The distribution characteristics of medusozoans (Cnidaria) related to environmental factors in cold source water intake area of the Fangchenggang Nuclear Power Plant based on eDNA metabarcoding technology

TL;DR

This study uses eDNA metabarcoding to track jellyfish near a nuclear power plant, revealing seasonal and environmental influences on their distribution.

Contribution

The study introduces eDNA metabarcoding as a novel, non-invasive method for assessing medusozoan diversity and distribution near coastal infrastructure.

Findings

Seasonal variations in medusozoan community composition were observed, with 29 species in winter and 56 in summer.

Hydrozoa showed higher abundance than Scyphozoa in both seasons.

Environmental factors like temperature and salinity influence medusozoan distribution patterns.

Abstract

The free-swimming gelatinous stage of medusozoans, generally called ‘jellyfish’, frequently swarms around the intake area of the Fangchenggang Nuclear Power Plant, posing a noticeable risk to its operational safety. Traditional ecological survey methods have limitations in rapidly and effectively assessing the diversity and spatiotemporal distribution of medusozoans, particularly during their early life stages, such as planulae, polyps, and ephyrae. To compensate for these limitations, we employed environmental DNA (eDNA) metabarcoding technology—a non-invasive, efficient, and broadly applicable approach—to conduct targeted surveys during the winter and summer seasons. The findings revealed notable seasonal variations in medusozoan community composition, with 29 and 56 species identified in winter and summer, respectively (p < 0.05). A higher abundance of Hydrozoa and relatively fewer Scyphozoa were observed in both seasons. Horizontally, no significant differences were identified among the defined zones (p > 0.05); however, specific sites such as estuarine, water intake, and drainage areas exhibited unique environmental features influencing the distribution of medusozoans. Vertically, within the 3–8 m depth range, no significant differences in the distribution of them were observed, likely due to the limited depth range and enhanced vertical mixing of the water column (p > 0.05). These observations underscore the utility of eDNA metabarcoding for the rapid detection and assessment of medusozoan diversity and spatiotemporal distribution. As a valuable supplement to traditional survey techniques, this method enhances medusozoan monitoring in marine areas adjacent to Fangchenggang Nuclear Power Plant. Moreover, it enables the investigation of how temperature, salinity, dissolved oxygen, and chlorophyll α variations—driven by both climate change and human activities—influence medusozoan distribution patterns around coastal infrastructures globally.

Figures

Map of sampling stations.

Comparative analysis of alpha diversity indices of medusozoans in winter and summer.(A) Shannon index, (B) Ace index, (C) Simpson index, (D) Shannon evenness index. * (p < 0.05) represents a significant difference. (p < 0.01) represents a very significant difference. * (p < 0.001) represents an extremely significant difference.

Relative read abundance of medusozoans at all sampling stations.(A) Winter, (B) summer.

Comparative analysis of alpha diversity indices of medusozoans across four zones.The zones are defined as follows: zone A comprises W1 and W2, zone B includes W3 and W4, zone C encompasses W5 and W6, and zone D consists of W7 and W8. No significant differences were observed among the zones.

Comparative analysis of alpha diversity indices of medusozoans in surface and bottom water layers.Surface refers to the layer located 0.5 m below the air–water interface, while bottom refers to the layer situated 0.5 m above the seabed. ns (p ≥ 0.05) represents no significant difference.

RDA biplots depicting the connection between the top 20 medusozoan families and environmental parameters across four zones in winter and summer.(A) Winter, (B) summer. Data points, distinguished by color and shape, represent samples from different zones. Arrow length reflects the relative importance of the corresponding parameters, with smaller angles between arrows indicating stronger correlations. All families were included in the analysis; only the 20 families with the highest explained-variance contribution (largest scores on the constrained axes) are labelled.

Spearman correlation heatmap between relative read abundance of medusozoan species and environmental parameters.(A) Winter, (B) summer. Only medusozoans with relative read abundance > 0.1% in each season are shown. * (0.01 < p < 0.05) represents a significant correlation. (p < 0.01) represents a very significant correlation. * (p < 0.001) represents an extremely significant correlation.

Comparison of eDNA metabarcoding and net sampling methods in medusozoan species detection.(A) Stacked bar chart of numbers of medusozoan taxa detected per taxonomic level. (B) Venn diagram of species overlap and uniqueness at the species level. Both (A) and (B) include identified species and species inquirendae.

Full text

Introduction

The subphylum Medusozoa includes species that cannot produce a free-swimming gelatinous stage, as well as those that can produce a free-swimming medusoid/siphonopore stage called jellyfish during their lifecycle. They play significant roles in ecosystems as predators and contribute to pelagic-benthic coupling and vertical carbon export (Murray et al., 2024). However, large-scale jellyfish blooms have caused various negative impacts. These include threats to the survival of other marine species, significant economic losses to fisheries and tourism (Purcell, Uye & Lo, 2007), and operational disruptions, such as blockages in nuclear power plants (NPPs) (Purcell, Uye & Lo, 2007; Wang et al., 2023). Since 1980, medusozoans (used herein to denote any member of the clade Medusozoa, irrespective of medusa-stage presence) have been responsible for 59% of blockage events caused by marine organisms, making them the leading cause (Han et al., 2018). In China, repeated blooms of scyphozoan jellyfish have clogged the seawater cooling systems of the Hongyanhe Nuclear Power Plant, leading to temporary shutdowns of some units. Similar problems have occurred in nuclear facilities worldwide (Wang et al., 2022). While jellyfish blooms were traditionally considered episodic and sporadic, the past decade has witnessed a substantial increase in their occurrence frequency (Dong, Liu & Keesing, 2010; Kennerley et al., 2022; Suárez et al., 2022; Wang et al., 2023). The main drivers behind these outbreaks near NPPs are alterations in oceanic ecosystems, primarily attributed to climate change and anthropogenic impacts (Mills, 2001; Quinones et al., 2018). NPPs are typically positioned in coastal zones to address the energy requirements of densely populated regions and to use seawater for cooling. The electricity generation process produces thermal effluent, which raises the temperature of discharged water, altering the physicochemical properties of the surrounding environment (Muthulakshmi et al., 2019). The extent of these changes depends on season and ambient conditions (Zhang et al., 2023). Qu, Song & Li (2014) indicated that rising sea temperatures create favorable conditions for jellyfish proliferation. Liu et al. (2009) found in laboratory experiments that Aurelia aurita polyps increase ephyra production with temperature, with their numbers doubling at 25 °C and 30 °C compared to 20 °C. The relatively warm seawater near NPPs outfalls often attracts large jellyfish, leading to their aggregation and even blooms (Wu et al., 2023). However, when temperatures rise beyond optimal levels, a certain life stage of medusozoans may cease to grow effectively (Sokołowski et al., 2016), or may die (Purcell et al., 2012).

Elucidating the species composition, spatiotemporal distribution patterns, and environmental drivers governing jellyfish aggregations is fundamental to reducing bloom-induced impacts and developing science-based mitigation strategies in NPPs’ cooling systems. However, a number of medusozoan species exhibit complex polymorphic life cycles, including small and cryptic stages such as planulae, polyps, and ephyrae. These stages are indispensable for population growth, yet pose difficulties for in situ detection and identification (Goldstein & Steiner, 2020; Schnedler-Meyer, Kiorboe & Mariani, 2018). Additionally, many medusozoan species exhibit phenotypic plasticity and have fragile tissues, while the presence of cryptic species further complicate traditional morphological identification (Peng et al., 2023). Historically, the distribution of medusozoans has been assessed through surface visual observation and net sampling of the jellyfish stage (Purcell, 2009). However, visual observation is inadequate for studying deep-water or turbid environments, while net sampling is labor-intensive, time-consuming, and unsuitable for extensive multi-depth and multi-site surveys (Takasu et al., 2019). Furthermore, small jellyfish often evade nets, and large aggregations can clog them, leading to underestimations of their abundance (Takasu et al., 2019). DNA barcoding has proven effective in identifying and detecting medusozoan species. Molecular markers, such as mitochondrial genes (COI and 16S rRNA) as well as nuclear genes (18S rRNA and ITS), have been demonstrated to be viable for phylogenetic analysis and species identification in Hydrozoa and Scyphozoa (Li et al., 2016; Scorrano et al., 2017; Zhang et al., 2015; Zheng et al., 2014). Nevertheless, traditional DNA barcoding technology relies on obtaining specific specimens, and current technological limitations hinder its ability to rapidly evaluate biological community composition across different areas.

The emergence of eDNA metabarcoding has enhanced medusozoan species identification and the study of their population dynamics. By extracting eDNA from water samples and employing high-throughput sequencing, this method enables the efficient identification of species across multiple samples, reducing reliance on traditional, labor-intensive specimen collection and morphological analysis. This relatively novel approach is considered to have certain advantages in terms of cost-effectiveness, labor efficiency, and sensitivity compared to conventional survey techniques, such as trawling, diving, acoustic observations, or aerial imaging. Over the past decade, eDNA technology has been identified as a highly efficient and non-invasive tool for impact assessments, biodiversity surveys, community structure analyses, and biosecurity monitoring (Bunholi, Foster & Casey, 2023). It is particularly effective in detecting rare (Simpfendorfer et al., 2016), invasive (Osathanunkul, 2024), and sporadically distributed species, including medusozoans. The early life stages of certain medusozoans include polyps that attach to benthic substrates and free-swimming, transparent stages such as planula larvae and ephyrae, posing challenges for conventional monitoring methods. eDNA technology has demonstrated potential in identifying these early life stages of scyphozoans. For instance, Gaynor et al. (2017) applied eDNA technique to identify the early life stages of Chrysaora quinquecirrha, while Takasu et al. (2019) used this technique to evaluate the spatiotemporal distribution of Chrysaora pacifica.

The Fangchenggang Nuclear Power Plant (FNPP), China’s first nuclear power project in the western region and ethnic minority areas, is a coastal nuclear power plant featuring pressurized water reactors. Ensuring the reliability of the cooling water system is critical for its safe operation. In recent years, media reports and observations by local fishermen have highlighted sporadic mass occurrences of jellyfish in the surrounding waters. Data from net trawling and visual surveys indicated that the jellyfish primarily consisted of large-sized species such as Rhopilema hispidum, Chrysaora sp., and Cyanea nozakii within the class Scyphozoa, with umbrella diameters ranging from 10 to 50 cm, as well as small jellyfish like Diphyes chamissonis. These medusozoan species can pose a threat to the safe operation of the nuclear power plant when they aggregate in large numbers. The presence and distribution of all types of medusozoans around the FNPP may be influenced by the environmental factors surrounding the plant. However, corresponding scientific studies remain relatively limited. The FNPP’s cold source water intake area hosts a complex ecosystem. Located in Qinzhou Bay, the plant is influenced by freshwater inlets that create varying salinity zones (Lao et al., 2020). The thermal discharge can raise water temperature, forming distinct gradients (Mulhollem, Colombo & Wahl, 2016). Additionally, aquaculture facilities and artificial structures provide suitable habitats for medusozoans to attach and thrive, influencing their species diversity and spatial distribution (Lo et al., 2008; Thé et al., 2020). Previous studies on medusozoans in nearby marine areas have primarily relied on traditional methods (Chen et al., 2015; Du et al., 2012; Zhang et al., 2015). As of the current time, no eDNA-based research has assessed the variety of medusozoans around the FNPP. Building on previous research and to enhance the understanding of medusozoan diversity in this region, this study focuses on the marine area near the FNPP. Understanding the spatiotemporal distribution of medusozoans is essential for devising effective management strategies, such as targeted removal or seasonal avoidance, to mitigate the impacts of medusozoan blooms. The study aims to: (1) Analyze medusozoan biodiversity in the FNPP’s cold source water intake area using eDNA metabarcoding. (2) Investigate the distribution of medusozoans across different zones and water layers during winter and summer. (3) Explore the relationships between medusozoan distribution patterns and main environmental factors, including temperature, salinity, dissolved oxygen, and chlorophyll α (Chl α).

Materials and Methods

Study sites

Based on geographic location and environmental factors, eight sampling sites (W1 to W8) were established in a section of Qinzhou Bay near the FNPP (Fig. 1). W1 was located near the estuarine area, characterized by significant salinity fluctuations and relatively lower salinity levels. W2 was situated at the cold-water intake, a critical zone for FNPP safety. Notably, W5 was positioned in the middle of the drainage nullah, while W6 was closest to the FNPP outfall. Water temperatures at these two sites were significantly higher than at the other sampling locations. W3, W4, W7, and W8 encircled the FNPP drainage outlet and extended seaward. The sampling sites were strategically chosen to ensure comprehensive monitoring of the study area around the FNPP. Two surveys were conducted in this area, on December 29, 2023, and June 11, 2024. A total of 32 seawater samples were collected specifically for eDNA analysis during these surveys. Winter sampling was conducted in response to visually observed large scyphozoan jellyfish near the FNPP’s cold water intake, which could pose a safety risk. Summer sampling aimed to assess the impacts of high temperatures, heavy rainfall and other environmental changes on conditions critical for medusozoans. More importantly, seasonal variations could influence the life histories and behaviors of medusozoans (Schnedler-Meyer, Kiorboe & Mariani, 2018). This pronounced seasonal contrast facilitates the analysis of variations in medusozoan species and distribution in relation to environmental changes.

Map of sampling stations.

Sample collection and processing

At designated stations, seawater samples of distinct volumes were collected from surface and bottom layers (0.5 m below the surface and 0.5 m above the seabed, respectively) using a Niskin Bottle, and separated for eDNA (1 L) and Chl α (500 mL) analyses. All samples were transferred into sterile bottles and stored at 4 °C in a vehicle-mounted refrigerator. The 1 L seawater samples were vacuum-filtered through 0.45 µm Mixed Cellulose Ester (MCE) filter membranes (Membrane Solutions, Hangzhou, China) within four hours of sampling. Negative controls were established throughout the sampling process. Filter membranes designated for DNA extraction were carefully folded, stored in two mL cryopreservation tubes, and cryopreserved in liquid nitrogen for subsequent analysis. To minimize the potential for cross-contamination, all equipment, including the storage containers for seawater, the vacuum filtration apparatus, and tweezers, was disinfected with a 0.1% sodium hypochlorite solution for 15 min and rinsed at least twice with Milli-Q water. Furthermore, to ensure sterility throughout the sampling and processing procedures, gloves and masks were consistently worn.

Environmental parameters (temperature, salinity, and dissolved oxygen) in seawater were measured in real-time using a YSI 650MDS multiparameter water quality analyzer (YSI, USA) at the sampling sites. The 500 mL seawater samples for Chl α analysis were collected from the surface (0.5 m below the surface) and bottom layers (0.5 m above the seabed) at various sites. During transportation to the laboratory, the samples were preserved at low temperatures. Upon arrival, they were filtered to concentrate Chl α. Subsequently, the extraction and measurement of Chl α were performed in accordance with the method described by Ye et al. (2024).

In addition to the seawater sampling and environmental measurements, medusozoan samples were collected at selected stations using a shallow-water Type I plankton net (mouth opening: 0.5 m in diameter, net length: 1.45 m, mesh size: 0.0505 cm) by vertical hauling from the bottom to the surface. Large scyphozoans floating on the sea surface were also collected using a long-handled dip net. Additionally, two specialized interception nets were deployed near the cooling water intake area of the FNPP: a coarse-mesh net (width: 60 m, height: 14 m, mesh size: 12 cm) for larger medusozoans (>15 cm umbrella diameter) and a fine-mesh net (width: 60 m, height: 7 m, mesh size: 3.5 cm) for smaller medusozoans (3–15 cm umbrella diameter). Large specimens were identified through morphological observation, while small specimens required examination under a stereomicroscope and light microscope for accurate identification. When necessary, samples were fixed in 5% formalin seawater for further analysis.

eDNA extraction, high-throughput sequencing and sequence processing

The extraction of eDNA from the MCE membrane was performed using the DNeasy Blood & Tissue Kit (Qiagen, Hilden, Germany), following a modified protocol by Minamoto et al. (2017). Each membrane was cut into small pieces, placed in a two mL sterile tube, and incubated with 40 µL of Proteinase K and 400 µL of buffer ATL at 56 °C for 3 h. Subsequently, the mixture was centrifuged to collect the lysate. An additional 200 µL of buffer TE was applied to the membrane. The eluate, collected through centrifugation, was mixed with 200 µL of Buffer AL and 600 µL of absolute ethanol and loaded onto a spin column in two aliquots, as per the manufacturer’s instructions. eDNA was eluted in two aliquots of 50 µL AE buffer, and the eluates were subsequently pooled. To monitor operational contamination, negative controls were employed in the DNA extraction process. Following elution, the eDNA concentration was measured at an average of 20.23 ng/µL (range: 3.5 to 62 ng/µL). All eDNA samples were immediately preserved at −20 °C, with samples from different sites kept separate to prevent cross-contamination.

The amplification of a 313-bp region within the mitochondrial COI gene was targeted using the primer pair mlCOIintF (5′GGWACWGGWTGAACWGTWTAYCCYCC3′) and jgHCO2198 (5′TAIACYTCIGGRTGICCRAARAAYCA3′) (Leray et al., 2013). The reaction system includes: 15 µL 2 × Hieff^®^ Robust PCR Master Mix, 1 µL each of forward and reverse primers (both at 10 µM), 10–20 ng of template DNA (with the volume adjusted according to DNA concentration), and ddH2O to make up the final volume to 30 µL. The PCR reaction procedure was as follows: an initial denaturation at 94 °C for 5 min, followed by 35 cycles of 30 s at 94 °C (denaturation), 30 s at 54.7 °C (annealing), and 45 s at 72 °C (extension), with a final extension step at 72 °C for 10 min. Illumina bridge PCR-compatible primers were introduced for the second-round PCR. The conditions were the same as above, except for five cycles with an annealing temperature of 58 °C. ddH_2_O negative controls were included throughout the amplification process, and each eDNA sample was amplified in duplicate. Polymerase chain reaction (PCR) products were analyzed by 2% agarose gel electrophoresis to confirm the presence of the target band. No target bands were observed in the negative controls. After purification, the products were quantified using a Qubit 4.0 fluorometer and normalized to equimolar concentrations. Finally, all the purified products were submitted to Sangon Biotech (Shanghai) Co., Ltd. for sequencing on the Illumina MiSeq platform.

Paired-end sequence data were processed using PEAR (v 0.9.8) to merge paired-end reads into single sequences based on their overlap relationships (Zhang et al., 2014). Samples were identified and differentiated based on barcode tag sequences. Clean reads were generated using Fastp (v 0.21.0) by removing adapter contamination and low-quality reads (Chen et al., 2018). Operational taxonomic units (OTUs) were clustered using USEARCH (v11.0.667) at a 97% sequence similarity threshold, with chimeric sequences subsequently identified and excluded (Edgar, 2010). Optimized sequences were mapped to representative OTU sequences using USEARCH to generate an OTU abundance table. Taxonomic classification was performed by aligning sequences to the NCBI Nucleotide Sequence Database via BLAST (E-value ≤ 10^−5^). OTUs with ≥97% sequence similarity were classified at species level, those between 95–97% at genus level, and OTUs below 95% similarity were assigned to family or higher taxonomic ranks (Laroche et al., 2020). Only information on all species within the phylum Cnidaria (excluding the class Anthozoa) and the phylum Ctenophora was retained. The matching results were further investigated by referencing the World Register of Marine Species (2024), an authoritative online database, to focus on medusozoan. To minimize cross-contamination, OTUs with a cumulative number of reads below 20 across all sites were filtered out of the dataset.

Statistical analysis

The sampling-station map was generated with ArcGIS (v 10.8). All downstream analyses and visualizations were restricted to Cnidaria (excluding Anthozoa). Relative read abundances of these taxa were plotted as stacked bar charts with OriginPro 2024. Alpha-diversity indices (Shannon, ACE, Simpson, Shannoneven) were calculated from the OTU count matrix after subsampling with the sub.sample command in Mothur (v 1.43.0) (Schloss et al., 2009). The differential analyses were performed on these indices. Non-parametric methods were chosen because non-normality was confirmed by Shapiro–Wilk tests for sample groups. Wilcoxon signed-rank tests were used for paired winter and summer samples, Mann–Whitney tests for surface and bottom water layers, and Kruskal–Wallis tests for multi-zone differences; all were executed and visualized with GraphPad Prism (v 10.3.1). Spearman correlation (species-level) and redundancy analysis (RDA; family-level) were used to examine relationships among monitoring sites, environmental parameters (salinity, temperature, Chl α, and dissolved oxygen) and medusozoan assemblages. RDA was performed with the vegan package in R (v 3.6.0), using the relative read abundances at the family level as the response-variable matrix and the four environmental parameters as the explanatory variables.

Results

Seasonal composition and distribution of medusozoans

In winter 2023, clustering of 2,257,441 sequencing reads resulted in the identification of 5,498 OTUs. In summer of 2024, clustering of 2,212,253 reads yielded 10,839 OTUs. Following the data screening process described in the ‘Materials and Methods’ section, the winter dataset comprised 55 OTUs and 22,144 reads, representing 29 named species and 12 species inquirendae across two phyla, four classes, eight orders, 26 families, and 33 genera. The summer dataset exhibited higher diversity, with 109 OTUs and 48,049 reads corresponding to 56 named species and 20 undescribed species across one phylum, two classes, five orders, 31 families, and 48 genera. The detected information on medusozoans may originate from distinct life history stages, including polyps, planula larvae, ephyrae, and medusae, as well as reproductive events such as gamete release. Negative controls showed no OTUs assigned to Cnidaria (excluding Anthozoa) or Ctenophora after 97% similarity clustering, confirming that the winter and summer medusozoan OTUs represent in situ assemblages rather than contamination from reagents or airborne sources.

Alpha diversity indices revealed significant seasonal differences (p < 0.05) (Fig. 2). Among species within the subphylum Medusozoa, Orthopyxis caliculata exhibited high relative read abundance in winter across all stations, along with Pennaria disticha, Hybocodon sp., Lytocarpia myriophyllum, and Lafoeidae sp., which collectively accounted for over 60% of reads at each site (Fig. 3A). Additionally, we observed the presence of scyphozoan species including Rhopilema hispidum, Cyanea nozakii, Stomolophus sp., and Chrysaora sp., despite their relatively low relative read abundance. In summer, Aglaophenia pluma was detected at all sampling points, with over two-thirds of these sites showing relative read abundances exceeding 60% (Fig. 3B). Within the monitored area, scyphozoan species including Nemopilema nomurai, Aurelia sp., and Cyanea nozakii were detected with substantially lower relative read abundance values (Fig. 3B). Comparative analysis revealed distinct seasonal shifts in dominant species, while shared medusozoans such as Orthopyxis caliculata, Lytocarpia myriophyllum, Sarsia tubulosa, and Clytia gracilis displayed seasonal fluctuations (Fig. 3).

Comparative analysis of alpha diversity indices of medusozoans in winter and summer.(A) Shannon index, (B) Ace index, (C) Simpson index, (D) Shannon evenness index. * (p < 0.05) represents a significant difference. ** (p < 0.01) represents a very significant difference. *** (p < 0.001) represents an extremely significant difference.

Relative read abundance of medusozoans at all sampling stations.(A) Winter, (B) summer.

Horizontal composition and distribution of medusozoans

Sampling points were categorized into four representative zones. Zone A, comprising W1B, W1D, W2B, and W2D, included sites at the estuary and the nuclear power plant’s cooling water intake, characterized by lower salinity levels compared to other regions. Zone B, encompassing W3B, W3D, W4B, and W4D, represented an intermediate area between the intake and outfall. Zone C, consisting of W5B, W5D, W6B, and W6D, covered the outfall channel and outfall area, exhibiting the highest temperatures due to thermal discharge. Zone D, denoted by W7B, W7D, W8B, and W8D, represented the area downstream of the warm water outfall, progressively distant from the FNPP. This zonal categorization enabled a comprehensive assessment of spatial variability in medusozoan diversity under different environmental conditions.

In this study, medusozoan species from the orders Leptothecata, Anthoathecata, Siphonophorae, Rhizostomeae, and Semaeostomeae were generally detected across all four zones (Fig. S1). Among these, Leptothecata exhibited the highest relative read abundance, followed by Anthoathecata, which showed the second-highest relative read abundance (Fig. S1). These taxa are ecologically widespread and possess both hydroid and/or medusa life stages. An integrated analysis of winter and summer datasets revealed no significant differences in alpha diversity across the four zones (p >  0.05) (Fig. 4). Interestingly, pooling data from multiple sampling sites across different seasons to focus solely on regional differences paradoxically enhanced species composition similarity within each zone (Fig. S2). However, accounting for seasonal factors provided novel insights.

Comparative analysis of alpha diversity indices of medusozoans across four zones.The zones are defined as follows: zone A comprises W1 and W2, zone B includes W3 and W4, zone C encompasses W5 and W6, and zone D consists of W7 and W8. No significant differences were observed among the zones.

Regarding horizontal distribution, particularly during summer, medusozoan species at zones A and B were predominantly characterized by Aglaophenia pluma, Aequorea sp., and Hydra vulgaris. However, in other sites, Aglaophenia pluma emerged as the dominant species, constituting over 50% of the relative read abundance and reaching as high as 80% in some instances (Fig. 3B). In winter, zones C and D exhibited more pronounced dynamic variations in medusozoans distribution. Surface water sampling revealed a lower relative read abundance of Orthopyxis caliculata and Lytocarpia myriophyllum at the warmest sites (zone C). In contrast, Pennaria disticha exhibited a sharp increase, constituting 41.30% and 55.17% of the relative read abundance, accompanied by a substantial rise in Sarsia tubulosa (Fig. 3A). With increasing distance from the thermal discharge outlet, surface water temperatures progressively decreased. Concurrently, the relative read abundance of Orthopyxis caliculata and Lytocarpia myriophyllum increased, while that of Pennaria disticha and Sarsia tubulosa declined (Fig. 3A). Notably, at site W7, the relative read abundance of Hybocodon sp. reached 40.52%, markedly higher than at other sites. At W8, farther from the FNPP and less influenced by thermal discharge, the relative read abundance of the main medusozoan species was comparatively high and evenly distributed (Fig. 3A).

Vertical distribution of medusozoans

Across two seasons (winter and summer), water depth at the sampling sites ranged from ∼3–8 m. At each site, surface (0.5 m below the air–water interface) and bottom (0.5 m above the seabed) samples were collected during each season. While species composition was similar between surface and bottom layers within a season, the relative read abundance of individual taxa exhibited slight disparities. In winter, Pennaria disticha and Orthopyxis caliculata contributed the highest relative read abundance at the surface, whereas the bottom was dominated by Orthopyxis caliculata, Hybocodon sp., and Lytocarpia myriophyllum (Fig. S3). In summer, Aglaophenia pluma had the highest relative read abundance among medusozoans at both depths, followed by Aequorea sp. and Aglaophenia tubulifera (Fig. S3). Taxa with relative read abundances below 0.1% per sample were categorized as “others”. Despite these differences in relative read abundance, a combined analysis of medusozoan data from both seasons showed no statistically significant differences in alpha diversity indices between the surface and bottom water layers (p > 0.05) (Fig. 5).

Comparative analysis of alpha diversity indices of medusozoans in surface and bottom water layers.Surface refers to the layer located 0.5 m below the air–water interface, while bottom refers to the layer situated 0.5 m above the seabed. ns (p ≥ 0.05) represents no significant difference.

The relationship between medusozoan distribution and environmental factors

The RDA biplots illustrate the relationships between the distribution patterns of the top 20 medusozoan families and environmental parameters (temperature, salinity, dissolved oxygen, and Chl α) across four zones in winter and summer (Fig. 6), with the specific environmental parameters presented in Table S1. In winter, temperature, salinity, and Chl α were identified as the main environmental factors. Campanulariidae exhibited a negative correlation with temperature, while Obeliidae showed a positive correlation. Pennariidae and Corynidae were notably negatively correlated with salinity. A strong correlation was observed between temperature and dissolved oxygen, with dissolved oxygen being positively correlated with most species. Chl α also exhibited positive correlations with Laodiceidae and Campanulariidae. Winter sampling points were relatively concentrated across zones, indicating similarities in the multivariate environmental space (Fig. 6A). In contrast, summer sampling points exhibited greater environmental variability across regions, except for zone C. Beyond temperature and salinity, the RDA plots indicated that Chl α and dissolved oxygen also influenced medusozoan distribution during summer. Clytiidae exhibited a positive correlation with temperature. Aglaopheniidae displayed a positive correlation with salinity, whereas Hydraidae and Agalmatidae exhibited negative correlations. Clytiidae exhibited a negative correlation with Chl α, while Aequoreidae, Hydridae, and Apolemiidae showed positive correlations with Chl α (Fig. 6B).

RDA biplots depicting the connection between the top 20 medusozoan families and environmental parameters across four zones in winter and summer.(A) Winter, (B) summer. Data points, distinguished by color and shape, represent samples from different zones. Arrow length reflects the relative importance of the corresponding parameters, with smaller angles between arrows indicating stronger correlations. All families were included in the analysis; only the 20 families with the highest explained-variance contribution (largest scores on the constrained axes) are labelled.

To further evaluate the impact of environmental parameters on medusozoans, our analysis focused on species with relative read abundances exceeding 0.1% in each season. The findings revealed distinct reactions of individual medusozoan species to environmental variables, demonstrating that certain medusozoans are significantly influenced—positively or negatively—by parameters including temperature, salinity, dissolved oxygen, and Chl α (Fig. 7).

Spearman correlation heatmap between relative read abundance of medusozoan species and environmental parameters.(A) Winter, (B) summer. Only medusozoans with relative read abundance > 0.1% in each season are shown. * (0.01 < p < 0.05) represents a significant correlation. ** (p < 0.01) represents a very significant correlation. *** (p < 0.001) represents an extremely significant correlation.

Discussion

Feasibility analysis of eDNA metabarcoding technique to study medusozoan community

The expanding use of eDNA techniques in medusozoan research has significantly enhanced the ability to monitor species, with a particular emphasis on identifying and quantitatively analyzing individual species (Gaynor et al., 2017; Minamoto et al., 2017; Takahashi et al., 2020). This approach has also proven valuable in uncovering the diversity of medusozoans, primarily enabled by the Illumina MiSeq platform. Optimal sequencing insert sizes of 200–500 bp are recommended to balance read length and quality control (Choi & Park, 2020). In studies of medusozoan diversity, the mlCOIintF-jgHCO2198 primer pair has become widely adopted for its efficiency in amplifying a 313-bp segment within the COI gene region, yielding reliable results in surveys of invertebrates and gelatinous plankton (Murray et al., 2024). Studies have further demonstrated that eDNA sampling outperforms conventional net trawling, detecting up to 2–4 times more medusozoan taxa (Feng et al., 2022; Murray et al., 2024). Although the 16S rRNA is considered a better choice for DNA barcoding of cnidarians (Zheng et al., 2014), the universal primers currently used for medusozoans generate longer amplicons that exceed the maximum sequencing length of the Illumina MiSeq platform. These primers are thus more suitable for barcoding tissues from individual medusozoan species rather than eDNA from environmental samples (Zhang et al., 2015). The consensus among many researchers is that COI is considered the most effective barcode for the monitoring of zooplankton, given its heightened specificity and its enhanced resolution at the species level, which is superior to that of 18S rRNA (Fonseca et al., 2022; Tang et al., 2012). Furthermore, Li et al. (2022) demonstrated that the COI metabarcoding marker outperforms the 18S rRNA in species identification within studies of medusozoan diversity in enclosed aquaculture ponds in Liaodong Bay.

Takahashi et al. (2023) conducted a comprehensive review of aquatic eDNA literature from 2012 to 2021, revealing that 33.5% of studies used a water volume of 500–1,000 mL, predominantly 1,000 mL. This volume has been shown to be suitable for detecting representative taxa in marine environments. The concentration of eDNA is influenced by the abundance and shedding rates of target organisms, as well as environmental degradation factors, leading to considerable fluctuations (Takahashi et al., 2023). Furthermore, a study by Minamoto et al. (2017) demonstrated that the extensive distribution of jellyfish may be linked to their substantial eDNA release. Medusae possess a higher rate of eDNA shedding than other animal groups (Andruszkiewicz et al., 2021). Recent studies employing eDNA metabarcoding techniques in field surveys suggest that a 1 L seawater sample is a practical choice for jellyfish-focused research (Peng et al., 2023; Ye et al., 2024).

The sequencing depth ranged from approximately 60,000 to 150,000 reads across the 32 samples examined in this study. Suter et al. (2021) revealed that a modest sequencing depth (∼30,000 sequences per environmental DNA sample) could be adequate for detecting the diversity of metazoans, as evidenced by the enhanced-depth reanalysis of a selection of samples (Suter et al., 2021). Traditionally, research on medusozoan species in the Beibu Gulf region has relied primarily on morphological identification or DNA barcoding derived from net sampling. Chen et al. (2015) documented 125 species across four categories over the course of a year and observed higher species diversity in summer. In the present study, we applied eDNA metabarcoding technology to investigate the medusozoan community in the cooling water intake region of the FNPP for the first time. We detected 29 species in winter and 56 in summer, most of which align with previously reported findings (Chen et al., 2015; Xu et al., 2014; Zhang et al., 2015). Our results indicated a predominance of Hydrozoa, with a smaller representation of Scyphozoa. During sampling, we collected large medusozoan specimens floating on the water surface within the study area. Morphological analysis and DNA barcoding identified these specimens as Rhopilema hispidum and Chrysaora sp., which were consistent with the species detected by eDNA metabarcoding.

Based on the above analyses, we compared the medusozoans detected by eDNA with those captured by all net-capture methods during the sampling period. The results revealed that both methods performed comparably at taxonomic levels above the order level, while eDNA technology demonstrated a clear advantage at the family level and below (Fig. 8A). Overall, a total of 109 medusozoan species were detected (including species inquirendae). Excluding overlaps, eDNA uniquely detected 84.40% of the species, net-capture uniquely detected 10.10%, and overlapping species accounted for 5.50% of the total detections (Fig. 8B).

Comparison of eDNA metabarcoding and net sampling methods in medusozoan species detection.(A) Stacked bar chart of numbers of medusozoan taxa detected per taxonomic level. (B) Venn diagram of species overlap and uniqueness at the species level. Both (A) and (B) include identified species and species inquirendae.

eDNA technology has demonstrated remarkable efficacy in detecting medusozoan diversity, particularly in identifying early life stages and Hydrozoa (Fig. 8, Table S2). However, the potential for false positives remains a consideration. Despite the implementation of stringent standardized protocols and bioinformatics filtering criteria to mitigate this risk, a small number of false positives may still persist, potentially leading to a slight overestimation of the number of species detected. Meanwhile, traditional net-capture methods, while effective in capturing large medusozoans and some smaller ones, also have limitations, such as the potential to overlook species in their early or fragile stages (Table S2). Therefore, further optimization of eDNA technology, in conjunction with insights gained from net-capture data, will enhance the reliability and precision of detection results. Murray et al. (2024) employed eDNA, nets, and video surveys to detect medusozoans, highlighting differences among these methods. Recent studies indicate that eDNA sampling detects two to four times more medusozoan taxa than net trawling, likely due to differences in sampling strategies, taxonomic expertise, and the limited representation of certain taxa in public barcode databases (Feng et al., 2022; Murray et al., 2024). A study further demonstrated that eDNA could capture greater phylogenetic and taxonomic diversity compared to bottom trawling, underscoring the potential of eDNA metabarcoding as a complementary approach for multi-component biodiversity monitoring based on species absence and presence (Veron et al., 2023).

Seasonal distribution and influencing factors of medusozoan community

Medusozoan community compositions, characterized by species richness, the dominance of specific taxa, and diversity indices, shows seasonal fluctuations driven by a complex interplay of environmental parameters, including seasonal precipitation patterns, temperature, and oceanic current dynamics, among others (Diamant et al., 2023; Jannel et al., 2024; Purcell, Uye & Lo, 2007). We observed 29 medusozoan species during the winter of 2023 and 56 species in the summer of 2024. Species diversity was higher in summer, likely due to more abundant food resources and favorable environmental conditions in the summer (Chen et al., 2015). During winter, hydrological instability and rapid water mass displacement allow single-point surface samples to represent larger water bodies, enabling a more comprehensive assessment of regional communities (Cao et al., 2019). Conversely, favorable summer conditions promote the prolific growth of various plankton species, potentially causing blooms of individual taxa (Di Capua et al., 2021). In this study, all reads were subjected to rigorous preliminary screening to ensure they originated from species within the phylum Cnidaria (with the class Anthozoa excluded). We employed bioinformatics tools for sequence alignment and filtering, thereby minimizing potential interference from non-target organisms. However, we acknowledge that there is still some uncertainty regarding whether these reads might include degraded DNA transported from distant sources. If such DNA is present, it could potentially affect our results, such as leading to an overestimation of medusozoan abundance. To address this concern, we recommend the integration of hydrological data into future research. For instance, the application of Lagrangian particle tracking models could simulate the transport pathways of eDNA (Andruszkiewicz et al., 2019). This approach may enhance the accuracy and reliability of eDNA studies in assessing medusozoan populations.

At the order level, Leptothecata (55.05%) and Anthoathecata (36.15%) dominate during winter, while Leptothecata (86.58%) is predominant in summer; all belong to the class Hydrozoa. The rapid generational turnover, high fecundity, and swift growth of medusozoans facilitate rapid population increases under favorable conditions. In the semi-enclosed bay near the FNPP, these conditions are enhanced by abundant food resources and limited dispersal due to moderate sea currents, which also support the sessile polyp stage. The succession of coastal warm-water ecological guilds is primarily driven by seasonal temperature fluctuations. During winter, surface temperatures decrease from offshore to nearshore, dropping below 20 °C north of 21°30′N, favoring the presence of warm-temperate species. In summer, elevated temperatures across the survey area led to a notable increase in warm-water species, particularly in nearshore and mixed water zones (Chen et al., 2015).

Based on RDA analysis, we elucidated the interrelationships between medusozoans classified at the family level, distinct regions, and key environmental factors. Although species composition at the family level showed partial similarities between winter and summer, the interactions between environmental factors (temperature, salinity, dissolved oxygen, and Chl α) and species varied seasonally (Fig. 6). Temperature, which directly influences the body temperature of organisms, significantly affects plankton metabolism, development rate, and reproductive capacity, ultimately impacting their biomass and distribution. Medusozoans adapt to changes in environmental salinity by modulating their internal ion concentrations, enabling survival in water bodies with fluctuating salinity, particularly in regions where salinity varies significantly (Ma & Purcell, 2005; Song et al., 2024). The strong correlation between Chl α and various medusozoans in summer may be linked to heightened influxes of freshwater, sediment, and nutrients from rivers, which collectively enhance phytoplankton biomass, a trend that is reflected in elevated Chl α levels (Lao et al., 2020). Additionally, from a bottom-up ecological perspective, large jellyfish blooms and mortality events can release substantial organic matter and nutrients into the aquatic environment. The catabolism of the organic matter by bacteria can stimulate phytoplankton growth (Wu et al., 2023). Although significant correlations between some medusozoan species and environmental factors were not observed, the Spearman’s correlation heatmap indicates that multiple environmental factors (temperature, salinity, dissolved oxygen, and Chl α) contribute to shaping medusozoan species distribution characteristics to varying degrees (Fig. 7). These findings provide a more comprehensive perspective, enhancing our understanding of the potential ecological relationships between environmental factors and medusozoan species.

In the present study, eDNA metabarcoding technology demonstrated its potential in monitoring the early life stages of medusozoans. During the peak reproductive period in summer, as well as in samples collected from nearshore shallow waters and benthic attachment zones, eDNA technology detected medusozoan species that are challenging to capture using traditional netting methods (Fig. 3, Table S2). The environmental conditions of these areas are conducive to the reproduction and growth of medusozoans in their early life stages (Qu, Song & Li, 2014). Furthermore, this study detected hydrozoan species such as Aglaophenia pluma and Hydra vulgaris, which remain in their polyp stages throughout their entire life cycle and are attached to benthic substrates and other organisms. These species do not form medusa stages, making them difficult to collect using plankton nets (Xu et al., 2014). In contrast, eDNA metabarcoding technology successfully detected their presence, highlighting its potential to monitor both lifelong polyp-stage medusozoans and other species in their early life stages. Additionally, sequencing results revealed that the relative read abundance of certain species was higher in specific areas and closely matched environmental characteristics, suggesting the possible presence of medusozoan early life stages in these regions (Fig. 3). Overall, these results highlight the value of eDNA metabarcoding technology as a complementary tool for monitoring the early life stages of medusozoans, which are critical for understanding their population dynamics.

Horizontal spatial distribution and influencing factors of medusozoan community

The study area near the FNPP supports a distinctive ecosystem that hosts medusozoans at various life history stages. Their sensitivity to environmental fluctuations may significantly influence their spatial distribution. In our study, we primarily observed nearshore warm-water medusozoan species. Notably, both surveys identified Agalma elegans, a species renowned for its broad tolerance to temperature and salinity. This planktonic tropical species, widely distributed, is present year-round in the offshore waters of the South China Sea and East China Sea (Xu et al., 2014). The seasonal circulation patterns of the Beibu Gulf water mass likely facilitate the influx of widely distributed species from the South China Sea, thereby reflecting the occurrence of oceanic species (Cao et al., 2019; Zhang et al., 2015). These findings highlight the complex interplay between environmental conditions, species distribution, and long-distance dispersal events in shaping local biodiversity.

While alpha diversity did not significantly differ among the four zones (p > 0.05), the higher Shannon diversity index observed in zones A and B suggests greater species diversity (Fig. 4), potentially due to their proximity to estuarine regions. During the summer, Qinzhou Bay frequently experiences high water levels, accompanied by increased precipitation and amplified river discharge. Notably, the Qinjiang River and Maoling River, located to the north of the bay, collectively contribute over 50% of the annual seawater volume in summer, approximately six times their contribution during winter (Liu et al., 2017). The study area was also influenced by the Jingu River. The surge in runoff, combined with heightened rainfall, enriches the bay with freshwater and introduces a substantial nutrient load, fostering plankton proliferation. Additionally, marine engineering structures such as ports, artificial shorelines, and aquaculture rafts provide suitable substrates for medusozoan larvae, facilitating settlement and asexual reproduction. Under favorable conditions, these factors can drive rapid medusozoan population growth and dominance (Feng et al., 2017; Thé et al., 2020).

Most medusozoans, which feed on fish eggs, juveniles, and plankton, require abundant food resources to support their rapid growth (Wang et al., 2023). Partial dietary overlap among medusozoan species may result in competition, while regional differences in food availability could limit their viability and fecundity (Goldstein & Steiner, 2020; Wang et al., 2023). Notably, during summer, seawater salinity near the estuaries drops sharply and gradually increases outward from the bay. Salinity fluctuations can influence the buoyancy, reproduction, and feeding rates of small medusae (Ma & Purcell, 2005; Song et al., 2024). Hydra vulgaris, a typical freshwater hydroid, was detected in zones A and B near the estuary of Qinzhou Bay but not in other study areas, suggesting that its presence may be transient rather than indicative of permanent establishment in the surrounding waters of the FNPP. The estuarine networks in Qinzhou Bay facilitated the transport of Hydra vulgaris genetic material from freshwater sources to the marine environment, particularly during flood seasons or heavy rains when the rapid flow of rivers may carry hydrozoans—attached to aquatic plants or other objects—from freshwater to estuarine areas (Lao et al., 2020). The detection of Hydra vulgaris in adjacent coastal cities in Fujian and Guangdong provinces, which shared similar environmental conditions with the study area in Guangxi, supported the hypothesis that Hydra vulgaris was present in the freshwater sources of Guangxi and could be transported to the estuaries via river systems (Xu et al., 2014). Additionally, Cordylophora caspia, is notable for its rapid proliferation across a wide range of salinities. It was reported that this species clogged intake pipes of power plants, and fouling issues were observed in the United States and Europe (Folino-Rorem & Indelicato, 2005). Its global spread has been facilitated by ballast water transport and increased boat traffic (Folino-Rorem & Indelicato, 2005).

During summer, Station W2 near the FNPP’s cooling water intake exhibited the highes species richness, with Aglaophenia pluma as the predominant contributor (Fig. 3B). This colonial hydroid, characterized by its feathery colonies and association with Halidrys siliquosa in shallow rocky areas (∼10 m deep), is globally distributed. Uniquely among Aglaophenia species, it also occurs in intertidal rock pools and shores. The widespread presence of Aglaophenia pluma across sites suggests that summer conditions favor its survival and reproduction. Its higher detection at W2 is probably caused by the entrainment effect of the cooling water intake, which concentrates the species in that area. Notably, during winter, scyphozoan jellyfish, especially Rhopilema hispidum and Chrysaora sp. (among others), were detected at nearly all points despite their low abundance (Fig. 3A). Given the limited swimming capabilities, the broad distribution of these medusozoans is likely driven by passive transport via buoyancy, ocean currents, and wind patterns, rather than active habitat selection (Song et al., 2024; Suzuki et al., 2018). The detection of large jellyfish near cooling water intake structures can pose a potential threat to nuclear power operations due to clogging risks. During winter sampling, staff at FNPP installed interception nets at the intake and removed jellyfish to mitigate the clogging risk they pose. When large medusozoans, particularly scyphozoan jellyfish, enter cooling-water systems, they can cause filter blockage and pipe accumulation, impeding normal water flow. This disruption can lead to reduced power level operation or even plant shutdowns, presenting notable safety and economic risks. For example, jellyfish blooms in 2011 across the United States, Japan, Israel, and Scotland resulted in nuclear power plant shutdowns (Han et al., 2018). Similarly, Hongyanhe Nuclear Power Plant has been facing jellyfish-related issues since 2014, mainly due to Aurelia coerulea and Nemopilema nomurai (Wang et al., 2023). These examples highlight the widespread nature of medusozoan intrusion as a challenge for NPPs. The implementation of interception nets at FNPP demonstrates a proactive approach to mitigating this risk. Future research should focus on developing effective monitoring and prevention strategies tailored to different NPPs to ensure their safe and stable operation.

Seasonal fluctuations and thermal discharges from the FNPP influence temperature variations in the adjacent marine area, particularly in zones C and D, where temperatures are notably higher near the thermal discharge outlet compared to other locations. Previous studies have shown that the impact of elevated seawater temperatures is most significant in the surface layer, rapidly attenuating with depth and becoming negligible below three m (Chen et al., 2023). Furthermore, temperature plays a critical role in medusozoan development, affecting ephyrae production during the asexual phase and medusa maturation during the sexual phase (Feng et al., 2020). The polyp stage, essential for sustaining and increasing jellyfish populations across seasons and years, is affected by its tolerance to temperature increases (Frolova & Miglietta, 2020). Temperature represents a direct factor influencing medusozoan growth rates, whereas water movement and food availability constitute indirect factors affecting medusozoan populations (Qu, Song & Li, 2014; Wu et al., 2023).

During a specific winter period, the FNPP’s discharge outlet and the downstream regions (W5 through W8) exhibited a decreasing temperature trend. Notably, the relative read abundances of Pennaria disticha and Sarsia tubulosa increased near the thermal discharge outlet (Fig. 3A). This phenomenon could be attributed to elevated seawater temperatures, which create conditions favorable for jellyfish populations and their aggregation (Qu, Song & Li, 2014), especially hydrozoan species such as Pennaria disticha that thrive in elevated temperatures and exhibit strong thermal adaptability (Bosch-Belmar, Piraino & Sarà, 2022). The substantial thermal effluents discharged from NPPs can affect the hydrodynamic conditions and marine biological diversity in adjacent areas (Lee, Tseng & Hwang, 2018; Wang et al., 2023). Conversely, during a specific summer period, the expected temperature trends at the FNPP’s discharge outlet and its downstream regions did not correspond to a clear pattern in medusozoan species data (Fig. 3B). This inconsistency may result from the combined effects of thermal effluent and elevated summer water temperatures. Species that thrive in the discharge area during winter might exhibit different patterns in summer (Lin, Zou & Huang, 2018), as thermal discharge can raise temperatures beyond the optimal range for the growth of some medusozoan species. This could suppress early larval development, slow growth rates, and reduce abundance (Liu et al., 2009). Additionally, eDNA degradation affects detection results, with temperature playing a critical role. Studies across various temperatures have demonstrated a linear correlation between temperature and eDNA degradation rate constants (McCartin et al., 2022; Strickler, Fremier & Goldberg, 2015). In this study, the eDNA signals of Aequorea sp. and Hydra vulgaris were reduced in the summer thermal discharge zones of FNPP. This reduction likely results from the elevated temperatures in these thermal discharge zones, which may expedite eDNA degradation (McCartin et al., 2022). Consequently, such degradation could lead to an underestimation of some target medusozoan species, potentially explaining the lack of a marked increase in medusozoan diversity observed in the summer thermal discharge zones. Therefore, when analyzing eDNA data from areas with temperature variations, it is essential to consider the effects of temperature on eDNA degradation to ensure more accurate assessments of species presence and diversity. Notably, during our investigation, scyphozoan jellyfish species including Nemopilema nomurai, Aurelia sp., and Cyanea nozakii were detected in proximity to thermal discharge zones. Wu et al. (2023) suggested a potential connection between thermal discharges and jellyfish blooms near NPPs, indicating that local warming may trigger complex ecological processes. These processes involve medusozoan abundance, temperature, nutrient concentrations, and community structure, thereby connecting the impacts of thermal discharges to the mechanisms driving jellyfish blooms (Wu et al., 2023).

Vertical spatial distribution and influencing factors of medusozoan community

Given the limited vertical variation of environmental factors across sampling zones, we separately merged all surface samples and all bottom samples for holistic analysis. This increased the sample size for each layer, enhancing statistical reliability and avoiding information loss from data partitioning. Simultaneously, it can comprehensively capture the vertical distribution of medusozoans and the combined effects of environmental factors. Determining the vertical distribution of medusozoans is essential for understanding their trophic interactions, vertical migration behaviors, and spatiotemporal changes in response to global change (Moriarty et al., 2012; Ye et al., 2024). However, within our research, no significant differences were found between surface and bottom waters regarding alpha diversity indices during both seasons (p > 0.05) (Fig. 5). This could be attributed to the narrow depth range of 3–8 m in our study area, which reduces the stratification distance between sampling layers. The water mass characteristics in the northeastern Beibu Gulf, particularly during winter, promote vertical mixing (Cao et al., 2019). Such mixing can homogenize eDNA distribution, possibly masking actual biological distribution patterns. Thus, the lack of significant surface-bottom differences might mainly arise from physical mixing rather than reflecting actual medusozoan distribution, highlighting the need for further inquiry. Additionally, the inherent limitations of eDNA technology must be considered, as it may not fully distinguish between the effects of environmental and anthropogenic factors on eDNA distribution. For instance, near the FNPP, environmental factors such as natural water temperature fluctuations and ocean currents can influence eDNA dispersal. Simultaneously, anthropogenic impacts like thermal discharge from the power plant and potential chemical emissions also play a role. Without specific hydrodynamic data, such as thermal discharge dispersion patterns, it is challenging to disentangle these influences. Given these findings, future research could benefit from equally mixing surface and bottom water samples at each station to ensure a comprehensive analysis and enrich the eDNA dataset (Li et al., 2022). Furthermore, incorporating hydrodynamic data, such as thermal discharge dispersion, would enhance the ability to differentiate between environmental and anthropogenic impacts on medusozoan eDNA distribution. However, for studies targeting specific medusozoan species or areas with significant depth variations—such as both bay interiors and exteriors—vertically stratified comparisons remain crucial (Minamoto et al., 2017; Peng et al., 2023). We recommend that future studies balance integrated sampling with detailed stratification to fully elucidate the structure and ecological distribution of medusozoan communities.

Limitations and future perspectives of the study

Medusozoan species exhibit considerable variability in their ecological presence and abundance, with significant differences in temporal, spatial, and numerical distribution across years and locations (Frolova & Miglietta, 2020). Conventional field surveys, limited by sampling omissions and the subjectivity of morphological species identification, may underestimate or misrepresent actual biomass. The introduction of eDNA metabarcoding has broadened the scope of medusozoan diversity research; however, species-level identification remains hindered by several factors, including the choice of molecular markers, the quality of reference databases, DNA degradation during sample handling, intrinsic biological traits of medusozoans, and technical limitations such as PCR amplification bias and sequencing errors (Bunholi, Foster & Casey, 2023; Murray et al., 2024; Yang, Zhang & Du, 2023). In this study, we used eDNA metabarcoding with the COI marker and NCBI Nucleotide Sequence Database for medusozoan species identification. While the COI marker demonstrates relatively high species identification potential for medusozoans, its effectiveness may vary across different molecular markers due to disparities in marker resolution and the intricate nature of medusozoan DNA in aquatic environments (Li et al., 2022). Compared to other marine fauna, foundational ecological data for medusozoan species remain scarce. Existing databases, such as GenBank, are acknowledged to have limitations and may contain inaccuracies, including misidentified nominal species resulting from taxonomic expertise gaps or the presence of cryptic species (Lindsay et al., 2017; Santoferrara, 2019). These limitations, combined with the fact that some OTUs are annotated only at the family or genus level, and that changes in the external environment may alter the coverage and amplification efficiency of the primer pair (mlCOIintF-jgHCO2198), can compromise the accuracy of species identification, particularly for understudied or low-abundance species, risking incomplete detection of certain groups. Due to the lack of a comprehensive medusozoan database, many studies opt for the NCBI Nucleotide Sequence Database (Peng et al., 2023; Ye et al., 2024). Although this database includes COI sequences for some common Chinese coastal medusozoans and is widely used in research, some species remain underrepresented. We acknowledge these limitations and recommend initially focusing on higher taxonomic levels, such as families or genera, to achieve a broader understanding of medusozoan distribution and habitat characteristics.

The new findings, such as the likely presence of previously undetected, fragile, and tiny hydromedusae, as well as the identification of cryptic, repeatedly encountered but unmarked taxa, will stimulate further research and enhance our understanding of their diversity in the adjacent sea area of FNPP. In this study, we introduced “species inquirendae” to explore medusozoan species that may be under-recognized or undescribed. The process of designating “species inquirendae” may lead to false positives or taxonomic errors. This underscores the challenges in species identification. The reliability of eDNA technology is highly dependent on comprehensive databases. Yet, current databases may not adequately cover the genetic information of these undescribed species (Santoferrara, 2019). Factors such as high DNA sequence similarity, insufficient primer specificity, or a lack of morphological and genetic data can lead to potential misidentifications of non-target species’ DNA as “species inquirendae” (Pagès, 2002). The widespread limitations can affect the accurate assessment of medusozoan diversity and community structure.

To improve the efficacy of eDNA technology in species-level identification, future studies should focus on optimizing sampling methods, expanding and refining local medusozoan eDNA databases, and employing multiple molecular markers with optimized primer design. It is also essential to validate the coverage and amplification efficiency of primers to ensure identification reliability, while integrating morphological identification can further enhance accuracy. Although traditional eDNA metabarcoding performs well in species identification, it typically fails to provide absolute quantitative information, limiting biomass assessment. Quantitative metabarcoding with internal standards can convert reads into absolute DNA copy numbers and correct PCR bias, improving data reliability (Smets et al., 2016; Ushio et al., 2018). These capabilities make the approach promising for future monitoring. In addition, incorporating quantitative PCR to determine absolute abundance metrics will provide a comprehensive understanding of medusozoan community composition and dynamics by combining relative and absolute abundance data. The quantitative PCR-based approach will also serve to further explore the use of eDNA technology in monitoring the early life stages of scyphozoan jellyfish (Gaynor et al., 2017). Moreover, future research could address the challenges of predicting and managing medusozoan-related risks by integrating eDNA data with particle-tracking models. By leveraging numerical ocean models to simulate particle movement, this approach can enhance the precision of predicting medusozoan bloom trajectories. A study employing Lagrangian particle tracking to simulate coastal ocean eDNA transport has confirmed the effectiveness of integrating eDNA data with hydrodynamic models in enhancing the comprehension of eDNA transport processes (Andruszkiewicz et al., 2019). This approach offers a promising method for more accurate predictions of jellyfish bloom dispersion paths. Consequently, future research could explore the potential of eDNA technology for long-term medusozoan community monitoring, as well as its application in predicting jellyfish blooms and assessing ecological risks.

Conclusion

The application of eDNA metabarcoding technology in this study has uncovered variations in the spatiotemporal distribution and species diversity of medusozoans within the FNPP cold source water intake area. Our findings revealed significant seasonal variations (p < 0.05), with higher species diversity observed in summer. Both seasons showed a notable prevalence of Hydrozoa and a limited occurrence of Scyphozoa. Although some medusozoan species could not be identified to the species level and were classified at higher taxonomic ranks, their widespread presence across multiple sampling sites and high relative read abundances provided valuable insights into medusozoan diversity, even with low database match confidence. Additionally, environmental factors in estuaries, cold source water intake points, and thermal discharge areas were correlated with medusozoan distribution, suggesting that these areas should be prioritized for future monitoring and research. No significant vertical distribution differences were observed within the 3–8 m depth range (p >  0.05), indicating that mixed water layer sampling could improve sample representativeness and detection efficiency in future studies. Finally, temperature, salinity, and Chl α concentration were identified as main environmental factors potentially influencing medusozoan distribution. These findings not only validate the potential and effectiveness of eDNA metabarcoding technology for monitoring delicate and less-known medusozoan species but also provide new data for understanding the ecological habits and spatiotemporal distribution of medusozoan communities, offering a scientific basis for setting monitoring priorities and management strategies in the cold source water intake area of NPPs. Future integration of eDNA data with particle-tracking models and traditional surveys will enhance predictive capabilities for medusozoan-related operational risks, particularly for scyphozoan jellyfish, at both regional and global scales.

Supplemental Information

10.7717/peerj.20890/supp-1Supplemental Information 1Relative read abundance of medusozoan orders across all sampling stations

10.7717/peerj.20890/supp-2Supplemental Information 2Relative read abundance of medusozoans across four zones(A) Winter, (B) summer. The zones are defined as follows: zone A comprises W1 and W2, zone B includes W3 and W4, zone C encompasses W5 and W6, and zone D consists of W7 and W8.

10.7717/peerj.20890/supp-3Supplemental Information 3Relative read abundance of medusozoans in surface and bottom water layers at all sampling stations(A) Winter, (B) summer. Surface refers to the layer located 0.5 m below the air–water interface, while bottom refers to the layer situated 0.5 m above the seabed.

10.7717/peerj.20890/supp-4Supplemental Information 4The environmental factors

10.7717/peerj.20890/supp-5Supplemental Information 5The information detected by both eDNA metabarcoding and net capture methods on medusozoans

10.7717/peerj.20890/supp-6Supplemental Information 6The list of names corresponding to sampling and sequencing stations