Abstract

Models based on the multivariate partial least squares (PLS) regression technique are developed for the retrieval of phytoplankton size structure from measured light absorption spectra (BOUSSOLE site, northwestern Mediterranean Sea). PLS-models trained with data from the Mediterranean Sea showed good accuracy in retrieving, over the nine-year BOUSSOLE time series, the concentrations of total chlorophyll a [Tchl a], of the sum of seven diagnostic pigments and of pigments associated with micro, nano, and picophytoplankton size classes separately. PLS-models trained using either total particle or phytoplankton absorption spectra performed similarly, and both reproduced seasonal variations of biomass and size classes derived by high performance liquid chromatography. Satisfactory retrievals were also obtained using PLS-models trained with a data set including various locations of the world’s oceans, with however a lower accuracy. These results open the way to an application of this method to absorption spectra derived from hyperspectral and field satellite radiance measurements.

© 2013 Optical Society of America

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2012 (1)

C. B. Mouw, J. A. Yoder, and S. C. Doney, “Impact of phytoplankton community size on a linked global ocean optical and ecosystem model,” J. Mar. Syst. 89, 61–75 (2012).
[CrossRef]

2011 (7)

A. Fujiwara, T. Hirawake, K. Suzuki, and S. I. Saitoh, “Remote sensing of size structure of phytoplankton communities using optical properties of the Chukchi and Bering Sea shelf region,” Biogeosciences 8, 3567–3580 (2011).
[CrossRef]

T. Hirata, N. J. Hardman-Mountford, R. J. W. Brewin, J. Aiken, R. Barlow, K. Suzuki, T. Isada, E. Howell, T. Hashioka, M. Noguchi-Aita, and Y. Yamanaka, “Synoptic relationships between surface chlorophyll-a and diagnostic pigments specific to phytoplankton functional types,” Biogeosciences 8, 311–327 (2011).
[CrossRef]

J. R. Moisan, T. A. H. Moisan, and M. A. Linkswiler, “An inverse modeling approach to estimating phytoplankton pigment concentrations from phytoplankton absorption spectra,” J. Geophys. Res. 116, C09018 (2011).
[CrossRef]

E. Torrecilla, D. Stramski, R. A. Reynolds, E. Millán-Núñez, and J. Piera, “Cluster analysis of hyperspectral optical data for discriminating phytoplankton pigment assemblages in the open ocean,” Remote Sens. Environ. 115, 2578–2593 (2011).
[CrossRef]

R. J. W. Brewin, N. J. Hardman-Mountford, S. J. Lavender, D. E. Raitsos, T. Hirata, J. Uitz, E. Devred, A. Bricaud, A. Ciotti, and B. Gentili, “An intercomparison of bio-optical techniques for detecting dominant phytoplankton size class from satellite remote sensing,” Remote Sens. Environ. 115, 325–339 (2011).
[CrossRef]

E. Organelli, C. Nuccio, C. Melillo, and L. Massi, “Relationships between phytoplankton light absorption, pigment composition and size structure in offshore areas of the Mediterranean Sea,” Adv. Oceanogr. Limnol. 2, 107–123 (2011).
[CrossRef]

R. L. Lucke, M. R. Corson, N. McGlothlin, S. Butcher, D. Wood, D. R. Korwan, R. Li, W. A. Snyder, C. O. Davis, and D. Chen, “Hyperspectral imager for the coastal ocean: instrument description and first images,” Appl. Opt. 50, 1501–1516(2011).
[CrossRef]

2010 (5)

J. C. Marty and J. Chiavérini, “Hydrological changes in the Ligurian Sea (NW Mediterranean, DYFAMED site) during 1995–2007 and biogeochemical consequences,” Biogeosciences 7, 2117–2128 (2010).
[CrossRef]

A. Bricaud, M. Babin, H. Claustre, J. Ras, and F. Tièche, “Light absorption properties and absorption budget of South East Pacific waters,” J. Geophys. Res. 115, C08009 (2010).
[CrossRef]

C. B. Mouw and J. A. Yoder, “Optical determination of phytoplankton size composition from global SeaWiFS imagery,” J. Geophys. Res. 115, C12018 (2010).
[CrossRef]

T. S. Kostadinov, D. A. Siegel, and S. Maritorena, “Global variability of phytoplankton functional types from space: assessment via the particle size distribution,” Biogeosciences 7, 3239–3257 (2010).
[CrossRef]

R. J. W. Brewin, S. Sathyendranath, T. Hirata, S. J. Lavender, R. M. Barciela, and N. J. Hardman-Mountford, “A three-component model of phytoplankton size class for the Atlantic Ocean,” Ecol. Model. 221, 1472–1483 (2010).
[CrossRef]

2009 (4)

T. S. Kostadinov, D. A. Siegel, and S. Maritorena, “Retrieval of the particle size distribution from satellite ocean color observations,” J. Geophys. Res. 114, C09015 (2009).
[CrossRef]

R. Martínez-Guijarro, I. Romero, M. Pachés, J. G. del Río, C. M. Martí, G. Gil, A. Ferrer-Riquielme, and J. Ferrer, “Determination of phytoplankton composition using absorption spectra,” Talanta 78, 814–819 (2009).
[CrossRef]

J. Uitz, H. Claustre, N. Garcia, F. B. Griffiths, J. Ras, and V. Sandroni, “A phytoplankton class-specific primary production model applied to the Kerguelen islands region (Southern Ocean),” Deep Sea Res. Part I 56, 541–560 (2009).
[CrossRef]

J. Aiken, Y. Pradhan, R. Barlow, S. Lavender, A. Poulton, P. Holligan, and N. Hardman-Mountford, “Phytoplankton pigments and functional types in the Atlantic Ocean: a decadal assessment, 1995–2005,” Deep Sea Res. Part II 56, 899–917 (2009).
[CrossRef]

2008 (10)

J. Uitz, Y. Huot, F. Bruyant, M. Babin, and H. Claustre, “Relating phytoplankton photophysiological properties to community structure on large scale,” Limnol. Oceanogr. 53, 614–630 (2008).
[CrossRef]

J. Ras, J. Uitz, and H. Claustre, “Spatial variability of phytoplankton pigment distributions in the subtropical South Pacific Ocean: comparison between in situ and modeled data,” Biogeosciences 5, 353–369 (2008).
[CrossRef]

D. Antoine, F. D’Ortenzio, S. B. Hooker, G. Bécu, B. Gentili, D. Tailliez, and A. J. Scott, “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),” J. Geophys. Res. 113, C07013 (2008).
[CrossRef]

V. Barale, J. M. Jacquet, and M. Ndiaye, “Algal blooming patterns and anomalies in the Mediterranean Sea as derived from the SeaWifs data set (1998–2003),” Remote Sens. Environ. 112, 3300–3313 (2008).
[CrossRef]

T. Hirata, J. Aiken, N. J. Hardman-Mountford, T. J. Smyth, and R. G. Barlow, “An absorption model to determine phytoplankton size classes from satellite ocean colour,” Remote Sens. Environ. 112, 3153–3159 (2008).
[CrossRef]

D. E. Raitsos, S. J. Lavender, C. D. Maravelias, J. Haralabous, A. J. Richardson, and P. C. Reid, “Identifying four phytoplankton functional types from space: an ecological approach,” Limnol. Oceanogr. 53, 605–613 (2008).
[CrossRef]

T. Platt and S. Sathyendranath, “Ecological indicators for the pelagic zone of the ocean from remote sensing,” Remote Sens. Environ. 112, 3426–3436 (2008).
[CrossRef]

J. Seppäla and K. Olli, “Multivariate analysis of phytoplankton spectral in vivo fluorescence: estimation of phytoplankton biomass during a mesocosm study in the Baltic Sea,” Mar. Ecol. Prog. Ser. 370, 69–85 (2008).
[CrossRef]

A. Nair, S. Sathyendranath, T. Platt, J. Morales, V. Stuart, M. H. Forget, E. Devred, and H. Bouman, “Remote sensing of phytoplankton functional types,” Remote Sens. Environ. 112, 3366–3375 (2008).
[CrossRef]

B. Lubac, H. Loisel, N. Guiselin, R. Astoreca, L. F. Artigas, and X. Mériaux, “Hyperspectral and multispectral ocean color inversions to detect Phaeocystis globosa blooms in coastal waters,” J. Geophys. Res. 113, C06026 (2008).
[CrossRef]

2007 (3)

C. Fuentes-Yaco, P. A. Koeller, S. Sathyendranath, and T. Platt, “Shrimp (Pandalus borealis) growth and timing of the spring phytoplankton bloom on the Newfoundland-Labrador shelf,” Fish. Ocean. 16, 116–129 (2007).
[CrossRef]

J. Aiken, J. R. Fishwick, S. Lavender, R. Barlow, G. F. Moore, H. Sessions, S. Bernard, J. Ras, and N. J. Hardman-Mountford, “Validation of MERIS reflectance and chlorophyll during the BENCAL cruise October 2002: preliminary validation of new demonstration products for phytoplankton functional types and photosynthetic parameters,” Int. J. Remote Sens. 28, 497–516 (2007).
[CrossRef]

B. H. Mevik and R. Wehrens, “The pls package: principal component and partial least squares regression in R,” J. Stat. Softw. 18, 1–24 (2007).

2006 (6)

S. E. Craig, S. E. Lohrenz, Z. Lee, K. L. Mahoney, G. J. Kirkpatrick, O. M. Schofield, and R. G. Steward, “Use of hyperspectral remote sensing reflectance for detection and assessment of the harmful alga, Karenia brevis,” Appl. Opt. 45, 5414–5425 (2006).
[CrossRef]

R. R. Hood, E. A. Laws, R. A. Armstrong, N. R. Bates, C. W. Brown, C. A. Carlson, F. Chai, S. C. Doney, P. G. Falkowski, R. A. Feely, M. A. Friedrichs, M. R. Landry, J. K. Moore, D. M. Nelson, T. L. Richardson, B. Salihoglu, M. Schartau, D. A. Toole, and J. D. Wiggert, “Pelagic functional group modeling: progress, challenges and prospects,” Deep Sea Res. Part II 53, 459–512 (2006).
[CrossRef]

T. Platt, S. Sathyendranath, and V. Stuart, “Why study biological oceanography?” Aquabiology 28, 542–557 (2006).

J. Uitz, H. Claustre, A. Morel, and S. B. Hooker, “Vertical distribution of phytoplankton communities in open ocean: an assessment based on surface chlorophyll,” J. Geophys. Res. 111, C08005 (2006).
[CrossRef]

E. Devred, S. Sathyendranath, V. Stuart, H. Maas, O. Ulloa, and T. Platt, “A two-component model of phytoplankton absorption in the open ocean: theory and applications,” J. Geophys. Res. 111, C03011 (2006).
[CrossRef]

A. M. Ciotti and A. Bricaud, “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 Brazil,” Limnol. Oceanogr. Methods 4, 237–253 (2006).
[CrossRef]

2005 (2)

C. Le Quéré, S. P. Harrison, I. C. Prentice, E. T. Buitenhuis, O. Aumont, L. Bopp, H. Claustre, L. Cotrim da Cunha, R. Geider, X. Giraud, C. Klaas, K. E. Kohfeld, L. Legendre, M. Manizza, T. Platt, R. B. Rivkin, S. Sathyendranath, J. Uitz, A. J. Watson, and D. Wolf-Gladrow, “Ecosystem dynamics based on plankton functional types for global ocean biogeochemistry models,” Glob. Chang. Biol. 11, 2016–2040 (2005).
[CrossRef]

S. Alvain, C. Moulin, Y. Dandonneau, and F. M. Bréon, “Remote sensing of phytoplankton groups in case 1 waters from global SeaWiFS imagery,” Deep Sea Res. Part I 52, 1989–2004 (2005).
[CrossRef]

2004 (2)

A. Bricaud, H. Claustre, J. Ras, and K. Oubelkheir, “Natural variability of phytoplanktonic absorption in oceanic waters: influence of the size structure of algal populations,” J. Geophys. Res. 109, C11010 (2004).
[CrossRef]

E. Bosc, A. Bricaud, and D. Antoine, “Seasonal and interannual variability in algal biomass and primary production in the Mediterranean Sea, as derived from four years of SeaWiFS observations,” Glob. Biogeochem. Cycles 18, GB1005 (2004).
[CrossRef]

2003 (3)

P. A. Stæhr and J. J. Cullen, “Detection of Karenia mikomotoi by spectral absorption signatures,” J. Plankton Res. 25, 1237–1249 (2003).
[CrossRef]

T. Platt, C. Fuentes-Yaco, and K. T. Frank, “Spring algal bloom and larval fish survival,” Nature 423, 398–399 (2003).
[CrossRef]

O. Aumont, E. Meier-Reimer, S. Blain, and P. Monfray, “An ecosystem model of the global ocean including Fe, Si, P colimitations,” Glob. Biogeochem. Cycles 17, 23–29 (2003).
[CrossRef]

2002 (3)

A. M. Ciotti, M. R. Lewis, and J. J. Cullen, “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 (2002).
[CrossRef]

L. Moberg, B. Karlberg, K. Sørensen, and T. Källqvist, “Assessment of phytoplankton class abundance using absorption spectra and chemometrics,” Talanta 56, 153–160 (2002).
[CrossRef]

J. C. Marty, J. Chiavérini, M. D. Pizay, and B. Avril, “Seasonal and interannual dynamics of nutrients and phytoplankton pigments in the western Mediterranean Sea at the DYFAMED time-series station (1991–1999),” Deep Sea Res. Part II 49, 1965–1985 (2002).
[CrossRef]

2001 (2)

A. Morel and S. Maritorena, “Bio-optical properties of oceanic waters: a reappraisal,” J. Geophys. Res. 106, 7163–7180 (2001).
[CrossRef]

F. Vidussi, H. Claustre, B. B. Manca, A. Luchetta, and J. C. Marty, “Phytoplankton pigment distribution in relation to upper thermocline circulation in the eastern Mediterranean Sea during winter,” J. Geophys. Res. 106, 19939–19956(2001).
[CrossRef]

2000 (1)

L. Moberg, B. Karlberg, S. Blomqvist, and U. Larsson, “Comparison between a new application of multivariate regression and current spectroscopy methods for the determination of chlorophylls and their corresponding pheopigments,” Anal. Chim. Acta 411, 137–143 (2000).
[CrossRef]

1999 (1)

J. A. Raven and P. G. Falkowski, “Ocean sink for atmospheric CO2,” Plant Cell Environ. 22, 741–755 (1999).
[CrossRef]

1998 (2)

F. Tsai and W. Philpot, “Derivative analysis of hyperspectral data,” Remote Sens. Environ. 66, 41–51 (1998).
[CrossRef]

A. Bricaud, A. Morel, M. Babin, K. Allali, and H. Claustre, “Variations of light absorption by suspended particles with chlorophyll a concentration in oceanic (case 1) waters: analysis and implications for bio-optical models,” J. Geophys. Res. 103, 31033–31044 (1998).
[CrossRef]

1997 (2)

K. Allali, A. Bricaud, and H. Claustre, “Spatial variations in the chlorophyll-specific absorption coefficients of phytoplankton and photosynthetically active pigments in the equatorial Pacific,” J. Geophys. Res. 102, 12413–12423 (1997).
[CrossRef]

D. F. Millie, O. M. Schofield, G. J. Kirkpatrick, G. Johnsen, P. A. Tester, and B. T. Vinyard, “Detection of harmful algal blooms using photopigments and absorption signatures: a case study of the Florida red tide dinoflagellate, Gymnodinium breve,” Limnol. Oceanogr. 42, 1240–1251 (1997).
[CrossRef]

1996 (1)

F. Vidussi, H. Claustre, J. Bustillos-Guzmàn, C. Cailliau, and J. C. Marty, “Determination of chlorophylls and carotenoids of marine phytoplankton: separation of chlorophyll a from divinyl-chlorophyll a and zeaxanthin from lutein,” J. Plankton Res. 18, 2377–2382 (1996).
[CrossRef]

1995 (2)

K. Allali, A. Bricaud, M. Babin, A. Morel, and P. Chang, “A new method for measuring spectral absorption coefficients of marine particles,” Limnol. Oceanogr. 40, 1526–1532 (1995).
[CrossRef]

H. Claustre and J. C. Marty, “Specific phytoplankton biomasses and their relation to primary production in the tropical North Atlantic,” Deep Sea Res. Part I 42, 1475–1493 (1995).
[CrossRef]

1991 (1)

N. Hoepffner and S. Sathyendranath, “Effect of pigment composition on absorption properties of phytoplankton,” Mar. Ecol. Prog. Ser. 73, 11–23 (1991).
[CrossRef]

1990 (1)

A. Bricaud and D. Stramski, “Spectral absorption coefficients of living phytoplankton and nonalgal biogenous matter: a comparison between Peru upwelling area and Sargasso Sea,” Limnol. Oceanogr. 35, 562–582 (1990).
[CrossRef]

1989 (1)

R. Bidigare, J. Morrow, and D. Kiefer, “Derivative analysis of spectra absorption by photosynthetic pigments in the western Sargasso Sea,” J. Mar. Res. 47, 323–341 (1989).
[CrossRef]

1987 (1)

S. Sathyendranath, L. Lazzara, and L. Prieur, “Variations in the spectral values of specific absorption of phytoplankton,” Limnol. Oceanogr. 32, 403–415 (1987).
[CrossRef]

1986 (1)

P. Geladi and B. R. Kowalski, “Partial least squares regression: a tutorial,” Anal. Chim. Acta 185, 1–17 (1986).
[CrossRef]

1985 (1)

M. Kishino, M. Takahashi, N. Okami, and S. Ichimura, “Estimation of the spectral absorption coefficients of phytoplankton in the sea,” Bull. Mar. Sci. 37, 634–642 (1985).

1981 (1)

A. Morel and A. Bricaud, “Theoretical results concerning light absorption in a discrete medium, and application to specific absorption of phytoplankton,” Deep Sea Res. Part I 28, 1375–1393 (1981).
[CrossRef]

1978 (1)

J. M. Sieburth, V. Smetacek, and J. Lenz, “Pelagic ecosystem structure: heterotrophic compartments of the plankton and their relationship to plankton size fractions,” Limnol. Oceanogr. 23, 1256–1263 (1978).
[CrossRef]

1977 (1)

A. Morel and L. Prieur, “Analysis of variations in ocean color,” Limnol. Oceanogr. 22, 709–722 (1977).
[CrossRef]

1975 (1)

Adams, D.

D. Antoine, M. Chami, H. Claustre, F. D’Ortenzio, A. Morel, G. Bécu, B. Gentili, F. Louis, J. Ras, E. Roussier, A. J. Scott, D. Tailliez, S. B. Hooker, P. Guevel, J. F. Desté, C. Dempsey, and D. Adams, “BOUSSOLE: a joint CNRS-INSU, ESA, CNES and NASA ocean color calibration and validation activity,” NASA Technical Memorandum No. 2006-214147 (2006).

Aiken, J.

T. Hirata, N. J. Hardman-Mountford, R. J. W. Brewin, J. Aiken, R. Barlow, K. Suzuki, T. Isada, E. Howell, T. Hashioka, M. Noguchi-Aita, and Y. Yamanaka, “Synoptic relationships between surface chlorophyll-a and diagnostic pigments specific to phytoplankton functional types,” Biogeosciences 8, 311–327 (2011).
[CrossRef]

J. Aiken, Y. Pradhan, R. Barlow, S. Lavender, A. Poulton, P. Holligan, and N. Hardman-Mountford, “Phytoplankton pigments and functional types in the Atlantic Ocean: a decadal assessment, 1995–2005,” Deep Sea Res. Part II 56, 899–917 (2009).
[CrossRef]

T. Hirata, J. Aiken, N. J. Hardman-Mountford, T. J. Smyth, and R. G. Barlow, “An absorption model to determine phytoplankton size classes from satellite ocean colour,” Remote Sens. Environ. 112, 3153–3159 (2008).
[CrossRef]

J. Aiken, J. R. Fishwick, S. Lavender, R. Barlow, G. F. Moore, H. Sessions, S. Bernard, J. Ras, and N. J. Hardman-Mountford, “Validation of MERIS reflectance and chlorophyll during the BENCAL cruise October 2002: preliminary validation of new demonstration products for phytoplankton functional types and photosynthetic parameters,” Int. J. Remote Sens. 28, 497–516 (2007).
[CrossRef]

Allali, K.

A. Bricaud, A. Morel, M. Babin, K. Allali, and H. Claustre, “Variations of light absorption by suspended particles with chlorophyll a concentration in oceanic (case 1) waters: analysis and implications for bio-optical models,” J. Geophys. Res. 103, 31033–31044 (1998).
[CrossRef]

K. Allali, A. Bricaud, and H. Claustre, “Spatial variations in the chlorophyll-specific absorption coefficients of phytoplankton and photosynthetically active pigments in the equatorial Pacific,” J. Geophys. Res. 102, 12413–12423 (1997).
[CrossRef]

K. Allali, A. Bricaud, M. Babin, A. Morel, and P. Chang, “A new method for measuring spectral absorption coefficients of marine particles,” Limnol. Oceanogr. 40, 1526–1532 (1995).
[CrossRef]

Alvain, S.

S. Alvain, C. Moulin, Y. Dandonneau, and F. M. Bréon, “Remote sensing of phytoplankton groups in case 1 waters from global SeaWiFS imagery,” Deep Sea Res. Part I 52, 1989–2004 (2005).
[CrossRef]

Antoine, D.

D. Antoine, F. D’Ortenzio, S. B. Hooker, G. Bécu, B. Gentili, D. Tailliez, and A. J. Scott, “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),” J. Geophys. Res. 113, C07013 (2008).
[CrossRef]

E. Bosc, A. Bricaud, and D. Antoine, “Seasonal and interannual variability in algal biomass and primary production in the Mediterranean Sea, as derived from four years of SeaWiFS observations,” Glob. Biogeochem. Cycles 18, GB1005 (2004).
[CrossRef]

D. Antoine, M. Chami, H. Claustre, F. D’Ortenzio, A. Morel, G. Bécu, B. Gentili, F. Louis, J. Ras, E. Roussier, A. J. Scott, D. Tailliez, S. B. Hooker, P. Guevel, J. F. Desté, C. Dempsey, and D. Adams, “BOUSSOLE: a joint CNRS-INSU, ESA, CNES and NASA ocean color calibration and validation activity,” NASA Technical Memorandum No. 2006-214147 (2006).

Armstrong, R. A.

R. R. Hood, E. A. Laws, R. A. Armstrong, N. R. Bates, C. W. Brown, C. A. Carlson, F. Chai, S. C. Doney, P. G. Falkowski, R. A. Feely, M. A. Friedrichs, M. R. Landry, J. K. Moore, D. M. Nelson, T. L. Richardson, B. Salihoglu, M. Schartau, D. A. Toole, and J. D. Wiggert, “Pelagic functional group modeling: progress, challenges and prospects,” Deep Sea Res. Part II 53, 459–512 (2006).
[CrossRef]

Artigas, L. F.

B. Lubac, H. Loisel, N. Guiselin, R. Astoreca, L. F. Artigas, and X. Mériaux, “Hyperspectral and multispectral ocean color inversions to detect Phaeocystis globosa blooms in coastal waters,” J. Geophys. Res. 113, C06026 (2008).
[CrossRef]

Astoreca, R.

B. Lubac, H. Loisel, N. Guiselin, R. Astoreca, L. F. Artigas, and X. Mériaux, “Hyperspectral and multispectral ocean color inversions to detect Phaeocystis globosa blooms in coastal waters,” J. Geophys. Res. 113, C06026 (2008).
[CrossRef]

Aumont, O.

C. Le Quéré, S. P. Harrison, I. C. Prentice, E. T. Buitenhuis, O. Aumont, L. Bopp, H. Claustre, L. Cotrim da Cunha, R. Geider, X. Giraud, C. Klaas, K. E. Kohfeld, L. Legendre, M. Manizza, T. Platt, R. B. Rivkin, S. Sathyendranath, J. Uitz, A. J. Watson, and D. Wolf-Gladrow, “Ecosystem dynamics based on plankton functional types for global ocean biogeochemistry models,” Glob. Chang. Biol. 11, 2016–2040 (2005).
[CrossRef]

O. Aumont, E. Meier-Reimer, S. Blain, and P. Monfray, “An ecosystem model of the global ocean including Fe, Si, P colimitations,” Glob. Biogeochem. Cycles 17, 23–29 (2003).
[CrossRef]

Avril, B.

J. C. Marty, J. Chiavérini, M. D. Pizay, and B. Avril, “Seasonal and interannual dynamics of nutrients and phytoplankton pigments in the western Mediterranean Sea at the DYFAMED time-series station (1991–1999),” Deep Sea Res. Part II 49, 1965–1985 (2002).
[CrossRef]

Babin, M.

A. Bricaud, M. Babin, H. Claustre, J. Ras, and F. Tièche, “Light absorption properties and absorption budget of South East Pacific waters,” J. Geophys. Res. 115, C08009 (2010).
[CrossRef]

J. Uitz, Y. Huot, F. Bruyant, M. Babin, and H. Claustre, “Relating phytoplankton photophysiological properties to community structure on large scale,” Limnol. Oceanogr. 53, 614–630 (2008).
[CrossRef]

A. Bricaud, A. Morel, M. Babin, K. Allali, and H. Claustre, “Variations of light absorption by suspended particles with chlorophyll a concentration in oceanic (case 1) waters: analysis and implications for bio-optical models,” J. Geophys. Res. 103, 31033–31044 (1998).
[CrossRef]

K. Allali, A. Bricaud, M. Babin, A. Morel, and P. Chang, “A new method for measuring spectral absorption coefficients of marine particles,” Limnol. Oceanogr. 40, 1526–1532 (1995).
[CrossRef]

Barale, V.

V. Barale, J. M. Jacquet, and M. Ndiaye, “Algal blooming patterns and anomalies in the Mediterranean Sea as derived from the SeaWifs data set (1998–2003),” Remote Sens. Environ. 112, 3300–3313 (2008).
[CrossRef]

Barciela, R. M.

R. J. W. Brewin, S. Sathyendranath, T. Hirata, S. J. Lavender, R. M. Barciela, and N. J. Hardman-Mountford, “A three-component model of phytoplankton size class for the Atlantic Ocean,” Ecol. Model. 221, 1472–1483 (2010).
[CrossRef]

Barlow, R.

T. Hirata, N. J. Hardman-Mountford, R. J. W. Brewin, J. Aiken, R. Barlow, K. Suzuki, T. Isada, E. Howell, T. Hashioka, M. Noguchi-Aita, and Y. Yamanaka, “Synoptic relationships between surface chlorophyll-a and diagnostic pigments specific to phytoplankton functional types,” Biogeosciences 8, 311–327 (2011).
[CrossRef]

J. Aiken, Y. Pradhan, R. Barlow, S. Lavender, A. Poulton, P. Holligan, and N. Hardman-Mountford, “Phytoplankton pigments and functional types in the Atlantic Ocean: a decadal assessment, 1995–2005,” Deep Sea Res. Part II 56, 899–917 (2009).
[CrossRef]

J. Aiken, J. R. Fishwick, S. Lavender, R. Barlow, G. F. Moore, H. Sessions, S. Bernard, J. Ras, and N. J. Hardman-Mountford, “Validation of MERIS reflectance and chlorophyll during the BENCAL cruise October 2002: preliminary validation of new demonstration products for phytoplankton functional types and photosynthetic parameters,” Int. J. Remote Sens. 28, 497–516 (2007).
[CrossRef]

Barlow, R. G.

T. Hirata, J. Aiken, N. J. Hardman-Mountford, T. J. Smyth, and R. G. Barlow, “An absorption model to determine phytoplankton size classes from satellite ocean colour,” Remote Sens. Environ. 112, 3153–3159 (2008).
[CrossRef]

Bates, N. R.

R. R. Hood, E. A. Laws, R. A. Armstrong, N. R. Bates, C. W. Brown, C. A. Carlson, F. Chai, S. C. Doney, P. G. Falkowski, R. A. Feely, M. A. Friedrichs, M. R. Landry, J. K. Moore, D. M. Nelson, T. L. Richardson, B. Salihoglu, M. Schartau, D. A. Toole, and J. D. Wiggert, “Pelagic functional group modeling: progress, challenges and prospects,” Deep Sea Res. Part II 53, 459–512 (2006).
[CrossRef]

Bécu, G.

D. Antoine, F. D’Ortenzio, S. B. Hooker, G. Bécu, B. Gentili, D. Tailliez, and A. J. Scott, “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),” J. Geophys. Res. 113, C07013 (2008).
[CrossRef]

D. Antoine, M. Chami, H. Claustre, F. D’Ortenzio, A. Morel, G. Bécu, B. Gentili, F. Louis, J. Ras, E. Roussier, A. J. Scott, D. Tailliez, S. B. Hooker, P. Guevel, J. F. Desté, C. Dempsey, and D. Adams, “BOUSSOLE: a joint CNRS-INSU, ESA, CNES and NASA ocean color calibration and validation activity,” NASA Technical Memorandum No. 2006-214147 (2006).

Bernard, S.

J. Aiken, J. R. Fishwick, S. Lavender, R. Barlow, G. F. Moore, H. Sessions, S. Bernard, J. Ras, and N. J. Hardman-Mountford, “Validation of MERIS reflectance and chlorophyll during the BENCAL cruise October 2002: preliminary validation of new demonstration products for phytoplankton functional types and photosynthetic parameters,” Int. J. Remote Sens. 28, 497–516 (2007).
[CrossRef]

Bidigare, R.

R. Bidigare, J. Morrow, and D. Kiefer, “Derivative analysis of spectra absorption by photosynthetic pigments in the western Sargasso Sea,” J. Mar. Res. 47, 323–341 (1989).
[CrossRef]

Blain, S.

O. Aumont, E. Meier-Reimer, S. Blain, and P. Monfray, “An ecosystem model of the global ocean including Fe, Si, P colimitations,” Glob. Biogeochem. Cycles 17, 23–29 (2003).
[CrossRef]

Blomqvist, S.

L. Moberg, B. Karlberg, S. Blomqvist, and U. Larsson, “Comparison between a new application of multivariate regression and current spectroscopy methods for the determination of chlorophylls and their corresponding pheopigments,” Anal. Chim. Acta 411, 137–143 (2000).
[CrossRef]

Bopp, L.

C. Le Quéré, S. P. Harrison, I. C. Prentice, E. T. Buitenhuis, O. Aumont, L. Bopp, H. Claustre, L. Cotrim da Cunha, R. Geider, X. Giraud, C. Klaas, K. E. Kohfeld, L. Legendre, M. Manizza, T. Platt, R. B. Rivkin, S. Sathyendranath, J. Uitz, A. J. Watson, and D. Wolf-Gladrow, “Ecosystem dynamics based on plankton functional types for global ocean biogeochemistry models,” Glob. Chang. Biol. 11, 2016–2040 (2005).
[CrossRef]

Bosc, E.

E. Bosc, A. Bricaud, and D. Antoine, “Seasonal and interannual variability in algal biomass and primary production in the Mediterranean Sea, as derived from four years of SeaWiFS observations,” Glob. Biogeochem. Cycles 18, GB1005 (2004).
[CrossRef]

Bouman, H.

A. Nair, S. Sathyendranath, T. Platt, J. Morales, V. Stuart, M. H. Forget, E. Devred, and H. Bouman, “Remote sensing of phytoplankton functional types,” Remote Sens. Environ. 112, 3366–3375 (2008).
[CrossRef]

Bréon, F. M.

S. Alvain, C. Moulin, Y. Dandonneau, and F. M. Bréon, “Remote sensing of phytoplankton groups in case 1 waters from global SeaWiFS imagery,” Deep Sea Res. Part I 52, 1989–2004 (2005).
[CrossRef]

Brewin, R. J. W.

T. Hirata, N. J. Hardman-Mountford, R. J. W. Brewin, J. Aiken, R. Barlow, K. Suzuki, T. Isada, E. Howell, T. Hashioka, M. Noguchi-Aita, and Y. Yamanaka, “Synoptic relationships between surface chlorophyll-a and diagnostic pigments specific to phytoplankton functional types,” Biogeosciences 8, 311–327 (2011).
[CrossRef]

R. J. W. Brewin, N. J. Hardman-Mountford, S. J. Lavender, D. E. Raitsos, T. Hirata, J. Uitz, E. Devred, A. Bricaud, A. Ciotti, and B. Gentili, “An intercomparison of bio-optical techniques for detecting dominant phytoplankton size class from satellite remote sensing,” Remote Sens. Environ. 115, 325–339 (2011).
[CrossRef]

R. J. W. Brewin, S. Sathyendranath, T. Hirata, S. J. Lavender, R. M. Barciela, and N. J. Hardman-Mountford, “A three-component model of phytoplankton size class for the Atlantic Ocean,” Ecol. Model. 221, 1472–1483 (2010).
[CrossRef]

Bricaud, A.

R. J. W. Brewin, N. J. Hardman-Mountford, S. J. Lavender, D. E. Raitsos, T. Hirata, J. Uitz, E. Devred, A. Bricaud, A. Ciotti, and B. Gentili, “An intercomparison of bio-optical techniques for detecting dominant phytoplankton size class from satellite remote sensing,” Remote Sens. Environ. 115, 325–339 (2011).
[CrossRef]

A. Bricaud, M. Babin, H. Claustre, J. Ras, and F. Tièche, “Light absorption properties and absorption budget of South East Pacific waters,” J. Geophys. Res. 115, C08009 (2010).
[CrossRef]

A. M. Ciotti and A. Bricaud, “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 Brazil,” Limnol. Oceanogr. Methods 4, 237–253 (2006).
[CrossRef]

A. Bricaud, H. Claustre, J. Ras, and K. Oubelkheir, “Natural variability of phytoplanktonic absorption in oceanic waters: influence of the size structure of algal populations,” J. Geophys. Res. 109, C11010 (2004).
[CrossRef]

E. Bosc, A. Bricaud, and D. Antoine, “Seasonal and interannual variability in algal biomass and primary production in the Mediterranean Sea, as derived from four years of SeaWiFS observations,” Glob. Biogeochem. Cycles 18, GB1005 (2004).
[CrossRef]

A. Bricaud, A. Morel, M. Babin, K. Allali, and H. Claustre, “Variations of light absorption by suspended particles with chlorophyll a concentration in oceanic (case 1) waters: analysis and implications for bio-optical models,” J. Geophys. Res. 103, 31033–31044 (1998).
[CrossRef]

K. Allali, A. Bricaud, and H. Claustre, “Spatial variations in the chlorophyll-specific absorption coefficients of phytoplankton and photosynthetically active pigments in the equatorial Pacific,” J. Geophys. Res. 102, 12413–12423 (1997).
[CrossRef]

K. Allali, A. Bricaud, M. Babin, A. Morel, and P. Chang, “A new method for measuring spectral absorption coefficients of marine particles,” Limnol. Oceanogr. 40, 1526–1532 (1995).
[CrossRef]

A. Bricaud and D. Stramski, “Spectral absorption coefficients of living phytoplankton and nonalgal biogenous matter: a comparison between Peru upwelling area and Sargasso Sea,” Limnol. Oceanogr. 35, 562–582 (1990).
[CrossRef]

A. Morel and A. Bricaud, “Theoretical results concerning light absorption in a discrete medium, and application to specific absorption of phytoplankton,” Deep Sea Res. Part I 28, 1375–1393 (1981).
[CrossRef]

Brown, C. W.

R. R. Hood, E. A. Laws, R. A. Armstrong, N. R. Bates, C. W. Brown, C. A. Carlson, F. Chai, S. C. Doney, P. G. Falkowski, R. A. Feely, M. A. Friedrichs, M. R. Landry, J. K. Moore, D. M. Nelson, T. L. Richardson, B. Salihoglu, M. Schartau, D. A. Toole, and J. D. Wiggert, “Pelagic functional group modeling: progress, challenges and prospects,” Deep Sea Res. Part II 53, 459–512 (2006).
[CrossRef]

Bruyant, F.

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M. Kishino, M. Takahashi, N. Okami, and S. Ichimura, “Estimation of the spectral absorption coefficients of phytoplankton in the sea,” Bull. Mar. Sci. 37, 634–642 (1985).

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D. F. Millie, O. M. Schofield, G. J. Kirkpatrick, G. Johnsen, P. A. Tester, and B. T. Vinyard, “Detection of harmful algal blooms using photopigments and absorption signatures: a case study of the Florida red tide dinoflagellate, Gymnodinium breve,” Limnol. Oceanogr. 42, 1240–1251 (1997).
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A. Bricaud, M. Babin, H. Claustre, J. Ras, and F. Tièche, “Light absorption properties and absorption budget of South East Pacific waters,” J. Geophys. Res. 115, C08009 (2010).
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Toole, D. A.

R. R. Hood, E. A. Laws, R. A. Armstrong, N. R. Bates, C. W. Brown, C. A. Carlson, F. Chai, S. C. Doney, P. G. Falkowski, R. A. Feely, M. A. Friedrichs, M. R. Landry, J. K. Moore, D. M. Nelson, T. L. Richardson, B. Salihoglu, M. Schartau, D. A. Toole, and J. D. Wiggert, “Pelagic functional group modeling: progress, challenges and prospects,” Deep Sea Res. Part II 53, 459–512 (2006).
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E. Torrecilla, D. Stramski, R. A. Reynolds, E. Millán-Núñez, and J. Piera, “Cluster analysis of hyperspectral optical data for discriminating phytoplankton pigment assemblages in the open ocean,” Remote Sens. Environ. 115, 2578–2593 (2011).
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Tsai, F.

F. Tsai and W. Philpot, “Derivative analysis of hyperspectral data,” Remote Sens. Environ. 66, 41–51 (1998).
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R. J. W. Brewin, N. J. Hardman-Mountford, S. J. Lavender, D. E. Raitsos, T. Hirata, J. Uitz, E. Devred, A. Bricaud, A. Ciotti, and B. Gentili, “An intercomparison of bio-optical techniques for detecting dominant phytoplankton size class from satellite remote sensing,” Remote Sens. Environ. 115, 325–339 (2011).
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J. Uitz, H. Claustre, N. Garcia, F. B. Griffiths, J. Ras, and V. Sandroni, “A phytoplankton class-specific primary production model applied to the Kerguelen islands region (Southern Ocean),” Deep Sea Res. Part I 56, 541–560 (2009).
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J. Ras, J. Uitz, and H. Claustre, “Spatial variability of phytoplankton pigment distributions in the subtropical South Pacific Ocean: comparison between in situ and modeled data,” Biogeosciences 5, 353–369 (2008).
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J. Uitz, Y. Huot, F. Bruyant, M. Babin, and H. Claustre, “Relating phytoplankton photophysiological properties to community structure on large scale,” Limnol. Oceanogr. 53, 614–630 (2008).
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J. Uitz, H. Claustre, A. Morel, and S. B. Hooker, “Vertical distribution of phytoplankton communities in open ocean: an assessment based on surface chlorophyll,” J. Geophys. Res. 111, C08005 (2006).
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C. Le Quéré, S. P. Harrison, I. C. Prentice, E. T. Buitenhuis, O. Aumont, L. Bopp, H. Claustre, L. Cotrim da Cunha, R. Geider, X. Giraud, C. Klaas, K. E. Kohfeld, L. Legendre, M. Manizza, T. Platt, R. B. Rivkin, S. Sathyendranath, J. Uitz, A. J. Watson, and D. Wolf-Gladrow, “Ecosystem dynamics based on plankton functional types for global ocean biogeochemistry models,” Glob. Chang. Biol. 11, 2016–2040 (2005).
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E. Devred, S. Sathyendranath, V. Stuart, H. Maas, O. Ulloa, and T. Platt, “A two-component model of phytoplankton absorption in the open ocean: theory and applications,” J. Geophys. Res. 111, C03011 (2006).
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F. Vidussi, H. Claustre, B. B. Manca, A. Luchetta, and J. C. Marty, “Phytoplankton pigment distribution in relation to upper thermocline circulation in the eastern Mediterranean Sea during winter,” J. Geophys. Res. 106, 19939–19956(2001).
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F. Vidussi, H. Claustre, J. Bustillos-Guzmàn, C. Cailliau, and J. C. Marty, “Determination of chlorophylls and carotenoids of marine phytoplankton: separation of chlorophyll a from divinyl-chlorophyll a and zeaxanthin from lutein,” J. Plankton Res. 18, 2377–2382 (1996).
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D. F. Millie, O. M. Schofield, G. J. Kirkpatrick, G. Johnsen, P. A. Tester, and B. T. Vinyard, “Detection of harmful algal blooms using photopigments and absorption signatures: a case study of the Florida red tide dinoflagellate, Gymnodinium breve,” Limnol. Oceanogr. 42, 1240–1251 (1997).
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C. Le Quéré, S. P. Harrison, I. C. Prentice, E. T. Buitenhuis, O. Aumont, L. Bopp, H. Claustre, L. Cotrim da Cunha, R. Geider, X. Giraud, C. Klaas, K. E. Kohfeld, L. Legendre, M. Manizza, T. Platt, R. B. Rivkin, S. Sathyendranath, J. Uitz, A. J. Watson, and D. Wolf-Gladrow, “Ecosystem dynamics based on plankton functional types for global ocean biogeochemistry models,” Glob. Chang. Biol. 11, 2016–2040 (2005).
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R. R. Hood, E. A. Laws, R. A. Armstrong, N. R. Bates, C. W. Brown, C. A. Carlson, F. Chai, S. C. Doney, P. G. Falkowski, R. A. Feely, M. A. Friedrichs, M. R. Landry, J. K. Moore, D. M. Nelson, T. L. Richardson, B. Salihoglu, M. Schartau, D. A. Toole, and J. D. Wiggert, “Pelagic functional group modeling: progress, challenges and prospects,” Deep Sea Res. Part II 53, 459–512 (2006).
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C. Le Quéré, S. P. Harrison, I. C. Prentice, E. T. Buitenhuis, O. Aumont, L. Bopp, H. Claustre, L. Cotrim da Cunha, R. Geider, X. Giraud, C. Klaas, K. E. Kohfeld, L. Legendre, M. Manizza, T. Platt, R. B. Rivkin, S. Sathyendranath, J. Uitz, A. J. Watson, and D. Wolf-Gladrow, “Ecosystem dynamics based on plankton functional types for global ocean biogeochemistry models,” Glob. Chang. Biol. 11, 2016–2040 (2005).
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D. Antoine, F. D’Ortenzio, S. B. Hooker, G. Bécu, B. Gentili, D. Tailliez, and A. J. Scott, “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),” J. Geophys. Res. 113, C07013 (2008).
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Figures (11)

Fig. 1.
Fig. 1.

Map of the stations where data were collected. Stations are displayed according to their geographical distribution ( square = BOUSSOLE site , circle = Mediterranean Sea , diamond = Atlantic Ocean , triangle = Pacific Ocean ) and to the oceanographic cruise during which they were visited. The map is drawn by the Ocean Data View software (Schlitzer, R., Ocean Data View, http://odv.awi.de, 2012).

Fig. 2.
Fig. 2.

Example of a smoothed phytoplankton absorption spectrum (solid curve) of the BOUSSOLE time series and its fourth-derivative (dashed curve).

Fig. 3.
Fig. 3.

Flowchart displaying distribution and use of HPLC pigment and spectral light absorption data for subsequent training and test of the PLS regression method.

Fig. 4.
Fig. 4.

Variations of the size index (SI) derived from the relative contributions of micro, nano, and picophytoplankton [Eqs. (1)–(4)] as a function of [Tchl a ] for BOUSSOLE, compared to various areas.

Fig. 5.
Fig. 5.

Cross-validated LOO predictions (in mg m 3 , n = 239 ) of the five variables ([Tchl a ], DP, Micro, Nano, and Pico) as derived by the PLS models trained using HPLC pigment measurements and a p ( λ ) (left column) or a phy ( λ ) (right column) values included in the MedCAL data set (see Subsection 2.D for details) versus measured concentrations. The solid lines indicate the 1 1 ratio, the dashed lines show linear regressions between predicted and measured concentrations.

Fig. 6.
Fig. 6.

Relationships between the predicted and measured concentrations (in mg m 3 ) of the five variables (Tchl a , DP, Micro, Nano, and Pico) for the BOUSSOLE data set. A few predicted negative values are disregarded. Pigment concentrations are predicted by the PLS models trained using HPLC pigment measurements and a p ( λ ) (left column) or a phy ( λ ) values (right column) included in the MedCAL data set. The 1 1 ratio is shown as a solid line.

Fig. 7.
Fig. 7.

Cross-validated predictions (in mg m 3 ; n = 716 ) of the 5 variables ([Tchl a ], DP, Micro, Nano, and Pico) versus measured concentrations. LOO predictions result from the PLS models trained with HPLC pigment concentrations and a phy ( λ ) values included in the GLOCAL data set (see Subsection 2.D for details). The solid lines indicate the 1 1 ratio, the dashed lines show linear regressions between predicted and measured concentrations.

Fig. 8.
Fig. 8.

Comparison between the predicted and measured concentrations (in mg m 3 ) of the five variables (Tchl a , DP, Micro, Nano, and Pico) for the BOUSSOLE data set. A few predicted negative values are disregarded. Predicted concentrations are obtained by the PLS models trained using HPLC pigment measurements and a phy ( λ ) values included in the GLOCAL data set. The 1 1 ratio is shown as a solid line.

Fig. 9.
Fig. 9.

Comparison between fourth-derivatives of phytoplankton absorption spectra sampled at the BOUSSOLE site and those from: (a), (b) the Mediterranean Sea; (c), (d) the Atlantic Ocean; (e), (f) the Pacific Ocean. For each area, the averages of all samples with Tchl a 0.1 mg m 3 (left column) and of all samples with 0.1 < Tchl a 0.5 mg m 3 (right column) are reported. n B , n M , n A , and n P are the number of spectra used to calculate the average spectrum for each region (BOUSSOLE, the Mediterranean Sea, the Atlantic Ocean, and the Pacific Ocean, respectively).

Fig. 10.
Fig. 10.

Entire BOUSSOLE time series (January 2003–May 2011) of pigment concentrations as derived from HPLC pigment measurements (blue line) and from PLS models trained using a p ( λ ) (red line) or a phy ( λ ) (green line) values included in the MedCAL data set. A few predicted negative values are replaced by zero. The plot shows the time series for: (a) [Tchl a ], (b) DP, (c) Micro, (d) Nano, and (e) Pico.

Fig. 11.
Fig. 11.

Annual cycle of [Tchl a ], DP, Micro, Nano, and Pico concentrations, over the period January 2003–May 2011, as derived from: HPLC pigment measurements (left column) and a p ( λ ) -PLS models trained with the MedCAL data set (right column). A few predicted negative values are replaced by zero.

Tables (5)

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Table 1. Cruises, Location, Sampling Period, Number of Samples ( n ) and [Tchl a ] range for the First Optical Depth, for the Data Used to Train Models

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Table 2. PLS Parameters of a p ( λ ) -and a phy ( λ ) -Models Trained Using HPLC Pigment Measurements and Absorption Spectral Values Included in the MedCAL Data Set ( n = 239 ), from Left to Right: Number of Components ( N ), RMSEP ( mg m 3 ), Explained Variance (%) for Independent [ r 2 X (%)] and Dependent [ r 2 Y (%)] Variablesa

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Table 3. Statistical Parameters of Comparison between the HPLC Measured and PLS Pigment Concentrations Predicted by the a p ( λ ) - and a phy ( λ ) -Models Trained with the MedCAL Data Set and Tested on the BOUSSOLE Time Series ( n = 484 )a

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Table 4. PLS Parameters of a phy ( λ ) -Models Trained Using HPLC Pigment Measurements and Absorption Spectral Values Included in the GLOCAL Data Set ( n = 716 ), from Left to Right: Number of Components ( N ), RMSEP ( mg m 3 ), Explained Variance (%) for Independent [ r 2 X (%)] and Dependent [ r 2 Y (%)] Variablesa

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Table 5. Statistical Parameters of Comparison between the HPLC Measured and PLS Pigment Concentrations Predicted by the a phy ( λ ) -Models Trained with the GLOCAL Data Set and Tested on the BOUSSOLE Time Series ( n = 484 )a

Equations (6)

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% microphytoplankton = 100 ( 1.41 [ Fuco ] + 1.41 [ Perid ] ) / DP ,
% nanoph ytopla nkton = 100 ( 0.60 [ Allo ] + 0.35 [ 19 BF ] + 1.27 [ 19 HF ] ) / DP ,
% picophytoplankton = 100 ( 0.86 [ Zea ] + 1.01 [ Chl b + D V C hl b ] ) / DP ,
SI = ( 1 ( % picophytoplankton ) + 5 ( % nanophytoplankton ) + 50 ( % microphytoplankton ) ) / 100 ,
RMSEP = ( i = 1 n ( x i x ¯ i ) 2 / n ) 1 / 2
BIAS = i = 1 n ( x ¯ i x i ) / n

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