Photophysiological Characterization of Phytoplankton by Measuring Pigment Production Rates: A Description of Detail Method and a Case Study

Abstract

Each phytoplankton species has intrinsic pigments, which result in different photophysiological characteristics in response to natural light conditions. Therefore, phytoplankton pigments provide important information on the photosynthetic activity that produces the basic food source for marine ecosystems. This study addresses the challenge of accurately measuring pigment production rates in phytoplankton communities. Two strategies are proposed for improving measurement sensitivity. Firstly, increasing the injection of ¹³C substrate into incubation bottles up to 15% of the total dissolved inorganic carbon is recommended, with minimal impact on pigment production rate determinations. Secondly, optimizing sample injection volume for high-performance liquid chromatography balances analysis time and dilution effects. The in situ field experiments conducted in this study for pigment production measurements revealed diminished activity of photoprotective mechanisms involving zeaxanthin and diatoxanthin during the study period. Furthermore, the results showed that the notable production rates of chl-b (0.069–0.105 ng C L^–1 h^–1, 74–89% of total accessary pigment production rates), an accessory pigment mainly attributed to prasinophytes, potentially due to restricted light availability. Prioritization of chl-b production over primary production (negative correlation between primary and chl-b production; R² = 0.6662) highlights the potential impact of compensatory pigment-related activities on overall phytoplankton productivity. In conclusion, this study underscores the significance of directly quantifying pigment production rates to enhance our comprehension of phytoplankton photophysiology and the production mechanisms specific to various pigments.

1. Introduction

Phytoplankton pigments, primarily chlorophyll and carotenoids, have been widely employed to discern the structure and dynamics of phytoplankton communities [1,2,3,4,5]. However, the importance of phytoplankton pigments extends far beyond their role in community analysis. It is imperative to recognize that these pigments fundamentally serve as conduits for harnessing light energy—a vital catalyst for the process of photosynthesis. They are responsible for capturing sunlight and converting it into chemical energy via photosynthesis, thereby sustaining life in aquatic environments and forming the basis of the marine food web [6,7,8,9,10]. In addition, studies on phytoplankton pigments are an important contribution to climate research. Monitoring changes in pigment concentrations provides important clues for phytoplankton responses to climate change and their role in carbon sequestration [6,11,12,13]. In conclusion, pigment analysis provides valuable insights into the dynamics of aquatic environments, making them essential for both scientific understanding and practical applications.

The intricate interplay of pigment composition, types, and concentrations varies extensively across phytoplankton species, with each species displaying unique and characteristic pigment responses to alterations in the light environment, encompassing irradiance, spectral composition, and day length [14]. Notably, this adaptation to light conditions underscores the profound connection between pigment variations and physiological attributes of phytoplankton species. The dynamic interplay of pigments assumes significance in the context of the phytoplankton’s response to varying light regimes [14]. Generally, larger phytoplankton species tend to exhibit diminished intracellular pigment content compared to their smaller counterparts, providing smaller phytoplankton an advantageous growth edge under low light conditions [15,16]. An intricate interplay further unfolds when phytoplankton are exposed to strong light and ultraviolet radiation, promoting the synthesis and accumulation of photoprotective pigments such as diatoxanthin and zeaxanthin [14,17]. Therefore, phytoplankton pigments are believed to offer insights into the physiological characteristics of distinct species and their intimate relationship with photosynthesis.

However, it is difficult to understand the intricate photophysiological properties of phytoplankton based solely on changes in pigment concentration because phytoplankton have to adapt rapidly to aquatic ecosystems where light conditions change dramatically [18,19,20]. Therefore, the development of an analytical framework that can dissect the intricate dynamics of pigment responses can provide insights into the photo-physiology of phytoplankton within aquatic ecosystems.

The most appropriate tool to directly measure pigment synthesis by phytoplankton under natural light conditions is considered to be the ¹³C tracer technique, which is widely applied to the primary production measurement of phytoplankton in various oceans [17,21]. However, the main bottlenecks for the precise pigment production analysis are pigment detectability via HPLC (high-performance liquid chromatography) analysis and the sensitivity of carbon stable isotope analysis from each pigment. This study strides forward by proffering pragmatic solutions to these impediments, thus enabling a refined measurement of pigment production rates. Here, we present a succinct description of the procedural framework for pigment production measurement for these solutions. Moreover, we apply this method to some field experiments to evaluate the photophysiological properties of natural phytoplankton communities.

2. Materials and Methods

2.1. Carbon Stable Isotope Fractionation Experiment for Pigment Production

Pigment production is based on the carbon stable isotope tracer technique, as elucidated by previous studies [17,21]. It is noteworthy that widely employed methods for phytoplankton pigment analysis using HPLC mainly involve the use of organic solvents [22,23,24,25,26], which could affect the carbon stable isotope values of photosynthetic pigments. Thus, a preliminary experiment was conducted to confirm the potential influence of these organic solvents on the delta ¹³C value of the pigments prior to the in situ culture experiment for quantifying pigment production rates. Concurrently, an additional experiment was executed to examine the effect of varying sample injection volumes (100, 200, 300, 400, and 500 µL) on the carbon stable isotope values of the pigments. Comprehensive details pertaining to the components and analytical conditions of the HPLC methodology are presented in

Table 1. HPLC equipment and analysis condition for pigment production.

Equipment	Conditions
Pump	- Quaternary pump (G1311C) - Eluents A = methanol: acetonitrile: aqueous pyridine (50:25:25, v:v:v) B = methanol: acetonitrile: acetone (20:60:20, v:v:v) - Gradient condition
	Time	Ratio
		A	B
	0	100	0
	21	60	40
	27	5	95
	37	5	95
	45	100	0
	- Post time: 5 min - Flow rate: 1.0 mL min–1
Sampler	- Autosampler (G1329B) - Injection upgrade kit (G1363A; increase in the injection volume up to 900 μL) - Thermostat (G1330B; keep the sampler temperature at 4 °C) - Injection volume Quantitative analysis: 100 μL Collection of each pigment: 500 μL
Column	- Column: Zobrax Eclipse XDB C8 (250 × 4.6 mm, 5 μm) - Thermostat (G1316A; keep the column temperature at 25 °C)
Detector	- Diode array detector (G1364C) - Detecting wavelength: 430 nm
Collector	- Fraction collector (G1364C) - Collection vial: 5 mL transparent glass vial

. An authentic standard of chlorophyll-a (chl-a; Sigma-Aldrich Korea, Gangnam-gu, Seoul, Republic of Korea) was utilized for a test pigment in this experiment. Each experiment was repeated three times. To compare with the method by [24] (hereafter referred to as ZM), an additional test under uniform conditions was conducted in accordance with the approach outlined by [26] (hereafter referred to as JM), a recognized HPLC analysis method for phytoplankton pigments. JM employed organic solvents such as methanol, ammonium acetate, acetonitrile, and ethyl acetate, while ZM employed methanol, acetonitrile, acetone, and aqueous pyridine.

2.2. In Situ Culture Experiment Procedure for Pigment Production Using a ¹³C Tracer

The evaluation of pigment production via field experiments was conducted using water samples collected from six different stations in the East/Japan Sea during the spring of 2016 (Figure 1 and

Table 2. Station information and primary production during the study period.

Station	Date	Latitude (°N)	Longitude (°E)	* PP (mg C m–3 h–1)
M2	07-Apr	37.010	130.250	3.85
M4-1	08-Apr	36.995	131.260	3.75
M5	09-Apr	37.328	131.457	6.42
UW7	13-Apr	37.017	130.502	2.57
M10	11-Apr	39.493	132.340	2.38
M12	10-Apr	40.473	132.317	4.74

* Primary production (data from [30]).

). Surface layer water samples were obtained using a CTD/rosette sampler equipped with 12 L Niskin bottles for subsequent pigment production analysis. Samples exceeding 13 L in volume were obtained. To determine the natural ¹³C value of each pigment, a portion of the collected seawater samples underwent filtration (>4 L) using precombusted (450 °C) Whatman GF/F filter paper (47 mm). Prior to the incubation, the collected water samples were filtered through a 300 µm mesh to eliminate larger zooplankton and detritus. Subsequently, the filtered samples were transferred to 9 L transparent polycarbonate bottles (Thermo Fisher Scientific Nalgene, Seoul, Republic of Korea). Following filtration, the stable carbon isotope (NaH¹³CO₃, 99%) was introduced as a tracer in accordance with established methodologies [17,21,27]. The quantity of ¹³C introduced was maintained at 10–15% of the determined ¹³C atoms derived from the total dissolved inorganic carbon within the water sample. The transparent polycarbonate carboys were incubated within a cooling-equipped polycarbonate incubator on deck. This incubation occurred under the influence of natural light conditions for a duration of 4 h [21,28,29]. Upon completion of the incubation period, water samples from the incubated carboys were filtered (>4 L) through 47 mm GF/F filter papers. These filtered samples were immediately enveloped in aluminum foil to prevent photolysis and were promptly stored in a deep freezer (–80 °C) for subsequent analysis. The field experiment procedures are schematically summarized in Figure 2a.

2.3. Extraction and Analysis of Phytoplankton Pigments for Production Assessment

To enhance extraction efficiency, the filter paper designated for pigment production was fragmented into smaller pieces [31]. These fragments were then placed within centrifuge tubes containing 100% acetone (3.5–4.0 mL) and canthaxanthin (100 µL) as an internal standard. Extraction of pigments was achieved by subjecting the samples in centrifuge tubes to 5 min of sonification, followed by a 24 h freezing period at 4 °C. Subsequently, the extracts were purified by passing them through a 0.2 µm syringe filter (Advantec, Dublin, CA, USA). The purified extract was combined with deionized water in a 1:0.3 volume ratio. The subsequent analysis of extracted pigments was conducted using an HPLC system (Agilent Infinite 1260, Santa Clara, CA, USA) in accordance with the approach detailed by [24] (Table 1). The identification of photosynthetic pigments relied on the retention time of authentic standards (DHI Water & Environment, Hørsholm, Denmark). Separated pigments were collected using an HPLC fraction collector, involving a 5 mL vial that included half of the precombusted filter paper (Whatman 25 mm GF/F filter, Maidstone, UK) (Table 1). Subsequently, solvents from the collected pigments were eliminated via nitrogen purge equipment. The filter within the collection vial was sealed with a tin cap, enabling the analysis of the delta ¹³C value of each pigment using a Finnigan Delta + XL mass spectrometer (Stable Isotope Laboratory of the University of Alaska Fairbanks, AK, USA). Figure 2b offers a succinct depiction of the HPLC analysis procedure.

2.4. Calculation of the Pigment Concentration and Production Rate

The determination of pigment concentrations was achieved via the assessment of chromatographic peak areas, adhering to the method devised by [32]. The pigment concentration (C) was calculated using the formula

$$\mathrm{C}=\mathrm{A}\mathrm{r}\mathrm{e}\mathrm{a}\times \mathrm{R}\mathrm{f}\times \frac{\mathrm{V}\mathrm{e}}{\mathrm{V}\mathrm{s}}$$

(1)

where C represents the pigment concentration [µg L^–1]; Area denotes the peak area [area]; Rf is the standard response factor [µg L^–1 area^–1]; Ve is determined as AIS × volume of internal standard (I.S.) added to the sample divided by peak area of the I.S. added to the sample [L]; AIS is the peak area of the I.S. with 1 mL I.S. mixed with 300 µL deionized water [area]; and Vs is the water sample filtering volume [L].

The production rate of each pigment was calculated from each ¹³C atomic percent and concentration based on [28] references therein.

$$∆\mathrm{P}\mathrm{P}\mathrm{R}\left(\mathrm{t}\right)=\mathrm{P}\mathrm{P}\mathrm{R}\times \frac{a_{is}-a_{ns}}{a_{ic}-a_{ns}}$$

(2)

where ∆PPR represents the amount of carbon photosynthetically produced by each pigment during the incubation, a_is is the ¹³C atom % in each pigment compound of the incubated sample, a_ns denotes the ¹³C atom % in each pigment compound of the natural sample, a_ic is the ¹³C atom % in the ¹³C enriched inorganic carbon, and PPR is the concentration of carbon in each pigment at the end of incubation.

2.5. Chemotaxonomic Analysis

The phytoplankton community compositions within the study area were determined by calculating the ratio of marker pigments to chl-a, facilitated using CHEMTAX software [33,34,35]. This analysis enabled the identification of eight distinct phytoplankton groups based on pigment content, namely prasinophytes, dinophytes, prymnesiophytes, pelagophytes, cyanophytes, chlorophytes, cryptophytes, and bacillariophyceae. The input pigment ratios employed in the CHEMTAX program were derived from the pigment associations of phytoplankton groups proximal to the study area [36,37].

2.6. Statical Analyses

The relative standard deviation (R.S.D.) was calculated to assess the precision of repeated experiments (n = 3) in quantitatively assessing pigment concentration by sample injection volume into HPLC analysis.

$$\mathrm{R}.\mathrm{S}.\mathrm{D}.=\frac{Standard Deviation}{Mean}\times 100$$

(3)

One-way ANOVA test was used to compare the delta ¹³C values of the original chl-a and the chl-a collected after HPLC analysis (different injection volume: 100–500 μL; n = 3), and Tukey’s HSD (honestly significant differences) test was carried out for subsequent pair-wise comparisons (SPSS v27 for Windows).

3. Results

3.1. Pigment Production Analysis Using HPLC

The utilization of HPLC for pigment production analysis was accompanied by several insightful observations. The peak areas of the chl-a standard solution that were analyzed using both ZM and JM methods exhibited a linear correlation with the sample injection volume (R² > 0.997; Figure 3). Notably, the relative standard deviation of the peak area (n = 3) for each injection volume remained below 1% in both methodologies (

Table 3. The variation of the chl-a peak area with different injection volumes in the ZM and JM.

ZM						JM
Injection Volume (µL)	100	200	300	400	500	Injection Volume (µL)	100	200	300	400	500
Area	2525.5	4732.3	6940.1	8952.1	11,686.6	Area	3282.1	6302.6	9251.6	12,246.7	14,546.3
	2526.1	4736.3	6896.5	9010.4	11,658.2		3276.7	6284.2	9277.7	12,227.9	14,498.6
	2532.8	4727.8	6889.3	9071.9	11,759.9		3277.7	6273.9	9250.8	12,288.5	14,512.3
1 S.D.	4.1	4.3	27.5	59.9	52.5	S.D.	2.9	14.5	15.3	31.0	24.6
2 R.S.D. (%)	0.16	0.09	0.40	0.66	0.45	R.S.D. (%)	0.09	0.23	0.17	0.25	0.17

¹ Standard deviation; ² Relative standard deviation.

). These findings collectively indicate that variations in sample injection volume did not introduce over- or underestimations in the analysis results.

The delta ¹³C values of the eluents used for HPLC analysis in ZM and JM methods are delineated in

Table 4. The delta ¹³C value of the eluents used in ZM and JM.

Eluents	A	B	C	A + B	A + C	B + C	A + B + C
ZM	−26.58	−30.30	-	−30.12	-	-	-
JM	−40.43	−33.69	−30.39	−40.51	−39.19	−30.96	−39.39

ZM: Eluent A = methanol + acetonitrile + aqueous pyridine; B = methanol + acetonitrile + acetone. JM: Eluent A = methanol + ammonium acetate; B = acetonitrile + water; C = ethyl acetate.

. Generally, the delta ¹³C values of each eluent and mixed eluent within both methodologies were relatively lower than that of the chl-a standard. Particularly low ¹³C values were evident in eluent A and its mixed counterpart used in JM (Table 4). Nonetheless, the delta ¹³C values of chl-a analyzed using both methods remained similar to those of the original chl-a standard (Figure 4). This consistency suggests that the organic solvents used in both methods had negligible impact on the carbon isotope fractionation of the pigments after the N₂ purge procedure aimed at eliminating all the solvents from pigments collected via HPLC analysis.

The average delta ¹³C values (n = 3) of the chl-a standard analyzed using ZM within each injection volume (ranging from 100 µL to 500 µL) were from –27.65 ± 0.70‰ to –28.45 ± 0.29‰ (Figure 4a). Statistical analysis (one-way ANOVA test, p > 0.05) did not reveal significant differences in the delta ¹³C values among different injection volumes. Similarly, the average delta ¹³C values of the chl-a standard analyzed by JM within each injection volume ranged from –27.25 ± 0.44‰ to –28.33 ± 0.23‰ (Figure 4b), with no significant differences among different injection volumes (one-way ANOVA test, p > 0.05). These results collectively affirm that increasing sample injection volume (~500 μL) serves as a suitable strategy for enhancing sensitivity and detectability in pigment production analysis, without incurring carbon isotope fractionation of the pigments.

3.2. Phytoplankton Community Structure and Pigment Production Rates

The investigation into the phytoplankton community structure revealed the absence of distinct spatial variations, with diverse phytoplankton classes exhibiting presence without a dominant class throughout the study period (Figure 5). Bacillariophyceae emerged as the predominant contributors to the phytoplankton community, constituting 30.5 ± 13.8% of the relative contribution, followed by cryptophytes (24.9 ± 8.8%), prasinophytes (17.4 ± 13.8%), prymnesiophytes (12.2 ± 2.0%), pelagophytes (6.5 ± 2.2%), cyanophytes (6.4 ± 2.5%), dinophytes (1.8 ± 2.0%), and chlorophytes (0.2 ± 0.3%) (Figure 5).

Pigment production rates, as determined by in situ field experiments, are presented in Figure 6. Notably, chl-b exhibited relatively high production rates (0.069–0.105 ng C L^–1 h^–1) across all stations except M10 and M12, whereas other pigment production rates remained low (<0.014 ng C L^–1 h^–1) during the study duration (Figure 6a). At M10 and M12, chl-b production rates (0.019–0.024 ng C L^–1 h^–1) were approximately 3.7 times lower compared to other stations, closely aligned with alloxanthin and fucoxanthin production rates at those stations (Figure 6a). Production rates of chl-a, present in all observed phytoplankton classes, outstripped those of other pigments by approximately 1 to 2 orders of magnitude during the study period (Figure 6b). The average chl-a production rate stood at 0.720 ± 0.370 ng C L^–1 h^–1 with a range of 0.358 to 1.371 ng C L^–1 h^–1.

4. Discussion

4.1. Enhancing Sensitivity in Pigment Production Rate Measurement

The dynamic light conditions experienced by phytoplankton in aquatic environments necessitate swift photoadaptation to optimize growth and mitigate photooxidative cell damage [20]. Consequently, pigment dynamics serve as critical indicators of the photophysiological traits of phytoplankton. Yet, unraveling pigment dynamics based solely on pigment concentration variations proves challenging, given the rapid pigment responses to diverse light conditions. This is particularly pertinent due to the high turnover rates of pigments, ranging from minutes to hours [18,19]. In this context, direct measurement of pigment production rates stands as a key parameter for understanding pigment dynamics related to the photophysiological characteristics of phytoplankton. The ¹³C tracer technique is considered the most pertinent method for measuring pigment production rates under natural light conditions due to safety and operational considerations [21]. However, typical pigment analysis using HPLC involves utilizing a small fraction (<10%) of the total sample volume due to the extraction and injection process, subsequently compromising pigment detectability [38]. Consequently, it is challenging to determine carbon allocation rates into individual pigments using the ¹³C tracer technique and HPLC analysis. In this study, to enhance the sensitivity of pigment production rate measurement, two strategies were implemented.

The first strategy involves increasing the ¹³C substrate injection into the incubation bottles to a maximum of 15–17% of the total dissolved inorganic carbon in the water sample. Concerns about this adjustment may arise regarding potential effects on pigment production rate estimations due to increased inorganic carbon levels. However, ref. [21] previously demonstrated that an injection volume of up to 17.7% of the existing inorganic carbon has a negligible impact on determining the photosynthetic rate of marine phytoplankton. As such, the injection volume of ¹³C in our study was chosen judiciously to ensure accurate pigment production rate measurement.

The second strategy is increasing the sample injection volume for HPLC analysis. The optimal injection volume must strike a balance. A small injection volume (<300 µL) of the samples requires numerous repetitions of HPLC analysis to achieve detectable carbon isotope values in the pigments. However, this approach elongates analysis time and induces a dilution effect on the collected pigments, leading to analytical errors in pigment production rate estimation. Conversely, a large sample injection (>700 µL) for HPLC analysis offers advantages in terms of analysis time and dilution effects in comparison to a small injection volume, yet entails the risk of sample loss during the pigment collection procedure. The challenge stems from the need to match the pigment retention time between the first and second analyses during pigment collection using HPLC fraction collectors, and the potential for unintended pigment mixing (Figure 7). Thus, an intermediate sample injection volume (400–600 µL) was identified as optimal for accurate pigment production rate measurement.

4.2. Recommendations for Pigment Production in Field Experiment

One of the most important conditions in field experiments on the pigment production rate is sunlight, so it is important to install the incubator in a well-lit place where sunlight is not blocked by surrounding structures. In field experiments targeting pigment production rates, sunlight availability emerges as a crucial factor. Ensuring the installation of the incubator in well-lit areas free from obstructions is paramount. It is advisable to refrain from incubation during periods of waning sunlight (e.g., after 2 p.m. in the East/Japan Sea), while extending incubation times (~5 h) under weak sunlight conditions, such as cloudy or rainy days, can be beneficial. Injecting the ¹³C reagent into incubation bottles at a level of up to 15% of existing inorganic carbon in the water sample is recommended. If the amount of total dissolved inorganic carbon in the study areas cannot be determined in advance, injecting 1 mL of the ¹³C reagent with a concentration of 4 mg ¹³C mL^–1 into 1 L of seawater volume is recommended. This concentration has proven applicable across diverse marine environmental conditions where the contribution of added ¹³C to existing inorganic carbon remains below 17% [30,39,40,41,42]. Utilizing filter volumes of at least 4–5 L for sample determination of pigment production rate is advised, with larger water volumes (>5 L) recommended to improve detectability and sensitivity.

4.3. Recommendations for Sample Analysis in Home Laboratory

For optimal pigment production, deploying two different HPLC analytical columns for natural and enriched samples can prevent potential delta ¹³C value contamination in pigments from natural samples. The analysis method detailed herein demands approximately 50 min per analysis, with a minimum of five analyses per sample, including pigment concentration, pigment production rate, identification of pigment retention time for collection, and pigment collection. Additional time (around 1 h) is essential to ensure HPLC equipment stabilization for reduced analysis errors. As such, meticulous planning is required to determine the number of samples for analysis each day. This is due to the need for manual verification and correction of pigment retention time shifts during the pigment collection process. A collection time not exceeding 0.4 min is recommended (Figure 8) to prevent excess pigment and analytical eluent accumulation, which could extend eluent removal time, potentially affecting pigment delta ¹³C values.

4.4. Photophysiological Status of Natural Phytoplankton Community

Natural phytoplankton communities are subjected to dynamic light environments, compelling them to adjust pigment compositions to swiftly adapt to light fluctuations. These adaptations encompass light harvesting to maximize energy capture under low light and photoprotection to minimize damage under high light [14]. Key photoprotective pigments, such as zeaxanthin and diatoxanthin, were notably absent, with only limited zeaxanthin production evident in this study (Figure 6a). This suggests that the photoprotective mechanisms may not have been significantly active during the study period. Among the accessory pigments (i.e., xanthophylls and chl-b), chl-b garnered the majority of pigment synthesis (Figure 6a). In this context, it was anticipated that prasinophytes would predominantly contribute to chl-b production, driven by their role as primary chl-b holders. This anticipation stemmed from prasinophytes prominence in the phytoplankton community, given the minimal contribution of chlorophytes (Figure 5). The elevated chl-b production rates in prasinophytes could be indicative of light deprivation or reduced light conditions, likely stemming from competitive disadvantage against dominant phytoplankton classes such as diatoms, cryptophytes, and prymnesiophytes. This assertion aligns with previous findings, suggesting higher light-harvesting pigment content and lower photoprotective carotenoid concentrations in low light-acclimatized cells, contrasting with high light-acclimatized cells [43,44,45,46]. The light deprivation experienced by the prasinophytes, a key component of the studied phytoplankton community, could detrimentally impact the overall primary production rate during the study period. Consequently, prasinophytes may prioritize the pigment production rate (chl-b) to counteract light deprivation, diverting energy from photosynthetic activity and organic matter production. While no relationship between total primary production rate (Table 2) and chl-b production rate was found in this study area, a negative correlation was evident between total primary production rate and chl-a production rate (Figure 9). This underscores the negative impact of compensatory activities, such as pigment production, on primary production due to light limitation. Such compensatory mechanisms could redirect energy away from primary production, potentially affecting overall phytoplankton productivity in the study area.

5. Conclusions

This study navigated the complexities of pigment production analysis, addressing technical challenges such as shifting pigment retention times during HPLC analysis and the manual adjustments required in the fraction collector (Figure 7 and Figure 8). These challenges necessitate further attention to achieve the precision demanded in pigment production assessments. Yet, this study underscores the significance of directly quantifying pigment production rates via advanced HPLC techniques, elucidating the intricate photophysiological responses of phytoplankton. The precision and reliability of our methods were affirmed by establishing linear correlations between chl-a standard peak areas and sample injection volumes. Notably, minimal isotope fractionation effects in the analyzed pigments solidify the robustness of our analytical approach. Furthermore, we demonstrated the efficacy of improving sensitivity in pigment production analysis by increasing the sample injection volume, providing a valuable tool for researchers in the field. Our investigations into phytoplankton community structure and pigment production rates revealed intriguing dynamics. Particularly, chl-b exhibited significant production rates, particularly in all but two stations, implying its vital role within the phytoplankton community. In contrast, other pigment production rates remained relatively low during the study period. Intriguingly, our findings suggest that photoprotective mechanisms, represented by diatoxanthin and zeaxanthin, were not extensively activated during the study. Instead, the conspicuous chl-b production primarily attributed to prasinophytes indicated potential light deprivation, possibly due to competitive disadvantages. This prioritization of pigment production over photosynthetic activity may have implications for overall phytoplankton productivity. Based on these results, incorporating both existing and novel research on phytoplankton pigments will yield valuable insights into the pho-tophysiological status of diverse phytoplankton species (

Table 5. List of references on phytoplankton pigment analysis and production research using HPLC.

Method	Application	Reference No.
Pigment analysis	Analysis of chlorophylls and carotenoids from marine phytoplankton	[23]
	Improved separations of phytoplankton pigments	[47]
	Qualitative and quantitative HPLC analysis	[26]
	HPLC separation of mono- and divinyl chlorophyll forms	[48]
	Separation of chlorophylls and carotenoids from marine phytoplankton	[24]
	Improving HPLC method for determination of carotenoids	[49]
	Increasing sensitivity for RP-HPLC phytoplankton pigment analysis	[38]
	Evaluation of phytoplankton pigment in situ measurements uncertainty	[50]
	Phytoplankton communities using HPLC-CHEMTAX approach	[51]
Pigment production	Chlorophyll a pigment turnover in the marine diatom	[20]
	Carotenoid pigment turnover in the marine diatom	[52]
	Measuring various pigment production rates	[53]
	Physiological characteristics of phytoplankton	[54]

). The potential applications of this methodology extend beyond pigment analysis, enabling in-depth exploration of various organic compounds such as fatty acids and amino acids. This broader scope is pivotal in delineating the nutritional quality of phytoplankton within the marine ecosystem. Additionally, the insights gleaned from the field experiment conducted in this study, employed for pigment production measurements, offer important clues for the complex relationship between light availability, pigment production, and primary production potential of phytoplankton in natural environments. These approaches offer a substantial contribution to the profound understanding of aquatic ecosystem dynamics, encompassing intricate biological interactions and the foundational role of phytoplankton in driving primary production.