Temporal and spatial dynamics of phytoplankton diversity in the East China Sea near Jeju Island (Korea): A pyrosequencing-based study

Boopathi, Thangavelu; Lee, Joon-Baek; Youn, Seok Hyun; Ki, Jang‐Seu

doi:10.1016/j.bse.2015.10.002

Cited by 9 publications

(7 citation statements)

References 35 publications

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“…Our study shows the order of brassicasterol > dinosterol > C 37 alkenones (concentrations; both maximum and mean values) and B/∑PB (45%–96%) > D/∑PB (4.3%–50%) > A/∑PB (0–20.77%) in the NEECS‐WTS in summer and autumn. The relatively high values of B/∑PB suggest the dominance of diatoms, consistent with the results in the NEECS‐WTS and adjacent areas in previous studies using small subunit ribosomal RNA pyrosequencing (Boopathi et al, ) and microscopic counting (Guo et al, ; Jang et al, ). For example, Guo et al () studied phytoplankton assemblages in the PN section of the ECS in summer by the Utermöhl method, showing that Bacteriastrum comosum and Chaetoceros decipiens were the dominant diatom species in offshore areas influenced by the Kuroshio intrusion.…”

Section: Discussionsupporting

confidence: 89%

Water Mass Control on Phytoplankton Spatiotemporal Variations in the Northeastern East China Sea and the Western Tsushima Strait Revealed by Lipid Biomarkers

Chen

Zhang

et al. 2018

JGR Biogeosciences

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Continental margin ecosystems in the western North Pacific Ocean are subject to strong climate forcing and anthropogenic impacts. To evaluate mechanisms controlling phytoplankton biomass and community structure variations in marginal sea‐open ocean boundary regions, brassicasterol, dinosterol, and C37 alkenones were measured in suspended particles in summer and autumn from 2012 to 2013 in the northeastern East China Sea and the western Tsushima Strait. In summer, the concentrations of brassicasterol (40–1535 ng/L) and dinosterol (4.2–94 ng/L) were higher in the southwest of Cheju Island, while C37 alkenones (0–30 ng/L) were higher in the south of Cheju Island. In autumn, brassicasterol (12–106 ng/L), dinosterol (2.4–21 ng/L), and C37 alkenones (0.7–7.0 ng/L) were higher in the southwest of Cheju Island and the western Tsushima Strait, and higher C37 alkenones also occurred in the Okinawa Trough. Correlation analysis of biomarkers and environmental conditions (temperature, salinity, and inorganic nutrient concentrations) clearly demonstrated that phytoplankton biomass and community structure variations can be well elucidated by water masses as indexed by temperature and salinity. High nutrients from the Changjiang River were the main cause of high biomass in summer, while nutrients from subsurface water were likely the key factor regulating phytoplankton biomass in open ocean water stations in autumn. This study indicates that mechanisms controlling phytoplankton biomass in marginal sea‐open ocean boundary regions should be classified by various water masses with different nutrient concentrations, instead of by geography.

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Section: Discussionsupporting

confidence: 89%

Water Mass Control on Phytoplankton Spatiotemporal Variations in the Northeastern East China Sea and the Western Tsushima Strait Revealed by Lipid Biomarkers

Chen

Zhang

et al. 2018

JGR Biogeosciences

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“…This phenomenon may be caused by their similar sources and cellular functions in algae (Stefels ). Among phytoplankton, diatoms and dinoflagellates constituted a major portion of all stations (60–90%) in ECS (Boopathi et al ). Diatoms and dinoflagellates are primary producers of DMSP and DMSO, exhibiting similar production capacity of DMSOp and DMSPp.…”

Section: Resultsmentioning

confidence: 99%

Spatiotemporal distribution characteristics and environmental control factors of biogenic dimethylated sulfur compounds in the East China Sea during spring and autumn

Jian

Zhang

et al. 2017

Limnology & Oceanography

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Biogenic dimethylated sulfur compounds could take part in the metabolic process of algal cells and are the key compounds in the biological cycle of sulfur in the marine system. In this study, seasonal and spatial variations of biogenic dimethylated sulfur compounds, including dimethylsulfide (DMS), dimethylsulfoniopropionate (DMSP), and dimethylsulfoxide (DMSO), and oceanographic parameters influencing their concentrations were measured in the East China Sea (ECS) during two cruises from 22 October 2015 to 13 November 2015 and from 31 May 2016 to 14 June 2016. Significant spatial variability was observed in seawater dimethylated sulfur compound concentrations with higher concentration in spring. In most cases, concentrations of DMS, particulate DMSP, and particulate DMSO showed significant relationships with the concentration of chlorophyll a under highly variable hydrographic conditions. In spring, bacterial abundance also significantly influenced DMS distribution. Photodegradation experiments showed that enhanced UV radiation could increase DMS photodegradation rate, and low seawater pH could facilitate DMS degradation rate under UVB radiation while it was decreased under UVA radiation. Preliminary estimates for the sea‐to‐air fluxes of DMS in spring showed a 2.3 μmol m−2 d−1 increase over autumn flux. Compared with total DMS emission of the global ocean to atmosphere, the contribution of the ECS to global DMS emissions was not negligible. At Sta. DH6‐1, the contribution of biological consumption to DMS removal (85%) was higher than those of photolysis (10%) and sea‐to‐air exchanges (4%). These findings reveal that biological consumption probably dominates removal of DMS at this station.

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“…Eleven phytoplankton species, namely, three dinoflagellates (Prorocentrum dentatum, zooxanthella, and Karenia mikimotoi), six diatoms (Skeletonema costatum, Thalassiosira weissflogii, Chaetoceros debilis Cleve, Phaeodactylum tricornutum, Chaetoceros curvisetus, and Cyclotella cryptica), one cryptophyta (Heterosigma akashiwo), and one chlorophyte (Nannochloris sp. ), which were frequently observed in Chinese ocean regions [7,8,15], were cultured in a laboratory incubator. The temperature was set at 18-20 • C, light intensity was 2500 lx, 12 h light and 12 h dark.…”

Section: Validation Datasetmentioning

confidence: 99%

“…Because the physiological processes of different phytoplankton species and associated compositions are distinct from each other, each individual phytoplankton species and its associated composition information are fundamental to its functional type [7]. In addition, they are also indicative of variability in phytoplankton species diversity in the ocean [8]. With the development of satellite-based ocean color remote sensing, which provides the advantages of wide-range, long-term coverage, high efficiency, and low cost [9], phytoplankton species, composition, and related research from space have been carried out [10,11].…”

Section: Introductionmentioning

confidence: 99%

Hyperspectral Remote Sensing of Phytoplankton Species Composition Based on Transfer Learning

et al. 2019

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Phytoplankton species composition research is key to understanding phytoplankton ecological and biogeochemical functions. Hyperspectral optical sensor technology allows us to obtain detailed information about phytoplankton species composition. In the present study, a transfer learning method to inverse phytoplankton species composition using in situ hyperspectral remote sensing reflectance and hyperspectral satellite imagery was presented. By transferring the general knowledge learned from the first few layers of a deep neural network (DNN) trained by a general simulation dataset, and updating the last few layers with an in situ dataset, the requirement for large numbers of in situ samples for training the DNN to predict phytoplankton species composition in natural waters was lowered. This method was established from in situ datasets and validated with datasets collected in different ocean regions in China with considerable accuracy (R 2 = 0.88, mean absolute percentage error (MAPE) = 26.08%). Application of the method to Hyperspectral Imager for the Coastal Ocean (HICO) imagery showed that spatial distributions of dominant phytoplankton species and associated compositions could be derived. These results indicated the feasibility of species composition inversion from hyperspectral remote sensing, highlighting the advantages of transfer learning algorithms, which can bring broader application prospects for phytoplankton species composition and phytoplankton functional type research.focused on the identification of specific phytoplankton species or groups under blooming conditions using ocean color satellites with a moderate spectral resolution [14][15][16]. Furthermore, discrimination of phytoplankton phyla in blooming conditions has been achieved based on differences in optical signals among different phytoplankton populations [17]. However, these endeavors are constrained to a limited type of phytoplankton species or groups because of the limitations in band settings for multi-spectral remote sensing. Moreover, some studies have been focused on Case 1 water with relatively simple optical properties where optically active constituents co-vary with chlorophyll concentration [18,19]; however, it is more challenging to invert phytoplankton species composition from current ocean color remote sensing data with moderate spectral resolution in optically complex waters. Comparatively, hyperspectral remote sensing presents a promising tool to resolve the spectral variability of phytoplankton species [20].Several ocean color algorithms have also been proposed for phytoplankton information inversion in natural waters [21][22][23][24]. Among these efforts, a derivative spectroscopy/similarity index (SI) approach is the most common method for identifying dominant phytoplankton species or groups [25][26][27]. However, because SI-based approaches assign unknown spectra to the reference spectra that have the largest SI, only dominant species or groups can be identified, so it is difficult to determine phytoplankton species compo...

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Temporal and spatial dynamics of phytoplankton diversity in the East China Sea near Jeju Island (Korea): A pyrosequencing-based study

Cited by 9 publications

References 35 publications

Water Mass Control on Phytoplankton Spatiotemporal Variations in the Northeastern East China Sea and the Western Tsushima Strait Revealed by Lipid Biomarkers

Water Mass Control on Phytoplankton Spatiotemporal Variations in the Northeastern East China Sea and the Western Tsushima Strait Revealed by Lipid Biomarkers

Spatiotemporal distribution characteristics and environmental control factors of biogenic dimethylated sulfur compounds in the East China Sea during spring and autumn

Hyperspectral Remote Sensing of Phytoplankton Species Composition Based on Transfer Learning

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