A story of resilience: Arctic diatom Chaetoceros gelidus exhibited high physiological plasticity to changing CO2 and light levels

Arctic phytoplankton are experiencing multifaceted stresses due to climate warming, ocean acidification, retreating sea ice, and associated changes in light availability, and that may have large ecological consequences. Multiple stressor studies on Arctic phytoplankton, particularly on the bloom-forming species, may help understand their fitness in response to future climate change, however, such studies are scarce. In the present study, a laboratory experiment was conducted on the bloom-forming Arctic diatom Chaetoceros gelidus (earlier C. socialis) under variable CO₂ (240 and 900 µatm) and light (50 and 100 µmol photons m^-2 s^-1) levels. The growth response was documented using the pre-acclimatized culture at 2°C in a closed batch system over 12 days until the dissolved inorganic nitrogen was depleted. Particulate organic carbon and nitrogen (POC and PON), pigments, cell density, and the maximum quantum yield of photosystem II (Fv/Fm) were measured on day 4 (D₄), 6 (D₆), 10 (D₁₀), and 12 (D₁₂). The overall growth response suggested that C. gelidus maintained a steady-state carboxylation rate with subsequent conversion to macromolecules as reflected in the per-cell POC contents under variable CO₂ and light levels. A substantial amount of POC buildup at the low CO₂ level (comparable to the high CO₂ treatment) indicated the possibility of existing carbon dioxide concentration mechanisms (CCMs) that needs further investigation. Pigment signatures revealed a high level of adaptability to variable irradiance in this species without any major CO₂ effect. PON contents per cell increased initially but decreased irrespective of CO₂ levels when nitrogen was limited (D₆ onward) possibly to recycle intracellular nitrogen resources resulting in enhanced C: N ratios. On D₁₂ the decreased dissolved organic nitrogen levels could be attributed to consumption under nitrogen starvation. Such physiological plasticity could make C. gelidus “ecologically resilient” in the future Arctic.

Introduction

The Arctic Ocean is one of the most vulnerable marine ecosystems to climate change (Smetacek and Nicol, 2005) mainly due to rising temperature (Bintanja, 2018), retreating sea ice, and the associated increase in light penetration (Arrigo et al., 2008; Nicolaus et al., 2012), and the accelerated rate of ocean acidification (OA) (Bellerby, 2017; Qi et al., 2017). Such changing hydrography and physicochemical conditions in the Arctic are affecting phytoplankton dynamics (Ardyna and Arrigo, 2020) and are important to understand. More specifically, light and CO₂ levels may have immediate consequences on the Arctic phytoplankton physiology and carbon cycling. Light is one of the most crucial factors that control phytoplankton bloom in the Arctic waters (Arrigo et al., 2008; Arrigo et al., 2012; Ardyna et al., 2020). An increase in light stress may impede a steady photosynthetic performance (Nixon et al., 2010; Li et al., 2016). Additionally, due to increased light penetration associated with retreating sea ice and stratification, the chances of photoinhibition may enhance (Leu et al., 2016) leading to reduced photosynthetic rates. Diatoms are the major players in phytoplankton bloom development in the Arctic waters (Lovejoy et al., 2002), and changing irradiance levels directly modulate their community dynamics. Croteau et al. (2022) observed that the spring bloom succession is controlled by the shift in growth light optima among the bloom-forming Arctic diatom species. However, the experimental studies revealed that Arctic diatoms possess high photophysiological plasticity to adjust to such fluctuating light levels (Lacour et al., 2018; Lacour et al., 2019; Hoppe, 2021). However, other stress factors like increasing CO₂ levels in combination with variable irradiance may affect the carbon capture potential of the bloom-forming diatoms in the Arctic, and such studies on multiple stressors are scarce from this region.

Persistent low temperatures in the Arctic water are responsible for the quick dissolution of CO₂ and accelerate the rate of ocean acidification compared to other oceanic areas (Barnes and Tarling, 2017). In addition to this, the influx of Pacific low pH waters, and the freshwater input from ice melts are causing a quick rate (with spatial variability) of decreasing surface seawater pH and increasing CO₂ levels (Arctic Monitoring and Assessment Programme: AMAP Assessment, 2018). But how Arctic phytoplankton would respond to such changing pH/CO₂ levels is still not clearly understood and is mostly dependent on their carbon metabolism patterns that are known to be regulated in response to changing carbonate chemistry (Hopkinson et al., 2011; Young and Morel, 2015). Among the dissolved inorganic carbon (DIC) species, the dissolved CO₂ level is usually<1% in the surface ocean whereas, bicarbonate ions (HCO₃^-) contribute to 90% of the oceanic DIC pool. Importantly, for the carboxylating enzyme Rubisco, CO₂ is the sole substrate and its concentration in the surface ocean (10 -12 µmol kg^-1) is significantly lower than its half-saturation constant (40 µmol kg^-1; Badger et al., 1998). To achieve steady state carbon fixation rates, a majority of marine phytoplankton run carbon dioxide concentration mechanisms (CCMs) to maintain a higher ratio of CO₂:O₂ levels in the proximity of Rubisco. Such CCMs can be biophysical or biochemical, although the former mechanism was found to prevail in the natural marine diatom population (Pierella Karlusich et al., 2021). In this process, bicarbonate ions are pumped actively inside the cell (Morel et al., 1994; Badger, 2003) with consequent conversion to CO₂ by a metalloenzyme carbonic anhydrase (CA) (Hopkinson et al., 2011; Reinfelder, 2011). The ongoing increase in surface seawater pCO₂ is expected to facilitate higher diffusive CO₂ influx inside the cell and decrease the diffusive loss of CO₂ from the cell (Reinfelder, 2011). Subsequently, the energy and resource allocation to run CCMs can be downregulated providing energetic savings (Hopkinson et al., 2011) and growth enhancement. Nonetheless, decreasing cellular pH due to enhanced CO₂ influx may also increase dark respiration rates (Wu et al., 2010) resulting in reduced growth. But how Arctic phytoplankton respond to such changing pH/CO₂ levels remains inconclusive.

Previous experimental studies revealed large species-specific variability in their responses to elevated CO₂ levels (Wolf et al., 2017; Kvernvik et al., 2020; Wolf et al., 2022). Some studies documented higher resilience of Arctic diatoms to ocean acidification and increasing irradiance levels (Hoppe et al., 2017; Hoppe et al., 2018a; Hoppe et al., 2018b) compared to the Antarctic species (Hoppe et al., 2015; Heiden et al., 2016). Increasing temperature alone (Coello-Camba et al., 2015) and in combination with ocean acidification were seen to impact the Arctic phytoplankton negatively (Coello-Camba et al., 2014). Open water diatoms showed higher plasticity under elevated CO₂ and light levels compared to a sea-ice diatom (Kvernvik et al., 2020; Wolf et al., 2022). And such variable responses make it difficult to predict whether the cumulative impact of increasing CO₂ and fluctuating irradiance on Arctic diatom physiology would be antagonistic or synergistic. Hence, the responses of bloom-forming diatoms, which contribute substantially to carbon capture, to changing irradiance as well as to higher CO₂ levels are important to address.

The centric diatom Chaetoceros gelidus (earlier known as Chaetoceros socialis) (Chamnansinp et al., 2013) is a significant player in bloom development in the Arctic water (Booth et al., 2002; Balzano et al., 2017) and usually dominates the deep chlorophyll maxima (Martin et al., 2010). Previous experimental studies showed that C. gelidus was capable of adjusting under changing light and CO₂ supply without compromising the growth. The competitiveness of this species was found to be quite high in response to variable light as well as nitrogen sources (Schiffrine et al., 2020). Hoppe et al. (2018a) conducted an onboard incubation experiment on the natural phytoplankton assemblage from the Baffin Bay in summer by mimicking the upwelling event when the phytoplankton from the subsurface (low light) are brought up to the surface (high light). The community was dominated by C. gelidus and showed no significant response to either variable CO₂ (380 and 1000 µatm) or light (15% and 35% incident solar light) levels. In another experiment conducted in the same location (Hussherr et al., 2017) the dominance of this species was noticed in all treatments with a pH range from 7.2 −8.1 indicating their physiological adaptability. In situ observations and onboard experiments on the entire phytoplankton community may not document the response of a particular species to a combination of stress factors. Hence, experimental studies on single species under controlled conditions are needed to improve our mechanistic understanding of their physiological plasticity and may help to envisage the community shift and niche occupancy in the future Arctic. Because, experimental studies on C. gelidus investigating the growth dynamics and carbon capture potential under variable light and CO₂ levels inside controlled laboratory conditions are rare to fill this lacuna, the present experiment was conducted.

Earlier studies on Arctic phytoplankton reveal that experimental setups largely differed in terms of selecting growth conditions like light (continuous or a definite light-dark cycle), temperature (0−8° C), and type (on-deck incubation, or laboratory condition) either in monoculture or natural population. And despite such a wide range of variability in growth conditions, growth responses were comparable under variable CO₂ supply (Hoppe et al., 2018b and references therein). Thus, different experimental conditions may not be a major factor affecting species-specific responses to ocean acidification in the Arctic phytoplankton. In this study, the growth response (elemental composition, pigment signature, and photophysiology) of C. gelidus were planned to be monitored under variable irradiance (50 and 100 µmol photons m^-2 s^-1) and pCO₂ (240 and 900 µatm) levels over 12 days at 2°C temperature under 10:14 hrs light-dark cycle in the laboratory condition. The 12-day growth phase was initially nutrient enriched and the last few days were with depleted nitrogen resources which may not be persistent in the future Arctic except at the end of a phytoplankton bloom. Monitoring this phase was planned to understand 1) how this bloom-forming diatom maintains per cell carbon accumulation and 2) if there was any indication of dissolved organic carbon (DOC) release under such conditions.

Materials and methods

Experimental setup

The present study was conducted at the Biological Oceanography Division, Alfred Wegener Institute of Polar and Marine Research, Bremerhaven, Germany between July –Aug 2015. A chain-forming centric diatom C. gelidus (earlier known C. socialis) strain Cpd2.2014 isolated from the Kongsfjord, Svalbard in 2014, was used for this investigation. Almost 100 L of aged Arctic water (collected from Kongsfjord, Svalbard in 2014, stored at 4°C in dark) was filtered using a 0.2 µm filter connected to a peristaltic pump into the acid-cleaned 20 L carboys and were supplemented with nutrients and trace metal mix according to the F/2 medium. Pre-cleaned Borosilicate 1 L bottles (60 No.) were filled with this water with the help of a clean Tygon tube and kept tightly closed (without headspace) to set “2 light levels × 2 CO₂ levels” (in triplicate) (Figure 1). A CO₂ pipeline with 1000 µatm pCO₂ was used with multi-channels to each bottle with a particular bottle top glass apparatus. pH values (NBS scale) were monitored in each bottle using a pH meter connected to a combined electrode and were calibrated using the standard buffer solutions (NBS). Within overnight, the pH values dropped from their initial value of 8.22 to 7.76 ± 0.004. The details of the carbon chemistry parameters are given in Table 1. The pCO₂ level in the ambient water was calculated as 238 µatm and will be regarded as ≈ 240 µatm (L-CO₂); in the high CO₂ treatment it was 890 µatm and will be regarded as ≈ 900 µatm (H-CO₂).

FIGURE 1

Figure 1 Schematic representation of the experimental pattern showing the replicates (3) and variables for each treatment. The blue and red marked bottles represent the low CO₂ (L-CO₂) and high CO₂ (H-CO₂) levels, respectively. The light and bright yellow shades indicate the low light (LL) and high light (HL) levels. The right side blue shaded boxes show the day of sampling.

TABLE 1

Table 1 Initial and final carbon chemistry parameters (n =3-10) calculated using CO2SYS (Pierrot et al., 2006) over the experimental period (considering salinity 31.62 ± 0.08; dissolved silicate and phosphate levels were 85 µM ± 3.7, 4.50 ± 0.08 µM, respectively, average temperature 2.07 ± 1.3 (n=2684) was recorded over the experimental period).

C. gelidus, strain Cpd2.2014 culture was pre-acclimatized at both L-CO₂ and H-CO₂ levels under two light levels (50 µmol photons m^-2s^-1 and 100 µmol photons m^-2s^-1, white fluorescence light sources measured daily by a Li-COR sensor) for 5 days (> 5 generations at 2 °C (using temperature logger EBI-20-T) inside a temperature-controlled room. A similar protocol was also followed by Wolf et al. (2019). The light levels chosen for this study were within the moderate range and neither growth limiting nor inhibiting. Selecting two extreme light levels may lead to dissimilar growth dynamics and may not be comparable for such an experimental design. The cells were exposed to a 10 hrs light:14 hrs dark cycle. These light and temperature levels resemble the condition in end Aug to September in Svalbard. Wolf et al. (2019) considered 2°C as the present-day temperature. These pre-acclimatized cells were used for the main experiment which continued for 12 days (Figure 1). There were a total of four experimental sets with triplicate for each sampling day. Sampling was done on day zero (D₀), day four (D₄), day six (D₆), day ten (D₁₀), and day twelve (D₁₂) without exposing the cells to any change in temperature and light levels. Individual bottles were completely used for everyday sampling. It was a closed batch culture experiment and the initial pCO₂ level was set on the initial day. Dilute culture (<200 cell mL^-1) was allowed to grow until nutrients and CO₂ levels were exhausted.

Analytical method

Carbon chemistry and dissolved inorganic nutrients

Total alkalinity (TA) values were measured in replicates using an Autotitrator (a titration Center with Titro Line alpha 05 plus, Autosampler TW alpha plus, and Software Titrisoft 2.71) from Schott Instrument GmbH, Germany by potentiometric titration (duplicate analysis) against the certified reference material (Dickson). Dissolved inorganic carbon (DIC) contents were measured using a coulometric acidification module (QuAAtro39 Continuous Segmented Flow Analyzer, SEAL Analytical, Germany) against a certified reference material (Dickson, Scripps Institute of Oceanography, USA). TA and DIC values were used to calculate the pCO₂ and pH using the program CO2SYS (Pierrot et al., 2006) considering the levels of dissolved silicate and phosphate, salinity, and temperature. Dissolved inorganic nutrients were measured following the standard colorimetric methods using a Continuous Segmented Flow Analyzer with TP-2020 Plus, Autosampler, and AACE 7.09 Software from Seal Analytical, Germany against the certified reference materials.

Elemental analysis

For estimating particulate organic carbon (POC) and nitrogen (PON), 50-100 mL of sample water was filtered using a pre-combusted GF/F filter (at 500°C overnight) (25 mm) and stored in a clean Petri dish under -20°C till analysis. Before analysis, the filters were oven-dried at 40°C overnight and analyzed using an elemental analyzer (Euro EA, HEKAtech GmbH, Germany) following the method of Sharp (1974). The POC and PON contents were normalized to their respective filtration volumes. The ratio of C:N (µmol: µmol) was calculated POC and PON contents expressed in µmol L^-1.

The POC-based specific growth rate (µ d^-1) was calculated using the following equation

$\begin{array}{ll}\left({\mu }_{POC}{d}^{-1}\right)=\left[\ln \left(Final POC contents\right) -\ln \left(Initial POC contents\right)\right]\text{/time}\left(d\right)& \text{(1)}\end{array}$

Pigment analysis by high performance liquid chromatography

For pigment analyses, 200-500 mL sample water was filtered using GF/F filters and kept folded in quarters inside a cryo-vial and stored at -80°C till analysis. Pigment samples were extracted in 1.5 mL 99.9% HPLC grade acetone (Merck, Germany) overnight at -20°C. A small aliquot (50 µL) of the synthetic pigment canthaxanthin (95%, HPLC grade, Sigma) was added to each sample (after analysis Canthaxanthin quantity was used to normalize the pigment contents to their extraction volume). To this mixture, a small portion of silica beads (0.5 mm diameter from BioSpec Products, USA) was added and a tissue homogenizer (Precellys 24, France) was used to homogenate (5500 rpm for 20 s) the samples. The samples were cold centrifuged at -10°C for 15 min at 15000 rpm (Eppendorf, Germany). The supernatant was filtered using a 0.2 µm PTFE syringe filter to remove any cell debris and collected in an Eppendorf tube wrapped with aluminum foil to avoid photodegradation. Ammonium acetate buffer (1M) was mixed with an aliquot of sample extract (170 µL) in 1:1 (v/v) ratio before analysis. An HPLC model WATERS 600 (Waters Corporation, USA) fitted with a temperature-controlled autosampler (Waters 717 plus), a photo-diode-Array- Detector (Waters 2998), a fluorescence detector (Waters 2475), and a binary pump (Waters 1525) was used to detect the extracted pigments. A C8 column (4.6 × 100 mm) VARIAN Microsorb-MV 3 from Agilent Technologies, (Inc., Santa Clara, CA, USA) was used for reverse phase HPLC using solvent 1 (a mixture of 70% methanol and 30% ammonium acetate (1 M)) and solvent 2 (100% methanol) from Merck (HPLC grade, Germany). Individual pigments were identified against the retention time of the standard procured from DHI Water and Environment (Netherlands) and the corresponding area was used to calculate the concentration of individual pigment.

Dissolved organic carbon and nitrogen

Samples for dissolved organic carbon (DOC) were collected using a specialized filtration unit which was placed inside a glass cover to avoid contamination. Pre-combusted GF/F filters were used to filter the particulate fraction and collected in a pre-acid cleaned hard plastic bottle at -20°C till analysis. DOC and total dissolved nitrogen (TDN) in the filtrate were determined by high-temperature catalytic oxidation (HTCO) and subsequent non-dispersive infrared spectroscopy and chemiluminescence detection using a Shimadzu TOC-VCPN analyzer fitted with an autosampler. To remove inorganic carbon the samples (6.5 mL) were acidified with HCl and sparged with oxygen for 5 min within the autosampler. 50 µL sample volume was injected directly into the catalyst (heated to 680°C). Final DOC concentrations were average values of triplicate measurements. If the standard variation or the coefficient of variation exceeded 0.1 µM or 1%, respectively, up to 2 additional analyses were performed and outliers were eliminated. After each batch of six samples one DSR (Deep Sea Water Reference Material, Hansell Research Lab, University of Miami, US), one Milli-Q blank, and one potassium hydrogen phthalate standard were measured. The limit of quantification (LOQ) was 7 µM for DOC and 11 µM for TDN and the accuracy was ±5%.

The maximum quantum yield of photosystem II (Fv/Fm)

The photophysiological responses in terms of photosynthetic quantum yield (F_v/Fm) of the diatom culture were measured using a Xenon-PAM fluorometer (WALZ GmbH, Germany) fitted with a magnetic stirrer and temperature control unit. The samples were dark-adapted for 10 min before fluorescence response was measured. The maximum quantum (F_v/F_m) yield was calculated as = (F_m – F₀)/F_m where F_m and F₀ represent the maximum and minimum fluorescence (Krause and Weis, 1991).

Cell density

Samples for cell density measurements (50 mL) were collected and preserved with Lugol’s iodine (4%) and kept in a refrigerator at 4°C. Cells were counted using an “Utermohl counter (3 mL, Hydro-Bios, Kiel, Germany) under an inverted microscope (Carl Zeiss, Germany) under ×400 magnification. The specific growth rate (µ d^-1) was calculated using the following equation:

$\begin{array}{ll}\left({\mu }_{cell no.}{d}^{-1}\right)=\left[\ln \left(Final cell density\right) -\ln \left(Initial cell density\right)\right]\text{/time}\left(d\right)& \text{(2)}\end{array}$

Statistical analysis

The individual data set was checked for normality and variance using the Shapiro-Wilk normality test and F-test, respectively. In case the data sets were normally distributed (null hypothesis accepted), showing equal variance, a two-way Analysis of Variance (ANOVA) with replication was performed for testing the level of significance due to light and CO₂ levels keeping the p-values at 0.05 (95% confidence level). Those parameters did not pass through the former check and revealed a non-normal distribution pattern (rejecting the null hypothesis) of distribution, the nonparametric Two-sample Mann-Whitney-U test was performed to understand if the observed differences were statistically significant (p-values at 0.05; at 95% confidence level).

Results

Growth response

Like other diluted batch culture experiments, the present experiment also started with a very low cell density (<200 cell mL^-1) which increased significantly (approximate 60,000 cell mL^-1) in all treatments over the incubation period (Figure 2A). A clear increase in pH (Table 1) was noticed from D₀ to D₁₂ with concomitant enhancement in cell density, POC and pigment contents in all treatments. The experiment started with POC concentrations<1 µmol L^-1 and within 12 days of the experimental period more than 300 µmol L^-1 POC production was recorded (Figure 2B). There was no statistically significant difference (p>0.05) in POC accumulation rates from the different light and CO₂ levels during the growth phase. Cell density (Figure 2A) and POC concentrations (Figure 2B) showed a typical exponential growth pattern without any significant difference within the treatments (p>0.05) suggesting that increasing CO₂ supply or enhanced light did not impact the cell division rates and carbon biomass accumulation in this diatom. The corresponding growth rates based on the cell density (Figure 2C) and POC contents (Figure 2D) increased exponentially in all treatments and revealed high linearity (p<0.05). This observation suggests that overall growth performance was almost comparable under variable light and CO₂ levels and the rate of cell division was coupled with photosynthetic and POC accumulation rates. The highest growth rates were noticed till D₆ and then there was a significant drop noticed in all treatments. Per cell POC content (Figure 2E) showed the highest values (61 ± 6 pg POC cell^-1) in the last two sampling days and this value was more than 26% higher (p<0.05) than the values (48.8 ± 4 pg POC cell^-1) noted during the first three sampling days.

FIGURE 2

Figure 2 Growth dynamics of C. gelidus over the experimental period (total 12 days, D₀ –D¹²) under two different light conditions [low light (LL) = 50 µmol m^-2 s^-1, high light (HL) =100 µmol m^-2 s^-1] and CO₂ levels [low CO₂ (LC) ≈240 µatm and high CO₂ (HC) ≈900 µatm levels]. (A) cell density; (B) particulate organic carbon (POC) contents; growth rates calculated based on (C) cell number and (D) POC contents; (E) POC contents per cell; (F) particulate organic nitrogen (PON); (G) PON contents per cell; (H) the ratio between POC and PON (C:N) (n =3; ± SD). The level of significance (p-values) related to CO₂ and light levels are shown as C and L, respectively. The gray line demarcates the nitrogen replete and deplete phases.

PON contents showed an exponential increase (Figure 2F) from an initial value of< 0.1 µmol L^-1 up to 13 µmolL^-1. These increasing trends were steady up to D₁₀ in all treatments and did not show any further enhancement. The concentrations of PON per cell (Figure 2G) within D₄ to D₁₀ were comparable and showed an average value of 6 ± 1.2 pg PON cell^-1 and this value was reduced on D₁₂ in all treatments. The average POC: PON values (Figure 2G) within the first three sampling days (9.2 ± 2) were slightly higher than the classical Redfield ratio of 6.63 and got almost doubled in the last two sampling days (19.6 ± 5). There was no statistically significant correlation (p>0.05) found between POC: PON values and light or CO₂ levels.

Photophysiological response

Photosynthetic quantum yield (Fv/Fm)

FigureFv/Fm values in all treatments (Figure 3A) showed a gradual increase from an initial value of 0.37, and the highest values (0.48) were seen on D₁₀ followed by a decrease on D₁₂ (0.4) suggesting the end of the growth phase. There was no statistically significant difference found between the treatments.

FIGURE 3

Figure 3 Photophysiogy and pigment signature of C. gelidus over the experimental period under two different light conditions [low light (LL) = 50 µmol m^-2 s^-1, high light (HL) =100 µmol m^-2 s^-1] and CO₂ levels [low CO₂ (LC) ≈240 µatm and high CO₂ (HC) ≈900 µatm levels]. (A) Fv/Fm values; (B) Chla contents; (C) Chla contents per cell; (D) the ratio between photoprotective and light harvesting pigment contents (PPP : LHP) and (E) diatoxanthin index [DT/(DD+DT)] (n =3; ± SD). The level of significance (p-values) related to CO₂ and light levels are shown as C and L, respectively. The gray line demarcates the nitrogen replete and deplete phases.

Pigment signature

Variable light levels exerted stronger impacts (p<0.05) on Chla concentrations than CO₂ (p>0.05). The concentrations of Chla (Figure 3B) increased from an initial value of< 0.2 µg L^-1 up to 15.7 µg L^-1 over the incubation period. The average Chla concentration up to D₆ was 1.78 ± 1.5 µg L^-1 and a difference (p<0.05) was noticed on D₁₀ when the average concentrations of Chla were 13.5 ± 1.4 µgL^-1and 6.27 ± 0.63 µgL^-1 at L-CO₂ and H-CO₂ treatments, respectively. On D_12, there was a decrease in Chla values in all treatments. The Chla content (3.74 ± 0.6 µgL^-1) in HL incubated cells (considering both CO₂ levels) was ≈ 38% lower than that of LL treatment (p<0.05). Per cell Chla contents (Figure 3C) was 0.44 pg on D₀ and increased linearly up to D₆ and decreased steadily thereafter in all treatments with variability. From D₀ to D₆ per cell Chla values did not reveal any difference between the treatments (p>0.05); however, the values from D₁₀ and D₁₂ were significantly different (p<0.05). The LL incubated cells from both CO₂ levels showed almost three times higher Chla (0.26 ± 0.19 pg cell^-1) contents than that of HL treated cells (0.082 ± 0.05 pg cell^-1) without any significant impact of variable CO₂ levels (p >0.05).

Accessory pigments

The accessory pigments of the diatom were fucoxanthin (Fuco), chlorophyllc₂ (Chlc₂), diadinoxanthin (DD), diatoxanthin (DT), and β-carotene. Among these pigments, the first two are light-harvesting pigments (LHP), and the last three work as photoprotective pigments (PPP). All these pigments showed significant variation in response to light and CO₂ levels. The ratios of PPP : LHP (Figure 3D) were impacted by both light and CO₂ levels (p<0.05). The highest value of PPP : LHP ratio was noticed in the cells grown under L-CO₂-HL treatment (average 0.093) and the minimum values (average 0.036) were seen in the cells incubated at H-CO₂-LL treatments. The H-CO₂ incubated cells showed higher LHP accumulation relative to PPP resulting in a lower PPP : LHP ratio. The values of de-epoxidation states [DT/(DT+DD)] (Figure 3E) were almost half (p<0.05) under the LL treated cells (0.15 ± 0.02) than that of HL (0.33 ± 0.09) and CO₂ levels did not show significant impact (p >0.05) on this ratio.

TDN, DOC, and DON

Total dissolved nitrogen (TDN) concentration was 38.3 ± 3.7 µM in the initial Arctic water and decreased steadily to half on D₁₂ (Figure 4A). To derive the values of dissolved organic nitrogen (DON), the concentrations of DIN were subtracted from the TDN values. DIN (Figure 4B) contributed to almost 36% of TDN and the rest was DON (Figure 4C). The concentrations of DIN showed an exponential declining trend coupled with biomass buildup in all treatments without any significant difference. DIN became almost undetectable in most of the treatments on D₁₂. The initial value of the DON was 24.6 ± 0.11 µM and no significant difference was seen under LL treatments (both CO₂ levels) until D₁₀. However, on D₁₂ almost a 27% decrease in DON concentrations was noticed under both CO₂ levels. In the case of HL-treated cells, the trend of DON values was different than noticed under LL conditions. In L-CO₂-HL treatment, ≈a 20% decrease in DON contents was noticed on D₄ and D₆ but increased again to its initial value on D₁₀ followed by a decline on the final day. Under H-CO₂-HL treatment, a significant decrease in DON was noticed on D₆ and the level increased again on D₁₀ followed by a further decrease on D₁₂. The average values of DON noticed on D₁₂ in all treatments were significantly (p<0.05) lower (28%) than the initial values.

FIGURE 4

Figure 4 (A) total dissolved nitrogen (TDN) contents; (B) dissolved inorganic nitrogen (DIN) contents; (C) dissolved organic nitrogen (DON); (D) dissolved organic carbon contents (DOC); (E) the ratio of DOC : DON; (F) the ratio of POC : DOC over the experimental period under two different light conditions [low light (LL) = 50 µmol m^-2 s^-1, high light (HL) =100 µmol m^-2 s^-1] and CO₂ levels [low CO₂ (LC) ≈240 µatm and high CO₂ (HC) ≈900 µatm levels] (n =3; ± SD). The level of significance (p-values) related to CO₂ and light levels are shown as C and L, respectively. The gray line demarcates the nitrogen replete and deplete phases.

The initial DOC concentration (Figure 4D) in the Arctic water was nearly 170 ± 5 µM. On D₄, DOC concentrations showed negligible variability (<1%) from the initial concentrations (p>0.05). Minor variability was seen under LL conditions on D₆ from the concentrations noticed on D₄. However, under HL, the decrease in DOC concentrations was >8% and ≈ 20% from the previous day. DOC values did not change beyond 5% on D₁₀ in all treatments and there was no statistically significant variability among the treatments. On the last day (D₁₂), DOC concentrations decreased to 30 – 40 µM in all treatments corresponding to a 27% decrease from the initial average but without any statistical significance based on light or CO₂ levels. DON and DOC revealed a linear positive correlation (p<0.05) and the ratio of DON : DOC (Figure 4E) varied close to 7.28 on average.

The ratio of POC : DOC (Figure 4F) was extremely low (0.005 ± 0.0012) on the initial day. With the progression of the experiment, POC concentration increased with a corresponding enhancement in POC : DOC ratio, and an eight-fold enhancement was noticed on D₄. A clear exponential increase was noticed in POC : DOC ratio and the maximum value (≈2.5) was seen on D₁₂. The decrease in DOC on the last day with a concomitant increase in POC probably resulted in such a considerable increase in this ratio.

Discussion

Growth under nutrient-enriched phase

The overall growth response depicted that the Arctic diatom C. gelidus can grow efficiently at low as well as high pH/CO₂ levels without compromising its carboxylation and cell division rates. Such observation indicates that the CO₂ resilience of marine diatoms can be natural in some diatoms, and the strategy for resilience could be species-specific (Valenzuela et al., 2021). The photosynthetic performance as reflected in POC content per cell was comparable under both CO₂ levels. Likewise, Hoppe et al. (2018b) documented a change in pCO₂ level from 240 to 970 µatm yielded no significant difference in net primary production under nutrient-enriched conditions in an Arctic phytoplankton community. However, there was high species-specific as well as strain-specific diversity in the observed responses. Wolf et al. (2017) noticed that variable pCO₂ (180 -1400 µatm) levels did not impact per cell POC production at 3°C in the Arctic diatom assemblage containing C. gelidus (mentioned as C. socialis). These observations hinted at the possibility of existing highly efficient mechanisms for acquiring and fixing sufficient CO₂ even at a very low pCO₂ level. As has been mentioned earlier that marine diatoms use efficient and diverse CCMs to accumulate higher CO₂ levels over O₂ close to Rubisco (Hopkinson et al., 2016; Young et al., 2016; reviewed by Matsuda et al., 2017), and similar mechanisms may also exist in this diatom.

Although CCMs components were not investigated in this study, the possibility of operating CCMs becomes obvious from the final POC value, particularly in the low CO₂ treatment. The accumulated POC can be considered as the net organic carbon buildup preceded by carboxylation excluding respiratory loss and DOC leaching if any. Importantly, POC : DOC ratio indicated insignificant DOC leaching compared to POC production in this diatom under both CO₂ levels. At the L-CO₂ treatment, the final POC content (303 µmol L^-1 or 296 µmol kg^-1) was about 20 times higher than the initial CO₂ concentration (14 µmol kg^-1) and importantly, CO₂ was not supplemented further. Considering the final CO₂ concentration (≈ 2 µmol kg^-1) from the L-CO₂ treatment, almost 280 µmol of CO₂ seemed to be acquired via CCMs mostly utilizing abundant bicarbonate ions. However, there could be some diffusive loss of CO₂ too. This fact strengthened the possibility of operating CCMs in C. gelidus. During a spring diatom bloom in the Western Antarctic Peninsula, it was observed that when CO₂ concentration was less than 6 µM, CCMs could supply CO₂ almost at the Rubisco saturation level (Kranz et al., 2015). Similarly, in the present study, C. gelidus was likely to perform a steady carbon fixation rate under the pCO₂ level that was much lower than the atmospheric level, particularly after D₆ when the CO₂ level dropped to<6 µmol kg^-1. Nevertheless, the absence of any CO₂ fertilization impact on growth parameters indicated that the diatom species did not benefit from increased CO₂ supply. As has been hypothesized (Hopkinson et al., 2011 and references therein) that a higher diffusive CO₂ influx could benefit cells by increasing CO₂ supply, decreasing diffusive CO₂ loss, and downregulating the functioning of CCMs to save the energetic cost and collectively may increase carboxylation and growth rates. However, it has been observed that not all phytoplankton show such growth impacts in response to enhanced CO₂ supply (Tortell et al., 2008; Hoppe et al., 2018a). Likewise, the study by Tortell et al. (2008) noted that the DIC uptake was not correlated with in situ pCO₂ variabilities in a phytoplankton community from the Ross Sea (Southern Ocean). In the same study, the authors observed no impact of an eight-fold increment in pCO₂ supply on the bicarbonate uptake rate. Such observation indicates that DIC acquisition via CCMs may not be altered for all phytoplankton at the elevated CO₂ supply and even if CCMs downregulation occurs, that may not change polar diatom growth rates (Young et al., 2015).

Other than acquiring CO₂ via CCMs, the type of Rubisco present in phytoplankton is also responsible to a large extent for fixing CO₂ efficiently. Diatoms possess one of the most proficient forms of Rubisco (red algal type ID) (Young et al., 2016) and it was found that Rubisco in some Arctic diatoms including C. gelidus possesses a high specificity factor for CO₂ relative to O₂ (Valegård et al., 2018).

Growth under nitrogen limitation

The growth phase was mostly declined by nitrogen depletion. The observed growth response during this period when the pCO₂ levels were already low in all treatments, may not be comparable to nitrogen limitation under the ocean acidification scenario (Table 1). And this phase was monitored, particularly to know if POC : DOC fractionation was impacted in C. gelidus. Under nitrogen limitation when synthesizing nitrogenous macromolecules like proteins become constrained, marine diatoms may release a high amount of DOC relative to POC (Myklestad, 2000). In this study, due to the presence of natural DOC in the Arctic water, the initial DOC level was higher than POC contents (low POC : DOC ratio). With the progression of the growth phase POC : DOC ratio increased significantly suggesting insignificant DOC leaching throughout the growth phase. Likely, C. gelidus was capable of converting fixed carbon to storage macromolecules under depleted nitrogen levels.

A simple mass balance calculation based on the classical Redfield ratio shows that under ideal conditions, 16 µmol of DIN is needed to accumulate 106 µmol of POC. Likewise, to produce 300 µmol POC (as seen at the end of the growth phase) ≈ 45 µmol of DIN shall be needed. But the amount of DIN was one-third of it and was consumed within six days of cultivation. PON contents per cell increased from D₀ to D₆ coupled with depleted DIN levels suggesting a steady nitrogen uptake during the exponential growth phase. However, it is likely that after D₆ the growth of C. gelidus was mostly nitrogen limited, yet POC content per cell did not decrease suggesting that carbon fixation and storage were unaffected. Similarly, Li et al. (2012) reported in a model diatom that under low and high CO₂ levels with sufficient nitrogen supply, per cell POC and PON contents did not show any significant change. However, the authors noticed a considerable decrease in per-cell nitrogen content under similar treatments when nitrogen supply was insufficient and thus supports the present study. Diatoms possess several strategies to overcome nitrogen starvation (Smith et al., 2019) and the cellular amino acid pool may be recycled to provide a nitrogen source to the cell (Alipanah et al., 2015).

Diatoms use stored carbon usually as chrysolaminarin or lipids (Kroth et al., 2008) and under nitrogen starvation, they reprogram the storage carbon from nitrogenous compounds like proteins and nucleic acid to neutral lipids (Valenzuela et al., 2012). It was recorded in a model marine diatom that under nitrogen stress, the cell allocated more nitrogen towards nitrogen assimilation enzymes compared to the photosynthetic apparatus, and the freshly produced carbon is utilized to synthesize more lipids (Levitan et al., 2014). Consequently, POC would increase at the cost of PON leading to a higher POC : PON ratio and is in agreement with our observation, particularly after D₆ (Figure 2H). Alipanah et al. (2015) also noticed a significant increase in POC : PON ratio in a model diatom under nitrogen exhaustion. Importantly, phytoplankton may also utilize Rubisco as a nitrogen reservoir under nitrogen stress and may recycle cellular organic nitrogen (Herrig and Falkowski, 1989). And high Rubisco contents (˜36%) as has been seen in Arctic diatoms (Gerecht et al., 2019) could be advantageous under nitrogen starvation. However, the existence of such nitrogen metabolism in C. gelidus is subjected to further investigation. Diatoms may also uptake organic nitrogen under nitrogen limitation (Cochlan et al., 2008) and also possess an animal-like urea cycle (Armbrust et al., 2004; Allen et al., 2011). Schiffrine et al. (2020) noticed that C. gelidus (strain RCC2046, Beaufort Sea isolate) was able to grow only at urea in the absence of other nitrogen sources. On D₁₂ the decline in DON contents under undetectable DIN content indicated probable DON consumption to supplement inorganic nitrogen. Likewise, it was observed in the Arctic that, DON may support nearly 60% of the primary production in the top 10 m of the water column (Le Fouest et al., 2013).

Photophysiological response

Arctic phytoplankton, particularly diatoms (Lacour et al., 2019) are highly efficient in adjusting to fluctuating light and are capable of keeping their photosynthetic apparatus functional over the dark winter period (Hoppe, 2021). In the present study, the comparable Fv/Fm values under variable light and CO₂ levels suggested that C. gelidus efficiently maintained photophysiological performances. Croteau et al. (2022) conducted a study on five ecologically important diatoms from the Arctic waters and revealed that C. gelidus showed necessary photoadaptable strategies to bloom in the subsurface chlorophyll maxima. A drop in Fv/Fm values on D₁₂ can be attributed to nitrogen limitation that may potentially impact photosystem II functioning (Falkowski et al., 2017).

Marine diatoms respond quickly to fluctuating light via short-term photoacclimation processes without compromising their photosynthetic performance (Raven and Geider, 2003). Diatoms predominantly use a xanthophyll cycle containing DD. Under light stress, the de-epoxidation of DD to DT is initiated by the pH gradient of the thylakoid (Lavaud et al., 2002) to dissipate excessively absorbed light energy as heat in a non-radiative process (non-photochemical quenching; NPQ) which is usually indicated by the occurrence of DT (Lavaud et al., 2007; Niyogi and Truong, 2013). In the present experiment, DT production under HL was significantly higher than observed in the LL-treated cells suggesting the activation of NPQ. Croteau et al. (2020) reported that C. gelidus exhibited higher DT production and NPQ when grown under 50 µmol photons m^-2 s^-1 compared to that of 15 µmol photons m^-2 s^-1 at close to freezing temperature. Similar results were also noticed in other bloom-forming Arctic diatoms (Lacour et al., 2018; Lacour et al., 2019). Unaffected growth under variable light and CO₂ levels were also reported in other marine diatoms (Ihnken et al., 2011; Valenzuela et al., 2018) including C. gelidus from the Arctic (Hoppe et al., 2018b). Kvernvik et al. (2020) and Wolf et al. (2022) showed that the open water diatoms grew better under the combined stress of light and CO₂ compared to sea ice diatoms in the Arctic. Contrarily, a few studies reported that variable light intensity-induced NPQ can be modulated by CO₂ levels in some marine diatoms (Hoppe et al., 2015 and references therein).

The occurrences of the minimum Chla contents in the HL-treated cells irrespective of CO₂ levels suggested that light-harvesting was downregulated in response to enhanced photons flux density from 50 to 100 µmol m^-2 s^-1 (Geider et al., 1996; Falkowski and Chen, 2003; Brunet et al., 2011). Likewise, a significant decrease in per cell Chla content was noticed in a marine diatom after eight-fold increased light intensity from 50 µmol m^-2s^-1 (Li and Campbell, 2013). Contrarily, when photons flux density is below growth saturating levels, Arctic diatoms increase light harvesting pigment contents and downregulate photoprotective pigment synthesis (Lacour et al., 2019) as noticed in the present study. The bulk and per cell Chla contents increased linearly up to D₆ (nitrogen replete phase) and these trends reversed with depleting nitrogen levels. Chlorophyll synthesis is directly dependent on nitrogen availability (Geider et al., 1997) and can be downregulated while upregulating the synthesis of photoprotective carotenoids under nitrogen stress. Under the combined stress of nitrogen limitation and light marine diatom upregulate photoprotection related genes (Alipanah et al., 2015). Decreased per cell Chla and photosynthetic rates under nitrogen starvation to adjust to elevated CO₂ levels were recorded in a model marine diatom (Hennon et al. (2014). In C. gelidus likely that photosynthesis remained steady as per cell POC contents remained unaffected in response to elevated CO₂ levels, changing irradiance, and depleted nitrogen resources. Because of such fitness to climate change variables, C. gelidus could be a potential bloom-forming species in the future Arctic water.

Conclusions

In the Arctic, besides increasing temperature, light, and CO₂ levels are the most rapidly varying climate change variables that control phytoplankton growth. Specifically, the accelerated rate of ocean acidification is an alarming issue. Thus, phytoplankton response study to multiple stressors is an important issue to investigate. Any species showing resilience to these factors may be successful in growing in future Arctic waters. We show that the bloom-forming Arctic diatom C. gelidus is resilient to changing CO₂ and light levels and are consistent with earlier reports. The high light level chosen for this experiment was not at the inhibitory level, and variable light alone and in combination with increasing CO₂ levels did not alter photosynthetic performances. The overall results also depict that the photosynthetically fixed carbons were subsequently converted to biomass as POC contents increased and there was no indication of enhanced DOC leaching. Comparable POC contents per cell under the variable CO₂ levels suggested that C. gelidus did not benefit from increasing CO₂ levels. The signal of DON consumption under nitrogen starvation is an important observation and needs to be investigated further. Such a high level of physiological plasticity in carbon and nitrogen metabolism can make C. gelidus an “ecologically resilient” species in the future Arctic water. However, further studies at the molecular level on this species are highly recommended to improve our mechanistic understanding of its carbon and nitrogen metabolism under multiple stressors.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author.

Author contributions

The author has written the research proposal, secured the funding and conducted the experiment including the major analysis. The data interpretation and manuscript preparation was also done by the author. The other academic and technical help from the host laboratory has been acknowledged.

Acknowledgment

This study was funded by Deutscher Akademischer Austauschdienst (DAAD) or German Government Exchange service under the re-invitation program, 2015 for former long-term fellowship holders. The laboratory facilities and other technical support were provided by the Biological Oceanography Division, Alfred Wegener Institute of Polar and Marine Research (AWI). The active support provided by Professor Anya Waite to get this funding and also to conduct the entire work at AWI is thankfully acknowledged. I am particularly thankful to Mrs. Susanne Spahic for her tireless effort to execute this experiment. I also acknowledge the kind support provided by Dr. Boris Koch (Ecological Chemistry Division, AWI) for analyzing the dissolved organic carbon and nitrogen and also for his scientific advice regarding data interpretation. All technical support and scientific advice for experimental planning extended by Drs. Bjorn Rost and Sebastian Rokitta are gratefully acknowledged. The active support from Mrs. Tanja Glawatty to complete this endeavor is highly appreciated. The technical assistance provided by Ms. Claudia Burau, Ms. Christiane, and Ms. Sonja is thankfully acknowledged. I am also thankful to the director of CSIR-NIO for his encouragement and support. The NIO contribution number is 6986. The valuable comments and suggestions by the anonymous reviewers are gratefully acknowledged.

Conflict of interest

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

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References

Alipanah, L., Rohloff, J., Winge, P., Bones, A. M., Brembu, T. (2015). Whole-cell response to nitrogen deprivation in the diatom Phaeodactylum tricornutum. J. Exp. Bot. 66 (20), 6281–6296. doi: 10.1093/jxb/erv340

PubMed Abstract | CrossRef Full Text | Google Scholar

Allen, A. E., Dupont, C. L., Oborník, M., Horák, A., Nunes-Nesi, A., McCrow, J. P., et al. (2011). Evolution and metabolic significance of the urea cycle in photosynthetic diatoms. Nature 473 (7346), 203–207. doi: 10.1038/nature10074

PubMed Abstract | CrossRef Full Text | Google Scholar

Arctic Monitoring and Assessment Programme: AMAP Assessment (2018). Arctic Ocean acidification, Tromsø, Norway.

Google Scholar

Ardyna, M., Arrigo, K. R. (2020). Phytoplankton dynamics in a changing Arctic ocean. Nat. Climate Change 10 (10), 892–903. doi: 10.1038/s41558-020-0905-y

CrossRef Full Text | Google Scholar

Ardyna, M., Mundy, C. J., Mills, M. M., Oziel, L., Grondin, P. L., Lacour, L., et al. (2020). Environmental drivers of under-ice phytoplankton bloom dynamics in the Arctic ocean. Elementa: Sci. Anthropocene 8, 1–21. doi: 10.1525/elementa.430

CrossRef Full Text | Google Scholar

Armbrust, E. V., Berges, J. A., Bowler, C., Green, B. R., Martinez, D., Putnam, N. H., et al. (2004). The genome of the diatom Thalassiosira pseudonana: ecology, evolution, and metabolism. Science 306 (5693), 79–86. doi: 10.1126/science.1101156

PubMed Abstract | CrossRef Full Text | Google Scholar

Arrigo, K. R., Perovich, D. K., Pickart, R. S., Brown, Z. W., Van Dijken, G. L., Lowry, K. E., et al. (2012). Massive phytoplankton blooms under Arctic sea ice. Science 336 (6087), 1408–1408. doi: 10.1126/science.1215065

PubMed Abstract | CrossRef Full Text | Google Scholar

Arrigo, K. R., van Dijken, G., Pabi, S. (2008). Impact of a shrinking Arctic ice cover on marine primary production. Geophysical Res. Lett. 35 (19), 1–6. doi: 10.1029/2008GL035028

CrossRef Full Text | Google Scholar

Badger, M. (2003). The roles of carbonic anhydrases in photosynthetic CO2 concentrating mechanisms. Photosynthesis Res. 77 (2), 83–94. doi: 10.1023/A:1025821717773

CrossRef Full Text | Google Scholar

Badger, M. R., Andrews, T. J., Whitney, S. M., Ludwig, M., Yellowlees, D. C., Leggat, W., et al. (1998). The diversity and coevolution of rubisco, plastids, pyrenoids, and chloroplast-based CO2-concentrating mechanisms in algae. Can. J. Bot. 76 (6), 1052–1071. doi: 10.1139/b98-074

CrossRef Full Text | Google Scholar

Balzano, S., Percopo, I., Siano, R., Gourvil, P., Chanoine, M., Marie, D., et al. (2017). Morphological and genetic diversity of Beaufort Sea diatoms with high contributions from the Chaetoceros neogracilis species complex. J. Phycology 53 (1), 161–187. doi: 10.1111/jpy.12489

CrossRef Full Text | Google Scholar

Barnes, D. K., Tarling, G. A. (2017). Polar oceans in a changing climate. Curr. Biol. 27 (11), R454–R460. doi: 10.1016/j.cub.2017.01.045

PubMed Abstract | CrossRef Full Text | Google Scholar

Bellerby, R. G. (2017). Ocean acidification without borders. Nat. Climate Change 7 (4), 241–242. doi: 10.1038/nclimate3247

CrossRef Full Text | Google Scholar

Bintanja, R. (2018). The impact of Arctic warming on increased rainfall. Sci. Rep. 8 (1), 1–6. doi: 10.1038/s41598-018-34450-3

PubMed Abstract | CrossRef Full Text | Google Scholar

Booth, B. C., Larouche, P., Bélanger, S., Klein, B., Amiel, D., Mei, Z. P. (2002). Dynamics of chaetoceros socialis blooms in the north water. Deep Sea Res. Part II: Topical Stud. Oceanography 49 (22-23), 5003–5025. doi: 10.1016/S0967-0645(02)00175-3

CrossRef Full Text | Google Scholar

Brunet, C., Johnsen, G., Lavaud, J., Roy, S. (2011). “Pigments and photoacclimation processes,” in Phytoplankton pigments: Characterization chemotaxonomy and applications in oceanography. Eds. Roy, S., Llewellyn, C. A., Egeland, E. S., Johnsen, G. (Cambridge: Cambridge University Press), 445–471.

Google Scholar

Chamnansinp, A., Li, Y., Lundholm, N., Moestrup, Ø. (2013). Global diversity of two widespread, colony-forming diatoms of the marine plankton, Chaetoceros socialis (syn. c. radians) and chaetoceros gelidus sp. nov. J. Phycology 49 (6), 1128–1141. doi: 10.1111/jpy.12121

CrossRef Full Text | Google Scholar

Cochlan, W. P., Herndon, J., Kudela, R. M. (2008). Inorganic and organic nitrogen uptake by the toxigenic diatom pseudo-nitzschia australis (Bacillariophyceae). Harmful Algae 8 (1), 111–118. doi: 10.1016/j.hal.2008.08.008

CrossRef Full Text | Google Scholar

Coello-Camba, A., Agustí, S., Holding, J., Arrieta, J. M., Duarte, C. M. (2014). Interactive effect of temperature and CO2 increase in Arctic phytoplankton. Front. Mar. Sci. 1. doi: 10.3389/fmars.2014.00049

PubMed Abstract | CrossRef Full Text | Google Scholar

Coello-Camba, A., Agustí, S., Vaqué, D., Holding, J., Arrieta, J. M., Wassmann, P., et al. (2015). Experimental assessment of temperature thresholds for Arctic phytoplankton communities. Estuaries coasts 38 (3), 873–885. doi: 10.1007/s12237-014-9849-7

CrossRef Full Text | Google Scholar

Croteau, D., Guérin, S., Bruyant, F., Ferland, J., Campbell, D. A., Babin, M., et al. (2020). Contrasting nonphotochemical quenching patterns under high light and darkness aligns with light niche occupancy in Arctic diatoms. Limnology Oceanography 66, S231–S245. doi: 10.1002/lno.11587

CrossRef Full Text | Google Scholar

Croteau, D., Lacour, T., Schiffrine, N., Morin, P. I., Forget, M. H., Bruyant, F., et al. (2022). Shifts in growth light optima among diatom species support their succession during the spring bloom in the Arctic. J. Ecol 110 (6), 1356–1375. doi: 10.1111/1365-2745.13874

CrossRef Full Text | Google Scholar

Falkowski, P. G., Chen, Y. B. (2003). “Photoacclimation of light harvesting systems in eukaryotic algae,” in Light-harvesting antennas in photosynthesis (Dordrecht: Springer), 423–447.

Google Scholar

Falkowski, P. G., Lin, H., Gorbunov, M. Y. (2017). What limits photosynthetic energy conversion efficiency in nature? lessons from the oceans. Philos. Trans. R. Soc. B: Biol. Sci. 372 (1730), 20160376. doi: 10.1098/rstb.2016.0376

CrossRef Full Text | Google Scholar

Geider, R. J., MacIntyre, H. L., Kana, T. M. (1996). A dynamic model of photoadaptation in phytoplankton. Limnology Oceanography 41 (1), 1–15. doi: 10.4319/lo.1996.41.1.0001

CrossRef Full Text | Google Scholar

Geider, R. J., MacIntyre, H. L., Kana, T. M. (1997). Dynamic model of phytoplankton growth and acclimation: responses of the balanced growth rate and the chlorophyll a: carbon ratio to light, nutrient-limitation and temperature. Mar. Ecol. Prog. Ser. 148, 187–200. doi: 10.3354/meps148187

CrossRef Full Text | Google Scholar

Gerecht, A. C., Eriksen, G. K., Uradnikova, M., Eilertsen, H. C. (2019). High ribulose-1, 5-bisphosphate carboxylase/oxygenase content in northern diatom species. bioRxiv 569285. doi: 10.1101/569285

CrossRef Full Text | Google Scholar

Heiden, J. P., Bischof, K., Trimborn, S. (2016). Light intensity modulates the response of two Antarctic diatom species to ocean acidification. Front. Mar. Sci. 3. doi: 10.3389/fmars.2016.00260

CrossRef Full Text | Google Scholar

Hennon, G. M., Quay, P., Morales, R. L., Swanson, L. M., Virginia Armbrust, E. (2014). Acclimation conditions modify physiological response of the diatom Thalassiosira pseudonana to elevated CO₂ concentrations in a nitrate-limited chemostat. J. Phycology 50 (2), 243–253. doi: 10.1111/jpy.12156

CrossRef Full Text | Google Scholar

Herrig, R., Falkowski, P. G. (1989). Nitrogen limitation in Isochrysis galbana (haptophyceae). i. photosynthetic energy conversion and growth efficiencies¹. J. Phycology 25 (3), 462–471. doi: 10.1111/j.1529-8817.1989.tb00251.x

CrossRef Full Text | Google Scholar

Hopkinson, B. M., Dupont, C. L., Allen, A. E., Morel, F. M. (2011). Efficiency of the CO2-concentrating mechanism of diatoms. Proc. Natl. Acad. Sci. 108 (10), 3830–3837. doi: 10.1073/pnas.1018062108

CrossRef Full Text | Google Scholar

Hopkinson, B. M., Dupont, C. L., Matsuda, Y. (2016). The physiology and genetics of CO2 concentrating mechanisms in model diatoms. Curr. Opin. Plant Biol. 31, 51–57. doi: 10.1016/j.pbi.2016.03.013

PubMed Abstract | CrossRef Full Text | Google Scholar

Hoppe, C. J. (2021). Always ready? primary production of Arctic phytoplankton at the end of the polar night. Limnology Oceanography Lett. 7 (2), 167–174. doi: 10.1002/lol2.10222

CrossRef Full Text | Google Scholar

Hoppe, C. J., Holtz, L. M., Trimborn, S., Rost, B. (2015). Ocean acidification decreases the light-use efficiency in an Antarctic diatom under dynamic but not constant light. New Phytol. 207 (1), 159–171. doi: 10.1111/nph.13334

PubMed Abstract | CrossRef Full Text | Google Scholar

Hoppe, C. J. M., Schuback, N., Semeniuk, D., Giesbrecht, K., Mol, J., Thomas, H., et al. (2018a). Resistance of Arctic phytoplankton to ocean acidification and enhanced irradiance. Polar Biol. 41 (3), 399–413. doi: 10.1007/s00300-017-2186-0

PubMed Abstract | CrossRef Full Text | Google Scholar

Hoppe, C. J., Schuback, N., Semeniuk, D. M., Maldonado, M. T., Rost, B. (2017). Functional redundancy facilitates resilience of subarctic phytoplankton assemblages toward ocean acidification and high irradiance. Front. Mar. Sci. 4. doi: 10.3389/fmars.2017.00229

CrossRef Full Text | Google Scholar

Hoppe, C. J. M., Wolf, K. K., Schuback, N., Tortell, P. D., Rost, B. (2018b). Compensation of ocean acidification effects in Arctic phytoplankton assemblages. Nat. Climate Change 8 (6), 529–533. doi: 10.1038/s41558-018-0142-9

CrossRef Full Text | Google Scholar

Hussherr, R., Levasseur, M., Lizotte, M., Tremblay, J.É., Mol, J., Thomas, H., et al. (2017). Impact of ocean acidification on Arctic phytoplankton blooms and dimethyl sulfide concentration under simulated ice-free and under-ice conditions. Biogeosciences 14 (9), 2407–2427. doi: 10.5194/bg-14-2407-2017

CrossRef Full Text | Google Scholar

Ihnken, S., Roberts, S., Beardall, J. (2011). Differential responses of growth and photosynthesis in the marine diatom chaetoceros muelleri to CO₂ and light availability. Phycologia 50 (2), 182–193. doi: 10.2216/10-11.1

CrossRef Full Text | Google Scholar

Kranz, S. A., Young, J. N., Hopkinson, B. M., Goldman, J. A., Tortell, P. D., Morel, F. M. (2015). Low temperature reduces the energetic requirement for the CO 2 concentrating mechanism in diatoms. New Phytol. 205 (1), 192–201. doi: 10.1111/nph.12976

PubMed Abstract | CrossRef Full Text | Google Scholar

Krause, G. H., Weis, E. (1991). Chlorophyll fluorescence and photosynthesis: the basics. Annu. Rev. Plant Biol. 42 (1), 313–349. doi: 10.1146/annurev.pp.42.060191.001525

CrossRef Full Text | Google Scholar

Kroth, P. G., Chiovitti, A., Gruber, A., Martin-Jezequel, V., Mock, T., Parker, M. S., et al. (2008). A model for carbohydrate metabolism in the diatom phaeodactylum tricornutum deduced from comparative whole genome analysis. PloS One 3 (1), e1426. doi: 10.1371/journal.pone.0001426

PubMed Abstract | CrossRef Full Text | Google Scholar

Kvernvik, A. C., Rokitta, S. D., Leu, E., Harms, L., Gabrielsen, T. M., Rost, B., et al. (2020). Higher sensitivity towards light stress and ocean acidification in an Arctic sea-ice-associated diatom compared to a pelagic diatom. New Phytol. 226 (6), 1708–1724. doi: 10.1111/nph.16501

PubMed Abstract | CrossRef Full Text | Google Scholar

Lacour, T., Lariviere, J., Ferland, J., Bruyant, F., Lavaud, J., Babin, M. (2018). The role of sustained photoprotective non-photochemical quenching in low temperature and high light acclimation in the bloom-forming arctic diatom thalassiosira gravida. Front. Mar. Sci. 5. doi: 10.3389/fmars.2018.00354

CrossRef Full Text | Google Scholar

Lacour, T., Morin, P. I., Sciandra, T., Donaher, N., Campbell, D. A., Ferland, J., et al. (2019). Decoupling light harvesting, electron transport and carbon fixation during prolonged darkness supports rapid recovery upon re-illumination in the Arctic diatom chaetoceros neogracilis. Polar Biol. 42 (10), 1787–1799. doi: 10.1007/s00300-019-02507-2

CrossRef Full Text | Google Scholar

Lavaud, J., Strzepek, R. F., Kroth, P. G. (2007). Photoprotection capacity differs among diatoms: possible consequences on the spatial distribution of diatoms related to fluctuations in the underwater light climate. Limnology Oceanography 52 (3), 1188–1194. doi: 10.4319/lo.2007.52.3.1188

CrossRef Full Text | Google Scholar

Lavaud, J., van Gorkom, H. J., Etienne, A. L. (2002). Photosystem II electron transfer cycle and chlororespiration in planktonic diatoms. Photosynthesis Res. 74 (1), 51–59. doi: 10.1023/A:1020890625141

CrossRef Full Text | Google Scholar

Le Fouest, V., Zakardjian, B., Xie, H., Raimbault, P., Joux, F., Babin, M. (2013). Modeling plankton ecosystem functioning and nitrogen fluxes in the oligotrophic waters of the Beaufort Sea, Arctic ocean: a focus on light-driven processes. Biogeosciences 10 (7), 4785–4800. doi: 10.5194/bg-10-4785-2013

CrossRef Full Text | Google Scholar

Leu, E., Graeve, M., Wulff, A. (2016). A (too) bright future? Arctic diatoms under radiation stress. Polar Biol. 39 (10), 1711–1724. doi: 10.1007/s00300-016-2003-1

CrossRef Full Text | Google Scholar

Levitan, O., Dinamarca, J., Hochman, G., Falkowski, P. G. (2014). Diatoms: a fossil fuel of the future. Trends Biotechnol. 32 (3), 117–124. doi: 10.1016/j.tibtech.2014.01.004

PubMed Abstract | CrossRef Full Text | Google Scholar

Li, G., Campbell, D. A. (2013). Rising CO₂ interacts with growth light and growth rate to alter photosystem II photoinactivation of the coastal diatom Thalassiosira pseudonana. PloS One 8 (1), e55562. doi: 10.1371/journal.pone.0055562

PubMed Abstract | CrossRef Full Text | Google Scholar

Li, W., Gao, K., Beardall, J. (2012). Interactive effects of ocean acidification and nitrogen-limitation on the diatom phaeodactylum tricornutum. PloS One 7 (12), e51590. doi: 10.1371/journal.pone.0051590

PubMed Abstract | CrossRef Full Text | Google Scholar

Li, G., Woroch, A. D., Donaher, N. A., Cockshutt, A. M., Campbell, D. A. (2016). A hard day's night: Diatoms continue recycling photosystem II in the dark. Front. Mar. Sci. 3. doi: 10.3389/fmars.2016.00218

CrossRef Full Text | Google Scholar

Lovejoy, C., Legendre, L., Martineau, M. J., Bâcle, J., Von Quillfeldt, C. H. (2002). Distribution of phytoplankton and other protists in the north water. Deep Sea Res. Part II: Topical Stud. Oceanography 49 (22-23), 5027–5047. doi: 10.1016/S0967-0645(02)00176-5

CrossRef Full Text | Google Scholar

Martin, J., Tremblay, J.É., Gagnon, J., Tremblay, G., Lapoussière, A., Jose, C., et al. (2010). Prevalence, structure and properties of subsurface chlorophyll maxima in Canadian Arctic waters. Mar. Ecol. Prog. Ser. 412, 69–84. doi: 10.3354/meps08666

CrossRef Full Text | Google Scholar

Matsuda, Y., Hopkinson, B. M., Nakajima, K., Dupont, C. L., Tsuji, Y. (2017). Mechanisms of carbon dioxide acquisition and CO₂ sensing in marine diatoms: a gateway to carbon metabolism. Philos. Trans. R. Soc. B: Biol. Sci. 372 (1728), 20160403. doi: 10.1098/rstb.2016.0403

CrossRef Full Text | Google Scholar

Morel, F. M. M., Reinfelder, J. R., Roberts, S. B., Chamberlain, C. P., Lee, J. G., Yee, D. (1994). Zinc and carbon co-limitation of marine phytoplankton. Nature 369 (6483), 740–742. doi: 10.1038/369740a0

CrossRef Full Text | Google Scholar

Myklestad, S. M. (2000). “Dissolved organic carbon from phytoplankton. dissolved organic carbon from phytoplankton,” in Marine chemistry. the handbook of environmental chemistry, vol. 5D . Ed. Wangersky, P. J. (Berlin, Heidelberg: Springer). doi: 10.1007/10683826_5

CrossRef Full Text | Google Scholar

Nicolaus, M., Katlein, C., Maslanik, J., Hendricks, S. (2012). Changes in Arctic sea ice result in increasing light transmittance and absorption. Geophysical Res. Lett. 39 (24). doi: 10.1029/2012GL053738

CrossRef Full Text | Google Scholar

Nixon, P. J., Michoux, F., Yu, J., Boehm, M., Komenda, J. (2010). Recent advances in understanding the assembly and repair of photosystem II. Ann. Bot. 106 (1), 1–16. doi: 10.1093/aob/mcq059

PubMed Abstract | CrossRef Full Text | Google Scholar

Niyogi, K. K., Truong, T. B. (2013). Evolution of flexible non-photochemical quenching mechanisms that regulate light harvesting in oxygenic photosynthesis. Curr. Opin. Plant Biol. 16 (3), 307–314. doi: 10.1016/j.pbi.2013.03.011

PubMed Abstract | CrossRef Full Text | Google Scholar

Pierella Karlusich, J. J., Bowler, C., Biswas, H. (2021). Carbon dioxide concentration mechanisms in natural populations of marine diatoms: insights from Tara oceans. Front. Plant Sci. 659. doi: 10.3389/fpls.2021.657821

CrossRef Full Text | Google Scholar

Pierrot, D., Lewis, D. E., Wallace, D. W. R. (2006). “CO2SYS,” in EXE–MS excel program developed for CO2 system calculations (Oak Ridge, Tennessee: Carbon Dioxide Information Center, Oak Ridge National Laboratory, U.S. Department of Energy). Available at: http://cdiac.ornl.gov/ftp/co2sys/. ORNL/CDIAC-105a.

Google Scholar

Qi, D., Chen, L., Chen, B., Gao, Z., Zhong, W., Feely, R. A., et al. (2017). Increase in acidifying water in the western Arctic ocean. Nat. Climate Change 7 (3), 195–199. doi: 10.1038/nclimate3228

CrossRef Full Text | Google Scholar

Raven, J. A., Geider, R. J. (2003). “Adaptation, acclimation and regulation in algal photosynthesis,” in Photosynthesis in algae (Dordrecht: Springer), pp. 385–412. doi: 10.1007/978-94-007-1038-2_17

CrossRef Full Text | Google Scholar

Reinfelder, J. R. (2011). Carbon concentrating mechanisms in eukaryotic marine phytoplankton. Annu. Rev. Mar. Sci. 3, 291–315. doi: 10.1146/annurev-marine-120709-142720

CrossRef Full Text | Google Scholar

Schiffrine, N., Tremblay, J.É., Babin, M. (2020). Growth and elemental stoichiometry of the ecologically-relevant Arctic diatom Chaetoceros gelidus: a mix of polar and temperate. Front. Mar. Sci. 6. doi: 10.3389/fmars.2019.00790

CrossRef Full Text | Google Scholar

Sharp, J. H. (1974). Improved analysis for “particulate” organic carbon and nitrogen from seawater 1. Limnology Oceanography 19 (6), 984–989. doi: 10.4319/lo.1974.19.6.0984

CrossRef Full Text | Google Scholar

Smetacek, V., Nicol, S. (2005). Polar ocean ecosystems in a changing world. Nature 437 (7057), 362–368. doi: 10.1038/nature04161

PubMed Abstract | CrossRef Full Text | Google Scholar

Smith, S. R., Dupont, C. L., McCarthy, J. K., Broddrick, J. T., Oborník, M., Horák, A., et al. (2019). Evolution and regulation of nitrogen flux through compartmentalized metabolic networks in a marine diatom. Nat. Commun. 10 (1), 1–14. doi: 10.1038/s41467-019-12407-y

PubMed Abstract | CrossRef Full Text | Google Scholar

Tortell, P. D., Payne, C., Gueguen, C., Strzepek, R. F., Boyd, P. W., Rost, B. (2008). Inorganic carbon uptake by southern ocean phytoplankton. Limnology Oceanography 53 (4), 1266–1278. doi: 10.4319/lo.2008.53.4.1266

CrossRef Full Text | Google Scholar

Valegård, K., Andralojc, P. J., Haslam, R. P., Pearce, F. G., Eriksen, G. K., Madgwick, P. J., et al. (2018). Structural and functional analyses of rubisco from arctic diatom species reveal unusual posttranslational modifications. J. Biol. Chem. 293 (34), 13033–13043. doi: 10.1074/jbc.RA118.003518

PubMed Abstract | CrossRef Full Text | Google Scholar

Valenzuela, J. J., Ashworth, J., Cusick, A., Abbriano, R. M., Armbrust, E. V., Hildebrand, M., et al. (2021). Diel transcriptional oscillations of a plastid antiporter reflect increased resilience of Thalassiosira pseudonana in elevated CO₂. Front. Mar. Sci. 8. doi: 10.3389/fmars.2021.633225

CrossRef Full Text | Google Scholar

Valenzuela, J. J., López García de Lomana, A., Lee, A., Armbrust, E. V., Orellana, M. V., Baliga, N. S. (2018). Ocean acidification conditions increase resilience of marine diatoms. Nat. Commun. 9 (1), 1–10. doi: 10.1038/s41467-018-04742-3

PubMed Abstract | CrossRef Full Text | Google Scholar

Valenzuela, J., Mazurie, A., Carlson, R. P., Gerlach, R., Cooksey, K. E., Peyton, B. M., et al. (2012). Potential role of multiple carbon fixation pathways during lipid accumulation in Phaeodactylum tricornutum. Biotechnol. Biofuels 5 (1), 1–17. doi: 10.1186/1754-6834-5-40

PubMed Abstract | CrossRef Full Text | Google Scholar

Wolf, K. K., Hoppe, C. J., Rost, B. (2017). Resilience by diversity: Large intraspecific differences in climate change responses of an Arctic diatom. Limnology Oceanography 63 (1), 397–411. doi: 10.1002/lno.10639

CrossRef Full Text | Google Scholar

Wolf, K. K., Rokitta, S. D., Hoppe, C. J., Rost, B. (2022). Pelagic and ice-associated microalgae under elevated light and pCO2: Contrasting physiological strategies in two Arctic diatoms. Limnology Oceanography 67 (9), 1895–1910. doi: 10.1002/lno.12174

CrossRef Full Text | Google Scholar

Wolf, K. K., Romanelli, E., Rost, B., John, U., Collins, S., Weigand, H., et al. (2019). Company matters: the presence of other genotypes alters traits and intraspecific selection in an Arctic diatom under climate change. Global Change Biol. 25 (9), 2869–2884. doi: 10.1111/gcb.14675

CrossRef Full Text | Google Scholar

Wu, Y., Gao, K., Riebesell, U. (2010). CO₂-induced seawater acidification affects physiological performance of the marine diatom phaeodactylum tricornutum. Biogeosciences 7 (9), 2915–2923. doi: 10.5194/bg-7-2915-2010

CrossRef Full Text | Google Scholar

Young, J. N., Heureux, A. M., Sharwood, R. E., Rickaby, R. E., Morel, F. M., Whitney, S. M. (2016). Large Variation in the rubisco kinetics of diatoms reveals diversity among their carbon-concentrating mechanisms. J. Exp. Bot. 67 (11), 3445–3456. doi: 10.1093/jxb/erw163

PubMed Abstract | CrossRef Full Text | Google Scholar

Young, J. N., Kranz, S. A., Goldman, J. A., Tortell, P. D., Morel, F. M. (2015). Antarctic Phytoplankton down-regulate their carbon-concentrating mechanisms under high CO₂ with no change in growth rates. Mar. Ecol. Prog. Ser. 532, 13–28. doi: 10.3354/meps11336

CrossRef Full Text | Google Scholar

Young, J. N., Morel, F. M. (2015). The CO₂ switch in diatoms. Nat. Climate Change 5 (8), 722–723. doi: 10.1038/nclimate2691

CrossRef Full Text | Google Scholar