Understanding the dynamics of marine phytoplankton productivity requires
mechanistic insight into the non-linear coupling of light absorption,
photosynthetic electron transport and carbon fixation in response to
environmental variability. In the present study, we examined the variability
of phytoplankton light absorption characteristics, light-dependent electron
transport and 14C-uptake rates over a 48 h period in the coastal
subarctic north-east (NE) Pacific. We observed an intricately coordinated
response of the different components of the photosynthetic process to diurnal
irradiance cycles, which acted to maximize carbon fixation, while
simultaneously preventing damage by excess absorbed light energy. In
particular, we found diurnal adjustments in pigment ratios, excitation energy
transfer to reaction centre II (RCII), the capacity for non-photochemical
quenching (NPQ), and the light efficiency (α) and maximum rates
(Pmax) of RCII electron transport (ETRRCII) and
14C uptake. Comparison of these results from coastal waters to
previous observations in offshore waters of the subarctic NE Pacific provides
insight into the effects of iron limitation on the optimization of
photosynthesis. Under iron-limited, low-biomass conditions, there was a
significant reduction of iron-rich photosynthetic units per chlorophyll a,
which was partly offset by higher light absorption and electron transport per
photosystem II (PSII). Iron deficiency limited the capacity of phytoplankton
to utilize peak midday irradiance for carbon fixation and caused an
upregulation of photoprotective mechanisms, including NPQ, and the decoupling
of light absorption, electron transport and carbon fixation. Such decoupling
resulted in an increased electron requirement (Φe,C) and
decreased quantum efficiency (ΦC) of carbon fixation at the
iron-limited station. In both coastal and offshore waters,
Φe,C and ΦC correlated strongly to NPQ, albeit
with a significantly different slope. We discuss the implications of our
results for the interpretation of bio-optical data and the parameterization
of numerical productivity models, both of which are vital tools in monitoring
marine photosynthesis over large temporal and spatial scales.
Introduction
It is well known that photosynthetic performance and light-harvesting
characteristics of phytoplankton vary widely across environmental conditions
and seasonal cycles (e.g. Falkowski and Raven, 2007; Geider et al., 2001;
Harris, 1986; Kirk, 1994). On physiological scales, these changes can be
observed as rapid metabolic adjustments occurring over seconds to hours,
while on ecological scales (days to months) they are manifested as
phytoplankton species succession. These physiological and ecological
responses are ultimately driven by the integrated growth environment
experienced by phytoplankton and the need to optimize the conversion of
light energy to carbon biomass, while preventing damage from supersaturating
light. The present study was designed to improve the mechanistic understanding of
the entire photosynthetic process in marine phytoplankton and its capacity to
respond to environmental variability. Such information is necessary to
understand and predict ongoing climate impacts associated with changes in
nutrient supply, temperature and irradiance levels on marine photosynthetic
carbon fixation (e.g. Behrenfeld et al., 2006, 2016; Hoegh-Guldberg and
Bruno, 2010; Taucher and Oschlies, 2011).
The photosynthetic process comprises a chain of diverse reactions, leading
from light absorption via electron transport to photosynthate (ATP and NADPH)
production and carbon fixation (Fig. 1). These reactions, operating on vastly
different timescales (e.g. Huner et al.,
1998), are ultimately powered by solar energy and depend
critically on nutrient availability. Variability in
surface ocean nutrient concentrations results from physical mixing and
biological consumption acting on scales of days to months. By comparison,
variability in light intensity occurs over a broader range of timescales,
with rapid transients induced by atmospheric variability (e.g. cloud cover)
and fine-scale mixing, superimposed on diel and seasonal cycles.
Importantly, while light energy is an absolute requirement for the
photosynthetic process, excess irradiance, even on short timescales, can lead
to photodamage and photoinhibition (Powles, 1984).
Schematic diagram of the photosynthetic process, highlighting rates,
variables and conversion factors measured or derived during this study. (1)
Light absorption: photosynthetically available radiation (PAR, 400–700 nm)
is absorbed by phytoplankton (a‾phy∗, m-2 mg Chl a-1).
Total absorption by phytoplankton can be subdivided into
absorption by photosynthetic pigments (a‾psp∗, m-2 mg Chl a-1) and photoprotective carotenoids
(a‾ppc∗, m-2 mg Chl a-1). The parameter
a‾psp∗, if specific for PSII (photosystem II) only, can be further decomposed
into values of the functional absorption cross section of each RCII (reaction centre II) in the
dark-regulated state, i.e. not affected by NPQ (σPSII,
Å2 RCII-1) and the number of functional RCII per Chl a
(nPSII, RCII Chl a-1). Both σPSII and
nPSII can be adjusted to regulate the amount of excitation energy
reaching RCII. The light energy absorbed by the pigments of PSII can have
three fates: photochemistry (ETRRCII), dissipation as heat
(including the upregulation of NPQ) and re-emission as fluorescence
(ChlF). Changes in ChlF can be used to infer changes in the other two
pathways. (2) Initial charge separation in RCII (ETRRCII,
mol e- mol RCII-1 s-1). (3) Electron transport after
initial charge separation in RCII ultimately leads to the generation of
“photosynthate” ((4) ATP and NADPH), which in turn can be used for carbon
fixation ((5) C fixation, here measured as 14C uptake). The
electron requirement of carbon fixation Φe,C
(mol e- mol RCII-1) is the ratio of electrons displaced by
the initial charge separation in RCII to 14C uptake. The photosynthetic
efficiency, ΦC (mol C mol quanta-1), is the amount of
14C fixed per quanta absorbed. Under conditions when the rate of
light absorption and delivery to RCII surpasses the potential for carbon
fixation or reductant formation, both Φe,C and NPQ will
increase to prevent over-reduction of RCII. The magnitude of
ΦC, in turn, is dependent on how much initially absorbed
energy is dissipated as fluorescence (ChlF) and heat (including NPQ) as
well as through processes decoupling ETRRCII from 14C uptake
(reflected in Φe,C).
To compensate for fluctuations in light availability, marine phytoplankton
have evolved extreme photo-physiological plasticity, allowing cells to
maximize light-harvesting capacity at low irradiance, while minimizing
photodamage under high light levels. A better mechanistic understanding of
the scope and limits of such coordinated regulation within the photosynthetic
process is essential for the accurate modelling of bottom-up controls on
marine primary productivity and its response to environmental change.
Furthermore, mechanistic insight into environmental controls on the light use
efficiency of carbon fixation is crucial for the development of algorithms
estimating primary productivity from remotely acquired optical data (Lee et
al., 2015; Silsbe et al., 2016; Zoffoli et al., 2018).
In the present study, we examined diurnal variability in the capacity of
phytoplankton to use light energy for biomass production in a productive
coastal upwelling regime. High-temporal-resolution measurements, conducted
over a 48 h period, revealed coordinated changes in light absorption, energy
dissipation, photosynthetic electron transport and 14C uptake. Our
results demonstrate strong variability in the stoichiometry of various
components of the photosynthetic process, providing insight into
phytoplankton metabolic acclimation potential in response to environmental
fluctuation in coastal waters. Comparison of these new results with previous
observations in the iron-limited subarctic north-east (NE) Pacific (Schuback et al.,
2016) allowed us to identify distinct diurnal patterns in these contrasting
environments, yielding insight into the effects of iron limitation on
various components of the photosynthetic process and their coupling over
diurnal irradiance cycles. Most significantly, our data demonstrate a limited
capacity of iron-limited phytoplankton to buffer fluctuations in light
availability, resulting in an increased need for photoprotection. This
enhanced photoprotection is achieved through alterations in pigment ratios
and light absorption characteristics, an increased potential for heat
dissipation of excess energy (NPQ) and decoupling of the different components
of the photosynthetic process, leading to reduced light use efficiency. Based
on our results, we discuss the correlation between photosynthetic light use
efficiency and NPQ, an optical signal amiable to high-resolution acquisition
by autonomous sensors.
Methods
In the present study, we examined light-dependent diurnal variability in
different components of the photosynthetic process in marine phytoplankton.
We present new results from a 2017 research expedition in high-productivity
coastal upwelling waters and compare these data to recently published
observations from the iron-limited waters of the subarctic Pacific Ocean
(Schuback et al., 2016). We first introduce the two datasets and then
briefly describe the methods used to assess each component of the
photosynthetic process (Fig. 1), from light absorption to carbon fixation.
Dataset 1
New field data were collected during a 48 h period from 19 to 21 August 2017
on board the R/V Oceanus in the subarctic NE Pacific. During
this period, the research vessel followed a Lagrangian drifter equipped with
a drogue sock at 5 m depth in order to track mean surface layer flow. The
drifter was deployed approximately 25 nautical miles off the coast of Oregon,
USA (44.3∘ N, 124.4∘ W; Fig. 2). More information on the
drifter study is available in Herr et al. (2019).
Map of the subarctic NE Pacific showing location of OSP14, in
offshore iron-limited waters, and OCE17, a coastal upwelling region.
Seawater samples were collected from the ship's underway water supply (intake
depth approx. 5 m) and used for photo-physiological measurements by fast
repetition rate fluorometry (FRRF; 2 h intervals) 14C-uptake
experiments, pigment analysis by HPLC (high-performance liquid chromatography)
and particulate light absorption (4 h
intervals). Sample collection, handling and experimental protocols were
identical to the methods used in Schuback et al. (2016). In the following, we
provide only brief details about sample analysis and rate measurements, with
emphasis on approaches that extend beyond the analysis of Schuback et
al. (2016). All measured variables and derived parameters are summarized in
Table 1.
List of parameters derived and discussed in the text.
Parameter UnitsMethodaphy-QFT∗(λ)Phytoplankton absorption spectram2 mg Chl a-1QFT with correction following Letelier et al. (2017).axx-HPLC∗(λ)Absorption spectra (xx specifies phytoplankton, photosynthetic pigments or photoprotectivecarotenoids)m2 mg Chl a-1HPLC spectral reconstruction with packaging correction.a^xx∗Absorption coefficientm2 mg Chl a-1Mean absorption 400–700 nm specific to flat white excitation light.a‾xx∗Weighted absorption coefficientm2 mg Chl a-1Mean absorption 400–700 nm weighted to spectral distribution of in situ light.σPSIIFunctional absorption cross sectionÅ2 RCII-1FRRF ST protocol during dark-regulated state, value specific to λ of excitation source.σPSII-ISFunctional absorption cross sectionÅ2 RCII-1As above, value corrected to be specific to in situ light spectrum.σPSII-IS′Functional absorption cross sectionÅ2 RCII-1FRRF ST protocol during light-regulated state, value corrected to in situ light spectrum.Fv/FmQuantum efficiency of initial charge separationNo unitsFRRF ST protocol during dark-regulated state; (Fm-Fo)/Fm.Fq′/Fv′(500)Fraction of RCII which remains open (QA oxidized) at a background irradianceof 500 µmol quanta m-2 s-1No unitsFRRF ST protocol during light-regulated state; (Fm′-F′)/(Fm′-Fo′).NPQNSVNon-photochemical quenching at in situ light intensity at the time and depth of samplingNo unitsFRRF ST protocol during light-regulated state; Fo′/(Fm′-Fo′).NPQNSV(500)Non-photochemical quenching for a reference light intensity of 500 µmol quanta m-2 s-1No unitsAs above.1/nPSIIPhotosynthetic unit size of PSIImol Chl a mol RCII-1Estimated from a‾psp∗ and σPSII-IS.ETRRCIIRate of initial charge separation in RCIImol e- mol RCII-1 s-1Calculated from FRRF ST protocol derived parameters as E⋅σPSII-IS′⋅Fq′/Fv′.ETRRCII-PmaxMaximum light-saturated ratemol e- mol RCII-1 s-1As above, but maximum rate of ETR achieved duringlight-response curve.ETRRCII-αLight efficiency under light limitationmol e- mol RCII-1 s-1 (µmol quanta m-2 s-1)-1As above, but initial slope of light-response ETR curve.14C uptakeRate of carbon fixationmol C mol Chl a-1 s-12 h 14C-uptake light-response curves measured at each time point.14C-PmaxMaximum light-saturated ratemol C mol Chl a-1 s-1As above, but maximum rate of 14C uptake achieved during light-response curve.14C-αLight efficiency under light limitationmol C mol Chl a-1 s-1 (µmol quanta m-2 s-1)-1As above, but initial slope of 14C-uptake light-response curve.EkLight saturation parameterµmol quanta m-2 s-1Point of saturation during light-response curve (Pmax/α) of ETR or 14C uptake.Φe,CElectron requirement for carbon fixationmol e- mol C-1Calculated from ETR and 14C-uptake rates.ΦCQuantum efficiency of carbon fixationmol C mol quanta-1Calculated from light absorption and 14C-uptake rates.
In addition to the discrete sample measurements described above, we acquired
a number of additional datasets from various sensors connected to the ship's
underway water supply. All measurements and sensors used on board the R/V
Oceanus are summarized in Table S1.1 in the Supplement (OCE17 data
set). Seawater surface temperature and salinity were measured by a
thermosalinograph (SBE 45 and SBE 38 for salinity and temperature,
respectively), while surface PAR (400–700 nm) was continuously logged using
a Satlantic PAR sensor mounted on the ship's superstructure. We used a
Soliense fast repetition rate fluorometer to continuously measure
photo-physiological parameters derived from single-turnover induction
protocols (see Sect. 3.5). In addition, we used the WetLabs ac-s to quantify
light attenuation and absorption (400–750 nm), following the protocols
described in Burt et al. (2018).
Dataset 2
In a previous study (Schuback et al., 2016), we assessed variability and
coupling of different components of the photosynthetic process in an
iron-limited phytoplankton assemblage at Ocean Station Papa in the
subarctic north-east Pacific (50∘ N, 145∘ W, Fig. 2). During this
earlier study, conducted in June 2014, and hereafter referred to as OSP14,
seawater samples collected from the vessel's underway water supply (intake
depth approx. 5 m) were used for photo-physiological measurements by FRRF
(3 h intervals), 14C-uptake experiments (3 h intervals), pigment
analysis by HPLC (6 h intervals) and particulate light absorption (3 h
intervals). All measurements taken are summarized in Table S1.2, and full
details of sample handling, experimental protocols and instrumentation can be
found in Schuback et al. (2016). In several instances, the dataset presented
in Schuback et al. (2016) was reanalyzed, as described below.
Absorption spectra
Phytoplankton absorption spectra (aphy(λ)) were determined
following the quantitative filter technique (QFT) of Mitchell et al. (2000)
with path length amplification estimates following Bricaud and
Stramski (1990), as described in detail in Schuback et al. (2017). All
absorption spectra were corrected for an overestimation of absorption at
short wavelengths following the approach suggested by Letelier et al. (2017)
and described in Supplement S2. To determine chlorophyll a-specific
absorption spectra (aphy∗(λ),
m2 mg Chl a-1), absorption values were normalized to corresponding
HPLC-derived [TChl a]. The Chl a-specific phytoplankton absorption
coefficient (400–700 nm) was calculated for a flat white spectrum
(a^phy∗) and weighted to the spectrum of available
light in situ (a‾phy∗) as described in Babin et
al. (1996).
Pigment analysis and spectral reconstruction
Collection and analysis of HPLC pigment samples was performed following the
method of Pinckney (2013), as described in detail in Schuback et al. (2016).
Pigment concentrations determined by HPLC and weight-specific absorption
spectra provided by Bidigare et al. (1990) were used for reconstruction of
phytoplankton light absorption spectra (aphy∗(λ)).
This approach estimates absorption spectra specific to photosynthetic
pigments (apsp∗(λ)) and photoprotective carotenoids
(appc∗(λ)). Following the approach described in Le et
al. (2009) and Letelier et al. (2017), absorption spectra were further
corrected for pigment packaging effects using a wavelength-specific estimate
of packaging developed by Morel and Bricaud (1981), with a size parameter
calculated from an empirical relationship to chlorophyll a concentration
([Chl a]) (Woźniak et al., 1999). As described in the Supplement (S2),
we found good agreement between results from the spectral reconstruction and
QFT approaches (R2=0.95, n=20).
FRRF-derived photo-physiology
Single-turnover induction curves of Chl a fluorescence (ChlF) yields
were measured on a bench-top FRRF instrument (Soliense Instruments), after
acclimation of samples to low light intensities (< 10 µmol quanta m-2 s-1) for 20 min. Blank correction, derivation of
ChlF yields and parameters, estimation of electron transport in reaction
centre II (ETRRCII, mol e- mol RCII s-1) and
fitting of ETRRCII light-response curves were performed as
described in Schuback et al. (2016, 2017). We derived values of the maximum
light-saturated capacity of ETRRCII
(ETRRCII-Pmax), the light-dependent increase in
ETRRCII (ETRRCII-α), and rates for the in situ
light intensity at the time and depth of sampling (Table 1).
We derived values of the minimum and maximum ChlF yields in the
dark-regulated state (Fo, Fm) and in each light-regulated state of
the light-response curve (F′, Fm′). The parameter Fo′, which
represents the minimum ChlF yield in the absence of photochemical
quenching but presence of non-photochemical quenching, was estimated
following Oxborough and Baker (1997). Chl a fluorescence yields were used
to estimate the ChlF parameter Fv/Fm (=[Fm-Fo]/Fm);
the maximum efficiency of absorbed light used for photochemistry, Fq′/Fm′ (=[Fm′-F′]/Fm′); the effective efficiency of
absorbed light being used for photochemistry; and Fq′/Fv′
(=[Fm′-F′]/[Fm′-Fo′]), an estimate of the fraction of RCII
in the `open' state (Table 1). The functional absorption cross section of
RCII was derived in the dark-regulated (σPSII, Å
RCII-1) and light-regulated state (σPSII′, Å
RCII-1) and spectrally corrected to the spectral quality of in situ
light (σPSII-IS), as described below. Non-photochemical
quenching was estimated as normalized Stern–Volmer quenching,
NPQNSV (=Fo′/Fv′), for each light level of the
light-response curves (McKew et al., 2013).
We note that the bio-physical model we used to derive photo-physiological
parameters from FRRF measurements (Kolber and Falkowski, 1993; Kolber et al.,
1998) is not likely to be equally accurate for all phytoplankton species
within mixed in situ assemblages. Similarly, the fully dark-regulated state,
necessary for the calculation of most ChlF parameters, is difficult to
achieve in mixed assemblages consisting of species of varying NPQ mechanisms
and capacities. As a result, the derived parameters represent best-guess
average values for taxonomically diverse phytoplankton assemblages.
Photosynthetic unit size of PSII
We estimated absolute values of the photosynthetic unit size of PSII
(1/nPSII, mol Chl a mol RCII-1) following the approach
suggested by Suggett et al. (2004). In this approach, 1/nPSII is
obtained from FRRF-derived dark-regulated σPSII (Å2 RCII-1) and photosynthetic pigment absorption spectra,
apsp∗ (m2 mg Chl a-1), estimated using the
pigment reconstruction approach.
1/nPSII=σPSIIa‾psp∗⋅0.013453
Here, both σPSII and a‾psp∗ are
specific to the spectral distribution of the FRRF excitation LED. The factor
0.013453 converts milligrams of Chl a to mol Chl a, Å2 to m2, and RCII
to mol RCII, and it is assumed that 50 % of absorbed photons go to PSII
(e.g. Kromkamp and Forster, 2003). The error introduced by this assumption is
difficult to assess, though it should be dependent on species composition,
and is unlikely to be greater than 20 % (Suggett et al., 2004).
14C uptake
Rates of 14C uptake were measured using small volume (20 mL), 2 h
light-response curves in a custom-built photosynthetron. Full details of the
experimental procedure, calculation of rates and fitting of light-response
curves can be found in Schuback et al. (2016, 2017). As for light-response
curves of ETRRCII, we derived values of the maximum
light-saturated capacity of 14C uptake (14C-Pmax)
and the light-dependent increase in 14C uptake
(14C-α). From these two parameters, we were able to derive
14C-uptake rates for the in situ light intensity at the time and
depth of sampling (Table 1), using the exponential model of Webb et
al. (1974).
Multiple studies have demonstrated that short-term 14C-uptake
experiments, as employed here, measure an intermediate quantity between gross
and net production (Halsey and Jones, 2015; Milligan et al., 2015; Pei and
Laws, 2013). For fast-growing, nutrient-replete phytoplankton (OCE17 in this
study), a larger fraction of the initially fixed 14C will be
retained in a transient C pool for longer, such that the measured rate will
be closer to gross productivity. For slow-growing, nutrient-limited
phytoplankton (OSP14 in this study) the turnover time of this transient C
pool is very fast, such that more of the initially fixed 14C will
be respired, and short incubation times will estimate rates closer to net
productivity. It is therefore likely that our derived 14C-uptake
rates at OSP14 are underestimated (closer to a net rate) relative to OCE17
(closer to a gross rate). This complicates the comparison of absolute
14C-uptake rates between the sites in the present study but does
not significantly change our conclusions regarding differences in the diel
cycle of photosynthetic processes.
Spectral correction and derivation of stoichiometries
The spectral distribution of light at 5 m depth (Eis(λ))
was estimated as described in Schuback et al. (2016, 2017). Prior to curve
fitting, absolute values of light intensity used for light-response curves of
14C uptake and ETRRCII (ELED(λ))
were corrected relative to the phytoplankton light absorption spectrum.
EIS=ELED⋅∑400700aphyλELED(λ)⋅∑400700EIS(λ)∑400700aphyλEIS(λ)⋅∑400700ELED(λ)
Here, aphy(λ) is the phytoplankton absorption spectrum
derived from the QFT approach. Values of σPSII, which are
specific to the spectral distribution of excitation and background light in
the FRRF instrument (ELED(λ)), were corrected to the in
situ spectral light distribution at the time and depth of sampling
(EIS(λ)) using the same approach.
The electron requirement for carbon fixation (Φe,C,
mol e- mol C-1, Fig. 1) was calculated by deriving
Chl a-specific rates of electron transport from ETRRCII
(mol e- mol RCII-1 s-1) and 1/nPSII
(mol Chl a mol RCII-1) and dividing these rates by Chl a-specific
rates of 14C uptake (mol C mol Chl a-1 s-1).
Φe,C=ETRRCII/nPSII14C uptake
The minimum value of Φe,C, encountered during light
limitation, was calculated using α values of each rate. The quantum
efficiency of carbon fixation (ΦC, mol C mol photon
absorbed-1, Fig. 1) was calculated from 14C uptake (mg C mg
Chl a-1 h-1) and the product of aphy∗(λ)
(m2 mg Chl a-1) and EIS (λ)
(µmol quanta m-2 s-1) as
ΦC=14C uptake∑400700aphy∗λEIS(λ)⋅0.023129.
The maximum photosynthetic efficiency, ΦC-max, which is achieved
under light-limiting conditions, was calculated from 14C-α
(mg C mg Chl a-1 h-1
[µmol quanta m-2 s-1]-1) and
a‾phy∗ (m2 mg Chl a-1)
ΦC-max=14C-αaphy∗⋅0.023129.
The conversion factor converts hours to seconds, µmol to mol, and mg
C to mol C.
Note that ΦC represents the quantum efficiency of
carbon fixation (mol C mol photon-1), while Φe,C is
generally defined as the electron requirement of carbon fixation
(mol e- mol C-1).
Results and discussion
In the following, we first describe the diurnal variability of the
photosynthetic process during the OCE17 experiment, from light absorption, via
electron transport to carbon fixation (Fig. 1). We then compare the observed
values and diurnal trends from this coastal upwelling regime to results
obtained from a similar study in an iron-limited low-biomass region (OSP14).
Based on this comparative analysis, we discuss the environmental controls on
the regulation of the photosynthetic process, the magnitude and variability
of the electron requirement and quantum efficiency of carbon fixation (Φe,C and ΦC, respectively), and the potential to use
NPQ measurements as a proxy for these important parameters.
Photosynthetic components and their diurnal periodicity during
OCE17
Light absorption characteristics and PSII photo-physiology for the 48 h
diurnal cycle at OCE17 are summarized in Table 2. During our intensive
sampling period, Chl a biomass, derived from ac-s 676 nm absorption light
height calibrated to HPLC [TChl a], remained relatively constant (1.08±0.15µg L-1).
Derived values of 1/nPSII ranged
from 284 to 446 mol Chl a mol RCII-1, which is within the range of
values measured in nutrient-replete cultures and field assemblages using the
oxygen flash yield approach (e.g. Table 2 in Suggett et al., 2010). We
observed no diurnal periodicity in the derived values of 1/nPSII,
indicating that the number of functional RCII was not reduced by severe
photodamage during high midday irradiances (Table 2).
Light absorption characteristics and PSII photo-physiology
(process 1 in Fig. 1) for the 48 h diurnal cycle at OCE17. Surface PAR
(400–700 nm, µmol quanta m-2 s-1) during each
sampling point. Chlorophyll a-specific absorption coefficients for phytoplankton
(a‾phy∗, m2 mg Chl a-1) and photosynthetic
pigment (a‾psp∗, m2 mg Chl a-1), estimated
using the HPLC pigment reconstruction approach and weighted to the spectral
quality of in situ light. The functional absorption cross section of PSII,
derived for the dark-regulated state (σPSII-IS, Å2 RCII-1) and specific to in situ light quantity at each sampling point
(σPSII-IS′, Å2 RCII-1), both corrected to the
spectral quality of in situ light. Estimates of the photosynthetic unit size
of PSII (1/nPSII, mol Chl a mol RCII-1). Fv/Fm,
the maximum quantum efficiency of charge separation in RCII. Fq′/Fv′(500), an estimate of the fraction of “open” reaction centres (QA
oxidized) at a reference irradiance of
500 µmol quanta m-2 s-1. NPQNSV,
normalized Stern–Volmer quenching derived for in situ light intensity at the time
and depth of sampling. NPQNSV, normalized Stern–Volmer quenching
derived at a reference irradiance of
500 µmol quanta m-2 s-1. See methods section and table
1 for details on derivation of these parameters.
Local timeSurface PARa‾phy∗a‾psp∗σPSII-ISσPSII-IS′1/nPSIIFv/FmFq′/Fv′(500)NPQNSVNPQNSV(500)04:0000.0180.0133263263800.590.290.711.5306:0003033030.570.410.761.6008:001750.0170.0143002633130.570.450.821.7410:001883172790.540.520.921.8212:0010540.0190.013252234460.490.571.51.8914:0010333262350.430.641.892.4716:0011250.0210.0123182283990.40.672.22.7718:0011633162210.480.51.832.2220:00240.0190.0143142973370.510.350.982.2622:0002972970.520.30.932.3900:0000.0180.0133033033380.520.30.932.3602:0003063060.520.360.922.3504:0000.0190.0132982983300.510.340.942.1606:0002902900.50.391.022.2908:002700.0170.01333810:0011073222160.470.671.732.1912:0012550.0220.0122712163410.430.652.262.5714:0014312711950.350.732.632.8716:0010850.0190.0133022213480.380.732.182.8718:003473142920.450.581.562.6920:00240.0150.0112722703820.410.481.552.2322:00000:0000.0150.0142682682840.540.270.862.0602:0002772770.50.350.992.68
Phytoplankton absorption coefficients derived from QFT
(a^phy∗) ranged from 0.012 to
0.017 m2 mg Chl a-1. Weighing these estimates to the spectral
distribution of in situ light (a‾phy∗) increased values
by approximately 25 %. No clear diurnal trend was observed in
a‾phy∗.
The use of HPLC-derived absorption spectra allowed us to examine the
contribution of photosynthetic and photoprotective pigments to total light
absorption. The Chl a-specific absorption coefficient of photosynthetic
pigments (a^psp∗) ranged from 0.009 to
0.011 m2 mg Chl a-1, accounting for approximately 75 % of
total phytoplankton absorption. By comparison, Chl a-specific absorption
coefficients for photoprotective pigments, a^ppc∗,
were lower (approximately 25 % of total absorption), ranging from 0.0024
to 0.0046 m2 mg Chl a-1. Both a^psp∗ and
a^ppc∗ increased by approximately 20 % when weighted
to in situ light (a‾psp∗ and a‾ppc∗). We observed diurnal variability in the relative
contribution of these two pigment classes to total absorption, with the
relative contribution of photoprotective carotenoids increasing during
daylight hours (Fig. 3b).
Diurnal variability in light absorption and energy transfer in the
light-harvesting antenna of PSII (Fig. 1, process 1) at the OCE17 site.
(a) PAR estimated for 5 m sampling depth. (b) Ratio of
absorption by photoprotective carotenoids (a‾ppc∗) to
absorption by photosynthetic pigment (a‾psp∗), where
both values are derived from spectral reconstruction of HPLC pigment data.
(b) Values of σPSII-IS′, spectrally corrected to in
situ spectral light quality, derived from FRRF light-response curves at light
levels corresponding to in situ light intensity. (c) Values of
NPQNSV derived from FRRF light-response curves at light levels
corresponding to in situ light intensity at the time and depth of sampling.
(d) Values of Fq′/Fv′ derived from FRRF light-response
curves at a reference background irradiance of
500 µmol quanta m-2 s-1.
In addition to the observed changes in pigment ratios, we observed a notable
diel cycle in the functional absorption cross section, σPSII-IS′, and non-photochemical quenching, NPQNSV,
derived for in situ light intensities (Table 2, Fig. 3c, d). Diurnal
variability in these two parameters reflects regulation in the transfer of
absorbed energy to RCII. The functional absorption cross section exhibited a
rapid decline following the onset of daylight, reaching minimum values at
noon before increasing back to night-time maxima (Fig. 3c).
NPQNSV showed the opposite trend, with maximum values observed
during midday, coincident with the minimum in σPSII-IS′
(Fig. 3d). The strong inverse correlation (Pearson's ρ=0.87, p<0.001, n=22) between σPSII-IS′ and
NPQNSV is expected and demonstrates that NPQNSV is
primarily attributable to thermal dissipation of excess excitation energy in
the antenna (e.g. Xu et al., 2017).
Diurnal cycles in photoprotective pigment content and energy transfer within
the pigment antenna (Fig. 3b–d) act to prevent excess excitation energy from
reaching RCII, thus minimizing potential photodamage (Fig. 1, process 1).
Excitation energy at the level of RCII can also be reduced by increasing the
rate of charge separation and downstream electron transport (Fig. 1,
process 2 and 3). Figure 3e shows the diel pattern in Fq′/Fv′(500),
a variable which estimates the fraction of open RCII at a reference
irradiance level of 500 µmol quanta m-2 s-1. Values of
Fq′/Fv′(500) clearly followed the availability of light, indicating
an increased ability to maximize the number of RCII in the open state
(QA oxidized) during high-light periods. The clear diurnal cycle in
Fq′/Fv′(500) illustrates diurnal regulation of reactions downstream
of light absorption and excitation energy transfer to RCII. This, in turn,
implicates the upregulation of reactions downstream of PSII (Fig. 1,
process 3).
Diurnal variability in light-response curve fit parameters for
ETRRCII (left) and 14C uptake (right) for the OCE17
site.(a) and (b) show PAR at 5 m sampling depths.
(c) and (d) show the maximum light-saturated
capacity Pmax of each rate. (e) and (f) show the
light efficiency of each rate under light limitation, α.
(g) and (h) show the light saturation parameter
Ek of each rate. Note different scales on (a), (b),
(g) and (h).
Parameters derived from ETRRCII and 14C-uptake
light-response curves are shown in Table 3 and Fig. 4. ETRRCII-Pmax ranged from 220 to 884 with a mean of 479 mol e- mol RCII-1 s-1. These values are in good agreement with values from
previous studies (e.g. Hancke et al., 2015; Zhu et al., 2017)
and fall below the theoretical maximum of 1000 mol e- mol RCII-1 s-1 for
linear electron transport (Falkowski and Raven, 1997). Values of
ETRRCII-α ranged from 1.24 to 2.42, with a mean of
1.76 mol e- mol RCII-1 s-1
(µmol quanta m-2 s-1)-1. The Ek of
ETRRCII varied from 160 to 410, with a mean of
262 µmol quanta m-2 s-1.
Light-response curve fit parameters for rates of charge separation
in RCII (ETRRCII) and 14C uptake for the 48 h diurnal
cycle at OCE17. Units of ETRRCII are mol e- mol RCII-1 s-1 and units of
14C uptake are g C g Chl a-1 h-1.
Pmax is the maximum rate at light saturation, α is light
efficiency of each rate under light limitation and Ek is the light
saturation parameter (µmol quanta m-2 s-1). The errors
given are the 95 % confidence intervals for the fit parameter
Pmax and α, as well as the propagated error for Ek. In situ
(IS) represents realized rates derived for in situ light intensities for the time
and depth of sampling. Φe,C is the electron requirement for
carbon fixation (mol e- mol C-1), and ΦC is the quantum
efficiency of carbon fixation (mol C mol photon absorbed-1). The minimum
value of Φe,C and maximum value of ΦC at each
time point are theoretical values describing the acclimation state of the
entire photosynthetic process. In situ (IS) values are realized values of
Φe,C and ΦC derived for in situ light
intensities at the time and depth of sampling.
Clear diurnal periodicity in Pmax, α and Ek of
ETRRCII was observed in response to diurnal changes in light
availability (Fig. 4c, e, g), with all three parameters showing maximum
values during high-irradiance midday periods. In situ light availability at
the time and depth of sampling exceeded the Ek for most of the day,
meaning that ETRRCII at 5 m depth was not light-limited during a
substantial portion of the day (Fig. 4a, g; note different scales on the
panels).
Maximum rates of 14C uptake ranged from 1.17 to 3.54 with a mean of
2.27 g C g Chl a-1 h-1. Based on the high-nutrient and biomass
conditions at OCE17, we assume that phytoplankton growth rate was relatively
high, such that these 2 h 14C-uptake experiments estimated a rate
close to gross primary productivity (e.g. Halsey and Jones, 2015; Milligan et
al., 2015). Values of the light-dependent increase in 14C uptake
(α) ranged from 0.03 to 0.08 g C g Chl a-1 h-1
(µmol quanta m-2 s-1), while the light-saturation
parameter Ek varied between 23 and
72 µmol quanta m-2 s-1 (Table 3, Fig. 4d, f, h). Clear
diurnal trends were apparent in the Pmax of 14C uptake
(Fig. 4d); however, this trend was not observed for α, which
decreased throughout each day (Fig. 4f). Values of Ek of
ETRRCII were always higher than Ek of 14C uptake,
meaning that 14C uptake saturated at light intensities at which
ETRRCII remained light-dependent (Fig. 4c, d; note different
scales on the panels).
An increase in the electron requirement for carbon fixation (Φe,C, mol e- mol C-1) is expected when
14C uptake, but not ETR, is light-saturated. Under such conditions,
additional electrons from charge separation in RCII must be used for
processes other than 14C uptake (Fig. 1). As expected, values of
Φe,C derived for in situ light availability (Table 3, Fig. 5b)
showed a clear diurnal trend, closely following the diurnal change in light
availability. Increased decoupling of 14C uptake and
ETRRCII under excess light (e.g. Corno et al., 2006; Fujiki et
al., 2007; Schuback et al., 2017; Zhu et al., 2017) can be attributed to an
upregulation of alternative electron sinks necessary to alleviate
backpressure along the electron transport chain, once carbon fixation is
light-saturated (e.g. Niyogi, 2000).
The realized electron and photon requirements of carbon fixation
over a 48 h diurnal cycle at the OCE17 site. Values of Φe,C
and 1/ΦC correspond to light conditions at the time and depth of
sampling. Note that we present the photon requirement for carbon fixation,
1/ΦC, instead of the photon efficiency of carbon fixation
(ΦC), to facilitate better comparability with Φe,C.
Figure 5 also shows diurnal trends in the quantum efficiency of carbon
fixation, ΦC. This variable is influenced by the decoupling of
electron transport and carbon fixation (i.e. Φe,C, Fig. 1)
and additionally by variations in the fraction of absorbed light energy
allocated to photochemistry (Fig. 1). Both the decoupling of electron
transport from carbon fixation (Φe,C, Fig. 5a) and the quantum
efficiency of carbon fixation (ΦC, Fig. 5b) showed a clear
dependence on diurnal variation in light availability.
Comparison between OCE17 and OSP14
The light-dependent photosynthetic response is strongly modified by
environmental factors including temperature, nutrient availability, average
light intensity and light history (e.g. Sakshaug et al., 1997).
Micronutrient limitation, most notably iron, has also been shown to exert a
significant effect on light-dependent photosynthetic responses (Greene et
al., 1991, 1992; Roncel et al., 2016; Schuback et al., 2015). Here, we
examine potential iron-dependent effects by comparing absolute values and
diurnal periodicity of components of the photosynthetic process between the
high-productivity coastal waters of OCE17 and the iron-limited NE subarctic
Pacific (OSP14, Schuback et al., 2016). Such a comparison is necessarily
complicated by uncontrolled variability in a number of environmental and
ecological factors, in addition to the iron status of resident phytoplankton
assemblages. Nonetheless, we argue below that a clear signature of
iron-limited physiology emerges from this comparison.
Comparison between environmental and ecological conditions
between sampling sites
Table 4 summarizes hydrographic and biological properties of the two study
sites. Temperature and salinity within the upper mixed layer were similar in
both environments (11.5 ∘C and 32.6 PSU at OCE17, 10.4 ∘C
and 32.4 PSU at OSP14), and the sites had well-defined mixed layers, with a
depth of ∼11 m at OCE17 and ∼33 m at OSP14. Excess
macronutrient concentrations were observed within the mixed layer of both
stations (Table 4). However, micronutrients, most notably iron, were likely
limiting phytoplankton growth at OSP14, thus accounting for the significantly
lower [Chl a] at this site (0.18 µg L-1, as compared to
1.04 µg L-1 at OCE17, Table 4).
Comparison of environmental conditions at
the offshore, iron-limited site OSP14 (17 June 2014) and
the coastal, nutrient-rich site OCE17 (21 August 2017). See text for details on derivation of each variable.
As expected, iron limitation also affected the phytoplankton community
structure. We derived an estimate of phytoplankton community structure using
pigment-based size classes (Claustre, 1994; Uitz et al., 2006; Vidussi et
al., 2001). These estimates revealed that OCE17 was dominated by
microphytoplakton (> 20 µm, ∼67 %), with
∼33 % of the phytoplankton assemblage attributable to the
picophytoplankton size class (0.2–2 µm). Based on the high
concentration of the pigment fucoxanthin, we assume that diatoms dominated
the microphytoplankton size class in this region. Characteristic pigments for
the nanophytoplankton size class (2–20 µm, e.g. cryptophytes,
chromophytes and nanoflagellates) were present in very low concentrations at
the OCE17 site, indicating a negligible contribution of this size to the
phytoplankton assemblage. In contrast to the OCE17 site, the phytoplankton
assemblage at OSP14 was dominated by picophytoplankton (∼46 %),
with an estimated contribution of ∼29 % and ∼25 % for the
nano and micro size classes, respectively. The high concentration of
zeaxanthin found at OSP14 suggests a high proportion of cyanobacteria in the
smallest size class, while the relatively high values of 19′BF and 19′HF
are characteristic for prymnesiophytes and pelagophytes. A summary of the
HPLC pigment data is provided in Supplement S3.
Daylight hours at OSP14 were slightly longer than at OCE17 (∼16 vs.
14 h, respectively), while daily integrated incident photon dose (E0)
was higher at OCE17 (36.21 vs. 31.94 mol quanta m-2). However, given
the greater water column light extinction coefficient (kd, m-1) at
the OCE17 site (1.6 m-1; vs. 0.7 m-1), light availability
calculated for the 5 m sampling depth was similar for the two sites
(Table 4, Fig. 6d). In our analysis, we used instantaneous in situ light
intensities to derive photo-physiological parameters and 14C-uptake
rates from light-response curves. This approach is justified for a direct
comparison of rates and diurnal patterns at a fixed depth. We note, however,
that the deeper mixed layer at OSP14 likely affected the photo-acclimation
status of the phytoplankton assemblage, as a result of stronger variability
in light, as well as lower mean and median mixed layer irradiance levels.
Comparison of light absorption characteristics at the OSP14 and
OCE17 sampling sites. (a) The mean (400–700 nm)
Chl a-specific absorption coefficient of phytoplankton (a^phy∗, m2 mg Chl a-1), showing contribution of
absorption by photosynthetic pigment (a^psp∗) and
photoprotective carotenoids (a^ppc∗).
(b) Photosynthetic unit size of PSII, 1/nPSII
(mol Chl a mol RCII-1). (c) The functional absorption
cross section of PSII, σPSII (Å2 RCII-1),
derived for the dark-regulated state at each time point. In (b) and
(c) the central mark in each box is the median, the edges of the box
are the 25th and 75th percentiles, and the whiskers extend to the range of
all data. No clear diurnal trend in 1/nPSII or
σPSII was detected at either station. (d) Values
of PAR (400–700 nm, µmol quanta m-2 s-1) at
5 m sampling depth. (e) The functional absorption cross
section of PSII, σPSII′ (Å2 RCII-1), measured
at the light-regulated state corresponding to in situ light intensity at each
time point. (f) Non-photochemical quenching, measured at the
light-regulated state corresponding to in situ light intensity at each
time point.
Effects of iron limitation on photo-physiology and diurnal
regulation of photosynthesis
The photosynthetic electron transport chain has a high requirement for iron
(Raven et al., 1999; Yruela, 2013), and iron limitation has been shown to
exert a significant effect on the abundance and stoichiometry of its
components (e.g. Davey and Geider, 2001; Ivanov et al., 2000; Strzepek and
Harrison, 2004). Our data also clearly demonstrate this effect. The mean
Chl a-specific phytoplankton absorption coefficient, a‾phy∗ (m2 mg Chl a-1), was 1.9-fold higher at OSP14
(Fig. 6a). This result can be explained by the smaller cell size and lower
cellular [Chl a] expected in iron-limited phytoplankton, both of which
reduce the packaging effect (Bricaud et al., 1995; Morel and Bricaud, 1981).
We also observed a greater contribution of photoprotective pigments to light
absorption at OSP14 (31 %) relative to OCE17 (22 %) (Fig. 6a). As
discussed below, this result can be explained by the increased requirement
for photoprotection under iron-limited growth conditions.
We found that the number of (iron-rich) PSII per Chl a (nPSII,
mol RCII mol Chl a-1) at OSP14 was approximately half of that observed
at OCE17 (Fig. 6b). To partly compensate for this reduction in RCII, the
dark-regulated functional absorption cross section (σPSII-IS,
Å2 RCII-1) at OSP14 was almost 3 times higher than at OCE17
(Fig. 6c). This physiological response to iron limitation has been frequently
observed in previous studies (Boyd et al., 2000; Kolber et al., 1994; Moore
et al., 2007; Strzepek et al., 2012; Vassiliev et al., 1995).
Increased light absorption and charge separation per RCII observed at OSP14
creates the potential for oversaturation of the reaction centres and
resulting photoinhibition. This, in turn, increases the requirement for
active energy dissipation mechanisms. Indeed, we observed strong diurnal
adjustments in σPSII-IS′ (Fig. 6e) and NPQNSV
(Fig. 6f), caused by active light-dependent regulation of excitation energy
within the pigment antenna. Importantly, the dynamic range of light-regulated
σPSII-IS′ and NPQNSV regulation over a diurnal
cycle was significantly larger at OSP14 than at OCE17 (3-fold vs. 1.5-fold at
OCE17), despite similar light intensities at the two sites (Fig. 6d–f). Our
data therefore suggest an increased need for active regulation of energy
dissipation in response to daily irradiance cycles in iron-limited waters.
Iron limitation comprises the plasticity of the photosynthetic process and
its ability to utilize high light intensities for carbon fixation. However,
this does not lead to the reduction in light absorption, as one might expect
of a system less capable of processing light energy and more susceptible to
damage by excess absorbed light. Rather, we observed an increased capacity
for dissipation of excess absorbed energy through enhanced NPQ. Such a
regulatory mechanism allows phytoplankton to maximize photosynthesis under
low-light conditions, while preventing damage at high irradiances. Our
results support previous observations showing high levels of NPQ in a variety
of iron-limited phytoplankton in laboratory and field studies (e.g. Alderkamp
et al., 2012; Allen et al., 2008; Hoppe et al., 2013; Petrou et al., 2014;
Schallenberg et al., 2019; Schuback et al., 2015; Terauchi et al., 2010;
Vassiliev et al., 1995). A high NPQ signature may thus hold potential as an
optical indicator for phytoplankton physiology and iron-nutrition status in
the oceans (Schallenberg et al., 2019).
Comparison of diurnal trends observed at the OSP14 and OCE17
sampling sites. (a) PAR estimated for 5 m depth.
(b) Rates of initial charge separation in individual RCII
(ETRRCII). (c) Rates of 14C uptake.
(d) The electron requirement for carbon fixation
(Φe,C). (e) The quantum requirement for carbon
fixation (1/ΦC). All rates and efficiencies correspond to in
situ light availability at the time and depth of sampling.
Further evidence of active regulation of excitation energy at the level of
RCII can be seen in the high values and strong light-dependent increase in
ETRRCII observed at OSP14 (Fig. 7b). The high midday rates of
ETRRCII at OSP14 were not balanced by increased
14C uptake (Fig. 7c) and exceeded the maximum theoretical value
for linear electron transport. As described by Schuback et al. (2015, 2016),
upregulation of alternative electron sinks, cyclic electron transport, and
charge recombination may all act to dissipate excess electrons and thereby
prevent over-reduction of RCII. These mechanisms are manifested in an
increase in ETRRCII and can account for the diurnal variation in
the electron requirement of carbon fixation (Φe,C, Fig. 7d),
with peak values observed in the mid-afternoon. Given that our
14C-uptake rates for OSP14 likely represent a lower bound
(corresponding to NPP, as opposed to GPP for OCE17), the absolute values of
Φe,C at OSP14 may be even higher than those presented in
Fig. 7d.
As expected, values of 1/ΦC followed a pattern very similar to
Φe,C, with high values observed under supersaturating light
intensities, and this light-dependent effect enhanced under iron limitation
(Fig. 7c).
NPQ as optical signal
Our simultaneous measurements of light absorption, ETRPSII and
14C uptake allowed us to calculate conversion factors between these
rates and observe variability in the electron requirement,
Φe,C (mol e- mol C-1), and quantum efficiency,
ΦC (mol C mol quanta absorbed-1), of carbon fixation.
Estimates of Φe,C are crucial to derive
high-spatial-resolution carbon-based productivity estimates from FRRF measurements (e.g.
Hughes et al., 2018b; Lawrenz et al., 2013), while the quantum efficiency of
carbon fixation is a key parameter in absorption-based phytoplankton primary
productivity models (Marra et al., 2007; Silsbe et al., 2016; Zoffoli et al.,
2018). Determination of these parameters in the field is labour intensive, and
it is therefore desirable to identify proxies that can be autonomously
monitored at high resolution. Our results suggest that estimates of NPQ, here
derived from FRRF measurements, may provide useful information on both
Φe,C and ΦC. We argue, based on our results and
previous work (Schuback et al., 2014, 2015, 2017), that NPQ is an optical
signal amiable to high-resolution acquisition by autonomous sensors or remote
sensing, which integrates the effects of multiple interacting environmental
variables influencing photosynthetic energy conversion. As discussed in the
following section, this parameter may hold unexploited potential to improve
marine primary productivity estimates.
The electron requirement for carbon fixation, Φe,C
Numerous studies have aimed to quantify variability in Φe,C in
order to derive high-resolution, FRRF-based estimates of phytoplankton
productivity in carbon units (reviewed by e.g. Hughes et al., 2018b; Lawrenz
et al., 2013). These studies have shown that Φe,C can vary
widely, due to physiological regulation on short timescales and taxonomic
shifts on longer temporal or larger spatial scales. In general, higher values
of Φe,C are found under conditions of high excitation pressure
at the level of RCII (high light and/or low nutrients). Indeed, for both
OCE17 and OSP14, maximum Φe,C was observed during
high-irradiance periods in the afternoon, and Φe,C, derived for in
situ light availability, followed PAR levels over the diurnal cycle (Fig. 7d).
However, the diurnal range of Φe,C differed between OCE17
andOSP14, with a significantly larger range and midday maximum in
Φe,C in the iron-limited waters of OPS14 (Fig. 7d). This
result suggests an enhanced need to dissipate excess electron pressure under
iron-limiting conditions.
High excitation pressure also triggers the upregulation of heat dissipation
mechanisms in the pigment antenna (here estimated as NPQNSV), and
several studies have reported a correlation between Φe,C and
NPQNSV (Hughes et al., 2018a; Schuback et al., 2015, 2016b,
2017a; Zhu et al., 2017). We observed such a correlation at both of our
sampling sites (Fig. 8a), but the slope of the NPQNSV:Φe,C correlation differed between the two sites (12.2 for
OCE17 vs. 2.34 for OSP14; Fig. 8a). Several recent studies have similarly
documented variability in the relationship between Φe,C and
NPQNSV. For example, Hughes et al. (2018a) reported
seasonally dependent slopes between NPQNSV and Φe,C at
a sampling site off the coast of Australia. In a previous study (Schuback et
al., 2017), we observed a strong correlation between NPQNSV and
Φe,C/nPSII in the upper mixed layer of the Arctic
Ocean but only very weak NPQNSV and no apparent correlation with
Φe,C/nPSII below the mixed layer.
(a) Correlations between the electron requirement of carbon
fixation, Φe,C and NPQNSV, both derived for in
situ light intensity at the time and depth of sampling for each time point during
daylight hours. OCE17: Φe,C=12.2⋅NPQNSV-4.53; R2=0.68; n=7. OSP14:
Φe,C=2.34⋅NPQNSV+3.74; R2=0.94, n=5. (b) Correlations between the photon requirement of
carbon fixation, 1/ΦC and NPQNSV, both derived for
in situ light intensity at the time and depth of sampling for each time point
during daylight hours. OCE17: 1/ΦC=75⋅NPQNSV-46; R2=0.68; n=7. OSP14:
1/ΦC=23⋅NPQNSV+30; R2=0.94;
n=5.
Differences in experimental procedures and data analysis make it impossible
to directly compare the slopes of
NPQNSV-Φe,C/nPSII relationships between
the different studies. Nonetheless, some general patterns do emerge. A strong
correlation between NPQNSV and Φe,C is likely to
exist in all environments where phytoplankton must adapt to fluctuations in
excitation pressure at the level of RCII. Such conditions result, for
example, from high and fluctuating light intensities, nutrient limitation and
cold temperatures. However, the substantial taxonomic variability in
phytoplankton photosynthetic architecture and photo-physiology (e.g. Campbell
et al., 1998; Kunath et al., 2012) makes it likely that NPQNSV:Φe,C relationships will require regional tuning.
Variability in the NPQNSV:Φe,C relationship may
limit the application of a single global approach to derive carbon-based
productivity from FRRF data. Yet, such variability may hold inherent
information about the physiological state of a phytoplankton assemblage and
the bottom-up controls on primary productivity. For example, phytoplankton
assemblages adapted to growth in high-light and/or low-nutrient environments
appear to show stronger light-dependent increases in NPQNSV than
Φe,C, leading to a change in the slope of the correlation
between these variables. This result reflects preferential changes in the
pigment antenna configurations (leading to heat dissipation as NPQ), over
alterations of the electron transport chain and upregulation of alternative
electron sinks (affecting Φe,C). In this way, the slope of the
NPQNSV:Φe,C correlation may reflect taxonomic
differences in evolutionary strategies to achieve balanced growth under
varying environmental conditions.
The quantum efficiency of carbon fixation, ΦC
The quantum efficiency of carbon fixation (ΦC), also referred to as photosynthetic
efficiency, is defined as carbon fixed per unit of light
absorbed. It is a fundamental biophysical parameter, which is poorly
constrained in models of primary productivity (Hiscock et al., 2008; Silsbe
et al., 2016; Sorensen and Siegel, 2001; Zoffoli et al., 2018). Regional
variability in its maximum value (ΦC-max), achieved under
limiting light conditions, is evident in the comparison of our two study
regions. The significantly lower values we observed at OSP14 (0.038±0.019 mol C mol photon-1) relative to OCE17
(0.078±0.019 mol C mol photon-1) are consistent with laboratory and field
observations showing a lower maximum quantum efficiency under nutrient
limitation and/or low temperatures and high-light environments (Babin et
al., 1996b; Finenko et al., 2002; Marra et al., 2000; Morel, 1978; Ostrowska
et al., 2012; Uitz et al., 2008).
The maximum quantum efficiency of carbon fixation is only achieved when
photosynthesis is light-limited. At higher light intensities, absorbed light
energy is increasingly redistributed to pathways other than
ETRRCII (fluorescence or heat, Fig. 1, process 1), and excess
energy within the electron transport chain is channelled to pathways other
than carbon fixation (thereby increasing Φe,C, Fig. 1,
processes 3 and 4). Consequently, values of ΦC are expected to
correlate with NPQNSV (Fig. 8b) in a manner similar to that
described for Φe,C (Sect. 4.3.1). Indeed, NPQ has been
extensively utilized as a proxy for variability in ΦC in
remote sensing algorithms of terrestrial primary productivity (Gamon et al.,
1997; Garbulsky et al., 2011; Peñuelas et al., 2013). In these
terrestrial applications, light use efficiency (LUE, which is equivalent to
ΦC) is estimated from the photochemical reflectance index
(PRI), a proxy for NPQ derived from changes in reflectance band ratios,
tracking changes in xanthophyll cycle (XC) pigments (e.g. Peñuelas et
al., 2011). Relative to vascular plants, NPQ mechanisms in phytoplankton
appear to be significantly more diverse and are less well understood (e.g.
Goss and Lepetit, 2015; Lavaud and Goss, 2014). It is, therefore, unlikely
that a PRI approach could be successfully applied to mixed phytoplankton
assemblages across contrasting oceanic environments. We note, however, that
light-dependent changes in pigment ratios have previously been correlated to
ΦC in phytoplankton (e.g Babin et al. 1996a; Johnson et al.
2002; Vaillancourt et al., 2003; Prieto et al., 2007; Marra et al., 2000).
Moreover, changes in pigment ratios have been successfully correlated to
absorption band ratios of phytoplankton (Eisner et al., 2003; Eisner and
Cowles, 2005; Méléder et al., 2018; Stuart et al., 2000). These
results suggest that absorption band ratios may hold potential to improve
estimates of ΦC at regional scales.
A mechanistic coupling is expected between photoprotection and ΦC across differing phytoplankton. Indeed, our results show that
estimates of NPQ correlate well to measured values of ΦC
(Fig. 8b), suggesting that NPQ should be further examined as a proxy for
ΦC. In the present study, we determined values of NPQ from
FRRF measurements. However, other approaches to estimate NPQ in marine
phytoplankton exist. These approaches have mostly been developed to correct
for NPQ effects on phytoplankton Chl a biomass estimates from in situ ChlF
sensors (Biermann et al., 2015; Thomalla et al., 2018; Xing et al., 2018),
without fully exploiting the information inherent in this signal.
While previous studies have shown that irradiance provides an easily
measurable proxy for changes in ΦC (Kiefer and Mitchell, 1983;
Silsbe et al., 2016), the response of ΦC to incident light will
be modulated by other environmental factors, including nutrient availability
and temperature. For example, the observed difference in ΦC-max
between OSP14 and OCE17 cannot be explained by differences in
instantaneous light availability, which was similar at the two sites (Fig. 7a).
In contrast, the regional difference we
observed in ΦC-max was well reflected in the extent of the
diurnal NPQ response (Fig. 6f). NPQ thus provides an optical signal
integrating a multitude of environmental controls on the photosynthetic
apparatus and may help constrain variability in ΦC, leading
to improved marine primary productivity estimates.
Conclusions
The photosynthetic process plays a key role in the energy budget of
phytoplankton metabolism, marine ecosystems and the global carbon cycle.
Yet, models of marine primary productivity typically do not adequately
account for the dynamic environmental controls on photosynthesis and
variations in the transfer of absorbed photon energy to organic carbon. The
present study aimed to enhance our understanding of the photo-physiological
mechanisms maintaining energetic balance within the photosynthetic system of
phytoplankton over diurnal timescales in contrasting marine environments.
Our results demonstrate how iron limitation affects the plasticity with
which marine phytoplankton can optimize the use of light energy for carbon
fixation. Low iron availability reduced the ability of phytoplankton to
utilize diurnal increases in absorbed light energy for carbon fixation and
increased the need for effective photoprotection. Based on our data, we
suggest that optical measurements of NPQ hold untapped potential to assess
energy conversion efficiencies and, in turn, increase our ability to monitor
phytoplankton physiology and primary productivity over a range of
ecologically relevant temporal and spatial scales.
Data availability
Data are available under 10.5281/zenodo.2616450 (Schuback, 2019).
The supplement related to this article is available online at: https://doi.org/10.5194/bg-16-1381-2019-supplement.
Author contributions
NS designed and performed the experiments. NS and PDT wrote
the manuscript.
Competing interests
The authors declare that they have no conflict of
interest.
Acknowledgements
We thank the crew and expedition participants of both expeditions, in
particular Mirkko Flecken for assistance during OSP14 and Sarah Rosengard
for help during OCE17. NS would like to thank the students of the “Arctic
Floating University 2018: Terra Novae” research and educational expedition,
which needed so little supervision that she had time to write this
manuscript.
Review statement
This paper was edited by Koji Suzuki and reviewed by two
anonymous referees.
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