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首页> 外文期刊>Marine ecology progress series >Physical and optical properties of phytoplankton-rich layers in a coastal fjord: a step toward prediction and strategic sampling of plankton patchiness
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Physical and optical properties of phytoplankton-rich layers in a coastal fjord: a step toward prediction and strategic sampling of plankton patchiness

机译:沿海峡湾中富含浮游植物的层的物理和光学性质:迈向浮游生物斑块预测和战略采样的一步

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Dense aggregations of phytoplankton in layers or patches alter the optical and physical properties of the water column and result in significant heterogeneity in trophic and demographic rates of local plankton populations. Determining the factors driving patch formation, persistence, intensity, and dissipation is key to understanding the ramifications of plankton patchiness in marine systems. Regression and multi-parametric statistical analyses were used to identify the physical and optical properties associated with 71 phytoplankton-rich layers (PRLs) identified from 158 CTD profiles collected between 2008 and 2010 in East Sound, Washington, USA. Generalized additive models (GAMs) were used to explore water column properties associated with and characterizing PRLs. Patch presence was associated with increasing water column stability represented by the Brunt-Vaisala frequency (N-2), Thorpe scale (L-t), and turbulent energy dissipation rate (epsilon). A predictive regression identified patch presence with 100% accuracy when log(10)(N-2) = -1 and 70% of the cases when log(10)(epsilon) = -3. A GAM of passively measured variables, which did not include fluorescence, was able to model patch intensity with considerable agreement (R-2 = 0.58), and the fit was improved by including fluorescence (R-2 = 0.69). Fluorescence alone was an insufficient predictor of PRLs, due in part to the influence of non-photochemical quenching (NPQ) in surface waters and the wide range of fluorescence intensities observed. The results show that a multi-parametric approach was necessary to characterize phytoplankton patches and that physical structure, resulting in steep gradients in bio-optical properties, hold greater predictive power than bio-optical properties alone. Integration of these analytical approaches will aid theoretical studies of phytoplankton patchiness but also improve sampling strategies in the field that utilize autonomous, in situ instrumentation.
机译:浮游植物在各层或各片中的密集聚集改变了水柱的光学和物理特性,并导致当地浮游生物种群的营养和人口统计学差异显着。确定驱动斑块形成,持续性,强度和散布的因素是理解海洋系统中浮游生物斑块后果的关键。回归分析和多参数统计分析被用于识别与71种富含浮游植物的层相关的物理和光学特性,这些层是从2008年至2010年在美国华盛顿州东桑德(East Sound)收集的158个CTD剖面中识别的。使用通用添加剂模型(GAM)来探索与PRL相关联并表征PRL的水柱特性。斑块的存在与增加的水柱稳定性有关,以布伦特-维萨拉频率(N-2),索普规模(L-t)和湍流能量耗散率(epsilon)表示。当log(10)(N-2)= -1时,预测回归可以以100%的准确性识别出斑块的存在,而log(10)(epsilon)= -3的情况中,有70%的情况可以识别出斑块的存在。被动测量变量的GAM(不包括荧光)能够以相当一致的方式对贴片强度进行建模(R-2 = 0.58),并且通过包含荧光(R-2 = 0.69)可以改善拟合度。单独的荧光不足以预测PRL,部分原因是地表水中非光化学猝灭(NPQ)的影响以及观察到的广泛的荧光强度。结果表明,采用多参数方法来表征浮游植物斑块是必要的,物理结构导致生物光学特性的陡峭梯度比单独的生物光学特性具有更大的预测能力。这些分析方法的集成将有助于浮游植物斑块的理论研究,但也将改善利用自主原位仪器的该领域的采样策略。

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