Variability in fluorescent dissolved organic matter concentrations across diel to seasonal time scales is driven by water temperature and meteorology in a eutrophic reservoir
Variability in fluorescent dissolved organic matter concentrations across diel to seasonal time scales is driven by water temperature and meteorology in a eutrophic reservoir
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DOI：
10.1007/s00027-021-00784-w
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发表时间：
2021-02
期刊：
影响因子：
2.4
通讯作者：
Dexter W. Howard;A. Hounshell;M. Lofton;W. Woelmer;P. Hanson;C. Carey
中科院分区：
文献类型：
--
作者：
Dexter W. Howard;A. Hounshell;M. Lofton;W. Woelmer;P. Hanson;C. Carey
淡水水库通过处理和储存大量的溶解有机质（DOM），在全球碳循环中发挥着重要作用。在多个时间尺度上量化DOM波动的幅度可以促进我们对水库碳循环控制如何变化的理解。在美国弗吉尼亚州西南部的一个富营养化水库中，我们使用原位电磁传感器以10分钟的分辨率监测了一年多的荧光DOM (fDOM)，该水库溶解有机碳浓度低（2-6 mg L−1）。利用连续小波变换和自回归时间序列模型确定了fDOM浓度变化的主要时间尺度和关键环境预测因子。全年fDOM浓度变化很大，秋季浓度最高（30.0个硫酸奎宁单位），春季浓度最低（4.7个硫酸奎宁单位）。月变率以时间尺度为主，日变率在夏季显著。基于自回归时间序列分析，降水、水温和短波辐射是fDOM在日尺度上的重要环境预测因子，而水温对月变化的预测效果最好。我们的研究首次揭示了全年fDOM浓度的实质性变化，强调了长期、高频的原位DOM监测的必要性，以捕捉多个时间尺度上发生的变化。通过量化fDOM在不同时间尺度上的变异性和环境预测因子，我们能够更好地理解DOM浓度全年变化的方式和原因。
Freshwater reservoirs play a significant role in the global carbon cycle by processing and storing large quantities of dissolved organic matter (DOM). Quantifying the magnitude of DOM fluctuations across multiple temporal scales can advance our understanding of how the controls on reservoir carbon cycling may vary. We monitored fluorescent DOM (fDOM) using an in situ epilimnetic sensor at a ten-minute resolution over one year in a eutrophic reservoir in southwestern Virginia, USA with low dissolved organic carbon concentrations (2–6 mg L−1). We determined the dominant time scales of variability and key environmental predictors of fDOM concentrations using continuous wavelet transforms and autoregressive time series modeling. Throughout the year, fDOM concentrations varied considerably, with maximum concentrations in the autumn (30.0 quinine sulfate units) and minimum concentrations in the spring (4.7 quinine sulfate units). The monthly time scale was the dominant time scale of variability, but the daily time scale was significant during the summer. Based on the autoregressive time series analysis, precipitation, water temperature, and shortwave radiation were important environmental predictors of fDOM on daily time scales, while water temperature alone best predicted monthly variability. Our study is one of the first to reveal substantial variability in fDOM concentrations during a full year, emphasizing the need for long-term, high-frequency in situ DOM monitoring to capture changes occurring on multiple time scales. By quantifying the variability and environmental predictors of fDOM on different time scales, we are able to better understand how and why DOM concentrations change throughout the year.