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Effect of dissolved organic nitrogen on the bloom of Prorocentrum donghaiense and Karenia spp. in the East China Sea coastal waters
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Xiaoru Cui1, 2, Guangming Zhen3, Jing Zhao1, *, Keqiang Li1, 3, *, Xiulin Wang1, 3
Acta Oceanologica Sinica | 2024, 43(6) : 71 - 85
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Acta Oceanologica Sinica | 2024, 43(6): 71-85
• Articles •
Effect of dissolved organic nitrogen on the bloom of Prorocentrum donghaiense and Karenia spp. in the East China Sea coastal waters
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Xiaoru Cui1, 2, Guangming Zhen3, Jing Zhao1, *, Keqiang Li1, 3, *, Xiulin Wang1, 3
Affiliations
  • 1 Key Laboratory of Marine Chemistry Theory and Technology/Frontiers Science Center for Deep Ocean Multispheres and Earth System of Ministry of Education, Ocean University of China, Qingdao 266100, China
  • 2 College of Environmental Science and Engineering, Ocean University of China, Qingdao 266100, China
  • 3 College of Chemistry and Chemical Engineering, Ocean University of China, Qingdao 266100, China
Published: 2024-06-25 doi: 10.1007/s13131-023-2308-9
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Understanding the mechanism of harmful algal bloom formation is vital for effectively preventing algal bloom outbreaks in coastal environments. Karenia spp. blooms in the East China Sea show a significant correlation with nutrient regimes. However, the impact of key components of nutrients, especially dissolved organic nitrogen (DON), on the blooms of Karenia spp. is not clear. Quantitative research is still lacking. In this study, the cruise observations, field mesocosm-flask culture experiments, and a multinitrogen-tri-phytoplankton-detritus model (NTPD) are combined to reveal the quantitative influence of nutrient regimes on the shift of Prorocentrum donghaiense and Karenia spp. in the East China Sea. It has a synchronism rhythm of diatom-P. donghaiense-Karenia spp.-diatom loop in the field culture experiment, which is consistent with the results of the cruise observation. The results showed that the processes of terrigenous DON (TeDON) and dissolved inorganic nitrogen (DIN: $\mathrm{NO}_{3}^{-} $-N, $\mathrm{NH}_{4}^{+} $-N) absorption promoted P. donghaiense to become the dominant algae in the community; whereas the processes of DON from P. donghaiense absorption promoted Karenia spp. to become the dominant algae in ambient DIN exhaustion. In addition, the three-dimensional fluorescence components of humus C, tyrosine and fulvic acid can indicate the processes of growth and extinction of P. donghaiense and Karenia spp., respectively. This study infers that P. donghaiense and Karenia spp. regime shift mechanism associated with the nutrient regime in coastal waters, which provides a scientific basis for the environmental management of coastal ecosystem health.

Karenia spp.  /  Prorocentrum donghaiense  /  nutrients  /  multinitrogen-tri-phytoplankton-detritus model  /  three-dimensional fluorescence
Xiaoru Cui, Guangming Zhen, Jing Zhao, Keqiang Li, Xiulin Wang. Effect of dissolved organic nitrogen on the bloom of Prorocentrum donghaiense and Karenia spp. in the East China Sea coastal waters[J]. Acta Oceanologica Sinica, 2024 , 43 (6) : 71 -85 . DOI: 10.1007/s13131-023-2308-9
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1 Introduction
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With the impact of human activities, excessive nutrients discharge into the sea can lead to eutrophication. Coastal eutrophication can result in a decline in biodiversity and is the main factor contributing to harmful algal bloom (HAB) outbreaks (Anderson et al., 2002; Imai et al., 2006; Heisler et al., 2008). The toxigenic dinoflagellate blooms of Karenia spp. in the Gulf of Mexico has been studied since the 1960s and is characterized by a long duration and significant harm to aquatic organisms (Steidinger, 2009). In recent decades, Karenia spp. blooms have frequently appeared in global near-shore waters. In China, Karenia spp. blooms have trended from south to north since 1998 in the Zhujiang River Estuary (Li et al., 2019), coastal waters of Fujian Province (Long and Du, 2005), Changjiang River Estuary (Zhou et al., 2006), coast of Zhejiang Province (Yao et al., 2007) and Bohai Sea (An et al., 2011). Among them, the typical species are Karenia mikimotoi (Chen et al., 2021), Karenia brevis (Wang et al., 2006) and Karenia digitalis (Cen et al., 2020). Therefore, it is essential to study the ecological and oceanographic mechanisms of the algal blooms of Karenia spp.
The coastal waters of Sansha Town in Fujian Province, China have been a critical monitoring area for HABs in the East China Sea since 1989, with an average number of algae cells in surface seawater reaching 106 cells/L (Zhao et al., 2021). According to the historical data, the peak HABs in the East China Sea were mainly concentrated in spring and summer, and the dominant algal species were Prorocentrum donghaiense and Karenia spp. Meanwhile, the dominant group of algal blooms in this area evolved from nontoxic diatoms to partially toxigenic dinoflagellates, which fits a historical pattern of bloom (Glibert and Burkholder, 2011; Yan and Zhou, 2004; Zhou et al., 2008). Some studies predicted that by the end of 21st century, the biomass of 70% of dinoflagellates in the East China Sea will increase and that of diatoms will decrease (Xiao et al., 2018). Toxigenic dinoflagellate blooms would become more frequent and intense, under uncontrolled conditions and threaten the marine ecological health of the East China Sea (Xiao et al., 2018a, 2018b; Wang et al., 2022).
Many studies on blooms focused on the nearshore region and ascribed blooms to rainfall, runoff and ground water (Hu et al., 2006; Brand and Compton, 2007; Medina et al., 2020). However, the outbreak and maintenance of HABs involve a series of complex biological and chemical processes, including nutrient preferences and competition, growth rates, species competition and mortality (Liu et al., 2001; Mulholland et al., 2006; Vargo et al., 2008; O’Neil and Heil, 2014; Tilney et al., 2019). For example, the cell density of Karenia spp. was significantly positively correlated with chlorophyll a, inorganic phosphorus, chemical oxygen demand (COD) and dissolved oxygen (DO), and negatively correlated with ammonia nitrogen (Killberg-Thoreson et al., 2014). It is crucial to study the growth characteristics, environmental factors, and other physiological and ecological mechanisms, as well as the impact of nutrients in controlling algal blooms.
The concentration level and structure of nutrients are the foundation for the occurrence and decline of Karenia spp. blooms (Zhao et al., 2020; Zhang et al., 2015). Heil et al. (2014) found that coastal eutrophication caused by the increased nutrient concentration in coastal waters was the main reason for the algal bloom of Karenia breuis. Generally, environmental conditions with low concentrations of dissolved inorganic nutrients (DIN) and high concentrations of dissolved organic nutrients (DON, DOP) are favorable for dinoflagellate growth (Antia et al., 1991; Jeong et al., 2017; Kwon et al., 2019; Park et al., 2022). It was found that DON and urea concentrations could be critical regulatory factors for the density of small nudidinodinates such as Karenia (Lai et al., 2011). Because Karenia had enhanced absorption and utilization capacity of urea, DON and DOP under eutrophication conditions (Wang, 2015; Xia, 2016). In addition, ammonia nitrogen may be the main nutrient controlling factor in the Karenia spp. blooms, especially K. mikimotoi (Zhao et al., 2020). HABs are known to be influenced by nutrient concentration levels and structures. However, the impact of key factors and processes of nutrients on the blooms of Karenia spp. remains unclear.
Eutrophication is usually the key driver of HABs. Although some studies have shown that Karenia spp. can sustain its growth or competitive growth by absorbing phagocytic DON or DOP, and the key components of the dissolved organic matter remain unclear. The quantitative influence of nutrients on Karenia spp. blooms, especially DON and DOP, has not been studied. Therefore, field culture experiments and field observations were carried out in the coastal waters of the East China Sea to investigate the effects of DON on the growth of Karenia spp., using algal culture water and sewage water as DON sources. In addition, a three-dimensional fluorescence spectrum was used to analyze the effects of different DOM components. Furthermore, a multinitrogen tri-algae biogeochemical model was constructed to clarify the driving impact of nutrients on the blooms of Karenia spp. This work will provide information on the healthy and sustainable development of coastal ecosystems.
2 Methods
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2.1 Study area and field cruise observation
The cruise stations are located in the East China Sea coastal waters of Sansha Town (26°92′N, 120°22′E), Fujian Province, China, with an average water depth of 34.9 m (Fig. 1). In recent years, due to the tremendous impact of human activities, P. donghaiense and Karenia spp. blooms have caused considerable damage to cooccurring organisms due to oxygen depletion and potential ammonium toxicity for fish (Huang and Qi, 1997; Harrison et al., 2011), resulting in profound negative impacts on the local tourism, aquaculture and marine ecological environments. A total of nine times of HABs occurred in Fujian Province, which lasted 57 d and affected an area of 110.54 km2 in 2019. Among them, there were three associated toxic HABs caused by K. mikimotoi, accounting for 23.97% of the total area of HABs (Fujian Provincial Department of Ocean and Fisheries, 2019).
Six cruises were conducted at 16 survey stations from April 25 to June 12, 2019, to observe the blooms of P. donghaiense and Karenia spp. in coastal waters of Sansha Town. From May 23 to May 29, 2019, K. mikimotoi and P. donghaiense blooms broke out in Sansha Town coastal waters. According to the field investigation results, the density of Karenia spp. and Scrippsiella sp. were 106 cells/L and 107 cells/L, respectively, and the abundance of P. donghaiense was 108 cells/L. The numerical changes in temperature, salinity and DO in Sansha Town from April 25 to June 11, 2019, were shown in Fig. S1.
2.2 Field culture experiment
The field mesocosm-flask culture experiments were performed on the fishing culture float shelf at the Station R1 (26°92.1′N, 120°27.1′E; Fig. 1) from June 6 to 16, 2019, where the seawater was collected at the time of the late stage of the algal bloom. The surface seawater was filtered by a 200 μm sieve (with zooplankton removed) to explore the effects of different sources of nutrients on the growth of phytoplankton. A 15 L PVC plastic bottle was filled with 10 L seawater, and the culture bottle was placed in the float shelf. The aim was to keep the temperature consistent with sea water and to simulate natural conditions as much as possible. We used three kinds of nitrogen nutrients ($\mathrm{NO}_{3}^{-} $-N, $\mathrm{NH}_{4}^{+} $-N, DON) and $\mathrm{PO}_{4}^{3-} $-P as the experimental groups and added $\mathrm{NH}_{4}^{+} $-N at low concentrations and no nutrients as the DON control and blank, respectively. All groups were subjected to double disposal. Two kinds of DON were used: marine DON (MDON), taken from P. donghaiense culture water, and terrigenous DON (TeDON), taken from sewage treatment plants. The initial nutrient concentrations of the different enrichment groups are shown in Table 1, and the experimental apparatus is shown in Fig. 2.
The incubation period was 10 d, and samples were taken seven times: 0 d, 1 d, 2 d, 3 d, 4 d, 7 d and 9 d. The samples were taken regularly after each shake. The water sample was passed through 0.7 μm glass fiber filters (GF/F) immediately after collection. The filtrate was stored in four 40 mL brown glass vials for the determination of dissolved nutrients ($\mathrm{NO}_{3}^{-} $-N, $\mathrm{NO}_{2}^{-} $-N, $\mathrm{NH}_{4}^{+} $-N, $\mathrm{PO}_{4}^{3-} $-P, TDN, TDP), dissolved organic carbon (DOC) and colored dissolved organic matter (CDOM). The filter was wrapped in aluminum foil for the determination of PN (particle nitrogen)/PP (particle phosphorus) and Chl a. Except for CDOM samples, other samples were frozen at −20℃. All glass vials and filters used for collecting samples were combusted at 450℃ for 4 h. The values of temperature, DO, and pH were measured with a YSI (Professional Plus) and an illuminometer (LIHUADA, DT1332A) before sampling.
2.3 Sample analysis method
2.3.1 Analysis methods of nutrients
Nutrients of $\mathrm{NH}_{4}^{+} $-N, $\mathrm{NO}_{2}^{-} $-N, $\mathrm{NO}_{3}^{-} $-N, and $\mathrm{PO}_{4}^{3-} $-P were determined by a nutrient automatic analyzer (Bran-Lubbe Aiii, Germany) according to the method of Strickland and Parsons (1970). Seawater samples of TDN and TDP were oxidized by persulfate oxidation (120℃, 30 min) before they were determined using an autoanalyzer (Kwon et al., 2019). DON and DOP concentrations were calculated by subtracting inorganic nutrient concentrations from total dissolved nutrients (DON = TDN − DIN, DOP = TDP − $\mathrm{PO}_{4}^{3-} $-P). The filter samples of PP and PN were oxidized by persulfate oxidation (120℃, 30 min) and then determined using an autoanalyzer (Kwon et al., 2019). The DOC concentration was measured by high-temperature catalytic oxidation with an automatic analyzer (Multi N/C 3100, Germany).
2.3.2 Method of Chl a and phytoplankton analysis
The samples of Chl a were analyzed using a UV‒Vis spectrophotometer (Optizen Alpha, Korea) after extraction with 90% acetone at 0℃ under dark conditions for 12−14 h (Parsons et al., 1984). The water samples of phytoplankton were fixed immediately after collection using Lugol’s solution (20 g KI + 200 mL MQ water + 10 g I2 + 20 mL acetic acid). Then the phytoplankton counting frame (0.1 mL) was utilized for identification and counting under an inverted microscope.
2.3.3 Three-dimensional fluorescence spectrometry
Fluorolog-3 (France-Jobin Yvon) was used to determine the emission excitation matrix (EEM) and three-dimensional fluorescence characteristics of the DOM samples (Massi et al., 2020). The composition and relative values of DOM in each sample were ultimately obtained by parallel factor analysis (Stedmon and Bro, 2008), which was performed using MATLAB software (MathWorks) with correction, descattering, and dearraying programs to analyze EEM.
2.4 Model description
The multinitrogen-tri-phytoplankton-detritus model (NTPD) was established using Modelmaker 4.0 (Cherwell Scientific Ltd., UK) to simulate the growth dynamics of three phytoplankton species. Based on the nutrient-biophytoplankton-detritus (NbPD) model (Chen et al., 2022), two dinoflagellates (P. donghaiense and Karenia spp.) and a diatom. In this model, the main environmental factors (e.g., temperature and light), nitrification and denitrification process equations of nutrients are consistent with the NbPD model (Chen et al., 2022).
The phytoplankton biomass in the field culture experiment was expressed as Chl a (μg/L) (Boyer et al., 2009; van de Poll et al., 2013). The biomass of the single species of algae (Bioi) was estimated according to the Berger-Parker dominance index in cell density (DIi) by the formula:
$ {\mathrm{Bio}}_{\mathrm{i}} = {\mathrm{Bio}}_{{\mathrm{total}}} \times {\mathrm{DI}}_{\mathrm{i}} \times R_{{\mathrm{CC}}}, $
where Biototal is the total Chl a concentration, and we corrected DIi from cell density to Chl a concentration by the ratio (RCC) of Chl a concentration to algal cell (Tester et al., 2008; Lai et al., 2011). Other parameters in the model are shown in the Supporting Information (Table S1).
3 Results
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3.1 Changes in the phytoplankton community during the field cruise
The P. donghaiense blooms broke out at stations N1−N4, M1−M4, R1, S2, and S8, with a cell density of 106 cells/L, whereas the Karenia spp. blooms outbroke at the same stations except S8, with densities from 104 cells/L to 105 cells/L during the observation period from April to June 2019. These harmful algal blooms cause severe damage to the ecological environment of local coastal waters (Zhang et al., 2023; Lin et al., 2014, 2016). There is a synchronism rhythm of diatoms-P. donghaiense-Karenia spp.-diatom in which the phytoplankton regime shifts from diatoms to dinoflagellates of P. donghaiense-Karenia spp. loop (Fig. 3). The peak cell density of Karenia spp. reached 4.6 × 105 cells/L on June 4 after the peak cell density of P. donghaiense, which was 5.6 ×107 cells/L at Station R1 on May 19 (Fig. 3a). Karenia spp. can produce cytotoxins such as galactose and hemolysin, whose bloom outbreak (cell density > 104 cells/L) might cause ecological disasters and economic losses (Lv et al., 2019). The changes of Chl a at the four stations during field cruise observations are shown in Fig. S2. The concentration of Chl a ranged from 5.85 μg/L to 36.32 μg/L, and showed a trend of first increasing with peek value on May 18−19 and then decreasing.
3.2 Spatial and temporal distribution of nutrients
The significant changes in nutrients (DIN, DON, $\mathrm{PO}_{4}^{3-} $-P) during field cruise observations are summarized in Fig. S3. The concentration of DIN ranged from 2.5 μmol/L to 36.0 μmol/L and gradually decreased over time. At the same time, the concentration of DON ranged from 2.0 μmol/L to 155.0 μmol/L and exhibited a trend of initially increasing and then decreasing. The rise in DON concentration was attributed partially due to terrestrial input and partially due to the mortality of phytoplankton such as P. donghaiense. The concentration of DON reached its maximum on May 18 and 19, 2019, and its descending order was R1, S2, M1 and N3. The trend in concentration variation trend of $\mathrm{PO}_{4}^{3-} $-P was similar to that of DON. The decrease in $\mathrm{PO}_{4}^{3-} $-P concentration might indirectly reflect the absorption and utilization of $\mathrm{PO}_{4}^{3-} $-P by K. mikimotoi. The change in nutrient concentration was consistent with the loop in which the phytoplankton regime shifted from diatoms to dinoflagellates of P. donghaiense-Karenia spp. The high concentration of nutrients occurred in both western nearshore (R3, M2) and coastal areas (S8, DH9), which meant that terrigenous input and aquaculture sources coexist. Besides, the positive correlation between salinity and nutrients from the RDA (Fig. S4) results also indicated the existence of coastal aquaculture sources. These nutrient sources might support the occurrence of algal blooms in East China Sea coastal waters (Marques et al., 2024).
3.3 Changes in phytoplankton biomass and community in the field culture experiment
A total of 55 species of diatoms and 27 species of dinoflagellates were identified in the experimental period (Table S2). At the initial stage of the field experiment, there were four dominant dinoflagellates: P. donghaiense, Scrippsiella trochooidea, K. mikimotoi, and Gonyaulax polygramma, with dominance indices of 75%, 10%, 8%, and 3%, respectively (Fig. 4). Prorocentrum donghaiense was always dominant except in the MDON-supplemented culture group, and K. mikimotoi and S. trochooidea were dominant except diatoms in the MDON treatment group (Fig. 4a). Based on the concentration of Chl a, the phytoplankton biomass was significantly higher in the MDON and $\mathrm{NO}_{3}^{-} $-N addition culture groups than in the $\mathrm{PO}_{4}^{3-} $-P, $\mathrm{NH}_{4}^{+} $-N and TeDON treatment groups (p < 0.05) (Figs 4a−e). According to the Chl a content in algal cells of P. donghaiense and K. mikimotoi reported in the literature (Wang et al., 2006), the biomass in Chl a of P. donghaiense and K. mikimotoi was calculated (Figs 4a−e). Karenia mikimotoi increased in 0−4 d, and P. donghaiense decreased in the MDON group (Fig. 4a). Except for P. donghaiense and diatoms, S. trochooidea was replaced by K. mikimotoi in the $\mathrm{PO}_{4}^{3-} $-P group (Fig. 4c). Generally, TeDON and DIN ($\mathrm{NO}_{3}^{-} $-N and $\mathrm{NH}_{4}^{+} $-N) can promote the growth of P. donghaiense, and MDON and $\mathrm{PO}_{4}^{3-} $-P might make K. mikimotoi more competitive.
3.4 Changes in nutrients in the field culture experiment
With the uptake and utilization of nutrients, phytoplankton grew during the first 4 d (exponential growth phase) as the concentration of PN increased in the field culture experiments (Fig. 5). The concentrations of $\mathrm{NO}_{3}^{-} $-N and $\mathrm{NH}_{4}^{+} $-N decreased quickly during the first 2 d to 3 d in the MDON and TeDON adding groups, and the DON concentration then decreased until Day 7 during the later experimental phases (Figs 5a and b), which was associated with the growth of Guinardia delicatula, P. donghaiense, S. trochooidea, and K. mikimotoi (Figs 4a, b, f). The $\mathrm{NO}_{3}^{-} $-N and $\mathrm{NH}_{4}^{+} $-N concentrations decreased during the first 4 days of the $\mathrm{NO}_{3}^{-} $-N and $\mathrm{NH}_{4}^{+} $-N treatments (Figs 5d and e). With the exhaustion of nitrogen, P. donghaiense died rapidly (Figs 4d and e). $\mathrm{NO}_{3}^{-} $-N exhaustion, especially $\mathrm{PO}_{4}^{3-} $-P addition, promoted the absorption of DON (Figs 5c and d), which might be the reason for the growth of K. mikimotoi in the later experimental phases (Figs 4c and d). In addition, the quantities of phosphate and DOP gradually decreased with the growth of phytoplankton (Fig. S5).
3.5 Growth and nutrient uptake kinetics
Based on the NTPD model, the growth and death processes of P. donghaiense, K. mikimotoi, and diatoms were well fitted (R2 = 0.9995 ± 0.2705, p < 0.05), as shown in Fig. 6. The growth curve conforms to the logistic function, with maximum growth rates of 0.6 d−1 and 0.5 d−1 for P. donghaiense and K. mikimotoi, respectively. The growth of P. donghaiense under TeDON and DIN enrichment conditions had advantages. Karenia mikimotoi increased significantly in the enrichment of MDON and $\mathrm{PO}_{4}^{3-} $-P.
The changes in nitrogen in the forms of $\mathrm{NH}_{4}^{+} $-N, $\mathrm{NO}_{3}^{-} $-N, DON, PN and TN were also well simulated by the NTPD model (R2 = 0.9443 ± 0.0732, p < 0.05) (Fig. 7). The concentration of TN in cultivation experiments was conserved, with a variation of less than 12%.
Some kinetic parameters associated with phytoplankton growth and nutrient uptake processes are shown in Table 2, and the other parameters are listed in the Table S1. A higher growth rate (KG, 0.6 d−1) with a quicker uptake rate of DIN (Kup_${\mathrm{NH}}_4^+ $, 0.4 d−1; Kup_${\mathrm{NO}}_3^- $, 0.5 d−1) made P. donghaiense more competitive than K. mikimotoi and diatoms. However, a higher growth rate (KG, 0.5 d−1) with a quicker uptake rate of DON (Kup_DON, 0.3 d−1) made K. mikimotoi more competitive than P. donghaiense in ambient MDON addition or DIN exhaustion. The DIN half-saturation (Ks) value of K. mikimotoi was higher than that of other algae, which might induce K. mikimotoi to bloom synchronously or after P. donghaiense and diatom blooms. This is consistent with the synchronism rhythm of the diatom-P. donghaiense-Karenia spp.-diatom loop in the field cruise.
3.6 Three-dimensional fluorescence
Based on the fluorescence intensity, there were three types of humus components including terrigenous humus C, fulvic acid and unknown substance N in the TeDON- added group. There were four types of components consisting of three types of humus (terrestrial humus C, marine humus and fulvic acid) and one type of protein (tyrosine) in the other nutrient-addition groups (Fig. 8).
The cell density of K. mikimotoi and G. delicatula were consistent with the fluorescence intensity fluctuation of the fulvic acid component with the decrease in DON concentration in the MDON and $\mathrm{PO}_{4}^{3-} $-P treatment groups (Figs 8a and c), while there was little correlation (p > 0.5) between the cell density of G. delicatula and the fluorescence intensity of the fulvic acid component in the $\mathrm{NO}_{3}^{-} $-N treatment group. This might imply that the growth of K. mikimotoi might be promoted by DON with a fulvic acid component in the MDON and $\mathrm{PO}_{4}^{3-} $-P treatment groups. The cell density of P. donghaiense was consistent with the fluorescence intensity fluctuation of terrestrial humus C and marine humus components with the decrease in DON concentration in the TeDON and $\mathrm{NO}_{3}^{-} $-N treatment groups and consistent with the fluorescence intensity fluctuation of the tyrosine component with the decrease in DON concentration in the $\mathrm{NH}_{4}^{+} $-N treatment group (Figs 8b, d and e). The fluorescence results of both field culture experiments were consistent with the field observation (Fig. S7), which showed that K. mikimotoi was related to the fulvic acid component, and P. donghaiense was related to the terrestrial humus C, marine humus and tyrosine components.
To further verify the relationship between three-dimensional fluorescence components and phytoplankton growth and extinction, the Monte Carlo method was used in MATLAB to conduct correlation analysis. The correlation analysis results are shown in Fig. 9. The absolute value of the number is close to 1, indicating a stronger correlation. The results showed that the growth of K. mikimotoi was related to fulvic acid (0.767 5 ± 0.287 5) and P. donghaiense (0.752 ± 0.228). The correlations between P. donghaiense and terrigenous humus C and tyrosine were 0.593 3 ± 0.113 3 and 0.582 5 ± 0.292 5, respectively.
4 Discussion
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4.1 Nutrient mechanism on the blooms of P. donghaiense and Karenia spp.
Nutrient structure is one of the main factors affecting phytoplankton abundance and dominant species (Mathew et al., 2021). From the perspective of nutrient structure, dinoflagellates can directly absorb and utilize DON and DOP (Huang et al., 2005; Xiao et al., 2019; Wang et al., 2021). According to the field culture experiments, P. donghaiense absorbed DIN faster with a lower Ks of DON than K. mikimotoi (Table 2), which was more conducive to its growth process. Nutrients such as DON released by the P. donghaiense cells could serve as nutrients to maintain the Karenia bloom. Karenia mikimotoi can take up the DON produced from P. donghaiense and other algae to promote its own growth, according to the results of our MDON treatment experiment (Figs 4a and 6a). Field culture experimental data showed the absorption of DON and $\mathrm{NH}_{4}^{+} $-N by K. mikimotoi in the later period (Figs 4 and 5), which might be released from the algae (Buchan et al., 2014). Many studies have also shown that Karenia has a competitive advantage under low nutrient concentrations (Liu, 2012), and the N/P ratio (average 4.7) is low during Karenia blooms (Ding and Zhang, 2018). Therefore, the nitrogen forms utilized by Karenia might include DIN and algal-sourced DON. Studies have shown that the bloom of S. trochoidea is driven not only by nutrients but also by symbiosis with other algae (Yih et al., 2004; Yin et al., 2008). This is consistent with our results that the simultaneous presence of Karenia spp. and P. donghaiense blooms in the field cruise observation (Fig. 3).
In this study, a multiprocess coupled biogeochemical model (NTPD) was used to fit the data from the field culture experiment, and the key migration and transformation processes of the growth and death of Karenia and P. donghaiense were accurately revealed by combining the least squares method and Mann-Kendall method. The absorption rhythm of $\mathrm{NO}_{3}^{-} $-N, $\mathrm{NH}_{4}^{+} $-N and DON among Karenia, P. donghaiense and diatoms in biogeochemical processes is proposed. There was competitive adsorption of DON and $\mathrm{NH}_{4}^{+} $-N between diatoms and Karenia and competitive absorption of $\mathrm{NO}_{3}^{-} $-N between diatoms and P. donghaiense (Table 2 and Fig. 7).
The results of the NTPD model and field culture experiment showed that higher KG with quicker addition of DIN made P. donghaiense more competitive than K. mikimotoi and diatoms, and higher KG with quicker addition of Kup_DON made K. mikimotoi more competitive than P. donghaiense in ambient MDON addition or DIN exhaustion (Table 2). The absorption preference of DON and $\mathrm{NH}_{4}^{+} $-N in Karenia is exactly consistent with the study that $\mathrm{NH}_{4}^{+} $-N can inhibit the absorption and assimilation of $\mathrm{NO}_{3}^{-} $-N by phytoplankton (Wilkerson et al., 2006; Parker et al., 2012; Glibert et al., 2014). The diatom can take up a large amount of nutrients and thus grow rapidly (Wasmund et al., 2017), but no research has shown that diatoms can uptake the DON released by the death of other algae. Based on the field culture experiments and the NTPD model, the DIN uptake Ks of K. mikimotoi was higher than that of the other algae. This might induce the K. mikimotoi bloom to lag behind the P. donghaiense bloom. Diatoms are dominant competitors when DIN is abundant (Xiao et al., 2018a), while they did not become the main dominant algal species in the early stage of the field culture experiments. This might be because P. donghaiense was the dominant algae (75%) at the initiation point in the field cultural system, which infers that the initial algal species are also critical for the phytoplankton regime shift.
There is a synchronism rhythm of diatoms-P. donghaiense-Karenia spp.-diatom in which the phytoplankton regime shifts from diatoms to dinoflagellates of P. donghaiense-Karenia spp. loop in the East China Sea coastal waters based on field cruise observations (Fig. 10). This is consistent with the field culture experiments. In our field culture experiments, the growth of P. donghaiense in the condition of TeDON and DIN enrichment had advantages, while K. mikimotoi increased significantly in the enrichment of MDON and $\mathrm{PO}_{4}^{3-} $-P (Fig. 6). Thus, nutrients from sewage treatment plants and aquaculture tailwater input and transport from southwest to northeast with the Taiwan Strait Current (Liu et al., 2021) promote the dinoflagellate blooms and diatom-dinoflagellate regime shifts, with the synchronism rhythm that P. donghaiense dominants at the loop-phase-I for the ambient eutrophic DIN and TeDON, whereas Karenia spp. dominant at the loop-phase-II for the exhaust of DIN and MDON released from P. donghaiense in the coastal waters of the East China Sea (Fig. 10).
4.2 Triggering effect of dissolved organic matter components on dinoflagellate blooms
Fluorescence analysis of CDOM has been widely used in algal bloom studies. CDOM is a component of dissolved organic carbon (DOC), which mainly absorbs blue and ultraviolet radiation and affects coastal primary production (Nielsen and Ekelund, 1993; Carlsson et al., 1995; Massi et al., 2020). Diatoms, cyanobacteria and green algae can be classified accurately by three-dimensional fluorescence analysis (Lv et al., 2005; Yin et al., 2014; Zhao et al., 2018). Nitrogen-containing organic compounds in seawater in this study may have different degrees of bioavailability, so it is important to further characterize this DON component. The absorption and utilization of DON components by phytoplankton can be understood through the analysis of the process of absorption, degradation, release and transformation of DOM by phytoplankton. Therefore, CDOM is considered to be one of the main characteristics of phytoplankton (Massi et al., 2020). Then, other phytoplankton processes, such as excretion/death, perhaps play an important role in the production of CDOM. Despite this, the role of phytoplankton in CDOM generation and the relationship between different algae and humus and amino acids remain unclear.
Therefore, the three-dimensional fluorescence spectrum data of field observation stations and nutrient enrichment experiments were analyzed based on parallel factor analysis. The results showed that there were three or four kinds of CDOM in all samples (Fig. 8). The correlation between DOC and FI was inversely proportional (Fig. S6). Combined with the BIX index and fluorescence intensity, it was found that the CDOM content was conducive to indicating algal blooms (Park et al., 2022). The fluorescence intensity of fulvic acid changed obviously, which has a good correlation with the biomass of Karenia spp. in coastal water (Fig. S7). There was a quantitative relationship between the fluorescence components of terrestrial humus C and tyrosine and the growth of P. donghaiense (Fig. S7). The blooms of P. donghaiense and Karenia spp. were synchronized, so the changes in the intensity of CDOM also reflected the changes in the number of the two dinoflagellates. This is consistent with the results of field culture experiments. Thus, the fluorescence components of fulvic acid, terrestrial humus C and tyrosine might be used as biomarkers of Karenia spp. and P. donghaiense in the East China Sea.
5 Conclusions
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In this study, a multinitrogen-tri-phytoplankton-detritus model was built based on field cruise observations and field mesocosm flask culture experiments. According to the results of field culture experiments, there is a synchronism rhythm of the diatom-P. donghaiense-Karenia spp.-diatom loop in East China Sea coastal waters. This is consistent with the results of field cruise observations. This study infers that the P. donghaiense and Karenia spp. regime shift mechanism is associated with the nitrogen forms, where TeDON and DIN promote P. donghaiense, while MDON promotes Karenia spp. in the coastal waters of the East China Sea. The growth and nutrient uptake kinetics and the three-dimensional fluorescence characteristic of CDOM proved the triggering effect of DON on the shift of P. donghaiense to Karenia spp. TeDON with characteristics of terrestrial humus C and tyrosine components promoted the growth processes of P. donghaiense, while MDON from P. donghaiense with fulvic acid components promoted the growth processes of Karenia spp.
Acknowledgements
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We thank to Yulan Zeng from the Second Institute of Oceanography, Ministry of Natural Resources for providing the data of algae from the field investigation.
Funding
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  • The National Natural Science Foundation of China under contract No. 42130403; the Fundamental Research Funds for the Central Universities under contract No. 202362003; the National Key Research & Development Program of China under contract No. 2017YFC1404300.
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Year 2024 volume 43 Issue 6
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doi: 10.1007/s13131-023-2308-9
  • Receive Date：2023-08-31
  • Online Date：2025-11-19
  • Published：2024-06-25
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  • Received：2023-08-31
  • Accepted：2024-01-15
Funding
The National Natural Science Foundation of China under contract No. 42130403; the Fundamental Research Funds for the Central Universities under contract No. 202362003; the National Key Research & Development Program of China under contract No. 2017YFC1404300.
Affiliations
    1 Key Laboratory of Marine Chemistry Theory and Technology/Frontiers Science Center for Deep Ocean Multispheres and Earth System of Ministry of Education, Ocean University of China, Qingdao 266100, China
    2 College of Environmental Science and Engineering, Ocean University of China, Qingdao 266100, China
    3 College of Chemistry and Chemical Engineering, Ocean University of China, Qingdao 266100, China

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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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