Mercury exposure may influence fluctuating asymmetry ... - setac - Wiley

Environmental Toxicology and Chemistry, Vol. 36, No. 6, pp. 1599–1605, 2017 Published 2016 SETAC Printed in the USA

MERCURY EXPOSURE MAY INFLUENCE FLUCTUATING ASYMMETRY IN WATERBIRDS GARTH HERRING,*y COLLIN A. EAGLES-SMITH,y and JOSHUA T. ACKERMANz

yForest and Rangeland Ecosystem Science Center, US Geological Survey, Corvallis, Oregon zWestern Ecological Research Center, Dixon Field Station, US Geological Survey, Dixon, California (Submitted 15 August 2016; Returned for Revision 20 October 2016; Accepted 14 November 2016) Abstract: Variation in avian bilateral symmetry can be an indicator of developmental instability in response to a variety of stressors, including environmental contaminants. The authors used composite measures of fluctuating asymmetry to examine the influence of mercury concentrations in 2 tissues on fluctuating asymmetry within 4 waterbird species. Fluctuating asymmetry increased with mercury concentrations in whole blood and breast feathers of Forster’s terns (Sterna forsteri), a species with elevated mercury concentrations. Specifically, fluctuating asymmetry in rectrix feather 1 was the most strongly correlated structural variable of those tested (wing chord, tarsus, primary feather 10, rectrix feather 6) with mercury concentrations in Forster’s terns. However, for American avocets (Recurvirostra americana), black-necked stilts (Himantopus mexicanus), and Caspian terns (Hydroprogne caspia), the authors found no relationship between fluctuating asymmetry and either whole-blood or breast feather mercury concentrations, even though these species had moderate to elevated mercury exposure. The results indicate that mercury contamination may act as an environmental stressor during development and feather growth and contribute to fluctuating asymmetry of some species of highly contaminated waterbirds. Environ Toxicol Chem 2017;36:1599–1605. Published 2016 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America. Keywords: Biomarker

Mercury

Stressor

Wetlands

Wildlife toxicology

asymmetry could be more prevalent in upper–trophic level birds foraging in wetlands, associated with enhanced methylmercury production [27]. We examined fluctuating asymmetry in 4 waterbird species breeding in San Francisco Bay, California, USA, an area in North America that is known to have elevated mercury [28–30]. We used a composite measure of fluctuating asymmetry from 5 different morphological traits because this integrative approach allowed us to draw inferences across multiple metrics [31]. We studied American avocet (Recurvirostra americana), blacknecked stilt (Himantopus mexicanus), Caspian tern (Hydroprogne caspia), and Forster’s tern (Sterna forsteri), which have been found to range in average mercury exposure by over 5-fold during the breeding season [29]. We used mercury concentrations in 2 tissues, blood and feathers, to examine how mercury exposure might be related to fluctuating asymmetry. Mercury in blood represents recent dietary exposure as well as internal tissue redistribution. Mercury in feathers represents mercury in blood at the time of feather growth, which is a balance of internal tissue redistribution during molt and dietary exposure at the time of feather growth.

INTRODUCTION

Biomarkers are commonly used tools for detecting biological responses to contaminant exposure. As functional measures of exposure to various stressors, biomarkers often serve as indicators for deteriorating environmental quality and population health [1] and can span molecular, biochemical, cellular, and physiological levels of organization [2–4]. A commonly used biomarker of individual quality is fluctuating asymmetry, which involves small nondirectional departures of bilateral traits from perfect symmetry as a result of variation in development [5–7]. Fluctuating asymmetry in birds has been associated with a variety of environmental stressors, including hormone levels [8], habitat disturbance and degradation [9], nutritional deficiencies [10,11], and environmental contaminant exposure [12–14]. Several contaminants, including mercury [13], lead [15], organochlorines [12], and sulfuric oxides [16], have been associated with fluctuating asymmetry in birds. Yet, the influence of environmental contaminants on fluctuating asymmetry has been equivocal and, in the case of mercury, has been relatively understudied. Mercury contamination is a global issue that can have implications for the health of aquatic birds [17]. Mercury exposure in waterbirds can be manifested in a variety of effects, including endocrine disruption [18–21], as hormones play a critical role in the development of both feathers [22,23] and skeletal structure [24–26]. Additionally, impaired levels of hormones have been experimentally linked to increased fluctuating asymmetry of tarsus length in chickens (Gallus gallus domesticus [8]). Thus, it is conceivable that fluctuating

METHODS

Capture and sample collection

We captured and collected American avocets, black-necked stilts, Caspian terns, and Forster’s terns (February–August) from several locations throughout San Francisco Bay (37.88N, 122.38W) in 2005 to 2007 during the prebreeding and breeding seasons, as described in Eagles-Smith et al. [29] and Ackerman et al. [32]. Immediately after collection, we sampled whole blood using 20-gauge to 25-gauge sodium-heparinized needles. We transferred blood to labeled cryovials, placed samples on dry ice in the field, and stored them frozen at –20 8C until analysis. We also collected breast feathers from each bird;

* Address correspondence to [email protected] Published online 16 November 2016 in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/etc.3688 1599

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feather samples were placed in Whirl-Paks (Nasco) and stored at –20 8C until processing and analysis. We included fluctuating asymmetry traits that could be considered as short-term (feathers) or long-term (bones) in our composite metric because these differing growth periods reflect the larger spatial scale and temporal periods at which birds are exposed to mercury and at which effects can occur. Waterbirds are frequently highly philopatric to breeding [33,34] and wintering [35–37] sites, and thus, tissue mercury concentrations are likely persistent over a long-term basis [38,39]. We therefore expected that some waterbird species may be regularly exposed to mercury throughout the annual cycle and much of their lives, increasing the likelihood of fluctuating asymmetry at different stages of development. Morphological measurements

We examined 5 measures of asymmetry on the right and left sides of each bird: 1) tarso-metatarsus length (tarsus) was measured to the nearest 0.01 mm using digital calipers (Fisher Scientific); 2) flattened wing length (wing) was measured with a wing ruler to the nearest 0.5 mm (Avinet); 3) the lengths of the outermost primary feather (P10); and 4) the innermost and 5) the outermost rectrices (R1 and R6, respectively) were measured to the nearest 0.5 mm using a wing ruler. Because measurement error can inflate estimates of fluctuating asymmetry [40], we used a double-blind approach with the same person remeasuring 1 of the traits later in the laboratory (P10) from a subsample (n ¼ 85) of the collected birds and running a correlation analysis (see Statistical analyses) to determine whether there was agreement in the repeated measurements. We observed a strong correlation (R2 ¼ 0.99; mean relative percent difference ¼ 0.2 0.01% standard error) in the twice-measured trait used to determine repeatability in the data, suggesting that measurement error did not increase variability or bias estimates of fluctuating asymmetry. Sample processing and mercury determination

We washed feathers in a 1% Alconox solution (Alconox) while manually scrubbing each feather to remove surface debris. We then dried feathers at 50 8C for up to 24 h and stored them in a desiccator prior to analysis. Blood samples were thawed to room temperature and mixed by stirring with a clean pipette tip to ensure sample homogeneity. Following studies of birds [28–30], we measured total mercury because >95% of the mercury is methylmercury. We analyzed all samples for total mercury following US Environmental Protection Agency method 7473 [41] on a DMA-80 Direct Mercury Analyzer (Milestone). Quality assurance measures included analysis of 2 certified reference materials (either dogfish muscle tissue [DORM-2], dogfish liver [DOLT-3], or lobster hepatopancreas [TORT-2]; National Research Council of Canada), 2 system and method blanks, 2 duplicates, 1 matrix spike, and 1 matrix spike duplicate per batch. Recoveries averaged 102.1 0.9% and 99.9 0.7% for certified reference materials and calibration checks, respectively. Absolute relative percent difference for duplicates averaged 4.9 1.1% in blood and 18.9 5.9% in feathers, and absolute relative percent difference for matrix spike duplicates averaged 2.7 0.8% in blood and 10.7 3.3% in feathers. Statistical analyses

All statistical analyses were conducted using JMP Ver 11.0 (SAS Institute). We tested for directional asymmetry (pattern of

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bilateral variation where differences exist between sides but the side that is larger is generally the same [40]) across all measured traits by subtracting the right from left measurements and then used a t test to determine if the values differed from 0. Additionally, we tested for antisymmetry (platykurtic or bimodal distribution [40]) using the distribution of the rightminus-left data and a Shapiro-Wilk test. To determine if there was any effect of size dependence (variation of the magnitude of fluctuating asymmetry as a result of the difference in trait size [40,42]), we ran a correlation between the absolute fluctuating asymmetry (right [R] minus left [L] side) and the average of both sides ([R þ L]/2) across all fluctuating asymmetry traits. For our final calculation of fluctuating asymmetry, we used the difference between the right and left trait measurements by dividing the absolute value of the difference by the average length of the 2 sides [43]. We analyzed fluctuating asymmetry using a composite model where all available fluctuating asymmetry measurements for each of the 5 measured traits were included in an individual model [31,44]. Composite metrics of fluctuating asymmetry have been found to be more beneficial than singular models because of an increased probability of detecting fluctuating asymmetry between populations [6,45–47]. Additionally, this composite approach was used because it is more statistically powerful and less likely to inflate type I error rates than models analyzed with just 1 fluctuating asymmetry trait [31]. Following Leung et al. [31], we calculated this composite fluctuating asymmetry value by dividing each individual’s fluctuating asymmetry value for a given trait by the mean value for that trait across the sampled population (Equation 1). These fluctuating asymmetry values were then summed across all 5 traits for an individual bird such that each individual had a composite fluctuating asymmetry (FA) score (Equation 1). Individual bird0 s composite FA ¼ 1 0 tarsus FA difference wing FA difference P10 FA difference þ þ B C ~ ~ ~ x tarsus FA x wing FA x P10 FA PB C ð1Þ B C @ A R1 FA difference R6 FA difference þ þ ~ ~ x R1 FA x R6 FA n traits

In some instances, we did not have data for all 5 fluctuating asymmetry traits from each bird; therefore, we divided the summed fluctuating asymmetry values of each individual bird by the number of traits measured in each bird to control for differences in the number of fluctuating asymmetry traits used for each individual. We used total mercury concentrations measured in either whole blood or breast feathers to represent different time frames for mercury exposure and, in the case of feather mercury, to represent the growth period for potential feather fluctuating asymmetries. Because total mercury concentrations differed considerably across species [29,48], we ran individual models evaluating factors related to fluctuating asymmetry for each species and tissue (blood and feathers) separately. To account for differences between males and females in total mercury concentrations [29], we included sex as a factor in the species-specific models. We natural log-transformed the composite fluctuating asymmetry values and added 0.01 to the raw data because in some instances fluctuating asymmetry traits had perfect symmetry (difference ¼ 0). Total mercury concentrations also were natural log-transformed to improve normality of residuals.

Fluctuating asymmetry in waterbirds

Although composite models of fluctuating asymmetry are considered to be more statistically powerful and less likely to inflate type I error rates [31], they do not explicitly identify which traits exhibit fluctuating asymmetry. After determining if fluctuating asymmetry occurred using the composite models, we used linear correlation models to ascertain the morphological trait where fluctuating asymmetry most likely occurred. For species with significant composite fluctuating asymmetry models, we correlated each of the 5 asymmetry traits (tarsus, wing, P10, R1, R6) with whole-blood and breast feather total mercury concentrations. RESULTS

From 2005 to 2007, we sampled 390 birds (122 American avocets, 114 black-necked stilts, 45 Caspian terns, and 109 Forster’s terns). The geometric mean whole-blood total mercury concentration across all years, dates, and sites was 0.33 0.04 (standard error) mg/g wet weight in American avocets, 1.02 0.08 mg/g wet weight in black-necked stilts, 1.39 0.15 mg/g wet weight in Caspian terns, and 1.41 0.15 mg/g wet weight in Forster’s terns. The geometric mean breast feather total mercury concentration across all years, dates, and sites was 2.44 0.16 mg/g dry weight in American avocets, 8.64 0.58 mg/g dry weight in black-necked stilts, 10.85 1.69 mg/g dry weight in Caspian terns, and 9.66 0.88 mg/g dry weight in Forster’s terns. Across all fluctuating asymmetry traits, we found no evidence of directional asymmetry because the right-minus-left values for morphological measurements did not differ significantly from 0, nor was there any evidence of antisymmetry because data from each trait were unimodally distributed and did not differ significantly from a normal distribution (all p values >0.06). Across all 5 fluctuating asymmetry traits, we found no indication of size dependence between the magnitude of fluctuating asymmetry and the trait size (all p values >0.18). Composite fluctuating asymmetry values were positively correlated with total mercury concentrations in whole blood of Forster’s terns (F1,95 ¼ 5.19, p ¼ 0.02; Figure 1A), increasing on average by 94% across the observed range in whole-blood total mercury concentrations (b ¼ 0.142 0.121, range ¼ 0.12–13.42 mg/g wet wt). In contrast, composite fluctuating asymmetry was not correlated with total mercury concentrations in whole blood of American avocets (F1,94 ¼ 3.34, p ¼ 0.07; Figure 1B), blacknecked stilts (F1,99 ¼ 0.11, p ¼ 0.75; Figure 1C), or Caspian terns (F1,39 ¼ 0.01, p ¼ 0.94; Figure 1D). Within these models of composite fluctuating asymmetry and whole-blood mercury, we found no difference between the sexes for American avocets (F1,94 ¼ 0.36, p ¼ 0.54), black-necked stilts (F1,99 ¼ 0.65, p ¼ 0.42), Caspian terns (F1,39 ¼ 0.57, p ¼ 0.45), or Forster’s terns (F1,95 ¼ 0.17, p ¼ 0.67). Post hoc analyses for Forster’s tern asymmetry traits suggested that R1 (F1,92 ¼ 3.42, p ¼ 0.06) had the strongest relationship with whole-blood total mercury concentrations, whereas there was little support for wing (F1,49 ¼ 0.08, p ¼ 0.77), tarsus (F1,93 ¼ 0.37, p ¼ 0.71), P10 (F1,82 ¼ 0.33, p ¼ 0.56), or R6 (F1,87 ¼ 0.29, p ¼ 0.58). Composite fluctuating asymmetry also was correlated with total mercury concentrations in breast feathers of Forster’s terns (F1,104 ¼ 6.18, p ¼ 0.01), which increased on average by 102% across the observed range in breast feather total mercury concentrations (b ¼ 0.157 0.123, range ¼ 1.22–105.58 mg/g dry wt; Figure 1E). Composite fluctuating asymmetry was not correlated with total mercury concentrations in breast feathers of American avocets (F1,119 ¼ 0.07, p ¼ 0.79; Figure 1F),


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black-necked stilts (F1,108 ¼ 2.28, p ¼ 0.13; Figure 1G), or Caspian terns (F1,42 ¼ 1.57, p ¼ 0.21; Figure 1H). Within models of composite fluctuating asymmetry and breast feather mercury, we found no difference between the sexes for American avocets (F1,119 ¼ 1.81, p ¼ 0.18), black-necked stilts (F1,108 ¼ 1.24, p ¼ 0.26), Caspian terns (F1,42 ¼ 0.35, p ¼ 0.55), or Forster’s terns (F1,104 ¼ 0.05, p ¼ 0.81). Post hoc analyses for Forster’s tern asymmetry traits suggested that, similar to blood total mercury, R1 (F1,99 ¼ 2.78, p ¼ 0.09) had the strongest relationship with breast feather total mercury concentrations, whereas there was little support for wing (F1,49 ¼ 1.47, p ¼ 0.23), tarsus (F1,101 ¼ 1.31, p ¼ 0.24), P10 (F1,89 ¼ 1.85, p ¼ 0.17), or R6 (F1,93 ¼ 0.01, p ¼ 0.89). DISCUSSION

Fluctuating asymmetry increased with total mercury concentrations in whole blood and breast feathers of Forster’s terns, but there was no relationship between composite measures of fluctuating asymmetry and total mercury concentrations in the 3 other species. Forster’s terns generally had higher mercury concentrations in blood and breast feathers compared with black-necked stilts and American avocets but had similar mercury concentrations as did Caspian terns. Further, Forster’s terns are known to have among the highest mercury concentrations among birds in western North America [30]. Other studies on Forster’s terns also have shown relationships between physiological impairment or reproductive impairment and elevated mercury concentrations. For example, Forster’s terns have a lower liver mercury demethylation threshold and a lower demethylation rate than either avocets or stilts [49]. In the case of Forster’s tern embryos, the probability of embryos being malpositioned within the egg increased with mercury exposure in terns but not in avocets or stilts [50]. Similarly, mercury exposure was associated with oxidative stress biomarkers in brains of Forster’s terns but not Caspian terns [51]. Together, these studies suggest that current mercury exposure levels in Forster’s terns are having effects on bird health. Our results did not detect a relationship between mercury exposure and fluctuating asymmetry in Caspian terns, although they had similar mercury concentrations in whole blood and breast feathers to the Forster’s terns. One potential explanation for this difference is that we sampled nearly 2.5 times more Forster’s terns than Caspian terns; thus, the lack of relationship in Caspian terns could simply be an artifact of sample size. Alternatively, the difference in the relationship between mercury and fluctuating asymmetry between the 2 species may be an issue of species sensitivity. Recent embryo dosing studies found that Caspian terns were only moderately sensitive to methylmercury exposure [52]. Unfortunately, no Forster’s tern embryos were dosed in that study, so comparisons of the 2 species’ sensitivity to mercury are not possible. To our knowledge, no other studies have explicitly tested for differences in the sensitivity between these 2 species. However, a recent review of methylmercury effects on avian reproduction found that, in general, larger (heavier) birds tend to be less sensitive than small or medium-sized birds based on both dietary and blood mercury concentrations [53]. The exact mechanism for this relationship is unclear, but it may be related to decreased metabolism in heavier birds [53]. Following this logic, in the present study, Caspian terns were on average 4.8 times heavier than Forster’s terns. Fluctuating asymmetry in rectrix 1, but not rectrix 6, was correlated with blood or feather mercury concentrations. We

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Figure 1. Relationship between composite fluctuating asymmetry and whole-blood (A–D) and breast feather (E–H) total mercury concentrations in Forster’s terns (A,E), American avocets (B,F), black-necked stilts (C,G), and Caspian terns (D,H) from San Francisco Bay, California, USA, during 2005 to 2007. THg ¼ total mercury.

expect that this may be related to differences in feather molt patterns in Forster’s tern rectrices; when all rectrices are molted, the molt sequence begins on the inside at rectrix 1 and continues out to rectrix 6 [54]. Subsequently, mercury concentrations and exposure (either circulating or redistribution) may be higher during the earlier feather molting stage as a result of the growth sequence differences [55,56], and developmental instability would be highest at the time of rectrix 1 feather growth. We are uncertain why we did not detect effects in other fluctuating asymmetry traits for Forster’s terns, but conceivably this could be associated with when those traits are developed and potential temporal differences in mercury exposure at the time of development. To minimize the aerodynamic costs associated with asymmetry, the optimal phenotype for paired feathers and

wing structures in birds is perfect symmetry [57–59]. Thus, the positive correlation between fluctuating asymmetry and mercury concentrations in Forster’s terns suggests that this species may be suffering mercury-induced physiological stress during development and feather molt. The actual energetic and fitness costs of increased asymmetry associated with mercury exposure in birds are unclear, particularly for small differences detected in fluctuating asymmetry studies. However, moderate handicapping (feather clipping) of birds has been found to reduce their foraging efficiency, decrease body condition, and decrease clutch size [60,61]. In particular, the present results showed a large degree of variation, even though fluctuating asymmetry increased by 94% and 102% over the range of observed mercury concentrations in Forster’s tern blood and feathers, respectively. Regardless, this finding may be of

Fluctuating asymmetry in waterbirds

concern because flight feathers, such as tail rectrices, are utilized for steering and creating lift when birds are in flight, and increased fluctuating asymmetry has been shown to be costly for birds in terms of flight performance and energy expenditure [57–59,62]. Furthermore, for aerial foragers with long forked tails, such as Forster’s terns, asymmetry in the tail feathers can result in a disproportionate loss of lift [57]. There may be additional neuromuscular and biomechanical costs associated with efforts to compensate for fluctuating asymmetry in flight feathers [63]. Additionally, predation rates have been shown to increase in species with higher morphological asymmetry in the case of fish and mammals [64–66]. We used both whole-blood and breast feather mercury concentrations because the tissues represent a different period of mercury exposure. The fact that Forster’s tern fluctuating asymmetry was positively correlated with both breast feather and whole-blood mercury concentrations provides additional support for the physiological effect of mercury on Forster’s terns and suggests that chronic exposure to mercury may be influencing fluctuating asymmetry. In the case of Forster’s terns, feathers represent a distinct depuration and sequestration source for mercury during the period of feather growth that differs from whole-blood concentrations during the breeding season [67]. Although breast feathers may be correlated with whole-blood mercury, the correlation is typically weak, suggesting that they do not represent similar time periods [29]. The mechanism associated with the correlation between mercury and fluctuating asymmetry in birds is unclear. However, from a physiological perspective, thyroid hormones play a central role in regulating growth and replacement of feathers [22,23] and are central to the linear growth of bones [24–26]. Elevated mercury exposure has been linked to endocrine disruption (including altered thyroid function) via hormone level impairment, including decreased concentrations (e.g., glucocorticoids) in birds [18–21] and triiodothyronine/ thyroxine in fish and turtles [68,69]. A reduction in hormones that are critical to feather or bone growth could produce a change in their development patterns [70–73]. In fact, variations in thyroid and corticosterone concentrations in chickens have been shown to produce abnormalities in skeletal proportions [8,71,74]. Further, thyroid hormone regulation of genes associated with bone growth can be site-specific [75], suggesting that certain symmetric characteristics could be more prone to fluctuating asymmetry. For example, increases in osteocalcin (a protein critical to bone growth) were observed in femoral bones but not vertebrae of rats following treatment with thyroxine [75]. Overall the present results indicate that fluctuating asymmetry in Forster’s terns may be related to environmentally relevant levels of mercury exposure. To our knowledge, only 1 previous study has found a relationship between fluctuating asymmetry and mercury concentrations in birds. In the present study, fluctuating asymmetry in secondary feathers of common loons (Gavia immer) differed among groupings of mercury concentrations in feathers [13]. Understanding how fluctuating asymmetry might influence the health and condition of birds is necessary to understand the effects that mercury-induced fluctuating asymmetry may be having on bird health, particularly those migratory and aerial foraging species that could be more impacted by fluctuating asymmetry. Acknowledgment—This research was funded by the CALFED Bay Ecosystem Restoration Program (grant ERP-02D-C12). We appreciate the support and cooperation of the Don Edwards San Francisco Bay


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National Wildlife Refuge staff (special use permits 11640-2005-002 and 11640-2006-006). We thank R. Keister, S. Stoner-Duncan, J. Henderson, C. Johnson, and D. Tsao for field and lab work; and M. Ricca provided valuable comments on a previous draft of the manuscript. Disclaimer—Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US Government. Data availability—Data can be accessed through Sciencebase.gov at https:// dx.doi.org/10.5066/F7KW5D5Z. REFERENCES 1. Adams SM, Giesy JP, Tremblay LA, Eason CT. 2001. The use of biomarkers in ecological risk assessment: Recommendations from the Christchurch Conference on Biomarkers in Ecotoxicology. Biomarkers 6:1–6. 2. Weeks JM. 1995. The value of biomarkers for ecological risk assessment: Academic toys or legislative tools? J Appl Ecol 2:215–216. 3. Ricketts HJ, Morgan AJ, Spurgeon DJ, Kille P. 2003. Measurement of annetocin gene expression: A new reproductive biomarker in earthworm toxicology. Ecotoxicol Environ Saf 57:4–10. 4. Bartell SM. 2006. Biomarkers, bioindicators, and ecological risk assessment—A brief review and evaluation. Environ Bioindic 1:60–73. 5. Van Valen L. 1962. A study of fluctuating asymmetry. Evolution 16:125–142. 6. Palmer AR, Strobeck C. 1986. Fluctuating asymmetry: Measurement, analysis, patterns. Annu Rev Ecol Syst 17:391–421. 7. Leung B, Forbes MR. 1996. Fluctuating asymmetry in relation to stress and fitness: Effects of trait type and as revealed by meta-analysis. Ecoscience 3:400–413. 8. Eriksen MS, Haug A, Torjesen PA, Bakken M. 2003. Prenatal exposure to corticosterone impairs embryonic development and increase fluctuating asymmetry in chickens (Gallus gallus domesticus). Br Poult Sci 44:690–697. 9. Lens L, van Dongen S, Galbusera P, Schenck T, Matthysen E, van De Casteele T. 2000. Developmental instability and inbreeding in natural bird populations exposed to different levels of habitat disturbance. J Evolution Biol 13:889–896. 10. Swaddle JP, Witter MS. 1997. On the ontogeny of developmental stability in a stabilized trait. Proc R Soc Lond B Biol Sci 264:329–334. 11. Grieco F. 2003. Greater food availability reduces tarsus asymmetry in nestling blue tits. Condor 105:599–603. 12. Bustnes JO, Folstad I, Erikstad KE, Fjeld M, Miland ØO, Skaaare JU. 2002. Blood concentration of organochlorine pollutants and wing feather asymmetry in glaucous gull. Funct Ecol 16:617–622. 13. Evers DC, Savoy LJ, DeSorbo CR, Yates DE, Hanson W, Taylor KM, Siegel LS, Cooley JH Jr, Bank MS, Major A, Munney K, Mower BF, Vogel HS, Schoch N, Pokras M, Goodale MW, Fair J. 2008. Adverse effects from environmental mercury loads on breeding common loons. Ecotoxicology 17:69–81. 14. Talloen W, Lens L, Van Dongen S, Mathyysen E. 2008 Feather development under environmental stress: Lead exposure effects on growth patterns in great tits Parus major. Bird Study 55:108–117. 15. Eeva T, Tanhuanp€a€a S, Råbergh C, Airaksinen S, Nikinmaa M, Lehikoinen E. 2000. Biomarkers and fluctuating asymmetry as indicators of pollution-induced stress in two hole-nesting passerines. Funct Ecol 14:235–243. 16. Sillanp€a€a S, Salminen JP, Eeva T. 2010. Fluctuating asymmetry in great tit nestlings in relation to diet quality, calcium availability and pollution exposure. Sci Total Environ 408:3303–3309. 17. Scheuhammer AM, Meyer MW, Sandheinrich MB, Murray MW. 2007. Effects of environmental methylmercury on the health of wild birds, mammals, and fish. Ambio 36:12–18. 18. Wada HD, Cristol A, McNabb FMA, Hopkins WA. 2009. Suppressed adrenocortical responses and thyroid hormone levels in birds near a mercury-contaminated river. Environ Sci Technol 43:6031–6038. 19. Franceschini MD, Lane OP, Evers DC, Reed JM, Hoskins B, Romero LM. 2009. The corticosterone stress response and mercury contamination in free-living tree swallows, Tachycineta bicolor. Ecotoxicology 18:514–521. 20. Herring G, Ackerman JT, Herzog M. 2012. Mercury exposure suppresses baseline stress levels in juvenile birds. Environ Sci Technol 46:6339–6346. 21. Moore CS, Cristol DA, Maddux SL, Varian-Ramos CW, Bradley EL. 2014. Lifelong exposure to methylmercury disrupts stress-induced

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