A comprehensive health risk assessment associated with bioaccumulation of heavy metals and nutrients in selected macrophytes of Loktak Lake, Manipur, India

The Loktak Lake, a Ramsar site in Northeast India, is known for its rich biodiversity that includes a variety of macrophyte species, most of which have not been studied for their phytoremediation capacities and potential toxicity via consumption of the edible species. Therefore, a comprehensive assessment was conducted to evaluate the accumulation of selected heavy metals and nutrients in 10 dominant macrophyte species growing in Loktak Lake and to assess the potential health risks associated with consumption of the edible plants. The concentrations of nutrients such as total phosphorus (TP), total nitrogen (TN), potassium (K), calcium (Ca), magnesium (Mg), and heavy metals such as copper (Cu), manganese (Mn), zinc (Zn), and iron (Fe) were found to be in the order of plant > sediment > water. The bioaccumulation factors (BAFs) revealed high efficiency of most plants to accumulate heavy metals and nutrients in their tissues from the lake water and sediments, indicating their potential to be used as phytoremediators. Translocation factors (TFs) were also estimated to determine the efficiency of the plants to translocate elements from root to shoot. Colocasia esculenta and Polygonum perfoliatum exhibited the highest BAF values, whereas Colocasia esculenta, Hedychium flavum, Phragmites karka, and Oenanthe javanica exhibited the highest TF values for most elements. Target hazard quotients (THQs) revealed potential health risks associated with one or more heavy metals in the plants, except for Zn, whose THQ values were below the level of concern in all the edible plant species. The hazard index (HI) signifying potential non-carcinogenic health risk from the combined effects of all the heavy metals was highest for Polygonum perfoliatum, indicating a potentially higher risk to health if this edible macrophyte is regularly consumed in higher quantities and may pose long-term health effects to the exposed population.


Introduction
Wetlands are important freshwater ecosystems that have the capacity to assimilate various nutrients and pollutants and purify the water (Joyce 2012; Singh et al. 2017). Presence of nutrients and essential trace metals in safe concentrations plays a significant role in ecohydrological and biological processes, but concentrations above certain threshold levels can result in adverse effects. Thus, excessive loads of nutrients and heavy metals may significantly threaten the ecological health of the wetlands. Heavy metals in wetlands and other aquatic ecosystems may be released from both natural geogenic sources and anthropogenic activities (Dvorak et al. 2020;Muhammad and Ahmad 2020;Tang et al. 2023). Natural sources are basically lithogenic activities like rock weathering, soil erosion, resuspension of soil, co-precipitation, and dissolution, whereas anthropogenic sources include mining activities, emissions from industries and automobiles, electronic wastes, fuel combustion, waste incineration, fertilizers and pesticides, etc. (Anandkumar et al. 2022;Huang et al. 2022;Wang et al. 2019;Lin et al. 2017;Xiao et al. 2019; Khan and Shah 2023).

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The deposition of heavy metals in water and sediments can drastically degrade their quality, and due to their toxic, nonbiodegradable, persistent, and bioaccumulative nature, they can undergo a biomagnification process in the aquatic food chain, consequently causing harm to aquatic life as well as to humans (Rinklebe et al. 2016;Hong et al. 2020;Habib et al. 2023;Petrov et al. 2023). Long-term exposure to metal toxicity in humans can lead to cancer, disabilities, renal failure, hypertension, stomach and heart diseases, and other adverse effects on the nervous, endocrine, and immune systems (Bhatti et al. 2022). Therefore, monitoring these elements in the environment becomes a priority (Hussain et al. 2020;Ricolfi et al. 2020;Khan et al. 2021). Similarly, excessive amounts of nutrients can lead to eutrophication of aquatic ecosystems, causing algal blooms, hypoxia, fish mortality, increased sedimentation rates and turbidity of water, along with other undesirable ecohydrological effects (Wisheu et al. 1991;Laishram et al. 2022). Sources of nutrient contamination may include agricultural runoff, domestic, municipal, biomedical and industrial waste discharges, sewage and septic wastes, etc.
The wetland sediments and plants tend to accumulate contaminants entering the water body through runoff processes from different natural and anthropogenic sources in varying degrees (Li et al. 2006;Adekola and Eletta 2007;Lu et al. 2011;Singh et al. 2017). Aquatic plants and macrophytes take up and accumulate most of these contaminants from both water and sediments through their roots and shoots due to their fast growth and high biomass (Bonanno and Lo Giudice 2010;Matache et al. 2013;Singh et al. 2017;Scofield et al. 2023). Although this helps in the purification of the water by lowering the concentrations of the pollutants in the water column (Janadeleh and Kameli 2017), but exposure to such edible macrophytes can cause many detrimental health effects to the local population. Macrophytes play a fundamental role in wetland geochemistry and have also been used as bioindicators of pollution in many cases to assess wetland pollution (Zhu et al. 2000;Kamal et al. 2004;Souza et al. 2013;El-Alfy et al. 2023;Petrov et al. 2023). Thus, determining heavy metal concentrations in environmental biota plays a significant role in assessing the risk on human health resulting from consuming contaminated food. The health risk associated with heavy metal accumulation can have non-carcinogenic and carcinogenic effects depending on the nature of the heavy metal. Generally, the non-carcinogenic risk is assessed based on the Target Hazard Quotient (THQ), whereas carcinogenic risk assessment is based on the Target Cancer Risk (TCR) (Markmanuel and Horsfall 2016;Yacoub et al. 2021). The assessment of bioaccumulation capacities of plants and macrophytes can also help in identifying specific species that can be potentially utilized for phytoremediation of contaminated aquatic environments in a cost-effective and environment-friendly manner (Salt et al. 1995;Paz-Alberto and Sigua 2013;Rai et al. 2019). Phytoremediation involves plant or plant parts to remove toxic metals from the soil/water, or to eliminate the bioavailability of toxic metals in the external environment through the process of phytoextraction, rhizofiltration, or phytostabilisation (Salt et al. 1995;Rai et al. 2019).
The Loktak Lake is one of the most important freshwater wetlands in India, known for its biodiversity, ecohydrological significance and socio-economic benefits. In recent years, the ecological health and environmental status of the lake have been at risk of significant deterioration due to anthropogenic disturbances such as uncontrolled discharge of pollutants, including sewage, municipal and domestic wastes, and agricultural runoff from the surrounding catchment. In addition to the unchecked discharges, the development of the Loktak Multipurpose Project has also affected the flushing of the lake water to some extent, causing pollutants to deposit and accumulate within the water body (Singh et al. 2013). A diverse variety of macrophytes are growing in the lake, many of which are edible and consumed by the local inhabitants surrounding the lake throughout the year. However, possible adverse health effects due to their overconsumption in relation to metal toxicity have not been studied in depth. Furthermore, the role of dominant aquatic plants in controlling the water quality of the lake could also be of interest to determine their phytoextraction capacities. Although a handful of studies have been carried out on the water quality of the lake, very limited research works on heavy metal/nutrient accumulation in the lake's aquatic plants have been reported (Meitei and Prasad 2016). Therefore, this research aims to study the bioaccumulation and translocation capacities of dominant macrophyte species of the lake, as well as the health effects associated with metal toxicity. In addition, bioaccumulation capacities have been previously reported considering only the lake water as the external environment. However, due to the fact that most of the macrophytes in the study area grow on vegetative mats locally called Phumdis, which are formed by varying degrees of decomposed aquatic weeds, vegetation, and organic debris, mixed with lake sediments. Bioaccumulation potential in the present study has been evaluated, considering lake water and sediments as the external environment to account for metal and nutrient contributions from water and sediments that accumulate in the plant tissues. The present study is carried out with lake water, sediments, and some selective macrophyte species which have not been reported previously. Thus, the study provides a significant result that contributes to the knowledge of bioaccumulation capacities as well as translocation efficiencies of the macrophyte species found in the study area. It also aims to determine the phytoremediation potentials of the different species and investigates potential health risks associated with the consumption of edible macrophytes of the lake.

Study area
Loktak Lake is the largest freshwater lake in Northeast India, located between longitudes 93°46'-93°55' E and latitudes 24°25'-24°41' N, in the southern part of the Manipur valley, at an altitude of about 770 m above msl (NWA 2009). The wetland is of international importance under the Ramsar Convention due to its rich biodiversity, ecohydrological importance and socio-economic significance. The lake covers a surface area of approximately 246.72 sq. km., with an average recorded depth of about 2.7 m as the lake depth varies from 0.5 to 4.58 m (LDA and WISA 1999;NWA 2009). The region typically experiences tropical to semi-tropical climatic conditions, with temperatures ranging between 0-35 °C and an average annual rainfall of around 1183 mm (WAPCOS 1993;NWA 2009). December-January are generally the coldest months and records the lowest amount of rainfall, while May-July are usually the warmer months that also receive the highest amount of rainfall (Meitei and Prasad 2016). The sub-catchment area of the lake is mainly characterized by clayey and silty types of soil (NBSS and LUP 2001). Numerous feeder streams and rivers are originating from the western hills of the catchment that flow directly into the lake, carrying with them significant amounts of anthropogenic wastes, consequently affecting the lake water quality (CGWB 2013;Laishram and Alam 2019;Laishram et al. 2022). The lake water finally flows out through the Ungamel channel/Ithai barrage, which serves as the lake's main outlet towards the southernmost part of the catchment. About 52% of the lake water is attributed from the western part of the catchment, followed by 27% from direct precipitation, and 21% from other linked feeder channels (LDA and WISA 2002). A unique feature of the lake is the presence of floating vegetation masses locally known as Phumdis (Fig. 1), which are formed by the proliferation of aquatic weeds, vegetation, and organic debris at various stages of decomposition. They vary in shape, size, and thickness, ranging from a few inches to several feet, covering a large portion of the lake, and provide habitat to various endemic flora and fauna. A thick contiguous mat of Phumdis covering an area of approximately 40 sq. km. is situated towards the southern part of the lake, which constitutes the Keibul Lamjao National Park, the only floating National Park in the world. The park is home to the endemic and endangered brow-antlered deer known as Sangai (Rucervus eldii eldii) (Trisal and Manihar 2002) and serves as a significant ecohydrological unit of the lake.

Sample collection
Water, sediment, and macrophyte samples were collected from different sites of the lake (Fig. 2). Geographical coordinates of the sampling sites were recorded using a handheld GPS unit (Garmin etrex 30) (Table 1). Water samples were collected at a depth of > 1 cm below the water surface in precleaned and properly rinsed (with dilute HNO 3 and deionized water) high-density polyethylene (HDPE) bottles as per standard protocols given by the American Public Health Association (APHA 2005). Sediment samples were collected from a depth of 0 to 20 cm from the sediment surface in polyethylene zip-lock bags (USEPA 2010). Macrophyte species were identified and samples were collected in triplicates, including their roots, wrapped in paper, and brought to the laboratory for analysis (CAFT 2012). 10 dominant macrophyte species were selected for the study ( water samples for heavy metal analysis were treated with 1:1 (v/v) HNO 3 solution, and those for analysis of total nitrogen (TN) and total phosphorus (TP) were treated with 1:1 (v/v) H 2 SO 4 solution to preserve the samples (pH < 2) and stored in the laboratory at 4 °C according to standard procedure (APHA 2005). In-situ analysis for parameters such as pH and EC were also carried out for the water samples in the field condition using field test kits/sensors (Eutech).

Sample preparation and analysis
The fresh macrophyte samples were washed thoroughly with tap water and then rinsed with deionized water, followed by their separation into roots and shoots, after which they were dried in the oven at 70 °C for 24-48 h. Care was taken to spread out the materials loosely in the oven to allow free movement of moisture-laden air. Once completely dry, the samples were ground into powder form and placed in appropriately labeled polyethylene containers for subsequent analysis. For analysis of heavy metals, Ca, Mg, and K, the macrophyte samples were first digested following the dry ashing method (FAO 2008) in which 0.5 g of each of the samples were placed in crucibles, heated to 500-600 °C in a muffle furnace (Narang Scientific Works NSW-101) for 3 h, and kept inside overnight. Subsequently, 10 ml of 2N HCl was added to the ash residues, stirred, and kept aside for 1 h. After 1 h, the extracted samples were filtered using 0.45 µm Whatman filter paper to remove the residues, and then diluting the filtrates to 50 ml using deionized water. Finally, concentrations of Cu, Zn, Mn, Fe, Ca, and Mg in the extracted samples were measured using atomic absorption spectrophotometer (AAS) (Perkin-Elmer AAnalyst 200), and K was measured using flame photometer (Systronics 128) (AOAC 1995;USEPA 1995;FAO 2008;CAFT 2012). Concentrations of key nutrients TP and TN in the sediment samples were also measured following standard methods (AOAC 1995;USEPA 1995;FAO 2008;CAFT 2012). TP was measured following the vanadium phosphomolybdate method using a spectrophotometer (Thermo-scientific Genesys 180), and TN was measured by the Kjeldahl method (Kelplus Classic-DX VATS (P)). Sediment samples were air dried until fully dry, ground using mortar and pestle to form powder, and then sieved to remove any coarse particles. The sediment pH and EC were measured in a 1:5 suspension with distilled water using appropriate sensors (Eutech). Similar to macrophyte analysis, the sediment samples were also digested by the dry ashing method using 1 g of each sample to obtain 50 ml diluted filtrate for analysis of heavy metals, Ca, and Mg using AAS, and K with a flame photometer (AOAC 1995;USEPA 1995;CAFT 2012). TP concentrations in the sediments were determined by the spectrophotometric vanadium phosphomolybdate method, whereas the Kjeldahl method was used for TN measurement (AOAC 1995;USEPA 1995;CAFT 2012). Water samples were filtered with 0.45 µm Whatman filter paper for heavy metal analysis using AAS. The concentration of TP was measured by persulphate digestion of the water followed by the stannous chloride method using a spectrophotometer, TN was measured with TOC/ TN analyzer (Shimadzu TNM-L ROHS), Ca and Mg were measured by titration method, and K was measured using flame photometer following standard APHA (2005) procedures (Table 3).

Quality assurance and quality control
Quality assurance and quality control measures were taken to detect the concentrations of target elements in the samples accurately. All chemicals and reagents used in the study were of analytical grade (Merck). Glassware Table 3 Methods and instruments used for sample analysis (AOAC 1995;USEPA 1995;FAO 2008;APHA 2005)  1 3 and plasticware were washed with dilute HNO 3 , rinsed with double distilled water, and dried in the oven before use. Certified standard solutions (Merck) were used for the calibration of AAS. Method blanks and quality control check standards were analyzed at the beginning, between every ten samples, and end of each analytical run. All plant, sediment, and water sample analyses were performed in three replicates, and mean results have been used for subsequent data analysis.

Bioaccumulation and translocation factors
The bioaccumulation factor (BAF) has been calculated to indicate the efficiency of a plant species to accumulate heavy metals or nutrients into its tissues from the surrounding environment, such as water and sediments (Ladislas et al. 2012;Singh et al. 2017). BAF is the ratio of selected metal/nutrient concentration in the plant tissues to that present in the external environment (Janadeleh and Kameli 2017;Nabi 2021;El-Alfy et al. 2023).
where C p = mean metal/nutrient concentration in plant part, expressed in mg/kg, and C e = mean metal/nutrient concentration in the external environment, i.e., water or sediments, expressed in mg/kg. Plants exhibiting BAF > 1 are considered to have high bioaccumulation efficiency, and the larger the BAF value, the greater is the ability of the plant to absorb metals/nutrients from the medium in which they grow (USEPA 2007;Favas et al. 2012;Usman et al. 2013). The translocation factor (TF) has been calculated to determine the metal/nutrient translocation properties of the plants from their roots to shoots. The TF is expressed as the ratio of mean metal/nutrient concentration in shoots to that in roots (Yoon et al. 2006;Zacchini et al. 2009;Janadeleh and Kameli 2017).
where C shoot = mean metal/nutrient concentration present in the shoots, expressed in mg/kg, and C root = mean metal/ nutrient concentration present in the roots, expressed in mg/ kg. TF value greater than 1 signifies that the plant can efficiently translocate metals/nutrients from its roots to shoots (Baker and Brooks 1989;Usman et al. 2013;Jha et al. 2016). Plants that have both TF and BAF values > 1 can be used effectively for phytoextraction of target elements (Fitz and Wenzel 2002;Usman et al. 2013;Chandra et al. 2017).

Human health risk assessment
The health risk assessment of trace metals due to the prolonged consumption of edible macrophytes from the study area was carried out by calculating the estimated daily intake (EDI) of trace metals, the target hazard quotient (THQ), and the hazard index (HI) (USEPA 2011;Fang et al. 2014). These calculations are based on the assumption that the ingested dose equals the absorbed dose (USEPA 1989). The EDI depends on the metal concentrations in the edible macrophyte species, the daily consumption amount, and the average body weight of consumers (Song et al. 2009;Li et al. 2013;Islam et al. 2020).
where C m = concentration of metal in the edible plant, IR = ingestion rate, which is assumed to be 0.1 kg/day per adult, and BW = body weight of consumer, assumed to be 70 kg for an adult (Alhashemi et al. 2012;Janadeleh and Kameli 2017). The THQ estimates the non-carcinogenic risk level due to metal exposure (Javed and Usmani 2016;Elhaddad et al. 2022). THQ is a dimensionless value and is calculated as follows (USEPA 2011) where EF is exposure frequency (365 days/year), ED is exposure duration (70 years) which is considered to be the average life span of a human (USEPA 1991), RFD is the oral reference dose (mg/kg/day), AT is the average exposure time (365 days/year × life span), and IR, C m , BW have been defined above. The oral reference doses for Cu, Mn, Zn, and Fe were 0.04, 0.14, 0.3, and 0.7 mg/kg/day, respectively (USEPA 2012). THQ value less than 1 indicates that the exposed population has a lower chance of experiencing adverse effects due to metal contamination; while THQ value equal to or greater than 1 indicates potential health risk to the exposed population (Wang et al. 2005 where i represents each metal, and n is the total number of heavy metals analysed. HI value exceeding 1 indicates significant potential health effects associated with the heavy Elowa et al. 2022).

Statistical analysis
The results of the experimental data have been presented as mean ± standard deviation (SD) values. Analysis of Variance (ANOVA) were used to study the level of significance between the variables. The required calculations and graphical presentations involved in the analysis of the experimental data, along with correlation analysis, were carried out using MS-EXCEL-2019. Principal component analysis (PCA) was carried out using SPSS software to explain the relationship between different variables. The hierarchical cluster analysis (CA) was also carried out using SPSS software to group the macrophyte species based on similar bioaccumulation capacities from the external environment, and their results were presented in the form of a dendrogram (Tiri et al. 2017;Prusty et al. 2018).

Heavy metal and nutrient concentrations in water and sediments
The concentrations of the selected nutrients and heavy metals in the lake water and sediments from the sites where the macrophyte samples were collected, along with the respective permissible limits prescribed by national and international regulatory bodies (BIS 2012;WHO 1996) have been presented in Table 4. The pH of the water was found to be neutral to slightly alkaline in nature (7.06-8.32) and within the permissible range of 6.5 to 8.5. EC of the water samples ranged from 152.6-192.7 µS/cm, which were under all the permissible limits of 250 µS/cm. The TP concentration in the water ranged from 0.47-1.61 ppm, and that of TN ranged between 0.43-3.37 ppm. The highest concentrations of these two key nutrients were observed in the northern region of the lake, close to the discharge points of the lake's feeder rivers, particularly the Nambul River, which passes through the heart of the state's capital city, Imphal, carrying with them sewage, domestic and municipal wastes, in addition to the agricultural runoff from the surrounding regions of the lake. The concentrations of alkali and alkaline earth elements (K, Ca, Mg) in the lake water were found in relatively low levels as per their respective BIS permissible limits. Among the heavy metals measured, the concentration of Fe in the water was found to be higher (0.101-1.134 ppm) than Cu, Mn, and Zn; and Fe level in the lake water towards the northern side exceeded the permissible limit of 0.3 ppm. These findings agree with previous research works that reported high iron content in the lake water (Singh et al. 2013;Meitei and Prasad 2016;Laishram et al. 2022). Mayanglambam and Neelam (2020a) also reported mean Fe content in the lake water higher than those of Cu, Mn, and Zn, although Fe levels in all the water samples were below the permissible limit in their study. Concentrations of Cu were found below the permissible limit of 1.5 ppm (ranging between 0.019-0.027 ppm). Similarly, Mn concentrations in water ranged between 0.032-0.085 ppm, under the permissible limit of 0.3 ppm, and Zn concentrations ranged between 0.013-0.033 ppm, well below the prescribed permissible limit of 15 ppm. Low levels of Cu, Mn, and Zn in the lake water were also reported by some researchers (Singh et al. 2013;Mayanglambam and Neelam 2020a). Although it was observed that the concentrations of most of the trace elements in the lake water were relatively low with respect to the drinking water quality standards, however, the presence of higher levels of Fe concentration in selected sites of the lake may be a cause of concern resulting in ecological damage to the lake and may pose serious adverse effects to human health, if the untreated lake water is regularly consumed on a long-term basis (Ibrahim et al. 2021).
The concentrations of heavy metals and nutrients in the lake sediments were found to be higher than in the lake water. The pH of the sediments indicated a slightly acidic nature, ranging from 4.5-5.46. Similarly, the EC levels were found to vary between 221-529 µS/cm, with the highest EC being observed in the southern portion of the lake. The high concentrations of key nutrients such as TP (6.53-33.65 mg/kg) and TN (3920-6580 mg/kg) in the sediments may be attributed to the accumulation and adsorption of the nutrients from the nutrient-laden discharges draining into the lake from the feeder rivers and surrounding catchment, mainly resulting from various anthropogenic discharges and chemical fertilizers from the surrounding agriculture fields. Similarly, K, Ca, and Mg concentrations ranged from 17410-17970 mg/kg, 107.73-134.61 mg/kg, and 279.12-286.07 mg/kg, respectively. TN content was found to be much higher than that reported by Meitei and Prasad (2016), while TP levels were found to be lower in comparison. Similar to the lake water scenario, the concentration of Fe in the lake sediments was much higher than the other heavy metals measured, with Fe levels in the sediments ranging from 962.14-983.27 mg/kg. This high iron content in the sediments may be a result of the weathering, erosion, and settlement of iron-bearing soils from the surrounding catchment eventually getting washed down and accumulating in the lake bottom, along with contributions from the dissolution of water-soluble salts from the feeder streams/rivers (Flefel et al. 2020). High levels of iron are also associated with the acidic nature of the sediments (USEPA 1995). In contrast, Cu levels in the sediments were comparatively the lowest, varying between 6.2-9.58 mg/ kg, well below the permissible limit in soil., i.e., 36 mg/ kg. Sources of Cu contamination have been traced to the excessive use of pesticides (Flefel et al. 2020). Concentrations of Mn ranged between 102.45-139.4 mg/kg, and Zn ranged between 52.09-67.32 mg/kg, which exceeded the permissible limit of 50 mg/kg in soil (Table 4). In general, lower pH leads to higher metal absorption by the sediments (Lakatos 1983;Demirezen and Aksoy 2006). The results of the present study were found to be higher than the respective sediment concentrations reported by Meitei and Prasad (2016), but lower than those reported by Mayanglambam and Neelam (2020b).

Heavy metal and nutrient concentrations in macrophytes
The scientific descriptions of ten (10) different plant/macrophyte species collected from Loktak Lake have been presented in Nutrient concentrations were generally found to be high in the plant tissues, which can be indicative of high nutrient uptake from the external environment and their retention in the plant tissues (Meitei and Prasad 2016). Among the heavy metals analysed, it was observed that Fe and Mn concentrations were highest in the plant tissues, while Cu concentrations were the lowest in most of the plants. Fe concentrations were observed to be much higher than the natural content of 370 mg/kg (Brooks and Robinson 1998) in the roots of most species, namely, Z. latifolia, P. perfoliatum, I. aquatica, Oenanthe sp., O. javanica, J. repens, E. crassipes, and C. esculenta, and shoots of a few species, namely, P. perfoliatum and I. aquatica. High Fe concentration in plant tissues has been reported to cause haemorrhagic necrosis, tissue injury, and activation of oncogenes (Gurzau et al. 2003). Mn concentrations in both shoots and roots of all the plants species studied, except the root of P. karka, exceeded the natural content of 52 mg/kg (Brooks and Robinson 1998), and all the plants except P. karka and Z. latifolia also exceeded the maximum permissible limit of 200 mg/kg (WHO 1996;Ohiagu et al. 2020). Mn toxicity in plants is reported to be expected in acidic soils with high Mn levels (USEPA 1995), which is reflected in the acidic nature and high Mn content of the lake sediments in the study area. Despite its concentrations being the lowest in comparison to the other heavy metals, Cu content in most of the plant species were above the WHO permissible limit of 10 mg/kg, except in the shoots of P. karka and J. repens, and most even exceeded the phytotoxic range, i.e., 25-40 mg/kg (Chaney 1989;Singh et al. 2017). On the other hand, all plants had Zn content below the phytotoxic range of 500-1500 mg/kg (Chaney 1989;Singh et al. 2017). Although Zn is needed for the development and function of the body, excessive levels can lead to nausea, respiratory disorders, diarrhoea, epigastric pain, focal neuronal deficits, and risk of prostate cancer (Plum et al. 2010;Ohiagu et al. 2020). In most cases, the metal concentrations were greater in the roots compared to the shoots, however higher concentrations of certain metals in the shoots have also been observed in some species (Fig. 3, Supplementary Table 1) (significant at 0.05 level). Other studies have also reported majority of heavy metals to accumulate more in the lower part of plants compared to their aerial parts (Singh et al. 2004;Gupta and Sinha 2008;Chandra et al. 2017). The concentrations of nutrients and trace metals in the aquatic macrophytes have been found to 1 3 be higher than in the lake water and sediments. Higher concentrations of these elements in the lake water and sediments from various sources have also been found to correspond to higher concentrations in the plants. The increase in heavy metal concentrations from the lake water to sediments to the edible macrophytes suggests further accumulation in fish and then humans, which can ultimately result in various health effects and diseases (Hasan et al. 2012;Flefel et al. 2020).

Bioaccumulation and translocation characteristics of macrophytes
Bioaccumulation factor (BAF) The BAF was calculated to estimate the capacities of the plant species to accumulate heavy metals or nutrients into their tissues from the external environment. BAF values of different macrophyte species for the selected nutrients and heavy metals have been presented in Tables 5 and 6. BAF values have been calculated taking into account both water and sediments as the external media due to the fact that the collected macrophytes grow on Phumdis, which absorb nutrients from both the water as well the sediment particles embedded in the vegetative mats, in addition to the bottom sediments that the mats can often come in contact with. Plants exhibiting BAFs greater than 1 are considered to be highly efficient in accumulating the particular element in their tissues, and larger BAF values indicate greater accumulative properties (USEPA 2007;Favas et al. 2012, Jha et al. 2016. Considering water as the external environment (Table 5), the BAF values revealed that all the macrophyte species had significantly (significant at 0.05 level as per ANOVA two-tailed) very high bioaccumulation efficiencies for the selected nutrients and heavy metals from the surrounding lake water. This signifies the role of aquatic macrophytes in maintaining the water quality of the lake and preventing eutrophication by serving as sinks for various nutrients and metals in the lake ecosystem.  Meitei and Prasad (2016). The plant tissues thus exhibited significant bioaccumulative capacities of nutrients from the lake water, including   (Fig. 4). Considering sediments as the external environment (Table 6), the overall BAF values were found to be smaller for all the nutrients and heavy metals under consideration in all the macrophyte species as compared to lake water as the external medium, with some of the species also exhibiting BAF < 1, indicating that they could not efficiently accumulate certain elements from the lake sediments, as shown in   average BAF values of total plant tissues including both shoot and roots revealed similar order of bioaccumulation efficiencies by the plants from water, with few minor variations. It was observed that C. esculenta was the most efficient accumulator of the nutrients TP, K, Ca, and heavy metal Zn; I. aquatica was the best accumulator of TN and Fe; E. crassipes was the most efficient accumulator of Mg; and P. perfoliatum was the best accumulator of heavy metals Cu and Mn (Fig. 4). The significant BAF values (significant at 0.05 level as per ANOVA two-tailed) thus help in establishing the phytoremediation capacities of the plants as those with higher accumulative properties may be potentially used for phytoremediation in polluted aquatic ecosystems.

Translocation factor (TF)
The TFs for nutrients and heavy metals in the different macrophyte species are shown in Fig. 5 (and Supplementary  Table S3), which represent the efficiencies of the plants to translocate the selected elements from their roots to shoots. The ability of plants to compartmentalize elements or translocate them from root to shoot is important in order to continue absorption from the external environment (Gupta and Sinha 2008). Efficient translocation (TF > 1) is desirable for effective phytoextraction since it is easier to harvest the shoots as opposed to harvesting the roots which is generally not feasible (Halim et al. 2003;Yang et al. 2005 Thus, these plants may be used for the extraction of those particular elements from contaminated aquatic environments as the elements will be effectively stored in their shoots, which can subsequently be harvested and disposed appropriately. In particular, P. karka and E. crassipes, which are found abundantly in the lake may play a significant role in the phytoextraction of the particular nutrients and heavy metals from the lake water and sediments, aiding in control of eutrophication and metal contamination of the lake. The order of plant species with the most effective translocation capacities have been given below:

Correlation analysis
Correlation analysis has been carried out to measure the degree of linear association between the variables measured in the study. Correlation (r) between two variables is considered to be significantly strong when the value of r lies within the range of ± 0.7 < r < ± 1, moderate when ± 0.5 < r < ± 0.7, and weak when 0 < r < ± 0.5. The Pearson correlation matrix between the water and sediment characteristics of the lake has been shown in Table 7. A strong correlation has been observed between many of the parameters in both water and sediments. A strong positive correlation between TP and TN (r = + 0.998) in water indicates similar or common sources of nutrient contamination in the water. A strong correlation has also been observed between some heavy metals in water, i.e., between Fe and Cu (r = + 0.93) and Zn and Mn (r = -0.826).
A moderate correlation was also observed between Zn and Cu (r = + 0.646) and Fe and Zn (r = + 0.687), indicating a significant association between most of the heavy metals in water which could be due to their similar sources. A strong correlation between the nutrients and heavy metals in water has also been observed, i.e., TP-Cu, TP-Fe, TN-Cu, TN-Zn, TN-Fe, which could further imply common sources of both nutrient and heavy metal contamination in the lake water. Similarly, a strong correlation among heavy metals in the sediments have been observed between Zn and Cu (r = + 0.842), and Fe and Zn (r = + 0.863), as well as the moderate correlation between Fe and Cu (r = + 0.508), and Fe and Mn (r = + 0.677). Moreover, a strong negative correlation was also observed between TP-Cu, TP-Zn, and TP-Fe. According to Kumar et al. (2010), the correlation between heavy metals in sediments can vary depending on the aquatic environment's physico-chemical and biological processes as well as anthropogenic discharges and their effects on the partitioning of metals in the aquatic ecosystem (Usman et al. 2013). The Pearson correlation matrix between nutrient and heavy metal concentration in the macrophyte samples (Table 8) revealed that only a few elements displayed a strong positive correlation at p ≤ 0.05, i.e., between Mn and Mg (r = + 0.784), and between Fe and Mn (r = + 0.725). However, a moderately strong positive correlation was observed between many of the parameters, namely, TP-K, TP-Zn, TN-Mn, TN-Fe, K-Zn, Ca-Mg, Mg-Zn, Mg-Fe, and Cu-Mn, signifying considerable association among most of the measured elements in the macrophytes.

Principal component analysis
Principal component analysis (PCA) was carried out to understand the variability in the characteristics of the lake water and sediments and to examine the interactions   between analysed elements in the macrophyte species (Gupta and Sinha 2008). PCA of the water quality data revealed that two principal components (PCs) with eigenvalues > 1 explained about 92.9% of the total variance in the water quality characteristics (Table 9). The first PC accounted for most of the total variance, i.e., 75.19%, with strong positive loadings of EC, TP, TN, K, Cu, Zn, and Fe. The second PC, which accounted for 17.71% of the total variance, contributed strong loading for Mn. On the other hand, the PCA of the sediment quality data (Table 9) showed that three PCs with eigenvalues > 1 accounted for 100% variance. PC1, accounting for 54.2% of the total variance, showed strong positive loadings of K, Zn, and Fe, while PC2 accounting for 30.57%, and PC3, for 15.23% of the total variance, exhibited strong loadings of pH and TN, respectively. Similarly, PCA of macrophyte data revealed that three PCs with eigenvalues > 1 explained about 83.31% of total variances within the variables (Table 10). PC1, which accounted for most of the total variance (40.02%), showed the contribution of strong positive loadings for Mg, Mn, and Fe. PC2, explaining 26.77% of the total variance, showed strong loading of K, whereas PC3 accounting for 16.52% of the total variance, exhibited strong loading of TP. The PCA results thus suggest similar sources of most elements in the lake water and sediments and indicate the distribution pattern of the analysed elements accumulated in the macrophytes (Gupta and Sinha 2008). These findings agreed with the Pearson correlation analysis results, enabling a better understanding of the pollution source apportionment.

Cluster analysis
The hierarchical cluster analysis (CA) was performed as a measure of similarity to classify and cluster the macrophyte species on the basis of their bioaccumulation efficiencies from the lake water and sediments by providing their respective visual illustrations in the form of dendrograms. The CA revealed that the macrophyte species could be grouped into 3 different groups or clusters based on their efficiency of bioaccumulation when lake water is considered as the external environment ( Fig. 6(a)); and into 2 groups when lake sediments are considered as the external environment ( Fig. 6(b)).

Health risk assessment of edible macrophytes
The health risks associated with the consumption of the edible macrophytes of the lake in terms of heavy metal contamination have been assessed on the basis of the THQs of the plant samples as well as the HI (USEPA 2012). The EDI, THQ, and HI values of the selected heavy metals through the consumption of the edible macrophyte species have been presented in   The higher THQs for Mn in the plant tissues may also be associated with the corresponding higher BAF values, signifying greater potential health risk due to greater uptake or accumulation of the metal in the plant tissues. Although Mn is required for the plants and animals, high concentrations can damage lungs and brain and lead to structural and reproductive problems in mammals (Flefel et al. 2020). Therefore, caution is to be taken when consuming edible plants that may accumulate Mn in large amounts in their tissues by avoiding regular or overconsumption of such plants. The hazard index (HI), representing the total effects of all the heavy metals under consideration to the exposed population, was found to be greater than 1 (ranging from 1.55-18.9) for all the edible plants indicating that long-term consumption of these edible macrophyte species by the dependent population may potentially cause undesirable health effects. HI was found to be highest in P. perfoliatum, indicating a potentially higher risk to health due to the combined effects of all the heavy metals if this edible macrophyte is consumed in higher quantities on a regular basis, and thereby possibly leading to long-term health effects to the exposed population. Graphical representations of the THQs of the plants for each heavy metal with reference to the threshold value have been presented in Figs. 7(a), (b), (c), and (d), while that of HIs has been shown in Fig. 8. The THQs and HI finally signify that the dependent communities in the vicinity of Loktak Lake may have unwanted long-term health effects associated with one or more heavy metal contamination from the edible macrophytes growing within the lake   if these plants have been consumed regularly in significant amounts. Thus, care should be taken in the future to avoid regular or excessive consumption of these plants by the local population to prevent unwanted toxic health effects associated with metal contamination.

Conclusion
Numerous edible plants and macrophyte species have been found growing within the water coverage area of Loktak Lake, which serves as a staple component in the diet of the local population residing within and around the lake. This study has revealed that there are significant potential health risks associated with the consumption of many of the edible plant species as they can accumulate heavy metals in their tissues effectively and may gradually result in their biomagnification when these plants are consumed by people directly or indirectly. Specifically, THQs of Cu, Mn, and Fe in all the plants revealed potential adverse health effects; only THQs for Zn were within safe levels. HI revealed P. perfoliatum to have the highest potential health risk due to the combined effects of all the target metals. The present knowledgebase can serve as information regarding potential metal contamination and resulting long-term health effects on the exposed population. Moreover, the present study has also identified the macrophyte species with high BAFs and TFs, indicating their potential phytoremediation application in contaminated aquatic ecosystems to effectively remove undesirable elements, consequently preserving the ecological health of the aquatic system. C. esculenta and P. perfoliatum exhibited the highest BAFs for most of the nutrients and heavy metals, respectively, while the highest TFs were exhibited by C. esculenta, H. flavum, P. karka, and O. javanica, suggesting their indispensable role in maintaining the trophic state of the lake and signifying their phytoremediation capacities. Concentrations of nutrients and heavy metals in the lake sediments have also been found to be relatively high due to long-term accumulation from surrounding runoff and sedimentation processes. On the other hand, the lake water was found to have relatively low concentrations of most heavy metals, except for the presence of high levels of Fe in some sampling sites. This may be indicative of the significant role of aquatic plants that aid in maintaining the water quality of the lake. Although the present study is based on a few selected trace elements, further investigation is required to assess the influence of other heavy metals in the lake ecosystem for holistic investigation and ecological protection of the lake from metal contamination. Along with the study of more heavy metals, their potential carcinogenic health effects may also be evaluated, as current reports have only assessed the noncarcinogenic health effects. Furthermore, future scientific works may also include the study of more plant species as there is a diverse variety of plants in the study area, many of which have not been investigated yet in terms of their bioaccumulation properties. Finally, biomagnification of the metals in fish species of the lake and local population may be studied. The findings of the present study may help in the establishment of appropriate management strategies to control the discharge and accumulation of heavy metal contaminants into the lake water body. In addition, the concerned stakeholders may create public awareness to caution the local population against overconsumption of the edible plants growing in the lake to prevent potential health risks.