Diatom cell-size composition as a novel tool for quantitative estimates of the water table in peatlands.

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-06-01 Epub Date: 2024-06-26 DOI:10.1098/rsbl.2024.0062
Shuangyu Xu, Bing Huang, Linghan Zeng, Zhao-Jun Bu, Xianyu Huang, Xu Chen
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Abstract

Diatom cell-size composition is an indicator of aquatic environmental changes but has been rarely investigated, especially in semi-terrestrial peatlands. In this study, both taxonomic composition and cell-size composition of diatoms were analysed in 41 samples from two montane peatlands, northeastern China. Redundancy analyses revealed that diatom taxonomic composition was significantly related to the depth to the water table (DWT) and Ca2+, while cell-size composition was significantly associated with DWT and Si. DWT was the most important factor and its sole effect explained 26.2% and 17.9% of the total variance in taxonomic composition and cell-size composition, respectively. Accordingly, diatom-based water-table transfer functions were developed based on taxonomic composition and cell-size composition, respectively. The maximum-likelihood (ML) model based on diatom taxonomic composition had the best performance, with a correlation coefficient value (R2) of 0.78 and the root mean squared error of prediction (RMSEP) of 6.66 cm. The ML model based on cell-size composition had similar performance, with an R2 of 0.78 and the RMSEP of 6.87 cm, suggesting that diatom cell-size composition can be a new quantitative means to track past water-table changes. This method requires further appraisal with palaeoecological data but offers a new option that deserves exploration.

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硅藻细胞大小组成作为泥炭地地下水位定量估算的新工具。
硅藻细胞大小组成是水生环境变化的一个指标,但很少有人对其进行研究,尤其是在半陆地泥炭地中。本研究分析了中国东北地区两块山地泥炭地 41 个样本中硅藻的分类组成和细胞大小组成。冗余分析表明,硅藻分类组成与地下水位深度(DWT)和Ca2+显著相关,而细胞大小组成与DWT和Si显著相关。DWT 是最重要的因子,其单独效应分别解释了分类组成和细胞大小组成总方差的 26.2% 和 17.9%。因此,根据分类组成和细胞大小组成分别开发了基于硅藻的水位转移函数。基于硅藻分类组成的最大似然(ML)模型性能最佳,相关系数(R2)为 0.78,预测的均方根误差(RMSEP)为 6.66 厘米。基于细胞大小组成的 ML 模型性能相似,R2 为 0.78,均方根预测误差为 6.87 厘米。这种方法需要古生态学数据的进一步评估,但它提供了一种新的选择,值得探索。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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