Phytoplankton community structure in the Qinzhou Bay, China: a baseline information for non-indigenous species before the operation of the “Pinglu Canal Waterway”

Phytoplankton community structure in the Qinzhou Bay, China: a baseline information for non-indigenous species before the operation of the “Pinglu Canal Waterway” | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Phytoplankton community structure in the Qinzhou Bay, China: a baseline information for non-indigenous species before the operation of the “Pinglu Canal Waterway” Karsoon Tan, Leiheng Huang, Jinman Huang, Cong Luo, Baoling Xie, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5823043/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The “Pinglu Canal Waterway” represents a mega-project in human history, currently under construction in Qinzhou Bay and scheduled to be fully operational by the end of 2026. Since shipping activities are a major pathway for introducing non-indigenous invasive species, baseline data on phytoplankton occurrence and distribution before the operation of the “Pinglu Canal Waterway” is necessary to better study the ecological impact of this mega anthropogenic activity. In this study, the phytoplankton community structure at the entrance of the “Pinglu Canal Waterway” (the Maowei Sea) and nearby control areas (Da Feng Jiang) was explored using metabarcoding techniques. A total of 205 phytoplankton species were identified, representing 110 families and 150 genera. Among them, 13 are harmful algal bloom species (HABs) or potential HABs, and 5 are potential non-indigenous invasive phytoplankton species. The results of this study not only enrich the baseline information on phytoplankton in Qinzhou Bay, but also strengthen our foundation for studying the potential environmental impact of the “Pinglu Canal Waterway” anthropogenic mega-project in the future. Metabarcoding analysis Environmental DNA Qinzhou Bay Phytoplankton community Invasive species Figures Figure 1 1. Introduction Shipping is a major pathway for introducing non-indigenous species, with about half of the known introduced species world-wide introduced through shipping activities (Gollasch et al., 2015). Among these, the introduction of non-indigenous phytoplankton species primarily occurs through ballast water, where ballast water along with native phytoplankton species from the loading port are released at discharging port worldwide (Marangoni et al., 2001; Wang et al., 2022; Kraus, 2023). Non-indigenous phytoplankton species can pose significant threats to native phytoplankton species by replacing their ecological niches or introducing new diseases or toxins (Gollasch et al., 2015; Kraus, 2023). Despite the existence of numerous legal frameworks, policies, agreements, and codes of practice regarding the invasion risk due to ballast water release, there is still a considerable probability of introducing non-indigenous species, especially in Chinese ports (Chen et al., 2023). In July 2022, the Chinese government approved a 10 billion USD mega project called the “Pinglu Canal Waterway” extending 134.2 km from Guangxi (southern China) to Guizhou and Yunnan (Xijiang River). It is expected to fully operate by the end of 2026. The entire route of the “Pinglu Canal Waterway” is constructed according to Class I inland waterway standards and is navigable for vessels of up to 5000-tons (Guo and Yan, 2023). The “Pinglu Canal Waterway” represents the largest river-sea canal in China in centuries, following the Beijing-Hangzhou Grand Canal, which was constructed more than 1000 years ago. He et al. (2023) and Tan et al. (2024) explored the distribution of harmful algae bloom species (HABs) in the Beibu Gulf using metabarcoding analysis. However, He et al. (2023) only covered a single offshore station with water depth of 20 m, and Tan et al. (2024) reported only on HABs. Recently, Xu et al. (2024) reported the occurrence and distribution of phytoplankton in the Beibu Gulf, China, based on traditional microscopic morphology-based observation methods. While this provides important information on phytoplankton community structure, microscopic observation methods face challenges in identifying cryptic, deformable, and small phytoplankton species (Massana et al., 2011). Additionally, the accuracy of these methods is highly dependent on the researchers’ experience and expertise. In this context, this study was carried out to explore the occurrence and distribution of phytoplankton in Qingzhou Bay using the DNA metabarcoding approach. In this study, a list of encountered phytoplankton was summarized to serve as baseline data before the operation of the “Pinglu Canal Waterway” for future investigations. The results of this study not only enrich phytoplankton diversity information in the Qinzhou Bay, but also provide valuable baseline data to study the actual environmental impact of this anthropogenic mega-project. 2. Materials and Methods 2.1 Study areas Qinzhou Bay is located in the northern part of Beibu Gulf (Figure 1), characterized by a tropical climate, and is set to become the most important China-ASEAN free trade area from the sea in Southwest China. On one hand, the Maowei Sea (135 km 2 ) in Qinzhou Bay represents the largest natural oyster breeding ground in South China, contributing over two-third of the total natural seed supply (mainly Crassostrea hongkongensis ) for oyster aquaculture (China Fishery Statistical Yearbook, 2023). The mouth of the Maowei Sea will be the entrance of the “Pinglu Canal Waterway” which is expected to be fully operational by the end of 2026 (Guo and Yan, 2023). On the other hand, the Da Feng Jiang is located about 30 km away from the Maowei Sea. It is known as a preferred habitat by white dolphins Sousa chinensis , and has become a tourist hot spot for dolphin watching (Chen et al., 2016). 2.2 Sample collection Samplings were performed from July 2023 to December 2023, covering a total of 12 sampling stations, six in Da Feng Jiang (stations A to F) representing the control stations, and six in Maowei Sea (stations G to L) where the entrance of the “Pinglu Canal Waterway” is located (Figure 1). At each sampling station, a multiparameter sensor (YSI; Loveland, Co, the USA) was used to record in situ environmental parameters, including water temperature (ºC), salinity (psu), pH, dissolved oxygen (DO) (mg/L), and chlorophyll-a (ug/L), while water depth (m) was measured using a depth sounder. At the same time, triplicate 1 L seawater samples were collected from a depth of 0.5 m below the water surface using a water sampler. These samples were subsequently filtered through a 0.45 μm GF/C membrane (Whatman) and preserved at -80 ºC until genomic DNA extraction. 2.3 Genomic DNA extraction, PCR amplification, and DNA sequencing Isolation of genomic DNA was performed using filtered membrane following the protocol described by Kang et al. (2018) using the DNeasy® Plant Mini Kit (QIAGEN, Hilden, Germany). In short, the membrane was homogenized with 500 μL of lysis buffer using ceramic spheres and a FastPrep-2 (MP Biomedicals), after which the aliquots were screened with a spectrophotometer and stored at -80 ºC. For PCR amplification, a total reaction volume of 50 μL included 25 μL of 2X Taq PCR Master Mix (Tiangen Biotech, Beijing, China), 50 ng of template DNA, 1 μL each of forward (5′-CCAGCA(G/C)C(C/T)GCGGTAATTCC-3′) and reverse (5′-ACTTTCGTTCTTGAT(C/T)(A/G)A-3′) primers targeting the 18S rDNA V4 region, and diethyl pyrocarbonate water to make up the remaining volume. The PCR conditions included an initial denaturation step at 95 °C for 3 min, followed by 20 cycles of denaturation for 30 s at 95 °C, annealing for 40 s at 50 °C , and extension for 10 min at 72 °C. This was concluded with a final extension step at 72 °C for 10 min. PCR products were evaluated by electrophoresis on 1% agarose gels and subsequently purified using the E.Z.N.A.® Gel Extraction Kit (Omega Bio-Tek, Inc., USA). To prepare sequencing libraries, the NEBNext® Ultra™ II DNA Library Prep Kit for Illumina® (New England Biolabs, Inc., USA) was employed following the manufacturer's instructions. The PCR products were then sequenced using Hiseq with 250-bp paired-end reads for next-generation sequencing. 2.4 Bioinformatic analysis The Fastp software (v0.12.4) was utilized to conduct quality control and filter low-quality reads from sequencing data (Chen et al., 2018). Following this, the filtered reads underwent concatenation using USARCH software (v11.0.667) (Edgar, 2010), during which concatenated sequences and primer sequences shorter than 150 bp were excluded. Then, the sequences were merged, and those with an abundance of less than 4 were discarded. The concatenated sequences were then clustered into Operational Taxonomic Units (OTUs) using a 98% similarity threshold. The resulting OTU sequences were aligned against the NCBI-18S rRNA database using BLAST (v2.2.31) (Sato et al., 2018), filtering out sequences with alignment lengths less than 90%. Species information was assigned based on a 98% similarity criterion (McClenaghan et al., 2020). 2.5 Statistical analysis and OTU diversity estimation The relative abundance of phytoplankton was assessed for statistical significance using the SPSS Windows Statistical Package (version 26). Significance was determined at P<0.05. Prior to analysis, normality and homogeneity of variance tests were conducted on all variables using Kolmogorov–Smirnov and Levene's tests. One-way ANOVA was employed, followed by Tukey's multiple comparison tests (Tukey HSD) for specific contrasts in spatial variations. To characterize community diversity, Shannon and Simpson indices (Simpson, 1949) were calculated. Community richness was evaluated using the Chao and Ace indices (Chao et al., 2005; Chao and Chiu, 2012). The formulas are as follows: 2.6 Literature search for potential non-indigenous invasive phytoplankton species Since phytoplankton that negatively impact human health or the environment are well-documented in the literatures, articles reporting on harmful algae blooms (HABs) were gathered from the Google Scholar and Web of Science (up to July, 2024). To ensure comprehensive coverage, additional related articles cited within the reference lists of each article were also retrieved. These steps were repeated until no additional articles were identified. Consequently, a total of 4511 articles were gathered from the literature search. To identify HABs or potential HABs species in Qingzhou Bay, China, all phytoplankton species collected in this study were cross-referenced with the list above (unpublished data). The occurence and ditribution history of each identified HABs or potential HABs were further explored to determine wherether these species are native or non-indigenous. 3. Results 3.1 Environmental parameters The spatial variation of environmental parameters in Qinzhou Bay is summarized in Table 1 . In general, the temperature, salinity pH, DO, Chl-a and water depth during the sampling period ranged from 26.50 ± 3.78 to 28.74 ± 3.80 ºC, 7.20 ± 5.92 to 28.50 ± 3.85 psu, 7.81 ± 0.46 to 8.72 ± 0.51, 6.62 ± 0.44 to 8.16 ± 0.41 mg/L, 0.98 ± 0.11 to 3.13 ± 0.35 ug/L, and 3.00 ± 0.10 to 20.00 ± 3.15 m, respectively. No statistically significant difference (P > 0.05) in water temperature and pH were observed among the sampling stations. The water salinity at stations D, E, and F (27.93 to 28.50 psu) was significantly higher (P < 0.05), whereas at stations J, K, and L (7.20 to 7.78 psu) was significantly lower (P < 0.05) than at other stations (9.05 to 23.23 psu). The DO at Da Feng Jiang (stations A to F) (7.44 to 8.16 mg/L) was significantly higher (P < 0.05) than that at Maowei Sea (station G to L) (6.62 to 6.76 mg/L). The Chl-a concentration at station A, D, E, and F (2.83 to 3.13 ug/L) was significantly higher (P < 0.05) than at other stations (0.98 to 1.99 ug/L). The water depth at stations D, E, and F (10 to 20 m) was significantly higher (P < 0.05), whereas in stations A, B, C, J, K, and L (3.0 to 4.8 m) was significantly lower (P < 0.05) than at other stations. Table 1 Environmental parameters in sampling areas Station Temperature (ºC) Salinity (psu) pH DO (mg/L) Chl-a (ug/L) Depth (m) A 27.26 ± 3.89 a 14.64 ± 7.88 bc 7.95 ± 0.45 a 7.91 ± 0.61 a 3.13 ± 0.35 a 3.50 ± 0.12 d B 26.77 ± 3.87 a 18.49 ± 8.12 b 8.05 ± 0.43 a 7.85 ± 0.59 a 1.99 ± 0.22 b 3.00 ± 0.10 d C 27.98 ± 3.84 a 23.23 ± 6.12 b 8.51 ± 0.50 a 7.44 ± 0.63 b 1.04 ± 0.24 c 4.50 ± 0.23 d D 26.50 ± 3.78 a 28.50 ± 3.85 a 8.49 ± 0.49 a 7.80 ± 0.42 a 2.83 ± 0.31 a 10.00 ± 0.58 b E 28.46 ± 3.79 a 27.93 ± 2.31 a 8.52 ± 0.50 a 8.14 ± 0.44 a 2.99 ± 0.33 a 20.00 ± 2.38 a F 28.74 ± 3.80 a 28.44 ± 2.12 a 8.72 ± 0.51 a 8.16 ± 0.41 a 2.93 ± 0.29 a 20.00 ± 3.15 a G 27.66 ± 3.77 a 19.34 ± 2.32 b 7.85 ± 0.45 a 6.75 ± 0.47 c 1.73 ± 0.21 bc 9.30 ± 0.52 bc H 27.81 ± 3.78 a 13.86 ± 3.92 bc 7.83 ± 0.45 a 6.62 ± 0.44 c 1.03 ± 0.14 c 8.45 ± 0.32 c I 27.50 ± 3.78 a 9.05 ± 4.23 c 7.86 ± 0.47 a 6.72 ± 0.46 c 0.98 ± 0.11 c 8.75 ± 0.41 bc J 27.44 ± 3.85 a 7.20 ± 5.92 d 7.82 ± 0.47 a 6.76 ± 0.59 c 1.11 ± 0.18 c 4.67 ± 0.13 d K 27.98 ± 3.87 a 7.43 ± 5.95 d 7.81 ± 0.46 a 6.66 ± 0.60 c 0.98 ± 0.13 c 4.80 ± 0.15 d L 27.35 ± 3.88 a 7.78 ± 6.21 d 7.84 ± 0.45 a 6.69 ± 0.62 c 1.21 ± 0.20 c 4.20 ± 0.11 d Different letters indicating significant differences 3.2 Phytoplankton community structure Approximately 6.1 million raw 18S rRNA reads were generated from Illumina sequencing, averaging around 505,000 sequences per sample. Following bioinformatic processing, 49.5% of these sequences were retained. A total of 9811 Operational Taxonomic Units (OTUs) were annotated as phytoplankton taxa, corresponding to 974 phytoplankton species based on 98% similarity. After excluding “uncultured” phytoplankton, 205 phytoplanton species were identified, representing 110 families and 150 genera. The dominant phytoplankton species in Da Feng Jiang during the sampling period were Teleaulax amphioxeia (21.16 ± 26.04%) > Thalassiosira eccentrica (11.08 ± 7.50%) > Cerataulina pelagica (9.11 ± 6.24%) > Guinardia striata (7.58 ± 5.46%). In Maowei Sea, the dominant phytoplankton species were Skeletonema costatum (22.83 ± 17.09%) > Storeatula major (7.46 ± 5.47%) > Gyrodinium jinhaense (6.34 ± 5.18%) > Teleaulax amphioxeia (5.09 ± 4.77%) (Table S1 ). The Chao1 (1070.58 ± 77.54 versus 695.62 ± 39.07) and ACE indices (1059.15 ± 77.64 versus 687.78 ± 34.49) in Da Feng Jiang were significantly higher (P 0.05). 3.3 Potential invasive phytoplankton A total of 13 HABs or potential HABs were identified in the present study. The average relative abundacne of HABs in Maowei Sea (24.60 ± 18.72%) was significantly higher than that in Da Feng Jiang (6.48 ± 2.28%) (Table 2 ). Specifically, the relative abundance of HABs was highest (P < 0.05) in the mouth of Maowei Sea (stations G and H), followed by inner bay of Maowei Sea (stations J, K and L), and lowest (P < 0.05) upstream of Da Feng Jiang (stations A, B and C). Based on the natural occurrence and distribution of each HAB or potential HAB species, five were identified as potential non-indigenous species, including Heterosigma akashiwo , Karenia mikimotoi , Karlodinium veneficum , Pseudo-nitzschia americana and Pseudo-nitzschia pungens . Table 2 HABs and potential invasive phytoplankton species in Qinzhou Bay, China Species Stations in Da Feng Jiang Stations in Mao Wei Sea A B C D E F G H I J K L Akashiwo sanguinea 0.06 0.06 0.10 0.02 0.01 0.02 0.26 0.28 0.02 0.04 0.04 0.16 Chattonella sp. > 0.01 > 0.01 > 0.01 > 0.01 > 0.01 > 0.01 0.06 0.02 0.01 0.01 0.01 0.02 Dinophyceae sp. > 0.01 > 0.01 0.01 0.42 0.10 0.09 0.02 > 0.01 > 0.01 > 0.01 0.01 > 0.01 Gymnodinium impudicum > 0.01 > 0.01 > 0.01 > 0.01 > 0.01 > 0.01 0.19 0.17 0.03 0.03 0.03 0.04 Heterocapsa pygmaea > 0.01 > 0.01 > 0.01 > 0.01 > 0.01 > 0.01 0.03 0.01 0.01 0.01 0.02 0.03 Heterocapsa rotundata 4.05 4.05 2.25 2.67 1.51 2.07 1.63 4.03 0.33 0.40 0.23 0.86 Heterosigma akashiwo 0.39 0.39 0.52 0.08 0.16 0.18 0.01 0.01 0.02 > 0.01 0.02 0.01 Karenia mikimotoi > 0.01 > 0.01 > 0.01 > 0.01 > 0.01 > 0.01 0.02 > 0.01 0.01 > 0.01 > 0.01 > 0.01 Karenia selliformis > 0.01 > 0.01 > 0.01 > 0.01 > 0.01 > 0.01 0.02 0.02 0.02 0.01 > 0.01 0.01 Karlodinium veneficum 0.28 0.28 0.21 0.03 0.07 0.14 > 0.01 0.23 > 0.01 > 0.01 > 0.01 > 0.01 Pseudo-nitzschia americana 0.09 0.09 0.81 6.23 4.88 4.52 0.62 0.04 0.01 0.05 0.01 0.07 Pseudo-nitzschia pungens 0.01 0.01 0.01 0.33 0.26 0.21 0.01 0.02 0.10 0.03 0.12 0.05 Skeletonema costatum 0.03 0.03 0.14 0.39 0.33 0.28 43.02 45.78 5.41 14.85 15.06 12.88 Average relative abundance of potential HABs (%) 4.92 4.92 4.06 10.17 7.31 7.51 45.89 50.62 5.98 15.42 15.54 14.13 Species names in bold are potential invasive phytoplankton species. 4. Discussion In recent years, the rapid advancement of molecular techniques has enabled the detection of phytoplankton communities across all size ranges, including picoplankton and nanoplankton. The 18S rRNA gene of the small ribosomal subunit is a highly effective and sensitive marker for identifying marine eukaryotic microorganisms. Consequently, metabarcoding has become an accurate and effective method for revealing phytoplankton species composition. Metabarcoding techniques have been extensively used to study the occurrence and distribution of phytoplankton (e.g., He et al., 2023; Tan et al., 2024; Xu et al., 2024). In general, the results of our metabarcoding analysis revealed that there are at least 13 HABs species in Qingzhou Bay. The significantly higher relative abundance of HABs in Maowei Sea compared to Da Feng Jiang is most likely attributed to the high stocking density of oyster aquaculture in the Maowei Sea, the largest natural oyster breeding ground in South China (China Fishery Statistical Yearbook, 2023). Numerous studies have demonstrated that commercial scale bivalve aquaculture caused bottom-uo alteration of phytoplankton community structure by releasing nutrients, especially phosphate and amminia, but not silicate, into the surrounding water (Richard et al., 2006; Jansen et al., 2011; Liang et al., 2019). In fact, the significant lower phytoplankton community richness (indicated by lower Chao1 and ACE indices) in Maowei Sea compared to Da Feng Jiang was evident in the present study. Therefore, it is reasonable to speculate that nutrients released during during bivalve life cycles enhance the growth of dinoflagellates and other HABs (Tan et al., 2024). Within Maowei Sea, the relative abundance of HABs at the mouth of Maowei Sea was remarkably higher than that in the inner bay. This observation could be attributed to the lower salinity in the inner bay of Maowei Sea, where salinity conditions are less favorable for many HAB species (Tan et al., 2023). Among HABs, five potential non-indigenous species have been identified. It is worth noting that the non-indigenous phytoplankton species identified in this study are mainly those HABs or potential HABs that have been reported to cause negative impact to human health or environment. Therefore, we do not rule out the possibility that there are more non-indigenous species in Qingzhou Bay, as some non-indigenous phytoplankton may not yet have caused significant negative impact that attract scholarly attention. Gymnodinium impudicum is a non-toxic, naked dinoflagellate known for causing high cell density harmful blooms. It has been commonly reported in Korea (Lee et al., 2001), the Arabian Gulf (Glibert et al., 2002), and various regions of the Mediterranean Sea, including the coastal waters of Spain, Italy, Tunisia, and Egypt (Fraga et al., 1995; Yahia-Kéfi et al., 2005; Mikhail et al., 2020). In China, G. impudicum has been observed in the coastal waters of the Bohai Sea (Ocean Administration of Tianjin, 2017) and the Yellow Sea (Yu and Liu, 2016; Wang et al., 2022b), indicating its presence in the region. However, specific documentation confirming it as "native" to southern China is limited, but the possibility of the introduction of this species to southern China through the intensive cargo/shipping port activities cannot not be ruled out. Heterosigma akashiwo is a small temperate raphidophytes (10-25 μm) that inhabits temperate zones, extending as far north as the Bering Sea and Artic waters, but has not been documented in the Antartic (Engesmo et al., 2016). H. akashiwo was first described in Massachusetts as Olisthodiscus carterae in 1965 (Hulburt, 1965), and then described as Entomosigma akashiwo in Japan in 1967 (Hada, 1967). Since then, H. akashiwo has been reported to cause blooms worldwide, including Chile (e.g. Torres et al., 2022), South Africa (e.g. Bornman et al., 2022), United State of America (e.g. Cochlan et al., 2014) etc. Blooms of H. akashiwo have been associated with mass mortality of farmed fish and significant economic loss, especially in British Columbia (loss of USD 4-5 million per bloom) and Washington (loss of USD 2-6 million per bloom) (Cochlan et al., 2014). This temperate species is most likely a non-indigenous HABs in Qinzhou Bay. Karenia mikimotoi is an ichthyotoxic dinoflagellate , initially described as Gymnodinium mikimotoi in 1935 when it first reported bloom in Gokasho Bay, Japan (Oda, 1935). Since then, blooms of K. mikimotoi have been documented in the temperate coastal waters of the Atlantic, Indian and Pacific Oceans (see review Li et al., 2019). In China, blooms of K. mikimotoi have mainly been documented in the Pearl River estuary and the East China Sea, where shipping activities are intense (Chen et al., 2021). It is most likely that this temperate HAB species is a non-indigenous species in southern China. Blooms of K arlodinium veneficum were first documented in South Africa (Braarud, 1957), followed by reports in Europe (Bjornland and Tangen, 1979), North America (Li et al., 2000), and Australia (Ajani et al., 2001). Recently, scientific studies have reported the presence of K arlodinium veneficum in Chinese waters (Dai et al., 2014; Liu et al., 2023), indicating that the species has established populations in these regions. However, detailed historical records of its first occurrence and pathways of introduction are often lacking. Since this species mainly reported in colder water of East China Sea, it could be a non-indigenous species in Qingzhou Bay, China. Pseudo-nitzschia americana was initially described in South America (Hasle, 1964), and has since been reported in the North Atlantic (Lange et al., 1992), Australian waters (Hallegraeff, 1994), Pacific Coasts of Maxico (Hernandez-Becerril, 1998) and Russian Seas (Orlova and Shevchenko, 2002). In China, Pseudo-nitzschia americana has been reported in Guangdong coastal waters since 2012 (Lu et al., 2012). This species has been reported to have better adaptation to cold water, thus it is likely a non-indigenous species in Qinzhou Bay, China. It is worth noting that most HABs, especially Heterosigma akashiwo (e.g. Kim et al., 2023), Karenia mikimotoi (e.g. Chen et al., 2021), Karlodinium veneficum (e.g. Liu et al., 2020), form resting cysts under unfavorable environmental conditions and have been found in ballast water. Therefore, we do not rue out the possibility that the introduction of these HABs is from ballast water. In fact, many more phytoplankton species are able to form resting cysts (Tang et al., 2021). Given that Qinzhou Bay is expecting busy international shipping traffic in the near future, more non-indigenous phytoplankton might be introduced into Qinzhou Bay if ballast water treatment is not well managed. The International Convention for the Control and Management of Ships’ Ballast Water and Sediments (BWM Convention) was implemented in September 2017 (IMO, 2017), and China ratified the convention in October 2018, with regulations coming into force on January 22, 2019. The effective implementation of the BWM Convention should substantially decrease the transfer of non-indigenous species via ballast water and vessel sediments. However, based on the results of a comprehensive risk assessment of ballast water-introduced non-indigenous species in Chinese ports, Wan et al. (2021) reported that Chinese ports are at high risk of invasion, especially busy ports (e.g. Yangtze River Delta, Pearl River Delta, and Southern Taiwan Province), suggesting more efforts are required to improve the efficiency of disinfection and the implementation of the BWM Convention. Given that Qingzhou Bay will be a busy and an important port connecting to the “Pinglu Canal Waterway”, strict standards, regular inspections, and effective disinfection are crucial to decrease the risk of introducing non-indigenous phytoplankton species. 5. Conclusions In a nutshell, the results of our metabarcoding analysis revealed that Qingzhou Bay has at least 205 species of phytoplankton, representing 110 families and 150 genera. Among them, 13 of them are HABs or potential HABs, and 5 of them are potential non-indigenous phytoplankton species. The results of this study are important to serve as baseline information before the operation of “Pinglu Canal Waterway”, an anthropogenic mega project. Declarations Acknowledgement This study was funded by the Natural Science Foundation of Guangxi Province (2023JJD150014), Guangxi Qingmiao Talent Fund for Research Projects (24QMKYQD10), Key Research Base of Humanities and Social Sciences in Guangxi Universities “Beibu Gulf Ocean Development Research Center”, and Pinglu Canal and Beibu Gulf Coastal Ecosystem Observation and Research Station of Guangxi. Author Contributions and Conflict of Interest The authors declare no conflicts of interest. Data Availability Statement The data that support the findings of this study are available from the corresponding author upon reasonable request. References Ajani P, Hallegraeff G, Pritchard T. Historic overview of algal blooms in marine and estuarine waters of New South Wales, Australia. Proceedings of the Linnean Society of New South Wales 2001; 123: 1-22. Bjornland T, Tangen K. 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Journal of Phycology 2000; 36: 33-45. Liu XH, Liu YY, Chai ZY, et al. A combined approach detected novel species diversity and distribution of dinoflagellate cysts in the Yellow Sea, China. Marine Pollution Bulletin 2023; 187: 114567. Liu YY, Hu ZX, Deng YY, et al. Evidence for resting cyst production in the cosmopolitan toxic dinoflagellate Karlodinium veneficum and the cyst distribution in the China seas. Harmful Algae 2020; 93: 101788. Lu SH, Li Y, Lundholm N, et al. Diversity, taxonomy and biogeographical distribution of genus Psedo-nitzschia (Bacillariophyceae) in Guangdong coastal waters, South China Sea. Nova Hedwigia 2012; 95(1-2): 123-152. Marangoni C, Pienaar RN, Sym SD. Possible introduction of alien phytoplankton via shipping ballast water: a South Africa perspective. South African Journal of Botany 2001; 67(3): 465-474. Massana R. 2011. Eukaryotic picoplankton in surface oceans. Annu al Rev iew of Microbiol ogy 65: 91-110. McClenaghan B, Fahner N, Cote D, et al. 2020. Harnessing the power of eDNA metabarcoding for the detection of deep-sea fishes. PloS one 15(11): e0236540. Mikhail S, Khalil N, El-Hadary M. A new recorded of red tide forming species; Heterocapsa triquetra , Gymnodinium impudicum , Heterosigma akashiwo and Thalassiosira rotula in Alexandria Waters, Egypt. Egyptian Journal of Aquatic Biology and Fisheries 2020; 24(6): 207-223. Oda M. The red tide of Gymnodinium mikimotoi Miyake et Kominamin . sp. (MS) and the influence of copper sulfate on the red tide. Zoologisches Magazin 1935; 47: 35-48. Ocean Administration of Tianjin. Report on Marine Environmental Quality of Tianjin, 2016. (in Chinese) Orlova TY, Shevchenko OG. The first finding of Pseudo-nitzchia americana (Bacillariophyta) in Russian Seas. Russian Journal of Marine Biology 2002; 28(5): 336-339. Richard M, Archambault P, Thouzeau G, et al. Inffuence of suspended mussel lines on the biogeochemical ffuxes in adjacent water in the ˆIles-de-la- Madeleine (Quebec, Canada). Can adian J ournal of Fish eries and Aquat ic Sci ences 2006; 63(6): 1198-1213. Tan KS, Xu P, Huang LH, et al. Effects of bivalve aquaculture on plankton and benthic community. Science of the Total Environment 2024; 914: 169892. Tan KS, Sun YZ, Zhang HK, et al. Effects of harmful algal blooms on the physiological, immunity and resistance to environmental stress of bivalves: special focus on paralytic shellfish poisoning and diarrthetic shellfish poisoning. Aquaculture 2023; 563: 739000. Tang YZ, Gu HF, Wang ZH, et al. Exploration of resting cysts (stages) and their relevance for possibly HABs-causing species in China. Harmful Algae 2021; 107: 102050. Torres MAP, Vergara-Jara M, Paredes-Mella J, et al. 2022. An extraordinary 2021 Heterosigma akashiwo (Raphidophyte) bloom in Chile: large-scale farmed salmon mortality associated with unusual environmental conditions. ICHA 19 th Proceedings Surveillance and Management 266-270. Wan Z, Shi ZF, Nie AW, et al. Risk assessment of marine invasive species in Chinese ports introduced by the global shipping network. Marine Pollution Bulletin 2021; 173: 112950. Wang Q, Lin L, Chen XR, et al. Transportation of bloom forming species in ballast water by commercial vessels at Yangshan deep water port. Ocean and Coastal Management 2022; 219(5): 106045. Wang JX, Kong FZ, Wang YF, et al. Newly recorded bloom-forming dinoflagellate Gymnodinium impudcum in Haizhou Bay, Yellow Sea, China. Journal of Oceanology and Limnology 2022; 40(6): 2430-2445. Xu SN, Xiao YY, Xu YW, et al. Effects of seasonal variations and environmental factors on phytoplankton community structure and abundance in Beibu Gulf, China. Ocean and Coastal Management 2024; 248: 106982. Yahia-Kéfi OD, Souissi S, Gomez F, et al. Spatio-temporal distribution of the dominant diatom and dinoflagellate species in the Bay of Tunis (SW Mediterranean Sea). Mediterranean Marine Science 2005; 6(1): 17-34. Yu RC, Liu DY. 2016. Harmful algal blooms in the coastal waters of China: Current situation, long-term changes and prevention strategies. Bull. CAS 31(10): 1167-1174. Additional Declarations No competing interests reported. Supplementary Files TableS1.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5823043","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":402538453,"identity":"7e61d97d-aeef-4a92-83cc-b377f9a414b4","order_by":0,"name":"Karsoon Tan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIiWNgGAWjYHACZhh9DMpKwK+eB6GFLY1kLTxmxGmxZz972ODnnjo5fumeb48Lfh1m4GfPMWD4uQOPLTx5yYk9zw4bS845u914Zt9hBsmeNwaMvWfwOSzH+ADPgQOJG27kbpPm7TnMYHAjx4CZsQ2PFv43xgf/HKgDasl5BtZiT1CLRI5xMs8BZpAWNmmeH0BbJAhpufHG2FjmANAvM9LMjWc2pPNInHlWcLAXjxb2/hxjyTcHgCEmkfzsccEfazn+9uSND37i0YIKgO7hAdEHiNUABH9IUDsKRsEoGAUjBgAAPstO8MYBoUAAAAAASUVORK5CYII=","orcid":"","institution":"Pinglu Canal and Beibu Gulf Coastal Ecosystem Observation and Research Station of Guangxi","correspondingAuthor":true,"prefix":"","firstName":"Karsoon","middleName":"","lastName":"Tan","suffix":""},{"id":402538454,"identity":"96e6b994-3662-4b5f-b054-b6f2c79e9303","order_by":1,"name":"Leiheng Huang","email":"","orcid":"","institution":"Pinglu Canal and Beibu Gulf Coastal Ecosystem Observation and Research Station of Guangxi","correspondingAuthor":false,"prefix":"","firstName":"Leiheng","middleName":"","lastName":"Huang","suffix":""},{"id":402538455,"identity":"3131bf2c-f450-4e4e-b96b-69bfc8403e64","order_by":2,"name":"Jinman Huang","email":"","orcid":"","institution":"Pinglu Canal and Beibu Gulf Coastal Ecosystem Observation and Research Station of Guangxi","correspondingAuthor":false,"prefix":"","firstName":"Jinman","middleName":"","lastName":"Huang","suffix":""},{"id":402538456,"identity":"fdd65acd-77b7-4a2b-8d28-1200e54c60aa","order_by":3,"name":"Cong Luo","email":"","orcid":"","institution":"Pinglu Canal and Beibu Gulf Coastal Ecosystem Observation and Research Station of Guangxi","correspondingAuthor":false,"prefix":"","firstName":"Cong","middleName":"","lastName":"Luo","suffix":""},{"id":402538457,"identity":"14d3c76b-58b5-494e-9f8d-272eae3b2879","order_by":4,"name":"Baoling Xie","email":"","orcid":"","institution":"Pinglu Canal and Beibu Gulf Coastal Ecosystem Observation and Research Station of Guangxi","correspondingAuthor":false,"prefix":"","firstName":"Baoling","middleName":"","lastName":"Xie","suffix":""},{"id":402538458,"identity":"b0bd1cb7-227d-44fa-b65c-c04b3132d594","order_by":5,"name":"Peng Xu","email":"","orcid":"","institution":"Pinglu Canal and Beibu Gulf Coastal Ecosystem Observation and Research Station of Guangxi","correspondingAuthor":false,"prefix":"","firstName":"Peng","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2025-01-14 00:53:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5823043/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5823043/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":74092252,"identity":"ce7be97f-5998-430d-aad7-11f239854070","added_by":"auto","created_at":"2025-01-17 16:24:17","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":322060,"visible":true,"origin":"","legend":"\u003cp\u003eLoction of sampling stations in Da Feng Jiang (control) (stations A-F) and Maowei Sea (affected by “Pinglu Canal Waterway” mega-project) (stations G-L).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5823043/v1/a48d674491abe1d625ca19a4.png"},{"id":75853153,"identity":"6a93939a-e1ab-45c3-8e55-b446942fa3ae","added_by":"auto","created_at":"2025-02-10 02:31:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1384386,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5823043/v1/1421f83c-f3a4-4437-ba90-204e1a55f726.pdf"},{"id":74091544,"identity":"9f966964-9688-4b41-b726-7e74f8d3bd6c","added_by":"auto","created_at":"2025-01-17 16:16:17","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":100507,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-5823043/v1/7d609d41d2430f4ac9188b0e.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Phytoplankton community structure in the Qinzhou Bay, China: a baseline information for non-indigenous species before the operation of the “Pinglu Canal Waterway”","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eShipping is a major pathway for introducing non-indigenous species, with about half of the known introduced species world-wide introduced through shipping activities (Gollasch et al., 2015). Among these, the introduction of non-indigenous phytoplankton species primarily occurs through ballast water, where ballast water along with native phytoplankton species from the loading port are released at discharging port worldwide (Marangoni et al., 2001; Wang et al., 2022; Kraus, 2023). Non-indigenous phytoplankton species can pose significant threats to native phytoplankton species by replacing their ecological niches or introducing new diseases or toxins (Gollasch et al., 2015; Kraus, 2023). Despite the existence of numerous legal frameworks, policies, agreements, and codes of practice regarding the invasion risk due to ballast water release, there is still a considerable probability of introducing non-indigenous species, especially in Chinese ports (Chen et al., 2023).\u003c/p\u003e\n\u003cp\u003eIn July 2022, the Chinese government approved a 10 billion USD mega project called the “Pinglu Canal Waterway” extending 134.2 km from Guangxi (southern China) to Guizhou and Yunnan (Xijiang River). It is expected to fully operate by the end of 2026. The entire route of the “Pinglu Canal Waterway” is constructed according to Class I inland waterway standards and is navigable for vessels of up to 5000-tons (Guo and Yan, 2023). The “Pinglu Canal Waterway” represents the largest river-sea canal in China in centuries, following the Beijing-Hangzhou Grand Canal, which was constructed more than 1000 years ago.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHe et al. (2023) and Tan et al. (2024) explored the distribution of harmful algae bloom species (HABs) in the Beibu Gulf using metabarcoding analysis. However, He et al. (2023) only covered a single offshore station with water depth of 20 m, and Tan et al. (2024) reported only on HABs. Recently, Xu et al. (2024) reported the occurrence and distribution of phytoplankton in the Beibu Gulf, China, based on traditional microscopic morphology-based observation methods. While this provides important information on phytoplankton community structure, microscopic observation methods face challenges in identifying cryptic, deformable, and small phytoplankton species (Massana et al., 2011). Additionally, the accuracy of these methods is highly dependent on the researchers’ experience and expertise.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn this context, this study was carried out to explore the occurrence and distribution of phytoplankton in Qingzhou Bay using the DNA metabarcoding approach. In this study, a list of encountered phytoplankton was summarized to serve as baseline data before the operation of the “Pinglu Canal Waterway” for future investigations. The results of this study not only enrich phytoplankton diversity information in the Qinzhou Bay, but also provide valuable baseline data to study the actual environmental impact of this anthropogenic mega-project. \u0026nbsp;\u0026nbsp;\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Study areas\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQinzhou Bay is located in the northern part of Beibu Gulf (Figure 1), characterized by a tropical climate, and is set to become the most important China-ASEAN free trade area from the sea in Southwest China. On one hand, the Maowei Sea (135 km\u003csup\u003e2\u003c/sup\u003e) in Qinzhou Bay represents the largest natural oyster breeding ground in South China, contributing over two-third of the total natural seed supply (mainly \u003cem\u003eCrassostrea hongkongensis\u003c/em\u003e) for oyster aquaculture (China Fishery Statistical Yearbook, 2023). The mouth of the Maowei Sea will be the entrance of the \u0026ldquo;Pinglu Canal Waterway\u0026rdquo; which is expected to be fully operational by the end of 2026 (Guo and Yan, 2023). On the other hand, the Da Feng Jiang is located about 30 km away from the Maowei Sea. It is known as a preferred habitat by white dolphins\u003cem\u003eSousa chinensis\u003c/em\u003e, and has become a tourist hot spot for dolphin watching (Chen et al., 2016).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Sample collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSamplings were performed from July 2023 to December 2023, covering a total of 12 sampling stations, six in Da Feng Jiang (stations A to F) representing the control stations, and six in Maowei Sea (stations G to L) where the entrance of the \u0026ldquo;Pinglu Canal Waterway\u0026rdquo; is located (Figure 1). At each sampling station, a\u0026nbsp;multiparameter sensor (YSI; Loveland, Co, the USA) was used to record \u003cem\u003ein situ\u0026nbsp;\u003c/em\u003eenvironmental parameters, including\u0026nbsp;water temperature (\u0026ordm;C), salinity (psu), pH, dissolved oxygen (DO) (mg/L), and chlorophyll-a (ug/L), while water depth (m)\u0026nbsp;was measured using\u0026nbsp;a depth sounder. At the same time,\u0026nbsp;triplicate 1 L seawater samples were collected from a depth of 0.5 m below the water surface using a water sampler. These samples were subsequently filtered through a 0.45 \u0026mu;m GF/C membrane (Whatman) and preserved at -80 \u0026ordm;C until genomic DNA extraction.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Genomic DNA extraction, PCR amplification, and DNA sequencing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIsolation of genomic DNA was performed using filtered membrane following the protocol described by Kang et al. (2018) using the DNeasy\u0026reg; Plant Mini Kit (QIAGEN, Hilden, Germany). In short, the membrane was homogenized with 500 \u0026mu;L of lysis buffer using ceramic spheres and a FastPrep-2 (MP Biomedicals), after which the aliquots were screened with a spectrophotometer and stored at -80 \u0026ordm;C.\u003c/p\u003e\n\u003cp\u003eFor PCR amplification, a total reaction volume of 50 \u0026mu;L included 25 \u0026mu;L of 2X Taq PCR Master Mix (Tiangen Biotech, Beijing, China), 50 ng of template DNA, 1 \u0026mu;L each of forward (5\u0026prime;-CCAGCA(G/C)C(C/T)GCGGTAATTCC-3\u0026prime;) and reverse (5\u0026prime;-ACTTTCGTTCTTGAT(C/T)(A/G)A-3\u0026prime;) primers targeting the 18S rDNA V4 region, and diethyl pyrocarbonate water to make up the remaining volume. The PCR conditions included an initial denaturation step at 95 \u0026deg;C for 3 min, followed by 20 cycles of denaturation for 30 s at 95 \u0026deg;C, annealing for 40 s at 50 \u0026deg;C , and extension for 10 min at 72 \u0026deg;C. This was concluded with a final extension step at 72 \u0026deg;C for 10 min. PCR products were evaluated by electrophoresis on 1% agarose gels and subsequently purified using the E.Z.N.A.\u0026reg; Gel Extraction Kit (Omega Bio-Tek, Inc., USA).\u003c/p\u003e\n\u003cp\u003eTo prepare sequencing libraries, the NEBNext\u0026reg; Ultra\u0026trade; II DNA Library Prep Kit for Illumina\u0026reg; (New England Biolabs, Inc., USA) was employed following the manufacturer\u0026apos;s instructions. The PCR products were then sequenced using Hiseq with 250-bp paired-end reads for next-generation sequencing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Bioinformatic analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Fastp software (v0.12.4) was utilized to conduct quality control and filter low-quality reads from sequencing data (Chen et al., 2018). Following this, the filtered reads underwent concatenation using USARCH software (v11.0.667) (Edgar, 2010), during which concatenated sequences and primer sequences shorter than 150 bp were excluded. Then, the sequences were merged, and those with an abundance of less than 4 were discarded. The concatenated sequences were then clustered into Operational Taxonomic Units (OTUs) using a 98% similarity threshold. The resulting OTU sequences were aligned against the NCBI-18S rRNA database using BLAST (v2.2.31) (Sato et al., 2018), filtering out sequences with alignment lengths less than 90%. Species information was assigned based on a 98% similarity criterion (McClenaghan et al., 2020).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Statistical analysis and OTU diversity estimation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe relative abundance of phytoplankton was assessed for statistical significance using the SPSS Windows Statistical Package (version 26). Significance was determined at P\u0026lt;0.05. Prior to analysis, normality and homogeneity of variance tests were conducted on all variables using\u0026nbsp;Kolmogorov\u0026ndash;Smirnov and Levene\u0026apos;s tests. One-way ANOVA was employed, followed by Tukey\u0026apos;s multiple comparison tests (Tukey HSD) for specific contrasts in spatial variations.\u003c/p\u003e\n\u003cp\u003eTo characterize community diversity, Shannon and Simpson indices (Simpson, 1949) were calculated. Community richness was evaluated using the Chao and Ace indices (Chao et al., 2005; Chao and Chiu, 2012). The formulas are as follows:\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\" 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\" width=\"528\" height=\"313\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.6 Literature search for potential non-indigenous invasive phytoplankton species\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSince phytoplankton that negatively impact human health or the environment are well-documented in the literatures, articles reporting on harmful algae blooms (HABs) were gathered from the Google Scholar and Web of Science (up to July, 2024). To ensure comprehensive coverage, additional related articles cited within the reference lists of each article were also retrieved. These steps were repeated until no additional articles were identified. Consequently, a total of 4511 articles were gathered from the literature search.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo identify HABs or potential HABs species in Qingzhou Bay, China, all phytoplankton species collected in this study were cross-referenced with the list above (unpublished data). The occurence and ditribution history of each identified HABs or potential HABs were further explored to determine wherether these species are native or non-indigenous.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 Environmental parameters\u003c/h2\u003e\n \u003cp\u003eThe spatial variation of environmental parameters in Qinzhou Bay is summarized in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. In general, the temperature, salinity pH, DO, Chl-a and water depth during the sampling period ranged from 26.50\u0026thinsp;\u0026plusmn;\u0026thinsp;3.78 to 28.74\u0026thinsp;\u0026plusmn;\u0026thinsp;3.80 \u0026ordm;C, 7.20\u0026thinsp;\u0026plusmn;\u0026thinsp;5.92 to 28.50\u0026thinsp;\u0026plusmn;\u0026thinsp;3.85 psu, 7.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46 to 8.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51, 6.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44 to 8.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41 mg/L, 0.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11 to 3.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35 ug/L, and 3.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10 to 20.00\u0026thinsp;\u0026plusmn;\u0026thinsp;3.15 m, respectively. No statistically significant difference (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) in water temperature and pH were observed among the sampling stations.\u003c/p\u003e\n \u003cp\u003eThe water salinity at stations D, E, and F (27.93 to 28.50 psu) was significantly higher (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), whereas at stations J, K, and L (7.20 to 7.78 psu) was significantly lower (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) than at other stations (9.05 to 23.23 psu). The DO at Da Feng Jiang (stations A to F) (7.44 to 8.16 mg/L) was significantly higher (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) than that at Maowei Sea (station G to L) (6.62 to 6.76 mg/L). The Chl-a concentration at station A, D, E, and F (2.83 to 3.13 ug/L) was significantly higher (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) than at other stations (0.98 to 1.99 ug/L). The water depth at stations D, E, and F (10 to 20 m) was significantly higher (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), whereas in stations A, B, C, J, K, and L (3.0 to 4.8 m) was significantly lower (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) than at other stations.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eEnvironmental parameters in sampling areas\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStation\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTemperature (\u0026ordm;C)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSalinity (psu)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003epH\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDO (mg/L)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eChl-a (ug/L)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDepth (m)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.26\u0026thinsp;\u0026plusmn;\u0026thinsp;3.89\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.64\u0026thinsp;\u0026plusmn;\u0026thinsp;7.88\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.77\u0026thinsp;\u0026plusmn;\u0026thinsp;3.87\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.49\u0026thinsp;\u0026plusmn;\u0026thinsp;8.12\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.98\u0026thinsp;\u0026plusmn;\u0026thinsp;3.84\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.23\u0026thinsp;\u0026plusmn;\u0026thinsp;6.12\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.50\u0026thinsp;\u0026plusmn;\u0026thinsp;3.78\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.50\u0026thinsp;\u0026plusmn;\u0026thinsp;3.85\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.46\u0026thinsp;\u0026plusmn;\u0026thinsp;3.79\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.93\u0026thinsp;\u0026plusmn;\u0026thinsp;2.31\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.00\u0026thinsp;\u0026plusmn;\u0026thinsp;2.38\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.74\u0026thinsp;\u0026plusmn;\u0026thinsp;3.80\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.44\u0026thinsp;\u0026plusmn;\u0026thinsp;2.12\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.00\u0026thinsp;\u0026plusmn;\u0026thinsp;3.15\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.66\u0026thinsp;\u0026plusmn;\u0026thinsp;3.77\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.34\u0026thinsp;\u0026plusmn;\u0026thinsp;2.32\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.81\u0026thinsp;\u0026plusmn;\u0026thinsp;3.78\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.86\u0026thinsp;\u0026plusmn;\u0026thinsp;3.92\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.50\u0026thinsp;\u0026plusmn;\u0026thinsp;3.78\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.05\u0026thinsp;\u0026plusmn;\u0026thinsp;4.23\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.44\u0026thinsp;\u0026plusmn;\u0026thinsp;3.85\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.20\u0026thinsp;\u0026plusmn;\u0026thinsp;5.92\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.98\u0026thinsp;\u0026plusmn;\u0026thinsp;3.87\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.43\u0026thinsp;\u0026plusmn;\u0026thinsp;5.95\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.60\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.35\u0026thinsp;\u0026plusmn;\u0026thinsp;3.88\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.78\u0026thinsp;\u0026plusmn;\u0026thinsp;6.21\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003eDifferent letters indicating significant differences\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Phytoplankton community structure\u003c/h2\u003e\n \u003cp\u003eApproximately 6.1 million raw 18S rRNA reads were generated from Illumina sequencing, averaging around 505,000 sequences per sample. Following bioinformatic processing, 49.5% of these sequences were retained. A total of 9811 Operational Taxonomic Units (OTUs) were annotated as phytoplankton taxa, corresponding to 974 phytoplankton species based on 98% similarity. After excluding \u0026ldquo;uncultured\u0026rdquo; phytoplankton, 205 phytoplanton species were identified, representing 110 families and 150 genera. The dominant phytoplankton species in Da Feng Jiang during the sampling period were \u003cem\u003eTeleaulax amphioxeia\u003c/em\u003e (21.16\u0026thinsp;\u0026plusmn;\u0026thinsp;26.04%)\u0026thinsp;\u0026gt;\u0026thinsp;\u003cem\u003eThalassiosira eccentrica\u003c/em\u003e (11.08\u0026thinsp;\u0026plusmn;\u0026thinsp;7.50%)\u0026thinsp;\u0026gt;\u0026thinsp;\u003cem\u003eCerataulina pelagica\u003c/em\u003e (9.11\u0026thinsp;\u0026plusmn;\u0026thinsp;6.24%)\u0026thinsp;\u0026gt;\u0026thinsp;\u003cem\u003eGuinardia striata\u003c/em\u003e (7.58\u0026thinsp;\u0026plusmn;\u0026thinsp;5.46%). In Maowei Sea, the dominant phytoplankton species were \u003cem\u003eSkeletonema costatum\u003c/em\u003e (22.83\u0026thinsp;\u0026plusmn;\u0026thinsp;17.09%)\u0026thinsp;\u0026gt;\u0026thinsp;\u003cem\u003eStoreatula major\u003c/em\u003e (7.46\u0026thinsp;\u0026plusmn;\u0026thinsp;5.47%)\u0026thinsp;\u0026gt;\u0026thinsp;\u003cem\u003eGyrodinium jinhaense\u003c/em\u003e (6.34\u0026thinsp;\u0026plusmn;\u0026thinsp;5.18%)\u0026thinsp;\u0026gt;\u0026thinsp;\u003cem\u003eTeleaulax amphioxeia\u003c/em\u003e (5.09\u0026thinsp;\u0026plusmn;\u0026thinsp;4.77%) (Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eThe Chao1 (1070.58\u0026thinsp;\u0026plusmn;\u0026thinsp;77.54 versus 695.62\u0026thinsp;\u0026plusmn;\u0026thinsp;39.07) and ACE indices (1059.15\u0026thinsp;\u0026plusmn;\u0026thinsp;77.64 versus 687.78\u0026thinsp;\u0026plusmn;\u0026thinsp;34.49) in Da Feng Jiang were significantly higher (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) than that in Maowei Sea. However, the Shannon and Simpson indices in both areas were statistically insignificant (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3 Potential invasive phytoplankton\u003c/h2\u003e\n \u003cp\u003eA total of 13 HABs or potential HABs were identified in the present study. The average relative abundacne of HABs in Maowei Sea (24.60\u0026thinsp;\u0026plusmn;\u0026thinsp;18.72%) was significantly higher than that in Da Feng Jiang (6.48\u0026thinsp;\u0026plusmn;\u0026thinsp;2.28%) (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Specifically, the relative abundance of HABs was highest (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the mouth of Maowei Sea (stations G and H), followed by inner bay of Maowei Sea (stations J, K and L), and lowest (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) upstream of Da Feng Jiang (stations A, B and C).\u003c/p\u003e\n \u003cp\u003eBased on the natural occurrence and distribution of each HAB or potential HAB species, five were identified as potential non-indigenous species, including \u003cem\u003eHeterosigma akashiwo\u003c/em\u003e, \u003cem\u003eKarenia mikimotoi\u003c/em\u003e, \u003cem\u003eKarlodinium veneficum\u003c/em\u003e, \u003cem\u003ePseudo-nitzschia americana\u003c/em\u003e and \u003cem\u003ePseudo-nitzschia pungens\u003c/em\u003e.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eHABs and potential invasive phytoplankton species in Qinzhou Bay, China\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"13\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSpecies\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eStations in Da Feng Jiang\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eStations in Mao Wei Sea\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eJ\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eK\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eL\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eAkashiwo sanguinea\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eChattonella sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eDinophyceae sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGymnodinium impudicum\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eHeterocapsa pygmaea\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eHeterocapsa rotundata\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeterosigma akashiwo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eKarenia mikimotoi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eKarenia selliformis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eKarlodinium veneficum\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePseudo-nitzschia americana\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePseudo-nitzschia pungens\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSkeletonema costatum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e43.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAverage relative abundance of potential HABs (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\"\u003eSpecies names in \u003cstrong\u003ebold\u003c/strong\u003e are potential invasive phytoplankton species.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn recent years, the rapid advancement of molecular techniques has enabled the detection of phytoplankton communities across all size ranges, including picoplankton and nanoplankton. The 18S rRNA gene of the small ribosomal subunit is a highly effective and sensitive marker for identifying marine eukaryotic microorganisms. Consequently, metabarcoding has become an accurate and effective method for revealing phytoplankton species composition. Metabarcoding techniques have been extensively used to study the occurrence and distribution of phytoplankton (e.g., He et al., 2023; Tan et al., 2024; Xu et al., 2024).\u003c/p\u003e\n\u003cp\u003eIn general, the results of our metabarcoding analysis revealed that there are at least 13 HABs species in Qingzhou Bay. The significantly higher relative abundance of HABs in Maowei Sea compared to Da Feng Jiang is most likely attributed to the high stocking density of oyster aquaculture in the Maowei Sea, the largest natural oyster breeding ground in South China (China Fishery Statistical Yearbook, 2023). Numerous studies have demonstrated that commercial scale bivalve aquaculture caused bottom-uo alteration of phytoplankton community structure by releasing nutrients, especially phosphate and amminia, but not silicate, into the surrounding water (Richard et al., 2006; Jansen et al., 2011; Liang et al., 2019). In fact, the significant lower phytoplankton community richness (indicated by lower Chao1 and ACE indices) in Maowei Sea compared to Da Feng Jiang was evident in the present study. Therefore, it is reasonable to speculate that nutrients released during during bivalve life cycles enhance the growth of dinoflagellates and other HABs (Tan et al., 2024). Within Maowei Sea, the relative abundance of HABs at the mouth of Maowei Sea was remarkably higher than that in the inner bay. This observation could be attributed to the lower salinity in the inner bay of Maowei Sea, where salinity conditions are less favorable for many HAB species (Tan et al., 2023).\u003c/p\u003e\n\u003cp\u003eAmong HABs, five potential non-indigenous species have been identified. It is worth noting that the non-indigenous phytoplankton species identified in this study are mainly those HABs or potential HABs that have been reported to cause negative impact to human health or environment. Therefore, we do not rule out the possibility that there are more non-indigenous species in Qingzhou Bay, as some non-indigenous phytoplankton may not yet have caused significant negative impact that attract scholarly attention.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eGymnodinium impudicum\u003c/em\u003e\u003c/strong\u003e is a non-toxic, naked dinoflagellate known for causing high cell density harmful blooms. It has been commonly reported in Korea (Lee et al., 2001), the Arabian Gulf (Glibert et al., 2002), and various regions of the Mediterranean Sea, including the coastal waters of Spain, Italy, Tunisia, and Egypt (Fraga et al., 1995; Yahia-Kéfi et al., 2005; Mikhail et al., 2020). In China, \u003cem\u003eG. impudicum\u0026nbsp;\u003c/em\u003ehas been observed in the coastal waters of the Bohai Sea (Ocean Administration of Tianjin, 2017) and the Yellow Sea (Yu and Liu, 2016; Wang et al., 2022b), indicating its presence in the region. However, specific documentation confirming it as \"native\" to southern China is limited,\u0026nbsp;but the possibility of the introduction of this species to southern China through the intensive cargo/shipping port activities cannot not be ruled out.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHeterosigma akashiwo\u003c/em\u003e is a small temperate raphidophytes (10-25 μm) that inhabits temperate zones, extending as far north as the Bering Sea and Artic waters, but has not been documented in the Antartic (Engesmo et al., 2016). \u003cem\u003eH. akashiwo\u0026nbsp;\u003c/em\u003ewas first described in Massachusetts as \u003cem\u003eOlisthodiscus carterae\u003c/em\u003e in 1965 (Hulburt, 1965), and then described as \u003cem\u003eEntomosigma akashiwo\u003c/em\u003e in Japan in 1967 (Hada, 1967). Since then, \u003cem\u003eH. akashiwo\u0026nbsp;\u003c/em\u003ehas been reported to cause blooms worldwide, including Chile (e.g. Torres et al., 2022), South Africa (e.g. Bornman et al., 2022), United State of America (e.g. Cochlan et al., 2014) etc. Blooms of \u003cem\u003eH. akashiwo\u0026nbsp;\u003c/em\u003ehave been associated with mass mortality of farmed fish and significant economic loss, especially in British Columbia (loss of USD 4-5 million per bloom) and Washington (loss of USD 2-6 million per bloom) (Cochlan et al., 2014). This temperate species is most likely a non-indigenous HABs in Qinzhou Bay.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKarenia mikimotoi\u0026nbsp;\u003c/em\u003eis an ichthyotoxic dinoflagellate\u003cem\u003e,\u0026nbsp;\u003c/em\u003einitially described as \u003cem\u003eGymnodinium mikimotoi\u003c/em\u003e in 1935 when it first reported bloom in Gokasho Bay, Japan (Oda, 1935). Since then, blooms of \u003cem\u003eK. mikimotoi\u0026nbsp;\u003c/em\u003ehave been documented in the temperate coastal waters of the Atlantic, Indian and Pacific Oceans (see review Li et al., 2019). In China, blooms of \u003cem\u003eK. mikimotoi\u0026nbsp;\u003c/em\u003ehave mainly been documented in\u0026nbsp;the Pearl River estuary and the East China Sea, where shipping activities are intense (Chen et al., 2021). It is most likely that this temperate HAB species is a non-indigenous species in southern China.\u003c/p\u003e\n\u003cp\u003eBlooms of \u003cem\u003eK\u003c/em\u003e\u003cem\u003earlodinium\u003c/em\u003e\u003cem\u003e\u0026nbsp;veneficum\u003c/em\u003e were first documented in South Africa (Braarud, 1957), followed by reports in Europe (Bjornland and Tangen, 1979), North America (Li et al., 2000), and Australia (Ajani et al., 2001). Recently,\u0026nbsp;scientific studies have reported the presence of\u003cem\u003eK\u003c/em\u003e\u003cem\u003earlodinium\u003c/em\u003e\u003cem\u003e\u0026nbsp;veneficum\u003c/em\u003e in Chinese waters (Dai\u0026nbsp;et al., 2014; Liu et al., 2023), indicating that the species has established populations in these regions. However, detailed historical records of its first occurrence and pathways of introduction are often lacking. Since this species mainly reported in colder water of\u0026nbsp;East China Sea, it could be a non-indigenous species in Qingzhou Bay, China.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePseudo-nitzschia americana\u003c/em\u003e was initially described in South America (Hasle, 1964), and has since been reported in the North Atlantic (Lange et al., 1992), Australian waters (Hallegraeff, 1994), Pacific Coasts of Maxico (Hernandez-Becerril, 1998) and Russian Seas (Orlova and Shevchenko, 2002). In China, \u003cem\u003ePseudo-nitzschia americana\u003c/em\u003e has been reported in Guangdong coastal waters since 2012 (Lu et al., 2012). This species has been reported to have better adaptation to cold water, thus it is likely a non-indigenous species in Qinzhou Bay, China.\u003c/p\u003e\n\u003cp\u003eIt is worth noting that most HABs, especially \u003cem\u003eHeterosigma akashiwo\u003c/em\u003e (e.g. Kim et al., 2023), \u003cem\u003eKarenia mikimotoi\u003c/em\u003e (e.g. Chen et al., 2021), \u003cem\u003eKarlodinium veneficum\u003c/em\u003e (e.g. Liu et al., 2020), form resting cysts under unfavorable environmental conditions and have been found in ballast water. Therefore, we do not rue out the possibility that the introduction of these HABs is from ballast water. In fact, many more phytoplankton species are able to form resting cysts (Tang et al., 2021). Given that Qinzhou Bay is expecting busy international shipping traffic in the near future, more non-indigenous phytoplankton might be introduced into Qinzhou Bay if ballast water treatment is not well managed.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe International Convention for the Control and Management of Ships’ Ballast Water and Sediments (BWM Convention) was implemented in September 2017 (IMO, 2017), and China ratified the convention in October 2018, with regulations coming into force on January 22, 2019. The effective implementation of the BWM Convention should substantially decrease the transfer of non-indigenous species via ballast water and vessel sediments. However, based on the results of a comprehensive risk assessment of ballast water-introduced non-indigenous species in Chinese ports, Wan et al. (2021) reported that Chinese ports are at high risk of invasion, especially busy ports (e.g. Yangtze River Delta, Pearl River Delta, and Southern Taiwan Province), suggesting more efforts are required to improve the efficiency of disinfection and the implementation of the BWM Convention. Given that Qingzhou Bay will be a busy and an important port connecting to the “Pinglu Canal Waterway”, strict standards, regular inspections, and effective disinfection are crucial to decrease the risk of introducing non-indigenous phytoplankton species.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eIn a nutshell, the results of our metabarcoding analysis revealed that Qingzhou Bay has at least 205 species of phytoplankton, representing 110 families and 150 genera. Among them, 13 of them are HABs or potential HABs, and 5 of them are potential non-indigenous phytoplankton species. The results of this study are important to serve as baseline information before the operation of \u0026ldquo;Pinglu Canal Waterway\u0026rdquo;, an anthropogenic mega project.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the Natural Science Foundation of Guangxi Province (2023JJD150014), Guangxi Qingmiao Talent Fund for Research Projects (24QMKYQD10),\u0026nbsp;Key Research Base of Humanities and Social Sciences in Guangxi Universities “Beibu Gulf Ocean Development Research Center”,\u0026nbsp;and Pinglu Canal and Beibu Gulf Coastal Ecosystem Observation and Research Station of Guangxi.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions and\u003c/strong\u003e \u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAjani P, Hallegraeff G, Pritchard T. 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CAS 31(10): 1167-1174.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Metabarcoding analysis, Environmental DNA, Qinzhou Bay, Phytoplankton community, Invasive species","lastPublishedDoi":"10.21203/rs.3.rs-5823043/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5823043/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe \u0026ldquo;Pinglu Canal Waterway\u0026rdquo; represents a mega-project in human history, currently under construction in Qinzhou Bay and scheduled to be fully operational by the end of 2026. Since shipping activities are a major pathway for introducing non-indigenous invasive species, baseline data on phytoplankton occurrence and distribution before the operation of the \u0026ldquo;Pinglu Canal Waterway\u0026rdquo; is necessary to better study the ecological impact of this mega anthropogenic activity. In this study, the phytoplankton community structure at the entrance of the \u0026ldquo;Pinglu Canal Waterway\u0026rdquo; (the Maowei Sea) and nearby control areas (Da Feng Jiang) was explored using metabarcoding techniques. A total of 205 phytoplankton species were identified, representing 110 families and 150 genera. Among them, 13 are harmful algal bloom species (HABs) or potential HABs, and 5 are potential non-indigenous invasive phytoplankton species. The results of this study not only enrich the baseline information on phytoplankton in Qinzhou Bay, but also strengthen our foundation for studying the potential environmental impact of the \u0026ldquo;Pinglu Canal Waterway\u0026rdquo; anthropogenic mega-project in the future.\u003c/p\u003e","manuscriptTitle":"Phytoplankton community structure in the Qinzhou Bay, China: a baseline information for non-indigenous species before the operation of the “Pinglu Canal Waterway”","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-17 16:16:12","doi":"10.21203/rs.3.rs-5823043/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"84dd0cf0-7790-4f92-a690-6dee9f5ebc0a","owner":[],"postedDate":"January 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-02-10T02:23:36+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-17 16:16:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5823043","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5823043","identity":"rs-5823043","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}