Next Article in Journal
Developing an Artificial Intelligence-Based Method for Predicting the Trajectory of Surface Drifting Buoys Using a Hybrid Multi-Layer Neural Network Model
Previous Article in Journal
Maritime Autonomous Surface Ships
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
JMSE
Volume 12
Issue 6
10.3390/jmse12060959
jmse-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Physiological and Biochemical Responses of the Green Tide-Forming Algae, Ulva Species, under Different Nutrient Conditions on Jeju Island, Korea

by
Kyeonglim Moon
1,
Sun Kyeong Choi
2,
Seong Bin Ham
1,
Young Baek Son
2,
Yun Hee Kang
3 and
Sang Rul Park
1,3,*
1
Estuarine & Coastal Ecology Laboratory, Department of Marine Life Sciences, Jeju National University, Jeju 63243, Republic of Korea
2
METLAB (Marine Environmental Remote-Sensing & Modeling LABoratory), Tropical & Subtropical Research Center, Korea Institute of Ocean Science and Technology, Jeju 63349, Republic of Korea
3
Center for Climate Change Response, Jeju National University, Jeju 63243, Republic of Korea
*
Author to whom correspondence should be addressed.
J. Mar. Sci. Eng. 2024, 12(6), 959; https://doi.org/10.3390/jmse12060959
Submission received: 26 May 2024 / Revised: 29 May 2024 / Accepted: 5 June 2024 / Published: 7 June 2024
(This article belongs to the Section Marine Biology)
Browse Figures
Versions Notes

Abstract

:
In this study, we investigated the physiological and biochemical responses of Ulva species to variation in nutrient availability. Sampling was conducted at two sites on Jeju Island, Korea, namely, Handong, which is close to seven intensive land-based fish farms, and Hado, which has no apparent nearby nutrient sources. We examined the water column nutrient concentrations, nitrate reductase (NR) activity, nitrate uptake efficiency, tissue C, N, and P content, and stable isotope ratios of Ulva species. Water column NH4+, NO3− + NO2−, and PO43− concentrations were significantly higher at Handong than at Hado. NR activity and tissue N content of Ulva species were significantly higher at Handong than at Hado. Notably, nitrate uptake efficiency was inversely proportional to NR activity and tissue N content. The physiological and biochemical responses of Ulva species were closely related to dissolved inorganic nitrogen, which stimulates Ulva species to regulate growth. Additionally, the δ15N values of Ulva tissues at both sites were within the previously reported range for fresh groundwater. Therefore, the main nitrogen source for Ulva growth may be submerged groundwater with high nutrient concentrations. Our results provide invaluable information for estimating dissolved inorganic nitrogen levels in water, which may facilitate development of management policies.

1. Introduction

Coastal eutrophication, which is the presence of excessive nutrients in water, has become one of the most pressing environmental issues and is a major contributor to the degradation of coastal marine ecosystems worldwide. Eutrophication in coastal waters is commonly caused by excessive levels of nitrogen (N) alone or N and phosphorus (P) together. Limiting nutrients play a crucial role in shaping ecosystems by influencing primary production and species distribution. Nitrogen is considered the limiting factor for primary production in temperate coastal waters [1,2], whereas P is often the element that limits production in tropical environments [3]. In temperate coastal marine environments with enriched nutrients, P rather than N likely limits production [4]. Natural and anthropogenic sources of dissolved inorganic nitrogen (NH4+, NO3−, and NO2−) and phosphorus (PO43−) in coastal systems include rivers, fresh/saline groundwater, fertilizers, wastewater or sewage treatment disposal, and aquaculture effluents [5,6,7,8].
Coastal ecosystems are strongly affected by various anthropogenic activities, including infrastructure development, intensive agricultural expansion, coastal development, and industrial facilities as well as by climate change [9]. Among the anthropogenic sources, the release of nutrient-enriched aquaculture effluents has been identified as a major cause of coastal eutrophication [10]. Aquaculture industrialization has developed rapidly over the past three decades owing to the growth in global consumption of seafood and the decline in capture fisheries [11,12]. Land-based aquaculture facilities and those using marine cages or coastal ponds may negatively affect coastal ecosystems because of the discharge of high-nutrient effluents containing excess feed and fish feces [13,14].
Korea is a major producer of seafood and one of the world’s largest seafood consumers [15]. Land-based fish farming is one of the main economic activities on Jeju Island, Korea. Since 1986, the number of land-based fish farms on Jeju Island has increased rapidly, with approximately 390 land-based fish farms along the coast of Jeju Island as of 2020, encompassing more than 50% of all land-based fish farms in Korea [16]. Most land-based fish farms on Jeju Island use a mixture of groundwater with high nutrient content and coastal seawater as rearing water, which must be maintained at a constant temperature throughout the year [7]. Fish effluents from intensive aquaculture systems generally contain high ammonium (NH4+) concentrations, whereas groundwater on Jeju Island has high nitrate (NO3−) concentrations [17,18]. Thus, large amounts of effluent containing inorganic nitrogen (NH4+, NO3−, and nitrite (NO2−)) from land-based fish farms are discharged off the island’s coast [8,17,19].
Nitrogen is critical for controlling the growth and productivity of macroalgae in marine environments [20]. Macroalgae take up and accumulate inorganic nitrogen and phosphorus for growth [21]. They preferentially absorb NH4+, the assimilation of which requires less energy than NO3−, even though NO3− is a major nitrogen source in eutrophic environments [21]. However, high nitrate concentrations in water can increase macroalgal growth by promoting nitrate uptake, resulting in macroalgal blooms such as green tides [22]. The utilization of nitrate by macroalgae requires nitrate reductase (NR), which catalyzes the conversion of NO3− to NO2− and is a key enzyme in nitrogen assimilation [23,24]. The NR activity of macroalgae is triggered by NO3− uptake and is strongly linked to ambient NO3− concentrations [25]. Additionally, the NR activity of macroalgae is dependent on water column NH4+ concentrations, which can reduce or inhibit the uptake of NO3− and NO2− [26]. Thus, the NR activity of macroalgae may be an important physiological parameter reflecting their nutrient status.
The internal N pool of macroalgae is strongly related to nutrient availability. The authors of [27] demonstrated that enriched water nutrient availability is positively related to the N concentration in algal tissues. Algal tissue nutrient content is used as a bioindicator to detect the influence of sewage effluents [28]. The 15N signature shows distinct patterns between natural and anthropogenic sources [29]. Further, 15N is an effective indicator of available nitrogen sources in the water column [30,31]. When macroalgae are continuously exposed to high environmental N concentrations, their uptake may decrease due to high intracellular N levels. These results indicate that data on biochemical composition parameters will enable the effects of different levels of ambient nutrients to be examined.
In this study, we investigated the physiological and biochemical characteristics of Ulva ohnoi specimens collected from different study sites, one of which was affected by discharge from land-based aquafarms, whereas the other was characterized by natural environmental conditions. We hypothesized that specimens of Ulva ohnoi would exhibit different physiological and biochemical responses to different nutrients. To test this hypothesis, we assessed nitrate reductase activity, nitrate uptake efficiency, tissue nutrient (carbon (C), N, and P) content, and stable isotope ratios (δ13C and δ15N) of Ulva specimens at two sites. This study will provide comprehensive information on the physiological and biochemical responses of Ulva species to nutrient-rich effluents from land-based aquafarms.

2. Materials and Methods

2.1. Study Area

The study sites were located on intertidal rocky shores at two sites (Hado and Handong) on the northeastern coast of Jeju Island, Korea (Figure 1). The Handong site is adjacent to seven intensive land-based fish farms that use groundwater as the water source, which facilitates maintenance of a constant water temperature throughout the year [19]. The Hado site was not clearly observed to be a nutrient source; therefore, it was designated as a control site because of its lack of exposure to high nutrient concentrations. More than two Ulva species were observed at both sites, with U. ohnoi and U. australis being the dominant species. The tide is semi-diurnal with tidal ranges of approximately 2.7 m during spring (Tide Tables for the Coast of Korea, Korea Hydrographic and Oceanographic Administration; http://www.khoa.go.kr, accessed on 10 May 2024).

2.2. Environmental Parameters

Water temperature, salinity, and pH were measured seasonally (May, July, and October, 2016) using a YSI salinometer (YSI Model 85; YSI Inc., Yellow Springs, OH, USA). To determine water column nutrient (NH4+, NO3− + NO2−, and PO43−) concentrations, four replicate surface water samples were collected from each site. The water samples were placed on ice and frozen until further analysis. The NH4+, NO3− + NO2−, and PO43− concentrations were determined after running the samples through a column containing copper-coated cadmium, which reduced NO3− to NO2−. Water column nutrient concentrations were determined using standard colorimetric techniques in accordance with the methods of [32].

2.3. Sample Preparations and Nitrate Uptake Efficiency

Thalli of Ulva ohnoi were collected seasonally (May, July, and October, 2016) from Hado and Handong, on Jeju Island. The specimens were rinsed with filtered seawater and scrubbed to remove sediment and epiphytic materials. The thalli were maintained in aerated filtered seawater (0.78 μM NH4+, 0.36 μM NO3− + NO2− and 0.16 μM PO43−) at an ambient field temperature in preparation for incubation. The seawater was collected from the southern part of Jeju Island (the East China Sea) and filtered first through Whatman glass-fiber filters (1.2 μm) and then through Advantec MFS membrane filters (0.2 μm). Nitrate uptake efficiency of Ulva ohnoi exposed to different nutrient conditions (100 μM KNO3− vs. control) was investigated 0, 1, and 3 days after incubations. The specimens of 1.5 g fresh weight were placed into 250 mL flasks containing 150 mL of nutrient medium (100 μM KNO3−), with six replicates per treatment. The experiments were conducted in a chamber room where ambient temperature (18 °C in May, 25 °C in June, and 20 °C in October) and light intensity (100 μmol photon m−2 s−1) were controlled for 3 h. Control experiments were performed without the addition of algal material (n = 3). The culture medium was replaced daily. Nitrate concentrations in the medium were measured at 0, 10, 30, 60, 120, and 180 min using procedures modified from [33]. The uptake efficiency (%) was calculated according to an equation adapted from [34].
Nitrate uptake efficiency (%) = [(S0 − St)/S0] × 100
where S0 is the initial concentration of the nitrate medium and St is the final concentration after T h of incubation.

2.4. Nitrate Reductase Activity

Nitrate reductase (NR) activity of Ulva species was measured using the in vivo assay described by [35]. The NR-activity medium contained 60 mM of KNO3, 0.1 M KH2PO4 (phosphate buffer, pH 8.0), and 2.5% [v/v] n-propanol. The algal tissues samples (0.7 ± 0.1 g) were incubated in 20 mL of NR-activity medium and then N2 gas was flushed continuously for 2 min to remove oxygen. The samples were incubated for 1 h in a dark water bath (30 °C). The concentration of nitrite produced was measured spectrophotometrically (540 nm) after adding 1 mL of 2% sulfanilamide and 1 mL of 0.2% N-1-napthyl ethylene diamine (NED) to 1 mL of the NR-activity medium. NR activity was expressed as μmol NO2− g−1 dry weight h−1.

2.5. Elemental Composition and Isotope Analysis

Samples were collected in May, July, and October 2016 to determine the elemental contents (C, N, and P) and isotope ratios (carbon and nitrogen) of Ulva tissue (n = 3). Algal specimens were oven dried at 60 °C to a constant weight and were ground using a Tissue Lyser II (Qiagen, Hilden, Germany). Approximately 1.5–2.0 mg of the dried sample was packed into tin capsules and shipped to the Stable Isotope Facility, University of California, Davis, CA, USA. Elemental and isotopic analyses of algal tissues (May, July, and October, 2016 samples) were performed at the Stable Isotope Facility, University of California, Davis, CA, USA using a PDZ Europe ANCAGSL elemental analyzer interfaced with a PDZ Europe 20–20 isotope ratio mass spectrometer (IRMS, Sercon Ltd., Cheshire, UK). For more details, see “https://stableisotopefacility.ucdavis.edu/ (accessed on 10 Janunary 2024)”. Stable isotope values are reported as the ratio of heavier to lighter isotopes referenced against international standards (nitrogen = AIR; carbon = Vienna Pee Dee Belemnite) and defined by δX (‰) = [(Rsample/Rstandard) − 1] × 1000, where R is the ratio of the heavy to light isotopes. Tissue phosphorus content was analyzed using the molybdovanadophosphate method after nitric acid/perchloric acid digestion [36]. Approximately 10–15 mg of ground tissue was combusted at 550 °C for 5 h. The ash was dissolved in 1 mL of 2 N hydrochloric acid, and distilled water was added. Ammonium–vanadomolybdate reagent was added to the extracts, and absorbance was measured colorimetrically (410 nm). Nutrient content was calculated on a dry weight basis, and elemental ratios were calculated on a mole:mole basis.

2.6. Statistical Analyses

All values are shown as means ± standard deviation (SD). The data were tested for normality and homogeneity of variance to meet the assumptions of parametric statistics. If these assumptions were not satisfied, data were square root transformed or arcsine transformed. Significant differences in water column nutrient concentrations, nitrate reductase activity, elemental composition, and stable isotope data between the two study sites and among sampling times were tested using two-way ANOVAs. Additionally, significant differences in nutrient uptake efficiency among sites and periods were analyzed using two-way ANOVAs for each sampling time. When a significant difference was observed among variables, a Student–Newman–Keuls (SNK) post hoc test was performed. An alpha level of 0.05 was used for all statistical tests. All statistical analyses were performed using the SPSS ver. 20.0 (SPSS, IBM Corporation, Armonk, NY, USA).

3. Results

3.1. Environmental Parameters

Water temperatures at the two study sites varied with sampling time and were highest in July and lowest in May (Table 1). Water temperature was higher at Hado than at Handong. Salinity at Handong ranged from 29.8 to 33.4 PSU, while salinity at Hado was highest in May and lowest in October (Table 1). The pH values were lower at Handong than at Hado and ranged from 7.86 to 8.62 (Table 1).
Water column NH4+, NO3− + NO2−, and PO43− concentrations at Handong were significantly (p < 0.001) higher than at Hado during the experimental period (Figure 2; Table 2). Water column NH4+ concentrations at Handong ranged from 4.87 ± 0.27 in July to 9.11 ± 0.24 μM in October while water column NH4+ concentrations at Hado were usually less than 3 μM, ranging from 0.98 ± 0.04 to 2.51 ± 0.10 μM (Figure 2A). Average water column NO3− + NO2− concentrations at Handong and Hado were 27.8 and 8.9 μM, respectively (Figure 2B). Water column PO43− concentrations at Handong and Hado were relatively constant during the study period, with averages of 7.8 and 0.4 μM, respectively (Figure 2C).

3.2. Nitrate Reductase Activity and Nitrate Uptake Efficiency

Nitrate reductase (NR) activity of Ulva tissues at both sites varied significantly (p < 0.001) with sampling time (Figure 3; Table 2). Additionally, the seasonal pattern of NR activity in Hado was slightly different from that in Handong. NR activity at Hado was highest (6.26 ± 0.36 μmol NO2− g−1 DW h−1) in May, while that at Handong reached a maximum value (6.35 ± 0.65 μmol NO2− g−1 DW h−1) in July. The mean NR activity levels at Hado and Handong were 4.37 ± 1.80 and 7.66 ± 1.51 μmol NO2− g−1 DW h−1, respectively.
The nitrate uptake efficiency of Ulva depended on the site and sampling time (Figure 4; Table 2). The nitrate uptake efficiency of Ulva in the control group ranged from 84 to 100% at 0, 1, and 3 days after acclimation in May, July, and October (Figure 4). Ulva at Hado absorbed over 85% of nitrate in the water column within 180 min at 0, 1, and 3 days after acclimation in May and July. However, Ulva at Handong took up 5–16% of nitrate in the water column over 180 min 0, 1, and 3 days after acclimation in May and October. Interestingly, the nitrate uptake efficiency of Ulva at Handong increased as the acclimation period progressed in July. Notably, Ulva reduced water nitrate concentrations by 69.5% within 180 min, 3 days after acclimation (Figure 4F).

3.3. Elemental and Isotope Analysis

The tissue nutrient (C, N, and P) content of Ulva at Hado varied significantly (p < 0.001 in all cases) with sampling time (Figure 5A–C; Table 2). The mean tissue C, N, and P contents were 33.4, 2.6, and 0.09%, respectively. Tissue C content at Handong also fluctuated significantly (p < 0.001) among sampling times, being the highest in May and lowest in July, whereas tissue N and P contents were constant during the experimental period (Figure 5A–C; Table 2). The average tissue C, N, and P contents at Handong were significantly higher (p < 0.001 in all cases) than those at Hado. The atomic C:N, C:P, and N:P ratios at both sites varied significantly (p < 0.001 in all cases) with sampling time (Figure 5D–F; Table 2). At Hado, the C:N and C:P ratios were highest in July, whereas the N:P ratio was highest in October. The C:N ratio at Handong was the lowest in July, while the N:P ratio was the highest in July; however, the C:P ratio was constant (ca. 40.85) throughout the experimental period. The ratios at Hado were significantly (p < 0.001 in all cases) higher than those at Handong during the experimental period (Table 2).
The δ13C values of Ulva tissues at both sites varied significantly (p < 0.001 in all cases) with sampling time (Figure 6A; Table 2). The δ13C values at Hado ranged from −13.84‰ in May to −9.66‰ in October with a mean of −11.72‰, while the values at Handong ranged from −16.19‰ in October to −11.52‰ in May with a mean of −14.12‰. The δ15N values showed a similar pattern to that of δ13C values (Figure 6B). The δ15N values at Hado were highest (6.21 ± 0.12‰) in October and lowest (5.20 ± 0.03‰) in May, while the δ15N values at Handong ranged from 7.28‰ in May to 4.88‰ in October. The δ13C values at Hado were less negative (p < 0.001) than those at Handong, while the δ15N values at Handong were significantly (p < 0.001) higher than those at Hado (Table 2).

4. Discussion

In this study, we investigated the physiological and biochemical responses of U. ohnoi to high versus normal nutrient conditions. The physiological and biochemical characteristics of U. ohnoi were strongly affected by nutrient concentrations and nitrogen form in the water column. The NR activity at Handong was significantly higher than that at Hado throughout the experiment. The NR activity of macroalgae is positively correlated with average water column NO3− concentrations [37]. Effluents from fish farms usually contain high concentrations of NH4+, NO3−, and P due to the feed residue, feces, and urine of fish, as well as nitrification [38,39]. The Handong site, which is adjacent to seven intensive land-based fish farms that use groundwater with high NO3− concentrations, showed higher NH4+ and NO3− + NO2− concentrations in the water column. Thus, the high NR activity at Handong reflected high dissolved nitrogen concentrations in the water column.
In particular, NR activity at Handong was dependent on ambient NH4+ concentrations. Both NH4+ and NO3− are critical inorganic nitrogen sources that regulate NR activity in macroalgae [40,41]. The NR activity of U. prolifera, a related species, is inhibited by enriched NH4+ and PO43− concentrations [42]. Moreover, an enriched (elevated by 20 μM) NO3− condition inhibited NR activity of ephemeral macroalgae, even though NR activity was enhanced by NO3− concentrations in the water column [43]. Water column NO3− + NO2− concentrations at Handong exceeded 20 μM throughout the study period; however, there were no relationships between water column NO3− + NO2− concentrations and NR activity. This suggests that NO3− + NO2− concentrations in the water column did not significantly impact NR activity at Handong. In contrast, the NR activity of U. ohnoi was high in July, when ambient NH4+ concentrations were low; however, it decreased in October when ambient NH4+ concentrations reached 10 μM. This indicates that ambient NH4+ concentrations may have a decisive effect on NR activity under high NO3− concentrations.
Nitrate uptake efficiency also reflected ambient NO3− concentrations and NR activity at our study sites. Nutrient uptake by seaweed is strongly affected by nutrient demand. For example, nutrient uptake rates by a seaweed are generally limited but increase under elevated bulk concentrations when ambient nutrient concentrations are low but demand is high [44]. Conversely, their uptake becomes biologically limited under high-nutrient conditions that exceed requirements. The duration of fertilization has an impact on the uptake rate; the macroalgae (e.g., Ulva sp.) exposed to continuous fertilizing, in comparison to short-pulse fertilization events, showed a higher uptake rate [45]. If nitrate availability in the water column is sufficient to activate the NR activity of U. ohnoi, the nitrate uptake efficiency of U. ohnoi exposed to high-nitrate conditions is likely to be extremely low. In this study, U. ohnoi took up more than 85% of nitrate in the water column within 3 h on 0, 1, and 3 d of incubation when it was exposed to high-nitrate conditions at Hado. The nitrate uptake efficiency of U. ohnoi was within the range reported for U. mutabilis [46]. This indicates that the water column nitrate availability at Hado does not sufficiently activate or support NR activity or the growth rate of U. ohnoi. Consequently, U. ohnoi at Hado may show relatively low NR activity compared to that at Handong. However, U. ohnoi under high nitrate availability at Handong exhibited very low nitrate uptake efficiency in May and October, but not in July. Such low uptake efficiency represents the physiological response of Ulva exposed to high water column nitrate concentrations and may be the result of large cellular nitrate pools [46,47]. Thus, this result suggests that the growth or NR activity of U. ohnoi at Handong may not be limited by the water column nitrate concentration, which, therefore, may not be the controlling factor.
Interestingly, the nitrate uptake efficiency of U. ohnoi in July increased with the incubation time. Although U. ohnoi did not take up nitrate from seawater on day 0, its uptake efficiency gradually increased on days 1 and 3. This may be explained by high growth rates during the growing season. Seaweeds require more energy for their high growth during the growing season, resulting in a high uptake rate [21]. Along the coast of Jeju Island, annual biomass peaks at most locations were observed in early July (in preparation, SR Park), indicating the highest growth rates and high NR activity, which resulted in a high uptake rate. Thus, U. ohnoi at Handong may experience a limitation in nitrogen availability if the supply of nitrogen is temporarily unavailable during the growing season.
Distinct aspects of biochemical composition have been observed owing to differences in nutrient sources [48]. Under nutrient-enriched conditions, tissue nutrient content can be used as an indicator of the nutritional status of macroalgae [28]. The biochemical composition and atomic C:N or N:P ratios of macroalgal tissues reflect nutritional status and nutrient limitation [49,50]. Ulva species exhibit different biochemical compositions in their effluents owing to variability in the allocation of nitrogen [21]. Higher N and P concentrations in the water at Handong, which was close to intensive land-based farms, resulted in an increase in the tissue N and P contents of Ulva species (4.03 ± 0.07 and 0.22 ± 0.01%, respectively). Thus, the tissue N and P contents of Ulva species at Handong reflected water column nutrient concentrations [51]. Atomic N:P ratios > 24 or >30 are considered as evidence of phosphorus limitation for seaweed growth [52,53]. Additionally, low C:N ratios (<13) indicate that seaweeds did not experience N limitation. Our results show that the average atomic C:N and N:P ratios at Handong were 8.6 and 41.5, respectively, over the experimental period. Overall, PO43− availability in this area may play a role as a limiting factor for growth, even though the water column PO43− concentrations at Handong were higher than those in the ocean.
The isotope approach is a valuable tool for tracing nitrogen sources [54,55]. The δ15N values in macroalgal tissues can be used to differentiate between natural and anthropogenic nitrogen sources [56,57]. Cho et al. (2019) [7] revealed that the main source of green tides was fertilizer in fresh groundwater (4.0–8.0‰) by comparing the δ15N values in various nitrogen sources. Our results showed that the δ15N values of Ulva tissues at both sites ranged from 4.88 ± 0.52 to 7.28 ± 0.05‰, which was within the range of δ15N values reported for fresh groundwater. Thus, the main nitrogen source for Ulva growth may be submerged groundwater with high nutrient concentrations given that submerged groundwater is used to maintain a constant water temperature at land-based fish farms throughout the year.

5. Conclusions

The results of this study support our hypothesis that U. ohnoi exhibits different physiological and biochemical responses to different nutrient availability conditions. The NR activity and tissue N content of U. ohnoi in Handong were significantly higher than those in Hado, reflecting ambient NO3− concentrations. Although the NR activity of Ulva was affected by water column NO3− concentrations, the NR activity at Handong with high NO3− concentrations was dependent on ambient NH4+ concentrations. The mean atomic C:N and N:P ratios in Handong indicated that PO43− availability in this area may be a limiting factor for growth.
The understanding the physiological and biochemical responses of green-tide-forming algae is helpful for evaluating environmental nitrogen conditions in coastal and estuarine ecosystems. Ulva can be used as a bioindicator to assess environmental nitrogen conditions in coastal and estuarine ecosystems. Additionally, species of the genus Ulva are widely used in bioremediation studies and highly suitable for bioremediation [13]. Thus, Ulva species are promising candidate species as a biofilter or bioremediation in integrated multi-trophic aquaculture with a continuous source of nitrate and a constant nitrate concentration [58].

Author Contributions

Conceptualization, K.M. and S.R.P.; methodology, K.M. and S.R.P.; validation, K.M., S.K.C., S.B.H. and Y.B.S.; formal analysis, K.M. and Y.H.K.; investigation, K.M., S.K.C. and S.B.H.; data curation, K.M.; writing—original draft preparation, K.M. and S.R.P.; writing—review and editing, K.M. and S.R.P.; visualization, K.M. and S.R.P.; supervision, S.R.P.; funding acquisition, S.R.P. and Y.B.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the Korea Institute of Marine Science & Technology Promotion (KIMST) funded by the Ministry of Oceans and Fisheries (20220559) and by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2019R1I1A2A01040865) to S.R.P. This research was also supported by a ‘regional innovation mega project’ program through the Korea Innovation Foundation funded by the Ministry of Science and ICT (Project Number: 2023-DD-UP-0007) to Y.B.S.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are contained within the article.

Acknowledgments

We would like to thank Min Ji Kim and Eun Ran Baek for their countless hours of field and lab assistance.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Nixon, S.W.; Pilson, M.E. Nitrogen in estuarine and coastal marine ecosystems. Nitrogen Mar. Environ. 1983, 565, 648. [Google Scholar]
  2. Howarth, R.W. Nutrient limitation of net primary production in marine ecosystems. Annu. Rev. Ecol. Syst. 1988, 19, 89–110. [Google Scholar] [CrossRef]
  3. Lapointe, B.E.; Clark, M.W. Nutrient inputs from the watershed and coastal eutrophication in the Florida Keys. Estuaries 1992, 15, 465–476. [Google Scholar] [CrossRef]
  4. Smith, S.V. Phosphorus versus nitrogen limitation in the marine environment. Limnol. Oceanogr. 1984, 29, 1149–1160. [Google Scholar] [CrossRef]
  5. Valiela, I.; Collins, G.; Kremer, J.; Lajtha, K.; Geist, M.; Seely, B.; Brawley, J.; Sham, C.H. Nitrogen loading from coastal watersheds to receiving estuaries: New method and application. Ecol. Appl. 1998, 7, 358–380. [Google Scholar] [CrossRef]
  6. Howarth, R.W.; Sharpley, A.; Walker, D. Sources of nutrient pollution to coastal waters in the United States: Implications for achieving coastal water quality goals. Estuaries 2002, 25, 656–676. [Google Scholar] [CrossRef]
  7. Cho, H.-M.; Kim, G.; Shin, K.-H. Tracing nitrogen sources fueling coastal green tides off a volcanic island using radon and nitrogen isotopic tracers. Sci. Total Environ. 2019, 665, 913–919. [Google Scholar] [CrossRef] [PubMed]
  8. Choi, S.K.; Kim, T.H.; Kang, Y.H.; Kim, S.; Kim, T.-H.; Kim, J.K.; Lee, T.; Son, Y.B.; Lee, H.J.; Park, S.R. Changes in the Dynamics and Nutrient Budget of a Macroalgal Community Exposed to Land-Based Fish Farm Discharge Off Jeju Island, Korea. Sustainability 2021, 13, 11793. [Google Scholar] [CrossRef]
  9. Rabalais, N.N.; Turner, R.E.; Díaz, R.J.; Justić, D. Global change and eutrophication of coastal waters. ICES J. Mar. Sci. 2009, 66, 1528–1537. [Google Scholar] [CrossRef]
  10. Azanza, R.V.; Benico, G.A. Toxic Alexandrium blooms in fish farming sites in Bolinao, Pangasinan. J. Environ. Sci. Manag. 2013, 44–49. [Google Scholar]
  11. Troell, M.; Rönnbäck, P.; Halling, C.; Kautsky, N.; Buschmann, A. Ecological engineering in aquaculture: Use of seaweeds for removing nutrients from intensive mariculture. In Proceedings of the Sixteenth International Seaweed Symposium, Cebu City, Philippines, 12–18 April 1998. [Google Scholar]
  12. Read, P.; Fernandes, T. Management of environmental impacts of marine aquaculture in Europe. Aquaculture 2003, 226, 139–163. [Google Scholar] [CrossRef]
  13. Troell, M.; Halling, C.; Neori, A.; Chopin, T.; Buschmann, A.; Kautsky, N.; Yarish, C. Integrated mariculture: Asking the right questions. Aquaculture 2003, 226, 69–90. [Google Scholar] [CrossRef]
  14. Neori, A.; Krom, M.D.; van Rijn, J. Biogeochemical processes in intensive zero-effluent marine fish culture with recirculating aerobic and anaerobic biofilters. J. Exp. Mar. Biol. Ecol. 2007, 349, 235–247. [Google Scholar] [CrossRef]
  15. FAO. The State of World Fisheries and Aquaculture. 2022. Available online: https://reliefweb.int/report/world/state-world-fisheries-and-aquaculture-2022 (accessed on 16 October 2023).
  16. Korea, S. Korean Statistical Information System (KOSIS). Available online: http://kostat.go.kr (accessed on 16 October 2023).
  17. Neori, A.; Chopin, T.; Troell, M.; Buschmann, A.H.; Kraemer, G.P.; Halling, C.; Shpigel, M.; Yarish, C. Integrated aquaculture: Rationale, evolution and state of the art emphasizing seaweed biofiltration in modern mariculture. Aquaculture 2004, 231, 361–391. [Google Scholar] [CrossRef]
  18. Kim, J.; Song, B.-C.; Lee, M.-Y.; Kim, T.-H. Monthly variation in flux of inorganic nutrients from submarine groundwater discharge in a volcanic island: Significant nitrogen contamination in groundwater. Front. Mar. Sci. 2022, 9, 835207. [Google Scholar] [CrossRef]
  19. Oh, Y.H.; Kim, Y.; Park, S.R.; Lee, T.; Son, Y.B.; Park, S.-E.; Lee, W.C.; Im, D.-H.; Kim, T.-H. Spatiotemporal change in coastal waters caused by land-based fish farm wastewater-borne nutrients: Results from Jeju Island, Korea. Mar. Pollut. Bull. 2021, 170, 112632. [Google Scholar] [CrossRef] [PubMed]
  20. Teichberg, M.; Fox, S.E.; Olsen, Y.S.; Valiela, I.; Martinetto, P.; Iribarne, O.; Muto, E.Y.; Petti, M.A.V.; Corbisier, T.N.; Soto-jiménez, M.; et al. Eutrophication and macroalgal blooms in temperate and tropical coastal waters: Nutrient enrichment experiments with Ulva spp. Glob. Chang. Biol. 2010, 16, 2624–2637. [Google Scholar] [CrossRef]
  21. Hurd, C.L.; Harrison, P.J.; Bischof, K.; Lobban, C.S. Seaweed Ecology and Physiology; Cambridge University Press: Cambridge, UK, 2014. [Google Scholar]
  22. Smetacek, V.; Zingone, A. Green and golden seaweed tides on the rise. Nature 2013, 504, 84–88. [Google Scholar] [CrossRef] [PubMed]
  23. Berges, J.A.; Harrison, P.J. Nitrate reductase activity quantitatively predicts the rate of nitrate incorporation under steady state light limitation: A revised assay and characterization of the enzyme in three species of marine phytoplankton. Limnol. Oceanogr. 1995, 40, 82–93. [Google Scholar] [CrossRef]
  24. Chow, F. Applied Photosynthesis New Progress; InTechOpen: London, UK, 2012; pp. 105–120. [Google Scholar]
  25. Teichberg, M.; Heffner, L.; Fox, S.; Valiela, I. Nitrate reductase and glutamine synthetase activity, internal N pools, and growth of Ulva lactuca: Responses to long and short-term N supply. Mar. Biol. 2007, 151, 1249–1259. [Google Scholar] [CrossRef]
  26. Gordillo, F.J. Environment and algal nutrition. In Seaweed Biology: Novel Insights into Ecophysiology, Ecology and Utilization; Springer: Berlin/Heidelberg, Germany, 2012; pp. 67–86. [Google Scholar]
  27. Amato, D.W.; Bishop, J.M.; Glenn, C.R.; Dulai, H.; Smith, C.M. Impact of submarine groundwater discharge on marine water quality and reef biota of Maui. PLoS ONE 2016, 11, e0165825. [Google Scholar] [CrossRef] [PubMed]
  28. Kim, S.; Park, S.R.; Kang, Y.H.; Kim, G.-Y.; Lee, K.-S.; Lee, H.J.; Won, N.-I.; Kil, H.-J. Usefulness of tissue nitrogen content and macroalgal community structure as indicators of water eutrophication. J. Appl. Phycol. 2014, 26, 1149–1158. [Google Scholar] [CrossRef]
  29. Samanta, P.; Shin, S.; Jang, S.; Song, Y.-C.; Oh, S.; Kim, J.K. Stable carbon and nitrogen isotopic characterization and tracing nutrient sources of Ulva blooms around Jeju coastal areas. Environ. Pollut. 2019, 254, 113033. [Google Scholar] [CrossRef]
  30. Orlandi, L.; Bentivoglio, F.; Carlino, P.; Calizza, E.; Rossi, D.; Costantini, M.L.; Rossi, L. δ15N variation in Ulva lactuca as a proxy for anthropogenic nitrogen inputs in coastal areas of Gulf of Gaeta (Mediterranean Sea). Mar. Pollut. Bull. 2014, 84, 76–82. [Google Scholar] [CrossRef] [PubMed]
  31. Lemesle, S.; Erraud, A.; Mussio, I.; Rusig, A.-M.; Claquin, P. Dynamics of δ15N isotopic signatures of different intertidal macroalgal species: Assessment of bioindicators of N sources in coastal areas. Mar. Pollut. Bull. 2016, 110, 470–483. [Google Scholar] [CrossRef]
  32. Parsons, T.R. A Manual of Chemical & Biological Methods for Seawater Analysis; Elsevier: Amsterdam, The Netherlands, 2013. [Google Scholar]
  33. Jones, M.N. Nitrate reduction by shaking with cadmium: Alternative to cadmium columns. Water Res. 1984, 18, 643–646. [Google Scholar] [CrossRef]
  34. Kang, Y.H.; Kim, S.; Choi, S.K.; Lee, H.J.; Chung, I.K.; Park, S.R. A comparison of the bioremediation potential of five seaweed species in an integrated fish-seaweed aquaculture system: Implication for a multi-species seaweed culture. Rev. Aquac. 2021, 13, 353–364. [Google Scholar] [CrossRef]
  35. Corzo, A.; Niell, F. Determination of nitrate reductase activity in Ulva rigida C. Agardh by the in situ method. J. Exp. Mar. Biol. Ecol. 1991, 146, 181–191. [Google Scholar] [CrossRef]
  36. Chapman, H.D.; Pratt, P.F. Methods of analysis for soils, plants and waters. Soil Sci. 1962, 93, 68. [Google Scholar] [CrossRef]
  37. Young, E.B.; Dring, M.J.; Savidge, G.; Birkett, D.A.; Berges, J.A. Seasonal variations in nitrate reductase activity and internal N pools in intertidal brown algae are correlated with ambient nitrate concentrations. Plant Cell Environ. 2007, 30, 764–774. [Google Scholar] [CrossRef]
  38. Dalsgaard, T.; Krause-Jensen, D. Monitoring nutrient release from fish farms with macroalgal and phytoplankton bioassays. Aquaculture 2006, 256, 302–310. [Google Scholar] [CrossRef]
  39. Tsagkamilis, P.; Danielidis, D.; Dring, M.J.; Katsaros, C. Removal of phosphate by the green seaweed Ulva lactuca in a small-scale sewage treatment plant (Ios Island, Aegean Sea, Greece). J. Appl. Phycol. 2010, 22, 331–339. [Google Scholar] [CrossRef]
  40. Cohen, R.A.; Fong, P. Physiological responses of a bloom-forming green macroalga to short-term change in salinity, nutrients, and light help explain its ecological success. Estuaries 2004, 27, 209–216. [Google Scholar] [CrossRef]
  41. Cabello-Pasini, A.; Macías-Carranza, V.; Abdala, R.; Korbee, N.; Figueroa, F.L. Effect of nitrate concentration and UVR on photosynthesis, respiration, nitrate reductase activity, and phenolic compounds in Ulva rigida (Chlorophyta). J. Appl. Phycol. 2011, 23, 363–369. [Google Scholar] [CrossRef]
  42. Zhu, M.; Liu, Z.; Shao, H.; Jin, Y. Effects of nitrogen and phosphate enrichment on the activity of nitrate reductase of Ulva prolifera in coastal zone. Acta Physiol. Plant. 2016, 38, 169. [Google Scholar] [CrossRef]
  43. Lartigue, J.; Sherman, T.D. Response of Enteromorpha sp.(Chlorophyceae) to a nitrate pulse: Nitrate uptake, inorganic nitrogen storage and nitrate reductase activity. Mar. Ecol. Prog. Ser. 2005, 292, 147–157. [Google Scholar] [CrossRef]
  44. Sanford, L.P.; Crawford, S.M. Mass transfer versus kinetic control of uptake across solid-water boundaries. Limnol. Oceanogr. 2000, 45, 1180–1186. [Google Scholar] [CrossRef]
  45. Zollmann, M.; Liberzon, A.; Golberg, A. Modeling of growth of the macroalga Ulva sp. in a controlled photobioreactor based on nitrogen accumulation dynamics. Appl. Phycol. 2023, 4, 121–140. [Google Scholar] [CrossRef]
  46. Alsufyani, T.; Weiss, A.; Wichard, T. Time course exo-metabolomic profiling in the green marine macroalga Ulva (Chlorophyta) for identification of growth phase-dependent biomarkers. Mar. Drugs. 2017, 15, 14. [Google Scholar] [CrossRef]
  47. Naldi, M.; Viaroli, P. Nitrae uptake and storage in the seaweed Ulva rigida C. Agardh in relation to nitrate availability and thallus nitrate content in a eutrophic coastal lagoon (Sacca di Goro, Po River Delta, Italy). J. Exp. Mar. Bio. Ecol. 2002, 269, 65–83. [Google Scholar] [CrossRef]
  48. Streicher, M.D.; Reiss, H.; Reiss, K. Impact of aquaculture and agriculture nutrient sources on macroalgae in a bioassay study. Mar. Pollut. Bull. 2021, 173, 113025. [Google Scholar] [CrossRef] [PubMed]
  49. Hanisak, M.D. The use of Gracilaria tikvahiae (Gracilariales, Rhodophyta) as a model system to understand the nitrogen nutrition of cultured seaweeds. Hydrobiologia 1990, 204, 79–87. [Google Scholar] [CrossRef]
  50. Wheeler, P.A.; Björnsäter, B.R. Seasonal fluctuations in tissue nitrogen, phosphorus, and N:P for five macroalgal species common to the pacific northwest coast. J. Phycol. 1992, 28, 1–6. [Google Scholar] [CrossRef]
  51. Yu, Z.; Zhu, X.; Jiang, Y.; Luo, P.; Hu, C. Bioremediation and fodder potentials of two Sargassum spp. in coastal waters of Shenzhen, South China. Mar. Pollut. Bull. 2014, 85, 797–802. [Google Scholar] [CrossRef]
  52. Atkinson, M.; Smith, S. C: N: P ratios of benthic marine plants. Limnol. Oceanogr. 1983, 28, 568–574. [Google Scholar] [CrossRef]
  53. Björnsäter, B.R.; Wheeler, P.A. Effect of nitrogen and phosphorus supply on growth and tissue composition of Ulva fenestrata and Enteromorpha intestinalis (ulvales, chlorophyta). J. Phycol. 1990, 26, 603–611. [Google Scholar] [CrossRef]
  54. Lin, D.T.; Fong, P. Macroalgal bioindicators (growth, tissue N, δ15N) detect nutrient enrichment from shrimp farm effluent entering Opunohu Bay, Moorea, French Polynesia. Mar. Pollut. Bull. 2008, 56, 245–249. [Google Scholar] [CrossRef] [PubMed]
  55. Albertin, A.R.; Sickman, J.O.; Pinowska, A.; Stevenson, R.J. Identification of nitrogen sources and transformations within karst springs using isotope tracers of nitrogen. Biogeochemistry 2012, 108, 219–232. [Google Scholar] [CrossRef]
  56. Viana, I.G.; Bode, A. Variability in δ15N of intertidal brown algae along a salinity gradient: Differential impact of nitrogen sources. Sci. Total Environ. 2015, 512, 167–176. [Google Scholar] [CrossRef] [PubMed]
  57. Van Alstyne, K.L. Seasonal changes in nutrient limitation and nitrate sources in the green macroalga Ulva lactuca at sites with and without green tides in a northeastern Pacific embayment. Mar. Pollut. Bull. 2016, 103, 186–194. [Google Scholar] [CrossRef]
  58. Ghaderiardakni, F.; Califiano, G.; Mohr, J.F.; Abreu, M.H.; Coates, J.C.; Wichard, T. Analysis of algal growth-and morphogenesis-promoting factors in an integrated multi-trophic aquaculture system for farming Ulva spp. Aquaculture 2019, 11, 375–391. [Google Scholar] [CrossRef]
Jmse 12 00959 g001
Figure 1. A map showing the study area and sampling sites (Handong and Hado) on the northeastern coast of Jeju Island, Korea. Star indicates land-based fish farms.
Figure 1. A map showing the study area and sampling sites (Handong and Hado) on the northeastern coast of Jeju Island, Korea. Star indicates land-based fish farms.
Jmse 12 00959 g001
Jmse 12 00959 g002
Figure 2. Temporal variation in water column NH4+ (A), NO3− + NO2− (B), and PO43− (C) concentrations at Hado and Handong. Values provide the mean ± standard deviation (n = 4). Different letters indicate significant differences by post hoc analysis (SNK test, p < 0.05).
Figure 2. Temporal variation in water column NH4+ (A), NO3− + NO2− (B), and PO43− (C) concentrations at Hado and Handong. Values provide the mean ± standard deviation (n = 4). Different letters indicate significant differences by post hoc analysis (SNK test, p < 0.05).
Jmse 12 00959 g002
Jmse 12 00959 g003
Figure 3. Temporal variation in nitrate reductase activity of Ulva ohnoi at Hado and Handong. Values provide the mean ± standard deviation (n = 6). Different letters indicate significant differences by post hoc analysis (SNK test, p < 0.05).
Figure 3. Temporal variation in nitrate reductase activity of Ulva ohnoi at Hado and Handong. Values provide the mean ± standard deviation (n = 6). Different letters indicate significant differences by post hoc analysis (SNK test, p < 0.05).
Jmse 12 00959 g003
Jmse 12 00959 g004
Figure 4. Temporal variation (May—(A–C); July—(D–F); October—(G–I)) in nitrate (NO3−) uptake efficiency of Ulva ohnoi exposed to different nutrient conditions (100 μM KNO3− vs. control) and incubation time (initial, 1 and 3 days) at Hado and Handong. Values provide the mean ± standard deviation (n = 6).
Figure 4. Temporal variation (May—(A–C); July—(D–F); October—(G–I)) in nitrate (NO3−) uptake efficiency of Ulva ohnoi exposed to different nutrient conditions (100 μM KNO3− vs. control) and incubation time (initial, 1 and 3 days) at Hado and Handong. Values provide the mean ± standard deviation (n = 6).
Jmse 12 00959 g004
Jmse 12 00959 g005
Figure 5. Ulva ohnoi. Temporal variation in carbon (A), nitrogen (B), and phosphorus (C) and the C:N (D), C:P (E), and N:P (F) ratios of Ulva ohnoi tissue at Hado and Handong. Values provide the mean ± standard error (n = 3–6). Different letters indicate significant differences by post hoc analysis (SNK test, p < 0.05).
Figure 5. Ulva ohnoi. Temporal variation in carbon (A), nitrogen (B), and phosphorus (C) and the C:N (D), C:P (E), and N:P (F) ratios of Ulva ohnoi tissue at Hado and Handong. Values provide the mean ± standard error (n = 3–6). Different letters indicate significant differences by post hoc analysis (SNK test, p < 0.05).
Jmse 12 00959 g005
Jmse 12 00959 g006
Figure 6. Carbon (A) and nitrogen (B) stable isotope (δ13C and δ15N) values of Ulva ohnoi tissue at Hado and Handong. Values provide the mean ± standard error (n = 3–6). Different letters indicate significant differences by post hoc analysis (SNK test, p < 0.05).
Figure 6. Carbon (A) and nitrogen (B) stable isotope (δ13C and δ15N) values of Ulva ohnoi tissue at Hado and Handong. Values provide the mean ± standard error (n = 3–6). Different letters indicate significant differences by post hoc analysis (SNK test, p < 0.05).
Jmse 12 00959 g006
Table 1. Temporal variation in water temperature (°C), salinity (PSU), and pH values at Hado and Handong.
Table 1. Temporal variation in water temperature (°C), salinity (PSU), and pH values at Hado and Handong.
ParameterTimeSite
HadoHandong
Water temperature (°C)May18.517.0
July25.920.4
October18.617.9
Salinity (PSU)May34.533.4
July33.133.2
October31.229.8
pHMay8.287.82
July8.627.88
October8.357.86
Table 2. Summary ANOVA table for nutrient concentrations (NH4+, NO3− + NO2−, PO43−) and nitrate reductase activity, nitrate uptake efficiency (in May and July), elemental contents (C, N, and P), atomic ratio (C:N, C:P, and N:P ratio), and isotope ratios (C and N) of Ulva at Hado and Handong. Data were either square root transformed (nutrient concentration and nitrate reductase activity) or arcsine transformed (elemental composition, stable isotope ratio, and nutrient uptake efficiency) prior to analysis to meet the assumptions of parametric statistics. df, degrees of freedom; MS, mean of square.
Table 2. Summary ANOVA table for nutrient concentrations (NH4+, NO3− + NO2−, PO43−) and nitrate reductase activity, nitrate uptake efficiency (in May and July), elemental contents (C, N, and P), atomic ratio (C:N, C:P, and N:P ratio), and isotope ratios (C and N) of Ulva at Hado and Handong. Data were either square root transformed (nutrient concentration and nitrate reductase activity) or arcsine transformed (elemental composition, stable isotope ratio, and nutrient uptake efficiency) prior to analysis to meet the assumptions of parametric statistics. df, degrees of freedom; MS, mean of square.
ParameterSourcedfMSF-Ratiop-Value
NH4+Site1131.794815.524<0.001
Time23.44521.319<0.001
Site × Time215.61596.624<0.001
NO3− + NO2−Site12142.8821807.797<0.001
Time2119.197100.558<0.001
Site × Time284.15570.996<0.001
PO43−Site139.0665162.910<0.001
Time20.09111.980<0.001
Site × Time20.0192.493<0.001
Nitrate reductaseSite196.52087.212<0.001
activityTime218.98317.1530.002
Site × Time212.15110.979<0.001
Nitrate uptake efficiencySite16.534715.159<0.001
(May)Time20.0131.4500.257
Site × Time20.0040.4550.641
Nitrate uptake efficiencySite12.574278.060<0.001
(July)Time20.68574.002<0.001
Site × Time20.0748.0410.003
Tissue C contentSite147.70494.620<0.001
Time221.34542.336<0.001
Site × Time244.07187.414<0.001
Tissue N contentSite19.441542.336<0.001
Time20.18810.771<0.001
Site × Time20.34719.963<0.001
Tissue P contentSite10.090488.876<0.001
Time20.0029.433<0.001
Site × Time20.00020.833<0.001
C:N ratioSite1162.691727.260<0.001
Time24.73721.177<0.001
Site × Time217.23177.024<0.001
C:P ratioSite11,746,261.6001062.402<0.001
Time240,411.85124.586<0.001
Site × Time257,225.17134.815<0.001
N:P ratioSite13248.704210.584<0.001
Time2173.03511.2160.001
Site × Time297.8106.3400.008
δ13CSite131.06144.155<0.001
Time20.4430.6300.544
Site × Time242.40960.288<0.001
δ15NSite12.89126.950<0.001
Time21.26711.8160.001
Site × Time25.90755.072<0.001
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Moon, K.; Choi, S.K.; Ham, S.B.; Son, Y.B.; Kang, Y.H.; Park, S.R. Physiological and Biochemical Responses of the Green Tide-Forming Algae, Ulva Species, under Different Nutrient Conditions on Jeju Island, Korea. J. Mar. Sci. Eng. 2024, 12, 959. https://doi.org/10.3390/jmse12060959

AMA Style

Moon K, Choi SK, Ham SB, Son YB, Kang YH, Park SR. Physiological and Biochemical Responses of the Green Tide-Forming Algae, Ulva Species, under Different Nutrient Conditions on Jeju Island, Korea. Journal of Marine Science and Engineering. 2024; 12(6):959. https://doi.org/10.3390/jmse12060959

Chicago/Turabian Style

Moon, Kyeonglim, Sun Kyeong Choi, Seong Bin Ham, Young Baek Son, Yun Hee Kang, and Sang Rul Park. 2024. "Physiological and Biochemical Responses of the Green Tide-Forming Algae, Ulva Species, under Different Nutrient Conditions on Jeju Island, Korea" Journal of Marine Science and Engineering 12, no. 6: 959. https://doi.org/10.3390/jmse12060959

APA Style

Moon, K., Choi, S. K., Ham, S. B., Son, Y. B., Kang, Y. H., & Park, S. R. (2024). Physiological and Biochemical Responses of the Green Tide-Forming Algae, Ulva Species, under Different Nutrient Conditions on Jeju Island, Korea. Journal of Marine Science and Engineering, 12(6), 959. https://doi.org/10.3390/jmse12060959

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop