收稿日期: 2009-05-06
修回日期: 2009-01-28
网络出版日期: 2010-03-23
基金资助
中国科学院知识创新工程重要方向项目(KZCX2-YW-215); 国家自然科学基金青年项目(40906021, 4090622, U0933005);
中科院南海海洋研究所青年人才领域前沿项目(SQ200812)
Retrieval of phytoplankton size structure based on the spectral slope of phytoplankton absorption in the northern South China Sea
Received date: 2009-05-06
Revised date: 2009-01-28
Online published: 2010-03-23
浮游植物的粒级结构是一个重要的生物参数。基于南海北部海区不同水体环境下测量的生物光学数据, 作者深入研究了粒级结构对浮游植物吸收光谱的影响。结果表明, 选择443和510nm波段计算得到的浮游植物光谱斜率S对粒级结构的变化具有较高的敏感性, 其随着小型浮游植物比例的增大呈不断增加的趋势。S与水体叶绿素a浓度、浮游植物吸收系数(aph(443))之间表现出明显的正相关特征。以40%为界对不同粒级浮游植物的优势进行定义, 发现在S与叶绿素a浓度、aph(443)的关系分布中小型(Micro)和微微型(Pico)浮游植物占据优势的水体表现出较为明显的分界, 叶绿素a浓度和aph(443)分别在0.70mg•m-3和0.05m-1附近, 相应的S在0.0004(m•nm)-1左右。基于实测数据建立的遥感反射率蓝绿波段比值与S之间的统计关系, 决定系数高达0.91, 为从水色遥感数据反演浮游植物粒级结构提供了重要手段。
王桂芬,曹文熙,周雯,梁少君,杨跃忠,赵俊, . 基于南海北部海区浮游植物吸收光谱斜率变化的粒级结构反演[J]. 热带海洋学报, 2010 , 29(2) : 25 -32 . DOI: 10.11978/j.issn.1009-5470.2010.02.025
Phytoplankton size structure is an important biological parameter that governs functioning of pelagic food-webs and consequently affects the rate of carbon cycle. Relationships between spectral phytoplankton absorption (aph(λ)) and phyto-plankton size structure were investigated based on in situ data collected in the northern South China Sea. The spectral slope of phytoplankton absorption in the range of 443 and 510 nm was used as an index (S) for describing phytoplankton size classes, which tended to increase with increasing dominant roles of large-sized phytoplankton. There existed positive correlations be-tween S and phytoplankton absorption coefficient and chlorophyll a concentration, which were then discussed by considering size-fractioned chlorophyll a contribution. Taking 40% as the cutoff, relatively clear division between pico- and mi-cro-phytoplankton dominated waters was found, with chlorophyll a concentration of ~0.70 mg•m-3 and aph(443) of ~0.05 m-1, and accordingly the value of S being around 0.0004 (m•nm)-1. A bio-optical model was developed between S and blue-to-green band ratio of remote sensing reflectance (Rrs(443)/Rrs(555 )), which showed good correlations with R2 being about 0.91. This model pro-vided much insight into the retrieval of phytoplankton size structure from ocean color remote sensing.
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