Science of the Total Environment 487 (2014) 233–244

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Science of the Total Environment

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Metal concentration in water, sediment and four fish species from reveals a large-scale environmental concern

Mario Monroy a,⁎, Alberto Maceda-Veiga b, Adolfo de Sostoa a a Department of Biology and Biodiversity Research Institute (IRBIO), University of Barcelona, E-08028 Barcelona, Spain b Cardiff School of Biosciences, Cardiff University, CF10 3AX Cardiff, United Kingdom

HIGHLIGHTS GRAPHICAL ABSTRACT

• Pb content in water exceeded interna- tional safety thresholds. • Sediments enriched in organic matter are a good sink for metals. • High levels of Cu, Zn, Cd and Hg were found in 4 fish species from Lake Titicaca. • Benthopelagic species showed highest metal concentrations. • The metal bioaccumulation pattern was mainly associated with tissue and species.

article info abstract

Article history: Although intensive mining activity and urban sewage discharge are major sources of metal inputs to Lake Received 28 February 2014 Titicaca, the risk posed by metal pollution to wildlife and human populations has been poorly studied. In this Received in revised form 28 March 2014 study we compared the concentrations of Cu, Zn, Cd, Hg, Pb, Co, and Fe in water, sediment, and two tissues Accepted 29 March 2014 (liver and muscle) of four fish species ( bonariensis, luteus, Orestias agassii,andTrichomycterus Available online 3 May 2014 rivulatus) across important fishery areas in Lake Titicaca. The concentration of Pb in water at the discharge sites of fi Editor: D. Barcelo the main rivers and of most elements, with the exception of Co and Fe, in all sh collected in this study exceeded the safety thresholds established by international legislation. The highest metal concentrations were observed in Keywords: benthopelagic species, and liver tissue was identified as the main depository for all metals with the exception of Endemic fish mercury. The metal bioaccumulation pattern in fish was weakly related to the metal concentrations in the Mining contamination environment with the exception of Hg at the most polluted location, partly explained by the different metabolic Fisheries role of essential and non-essential elements and the influence of other factors such as species' ecology and Heavy metals individual traits in the bioaccumulation of most metals. As metal pollution extended across the study area and Bioaccumulation high metal concentrations were detected in all four fish species, we urge the authorities to enforce legislation for water and fish consumption and to evaluate the effects of metal pollution on fish health. © 2014 Elsevier B.V. All rights reserved.

1. Introduction

fi ⁎ Corresponding author. Tel.: +34 93 402 1041; fax: +34 93 403 4426. The conservation of inland sheries is an ecological, economic and E-mail address: [email protected] (M. Monroy). social concern given the of many fish species and

http://dx.doi.org/10.1016/j.scitotenv.2014.03.134 0048-9697/© 2014 Elsevier B.V. All rights reserved. 234 M. Monroy et al. / Science of the Total Environment 487 (2014) 233–244 the strong dependence of human populations living around lakes on fish last 30 years, and many species now listed as threatened according to resources as a major source of protein (Welcomme, 2001). Common the International Union for the Conservation of Nature (Loubens, 1989; threats to inland fisheries are overharvesting, the introduction of exotic Revollo et al., 2003; Vila et al., 2007; Gobierno Regional de Puno, 2008; species and a wide range of anthropogenic disturbances such as Aliaga and Segura, 2013). This lake is an important breeding and winter- water pollution (Allan and Flecker, 1993; Dudgeon et al., 2006). The ing area for up to 60 bird species (e.g., sandpipers, egrets, waterfowl, input of sewage discharge to rivers is often the main input of pollution grebes) including some endemisms such as the titicaca flightless grebe into large lakes (Carpenter and Cottingham, 2002; Dudgeon et al., (Rollandia microptera). In addition 18 species inhabit this 2006). To assess the consequences of sewage pollution for wildlife and lake, including the endemic Titicaca water culeus,and humans while increasing our understanding about pollutant dynamics a growing number of fish species, currently standing at 26 species, pend- in lakes, it is crucial to determine the variation in the concentration of ing genetic confirmation (Lauzanne, 1991; Sarmiento and Barrera, 2003; contaminants over space and across ecosystem compartments. Costa, 2003; Vila et al., 2007; Gobierno Regional de Puno, 2008). The The effect of sewage discharge on aquatic ecosystems primarily native fish community is dominated by members of the killifish genus depends on the mixture of organic (e.g. household products, drugs) Orestias (Teleostei, Cyprinodontidae) and the catfish and inorganic (e.g. acids, heavy metals) contaminants that they contain rivulatus,withnomarkedbreedingseason(Vila et al., 2007). Fisheries (Pinto, 2009). Heavy metals are of particularly high environmental risk resources are economically important as a source of income and food because of their long-term persistence in nature and possible bioaccu- for local communities around Lake Titicaca. In addition Lake Titicaca mulation and biomagnification (Demirak et al., 2006; Ivanciuc et al., provides three million people with drinking water, which is also used 2006; Agah et al., 2009; Uysal et al., 2009). Metal sources other than sew- for agricultural purposes (Revollo et al., 2003). age are atmospheric deposition, geologic weathering and the run-off Previous studies addressing the environmental aspects of metal pollu- from adjacent agricultural areas (e.g. pesticides, fertilizers) (Demirak tion in Lake Titicaca have focused on mercury in its main tributary, the et al., 2006; Uysal et al., 2009; Bereswill et al., 2013). However, elements Ramis River (Gammons et al., 2006), but a more comprehensive study such as copper (Cu), zinc (Zn), cobalt (Co) and iron (Fe) cannot be con- assessing the magnitude of metal pollution in this area has been lacking. sidered a water quality hazard unless they reach high concentrations The present study compared the concentrations of Cu, Cd, Zn, Hg, Pb, Co since they are necessary for animal life (Miller et al., 1992; Canli and and Fe in water, sediment and fish across the main fishery areas in Lake Atli, 2003). In contrast, other elements such as cadmium (Cd), mercury Titicaca. Since the main rivers have been portrayed as the main sources (Hg) and lead (Pb) always behave as toxic elements in organisms of metal pollution, we expected that sediments and fish at the discharge (Miller et al., 1992; Amundsen et al., 1997; Kojadinovic et al., 2007). sites would have the highest metal concentrations, and that the metal Sediments are the main sink of metals in lakes and sediment trans- concentrations in fishwouldbeinturndrivenbyenvironmental(organic port along the upstream–downstream river gradient, especially in high matter content) and species traits (size, age, species ecology). The senti- flow periods, is one of the main pathways of metal input into these nel species were the native and benthopelagic killifishes Orestias agassii ecosystems (Alloway, 2013). Because sediments concentrate metals and Orestias luteus, the native and benthonic catfish T. rivulatus,andthe and the concentration of these elements in sediment is less variable introduced and pelagic silverside . All species are than in water, sediments are suitable for monitoring the long-term omnivorous with the exception of silverside, which mainly feeds on metal deposition in ecosystems (MacDonald et al., 2000; Alloway, macroinvertebrates or fish depending on the silversides' size (Vaux 2013). However, measuring metal concentrations either in water or et al., 1988; Vila et al., 2007). Previous studies have suggested that sediment does not provide information on the risk posed by metal bioac- metal concentration is highest in species living close to the sediment or cumulation or biomagnification (Ricart et al., 2010; Maceda-Veiga et al., in species feeding on high trophic levels (Roméo et al., 1999; Mason 2013). These processes are firstly driven by metal availability for the et al., 2000; Agarwal et al., 2007; Kojadinovic et al., 2007; Yilmaz et al., biota (i.e. bioavailability), which in turn is related to water variables, 2007; Agah et al., 2009). Therefore, we predicted that benthonic and such as pH, oxygen concentration, water hardness and temperature, fish predators would have the highest metal load. Finally, we discuss and sediment characteristics, such as organic carbon content (Kotze the implications of our findings for the development of management et al., 1999; Canli and Atli, 2003; Adhikari et al., 2009). However, species strategies at Lake Titicaca. traits such as trophic position, age, body size or home range also modify metal bioaccumulation patterns (Mason et al., 2000; Gammons et al., 2. Material and methods 2006; Kojadinovic et al., 2007), illustrating that a combination of sentinel species with different ecological attributes will provide the best picture 2.1. Study area of the risk posed by metal pollution for the biota (Jorgensen, 2011). Fish are suitable bioindicators for metal pollution because they occupy Lake Titicaca, located between Peru and Bolivia at 3810 m above sea a range of trophic levels and they have a known ability to concentrate level, is the largest freshwater lake in South America with 8559 km2 of pollutants (e.g. pesticides, biphenyls, heavy metals) (Manirakiza et al., surface area and a water volume of 932 km3. The lake is divided into 2002; Bervoets and Blust, 2003; Agarwal et al., 2007). The life span of two large water bodies, the “Lago Mayor” and the “Lago Menor”,with fish also enables detection of the consequences of pollution over long a maximum depth of approximately 280 and 40 m, respectively. Lake time periods compared to other bioindicators, such as macroinverte- Titicaca is a cold oligotrophic lake with a high salt concentration due brates and diatoms (Jorgensen, 2011). In addition, because many species, to the geology of the basin (e.g. carbonate/bicarbonates, chlorides) including humans, consume fish as part of their diet, fish reflectbestthe (Arze and Quintanilla, 1991). The water chemistry is relatively con- consequences of metal pollution in lakes for wildlife and humans. stant across seasons and sites, with the exception of the rainy period Although metal bioaccumulation patterns have been described for between December and March, and those sites close to the mouth of many freshwater fish species (e.g. Oreochromis mossambicus, Kotze the main tributaries, the Ramis, Coata and Ilave Rivers (Vila et al., et al., 1999; Tilapia nilotica, Rashed, 2001), even lakes with similar inputs 2007). These rivers represent the main source of metal pollution in of metals can produce fish with widely different metal concentrations, the Lake due to the location of mining areas upstream (Gammons due to variation in biological, geochemical, and environmental factors et al., 2006). However, agricultural areas close to the rivers or sur- that affect metal uptake and accumulation (Chen et al., 2000; Ward rounding Lake Titicaca could be potential source of contamination et al., 2012). (e.g. pesticides, fertilizers). The situation in Lake Titicaca typifies the global decline in inland In order to gain an overall picture of the metal pollution in Lake fisheries due to anthropogenic perturbations, including the discharge Titicaca, we collected water, sediment and fish from two supposed of mining waste, with a 45% reduction in native fish biomass over the non-polluted areas (R1: Huencalla Bay and R2: Tamán Bay) and seven M. Monroy et al. / Science of the Total Environment 487 (2014) 233–244 235 known polluted locations (L1: Mouth of Ilave River, L2: Barco-Chucuito, 2.2. Fish sampling and collection of biological data L3: Mouth of Ramis River, L4: Pusi, L5: Mouth of Coata River, L6: Mohokachi and L7: Inka Chaka Bay) across the main fishery areas of Fish were collected by local fishermen using gillnets with a mesh- Lake Titicaca in November 2010 (Fig. 1). All sampling sites were located size ranging from 10 to 30 mm length, set overnight in each bay. All in Lago Mayor with the exception of L6 which was located in Lago Menor. individuals were identified to species level and a random sub-sample These sampling sites were selected based on an extensive literature of 10 individuals per species at each location was used for metal analy- review, interviews with local communities and our personal observations sis. As the juveniles of these species (b90 mm total length, LT) could not (Supplementary material: Table S1). be reliably identified, they were excluded from the analyses. The ten fish used for metal analyses were euthanized with an overdose of MS-222 (3-aminobenzoic acid ethyl ether, Sigma-Aldrich®, see Noga, 2010 for

2.1.1. Water quality and sediment characteristics details), measured to the nearest mm (LT) and weighed to the nearest General water quality variables were determined at each sampling 0.01 g (total body wet weight, WT). Fish were then dissected, sexed site using a digital YSI® 556 MPS multiprobe for temperature (°C), by a visual gross examination of gonads and a sample of muscle conductivity (μScm−1), dissolved oxygen (mg L−1) and pH, and the (ca. 500 mg) below the dorsal fin and the whole liver were stored for −1 colorimetric test kit VISOCOLOR® for ammonia (NH3,mgL ), nitrite metal analyses in polypropylene vials previously pre-cleaned with nitric −1 −1 −1 (NO2,mgL ), nitrate (NO3,mgL ) and phosphate (PO4,mgL ) acid (10%) and rinsed three times in water. Muscle was selected to concentrations, and general (°GH) and carbonate hardness (°KH). For determine the risk posed by metal pollution to humans and liver metal analysis, triplicate water samples were collected at each location because it is a key organ in detoxification processes and is targeted in in 250-mL polyethylene bottles pre-cleaned with nitric acid (10%) for metal accumulation (Miller et al., 1992). For age determination six to 24 h and rinsed three times with ultrapure water. Water samples were eight scales per fish were also collected from above the lateral line and immediately filtered through a 0.45-μm Millipore membrane filter and posterior to the dorsal fin area (see Carmona-Canot et al., 2011 for kept acidified with nitric acid (pH ~2) until metal concentrations were details on ageing criteria using scales). Scales were cleared in KOH for determined (see below). 12 h, rinsed in distilled water and examined using a Microbox® reader At each sampling three random sediment samples were collected at for the determination of year annuli. For T. rivulatus, which lacks scales, a 10-m deep in the midregion of the nine bays surveyed using a grab we used the age groups established by Paca et al. (2003) based on fish sampler of 325 cm2. These samples were air-dried and sieved through length histograms as a proxy measure of fish age since alternative a 100-μm mesh. pH was determined using a Thermo pH Orion Star tissues for fish ageing, such as otoliths, could not be examined due to A221 in a suspension of 10 g of soil and 25 mL of distilled water that logistic constraints. was shaken for 15 min and left to settle for 30 min (Pansu and Gautheyrou, 2007). In addition, three subsamples (~1.5 g) per sampling 2.3. Determination of metal concentration in water, sediment and fish site were combusted at 540 °C for 4 h to determine the percentage of organic matter content by measuring the weight difference before and Water, sediments and fish samples were frozen at − 20 °C, after combustion. transported in polystyrene boxes embedded in dry ice to the

Fig. 1. Location of the two reference sites (R1 and R2) and the seven known polluted sites (L1–L7) in Lake Titicaca where metal analyses were conducted in water, sediment and fish for the current study. Original map provided by National Aeronautics and Space Administration (NASA®). 236 M. Monroy et al. / Science of the Total Environment 487 (2014) 233–244

University of Barcelona (Spain) and kept for 1 month at the same tem- and sediments, two principal component analyses (PCAs) were indepen- perature until analysis. Metal concentrations in water were directly dently applied to each metal data set. The “varimax” rotation method was determined in acidified solutions prepared in the field. For sediments a used to increase the interpretation of axes and the number of PCA axes total attack with aqua regia was carried out by adding 6 mL HCl and was determined using Kaiser's rule (eigenvalue ≥ 1) (Legendre and

2mLHNO3 to 500 mg of well-homogenised sediment sample. This mix- Legendre, 1998). The synthetic gradients built (henceforth, PCbio and ture was digested in closed 60-mL Teflon vessels using a Milestone Ethos PCenv scores) also made the degree of divergence between metal concen- Plus microwave digestion system at 200 °C following ISO 11466. Fish trations in fish and sediments visible, and facilitated the interlinking tissues were first freeze-dried and ground to a powder to facilitate between the metal concentrations in the environment and fish. Pearson's homogenisation. Fish samples were then acid-digested in an oven at correlation coefficient (r) was calculated to determine pair-wise relation-

90 °C for 12 h according to their weight as follows: 3 mL HNO3 and ships between the synthetic gradients built with metal concentrations. 1mLH2O2 added to 100 mg tissue, 2 mL HNO3 and 1 mL H2O2 added All statistical analyses were performed using the R package (RCore to samples weighing over 50 mg, and 1 mL HNO3 and 0.5 mL H2O2 Team, 2012) and the libraries car, vegan and MASS. GLM assumptions added to samples weighing under 50 mg, using reagents of Instra quality were checked by examining standardised residuals using qq plots and (J. T. Baker®). plotting fitted versus predicted values. Metal concentrations were determined at the Technical Services of the University of Barcelona using a PerkinElmer OPTIMA-3200 RL Inductively 3. Results Coupled Plasma Optical Spectrometer (ICP-OES) for iron (Fe, μgL−1)and a PerkinElmer ELAN-6000 Inductively Coupled Plasma Mass Spectrome- 3.1. Metal concentrations in water and sediments and their relationship ter (ICP-MS) for zinc (Zn, μgL−1), cadmium (Cd, μgL−1), total mercury with environmental variables (Hg, μgL−1), lead (Pb, μgL−1), and cobalt (Co, μgL−1), using standard procedures (Maceda-Veiga et al., 2013 for details). Blanks and a certified The mean metal concentrations in water differed significantly reference material for soils (WQB1, National Research Institute, Canada) between locations for all elements determined (ANOVA, p b 0.001) and fish (DORM-3, National Research Council Canada) were also proc- with the exception of Hg, which remained below the detection limits −1 essed in each batch of digestions to provide quality control data. The at all locations (b0.2 μgL ;F8,18 = 1, p = 0.46) (Table 1). The peak metal concentrations in blanks were always below the detection limits, concentrations of Cu, Cd, Pb and Co were significantly associated with and the metal recovery rate for soil and fish samples was always above the discharge site of the River Ramis (Tukey post-hoc, p b 0.05), while 90% (see Supplementary material: Table S2 for details). Metal concentra- the highest values of Zn and Fe were respectively observed at locations tions under the detection limits were replaced by half the detection limit L2 and L6 (Tukey post-hoc, p b 0.05), without any river effect (Table 1). before the statistical analysis (Maceda-Veiga et al., 2012, 2013). Heavy As the highest conductivity values were observed at the discharge site metal concentrations in sediments and fish are presented as the mean of the River Ramis, conductivity was also positively associated with ± standard deviance (SD) in mg g−1 on a dry weight (dw) basis. We metals such as Cu (r = 0.85, p = 0.003) and Pb (r = 0.75, p = 0.01). also estimated the water content of both tissues to facilitate the conver- Nitrate concentration was also positively related to Cu (r = 0.66, p = sion of metal concentration from dry to wet weight (24.58%, 23.48%, 0.04) and Cd (r = 0.74, p = 0.02) levels in water, possibly because of 23.65% and 25.76% for muscle and 25.82%, 24.45%, 24.78% and 27.12% the spatial co-occurrence of the slight increase in nitrate concentration for liver of O. bonariensis, O. luteus, O. agassii and T. rivulatus, respectively), and that of these two elements in Barco–Chucuito (Table 1). based on 10 samples of each tissue and species. The mean metal concentrations in sediments also varied significant- ly between locations (ANOVA, p b 0.001), as did organic matter content

2.4. Data analysis (ANOVA, F8,18 = 437,500, p = 0.001) and pH (ANOVA, F8,18 = 16,706, p= 0.001)(Table 2). Specifically, the highest organic matter concentra- Water, sediment and fish variables were tested for normality and tions and lowest pH were observed at Mohokachi (Lago Menor) and homogeneity of variances using Shapiro–Wilk and Levene's tests, those sites close to the discharge sites of the Ramis and Coata Rivers in respectively, and parametric and non-parametric statistics were then Lago Mayor (Table 2; Tukey post-hoc, p b 0.05). This explains why applied accordingly. The mean metal concentrations either in water or organic matter content was also positively related to the concentra- sediment and sediment features (organic matter and pH) were com- tion of most elements: Cu (r = 0.64, p b 0.001), Zn (r = 0.51, p = pared between locations using a one-way ANOVA followed by Tukey 0.006), Cd (r = 0.57, p = 0.001) and Co (r = 0.51, p = 0.006). In HSD post-hoc test for pair–site comparisons. The relationships between addition, pH was negatively related to the concentration of organic metal concentrations, other water chemistry variables (temperature, matter (r = -0.58, p = 0.001), and all metal concentrations in sediments conductivity, dissolved oxygen, pH, general and carbonate hardness, (all, r N −0.66, p b 0.001) with the exception of Co (r = −0.16, p = 0.4). and ammonia, nitrite, nitrate and phosphate concentrations) and sedi- ment characteristics were explored using Spearman's rank correlation 3.2. Determinants of metal bioaccumulation in fish and their relationship analysis (rho). Differences in mean metal concentrations between spe- with environmental concentrations cies, tissues and locations were compared using a three-way ANOVA. Where significance was observed, one-way ANOVA was applied follow- The concentrations of all metals analysed differed significantly ed by Tukey HSD post-hoc test for paired comparisons between loca- between species (ANOVA, F3,696 N 9.72, p b 0.01), tissues (ANOVA, tions or species. As LT and WT were strongly correlated (Pearson's F1,696 N 50.45, p b 0.01) and locations (ANOVA, F8,696 N 3.03, p b 0.01). correlation coefficient, r N 0.9), LT was considered in this study as a Liver was the main metal depository for all elements with the exception more direct measure of fish size than weight. To explore the relative of Hg (Fig. 2). The tissue analysed was indeed the main factor explaining influence of fish attributes on the observed metal bioaccumulation the variation in all metal concentrations with the exception of Hg and Pb pattern in fish, sampling site, tissue, species, age, sex and LT was com- when individual traits were incorporated into the analysis (Table 4). bined in a general lineal model (GLM) fitted to each metal concentration Together with tissue, the sentinel species used for the metal analysis (log-transformed) with a Gaussian error distribution. The best models was also a significant contributor for most elements (Table 4), illustrating were selected using a manual stepwise backward deletion of non- that native benthopelagic species (O. luteus and O. agassii) generally had significant terms from the full global models containing all fixed factors the highest metal concentrations, followed by the catfish (T. rivulatus) and interactions (i.e. including covariate effects). The significance of (Fig. 2). Specifically, O. luteus had the highest mean values of Cu each factor was checked using an F-test (‘Anova’ function in R). Finally, (108.84 ± 85.75 μgg−1 dw), Hg (0.8 ± 0.93 μgg− 1 dw) and Co to describe the main sources of variation in metal concentrations in fish (0.64 ± 0.4 μgg−1 dw), O. agassii contained the highest concentrations M. Monroy et al. / Science of the Total Environment 487 (2014) 233–244 237

of Zn (102.22 ± 21.36 μgg−1 dw), and T. rivulatus had the highest values of Cd (0.15 ± 0.18 μgg−1 dw), Pb (0.06 ± 0.08 μgg−1 dw) and Fe (266.1 ± 146.56 μgg−1 dw) (Fig. 2). As the fish used for metal analyses spanned a wide range of sizes and

y y fl

idered homogenous ages (Table 3), GLMs were employed to explore the relative in uence of y y y x 9 x y y y – z individual traits (L , gender and age) compared to the location of sam- – – – – – – T pling sites in explaining the variation in metal bioaccumulation (Table 4). Interestingly, location was the most significant contributor to Hg bioaccumulation but the interaction between species and location was also significant for most elements, showing that the metal bioaccu- mulation pattern observed in all four species differed across the study 0.2 2 area (Fig. 3). Individual traits appeared to have a low influence on the concentration of all elements in fish with the exception of Zn, Co and Fe, for which gender was a significant predictor but with a marginal ± 0.02 0.02 0 ±0.01 10 300 ± 0.02 0.2 1300 ± 0.008 0.1 5 ± 0.001 0.02d i 5 ± 0.02 0.2 5000

h i f a effect (Table 4) and no clear trend observed in metals between males a 0.02 0.02 0.1 0.02 0.02 1 0.2 0.2

0.1 and females across species (Table 5). None of the GLM models retained b b b length or age as a significant explanatory variable (Table 4). To further examine the metal bioaccumulation pattern in fish and in the sediments of the locations surveyed we generated two PCA analyses ± 0.005 21.61 ± 0.005 0.04 ±0.02 20.1 ±0.01 14.35

h fi fi

± 0.005 0.05 for each data set, which produced two signi cant axes for sh (PC1bio, ± 0.02 5.47 h h f b,e,f e a ± standard deviation) and detection limits are reported for each element. The PC2bio) and environment (PC1env,PC2env) that together explained, 0.02 0.2 1 0.1 b b − respectively, 61.32% and 91.80% of the variation in metal concentrations gL

μ (Fig. 4 and Supplementary material: Table S3). PC1bio accounted for 37.31% of the variation and loaded on Cu, Zn, Cd, Hg, Co and Fe concen- ± 0.02± 0.02 7.43 45.77 ± 0.02 15.62 ± 0.01 211.08 ± 0.001 0.05 trations, while PC2 explained 24.01% of variation and was mainly

± 0.01 0.15 bio rations ( g g g g b,c d a related to Pb concentration. In contrast, PC1env accounted for 79.22% of 0.2 0.1 b the variation and loaded on Cu, Zn, Cd, Hg, Pb and Fe concentrations,

while PC2env accounted for 12.59% of variation and was mainly related to Co concentration. These environmental metal synthetic gradients fi ± 0.005 0.07 were poorly and non-signi cantly correlated with the metal bioaccu- ±0.02 51.09 ±0.01 24.43 ± 0.009 19.37 ± 0.01 0.19 ± 0.007 11.09 f f f fi a f b,c,e c mulation pattern observed in sh summarised in PC1bio (PC1env:r= 0.02 0.1 0.2 0.1 0.54, p = 0.13; PC2env:r=− 0.54, p = 0.13) and PC2bio (PC1env: b b b r=−0.11, p = 0.77; PC2env:r=−0.04, p = 0.91) (Fig. 4). ± 0.004± 0.01 7.28 31.42 ± 0.01 19.34 ± 0.01 52.12 ± 0.004 0.06 ± 0.01 0.12 e e e e 4. Discussion a d b 0.02 0.2 0.1 b b b 4.1. Metal concentrations in water and sediments and relationship with other environmental variables ±0.02 47.48 ±0.02 32.39 ±0.01 40.78 ± 0.005 0.11 d ±0.01 16.84 ± 0.006 0.28 d d Water chemical analyses showed that the Ramis River was the main a d b,c c 0.02 0.2 0.1 source of metal pollution in Lake Titicaca with peak concentrations of b b b Cu, Cd, Pb and Co observed at this location. Specifically, the Pb concen- tration exceeded the safety thresholds established by legislation by to establish the safety threshold for each water quality variable is also included. The letters (a, b, c, d, e, f, g, h, i) group sites by heavy metal, cons )

z 30-fold (US EPA, 2009). This peak in Pb might be related to the use of ± 0.01 117.32 ± 0.02 25.33 ± 0.006 0.07 ± 0.005 0.12 ± 0.01 8.93 ± 0.006 14.44 c c

a fuel additives and lubricants enriched in Pb in the mining and industrial c b c b 0.02 0.1 0.1 0.1 0.1 0.1 0.02 0.2 0.1 areas located upstream, since no hunting practices using Pb are present b b b 0.06 b

BOE (2011 in this area (Revollo et al., 2003; Gammons et al., 2006). Baseline loca- tions generally had fairly low concentrations of all elements determined ,and ) y but our results also showed that all polluted locations showed a degree ±0.03 23.67 ± 0.01 111.6 a ± 0.008 2.45 ± 0.005 3.07 ± 0.008 0.25 b b a b b a of metal pollution (e.g. Cu, Zn, Pb, Co) regardless of their proximity to 0.02 0.2 0.01 0.1 b b b b the main rivers. The release of domestic wastewaters might increase the metal concentrations in these areas because a wide variety of house- US EPA (2009

, hold products, such as cleaning materials, toothpaste and cosmetics, can ) x

± 0.01 13.43 contain trace concentrations of Cu, Zn, Pb and Fe (Sörme and Lagerkvist, ± 0.005± 0.01 0.27 58.46 ± 0.01± 0.008 0.18 0.05 a a a a a a a 2002; Alloway, 2013), and only large urban areas around Lake Titicaca 0.02 0.1 0.01 0.2 b b b b have proper sewage treatment plants (Revollo et al., 2003). Nonethe-

) 5.7 6.1 6.6 5.5less, 5.3 metals are 6.2 refractive to 11 biological degradation 5.7 and 6.9 are also present 0 1

− fl

) 1207 1239 1239 1318 1754in natural systems 1258 receiving 1570 the ef 1540uents from 1280 sewage treatment 0 plants 1 ) − 1

Health Canada (2012 (Maceda-Veiga et al., 2012). In addition, the run-off from adjacent agri- )0.10.1 1 − 11 2 3)1114 2 1 11 10 ) − 1

1 cultural areas might also be responsible for Cu, Zn, Cd, Hg and Pb release Scm − μ − since these are often present in fertilizers or pesticides (Alloway, 2013). ) )0.63 ) )7.11 )0.05 )2.57 ) 74.08 1 1 1 1 1 1 1 − − − − − − However, our study was unable to detect any other evidence of agricul- − gL gL gL gL gL gL gL

0.05. tural practices (e.g. eutrophication) despite the fact that excessive use of μ c legislation of μ μ μ μ μ μ fi b nitrogenous compounds as fertilizers is a growing concern at Lake Carbonate hardness (°KH)Ammonia (mg L 6 7 8 5 7 6 3 4 7 1 General hardness (°dH) 17Nitrites (mg L Nitrates (mg L Phosphates (mg L Zn ( 20Cd ( Hg ( Pb ( Co ( Fe ( 17 18 20 16 5 16 18 1 pH 8.2 8.2 8.2 8.2 8 8.3 8 8.9 8.8 1 5 Dissolved oxygen (mg L LocationTemperature (°C) 15 R1 15 R2 15 L1 16 L2 15 L3 15 L4 15 L5 17 L6 15 L7 0 Detection limits Legislation thresholds Conductivity ( Cu ( Table 1 Water quality of the nine bays surveyed in Lake Titicaca. Descriptive results are shown for general indicators of water quality but mean metal concent at p speci Titicaca (Fontúrbel, 2008), possibly because of the instability of these 238 M. Monroy et al. / Science of the Total Environment 487 (2014) 233–244 . compounds in the environment compared to metals and/or the dilution associated with the rain that fell during some of our surveys. The contribution of the main tributaries to metal pollution in Lake Titicaca was better reflected by the spatial variation in metal concentra- tion in sediments. Sediments enriched in organic matter act as good sinks for metals compared to water because humic substances present – – MacDonald et al. (2000) in sediments create metal complexes (Rognerud and Fjeld, 2001; Alloway, 2013). An increase in organic matter content was particularly sed on evident in the current study at the discharge site of the River Ramis, which in turn would explain the high metal concentrations observed at this site. The high river flow conditions two weeks before our survey was performed might also have increased the release of sediments from upstream areas down to the mouth. In addition the low pH observed at –– –– 1.09 ± 0.15 1.06 these sampling sites might be due to the decomposition of the organic matter in sediments or the sewage discharge from the mining activities (e.g. Galán et al., 2003 in Spain or Alpers et al., 2005 in California).

± 0.003 47358 ± 10536 Because the concentration of some of the metals analysed was moder- i ± 0.002 275 ± 58± 0.002 83.7 ± 22.3 459 128 ± 0.01 2 ± 0.91 4.98 i i ±0.01 ±0.01 ± 0.004 79.6 ± 19.1± 0.002 20.1 ± 9.3 149

i i i e i ately high, with some exceeding the safety thresholds established by l concentrations in sediments are ba a

0.1 international legislation (i.e. Pb in water), and as the long-term release of metals from contaminated sediments is well known, negative effects are expected in aquatic and terrestrial organisms as long as metals are

± 0.003± 9.95 0.002 46.57 ± 0.002 199.72 able to incorporate into the biota (MacDonald et al., 2000). ± 0.02± 0.01 4.45 8.12 ± 0.004± 0.002 10.45 6.28 ± 0.005 0.08 h h h h h d h h a 0.1 4.2. Metal bioaccumulation in fish

± 0.001 58.05 The metal concentrations in all fish species collected exceeded the ±0.05 21.3 ± 0.002± 0.002 14.17 11.97 ± 0.001 5.47 g ± 0.01 0.18 ± 0.02 7.51 ± 0.004 1.75 g g g g g b g e safety thresholds reported for meta threshold established by the European (European Commission, 2001, a 2006) and American (FAO/WHO, 1998) legislation with the exception of Pb, Co and Fe. This finding is consistent with Gammons et al. (2006) and IMARPE and FONCHIP (2010), who also detected Hg levels in

± 0.001 290.79 O. bonariensis and T. rivulatus above the safety threshold at the mouth ± 0.01± 0.002 25.77 65.61 ± 0.001 16.61 f ± 0.001 0.1 ± 0.005 0.13 ± 0.03f 23.66 f f ± 0.004 10.1 a f ± 0.01 7.05 d f of the River Ramis and at other locations around the lake. Although the f

0.1 cross-study comparison of metal bioaccumulation in fish species from b other water ecosystems is challenging, the mean concentrations of Cu Zn, Hg, Co and Fe observed in the current study were higher than those μ −1

± 0.006 73.89 ± 0.002 374.98 reported in the liver of Abramis brama for Cu (49.07 gg dw) and in ± 0.002 27.21 ± 0.001 25.82 e e −1 ±0.01 ± 0.02± 0.01 2.67 6.9 ± 0.001 4.76 ± 0.01 0.21 e e muscle for Hg (0.09 μgg dw) in Lake Balanton (Farkas et al., 2002), 0.05. e e c b e − − b in the liver of Labeo rohita for Cu (1.03 μgg 1 dw), Zn (1.03 μgg 1 0.78 dw) and in muscle for Hg (0.07 μgg−1 dw) in Lake of Bhopal (Malik et al., 2010) or in the liver of Tilapia nilotica for Cu (7.5 μgg−1 dw), Zn (2.28 μgg−1 dw), Co (0.31 μgg−1 dw) and Fe (4.58 μgg−1 dw) in ± 0.002 433.38 ± 0.002± 0.002 41.09 323.24 ± 0.001 74.97 ± 0.01 1.98 d ±0.05± 35.8 0.005 5.13 ± 0.002 8.68

d d d Lake Nasser (Rashed, 2001). However, Cd and Pb concentrations were a d d b,e d lower than those reported in the liver of Abramis brama for Cd (1.72 μg 0.1 0.11 b g−1 dw) and Pb (2.22 μgg−1 dw) from Lake Balanton (Farkas et al., 2002), the liver of Labeo rohita for Cd (0.52 μgg−1 dw) and Pb (1.26 μg g−1 dw) in Lake of Bhopal (Malik et al., 2010) or even in muscle of ± 0.002 319.19 −1 −1 ± 0.004± 0.001 20.99 71.09 c μ μ ± 0.01± 0.005 3.66 8.12 ± 0.001± 0.004 17.65 10.3

a Lates marie for Cd (0.25 gg dw) and Pb (4.96 gg dw) in Lake Tan- c c a c c c c dw ± standard deviation) at each sampling site surveyed in Lake Titicaca. Th

1 ganyika (Chale, 2002). 0.01 0.1 − b b The bioaccumulation pattern of all elements in fish at Lake Titicaca gg μ was mainly associated with tissue and sentinel species effects. Of the tissues, the liver was confirmed as the best metal depository for all ± 0.002 246.81 ± 0.01± 0.01 5.96 ± 0.002 7.31 ± 0.001 10.39 19.04 ± 0.001± 0.003 8.33 5.69 a b elements determined with the exception of Hg (Farkas et al., 2002; a b b b b b b

0.01 0.1 Gammons et al., 2006; Çogun et al., 2006). This could be because Hg b b has a high affinity for the sulphydryl groups of proteins (Miller et al., 1992; Mason et al., 2000), as well as because the muscle contains low levels of binding proteins (i.e. metallothioneins) compared to the liver ± 0.002 87.79 0012.16 ±0.001 a ± 0.04± 0.01 1.19 7.95 ± 0.001 1.62

a (Roméo et al., 1999; Karadede et al., 2004; Kojadinovic et al., 2007). a ± 0.002± 0.003 3.07 4.32 a a a a

a a In terms of species, our results corroborated our predictions and the 0.1 0.01 b b highest metal concentrations were observed in O. luteus, O. agassii and T. rivulatus, possibly because they live close to the sediments (Roméo et al., 1999; Agarwal et al., 2007; Yilmaz et al., 2007). However, pelagic ) )3.3 ) )9.1 )3.77 ) 15.82 ) 162.44 1 1 1 1 1 1 1 −

− − species such as O. bonariensis often showed a similar metal bioaccumula- − − − −

gg fl gg gg gg gg gg

gg tion pattern (e.g. Hg) to native benthopelagic species, possibly re ecting μ μ μ μ μ μ μ the different metabolic dynamics of essential and non-essential elements LocationOrganic matter (%) 1.85 R1 R2 L1 L2 L3 L4 L5 L6 L7 Reference material WQB1 Legislation thresholds Hg ( pHCu ( 8.43 Fe ( Zn ( Cd ( Co ( Pb ( fi fl Table 2 Sediment characteristics and mean metal concentration ( The letters (a, b, c, d, e, f, g, h, i) group sites by environmental variable, considered homogenous at p in sh species coupled with the in uence of other individual traits. M. Monroy et al. / Science of the Total Environment 487 (2014) 233–244 239

Fig. 2. Mean metal concentrations in muscle (white boxes) and liver (grey boxes) in the native benthopelagic (O. agassii and O. luteus), the native benthonic (T. rivulatus)andthepelagic introduced species (O. bonariensis) collected from nine study sites in Lake Titicaca. Discontinuous lines indicate the safety thresholds for metal concentration established by international legislation for human consumption (Cu, Cd, Hg and Pb according to the EC, 2006; and Zn based on FAO/WHO, 1998). The letters (a, b, c, d) group sites by variable, considered homogenous at p b 0.05. Note that metal concentrations in males and females are grouped by location.

The spatial variation in metal concentrations in fish showed that the showed that essential elements (e.g. Cu) can bioaccumulate when envi- levels of non-essential elements (Cd, Hg, Pb) in fish were generally ronmental concentrations are high, thereby becoming a pollution source, more consistent with the peaks in metal concentrations in the environ- just as non-essential elements do (Chale, 2002; Farkas et al., 2002; ment than essential elements. In this regard, the most polluted locations Demirak et al., 2006; Maceda-Veiga et al., 2013). Likewise, an increase were Barco–Chucuito (located inside Puno Bay) and, as predicted, the in essential elements in a given individual from a polluted location mouth of Ramis River. The considerable variation in the concentration might also be attributed to the participation of Cu, Zn, Co and Fe in met- of essential elements could be due to the greater regulation of the abolic functions (e.g. detoxification processes) to cope with pollution uptake and excretion of essential elements compared to that of non- effects (e.g. oxidative stress) (Bervoets and Blust, 2003; Çogun et al., essential elements (Kojadinovic et al., 2007). However, our results also 2006). Because non-essential elements are better tracers of pollution 240 M. Monroy et al. / Science of the Total Environment 487 (2014) 233–244

Table 3

Sample size (N), mean and standard deviation of body length (LT mm) and weight (W g), minimum and maximum range, and details of gender and ages of the four fish species in Lake Titicaca used for metal analysis.

Species Gender N LT Min–max W Min–max Age (years) 0+ 1+ 2+ 3+ 4+ 5+ 6+ 7+

O. bonariensis ♂ 52 210.65 ± 24.83 166–280 58.32 ± 21.56 25.25–121.18047500000 ♀ 37 228.02 ± 37.27 165–375 85.83 ± 47.44 25.54–278.08028810000 O. luteus ♂ 46 120.95 ± 18.2 94–155 44.51 ± 18.77 17.06–79.710 93332350 ♀ 39 131.94 ± 20.41 90–164 62.51 ± 24.85 16.84–105.180511119102 O. agassii ♂ 27 121.44 ± 22.93 90–160 31.11 ± 16.74 11.12–61.570 6946200 ♀ 63 133.71 ± 22.26 90–170 42.86 ± 18.95 9.31–90 0 4 14 19 13 13 0 0 T. rivulatus ♂ 39 158.15 ± 15.64 121–181 40.39 ± 11.19 18.73–60.370 43500000 ♀ 44 164.97 ± 18.54 122–204 44.82 ± 12.56 19.21–69.160 23903000 than essentials and because all species showed increased Hg concentra- (i.e. killifish/catfish) (Mason et al., 2000; Kojadinovic et al., 2007; Agah tion at the most polluted location regardless of their swimming behaviour et al., 2009; Maceda-Veiga et al., 2013). In the case of O. bonariensis (i.e. pelagic/benthonic), our results suggest that all species, including the the high concentration of Hg observed in some locations relative apparent highly mobile O. bonariensis, are resident in this area, although to other species could also be attributed to its high trophic position the home range of all four species is currently unknown. Nonetheless, (i.e. biomagnification) (Mason et al., 2000; Kojadinovic et al., 2007; the metal bioaccumulation pattern observed in all four fish species should Agah et al., 2009). In this regard, the mean length of O. bonariensis indi- be considered mostly poorly related to the environmental metal concen- viduals examined in the current study (217.8 mm) suggests that they are trations as suggested by the pair-wise correlation analysis between mainly piscivorous (above 200 mm, see Vaux et al., 1988; or above PCA scores. 90 mm, Monroy et al., in preparation). Likewise, a high metal concentra- An additional explanation for the sometimes similar bioaccumula- tion in O. luteus could be attributed to the fact that this fish species tion pattern observed in pelagic and benthopelagic species is that occasionally feeds on fish juveniles (Monroy et al., in preparation). Alter- all four species can feed on bottom drift invertebrates and may ingest natively, the more active metabolism of pelagic species could also lead to sediment or suspended organic matter when they feed (Lauzanne, an increase in metal uptake compared to benthopelagic fish (Kojadinovic 1982; Parenti, 1984; Loubens, 1989; Vila et al., 2007). Differences in the et al., 2007). However, this hypothesis seems unlikely owing to the fact relative proportion of items in fish diets with a variable metal content that the metal bioaccumulation in pelagic species was not consistently could have determined the observed metal concentration in fish species higher than that in the benthopelagic species across the study area. Species occurrence in deep and poorly oxygenated waters, as is the case for O. bonariensis, is also likely to increase Hg bioaccumulation since these environmental conditions favour methylation and hence Hg Table 4 Results of the final GLM models for all metals (Cu, Zn, Cd, Hg, Pb, Co and Fe) determined in accumulation (Gammons et al., 2006; Kojadinovic et al., 2007). the four fish species (O. bonariensis, O. luteus, O. agassii, T. rivulatus) collected in Lake Individual traits made a minor contribution towards explaining the Titicaca. Note that only significant variables highlighted in previous full models with all variation in the concentration of most elements in all four fish species. explanatory variables and interactions (see methods) are shown. Previous studies have suggested that age and fish size could increase Metal Fish attributes SS Df F p-value metal accumulation due to the long-term exposure of individuals to

Cu Species 182.02 3 101.34 b0.001 pollution (Gammons et al., 2006), the metabolic activity of individuals Tissue 993.11 1 1658.82 b0.001 (Canli and Atli, 2003), ontogenetic changes in fish diet (Mason et al., Species x Location 23.94 24 1.66 0.02 2000) or a reduction in the detoxification ability of old fish (Kojadinovic Residuals 393.34 657 et al., 2007). In the current study fish size and age might have been b Zn Species 23.7 3 59.09 0.001 secondary factors affecting metal bioaccumulation, possibly because Location 3.36 8 3.14 0.001 Tissue 105.73 1 790.63 b0.001 they were not evenly distributed across the polluted locations given the Gender 0.639 1 4.77 0.02 likely effect of fisheries pressure. In terms of gender, there was no clear Residuals 90.94 680 difference between males and females in the bioaccumulation pattern b Cd Species 0.31 3 26.9 0.001 of the essential elements Zn, Co and Fe in most species However, studies b Location 0.2 8 6.79 0.001 fi Tissue 0.85 1 221.17 b0.001 on other sh species, such as skipjack tuna Katsuwonus pelamis and com- Residuals 2.53 657 mon dolphinfish Coryphaena hippurus have reported the effect of gender Hg Species 1.98 3 21.13 b0.001 on Zn and Fe bioaccumulation (Kojadinovic et al., 2007). The concentra- Location 34.02 8 135.82 b0.001 tions of these essential elements could be associated with differing meta- b Tissue 8.75 1 279.67 0.001 bolic activities or the different gonad developmental stage of males and Species x Location 6.48 24 8.62 b0.001 Residuals 20.57 657 females (Kojadinovic et al., 2007). As gonads were not weighed in this Pb Species 0.08 3 15.89 b0.001 study, the effect of gonad development cannot be ruled out, although an Location 0.07 8 5.4 b0.001 apparently similar developmental stage was observed in the field. Metal b Tissue 0.02 1 15.72 0.001 bioaccumulation in fish in Lake Titicaca may also be affected by factors Species x Location 0.14 24 3.3 b0.001 Residuals 1.16 657 other than those mentioned above, including metal speciation (Ivanciuc Co Species 1.96 3 33.75 b0.001 et al., 2006; Adhikari et al., 2009), the rate of export of metals through Tissue 17.69 1 910.87 b0.001 other food web compartments (Amundsen et al., 1997; Bervoets and Gender 0.43 1 22.5 b0.001 Blust, 2003; Kojadinovic et al., 2007) and species physiology, and there- b Species x Gender 0.44 3 7.62 0.001 fore this study cannot explain the likely mechanisms associated with Residuals 13.3 685 fi Fe Species 45.58 3 38.26 b0.001 the bioaccumulation pattern we observed in these sh species. Finally, Tissue 1068.64 1 2691.94 b0.001 we note that although the present study focused on metals, exposure Gender 3.05 1 7.67 b0.001 to other toxic compounds present in sewage waters (e.g. drugs, pesti- Species x Location 82.03 32 6.45 b0.001 cides) could also have been responsible for the observed bioaccumulation Residuals 260.42 656 patterns. M. Monroy et al. / Science of the Total Environment 487 (2014) 233–244 241

Fig. 3. Variation in mean metal concentrations in the nine bays surveyed and in the four fish species examined (O. bonariensis, black; O. luteus, dark grey; O. agassii, grey and T. rivulatus, white boxes) using the liver as the sentinel tissue for the assessment of all metals with the exception of Hg. Discontinuous lines indicate the safety thresholds for each metal established by international legislation for human consumption (Cu, Cd, Hg and Pb according to the EC, 2006;andZnbasedonFAO/WHO, 1998). Metal concentrations are plotted without log-transformation to facilitate the interpretation of axes.

5. Concluding remarks and management actions the species affected have a high conservation value, the evaluation of the risk posed by pollution in Lake Titicaca to fish health is also This study demonstrates contrasting metal bioaccumulation pat- mandatory. terns in water, sediments and fish, suggesting caution when inferring Supplementary data to this article can be found online at http://dx. the risk posed by metal pollution based on analysis of a single ecosys- doi.org/10.1016/j.scitotenv.2014.03.134. tem compartment. Most elements in fish and Pb in water were above the safety threshold, illustrating the large-scale metal pollution at Conflict of interest Lake Titicaca. Given that both humans and wildlife (e.g. piscivorous birds and ) depend on the fisheries resources in the lake Authors declare that they have no financial and personal relationships and high Hg levels in blood of humans living close to mining areas with other people or organizations that can inappropriately influence or have been already reported (Hurtado et al., 2006), we would encour- be perceived to influence their work. age the authorities to enforce legislation to reduce metal pollution in Lake Titicaca. Limiting species consumption would be a better man- Acknowledgements agement strategy than the prohibition of fishing in certain areas since pollution by metals seems to extend across the study area. This work and protocols were funded and approved by the Spanish Further studies should focus on the ecology of fish species, metal Agency for International Cooperation and Development (AECID) and speciation and metal export from contaminated areas through other the Department of Production of Peru trough the Hispanic-Peruvian components of the food web to increase our knowledge about the Cooperation Program (PCHP) (projects no FBG305168 and FBG306311). likely mechanisms behind the observed metal bioaccumulation. As We thank O. Flores, E. Yujra and the rest of the crew at the Binational 242 M. Monroy et al. / Science of the Total Environment 487 (2014) 233–244 7 ± 112.9 94 ± 73.2 .24 ± 57.72 8.69 ± 56.67 194.43 ± 125.46 304.82 ± 170.36 4 170.9 ± 119.23 .01 261.02 ± 197.61 cant differences were observed fi : 4) gender and tissue in Lake Titicaca. Note that only signi T. rivulatus :3, O. agassii 0.49 0.3 ± 0.55 0.02 ± 0.02 0.01 ± 0.01 0.03 ± 0.07 0.2 ± 0.11 23.68 ± 43.84 164. :2, ± 0.99 0.2 ± 0.2 0.01 ± 0.02 0.04 ± 0.05 0.01 ± 0.009 0.44 ± 0.24 13.99 ± 7.02 112 76 ± 0.89 0.16 ± 0.15 0.02 ± 0.02 0.04 ± 0.09 0.01 ± 0.008 0.82 ± 0.44 12.31 ± 5.7 44 ± 0.66 0.36 ± 0.6643 ± 0.45 0.02 ± 0.02 0.2 0.02 ± ± 0.4 0.02 0.01 ± 0.01 0.04 ± 0.09 0.42 0.07 ± ± 0.28 0.09 0.02 15.83 ± ± 0.01 14.64 0.42 ± 0.23 21 ± 7.47 231.7 44 ± 0.38 0.19 ± 0.24 0.02 ± 0.03 0.06 ± 0.07 0.02 ± 0.01 0.4 ± 0.19 22.66 ± 12.46 0.67 ± 1.12 0.47 ± 0.75 0.009 ± 0.01 0.01 ± 0.01 0.02 ± 0.01 0.75 ± 0.48 13.37 ± 5 O. luteus :1, O. bonariensis

Fig. 4. Principal component analysis of the metal concentrations in the environment and fish. Scores are according to location either in sediments (a) or fish (b), and only by species (c). dw ± standard deviation) in relation to species ( 1 − gg . μ Special Project of Lake Titicaca (PELT), the Sea of Peru Institute (IMARPE)

Table 4 and the Lake Titicaca Agency (ALT), for field and laboratory assistance. We also thank to Dr. Carsten Müller for useful insights on metal pollution in lakes, Toffa Evans from the Language Service at the University of Barce- lona for the English revision and three anonymous referees for valuable comments on the manuscript. AMV is currently funded by a Marie Muscle Liver Muscle Liver Muscle Liver Muscle Liver Muscle Liver Muscle Liver Muscle Liver Curie Fellowship (Para-Tox project no 327941). 46 1.26 ± 1.03 118.42 ± 85.35 30.6 ± 9.86 77.4 ± 20.68 0.006 ± 0.003 0.14 ± 0.003 0. 37 0.93 ± 1.3139 5.46 1.26 ± ± 3.47 1 28.6363 ± 9.16 0.96 ± 0.44 97.54 ± 85.93 44.2244 65.55 ± 29.32 ± ± 15.66 44.85 2.05 6.67 ± 0.007 1.4 31.67 ± ± 0.008 9.16 83.37 0.02 ± ± 12.03 0.01 24.78 101.49 ± ± 10.06 23 0.007 ± 0.84 0.003 ± 46.2 0.48 0.08 ± ± 15.85 0.34 0.003 0.004 ± ± 0.57 0.004 0.86 90.36 ± 0.04 19.57 ± 0.02 0.004 ± 0.004 0.05 ± 0. 0.004 0.01 ± 0.15 0.01 ± 0.004 0.04 ± 0. 0.07 0.17 ± 0.07 21.1 ± 36.46 13 27 1.06 ± 0.5439 83.18 ± 77.87 1.9 32.94 ± ± 0.75 10.29 103.93 ± 10.89 17.2 ± 4.82 0.003 ± 49.17 0.004 ± 15.26 0.07 ± 0.004 87.97 ± 11.93 0.006 ± 0.007 0.14 ± 0.007 0. 52 1.3 ± 1.8 7.65 ± 7.07 38.45 ± 15.55 50.43 ± 17.27 0.007 ± 0.007 0.02 ± 0.01 0.74 ± ♂ ♀ ♀ ♀ ♀ ♂ ♂ ♂ References

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