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Abstract
Red Noctiluca scintillans (RNS) is one of the major red tide species and dominant bioluminescent plankton in the global offshore. Bioluminescence offers a number of applications for ocean environment assessments such as interval waves study, fish stocks evaluation and underwater target detection making it of significant interest in forecasting bioluminescence occurrence and intensity. RNS is susceptible to changes in marine environmental factors. However, the effects of marine environmental factors on the bioluminescent intensity (BLI, photon s−1) of individual RNS cells (IRNSC) is poorly known. In this study, the effects of temperature, salinity and nutrients on the BLI were studied by field and laboratory culture experiments. In the field experiments, bulk BLI was measured by an underwater bioluminescence assessment tool at various temperature, salinity and nutrient concentrations. To exclude the contribution by other bioluminescent planktons, an identification method of IRNSC was first developed using the features of the bioluminescence flash kinetics (BFK) curve of RNS to identify and extract BLI emitted by an individual RNS cell. To decouple the effects of each environmental factor, laboratory culture experiments were conducted to examine the effects of a single factor on the BLI of IRNSC. The field experiments showed that BLI of IRNSC negatively correlated with temperature (3-27°C) and salinity (30-35‰). The logarithmic BLI can be well fitted using a linear equation with temperature or salinity with Pearson correlation coefficients of -0.95 and -0.80, respectively. The fitting function with salinity was verified by the laboratory culture experiment. On the other hand, no significant correlation was observed between BLI of IRNSC and nutrients. These relationships could be used in the RNS bioluminescence prediction model to improve the prediction accuracy of bioluminescent intensity and spatial distribution.
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1. Introduction
Red Noctiluca scintillans (RNS) is a heterotrophic dinoflagellate feeding on particles, mainly on Platymonas and diatoms, acting as a micro-phytoplankton grazer in the food web in temperate and subtropical coastal waters [1,2]. RNS contains a gas vacuole that enables the creature to move between the surface and bottom of the ocean [3]. RNS is also one of the most important and abundant red tide organisms. In recent years, due to the increasing eutrophication of the marine ecosystem, RNS blooms frequently occurred in the coastal waters worldwide such as in the Sea of Marmara [4,5], the North Sea [6,7], the Black Sea [8,9], coast of India [10,11] and East China Sea [12,13]. Generally, RNS cells aggregate in the spring to summer generating reddish patches or orange discoloration of the water to form the RNS red tide. Due to its unique spectral feature (e.g., strong absorption in the blue-green bands and enhanced scattering in other bands), RNS blooms can be detected and distinguished from the satellite remote sensing imageries [14,15].
In addition to forming red tide, RNS is also one of the primary bioluminescent plankton producing blue bioluminescence at night under mechanical stimulus such as the perturbation of a boat. Bioluminescence of RNS is produced by the chemical reaction of luciferase and fluorescein. Specifically,mechanical disturbances (natural form of stimulation in the marine environment) evoke the mechanical deformation of the RNS cells cytoderm, which in turn can give rise to open the Ca2+ signaling pathway [16,17]. An action potential is then generated on the vacuolar membrane which causes the pH of the scintillation to decrease. The decreasing of pH within the organelles activates luciferase leading to the bioluminescence of RNS [18,19]. Bioluminescence offers a number of applications for ocean environment assessments such as interval waves study, fish stocks evaluation and underwater target detection [20,21]. Therefore, forecasting bioluminescence occurrence and intensity in surface waters is of significant interest. In previous studies, a number of bioluminescence models had been developed to forecast the intensity and spatial distribution of bioluminescence [22–24]. However, these models had limited success in forecasting the abundance and intensity of bioluminescence primarily due to the lack consideration of the ecological and behavioral dynamics of the bioluminescent organisms themselves. The impacts of marine environmental factors on abundance of RNS had been extensive studied. Lugomela et al. (2007) conducted a one-year study in the coastal waters of central Tanzania to explore the spatiotemporal variability of potentially harmful dinoflagellates, and they found that the abundance of RNS was negatively correlated with salinity [25]. Meanwhile, Tian et al. (2017) found that the abundance of RNS in Jiaozhou Bay was negatively correlated with water temperature with the highest population density in February [26]. As a heterotrophic dinoflagellate, RNS is not directly affected by the nutrients, while its dietary algae are affected by nutrients. Intuitively, with the increase of nutrients in the coastal waters, the abundance of Platymonas and diatoms will increase and hence the RNS. Indeed, the increase in RNS abundance was stimulated by high food availability, and the population size of RNS depends on the abundance of diatoms [27–29].
However, the influences of marine environmental factors on bioluminescent intensity (BLI, $\textrm{photon}\,{\textrm{s}^{ - 1}}$) are poorly known. A few studies had been conducted to quantitatively describe the correlations between BLI of bulk bioluminescent organisms and marine environmental factors. For example, Lapota et al. (1992) found that measured bioluminescence in the Beaufort Sea negatively correlated with salinity with coefficients of -0.9 (p < 0.01) [30]. Cao et al. (2011) studied the influence of environmental factors on ship wake bioluminescent organisms by field measurement. The results show that ship wake is more likely to cause bioluminescence under high temperature and salinity or harsh sea conditions [31]. Yishi Li et al. (2020) investigated the effects of temperature, salinity, and chlorophyll concentration on the spatial distribution of bioluminescence by field measurements [32]. To our best knowledge, the impacts of marine environmental factors on the BLI of RNS have not been reported yet. To fill this knowledge gap, we conducted field and laboratory experiments to quantify the relationships between some key marine environmental factors (i.e., temperature, salinity, and nutrients) and the BLI of individual RNS cell. The findings of this study would provide the essential parameters to improve RNS bioluminescence forecasting model.
2. Data and methods
2.1 Field experiments
The field experiments were conducted in the East China Sea (ECS), the Yellow Sea (YS) and the Bohai Sea (BS) from 2017 to 2018. The locations of each experiment are shown in Fig. 1. In each experiment, profiling bioluminescence flash kinetic (BFK) of bioluminescent organisms in the seawater was measured by an Underwater Bioluminescence Assessment Tool (UBAT, WET Labs) with 60 Hz sampling rate. BFK refers to the change of BLI over time during a flash, describing the bioluminescence capacity and characteristics of a bioluminescent organism. The UBAT was horizontally mounted on an optical cage to expel the air from the detection chamber and the optical cage was attached to a winch to measure BFK from the ocean surface down to the bottom or 200 m depth. UBAT uses an internal pump to provide the mechanical stimulation for seawater in the detection chamber with the volume of 0.44 L. The flow rate of the pump is approximately 1200 revolutions per minute (RPM) which roughly equals to 0.33 L seawater passing through the detection chamber of UBAT in each second. The characteristics of BFK are described with four parameters, i.e., the peak intensity ($B{L_{max}}$), average intensity ($B{L_{mean}}$), time from start to peak (${T_{max}}$), and duration of bioluminescence (${T_{total}}$) [33], as illustrated in Fig. 2. Mean bioluminescence intensity (MBLI) was calculated as the ratio of integration of BLI to ${T_{total}}$ to represent the average bioluminescence intensity of RNS. The BLI was directedly calculated by applying a calibration coefficient to the raw data.
where DN is raw data in digital counts and S is the calibration coefficient. The concurrent seawater temperature and salinity were measured by a CTD (SBE19PLUS, SeaBird) deployed in the rosette sampling system.
Fig. 1. Distribution of sampling stations in the East China Sea (ECS, red dots), the Yellow Sea and Bohai Sea in the winter of 2017 (YSBS-2017, blue dots) and the spring of 2018 (YSBS-2018, green dots), and Xiamen Bay (XMB, black dots).
Fig. 2. Schematic diagram of bioluminescence flash kinetics (BFK) curve and the associated BFK parameters including the peak intensity ($B{L_{max}}$), average intensity ($B{L_{mean}}$), time from start to peak (${T_{max}}$), and duration of bioluminescence (${T_{total}}$)
Profiling BFK measured by the UBAT mounted in the optical cage were contributed by all potential bioluminescent organisms in the study area. The BFK of individual RNS cell was measured by the UBAT using water samples collected by the Niskin bottles in the CTD rosette sampling system onboard the research vessel. Water samples were first filtered using a sieve with pore size of 20 µm to remove large particles or zooplanktons. The filtered water samples were processed in different ways for abundance estimation and BFK measurement. For bioluminescent organism abundance estimation, filtered water samples were poured into a 250 ml sampling bottles and added 2% formaldehyde to preserve the morphology of the cells. The preserved samples were analyzed in the laboratory to determine the bioluminescent species using an inverted microscope (CNOPTEC, BDS400) and calculate the corresponding abundance of each species. For bioluminescent organism BFK measurement, the filtered water samples were poured into a glass beaker and phytoplankton cells were picked up using a plastic dropper with the inverted microscope and stored in different cell culture flasks. Then, three cells of each bioluminescent species were gently picked up using a large-caliber pipette to prevent pre-stimulation. Once the bioluminescent cell was stimulated, a flash would be observed and this cell were discarded. The un-stimulated cell was placed in the intake of the UBAT filled in a tank with 0.7$\mu $m-filtered seawater to measure BFK of the individual cell. The background values were recorded before the measurements. After the 5-minute measurements, the tank was completely rinsed to make sure the bioluminescent cell was removed.
Nutrients were measured in the spring of 2018 (YSBS-2018). First, 2 L of water samples were filtered through a 0.45µm polyethersulfone membrane to remove particles. Then, $\textrm{N}{\textrm{H}_4} - \textrm{N}$ was determined using the sodium hypobromite oxidation-spectrophotometric method. Other nutrients including $\textrm{Si}{\textrm{O}_4} - \textrm{Si}$, $\textrm{N}{\textrm{O}_3} - \textrm{N}$, $\textrm{N}{\textrm{O}_2} - \textrm{N}$, $\textrm{P}{\textrm{O}_4} - \textrm{P}$ were determined using a SEAL AA3 nutrient autoanalyzer. Table 1 summarizes the cruise information and parameters measured in each experiment.
Table 1. Cruise information and measured parameters including bioluminescence flash kinetic (BFK) of bulk bioluminescent organisms, temperature (T), salinity (S), BFK of individual Red Noctiluca Scintillans cells (BFK-IRNSC), nutrients and main bioluminescent phytoplankton species.
2.2 Identification and extraction of IRNSC from bulk BFK curves in the fieldexperiments
The BFK curves measured by the UBAT in the field were the bioluminescent intensity contributed by all bioluminescent organisms. To examine the BFK curve of individual RNS cell (IRNSC), the BLI solely contributed by each RNS cell need to be identified and extracted from the bulk BFK curves. Figure 3 shows two examples of BFK measured by the UBAT in the YSBS-2018 experiment. For both measurements, BLI exhibits multi-peaks indicating the bioluminescence was very likely emitted by multiple bioluminescent organisms at nearly the same time. However, a few single BLI peaks can also be observed (boxed by the red rectangle in Fig. 3) with different peak intensity ($B{L_{max}}$) and duration time (${T_{max}}$). In principle, the single peak BLI was emitted by a bioluminescent organism. By extracting single peaks from bulk BFK curves, the BFK emitted by individual bioluminescent organism can be determined. The criterion to extracting single peak from bulk BFK curves is whether two sides of the peak are monotonically decreasing down to zero. If the curve meets this criterion, it has a single peak, otherwise, it has multiple peaks. Once the single-peak BFK was extracted, the specific organism can be determined by its characteristics such as $B{L_{max}}$ and ${T_{max}}$. Indeed, BFK has been used in marine biology studies to identify different bioluminescent organisms [33]. Following this principle, an IRNSC identification and extraction method from bulk BFK curves was proposed in this study (Fig. 4). Basically, BFK curves of main bioluminescent organisms such as RNS, Protoperidinuim, Dinophysis, Ceratium furca, and Ceratium horridum were measured and analyzed. The thresholds of BFK parameters for RNS were determined to differentiate RNS cells from other bioluminescent organisms. Then, single BLI peaks were identified from the bulk BFK measured by the UBAT and the corresponding BFK parameters were calculated. Finally, the thresholds were applied to determine whether the sing peak BLI was emitted by an RNS cell.
Fig. 3. Two examples of bioluminescence flash kinetic (BFK) measured by the UBAT in the Yellow Sea and Bohai Sea in the spring of 2018 (YSBS-2018) experiment, the single peak BFK boxed by the red rectangle indicated bioluminescence was emitted by an individual cell.
Fig. 4. Flow chart for discrimination of bioluminescence flash kinetics (BFK) curve of individual Red Noctiluca Scintillans cell (IRNSC). $B{L_{max}}$ and ${T_{max}}$ are characteristic of BFK indicating peak bioluminescence intensity and duration time. , $B{L_2}$, ${T_1}$, and ${T_2}$ are thresholds to differentiate Red Noctiluca Scintillans from other bioluminescence organisms.
2.3 Laboratory culture experiment
RNS culture experiments were conducted in the laboratory of algae culture in Xiamen University to study the effects of salinity and nutrients on the bioluminescence of IRNSC. The RNS samples were collected in Xiamen Bay (XMB, Fig. 1). Following the protocols of phytoplankton survey specifications, a biological trawl net with an aperture of 20µm was vertically dragged at a speed of 0.5 m/s at each sampling station in the surface layer (0 ∼ 5 m). The water samples collected by trawl net were stored in 500 mL sampling bottles for further operations in the laboratory. After sample collection, they were poured into a glass beaker in the laboratory and allowed RNS to aggregate on the surface for 6 h. Then, RNS cells were picked up using a large-caliber pipette. The mature nurse cells of RNS were further extracted with a plastic dropper under an inverted microscope. The picked RNS cells were approximately 10 thousand and stored in a 1 L cell culture flask for the culture experiments. Meanwhile, the culture medium was prepared with filtered seawater using a 0.7-µm glass fiber (GF/F) membrane to remove other plankton organisms.
The laboratory culture experiments were conducted under four salinities and five nutrient conditions. In addition, the culture temperature was set as (20 ± 1) °C, the illuminance was set as 2000 lux, and the light cycle of this experiment was set as 10 L:14 D. Totally, there were 20 scenarios for a different combination of salinity and nutrients. In each culture experiment, 200 RNS cells were picked into a 250 mL cell culture flask with 200 mL sterilized seawater and cultured them for 17 days since their life cycle is about three weeks [34]. The suitable salinity for RNS growth is ranging from 19 to 33 [35]. Therefore, the salinity of seawater was set as 20‰, 25‰, 30‰, and 35‰ by mixing high salinity seawater with ultrapure water in appropriate proportions. Nitrogen and phosphorus are two major nutrients affecting the growth and reproduction of RNS. However, studies showed that inorganic phosphorus dramatically changed before and after the RNS blooms while inorganic nitrogen barely changed . To examine the effects of phosphors on the bioluminescence of RNS, two nitrogen and phosphorus molar ratios, i.e., N:P = 24:1 and N:P = 24:0.5, were adopted in the culture experiments. Specifically, nutrients in the culture experiments were set as N & P-free, P-free, N-free, N:P = 24:1, and N:P = 24:0.5. The inorganic nitrogen and phosphorus were prepared by mixing $\textrm{Na}{\textrm{H}_2}\textrm{P}{\textrm{O}_4}$ and $\textrm{NaN}{\textrm{O}_3}$ (Cellbio) master solutions. Platymonas was selected as the dietary algae of RNS with the density of ${10^8}$ cells/L in each culture experiment [26]. Three RNS cells were randomly picked up from the culturing bottle to measure BFK of each RNS cell using the UBAT in the black tank following the same procedure adopted in the section 2.1.
3. Result
3.1 BFK of IRNSC
The mean BFK curves of five major bioluminescent organisms measured in the field and RNS measured in the culture experiment are shown in Fig. 5. The corresponding BFK parameters are listed in Table 2. Obviously, RNS cell emits strong bioluminescent with the peak intensity up to $9.5 \times {10^9}$ and mean intensity of 3.$0 \times {10^8}$ photon ${s^{ - 1}}$, much stronger than other bioluminescent organisms with peak intensity < 1.3${\times} {10^9}$ photon ${s^{ - 1}}$ and mean intensity < 1.$0 \times {10^8}$ photon ${s^{ - 1}}$. Also, bioluminescent emitting time of RNS cell is longer than most other bioluminescent organism except for Protoperidinium with ${T_{max}}$ up to 0.1 s and ${T_{total}}$ up to 0.7 s. Interestingly, RNS cultured in the laboratory emitted stronger bioluminescent light and lasted relatively longer time than those measured in the field. For example, $B{L_{max}}$ and $B{L_{mean}}$ can be up to 440 ${\times} {10^9}$ and 13.$7 \times {10^8}$ photon ${s^{ - 1}}$, approximately 4-fold stronger than those measured in the field. In contrast, Ceratium furca and Ceratium horridum emit relatively weak BLI with the mean value of 4${\times} {10^6}$ and 5${\times} {10^6}$ photon ${s^{ - 1}}$, and short duration time with the mean value of 0.1s.
Fig. 5. The bioluminescence flash kinetics (BFK) of five major bioluminescent organisms measured in the field. The error bars represent the standard deviation of bioluminescent intensity of each bioluminescent organism measured in the field.
Table 2. The ranges of bioluminescence flash kinetics (BFK) characteristics of main bioluminescent phytoplankton in the study area. The characteristics of BFK include peak intensity (BLmax), mean intensity (BLmean), total duration time (Ttotal) and duration time to the peak intensity (Tmax)
Based on BFK features measured in the field and cultured experiments for main bioluminescent organisms, four thresholds were determined to differentiate RNS from other main bioluminescent organisms, i.e., $B{L_1}$ = 5 x${10^8}$ photon ${\textrm{s}^{ - 1}}$, $B{L_2}$ = 500 x${10^8}$ photon ${\textrm{s}^{ - 1}}$, ${T_1}$ = 0.05 s and ${T_2}$ = 0.2 s. These thresholds were applied to bulk BFK curves measured by the UBAT in the field to identify bioluminescent intensity emitted by each RNS cell following the procedure described in Fig. 4. In other words, only when single peak BLI meets $B{L_1}$<$B{L_{max}}$<$B{L_2}$ and ${T_1}$<Tmax<${T_2}$, this single peak is identified as emitted by IRNSC.
3.2 Effects of temperature on the MBLI of IRNSC
Temperature is an essential environmental regulator of phytoplankton growth and reproduction in the ocean through photosynthesis or the respiration process. Because the field experiments were conducted in spring, summer, and winter, sea water temperature widely changed from 3 to 27 °C, providing the opportunity to study the effects of temperature on the bioluminescent intensity of IRNSC. For each measurement, BFK curve of IRNSC was first identified and extracted from the bulk BFK curves measured by the UBAT in the field. Subsequently, each MBLI of IRNSC was calculated and classified into different groups based on the measured temperature in 1°C intervals. The number of measurements in each temperature bin were different with the minimum value of 61 occurring in the temperature of 18-19$\mathrm{\circ{C}}$ and the maximum value of 410 occurring in the temperature of 4-5$\mathrm{\circ{C}}$. Finally, the median and one standard deviation of MBLI in each temperature group were calculated and shown in Fig. 6. Because BS and YS are located in the north of China marginal seas and two experiments were conducted in the spring and winter, the temperature observed in YSBS-2017 and YSBS-2018 experiments is lower ranging from 3 to 14 °C. On the other hand, the higher temperature is observed in the ECS ranging from 13 to 27 °C. Overall, a strong negative correlation is observed between MBLI and temperature with the Pearson correlation coefficient of -0.95 (P < 0.01). The logarithmic MBLI can be well fitted with the linear equation and expressed in Eq. (2). The equation indicated that the BLI decreases approximately 15% with 1°C temperature increase. To examine whether the relationship observed in Fig. 6 is affected by the salinity, the relationship between MBLI and temperature at two constant salinities (i.e., S = 32.3‰ and S = 34.3‰) is shown in Fig. 7. Similarly, strong negative correlations between MBLI and temperature are observed at two fixed salinities (P < 0.01), suggesting that BLI of IRNSC indeed decreases with the increase of temperature at least in the study area.
Fig. 6. Relationship between mean bioluminescence intensity (MBLI) with temperature in the East China Sea (ECS), the Yellow Sea and Bohai Sea in spring of 2017 (YSBS-2017) and in the winter of 2018 (YSBS-2018) experiments. The error bars represent one standard deviation. The Pearson correlation coefficient (r) is -0.95.
Fig. 7. Same with Fig. 6 but at two fixed salinities of 32.3 ‰ (blue circle) and 34.3 ‰ (red circle).
3.3 Effects of salinity on the MBLI of IRNSC
To examine the effects of salinity on the MBLI, a similar procedure was conducted to group MBLI measured at various salinities in intervals of 0.5 ‰ for measurements in the ECS, YSBS-2017, and YSBS-2018. The corresponding median and one standard deviation of MBLI were also calculated and shown in Fig. 8. Similar with temperature, a strong negative correlation between MBLI and salinity is observed with Pearson correlation coefficient of -0.80 (P < 0.01). The logarithmic MBLI can also be expressed with the linear equation (Eq. (3)). The equation implied that the MBLI decreases approximately 50% with 1‰ salinity increases. Likewise, MBLI against salinity at two constant temperatures (e.g., T = 10 °C and T = 20 °C) was investigated to minimize the effects of temperature (Fig. 9). Also, strong negative correlations between MBLI and salinities are observed regardless of the temperature (P < 0.01). During field measurements, salinity only varied in a limited range approximately from 31 ∼ 35‰. To further examine the effects of salinity on the MBLI in the relatively wide ranges, the MBLI of IRNSC cultured in the laboratory in the salinity range of 25 ∼ 35‰ was measured. Unlike the negative linear relationship observed in the field (31-35‰), a nonlinear relationship between MBLI and salinity was observed in the salinity range of 25∼ 35‰ exhibiting different behaviors with a peak at salinity of 25 and decreasing toward higher or lower salinity. In the salinity ranges between 30 ∼ 35‰, MBLI of IRNSC cultured in the laboratory decreases with the increase of salinity, consistent with field observations, while the opposite relationship was observed in the salinity ranges between 20 ∼ 25‰.
Fig. 8. Relationship between mean bioluminescence intensity (MBLI) with salinity in the East China Sea (ECS), the Yellow Sea and Bohai Sea in spring of 2017 (YSBS-2017), the winter of 2018 (YSBS-2018) experiments and in the laboratory experiments. The error bars represent one standard deviation. The Pearson correlation coefficient (r) is -0.80.
3.4 Effects of nutrients on the MBLI of IRNSC
Nitrogen and phosphorus play an important role in the growth of plankton, and they are indispensable environmental factors for the growth and reproduction of plankton. The concentrations of five nutrients including $\textrm{N}{\textrm{H}_4} - \textrm{N}$, $\textrm{Si}{\textrm{O}_4} - \textrm{Si}$, $\textrm{N}{\textrm{O}_3} - \textrm{N}$, $\textrm{N}{\textrm{O}_2} - \textrm{N}$, $\textrm{P}{\textrm{O}_4} - \textrm{P}$ were measured in each station in the YSBS-2018 experiment (Table 3). To examine the effects of nutrients on the MBLI, the comparison between MBLI and various nutrients is shown in Fig. 10. Clearly, no significant correlation between nutrients and MBLI was observed with $\textrm{N}{\textrm{H}_4} - \textrm{N}$ (r < 0.2) and other nutrients (r < 0.1). In the laboratory culture experiment, the effects of nutrients on the MBLI were also studied by adding different concentrations of nitrogen and phosphorus (Fig. 11). Similar to field measurements, no significant correlation between nutrients and MBLI (r < 0.2) was observed though a slight dependence of MBLI on the nutrients can be found. The lowest MBLI was observed in nutrient-free conditions and the highest MBLI was observed in phosphorus-rich conditions (N:P = 24:1). Note that, the influence of nutrients on NS is indirect through feeding dietary algae.
Fig. 10. Variations of mean bioluminescence intensity (MBLI) of individual Red Noctiluca scintillans cells (IRNSC) with five main nutrients measured in the YSBS-2018.
Fig. 11. Mean and one standard deviation of bioluminescence intensity under different nutrient salts conditions in the laboratory culture experiment.
Table 3. Concentration ranges of five nutrients measured in YSBS-2018 experiment
4. Discussion and conclusion
RNS is one of the major red tide species and dominant bioluminescent plankton in the global offshore and is susceptible to changes in marine environment factors. Bioluminescence of RNS can be applied in various ocean environmental assessments such as interval waves study, fish stocks evaluation and underwater target detection. A number of bioluminescence models had been developed to forecast the intensity and spatial distribution of bioluminescence but had limited success primarily due to the lack of consideration of the ecological and behavioral dynamics of the bioluminescent organisms themselves. Many laboratory experiments were conducted to study the effects of environmental factors on the growth and reproduction of RNS and found that RNS grew well under low temperature and low salt conditions. However, the influences of marine environmental factors on BLI are poorly known.
In this study, field and laboratory experiments were conducted to study the relationships between marine environmental factors (i.e., temperature, salinity and nutrients) and BLI of IRNSC. In the field experiments, the BLI of various bioluminescence organisms in the China seas were measured by the UBAT. To exclude the contribution by other bioluminescent planktons, an IRNSC identification and extraction method from bulk BFK measurements was developed by comparing BFK features of five main bioluminescence organisms. The extracted BLI of IRNSC was pooled together and divided into 1°C interval temperature bins or 1‰ salinity bins. In each bin, the mean and standard deviation of BLI was calculated. The results showed that BLI of IRNSC negatively correlated with temperature (3-27°C) and salinity (30-35‰). The logarithmic BLI can be well fitted using a linear equation with temperature (Eq. (2)) or salinity (Eq. (3)) with Pearson correlation coefficients of -0.95 and -0.80, respectively. The fitting functions indicated that BLI decreases approximately 15% and 50% with 1°C temperature or 1‰ salinity increases, respectively. The relationship of BLI with salinity (Eq.3) was verified with the laboratory culture experiment (Fig. 8). Indeed, BLI negatively correlated with salinity in the range of 30-35‰ consistent with field experiments. However, BLI positively correlated with salinity in the range of 20-25‰ indicating the complex dependence of BLI on salinity.
Both field and laboratory culture experiments showed that BLI of IRNSC barely depended on nutrients. A possible explanation is the eutrophication status of the YS and BS. In recent years, the abundance of diatoms, one of the main diets of RNS, in the YS and BS has increased significantly due to the increasing fertilizer use and wastewater discharge. Therefore, the feeding of RNS on the dietary algae may reach saturation and be independent on the concentration of nutrients. However, nutrients might affect BLI of IRNSC in oligotrophic waters.
Many marine environmental factors such as light, depth even the physiological status of the cell can affect the BLI of a plankton cell and some of their effects might couple together making it difficult to study the impacts of a single factor on the BLI in the field. In this manuscript, we presented the primary results of impacts of temperature, salinity and nutrients on the BLI of a single RNS cell. To minimize the effects of other factors, we plotted the BLI vs. temperature at two fixed salinities (Fig. 7) and BLI vs. salinity at two fixed temperatures (Fig. 9). Interestingly, the patterns of BLI with temperature and salinity are very similar regardless of the other factors were fixed or not (Fig. 6 vs. Figure 7, Fig. 8 vs. Figure 9). This might imply that the effects of other factor were cancelled out when averaging in some extent. Nevertheless, more works are needed to separate the effects of each factor on the BLI of RNS.
Funding
National Natural Science Foundation of China (T2222010.).
Acknowledgments
Data acquisition and sample collections were supported by NSFC. We are very grateful to the people who helped during the field measurements. We appreciate valuable comments from two anonymous reviewers which greatly improve this manuscript.
Disclosures
The authors declare no conflicts of interest.
Data availability
Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.
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