PREVALENCE AND SPATIO-TEMPORAL VARIATION OF AN

ALOPECIA SYNDROME IN POLAR BEARS OF THE SOUTHERN

BEAUFORT SEA

Todd Atwood,1,5 Elizabeth Peacock,1 Kathy Burek-Huntington,2 Valerie Shearn-Bochsler,3

Barbara Bodenstein,3 Kimberlee Beckmen,4 and George Durner1

1 US Geological Survey, Alaska Science Center, 4210 University Dr., Anchorage, Alaska 99508, USA2 Alaska Veterinary Pathology Services, 23834 The Clearing Drive, Eagle River, Alaska, USA 995773 US Geological Survey, National Wildlife Health Center, 6006 Schroeder Road, Madison, Wisconsin 53711, USA4 Alaska Department of Fish and Game, 1300 College Road, Fairbanks, Alaska 99701, USA5 Corresponding author (email: tatwood@usgs.gov)

ABSTRACT: Alopecia (hair loss) has been observed in several marine mammal species and haspotential energetic consequences for sustaining a normal core body temperature, especially forArctic marine mammals routinely exposed to harsh environmental conditions. Polar bears (Ursusmaritimus) rely on a thick layer of adipose tissue and a dense pelage to ameliorate convective heatloss while moving between sea ice and open water. From 1998 to 2012, we observed an alopeciasyndrome in polar bears from the southern Beaufort Sea of Alaska that presented as bilaterallyasymmetrical loss of guard hairs and thinning of the undercoat around the head, neck, andshoulders, which, in severe cases, was accompanied by exudation and crusted skin lesions. Alopeciawas observed in 49 (3.45%) of the bears sampled during 1,421 captures, and the apparentprevalence varied by years with peaks occurring in 1999 (16%) and 2012 (28%). The probabilitythat a bear had alopecia was greatest for subadults and for bears captured in the Prudhoe Bayregion, and alopecic individuals had a lower body condition score than unaffected individuals. Thecause of the syndrome remains unknown and future work should focus on identifying the causativeagent and potential effects on population vital rates.

Key words: Alopecia, Arctic, disease, polar bears, skin lesion, Ursus maritimus.

INTRODUCTION

Observations of alopecia (i.e., focal hairthinning and loss) have been reported forseveral species of marine mammals in-cluding northern elephant seals (Mir-ounga angustirostris), Australian fur seals(Arctocephalus pusillus doriferus), south-ern sea lions (Otaria flavescens), grey seals(Halichoerus grypus), ringed seals (Pusahispida), and Pacific walrus (Odobenusrosmarus) (Bergman and Olsson 1985;Nettleton et al. 1995; Beckmen et al.1997; Lynch et al. 2011; Pistorius andBaylis 2011). In some cases, alopecia hasbeen associated with elevated concentra-tions of polychlorinated biphenyls (e.g.,Bergman and Olsson 1985; Beckmen et al.1997), a group of lipophilic persistentorganic pollutants known to concentratein marine food webs (Ruus et al. 2002) andinterfere with thyroid hormone homeosta-sis (Routti et al. 2010). Other cases ofalopecia have been attributed to nutrient

deficiencies (Trites and Donnelly 2003),parasitic agents (e.g., Dailey 2001), andfungal infection of the hair shaft (Guillot etal. 1998). However, in many cases thecausative agent of alopecia remains un-known, which further complicates efforts tounderstand its epidemiology.

Alopecia is a concern for marine mam-mals because of the primary role of hair inthermoregulation (Hind and Gurney 1997;Rosen et al. 2007). Individuals withalopecia may have difficulty maintainingadequate thermoregulation (e.g., Lynchet al. 2011) and thus expend additionalenergy to sustain a constant core bodytemperature (Beauplet et al. 2003). Theelevated energy demands on alopecicanimals could have an adverse effect onbody condition (e.g., Lynch et al. 2011).Polar bears (Ursus maritimus) routinelymove between sea ice and open water (i.e.,leads and polynyas) which can result in awide temperature gradient between thebody core and the external environment

DOI: 10.7589/2013-11-301 Journal of Wildlife Diseases, 51(1), 2015, pp. 000–000# Wildlife Disease Association 2015

0

(Øritsland 1970; Blix and Lentfer 1979),and lead to a substantial increase inthermoregulatory costs for alopecic polarbears, particularly during winter.

We describe an alopecia syndromeobserved in polar bears captured in theAlaska portion of the southern BeaufortSea (SB) from 1998 to 2012. Here we 1)describe the clinical appearance of thesyndrome, 2) estimate prevalence bydemographic class, 3) assess spatial andtemporal variation in prevalence, and 4)characterize the effect of alopecia on bodycondition. In 2008, polar bears were listedas ‘‘threatened’’ under the US Endan-gered Species Act. If a disease were toemerge that had the potential to negativelyaffect polar bear health, there would be apressing need to identify its etiology andtake action to mitigate adverse effects.

MATERIALS AND METHODS

Study area

The study area ranged from DemarcationPoint (140uW) at the US-Canada border in theeast to Point Barrow (156uW) in the west, andincluded the Alaska portion of the SB sub-population of polar bears. Polar bears werecaptured from 1998 through 2012 (Fig. 1).The spatial distribution of sampling effort waslargely consistent over the course of the study.Capture extended from shoreline to approxi-mately 135 km out over sea ice, but theseasonality of captures varied. For all years,captures occurred during spring (20 March–5May), with additional captures occurring in fall(typically September or October) of 1999,2000, 2001, 2008, and 2009.

Data collection

Polar bears were encountered from ahelicopter and immobilized with tiletaminehydrochloride plus zolazepam hydrochloride(TelazolH, Fort Dodge Animal Health, FortDodge, Iowa, USA, and Warner-Lambert Co.,Groton Connecticut, USA) using projectilesyringes fired from a dart gun. Bears were ear-tagged with an identification number that wasalso tattooed on the inner surface of the lip.We determined body weight using a scale andcollected morphometric measurements. Cubs-of-the-year (COY) were always with theirmothers and could be visually aged withouterror (Ramsay and Stirling 1988). Some bears

had been captured and marked in previousyears, so their age was determined from theircapture history. For other bears, we extracteda vestigial premolar and determined age byanalysis of cementum annuli (Calvert andRamsay 1998). We assigned bears to five ageclasses: adult ($5 yr), subadult (3–4 yr), 2-yr-old, yearling, and COY. We classified bodycondition using a subjective fatness index: wepalpated the body and assigned individuals ascore from 1 (extremely thin) to 5 (obese)based on the distribution of adipose tissuearound the body (Stirling et al. 2008). Thisindex correlates positively with lipid concen-tration of adipose tissue in polar bears(McKinney et al. 2014).

We inspected all animals for distinguishingmarks (e.g., scars, fresh wounds), lesions, andpatches of hair loss. From alopecic individuals,we collected plucks of hair from the edge ofthe affected area, along with a skin scrape andtwo replicates (when possible) of lesionbiopsies. We collected plucks of hair fromunaffected areas on alopecic animals and froma subsample of unaffected individuals to serveas controls. From 1998 to 2010, we stored skinscrapes in methanol, and biopsy and lesionreplicates in 10% formalin. In 2012, wecollected fresh skin scrapes, hair, and biopsiesthat were not preserved so that routinebacterial and fungal cultures could be run.Additionally, we collected oral, nasal, andrectal swabs and stored them in RNAlaterH(Qiagen, Hilden, Germany). Samples stored in10% formalin were kept at room temperatureprior to analysis; samples stored in RNAlaterHwere immediately snap-frozen and stored at280 C prior to analysis.

Pathology

Hair samples were analyzed by placing hairbundles on a glass slide with a small amount ofimmersion oil and observing the hair shaftsunder the light microscope. Biopsy tissuesamples were processed by routine methods forparaffin wax embedding. Sections (4–5 mm) werestained with hematoxylin and eosin. All sectionswere also stained with periodic acid-Schiff andGram stains to assist in the detection of bacteriaand fungi. Histologic sections were analyzed bylight microscopy by two board-certified veteri-nary pathologists (K.B.H. and V.S.B.).

Prevalence

We calculated apparent prevalence as thepercentage of bears captured that had signs ofalopecia. We used Fisher’s exact tests for eachsex to determine if the occurrence of alopeciawas independent of age class and year and

0 JOURNAL OF WILDLIFE DISEASES, VOL. 51, NO. 1, JANUARY 2015

used the Cochran-Armitage test to determineif trends were present in the number ofalopecia cases. We used adjusted residualsfor describing and making inferences aboutthe true association structure among theresponse variables (Agresti 2002).

We used generalized linear models within amodel selection framework (Burnham andAnderson 2002) to test hypotheses aboutdifferences in probability of occurrence ofalopecia by demographic, spatial, and tempo-ral factors. Variables used in modeling includ-ed sex, age-class, year of capture, and capturelocation. To assign bears to a capture location,we divided the study area into three evenlyspaced sectors (Barrow, Prudhoe Bay, andKaktovik). We determined the midpoint ofeach sector and used a clustering routine in ageographic information system (GIS) to assignbears to sectors based on capture locationcoordinates. The clustering approach allowedus to objectively assign bears to a locationsector based on the location of capture ratherthan the logistical base (Barrow, Prudhoe Bay,or Kaktovik) from which flights originated.

We developed, a priori, a set of biologicallyplausible candidate models (Table 1) and usedAkaike’s information criterion values (Akaike1973) corrected for small sample bias (AICc) toaid in determining top models. We consideredmodels with DAICc values .2.0 to measurablydiffer in information content (Burnham andAnderson 2002). We used AICc to rank andcompare models based on DAICc and normal-ized Akaike weights wi, and used the sum of allwi for each variable to rank them in order ofimportance. When faced with model uncertain-ty, we used model averaging to account forvariation to estimate probability of occurrencemore robustly (Burnham and Anderson 2002;Arnold 2010). We ensured model fit by testingwith the Hosmer and Lemeshow goodness-of-fitstatistic (Hosmer and Lemeshow 2000). Modelswith poor goodness-of-fit (i.e., P$0.05) were notused for ranking and comparison.

Spatial analyses

Prudhoe Bay is at the approximate geo-graphic center of the study area (Fig. 1) and

FIGURE 1. Study area and distribution of alopecia-positive and -negative polar bears (Ursus maritimus)captured in the southern Beaufort Sea, Alaska, USA, 1998–2012.

ATWOOD ET AL.—ALOPECIA IN POLAR BEARS 0

should represent the mean center of occur-rence of cases detected each year in Alaska inthe absence of spatial heterogeneity. We useda GIS to plot geo-referenced capture locationsand derive standard deviational ellipses andmean centers of occurrence for each year inwhich there were $3 cases. Standard devia-tional ellipses measure the orientation of casedistribution. We used the ellipses to determineif a directional trend in case distributionexisted over the years. We calculated thedirection between mean centers by derivingthe angle between centers as described inGuerra et al. (2003), and converting angles todegrees using a reference angle of 0u (truenorth). We used the Watson-Williams test todetermine if the angle of rotation differedbetween the yearly mean centers.

Body condition

We used paired t-tests to compare thefatness index of cases and controls (bears

without alopecia) that were matched by ageand sex. Following Lynch et al. (2011), wematched case-control pairs for age and sexbased on the order in which they werecaptured so that matched pairs were capturedwithin a relatively short time. Each bear wasused only once for this analysis. We alsopooled case-control pairs and used a three-wayanalysis of variance to further explore theinfluence of age, sex, and year and respectivepairwise interactions on fatness index. Weused Kolmogorov-Smirnov and Levene’s teststo check data for normality and homogeneityof variances, respectively. We accepted statis-tical significance at a50.05.

RESULTS

From 1998 through 2012, 49 of the1,421 bears captured or recaptured wereclassified as having alopecia for an overallapparent prevalence of 3.45%. Peaks inprevalence occurred in 1999 (16%) and2012 (28%); no cases were detected in2000, 2004, 2006, and 2009–11 (Fig. 2).Over the course of the study, we recap-tured 12 (11 adults and one subadult)bears that had been previously classifiedas alopecic but had recovered by the timeof recapture. The time between captureand recapture ranged 0.5–10 yr (x54 yr,SE50.7). Five of the 10 bears wererecaptured 1 yr after being classified asalopecic and appeared to have recoveredcompletely. Only one case of alopecia wasobserved in a bear captured during the fall(ncaptures5212; prevalence: 0.5%), so we

TABLE 1. A priori models relating sex, age class, capture location, and year to the prevalence of alopecia inpolar bears (Ursus maritimus) in the southern Beaufort Sea, Alaska, USA, 1998–2012.

Model Hypothesis description Model variables

1 Prevalence varied by capture location Location2 Prevalence varied by sex Sex3 Prevalence varied by year Year4 Prevalence varied by age class Age5 Prevalence varied additively with year and age class Year, age6 Prevalence varied additively with year and sex Year, sex7 Prevalence varied additively with year and location Year, location8 Prevalence varied additively with location and sex Location, sex9 Prevalence varied additively with location, sex, and age class Location, sex, age

10 Prevalence varied additively with location, sex, age class, and year Location, sex, age, year11 Prevalence varied additively with sex and age class Sex, age12 Prevalence varied additively by age class, year, and sex Age, year, sex

FIGURE 2. Annual variation in apparent preva-lence of alopecia in polar bears (Ursus maritimus)captured in Alaska’s southern Beaufort Sea,USA, 1998–2012.

0 JOURNAL OF WILDLIFE DISEASES, VOL. 51, NO. 1, JANUARY 2015

restricted analyses to spring captures(ncaptures51,232; ncases548; prevalence:3.9%).

Pathology

Alopecia varied in severity and mostcommonly presented as bilaterally asym-metrical loss of guard hair and thinning ofthe undercoat along the dorsoventral axis ofthe head and neck (Fig. 3A, B). Comparedto unaffected bears, biopsies from alopecicindividuals had a preponderance of telogenfollicles, follicular and epidermal hyperker-atosis, and occasional follicular dysplasiacharacterized by thickening and irregular-ity of the trichilemmal keratin with fre-quent, irregular extrusions of trichilemmalkeratin into the outer root sheath (Fig. 4A–C). Some affected bears had crusting andoozing lesions, which typically includedchronic proliferative dermatitis characterizedby acanthosis, hyperkeratosis, and chronicperivascular inflammation (Fig. 4D), typicalof pruritic lesions. There was some evidenceof colonization of hair shafts by bacteria andfungi, but it did not appear to be associatedwith inflammation except in cases of furun-culosis secondary to self-trauma. No mites,lice, or other ectoparasites were detected.

There was a variable degree of anagenfollicle formation indicating initiation ofthe next hair cycle and formation of newhair shafts. Trichograms of affected ani-mals demonstrated fewer guard hairs in

affected samples, light yellow-brown dis-coloration of the hair shafts and bulbs, andfragmentation of the medulla in existingunderfur hair shafts. The peripheral endswere often frayed, indicating breakage(trichomalacia or self-trauma). In 1999,trichograms placed in dermatophyte testmedia were negative for growth of der-matophytes.

Demographic analyses

No cases of alopecia were observed infamily groups that included COY so wepooled all COY, yearlings, and 2-yr-oldsinto a ‘‘dependent young’’ class for demo-graphic analysis. Alopecia status (positiveor negative) was not independent of agefor males (n5659, df52, x259.39,P50.009) or females (n5762, df52,x2512.40, P50.002) (Fig. 5). For males,the estimated odds of alopecia occurringin subadults were eight times greater thanfor dependent young and two timesgreater than for adults. For females, theodds of alopecia occurring in subadultswere 18 and three times greater than fordependent young and adults, respectively.Cochran-Armitage tests indicated an ab-sence of trends in yearly counts of alopeciacases for both males (z50.20, P50.84) andfemales (z521.26, P50.27).

Based on Hosmer-Lemeshow tests,models that included the variable yeardisplayed poor fit and were deleted from

FIGURE 3. Appearance and distribution of alopecia in southern Beaufort Sea polar bears (Ursusmaritimus) in Alaska, USA, 1998–2012. (A) Thinning of hair at the base of neck over the shoulder blades. (B)Patchy hair loss on the side of the neck.

ATWOOD ET AL.—ALOPECIA IN POLAR BEARS 0

the model set. The remaining generalizedlinear models indicated the probabilitythat a bear had alopecia was influenced bydemography and location. Two modelswere within 1.2 DAICc units of each otherand thus were comparably supported bythe data (Table 2). This top model setcollectively accounted for 66% of the totalmodel weight and the variables sex andage-class were retained in both models.Location, a categorical variable represent-ing the general area in which an individualwas captured, was retained in the secondmodel (Table 2). Based on the normalizedAkaike weights of the three variables thatcomprised the top model set, sex

FIGURE 4. Skin biopsies from affected and unaffected polar bears captured in the southern Beaufort Sea,Alaska, USA, in the spring of 2012. (A) Note large, well-developed anagen follicles in the deeper dermis, thinepithelium, and minimal keratin on the surface of the unaffected individual (bar5200 mm). (B) Biopsy froman alopecic polar bear exhibits sparcity and dysplasia of the follicles and very little anagen follicle development(bar5500 mm). (C) Follicular dysplasia and intranuclear clearing (bar550 mm). (D) Biopsy from a bear thathad a proliferative change with some crusting that included thickening of the epithelium, excess keratin,fibrosis, and inflammation (bar5300 mm).

FIGURE 5. Mean prevalence and standard errorof alopecia by age class for male and female polarbears (Ursus maritimus) captured in Alaska’s south-ern Beaufort Sea, USA, 1998–2012.

0 JOURNAL OF WILDLIFE DISEASES, VOL. 51, NO. 1, JANUARY 2015

(wi50.89) was most important, followedby age (wi50.75), and location (wi50.33).Model-averaged estimates derived fromthe top model set indicated that theprobability that a bear had alopecia wasgreatest for subadults (b51.13, SE50.486)and individuals captured in the PrudhoeBay (b50.226, SE50.109) region of thestudy site, and lowest for females(b520.205, SE50.095).

Spatial analysis

Enough cases were available to calcu-late mean centers and standard deviationalellipses for the years 1999, 2003, 2007,2008, and 2012. Mean centers of cases

from 4 yr of the 5 yr (1999, 2003, 2007,and 2012) were located in the PrudhoeBay sector; the center of 2008 cases waslocated in the Barrow sector. Meancenters for alopecia-free bears from thosesame years were all located within thePrudhoe Bay sector. Mean direction anddistance traveled of cases varied by year,moving an average of 98.3 km from 1999to 2012. The Watson-Williams test re-vealed that mean centers of alopecia andalopecia-free bears were moving in dis-similar directions (F1,953.31, P50.001)over the 5 yr. The cumulative meandirection of individuals with alopeciafrom 1999 to 2012 was 65.33631.23u (SE),whereas the cumulative mean direction ofalopecia-free bears was 292.24624.17u.

Body condition

We used 86 individuals for thematched-pair (case-control) comparisonof alopecia status on body condition. Meanfatness index values of animals classified aspositive (case) for the alopecia syndromewere significantly lower than that ofmatched animals classified as unaffected(control) (t522.94, P50.005) (Fig. 6).Additionally, values also were influencedby year (F1,8556.16, P50.01) but not sex(F1,8551.79, P50.18) or age-class (F3,835

1.12, P50.35), and no interactions werestatistically significant. Values for caseswere consistently lower than mean valuesfor all control bears within case years. Forreference, we also included index values

TABLE 2. General linear models of factors influencing the probability of alopecia in polar bears (Ursusmaritimus) in the southern Beaufort Sea, Alaska, USA, 1998–2012. Model structure is followed bycorresponding model number (i.e., hypothesis description from Table 1), number of parameters (k), Akaikeinformation criterion with a small sample size correction factor values (AICc), weights of evidence (wi), andHosmer-Lemeshow (HL) goodness-of-fit statistic P-value. Models from the a priori set that demonstratedpoor goodness-of-fit were deleted from the set.

Model Model number k AICc DAICc wi HL P-value

Sex+age 11 4 391.46 0.00 0.43 0.83Location+sex+age 9 7 392.70 1.24 0.23 0.93Sex 2 1 393.59 2.13 0.15 0.87Age 4 3 394.52 3.06 0.09 0.79Location+sex 8 6 394.85 3.39 0.08 0.89Location 1 3 397.97 6.52 0.02 0.91

FIGURE 6. Mean fatness index scores formatched pairs of polar bears (Ursus maritimus) with(cases) and without (controls) alopecia and for allunmatched bears without (negative) alopecia cap-tured in Alaska’s southern Beaufort Sea, USA, 1998–2012.

ATWOOD ET AL.—ALOPECIA IN POLAR BEARS 0

by year for all unaffected bears (‘‘FInegative’’; Fig. 6) that were not used inthe case-control comparison. We did notdetect a difference in fatness index scoresfor the 11 adults that had been previouslyclassified as alopecic but had recovered bythe time of recapture (alopecia positiveduring initial capture: xBCS52.9, 95%

confidence interval (CI)52.6–3.1; alopecianegative during subsequent recapture:xBCS53.0, 95% CI52.7–3.3).

DISCUSSION

The manifestation of alopecia wassimilar to recent accounts published forpinnipeds (e.g., Lynch et al. 2011, 2012) inthat it presented as patchy hair thinningand loss and could be accompanied bypruritic skin. However, it differed in thatthe distribution was often reduced in polarbears and was bilaterally asymmetrical.There was cause for concern over theoccurrence of alopecia in polar bears,particularly given the concomitant occur-rence of a similar syndrome in ringed sealsin the Chukchi and SB seas. The under-lying cause of alopecia in polar bears andnorthern pinnipeds remains unknown andthere is no clinical evidence to suggestthey are related. Ringed seals are theprimary prey of polar bears in the SB andChukchi seas. Given the conservationstatus of the species involved, there isconcern over any risk factor that couldhave the potential to adversely impactpopulation health.

The body condition of alopecic bearswas lower than the condition of unaffectedbears. Reductions in body condition couldresult from affected bears expendingadditional energy to maintain core bodytemperatures, as has been reported foralopecic pinnipeds (e.g., Lynch et al.2011). The consistent loss of body heatto the environment by alopecic bears maybe exacerbated by the increased frequencyof swimming events that have beendetected for bears in the SB (Durner etal. 2011; Pagano et al. 2012), resulting

from reductions in sea ice extent over thelast decade (Stroeve et al. 2011). Thethermal conductivity of water is substan-tially greater than air (Bonner 1984), andrepeated movement in and out of water, aswell as an increase in the frequency oflong-distance swims, may exacerbate heatloss to the environment for alopecic bears.Conversely, reduced body condition couldresult from other stressors that contributeto alopecia. The body condition of polarbears in the SB has been declining inassociation with reduced availability of seaice habitat (Rode et al. 2010). Nutritionallimitations mediating body condition mayalso factor in the occurrence of alopecia(e.g., Goldberg and Lenzy 2010). Theexact mechanism of the reduced bodycondition is not clear and warrants furtherinvestigation.

Alopecia occurred more consistentlyover time in females than in males; weobserved cases in females in 8 yr of 15 yras opposed to 5 yr of 15 yr for males. Yetfor all years when cases were observedsimultaneously in males and females,prevalence estimates for male age classeswere consistently higher. These findingswere supported by general linear models,which indicated that sex and age classwere the most important determinants ofthe probability of alopecia. Males werenearly twice as likely to have the syndromeas were females. In part, this may be dueto males typically ranging over a largerarea than females (Laidre et al. 2012),which may mediate increased exposure topotential disease-causing agents (Altizer etal. 2006; Biek et al. 2006). However, we donot present an analysis of movement datato corroborate this hypothesis. Additional-ly, the energetic demands of extensiveranging behavior can result in immuno-modulation (e.g., lowering of innate im-munity; French et al. 2007), possiblyleading to immune suppression and vul-nerability to infections (Chandra 1996;Demas 2004). Prevalence of alopecia wasrelatively high for male and female sub-adults, which lends further credence to

0 JOURNAL OF WILDLIFE DISEASES, VOL. 51, NO. 1, JANUARY 2015

the notion that energetically stressedindividuals may be more susceptible tothe syndrome than are energetically bal-anced individuals. Subadults would beexpected to be vulnerable to energeticstress because they no longer travel andfeed with their mothers (e.g., Rode et al.2010; Thompson et al. 2010). Indeed, aninteractive effect of extensive ranging andimmunomodulation may be contributingrisk factors for the occurrence of alopeciain multiple demographic classes of polarbears in the SB.

Perhaps the most notable demographiceffect on occurrence was the absence ofalopecia in all members of family groupsthat included COY. For polar bears, onlypregnant females use dens, which theytypically enter in November and exit in lateMarch after giving birth in January(Amstrup 2003). The failure to detectalopecia in family groups with COY suggeststhat either exposure to the cause of alopeciacould have occurred between Novemberand March, when those family groups werein dens and thus not available to be exposed,or pregnant females with alopecia lose theircubs prior to or during denning. Althoughthis observation provides no indication ofthe etiology of alopecia, note that the samplesize of family groups with COY wasrelatively large (n5145; groups sampled inboth spring and fall). The only referenceswe found regarding the occurrence ofalopecia in free-ranging ursids concernsymptoms of an undiagnosed dermatitisassociated with hibernating black bears(Ursus americanus), which included alope-cia of the head, neck, and thorax (Beck 1991;Garrison 2004; Costello et al. 2006). Forboth species, evidence suggests that theeffects of alopecia are typically sublethalwith individuals recovering over time. Forpolar bears, recovery is manifested as thegrowth of new fur following the spring molt(Born et al. 1991).

Disease is generally characterized bysome form of spatio-temporal heterogene-ity (Ostfeld et al. 2005). Landscapecharacteristics such as the juxtaposition

and connectivity of habitat patches, thepresence of physical or biotic gradients,and patterns of land use can stronglyinfluence disease spread and prevalence(Root et al. 2009; Almberg et al. 2010).The prevalence of alopecia varied throughtime, with distinctive peaks in 1999 and2012, which were separated by an inter-vening period of consistently low preva-lence. Additionally, we found that cases ofalopecia in fall captures were rarer,although our sample size was much lower.Environmental drivers can generate peri-odic variation in disease dynamics (e.g.,Dushoff et al. 2004; Hoshen and Morse2004). Temporal variation in the preva-lence of alopecia could be caused byseasonal or annual changes in the pres-ence, concentration, or virulence of thecausative agent (Altizer et al. 2006), andchanges in the functioning of endocrine orimmune systems of bears could modulatesusceptibility (Bernhoft et al. 2000; Lieet al. 2004). Conversely, alopecia couldbe secondary to another disease that isaffected by the aforementioned factors.

The Arctic marine ecosystem is experi-encing dramatic change due to a warmingclimate, which has been hypothesized toalter exposure levels of marine mammalsto toxicants (McKinney et al. 2009),diseases, and parasites (Burek et al. 2008;Stirling and Derocher 2012). The warmingtrend has resulted in a decline of annualmean September sea ice extent by about7% per decade from 1979 to 2001,whereas for the period 2002 to 2013, thetrend is 214.0% per decade (e.g., Comisoet al. 2008; Stroeve et al. 2012, 2014). Theseven lowest September sea ice extents onrecord have all occurred since 2007. Theincreased prevalence of alopecia in thespring of 1999 and 2012 followed afterunusually warm fall (1998 and 2011)surface air temperatures (SAT) alongAlaska’s North Slope, which persistedthrough winter and spring (1999 and2012) (Lindsay and Zhang 2005; Jeffrieset al. 2012). However, fall (October) SATfor the North Slope were also anomalously

ATWOOD ET AL.—ALOPECIA IN POLAR BEARS 0

high for multiple years in between in whichno or few cases of alopecia were detected.If alopecia in polar bears is mediated byclimate-driven changes to the marineecosystem, we should expect to see anincrease in the frequency of occurrence ofthe syndrome, and a correlation betweenprevalence and climate-related metrics.

We detected a general trend of aneastward shift in the mean centers ofalopecia cases over time. However, thesample of cases was low, resulting inimprecise standard deviational ellipses(Zimmerman et al. 2011), and polar bearscan range over extensive distances in thespring, when most captures occur(Amstrup et al. 2000, 2001; Laidre et al.2012). Given that bears can, over thecourse of a month, traverse a distancesimilar to the distance between meancenters of annual cases, the capturelocation of affected bears reveals littleabout where exposure to the causativeagent may have occurred.

The cause and consequence of alopeciain polar bears remains unknown. We diddetect a decrease in body condition ofalopecic bears, but it remains undeter-mined if the reduction in body condition isa result of alopecia-mediated thermoregu-latory stress or due to an underlying diseasethat resulted in alopecia. Reductions inbody condition have been linked to de-clines in reproductive output in a variety ofspecies (e.g., Guinet et al. 1998; Harwoodet al. 2000), including polar bears (Atkinsonand Ramsay 1995; Rode et al. 2010). Causalinvestigations are needed to understandthe potential impacts that alopecia mayhave on polar bear population dynamics.Future work should be broadened into aholistic approach for evaluating cumulativeand synergistic effects of multiple stressorson population vital rates.

ACKNOWLEDGMENTS

We thank K. Simac, A. Pagano, T. Donnelly,G. York, and S. Amstrup for their effort in thefield. Funding was provided by the USGeological Survey’s Ecosystems Mission Area

and Climate and Land Use Change, OuterContinental Shelf, and Environmental Healthprograms, and the Bureau of Land Manage-ment. D. Gohmert and H. Reed safely pilotedhelicopters during polar bear captures. K. Rodeand R. Stimmelmayr provided crucial input ondeveloping the sampling protocol. We thankK. Oakley, A. DeGange, D. Mulcahy, and J.Pearce for facilitating the research, and C.Duncan for aiding with the interpretation ofpathology results. D. Mulcahy, C. Van Hemert,and K. Titus provided comments on an earlierversion of this manuscript. Polar bear capture,handling, and sampling protocols were ap-proved by the US Geological Survey, AlaskaScience Center Animal Care and Use Commit-tee. Any use of trade names is for descriptivepurposes only and does not reflect endorse-ment by the federal government.

LITERATURE CITED

Agresti A. 1996. An introduction to categoricalanalysis. John Wiley & Sons, New York, NewYork, 290 pp.

Akaike H. 1973. Information theory as an extensionof the maximum likelihood principle. In: Secondinternational symposium on information theory,Petrov BN, Csaki F, editors. Akademia Kiado,Budapest, Hungary, pp. 267–281.

Almberg ES, Cross PC, Smith DW. 2010. Persis-tence of canine distemper virus in the GreaterYellowstone Ecosystem’s carnivore community.Ecol Appl 20:2058–2074.

Altizer S, Dobson A, Hosseini P, Hudson P, PascualM, Rohani P. 2006. Seasonality and the dynam-ics of infectious diseases. Ecol Lett 9:467–484.

Amstrup SC. 2003. Polar bear, Ursus maritimus. In:Wild mammals of North America. Biology,management, and conservation, Feldhamer GA,Thompson BC, Chapman JA, editors. 2nd Ed.Johns Hopkins University Press, Baltimore,Maryland, pp. 587–610.

Amstrup SC, Durner GM, Stirling I, Lunn NJ,Messier F. 2000. Movements and distribution ofpolar bears in the Beaufort Sea. Can J Zool78:948–966.

Amstrup SC, Durner GM, McDonald TL, MulcahyDM, Garner GW. 2001. Comparing movementpatterns of satellite-tagged male and femalepolar bears. Can J Zool 79:2147–2158.

Arnold TW. 2010. Uninformative parameters andmodel selection using Akaike’s informationcriterion. J Wildl Manag 74:1175–1178.

Atkinson SN, Ramsay MA. 1995. The effects ofprolonged fasting of the body composition andreproductive success of female polar bears(Ursus maritimus). Funct Ecol 9:559–567.

Beauplet G, Guinet C, Arnould JPY. 2003. Bodycomposition changes, metabolic fuel use, and

0 JOURNAL OF WILDLIFE DISEASES, VOL. 51, NO. 1, JANUARY 2015

energy expenditure during extended fasting insubantarctic fur seal (Arctocephalus tropicalis)pups at Amsterdam Island. Physiol Biochem Zool76:262–270.

Beck TM. 1991. Black bears of west-central Colora-do. Colorado Division of Wildlife TechnicalPublication 39. 86 pp.

Beckmen KB, Lowenstine LJ, Newman J, Hill J,Hanni K, Gerber J. 1997. Clinical and patholog-ical characterization of northern elephant sealskin disease. J Wildl Dis 33:438–449.

Bergman A, Olsson M. 1985. Pathology of Baltic greyseal and ringed seal females with specialreference to adrenocortical hyperplasia: Is envi-ronmental pollution the cause of widely distrib-uted disease syndrome? Finn Game Res 44:47–62.

Bernhoft A, Skaare JU, Wiig Ø, Derocher AE,Larsen HJS. 2000. Possible immunotoxic effectsof organochlorines in polar bears (Ursus mar-itimus) at Svalbard. J Toxicol Environ Health:Part A 59:561–574.

Biek R, Ruth TK, Murphy KM, Anderson CR Jr,Johnson M, DeSimone R, Gray R, HornockerMG, Gillin CM, Poss M. 2006. Factors associ-ated with pathogen seroprevalence and infectionin Rocky Mountain cougars. J Wildl Dis 42:606–615.

Blix CS, Lentfer JW. 1979. Modes of thermalprotection in polar bear cubs—At birth and onemergence from the den. Am J Physiol 236:R67–R74.

Bonner WN. 1984. Lactation strategies in pinnipeds:Problems for a marine mammalian group. SympZool Soc Lond 51:253–272.

Born EW, Renzoni A, Dietz R. 1991. Total mercuryin hair of polar bears (Ursus maritimus) fromGreenland and Svalbard. Polar Res 9:113–120.

Burnham KP, Anderson DR. 2002. Model selectionand multi-model inference: A practical informa-tion-theoretic approach, 2nd Ed. Springer-Ver-lag, New York, New York, 488 pp.

Burek KA, Gulland FMD, O’Hara TM. 2008. Effectsof climate change on Arctic marine mammalhealth. Ecol Appl 18:S126–S134.

Calvert W, Ramsay MA. 1998. Evaluation of agedetermination of polar bears by counts ofcementum growth layer groups. Ursus 10:449–453.

Chandra RK. 1996. Nutrition, immunity, and infec-tion: From basic knowledge of dietary manipu-lation of immune responses to practical applica-tion of ameliorating suffering and improvingsurvival. Proc Nat Acad Sci USA 93:14304–14307.

Comiso JC, Parkinson CL, Gersten R, Stock L. 2008.Accelerated decline in the Arctic sea ice cover.Geophys Res Lett doi:10.1029/2007GL031972.

Costello CM, Quigley KS, Jones DE, Inman RM,Inman KH. 2006. Observations of a denning-

related dermatitis in American black bears.Ursus 17:186–190.

Dailey MD. 2001. Parasitic diseases. In: CRChandbook of marine mammal medicine, , 2ndEd., Dierauf LA, Gulland FMD, editors. CRCPress, Boca Raton, Florida, pp. 357–379.

Demas GE. 2004. The energetics of immunity: Aneuroendocrine link between energy balanceand immune function. Horm Behav 45:173–180.

Durner GM, Whiteman JP, Harlow HJ, Amstrup SC,Regehr EV, Ben-David M. 2011. Consequencesof long-distance swimming and travel over deep-water pack ice for a female polar bear during ayear of extreme sea ice retreat. Polar Biol34:975–984.

Dushoff J, Plotkin JB, Levin SA, Earn DJD. 2004.Dynamical resonance can account for seasonalityof influenza epidemics. Proc Nat Acad Sci USA101:16915–16916.

French SS, McLemore R, Vernon B, Johnston GIH,Moore MC. 2007. Corticosterone modulation ofreproductive and immune systems trade-offs infemale tree lizards: Long-term corticosteronemanipulations via injectable gelling material.J Exp Biol 210:2859–2865.

Garrison EP. 2004. Reproductive ecology, cubsurvival and denning ecology of the Floridablack bear. Master’s Thesis, Department ofWildlife Ecology and Conservation, Universityof Florida, Gainesville, Florida, 88 pp.

Goldberg LJ, Lenzy Y. 2010. Nutrition and hair. ClinDermatol 28:412–419.

Guerra MA, Curns AT, Rupprecht CE, Hanlon CA,Krebs JW, Childs JE. 2003. Skunk and raccoonrabies in the eastern United States: Temporal andspatial analysis. Emerg Infect Dis 9:1143–1150.

Guillot J, Petit T, DeGorce-Rubiales F, Gueho E,Chermette R. 1998. Dermatitis caused byMalassezia pachydermatis in a California sealion (Zalophus californianus). Vet Rec 142:311–312.

Guinet C, Roux JP, Bonnet M, Mison V. 1998. Effectof body size, body mass, and body condition onreproduction of female South African fur seals(Arctocephalus pusillus) in Namibia. Can J Zool76:1418–1424.

Harwood LA, Smith TG, Melling H. 2000. Variationin reproduction and body condition of the ringedseal (Phoca hispida) in western Prince AlbertSound, NT, Canada, as assessed through aharvest-based sampling program. Arctic 53:422–431.

Hind AT, Gurney WS. 1997. The metabolic cost ofswimming in marine homeotherms. J Exp Biol200:531–542.

Hoshen MB, Morse AP. 2004. A weather-drivenmodel of malaria transmission. Malaria J 3:32.

Hosmer DW, Lemeshow S. 2000. Applied logisticregression. John Wiley & Sons, Inc., New York,New York, 392 pp.

ATWOOD ET AL.—ALOPECIA IN POLAR BEARS 0

Jeffries MO, Richter-Menge JA, Overland JE, editors.2012. Arctic report card 2012, www.arctic.noaa.gov/reportcard. Accessed March 2014.

Laidre KL, Born EW, Gurarie E, Wiig Ø, Dietz R,Stern H. 2012. Females roam while males patrol:Divergence in breeding season movements ofpack-ice polar bears (Ursus maritimus). ProcRoy Soc B doi:10.1098/rspb2012.2371.

Lie E, Larsen HJ, Larsen S, Johansen GM, DerocherAE, Lunn NJ, Norstrom RJ, Wiig Ø, Skaare JU.2004. Does high organochlorine (OC) exposureimpair the resistance to infection in polar bears(Ursus maritimus)? Part 1: Effect of OCs on thehumoral immunity. J Toxicol Environ Health A67:555–582.

Lindsay RW, Zhang J. 2005. The thinning of Arcticsea ice, 1988–2003: Have we passed a tippingpoint? J Climate 18:4879–4894.

Lynch M, Kirkwood R, Mitchell A, Duignan P,Arnould JPY. 2011. Prevalence and significanceof an alopecia syndrome in Australian fur seals(Arctocephalus pusillus doriferus). J Mammal92:342–351.

Lynch M, Kirkwood R, Gray R, Robson D, BurtonG, Jones L, Sinclair R, Arnould JPY. 2012.Characterization and causal investigations ofan alopecia syndrome in Australian fur seals(Arctocephalus pusillus doriferus). J Mammal93:504–513.

McKinney MA, Peacock E, Letcher RJ. 2009. Seaice-associated diet change increases the levelsof chlorinated and brominated contaminantsin polar bears. Environ Sci Technol 43:4334–4339.

McKinney M, Atwood TC, Dietz R, Sonne C, RigetF, Born E, Peacock E. 2014. Validation ofadipose lipid content from biopsies as a bodycondition index using polar bears. Ecol Evol4:516–527.

Nettleton PF, Munro R, Pow I, Gilray J, Gray EW, ReidHW. 1995. Isolation of parapoxvirus from a greyseal (Halichoerus grypus). Vet Rec 137:562–564.

Øritsland NA. 1970. Temperature regulation of thepolar bear (Thalarctos maritimus). Comp BiolPhysiol 37:225–233.

Ostfeld RS, Glass GE, Keesing F. 2005. Spatialepidemiology: An emerging (or re-emerging)discipline. Trends Ecol Evol 20:328–336.

Pagano AM, Durner GM, Amstrup SC, Simac KS,York GS. 2012. Long-distance swimming bypolar bears of the southern Beaufort Sea duringyears of extensive open water. Can J Zool90:663–676.

Pistorius PA, Baylis AMM. 2011. A bald encounter:Hairless southern sea lion at the FalklandIslands. Polar Biol 34:145–147.

Ramsay MA, Stirling I. 1988. Reproductive biologyand ecology of female polar bears (Ursusmaritimus). J Zool 214:601–634.

Rode KD, Amstrup SC, Regehr EV. 2010. Reducedbody size and cub recruitment in polar bearsassociated with sea ice decline. Ecol Appl20:768–782.

Root JJ, Puskas RB, Fischer JW, Swope CB,Neubaum MA, Reeder SA, Piaggio AJ. 2009.Landscape genetics of raccoons (Procyon lotor)associated with ridges and valleys of Pennsylva-nia: Implications for oral rabies vaccinationprograms. Vector-Borne Zoonotic Dis 9:583–588.

Rosen DAS, Winship AJ, Hoopes L. 2007. Thermaland digestive constraints to foraging behavior inmarine mammals. Proc Roy Soc B 362:2151–2168.

Routti H, Arukwe A, Jenssen BM, Letcher RJ,Nyman M, Backman C, Gabrielsen GW. 2010.Comparative endocrine disruptive effects ofcontaminants in ringed seals (Phoca hispida)from Svalbard and the Baltic Sea. Comp BiolPhysiol C 152:306–312.

Ruus A, Ugland KI, Skaare JU. 2002. Influence oftrophic position on organochlorine concentra-tions and compositional patterns in a marinefood web. Environ Toxicol Chem 21:2356–2364.

Stirling I, Thiemann GW, Richardson E. 2008.Quantitative support for a subjective fatnessindex for immobilized polar bears. J WildlManag 72:568–574.

Stirling I, Derocher AE. 2012. Effects of climatewarming on polar bears: A review of evidence.Global Change Biol 18:2694–2706.

Stroeve JC, Serreze MC, Kay JE, Holland MM,Meier WN, Barrett AP. 2012. The Arctic’srapidly shrinking sea ice cover: A researchsynthesis. Clim Change 110:1005–1027.

Stroeve JC, Markus T, Boisvert L, Miller J, Barrett A.2014. Changes in Arctic melt season andimplications for sea ice loss. Geophys Res Lettdoi:10.1002/2013GL058951.

Thompson ME, Muller MN, Kahlenberg SM,Wrangham RW. 2010. Dynamics of social andenergetic stress in wild female chimpanzees.Horm Behav 58:440–449.

Trites AW, Donnelly CP. 2003. The decline of Stellersea lions Eumetopias jubatus in Alaska: A reviewof the nutritional stress hypothesis. Mammal Rev33:3–28.

Zimmerman DL, Li J, Fang X. 2011. Spatialautocorrelation among automated geocodingerrors and its effects on testing for diseaseclustering. Stat Med 29:1025–1036.

Submitted for publication 15 November 2013.Accepted 8 April 2014.

0 JOURNAL OF WILDLIFE DISEASES, VOL. 51, NO. 1, JANUARY 2015