Heavy metals bio-accumulation in tilapia and catfish species in Lake Rukwa ecosystem Tanzania

Heavy metals bio-accumulation in tilapia and catfish species in Lake Rukwa ecosystem Tanzania

Journal Pre-proof Heavy metals bio-accumulation in tilapia and catfish species in Lake Rukwa ecosystem Tanzania Levinus Leonard Mapenzi, Moses Joel S...

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Journal Pre-proof Heavy metals bio-accumulation in tilapia and catfish species in Lake Rukwa ecosystem Tanzania

Levinus Leonard Mapenzi, Moses Joel Shimba, Edward Angelo Moto, Reuben Silas Maghembe, Aviti John Mmochi PII:

S0375-6742(18)30624-1

DOI:

https://doi.org/10.1016/j.gexplo.2019.106413

Reference:

GEXPLO 106413

To appear in:

Journal of Geochemical Exploration

Received date:

29 October 2018

Revised date:

26 June 2019

Accepted date:

4 November 2019

Please cite this article as: L.L. Mapenzi, M.J. Shimba, E.A. Moto, et al., Heavy metals bioaccumulation in tilapia and catfish species in Lake Rukwa ecosystem Tanzania, Journal of Geochemical Exploration (2019), https://doi.org/10.1016/j.gexplo.2019.106413

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

© 2019 Published by Elsevier.

Journal Pre-proof Heavy Metals Bio-accumulation in Tilapia and Catfish Species in Lake Rukwa Ecosystem Tanzania Levinus Leonard Mapenzi, 3Moses Joel Shimba, 1Edward Angelo Moto, 4Reuben Silas Maghembe and 2Aviti John Mmochi 1 Department of Bioinformatics and Biotechnology, School of Biological Sciences, P. O. Box 338, University of Dodoma, Tanzania 2 Institute of Marine Science, University of Dar es Salaam, P.O. Box 668 Zanzibar, Tanzania 3 Department of Conservation Biology, P. O. Box 338, University of Dodoma, Tanzania 4 Department of Biological and Marine Sciences, Marian University College, P.O. Box 47, Bagamoyo, Pwani, Tanzania Corresponding author: [email protected]

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Abstract

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Investigation on accumulation of selected heavy metals of Zinc, Mercury, Copper, Lead, Chromium and Nickel in sediment, water and muscle tissues of Clarias gariepinus (African

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catfish) and Oreochromis esculentus (Singida tilapia) fish was done in Lake Rukwa, Tanzania. Samples were obtained from transects of 100 m long extending from Luika and Songwe River

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mouths to offshore. Water and sediment samples were collected directly from the study sites while fish were obtained from fisherfolk operating in the Lake. Sampling was done in dry and

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wet seasons. Heavy metals analysis was done using the Atomic Absorption Spectrophotometry. Concentration of heavy metals was higher in catfish than in tilapia (p < 0.05). There were no

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significant differences in metal concentration between seasons except for Zn (p < 0.05). In this

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study only Zn was above standard WHO concentrations in fish muscles. Likewise, the concentrations of heavy metals were within recommended limits in water except Pb. The detected metals in sediment were above recommended limits. Other heavy metals in particular Hg, Ni and Cr were not detected in all samples. Therefore, studied fish from Lake Rukwa may threaten human health upon consumption. The detected heavy metals in water were within the maximum residual levels (MRLs) permitted by WHO. Sustainable Lake Rukwa’s fish, ecosystem management and conservation are recommended to discourage heavy metals discharge from elevating beyond permissible limits and thus prevent harmful health effects to fish consumers and water users. Key words: Bio-accumulation, Fisher folk, Catfish, Singida tilapia, Heavy metals

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Introduction Heavy metals produced by local and commercial miners may pose negative effects to the environment and living organisms. Pollution from mining activities is among the most common sources of highly toxic chemical substances in aquatic and terrestrial ecosystems (Gerhardt, 2000; Henry and Mamboya, 2012). Mining pollution may be due to seepage of chemicals used for gold processing through soil in mining sites into aquatic ecosystems. Heavy metals may also

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enter aquatic ecosystems through atmospheric deposition, geological weathering, agricultural,

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domestic and industrial waste discharges (Demirak et al., 2006; Maier et al., 2014). Heavy metals impact fish due to their toxicity further enhanced by bio-accumulation and bio-

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magnification (Afshan et al., 2014).Contaminants in water enter the food chain leading to negative impacts (Akinmoladun et al., 2007) and mortality to fish (Per-Arne et al., 1997;

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Akinmoladun, et al., 2007). Heavy metal bio-accumulation in fish are important because fish

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tissues have higher uptake levels of some metals e.g. arsenic and mercury (Afshan et al., 2014). Accordingly, such pollutants can easily reach human through bio-magnification up the food chain (Amundsen et al., 1997), leading to diseases (Al-Yousuf et al., 2000). The prevalence of

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heavy metals in measurable amounts across all aquatic ecosystems (Authman et al., 2015) raises

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an important environmental concern.

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Afshan et al. (2014) reported that heavy metals enter fish bodies through gills, gastro intestinal tract and the body surfaces. The metals impact fish growth and reproductive potential (Per-Arne et al., 1997), deteriorate immunity and cause pathological changes (Authman et al., 2015). Fish respond to heavy metals either by accumulating, elimination or shifting them to higher trophic levels (Shah and Altindag, 2005). The fate of accumulated heavy metals in fish is dependent on storage and/or elimination capacity (Abdallah and Morsy, 2013). Therefore, higher uptake with low elimination results into high accumulation of contaminants in tissues and vice versa.

Pollutants that have been reported to negatively affect fish include mercury, chromium, copper, zinc, lead and nickel. Lake Rukwa hosts a variety of catfish species including Clarias gariepinus and tilapiines like Oreochromis rukwaensis and Oreochromis escluentus declared vulnerable

Journal Pre-proof according to IUCN Red List (2018). Therefore, the present study focused at both sustainable management and conservation of fish resources in Lake Rukwa by assessing the extent of heavy metal contamination. The primary objective of the study was to determine the concentration of heavy metals in C. gariepinus, O. esculantus, sediments and water in Lake Rukwa and its river inlets in Songwe District (former Chunya District), Songwe Region, Tanzania. Description of the Study Site Lake Rukwa is an inland lake covering an area of about 5,760 km2. Major inlets into the Lake are

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Luika, Songwe, Kikamba and Yeye Rivers. The Lake lying between 8°00′S and 32°25′E is close

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to abandoned and ongoing gold mining sites. The present study was done in the Southern part of the Lake covering Luika and Songwe River Mouths and offshore (Figure 1). Socio-economic

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activities of communities along Lake Rukwa include agriculture, livestock keeping, fishing and gold mining. The lake is surrounded by varieties of terrestrial wildlife animals and plant species.

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The Lake is also gifted with aquatic biodiversity that include hippopotamus, crocodiles, turtles

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and fish species. The lake experiences two seasons that are dry and wet annually.

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Figure 1: A map of Lake Rukwa showing the sampling stations, data source Institute of Marine Sciences, GIS lab.

Journal Pre-proof Sampling Methods Five transects were established for sampling in the South of Lake Rukwa including Luika and Songwe River mouths. The rivers flow through abandoned mines areas; current mining and artisanal fisheries are taking place. Sampling was done twice during the dry (September – October, 2016) and wet (March – May, 2017) seasons. Choice of the wet seasons based on the fact that probability that uptake of metals would be high due to River discharges and surface runoffs. Transects (100m long) on the Lake shore and River mouths were used for water and

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sediment sampling. On each transect one sampling point was set in the middle. Water samples were collected from the water surface using three water bottles each with a capacity of 0.5 litres.

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A grab sampler was used for sediment sampling on the shoreline of the lake. Fish sampling was randomly done by purchasing fresh fish from fisherfolk while they were still fishing. Sediment

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sampling was done close to river mouths where the two rivers meet (SS1), Luika (SS2) and

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Songwe (SS3) river mouths stations.

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Water quality parameters were measured in situ. These involved conductivity (μS cm−1), salinity, turbidity and temperature (°C). Salinity was measured using a hand-held salinometer (Model: YSI # 85/10 FT, USA), pH by a hand-held pH/mV meter (Model: SX 711), turbidity by

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secchi disc and coordinates by using GPS. The samples were preserved in cool boxes with ice blocks and transported to the University of Dar es Salaam, Institute of Marine Sciences where

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they were stored in a freezer at -21°C.

Laboratory Analysis

At S4 and S5 sampling stations we did not obtain sediment samples hence such two stations were not included in all analyses. All analyses lied on S1, S2 and S3. Laboratory analyses of fish, sediments and water samples were done at the University of Dar es Salaam, Chemistry Department. Fish tissue samples were dried at 80°C for 12 hours. Dried samples were then ground in a mortar. About 5 g of dried samples were weighed into beakers. Then 10 ml of concentrated nitric acid was added followed by 10 ml concentrated sulphuric acid. The reaction was left to proceed for 30 minutes. Where the reaction was slow, the beaker was placed on a hot plate and heated at 60°C. The mixture was allowed to cool before adding 10 ml of concentrated

Journal Pre-proof nitric acid followed by heating at 120-150°C until the brown fumes are finished. The reaction was allowed to cool after which 5 ml of H2O2 was added and heated for 5 minutes. This was repeated several times until the fumes are finished. Samples were then filtered into a 50 ml volumetric flask, diluted to the mark with de-ionized water prior to analysis using Atomic Absorption Spectrometer (Spectrum Thermo Scientific ICE 3000 series). Maximum limits for heavy metals concentration in fish, water and sediments as recommended by WHO are indicated (Table 2). The following detection limits were used to detect heavy metals concentration in fish

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tissues, sediment and water (Table 1).

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Table 1: Detection limits of heavy metals in fish, sediment and water S/No Metal Detection Limit 0.01 mg/l

2. Cr

0.00 2 mg/l

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0.009 mg/l

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3. Ni

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1. Hg

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4. Cu

0.005 mg/l

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5. Pb

0.001 mg/l

recommendations

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Table 2: Maximum limits of heavy metals in fish, sediment and water as per WHO

Maximum Limit WHO/FEPA Water Sediment Fish mg/kg mg/L mg/kg Zn 3 0.0123 30 Cu 1 0.025 3 Pb 0.01 0.04 2

Statistical Data Analysis

Journal Pre-proof All data for water quality and fish abundance were pooled followed by Kolmogorov–Smirnov normality and Levene homoscedasticity tests respectively. The concentration of heavy metals in water, sediment, fish tissues and water quality were found to be normally distributed and behaved homoscedastically. Therefore, statistical analysis of the data was done using one-way ANOVA in Statistica 10 software. Accumulation of heavy metals in fish was analysed between the two fish species (African catfish and Singida tilapia) which are the commercial and subsistence fish species in Lake Rukwa. Spearman correlation between water and heavy metals accumulation in fish was also conducted. Fish diversity index was analysed using Primer 6

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software. Significant variation in heavy metals concentration of the tested samples was done

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following Turkey tests.

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Results

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Seasonal and spatial variability in heavy metals

Cu showed significant seasonal variation (p <0.04, Table 3) with the highest concentration during the wet season. Zinc and lead did not reveal any significant variation among seasons (p >

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0.05, Table 3) while Hg, Cr and Ni were not detected in the water. On the overall, there were no

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significant variations in heavy metals among stations (p > 0.05, Table 3). Table 3: Seasonal and spatial concentrations of heavy metals (mg/L) in water where; DS and WS

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denote dry and wet seasons while SS1-SS3 denote sampling stations

Seasonal variation Metal DS WS

p

SS1

Variation in Sampling stations SS2 SS3 0.86±0.33

Zn

0.75±0.23 0.49±0.07 0.35 0.49±0.08

Cu

0.02±0.01 0.01±0.01 0.04 0.01±0.004 0.014±0.01 0.003±0.001 0.55

Pb

0.38±0.07 0.29±0.04 0.36 0.3±0

0.32±0.03

0.49±0.14

p

0.37±0.15

0.45

0.85

Journal Pre-proof Lower mean temperature values were recorded during dry than the wet season (Fig. 2). Higher conductivity was recorded in the dry season compared to the wet season. The water chemistry differed temporally with respect to most of the parameters. However, no physical variables

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showed any significant variation between the dry and wet seasons.

Figure 2: Seasonal variations of physical parameters (mean ± SE) of the study area: A) temperature (oC); B) pH; C) Conductivity (μS cm−1); D) Turbidity (NTU).

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Seasonal Variability of Heavy Metals in Sediments Variation of heavy metal concentrations in sediments referred (Fig. 3). The concentrations of heavy metals in Lake Rukwa sediments differed between seasons. These variations were insignificant (p > 0.05; Fig. 3). The trend was Zn > Pb > Cu>Hg with Cr and Ni showing no detectable amounts in both seasons. Across sampling stations, the trend of Zn concentration was

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SS2>SS3>SS1 in dry season while during wet season it was SS3>SS1>SS2. The trend of Hg was

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SS2>SS3>SS1 during wet season and SS1>SS2>SS3 during dry season. The concentration trend

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of Cu was SS2>SS1>SS3 during dry season and SS1>SS2>SS3 during wet season whereas that

Zn

Hg

Pb

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250

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200 150

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Concentration in mg/kg

Cu

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300

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of Pb was SS2>SS1>SS3 during dry season and SS3>SS1>SS2 in the wet season.

100 50 0 SS1 DS

SS2

SS3

SS1 WS

SS2

SS3

Figure 3: Variability of heavy metal concentrations in sediments across sampling stations during both dry and wet seasons.

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Fish Abundance and Diversity Common fish species were African catfish, Chiloglanis rukwaensis (Kolokolo), Chelaethiops rukwaensis (Lake Rukwa Sardine), Singida tilapia and Rukwa tilapia.

A total of 1000

individuals of the above species were collected. The abundance was 600 Singida tilapia, 150 catfish, 100 Rukwa, 90 kolokolo and 60 Lake Rukwa sardine, indicating that Singida tilapia that was introduced to the Lake is now more abundant than other fish species (including the native –

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Rukwa tilapia followed by catfish. Shanon Wiener diversity index was used in determination of

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fish species diversity in Primer 6 software. A one-way Analysis of Similarities (ANOSIM) showed very little difference (Global R = 0.21, P < 0.001). However, the R values were weak

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Heavy Metals Concentration in Fish

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and hence the post-hoc analysis (the similarity of percentages (SIMPER)) was not computed.

Heavy metals concentration was determined for the commercially important African catfish and

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Singida tilapia. The African catfish and Singida tilapia samples showed significant variation in concentrations of Zn (p < 0.05, Table 5) between seasons, with higher concentration observed in

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the wet season. However, Cu and Pb concentrations were not significantly different between dry and wet seasons (p > 0.05, Table 5). All detected heavy metals were relatively higher in wet than

Table 5).

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dry season. Catfish heavy metal concentrations varied significantly between seasons (p <0.05, Catfish muscles recorded significantly higher concentration of heavy metals as

compared to tilapia (p < 0.05, Table 5). Table 5: ANOVA results for variation of Zn, Cu and Pb metals in catfish and Singida tilapia with standard error of the mean. Differential superscripts indicate significant variation in concentration. Catfish

Conc.

Tilapia

Metal

Dry season

Wet season

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Zn

141.2±17.3a

74.37±8.05b

0.001

Conc.

Me tal

Dry season

Wet season

p

Zn

133.5±12.2a

64.05±4.14b

0.03

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3.71±1.39a

2.45±0.32b

Pb

a

a

7.79±1.32

7.56±2.72

0.02

(mg/kg)

0.07

Cu

1.52±0.16a

0.25±0.02b

0.01

Pb

a

a

0.08

1.51±0.16

1.03±1.17

Discussion Zn and Cu are essential for enzymatic reactions at low concentrations. People near Lake Rukwa and the associated rivers consume the fish as source of food and protein. Fish species vary in the ability to bio-accumulate heavy metals. When heavy metals accumulate in fish, there is a

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possibility of leading to human health concerns upon consumption. Higher levels of heavy metals in catfish than tilapia in this study agree with Sani (2011), who reported differences in

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heavy metal concentrations between the two species. Furthermore, carnivorous fish were

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reported to accumulate high levels of Pb than omnivorous (Hashim et al., 2014). Catfish feeds on smaller fish of other species unlike tilapia which feeds on phytoplankton (Nzeve et al.,

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2014).Therefore, difference in Zn, Cu and Pb concentration in studied fish is due to their feeding behavior (Nzeve et al., 2014). Catfish also have high percentage of fat, which leads to easier

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accumulation in the blubber. Accumulation of heavy metals in fish also depends on exposure time and concentration of metals in the water column (Authman, 2015). In the present study Zn

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concentrations were about four times higher in dry season and therefore concentration dropped to about twice above recommended limits for both catfish and tilapia. On the other hand, Cu and Pb

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concentration in tilapia remained within WHO recommended standard limits during all seasons

all seasons.

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while Pb concentration was three times higher than the normal recommended limits for catfish in

Water quality parameters are essential for fish life. The highest water temperature at station sampling station 4 (SS4) can be due to the heating effect as it was located afar from the lake shores (shallow waters). Temperature as one of the most important water physical parameters is closely related to latitude, altitude and season (Shimba and Jonah, 2016). Lower temperature recorded at station SS5 was due to good cover by riparian vegetation at that location. Vegetation cover limits solar radiation reaching the water, thus contributing to minimal fluctuations of temperature (Shimba and Jonah, 2016). The range of temperature seen at stations SS1 – SS5 were probably due to the variable heating effect of the sun. The mean pH values observed in this are in agreement with those reported in Rau, Pangani and Mkondoa River Mouths (Kaaya et al.,

Journal Pre-proof 2015; Shimba, 2017). On the other hand, higher turbidity recorded may be due to heavy rainfall along with the increased run-off from nutrient rich agricultural and mining lands. Seasonal higher conductivity values during the dry season may be due to poor dilution compared to the we season. Agricultural activities have potential for increased ionic substances such as nitrate, chloride and phosphate from fertilizers (Kaaya et al., 2015). These are more concentrated during dry season compared to the wet season due to dilution effect (Kaaya et al., 2015; Shimba and Jonah, 2016). Furthermore, higher values of Zn, Pb and Cu in water in wet season may be due to erosion and transportation of sediments with adsorbed metals by rain runoffs (Obasohan and

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while Pb concentration was above recommended limits.

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Eguavoen, 2008). The concentrations of Zn and Cu in water were within WHO allowable limits

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In each season, Zn concentration in sediment was significantly higher levels than the rest of heavy metals (Verma and Pradesh, 2015). Zn is a vital co-factor in metabolic pathways across all

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forms of biodiversity. However, at levels above normal range, Zn has been linked to eco-

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toxicological effects (De Schamphelaere et al., 2004) manifested in phototoxicity to aquatic

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flora and fauna (Shaziya, et al., 2015; Tytler and Ehinmidu, 2016). Accordingly, Zn concentration in the current study is a course for concern and need for further monitoring of the

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ecological status of Lake Rukwa biota. The higher concentration of Zn may be from natural

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sources depending on the concentration in the rocks. However, higher than normal levels of Zn could also be attributed to anthropogenic activities such as mining activities (Ezeh and Anike, 2009; Leppänen et al., 2017). In this study sampling stations in Luika and Songwe River mouths which flow through mining sites exhibited higher Zn levels than the other areas (Leppänen et al., 2017). All detected heavy metal concentrations in sediment were above the recommended limits by WHO. The results prove the impact of mines on the contamination of sediments and fish.

Conclusions

Journal Pre-proof The average concentrations of heavy metals in fish and sediments in this study were above the WHO standards particularly Zn and Pb. The detected heavy metals of Zn, Cu and Pb are considered to be due to seepage from agricultural fields, current mining sites and abandoned mines in Songwe and Luika River Basins. A more detailed follow up study on heavy metal concentration in Lake Rukwa ecosystem is crucial to critically investigate the fate of heavy metals in fish, sediment and water. With the current results careful management of both the Lake and Rivers should be undertaken to avoid further contaminations.

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Acknowledgement

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This work was supported by the United Nations Educational, Scientific and Cultural Organization, UNESCO [Grant number 4500309532] to facilitate sampling expeditions and

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analysis of the samples under the “Abandoned Mines” project. The authors greatly appreciate the

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where analysis of the samples was done.

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support. The authors also like to appreciate the role played by the University of Dar es Salaam

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