Eukaryotic phytoplankton drive a decrease in primary production in response to elevated CO₂ in the tropical and subtropical oceans

Significance

Marine phytoplankton, which contribute ~45% of global net primary production, are projected to be affected by ongoing ocean acidification (OA). However, the response of phytoplankton to acidification is not well constrained in ultraoligotrophic tropical and subtropical oceans where small (<20 µm) phytoplankton dominate. By conducting onboard microcosm experiments, we found community-level primary production decreased consistently following CO₂ enrichment in the North Pacific Subtropical Gyre and northern South China Sea, while no significant changes were observed at the northernmost boundary of the subtropical gyre. Eukaryotic phytoplankton but not cyanobacteria were key drivers of these responses which occur primarily under nitrogen limitation. These findings enhance our understanding of OA impacts on phytoplankton and marine productivity in a changing climate.

Abstract

Ocean acidification caused by increasing anthropogenic CO₂ is expected to impact marine phytoplankton productivity, yet the extent and even direction of these changes are not well constrained. Here, we investigate the responses of phytoplankton community composition and productivity to acidification across the western North Pacific. Consistent reductions in primary production were observed under acidified conditions in the North Pacific Subtropical Gyre and the northern South China Sea, whereas no significant changes were found at the northern boundary of the subtropical gyre. While prokaryotic phytoplankton showed little or positive responses to high CO₂, small (<20 µm) eukaryotic phytoplankton which are primarily limited by low ambient nitrogen drove the observed decrease in community primary production. Extrapolating these results to global tropical and subtropical oceans predicts a potential decrease of about 5 Pg C y⁻¹ in primary production in low Chl-a oligotrophic regions, which are anticipated to experience both acidification and stratification in the future.

The world’s oceans have absorbed approximately 30% of anthropogenic carbon, causing an increase in partial pressure of CO₂ (pCO₂) and a decrease in pH of seawater (1), a process known as ocean acidification (OA). This process is projected to impact all areas of the ocean, with varying consequences for marine species, ecosystems, and their functions (2). The results of laboratory studies on phytoplankton responses to OA vary widely (3). Positive effects of acidification are often attributed to resource and energy savings from the downregulation of carbon-concentrating mechanisms (CCMs) (3). Negative effects may result from disrupted intracellular pH homeostasis or altered nutrient bioavailability at lower ambient pH (4, 5). The extent of these effects varies considerably across and within phytoplankton groups (3–9) and is further modulated by factors like nutrient availability, temperature, and light intensity (10–12).

Field experiments investigating the effects of acidification on natural phytoplankton communities are scarce compared to laboratory studies, with most conducted in mid-high latitude oceanic regions or coastal waters characterized by relatively low temperatures and elevated nutrient concentrations (SI Appendix, Fig. S1). In these studies, phytoplankton communities were generally dominated by large eukaryotic algae, including diatoms, dinoflagellates, and coccolithophores (13–16), with diverse responses of primary production to acidification (SI Appendix, Fig. S2). Highly dynamic and complex environmental conditions in these areas are expected to influence the overall community response (16–18). Far fewer CO₂ enrichment studies have been carried out in the tropical and subtropical oligotrophic regions (SI Appendix, Fig. S1), which encompass vast oceanic areas and are estimated to contribute ~20% of global oceanic primary production (19). In these oligotrophic oceans, prokaryotes such as Prochlorococcus and Synechococcus along with small (<20 µm) eukaryotes (20) contribute the bulk of primary production (21–23). Early studies in the tropical South Atlantic observed a slight increase in primary production following a short-term (2-h) CO₂ enrichment (24), while longer experiments (1 to 3 d) in the tropical North Pacific reported neutral or negative effects of high CO₂ (25, 26). In addition to varied incubation durations, these divergent outcomes may stem from differences in environmental conditions and phytoplankton community compositions across studies. Due to the limited number of field experiments and their restricted spatial coverage, the response of phytoplankton in oligotrophic oceans to OA, as well as the factors governing this response, remain highly uncertain.

In this six-year study, we conducted 48 onboard microcosm CO₂ enrichment experiments (10 to 20 L volume; ~3 d durations) at 45 stations throughout the western North Pacific, spanning the oligotrophic North Pacific Subtropical Gyre and the northern South China Sea to the west, as well as the North Pacific Transition Zone at the northern boundary (Fig. 1A). In the oligotrophic regions, we observed consistent declines in overall community-level primary production under acidification (pCO₂ ~700 µatm) that were driven by effects on eukaryotic phytoplankton.

Fig. 1.

Responses of overall community-level primary production to OA across the western North Pacific. (A) Locations of CO₂ enrichment experiments conducted in this study (yellow dots). The background is the annual average surface nitrate concentration derived from the World Ocean Atlas (https://www.ncei.noaa.gov/products/world-ocean-atlas). NSCS, northern South China Sea; NPSG, North Pacific Subtropical Gyre; NPTZ, North Pacific Transition Zone. The detailed station and group information are shown in SI Appendix, Fig. S3 and Datasets S2 and S3. (B) Relative changes in primary production after acidification [(acidified – ambient)/ambient] in the North Pacific Subtropical Gyre during late spring and summer (May to August, Subtropical Gyre-s) and winter (December to February, Subtropical Gyre-w) seasons, South China Sea during late spring and summer (May to August) seasons (South China Sea) and North Pacific Transition Zone in summer (Transition Zone). Each black dot in the plot represents the average relative change of primary production rate of two or three biological replicates for each CO₂ enrichment experiment. The black dashed line (y = 0) represents no change under CO₂ enrichment. For each boxplot: the box extends from the lower to upper quartile values of the data (Q1 and Q3), with a line at the median (Q2). The whiskers extend from the box to show the range of the data and are defined as follows: where IQR is the interquartile range (Q3–Q1), the upper whisker will extend to the last data point less than Q3 + 1.5 × IQR and the lower whisker will extend to the first data point greater than Q1 – 1.5 × IQR. The white symbol indicates the mean relative change for each defined group (n shows the number of OA-incubation experiments conducted in each group). The statistical significance of the OA-induced positive or negative impact was assessed using Student’s t test and marked with stars (***P < 0.001 and SI Appendix, Table S1). Significant differences between the four defined groups were tested using a one-way ANOVA followed by the Tukey-HSD post hoc test (P < 0.05) and marked with letters above the boxplots (boxplots labeled with the same letter are statistically indistinguishable).

Results and Discussion

Response of Community Primary Production to Acidification.

The subtropical Gyre stations were characterized by warm sea surface temperature (SST, 29.6 ± 0.78 °C in the summer and 27.3 ± 1.1 °C in the winter), deep nitracline (129 ± 31 m), and low surface primary production (SI Appendix, Fig. S4). The South China Sea stations had significantly higher surface primary production (P < 0.05, SI Appendix, Fig. S4C) and shallower nitracline (46 ± 15 m, P < 0.001, Fig. 4B) than the Subtropical Gyre stations. The highest primary production was observed at the Transition Zone stations, which were further distinguished by the shallowest nitraclines (35 ± 22 m average) and mixed layer depths (35 ± 16 m), as well as the lowest SST (18.9 ± 2.1 °C, SI Appendix, Fig. S4).

Fig. 4.

Nutrient availability regulates the response of primary production to OA. (A) Relative changes in primary production after acidification versus average community-level Chl-a concentrations under ambient condition. Each dot in the plot corresponded to one CO₂ enrichment experiment. The y-axis represented the relative changes in primary production after acidification [(acidified – ambient)/ambient] for each CO₂ enrichment experiment. The whiskers on the y-axis, extending from the dot, represented the error propagation for the corresponding CO₂ enrichment experiment (see calculations in the method). The x-axis represented the average community-level Chl-a concentrations under ambient condition of the corresponding CO₂ enrichment. The whiskers on the x-axis, extending from the dot, represented the SD of the community-level Chl-a concentrations. (B) Nitracline depth. For each boxplot: The box extends from the lower to upper quartile values of the data (Q1 and Q3), with a line at the median (Q2). The whiskers extend from the box to show the range of the data and are defined as follows: where IQR is the interquartile range (Q3–Q1), the upper whisker will extend to the last data point less than Q3 + 1.5 × IQR and the lower whisker will extend to the first data point greater than Q1 – 1.5 × IQR. The white symbol indicates the mean value for each defined group (n shows the number of observations, see details in Dataset S2). Significance of differences among the four defined groups was tested by one-way ANOVA followed by Tukey-HSD post hoc tests and marked with letters above the boxplots (the same letter indicates statistically indistinguishable means). A significance level of P < 0.05 was applied. Raw data are shown in Dataset S3. (C) Combined OA-nutrient amendment experiments at two stations (PS4 and PS6 in SI Appendix, Fig. S3, each treatment with two replicates) in the oligotrophic North Pacific Subtropical Gyre during summer seasons [Ctrl = Control (without nutrients addition), N = 2 μM nitrate added]. Bar heights indicate the mean of duplicate measurements in each treatment (black symbols and lines indicate the range), and the light and dark colors represent the ambient and acidified treatments, respectively.

Acidification resulted in a very substantial decrease in primary production in the Subtropical Gyre in the summer (~ 30%; n = 16; P < 0.001; Fig. 1B and SI Appendix, Table S1) and a more modest one in the winter (~ 15%; n = 8, P < 0.001). Summer primary production exhibited a significant but smaller decrease at the South China Sea stations (~15%, n = 20, P < 0.001) and no significant change in the Transition Zone (n = 4, P > 0.05). This last result aligns with most experiments previously conducted in mid-latitude regions, which reported no significant changes or slight increases in primary production after acidification (27, 28).

Response of Phytoplankton Cell Abundances to Acidification.

Pigment analysis revealed that phytoplankton communities in our study areas were dominated by Prochlorococcus, Synechococcus, and small eukaryotes, with the picocyanobacteria contributing typically about 75% of the surface Chl-a (SI Appendix, Fig. S5). Flow cytometry analyses showed that the cell abundances of Prochlorococcus and Synechococcus in the North Pacific Subtropical Gyre were generally unaffected by acidification (P > 0.05, Fig. 2 and SI Appendix, Table S1), which is consistent with the insensitivity of picocyanobacteria to acidification previously observed in the ultraoligotrophic North Atlantic and South Pacific (28, 29). In the South China Sea basin, the change in Prochlorococcus cell abundance following acidification was highly variable, while Synechococcus abundance exhibited a significant increase (Fig. 2 and SI Appendix, Table S1). Culture studies have shown that cellular carbon fixation rates by these picocyanobacteria are either unaffected or increased under acidification (11, 30). Clearly, Prochlorococcus and Synechococcus were unlikely responsible for the acidification-induced decrease in primary production in the North Pacific Subtropical Gyre and South China Sea (Fig. 2).

Fig. 2.

Responses of cell abundances and overall community-level primary production to OA. Cell abundances are direct estimates based on cell counts. Relative changes following acidification are shown [(acidified – ambient)/ambient]. Each point represents the relative change value for each CO₂ enrichment experiment, characterized by [(acidified – ambient)/ambient]. The black dashed line (y = 0) represents no change under acidification. For each boxplot: the box extends from the lower to upper quartile values of the data (Q1 and Q3), with a line at the median (Q2). The whiskers extend from the box to show the range of the data and are defined as follows: where IQR is the interquartile range (Q3–Q1), the upper whisker extends to the last data point less than Q3 + 1.5 × IQR and the lower whisker extends to the first data point greater than Q1 – 1.5 × IQR. The white symbol indicates the mean relative change for each defined group. The statistical significance of the OA-induced positive or negative effects (relative to ambient conditions) was assessed using a Student’s t test. A significance level of P < 0.05 was applied (***P < 0.001; **P < 0.01; *P < 0.05).

In contrast, under acidified conditions, the abundance of small eukaryotic phytoplankton in the Subtropical Gyre decreased very significantly in the summer (by ~30% n = 16, P < 0.001) and more modestly in the winter (by 13 ± 13 %, P < 0.05; SI Appendix, Table S1 and Fig. 2). The corresponding decline after acidification in the South China Sea (by ~8%) was not statistically significant while in the Transition Zone, acidification resulted in a slight and variable increase (by 11 ± 20 %; P > 0.05) in eukaryotic phytoplankton. The observed changes in eukaryotic cell abundance are determined by the balance between growth and loss processes. Studies examining the OA effects on predation and viral infection of small eukaryotic phytoplankton are scarce and have shown inconsistent responses (31–35). We can, however, estimate the growth rate decrease necessary to explain the measured decline in eukaryote abundance. Assuming an ambient growth rate of 1 d⁻¹ (36, 37) and no change in loss rate, the observed ~30% OA-induced decline over three days in summer eukaryotic cell abundance in the Subtropical Gyre (Fig. 2) would correspond to a 12% decrease in growth rate (Supplementary text). Smaller decreases of ~ 5% would explain the observations in the South China Sea and in the Subtropical Gyre in the winter. Published data on the effects of OA on small eukaryotic phytoplankton are scarce, but acidification promoted large decrease in photosynthetic rate of the diatom Thalassiosira pseudonana in nitrogen-limited continuous cultures (38).

In any case, the response of eukaryotic phytoplankton to acidification, which contrasts with that of the picocyanobacteria, was primarily responsible for the observed overall changes in community primary production.

Eukaryotic Phytoplankton Community Structure and Its Responses to Acidification.

The eukaryotic phytoplankton community was predominantly composed of Chrysophyceae (46%) Prymnesiophyceae (21%), Eustigmatophyceae (8%), and Dictyochophyceae (7%) (SI Appendix, Fig. S6 A and B). Acidification did not significantly alter the composition of this community at any site in any of the experiments (PERMANOVA analyses, P > 0.05, Fig. 3A and SI Appendix, Table S2), indicating that the acidification-induced decline in eukaryotic cell abundance in the North Pacific Subtropical Gyre and South China Sea was a general decrease in cell numbers across the entire community rather than in specific taxa.

Fig. 3.

The responses of photosynthetic eukaryotic phytoplankton community structure and α-diversity (indicated by Shannon index) to OA. (A) The community structure of eukaryotic phytoplankton under the ambient and acidified conditions at 18 sequenced stations in the four defined groups (locations and sample list are shown in SI Appendix, Fig. S6A and Dataset S2, respectively), determined by chloroplast 16S rRNA gene sequencing. Each bar shows the average relative abundance of three biological replicates in each experiment conducted at each station (only two replicates at stations S10, S11, S12, PS4, and PS6). (B) Eukaryotic phytoplankton α-diversity (indicated by Shannon index) of the four defined groups. Each point represents the Shannon index of an individual sequenced sample, with 38 samples in Subtropical Gyre-s, 18 samples in Subtropical Gyre-w, 18 samples in South China Sea, and 24 samples in Transition Zone, respectively. For each boxplot: the box extends from the lower to upper quartile values of the data (Q1 and Q3), with a line at the median (Q2). The whiskers extend from the box to show the range of the data and are defined as follows: where IQR is the interquartile range (Q3–Q1), the upper whisker will extend to the last data point less than Q3 + 1.5 × IQR and the lower whisker will extend to the first data point greater than Q1 – 1.5 × IQR. The white symbol indicates the mean relative change for each defined group. The significance of differences among the four defined groups was tested by one-way ANOVA followed by Tukey-HSD post hoc tests (P < 0.05) with the same letters above the boxplots indicating statistically indistinguishable means. (C) Relationship between the mean Shannon index and OA-induced changes of nano-/pico-eukaryotic cell abundance counted by flow cytometry in the corresponding 18 DNA sequencing stations. The y-axis represents the mean Shannon index at each DNA sequencing station, including all sequencing samples collected from both ambient and acidified treatments at one station (n = 4 or 6), and the error bar indicates the SD. The x-axis depicts the OA-induced changes of nano-/pico-eukaryotic cell abundance counted by flow cytometry in the corresponding 18 DNA sequencing stations. The black dashed line (x = 0) represents no change under CO₂ enrichment.

The eukaryotic phytoplankton diversity was not significantly affected by acidification in all experiments except one at station PS7 (SI Appendix, Table S2) but was lower in the Subtropical Gyre during the summer than in the winter and at other sites (Fig. 3B). The Shannon index of diversity was significantly anticorrelated with the acidification-induced decrease in eukaryotic cell abundance (Fig. 3C, r = 0.7, P < 0.01), suggesting that lower diversity made the eukaryotic community more vulnerable to acidification. Previous studies have suggested that reduced biodiversity might decrease community resilience in changing environments (39–42).

Acidification Effects on Primary Production Controlled by Nitrogen Availability.

The negative effects of acidification on primary production were largest in the experiments with the lowest Chl-a concentrations and decreased in those where Chl-a was higher (r = 0.63, P < 0.001, Fig. 4A) with no significant changes in the North Pacific Transition Zone. Variations in Chl-a concentrations and in situ primary production rates across our study regions are expected to be regulated by nutrient availability, particularly nitrate which was depleted below the detection limit at most stations (43, 44). The very deep nitraclines in the North Pacific Subtropical Gyre (129 ± 31 m; Fig. 4B) should result in very low nitrate supply rates to eukaryotic phytoplankton at the surface, much lower than those in the South China Sea basin and North Pacific Transition Zone where the nitraclines are much shallower (Fig. 4B). Published data demonstrate the primary role of nitrogen supply in limiting phytoplankton in the western North Pacific, with P and Fe acting as secondary limiting nutrients in certain specific regions (43).

Nitrogen limitation in our study was confirmed by two nutrient amendment experiments conducted in the North Pacific Subtropical Gyre during the summer. The addition of 2 µM nitrate resulted in significant increases in primary production and eukaryotic phytoplankton abundance (Fig. 4C and SI Appendix, Fig. S7 and Table S4). In addition, although the overall phytoplankton community remained dominated by picocyanobacteria, the diversity of the eukaryotic phytoplankton community increased markedly, accompanied by notable shifts in community structure (SI Appendix, Fig. S8). These changes are consistent with the broader trends observed along nitraclines in our study areas (Fig. 3 A and B).

Importantly, the addition of nitrate alleviated the negative effect of acidification. The increased eukaryotic diversity following nitrate addition (SI Appendix, Fig. S8) may have enhanced the community resilience under acidified conditions (39–42), as we observed in the areas of higher nutrient availability (Fig. 3). Previous studies have highlighted the critical role of essential nutrients (e.g., N, Fe, and P) in modulating the physiological response of phytoplankton to acidification (45, 46). For instance, the adverse effect of acidification on the diazotrophic cyanobacterium Trichodesmium under Fe-limited conditions was mitigated by Fe addition (5, 47). Similarly, declines in diatom photosynthesis and respiration after acidification were observed with N-limited cultures but were absent in N-replete ones (38, 48). A plausible explanation is that higher nutrient availability allows for increased energy production and conversion rates through photosynthesis and respiration, enabling cells to allocate additional energy to maintain physiological homeostasis under acidification (48, 49).

The dependence of the effect of acidification on low nutrient supply (mainly nitrogen supply) to eukaryotes provides an explanation for its negligible effect on Prochlorococcus and Synechococcus observed in the North Pacific Subtropical Gyre. Owing to their very small sizes these prokaryotes can satisfy their nutrient requirements with very low concentrations of nitrogen, iron, and phosphorus (50–53). In addition, this dependency provides insights into how phytoplankton productivity might respond to episodic nutrient supply (e.g., via eddies) in a future carbon-enriched ocean.

Aside from nutrient availability, temperature may also play a role in regulating phytoplankton response to acidification. Surface temperature in the wintertime North Pacific Subtropical Gyre was on average 2.3 °C cooler than in summer, and it was on average 10 °C lower in the North Pacific Transition Zone than in the lower latitude regions (SI Appendix, Fig. S4A). However, limited studies show conflicting findings on how temperature modulates the sensitivities of primary production to acidification (54, 55). Further studies are needed to understand the effects and mechanisms of OA on natural phytoplankton assemblages under changing temperatures.

Implications for Primary Production in the Future High CO₂ Ocean.

Our field data show a correlation between the negative effects of acidification on primary production and low Chl-a concentrations (Fig. 4A). Results from previous field studies in similar low Chl-a regions align with our findings (SI Appendix, Table S5), suggesting a possible broader applicability of this relationship. Using a linear fit to Fig. 4A (relative change in primary production = 1.33 × Chl-a – 0.34, applicable to Chl-a < 0.35 μg L⁻¹) and satellite-based monthly Chl-a data, we calculated an approximately 20% reduction in primary production across oceanic regions between 40°S and 40°N with Chl-a concentrations < 0.35 μg L⁻¹ (SI Appendix, Fig. S9). This would correspond to a decrease of about 5 Pg C y⁻¹ (or nearly 10%) of global oceanic primary production due to OA, with the greatest reductions occurring in nutrient-depleted and low Chl-a ocean gyres (SI Appendix, Fig. S9).

Our experimental results show that small photosynthetic eukaryotes are responsible for a basin-scale decline of primary production in the western North Pacific under elevated CO₂, despite their low numerical abundance (56, 57). Our findings highlight the importance of nutrient availability in regulating the response of primary production to OA and suggest that possible increases in stratification of the tropical and subtropical oceans could further decrease their productivity.

Materials and Methods

Sample Collection.

All the investigations and OA experiments were conducted on nine cruises onboard the R/V Dongfanghong 2# and R/V Tan Kah Kee during 2016 to 2022 (see details in Datasets S2 and S3). Forty-five stations (yellow dots in Fig. 1A) were investigated and a total of 48 OA experiments were conducted. The stations were classified into four distinct groups (Subtropical Gyre-s, Subtropical Gyre-w, South China Sea, and Transition Zone) according to the geographic location and sampling season (SI Appendix, Fig. S3 and Fig. 1). At each station, temperature was recorded by a Seabird 911 CTD. Water samples were collected using Niskin-X bottles for the determination of nutrient concentration, pigment-based phytoplankton community structure, and primary production. Surface seawater samples for the OA experiments were collected either using Niskin-X bottles or using a towed sampling device with suction provided by a Teflon bellows pump.

OA Experiment Setup.

Acid-cleaned Nalgene polycarbonate carboys (10 or 20 L) were filled with surface seawater, and the carbonate chemistry was manipulated by gently bubbling with 0.22 µm-filtered air or CO₂-air mixture generated by CO₂ mixers (Ruihua Instrument & Equipment Ltd). CO₂ concentrations were set as 400 μatm, representing present-day ambient condition, and 700 μatm, simulating the acidified condition projected for the year 2100 under moderate-emission scenarios RCP 6.0 (58). For the CO₂ enrichment combined with nutrient amendment experiments conducted at stations PS4 and PS6 in the Subtropical Gyre-s (SI Appendix, Fig. S3), NaNO₃ was added to a concentration of 2 μM. Most experiments included triplicate samples at ambient and acidified conditions (only two replicates were conducted at stations S10, S11, S12, PS3, PS4, and PS6), with a ~3-d incubation in on-deck flow-through incubators screened with neutral density screening to ~45% of sea surface irradiance. After incubation, seawater was subsampled for the determinations of the seawater carbonate system, Chl-a concentrations, primary production rates, and phytoplankton abundances. Seawater was also subsampled for 16S-rRNA-gene-based sequencing in 18 of the OA experiments conducted at stations in the Subtropical Gyre-s, Subtropical Gyre-w, South China Sea, and Transition Zone.

Carbonate Chemistry Measurement.

In the CO₂ enrichment experiments conducted at stations S1 to S9, pH was measured using a pH electrode (Eutech pH 110 m with Eutech ECFC7352901B probe) calibrated with National Institute of Standards and Technology pH standard buffers. After back to the land, the pH values obtained from these measurements during the cruise were subsequently converted to pH_T (pH on the total scale) using a calibration relationship established between the electrode-based pH measurements and spectrophotometric pH_T measurements (59) of seawater. In the remaining CO₂ enrichment experiments, pH_T was measured directly using the spectrophotometric method directly. The dissolved inorganic carbon (DIC) of media was analyzed by acidification and subsequent quantification of released CO₂ with a CO₂ analyzer (AS-C3, Apollo SciTech). DIC was calibrated using certified reference materials obtained from Andrew Dickson’s laboratory at the Scripps Institution of Oceanography, University of California, San Diego. The precision of the DIC analysis was 1‰ (60). Calculations of alkalinity and pCO₂ were made using the CO₂ Sys program (61). The carbonate chemistry of all experiments is shown in SI Appendix, Table S6.

Primary Production Measurement.

Primary production was determined after CO₂ enrichment incubations using the ¹³C tracer method (62). 2.3 L seawater from each incubation carboy was (sub)sampled into an acid-cleaned Nalgene polycarbonate bottle, spiked with NaH¹³CO₃ (99 atom % ¹³C, Cambridge Isotope Laboratories) solution at a concentration of 100 μM, and incubated for 24 h under the same light level (~45% of sea surface irradiance) as used in the OA experiments. The average ¹³C enrichment was 4.63 ± 0.17% (n = 284). After incubation, particulate matter in seawater was filtered onto precombusted (450 °C, 4 h) GF/F filters under a vacuum pressure less than 75 mm Hg. POC samples from each CO₂ enrichment incubation carboy without ¹³C enrichment were collected to determine background ¹³C-POC natural abundances. All filtration samples were acid-fumed to remove the inorganic carbon and then analyzed using an elemental analyzer coupled to a mass spectrometer (Flash HT 2000-Delta V Plus, Thermo Fisher Scientific). The primary production rates were then calculated according to Hama et al. (62). Additionally, the initial sea surface primary production was measured following the same procedure in the CO₂ enrichment experiments, except without covering of neutral-density screen (Dataset S3).

Chl-a and Nutrient Analyses.

Samples for analysis of Chl-a concentrations were filtered (200 to 500 mL), extracted in 90% acetone, and analyzed fluorometrically on a Turner Designs fluorometer (63). Samples for nutrient analyses were collected in 50-mL acid-washed high-density polyethylene bottles (Nalgene) and analyzed onboard using a Four-channel Continuous Flow Technicon AA3 Auto-Analyzer (Bran-Lube GmbH). The detection limits of NO₃⁻ and NO₂⁻ were 0.03 and 0.02 μM, respectively. The nitracline was defined as the depth at which NO_X (NO₃⁻ + NO₂⁻) concentration equaled 0.1 μmol L⁻¹ (64).

Phytoplankton Cell Abundances.

Seawater for flow cytometry analysis was filtered through a 20-μm mesh, preserved with glutaraldehyde (65–67) at a final concentration of 0.5%, and then placed in the dark for 15 min. The samples were subsequently frozen in liquid nitrogen and stored at −80 °C until further analysis. In the land-based laboratory, cell numbers of three small (<20 µm) phytoplankton populations (Prochlorococcus, Synechococcus, and nano-/pico-eukaryotes) were determined using a FACSAria flow cytometer (Becton, Dickinson and Company, USA) following procedures described previously (68). Phytoplankton groups were identified and enumerated using the software FCS Express 3.

Phytoplankton Pigment Analysis.

Phytoplankton pigment analysis was conducted at 39 stations to assess the in situ community structure. 4.5 L surface seawater was directly filtered onto precombusted 25-mm GF/F filters under a vacuum pressure less than 75 mm Hg and in dim light. Filters were immediately frozen in liquid nitrogen before analysis in the laboratory. Pigments were extracted in N,N-dimethylformamide for about 1 to 2 h at −20 °C. After that, the extracts were filtered through 0.22-μm pore-sized filters (Millipore) and mixed with 1 mol L⁻¹ ammonium acetate solution (1:1, v:v) (69). Pigments were separated on a 3.5-mm Eclipse XDB C₈ column (Agilent Technologies) coupled to a DIONEX UltiMate 3000 high-performance liquid chromatography (HPLC), following a modified method of Mantoura and Llewellyn (70) and Van Heukelem and Thomas (71). The representative pigments of nine phytoplankton taxa (including Dinoflagellates, Diatoms, Haptophytes_type8, Haptophytes_type6, Chlorophytes, Cryptophytes, Prochlorococcus, Synechococcus, and Prasinophytes) in each sample were determined and quantified according to the standards manufactured by Danish Hydraulic Institute (DHI) Water and Environment (72). The results of the pigment analysis were then converted to approximate contributions of each phytoplankton taxa to total Chl-a using CHEMTAX (73).

DNA Extraction, 16S rRNA Gene Sequencing, and Sequence Analysis.

Samples for 16S rRNA gene sequencing were collected from 18 out of the 48 CO₂ enrichment experiments conducted in North Pacific Subtropical Gyre, South China Sea, and North Pacific Transition Zone (SI Appendix, Fig. S6A). Briefly, ~3 L seawaters were subsampled from the CO₂ enrichment incubation carboys onto 0.22-μm pore-sized membrane filters (Supor 200, Pall Gelman, NY) and then frozen immediately in liquid nitrogen until further analysis. To extract the environmental DNA, membranes were cut into pieces under sterile conditions and then extracted using the QIAamp DNA Mini Kit (Qiagen) following the manufacturer’s protocol. Partial 16S rRNA genes were amplified using previously described primers targeting the V3-V4 variable region of the 16S rRNA gene (341Fb: 5′-ACTCCTACGGGAGGCAGCAG-3′; 806Rb: 5′-GGACTACHVGGGTWTCTAAT-3′) (74). Tag sequencing of DNA amplicons was carried out on an Illumina HiSeq platform using 2 × 300 bp paired-end v3 chemistry at BGI Genomics, Shenzhen, China.

After sequencing, raw reads were filtered to remove adaptors, and low-quality and ambiguous bases. Then, paired-end reads were added to tags by using the Fast Length Adjustment of Short reads program (FLASH, v1.2.11) (75) to get the tags. Quality control of the sequencing reads, identification of the amplicon sequencing variants (ASV, defined by 99% sequence similarity), and primary taxonomic affiliation based on SILVA SSU (version 138) were all conducted by QIIME2 workflow (76) and the R package DADA2 (77). The sequences identified as chloroplast by the SILVA SSU (version 138) were filtered and then annotated taxonomy using the PR2 version 5.0.0 database (78, 79).

Implications for Primary Production in the Future High CO₂ Ocean.

We predicted the relative changes in primary production under acidified conditions, based on the relationship observed in this study (relative change in primary production = 1.33 × Chl-a – 0.34, R² = 0.389, P < 0.001). This relationship was extrapolated to global subtropical oceanic regions between 40°S and 40°N with Chl-a concentrations <0.35 μg L⁻¹. Based on the relationship, we calculated the relative changes in primary production for each grid cell area between 40°S and 40°N with Chl-a concentrations <0.35 μg L⁻¹, using monthly climatology Chl-a concentrations derived from Ocean-Colour Climate Change Initiative via MODIS-Aqua satellite sensors from 2003 to 2022 (https://www.oceancolour.org/). The analysis suggests a reduction in primary production by 18.3 to 20.2% across different months (SI Appendix, Fig. S9 A–L). Next, changes in absolute primary production rates were estimated by overlaying the percentage changes in primary production of each grid cell area with absolute monthly climatology primary production estimates from 2003 to 2022 derived via the MODIS sensing algorithms carbon-based production model (CbPM, http://orca.science.oregonstate.edu/npp_products.php). The products of the climatology Chl-a and the carbon-based primary production were corrected to the same resolution and calculated each grid cell area using Climate Data Operators (CDO, Version 2.3.0) (80). The estimates suggest a decrease of 5 Pg C y⁻¹ in primary production due to acidification.

Statistical Analysis.

For each CO₂ enrichment experiment, relative changes in primary production rates and small phytoplankton abundances after acidification were calculated as [(acidified – ambient)/ambient], using the average value of duplicate or triplicate measurements for each treatment. The SD of relative change was calculated via error propagation {σ_{relative change} = sqrt[(σ_acidified)² + (σ_ambient)²]}, where σ indicated the SD within each treatment. The significance of OA impacts within each of the defined groups was tested using Student’s t test, by using the normalized data [(acidified- ambient)/ambient] from all CO₂ enrichment experiments. Differences between the four defined groups were determined by a one-way ANOVA followed by a Tukey HSD test. A significance level of P < 0.05 was applied, except as noted where significance was even greater.

For the bioinformatic analysis of the 16S rRNA gene sequencing data, the α-diversity, indicated by the Shannon index was calculated using the R packages vegan (81). The PERMANOVA test was conducted using the adonis2 in vegan package (81) and RVAideMemoire package (82) in R to compare the difference in eukaryotic phytoplankton community under ambient and acidified conditions for each CO₂ enrichment experiment.

Supplementary Material

Appendix 01 (PDF)

Dataset S01 (XLSX)

Dataset S02 (XLSX)

Dataset S03 (XLSX)

Dataset S04 (XLSX)

Data, Materials, and Software Availability

The 16S rRNA gene raw sequences generated in this study have been deposited in the National Center for Biotechnology Information [NCBI; BioProject PRJNA1107808 (83)]. All other data are included in the manuscript and/or supporting information.