Explanatory/Predictive Models of Hunter-Gatherer AdaptationAuthor(s): Robert L. BettingerSource: Advances in Archaeological Method and Theory, Vol. 3 (1980), pp. 189-255Published by: SpringerStable URL: http://www.jstor.org/stable/20170157 .Accessed: 24/03/2011 15:45Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at .http://www.jstor.org/page/info/about/policies/terms.jsp. JSTOR's Terms and Conditions of Use provides, in part, that unlessyou have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and youmay use content in the JSTOR archive only for your personal, non-commercial use.Please contact the publisher regarding any further use of this work. Publisher contact information may be obtained at .http://www.jstor.org/action/showPublisher?publisherCode=springer. .Each copy of any part of a JSTOR transmission must contain the same copyright notice that appears on the screen or printedpage of such transmission.JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range ofcontent in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new formsof scholarship. For more information about JSTOR, please contact support@jstor.org.Springer is collaborating with JSTOR to digitize, preserve and extend access to Advances in ArchaeologicalMethod and Theory.http://www.jstor.org5 Explanatory/Predictive Models ofHunter-Gatherer Adaptation ROBERTLBETTINGER Thisis anassessmentofcurrentresearchon hunter-gathereradaptation. Mypurpose hereistoshowthat hunter-gatherer studiesareatacritical point intheir development, toshowhowthiscame about, andwhatthe resolutionofthesituation might be.Atthe outset, Iwill readily ac knowledge thatthestatedconcernwith hunter-gatherers is something of a problem: it has yet tobe shown,exceptby the tautology of definition,why hunting-gathering shouldbe regarded asadiscreteand uniqueadaptive formsetofffrom others, sothatwe might beableto say with certainty at what point ina group's evolutionitceasestobe hunting-gathering and becomes agricultural or something else.I will side-step thisissue bypointing outthatI amconcernedwith groups andstudiesof groupstraditionally held tobehuntersand gatherers without presuming thatwhatis observedhereis necessarily distinctivetothemorwithoutwider application. BACKGROUND Long a pursuit of great interestto archaeologists and anthropologists alike, the study of hunter-gathereradaptation hasadvancedatanever increasingpace overthelastfourdecades.The knowledge thus gained has proved fertile ground forbothculture evolutionary theoristsandin dividuals seeking tounderstandhumanbehaviorincontextswhere hunting and gatheringdisappeared asa way oflife long beforeitcouldbeobserved firsthand. Despite these gains,however, a survey ofthefield through its literatureshowsthatthereis an impending crisisin hunter-gatherer studies. 189 ADVANCESIN ARCHAEOLOGICALMETHOD Copyright ?1980 by AcademicPress, Inc. AND THEORY, VOL.3All rights of reproduction in any formreserved. ISBN 0-12-003103-5 190ROBERTLBETTINGER Thecrisisisevidenced by a growing undercurrentofconvictionthatin termsof presentneeds, traditional approaches to aboriginal man-landrela tionshipsamongnonagriculturalists have grown sterile (cf. Schiffer 1975; Reid 1978) and vacuous, whereasthe proposed alternative approaches, many ofthemdrawnwithlittlemodificationfromsuchfields as economy, geography, and biology, donot quite seemtobetheanswerweare looking for. Manyappear mechanisticor simplistic, andothersareso poorly suited totheirintendedtaskthat they eitherconfuseordrawattention away from the problem athand. TherootsofthiscrisiscanbetracedbacktoSteward'sseminalworkson the methodofcultural ecology(Steward1936,1938), in whichhedrew sys tematic relationships between environment,technology, the organization of work, and sociopolitical behavior.In doing so, herekindled anthropolog icalinterestin man-land relationships, anareaof inquiry thathadfound eredwhentheoriesofenvironmentaldeterminism (e.g.,Semple1911; Hun tington1959) were rejected and replaced?firstby the antigeographical bias ofBoas (1948), andlater by theenvironmental "possibilist"approaches of Kroeber (1939), Wissler (1926), andForde (1934), in whichtheenvironment wasseenas imposingonly broadlimitswithinwhichculture mightvary sub stantially. Asoutlined by Steward (1938:260-261), cultural ecologyplaced strong relianceonthe explanatorypower of environment, butnottotheex tentthatthe relationship betweencultureandenvironmentwas strictly de termined. Rather, theirinteractionwasmediated bytechnology andlabor. In effect, theenvironmentisa given, immutablecondition (ibid.261) to whichlabormust conform, andthat conformity istoa large extentdictated bytechnology. In turn, the organization oflabor requiredconformity from socialand politicalorganization. Stewardfurther argued thattheeffectsof thiscausalchainweretobemost readilyperceived inthoseelementsof culturethat most directly articulatedwiththe environment; hetermedthese elementstheculturecore (Steward1955). Giventhistheoretical approach, itis not surprising thatSteward initially applied itto hunter-gatherers(1936,1938), forit wasconventionalwisdom then, as now, thatfor hunter-gatherers,culture,environment, andsub sistence adaptation are inextricably linked (Service1962,1966; Childe 1951; White 1959; Murphy1970; Steward 1938:1-3,258-262).Thus, forall prac tical purposeshunter-gatherer cultureinits entirety isall"culture core"; Stewardsawthisincontrasttomore complexagricultural situationsin whichculture increasingly tookonalifeofitsown (Steward1938:262). Although our understanding ofhuman ecology hasbecomemore sophis ticatedsinceSteward'sinitial exposition ofthe culture-ecologicalmethod, currentresearchis clearly derivedfromhis approach, anditcanbe argued thatthe perspective of many studentsof hunter-gathererstoday isessen tiallyequivalent tothatofSteward.A potentialexception tothis generaliza EXPLANATORY/PREDICTIVE MODELSOFHUNTER-GATHERERADAPTATION 191 tion,however,may befoundinthecriticismsofSteward'scultural ecology by scholars posing a key roleforthelatent adaptive functionsofcultural behaviorsthat superficiallyappear farremovedfromtheculturecore (Vayda and Rappoport1968). Inbroad outline, the position taken by these individualsisthatcultureistobeviewedin muchthesame way thatan ecologist viewsan organism or population.Hence, all aspects ofcultural behaviorbecome explicable intermsoftheir adaptive effects.Onethen strivestofindthevariablethata given behavior (oftenbizzare)allegedly regulates. An example ofthis approach wouldbePiddocke's analysis ofthe AmericanNorthwestCoast potlatch, whichhe argues canbe explained asa meansfor redistributing food supplies in ordertocounteractlocalresource fluctuations (Piddocke1965; butseeOrans 1975). Areviewoftheliteratureshowsthat despite some objections(Murphy 1970), thereis broad acceptance forthis more comprehensiveperspective of culture-environment interaction, whichhasbeentermedthe"new ecology" (Thomas1972; Jochim 1979; Willey andSabloff 1974).Nevertheless, the differencesbetweenSteward'scultural ecology andthenew ecology seemto be moreof degree than kind, andIseenoreasonto argue thatthesereflect distinct paradigms(Brush1975), atleastin Kuhn'ssense (1962). Thisisin part becauseSteward (1938,1955) was explicit onthe point thatsuch things as religion and sociopoliticalorganization werecriticalelementsofhis cultural ecologymodel, andin part becauseitis possible totraceacon tinuumofviewsfromStewardtothenew ecologists,differingonly with respect tothe relativelygreaterimportanceassignedby thelattertoeco logicalrelationshipsamong more complex societies. Parenthetically, we mightpoint outthatwhile Vayda and Rappaport(1968) andothers severely criticizedSteward'snotionthat purelyecologicalexplanations of organiza tionalbehaviorbecomelessusefulassocietal complexityincreases,Rap paport(1969) himselfseemstohavetaken just sucha position(see also Flannery1972). Howeverwechoosetoreconcilethe relationship betweenthevarious viewsofcultural ecology, thereisalmostnodebatethata comprehensive approach toalmost anyaspect of hunter-gatherer culturemustbe firmly grounded inadetailedassessmentofthe technological-environmental con text (Harris1971; Leone 1972; Helm 1962;Willey and Sabloff 1974; for a specificexample seeLeeandDeVore 1976). Furthermorethe presumption is equallystrong thattechnoenvironmental explanation is inherentlysuperior tootherkindsof explanation(e.g.,historical). In practice, thishasmeant thattoaccountforabehavior pattern orabehavioraldifferencebetween two groups onotherthan technological orenvironmental groundsrequires thatthe possible effectsofman-land relationships be first consideredand convincingly dismissed (e.g., Damas 1969d;Rogers1969b,c). Intermsofactual research, thealmostincrediblenumberofhunter 192ROBERTLBETTINGER gatherer studiescarriedoutfroman ecologicalperspective are ample evi dencethatthisbiasisof greatutility asan investigative tool.Onecan nowcitealmostendlesslistsofsuch studies, both archaeological and ethnographic, from virtually all parts oftheworld.Studiesofmodern hunter-gatherers havebeen particularlyprominent inthis regard,especially in NorthAmerica (e.g., Steward 1938;Fitzhugh1972;Rogers1962,1969a; Balikci 1970; Smith 1978; Bean 1972), Africa (e.g., Lee 1968,1969; Silber bauer 1972; Tanaka 1976; Harako 1976; Tanno 1976; Turnbull 1965a,b; Marks 1976), andAustralia (Gould1969a, Meehan 1977; Petersen 1973; O'Connelland Hayden1977; Tindale 1972). Inadditiontosuch primary research, several symposia devotedin wholeor part to hunter-gatherers have provedespecially usefulfor integrating the findings of investigators working onadiverse range of topics(Damas1969a,c; LeeandDevore 1968). Outofthisworkhasevolveda basicallydescriptivegeneralhunter-gath erermodelthat attempts to synthesize thesalientcharacteristicsofthis lifeway. One might summarize concisely the mainpoints ofthis descrip tive/normativemodelasfollows. Hunter-gatherer subsistenceisreliant primarily on plant resources, shell fish,fish, andsmall game;largegame is typically a minor dietary constitu ent (Lee andDevore 1968:7).Further,owing to this,women, ratherthan men, arethe primary subsistence providers. Hunter-gatherers arenothard pressed to satisfy theirsubsistenceneeds (Gould1969a; Lee 1969; Sahlins 1968). Most groupsspendonly asmall fractionoftheirtimeinthe procurement and processing ofresources (Lee andDevore 1968:6). Failureto exploit resourceswith greaterintensity than thisis thought toreflect adjustment of"satisfactionlevels"toa point that is readily achievedwithout greathardship(Sahlins1968:85-89). Population densitiesare characteristicallylow,ranging between.05and .001individuals perkilometer, andare probably maintainedatornear30to 70%ofthe potentialcarryingcapacity oftheenvironment (Birdsell1968; LeeandDevore 1968:11). The demographicarrangement consistsoftwo organizational levels:the maximum band, or mating network (connubium), consisting ofabout500 individuals, andthe minimum band, orlocal group, consisting ofabout25individuals (Birdsell1968; Steward 1969; Wobst 1974).Sociopoliticalorganization is simple. Mostinteractionis withthe local group,although thereis periodicaggregation in largergroups that ap proximate themaximumband (Helm1968,1969a; Leacock 1969; Wobst 1976; Damas 1969b). Affiliationstendtobe bilateral,groupcomposition fluidratherthan stable, andterritorial conceptsweaklydeveloped(Damas 1969b; Turnbull 1968; Woodburn 1968; LeeandDevore 1968:7-9; Steward 1955; Lee 1972; Yellenand Harpending1972). Most groups are egalitarian EXPLANATORY/PREDICTIVE MODELSOFHUNTER-GATHERERADAPTATION 193 (Fried1960), status being reckoned byage,sex, andachievement (Steward 1955; Service 1962).Leadership is usuallyephemeral andcarrieslittleinflu ence beyond an advisory role (Steward1955;Flannery1972; Damas 1969b; Gould 1969b:90; Woodburn 1968:105). Archaeological contributionshavebeen equally influentialin shaping our currentviewof hunter-gathererecology.Here,however,special attention hasbeen given to patterns ofsubsistence (Clark1952; Gorman 1969; Mei ghan1959; Braun 1974;Asch,Ford, andAsch 1972;Bryant and Williams Dean 1975; Watson 1976; Casteel 1972a) andsettlement (Winters1969; Struever 1968; Thomas 1973; RitchieandFunk 1973),although nottothe exclusionof demography(Ascher1959; CookandHeizer 1965; forasum mary, see Hassan 1978), orsocial organization(Binford1962; King 1972; Thomas 1974; Yellenand Harpending1972). Toa largeextent, sucharchae ological studiesfurnishedthefirstdetailed quantitativeanalyses ofthese aspects of hunter-gathererlifeways, whichhadreceived onlypassing atten tionfromtraditional ethnographic research. Ultimately, thisworkrenewed interestinthe ethnographicstudy ofmodern hunter-gatherers, muchofit being carriedout byarchaeologists intenton collecting datarelevanttothe investigation of prehistorichunter-gatherers. In light ofthese principal concerns, tworecent conceptualdevelopments havebeen especiallyhelpful inthe archaeologicalinterpretation ofman land relationships?particularlyamongnonagriculturalists. Oneoftheseis thecatchment concept(Vita-Finzi and Higgs1970;Roper1979), in which the archaeological siteisviewedasthefocal point ofabroaderresource areathatcanbe exploited ona regular(daily) basis.Theotheristhenotion ofthesubsistence-settlement system(Winters1963; Struever 1968), which portrays individual adaptivesystems as comprising anumberofdistinct functionalorseasonal aspects, eachwithitscharacteristicenvironmental setting and archaeologicalassemblage. These concepts wereinstrumentalin drawing attentiontothe larger naturalandculturalunitswithwhichin dividualsites articulated; withoutthe explicitrecognition and study ofthese units,interpretations ofsitefunctionremained incomplete and speculative. Moreover,archaeologists havenotlackedfortheirown general hunter gatherer models.Asan example ofthe manyproposed, one might citethe highly successfuland widely endorsedNorthAmericanArchaic stage (Ritchie1932;Willey and Phillips1958; Jennings1968,1974). Asmost recently summarized (Jennings1974), theArchaicisan adaptivepattern that encompassesvirtually all aboriginal NorthAmerican hunter-gatherers from8000bctoad 1850;thus, itistobeviewedas"afundamental lifeway, not geared to any one ecosystem"(Jennings1974:129). Theessen tialcharacteristicofArchaic groups isthat they are"efficient" (Caldwell 1958), that is, that theyrelyupon resourcesthatare "abundant,nutritious, 194ROBERTLBETTINGER andnearathand (Jennings1974:132),subject totheconstraintsoftechnol ogy and knowledge ofthe environment;gradualadjustment tothesecon straintswiththe goal of improvedefficiency isseento guide culturaldevel opment withintheArchaic. Thus, theArchaicmodelof hunter-gatherers is firmlygrounded in ecologicaltheory,employing itin a distinctlyevolutionary sense. Except for this evolutionarycast,however, theArchaicmodelofthe archaeologists restson essentially thesame culture-ecologicalassumptions thathave guided the ethnographicinvestigation ofmodern hunter-gatherers. Itis not surprising,therefore, thatthe specificeconomic,demographic, and organi zationalcharacteristicsofthe Archaicare essentiallyequivalent tothoseset forth byethnographers intheir generalhunter-gatherer model. Discussion Although increased understanding of hunter-gatherer behaviorhasat tendedthe adoption ofan ecologicalperspective, areviewofboth ar chaeological and ethnographic studiesshowsthatcultural ecology continues to be, morethan anythingelse, a generalapproach orresearch strategy and that despiteattempts tointroduce generalconcepts(e.g.,homeostasis; Vayda and Rappaport1968; Brush 1975) stillwantsaunified body of theory.Lackingthis, the accepted research strategy hasof necessity become onein whichitisassumedthat hunter-gatherersadapt totheirenviron mentsandthatthis process isconstrainedanddirected sufficiently to pro ducean optimum(efficient) solutionunder anygiven circumstance. Hence, thetaskforthe anthropologist hasbecomefirsttoinferanddescribebehav iorandthentooffer explanations astohowthisbehavior accomplishes its presumedadaptive functions. Insome cases, thisresearch sequence hasbecomeasterileand repetitive cycle. InGreatBasin archaeology, for example, an ecologically oriented research designinitially proposed by Binford (1964) and applied by Thomas (1973) hasbeenreducedtoasetofmechanical procedures thatcanbeused inalmost any situation by individuals havingonly minimal understanding ofits purpose. Thishasresultedinincreased emphasis ondata acquisition intheabsenceof any increased ability to interpret thosedata.Conse quently,knowledge ofGreatBasinhuman ecology has changed littlesince Steward'sinitial exposition morethan fortyyearsago(Steward1938). One suspects thatsimilar generalizations holdtruefor ecological researchin otherareasaswell. More important than this,however, the empirical and particularisticap proach of manyecologicalanalyses makesthemvulnerabletothecriticism EXPLANATORY/PREDICTIVE MODELSOFHUNTER-GATHERERADAPTATION195 that theyexplainnothing atall.Thisis because, asOrans (1975) hasso cogentlypointed out,arguments that explain cultural behaviors, whether they bekin systems, settlement systems, or religioussystems, intermsof theirsubsistencevalueare essentially functional arguments. Andasisthe casewithallfunctional arguments, in anyparticular instanceonecannever becertainthatthe presence of a specific behavioraltraitis properly ex plained asa consequence of aneeditis thought to fulfill, sinceitis always possible thatsomeothertraitisinfact fulfilling thatneed (cf. Helm 1969b: 171). Oransfurtherindicatesthattoavoidthis ambiguityrequires, among other things, cross-cultural testing toseewhetherthetraitin ques tionoccursmoreoftenthanwouldotherwisebe expectedamong societies thatexhibitthe needitis thought tofulfill (Orans1975:317-328). Such cross-cultural testing, ofcourse,presumes thatoneunderstandsa suspected functional relationship insufficientdetailto permit a predicted cross culturalassociationandoneisabletodefineboththetraitandthecor responding needin sufficientlygeneral termssoastobeableto identify themin any culturalcontextwhere theymight occur. If we apply this reasoning tothe problem at hand, it amountstothe prop ositionthatweneedto developgeneral modelsof hunter-gatherer be haviorthatwill permit usto predictadaptiveresponses to given situations ratherthan merely describebehaviorasthe range of empirically observed responses, asisthecasewiththe archaeological and ethnographicgeneral hunter-gatherer modelsdescribedhere.Thisneedhasbecome increasingly perceived inrecent years,although not necessarily intheseexact terms, and thecrisisofwhichI spoke attheoutsetofthisdiscussionis largely dueto thefactthatsuchmodelshave proved hardtocome by.Proponents ofthe new ecology haveadvancedtheuseofmodelsdrawnfrom biology, butthis is hardly new. Moreover, it begs the question ofhowsuchmodelsaretobe applied?and which ones, given thatthereis debatewithin ecologyregarding the validity ofcertain evolutionaryconcepts some anthropologists have argued areusefulfor understanding human ecology(Vayda1976; Brush 1976; Sauer 1978; Slobodin 1978). Whenthestateofthe discipline isviewedfromthis perspective, it becomesclear why the moreadvanced archaeological studiesof prehistoric hunter-gathererecology havetendedtobe performed inareas historically inhabited byhunter-gatherers(Gould1977; Thomas 1973;Jennings1957): ethnographic modelsmakeit unnecessary to develop theoretical expecta tionsof hunter-gatherer behavior.If explanatorygeneral modelsofhunter gathereradaptation were available, of course, onecould investigate the ecology of nonagriculturalistslargely withoutreferencetodirecthistoric analogies.Moreover, intermsofthe presentsituation, this explainswhy 196ROBERTLBETTINGER someofthebest predictive modelsof hunter-gatherer behaviorhavehave developed forusewhere ethnographicanalogies are largely absent (Jochim 1976; Wilmsen 1973; Gorman 1970; Wobst 1974). Simplystated, inthedilemmathat presently besets hunter-gatherer studies, the goals of explanation and prediction are merged. Tomove beyond theendlessformulationof merelyplausiblehypothesesrequires the devising of generalexplanatorymodels; in turn, suchmodels will, in effect, permit the meaningfulanthropologicalstudy of hunter-gathereradaptation in virtuallyany context by meansofthe predictions thatfollowfromthese models. Asthe preceding discussion hints, therehasbeen increasingexperimen tationwithsuch general modelsinthe past few years,although ina more limited way effortsofthiskindhave always interested hunter-gatherer specialists andbeenthe object ofsometraditional types of investigation. Systematic discussionoftheserecent studies,however, is difficult because, owing totheir exploratorynature,theycomprise arathereclecticassort mentof formulations; no particularapproach hasseemed sufficiently promising orattracted enough adherentstobeconsideredadistincttheoret icalschool.In reviewing thisbroadareaof anthropologicalinquiry, I have chosentodealwithalimited group ofstudiesthatseem particularly viable asresearch tools, sothisisaselectiveratherthan comprehensive review. Further, intheabsenceofclear-cutschoolsof thought, I haveforconven iencemoreorless arbitrarily dividedthesestudiesintoasmaller group that attempts todraw regularities or generalprinciples(other than purely descriptiveones) fromtheinductiveuseof ethnographic dataanda larger group that attempts to developgeneral models byinvoking abstract prin ciples or theories,frequentlytaking themfromotherfieldssuchas geography,biology, and economy; each group issubdividedintosomewhat more specifictopical areas.Thesedivisionswillnodoubt appear toacertain extentunnaturaland mechanical;however, this is, as muchas anythingelse, areflectionthatthefieldisimmatureand poorlydeveloped. ETHNOGRAPHICSTUDIES Although the major thrustof ethnographic studiesof hunter-gatherer ecology hasbeen particularistic,dealing withthe adaptive behaviorof specificgroups, itis nevertheless possible todiscern among themtwo types of investigation thathave attempted toextractinformationofmore general application: oneoftheseistheintensive investigation of specific resources; the other, the attempt toreduce patterns ofhuman ecology toasetofun derlyinggoals or principles. I begin my reviewof explanatory-predictive EXPLANATORY/PREDICTIVE MODELSOFHUNTER-GATHERERADAPTATION197 hunter-gatherer modelswiththese ethnographic studiesbecause theybridge the gap between particularistic and generalizing(explanatory)approaches tohuman ecology andatthesametimeillustratethelimitationsaswellas advantages thatcharacterize attempts to generalize from ethnographic data. ResourceStudies By resource studies, I mean investigations oftheinherentsubsistence potential ofa particularplant oranimal species, or group thereof.Theidea is that,allowing for technological differences, theconstraintsandbenefits thusisolatedwillbefelt byanygroupmaking useoftheresource.While necessarily narrowin focus, researchofthiskindis clearly an attempt inthe directionof prediction. Suchstudiesaretraditionalandhavea longhistory in hunter-gatherer research. Dietarystaples are normally selectedfor study. In California, forexam ple, theacornhas long beenseenas lending adistinctivecharactertosub sistence adaptation,owing toitsuseasasubsistence mainstay(Gifford 1936; Beanand Saubel 1961; Baumhoff 1963;Willey and Phillips1958). In theGreat Basin, Thomas (1973) hasassessedtheeffectof pinyon(Pinus monophylla)productivity onthelocationandsocial composition of groups dependent onit.Hisworktendstoconfirmthe impressions ofSteward (1938), whohadearliercommentedonthe sociallyfragmenting effectsof pinyon andother similarly unreliableresources.In addition, inanearlier workSteward (1936) had explained the patrilineal bandasa development in response tothe requirementsimposedbylargegamehunting. Morere cently, inmuchmore sharply focused studies, Burch (1972) andSmith (1978) have investigated the implications ofcaribou exploitation forthesize andmovementsof groupsheavily reliantonthisresource.Parmaleeand Klippel(1974) discussthesubsistence potential ofmusselsforthe prehis toricMidwestandconcludethatitslimitationsmakeit an unlikelyprimary resourceandamore likelydietarysupplement. Meehan (1977)reports similar findings formodern hunter-gatherers in Arnhem Land; she argues, however, thatthe importance ofthisresourceshouldnotbemeasuredin termsof proportionaldietary contributionalone.In particular, shefound thatwhereasshellfish yieldedprotein and energy in only modest quantities, easyprocurement andconstantand dependableavailability madethemim portant elementsintheArnhemLanddiet. Aschmann (1959:78) has pointed tothecritical importance of species that are minor dietary constituentsbutwhichareavailablewhen major resources failorare seasonally unavailable and,thus,anticipated Meehan'swork. Similarly, Wilkinson (1975) has suggested that muskoxservedsucha func tion among Arctic hunters, andSteward (1938) andTanaka (1976)portray a 198ROBERTLBETTINGER similarroleforcertain plantsamong theShoshoneand/Gwi San,respec tively. AdaptivePrinciples Recently, asecond group of ethnographic studieshave attempted to generalizeregarding the adaptiveprinciplesunderlying a given subsistence settlement system. Theiraimistoshowthatwhat appears tobea complex setofeconomicdecisionsis intelligible asthe application ofafewrulesin diverse situations, thus paralleling Simon'sdictumthat "Man, viewedasa behavingsystem, is quitesimple. The apparentcomplexity ofhisbehavior overtimeis largely areflectionofthe complexity oftheenvironmentin whichhefindshimself" (Simon1969:25). Thebenefitofsuch analyses is that, if successful, the principles thus definedshouldtranscendthe exigenciesimposedby the specific technoen vironmentalsituationinwhichthe investigator findsthem. Thus,they shouldbe readilycomparable to principlessimilarly derivedinothercon texts and, in theory, shouldbe capable of furnishingpredictions about economicdecisionsin a variety ofsituations. Examples ofthis approach are providedbyRogers andBlack (1976), Lee (1969,1972), Gould (1969a), Marks (1976,1977a,b), MarksandShea (1977), and Flannery(1968). Inoneofthe most enlighteninganalyses ofthis kind,Rogers andBlack discusssubsistenceandsettlement strategiesamong the WeagamowOjibwa between1880and1910?a period whentraditional big-gamespecies were severelydepleted andsubsistencebecame dependent onfishandhare (Lepus). Basedoninterviewsand documentary sources, theysuggest that adaptive behaviorinthisintervalresultsfromthree principlesguiding economicchoices.Theseare: 1.Toseekfoodresources chiefly atthetime they aremost readily and abundantly available. 2.Tolocateanddistributethehuman population(providers and consumers) insucha mannerasto minimizetimeand energyspent ontraveland transport, and regulategroup sizeinaccordancewithresource availability(PrincipleOne) andtheexistenceof ap propriate habitatfor campsites. 3.Tobe ready with contingencyplans that may overrideor supersede therulesas given abovewhencircumstancesdemandeditforsurvival (Rogers andBlack1976: 20-22). Rogers andBlackfurtherdescribethesettlement system usedtomeet these principles asoneinwhichtherewerehomebase camps,occupied repeatedly for longperiods andsituatedattheheartofan exploitation area thatfurnishedthebulkofsubsistencein anygivenyear, andsatellite camps, EXPLANATORY/PREDICTIVE MODELSOFHUNTER-GATHERERADAPTATION 199 occupied forshorter periods andsituatedatsomedistancefromthebase camp inorderto permitexploitation of special resources. Lee (1968,1969,1972) has presented detaileddiscussionsof !Kung San (Bushman) subsistencebehavior.Heshowsthatthe !Kung are extremely selectiveintheirchoiceof resources, favoringspecies thataffordthema secure dietaryregimen. In particular,althoughthey have knowledge of some85edible plantspecies,just oneofthese?the mongongo nut (Ricinodendron rautaneii Schinz)?furnishes one-halftotwo-thirdsofthe plant intake byweight, aboutone-thirdtheoverall dietary intake byweight, andmorethanhalfofthe protein intake.Similar selectivity characterizes huntingpatterns.Only 10of54 potentialtargetspecies are regularlypur sued, the proceeds ofthis activitycontributing in weight about37%ofthe subsistenceintakeandalittle morethanonethirdofthe protein intake.In termsofreturnfor effort,plantcollecting isabouttwoandone-halftimes more productive than huntingper unittime (100 to240calories perhour). Since plant resourcesare quitereliable, Lee (1968) characterizes plant col lecting asa high-yield, low-risk activity and hunting asa low-yield,high-risk activity.Thus,by theirrelianceon plant resourcesthe !Kung maximizetheir energy intakewhile reducing theirsubsistencerisks. Lee (1969) alsoconsidersthe !Kung settlement system and again findsit onein whichrisksarereducedand energy intakeis maximized; in more specific terms, "at anygiven moment, the membersofa campprefer tocol lectandeatthe mostdesirablefoodsthataretheleastdistancefromstand ing water" (Lee1969:81). Whenasettlementisestablishedthisisac complishedby"eating outofthe camp,"concentrating onfoodswithina one-mileradiusinthefirst week, twomilesinthesecond week, andso on, untila maximumofsix milesisreachedandthe camp isshifted owing tothe difficultyof, andlackof economyin,dailytripslonger thantwelvemiles roundtrip. Finally, Lee (1972) hasconsideredthesocialeffectsof maintaining these subsistence principles inthefaceof temporal, that is,long-term and seasonal-resource variability. Heconcludesthatunderthese conditions, rigidly maintainedsocialandterritorialboundarieswouldbedisadvan tageous andthatamoreviablealternativewouldbeonein which group composition is open andresource-use rights areextendedtoabroad range ofrelatives?a pattern to whichthe !Kungactually conform (but, see Heinz 1972) andwhichLee proposes is of generalapplication to hunter-gatherers. Yellenand Harpending(1972) haveelaboratedfurtheronthis point and consideredits archaeologicalimplications, andVita-Finziand Higgs(1970) haveusedLee's findings on !Kungexploitativepatterns to develop their methodofcatchment analysis. Gould (1969a,1977) hasstudied aboriginal subsistence adaptation inthe 200ROBERTLBETTINGER WesternDesertof Australia, anarea considerably less productive of plants, animals, andwaterthanthenorthernKalahariofthe !KungSan,being in these respects morelikethecentralKalahariofthe/Gwiand//GanaSan (Tanaka1976; Silberbauer 1972).Despite the severity of conditions, Gould foundWesternDesert exploitativepatterns toexhibit a degree of selectivity approaching thatofthe !Kung:only 8 of36edible plants and16 of47edible animalfoodscontribute significantly tothe diet; andofthesethe plants are by farthe most important,constitutingupwards of80to90%ofthefood consumed. Taking itscharacteristicsfromthechronic shortage of water, thesubsistence cycle isdistinctiveinthattheerraticoccurrenceofrain storms, ratherthana predictable seasonal rhythm,governs economicde cisions.In effect, the pattern isoneof"rain chasing";regardless of season, thedirectionof group movementisdictated byobserving where rainshave recently fallenandthen deciding whetherthefoodresourcesin theseareasmeritcollectionin light oftheuncertainties regarding whether therainfallhasbeensufficientto replenish watersourcestoa point where they willsustainhuman occupation. Thesedecisionsarefacilitated by in timate geographicalknowledge,particularly ofchainsof relatively reliable watersourcesthat permit travelacrossthe incredibly arid WesternDesert. Inactual practice,groupsmoving toanareaofrecentrainfallmakeuseof small,unreliable, and rapidlyevaporating watersources first,eventually working their way towardthe larger morereliableones.Oncea camp is established, theinhabitants proceed tocollectresourcesnearathand first, subsequentlyturning theirattentiontothosefarther away?apattern com parable tothatfound among the !Kung. Gould (1977:168-170) thinksthe WesternDesertsubsistence adaptation is governedby a strategy of"riskminimization"in which plant foodsfur nishthebulkofsubsistenceintakeandeconomicdecisionsare kept flexible bymatchingknowledge of fast-changing environmentalconditions against detailed geographical information.In general, decisionsare madeinsucha way astoreduce uncertainty, sothatwhenalternativecoursesare available, groupsinvariably favorthecourseofwhichtheresultsare relatively certain overcourseswherethesubsistence gain is potentiallyhigher buttheout comeislesscertainandthereforeentailsmorerisks. Thus, LeeandGould perceive the systemsthey havestudiedtobeonesin whichrisksareminimized. However, sincetheAustralianDesertasde scribed by Gould appears tobeatleastaserraticin productivity asthe northern Kalahari, itis surprising thattheAustralian groups exhibitsub stantially more well-developedconcepts of territoriality andresourceuse rights(Gould1969a) thanonewould expect fromLee's (1972)study ofthe !Kung andhis general inferences regarding the dysfunctionalaspects ofter ritorialbehaviorwhereresourcesareerratic.AsGould points out,however, EXPLANATORY/PREDICTIVE MODELSOFHUNTER-GATHERERADAPTATION 201 in Australia, territorialbehavioris closely tiedtoaritual system thatserves totransfer geographical informationfrom generation to generation; thusit is, inthis sense, conducivetosuccessful adaptation. Itisstillunclear why a similarterritorial system failedto develop inthe Kalahari.One possibility is the recency ofSan entry intothe area; in anycase, thisis a point forfurther study. Although mostrecentresearchonmodern hunter-gatherers hasfocused on plant resourcesandtheir procurement, Marks (1976,1977a,b; Marks andShea 1977)presents severaldetaileddiscussionsofsubsistence hunting among the Valley BisaofZambia.HisresearchshowsthattheBisadonot choosetheir targets inarandomor haphazardfashion, butmakedefinite selectionsdetermined byspecies andlocal conditions, hence reflectingpat ternedeconomicdecisions.Theresultofthesedecisionsistotakethe larger individualsofthe largerspecies(Marks 1976:Tables 39,41). Marksand Shea (1977) havealso presented adetailed analysis ofBisabuffalo hunting. They showthattheBisahuntersselecttheir targets fromthreedifferent kindsofherds: (1)omnipresent,sedentarybachelors;(2)large herdscon sisting ofboth sexes; (3) smallmixedherds.Thebachelorsare always within huntingrange and easy tolocatebuttendtobe lean, difficultto approach, and dangerous oncewounded.Ontheother hand, themixed herds, both large and small, areeasierto stalk, less dangerous, andcontain high fat content females, butarenot alwayspresent withinthe huntingrange ofthe Bisa.Giventhese choices, MarksandShea argue thatifthehunterswerein terested only in maximizing thenumberof kills,they wouldhuntbachelors almost exclusively;similarly, if huntingpatterns wererandomsothat animalswereselected onlyaccording tothe frequencies in they were present inthe huntingrange, thenbachelorswouldbetakenmost often, followed bylarge mixed-herdanimalsandsmall-herd animals, inthatorder.The pat tern observed,however, isonein whichthe large mixedherdsarehunted mostofthe time, bachelorherdswithsomewhatlesser intensity, andsmall mixedherdsalmostnotatall.MarksandShea argue thatin adopting this behaviortheBisahunters approximate a"minimax" strategy in which they minimizethe maximum hunting risks they takeandin doing so guarantee a relativelysafe, moderatereturnfortheirefforts. Although their attempt to rendertheBisahunter strategy ina gametheory formatisnot entirely satisfactory(seebelow), itis nonetheless enlightening inthesensethatitfor malizesthechoices facing Bisahuntersandshowshowthesehunters weigh thesechoices. Inthefinal study consideredinthis section,Flannery(1968) hasuseda smallsetof adaptiveprinciples toaccountfor preceramic subsistenceand settlement patterns intheSouthern Highlands ofMexico. Although the datawithwhichheis ultimately concernedare archaeological, herelies 202ROBERTLBETTINGER uponethnographic accountsfromMexicoandthewesternUnitedStatesto develop a modelofthe principlesunderlyingprehistoric subsistencedeci sions. According to Flannery, tobesuccessfulthese principles hadtoad dresstwocriticalconsiderations: (a)seasonally limited availability of pro ductiveresources (seasonality), and (b) theneedtochoose among several resourceswhen they areallavailableatthesametime (scheduling). Under these circumstances, threebasic principlesgoverned economicdecisions: (1) plant resourcestake exploitativeprecedence overanimal resources; (2) when available,seasonally restrictedresourcestake precedence overresources available yearround; and (3) thesizeof populationaggregation is adjusted seasonally toreflectthelocalabundanceofresources. Largeaggregates characterizingperiods of peak resourceabundancefissionintosmallerunits asresourcelevelsdecline seasonally. Clearly, the principlesproposedbyFlannery are essentially thesameas thosesetforth byRogers and Black;moreover, theyimplicitly stresstheim portance of minimizing riskandthusareconsistentwiththeconclusionsof Lee,Gould, and Marks?except that Flannery addsthe point thatthisrisk minimizationcarrieswithitthe penalty of inhibiting the potential forevolu tionarychange to moresuccessful adaptations. Discussion Characteristic simplicity and parsimonious summarizationand explica tionof seeminglycomplex subsistencebehavioraretheobviousbenefitsof the empirical searchforbasic adaptiveprinciples or goals. Thedisadvan tages,however, seem equallyapparent. In particular, such principles are ambiguous and qualitativelydefined,making itdifficulttoseehow they might be operationalized intheformofconcrete predictions for generalap plication orhowthe goals thusisolated might be compared witheachother. And failingthis, studiesof adaptiveprinciples are open toallthecriticisms that plague functional arguments asreviewedina preceding section.Inad dition, thereare practical limitsonour ability toextractsuch principles, sincethenumberofcaseswhereonecaninferthemonthebasisoffield workorhistoricaccountsis severely restrictedandthereis no guarantee that thecasesatour disposalrepresent thefull range of principles either possible or actuallypracticedbyhunter-gatherers(cf. Binford 1967; Freeman 1968). Comparableobjectionsapply to similarlyinspiredspecific resource studies,namely, thatthenumberof potential resourcestobestudiedis limitless, whereasour ability to study themis quitelimited, this being most obviouswherea particular resourceisextinctorno longer occursinits pristine state. Moreover, the study ofindividualresources, however enlight ening, tellsuslittleabouttheinteractiveeffectsof combining thesamere EXPLANATORY/PREDICTIVE MODELSOFHUNTER-GATHERERADAPTATION203 sourcewithseveraldifferent possible mixturesofotherresourcesinthe same adaptivesystem;scheduling and synergisticdietary effectsare only twoofthe many considerationshere (see alsoClarke 1976). Without wishing tobecomeembroiledinthedebate regarding therelative meritsofinductiveanddeductive research, Ishall simplypoint outthatin light oftheseandother obstacles, it wouldseemtobe extremely difficultto generalize about hunter-gathereradaptation from particular studies? howeverdetailed they may be.Thisviewisshared by many, sothatinrecent years therehasbeenincreased emphasis on generalexplanatory models whose application isnot expressly tiedtoa specific case.Itistothese modelsthatI nowturn. GENERALMODELS OFHUNTER-GATMERERADAPTATION To repeat whatI have already said above, the general modelsI havein mindherearetheoreticalconstructsthatreston postulated causalrelation ships inhumanbehavioror adaptiveprocesses andareofmoreorless universal application incontrastto modelsthataredevised only toaccount fora specific caseorare simplyempiricalgeneralizations(cf. Binford 1978). Many ofthesemodelsdrawontheoriesor principlesdeveloped andusedin other disciplines,particularlybiology, economy, and geography;others, however,merely formalizecertaincommonsense assumptions.Regardless oftheir origin, itshouldnotbeconcludedthatsuchmodelsare developed completely withoutreferenceto empiricalethnographic data.Onthecon trary, thereis a veryimportantinterplay betweendataandmodelin theory building. Butinthis interplay, the modelis of primary interestbecauseitis todothe explaining; thedataareof secondary interestbecause they are useful only toindicatethe viability ofthemodelasan explanatory and predictive device (Binford1978). The general modelsconsideredherefallintofour groups, eachofwhich approacheshunter-gathereradaptation fromadifferent vantagepoint. Theseare: (1) modelsof environment;(2) modelsof subsistence;(3) models ofsettlementor location; and (4) modelsof population. ModelsofEnvironment Thesemodelssetforthbroad generalizationsregarding theeffectsofcer tain qualities ofenvironmentonhuman adaptation,many ofthem simply extendinglongstandingbiogeographicalexplanations of adaptivepatterns tohuman ecology.Characteristically, theenvironmental qualities selected for study aredefinedsoastobe applicable in anysituation, thus permitting 204ROBERTLBETTINGER comparative studiesin grossly dissimilarnatural settings.Investigations of thiskindhave clearlysharpened our understanding ofthearticulationbe tweenhumanbehaviorandthenatural environment;nevertheless, intheir present formthe resultinggeneralizations wouldseemtoo ambiguously definedto permitmeaningfulpredictions about specific cases. Someofthe more frequently studied qualities ofenvironmentareasfollows. Diversity Diversity referstothenumberand proportionalrepresentation ofdif ferent species ina given environment.Environmentsoflow diversity(occa sionally termed specializedenvironments) containfew species andare dominated by oneortwo particularly abundant ones; environmentsof high diversity(occasionally termed generalizedenvironments) containnumerous species in roughlyequalproportion.Diversity canbemeasuredinseveral ways, themostcommon being theShannon-Wiener Index, H': s H' = - Sa logA 1=1 where a isthe proportion ofthe population in question that belongs tothe fth species andsisthetotalnumberof species(Pielou1974). Asecondin dex,Simpson'sDiversityIndex,X, isalso frequentlyemployed: X =?A2 i=i where,again,a isthe proportion ofthetotal populationbelonging tothe fth species; sinceXdecreaseswith increasingdiversity, itisconvenientto takeits inverse, 1 A, asa diversity measure.Hill (1970) favorsthe Simpson Index, whilePielou (1974)argues fortheShannon-Wiener Index; itis doubtful,however, thatin mostcasesthedifferencewillbe important toar chaeologists. Itshouldbefurthernotedthatboth diversity indicesmeasure atthesametime diversity(i.e., numberof species) andevenness (propor tionaldistribution amongspecies), itistherefore necessary toobtaina separate measurefor evenness; thisis generally takentobetheratioofthe observed diversity indextothemaximum diversity indexvalueobtainable given thesamenumberof species.Thus, forShannon-Wiener: s evenness = //'///'max = -J^Pilogp/log s /=i andfor Simpson's index: evenness = (1/X)/(1/Xmax) = (\/^pT)/s In relating environmental diversity tothe problem ofhuman ecology, Harris (1969) andGambel (1978) have argued that amonghunter-gatherers subsistence diversity is stronglydependent on ecologicaldiversity, that is, EXPLANATORY/PREDICTIVE MODELSOFHUNTER-GATHERERADAPTATION 205 broad spectrum(generalized)adaptations occurin generalized environ mentsandnarrow spectrum(specialized)adaptations occurin specialized environments. Whilethis generalization seems plausibleintuitively, thereis muchem pirical evidencetocontradictit. Indeed, ascitedinthe preceedingsection, dietary datafromthenorthernKalahariandthe AustralianWesternDesert showthatsubsistence diversity is comparable betweenthetwoareaseven though theenvironmental diversity oftheKalahariasdescribed by Lee (1969) would appear tobe much greater thanthatofthe AustralianWestern Desertasdescribed by Gould (1969). In fact, one might well argue thatthe Kalaharidietis more specialized thanthatofthe WesternDesertbecause the range offoods actuallyexploitedrepresents asmallerfractionofthe foodavailablethandothe range offoods actuallyexploited in Australia. Moreover, Winters (1969) andBaumhoff (1963) document extremelyspe cialized aboriginal dietsinenvironmentsthatwouldbeconsidereddiverse (generalized)by almost any standards.Tothisit might beaddedthatifsub sistence diversity istakenasameasureofniche width, thereislittlein ecologicaltheory to support theideathatnichewidthisrelatedtoen vironmental diversity. In sum, the relationship betweensubsistencediver sity andenvironmental diversityappears more complex thanHarrisand Gambel imply(see Asch,Ford, andAsch [1972] forafurtherdiscussionof subsistence diversity). Ina more sharply focused study,Harpending andDavis (1978) consider the relationship betweenenvironmental diversity andthesizeofsubsistence territory;theypropose aninverse relationship betweenthetwo. Stability Environmental stability variesbetweentwoextremes:environmentsof low stability, whereseasonaland long-termvariability inclimateissevere and erratic, andenvironmentsof highstability, wheresuch temporal vari ability isminor. Ecologists(Pianka1970; Sanders 1968)point outthatun stableenvironmentstendtobecharacterized byspecies thatare small, fast maturing, andhave high ratesof population increaseto compensate forthe heavymortality that accompanies the frequent climaticextremes.Such species, termedr-selected (for the symbol r forrateof populationincrease), usually exhibit population densitieswellbelowthe potentialcarrying capacity oftheirenvironment (MacArthur andWilson 1967). Sanders (1968) hastermedsuchenvironments physicallycontrolled, sincethe population structureandinteractionis primarily a consequence ofclimatic variability. In contrast, inenvironmentsof highstability,species tendtobe large, slow growing,longlived, withslowratesof population increase. These speciesregulate theirnumbersclosetotheir carryingcapacity and hencearetermed^-selected (for the symbol Kfor carryingcapacity; 206ROBERTLBETTINGER MacArthurandWilson 1967).Moreover, becauseundertheseconditions population structureandinteractionare primarily theresultof competition andother densitydependentelements, Sanders (1968) referstotheseen vironmentsas biologically accommodated.Thisaccommodation generally produces communitiesof highdiversity, while physically controlleden vironmentstendtobedominated by afew highly successful species(i.e., low diversity;McNaughton andWolf 1970). Yellen (1978) hasdrawnabroad analogy betweenthelow diversity characterizingphysically controlledenvironmentsandthe uniformity and conservatism displayedbyhunter-gathereradaptation in deserts, whileDia mond (1978)argues that r- and^-selection may characterizehuman reproductivestrategies underdifferentenvironmentalconditions.Beaton (n.d.) takesan altogether different approach andconsidersthedifferential subsistence potential of r- andAT-selectedshellfish species. Inafarmore sweepingattempt,Hayden(n.d.) characterizesPleistocenesubsistence resourcesas^-selectedandHoloceneresourcesasr-selectedandtiesthis distinctionto cultural,technological, and organizational contrastsbetween PaleolithicandPaleoindian adaptations ontheone hand, andMesolithic andArchaic adaptations ontheother. Several investigators havealso explored environmental stability froma spatialperspective.Here, stableenvironmentsarethosecharacterized by resourcesthatare relatively immobileand uniformlydistributed, while unstableenvironmentscontainresourcesthatare mobile, unevenindis tribution, andvariableintheir localitythrough time.BasedonHorn's study ofBrewer'sblackbirds (Horn1968), Wilmsen (1973)suggests that highly stableresourceswilltendto promotesmall,widelydispersed settlements and highly unstableresources larger, morecentralizedsettlements.This makesintuitive sense, becausea large central place settlementeliminatesthe riskof being intheworst spot(i.e., themaximumdistance away) whena mobileresource presentsitself;conversely, whenaresourceis widely distributedand stationary, nodistanceriskisentailedsothebest approach istobreakintosmaller dispersed unitsthatminimizethedistanceanin dividualmusttravelto exploit theavailableresources. Alternatively,Dyson-Hudson andSmith (1978)propose thatunstable resourcesfavor large subsistenceareasand shiftingsettlements, towhich Harpending andDavis (1978) addthatthis unstability wouldalsoleadtoin creasedfood storage. Productivity Thisreferstotheamountofbiomassorcalories producedannually ina given environment. Biologists havestudied productivityprimarily interms ofa proposedpositiverelationship betweenitand diversity(Connell and Orias 1964). Ontheother hand,anthropologicalapplications centeronits EXPLANATORY/PREDICTIVE MODELSOFHUNTER-GATHERERADAPTATION 207 useasa measureof carryingcapacity(Casteel1972b; Zubrow 1971) orin termsofits implications for exploitation territories amonghunter-gatherers (Dyson-Hudson andSmith 1978) and primates(Altmann1974), theselatter studies arguing fordecreased territory sizeandincreasedterritorialdefense as productivity increases. Patchiness Environments varysubstantially inthe degree towhichtheirresource distributions depart from uniformity, that is, their patchiness. Suchdif ferencesare important to organismsusing these resources, sinceasthe degree of patchinessincreases, sodoesthecostofresource procurement (Weins1976; MacArthurandPianka 1966). Thosewhohave explored the implications of patchiness forhumanornonhuman primates haveem phasized thiscost relationship;theyconsistently concludethatincreased patchiness resultsin expanded subsistenceterritoriesthat quickly become uneconomicaltodefend (Harpending andDavis 1978;Dyson-Hudson and Smith 1978; Altmann 1974). Discussion Adetaileddiscussionoftheaboveenvironmentalmodelsis beyond the scope ofthiswork. Nevertheless, the point shouldbemadethat although thesestudieshaveina verygeneralway addedtoour understanding of man-land relationships fromabroad?as opposed to particularistic perspective, the regularitiesthey setforthwouldseemtobe onlyweakly felt (and hence weaklypredictive) in anygiven situation.For instance, the weight ofrecent demographic studies (e.g., Hassan 1978)suggests that whilehuman reproductivestrategiesprobably vary,they dosoin afar more subtlemannerthanDiamond'sr-Kcontrast implies.Perhaps the major point hereisthatallofthesemodels employ the assumption ofceterus paribus, andthis assumption will always be inappropriate when specific casesareconcernedunlessonecanaddressthe problem ofhowthe general modelistobemodified according tolocalconditions.As presently out lined, mostoftheabove investigations failtocometo grips withthisissue andsohave onlygeneral ratherthan specificimplications forhunter gathereradaptation. MODELS OFSUBSISTENCE Historically, subsistence patterns havecommandedmoreattentionthan any other singleaspect of hunter-gathererecology.Quiteclearly, thereis a generally held assumption thatwhenoneconsidersman-land relationships 208ROBERTLBETTINGER subsistenceis really whatitis allabout.Itis true, of course, that population increaseis widely citedasthe most theoreticallyacceptableway ofmeasur ingadaptive successorfitness.Butbecause population has provedquite dif ficulttodealwithboth archaeologically and ethnographically, whenoneis actuallyjudging the performance ofan adaptivepattern, the ability to pro ducean acceptable foodintakeis usually thebottomline (e.g., Lee 1969). Despitethis,however,very few explanatory-predictive subsistence modelshavebeen proposed. Inthe followingsection, Idiscussthesefew along withothermodelsfrom biology and economy thathave yet tobe ap pliedfully to hunter-gatherers butwhicha growing numberof investigators suspectmightultimately be appropriate tothe problem. OptimalForaging ModelsIn Biology Inrecent years,biologists havebecome increasingly concernedwiththe development of general models capable of predicting an optimalforaging patternapplicable overa wide range of species andenvironments (Schoener 1971;Pyke,Pulliam, andCharnov 1977). Inthese studies,particular atten tionhasbeen given tomodelsof optimum diet ultimately drawnfrom economic theory(MacArthur andPianka 1966), andthishasresultedina broadconsensusonasolutiontothe problem. Sincethe modelseemsread ilyapplicable, atleastin theory, to hunter-gatherers(having inafewin stances actually beenusedinthis context) andbecauseitdiffersin impor tant respects fromothermodelsthathavebeen developedspecifically for usewith hunter-gatherers, Ishalldiscussit briefly. The optimal dietmodelassumesthatfora specific consumerin a specific environmentonecanenumerateall potential subsistenceitemsanddeter mineforeachtheamountoftimeittakestolocateoneoftheitem (search time) andtheamountoftimeittakesto capture,prepare, andconsumeone oftheitem (handlingtime). In general, searchtimeforanitemdecreasesas its densityincreases; butthisistrue onlyup toacertain"saturation point," afterwhichincreasesin densityproduce no appreciable decreaseinsearch time.Ontheother hand,handling time generally variesasafunctionofthe sizeofthe dietary itemrelativetothesizeofthe consumer, increasing with larger itemsand decreasing with larger consumers. Withthese quantitiesdetermined, wecanseethat dietary relianceonthe itemwiththelowest handling timewillmaximize harvestingefficiency but may resultin unacceptablyhigh searchtimesbetween locating individuals ofthatitem. Obviously, if weaddotheritemstothedietthesearchtimewill decreasebut handling timewill (usually) increase.The problem,then, isto determinehow many oftheitemstoaddtothedietinorderto optimize in take per time spentforaging. In essence, the optimalforaging modelsolves EXPLANATORY/PREDICTIVE MODELSOFHUNTER-GATHERERADAPTATION209 thisdilemma byarguingthat, inorderof increasinghandlingtimes, items shouldbeaddedtothedietso long asthe resulting decreaseinsearchtimein the expanded dietis greater thantheincreasein handling time.Whenthe decreaseinsearchtime justequals theincreasein handlingtime,equilib riumhasbeenreachedandnootheritemsshouldbeadded (MacArthur and Pianka 1966; Schoener 1971;Pyke, PulliamandCharnov 1977). This pro cesscanbe plotted asa graph in which dietary itemsarerankedfromlowest to highesthandling timeandsearchand handling timeassociatedwithdif ferentdietsaredrawnas separate lines (Figure5.1).Here, the optimal diet isindicatedwherethetwolines (search and handling) intersect.Itshouldbe notedthatthismodelassumesthatallitemsofthedietareof equal food value; wherethisis notthe case, thentheinitial ranking ofitemsis ordered intermsofnetfoodvalue perhandling time. Two importantimplications followfromthismodel. First, whetheran ITEMSOF DIET RANKEDFROMLOWESTTO HIGHESTHANDLINGTIME Figure 5.1. Graphicdisplay of changes in pursuit and handling timesasitemsare addedto an hypothetical diet.At point"A," thedecreasein searchtime just equals theincreasein handlingtime, sothe optimum dietshouldincludeitems 1, 2,3,4, and5. 210ROBERTLBETTINGER itemisincludedinthedietis independentof its ownabundanceand depends only ontheabundanceofitemswithlower handling times.That is, low rankeditemsareconsumed only if higher-ranked itemsare relatively scarce. Second, astheoverallabundanceofallitems decreases, moreitemsare addedtothediet.Thiswouldseemtoaccountfor highlyspecialized aboriginal dietsin relatively richCalifornia (Baumhoff1963) andMidwest (Winters1969)environments, as suspectedbyAsch,Ford, andAsch (1972), aswellasthe tendency fordiettobesomewhatmore specialized inthe Kalaharithanintheless productive WesternDesertofAustralia (see above).Moreover,many ofthe dietaryresponses tofood shortageproposed by Cohen (1975) are explainedby the optimalforagingmodel, so long as we interpret abundanceasa relationship betweenconsumerandresources.Ad ditionally, itis worth noting thatthe range of dietary itemswilloften vary according toseasonalfood availability,being restrictedinsome seasons, much expanded inothers. Indeed, thiskindofshort-term temporal varia tionbetweenrestrictedand expanded diets appears common amongmany hunter-gatherergroups, acharacteristicthatwouldseemto severely limit the utility of designating individual adaptations as generalized(diversified) or specialized(restricted)?at leastinthesense usually intended. Despite whatwould appear tobeobviousattractionsofthismodelfor those working with hunter-gatherers, therehavebeen only afew applica tions.Beaton (n.d.) has attempted to employ itin predicting shellfish pro curement patterns; his application,however, isheuristicand nonquan titative.Ina broadly similarbut expandedanalysis, Perlman (n.d.) usesthe modelto predictgeneralpatterns ofcoastal adaptation. His study differs fromBeaton'sinthatsomeactual quantitative dataare employed toderive expectations aboutsubsistencebehaviorincoastalcontexts. TheHunter-GathererGoalModel Jochim (1976) hasoutlined a comprehensivequantitativeapproach to hunter-gathereradaptation thatrests ultimately ona predictive modelof resourceuse.Heassumesthatresourcesare exploited in proportion totheir ability to satisfy twobasicsubsistence goals:(a) attainmentofasecurein come; and (b) maintenanceof populationaggregation atlowcost. Applica tionofthis modeltoa specific case requires thatall potential resourcesbe measured according totheir: (1) weight(w);(2) nonfood yield, for example, antlers, hides (n;expressed asa proportional increaseof w);(3)aggregation size (a);(4)density(d); and (4) mobility(m). Giventhese quantities, the secureincomescorefor any resourceistakenassecureincomescore = wnd/mandthelowcost populationaggregation scoreaslowcost popula tion aggregation = wna/m. EXPLANATORY/PREDICTIVE MODELSOFHUNTER-GATHERERADAPTATION211 The proportional useofindividualresourcesis calculated bysumming the secureincomescoresandlowcost aggregation scores separately overall resourcesandthen determining the proportional contributionmade by each resourcetothese sums; foreach resource, the meanofthesetwo propor tionsisits predicted contributiontosubsistence.This general modelcanbe modifiedtotakeintoaccountseasonalvariationsinthecharacterofa given resource. Thereareseveraldifferencesbetweenthis modelandthe optimalforaging modeldiscussedearlier. First, inJochim's scheme, allresourcesenterthe diet regardless oftheir proportional contributionandthatcontributionis determined by the physical characteristicsand spatial distributionofeach resource.Inthe optimalforagingdiet, resourcesbelowacertaincutoff point are ignored andthosethatareincludedareconsumed exactly in pro portion totheirrelativeabundance. Second, andrelatedto this, Jochim's model predicts no change inresourceuseunderconditionsof increasing overall scarcity, whereasin optimalforaging, as scarcityincreases, more itemsareaddedtothediet. Judging fromwhatwould appear tobe nearly universal selectivity onthe part of hunter-gatherers?whether undercondi tionsof scarcity(Gould1969a) or plenty(Asch,Ford, andAsch 1972)?the optimalforaging model might be preferable toJochim's model, which seemsmostusefulincaseswherethe range ofresources exploited is known to begin withandthe problem isto predict their proportional use. Itis probablyworthy ofnotethatJochimdoesnot attempt totreat plants predictively?probably becausesomeofthebasicmeasuresin hismodel ap pearinappropriate inthat context, for example,mobility. This problem wouldnotseem insurmountable,however, anditis likely thatthebasicfor matcouldbe readily modifiedsoastoinclude plants aswellasanimals. Theseissues aside, itis clearthatJochim'smodelis a major advancementin our understanding of hunter-gatherers andthefirstsolid step towardex planation and prediction. ModelsofDecisionsandGames Inabroad sense, the model developedby Jochim (1976) is an example of a larger fieldofeconomic study thattakesdecision making asacentral problem of analysis(Simon1957; MillerandStarr 1967;Fabrycky and Thuesen 1974; Dillonand Heady1960).Typically, thedecision process is couchedintermsofaconsumerfacedwitha variety ofalternative choices, eachofwhichresultsinaknown range of payoffs underdifferentcondi tions (e.g., alternative croptypes withdifferent yields under varying mois ture regimes). Two parametersweightheavily insuch situations, one being the ability to anticipate future conditions, which ranges fromabsolutecer 212ROBERTLBETTINGER tainty toabsolute uncertainty with varying intermediate degrees of risk, and theother being the goalssoughtby theconsumer.Such goals are usually set to maximizesome payoff, minimizesomecostor loss, orto satisfy someex ternal requirement(e.g., inJochim'smodelthesatisfactionlevelissetatat taining secureincomeandlow-cost aggregation). WhereasJochim (1976:7) andothersfavorthesatisficer principle over others, IwouldfollowJohnson (1977) in pointing outthatitis descriptive unlessthesatisfactionlevelitself canbe explained. Themore commonly cited goals thatremainare: (1) tomaximizethe maximum payoff(maximax);(2) to maximizetheminimum payoff(max imin);(3) to maximizethe mean payoff; and (4) to minimizethe maximum regret, where regret istakentomeanthedifferencein payoff betweena given choiceandthebestchoicefora givencondition;thus, the maximum regret isthe largest suchdifferencefora given choiceoverallconditions (Grawoig1967). Toillustratehowthese goalsmightapply inanactual case, I havecom puted an hypotheticalpayoff matrixfora group ofhunters embarking ona huntingtrip(Table5.1).They mustselectbetweentwokindsof weapons (I and II), whichare differentially effective against thetwokindsofani malherds (I and II)theymay encounter.The payoff matrixindicatesthe amountofmeat perperson thatcanbe expected whena particularweapon is used against a particular herd type. Asanaidto understanding, the max imum,minimum,mean, andmaximum regret valuesassociatedwitheach weapon choice are given tothe right ofthe payoff matrix.Withthese quan tities calculated, itis easy toseethatifthehuntershadnobasisforan ticipating whichherd typetheymight encounter (i.e., absolute uncertainty), they shouldchoose: weapon Ito maximizethe maximum return,weapon II tomaximizetheminimum return, andeither weapon Ior weapon II (it TABLE5.1 Payoff Matrixfor a Hypothetical SituationinWhichThereAreTwoPossible Weapon Types andTwoPossibleHerd Types Nature _Decisionvalues8_ Maximum HunterHerdIHerdIIMaximumMinimumMean regret Weapon I9 kg 4 kg 946.5 4(=|4-8|) Weapon II 5kg8kg 856.5 4(=|5-9|) a The maximum,minimum,mean, andmaximum regret valuesattachedtoeach weapon setareindicatedonthe right ofthe payoff matrixitself. EXPLANATORY/PREDICTIVE MODELSOFHUNTER-GATHERERADAPTATION 213 makesnodifference here) to maximizethe mean payoff orto minimizethe maximum regret. Without makingany further assumptions, itis possible to regard these different goalsmerely asasuiteof hypotheses tobetested against each otherfor comparativeviability in anygiven situation. Nevertheless, there canbelittledoubtthatcertainconditionswilllendthemselvestothe adop tionofsome goals butnotothers.For instance,ceterusparibus, maximax goal behaviorwouldseemmore likely whererisksare perceived as being minimalor unthreatening?as when playingpoker withadeckthathasbeen markedinacode you understandorwhen playing formatchesratherthan real money.Conversely, whererisksare especiallyhigh or threatening, a maximin strategy, which guarantees thebestriskless return, wouldseem more appropriate; herean example wouldbe choosing to deposit one's retirement savings in anFDICinsuredbank-accountratherthan risking itin thestockmarket.Goalbehavior maximizing the mean payoffmight beex pected tooccurwherethenumberoftrialsituationsis largeenough toin somesubstantial way overcomethe vagaries of sampling error,thusinsur ing thatthe mean payoff willbe closelyapproximated. An example drawn frombaseballwouldbethe practice of consistentlypinch-hittingright handedhitters against left-handed pitchers(and left-handers againstright handers), while substituting left-handed pitchersagainst left-handedhitters (andright-handersagainstright-handers).Finally, a strategy that minimizes themaximum regret can perhaps bestbeunderstoodasan attempt to "track"the maximum payoff overa variety ofconditionssothatthis max imumwilltendtobe approximated as closely as possible. This strategy strikes something ofa compromise betweenmaximax strategies(where risks arefelttobe quitelow) andmaximin strategies(where risksarefelttobe quitehigh).Alternatively, one might also expect behavior minimizing the maximum regret tocharacterizesituationswhereoneconsumeris attempt ing to outperform(e.g.,outfish,outhunt,etc.) anotherconsumer playing against thesameconditions. Game Theory Thosewhohave attempted to apply thekindof decision-making context describedaboveto anthropologicalproblems haveoftendoneso bycasting it asatwo player, zerosum game, arather special situationthatfallsunder thefieldof gametheory(for a range of gametheory discussionsfromsim ple to extremelycomplex seeWilliams 1954;Rapoport1960; Luceand Raiffa 1957; vonNeumannand Morgenstern1944).Here, boththecon sumerandNatureareactive players, and any gain tooneisa losstothe other (i.e., the payoff totheconsumerisalossto Nature [environment]). According tothe principles of gametheory underthese circumstances, 214ROBERTLBETTINGER Natureshould adopt a strategy in whichShe presents theconsumerwith conditionsthatminimizethemaximum payoff tothe consumer, that is, a minimax strategy; in turn, theconsumershould adopt choicesinsucha way asto maximizethe minimum payoff to him, that is, a maximin strategy. Tounderstandtheeffectofthese assumptions onthe decision-making process, returntothe payoff matrixin Table5.1andnote that, as before, if thehunterswishtomaximizetheirminimum payoffthey shoulduse weapon II?thisistheirmaximin strategy and guarantees thema payoff of atleast5 kg ofmeat perperson.However, nowNatureis also playing; and ifShefollowstherecommended strategy of minimizing themaximum payoff tothe hunters, Sheshould present themwithherdII becauseits max imum payoff tothehuntersis8 kg, whereasthatofherdIis9 kg. Thisis good newstothehunterssinceif they followtheirmaximin strategy while Naturefollowsher minimax strategy, the resultingpayoff tothehuntersis 8 kg?3kg morethanthehunter's strategy was designed to guarantee. To followthe logic of gametheory,however, thissituationis unacceptable to NaturebecauseitcostshermorethanifShehad presented thehunterswith herdI (which wouldhavesatisfiedthehunter'smaximin goal). Tocounter this, She might chooseherdI.IfShedoes so,however, thehunters might then respondbychoosingweapon I andthusincreasetheir payoff totheab solutemaximumof9 kg; butshould they do so, they runtheriskthat Naturewillinturncounter bychoosing herdIIandthus sharply reduce their payoff totheabsoluteminimumof4 kg. Clearly,given the assumption oftwoactive opponents, the payoff matrix inTable5.1becomesindeterminateintermsofthe simple solutionsthat followwhen only theconsumeris making rationalchoices.Game theory resolvesthis indeterminacybyproposing thattheconsumers (hunters) mix theirchoicesinsucha way thatnomatterwhatNature does, their payoff is thesame.Without goingthrough the calculations, itcanbeshownthatif thehuntersuse weapon I three-eighths ofthetimeand weapon IIfive eighths ofthe time, overthe long run theyguarantee themselvesa steady payoff of6.5 kg nomatterwhatNaturedoes.Notethatthis payoff is higher than they wouldhaveobtainedwiththeir simple maximin strategy(6.5kg vs.5 kg). Itis worth pointing outthatinthis instance, hadthemaximin strategy ofthehunterscoincidedwiththe minimax strategy of nature, the hunterswouldhavehadtofollow a "purestrategy," that is, onein which thesamealternativeis alwaysfollowed, ratherthan being mixedwithother alternatives. Thebestknown anthropological studies usinggametheory areDaven port's(1960)analysis ofJamaican fishingstrategy andGould's (1963) in vestigation ofAfrican pastoralists, the onlyapplication ofthe technique to hunters being MarksandShea's (1977)attempt toaccount for Bisabuffalo EXPLANATORY/PREDICTIVE MODELSOFHUNTER-GATHERERADAPTATION 215 hunting asa minimax game solution.The explanation ofMarksand Shea, however, is unacceptable because they forma game in whichthebuffalo havetwochoices open tothem:inone they are killed, intheother they escape. Nowitisobviousthatifthebuffaloare actingrationallythey shouldfollow a minimax strategy and alwaysopt forthechoicethatresults intheir escape. Sincethe empirical datashowthatsometimesthebuffalo are killed,they cannotbe actingrationally andthusthe assumptions and resultantsolutionsof gametheory are inapplicable. Inthis context, itseemsworthwhiletoreviewsomeofthecriticismsthat havebeenleveled againstgametheory andthen suggest some guidelines for itsuse. Perhaps themostfundamental challenge hasbeenraised by Read (1974), who questions the validity ofbasic gametheoryassumptions when applied tothe problem ofhuman adaptation onthe grounds thatthereis no reasontobelievethatNatureis actingrationally andhence vindictively. Clearly, Readhasa pointbecause,according to modern science, Nature hasno being andthuscannotact rationally.Nevertheless, this objection misplaces the potential roleof gametheory in hunter-gatherer studies becauseittakesthe game solutionitselftobeof primaryinterest, whichitis not.More properly, theroleof gameanalysis liesin developingquantitative modelsof hunter-gatherersacting as ifthey believedNaturetobevindic tiveasabasisfor testingagainst realdata.The ethnographicliterature, of course, doescontain examples of aboriginalgroups thatconsiderNatureto beanimateand hostile, andundertheseconditionswe mightcertainly ex pect a gamelikeapproach to adaptation(Rassmussen1929:56). Evendisre gardingthis,althoughgametheory assumesthatNatureis anactive player, itdoesnotfollowthatthe strategy itrecommendstothe opposing ab originalgroup isvaluable only wherethese assumptions hold.Forexam ple, the gameapproachproduces ausefulmethodfor problemsolving underconditionsofabsolute uncertainty. Thisisclearbecauseunder game theory thesuccessful strategy wouldhavethe aboriginal"player" make thechoicethat guarantees the highest(maximum)payoff ofthelowest (minimum)possiblepayoffs(i.e., the highest risk-free payoff)regardless of whatthe opposingplayer does?a strategyeminentlyprudent whenonehas littleideaofwhatcoursethe opposingplayer(Nature)might followand cannotchancethedisastera poor choice mightbringregardless ofwhether thisisan intentionalactofNature. Moreover, withthe game solution ap proach oneoftwo things willbetrue: (1) ifthe game solutionrecommended forthe aboriginalgroup is a "purestrategy," andNaturefailstoactvindic tively, thenthenetresultwill always betoincreasethe group'spayoff;(2) if thesolutionis a"mixed strategy," thenitmakesno difference whatNature doessincethe makeup ofthe"mixedsolution" alwaysyields thesamere sults.Ineither case, we might describethe gamestrategy asonethat 216ROBERTLBETTINGER neutralizesorstabilizesthe vindictive,capricious,mischievous, or simply randomtendenciesofNature.Since manycontemporaryhunter-gatherers seemto wantto minimizetheir risks, asseveralstudiescitedabove indicate, gametheorypresents an approach to formalizingquantitatively this type of behavior. Ontheother hand, severalcircumstanceslimitthe application of game theory to specific cases.Forone thing, itisoftendifficulttodevisesitua tionsthat actually meetthe requirements toforma gamesolution, astheat tempt ofMarksandShea (1977)aptly illustrates. Similarly, the payoff valuesareoftendifficulttodeterminefor given instances.Alsotroublesome isthat gametheoryrequires both players tocommitthemselvestoa particu lar strategy andsticktoit. Empirically, asresearch among modernhunter gatherersshows,aboriginalgroups are capable of rapidlymodifying their behaviorascircumstances develop; the gamemodel, thereforeseemsmost appropriate wheresomesortofirrevocablechoiceisinvolved. Keeping theselimitationsin mind,perhaps thebest application for game theory, andtheonefavored bygame theoreticians (Rapoport1960; Wil liams 1954), is notasa methodfor determining a precisestrategy fora given situationbutratherasa meansfor understanding thekindsof options that are open to players underdifferentconditionsandhow they mightgo about making thebestofuncertainsituations. AsRead (1974)observes, thereal danger with gametheory liesinitsuse whenmore simple andclearcut understanding couldhavebeenobtained by detailedexaminationofthedataathandandconsiderationofthe logical implications ofvariousalternative choices; inthese cases,gametheory will confuse, ratherthan clarify, thesituation.In short,gameanalysismaypro vide insights aboutcertain problems, butitis nosubstituteforhardheaded thinking about empirical data. Linear Programming Although concerted attempts atits anthropologicalapplication are just beginning, linear programming offers yet another potentialapproach tothe development of generalhunter-gatherer subsistencemodels (Benke and Winterboer 1973;Dantzig1963;Dorfman,Samuelson, andSolow 1958; Wagner1975;Spivey andThrall 1970). Computationally somewhatsimilarto gametheory, linear programming differsinthatitsaimistofindthe mosteconomical (leastCOst) solutiontoa given economic problem. Inthe problemgenerallyaddressed, aseriesof production activities are contemplated, eachwithassociatedcostsand payoffs. These payoffs are usually calculatedintermsofmorethanonecur rency; for example, adeerkill mightproducepayoffs in calories,protein, EXPLANATORY/PREDICTIVE MODELSOFHUNTER-GATHERERADAPTATION217 TABLE5.2 GeneralizedMatrixFormatofaLinear Programming Problem Productionactivities (/) Payoffs(/) 12345n Requirements I SuSu3i3auSisSi?U\ C. &21S22?23??24325^2??2 3 33133233382483533?D3 M ?inl3m23m33m43m53m? CostsC,C2C3C4C5C? fat,hide,antler,prestige, etc. Further, the problem may include stipula tionsofvariouskinds:for example, limited ability to meet costs, limited ability to carry outan activity, needto carry outan activity aboveacertain minimal level, anddesired payoff. Giventhese conditions, linear program ming findsan optimum solutionthateithermeetsadesired payoff (minimizationproblem) or simply maximizes payoff intheleast expensive fashion (maximizationproblem). Sucha problem canbe phrased more rigorously in matrix form, asin Table5.2. Here,production activities (j) aredescribedincolumnsl-n (col umn vectors) andthevariouskindsof payoffs(i.e.,currencies) arede scribedinrows1-m (rowvectors).Thus, thevaluea22 corresponds tothe yieldper unitof activity 2intermsof payoff currency 2.Asidefromthese values, the matrixalso displays a (lowermost) row, orc vector,correspond ing tothecost per unitofeach activity. Alsoshownis anextreme right-hand column, orb vector, which specifies the requiredpayoff foreach currency inthe problem. Ifthe problem is oneof minimization, thenthesevaluesin dicateminimum acceptable levels (>b); ifthe problem is oneofmaximiza tion, thenthevaluesindicatethe upper limitsof production(, for/ = 1,2,...m(b^0) and: xy>0fory= 1,2,. ..n wherez = costof production,c, = thecost per unitof activityj,Xj = the 218ROBERTLBETTINGER quantity of y carried out,au = theamountoftheith currencyper unitof they th activity, and 6, theamountofeach currencyrequired inthe problem. Toseehowthis mightwork, considera simpleexample in which a group ofhuntershasatits disposal three trapping areas (I,II, and III,respec tively), eachofwhich produces smallandmedium game in different propor tionsand quantities thatcanbe specified intermsof outputpertrip. Inad dition, dueto varyingroughness ofterrainandother conditions, eacharea requires differentamountsofmanhoursto trapproperly. Asathirdcondi tion, letusassumethatinthissituationthehuntersare attempting totakea specificquantity andmixtureofsmallandmedium game. The problem isto produce thedesired payoff withtheleastnumberofmanhours (i.e., a mini mization problem). Theseconditionsandassociatedvalues assigned themarerenderedina matrix (Table5.3)equivalent tothe generalized linear programming matrix describedin Table5.2.Inthis instance,trapping in areaIis one production activity,trapping inareaIIa second productionactivity, andsoon.The unitof activity is one trip, thecostisintermsofman hours, andthe payoff currenciesaresmallanimalsandmediumanimals.As seen, thedesired payoff consistsof160 animals, 40smallonesand120 mediumones.AreaI isthe most productive ofmedium game, whicharethe more desired, butis alsothemost costly to exploit. AreaIIIisthemost productive ofsmall game andistheeasiestto exploit. AreaIIisintermediatein allthree respects (i.e., medium game, small game, and cost). Giventhese conditions, itis not intuitively obvioushowthehunters might setabout fulfilling theirneedsin theleast costlyfashion; the advantage oflinear programming,hence, isthat it provides a meansfor finding sucha solution. TABLE5.3 Hypothetical DataandMatrixfor aLinear Programming ProbleminWhich Trappers May Choose among Three TrappingAreas, EachwithaDistinctive Output in Small andMediumAnimalsandMan-Hour RequirementsperTripa Activities AreaIArealiAreaIII PayoffsTripTripTripRequirements Small animals151040 Medium animals15116120 Cost (manhours) 1358565 a Leastcostsolution:10.9 trips inArea II; 927man hours; 54small animals; 120 mediumanimals. EXPLANATORY/PREDICTIVE MODELSOFHUNTER-GATHERERADAPTATION 219 Without presenting the computations, whichare quitelengthy, itcanbe shownthatto gain theirdesired payoff intheleast costlyway, thehunters should spend alloftheirtimeinareaII.Thiswill require 10.9 trips, 927 manhours, andwill produce 54smallanimalsand120 mediumanimals. Noteherethat14smallanimalsareexcessor waste?theymay be kept or discarded according tothehunters' preferences. The point isthateven given this waste, areaIIstill provides the cheapestway of producing theanimal intakeinthedesired quantity; any other mixture, that is, onethatusesarea I orarea HI, willmeanthatthecostwillincrease. Asidefrom providing the optimal solutiontothis problem, linear pro gramming affordsusthe opportunity toexamineseveralother parameters ofthe given situation.For example, itisobviousthatinthiscasesmall animalsare provided inexcessinthe optimal solutionandthatmedium animalsarethe limiting currency(i.e., the optimal solution just satisfiesthe minimum requirement for medium animals).Similarly, it canbeseenthatin termsofmedium animals, areaII produces .13individuals per man hour, whileareaI produces.11, andareaIII.09.Giventhesevaluesandour knowledge thatmediumanimalsarethe limitingcurrency inthis problem, onecanseethatifthe manhourcostwereto drop to115 pertrip forareaI andto46 pertrip forarea III, theseareaswouldbe producing medium animalsatarate comparable toareaII. Werethisto happen, then trapping inbothareaIandareaIIIwouldbecome part ofthe optimal solution. These particular values (115 forareaIand46forarea III) areknownas shadow prices fortheir respective areas. They markthe points atwhichit wouldbecome profitable to trap intheseareas.Wecanalsocalculate shadow prices intermsofincreasedmediumanimal outputpertrip in areaI andarea III; herethevalueswouldbe17.55mediumanimals pertrip in area I and8.45mediumanimals pertrip forareaIII. Further, itisworth noting thatlinear programming wouldallowthe above example tobemodifiedto more accurately reflectarealsituation. For example, maximumrestraints might havebeen placed onthenumberof animalstobetakenfromoneor moreofthe areas, thus reflecting aconser vation policy onthe part ofthehunters. Similarly, aneedto constantly monitorallsubsistenceareas might havebeenincludedasa minimallimit ontheamountoftime spent in any area.Itshouldbe obvious,however, thattheintroductionofsuchrestraints frequently increasesthecostofthe payoff(as it wouldinthis case); even so, the technique wouldindicate whichrestraintsresultedinincreasedcostsorreduced payoffs. Clearly, therewouldseemtobea wide range of potentialapplications for linear programming inthe study ofsubsistence adaptation. Altmannand Wagner(1978), for example, have alreadysuggested itsusetoexaminea subsistence problem in whichseveralresourcesare available, eachwithits 220ROBERTLBETTINGER owncostandassociatedfoodvalue (e.g.,calories,protein,etc.).Here, the ideaistofurnishtheleast costly balanceddiet.Themostnotable applica tionsoflinear programming in archaeology, thoseofReidhead (1979,1980) andKeene (1979,n.d.), takemuchthesame approach. Reidheadreconstructedthe availability, nutrient composition, andcost of production associatedwith aboriginal foodresourcesintheOhio Valley asabasisfor generating an optimal leasteffortsolutionfortwodifferent prehistoric situations:onewasforaLateWoodland hunter-gatherergroup, theotherfor aFortAncient agriculturalgroup.Comparison betweenthese optimal solutionsandactual archaeological dataonsubsistenceledhimto reject theleasteffort hypothesis basedontheobservationthatsome high costfoodswerefavoredovercertainlowcost foods,addingunnecessary costtosubsistence procurement. Keenecalculatedtwo optimaldietary solutionsfortheNetsilikEs kimo?oneofthesewasfor prerifletechnology, theotherfor postrifle technology. The prerifle solution requires theintensiveuseofsix major resourcesandmoremoderateuseofseveral others; the postrifle solutionin corporatesonly two major resources.These predictionscorrespondfairly wellwith empirical dataonNetsiliksubsistencebehavior. Asillustrated by these studies, one importantadvantage oflinear pro gramminganalysis ofsubsistence problems isthatit permits a comprehen sivetreatmentofdietbasedonasuiteof required nutrients (e.g.,protein, fats,vitamins,etc.) ratherthanthetraditionalrelianceoncaloriesalone (for an exception see Winters 1969).Thus, in Keene'sNetsilik study, cal ciumandhideswerethe limitingpayoff currencies.ThisleadsKeeneto argue thata modelbasedon energy(calories) alonewould seriously overes timate carryingcapacity forthe Netsilik.In Reidhead'sOhio Valleystudy, energy, ascorbic acid, and possibly calcium emerged as limiting currencies. Inthis case, the importance of energy asa major limitation suggests thata modelbasedoncaloriesalone might sufficeasanestimatorof carrying capacity. Itbears mentioningthat, forvarioustechnicaland practical reasons, linear programming hastwobasicdefectsthat complicate its application. Oneisthatit assumesthat per unitcostand payoff areconstantfora given activity, sothatthereis a straight linear relationship between intensity,cost, and payoff. In manycircumstances,however, thecost per unitofanactiv ity willincreasewith increasingintensity, that is, the activity becomesmore costly asits intensity increases.Atthesame time,payoffs willoftende creasewithincreased intensity ofan activity(diminishingreturns),again making the activity more costly. This problem,however, canbeovercome bytreating theone activity asifit weretwoor more activities, oneatlowin tensity with relativelyhighpayoffs andlow costs, theothersat higher inten EXPLANATORY/PREDICTIVE MODELSOFHUNTER-GATHERERADAPTATION 221 sities, withlower payoffs and higher costs.The programming solution wouldthenindicatethe point atwhichthe activity wouldceasetobe economical. Thesecond problem isthatlinear programming solutionsdonotconsider risk, adefectnotso easily evaded.Keene (1979) treatsriskasacosttobe addedtothetotalcostof exploiting aresource.Thisdoesnotseem entirely satisfactory asit wouldseemadvisableto keep costsand payoffsdirectly associatedwithresourcetransactions separate fromthoseassociatedwith risks.The reasoning hereisthatthese represententirely differentkindsof "cost"thatare likely tobe brought intoconsiderationat entirely different levelsinthesubsistence decision-makingprocess. Intheabsenceofabetter solution, at present aboutthebestthatcanbedoneinthis regard isto develop someother meansfor determining therisksassociatedwithdif ferentactivitiesandto incorporate theseasmaximallimitsonactivities whereriskis likely tobe important. Discussion In spite oftheirsubstantialtechnical differences, thefour general sub sistencemodelsoutlinedaboveshareonecommon feature, this being that they accountforsubsistencebehaviorintermsofoneormore simpleprin ciples that weigh therelativecostsand payoffs ofdifferenteconomic choicesasabasisfor adaptive solutions.Astheoretical constructs, there fore, the principaldifficulty intheiruseliesin how they aretobe applied to specific situations.In particular, itisclearthatthesefourmodelsarevalid as predictive devices only incaseswhereall potential subsistence options are knownandtheir expectedpayoffs canbe quantified moreorless exactly; they becomelessreliablein direct proportion tothe degree to whichthisas sumption isviolated.The implications ofthis veryimportantqualification areconsideredmore fully inalatersection. Apart fromthisbroad similarityamong thefour models, Jochim's goal satisfactionmodelandthe gametheory modelstandoutas beingbasically differentfromtheothers.The goal satisfactionmodelis unique becauseit assumesthatall potential subsistenceactivitieswillbeincludedinan adap tive solution, whiletheothermodels permit someactivitiestobeexcludedif theirrisksorcostaretoo high.Similarly, the gametheory modelis unique becauseitconsiderstheeffectsofdifferentialsubsistence payoffs under varyingconditions, whiletheothermodelstreat payoffsonly as long term values (linearprogramming alsoofferssome capabilities inthis regard: See Reidhead 1979). Atthis point, no single modelhasdemonstratedclear superiority overtheothers.Oneobviousavenueforfuture research, thereforewillbetotesttheir comparativepredictive successoverawide 222ROBERTLBETTINGER range ofsituationsin muchthesame way that biologists have investigated foraging modelsinrecent years(Pyke,Pulliam, andCharnov 1977). It seems quitepossible,however, thatthisresearchwillshownoone modelto be universallysuperior andratherthattheirrelativemerit depends onhow closely their assumptionsapproximate a particular subsistencesituationor canbereconciledtothe quality ofdataavailablefor analysis. MODELS OFSETTLEMENTLOCATION ANDTERRITORIALLY Probably astheresultofthe growing interestin regionalanalysis inar chaeology asawhole (cf. Johnson 1977; Smith 1976; HodderandOrton 1976), recent investigations ofsettlementlocationhavetendedto emphasize the importance of viewing thedeterminantsofsite placement intermsofthe broadsubsistenceareacommandedfroma givenpoint ratherthaninterms ofthedistinctivecharacteristicsofthe point itself (for a summary ofbasic locationalmodelssee Crumley1979). The signaldevelopment hereisthe site-catchment concept(seeabove; Vita-Finziand Higgs1970;Roper1979), whichdominatescurrentstudiesof prehistoric siteuse (e.g., O'Connelland Hayward1972;Sturdy1975).Unfortunately,although therehavebeenat tempts todevise generalprinciples forusein conjunction withcatchment analysis(Jarman1972), the technique continuestobe largely adevicefor describing or inferring economicbehavioroncea sitelocationis known, ratherthanfor predicting thesitelocationitself.Onthe whole, in fact, predictive modelsofsettlementlocationhavebeenless frequentlyattempted thansubsistence models?probably becausefor hunter-gatherers thedeter minantsofsitelocation are stronglydependent onsubsistence adaptation so thata trulygeneralpredictive modeloflocationmustbe accompaniedby a predictive modelofsubsistencebehavior.Inthis sense, the onlytruly com prehensive modelisthe gravity model proposedby Jochim (1976). Never theless, twootherlocationalmodels?aneconomicdecisionmodeldevel opedby Wood (1978) anda polythetic model developedby Williams, Thomas, and Bettinger(1973)?provide alternative approaches tothe prob lemand may beusefulinfuturestudies.Eachofthesethreemodelsis discussed separately below. The Gravity Model InJochim's gravitymodel, whichis closelypatterned aftermodelsusedin geography(Crumley1979), sitelocationis heldtobetheresultofthecom binedattractionsbetweenasocial group anditsindividualsubsistence EXPLANATORY/PREDICTIVE MODELSOFHUNTER-GATHERERADAPTATION 223 resources?themore important the resource, the greater itsattraction.The precise natureofthisattractionis derivedfromthe generalgravity formula tion/ = MiM2/R2 whereJissomeunitof interaction,Mi and M2 arethe twomasses interacting(in this case, one being theresource mass, theother the populationmass), andRisthedistancebetweenthetwo masses.Jochim takesJtobethe proportional useofa given resource (p) multipliedby a constant (k), so / = kp. Hefurther proposes thatfor anyparticulargroup the massofthe population is aconstant (K) andthe massoftheresourcein question is equal towna (thesesymbolsbeing thesameasin hissubsistence modelasdiscussed earlier).Dropping theconstantsand solving fordistance thisleadsto R2 = wna/p.Hence, sitelocationis predictedbyknowing the physical characteristicsand proportional useofeachsubsistenceresource andthen adjusting sitelocationsothatthedistancetoeachisin keeping withthevalues givenby theaboveformula. Giventhis model, Jochim explores theeffectsofdifferentresource characteristicsonsitelocationandfinds that,ceterusparibus, sitelocations willbeclosertolessmobile resources, moredense resources, andless clustered resources, these propositionsbeing similartotheconclusionsof Horn (1968) and Wilmsen (1973). Atthesame time,however, heconcludes thatresource weight haslittleeffectonsite location, whichisincontrast to foraging modelsin biology which propose thatasdistanceincreases minimum prey sizeincreases and, atalesser rate, maximumsizedecreases (Schoener1971); theirrelevanceof weight inJochim's scheme,however, is tracedtothe appearance of weight in boththenumeratoranddenominator (i.e., inthe proportional use value) ofhisdistance equation, anditis unclearwhetherthe foraging modelsconsiderthissimultaneouseffectof weight. In passing, I would point outthatit might insomecasesbeusefulnotto treat population massas constant, butrather adjust itintermsofthesizeof thework groupactuallyexploiting theresourcein question; at least, this wouldbemorein keeping withthe generalgravity