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Accumulation trends of metals and a
metalloid in the freshwater crayfish
Astacus leptodactylus from Lake
Yeniçağa (Turkey)
abc
Evren Tunca
c
bc
a
, Esra Üçüncü , Bedri Kurtuluş , Alper Devrim
Ozkan & Sibel Atasagun
b
a
Department of Geological Engineering, University of Muğla,
Muğla, Turkey
b
Department of Biology, Faculty of Science, Ankara University,
Ankara, Turkey
c
UNAM-Institute of Materials Science and Nanotechnology, Bilkent
University, Ankara, Turkey
Published online: 22 Jul 2013.
To cite this article: Evren Tunca, Esra Üçüncü, Bedri Kurtuluş, Alper Devrim Ozkan & Sibel
Atasagun (2013) Accumulation trends of metals and a metalloid in the freshwater crayfish
Astacus leptodactylus from Lake Yeniçağa (Turkey), Chemistry and Ecology, 29:8, 754-769, DOI:
10.1080/02757540.2013.810724
To link to this article: http://dx.doi.org/10.1080/02757540.2013.810724
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Chemistry and Ecology, 2013
Vol. 29, No. 8, 754–769, http://dx.doi.org/10.1080/02757540.2013.810724
Accumulation trends of metals and a metalloid in the freshwater
crayfish Astacus leptodactylus from Lake Yeniçağa (Turkey)
Evren Tuncaa,b,c *, Esra Üçüncüb,c , Bedri Kurtuluşa , Alper Devrim Ozkanc and Sibel Atasagunb
of Geological Engineering, University of Muğla, Muğla, Turkey; b Department of Biology,
Faculty of Science, Ankara University, Ankara, Turkey; c UNAM-Institute of Materials Science and
Nanotechnology, Bilkent University, Ankara, Turkey
Downloaded by [Bilkent University] at 05:03 07 May 2014
a Department
(Received 20 December 2012; final version received 29 May 2013)
This study aims to determine the extent of metal pollution in LakeYeniçağa (Bolu, Turkey) by investigating
the accumulation trends of five metals (Al, Cu, Fe, Ni and Zn) and a metalloid (As) in gills, exoskeleton, hepatopancreas and abdominal muscles of the freshwater crayfish Astacus leptodactylus. Principal
component analysis (PCA), cluster analysis (CA), correlation analysis and analysis of variance (ANOVA)
were utilised to determine the accumulation profiles of each element over four seasons. The greatest element accumulation was found to occur in the gills. All elements in exoskeletal tissue displayed positive
correlations with each other, a similar trend was also observed in the hepatopancreas samples. Strong
(r = 0.868) and very strong (r = 0.960) positive correlations were found between the accumulations of
Al and Fe in gills and the exoskeleton, respectively. Correlations in tissue accumulation rates are discussed
in the context of metabolic roles and impacts associated with the elements tested. Elemental compositions
of Yeniçağa water and sediment samples were also investigated to determine whether the composition of
the surrounding environment matches the metal accumulation trends of tissue samples. We demonstrate
that, by the criteria set by the United States Environmental Protection Agency, Lake Yeniçağa is heavily
polluted in terms of As and Ni.
Keywords: bioaccumulation; bioindicator; cluster analysis (CA); correlation analysis; crayfish; heavy
metal; principal component analysis (PCA); Lake Yeniçağa
1.
Introduction
Because heavy metals are highly toxic, commonly utilised in various industrial applications,
difficult to remediate and capable of accumulating in live organisms, contamination of aquatic
environments by those pollutants is a vital issue.[1] Heavy metals can be introduced into tissues by
ingestion, inhalation or skin contact, and their accumulation may result in a number of debilitating
chronic disorders. Because aquatic organisms are constantly exposed to dissolved metal ions in
their environment, they are particularly liable to accumulate high metal concentrations in various
tissues.[2] As such, aquatic animals are considered suitable for use in monitoring environmental
quality, especially with regards to metal pollution, and many such species are utilised to this end.[3]
Crayfish in particular display several features advantageous for their use as bioindicator organisms,
including a benthic and solitary lifestyle, constant contact with the substratum, omnivorous diet,
high fecundity, relatively long lifespans, narrow territory ranges and sizes large enough to permit
*Corresponding author. Email: [email protected]
© 2013 Taylor & Francis
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Chemistry and Ecology
755
convenient sampling of all major tissues.[4] Previous reports demonstrate that crayfish accumulate
considerable concentrations of heavy metals in their tissues and that the amounts accumulated are
largely dependent on heavy metal concentrations present in the external environment, although
a number of mechanisms successfully regulate the concentrations of essential elements such as
Cu and Zn.[3,5–8] In addition, crayfish occupy an important role in freshwater food webs, with
some species being considered keystones in aquatic environments, and may facilitate the transfer
of accumulated metals to higher trophic levels.[9] As such, crayfish have seen extensive use as
bioindicator species in the literature.[10–12]
The accumulation and distribution of metals in crayfish tissues are influenced by several factors,
including environmental conditions, metal concentrations in the surrounding water or sediment,
and metabolic pathways involving the accumulated metals. Furthermore, the metabolic impact
made by the presence of one metal may significantly alter the accumulation profile of another. As
such, this study was undertaken to investigate the relationship between accumulation patterns and
to detail the accumulation profiles of five metals (Al, Cu, Fe, Ni and Zn) and a metalloid (As) in
Lake Yeniçağa crayfish. We also investigate and discuss whether different seasons alter the metal
and metal accumulation trends in various tissues.
Lake Yeniçağa is a Ramsar site and constitutes one of the most important wetlands in Turkey.
Heavy metal pollution of the lake was previously studied from March 2008 to February 2009
using water, sediment and plankton samples, as well as three species of fish.[13–15] The metals
investigated in this article were chosen using those studies as a reference. This study aims to
further characterise the effects of metal pollution to the food web of Lake Yeniçağa by monitoring
crayfish, which are abundant in the locale, over four seasons. In addition, we measure the extent of
metal pollution in the water and sediment samples, and compare them with the metal accumulation
trends in crayfish tissues.
2.
Materials and methods
2.1. Study area and sample preparation
Lake Yeniçağa is located in the western Black Sea region of Turkey (Figure 1).[13] It has a surface
area of 1800 ha and a maximum depth of 5.2 m. One hundred and eighty-three different bird species
migrate annually over İstanbul and the Çanakkale Straits to shelter at Lake Yeniçağa, rendering
it an important nature reserve.[16] The water quality of Lake Yeniçağa has diminished over the
last decade as a result of increased anthropogenic effects.[13] Two main creeks (Kuzuviran and
Deliler) feeding the lake are subject to extensive domestic and industrial waste discharge, which
is suspected to be a primary reason for the observed decrease in water quality.[17]
Sampling was conducted between April 2010 and February 2011. Crayfish traps and trammel
nets of various mesh sizes were utilised to capture crayfish. Ten crayfish specimens, in addition
to water and sediment samples, were collected for each season. All samples were recovered
from predetermined stations. Water samples were taken in 500-mL plastic containers at a depth
of 0.5 m, acidified using 65% nitric acid to a final concentration of 2% and filtered through a
0.45-μm filter prior to analysis. Sediment samples were taken in plastic containers at a sediment
depth of 20 cm. Both water and sediment samples were kept at 4◦ C prior to analysis, samples
were read in triplicate. For crayfish samples, specimens with total body lengths around 20–25 cm
were transported in cooler boxes and stored at −18◦ C in plastic containers until dissection.
Approximately 1 g of exoskeleton, gill, hepatopancreas and abdominal muscle samples were
recovered from each specimen. Tissue samples were digested with 2 mL HNO3 and 1 mL HClO4
at 80◦ C for 20 min. Following digestion, samples were resuspended in 5 mL distilled water and
acidified as above with 65% nitric acid prior to analysis.[14,18]
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756
Figure 1.
E. Tunca et al.
Map of the Lake Yeniçağa region.
All measurements were performed in YEBİM (Ankara University, Turkey). Tissue and water
samples were analysed by inductively coupled plasma optical emission spectrometry (ICP-OES),
while X-ray fluorescence (XRF) was utilised for sediment samples. Prior to analysis, sediment
samples were crushed in a FRITSCH tungsten carbide mortar, mixed with connective material
(Wachs) at a ratio of 4 g sample to 0.9 g Wachs and pelleted under 15 N force using a hydraulic
press. Pellets were analysed using a Spectro X-Lab 200 PED-XRF, analysis was conducted with
the Tq-7220 method. A Spectro Genesis ICP spectrometer (Petrolab, Germany) was utilised for
ICP-OES measurements. New blank and calibration samples were read every 40 measurements to
ensure accuracy, LUTS-1 (non-defatted lobster hepatopancreas reference material) was utilised as
quality control. A multi-element calibration solution (Bernd Kraft, Germany) was utilised for ICPOES calibrations, detection limits for Al, As, Cu, Fe, Ni and Zn were 0.06 ± 0.002, 0.05 ± 0.04,
0.06 ± 0.01, 0.5 ± 0.4, 0.01 ± 0.009 and 0.29 ± 0.06 μg/L, respectively.
2.2. Statistical analysis
2.2.1. Accumulation profiles
SPSS 17.0 (International Business Machines Corporation, USA) was utilised for statistical analysis. Normality of distribution was evaluated for all data by Shapiro–Wilk’s test. Data that did not fit
a normal distribution were subjected to logarithmic transformation and retested for normality.[19]
Data displaying normal distribution after transformation were evaluated with analysis of variance
(ANOVA), non-parametric tests were utilised otherwise. For multiple comparison tests, Levene
test was first utilised to determine the homogeneity of variances. Tukey’s test was utilised for
homoscedastic data sets; Tamhane’s test was applied otherwise.[3] Non-parametric tests were
utilised in cases where parametric tests were not applicable. A Kruskal–Wallis test was used for
the investigation of accumulation differences in non-parametric data, while the Mann–Whitney
U-test was used to identify significant accumulation differences between tissues.[20]
Chemistry and Ecology
2.2.2.
757
Correlation analysis
Correlation analysis is a potent statistical method utilised to observe the relation between two
independent variables, and was used in this study to evaluate the correlations between metal
accumulations in the four tissue types tested. Prior to analysis, all results were subjected to the
Kolmogorov–Smirnov test to observe the normality of data distribution. The normality graph was
evaluated; the data sets that fit a probability distribution were analysed via Pearson’s test, whereas
those that did not were analysed via Spearman’s rank test. p < 0.05 and p < 0.01 were used as
significance criteria.
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2.2.3. Principal component analysis
Principal component analysis (PCA) is a statistical method utilised to partition the available data
into linearly uncorrelated variables in a way that concentrates the maximum variance in the group
into the first few components. Interrelations amongst the metal concentrations in each of the
four tissues were investigated by PCA. Two main component groups were observed by PCA
for all tissues, contribution ratios of the first and second principal components were 46.90 and
25.17% (72.07% total) for exoskeleton, 47.03 and 27.33 (74.36% total) for gills, 39.52 and 23.17%
(62.70% total) for hepatopancreas, and 34.36 and 30.92% (65.29% total) for muscle samples.
2.2.4. Cluster analysis
Cluster analysis is a commonly utilised technique for classifying a large volume of data into a
number of groups based on similarity and was utilised to characterise the overlying trends in metal
accumulation results. Hierarchical clustering was performed based on Euclidean distances and
Ward’s method; data were standardised using Z-scores.[21]
3.
Results and discussion
Seasonal changes in trace element concentrations in crayfish tissues are presented in Table 1.
Greater statistical differences were observed in exoskeleton and gill tissues in all seasons, possibly
because these tissues are in constant contact with the external environment. Hepatopancreas and
muscle tissues were found to experience fewer fluctuations in metal accumulation rates, and
seasonal changes generally did not have a significant bearing on metal accumulation in these
tissues. This result is in line with previous evidence that hepatopancreas and muscle tissues
accumulate metals more slowly than the exoskeleton and gills, especially after exposure to high
metal concentrations.[22] Cu was the only exception to this trend and displayed notable seasonal
differences in hepatopancreas and muscle tissues, which might be a result of the vital metabolic
role of this element. The overall greatest seasonal difference was displayed by Zn, gill tissue
accumulation of which was statistically different for all seasons. No other metal demonstrated
such rapid changes in accumulation. Heavy metal analysis results previously conducted in Lake
Yeniçağa are also shown in Table 2, and are generally in line with our observations.
The correlation matrix of all metal accumulations across all tissues tested in given in Table 3.
All correlations between metal accumulation amounts in exoskeletal tissue were found to be
positive, the same situation is observed in metal accumulations in hepatopancreatic tissue. Both
tissue types are known to serve as ‘sinks’ for accumulated metals, and the positive correlations
observed may be a result of many metals being sequestered in the same site.[24,25] In addition,
positive correlations were also prominent between metal accumulations in the exoskeleton and
abdominal muscle.
Metals and metalloid concentrations of crayfish tissues, analysed by separately considering different seasons and tissues (μg/g dry weight).
Al
Spring
Exoskeleton
Gills
Hepatopancreas
Muscle
Summer Exoskeleton
Gills
Hepatopancreas
Muscle
Autumn Exoskeleton
Gills
Hepatopancreas
Muscle
Winter Exoskeleton
Gills
Hepatopancreas
Muscle
(a) 889.50
± 556.89a.b
(b) 6573.04 ± 2628.60a.d
(c) 72.99 ± 122.95a.c.d
(d) 138.64 ± 108.29a.b.c.d
(a,b,d) 728.99 ± 418.21a.b
(a,b) 2890.20
± 2465.82b.c.d
(c,d) 180.57 ± 140.96b.c.d
(a,c,d) 164.68 ± 67.22a.b.c
As
(a,c,d) 1.84 ± 0.70a
(b) 6.93 ± 1.70a.b
(a,c,d) 2.53 ± 1.85a.b.c.d
(a,c,d) 2.56 ± 0.59a.b
(a,c,d) 2.54 ± 0.82b
(b) 5.53 ± 2.62a.b.c
(a,c) 3.27 ± 1.90a.b.c,d
(a,d) 1.73 ± 1.05a.b.c.d
(a) 375.36 ± 180.01c
(a,d) 1.01 ± 0.34c.d
(c,d) 86.23 ± 39.22a.b.c.d
(c,d) 1.65 ± 0.79a.b,c.d
(b) 3094.18 ± 1071.22b.c.d
(c,d) 99.15 ± 65.81a.b.c.d
(a) 136.36 ± 32.15d
± 1496.67a.b.c.d
(c,d) 87.22 ± 40.24a.b.c.d
(c,d) 60.46 ± 22.20a.c.d
(b) 3834.30
(b) 2.78 ± 1.15b.c.d
(a,c,d) 1.19 ± 0.38b.c.d
(a,b,d) 1.01 ± 0.23c.d
(a,b,c,d) 1.74 ± 1.20c.d
(b,c,d) 2.08 ± 1.04a.b.c.d
(a,b,c,d) 1.4 ± 0.71b.c.d
Cu
± 1.32a,d
± 11.70a.b.d
(c,d) 16.87 ± 11.31a.b
(c,d) 21.21 ± 7.94a.b.c.d
(a,c,d) 14.55 ± 4.11b.c
(b) 40.44 ± 13.13a.b.d
(a,c,d) 8.00 ± 5.20a.b
(a,c,d) 14.80 ± 4.43a.b.d
(a) 13.30 ± 3.30b.c
(b,c) 79.52 ± 13.98c
(b,c) 75.42 ± 56.16c.d
(d) 22.96 ± 3.82a.c.d
(a) 8.83 ± 3.06a.d
(b,c) 52.30 ± 10.92a.b.d
(b,c) 130.37 ± 77.81c.d
(d) 17.21 ± 5.99a.b.c.d
(a) 8.20
(b) 55.12
Fe
Ni
(a,) 66.39 ± 40.07a.b
(a,c) 2.12
(c) 70.36 ± 109.37a.c
(a,c) 1.55 ± 1.29a.c
(b) 686.95 ± 290.64a
(d) 8.67 ± 2.99a.b.c
(a,b) 53.39 ± 27.68a.b
(a,b) 208.75 ± 189.33b.c
± 8.04b
(d) 6.10 ± 2.64a.b.c.d
(a) 22.27 ± 11.27c
(b) 254.46 ± 83.60b.c
(c) 46.77 ± 12.72a.c.d
(d) 6.78 ± 5.95a.b.c.d
(a) 7.36 ± 2.09d
(b) 426.52 ± 178.17d
(c) 62.79 ± 29.32c.d
(d) 4.09 ± 1.87b.c.d
(c) 18.22
± 1.17a.b.c.d
(b) 21.41 ± 9.09a.d
(d) 0.24 ± 0.18a.c
± 1.68a.b.c.d
(b,c) 7.17 ± 2.82b
(a,b,c) 5.41 ± 3.40b.d
(a,d) 2.22 ± 1.67b
(a) 3.68 ± 2.27a.b.c.d
(b) 12.93 ± 3.86c.d
(c) 1.18 ± 0.67a.c
(d) 0.26 ± 0.39a.c.d
(a) 2.08 ± 1.58a.b.c.d
(b) 18.09 ± 4.95a.c.d
(c) 3.79 ± 0.73b.d
(d) 0.55 ± 0.15c.d
(a,c,d) 3.60
Zn
(a) 92.48 ± 62.75a.b
(b,c) 16.96 ± 5.47a
(b,c) 12.91 ± 6.38a.b.c
(d) 19.20
± 2.85a.c
(a,b) 100.02
± 39.11b
(a,d) 198.90
± 108.53b
(a,b,d) 113.46 ± 37.57a.b
(c) 11.13 ± 5.95a.b.c
(a) 4.47 ± 1.82c.d
± 2.20c
± 5a.b.c
(c,d) 17.76 ± 2.45a.c
(a) 3.49 ± 0.49c.d
(b) 10.24 ± 1.75d
(c) 48.22 ± 27.37d
(c) 25.38 ± 4.26d
(b) 8.30
(c,d) 15.90
Note: Superscript letters to the right of entries in the table denote comparisons between different seasons in the same tissue. Columns bearing the same letter are not statistically different (p = 0.05). Superscript letters
in parentheses to the left of entries in the table denote comparisons between different tissues in the same tissue. Columns bearing the same letter are not statistically different (p = 0.05).
E. Tunca et al.
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758
Table 1.
Concentration ranges of heavy metals in water and sediment samples from Lake Yeniçağa, compared with 2008–2009 results, quality classes and guideline limits.
Lake Yeniçağa
water samples
(μg/L)
As
Cu
Ni
Zn
Drinking
water criteria
(μg/L)
Turkish inland water
quality classes
(μg/L)
Lake Yeniçağa
sediment samples
(μg/g)
Sediment quality
guidelines
(μg/g)
2008–2009
[13]
This study
WHO
[23]
I
II
III
IV
2008–2009
[13]
This study
Nonpolluted
Moderately
polluted
Heavily
polluted
2.7–26.9
0–0.6
0–9.7
14.6–110.6
25–26
14–79
189–255
47–506
10
2000
20
3000
20
20
20
200
50
50
50
500
100
200
200
2000
>100
>200
>200
>2000
4.4–49
18–34
50–103
1.2–713
8.8–32.3
21.6–33.9
61.5–95.3
49–77.3
<3
<25
<20
<90
3–8
25–50
20–50
90–200
>8
>50
>50
>200
Chemistry and Ecology
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Table 2.
759
760
Al− Exo
As− Exo
Cu− Exo
Fe− Exo
Ni− Exo
Zn− Exo
Al− Gill
As− Gill
Cu− Gill
Fe− Gill
Ni− Gill
Zn− Gill
Al− Hep
As− Hep
Cu− Hep
Fe− Hep
Ni− Hep
Zn− Hep
Al− Msc
As− Msc
Cu− Msc
Fe− Msc
Ni− Msc
Zn− Msc
Correlation of all metals and metalloid in tissues.
Al− Exo
As− Exo
Cu− Exo
Fe− Exo
Ni− Exo
Zn− Exo
Al− Gill
As− Gill
Cu− Gill
Fe− Gill
Ni− Gill
Zn− Gill
Al− Hep
1
.60a
.18
.96a
.17
.74a
.17
.64a
−.16
.10
−.16
.52a
.00
.17
−.62a
−.46a
−.16
−.63a
.30
.55a
−.04
.48a
−.08
.05
1
.21
.68a
.46a
.64a
.13
.62a
−.51a
−.02
−.32b
.75a
.17
.49a
−.72a
−.52a
.24
−.48a
.59a
.41a
−.05
.42a
.38b
.43a
1
.13
.46a
0.11
−.28
.03
.17
−.44a
−.56a
.08
.09
.14
−.18
−.23
.00
−.40b
.21
−.29
−.05
.13
.21
.14
1
.18
.74a
.21
.72a
−.24
.14
−.15
.57a
−.01
.19
−.69a
−.46a
−.11
−.66a
.32b
.54a
−.06
.48a
−.02
.07
1
.02
−.10
.05
−.14
−.25
−.31
.10
.27
.44a
−.16
−.15
.06
−.23
.39b
−.14
.13
.14
.24
.09
1
.14
.68a
−.47a
.03
−.26
.74a
−.04
.12
−.78a
−.72a
.05
−.63a
.29
.46a
−.33b
.28
.21
.34a
1
.30
.07
.87a
.59a
.08
−.26
.21
−.03
.17
−.24
−.16
−.15
.37b
.18
.14
−.29
−.19
1
−.20
.22
−.05
.57a
−.07
.26
−.61a
−.46a
−.12
−.65a
.40a
.50a
−.08
.57a
.11
.02
1
.08
.30
−.60a
−.33b
−.35b
.40b
.39b
−.57a
.01
−.29
−.26
.45a
−.03
−.67a
−.64a
1
.78a
−.02
−.31
.12
0.12
.36b
−.17
.02
−.26
.36b
0.12
0.14
−.37b
−.24
1
−.33b
−.39b
−.15
.46a
.54a
−.15
.31
−.43a
.25
.17
.03
−.40b
−.46a
1
.09
.31
−.73a
−.67a
.25
−.46a
.36b
.39b
−.31b
.19
.41a
.58a
1
.50a
.03
−.02
.61a
.30
.22
−.21
−.15
−.19
.48a
.45a
(Continued)
E. Tunca et al.
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Table 3.
Al− Exo
As− Exo
Cu− Exo
Fe− Exo
Ni− Exo
Zn− Exo
Al− Gill
As− Gill
Cu− Gill
Fe− Gill
Ni− Gill
Zn− Gill
Al− Hep
As− Hep
Cu− Hep
Fe− Hep
Ni− Hep
Zn− Hep
Al− Msc
As− Msc
Cu− Msc
Fe− Msc
Ni− Msc
Zn− Msc
Continued
As− Hep
Cu− Hep
Fe− Hep
Ni− Hep
1
.01
−.12
.34a
.08
.48a
.08
.01
.24
.33b
.41b
1
.69a
.02
.75a
−.36b
−.23
.22
−.20
−.24
−.26
1
.03
.60a
−.37b
−.07
.39b
−.08
−.30
−.40b
1
.41a
.01
−.02
−.47a
−.20
.68a
.64a
a
Zn− Hep
Al− Msc
As− Msc
Cu− Msc
1
.20
.14
.59a
.46a
.36b
1
.15
.46a
−.12
.04
1
.26
−.44a
−.45a
Fe− Msc
Ni− Msc
Zn− Msc
1
.74a
1
Chemistry and Ecology
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Table 3.
1
−.25
−.26
−.04
−.31
.08
.13
1
.06
−.09
b
Notes: Exo, exoskeleton; Hep, hepatopancreas; Msc, muscle. The mean difference is significant at the 0.01 level (p < 0.01). The mean difference is significant at the 0.05 level (p < 0.05).
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E. Tunca et al.
Figure 2. Principal component analysis (PCA) results of (a) exoskeleton, (b) gill, (c) hepatopancreas and (d) abdominal
muscle tissues.
It is now well-established that aqueous Al is bioavailable and toxic to freshwater fish and
invertebrates at neutral pH.[26] All correlations between Al and As were found to be positive,
while Al and Cu consistently yielded negative correlations. Al accumulation in any tissue did not
correlate with Al in any other tissue. PCA of individual tissues place Al in the same component
as Fe in all tissues except abdominal muscle. Likewise, when overall metal concentrations are
taken into account, Al and Fe are placed in the same cluster and are the closest among any
metal. Correlation analysis supports this result, yielding a strong correlations between Al and
Fe concentrations in the exoskeleton (r = 0.960) and gills (0.868). A weaker correlation is also
observed between the two metals in abdominal muscle tissue (r = 0.592) while no correlation
is apparent in the hepatopancreas. Kurun et al. report similar interactions between Al and Fe
accumulations, which may result from similarities in the metals’ adsorption kinetics.[12] The
weakness (or absence) of correlations in internal tissues (hepatopancreas and abdominal muscle)
suggest that adsorption, and not regulatory processes, is the main driving force behind the Al–Fe
correlations observed. This observation is supported by the similar chemistry shared by Al and
Fe, which share similar chemical characteristics and are known to substitute each other in human
proteins.[27,28] Also conspicuous is the correlation of exoskeletal Al amounts with Zn in the
same tissue. PCA analysis generally supports the correlations observed (Figure 2a–d).
A significant correlation was observed between Al and Ni in gill tissue (r = 0.586), Al, Fe
and Ni were also included in the same component in the PCA of gill tissues. In hepatopancreas
samples, the correlations of Al accumulation with Ni and As are notable (Al–Ni: r = 0.611, Al
– As: r = 0.498). This might be because the hepatopancreas is the main site of detoxification in
crayfish, and may accumulate a variety of metals. PCA of hepatopancreas data placed Al, Ni and
As in the same component, although Fe was also included in this component.
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Chemistry and Ecology
763
Gills were found to be the prime site of Al accumulation. In addition, Al accumulation was
observed to be the greatest among the metals tested, a result supported in previous literature.[29]
Gills are a prime site of pollutant accumulation and damage, and it is known that gills play an
important role for the uptake of Al.[12,30] Histochemical analysis has previously demonstrated
that Al is preferentially accumulated in the extracellular space of the gill epithelium, which is
associated with the mucus layer.[29]
Some inorganic forms of arsenic, such as As(III) and As(V), are toxic, being associated with
mitochondrial impairment and inhibition of the glycolytic energy metabolism.[31] In addition,
As is a known carcinogen for humans.[3] In no situation was As positively correlated with Cu,
although all Al–As correlations were positive. Exoskeletal As concentrations were found to correlate with Zn accumulation across all tissues; this correlation was negative in the hepatopancreas
and positive in all other tissues. Although gill concentrations of As were slightly higher, a more uniform tissue distribution of this metal was observed compared with other elements tested. As is the
only element displaying no statistically significant accumulation difference between tissues, this
situation was only observed in winter season As accumulations. Because As can be converted to
non-toxic organoarsenic compounds in crayfish, the relatively homogenous presence of As might
be accounted by the fact that certain amounts of As can be tolerated in all tissues. In addition,
adsorption to the carapace has been suggested as an important accumulation mechanism for As.
Since the carapace is a major As adsorption site, moult events can lead to substantial decreases in
overall As accumulation. This, in turn, could partially account for the relatively high homogenity
of this element in crayfish tissues, especially in the immediate period after moulting.[32]
Cu is of paramount importance for decapod crustaceans due to its incorporation into the
oxygen-carrying protein haemocyanin. Cu mostly accumulates inside lysosomal-type, acidphosphatase-containing vesicles, whereas most of the other metals are stored in granules.[24]
Crayfish species are known to possess an effective Cu regulation system, by which tissue Cu
levels can be kept relatively constant regardless of external Cu concentrations.[33] Zn is likewise
capable of accumulating in high amounts independently of exposure concentrations, and it is curious that accumulations of those two metals have correlated in several tissues. The sole positive
correlation observed between the two metals was in the hepatopancreas, where a relatively strong
interaction was observed (r = 0.745). Prior studies have also indicated that Zn and Cu accumulations are positively correlated in this tissue.[34] All other correlations, however, are negative, and
similar results are attested in the literature, albeit without a proposed mechanism.[35] We propose
here that the effect in question is potentially attributable to metallothioneins; low molecular mass
proteins showing high affinity for Group IB and IIB metal ions.[36] Metals usually associated
with metallothioneins are Cu, Zn and Cd. Their major physiological role is to serve as a reservoir
of cations such as Cu and Zn, which are used for a number of vital metabolic functions.[37]
However, their possible role in the redistribution of heavy metals in tissues has not fully been
elucidated.[38]
Negative correlations generally observed in Zn–Cu associations may result from those metals
saturating available metallothionein amounts in all tissues except the hepatopancreas (where
metallothioneins are abundantly produced and thus a positive correlation is present). As such, the
two metals compete for available metallothionein binding sites, resulting in a negative correlation.
In addition, metallothionein expression levels generally correlate with the availability of the metals
they sequester.[39]As such, the presence of Cu or Zn may have induced metallothionein expression
and led to the sequestration of both metals in the hepatopancreas. Because the hepatopancreas is the
main site of toxin decontamination in crayfish and bears high concentrations of metallothioneins,
the competitive environment is expected to be absent in this tissue.[40] This, in turn, would lead to
co-accumulation of both Zn and Cu by the metallothionein supply, resulting in a relatively strong
positive correlation. No correlation between Cu and Zn was observed in the exoskeleton, where
the impact of metallothioneins is expected to be minimal.
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E. Tunca et al.
In addition, Zn may compete with Cu in a variety of metabolic functions, such as the divalent
cation antiport process, which may further account for the negative correlations observed.[37] It
must also be stressed that metal–metallothionein interactions are altered by a number of other
factors, including the effects of hormones, pH, other metals and environmental conditions.[41]
However, despite the existence of metal-specific metallothioneins, those proteins are also triggered as a general response to the presence of many metals, suggesting that Zn and Cu-binding
mechanisms may partially overlap.[42]
Cu yielded three statistically meaningful correlations with Al (gills Cu–hepatopancreas Al,
hepatopancreas Cu–exoskeletonAl and hepatopancreas Cu–muscle tissueAl), all three were found
to be negative. PCA placed Cu and Al in different components for all tissue types tested. The
greatest Cu accumulation was in gills, followed by the hepatopancreas. Those results differ from
previous studies, where the hepatopancreas was generally found to be the prime accumulation
site.[6,12,43]
Zn is utilised in metalloenzymes as the active core. In addition, the metal serves as a cofactor
in various enzymatic systems.[3] It is notable that a positive correlation was observed between
Zn accumulations in gills and the exoskeleton (r = 0.735), possibly due to the constant external
contact both tissue types experience. It is difficult to speak of general accumulation trends for
Zn, because significant differences in accumulation were observed between seasons. This result
is in stark contrast with prior studies, where Zn accumulation was generally and consistently
concentrated in hepatopancreatic tissue.[43]
The primary function of iron in decapod crustaceans is generally to form the nuclei of enzymes
and pigments. The bioavailability of aqueous iron is affected by the valence of the metal: While
ferrous iron (Fe2+ ) is vital for most animals, ferric iron (Fe3+ ) is non-essential.[44] A moderate
relationship between Fe accumulations in the exoskeleton–hepatopancreas and exoskeleton–
muscle tissue pairs was observed by correlation analysis, whereas the exoskeleton–hepatopancreas
result was found to be negative. Further, Fe correlated with Ni in gill tissue (r = 0.781).
The greatest accumulation amounts were noted in the gills, reflecting previous results on Fe
accumulation.[12]
It is still uncertain whether Ni should be considered an essential element.[45] As such, work
in the literature may regard the element as essential or non-essential.[46,47] Essential or otherwise, Ni still shows toxic effects above a threshold concentration, having been shown to induce
chromosomal aberrations and suppress immunological responses in animal cells.[24] A significant positive correlation between Ni and Zn accumulations was observed in abdominal muscle
tissue (r = 0.736). Ni was observed to accumulate in greatest amounts in gill tissue, while the
least accumulation was observed in the abdominal muscle. Those results are in line with previous
studies.[46]
Metal accumulations were also investigated on a per specimen basis without regard to tissue
origin. Hierarchical cluster analysis was used for this purpose. Al and Fe were found to cluster
extremely close in this study (Al–Fe = 4.621 Euclidean distance), possibly because the trivalency
of Fe3+ and Al3+ cations result in similar mechanisms for the accumulation metabolism of those
Table 4.
Dendrogram of cluster analysis (specimen basis).
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Chemistry and Ecology
Figure 3.
Metal concentrations determined in (a) water and (b) sediment samples.
765
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766
E. Tunca et al.
metals, especially since those metals were primarily accumulated on the exoskeleton and gills,
where adsorption processes dominate. Accumulations of Al and Fe were greater than that of
any other element, again possibly resulting from their adsorption on the exoskeleton. In addition,
Al–Fe correlations were observed to be very high in correlation analysis.Al–Ni and Fe–Ni are other
pairs placed close together in cluster analysis (Al–Ni = 7.124 Euclidean distance, Fe–Ni = 6.108
Euclidean distance). In addition, Al and Fe are placed in the same cluster, and Ni is also placed
near this group (Table 4). Zn and Ni were placed furthest apart from each other (Zn–Ni = 19.162
Euclidean distance).
The seasonal variation of element distribution in the water and sediment samples is shown in
Figure 3a,b. Water metal concentrations are higher in spring and summer than in other seasons,
possibly due to excavation work that took place in the lake during this time. These results were
compared with the Sediment Quality Guidelines (SQG) of US EPA, Turkish Inland Water Quality
Criteria and a prior study by Saygı and Yigit, which was carried out from March 2008 to February
2009 in this lake (Table 5).[13,48]
Perin et al. classified sediments in three classes; non-polluted, moderately polluted and heavily
polluted, based on the SQG of US EPA.[49] According to these criteria, Lake Yeniçağa is heavily
polluted with As and Ni, moderately polluted with Cu, and bears no Zn pollution. These results are
quite similar to the 2008–2009 results of Saygı andYigit, except for Zn, which displayed a wide and
fluctuating concentration range in the 2008–2009 study.[13] Metal concentrations in water samples
were generally higher than in Saygı and Yigit. This situation is likely caused by the excavation
work performed in the lake during spring and summer 2010. Water metal concentrations diminish
after these seasons, suggesting that the lake may recover from the additional contamination over
a short period. According to the Turkish Inland Water Quality Criteria, Lake Yeniçağa is second
class for As, third or fourth class for Ni and oscillates between first, second and third classes for
Cu and Zn, depending on seasonal variations.
Table 5.
Previous studies on fish in Lake Yeniçağa.[14,15]
Cyprinus carpio
As
Cu
0.47 ± 0.11
0.28 ± 0.07
0.71 ± 0.11
1.56 ± 0.23
0.68 ± 0.25
1.44 ± 0.25
Spring
Muscle
Liver
Gills
Al
15.24 ± 1.50
148.21 ± 10.74
30.01 ± 6.15
Summer
Muscle
Liver
Gills
5.40 ± 0.61
155.25 ± 11.33
17.04 ± 12.12
0.09 ± 0.01
2.48 ± 0.53
1.13 ± 0.90
Autumn
Muscle
Liver
Gills
42.14 ± 1.78
280.20 ± 53.2
203.3 ± 187.7
Winter
Muscle
Liver
Gills
4 Seasons
4 Seasons
Fe
8.42 ± 1.25
120.2 ± 7.19
38.88 ± 7.30
Ni
0.31 ± 0.12
1.74 ± 0.23
1.90 ± 0.28
Zn
38.72 ± 2.14
487.5 ± 32.80
958.9 ± 275.0
0.80 ± 0.05
3.50 ± 0.46
2.95 ± 0.47
3.21 ± 0.37
80.35 ± 10.25
161.29 ± 73.15
0.22 ± 0.08
7.80 ± 1.05
4.33 ± 2.24
10.05 ± 0.65
571.09 ± 107.3
1110.0 ± 289.0
0.15 ± 0.02
0.67 ± 0.11
1.07 ± 0.64
0.71 ± 0.08
2.25 ± 0.15
1.20 ± 0.09
9.58 ± 1.22
19.65 ± 4.18
66.01 ± 10.90
ND
ND
ND
41.26 ± 3.45
244.48 ± 133.3
341.8 ± 162.4
75.32 ± 2.97
108.04 ± 22.40
100.0 ± 45.1
0.22 ± 0.03
0.48 ± 0.11
0.65 ± 0.16
1.47 ± 0.17
1.20 ± 0.09
12.91 ± 5.87
10.77 ± 2.02
17.61 ± 8.23
58.56 ± 14.09
ND
ND
ND
58.54 ± 12.43
145.23 ± 54.97
285.3 ± 55.71
Muscle
Liver
Gills
Al
59.06 ± 13.37
528.56 ± 152.9
82.38 ± 18.4
As
0.26 ± 0.11
1.78 ± 0.85
1.28 ± 0.57
Tinca tinca
Cu
Fe
1.42 ± 0.25
9.23 ± 4.08
5.21 ± 1.78
84.10 ± 28.9
1.63 ± 0.30
99.21 ± 22.9
Ni
0.34 ± 0.10
1.52 ± 0.40
1.99 ± 0.55
Zn
45.53 ± 9.10
116.04 ± 35.8
86.71 ± 22.8
Muscle
Liver
Al
108.26 ± 10.9
453.62 ± 225
As
0.58 ± 0.26
2.29 ± 0.71
Leuciscus cephalus
Cu
Fe
1.79 ± 0.55
16.03 ± 4.78
3.16 ± 0.75
49.73 ± 16.1
Ni
0.06 ± 0.01
0.57 ± 0.25
Zn
57.81 ± 21.5
123.64 ± 0.64
Note: ND., not determined.
Chemistry and Ecology
767
Factors which influence the absorption rate of metals include alterations in salinity or water
hardness, temperature and pH of the surrounding medium, antagonistic and synergistic effects
between metals, specimen size, reproductive cycles and time elapsed since last moult.[24] As
many of those factors are subject to substantial changes over a year-long time period, the seasonal
changes observed in metal accumulations are not unexpected. In addition, the external metal concentrations and the duration in which the organism in question is exposed to metal contamination
are of obvious and substantial importance.[33,50]
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4.
Conclusion
In this study, water, sediment and narrow-clawed crayfish (Astacu leptodactylus) samples were
investigated to determine metal pollution at Lake Yeniçağa (Bolu, Turkey). The distribution of
five metals (Al, Cu, Fe, Ni, Zn) and a metalloid (As) in four crayfish tissues were evaluated and
the competitive and cooperative effects between heavy metal accumulation amounts were elucidated over four seasons. As accumulation displayed minimal fluctuations across tissues, possibly
because this element does perform vital functions and can be tolerated in form of organoarsenic
compounds. Strong positive correlations were found to be present between the accumulations
of Al and Fe in gills and the exoskeleton, and are interpreted to result from similarities in the
adsorption chemistries of these metals. All correlations in hepatopancreatic and exoskeletal tissue
data were found to be positive, which might be reflective of the fact that both tissue types serve as
deposits for a variety of metals. Strong negative correlations were observed between Zn and Cu,
this effect might be a result of the fact that metallothioneins display a strong affinity to both metals.
Zn–Cu correlations were positive in the hepatopancreas, where metallothionein concentrations
are sufficiently high to successfully sequester both metals, and absent in the exoskeleton, where
metallothionein-mediated binding presumably does not play a prominent role.
Acknowledgements
This research project (No 10B4240004) was supported by Ankara University. The authors are grateful to Kıymet Deniz,
Özge Buyurgan, Dr. Borga Ergönül, Assoc. Prof. Yasemin Saygı and Prof. Dr. Yusuf Kağan Kadıoğlu for their valuable
contributions in the construction of this manuscript.
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