Abe Et Alii - The Analysis of Cutmarks on Archaeofauna

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The Analysis of Cutmarks on Archaeofauna: A Review and Critique of QuantificationProcedures, and a New Image-Analysis GIS ApproachAuthor(s): Yoshiko Abe, Curtis W. Marean, Peter J. Nilssen, Zelalem Assefa, Elizabeth C. StoneSource: American Antiquity, Vol. 67, No. 4 (Oct., 2002), pp. 643-663Published by: Society for American ArchaeologyStable URL: http://www.jstor.org/stable/1593796

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THE ANALYSIS OF CUTMARKS ON ARCHAEOFAUNA:A REVIEW AND CRITIQUE OF QUANTIFICATIONPROCEDURES,AND A NEW IMAGE-ANALYSISGIS APPROACH

YoshikoAbe, CurtisW.Marean,Peter J. Nilssen, ZelalemAssefa, andElizabethC. Stone

Zooarchaeologists utilize a divere set of approaches or quantifyingcutmarkfrequencies.The least quantitativemethod orcutmarkanalysis relies on composite diagrams of cutmarksoverlain on drawingsof skeletal elements (diagramaticmethods).Todate, interpretationsof these data have generallyrelied on qualitativeand subjectiveassessmentsof cutmarkrequencyandplacement. Many analysts count the number fragments that have a cutmark,regardlessof the numberof cutmarkson thefragments (fragment-countdata). Others count the numberof cutmarks cutmark-countdata). Both can be expressedas sim-ple counts (NISP data), or as a count of some more-derivedmeasureof skeletal element abundance(MNE data). All of theseapproachesprovidedifferent ypesof data and are not intercomparable.Several researchershave shown thatfragmentationofspecimens impacts thefrequency of cuts, and we show here thatfragmentation impactsall these currentapproachesin waysthat compromisecomparative analysis whenfragmentationdiffersbetween assemblages. Weargue that cutmarkrequenciesfrom assemblages with differinglevels offragmentation are most effectivelymade comparable by correctingthefrequency ofcutmarksby the observed surface area. Wepresent a new method that allows this surface area correctionby using the imageanalysis abilities of GIS.Thisapproachovercomes the ragmentationproblem.We llustratethepower of this techniquebycom-paring a highlyfragmentedarchaeological assemblage to an unfragmented xperimentalcollection.Los zooarqueologosutilizandiversosmetodospara cuantificar afrecuenciade huellas de corte. El metodomenoscuantitativopara el andlisis de huellasde corte utilizadiagramascompuestosde este tipode huellasquese sobreponena dibujosde elemen-tos esqueleticos (metododiagramdtico).Hasta el dia de hoy, la interpretaci6nde estas observaciones se ha basado en evalua-ciones cualitativasy subjetivasde la frecuencia y posicion de huellas de corte. Muchosinvestigadorescuentan el numerodefragmentos6seos con huellas de corte,sin considerarel nlimerode huellasen los mismosfragmentos metodode conteodefrag-mentos).Otros nvestigadores uentansimplemente l numerode huellas de corte (metodode conteo de huellas de corte).Ambosse puedenexpresarya sea como cuantificacidn imple(datosde NISP),6 como una medidaderivadade abundanciade elemen-tos 6seos (datosde MNE).Todosestos metodosofrecendistintostiposde observaciones, os cuales nos son comparablesentresi.Varios nvestigadoreshan mostradoque lafragmentaci6nosea afecta lafrecuencia de huellas de corte. Nosotrosmostramoseneste articuloque lafragmentacion6sea influyenotablemente n todos los m6todosusadoshastael momento, que,debidoa ello,se arriesganlos andlisiscomparativos uando el gradodefragmentaci6nosea es distintoentrelas coleccionesa comparar.Pro-ponemosquecuandoel gradodefragmentaci6n6sea variaentre as colecciones, lafrecuenciade huellas de cortepodriaser com-parada en forma mds efectiva al corregirla referida recuencia con la medidadel area de la superficieobservada. Nosotrospresentamosunmetodonuevoquepermiteestandarizar afrecuencia de huellas de cortepor drea de superficiea travesdel usode andlisis de imagencon GIS.Este metodosuperael problemade lafragmentacidnosea. Aquimostramos upotencial al com-parar una colecci6n osea altamentefragmentada on otracolecci6n experimentalnofragmentada.

T he analysisof cutmarks n skeletalelements beenused to reconstruct utchery trategies,whichis a standardresearchendeavorin zooar- then are used to addressmorewide-ranging opicschaeology and has been used to addressa ofgreaternterest.Weuse theterm"butchery"orefervarietyoftopics.Generally,tudiesofcutmarks ave to the actions takento rendera carcass nto usableYoshiko Abe and Zelalem Assefa * InterdepartmentaloctoralProgramn AnthropologicalSciences, SUNY at StonyBrook,StonyBrook,NY 11794-4364Curtis W. Marean * Instituteof HumanOrigins, Department f Anthropology,PO Box 872402,ArizonaStateUniversity,Tempe,AZ 85287-2402Peter J. Nilssen * Department f Archaeology,Iziko - SouthAfricanMuseum,P.O.Box 61, CapeTown, 8000, South AfricaElizabeth C. Stone * Department f Anthropology,SUNY at StonyBrook,StonyBrook,NY 11794-4364

AmericanAntiquity,67(4), 2002, pp. 643-663Copyright? 2002 by the Society forAmericanArchaeology

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portions Lyman1987),often forconsumption,buttheproduction f rawmaterialsor tool manufacturecanalso be a singleorrelatedgoal.Butcheryby cuttingfor consumption ypically

involvesskinning,disarticulation,efleshing,and nsome cases removal of periosteum.Hammerstonepercussionof skeletalelementsis also technicallybutchery, ut thatprocessgenerallyhasthegoal offragmentingkeletalparts oaccess marrow rmakethemmoreeasilyboiled forgreaserendering.Ham-merstonepercussioneavesa mark hat, o a trainedanalyst, s distinct roma cutmarkBlumenschine tal. 1996). Ourfocus here is on cutmarksand theiranalysis.

Studiesofcutmarksigureprominentlyn humanoriginsresearchwherezooarchaeologistsave stud-ied patterningn cutmarks o investigatewhetherPlio-Pleistocenehominids were huntersor scav-engers Binford1981,1985,1988;Bunn1981,1991;BunnandKroll1986, 1988;Potts1983, 1988;PottsandShipman1981;Shipman1986, 1988;Shipmanand Rose 1983). Over time this dichotomousapproach avewaytousingcutmarkingohelp den-tify wherein the sequenceof carcassconsumptionhominidsregularly it (Capaldo1995, 1998b;Sel-vaggio 1994, 1998).Studiesof cutmarkshave alsobeen used in modemhumanoriginsresearcho testBinford'ssuggestions hatevenlate-occurring on-modemhominidswereprimarilycavengers f largeungulates Chase1986,1988;Grayson ndDelpech1994;Marean1998;Mareanet al. 2000a;MareanandAssefa1999;Marean ndKim1998;Milo 1994,1998;Stiner1994).However,cutmark tudies have been conductedin manyotherresearch ndeavorswherethe recon-struction f butchery rocesses s seen asrelevant oother behavioral raits.The optimisticview is thatthebutcheryprocessvarieswiththe intendeduseofacarcass,andthat his variationwill be expressednthe placementand frequencyof cutmarkson theskeleton,allowingus to infercarcassuse from cut-markstudies.Forexample, t has been argued hatbutcheryshouldvarybetweencontextswhere thegoals are immediateconsumptionversus storage(Binford1978).Binford'swell-knownutilitymodelhaddifferingpredictionsor skeletal lementchoice,and researchershave anticipated hatcutmarkingshouldalso vary widely between,for example,anunselective r"gourmettrategy"ersusmore nten-sive utilization(Binford1984). Zooarchaeologists

havehoped oidentify illetingversus kinning Bin-ford1981;Shipman1981;ShipmanandRose 1983;Wilson 1982).Yellen(1991) has argued hatsomebutcherypatternshavea "style" hatcould be cul-turallydetermined,husholdingout thepossibilitythatbutchery atternsmay providewaysto examineethnicity.Thishighpromisehas been frustrated y severalfactors.First is a lack of detailed observationsofbutchery nd tsresultant atterning. herearemanystudiesof butcheredmoder bones (Binford1981,1984;Crader 983;Gifford-Gonzalez989;GiffordandCrader 977),butnoneof theseactually bservedthe act of butchery hatproducedmarks,andthenlinked hosespecificactions o specificcutmarks.Arecentstudythat filmedbutcheryactionsclose-up,thusprovidinghisunambiguousinkage, ound hatmanyof thedisarticulationrdefleshingmarksllus-trated n Binford(1981), and regularlyused as aguide to butcheryanalysis, are not unambiguousindicators f specificactivities Nilssen2000).Thusthe strictcausallinkagebetween observedspecificbehaviors suchas cutting or disarticulationr fordefleshing)and theirtraces(such as cutmarksonarticular nds versusshafts),called forby Gifford-Gonzalez(1991), is not yet fully developed n theliterature.Another critical problem is the diversity ofapproachesfor recordingthe cutmarksand thenquantifyingheir requency.t s safetosaythat hereis no acceptedmethod oreither.Ourreview of theliterature hows thatrecordingcutmarkscan taketwopaths.Oneis to recorda count anddescriptionof the cutmarksonto a database.This can be doneeitheratagross evel(howmanyareon a specimen)or a finer evel (whereon the specimentheyoccuralongwitha diagnosisof theircharacter). secondapproachs to drawcutmarksonto a diagramof abone, or what we will call a template.The twoapproaches an be easily combined,andprobablyoftenare.Oncethecutmarks rerecordedheanalystmustchoose a way to quantify,analyze,andpresent hedata npublication, ndhere here s also a widevari-ety of approaches.This stepis problematicdue tothepotential or wide interanalyst ariationn con-vention.This variations a severeproblem or com-parativetudies nzooarchaeology ecause tmakesitdifficult,f not mpossible,ocompare atabetweenresearchers. ustas zooarchaeologists ave defined

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anatomicalandmarks nd measurementshatstan-dardize their approachto osteometrics (Driesch1976), zooarchaeologistsmust also strivefor stan-dardizationn other ormsof data.Importantly,otonlyshould herebestandards, e needtoknow hatthese standards re effective.

In thispaperwe beginwitha briefreview of themainapproachesused by analysts o quantifycut-marking.We then reviewthe impactof bone frag-mentation n theeffectiveness f thesequantificationprocedures.We arguethat these currentanalyticalapproachesdo not adequatelyovercomeproblemscausedby differentialragmentation. ecentdevel-opmentsngraphical r mage-analysisoftware,webelieve,holdpromise orsolving manyof theprob-lems inherent n quantifying utmarks.Finally,wepresenta new approachwithGIS software hat wethink overcomes he mainproblems n quantifyingandanalyzingcutmarks.We illustrate his methodwith an application o two radicallydifferentcol-lections, a fragmentedMiddle Stone Age (MSA)faunalcollection and an unfragmented xperimen-tal collection. Our ntent s notto review theissuesof how to definea cutmark,because that has beendiscussed in detail elsewhere(Blumenschine t al.1996;Fisher1995;Shipman1981).Also, we donotexamine he ssueofhow todiagnosehowmanycut-marksarepresenton a fragment, uch as whether orecordmultiple triaeas one or more ndividual ut-marks Lyman1987).Rather, urgoal is to addresstheissueofhow to recordand henanalyze he num-bers afterone hasdiagnoseda cutmark,decidedona count,and s ready o recordandultimatelyquan-tify thesampleformeaningfulbehavioral nalysis,such as comparisono modem controlassemblagesor otherarchaeological ssemblages.

Review of Methods forQuantifying Cutmark Frequency

The literature n cutmarkanalysisis vast,andourgoal here is not to reviewit all butrather o distillfromthat iterature he basicmethods orquantify-ing cutmarkfrequencies. The least quantitativemethod orcutmark nalysis eliesoncompositedia-gramsof cutmarks verlainon drawingsof skeletalelements (Binford 1988; Grayson and Delpech1994:Figure10;Landon1996;Marshall1990).Wecall these"diagramatic ethods," nd, odate, nter-pretationsfthesedatahavegenerally eliedonqual-itative and subjective assessments of cutmark

frequencyandplacement. t is ourimpressionromdiscussionswith many zooarchaeologistshattheyoftenbegintheirrecordingof cutmarks y drawingcutmarks n bonediagrams.However,nanattemptto be morequantitative ndtest for statisticalsig-nificance,zooarchaeologists ypicallyuse variousmethods orcountingandsummarizingutmarkre-quencies,neveractuallyusing hediagrammaticatafor anythingother thanpresentationand impres-sionableanalysis.Whenanalystspresentcutmarkdata,they typi-cally choose to count one of two observationsseeTable1). Manyanalystscount the numberof frag-ments hathave acutmark,egardless f the numberof cutmarks n thefragments, nd we refer o theseas"fragment-count"ata.Thesecanbeexpressedasasimplecountof fragmentshatarecutmarked, hatwe call"NISPdata" NISP= number f identifiablespecimens), r asacountof some morederivedmea-sure of skeletal elementabundance,what we call"MNEdata."TheMNE (minimumnumberof ele-ments)underliesmost otherderivedmeasures uchas the MNI (minimumnumberof individuals)orMAU(minimum umber f animalunits),so we usethis termgenerallyo refer oall MNE-derivedmea-sures.Analystsoften choosetopresent hedataas aproportion,nd ypicallyheseoccuras theNISPcut-markeddividedby thetotalNISP,orthe MNE cut-markeddividedby thetotalMNE.

Alternatively,nalysts an count hefrequency findividual utmarks n specimenswithina skeletalelement,and/orwithina definedregion(suchas theproximal ndorthemiddleshaft).Werefer o theseas"cutmark-count"ata.Cutmark-countata reoftenexpressedas both a rawvalue,oras a proportionrindex.As withfragment-countata, heanalystmayemploythe NISP or MNEas thedenominatorn theproportionalculation,esultingn thepermutationslisted n Table1. There s no standardn zooarchae-ologyas to whatapproachouse,so as is indicatednour discussionbelow,much of thepublisheditera-turepresentsdata hat s onlydirectly omparableoa narrow ampleof otherstudies.One of the simplestapproaches o quantifyingcutmarks, nd otherforms of surfacemodification,has developed within the field of early hominidresearch.Thisapproachwas firstusedby Blumens-chine (1988) in his analysisof hammerstoneper-cussion and carnivore ooth marks,and was laterextended o cutmarksCapaldo1995, 1997, 1998a,

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Table 1.Approaches o CutmarkQuantification.Expressedas NISP Expressedas MNE

Counts of Cutmarks NISP cutmark-count ata MNE cutmark-count ataCounts of Cut Fragments NISP fragment-countdata MNE fragment-countdata

1998b;Marean t al.2000a;Selvaggio1994,1998).Thegoalsin these studiesareprimarilywo: identi-fying the positionof hominids within the carcassconsumption sequence (early access versus lateaccess),andmeasuringheamountand ntensityofcarnivore ctionon the faunalassemblage ollowinghominid discard.These approachesocus only onlong bone fragments hat are classified into threetypes: epiphyseal(technicallyarticular),near-epi-physeal,andshaft seeBlumenschine1988fora def-inition).Thefragmentsmayormaynotbe groupedby skeletalelement oranalysis.Fragments reonlyassignedobody-sizeclasses Brain1981),not axon,andonly ungulate ong bones are used.Fragmentsare tabulated s havinga markof a certain ype ornot (numbersof marksper specimenare not uti-lized), so this approachproducesNISP fragment-count data.An example of NISP cutmark-countdata isStiner's(1994) presentationof Paleolithic faunasfromItaly.Stiner 1994)providesskeletaldiagramsof anatomically omplete axa with thefrequenciesof cutmarks ndicatedon the skeleton(by numberspointing o a skeletalelement).Suchdiagramspro-vide a useful visualsummary f theintensityof cut-ting at variousanatomicalocations.Stiner(1994)alsoprovidesablesofcutmarkedragments er otalNISP assignedto a specifictaxon,so herpresenta-tion includes both cutmark-countand fragment-countdata,all in NISP.Giffordet al. (1980) andBunn andKroll(1986)provide keletaldiagramshataresuperficiallyim-ilar to thosein Stiner 1994),butthepresentedval-ues arefrequenciesof cutmarkedfragmentsrom aparticular keletalelement. These are NISP frag-ment-count ata,and husverydifferentromStiner'sskeletaldiagrams, espite hesimilaritynpresenta-tion.Gifford tal. (1980)alsopresents ablesof cut-markedragments, ut heyaresegregated yskeletalelement and body-size category,not species, andthus arenot directly comparable o Stiner'stables(1994). NISP fragment-count ata arecommonintheliteratureince the 1960s(BunnandKroll1986;Frison 1970; Gilbert 1969; Guilday et al. 1962;

Marean1992;Parmalee1965;Wheat1979).Whilethedataarecarefullydescribed ndpresentedn eachof thesestudies,hevariationnanalytical roceduresmakescomparative nalysissomewhatdifficult.It has becomeincreasingly ommon oranalyststopresentandanalyzecutmark atacorrected ytheMNE,or a measurederived rom it (Binford1984;Graysonand Delpech 1994;Milo 1998). Binford(1984) was one of the firstanalysts o presentcut-markdata n thismanner,ndhis tableson theKlasiesRiver faunaprovidean MNE on cutmarked rag-mentsby bovidsize class and skeletalelement,andthen a total MNE. Milo's analysisof the KlasiesRiver fauna provides similar data (1998:Table2:104):the MNI calculated rom all fragmentsperskeletal lementandportion, nd heMNIcalculatedfrom ust thosefragmentshatarecutmarked.Milo(1998) also employs an index of cutmarksperanatomical one (in thiscasejoints),and these areclearly ndexedMNE cutmark-count ata.By pro-vidingboth,he broadenshepotentialusefulnessofhis presenteddata.His reasonsfor calculating heindexareclear Milo1998:109):"Absolute umbersof marks annotbe compared ecauseof disparitiesin skeletalpart epresentation."otethat n all caseshis denominators a derivedmeasureof skeletalele-mentabundance,ndhe usesitbecausederivedmea-sures "partlycircumvent the problem posed bydifferentialragmentation"Milo 1998:102).Milodoes not elaborateon this statement,but Bartram(1993) provideda thoughtfuldiscussion,and webuildon thatbelow.

The Fragmentation ProblemThe use of derivedmeasuress often undertakenoovercomeor at least minimizetheprimaryanalyti-cal problemfacing the analysisof cutmarks: ut-mark requencies resensitive ofragmentationromboth human and nonhumanprocesses (Bartram1993). Bartramdiscussedthe problemswith cut-mark-count ata,andwe summarizehatbelow,butnot for fragment-count ata,so we extendhis dis-cussionto thoseapproaches s well.Figure1beginstheillustration f thefragmenta-

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A)

Expressedas:NISP MNERaw Proportion Raw ProportionCutmarkCount 5

FragmentCount 3

B) Is ._sl-

1.661.0

,3 ^'

5 1.663 1.0

!;^U:;>

Expressedas:NISP MNERaw Proportion Raw Proportion

CutmarkCount 2FragmentCount 2

.666

.6662 .6662 .666

Figure 2. a) Cutmarks on 3 proximal bovid femora broken by hammerstone percussion prior to attrition by sedimentaryprocesses, and b) the same three proximal bovid femora after attrition by sedimentary processes. The surviving fragmentsare shown in dark outline while the original bone is shown in gray outline as a ghost image. Small arrows on a) indicate theposition of cut marks.realisticallyportray he realitiesof the taphonomichistoryof archaeological oneassemblages.Figure2a shows threeproximal emorabrokenbyhammerstoneercussion,wo with twocutmarksand one withone cutmark.Thisrepresentshepre-depositionaltate,before edimentary rocesseshave

impacted hefragments.Figure2b shows an exam-ple of how the femora n 2a wouldtypicallysurvivefragmentationand bone loss from sedimentaryprocesses.It is widely believedthatfragmentationby sedimentary processes is density mediated(Grayson1989; Klein 1989; Lyman 1984, 1985,

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ative to theoriginalsurface.This is why MNEdataarenot mmune o thefragmentationroblem.How-ever,if we dividedthe numberof cutmarksby thepreservedsurface area, our cutmarkfrequencieswouldclosely matchthe original requencies.Thissituation houldholdif cutmarking oes notprefer-entiallyoccur,ornotoccur, ndenseregionsofbone.We have no reason o believe thatcutmarkingnten-sity systematically arieswithbonedensity,butevenif it does, the GISmethodwe describebelowhas ameansto overcome hisproblem.Theresults that he ikelihood fa cutmark eingpreserved ndcountedby ananalyst s a functionofthe amount f bonesurface rea tudied ndrecorded.As more surfacearea s studiedandrecordedby ananalyst,morecutmarkswill befound,andvice versa.Thus f we can correct henumber f cutmarks ytheamountof examinedsurfacearea,muchas demog-raphersstandardizepopulationsize by estimatingpopulation ensity, henwe can standardizeutmarknumbersbetweensites, betweenbody sizes, evenbetweenanalysts hatmaydiffer n theirchoice andabilities to identify and recordfragmentedbone.Importantly,s samplesize(and hussurfacearea) sincreased,hefrequencies enerated y this methodare ess susceptibleo chanceoccurrenceshatcouldskew the results.Thekeyis, of course, hatwe havesomewayof recordinghe amountof examined ur-face areaandhowmanycutmarksorother ormsofsurfacemodification)were found.

Rapson (1990) recognized the fragmentationproblem and recommended correcting cutmarkcountsbysurfaceareawiththefollowingprocedure:calculate hefrequency f cutmarks erunitarea oreachspecimenby multiplyinghetotalcutmarks erspecimenby 1,000 and thendividingby specimenarea,resultingn a figure hatestimatedhe numberof cutmarks er 1,000mm2of bonesurfacearea oreachspecimen, hencalculate he meansurfaceareaandthe mean numberof cutmarksperunit areabytaxonomicgroup.Rapson'smethod for estimatingsurfaceareaperspecimen nvolvedmultiplyinghemaximumengthofafaunal pecimenbyanapprox-imate measureof specimenwidth.Specimenwidthis estimatedby measuringhedistancebetween hemaximumweatheringurface nd tsoppositeaspect(the "weatheringprofile height"). Rapson arguedthat hisapproach llowscomparison f cutmarkre-quenciesbetweendifferentiallyragmentedamples,in his case bighornsheepand bison.

Rapson's uggestiono correct utmark ountsbysurfacearea,and his use of a grossestimateof sur-facearea,was anexcellent irst tep.Recentadvancesin image-analysissoftware,and particularlyGIS,allow us to go farbeyondthatapproach.GIS soft-ware makespossiblethe followingprocedureshatcapturehebestof themethodsdiscussedabove,andexcel in severalcriticalways: 1)captureand calcu-late the preservedsurface area of fragments n amuchmorerealisticmanner ndthussolve thefrag-mentationdilemma,2) precisely quantifythe fre-quencyofcutmarks n askeletal lement nanywaydesired o thatpositionalquestions anbe asked lex-ibly,3) attachadescriptive atabaseoagraphicallyrecorded utmark o that utmarks anbe further na-lyzed by type, length, angulation, or any otherrecordedvariable,4) allowdiagrammatic epresen-tationof cutmarkplacement n any permutation fvariables esired taxon,provenience,utmarkype,and so on), and5) if it is eventually ound thatcut-marking ntensitysystematicallyvaries with bonedensity, his methodwill allow theanalyst o restrictanalysisto surface-area amplesthatare density-equivalent.We havedevelopeda series of methods hatuti-lize ArcView GIS software,the ArcView SpatialAnalyst extension,and several modificationsandextensions writtenin Avenue (the ArcView pro-gramming anguage)and MicrosoftVisualBasic.ThesematerialsncludeanArcViewprojectwiththeaddedAvenue eatures,anexampleprojectwith thedigital mages,amanual, ndaVisualBasicprogramdeveloped to overcome several file managementproblemsassociatedwithlinkingArcView o exter-nal databases.Thereare also instructions n how todevelopinterfaces oryourown animalsof prefer-ence (hare, ish,bird,orwhatever), ndsplicetheminto ourprogrammingode. All are availablegratisfrom Mareanby request([email protected]),butyou mustalreadyhave a copy of ArcView, orwhichmanyuniversitieshave site licenses.

The Image-Analysis GIS MethodTo understand ur methodof cutmark nalysis,wemust firstexplainhow we calculate heMNEusingthe image-analysisGIS approach(Mareanet al.2001).Zooarchaeologicalystems orestimatingheMNE, andother measuresderivedfromit, can beclassified into two types: fraction summationapproaches ndoverlapapproaches Marean t al.

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/ W

Overlap

Figure 4: a) Example of a femur fragment drawn onto a template, b) a second femur fragment where the MNE still equals1, and c) a third femur fragment raises the MNE to 2. The darker shading indicates the area of overlap between the twospecimens.2001). Overlapapproaches see Figure4) seek anactual ountof thenumber foverlappingragmentsand thus a directestimateof thenumberof skeletalelementsrepresented ya seriesof fragments.How-ever, hesemethods,when donemanually, recum-bersome, imeconsuming,andcould be inaccuratewhenworkingwithlargecollections.Wedescribeda newimage-analysisGISmethod(Mareanet al. 2001) thatutilizes GIS software omaketheoverlapapproachmoreapproachablendaccurate.Thesimplestandmostcompleterecordofa fragmentwould be to draw ts positionon a tem-plate.With heGISmethodwe use themouse o drawtheoutline of a fragmentonto an outlineof a com-pletebone,called atemplate,bothof whicharevec-tor images (Figure5). Ourprocedures to do thisdirectly o computer, ut f neededananalystcouldgeneratehard-copyormsof thetemplatesandenterthem ater.ArcView reatseachfragmentas a sepa-ratetheme,andeach theme is a relatedset of filesthat ncludea shape ile (thevector mage)linked oa table file (whereother nformation,uch as speci-men number,can be stored).ArcView names the

files for you in a ratheruninformativeway, so wehavedevelopedaVisualBasicprogramhatrenamesall filesby thespecimennumber, llowingeasy filemanagement.Thefragment ectoroutlinesare atertranslatedntobitmaps or thevariouscalculationsdescribedbelow.Sittingon topof thetemplatedur-ingtheentryprocess s ahigh-resolution igitalpho-tographof thebone thathelpstheanalystpreciselyposition hefragment ndsurfacemodification ntothetemplate.Figure5 shows anexampleof thefrag-mententry nterfacewe havedesignedfor femur.Likewise,cutmarksandothermodifications)reentereddirectlybymouseontothetemplate nddig-italphotograph.Wedesigned hesystemso thatcut-marksareentered ogetheronto a singletheme forcutmarks.Eachcutmarks namedontheunderlyingdatabase ableby specimennumberand describedby a varietyof variables angulation, utmarkype,andsoon).Ananalyst anadd o or essen heamountof detailrecorded.Using varioussoftwareroutines, he positionoffragmentsn relation o each othercanbe assessedaccurately, nd theoverlapscan be estimated o the

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Abe Et Alii - The Analysis of Cutmarks on Archaeofauna