Articles | Volume 16, issue 9
https://doi.org/10.5194/bg-16-1975-2019
© Author(s) 2019. 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-16-1975-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 May 2019
Research article |
| 14 May 2019
| 14 May 2019
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
Department of Oceanography and Coastal Sciences, Louisiana State
University, Baton Rouge, LA 70803, USA
Eurico J. D'Sa
Department of Oceanography and Coastal Sciences, Louisiana State
University, Baton Rouge, LA 70803, USA
Ishan D. Joshi
Department of Oceanography and Coastal Sciences, Louisiana State
University, Baton Rouge, LA 70803, USA
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Zhengchen Zang, Z. George Xue, Kehui Xu, Samuel J. Bentley, Qin Chen, Eurico J. D'Sa, Le Zhang, and Yanda Ou
Biogeosciences, 17, 5043–5055, https://doi.org/10.5194/bg-17-5043-2020, https://doi.org/10.5194/bg-17-5043-2020, 2020
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.
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
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Biogeosciences, 15, 613–630, https://doi.org/10.5194/bg-15-613-2018, https://doi.org/10.5194/bg-15-613-2018, 2018
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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
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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
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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
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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
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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
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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
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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
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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.
An approach using bio-optical field and ocean color (Sentinel-3A OLCI) data combined with...
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