, Greenland, Sweden and Finland. Internal model-cross-validation resulted in a R2 of 0.57 and a prediction error of 4.4 mg TOC L-1. First applications to lakes in southern Ontario and Scotland, which are outside of the model’s geographic range, show the model accurately captures monitoring trends, and suggests that TOC dynamics during the 20th century at these sites were primarily driven by changes in atmospheric deposition. Our results demonstrate that the lake-water TOC model has multi-regional applications and is not biased by post-depositional diagenesis, allowing the identification of past TOC variations in northern lakes of Europe and North America over timescales of decades to millennia.
机译:改变湖水总有机碳(TOC)浓度对湖泊管理有所关注,因为对水生态系统运作,饮用水资源和陆地循环循环的相应影响。了解人类活动对TOC变化的重要性需要了解过去浓度;但是,如果有的话,水监测数据通常仅在几十年中可用。在这里,我们提出了一种普遍的模型,可在欧洲和北美北部湖泊中推断出湖水TOC浓度,这些模型在欧洲和北美使用湖泊沉积物上可见近红外(VNIR)光谱。在正交的部分最小二乘模型中,表面沉积物样品的VNIR光谱与来自加拿大,格陵兰州,瑞典和芬兰的北温带湖到北温带湖的345北极的相应的表面 - 水TO C浓度(0.5-41mg L-1)校准。内部模型交叉验证导致R2为0.57和4.4 mg TOC L​​-1的预测误差。在南安大略省南部和苏格兰的第一个应用,这些应用于模型的地理范围,表明模型准确地捕获了监测趋势,并提出了在20世纪20世纪的TOC动态主要由大气沉积的变化驱动。我们的结果表明,湖水TOC模型具有多区域应用,并未被沉积后成岩作用偏见,允许识别欧洲和北美北部湖泊的过去的变化,几十年到千年。

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