Hyperspectral optical discrimination of phytoplankton community structure in Funka Bay and its implications for ocean color remote sensing of diatoms
Hyperspectral optical discrimination of phytoplankton community structure in Funka Bay and its implications for ocean color remote sensing of diatoms
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DOI：
10.1016/j.rse.2014.12.006
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发表时间：
2015-03
影响因子：
13.5
通讯作者：
Tomonori Isada;T. Hirawake;Tsukuru Kobayashi;Yuichi Nosaka;Masafumi Natsuike;I. Imai;Koji Suzuki;S. Saitoh
中科院分区：
文献类型：
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作者：
Tomonori Isada;T. Hirawake;Tsukuru Kobayashi;Yuichi Nosaka;Masafumi Natsuike;I. Imai;Koji Suzuki;S. Saitoh
浮游植物功能群的识别是理解海洋生态地球化学循环的关键。为了更准确地了解浮游植物群落结构及其在海洋水色遥感应用中的意义，我们利用高效液相色谱（HPLC）、碎屑高光谱吸收系数（ad（λ））、浮游植物高光谱吸收系数（aph（λ））和有色溶解有机物（aCDOM（λ））研究了浮游植物色素的季节变化，2010 - 2012年丰卡湾沿海沃茨遥感反射率（aph_Rrs-derived（λ））的高光谱（λ）。通过HPLC测得的叶绿素浓度范围为0.29至8.6 mg m− 3。浮游植物群落组成，估计化学分类分析（CHEMTAX）的基础上HPLC浮游植物色素，硅藻，含叶绿素的浮游植物（绿藻和prasinophytes），蓝藻的季节性演替。此外，为了用CHEMTAX分析的替代技术识别浮游植物的优势类型，我们采用了导数光谱/相似性指数（SI）方法作为区分不同类型浮游植物的光学检测技术。特别是对于以硅藻为主的站位，从我们研究区域分离的硅藻培养物的相对于aph（λ）二阶导数光谱的SI值显著高于以含叶绿素的浮游植物和蓝藻为主的站位。此外，我们发现从二阶导数光谱计算的SI值和由CHEMTAX估计的硅藻组成之间有很强的关系。这些结果表明，这两种不同的方法验证了对方的性能和精度估计相对丰度硅藻从散装样品，它是可能的光学判别硅藻的优势使用导数光谱的aph（λ）。我们使用400-546 nm范围内的准解析算法将这种组合方法扩展到高光谱aph_Rrs-导出的（λ）。我们发现aph_Rrs-衍生（λ）/aph_Rrs-衍生（443）的二阶导数光谱的SI值与CHEMTAX衍生的硅藻组成有显著的相关性，但没有滤纸分析的aph（λ）高。这些结果表明，利用高光谱光学数据的aph（λ）和Rrs（λ）与导数光谱是一个潜在的有前途的方法来确定的季节变化的硅藻组成在沿海沃茨。此外，高光谱的方法结合CHEMTAX分析作为浮游植物群落结构的参考已被证明是有用的，在提高我们的理解浮游植物群落结构在沿海沃茨的丰卡湾。
Identification of phytoplankton functional groups is key to understanding marine biogeochemical cycles. For more accurate understanding of phytoplankton community structure and its implications for ocean color remote sensing applications, we investigated seasonal changes in phytoplankton pigments with high-performance liquid chromatography (HPLC), hyperspectral absorption coefficients of detritus (ad(λ)), phytoplankton (aph(λ)), and colored dissolved organic matter (aCDOM(λ)), and hyperspectralaph(λ) derived from remote sensing reflectance (aph_Rrs-derived(λ)) in the coastal waters of Funka Bay from 2010 to 2012. Chlorophylla(Chla) concentrations measured by HPLC ranged from 0.29 to 8.6 mg m− 3. Phytoplankton community compositions, as estimated by chemotaxonomic analysis (CHEMTAX) based on HPLC phytoplankton pigments, showed a seasonal succession of diatoms, chlorophyllb-containing phytoplankton (chlorophytes and prasinophytes), and cyanobacteria. Additionally, to identify the dominant type of phytoplankton with an alternative technique to CHEMTAX analysis, we employed a derivative spectroscopy/similarity index (SI) approach foraph(λ) as an optical detection technique for discriminating between different types of phytoplankton. In particular for diatom-dominated stations, SI values relative to the second derivative spectra ofaph(λ) of diatom cultures, isolated from our study region, were significantly higher than those for chlorophyllb-containing phytoplankton- and cyanobacteria-dominated stations. Furthermore, we found a strong relationship between the SI values calculated from the second derivative spectra and the composition of diatoms as estimated by CHEMTAX. These results suggest that the two different methods validated each other's performance and precision in estimating relative diatom abundance from bulk samples and that it is possible to optically discriminate the dominance of diatoms using derivative spectra ofaph(λ). We extended this combination approach to hyperspectralaph_Rrs-derived(λ), using a quasi-analytical algorithm within 400–546 nm range. We found a significant correlation between SI values obtained from the second derivative spectra ofaph_Rrs-derived(λ)/aph_Rrs-derived(443) and the composition of diatoms derived by CHEMTAX, but it was not as high as foraph(λ) measured by filter-pad analysis. These results indicate that using hyperspectral optical data ofaph(λ) andRrs(λ) with derivative spectroscopy is potentially a promising approach to identify seasonal variability in the composition of diatoms in coastal waters. Furthermore, a hyperspectral approach in combination with CHEMTAX analysis as a reference for phytoplankton community structure has proven useful in improving our understanding of phytoplankton community structure in the coastal waters of Funka Bay.