Amino Acid Specific Stable Nitrogen Isotope Values in Avian Tissues

Oct 27, 2016 - Trophic discrimination factors based upon the source (phenylalanine, Phe) and trophic (glutamic acid, Glu) AAs were 4.1 (muscle) and 5...
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Amino acid-specific Stable Nitrogen Isotope Values in Avian Tissues: Insights from Captive American Kestrels and Wild Herring Gulls Craig E. Hebert, Brian N. Popp, Kim J. Fernie, Cassie Ka'apu-Lyons, Barnett A. Rattner, and Natalie Wallsgrove Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b04407 • Publication Date (Web): 27 Oct 2016 Downloaded from http://pubs.acs.org on October 31, 2016

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Amino acid-specific Stable Nitrogen Isotope Values in Avian Tissues: Insights from Captive

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American Kestrels and Wild Herring Gulls

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C.E. Hebert1*, B.N. Popp2, K.J. Fernie3, C. Ka’apu-Lyons2, B.A. Rattner4, N. Wallsgrove2

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National Wildlife Research Centre, Ottawa, ON, Canada

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Geophysics, Honolulu, HI, USA

C. E. Hebert, Environment and Climate Change Canada, Science and Technology Branch,

B. N. Popp, C. Ka’apu-Lyons, N. Wallsgrove, University of Hawaii, Department of Geology and

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Centre for Inland Waters, Burlington, ON, Canada

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MD, USA

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*Corresponding author: C. E. Hebert, Environment and Climate Change Canada, Science and

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Technology Branch, National Wildlife Research Centre, Ottawa, ON, Canada. Phone 613-998-

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6693, fax 613-998-0458, [email protected]

K. J. Fernie, Environment and Climate Change Canada, Science and Technology Branch, Canada

B. A. Rattner, United States Geological Survey, Patuxent Wildlife Research Center, Beltsville,

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Abstract

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Through laboratory and field studies, the utility of amino acid compound-specific nitrogen

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isotope analysis (AA-CSIA) in avian studies is investigated. Captive American kestrels (Falco

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sparverius) fed an isotopically-characterized diet were sacrificed and patterns in δ15N values of

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amino acids (AAs) were compared in their tissues (muscle, red blood cells) and food. Based

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upon nitrogen isotope discrimination between diet and kestrel tissues, AAs could mostly be

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categorized as source AAs (retaining baseline δ15N values) and trophic AAs (showing 15N

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enrichment). Trophic discrimination factors based upon source (phenylalanine, Phe) and trophic

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(glutamic acid, Glu) AAs were 4.1 (muscle) and 5.4 (red blood cells); lower than reported for

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metazoan invertebrates. In a field study involving omnivorous herring gulls (Larus argentatus

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smithsonianus), egg AA isotopic patterns largely retained those observed in the laying female’s

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tissues (muscle, red blood cells, liver). Realistic estimates of gull trophic position were obtained

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using bird Glu and Phe δ15N values combined with β-values (difference in Glu and Phe δ15N in

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primary producers) for aquatic and terrestrial food webs. Egg fatty acids were used to weight β-

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values for proportions of aquatic and terrestrial food in gull diets. This novel approach can be

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applied to generalist species that feed across ecosystem boundaries.

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Introduction

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Monitoring and research programs using top trophic level predatory birds have been

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conducted for decades. These species integrate lower food web processes making them useful 2 ACS Paragon Plus Environment

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indicators of ecosystem conditions. Integral to these programs is the ability to accurately

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estimate organism trophic position. For example, changes in bird trophic position can provide

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insights into alterations in food web structure.1 Trophic position is also an important factor to

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be considered when interpreting spatial and temporal trends in concentrations of contaminants

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that biomagnify in birds.2-4 One method to estimate trophic position is through the application

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of stable nitrogen isotope ratios (15N/14N relative to a standard expressed as δ15N values). Many

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studies have demonstrated that higher trophic level organisms have greater δ15N values.5 In the

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past, most nitrogen isotopic studies of birds have been based upon the analysis of bulk matter

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in tissues, e.g. generation of one δ15N value from the analysis of a tissue sample analyzed as a

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whole. However, spatial and temporal comparison of δ15N values may not be appropriate

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because of potential differences in tissue composition and baseline δ15N values. With respect to

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the latter issue, interpreting δ15N values in a trophic context may only be appropriate when

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comparing individuals or species at one location during the same time period. When comparing

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organism δ15N values over time and across space it is necessary to consider spatial differences

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and/or temporal changes in δ15N values associated with nitrogen being incorporated into the

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base of food webs6 even at one site. Many studies do this by measuring δ15N values in primary

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invertebrate consumers, such as filter-feeding molluscs.7 These primary consumer values are

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used as baselines from which trophic position estimates can be generated for higher order

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consumers.7 However, it is often not possible to collect such food web samples either because

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of logistical difficulties associated with working in isolated locations (e.g. Arctic site) or because

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samples are being studied, e.g. archived samples, for which no contemporary food web samples

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exist. Furthermore, such an approach to baseline correction assumes that the higher trophic 3 ACS Paragon Plus Environment

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level organisms being evaluated are solely linked to the food web integrated in time and space

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by the primary consumer. This may, or may not, be the case for organisms that exhibit

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individual specialization in feeding habits, e.g. wildlife such as birds.8,9

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Many research and monitoring studies involving wildlife focus on birds and their eggs. Egg

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collections often form the basis of such studies.10 While egg collections may not be possible for

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all species, e.g. species at risk, they have a minimal impact on bird populations. Eggs can be

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used to measure a variety of endpoints, e.g. diet composition, chemical contaminants, stress

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hormones, and are an effective way to evaluate how changes in the environment may be

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affecting top predators .4, 11-14 When egg samples are the only sample matrix available it is

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necessary to utilize a method that will generate both a baseline δ15N value as well as a trophic

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position estimate solely from the wildlife sample being studied. Such an approach is feasible

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through compound-specific stable isotope analysis (CSIA). 15-18 More specifically, the

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measurement of δ15N values in individual amino acids (AA-CSIA) in egg samples offers a possible

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method to generate both baseline (or source) δ15N values and trophic position. Most amino

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acids (AAs) can be categorized as either source or trophic AAs (sensu Popp et al.19). Source AAs

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have δ15N values that retain the baseline/source δ15N values in the food webs utilized by higher

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order consumers.19 This is thought to reflect the fact that the dominant metabolic pathways for

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these AAs do not involve transamination reactions. Conversely, the amine groups on trophic

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AAs undergo extensive deamination/transamination resulting in trophic discrimination of

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nitrogen isotopes.20, 21 As a result, the δ15N values of trophic AAs are greater in consumers than

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in their diet.18,19 To date, most studies applying the AA-CSIA approach to estimate organism

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trophic position have focused on using the difference in the δ15N values of glutamic acid (Glu) 4 ACS Paragon Plus Environment

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and phenylalanine (Phe) as trophic and source AAs, respectively.18,19 A variety of studies

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involving a diverse range of taxa have consistently shown their utility in this context.17-24

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Significant work has laid the foundation for applying the AA-CSIA approach to the evaluation of

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trophic position in aquatic systems. However, inter-taxa differences in the degree of trophic

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discrimination of amino acids require further study, especially for groups such as birds, for

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which, few studies have been conducted (but see 25,26). Results from Lorrain et al.25 (penguin

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blood) and McMahon et al.26 (penguin feathers) point to the likelihood that AA nitrogen isotope

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fractionation in birds is different than in lower trophic level metazoan invertebrates. However,

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the paucity of bird studies highlights the need for further avian research. In particular, captive

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work is required to evaluate the validity of the AA-CSIA approach for avian species in a

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controlled setting. To date, there has only been one such study.26 Also required are studies

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examining a wider variety of tissue types, e.g. eggs, muscle, liver, and species, e.g. terrestrial

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carnivores, aquatic/terrestrial generalists. With respect to the latter, little effort has been

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devoted to applying the AA-CSIA approach to species that consume food originating from more

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than one type of ecosystem, e.g. aquatic and terrestrial. Here, we use an aquatic/terrestrial

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omnivore to describe a method for estimating trophic position in species that utilize resources

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from multiple ecosystems.

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The issues outlined above were addressed through two studies: 1) diet to bird tissue

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comparison. Captive adult American kestrels (Falco sparverius), a terrestrial carnivore, were fed

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an isotopically-characterized diet, tissue (muscle, red blood cell) samples collected, and AA-

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specific δ15N values were generated, and patterns in kestrel tissues were compared to their

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food to determine whether different AAs exhibited patterns in δ15N values consistent with 5 ACS Paragon Plus Environment

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source and trophic AAs. 2) Adult tissue to egg comparison. Wild adult female herring gulls were

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captured in the field, sacrificed and AA-specific δ15N values were measured in tissues (muscle,

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red blood cell, liver) and compared to values in eggs laid by the same female. Herring gulls are

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colonial waterbirds that generally focus on aquatic prey but they are also opportunists that will

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shift their diets to whatever foods may be locally abundant, e.g. terrestrial foods. These two

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studies allow us to assess the AA-CSIA approach for evaluating trophic position in birds and

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their eggs; an important component of many avian-based environmental monitoring programs.

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Methods

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Diet to Bird Tissue Comparison: Captive American kestrels were individually housed in outdoor

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flight pens at the United States Geological Survey-Patuxent Wildlife Research Center (Laurel,

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Maryland, U.S.A.). The five male American kestrels used in the captive feeding study were fully

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grown 1 year-old adult birds. Kestrels fledge from the nest 28-31 days post-hatch at which time

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they are fully grown. Hence, at the time of sampling the kestrels used in this study would have

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been at constant mass for the previous 11 months. Birds were fed a constant ration during the

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study and maintained a similar level of activity in their flight pens. Therefore, with the

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exception of the first month post-hatch, the kestrels in this study would not have changed

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much in size or condition. Isotopic turnover in bird tissues is rapid compared to ectotherms but

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is tissue specific with isotopic half-lives (t1/2) differing among tissues (t1/2 is the time required

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for an isotope ratio to change 50% from its initial steady state value to a new steady state

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value). In birds, t1/2 in red blood cells > muscle > liver but due to the rapid metabolic rates of

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homeothermic birds t1/2 of all these tissues is relatively rapid ( 0.05). Relative patterns of AA-specific δ15N values in

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RBC and muscle were similar (Figure 1). The degree to which there were differences between

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δ15N values of food and kestrel tissues was AA-specific (Figure 1). In general, these differences

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reflected previous categorizations of AAs as source, trophic, or metabolic AAs.19, 44 However,

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there were some notable differences. In particular, previously categorized source AAs, Gly and

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Ser, showed significant trophic discrimination in bird tissues (Figures 1, 2). Of the trophic AAs,

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Pro exhibited the greatest increase in δ15N values from food to bird tissues (Figure 2) while the

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source AAs showing the least degree of change in δ15N between food and kestrel tissues were

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Phe, Lys, and Met (Figure 2). Mean (± 1 std dev) TDFGlu-Phe in red blood cells and muscle were

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5.39 ± 1.26‰ and 4.07 ± 1.03‰, respectively. TDFGlu-Phe derived from red blood cells was

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statistically greater than that derived from muscle (t(18) = 2.12, p = 0.048).

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Adult Tissue to Egg Comparison: Relative patterns of AA-specific δ15N values in adult female

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herring gull tissues (i.e. liver, muscle, RBC) were similar to those observed in kestrels (Figure 3).

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Patterns generally followed those expected for previously categorized source, trophic, and

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metabolic AAs.19, 44 However, similar to kestrels, Gly and Ser showed deviations from δ15N

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values expected for source AAs signalling significant trophic discrimination of nitrogen isotopes

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in body tissues and eggs of herring gulls (Figure 4). AA-specific patterns in δ15N values of herring

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gull body tissues and eggs were largely similar (Figure 4). However, differences in tissue and egg

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δ15N values did show deviations from zero for seven of the 14 muscle:egg AA comparisons, five 13 ACS Paragon Plus Environment

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of the liver:egg AA comparisons, and three of the RBC:egg comparisons (Table 2). In general,

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the trophic AA displayed greater differences between tissue and egg δ15N values. For example,

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Ala, Asp, and Glu displayed relatively high differences in tissue:egg δ15N values. Conversely,

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other trophic AAs, such as Pro, showed no differences in tissue:egg δ15N values. Inter-tissue

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differences in δ15N values were least apparent for comparisons between RBC and eggs.

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Trophic Position Estimates: Egg δ15N values for Glu and Phe were used in conjunction with the

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equation defined in Methods (red blood cell TDF, 5.4) to estimate herring gull trophic position.

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Trophic position estimates ranged from 2.8-3.7 with a mean (± 1 std. dev.) value of 3.0 (± 0.3).

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If TDFbird was the trophic discrimination factor for Glu/Phe in kestrel muscle (4.1), then trophic

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position estimates ranged from 3.3-4.6 with a mean (± 1 std. dev.) value of 3.6 (± 0.4). Discussion

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Results from this study and another recent controlled feeding study involving penguins26

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indicate that, in general, birds exhibit similar patterns in AA-specific δ15N values as those

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reported for other metazoan taxa.17-19 For example, all of the AAs previously defined as trophic

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AAs19 showed 15N enrichment in birds compared to their diets. There were, however, some

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important inter-taxa differences in those AAs previously identified as source AAs. AAs exhibiting

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“source” AAs: Gly and Ser. Of all of these AAs, Pro showed the greatest trophic discrimination

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between diet and consumer tissues (6-7 ‰) similar to what has been reported for other high

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trophic level marine endotherms.25,44 This differed from what has been observed in

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zooplankton and fish where Glu or Ala showed the greatest trophic enrichment of 15N.15, 17, 18, 23,

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N trophic discrimination in kestrels included: Ala, Asp, Glu, Ile, Leu, Pro, and Val as well as the

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discrimination associated with diet quality. Furthermore, trophic discrimination factors for Pro-

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Phe have been found to be relatively similar among consumer taxa, trophic levels, and diet

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types.17, 18, 20, 26, 44, 46 On the other hand, there was little correlation between trophic

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discrimination factors for Pro-Phe and trophic position in marine teleosts,23 and in a meta-

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analysis of AA-CSIA results including those from penguins, trophic discrimination factors for

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Pro-Phe were quite different in herbivores compared to omnivores and carnivores.24 Hence,

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these findings may point to the potential utility of Pro as an alternative to Glu in some trophic

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position calculations although with caution. Significant differences in δ15N values of Pro

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between RBC and muscle were found for the kestrels but not for the gulls studied. It is

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interesting to note that the only two AA (Asp and Pro) that showed statistically significant

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temporal differences in RBC δ15N values were also the two that exhibited the greatest degree of

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trophic discrimination in kestrels. We can only speculate on the reasons for this but one

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possibility is that change in internal isotopic fractionation of these compounds was occurring

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rapidly in kestrels. Further research, including controlled feeding studies, are needed to address

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this issue. In kestrels, tissue δ15N values of Phe, Lys, and Met showed negligible trophic enrichment of

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N; however, Phe and Lys did exhibit small decreases in δ15N values relative to diet. As

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mentioned above, evidence of trophic discrimination of 15N in Gly and Ser indicated they should

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not be considered as source AAs for birds (also see 16, 26, 44). δ15N values of Ser were greater in

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both muscle and RBC than in kestrel food while muscle Gly δ15N values were greater than in

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food. Although we did not have specific information regarding the diets of the wild herring

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gulls studied here, results for that species showed elevated δ15N values in Gly and Ser 15 ACS Paragon Plus Environment

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compared to those of other candidate source AAs. This provided further support arguing

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against the use of these AAs as source AAs in birds.

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Threonine δ15N values measured in kestrels and gulls displayed extreme 15N depletion

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relative to all other AAs. This finding was consistent with previous reports.16,19,23,44,47-49 Factors

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proposed for low Thr δ15N values included the possibility of progressive lowering of δ15N values

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with trophic position23, 50, or with longevity, or due to nutritional stress16, or because the

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organisms were associated with marine environments. Depletion of 15N in terrestrial and

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freshwater (gulls in this study were from freshwater) organisms examined here and

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elsewhere16, 50 indicate that patterns in Thr δ15N values cannot be explained by connections to

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marine food webs. Also, the kestrels in our study were fed ad lib so they should not have been

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experiencing nutritional stress. Clearly the factors underlying δ15N values in Thr require further

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study.

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Amino acid-specific patterns in δ15N values of tissues in adult female herring gulls and their

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eggs were similar indicating that eggs largely retained the isotopic compositions of adult

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tissues. This finding is important as it provides a foundation for applying the AA-CSIA approach

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to evaluate bird trophic position using eggs. Differences in δ15N values between eggs and other

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tissues were least apparent for eggs and RBC. Therefore, non-destructive sampling of RBC could

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provide similar trophic position information to that obtained through the collection of eggs.

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Both of these sampling matrices are preferable to the lethal sampling required to collect muscle

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or liver tissue. Furthermore, differences in tissue and egg δ15N values were more apparent in

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muscle and liver. Differences in Glu δ15N values between eggs and muscle or liver could result in

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trophic position estimates stemming from AA-CSIA analysis of eggs to be lower than those 16 ACS Paragon Plus Environment

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based upon the analysis of liver or muscle. A possible mechanism contributing to tissue:egg

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isotopic differences could stem from the fact that gulls are primarily income breeders with egg

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isotope patterns reflecting less dietary isotopic discrimination than body tissues. Furthermore,

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differences between body tissues and eggs could have reflected inter-tissue differences in

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isotopic routing and/or rates of isotopic turnover. All of these possibilities require further

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investigation. It is interesting to note that Pro showed no differences in tissue:egg δ15N values

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indicating that its use as a trophic AA to assess trophic position would result in consistent

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trophic position estimates regardless of the type of tissue analyzed. The use of Pro as an

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alternative to Glu in trophic position calculations has been suggested previously46 and merits

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further study provided Pro δ15N values show consistent enrichment in 15N across taxa.

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In AA-CSIA studies to date, Glu and Phe have been most widely used as trophic and source

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AAs, respectively. Recent studies have highlighted the potential value of utilizing multiple

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source and trophic AAs when estimating organism trophic position23, 24 but it is evident that

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care must be taken to ensure that AAs designated as source and trophic AAs consistently fall

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into those categories across taxa. Further research should investigate the advantages of using a

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multiple AA approach for estimating trophic position. For our estimates of trophic position we

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focus on the use of the canonical AA, i.e. Phe and Glu, which have consistently demonstrated

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source (i.e. Phe) and trophic (i.e Glu) AA characteristics across a variety of taxa.

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Accurate trophic position estimates depend on the application of taxa-specific trophic

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discrimination factors (TDF) for Phe and Glu. For lower trophic level metazoan aquatic

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organisms, TDFGlu-Phe has traditionally been thought to be on the order of 7.6‰17, 18 but recent

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research has indicated that a lower value (~5.7 ± 0.3‰) may be more appropriate for teleost

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fish.23 Furthermore, even lower TDFGlu-Phe values have been measured in marine mammals (i.e.

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seal serum and muscle)44 and birds (penguin feathers)26 or estimated (based upon expected

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trophic position) in birds (i.e. penguin whole blood)25 and elasmobranchs (i.e. stingray and

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shark muscle).51 In the kestrels studied here, TDFGlu-Phe derived from RBC was statistically

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greater than that derived from muscle. This pattern was consistent with results for harbor seals

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(Phoca vitulina) that showed greater TDFGlu-Phe values in blood serum compared to muscle.44

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Kestrel muscle TDFGlu-Phe was very similar to that reported for penguin whole blood. Regardless

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of inter-tissue differences in TDFGlu-Phe values, both TDFsGlu-Phe derived from kestrels were

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consistent with lower values reported in seals, penguins, and elasmobranchs. Different

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hypotheses have been put forward to explain these lower TDFsGlu-Phe including growth status,

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feeding ecology, and/or differences in nitrogen metabolism and excretion.24, 44, 46 In our study,

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the growth status of the kestrels examined would not have been important as the birds were

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fully grown. However, the latter two factors could have contributed to the lower TDFGlu-Phe

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values in kestrels. Diet quality and degree of carnivory24, 46 could have been important in

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contributing to the lower TDFGlu-Phe values observed here for kestrels. Similarly, differences in

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nitrogen processing and production of waste products, i.e. urea/uric acid in mammals/birds

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versus ammonium in fish (see 21, 44) could have played a role in generating lower TDFGlu-Phe

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values in kestrels. It is worth noting that the birds used in captive feeding studies to date, i.e.

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penguins and kestrels, are divergent evolutionarily yet show similar source/trophic AA patterns

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and similar TDFGlu-Phe values. This may indicate that the patterns observed here and in

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McMahon et al.26 may be broadly applicable across carnivorous avian species (see 24). To better

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understand the mechanism underlying lower TDFGlu-Phe values in birds, it will be necessary to

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conduct controlled feeding studies using omnivorous/herbivorous species. Regardless of the

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mechanisms regulating TDFGlu-Phe values, it is apparent that there are consistent differences in

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TDFGlu-Phe values among taxa that point to the need of adopting a multi-TDF approach when

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calculating trophic position across entire food webs (as advocated in 44, 52). The trophic position

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estimates generated here based upon AA-CSIA analysis of gull eggs resulted in estimates of gull

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trophic position at the Chantry Island colony that were consistent with the known feeding

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habits, i.e. considerable quantities of terrestrial prey, of birds nesting at that location.

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Application of the multi-source trophic position equation complicates the estimation of trophic

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position because it requires knowledge of the proportions of aquatic versus terrestrial food in

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the consumer diet. However, not considering the potential for terrestrial foods to be

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incorporated into Chantry Island gull diets results in unrealistically low trophic position

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estimates for these birds (Equation 2 100% aquatic diet; mean ± 1 std. dev. = 1.4 ± 0.3). The

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novel method applied here for assessing trophic position in a species that crosses ecosystem

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boundaries to feed resulted in more realistic estimates of trophic position in this omnivorous

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predator. This finding suggests that in birds where trophic position is reasonably well known,

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the proportions of aquatic and terrestrial foods might be estimated from AA-CSIA by

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rearranging equation 2.

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There is great potential to apply the AA-CSIA approach to generate baseline and trophic

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level δ15N values in eggs collected as part of avian monitoring programs. Further AA-CSIA

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analysis of samples from these programs, e.g. egg contents, possibly eggshell, could improve

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our understanding of inter-tissue similarities/differences in nitrogen isotope discrimination.

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Such information is critical for expanding the scope of avian CSIA research into fields such as

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paleoecology. Eggshells obtained from archeological sites and housed in museum collections

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could be a rich source of material for AA-CSIA studies investigating changes in bird trophic

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position over long periods of time. AA-CSIA approaches could also assist with the interpretation

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of other types of information generated from avian research and monitoring programs.

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Frequently, these involve the collection and analysis of eggs to assess spatial and temporal

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patterns in levels of biomagnifying contaminants in the environment. Organism trophic position

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is a critical factor regulating chemical exposure and uptake but most work has focused on using

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bulk δ15N values to assess organism trophic position. Application of the AA-CSIA approach offers

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a new method to estimate organism trophic position while adjusting “internally” for possible

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baseline shifts in nitrogen isotope values. Trophic position-normalized contaminant levels are

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more suitable for deducing the factors, e.g. proximity to sources, changes in contaminant

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emissions as a result of mitigation activities that regulate spatial and temporal differences in

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contaminant levels in wildlife. Clearly, opportunities to apply AA-CSIA continue to expand; here,

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we strengthen the foundation upon which to apply this approach in avian research and

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monitoring studies.

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Acknowledgments

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We thank Sandra Schultz (USGS) for assisting with the feeding and maintenance of the kestrels

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throughout the study, and Sandra, Wayne Bauer and Mary Maxey (USGS) for help with the

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collection of the kestrel tissue samples. Doug Crump, Robert Letcher and Kim Williams (ECCC)

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assisted with field collections of herring gulls. NWRC Laboratory Services staff processed the

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kestrel and herring gull samples prior to isotope analysis and conducted the egg fatty acid

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analyses. The authors also thank Kelton McMahon and four anonymous reviewers for their

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insightful comments and Dr. Ron Hites for his editorial assistance. Any use of trade, product, or

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firm names is for descriptive purposes only and does not imply endorsement by the U.S.

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Government. This is SOEST contribution number A1.

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References

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(1) Hebert, C. E.; Weseloh, D. V. C.; Idrissi, A.; Arts, M. T.; O’Gorman, R.; Gorman, O. T.; Locke,

445

B.; Madenjian, C. P.; Roseman, E. F. Restoring piscivorous fish populations in the Laurentian

446

Great Lakes causes seabird dietary change. Ecology 2008, 89, 891-897.

447 448

(2) Hebert, C. E.; Weseloh, D. V. Adjusting for temporal change in trophic position results in

449

reduced rates of contaminant decline. Environ. Sci. Technol. 2006, 40, 5624-5628.

450 451

(3) Weseloh, D. V. C.; Moore, D. J.; Hebert, C. E.; de Solla, S. R.; Braune, B. M.; McGoldrick, D.

452

Current concentrations and spatial and temporal trends in mercury in Great Lakes Herring Gull

453

eggs, 1974-2009. Ecotoxicology 2011, 20, 1644-1658.

454 455

(4) Braune, B. M.; Gaston, A. J.; Hobson, K. A.; Gilchrist, H. G.; Mallory, M. L. Changes in food

456

web structure alter trends of mercury uptake at two seabird colonies in the Canadian Arctic.

457

Environ. Sci. Technol. 2014, 48, 13246−13252.

458 459

(5) Boecklen, W. J.; Yarnes, C. T.; Cook, B. A.; James, A. C. On the use of stable isotopes in

460

trophic ecology. Annu. Rev. Ecol. Evol. Syst. 2011, 42, 411–440

461

21 ACS Paragon Plus Environment

Environmental Science & Technology

462

(6) Post, D. M. Using stable isotopes to estimate trophic position: models, methods, and

463

assumptions. Ecology 2002, 83, 703–718.

464 465

(7) Cabana, G.; Rasmussen, J. B. Modelling food chain structure and contaminant

466

bioaccumulation using stable nitrogen isotopes. Nature (Lond.), 1994, 372, 255–257.

467 468

(8) Woo, K. J.; Elliott, K. H.; Davidson, M.; Gaston, A. J.; Davoren, G.K. Individual specialization in

469

diet by a generalist marine predator reflects specialization in foraging behavior. J. Animal Ecol.

470

2008, 77, 1082–1091.

471 472

(9) Hebert, C. E.; Weseloh, D. V. C.; Gauthier, L. T.; Arts, M. T.; Letcher, R. J. Biochemical tracers

473

reveal intra-specific differences in the food webs utilized by individual seabirds. Oecologia

474

2009, 160, 15–23.

475 476

(10) Klein, R.; Bartel-Steinbach, M.; Koschorreck, J.; Paulus, M.; Tarricone, K.; Teubner, D.;

477

Wagner, G.; Weimann, T.; Veith, M. Standardization of egg collection from aquatic birds for

478

biomonitoring – A critical review. Environ. Sci. Technol. 2012, 46, 5273-5284.

479 480

(11) Hebert, C. E.; Norstrom, R. J.; Weseloh, D. V. A quarter century of environmental

481

surveillance: the Canadian Wildlife Service’s Great Lakes Herring Gull Monitoring Program.

482

Environ. Rev. 1999, 7, 147-166.

483

22 ACS Paragon Plus Environment

Page 22 of 38

Page 23 of 38

Environmental Science & Technology

484

(12) Hebert, C. E.; Campbell, D.; Kindopp, R.; MacMillan, S.; Martin, P.; Neugebauer, E.;

485

Patterson, L.; Shatford, J. Mercury trends in colonial waterbird eggs downstream of the oil

486

sands region of Alberta, Canada. Environ. Sci. Technol. 2013, 47, 11785-11792.

487 488

(13) Toschik, P. C.; Rattner, B. A.; McGowan, P. C.; Christman, M. C.; Carter, D. B.; Hale, R. C.;

489

Matson, C. W., Ottinger, M. A. Effects of contaminant exposure on reproductive success of

490

ospreys (Pandion haliaetus) nesting in Delaware River and Bay, USA. Environ. Toxicol. Chem.

491

2005, 24, 617-628.

492 493

(14) Lazarus, R. L.; Rattner, B. A.; McGowan, P. C.; Hale, R. C.; Schultz, S. L.; Karouna-Renier, N.

494

K.; Ottinger, M. A. Decadal re-evaluation of contaminant exposure and productivity of ospreys

495

(Pandion haliaetus) nesting in Chesapeake Bay regions of concern. Environ. Pollut. 2015, 205,

496

278-290.

497 498

(15) Macko, S. A.; Uhle, M. E.; Engel, M. H.; Andrusevich, V. Stable nitrogen isotope analysis of

499

amino acid enantiomers by gas chromatography/combustion/isotope ratio mass spectrometry.

500

Anal. Chem. 1997, 69, 926–929.

501 502

(16) Hare, P. E.; Fogel, M. L.; Stafford Jr., T. W.; Mitchell, A. D.; Hoering, T. C. The isotopic

503

composition of carbon and nitrogen in individual amino acids isolated from modern and fossil

504

proteins. J. Archaeol. Sci. 1991, 18, 277–292.

505

23 ACS Paragon Plus Environment

Environmental Science & Technology

506

(17) Chikaraishi, Y.; Ogawa, N. O.; Kashiyama, Y.; Takano, Y. and others. Determination of

507

aquatic food-web structure based on compound-specific nitrogen isotopic composition of

508

amino acids. Limnol. Oceanogr. Methods 2009, 7, 740–750.

509 510

(18) McClelland, J. W.; Montoya, J. P. Trophic relationships and the nitrogen isotopic

511

composition of amino acids in plankton. Ecology 2002, 83, 2173–2180

512 513

(19) Popp, B. N.; Graham, B. S.; Olson, R. J.; Hannides, C. C. et al. Insight into the trophic ecology

514

of yellowfin tuna, Thunnus albacares, from compound-specific nitrogen isotope analysis of

515

proteinaceous amino acids. In Stable isotopes as indicators of ecological change; Dawson, T.,

516

Siegwolf, R., Eds.; Elsevier, Amsterdam 2007; pp 173–190.

517 518

(20) Chikaraishi, Y.; Kashiyama, Y.; Ogawa, N. O.; Kitazato, H.; Ohkouchi, N. Metabolic control of

519

nitrogen isotope composition of amino acids in macroalgae and gastropods: implications for

520

aquatic food web studies. Mar. Ecol. Prog. Ser. 2007, 342, 85–90.

521 522

(21) McMahon, K. W.; McCarthy, M. D. Embracing variability in amino acid δ15N fractionation:

523

Mechanisms, implications, and applications for trophic ecology. Ecosphere, in press.

524 525

(22) McCarthy, M. D.; Benner, R.; Lee, C.; Fogel, M. L. Amino acid nitrogen isotopic fractionation

526

patterns as indicators of heterotrophy in plankton, particulate, and dissolved organic matter.

527

Geochim. Cosmochim. Acta 2007, 71, 4727−4744

24 ACS Paragon Plus Environment

Page 24 of 38

Page 25 of 38

Environmental Science & Technology

528 529

(23) Bradley, C. J; Wallsgrove, N. J.; Choy, C. A.; Drazen, J. C.; Hetherington, E. D.; Hoen, D. K .;

530

Popp, B. N. Trophic position estimates of marine teleosts using amino acid compound specific

531

isotopic analysis. Limnol. Oceanogr.: Methods 2015, 13, 476–493.

532 533

(24) Nielsen, J. M.; Popp, B. N.; Winder, M. Meta‑analysis of amino acid stable nitrogen isotope

534

ratios for estimating trophic position in marine organisms. Oecologia 2015, 178, 631-642.

535 536

(25) Lorrain, A.; Graham, B.; Menard, F.; Popp, B.; Bouillon, S.; van Breugel, P.; Cherel, Y.

537

Nitrogen and carbon isotope values of individual amino acids: a tool to study foraging ecology

538

of penguins in the Southern Ocean. Mar. Ecol. Prog. Ser. 2009, 391, 293–306.

539 540

(26) McMahon, K. W.; Polito, M. J.; Abel, S.; McCarthy, M. D.; Thorrold, S. R. Carbon and

541

nitrogen isotope fractionation of amino acids in an avian marine predator, the gentoo penguin

542

(Pygoscelis papua). Ecol. Evol. 2015, 5, 1278-1290.

543 544

(27) Fernie, K. J.; Palace, V.; Peters, L.; Basu, N.; Letcher, R. J.; Karouna-Renier, N. K.; Schultz, S.

545

L.; Lazarus, R. S.; Rattner, B. A. Investigating endocrine and physiological parameters of captive

546

American Kestrels exposed by diet to selected organophosphate flame retardants. Environ. Sci.

547

Technol. 2015, 49, 7448-7455.

548

25 ACS Paragon Plus Environment

Environmental Science & Technology

549

(28) Bond, A. L.; Diamond, A. W. Nutrient allocation for egg production in six Atlantic seabirds.

550

Can. J. Zool. 2010, 88, 1095–1102.

551 552

(29) Chikaraishi, Y.; Steffan, S. A.; Ogawa, N. O.; Ishikawa, N. F.; Sasaki, Y.; Tsuchiya, M.;

553

Ohkouchi, N. High-resolution food webs based on nitrogen isotopic composition of amino acids.

554

Ecol. Evol. 2014, 4, 2423–2449.

555 556

(30) Hebert, C. E.; Arts, M. T.; Weseloh, D. V. Ecological tracers can quantify food web structure

557

and change. Environ. Sci. Technol. 2006, 40, 5618-5623.

558 559

(31) McMeans, B. C.; Arts, M. T.; Rush, S. A.; Fisk, A. T. Seasonal patterns in fatty acids and

560

stable isotopes of Calanus hyperboreus (Copepoda, Calanoida) from Cumberland Sound, Baffin

561

Island. Mar. Biol. 2012, 159, 1095-1105.

562 563

(32) Huang, Z-B.; Leibovitz, H.; Lee, C. M.; Millar, R. Effect of dietary fish oil on omega-3 fatty

564

acid levels in chicken eggs and thigh flesh. J. Agric. Food Chem. 1990, 38, 743-747.

565 566

(33) Farrell, D. J. Enrichment of hen eggs with n-3 long-chain fatty acids and evaluation of

567

enriched eggs in humans. Amer. J. Clin. Nutr. 1998, 68, 538–544.

568

26 ACS Paragon Plus Environment

Page 26 of 38

Page 27 of 38

Environmental Science & Technology

569

(34) Napolitano, G. E. Fatty acids as trophic and chemical markers in freshwater ecosystems. In

570

Lipids in freshwater ecosystems, Arts, M.T., Wainman, B.C. Eds.; Springer-Verlag, New York,

571

New York, USA, 1998; pp 21–44.

572 573

(35) Leeson, S.; Summers, J. Ingredient evaluation and diet formulation. In Commercial poultry

574

nutrition 3rd ed., University Books, Guelph, Ontario, Canada, 2005; pp 9–76.

575 576

(36) Hibbeln, J. R.; Nieminen, L. R. G.; Blasbalg, T. L.; Riggs, J. A., Lands, W. E. M. Healthy intakes

577

of n-3 and n-6 fatty acids: Estimations considering worldwide diversity. Am. J. Clin. Nutr. 2006,

578

83 (6 Suppl), 1483S-1493S.

579 580

(37) Phillips, D. L.; Gregg, J. W. Uncertainty in source partitioning using stable isotopes. Oecologia

581

2001, 127, 171-179.

582 583

(38) Chikaraishi, Y.; Ogawa, N. O.; Ohkouchi, N. Further evaluation of the trophic level

584

estimation based on nitrogen isotopic composition of amino acids. In Earth, life, and isotopes;

585

Ohkouchi, N., Tayasu, I., Koba, K., Eds.; Kyoto Univ. Press, Kyoto, Japan 2010; pp. 37–51.

586 587

(39) Ogawa, N. O.; Chikaraishi, Y.; Ohkouchi, N. Trophic position estimates of formalin-fixed

588

samples with nitrogen isotopic compositions of amino acids: an application to gobiid fish (Isaza)

589

in Lake Biwa, Japan. Ecol. Res. 2013, 28, 697-702.

590

27 ACS Paragon Plus Environment

Environmental Science & Technology

591

(40) Still, C. J., J. A. Berry, G. J. Collatz, and R. S. DeFries, Global distribution of C3 and C4

592

vegetation: Carbon cycle implications. Global Biogeochem. Cycles 2003, 17, 6-1–6-14.

593 594

(41) Hannides, C. C. S.; Popp, B. N.; Landry, M. R.; Graham, B. S. Quantification of zooplankton

595

trophic position in the North Pacific Subtropical Gyre using stable nitrogen isotopes. Limnol.

596

Oceanogr. 2009, 54, 50–61.

597 598

(42) Cowie, G. L.; Hedges, J. I. Improved amino acid quantification in environmental samples:

599

Charge-matched recovery standards and reduced analysis time. Mar. Chem. 1992, 37, 223–238.

600 601

(43) Ueda, K.; Morgan, S. L.; Fox, A.; Gilbart, J.; Sonesson, A.; Larsson, L.; Odham, G. D-alanine as

602

a chemical marker for the determination of streptococcal cell wall levels in mammalian tissues.

603

Anal. Chem. 1989, 61, 265–270.

604 605

(44) Germain, L. R.; Koch, P. L.; Harvey, J.; McCarthy, M. D. Nitrogen isotope fractionation in

606

amino acids from harbor seals: implications for compound-specific trophic position calculations.

607

Mar. Ecol. Prog. Ser. 2013, 482, 265–277.

608 609

(45) StatSoft, Inc. STATISTICA (data analysis software system), version 12. Tulsa, OK, USA, 2013.

610

28 ACS Paragon Plus Environment

Page 28 of 38

Page 29 of 38

Environmental Science & Technology

611

(46) McMahon K. W.; Elsdon, T.; Thorrold, S. R.; McCarthy, M. Trophic discrimination of

612

nitrogen stable isotopes in amino acids varies with diet quality in a marine fish. Limnol.

613

Oceanogr. 2015, 60, 1076-1087.

614 615

(47) Sherwood, O. A.; Lehmann, M. F.; Schubert, C. J.; Scott, D. B.; McCarthy, M. D. Nutrient

616

regime shift in the western North Atlantic indicated by compound-specific δ15N of deep-sea

617

gorgonian corals. Proc. Natl. Acad. Sci. USA 2011, 108, 1011−1015.

618 619

(48) Petzke, K. J.; Boeing, H.; Metges, C. C. Choice of dietary protein of vegetarians and

620

omnivores is reflected in their hair 13C and 15N abundance. Rapid Commun. Mass Spectrom.

621

2005, 19, 1392-1400.

622 623

(49) Petzke, K. J.; Feist, T.; Fleig, W. E.; Metges, C. C. Nitrogen isotopic composition of hair

624

protein is different in liver cirrhotic patients. Rapid Commun. Mass Spectrom. 2006, 20, 2973-

625

2978.

626 627

(50) Styring, A. K.; Sealy, J. C.; Evershed, R. P. Resolving the bulk δ15N values of ancient human

628

and animal bone collagen via compound-specific nitrogen isotope analysis of constituent amino

629

acids. Geochim. Cosmochim. Acta 2010, 74, 241−251.

630

29 ACS Paragon Plus Environment

Environmental Science & Technology

631

(51) Dale, J. J.; Wallsgrove, N. J.; Popp, B. N.; Holland, K. N. Nursery habitat use and foraging

632

ecology of the brown stingray Dasyatis lata determined from stomach contents, bulk and

633

amino acid stable isotopes. Mar. Ecol. Prog. Ser. 2011, 433, 221–236.

634 635

(52) Hoen, D. K.; Kimb, S. L.; Hussey, N. E.; Wallsgrove, N. J.; Drazen, J.C.; Popp, B. N. Amino acid

636

15

637

453, 76-83.

N trophic enrichment factors of four large carnivorous fishes. J. Exp. Mar. Biol. Ecol. 2014,

30 ACS Paragon Plus Environment

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Page 31 of 38

Environmental Science & Technology

638

Table 1. Mean (± 1 std dev) δ15N values in amino acids (AAs) measured in tissues of captive

639

American kestrels. Red blood cells (RBC) were collected at weekly intervals beginning two

640

weeks prior to birds being sacrificed (period 1 – 2 weeks prior to sacrifice, period 2 - 1 week

641

prior to sacrifice, period 3 – time of sacrifice). At sacrifice, muscle was also collected. AA-

642

specific δ15N values in the kestrel diet are also shown as is the change in δ15N values between

643

diet and tissue at the time of sacrifice (RBC versus diet: Δδ15NR-D, muscle versus diet Δδ15NM-D).

644

Sample size for all AAs in kestrels and in food is the same as Ala except where indicated.

645

Statistically significant inter-period differences in AA δ15N values in RBC are indicated by

646

superscript letters beside means. Statistically significant differences in mean δ15N values of RBC

647

and muscle at time of sacrifice are indicated in bold for individual AA (Asp, Gly, Leu, Pro, Thr).

648

The results of one sample t-tests (α = 0.05) to determine whether individual AA Δδ15NR-D and

649

Δδ15NM-D values were significantly different from 0‰ are indicated (ns P > 0.05, *P < 0.05, **P