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Haematological status of wintering great tits (Parus major) along a metal pollution gradient
Science of the Total Environment 408 (2010) 1174–1179
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Science of the Total Environment j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / s c i t o t e n v
Haematological status of wintering great tits (Parus major) along a metal pollution gradient Ann Geens a,⁎, Tom Dauwe a,c, Lieven Bervoets b, Ronny Blust b, Marcel Eens a a b c
Department of Biology, University of Antwerp, Ethology, Universiteitsplein 1, B-2610 Antwerp, Belgium Department of Biology, University of Antwerp, Ecophysiology, Biochemistry and Toxicology, Groenenborgerlaan 171, B-2020 Antwerp, Belgium VITO, Boeretang 200, B-2400 Mol, Belgium
a r t i c l e
i n f o
Article history: Received 3 August 2009 Received in revised form 13 November 2009 Accepted 16 November 2009 Available online 2 December 2009 Keywords: Metal pollution Parus major Haematology Blood Biomarker Biomonitoring
a b s t r a c t In the long-term biomonitoring of wild populations inhabiting polluted areas, the use of non-destructive biomarkers as markers of condition is very important. We examined the possible effects of metal pollution on the haematological status of adult great tits (Parus major) along a well-established pollution gradient near a non-ferrous smelter in Belgium. We measured blood and feather metal concentrations and assessed the haematological status (amount of red blood cells, haemoglobin concentration, haematocrit, mean corpuscular volume and mean corpuscular haemoglobin) of adult great tits during winter at four study sites. Metal concentrations in blood and feathers indicated that cadmium and lead were the most important metals in the pollution gradient under study. Measurements of haematological parameters revealed that haemoglobin concentration, haematocrit, mean corpuscular volume and mean corpuscular haemoglobin were lower in great tits from the more polluted sites. These parameters were significantly negatively correlated with blood lead concentration. The amount of red blood cells, however, did not significantly differ among study sites. Our results indicate that the haematological status of great tits is negatively affected by metal pollution and may therefore be used as a successful biomarker for monitoring the negative impact of metal exposure in the wild. © 2009 Elsevier B.V. All rights reserved.
1. Introduction Excessive deposition of metals in the environment and the resulting pollution is a well known problem in several areas around the world. Monitoring this pollution and assessing its effect on organisms is therefore an important issue. It has become important to look for organisms which can be used as biological indicators or monitors of those pollutants. The relevance of birds as biomonitors, especially for metal pollution, has often been emphasized (Burger, 1993; Furness, 1993). Several studies have successfully used bird eggs, feathers or other tissues to examine metal pollution (review see Burger, 1993). Although measuring metal concentrations in bird tissues alone is very useful, it may not be sufficient. Metal concentrations alone do not give any information about the biological stress caused by pollution. Therefore it is also necessary to look for meaningful biomarkers to assess the health state of organisms in relation to environmental pollution (Peakall, 1992). Special attention is given to the application of non-destructive biomarkers, such as morphometric measures and haematological characteristics, which may reflect an impact on the condition of the exposed animals. Body
⁎ Corresponding author. Tel.: +32 3 2652347; fax: +32 3 2652271. E-mail address: [email protected] (A. Geens). 0048-9697/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.scitotenv.2009.11.029
mass, tarsus and wing length reflect the condition of birds and are also indicative of survival and reproductive success (Tinbergen and Boerlijst, 1990). Several studies reported negative effects of metals (such as cadmium, copper, lead, mercury, nickel and selenium) on the growth and body weight of birds, affecting the bird's condition (Burger and Gochfeld, 1988; Eeva and Lehikoinen, 1996; Takekawa et al., 2002). Changes in haematology can act as sensitive, early warning signals of the possible toxic effects of metals on health and physiological status (Weeks et al., 1992). Haematological parameters are therefore widely used as indicators of condition (Bowerman et al., 2000; Dauwe et al., 2006; Rogival et al., 2006). The amount of red blood cells, haemoglobin concentration, haematocrit and red blood cell indices are indicative for the oxygen transport capacity of the blood (Ots et al., 1998). Metals such as cadmium and lead are also known to cause anemia, which might be reflected as lowered haematocrit values, lower haemoglobin concentrations and smaller mean corpuscular volume (Nyholm, 1998; Iolascon et al., 2009). Moreover, lead directly influences haemoglobin production through inhibition of the enzyme δ-aminolevuline acid dehydratase (ALAD; Bergdahl, 1998; Papanikolaou et al., 2005), which catalyzes the second step in the porphyrin and haem biosynthetic pathway. Zinc, which plays an essential role in the functioning of this enzyme is replaced by lead, which causes malfunction of the enzyme. ALAD has been used successfully as a biomarker for metal pollution in birds (Vanparys et al., 2008).
A. Geens et al. / Science of the Total Environment 408 (2010) 1174–1179
In this study, we examined the effects of metal pollution on the condition and health of adult great tits (Parus major) in four study sites located in a well known pollution gradient emanating from a non-ferrous smelter near Antwerp, Belgium. Previous research in this pollution gradient reported that levels of metals in the feathers of great tits from the site closest to the pollution source are among the highest reported in literature (Janssens et al., 2001). Levels of lead and cadmium in juvenile feathers and eggs of great and blue tits (Cyanistes caeruleus) from this site were very high for passerine species (Dauwe et al., 1999) and are strikingly higher than concentrations assumed to cause detrimental effects (Scheuhammer, 1987). This poses a serious strain on the surrounding natural environment and the organisms that live there. Previous research in this pollution gradient reported negative effects of metal pollution on biochemical markers (Vanparys et al., 2008), immunocompetence (Snoeijs et al., 2004), behaviour (Janssens et al., 2003a; Gorissen et al., 2005), colouration (Dauwe and Eens, 2008; Geens et al., 2009) and reproductive success of great tits (Janssens et al., 2003b). Our main goal was to compare both morphometric (body weight, tarsus and wing length) and haematological parameters along the pollution gradient. Metal concentrations in blood were determined as an indicator of the internal metal levels. We also measured metal concentrations in tail feathers. Metal concentrations in feathers may, however, change and increase with the age of the feather due to exogenous contamination onto the feather surface by atmospheric depositions and/or from secretion products of the uropygial gland smeared onto the feathers during preening (Dauwe et al., 2003; Jaspers et al., 2004). Haematological characteristics, such as amount of red blood cells, haemoglobin concentration, haematocrit and red blood cell characteristics (mean corpuscular volume and mean corpuscular haemoglobin), were measured to evaluate the impact of metal pollution on haematological status. The haematological status is important for the performance and survival of the bird (Kilgas et al., 2006; Nadolski et al., 2006). Haematological parameters have already been used as biomarkers for biologically active metal concentrations in organisms. Because of their fast response to metal pollution, these markers can be used to scan for toxic effects in an early stage, for example in humans (Papanikolaou et al., 2005) and mice (Rogival et al., 2006).
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Antwerp. Pollution originates from uncontrolled emissions from dust of ore piles, which is deposited in close proximity of the smelter. Lead, cadmium, arsenic, copper and zinc are especially common pollutants in this area and they form an exponentially decreasing pollution gradient away from the factory complex (Janssens et al., 2001). In 2005, mean values of lead and cadmium in PM10-dust fraction ranged from respectively 35–381 ng/m3 and 2–7 ng/m3 in the area surrounding the smelter and were among the highest values measured in Belgium and surrounding European countries (VMM, 2007). Our study sites are located eastwards at different distances from the smelter, namely UM (0–350 m), F8 (400–600 m), F7 (2500 m) and F4 (8500 m; Fig. 1). These sites have been used for research on great tits since 1999 (Dauwe et al., 1999) so there is a well-established population of great tits, occupying 30–50 nest boxes in every study site. Special attention was paid in selecting study sites with a similar habitat type (deciduous park sites). 2.2. Data sampling Between 15th of November and 1st of December 2006, 69 great tit adults (45 males and 24 females) were caught while sleeping in a nest box. Captured birds were sexed and aged (first-year versus older birds) and marked with individually numbered metal rings. All birds were weighed with a precision of 0.1 g, using a digital balance (Kern 466-41) and the tarsus length was measured to the nearest 0.1 mm with a digital sliding calliper. Wing length was measured to the nearest 1 mm using a ruler. Body condition was calculated as the standardized residuals from a linear regression of body mass on tarsus length (Ots et al., 1998). We collected a blood sample (300 µl) from the brachial vein with a Microvette® CB 300 lithium-heparin capillary tube (Sarstedt AG & Co., Germany) to measure haematological parameters and blood metal concentrations. It was however not always possible to collect 300 µl, so only samples with sufficient volume were used both for haematological and metal analysis. Blood samples were immediately stored at 4 °C and haematological analysis took place within 2 h. The left and right outermost tail feathers were collected and stored in paper envelopes for determination of metal concentrations (Eens et al., 1999).
2. Methods 2.3. Haematological analysis 2.1. Study sites The present study was performed in four study sites along a pollution gradient originating from a non-ferrous smelter in the South of
We measured the amount of red blood cells (RBC in 106/mm3), haemoglobin concentration (HGB in g/dl), haematocrit (HCT in %), mean corpuscular volume of red blood cells (MCV in µm3) and mean
Fig. 1. The location of the four study sites (UM, F8, F7 and F4) along a heavy metal pollution gradient originating from a large non-ferrous metal smelter in the south of Antwerp.
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corpuscular haemoglobin per red blood cell (MCH in pg), using an Horiba ABX Micros 60 haematology analyzer (Horiba ABX, Montpellier, France). Because of the limited blood sample volume, we could only measure haematological parameters for 58 birds. Reproducibility (runto-run precision) of the measurements is certified by measuring a control (provided by Horiba ABX) with known concentrations each run. Repeatability (within-run precision) of the measurements is ensured because the ABX Micros 60 measures every sample for a maximum of three times. Results are only accepted if two out of three counts are within the systems precision limits for that specific parameter.
were not included in the statistical analysis because concentrations were below the detection limit of the ICP-MS. The relation between blood and feather metal concentrations was tested with a Pearson correlation. To test the relation between blood metal concentrations and haematological parameters, we used linear regressions, corrected for the effect of study site. We assessed which metals in blood samples differed significantly among study sites. As will follow, this was the case for cadmium and lead. Subsequently, we only calculated the relation between haematological parameters and these metals. All values given are arithmetic means ± standard errors (SE).
2.4. Metal analysis
3. Results
Feathers were washed two times, both in deionised water and acetone (1 mol l− 1) to remove loosely adherent external contamination (Gochfeld et al., 1996). All feather samples were then put individually in 4 ml polypropylene, metal free vials and dried in an oven at 60 °C for 24 h. Dry weight was determined on a Mettler AT 261 Deltarange balance to the nearest 0.01 mg. Blood samples were stored in 1.5 ml polypropylene, metal free vials., The fresh weight of the remaining blood after haematological analysis was determined. Blood samples were then dried in an oven at 60 °C and after 24 h dry weight was also measured. Subsequently, feather and blood samples were digested prior to metal analysis following the microwave heating digestion described in Blust et al. (1988). We added a 1:1 mixture of 100 μl HNO3 (70%) and H2O2 (30%) per 10 μg dry sample, followed by repeated microwave heating. After digestion, samples were diluted with 2 ml ultrapure, deionized water (MilliQ, Millipore) and stored at −20 °C until metal analysis. We measured silver (Ag), arsenic (As), cadmium (Cd), copper (Cu), cobalt (Co), nickel (Ni), lead (Pb) and zinc (Zn) levels in the samples with an axial Inductively Coupled Plasma-Mass Spectrophotometer (ICP-MS; Varian Inc., Palo Alto, USA). Blanks and certified BCR-reference material (VMK 102, Bureau of Certified References) were added to each batch of samples as quality control. Recovered concentrations of the certified samples were within 10% of the certified values, which is an acceptable margin. Metal concentrations were expressed as μg/g on a fresh weight basis.
3.1. Metal concentrations in blood and feathers
2.5. Statistical analyses We used SPSS 15.0 for Windows (SPSS Inc., Chicago, Illinois, USA) and XLSTAT Version 2009.1.02 (Addinsoft, New York, USA), to perform statistical analysis. Outliers in the data (data points that are minimum three standard deviations larger than the mean) were removed prior to analyses. A significance level of 0.05 was chosen for all statistical tests. Normality of the data was tested with a Shapiro– Wilk test (p b 0.05). Data of metal concentrations was not normally distributed, so data was normalised using a ln(x + 1) transformation. Blood and feather metal concentrations and haematological parameters were compared among study sites using general linear mixed models, with study site, sex and age as fixed parameters and body condition as a covariate. Significant differences were tested post hoc with a Tukey HST test. Ag and As concentrations in blood samples
We tested for significant differences in mean feather and blood metal concentrations among study sites. Mean blood and feather metal concentrations per study site and the results of the ANOVA and Tukey HST tests are reported in Tables 1 and 2. In feathers, all metals differed significantly among study sites, with the highest concentrations measured in the sites closest to the pollution source (UM and F8). Blood metal concentrations differed only among study sites for cadmium and lead, with the highest concentrations also in UM and F8. Sex, age, body condition did not significantly affect blood or feather metal concentrations (F b 2.7, p N 0.3 in all cases). We also examined the correlations between metal levels in blood and feathers. There was both a significant positive correlation between Pb (r = 0.76, p b 0.001) and Cd (r = 0.37, p b 0.01) levels in blood and feathers of great tits. For all other measured metals, there were no significant correlations between the metal concentrations of blood and feathers (all p N 0.1). 3.2. Morphometric and haematological parameters Male great tits had significantly longer tarsi (males: 20.38 mm± 0.07; females: 19.82 mm± 0.15; F1,66 = 15.3, p b 0.001, n = 69) and wings (males: 73 mm± 1; females: 70 mm± 1; F1,66 = 22.3, p b 0.001, n = 69) and were heavier (males: 17.0 g ± 0.1; females: 15.8 g ± 0.2; F1,66 = 33.8, p b 0.001, n = 69) than females. Males also had a higher body condition compared to females (males: 0.23 ± 0.11; females: − 0.43± 0.14; F1,66 = 12.6, p = 0.001, n = 69). There were no significant differences for tarsus, wing length, body mass and body condition between age groups or among sites (F b 1.436, p N 0.1, n = 69 in all cases). Sex and age never had a significant effect on the measured haematological parameters (F b 1.9, p N 0.2, n = 58 in all cases). The amount of red blood cells (RBC) did not differ significantly among study sites (F3,57 = 1.4, p = 0.3; Table 3). Great tits from UM and F8 however did have a significant lower haemoglobin concentration compared to great tits from F7 and F4 (F3,57 = 3.2, p = 0.03, Tukey HST test p b 0.05; Table 3). Haematocrit levels were also significantly lower in UM and F8 compared to F7 and F4 (F3,57 = 3.0, p = 0.04, Tukey HST test p b 0.05; Table 3). Mean cell volume and mean cell haemoglobin concentration were both significantly higher in the least polluted sites F7 and F4
Table 1 Mean metal concentration (µg/g fresh weight±SE; n =57) and results of the one-way ANOVA for blood of great tits in a metal pollution gradient. The letters (A–B) indicate significant differences (Tukey-test, pb 0.05). Letters are not shown if there are no significant differences. UM (n = 16) Cd Co Cu Ni Pb Zn
0.016 ± 0.003 0.35 ± 0.08 0.13 ± 0.02 0.11 ± 0.03 0.28 ± 0.02 5.5 ± 0.5
F8 (n = 15) A
A
0.011 ± 0.002 0.25 ± 0.05 0.09 ± 0.02 0.14 ± 0.03 0.17 ± 0.02 6.9 ± 0.5
F7 (n = 16) A
A
0.007 ± 0.001 0.25 ± 0.04 0.20 ± 0.03 0.13 ± 0.05 0.03 ± 0.01 7.9 ± 0.7
F4 (n = 10) B
B
0.007 ± 0.001 0.23 ± 0.07 0.13 ± 0.03 0.18 ± 0.03 0.02 ± 0.02 6.9 ± 0.7
B
B
F
p
4.4 0.6 0.3 4.1 37.1 1.2
b0.01 0.6 0.8 0.1 b0.001 0.3
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Table 2 Mean metal concentration (µg/g fresh weight±SE; n= 69) and results of the one-way ANOVA for feathers of great tits in a metal pollution gradient. The letters (A–B) indicate significant differences (Tukey-test, pb 0.05). Letters are not shown if there are no significant differences. UM (n = 18) Ag As Cd Co Cu Ni Pb Zn
3.9 ± 0.5 31 ± 3 11 ± 3 0.27 ± 0.05 37 ± 4 13.0 ± 3.0 140 ± 18 240 ± 26
F8 (n = 17) A A A A A A A
2.6 ± 0.5 21 ± 3 17 ± 6 0.25 ± 0.07 36.5 ± 5.0 14.0 ± 6.0 110 ± 19 216 ± 25
F7 (n = 22) A A A A A
0.11 ± 0.02 2.6 ± 0.2 0.39 ± 0.04 0.02 ± 0.01 9.8 ± 0.9 7.2 ± 2.2 8.1 ± 1.3 142 ± 13
A A
compared to the other two sites UM and F8 (MCV: F3,57 = 4.0, p = 0.01; Tukey HST test p b 0.02; MCH: F3,57 = 5.4, p = 0.003, Tukey HST test p b 0.03; Table 3). 3.3. Relation between metal pollution and haematological parameters There were no significant relations between blood cadmium concentration and haematological parameters (p N 0.09 in all cases). We however did find negative relations between blood lead concentrations and haemoglobin concentration (lead: β = −0.56, p b 0.05; study site: β = 0.58, p b 0.05), haematocrit (lead: β = −0.37, p b 0.01; study site: β = 0.42, p b 0.05), mean cell volume (lead: β = −0.62, p b 0.05; study site: β = 0.63, p b 0.01) and mean cell haematocrit (β = −0.31, p b 0.05; study site: β = 0.52, p b 0.05; Fig. 2). The regression between blood lead concentration and the amount of red blood cells was however not significant (p = 0.994). 4. Discussion According to our expectations, metal levels in feathers of great tits, caught in study sites near a non-ferrous smelter in South-Antwerp, showed a clear metal pollution gradient. We found significant differences in feather metal concentrations for all measured metals, with the highest values closest to the pollution source. This clear pollution gradient in feathers was however not fully reflected in the blood of great tits. Our results showed that there is a clear gradient for cadmium and lead in the blood of adult great tits, with the highest levels in tits that were caught closest to the pollution source (UM and F8). Concentrations of other metals in the blood however did not differ significantly among sites. These results are comparable to earlier studies conducted in this pollution gradient (e.g. Dauwe et al., 1999, 2003; Jaspers et al., 2004; Rogival et al., 2006; Vanparys et al. 2008). A reason for the discrepancy between blood and feather metal concentrations could be that blood metal concentrations reflect the immediate (i.e. dietary) conditions, while feather concentrations are highly affected by exogenous contamination. Jaspers et al. (2004) suggested that concentrations of most metals build up with increasing age of the feather, indicating that exogenous contamination may be an important source of metals in feathers. The feather metal concentrations thus may mirror the environmental pollution, but might not accurately reflect endogenous concentrations. This is also mirrored by the non-significant correlations
F4 (n = 12) B B B B B
0.16 ± 0.04 0.51±0.09 0.19 ± 0.08 0.08 ± 0.08 9.4 ± 0.4 5.7 ± 1.1 4.1 ± 0.4 184 ± 24
B B
B C B AB B B AB
F
p
45.8 157.4 52.3 5.9 31.8 2.8 82.4 4.6
b0.001 b0.001 b0.001 0.001 b0.001 0.05 b0.001 b0.01
between blood en feather metal concentrations in our study. Blood concentrations of the essential metals cobalt, copper, nickel and zinc did not reflect feather concentrations. It is possible that the essential elements in the blood are regulated and therefore are not reflected in the concentrations in the feathers. In concordance with Vermeulen et al. (2009), we found a positive correlation between cadmium and lead levels in both blood and feathers in the present study. Cadmium and lead concentrations are very high in our study, and therefore are also probably taken up in large concentrations through the diet. This may explain the significant correlations of these non-essential metals in the present study. This is however in contrast with a study by Scheifler et al. (2006), where they did not find a significant relation between blood and feather lead levels in the common blackbird (Turdus merula). Haematological parameters described in this study are comparable to values reported earlier for great tits (Ots et al., 1998; Hauptmanova et al., 2002; Nadolski et al., 2006). Metal pollution seemed to have a negative effect on the haematological status of great tits. Great tits caught in study sites near the pollution source had a lower haemoglobin concentration, haematocrit, mean corpuscular volume and mean corpuscular haemoglobin concentration. The amount of red blood cells was however not significantly affected. These results are comparable with a study of Rogival et al. (2006) on wood mice (Apodemus sylvaticus), conducted in the same pollution gradient. A weakened haematological status can have serious implications for the fitness and breeding capacity of a bird. Low haematocrit values have been shown to reflect low body condition (Svensson and Merilä, 1996), infections with blood parasites (Booth and Elliott, 2002) and low aerobic and flight performance (Saino et al., 1997), but did not seem to affect adult survival in great tits (Kilgas et al., 2006). Bearhop et al. (1999) have shown that MCV of parental great skuas (Cattharacta skua) is negatively related with fledgling success of their offspring. Nadolski et al. (2006) however showed that MCV is positively related with fledgling success. In our study, MCV and MCH were significantly higher in F7 and F4, the least polluted study sites compared to the more polluted sites UM and F8. Low MCV and MCH values are indicative for microcytic anemia (a generic term for any type of anemia characterized by small red blood cells; Iolascon et al., 2009). It is known that microcytic anemia can be caused by lead poisoning (Papanikolaou et al., 2005). This is supported by our results, which also reflect a negative effect of lead concentrations on both MCV and MCH. The present study confirms that lead concentrations are strikingly higher than assumed to cause detrimental effects (Scheuhammer,
Table 3 Results of the ANOVA, means and standard errors of haematological parameters for great tits in a pollution gradient originating from a metal smelter (n = 58).The letters (A–B) indicate significant differences (Tukey-test, p b 0.05). Letters are not shown if there are no significant differences.
RBC (106/mm3) HGB (g/dl) HCT (%) MCV (µm3) MCH (pg)
UM (n = 16)
F8 (n = 16)
F7 (n = 16)
F4 (n = 10)
F3,57
p
4.30 ± 0.09 20.39 ± 0.37 50.07 ± 0.93 116.31±0.70 47.55 ± 0.50
4.34 ± 0.07 20.28 ± 0.29 50.39 ± 0.76 116.06 ± 0.92 46.63 ± 0.51
4.53 ± 0.07 22.50 ± 0.34 54.02±0.96 119.25±1.17 49.66 ± 0.42
4.39 ± 0.14 21.20 ± 0.51 52.85±1.54 120.50 ± 0.70 50.07 ± 0.96
1.4 3.2 3.0 4.0 5.4
0.3 0.03 0.04 0.01 0.003
A A A A
A A A A
B B B B
B B B B
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Fig. 2. Relation between ln(Pb + 1) blood lead concentrations and haematological parameters, namely haemoglobin concentration (HGB), haematocrit (HCT), mean corpuscular volume (MCV) and mean corpuscular haemoglobin (MCH) with indication of study site: UM (○), F8 (●), F7 (□) and F4 (■).
1987). Moreover, the threshold value of 0.2 μg Pb/g blood (fresh weight) for sub-clinical effects in birds was exceeded in the most polluted area (UM). Inhibition of haematological enzymes, such as δ-aminolevuline acid dehydratase (ALAD), is one of the most described effects (Bergdahl, 1998; Thompson and Dowding, 1999), hampering haemoglobin production. It is therefore not surprising that we found a strong negative effect of lead on haemoglobin concentration. Haemoglobin concentrations were the lowest at the most polluted sites UM and F8, reflecting the metal pollution gradient. This is in contrast with a study of Eeva et al. (2000) where haemoglobin concentration did not depend on the distance from a metal pollution source in both great tits and pied flycatchers (Ficedula hypoleuca). In the study by Eeva et al. (2000), lead emissions seemed to be however considerably lower, which could explain the dissimilarity between the two studies. Nadolski et al. (2006) showed that haemoglobin concentration is linked to the survival of nestlings from hatching to fledging. A lower haemoglobin concentration due to metal pollution could therefore severely affect the breeding output and fitness of great tits in the pollution gradient under study. This is in accordance with findings of Janssens et al. (2003b) in the same pollution gradient, where they reported that overall breeding success was significantly lower toward the factory complex. This lowered
breeding success was caused not only by the decreased hatching success toward the pollution source but also by the significant difference in fledging success among sites (Janssens et al., 2003b). With this study we can however not conclude whether the negatively affected haematological profile of great tits directly influenced subsequent breeding output or survival. In summary, we can conclude that metal pollution, especially lead, has deleterious effects on the haematological status of adult great tits. Our results indicate that the haematological status of great tits is negatively affected by metal pollution and may therefore be used as a successful biomarker for monitoring the negative impact of metal exposure in the wild. Concerning the vast amount of studies that report low fitness and survival caused by metal pollution (e.g. Scheuhammer, 1987; Janssens et al., 2003b) and studies that relate haematological status to condition and survival (e.g. Bearhop et al., 1999; Kilgas et al., 2006), it is possible that some of the detrimental results of metal pollution are partially caused by negatively affected haematological status. Acknowledgements We would like to thank Irina Komjarova and Valentine Mubiana for their help with the metal measurements. We would also like to
A. Geens et al. / Science of the Total Environment 408 (2010) 1174–1179
thank Veerle Jaspers for her help with the statistical analysis of the data. This study was supported by an I.W.T.- and an F.W.O.-grant to A.G., an F.W.O.-postdoctoral grant to T.D. and by the University of Antwerp (NOI-BOF UA-2006). M.E. is supported by the University of Antwerp and FWO-Flanders. The study was conducted in full compliance with Belgian laws and regulations. References Bearhop S, Griffiths R, Orr K, Furness RW. Mean corpuscular volume (MCV) as a measure of condition in birds. Ecol Lett 1999;2:352–6. Bergdahl IA. Lead-binding proteins — a way to understand lead toxicity? Analusis 1998;26:81–4. Blust R, Van der Linden A, Verheyen E, Decleir W. Evaluation of microwave heating digestion and graphite furnace atomic absorption spectrometry with continuum source background correction for the determination of iron, copper and cadmium in brine shrimp. J Anal At Spectrom 1988;3:387–93. Booth CE, Elliott PF. Hematological responses to hematozoa in North American and neotropical songbirds. Comp Biochem Physiol A 2002;133:451–67. Bowerman WW, Stickle JE, Sikarskie JG, Giesy JP. Hematology and serum chemistries of nestling bald eagles (Haliaeetus leucocephalus) in the lower peninsula of MI, USA. Chemosphere 2000;41:1575–9. Burger J. Metals in avian feathers: bioindicators of environmental pollution. Rev Environ Toxicol 1993;5:203–311. Burger J, Gochfeld M. Effects of lead on growth in young herring gulls (Larus argentatus). J Toxicol Environ Health 1988;2:227–36. Dauwe T, Bervoets L, Blust R, Pinxten R, Eens M. Are eggshells and egg contents of Great and Blue Tits suitable as indicators of heavy metal pollution? Belg J Zool 1999;129:439–47. Dauwe T, Bervoets L, Pinxten R, Blust R, Eens M. Variation of heavy metals within and among feathers of birds of prey: effects of molt and external contamination. Environ Pollut 2003;124:429–36. Dauwe T, Janssens E, Eens M. Effects of heavy metal exposure on the condition and health of adult great tits (Parus major). Environ Pollut 2006;140:71–8. Dauwe T, Eens M. Melanin- and carotenoid-dependent signals of great tits (Parus major) relate differently to metal pollution. Naturwissenschaften 2008;95:969–73. Eens M, Pinxten R, Verheyen RF, Blust R, Bervoets L. Great and blue tits as indicators of heavy metal contamination in terrestrial ecosystems. Ecotoxicol Environ Saf 1999;44:81–5. Eeva T, Tanhuanpaa S, Rabergh C, Airaksinen S, Nikinmaa M, Lehikoinen E. Biomarkers and fluctuating asymmetry as indicators of pollution-induced stress in two holenesting passerines. Funct Ecol 2000;14:235–43. Eeva T, Lehikoinen E. Growth and mortality of nestling great tits (Parus major) and pied flycatchers (Ficedula hypoleuca) in a heavy metal pollution gradient. Oecologia 1996;108:631–9. Furness RW. Birds as monitors of pollutants. In: Furness RW, Greenwood JJD, editors. Birds as monitors of environmental change. London, England: Chapman & Hall; 1993. p. 86-131. Geens A, Dauwe T, Eens M. Does anthropogenic metal pollution affect carotenoid colouration, antioxidative capacity and physiological condition of great tits (Parus major)? Comp Biochem Physiol C 2009;150:155–63. Gochfeld M, Belant JL, Shukla T, Benson T, Burger J. Heavy metals in laughing gulls: gender, age and tissue differences. Environ Toxicol Chem 1996;15:2275–83. Gorissen L, Snoeijs T, Van Duyse E, Eens M. Heavy metal pollution affects dawn singing behaviour in a small passerine bird. Oecologia 2005;145:504–9. Hauptmanova K, Literak I, Bartova E. Haematology and leucocytozoonosis of great tits (Parus major L.) during winter. Acta Vet (Brno) 2002;71:199–204. Iolascon A, De Falco L, Beaumont C. Molecular basis of inherited microcytic anemia due to defects in iron acquisition or heme synthesis. Haematologica 2009;94:395–408. Janssens E, Dauwe T, Bervoets L, Eens M. Heavy metals and selenium in feathers of great tits (Parus major) along a pollution gradient. Environ Toxicol Chem 2001;20:2815–20.
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Janssens E, Dauwe T, Van Duyse E, Beernaert J, Pinxten R, Eens M. Effects of heavy metal exposure on aggressive behavior in a small territorial songbird. Arch Environ Contam Toxicol 2003a;45:121–7. Janssens E, Dauwe T, Pinxten R, Eens M. Breeding performance of great tits (Parus major) along a gradient of heavy metal pollution. Environ Toxicol Chem 2003b;22:1140–5. Jaspers V, Dauwe T, Pinxten R, Bervoets L, Blust R, Eens M. The importance of exogenous contamination on heavy metal levels in bird feathers. A field experiment with freeliving great tits, Parus major. J Environ Monit 2004;6:356–60. Kilgas P, Tilgar V, Mand R. Hematological health state indices predict local survival in a small passerine bird, the great tit (Parus major). Physiol Biochem Zool 2006;79:565–72. Nadolski J, Skwarska J, Kalinski A, Banbura M, Sniegula R, Banbura J. Blood parameters as consistent predictors of nestling performance in great tits (Parus major) in the wild. Comp Biochem Physiol A 2006;143:50–4. Nyholm NEI. Influence of heavy metal exposure during different phases of the ontogeny on the development of pied flycatchers, Ficedula hypoleuca, in natural populations. Arch Environ Contam Toxicol 1998;35:632–7. Ots I, Murumagi A, Hõrak P. Haematological health state indices of reproducing great tits: methodology and sources of natural variation. Funct Ecol 1998;12:700–7. Papanikolaou NC, Hatzidaki EG, Belivanis S, Tzanakakis GN, Tsatsakis AM. Lead toxicity update. A brief review. Med Sci Monit 2005;11:RA329-36. Peakall D. Animal biomarkers as pollution indicators. London, UK: Chapman & Hall; 1992. 320 pp. Rogival D, Scheirs J, De Coen W, Verhagen R, Blust R. Metal blood levels and hematological characteristics in wood mice (Apodemus sylvaticus L.) along a metal pollution gradient. Environ Toxicol Chem 2006;25:149–57. Saino N, Cuervo JJ, Krivacek M, de Lope F, Møller AP. Experimental manipulation of tail ornament size affects the hematocrit of male barn swallows (Hirundo rustica). Oecologia 1997;110:186–90. Scheuhammer AM. The chronic toxicity of aluminium, cadmium, mercury and lead in birds — a review. Environ Pollut 1987;45:263–95. Scheifler R, Coeurdassier M, Morilhat C, Bernard N, Faivre B, Flicoteaux P, et al. Lead concentrations in feathers and blood of common blackbirds (Turdus merula) and in earthworms inhabiting unpolluted and moderately polluted urban areas. Sci Total Environ 2006;371:197–205. Snoeijs T, Dauwe T, Pinxten R, Vandesande F, Eens M. Heavy metal exposure affects the humoral immune response in a free-living small songbird, the great tit (Parus major). Arch Environ Contam Toxicol 2004;46:399–404. Svensson E, Merilä J. Molt and migratory condition in blue tits: a serological study. Condor 1996;98:825–31. Takekawa JY, Wainwright-De La Cruz SE, Hothem RL, Yee J. Relating body condition to inorganic contaminant concentrations of diving ducks wintering in coastal California. Arch Environ Contam Toxicol 2002;42:60–70. Thompson DR, Dowding JE. Site-specific heavy metal concentrations in blood of South Island pied oystercatchers Haematopus ostralegus finschi from the Auckland Region. New Zealand Mar Pollut Bull 1999;38:202–6. Tinbergen JM, Boerlijst MC. Nestling weight and survival in individual great tits (Parus major). J Anim Ecol 1990;59:1113–27. Vanparys C, Dauwe T, Van Campenhout K, Bervoets L, De Coen W, Blust R, et al. Metallothioneins (MTs) and δ-aminolevulinic acid dehydratase (ALAd) as biomarkers of metal pollution in great tits (Parus major) along a pollution gradient. Sci Total Environ 2008;401:184–93. Vermeulen F, D'Havé H, Mubiana VK, Van den Brink NW, Blust R, Bervoets L, et al. Relevance of hair and spines of the European hedgehog (Erinaceus europaeus) as biomonitoring tissues for arsenic and metals in relation to blood. Sci Total Environ 2009;407:1775–83. VMM. Verspreiding van zware metalen. Achtergronddocument, MIRA milieurapport Vlaanderen 2007. Vlaamse Milieumaatschappij, Mechelen, Belgium, 2007 (in Dutch). Weeks BA, Anderson DP, DuFour AP, Fairbrother A, Goven AJ, Lahvis GP, et al. Immunological biomarkers to assess environmental stress. Biomarkers: biochemical, physiological, and histological markers of anthropogenic stress. In: Huggett RJ, Kimerle RA, Mehrle Jr PM, Bergman HL, editors. SETAC Special Publication Series. Boca Raton, FL, USA: Lewis; 1992. p. 211–34.
Contents lists available at ScienceDirect
Science of the Total Environment j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / s c i t o t e n v
Haematological status of wintering great tits (Parus major) along a metal pollution gradient Ann Geens a,⁎, Tom Dauwe a,c, Lieven Bervoets b, Ronny Blust b, Marcel Eens a a b c
Department of Biology, University of Antwerp, Ethology, Universiteitsplein 1, B-2610 Antwerp, Belgium Department of Biology, University of Antwerp, Ecophysiology, Biochemistry and Toxicology, Groenenborgerlaan 171, B-2020 Antwerp, Belgium VITO, Boeretang 200, B-2400 Mol, Belgium
a r t i c l e
i n f o
Article history: Received 3 August 2009 Received in revised form 13 November 2009 Accepted 16 November 2009 Available online 2 December 2009 Keywords: Metal pollution Parus major Haematology Blood Biomarker Biomonitoring
a b s t r a c t In the long-term biomonitoring of wild populations inhabiting polluted areas, the use of non-destructive biomarkers as markers of condition is very important. We examined the possible effects of metal pollution on the haematological status of adult great tits (Parus major) along a well-established pollution gradient near a non-ferrous smelter in Belgium. We measured blood and feather metal concentrations and assessed the haematological status (amount of red blood cells, haemoglobin concentration, haematocrit, mean corpuscular volume and mean corpuscular haemoglobin) of adult great tits during winter at four study sites. Metal concentrations in blood and feathers indicated that cadmium and lead were the most important metals in the pollution gradient under study. Measurements of haematological parameters revealed that haemoglobin concentration, haematocrit, mean corpuscular volume and mean corpuscular haemoglobin were lower in great tits from the more polluted sites. These parameters were significantly negatively correlated with blood lead concentration. The amount of red blood cells, however, did not significantly differ among study sites. Our results indicate that the haematological status of great tits is negatively affected by metal pollution and may therefore be used as a successful biomarker for monitoring the negative impact of metal exposure in the wild. © 2009 Elsevier B.V. All rights reserved.
1. Introduction Excessive deposition of metals in the environment and the resulting pollution is a well known problem in several areas around the world. Monitoring this pollution and assessing its effect on organisms is therefore an important issue. It has become important to look for organisms which can be used as biological indicators or monitors of those pollutants. The relevance of birds as biomonitors, especially for metal pollution, has often been emphasized (Burger, 1993; Furness, 1993). Several studies have successfully used bird eggs, feathers or other tissues to examine metal pollution (review see Burger, 1993). Although measuring metal concentrations in bird tissues alone is very useful, it may not be sufficient. Metal concentrations alone do not give any information about the biological stress caused by pollution. Therefore it is also necessary to look for meaningful biomarkers to assess the health state of organisms in relation to environmental pollution (Peakall, 1992). Special attention is given to the application of non-destructive biomarkers, such as morphometric measures and haematological characteristics, which may reflect an impact on the condition of the exposed animals. Body
⁎ Corresponding author. Tel.: +32 3 2652347; fax: +32 3 2652271. E-mail address: [email protected] (A. Geens). 0048-9697/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.scitotenv.2009.11.029
mass, tarsus and wing length reflect the condition of birds and are also indicative of survival and reproductive success (Tinbergen and Boerlijst, 1990). Several studies reported negative effects of metals (such as cadmium, copper, lead, mercury, nickel and selenium) on the growth and body weight of birds, affecting the bird's condition (Burger and Gochfeld, 1988; Eeva and Lehikoinen, 1996; Takekawa et al., 2002). Changes in haematology can act as sensitive, early warning signals of the possible toxic effects of metals on health and physiological status (Weeks et al., 1992). Haematological parameters are therefore widely used as indicators of condition (Bowerman et al., 2000; Dauwe et al., 2006; Rogival et al., 2006). The amount of red blood cells, haemoglobin concentration, haematocrit and red blood cell indices are indicative for the oxygen transport capacity of the blood (Ots et al., 1998). Metals such as cadmium and lead are also known to cause anemia, which might be reflected as lowered haematocrit values, lower haemoglobin concentrations and smaller mean corpuscular volume (Nyholm, 1998; Iolascon et al., 2009). Moreover, lead directly influences haemoglobin production through inhibition of the enzyme δ-aminolevuline acid dehydratase (ALAD; Bergdahl, 1998; Papanikolaou et al., 2005), which catalyzes the second step in the porphyrin and haem biosynthetic pathway. Zinc, which plays an essential role in the functioning of this enzyme is replaced by lead, which causes malfunction of the enzyme. ALAD has been used successfully as a biomarker for metal pollution in birds (Vanparys et al., 2008).
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In this study, we examined the effects of metal pollution on the condition and health of adult great tits (Parus major) in four study sites located in a well known pollution gradient emanating from a non-ferrous smelter near Antwerp, Belgium. Previous research in this pollution gradient reported that levels of metals in the feathers of great tits from the site closest to the pollution source are among the highest reported in literature (Janssens et al., 2001). Levels of lead and cadmium in juvenile feathers and eggs of great and blue tits (Cyanistes caeruleus) from this site were very high for passerine species (Dauwe et al., 1999) and are strikingly higher than concentrations assumed to cause detrimental effects (Scheuhammer, 1987). This poses a serious strain on the surrounding natural environment and the organisms that live there. Previous research in this pollution gradient reported negative effects of metal pollution on biochemical markers (Vanparys et al., 2008), immunocompetence (Snoeijs et al., 2004), behaviour (Janssens et al., 2003a; Gorissen et al., 2005), colouration (Dauwe and Eens, 2008; Geens et al., 2009) and reproductive success of great tits (Janssens et al., 2003b). Our main goal was to compare both morphometric (body weight, tarsus and wing length) and haematological parameters along the pollution gradient. Metal concentrations in blood were determined as an indicator of the internal metal levels. We also measured metal concentrations in tail feathers. Metal concentrations in feathers may, however, change and increase with the age of the feather due to exogenous contamination onto the feather surface by atmospheric depositions and/or from secretion products of the uropygial gland smeared onto the feathers during preening (Dauwe et al., 2003; Jaspers et al., 2004). Haematological characteristics, such as amount of red blood cells, haemoglobin concentration, haematocrit and red blood cell characteristics (mean corpuscular volume and mean corpuscular haemoglobin), were measured to evaluate the impact of metal pollution on haematological status. The haematological status is important for the performance and survival of the bird (Kilgas et al., 2006; Nadolski et al., 2006). Haematological parameters have already been used as biomarkers for biologically active metal concentrations in organisms. Because of their fast response to metal pollution, these markers can be used to scan for toxic effects in an early stage, for example in humans (Papanikolaou et al., 2005) and mice (Rogival et al., 2006).
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Antwerp. Pollution originates from uncontrolled emissions from dust of ore piles, which is deposited in close proximity of the smelter. Lead, cadmium, arsenic, copper and zinc are especially common pollutants in this area and they form an exponentially decreasing pollution gradient away from the factory complex (Janssens et al., 2001). In 2005, mean values of lead and cadmium in PM10-dust fraction ranged from respectively 35–381 ng/m3 and 2–7 ng/m3 in the area surrounding the smelter and were among the highest values measured in Belgium and surrounding European countries (VMM, 2007). Our study sites are located eastwards at different distances from the smelter, namely UM (0–350 m), F8 (400–600 m), F7 (2500 m) and F4 (8500 m; Fig. 1). These sites have been used for research on great tits since 1999 (Dauwe et al., 1999) so there is a well-established population of great tits, occupying 30–50 nest boxes in every study site. Special attention was paid in selecting study sites with a similar habitat type (deciduous park sites). 2.2. Data sampling Between 15th of November and 1st of December 2006, 69 great tit adults (45 males and 24 females) were caught while sleeping in a nest box. Captured birds were sexed and aged (first-year versus older birds) and marked with individually numbered metal rings. All birds were weighed with a precision of 0.1 g, using a digital balance (Kern 466-41) and the tarsus length was measured to the nearest 0.1 mm with a digital sliding calliper. Wing length was measured to the nearest 1 mm using a ruler. Body condition was calculated as the standardized residuals from a linear regression of body mass on tarsus length (Ots et al., 1998). We collected a blood sample (300 µl) from the brachial vein with a Microvette® CB 300 lithium-heparin capillary tube (Sarstedt AG & Co., Germany) to measure haematological parameters and blood metal concentrations. It was however not always possible to collect 300 µl, so only samples with sufficient volume were used both for haematological and metal analysis. Blood samples were immediately stored at 4 °C and haematological analysis took place within 2 h. The left and right outermost tail feathers were collected and stored in paper envelopes for determination of metal concentrations (Eens et al., 1999).
2. Methods 2.3. Haematological analysis 2.1. Study sites The present study was performed in four study sites along a pollution gradient originating from a non-ferrous smelter in the South of
We measured the amount of red blood cells (RBC in 106/mm3), haemoglobin concentration (HGB in g/dl), haematocrit (HCT in %), mean corpuscular volume of red blood cells (MCV in µm3) and mean
Fig. 1. The location of the four study sites (UM, F8, F7 and F4) along a heavy metal pollution gradient originating from a large non-ferrous metal smelter in the south of Antwerp.
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corpuscular haemoglobin per red blood cell (MCH in pg), using an Horiba ABX Micros 60 haematology analyzer (Horiba ABX, Montpellier, France). Because of the limited blood sample volume, we could only measure haematological parameters for 58 birds. Reproducibility (runto-run precision) of the measurements is certified by measuring a control (provided by Horiba ABX) with known concentrations each run. Repeatability (within-run precision) of the measurements is ensured because the ABX Micros 60 measures every sample for a maximum of three times. Results are only accepted if two out of three counts are within the systems precision limits for that specific parameter.
were not included in the statistical analysis because concentrations were below the detection limit of the ICP-MS. The relation between blood and feather metal concentrations was tested with a Pearson correlation. To test the relation between blood metal concentrations and haematological parameters, we used linear regressions, corrected for the effect of study site. We assessed which metals in blood samples differed significantly among study sites. As will follow, this was the case for cadmium and lead. Subsequently, we only calculated the relation between haematological parameters and these metals. All values given are arithmetic means ± standard errors (SE).
2.4. Metal analysis
3. Results
Feathers were washed two times, both in deionised water and acetone (1 mol l− 1) to remove loosely adherent external contamination (Gochfeld et al., 1996). All feather samples were then put individually in 4 ml polypropylene, metal free vials and dried in an oven at 60 °C for 24 h. Dry weight was determined on a Mettler AT 261 Deltarange balance to the nearest 0.01 mg. Blood samples were stored in 1.5 ml polypropylene, metal free vials., The fresh weight of the remaining blood after haematological analysis was determined. Blood samples were then dried in an oven at 60 °C and after 24 h dry weight was also measured. Subsequently, feather and blood samples were digested prior to metal analysis following the microwave heating digestion described in Blust et al. (1988). We added a 1:1 mixture of 100 μl HNO3 (70%) and H2O2 (30%) per 10 μg dry sample, followed by repeated microwave heating. After digestion, samples were diluted with 2 ml ultrapure, deionized water (MilliQ, Millipore) and stored at −20 °C until metal analysis. We measured silver (Ag), arsenic (As), cadmium (Cd), copper (Cu), cobalt (Co), nickel (Ni), lead (Pb) and zinc (Zn) levels in the samples with an axial Inductively Coupled Plasma-Mass Spectrophotometer (ICP-MS; Varian Inc., Palo Alto, USA). Blanks and certified BCR-reference material (VMK 102, Bureau of Certified References) were added to each batch of samples as quality control. Recovered concentrations of the certified samples were within 10% of the certified values, which is an acceptable margin. Metal concentrations were expressed as μg/g on a fresh weight basis.
3.1. Metal concentrations in blood and feathers
2.5. Statistical analyses We used SPSS 15.0 for Windows (SPSS Inc., Chicago, Illinois, USA) and XLSTAT Version 2009.1.02 (Addinsoft, New York, USA), to perform statistical analysis. Outliers in the data (data points that are minimum three standard deviations larger than the mean) were removed prior to analyses. A significance level of 0.05 was chosen for all statistical tests. Normality of the data was tested with a Shapiro– Wilk test (p b 0.05). Data of metal concentrations was not normally distributed, so data was normalised using a ln(x + 1) transformation. Blood and feather metal concentrations and haematological parameters were compared among study sites using general linear mixed models, with study site, sex and age as fixed parameters and body condition as a covariate. Significant differences were tested post hoc with a Tukey HST test. Ag and As concentrations in blood samples
We tested for significant differences in mean feather and blood metal concentrations among study sites. Mean blood and feather metal concentrations per study site and the results of the ANOVA and Tukey HST tests are reported in Tables 1 and 2. In feathers, all metals differed significantly among study sites, with the highest concentrations measured in the sites closest to the pollution source (UM and F8). Blood metal concentrations differed only among study sites for cadmium and lead, with the highest concentrations also in UM and F8. Sex, age, body condition did not significantly affect blood or feather metal concentrations (F b 2.7, p N 0.3 in all cases). We also examined the correlations between metal levels in blood and feathers. There was both a significant positive correlation between Pb (r = 0.76, p b 0.001) and Cd (r = 0.37, p b 0.01) levels in blood and feathers of great tits. For all other measured metals, there were no significant correlations between the metal concentrations of blood and feathers (all p N 0.1). 3.2. Morphometric and haematological parameters Male great tits had significantly longer tarsi (males: 20.38 mm± 0.07; females: 19.82 mm± 0.15; F1,66 = 15.3, p b 0.001, n = 69) and wings (males: 73 mm± 1; females: 70 mm± 1; F1,66 = 22.3, p b 0.001, n = 69) and were heavier (males: 17.0 g ± 0.1; females: 15.8 g ± 0.2; F1,66 = 33.8, p b 0.001, n = 69) than females. Males also had a higher body condition compared to females (males: 0.23 ± 0.11; females: − 0.43± 0.14; F1,66 = 12.6, p = 0.001, n = 69). There were no significant differences for tarsus, wing length, body mass and body condition between age groups or among sites (F b 1.436, p N 0.1, n = 69 in all cases). Sex and age never had a significant effect on the measured haematological parameters (F b 1.9, p N 0.2, n = 58 in all cases). The amount of red blood cells (RBC) did not differ significantly among study sites (F3,57 = 1.4, p = 0.3; Table 3). Great tits from UM and F8 however did have a significant lower haemoglobin concentration compared to great tits from F7 and F4 (F3,57 = 3.2, p = 0.03, Tukey HST test p b 0.05; Table 3). Haematocrit levels were also significantly lower in UM and F8 compared to F7 and F4 (F3,57 = 3.0, p = 0.04, Tukey HST test p b 0.05; Table 3). Mean cell volume and mean cell haemoglobin concentration were both significantly higher in the least polluted sites F7 and F4
Table 1 Mean metal concentration (µg/g fresh weight±SE; n =57) and results of the one-way ANOVA for blood of great tits in a metal pollution gradient. The letters (A–B) indicate significant differences (Tukey-test, pb 0.05). Letters are not shown if there are no significant differences. UM (n = 16) Cd Co Cu Ni Pb Zn
0.016 ± 0.003 0.35 ± 0.08 0.13 ± 0.02 0.11 ± 0.03 0.28 ± 0.02 5.5 ± 0.5
F8 (n = 15) A
A
0.011 ± 0.002 0.25 ± 0.05 0.09 ± 0.02 0.14 ± 0.03 0.17 ± 0.02 6.9 ± 0.5
F7 (n = 16) A
A
0.007 ± 0.001 0.25 ± 0.04 0.20 ± 0.03 0.13 ± 0.05 0.03 ± 0.01 7.9 ± 0.7
F4 (n = 10) B
B
0.007 ± 0.001 0.23 ± 0.07 0.13 ± 0.03 0.18 ± 0.03 0.02 ± 0.02 6.9 ± 0.7
B
B
F
p
4.4 0.6 0.3 4.1 37.1 1.2
b0.01 0.6 0.8 0.1 b0.001 0.3
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Table 2 Mean metal concentration (µg/g fresh weight±SE; n= 69) and results of the one-way ANOVA for feathers of great tits in a metal pollution gradient. The letters (A–B) indicate significant differences (Tukey-test, pb 0.05). Letters are not shown if there are no significant differences. UM (n = 18) Ag As Cd Co Cu Ni Pb Zn
3.9 ± 0.5 31 ± 3 11 ± 3 0.27 ± 0.05 37 ± 4 13.0 ± 3.0 140 ± 18 240 ± 26
F8 (n = 17) A A A A A A A
2.6 ± 0.5 21 ± 3 17 ± 6 0.25 ± 0.07 36.5 ± 5.0 14.0 ± 6.0 110 ± 19 216 ± 25
F7 (n = 22) A A A A A
0.11 ± 0.02 2.6 ± 0.2 0.39 ± 0.04 0.02 ± 0.01 9.8 ± 0.9 7.2 ± 2.2 8.1 ± 1.3 142 ± 13
A A
compared to the other two sites UM and F8 (MCV: F3,57 = 4.0, p = 0.01; Tukey HST test p b 0.02; MCH: F3,57 = 5.4, p = 0.003, Tukey HST test p b 0.03; Table 3). 3.3. Relation between metal pollution and haematological parameters There were no significant relations between blood cadmium concentration and haematological parameters (p N 0.09 in all cases). We however did find negative relations between blood lead concentrations and haemoglobin concentration (lead: β = −0.56, p b 0.05; study site: β = 0.58, p b 0.05), haematocrit (lead: β = −0.37, p b 0.01; study site: β = 0.42, p b 0.05), mean cell volume (lead: β = −0.62, p b 0.05; study site: β = 0.63, p b 0.01) and mean cell haematocrit (β = −0.31, p b 0.05; study site: β = 0.52, p b 0.05; Fig. 2). The regression between blood lead concentration and the amount of red blood cells was however not significant (p = 0.994). 4. Discussion According to our expectations, metal levels in feathers of great tits, caught in study sites near a non-ferrous smelter in South-Antwerp, showed a clear metal pollution gradient. We found significant differences in feather metal concentrations for all measured metals, with the highest values closest to the pollution source. This clear pollution gradient in feathers was however not fully reflected in the blood of great tits. Our results showed that there is a clear gradient for cadmium and lead in the blood of adult great tits, with the highest levels in tits that were caught closest to the pollution source (UM and F8). Concentrations of other metals in the blood however did not differ significantly among sites. These results are comparable to earlier studies conducted in this pollution gradient (e.g. Dauwe et al., 1999, 2003; Jaspers et al., 2004; Rogival et al., 2006; Vanparys et al. 2008). A reason for the discrepancy between blood and feather metal concentrations could be that blood metal concentrations reflect the immediate (i.e. dietary) conditions, while feather concentrations are highly affected by exogenous contamination. Jaspers et al. (2004) suggested that concentrations of most metals build up with increasing age of the feather, indicating that exogenous contamination may be an important source of metals in feathers. The feather metal concentrations thus may mirror the environmental pollution, but might not accurately reflect endogenous concentrations. This is also mirrored by the non-significant correlations
F4 (n = 12) B B B B B
0.16 ± 0.04 0.51±0.09 0.19 ± 0.08 0.08 ± 0.08 9.4 ± 0.4 5.7 ± 1.1 4.1 ± 0.4 184 ± 24
B B
B C B AB B B AB
F
p
45.8 157.4 52.3 5.9 31.8 2.8 82.4 4.6
b0.001 b0.001 b0.001 0.001 b0.001 0.05 b0.001 b0.01
between blood en feather metal concentrations in our study. Blood concentrations of the essential metals cobalt, copper, nickel and zinc did not reflect feather concentrations. It is possible that the essential elements in the blood are regulated and therefore are not reflected in the concentrations in the feathers. In concordance with Vermeulen et al. (2009), we found a positive correlation between cadmium and lead levels in both blood and feathers in the present study. Cadmium and lead concentrations are very high in our study, and therefore are also probably taken up in large concentrations through the diet. This may explain the significant correlations of these non-essential metals in the present study. This is however in contrast with a study by Scheifler et al. (2006), where they did not find a significant relation between blood and feather lead levels in the common blackbird (Turdus merula). Haematological parameters described in this study are comparable to values reported earlier for great tits (Ots et al., 1998; Hauptmanova et al., 2002; Nadolski et al., 2006). Metal pollution seemed to have a negative effect on the haematological status of great tits. Great tits caught in study sites near the pollution source had a lower haemoglobin concentration, haematocrit, mean corpuscular volume and mean corpuscular haemoglobin concentration. The amount of red blood cells was however not significantly affected. These results are comparable with a study of Rogival et al. (2006) on wood mice (Apodemus sylvaticus), conducted in the same pollution gradient. A weakened haematological status can have serious implications for the fitness and breeding capacity of a bird. Low haematocrit values have been shown to reflect low body condition (Svensson and Merilä, 1996), infections with blood parasites (Booth and Elliott, 2002) and low aerobic and flight performance (Saino et al., 1997), but did not seem to affect adult survival in great tits (Kilgas et al., 2006). Bearhop et al. (1999) have shown that MCV of parental great skuas (Cattharacta skua) is negatively related with fledgling success of their offspring. Nadolski et al. (2006) however showed that MCV is positively related with fledgling success. In our study, MCV and MCH were significantly higher in F7 and F4, the least polluted study sites compared to the more polluted sites UM and F8. Low MCV and MCH values are indicative for microcytic anemia (a generic term for any type of anemia characterized by small red blood cells; Iolascon et al., 2009). It is known that microcytic anemia can be caused by lead poisoning (Papanikolaou et al., 2005). This is supported by our results, which also reflect a negative effect of lead concentrations on both MCV and MCH. The present study confirms that lead concentrations are strikingly higher than assumed to cause detrimental effects (Scheuhammer,
Table 3 Results of the ANOVA, means and standard errors of haematological parameters for great tits in a pollution gradient originating from a metal smelter (n = 58).The letters (A–B) indicate significant differences (Tukey-test, p b 0.05). Letters are not shown if there are no significant differences.
RBC (106/mm3) HGB (g/dl) HCT (%) MCV (µm3) MCH (pg)
UM (n = 16)
F8 (n = 16)
F7 (n = 16)
F4 (n = 10)
F3,57
p
4.30 ± 0.09 20.39 ± 0.37 50.07 ± 0.93 116.31±0.70 47.55 ± 0.50
4.34 ± 0.07 20.28 ± 0.29 50.39 ± 0.76 116.06 ± 0.92 46.63 ± 0.51
4.53 ± 0.07 22.50 ± 0.34 54.02±0.96 119.25±1.17 49.66 ± 0.42
4.39 ± 0.14 21.20 ± 0.51 52.85±1.54 120.50 ± 0.70 50.07 ± 0.96
1.4 3.2 3.0 4.0 5.4
0.3 0.03 0.04 0.01 0.003
A A A A
A A A A
B B B B
B B B B
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Fig. 2. Relation between ln(Pb + 1) blood lead concentrations and haematological parameters, namely haemoglobin concentration (HGB), haematocrit (HCT), mean corpuscular volume (MCV) and mean corpuscular haemoglobin (MCH) with indication of study site: UM (○), F8 (●), F7 (□) and F4 (■).
1987). Moreover, the threshold value of 0.2 μg Pb/g blood (fresh weight) for sub-clinical effects in birds was exceeded in the most polluted area (UM). Inhibition of haematological enzymes, such as δ-aminolevuline acid dehydratase (ALAD), is one of the most described effects (Bergdahl, 1998; Thompson and Dowding, 1999), hampering haemoglobin production. It is therefore not surprising that we found a strong negative effect of lead on haemoglobin concentration. Haemoglobin concentrations were the lowest at the most polluted sites UM and F8, reflecting the metal pollution gradient. This is in contrast with a study of Eeva et al. (2000) where haemoglobin concentration did not depend on the distance from a metal pollution source in both great tits and pied flycatchers (Ficedula hypoleuca). In the study by Eeva et al. (2000), lead emissions seemed to be however considerably lower, which could explain the dissimilarity between the two studies. Nadolski et al. (2006) showed that haemoglobin concentration is linked to the survival of nestlings from hatching to fledging. A lower haemoglobin concentration due to metal pollution could therefore severely affect the breeding output and fitness of great tits in the pollution gradient under study. This is in accordance with findings of Janssens et al. (2003b) in the same pollution gradient, where they reported that overall breeding success was significantly lower toward the factory complex. This lowered
breeding success was caused not only by the decreased hatching success toward the pollution source but also by the significant difference in fledging success among sites (Janssens et al., 2003b). With this study we can however not conclude whether the negatively affected haematological profile of great tits directly influenced subsequent breeding output or survival. In summary, we can conclude that metal pollution, especially lead, has deleterious effects on the haematological status of adult great tits. Our results indicate that the haematological status of great tits is negatively affected by metal pollution and may therefore be used as a successful biomarker for monitoring the negative impact of metal exposure in the wild. Concerning the vast amount of studies that report low fitness and survival caused by metal pollution (e.g. Scheuhammer, 1987; Janssens et al., 2003b) and studies that relate haematological status to condition and survival (e.g. Bearhop et al., 1999; Kilgas et al., 2006), it is possible that some of the detrimental results of metal pollution are partially caused by negatively affected haematological status. Acknowledgements We would like to thank Irina Komjarova and Valentine Mubiana for their help with the metal measurements. We would also like to
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