Abstract: Picophytoplankton are essential components of phytoplankton in the oligotrophic South China Sea (SCS). Understanding the variation in the picophytoplankton community structure will provide important information about primary production and the biogeochemical cycling of carbon in the SCS. Based on a field dataset from the SCS, we developed empirical algorithms using the absorption coefficient of phytoplankton at 443 nm [aph(443)] as the input to estimate the cell abundances of picophytoplankton, including Prochlorococcus (Pro), Synechococcus (Syn), and autotrophic picoeukaryotes (PE), in the SCS. Evaluation of algorithm performances demonstrated good agreement with field measurements. The root mean square errors and the mean absolute errors (MAEs) between the algorithm derivations and measurements were 0.44, 0.35, and 0.29, and 2.67, 2.02, and 1.88 for the cell abundances of Pro, Syn, and PE, respectively. The match-up comparisons showed that the satellite-derived cell abundances of picophytoplankton (e.g., MAEs ranged from 1.73 to 2.76) also agreed with the field data. We also analyzed the influences of both temperature and nutrient concentration on algorithm performance. The influence of temperature on the algorithms was not significant because the data were mainly collected in the summer, and the analysis should be repeated in the future with data from other seasons. The algorithm for estimating cell abundance of Syn was sensitive to variations in nutrient levels in coastal waters where nano- or microphytoplankton dominated. The input of our algorithms, aph(443) was easily obtained from field measurements and remote sensing. These algorithms provide a relatively easy way to estimate the cell abundances of picophytoplankton and provide data for studying the picophytoplankton community structure in the SCS.

中文翻译：

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基于南海浮游植物吸收系数的微型浮游植物细胞丰度估算

摘要： 微型浮游植物是贫营养南海（SCS）浮游植物的重要组成部分。了解微型浮游植物群落结构的变化将提供有关南海初级生产和碳的生物地球化学循环的重要信息。基于来自 SCS 的现场数据集，我们开发了经验算法，使用 443 nm 处浮游植物的吸收系数 [aph(443)] 作为输入来估计微型浮游植物的细胞丰度，包括原绿球藻 (Pro)、聚球藻 (Syn)、和自养微核生物 (PE)，在 SCS。算法性能的评估表明与现场测量非常吻合。算法推导和测量之间的均方根误差和平均绝对误差 (MAE) 分别为 0.44、0.35 和 0.29，以及 2.67、2.02、Pro、Syn 和 PE 的细胞丰度分别为 1.88 和 1.88。匹配比较表明，卫星衍生的微型浮游植物细胞丰度（例如，MAEs 范围从 1.73 到 2.76）也与现场数据一致。我们还分析了温度和养分浓度对算法性能的影响。温度对算法的影响不显着，因为数据主要是在夏季收集的，未来应该用其他季节的数据重复分析。估计 Syn 细胞丰度的算法对纳米或微型浮游植物占主导地位的沿海水域营养水平的变化很敏感。我们算法的输入 aph(443) 很容易从现场测量和遥感中获得。