Articles | Volume 15, issue 13
https://doi.org/10.5194/bg-15-4271-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-15-4271-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Jul 2018
Research article |
| 13 Jul 2018
| 13 Jul 2018
Phytoplankton size class in the East China Sea derived from MODIS satellite data
Hailong Zhang
School of Marine Sciences, Nanjing University of Information Science
& Technology, Nanjing, Jiangsu, China
Jiangsu Research Centre for Ocean Survey Technology, NUIST,
Nanjing, Jiangsu, China
Shengqiang Wang
School of Marine Sciences, Nanjing University of Information Science
& Technology, Nanjing, Jiangsu, China
Jiangsu Research Centre for Ocean Survey Technology, NUIST,
Nanjing, Jiangsu, China
Zhongfeng Qiu
CORRESPONDING AUTHOR
School of Marine Sciences, Nanjing University of Information Science
& Technology, Nanjing, Jiangsu, China
Jiangsu Research Centre for Ocean Survey Technology, NUIST,
Nanjing, Jiangsu, China
Deyong Sun
School of Marine Sciences, Nanjing University of Information Science
& Technology, Nanjing, Jiangsu, China
Jiangsu Research Centre for Ocean Survey Technology, NUIST,
Nanjing, Jiangsu, China
Joji Ishizaka
Institute for Space-Earth Environmental Research, Nagoya
University, Nagoya, Japan
Shaojie Sun
College of Marine Science, University of South Florida, St.
Petersburg, Florida, USA
Yijun He
School of Marine Sciences, Nanjing University of Information Science
& Technology, Nanjing, Jiangsu, China
Jiangsu Research Centre for Ocean Survey Technology, NUIST,
Nanjing, Jiangsu, China
Related authors
No articles found.
Shun Ohishi, Tsutomu Hihara, Hidenori Aiki, Joji Ishizaka, Yasumasa Miyazawa, Misako Kachi, and Takemasa Miyoshi
Geosci. Model Dev., 15, 8395–8410, https://doi.org/10.5194/gmd-15-8395-2022, https://doi.org/10.5194/gmd-15-8395-2022, 2022
Short summary
Short summary
We develop an ensemble-Kalman-filter-based regional ocean data assimilation system in which satellite and in situ observations are assimilated at a daily frequency. We find the best setting for dynamical balance and accuracy based on sensitivity experiments focused on how to inflate the ensemble spread and how to apply the analysis update to the model evolution. This study has a broader impact on more general data assimilation systems in which the initial shocks are a significant issue.
S. Q. Wang, J. Ishizaka, H. Yamaguchi, S. C. Tripathy, M. Hayashi, Y. J. Xu, Y. Mino, T. Matsuno, Y. Watanabe, and S. J. Yoo
Biogeosciences, 11, 1759–1773, https://doi.org/10.5194/bg-11-1759-2014, https://doi.org/10.5194/bg-11-1759-2014, 2014
Y. Umezawa, A. Yamaguchi, J. Ishizaka, T. Hasegawa, C. Yoshimizu, I. Tayasu, H. Yoshimura, Y. Morii, T. Aoshima, and N. Yamawaki
Biogeosciences, 11, 1297–1317, https://doi.org/10.5194/bg-11-1297-2014, https://doi.org/10.5194/bg-11-1297-2014, 2014
Related subject area
Biogeochemistry: Bio-Optics
Spatial and temporal dynamics of suspended sediment concentrations in coastal waters of the South China Sea, off Sarawak, Borneo: ocean colour remote sensing observations and analysis
Comment on “Fundamental molecules of life are pigments which arose and co-evolved as a response to the thermodynamic imperative of dissipating the prevailing solar spectrum” by K. Michaelian and A. Simeonov (2015)
A limited effect of sub-tropical typhoons on phytoplankton dynamics
The suspended small-particle layer in the oxygen-poor Black Sea: a proxy for delineating the effective N2-yielding section
Diel quenching of Southern Ocean phytoplankton fluorescence is related to iron limitation
A global end-member approach to derive aCDOM(440) from near-surface optical measurements
Floodwater impact on Galveston Bay phytoplankton taxonomy, pigment composition and photo-physiological state following Hurricane Harvey from field and ocean color (Sentinel-3A OLCI) observations
Diurnal regulation of photosynthetic light absorption, electron transport and carbon fixation in two contrasting oceanic environments
Bio-optical characterization of subsurface chlorophyll maxima in the Mediterranean Sea from a Biogeochemical-Argo float database
Carbon Flux Explorer optical assessment of C, N and P fluxes
An estuarine-tuned quasi-analytical algorithm (QAA-V): assessment and application to satellite estimates of SPM in Galveston Bay following Hurricane Harvey
Remote sensing of canopy nitrogen at regional scale in Mediterranean forests using the spaceborne MERIS Terrestrial Chlorophyll Index
Modelling ocean-colour-derived chlorophyll a
Optical properties of size fractions of suspended particulate matter in littoral waters of Québec
Methods to retrieve the complex refractive index of aquatic suspended particles: going beyond simple shapes
Changes in optical characteristics of surface microlayers hint to photochemically and microbially mediated DOM turnover in the upwelling region off the coast of Peru
Quantifying the biological impact of surface ocean light attenuation by colored detrital matter in an ESM using a new optical parameterization
Monitoring seasonal and diurnal changes in photosynthetic pigments with automated PRI and NDVI sensors
Autonomous profiling float observations of the high-biomass plume downstream of the Kerguelen Plateau in the Southern Ocean
A simple optical index shows spatial and temporal heterogeneity in phytoplankton community composition during the 2008 North Atlantic Bloom Experiment
Ocean colour remote sensing in the southern Laptev Sea: evaluation and applications
Multidecadal time series of satellite-detected accumulations of cyanobacteria in the Baltic Sea
Absorption and fluorescence properties of chromophoric dissolved organic matter of the eastern Bering Sea in the summer with special reference to the influence of a cold pool
A synthesis of light absorption properties of the Arctic Ocean: application to semianalytical estimates of dissolved organic carbon concentrations from space
Influence of the Changjiang River on the light absorption properties of phytoplankton from the East China Sea
On the consistency of MODIS chlorophyll $a$ products in the northern South China Sea
Contribution to a bio-optical model for remote sensing of Lena River water
Light absorption and partitioning in Arctic Ocean surface waters: impact of multiyear ice melting
Biogeochemical origins of particles obtained from the inversion of the volume scattering function and spectral absorption in coastal waters
Apparent optical properties of the Canadian Beaufort Sea – Part 1: Observational overview and water column relationships
Apparent optical properties of the Canadian Beaufort Sea – Part 2: The 1% and 1 cm perspective in deriving and validating AOP data products
Increasing cloudiness in Arctic damps the increase in phytoplankton primary production due to sea ice receding
Estimating absorption coefficients of colored dissolved organic matter (CDOM) using a semi-analytical algorithm for southern Beaufort Sea waters: application to deriving concentrations of dissolved organic carbon from space
Variations of net primary productivity and phytoplankton community composition in the Indian sector of the Southern Ocean as estimated from ocean color remote sensing data
Spectroscopic detection of a ubiquitous dissolved pigment degradation product in subsurface waters of the global ocean
Remote sensing of coccolithophore blooms in selected oceanic regions using the PhytoDOAS method applied to hyper-spectral satellite data
Tracing the transport of colored dissolved organic matter in water masses of the Southern Beaufort Sea: relationship with hydrographic characteristics
Bio-optical provinces in the eastern Atlantic Ocean and their biogeographical relevance
Inferring phytoplankton carbon and eco-physiological rates from diel cycles of spectral particulate beam-attenuation coefficient
Characterization of the bio-optical anomaly and diurnal variability of particulate matter, as seen from scattering and backscattering coefficients, in ultra-oligotrophic eddies of the Mediterranean Sea
MODIS observed phytoplankton dynamics in the Taiwan Strait: an absorption-based analysis
Global variability of phytoplankton functional types from space: assessment via the particle size distribution
Optical Characterization of an Eddy-induced Diatom Bloom West of the Island of Hawaii
The dissolved yellow substance and the shades of blue in the Mediterranean Sea
Jenny Choo, Nagur Cherukuru, Eric Lehmann, Matt Paget, Aazani Mujahid, Patrick Martin, and Moritz Müller
Biogeosciences, 19, 5837–5857, https://doi.org/10.5194/bg-19-5837-2022, https://doi.org/10.5194/bg-19-5837-2022, 2022
Short summary
Short summary
This study presents the first observation of water quality changes over space and time in the coastal systems of Sarawak, Malaysian Borneo, using remote sensing technologies. While our findings demonstrate that the southwestern coast of Sarawak is within local water quality standards, historical patterns of water quality degradation that were detected can help to alert local authorities and enhance management and monitoring strategies of coastal waters in this region.
Lars Olof Björn
Biogeosciences, 19, 1013–1019, https://doi.org/10.5194/bg-19-1013-2022, https://doi.org/10.5194/bg-19-1013-2022, 2022
Short summary
Short summary
The origin and evolution of life do not contradict the laws of thermodynamics, but we have no proof that it is an inevitable consequence of these laws. We do not know if the first life arose under illumination or in darkness in the deep ocean or in the Earth's crust. We have no proof that it arose due to a
thermodynamic imperative of dissipating the prevailing solar spectrum, as there are other ways for entropy increase in solar radiation. The biosphere may instead delay entropy production.
Fei Chai, Yuntao Wang, Xiaogang Xing, Yunwei Yan, Huijie Xue, Mark Wells, and Emmanuel Boss
Biogeosciences, 18, 849–859, https://doi.org/10.5194/bg-18-849-2021, https://doi.org/10.5194/bg-18-849-2021, 2021
Short summary
Short summary
The unique observations by a Biogeochemical Argo float in the NW Pacific Ocean captured the impact of a super typhoon on upper-ocean physical and biological processes. Our result reveals typhoons can increase the surface chlorophyll through strong vertical mixing without bringing nutrients upward from the depth. The vertical redistribution of chlorophyll contributes little to enhance the primary production, which is contradictory to many former satellite-based studies related to this topic.
Rafael Rasse, Hervé Claustre, and Antoine Poteau
Biogeosciences, 17, 6491–6505, https://doi.org/10.5194/bg-17-6491-2020, https://doi.org/10.5194/bg-17-6491-2020, 2020
Short summary
Short summary
Here, data collected by BGC-Argo floats are used to investigate the origin of the suspended small-particle layer inferred from optical sensors in the oxygen-poor Black Sea. Our results suggest that this layer is at least partially composed of the microbial communities that produce dinitrogen. We propose that oxygen and the optically derived small-particle layer can be used in combination to refine delineation of the effective N2-yielding section of the Black Sea and oxygen-deficient zones.
Christina Schallenberg, Robert F. Strzepek, Nina Schuback, Lesley A. Clementson, Philip W. Boyd, and Thomas W. Trull
Biogeosciences, 17, 793–812, https://doi.org/10.5194/bg-17-793-2020, https://doi.org/10.5194/bg-17-793-2020, 2020
Short summary
Short summary
Measurements of phytoplankton health still require the use of research vessels and are thus costly and sparse. In this paper we propose a new way to assess the health of phytoplankton using simple fluorescence measurements, which can be made autonomously. In the Southern Ocean, where the most limiting nutrient for phytoplankton is iron, we found a relationship between iron limitation and the depression of fluorescence under high light, the so-called non-photochemical quenching of fluorescence.
Stanford B. Hooker, Atsushi Matsuoka, Raphael M. Kudela, Youhei Yamashita, Koji Suzuki, and Henry F. Houskeeper
Biogeosciences, 17, 475–497, https://doi.org/10.5194/bg-17-475-2020, https://doi.org/10.5194/bg-17-475-2020, 2020
Short summary
Short summary
A Kd(λ) and aCDOM(440) data set spanned oceanic, coastal, and inland waters. The algorithmic approach, based on Kd end-member pairs, can be used globally. End-members with the largest spectral span had an accuracy of 1.2–2.4 % (RMSE). Validation was influenced by subjective
nonconservativewater masses. The influence of subcategories was confirmed with an objective cluster analysis.
Bingqing Liu, Eurico J. D'Sa, and Ishan D. Joshi
Biogeosciences, 16, 1975–2001, https://doi.org/10.5194/bg-16-1975-2019, https://doi.org/10.5194/bg-16-1975-2019, 2019
Short summary
Short summary
An approach using bio-optical field and ocean color (Sentinel-3A OLCI) data combined with inversion models allowed for the first time an assessment of phytoplankton response (changes in taxonomy, pigment composition and physiological state) to a large hurricane-related floodwater perturbation in a turbid estuary. The study revealed the transition in phytoplankton community species as well as the spatiotemporal distributions of phytoplankton diagnostic pigments in the floodwater-impacted bay.
Nina Schuback and Philippe D. Tortell
Biogeosciences, 16, 1381–1399, https://doi.org/10.5194/bg-16-1381-2019, https://doi.org/10.5194/bg-16-1381-2019, 2019
Short summary
Short summary
Understanding the dynamics of primary productivity requires mechanistic insight into the coupling of light absorption, electron transport and carbon fixation in response to environmental variability. Measuring such rates over diurnal timescales in contrasting regions allowed us to gain information on the regulation of photosynthetic efficiencies, with implications for the interpretation of bio-optical data, and the parameterization of models needed to monitor productivity over large scales.
Marie Barbieux, Julia Uitz, Bernard Gentili, Orens Pasqueron de Fommervault, Alexandre Mignot, Antoine Poteau, Catherine Schmechtig, Vincent Taillandier, Edouard Leymarie, Christophe Penkerc'h, Fabrizio D'Ortenzio, Hervé Claustre, and Annick Bricaud
Biogeosciences, 16, 1321–1342, https://doi.org/10.5194/bg-16-1321-2019, https://doi.org/10.5194/bg-16-1321-2019, 2019
Short summary
Short summary
As commonly observed in oligotrophic stratified waters, a subsurface (or deep) chlorophyll maximum (SCM) frequently characterizes the vertical distribution of phytoplankton chlorophyll in the Mediterranean Sea. SCMs often result from photoacclimation of the phytoplankton organisms. However they can also result from an actual increase in phytoplankton carbon biomass. Our results also suggest that a variety of intermediate types of SCMs are encountered between these two endmember situations.
Hannah L. Bourne, James K. B. Bishop, Todd J. Wood, Timothy J. Loew, and Yizhuang Liu
Biogeosciences, 16, 1249–1264, https://doi.org/10.5194/bg-16-1249-2019, https://doi.org/10.5194/bg-16-1249-2019, 2019
Short summary
Short summary
The biological carbon pump, the process by which carbon-laden particles sink out of the surface ocean, is dynamic and fast. The use of autonomous observations will better inform carbon export simulations. The Carbon Flux Explorer (CFE) was developed to optically measure hourly variations of particle flux. We calibrate the optical measurements of the CFE against C and N flux using samples collected during a coastal California cruise in June 2017. Our results yield well-correlated calibrations.
Ishan D. Joshi and Eurico J. D'Sa
Biogeosciences, 15, 4065–4086, https://doi.org/10.5194/bg-15-4065-2018, https://doi.org/10.5194/bg-15-4065-2018, 2018
Short summary
Short summary
The standard quasi-analytical algorithm (QAA) was tuned for various ocean color sensors as QAA-V and optimized for and evaluated in a variety of waters from highly absorbing and turbid to relatively clear shelf waters. The QAA-V-derived optical properties of total absorption and backscattering coefficients showed an obvious improvement when compared to the standard QAA and were used to examine suspended particulate matter dynamics in Galveston Bay following flooding due to Hurricane Harvey.
Yasmina Loozen, Karin T. Rebel, Derek Karssenberg, Martin J. Wassen, Jordi Sardans, Josep Peñuelas, and Steven M. De Jong
Biogeosciences, 15, 2723–2742, https://doi.org/10.5194/bg-15-2723-2018, https://doi.org/10.5194/bg-15-2723-2018, 2018
Short summary
Short summary
Nitrogen (N) is an essential nutrient for plant growth. It would be interesting to detect it using satellite data. The goal was to investigate if it is possible to remotely sense the canopy nitrogen concentration and content of Mediterranean trees using a product calculated from satellite reflectance data, the MERIS Terrestrial Chlorophyll Index (MTCI). The tree plots were located in Catalonia, NE Spain. The relationship between MTCI and canopy N was present but dependent on the type of trees.
Stephanie Dutkiewicz, Anna E. Hickman, and Oliver Jahn
Biogeosciences, 15, 613–630, https://doi.org/10.5194/bg-15-613-2018, https://doi.org/10.5194/bg-15-613-2018, 2018
Short summary
Short summary
This study provides a demonstration that a biogeochemical/ecosystem/optical computer model which explicitly captures how light is radiated at the surface of the ocean and can be used as a laboratory to explore products (such as Chl a) that are derived from satellite measurements of ocean colour. It explores uncertainties that arise from data input used to derive the algorithms for the products, and issues arising from the interplay between optically important constituents in the ocean.
Gholamreza Mohammadpour, Jean-Pierre Gagné, Pierre Larouche, and Martin A. Montes-Hugo
Biogeosciences, 14, 5297–5312, https://doi.org/10.5194/bg-14-5297-2017, https://doi.org/10.5194/bg-14-5297-2017, 2017
Short summary
Short summary
The mass-specific absorption coefficients of total suspended particulate matter (aSPM*) had relatively low (high) values in areas of of the St. Lawrence Estuary influenced by marine (freshwater) waters and dominated by large-sized (small-sized) and organic-rich (mineral-rich) particulates.
The inorganic content of particulates was correlated with size-fractionated aSPM* values at a wavelength of 440 nm and the spectral slope of aSPM* as computed within the spectral range 400–710 nm.
Albert-Miquel Sánchez and Jaume Piera
Biogeosciences, 13, 4081–4098, https://doi.org/10.5194/bg-13-4081-2016, https://doi.org/10.5194/bg-13-4081-2016, 2016
Short summary
Short summary
In this paper, several methods for the retrieval of the refractive indices are used in three different examples modeling different shapes and particle size distributions. The error associated with each method is discussed and analyzed. It is finally demonstrated that those inverse methods using a genetic algorithm provide optimal estimations relative to other techniques that, although faster, are less accurate.
Luisa Galgani and Anja Engel
Biogeosciences, 13, 2453–2473, https://doi.org/10.5194/bg-13-2453-2016, https://doi.org/10.5194/bg-13-2453-2016, 2016
G. E. Kim, M.-A. Pradal, and A. Gnanadesikan
Biogeosciences, 12, 5119–5132, https://doi.org/10.5194/bg-12-5119-2015, https://doi.org/10.5194/bg-12-5119-2015, 2015
Short summary
Short summary
Light absorption by colored detrital material (CDM) was included in a fully coupled Earth system model. Chlorophyll and biomass increased near the surface but decreased at greater depths when CDM was included. Concurrently, total biomass decreased leaving more nutrients in the water. Regional changes were analyzed by comparing the competing factors of diminished light availability and increased nutrient availability on phytoplankton growth.
J. A. Gamon, O. Kovalchuck, C. Y. S. Wong, A. Harris, and S. R. Garrity
Biogeosciences, 12, 4149–4159, https://doi.org/10.5194/bg-12-4149-2015, https://doi.org/10.5194/bg-12-4149-2015, 2015
Short summary
Short summary
NDVI and PRI sensors (SRS, Decagon Inc.) exhibited complementary responses during spring photosynthetic activation in evergreen and deciduous stands. In evergreens, PRI was most strongly influenced by changing chlorophyll:carotenoid pool sizes over the several weeks of the study, while it was most affected by xanthophyll cycle pigment activity at the diurnal timescale. These automated PRI and NDVI sensors offer new ways to explore environmental and physiological constraints on photosynthesis.
M. Grenier, A. Della Penna, and T. W. Trull
Biogeosciences, 12, 2707–2735, https://doi.org/10.5194/bg-12-2707-2015, https://doi.org/10.5194/bg-12-2707-2015, 2015
Short summary
Short summary
Four bio-profilers were deployed in the high-biomass plume downstream of the Kerguelen Plateau (KP; Southern Ocean) to examine the conditions favouring phytoplankton accumulation. Regions of very high Chla accumulation were mainly associated with surface waters from the northern KP. Light limitation seems to have a limited influence on production. A cyclonic eddy was associated with a significant export of organic matter and a subsequent dissolved inorganic carbon storage in the ocean interior.
I. Cetinić, M. J. Perry, E. D'Asaro, N. Briggs, N. Poulton, M. E. Sieracki, and C. M. Lee
Biogeosciences, 12, 2179–2194, https://doi.org/10.5194/bg-12-2179-2015, https://doi.org/10.5194/bg-12-2179-2015, 2015
Short summary
Short summary
The ratio of simple optical properties measured from underwater autonomous platforms, such as floats and gliders, is used as a new tool for studying phytoplankton distribution in the North Atlantic Ocean. The resolution that optical instruments carried by autonomous platforms provide allows us to study phytoplankton patchiness and its drivers in the oceanic systems.
B. Heim, E. Abramova, R. Doerffer, F. Günther, J. Hölemann, A. Kraberg, H. Lantuit, A. Loginova, F. Martynov, P. P. Overduin, and C. Wegner
Biogeosciences, 11, 4191–4210, https://doi.org/10.5194/bg-11-4191-2014, https://doi.org/10.5194/bg-11-4191-2014, 2014
M. Kahru and R. Elmgren
Biogeosciences, 11, 3619–3633, https://doi.org/10.5194/bg-11-3619-2014, https://doi.org/10.5194/bg-11-3619-2014, 2014
E. J. D'Sa, J. I. Goes, H. Gomes, and C. Mouw
Biogeosciences, 11, 3225–3244, https://doi.org/10.5194/bg-11-3225-2014, https://doi.org/10.5194/bg-11-3225-2014, 2014
A. Matsuoka, M. Babin, D. Doxaran, S. B. Hooker, B. G. Mitchell, S. Bélanger, and A. Bricaud
Biogeosciences, 11, 3131–3147, https://doi.org/10.5194/bg-11-3131-2014, https://doi.org/10.5194/bg-11-3131-2014, 2014
S. Q. Wang, J. Ishizaka, H. Yamaguchi, S. C. Tripathy, M. Hayashi, Y. J. Xu, Y. Mino, T. Matsuno, Y. Watanabe, and S. J. Yoo
Biogeosciences, 11, 1759–1773, https://doi.org/10.5194/bg-11-1759-2014, https://doi.org/10.5194/bg-11-1759-2014, 2014
S. L. Shang, Q. Dong, C. M. Hu, G. Lin, Y. H. Li, and S. P. Shang
Biogeosciences, 11, 269–280, https://doi.org/10.5194/bg-11-269-2014, https://doi.org/10.5194/bg-11-269-2014, 2014
H. Örek, R. Doerffer, R. Röttgers, M. Boersma, and K. H. Wiltshire
Biogeosciences, 10, 7081–7094, https://doi.org/10.5194/bg-10-7081-2013, https://doi.org/10.5194/bg-10-7081-2013, 2013
S. Bélanger, S. A. Cizmeli, J. Ehn, A. Matsuoka, D. Doxaran, S. Hooker, and M. Babin
Biogeosciences, 10, 6433–6452, https://doi.org/10.5194/bg-10-6433-2013, https://doi.org/10.5194/bg-10-6433-2013, 2013
X. Zhang, Y. Huot, D. J. Gray, A. Weidemann, and W. J. Rhea
Biogeosciences, 10, 6029–6043, https://doi.org/10.5194/bg-10-6029-2013, https://doi.org/10.5194/bg-10-6029-2013, 2013
D. Antoine, S. B. Hooker, S. Bélanger, A. Matsuoka, and M. Babin
Biogeosciences, 10, 4493–4509, https://doi.org/10.5194/bg-10-4493-2013, https://doi.org/10.5194/bg-10-4493-2013, 2013
S. B. Hooker, J. H. Morrow, and A. Matsuoka
Biogeosciences, 10, 4511–4527, https://doi.org/10.5194/bg-10-4511-2013, https://doi.org/10.5194/bg-10-4511-2013, 2013
S. Bélanger, M. Babin, and J.-É. Tremblay
Biogeosciences, 10, 4087–4101, https://doi.org/10.5194/bg-10-4087-2013, https://doi.org/10.5194/bg-10-4087-2013, 2013
A. Matsuoka, S. B. Hooker, A. Bricaud, B. Gentili, and M. Babin
Biogeosciences, 10, 917–927, https://doi.org/10.5194/bg-10-917-2013, https://doi.org/10.5194/bg-10-917-2013, 2013
S. Takao, T. Hirawake, S. W. Wright, and K. Suzuki
Biogeosciences, 9, 3875–3890, https://doi.org/10.5194/bg-9-3875-2012, https://doi.org/10.5194/bg-9-3875-2012, 2012
R. Röttgers and B. P. Koch
Biogeosciences, 9, 2585–2596, https://doi.org/10.5194/bg-9-2585-2012, https://doi.org/10.5194/bg-9-2585-2012, 2012
A. Sadeghi, T. Dinter, M. Vountas, B. Taylor, M. Altenburg-Soppa, and A. Bracher
Biogeosciences, 9, 2127–2143, https://doi.org/10.5194/bg-9-2127-2012, https://doi.org/10.5194/bg-9-2127-2012, 2012
A. Matsuoka, A. Bricaud, R. Benner, J. Para, R. Sempéré, L. Prieur, S. Bélanger, and M. Babin
Biogeosciences, 9, 925–940, https://doi.org/10.5194/bg-9-925-2012, https://doi.org/10.5194/bg-9-925-2012, 2012
B. B. Taylor, E. Torrecilla, A. Bernhardt, M. H. Taylor, I. Peeken, R. Röttgers, J. Piera, and A. Bracher
Biogeosciences, 8, 3609–3629, https://doi.org/10.5194/bg-8-3609-2011, https://doi.org/10.5194/bg-8-3609-2011, 2011
G. Dall'Olmo, E. Boss, M. J. Behrenfeld, T. K. Westberry, C. Courties, L. Prieur, M. Pujo-Pay, N. Hardman-Mountford, and T. Moutin
Biogeosciences, 8, 3423–3439, https://doi.org/10.5194/bg-8-3423-2011, https://doi.org/10.5194/bg-8-3423-2011, 2011
H. Loisel, V. Vantrepotte, K. Norkvist, X. Mériaux, M. Kheireddine, J. Ras, M. Pujo-Pay, Y. Combet, K. Leblanc, G. Dall'Olmo, R. Mauriac, D. Dessailly, and T. Moutin
Biogeosciences, 8, 3295–3317, https://doi.org/10.5194/bg-8-3295-2011, https://doi.org/10.5194/bg-8-3295-2011, 2011
S. Shang, Q. Dong, Z. Lee, Y. Li, Y. Xie, and M. Behrenfeld
Biogeosciences, 8, 841–850, https://doi.org/10.5194/bg-8-841-2011, https://doi.org/10.5194/bg-8-841-2011, 2011
T. S. Kostadinov, D. A. Siegel, and S. Maritorena
Biogeosciences, 7, 3239–3257, https://doi.org/10.5194/bg-7-3239-2010, https://doi.org/10.5194/bg-7-3239-2010, 2010
F. Nencioli, G. Chang, M. Twardowski, and T. D. Dickey
Biogeosciences, 7, 151–162, https://doi.org/10.5194/bg-7-151-2010, https://doi.org/10.5194/bg-7-151-2010, 2010
A. Morel and B. Gentili
Biogeosciences, 6, 2625–2636, https://doi.org/10.5194/bg-6-2625-2009, https://doi.org/10.5194/bg-6-2625-2009, 2009
Cited articles
Aiken, J., Pradhan, Y., Barlow, R., Lavender, S., Poulton, A., Holligan, P., and Hardman-Mountford, N.: Phytoplankton pigments and functional types in the Atlantic Ocean: A decadal assessment, 1995–2005, Deep-Sea Res. Pt. II, 56, 899–917, https://doi.org/10.1016/j.dsr2.2008.09.017, 2009.
Barlow, R., Gibberd, M., Lamont, T., Aiken, J., and Holligan, P.: Chemotaxonomic phytoplankton patterns on the eastern boundary of the Atlantic Ocean, Deep-Sea Res. Pt. I, 111, 73–78, https://doi.org/10.1016/j.dsr.2016.02.011, 2016.
Barnes, C., Irigoien, X., De Oliveira, J. A., Maxwell, D., and Jennings, S.: Predicting marine phytoplankton community size structure from empirical relationships with remotely sensed variables, J. Plankton Res., 33, 13–24, https://doi.org/10.1093/plankt/fbq088, 2010.
Behrenfeld, M. J., O'Malley, R. T., Siegel, D. A., McClain, C. R., Sarmiento, J. L., Feldman, G. C., Milligan, A. J., Falkowski, P. G., Letelier, R. M., and Boss, E. S.: Climate-driven trends in contemporary ocean productivity, Nature, 444, 752–755, https://doi.org/10.1038/nature05317, 2006.
Behrenfeld, M. J.: Abandoning Sverdrup's critical depth hypothesis on phytoplankton blooms, Ecology, 91, 977–989, https://doi.org/10.1890/09-1207.1, 2010.
Bouman, H., Platt, T., Sathyendranath, S., and Stuart, V.: Dependence of light-saturated photosynthesis on temperature and community structure, Deep-Sea Res. Pt. I, 52, 1284–1299, https://doi.org/10.1016/j.dsr.2005.01.008, 2005.
Boyce, D. G., Lewis, M. R., and Worm, B.: Global phytoplankton decline over the past century, Nature, 466, 591–596, https://doi.org/10.1038/nature09268, 2010.
Bracher, A., Bouman, H. A., Brewin, R. J., Bricaud, A., Brotas, V., Ciotti, A. M., Clementson, L., Devred, E., Di Cicco, A., and Dutkiewicz, S.: Obtaining phytoplankton diversity from ocean color: a scientific roadmap for future development, Front. Mar. Sci., 4, 55, https://doi.org/10.3389/fmars.2017.00055, 2017.
Brewin, R. J., Sathyendranath, S., Hirata, T., Lavender, S. J., Barciela, R. M., and Hardman-Mountford, N. J.: A three-component model of phytoplankton size class for the Atlantic Ocean, Ecol. Model., 221, 1472–1483, https://doi.org/10.1016/j.ecolmodel.2010.02.014, 2010.
Brewin, R. J. W., Sathyendranath, S., Jackson, T., Barlow, R., Brotas, V., Airs, R., and Lamont, T.: Influence of light in the mixed-layer on the parameters of a three-component model of phytoplankton size class, Remote Sens. Environ., 168, 437–450, https://doi.org/10.1016/j.rse.2015.07.004, 2015.
Bricaud, A., Claustre, H., Ras, J., and Oubelkheir, K.: Natural variability of phytoplanktonic absorption in oceanic waters: Influence of the size structure of algal populations, J. Geophys. Res.-Oceans, 109, 45–50, https://doi.org/10.1029/2004JC002419, 2004.
Chen, C., Gong, G., and Jan, S.: Seasonal and episodic effects (dust storm) on nutrient dynamics in the upwelling across shelf break on the East China Sea to the Kuroshio Water, northeastern Taiwan, AGU Spring Meeting, 24–27 May 2009, 2009.
Chen, Y. L. L.: Comparisons of primary productivity and phytoplankton size structure in the marginal regions of southern East China Sea, Cont. Shelf Res., 20, 437–458, https://doi.org/10.1016/S0278-4343(99)00080-1, 2000.
Ciotti, A. M., Lewis, M. R., and Cullen, J. J.: Assessment of the relationships between dominant cell size in natural phytoplankton communities and the spectral shape of the absorption coefficient, Limnol. Oceanogr., 47, 404–417, https://doi.org/10.4319/lo.2002.47.2.0404, 2002.
Cleveland, J. and Weidemann, A. D.: Quantifying absorption by aquatic particles: A multiple scattering correction for glass-filters, Limnol. Oceanogr., 38, 1321–1327, https://doi.org/10.4319/lo.1993.38.6.1321, 1993.
Finkel, Z. V., Beardall, J., Flynn, K. J., Quigg, A., Rees, T. A. V., and Raven, J. A.: Phytoplankton in a changing world: cell size and elemental stoichiometry, J. Plankt. Res., 32, 119–137, https://doi.org/10.1093/plankt/fbp098, 2009.
Furuya, K., Kurita, K., and Odate, T.: Distribution of phytoplankton in the East China Sea in the winter of 1993, J. Oceanogr., 52, 323–333, https://doi.org/10.1007/BF02235927, 1996.
Furuya, K., Hayashi, M., Yabushita, Y., and Ishikawa, A.: Phytoplankton dynamics in the East China Sea in spring and summer as revealed by HPLC-derived pigment signatures, Deep-Sea Res. Pt. II, 50, 367–387, https://doi.org/10.1016/S0967-0645(02)00460-5, 2003.
Guan, B.: Patterns and structures of the currents in Bohai, Huanghai and East China Seas, in: Oceanology of China seas, Springer, Dordrecht, the Netherlands, 17–26, 1994.
Guidi, L., Stemmann, L., Jackson, G. A., Ibanez, F., Claustre, H., Legendre, L., Picheral, M., and Gorskya, G.: Effects of phytoplankton community on production, size, and export of large aggregates: A world-ocean analysis, Limnol. Oceanogr., 54, 1951–1963, https://doi.org/10.4319/lo.2009.54.6.1951, 2009.
Guo, S., Feng, Y., Wang, L., Dai, M., Liu, Z., Bai, Y., and Sun, J.: Seasonal variation in the phytoplankton community of a continental-shelf sea: the East China Sea, Mar. Ecol. Prog. Ser., 516, 103–126, https://doi.org/10.3354/meps10952, 2014.
He, X., Bai, Y., Pan, D., Chen, C.-T. A., Cheng, Q., Wang, D., and Gong, F.: Satellite views of the seasonal and interannual variability of phytoplankton blooms in the eastern China seas over the past 14 yr (1998–2011), Biogeosciences, 10, 4721–4739, https://doi.org/10.5194/bg-10-4721-2013, 2013.
Hirata, T., Aiken, J., Hardman-Mountford, N., Smyth, T. J., and Barlow, R. G.: An absorption model to determine phytoplankton size classes from satellite ocean colour, Remote Sens. Environ., 112, 3153–3159, https://doi.org/10.1016/j.rse.2008.03.011, 2008.
Hirata, T., Hardman-Mountford, N. J., Barlow, R., Lamont, T., Brewin, R., Smyth, T., and Aiken, J.: An inherent optical property approach to the estimation of size-specific photosynthetic rates in eastern boundary upwelling zones from satellite ocean colour: an initial assessment, Prog. Oceanogr., 83, 393–397, https://doi.org/10.1016/j.pocean.2009.07.019, 2009.
Hirata, T., Hardman-Mountford, N. J., Brewin, R. J. W., Aiken, J., Barlow, R., Suzuki, K., Isada, T., Howell, E., Hashioka, T., Noguchi-Aita, M., and Yamanaka, Y.: Synoptic relationships between surface Chlorophyll a and diagnostic pigments specific to phytoplankton functional types, Biogeosciences, 8, 311–327, https://doi.org/10.5194/bg-8-311-2011, 2011.
Hirawake, T., Takao, S., Horimoto, N., Ishimaru, T., Yamaguchi, Y., and Fukuchi, M.: A phytoplankton absorption-based primary productivity model for remote sensing in the Southern Ocean, Polar Biol., 34, 291–302, https://doi.org/10.1007/s00300-010-0949-y, 2011.
Hosmer Jr, D. W., Lemeshow, S., and Sturdivant, R. X.: Applied logistic regression, John Wiley & Sons, Hoboken, New Jersey, 2013.
Hu, C., Feng, L., and Lee, Z.: Uncertainties of SeaWiFS and MODIS remote sensing reflectance: Implications from clear water measurements, Remote Sens. Environ., 133, 168–182, https://doi.org/10.1016/j.rse.2013.02.012, 2013.
Ichikawa, H. and Beardsley, R. C.: The current system in the Yellow and East China Seas, J. Oceanogr., 58, 77–92, https://doi.org/10.1023/A:1015876701363, 2002.
IOCCG: Phytoplankton functional types from Space, in: Reports of International Ocean-Colour Coordinating Group, edited by: Sathyendranath, S., no 15, 1–156, Dartmouth, Canada: IOCCG, 2014.
Jiang, Z., Liu, J., Chen, J., Chen, Q., Yan, X., Xuan, J., and Zeng, J.: Responses of summer phytoplankton community to drastic environmental changes in the Changjiang (Yangtze River) estuary during the past 50 years, Water Res., 54, 1–11, https://doi.org/10.1016/j.watres.2014.01.032, 2014.
Jiang, Z., Chen, J., Zhou, F., Shou, L., Chen, Q., Tao, B., Yan, X., and Wang, K.: Controlling factors of summer phytoplankton community in the Changjiang (Yangtze River) Estuary and adjacent East China Sea shelf, Cont. Shelf Res., 101, 71–84, https://doi.org/10.1016/j.csr.2015.04.009, 2015.
Jiao, N., Yang, Y., Hong, N., Ma, Y., Harada, S., Koshikawa, H., and Watanabe, M.: Dynamics of autotrophic picoplankton and heterotrophic bacteria in the East China Sea, Cont. Shelf Res., 25, 1265–1279, https://doi.org/10.1016/j.csr.2005.01.002, 2005.
Kiørboe, T.: Turbulence, phytoplankton cell size, and the structure of pelagic food webs, Adv. Mar. Biol., 29, 1–72, https://doi.org/10.1016/S0065-2881(08)60129-7, 1993.
Lamont, T., Brewin, R., and Barlow, R.: Seasonal variation in remotely-sensed phytoplankton size structure around southern Africa, Remote Sens. Environ., 204, 617–631, https://doi.org/10.1016/j.rse.2017.09.038, 2018.
Lee, Z., Carder, K. L., and Arnone, R. A.: Deriving inherent optical properties from water color: a multiband quasi-analytical algorithm for optically deep waters, Appl. Opt., 41, 5755–5772, https://doi.org/10.1364/AO.41.005755, 2002.
Lee, Z., Lubac, B., Werdell, J., and Arnone, R.: An update of the quasi-analytical algorithm (QAA_v5), International Ocean Color Group Software Report, 1–9, 2009.
Lee, Z., Shang, S., Hu, C., and Zibordi, G.: Spectral interdependence of remote-sensing reflectance and its implications on the design of ocean color satellite sensors, Appl. Opt., 53, 3301–3310, https://doi.org/10.1364/AO.53.003301, 2014.
Li, Y., Li, D. J., Tang, J. L., Wang, Y. M., Liu, Z. G., Ding, P. X., and He, S. Q.: Phytoplankton Distribution and Variation in the Yangtze River Estuary and Its Adjacent Sea, Environ. Sci., 28, 719–729, 2007 (in Chinese).
Liu, D. and Wang, Y.: Trends of satellite derived chlorophyll a (1997–2011) in the Bohai and Yellow Seas, China: Effects of bathymetry on seasonal and inter-annual patterns, Prog. Oceanogr., 116, 154–166, https://doi.org/10.1016/j.pocean.2013.07.003, 2013.
Liu, J., Xu, K., Li, A. E. A., Milliman, J., Velozzi, D., Xiao, S., and Yang, Z.: Flux and fate of Yangtze River sediment delivered to the East China Sea, Geomorphology, 85, 208–224, https://doi.org/10.1016/j.geomorph.2006.03.023, 2007.
Liu, X., Xiao, W., Landry, M. R., Chiang, K. P., Wang, L., and Huang, B.: Responses of Phytoplankton Communities to Environmental Variability in the East China Sea, Ecosystems, 19, 832–849, https://doi.org/10.1007/s10021-016-9970-5, 2016.
Lou, X. and Hu, C.: Diurnal changes of a harmful algal bloom in the East China Sea: Observations from GOCI, Remote Sens. Environ., 140, 562–572, https://doi.org/10.1016/j.rse.2013.09.031, 2014.
Lovelock, J.: The revenge of gaia: Earth's climate crisis & the fate of humanity, Basic Books, New York, 2007.
Luan, Q. S., Sun, J., Song, S. Q., Shen, Z. L., and Yu, Z. M.: Canonical correspondence analysis of summer phytoplankton community and its environment in the Yangtze River Estuary, China, J. Plant Ecol., 31, 445–450, https://doi.org/10.17521/cjpe.2007.0054, 2007 (in Chinese).
Malone, T. C.: Environmental control of phytoplankton cell size, Limnol. Oceanogr., 20, 490–490, https://doi.org/10.4319/lo.1973.18.4.0511, 1975.
Meister, G.: Calibration and characterization adjustments to the MODIS ocean color band by the OBPG, Proc. MODIS Sci. Team Meeting, 18–20 May 2011, 1–23, 2011.
Mitchell, B. G.: Algorithms for determining the absorption coefficient for aquatic particulates using the quantitative filter technique, Orlando'90, 16–20 April, 137–148, 1990.
Montagnes, D. J., Berges, J. A., Harrison, P. J., and Taylor, F.: Estimating carbon, nitrogen, protein, and chlorophyll a from volume in marine phytoplankton, Limnol. Oceanogr., 39, 1044–1060, https://doi.org/10.4319/lo.1994.39.5.1044, 1994.
Mueller, J. L., Fargion, G. S., Mcclain, C. R., Pegau, S., Zanefeld, J. R. V., Mitchell, B. G., Kahru, M., Wieland, J., and Stramska, M.: Ocean Optics Protocols for Satellite Ocean Color Sensor Validation, Revision 4, Volume IV: Inherent Optical Properties: Instruments, Characterizations, Field Measurements and Data Analysis Protocols, 2003.
Sheldon, R. and Parsons, T. R.: A practical manual on the use of the Coulter Counter in marine research, Coulter Electronics Sales, 1967.
Sieburth, J. M., Smetacek, V., and Lenz, J.: Pelagic ecosystem structure: heterotrophic compartments of the plankton and their relationship to plankton size fractions, Limnol. Oceanogr., 23, 1256–1263, https://doi.org/10.4319/lo.1978.23.6.1256, 1978.
Siswanto, E., Nakata, H., Matsuoka, Y., Tanaka, K., Kiyomoto, Y., Okamura, K., Zhu, J., and Ishizaka, J.: The long-term freshening and nutrient increases in summer surface water in the northern East China Sea in relation to Changjiang discharge variation, J. Geophys. Res.-Oceans, 113, 2601–2613, https://doi.org/10.1029/2008JC004812, 2008.
Smith, W. O., Heburn, G. W., Barber, R. T., and O'Brien, J. J.: Regulation of phytoplankton communities by physical processes in upwelling ecosystems, J. Mar. Res., 41, 539–556, https://doi.org/10.1357/002224083788519777, 1983.
Su, J. L. and Yuan, Y. L.: Coastal Hydrology in China, Ocean Press, Beijing, 2005 (in Chinese).
Sun, D., Hu, C., Qiu, Z., and Wang, S.: Reconstruction of hyperspectral reflectance for optically complex turbid inland lakes: test of a new scheme and implications for inversion algorithms, Opt. Exp., 23, A718–A740, https://doi.org/10.1364/OE.23.00A718, 2015.
Sun, D., Huan, Y., Qiu, Z., Hu, C., Wang, S., and He, Y.: Remote-Sensing Estimation of Phytoplankton Size Classes From GOCI Satellite Measurements in Bohai Sea and Yellow Sea, J. Geophys. Res.-Oceans, 122, 8309–8325, https://doi.org/10.1002/2017JC013099, 2017.
Sun, S., Lu, J., and Zhang, L.: Applications of flow cytometer in ecological studies of nano- and pico-phytoplankton, Chinese Journal of Ecology, 19, 72–78, 2000 (in Chinese).
Tang, J., Tian, G., Wang, X., Wang, X., and Song, Q.: The methods of water spectra measurement and analysis I: above-water method, J. Remote Sens., 8, 37–44, 2004.
Tassan, S. and Ferrari, G. M.: An alternative approach to absorption measurements of aquatic particles retained on filters, Limnol. Oceanogr., 40, 1358–1368, https://doi.org/10.4319/lo.1995.40.8.1358, 1995.
Tassan, S. and Ferrari, G.: A sensitivity analysis of the “Transmittance–Reflectance” method for measuring light absorption by aquatic particles, J. Plankt. Res., 24, 757–774, https://doi.org/10.1093/plankt/24.8.757, 2002.
Taylor, A. H. and Joint, I.: A steady-state analysis of the “microbial loop” in stratified systems, Mar. Ecol. Prog., 59, 1–17, https://doi.org/10.3354/meps059001, 1990.
Tiwari, S. P. and Shanmugam, P.: An evaluation of models for the satellite-estimation of phytoplankton absorption coefficients in coastal/oceanic waters, IEEE J. S. Top. Appl., 7, 364–371, https://doi.org/10.1109/JSTARS.2013.2252151, 2014.
Uitz, J., Claustre, H., Morel, A., and Hooker, S. B.: Vertical distribution of phytoplankton communities in open ocean: An assessment based on surface chlorophyll, J. Geophys. Res.-Oceans, 111, C8005, https://doi.org/10.1029/2005JC003207, 2006.
Uitz, J., Huot, Y., Bruyant, F., Babin, M., and Claustre, H.: Relating phytoplankton photophysiological properties to community structure on large scales, Limnol. Oceanogr., 53, 614–630, https://doi.org/10.4319/lo.2008.53.2.0614, 2008.
Van Heukelem, L. and Hooker, S.: The importance of a quality assurance plan for method validation and minimizing uncertainties in the HPLC analysis of phytoplankton pigments, Phytoplankton Pigments, 5, 195–256, https://doi.org/10.1017/CBO9780511732263.009, 2011.
Van Heukelem, L. and Thomas, C. S.: Computer-assisted high-performance liquid chromatography method development with applications to the isolation and analysis of phytoplankton pigments, J. Chromatogr. A, 910, 31–49, https://doi.org/10.1016/S0378-4347(00)00603-4, 2001.
Vidussi, F., Claustre, H., Manca, B. B., Luchetta, A., and Marty, J. C.: Phytoplankton pigment distribution in relation to upper thermocline circulation in the eastern Mediterranean Sea during winter, J. Geophys. Res.-Oceans, 106, 19939–19956, https://doi.org/10.1029/1999JC000308, 2001.
Wang, S., Ishizaka, J., Hirawake, T., Watanabe, Y., Zhu, Y., Hayashi, M., and Yoo, S.: Remote estimation of phytoplankton size fractions using the spectral shape of light absorption, Optics Exp., 23, 10301–10318, https://doi.org/10.1364/OE.23.010301, 2015.
Wang, S. Q., Ishizaka, J., Yamaguchi, H., Tripathy, S. C., Hayashi, M., Xu, Y. J., Mino, Y., Matsuno, T., Watanabe, Y., and Yoo, S. J.: Influence of the Changjiang River on the light absorption properties of phytoplankton from the East China Sea, Biogeosciences, 11, 1759–1773, https://doi.org/10.5194/bg-11-1759-2014, 2014.
Yamaguchi, H., Kim, H. C., Son, Y. B., Sang, W. K., Okamura, K., Kiyomoto, Y., and Ishizaka, J.: Seasonal and summer interannual variations of SeaWiFS chlorophyll a in the Yellow Sea and East China Sea, Prog. Oceanogr., 105, 22–29, https://doi.org/10.1016/j.pocean.2012.04.004, 2012.
Zhang, H., Qiu, Z., Sun, D., Wang, S., and He, Y.: Seasonal and Interannual Variability of Satellite-Derived Chlorophyll a (2000–2012) in the Bohai Sea, China, Remote Sensing, 9, 582, https://doi.org/10.3390/rs9060582, 2017.
Zhang, J., Liu, S., Ren, J., Wu, Y., and Zhang, G.: Nutrient gradients from the eutrophic Changjiang (Yangtze River) Estuary to the oligotrophic Kuroshio waters and re-evaluation of budgets for the East China Sea Shelf, Prog. Oceanogr., 74, 449–478, https://doi.org/10.1016/j.pocean.2007.04.019, 2007.
Zhou, M. J., Shen, Z. L., and Yu, R. C.: Responses of a coastal phytoplankton community to increased nutrient input from the Changjiang (Yangtze) River, Cont. Shelf Res., 28, 1483–1489, https://doi.org/10.1016/j.csr.2007.02.009, 2008.
Short summary
The PSC model was re-tuned for regional application in the East China Sea, and successfully applied to MODIS data. We investigated previously unknown temporal–spatial patterns of the PSC in the ECS and analyzed their responses to environmental factors. The results show the PSC varied across both spatial and temporal scales, and was probably affected by the water column stability, upwelling, and Kuroshio. In addition, human activity and riverine discharge may impact the PSC dynamics.
The PSC model was re-tuned for regional application in the East China Sea, and successfully...
Altmetrics
Final-revised paper
Preprint