生物发光
盐度
浮游生物
光强度
海洋学
生物
海水
环境科学
温盐度图
赤潮
生态学
物理
地质学
光学
作者
Shuguo Chen,Gan Shen,Lianbo Hu,Rong Bi,Yue Gao
出处
期刊:Optics Express
[Optica Publishing Group]
日期:2023-03-27
卷期号:31 (8): 12114-12114
摘要
Red Noctiluca scintillans (RNS) is one of the major red tide species and dominant bioluminescent plankton in the global offshore. Bioluminescence offers a number of applications for ocean environment assessments such as interval waves study, fish stocks evaluation and underwater target detection making it of significant interest in forecasting bioluminescence occurrence and intensity. RNS is susceptible to changes in marine environmental factors. However, the effects of marine environmental factors on the bioluminescent intensity (BLI, photon s −1 ) of individual RNS cells (IRNSC) is poorly known. In this study, the effects of temperature, salinity and nutrients on the BLI were studied by field and laboratory culture experiments. In the field experiments, bulk BLI was measured by an underwater bioluminescence assessment tool at various temperature, salinity and nutrient concentrations. To exclude the contribution by other bioluminescent planktons, an identification method of IRNSC was first developed using the features of the bioluminescence flash kinetics (BFK) curve of RNS to identify and extract BLI emitted by an individual RNS cell. To decouple the effects of each environmental factor, laboratory culture experiments were conducted to examine the effects of a single factor on the BLI of IRNSC. The field experiments showed that BLI of IRNSC negatively correlated with temperature (3-27°C) and salinity (30-35‰). The logarithmic BLI can be well fitted using a linear equation with temperature or salinity with Pearson correlation coefficients of -0.95 and -0.80, respectively. The fitting function with salinity was verified by the laboratory culture experiment. On the other hand, no significant correlation was observed between BLI of IRNSC and nutrients. These relationships could be used in the RNS bioluminescence prediction model to improve the prediction accuracy of bioluminescent intensity and spatial distribution.
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