Characteristics of Macrobenthic Communities and their Response to Environmental Changes in East Taihu Lake, China

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In this study, we investigated the diversity of macrobenthic communities and analyzed the pivotal environmental factors affecting alterations in the macrobenthic communities of East Taihu Lake. This analysis was augmented by controlled laboratory simulation experiments designed to elucidate and validate the responses of critical indicator species within various functional zones to environmental shifts. This study shows:(1) Bellamya purificata , Limnodrilus and Tubifex were the dominant species on a year-round scale. Water depth was the most important environmental factor affecting the macrobenthic communities;(2) Simulation experiments revealed that the growth condition of Bellamya was significantly worse in the simulated entrance area than in the simulated original enclosure aquaculture and wetland areas. The growth of Radix auricularia was significantly better in the presence of aquatic plants than in the absence of plants, and was more significantly influenced by environmental factors closely related to aquatic plants. The densities of Annelida were significantly higher in the treatment group without plants than that with plants, generally showing the trend of the simulated original enclosure aquaculture area > the simulated entrance area > the simulated wetland area. The trend of diversity was mainly influenced by environmental factors such as turbidity and eutrophication index of the water, which was consistent with the results of the field survey. East Taihu Lake Macrobenthos Aquatic plants Environmental factors Different functional areas Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction Recently, with the advancement of urban industrialization and the increasing level of water resource utilization, aquatic ecosystems have been seriously degraded or destroyed, and biodiversity has been drastically reduced (Vugteveen et al., 2006 ). In order to promote a benign and healthy ecological cycle, the health of water ecosystems, which comprehensively reflects water quality, biological and habitat indicators, has been increasingly emphasized (Grizzetti et al., 2017 ; Hopkins et al., 2011 ; Jayawardana et al., 2017 ; Stromberg et al., 2006 ). The health of aquatic ecosystems comprehensively reflects the physicochemical characteristics, biological integrity and spatial differentiation differences of lakes, rivers, etc., and can effectively reflect the structure and function of ecosystems (Banagar et al., 2018 ). Macrobenthos are a large group of ecosystems in aquatic ecosystems and are an important part of aquatic communities (Mermillod-Blondin and Florian, 2011; Statzner, 2012 ). The characteristics of macrobenthic fauna can reflect the degree of damage to aquatic ecosystems at different scales in a watershed, so macrobenthic fauna has become one of the most important biological indicators of watershed and aquatic ecosystem health (Jani Heino, 2009 ; Sánchez-Montoya et al., 2010 ; Wells et al., 2002 ). In lake ecosystems, macrobenthic fauna has been used as indicators for comprehensive measures such as identification and evaluation of lake ecosystem health compared to other physicochemical hydrological parameters due to the advantages of limited activity, large-scale applicability, wide distribution in lakes and long life cycle (Beyene et al., 2009 ; Stockdale et al., 2010 ). East Taihu Lake is a typical grass-type shallow lake, and it is also the water area with the largest distribution of aquatic plants in Taihu Lake (Wang et al., 2019 ; Zhang et al., 2019 ). East Taihu Lake is not only the source of drinking water in Suzhou and the source of the Taipu River, but also the water source of Jinze Reservoir in the downstream of Shanghai, so it has attracted wide attention from all walks of life. In recent years, the strong anthropogenic impact on East Taihu Lake has intensified, resulting in severe eutrophication and swamping (Zhang et al., 2022 ), and the area of submerged plants in the eastern grass-shaped lake area has decreased from 270 km 2 to 28 km 2 (Wu et al., 2023). In May 2007, a severe algal bloom event occurred in Taihu Lake, leading to a drinking water crisis (Yan et al., 2024 ). In addition, East Taihu Lake, as one of the earliest lakes in China to develop fishery aquaculture, has largely received exogenous pollution, which has improved after the purse seine nets were completely removed in 2019, but the pollutants still have a great impact on the water body. Studies have shown that when the input of exogenous pollutants in lakes exceeds their own purification capacity, most of the pollutants will eventually accumulate in sediments through a series of complex physical, chemical and physicochemical processes. Due to years of exogenous import and pollution deposits, the sediments of Taihu Lake have become a huge potential source of pollution due to high levels of organic matter and nutrients (Chen et al., 2024 ). This study investigates the spatial and temporal distribution pattern, diversity and interaction between benthic fauna and environmental factors in different functional areas of East Taihu Lake, with a view to enriching the database of macrobenthos in East Taihu Lake, understanding the status of macrobenthic fauna in East Taihu Lake, deepening the understanding of the impacts of environment on macrobenthos, and at the same time providing theoretical references for the ecological protection and scientific management of East Taihu Lake. 2. Samples and analysis 2.1. Study site In this study, the sample line method was mainly used to set up sampling points, and the principle of sample line layout was to cover the most representative areas of each functional area of East Taihu Lake as much as possible, and the number of sample lines was decided according to the size of each area. Additional sampling points were set up in the entrance area of East Zizania Tsui, which is an important ecological barrier in the East Taihu Lake, to investigate the macrobenthic fauna and their habitat conditions. A total of eight sample lines were set up in this study. When sampling according to the sample line forward direction of observation and on-site to determine the specific sampling points, each sample line on the selection of three sample points as a representative of the functional characteristics of the sampling point, to ensure that the distance between the sampling point distribution is more uniform, as far as possible to reflect the characteristics of the region as a whole (Fig. 1 .). Sample lines No. 1, No. 2 and No. 3 are located in the entrance area (S1), which is the access point connecting East and West Taihu Lakes, and the area is large, with a large distribution of aquatic plants in the past, which is an important ecological barrier of East Taihu Lake; Sample line No. 4 is located in the aquatic plant conservation area (S2), which is an independent area set up in the process of comprehensive remediation of East Taihu Lake for the purpose of protecting the aquatic plants in the open area, and the decline of aquatic plants has been more severe in recent years; Sample line No. 5 is located in the pelagic area (S3), in the long and narrow central channel of East Taihu Lake, near the backup water source; Sample lines No. 6 and No. 7 are located in the original enclosure aquaculture area (S4), with large aquatic plants, mainly floating-leafed plants, and the habitat condition is in the restoration period after the removal of the enclosure aquaculture activities; Sample line No. 8 is located in the near-shore wetland, which has the most abundant aquatic plants and the best quality of water in the East Taihu Lake. The general habitat conditions of the sampling sites in each functional area are shown in Table 1 . Table 1 Description of habitat conditions in each sampling area. Sample points Functional areas Location Substrate characteristics Aquatic plants Average depth/m S1 Entrance area Entrance to the lake Surface layer yellow, lower layer gray-black, semi-fluid, no odor Few 1.80 S2 Conservation area Aquatic Plant Conservation Areas Surface layer yellow, lower layer gray-black, semi-fluid, slight putrid odor Floating-leaf plants in spring and summer 1.28 S3 Pelagic area Centralized channel, clear water Yellow, semi-fluid, no odor None 1.39 S4 Original enclosure aquaculture area Original enclosure aquaculture area Gray-black, flowing, no odor Dense aquatic plants 1.36 S5 Wetland area nearshore shallow wetland Gray-black, flowing, no odor Dense aquatic plants with many emergent plants 1.14 2.2. Sampling and analysis This study was conducted from October 2020 to November 2021. Water body physicochemical characteristics such as water depth, water temperature, clarity, and nutrients were surveyed monthly in each functional area, and sediment sampling surveys were conducted once in October 2020, April and August 2021 in each functional area. Conduct a macrobenthic sampling survey in December 2020, April, August and November 2021 for each of the four seasons: winter, spring, summer and autumn. 2.2.1. Water samples A water sampler was used to collect 500 mL of water samples at 0.5 m underwater at the sampling point, and three parallel samples were collected at each sampling point, which were transported to the laboratory and put into the refrigerator at 4℃ for refrigeration to complete the determination of the indexes as soon as possible. After collecting water samples, the water quality multi-parameter meter (YSI EXO2, USA) was used to measure water temperature (WT), dissolved oxygen (DO), pH, conductivity (EC) and other indicators at 0.5 m underwater, and the standard transparency disk was used to measure the secchi depth (SD) of the sampling site, and a 3m-ruler was used to measure the water depth of the sampling site. Water samples under refrigerated conditions were transported back to the laboratory for in-house analytical experiments as soon as possible. The water samples were shaken well to determine the turbidity of the water samples using a turbidimeter (1900C, HACH, USA), and then the chlorophyll- a (Chl- a ) concentration of the water samples was determined using a phyto-PAM modulated fluorometer (Heinz Walz GmbH, Effeltrich, Germany). Unfiltered water samples were used to test total nitrogen (TN) and total phosphorus (TP) concentrations in the water column. Another 200 mL or so of raw water was filtered through 0.45 µm cauterized glass fiber filter membrane, and the filtrate was stored in a brown reagent bottle for determining the concentrations of total dissolved nitrogen (TDN), total dissolved phosphorus (TDP), ammonia nitrogen (NH 4+ -N), nitrate nitrogen (NO 3− -N), dissolved orthophosphate (PO 4 3− -P) and dissolved organic carbon (DOC). Nitrogen and phosphorus nutrient salt indicators were analyzed and determined by a double-beam ultraviolet-visible spectrophotometer (UV-2450, Shimadzu, Japan), and DOC was determined by a total organic carbon analyzer (TOC-VCPN, Shimadzu, Japan). The analytical methods for the above indicators were mainly referred to the Specification for Investigation of Eutrophication in Lakes, the National Standard Methods, and the Analytical Methods for Water and Wastewater Monitoring (4th Edition). 2.2.2. Sediment samples Sediment samples were transported back to the laboratory for cold storage. The samples were analyzed by removing aquatic plant debris and stone particles and mixing them well, and the pH and redox potential of the samples were determined using a pH meter. A certain mass of sediment was weighed and placed in aluminum foil, dried at 105℃ for 12 h, weighed again after drying, and the difference was the moisture content (MC) of the sediment; the dried sample was placed in an empty crucible with a known mass after burning at 105℃, and then moved to a muffle furnace to be heated up to 550℃ for 5 h. The sample was cooled down and weighed in a desiccator, and the mass was recorded, and then the difference was calculated to be the amount of loss on ignition (LOI) of the sediment. The soil total phosphorus (STP) of the sediments was determined with reference to the alkali fusion-molybdenum antimony antispectrophotometric method for total soil phosphorus determination (HJ 632–2011), and the soil total nitrogen (STN) was determined by using the method of persulfate digestion(Bronk et al., 2000 ; Sharp et al., 2002 ; Vandenbruwane et al., 2007 ). After pretreatment of sediment samples by grinding and H 2 O 2 digestion, the substrate samples were analyzed using a laser particle sizer to obtain the particle size distribution. 2.2.3. Macrobenthos samples Using a 1/16 m 2 Peterson mud collector, 3 parallel samples were collected from each sample point, 1 ~ 3 mixed counts were collected according to the bottom mud condition, and the cumulative sampling area of each sample point was 1/8 m 2 ~ 1/3 m 2 , and the sampling thickness was generally 10 cm ~ 15 cm. 60-mesh screen was used to shake the mud samples in the lake water, and initially washed off the mud in the mud samples. The residue left in the net was put into a self-sealing plastic bag with 75% ethanol solution for preservation, labeled and brought back to the laboratory for processing. The samples brought back are poured into a 60-mesh screen and the bottom of the screen is placed in a basin of fresh water and gently shaken to wash away the remaining sludge in the samples. After sieving and washing, pick out the debris and plant branches, leaves, etc., and pour the cleaned sample into a white porcelain dish. A little water was added to the white porcelain dish, and all kinds of macrofauna were picked out with round-tip tweezers, pipettes and other tools, with the aid of a body-vision microscope if necessary. Use a brush to sort out smaller and softer animals to avoid damaging the worm. The picked samples were put into wide-mouth specimen bottles and fixed with 75% ethanol solution. Species identification and taxonomic counting of macrobenthos were carried out using a magnifying glass or a stereomicroscope. Species identification was made with reference to Advanced Aquatic Biology, Atlas of Freshwater Micro-organisms and Macrobenthos (2nd Edition), Journal of the Economic Zoology of China (Freshwater Mollusca), and Macrobenthos Monitoring Atlas of the Liaohe River Basin; species identification was made to the lowest possible taxonomic units such as genera or species, and some species identification was made to the family level. Some species were identified to the family level, and the uncertain species were photographed and filed for further identification by experts. The liquid on the surface of the macrobenthos is absorbed by filter paper, and the biomass (wet weight) of the macrobenthos is weighed using a 1/10,000 analytical balance. The results of counting and weighing were converted to density and biomass per unit area. 2.2.4. Indoor experimental design (1)Experimental material Sediments for the experiment was collected from three functional areas (the entrance area, the original enclosure aquaculture area and the wetland area of East Taihu Lake), representing their respective benthic environments. Sediments were collected from the field by a modified 1/16 m 2 Pedersen grab sampler, brought back to the laboratory and rinsed with flowing tap water to separate the benthos therein, and the sediments were air-dried in a ventilated area and then dispensed into glassware and sterilized in an autoclave at 0.12 MPa and 121°C for 15 min to kill the remaining benthos and dormant eggs. The experimental water was pumped from the Taipu River into the laboratory storage tank, and then introduced into the experimental setup after 2 h of resting to ensure that the experimental water was closest to the reality of the East Taihu Lake. The test benthos was selected from Mollusca such as Bellamya purificata and Bellamya patina with low fouling tolerance and Radix auricularia , and Limnodrilus and Chironomus plumosus with high fouling tolerance. The snails were collected from the Pujiangyuan Ecological Wetland of East Taihu Lake, and the Limnodrilus and Chironomus plumosus were purchased from the flower, bird and fish market near the experimental site, which were freshly salvaged on the same day. All the benthic animals were kept in the laboratory for 5 d in tap water that had been aerated for more than 7 d. The water was changed daily, and the snails with good growth condition and uniform size were selected to be put into the experimental setup. The test aquatic plants were selected from the common local species in East Taihu Lake, and the submerged plants included Myriophyllum spicatum , Ceratophyllum demersum L., Vallisneria sp iralis , and Hydrilla uerticillata , while the floating plants were Nymphoides peltatum . The aquatic plants were collected from the natural waters of East Taihu Lake or purchased from the planting bases, and then brought back to the laboratory to select the well-grown plants to be washed and put into the experimental setup. (2)Experimental design The experiment was conducted on an indoor experimental bench from April 28, 2021 to June 28, 2021 for a period of 60 d. A total of nine groups of treatments were set up, numbered in order from 1 to 9. Treatments 1 to 3 were the experimental groups with the sediment in the entrance area as the substrate, treatments 4 to 6 were the original enclosure aquaculture area, and treatments 7 to 9 were the wetland area, and the experimental groups of each functional area were divided into three treatments: no-plant, submerged plant, and submerged×floating plant three treatments, each treatment set three parallel groups. The biomass of the same category of aquatic plants and benthic animals placed in each experimental group was kept as consistent as possible, and the specific settings are shown in Table 2 . Table 2 Experimental setup and initial biomass of benthic animals responding to the environment. Number Functional area Aquatic plants Benthic biomass (g) Treatment Total biomass(g) Bellamya Radix auricularia 1 Entrance area no-plant — 8.93 ± 1.55 0.18 ± 0.05 2 submerged plant 102.58 ± 3.12 9.16 ± 1.18 0.16 ± 0.02 3 submerged×floating plant 120.83 ± 3.50 8.51 ± 1.65 0.16 ± 0.03 4 Original enclosure aquaculture area no-plant — 8.38 ± 1.08 0.15 ± 0.03 5 submerged plant 100.55 ± 2.57 8.05 ± 1.13 0.16 ± 0.03 6 submerged×floating plant 121.60 ± 4.25 9.36 ± 2.65 0.17 ± 0.02 7 Wetland area no-plant — 8.38 ± 1.45 0.15 ± 0.03 8 submerged plant 101.70 ± 2.36 8.30 ± 1.54 0.17 ± 0.04 9 submerged×floating plant 120.57 ± 4.51 8.99 ± 0.97 0.16 ± 0.03 The experimental container was a cylindrical glass cylinder with a radius of 7.5 cm and a height of 40 cm, which was washed and air-dried, then filled with treated substrate and spread to a thickness of about 8 cm − 10 cm, and aquatic plants were planted in the substrate. The treated water was slowly added into the device at a height of about 35 cm to avoid large-scale disturbance of the substrate. The benthic animals were added according to the experimental setup, and an oxygenation and aeration device with a flow rate of 160 L/H was fixed on the upper part of each device, so that a slow water flow was formed on the upper water surface of the device to provide necessary oxygen for the benthic animals to form a micro-ecosystem. The incubation light-dark ratio was 12 h:12 h, and the temperature was (25 ± 1)℃. The Chl- a concentration of the water body was measured periodically during the experiment, while water was replenished periodically to the original liquid level height to supplement evaporation losses. Turbidity, TN, TP, NO 3− -N, PO 4 3− -P concentrations in the water column and TN and TP contents in the sediments were measured at the beginning and end of the experiment, respectively. At the end of the experiment, the survival rate, density and biomass of each type of macrobenthos were counted. 2.3 Data processing 2.3.1. Dominant species Dominant species are the dominant populations of organisms in a community that have a controlling influence on the community. In this study, Index of Relative Importance ( IRI ) was chosen to determine the dominant species. The calculation method is according to Eq. ( 1 ): $$\:IRI=\left(W+N\right)\times\:F$$ 1 where, \(\:W\) is the percentage of the biomass of a species to the total biomass; \(\:N\) is the percentage of the density of a species to the total density; and \(\:F\) is the percentage of the number of sample points in which a species occurs to the total number of sample points. IRI > 1000 is considered as the dominant species, IRI between 100 and 1000 is the important species, IRI between 10 and 100 is the common species, and IRI < 10 is the rare species (Pianka, 1971 ). 2.3.2. Biodiversity index In this study, three diversity indices, Shannon-Wiener diversity index ( H' ), Margalef richness index ( D ) and Pielou evenness index ( J ), were used to calculate and assess the level of diversity in macrobenthic communities. The calculations were shown in Eqs. (2), (3) and (4), respectively. \(\:{H}^{{\prime\:}}=-\sum\:_{i=1}^{S}{P}_{i}\text{ln}{P}_{i}\) (2) \(\:D=\left(S-1\right)\text{ln}N\) (3) \(\:J=-\frac{\sum\:_{i=1}^{S}{P}_{i}\text{ln}{P}_{i}}{\text{ln}S}\) (4) where \(\:S\) is the total number of species, \(\:{P}_{i}\) is the ratio of the number of individuals of species \(\:i\) to the total number of samples, and \(\:N\) is the total number of all species in the collected samples. 2.3.3. Analysis of variance Independent samples t-test or One-way ANOVA were used to compare the differences in various variables, such as environmental indicators, macrobenthic densities and biomass, between seasons and sampling sites. 2.3.4. Correlation analysis Pearson correlation coefficients were used to analyze the correlations between macrobenthos density and biomass and environmental factors in the water column and sediments in East Taihu Lake; the top 20 macrobenthos densities and environmental factors ranked in the IRI index were ranked and analyzed using Canoco 4.5, and the raw values of environmental factors and macrobenthos densities, except for pH, were transformed by lg (x + 1). To determine whether the data were unimodal or linearly distributed, the transformed data were subjected to descending trend correspondence analysis (DCA), and if the maximum gradient length of the DCA results was greater than 4, canonical correspondence analysis (CCA) was selected; conversely, redundancy analysis (RDA) was selected; SPSS 22.0 was used for data processing and other statistical analyses in this study, and Origin 2019 was used for plotting. 3. Results and discussion 3.1. Community structure of macrobenthos in East Taihu Lake During the four seasons between January 2021 and November 2021, a total of 266 macrobenthic organisms was collected, consisting of three major groups: Mollusca, Annelida and arthropods, were collected from five sampling areas in the main functional area of East Taihu Lake. In terms of the number of organisms, there were 58 Mollusca, accounting for 21.80%; 164 Annelida, accounting for 61.65%; and 44 Arthropoda, accounting for 16.54%. After further observation and identification, there were 28 species of macrobenthos, belonging to 3 phyla, 6 classes, 13 orders, 18 families and 25 genera. There were 10 species of Mollusca in the three phyla, accounting for 35.71%, including 7 species of Gastropoda and 3 species of Lamellibranchia ; 7 species of Annelida, accounting for 25.00%, including 6 species of Oligochaeta and 1 species of Polychaeta; 11 species of Arthropoda, accounting for 39.27%, including 1 species of Chironomus plumosus , 3 species of Crustacea, and 7 species of other small number of aquatic insects (Fig. 2 .). The dominant macrobenthic species in East Taihu Lake also varied between seasons and across functional areas (Table 3 and Table 4 ). Seasonally, Bellamya purificata and Limnodrilus were dominant species throughout the year. Among them, Limnodrilus had the highest IRI index values in spring, summer and winter, and Bellamya purificata had the highest IRI index values in autumn. In addition to this, Bellamya aeruginosa was also more dominant in the spring; Tubifex was more dominant in the summer and autumn; and Chironomus plumosus was more dominant in the autumn, and thus autumn had the highest number of dominant species. Table 3 Seasonal changes of dominant macrobenthic species in East Taihu Lake. Species IRI Spring Summer Autumn Winter Bellamya purificata 2830.05 2949.69 2381.91 2732.04 Bellamya aeruginosa 1157.55 — — — Limnodrilus 4155.21 2967.02 1265.87 3065.19 Tubifex — 2194.08 1985.47 — Chironomus plumosus — — 1103.22 — Bold font indicates the maximum IRI value for the season. Spatially, Limnodrilus was the only dominant species in all functional areas of East Taihu Lake and had the highest IRI indexes in three areas: the conservation area, the pelagic area and the original enclosure aquaculture area. Bellamya purificata was the most dominant species in the wetland area, and was also a relatively important species in the original enclosure aquaculture area. Each functional area had 2 ~ 3 kinds of macrobenthic species with IRI index values of 1000 or more, and only the wetland area was dominated by Mollusca, while the entrance area, the conservation area and original enclosure aquaculture area were dominated by Annelida (Oligochaeta, Polychaeta) and Chironomus plumosus . Table 4 Spatial variation of dominant macrobenthic species in East Taihu Lake. Species IRI S1 S2 S3 S4 S5 Bellamya purificata 2071.38 2262.94 — — 9709.04 Bellamya aeruginosa — — — — 2314.05 Limnodrilus 1217.68 4762.96 3008.53 4969.43 1349.56 Tubifex — 2134.77 — 3642.47 — Chironomus plumosus 1628.25 — — 1224.06 — Polymoe 3467.21 — — — — Corbicula fluminea — — 2602.66 — — Bold font indicates the maximum IRI value for the area. 3.2. Relationship between macrobenthic community structure and environmental factors 3.2.1. Impact of water environmental factors Changes in macrobenthic community structure are affected by various environmental factors in the habitat and human activities, and the influencing factors and mechanisms are very complex. The heterogeneity of habitats in different habitats and seasons leads to different environmental influencing factors and feedback mechanisms for macrobenthos. The distribution of the correlation between the physical and chemical factors of the water environment and the density and biomass of macrobenthic species on the annual scale of East Taihu Lake during the study period is shown in Fig. 3 . The correlations between macrobenthos density, biomass and environmental factors were basically consistent, but there were some differences in the strength of significance. The correlations between species of similar taxonomic units (e.g., Bellamya purificata and Bellamya aeruginosa , Limnodrilus and Tubifex , etc.) and the various water environmental factors were somewhat similar, showing similar environmental impact effects. The aquatic environmental factor that reached the most significant correlation with inter-species correlations at the year-round time scale was water depth, indicating that water depth is one of the most important environmental influences on macrobenthic communities in East Taihu Lake. This result is consistent with previous studies (Chatzinikolaou et al., 2018 ; Li et al., 2017 ; Zhang et al., 2023 ). For shallow lakes with large perennial water level fluctuations, water depth will mostly be the primary environmental influence factor for differences in the distribution of macrobenthic communities, and underwater transmitted light decreases with increasing depth of the water column, with a consequent decrease in macrobenthic densities and biomass, which is especially more pronounced for the Mollusca(e.g., Gastropoda and Lamellibranchia) (Cai et al., 2017 ). Deep water is more likely to be occupied by phytoplankton, which may sometimes even form blooms due to the input of nutrients and other pollutants, and the low-oxygen environment is more favorable for the survival of some macroinvertebrates (e.g., Oligochaetes, Chlamydia, etc.) with high stress tolerance (Li et al., 2017 ). A similar pattern was presented in this study, in which the density and biomass of Bellamya aeruginosa and Radix Auricularia were significantly negatively correlated with water depth ( p < 0.05), and other Mollusca species also had a negative correlation with water depth; whereas the density and biomass of the Oligochaeta, as well as that of Chironomus plumosus , showed a significant or highly significant positive correlation with water depth. The relationship between water depth and macrobenthic species is significant, not only caused by water depth alone, but also due to how water depth varies between different seasons and functional areas, which leads to the regular changes of water transparency, aquatic plant growth and coverage, hydrodynamic conditions and dissolved oxygen. The distribution of macrobenthic animals is affected by various factors at the same time, mostly associated with water depth, and macrobenthos is a thermotropic animal preferring different optimal growth temperatures, and its growth, reproduction and metabolism are largely affected by water temperature, which is closely related to water depth (Arscott et al., 2003 ; Dudgeon, 1985 ; Mantelatto et al., 2022 ). In addition, the concentration of Chl- a and nitrogen and phosphorus of water are also important environmental factors affecting macrobenthos in East Taihu Lake. More information needs to be analyzed in relation to the correlation between macrobenthos and water environmental factors in different seasons. 3.2.2. RDA analysis of macrobenthos and environmental factors Using the descending trend correspondence analysis (DCA) between the main environmental factors that have a greater impact on macrobenthos in the correlation analysis and the macrobenthic species ranked in the top 20 of IRI values, the gradient lengths of the four ranking axes were analyzed to be 3.02, 2.90, 1.88, and 1.55, which were all less than 4, and the maximum gradient length was close to 3. Therefore, the choice of redundancy analysis (RDA) to further reveal the effect of environment on macrobenthic communities. The ordination plot between water environmental factors and each species and sample site is shown in Fig. 4 ., the length of the arrows represents the magnitude of the influence of environmental and species factors on the ordination, thus species located at the skewed edges of the ordination plot will respond to specific environmental factors (Shen et al., 2024). Species with large positive values in the first axis include mollusc species such as Bellamya purificata , Bellamya aeruginosa , Cipangopaludina ussuriensis , Bellamya quadrata , and Unio douglasiae , which are distributed in the functional areas with higher water transparency, shallower water depths, lower concentrations of TP, and lower levels of TSS, and the angles between the arrows of the above species are small, which indicates that the relationships between them and the water environmental factors have high similarity, which is in line with the results of the correlation heatmap analysis. In fact, all these species belong to the low and medium pollution-tolerant taxa, which indicates a better water quality environment, and the wetland sampling sites in each season are located in the positive direction of the first axis in the sample point ranking map, which indicates that Mollusca occur most frequently in this functional area and have the best water quality. The genera of Limnodrilus and Tubifex were located in the second axis with the largest negative value, and the genera of Aulophorus tonkinensis belonging to the same Oligochaeta were also located in the same position, and they were all distributed in the functional areas with high Chl- a concentration, and at the same time, in the same area in the sample sorting map were the conservation area and the original enclosure aquaculture area, which was in line with the high Chl- a concentration in the water bodies of these two functional areas. Chironomus plumosus was located in similar positions and distributed in waters with deeper water depths and high concentrations of TP and TN, same as Pristina longiseta and Aeolosoma hemprichii , which belong to the Oligochaeta. These species with high fouling tolerance values prefer to live in low oxygen environments of deeper water depth, which can be indicative of a more severe eutrophication status of the water body (Gao et al., 2023 ). Organic matter provides an important food source and shelter for macrobenthos, so the organic matter content of habitats is crucial for macrobenthic community structure (Shen et al., 2024). It has been shown that the removal of organic matter will lead to a significant decrease in the abundance of Chironomidae Diptera in freshwater ecosystems, such as rivers, and a significant change in the community structure (Entrekin et al., 2007 ). However, higher organic matter content will be accompanied by a decrease in habitat pH, water transparency and dissolved oxygen, and an inhibitory effect on the growth of macrobenthos (Luoto et al., 2016 ). Cai also found that in Zhushan Bay, Meiliang Bay and estuarine areas of Taihu Lake, which are heavily polluted and highly eutrophic, the substrate is silt-clay and high in organic matter, and Limnodrilus hoffmeisteri is the main dominant macrobenthic fauna (Cai et al., 2010 ). Alphabetical labels: Bellamya purificata Be.p , Limnodrilus Li , Tubifex Tu , Chironomus plumosus Ch , Bellamya aeruginosa Be.a , Polymoe Po , Unio douglasiae Un , Pristina longiseta Pr , E.modestus E.mo , Cipangopaludina ussuriensis Ci.u , Cipangopaludina chinensis Ci.c , Corbicula fluminea Co , Bellamya quadrata Be.q , Aulophorus tonkinensis Au , Radix auricularia Ra , Cipangopaludina ampulliformis Ci.a , N.denticulata N.de , Aeolosoma hemprichii Ae , Macrobrachium Mac , Cuneopsis heudei Cu. 3.3. Response of macrobenthos in East Taihu Lake to changes in different habitats In order to further analyze and verify the effects of various environmental factors on macrobenthos in East Taihu Lake, the sediments of the three most representative functional areas of the entrance area, the original enclosure aquaculture area and the wetland area were selected as the substrate environment, and the raw water of East Taihu Lake as the aqueous environment. Three groups of parallel experiments were set up in each functional area to form a micro-ecosystem with no aquatic plants, submerged plants, submerged plants and floating leaf plants coexisting, to investigate the response of macrobenthos to the environmental changes in different habitats in each experimental group. The macrobenthos included Bellamya ( Bellamya purificata , Bellamya aeruginosa ) and Radix auricularia in Mollusca, Limnodrilus , Tubifex , and other detected annelid species in Annelida, as well as Chironomus plumosus in Arthropoda. These macrobenthic species in the three phyla were selected as the relatively dominant and representative species found in the field sampling of East Taihu Lake, with Bellamya purificata being the first species in the relative importance index. The responses of these macrobenthos to environmental changes in different functional areas can effectively verify the correlation between macrobenthos and environmental factors in East Taihu Lake. 3.3.1 Physical and chemical indicators of water bodies and sediments The changes of Chl- a concentration in the system of each experimental group during the 15th, 30th, 45th and 60th time periods of the experimental period are shown in Fig. 5 . Since the experimental light intensity was not as sufficient as under natural conditions, the Chl- a concentration in the system of each experimental group was not high, and only diatoms grew, but still showed a certain pattern. Submerged plants can inhibit algae by secreting chemosensory chemicals and also indirectly by reducing sediment resuspension and increasing water transparency (Liu et al., 2024 ). The overall Chl- a concentration within the three experimental environmental groups in the entrance area, the original enclosure aquaculture area and the wetland area all showed that the no-plant group < submerged plant group < submerged × floating plant group. In the early stage of the experiment (15 d), the Chl- a concentrations in the two treatment groups with aquatic plant growth were similar and significantly higher than those in the no-plant group. In the middle and late stages (30 d ~ 60 d) under constant water replenishment, the Chl- a concentrations of the three functional areas without aquatic plants treatment groups were all in an increasing trend, but the increase was not large, and the concentrations were still lower than 10 ug/L; the Chl- a concentrations of the three submerged plant treatment groups were significantly lower than those in the early stage ( p < 0.05), and stabilized in the range of 8.30 ug/L − 9.82 ug/L; the Chl- a concentrations of the three submerged × floating plant treatment groups Chl- a concentrations had a decreasing trend but was not obvious, so the Chl- a concentration of the submerged plant treatment group was more similar to that of the no-plant group in the late stage of the experiment and had a greater difference from that of the submerged × floating plant group. Chl- a concentration can characterize phytoplankton biomass to a certain extent and is also an important component of organic suspended particulate matter in the water column. Aquatic plants can directly absorb nutrients from the lake, and also regulate the microbial community through exudation from their roots and further influence nitrification (Yin et al., 2020 ), thus the experimental group with aquatic plant growth had less total suspended particulate matter than the group without plants, and the water body had lower turbidity (Table 5 ) and higher transparency. Aquatic plants can inhibit the growth of algae to a certain extent, and under natural conditions, when aquatic plants decline, it will lead to an increase in the Chl- a concentration in the water body; but on the other hand, having aquatic plant growth will increase the percentage of organic suspended particulate matter in the water body, which is greater than that of inorganic particulate matter. In this experiment, the second process was more obvious due to the insufficient light conditions, which were not favorable for algal bloom growth. Meanwhile, scrapers have an inhibitory effect on algae, which can effectively remove suspended particles from the water body and improve water transparency (Waajen et al., 2016 ; Y. Zhang et al., 2023 ). Overall, the Chl- a concentration was similar between the same aquatic plant treatment groups in the three functional areas in this experiment, while there was a significant difference in Chl- a concentration between the different aquatic plant treatment groups, suggesting that there is a close relationship between Chl- a concentration and aquatic plants. Table 5 Physicochemical indicators of water and sediment in the final state for each experimental group. Experimental group Water index Sediments NTU TN (mg/L) NO 3− -N (mg/L) TP (mg/L) PO 4 3− -P (mg/L) STN (mg/kg) STP (mg/kg) S1་no-plant 9.64 7.37 7.31 0.06 0.03 195.07 75.18 S1་submerged plant 1.89 6.79 5.75 0.29 0.25 351.38 69.92 S1་submerged×floating plant 1.51 4.26 3.71 0.34 0.28 361.63 73.73 S4་no-plant 18.49 9.99 9.90 0.04 0.03 1562.80 136.12 S4་submerged plant 5.23 9.11 7.43 0.03 0.02 1529.64 120.74 S4་submerged×floating plant 3.22 7.39 5.26 0.24 0.13 1341.94 98.14 S5་no-plant 8.25 9.37 8.28 0.03 0.00 249.82 49.10 S5་submerged plant 2.70 7.65 7.40 0.51 0.14 512.47 51.49 S5་submerged×floating plant 1.97 5.65 5.18 0.61 0.30 443.83 50.74 TN in the water column of the experimental system was mainly in the form of nitrate nitrogen (NO 3− -N). Nitrogen concentrations in the water column were similar overall in the original enclosure aquaculture area and the wetland area, while the entrance area was slightly lower overall than the original enclosure aquaculture area and the wetland area. Within the experimental groups of each functional area, the concentrations of TN and nitrate nitrogen in the three treatment groups of no plant, submerged plant, and submerged × floating plant decreased sequentially, indicating that the uptake of nutrients by aquatic plants in the experimental system mainly manifested itself as the uptake of nitrogen in the water column. While TP and PO 4 3− -P concentrations in each functional area showed that the group with plants was significantly higher than the group without plants, which may be the reason that Chl- a concentration was higher in the group with plants, and higher phosphorus concentration was more suitable for the growth of algae. Unlike the large differences in water body nitrogen and phosphorus indicators in different aquatic plant treatment groups, sediment TN and TP contents were significantly different among the three functional zones, with sediment nitrogen and phosphorus contents in the original enclosure aquaculture area significantly higher than those in the entrance area and the wetland area ( p < 0.05), and higher in the wetland area than those in the entrance area, and the sediment nitrogen and phosphorus contents were basically similar between the treatment groups with and without aquatic plants in all the functional areas with no significant differences. The nitrogen and phosphorus indices of the water body in the final state of the experiment were higher than that of the raw water of East Taihu Lake used in the experiment at the initial time, while the sediment TN and TP were on the contrary, with the concentration of the sediment nitrogen and phosphorus in the final state lower than that measured at the initial time. The reason for this may be due to the fact that the water movement caused by the oxygenation device promoted the release of nitrogen and phosphorus from the sediments in the relatively small-scale closed experimental environment. While in natural lakes, the input of organic matter occurs continuously due to phytoplankton growth (Zhang et al., 2024 ). 3.3.2. Density change of macrobenthos and correlation analysis of environmental factors (1) Changes in the density of various macrobenthic fauna The densities of Bellamya , Radix auricularia , Annelida (mainly composed of Limnodrilus and Tubifex ) and Chironomus plumosus observed and counted in the final state of the experiment are shown in Fig. 6 . The densities of Bellamya , except for the submerged × floating plant group in the entrance area where the densities were significantly lower due to higher mortality rates, varied between 188.64 ind/m 2 and 264.10 ind/m 2 in each group. The biomass of Bellamya was absolutely dominant among the benthos of all experimental groups, while the density was only maximum in the submerged × floating plant group in the entrance and wetland areas, and there was no absolute dominance. The density of Radix auricularia was higher in the group with aquatic plants than in the group without, and its density peaked (877.7 ind/m 2 ) in the group of the submerged × floating plant coexisting in the original enclosure aquaculture area. Its density peaked at 877.19 ind/m 2 in the submerged × floating plant group in the wetland area and was the second highest (377.29 ind/m 2 ). The density distribution of Chironomus plumosus and Radix auricularia showed some similarity, and Chironomus plumosus were observed only in the submerged × floating plant group in the entrance area and the original enclosure aquaculture area, which also showed some dependence on aquatic plants. The density of the Annelida in each experimental group was original enclosure aquaculture area>entrance area>wetland area, and the density of the original enclosure aquaculture area without plant treatment group was the highest, which was 1490.28 ind/m 2 . The density of the Annelida in each experimental group in each functional area was significantly higher than that of the treatment group with plant growth, and the root growth of aquatic plants damaged the anaerobic environment at the sediment-water interface and within the sediments, increasing the dissolved oxygen concentration in the water and improving the water transparency. The root growth of aquatic plants destroyed the anaerobic environment at the sediment-water interface and inside the sediments, increased the concentration of dissolved oxygen in the water, and at the same time improved the transparency of the water body and the water quality (Li et al., 2024 ; Yan et al., 2022 ; Zhang et al., 2014 ). The higher density of Annelida, which are fouling-tolerant species adapted to polluted water and anaerobic environments, was consistent with the results of the benthic field collection and analysis, and further verified their environmental adaptation characteristics. The difference in density of the four benthic species in the no-plant group in the entrance area was distinct, and the density of Annelida was dominant, only the difference in density of the four benthic species in the submerged plan group was reduced, and the difference in density in the submerged × floating plant group was the smallest, due to the diversity of aquatic plants, which provided a complex habitat for the survival of benthic animals, and the benthic animals detected in a single habitat were more diverse, and the density distribution was more uniform. In the original enclosure aquaculture area, the density of benthos varied greatly among the three treatment groups, with Annelida being the dominant species in the no-plant and submerged plant groups, and Radix auricularia dominating in the submerged × floating plant group. On the contrary, there was little difference in the density of each benthic fauna in all three treatment groups in the wetland area, and none of them had a clear density-dominant species. (2) Correlation analysis of environmental factors The correlation heatmaps of the pre- and post-experimental rates of change in biomass, final survival and final density of Bellamya and Radix auricularia , and the final density of Annelida with the measured environmental factors are shown in Fig. 7 . The three indices, rate of change in biomass, survival and final density of Radix auricularia , were all significantly and positively correlated ( p < 0.05) with the Chl- a concentration, while they were negatively or significantly negatively correlated with the TN and NO 3− -N concentrations which relate to pollution(Xie et al., 2016 ). The Chl- a concentration in the water column was closely related to the presence or absence of aquatic plants, and there was no significant difference in the Chl- a concentration among the same aquatic plant treatment groups in the three functional areas in this experiment, while there was a significant difference in the Chl- a concentration among the different aquatic plant treatment groups, which were as follows: no-plant group<submerged plant group<submerged × floating plant group. The growth condition of Radix auricularia was better in the treatment group with aquatic plant growth than in the no-plant group, especially in the original enclosure aquaculture and wetland areas where the biomass and density of the submerged × floating plant treatment group increased dramatically, and the survival rate was also the highest, thus showing a significant positive correlation with the Chl- a concentration in the water column. The relationship between aqutic plant and Radix auricularia with herbivory also play an important role on this phenomenon(Lv et al., 2019 ). The water column TN and NO 3− -N concentrations were also closely related to the presence or absence of aquatic plant distribution, and the TN and NO 3− -N concentrations in the treatment group with aquatic plants were reduced due to plant uptake, and thus negatively correlated with the growth status of Radix auricularia . Bellamya grew better in most of the experimental groups, and densities also did not change significantly in any of the experimental groups, except for the submerged × floating plant group in the entrance area, so the correlations between the three indicators and the environmental factors were not significant, in line with its high environmental adaptability. The density of Annelida was significantly correlated with both the water and sediment environments, and was significantly higher in the no-plant group than in the planted group. The Chl- a concentration in the water body was low in the no-plant group, and the turbidity was significantly higher than that in the planted group, so the density of Annelida was significantly positively correlated with turbidity ( p < 0.05) and negatively correlated with Chl- a . The nitrogen concentration in the water body was significantly lower in the planted group than that in the no-plant group, while the concentration of TP and PO 4 3− -P were higher in the planted group, thus, the density of Annelida was positively correlated with the concentration of nitrogen, and negatively correlated with the concentration of TP and PO 4 3− -P. PO 4 3− -P concentration was significantly negatively correlated. Sediment nitrogen and phosphorus content also affected the density of Annelida significantly. The sediment nitrogen and phosphorus content in the original enclosure aquaculture area was significantly higher than that in the entrance and wetland areas, and the density of Annelida was also the highest in the original enclosure aquaculture area, and at the same time, the substrate particle size in the original enclosure aquaculture area was relatively small, so the density of Annelida in the original enclosure aquaculture area was the highest in the group of the treatment without plants. 4. Conclusion (1) In the East Taihu Lake basin, Bellamya purificata , Limnodrilus , and Tubifex were the dominant species on a year-round scale. Water depth was the most important environmental factor affecting the macrobenthic community, and other important factors in different seasons included water temperature, SD, TSS content, Chl- a concentration, and nitrogen and phosphorus concentration. (2) The growth of Bellamya was significantly worse in the modelled habitats of the entrance area than in those of the original enclosure aquaculture area and the wetland area, but was overall better adapted to the environment. The growth of Radix auricularia was significantly better in the presence of aquatic plants than in the absence of plants, and was more significantly influenced by environmental factors closely related to aquatic plants. The densities of Annelida were significantly higher in the treatment group without plants than group with plants, showing the trend of the simulated original enclosure aquaculture area > the simulated entrance area > the simulated wetland area. It was mainly influenced by environmental factors such as turbidity and eutrophication index of the water, which was consistent with the results of the field survey. Declarations Acknowledgments This work was financially supported by the National Special Item on Water Resource and Environment from Ministry of Science and Technology of China (2017ZX07603003). We also want to thank Dr. Changtao Yang for his strong assistance during the field sampling process. Author contribution Changming Yang: Conceptualization, Field investigation, Methodology and Writing-review & editing; Shuhan Ding: Original draft, Writing-review & editing; Yangdan Niu: Lab experiment, Data collection, Formal analysis; Xiang Zhang: Data statistics and processing; Jianghua Li: Conceptualization, Methodology and Reviewing & editing. All authors edited the manuscript and approved the final version. Funding This research was funded by Ministry of Science and Technology of China (2017ZX07603003). Data availability The datasets analyzed during the current study are available from the corresponding author upon reasonable request. 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The abundance of nirS -type denitrifiers and anammox bacteria in rhizospheres was affected by the organic acids secreted from roots of submerged macrophytes. Chemosphere. 240, 124903. https://doi.org/10.1016/j.chemosphere.2019.124903. Zhang, D., Gersberg, R.M., Ng, W.J., Tan, S.K., 2014. Removal of pharmaceuticals and personal care products in aquatic plant-based systems: A review. Environ. Pollut. 184, 620–639. https://doi.org/10.1016/j.envpol.2013.09.009 Zhang, M., Li, Y., Uddin, K.B., Liu, J.-H., Qiao, R.-T., Zhao, Y.-J., Ma, S.-N., Søndergaard, M., Wang, H.-Z., 2024. Benthic primary production decreases internal phosphorus loading from lake sediments under light supplement. Ecotoxicol. Environ. Saf. 270, 115834. https://doi.org/10.1016/j.ecoenv.2023.115834. Zhang, Q., Cai, Y., Gong, Z., Wang, L., Heino, J., Qin, B., 2023. Unveiling the influence of specialists and generalists on Macroinvertebrate assemblage heterogeneity in lake Taihu. Ecol. Indic. 154, 110741. https://doi.org/10.1016/j.ecolind.2023.110741. Zhang, Q., Dong, X., Yang, X., Liu, E., Lin, Q., Cheng, L., Liu, L., Jeppesen, E., 2022. Aquatic macrophyte fluctuations since the 1900s in the third largest Chinese freshwater lake (Lake Taihu): Evidences, drivers and management implications. CATENA 213, 106153. https://doi.org/10.1016/j.catena.2022.106153. Zhang, Y., Ma, R., Liang, Q., Guan, B., Loiselle, S.A., 2019. Secondary impacts of eutrophication control activities in shallow lakes: Lessons from aquatic macrophyte dynamics in Lake Taihu from 2000 to 2015. Freshw. Sci. 38, 802–817. https://doi.org/10.1086/706197. Zhang, Y., Shen, R., Gu, X., Li, K., Chen, H., He, H., Mao, Z., Johnson, R.K., 2023. Simultaneous increases of filter-feeding fish and bivalves are key for controlling cyanobacterial blooms in a shallow eutrophic lake. Water Res. 245, 120579. https://doi.org/10.1016/j.watres.2023.120579. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 09 May, 2025 Read the published version in Environmental Monitoring and Assessment → Version 1 posted Editorial decision: Revision requested 09 Oct, 2024 Reviews received at journal 04 Oct, 2024 Reviews received at journal 19 Sep, 2024 Reviewers agreed at journal 16 Sep, 2024 Reviewers agreed at journal 12 Sep, 2024 Reviewers agreed at journal 11 Sep, 2024 Reviewers agreed at journal 11 Sep, 2024 Reviewers agreed at journal 09 Sep, 2024 Reviewers agreed at journal 14 Aug, 2024 Reviewers invited by journal 14 Aug, 2024 Editor assigned by journal 02 Aug, 2024 Submission checks completed at journal 02 Aug, 2024 First submitted to journal 17 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4756419","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":344646479,"identity":"fe5cd9b2-bead-4289-acfa-136b0dd6fde3","order_by":0,"name":"Changming Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5UlEQVRIiWNgGAWjYPACGzBpkMDAwNhApJY0CZK1HJaAsQhr4Z92xvBzwa/zdfzS7RcKHjDYyG44wPzsAT4tErdzjKVn9t2WkJxzpgDosDTjDQfYzA3waTGQzjGQ5u25LWFwIycBqOVw4oYDPGwSBLQY/+btOQfT8p8oLWbSPD8OALWkHwBqOUBYi8TttDJr3oZkyZkzcoCBbJBsPPMwmxleLfyzkzff5vljx88vkf7M8EeFnWzf8eZneLUwMHAYMDC2gRg8ZgYMoKBixq8eCNgfMDD8ATMePyCoeBSMglEwCkYkAAB5qEhzWd6z+AAAAABJRU5ErkJggg==","orcid":"","institution":"Tongji University","correspondingAuthor":true,"prefix":"","firstName":"Changming","middleName":"","lastName":"Yang","suffix":""},{"id":344646480,"identity":"e4512962-6f59-4678-b3ab-c64c38395c54","order_by":1,"name":"Shuhan Ding","email":"","orcid":"","institution":"Tongji University","correspondingAuthor":false,"prefix":"","firstName":"Shuhan","middleName":"","lastName":"Ding","suffix":""},{"id":344646481,"identity":"832eed37-d135-4c18-9e5f-67b3f567884b","order_by":2,"name":"Yangdan Niu","email":"","orcid":"","institution":"Tongji University","correspondingAuthor":false,"prefix":"","firstName":"Yangdan","middleName":"","lastName":"Niu","suffix":""},{"id":344646483,"identity":"2aae8bdf-34a0-4dcb-93d2-776d78ba4597","order_by":3,"name":"Xiang Zhang","email":"","orcid":"","institution":"Nankai University","correspondingAuthor":false,"prefix":"","firstName":"Xiang","middleName":"","lastName":"Zhang","suffix":""},{"id":344646484,"identity":"73622cca-46f0-4217-b205-b91a52a8399b","order_by":4,"name":"Jianhua Li","email":"","orcid":"","institution":"Tongji University","correspondingAuthor":false,"prefix":"","firstName":"Jianhua","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2024-07-17 13:00:43","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4756419/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4756419/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10661-025-14084-5","type":"published","date":"2025-05-09T15:57:08+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":63513195,"identity":"b8653d5a-09d8-4f8d-8a10-c5abc702a669","added_by":"auto","created_at":"2024-08-29 03:50:31","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":537720,"visible":true,"origin":"","legend":"\u003cp\u003eMap of the study area and layout of sample lines.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4756419/v1/019a588e044e11f3d19f0aa7.png"},{"id":63512634,"identity":"78a0367a-c6f6-43c3-bca1-a34094411bd2","added_by":"auto","created_at":"2024-08-29 03:42:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":83036,"visible":true,"origin":"","legend":"\u003cp\u003eComposition of macroinvertebrate communities in East Taihu Lake.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4756419/v1/605ec24fb933cb4f40ae0f0c.png"},{"id":63512629,"identity":"18872e4f-d471-4423-9c72-bfdead9a0cf8","added_by":"auto","created_at":"2024-08-29 03:42:31","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":193942,"visible":true,"origin":"","legend":"\u003cp\u003eThermogram of correlations between water environmental factors and macrobenthic fauna density (top) and biomass (bottom) over the year.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4756419/v1/463824b29373d7b922b9bec9.png"},{"id":63512633,"identity":"008fbddb-2483-4927-950a-29c92ea2b22a","added_by":"auto","created_at":"2024-08-29 03:42:32","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":283038,"visible":true,"origin":"","legend":"\u003cp\u003eSequencing of water environment factors with species (left) and sample sites (right).\u003c/p\u003e\n\u003cp\u003eAlphabetical labels: \u003cem\u003eBellamya purificata Be.p\u003c/em\u003e, \u003cem\u003eLimnodrilus Li\u003c/em\u003e, \u003cem\u003eTubifex\u003c/em\u003e \u003cem\u003eTu\u003c/em\u003e, \u003cem\u003eChironomus plumosus Ch\u003c/em\u003e, \u003cem\u003eBellamya aeruginosa\u003c/em\u003e \u003cem\u003eBe.a\u003c/em\u003e, \u003cem\u003ePolymoe Po\u003c/em\u003e, \u003cem\u003eUnio douglasiae\u003c/em\u003e \u003cem\u003eUn\u003c/em\u003e, \u003cem\u003ePristina longiseta\u003c/em\u003e \u003cem\u003ePr\u003c/em\u003e, \u003cem\u003eE.modestus\u003c/em\u003e \u003cem\u003eE.mo\u003c/em\u003e, \u003cem\u003eCipangopaludina ussuriensis\u003c/em\u003e \u003cem\u003eCi.u\u003c/em\u003e, \u003cem\u003eCipangopaludina chinensis Ci.c\u003c/em\u003e, \u003cem\u003eCorbicula fluminea\u003c/em\u003e \u003cem\u003eCo\u003c/em\u003e, \u003cem\u003eBellamya quadrata\u003c/em\u003e \u003cem\u003eBe.q\u003c/em\u003e, \u003cem\u003eAulophorus tonkinensis\u003c/em\u003e \u003cem\u003eAu\u003c/em\u003e, \u003cem\u003eRadix auricularia\u003c/em\u003e \u003cem\u003eRa\u003c/em\u003e, \u003cem\u003eCipangopaludina ampulliformis\u003c/em\u003e \u003cem\u003eCi.a\u003c/em\u003e, \u003cem\u003eN.denticulata\u003c/em\u003e \u003cem\u003eN.de\u003c/em\u003e, \u003cem\u003eAeolosoma hemprichii\u003c/em\u003e \u003cem\u003eAe\u003c/em\u003e, \u003cem\u003eMacrobrachium Mac\u003c/em\u003e, \u003cem\u003eCuneopsis heudei Cu.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4756419/v1/eef75ecac33322f383472420.jpeg"},{"id":63512630,"identity":"609210ac-181d-4553-b3fd-a770a0b8c0f2","added_by":"auto","created_at":"2024-08-29 03:42:32","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":136120,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in water column Chl-\u003cem\u003ea\u003c/em\u003e concentration with time for experimental groups in each functional area.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-4756419/v1/d68307245de96891964225bd.png"},{"id":63512632,"identity":"1430dae4-7c6f-4246-9f28-ffc20183959f","added_by":"auto","created_at":"2024-08-29 03:42:32","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":76985,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in density of various benthic species in the final state of the experiment\u003c/p\u003e\n\u003cp\u003eN:no-plant group; S: submerged plant group; S×F: submerged × floating plant group.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-4756419/v1/3b22b6668acdb652503e0fa9.png"},{"id":63513196,"identity":"e591facb-cf37-4e81-977e-ce1a34a82052","added_by":"auto","created_at":"2024-08-29 03:50:32","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":50874,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation analysis of the density, survival rate and rate of biomass change of each benthic species with environmental factors.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-4756419/v1/348981518db007c54593fd8e.png"},{"id":82537555,"identity":"c3310d79-87b7-4fe4-b4ab-ac616c9550ce","added_by":"auto","created_at":"2025-05-12 16:08:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2911398,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4756419/v1/7919fee6-b49d-43db-9108-f476b967ddfa.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Characteristics of Macrobenthic Communities and their Response to Environmental Changes in East Taihu Lake, China","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eRecently, with the advancement of urban industrialization and the increasing level of water resource utilization, aquatic ecosystems have been seriously degraded or destroyed, and biodiversity has been drastically reduced (Vugteveen et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). In order to promote a benign and healthy ecological cycle, the health of water ecosystems, which comprehensively reflects water quality, biological and habitat indicators, has been increasingly emphasized (Grizzetti et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Hopkins et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Jayawardana et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Stromberg et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The health of aquatic ecosystems comprehensively reflects the physicochemical characteristics, biological integrity and spatial differentiation differences of lakes, rivers, etc., and can effectively reflect the structure and function of ecosystems (Banagar et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMacrobenthos are a large group of ecosystems in aquatic ecosystems and are an important part of aquatic communities (Mermillod-Blondin and Florian, 2011; Statzner, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The characteristics of macrobenthic fauna can reflect the degree of damage to aquatic ecosystems at different scales in a watershed, so macrobenthic fauna has become one of the most important biological indicators of watershed and aquatic ecosystem health (Jani Heino, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; S\u0026aacute;nchez-Montoya et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Wells et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). In lake ecosystems, macrobenthic fauna has been used as indicators for comprehensive measures such as identification and evaluation of lake ecosystem health compared to other physicochemical hydrological parameters due to the advantages of limited activity, large-scale applicability, wide distribution in lakes and long life cycle (Beyene et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Stockdale et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEast Taihu Lake is a typical grass-type shallow lake, and it is also the water area with the largest distribution of aquatic plants in Taihu Lake (Wang et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). East Taihu Lake is not only the source of drinking water in Suzhou and the source of the Taipu River, but also the water source of Jinze Reservoir in the downstream of Shanghai, so it has attracted wide attention from all walks of life. In recent years, the strong anthropogenic impact on East Taihu Lake has intensified, resulting in severe eutrophication and swamping (Zhang et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and the area of submerged plants in the eastern grass-shaped lake area has decreased from 270 km\u003csup\u003e2\u003c/sup\u003e to 28 km\u003csup\u003e2\u003c/sup\u003e (Wu et al., 2023). In May 2007, a severe algal bloom event occurred in Taihu Lake, leading to a drinking water crisis (Yan et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In addition, East Taihu Lake, as one of the earliest lakes in China to develop fishery aquaculture, has largely received exogenous pollution, which has improved after the purse seine nets were completely removed in 2019, but the pollutants still have a great impact on the water body. Studies have shown that when the input of exogenous pollutants in lakes exceeds their own purification capacity, most of the pollutants will eventually accumulate in sediments through a series of complex physical, chemical and physicochemical processes. Due to years of exogenous import and pollution deposits, the sediments of Taihu Lake have become a huge potential source of pollution due to high levels of organic matter and nutrients (Chen et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study investigates the spatial and temporal distribution pattern, diversity and interaction between benthic fauna and environmental factors in different functional areas of East Taihu Lake, with a view to enriching the database of macrobenthos in East Taihu Lake, understanding the status of macrobenthic fauna in East Taihu Lake, deepening the understanding of the impacts of environment on macrobenthos, and at the same time providing theoretical references for the ecological protection and scientific management of East Taihu Lake.\u003c/p\u003e"},{"header":"2. Samples and analysis","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study site\u003c/h2\u003e \u003cp\u003eIn this study, the sample line method was mainly used to set up sampling points, and the principle of sample line layout was to cover the most representative areas of each functional area of East Taihu Lake as much as possible, and the number of sample lines was decided according to the size of each area. Additional sampling points were set up in the entrance area of East Zizania Tsui, which is an important ecological barrier in the East Taihu Lake, to investigate the macrobenthic fauna and their habitat conditions. A total of eight sample lines were set up in this study. When sampling according to the sample line forward direction of observation and on-site to determine the specific sampling points, each sample line on the selection of three sample points as a representative of the functional characteristics of the sampling point, to ensure that the distance between the sampling point distribution is more uniform, as far as possible to reflect the characteristics of the region as a whole (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSample lines No. 1, No. 2 and No. 3 are located in the entrance area (S1), which is the access point connecting East and West Taihu Lakes, and the area is large, with a large distribution of aquatic plants in the past, which is an important ecological barrier of East Taihu Lake; Sample line No. 4 is located in the aquatic plant conservation area (S2), which is an independent area set up in the process of comprehensive remediation of East Taihu Lake for the purpose of protecting the aquatic plants in the open area, and the decline of aquatic plants has been more severe in recent years; Sample line No. 5 is located in the pelagic area (S3), in the long and narrow central channel of East Taihu Lake, near the backup water source; Sample lines No. 6 and No. 7 are located in the original enclosure aquaculture area (S4), with large aquatic plants, mainly floating-leafed plants, and the habitat condition is in the restoration period after the removal of the enclosure aquaculture activities; Sample line No. 8 is located in the near-shore wetland, which has the most abundant aquatic plants and the best quality of water in the East Taihu Lake. The general habitat conditions of the sampling sites in each functional area are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescription of habitat conditions in each sampling area.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample points\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFunctional areas\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSubstrate characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAquatic plants\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAverage depth/m\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEntrance area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEntrance to the lake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSurface layer yellow, lower layer gray-black, semi-fluid, no odor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFew\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConservation area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAquatic Plant Conservation Areas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSurface layer yellow, lower layer gray-black, semi-fluid, slight putrid odor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFloating-leaf plants in spring and summer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePelagic area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCentralized channel, clear water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYellow, semi-fluid, no odor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOriginal enclosure aquaculture area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOriginal enclosure aquaculture area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGray-black, flowing, no odor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDense aquatic plants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWetland area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003enearshore shallow wetland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGray-black, flowing, no odor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDense aquatic plants with many emergent plants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Sampling and analysis\u003c/h2\u003e \u003cp\u003eThis study was conducted from October 2020 to November 2021. Water body physicochemical characteristics such as water depth, water temperature, clarity, and nutrients were surveyed monthly in each functional area, and sediment sampling surveys were conducted once in October 2020, April and August 2021 in each functional area. Conduct a macrobenthic sampling survey in December 2020, April, August and November 2021 for each of the four seasons: winter, spring, summer and autumn.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1. Water samples\u003c/h2\u003e \u003cp\u003eA water sampler was used to collect 500 mL of water samples at 0.5 m underwater at the sampling point, and three parallel samples were collected at each sampling point, which were transported to the laboratory and put into the refrigerator at 4℃ for refrigeration to complete the determination of the indexes as soon as possible. After collecting water samples, the water quality multi-parameter meter (YSI EXO2, USA) was used to measure water temperature (WT), dissolved oxygen (DO), pH, conductivity (EC) and other indicators at 0.5 m underwater, and the standard transparency disk was used to measure the secchi depth (SD) of the sampling site, and a 3m-ruler was used to measure the water depth of the sampling site.\u003c/p\u003e \u003cp\u003eWater samples under refrigerated conditions were transported back to the laboratory for in-house analytical experiments as soon as possible. The water samples were shaken well to determine the turbidity of the water samples using a turbidimeter (1900C, HACH, USA), and then the chlorophyll-\u003cem\u003ea\u003c/em\u003e (Chl-\u003cem\u003ea\u003c/em\u003e) concentration of the water samples was determined using a phyto-PAM modulated fluorometer (Heinz Walz GmbH, Effeltrich, Germany). Unfiltered water samples were used to test total nitrogen (TN) and total phosphorus (TP) concentrations in the water column. Another 200 mL or so of raw water was filtered through 0.45 \u0026micro;m cauterized glass fiber filter membrane, and the filtrate was stored in a brown reagent bottle for determining the concentrations of total dissolved nitrogen (TDN), total dissolved phosphorus (TDP), ammonia nitrogen (NH\u003csup\u003e4+\u003c/sup\u003e-N), nitrate nitrogen (NO\u003csup\u003e3\u0026minus;\u003c/sup\u003e-N), dissolved orthophosphate (PO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e3\u0026minus;\u003c/sup\u003e-P) and dissolved organic carbon (DOC). Nitrogen and phosphorus nutrient salt indicators were analyzed and determined by a double-beam ultraviolet-visible spectrophotometer (UV-2450, Shimadzu, Japan), and DOC was determined by a total organic carbon analyzer (TOC-VCPN, Shimadzu, Japan). The analytical methods for the above indicators were mainly referred to the Specification for Investigation of Eutrophication in Lakes, the National Standard Methods, and the Analytical Methods for Water and Wastewater Monitoring (4th Edition).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2. Sediment samples\u003c/h2\u003e \u003cp\u003eSediment samples were transported back to the laboratory for cold storage. The samples were analyzed by removing aquatic plant debris and stone particles and mixing them well, and the pH and redox potential of the samples were determined using a pH meter. A certain mass of sediment was weighed and placed in aluminum foil, dried at 105℃ for 12 h, weighed again after drying, and the difference was the moisture content (MC) of the sediment; the dried sample was placed in an empty crucible with a known mass after burning at 105℃, and then moved to a muffle furnace to be heated up to 550℃ for 5 h. The sample was cooled down and weighed in a desiccator, and the mass was recorded, and then the difference was calculated to be the amount of loss on ignition (LOI) of the sediment. The soil total phosphorus (STP) of the sediments was determined with reference to the alkali fusion-molybdenum antimony antispectrophotometric method for total soil phosphorus determination (HJ 632\u0026ndash;2011), and the soil total nitrogen (STN) was determined by using the method of persulfate digestion(Bronk et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Sharp et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Vandenbruwane et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). After pretreatment of sediment samples by grinding and H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e digestion, the substrate samples were analyzed using a laser particle sizer to obtain the particle size distribution.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3. Macrobenthos samples\u003c/h2\u003e \u003cp\u003eUsing a 1/16 m\u003csup\u003e2\u003c/sup\u003e Peterson mud collector, 3 parallel samples were collected from each sample point, 1\u0026thinsp;~\u0026thinsp;3 mixed counts were collected according to the bottom mud condition, and the cumulative sampling area of each sample point was 1/8 m\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;~\u0026thinsp;1/3 m\u003csup\u003e2\u003c/sup\u003e, and the sampling thickness was generally 10 cm\u0026thinsp;~\u0026thinsp;15 cm. 60-mesh screen was used to shake the mud samples in the lake water, and initially washed off the mud in the mud samples. The residue left in the net was put into a self-sealing plastic bag with 75% ethanol solution for preservation, labeled and brought back to the laboratory for processing.\u003c/p\u003e \u003cp\u003eThe samples brought back are poured into a 60-mesh screen and the bottom of the screen is placed in a basin of fresh water and gently shaken to wash away the remaining sludge in the samples. After sieving and washing, pick out the debris and plant branches, leaves, etc., and pour the cleaned sample into a white porcelain dish. A little water was added to the white porcelain dish, and all kinds of macrofauna were picked out with round-tip tweezers, pipettes and other tools, with the aid of a body-vision microscope if necessary. Use a brush to sort out smaller and softer animals to avoid damaging the worm. The picked samples were put into wide-mouth specimen bottles and fixed with 75% ethanol solution.\u003c/p\u003e \u003cp\u003eSpecies identification and taxonomic counting of macrobenthos were carried out using a magnifying glass or a stereomicroscope. Species identification was made with reference to Advanced Aquatic Biology, Atlas of Freshwater Micro-organisms and Macrobenthos (2nd Edition), Journal of the Economic Zoology of China (Freshwater Mollusca), and Macrobenthos Monitoring Atlas of the Liaohe River Basin; species identification was made to the lowest possible taxonomic units such as genera or species, and some species identification was made to the family level. Some species were identified to the family level, and the uncertain species were photographed and filed for further identification by experts. The liquid on the surface of the macrobenthos is absorbed by filter paper, and the biomass (wet weight) of the macrobenthos is weighed using a 1/10,000 analytical balance. The results of counting and weighing were converted to density and biomass per unit area.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.2.4. Indoor experimental design\u003c/h2\u003e \u003cp\u003e(1)Experimental material\u003c/p\u003e \u003cp\u003eSediments for the experiment was collected from three functional areas (the entrance area, the original enclosure aquaculture area and the wetland area of East Taihu Lake), representing their respective benthic environments. Sediments were collected from the field by a modified 1/16 m\u003csup\u003e2\u003c/sup\u003e Pedersen grab sampler, brought back to the laboratory and rinsed with flowing tap water to separate the benthos therein, and the sediments were air-dried in a ventilated area and then dispensed into glassware and sterilized in an autoclave at 0.12 MPa and 121\u0026deg;C for 15 min to kill the remaining benthos and dormant eggs. The experimental water was pumped from the Taipu River into the laboratory storage tank, and then introduced into the experimental setup after 2 h of resting to ensure that the experimental water was closest to the reality of the East Taihu Lake.\u003c/p\u003e \u003cp\u003eThe test benthos was selected from Mollusca such as \u003cem\u003eBellamya purificata\u003c/em\u003e and \u003cem\u003eBellamya patina\u003c/em\u003e with low fouling tolerance and \u003cem\u003eRadix auricularia\u003c/em\u003e, and \u003cem\u003eLimnodrilus\u003c/em\u003e and \u003cem\u003eChironomus plumosus\u003c/em\u003e with high fouling tolerance. The snails were collected from the Pujiangyuan Ecological Wetland of East Taihu Lake, and the \u003cem\u003eLimnodrilus\u003c/em\u003e and \u003cem\u003eChironomus plumosus\u003c/em\u003e were purchased from the flower, bird and fish market near the experimental site, which were freshly salvaged on the same day. All the benthic animals were kept in the laboratory for 5 d in tap water that had been aerated for more than 7 d. The water was changed daily, and the snails with good growth condition and uniform size were selected to be put into the experimental setup. The test aquatic plants were selected from the common local species in East Taihu Lake, and the submerged plants included \u003cem\u003eMyriophyllum spicatum\u003c/em\u003e, \u003cem\u003eCeratophyllum demersum\u003c/em\u003e L., \u003cem\u003eVallisneria\u003c/em\u003e sp \u003cem\u003eiralis\u003c/em\u003e, and \u003cem\u003eHydrilla uerticillata\u003c/em\u003e, while the floating plants were \u003cem\u003eNymphoides peltatum\u003c/em\u003e. The aquatic plants were collected from the natural waters of East Taihu Lake or purchased from the planting bases, and then brought back to the laboratory to select the well-grown plants to be washed and put into the experimental setup.\u003c/p\u003e \u003cp\u003e(2)Experimental design\u003c/p\u003e \u003cp\u003eThe experiment was conducted on an indoor experimental bench from April 28, 2021 to June 28, 2021 for a period of 60 d. A total of nine groups of treatments were set up, numbered in order from 1 to 9. Treatments 1 to 3 were the experimental groups with the sediment in the entrance area as the substrate, treatments 4 to 6 were the original enclosure aquaculture area, and treatments 7 to 9 were the wetland area, and the experimental groups of each functional area were divided into three treatments: no-plant, submerged plant, and submerged\u0026times;floating plant three treatments, each treatment set three parallel groups. The biomass of the same category of aquatic plants and benthic animals placed in each experimental group was kept as consistent as possible, and the specific settings are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eExperimental setup and initial biomass of benthic animals responding to the environment.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFunctional area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eAquatic plants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eBenthic biomass (g)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTreatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal biomass(g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBellamya\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRadix auricularia\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eEntrance area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eno-plant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.93\u0026thinsp;\u0026plusmn;\u0026thinsp;1.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esubmerged plant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e102.58\u0026thinsp;\u0026plusmn;\u0026thinsp;3.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.16\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esubmerged\u0026times;floating plant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120.83\u0026thinsp;\u0026plusmn;\u0026thinsp;3.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.51\u0026thinsp;\u0026plusmn;\u0026thinsp;1.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eOriginal enclosure aquaculture area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eno-plant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.38\u0026thinsp;\u0026plusmn;\u0026thinsp;1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esubmerged plant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100.55\u0026thinsp;\u0026plusmn;\u0026thinsp;2.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.05\u0026thinsp;\u0026plusmn;\u0026thinsp;1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esubmerged\u0026times;floating plant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e121.60\u0026thinsp;\u0026plusmn;\u0026thinsp;4.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.36\u0026thinsp;\u0026plusmn;\u0026thinsp;2.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eWetland area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eno-plant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.38\u0026thinsp;\u0026plusmn;\u0026thinsp;1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esubmerged plant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e101.70\u0026thinsp;\u0026plusmn;\u0026thinsp;2.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esubmerged\u0026times;floating plant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120.57\u0026thinsp;\u0026plusmn;\u0026thinsp;4.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe experimental container was a cylindrical glass cylinder with a radius of 7.5 cm and a height of 40 cm, which was washed and air-dried, then filled with treated substrate and spread to a thickness of about 8 cm \u0026minus;\u0026thinsp;10 cm, and aquatic plants were planted in the substrate. The treated water was slowly added into the device at a height of about 35 cm to avoid large-scale disturbance of the substrate. The benthic animals were added according to the experimental setup, and an oxygenation and aeration device with a flow rate of 160 L/H was fixed on the upper part of each device, so that a slow water flow was formed on the upper water surface of the device to provide necessary oxygen for the benthic animals to form a micro-ecosystem. The incubation light-dark ratio was 12 h:12 h, and the temperature was (25\u0026thinsp;\u0026plusmn;\u0026thinsp;1)℃.\u003c/p\u003e \u003cp\u003eThe Chl-\u003cem\u003ea\u003c/em\u003e concentration of the water body was measured periodically during the experiment, while water was replenished periodically to the original liquid level height to supplement evaporation losses. Turbidity, TN, TP, NO\u003csup\u003e3\u0026minus;\u003c/sup\u003e-N, PO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e3\u0026minus;\u003c/sup\u003e-P concentrations in the water column and TN and TP contents in the sediments were measured at the beginning and end of the experiment, respectively. At the end of the experiment, the survival rate, density and biomass of each type of macrobenthos were counted.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Data processing\u003c/h2\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1. Dominant species\u003c/h2\u003e \u003cp\u003eDominant species are the dominant populations of organisms in a community that have a controlling influence on the community. In this study, Index of Relative Importance (\u003cem\u003eIRI\u003c/em\u003e) was chosen to determine the dominant species. The calculation method is according to Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e):\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:IRI=\\left(W+N\\right)\\times\\:F$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:W\\)\u003c/span\u003e\u003c/span\u003e is the percentage of the biomass of a species to the total biomass; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:N\\)\u003c/span\u003e\u003c/span\u003e is the percentage of the density of a species to the total density; and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:F\\)\u003c/span\u003e\u003c/span\u003e is the percentage of the number of sample points in which a species occurs to the total number of sample points.\u003c/p\u003e \u003cp\u003e \u003cem\u003eIRI\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;1000 is considered as the dominant species, \u003cem\u003eIRI\u003c/em\u003e between 100 and 1000 is the important species, \u003cem\u003eIRI\u003c/em\u003e between 10 and 100 is the common species, and \u003cem\u003eIRI\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;10 is the rare species (Pianka, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1971\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2. Biodiversity index\u003c/h2\u003e \u003cp\u003eIn this study, three diversity indices, Shannon-Wiener diversity index (\u003cem\u003eH'\u003c/em\u003e), Margalef richness index (\u003cem\u003eD\u003c/em\u003e) and Pielou evenness index (\u003cem\u003eJ\u003c/em\u003e), were used to calculate and assess the level of diversity in macrobenthic communities. The calculations were shown in Eqs.\u0026nbsp;(2), (3) and (4), respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{H}^{{\\prime\\:}}=-\\sum\\:_{i=1}^{S}{P}_{i}\\text{ln}{P}_{i}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:D=\\left(S-1\\right)\\text{ln}N\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:J=-\\frac{\\sum\\:_{i=1}^{S}{P}_{i}\\text{ln}{P}_{i}}{\\text{ln}S}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:S\\)\u003c/span\u003e\u003c/span\u003e is the total number of species, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{P}_{i}\\)\u003c/span\u003e\u003c/span\u003e is the ratio of the number of individuals of species \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:i\\)\u003c/span\u003e\u003c/span\u003e to the total number of samples, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:N\\)\u003c/span\u003e\u003c/span\u003e is the total number of all species in the collected samples.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e2.3.3. Analysis of variance\u003c/h2\u003e \u003cp\u003eIndependent samples t-test or One-way ANOVA were used to compare the differences in various variables, such as environmental indicators, macrobenthic densities and biomass, between seasons and sampling sites.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e2.3.4. Correlation analysis\u003c/h2\u003e \u003cp\u003ePearson correlation coefficients were used to analyze the correlations between macrobenthos density and biomass and environmental factors in the water column and sediments in East Taihu Lake; the top 20 macrobenthos densities and environmental factors ranked in the IRI index were ranked and analyzed using Canoco 4.5, and the raw values of environmental factors and macrobenthos densities, except for pH, were transformed by \u003cem\u003elg\u003c/em\u003e(x\u0026thinsp;+\u0026thinsp;1). To determine whether the data were unimodal or linearly distributed, the transformed data were subjected to descending trend correspondence analysis (DCA), and if the maximum gradient length of the DCA results was greater than 4, canonical correspondence analysis (CCA) was selected; conversely, redundancy analysis (RDA) was selected;\u003c/p\u003e \u003cp\u003eSPSS 22.0 was used for data processing and other statistical analyses in this study, and Origin 2019 was used for plotting.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3. Results and discussion","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Community structure of macrobenthos in East Taihu Lake\u003c/h2\u003e \u003cp\u003eDuring the four seasons between January 2021 and November 2021, a total of 266 macrobenthic organisms was collected, consisting of three major groups: Mollusca, Annelida and arthropods, were collected from five sampling areas in the main functional area of East Taihu Lake. In terms of the number of organisms, there were 58 Mollusca, accounting for 21.80%; 164 Annelida, accounting for 61.65%; and 44 Arthropoda, accounting for 16.54%. After further observation and identification, there were 28 species of macrobenthos, belonging to 3 phyla, 6 classes, 13 orders, 18 families and 25 genera. There were 10 species of Mollusca in the three phyla, accounting for 35.71%, including 7 species of Gastropoda and 3 species of \u003cem\u003eLamellibranchia\u003c/em\u003e; 7 species of Annelida, accounting for 25.00%, including 6 species of Oligochaeta and 1 species of Polychaeta; 11 species of Arthropoda, accounting for 39.27%, including 1 species of \u003cem\u003eChironomus plumosus\u003c/em\u003e, 3 species of Crustacea, and 7 species of other small number of aquatic insects (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe dominant macrobenthic species in East Taihu Lake also varied between seasons and across functional areas (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Seasonally, \u003cem\u003eBellamya purificata\u003c/em\u003e and \u003cem\u003eLimnodrilus\u003c/em\u003e were dominant species throughout the year. Among them, \u003cem\u003eLimnodrilus\u003c/em\u003e had the highest \u003cem\u003eIRI\u003c/em\u003e index values in spring, summer and winter, and \u003cem\u003eBellamya purificata\u003c/em\u003e had the highest \u003cem\u003eIRI\u003c/em\u003e index values in autumn. In addition to this, \u003cem\u003eBellamya aeruginosa\u003c/em\u003e was also more dominant in the spring; \u003cem\u003eTubifex\u003c/em\u003e was more dominant in the summer and autumn; and \u003cem\u003eChironomus plumosus\u003c/em\u003e was more dominant in the autumn, and thus autumn had the highest number of dominant species.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSeasonal changes of dominant macrobenthic species in East Taihu Lake.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eIRI\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpring\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSummer\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAutumn\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWinter\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBellamya purificata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2830.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2949.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2381.91\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2732.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBellamya aeruginosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1157.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLimnodrilus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e4155.21\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2967.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1265.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e3065.19\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTubifex\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2194.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1985.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChironomus plumosus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1103.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBold font indicates the maximum \u003cem\u003eIRI\u003c/em\u003e value for the season.\u003c/p\u003e \u003cp\u003eSpatially, \u003cem\u003eLimnodrilus\u003c/em\u003e was the only dominant species in all functional areas of East Taihu Lake and had the highest \u003cem\u003eIRI\u003c/em\u003e indexes in three areas: the conservation area, the pelagic area and the original enclosure aquaculture area. \u003cem\u003eBellamya purificata\u003c/em\u003e was the most dominant species in the wetland area, and was also a relatively important species in the original enclosure aquaculture area. Each functional area had 2\u0026thinsp;~\u0026thinsp;3 kinds of macrobenthic species with \u003cem\u003eIRI\u003c/em\u003e index values of 1000 or more, and only the wetland area was dominated by Mollusca, while the entrance area, the conservation area and original enclosure aquaculture area were dominated by Annelida (Oligochaeta, Polychaeta) and \u003cem\u003eChironomus plumosus\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSpatial variation of dominant macrobenthic species in East Taihu Lake.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eIRI\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eS2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eS4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eS5\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBellamya purificata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2071.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2262.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e9709.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBellamya aeruginosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2314.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLimnodrilus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1217.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e4762.96\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e3008.53\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e4969.43\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1349.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTubifex\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2134.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3642.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChironomus plumosus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1628.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1224.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePolymoe\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e3467.21\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCorbicula fluminea\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2602.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBold font indicates the maximum \u003cem\u003eIRI\u003c/em\u003e value for the area.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Relationship between macrobenthic community structure and environmental factors\u003c/h2\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e3.2.1. Impact of water environmental factors\u003c/h2\u003e \u003cp\u003eChanges in macrobenthic community structure are affected by various environmental factors in the habitat and human activities, and the influencing factors and mechanisms are very complex. The heterogeneity of habitats in different habitats and seasons leads to different environmental influencing factors and feedback mechanisms for macrobenthos.\u003c/p\u003e \u003cp\u003eThe distribution of the correlation between the physical and chemical factors of the water environment and the density and biomass of macrobenthic species on the annual scale of East Taihu Lake during the study period is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The correlations between macrobenthos density, biomass and environmental factors were basically consistent, but there were some differences in the strength of significance. The correlations between species of similar taxonomic units (e.g., \u003cem\u003eBellamya purificata\u003c/em\u003e and \u003cem\u003eBellamya aeruginosa\u003c/em\u003e, \u003cem\u003eLimnodrilus\u003c/em\u003e and \u003cem\u003eTubifex\u003c/em\u003e, etc.) and the various water environmental factors were somewhat similar, showing similar environmental impact effects.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe aquatic environmental factor that reached the most significant correlation with inter-species correlations at the year-round time scale was water depth, indicating that water depth is one of the most important environmental influences on macrobenthic communities in East Taihu Lake. This result is consistent with previous studies (Chatzinikolaou et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). For shallow lakes with large perennial water level fluctuations, water depth will mostly be the primary environmental influence factor for differences in the distribution of macrobenthic communities, and underwater transmitted light decreases with increasing depth of the water column, with a consequent decrease in macrobenthic densities and biomass, which is especially more pronounced for the Mollusca(e.g., Gastropoda and Lamellibranchia) (Cai et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Deep water is more likely to be occupied by phytoplankton, which may sometimes even form blooms due to the input of nutrients and other pollutants, and the low-oxygen environment is more favorable for the survival of some macroinvertebrates (e.g., Oligochaetes, Chlamydia, etc.) with high stress tolerance (Li et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA similar pattern was presented in this study, in which the density and biomass of \u003cem\u003eBellamya aeruginosa\u003c/em\u003e and \u003cem\u003eRadix Auricularia\u003c/em\u003e were significantly negatively correlated with water depth (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and other Mollusca species also had a negative correlation with water depth; whereas the density and biomass of the Oligochaeta, as well as that of \u003cem\u003eChironomus plumosus\u003c/em\u003e, showed a significant or highly significant positive correlation with water depth.\u003c/p\u003e \u003cp\u003eThe relationship between water depth and macrobenthic species is significant, not only caused by water depth alone, but also due to how water depth varies between different seasons and functional areas, which leads to the regular changes of water transparency, aquatic plant growth and coverage, hydrodynamic conditions and dissolved oxygen. The distribution of macrobenthic animals is affected by various factors at the same time, mostly associated with water depth, and macrobenthos is a thermotropic animal preferring different optimal growth temperatures, and its growth, reproduction and metabolism are largely affected by water temperature, which is closely related to water depth (Arscott et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Dudgeon, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1985\u003c/span\u003e; Mantelatto et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In addition, the concentration of Chl-\u003cem\u003ea\u003c/em\u003e and nitrogen and phosphorus of water are also important environmental factors affecting macrobenthos in East Taihu Lake. More information needs to be analyzed in relation to the correlation between macrobenthos and water environmental factors in different seasons.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e3.2.2. RDA analysis of macrobenthos and environmental factors\u003c/h2\u003e \u003cp\u003eUsing the descending trend correspondence analysis (DCA) between the main environmental factors that have a greater impact on macrobenthos in the correlation analysis and the macrobenthic species ranked in the top 20 of \u003cem\u003eIRI\u003c/em\u003e values, the gradient lengths of the four ranking axes were analyzed to be 3.02, 2.90, 1.88, and 1.55, which were all less than 4, and the maximum gradient length was close to 3. Therefore, the choice of redundancy analysis (RDA) to further reveal the effect of environment on macrobenthic communities.\u003c/p\u003e \u003cp\u003eThe ordination plot between water environmental factors and each species and sample site is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e., the length of the arrows represents the magnitude of the influence of environmental and species factors on the ordination, thus species located at the skewed edges of the ordination plot will respond to specific environmental factors (Shen et al., 2024). Species with large positive values in the first axis include mollusc species such as \u003cem\u003eBellamya purificata\u003c/em\u003e, \u003cem\u003eBellamya aeruginosa\u003c/em\u003e, \u003cem\u003eCipangopaludina ussuriensis\u003c/em\u003e, \u003cem\u003eBellamya quadrata\u003c/em\u003e, and \u003cem\u003eUnio douglasiae\u003c/em\u003e, which are distributed in the functional areas with higher water transparency, shallower water depths, lower concentrations of TP, and lower levels of TSS, and the angles between the arrows of the above species are small, which indicates that the relationships between them and the water environmental factors have high similarity, which is in line with the results of the correlation heatmap analysis. In fact, all these species belong to the low and medium pollution-tolerant taxa, which indicates a better water quality environment, and the wetland sampling sites in each season are located in the positive direction of the first axis in the sample point ranking map, which indicates that Mollusca occur most frequently in this functional area and have the best water quality.\u003c/p\u003e \u003cp\u003eThe genera of \u003cem\u003eLimnodrilus\u003c/em\u003e and \u003cem\u003eTubifex\u003c/em\u003e were located in the second axis with the largest negative value, and the genera of \u003cem\u003eAulophorus tonkinensis\u003c/em\u003e belonging to the same Oligochaeta were also located in the same position, and they were all distributed in the functional areas with high Chl-\u003cem\u003ea\u003c/em\u003e concentration, and at the same time, in the same area in the sample sorting map were the conservation area and the original enclosure aquaculture area, which was in line with the high Chl-\u003cem\u003ea\u003c/em\u003e concentration in the water bodies of these two functional areas. \u003cem\u003eChironomus plumosus\u003c/em\u003e was located in similar positions and distributed in waters with deeper water depths and high concentrations of TP and TN, same as \u003cem\u003ePristina longiseta\u003c/em\u003e and \u003cem\u003eAeolosoma hemprichii\u003c/em\u003e, which belong to the Oligochaeta. These species with high fouling tolerance values prefer to live in low oxygen environments of deeper water depth, which can be indicative of a more severe eutrophication status of the water body (Gao et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Organic matter provides an important food source and shelter for macrobenthos, so the organic matter content of habitats is crucial for macrobenthic community structure (Shen et al., 2024). It has been shown that the removal of organic matter will lead to a significant decrease in the abundance of \u003cem\u003eChironomidae Diptera\u003c/em\u003e in freshwater ecosystems, such as rivers, and a significant change in the community structure (Entrekin et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). However, higher organic matter content will be accompanied by a decrease in habitat pH, water transparency and dissolved oxygen, and an inhibitory effect on the growth of macrobenthos (Luoto et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Cai also found that in Zhushan Bay, Meiliang Bay and estuarine areas of Taihu Lake, which are heavily polluted and highly eutrophic, the substrate is silt-clay and high in organic matter, and \u003cem\u003eLimnodrilus hoffmeisteri\u003c/em\u003e is the main dominant macrobenthic fauna (Cai et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAlphabetical labels: \u003cem\u003eBellamya purificata Be.p\u003c/em\u003e, \u003cem\u003eLimnodrilus Li\u003c/em\u003e, \u003cem\u003eTubifex Tu\u003c/em\u003e, \u003cem\u003eChironomus plumosus Ch\u003c/em\u003e, \u003cem\u003eBellamya aeruginosa Be.a\u003c/em\u003e, \u003cem\u003ePolymoe Po\u003c/em\u003e, \u003cem\u003eUnio douglasiae Un\u003c/em\u003e, \u003cem\u003ePristina longiseta Pr\u003c/em\u003e, \u003cem\u003eE.modestus E.mo\u003c/em\u003e, \u003cem\u003eCipangopaludina ussuriensis Ci.u\u003c/em\u003e, \u003cem\u003eCipangopaludina chinensis Ci.c\u003c/em\u003e, \u003cem\u003eCorbicula fluminea Co\u003c/em\u003e, \u003cem\u003eBellamya quadrata Be.q\u003c/em\u003e, \u003cem\u003eAulophorus tonkinensis Au\u003c/em\u003e, \u003cem\u003eRadix auricularia Ra\u003c/em\u003e, \u003cem\u003eCipangopaludina ampulliformis Ci.a\u003c/em\u003e, \u003cem\u003eN.denticulata N.de\u003c/em\u003e, \u003cem\u003eAeolosoma hemprichii Ae\u003c/em\u003e, \u003cem\u003eMacrobrachium Mac\u003c/em\u003e, \u003cem\u003eCuneopsis heudei Cu.\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Response of macrobenthos in East Taihu Lake to changes in different habitats\u003c/h2\u003e \u003cp\u003eIn order to further analyze and verify the effects of various environmental factors on macrobenthos in East Taihu Lake, the sediments of the three most representative functional areas of the entrance area, the original enclosure aquaculture area and the wetland area were selected as the substrate environment, and the raw water of East Taihu Lake as the aqueous environment. Three groups of parallel experiments were set up in each functional area to form a micro-ecosystem with no aquatic plants, submerged plants, submerged plants and floating leaf plants coexisting, to investigate the response of macrobenthos to the environmental changes in different habitats in each experimental group.\u003c/p\u003e \u003cp\u003eThe macrobenthos included \u003cem\u003eBellamya\u003c/em\u003e (\u003cem\u003eBellamya purificata\u003c/em\u003e, \u003cem\u003eBellamya aeruginosa\u003c/em\u003e) and \u003cem\u003eRadix auricularia\u003c/em\u003e in Mollusca, \u003cem\u003eLimnodrilus\u003c/em\u003e, \u003cem\u003eTubifex\u003c/em\u003e, and other detected annelid species in Annelida, as well as \u003cem\u003eChironomus plumosus\u003c/em\u003e in Arthropoda. These macrobenthic species in the three phyla were selected as the relatively dominant and representative species found in the field sampling of East Taihu Lake, with \u003cem\u003eBellamya purificata\u003c/em\u003e being the first species in the relative importance index. The responses of these macrobenthos to environmental changes in different functional areas can effectively verify the correlation between macrobenthos and environmental factors in East Taihu Lake.\u003c/p\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e3.3.1 Physical and chemical indicators of water bodies and sediments\u003c/h2\u003e \u003cp\u003eThe changes of Chl-\u003cem\u003ea\u003c/em\u003e concentration in the system of each experimental group during the 15th, 30th, 45th and 60th time periods of the experimental period are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Since the experimental light intensity was not as sufficient as under natural conditions, the Chl-\u003cem\u003ea\u003c/em\u003e concentration in the system of each experimental group was not high, and only diatoms grew, but still showed a certain pattern. Submerged plants can inhibit algae by secreting chemosensory chemicals and also indirectly by reducing sediment resuspension and increasing water transparency (Liu et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The overall Chl-\u003cem\u003ea\u003c/em\u003e concentration within the three experimental environmental groups in the entrance area, the original enclosure aquaculture area and the wetland area all showed that the no-plant group\u0026thinsp;\u0026lt;\u0026thinsp;submerged plant group\u0026thinsp;\u0026lt;\u0026thinsp;submerged \u0026times; floating plant group. In the early stage of the experiment (15 d), the Chl-\u003cem\u003ea\u003c/em\u003e concentrations in the two treatment groups with aquatic plant growth were similar and significantly higher than those in the no-plant group. In the middle and late stages (30 d\u0026thinsp;~\u0026thinsp;60 d) under constant water replenishment, the Chl-\u003cem\u003ea\u003c/em\u003e concentrations of the three functional areas without aquatic plants treatment groups were all in an increasing trend, but the increase was not large, and the concentrations were still lower than 10 ug/L; the Chl-\u003cem\u003ea\u003c/em\u003e concentrations of the three submerged plant treatment groups were significantly lower than those in the early stage (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and stabilized in the range of 8.30 ug/L \u0026minus;\u0026thinsp;9.82 ug/L; the Chl-\u003cem\u003ea\u003c/em\u003e concentrations of the three submerged \u0026times; floating plant treatment groups Chl-\u003cem\u003ea\u003c/em\u003e concentrations had a decreasing trend but was not obvious, so the Chl-\u003cem\u003ea\u003c/em\u003e concentration of the submerged plant treatment group was more similar to that of the no-plant group in the late stage of the experiment and had a greater difference from that of the submerged \u0026times; floating plant group.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eChl-\u003cem\u003ea\u003c/em\u003e concentration can characterize phytoplankton biomass to a certain extent and is also an important component of organic suspended particulate matter in the water column. Aquatic plants can directly absorb nutrients from the lake, and also regulate the microbial community through exudation from their roots and further influence nitrification (Yin et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), thus the experimental group with aquatic plant growth had less total suspended particulate matter than the group without plants, and the water body had lower turbidity (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) and higher transparency. Aquatic plants can inhibit the growth of algae to a certain extent, and under natural conditions, when aquatic plants decline, it will lead to an increase in the Chl-\u003cem\u003ea\u003c/em\u003e concentration in the water body; but on the other hand, having aquatic plant growth will increase the percentage of organic suspended particulate matter in the water body, which is greater than that of inorganic particulate matter. In this experiment, the second process was more obvious due to the insufficient light conditions, which were not favorable for algal bloom growth. Meanwhile, scrapers have an inhibitory effect on algae, which can effectively remove suspended particles from the water body and improve water transparency (Waajen et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Y. Zhang et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Overall, the Chl-\u003cem\u003ea\u003c/em\u003e concentration was similar between the same aquatic plant treatment groups in the three functional areas in this experiment, while there was a significant difference in Chl-\u003cem\u003ea\u003c/em\u003e concentration between the different aquatic plant treatment groups, suggesting that there is a close relationship between Chl-\u003cem\u003ea\u003c/em\u003e concentration and aquatic plants.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePhysicochemical indicators of water and sediment in the final state for each experimental group.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eExperimental group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eWater index\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eSediments\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNTU\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTN\u003c/p\u003e \u003cp\u003e(mg/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNO\u003csup\u003e3\u0026minus;\u003c/sup\u003e-N\u003c/p\u003e \u003cp\u003e(mg/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTP\u003c/p\u003e \u003cp\u003e(mg/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e3\u0026minus;\u003c/sup\u003e-P\u003c/p\u003e \u003cp\u003e(mg/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSTN\u003c/p\u003e \u003cp\u003e(mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSTP\u003c/p\u003e \u003cp\u003e(mg/kg)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS1་no-plant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e195.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e75.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS1་submerged plant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e351.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e69.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS1་submerged\u0026times;floating plant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e361.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e73.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS4་no-plant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1562.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e136.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS4་submerged plant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1529.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e120.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS4་submerged\u0026times;floating plant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1341.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e98.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS5་no-plant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e249.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e49.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS5་submerged plant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e512.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e51.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS5་submerged\u0026times;floating plant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e443.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e50.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTN in the water column of the experimental system was mainly in the form of nitrate nitrogen (NO\u003csup\u003e3\u0026minus;\u003c/sup\u003e-N). Nitrogen concentrations in the water column were similar overall in the original enclosure aquaculture area and the wetland area, while the entrance area was slightly lower overall than the original enclosure aquaculture area and the wetland area. Within the experimental groups of each functional area, the concentrations of TN and nitrate nitrogen in the three treatment groups of no plant, submerged plant, and submerged \u0026times; floating plant decreased sequentially, indicating that the uptake of nutrients by aquatic plants in the experimental system mainly manifested itself as the uptake of nitrogen in the water column. While TP and PO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e3\u0026minus;\u003c/sup\u003e-P concentrations in each functional area showed that the group with plants was significantly higher than the group without plants, which may be the reason that Chl-\u003cem\u003ea\u003c/em\u003e concentration was higher in the group with plants, and higher phosphorus concentration was more suitable for the growth of algae.\u003c/p\u003e \u003cp\u003eUnlike the large differences in water body nitrogen and phosphorus indicators in different aquatic plant treatment groups, sediment TN and TP contents were significantly different among the three functional zones, with sediment nitrogen and phosphorus contents in the original enclosure aquaculture area significantly higher than those in the entrance area and the wetland area (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and higher in the wetland area than those in the entrance area, and the sediment nitrogen and phosphorus contents were basically similar between the treatment groups with and without aquatic plants in all the functional areas with no significant differences.\u003c/p\u003e \u003cp\u003eThe nitrogen and phosphorus indices of the water body in the final state of the experiment were higher than that of the raw water of East Taihu Lake used in the experiment at the initial time, while the sediment TN and TP were on the contrary, with the concentration of the sediment nitrogen and phosphorus in the final state lower than that measured at the initial time. The reason for this may be due to the fact that the water movement caused by the oxygenation device promoted the release of nitrogen and phosphorus from the sediments in the relatively small-scale closed experimental environment. While in natural lakes, the input of organic matter occurs continuously due to phytoplankton growth (Zhang et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003e3.3.2. Density change of macrobenthos and correlation analysis of environmental factors\u003c/h2\u003e \u003cp\u003e(1) Changes in the density of various macrobenthic fauna\u003c/p\u003e \u003cp\u003eThe densities of \u003cem\u003eBellamya\u003c/em\u003e, \u003cem\u003eRadix auricularia\u003c/em\u003e, Annelida (mainly composed of \u003cem\u003eLimnodrilus\u003c/em\u003e and \u003cem\u003eTubifex\u003c/em\u003e) and \u003cem\u003eChironomus plumosus\u003c/em\u003e observed and counted in the final state of the experiment are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. The densities of \u003cem\u003eBellamya\u003c/em\u003e, except for the submerged \u0026times; floating plant group in the entrance area where the densities were significantly lower due to higher mortality rates, varied between 188.64 ind/m\u003csup\u003e2\u003c/sup\u003e and 264.10 ind/m\u003csup\u003e2\u003c/sup\u003e in each group. The biomass of \u003cem\u003eBellamya\u003c/em\u003e was absolutely dominant among the benthos of all experimental groups, while the density was only maximum in the submerged \u0026times; floating plant group in the entrance and wetland areas, and there was no absolute dominance. The density of \u003cem\u003eRadix auricularia\u003c/em\u003e was higher in the group with aquatic plants than in the group without, and its density peaked (877.7 ind/m\u003csup\u003e2\u003c/sup\u003e) in the group of the submerged \u0026times; floating plant coexisting in the original enclosure aquaculture area. Its density peaked at 877.19 ind/m\u003csup\u003e2\u003c/sup\u003e in the submerged \u0026times; floating plant group in the wetland area and was the second highest (377.29 ind/m\u003csup\u003e2\u003c/sup\u003e). The density distribution of \u003cem\u003eChironomus plumosus\u003c/em\u003e and \u003cem\u003eRadix auricularia\u003c/em\u003e showed some similarity, and \u003cem\u003eChironomus plumosus\u003c/em\u003e were observed only in the submerged \u0026times; floating plant group in the entrance area and the original enclosure aquaculture area, which also showed some dependence on aquatic plants.\u003c/p\u003e \u003cp\u003eThe density of the Annelida in each experimental group was original enclosure aquaculture area\u0026gt;entrance area\u0026gt;wetland area, and the density of the original enclosure aquaculture area without plant treatment group was the highest, which was 1490.28 ind/m\u003csup\u003e2\u003c/sup\u003e. The density of the Annelida in each experimental group in each functional area was significantly higher than that of the treatment group with plant growth, and the root growth of aquatic plants damaged the anaerobic environment at the sediment-water interface and within the sediments, increasing the dissolved oxygen concentration in the water and improving the water transparency. The root growth of aquatic plants destroyed the anaerobic environment at the sediment-water interface and inside the sediments, increased the concentration of dissolved oxygen in the water, and at the same time improved the transparency of the water body and the water quality (Li et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Yan et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The higher density of Annelida, which are fouling-tolerant species adapted to polluted water and anaerobic environments, was consistent with the results of the benthic field collection and analysis, and further verified their environmental adaptation characteristics.\u003c/p\u003e \u003cp\u003eThe difference in density of the four benthic species in the no-plant group in the entrance area was distinct, and the density of Annelida was dominant, only the difference in density of the four benthic species in the submerged plan group was reduced, and the difference in density in the submerged \u0026times; floating plant group was the smallest, due to the diversity of aquatic plants, which provided a complex habitat for the survival of benthic animals, and the benthic animals detected in a single habitat were more diverse, and the density distribution was more uniform. In the original enclosure aquaculture area, the density of benthos varied greatly among the three treatment groups, with Annelida being the dominant species in the no-plant and submerged plant groups, and \u003cem\u003eRadix auricularia\u003c/em\u003e dominating in the submerged \u0026times; floating plant group. On the contrary, there was little difference in the density of each benthic fauna in all three treatment groups in the wetland area, and none of them had a clear density-dominant species.\u003c/p\u003e \u003cp\u003e(2) Correlation analysis of environmental factors\u003c/p\u003e \u003cp\u003eThe correlation heatmaps of the pre- and post-experimental rates of change in biomass, final survival and final density of \u003cem\u003eBellamya\u003c/em\u003e and \u003cem\u003eRadix auricularia\u003c/em\u003e, and the final density of Annelida with the measured environmental factors are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. The three indices, rate of change in biomass, survival and final density of \u003cem\u003eRadix auricularia\u003c/em\u003e, were all significantly and positively correlated (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) with the Chl-\u003cem\u003ea\u003c/em\u003e concentration, while they were negatively or significantly negatively correlated with the TN and NO\u003csup\u003e3\u0026minus;\u003c/sup\u003e-N concentrations which relate to pollution(Xie et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The Chl-\u003cem\u003ea\u003c/em\u003e concentration in the water column was closely related to the presence or absence of aquatic plants, and there was no significant difference in the Chl-\u003cem\u003ea\u003c/em\u003e concentration among the same aquatic plant treatment groups in the three functional areas in this experiment, while there was a significant difference in the Chl-\u003cem\u003ea\u003c/em\u003e concentration among the different aquatic plant treatment groups, which were as follows: no-plant group\u0026lt;submerged plant group\u0026lt;submerged \u0026times; floating plant group. The growth condition of \u003cem\u003eRadix auricularia\u003c/em\u003e was better in the treatment group with aquatic plant growth than in the no-plant group, especially in the original enclosure aquaculture and wetland areas where the biomass and density of the submerged \u0026times; floating plant treatment group increased dramatically, and the survival rate was also the highest, thus showing a significant positive correlation with the Chl-\u003cem\u003ea\u003c/em\u003e concentration in the water column. The relationship between aqutic plant and \u003cem\u003eRadix auricularia\u003c/em\u003e with herbivory also play an important role on this phenomenon(Lv et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The water column TN and NO\u003csup\u003e3\u0026minus;\u003c/sup\u003e-N concentrations were also closely related to the presence or absence of aquatic plant distribution, and the TN and NO\u003csup\u003e3\u0026minus;\u003c/sup\u003e-N concentrations in the treatment group with aquatic plants were reduced due to plant uptake, and thus negatively correlated with the growth status of \u003cem\u003eRadix auricularia\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003cem\u003eBellamya\u003c/em\u003e grew better in most of the experimental groups, and densities also did not change significantly in any of the experimental groups, except for the submerged \u0026times; floating plant group in the entrance area, so the correlations between the three indicators and the environmental factors were not significant, in line with its high environmental adaptability. The density of Annelida was significantly correlated with both the water and sediment environments, and was significantly higher in the no-plant group than in the planted group. The Chl-\u003cem\u003ea\u003c/em\u003e concentration in the water body was low in the no-plant group, and the turbidity was significantly higher than that in the planted group, so the density of Annelida was significantly positively correlated with turbidity (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and negatively correlated with Chl-\u003cem\u003ea\u003c/em\u003e. The nitrogen concentration in the water body was significantly lower in the planted group than that in the no-plant group, while the concentration of TP and PO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e3\u0026minus;\u003c/sup\u003e-P were higher in the planted group, thus, the density of Annelida was positively correlated with the concentration of nitrogen, and negatively correlated with the concentration of TP and PO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e3\u0026minus;\u003c/sup\u003e-P. PO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e3\u0026minus;\u003c/sup\u003e-P concentration was significantly negatively correlated. Sediment nitrogen and phosphorus content also affected the density of Annelida significantly. The sediment nitrogen and phosphorus content in the original enclosure aquaculture area was significantly higher than that in the entrance and wetland areas, and the density of Annelida was also the highest in the original enclosure aquaculture area, and at the same time, the substrate particle size in the original enclosure aquaculture area was relatively small, so the density of Annelida in the original enclosure aquaculture area was the highest in the group of the treatment without plants.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003e(1) In the East Taihu Lake basin, \u003cem\u003eBellamya purificata\u003c/em\u003e, \u003cem\u003eLimnodrilus\u003c/em\u003e, and \u003cem\u003eTubifex\u003c/em\u003e were the dominant species on a year-round scale. Water depth was the most important environmental factor affecting the macrobenthic community, and other important factors in different seasons included water temperature, SD, TSS content, Chl-\u003cem\u003ea\u003c/em\u003e concentration, and nitrogen and phosphorus concentration.\u003c/p\u003e \u003cp\u003e(2) The growth of \u003cem\u003eBellamya\u003c/em\u003e was significantly worse in the modelled habitats of the entrance area than in those of the original enclosure aquaculture area and the wetland area, but was overall better adapted to the environment. The growth of \u003cem\u003eRadix auricularia\u003c/em\u003e was significantly better in the presence of aquatic plants than in the absence of plants, and was more significantly influenced by environmental factors closely related to aquatic plants. The densities of Annelida were significantly higher in the treatment group without plants than group with plants, showing the trend of the simulated original enclosure aquaculture area\u0026thinsp;\u0026gt;\u0026thinsp;the simulated entrance area\u0026thinsp;\u0026gt;\u0026thinsp;the simulated wetland area. It was mainly influenced by environmental factors such as turbidity and eutrophication index of the water, which was consistent with the results of the field survey.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003eThis work was financially supported by the National Special Item on Water Resource and Environment from Ministry of Science and Technology of China (2017ZX07603003). We also want to thank Dr. Changtao Yang for his strong assistance during the field sampling process.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution\u0026nbsp;\u003c/strong\u003eChangming Yang: Conceptualization, Field investigation, Methodology and Writing-review \u0026amp; editing; Shuhan Ding: Original draft, Writing-review \u0026amp; editing; Yangdan Niu: Lab experiment, Data collection, Formal analysis; Xiang Zhang: Data statistics and processing; Jianghua Li: Conceptualization, Methodology and Reviewing \u0026amp; editing. All authors edited the manuscript and approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding \u0026nbsp;\u003c/strong\u003eThis research was funded by Ministry of Science and Technology of China (2017ZX07603003).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability \u0026nbsp;\u003c/strong\u003eThe datasets analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests \u0026nbsp;\u003c/strong\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval \u0026nbsp;\u003c/strong\u003eAll authors have read, understood, and have complied as applicable with the statement on \u0026ldquo;ethical responsibilities of authors.\u0026rdquo;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eArscott, D., Tockner, K., Ward, J.V., 2003. Spatio-temporal patterns of benthic invertebrates along the continuum of a braided Alpine river. Arch. Hydrobiol. 158, 431\u0026ndash;460. https://doi.org/10.1127/0003-9136/2003/0158-0431.\u003c/li\u003e\n\u003cli\u003eBanagar, G., Riazi, B., Rahmani, H., Jolodar, M.N., 2018. Monitoring and assessment of water quality in the Haraz River of Iran, using benthic macroinvertebrates indices. Biologia (Bratisl.) 73, 965\u0026ndash;975. https://doi.org/10.2478/s11756-018-0107-5.\u003c/li\u003e\n\u003cli\u003eBeyene, A., Legesse, W., Triest, L., Kloos, H., 2009. Urban impact on ecological integrity of nearby rivers in developing countries: the Borkena River in highland Ethiopia. Environ. Monit. Assess. 153, 461\u0026ndash;476. https://doi.org/10.1007/s10661-008-0371-x.\u003c/li\u003e\n\u003cli\u003eBronk, D.A., Lomas, M.W., Glibert, P.M., Schukert, K.J., Sanderson, M.P., 2000. Total dissolved nitrogen analysis: comparisons between the persulfate, UV and high temperature oxidation methods. Mar. Chem. 69, 163\u0026ndash;178. https://doi.org/10.1016/S0304-4203(99)00103-6.\u003c/li\u003e\n\u003cli\u003eCai Y., Gong Z., Qin B., 2010. Community structure and diversity of macrozoobenthos in Lake Taihu,a large shallow eutrophic lake in China. Biodiv Sci 18, 50\u0026ndash;59. https://doi.org/10.3724/SP.J.1003.2010.050.\u003c/li\u003e\n\u003cli\u003eCai, Y., Xu, H., Vilmi, A., Tolonen, K.T., Tang, X., Qin, B., Gong, Z., Heino, J., 2017. Relative roles of spatial processes, natural factors and anthropogenic stressors in structuring a lake macroinvertebrate metacommunity. Sci. Total Environ. 601\u0026ndash;602, 1702\u0026ndash;1711. https://doi.org/10.1016/j.scitotenv.2017.05.264.\u003c/li\u003e\n\u003cli\u003eChatzinikolaou, E., Mandalakis, M., Damianidis, P., Dailianis, T., Gambineri, S., Rossano, C., Scapini, F., Carucci, A., Arvanitidis, C., 2018. Spatio-temporal benthic biodiversity patterns and pollution pressure in three Mediterranean touristic ports. Sci. 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Water Res. 245, 120579. https://doi.org/10.1016/j.watres.2023.120579.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-monitoring-and-assessment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emas","sideBox":"Learn more about [Environmental Monitoring and Assessment](http://link.springer.com/journal/10661)","snPcode":"10661","submissionUrl":"https://submission.nature.com/new-submission/10661/3","title":"Environmental Monitoring and Assessment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"East Taihu Lake, Macrobenthos, Aquatic plants, Environmental factors, Different functional areas","lastPublishedDoi":"10.21203/rs.3.rs-4756419/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4756419/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAs an important component of aquatic ecosystems, benthic animals are sensitive bioindicators for evaluating water pollution. In this study, we investigated the diversity of macrobenthic communities and analyzed the pivotal environmental factors affecting alterations in the macrobenthic communities of East Taihu Lake. This analysis was augmented by controlled laboratory simulation experiments designed to elucidate and validate the responses of critical indicator species within various functional zones to environmental shifts. This study shows:(1) \u003cem\u003eBellamya purificata\u003c/em\u003e, \u003cem\u003eLimnodrilus\u003c/em\u003e and \u003cem\u003eTubifex\u003c/em\u003e were the dominant species on a year-round scale. Water depth was the most important environmental factor affecting the macrobenthic communities;(2) Simulation experiments revealed that the growth condition of \u003cem\u003eBellamya\u003c/em\u003e was significantly worse in the simulated entrance area than in the simulated original enclosure aquaculture and wetland areas. The growth of \u003cem\u003eRadix auricularia\u003c/em\u003e was significantly better in the presence of aquatic plants than in the absence of plants, and was more significantly influenced by environmental factors closely related to aquatic plants. The densities of Annelida were significantly higher in the treatment group without plants than that with plants, generally showing the trend of the simulated original enclosure aquaculture area\u0026thinsp;\u0026gt;\u0026thinsp;the simulated entrance area\u0026thinsp;\u0026gt;\u0026thinsp;the simulated wetland area. The trend of diversity was mainly influenced by environmental factors such as turbidity and eutrophication index of the water, which was consistent with the results of the field survey.\u003c/p\u003e","manuscriptTitle":"Characteristics of Macrobenthic Communities and their Response to Environmental Changes in East Taihu Lake, China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-29 03:42:27","doi":"10.21203/rs.3.rs-4756419/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-09T13:45:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-04T18:02:11+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-19T10:57:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"316775894313655999104575746139410904322","date":"2024-09-16T08:33:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"173409319799589605318959262485903659569","date":"2024-09-12T11:56:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"282923401370910594616025586798009147881","date":"2024-09-11T12:25:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"28373761774449773010579787534062433546","date":"2024-09-11T08:42:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"125889634301231320152941763388946090727","date":"2024-09-09T23:53:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"175135490718890391655244753180854130159","date":"2024-08-14T08:32:26+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-14T08:23:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-02T06:14:12+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-02T06:12:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Monitoring and Assessment","date":"2024-07-17T12:59:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-monitoring-and-assessment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emas","sideBox":"Learn more about [Environmental Monitoring and Assessment](http://link.springer.com/journal/10661)","snPcode":"10661","submissionUrl":"https://submission.nature.com/new-submission/10661/3","title":"Environmental Monitoring and Assessment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"b02e6e02-7e3d-4d29-b4b9-f945e3bf0bbd","owner":[],"postedDate":"August 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-05-12T16:04:15+00:00","versionOfRecord":{"articleIdentity":"rs-4756419","link":"https://doi.org/10.1007/s10661-025-14084-5","journal":{"identity":"environmental-monitoring-and-assessment","isVorOnly":false,"title":"Environmental Monitoring and Assessment"},"publishedOn":"2025-05-09 15:57:08","publishedOnDateReadable":"May 9th, 2025"},"versionCreatedAt":"2024-08-29 03:42:27","video":"","vorDoi":"10.1007/s10661-025-14084-5","vorDoiUrl":"https://doi.org/10.1007/s10661-025-14084-5","workflowStages":[]},"version":"v1","identity":"rs-4756419","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4756419","identity":"rs-4756419","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}