Seasonal changes of prokaryotic microbial community structure in Zhangjiayan Reservoir and its response to environmental factors

As a typical sub-deep reservoir in the upper reaches of the Yangtze River in the southwest region, Zhangjiayan Reservoir is also an important source of drinking water. Exploring the role of microorganisms in the material cycle of water bodies is of great significance for preventing the exacerbation of eutrophication in the reservoir. In this study, water samples from the overlying water of five points in the reservoir were collected four times in spring (April), summer (July), autumn (November), and winter (January) of 2022–2023 using a gas-tight water sampler. Physicochemical factors were measured, and the microbial community structure was analyzed by high-throughput MiSeq sequencing of the V3–V4 hypervariable region of 16S rRNA gene in order to explore the relationship between physicochemical factors and microbial community structure and the dominant microbial populations that affect eutrophication of the reservoir. The following results were obtained through analysis. Among the 20 overlying water samples from Zhangjiayan Reservoir, a total of 66 phyla, 202 classes, 499 orders, 835 families, 1716 genera, and 27,904 ASVs of the bacterial domain were detected. The phyla Proteobacteria and Actinobacteria were dominant in the microbial community of the overlying water in Zhangjiayan Reservoir. At the genus level, hgcI_clade and Actinobacteria had the highest abundance and was the dominant population. The microbial community in the water of Zhangjiayan Reservoir has a high level of diversity. The diversity index ranked by numerical order was winter > autumn > summer > spring. Significant differences were found in the composition and structure of the microbial community between the spring/summer and autumn/winter seasons (p < 0.05). Total phosphorus, dissolved total phosphorus, soluble reactive phosphorus, and dissolved oxygen have a significant impact on the composition and structure of the microbial community (p < 0.01). The bacterial community in the overlying water of Zhangjiayan Reservoir showed a mainly positive correlation. Sphingomonas, Brevundimonas, and Blastomonas were the central populations of the bacterial community in the overlying water of Zhangjiayan Reservoir. This study indicates that environmental factors, such as phosphorus and other nutrients, have a significant impact on the formation of the microbial community structure in different seasons. Sphingomonas, Brevundimonas, and Blastomonas are key populations that may have a significant impact on eutrophication in Zhangjiayan Reservoir.


Research area and sample collection
Based on the characteristics of the overlying water body and eutrophication status of Zhangjiayan Reservoir, a total of 5 sampling points were set up in the entire lake (Fig. 1).In spring (April), summer (July), autumn (November), and winter (January) of 2022-2023, the overlying water (5-10 cm above the sediment) was collected using an gas-tight water sampler.Each sampling point is repeated three times for sampling.The samples are then stored and transported in accordance with the relevant requirements of the "Water Quality Monitoring Specification SL219-98".The samples containing the ice packs shall be kept in a cold storage at 4 °C for temporary storage and undergo physical and chemical analysis within 24 h.The raw water (1 L per sample) used for DNA extraction was immediately filtered through a 0.45 μm water-based polyethersulfone material microporous filter membrane to remove impurities.Subsequently, a vacuum pump was used to filter the sample through a 0.22 μm water-based polyethersulfone material microporous filter membrane.The filtered membranes were then carefully removed and stored at − 80 °C in an ultra-low temperature freezer for subsequent DNA extraction purposes.

Measurement of water quality indicators
pH and water temperature (T) were measured on site using the HI991301 portable multi-parameter temperature measuring instrument.Dissolved oxygen (DO) was measured on site using the HQ3OD portable dissolved oxygen meter.Total nitrogen (TN), five-day biochemical oxygen demand (BOD 5 ), permanganate index (COD Mn ), and chlorophyll a (Chla) were measured according to the experimental protocol of Guo et al. 6 .Total phosphorus (TP), dissolved total phosphorus (DTP), and soluble reactive phosphorus (SRP) were measured according to the experimental protocol of Li et al. 13 .

DNA extraction and PCR amplification
After cutting the sterile membrane used for DNA extraction into pieces with sterile scissors, the total genomic DNA was extracted using the DNA extraction kit (FastDNA Spin Kit, MP Biomedicals, Santa Ana, CA, USA) and the operating procedures were followed as instructed by the kit manual.The DNA extracted was checked by 1% agarose gel electrophoresis, and the concentration of DNA was determined using a micro-spectrophotometer (NanoDrop ND-2000, ThermoScientific, Waltham, MA, USA).The extracted DNA was stored in a freezer at − 80 °C for future use.
PCR amplification and high-throughput sequencing were performed using bacterial primers 338F: 5′-ACT CCT ACG GGA GGC AGC A-3′ and 806R: 5′-GGA CTA CHVGGG TWT CTAAT-3′ 15 .The PCR protocol was as follows: 30 cycles of initial denaturation at 95 °C for 30 s, denaturation at 98 °C for 15 s, annealing at 55 °C for 30 s, extension at 72 °C for 30 s, and then extension at 72 °C for 10 min.The PCR amplification products were subjected to agarose gel electrophoresis using a 2% agarose gel.The desired fragments were then recovered using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA).Each sample was repeated three times.After fluorescence quantification of the PCR products, the sequencing was performed on an Illumina's Miseq PE300 platform (provided by Shanghai Majorbio Bio-Pharm Technology Co. Ltd., Shanghai, China).

Data processing
The DNA was sequenced using the Illumina Miseq PE300 platform (Shanghai Majorbio Bio-pharm Technology Co., Ltd.) with paired-end reads of 300 base pairs.The original paired-end sequencing reads were subjected to quality control and assembly using the fastp software (https:// github.com/ OpenG ene/ fastp) 16 .The Dada2 algorithm in the QIIME2 17 pipeline was employed to denoise the sequences, resulting in high-quality sequences.The sequences that have undergone Dada2 denoising are typically referred to as Amplified Sequence Variants (ASVs).In order to compare the changes in microbial communities among different varieties, all bacterial samples were subsampled at a certain sequencing depth, and subsequent analysis was performed on the subsampled bacterial samples.

Data analysis
Statistical analysis was performed using the statistical product and service solutions (SPSS) statistical software (version 20.0, IBM, Armonk, NY, USA).Based on the Silva 16S rRNA gene database (v 138, http:// green genes.secon dgeno me.com), the ASVs were taxonomically classified using the Blast classifier in Qiime2 for species-level analysis 18 .The Alpha diversity indices Chao and Shannon were calculated using the software mothur 19 (http:// www.mothur.org/ wiki/ Calcu lators), and the Wilcoxon rank-sum test was performed to analyze the inter-group differences in Alpha diversity.The similarity of microbial community structure among samples was examined www.nature.com/scientificreports/through NMDS analysis using the Bray-Curtis distance algorithm.The Wilcoxon multiple test was performed to conduct hypothesis testing of the species in the microbiota among multiple sample groups, in order to determine the bacterial taxa with significantly different abundance between different groups.Redundancy analysis (RDA) is used to investigate the impact of environmental factors on bacterial community structure 20 .The co-occurrence network at the genus level was visualized using Gephi software.In order to reduce the complexity of the network, only genera with a relative abundance that accounted for the top 50% and appeared in at least 50% of the samples were included.The Spearman's correlation coefficient r ≥ 0.6 was used to determine significance, with a significance level set at P < 0.05 21 .The heatmap analysis of the correlation between the microbial community and environmental factors was generated using Origin software (version 2021b, OriginLab, Northampton, MA, USA).Regression analysis using SPSS software (version 20.0, IBM, Armonk, NY, USA) was employed to examine the correlation between environmental factors and microbial community.

Physicochemical properties of the overlying water
The

Diversity of microbial communities
This article investigates and analyzes diversity indices including ace and Chao reflecting bacterial community richness, Shannon and Simpson community diversity reflecting community diversity, and coverage reflecting sequencing depth (Table 2).The coverage of all samples was greater than 0.9, indicating that the sequencing depth was sufficient to cover most microbial species information and the sample size was sufficient to reflect the diversity differences among different communities.

Microbial community composition
Four seasons, a total of 20 samples were collected at five sampling points in Zhangjiayan Reservoir.Among the 20 samples, a total of 2,142,849 valid sequences were obtained, with an average length of 416.537 bp.The range of sample sequence numbers was 31,381 to 106,886, with an average of 53,575.Among the 2,142,849 sequences, a total of 27,904 ASVs were obtained.A Venn diagram (Fig. 2) was used to compare the ASVs from the four In the overlying water samples taken from the overlying water of Zhangjiayan Reservoir, a total of 66 phyla, 202 classes, 499 orders, 835 families, and 1716 genera from the bacterial domain were detected.At the phylum level, the distribution and relative abundance of the top 15 bacterial groups in the overlying water at each sampling point in Zhangjiayan Reservoir throughout the four seasons are shown in Fig. 3.The ranking of microbial populations with high abundance (average abundance > 1%) is as follows: Proteobacteria (relative abundance ranged from 17.26 to 88.40%, with an average abundance of 40.53%, the same below), Actinobacteriota (5.19-73.68%,23.91%), Bacteroidota (2.26-18.41%,9.06%), Chloroflex (0.06-18.32%, 8.13%), Firmicutes (0.05-10.40%, 5.52%), Acidobacteriota (0.03-8.23%, 3.69%), Desulfobacterota (0.01-6.64%, 2.15%), Verrucomicrobiota (0.01-4.37%, 1.30%), Cyanobacteria (0.04-8.13%, 1.14%).Proteobacteria and Actinobacteria dominate the microbial community in Zhangjiayan Reservoir.In spring and summer, Proteobacteria and Actinobacteria together accounted for more than 76.40% of each sample.
Abundant microbial populations were present in all four sampling seasons, but with significant differences in abundance.According to the results of the Wilcoxon multiple test (Fig. 4), there were significant differences in the mean abundance of bacterial groups with a relative abundance of > 1% among different seasons, including Actinobacteriota, Bacteroidota, Chloroflex, Firmicutes, Acidobacteriota, Desulfobacterota, and Verrucomicrobiota.Actinobacteriota had the highest abundance in summer, followed by spring, and the lowest in autumn and winter.
Bacteroidota had the highest abundance in autumn, followed by winter, and the lowest in spring and summer.
Chloroflex and Firmicutes gradually increased from spring to winter.Acidobacteriota and Desulfobacterota had the highest abundance in autumn, followed by winter, and the lowest in spring and summer.Verrucomicrobiota had the highest abundance in winter, followed by autumn, and the lowest in spring and summer.At the genus level, the distribution and relative abundance of microbial populations at each sampling point in Zhangjiayan Reservoir for seasons are shown in Fig. 5.Among the 1716 genera detected in Zhangjiayan Reservoir, eight genera had a relative abundance > 1%, including hgcI_clade (0.12-46.53%, 19.07%), Acinetobacter (0.07-79.62%, 8.12%), Sphingomonas (0.04-49.33%, 4.78%), CL500-29_marine_group (0.04-22.95%, 3.27%), Brevundimonas (0.01-20.65%, 2.72%), ASV670 at the family level of Anaerolineaceae (0.01-9.95%, 1.67%), Dechloromonas (0.01-7.34%, 1.53%), and ASV245 at the family level of Bacteroidetes_vadinHA17 (0.01-5.47%, 1.12%).At the genus level, there are numerous unidentified bacteria, such as ASV670 at the family level of Anaerolineaceae and ASV245 at the family level of Bacteroidetes_vadinHA17, which are present in relatively high abundance.These unidentified bacteria pose difficulties in analyzing bacterial community compositions.www.nature.com/scientificreports/However, this also indicates that the diversity of microorganisms in the overlying water of Zhangjiayan Reservoir is rich, and the unknown bacterial groups contains are a valuable resource that we need to explore.
From the results of the Wilcoxon test (Fig. 6), there were significant differences in the average abundance of Sphingomonas, CL500-29_marine_group, Dechloromonas, Brevundimonas, Blastomonas, Sediminibacterium, and Polynucleobacter among the four seasons (p < 0.05).The hgcI_clade had the highest average abundance in the summer, followed by spring, and the lowest in autumn and winter.Sphingomonas and Brevundimonas gradually decreased from spring to winter.CL500-29_marine_group had the highest average abundance in the summer, followed by spring, and was less abundant in autumn and winter.Dechloromonas had the highest average abundance in autumn, followed by winter, and was less abundant in spring and summer.

Differences in microbial community structure
The results of evaluating the similarities and differences in microbial community composition across different samples in Zhangjiayan Reservoir based on NMDS analysis using Bray-Curtis are shown in Fig. 7.The figure reveals that the microbial communities in the spring and summer sampling points were mostly concentrated in the second and third quadrants, while those in the autumn and winter sampling points were distributed in the first and fourth quadrants, indicating a significant seasonal difference in microbial community structure.www.nature.com/scientificreports/Furthermore, the microbial community structures of different samples showed high similarity in terms of spatial distribution, indicating that the impact of sampling point types on microbial community structure is limited.
To further identify differing bacterial species between the spring/summer and fall/winter seasons, the LEfSe method was used to calculate the differential bacterial genera in each season, as shown in Fig. 8.The primary microbial community structures that were significantly impacted by differences between the spring/summer and fall/winter seasons included hgcI_clade, Acinetobacter, CL500-29_marine_group, Sphingomonas, CL500-29_marine_group, Brevundimonas, Sediminibacterium, Blastomonas, Dechloromonas, as well as ASV1467 at the family level of Clade_III, ASV670 at the family level of Anaerolineaceae, ASV367 at the family level of Sporichthyaceae, and ASV245 at the family level of Bacteroidetes_vadinHA17.

Microbial co-occurrence network
The microbial correlation network at the genus level consists of 50 nodes and 935 edges (Fig. 11).The network has an average connectivity of 38.163, an average path length of 1.228, and an average clustering coefficient of 0.932.The proportion of positive and negative correlations in the bacterial network is 52.45% and 47.55%, respectively.Based on the topological properties of the co-occurrence network, Sphingomonas, Brevundimonas, and Blastomonas play central roles in the network, with specific parameters shown in Table 3.

Microbial diversity and composition
The dominant bacterial groups in the overlying water of Zhangjiayan Reservoir were Proteobacteria and Actinobacteria.Other scholars have studied the microbial community structure of lakes and reservoirs such as Lake Mar 22 , and Beihai Lake 9 , and also found that Proteobacteria and Actinobacteria were the main phylum in the water samples.The composition of dominant bacterial groups in lakes at different spatial scales was similar.Proteobacteria, Actinobacteria, or the main bacterial community in lake waters.At the dominant genus level, hgcI_clade, CL500-29_marine_group of the phylum Actinobacteria, are likewise frequently found to be the dominant population in river, lake, and reservoir water 23,24 .Acinetobacter and Sphingomonas of the phylum Proteobacteria are also often reported to occur in lake-reservoir water ecosystems.Acinetobacter is widely distributed in water bodies and soils, and it has been suggested that it is a common phosphorus-related genus in www.nature.com/scientificreports/ecosystems 25 .Sphingomonas have the ability to metabolize a variety of carbon sources and are common bacteria that have a certain conversion effect on nitrogen 26 .The water overlying body on the Zhangjiayan Reservoir has a rich microbial diversity.A total of 66 phyla, 202 classes, and 1716 genera in the bacterial domain were detected in the water body on the Zhangjiayan Reservoir.Compared with other lakes or reservoirs (such as Lake Taihu 27 and the Chetelson Reservoir 28 ), the water body on the Zhangjiayan Reservoir exhibits a higher diversity.

Seasonal changes in microorganisms and their response to environmental factors
Microbial communities in the water overlying body of Zhangjiayan Reservoir exhibit different levels of bacterial diversity between the spring/summer and autumn/winter seasons.Guo et al. 29 also found a lower microbial diversity index in the spring/summer seasons compared to the autumn/winter seasons in a study of microbial communities in a drinking water source in Shanghai.In contrast to the results of this study, Zhu et al. 30 found that bacterial diversity was highest in the spring and lowest in the autumn when studying bacterial community structures in Lake Taihu.Sun et al. 31 found that the abundance and diversity of bacteria in the water body of Guanting Reservoir were higher in the summer, while both abundance and diversity decreased in the autumn.The diversity index of microorganisms in the overlying water body of Zhang Jiayan Reservoir in spring and summer is lower than that in autumn and winter, which may be due to the fact that spring and summer are in the rainy season and there is a period of agricultural irrigation drainage, resulting in strong water flow and uniform water quality at each sampling point, with similar bacterial community types between sampling points.In contrast, during the autumn and winter seasons, the poor water circulation capacity and uneven distribution of nutrients such as phosphorus throughout the entire lake result in higher bacterial community diversity between sampling points.This study found that the microbial community structure in Zhangjiayan Reservoir exhibited significant seasonal variations throughout the four seasons, especially with notable differences (p < 0.05) between the microbial community structures during the spring/summer seasons compared to those in the autumn/winter seasons.Similarly, Pascaline Nyirabuhoro et al. 32 analyzed the planktonic bacteria in the surface water of Xinglin Bay reservoir, a subtropical urban area in southeastern China.Through seasonal sampling, the study identified different seasonal succession patterns of planktonic bacterial communities in lakes and reservoirs, with significant seasonal variations.Furthermore, Nyirabuhoro et al. 33 also studied the dynamic of microbial communities in East Town, Tingxi and Shidou Reservoirs in southeastern Fujian Province, China, and found four different bacterial community successions that corresponded well with four different seasons.These works indicate that different environmental variables shape microbial communities at different continuous time scales.
Correlation analysis between microbial communities and environmental factors showed that TP, DTP, SRP, and dissolved oxygen are the main factors influencing the seasonal variations of microbial community structure   11 found that TN, TP, and transparency were the main factors affecting the microbial community in Dongting Lake.Huang et al. 8 discovered that the microbial community in Poyang Lake was greatly influenced by TN and TP.Similar conclusions were drawn about the lakes like Dongting Lake and Poyang Lake, where nutrient concentrations mainly affect the microbial community.The eutrophication of water bodies caused by environmental factors such as phosphorus has shaped the microbial community structure in the overlying water of Zhangjiayan Reservoir.Seasonal variations in the microbial structure composition of the overlying water body at Zhangjiayan are significantly influenced by environmental factors such as phosphorus.The results of the study indicated that the main genera responsible for differences in microbial community structures between spring and summer, and autumn and winter, include hgcI_clade, Acinetobacter, CL500-29_marine_group, Sphingomonas, CL500-29_ marine_group, Brevundimonas, Sediminibacterium, Blastomonas during spring and summer, as well as ASV1467 at the family level of Clade_III and ASV367 at the family level of Sporichthyaceae.These dominant groups are mainly positively correlated with environmental factors, indicating that an increase in nutrient concentration in the water is more conducive to the growth and reproduction of dominant species in the bacterial community.The possible reason is that these dominant groups, such as Hgcl_clade and CL500-29_marine_group, have a close relationship with plankton, especially cyanobacteria, and are more adapted to grow and reproduce in high-nutrient water bodies 34 .

Role of keystone species in microbial communities and eutrophication
Results generated by the network indicate that positive links dominate the interactions among bacterial groups in the overlying water of Zhangjiayan Reservoir.This demonstrates the importance of cooperative interactions among microorganisms in the habitat of Zhangjiayan Reservoir, with most bacteria resisting external environmental disturbances through cooperative relationships with other species.Similarly, He et al. 35 investigated the bacteria and archaea in the South China Sea, showing that the most significant correlation in the DNA-based bacterial and archaeal networks are positive, with proportions of 77.5% and 82.61% respectively.The dominant positive connections in the networks are likely to be explained by cooperation between species, indicating that the survival mode of the microbial community in Zhangjiayan Reservoir is the result of long-term co-evolution and mutualistic symbiosis 36 .
Brevundimonas, Blastomonas, and Sphingomonas as central species in the microbial co-occurrence network of Zhangjiayan Reservoir, have a significant impact on interspecies interactions and community stability.Interactions between microbial communities play a crucial role in maintaining ecosystem function and structural stability.Interactions among bacterial community species to some extent affect the composition of bacterial communities and play an important role in maintaining ecosystem function and structural stability 37 .As central species, Sphingomonas, Brevundimonas, and Blastomonas were also predominant species with relative abundances in the top 20 in the overlying water of Zhangjiayan.We speculate that they play important roles in the seasonal variation of interspecies interactions and community structure.
Brevundimonas, Blastomonas, and Sphingomonas are central species in the microbial co-occurrence network of Zhangjiayan Reservoir, where they play important roles not only in community stability and interspecific interactions, but also in material cycling processes, especially in the phosphorus cycle.Bacteria are important mineralizers of organic phosphorus, as they can mineralize organic phosphorus into orthophosphate, participating in the chemical cycling of phosphorus and maintaining the eutrophication status of lakes 38 .Brevundimonas is a common genus of phosphate-related bacteria in ecosystems 39 .Although Sphingomonas and Blastomonas have few reports related to phosphorus, we speculate that they may play an important role in the transformation of phosphorus forms.Phosphorus is typically the first limiting nutrient for primary productivity in lakes, with the phosphorus available directly to plankton being SRP.Therefore, SRP is an important factor in determining the nutrient status and productivity of lakes 40 .In order to further demonstrate the important impact of Brevundimonas, Blastomonas, and Sphingomonas on eutrophication of the Zhangjiayan Reservoir water body, linear regression analysis was conducted between these bacteria and SRP in overlying water.The results showed that the relative abundance of Brevundimonas, Blastomonas, and Sphingomonas was significantly positively correlated with SRP content (p < 0.01).This indicates that these bacteria may play an important role in the transfer and transformation of phosphorus at the sediment-water interface.Phosphorus in the sediment is decomposed or mineralized by bacteria, releasing SRP into the overlying water, causing eutrophication of the lake.Therefore, these bacterial groups play an important role in the process of phosphorus migration and transformation at the sediment-water interface, which has a significant impact on eutrophication in the Zhangjiayan Reservoir.Tong et al. 41 also similarly found that the microbial communities in Lake Chaohu are conducive to maintaining or further accelerating the eutrophication process in lakes.Therefore, we speculate that Brevundimonas, Blastomonas, and Sphingomonas act as the central nodes in the microbial co-occurrence network of Zhangjiayan Reservoir, significantly impacting the eutrophication of the reservoir water (Fig. 12).

Conclusions
A total of 66 phyla, 202 classes, 499 orders, 835 families, 1716 genera, and 27,904 ASVs of the bacterial domain were detected in the 20 overlying water samples collected from the Zhangjiayan Reservoir.The microbial community composition exhibited a high level of diversity.Actinobacteria and Proteobacteria dominate the microbial community in Zhangjiayan Reservoir.At the genus level, hgcI_clade has the highest abundance, making it the dominant population.The bacterial community structure in spring/summer and autumn/winter shows significant differences under the influence of seasonal environmental factors.Total phosphorus, dissolved total phosphorus, soluble reactive phosphorus, and dissolved oxygen are the main environmental factors that affect the microbial community structure of Zhangjiayan Reservoir.Sphingomonas, Brevundimonas, and Blastomonas, www.nature.com/scientificreports/as central species in the overlying water of Zhangjiayan Reservoir, play important roles not only in community stability and interspecies interactions, but also in material cycling processes, especially in the phosphorus cycle.They may have a significant impact on the eutrophication of Zhangjiayan Reservoir water.

Figure 3 .
Figure 3. Relative abundance and composition of bacterial phyla detected in the overlying water of Zhangjiayan Reservoir, in the four seasons.

Figure 5 .
Figure 5. Relative abundance and composition of bacterial genus detected in the overlying water of Zhangjiayan Reservoir, in the four seasons.

Figure 7 .
Figure 7. NMDS analysis of bacteria phyla and physico-chemical factors in Zhangjiayan Reservoir.

Figure 8 .
Figure8.The major genera that contribute to differences in community structure.

Figure 9 .
Figure 9. RDA analysis of bacterial genus and physicochemical factors in Zhangjiayan Reservoir.

Figure 10 .
Figure 10.Correlation analysis of microbial populations and environmental factors at the genus level.

Figure 11 .
Figure 11.Microbial correlation network diagram Correlation between relative abundance of core bacterial groups and SRP content.The size of the nodes in the figure represents the abundance of species. https://doi.org/10.1038/s41598-024-55702-5

Table 1 .
Physicochemical factors of overlying water in different seasons.Data are means ± stand deviation.In the same row, data with different letter such as a, b, and c indicate significant differences, while data with the same letter indicated insignificant differences at 0.05 level.Data with letters ab were insignificantly different from both data with letter a and data with letter b.Vol.:(0123456789) Scientific Reports | (2024) 14:5513 | https://doi.org/10.1038/s41598-024-55702-5www.nature.com/scientificreports/seasons.There were 27,673 ASVs in total, with 666 unique ASVs in spring, 1439 in summer, 10,891 in autumn, and 12,206 in winter.The order of ASV abundance was spring < summer < autumn < winter.

Table 2 .
Bacterial diversity index in Zhangjiayan Reservoir.SP, SU, AU, WI corresponds to the spring, SU corresponds to the spring, summer, autumn, and winter.This is consistent throughout the text.

Table 3 .
Network co-occurrence topology parameters of the genus Centrolobium in the internet center.