The fate of photons absorbed by phytoplankton in the global ocean

Abstract

Using solar energy suboptimally
How efficient are phytoplankton at converting sunlight into the products of photosynthesis? The two other pathways that that absorbed energy can take are emission back to the environment by fluorescence or conversion to heat. Lin et al. measured phytoplankton fluorescence lifetimes in the laboratory and combined them with satellite measurements of variable chlorophyll fluorescence. Combined, they determined the quantum yields of photochemistry and fluorescence in four ocean basins. Approximately 60% of absorbed solar energy is converted to heat, a figure 50% higher than has been determined for conditions of optimal growth.
Science , this issue p. 264

Full text

REPORTS
Cite as: H. Lin et al., Science
10.1126/science.aab2213 (2016).
For several decades, chlorophyll concentrations based on
remotely sensed variations in ocean color have been used to
derive global phytoplankton productivity (1, 2). Primary
productivity models implicitly include physiological
processes, but their explicit representation has, thus far,
been elusive (3, 4). Variable chlorophyll fluorescence is the
most sensitive, non-destructive signal detectable in the
upper ocean that reflects instantaneous phytoplankton
photophysiology (5–7). Over the past two decades, many
hundreds of thousands of discrete in situ measurements of
variable fluorescence have been made using ship-based
active fluorometers. These instruments, primarily designed
to quantify the quantum yield of photochemistry (Fv/Fm) in
photosystem II (PSII), the reaction center responsible for
splitting water, have been used to follow phytoplankton
photophysiology in response to iron fertilization (8), across
eddies (9, 10) along meridional transects (11), and many
other phenomena (12, 13). Although active variable
fluorescence measurements have become almost routine, by
themselves, they do not allow closure on the fate of light
absorbed by phytoplankton. Here, we report the fraction of
sunlight absorbed by phytoplankton that actually is used to
form chemical bonds in the global ocean. Further, we
compare the spatial distributions of photochemical energy
conversion to the pattern inferred from space-based
retrievals of solar induced fluorescence yields
The biophysical basis of fluorescence measurements de-
rives from the three possible fates of solar energy absorbed
by any photosynthetic organism (14). Absorbed photons can
(1) generate photochemical reactions leading to production
of organic matter (with the rate kp), (2) be dissipated as heat
(kt), or (3) be emitted back to the environment as fluores-
cence (kf) (15). In a dark-adapted state or under low irradi-
ance (when kt is constant), the quantum yield of chlorophyll
fluorescence, ϕf (= kf/(kp+kt+kf)), is inversely related to the
quantum yield of photochemistry in PSII, ϕp = kp/(kp+kt+kf)
= Fv/Fm.
Substitution and rearrangement leads to:
ϕf = ϕfm (1 – Fv/Fm) (1)
where ϕfm (= kf/(kt+kf)) is the maximum fluorescence yield
obtained when photochemistry is nil (e.g., at saturating
background light).
This biophysical model predicts an inverse linear rela-
tionship between the quantum yield of photochemistry and
that of chlorophyll fluorescence. However, by the early
1980’s it was realized that exposure to high continuous irra-
diance can lead to a suite of thermal dissipative mecha-
nisms, collectively called non-photochemical quenching
(NPQ) (16). These reactions markedly decrease the quantum
yield of fluorescence at high background light. Hence, the
relationship between chlorophyll fluorescence and photo-
chemistry, described in Eq. 1, becomes highly non-linear as
NPQ phenomena play an increasingly larger role in energy
dissipation.
Calculating the budget of absorbed solar radiation re-
quires measurements of the quantum yields of at least two
pathways, for example, photochemistry and fluorescence.
Although the development and use of variable fluorescence
techniques over the past two decades has provided unprec-
The fate of photons absorbed by phytoplankton in the
global ocean
Hanzhi Lin,1* Fedor I. Kuzminov,1 Jisoo Park,2 SangHoon Lee,2 Paul G. Falkowski,1,3† Maxim Y. Gorbunov1†
1Environmental Biophysics and Molecular Ecology Program, Department of Marine and Coastal Sciences, Rutgers, The State University of New Jersey, 71 Dudley Road, New
Brunswick, NJ, USA. 2Korea Polar Research Institute, 26 Songdomirae-ro, Yeonsu-Gu, Incheon, Republic of Korea. 3Department of Earth and Planetary Sciences, Rutgers,
The State University of New Jersey, Piscataway, NJ, USA.
*Present Address: Institute of Marine and Environmental Technology, University of Maryland Center for Environmental Sciences, Baltimore, MD 21202, USA.
†Corresponding author. E-mail: falko@marine.rutgers.edu (P.G.F.); gorbunov@marine.rutgers.edu (M.Y.G.)
Solar radiation absorbed by marine phytoplankton can follow three possible paths. By simultaneously
measuring the quantum yields of photochemistry and chlorophyll fluorescence
in situ,
we calculate that,
on average, ~60% of absorbed photons are converted to heat, while only 35% are directed toward
photochemical water splitting and the rest are re-emitted as fluorescence. The spatial pattern of
fluorescence yields and lifetimes strongly suggests that photochemical energy conversion is
physiologically limited by nutrients. Comparison of in situ fluorescence lifetimes with satellite retrievals
of solar induced fluorescence yields suggest that the mean values of the latter are generally
representative of the photophysiological state of phytoplankton, however the signal to noise ratio is
unacceptably low in extremely oligotrophic regions, which comprise 30% of the open ocean
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edented information about photochemical conversion in
phytoplankton in situ, these instruments are unable to
measure the absolute quantum yields of fluorescence. To
overcome this basic limitation, we constructed an extremely
sensitive sea-going instrument that measures chlorophyll
fluorescence lifetimes in the picosecond time domain (17).
The fluorescence lifetime can be quantitatively related to
the absolute quantum yield of fluorescence (18):
ϕf = τ/τn (2)
where τn is the intrinsic (or natural) lifetime constant for
chlorophyll a molecules (17). Thus, the longer the lifetime,
the higher the quantum yield of fluorescence.
Between 2008 and 2014, we obtained >150,000 discrete
chlorophyll fluorescence lifetime measurements from the
Pacific, Atlantic, Arctic, and Southern Oceans. These meas-
urements comprise the map of quantum yields of chloro-
phyll fluorescence from phytoplankton in the upper ocean
(Fig. 1). The night-time in situ lifetimes ranged from 0.5 to
2.7 ns with a mean of 1.13 ± 0.33 ns (Fig. 2). This naturally
dark-adapted condition corresponds to a state when all
functional reaction centers are open and NPQ is absent.
These values span the entire range of published lifetimes of
in vivo chlorophyll fluorescence obtained from cultured
phytoplankton (17) and reflect extraordinary variability in
phytoplankton physiology in the global ocean. The general
pattern of the fluorescence lifetimes in the central gyres of
the global ocean is rather featureless although phytoplank-
ton growth is subject to both macro- and micronutrient lim-
itation (14). The shortest fluorescence lifetimes (<1ns) were
observed along continental margins, in the Antarctic con-
vergence, Subtropical Atlantic and Pacific oceans. These
lifetime distributions support the hypothesis that phyto-
plankton in the central gyres are acclimated to broad scale
and persistent nutrient limitation (11, 12). In contrast the
longest fluorescence lifetimes were observed in high-
nutrient-low-chlorophyll (HNLC) regions of the equatorial
Pacific Ocean and the Southern Ocean where primary pro-
duction is limited by the paucity of iron (19), a micronutri-
ent that is critical for the function of photosystem II (20,
21). The exceptionally high values of fluorescence lifetimes
in these areas of the global ocean are consistent with ex-
tremely low Fv/Fm values and indicative of a large fraction of
non-functional PSII reaction centers and energetically un-
coupled antenna pigment-protein complexes (21–23).
There is a strong diel cycle in fluorescence lifetimes; in
general, lifetimes were longer at night than during daytime,
in spite of a marked reduction in the quantum yields of
photochemistry under strong sunlight (Fig. 2). The >5 fold
variability in dark-adapted fluorescence lifetimes in situ far
exceeds that predicted by Eq. 1. However, this dynamic
range is greatly attenuated in high light, when NPQ pro-
cesses are activated. For example, exceptionally long life-
times (>2 ns) measured in a dark-adapted state in HNLC
regions decrease by more than two-fold in high light,
whereas relatively short lifetimes (~ 1 ns) in low-nutrient-
low-chlorophyll (LNLC) regions decrease by only 30% under
the same conditions (Fig. 2A). Regardless of the molecular
mechanisms responsible for NPQ, the net result for high
light conditions is increased thermal dissipation of absorbed
light in PSII leading to both reductions in photochemical
energy conversion efficiency and in the range of variability
of the quantum yields of fluorescence.
With the launch of the Moderate Resolution Imaging
Spectroradiometer (MODIS) and MEdium Resolution Imag-
ing Spectrometer (MERIS) satellites, which possess the ca-
pability of remotely detecting solar induced chlorophyll
fluorescence signals from the global ocean, it became theo-
retically possible to calculate the quantum yield of chloro-
phyll fluorescence from space (24–26). However, the
theoretical basis for estimating the relationship between
chlorophyll fluorescence and photochemistry was developed
before there was an understanding of NPQ (24). We there-
fore examined how the measured in situ fluorescence life-
times are related to satellite-derived estimates of the
quantum yield of chlorophyll a fluorescence.
Statistical analyses (effective sample size >20,000) by
both Pearson’s linear correlation coefficient and two non-
parametric Kendall’s tau and Spearman’s rho coefficients
revealed a weak linear correlation (p<0.01) between these
satellite derived solar induced fluorescence yields and the
ship based measurements (Table S1). Satellite-based esti-
mates of the quantum yield are derived from observations of
the surface ocean close to local noon (27). Hence, the re-
motely sensed estimates inevitably are obtained at very high
irradiances and are strongly influenced by NPQ, a phenom-
enon that is extremely difficult to quantify in global bio-
physical models. NPQ is not only critically dependent on
pigment composition within the light harvesting antennae
(which, in turn, is affected by phytoplankton community
composition), but also on upper ocean turbulence as it af-
fects the light field experienced by the community (28), as
well as nutrient stress (19). Despite these complications,
qualitative comparison of satellite-derived maps of quantum
yields of chlorophyll fluorescence (Fig. 3) reveals basic
trends that often, but not always correspond to in situ life-
time measurements. For example, in the Southern Ocean
(an HNLC region), satellite-derived quantum yields are high
and correlate with long lifetimes. In this iron limited region
of the world oceans, there is a well-documented reduction in
photosynthetic energy conversion efficiency as a result of
impairment of PSII reaction centers and potential energetic
uncoupling of the antenna pigment-protein complexes (7,
22). In the low nutrient, low chlorophyll regions of the cen-
tral oceanic gyres of the North and South Pacific and the
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North Atlantic, measured fluorescence lifetimes are signifi-
cantly shorter compared to HNLC regions. Although the
mean fluorescence yield based on the satellite retrievals for
the oligotrophic open ocean is 0.043 (Fig. 4) and is generally
concordant with that measured in situ values, the high es-
timates of quantum yields obtained from the space-based
platform (Fig. 3) are not corroborated by in situ lifetime
measurements. Further, the range of estimated quantum
yields derived from satellite-based measurements (> six
fold) is far larger than that of the in situ lifetimes measured
at high irradiances (~ 3-fold). Indeed, the range of the esti-
mated quantum yields of fluorescence in the global ocean (~
0.02 to 0.15) appears to exceed that of our current biophysi-
cal understanding of photochemistry in phytoplankton.
What might be the source of this discrepancy?
In the central ocean gyres, where surface chlorophyll
concentrations are very low (<0.1 mg·m−3), the fluorescence
signals propagated to space are extremely weak. As a result,
the current algorithms used to calculate quantum yields of
fluorescence become increasingly uncertain (Fig. 4 and (26,
29)). The relationship between measured lifetimes and satel-
lite-derived quantum yields diverge. In contrast to the satel-
lite-derived yields which have significant “noise”, the in situ
lifetime measurements remain extremely precise (within
5%) even at the lowest chlorophyll concentrations found in
the upper ocean. Another factor behind this discrepancy is
the effect of pigment packaging within a phytoplankton cell
(25, 30, 31), which is most pronounced in larger cells and
reduces the observed quantum yields, as compared to their
true “molecular” values inferred from lifetime measure-
ments. Similarly, the uncertainties of the current algorithms
for remote sensing retrievals of phytoplankton absorption
coefficients (25) further reduce the accuracy of satellite-
based estimates of the quantum yields.
Although quantum yields of chlorophyll fluorescence ob-
tained from current satellite sensors have many inherent
inaccuracies, this approach to understanding global photo-
physiology of phytoplankton should not be abandoned. We
suggest that relating the space-based estimates to in situ
measurements of chlorophyll fluorescence lifetimes will
provide a pathway to understanding photobiological energy
utilization and dissipation processes on a global scale. For
example, the maximal average photochemical energy con-
version efficiency (ϕp) at night in the global ocean, obtained
simultaneously with our lifetime measurements, is 0.35 ±
0.11 (Fig. S2). Given an average night-time lifetime of 1.13 ns
(Fig. 2), we deduce that thermal energy dissipation accounts
for ~ 60% of the photosynthetically active quanta absorbed
by phytoplankton globally. In contrast, under optimal
growth conditions in the laboratory, an average phytoplank-
ton cell utilizes ~ 65% of the absorbed quanta for photo-
chemistry and dissipates <35% as heat. That thermal
dissipation of absorbed quanta by phytoplankton in the up-
per ocean is so high strongly implies that a large fraction of
cells have impaired or non-functional PSII reaction centers,
and/or uncoupled photosynthetic antenna. We conclude
that, while photochemical energy conversion to biomass in
the oceans accounts for half of the global carbon fixed per
annum, the overall energy conversion efficiency is relatively
low and is limited by nutrient supply
REFERENCES AND NOTES
1. D. Antoine, J. M. Andre, A. Morel, Oceanic primary production. 2. Estimation at
global scale from satellite (coastal zone color scanner) chlorophyll. Global
Biogeochem. Cycles
10
, 57–69 (1996). doi:10.1029/95GB02832
2. C. B. Field, M. J. Behrenfeld, J. T. Randerson, P. Falkowski, Primary production of
the biosphere: Integrating terrestrial and oceanic components. Science
281
,
237–240 (1998). Medline doi:10.1126/science.281.5374.237
3. M. J. Behrenfeld, E. Boss, D. A. Siegel, D. M. Shea, Carbon-based ocean
productivity and phytoplankton physiology from space. Global Biogeochem.
Cycles
19
, GB1006 (2005). doi:10.1029/2004GB002299
4. M. J. Behrenfeld, P. G. Falkowski, Photosynthetic rates derived from satellite-
based chlorophyll concentration. Limnol. Oceanogr.
42
, 1–20 (1997).
doi:10.4319/lo.1997.42.1.0001
5. P. G. Falkowski, Z. Kolber, Variations in chlorophyll fluorescence yields in
phytoplankton in the world oceans. Aust. J. Plant Physiol.
22
, 341–355 (1995).
doi:10.1071/PP9950341
6. Z. Kolber, P. G. Falkowski, Use of active fluorescence to estimate phytoplankton
photosynthesis in situ. Limnol. Oceanogr.
38
, 1646–1665 (1993).
doi:10.4319/lo.1993.38.8.1646
7. G. H. Krause, E. Weis, Chlorophyll fluorescence and photosynthesis: The basics.
Annu. Rev. Plant Physiol.
42
, 313–349 (1991).
doi:10.1146/annurev.pp.42.060191.001525
8. P. W. Boyd, A. J. Watson, C. S. Law, E. R. Abraham, T. Trull, R. Murdoch, D. C.
Bakker, A. R. Bowie, K. O. Buesseler, H. Chang, M. Charette, P. Croot, K.
Downing, R. Frew, M. Gall, M. Hadfield, J. Hall, M. Harvey, G. Jameson, J.
LaRoche, M. Liddicoat, R. Ling, M. T. Maldonado, R. M. McKay, S. Nodder, S.
Pickmere, R. Pridmore, S. Rintoul, K. Safi, P. Sutton, R. Strzepek, K.
Tanneberger, S. Turner, A. Waite, J. Zeldis, A mesoscale phytoplankton bloom in
the polar Southern Ocean stimulated by iron fertilization. Nature
407
, 695–702
(2000). Medline doi:10.1038/35037500
9. T. S. Bibby, M. Y. Gorbunov, K. W. Wyman, P. G. Falkowski, Photosynthetic
community responses to upwelling in mesoscale eddies in the subtropical North
Atlantic and Pacific Oceans. Deep Sea Res. Part II Top. Stud. Oceanogr.
55
, 1310–
1320 (2008). doi:10.1016/j.dsr2.2008.01.014
10. P. G. Falkowski, D. Ziemann, Z. Kolber, P. K. Bienfang, Role of eddy pumping in
enhancing primary production in the ocean. Nature
352
, 55–58 (1991).
doi:10.1038/352055a0
11. M. J. Behrenfeld, K. Worthington, R. M. Sherrell, F. P. Chavez, P. Strutton, M.
McPhaden, D. M. Shea, Controls on tropical Pacific Ocean productivity revealed
through nutrient stress diagnostics. Nature
442
, 1025–1028 (2006). Medline
doi:10.1038/nature05083
12. D. J. Suggett, C. M. Moore, A. E. Hickman, R. J. Geider, Interpretation of fast
repetition rate (FRR) fluorescence: Signatures of phytoplankton community
structure versus physiological state. Mar. Ecol. Prog. Ser.
376
, 1–19 (2009).
doi:10.3354/meps07830
13. D. Tchernov, M. Y. Gorbunov, C. de Vargas, S. Narayan Yadav, A. J. Milligan, M.
Häggblom, P. G. Falkowski, Membrane lipids of symbiotic algae are diagnostic of
sensitivity to thermal bleaching in corals. Proc. Natl. Acad. Sci. U.S.A.
101
,
13531–13535 (2004). Medline doi:10.1073/pnas.0402907101
14. P. Falkowski, J. A. Raven, Aquatic Photosynthesis. (Princeton Univ., Princeton,
NJ, ed. 2, 2007).
15. W. L. Butler, R. J. Strasser, Tripartite model for the photochemical apparatus of
green plant photosynthesis. Proc. Natl. Acad. Sci. U.S.A.
74
, 3382–3385 (1977).
Medline doi:10.1073/pnas.74.8.3382
16. M. Bradbury, N. R. Baker, Analysis of the induction of chlorophyll fluorescence in
First release: 7 January 2016 www.sciencemag.org (Page numbers not final at time of first release) 3

leaves and isolated thylakoids - contributions of photochemical and non-
photochemical quenching. Proc. R. Soc. London Ser. B
220
, 251–264 (1983).
doi:10.1098/rspb.1983.0098
17. Information on materials and methods is available on Science Online.
18. J. R. Lakowicz, Principles of Fluorescence Spectroscopy (Springer
Science+Business Media, LLC., New York, ed. 3, 2006).
19. C. M. Moore, M. M. Mills, K. R. Arrigo, I. Berman-Frank, L. Bopp, P. W. Boyd, E. D.
Galbraith, R. J. Geider, C. Guieu, S. L. Jaccard, T. D. Jickells, J. La Roche, T. M.
Lenton, N. M. Mahowald, E. Marañón, I. Marinov, J. K. Moore, T. Nakatsuka, A.
Oschlies, M. A. Saito, T. F. Thingstad, A. Tsuda, O. Ulloa, Processes and patterns
of oceanic nutrient limitation. Nat. Geosci.
6
, 701–710 (2013).
doi:10.1038/ngeo1765
20. J. A. Raven, M. C. W. Evans, R. E. Korb, The role of trace metals in photosynthetic
electron transport in O2-evolving organisms. Photosynth. Res.
60
, 111–150
(1999). doi:10.1023/A:1006282714942
21. I. R. Vassiliev, Z. Kolber, K. D. Wyman, D. Mauzerall, V. K. Shukla, P. G. Falkowski,
Effects of iron limitation on photosystem II composition and light utilization in
Dunaliella tertiolecta. Plant Physiol.
109
, 963–972 (1995). Medline
22. P. G. Falkowski, R. M. Greene, R. J. Geider, Physiological limitations on
phytoplankton productivity in the ocean. Oceanography (Wash. D.C.)
5
, 84–91
(1992). doi:10.5670/oceanog.1992.14
23. P. S. Schrader, A. J. Milligan, M. J. Behrenfeld, Surplus photosynthetic antennae
complexes underlie diagnostics of iron limitation in a cyanobacterium. PLOS ONE
6
, e18753 (2011). Medline doi:10.1371/journal.pone.0018753
24. M. R. Abbott, R. M. Letelier, “Algorithm theoretical basis document: Chlorophyll
fluorescence (MODros. Inf. Serv. Product Number 20)” (Ocean Biology
Processing Group, NASA's Earth Observing System, 1999).
25. M. J. Behrenfeld, T. K. Westberry, E. S. Boss, R. T. O’Malley, D. A. Siegel, J. D.
Wiggert, B. A. Franz, C. R. McClain, G. C. Feldman, S. C. Doney, J. K. Moore, G.
Dall’Olmo, A. J. Milligan, I. Lima, N. Mahowald, Satellite-detected fluorescence
reveals global physiology of ocean phytoplankton. Biogeosciences
6
, 779–794
(2009). doi:10.5194/bg-6-779-2009
26. Y. Huot, B. A. Franz, M. Fradette, Estimating variability in the quantum yield of
Sun-induced chlorophyll fluorescence: A global analysis of oceanic waters.
Remote Sens. Environ.
132
, 238–253 (2013). doi:10.1016/j.rse.2013.01.003
27. A. Savtchenko, D. Ouzounov, S. Ahmad, J. Acker, G. Leptoukh, J. Koziana, D.
Nickless, Terra and Aqua MODIS products available from NASA GES DAAC. Adv.
Space Res.
34
, 710–714 (2004). doi:10.1016/j.asr.2004.03.012
28. A. C. Alderkamp, H. J. W. de Baar, R. J. W. Visser, K. R. Arrigo, Can
photoinhibition control phytoplankton abundance in deeply mixed water
columns of the Southern Ocean? Limnol. Oceanogr.
55
, 1248–1264 (2010).
doi:10.4319/lo.2010.55.3.1248
29. T. J. Browning, H. A. Bouman, C. M. Moore, Satellite-detected fluorescence:
Decoupling nonphotochemical quenching from iron stress signals in the South
Atlantic and Southern Ocean. Global Biogeochem. Cycles
28
, 510–524 (2014).
doi:10.1002/2013GB004773
30. A. Bricaud, H. Claustre, J. Ras, K. Oubelkheir, Natural variability of
phytoplanktonic absorption in oceanic waters: Influence of the size structure of
algal populations. J. Geophys. Res. Oceans
109
, C11010 (2004).
doi:10.1029/2004JC002419
31. A. Morel, A. Bricaud, Theoretical results concerning light absorption in a discrete
medium, and application to specific absorption of phytoplankton. Deep-Sea Res.
28
, 1375–1393 (1981). doi:10.1016/0198-0149(81)90039-X
32. T. P. Boyer et al., “World Ocean Database 2013” (Silver Spring, MD, U.S., 2013).
33. F. I. Kuzminov, M. Y. Gorbunov, Energy dissipation pathways in Photosystem 2 of
the diatom, Phaeodactylum tricornutum, under high-light conditions.
Photosynth. Res. (2015). Medline doi:10.1007/s11120-015-0180-3
34. J. Enderlein, R. Erdmann, Fast fitting of multi-exponential decay curves. Opt.
Commun.
134
, 371–378 (1997). doi:10.1016/S0030-4018(96)00384-7
35. S. S. Brody, E. Rabinowitch, Excitation lifetime of photosynthetic pigments in
vitro and in vivo. Science
125
, 555 (1957). Medline
doi:10.1126/science.125.3247.555
36. G. N. Lewis, M. Kasha, Phosphorescence in fluid media and the reverse process
of singlet-triplet absorption. J. Am. Chem. Soc.
67
, 994–1003 (1945).
doi:10.1021/ja01222a032
37. A. R. Holzwarth, Fluorescence Lifetimes in Photosynthetic Systems. Photochem.
Photobiol.
43
, 707–725 (1986).
38. F. Morales, N. Moise, R. Quílez, A. Abadía, J. Abadía, I. Moya, Iron deficiency
interrupts energy transfer from a disconnected part of the antenna to the rest of
Photosystem II. Photosynth. Res.
70
, 207–220 (2001). Medline
doi:10.1023/A:1017965229788
39. I. Moya, M. Silvestri, O. Vallon, G. Cinque, R. Bassi, Time-resolved fluorescence
analysis of the photosystem II antenna proteins in detergent micelles and
liposomes. Biochemistry
40
, 12552–12561 (2001). Medline
doi:10.1021/bi010342x
40. R. Croce, H. van Amerongen, Light-harvesting and structural organization of
Photosystem II: From individual complexes to thylakoid membrane. J.
Photochem. Photobiol. B
104
, 142–153 (2011). Medline
doi:10.1016/j.jphotobiol.2011.02.015
41. M. Gorbunov, P. Falkowski, in Photosynthesis: Fundamental Aspects to Global
Perspectives: Proceedings of the 13th International Society of Photosynthesis, A.
van der Est, D. Bruce, Eds. (Alliance Commnuncations Group, Lawrance, KS,
2005), vol. 2, pp. 1029–1031.
42. C. M. Hu, Z. Lee, B. Franz, Chlorophyll a algorithms for oligotrophic oceans: A
novel approach based on three-band reflectance difference. J. Geophys. Res.
Oceans
117
, C01011 (2012). doi:10.1029/2011JC007395
43. A. Bricaud, A. Morel, M. Babin, K. Allali, 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. Oceans
103
, 31033–31044 (1998). doi:10.1029/98JC02712
44. Y. Huot, C. A. Brown, J. J. Cullen, New algorithms for MODIS sun-induced
chlorophyll fluorescence and a comparison with present data products. Limnol.
Oceanogr. Methods
3
, 108–130 (2005). doi:10.4319/lom.2005.3.108
45. A. Morel, Y. Huot, B. Gentili, P. J. Werdell, S. B. Hooker, B. A. Franz, Examining the
consistency of products derived from various ocean color sensors in open ocean
(Case 1) waters in the perspective of a multi-sensor approach. Remote Sens.
Environ.
111
, 69–88 (2007). doi:10.1016/j.rse.2007.03.012
46. K. Pearson, Note on regression and inheritance in the case of two parents. Proc.
R. Soc. London
58
, 240–242 (1895). doi:10.1098/rspl.1895.0041
47. M. G. Kendall, A new measure for rank correlation. Biometrika
30
, 81–93 (1938).
doi:10.1093/biomet/30.1-2.81
48. C. Spearman, The proof and measurement of association between two things.
Am. J. Psychol.
15
, 72–101 (1904). doi:10.2307/1412159
49. A. N. Kolmogorov, Sulla determinazione empirica di una legge di distribuzione.
Giornale dell'Istituto Italiano degli Attuari
4
, 83-91 (1933).
50. N. Smirnov, Table for estimating the goodness of fit of empirical distributions.
Ann. Math. Stat.
19
, 279–281 (1948). doi:10.1214/aoms/1177730256
51. G. W. Corder, D. I. Foreman, in Nonparametric Statistics: A Step-by-Step
Approach (Wiley, Hoboken, NJ, 2014), pp. 140–142.
52. H. Abdi, in Encyclopedia of measurement and statistics, N. J. Salkind, Ed. (SAGE
Publications, Inc., Thousands Oaks, CA, 2007), vol. 2.
ACKNOWLEDGMENTS
We thank Drs. E. Boyle, P. Quinn, K. Thamatrakoln, and V.Fadeev for providing
shiptime, and the captains and crews of RV Oceanus, RV Knorr, RV Melville, RV
Akademik Yoffe, and RV Araon. This research was supported by Grants
NNX08AC24G from NASA Ocean Biology and Biogeochemistry Program and SI-
1334 from the Strategic Environmental Research and Development Program to
MYG and PGF. HL and FIK were supported by the Institute of Marine and Coastal
Sciences post-doctoral fellowships and the Bennett L. Smith Endowment to PGF.
MYG and FIK were in part supported by Grant 14-17-00451 from the Russian
Science Foundation. JP and SL were supported by Grant PP15020 from the
Korean Polar Research Institute. All fluorescence data are deposited at
PANGAEA (Publishing Network for Geoscientific and Environmental Data) under
accession number PDI-11228.
First release: 7 January 2016 www.sciencemag.org (Page numbers not final at time of first release) 4

SUPPLEMENTARY MATERIALS
www.sciencemag.org/cgi/content/full/science.aab2213/DC1
Materials and Methods
Figs. S1 to S4
Table S1
References (32–52)
30 March 2015; accepted 9 December 2015
Published online 7 January 2016
10.1126/science.aab2213
First release: 7 January 2016 www.sciencemag.org (Page numbers not final at time of first release) 5

Fig. 1. Global distribution of ship-
based measurements of
chlorophyll fluorescence lifetimes
and the derived quantum yields of
fluorescence (Eq. 2) in the upper
ocean superimposed on the
climatological map of surface
nitrate concentrations in the world
ocean (32
). Periods of in situ
sampling were (A) July-Aug. 2011;
(B) Oct.-Nov. 2011; (C) Oct.-Nov.
2010; (D) Jan. 2012; (E) July 2014;
(F) Sept. 2010; (G) May 2014; (H)
Aug. 2008.
Fig. 2. (A) Representative diel
cycles of chlorophyll fluorescence
lifeti
mes in HNLC and LNLC
regions of the Pacific Ocean
obtained in Oct. 2011. Color bar for
lifetimes is the same as in Fig. 1;
(
B
) Histograms of the fractional
frequency of lifetime
measurements in daytime and at
night, respectively. The mean value
of nighttime lifetimes is 1.13 ± 0.33
ns and that of daytime lifetimes is
1.02 ± 0.22 ns.
First release: 7 January 2016 www.sciencemag.org (Page numbers not final at time of first release) 6

Fig. 3. Global seasonal maps of quantum yields of solar induced chlorophyll
fluorescence in the upper ocean. (
A
) boreal winter (21 Dec. 2011 – 20 Mar., 2012); (
B
)
boreal spring (21 Mar. - 20 June, 2012); (
C
) boreal summer (21 Sept. – 20 Dec., 2012);
(D) boreal autumn (21 Sept. – 20 Dec., 2012).
Fig. 4. Variations in MODIS retrievals of the quantum yields of
chlorophyll fluorescence (N=5.17 ×106) with chlorophyll abundance (17).
The mean value of these satellite-derived quantum yields is 0.043. The
average value of in situ lifetime measurements at noon (between 10 a.m
to 2 p.m local time) is 0.99 ± 0.2 ns, which corresponds to the quantum
yield of 0.066 ± 0.013. (
Inset
) Global distribution (ten year average) of
chlorophyll concentrations in the boreal summer. The grey area
indicates oligotrophic regions with chlorophyll concentrations below 0.1
mg·m−3; this area covers ~30
%
of the global ocean.
First release: 7 January 2016 www.sciencemag.org (Page numbers not final at time of first release) 7