journal article·2018-12-19Open access

The Fundamental Contribution of Phytoplankton Spectral Scattering to Ocean Colour: Implications for Satellite Detection of Phytoplankton Community Structure

Lisl Robertson Lain, Stewart Bernard

Applied Sciences· Volume 8· Issue 12

Abstract

There is increasing interdisciplinary interest in phytoplankton community dynamics as the growing environmental problems of water quality (particularly eutrophication) and climate change demand attention. This has led to a pressing need for improved biophysical and causal understanding of Phytoplankton Functional Type (PFT) optical signals, in order for satellite radiometry to be used to detect ecologically relevant phytoplankton assemblage changes. Biophysically and biogeochemically consistent phytoplankton Inherent Optical Property (IOP) models play an important role in achieving this understanding, as the optical effects of phytoplankton assemblage changes can be examined systematically in relation to the bulk optical water-leaving signal. The Equivalent Algal Populations (EAP) model is used here to investigate the source and magnitude of size- and pigment- driven PFT signals in the water-leaving reflectance, as well as the potential to detect these using satellite radiometry. This model places emphasis on the determination of biophysically consistent phytoplankton IOPs, with both absorption and scattering determined by mathematically cogent relationships to the particle complex refractive indices. All IOPs are integrated over an entire size distribution. A distinctive attribute is the model’s comprehensive handling of the spectral and angular character of phytoplankton scattering. Selected case studies and sensitivity analyses reveal that phytoplankton spectral scattering is most useful and the least ambiguous driver of the PFT signal. Key findings are that there is the most sensitivity in phytoplankton backscatter ( b b ϕ ) in the 1–6 μ m size range; the backscattering-driven signal in the 520 to 570 nm region is the critical PFT identifier at marginal biomass, and that, while PFT information does appear at blue wavelengths, absorption-driven signals are compromised by ambiguity due to biomass and non-algal absorption. Low signal in the red, due primarily to absorption by water, inhibits PFT detection here. The study highlights the need to quantitatively understand the constraints imposed by phytoplankton biomass and the IOP budget on the assemblage-related signal. A proportional phytoplankton contribution of approximately 40% to the total b b appears to a reasonable minimum threshold in terms of yielding a detectable optical change in R r s . We hope these findings will provide considerable insight into the next generation of PFT algorithms.
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Research context

OpenAlex topics: Marine and coastal ecosystems · Marine Biology and Ecology Research · Water Quality Monitoring and Analysis

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Oceanography, University of Cape Town, Cape Town 7700, South Africa

NRE, Centre for Scientific and Industrial Research (CSIR), Cape Town 7700, South Africa

Funding

University of Cape Town

References (100+)

Show source-provided references
1. Primary production of the biosphere: Integrating terrestrial and oceanic components10.1126/science.281.5374.237 ↗
2. A decade of satellite ocean color observations10.1146/annurev.marine.010908.163650 ↗
3. Southern Ocean Seasonal Cycle Experiment 2012: Seasonal scale climate and carbon cycle links10.4102/sajs.v108i3/4.1089 ↗
4. Regional scale characteristics of the seasonal cycle of chlorophyll in the Southern Ocean10.5194/bg-8-2849-2011 ↗
5. Modelled estimates of spatial variability of iron stress in the Atlantic sector of the Southern Ocean10.5194/bg-14-3883-2017 ↗
6. Uncertainty in Ocean-Color Estimates of Chlorophyll for Phytoplankton Groups10.3389/fmars.2017.00104 ↗
7. Assessment of uncertainty in the ocean reflectance determined by three satellite ocean color sensors (MERIS, SeaWiFS and MODIS-A) at an offshore site in the Mediterranean Sea (BOUSSOLE project)10.1029/2007JC004472 ↗
8. Discrimination of diatoms from other phytoplankton using ocean-colour data10.3354/meps272059 ↗
9. Theoretical analysis of ocean color radiances anomalies and implications for phytoplankton groups detection in Case 1 waters10.1364/OE.20.001070 ↗
10. Kostadinov, T., Siegel, D., and Maritorena, S. (2009). Retrieval of the particle size distribution from satellite ocean color observations. J. Geophys. Res. Oceans, 114.10.1029/2009JC005303 ↗
11. Carbon-based phytoplankton size classes retrieved via ocean color estimates of the particle size distribution10.5194/os-12-561-2016 ↗
12. Plankton functional type modelling: Running before we can walk?10.1093/plankt/fbi076 ↗
13. The origin and global distribution of second order variability in satellite ocean color and its potential applications to algorithm development10.1016/j.rse.2008.06.008 ↗
14. Uncertainty estimates of remote sensing reflectance derived from comparison of ocean color satellite data sets10.1016/j.rse.2016.02.014 ↗
15. Remote Sensing of Inherent Optical Properties: Fundamentals, Tests of Algorithms and Applications
16. Assessment of satellite ocean color products at a coastal site10.1016/j.rse.2007.02.026 ↗
17. A Consumer’s Guide to Satellite Remote Sensing of Multiple Phytoplankton Groups in the Global Ocean10.3389/fmars.2017.00041 ↗
18. Synoptic relationships between surface Chlorophyll-a and diagnostic pigments specific to phytoplankton functional types10.5194/bg-8-311-2011 ↗
19. An intercomparison of bio-optical techniques for detecting dominant phytoplankton size class from satellite remote sensing10.1016/j.rse.2010.09.004 ↗
20. A three-component model of phytoplankton size class for the Atlantic Ocean10.1016/j.ecolmodel.2010.02.014 ↗
21. Remote sensing of phytoplankton groups in Case 1 waters from global SeaWiFS imagery10.1016/j.dsr.2005.06.015 ↗
22. Seasonal distribution and succession of dominant phytoplankton groups in the global ocean: A satellite view10.1029/2007GB003154 ↗
23. A three component classification of phytoplankton absorption spectra: Application to ocean-color data10.1016/j.rse.2011.04.025 ↗
24. Retrievals of a size parameter for phytoplankton and spectral light absorption by colored detrital matter from water-leaving radiances at SeaWiFS channels in a continental shelf region off Brazil10.4319/lom.2006.4.237 ↗
25. Quantitative observation of cyanobacteria and diatoms from space using PhytoDOAS on SCIAMACHY data10.5194/bg-6-751-2009 ↗
26. Global variability of phytoplankton functional types from space: assessment via the particle size distribution10.5194/bg-7-3239-2010 ↗
27. Simulating the optical properties of phytoplankton cells using a two-layered spherical geometry
28. Assessing phytoplankton community composition from hyperspectral measurements of phytoplankton absorption coefficient and remote-sensing reflectance in open-ocean environments10.1016/j.rse.2015.09.027 ↗
29. Cluster analysis of hyperspectral optical data for discriminating phytoplankton pigment assemblages in the open ocean10.1016/j.rse.2011.05.014 ↗
30. Hyperspectral differentiation of phytoplankton taxonomic groups: A comparison between using remote sensing reflectance and absorption spectra10.3390/rs71114781 ↗
31. Remote sensing of coccolithophore blooms in selected oceanic regions using the PhytoDOAS method applied to hyper-spectral satellite data10.5194/bg-9-2127-2012 ↗
32. Modeling the inherent optical properties of the ocean based on the detailed composition of the planktonic community10.1364/AO.40.002929 ↗
33. Bio-optical characteristics of the western Arctic Ocean: Implications for ocean color algorithms10.5589/m07-059 ↗
34. The use of equivalent size distributions of natural phytoplankton assemblages for optical modeling10.1364/OE.15.001995 ↗
35. Understanding the contribution of phytoplankton phase functions to uncertainties in the water colour signal10.1364/OE.25.00A151 ↗
36. Consequences of a Synechococcus bloom upon the optical properties of oceanic (case 1) waters10.4319/lo.1997.42.8.1746 ↗
37. Sensitivity in reflectance attributed to phytoplankton cell size: Forward and inverse modelling approaches10.1364/OE.22.011536 ↗
38. On the discrimination of multiple phytoplankton groups from light absorption spectra of assemblages with mixed taxonomic composition and variable light conditions10.1364/AO.56.003952 ↗
39. Defoin-Platel, M., and Chami, M. (2007). How ambiguous is the inverse problem of ocean color in coastal waters?. J. Geophys. Res. Oceans, 112.10.1029/2006JC003847 ↗
40. A theoretical analysis of the contribution of algal cells to the attenuation of light within natural waters I. General treatment of suspensions of pigmented cells10.1111/j.1469-8137.1975.tb01366.x ↗
41. Theoretical results concerning light absorption in a discrete medium, and application to specific absorption of phytoplankton10.1016/0198-0149(81)90039-X ↗
42. Variations in the spectral values of specific absorption of phytoplankton10.4319/lo.1987.32.2.0403 ↗
43. Optical properties of diverse phytoplanktonic species: Experimental results and theoretical interpretation10.1093/plankt/10.5.851 ↗
44. Light backscattering efficiency and related properties of some phytoplankters10.1016/0198-0149(92)90002-B ↗
45. Spectral absorption coefficients of living phytoplankton and nonalgal biogenous matter: A comparison between the Peru upwelling areaand the Sargasso Sea10.4319/lo.1990.35.3.0562 ↗
46. Ecosystem dynamics based on plankton functional types for global ocean biogeochemistry models10.1111/j.1365-2486.2005.1004.x ↗
47. Remote sensing of phytoplankton functional types10.1016/j.rse.2008.01.021 ↗
48. IOCCG (2014). Phytoplankton Functional Types from Space. Reports of the International Ocean Colour Coordinating Group, IOCCG.
49. Capturing optically important constituents and properties in a marine biogeochemical and ecosystem model10.5194/bg-12-4447-2015 ↗
50. Moutier, W., Duforet-Gaurier, L., Thyssen, M., Loisel, H., Meriaux, X., Courcot, L., Dessailly, D., Reve, A.H., Gregori, G., and Alvain, S. (2017). Evolution of the scattering properties of phytoplankton cells from flow cytometry measurements. PLoS ONE, 12.10.1371/journal.pone.0181180 ↗
51. Optical properties of photosynthetic picoplankton in different physiological states as affected by growth irradiance10.1016/0198-0149(90)90126-G ↗
52. The effect of nitrogren limitation on the absorption and scattering properties of the marine diatom Thalassiosira pseudonana10.4319/lo.1997.42.5.0881 ↗
53. Effects of temperature, nitrogen, and light limitation on the optical properties of the marine diatom Thalassiosira pseudonana10.4319/lo.2002.47.2.0392 ↗
54. Diel variations in the optical properties of a marine diatom10.4319/lo.1993.38.7.1347 ↗
55. Optical characterization of the oceanic unicellular cyanobacterium Synechococcus grown under a day-night cycle in natural irradiance10.1029/95JC00452 ↗
56. Under the hood of satellite empirical chlorophyll a algorithms: Revealing the dependencies of maximum band ratio algorithms on inherent optical properties10.1364/OE.20.020920 ↗
57. Ocean-colour products for climate-change studies: What are their ideal characteristics?10.1016/j.rse.2017.04.017 ↗
58. Effects of microbial particles on oceanic optics: Methodology for radiative transfer modeling and example simulations10.4319/lo.1997.42.3.0550 ↗
59. Effects of microbial particles on oceanic optics: A database of single-particle optical properties10.4319/lo.1997.42.3.0538 ↗
60. Analysis of variations in ocean color10.4319/lo.1977.22.4.0709 ↗
61. Hoepffner, N., and Sathyendranath, S. (1991). Effect of pigment composition on absorption properties of phytoplankton. Mar. Ecol. Prog. Ser., 11–23.10.3354/meps073011 ↗
62. Discrimination of eukaryotic phytoplankton cell types from light scatter and autofluorescence properties measured by flow cytometry10.1002/cyto.990100520 ↗
63. Using a two-layered sphere model to investigate the impact of gas vacuoles on the inherent optical properties of M. aeruginosa10.5194/bg-10-8139-2013 ↗
64. An optimized Chlorophyll a switching algorithm for MERIS and OLCI in phytoplankton-dominated waters10.1016/j.rse.2018.06.002 ↗
65. Biophysical modelling of phytoplankton communities from first principles using two-layered spheres: Equivalent Algal Populations (EAP) model10.1364/OE.22.016745 ↗
66. The role of seawater constituents in light backscattering in the ocean10.1016/j.pocean.2004.07.001 ↗
67. Causality and the Dispersion Relation: Logical Foundations10.1103/PhysRev.104.1760 ↗
68. Refractive index of phytoplankton derived from its metabolite composition10.1093/plankt/18.12.2223 ↗
69. Measured and modelled optical properties of particulate matter in the southern Benguela
70. Refractive index of planktonic cells as a measure of cellular carbon and chlorophyll a content10.1016/S0967-0637(98)00065-X ↗
71. Johnsen, G., Samset, O., Granskog, L., and Sakshaug, E. (1994). In vivo absorption characteristics in 10 classes of bloom-forming phytoplankton: Taconomic characteristics and responses to photoadaptation by means of discriminant and HPLC analysis. Mar. Ecol. Prog. Ser., 149–157.10.3354/meps105149 ↗
72. Variability in the chlorophyll-specific absorption coefficients of natural phytoplankton: Analysis and parameterization10.1029/95JC00463 ↗
73. Climate change and Southern Ocean ecosystems I: How changes in physical habitats directly affect marine biota10.1111/gcb.12623 ↗
74. Mtshali, T.N. (2016). SANAE 55 Cruise Report, South African National Antarctic Programme (SANAP).
75. Del Castillo, C.E., and Miller, R.L. (2011). Horizontal and vertical distributions of colored dissolved organic matter during the Southern Ocean Gas Exchange Experiment. J. Geophys. Res. Oceans, 116.10.1029/2010JC006781 ↗
76. A chlorophyll-dependent semianalytical reflectance model derived from field measurements of absorption and backscattering coefficients within the Southern Ocean10.1029/1999JC000311 ↗
77. Cryptophyte algae are robbed of their organelles by the marine ciliate Mesodinium rubrum10.1038/35016570 ↗
78. Estimation of the absorption and backscattering coefficients from in water radiometric measurements10.4319/lo.2000.45.3.0628 ↗
79. Partitioning total spectral absorption in phytoplankton and colored detrital material contributions10.4319/lom.2007.5.384 ↗
80. Influence of the angular shape of the volume-scattering function and multiple scattering on remote sensing reflectance10.1364/AO.45.009210 ↗
81. Atmospheric correction of ocean color imagery in the Earth Observing System era10.1029/96JD02443 ↗
82. The biogeochemical cycle of iron in the ocean10.1038/ngeo964 ↗
83. Bernard, S., Pitcher, G., Evers-King, H., Robertson, L., Matthews, M., Rabagliati, A., and Balt, C. (2014). Ocean Colour Remote Sensing of Harmful Algal Blooms in the Benguela System. Remote Sensing of the African Seas, Springer.10.1007/978-94-017-8008-7_10 ↗
84. Devred, E., Sathyendranath, S., Stuart, V., Maass, H., Ulloa, O., and Platt, T. (2006). A two-component model of phytoplankton absorption in the open ocean: Theory and applications. J. Geophys. Res. Oceans, 111.10.1029/2005JC002880 ↗
85. Accurate estimation of the backscattering coefficient by light scattering at two backward angles10.1364/AO.54.007718 ↗
86. Laboratory experiments for inter-comparison of three volume scattering meters to measure angular scattering properties of hydrosols10.1364/OE.24.00A234 ↗
87. Bricaud, A., Claustre, H., Ras, J., and Oubelkheir, K. (2004). Natural variability of phytoplanktonic absorption in oceanic waters: Influence of the size structure of algal populations. J. Geophys. Res. Oceans, 109.10.1029/2004JC002419 ↗
88. Red and black tides: Quantitative analysis of water-leaving radiance and perceived color for phytoplankton, colored dissolved organic matter, and suspended sediments10.4319/lo.2006.51.6.2646 ↗
89. Light-scattering methods for modelling algal particles as a collection of coated and/or nonspherical scatterers10.1016/j.jqsrt.2005.11.048 ↗
90. Abundance, size structure and community composition of phytoplankton in the Southern Ocean in the austral summer 1999/2000
91. Analysis of phytoplankton of the Australian sector of the Southern Ocean: Comparisons of microscopy and size frequency data with interpretations of pigment HPLC data using the∖’CHEMTAX∖’matrix factorisation program10.3354/meps144285 ↗
92. Wright, S.W., and Jeffrey, S. (1987). Fucoxanthin pigment markers of marine phytoplankton analysed by HPLC and HPTLC. Mar. Ecol. Prog. Ser., 259–266.10.3354/meps038259 ↗
93. Absorption by dissolved organic matter of the sea (yellow substance) in the UV and visible domains10.4319/lo.1981.26.1.0043 ↗
94. Modeling in situ phytoplankton absorption from total absorption spectra in productive inland marine waters10.4319/lo.1989.34.8.1510 ↗
95. Towards the validation of SeaWiFS in southern African waters: The effects of gelbstoff10.2989/025776198784126944 ↗
96. In situ phytoplankton absorption, fluorescence emission, and particulate backscattering spectra determined from reflectance10.1029/95JC00455 ↗
97. Spectral variation of the volume scattering function measured over the full range of scattering angles in a coastal environment10.1364/AO.45.003605 ↗
98. Model for estimating bulk refractive index from the optical backscattering ratio and the implications for understanding particle composition in case I and case II waters10.1029/2000JC000404 ↗
99. Boss, E., Pegau, W., Lee, M., Twardowski, M., Shybanov, E., Korotaev, G., and Baratange, F. (2004). Particulate backscattering ratio at LEO 15 and its use to study particle composition and distribution. J. Geophys. Res. Oceans, 109.10.1029/2002JC001514 ↗
100. Fluorometric determination of chlorophyll10.1093/icesjms/30.1.3 ↗