Characteristics of the Zooplankton Community Structure in Shengjin Lake and Its Response to the Restored Aquatic Vegetation

Abstract

Macrophytes taxa composition determines microinvertebrates utilized as environmental indicators in freshwater ecosystems. This study was conducted in Shengjin Lake. In this lake, local communities have been practicing using sine fishing nets for fishing and this has a disrupting effect on macrophyte vegetation, even though it was the major for the disappearance of submerged vegetation before it was banned. As a result of this sine fishing net ban by the local authorities, the vegetation that had disappeared began to recover. Thus, this study investigated the role of architecturally differentiated macrophytes restoration effect on zooplankton communities’ diversity, abundance, and species composition; open water was used as a control. For this, the data were collected from different habitats via site 1 (open water) site 2, (free-floating), site 3 (emergent and submerged), site 4 (submerged), and site 5 (emergent) macrophytes. In the present study, the results demonstrated that the relative mean density of Rotifer was measured high which ranged from (219 ± 141–678 ± 401 ind L⁻¹), mainly dominated by Keratella cochlearis and Lecane cornuta species. Following Rotifera, Cladocera population density was reported high and ranged within (36 ± 6.2–262.5 ± 49.4 ind L⁻¹). The Cladocera group was dominated by Daphnia spp., Moina micura, Ceriodaphnia reticulata, and Chydorus latus species. Compared to Rotifer and Cladocera, Copepod community were recoded least with relative mean density ranged within (11.52 ± 2.22–85.5 ± 27 ind L⁻¹) and dominated by Microcyclops javanus, Thermodiaptomus galebi, and Sinocalanus doerrii species. From environmental variables and the zooplankton density relationship analyzed, the redundancy analysis (RDA) results indicated that Water Temperature, Chlorophyll a, Dissolved Oxygen, Total Phosphorus, and Ammonium Nitrogen were found the most influential variables on zooplankton communities. Stepwise regression correlation showed that Copepod and Cladocera were found more dependent on environmental factors. For instance, Nitrate Nitrogen was negatively correlated with Cladocera, Copepod, and total zooplankton biomass but positively with Cladocera diversity. Water Temperature showed a positive relationship with Rotifer diversity; however, both Chlorophyll a and Electrical Conductivity were correlated positively with Cladocera biomass. Species diversity by the Shannon–Wiener index (H) illustrated a dynamic trend among the monitored sites which ranged between (0.65–4.25). From the three groups of zooplankton communities in contrast to Cladocera and Copepod, Rotifer species obtained more diversity across the studied sites. The Cladocera diversity (H′) index indicated a similar tendency in all sites. However, more Copepod diversity (H′) was observed in site 4. In conclusion, this study results can provide valuable insights into the health and dynamics of the aquatic ecosystem to understand factors deriving ecological imbalance and develop an integrated approach for effective strategies for management and conservation.

1. Introduction

The rapid growth of human populations has resulted in significant environmental challenges such as eutrophication and climate change. These factors contribute to the degradation of aquatic ecosystems and biodiversity loss [1,2,3]. As a result, freshwater ecosystems are facing considerable habitat degradation and biodiversity loss compared to terrestrial and marine ecosystems [4]. Therefore, maintaining aquatic ecosystems in good status has become a critical challenge globally [5]. Further, Arora and Mehra [6] reported various human pressures are the main challenging issue in freshwater ecosystems to understand protection and conservation practices. Thus, conserving aquatic biodiversity and restoring degraded wetlands or creating new ones is becoming a global concern [7] to mitigate human impact activities [8]. Restoring degraded ecosystems can enhance biodiversity and ecosystem services, although the success of these efforts can depend on various factors including specific restoration action taken. For example, Sagrario et al. [9] found that lakes tend to shift to a turbid state in areas with low plant coverage when TN > 2 mg NL⁻¹ and TP > 0.13–0.2 mg PL⁻¹. These threshold values can vary depending on factors such as fish density and climatic conditions. This shift to a turbid state can influence the diverse range of flora and fauna supported in aquatic ecosystems integrated into human welfare [4]. Therefore, restoring aquatic ecosystems is crucial not only for the biodiversity supported within the systems but also for the well-being of human welfare depend on them. Zooplankton and phytoplankton structures, species diversity, and composition are important ecological indicators to understand ecological status [10]. Thus, monitoring the plankton population can provide valuable evidence to gain insight into aquatic ecosystems’ ecological status and detect early environmental changes. Further, Loick et al. [11] stated that zooplankton communities play a crucial role in reflecting freshwater ecosystems’ ecological status as they play a significant role in transferring energy from lower trophic organisms to higher ones and regulating phytoplankton growth [12]. However, due to their small size, short life span, and frequent species succession, zooplankton are highly sensitive to physicochemical changes and fish-feeding pressures in aquatic ecosystems [13]. Therefore, zooplankton diversity, composition change, and individual density are important indicators for ecological processes and environmental changes in routine monitoring studies [14].

Macrophyte vegetation can play a vital role in aquatic ecosystems by providing food and refuge for the zooplankton community from pelagic predators [15,16]. However, the availability of macrophyte plants as food sources and refuges for zooplankton depends on factors such as plant architecture, patch size, density, and the predators they host [16]. Therefore, it is important to understand how macrophyte plants interact with zooplankton communities’ structure to maintain ecosystem balance and ecological integration [17]. While most previous studies [11,15] exclusively considered submerged vegetation as a refuge for zooplankton [18,19], reported emergent and freely floating macrophytes also play a significant role in reducing zooplankton visibility to predators, particularly in turbid lakes where submerged plants are limited or absent. This variation in the scientific gap needs emphasis to understand the role of different macrophyte plants for the development of effective restoration strategies to rehabilitate degraded aquatic ecosystems. Thus, the present study emphasized the interaction between different macrophyte plants and zooplankton community structure. In particular, this study was conducted in Shengjin Lake connected to the Yangtze River. Since 2008, this lake has been under a restoration program by banning sine fishing nets to restore disappeared vegetation especially submerged macrophytes [20]. As a result, the degraded ecosystem and disappeared vegetation have begun recovering. This action has been designed to manipulate the physical, chemical, and biological features of the lake to recover the natural and historical function of the former wetland vegetation. The Zooplankton community’s structure has been used as an excellent indicator for assessing restoration success and enhancing our understanding of restoration and community ecology [21,22]. In this area, Dibar et al. [23] conducted the effect of macrophyte restoration on ecological stoichiometric characteristics of Carbon (C), Nitrogen (N), and Phosphorus (P) in leaf, root, stem, and soil in four wetland plant communities after the ban of sine fishing net. As of our knowledge, no previous study was conducted to assess the effect of restored macrophytes and their response to zooplankton communities in this lake. Thus, the current study may provide good insight into the effect of the macrophyte restoration efforts to understand the current ecological status in this region. Therefore, the main objectives of this study were as follows: (1) to examine zooplankton distribution and species composition in rehabilitated macrophytes and open water; (2) to assess the relationship between environmental variables and zooplankton communities in different areas with various macrophytes community composition with open water being used as a control.

2. Materials and Method

2.1. Study Area Description

This study was conducted in Shengjin Lake located at (30°16′–30°25′ N, 116°59′–117°12′ E) in Anhui Province, China (Figure 1). The lake is connected to the Yangtze River on the southern bank and covers an area of 109.3 km² during the wet seasons and 33 km² in the dry seasons. During the peak flooding, the lake area can expand approximately to 14,000 hectares (17.0 m above sea level). Nevertheless, as the water level typically drops to below 10 m above sea level during the dry season; it reduces its area to around 3400 hectares. The lake depth is ranged from 4.89 m to 5.9 m. In addition, the Yangtze River, namely the Huangpen Sluice, is receiving inflow from three small rivers flowing into it directly. The region experiences an average annual rainfall of 1600 mm, mostly from March to August and its annual temperature is ranged from 16.1 to 4.0 °C in January. In addition, this lake is surrounded by various terrains with Low Mountain that cause water level fluctuations which attain peak points mostly in July month.

2.2. Sampling Procedures and Experimental Design

The sampling campaign was carried out in the summer season of August 2019, when the targeted restoring vegetation was flourishing in the studied region. For this purpose, five sampling sites dominated by different vegetation groups were selected from ecological restoration areas (Figure 1). In addition to recovered plant sites, one open-water site was selected as a control for this study. In addition to the control site without vegetation, those sites with re-vegetated plants were classified with the list of plant species they contain as follows: site 2 contains freely floating plants, such as Euryale ferox and Trapa bispinosa; site 3 contains mixed emergent and submerged plants, namely Nymphoides peltatum and Vallisneria natans; site 4 contains submerged plants, namely Ceratophyllum demersum and Ceratophyllum spectrum); and site 5 contains emergent plants, namely Phragmites australis and Zizania latifolia. While identifying different vegetation groups in ecological life forms and species in particular sites, minor species found within these re-vegetated groups were excluded from consideration. Macrophyte occurrence and plant abundance were estimated as percent volume invested (PVI), and calculated by multiplying the percentage coverage by macrophytes (visually estimated) by the pant height and WD after [24] as: $PVI\left(\%\right)=MacC\times MacL/D$, where MacC denotes the macrophyte coverage (%) of each species per site, MacL is the macrophyte length (m), and D is sampling site depth (m). For macrophyte, and taxonomic identification [25] aquatic vegetation identification key has been used during data collection. To rehabilitate degraded ecosystems and recover the ecological functions of macrophyte plants in Shengjin Lake, the restoration activity was started in 2008 by banning sine fishing by the local authorities. This project has been carried out in two ways to recover the impacted areas. One is artificially restoring a degraded site designated as site 2 in the sampling location. In this site, the vegetation coverage was light and mainly composed of freely floating (E. forex, and T. bispinosa) vegetation community and without marginal vegetation. The rest sampling sites are rehabilitating areas where the vegetations are recovered naturally following the ban of sine fishing nets and are classified as site 3, site 4, and site 5. In these sampling sites, the area coverage and ecological life form of the vegetation under ecological restoration are different in composition. In each site, the macrophyte taxa areal coverage shows variation. For instance, in contrast to site 2 and site 3 which contain sparse vegetation in area coverage, site 4 and site 5 are denser. The PVI of those vegetations ordered in percentage as, in site 2 T. bispinosa covered 80% and E. forex 40%, whereas in site 3, N. pelatatum 40% and V. natans 55% while in site 4 M. verticillatum covered 70% and C. demersum 50%, and site 5 P. australis covered 70% and Z. latifolia 40%, respectively (Table 1).

Table 1. Description of macrophyte community taxa per sampling stations in Shengjin Lake.

Sites	Common Name	Scientific Species Name	Dominant Macrophyte Taxa	Macrophyte Abundance	Ecological Life Forms
Site 1	-	-	-	-	-
Site 2	Foxnut	Euryale ferox. Salisb.	Euryale ferox Salisb.	Abundant	Freely floating
	Water chestnut	Trapa bispinosa Roxb.		Spars
Site 3	Yellow floating heart	Nymphoides peltatum (Gmel.)		Spars	Emergent
	Eelgrass	Vallisneria natans L.	Vallisneria natans L.	Abundant	submerged
Site 4	Coontail (rigid hornwort)	Ceratophyllum demersum Lenn.	Ceratophyllum demersum Lenn.	Abundant	submerged
	Eurasian watermilfoil	Myriophyllum spicatum L.		Spars
Site 5	Common reed	Phragmites australis	Phragmites australis	Abundant	Emergent
	Wild rice	Zizania latifolia		Spars

Table 1. Description of macrophyte community taxa per sampling stations in Shengjin Lake.

Sites	Common Name	Scientific Species Name	Dominant Macrophyte Taxa	Macrophyte Abundance	Ecological Life Forms
Site 1	-	-	-	-	-
Site 2	Foxnut	Euryale ferox. Salisb.	Euryale ferox Salisb.	Abundant	Freely floating
	Water chestnut	Trapa bispinosa Roxb.		Spars
Site 3	Yellow floating heart	Nymphoides peltatum (Gmel.)		Spars	Emergent
	Eelgrass	Vallisneria natans L.	Vallisneria natans L.	Abundant	submerged
Site 4	Coontail (rigid hornwort)	Ceratophyllum demersum Lenn.	Ceratophyllum demersum Lenn.	Abundant	submerged
	Eurasian watermilfoil	Myriophyllum spicatum L.		Spars
Site 5	Common reed	Phragmites australis	Phragmites australis	Abundant	Emergent
	Wild rice	Zizania latifolia		Spars

2.3. Limnological Variables and Zooplankton Data Collection

For water quality analysis, the samples were collected from re-vegetated and sites without vegetation to understand the effect of restored macrophyte vegetation on water quality parameters in line with the designed objective. The samples were collected to analyze Total Nitrogen, Nitrate Nitrogen, Ammonium Nitrogen, Total Phosphorus, and Chlorophyll concentration, as described by [26]. Before collection, the sampling bottles were washed with phosphate-free detergent and rinsed with 10% hydrochloric acid and de-ionized water, respectively. The samples were collected in polyethylene sampling bottles and preserved by adding 1 mL of concentrated sulfuric acid to lower the pH below 2 standard units. After the samples had been collected, the sampling bottles were overturned several times to ensure the mixing of the preservative with the samples. The preserved samples were placed in an icebox at 4 °C for transportation to be analyzed in the laboratory [26]. From the preserved samples, the nutrient concentration analysis was performed within 24 h. Among the nutrient contents analyzed, Ammonium Nitrogen was measured using a spectrophotometer at 640 nm wavelength following [26]. After absorbance, the calibration curve was plotted against deionized water used as a blank reference. In the same manner, the concentration of Nitrate Nitrogen was also measured using a spectrophotometer, and its absorbance was taken from 220 to 275 nm wavelength for both samples and blank. In addition, to determine Total Nitrogen contents, the absorbance was taken at 410 nm and a standard curve was plotted from absorbance versus concentration from blank following the [26] method. For Total Phosphorus concentration analysis, the Ascorbic acid method was applied. For this, the sample absorbance was conducted at 880 nm wavelength using a UV spectrophotometer, and a calibration curve was prepared from a serious standard. For all nutrient content analyses carried out, de-ionized water was used as a blank. Chlorophyll concentration was measured after the sample was filtered through GF/F (0.25 µm pore) fiberglass Whatman and stored at −20 °C. After storing the sample for 24 h, the pigment was extracted using 90% ethanol solvent and then centrifuged to separate the pigments [27]. The measurement of Chlorophyll concentration was conducted at 750 and 665 nm using a spectrophotometer [27] protocol. In contrast to the nutrients and Chlorophyll concentration, water quality physical parameters like Dissolved Oxygen, Water temperature, pH, Electrical Conductivity, Secchi disk, and Turbidity data were measured on-site using a portable probe [26]. In the same manner, the depth of each sampling site was measured on-site using a Secchi disk meter.

For zooplankton analysis, the water samples were collected using a plankton net (No. 25) with 64 μm mesh size. To analyze Rotifer species, water samples were collected in 1 L plastic sample bottles [28] whereas, for crustacean communities, 10 L water samples were filtered and concentrated in 50 mL plastic bottles [29,30]. The collected water samples were immediately preserved in a 4% formaldehyde solution in the field [30] and the subsample was examined from two counts of 1 mL samples. The sample was preserved for 48 h. After 48 h, the upper layer of the sample was discarded while the remaining bottom part was used for quantitative species counting. Species counting was conducted under a light microscope (Olympus (Tokyo, Japan), BX53) at 40× magnification powers [31]. For species identification [32] identification keys were used for Cladoceran, Copepod, and Rotifer identification. Micro zooplankton (nauplii and Rotifer) were counted by pipetting the subsamples on 1 mL Sedgwick–Rafter chambers (SRC) using the Hensen–Stempel pipette. A 5 mL Bogorov chamber was used for Macro zooplankton (Copepod and Cladocera) species counting. During the counting procedure, more than 300 individual species were encountered in a sample and an additional subsample was examined based on the availability of animals [31]. The encountered species was expressed in individual per litter (ind/L) as D $=$ $V1$, where D denotes the relative density of encountered species per cubic meter, N is the counted individual species, V is the analyzed concentrated sample in volume, and V1 represents the sample before concentration. In addition, in the present study, zooplankton biomass was expressed as (mg/m³), after estimating as $B=W/V$, where B is zooplankton biomass (mg), W is the weight of the sample, and V is the volume of filtered water (m³).

2.4. Statistical Treatment

A one-way analysis of variance (ANOVA) with Tukey’s post hoc test was used to assess statistically significant differences in environmental variables and plankton communities. To determine the most influential environmental variables affecting plankton populations, redundancy analysis (RDA) was conducted using CANOCO for Windows version 4.5 [33,34] with forward selection and 499 unrestricted Monte Carlo permutations to identify the key environmental variables influencing plankton community composition. Zooplankton data were analyzed using detrended correspondence analysis (DCA) [35] to examine the correlation between environmental variables and zooplankton populations, determining the gradient lengths for the two axes before performing RDA. Stepwise regression analysis was conducted to correlate environmental variables with zooplankton diversity indices and biomass across the study sites. The Monte Carlo permutation test was used to test the significance of the eigenvalues of the first and all ordination axes.

To standardize the dataset and minimize the impact of extreme values on ordination scores, environmental variables, and species counts were transformed to [log10(x + 1)] prior to statistical analysis. The Shapiro–Wilk test was used to assess normality. Discrepancies in environmental indicators among the five sampling stations were compared using the Kruskal–Wallis nonparametric test. To analyze zooplankton community structures univariate indices, Shannon Weiner (H) and species richness (D) have been used to assess the distribution of individual taxa among the studied sites given as follows: $\mathrm{H}=-\sum \mathrm{p}\mathrm{i}\ast \mathrm{l}\mathrm{n}\left(\mathrm{p}\mathrm{i}\right)$, where pi is the proportion of species i relative to the total number of species encountered and ln (pi) is the natural logarithm. The species richness (D) has been estimate as follows:

$$D=\sum _{\mathrm{I}=1}^{\mathrm{S}}{\left({\displaystyle \frac{\mathrm{n}\mathrm{i}}{N}}\right)}^2$$

where ni denotes the number of individuals in species i, N = total number of individuals of all species, ni/N = pi (proportion of individuals of species i), and S = species richness. Statistical significance was set at p < 0.05. All graphs were created using GraphPad Prism version 5 (http://www.graphpad.com, accessed on 18 October 2022), and all statistical analyses were performed using IBM SPSS Statistics version 20.0 (http://www.ibm.com, accessed on 25 November 2022).

3. Result

3.1. Environmental Parameters

The analyzed physicochemical variables across the studied sites have been reported in (

Table 2. Overall limnological characteristics summary along the studied sites in Shengjin Lake with (Mean ± SD).

Variables	Site 1	Site 2	Site 3	Site 4	Site 5
TN (mg L−1)	1.85 ± 0.49 *	1.68 ± 0.67 *	1.3 ± 0.29 *	0.71 ± 0.55 *	1.06 ± 0.84 *
NO3-N (mg L−1)	1.32 ± 0.25	0.113 ± 0.32 *	0.12 ± 0.015 *	0.037 ± 0.031 *	0.059 ± 0.03 **
NH4-N ((mg L−1	0.718 ± 0.231 *	0.077 ± 0.055 *	0.0117 ± 0.12 *	0.017 ± 0.156 *	0.039 ± 0.03 *
TP (mg L−1)	0.146 ± 0.145 *	0.036 ± 0.033 *	0.028 ± 0.035 *	0.018 ± 0.002 *	0.107 ± 0.015 *
WT (°C)	31.7 ± 1.53 *	28.6 ± 0.15 *	25.4 ± 0.5	19.9 ± 1.762 **	22.13 ± 0.59 *
EC (µS cm−3)	190 ± 0.53 **	164.9 ± 13.6 *	128.5 ± 0.96	114.9 ± 0.31 **	185.3 ± 32.3 *
SD (m)	0.417 ± 0.202 *	27.9 ± 4.02	53. ± 3.05 *	64.7 ± 10.02 *	69 ± 9.8 *
Chl.a (µg L–l)	14.08 ± 2.72 *	4.24 ± 1.24	4.25 ± 0.69 **	2.56 ± 2.74 **	4.56 ± 1.49 *
Trub (NTU)	66.87 ± 7.2	15.67 ± 2.8 *	9.4 ± 1.72 *	5.38 ± 0.8 *	24.13 ± 1.06
DO (mg L−1)	4.67 ± 0.038	9.54 ± 1.42 *	6.75 ± 2.4 **	8.24 ± 1.7	6.16 ± 0.051 **
pH	5.98 ± 1.54 *	3.48 ± 0.42	7.31 ± 1.31 *	7.62 ± 0.04	6.75 ± 0.19
WD (m)	0.92 ± 0.854 *	3.97 ± 0.73	8.41 ± 0.50 *	1.52 ± 0.05 *	2.9 ± 0.035

Note: Significant difference * p < 0.05, ** p < 0.01 (2-tailed). TN, Total Nitrogen; NO₃-N, Nitrate Nitrogen; NH₄-N, Ammonium Nitrogen; TP, Total Phosphorus; WT, Water Temperature; EC, Electrical Conductivity; SD, Secchi disk; Chl.a, Chlorophyll a; Trub, Turbidity; DO, Dissolved Oxygen; pH, pH concentration; WD, Water Depth.

). The results demonstrated that the mean values of Water Temperature ranged from (19.9 ± 1.76 °C) to (31.7 ± 1.53 °C), while the concentration of Dissolved Oxygen was recorded between (4.01 ± 1.01 mg L⁻¹) to (15.32 ± 4.41 mg L⁻¹) with statistically significant difference (p < 0.05). Among the five studied sites in this region, the highest Water Temperature was observed at site 1 (open water), whereas the highest Dissolved Oxygen level was measured in sites 2 and 4. Water Transparency and Turbidity values ranged from (0.417 ± 0.202 m) to (69 ± 9.8 m) and (5.38 ± 0.3 NTU) to (66.87 ± 7.2 NTU), where high Water Transparency but low Turbidity values were recorded in the site without vegetation. In spite of Turbidity, only Water Transparency shows statistically significant differences (p < 0.05). The presence and type of vegetation can greatly influence nutrient dynamics in aquatic ecosystems. For instance, the concentration of Total Nitrogen ranged between (0.71 ± 0.55 mg L⁻¹) and (1.85 ± 0.49 mg L⁻¹), whereas, Nitrate Nitrogen was measured from (0.059 ± 0.03 mg L⁻¹) to (1.32 ± 0.25 mg L⁻¹). High Total Nitrogen and Nitrate Nitrogen concentrations were measured in the open water with statistically significant differences (p < 0.05). On the other hand, as in Water Temperature, the concentration of Total Phosphorus was observed high in the site without vegetation with (0.146 ± 0.145 mg L⁻¹) but low in site 2, (0.036 ± 0.033 mg L⁻¹) with significant statistical differences (p < 0.05). In the same manner as Total Phosphorus, the level of Chlorophyll a was measured high in the site without vegetation but observed low in site 3 with statistically significant differences (p < 0.05). The pH value ranged from (3.48 ± 0.42 to 7.62 ± 0.04) with statistically significant differences in sites 1 and 4 (p < 0.05). On the other hand, the values of Electrical Conductivity ranged from (114.9 ± 0.31 µS/cm to 190 ± 0.53 µS/cm).

3.1.1. Zooplankton Distribution in Open Water and Vegetated Macrophyte Zones

Out of the 253 zooplankton species observed across all studied sites, 105 Rotifer, 63 Copepods, and 85 Cladoceran species were recorded. Among the studied sites in this study region, the dominant zooplankton groups show variation spatially except Cyclopoid nauplii. For instance, the mean density of Cladocera ranged from (36 ± 6.2) to (262.5 ± 49.4 ind L⁻¹) (Figure 2). In this study, species that contributed at least 20% of the total abundance were considered dominant. Accordingly, in comparison with other species encountered, the Cladoceran community was dominated by Daphnia cucullata (G.O.Sars) species in site 1 (open water) while Daphnia longispina (O.F.Müller) and Moina micura (Kurz) species showed maximum contributions in site 3. In the same trend, Chydrous latus (Sars) species was found dominant in sites 4 and site 5. In addition, Ceriodaphnia reticulata (Jurine) and Chydrous latus (Sars) species were recorded high in site 5. On the other hand, Daphnia galeata (Sars) was found commonly recorded species in all sites except in sites 1 and site 2. The mean density of Copepods ranged from (11.52 ± 2.22) to (85.5 ± 27 (ind L⁻¹), where the highest mean density was observed in sites 3 and 5 (Figure 2). Except in site 3, where Microcyclops javanus (Kiefer) showed a high contribution as a frequently observed species, Thermodiaptomus galebi (Barrois) and Sinocalanus dorrii (Brehm) species were recorded as a commonly encountered species in the remaining sites. Among the three zooplankton groups, Rotifer showed higher mean density than Copepods and Cladoceran, ranging from (219 ± 141 to 678 ± 401 ind L⁻¹). This group was mainly dominated by Keratella cochlearis (Gosse), Lecane cornuta (Müller), Brachionus forficula (Wierzejski), Filinia longiseta (Ehrenberg), and Monostyla bulla (Gosse) species. From these dominant species recorded, Kartella cochlearis (Gosse), and Lecane cornuta (Müller) species were registered as common species in all sites. From the five sites studied, high Rotifer abundance was recorded in open water rather than vegetated. The Rotifer group contributed more than 50% of the zooplankton community in sites 3 and 4. In addition, this group was recorded more in all studies site part from site 2, the site covered by floating macrophyte vegetations (Figure 3).

The spatial variation in zooplankton density shows statistically significant for Cladoceran (F = 28.29, p = 0.013), Copepods (F = 1953, p = 0.012), Rotifer (F = 10.22, p = 0.049), and total zooplankton (F = 7875.51, p = 0.003), along the studied sites. The result of zooplankton biomass shows inconsistent results across the sampling areas (Figure 3). For instance, from the two micro-crustacean groups, Cladocera biomass was measured high relatively (

Table 3. The Spatial mean biomass (mg/m³) variation in total zooplankton and the three subgroups of microinvertebrates among five stations in Shengjin Lake.

	Site 1	Site 2	Site 3	Site 4	Site 5
Rotifer	40	30	45	76	39
Copepods	16	17	24	47	30
Cladocera	42	30	64	98	37
Total zooplankton biomass	102	128	335	385	341

The data are the average of five sampling sites.

and

Table 4. Summary of redundancy analysis result (RDA) between zooplankton community and environmental variables (p < 0.05).

Axes	1	2	3	4	Total Variance
Eigenvalues	0.572	0.378	0.038	0.011	1.000
Species–environment correlations	0.962	0.902	0.952	0.867
Cumulative percentage variance of species data	57.2	69.1	89.6
Cumulative percentage variance of species–environment relation	74.5	83.9	86.4	97.5
Sum of all eigenvalues					1.000
Sum of all canonical eigenvalues					0.879

). Spatially, high Cladoceran biomass was registered in sites 3 and 4, respectively, but low in site 1 used as a control in this study (Table 3). The lists of the most dominant zooplankton species identified in the current study have been given in

Table 5. The lists of dominant zooplankton species identified during the current study in Shengjin Lake.

Phylum	Family	Genera	Species
Rotifer	Brachionidae	Anuraeopsis	Anuraeopsis fissa (Gosse, 1851)
	Gastopodidae	Ascomorpha	Ascomorpha ecaudis (Perty, 1850)
			Ascomorpha ovalis (Bergendal, 1892)
	Asphalnchnidae	Aspalnchna	Aspalnchna brightwellii (Gosse, 1850)
			Asplanchna girodi (Guerne, 1888)
	Barchionidae	Barchionus	Barchionus angularis(Gosse, 1851)
			Barchionus forficula (Wierzejski, 1891)
			Brachionus calyciflorus(Pallas, 1766)
			Brachionus caudatus (Barrois & Daday, 1894)
			Brachionus falcatus (Zacharias, 1898)
			Brachionus forficula(Wierzejski, 1891)
			Brachionus leydigi (Cohn, 1862)
			Brachionus patulus (Müller, 1786)
			Brachionus urceus (Pallas, 1766)
	Notommatidae	Cephalodella	Cephalodella catellina (Müller, 1786)
	Collothecidae	Collotheca	Collotheca pelagica (Rousselet, 1893)
	Conochilidae	Conochilus	Conochilus unicornis (Rousselet, 1892)
	Euchlanidae	Euchlanis	Euchlanis dilatata (Ehrenberg, 1832)
	Filiniidae	Filinia	Filinia cornuta (Weisse 1847)
			Filina terminalis (Plate,1886)
			Filinia longiseta (Ehrenberg, 1834)
			Filinia passa (O.F. Muller, 1786)
	Hexarthridae	Hexarthra	Hexarthra mira (Hudson, 1871)
	Brachionidae	Keratella	Keratella cochlearis (Gosse, 1851)
			Keratella quadrata (Müller, 1786)
			Keratella serrulata (Ehrenberg, 1838)
			Keratella tecta (Gosse, 1851)
			Keratella valga(Ehrenberg, 1834)
			Keratella tropica (Apstein, 1907)
	Lapdellidae	Lapdella	Lapdella patella (Müller, 1773)
	Lecaniidae	Lecane Nitzsch	Lecane luna (Müller, 1776)
			Lecane closterocerca (Schmarda, 1859)
			Lecane ludwigii (Eckstein, 1883)
			Lecane ungulata (Gosse, 1887)
			Lecane lunaris (Ehrenberg,1832) Lecane furcata (Murray, 1913)
		Monostyla	Monostyla bulla (Gosse, 1851)
			Monostyla copies (Harring & Myers, 1926)
			Monostyla lunaris (Ehrenberg,1832)
			Monostyla clostercerca (Schmarda, 1859)
	Brachionidae	Notholca	Notholca accuminata (Ehrenberg,1832)
			Notholca caudate (Carlin, 1943)
			Notholca labis (Gosse, 1886)
			Notholca longispina (Kellicott, 1879)
	Hexarthridae	Hexarthra Schmarda	Pedalia mira (Hudson, 1871)
	Synchaetidae	Ploesoma	Ploesoma hudsoni (Imhof, 1891)
		Ploesoma Herric	Ploesoma truncatum (Levander, 1894)
		Polyarthra	Polyarthra euryptera (Wierzejski, 1891)
	Testudinellidae	Pompholyx	Pompholyx sulcata (Hudson, 1885)
	Philodinidae	Rotaria Scopoli	Rotaria neptunia (Ehrenberg, 1832)
	Synchaetidae	Synchaeta Ehrenberg	Synchaeta stylata (Wierzejski, 1893)
			Synchaeta pectinata (Ehrenberg, 1832)
	Trichocercidae	Trichocera	Trichocera pusilla (Jennings, 1903)
	Trichocercidae	Trichocera	Trichocerca longiseta (Schrank, 1802)
			Trichocerca similis (Wierzejski, 1893)
			Trichocerca turnacata (Müller, 1776)
			Trichocerca bicristata (Gosse, 1887)
	Cyclopidae	Acanthocyclops Kiefer	Acanthocyclops robustus (Sars G.O., 1863)
	Macrothricidae	Acantholeberis Lillijborg	Acantholeberis curvirostris (O.F.Müller, 1776)
	Chydoridae	Alona	Alona affinis (Leydig, 1860)
Cladocera		Alona baird	Alona bicolor (Frey, 1965)
			Alona costata (Sars, 1862)
			Alona guttata (G.O. Sars, 1862)
		Alona	Alona rectangular (G.O. Sars, 1862)
		Alonella	Alonella exigua (Lilljeborg, 1853)
			Alonella nana (Baird, 1843)
		Alonopsis	Alonopsis americana (G.O. Sars, 1862)
	Bosiminidae	Bosmina	Bosmina coregoni (Baird,1857)
			Bosmina fatalis (Burckhardt, 1924)
			Bosmina longispina (Leydig, 1860)
			Bosminopsis deitersi (Richard, 1895)
			Bosmina longirostsis (O.F. Müller, 1785)
	Daphniidae	Ceriodaphnia	Ceriodaphnia cornuta (G.O. Sars, 1885)
			Ceriodaphnia dubia (Richard, 1894)
			Ceriodaphnia laticaudata (P.E.Müller, 1867)
			Ceriodaphnia cornuta (G.O. Sars, 1885)
			Ceriodaphnia longispina (O.F. Müller, 1776)
			Ceriodaphnia quadrangula (O.F. Müller, 1785)
	Chydoridae	Chydorus	Chydorus sphaericus (O.F. Müller, 1776)
			Chydrous latus (Sars, 1862)
			Chydorus bicornutus (Doolitle, 1909)
	Daphniidae	Daphnia	Daphnia cucculata (G.O. Sars, 1862)
			Daphnia duplex (Leydig, 1860)
			Daphnia galeata (Sars, 1864)
			Daphnia longispina (O.F. Müller, 1776)
			Daphnia magna (Straus, 1820)
			Daphnia Sarsi (O.F.Müller, 1785)
			Daphnia dubia (Herrick, 1883)
	Sididae	Daphinosoma	Diaphanosoma brachyurum (Liévin, 1848)
	Diaphniidae	Diaphnia	Diaphina pulex (Leydig, 1860)
			Daphnia carinata (King, 1853)
	Eurycercidae	Eurycercus	Eurycercus lamellatus (O.F.Müller, 1776)
	Chydoridae	Kurzia	Kurzia latissima (Kurz, 1875)
	leptodoridae	leptodora	Leptodora kindtii (Focke, 1844)
	Chydoridae	Leydigia	Leydigia acanthocercoides (Fischer, 1854)
	Moinidae	Moina	Moina affinis (Birge, 1893)
			Moina micura (Kurz, 1875)
	Chydoridae	Peluroxus	Pleuroxus trigonellus (O.F.Müller, 1776)
	Barchionidae	Platyias	Platyias quadricornis (Ehrenberg, 1832)
	Chydoridae	Pleuroxus	Picripleuroxus denticulatus (Birge, 1879)
			Pleuroxus hamulatus (Birge, 1879)
			Pleuroxus striatus (Schödler, 1862)
			Pleuroxus trigonellus (O.F.Müller, 1776)
	Daphniidae	Scapholeberis	Scapholeberis mucronata (O.F.Müller, 1776)
	Sididae	Sida	Sida crystallina (O.F.Müller, 1776)
	Daphniidae	Simnocephalus	Simocephalus vetulus (O.F.Müller, 1776)
			Simocephalus serrulatus (Koch, 1841)
	Cyclopidae	Acanthocyclops	Acanthocyclops vernalis (Fischer, 1853)
			Acanthocyclops formosanus (Harada, 1931)
Copepods	Canthocamptidae	Afrocamptus	Canthocamptus (Westwood, 1836)
	Cyclopidae	Cyclops Müller	Cyclops strenuus (Fischer, 1851)
			Cyclops vicinus (Ulyanin, 1875)
		Cyclops	Eucyclops elegans (Herrick, 1884)
			Eucyclops serrulatus (Fischer, 1851)
			Eucyclops agilisEucyclops agilis (Koch, 1838)
			Eucyclops macruroides (Lilljeborg, 1901)
	Temoridae	Eurythemora Giesbrecht	Eurytemora affinis (Poppe, 1880)
	Cyclopidae	Homocyclops Forbes	Homocyclops ater (Herrick,1882)
	Diaptomidae	Leptodiaptomus Light	Leptodiaptomus minutus (Lilljeborg, 1889)
	Centropagidae	Limnocalanus m	Limnocalanus macrurus (Sars G.O., 1863)
	Diaptomidae	Acanthodiaptomus Kiefer	Leptodiaptomus sicilis (Forbes S.A., 1882)
		Macrocyclops	Macrocyclops albidus (Jurine, 1820)
			Macrocyclops distinctus (Richard, 1887)
		Mesocyclops	Mesocyclops leuckarti (Claus, 1857)
			Mesocyclops ogunnus (Sars G.O.1914)
			Microcyclops javanus (Kiefer, 1930)
		Microcyclops	Microcyclops vericanas (Sars G.O., 1863)
	Nannopodidae	Nannopus	Nannopus palustris (Brady, 1880)
	Laophontidae	Onychocamotus	Onychocamptus mohammed (Blanchard & Richard, 1891)
	Cyclopidae	Orthocyclops	Orthocyclops modusta (Herrick, 1883)
		Paracyclops	Paracyclops affinis (Sars G.O., 1863)
	Pseudodiaptomidae	Archiaptomus	Schmackeria inopinus (Burckhardt, 1913)
	Centropagidae	Sinocalanus	Sinocalanus doerrii (Berhm.1909)
	Diaptomidae	Sinodiaptomus	Sinodiaptomus sarsi (Rylov, 1923)
		Skistodiaptomus	Skistodiaptomus oregonensis (Lilljeborg in Guerne and Richard, 1889)
		Mesocyclops	Thermocyclops brevifurcatus (Harada, 1931)
	Cyclopidae	Thermocyclops	Thermocyclops minutus (Lowndes, 1934)
			Thermocyclops neglectus (Sars G.O., 1909)
			Thermocyclops taihokuensis (Harada, 1931)
	Cyclopidae	Thermocyclops	Thermocyclops vermifer (Lindberg, 1935)
		Thermodiaptomus	Thermodiaptomus galebi (Barrois, 1891)
		Tropocyclops	Tropocyclops prasinus (Fischer, 1860)

.

3.1.2. Species Diversity Index

A multivariate analysis of spatial variation in species diversity using the Shannon–Wiener index (H) showed dynamic trends among the monitored sites with statistically significant differences (F = 6.12, p < 0.05). From the three zooplankton subgroups, the Shannon–Wiener diversity index (H′) ranged from 0.65 to 4.25, where Rotifera species was found more diverse than Cladocera and Copepods with significant differences (t = 9.73, p = 0.001) (Figure 4). Despite Cladoceran diversity showing a similar trend in all sampling sites with statistically significant differences (t = 3.93, p = 0.017), zooplankton diversity result was measured low in the site without vegetation. In contrast, Cladoceran diversity shows insignificant variation across the sample sites, Copepod diversity (H′) was measured high in site 4. In the same manner, species richness variation analyzed results among three zooplankton groups have given with the overall zooplankton population (Figure 5).

3.1.3. The Relationship Between Zooplankton Community and Environmental Variables

The summary of environmental factors’ relationship with the relative density of dominant zooplankton species from the redundancy analysis (RDA) output is provided in (Table 4). The first two RDA axes of the environmental and zooplankton linear combination accounted for 69.1% of the variance in zooplankton assemblage data. Axis 1 explained 57.2% of the zooplankton data. Among the environmental variables, Axis 1 showed strong correlations with Water Temperature (−0.6949), Chlorophyll a (−0.6707), Electrical Conductivity (0.640), and Total Phosphorus (−0.8765). Axis 2 explained 37.8% of the zooplankton community and correlated with Dissolved Oxygen (0.809), Ammonium Nitrogen (−0.7739), Turbidity (0.7076), and Water Depth (−0.5078). The relationship between the relative density of zooplankton and environmental variables from the first two axes is illustrated in Figure 6. The analyzed relationship result shows that Monia micura (MM) and Chydrous latus (CL) were positively correlated with Ammonium Nitrogen (NH₄-N) and Water Temperature, and negatively correlated with Dissolved Oxygen and Water Depth. Brachionus forficula (BF) was negatively correlated with Total Nitrogen. But, Daphnia cucullata (DC) and Daphnia longispina (DL) showed strong associations with Total Phosphorus, Electrical conductivity, and pH, respectively. The Pearson correlation for the environment-species interaction was 0.916 for Axis 1 and 0.789 for Axis 2, indicating a strong relationship between environmental variables and zooplankton density. In addition to the RDA, stepwise regression analysis was conducted to test the relationship between environmental variables and zooplankton diversity index (H′) and their respective biomass, as shown in

Table 6. Stepwise regression analysis on species diversity index (H′), and zooplankton groups’ biomass (mg/m³) and environmental variables relationship result illustration.

Response Variables		Explanatory Variables
		WT	DO	EC	pH	Chla.	WD	SCh.	TN	NO3-N	NH4-N	TP	TUB
RoH	Coef.	9.28	-	-	-	-	-	-	-	-	-	−42.7	-
	S.E.	0.573	-	-	-	-	-	-	-	-	-	10	-
	T-value	17.14	-	-	-	-	-	-	-	-	-	−4.26	-
	p-value	0.037	-	-	-	-	-	-	-	-	-	−0.024	-
RoB	Coef.	-	-	-	-	-	-	-	-	-	-	-	-
	S.E.	-	-	-	-	-	-	-	-	-	-	-	-
	T-value	-	-	-	-	-	-	-	-	-	-	-	-
	p-value	-	-	-	-	-	-	-	-	-	-	-	-
ClH	Coef.	-	-	-	-	-	−6.316	-	-	0.2514	−9.366	-	-
	S.E.	-	-	-	-	-	0.09	-	-	0.013	0.156	-	-
	T-value	-	-	-	-	-	−70.18	-	-	22.17	−60.17	-	-
	p-value	-	-	-	-	-	0.009	-	-	0.029	0.011	-	-
ClB	Coef.	-	-	0.229	-	1.6613	-	-	-	−16.588	-	-	-
	S.E.	-	-	0.009	-	0.0205	-	-	-	0.0285	-	-	-
	T-value	-	-	238.8	-	81.01	-	-	-	−581.36	-	-	-
	p-value	-	-	0.003	-	0.008	-	-	-	0.001	-	-	-
CoH	Coef.	-	-	-	-	-	-	-	-	-	-	-	-
	S.E.	-	-	-	-	-	-	-	-	-	-	-	-
	T-value	-	-	-	-	-	-	-	-	-	-	-	-
	p-value	-	-	-	-	-	-	-	-	-	-	-	-
CoB	Coef.	-	-	-	-	-	-	-	-	−7.25	-	-	-
	S.E.	-	-	-	-	-	-	-	-	1.94	-	-	-
	T-value	-	-	-	-	-	-	-	-	−3.74	-	-	-
	p-value	-	-	-	-	-	-	-	-	0.033	-	-	-
TZH	Coef.	-	-	-	-	-	-	-	-	-	-	-
	S.E.	-	-	-	-	-	-	-	-	-	-	-
	T-value	-	-	-	-	-	-	-	-	-	-	-
	p-value	-	-	-	-	-	-	-	-	-	-	-
TZB	Coef.	-	-	-	-	-	-	-	-	−7.609	-	-	-
	S.E.	-	-	-		-	-	-	-	0.0857	-	-	-
	T-value	-	-	-	-	-	-	-	-	−88.7	-	-	-
	p-value	-	-	-	-	-	-	-	-	0.007	-	-	-

Note: Rotifer species diversity (H′); Rotifer species biomass; Cladocera species diversity (H′); Cladocera biomass; Copepod species diversity (H′); Copepod biomass; total zooplankton species diversity (H′); and total zooplankton biomass. For abbreviated environmental variables, see (Table 2).

. The results indicated that, unlike Rotifera and Copepods, the Cladoceran population was more dependent on environmental variables. For instance, Cladocera, Copepods, and total zooplankton biomass were negatively correlated with Nitrate Nitrogen while Cladoceran diversity was negatively correlated. However, Cladoceran diversity was related positively to Nitrate Nitrogen. In contrast, Water Depth was positively correlated with total zooplankton biomass. Water Temperature was positively correlated with Cladoceran diversity, while Chlorophyll a and Electrical Conductivity were positively associated with Cladoceran biomass, respectively. On the other hand, Total Phosphorus concentration was negatively associated with total zooplankton diversity.

4. Discussion

4.1. Limnological Variables Along the Sampling Stations

Excessive loads of key nutrients like nitrogen and phosphorus can disrupt the balance of aquatic ecosystems significantly. Thus, to maintain ecological balance, careful nutrient management is often required to understand water clarity [36,37]. Consequently, ecosystem shifts from phytoplankton to macrophyte-dominated to improve water quality can support ecological conservation and management [38]. In the present study, Total Nitrogen and Total Phosphorus concentrations were ranged within (1.85 mg L⁻¹ to 0.71 mg L⁻¹) and (0.146 mg L⁻¹ to 0.018 mg L⁻¹) (Table 2). Among the studied sites with and without vegetation, low Total Nitrogen concentration was measured in sites 4 and 5 occupied by emergent and submerged plants. On the other hand, low Total Phosphorus values were reported in sites 3 and 4 dominated by emergent and submerged plant species (Table 2). This result is supported by [39] investigation results. In his findings, he reported that, due to their labile tissues and tiny root structures, submerged vegetation can absorb nutrients from water columns that reduce the concentration of nutrients in aquatic ecosystems. In addition, Finkler Ferreira [40] also described that macrophyte plants with tiny root structures can potentially deplete Nitrogen and Phosphorus from freshwater bodies and act as nutrient sinks in shallow lakes [41]. On the other hand, in site 5 covered by emergent macrophytes (Phragmites australis and Zizania latifolia), high Total Phosphorus concentration was measured next to open water treated as a control to understand the effect of recovered macrophyte on limnological variables in the studied lake. This can be justified as emergent macrophytes are less sensitive to ecological variables effects than submerged plants as has been reported by [42,43]. However, Kolada [44] contradicted this finding, stating that emergent macrophytes are more universal and perform better quality in improving water than submerged vegetation. This may indicate sensitivity variation among different aquatic vegetations to different nutrient loads and how they respond differently in the same ecosystem. Despite Total Nitrogen and Phosphorus concentration showing a decreasing trend among the re-vegetated sites, site 2 occupied by freely floating (E. forex and T. bispinosa) plant species demonstrated a high Total Nitrogen concentration (1.68 ± 0.67 mg L⁻¹). This result is consistent with the [45] conclusion. In their findings, they reported a significantly increasing effect of macrophyte species following external nutrient loading a reduction might take up to 20 years. This requires patience for the re-establishment of macrophyte plants in degraded ecosystems to understand their effect on excessive nutrient loads in aquatic ecosystems [46]. In the present study, the measured values of Dissolved Oxygen levels ranged from (4.67 mg L⁻¹ to 9.54 mg L⁻¹). This result is aligned with a study report [47] that indicated the level of Dissolved Oxygen (4.8 mg L⁻¹) in aquatic ecosystems is a lower limit and reduces phytoplankton production. This result may conclude the positive significant contribution of recovered macrophyte plants in our study site by improving water quality and indicator for the ecological status of the studied ecosystem. It has also been highlighted by [48] that Water Turbidity is related to light availability in the water column and is often used to assess freshwater quality to understand ecological status. In our study result, the measured Water Turbidity values ranged from (5.38 ± 0.8 NTU to 66.87 ± 7.2 NTU). Among the studied vegetation this result was measured low in sites 3 and 4, respectively, but high in open water. This result is supported by [49] who reported more Water Turbidity results in open water than in the sites with vegetations that affect light incidence. In turn, this effect can limit macrophyte occurrences in freshwater ecosystems especially submerged macrophytes [6]. The content of pH values was measured in between ranges (3.48 ± 0.42 to 7.62 ± 0.04). This result is consistent with the [50] study report which is common in freshwater ecosystems that may support suitable neutral environments that support diversified biological composition.

4.2. The Relationship Between Environmental Variables and Zooplankton Communities

The composition and abundance of zooplankton communities are highly influenced by various environmental factors. Thus, understanding the interactions between environmental variables and zooplankton communities is crucial for the effective management and conservation of aquatic ecosystems. For instance, Jakhar [51] reported that the type, number, and distribution of zooplankton in aquatic habitats can provide clues about the physical and chemical conditions of that ecosystem. In addition, the authors of [52] also described that environmental factors can shape zooplankton structure in freshwater ecosystems directly or indirectly. This interaction can either promote the growth or cause mortality of zooplankton communities [53]. In this study, the RDA results showed Water Temperature was positively correlated with Cladocera groups (Figure 6). This finding is consistent with [43] who indicated that Water Temperature plays a major role in determining zooplankton community development, growth, composition, quantity changes, and horizontal distribution. In addition, Trevisan and Forsberg [54] also pointed out that Temperature is a key element in determining zooplankton community composition in the lake. Similarly, Dissolved Oxygen was found to be an influential variable and was positively correlated with zooplankton groups, especially Copepods with Microcyclops javanus (Kiefer) and Thermodiaptomus galebi (Barrois). Pearson correlation analysis results also revealed that there is a positive relationship between Copepods density and Dissolved Oxygen concentration (r = 0.763, p < 0.01) (

Table 7. Pearson correlation coefficients r that indicate the relationship between environmental variables and zooplankton community density during the study period.

Zooplaknton Taxa	Environmental Variables
	WT	DO	EC	pH	Chla.	WD	SCh.	TN	NO3-N	NH4-N	TP	TUB
Rotifer (ind L−1)	−0.836	0.439 *	−0.374 *	−0.825 **	0.415 *	−0.122	0.132 *	0.510 *	−0.671 *	0.185 *	−0.109	0.158
Copepod (ind L−1)	0.215 *	0.763 **	0.89	0.131 *	0.182	0.432 *	0.289 **	0.99 **	0.428 **	0.569	0.116 *	−0.789 *
Cladocera (ind L−1)	0.326 *	0.75 *	0.56 *	0.78 *	−0.265	−0.419 *	−0.218	−0.329 *	0.295	−0.625 **	0.356	−0.861 **

Note: Correlation * p < 0.05, ** p < 0.01, (2-tailed). For abbreviated environmental variables, see (Table 2).

). This interaction demonstrates that Dissolved Oxygen plays a critical role in maintaining important processes of respiration and metabolism in zooplankton. Additionally, zooplankton can influence the food web structure through their heterogeneous connections with various trophic [55,56].

Chlorophyll a concentration was positively correlated with Cladocera groups. This result is in agreement with [57] finding; however, it is contradicted by [14]. This can be explained by the fact that zooplankton use phytoplankton (Chl.a) as a food source. Additionally, Trevisan and Forsberg [54] also highlighted large zooplankton communities have a positive relationship with Chlorophyll a, indicating zooplankton dependence on this resource for development. In areas with abundant aquatic vegetation, especially Copepods and Cladoceran, Chlorophyll a levels decline due to phytoplankton consumption [58]. The current result also found similar results as more Cladocera groups were recorded in vegetated areas than in open water with a notable positive relationship with Chlorophyll a and Ammonium Nitrogen concentration. However, in sites dominated by Ceratophyllum demersum species, our result demonstrated more zooplankton biomass (Table 3) but low Chlorophyll a concentration (Table 2). This can be justified in two ways: one is related to the grazing effect of zooplankton, especially larger Cladocera, on phytoplankton [59]. Another factor is related to the influence of submerged macrophytes on phytoplankton through allelopathic and nutrient removal effects [60]. Thus, this favored zooplankton biomass enhancement but its influences negatively phytoplankton growth.

In the present study, Turbidity, pH, Total Nitrogen, and Secchi disk showed low influence on the distribution of zooplankton which is aligned with the [findings of [61]. Additionally, Vakkilainen et al. [62] explained in their study result that high Turbidity may reduce the effect of fish predation on zooplankton. The contributions can potentially boost zooplankton density, though dominant groups may increase even under fish predation pressure [63]. In aquatic ecosystems, the response of zooplankton communities to nutrient enrichment can provide basic clues not only to consider the number of trophic levels but also the nature of the organisms within that system [18]. In accordance with this point, the current finding demonstrated that Total Phosphorus concentration was strongly correlated with Daphnia cucculata (G.O. Sars), the dominant species in open water. This is an indication of the direct relationship between Total Phosphorus, algal biomass, and zooplankton feeding habits in the phytoplankton community in which phosphorus availability determines zooplankton biomass [62].

4.3. Zooplankton Spatial Variation, Distribution, and Species Composition

Zooplankton communities can serve as an excellent model to assess the success of restoration efforts and their effect on community ecology [22]. In the present study, results that the presence of zooplankton species composition and distribution obtained vary across the studied sites even within the re-vegetated sites. This suggests that the relative abundance and species composition of zooplankton taxa can be influenced by microhabitat types, such as plant species, benthic sediments, or water column [64]. According to [65] research results, dominant zooplankton species have been categorized in the following ranges: 0–5% low, 5–15% middle, 15–40% high, and >40% very high, to estimate species abundance relative to the total. With the same approach, Daphnia cucculata (G.O. Sars) was found to be the dominant species in open water with a high relative density. This result coincides with [66] who found more zooplankton density in open water compared to the site occupied by submerged and free-floating macrophyte vegetations. This may indicate that large-sized Cladoceran feeds on small particles, including zooplankton, phytoplankton, and other organic matter [67]. It has been reported that large-sized Cladocera species, such as Daphnia spp., are more sensitive to algal blooming and fish predation pressure [68]. However, the result of our study contradicts this report that most large-sized Cladocera species were found more abundant. This is an indication of the significant role of macrophyte plants that provide refuge for zooplankton from fish predation [69], besides controlling algal effects [67]. In addition, the large size of our study site was also dominated by small-sized Cladocera, such as Bosmina fatalis (Burckhard), Moina micura (Kurz), and Ceriodaphnia reticulata (Jurine) species. In line with the current result, the authors of [70] also reported more small-bodied zooplankton in shallow lakes in Uruguay. This conclusion may support the positive effect of a re-vegetated macrophyte community and improvement of the studied lake status. Some studies [71] found the diel migration of Ceriodaphnia and Bosmina in macrophyte enclosures for seeking refuge in plant beds during the day and back to the pelagic zone at night. The same studies have also have been also have been also reported that Moina and Bosmina are resistant to fish predation [72]. In addition, Iglesias et al. [73] reported more Chydrous latus (Sars) in littoral vegetation zones than open water and actively graze on periphytons [74] that show provision of macrophyte for zooplankton against fish predation and purify nutrients from the water column.

In contrast to Cladocera and Copepod, Rotifer mean density was measured as high in our study site (Figure 2). This result is supported by [13] and explains that due to their short development time and parthenogenesis reproduction means, Rotifer can respond quickly to favorable environmental changes. In addition to re-vegetated sites, Rotifer species were also found abundant in non-vegetated areas (Figure 3). Previous studies report [75] can support our result. This report indicated that compared to crustaceans, Rotifer species have a high fecundity rate, resistance to sedimentation, and capacity to avoid predation by insect larvae in littoral zones. These features can be considered as evidence for Rotifer to conclude as a reason why they are more in open water in the current study. Keratella cochlearis (Gosse), Brachionus forficula (Wierzejski), and Lecane cornuta (Müller) species were registered dominant species in our study sites. According to [68,76] studies results, more than 20 Lecane species preferred macrophytes due to their small size and short toes. In addition, Sakuma et al. [77] also reported that even after shaking this species remains attached to plants. This can provide resistance against predator influence and feed on epiphytic microorganisms to increase their numbers in aquatic ecosystems. Similarly, K. cochlearis and B. forficula are frequently planktonic, although they rarely attached to vegetation as [6,68] reported in their findings which support the current result to justify why Keratella cochlearis species were recorded more.

Despite young Copepods nauplii being numerically dominant in all study sites, their numbers may be underestimated due to mesh size in freshwater habitats [71]. Copepods species were recorded more compared to Cladocera and Rotifer, with higher contributions from Cyclopoida species, such as Microcyclops javanus (Kiefer) and Thermodiaptomus galeb (Barrois) in all studied sites. This result agrees with the findings in [78] that suggest Copepods are good swimmers and feed on planktonic algae as an energy source [76]. Species diversity (richness and diversity) is commonly used as a biological parameter for community-level investigation of environmental status. Based on species index values, high index values indicate better quality and lower pollution provides good insight to understand ecological status [52]. In this study, spatial inconsistency was observed with respect to the diversity index (H′) and species richness (D’) result. For example, high diversity and richness were noted in sites 3 and 4 covered by submerged plants (Figure 5 and Figure 6). This result is supported by [70,79] findings that indicate the role of submerged vegetation known in supporting high biodiversity, density, and zooplankton biomass compared to open water. Additionally, habitat heterogeneity and physical complexity increase species richness and diversity by enhancing niche availability [80,81].

4.4. Macrophytes Restoration Practise and Management Strategies to Improve Zooplankton Taxa Diversity and Implication to Macrophyte Management

Suitable chemical and hydromorphlogical conditions support more different groups of biological indicators like microinvertabrate, fish, phytoplankton, and macrophytes in one particular habitat. In this sense, the largely unknown effects of macrophyte plants on community composition, ecosystem functions, and ecological integrity are now becoming an emerging research topic. The current study examined the response of zooplankton distribution to macrophytes in the context of macrophyte management and ecosystem restoration. Basic data on the protective and restorative values of macrophytes, focusing on maintaining high zooplankton biodiversity, abundance, and species composition across various sites under similar climatic conditions, were collected. Consistent with previous findings by [82] this study found that zooplankton taxa diversity, species composition, and abundance were closely related to macrophyte community characteristics. This relationship besides supporting the improvement of biological diversity also enhances the positive role of macrophytes in sustaining a healthy ecological food web. Previous research results [61] reported that freely floating or submerged plant vegetation coexistence supports higher zooplankton species and abundance. On the other hand, Ailstock et al. [83] indicate in their finding emergent plant species are commonly recommended to restore degraded ecosystems rather than submerged and freely floating due to their strong viability and ease management. Future biological assessments in this area should consider incorporating long-term macrophyte monitoring, functional and phylogenetic approaches, and the development of integrated indices, considering macrophytes as a target biological group. This approach should also include the interactions of diverse fish species with zooplankton in the lake, fostering animal diversity, food web structure, and comprehensive management strategies and policies to evaluate restoration success.

5. Conclusions

The removal of macrophyte vegetation can affect negatively the environment leading to habitat degradation and ecosystem imbalance. Thus, the primary goal of aquatic ecosystem management is to control nuisance species and restore plant communities to provide ecosystem stability. The present study investigated the response of zooplankton distribution, species composition, and abundance to macrophyte restoration as the key biological indicators of aquatic ecosystem health. The data showed significant findings regarding macrophyte presence and the distribution of zooplankton groups in different sites studied with various macrophyte vegetations. The current results indicated there are significant dynamics of zooplankton communities’ structure in areas with sole and co-existing re-vegetated plants. This shows the major architectural effect of vegetations that shape the distribution of Rotifera and crustacean communities in specific habitats compared to open water. In the current study, Rotifer found abundant zooplankton taxa, followed by Cladocera in different sites with different vegetation and open water treated as control sites to understand the effect of re-vegetated plants on zooplankton community structure. This suggests that zooplankton species of different sizes use macrophytes as refuges against biological predation and to resist phytoplankton biomass increases. Our finding indicated that, though the variation was as it was, both small and large size zooplankton communities were found more within the re-vegetated macrophyte sites. This conclusion is an indicator of the positive effect of the restoration activities practiced in our study region and enhances those studied biological indicators to understand the current status of the studied lake.

Among the five sampling stations in the present study, open water showed relatively high rotifer distribution compared to sites with freely floating macrophyte plants. This demonstrates the time vibration among restored macrophytes to show an effect on ecological status. Most previous research results reported that emergent and freely floating macrophytes are sometimes considered less important to restore degraded ecosystems. However, our study finding contradicts these points as our result shows significant ecological contributions of these taxa by offering predator-free spaces that improve water clarity and provide refuges for zooplankton, similar to submerged species. The RDA identified Water Temperature, Chlorophyll a, Ammonium Nitrogen, Total Phosphorus, and Dissolved Oxygen as the most influential variables in affecting zooplankton distribution. Overall, the study’s results are relevant for management and strategic policies focused on conservation and the assessment of restoration effects, particularly by taking into account the interaction between zooplankton responses and macrophyte restoration effects in lake ecosystems as biological indicators. Additionally, this study may need a comprehensive investigation focusing on the interaction between different fish species and zooplankton communities, phytoplankton and different species interaction, the effectiveness of sole or/and mixed macrophyte species for nature restoration, and the distribution of microbial and other parasitic organisms in relation to the bird population, especially those bird species dependent on macrophyte vegetation communities for their feeding.