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The Condor 106:386390q The Cooper Ornithological Society 2004

FACULTATIVE REST-PHASE HYPOTHERMIA IN FREE-RANGINGWHITE-THROATED SPARROWS

ANDREW S. DOLBY1, JOHN G. TEMPLE, LAURA E. WILLIAMS, EMILY K. DILGER, KATRINA M. STECHLER ANDVANESSA S. DAVIS

Department of Biological Sciences, Mary Washington College, 1301 College Avenue,Fredericksburg, VA 22401

Abstract. Shallow facultative rest-phase hypother-mia has been reported in a number of passerine fam-ilies, but few published data exist about its use by free-ranging birds. We used temperature-sensitive radio-transmitters to determine whether White-throatedSparrows (Zonotrichia albicollis) employ nocturnalhypothermia during winter. We measured skin temper-atures of 24 free-ranging sparrows between 13:00 and14:00 and between 02:00 and 03:00 for each of threedays and nights per subject. The average nightly skin-temperature reduction per individual was 3.4 6 1.08C(SD). Skin temperature reductions ranged from 0.28Cto 7.08C among all individuals. There was a significantnegative correlation between the magnitude of skintemperature decline and nighttime ambient tempera-ture. Additionally, we found a negative trend betweendepth of hypothermia and a body density index.

Key words: hypothermia, thermoregulation, White-throated Sparrow, Zonotrichia albicollis.

Fase de Reposo Hipotermica Facultativa enIndividuos de Zonotrichia albicollis que seDesplazan Libremente

Resumen. La fase de reposo facultativa somera hasido mencionada para un numero de familias de pa-seriformes, pero existen pocos datos publicados sobresu uso por parte de aves que se desplazan libremente.Usamos radio transmisores sensibles a la temperaturapara determinar si Zonotrichia albicollis emplea hi-potermia nocturna durante el invierno. Medimos latemperatura de la piel de 24 individuos que se despla-zan libremente entre las 13:00 y 14:00 y entre las02:00 y 03:00 durante tres das y tres noches por in-dividuo. La reduccion nocturna promedio de la tem-

Manuscript received 17 October 2003; accepted 20January 2004.

1 E-mail: adolby@mwc.edu

peratura de la piel por individuo fue 3.4 6 1.08C (DE).Las reducciones de la temperatura de la piel variaronentre 0.28C y 7.08C considerando todos los individuos.Hubo una correlacion negativa significativa entre ladisminucion de la magnitud de la temperatura de lapiel y la temperatura ambiental nocturna. Adicional-mente, encontramos una tendencia negativa entre laprofundidad de la hipotermia y el ndice de densidadcorporal.

Body temperature maintenance entails considerablemetabolic cost for endothermic animals. When meta-bolic demand exceeds energy supply, some birds usefacultative hypothermic responses to reduce energy ex-penditure (McKechnie and Lovegrove 2002). Such cir-cumstances may arise when food supplies are insuffi-cient or unpredictable, when weather is cold, or whenforaging is inhibited for prolonged periods (Reinertsen1996).

Avian facultative hypothermic responses occur in abroad range of depths and bout lengths, ranging fromseasonal hibernation, exhibited by Common Poorwill(Phalaenoptilus nuttallii), to shallow rest-phase hypo-thermia observed in an array of avian families(McKechnie and Lovegrove 2002). They are generallymost pronounced among nonpasserine nectarivoresand aerial-feeding insectivores whose food sources areephemeral and dependent upon weather (McKechnieand Lovegrove 2002). Among such taxa (e.g., Apo-didae, Trochilidae, and Caprimulgidae), body temper-ature (Tb) reductions exceeding 108C are common, andindividuals often enter torpor (Geiser and Ruf 1995,Reinertsen 1996, Kortner et al. 2000, Barclay et al.2001). In contrast, most passerines examined maintainnocturnal Tb within 108C of active-phase normother-mic Tb and typically do not become torpid (Reinertsen1996, McKechnie and Lovegrove 2003). A notable ex-ception is the nectarivorous Malachite Sunbird (Nec-tarinia famosa; Downs and Brown 2002). However,while relatively modest in depth, facultative rest-phase

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hypothermia likely affords passerines biologically sig-nificant energetic savings (Dawson and Whittow2000).

Much about passerines use of this energy-savingstrategy remains unknown. Most research has beenconducted on captive subjects (McKechnie and Love-grove 2003), or has targeted nonpasserines (Brigham1992, Bech et al. 1997). Our first objective was there-fore to determine whether it occurs in a free-rangingtemperate-zone species, the White-throated Sparrow(Zonotrichia albicollis).

White-throated Sparrows are winter residents of theMid-Atlantic region of the eastern United States. Theyare regularly exposed to nighttime ambient tempera-tures (Ta) at or below those known to produce hypo-thermia in other passerines (Reinertson and Haftorn1986, Clemens 1989). Furthermore, since they are pri-marily ground-feeding granivores (Falls and Kopache-na 1994), their food supply may be periodically ob-scured by snow and ice, possibly subjecting them toshort-term food limitation.

Another poorly understood facet of avian thermo-regulation relates to the factors that produce intraspe-cific variability. Such factors may include both envi-ronmental and physiological variables (Reinertsen1996). A number of studies have reported relationshipsbetween Ta and the depth of hypothermia bouts, butfew have examined the effects of Ta on free-rangingbirds (Brigham 1992). Moreover, the effects of indi-viduals energetic status on the depth of hypothermiahave generally been addressed via food deprivation ex-periments in the laboratory (Ketterson and King 1977,Graf et al. 1989, McKechnie and Lovegrove 2003).Data for individuals in the field are needed to under-stand the effects of energy reserves on facultative rest-phase hypothermic strategies.

Thus, our second objective was to determine wheth-er Ta or stored energy predict the depth of facultativerest-phase hypothermia. We predicted that magnitudeof skin temperature (Tsk) depression would be nega-tively correlated with both Ta and fat supply, estimatedusing a body density index. Additionally, we predictedthat there would be an interaction between these var-iables.

METHODSWe conducted our study 721 January 2002 and from10 January to 3 February, 2003, on the Mary Wash-ington College grounds and adjacent residential neigh-borhood of Fredericksburg, Virginia (388109N,778359W). The area contains a mixture of lawns andhedgerows, as well as unmanaged Eastern deciduousforest fragments. Bird feeders were present in the studyarea. During the day, we typically observed White-throated Sparrows in loosely structured social groupsforaging in leaf litter. At night, sparrows most fre-quently roosted in broad-leaved evergreens (e.g., Ilexopaca, Photinia serrulata, and Ligustrum lucidum).

We mist-netted 24 adult sparrows opportunisticallyand weighed and measured the wing chords of each.Body masses ranged from 23.3 to 32.8 g (mean 6 SD5 27.9 6 2.7 g), and wing chords ranged from 65.5to 78.0 mm (mean 6 SD 5 71.6 6 3.0 mm). Fromthese measurements, we calculated a body density in-dex by dividing body mass by the cube of wing chord

length. This index is frequently used as an indicator ofphysical condition in birds, and variation among in-dividuals is indicative of variation in fat supply (Pra-vosudov et al. 1999, Ekman and Hake 1990).

We sexed 18 individuals based on wing chord length(Piper and Wiley 1991). The wing chord lengths of sixindividuals were within the published range of overlapbetween males and females (Piper and Wiley 1991,Falls and Kopachena 1994), and consequently, wecould not sex them with certainty.

Each bird was fitted with two colored leg bands topermit individual identification. We affixed a temper-ature-sensitive radio-transmitter (Model BD-2AT; 0.7g; Holohil Systems Ltd., Carp, Ontario, Canada) to theinterscapular apteria of each bird using Skin-Bondtlatex cement (Smith & Nephewt Inc., Largo, Florida).

We measured Tsk of birds between 13:00 and 14:00and between 02:00 and 03:00 during the next threeconsecutive days and nights by timing the interpulseinterval and comparing it with the calibration curvesprovided by the manufacturer. We based the timing ofour Tsk measurements on data for six individuals whoseTsk we measured every 3 hr also over 3 days andnights. From these pilot observations, we determinedthat we reliably captured maximum diurnal Tsk andminimum nocturnal Tsk during these hours. To verifythat transmitters were properly attached following thethird nights reading, we measured Tsk the next after-noon. If a transmitter detached from a bird at any time,we attached it to a new subject. We obtained six Tskmeasurements for 12 sparrows each winter. Observa-tions were spread as evenly as possible across calendardates each year.

Since we were interested in measuring temperaturechanges only, and not absolute body temperature (Tb)values, we did not record subjects cloacal tempera-tures immediately after applying transmitters. Brigham(1992) found that cloacal and interscapular Tsk tem-peratures in Common Poorwills are tightly correlated(r2 5 0.99). We assumed that Tsk changes would reflectTb changes in our White-throated Sparrows with a sim-ilar degree of precision. Moreover, the diurnal Tsk inour sample averaged 40.9 6 1.68C (SD), which iswithin one degree of the mean Tb typical of passerines(Prinzinger et al. 1991). It is possible that Tsk mea-surements are affected by ambient cooling (Willis andBrigham 2003). However, even though the daytime Tarange was nearly equivalent to nighttime range, therewas only a 0.028C change in daytime Tsk measurementsfor every 1.08C change in daytime Ta. Thus, it appearsthat Ta had little direct effect on Tsk measurements. Wetherefore feel that our use of external transmitters wasa valid means of assessing Tb fluctuations.

When we measured Tsk, we also recorded Ta andwind speed (m sec21). Ta ranged from 278C to 128C(mean 6 SD 5 5.0 6 4.38C) during the day, and 288Cto 78C at night (21.6 6 4.78C). Ta averages were con-sistent with historical Ta averages for the region. Windspeeds were negligible during both years in the vicinityof sparrows nocturnal roost sites. Thus, we excludedwind speed from our analyses. Snow and ice coverwere also insignificant during our observation period.

STATISTICAL ANALYSES

We used ANCOVA to test our predictions (SPSS 11.0for windows). To eliminate pseudoreplication, we cal-

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FIGURE 1. Frequency distribution of rest-phase skintemperature (Tsk) reduction in White-throated Sparrows(n 5 24 individuals; three observations per subject).

FIGURE 2. Significant negative correlation betweenmean rest-phase skin temperature (Tsk) reduction andthe average nocturnal ambient temperature (Ta) in 24White-throated Sparrows (r 5 20.42, P 5 0.05). Eachdata point represents the mean of three Tsk measure-ments of an individual.

FIGURE 3. Negative relationship between rest-phaseskin temperature (Tsk) reduction and an index of bodydensity in White-throated Sparrows, after controllingfor ambient temperature (Ta) (rpartial 5 20.40, P 50.06). Each data point represents the ANCOVA resid-ual of rest-phase skin temperature (Tsk) reduction afterwe removed the effects of Ta (Fig. 2).

culated the average nocturnal Tsk reduction exhibitedby each individual. Our response variable, therefore,comprised the mean of the three diurnal-nocturnal Tskdifferences recorded per individual. We also averagedthe Ta for the three nights corresponding to when eachsubjects nocturnal Tsk readings were taken. Since thepredicted interaction term was not significant, we re-moved it from our final model. We performed a sep-arate, but identical analysis on the 18 birds that wecould sex reliably. Values represent means 6 SD.

RESULTS

Overall nocturnal Tsk reduction ranged from 0.28C to7.38C (mean 3.5 6 1.48C; Fig. 1), while per-subjectaverage Tsk reductions ranged between 2.28C and 5.78C(mean 3.4 6 1.08C). Twelve of 24 sparrows exhibitedmean Tsk decreases $3.08C.

We found a significant negative correlation betweenaverage per-subject Tsk reduction and Ta (F1,21 5 4.5,P 5 0.05; Fig. 2). Additionally, average Tsk reductiontended to be negatively related to body density (F1,215 3.9, P 5 0.06; Fig. 3). Both variables accounted forapproximately one-third of the variation among indi-viduals mean nocturnal Tsk decline and significantlypredicted the depth of hypothermia (R2 5 0.30, P 50.02).

In our analysis of those individuals that we couldsex reliably, we found no difference in depth of hy-pothermia between seven males and 11 females aftercontrolling for the effects of Ta and body density (F1,145 1.1, P 5 0.32).

DISCUSSIONWhite-throated Sparrows in our study exhibited noc-turnal Tsk depression that varied among individuals.Half of our 24 subjects reduced their Tsk by $3.08C,enough to suggest use of facultative rest-phase hypo-thermia (Prinzinger et al. 1991), likely to lessen ther-moregulatory costs. To our knowledge, these data rep-resent the first evidence of facultative rest-phase hy-pothermia in a free-ranging emberizid. They are con-sistent, however, with laboratory evidence that mostpasserines are capable of only modest rest-phase tem-perature reduction (McKechnie and Lovegrove 2002).

The average Tsk reduction we recorded was greaterthan that of well-fed captive White-crowned Sparrows(Z. leucophrys), a congener of equal body mass, whose

Tb dropped by less than 1.08C between night and dayat a mean Ta of about 7.08C (Ketterson and King1977). In fact, the average Tsk decline we recorded wascomparable to those of captive White-crowned Spar-rows (Tb decline 5 3.48C) fasted for 56 hr, also at Ta5 7.08C, during which birds lost more than 20% oftheir body mass (Ketterson and King 1977).

The average nocturnal Ta in our study was nearly9.08C lower than in Ketterson and Kings (1977) fooddeprivation experiment (21.68C versus 7.08C). We didrecord 14 Tsk observations when the Ta was comparable(i.e., 4.08C to 7.08C). Under these conditions, Tsk re-duction was still within 0.58C (mean 3.1 6 1.08C) ofthe Tb declines reported by Ketterson and King (1977)for severely fasted White-crowned Sparrows. Thus,our data are consistent with recent arguments that lab-oratory studies underestimate the amplitude of circa-dian Tb fluctuations typical of free-ranging birds (Gei-ser et al. 2000, McKechnie and Lovegrove 2002).

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Variability in depth of Tsk reduction was at least par-tially explained by Ta. As Ta declines, energetic costsassociated with thermoregulation should increase, cre-ating greater need for conservation (Reinertsen andHaftorn 1983, Merola-Zwartjes 1998). The variation innocturnal Tsk reduction we found was also partly ex-plained by our body density index, although our ob-served negative correlation was only marginally sig-nificant. This relationship suggests that birds with low-er fat reserves have greater need to reduce thermoreg-ulatory costs.

We must interpret this trend with caution. Additionalvariables such as muscle mass and gut contents affectthe density index. Furthermore, consistent relation-ships between energy limitation and depth of hypo-thermia have not been found in the field (Dawson andWhittow 2000). Birds that are not obviously energylimited may still enter rest-phase hypothermia or evenbecome torpid. Brigham (1992) found that food supplydid not reliably predict torpor use by free-rangingCommon Poorwills. Willow Tits (Poecile montanus;Reinertsen and Haftorn 1983) regularly fell into hy-pothermia despite access to adequate food. Further-more, the biological consequences of hypothermia forour subjects cannot be quantified based on our data.

There was no interaction between Ta and body den-sity index, perhaps because these variables exert in-dependent effects on subjects thermoregulatory strat-egies. Alternatively, climatic conditions during ourstudy, although typical of the region, may not havebeen sufficient to cause birds to thermoregulate differ-ently depending upon their energetic status. Finally,physiological differences among individuals not cap-tured by our body density index may have had over-riding effects on thermoregulation as Ta declined.

In summary, we provide evidence that free-rangingWhite-throated Sparrows use facultative rest-phase hy-pothermia to a greater extent than would be predictedby previous laboratory work. Additional factors suchas diurnal Ta, wind exposure, nocturnal predation risk,social status, and energetic quality of food consumedby birds may influence White-throated Sparrow noc-turnal thermoregulation. Furthermore, much debatecurrently exists regarding heterothermy terminologyand the physiological significance of rest-phase hypo-thermia (Geiser and Ruf 1995, Barclay et al. 2001,Lovegrove and Smith 2003). Nonetheless, our resultsreinforce the conclusion by others (McKechnie andLovegrove 2002) that more field studies are needed tounderstand passerine rest-phase thermoregulation.

We thank Sigma Xi, the Virginia Academy of Sci-ence, and Mary Washington College for project fund-ing. We also thank Dr. Debra Hydorn for statisticaladvice, and the E. G. Thornton family for access totheir private property. Helpful comments by R. M.Brigham and an anonymous reviewer improved thismanuscript.

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EKMAN, J. B., AND M. K. HAKE. 1990. Monitoring star-vation risk: adjustments of body reserves inGreenfinches (Carduelis chloris L.) during periodsof unpredictable foraging success. BehavioralEcology 1:6267.

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KETTERSON, E. D., AND J. R. KING. 1977. Metabolicrate and behavioral responses to fasting in theWhite-crowned Sparrow (Zonotrichia leucophrysgambelii). Physiological Zoology 50:115129.

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LOVEGROVE, B. G., AND G. A. SMITH. 2003. Is noc-turnal hypothermia a valid physiological conceptin small birds?: a study on Bronze MannikinsSpermestes cucullatus. Ibis 145:547557.

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MCKECHNIE, A. E., AND B. G. LOVEGROVE. 2003. Fac-ultative hypothermic responses in an Afrotropicalarid-zone passerine, the Red-headed Finch (Ama-dine erythrocephala). Journal of ComparativePhysiology B 173:339346.

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PIPER, W. H., AND R. H. WILEY. 1991. Effects of lap-arotomies on wintering White-throated Sparrowsand the usefulness of wing chord as a criterion forsexing. Journal of Field Ornithology 62:4045.

PRAVOSUDOV, V. V., T. C. GRUBB JR., P. F. DOHERTY JR.,C. L. BRONSON, E. V. PRAVOSUDOVA, AND A. S.DOLBY. 1999. Social dominance and energy re-serves in wintering woodland birds. Condor 101:880884.

PRINZINGER, R., A. PREMAR, AND E. SCHLEUCHER.1991. Body temperature in birds. ComparativeBiochemistry and Physiology 99A:499506.

REINERTSEN, R. E. 1996. Physiological and ecologicalaspects of hypothermia, p. 125157. In C. Carey[ED.], Avian energetics and nutritional ecology.Chapman & Hall, New York.

REINERTSEN, R. E., AND S. HAFTORN. 1983. Nocturnalhypothermia and metabolism in the Willow TitParus montanus at 638N. Journal of ComparativePhysiology 156:655663.

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The Condor 106:390395q The Cooper Ornithological Society 2004

YOU CANT JUDGE A PIGMENT BY ITS COLOR: CAROTENOID AND MELANINCONTENT OF YELLOW AND BROWN FEATHERS IN SWALLOWS, BLUEBIRDS,

PENGUINS, AND DOMESTIC CHICKENS

KEVIN J. MCGRAW1,8, KAZUMASA WAKAMATSU2, SHOSUKE ITO2, PAUL M. NOLAN3, PIERRE JOUVENTIN4,F. STEPHEN DOBSON3, RICHARD E. AUSTIC5, REBECCA J. SAFRAN6, LYNN M. SIEFFERMAN3, GEOFFREY E. HILL3

AND ROBERT S. PARKER71Department of Neurobiology and Behavior, Cornell University, Ithaca, NY 14853

2Fujita Health University, School of Health Sciences, Toyoake, Aichi 470-1192, Japan3Department of Biological Sciences, Auburn University, 331 Funchess Hall, Auburn, AL 36849

4Centre dEcologie Fonctionnelle et Evolutive, Centre National de la Recherche Scientifique, 1919 Route deMende, Montpellier, France

5Department of Animal Science, Cornell University, Ithaca, NY 148536Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY 14853

7Division of Nutritional Sciences, Cornell University, Ithaca, NY 14853

Abstract. The two main pigment types in birdfeathers are the red, orange, and yellow carotenoidsand the black, gray, and brown melanins. Reports con-flict, however, regarding the potential for melanins toproduce yellow colors or for carotenoids to producebrown plumages. We used high-performance liquidchromatography to analyze carotenoids and melaninspresent in the yellow and brown feathers of five avianspecies: Eastern Bluebirds (Sialia sialis), Barn Swal-lows (Hirundo rustica), King Penguins (Aptenodytespatagonicus), Macaroni Penguins (Eudyptes chrysolo-phus), and neonatal chickens (Gallus domesticus). In

Manuscript received 16 June 2003; accepted 19 Jan-uary 2004.

8 Present address: Dept. of Animal Science, Univer-sity of California-Davis, One Shields Ave., Davis, CA95616. E-mail: kjmcgraw@davis.edu

none of these species did we detect carotenoid pig-ments in feathers. Although carotenoids are reportedlycontained in the ventral plumage of European BarnSwallows (Hirundo rustica rustica), we instead foundhigh concentrations of both eumelanins and phaeo-melanins in North American Barn Swallows (H. r. er-ythrogaster). We believe we have detected a new formof plumage pigment that gives penguin and domestic-chick feathers their yellow appearance.

Key words: Aptenodytes patagonicus, carotenoids,Eudyptes chrysolophus, Gallus domesticus, Hirundorustica, melanins, Sialia sialis.

No Puedes Juzgar un Pigmento por su Color:Contenido de Carotenoide y Melanina dePlumas Amarillas y Marrones en Golondrinas,Azulejos, Pinguinos y Gallinas Domesticas

Resumen. Los dos tipos principales de pigmentosque las aves incorporan en sus plumas son carotenoi-

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des, para desarrollar plumajes rojo, naranja o amarillo,y melaninas, para adquirir coloracion negra, marron,gris o tonalidades color tierra. Sin embargo, existe in-formacion conflictiva sobre la potencial coloracion deplumas amarillas basadas en melanina y la presenciade caroteniodes en el plumaje marron de ciertas es-pecies. En este estudio, usamos cromatografa lquidade alto rendimiento para analizar los tipos y cantidadesde carotenoides y melaninas presentes en las plumasamarillas y marrones de cinco especies de aves: el azu-lejo Sialia sialis y la golondrina Hirundo rustica, lospinguinos Aptenodytes patagonicus y Eudyptes chryso-lophus y el plumon natal amarillo de la gallina do-mestica Gallus domesticus. En ninguna de estas es-pecies detectamos pigmentos carotenoides en las plu-mas. A pesar de que los carotenoides han sido encon-trados en el plumaje ventral de la golondrina Hirundorustica rustica, nosotros en cambio encontramos altasconcentraciones de eumelaninas y feomelaninas en H.r. erythrogaster y en azulejos que variaron entre in-dividuos y regiones de plumaje. Creemos que hemosdetectado una nueva forma de pigmento de plumajeque le da a las plumas de pinguinos y pollos domes-ticos su apariencia amarilla.

Carotenoids and melanins are the two primary typesof pigment incorporated into bird feathers (Fox 1976).Red, orange, and yellow plumage colors are typicallythe result of carotenoid pigments, whereas black,brown, gray, and earth-toned colors are created by thepresence of melanins (Fox and Vevers 1960). Manyclasses of carotenoids exist, based on their molecularstructure (e.g., carotenes, xanthophylls), and these mayconfer different colors on an animal (Goodwin 1984).In contrast, melanin pigments come in only two mainforms, eumelanin and phaeomelanin, and the relativeratio of these two melanins can influence feather col-oration (e.g., domestic pigeons [Columba livia]; Haaseet al. 1992). Black and gray feathers are typicallythought to contain predominantly eumelanins, whereasearth-toned feathers are dominated by phaeomelanins,much like red human hair (Fox and Vevers 1960).

Interestingly, some have attributed the yellow colorof feathers in certain species to melanins. Volker(1934), for example, classified the yellow plumagepigmentation of domestic chicks (Gallus domesticus)as melanin based. Still others have reported that brownplumage, particularly in the Barn Swallow (Hirundorustica rustica), contains a host of colorful carotenoidpigments (Stradi 1998, Camplani et al. 1999, Saino etal. 1999). These biochemical reports seem to contra-dict the normal appearance of the respective plumagecolors, so we investigated both the carotenoid and mel-anin content of yellow and brown feathers from fiveavian species, including these two mentioned above.We sampled feathers from wild Eastern Bluebirds (Sia-lia sialis) and Barn Swallows from North America (Hi-rundo rustica erythrogaster), from wild King Penguins(Aptenodytes patagonicus) and Macaroni Penguins(Eudyptes chrysolophus) on the Crozet archipelago,and from domestic chicks. We used high-performanceliquid chromatography (HPLC) to determine whethercarotenoids, melanins, or both types of pigment werepresent in the colorful plumage of these species.

METHODS

SPECIES DESCRIPTIONS AND FEATHER COLLECTION

Barn Swallows. The ventral plumage of North Amer-ican Barn Swallows is rufous or chestnut colored(Brown and Brown 1999). This trait honestly signalsmate quality in both males and females and variesmost among individuals in the color of specific bodyregions (e.g., throat, breast, belly, vent; Safran and Mc-Graw 2004). As part of an ongoing study of BarnSwallows in Tompkins County, New York (428279N,768299W), RJS collected up to 10 pigmented ventralfeathers from three males and three females in Marchand April 2001. Feathers were stored attached to indexcards in the dark at room temperature and analyzed forcarotenoids in October 2001 and melanins in Decem-ber 2001 and January 2002. Carotenoid analyses wereperformed on a group of five feathers from each bird;the remaining feathers from each body region werepooled for all birds to understand the variation in eu-melanin and phaeomelanin pigmentation across thecolored plumage areas.

Eastern Bluebirds. Eastern Bluebirds display or-ange-red plumage on the breast (Gowaty and Plissner1998) and exhibit marked within- and between-sexvariation in the size of this feather patch (Sieffermanand Hill 2004). We characterized the pigment com-position from a standardized location on the breastpatch (the center). As part of a study of bluebirds inLee County, Alabama (328369N, 858309W), LMS col-lected three pigmented breast feathers from six malesand six females in March 2002. These feathers werestored in envelopes in the dark at room temperatureand analyzed for the presence of carotenoids (in threemales and three females) and melanins (the remainingthree of each sex) in April and May 2002.

King and Macaroni Penguins. King Penguins haveflashy auricular and chest patches of yellow-orangefeathers (Jouventin 1982). Macaroni penguins developyellow-orange filamentous forehead plumes (Warham1975, Jouventin 1982). As part of a study of penguinson Possession Island, Crozet Archipelago in the IndianOcean (468279S, 518519E), PMN and FSD collected ca.100 breast and auricular feathers from three King Pen-guins and single feather plumes from two MacaroniPenguins (all of unknown sex) in NovemberDecem-ber 2001. These feathers were folded within indexcards and stored in sealed plastic packets at 228C untilpigment analysis in MarchMay 2002. We separatelyanalyzed ca. 10 breast and 10 auricular feathers fromall King Penguins and halves of each Macaroni Pen-guin forehead plume for carotenoids and melanins.

Domestic chicks. Yellow downy feathers were col-lected from two 1-day-old single-comb white leghorndomestic chicks (Cornell K-strain; one in February2002 and one in May 2002). All feathers were storedin the dark in a plastic bag. In March 2002 and againJune 2002, ca. 10 feathers from each bird were ana-lyzed for both carotenoids and melanins.

CAROTENOID EXTRACTION ANDCHROMATOGRAPHY

All carotenoid analyses were conducted in the labo-ratory of RSP. We used both thermochemical (Hudonand Brush 1992) and mechanical (Stradi et al. 1995)

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extraction techniques to isolate carotenoid pigmentsfrom bird feathers. Prior to both procedures, feathersfrom all species were washed separately in ethanol andhexane for 30 min each and blotted dry. We trimmed35 mg of pigmented barbules and split them intoequal portions for the two extractions. For the ther-mochemical method, we placed the colored barbulesin 1 mL acidified pyridine (3 drops HCl in 50 mLpyridine) and held them at 958C under argon for 4 hr.The solution was then cooled to room temperature, andwe twice extracted the lipids with 1 mL distilled waterand 5 mL hexane:tert-butyl methyl ether (1:1, v/v). Wecentrifuged the mixture for 5 min at 3000 rpm, re-moved the supernatant, and evaporated the solvent todryness under a stream of nitrogen. For the mechanicalextraction, we ground the trimmed barbules for 15 minat 30 Hz in a Retscht MM200 mixer mill (Retsch Inc.,Irvine, California) using a zirconia grinding jar andballs (fitted with a Teflont O-ring) and in the presenceof 3 mL methanol. Again, the solution was centrifugedfor 5 min at 3000 RPM and the supernatant removedand evaporated under nitrogen. For both extractionprocedures, we ran a positive control (yellow, carot-enoid-pigmented contour feathers from AmericanGoldfinches [Carduelis tristis]; McGraw et al. 2001,McGraw, Hill, et al. 2002) along with our samples.

For HPLC analysis, the purified extracts were redis-solved in 200 mL HPLC mobile phase (acetonitrile:methanol:chloroform, 46:46:8, v/v/v) and 50 mL wasinjected into a WatersTM 717plus Autosampler HPLC(Millipore Corp., Bedford, Massachusetts) fitted witha Develosil RPAqueous RP-30 column (250 3 4.6 mmID; Nomura Chemical Co. Ltd., Aichi, Japan) and anEppendorf TC-50 column heater (Hamburg, Germany)set at 328C (McGraw, Adkins-Regan, and Parker2002). We used an isocratic system (Hewlett-Packard1050 Series Isocratic Pump) at a constant flow rate of1.2 mL min21 for 90 min to allow sufficient time forboth xanthophylls and carotenes to elute. Data werecollected from 250600 nm using a WatersTM 996 pho-todiode array detector (Waters Chromatography, Mil-ford, Massachusetts). The minimum detection limit ofthis instrument is 0.0001 absorbance units, whichamounts to approximately 0.005 mg of carotenoid pergram of pigmented feather portion using this protocol.

MELANIN EXTRACTION AND CHROMATOGRAPHY

All melanin procedures were performed in the labo-ratory of SI and KW. Methods of analyzing bothphaeomelanins and eumelanins in bird feathers followthose in Haase et al. (1992). To determine eumelanincontent, colored feather barbules were homogenized inwater (1:100, w/v) and 400 mL of the homogenatewere added to 800 mL 1 M H2SO4, oxidized with 3%KMnO4. The resulting oxidation product (pyrrole-2,3,5-tricarboxylic acid; PTCA) was analyzed viaHPLC (Ito and Fujita 1985, Ito and Wakamatsu 1994).Phaeomelanins were examined by hydrolyzing 200 mLfeather homogenate with 500 mL 57% hydriodic acidat 1308C in the presence of H3PO2 for 24 hr, and sub-sequently analyzing the product (4-amino-3-hydroxy-phenylalanine; 4-AHP) using HPLC with electrochem-ical detection (Wakamatsu et al. 2002). Amounts ofeumelanin and phaeomelanin were obtained by multi-plying the amount of PTCA and 4-AHP by conversion

factors of 50 and 9, respectively (Ito and Fujita 1985,Wakamatsu and Ito 2002). Analyses of all sampleswere performed in duplicate, and we report averagesof these values here.

RESULTSIn none of the feathers from the five species studieddid we detect carotenoid pigments. Lipid-soluble ex-tracts were colorless; brown and yellow feathers re-tained their respective hues. In contrast, our featherstandards from American Goldfinches yielded 0.26mg carotenoid per g of feather (McGraw, Hill, et al.2002).

In the chestnut ventral feathers from both EasternBluebirds and Barn Swallows, we found substantialamounts of both eumelanin and phaeomelanin (Table1). Eumelanin concentrations were higher than phaeo-melanin in all bluebird and swallow samples exceptone: Barn Swallow throat feathers. Throat feathers inBarn Swallows also contained the highest concentra-tion of pigments among the four plumage regions wesampled in this species. In our bluebird samples, malefeathers tended to contain more pigments overall, anda higher percentage of eumelanin pigments, than thoseof females (Table 1).

In the breast and auricular feathers of King Pen-guins, we also detected a small amount of melanin,primarily eumelanin (Table 1). However, there re-mained much yellow pigment in the feather that couldnot be accounted for by either carotenoids or melanins.Yellow plumes from Macaroni Penguins similarly con-tained very low levels of melanin (Table 1) and re-mained brilliant yellow after pigment analyses. Thesame was true for the yellow natal down of domesticchicks, as we were unable to detect any appreciableamounts of melanins or carotenoids in these feathers(Table 1).

DISCUSSIONThe aim of this study was to analyze the extent towhich carotenoid and melanin pigments determine yel-low and brown feather coloration in a diverse groupof bird species. Although carotenoids and melanins arenot the only two forms of yellow or brown pigmentsin animals (Needham 1974, Brush 1978), several re-cent behavioral-ecology studies in birds have assumedthat yellow integumentary features (e.g., feathers,beaks) are carotenoid based (e.g., Irwin 1994, Massaroet al. 2003), and that certain rust-colored plumage col-ors contain a high concentration of carotenoid pig-ments (e.g., Mller and Mousseau 2001).

We first characterized the plumage pigments con-tained within the chestnut ventral feathers of male andfemale Barn Swallows and Eastern Bluebirds fromNorth America. We found no carotenoid pigments inthe colorful throat, breast, belly, or vent feathers ofNorth American swallows or in the breast feathers ofbluebirds. This was a surprising result, as it is reportedin the literature that the chestnut-colored facial andthroat plumage in the European subspecies of BarnSwallows (H. r. rustica) contains carotenoid pigments(e.g., Stradi 1998, Camplani et al. 1999, Saino et al.1999). Stradi (1998) first published a complete HPLCchromatogram profiling the suite of hydroxy- and keto-carotenoid pigments that are found in the rust-colored

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TABLE 1. Mean eumelanin and phaeomelanin concentrations (mg pigment per g pigmented feather barbule)in yellow and brown feathers from swallows, bluebirds, penguins, and domestic chicks. Blank entries indicatethat pigment concentrations were below our detection limit (0.01 mg g21).

Species(Plumage color) Bird ID Sex Body region Eumelanin

Phaeomela-nin

Barn Swallowa(chestnut or rufous)

pooledpooledpooledpooled

pooledpooledpooledpooled

throatbreastbellyvent

3.21.00.71.3

6.60.50.41.0

Eastern Bluebird(orange-red)

12345

malemalemalefemalefemale

breastbreastbreastbreastbreast

4.54.64.42.83.0

2.82.02.90.90.7

King Penguin(yellow-orange)

112233

unknownunknownunknownunknownunknownunknown

breastauricularbreastauricularbreastauricular

0.40.40.20.20.40.7

0.040.040.020.020.020.05

Macaroni Penguin(yellow-orange)

12

unknownunknown

head plumehead plume 0.3

0.160.2

Domestic chicken(yellow)

12

unknownunknown

natal downnatal down 0.06

a North American subspecies. Ventral feathers were pooled from 3 males and 3 females and analyzed by bodyregion.

throat feathers of European H. rustica. Saino et al.(1999) later asserted, however, that this reddish coloris mainly caused by melanin, although small amountsof lutein have also been found in these feathers (R.Stradi, unpubl. data) (p. 442).

In fact, we isolated a high concentration of melaninpigments in the chestnut ventral plumage of male andfemale Barn Swallows and Eastern Bluebirds fromNorth America. Both phaeomelanins and eumelaninswere present, and this is typical of brown feathers inother species (e.g., pigeons, ducks; Haase et al. 1992,1995). Compared to swallows, bluebirds exhibited aricher chestnut hue in the ventral plumage we exam-ined, and these feathers contained a higher overall con-centration of melanins. Among the body regions westudied in Barn Swallows, the throat feathers yieldedthe highest concentration of melanins, and this is in-variably the most deeply colored ventral region ofplumage in both sexes (Safran and McGraw 2004).Eumelanins are typically darker than phaeomelanins(Ito and Fujita 1985), however, and yet the dark throatplumage in Barn Swallows also yielded the highestpercentage of phaeomelanins compared to other feath-er regions.

Ventral plumage color is a sexually selected trait inNorth American Barn Swallows (Safran and McGraw2004) and in Eastern Bluebirds (Siefferman and Hill2004), with the most colorful birds breeding earliestand producing the most offspring in a year. To rein-force the honesty of these mating signals, there maybe physiological costs to producing brightly coloredplumage. Animals synthesize melanins from nutrition-ally dispensable amino acids (e.g., tyrosine; Meister1965), but phaeomelanin and eumelanin biosynthesis

follow markedly different biochemical pathways (Landand Riley 2000) that appear to be differentially sensi-tive to levels of circulating sex steroids in certain spe-cies (Haase et al. 1995). In Mallard drakes (Anasplatyrhynchos), for example, androgen treatment stim-ulates phaeomelanogenesis, but not eumelanogenesis,in feather tracts and results in more phaeomelanic headplumage and undertail coverts (Haase et al. 1995).Thus, there may be important and fine-tuned enzy-matic and hormonal control over the production anddeposition of these two forms of melanin pigments infeathers, so that birds may manufacture optimal levelsof phaeomelanins and eumelanins to express brightplumage coloration. There may be sex-related differ-ences in phaeomelanin or eumelanin biosynthesis aswell, as suggested by the fact that male bluebird feath-ers in this study had higher melanin levels, and a high-er relative amount of phaeomelanins, than those of fe-males.

Next, we investigated the biochemical nature of yel-low feathers in two sub-Antarctic penguin species andfrom domestic chicks. Again, despite the widespreadview that yellow plumage is derived from carotenoidsin birds (e.g., in finches, sparrows, woodpeckers; Fox1976, Stradi 1998), we found that yellow feathers inpenguins and domestic chicks lacked carotenoids en-tirely. We also investigated the possibility that theseyellow plumage colors could be attributed to the pres-ence of melanins, as there is evidence in mammals thatyellow fur contains melanins (primarily phaeomelanin;Cone et al. 1996, Miltenberger et al. 1999) and assome have speculated about the melanic nature of yel-low chick feathers (Volker 1934). In King Penguinfeathers, we indeed found small amounts of melanin

394 SHORT COMMUNICATIONS

pigments. These were primarily eumelanins, but oc-curred nearly one order of magnitude less in concen-tration than in the brown feathers described above forbluebirds and swallows. Pigmented plumage regionsin King Penguins have been occasionally described asorange (Jouventin 1982), and in the hand individualfeathers appear yellow at the base but tipped withsmall amounts of brown. This small amount of mela-nin is presumably what gives King Penguin featherstheir brown edges.

In contrast to King Penguin plumage, only traceamounts of melanin were quantified from yellow Mac-aroni Penguin and domestic chick feathers. However,like King Penguin feathers, a substantial amount ofyellow pigment remained after analysis that could notbe classified as either melanin or carotenoid. At pre-sent, the only other yellow pigments that have beendescribed from bird feathers are the psittacofulvinsfound in the plumage of parrots (Stradi 1998) and pter-in pigments in the yellow, orange, and red irises ofblackbirds, starlings, owls, and pigeons (e.g., Oehme1969, Oliphant 1988, Oliphant et al. 1992, Oliphantand Hudon 1993, Hudon and Muir 1996). We havegathered preliminary biochemical evidence that theseyellow penguin and chick pigments are soluble in mildacids and bases and fluoresce strongly under UV light,characteristics that typify pterins (Needham 1974).This suggests that penguins and domestic chicks colorthemselves with a class of pigments never before de-scribed from bird feathers.

We thank F. Bath and Retsch Inc. for loaning themixer mill that was used to grind feathers, four anon-ymous referees for helpful comments on the manu-script, and the American Museum of Natural History,Sigma Xi, the Environmental Protection Agency(grants to KJM), the National Science Foundation(IBN 97122971 to GEH and OPP0128913 to PMN andFSD), and the Ministry of Education, Science, Sportsand Culture of Japan (Grant # 14570829 to KW andSI) for funding this research.

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HAASE, E., S. ITO, A. SELL, AND K. WAKAMATSU. 1992.Melanin concentrations in feathers from wild anddomestic pigeons. Journal of Heredity 83:6467.

HAASE, E., S. ITO, AND K. WAKAMATSU. 1995. Influ-ences of sex, castration, and androgens on the eu-melanin and phaeomelanin contents of differentfeathers in wild Mallards. Pigment Cell Research8:164170.

HUDON, J., AND A. H. BRUSH. 1992. Identification ofcarotenoid pigments in birds. Methods in Enzy-mology 213:312321.

HUDON, J., AND A. D. MUIR. 1996. Characterization ofthe reflective materials and organelles in the brightirides of North American blackbirds (Icterinae).Pigment Cell Research 9:96104.

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ITO, S., AND K. FUJITA. 1985. Microanalysis of eume-lanin and phaeomelanin in hair and melanomas bychemical degradation and liquid chromatography.Analytical Biochemistry 144:527536.

ITO, S., AND K. WAKAMATSU. 1994. An improved mod-ification of permanganate oxidation that givesconstant yield of pyrrole-2,3,5-tricarboxylic acid.Pigment Cell Research 7:141144.

JOUVENTIN, P. 1982. Visual and vocal signals in pen-guins: their evolution and adaptive characters. P.Parey, Berlin.

LAND, E. J., AND P. A. RILEY. 2000. Spontaneous redoxreactions of dopaquinone and the balance betweenthe eumelanic and phaeomelanic pathways. Pig-ment Cell Research 13:273277.

MASSARO, M., L. S. DAVIS, AND J. T. DARBY. 2003.Carotenoid-derived ornaments reflect parentalquality in male and female Yellow-eyed Penguins(Megadyptes antipodes). Behavioral Ecology andSociobiology 55:169175.

MCGRAW, K. J., E. ADKINS-REGAN, AND R. S. PARKER.2002. Anhydrolutein in the Zebra Finch: a new,metabolically derived carotenoid in birds. Com-parative Biochemistry and Physiology B 132:811818.

MCGRAW, K. J., G. E. HILL, R. STRADI, AND R. S.PARKER. 2001. The influence of carotenoid acqui-sition and utilization on the maintenance of spe-cies-typical plumage pigmentation in male Amer-ican Goldfinches (Carduelis tristis) and NorthernCardinals (Cardinalis cardinalis). Physiologicaland Biochemical Zoology 74:843852.

MCGRAW, K. J., G. E. HILL, R. STRADI, AND R. S.PARKER. 2002. The effect of dietary carotenoid ac-cess on sexual dichromatism and plumage pig-

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MILTENBERGER, R. J., R. L. MYNATT, B. D. BRUCE, W.O. WILKISON, R. P. WOYCHIK, AND E. J. MICHAUD.1999. An agouti mutation lacking the basic do-main induces yellow pigmentation but not obesityin transgenic mice. Proceedings of the NationalAcademy of Sciences 96:85798584.

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OLIPHANT, L. W., J. HUDON, AND J. T. BAGNARA. 1992.Pigment cell refugia in homeothermsthe uniqueevolutionary position of the iris. Pigment Cell Re-search 5:367371.

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SIEFFERMAN, L. M., AND G. E. HILL. 2004. Structuraland phaeomelanin colors indicate male quality inthe Eastern Bluebird (Sialia sialis). BehavioralEcology 14:855861.

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STRADI, R., G. CELENTANO, AND D. NAVA. 1995. Sep-aration and identification of carotenoids in birdsplumage by high-performance liquid chromatog-raphydiode-array detection. Journal of Chro-matography B 670:337348.

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WAKAMATSU, K., AND S. ITO. 2002. Advanced chemi-cal methods in melanin determination. PigmentCell Research 15:174183.

WAKAMATSU, K., S. ITO, AND J. L. REES. 2002. Theusefulness of 4-amino-3-hydroxyphenylalanine asa specific marker of phaeomelanin. Pigment CellResearch 15:225232.

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The Condor 106:395400q The Cooper Ornithological Society 2004

CAN LANCHESTERS LAWS HELP EXPLAIN INTERSPECIFIC DOMINANCE IN BIRDS?

ERIN L. SHELLEY, MAILE Y. U. TANAKA, ANNA R. RATNATHICAM AND DANIEL T. BLUMSTEIN1

Department of Organismic Biology, Ecology, and Evolution, University of California, 621 Young Drive South,Los Angeles, CA 90095-1606

Abstract. We studied the applicability of Lanches-ters laws of combat to explain interspecific dominancein birds. We focused on 10 species of Australian birdsin the arid zone of New South Wales that foraged atan established locust trap. Consistent with the linearlaw, larger species usually dominated smaller speciesin one-on-one encounters. We found no support for theN-square law, which predicted that large numbersof smaller species could dominate larger species when

Manuscript received 31 July 2003; accepted 8 Jan-uary 2004.

1 Corresponding author: E-mail: marmots@ucla.edu

more abundant. Further analysis of the most abundantspecies revealed that it was less likely to visit the lo-cust trap when larger, more dominant heterospecificswere present. Body size, and not numerical superiority,seems to be an important determinant in interspecificforaging decisions in birds.

Key words: body size, foraging behavior, groupsize, interspecific competition, Lanchesters laws.

Puede la Ley de Lanchester Ayudar aExplicar la Dominancia Interespecfica enAves?

Resumen. Hemos estudiado la aplicabilidad de lasleyes del combate de Lanchester en explicar la domi-

396 SHORT COMMUNICATIONS

nancia interespecfica en aves. Hemos focalizado esteestudio en 10 especies de aves australianas de la zonaarida de New South Wales, las cuales se alimentaronen trampas de insectos establecidas para tal fin. Con-sistente con la ley lineal, las especies de mayor ta-mano usualmente dominaron a las especies mas pe-quenas en los encuentros uno a uno. No encontramosevidencia que apoye la ley cuadratica, la cual pre-dice que un gran numero de especies de pequeno ta-mano podran dominar a especies de tamano mayorcuando las primeras son mas abundantes. Posterioresanalisis sobre la especie mas abundantes revelaron quela probabilidad de visita a las trampas de insectos esmenor cuando individuos heteroespecficos mas gran-des y mas dominantes estan presentes. El tamano cor-poral, y no la superioridad numerica, parece ser unimportante factor en las decisiones de forrajeo en lasaves.

Competition for resources within multispecies systemsleads to the establishment of dominance hierarchies inwhich certain species outcompete others (Wallace andTemple 1987, Travaini et al. 1998, Sandlin 2000). Insome cases, body size is the primary factor that deter-mines interspecific rank (Kohda 1991, Daily and Ehr-lich 1994, Bassett 1995, McGlynn 2000). However, inother instances, the relative number of individuals, in-dependent of body size or behavior, may affect inter-specific dominance (Basset 1997, Burger and Gochfeld1984, Creel 2001, Chapman and Kramer 1996, Mc-Glynn 2000).

The study of human warfare has led to the devel-opment of many different military strategies. In 1916,F. W. Lanchester published his theory of combat,which included two mathematical models which havebecome known as the linear law and the N-squarelaw (Lanchester 1916). The linear law predicts thatin one-on-one combat, the stronger (i.e., larger) indi-vidual will win. The N-square law predicts that larger-numbered groups can overcome smaller-numberedgroups, with differences in individual body size beingof little or no importance. Aside from military appli-cations, small businesses have used Lanchesters strat-egies to take over markets dominated by larger busi-ness (e.g., Yano 1995), a scenario which is at leastsuperficially much like animals competing for accessto a limited resource. Recently, biologists have begunto test the applicability of these laws to a variety ofanimal species engaged in mortal combat. In 1993,Franks and Partridge were the first to show that Lan-chesters models could explain the outcome of inter-actions among slave-making and army ants. Additionalstudies of interspecific competition among ants(McGlynn 1999, 2000) provide further support for thelinear and N-square laws. Intraspecific interactionsamong ants (Whitehouse and Jaffe 1996), as well asbetween chimpanzee groups (Wilson et al. 2002), alsofollow the predictions Lanchester set forth. In thesestudies, larger individuals dominated smaller individ-uals in one-on-one lethal combat (Lanchesters linearlaw), and greater numbers of individuals dominatedfewer numbers regardless of individual body size(Lanchesters N-square law).

We observed the behavior of birds foraging for in-sects at a locust trap in the arid zone of southeasternAustralia. We studied interspecific interactions to de-termine the effect of (1) species type, (2) body size,and (3) abundance on interspecific dominance rank. Indoing so, we evaluated Lanchesters laws ability toexplain nonfatal aggression and dominance in this as-semblage. Although the interactions between thesespecies are not immediately lethal, the ephemeral andpatchy nature of resources in the arid zone increase theimportance of locating and obtaining food. Should in-terspecific interactions interfere with an individualsability to obtain food, we can envision a large fitnesscost.

METHODS

We observed birds foraging at an insect light trap setup by the Australian Plague Locust Commission formonitoring and researching plague locusts on the Fow-lers Gap, New South Wales sheep station (31859S,1428429E). This locust trap, though technically an ar-tificial food source for birds in the area, was in oper-ation from 19761988, and 1994 to present. The trapconsisted of a 3.0-m-diameter circular metal tub posi-tioned 0.6 m above the ground and filled with 0.15 mof water. Trees and brush were present nearby. We po-sitioned ourselves on a platform 22.3 m from the locusttrap. Directly above the center of the tub, a bright lightwas turned on nightly. Insects, most commonly moths(Order Lepidoptera), were drawn to and disoriented bythe light, whereupon they fell into the water and col-lected on the surface. Additionally, a large number ofwater insects such as water-boatmen and backswim-mers (Hemiptera) and diving beetles (Coleoptera) in-habited the trap. Although the relative abundance ofinsects in the trap seemed to vary each morning, avariety of insects were present each day. All observedbird species foraged on these insects on multiple oc-casions, although not all were exclusively insectivo-rous (e.g., honeyeaters).

During 53 hr of morning observations between 21April and 3 May 2001, we continuously recorded ev-ery dominantsubordinate interspecific interaction thatoccurred at the locust trap as a win or a loss. At thetime of the interaction, the recorder noted the speciesof the winner and loser, the time of the interaction, andthe number of other individuals of each species presentat the trap. Presence was predefined as being perchedatop or inside the main tub of the trap or the lightcanister, flying in the immediate airspace, (within 0.3vertical m of the surface of the trap), or sitting atop asmall post connected to one edge of the tub. Domi-nant-subordinate interactions consisted of pecking at,chasing, supplanting, or any other interactions inwhich the subordinate individual of one species movedaway as a direct result of the dominant individual ofa different species actions. We took care to avoid re-cording what appeared to be coincidental, simulta-neous departures from the locust trap, as well as de-partures that were potentially attributable to externaldisturbances.

In order to ascertain which species were likely tointeract, and to calculate the overall rate of speciesvisitation, we also took an instantaneous census of the

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TABLE 1. Body size and mass hierarchy for insectivorous birds foraging at a locust trap in New South Wales,Australia. Body sizes are midpoints of ranges reported in Pizzey and Knight (2001). Average body masses arefrom Geffen and Yom-Tov (2000), except for Yellow-throated Miner and White-plumed Honeyeater (Higgins etal. 2001), Spiny-cheeked Honeyeater (Casotti and Richardson 1992), and Singing Honeyeater (Wooler et al.1985).

Species Body size (cm) Body mass (g)

Australian Raven (Corvus coronoides)Australian Magpie (Gymnorhina tibicen)Apostlebird (Struthidea cinerea)Magpie-lark (Grallina cyanoleuca)Yellow-throated Miner (Manorina flavigula)

50.041.031.028.026.3

674.5322.8130.0

80.055.0

Spiny-cheeked Honeyeater (Acanthagenys rufogularis)Willie Wagtail (Rhypidura leucophrys)Restless Flycatcher (Myiagra inquieta)Singing Honeyeater (Lichenostomus virescens)White-plumed Honeyeater (Lichenostomus penicillatus)

24.020.518.520.016.0

44.019.015.019.018.5

number of each species present at the trap every 2 min.From the preliminary observations, we determined thata 2-min interval gave the most reasonable overview ofthe dynamics of bird visitation to the trap. In addition,at the beginning of every hour, the current weatherconditions and temperature were recorded.

We standardized the census data by dividing the 6-hr observation window into three 2-hr periods (06:0008:00, 08:0110:00, 10:0112:00) based upon naturaldivisions in a plot of species abundance over time.Then, for these three time intervals, we divided thenumber of birds of each species by the total numberof observation points to obtain the rate of visitation ofeach species for each interval. From this, we were ableto see what species were rarely or never present at thesame time, exclude them, and develop a subhierarchyfor each period. Ten avian species (Table 1; scientificnames therein) visited the trap during our period ofobservation and were used for our statistical analyses.These 10 species were all observed foraging on deadinsects in the trap on multiple occasions. We removeda single interaction where a Restless Flycatcher veryaggressively mobbed an Australian Raven becausemobbing is not a typical foraging behavior.

STATISICAL ANALYSES

To test the applicability of Lanchesters linear law tothis group of birds, we compared whether the domi-nance patterns exhibited at the food source matchedthe size hierarchy we created by comparing body size(cm) and mass (g) of the species. To quantify domi-nance at the trap, we input the win-loss data into theprogram Peck Order (Hailman 1994) to create an over-all hierarchy spanning the entire observation period.To determine whether body size explained significantvariation in dominance ranking, we calculated Spear-man rank correlations of rank versus the midpoint ofthe body length and rank versus average mass.Throughout, we interpret P , 0.05 as significant.

We calculated subhierarchies during each of thethree census periods and excluded uncommon speciesuntil we obtained a linear hierarchy (Landaus h 5 1.0;Lehner 1996). For period 1, we first excluded SingingHoneyeater because they were never present during

that period, and then excluded Australian Ravens,Spiny-cheeked Honeyeaters, and White-plumed Hon-eyeaters because certain dyadic encounters with thesespecies did not occur. To create a linear hierarchy inperiod 2, we excluded Australian Ravens because theywere not present during that period, and then Spiny-cheeked Honeyeaters, Singing Honeyeaters, andWhite-plumed Honeyeaters. To create a linear hierar-chy in Period 3, we excluded Australian Ravens be-cause they were never present, and then Spiny-cheekedHoneyeaters, Yellow-throated Miners, Apostlebirds,and Australian Magpies.

In addition, because Willie Wagtails were presentmore often than any other species and were also pre-sent throughout the entire observational period, wewere able to use a contingency table analysis to deter-mine whether the time Willie Wagtails spent at thefeeder was influenced by the presence or absence ofother birds.

To test the applicability of Lanchesters N-squarelaw, we determined whether the presence or numberof potential competitors influenced the outcome of anencounter. We fitted logistic regressions using Stat-View 5.1 (SAS Institute 1999) to estimate the variationexplained by group size on the likelihood that an in-dividual of a species would win or lose an interactionwith another species. Species-pairs were selected basedon the number of observations.

RESULTS

LINEAR LAW

Our overall hierarchy, compiled from the win-loss datafor the 10 species feeding on the locust trap, was notstrictly linear (Table 2). Although not all of the 10species had the same likelihood of being seen at thesame times at the trap, causing certain dyadic encoun-ters to be either missing or tied in our data set, theoverall best-fit dominance hierarchy followed thebody-size hierarchy (Table 1).

When we focused on birds regularly present at thesame time, dominance rank was positively correlatedwith body size. For both period 1 and period 2, thehierarchy was, from most dominant to most subordi-

398 SHORT COMMUNICATIONS

TABLE 2. Interspecific dominance matrix for 10 bird species foraging at a locust trap in New South Wales,Australia. Species are arranged by body size. Winners are listed down the left column; losers are listed acrossthe upper row. Values within the matrix represent the number of occurrences of each win-loss dyad. Not allpossible dyadic interactions occurred; the matrix reflects the best-fit hierarchy.

Winners

Losers

Aust.Raven

Aust.Magpie

Apostle-bird

Magpie-lark

Y-thrtd.Miner

Sp-ch.Honey-

eaterWillie

WagtailFly-

catcher

SingingHoney-

eater

Wh-pl.Honey-

eater

Australian RavenAustralian MagpieApostlebirdMagpie-larkYellow-throated Miner

0000

6100

728

80

21822

0

0151111

01061

0122445

5

045

271

00010

00060

Spiny-cheeked HoneyeaterWillie WagtailRestless FlycatcherSinging HoneyeaterWhite-plumed Honeyeater

00000

00000

01000

00100

01000

0000

4

431

15

00

0833

1257

TABLE 3. The unique linear hierarchy of species foraging at a locust trap in New South Wales, Australia,during periods 1 (06:0008:00) and 2 (08:0110:00). Species are arranged by body size. The species compo-sitions and dominance rankings were the same for these two periods; therefore we combined these numbers intoa single matrix. Landaus h 5 1.

Winners

Losers

Magpie Apostlebird Magpie-larkY-thrtd.Miner

WillieWagtail Flycatcher

Australian MagpieApostlebirdMagpie-larkYellow-throated MinerWillie WagtailRestless Flycatcher

10000

28

8010

1822

001

151111

10

122445

5

4

45

2715

nate, Australian Magpies, Apostlebirds, Magpie-larks,Yellow-throated Miners, Willie Wagtails, Restless Fly-catchers (Table 3). For period 3, the hierarchy wasMagpie-larks, Willie Wagtails, Restless Flycatchers,Singing Honeyeaters (Table 4). All three of these hi-erarchies were linear with a Landaus h 5 1. The mid-points of species body length (rs 5 0.99, P , 0.001)and average body mass (rs 5 0.95, P , 0.001) wereboth highly correlated with rank.

The presence of Willie Wagtails was significantlyaffected by the presence or absence of other species atthe locust trap (x21 5 6.1, P 5 0.01). Out of 1733censuses, Willie Wagtails were present during 220. Ofthese, Willie Wagtails were present at 154 censuseswhen other species dominant to Willie Wagtails wereabsent, but were present at only 66 censuses when oth-er species dominant to Willie Wagtails were present.Of the 1513 censuses at which Willie Wagtails wereabsent, there were 1173 censuses where species dom-inant to Willie Wagtails were absent as well and 340censuses where species dominant to Willie Wagtailswere present. Willie Wagtails were more likely to bepresent at the locust trap in the absence of other moredominant birds.

N-SQUARE LAW

Of the 10 logistic regressions, only the Apostlebirdsversus all others visiting the feeder showed any sig-nificant association between group size and dominance(P , 0.001, Table 5). This relationship was, however,negative: as Apostlebird numbers increased, their like-lihood of dominating other species decreased.

DISCUSSION

Body size in this particular group of Australian insec-tivorous birds was positively correlated with the inter-specific dominance relationships we observed at Fow-lers Gap. The species that dominated more often werethose that had a larger overall body size. This supportsLanchesters linear law in that larger species will dom-inate smaller species in one-on-one interactions.

Further support for the linear law is seen in our anal-ysis of how the presence or absence of Willie Wagtailswas influenced by other species. Willie Wagtails weresignificantly less likely to be at the locust trap whenan individual of a larger, more dominant species waspresent. This suggests that the different bird speciesmight have used the presence and size of other species

SHORT COMMUNICATIONS 399

TABLE 4. The unique linear hierarchy of species foraging at a locust trap in New South Wales, Australia,during period 3 (10:0112:00). Species are arranged by body size. Landaus h 5 1.

Winners

Losers

Magpie-larkWillie

WagtailRestless

FlycatcherSp-ch.

HoneyeaterWh-pl.

Honeyeater

Magpie-larkWillie WagtailRestless FlycatcherSpiny-cheeked HoneyeaterWhite-plumed Honeyeater

0100

45

431

275

00

1833

6257

TABLE 5. Summary of the logistic regression models that explained the probability that a given species wouldwin an encounter given the group size of its competitor. Group sizes are means 6 SD. Full common namesappear in Table 1.

Species 1

Species Group sizeNo. ofwins

No. oflosses

Competitor

Species Group size P R2

ApostlebirdAustr. MagpieMagpie-larkApostlebirdAustr. Raven

6.3 6 3.31.7 6 0.51.3 6 0.54.6 6 2.91.5 6 0.5

118

86315

280

2244

0

Austr. MagpieMagpie-larkApostlebirdall speciesaall speciesa

1.6 6 0.51.1 6 0.33.6 6 1.81.9 6 0.94.6 6 3.2

0.15

0.97,0.001

0.44

0.0020.10

Austr. MagpieMagpie-larkSp-ch. HoneyeaterWh-pl. HoneyeaterY-thrtd. Miner

1.5 6 0.51.3 6 0.51.2 6 0.51.9 6 1.41.9 6 1.2

78104

1047

743152138

all speciesaall speciesaall speciesaall speciesaall speciesa

3.9 6 3.02.7 6 2.01.8 6 1.31.9 6 0.92.8 6 2.7

0.270.060.200.390.12

0.030.020.050.030.06

a All other species present during species 1s interactions.

present at the locust trap when deciding whether toland and forage (Daily and Ehrlich 1994). These pat-terns of interspecific social interactions or avoidancecan influence both the instantaneous and long-term dis-tributions of birds in a given area. Thus, pairwise dom-inance relationships may explain the development ofdifferent ecological niches, as well as resource parti-tioning (Fisler 1977, Nagamitsu and Inoue 1997).

However, we found no support for Lanchesters N-square law with our data. Group size was not a sig-nificant factor in influencing interspecific dominanceinteractions among the 10 bird species that fed at thelocust trap. Of the 10 logistic regressions we ran, onlyone was significant. For some of the pairings, the lackof significance may result from a paucity of data. Thenegative relationship in the one significant regressionis further evidence against Lanchesters N-square law.The N-square law also may not apply to these birdsdue to the lesser degree of cooperation seen in flocksor gatherings of birds as compared to humans, chim-panzees, or ants.

The birds foraging at the locust trap were concen-trated around an abundant food source. Thus, it is rea-sonable to assume that the same dominance relation-ships identified in our study are likely to apply at con-centrated food patches throughout the arid zone.

In conclusion, while it seems that both of Lanches-ters laws have great explanatory value for potentially

fatal combat among ants and chimpanzees, the N-square law has limited ability to explain the nonfatalinterspecific dominance hierarchies in at least onegroup of Australian insectivorous birds. These specificfindings may have applicability to a much broader un-derstanding of behavioral interactions among speciesinhabiting a common habitat and sharing some or allof the same resources.

Research protocols were approved by the Universityof New South Wales Animal Care and Ethics Com-mittee (permit # 02/08). Partial support of the projectcame from grants by the UCLA Office of InstructionalImprovement, the Department of Organismic Biology,Ecology and Evolution, and the Lida Scott Brown Or-nithology Trust. We thank the staff of the Fowlers GapStation for logistical support, David Croft for assis-tance obtaining permits, and Claudia Cecchi, JaniceDaniel, Peter Nonacs, and Aviva Liebert for additionalhelp. We also thank Paul Walker and the AustralianPlague Locust Commission for the use of their locusttrap as well as providing us with background infor-mation. Comments by David Dobkin and two anony-mous reviewers helped us tighten and clarify our mes-sage.

400 SHORT COMMUNICATIONS

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SHORT COMMUNICATIONS 401

The Condor 106:401404q The Cooper Ornithological Society 2004

PARENTAGE IN AN OKLAHOMA POPULATION OF LOGGERHEAD SHRIKES ASSESSEDUSING NUCLEAR MICROSATELLITES

MATTHEW A. ETTERSON1

Conservation Biology Program, University of Minnesota, 100 Ecology Building, 1987 Upper Buford Circle,St. Paul, MN 55108

Abstract. I used six nuclear microsatellites to as-sess rates of intraspecific brood parasitism and extra-pair paternity in relationship to conspecific density in218 offspring from 44 broods of Loggerhead Shrikes(Lanius ludovicianus). I also estimated statistical pow-er associated with these markers for each parentagetest and suggest a method for adjusting power esti-mates when individuals are incompletely genotyped.No offspring were the result of intraspecific brood par-asitism. Eight offspring from five families (4% of alloffspring; 14% of families) were sired by extra-pairfertilization. Average exclusionary power was 0.94when adjusted to account for incomplete genotyping.Assuming a 1% genotyping error rate, this powerdrops to 0.91. This is the first genetic assessment ofparentage in a wild population of Loggerhead Shrikes.

Key words: extra-pair fertilization, Lanius ludovi-cianus, Loggerhead Shrike, parentage exclusion, pow-er.

Parentesco en una Poblacion de Oklahoma deLanius ludovicianus Evaluado UsandoMicrosatelites Nucleares

Resumen. Utilice seis microsatelites nucleares paraevaluar las tasas de parasitismo intra-especfico de lanidada y paternidad extra-pareja con relacion a la den-sidad de individuos coespecficos en 218 cras prove-nientes de 44 nidadas de Lanius ludovicianus. Tambienestime el poder estadstico asociado con estos marca-dores para cada prueba de paternidad y sugiero un me-todo para ajustar las estimaciones de poder cuando elgenotipo de los individuos no ha sido determinadocompletamente. Ninguna cra fue el resultado de pa-rasitismo intra-especfico de la nidada. Ocho cras pro-venientes de cinco familias (4% de todas las cras;14% de las familias) fueron engendradas por medio defertilizaciones extra-pareja. El poder de exclusion pro-medio fue de 0.94 cuando fue ajustado para tener encuenta los genotipos incompletos. Suponiendo que latasa de error de evaluacion genotpica es del 1%, este

Manuscript received 3 February 2003; accepted 20November 2003.

1 Present address: U.S. Environmental ProtectionAgency, Mid-Continent Ecology Division, 6201 Cong-don Boulevard, Duluth, MN 55804. E-mail: etterson.matthew@epa.gov

poder desciende a 0.91. Esta es la primera evaluaciongenetica de parentesco en una poblacion silvestre deL. ludovicianus.

Loggerhead Shrikes (Lanius ludovicianus) settle in rel-atively dense territorial clusters (Cade and Woods1997, Pruitt 2000, Etterson 2000, 2003). Woods (1995:154) reported spatial clumping in the distribution ofLoggerhead Shrikes nesting in sagebrush habitats ofsouthwestern Idaho and discussed the potential rolesof nest predation and the need to find suitable matesas causes for aggregation. Etterson (2003) found thatnave shrikes nesting in southwest Oklahoma weremore likely to settle near conspecifics than were indi-viduals with previous experience in the study area. Inan unpublished 1990 report to the Indiana Departmentof Natural Resources, K. Burton and D. Whiteheadfound 20 of 117 (17%) nest attempts by LoggerheadShrikes in Indiana in 1988 and 1989 in a single town-ship (93 km2). Only 13% of these 117 attempts wereisolated from conspecifics by more than 5 km. Pruitt(2000) cited unpublished reports of territorial aggre-gation in Montana and New York.

Recent research in avian mating systems has sug-gested that the pursuit of extra-pair mating strategiesmay lead to aggregation and the evolution of colonia-lity in territorial birds (Wagner 1993, Hoi and Hoi-Leitner 1997). Westneat and Sherman (1997) foundpositive correlations between extra-pair fertilization(EPF) rates and conspecific density in eight of 11 stud-ies. Rates of intraspecific brood parasitism have alsobeen shown to correlate with density in at least threebird species including the Eared Grebe (Podiceps ni-gricollis; Hill et al. 1997), Wood Duck (Aix sponsa;Semel et al. 1988), and Common Moorhen (Gallinulachloropus; Ueda et al. 1993).

The objective of this study was to assess rates ofintraspecific brood parasitism and EPF in LoggerheadShrikes in relation to conspecific density in order toevaluate the potential for extra-pair mating strategiesto influence conspecific density in this species.

METHODSI collected tissue from 44 broods (218 offspring) ofshrikes breeding in Comanche County, Oklahoma(348N, 988W), during the 1998 and 1999 breeding sea-sons. For 31 broods (156 offspring) I sampled bothparents. For an additional five broods (23 offspring) Isampled only the putative father and for another eight

402 SHORT COMMUNICATIONS

broods (39 offspring) I sampled only the putativemother. I trapped adults using modified potter traps(Craig 1997) and mist nets, and banded each with aUnited States Fish and Wildlife Service aluminumband and a unique combination of three plastic colorbands. I took one rectrix and two contour feathers fromeach adult and stored them at 2208C. I sampled nes-tlings at 8 days using the same protocol.

I extracted DNA from the basal 45 mm of the ra-chis of feathers using the Qiagen DNA Mini Kit (Qia-gen, Valencia, California) with the standard protocolmodified as follows. I digested the feather tissue for2436 hr in lysis buffer and added a second (20 mL)aliquot of Proteinase K to ensure the complete diges-tion of feather tissue. At the final step, I passed theeluate back through the microfilter (for adult feathertissue only) to increase the concentration of DNA.

I took primers for six microsatellite loci fromMundy et al. (1997). Four of these loci (LS1, LS2,LS3, and LS4; Mundy and Woodruff 1996) were orig-inally developed from Loggerhead Shrike tissue. Onelocus each was developed from Florida Scrub-Jay (Ap-helocoma coerulescens) and Long-tailed Manakin(Chiroxiphia linearis; SJR4 and LTMR7 respectively,MacDonald and Potts, unpubl. data). I labeled all prim-ers with one of three fluorescent dyes (6-FAM, HEX,TET). I optimized PCR using a MasterAmp PCR op-timization kit (Epicentre Technologies, Madison, Wis-consin) and I performed all reactions on ThermolyneAmplitron II Thermal Cyclers (Barnstead Internation-al, Dubuque, Iowa) using touchdown PCR (Hecker andRoux 1996) to increase yield and reduce nonspecificpriming. I visualized fragments on an ABI 310 GeneticAnalyzer (PE Applied Biosystems, Foster City, Cali-fornia). I initially typed fragments using Genotyper 3.0software (PE Applied Biosystems 1999), and then ver-ified all assignments visually.

STATISTICAL ANALYSES

I calculated observed heterozygosity for each locus asthe frequency of adults that were heterozygous at thatlocus. I estimated expected heterozygosity as 1 2 Sip2i, where pi is the frequency of allele i. The presenceof null alleles could result in an apparent mismatchbetween parent-offspring genotypes and result in anoverestimate of EPF rates. Null alleles will also resultin more apparently homozygous individuals thanwould be expected under Hardy-Weinberg conditions.To determine whether null alleles were likely amongthe individuals I sampled, I used a recent update ofthe software program GENEPOP (Version 3.3; Ray-mond and Rousset 1995) to test for heterozygote de-ficiency, a one-sided test of departure from Hardy-Weinberg equilibrium. I also performed a second testfor null alleles using CERVUS (Marshall et al. 1998).Finally, I used GENEPOP to test for linkage disequi-librium among loci.

PARENTAGE ANALYSIS

For each offspring tested I excluded an attending par-ent as a true parent when the offspring genotype couldnot have arisen from the parent based on Mendelianinheritance patterns. To increase power of paternitytests I also compared paternal genotypes to offspringgenotypes contingent upon the presumed maternal ge-

notype. This was not necessary to do for maternitytests (i.e., to test for intraspecific brood parasitism) be-cause no offspring failed to share at least one allele ateach locus with its presumed mother (see results be-low). For offspring for which I had sampled only thepresumed father (n 5 23), I tested for cases in whichthe offspring and presumed father did not share allelesat one or more loci.

I calculated single-locus exclusion power usingequations described in Chakraborty et al. (1988), butmodified to allow for incomplete genotyping as fol-lows: If pi is the proportion of individuals typed atlocus i, and PE is the calculated exclusionary power atthat locus, then the functional exclusionary power atthat locus is

P9 5 p 3 PE i E

which gives a revised estimate (b9i) of the probabilityof a Type II error:

b9 5 1 2 P9 5 1 2 p 3 Pi E i E

I estimated expected multilocus exclusionary powerusing equations in Bruford et al. (1992).

For each offspring I also used CERVUS (Marshallet al. 1998) to determine the most likely father fromamong all genotyped males (including the attendingmale) nesting concurrently and within 5 km of the nestin which the offspring hatched. I scored an offspringas having been sired by EPF when both exclusion andCERVUS indicated the offspring had been sired byEPF, in other words, when the offspring could not haveinherited its alleles from the attending male and an-other genotyped male was scored as being a more like-ly sire than the attending male. To investigate the re-lationship between EPF and local density I performeda logistic regression with EPF as the response variableand distance to nearest neighbor as the independentvariable using SAS 8.0 (SAS Institute 1999). I calcu-lated distance to nearest neighbor as the linear distancebetween adjacent nests. I also report the probability ofexclusion (here calculated as one minus the probabilityof nonexclusion) as estimated by CERVUS.

RESULTS

Both GENEPOP and CERVUS detected significant de-partures from Hardy-Weinberg equilibrium at LS1 (P, 0.02 and P , 0.01, respectively). Using algorithmsfrom Summers and Amos (1997) CERVUS estimatednull allele frequency at LS1 to be 0.03. Using GE-NEPOP I detected no evidence of linkage disequilib-rium among pairwise comparisons of LS1, LS2, LS3,LS4, and SJR4. No comparisons with LTMR7 werepossible because the large number of genotypes at thislocus resulted in expected values too small to conformto chi-square assumptions.

Multilocus exclusion power ranged from 0.63 to0.99 and averaged 0.94 (Table 1). Expected multilocusexclusionary power was 0.94. Both observed and ex-pected exclusionary power for each locus are given inTable 1. These estimates always agreed to within 4percentage points. The average multilocus probabilityof exclusion as calculated by CERVUS (with a 1%genotyping error rate) was 0.91.

SHORT COMMUNICATIONS 403

TABLE 1. Number of alleles, heterozygosity, and exclusionary power at six microsatellite loci used for pa-ternity exclusion in Loggerhead Shrikes.

Locusa Alleles

Heterozygosity

Observed Expected

Exclusionary power (multilocus)b

Average Expected

Proportion ofindividuals typed(adults/juveniles)

LS4LS2SJR4LS3LS1LTMR7

43646

14

0.290.440.380.390.720.83

0.350.470.400.490.640.90

0.150.24 (0.35)0.25 (0.52)0.23 (0.63)0.37 (0.77)0.73 (0.94)

0.180.21 (0.35)0.22 (0.50)0.23 (0.61)0.41 (0.77)0.74 (0.94)

0.97/1.00.98/1.0

1.0/1.00.99/1.0

1.0/1.00.92/1.0

a Loci are in ascending order by exclusionary power.b Multilocus exclusionary power calculated with all preceding loci in table.

Among 195 offspring from 39 families (all familiesfor which I had sampled the putative mother), allshared at least one allele at each locus with their moth-er. Among 179 offspring from 36 families for which Ihad sampled the putative father, eight offspring fromfive families were both excluded from being sired bythe attending male and were successfully assigned toanother male within 5 km. EPF occurred in 4% ofoffspring from 14% of broods. When an EPF occurredit was not typically assigned to the nearest neighbor,except in two cases in which only one other male wasgenotyped within 5 km. Logistic regression showed aslightly positive (slope parameter ,0.001), thoughnonsignificant, relationship between presence of anEPF offspring and distance to nearest neighbor (x2 50.2, P 5 0.66).

DISCUSSION

Exclusionary power using these six markers was good,even with the relatively low degree of variation at mostof the loci. The rate of EPF discovered here in Log-gerhead Shrikes (4%) is similar to rates reported forother shrike species. Using multilocus DNA finger-printing, Yamagishi et al. (1992) found that 10 of 99(10%) Bull-headed Shrike (Lanius bucephalus) nes-tlings were sired by EPF. Fornasari et al. (1994) usedthe same technique to discover that 1 of 19 (5%) nes-tlings of Red-backed Shrikes (Lanius collurio) weresired by EPF. In a behavioral study of Northern Shrikes(Lanius excubitor) in Poland, Lorek (1995) observed23 of 83 (28%) copulati