Biodiversity and distribution of zoobenthos in the ecological water replenishment area of the Yellow River estuary coastal wetland revealed by eDNA metabarcoding

sequence was manually verified through BLAST searches in the NCBI nucleotide sequence database and compared against local species surveys following previously described criteria [19]. Only sequences with �98% identity to GenBank entries were included in subsequent analyses to ensure accurate species-level assignments. Human sequences were excluded from all analyses. 2.5. Statistical and multivariate analyses Zoobenthic invertebrate abundance was analyzed with detrended correspondence analysis (DCA) to determine gradient lengths, revealing values below 3, which justified the use of Redundancy Analysis (RDA) to explore relationships between community composition and environmental variables [31]. Community composition differences were visualized using Non- metric Multidimensional Scaling (NMDS), with PERMANOVA assessing significant differ- ences across sampling sites [32,33]. The Shannon–Wiener index and ANOVA were used to analyze alpha diversity indices and community composition differences [34]. The Kruskal– Wallis test was used only when data did not meet ANOVA assumptions [35]. A co-occurrence ecological network was constructed using OTUs with > 0.1% relative abundance, analyzed through RMT-based methods [36,37]. 3. Results 3.1. Environmental parameters The water quality analysis from various sampling sites (S1 to S16) reveals significant variability with ecological water replenishment, along with several noteworthy relationships among the physical and chemical parameters (Table 1). EC and TDS exhibit a strong positive correlation,

as TDS measures the dissolved ions contributing to EC. For example, site S16 shows both the highest EC (70400 ± 5895 μS/cm) and TDS (38250 ± 1665 mg/L), while site S2 has the lowest values for both parameters (EC: 889 ± 1 μS/cm, TDS: 444 ± 2 mg/L). Additionally, SAL also positively correlates with EC and TDS. This suggests that salinity is a major contributor to the dissolved solids that influence conductivity. Sulfate concentrations also contribute to the over- all dissolved solids and conductivity. For example, site S16, with high sulfate levels (1024 ± 5 mg/L), exhibits correspondingly high TDS and EC. The concentrations of cations such as Na+, K+, Mg2+, and Ca2+ are positively correlated with each other and with TDS, reflecting the com- mon ionic composition of the coastal water samples. DO generally shows an inverse relation- ship with temperature, with higher temperatures often resulting in lower DO levels due to decreased oxygen solubility in warmer water. Nutrient levels, such as NH4+-N and TP, show variable correlations with organic and inorganic parameters. Higher NH4+-N levels, indicating potential pollution sources such as anthropogenic activities, are observed at sites S8 and S9, correlating with high TOC levels. 3.2. Zoobenthos community compositions and distributions Zoobenthos comprising 20 phyla, 31 classes, 73 orders, and 174 families were identified through sediment eDNA metabarcoding (S2 Table). The primary phyla include Annelida, Arthropoda, Gastrotricha, Nematoda, Ostracoda, and Platyhelminthes. These phyla are

divided into classes such as Chromadorea, Clitellata, norank, Ostracoda, and Rhabditophora. Each class further divides into orders, including Chaetonotida, Chromadorida, Monhysterida, and Plectida. These orders lead to specific families such as Aphanolaimidae, Chaetonotidae, Chromadoridae, Dalyelliidae, Limnocytheridae, Monhysteridae, Naididae, Schizocytheridae, Typhloplanidae, and Xyalidae, among others (S1 Fig). PLOS ONE Biodiversity and zoobenthos distribution in yellow river estuary wetlands revealed by eDNA metabarcoding PLOS ONE | https://doi.org/10.1371/journal.pone.0315346 December 18, 2024 6 / 19