Relationships between organohalogen contaminants and blood plasma clinical–chemical parameters in chicks of three raptor species from Northern Norway

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Ecotoxicology and Environmental Safety 73 (2010) 7–17

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Ecotoxicology and Environmental Safety

0147-65

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adrian.c

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Relationships between organohalogen contaminants and blood plasmaclinical–chemical parameters in chicks of three raptor species fromNorthern Norway

Christian Sonne a,n, Jan Ove Bustnes b, Dorte Herzke c, Veerle L.B. Jaspers d, Adrian Covaci d,Duncan J. Halley e, Truls Moum f, Igor Eulaers d, Marcel Eens d, Rolf A. Ims b, Sveinn A. Hanssen b,Kjell Einar Erikstad b, Trond Johnsen b, Lisbeth Schnug g, Frank F. Rig�et a, Asger L. Jensen h

a Arhus University, National Environmental Research Institute, Department of Arctic Environment, Frederiksborgvej 399, PO Box 358, DK-4000 Roskilde, Denmarkb Norwegian Institute for Nature Research, Unit for Arctic Ecology, The Polar Environmental Centre, NO-9296 Tromsø, Norwayc Norwegian Institute for Air Research, The Polar Environmental Centre, NO-9296 Tromsø, Norwayd University of Antwerp, Ethology Research Group, Department of Biology and Toxicological Centre, B-2610 Antwerp, Belgiume Norwegian Institute for Nature Research, Department of Terrestrial Ecology, Tungasletta 2, NO-7485 Trondheim, Norwayf Bodø University College, Faculty of Biosciences and Aquaculture, NO-8049 Bodø, Norwayg Norwegian Institute for Agricultural and Environmental Research, Soil and Environment Division, Fr. A. Dahlsvei 20, NO-1432 As, Norwayh Department of Basic Animal and Veterinary Sciences, Faculty of Life Sciences, University of Copenhagen, Frederiksberg, Denmark

a r t i c l e i n f o

Article history:

Received 3 April 2009

Received in revised form

25 August 2009

Accepted 29 August 2009Available online 3 October 2009

Keywords:

ALAT

ALKP

Cholesterol

DDT

GGT

Golden eagle

Goshawk

PCBs

Uric acid

White-tailed eagle

13/$ - see front matter & 2009 Elsevier Inc. A

016/j.ecoenv.2009.08.017

esponding author. Fax: +45 4630 1914.

ail addresses: [email protected] (C. Sonne), jan.o.b

[email protected] (A. Covaci), duncan.halley@ni

s), [email protected] (R.A. Ims), sveinn.a.hans

[email protected] (L. Schnug), [email protected] (

: http://www.neri.dk (C. Sonne).

a b s t r a c t

Organohalogen contaminants (OHCs) may affect various physiological parameters in birds including

blood chemistry. We therefore examined blood plasma clinical–chemical parameters and OHCs in

golden eagle, white-tailed eagle and goshawk chicks from Northern Norway. Correlation analyses on

pooled data showed that alkaline phosphatase (ALKP), glucose and creatinine were significantly

negatively correlated to various OHCs (all: po0.05; r: �0.43 to �0.55; n=23), while alanine

aminotransferase (ALAT), total protein, cholesterol, uric acid, total bilirubin, ratios protein:creatinine

and uric acid:creatinine were significantly positively correlated to various OHCs (all: po0.05; r: 0.43–

0.96). Based on these relationships, we suggest that the OHC concentrations found in certain raptor

chicks of Northern Scandinavia may impact blood plasma biochemistry in a way that indicates impacts

on liver, kidney, bone, endocrinology and metabolism. In order to elaborate further on these

relationships and mechanisms, we recommend that a larger study should take place in the near future.

& 2009 Elsevier Inc. All rights reserved.

1. Introduction

Homeostasis is important for all vertebrate species in order tomaintain the function of organ systems that are critical forsurvival and reproduction. Infectious diseases, genetic defects andenvironmental stressors are all factors that induce perturbationsin blood biochemistry and in the homeostasis of vertebratespecies in general (Braun, 2003; Harr, 2002; Richards and

ll rights reserved.

[email protected] (J.O. Bustnes), dor

na.no (D.J. Halley), Truls.Moum@h

[email protected] (S.A. Hanssen), kjell.e

F.F. Rig �et), [email protected] (A.L. Jens

Proszkowiec-Weglarz, 2007; Schulz et al., 2000). Environmentalstressors include extreme sound, temperatures, starvation, dehy-dration and environmental pollutants, such as organohalogencontaminants (OHCs) and heavy metals, that all have an impacton physiology and behaviour (AMAP, 1998, 2004; Chrousosand Gold, 1992; Johnson et al., 1992; Sharit and Salvendy, 1982).OHCs include polychlorinated biphenyls (PCBs), organochlorinepesticides (OCPs), brominated flame retardants (BFRs) and

[email protected] (D. Herzke), [email protected] (V.L. Jaspers).

ibo.no (T. Moum), [email protected] (I. Eulaers), [email protected]

[email protected] (K. Einar Erikstad), [email protected] (T. Johnsen).

en).

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C. Sonne et al. / Ecotoxicology and Environmental Safety 73 (2010) 7–178

perfluorinated compounds (PFCs). Due to transport mechanismsand chemical and biological properties, these compounds areretained within organisms and tend to biomagnify at the top ofmarine and terrestrial food webs (Muir et al., 1992; Norstrom andMuir, 1994; Rocca and Mantovani, 2006). OHCs are present in themarine environments of the Northern Hemisphere and areparticularly high in industrialised areas, such as the Baltic Sea.However, OHCs are also transported by atmospheric and seacurrent mechanisms from lower latitudes, such as Eurasia andNorth America, toward the north (AMAP, 1998, 2004; Colborn,2004; Macdonald et al., 2003, 2005) and consequently lipidsoluble organohalogen pollutants biomagnify in the marine foodchains of the Arctic. Top predators, such as polar bears (Ursus

maritimus) and raptors, accumulate high levels of OHC residuesthat may have adverse health impacts (AMAP, 1998, 2004).

Raptors including white-tailed eagles (Haliaeetus albicilla),golden eagles (Aquila chrysaetos) and northern goshawks (Accipiter

gentilis) are top predators of either marine or terrestrial foodwebs. As a result, significant OHC concentrations are found inspecific birds of prey (Colborn, 1991; Donaldson et al., 1999;Herzke et al., 2002, 2005). For example, white-tailed eagles relymainly on marine fish-eating seabird species, such as greatcormorant (Phalacrocorax carbo) and several gull species (Laridae)and also feed on a variety of marine fish species of which themajority is picked up from gulls or fishing vessels (Willgohs,1961). Studies have shown that several marine bird species andfish from Northern Norway are heavily polluted with OHCs(Bustnes et al., 2008; Helberg et al., 2005; Julshamn et al.,2004), which subsequently accumulate in eagles and hawks(Gjershaug et al., 2008). Coastal goshawks and golden eagles canalso prey on seabirds, but usually rely on terrestrial food sources.The primary main prey species in Northern Norway includeamongst others redwing (Turdus iliacus), fieldfare (Turdus pilaris),carrion crow (Corvus corone cornix), grouse species (Lagopus spp.;Tetrao spp.) and small mammals such as mountain hare (Lepus

timidus) and red squirrels (Sciurus vulgaris) (Grønnesby andNygard, 2000). The golden eagle’s diet is dominated by grouse,with mountain hares and reindeer (Rangifer tarandus) as im-portant secondary sources, the latter often found as carrion(Johnsen et al., 2007; Halley et al., 2007). Terrestrial prey speciesare all relatively low in OHCs compared with food from themarine environment (AMAP, 1998, 2004). Therefore, raptors thathave specialised on the terrestrial food web are likely to be lowerin OHCs compared with the marine predator species (Gjershauget al., 2008; Herzke et al., 2002, 2005).

The mode of toxic action of OHCs on vertebrate organisms isvariable and includes responses of neuro-endocrine pathwayssuch as the hypothalamic–hypophysis–target organ axis and up-regulation of liver cytochrome (CYP) metabolism (Bandiera et al.,1997; Grasman et al., 2000; Henriksen et al., 2000; Kennedy et al.,2003; Letcher et al., 1996; Østby et al., 2005). Briefly, thesechanges lead to disruptions of specific endogenous peptide andsteroid hormones like thyroid hormones T3/T4, estrogens andtestosterone with fatal consequences for development, reproduc-tive success and immune competence (Colborn, 2004; Darnerudet al., 2001; Erikstad et al., 2009; Guvenius et al., 2002; Hamerset al., 2006; Harju et al., 2007; Letcher et al., 2000; Verreault et al.,2004, 2006, 2007). A fatal impact on raptor species is a thinning ofegg-shells that subsequently results in low reproductive rates dueto fragile/porous eggs although the exposure that caused this toxicresponse seems to have decreased over the last 10 years (Elliottand Martin, 1994; Falk et al., 2006; Helander et al., 2002;Scharenberg and Looft, 2004). Moreover, studies of birds andmammals have shown that OHCs have a toxic impact on liver andkidney function and the general homeostasis measured by bloodclinical–chemical parameters (Dieter et al., 1977; Fischbein, 1985;

Hayes et al., 1984; Kutlu et al., 2007). Due to the low endocrineplasticity and low homeostatic buffering capacity at the foetal andneonatal stages, these effects are probably most severe at thesedevelopmental stages (Damstra et al., 2002; Grandjean andLandrigan, 2006).

To further investigate the potential OHC impacts on the healthof raptors, we conducted a study on blood plasma clinical–chemical parameters in golden eagle, white-tailed eagle andgoshawk chicks in the Troms and Finnmark counties of NorthernNorway (Fig. 1). The study species and nest locations were chosenin order to have breeding pairs and chicks that were supposedlyhigh (white-tailed eagles breeding in the coastal environment)and low (terrestrial goshawks and golden eagles) in their OHCbody burdens due to their reliance on the marine versusterrestrial food webs in this area (Cramp and Simmons, 1980).The present study reports on the relationship between bloodplasma OHCs and biochemical parameters and thereby thepotential health impacts on the chicks of these three raptorspecies.

2. Materials and methods

The study was conducted on white-tailed eagles and northern goshawks from

Troms County, and golden eagles from Finnmark County, Northern Norway, from

April to the end of June 2008. The study area ranged from 691 to 711N and from 181

to 261E (Fig. 1). Nests of the three species were checked for breeding activity from

late March to the middle of May using binoculars and telescopes, whilst keeping a

distance to avoid disturbing the breeding pairs. The presence of at least one bird

lying on the nest was used as a confirmation of breeding activity.

2.1. Study design and sampling

In winter 2008 (January–April), a large number of nests of all three species

were visited and birds with territorial behaviour were recorded. In late April and

early May it was determined if the birds had laid eggs. In May–June nestlings in

successful nests were inspected for the first time, and a second time at beginning of

July shortly before fledging, approximately 2 weeks later. Due to variation in

hatching date, the first visit took place at a nestling age of between 1 and 3 weeks.

The nestlings (2 golden eagles, 16 goshawks and 5 white-tailed eagles) were

lowered from the nest in a nylon bag and blood (0.1–4.0 mL) was sampled from the

brachial vein during the second visit after which the chicks were returned to their

nests. Blood was centrifuged at 8000 rpm for 10 min and 1 mL supernatant plasma

was transferred to a sterile 1.5 mL Eppendorfs tube and frozen at �20 1C the same

day prior to analyses. The study was approved by the National Animal Research

Authority of Norway.

2.2. Analyses of blood plasma clinical–chemical parameters

The analyses were conducted at the Central Clinical Laboratory at the

Department of Small Animal Clinical Sciences, Faculty of Life Sciences, University

of Copenhagen and included the following 19 components: albumin (Alb; g/L),

glucose (Glu; mmol/L), total protein (TP; g/L), alkaline phosphatase (ALKP; U/L),

alanine aminotransferase (ALAT; U/L), total bilirubin (TB; mmol/L), fructosamine

(Fructo; mmol/L), cholesterol (Cho; mmol/L), creatinine (Cre; mmol/L), inorganic

phosphate (Iph; mmol/L), bile acids (BA; mmol/L), amylase (Amy; U/L), urea (Urea;

mmol/L), gamma glutamyl transferase (GGF; U/L), calcium (Ca; mmol/L),

magnesium (Mg; mmol/L), uric acid (UA; U/L), sodium (Na; mmol/L) and

potassium (K; mmol/L). The analyses were routinely conducted at the laboratory

using an automated spectrophotometrical analyser also containing ion-selective

electrodes (ADVIA 1800, Siemens). All assays were subjected to daily internal and

quarterly external quality control. Only results from accepted analytical runs are

reported here. Information on methods can be found at the Department of Small

Animal Clinical Sciences (http://www.life.ku.dk).

2.3. OHC analyses

Details regarding the analyses can be found in Herzke et al. (2005) and Gotsch

et al. (2004). Briefly, plasma samples from nestlings were analyzed for a set of OCs

(organochlorines: PCBs [polychlorinated biphenyls: CB-18, CB-28, CB-99, CB-101,

CB-105, CB-118, CB-138, CB-153, CB-180, CB-183, CB-187, CB-194], p,p0-DDE

[dichlorodiphenyldichloroethylene], b-HCH [hexachlorohexane], HCB [hexachlor-

obenzene], heptachlor epoxide, CHLs [chlordanes: t-chlordane, c-chlordane,

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Fig. 1. Map identifying Troms and Finnmark provinces in Northern Norway from which we obtained blood plasma samples of golden eagles (n=2), goshawks (n=16) and

white-tailed eagles (n=5).

C. Sonne et al. / Ecotoxicology and Environmental Safety 73 (2010) 7–17 9

oxy-chlordane, t-Nonachlor, c-Nonachlor] and Mirex), PBDEs (polybrominated

diphenylethers: BDE-28, BDE-47, BDE-99, BDE-100, BDE-153, BDE-154), TBA

(tribromoanisole) and perfluorinated compounds (PFCs: PFHpS, PFOS, PFDcS,

PFPA, PFOA, PFNA, PFDcA, PFUnA, PFDoA, PFTriA). The analyses of environmental

contaminants in blood plasma were carried out at the Norwegian Institute of Air

Research (Norsk Institutt for Luftforskning, NILU) in Tromsø and followed standard

procedures. Briefly, in order to extract OHCs from the plasma, an aliquot of each

sample was denatured with saturated ammonium sulphate solution and ethanol

after the addition of an internal standard solution (13C-labelled compounds). The

solution was extracted twice with n-hexane and the combined extract was further

cleaned up by Florisil column chromatography. To all samples, octachloronaphta-

lene was added as recovery standard prior to analyses. Samples were quantita-

tively analyzed by gas chromatography coupled with a mass selective detector

(GC/MS). For quantification of all compounds, crystalline reference standards was

obtained from Cambridge Isotope Laboratories (Woburn, MA, USA). Solvents of

pesticide grade were employed (E. Merck, Darmstadt, Germany). 13C-labeled

compounds were used as internal standards representing each group of analytes,

containing between 77 and 500 pg/mL of 13C-p,p0-DDE, 13C-p,p0-DDT, 13C-labeled

CB-28, -52, -101, -118, -153 and -180, 13C-labeled trans-nonachlor, HCB and b-HCH.

The results were not corrected for recovery. PBDEs and TBA were analysed by

applying negative chemical ionisation (NCI) in the GC/MS. The masses m/z 79

and 81 were analysed for brominated compounds in addition to comparison

of retention times of standard compounds for each individual PBDE congener. 13C-

labeled CB-118 was used for quantification.

Prior to PFC analysis, ca. 0.2 g of plasma was fortified with internal standard13C-labeled PFOS and PFOA (Wellington, US) and extracted with 1 mL acetonitrile

for three times 10 min in an ultrasonic bath. Vortex was applied in between the

application of the ultrasound. After centrifugation, 1 mL of the supernatant

solution was added to 25 mg ENVI-Carb and 50 mL glacial acetic acid and vortexed

thoroughly. After additional centrifugation at 10,000 rpm for 10 min, 0.5 mL of the

solution was transferred in an autoinjector vial. Prior to analysis, 3,7-dimethyl-

perfluorooctanoic acid (3,7-di-methyl-PFOA, 97%, ABCR; Germany) and 0.5 mL of a

22 mM ammonium acetate solution was added to each sample. We analysed the

ionic PFCs: perfluorocarboxyl acids (PFCA) with a carbon chain containing 4–13

carbons, as well as perfluorosulphonates (PFS) as perfluorobutane-, perfluorohex-

ane-, perfluorooctane-, and perfluordecane-sulphonate in addition to perfluor-

ooctane sulfonamide (PFOSA). All standards were purchased as crystalline

substances from Aldrich, Fluka and ABCR with purities greater than 95%. Aliquots

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C. Sonne et al. / Ecotoxicology and Environmental Safety 73 (2010) 7–1710

(25 mL) were injected automatically on a HPLC (Agilent 1100; Agilent Technologies,

Palo Alto, CA) coupled to ESI time-of-flight-high-resolution MS in the negative ion

mode (HPLC–ToF–HRMS ESI) (LCT, Micromass, Manchester, England). The values

for the pollutant concentrations are all given in pg/g wet weight (ww).

2.4. Statistical analyses

SAS statistical software package (SAS 9.1 and enterprise guide V4.0, SAS

Institute Inc., Cary, NC, USA) was used for the initial statistical analyses. All OHC

and blood clinical–chemical parameters (BCCP) data were log-transformed to meet

the requirement of equal variance and homogeneity of the data distribution

between groups (Zar, 1984), and the level of significance was set to a=0.05, while

0.05opo0.1 was considered a trend. First, a non-parametric Kruskal–Wallis test

was applied to test for differences in mean concentrations of OHCs (P

PCB, p,p0-

DDE, b-HCH, HCB, heptachlor epoxide, chlordanes [P

CHL], Mirex,P

PBDE, TBA

andP

PFC) and BCCPs between species, which is applicable despite the low

samples size of 2, 5, 16 individuals and the relative uncertainty of the w2

approximation according to Siegel (1988). Shapiro–Wilk tests showed that pooled

data (n=23) were normally distributed and therefore Pearson’s correlation analysis

was applied to test for the relationships between OHCs and BCCPs. Only in cases

with species differences in OHC and BCCP concentrations the correlation analyses

were split into each species; and subsequently the non-parametric Spearman rank

test was applied to white-tailed eagles. The statistics were not Bonferroni

corrected in order not to introduce type II errors (i.e. rejecting true null-

hypothesis) (Perneger, 1998) and as each specific OHCs vs. BCCPs was of clinical/

biological interest rather than just the pattern.

A principal component analysis (PCA) was applied to investigate the patterns

of BCCPs in the three raptorial bird species. The PCA was performed on the

correlation matrix and differences in mean scores of the PCA components between

bird species were tested by analysis of variance (ANOVA) followed by Tukey’s

multiple comparisons of means.

The multiple relationships between contaminants (OHCs) and BCCPs were

analysed by redundancy analysis (RDA). The RDA expresses how much of the

variance in one data set (BCCPs) can be explained by the other data set (OHCs). The

RDA is a PCA of the predicted values of a multivariate regression with BCCPs as

dependent variables and OHCs as independent variables. For a detailed description

of RDA, see Ter Braak and Prentice (1988). Because of the relative low number of

samples, the variables included in the analysis were limited to the following: ALKP,

ALAT, amylase, glucose, albumin, total protein, cholesterol, bile acid, uric acid, total

bilirubin, magnesium, potassium, creatinine, SPCB, p,p0-DDE, b-HCH, HCB,

heptachlor epoxide, SCHL, Mirex, TBA, SPBDE and SPFC. The PCAs and RDAs

were performed using the free software R version 2.8.1.

3. Results

3.1. Blood plasma clinical–chemical parameters

Twenty-two blood plasma clinical–chemical parameters(BCCPs) were measured in all 23 raptor specimens (Table 1). Insummary, these were composed of 3 liver enzymes, 1 digestiveenzyme, 2 protein groups, erythrocyte metabolism wasteproducts, cholesterol, 2 carbohydrates, creatinine (muscleprotein metabolism) and 5 electrolytes/minerals. In addition,protein:creatinine, urea:creatinine and uric acid:creatinine wereintroduced as supportive parameters for renal functioning. Ingeneral, the species differences were few and inconsistent,although fructosamine, cholesterol, gamma glutamyl transferase,sodium and potassium differed significantly between species(Kruskal–Wallis: all po0.05 and w246.6) (Table 1, Fig. 2).Therefore, the statistical analyses of OHCs versus BCCPs wereconducted separately for these five BCCPs within goshawks(Pearson’s correlation analysis) and white-tailed eagles(Spearman rank test). For the remaining 17 BCCPs, data werepooled across species in order to increase the statistical power ofthe analyses with an ntotal=23.

3.2. OHC concentrations

Ten distinct OHC classes/types were measured in blood plasmaof all three raptor species (Table 2). These were

PPCB, p,p0-DDE,

b-HCH, HCB, heptachlor epoxide, chlordanes (P

CHL), Mirex,

PPBDE, TBA and

PPFC. The mean blood plasma OHC

concentrations (pg/mL ww) are shown for each species in Fig. 3.It is seen that the most dominating OHC groups were PCBs, PFCsand p,p0-DDE and the concentrations generally increased white-tailed eagles ‘‘goshawks’’ golden eagles except for p,p0-DDE andb-HCH. In all three species, the most dominating PCB congenerswere the higher chlorinated CB-138, �153 and �180 whilefor PBDEs it was BDE-47, �99 and �100. Oxy-chlordane andt-nonachlor were the chlordanes found in highest concentrationsin all three species. PFOS was the most dominating fluorinatedcompound and, together with PFNA, the only PFC found in allspecimens. PFPA was only found in a single goshawk, while PFDcSwas found in three goshawks and one white-tailed eagle. The PFCsincreased in the following order: PFDcS�PFHpS)PFDoA�PFTriA�PFPA)PFDcA�PFOA)PFUnA)PFNA)PFOS. From Table 2 itcan be seen that the OHC difference between white-tailed eaglesversus goshawks is ranging up to a factor ca. 1.5–15 (only p,p0-DDEwas lowest in the white-tailed eagles), whilst golden eagleconcentrations for some compounds were comparable to thoseof goshawks (e.g. Mirex) and a factor 20–60 lower than bothgoshawks and white-tailed eagles (e.g. PFCs). There were,however, only significant differences in concentrations ofchlordanes, TBA and PFCs between species with white-tailedeagles carrying the highest concentrations followed by goshawksand golden eagles, respectively (Kruskal–Wallis: all po0.05 andw246.2) (Table 2, Fig. 3). Therefore, the statistical analyses ofOHCs vs. BCCPs were conducted separately for chlordanes, PFCsand TBA within each species. For the remaining 7 OHCs, data werepooled across species in order to increase the statistical power ofthe analyses with an ntotal=23.

3.3. BCCPs versus contaminant concentrations

Due to species-specific differences, the relationships betweenchlordanes, PFCs, TBA and BCCPs, respectively, were evaluatedseparately for goshawks and white-tailed eagles. This was also thecase for OHCs and fructose, cholesterol, gamma glutamyltransferase, sodium and potassium, respectively. In case of goldeneagles the sample size was too small (n=2) to conduct anyseparate statistical analyses. All results are summarised in Table 3in which only significant differences and trends are given. Thepooled species samples showed a highly negative correlation ofglucose to PCBs (po0.01, r=�0.53, n=23). Specifically ingoshawks, cholesterol (p=0.002, r=0.72, n=16) was highlypositively correlated to PCBs and that was also the case forwhite-tailed eagles (p=0.03, r=0.85, n=5).

For p,p0-DDE, a positive correlation was found to the pooledsamples of alanine aminotransferase (ALAT) (p=0.01, r=0.52,n=23), total bilirubin (p=0.03, r=0.46, n=23) and protein:creati-nine (p=0.04, r=0.43, n=23). HCB was positively correlated to uricacid (p=0.005, r=0.57, n=23) and uric acid:creatinine (p=0.003,r=0.58, n=23). Specifically in goshawk, HCB was positivelycorrelated to cholesterol (po0.01, r=0.74, n=23). Heptachlorepoxide showed a positive correlation with uric acid:creatinine(p=0.04, r=0.43, n=23). Specifically in goshawks, heptachlorepoxide was positively correlated to cholesterol (po0.01,r=0.63, n=16) and a similar positive trend was found for totalprotein (p=0.06, r=0.48, n=16).

In goshawks, cholesterol was highly positively correlated tochlordanes (po0.01, r=0.65, n=16) and a similar trend was foundfor total protein (p=0.07, r=0.47, n=16). In white-tailed eagles,chlordanes were positively correlated to cholesterol (p=0.04,r=0.82, n=5). Regarding Mirex, three significant results werefound in the pooled samples. These were glucose (p=0.05,r=�0.43, n=20) and ALKP (p=0.04, r=�0.45, n=20) being

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Table 1Summary statistics [median(min–max)] of blood plasma clinical–chemical parameters in chicks of golden eagles, white-tailed eagles and goshawks from Northern Norway.

Parameter (concentration) Golden eagles (n=2). Goshawk (n=16) White-tailed eagles (n=5)

Alkaline phosphatase (ALKP; U/L) 1331–1595 1381 (740–1451) 1247 (974–1632)

Alanine aminotransferase (ALAT; U/L) 12–16 18 (14–27) 15 (14–27)

Gamma glutamyl transferase (GGT; U/L)n 4–5 5 (2–8) 4.8271.68 (2–8)

Amylase (U/L) 483–569 772 (365–813) 493 (416–1136)

Albumin (g/L) 13.9–14.5 13 (11.7–14) 12.7 (11–14.4)

Total protein (g/L) 29.8–32.8 27 (25.5–31.2) 27.6 (23.3–29.4)

Uric acid (U/L) 367.5–967.3 715 (367–808) 611 (207–1200)

Urea (mmol/L) 1.64–2.89 3 (1.08–11.9) 2.2 (2.15–4.41)

Urea:creatinine 0.1–0.15 0.2 (0.14–0.35) 0.15 (0.09–0.57)

Uric acid:creatinine 33.3–33.4 41 (7.9–92) 31 (24–62)

Protein:creatinine 1.13–2.71 2 (1.13–2.71) 2.3 (1.07–2.44)

Total bilirubin (mmol/L) 8.3–17.1 16 (13.5–19.3) 16 (9.9–26)

Bile acids (mmol/L) 37.2–57.5 55 (43.7–75.8) 50 (44.4–158)

Cholesterol (mmol/L)n 4.2–4.8 4 (3.15–5.78) 6.11 (6.01–9.18)

Glucose (mmol/L) 16.9–18.1 17 (14.3–17.4) 15.8 (15.5–20.7)

Fructoseamine (mmol/L)n 173.8–184 154 (173–210) 187 (127–223)

Creatinine (mmol/L) 11–29 17 (12–25) 13 (8–26)

Inorganic phosphate (mmol/L) 2.05–2.17 2 (1.77–2.21) 2 (1.5–2.44)

Calcium (mmol/L) 2.33–2.47 2 (2.26–2.62) 2.45 (2.26–2.62)

Magnesium (mmol/L) 0.87–0.89 0.8 (0.79–0.87) 0.8 (0.73–1.16)

Sodium (mmol/L)n 155.5–155.8 153 (149–155) 152 (150–156)

Potassium (mmol/L)n 1.86–2.9 2 (2.23–4.95) 2.9 (0.75–3.03)

Note the statistically significant differences in five of the blood clinical–chemical parameters between the three raptor species.

n Statistically significant difference between species the three species (po0.05, Kruskal–Wallis).

0

1

10

100

1000

10000

Album

inG

lucoseTotal proteinA

LKP

ALAT

Tot bilirubinFructosam

ineC

holesterolC

reatinineInorganic phosphateB

ile acidA

mylase

Urea

GG

TC

alciumM

agnesiumU

ric acidS

odiumP

otassiumU

rea:Creat

Uric acid:C

reatP

rot:Creat

BCCPs

(U/L

, mm

ol/L

, mm

ol/L

)

Golden eagle (n = 2)Goshawk (n = 16)Sea eagle (n = 5)

*

**

**

Fig. 2. Log 10 concentrations (mean7SD) of 22 blood plasma clinical–chemical parameters in 3 raptor species from Northern Norway (see Table 1 for concentration units).

Note the few inconsistent significant species differences and relatively low sample size for golden eagles and white-tailed eagles. See Table 1 for abbreviations and

concentrations. n: Statistical significant differences between species (pr0.05, Kruskal–Wallis).

C. Sonne et al. / Ecotoxicology and Environmental Safety 73 (2010) 7–17 11

negatively correlated to Mirex and ALAT being positively corre-lated to Mirex (p=0.04, r=0.47, n=20). In both goshawks (p=0.07,r=0.49, n=14) and white-tailed eagles (p=0.04, r=0.8, n=5),cholesterol was positively correlated to Mirex.

PBDEs and TBA were detected in all three species. These werePBDEs and TBA. PBDEs were positively correlated to ALAT(p=0.02, r=0.48, n=23), total bilirubin (p=0.03, r=0.45, n=23)and uric acid (p=0.02, r=0.5, n=23) in the pooled species samples.This was also the case for cholesterol (p=0.05, r=0.49, n=16) ingoshawks and white-tailed eagles (p=0.02, r=0.82, n=5). For TBAin goshawks, a positive correlation was found to total protein(p=0.03, r=0.61, n=13) and protein:creatinine (p=0.01, r=0.67,n=13) while a negative correlation was found for creatinine

(p=0.05, r=�0.55, n=13) and a negative trend for amylase(p=0.07, r=�0.52, n=13). No significant results between TBAand BCCPs were found in white-tailed eagles. All results aresummarised in Table 3.

In the pooled samples, uric acid:creatinine was positivelycorrelated to PFCs (p=0.02, r=0.48, n=23). In goshawks, PFCs werepositively correlated to cholesterol (po0.01, r=0.71, n=16) anduric acid (po0.01, r=0.67, n=16). Similar positive trends werefound for albumin (p=0.06, r=0.48, n=16) and total bilirubin(p=0.08, r=0.44, n=16) while amylase was negatively correlatedto PFCs (p=0.08, r=�0.45, n=16). In white-tailed eagles, negativecorrelations were found comparing PFCs and bile acids (p=0.09,r=�0.71, n=5) and potassium (p=0.08, r=�0.81, n=5), while

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Table 2Summary statistics [median(min–max, n)] of organohalogen contaminants in chicks of golden eagles, white-tailed eagles and goshawks from Northern Norway.

Parameter (concentration) Golden eagles (n=2). Goshawk (n=16) White-tailed eagles (n=5).

PPCB (pg/ml ww) 3795–14801 8412 (2296–44830) 19,509 (9144–68837)

p,p0-DDE (pg/ml ww) 603–4880 7527 (1769–24718) 5236 (1087–10907)

b-HCH (pg/ml ww) 128–145 122 (74.4–143, 9) 118 (1)

HCB (pg/ml ww) 185–193 486 (150–2251) 819 (500–976)

Heptachlor epoxide (pg/ml ww) 92–120 279 (104–818) 280 (194–848)

Chlordanes (pg/ml ww)n 49–763 737 (232–2634) 2247 (904–5062)

Mirex (pg/ml ww) 94 (1) 99 (48–362, 14) 202 (46–622)

TBA (pg/ml ww)n 46–94 59 (24–371, 13) 874 (788–4719)P

PBDE (pg/ml ww) 252–302 731 (161–4622) 2000 (386–4573)P

PFC (pg/ml ww)n 900–1300 21,300 (8800–99000) 55,000 (32500–70400)

% Lipids (g/ml) 0.48–0.66 0.63 (0.44–0.83) 0.76 (0.66–1.06)

Note that there are statistically significant differences in blood plasma concentrations of chlordanes, TBA and PFCs between the three raptor species. Reasons for reduced

number of observations are ascribed to detection limits.

n Statistically significant differences between the three species (po0.05, Kruskal–Wallis).

1

10

100

1000

10000

100000

PCBs

p,p-D

DE

β-HCH

HCB

Heptac

hlor e

poxid

e

Chlorda

nes

Mirex

TBA

PBDEsPFCs

OHC group

LogC

once

ntra

tions

(pg/

ml w

w)

Golden eagle (n = 2)Goshawk (n = 16)Sea eagle (n = 5)

*

*

*

Fig. 3. Log 10 concentrations (mean7SD) of 10 groups of organohalogen contaminants divided on 3 raptor species from Northern Norway. Note the few inconsistent

significant species differences and the relatively low sample size for golden eagles and white-tailed eagles. See Table 2 for abbreviations and concentrations. n: Statistical

significant differences between species (pr0.05, Kruskal–Wallis).

C. Sonne et al. / Ecotoxicology and Environmental Safety 73 (2010) 7–1712

positive correlations were found to glucose (p=0.08, r=0.8, n=5)and protein:creatinine (p=0.09, r=0.78, n=5). Based on thecorrelation coefficients, some of these results are likely to occurdue to the low sample size.

3.4. PCAs

The PCA analysis of BCCPs and species resulted in sevencomponents with eigen values above 1 and should therefore beconsidered (Kaiser’s rule (Joliffe, 2002)). However, for simplicityreasons we only deal with the two first components, whichexplained 39% of the total variation in the data. Fig. 4 shows abiplot of the two first components where the arrows represent theloadings of each of the BCCPs and the points (goshawks, goldeneagles and white-tailed eagles) the components value of eachindividual. The BCCPs points in all directions, however, somegrouping of parameters can be seen. Gamma glutamyl transferaseand glucose points in the direction of the first principalcomponent (PCA1), while total protein, albumin and calciumforms a group pointing in the direction of the second principalcomponent (PCA2). Cholesterol and fructose are closely togetherand points in the direction of negatively PCA1 and amylase in thedirection of negatively PCA2. Total bilirubin, ALAT, magnesium

and sodium form a group pointing appx. 451 to the PCA1 and PCA2axis while urea, creatinine and potassium group in the opposite(180 degrees) direction. An ANOVA followed by Tukey’s multiplecomparisons of means showed that white-tailed eagle hadsignificantly (po0.05) lower PCA1 scores than goshawk, whileno other pairwise comparisons were found significant. Nosignificant differences were found between species of the meanPCA2 (ANOVA, p=0.094, respectively).

3.5. RDAs

The RDA analysis of BCCPs, OHCs and species divided the totalvariance into two parts; 54% constrained (by the multivariateregression) and 46% unexplained. The first two canonical axisexplained 17% and 9% (26% in total) of the entire variation. Fig. 5shows a biplot of the RDA results. The arrows represent the firsttwo RDA axis scores. The BCCP scores and the individual birds arerepresented by their abbreviations. Arrows pointing in the samedirection indicate that the compounds are positively correlatedwhile arrows pointing in opposite direction indicate a negativelycorrelation. Lines with an angle of 901 indicate uncorrelation.Most of the OHCs points in the same direction. p,p0-DDE and b-HCH are exceptions where p,p0-DDE is uncorrelated with the other

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Table 3Pearson’s correlation (rp) analyses of BCCPs vs. OHCs in pooled samples of Northern Norway golden eagles (n=2), white-tailed eagles (n=5) and goshawks (n=16).

BCCPs (abbreviation)P

PCB p,p0-DDE b-HCH HCB Hep EpoxP

CHL Mirex TBAP

PBDEP

PFC

ALKP �0.39ns,y�0.45n,h

ALAT 0.06ns,y 0.52n,h 0.47n,h 0.48n,h

Amylase (Amy) �0.52ns,#�0.45ns,#

Glucose (Glu) �0.53nn,y�0.35ns,y

�0.36ns,y�0.43n,h 0.8ns,f

Albumin (Alb) 0.48ns,#

Total protein (TP) 0.47ns,# 0.61n,#

Cholesterol (Cho) 0.85n,f 0.74nn,# 0.63nn,# 0.82n,f 0.8n,f 0.82n,f 0.71nn,#

0.72nn,# 0.65nn,# 0.49ns,# 0.49n,#

Bile acid (BA) �0.71ns,f

Uric acid (UA) 0.06ns,h 0.57nn,h 0.38ns,y 0.67nn,#

Total bilirubin (TB) 0.46n,h�0.52ns,y 0.36ns,y 0.45n,h 0.44ns,#

Protein:creatinine 0.43n,h 0.67nn,# 0.78ns,f

Uric acid:creatinine 0.6nn,h 0.43n,h 0.5n,h 0.48n,h

Magnesium (Mg) 0.39ns,y

Potassium (K) �0.49ns,#�0.81ns,f

Creatinine (Cre) �0.55n,#

In case of separate white-tailed eagle analyses the Spearman rank test was applied. Significant results are given in bold. See Table 1 for abbreviations and concentrations.

Ns: non-significant trend (0.05opo0.1); n: pr0.05; nn: po0.01. y: pooled sample. #: goshawks. f: white-tailed eagles. Hep Epox: Heptachlor expoxide;P

CHL:

Chlordanes.

Com

p.2

GEGE

GH

GH

GH

GH

GHGH

GH

GH

GHGH

SE

SE

SE

SE

-4

Alb

Glu

TP

ALAT

ALKP

TB

FructoCho Iph

BA GGF

Ca

Mg

UA

Na

K

0.0

0.2

0.4

0

2

4

-2 0 2 4

C. Sonne et al. / Ecotoxicology and Environmental Safety 73 (2010) 7–17 13

OHCs and b-HCH is negatively correlated. ALAT, and to someextent glucose and amylase, are associated with b-HCH. Similarly,cholesterol is associated with most of the OHCs. Total bilirubin,ALKP, magnesium, creatinine and potassium are spread betweenthe gradients of the OHCs, while no associations are foundbetween OHCs and albumin, bile acid and uric acid. Regardingspecies, most of the goshawk individuals are found in the oppositedirections of the main part of the OHCs meaning thatconcentrations of these OHCs were lower in this species, whilethe five individuals of white-tailed eagle are found in the samedirection as the main part of the OHCs. Of the two golden eagles,one is close to the origin and the other among the main part ofgoshawks.

-0.4Comp.1

GH

GH

GHGH

GHGHSE

Cre

AmyUrea

-0.4

-0.2

-0.2 0.0 0.2 0.4

-4

-2

Fig. 4. Biplot of the PCA on BCCP concentrations in golden eagles (GE), white-

tailed eagle (SE) and goshawks (GH). PC1 explained 21% and PC2 18% of the

variation. See Section 2 for abbreviations.

4. Discussion

4.1. Species differences: BCCPs

In the present study, we found species differences in theconcentrations of 7 of 22 BCCPs measured. This may be due totheir environment with different patterns of physiology, feedingbehaviour and dietary composition. Admittedly, the statisticalpower for these inter-specific comparisons was low, owing to thelow sample sizes, meaning that true differences in somecompounds may not have been detected. However, the differentfeeding regimes between the three species (terrestrial versusmarine) results in a dietary intake differing in its chemicalcomposition of nutrients and microelements (Bustnes et al., 2008;Ferrer and Dobado-Berrios, 1998; Gjershaug et al., 2008; Herzkeet al., 2002, 2005). This dietary composition is known to influenceBCCPs via either a repetitive direct impact (e.g. cholesterol) orindirect continuous impact via e.g. renal, liver and pancreaticmetabolism and function (Braun, 2003; Harr, 2002; Richards andProszkowiec-Weglarz, 2007; Schulz et al., 2000; Van Loverenet al., 2001). Influences from seasonal and year-to-year variations,that is usually seen in Arctic species, could be excluded as co-factors as could age and sex since all sampled individuals whereyoung hatchlings of approximately same age (Braun, 2003; Harr,2002; Richards and Proszkowiec-Weglarz, 2007; Schulz et al.,2000; Van Loveren et al., 2001). We did not have access to anormal/reference interval for the three raptor species and there-fore we could not evaluate the absolute significance (trueness) ofthe differences. When comparing with BCCPs in other raptor

species of e.g. adult and nestlings of bald (Haliaeetus leucocepha-

lus) and booted (Aquila pennata) eagles, clear differences werefound between these two species and the three Norwegian raptorsfor all BCCPs (Bowerman et al., 2000; Casado et al., 2002).Therefore, these values from similar studies of other species couldnot be applied as normal value reference intervals.

4.2. Species differences: OHCs

We found differences in chlordane, TBA and PFC concentra-tions between the three raptor species. The chick OHC concentra-tions found can be ascribed to yolk sac transfer and foodconcentrations brought by the parents (De Vos et al., 2005;Drouillard et al., 2003; Maervoet et al., 2005). OHCs were ingeneral highest in the white-tailed eagles, probably due to theirreliance on prey species from the marine food web (Gjershaug

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-2

RDA1

RD

A2

AlbGlu TP

ALKP

ALAT

TB

Cho

CreBA

Amy

Mg

UA

K

sPCB

ppDDE

HepEpo

bHCH

HCBsCHL

Mirex

TBA

sPBDE

sPFC

GE

GE

GH

GH

GH

GH

GH

GH

GH

GH

GH

GH

GH

GH

GH

GH

GH

GH

SE

SE

SE

SE

SE

-1

0

1

2

-1 0 1 2

1

0

Fig. 5. Biplot of the RDA of BCCP and OHC concentrations in golden eagles (GE),

white-tailed eagles (SE) and goshawks (GH). RDA1 explained 17% and RDA2 9% of

the variation. See Table 3 for abbreviations.

C. Sonne et al. / Ecotoxicology and Environmental Safety 73 (2010) 7–1714

et al., 2008; Herzke et al., 2002, 2005). Only with respect tochlordanes, TBA and PFCs the difference was highest in white-tailed eagles due to the higher concentrations of TBA (possibly ofnatural origin) in the marine environment (Giesy et al., 2001;Vetter et al., 2006). The relatively high OHC concentrations ingolden eagles and goshawks may be ascribed to the fact that thesetwo species to some extent prey on species that relate to both themarine and terrestrial food webs. In the present study, chicks ofgolden eagles were fed mainly grouse, mountain hare andreindeer, while goshawks mainly fed on grouse and passerinesand the white-tailed eagle chicks fed on fish (cod [Gadus morhua],saithe [Pollachius virens], lumpsuckers [Cyclopterus lumpus]) andsea ducks (Mergini spp.) (Cramp and Simmons, 1980; TrondJohnsen unpublished).

4.3. Relationships between BCCPs and OHCs

As discussed above, we cannot distinguish between thebiochemical effects from dietary variation (nutrients and micro-elements) and OHC profiles on BCCPs in the three raptor species asa control group of non-polluted raptors could not be established.We decided not to Bonferroni correct as we were interested in therelationships between the specific OHCs and BCCPs in order toevaluate specific impacts and not just a general pattern. We foundsignificant correlations between OHCs and important BCCPmarkers in both pooled groups of raptors and within species,which indicate relatively strong relationships.

The BCCP vs. OHC relationships/changes could be divided intoimpacts on internal organs like liver (ALKP, ALAT, bile acid, totalbilirubin, albumin, total protein and cholesterol), kidney (uricacid, creatinine, uric acid:creatinine and protein:creatinine), bone(ALKP, total protein, protein:creatinine) and on other biochemicalparameters linked to energy metabolism, digestion, endocrinologyand general electrolytic homeostasis (protein, uric acid, amylase,glucose, magnesium, potassium and creatinine). In general, birdbiochemistry is difficult to interpret and very few bird studieshave been conducted on the relationship between OHCs andBCCPs. Therefore, scientific literature from mammals is alsoincluded in the following. Earlier studies have shown that variousliver BCCPs, such as ALKP, ALAT, bile acid, total bilirubin, albumin,

total protein and cholesterol, are influenced by OHCs (Dieter, 1974,1975; Dieter et al., 1976, 1977; Dieter and Wiemeyer, 1978;Fischbein, 1985; Kutlu et al., 2007; Hayes et al., 1984). However,the increase or decrease of these biochemical end points seems todepend on species, exposure route, time of exposure and thespecific compound (Arnold et al., 1993; Chu et al., 1994). Severalstudies have reported on increase in blood plasma liver enzymes,such as ALKP and ALAT in case of liver toxicity from PCB, benzeneand other OHC exposure, while few bird studies have beenconducted (Dieter, 1974, 1975; Dieter et al., 1976, 1977; Dieter andWiemeyer, 1978; Fox et al., 2007; Hoff et al., 2005). In the presentstudy, we found negative associations between ALKP versus PCBs,chlordanes and Mirex, while positive associations were foundbetween ALAT and DDE, chlordanes, Mirex and PBDEs. Usually anincreased leakage of ALAT into the blood stream is a result ofhepatocyte lesions, however, it must be noted that there is alwaysan insignificant concentration of liver enzymes in vertebrate bloodplasma, which is considered normal and equals the normalreference interval (Rustad et al., 2004; Sonne et al., 2008).

The positive association of ALAT and four different OHCs (threeof them significant) in the pooled raptor samples may indicateOHC liver toxicity. In theory, increasing blood plasma ALAT valuesmay be a result of e.g. hypoxia, inflammation, diet, infection,neoplasia, trauma, metabolic abnormalities (storage diseases),endocrine diseases or hepatocyte regeneration (Ettinger andFeldman, 1995; Thrall et al., 2006). Of these, the last three areknown to be OHC related (Ettinger and Feldman, 1995; Thrallet al., 2006) as shown in e.g. PFOS-contaminated blue tits (Parus

caeruleus) where elevated ALAT concentrations were foundrelative to control birds (Hoff et al., 2005). In the case of thenegative association between ALKP and three OHCs, the reason isunknown, but may be ascribed to an inhibition of normalhepatocyte function and subsequent lower enzyme blood plasmaconcentrations as found in previous studies of gull spp. in theGreat Lake ecosystem of North America (Fox et al., 2007). Otherhepatotoxic studies of rats have shown that ALKP may beunaffected by PCB exposure probably as a function of compositionand concentration of contaminants (Kutlu et al., 2007).

Total bilirubin, albumin, total protein and cholesterol seemedto increase with increasing OHC concentrations in both pooledsamples and species-specific analyses. Elevated total protein andalbumin is often used as assessment for dehydration (Ettinger andFeldman, 1995; Thrall et al., 2006). Although the present raptorresults were not designed to evaluate cause and effect relation-ships, it indicates that blood biochemistry could be affected byOHCs in the three Norwegian raptor species. This is supported bystudies of e.g. Chu et al. (1994), who found that the bilirubin andcholesterol blood concentrations were highest in a PCB-exposedrat group and a similar relationship has been found in OHCexposed sledge dogs (Sonne et al., 2008). Tryphonas et al. (1984)also found increased blood concentrations of cholesterol andbilirubin in PCB-treated cynomolgus monkeys (Macaca fascicu-

laris), while Arnold et al. (1993) found more or less the oppositerelationships in rhesus monkeys (Macaca mulatta). This showsthat species, composition, time and other important chemical andbiological parameters matter when extrapolating between BCCPstudies. Therefore, the present raptor results should be inter-preted with great caution. In humans, both cholesterol andbilirubin seemed to increase with increasing PCB concentrations(Stehr-Green et al., 1986). The studies of gulls in the Great Lakesshowed decreasing blood plasma concentrations of bilirubin,albumin, total protein and cholesterol in a group of high OHC-polluted gulls when compared with a low polluted group (Foxet al., 2007). In the case of decreasing bile acid concentrationswith increasing PFCs in white-tailed eagles, only a single non-negative association was found and could indicate modulative

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C. Sonne et al. / Ecotoxicology and Environmental Safety 73 (2010) 7–17 15

effects on hepatocyte bile synthesis/secretion and hepatocyte andbile duct lesions although that is highly speculative (Fox et al.,2007).

BCCP renal parameters also showed significant relationships toOHC concentrations. These were total protein (increase), uric acid(increase), creatinine (decrease), uric acid:creatinine (increase)and protein:creatinine (increase). Furthermore, the statisticalrelationships indicated elevated levels of protein and uric acidcompared with creatinine with increasing OHC concentrations.The increased blood protein and uric acid concentrations mayindicate metabolic shifts, high protein diet – which is not unlikelyfor the raptor species – or dehydration as discussed above(Ettinger and Feldman, 1995; Thrall et al., 2006). Furthermore,the elevated levels of protein and uric acid might be related tochick muscle metabolism and growth (Waikar and Bonventre,2008). Chu et al. (1994) found a similar urea increase in theirstudy of PCB-exposed female rats. In addition, previous OHCstudies of Arctic species have shown renal histopathologicalchanges that would allow such interpretations (Sonne et al., 2006,2007, 2008). However, histopathological end points were un-fortunately not possible to investigate in the present Norwegianraptor chicks.

Similarly for bones, decreasing ALKP concentrations withincreasing OHC concentrations could indicate changes in boneturn-over and metabolism (Andrews, 1989). Such impacts aresupported by OHC-driven eggshell thinning theories and observa-tions (Lundholm, 1997; Elliott and Martin, 1994; Falk et al., 2006;Helander et al., 2002; Hernandez et al., 2008; Scharenberg andLooft, 2004) and may even be a result of trans-generationaltoxicity (Steinberg et al., 2008). Unfortunately, bone end pointmarkers were also not possible to investigate in the present raptorchicks.

Changes in the more overall and broader biochemical endpoint OHC markers were found (amylase, glucose, magnesium andpotassium). The decreasing blood glucose levels as a function ofvarious OHCs could indicate endocrine changes as serumfructosamine was not affected and as birds in general are knownto maintain high blood glucose concentrations (Braun andSweazea, 2008). The endocrine pathways for this could be dueto an inverse relationship between maximum corticosterone-driven stress response and PCB concentrations as seen in fishspecies (Jørgensen et al., 2006; Lacroix and Hontela, 2003). Formagnesium and potassium the relationships may be dietary and/or OHC explained while a linkage to renal disorders cannot beexcluded (Musso, in press).

4.4. Interpretations

The present study may suggest a relationship between OHCsand specific BCCPs in the three raptor species. However, thepresent results should be interpreted with great caution as BCCPsare influenced by multiple factors such as age, diseases, diet,hydration and other environmental factors as well as species-specific differences driven by physiology, diet and OHC loadsespecially in case of goshawks and white-tailed eagles. Therefore,the present pilot study points towards a larger study whereanalyses can be conducted within each species and on a largerdata set likely including histopathology and bone biomarkers ifpossible. It is not easy to conclude on the health impacts from theOHC relationships to liver, kidney and general homeostasis in thethree raptor species. It is either not possible to assess whetherthere are indications of a decline in the raptor populations ofNorthern Norway although climate-driven year-to-year variationsare seen (Cramp and Simmons, 1980). Especially the high OHCcontaminated goshawk and white-tailed eagle populations may

suffer from increased risks of infections and lower reproductionrates resulting in impaired fitness, survival and adaptations toecological changes like global warming.

5. Conclusions

Three OHC groups and five BCCPs showed species-specificdifferences. Furthermore, the relationships between OHCs andvarious BCCPs suggested an impact from dietary composition and/or persistent organic contaminants on liver/kidney function,endocrinology and metabolism in raptor chicks of NorthernNorway in a direction that may indicate health impacts.Ultimately, the chemical stress on blood plasma biochemistrycould have consequences on goshawk and white-tailed eaglepopulations in particular as they carry the highest body burdens.The pathways for this are due to increased infection risks,decreased reproductive performance and thereby impaired fit-ness, survival and adaptations to ecological changes such as globalwarming. We therefore recommend that a larger study shouldtake place in the near future in order to monitor potentialpopulation impacts.

Acknowledgments

The Norwegian Research Council and the Funds of ScientificResearch Flanders (personally to Dr. VLB Jaspers and Dr. A Covaci);are acknowledged for funding. Laboratory technicians at theDepartment of Small Animal Clinical Sciences, University ofCopenhagen and at the Norwegian Institute for Air Research areacknowledged for conducting the BCCP and OHC analyses,respectively.

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