Ling Zunbin, Sun Deyong, Wang Shengqiang, Qiu Zhongfeng, Huan Yu, Mao Zhihua, He Yijun
Opt Express. 2018 Nov 12;26(23):30556-30575. doi: 10.1364/OE.26.030556.
Phytoplankton community is an important organism indicator of monitoring water quality, and accurately estimating its composition and biomass is crucial for understanding marine ecosystems and biogeochemical processes. Identifying phytoplankton species remains a challenging task in the field of oceanography. Phytoplankton fluorescence is an important biological property of phytoplankton, whose fluorescence emissions are closely related to its community. However, the existing estimation approaches for phytoplankton communities by fluorescence are inaccurate and complex. In the present study, a new, simple method was developed for determining the Chlorophytes, Chrysophytes, Cryptophytes, Diatoms, Dinoflagellates, and Prymnesiophytes based on the fluorescence emission spectra measured from the HOBI Labs Hydroscat-6P (HS-6P) in the Bohai Sea, Yellow Sea, and East China Sea. This study used single bands, band ratios, and band combinations of the fluorescence signals to test their correlations with the six dominant algal species. The optimal band forms were confirmed, i.e., X1 (i.e., fl(700), which means the fluorescence emission signal at 700 nm band) for Chlorophytes, Cryptophytes, Dinoflagellates, and Prymnesiophytes (R = 0.947, 0.862, 0.911, and 0.918, respectively) and X7 (i.e., [fl(700) + fl(550)]/[fl(550)/fl(700)], where fl(550) denotes the fluorescence emission signal at 550 nm band) for Chrysophytes and Diatoms (R = 0.893 and 0.963, respectively). These established models here show good performances, yielding low estimation errors (i.e., root mean square errors of 0.16, 0.02, 0.06, 0.36, 0.18, and 0.03 for Chlorophytes, Chrysophytes, Cryptophytes, Diatoms, Dinoflagellates, and Prymnesiophytes, respectively) between in situ and modeled phytoplankton communities. Meanwhile, the spatial distributions of phytoplankton communities observed from both in situ and fluorescence-derived results agreed well. These excellent outputs indicate that the proposed method is to a large extent feasible and robust for estimating those dominant algal species in marine waters. In addition, we have applied this method to three vertical sections, and the retrieved vertical spatial distributions by this method can fill the gap of the common optical remote sensing approach, which usually only detects the sea surface information. Overall, our findings indicate that the proposed method by the fluorescence emission spectra is a potentially promising way to estimate phytoplankton communities, in particular enlarging the profiling information.
浮游植物群落是监测水质的重要生物指标,准确估算其组成和生物量对于理解海洋生态系统和生物地球化学过程至关重要。在海洋学领域,识别浮游植物物种仍然是一项具有挑战性的任务。浮游植物荧光是浮游植物的一项重要生物学特性,其荧光发射与群落密切相关。然而,现有的基于荧光估算浮游植物群落的方法不准确且复杂。在本研究中,基于在渤海、黄海和东海使用HOBI Labs Hydroscat-6P(HS-6P)测量的荧光发射光谱,开发了一种新的、简单的方法来测定绿藻、金藻、隐藻、硅藻、甲藻和颗石藻。本研究使用荧光信号的单波段、波段比值和波段组合来测试它们与六种优势藻类物种的相关性。确定了最佳波段形式,即绿藻、隐藻、甲藻和颗石藻的X1(即fl(700),表示700nm波段的荧光发射信号)(相关系数分别为0.947、0.862、0.911和0.918)以及金藻和硅藻的X7(即[fl(700)+fl(550)]/[fl(550)/fl(