Revised fractional abundances and warm-season temperatures substantially improve brGDGT calibrations in lake sediments
Revised fractional abundances and warm-season temperatures substantially improve brGDGT calibrations in lake sediments
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DOI：
10.5194/bg-18-3579-2021
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发表时间：
2021-01
期刊：
影响因子：
4.9
通讯作者：
J. Raberg;David J. Harning;S. Crump;G. De Wet;A. Blumm;S. Kopf;Á. Geirsdóttir;G. Miller;J. Sepúlveda
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文献类型：
--
作者：
J. Raberg;David J. Harning;S. Crump;G. De Wet;A. Blumm;S. Kopf;Á. Geirsdóttir;G. Miller;J. Sepúlveda
抽象的。分支甘油二烷基甘油四醚（brGDGTs）的分布经常被用来重建陆地古温度从湖泊沉积物档案。虽然brGDGT是全球普遍存在的，这些膜脂质的微生物生产者仍然未知，排除了环境参数控制其生产和分布的方式的全面了解。在这里，我们从三个方面来推进这一理解。首先，我们提出了43个新的高纬度湖泊站点，其特点是年平均气温（MAT）低，季节性强，填补了全球数据集的一个重要空白。其次，我们介绍了一种新的方法来分析brGDGT数据，其中化合物的分数丰度（FA）计算的基础上甲基化数，甲基化位置和环化数的结构组内。最后，我们进行线性和非线性回归的结果FA对一套环境参数的编译全球湖泊沉积物数据集（n = 182）。我们发现，我们的方法去卷积的温度，电导率和pH值的趋势brGDGT，而不增加校准误差的标准方法。我们还发现，它揭示了brGDGT分布的新模式，并提供了一种方法来调查其结构多样性的生物学基础。在我们的回归中，暖季温度指数的表现优于MAT，冰点以上的月份产生了最高性能的模型（调整后的R2 = 0.91，RMSE = 1.97 °C，n = 182）。电导率的自然对数与brGDGT分布的关系第二强（调整后的R2 = 0.83，RMSE = 0.66，n = 143），在我们的数据集中明显优于pH（调整后的R2 = 0.73，RMSE = 0.57，n = 154），并为古水文学应用提供了一个潜在的新代理。我们建议将这些校准用于全球湖泊沉积物，包括高纬度地区，并详细介绍了每种校准方法的优缺点。
Abstract. Distributions of branched glycerol dialkyl glycerol tetraethers (brGDGTs) are frequently employed for reconstructing terrestrial paleotemperatures from lake sediment archives. Although brGDGTs are globally ubiquitous, the microbial producers of these membrane lipids remain unknown, precluding a full understanding of the ways in which environmental parameters control their production and distribution. Here, we advance this understanding in three ways. First, we present 43 new high-latitude lake sites characterized by low mean annual air temperatures (MATs) and high seasonality, filling an important gap in the global dataset. Second, we introduce a new approach for analyzing brGDGT data in which compound fractional abundances (FAs) are calculated within structural groups based on methylation number, methylation position, and cyclization number. Finally, we perform linear and nonlinear regressions of the resulting FAs against a suite of environmental parameters in a compiled global lake sediment dataset (n = 182). We find that our approach deconvolves temperature, conductivity, and pH trends in brGDGTs without increasing calibration errors from the standard approach. We also find that it reveals novel patterns in brGDGT distributions and provides a methodology for investigating the biological underpinnings of their structural diversity. Warm-season temperature indices outperformed MAT in our regressions, with Months Above Freezing yielding the highest-performing model (adjusted R2 = 0.91, RMSE = 1.97 °C, n = 182). The natural logarithm of conductivity had the second-strongest relationship to brGDGT distributions (adjusted R2 = 0.83, RMSE = 0.66, n = 143), notably outperforming pH in our dataset (adjusted R2 = 0.73, RMSE = 0.57, n = 154) and providing a potential new proxy for paleohydrology applications. We recommend these calibrations for use in lake sediments globally, including at high latitudes, and detail the advantages and disadvantages of each.