Bioaccumulation pattern of heavy metals in Avicennia marina at Visakhapatnam and Coringa mangroves in India

Bioaccumulation pattern of heavy metals in Avicennia marina at Visakhapatnam and Coringa mangroves in India | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Bioaccumulation pattern of heavy metals in Avicennia marina at Visakhapatnam and Coringa mangroves in India Anand Raju Kambala, Ramakrishna Chintala, Srinivas Reka This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5243473/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Jul, 2025 Read the published version in Ecotoxicology → Version 1 posted 9 You are reading this latest preprint version Abstract This study explores the impact of heavy metal accumulation on Avicennia marina's physiological and anatomical aspects, focusing on its capacity for metal uptake and tolerance. Conducted across the Visakhapatnam Entrance Channel (VEC) field, Control Coringa mangroves, and controlled ex-situ greenhouse environments, the study examines the accumulation patterns of chromium (Cr), lead (Pb), and cadmium (Cd). The Potential Ecological Risk Index (RI) indicated that Cd posed a very high risk, with Cr and Pb also showing significant risks. Heavy metal concentrations in the VEC from Cr (36.58–76.41 µg/g), Mn (209.19–428.8 µg/g), Cu (29.91–45.56 µg/g), Zn (306.44–925.16 µg/g), Cd (2.49–4.65 µg/g), and Pb (42.0–155.64 µg/g). The potential ecological risk coefficient Eir consistently placed Cd in the high-risk category, with other metals generally in low to moderate-risk categories. Physiological changes in plant tissues were analyzed using a fluorescence microscope, and higher metal concentrations were assessed with Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The Bioconcentration Factor (BCF) and Translocation Factor (TF) were calculated to evaluate metal accumulation and translocation efficiency. In VEC, significant anatomical changes in Avicennia marina included moist leaves, expanded mesophyll areas, and thick cuticles with heavy metal deposits, especially in high metal concentrations. The region's pollution, driven by port activities and nearby industries, elevated heavy metal levels in sediments. Cd was identified as a very high-risk element at all stations, while other metals were categorized under low or moderate risk. Comparative analysis with the Control Coringa mangroves indicated potential variations in metal accumulation strategies between the two regions within the same species. Anatomical changes in the VEC were more pronounced than fewer disruptions in Coringa mangroves, suggesting differential adaptive responses to environmental stressors. This study underscores the need for targeted environmental management strategies to mitigate heavy metal contamination and highlights the importance of maintaining healthy mangrove habitats amidst increasing anthropogenic pressures. Meghadrigedda Creek Bioconcentration factor Translocation factor Mangroves Coringa Avicennia marina Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 1. Introduction Mangrove plants face various abiotic pressures in the natural environment, including heavy metals and biotic interferences. Mangroves, recognized as accumulators of heavy metals (De Lacerda, 1998), primarily accumulate these metals at the root and lower parts, with limited transport to the stem (Silva et al., 1990 ; Chiu & Chou, 1991 ). Typically, mangrove leaves exhibit concentration factors for heavy metals considerably lower than one (Saenger et al., 1990 ; Rao et al., 1991 ; Tam & Wong, 1995 ; Thomas & Fernandez, 1997 ; Che, 1999). In recent years, intensified anthropogenic activities, rapid industrial expansion, and contemporary farming practices have escalated heavy metal contamination in the environment, leading to toxicity in living organisms (Eapen & D'souza, 2005 ; Kavamura & Esposito, 2010 ; Miransari, 2011 ). Extensive land areas have been polluted with heavy metals due to using fertilizers, pesticides, compost wastes, municipal waste, and emissions from industries and mining processing units (Yang et al., 2005 ). Although many heavy metals exist naturally in the earth's crust, problems arise when they are excessively released into the environment due to natural and/or anthropogenic activities. The current study aimed to assess metal accumulations in various parts of the Avicennia marina. The investigation involved determining concentrations in sediments, water, and different parts of the Avicennia marina . Additionally, a greenhouse was established at the Gandhi Institute of Technology and Management campus, and marina seeds were cultivated by introducing different amended heavy metal concentrations into sediments. Avicennia marina plants were irrigated with medium saline water, and after a cultivation period of 100 days, the plants were harvested for analysis. Seeds were used to grow plants across all concentrations, namely 1 mg, 5 mg, and 10 mg/kg of soil, and were named pots as T1, T5, and T10, respectively, resulting in observable size variations corresponding to different concentration levels, as illustrated. Concurrently, a similar experimental setup was implemented for Coringa mangroves, enabling comparative analysis of metal accumulations in both mangrove species. The harvested plant parts were analyzed, and metal accumulations with physiological changes in different mangrove components were identified using a fluorescent microscope. Anatomical changes in the Avicennia marina were systematically investigated to heavy metal pollution in Visakhapatnam's Meghadrigedda Creek VEC area. The study included a comparative analysis with Coringa mangroves to discern species-specific responses to heavy metal exposure. This study identifies structural characteristics and changes in the Avicennia marina resulting from heavy metal pollution in mangrove regions and nearby areas. It aims to determine whether Avicennia marina , under field conditions, accumulates metals such as Cr, Pb, and Cd, investigating the level of accumulation and distribution in roots, leaves, and stems. The study also explores whether sediment metal levels correlate with metal levels in plant tissues and examines temporal variations in metal accumulation. In ex-situ greenhouse conditions, concentrations of toxic heavy metals (Cr, Pb, Cd) are assessed in sediments and different plant parts, examining their effects on plant physiology using a fluorescent microscope. The primary focus is on highly toxic heavy metals such as Cr, Pb, and Cd, accumulating in sediments through industrial waste and sewage disposal (Raju & Ramakrishna, 2021 ). Although heavy metals are essential for various physiological processes in plants, this research targets explicitly the most toxic metals to understand their impact on plant growth, metabolism, and physiology. Conducted in a greenhouse using a 10×10×10 factorial design with varying concentrations of each heavy metal (1 mg, 5 mg, and 10 mg/kg of soil), the study aims to identify stress-induced changes in the physiology of the mangrove plant Avicennia marina and assess the responses of different mangrove plant species to varying concentrations of toxicants and other environmental stresses affecting different plant parts. 2. Study Area Visakhapatnam, with a population of 2.5 million, is the largest metropolitan city in Andhra Pradesh. At the heart of the city's landscape lies the Visakhapatnam Entrance Channel, a crucial feature comprising three intricately connected arms integrated into the stormwater drainage network. The significance of the VEC extends beyond its role in drainage, acting as a central hub for a diverse range of industrial activities. This includes mining, smelting, fossil fuel burning, petrochemical industries, agricultural chemical use, metal production, sewage disposal, and waste management. The VEC, situated strategically, becomes a focal point for various industrial processes that contribute to the city's economic and infrastructural dynamics. For the study, sampling stations were strategically chosen from two drains, Table 1 , the Airport Side Drain (AS) and Dockyard Side Drain (DS) (Fig. 1 ), to analyze heavy metals in sediments and sediments. This comparison aims to assess pollution levels and their impact on the plant anatomy of mangroves in these distinct zones. Globally, urban areas like Visakhapatnam grapple with environmental challenges, especially concerning sewage and stormwater management. Cities worldwide strive to balance industrial growth and environmental conservation, recognizing the significance of landlocked ports, such as those supporting Visakhapatnam, in facilitating international trade. Table 1 GPS coordinates between sampling points of station 1 and station 2 S.No. Sampling points Latitude Longitude Station 1 (Dockyard side) 1. DYS1 17°42'37.55"N 83°15'44.57"E 2. DYS2 17°42'32.22"N 83°15'23.91"E 3. DYS3 17°42'37.32"N 83°15'15.80"E 4 DYS4 17°42'19.56"N 83°15'13.16"E Station 2 (Airport side) 5. AS1 17°42'48.31"N 83°15'30.90"E 6. AS2 17°42'50.75"N 83°15'19.20"E 7. AS3 17°42'51.32"N 83°15'9.28"E 8. AS4 17°43'4.19"N 83°15'11.91"E These urban areas often face environmental challenges, particularly in managing sewage and stormwater. Across the globe, cities grapple with balancing industrial growth and environmental conservation. Historically, the confluence zone of the VEC and Meghadrigedda supported thriving mangrove forests, which have sadly dwindled into a few fragmented patches. Simultaneously, the VEC and its confluence zone with Meghadrigedda Creek face pollution challenges from domestic and industrial discharges. "In various parts of the world, metropolitan cities serve as economic and industrial powerhouses, mirroring the dynamics observed in Visakhapatnam. These cities, with populations often exceeding millions, contribute significantly to global industrial and economic landscapes. Many are strategically located along coastlines, utilizing natural advantages such as landlocked ports to become pivotal industrial centers on a global scale. These urban areas often face environmental challenges, particularly in managing sewage and stormwater. Across the globe, cities grapple with balancing industrial growth and environmental conservation. Like the Visakhapatnam, environmental corridors can be found in various regions, acting as vital conduits for water management and ecological balance. However, the delicate balance between urban development and ecological preservation is a global concern, and many cities witness a decline in vital ecosystems, such as mangrove forests, due to increasing urbanization and industrial activities. Issues of pollution, driven by domestic and industrial discharges, are not unique to a specific region. Major metropolitan areas worldwide experience challenges related to sewage treatment, industrial effluents, and pollutants entering water bodies. The sources of pollution are diverse, encompassing activities like mining, metal production, fossil fuel burning, and agricultural practices that involve the use of fertilizers and pesticides. These global environmental concerns often manifest as heavy metal contamination in sediments. The impact on plant life, particularly in coastal regions, is a subject of international interest. Efforts to study and mitigate these issues are seen in various parts of the world, with sampling stations established to monitor pollution levels and assess their effects on plant anatomy. As cities continue to grow globally, addressing the environmental implications of urbanization becomes paramount. The challenges faced by Visakhapatnam are echoed in urban centers worldwide, necessitating a coordinated global effort to balance industrial progress with sustainable environmental practices. Mangroves are crucial in mitigating the environmental challenges growing metropolitan cities face globally. As urban areas expand, mangrove forests act as vital ecosystems, providing ecological balance and buffering against sewage and industrial discharge pollution. Their presence along coastlines safeguards against the impacts of urbanization and industrial activities, maintaining water quality and supporting biodiversity. Mangroves are essential in managing stormwater, preventing soil erosion, and acting as natural barriers against coastal hazards. Conserving mangrove ecosystems, like those facing decline in Visakhapatnam, is imperative globally, emphasizing the interconnectedness of urban development and environmental preservation. Efforts for worldwide mangrove conservation align with the broader need to balance industrial growth with sustainability. Avicennia marina , a mangrove species, exhibits significant metal accumulation, particularly Cd and Pb, with higher levels in its root tissues than surrounding sediments. The plant's superior metal absorption capabilities, surpassing sediment levels, make it a promising bio-accumulator. This study confirms Avicennia marina's efficacy in phytoremediation, highlighting its potential as a bio-accumulator even with subtle physiological changes. The variability in Bio-concentration Factors suggests its role as a reliable bio-accumulator and phytoextractor, particularly in areas with lower metal concentrations in soil. The observed adaptive response, with higher translocation factors in plants from higher soil concentrations, underscores its potential for efficient metal removal in coastal regions. To compare the pollution levels and their effects on plant anatomy, these two zones were selected based on the concentration of heavy metals present in plant parts of mangroves. For convenience, the most common and dominant mangrove plants were Avicennia marina species, which were considered for plants to collect from all eight sampling stations. 3. Materials and Methods Plant specimens were systematically collected from the cardinal points delineating a demarcated square expanse measuring 20 x 20 meters. The amalgamated substance derived from these specimens was the basis for subsequent analytical procedures. Employing the United States Environment Protection Agency USEPA 3050B protocol 1986, the plant samples underwent meticulous aqua regia digestion. Subsequently, estimating heavy metal concentrations was meticulously executed utilizing ICP-MS techniques, with Agilent Technologies 7500c serving as the instrumental platform for this sophisticated analysis. 3.1 Histological Studies Transverse sections of these respective plant components were examined to discern potential alterations within the tissues of mangrove plants' roots, stems, and leaves in response to pollution-induced stress. The mangrove plants were cultivated within a controlled environment, simulating conditions reflective of sediments with varying concentrations of heavy metals. This experimental design aimed to scrutinize and comprehend any discernible changes at the histological level brought about by the imposed pollution stress on the mangrove vegetation. 3.2 Fixation with storage The regenerative tissues, representing various developmental stages, underwent fixation using FAA solution, a blend of Formalin, Glacial Acetic Acid, and Alcohol (70%) in a precise ratio of 5:5:90 (v/v). This fixation process extended for approximately 24 hours, following which the specimens were methodically preserved in 70% alcohol for subsequent analysis. 3.3 Embedding, sectioning with staining and microscopic observation The specimen underwent dehydration using the Tertiary Butyl Alcohol series, followed by infiltration with paraffin wax and eventual embedding in pure paraffin wax. Subsequently, the paraffin-embedded tissues were sectioned into slices measuring 8 to 10 µm in thickness utilizing a Thermo Fisher microtome. The dewaxed stain-free microsections were affixed to micro slides and permanently mounted in a Dibutylphthalate Polystyrene Xylene (DPX) mount for scrutiny under an LM-52-3000 EPI Fluorescence microscope (Lawarance Mayo Microscope). Photographic documentation was facilitated using a Nikon Coolpix P7800 12.2 MP Point-and-Shoot Camera. 4. Results This study aims to assess the levels of heavy metal contamination in sediments at different sampling stations of the VEC mangroves. By analyzing the concentrations of Cr, Mn, Cu, Zn, Cd, and Pb in sediment samples, this research provides insights into the spatial distribution of these metals and their potential ecological impacts. Understanding the extent of contamination can aid in developing management strategies for conserving these vital ecosystems. The data obtained can also serve as a baseline for future monitoring of heavy metal pollution in the region. The metal concentrations in Avicennia marina mangrove plants from VEC sampling stations 1 to 8 are presented in Table 2 , and coringa mangrove forest samples were also taken for analysis, reference, and comparison. Table 2 Heavy metal concentrations in the soils and sediments of different sampling stations of the VEC mangroves, Visakhapatnam. S.No St.Cd Heavy metal concentrations ( µg/g ) Cr Mn Cu Zn Cd Pb Soil Sed Soil Sed Soil Sed Soil Sed Soil Sed Soil Sed 1 DS 1 13.08 72.7 463.8 241.7 22.68 43.82 244.7 811.1 3.36 4.3 1.74 149.2 2 DS 2 16.66 60.26 536.22 265.26 26.35 45.56 356.19 925.16 2.63 3.16 2.46 155.64 3 DS 3 8.23 61.82 236.36 325.49 19.64 26.48 264.26 499.15 2.45 2.9 1.95 98.96 4 DS 4 16.56 76.41 625.25 366.91 20.26 35.95 236.26 619.48 3.95 3.14 3.26 65.46 5 AS 1 11.28 68.3 239.3 428.8 20.36 41.64 175.6 376.3 3.12 4.2 2.22 42 6 AS 2 8.23 66.25 162.29 355.64 19.22 34.67 162.89 435.97 2.15 4.65 1.91 85.56 7 AS 3 10.2 50.56 149.46 256.25 16.18 30.15 154.51 346.76 2.88 3.21 2.26 61.47 8 AS 4 2.02 36.58 56.18 209.19 9.95 29.91 136.5 306.44 1.58 2.49 1.49 46.92 Table 3 presents the heavy metal accumulation levels in various parts (root, stem, and leaf) of Avicennia marina plants from different sampling stations. Notably, high Fe, Mn, and Cr concentrations were observed in the root and leaf tissues, with DS1 showing the highest Fe content (6544.4 µg/g) in the root. Additionally, Cd and Pb were relatively low across all tissues, except in Coringa, where elevated Pb levels (275.6 µg/g) were detected in leaf tissues. Table 3 Heavy metal accumulation in different parts of mangrove plants (µg/g). Stans Cr Mn Fe Co Ni Cu Zn Cd Ba Pb ROOT DS1 224.8 ± 2.1 1035.7 ± 1 6544.4 ± 1.4 7.7 ± 1.2 142.4 ± 1.5 51.6 ± 1.2 1233.9 ± 12.9 12.1 ± 0.1 70.4 ± 0.9 124.5 ± 1.3 DS2 150.5 ± 1.4 205.3 ± 2.4 2624.8 ± 1.3 6.5 ± 1 12.4 ± 10.1 69.5 ± 0.1 510.6 ± 1.7 4.9 ± 2.1 9.5 ± 0.8 65.9 ± 1 DS3 92.6 ± 1.5 167.6 ± 2.1 2256.5 ± 3.7 15.3 ± 0.7 12.5 ± 3.3 4.2 ± 0.1 84.2 ± 1.8 3.5 ± 2.3 29.5 ± 0.9 54.3 ± 1.1 DS4 98.6 ± 1.8 297.6 ± 1.1 1455.3 ± 3.6 13.8 ± 0.6 40.3 ± 3.4 40.3 ± 5.4 164.6 ± 1.9 2.5 ± 2.3 45.1 ± 0.9 24.3 ± 1.2 AS1 51.3 ± 4.3 160 ± 0.6 1981.2 ± 3.7 11.2 ± 0.6 26.9 ± 3.3 9.5 ± 5.2 52.3 ± 1.9 0.6 ± 2.4 26.4 ± 0.9 65.9 ± 1.2 AS2 66 ± 4.2 26.6 ± 1.4 749.1 ± 3.8 6.9 ± 0.6 64.3 ± 3.2 9.5 ± 4.4 98.7 ± 1.9 2.2 ± 2.2 92.7 ± 0.9 98.5 ± 1.1 AS3 65.7 ± 3.6 24.5 ± 1.8 564.2 ± 3.8 6.5 ± 0.5 21.6 ± 3.3 5.3 ± 3.4 97.9 ± 1.9 2.2 ± 1 45.6 ± 1 50.5 ± 0.5 AS4 65.2 ± 3.4 41.6 ± 1.8 1652.6 ± 2.3 2.3 ± 0.9 5.3 ± 4 5.3 ± 3.9 52.2 ± 2 2.5 ± 1.4 61.3 ± 1 12.5 ± 0.7 Coringa 7.3 ± 3.5 83.9 ± 1.9 2492.2 ± 2.3 4.5 ± 0.9 9.2 ± 4 14.2 ± 10.1 163.8 ± 2 0.1 ± 1.4 33.6 ± 1 6.4 ± 0.7 STEM DS1 158 ± 3.3 85.9 ± 1.9 1510.7 ± 2.2 3.2 ± 0.9 172.3 ± 4 38.1 ± 5.5 169.4 ± 2 1.5 ± 2.6 2 ± 1 1.3 ± 1.3 DS2 164.9 ± 3.2 21 ± 1.9 1560.3 ± 1 11.4 ± 1 32 ± 3.6 12.5 ± 5.8 64.3 ± 1.8 1.3 ± 2.7 15.8 ± 0.9 9.5 ± 1.4 DS3 25 ± 3.1 24.1 ± 2 1875.2 ± 1.4 9.4 ± 1 6.5 ± 3.6 12.6 ± 2.6 152.2 ± 1.7 1.3 ± 2.7 31.6 ± 0.8 7.3 ± 1.4 DS4 56.5 ± 3 34.6 ± 2 614.6 ± 1.4 2.5 ± 1 2.9 ± 3.1 12.5 ± 2.5 62.1 ± 1.9 0.6 ± 2.7 25.2 ± 1 14.5 ± 1.3 AS1 10 ± 2.8 69 ± 2.1 1598.6 ± 1.4 5.6 ± 1.1 7.3 ± 3.1 15.7 ± 2.5 80.3 ± 2 1.9 ± 2.6 95.7 ± 1 15.6 ± 1.3 AS2 84.4 ± 3 9.5 ± 2 1948.6 ± 2.6 8.9 ± 1 6.5 ± 3.2 6.2 ± 2.4 6.6 ± 1.5 1.9 ± 2.5 52.1 ± 0.8 65.8 ± 1.3 AS3 20.2 ± 2 69.3 ± 1.8 1625.2 ± 2.7 2.5 ± 0.9 8.3 ± 3.2 9.2 ± 2.6 60.8 ± 1.6 0.6 ± 2.5 65.3 ± 0.8 21.7 ± 1.3 AS4 10.9 ± 1.8 58.3 ± 1.7 467.3 ± 2.7 3.4 ± 0.8 10.5 ± 3.2 2.2 ± 1.7 14.1 ± 1.7 1.1 ± 2.4 70.7 ± 0.8 31.5 ± 1.2 Coringa 6.9 ± 1.8 41.9 ± 1.9 931.2 ± 2.7 4 ± 1 3.7 ± 3.1 11.8 ± 1.4 149.4 ± 3.8 0.2 ± 2.6 28.8 ± 1.9 124.9 ± 1.3 LEAF DS1 150.8 ± 0.8 51.5 ± 1.5 2207.5 ± 2.5 0.8 ± 0.8 35 ± 3.8 10.3 ± 2 48.3 ± 3.9 0.2 ± 5.6 32 ± 1.9 7.8 ± 2.8 DS2 90.7 ± 0.7 92.4 ± 1.6 1193.2 ± 2.5 5 ± 0.8 65.2 ± 2.6 2.2 ± 2.1 20.6 ± 3.9 0.3 ± 5.8 10.8 ± 1.9 68 ± 2.9 DS3 64.7 ± 1 82.7 ± 1.7 548.5 ± 2.4 2.6 ± 0.8 2.1 ± 1.7 2.6 ± 1 69.3 ± 1.5 1.9 ± 6.2 9.6 ± 0.7 20.4 ± 3.1 DS4 64.3 ± 0.9 94.7 ± 3.8 1561.3 ± 2.6 12.5 ± 1.9 6.9 ± 37.6 3 ± 0.8 94.1 ± 0.9 0.9 ± 6.7 33.9 ± 0.4 62 ± 3.3 AS1 76.5 ± 0.9 127 ± 3.8 654.6 ± 1.7 9.3 ± 1.9 12.5 ± 0.1 6.5 ± 0.2 9.3 ± 2.7 1.2 ± 0.4 65.9 ± 0.2 47.6 ± 3.7 AS2 34.6 ± 0.4 70.5 ± 0.6 564.7 ± 1.3 68.1 ± 1.1 2.6 ± 0.1 15.9 ± 0.2 33 ± 3 0.5 ± 0.4 69.3 ± 0.2 52.8 ± 4.2 AS3 21.7 ± 0.4 56.4 ± 0.7 1917.5 ± 1.1 2.2 ± 0 3.3 ± 0.1 5.9 ± 0.2 98.1 ± 2.4 1.1 ± 1 52 ± 0.2 2.4 ± 5.1 AS4 26.5 ± 0.5 64 ± 0.7 964.4 ± 0.9 2.1 ± 0.1 2 ± 0.1 3.9 ± 0.2 25.9 ± 33.1 2.9 ± 0.1 62.8 ± 0 21.6 ± 6 Coringa 5.8 ± 3.5 94.3 ± 1.9 1506 ± 2.4 4.5 ± 0.9 5.8 ± 3.9 12.3 ± 7.3 1430.7 ± 2.1 0.1 ± 1.4 63.4 ± 1.1 275.6 ± 0.7 4.1 Risk Analysis of Heavy Metal Contamination in VEC Mangroves, Visakhapatnam This study evaluates the ecological risk of heavy metals in the Visakhapatnam Entrance Channel (VEC), focusing on Avicennia marina's physiological responses and metal uptake. Utilizing the Potential Ecological Risk Index (RI) as proposed by Hakanson (1980), the study aims to assess the risk levels of various heavy metals in sediments $$\:RI=\sum\:_{i=1}^{n}{E}_{r}^{i}$$ Where n is the number of heavy metals analyzed in the sample (i.e., n = 6 in the present study), Eir is the product of the toxicity response factor of metal i and the contamination factor of metal i. $$\:{E}_{r}^{i}=\left({T}_{r}^{i}\:x\:{C}_{f}^{i}\right)$$ T i r is the toxic response factor of metal i, and C i f is the contamination factor of metal i. $$\:{C}_{f}^{i}=\:\frac{{C}_{s}^{i}}{{C}_{n}^{i}}=\:\frac{\text{m}\text{e}\text{a}\text{s}\text{u}\text{r}\text{e}\text{d}\:\text{c}\text{o}\text{n}\text{c}\text{e}\text{n}\text{t}\text{r}\text{a}\text{t}\text{i}\text{o}\text{n}\:\text{o}\text{f}\:\text{m}\text{e}\text{t}\text{a}\text{l}\:i}{\text{b}\text{a}\text{c}\text{k}\text{g}\text{r}\text{o}\text{u}\text{n}\text{d}\:\text{c}\text{o}\text{n}\text{c}\text{e}\text{n}\text{t}\text{r}\text{a}\text{t}\text{i}\text{o}\text{n}\:\text{o}\text{f}\:\text{m}\text{e}\text{t}\text{a}\text{l}\:i}$$ Table 4 compares the heavy metal concentrations in the VEC mangroves with their natural background concentrations (BGC1: soils from Meghadri catchment and BGC2: sediments of Coringa mangroves). The VEC mangroves exhibit significantly higher levels of metals such as Zn, ranging from 306.44 to 925.16 µg/g, and Pb, with values between 42.0 and 155.64 µg/g. These elevated concentrations indicate considerable heavy metal enrichment compared to the natural background levels. Table 4 Heavy metal concentrations in the VEC mangroves compared to their natural background concentrations Metal BGC1 BGC2 VEC range Cr 2.374 2.146 36.58–76.41 Mn 68.14 44.7 209.19–428.8 Cu 7.33 8.906 29.91–45.56 Zn 68.78 113.55 306.44–925.16 Cd 0.295 0.047 2.49–4.65 Pb 1.722 0.334 42.0–155.64 BGC1 Soils from Meghadri catchment; BGC2 Sediments of Coringa mangroves The results indicated that the DS stations were more polluted than the AS stations. Among all the DS stations, DS4 is the most polluted, and AS4 has the lowest load of heavy metal pollutants. As per the state of exceeding the concentration levels over the BGC levels, the order of the study stations by pollution load in soils and sediments are as follows: Table 5 presents the categorization of ecological risk from heavy metals at various stations in the Visakhapatnam Entrance Channel, expressed in the Log 10 range. The results indicate that most stations fall under the "considerable risk" and "high risk" categories for metals such as Cr, Cu, and Zn. At the same time, Cd and Pb show "very high risk" levels across all stations, particularly with Cd reaching a maximum Log 10 value of 4.95. This highlights the significant ecological threat of heavy metal contamination in the region. Table 5 Categorization of Ecological Risk in Log 10 Range from different Heavy metals at various Visakhapatnam Entrance Channel soils and sediments stations. S.No St.Cd. Categorization Ecological Risk from heavy metals using Cr Mn Cu Zn Cd Pb 1 DS1 2.13 2.73 2.09 2.69 4.92 4.05 2 DS2 2.05 2.77 2.11 2.74 4.78 4.07 3 DS3 2.06 2.86 1.87 2.47 4.74 3.87 4 DS4 2.15 2.91 2.00 2.57 4.78 3.69 5 AS1 2.10 2.98 2.07 2.35 4.91 3.50 6 AS2 2.09 2.90 1.99 2.42 4.95 3.81 7 AS3 1.97 2.76 1.93 2.32 4.79 3.66 8 AS4 1.83 2.67 1.92 2.26 4.68 3.55 Table 6 Comparisons of Present Study VEC Range sediment concentrations with sediment quality guidelines Heavy Metal Long et al., 1995 USEPA SQG Nasir & Harikumar, 2011 Present Study VEC Range sediment ERL ERM NP MP HP Cd 1.2 9.6 NA NA NA 0.27–26.35 2.49–4.65 Cr 81 370 NA NA NA NA 36.58–76.41 Cu 34 270 50 38.87–1723.75 26.48–45.56 Pb 46.7 218 60 21.70–162.59 42–155.64 Zn 150 410 2000 70.07–1963.67 306.44–925.16 Mn NA NA NA NA NA 320. 51–15586.88 209.19–428.8 ERL = Effect Range Low ERM = Effect Range Medium NP = Not polluted; MP = Moderately Polluted; HP = Highly Polluted. The degree of ecological risk in the Log 10 Range can be categorized as follows: < E i r 1.60: low risk, 1.60 < E i r <1.90: moderate risk, 1.90 < E i r <2.21: considerable risk, 2.20 < E i r 2.50: very high risk. The ecological risk potential (E i r ) was observed in the order of Cd > Pb > Cr > Mn > Zn > Cu, indicating that the ecological risk from Cd was high . As compared to the sediment quality guidelines reported by Long et al. (1995), Nasir Harikumar (2011), and USEPA (1998), the ranges of the metal concentrations in the sediments of the present study area are in the ranges that may potentially affect the life and ecology (Table.6). As per the above categorization, the values for all the metals (except for Cd) were considered under low- or moderate-risk categories in all the stations. However, Cd was ranked as a very-high-risk category in all the stations (Fig. 2 ). Risk index (RI) represents an overall ecological risk of six studied heavy metal concentrations in the soil, and sediment was calculated using the formula (Hakanson, 1980). As per the above categorization, the RI values for all the metals in soil (except for Cd) were considered under low- or moderate-risk categories. However, Cd was ranked as a very high-risk category. RI values of Mn and Zn were considered under low risk for categories. The remaining Cd, Pb, and Cu were ranked as high-risk categories. As per the above categorization, the \(\:{E}_{r}^{i}\) values for all the metals (except for Cd) were considered under Low or Moderate risk categories in all the stations. However, Cd was ranked as a Very High-Risk category in all the stations. As suggested by Hakanson (1980), the potential ecological risk coefficient ( \(\:{E}_{r}^{i}\) ) was calculated for each heavy metal, and similarly, the total Risk Index (RI) for the total metal concentration was arbitrarily categorized into five risk categories, and the RI with four Risk Classes as delineated below in risk Classes as delineated above Table 7 . Table 7 Categorization of Ecological Risk from heavy metal using \(\:{\varvec{E}}_{\varvec{r}}^{\varvec{i}}\:\varvec{i}\varvec{n}\varvec{d}\varvec{e}\varvec{x}\:\) and \(\:{\sum\:\varvec{E}}_{\varvec{r}}^{\varvec{i}}\:\varvec{i}\varvec{n}\varvec{d}\varvec{e}\varvec{x}\) . Risk Classes of individual metal Risk Classes for the total metal concentrations \(\:{E}_{r}^{i}\:\:\) Index Range Log 10 Range Risk Category 40 or below < 1.6021 Low \(\:{\:\sum\:E}_{r}^{i}\:\:\) Index Range Risk Category 41–80 1.6021–1.9031 Moderate 150 or below Low 81–160 1.9031–2.2041 Considerable 151–300 Moderate 161–320 2.2041–2.5052 High 301–600 High > 320 > 2.5052 Very High > 600 Very High The risk index (RI) represents the ecological risk of six studied heavy metal concentrations in the soil and sediment, which was calculated using the formula (Hakanson, 1980). As per the above categorization, the RI values for all the metals in soil (except Cd considered) were considered under Low or moderate risk categories. However, Cd was ranked as a Very High-Risk category. RI values Mn and Zn were considered under Low risk for categories. The remaining, Cd, Pb, and Cu, were ranked in the Very High-Risk category. The degree of ecological risk in the log 10 range can be categorized as follows:<Eir 1.60: low risk, 1.60 < Eir < 1.90: moderate risk, 1.90 < Eir < 2.21: considerable risk, 2.20 2.50: very-high-risk classes. 4.2 Bio-concentration and translocation factors of Study Area and Coringa The calculation of BCF and TF is integral in assessing a plant's efficiency in accumulating heavy metals from sediment and their subsequent translocation from roots to stems and leaves. This evaluation is crucial for understanding the plant's response to heavy metal uptake and distribution within its various parts. To assess the efficiency of the plant in accumulating heavy metals from sediment to its roots and translocating them from roots to stems, BCF and Translocation Factor (TF) were computed. The formulations for BCF and TF calculations were derived from established methodologies (Wilson & Pyatt, 2007 ; Zacchini et al., 2009 ). $$\:\text{B}\text{C}\text{F}\:=\:\frac{\text{C}\text{p}\text{l}\text{a}\text{n}\text{t}}{\text{C}\text{r}\text{o}\text{o}\text{t}}\:\text{T}\text{F}\:=\:\frac{\text{l}\text{e}\text{a}\text{f}}{\text{C}\:\text{s}\text{e}\text{d}\text{i}\text{m}\text{e}\text{n}\text{t}}$$ Heavy metals available for plant uptake include soluble components in the soil solution or those easily solubilized by root exudates. The calculated BCF and TF, following the established formulas by (Wilson & Pyatt, 2007 ; Zacchini et al., 2009 ), offer quantitative measures of the plant's ability to accumulate and translocate heavy metals, providing valuable insights into the ecological dynamics of metal absorption and distribution in the studied plant species. The BCF, serving as an indicator of the ability of plants and aquatic organisms to absorb pollutants from sediment, reveals the ratio of trace metal content in tissue to that in sediment (Usman et al., 2012; Qiu et al., 2011). In the case of Avicennia marina , most BCF values were deemed excessively high, signifying its role as a highly efficient plant for bioaccumulating metals. Notably, the study observed significantly elevated BCF values for Cu in leaf, branch, and root, as well as for Cr in branch and root, indicating the pronounced bio-accumulation and heightened mobility of these metals in Avicennia marina compared to other investigated metals. The reported bio-concentration factors in this study surpassed those documented by (Qiu et al., 2011; Jian et al., 2017), emphasizing the exceptional bio-accumulation potential of Avicennia marina in the studied environmental context. The heavy metal concentrations in Avicennia marina roots and their respective Bioconcentration Factors in the sediments at various stations are presented in Table 8 . The Chromium BCF exhibited a range from 32.28 at AS4 to 4.54 at AS1, with a mean value of 18.41. Manganese displayed a range between 2.23 at DS1 and 0.16 at AS2, with a mean of 1.20. Iron variations spanned from 3.34 at DS1 to 0.34 at AS3, yielding a mean of 1.84. Cobalt exhibited a range between 4.59 at AS4 and 0.63 at DS2, with a mean of 2.61. Nickel values ranged from 4.18 at DS1 to 0.48 at DS2, with an overall mean of 0.58. Copper values ranged between 2.64 at DS2 and 0.21 at DS3, resulting in a mean of 1.42. Zinc concentrations ranged from 5.04 at DS1 to 0.30 at AS1, with a mean of 2.67. Cadmium levels varied between 3.60 at DS1 and 0.19 at AS1, yielding a mean of 1.90. Barium concentrations ranged from 29.03 at AS4 to 0.08 at DS2, resulting in a mean of 14.55. Lead concentrations range from 71.55 at DS1 to 7.46 at DS4, with a mean value of 39.51. Table 8 Bio-concentration factor (BCF) in Avicennia marina metal concentration in soil to roots of study area and control Coringa (Root/Soil) Cr Mn Fe Co Ni Cu Zn Cd Ba Pb DS1 17.19 2.23 3.34 0.78 4.18 2.27 5.04 3.60 0.61 71.55 DS2 9.03 0.38 1.07 0.63 0.48 2.64 1.43 1.87 0.08 26.79 DS3 11.25 0.71 1.67 2.45 0.76 0.21 0.32 1.42 0.31 27.82 DS4 5.96 0.48 0.49 1.22 1.38 1.99 0.70 0.64 0.40 7.46 AS1 4.54 0.67 1.20 1.03 0.82 0.47 0.30 0.19 0.46 29.69 AS2 8.01 0.16 0.38 1.15 2.39 0.50 0.61 1.00 2.01 51.57 AS3 6.44 0.16 0.34 1.26 0.97 0.33 0.63 0.75 0.74 22.34 AS4 32.28 0.74 1.73 4.59 0.50 0.53 0.38 1.60 29.03 8.40 Coringa 5.00 4.52 37.92 0.57 0.20 0.43 0.37 0.69 0.27 4.51 The heavy metal concentrations in Avicennia marina stems, and their respective Bioconcentration Factors in the sediments at various stations are presented in Table 9 . Chromium BCF ranged from 12.1 at DS1 to 0.89 at AS1, with a mean value 5.87. Manganese ranged between 1.04 at AS4 and 0.04 at DS2, resulting in a mean of 0.28. Iron variations spanned from 1.39 at DS3 to 0.21 at DS4, yielding a mean of 0.81. Cobalt exhibited a range between 6.96 at AS4 and 0.22 at DS4, with a mean of 1.57. Nickel values ranged from 5.06 at DS1 to 0.1 at DS4, with an overall mean of 1.08. Copper values ranged between 1.68 at DS1 and 0.22 at AS4, resulting in a mean of 0.66. Zinc concentrations ranged from 0.69 at DS1 to 0.04 at AS2, with a mean of 0.34. Cadmium levels varied between 0.88 at AS2 and 0.14 at DS4, yielding a mean of 0.49. Barium concentrations ranged from 33.5 at AS4 to 0.017 at DS1, resulting in a mean of 4.75. Lead concentrations range from 34.46 at AS2 to 0.736 at DS4, with a mean value of 10.62. Table 9 Bio-concentration factor (BCF) in Avicennia marina metal concentration in soil to stem of study area and control Coringa (Stem/Soil) Cr Mn Fe Co Ni Cu Zn Cd Ba Pb DS1 12.08 0.19 0.77 0.32 5.06 1.68 0.69 0.43 0.02 0.74 DS2 9.90 0.04 0.64 1.11 1.25 0.48 0.18 0.48 0.13 3.87 DS3 3.03 0.10 1.39 1.51 0.39 0.64 0.58 0.53 0.33 3.73 DS4 3.41 0.06 0.21 0.22 0.10 0.62 0.26 0.14 0.22 4.43 AS1 0.89 0.29 0.97 0.52 0.22 0.77 0.46 0.62 1.67 7.04 AS2 10.26 0.06 1.00 1.48 0.24 0.32 0.04 0.88 1.13 34.46 AS3 1.98 0.46 0.99 0.48 0.37 0.57 0.39 0.20 1.07 9.58 AS4 5.37 1.04 0.49 6.96 1.00 0.22 0.10 0.66 33.50 21.11 Coringa 4.78 2.26 14.17 0.51 0.08 0.36 0.34 1.44 0.23 87.94 The heavy metal concentrations in Avicennia marina leaves and their respective Bioconcentration Factors (BCF) in the sediments at various stations are presented in Table 10 . Chromium BCF exhibited a range from 13.13 at AS4 to 2.12 at AS3, with a mean value of 6.87. Manganese ranged between 1.14 at AS4 and 0.11 at DS1, resulting in a mean of 0.41. Iron variations spanned from 1.16 at AS3 to 0.29 at AS2, yielding a mean of 0.68. Cobalt exhibited a range between 11.29 at AS2 and 0.08 at DS1, with a mean of 3.85. Nickel values ranged from 2.54 at DS2 to 0.10 at AS2, with an overall mean of 0.59. Copper values ranged between 0.83 at AS2 and 0.08 at DS2, resulting in a mean of 0.34. Zinc concentrations ranged from 0.64 at AS3 to 0.05 at AS1, with a mean of 0.25. Cadmium levels varied between 1.85 at AS4 and 0.07 at DS1, yielding a mean of 0.50. Barium concentrations ranged from 29.76 at AS4 to 0.09 at DS2, resulting in a mean of 10.32. Lead concentrations range from 27.66 at AS2 to 1.04 at AS3, with a mean value of 15.78. Table 10 Bio-concentration factor (BCF) in Avicennia marina metal concentration in soil to leaf of study area and control Coringa (Leaf/Soil) Cr Mn Fe Co Ni Cu Zn Cd Ba Pb DS1 11.53 0.11 1.13 0.08 1.03 0.46 0.20 0.07 0.28 4.50 DS2 5.44 0.17 0.49 0.48 2.54 0.08 0.06 0.12 0.09 27.65 DS3 7.86 0.35 0.41 0.41 0.13 0.13 0.26 0.76 0.10 10.44 DS4 3.88 0.15 0.53 1.10 0.23 0.15 0.40 0.23 0.30 19.00 AS1 6.78 0.53 0.40 0.85 0.38 0.32 0.05 0.37 1.15 21.42 AS2 4.20 0.43 0.29 11.29 0.10 0.83 0.20 0.24 1.50 27.66 AS3 2.12 0.38 1.16 0.42 0.15 0.37 0.64 0.36 0.85 1.04 AS4 13.13 1.14 1.01 4.33 0.19 0.39 0.19 1.85 29.76 14.48 Coringa 4.02 5.08 22.92 0.56 0.13 0.37 3.25 0.88 0.51 194.05 Additionally, Ex-situ studies were conducted in a greenhouse to investigate the accumulation capacities of Avicennia marina. Lead (Pb), Chromium (Cr), and Cadmium (Cd) were chosen as the heavy metals for toxicity testing. Different concentrations of each heavy metal, specifically 1mg, 5mg, and 10mg/kg of soil, were incorporated into the soil for greenhouse experiments with a control. The actual concentrations of heavy metals in the sediments, following the addition of known amounts of Pb, Cr, and Cd to various sediments collected from VEC and coring, are outlined in Table 11 . These studies are designed to evaluate the impacts of elevated concentrations of different heavy metals without introducing further changes due to additional contamination. After completing the hundred-day growth period, the Avicennia marina plants were harvested, and their different parts were separated. Subsequently, an analysis was conducted to determine the concentration of heavy metal accumulation in all components of the plants. The soil concentrations in the pots were also analyzed after mixing with known amounts of induced metals, as illustrated in Fig. 3 . In this exploration, I have delved into the repercussions of heavy metal exposure on plants, scrutinizing the influence of varying concentrations of heavy metal stress and evaluating the plant's capacity for tolerance. Table 11 The concentration of heavy metals in the soils of the greenhouse after mixing with known amounts of VEC soils Soil concentrations Cr Cd Pb Vizag study area 13.08 3.36 1.74 Coringa 1.449 0.16 1.42 T 1mg/kg 14.08 4.36 2.74 T 5mg/kg 18.08 8.36 6.74 T 10mgkg 23.08 13.36 11.74 The concentration of cadmium in the roots of Avicennia marina plants exhibited variations, ranging from a minimum of 0.11 µg/g in Coringa to a maximum of 59.52 µg/g in the greenhouse pot labeled as T10, as illustrated in Fig. 4 . Similarly, in the stems, the Cadmium concentration ranged from a minimum of 0.23 µg/g in Coringa to a maximum of 17.25 µg/g in T10. In the leaves, the Cadmium concentration varied from a minimum of 0.14 µg/g in Coringa to 30.81 µg/g in the T10 greenhouse pot. The concentration trends across all studies consistently revealed that Cd predominantly accumulated in the roots and stems before reaching the leaves, with concentrations increasing in correlation with soil concentrations, as illustrated in Fig. 5 The Pb concentration in the roots of Avicennia marina plants varied, with a minimum of 6.41 µg/g in Coringa and a maximum of 124.5 µg/g in the VEC study area. In the stems, the lead concentration ranged from a minimum of 1.28 µg/g in the VEC study area to a maximum of 124.87 µg/g in Coringa. For leaves, the lead concentration in plants from the VEC study area had a minimum of 7.83 µg/g and a maximum of 275.55 µg/g in the VEC study area. The concentration trends across all studies consistently showed that Pb predominantly accumulated in the roots and stems before reaching the leaves, with concentrations increasing in correlation with soil concentrations. Notably, in Coringa, a reversal in accumulation pattern was observed, with Pb concentrations in leaves surpassing those in stems and roots. This variation suggests a specific behavior in Pb accumulation in Coringa compared to other study areas. All concentration data with respective soil concentrations are presented in Fig. 6 . The figure depicts various plant tissues' dynamic Cd accumulation patterns. As the induced metal concentration increases in the greenhouse, the accumulation follows a distinct order, progressing from roots to stems and leaves. This graphical representation provides a visual insight into the observed Cd distribution within different parts of the Avicennia marina plant under varying metal concentrations. Metal accumulation in above-ground plant parts is a crucial indicator of controlling heavy metal contamination through a phytoextraction strategy. When bio-concentration and translocation factors exceed 1, it signifies a greater potential for metal phytoextraction from polluted sites. The computed BCF values from the available data indicate that the roots exhibit notably high BCFs in the 10mg/kg greenhouse studies compared to other sites, particularly for metals Cr, Cd, and Pb. Among these metals, Cr demonstrated a particularly high BCF concentration in the soil (Table 12 ). This observation underscores the efficacy of the phytoextraction strategy, specifically highlighting the potential of Avicennia marina to accumulate and extract heavy metals from contaminated environments, particularly in the greenhouse setting with elevated metal concentrations. Table 12 Heavy metals accumulation Concentration in mangrove plants of Avicennia marina tissues was in increasing order according to increasing the induced metal concentration (Cr, Cd, Pb) in the greenhouse. Metals Concentrations T1mg/kg T 5mg/kg T 10mg/kg Leaf Cr 16.21 29.5 18.7 Cd 22.6 28.52 37.85 Pb 25.1 30.81 51.5 Root Cr 30.1 43.86 14.4 Cd 45.3 55.92 50.84 Pb 63.21 59.52 61.38 Stem Cr 17 18.37 23.6 Cd 42.6 15.54 54.7 Pb 54.45 17.25 57.2 Sediment Cr 14.08 18.08 23.08 Cd 4.36 8.36 6.74 Pb 2.74 6.74 11.74 After conducting an anatomical structure examination using a fluorescent microscope, it was observed that there were no significant changes when comparing the transverse section images of Avicennia marina plant parts at induced metal concentrations of 1 mg, 5 mg, and 10 mg of Cr, Cd, Pb, under different light filters. 4.3 Post-harvest Metal Accumulation Analysis in Avicennia Marina Following the 100-day growth period and subsequent harvesting, the various parts of Avicennia marina plants were meticulously separated and subjected to detailed analysis. The findings revealed a distinct metal accumulation pattern, with a noteworthy emphasis on Pb and Cd concentrations. Primarily, the roots of Avicennia marina exhibited the highest accumulations of both Lead and Cadmium. Subsequently, accumulations were observed in the stems, with the recorded concentrations showing an increasing trend corresponding to the elevated concentrations of these metals in the sediments. This observed accumulation pattern underscores the plant's selective uptake and storage of Lead and Cadmium, with the roots serving as a primary repository for these metals. The systematic increase in concentrations from roots to stems further emphasizes the dynamic interaction between the plant and the surrounding metal-rich environment. 4.4 Avicennia marina Physiology In Fig. 7, where the metal concentrations were 1 mg/kg (T1) under the blue light filter (A-D-G), the anatomical structures Leaf, Root, and Stem, respectively, were examined; similarly, under normal light (B-E-H) and green light filter (C-F-I), the anatomical structures of Leaf, Root, Stem, respectively were examined. Despite the 1 mg/kg metal concentration, there were no alterations in the anatomical features of the plant parts. In Fig. 8, where the metal concentrations were 5 mg/kg mg (T5), under the blue light filter (A-D-G), the anatomical structures of the root, leaf, and stem were examined. Similarly, under normal light (B-E-H) and green light filter (C-F-I), the root, leaf, and stem anatomical structures were examined. Despite the higher metal concentration, there were no noticeable alterations in the anatomical features of the plant parts. Likewise, in Fig. 9, depicting metal concentrations of 10 mg/kg, the examination under different light filters (blue light filter A-D-G, normal light B-E-H, and green light filter C-F-I) revealed no significant structural changes in the leaf, stem, and root compared to lower metal concentrations. Although the high fluorescent light absorption was observed in the 10 mg/kg (T10) concentration, indicative of metal accumulation in the cortex and epidermis, the overall structural integrity of the plant parts remained unchanged. Conclusion In a comprehensive exploration, the study uncovers the ubiquitous presence of three heavy metals, Cr, Pb, and Cd, in the intricate tissues of Avicennia marina , as illustrated in Fig. 10 . The roots stand out as prominent repositories for Cd and Pb, surpassing sediment levels and other plant parts. Avicennia marina emerges as a proficient metal accumulator, eclipsing sediments in metal absorptions and affirming its candidacy for bio-accumulation in the remediation of heavy metal-contaminated coastal domains. This investigation unequivocally establishes Avicennia marina as an exceptionally potent bio-accumulator. Its capacity to amass metals, even with subtle alterations in physiological structures, positions it as a stalwart bio-remediator and phyto-stabilizer, particularly in heavily metal-polluted coastal regions. As a linchpin in the ecological rejuvenation of metal-laden coastal ecosystems, Avicennia marina exhibits unparalleled potential as a bio-accumulator and a linchpin in phytoremediation initiatives. The observed variability in Bioconcentration Factors (BCFs) underscores Avicennia marina's adaptability, excelling as both a bioaccumulator and phytoextractor. In this comparative analysis, plants in sediments with lower metal concentrations boast the highest BCFs. In contrast, those in higher metal concentration sediments showcase superior translocation factors and an adaptive response to environmental nuances. Aligning with these revelations, the study demystifies the intricate relationship between mangroves' metal concentrations, BCFs, and translocation factors. Avicennia marina's nuanced responses, featuring efficient metal uptake and translocation, reaffirm its adaptive prowess in diverse environmental conditions; this study delves into the intricate adaptive mechanisms of Avicennia marina , portraying it as a versatile and resilient species adept at navigating varying metal concentration landscapes. These insights enrich our comprehension of mangrove ecosystems, propelling Avicennia marina to the forefront of phytoremediation and ecological restoration endeavors. Declarations The authors declare no competing interests. Funding: This work was supported by the Ministry of Environment, Forests, and Climate Change (MoEF & CC), New Delhi, under Grant number 22-49/2010-CS-I. All authors acknowledge their support. Competing Interests: The authors declare no competing interests. Author Contributions: K. Anand Raju: Writing – review & editing, Writing – original draft, Visualization, Supervision, Software, Resources, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Ramakrishna Chintala: Writing – review & editing, Writing – original draft, Supervision, Resources, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Srinivas Reka: Writing – review & editing, Writing – original draft, Visualization, Software, Resources, Methodology, Investigation, Formal analysis, Conceptualization. Data Availability: The data supporting this study will be made available upon request. References Chiu, C.Y., Chou, C.H., (1991). The distribution and influence of heavy metals in the Tamshui Estuary mangrove forests in Taiwan. Soil Science and Plant Nutrition 37, 659–669. Eapen, S., and D'souza, S. F. (2005). Prospects of genetic engineering of plants for phytoremediation of toxic metal. Biotechnol. 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Cite Share Download PDF Status: Published Journal Publication published 17 Jul, 2025 Read the published version in Ecotoxicology → Version 1 posted Editorial decision: Revision requested 16 Apr, 2025 Reviews received at journal 13 Apr, 2025 Reviews received at journal 29 Mar, 2025 Reviewers agreed at journal 29 Mar, 2025 Reviewers agreed at journal 24 Mar, 2025 Reviewers invited by journal 24 Mar, 2025 Editor assigned by journal 11 Oct, 2024 Submission checks completed at journal 11 Oct, 2024 First submitted to journal 11 Oct, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5243473","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":364875746,"identity":"ebad927e-7539-4f6b-82ea-9c594adf37b9","order_by":0,"name":"Anand Raju Kambala","email":"data:image/png;base64,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","orcid":"","institution":"Ministry of Earth Sciences","correspondingAuthor":true,"prefix":"","firstName":"Anand","middleName":"Raju","lastName":"Kambala","suffix":""},{"id":364875747,"identity":"2300df8a-8405-47b6-ab19-22572482851b","order_by":1,"name":"Ramakrishna Chintala","email":"","orcid":"","institution":"GITAM University","correspondingAuthor":false,"prefix":"","firstName":"Ramakrishna","middleName":"","lastName":"Chintala","suffix":""},{"id":364875748,"identity":"af0bb36d-98a9-4e73-89e4-3538ae208cac","order_by":2,"name":"Srinivas Reka","email":"","orcid":"","institution":"Ministry of Earth Sciences","correspondingAuthor":false,"prefix":"","firstName":"Srinivas","middleName":"","lastName":"Reka","suffix":""}],"badges":[],"createdAt":"2024-10-11 05:23:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5243473/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5243473/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10646-025-02932-6","type":"published","date":"2025-07-17T16:05:38+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":66581055,"identity":"f9a89f0c-16f4-451a-9ce5-8edea9ee7c93","added_by":"auto","created_at":"2024-10-14 13:30:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1869742,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMap of Visakhapatnam Entrance Channel, at Visakhapatnam city of Andhra Pradesh, India.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5243473/v1/c6c757f5896277ded70324a3.png"},{"id":66581058,"identity":"7fd7d548-c9c6-4a44-b64d-78b0f8c43a9b","added_by":"auto","created_at":"2024-10-14 13:30:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":558425,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhoto (Clockwise) showing the culture house structure; mechanism for marine water and freshwater mixings; pot cultures in soil amended with heavy metals of different concentrations.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-5243473/v1/833740035f067833ca4e2fac.png"},{"id":66581053,"identity":"446afd95-f7c1-4274-bad4-287dd1fb8371","added_by":"auto","created_at":"2024-10-14 13:30:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":7213,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eConcentration of heavy metals in the soils of the greenhouse after mixing with known amounts of metals Cd, Pb, and Cr on VEC soils\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5243473/v1/5b6768e165eca1ce0badb965.png"},{"id":66581054,"identity":"8b2f1230-47f9-4b5e-a287-d03d93d5fea8","added_by":"auto","created_at":"2024-10-14 13:30:08","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":35180,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChromium Accumulation Patterns in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eAvicennia marina\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-5243473/v1/2f518473bc36d779d0a671fc.png"},{"id":66581274,"identity":"d14675b0-2150-4086-9bcc-e08f3a32c828","added_by":"auto","created_at":"2024-10-14 13:38:09","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":41017,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCadmium Accumulation Patterns in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eAvicennia marina\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-5243473/v1/764977fd10e0f81cb245bb05.png"},{"id":66581057,"identity":"afd2ebfe-84ec-4f0c-9b24-7c9de0291064","added_by":"auto","created_at":"2024-10-14 13:30:09","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":172324,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLead Accumulation Patterns in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eAvicennia marina\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-5243473/v1/075775711230b0a41461628b.png"},{"id":66581062,"identity":"4a9ab67a-5462-4c00-bd3c-80a2aca7cd21","added_by":"auto","created_at":"2024-10-14 13:30:09","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":143734,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTransverse section images of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eAvicennia marina\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e (Forssk.) Vierh plant parts at induced metal concentrations with 1 mg of Cr, Cd, Pb, under different light filters.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e· Blue light filter (A-D-G): Leaf, Root, Stem, respectively\u003c/p\u003e\n\u003cp\u003e· Normal light (B-E-H): Leaf, Root, Stem, respectively\u003c/p\u003e\n\u003cp\u003e· Green light filter (C-F-I): Leaf, Root, Stem, respectively\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-5243473/v1/4925a9f58baa3da2e526770e.png"},{"id":66581276,"identity":"57e5adad-1437-4a63-8ff2-9c271faf4f54","added_by":"auto","created_at":"2024-10-14 13:38:09","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":137439,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTransverse section images of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eAvicennia marina\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e (Forssk.) Vierh plant parts at induced metal concentrations with 5 mg of Cr, Cd, Pb, under different light filters.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e· Blue light filter (A-D-G): Root, Leaf, Stem, respectively\u003c/p\u003e\n\u003cp\u003e· Normal light (B-E-H): Root, Leaf, Stem, respectively\u003c/p\u003e\n\u003cp\u003e· Green light filter (C-F-I): Root, Leaf, Stem, respectively\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-5243473/v1/4dddebc80b9a3b23f622e747.png"},{"id":66581060,"identity":"0cf68d59-c259-48ab-97f3-18ef9c98a774","added_by":"auto","created_at":"2024-10-14 13:30:09","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":139180,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTransverse section images of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eAvicennia marina\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e (Forssk.) Vierh plant parts at induced metal concentrations with 10 mg of Cr, Cd, Pb, under different light filters.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e· Blue light filter (A-D-G): Leaf, Stem, Root respectively\u003c/p\u003e\n\u003cp\u003e· Normal light (B-E-H): Leaf, Stem, Root respectively\u003c/p\u003e\n\u003cp\u003e· Green light filter (C-F-I): Leaf, Stem, Root respectively\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-5243473/v1/eb408e97bf720954b2189025.png"},{"id":66581271,"identity":"d63cf620-3787-46c2-af0f-a2405d220bdf","added_by":"auto","created_at":"2024-10-14 13:38:09","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":23053,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMetal accumulation in leaf, root, and stem parts of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eAvicennia marina m\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eangrove plants control studies for accumulation capacities by induced metal concentration in greenhouse (Cr, Pb, Cd) - 1mg/kg, 5mg/kg, and 10mg/kg\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-5243473/v1/d03db10b00457d3cc207dffb.png"},{"id":88506943,"identity":"58ed7c2a-8481-4289-9ca2-df73d6affa06","added_by":"auto","created_at":"2025-08-07 07:35:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5154077,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5243473/v1/edb9f325-61f3-4862-a05e-cfd297e5fc70.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Bioaccumulation pattern of heavy metals in Avicennia marina at Visakhapatnam and Coringa mangroves in India","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eMangrove plants face various abiotic pressures in the natural environment, including heavy metals and biotic interferences. Mangroves, recognized as accumulators of heavy metals (De Lacerda, 1998), primarily accumulate these metals at the root and lower parts, with limited transport to the stem (Silva et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Chiu \u0026amp; Chou, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). Typically, mangrove leaves exhibit concentration factors for heavy metals considerably lower than one (Saenger et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Rao et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Tam \u0026amp; Wong, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Thomas \u0026amp; Fernandez, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Che, 1999). In recent years, intensified anthropogenic activities, rapid industrial expansion, and contemporary farming practices have escalated heavy metal contamination in the environment, leading to toxicity in living organisms (Eapen \u0026amp; D'souza, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Kavamura \u0026amp; Esposito, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Miransari, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Extensive land areas have been polluted with heavy metals due to using fertilizers, pesticides, compost wastes, municipal waste, and emissions from industries and mining processing units (Yang et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Although many heavy metals exist naturally in the earth's crust, problems arise when they are excessively released into the environment due to natural and/or anthropogenic activities.\u003c/p\u003e \u003cp\u003eThe current study aimed to assess metal accumulations in various parts of the \u003cem\u003eAvicennia marina.\u003c/em\u003e The investigation involved determining concentrations in sediments, water, and different parts of the \u003cem\u003eAvicennia marina\u003c/em\u003e. Additionally, a greenhouse was established at the Gandhi Institute of Technology and Management campus, and marina seeds were cultivated by introducing different amended heavy metal concentrations into sediments. \u003cem\u003eAvicennia marina\u003c/em\u003e plants were irrigated with medium saline water, and after a cultivation period of 100 days, the plants were harvested for analysis. Seeds were used to grow plants across all concentrations, namely 1 mg, 5 mg, and 10 mg/kg of soil, and were named pots as T1, T5, and T10, respectively, resulting in observable size variations corresponding to different concentration levels, as illustrated. Concurrently, a similar experimental setup was implemented for Coringa mangroves, enabling comparative analysis of metal accumulations in both mangrove species. The harvested plant parts were analyzed, and metal accumulations with physiological changes in different mangrove components were identified using a fluorescent microscope. Anatomical changes in \u003cem\u003ethe Avicennia marina\u003c/em\u003e were systematically investigated to heavy metal pollution in Visakhapatnam's Meghadrigedda Creek VEC area. The study included a comparative analysis with Coringa mangroves to discern species-specific responses to heavy metal exposure.\u003c/p\u003e \u003cp\u003eThis study identifies structural characteristics and changes in the \u003cem\u003eAvicennia marina\u003c/em\u003e resulting from heavy metal pollution in mangrove regions and nearby areas. It aims to determine whether \u003cem\u003eAvicennia marina\u003c/em\u003e, under field conditions, accumulates metals such as Cr, Pb, and Cd, investigating the level of accumulation and distribution in roots, leaves, and stems. The study also explores whether sediment metal levels correlate with metal levels in plant tissues and examines temporal variations in metal accumulation. In ex-situ greenhouse conditions, concentrations of toxic heavy metals (Cr, Pb, Cd) are assessed in sediments and different plant parts, examining their effects on plant physiology using a fluorescent microscope.\u003c/p\u003e \u003cp\u003eThe primary focus is on highly toxic heavy metals such as Cr, Pb, and Cd, accumulating in sediments through industrial waste and sewage disposal (Raju \u0026amp; Ramakrishna, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Although heavy metals are essential for various physiological processes in plants, this research targets explicitly the most toxic metals to understand their impact on plant growth, metabolism, and physiology. Conducted in a greenhouse using a 10\u0026times;10\u0026times;10 factorial design with varying concentrations of each heavy metal (1 mg, 5 mg, and 10 mg/kg of soil), the study aims to identify stress-induced changes in the physiology of the mangrove plant \u003cem\u003eAvicennia marina\u003c/em\u003e and assess the responses of different mangrove plant species to varying concentrations of toxicants and other environmental stresses affecting different plant parts.\u003c/p\u003e"},{"header":"2. Study Area","content":"\u003cp\u003eVisakhapatnam, with a population of 2.5\u0026nbsp;million, is the largest metropolitan city in Andhra Pradesh. At the heart of the city's landscape lies the Visakhapatnam Entrance Channel, a crucial feature comprising three intricately connected arms integrated into the stormwater drainage network. The significance of the VEC extends beyond its role in drainage, acting as a central hub for a diverse range of industrial activities. This includes mining, smelting, fossil fuel burning, petrochemical industries, agricultural chemical use, metal production, sewage disposal, and waste management. The VEC, situated strategically, becomes a focal point for various industrial processes that contribute to the city's economic and infrastructural dynamics.\u003c/p\u003e \u003cp\u003eFor the study, sampling stations were strategically chosen from two drains, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the Airport Side Drain (AS) and Dockyard Side Drain (DS) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), to analyze heavy metals in sediments and sediments. This comparison aims to assess pollution levels and their impact on the plant anatomy of mangroves in these distinct zones. Globally, urban areas like Visakhapatnam grapple with environmental challenges, especially concerning sewage and stormwater management. Cities worldwide strive to balance industrial growth and environmental conservation, recognizing the significance of landlocked ports, such as those supporting Visakhapatnam, in facilitating international trade.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGPS coordinates between sampling points of station 1 and station 2\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS.No.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSampling points\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLatitude\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLongitude\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eStation 1 (Dockyard side)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDYS1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u0026deg;42'37.55\"N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83\u0026deg;15'44.57\"E\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDYS2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u0026deg;42'32.22\"N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83\u0026deg;15'23.91\"E\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDYS3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u0026deg;42'37.32\"N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83\u0026deg;15'15.80\"E\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDYS4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u0026deg;42'19.56\"N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83\u0026deg;15'13.16\"E\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eStation 2 (Airport side)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAS1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u0026deg;42'48.31\"N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83\u0026deg;15'30.90\"E\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAS2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u0026deg;42'50.75\"N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83\u0026deg;15'19.20\"E\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAS3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u0026deg;42'51.32\"N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83\u0026deg;15'9.28\"E\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAS4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u0026deg;43'4.19\"N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83\u0026deg;15'11.91\"E\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThese urban areas often face environmental challenges, particularly in managing sewage and stormwater. Across the globe, cities grapple with balancing industrial growth and environmental conservation. Historically, the confluence zone of the VEC and Meghadrigedda supported thriving mangrove forests, which have sadly dwindled into a few fragmented patches. Simultaneously, the VEC and its confluence zone with Meghadrigedda Creek face pollution challenges from domestic and industrial discharges.\u003c/p\u003e \u003cp\u003e\"In various parts of the world, metropolitan cities serve as economic and industrial powerhouses, mirroring the dynamics observed in Visakhapatnam. These cities, with populations often exceeding millions, contribute significantly to global industrial and economic landscapes. Many are strategically located along coastlines, utilizing natural advantages such as landlocked ports to become pivotal industrial centers on a global scale.\u003c/p\u003e \u003cp\u003eThese urban areas often face environmental challenges, particularly in managing sewage and stormwater. Across the globe, cities grapple with balancing industrial growth and environmental conservation. Like the Visakhapatnam, environmental corridors can be found in various regions, acting as vital conduits for water management and ecological balance. However, the delicate balance between urban development and ecological preservation is a global concern, and many cities witness a decline in vital ecosystems, such as mangrove forests, due to increasing urbanization and industrial activities. Issues of pollution, driven by domestic and industrial discharges, are not unique to a specific region. Major metropolitan areas worldwide experience challenges related to sewage treatment, industrial effluents, and pollutants entering water bodies. The sources of pollution are diverse, encompassing activities like mining, metal production, fossil fuel burning, and agricultural practices that involve the use of fertilizers and pesticides. These global environmental concerns often manifest as heavy metal contamination in sediments. The impact on plant life, particularly in coastal regions, is a subject of international interest. Efforts to study and mitigate these issues are seen in various parts of the world, with sampling stations established to monitor pollution levels and assess their effects on plant anatomy. As cities continue to grow globally, addressing the environmental implications of urbanization becomes paramount. The challenges faced by Visakhapatnam are echoed in urban centers worldwide, necessitating a coordinated global effort to balance industrial progress with sustainable environmental practices. Mangroves are crucial in mitigating the environmental challenges growing metropolitan cities face globally. As urban areas expand, mangrove forests act as vital ecosystems, providing ecological balance and buffering against sewage and industrial discharge pollution. Their presence along coastlines safeguards against the impacts of urbanization and industrial activities, maintaining water quality and supporting biodiversity. Mangroves are essential in managing stormwater, preventing soil erosion, and acting as natural barriers against coastal hazards. Conserving mangrove ecosystems, like those facing decline in Visakhapatnam, is imperative globally, emphasizing the interconnectedness of urban development and environmental preservation. Efforts for worldwide mangrove conservation align with the broader need to balance industrial growth with sustainability.\u003c/p\u003e \u003cp\u003e \u003cem\u003eAvicennia marina\u003c/em\u003e, a mangrove species, exhibits significant metal accumulation, particularly Cd and Pb, with higher levels in its root tissues than surrounding sediments. The plant's superior metal absorption capabilities, surpassing sediment levels, make it a promising bio-accumulator. This study confirms \u003cem\u003eAvicennia marina's\u003c/em\u003e efficacy in phytoremediation, highlighting its potential as a bio-accumulator even with subtle physiological changes. The variability in Bio-concentration Factors suggests its role as a reliable bio-accumulator and phytoextractor, particularly in areas with lower metal concentrations in soil. The observed adaptive response, with higher translocation factors in plants from higher soil concentrations, underscores its potential for efficient metal removal in coastal regions.\u003c/p\u003e \u003cp\u003eTo compare the pollution levels and their effects on plant anatomy, these two zones were selected based on the concentration of heavy metals present in plant parts of mangroves. For convenience, the most common and dominant mangrove plants were \u003cem\u003eAvicennia marina\u003c/em\u003e species, which were considered for plants to collect from all eight sampling stations.\u003c/p\u003e"},{"header":"3. Materials and Methods","content":"\u003cp\u003ePlant specimens were systematically collected from the cardinal points delineating a demarcated square expanse measuring 20 x 20 meters. The amalgamated substance derived from these specimens was the basis for subsequent analytical procedures. Employing the United States Environment Protection Agency USEPA 3050B protocol 1986, the plant samples underwent meticulous aqua regia digestion. Subsequently, estimating heavy metal concentrations was meticulously executed utilizing ICP-MS techniques, with Agilent Technologies 7500c serving as the instrumental platform for this sophisticated analysis.\u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Histological Studies\u003c/h2\u003e \u003cp\u003eTransverse sections of these respective plant components were examined to discern potential alterations within the tissues of mangrove plants' roots, stems, and leaves in response to pollution-induced stress. The mangrove plants were cultivated within a controlled environment, simulating conditions reflective of sediments with varying concentrations of heavy metals. This experimental design aimed to scrutinize and comprehend any discernible changes at the histological level brought about by the imposed pollution stress on the mangrove vegetation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Fixation with storage\u003c/h2\u003e \u003cp\u003eThe regenerative tissues, representing various developmental stages, underwent fixation using FAA solution, a blend of Formalin, Glacial Acetic Acid, and Alcohol (70%) in a precise ratio of 5:5:90 (v/v). This fixation process extended for approximately 24 hours, following which the specimens were methodically preserved in 70% alcohol for subsequent analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Embedding, sectioning with staining and microscopic observation\u003c/h2\u003e \u003cp\u003eThe specimen underwent dehydration using the Tertiary Butyl Alcohol series, followed by infiltration with paraffin wax and eventual embedding in pure paraffin wax. Subsequently, the paraffin-embedded tissues were sectioned into slices measuring 8 to 10 \u0026micro;m in thickness utilizing a Thermo Fisher microtome. The dewaxed stain-free microsections were affixed to micro slides and permanently mounted in a Dibutylphthalate Polystyrene Xylene (DPX) mount for scrutiny under an LM-52-3000 EPI Fluorescence microscope (Lawarance Mayo Microscope). Photographic documentation was facilitated using a Nikon Coolpix P7800 12.2 MP Point-and-Shoot Camera.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Results","content":"\u003cp\u003eThis study aims to assess the levels of heavy metal contamination in sediments at different sampling stations of the VEC mangroves. By analyzing the concentrations of Cr, Mn, Cu, Zn, Cd, and Pb in sediment samples, this research provides insights into the spatial distribution of these metals and their potential ecological impacts. Understanding the extent of contamination can aid in developing management strategies for conserving these vital ecosystems. The data obtained can also serve as a baseline for future monitoring of heavy metal pollution in the region.\u003c/p\u003e \u003cp\u003eThe metal concentrations in \u003cem\u003eAvicennia marina\u003c/em\u003e mangrove plants from VEC sampling stations 1 to 8 are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, and coringa mangrove forest samples were also taken for analysis, reference, and comparison.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHeavy metal concentrations in the soils and sediments of different sampling stations of the VEC mangroves, Visakhapatnam.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"14\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eS.No\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSt.Cd\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colspan=\"12\" nameend=\"c14\" namest=\"c3\"\u003e \u003cp\u003eHeavy metal concentrations (\u003cem\u003eµg/g\u003c/em\u003e)\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eMn\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eCu\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eZn\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSoil\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSed\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSoil\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSed\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSoil\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSed\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSoil\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSed\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eSoil\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eSed\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eSoil\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eSed\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDS\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e72.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e463.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e241.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e22.68\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e43.82\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e244.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e811.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e3.36\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e1.74\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e149.2\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDS\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.66\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e60.26\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e536.22\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e265.26\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e26.35\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e45.56\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e356.19\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e925.16\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2.63\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3.16\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e2.46\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e155.64\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDS\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.23\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e61.82\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e236.36\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e325.49\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e19.64\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e26.48\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e264.26\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e499.15\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2.45\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e1.95\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e98.96\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDS\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.56\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e76.41\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e625.25\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e366.91\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e20.26\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e35.95\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e236.26\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e619.48\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e3.95\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3.14\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e3.26\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e65.46\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAS\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.28\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e68.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e239.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e428.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e20.36\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e41.64\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e175.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e376.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e3.12\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e2.22\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAS\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.23\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e66.25\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e162.29\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e355.64\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e19.22\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e34.67\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e162.89\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e435.97\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2.15\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e4.65\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e1.91\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e85.56\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAS\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e50.56\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e149.46\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e256.25\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e16.18\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e30.15\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e154.51\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e346.76\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2.88\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3.21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e2.26\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e61.47\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAS\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.02\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.58\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e56.18\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e209.19\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9.95\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e29.91\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e136.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e306.44\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e2.49\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e1.49\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e46.92\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the heavy metal accumulation levels in various parts (root, stem, and leaf) of \u003cem\u003eAvicennia marina\u003c/em\u003e plants from different sampling stations. Notably, high Fe, Mn, and Cr concentrations were observed in the root and leaf tissues, with DS1 showing the highest Fe content (6544.4 µg/g) in the root. Additionally, Cd and Pb were relatively low across all tissues, except in Coringa, where elevated Pb levels (275.6 µg/g) were detected in leaf tissues.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHeavy metal accumulation in different parts of mangrove plants (µg/g).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"11\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStans\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMn\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFe\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCo\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNi\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCu\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eZn\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eBa\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003eROOT\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e224.8 ± 2.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1035.7 ± 1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6544.4 ± 1.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.7 ± 1.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e142.4 ± 1.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e51.6 ± 1.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1233.9 ± 12.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e12.1 ± 0.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e70.4 ± 0.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e124.5 ± 1.3\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e150.5 ± 1.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e205.3 ± 2.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2624.8 ± 1.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.5 ± 1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.4 ± 10.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e69.5 ± 0.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e510.6 ± 1.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.9 ± 2.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9.5 ± 0.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e65.9 ± 1\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92.6 ± 1.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e167.6 ± 2.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2256.5 ± 3.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.3 ± 0.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.5 ± 3.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.2 ± 0.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e84.2 ± 1.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.5 ± 2.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e29.5 ± 0.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e54.3 ± 1.1\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98.6 ± 1.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e297.6 ± 1.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1455.3 ± 3.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.8 ± 0.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40.3 ± 3.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40.3 ± 5.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e164.6 ± 1.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.5 ± 2.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e45.1 ± 0.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e24.3 ± 1.2\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAS1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51.3 ± 4.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e160 ± 0.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1981.2 ± 3.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.2 ± 0.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.9 ± 3.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.5 ± 5.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e52.3 ± 1.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.6 ± 2.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e26.4 ± 0.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e65.9 ± 1.2\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAS2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66 ± 4.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.6 ± 1.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e749.1 ± 3.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.9 ± 0.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e64.3 ± 3.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.5 ± 4.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e98.7 ± 1.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.2 ± 2.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e92.7 ± 0.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e98.5 ± 1.1\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAS3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65.7 ± 3.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.5 ± 1.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e564.2 ± 3.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.5 ± 0.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.6 ± 3.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.3 ± 3.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e97.9 ± 1.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.2 ± 1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e45.6 ± 1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e50.5 ± 0.5\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAS4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65.2 ± 3.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.6 ± 1.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1652.6 ± 2.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.3 ± 0.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.3 ± 4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.3 ± 3.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e52.2 ± 2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.5 ± 1.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e61.3 ± 1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e12.5 ± 0.7\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCoringa\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.3 ± 3.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83.9 ± 1.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2492.2 ± 2.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.5 ± 0.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.2 ± 4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14.2 ± 10.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e163.8 ± 2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.1 ± 1.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e33.6 ± 1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6.4 ± 0.7\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSTEM\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e158 ± 3.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85.9 ± 1.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1510.7 ± 2.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.2 ± 0.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e172.3 ± 4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e38.1 ± 5.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e169.4 ± 2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.5 ± 2.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2 ± 1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.3 ± 1.3\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e164.9 ± 3.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 ± 1.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1560.3 ± 1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.4 ± 1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32 ± 3.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.5 ± 5.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e64.3 ± 1.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.3 ± 2.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e15.8 ± 0.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e9.5 ± 1.4\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 ± 3.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.1 ± 2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1875.2 ± 1.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.4 ± 1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.5 ± 3.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.6 ± 2.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e152.2 ± 1.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.3 ± 2.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e31.6 ± 0.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e7.3 ± 1.4\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56.5 ± 3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.6 ± 2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e614.6 ± 1.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.5 ± 1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.9 ± 3.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.5 ± 2.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e62.1 ± 1.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.6 ± 2.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e25.2 ± 1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e14.5 ± 1.3\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAS1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 ± 2.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69 ± 2.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1598.6 ± 1.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.6 ± 1.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.3 ± 3.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15.7 ± 2.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e80.3 ± 2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.9 ± 2.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e95.7 ± 1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e15.6 ± 1.3\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAS2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84.4 ± 3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.5 ± 2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1948.6 ± 2.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.9 ± 1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.5 ± 3.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.2 ± 2.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.6 ± 1.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.9 ± 2.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e52.1 ± 0.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e65.8 ± 1.3\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAS3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.2 ± 2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.3 ± 1.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1625.2 ± 2.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.5 ± 0.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.3 ± 3.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.2 ± 2.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e60.8 ± 1.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.6 ± 2.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e65.3 ± 0.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e21.7 ± 1.3\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAS4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.9 ± 1.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.3 ± 1.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e467.3 ± 2.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.4 ± 0.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.5 ± 3.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.2 ± 1.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14.1 ± 1.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.1 ± 2.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e70.7 ± 0.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e31.5 ± 1.2\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCoringa\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.9 ± 1.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.9 ± 1.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e931.2 ± 2.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 ± 1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.7 ± 3.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11.8 ± 1.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e149.4 ± 3.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.2 ± 2.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e28.8 ± 1.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e124.9 ± 1.3\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLEAF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e150.8 ± 0.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.5 ± 1.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2207.5 ± 2.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.8 ± 0.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35 ± 3.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.3 ± 2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e48.3 ± 3.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.2 ± 5.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e32 ± 1.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e7.8 ± 2.8\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90.7 ± 0.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.4 ± 1.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1193.2 ± 2.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 ± 0.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e65.2 ± 2.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.2 ± 2.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20.6 ± 3.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.3 ± 5.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e10.8 ± 1.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e68 ± 2.9\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64.7 ± 1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82.7 ± 1.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e548.5 ± 2.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.6 ± 0.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.1 ± 1.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.6 ± 1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e69.3 ± 1.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.9 ± 6.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9.6 ± 0.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e20.4 ± 3.1\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64.3 ± 0.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94.7 ± 3.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1561.3 ± 2.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.5 ± 1.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.9 ± 37.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3 ± 0.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e94.1 ± 0.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.9 ± 6.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e33.9 ± 0.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e62 ± 3.3\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAS1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76.5 ± 0.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e127 ± 3.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e654.6 ± 1.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.3 ± 1.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.5 ± 0.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.5 ± 0.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.3 ± 2.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.2 ± 0.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e65.9 ± 0.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e47.6 ± 3.7\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAS2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34.6 ± 0.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.5 ± 0.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e564.7 ± 1.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68.1 ± 1.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.6 ± 0.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15.9 ± 0.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e33 ± 3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.5 ± 0.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e69.3 ± 0.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e52.8 ± 4.2\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAS3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.7 ± 0.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56.4 ± 0.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1917.5 ± 1.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.2 ± 0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.3 ± 0.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.9 ± 0.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e98.1 ± 2.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.1 ± 1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e52 ± 0.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.4 ± 5.1\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAS4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.5 ± 0.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64 ± 0.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e964.4 ± 0.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.1 ± 0.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 ± 0.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.9 ± 0.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25.9 ± 33.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.9 ± 0.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e62.8 ± 0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e21.6 ± 6\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCoringa\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.8 ± 3.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94.3 ± 1.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1506 ± 2.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.5 ± 0.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.8 ± 3.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.3 ± 7.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1430.7 ± 2.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.1 ± 1.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e63.4 ± 1.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e275.6 ± 0.7\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Risk Analysis of Heavy Metal Contamination in VEC Mangroves, Visakhapatnam\u003c/h2\u003e \u003cp\u003eThis study evaluates the ecological risk of heavy metals in the Visakhapatnam Entrance Channel (VEC), focusing on Avicennia marina's physiological responses and metal uptake. Utilizing the Potential Ecological Risk Index (RI) as proposed by Hakanson (1980), the study aims to assess the risk levels of various heavy metals in sediments\u003c/p\u003e\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:RI=\\sum\\:_{i=1}^{n}{E}_{r}^{i}$$\u003c/div\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e \u003cp\u003eWhere n is the number of heavy metals analyzed in the sample (i.e., n = 6 in the present study), Eir is the product of the toxicity response factor of metal i and the contamination factor of metal i.\u003c/p\u003e\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:{E}_{r}^{i}=\\left({T}_{r}^{i}\\:x\\:{C}_{f}^{i}\\right)$$\u003c/div\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e \u003cp\u003eT\u003csup\u003ei\u003c/sup\u003e\u003csub\u003er\u003c/sub\u003e is the toxic response factor of metal i, and C\u003csup\u003ei\u003c/sup\u003e\u003csub\u003ef\u003c/sub\u003e is the contamination factor of metal i.\u003c/p\u003e\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$$\\:{C}_{f}^{i}=\\:\\frac{{C}_{s}^{i}}{{C}_{n}^{i}}=\\:\\frac{\\text{m}\\text{e}\\text{a}\\text{s}\\text{u}\\text{r}\\text{e}\\text{d}\\:\\text{c}\\text{o}\\text{n}\\text{c}\\text{e}\\text{n}\\text{t}\\text{r}\\text{a}\\text{t}\\text{i}\\text{o}\\text{n}\\:\\text{o}\\text{f}\\:\\text{m}\\text{e}\\text{t}\\text{a}\\text{l}\\:i}{\\text{b}\\text{a}\\text{c}\\text{k}\\text{g}\\text{r}\\text{o}\\text{u}\\text{n}\\text{d}\\:\\text{c}\\text{o}\\text{n}\\text{c}\\text{e}\\text{n}\\text{t}\\text{r}\\text{a}\\text{t}\\text{i}\\text{o}\\text{n}\\:\\text{o}\\text{f}\\:\\text{m}\\text{e}\\text{t}\\text{a}\\text{l}\\:i}$$\u003c/div\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e compares the heavy metal concentrations in the VEC mangroves with their natural background concentrations (BGC1: soils from Meghadri catchment and BGC2: sediments of Coringa mangroves). The VEC mangroves exhibit significantly higher levels of metals such as Zn, ranging from 306.44 to 925.16 µg/g, and Pb, with values between 42.0 and 155.64 µg/g. These elevated concentrations indicate considerable heavy metal enrichment compared to the natural background levels.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHeavy metal concentrations in the VEC mangroves compared to their natural background concentrations\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetal\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBGC1\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBGC2\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVEC range\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.374\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.146\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.58–76.41\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMn\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68.14\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e209.19–428.8\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCu\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.33\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.906\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29.91–45.56\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZn\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68.78\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e113.55\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e306.44–925.16\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.295\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.49–4.65\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.722\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.334\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42.0–155.64\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eBGC1 Soils from Meghadri catchment; BGC2 Sediments of Coringa mangroves\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eThe results indicated that the DS stations were more polluted than the AS stations. Among all the DS stations, DS4 is the most polluted, and AS4 has the lowest load of heavy metal pollutants. As per the state of exceeding the concentration levels over the BGC levels, the order of the study stations by pollution load in soils and sediments are as follows:\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e presents the categorization of ecological risk from heavy metals at various stations in the Visakhapatnam Entrance Channel, expressed in the Log 10 range. The results indicate that most stations fall under the \"considerable risk\" and \"high risk\" categories for metals such as Cr, Cu, and Zn. At the same time, Cd and Pb show \"very high risk\" levels across all stations, particularly with Cd reaching a maximum Log 10 value of 4.95. This highlights the significant ecological threat of heavy metal contamination in the region.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCategorization of Ecological Risk in Log 10 Range from different Heavy metals at various Visakhapatnam Entrance Channel soils and sediments stations.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eS.No\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSt.Cd.\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colspan=\"6\" nameend=\"c8\" namest=\"c3\"\u003e \u003cp\u003eCategorization Ecological Risk from heavy metals using\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMn\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCu\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eZn\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDS1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.13\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.73\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.09\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.69\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.92\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4.05\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDS2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.05\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.77\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.11\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.74\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.78\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4.07\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDS3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.06\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.86\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.87\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.47\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.74\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3.87\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDS4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.15\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.91\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.57\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.78\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3.69\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAS1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.98\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.07\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.35\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.91\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3.50\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAS2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.09\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.90\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.99\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.42\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.95\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3.81\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAS3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.97\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.76\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.93\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.32\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.79\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3.66\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAS4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.83\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.67\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.92\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.26\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.68\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3.55\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparisons of Present Study VEC Range sediment concentrations with sediment quality guidelines\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHeavy Metal\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eLong et al., 1995\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eUSEPA SQG\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNasir \u0026amp; Harikumar, 2011\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePresent Study VEC Range sediment\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eERL\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eERM\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNP\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMP\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHP\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.27–26.35\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.49–4.65\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e370\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e36.58–76.41\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCu\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e270\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt; 25\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25–50\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026gt; 50\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e38.87–1723.75\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e26.48–45.56\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e218\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt; 40\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40–60\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026gt; 60\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21.70–162.59\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e42–155.64\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZn\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e410\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt; 90\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90–200\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026gt; 2000\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e70.07–1963.67\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e306.44–925.16\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMn\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e320. 51–15586.88\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e209.19–428.8\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003eERL = Effect Range Low ERM = Effect Range Medium NP = Not polluted;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003eMP = Moderately Polluted; HP = Highly Polluted.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eThe degree of ecological risk in the \u003cb\u003eLog 10 Range\u003c/b\u003e can be categorized as follows: \u0026lt; E\u003csup\u003ei\u003c/sup\u003e\u003csub\u003er\u003c/sub\u003e 1.60: low risk, 1.60 \u0026lt; E\u003csup\u003ei\u003c/sup\u003e\u003csub\u003er\u003c/sub\u003e \u0026lt;1.90: moderate risk, 1.90 \u0026lt; E\u003csup\u003ei\u003c/sup\u003e\u003csub\u003er\u003c/sub\u003e\u0026lt;2.21: considerable risk, 2.20 \u0026lt; E\u003csup\u003ei\u003c/sup\u003e\u003csub\u003er\u003c/sub\u003e \u0026lt;2.50: high risk, and E\u003csup\u003ei\u003c/sup\u003e\u003csub\u003er\u003c/sub\u003e \u0026gt;2.50: very high risk.\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe ecological risk potential (E\u003c/b\u003e \u003csup\u003e \u003cb\u003ei\u003c/b\u003e \u003c/sup\u003e \u003csub\u003e \u003cb\u003er\u003c/b\u003e \u003c/sub\u003e \u003cb\u003e) was observed in the order of Cd \u0026gt; Pb \u0026gt; Cr \u0026gt; Mn \u0026gt; Zn \u0026gt; Cu, indicating that the ecological risk from Cd was high\u003c/b\u003e. As compared to the sediment quality guidelines reported by Long et al. (1995), Nasir Harikumar (2011), and USEPA (1998), the ranges of the metal concentrations in the sediments of the present study area are in the ranges that may potentially affect the life and ecology (Table.6).\u003c/p\u003e \u003cp\u003eAs per the above categorization, the values for all the metals (except for Cd) were considered under low- or moderate-risk categories in all the stations. However, Cd was ranked as a very-high-risk category in all the stations (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Risk index (RI) represents an overall ecological risk of six studied heavy metal concentrations in the soil, and sediment was calculated using the formula (Hakanson, 1980). As per the above categorization, the RI values for all the metals in soil (except for Cd) were considered under low- or moderate-risk categories. However, Cd was ranked as a very high-risk category. RI values of Mn and Zn were considered under low risk for categories. The remaining Cd, Pb, and Cu were ranked as high-risk categories.\u003c/p\u003e \u003cp\u003eAs per the above categorization, the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{E}_{r}^{i}\\)\u003c/span\u003e\u003c/span\u003e values for all the metals (except for Cd) were considered under \u003cb\u003eLow\u003c/b\u003e or \u003cb\u003eModerate\u003c/b\u003e risk categories in all the stations. However, Cd was ranked as a Very High-Risk category in all the stations.\u003c/p\u003e \u003cp\u003eAs suggested by Hakanson (1980), the potential ecological risk coefficient (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{E}_{r}^{i}\\)\u003c/span\u003e\u003c/span\u003e) was calculated for each heavy metal, and similarly, the total Risk Index (RI) for the total metal concentration was arbitrarily categorized into five risk categories, and the RI with four Risk Classes as delineated below in risk Classes as delineated above Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCategorization of Ecological Risk from heavy metal using \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{E}}_{\\varvec{r}}^{\\varvec{i}}\\:\\varvec{i}\\varvec{n}\\varvec{d}\\varvec{e}\\varvec{x}\\:\\)\u003c/span\u003e\u003c/span\u003eand \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\sum\\:\\varvec{E}}_{\\varvec{r}}^{\\varvec{i}}\\:\\varvec{i}\\varvec{n}\\varvec{d}\\varvec{e}\\varvec{x}\\)\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eRisk Classes of individual metal\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c5\" namest=\"c4\" rowspan=\"2\"\u003e \u003cp\u003eRisk Classes for the total metal concentrations\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{E}_{r}^{i}\\:\\:\\)\u003c/span\u003e\u003c/span\u003eIndex Range\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLog 10 Range\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRisk Category\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40 or below\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt; 1.6021\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\:\\sum\\:E}_{r}^{i}\\:\\:\\)\u003c/span\u003e\u003c/span\u003e\u003cb\u003eIndex Range\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eRisk Category\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e41–80\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.6021–1.9031\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e150 or below\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e81–160\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.9031–2.2041\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eConsiderable\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e151–300\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e161–320\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.2041–2.5052\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e301–600\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt; 320\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt; 2.5052\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVery High\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt; 600\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVery High\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eThe risk index (RI) represents the ecological risk of six studied heavy metal concentrations in the soil and sediment, which was calculated using the formula (Hakanson, 1980). As per the above categorization, the RI values for all the metals in soil (except Cd considered) were considered under Low or moderate risk categories. However, Cd was ranked as a Very High-Risk category. RI values Mn and Zn were considered under Low risk for categories. The remaining, Cd, Pb, and Cu, were ranked in the Very High-Risk category.\u003c/p\u003e \u003cp\u003eThe degree of ecological risk in the log 10 range can be categorized as follows:\u0026lt;Eir 1.60: low risk, 1.60 \u0026lt; Eir \u0026lt; 1.90: moderate risk, 1.90 \u0026lt; Eir \u0026lt; 2.21: considerable risk, 2.20 \u0026lt; Eir2.50: high-risk, Eir \u0026gt; 2.50: very-high-risk classes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Bio-concentration and translocation factors of Study Area and Coringa\u003c/h2\u003e \u003cp\u003eThe calculation of BCF and TF is integral in assessing a plant's efficiency in accumulating heavy metals from sediment and their subsequent translocation from roots to stems and leaves. This evaluation is crucial for understanding the plant's response to heavy metal uptake and distribution within its various parts.\u003c/p\u003e \u003cp\u003eTo assess the efficiency of the plant in accumulating heavy metals from sediment to its roots and translocating them from roots to stems, BCF and Translocation Factor (TF) were computed. The formulations for BCF and TF calculations were derived from established methodologies (Wilson \u0026amp; Pyatt, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Zacchini et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Equd\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equd\" name=\"EquationSource\"\u003e\n$$\\:\\text{B}\\text{C}\\text{F}\\:=\\:\\frac{\\text{C}\\text{p}\\text{l}\\text{a}\\text{n}\\text{t}}{\\text{C}\\text{r}\\text{o}\\text{o}\\text{t}}\\:\\text{T}\\text{F}\\:=\\:\\frac{\\text{l}\\text{e}\\text{a}\\text{f}}{\\text{C}\\:\\text{s}\\text{e}\\text{d}\\text{i}\\text{m}\\text{e}\\text{n}\\text{t}}$$\u003c/div\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e \u003cp\u003eHeavy metals available for plant uptake include soluble components in the soil solution or those easily solubilized by root exudates. The calculated BCF and TF, following the established formulas by (Wilson \u0026amp; Pyatt, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Zacchini et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), offer quantitative measures of the plant's ability to accumulate and translocate heavy metals, providing valuable insights into the ecological dynamics of metal absorption and distribution in the studied plant species.\u003c/p\u003e \u003cp\u003eThe BCF, serving as an indicator of the ability of plants and aquatic organisms to absorb pollutants from sediment, reveals the ratio of trace metal content in tissue to that in sediment (Usman et al., 2012; Qiu et al., 2011). In the case of \u003cem\u003eAvicennia marina\u003c/em\u003e, most BCF values were deemed excessively high, signifying its role as a highly efficient plant for bioaccumulating metals. Notably, the study observed significantly elevated BCF values for Cu in leaf, branch, and root, as well as for Cr in branch and root, indicating the pronounced bio-accumulation and heightened mobility of these metals in \u003cem\u003eAvicennia marina\u003c/em\u003e compared to other investigated metals. The reported bio-concentration factors in this study surpassed those documented by (Qiu et al., 2011; Jian et al., 2017), emphasizing the exceptional bio-accumulation potential of \u003cem\u003eAvicennia marina\u003c/em\u003e in the studied environmental context.\u003c/p\u003e \u003cp\u003eThe heavy metal concentrations in \u003cem\u003eAvicennia marina\u003c/em\u003e roots and their respective Bioconcentration Factors in the sediments at various stations are presented in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. The Chromium BCF exhibited a range from 32.28 at AS4 to 4.54 at AS1, with a mean value of 18.41. Manganese displayed a range between 2.23 at DS1 and 0.16 at AS2, with a mean of 1.20. Iron variations spanned from 3.34 at DS1 to 0.34 at AS3, yielding a mean of 1.84. Cobalt exhibited a range between 4.59 at AS4 and 0.63 at DS2, with a mean of 2.61. Nickel values ranged from 4.18 at DS1 to 0.48 at DS2, with an overall mean of 0.58. Copper values ranged between 2.64 at DS2 and 0.21 at DS3, resulting in a mean of 1.42. Zinc concentrations ranged from 5.04 at DS1 to 0.30 at AS1, with a mean of 2.67. Cadmium levels varied between 3.60 at DS1 and 0.19 at AS1, yielding a mean of 1.90. Barium concentrations ranged from 29.03 at AS4 to 0.08 at DS2, resulting in a mean of 14.55. Lead concentrations range from 71.55 at DS1 to 7.46 at DS4, with a mean value of 39.51.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBio-concentration factor (BCF) in \u003cem\u003eAvicennia marina\u003c/em\u003e metal concentration in soil to roots of study area and control Coringa (Root/Soil)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"11\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMn\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFe\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCo\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNi\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCu\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eZn\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eBa\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17.19\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.23\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.34\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.18\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.27\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5.04\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e3.60\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e71.55\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.03\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.64\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.43\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.87\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e26.79\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.25\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.67\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.45\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.42\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e27.82\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.96\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.38\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.99\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e7.46\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAS1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.54\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e29.69\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAS2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.01\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.39\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.01\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e51.57\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAS3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.44\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e22.34\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAS4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32.28\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.73\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.59\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.60\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e29.03\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e8.40\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCoringa\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.52\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.92\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e4.51\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eThe heavy metal concentrations in \u003cem\u003eAvicennia marina\u003c/em\u003e stems, and their respective Bioconcentration Factors in the sediments at various stations are presented in Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e. Chromium BCF ranged from 12.1 at DS1 to 0.89 at AS1, with a mean value 5.87. Manganese ranged between 1.04 at AS4 and 0.04 at DS2, resulting in a mean of 0.28. Iron variations spanned from 1.39 at DS3 to 0.21 at DS4, yielding a mean of 0.81. Cobalt exhibited a range between 6.96 at AS4 and 0.22 at DS4, with a mean of 1.57. Nickel values ranged from 5.06 at DS1 to 0.1 at DS4, with an overall mean of 1.08. Copper values ranged between 1.68 at DS1 and 0.22 at AS4, resulting in a mean of 0.66. Zinc concentrations ranged from 0.69 at DS1 to 0.04 at AS2, with a mean of 0.34. Cadmium levels varied between 0.88 at AS2 and 0.14 at DS4, yielding a mean of 0.49. Barium concentrations ranged from 33.5 at AS4 to 0.017 at DS1, resulting in a mean of 4.75. Lead concentrations range from 34.46 at AS2 to 0.736 at DS4, with a mean value of 10.62.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBio-concentration factor (BCF) in \u003cem\u003eAvicennia marina\u003c/em\u003e metal concentration in soil to stem of study area and control Coringa (Stem/Soil)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"11\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMn\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFe\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCo\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNi\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCu\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eZn\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eBa\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.06\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.68\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.90\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e3.87\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.03\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.51\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e3.73\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.41\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e4.43\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAS1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.67\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e7.04\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAS2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.26\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.48\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e34.46\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAS3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.98\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e9.58\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAS4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.37\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.96\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e33.50\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e21.11\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCoringa\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.78\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.26\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.17\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.44\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e87.94\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eThe heavy metal concentrations in \u003cem\u003eAvicennia marina\u003c/em\u003e leaves and their respective Bioconcentration Factors (BCF) in the sediments at various stations are presented in Table\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e. Chromium BCF exhibited a range from 13.13 at AS4 to 2.12 at AS3, with a mean value of 6.87. Manganese ranged between 1.14 at AS4 and 0.11 at DS1, resulting in a mean of 0.41. Iron variations spanned from 1.16 at AS3 to 0.29 at AS2, yielding a mean of 0.68. Cobalt exhibited a range between 11.29 at AS2 and 0.08 at DS1, with a mean of 3.85. Nickel values ranged from 2.54 at DS2 to 0.10 at AS2, with an overall mean of 0.59. Copper values ranged between 0.83 at AS2 and 0.08 at DS2, resulting in a mean of 0.34. Zinc concentrations ranged from 0.64 at AS3 to 0.05 at AS1, with a mean of 0.25. Cadmium levels varied between 1.85 at AS4 and 0.07 at DS1, yielding a mean of 0.50. Barium concentrations ranged from 29.76 at AS4 to 0.09 at DS2, resulting in a mean of 10.32. Lead concentrations range from 27.66 at AS2 to 1.04 at AS3, with a mean value of 15.78.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBio-concentration factor (BCF) in \u003cem\u003eAvicennia marina\u003c/em\u003e metal concentration in soil to leaf of study area and control Coringa (Leaf/Soil)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"11\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMn\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFe\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCo\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNi\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCu\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eZn\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eBa\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.53\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e4.50\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.44\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.54\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e27.65\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.86\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e10.44\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDS4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.88\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e19.00\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAS1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.78\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e21.42\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAS2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.20\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.29\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.50\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e27.66\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAS3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.12\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAS4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.13\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.33\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.85\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e29.76\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e14.48\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCoringa\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.02\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.92\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3.25\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e194.05\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eAdditionally, Ex-situ studies were conducted in a greenhouse to investigate the accumulation capacities of \u003cem\u003eAvicennia marina.\u003c/em\u003e Lead (Pb), Chromium (Cr), and Cadmium (Cd) were chosen as the heavy metals for toxicity testing. Different concentrations of each heavy metal, specifically 1mg, 5mg, and 10mg/kg of soil, were incorporated into the soil for greenhouse experiments with a control. The actual concentrations of heavy metals in the sediments, following the addition of known amounts of Pb, Cr, and Cd to various sediments collected from VEC and coring, are outlined in Table\u0026nbsp;\u003cspan refid=\"Tab11\" class=\"InternalRef\"\u003e11\u003c/span\u003e. These studies are designed to evaluate the impacts of elevated concentrations of different heavy metals without introducing further changes due to additional contamination. After completing the hundred-day growth period, the \u003cem\u003eAvicennia marina\u003c/em\u003e plants were harvested, and their different parts were separated. Subsequently, an analysis was conducted to determine the concentration of heavy metal accumulation in all components of the plants. The soil concentrations in the pots were also analyzed after mixing with known amounts of induced metals, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. In this exploration, I have delved into the repercussions of heavy metal exposure on plants, scrutinizing the influence of varying concentrations of heavy metal stress and evaluating the plant's capacity for tolerance.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab11\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 11\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe concentration of heavy metals in the soils of the greenhouse after mixing with known amounts of VEC soils\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoil concentrations\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVizag study area\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.36\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.74\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoringa\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.449\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.42\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT 1mg/kg\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.36\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.74\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT 5mg/kg\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.36\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.74\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT 10mgkg\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.36\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.74\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eThe concentration of cadmium in the roots of \u003cem\u003eAvicennia marina\u003c/em\u003e plants exhibited variations, ranging from a minimum of 0.11 µg/g in Coringa to a maximum of 59.52 µg/g in the greenhouse pot labeled as T10, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Similarly, in the stems, the Cadmium concentration ranged from a minimum of 0.23 µg/g in Coringa to a maximum of 17.25 µg/g in T10. In the leaves, the Cadmium concentration varied from a minimum of 0.14 µg/g in Coringa to 30.81 µg/g in the T10 greenhouse pot. The concentration trends across all studies consistently revealed that Cd predominantly accumulated in the roots and stems before reaching the leaves, with concentrations increasing in correlation with soil concentrations, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u003c/p\u003e \u003cp\u003eThe Pb concentration in the roots of \u003cem\u003eAvicennia marina\u003c/em\u003e plants varied, with a minimum of 6.41 µg/g in Coringa and a maximum of 124.5 µg/g in the VEC study area. In the stems, the lead concentration ranged from a minimum of 1.28 µg/g in the VEC study area to a maximum of 124.87 µg/g in Coringa. For leaves, the lead concentration in plants from the VEC study area had a minimum of 7.83 µg/g and a maximum of 275.55 µg/g in the VEC study area. The concentration trends across all studies consistently showed that Pb predominantly accumulated in the roots and stems before reaching the leaves, with concentrations increasing in correlation with soil concentrations. Notably, in Coringa, a reversal in accumulation pattern was observed, with Pb concentrations in leaves surpassing those in stems and roots. This variation suggests a specific behavior in Pb accumulation in Coringa compared to other study areas. All concentration data with respective soil concentrations are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. The figure depicts various plant tissues' dynamic Cd accumulation patterns. As the induced metal concentration increases in the greenhouse, the accumulation follows a distinct order, progressing from roots to stems and leaves. This graphical representation provides a visual insight into the observed Cd distribution within different parts of the \u003cem\u003eAvicennia marina\u003c/em\u003e plant under varying metal concentrations.\u003c/p\u003e \u003cp\u003eMetal accumulation in above-ground plant parts is a crucial indicator of controlling heavy metal contamination through a phytoextraction strategy. When bio-concentration and translocation factors exceed 1, it signifies a greater potential for metal phytoextraction from polluted sites. The computed BCF values from the available data indicate that the roots exhibit notably high BCFs in the 10mg/kg greenhouse studies compared to other sites, particularly for metals Cr, Cd, and Pb. Among these metals, Cr demonstrated a particularly high BCF concentration in the soil (Table\u0026nbsp;\u003cspan refid=\"Tab12\" class=\"InternalRef\"\u003e12\u003c/span\u003e). This observation underscores the efficacy of the phytoextraction strategy, specifically highlighting the potential of \u003cem\u003eAvicennia marina\u003c/em\u003e to accumulate and extract heavy metals from contaminated environments, particularly in the greenhouse setting with elevated metal concentrations.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab12\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 12\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHeavy metals accumulation Concentration in mangrove plants of \u003cem\u003eAvicennia marina\u003c/em\u003e tissues was in increasing order according to increasing the induced metal concentration (Cr, Cd, Pb) in the greenhouse.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetals\u003c/p\u003e \u003cp\u003eConcentrations\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT1mg/kg\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eT 5mg/kg\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eT 10mg/kg\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCr\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.7\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCd\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.52\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.85\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePb\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.81\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51.5\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRoot\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCr\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.86\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.4\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCd\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.92\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.84\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePb\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63.21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.52\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61.38\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStem\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCr\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.37\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.6\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCd\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.54\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.7\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePb\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54.45\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.25\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57.2\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSediment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCr\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.08\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCd\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.36\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.36\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.74\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePb\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.74\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.74\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.74\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eAfter conducting an anatomical structure examination using a fluorescent microscope, it was observed that there were no significant changes when comparing the transverse section images of \u003cem\u003eAvicennia marina\u003c/em\u003e plant parts at induced metal concentrations of 1 mg, 5 mg, and 10 mg of Cr, Cd, Pb, under different light filters.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Post-harvest Metal Accumulation Analysis in \u003cem\u003eAvicennia Marina\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eFollowing the 100-day growth period and subsequent harvesting, the various parts of \u003cem\u003eAvicennia marina\u003c/em\u003e plants were meticulously separated and subjected to detailed analysis. The findings revealed a distinct metal accumulation pattern, with a noteworthy emphasis on Pb and Cd concentrations.\u003c/p\u003e \u003cp\u003ePrimarily, the roots of \u003cem\u003eAvicennia marina\u003c/em\u003e exhibited the highest accumulations of both Lead and Cadmium. Subsequently, accumulations were observed in the stems, with the recorded concentrations showing an increasing trend corresponding to the elevated concentrations of these metals in the sediments.\u003c/p\u003e \u003cp\u003eThis observed accumulation pattern underscores the plant's selective uptake and storage of Lead and Cadmium, with the roots serving as a primary repository for these metals. The systematic increase in concentrations from roots to stems further emphasizes the dynamic interaction between the plant and the surrounding metal-rich environment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.4 \u003cem\u003eAvicennia marina\u003c/em\u003e Physiology\u003c/h2\u003e \u003cp\u003eIn Fig.\u0026nbsp;7, where the metal concentrations were 1 mg/kg (T1) under the blue light filter (A-D-G), the anatomical structures Leaf, Root, and Stem, respectively, were examined; similarly, under normal light (B-E-H) and green light filter (C-F-I), the anatomical structures of Leaf, Root, Stem, respectively were examined. Despite the 1 mg/kg metal concentration, there were no alterations in the anatomical features of the plant parts.\u003c/p\u003e \u003cp\u003eIn Fig.\u0026nbsp;8, where the metal concentrations were 5 mg/kg mg (T5), under the blue light filter (A-D-G), the anatomical structures of the root, leaf, and stem were examined. Similarly, under normal light (B-E-H) and green light filter (C-F-I), the root, leaf, and stem anatomical structures were examined. Despite the higher metal concentration, there were no noticeable alterations in the anatomical features of the plant parts.\u003c/p\u003e \u003cp\u003eLikewise, in Fig.\u0026nbsp;9, depicting metal concentrations of 10 mg/kg, the examination under different light filters (blue light filter A-D-G, normal light B-E-H, and green light filter C-F-I) revealed no significant structural changes in the leaf, stem, and root compared to lower metal concentrations. Although the high fluorescent light absorption was observed in the 10 mg/kg (T10) concentration, indicative of metal accumulation in the cortex and epidermis, the overall structural integrity of the plant parts remained unchanged.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn a comprehensive exploration, the study uncovers the ubiquitous presence of three heavy metals, Cr, Pb, and Cd, in the intricate tissues of \u003cem\u003eAvicennia marina\u003c/em\u003e, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e10\u003c/span\u003e. The roots stand out as prominent repositories for Cd and Pb, surpassing sediment levels and other plant parts. \u003cem\u003eAvicennia marina\u003c/em\u003e emerges as a proficient metal accumulator, eclipsing sediments in metal absorptions and affirming its candidacy for bio-accumulation in the remediation of heavy metal-contaminated coastal domains. This investigation unequivocally establishes \u003cem\u003eAvicennia marina\u003c/em\u003e as an exceptionally potent bio-accumulator. Its capacity to amass metals, even with subtle alterations in physiological structures, positions it as a stalwart bio-remediator and phyto-stabilizer, particularly in heavily metal-polluted coastal regions. As a linchpin in the ecological rejuvenation of metal-laden coastal ecosystems, \u003cem\u003eAvicennia marina\u003c/em\u003e exhibits unparalleled potential as a bio-accumulator and a linchpin in phytoremediation initiatives. The observed variability in Bioconcentration Factors (BCFs) underscores \u003cem\u003eAvicennia marina's\u003c/em\u003e adaptability, excelling as both a bioaccumulator and phytoextractor. In this comparative analysis, plants in sediments with lower metal concentrations boast the highest BCFs. In contrast, those in higher metal concentration sediments showcase superior translocation factors and an adaptive response to environmental nuances. Aligning with these revelations, the study demystifies the intricate relationship between mangroves' metal concentrations, BCFs, and translocation factors. \u003cem\u003eAvicennia marina's\u003c/em\u003e nuanced responses, featuring efficient metal uptake and translocation, reaffirm its adaptive prowess in diverse environmental conditions; this study delves into the intricate adaptive mechanisms of \u003cem\u003eAvicennia marina\u003c/em\u003e, portraying it as a versatile and resilient species adept at navigating varying metal concentration landscapes. These insights enrich our comprehension of mangrove ecosystems, propelling \u003cem\u003eAvicennia marina\u003c/em\u003e to the forefront of phytoremediation and ecological restoration endeavors.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Ministry of Environment, Forests, and Climate Change (MoEF \u0026amp; CC), New Delhi, under Grant number 22-49/2010-CS-I. All authors acknowledge their support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eK. Anand Raju:\u003c/strong\u003e Writing \u0026ndash; review \u0026amp; editing, Writing \u0026ndash; original draft, Visualization, Supervision, Software, Resources, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. \u003cstrong\u003eRamakrishna Chintala:\u003c/strong\u003e Writing \u0026ndash; review \u0026amp; editing, Writing \u0026ndash; original draft, Supervision, Resources, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. \u003cstrong\u003eSrinivas Reka:\u003c/strong\u003e Writing \u0026ndash; review \u0026amp; editing, Writing \u0026ndash; original draft, Visualization, Software, Resources, Methodology, Investigation, Formal analysis, Conceptualization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data supporting this study will be made available upon request.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChiu, C.Y., Chou, C.H., (1991). The distribution and influence of heavy metals in the Tamshui Estuary mangrove forests in Taiwan. Soil \u003cem\u003eScience\u003c/em\u003e and Plant Nutrition 37, 659\u0026ndash;669.\u003c/li\u003e\n\u003cli\u003eEapen, S., and D\u0026apos;souza, S. F. (2005). Prospects of genetic engineering of plants for phytoremediation of toxic metal. Biotechnol. Adv. 23, 97\u0026ndash;114. doi: 10.1016/j.biotechadv.2004.10.001.\u003c/li\u003e\n\u003cli\u003eEpstein, E. (1999). Silicon. Annu. Rev. Plant Physiol. Plant Mol. Biol. 50, 641\u0026ndash;664. doi: 10.1146/annurev.arplant.50.1.641\u003c/li\u003e\n\u003cli\u003eErnst, W. H. O. (2006). Evolution of metal tolerance in higher plants. For. Snow Landsc. Res. 80, 251\u0026ndash;274. \u003c/li\u003e\n\u003cli\u003eG.R MacFarlane, A Pulkownik, M.D Burchett (2003), Accumulation and distribution of heavy metals in the grey mangrove, \u003cem\u003eAvicennia marina\u003c/em\u003e (Forsk.)Vierh.: biological indication potential, Environmental Pollution123, May, 139-151.\u003c/li\u003e\n\u003cli\u003eKavamura, V. N., and Esposito, E. (2010). Biotechnological strategies applied to the decontamination of sediments polluted with heavy metal. Biotechnol. Adv. 28, 61\u0026ndash;69. doi: 10.1016/j.biotechadv.2009.09.002.\u003c/li\u003e\n\u003cli\u003eLacerda LD (1997). Trace metals in mangrove plantas: why such low concentrations In: Kjerfve B, Lacerda LD, Diop HS (eds.), Mangrove ecosystem studies in Latin America and Africa, pp. 171-178. Unesco, Paris.\u003c/li\u003e\n\u003cli\u003eMacFarlane, G.R., Burchett, M.D., (2000). Cellular distribution of Cu, Pb, and Zn in the Grey Mangrove \u003cem\u003eAvicennia marina\u003c/em\u003e (Forsk.). Veirh. Aquatic Botany 68, 45\u0026ndash;59.\u003c/li\u003e\n\u003cli\u003eMiransari, M. (2011). Hyperaccumulators, arbuscular mycorrhizal fungi and stress of heavy metal. Biotechnol. Adv. 29, 645\u0026ndash;653. doi: 10.1016/j.biotechadv.2011.04.006.\u003c/li\u003e\n\u003cli\u003ePeng, L., Wenjian, Z., Zhenji, L., (1997). Distribution and accumulation of heavy metals in \u003cem\u003eAvicennia marina\u003c/em\u003e community in Shenzhen, China. Journal of Environmental Sciences 9 (4), 472\u0026ndash;479.\u003c/li\u003e\n\u003cli\u003eRaju, K.A., Ramakrishna, C (2021). The effects of heavy metals on the anatomical structures of Avicennia marina (Forssk.) Vierh. Braz. J. Bot 44, 439\u0026ndash;447. https://doi.org/10.1007/s40415-021-00698-9\u003c/li\u003e\n\u003cli\u003eRao, C.K., Chinnaraj, S., Inamdar, S.N., Untawale, A.G., (1991). Arsenic content in certain marine brown algae and mangroves from the Goa coast. Indian Journal of Marine Science 20, 283\u0026ndash; 285.\u003c/li\u003e\n\u003cli\u003eSaenger, P., McConchie, D., Clark, M., (1990). Mangrove Forests as a Buffer Zone Between Anthropogenically Polluted Areas and the Sea. In: Saenger, P. (Ed.), Proceedings 1990 CZMWorkshop. Yeppoon, Qld, pp. 280\u0026ndash;297.\u003c/li\u003e\n\u003cli\u003eSilva, C.A.R., Lacerda, L.D., Rezende, C.E., (1990). Heavy metal reservoirs in a red mangrove forest. Biotropica 22, 339\u0026ndash;345.\u003c/li\u003e\n\u003cli\u003eTam, N.F.Y., Wong, Y.S., (1995). Spatial and temporal variations of heavy metal contamination in sediments of a mangrove swamp in Hong Kong. Marine Pollution Bulletin 31 (4\u0026ndash;12), 254\u0026ndash;261.\u003c/li\u003e\n\u003cli\u003eThomas, C., Eong, O.J., (1984). Effects of the heavy metals Zn and Pb on \u003cem\u003eR. mucronata\u003c/em\u003e and \u003cem\u003eA. alba \u003c/em\u003eseedlings. In: Soepadmo, E., Rao, A.M., MacIntosh, M.D. (Eds.), Proceedings of the Asian Symposium on Mangroves and Environment; Research and Management. ISME, Malaysia, pp. 568\u0026ndash;574.\u003c/li\u003e\n\u003cli\u003eThomas, G., Fernandez, T.V., (1997). Incidence of heavy metals in the mangrove flora and sediments in Kerala, India. Hydrobiologia 352, 77\u0026ndash;87.\u003c/li\u003e\n\u003cli\u003eWilson B, Pyatt FB (2007) Heavy metal bioaccumulation by the important food plant, olea europaea L., in an ancient metalliferous pollutedarea of cyprus. Bull Environ Contam Toxicol 78:390\u0026ndash;394. https ://doi.org/10.1007/s0012 8-007-9162-2\u003c/li\u003e\n\u003cli\u003eYang, X., Feng, Y., He, Z., and Stoffell, P. J. (2005). Molecular mechanisms of heavy metal hyperaccumulation and phytoremediation. J. Trace Elem. Med. Biol. 18, 339\u0026ndash;353. doi: 10.1016/j.jtemb.2005.02.007.\u003c/li\u003e\n\u003cli\u003eZacchini M, Pietrini F, Scarascia Mugnozza G, Lori V, Pietrosanti L, Massacci A (2009) Metal tolerance, accumulation and translocation in poplar and willow clones treated with Cadmium in hydroponics. Water Air Soil Pollut 197:23\u0026ndash;34. https ://doi.org/10.1007/ s1127 0-008-9788-7.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"ecotoxicology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ectx","sideBox":"Learn more about [Ecotoxicology](https://www.springer.com/journal/10646)","snPcode":"10646","submissionUrl":"https://submission.nature.com/new-submission/10646/3","title":"Ecotoxicology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Meghadrigedda Creek, Bioconcentration factor, Translocation factor, Mangroves, Coringa, Avicennia marina","lastPublishedDoi":"10.21203/rs.3.rs-5243473/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5243473/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study explores the impact of heavy metal accumulation on \u003cem\u003eAvicennia marina's\u003c/em\u003e physiological and anatomical aspects, focusing on its capacity for metal uptake and tolerance. Conducted across the Visakhapatnam Entrance Channel (VEC) field, Control Coringa mangroves, and controlled ex-situ greenhouse environments, the study examines the accumulation patterns of chromium (Cr), lead (Pb), and cadmium (Cd). The Potential Ecological Risk Index (RI) indicated that Cd posed a very high risk, with Cr and Pb also showing significant risks. Heavy metal concentrations in the VEC from Cr (36.58\u0026ndash;76.41 \u0026micro;g/g), Mn (209.19\u0026ndash;428.8 \u0026micro;g/g), Cu (29.91\u0026ndash;45.56 \u0026micro;g/g), Zn (306.44\u0026ndash;925.16 \u0026micro;g/g), Cd (2.49\u0026ndash;4.65 \u0026micro;g/g), and Pb (42.0\u0026ndash;155.64 \u0026micro;g/g). The potential ecological risk coefficient Eir consistently placed Cd in the high-risk category, with other metals generally in low to moderate-risk categories. Physiological changes in plant tissues were analyzed using a fluorescence microscope, and higher metal concentrations were assessed with Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The Bioconcentration Factor (BCF) and Translocation Factor (TF) were calculated to evaluate metal accumulation and translocation efficiency. In VEC, significant anatomical changes in \u003cem\u003eAvicennia marina\u003c/em\u003e included moist leaves, expanded mesophyll areas, and thick cuticles with heavy metal deposits, especially in high metal concentrations. The region's pollution, driven by port activities and nearby industries, elevated heavy metal levels in sediments. Cd was identified as a very high-risk element at all stations, while other metals were categorized under low or moderate risk. Comparative analysis with the Control Coringa mangroves indicated potential variations in metal accumulation strategies between the two regions within the same species. Anatomical changes in the VEC were more pronounced than fewer disruptions in Coringa mangroves, suggesting differential adaptive responses to environmental stressors. This study underscores the need for targeted environmental management strategies to mitigate heavy metal contamination and highlights the importance of maintaining healthy mangrove habitats amidst increasing anthropogenic pressures.\u003c/p\u003e","manuscriptTitle":"Bioaccumulation pattern of heavy metals in Avicennia marina at Visakhapatnam and Coringa mangroves in India","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-14 13:30:04","doi":"10.21203/rs.3.rs-5243473/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-16T12:42:36+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-14T01:32:04+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-29T16:02:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"10112392028142387703237306729787687321","date":"2025-03-29T14:05:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"146463624341796701159660514848403695361","date":"2025-03-24T16:12:48+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-24T13:26:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-10-11T08:37:04+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-10-11T08:33:21+00:00","index":"","fulltext":""},{"type":"submitted","content":"Ecotoxicology","date":"2024-10-11T05:10:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"ecotoxicology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ectx","sideBox":"Learn more about [Ecotoxicology](https://www.springer.com/journal/10646)","snPcode":"10646","submissionUrl":"https://submission.nature.com/new-submission/10646/3","title":"Ecotoxicology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"6004a450-13f7-44cf-b298-fca40755a70d","owner":[],"postedDate":"October 14th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-08-07T07:28:26+00:00","versionOfRecord":{"articleIdentity":"rs-5243473","link":"https://doi.org/10.1007/s10646-025-02932-6","journal":{"identity":"ecotoxicology","isVorOnly":false,"title":"Ecotoxicology"},"publishedOn":"2025-07-17 16:05:38","publishedOnDateReadable":"July 17th, 2025"},"versionCreatedAt":"2024-10-14 13:30:04","video":"","vorDoi":"10.1007/s10646-025-02932-6","vorDoiUrl":"https://doi.org/10.1007/s10646-025-02932-6","workflowStages":[]},"version":"v1","identity":"rs-5243473","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5243473","identity":"rs-5243473","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}