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浮游植物色素如何才能最有效地用于为海洋颜色遥感算法表征海洋表层浮游植物群落?

How Can Phytoplankton Pigments Be Best Used to Characterize Surface Ocean Phytoplankton Groups for Ocean Color Remote Sensing Algorithms?

作者信息

Kramer Sasha J, Siegel David A

机构信息

Interdepartmental Graduate Program in Marine Science University of California Santa Barbara CA USA.

Earth Research Institute University of California Santa Barbara CA USA.

出版信息

J Geophys Res Oceans. 2019 Nov;124(11):7557-7574. doi: 10.1029/2019JC015604. Epub 2019 Nov 11.

Abstract

High-performance liquid chromatography (HPLC) remains one of the most widely applied methods for estimation of phytoplankton community structure from ocean samples, which are used to create and validate satellite retrievals of phytoplankton community structure. HPLC measures the concentrations of phytoplankton pigments, some of which are useful chemotaxonomic markers for phytoplankton groups. Here, consistent suites of HPLC phytoplankton pigments measured on global surface water samples are compiled across spatial scales. The global dataset includes >4,000 samples from every major ocean basin and representing a wide range of ecological regimes. The local dataset is composed of six time series from long-term observatory sites. These samples are used to quantify the potential and limitations of HPLC for understanding surface ocean phytoplankton groups. Hierarchical cluster and empirical orthogonal function analyses are used to examine the associations between and among groups of phytoplankton pigments and to diagnose the main controls on these associations. These methods identify four major groups of phytoplankton on global scales (cyanobacteria, diatoms/dinoflagellates, haptophytes, and green algae) that can be identified by diagnostic biomarker pigments. On local scales, the same methods identify more and different taxonomic groups of phytoplankton than are detectable in the global dataset. Notably, diatom and dinoflagellate pigments group together on global scales, but dinoflagellate marker pigments always separate from diatoms on local scales. Together, these results confirm that HPLC pigments can be used for satellite algorithm quantification of no more than four phytoplankton groups on global scales, but can provide higher resolution for local-scale algorithm development and validation.

摘要

高效液相色谱法(HPLC)仍然是从海洋样本中估算浮游植物群落结构应用最广泛的方法之一,这些样本用于创建和验证浮游植物群落结构的卫星反演数据。HPLC可测量浮游植物色素的浓度,其中一些色素是浮游植物类群有用的化学分类标记。在此,我们汇总了在全球地表水样本上测量的HPLC浮游植物色素的一致数据集,涵盖了不同的空间尺度。全球数据集包括来自每个主要海洋盆地的4000多个样本,代表了广泛的生态区域。本地数据集由来自长期观测站点的六个时间序列组成。这些样本用于量化HPLC在理解表层海洋浮游植物类群方面的潜力和局限性。层次聚类分析和经验正交函数分析用于检验浮游植物色素组之间的关联,并诊断这些关联的主要控制因素。这些方法在全球尺度上识别出四大类浮游植物(蓝细菌、硅藻/甲藻、定鞭藻和绿藻),它们可通过诊断性生物标志物色素来识别。在局部尺度上,相同的方法识别出的浮游植物分类群比全球数据集中可检测到的更多且不同。值得注意的是,硅藻和甲藻色素在全球尺度上归为一组,但甲藻标记色素在局部尺度上总是与硅藻分开。总之,这些结果证实,HPLC色素可用于在全球尺度上对不超过四类浮游植物进行卫星算法量化,但可为局部尺度的算法开发和验证提供更高分辨率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/efd9/7043335/2e8eaa57b94c/JGRC-124-7557-g001.jpg

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