Abstract
The mariculture industry has grown rapidly worldwide over the past few decades. The industry helps meet growing food demands and may provide an effective means of carbon sequestration; however, it may harm the marine ecological environment, and the extent of its impact depends on the type of mariculture. Here we focus on the impact of mariculture on the nutrient status and eutrophication in Sansha Bay, which is a typical aquaculture harbor in southeastern China that employs a combination of shellfish and seaweed farming. Nutrient concentrations and dual nitrate isotopes were measured in Sansha Bay during the winter of 2021. The average concentrations of nitrate and phosphate were 31.3 ± 10.5 and 2.26 ± 0.84 µM, respectively, indicating that the water was in a eutrophic state. However, the N/P ratios were relatively low (14.3 ± 2.2). Nitrate isotope measurements were 8.8‰–11.9‰ for δ15N-NO3− and 2.2‰–6.0‰ for δ18O-NO3−. Source analysis based on the nitrate isotope measurements indicates that nitrate in Sansha Bay is derived mainly from the excretion of organisms and sewage discharge from mariculture. The isotopic fractionation model of nitrate assimilation by organisms indicates that surface waters in Sansha Bay experience strong biological uptake of nitrate, which is likely related to seaweed farming in winter. The low N/P ratios may be attributed to excessive nitrogen uptake (relative to phosphorus) during shellfish and seaweed farming, as well as nitrogen removal through sediment denitrification, which is fueled by the sinking of particulate organic matter from mariculture. Overall, our study shows that mariculture activities dominated by shellfish and seaweed cultivation in Sansha Bay may exacerbate eutrophication but reduce N/P ratios in the water column in aquaculture areas.
1 Introduction
Under the combined influence of global warming and human activities, the open ocean regions of the world’s oceans have become more nutrient-poor, whereas coastal areas have become more nutrient-rich (; ; Zhuang et al., 2021a). Coastal eutrophication is primarily caused by excessive loading of nitrogen (N) and phosphorus (P). Over the past few decades, the influx of N and P into coastal waters has increased dramatically (), leading to dramatic ecological and environmental consequences such as the expansion of harmful algal blooms () and hypoxia (). In general, nutrients in coastal waters are derived mainly from river input, organic matter regeneration, atmospheric deposition, submarine groundwater discharge, and seasonal transport of water masses (; ). Mariculture activities, dominated by the extractive culture of aquatic plants, filter-feeding bivalves, and fed-culture marine finfish and crustaceans, may also contribute to eutrophication in coastal zones (; ).
Owing to the growing global demand for seafood, the scale of mariculture has expanded rapidly in recent decades, and the Food and Agriculture Organization (FAO) predicts that this growth will continue (). Studies have shown that mariculture may have significant environmental impacts that are closely related to the type of mariculture employed (; ). Two generally accepted views are that fed culture (i.e., cages and ponds) releases N and P (; ; ), and photosynthetic seaweed may act as a nutrient sink (). The nitrogen discharged into the water as mariculture feed each year may reach levels as high as 2.1 × 106 tons, but most of the feed is not utilized by cultured organisms (), thus promoting eutrophication in coastal waters. In contrast, mariculture systems involving seaweed cultivation can absorb nutrients through photosynthesis, converting nutrient-rich waters into beneficial resources and somewhat offsetting the environmental impact of heterotrophic fish and shrimp farming (). Furthermore, seaweed cultivation is widely recognized, not only for providing food and biofuels, but also for removing CO2 from seawater, thus increasing the ocean’s carbon absorption capacity and providing new potential means for carbon neutrality (Zhang et al., 2017; ). These studies emphasize the need to better understand the impact of mariculture systems involving seaweed cultivation on the nutrient dynamics of coastal waters in our quest to adopt sustainable and environmentally friendly mariculture models.
Sansha Bay is a semi-enclosed bay located in the coastal area of the East China Sea. It is known for its seaweed-based mariculture systems and is referred to as the “hometown of Chinese nori” and the “hometown of Chinese kelp” (). The bay experiences minimal winter runoff, and its hydrography is primarily influenced by the China Coastal Current (CCC) in winter. The nutrient concentrations of the bay waters are more heavily affected by mariculture activities than other factors such as ocean currents owing to the narrow outlet connecting the bay to the open ocean (). Larimichthys crocea is the main species of fish cultured in the bay, and millions of tons of feed are required annually to maintain the fish culture (). However, approximately 5%–10% of the feed decomposes in the water (). observed that the Sansha Bay water mass had relatively low salinity compared with the East China Sea Shelf Water and the CCC but much higher nutrient concentrations than other water masses in this coastal area, and they suggested this disparity may be due to the influence of intensive mariculture activities. These factors make Sansha Bay an ideal location for studying the environmental impact of mixed mariculture systems involving seaweed cultivation. The biogeochemical processes of nutrients in Sansha Bay are complicated; however, systematic biogeochemical studies are lacking.
The abundance of 15N and 18O in nitrates (δ15N-NO3− and δ18O-NO3−) is useful for identifying the sources and biological transformations of N in coastal ecosystems (; ; ). In this study, nutrients and dual nitrate isotopes (δ15N-NO3−, δ18O-NO3−) were measured in the waters of Sansha Bay during the winter of 2021. In addition, a Bayesian stable isotope mixing model was used to calculate the relative contributions from several nitrate sources. Our overall aims were to (1) determine the eutrophication status of the bay’s winter seawater; (2) identify the ranges of dual nitrate isotope values and assess the main sources of nitrate in Sansha Bay; and (3) evaluate the impact of seaweed-based aquaculture on the nutrient dynamics of the bay waters.
2 Materials and methods
2.1 Study area
Sansha Bay (26°30′–26°58′E, 119°26′–120°10′N) is located on the northeast coast of Fujian Province, China (Figure 1). The surface current outside Sansha Bay is influenced by the CCC in winter and the South China Sea Warm Current (SCSWC) in summer. In late autumn and winter, seawater from the East China Sea or from farther north of China is transported along the coast under the influence of winter winds. In addition, observations based on radium isotopes (226Ra and 228Ra) have shown that groundwater input in Sansha Bay also affects the nutrient flux (). Seasonal activities such as seeding, growing, and harvesting on the densely clustered floating mariculture mats in the bay also have a substantial effect on the spatial–temporal distribution of its hydrochemical parameters (). In addition, driven by the Asian monsoon, the hydrographic characteristics of Sansha Bay were significantly influenced by the plume water of the Jiao River, which showed the highest freshwater discharge rate in warm months (from April to September) and the lowest in cold months (from October to April the following year). observed a water mass with relatively lower salinity than CCC meandering in Sansha Bay and influenced by intensive mariculture activities, nutrient concentrations in this Bay were much higher than other water masses in this coastal area.
Figure 1
2.2 Sampling strategy
A research cruise was carried out in Sansha Bay on 11–12 December, 2021 (Figure 1). Water samples were collected at 25 stations using a 5L Niskin bottle guided by a Conductivity–Temperature–Depth (CTD; Seabird® WQM 2019) recorder, which simultaneously measured sea surface temperature (SST) and salinity (SSS). Salinity in the water column samples was determined using a portable salinometer (Portasal 8410A, Guildline Co., Canada) and used to calibrate data from the CTD recorder. Water samples were obtained from two or three depth layers at each sampling site, depending on the overall water depth. “Surface waters” refer to waters 1 m below the surface, and “bottom waters” denote waters 1 m above the sediment bed.
2.3 Nutrient analysis
Nutrient samples were filtered using cellulose acetate membranes with a pore size of 0.45 μm that had been acid-cleaned. Two hundred and fifty mL of filtered seawater was frozen and stored at −20°C and used for routine spectrophotometric analysis of NO3−, NO2−, PO43−, and Si(OH)4 concentrations using the Technicon AA3 automatic analyzer (Bran-Lube, GmbH; ). Concentrations of NO3− + NO2− were determined using a Cu–Cd column reduction method, and NO2− contents were determined using spectrophotometry with standard pink azo dye (). Concentrations of PO43− and Si(OH)4 were measured using standard spectrophotometric methods (). The detection limits for NO3− + NO2−, PO43−, and Si(OH)4 were 0.1, 0.08, and 0.08 µM, respectively. The relative standard deviations (RSD) of repeat measurements of selected samples were<5%.
2.4 Analysis of nitrate isotopes
Isotope analyses of NO3− were carried out according to the method of and (Equations 1 and 2) using an isotope-ratio mass spectrometer (IRMS). The international nitrate reference materials NITS USGS34 (δ15N = −1.8‰; δ18O = −27.9‰) and NITS USGS35 (δ15N = 2.7‰; δ18O = 57.5‰) were used to correct for drift, oxygen isotopic exchange, and blanks. The average standard deviation was typically 0.2‰ for δ15N and 0.5‰ for δ18O, which is applicable to samples with NO3− concentrations ≥ 1 μM. Isotope ratios are reported in delta (δ) notation in units of per mil (‰):
where denotes N2 in air and denotes Vienna Standard Mean Ocean Water (VSMOW).
2.5 Potential eutrophication
Phytoplankton absorbs nutrients from seawater according to the Redfield ratio (), leaving relative excess of nitrogen or phosphorus. Excess nitrogen or phosphorus do not have direct contribution to eutrophication but could be considered as a potential factor, known as potential eutrophication (). In order to highlight the limiting characteristics of nutrient salts, dissolved inorganic nitrogen (DIN, including NO3-, NO2- and NH4+) and active phosphate (PO43-), which play a bottleneck role in phytoplankton growth (Zhuang et al., 2021b), were selected as evaluation parameters. The potential eutrophication evaluation model (Table 1, ; ; ) was adopted for the evaluation of the nutrient condition in the study area.
Table 1
| Grade | Nutrient level | DIN (μmol L−1) | DIP (μmol L−1) | DIN/DIP |
|---|---|---|---|---|
| I | Oligotrophic level | <14.28 | <0.97 | 8-30 |
| II | Moderate-level nutrient | 14.28-21.41 | 0.97-1.45 | 8-30 |
| III | Eutrophication | >21.41 | >1.45 | 8-30 |
| IVp | Phosphate-limiting moderate-level nutrient | 14.28-21.41 | / | >30 |
| Vp | Phosphate moderate limiting potential eutrophication | >21.41 | / | 30-60 |
| VIp | Phosphate-limiting potential eutrophication | >21.41 | / | >60 |
| IVN | Nitrogen-limiting moderate-level nutrient | / | 0.97-1.45 | <8 |
| VN | Nitrogen moderate limiting potential eutrophication | / | >1.45 | 4-8 |
| VIN | Nitrogen-limiting potential eutrophication | / | >1.45 | <4 |
The evaluation standards for potential eutrophication.
2.6 Calculation of N*
To evaluate the nitrate deficit, we used the parameter N* proposed by , where N* = ([NO3−] − 16*[PO43−] + 2.9) × 0.87. In the equation, 16 is the Redfield ratio of 16:1, and 0.87 is a calculated factor based on the specific stoichiometric ratios in denitrification and remineralization processes. The constant (2.9) was introduced to set the mean N* to zero and is based on global measurements (). The N* index reflects the net effect of N2 fixation and denitrification, and negative N* values imply a nitrate deficit in the ocean ().
2.7 Stable isotope analysis in R mixing model
SIAR (stable isotope analysis in R) is a software package that uses a Bayesian stable isotope mixing model, which is used to calculate the relative proportion of various nitrate sources. In the mixing model, the Bayesian framework is utilized to calculate the probability distribution amongst the different nitrate sources. The model framework is as follows:
where denotes the isotope values (j = 2, δ15N-NO3−, and δ18O-NO3−) of the sample i (i = 1, 2, 3, … N); is the isotope value j of the source k (k = 1, 2, 3, … K) and is normally distributed with an average and standard deviation ; Pk is the proportion of source k, as calculated using the SIAR model; is the fractionation factor for j on source k and is normally distributed with an average and standard deviation ; ϵjk is the residual error of the additional unquantified variations between individual samples and is normally distributed with an average 0 and standard deviation σj. The model uses CSV Microsoft Excel of δ15N-NO3− and δ18O-NO3−, , and as inputs. It then outputs numerical and graphical depictions of the relative contributions of the potential sources (Zhang et al., 2018) (Equation 3). More detailed information of the Bayesian stable isotope mixing model has been provided by ; , and Zhang et al. (2018).
3 Results
The water depth in Sansha Bay ranges from 8 to 50 meters (Figure 2A). During winter, water temperatures at the survey stations in Sansha Bay range from 17.8 to 18.6°C, with an average of 18.4 ± 0.1°C, and salinity ranges from 20.25 to 21.99, with an average of 21.45 ± 0.45 (Figures 2B, C; Supplementary Figure 1). There were only very small horizontal and vertical variations in temperature and salinity within the bay (Supplementary Figure 2), indicating a relatively homogeneous hydrographical property. The small amount of winter runoff from rivers into Sansha Bay (Supplementary Figure 3), the influence of riverine inputs on the physicochemical properties of the water is minimal, as reflected by the distribution patterns of temperature and salinity.
Figure 2
During the investigation, nitrate concentrations at the Sansha Bay survey stations ranged from 8.4 to 44.9 µM, with an average concentration of 31.3 ± 10.5 µM, phosphate concentrations ranged from 0.46 to 3.61 µM, with an average concentration of 2.26 ± 0.84 µM, and silicate concentrations ranged from 9.8 to 52.9 µM, with an average concentration of 32.8 ± 11.3 µM (Figures 2D–F; Supplementary Figure 1). The lowest nutrient concentrations in the surface and bottom waters were recorded at the mouth of Sansha Bay.
The NO3−/PO43− ratios in the water at the survey stations ranged from 9.3 to 20.0, with an average value of 14.3 ± 2.2, which is lower than the Redfield ratio (16:1). The highest NO3−/PO43− ratios in surface and bottom layers were observed at the mouth of Sansha Bay, corresponding to the lowest nutrient concentrations (Figure 2G; Supplementary Figure 1). The NO3−/PO43− ratios in the bay were lower than those at the bay mouth, suggesting that biogeochemical processes modify the nutrient structure in the bay. During the investigation, the NO3−/DSi ratios in the water ranged from 0.6 to 1.1, with an average value of 0.96 ± 0.11, which is close to the Redfield ratio (1:1).
In winter, the δ15N-NO3− values in Sansha Bay were 8.8‰–11.9‰, with an average value of 9.8‰ ± 0.6‰. δ18O-NO3− values were 2.2‰–6.0‰, with an average value of 4.0‰ ± 0.8‰ (Figures 2H–I). There is a positive correlation between δ15N-NO3− and δ18O-NO3− in surface waters (using the equation δ18O-NO3− = 0.70 × δ15N-NO3− − 2.9), indicating either a relatively uniform source of surface nitrate or that similar biogeochemical processes were active (Figure 3A). However, there is no significant correlation between δ15N-NO3− and δ18O-NO3− values in bottom waters (Figure 3B). As observed in the nutrient distribution pattern, δ15N-NO3− and δ18O-NO3− values were higher in the mariculture area within the bay and lower at the bay mouth.
Figure 3
4 Discussion
4.1 Nutrient status of Sansha Bay in winter
The winter waters in Sansha Bay, like most coastal harbors affected by the CCC in southeastern China, appear to be characterized by eutrophication (e.g., ; ). Approximately 81% of the data points (50/62) in this study exceeded the thresholds for eutrophication in harbor waters proposed by Guo et al. (; NO3− >21.4 µM, PO43−>1.45 µM), indicating that most of the winter water in Sansha Bay was eutrophic (Figure 4). The small amount of winter run off from rivers into Sansha Bay and another area of low surface nutrient concentrations was found at the mouth of the Sai River, suggesting that winter river input does not greatly influence nutrient levels in the bay. The lowest nutrient concentrations in the surface and bottom waters were recorded at the mouth of Sansha Bay., indicating that offshore water input may not be the main source of nutrients into the bay. Areas of high nutrient concentrations were observed mainly in mariculture areas, indicating that mariculture activities contribute to nutrient levels in the bay. The influence of the winter CCC extends from 26°N to 35°N along the southeastern coast (). As shown in Figure 5, the NO3−/PO43− ratios in CCC-influenced harbors along the southeastern coast of China generally decrease from north to south. Owing to the input of nutrients from the Yangtze River, NO3−/PO43− ratios can exceed 80 in the winter waters of the Yangtze River estuary (). The CCC carries signals from the land sources of the Yangtze River and a large volume of nutrients to the southeastern coastal harbors during winter, which is one of the main reasons for the high N/P ratios in these harbors (). The NO3−/PO43− ratios in Hangzhou Bay, Xiangshan Bay, and Sanmen Bay are relatively similar (; ) and lower than those of the Yangtze River estuary, but they further decrease to 14.3 ± 2.2 in Sansha Bay (Figure 5; Supplementary Table 1).
Figure 4
Figure 5
The winter waters of Sansha Bay have lower NO3−/PO43− and NO3−/DSi ratios than many other nearshore harbors influenced by the CCC (Supplementary Table 1). Correlation analysis showed significant positive relationships between concentrations of NO3− and both PO43− and DSi (Figure 4). The relationship between NO3− and PO43− concentrations was examined by linear regression and indicates that NO3− concentrations increased with increasing PO43−; however, the slope was only 11.5, lower than the Redfield ratio (Figure 4A). Similarly, NO3− concentrations increased with increasing DSi, with a slope of 0.9 (Figure 4A). These results indicate that the winter waters of Sansha Bay are eutrophic but have relatively low N/P ratios.
The distribution of the N* index reflects the excess (positive values) or deficiency (negative values) of nitrate relative to phosphate (). The N* values decrease gradually along the southeastern coast, with values approaching 0 in Sansha Bay, indicating that strong denitrification processes occur as the excess nitrate flows southward and enters coastal harbors. This may be related to intense nitrogen removal via sedimentary denitrification (). Indeed, observations show that denitrification at the mouth of the Yangtze River is the main pathway for the removal of excess nitrogen, with nitrogen removal rates reaching up to 28.49 ng N g−1·h−1 ().
4.2 Sources and biochemical transformation of nitrate in Sansha Bay waters
Based on the dual isotope method for nitrate source identification (; ), the δ15N-NO3− (8.8‰–11.9‰) and δ18O-NO3− (2.2‰–6.0‰) values in Sansha Bay waters (Figure 6) suggest that the main sources of nitrate are manure and sewage, as evidenced by the more positive δ15N-NO3− values. The δ15N-NO3− values are lower at the mouths of the main rivers entering the bay (Figure 2) when the river input is low (Supplementary Figure 3), suggesting that the more positive anthropogenic signal may be introduced by mariculture activities within the bay. Previous studies have suggested that the main sources of nutrients in Sansha Bay during winter are the eutrophic coastal currents and mariculture inputs (); however, the extent of the latter depends heavily on the type of mariculture. found that seaweed aquaculture in Xiangshan Bay absorbed nutrients and alleviated eutrophication. The type of mariculture may also affect the distribution of dual nitrate isotopes. In Xiangshan Bay, where seaweed aquaculture is dominant, δ15N-NO3− and δ18O-NO3− values range from 5.7‰ to 8.8‰ and from 1.8‰ to 6.8‰, respectively (). In Laizhou Bay, where sea cucumber aquaculture is dominant, δ15N-NO3− and δ18O-NO3− values range from 2.0‰ to 11.8‰ and from −7.8‰ to 12.6‰, respectively ().
Figure 6
The application of Bayesian mixing models reveals that the surface water in Sansha Bay has a mixture of sources (Supplementary Figure 4), which poses a challenge for nitrate source analysis. According to previous studies, the main nitrate sources in water are likely manure and sewage, reduced nitrogen fertilizer, nitrate derived from soil nitrogen, and atmospheric deposition (; ). The relative contributions of these four potential nitrate sources have been calculated in many studies across a broad range of study areas (e.g., ; ; Zhang et al., 2018; ). Therefore, we calculated the potential sources of nitrate using δ15N-NO3− and δ18O-NO3− values in a Bayesian isotope mixing model (). The uncertainty associated with these calculations is difficult to constrain with the present data because (a) the range of isotopic values from potential nitrate sources is relatively large (Supplementary Table 2), and (b) the end-members of the potential nitrate sources originate from the reference literature and not from the measurement of samples in Sansha Bay. Nevertheless, such an estimate can provide an insight into nitrate sources in Sansha Bay. The end-member values for the potential nitrate sources are presented in Supplementary Table 2, and the results are shown in Figure 6. The results suggest that manure and sewage were the predominant sources of nitrate in the surface waters of Sansha Bay (51%–75%, average 63%), followed by soil organic nitrogen (3%–45%, average 26%) and reduced nitrogen fertilizer (0%–24%, average 11%).
4.3 Impact of mariculture on nutrient loading and N/P ratios
Mariculture activities are commonplace in the harbors along the southeastern coast of China and include kelp farming in Xiangshan Bay (), mixed crab and seaweed farming in Sanmen Bay (), and mixed shellfish and seaweed farming in Sansha Bay (). Most mariculture activities increase nutrient loading in water owing to the excretion of farmed organisms and the addition of feed (). In this study, the higher nutrient concentrations in Sansha Bay compared with the bay mouth suggest nutrient loading from mariculture. However, the low NO3−/PO43− ratios in Sansha Bay compared with the bay mouth indicate the possibility of denitrification in the bay, which may be caused by the structural modification of nutrients, potentially owing to seaweed farming. suggested that seaweed farming may increase N/P ratios, whereas bivalve farming may decrease N/P ratios. Overall, the N/P ratio of nutrients removed by mariculture is close to 18. In Sansha Bay, where mixed shellfish and seaweed farming occurs, excess nitrate (relative to phosphate) may be absorbed during mariculture activities under conditions of sufficient nitrogen, and excess nitrogen may be removed from the water during the harvest season ().
Previous studies have shown that when algae have high rates of nitrate assimilation, the δ15N of the remaining nitrate will increase significantly owing to the preferential utilization of 14N by the organism (; ). Average δ15N-NO3− values in Sansha Bay during winter were as high as 9.8‰ ± 0.6‰, higher than the spring ratios measured in the Yangtze River Estuary (6.9‰, ) and the Pearl River Estuary (2.2‰–4.4‰, ). These values are also higher than those measured in the upper bay area of Xiangshan Bay, where kelp farming is predominant (8.1‰ ± 0.5‰), and the lower bay area, which is significantly influenced by dilution via input from the Yangtze River (6.2‰ ± 0.3‰) (). These results indicate that Sansha Bay experiences strong biological absorption and transformation of nitrate.
The intense biological production and deposition of organic debris in the surface layer during seaweed cultivation provides abundant organic matter to the sediment (Zhuang et al., 2022). The re-mineralization of this organic matter may enhance sedimentary denitrification (), thus removing more nitrogen (while phosphates remain unaffected) and reducing N/P ratios. Denitrification enriches the residual nitrate, with δ15N and δ18O having a ratio close to 2:1 (; ). The higher δ15N-NO3− and δ18O-NO3− values in the bottom waters of the mariculture area in Sansha Bay compared with the surface waters support the idea that denitrification processes are occurring in the sediment (Figure 3). These findings suggest that in areas where shellfish and seaweed are cultivated, the strong absorption of nitrate by organisms and enhanced sedimentary denitrification stimulated by the downward settling of organic matter result in the reduction of N/P ratios in the water.
5 Conclusion
The average concentrations of nitrate and phosphate in Sansha Bay during winter 2021 were 31.3 ± 10.5 and 2.26 ± 0.84 µM, respectively, indicating eutrophic conditions. However, N/P ratios were relatively low, with an average of only 14.3 ± 2.2. Nitrate isotope ratios in Sansha Bay were 8.8‰–11.9‰ for δ15N-NO3− and 2.2‰–6.0‰ for δ18O-NO3−. Based on the nitrate isotopes, it is suggested that the main sources of nitrate in Sansha Bay are likely sewage discharge and biological excretion associated with mariculture activities. Therefore, mariculture has contributed to the eutrophication of the water. However, the isotopic fractionation model of nitrate assimilation by organisms indicates that strong biological uptake of nitrate is occurring in the surface waters of Sansha Bay, possibly owing to extensive algal cultivation during winter. The low N/P ratios of Sansha Bay may be attributed to excessive nitrogen uptake by shellfish and algae cultivation, as well as the introduction of organic matter from algal cultivation, which enhances denitrification and nitrogen removal in sediments. Therefore, aquaculture activities in Sansha Bay may exacerbate eutrophication while also altering nutrient compositions and reducing N/P ratios.
Statements
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Author contributions
DB: Writing – original draft. QZ: Writing – review & editing, Data curation, Methodology. JL: Writing – review & editing, Methodology. JH: Writing – review & editing, Data curation, Methodology. YZ: Writing – review & editing. WY: Writing – review & editing, Investigation. DQ: Writing – review & editing.
Funding
This study was funded by National Key Research and Development Program of China (2023YFC3108102), Fujian Provincial Science and Technology Plan & Natural Science Foundation of Fujian Province (2023J06036), and the Fujian Provincial Department of Education - Sea Economy government, industry, University and research alliance (FOCAL2023-0101) the Ocean Negative Carbon Emissions (ONCE) Program.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmars.2024.1351657/full#supplementary-material
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Summary
Keywords
marine aquaculture, nutrients, N/P ratio, nitrate isotopes, denitrification
Citation
Bu D, Zhu Q, Li J, Huang J, Zhuang Y, Yang W and Qi D (2024) Mariculture may intensify eutrophication but lower N/P ratios: a case study based on nutrients and dual nitrate isotope measurements in Sansha Bay, southeastern China. Front. Mar. Sci. 11:1351657. doi: 10.3389/fmars.2024.1351657
Received
12 December 2023
Accepted
08 January 2024
Published
25 January 2024
Volume
11 - 2024
Edited by
Ruijie Zhang, Guangxi University, China
Reviewed by
Guo Wei, East China University of Technology, China
Jiapeng Wu, Guangzhou University, China
Updates
Copyright
© 2024 Bu, Zhu, Li, Huang, Zhuang, Yang and Qi.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Yanpei Zhuang, zhuangyp@jmu.edu.cn; Di Qi, qidi@jmu.edu.cn
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