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Diatom-based models for inferring past water chemistry in western Ugandan crater lakes

机译:基于硅藻的推断乌干达西部火山口湖过去水化学的模型

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Diatom surface sediment samples and corresponding water chemistry were collected from 56 lakes across a natural conductivity gradient in western Uganda (reflecting a regional climatic gradient of effective moisture) to explore factors controlling diatom distribution. Here we develop a regional training set from these crater lakes to test the hypothesis that this approach, by providing more appropriate and closer analogues, can improve the accuracy of palaeo-conductivity reconstructions, and so environmental inferences in these lake systems compared to larger training sets. We compare this output to models based on larger, but geographically and limnologically diverse training sets, using the European Diatom Database Initiative (EDDI) database. The relationships between water chemistry and diatom distributions were explored using canonical correspondence analysis (CCA) and partial CCA. Variance partitioning indicated that conductivity accounted for a significant and independent portion of this variation. A transfer function was developed for conductivity (r jack 2 = 0.74). Prediction errors, estimated using jack-knifing, are low for the conductivity model (0.256 log10 units). The resulting model was applied to a sedimentary sequence from Lake Kasenda, western Uganda. Comparison of conductivity reconstructions using the Ugandan crater lake training set and the East Africa training set (EDDI) highlighted a number of differences in the optima of key diatom taxa, which lead to differences in reconstructed values and could lead to misinterpretation of the fossil record. This study highlights issues of how far transfer functions based on continental-scale lake datasets such as the EDDI pan-African models should be used and the benefits that may be obtained from regional training sets.
机译:从乌干达西部的一个天然电导率梯度(反映有效水分的区域气候梯度)的56个湖泊中收集了硅藻表面沉积物样本和相应的水化学,以探索控制硅藻分布的因素。在这里,我们从这些火山口湖泊中开发了一个区域训练集,以检验以下假设:该方法通过提供更适当和更接近的类似物,可以提高古电导率重建的准确性,因此与较大的训练集相比,这些湖泊系统中的环境推断。我们使用欧洲硅藻数据库计划(EDDI)数据库,将该输出结果与基于更大的,但地理和语言学上不同的培训集的模型进行比较。使用规范对应分析(CCA)和部分CCA探索了水化学与硅藻分布之间的关系。方差划分表明,电导率占该变化的重要且独立的部分。开发了用于电导率的传递函数(r jack 2 = 0.74)。对于电导率模型,使用千斤顶刀估计的预测误差很小(0.256 log10 单位)。生成的模型应用于乌干达西部Kasenda湖的沉积序列。使用乌干达火山口湖训练集和东非训练集(EDDI)进行电导率重建的比较突出显示了主要硅藻类群的最优性存在许多差异,这导致了重建值的差异,并可能导致对化石记录的误解。这项研究突出了应该使用基于大陆尺度湖泊数据集(例如EDDI泛非模型)的传递函数有多远的问题以及可能从区域训练集中获得的收益的问题。

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