Abstract
Seabirds, as long-lived top predators, accumulate contaminants such as mercury (Hg), an established endocrine disruptor. In long lived species hormonal secretion varies with age; therefore, Hg-induced endocrine disruption may be exacerbated in some age classes. Here we investigated relationships between blood total Hg and luteinizing hormone (LH, a key pituitary hormone for the onset of breeding), in pre-laying known-age (11–45 years old) snow petrels (Pagodroma nivea) from Adélie Land, Antarctica. We predicted that 1) blood Hg would increase with advancing age as a consequence of bio-accumulation; and that 2) increasing blood Hg would be related to decreased concentrations of LH in the most Hg-contaminated individuals. Hg concentrations were higher in females than in males (p<0.001), and contrary to our prediction, decreased with advancing age in males (p = 0.009) and tended to do so in females (p = 0.06). The analysis of stable isotopes (δ13C and δ15N) suggested that this unexpected pattern could originate from age and sex-related variations in trophic niche, and hence Hg exposure. Regarding LH, our prediction was only supported in young birds (≤23 years) where baseline LH was inversely correlated with Hg concentrations (p = 0.04). Hg burden did not predict baseline LH or GnRH-induced LH in birds that were more than 23 years old. These results show that age and contaminants may interfere with major endocrine mechanisms and, together with other recent studies, support the view that Hg could be connected to LH secretion and could then impair the fitness of long-lived birds.
Introduction
Mercury (Hg) is a ubiquitous contaminant, present in aquatic biota with elevated concentrations in fish, some mammals and seabirds [1], [2]. Diet is the principal route of contamination: Hg bio-accumulates into individuals [3], [4], [5], [6] and bio-magnifies along the food web [7], [8]. Seabirds are top predators which often bear elevated levels of Hg, and are thus considered good bio-monitors to describe Hg bio-accumulation and bio-magnification in the marine environment [9]. Seabirds are also long-lived organisms, and therefore would accumulate Hg in their tissues over a long life-span [10]. Although it has been well established that seabird nestlings show lower Hg concentrations than adults [11], very few studies have examined the influence of age on Hg contamination in adults and the patterns are not clear [12], [13], [14], [15], [16]. In this study, we report the results of a cross-sectional study on known-age adult snow petrels Pagodroma nivea, a small (≈400 g) but very long-lived Antarctic seabird (≈50 years) [17]. We made use of an exceptional long-term banding study (1964- to present, [17]) to identify the age of each bird and measured blood total Hg concentrations. Blood Hg concentrations reflect dietary exposure over the last several weeks and also a complex equilibrium between ingestion, deposition and mobilization [10], [18], [19]. In seabirds, blood Hg is strongly correlated to Hg concentrations in storage organs [20], [21], [22]; blood Hg is thus considered as a good proxy of overall Hg burden. Given the ability of Hg to bio-accumulate we would expect blood Hg concentrations to be positively related to age in adult snow petrels. As mentioned previously, diet is the principal route of Hg contamination and to further interpret the possible Hg/age relationship, we used the isotopic niche as a proxy of the trophic niche, with δ13C and δ15N values indicating the birds’ foraging habitats and trophic position, respectively [23]. Indeed this possible Hg/age relationship could originate from an age-related change in trophic niche. Snow petrels forage in close association with ice-pack and during summer they mainly feed their chicks with fish (up to 95% of the preys [24]). To our knowledge no studies have described the trophic niche of snow petrels during the inter-breeding period, and there is no evidence of age and/or sex related trophic niche segregation.
Taking age into consideration is crucial when considering the consequences of Hg contamination. Indeed, several studies on vertebrates have reported breeding impairment from Hg including suppression of reproduction, reduced clutch size, poor breeding performances or unusual courtship behavior [25], [26], [27], [28], [29]. Indeed, in its methylated form, Hg is highly toxic and is known to disrupt the reproductive endocrine system [25]. For instance, in an Arctic seabird, the black-legged kittiwake Rissa tridactyla, a recent study has reported that Hg could interfere with the secretion of luteinizing hormone (LH) [29] a major hormone for the onset of breeding [30]. In vertebrates, the onset of breeding involves the activation of the hypothalamic-pituitary-gonadal axis (hereafter HPG axis): increasing day length activates the expression of a neuro-hormone, the Gonadotropin Releasing Hormone (GnRH) which triggers the secretion of LH from the pituitary gland. LH, in concert with follicle-stimulating hormone (FSH), promotes gonadal maturation, sex steroid secretion and in turn, sexual behaviors [30]. In black-legged kittiwakes plasma baseline LH concentrations of non-breeding males were negatively correlated to blood Hg concentrations [29]. By using the injection of exogenous GnRH, a common and powerful method to test the functionality of the pituitary through its ability to release LH [31], [32], [33], the authors suggested that Hg contamination may disrupt GnRH secretion from the hypothalamus in black-legged kittiwakes [29]. The effect of Hg on LH secretion is supported by experimental investigations: Hg-fed male rats had decreased concentrations of LH and testosterone [34]. LH secretion could thus be a potential target for Hg. In addition LH secretion is also closely related to age across vertebrates [35] including long-lived seabirds like the snow petrel [33]. Regarding our study model, the snow petrel, we therefore predict a negative relationship between blood Hg and baseline LH in the most contaminated age class. To investigate the underlying mechanism of such possible relationship, we used a GnRH challenge to test the ability of the pituitary to release LH in relation to Hg. If GnRH-induced LH concentrations are negatively correlated to blood Hg, this would indicate that Hg affects the ability of the pituitary to properly release LH.
Materials and Methods
Ethics statement
Animals were cared for in accordance with the guidelines of the ethics committee of the Institut Polaire Français Paul Emile Victor (IPEV) that specifically approved this study (Program no. 109, H. Weimerskirch).
Capture, blood sampling and GnRH-challenge
The study was conducted on Adélie land (66°40′ S, 140°01′ E), Antarctica. Many snow petrels were of known age, because chicks have been banded each year since 1964 [17]. Twenty-nine males and 16 females, from 11 to 45 years old, were handled during the pre-laying period (i.e. the courtship and mating period, a few days after arrival to the colony), from 11 to 23 November 2008. Only one bird was captured at each nest and the sex of the birds was previously determined by molecular sexing [36]. Snow petrels were caught by hand and a first blood sample was collected from the alar vein with a syringe immediately after capture (mean ± S.D.: 3 min±5 s) to determine baseline plasma LH concentrations. Then, 40 birds were immediately injected with 0.1 ml of a GnRH solution in the second alar vein ([Gln8], Sigma Lot 121H04314). The GnRH was dissolved in a physiological solution to yield a dosage of 0.6 mg for 0.1 ml (about 1.5 mg kg−1 body mass in 1 ml of 0.9% saline solution, as validated in this species [33]). In snow petrels, a GnRH injection elicits a maximal increase of LH after 10 minutes, and this response documents the ability of the pituitary to release LH. In this species, measuring LH levels 30 minutes post-GnRH challenge can inform on an individual’s capacity to maintain elevated LH concentrations [33]. Blood samples were therefore collected from alar veins at 10 and 30 min after the GnRH injection to measure plasma LH concentrations. LH changes from 0 to 10 min post-GnRH injection [(LHt = 10 − LHt = 0)/LHt = 0] and LH changes from 10 to 30 min post-GnRH injection [(LHt = 30 − LHt = 10)/LHt = 10] were used as indicators of different individuals’ abilities to release LH. Blood samples were centrifuged and plasma (for LH assay) and red blood cells (for total Hg and stable isotopes assays) were stored at −20°C. Adults were weighted to the nearest 2 g using a spring balance and their skull length (head+bill) was measured to the nearest 0.5 mm using a caliper. In snow petrels, skull length appears to be a reliable measurement of the overall size of a bird [36] and adult scaled mass index was then calculated [37].
Hg analysis
Total Hg was measured as described in [38] from freeze-dried and powdered red blood cells (hereafter called blood) in an Advanced Hg Analyzer spectrophotometer (Altec AMA 254). Prior and after freeze-drying, blood samples were weighed to determine the percentage of water in blood to facilitate comparisons with other studies. At least two aliquots ranging from 5 to 10 mg were analyzed for each individual and quality assessment was measured by repeated analyses of certified reference material TORT-2 (lobster hepatopancreas, NRCC; certified value 0.27±0.06 µg⋅g−1). Hg concentrations are expressed in µg⋅g−1 dry weight (dw).
Stable isotopes analysis
The isotopic niche of snow petrels was used as a proxy of their trophic niche during the pre-breeding period, as blood cells is a metabolically active tissue that integrates periods of weeks before sampling [39], [40] and [41]. The isotopic method was validated in the southern Indian Ocean, with δ13C values of seabirds indicating their foraging habitats [42], [43] and their δ15N values increasing with trophic level [44]. Before isotopic analysis, blood samples were freeze-dried and powdered. Sub-samples of homogenized blood powder were then weighed (∼0.4 mg) with a microbalance and packed in tin containers. Relative abundances of C and N isotopes were determined with a continuous flow mass spectrometer (Thermo Scientific Delta V Advantage) coupled to an elemental analyzer (Thermo Scientific Flash EA 1112). Isotopic results are presented in the δ notation relative to Vienna PeeDee Belemnite and atmospheric N2 for δ13C and δ15N, respectively. Replicate measurements of internal laboratory standards (acetanilide) indicate measurement errors <0.10 ‰ for both δ13C and δ15N values. The C:N mass ratios of the samples were calculated as the ratio between the mass percentages in carbon and nitrogen. The consistently low C:N values of blood cells verified that low lipid content did not necessitate lipid extraction [45].
Hormone assays
Plasma LH concentrations were assayed by radioimmunoassay as validated for snow petrels [33]. The lowest detectable concentration of LH was 0.05 ng⋅ml−1 and the intra-assay coefficient of variation was 6.2% (three duplicates). In 4 birds plasma levels were too low to measure LH.
Statistics
All analyses were performed using R v. 2.13.1. We used GLM with normal error and identity link function to explain: (i) blood Hg concentration in relation to age, blood δ13C and δ15N, scaled mass index, and interactions with sex, (ii) blood δ13C and δ15N values in relation to age, age2, scaled mass index and interactions with sex (linear and/or quadratic). To address the interaction between LH, Hg and age, the dataset was split into two groups using a recently developed Bayesian approach (‘broken stick’ modelling technique [46], [47], based on beta regression analysis with ‘betareg’ package in R, [48]. This method will infer the ‘age limit’ where blood Hg concentration starts translates statistically as a change-point in the distribution of blood Hg concentration versus age. To estimate the age limit of the change-point Ti, in blood Hg concentrations we used a profile likelihood approach [47]: the likelihood was computed for each age. The value of Ti that maximized the likelihood was thus evaluated, and an approximate confidence interval for Ti was computed with a Likelihood Ratio Test with 1 df. This method bypasses the need to manually inspect the data for identification of a change-point, which could only be uncertain in our case owing to the high variance observed in individual blood Hg concentrations. Thanks to this method we were able to distinguish a ‘break’ in Hg distribution at 23 years old in our data set. Thus we considered two groups: birds that were until 23 years old (N = 31) and birds that were more than 23 (N = 14) hereafter ‘≤23 y.o.’ and ‘>23 y.o.’, respectively), blood Hg concentrations were significantly higher in ‘≤23 y.o’ birds than in the ‘>23 y.o.’ ones (GLM, F1,43 = 4.8, p = 0.034). Finally (iii) absolute plasma baseline LH concentrations, LH changes from 0 to 10 minutes, and changes from 10 to 30 minutes were tested as functions of blood Hg concentration (linear) in relation to age classes (‘≤23 y.o.’ and ‘>23 y.o.’). We performed all our model selection starting from the most parameterized model that included all the variables/factors and their interactions and we removed step by step the non-significant interactions, variables or factors. Selected models were checked for assumptions and values were log-transformed when necessary, we used GLM with normal error and identity link function to explain LH concentrations in relation with Hg and interaction with sex. Values are means ± SD.
Results
Hg concentrations in relation to age, sex and trophic niche
In snow petrels dw blood was equivalent to 35.5±0.3% of ww blood and Hg concentration averaged 2.7±1.1 (range: 1.0; 5.3) µg⋅g−1 dw During the pre-laying period, blood Hg concentrations were not related to sampling date (GLM, F1,43 = 0.5, p = 0.488) and were higher in females than in males ( Table 1 ). Blood Hg concentration decreased with increasing age in males (GLM, F1,27 = 7.9, p = 0.009, Fig. 1 ) and this negative relationship was only close to statistical significance in females (GLM, F1,14 = 4.0, p = 0.06, Fig. 1 ). Females had significantly higher δ13C and lower δ15N values than males ( Table 1 ). A significant U-shaped relationship between blood δ13C values and age was found, i.e. young and old birds had higher δ13C values than middle-aged ones ( Fig. 2 , Table 2 ). Blood δ15N values were not related to age ( Table 2 ). Blood Hg concentrations increased with increasing blood δ13C in females while in males the similar pattern was found but only close to statistical significance ( Fig. 3A , Table 3 ). Regarding the relationships between blood Hg and δ15N values, a positive relationship was found in females only ( Fig. 3B , Table 3 ). Scaled mass index was not related to blood Hg concentration, δ13C or δ15N values and interactions with sex (p>0.099 for all tests).
Table 1. Blood Hg concentrations, δ13C and δ15N values in pre-laying snow petrels in relation to sex.
Blood values | Males | Females | Sex differences | |||
SS* | Df | F | p-value | |||
Hg (µg⋅g−1 ww) | 2.2±0.9 (1.0; 4.5) | 3.6±1.0 (2.0; 5.3) | 18.7 | 1,43 | 21.9 | >0.001 |
δ13C (‰) | −25±0.3 (−25.6; −24.4) | −24.5±0.6 (−25.6; −23.6) | 1.9 | 1,43 | 10.1 | >0.001 |
δ15N (‰) | 9.3±0.6 (8.5; 12.5) | 10.1±1.0 (8.2; 10.4) | 6.5 | 1,43 | 8.3 | 0.006 |
*SS = Sum of squares.
Values are means ± SD with ranges in parentheses.
Table 2. Modelling the effects of age (years), age2, sex and interactions as a function of blood δ13C and δ15N values (‰) in pre-laying snow petrels.
Dependent variable | Independent variable | SS* | Df | F | p-value |
a) δ13C | Age2 | 1.0 | 1,32 | 5.0 | 0.033 |
Age | 0.9 | 1,32 | 4.5 | 0.041 | |
Sex | 1.5 | 1,32 | 7.5 | >0.001 | |
Age2×Age | 0.8 | 1,32 | 4.1 | 0.052 | |
Age2×Sex | 0.7 | 1,32 | 3.7 | 0.063 | |
Age×Sex | 0.7 | 1,32 | 3.4 | 0.074 | |
Age2×Age×Sex | >0.1 | 1,32 | >0.1 | 0.862 | |
b) δ15N | Age2 | >0.1 | 1,32 | >0.1 | 0.809 |
Age | >0.1 | 1,32 | >0.1 | 0.876 | |
Sex | 5.3 | 1,32 | 6.1 | 0.019 | |
Age2×Age | 0.2 | 1,32 | 0.2 | 0.644 | |
Age2×Sex | 0.6 | 1,32 | 0.7 | 0.421 | |
Age×Sex | 0.7 | 1,32 | 0.8 | 0.369 | |
Age2×Age×Sex | >0.1 | 1,32 | >0.1 | 0.927 |
*SS = Sum of squares.
Table 3. Modelling the relationships between blood δ13C, δ15N values (‰) and blood Hg concentration (µg⋅g−1 dw) in male and female pre-laying snow petrels.
Dependent variable | Sex | Independent variable | SS | Df | F | p-value |
Hg | Males | δ13C | 2.8 | 1,27 | 3.9 | 0.060 |
δ15N | 1.7 | 1,27 | 2.2 | 0.150 | ||
Females | δ13C | 5.7 | 1,14 | 9.1 | 0.009 | |
δ15N | 8.6 | 1,14 | 20.6 | >0.001 |
*SS = Sum of squares.
Hg, age and plasma LH
Following GnRH injections, absolute LH concentrations (baseline: 8.4±0.5 ng⋅ml−1) significantly increased (10 min: 11.5±0.8 ng⋅ml−1), then decreased (30 min: 9.1±0.8 ng⋅ml−1; generalized linear mixed model (GLMM), time as factor: F2,61 = 12.57, p<0.001) these LH variations were not different between sexes or age classes (≤23 y.o. versus >23 y.o.) (p>0.08 for all tests). Absolute plasma LH concentrations (baseline, after 10 and after 30 minutes) were significantly higher in males compared to females (p<0.009 for all tests) and were not related to sampling date (p>0.123 for all tests) or to scaled mass index (p>0.07 for all tests). In birds that were ≤23 y.o., plasma baseline LH significantly decreased with increasing Hg concentration in blood ( Fig. 4A , Table 4 ) and LH changes from 0 to 10 minutes and from 10 to 30 minutes following the GnRH challenge were unrelated to blood Hg concentration ( Fig. 4B–C , Table 4 ). In birds that were >23 y.o., plasma baseline LH concentration, LH changes from 0 to 10 minutes and from 10 to 30 minutes, were unrelated to blood Hg concentration ( Fig. 4D–E–F , Table 4 ).
Table 4. Modelling the relationships between blood Hg concentration a) baseline plasma LH concentrations, b) LH change from 0 to 10 minutes and c) LH change from 10 to 30 minutes in pre-laying snow petrels ≤23 years old and >23 years old.
Independent variable: Hg | ≤23 years old | >23 years old | ||||||
Dependent variable | SS | Df | F | p-value | SS | Df | F | p-value |
a) Baseline LH | 31 | 1,25 | 5 | 0.041 | 0.8 | 1,11 | 0 | 0.830 |
b) LH change from 0 to 10 minutes | 0 | 1,21 | 0 | 0.713 | 0.1 | 1,10 | 1 | 0.429 |
c) LH change from 10 to 30 minutes | 0 | 1,19 | 1 | 0.269 | 0.1 | 1,9 | 2 | 0.205 |
SS = Sum of squares.
Discussion
Hg exposure, trophic niche and age
In pre-laying snow petrels, blood Hg concentrations were in the range of concentrations found in other species from the Southern ocean [16], [49], [50] and equivalent to those reported at the same location (Adélie Land) in south polar skuas Catharacta maccormicki (2.2±0.2 µg⋅g−1 dw [51]). Blood Hg concentrations were higher in females than in males. In birds, Hg sex differences are often observed and are more likely to be related to trophic guild than other extrinsic or intrinsic factors [52]. In the present study we have an evidence of trophic guild difference between sexes; indeed stable isotopes analyses showed that foraging habitat (δ13C values) was positively related to blood δ13C values especially in females. According to the latitudinal δ13C gradient in oceanic waters of the Southern Ocean [42], [43], blood δ13C values suggest the use of a high Antarctic habitat [53]. More precisely, the δ13C values close to −23 ‰ depict warmer waters at more northern latitudes and the δ13C values close to −26 ‰ colder waters at more southern latitudes, but still within the Antarctic zone [53]. Hg distribution, and hence its bioavailability is known to be heterogeneous in the Southern Ocean [54]. The positive relationship between δ13C values and Hg concentrations means that Hg might be more bioavailable for snow petrels at more northern latitudes (δ13C values close to −23 ‰).
Trophic position, as depicted by blood δ15N values, was positively related to blood Hg concentration in females only. The enrichment of Hg with increasing trophic level has been described in food-webs and species communities [8], [9] but more rarely within a given species. For example, Hg enrichment with increasing δ15N values was found in chicks but not in adults of great skuas Catharacta skua [19]. In Adélie land, snow petrels feed their chicks mainly with fish [24], but the adults’ diet is still unknown. When compared to other Antarctic seabirds and their prey [53], the large range of blood δ15N values suggests that self-feeding breeding adults fed from a krill- to a fish-based diet, depending on individuals. The higher blood δ15N values of males indicate they fed more on fish than females. However and unexpectedly despite their higher trophic level, males are less Hg contaminated than females, suggesting once more that females may feed in areas where Hg is more bioavailable. This is in agreement with the δ13C values-Hg concentration relationship. Alternatively, detoxification processes could be more efficient in males. Noticeably, their stable isotope values indicate that the most contaminated males fed on fish at more northern latitudes than the others, suggesting again a latitudinal effect on Hg availability [54]. To summarize, females probably fed at more northern latitudes and at a lower trophic position compared to males. However, females were more Hg contaminated and Hg contamination was positively related to foraging habitat and trophic position, while in males no relationships were found. These results could be the consequence of sex-specific foraging preferences [55], [56] or maybe sex-specific physiological constraints. Indeed, females are 20% lighter than males consequently they could be more sensitive to the harsh Antarctic climate during winter and constraint to forage in more northern latitudes where Hg is more bioavailable.
Contrary to our prediction blood Hg concentration decreased with increasing age in pre-laying snow petrels, especially in males. The relationship between Hg and age in seabirds is poorly documented and often contradictory. For example, in organs involved in storage and detoxification as the liver, Hg concentration may decrease, increase, with advancing age or may not be related to age [12], [13] and [15]. In excretory tissues as feathers, Hg reaches a plateau until individuals start breeding, and then feather Hg concentration decreases [16]. Regarding blood Hg, two studies on Procellariiforms found no relationship between Hg and age [16], [50]. However in south polar skuas, breeding experience (which is tightly related to age) was negatively related to blood Hg [51], as found in our study. This pattern could originate from an age-related change in trophic niche i.e. older individuals would forage in areas where Hg is less bioavailable and/or at a lower trophic level than younger ones. Indeed, trophic niche segregations by age, has been observed in some Procellariform species [55], [56]. In our study, a quadratic relationship was found between foraging habitat (δ13C values) and age. This suggests that, compared to middle-aged birds, young and old individuals foraged at higher latitudes which may be more Hg contaminated. Isotopic signature of blood represents the isotopic niche during the last month preceding sampling [53]. As birds have been sampled in November (a few days after their arrival on the breeding area) those values may mirror the trophic niche used during late winter and suggest that young and old snow petrels do not use the same foraging areas than middle-aged birds at that time. And why older individuals bear lower Hg concentrations than younger birds could be the consequence of an increase in Hg excretion rate with increasing age or the selective disappearance of the most contaminated individuals over time. One may assume that Hg excretion opportunities increase with age; as older individuals had more opportunities to excrete Hg, through molting, and egg-laying for females, than younger birds. But there is no evidence for supporting such an assumption. Also, our study was cross-sectional, and since in its methylated form Hg is highly toxic, the possibility that most of the highly contaminated birds died selectively over time cannot be excluded. In Adult common loons (Gavia immer) blood Hg concentrations of 2–3 µg⋅g−1 (ww) are considered at moderate risk to effects of Hg contamination [57]. In snow petrels ww blood Hg concentrations would reach 1.6 µg⋅g−1 and 1.9 µg⋅g−1, for the most contaminated male and female respectively; these concentrations are close to the threshold level for moderate risk in common loons and snow petrels could maybe be more sensitive to lower Hg concentrations. However, in free-living birds, Hg has so far never been reported as affecting survival probabilities, even in highly contaminated areas [51], [58], [59], [60], [61].
LH secretion in relation to age and Hg
In the present study, plasma baseline LH decreased with increasing blood Hg in individuals until 23 y.o., which were those that bore the higher concentrations of blood Hg. This negative relationship between plasma baseline LH and blood Hg could either originate from a Hg-related dysfunction of the pituitary (i.e. an inability to produce enough LH) and/or of the hypothalamus (i.e. a lack of endogenous GnRH production). Since LH changes (0–10 min and 10–30 min) following an exogenous input of GnRH were not related to Hg, this means that Hg does not disrupt the capability of the pituitary to release LH in birds until 23 y.o.: their pituitary is thus functional. This rather suggests, as found in black-legged kittiwakes, of a problem originating from the hypothalamus, which may not release enough GnRH in response to high Hg exposure [29]. However, contrary to black-legged kittiwakes [29], Hg contamination did not result in an over-release of LH post-GnRH injection in snow petrels. In black-legged kittiwakes, the over-release of LH was interpreted as an increase of GnRH receptors on the pituitary in response to the low level of GnRH secreted by the hypothalamus [29]. In snow petrels, the concentrations of blood Hg are slightly higher than in black-legged kittiwakes (2.7±1.1 µg⋅g−1 against 2.0±0.5 µg⋅g−1, respectively) and LH secretion post-GnRH injection was less pronounced in snow petrels compared to kittiwakes (averagely 1.4-fold and 2.0-fold, respectively). It is always difficult to compare different species as hazardous effects of Hg could be highly species-specific [51]: e.g. average blood Hg concentrations in brown skuas were much higher than in south polar skuas (8.2±0.2 and 2.2±0.2 µg⋅g−1 dw, respectively) however south polar skuas suffered from higher Hg-induced breeding failure than their closely relative [51]. Thus, it is possible that black-legged kittiwakes could be more sensitive to Hg than snow petrels and would react more strongly to slightly lower Hg concentrations. In birds that were more than 23 y.o., blood Hg concentrations were lower than in the ≤23 age class, and no relationship appeared between plasma LH and blood Hg concentrations. However sample size was low for individuals aged above 23, and such interpretation must be taken cautiously. The onset of breeding is importantly controlled by an increase of circulating LH in the plasma [62], [63], if these concentrations are not high enough individuals will be less receptive to mating behaviors [64]. In snow petrels a large proportion of young individuals do not breed each year [65], this non-breeding behavior could thus be related to Hg contamination.
Conclusion
This study shows the importance of considering age in eco-toxicological studies. We reported an unexpected negative relationship between age and blood Hg concentrations in adult snow petrels and the use of stable isotopes suggests that this pattern could originate from an age and sex-related variation in late wintering areas, and hence Hg bioavailability. It is now possible to map migration and winter distribution of relatively small birds such as snow petrels via miniature loggers (geolocation sensors, GLS, e.g. [66]). These devices could thus open new research possibilities to confirm the influence of age on the wintering areas used by this Antarctic species and to document how migratory strategies and winter distribution can affect the uptake of contaminants. We also showed that the age of the birds and their contaminant burden could influence the secretion of a key pituitary hormone for the onset of breeding (LH). This result, together with recent findings on black-legged kittiwakes, supports the view that Hg is tightly connected to LH secretion and then can impair the decision to breed [29] and long-term reproductive success [51] in polar seabirds. Anthropogenic Hg emissions are expected to rise in the coming decades [67], probably resulting in increasing Hg exposure for Antarctic top predators. This, coupled with a wide range of environmental perturbations in Antarctic regions could exacerbate the demographic responses of top predators to Hg [51].
Acknowledgments
The authors thank M. Kriloff and E. Antoine for their help in the field, C. Trouvé, C. Parenteau, S. Dano and C. Churlaud for their assistance in hormone and Hg assays, C. Barbraud for his help in statistical analyses, J.B. Thiébot and M. Authier for providing the R code for the ‘broken sticks’ method and C. Breuner for improving the English and the manuscript. We also thank two anonymous referees for their constructive comments.
Funding Statement
Financial support was provided by the Agence Nationale de la Recherche (program POLARTOP, O. Chastel), the Institut Polaire Français Paul Emile Victor (IPEV, program no. 109, H. Weimerskirch), and the Terres Australes et Antarctiques Françaises (TAAF). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
References
- 1. Scheuhammer AM, Meyer MW, Sandheinrich MB, Murray MW (2007) Effects of Environmental Methylmercury on the Health of Wild Birds, Mammals, and Fish. AMBIO: A Journal of the Human Environment 36: 12–19 10.1579/0044-7447(2007)3612:EOEMOT2.0.CO2 [DOI] [PubMed] [Google Scholar]
- 2.Gabrielsen GW, Sydnes L (2009) Pollution in the Barents Sea. Ecosystem Barents Sea. Tapir Academic Press.
- 3. Koeman JH, van de Ven WSM, de Goeij JJM, Tjioe PS, van Haaften JL (1975) Mercury and selenium in marine mammals and birds. Science of The Total Environment 3: 279–287 10.1016/0048-9697(75)90052-2 [DOI] [PubMed] [Google Scholar]
- 4. Honda K, Fujise Y, Tatsukawa R, Itano K, Miyazaki N (1986) Age-related accumulation of heavy metals in bone of the striped dolphin, Stenella coeruleoalba. Marine Environmental Research 20: 143–160 10.1016/0141-1136(86)90045-0 [DOI] [Google Scholar]
- 5. Wagemann R (1989) Comparison of Heavy Metals in Two Groups of Ringed Seals (Phoca hispida) from the Canadian Arctic. Can J Fish Aquat Sci 46: 1558–1563 10.1139/f89-198 [DOI] [Google Scholar]
- 6. Dietz R, Riget F, Born E (2000) Geographical differences of zinc, cadmium, mercury and selenium in polar bears (Ursus maritimus) from Greenland. Science of The Total Environment 245: 25–47 10.1016/S0048-9697(99)00431-3 [DOI] [PubMed] [Google Scholar]
- 7. Bargagli R, Monaci F, SanchezHernandez JC, Cateni D (1998) Biomagnification of mercury in an Antarctic marine coastal food web. Mar Ecol Prog Ser 169: 65–76 10.3354/meps169065 [DOI] [Google Scholar]
- 8. Blévin P, Carravieri A, Jaeger A, Chastel O, Bustamante P, et al. (2013) Wide Range of Mercury Contamination in Chicks of Southern Ocean Seabirds. PLoS ONE 8: e54508 10.1371/journal.pone.0054508 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Furness RW (1993) Birds as monitors of pollutants. In: Furness RW, Greenwood JJD, editors. Birds as Monitors of Environmental Change. Springer Netherlands. 86–143. [Google Scholar]
- 10. Rowe CL (2008) “The Calamity of So Long Life”: Life Histories, Contaminants, and Potential Emerging Threats to Long-lived Vertebrates. BioScience 58: 623 10.1641/B580709 [DOI] [Google Scholar]
- 11. Carravieri A, Cherel Y, Blévin P, Brault-Favrou M, Chastel O, et al. (2014) Mercury exposure in a large subantarctic avian community. Environmental Pollution 190: 51–57 10.1016/j.envpol.2014.03.017 [DOI] [PubMed] [Google Scholar]
- 12. Furness R, Hutton M (1979) Pollutant levels in the great skua Catharacta skua. Environmental Pollution (1970) 19: 261–268 10.1016/0013-9327(79)90118-6 [DOI] [Google Scholar]
- 13. Hutton M (1981) Accumulation of heavy metals and selenium in three seabird species from the United Kingdom. Environmental Pollution Series A, Ecological and Biological 26: 129–145 10.1016/0143-1471(81)90043-X [DOI] [Google Scholar]
- 14. Furness RW, Lewis SA, Mills JA (1990) Mercury levels in the plumage of red-billed gulls Larus novaehollandiae scopulinus of known sex and age. Environmental Pollution 63: 33–39 10.1016/0269-7491(90)90101-H [DOI] [PubMed] [Google Scholar]
- 15. Thompson DR, Hamer KC, Furness RW (1991) Mercury Accumulation in Great Skuas Catharacta skua of Known Age and Sex, and Its Effects Upon Breeding and Survival. The Journal of Applied Ecology 28: 672 10.2307/2404575 [DOI] [Google Scholar]
- 16. Tavares S, Xavier JC, Phillips RA, Pereira ME, Pardal MA (2013) Influence of age, sex and breeding status on mercury accumulation patterns in the wandering albatross Diomedea exulans. Environmental Pollution 181: 315–320 10.1016/j.envpol.2013.06.032 [DOI] [PubMed] [Google Scholar]
- 17. Chastel O, Weimerskirch H, Jouventin P (1993) High annual variability in reproductive success and survival of an Antarctic seabird, the snow petrel Pagodroma nivea. Oecologia 94: 278–285 10.1007/BF00341328 [DOI] [PubMed] [Google Scholar]
- 18. Bearhop S, Ruxton GD, Furness RW (2000) Dynamics of mercury in blood and feathers of great skuas. Environmental Toxicology and Chemistry 19: 1638–1643 10.1002/etc.5620190622 [DOI] [Google Scholar]
- 19. Bearhop S, Waldron S, Thompson D, Furness R (2000) Bioamplification of Mercury in Great Skua Catharacta skua Chicks: the Influence of Trophic Status as Determined by Stable Isotope Signatures of Blood and Feathers. Marine Pollution Bulletin 40: 181–185 10.1016/S0025-326X(99)00205-2 [DOI] [Google Scholar]
- 20. Gochfeld M (1980) Tissue distribution of mercury in normal and abnormal young Common Terns. Marine Pollution Bulletin 11: 362–366 10.1016/0025-326X(80)90284-2 [DOI] [Google Scholar]
- 21. Wayland M, Garcia-Fernandez AJ, Neugebauer E, Gilchrist HG (2001) Concentrations of Cadmium, Mercury and Selenium in Blood, Liver and Kidney of Common Eider Ducks from the Canadian Arctic. Environ Monit Assess 71: 255–267 10.1023/A:1011850000360 [DOI] [PubMed] [Google Scholar]
- 22. Henny CJ, Hill EF, Hoffman DJ, Spalding MG, Grove RA (2002) Nineteenth Century Mercury: Hazard to Wading Birds and Cormorants of the Carson River, Nevada. Ecotoxicology 11: 213–231 10.1023/A:1016327602656 [DOI] [PubMed] [Google Scholar]
- 23. Newsome SD, Martinez del Rio C, Bearhop S, Phillips DL (2007) A niche for isotopic ecology. Frontiers in Ecology and the Environment 5: 429–436 10.1890/060150.1 [DOI] [Google Scholar]
- 24. Ridoux V, Offredo C (1989) The diets of five summer breeding seabirds in Adélie Land, Antarctica. Polar Biol 9: 137–145 10.1007/BF00297168 [DOI] [Google Scholar]
- 25. Tan SW, Meiller JC, Mahaffey KR (2009) The endocrine effects of mercury in humans and wildlife. Critical Reviews in Toxicology 39: 228–269 10.1080/10408440802233259 [DOI] [PubMed] [Google Scholar]
- 26. Drevnick PE, Sandheinrich MB (2003) Effects of Dietary Methylmercury on Reproductive Endocrinology of Fathead Minnows. Environ Sci Technol 37: 4390–4396 10.1021/es034252m [DOI] [PubMed] [Google Scholar]
- 27. Frederick P, Jayasena N (2011) Altered pairing behaviour and reproductive success in white ibises exposed to environmentally relevant concentrations of methylmercury. Proc R Soc B 278: 1851–1857 10.1098/rspb.2010.2189 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Evers DC, Savoy LJ, DeSorbo CR, Yates DE, Hanson W, et al. (2008) Adverse effects from environmental mercury loads on breeding common loons. Ecotoxicology 17: 69–81 10.1007/s10646-007-0168-7 [DOI] [PubMed] [Google Scholar]
- 29. Tartu S, Goutte A, Bustamante P, Angelier F, Moe B, et al. (2013) To breed or not to breed: endocrine response to mercury contamination by an Arctic seabird. Biol Lett. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Norris DO, Carr JA (2013) Vertebrate Endocrinology. Academic Press. 599 p. [Google Scholar]
- 31. Schoech SJ, Mumme RL, Wingfield JC (1996) Delayed breeding in the cooperatively breeding Florida scrub-jay (Aphelocoma coerulescens): inhibition or the absence of stimulation? Behav Ecol Sociobiol 39: 77–90 10.1007/s002650050269 [DOI] [Google Scholar]
- 32. Goutte A, Angelier F, Chastel CC, Trouvé C, Moe B, et al. (2010) Stress and the timing of breeding: Glucocorticoid-luteinizing hormones relationships in an arctic seabird. General and Comparative Endocrinology 169: 108–116 10.1016/j.ygcen.2010.07.016 [DOI] [PubMed] [Google Scholar]
- 33. Goutte A, Kriloff M, Weimerskirch H, Chastel O (2011) Why do some adult birds skip breeding? A hormonal investigation in a long-lived bird. Biol Lett 7: 790–792 10.1098/rsbl.2011.0196 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34. Ramalingam V, Vimaladevi V, Rajeswary S, Suryavathi V (2003) Effect of mercuric chloride on circulating hormones in adult albino rats. J Environ Biol 24: 401–404. [PubMed] [Google Scholar]
- 35.Vom Saal FS, Finch CE (1988) Reproductive senescence: Phenomena and mechanisms in mammals and selected vertebrate. The physiology of reproduction. New York.
- 36. Angelier F, Moe B, Weimerskirch H, Chastel O (2007) Age-specific reproductive success in a long-lived bird: do older parents resist stress better? Journal of Animal Ecology 76: 1181–1191 10.1111/j.1365-2656.2007.01295.x [DOI] [PubMed] [Google Scholar]
- 37. Peig J, Green AJ (2009) New perspectives for estimating body condition from mass/length data: the scaled mass index as an alternative method. Oikos 118: 1883–1891 10.1111/j.1600-0706.2009.17643.x [DOI] [Google Scholar]
- 38. Bustamante P, Lahaye V, Durnez C, Churlaud C, Caurant F (2006) Total and organic Hg concentrations in cephalopods from the North Eastern Atlantic waters: Influence of geographical origin and feeding ecology. Science of The Total Environment 368: 585–596 10.1016/j.scitotenv.2006.01.038 [DOI] [PubMed] [Google Scholar]
- 39. Hobson KA, Clark RG (1993) Turnover of 13 C in Cellular and Plasma Fractions of Blood: Implications for Nondestructive Sampling in Avian Dietary Studies. The Auk 110: 638–641 10.2307/4088430 [DOI] [Google Scholar]
- 40. Hobson KA, Clark RG (1992) Assessing Avian Diets Using Stable Isotopes II: Factors Influencing Diet-Tissue Fractionation. The Condor 94: 189–197 10.2307/1368808 [DOI] [Google Scholar]
- 41. Bearhop S, Waldron S, Votier SC, Furness RW (2002) Factors That Influence Assimilation Rates and Fractionation of Nitrogen and Carbon Stable Isotopes in Avian Blood and Feathers. Physiological and Biochemical Zoology 75: 451–458 10.1086/342800 [DOI] [PubMed] [Google Scholar]
- 42. Cherel Y, Hobson KA (2007) Geographical variation in carbon stable isotope signatures of marine predators: a tool to investigate their foraging areas in the Southern Ocean. Marine Ecology Progress Series 329: 281–287. [Google Scholar]
- 43. Jaeger A, Lecomte VJ, Weimerskirch H, Richard P, Cherel Y (2010) Seabird satellite tracking validates the use of latitudinal isoscapes to depict predators’ foraging areas in the Southern Ocean. Rapid Communications in Mass Spectrometry 24: 3456–3460 10.1002/rcm.4792 [DOI] [PubMed] [Google Scholar]
- 44. Cherel Y, Fontaine C, Richard P, Labat J-P (2010) Isotopic niches and trophic levels of myctophid fishes and their predators in the Southern Ocean. Limnology and oceanography 55: 324–332. [Google Scholar]
- 45. Cherel Y, Hobson KA, Hassani S (2005) Isotopic Discrimination between Food and Blood and Feathers of Captive Penguins: Implications for Dietary Studies in the Wild. Physiological and Biochemical Zoology 78: 106–115 10.1086/425202 [DOI] [PubMed] [Google Scholar]
- 46. Thiebot JB, Authier M, Trathan PN, Bost C-A (2014) Gentlemen first? “Broken stick” modelling reveals sex-related homing decision date in migrating seabirds. Journal of Zoology 292: 25–30 10.1111/jzo.12080 [DOI] [Google Scholar]
- 47. Authier M, Martin C, Ponchon A, Steelandt S, Bentaleb I, et al. (2012) Breaking the sticks: a hierarchical change-point model for estimating ontogenetic shifts with stable isotope data. Methods in Ecology and Evolution 3: 281–290 10.1111/j.2041-210X.2011.00162.x [DOI] [Google Scholar]
- 48. Cribari-Neto L, Zeilis A (2010) Beta Regression in R. J Stat Softw. 34: 1–24. [Google Scholar]
- 49. Anderson O, Phillips R, McDonald R, Shore R, McGill R, et al. (2009) Influence of trophic position and foraging range on mercury levels within a seabird community. Marine Ecology Progress Series 375: 277–288 10.3354/meps07784 [DOI] [Google Scholar]
- 50. González-Solís J, Sanpera C, Ruiz X (2002) Metals and selenium as bioindicators of geographic and trophic segregation in giant petrels Macronectes spp. Mar Ecol Prog Ser 244: 257–264 10.3354/meps244257 [DOI] [Google Scholar]
- 51. Goutte A, Bustamante P, Barbraud C, Delord K, Weimerskirch H, et al. (2013) Demographic responses to mercury exposure in two closely-related Antarctic top predators. Ecology. [DOI] [PubMed] [Google Scholar]
- 52. Robinson SA, Lajeunesse MJ, Forbes MR (2012) Sex Differences in Mercury Contamination of Birds: Testing Multiple Hypotheses with Meta-Analysis. Environ Sci Technol 46: 7094–7101 10.1021/es204032m [DOI] [PubMed] [Google Scholar]
- 53. Cherel Y (2008) Isotopic niches of emperor and Adélie penguins in Adélie Land, Antarctica. Mar Biol 154: 813–821 10.1007/s00227-008-0974-3 [DOI] [Google Scholar]
- 54. Cossa D, Heimbürger L-E, Lannuzel D, Rintoul SR, Butler ECV, et al. (2011) Mercury in the Southern Ocean. Geochimica et Cosmochimica Acta 75: 4037–4052 10.1016/j.gca.2011.05.001 [DOI] [Google Scholar]
- 55. Lecomte VJ, Sorci G, Cornet S, Jaeger A, Faivre B, et al. (2010) Patterns of aging in the long-lived wandering albatross. PNAS 107: 6370–6375 10.1073/pnas.0911181107 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56. Thiers L, Delord K, Barbraud C, Phillips RA, Pinaud D, Weimerskirch (2014) Foraging zones of the two sibling species of giant petrels in the Indian Ocean throughout the annual cycle: implication for their conservation. Marine Ecology Progress Series 499: 233–248. [Google Scholar]
- 57.Champoux L, Masse DC, Evers D, Lane OP, Plante M, et al. (2006) Assessment of mercury exposure and potential effects on common loons (Gavia immer) in Québec. In: Hanson AR, Kerekes JJ, editors. Limnology and Aquatic Birds. Developments in Hydrobiology. Springer Netherlands. 263–274. [Google Scholar]
- 58. Mitro MG, Evers DC, Meyer MW, Piper WH (2008) Common Loon Survival Rates and Mercury in New England and Wisconsin. The Journal of Wildlife Management 72: 665–673 10.2193/2006-551 [DOI] [Google Scholar]
- 59. Wayland M, Drake KL, Alisauskas RT, Kellett DK, Traylor J, et al. (2008) Survival rates and blood metal concentrations in two species of free-ranging North American sea ducks. Environmental Toxicology and Chemistry 27: 698–704 10.1897/07-321.1 [DOI] [PubMed] [Google Scholar]
- 60. Hallinger KK, Cornell KL, Brasso RL, Cristol DA (2011) Mercury exposure and survival in free-living tree swallows (Tachycineta bicolor). Ecotoxicology 20: 39–46 10.1007/s10646-010-0554-4 [DOI] [PubMed] [Google Scholar]
- 61.Goutte A, Barbraud C, Meillère A, Carravieri A, Bustamante P, et al. (2014) Demographic consequences of heavy metals and persistent organic pollutants in a vulnerable long-lived bird, the wandering albatross. Proc. R. Soc. B 20133313. 10.1098/rspb.2013.3313. [DOI] [PMC free article] [PubMed]
- 62. Follett BK, Farner DS, Mattocks PW Jr (1975) Luteinizing hormone in the plasma of white-crowned sparrows (Zonotrichia leucophrys gambelii) during artificial photostimulation. General and Comparative Endocrinology 26: 126–134 10.1016/0016-6480(75)90223-3 [DOI] [PubMed] [Google Scholar]
- 63. Sharp PJ (1975) A Comparison of Variations in Plasma Luteinizing Hormone Concentrations in Male and Female Domestic Chickens (gallus Domesticus) from Hatch to Sexual Maturity. J Endocrinol 67: 211–223 10.1677/joe.0.0670211 [DOI] [PubMed] [Google Scholar]
- 64. Bentley GE, Jensen JP, Kaur GJ, Wacker DW, Tsutsui K, et al. (2006) Rapid inhibition of female sexual behavior by gonadotropin-inhibitory hormone (GnIH). Hormones and Behavior 49: 550–555 10.1016/j.yhbeh.2005.12.005 [DOI] [PubMed] [Google Scholar]
- 65. Goutte A, Antoine É, Weimerskirch H, Chastel O (2010) Age and the timing of breeding in a long-lived bird: a role for stress hormones? Functional Ecology 24: 1007–1016 10.1111/j.1365-2435.2010.01712.x [DOI] [Google Scholar]
- 66. Frederiksen M, Moe B, Daunt F, Phillips RA, Barrett RT, et al. (2012) Multicolony tracking reveals the winter distribution of a pelagic seabird on an ocean basin scale. Diversity and Distributions 18: 530–542 10.1111/j.1472-4642.2011.00864.x [DOI] [Google Scholar]
- 67. Streets DG, Zhang Q, Wu Y (2009) Projections of Global Mercury Emissions in 2050. Environmental Science & Technology 43: 2983–2988 10.1021/es802474j [DOI] [PubMed] [Google Scholar]