Next Article in Journal
Appropriateness Evaluation of Releasing Area for Four Marine Organisms in Stock Enhancement: A Fatty Acid Approach
Next Article in Special Issue
The Effects of Different Carbon Sources on Water Quality, Growth Performance, Hematology, Immune, and Antioxidant Status in Cultured Nile Tilapia with Biofloc Technology
Previous Article in Journal
Evaluation of the Viral Diversity of Artemia Cysts from Saline Lakes in Kazakhstan Using Viral Metagenomics Analysis
Previous Article in Special Issue
Exploring Biofouling Control by the California Sea Cucumber (Apostichopus californicus) in Integrated Multi-Trophic Aquaculture (IMTA) with Organic Chinook Salmon (Oncorhynchus tshawytscha)
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Fishes
Volume 8
Issue 10
10.3390/fishes8100488
fishes-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Effects of Snail Bellamya purificata Farming at Different Stocking Densities on the Algal and Fungal Communities in Sediment

by
Yiran Hou
1,2,
Mengmeng Zhou
1,2,
Rui Jia
1,2,
Wei Sun
2,
Yanhong Yang
3,
Xiongjian Huang
3,
Bing Li
1,2,* and
Jian Zhu
1,2,*
1
Wuxi Fisheries College, Nanjing Agricultural University, Wuxi 214081, China
2
Key Laboratory of Integrated Rice-Fish Farming Ecology, Ministry of Agriculture and Rural Affairs, Freshwater Fisheries Research Center, Chinese Academy of Fishery Sciences, Wuxi 214081, China
3
Honghe Hani and Yi Autonomous Prefecture Fisheries Management Station, Mengzi 661100, China
*
Authors to whom correspondence should be addressed.
Fishes 2023, 8(10), 488; https://doi.org/10.3390/fishes8100488
Submission received: 7 August 2023 / Revised: 25 September 2023 / Accepted: 27 September 2023 / Published: 28 September 2023
(This article belongs to the Special Issue Integrated Aquaculture and Monoculture of Low-Trophic Species)
Browse Figures
Versions Notes

Abstract

:
The snail Bellamya purificata is recognized as a potential bio-remediation species, and is commonly employed in polyculture to enhance resource utilization efficiency and realize culture environment regulation. In order to enrich the microbiome studies on elucidating the ecological effects of snail B. purificata farming, we assessed the effect of B. purificata farming activities, at varying stocking densities, on the algal and fungal communities in sediment. Four experimental groups were established in our study, each corresponding to a different stocking density: 0, 234.38, 468.75, and 937.5 g/m2, represented as CON, LD, MD, and HD, respectively. High-throughput sequencing based on ITS and 23S ribosomal RNA (rRNA) genes was employed to analyze the variations in algal and fungal communities under B. purificata farming activities at different stocking densities. B. purificata farming activities had no significant effect on the alpha diversities of fungal and algal communities, but significantly altered the compositions of fungal and algal communities in sediments, especially B. purificata farming activity at low stocking density. B. purificata farming activities at low stocking density could significantly increase the relative abundances of fungal genera Paraconiothyrium and Penicillium compared with the CON group. The promoting effect diminished with increasing density. B. purificata farming activities at low or medium stocking density also could enhance the relative abundances of algal genera Microchloropsis, Scenedesmus, and Auxenochlorella. Hence, B. purificata farming activity at low stocking density might be the optimum density to enhance resource utilization efficiency and minimize environmental pollution.
Keywords:
Bellamya purificata cultivation; aquaculture; algal community; fungal community; sediment
Key Contribution: The findings of this study provide valuable insights into the impacts of B. purificata farming activities at different stocking densities on the algal and fungal communities in sediment and contribute a broader understanding for the snail B. purificata’s ecological effects and serve as a valuable theoretical reference for the rational application and development of B. purificata farming.

1. Introduction

Global aquaculture production approached a record high of 122.6 million tons valued at USD281.5 billion in 2020, with China contributing nearly 70% to the total world aquaculture output [1]. The development of aquaculture has contributed to ensuring global food security and meeting the increasing demand of the growing world population for high-quality proteins [1,2]. Along with rapid development, the aquaculture industry is facing several pressing challenges. Aquaculture ecosystems, including ponds, lakes, reservoirs, and rivers, play a vital role in maintaining the quality of aquatic products and ensuring food security supply. However, traditional aquaculture always pursues maximizing yield and benefits through blindly increasing stocking densities and feeding amounts, which in turn lead to a low utilization of resource, large amounts of residual organic waste, and various environment issues in its own and surrounding aquatic ecosystems [3,4,5,6,7,8].
To address this issue for sustainable aquaculture, integrated multi-trophic aquaculture (IMTA) has been studied and developed in recent years, which represents an innovative approach to aquaculture that aims to optimize resource utilization and minimize negative impacts on the environment [9,10,11,12,13]. IMTA refers to the polyculture of multiple species from different trophic levels in a mutually beneficial relationship, where waste products from one species serve as nutrients for others [9]. The snail Bellamya purificata is recognized as a potential bio-remediation species, and commonly employed in polyculture to enhance the resource utilization efficiency and realize the culture environment regulation [14,15,16]. The snail B. purificata is a highly representative freshwater snail and is widely distributed across ponds, lakes, reservoirs, rivers, and other aquatic ecosystems in China, which has a natural preference for inhabiting silt and consuming organic debris and algae in its surrounding environment [17,18]. There have been some studies on the ecological effects of B. purificata in aquaculture or water purification processes [14,19,20]. The snail B. purificata can enhance organic matter degradation within sediment and promote material circulation at the sediment–water interface, in addition to purifying the culture water [14,19,20]. We have attempted to explore the mechanisms or pathways of B. purificata’s ecological effects from a microbiological perspective by determining the bacterial communities in sediments [21]. However, fungi and algae are also important components of microorganisms, although the biomass of bacteria may be ten times that of fungi in the sediment [22].
Fungi and algae play a vital role in material circulation and biogeochemical processes in the aquatic ecosystem. Algae serve as crucial primary producer and food chain driver in aquatic ecosystems [23]. Fungi and algae can provide insight into dynamic variations in ponds, lakes, reservoirs, rivers, and other aquatic ecosystems through the algae’s and fungi’s structural, functional, and physiological features [23,24,25,26]. A previous study has revealed that different farming practices and farming species markedly affect the fungal communities in sediments [27]. Xu [25] first reported the dynamic variations of fungal community and diversity in the integrated rice–crab farming system to better understand and optimize the farming ecosystem. Even so, there is still a lack of studies focusing on the fungal and algal communities In aquaculture ecosystems, particularly the influences of B. purificata farming activities on the fungal and algal communities. We believe that enriching the content of microbiome studies to demonstrate the snail B. purificata’s ecological effects is crucial for the rational application and development of B. purificata farming.
Hence, we performed high-throughput sequencing based on ITS and 23S ribosomal RNA (rRNA) genes in sediment to assess the effects the B. purificata farming activities with different stocking densities on the fungal and algal communities. The findings of this study would lead to a broader understanding of the snail B. purificata’s ecological effects and serve as a valuable theoretical reference for the rational application and development of B. purificata farming.

2. Materials and Methods

2.1. Experiment Design

The experiments were conducted at the Freshwater Fisheries Research Center of the Chinese Academy of Fishery Sciences (120.250479° E, 31.51581° N; Wuxi, China). The experimental snail and sediment were collected from aquaculture ponds located at the Dapu aquaculture facility (119.939129° E, 31.316981° N; Wuxi, China). Before commencing the experiment, a period of 14 days was allotted for the B. purificata snails to acclimatize to the controlled laboratory environment by placing them in a glass tank. To ensure homogeneity and consistency, the sediment used in the experiment underwent drying, grinding, sieving, and mixing according to the pre-processing steps implemented in the previous studies [28,29,30]. Twelve glass tanks (80 × 40 × 45 cm) were employed in the experiment. All the glass tanks were covered with sediment to a depth of 7 cm on the bottom, filled with aerated and filtered tap water, and then left to be precipitated and stabilized for 14 d before the experiment. For the experiment, four separate groups, including one control group and three treatment groups, were established according to four different stocking densities and each group with three replicates. The four different stocking densities were 0, 234.38, 468.75, and 937.50 g/m2, respectively. The corresponding groups were abbreviated as CON, LD, MD, and HD, respectively. After acclimation, healthy snails with an average wet weight of 2.53 ± 0.01 g were collected and randomly distributed between glass tanks. During the experiment period, the commercial feed (Zhejiang Haida Feed Co., Ltd., Shaoxing, China) was utilized as the experimental diet. The snails were fed every day at 4:00 pm, with the amount approximating 2% of their individual body weights. The experimental conditions were maintained at a constant water temperature of 26.5 ± 0.5 °C and a dissolved oxygen (DO) level of about 6.5 mg/L. One-third of the water in each glass tank was changed every two days. The experimental lighting condition was a natural light/dark cycle. The experimental period lasted for 80 days, during which all snails were observed to be in good health with no mortalities recorded.

2.2. Sample Collection

At the end of the experiments, sediment samples were collected using plastic tubes with a diameter of 2 cm from ten randomly chosen sampling points in each glass tank. The sediment samples were taken from the surface sediment layer, which was between 0–1 cm deep. To maintain consistency, all the sediment samples from each identical glass tank were mixed thoroughly. Sediment samples designated for the analysis of fungal and algal communities were promptly stored at −80 °C to preserve their integrity for further analysis.

2.3. PCR Amplification and Sequencing

The DNA of fungi and algae in the sediment samples was extracted using the E.Z.N.A.® soil DNA Kit (Omega Bio-tek, Norcross, GA, USA) according to the manufacturer’s protocol. The quality and concentration of DNA were evaluated using 1.0% agarose gel electrophoresis and a NanoDrop® ND-2000 spectrophotometer (Thermo Scientific Inc., Waltham, MA, USA), and subsequently, the DNA was stored at −80 °C until further use. Specific primers were designed and synthesized to amplify the ITS1-ITS2 and 23S rDNA regions using an ABI GeneAmp® 9700 PCR thermocycler (ABI, CA, USA). The ITS1-ITS2 region was amplified with primer pairs ITS1 (5′–CTTGGTCATTTAGAGTAAGTAA–3′) and ITS2 (5′–GCTGTGTTCATCGATGC–3′). The 23S rDNA region was amplified with two forward primers (A23SrVF1: 5′–AGACARAAAAGACCCTATG–3′ and A23SrVF2: 5′–CARAAAGACCTATTGMAGCT–3′) and two reverse primers (A23SrVR1: 5′–AGATCAGCCTTTATCC–3′ and A23SrVR2: 5′–TCAGCCTGTTATCCTAG–3′) [31].
PCR amplification for ITS1-ITS2 region was carried out three times in 20 µL reaction mixtures consisting of 2 μL of 10× Buffer, 2 μL of 2.5 mM dNTPs, 0.8 μL of forward primer (5 μM), 0.8 μL of reverse primer (5 μM), 0.2 μL of rTaq Polymerase, 0.2 μL of BAS, 10 ng of template DNA, and double-distilled H2O to the final volume. PCR amplification for the 23S rDNA region was carried out three times in 20 µL reaction mixtures including 4 μL of 5× FastPfu Buffer, 2 μL of 2.5 mM dNTPs, 0.8 μL of forward primer (5 μM), 0.8 μL of reverse primer (5 μM), 0.4 μL of FastPfu Polymerase, 0.2 μL of BAS, 10 ng of template DNA, and double-distilled H2O to the final volume. The PCR amplification was performed using the following cycling conditions: initial denaturation at 95 °C for 3 min, followed by 30 cycles of denaturing at 95 °C for 30 s, annealing at 55 °C for 30 s and extension at 72 °C for 45 s, and single extension at 72 °C for 10 min, and end at 10 °C. The PCR product was extracted with a 2% agarose gel. The extracted PCR product was then purified and quantified by the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA) and Quantus™ Fluorometer (Promega, WI, USA) following the manufacturer’s protocol, respectively.
Purified amplicons were pooled in equimolar amounts and subjected to paired-end sequencing on an Illumina MiSeq PE300 platform/NovaSeq PE250 platform (Illumina, CA, USA) at Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China). Raw sequencing reads were deposited into the NCBI Sequence Read Archive (SRA) database (Accession Number: PRJNA993837).

2.4. Data Processing

The raw FASTQ files underwent de-multiplexing through an in-house perl script. Subsequently, raw FASTQ files were subjected to quality filtering using fastp version 0.19.6 and merged using FLASH version 1.2.7 [32,33]. The optimized sequences were clustered into operational taxonomic units (OTUs) using UPARSE 7.1 with a 97% sequence similarity level [34]. The most abundant sequence for each OTU was chosen as a representative sequence. To ensure accuracy, the OTU table was manually filtered, and chloroplast sequences were eliminated from all samples. In order to mitigate the effects of sequencing depth on the alpha and beta diversity measure, the number of ITS DNA and 23S rDNA sequences from each sample were rarefied to 44,639 and 13,331, respectively. The taxonomy of each OTU representative sequence was analyzed using RDP Classifier version 2.2 against the ITS DNA and 23S rDNA database (Unite ITS 8.0 and NT v20210917) with a confidence threshold of 0.7, respectively [31,35].

2.5. Statistical Analysis

Bioinformatic analysis for the sediment samples was conducted by the Majorbio Cloud platform (https://cloud.majorbio.com (accessed on 1 December 2022)). Alpha diversity indices including the observed richness (Sobs), Shannon, Simpson, Chao1, and ACE were calculated using Mothur v1.30.1 [36]. The Sobs, Chao1, and ACE were used for accessing the richness of the fungal and algal communities, while Shannon and Simpson were employed to evaluate the diversity. Higher values of these indices indicate higher richness or diversity. One-way ANOVA followed by the Tukey–Kramer post hoc test was used to confirm differences in the alpha diversity indices of fungal and algal communities within sediment between CON, LD, MD, and HD groups. Subsequently, for the beta diversity, the Bray–Curtis distances among different samples were calculated and the principal coordinate analysis (PCoA) based on Bray–Curtis distances was conducted to reveal the differences in the fungal and algal communities between different groups. The Adonis test accompanying the PCoA analysis was performed to further determine the differences in the fungal and algal communities between different groups. The community bar plot was conducted to demonstrate the relative abundances of the dominate phyla and genera in the fungal and algal communities. The phylum or genus in the fungal and algal communities with a relative abundance greater than 1% would be defined as a dominant phylum or genus. One-way ANOVA followed by the Tukey–Kramer post hoc test was used to confirm differences in the relative abundances of all the phyla and genera within fungal and algal communities. All analyses and related figures were completed using the vegan and ggplot2 packages in R v. 4.0.3 (R Core Team, Vienna, Austria).

3. Results

3.1. Overview of Fungal and Algal Communities in Sediment

In the present study, 2295 distinct OTUs were obtained from the sediment samples through Illumina sequencing technology based on the fungal ITS gene, and subsequentially assigned into 12 phyla and 259 genera. As shown in Figure 1, there were 124 OTUs and 11 genera unique to the CON group, 515 OTUs and 108 genera unique to the LD group, 262 OTUs and 20 genera unique to the MD group, and 336 OTUs and 17 genera unique to the HD group. Moreover, the LD group exhibited 834 OTUs and 143 genera not included in the CON group, which were far more than those exhibited by MD and HD groups.
We also obtained 1391 algae-related OTUs based on the 23S rRNA gene, which were assigned into 44 phyla and 333 genera. As shown in Figure 2, there were 205 OTUs and 36 genera unique to the CON group, 156 OTUs and 21 genera unique to the LD group, 140 OTUs and 19 genera unique to the MD group, and 119 OTUs and 22 genera unique to the HD group. Compared with the CON group, the LD group owned 286 unique OTUs and 53 unique genera, the MD group owned 268 unique OTUs and 48 unique genera, and the HD group owned 248 unique OTUs and 53 unique genera.

3.2. Alpha and Beta Diversities of Fungal Community in Sediment

Alpha diversity indices including Sobs, Shannon, Simpson, ACE, and Chao1 were calculated to evaluate the diversity and richness of the fungal community in sediment. As shown in Figure 3, no significant differences in the Sobs, Shannon, Simpson, ACE, and Chao1 between the CON, LD, MD, and HD groups were observed according to the results of one-way ANOVA followed by the Tukey–Kramer post hoc test (p > 0.05). For the beta diversity, PCoA analysis was conducted to investigate the differences in fungal community based on Bray–Curtis distances. As shown in Figure 4a, PC1 and PC2 explained 25.39% and 18.94% of the total variation in the fungal community within sediment, respectively. The CON, LD, MD, and HD groups were not obviously separated, as they all have overlapping areas. The result of the Adonis test also indicated no significant differences between the CON, LD, MD, and HD groups (p > 0.05).

3.3. Alpha and Beta Diversities of Algal Community in Sediment

According to the results of one-way ANOVA followed by the Tukey–Kramer post hoc test, there were no significant differences in Sobs, Shannon, Simpson, ACE, and Chao1 between the CON, LD, MD, and HD groups as shown in Figure 5 (p > 0.05). For the beta diversity, as shown in Figure 4b, the first two PCs in the PCoA analysis explained 34.17% and 16.41% of the total variation in the algal community within sediment, respectively. The LD group was obviously separated from the other three groups as revealed by the PCoA results. The result of the Adonis test also confirmed the PCoA results and indicated a significant difference between the CON, LD, MD, and HD groups (p < 0.05).

3.4. Composition of Fungal Community in Sediment

There were in total 12 phyla and 259 genera assigned from 2295 distinct OTUs in the sedimentary fungal community in the present study. The dominate phyla and genera (relative abundance > 1%) in the fungal community are shown in Figure 6. Similar with previous studies, most fungi could not be effectively annotated at either the phylum or genus level and has been represented as unclassified_k_Fungi in Figure 6 [27,37]. Excluding the unclassified fungal taxa, the dominate phyla were Ascomycota, Rozellomycota, Basidiomycota, and Chytridiomycota, and the dominate genera were Scutellinia, unclassified_p_Rozellomycota, unclassified_p_Chytridiomycota, and Apiotrichum in the present study.
As shown in Figure 7, the relative abundances of genera Paraconiothyrium and Penicillium were significantly different among the CON, LD, MD, and HD groups (p < 0.05). The relative abundance of Paraconiothyrium in sediment of LD groups was significantly higher than that of CON group (p < 0.05). However, no significant differences in the relative abundance of Paraconiothyrium between the LD, MD, and HD groups were observed (p > 0.05). The relative abundance of Penicillium in the LD groups was significantly higher than in the CON, MD, and HD groups (p < 0.05).

3.5. Composition of Algal Community in Sediment

There were a total of 44 phyla and 333 genera in the algal community in the present study. The dominate phyla and genera (relative abundance > 1%) in the algal community were shown in Figure 8. The dominate phyla ranked in descending order of relative abundance were Verrucomicrobia, unclassified_d_unclassified, Chlorophyta, Cyanobacteria, Ignavibacteriae, Firmicutes, unclassified_d_Bacteria, unclassified_d_Eukaryota, Bacillariophyta, Candidatus_Woesebacteria, unclassified, Proteobacteria, and Oomycota. There were 23 dominate genera. Excluding the unclassified algal genus, the top 5 dominate genera were Pedosphaera, Prosthecobacter, Desmodesmus, Synechococcus, and Opitutus.
Through One-way ANOVA, there were 1 phylum and 6 genera that were significantly different among the CON, LD, MD, and HD groups. As shown in Figure 9, the relative abundance of phylum Streptophyta in the sediment of the LD group was significantly higher than that of MD group (p < 0.05). However, the CON, LD, and HD groups showed similar relative abundances of Streptophyta (p > 0.05). The relative abundance of genus Nibricoccus in the HD group was significantly higher than in the MD group (p < 0.05). The LD and MD groups exhibited significantly higher relative abundances of Scenedesmus compared with the CON group (p < 0.05), but the relative abundance of Scenedesmus in the HD group was similar with that in the CON group (p > 0.05). The relative abundance of Microchloropsis in the LD group was significantly higher than that in the CON, MD, and HD groups (p < 0.05). The relative abundance of Auxenochlorella in the CON group was significantly lower than that in the MD group (p < 0.05), and no significant differences among the LD, MD, and HD groups were observed (p > 0.05). The relative abundance of Choricystis in the LD group showed a significant decreasing trend with increasing stocking density, while the relative abundance of Chthoniobacter showed a significant increasing trend with increasing stocking density and reached a maximum in the MD group (p < 0.05).

4. Discussion

4.1. Fungal Community in Sediment Affect by B. purificata Farming Activities

Fungal community, as well as algal and bacterial communities, play a significant role in the biogeochemical cycle of aquatic ecosystems. Fungi have diverse morphological structures, complex community structures, and strong metabolic capabilities, the physiological and biochemical characteristics of which are affected by the surrounding environment [38]. In the present study, most fungi could not be well annotated, which could be attributed to the relatively limited DNA sequences in the existing fungal databases compared to the total amount of fungal DNA sequences [39,40]. The phyla Ascomycota, Rozellomycota, Basidiomycota, and Chytridiomycota were the dominate phyla in the present study, ranking among the top 5 in relative abundance, respectively. Fan [39] analyzed the fungal community in sediment from tilapia (Oreochromis niloticus) cultural ponds and reported the Basidiomycota, Ascomycetes, and Chytridiomycota as the dominate phyla. Zhang et al. [27] investigated dozens of fish, crab, and crayfish ponds and the dominant fungal phyla observed in these ponds were predominantly Ascomycota, Chytridiomycota, Rozellomycota, and Basidiomycota. Wang et al. [41] and Zhao et al. [42] also revealed the Ascomycetes and Basidiomycota as the dominant phyla in Poyang Lake and Hongze Lake. These similar results indicate that the present indoor simulation experiment could well simulate the real state of the fungal community in the cultural ecosystem.
B. purificata farming activities at different stocking densities had no obvious impacts on the fungal community diversity in the sediment, which was different with the variations in fungal community diversity under tilapia farming activities reported in a previous study [39]. Fan [39] pointed out that the fungal community in the cultural pond was not only sensitive to temperature and climate, but also to the external nutrient inputs. The accumulation of organic waste, including feed residues and faces, in sediment significantly affect the fungal community [39]. However, the snail B. purificata is a typical species which has been proven to play an important role in organic matter degradation in sediment [19]. Snails promote the degradation of organic matter, reduce the accumulation of organic matter in sediment, and enhance material cycling at the sediment–water interface [19]. Hence, the snail B. purificata might have the potential to maintain the consistency in sedimentary organic matter content between different groups by ingestion and promoting the degradation and recycling of organic matter, thereby avoiding the obvious impact derived from organic matter accumulation on the fungal community. Meanwhile, the unaffected fungal community also revealed that bioturbation by the snail B. purificata could not directly alter the fungal community in sediment, although B. purificata bioturbation could significantly change the physico-chemical properties of the sediment [19]. As the relevant physicochemical properties within the sediment were not measured in our study, this inference needs to be explored in further studies.
Although the overall impact of B. purificata farming activities on the fungal community in sediment is not significant according to the results of alpha and beta diversity, B. purificata cultivation affected several specific genera. B. purificata cultivation in the low stocking density (LD) group significantly increased the genera Paraconiothyrium and Penicillium. The genus Paraconiothyrium is widely distributed worldwide with diverse host habitats and has potential applications as a producer of antibiotics [43]. Paraconiothyrium can suppress the activity of harmful fungi such as Sclerotinia sclerotiorum in the soil, thus reducing the infection caused by pathogenic microorganisms [43]. The genus Penicillium, as a saprophytic fungus, is widely distributed in soil and sediment [44,45]. The secondary metabolites of the Penicillium are various compounds with antibacterial and antioxidant activities, which can inhibit the growth of pathogenic bacteria as well as plant-pathogenic fungi [44,45,46,47,48,49,50]. Hence, the significantly increased Paraconiothyrium and Penicillium in the LD group indicated that B. purificata farming activity at a low stocking density may effectively promote the enrichment of Paraconiothyrium and Penicillium in sediment, thereby inhibiting pathogenic microbe activity, improving the performance of cultured aquatic animals, and establishing more sustainable aquatic food production [51]. However, this promoting effect diminished with the increasing density.

4.2. Algal Community in Sediment Affect by B. purificata Farming Activities

Algae play a significant role in autochthonous primary production, providing the basis for littoral secondary production, and act as crucial regulators of nutrient dynamics within aquatic ecosystems [52,53]. Despite their importance, variations in the algal community within the aquaculture ecosystem has received relatively little attention [52]. In the present study, B. purificata farming activities imposed a more pronounced effect on the algal community in sediment relative to the fungal community. In particular, B. purificata farming activity at a low stocking density had a stronger overall effect on the algal community than that at medium and high stocking densities according to the results of the PCoA. As reported in a previous study, phyla such as Chlorophyta and Cyanobacteria, were dominated in the algal community of the East Sea [54]. Similarly, the relative abundance of phyla Chlorophyta and Cyanobacteria were also dominated in the present study, both of which ranked among the top 5 in relative abundance without unclassified taxa.
Similar to the effects of B. purificata farming activities at different stocking densities on the fungal community’s diversity, B. purificata farming activities also had no obvious impacts on the algal community’s diversity in the sediment. However, there has been limited research on the interactions and effects of culture species with algal communities in sediments. The dynamics of algal communities are associated with various physical and chemical factors in the aquaculture environment, among which inorganic nutrients such as nitrogen and phosphorus are fundamental substances required for the growth and reproduction of algae [55,56]. B. purificata can enhance the organic matter degradation within sediment and promote material circulation at the sediment–water interface, which may facilitate the growth of algae [14,19,20]. On the other hand, B. purificata prefers to ingest organic debris and algae in its surroundings [17,18]. Hence, we hypothesized that the non-significant impacts were likely to be attributed to a combined effect of promoting algal growth by bioturbation and inhibiting the algal community by ingestion.
Moreover, in the present study, the algal genera Microchloropsis, Scenedesmus, and Auxenochlorella were significantly enhanced in the LD or MD group relative to those in the CON group. The algal genus Microchloropsis adapts to different nutritional conditions and can effectively utilize nitrate and organic nitrogen [57,58]. The genus Scenedesmus is capable of removing nitrate and phosphate from the surrounding environment [59]. In addition, the genus Auxenochlorella is an early-appearing single-celled eukaryotic green algae, which is an efficient primary producer in ecosystems and capable of removing ammonium [60,61]. The significantly increased relative abundances of Microchloropsis, Scenedesmus, and Auxenochlorella in the LD or MD groups might result from the enhanced degradation of organic matter in sediment and the improved cycling of nutrients at the sediment–water interface caused by B. purificata snail farming. Talib et al. [62] have investigated mitigating eutrophication in lakes through nutritional control and biological manipulation and discovered that the significant increase in the abundance of the harmless genus Scenedesmus is an important phenomenon during the process of reducing eutrophication levels. Meanwhile, the importance of Scenedesmus and Auxenochlorella has been confirmed and they are widely employed in wastewater treatment and environmental regulation [59,60,61]. This revealed that the enhanced degradation of organic matter in sediment and the improved migration of nutrients from sediment to the overlying water caused by B. purificata bioturbation would not induce an increase in the relative abundance of harmful algae. Instead, it increased the relative abundance of harmless algae that have an environmental regulatory significance.

5. Conclusions

B. purificata farming activities had no significant effect on the alpha diversities of fungal and algal communities, but significantly altered the compositions of fungal and algal communities in sediments, especially B. purificata farming activity at a low stocking density. B. purificata farming activities at a low stocking density could significantly increase the relative abundances of fungal genera Paraconiothyrium and Penicillium, thereby inhibiting pathogenic microbe activity and improving the performance of cultured aquatic animals. B. purificata farming activities at low or medium stocking densities could also enhance the relative abundances of harmless algal genera Scenedesmus and Auxenochlorella, which are widely employed in wastewater treatment and environmental regulation. Therefore, the low stocking density (234.38 g/m2) in the present study might be the most optimum density from the perspective of fungal and algal communities. Implementing B. purificata cultivation at a low stocking density might lead to more sustainable aquatic food production. The findings of this study might contribute to better understanding for the ecological effects of snail B. purificata farming and serve as a valuable theoretical reference for the rational application and development of B. purificata farming.

Author Contributions

Y.H.: conceptualization, methodology, formal analysis, data curation, writing—original draft. M.Z.: formal analysis, data curation, writing—original draft. R.J.: visualization, writing—review and editing. W.S.: formal analysis, data curation. Y.Y.: investigation. X.H.: investigation. B.L.: resources, investigation. J.Z.: resources, funding acquisition, supervision. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Central Public-interest Scientific Institution Basal Research Fund, CAFS (grant No. 2022XT0504), the National Natural Science Foundation of China (grant No. 31802302), and the China Agriculture Research System of MOF and MARA (grant No. CARS-45).

Data Availability Statement

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) are PRJNA993837.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Food and Agriculture Organization of the United Nations. The State of World Fisheries and Aquaculture 2022; Food and Agriculture Organization of the United Nations: Rome, Italy, 2022. [Google Scholar]
  2. Costello, C.; Cao, L.; Gelcich, S.; Cisneros-Mata, M.A.; Free, C.M.; Froehlich, H.E.; Golden, C.D.; Ishimura, G.; Maier, J.; Macadam-Somer, I.; et al. The future of food from the sea. Nature 2020, 588, 95–100. [Google Scholar] [CrossRef]
  3. Cao, L.; Wang, W. Wastewater management in freshwater pond aquaculture in China. In Sustainability in Food and Water. Alliance for Global Sustainability Bookseries (Science and Technology: Tools for Sustainable Development); Sumi, A., Fukushi, K., Honda, R.K.H., Eds.; Springer: Dordrecht, The Netherlands, 2010; Volume 18. [Google Scholar]
  4. Deng, L.F.; Jiang, X.L. The application and research progress of bioremediation in pond aquaculture. Oceanol. Limnol. Sin. 2013, 44, 1270–1275. [Google Scholar]
  5. Liu, H.L.; Cao, X.Y.; Song, C.L.; Zhou, Y.Y. Environmental effects of organic matter enrichment and restoration strategy in sediment of aquaculture ponds. J. Hydroecol. 2011, 32, 130–134. [Google Scholar]
  6. Liu, X.G. Study on the Pond Aquaculture Pollution and Ecological Engineering Regulation Techniques; Nanjing Agricultural University: Nanjing, China, 2011. [Google Scholar]
  7. Ji, X.; Lin, X.; Xu, Z.; Lin, Y. Machenism of mariculture self-pollution and its effects on environment. Mar. Environ. Sci. 2000, 19, 66–71. [Google Scholar]
  8. Zhou, H.; Jiang, C.; Zhu, L.; Wang, X.; Hu, X.; Cheng, J.; Xie, M. Impact of pond and fence aquaculture on reservoir environment. Water Sci. Eng. 2011, 4, 92–100. [Google Scholar]
  9. Knowler, D.; Chopin, T.; Martinez-Espineira, R.; Neori, A.; Nobre, A.; Noce, A.; Reid, G. The economics of Integrated Multi-Trophic Aquaculture: Where are we now and where do we need to go? Rev. Aquac. 2020, 12, 1579–1594. [Google Scholar] [CrossRef]
  10. Neori, A.; Chopin, T.; Troell, M.; Buschmann, A.H.; Kraemer, G.P.; Halling, C.; Shpigel, M.; Yarish, C. Integrated aquaculture: Rationale, evolution and state of the art emphasizing seaweed biofiltration in modem mariculture. Aquaculture 2004, 231, 361–391. [Google Scholar] [CrossRef]
  11. Shi, H.H.; Zheng, W.; Zhang, X.L.; Zhu, M.Y.; Ding, D.W. Ecological-economic assessment of monoculture and integrated multi-trophic aquaculture in Sanggou Bay of China. Aquaculture 2013, 410, 172–178. [Google Scholar] [CrossRef]
  12. Troell, M.; Joyce, A.; Chopin, T.; Neori, A.; Buschmann, A.H.; Fang, J.G. Ecological engineering in aquaculture—Potential for integrated multi-trophic aquaculture (IMTA) in marine offshore systems. Aquaculture 2009, 297, 1–9. [Google Scholar] [CrossRef]
  13. Yu, L.Q.J.; Mu, Y.; Zhao, Z.; Lamc, V.W.Y.; Sumaila, U.R. Economic challenges to the generalization of integrated multi-trophic aquaculture: An empirical comparative study on kelp monoculture and kelp-mollusk polyculture in Weihai, China. Aquaculture 2017, 471, 130–139. [Google Scholar] [CrossRef]
  14. Chen, J.; Song, G.; Wang, X.; She, L.; Wu, S.; Wu, M.; Ding, F. The efficiency of water purification by different densities of Bellamya aeruginosa and Bellamya purificata. J. Anhui Agric. Sci. 2012, 40, 11708–11709. [Google Scholar]
  15. Ma, B.; Wang, H.; Jin, W.; Huang, B.; Li, Y.; Li, Z.; Wang, M.; Li, C. Study on the water purification effect of the algae Elodea nuttallii and snail Bellamya purificata. Jiangxi Fish. Sci. Technol. 2022, 2, 3–6. [Google Scholar]
  16. Duan, X.; Xie, C.; Lv, Y.; Zhang, N.; ZHao, F.; Li, R. Feeding habits of Bellamya purificata and its function in water purification system of ecological ditch. Fish. Mod. 2013, 40, 17–21. [Google Scholar]
  17. Cao, Z.; Jiang, X. The influence of environmental factors on Bellamya purificate. J. Shanghai Fish. Univ. 1998, 7, 200–205. [Google Scholar]
  18. Yan, Y.; Jin, W.; Wen, H.; Ma, X.; Xue, T.; Sun, C.; He, Y.; Bing, X. Estimation of genetic parameters for growth traits of Bellamya purificata in 60 days. Freshw. Fish. 2018, 48, 108–111. [Google Scholar]
  19. Hou, Y.R.; Li, B.; Luo, J.W.; Zhang, C.F.; He, J.; Zhu, J. Effect of Bellamya purificata on organic matter degradation in surface sediment as revealed by amino acids. Aquac. Environ. Interact. 2021, 13, 1–12. [Google Scholar] [CrossRef]
  20. Zhao, F.; Xie, C.; Zhang, N.; Lv, Y.; Li, R. Efficiency of water purification and the nitrogen and phosphorous release of the sediment by different densities of Bellamya purificata. J. Hydroecol. 2014, 35, 32–38. [Google Scholar]
  21. Zhou, M.; Hou, Y.; Jia, R.; Li, B.; Zhu, J. Effects of Bellamya purificata Cultivation at Different Stocking Densities on the Dynamics and Assembly of Bacterial Communities in Sediment. Biomolecules 2023, 13, 254. [Google Scholar] [CrossRef]
  22. Liu, L.; Xu, M. Microbial biomass in sediments affects greenhouse gas effluxes in Poyang Lake in China. J. Freshw. Ecol. 2016, 31, 109–121. [Google Scholar] [CrossRef]
  23. Sabater, S.; Buchaca, T.; Cambra, J.; Catalan, J.; Guasch, H.; Ivorra, N.; Muñoz, I.; Navarro, E.; Real, M.; Romaní, A. Structure and function of benthic algal communities in an extremely acid river. J. Phycol. 2003, 39, 481–489. [Google Scholar] [CrossRef]
  24. Marino, J.A.; Denef, V.J.; Dick, G.J.; Duhaime, M.B.; James, T.Y. Fungal community dynamics associated with harmful cyanobacterial blooms in two Great Lakes. J. Great Lakes Res. 2022, 48, 1021–1031. [Google Scholar] [CrossRef]
  25. Xu, S. Diversity of Microbial Communities in Mixed Crab Breeding Rice Plantations; Tianjing University: Tianjing, China, 2021. [Google Scholar]
  26. Zhang, H.; Jia, J.; Chen, S.; Huang, T.; Wang, Y.; Zhao, Z.; Feng, J.; Hao, H.; Li, S.; Ma, X. Dynamics of Bacterial and Fungal Communities during the Outbreak and Decline of an Algal Bloom in a Drinking Water Reservoir. Int. J. Environ. Res. Public Health 2018, 15, 361. [Google Scholar] [CrossRef]
  27. Zhang, Z.; Deng, Q.; Cao, X.; Zhou, Y.; Song, C. Patterns of sediment fungal community dependent on farming practices in aquaculture ponds. Front. Microbiol. 2021, 12, 542064. [Google Scholar] [CrossRef] [PubMed]
  28. Hou, Y.; Li, B.; Feng, G.; Zhang, C.; He, J.; Li, H.; Zhu, J. Responses of bacterial communities and organic matter degradation in surface sediment to Macrobrachium nipponense bioturbation. Sci. Total Environ. 2021, 759, 143534. [Google Scholar] [CrossRef]
  29. Nie, X.; Wu, S.; Wu, F.; Sun, S.; Jiang, C.; Tan, W.; Wan, J. Effects of the bioturbation activity of Tubifex tubifex on nitrogen release from sediments. Acta Sci. Circumstantiae 2011, 31, 107–113. [Google Scholar]
  30. Wang, Y.; Song, J.; Weiwei, J.; Cheng, D.; Xue, J.; Yang, X.; Zhang, B.; Zhang, J. Effect of bioturbation of Chironomid larvae and Limno drilus hoffmeiteri on the release of nitrogen, oxygen and phosphate in the sediments from a river. Acta Sci. Circumstantiae 2015, 35, 2504–2511. [Google Scholar]
  31. Yoon, T.-H.; Kang, H.-E.; Kang, C.-K.; Lee, S.H.; Ahn, D.-H.; Park, H.; Kim, H.-W. Development of a cost-effective metabarcoding strategy for analysis of the marine phytoplankton community. PeerJ 2016, 4, e2115. [Google Scholar] [CrossRef]
  32. Chen, S.F.; Zhou, Y.Q.; Chen, Y.R.; Gu, J. fastp: An ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 2018, 34, 884–890. [Google Scholar] [CrossRef]
  33. Magoc, T.; Salzberg, S.L. FLASH: Fast length adjustment of short reads to improve genome assemblies. Bioinformatics 2011, 27, 2957–2963. [Google Scholar] [CrossRef]
  34. Edgar, R.C. UPARSE: Highly accurate OTU sequences from microbial amplicon reads. Nat. Methods 2013, 10, 996–998. [Google Scholar] [CrossRef]
  35. Nilsson, R.H.; Larsson, K.-H.; Taylor, A.F.S.; Bengtsson-Palme, J.; Jeppesen, T.S.; Schigel, D.; Kennedy, P.; Picard, K.; Gloeckner, F.O.; Tedersoo, L.; et al. The UNITE database for molecular identification of fungi: Handling dark taxa and parallel taxonomic classifications. Nucleic Acids Res. 2019, 47, D259–D264. [Google Scholar] [CrossRef] [PubMed]
  36. Schloss, P.D.; Westcott, S.L.; Ryabin, T.; Hall, J.R.; Hartmann, M.; Hollister, E.B.; Lesniewski, R.A.; Oakley, B.B.; Parks, D.H.; Robinson, C.J.; et al. Introducing mothur: Open-Source, Platform-Independent, Community-Supported Software for Describing and Comparing Microbial Communities. Appl. Environ. Microbiol. 2009, 75, 7537–7541. [Google Scholar] [CrossRef] [PubMed]
  37. Xu, F.; Zhu, L.; Wang, J.; Xue, Y.; Liu, K.; Zhang, F.; Zhang, T. Nonpoint Source Pollution (NPSP) Induces Structural and Functional Variation in the Fungal Community of Sediments in the Jialing River, China. Microb. Ecol. 2023, 85, 1308–1322. [Google Scholar] [CrossRef] [PubMed]
  38. Jiang, G.; Yao, R.; Lin, Y. A survey of study on secondary metabolite s from marine imperfect fungi. J. Microbiol. 2001, 21, 41–44. [Google Scholar]
  39. Fan, L. Microbial Community in Tilapia (Oreochromis niloticus) Cultural Ponds; Nanjing Agricultural University: Nanjing, China, 2015. [Google Scholar]
  40. Zhang, Y.; Guo, L. Progress of fungal DNA barcode. Mycosystema 2012, 31, 809–820. [Google Scholar]
  41. Wang, P.; Xiao, H.; Yuan, R.; Zhao, J.; Yu, X. Fungal community in the estuarine sediment of Poyang Lake. Acta Sci. Circumstantiae 2018, 38, 1949–1956. [Google Scholar]
  42. Zhao, Y.; Zheng, S.; Fang, Z.; Yu, Z. Vertical distribution of fungal communities in Honghu Lake sediment. Mycosystema 2011, 30, 721–728. [Google Scholar]
  43. Wang, J.F.; Shao, S.C.; Liu, C.S.; Song, Z.Q.; Liu, S.S.; Wu, S.H. The genus Paraconiothyrium: Species concepts, biological functions, and secondary metabolites. Crit. Rev. Microbiol. 2021, 47, 781–810. [Google Scholar] [CrossRef]
  44. Du, L.; Li, D.H.; Zhu, T.J.; Cai, S.X.; Wang, F.P.; Xiao, X.; Gu, Q.Q. New alkaloids and diterpenes from a deep ocean sediment derived fungus Penicillium sp. Tetrahedron 2009, 65, 1033–1039. [Google Scholar] [CrossRef]
  45. Xu, T.; Wu, Y.; Jia, Y.; Liu, B.; Ye, B. A Penicillium sp. XGH2321 isolated from the rhizospheric soil of Rhizophora stylosa griff and its antibacterial activity. Microbiol. China 2009, 36, 1682–1687. [Google Scholar]
  46. Corte, A.M.; Liotta, M.; Venturi, C.B.; Calegari, L. Antibacterial activity of Penicillium spp. strains isolated in extreme environments. Polar Biol. 2000, 23, 294–297. [Google Scholar] [CrossRef]
  47. Bringmann, G.; Lang, G.; Gulder, T.A.M.; Tsuruta, H.; Muhlbacher, J.; Maksimenka, K.; Steffens, S.; Schaumann, K.; Stohr, R.; Wiese, J.; et al. The first sorbicillinoid alkaloids, the antileukemic sorbicillactones A and B, from a sponge-derived Penicillium chrysogenum strain. Tetrahedron 2005, 61, 7252–7265. [Google Scholar] [CrossRef]
  48. Petit, K.E.; Mondeguer, F.; Roquebert, M.F.; Biard, J.F.; Pouchus, Y.F. Detection of griseofulvin in a marine strain of Penicillium waksmanii by ion trap mass spectrometry. J. Microbiol. Methods 2004, 58, 59–65. [Google Scholar] [CrossRef] [PubMed]
  49. Silva, M.G.; Aracari, N.; Furtado, J.C.; Pupo, M.T.; Fonseca, M.J.V.; Said, S.; da Silva, A.A.; Bastos, J.K. Antibacterial activity from Penicillium corylophilum Dierckx. Microbiol. Res. 2004, 159, 317–322. [Google Scholar] [CrossRef]
  50. Xu, M.J.; Gessner, G.; Groth, I.; Lange, C.; Christner, A.; Bruhn, T.; Deng, Z.W.; Li, X.; Heinemann, S.H.; Grabley, S.; et al. Shearinines D-K, new indole triterpenoids from an endophytic Penicillium sp (strain HKI0459) with blocking activity on large-conductance calcium-activated potassium channels. Tetrahedron 2007, 63, 435–444. [Google Scholar] [CrossRef]
  51. De Schryver, P.; Vadstein, O. Ecological theory as a foundation to control pathogenic invasion in aquaculture. Isme J. 2014, 8, 2360–2368. [Google Scholar] [CrossRef]
  52. Francoeur, S.N.; Pinowska, A.; Clason, T.A.; Makosky, S.; Lowe, R.L. Unionid bivalve influence on benthic algal community composition in a Michigan Lake. J. Freshw. Ecol. 2002, 17, 489–500. [Google Scholar] [CrossRef]
  53. James, M.R.; Hawes, I.; Weatherhead, M.; Stanger, C.; Gibbs, M. Carbon flow in the littoral food web of an oligotrophic lake. Hydrobiologia 2000, 441, 93–106. [Google Scholar] [CrossRef]
  54. Xu, Z.; Chen, Y.; Meng, X.; Wang, F.; Zheng, Z. Phytoplankton community diversity is influenced by environmental factors in the coastal East China Sea. Eur. J. Phycol. 2016, 51, 107–118. [Google Scholar] [CrossRef]
  55. Liang, Y.; Liu, C.; Tian, C.; Sun, M. Effects of nutrients sources and input mode on the community succession of six marine microalgal species. Trans. Oceanol. Limnol. 2014, 2, 23–30. [Google Scholar] [CrossRef]
  56. Zhao, B.; Hu, W.; Li, C.; Zhou, H.; Zhao, H.; Sun, Y.; Ju, W.; Han, S. Community structure of phytoplankton and benthophyte in Apostichopus japonicus aquaculture ponds and water quality characteristics. J. Guangxi Acad. Sci. 2020, 36, 399–405. [Google Scholar]
  57. Dal Bo, D.; Magneschi, L.; Bedhomme, M.; Billey, E.; Deragon, E.; Storti, M.; Menneteau, M.; Richard, C.; Rak, C.; Lapeyre, M.; et al. Consequences of Mixotrophy on Cell Energetic Metabolism in Microchloropsis gaditana Revealed by Genetic Engineering and Metabolic Approaches. Front. Plant Sci. 2021, 12, 628684. [Google Scholar] [CrossRef]
  58. El-Sheekh, M.M.; Mansour, H.M.; Bedaiwy, M.Y.; El-shenody, R.A. Influence of nutrient supplementation and stress conditions on the biomass and lipid production of Microchloropsis salina for biodiesel production. Biomass Convers. Biorefin. 2022. Available online: https://link.springer.com/article/10.1007/s13399-022-03434-9#article-info (accessed on 1 December 2022). [CrossRef]
  59. Fierro, S.; Sanchez-Saavedra, M.D.P.; Copalcua, C. Nitrate and phosphate removal by chitosan immobilized Scenedesmus. Bioresour. Technol. 2008, 99, 1274–1279. [Google Scholar] [CrossRef] [PubMed]
  60. Wang, Q.K.; Yu, Z.Y.; Wei, D. High-yield production of biomass, protein and pigments by mixotrophic Chlorella pyrenoidosa through the bioconversion of high ammonium in wastewater. Bioresour. Technol. 2020, 313, 123499. [Google Scholar] [CrossRef] [PubMed]
  61. Zhao, X.C.; Tan, X.B.; Yang, L.B.; Liao, J.Y.; Li, X.Y. Cultivation of Chlorella pyrenoidosa in anaerobic wastewater: The coupled effects of ammonium, temperature and pH conditions on lipids compositions. Bioresour. Technol. 2019, 284, 90–97. [Google Scholar] [CrossRef] [PubMed]
  62. Talib, A.; Recknagel, F.; Cao, H.; van der Molen, D.T. Forecasting and explanation of algal dynamics in two shallow lakes by recurrent artificial neural network and hybrid evolutionary algorithm. Math. Comput. Simul. 2008, 78, 424–434. [Google Scholar] [CrossRef]
Fishes 08 00488 g001
Figure 1. Venn diagrams of the fungal communities in CON, LD, MD, and HD groups at operational taxonomic unit (a) and genus (b) levels.
Figure 1. Venn diagrams of the fungal communities in CON, LD, MD, and HD groups at operational taxonomic unit (a) and genus (b) levels.
Fishes 08 00488 g001
Fishes 08 00488 g002
Figure 2. Venn diagrams of the algal communities in CON, LD, MD, and HD groups at operational taxonomic unit (a) and genus (b) levels.
Figure 2. Venn diagrams of the algal communities in CON, LD, MD, and HD groups at operational taxonomic unit (a) and genus (b) levels.
Fishes 08 00488 g002
Fishes 08 00488 g003
Figure 3. Differences in the alpha diversity indices of fungal communities including Sobs (a), Shannon (b), Simpson (c), ACE (d), and Chao1 (e) between CON, LD, MD, and HD groups. Different letters indicated significant differences between different groups.
Figure 3. Differences in the alpha diversity indices of fungal communities including Sobs (a), Shannon (b), Simpson (c), ACE (d), and Chao1 (e) between CON, LD, MD, and HD groups. Different letters indicated significant differences between different groups.
Fishes 08 00488 g003
Fishes 08 00488 g004
Figure 4. Principal coordinate analysis (PCoA) of fungal (a) and algal (b) communities in sediment based on Bray–Curtis distances.
Figure 4. Principal coordinate analysis (PCoA) of fungal (a) and algal (b) communities in sediment based on Bray–Curtis distances.
Fishes 08 00488 g004
Fishes 08 00488 g005
Figure 5. Differences in the alpha diversity indices of algal communities including Sobs (a), Shannon (b), Simpson (c), ACE (d), and Chao1 (e) between CON, LD, MD, and HD groups. Different letters indicated significant differences between different groups.
Figure 5. Differences in the alpha diversity indices of algal communities including Sobs (a), Shannon (b), Simpson (c), ACE (d), and Chao1 (e) between CON, LD, MD, and HD groups. Different letters indicated significant differences between different groups.
Fishes 08 00488 g005
Fishes 08 00488 g006
Figure 6. Fungal community composition at phylum (a) and genus (b) levels within sediment in CON, LD, MD, and HD groups.
Figure 6. Fungal community composition at phylum (a) and genus (b) levels within sediment in CON, LD, MD, and HD groups.
Fishes 08 00488 g006
Fishes 08 00488 g007
Figure 7. The significantly different genera of fungal communities in the sediment between CON, LD, MD, and HD groups, including Paraconiothyrium (a) and Penicillium (b). Different letters indicated significant differences between different groups.
Figure 7. The significantly different genera of fungal communities in the sediment between CON, LD, MD, and HD groups, including Paraconiothyrium (a) and Penicillium (b). Different letters indicated significant differences between different groups.
Fishes 08 00488 g007
Fishes 08 00488 g008
Figure 8. Algal community composition at phylum (a) and genus (b) levels within sediment in CON, LD, MD, and HD groups.
Figure 8. Algal community composition at phylum (a) and genus (b) levels within sediment in CON, LD, MD, and HD groups.
Fishes 08 00488 g008
Fishes 08 00488 g009
Figure 9. The significantly different phylum and genera of algal communities in the sediment between CON, LD, MD, and HD groups, including Streptophyta (a), Nibricoccus (b), Scenedesmus (c), Microchloropsis (d), Auxenochlorella (e), Choricystis (f), and Chthoniobacter (g). Different letters indicated significant differences between different groups.
Figure 9. The significantly different phylum and genera of algal communities in the sediment between CON, LD, MD, and HD groups, including Streptophyta (a), Nibricoccus (b), Scenedesmus (c), Microchloropsis (d), Auxenochlorella (e), Choricystis (f), and Chthoniobacter (g). Different letters indicated significant differences between different groups.
Fishes 08 00488 g009
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Hou, Y.; Zhou, M.; Jia, R.; Sun, W.; Yang, Y.; Huang, X.; Li, B.; Zhu, J. Effects of Snail Bellamya purificata Farming at Different Stocking Densities on the Algal and Fungal Communities in Sediment. Fishes 2023, 8, 488. https://doi.org/10.3390/fishes8100488

AMA Style

Hou Y, Zhou M, Jia R, Sun W, Yang Y, Huang X, Li B, Zhu J. Effects of Snail Bellamya purificata Farming at Different Stocking Densities on the Algal and Fungal Communities in Sediment. Fishes. 2023; 8(10):488. https://doi.org/10.3390/fishes8100488

Chicago/Turabian Style

Hou, Yiran, Mengmeng Zhou, Rui Jia, Wei Sun, Yanhong Yang, Xiongjian Huang, Bing Li, and Jian Zhu. 2023. "Effects of Snail Bellamya purificata Farming at Different Stocking Densities on the Algal and Fungal Communities in Sediment" Fishes 8, no. 10: 488. https://doi.org/10.3390/fishes8100488

Article Metrics

Back to TopTop