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Analyzing Adaptive Strategies: Human BehavioralEcology at Twenty-FiveBRUCE WINTERHALDER AND ERIC ALDEN SMITH

INTRODUCTION

Human behavioral ecology (HBE)began in the mid-1970s with the ap-plication of optimal foraging modelsto hunter-gatherer decisions concern-ing resource selection and land use. Inthe 25 years since, the field has devel-oped and successfully adapted evolu-tionary ecology theory and methodsto a wide range of topics important toarchaeology and to anthropology gen-erally. In this review we examine thebasic theory and its extensions to chil-dren’s foraging, conservation biology,demographic transitions, domestica-tion and agricultural origins, the evo-lution of menopause, field processingand central place foraging, life his-tory, male-female division of labor,mating tactics and fertility decisions,and resource intensification. Work onresource acquisition continues, buthas been extended from foragers topastoral and agricultural productionsystems. Studies of resource distribu-tion, and especially intragroup pro-

cesses of resource competition andtransfers, now supplement and enrichthose of resource production. Demo-graphic and life history analyses havebegun to show how ecological factorsof production and distribution relateto those of mortality, fertility, and lifecourse.

Besides providing a comprehensiveview of the field, we hope to demon-strate that HBE has established itselfas a progressive research tradition,1 aquestion we take up in our conclu-sion. We note that this review supple-ments others. Two edited collectionssummarized the state of HBE in theearly 1980s2 and early 1990s;3 shorterreviews have appeared as well.4–6 Apending collection carries us to thelate 1990s.7 Reviews of HBE general-ly,8,9 as well as life history and demog-raphy,10–12 maturation,13 primate lifespan and litter size,14 mating strate-gies,15,16 reproductive ecology,17,18 re-source transfers,19 resource conserva-tion,20 and division of labor21 haveappeared previously in this Journal.

Evolutionary ecology studies “evo-lution and adaptive design in ecologi-cal context.”22 As a distinct field, evo-lutionary ecology emerged in the1960s with the work of Charnov andOrians,23 Hutchinson,24,25 Lack,26

MacArthur and Pianka,27 MacArthurand Levins,28 MacArthur,29 Ori-ans,30,31 and others. Textbooks on evo-lutionary ecology appeared in the1970s, covering topics from the struc-tural and behavioral traits of organ-isms to the organization of ecologicalcommunities. Evolutionary ecologyshares fuzzy boundaries with evolu-tionary genetics, community ecology,animal behavior, and decision theory.When applied to the analysis of behav-ior, evolutionary ecology is conven-

tionally termed “behavioral ecology.”Behavioral analyses have been an in-tegral element of evolutionary ecologyfrom the beginning, treating topicssuch as foraging strategies,27 matingsystems,30 and spatial organizationand competition.32 The first textbookson behavioral ecology appeared inlate 1970s33 and early 1980s.34 Therenow is a voluminous literature, in-cluding monograph series, dedicatedjournals (e.g., Evolutionary Ecology,and Behavioral Ecology and Sociobiol-ogy), and a widely read, state-of-the-art series of volumes,35–38 each editionwith a new set of papers.

Human behavioral ecology appliesevolutionary ecology models and con-cepts to the study of human behav-ioral diversity. HBE began in the mid-1970s with a small set of interpretivepapers39–41 and independent disserta-tion projects. Initially centered on for-aging theory and hunter-gathererstudies, HBE has expanded over thelast 25 years to encompass diversetopics and subsistence systems (Fig.1). Although a second generation ofHBE researchers is now in academicpositions, the field is young enoughthat its initiators remain the majorityof those publishing in it.

HBE’s early goals were to set thecultural ecology of Steward,42 partic-ularly as developed in his hunter-gath-erer work43 and as represented in laterstudies such as those by Lee,44 on asounder theoretical footing by allyingit to emerging, neo-Darwinian ap-proaches to behavior. From the start,the proposed alliance was a somewhatwary and selective one. To varying de-grees, there were attempts to distancethis anthropological effort (some-times termed “socioecology”2) fromthe sociobiology of Wilson,45 and

Bruce Winterhalder is Professor of Anthro-pology and Chair of the Curriculum in Ecol-ogy at University of North Carolina, ChapelHill. He currently is working on a book-length analysis of the microecologicalbases of the hunter-gatherer mode of pro-duction. E-mail: [email protected] Alden Smith is Professor of Anthro-pology and Director of the Graduate Pro-gram in Environmental Anthropology atUniversity of Washington, Seattle. He iscurrently engaged in studies of marineforaging, reproductive strategies, and so-cial status among Torres Strait Islandersin collaboration with Rebecca BliegeBird and Douglas W. Bird. E-mail:[email protected]

Key words: behavioral ecology; foraging strate-gies; human adaptation; human evolution; hu-man life history; reproductive strategies

Evolutionary Anthropology 51

more recently from the approachknown as evolutionary psychology(see Box 1).

THEORY AND METHOD IN HBE

HBE is an anomaly within sociocul-tural anthropology due to its hypo-thetico-deductive research strategyand its neo-Darwinian theoretical

sources. HBE derives testable hypoth-eses from mathematical or graphicalmodels anchored in basic principlesof evolution by natural selection. Em-phasizing generality, most HBE mod-els strive to be as simple as possible.They seek to capture the essential fea-tures of an adaptive problem, and ne-glect to some degree the myriad ancil-lary variables of concern in the more

particularist tradition of anthropolo-gy.70 HBE assumes that complex so-cioecological phenomenon are mostfruitfully studied in a reductionistrather than holistic fashion.

However, the methods of HBE andanthropology overlap in a commonconcern with ethnography: the ex-tended recording of behavioral obser-vations in their immediate socioenvi-ronmental context, often in smallcommunities in remote and materi-ally impoverished conditions, supple-mented with data collected by survey,interview, or archival research. Herethe uncluttered predictions of simplemodels meet the messy reality of field-work and participant observation. Al-

though HBE is more committed toquantitative methods that reliablydocument observable behavior than issociocultural anthropology generally,it is rare that key variables can becontrolled, samples randomized, orreplication achieved. HBE research-ers share field methods with their so-ciocultural colleagues, but within atheoretical and epistemologicalframework that is alien to that field.

A complete HBE explanation com-bines models of circumstance andmodels of mechanism.71 Models of cir-cumstance ask, “How do socioenvi-ronmental factors shape the costs and

Figure 1. A tabulation ofHBE publications, by topicand decade. The topicaldivisions correspond tosections of this article, with“Other” representing publi-cations that cross theseboundaries (e.g., reviewarticles) or do not fit neatlyin any of them. As indi-cated, the graph is dividedinto ethnographic, ar-chaeological, and com-bined tabulations. Thecount is based on a com-bination of the authors’personal bibliographic da-tabases, plus a survey ofselected journals and re-cent review articles (wethank Geoff Kushnick forbibliographic assistance).

HBE is an anomaly withinsocioculturalanthropology due to itshypothetico-deductiveresearch strategy and itsneo-Darwiniantheoretical sources. HBEderives testablehypotheses frommathematical orgraphical modelsanchored in basicprinciples of evolutionby natural selection.

52 Evolutionary Anthropology ARTICLES

Box 1. HBE Compared to Some Closely Related Fieldsa

Behavioral ecology Evolutionary psychology Dual inheritance theory

Explanatory focus Behavioral strategies Psychological mechanisms Cultural evolutionKey constraints Ecological, material Cognitive, genetic Structural, informationTemporal scale of

adaptive changeShort-term

(phenotypic)Long-term (genetic) Medium-term (cultural)

Expected currentadaptiveness

Highest Lowest Intermediate

Hypothesis generation Optimality and ESSmodels

Informal inference Population-level models

Primary hypothesis-testingmethods

Quantitativeethnographicobservation

Survey, laboratoryexperiment

Mathematical modelingand simulation

Favored topics Subsistence,reproductivestrategies

Mate choice, sex differences Cooperation,maladaptation

a Modified from Smith.46

HBE is only one of several distinct approaches to evolutionary analysis of human behavior that have developed inrecent years; other prominent ones include evolutionary psychology and dual inheritance theory. Here we offer a briefcomparison with these two fields.46–49

Evolutionary psychology (EP) aims to uncover the evolved “psychological mechanisms that underpin human . . . be-havior,” and “the selective forces that shaped those mechanisms”50 (see reviews51–54). EP posits that human behavioris guided by specialized cognitive modules rather than “general purpose” mechanisms that work across multiplebehavioral domains. It argues that these modules evolved in the EEA (environment of evolutionary adaptedness), andare designed to produce very specific outcomes that may no longer be adaptive in modern (post-paleolithic) environ-ments. Based on these assumptions, some evolutionary psychologists55–57 have actively criticized behavioral ecolo-gists for studying adaptive patterns in contemporary nonforaging contexts, and for measuring degree of adaptation viafitness outcomes or correlates.

Dual inheritance theory (DIT) views culture and genes as providing separate (but linked) systems of inheritance,variation, and hence evolutionary change.58–63 Most DIT practitioners posit that the spread of cultural information isaffected by multiple forces, including natural selection (differential fitness of culturally inherited variation), decision-making (based on genetically or culturally evolved preferences and constraints), and transmitter influence or promi-nence. They differ in the relative strengths or attention they give to these various forces.

In contrast to classical forms of cultural evolutionism64,65 and to evolutionary archaeology,66,67 DIT practitioners positthat cultural evolution is embedded in and constrained by genetically evolved psychological propensities. They oftenbuild these assumptions into explicit mathematical models. Since cultural inheritance differs from genetic inheritancein key ways (e.g., nonparental transmission, multiple transmission events over a lifetime), the evolutionary dynamics ofculture will also differ in important but analytically understandable ways. Hence, genetically nonadaptive culturalevolution is possible, and may be likely in hierarchical and modern bureaucratic societies. However, this divergence ofcultural and genetic evolution can cut both ways: several DIT theorists60,68,69 posit that mechanisms of cultural evolutionoften find ways of improving on adaptive outcomes compared to what can be achieved by ordinary genetic evolutionplus phenotypic adaptation.

Although EP, DIT, and HBE are often portrayed as competing alternatives, a case can be made for viewing them ascomplementary.46,48,49 Competition is fueled by different assumptions, analytical methods, and alliances with otherdisciplines, as well as by ordinary academic politics. Complementarity between the three styles is increasinglyrecognized, however, and can be fostered by taking advantage of differences in their methods of investigation (e.g.,observation vs. experiment), empirical foci (e.g., psychological vs. behavioral vs. cultural), selection of constraints(cognitive, ecological, informational), time scales of adaptation, and behavioral domains (see table, above). There arelimits to this complementarity, however. A behavior cannot simultaneously be the product of a genetically programmedcognitive algorithm that no longer produces adaptive results, a product of a culturally inherited meme that persistsbecause it has a high replication rate, and a product of phenotypic adaptation that is optimally geared to localenvironmental conditions. Nevertheless, these hypotheses could be simultaneously true for different behavioral do-mains or instances.46

ARTICLES Evolutionary Anthropology 53

benefits associated with potential al-ternatives in this behavioral catego-ry?” Models of mechanism require thatwe specify how natural selection, or avariant such as sexual or kin selection,will act on these costs and benefits. Bycombining these two elements, theHBE approach avoids some of theproblems associated with sociologicalfunctionalism.3 In particular, neo-Darwinism restricts the range ofunits, costs, and benefits that we ex-pect to have causal salience in evolu-tionary processes.

HBE usually frames the study ofadaptive design in terms of decisionrules72 or conditional strategies: “Incontext X, do a; in context Y, switch tob.” For example, the polygyny thresh-old model30,73 assumes that femalemate choice has evolved to follow thedecision rule, “If the bachelor suitorhas at least half the resources of analready-married suitor, accept his of-fer; otherwise, become the secondwife of the married suitor.” Behav-ioral variation arises as individualsmatch their conditional strategies totheir diverse socioenvironmental set-tings. More generally, HBE assumesthat the details of genetic, phyloge-netic, and cognitive mechanisms donot, to a first approximation, seriouslyconstrain human adaptive responsesto ecological variation.74

PRODUCTION: FORAGINGBEHAVIOR AND RESOURCE

SELECTION

Analyses of resource selection andharvesting behavior—“production” ineconomic terms—formed the greaterpart of the HBE literature through the1980s (see Fig. 1). This research drawsfrom “optimal foraging theory” (orOFT).75,76 Although OFT was initiallydeveloped by biologists, anthropolo-gists have made some original theo-retical contributions in recent years.77

OFT consists of a family of modelsaddressing resource selection, time al-location, and habitat movement or“patch choice.” By far the most popu-lar of these foraging models has beenthe diet breadth or prey-choice mod-el.78 We focus on this particularmodel to illustrate the logic of theHBE approach in general.

Prey Choice: An Example ofthe HBE Approach

As with all HBE models, the prey-choice model incorporates a goal (op-timize net acquisition rate), a currency(for measuring the relevant costs andbenefits), a set of constraints (charac-terizing the social and environmentalcontext), and a decision or alternativeset (the range of behavioral options tobe examined).

Different evolutionary goals may re-quire different optimization methods,and HBE analyses may draw on eitherdeterministic, stochastic, or dynamicoptimization, as well as on game-the-oretic analysis.79 The prey-choicemodel typically uses a deterministicoptimization approach, and it speci-fies which resource types can be har-vested most efficiently from amongthose available in a given locale. Prey-choice model predictions test our as-sumption that foragers have the goalof responding to changing environ-mental constraints with choices thatoptimize net yield.

Because it can be readily measuredand is quite general, the currency usedin the prey-choice model is usually thenet acquisition rate of energy. Net ac-quisition rate can be used when for-agers are time-limited (i.e., gain morefrom freeing time for other activitiesthan from harvesting additional re-sources), energy-limited (i.e., gainmore from additional units of harvestthan from reduced foraging time), orface foraging conditions that exposethem to hazard levels greater thanthose they experience when not forag-ing (e.g., predation, higher risk of in-jury, or climate stress).80–85 Thus, netacquisition rate may be importanteven if food energy is not strictly lim-iting (see Smith,81 contra Vayda andMcCay86).

The constraints of the prey-choicemodel include those endogenous tothe forager, such as the informationavailable, cognitive processing capac-ities, and technology, as well as exog-enous factors such as the distribution,density, and nutritional content of theavailable resources. In applying themodel, all constraints but one are con-sidered to be relatively fixed. The re-maining constraint becomes the inde-pendent variable that predicts choicesamong the decision set. For instance,

the independent variable might be theencounter rate with various resourcetypes. Other constraints (e.g., foragingtechnology, information processing)could take this role, depending ontheir rate and degree of change, andthe researcher’s interest.

The alternative set in the prey-choice model is the diet combinations(or breadth) achieved by stepwise ad-dition of resources which have beenranked by their pursuit and handlingprofitability (or 1, 1 1 2, 1 1 2 1 3,etc.). Diet breadth is said to expand asmore resources are added to the opti-mal set, i.e., those pursued on encoun-ter.

Given the universal and recurrentshort-term need for metabolic en-ergy, it is reasonable to assume thatforaging strategies that maximizethe net acquisition rate of energywhile foraging have higher fitness, atleast within broad limits. We shouldexpect selection to favor cognitivemechanisms (and culturally inher-ited rules of thumb) to produce be-haviors keyed to this goal. However,most optimal foraging models aregeneral enough that the currencycould be any rate measure of re-source value—protein capture, ma-terial need, monetary return, orprestige. Recent applications of theprey-choice model have examinedthe circumstances under which sex-ual selection might favor differentcurrencies for males and females(see Sexual Division of Labor, be-low).

Although we abbreviate their pre-sentation, it is important to keep inmind that all hypotheses or interpre-tations discussed in the balance of thispaper are derived from models con-structed of this same set of elements:an evolutionary goal, a currency, con-straints, and an alternative set.

Ethnographic Applicationsand Extensions of OFT

A small set of ethnographic analyseshave tested basic OFT models amonghunter-gatherers.87,88 These rangefrom primarily qualitative and heuris-tic applications to detailed, quantita-tive analyses of foraging deci-sions.89–92 Specific applicationsexplain shifts in subsistence patterns


over time, in response to such factorsas changes in technology,93,94 climaticfluctuations,95 the availability of im-ported substitutes (wheat flour) for re-sources with high handling costs

(grass seed harvesting among Austra-lian Aborigines),96 or hunting com-panions.97

Fieldwork application of OFT mod-els to several long-standing and some

novel research questions illustrateshow HBE has stimulated importantnew research (Box 2).

Children’s foraging

Children exhibit different levels offoraging effort and self-provisioningacross hunter-gatherer groups (Fig.2). The !Kung are low-effort foragerswhose children do almost no produc-tive work. Among the Hadza, evenyoung children provide substantialportions of their food needs in someseasons of the year. Using cost-benefitmeasures derived from OFT, BlurtonJones,101 Blurton Jones et al.,102 andHawkes et al.103 argued that these dif-ferences occur because Hadza coun-try periodically offers children higherreturns than their !Kung counter-parts, and Hadza children are lesslikely to get lost or be attacked bypredators.

The question of why children differfrom adults in their foraging choicesand net acquisition rate is currently amatter of debate. Working withHadza, Blurton Jones et al.104 suggestthat children select different re-sources because of their lesser upper-body strength, not because of limita-tions of cognition or experience. Incontrast, Kaplan et al.12 propose thathumans have evolved to specialize innutrient-dense resources that are dif-ficult for children to procure and pro-cess. Effective use of these resources,they argue, requires maturity, experi-ence, and lengthy skill acquisition.

Box 2. Leapfrogging From Prehistoric to Postmodern:Foraging for Information on the World Wide Web

Foraging theory has established a secure place in archaeological analysesof economic decisions in prehistoric societies. Much of the ethnographic useof these models has focused on the subsistence behavior of extant hunter-gatherers, pastoralists, or, less commonly, agriculturists (see Production:Foraging Behavior and Resource Selection). One can imagine applications inurbanized, industrial economies, although we know of few specific studies.For instance, taxi drivers act as predators seeking to optimize the benefit-to-cost ratio of encountering and “harvesting” their prey. Routinely, they mustdecide whether to actively search or to use a sit-and-wait, ambush tactic,when to leave a patch that is declining in its yield, etc. In an actual study,political scientists Gray and Lowery98 make a preliminary case that behavioralecology models of group formation can be used to examine competition andalliance formation among political groups lobbying state legislatures.

One of the more interesting recent applications leaps directly to the hunter-gatherers of the postmodern world: software engineers are using HBE theoryto analyze and optimize patterns of “information foraging” on the internet.Computer scientists Pirolli and Card99 argue that foraging theory models areapplicable to the analysis and design of effective information-gathering mech-anisms from the world wide web and other large-scale, patchy, informationaldatabases. In a similar analysis, library scientist Pamela Sandstrom100 sug-gests that foraging theory will be important for her field, as librarians seek tooptimize the search capacities of their patrons.

This presents us with one of those marvelous, time-transcending ironiesthat appeal to postmodernist sensibilities: information-seeking readers mayhave found this paper because their internet software or library referenceservices use HBE principles designed originally to understand the subsis-tence-seeking behavior of prehistoric hunter-gatherers.

Figure 2. Among Mikea forager-farmers ofsouthwestern Madagascar, children pro-vide for much of their own subsistenceneeds through tuber foraging. Wild tubersare the dietary basis for many Mikea house-holds, especially during years of agriculturalshortfall. The potential impact of self-provi-sioning by children on socioecological ad-aptations of hominids and contemporaryhunter-gatherers is an active area of HBEinquiry. Photograph courtesy of BramTucker.


Bird and Bliege Bird105 show that Me-riam children foraging for shellfish ontropical reef-tops quickly learn to pur-sue an optimal set of prey which,given their slower travel speeds andlesser strength, differs from the opti-mal set taken by adults in the sameenvironment. In this case, body sizerather than cognitive or experientialconstraints explain the differences be-tween adult and child foraging strate-gies. In some environments, childrenare able to forage quite effectively andmatch OFT predictions, even if theirdifferent capabilities require that theydiverge from the resources selectionof their parents.

Nonforager applications

Behavioral ecologists have now suc-cessfully applied optimality and selec-tionist logic to horticultural106,107 andpastoral108 production systems. Dy-namic optimization analysis has beenused to examine the cost-benefittrade-offs faced by pastoralist familiesdeciding between inexpensive, high-fertility but environmentally sensitivesmall stock, and expensive, low-fertil-ity but reliable large stock.109 Datafrom several East African societies(Somali, Twareg, Meidob, Turkana)fit the model predictions well.110,111

Because they manage the movementand feeding of their herds, pastoralistssuch as the Fulani can be analyzed asmaking foraging decisions on behalfof their domestic stock.112 Models ofpatch choice and optimal informa-tion-sharing have also been employedin an industrialized context, to helpexplain the behavior of Alaskan com-mercial fishermen.113

Conservation biology

Some writings portray indigenouspeoples as living in ecological har-mony with their environments andcarefully conserving resources againstoverexploitation. Others cite archaeo-logical examples of apparent anthro-pogenic extinction, and argue thatsustainability may be due more to lowpopulation densities, simple technolo-gies, or absence of markets than toecological restraint.114,115 This inter-pretive disagreement is partly an em-pirical problem—evidence is scant—and it is partly due to uncleardefinitions and ambiguous relation-

ships between observed behaviors andinferences. Sustainable harvests havebeen cited in favor of conservationwhen they may be incidental to goodhunting tactics or a consequence ofother constraints. For instance, rota-tion of hunting ranges has been citedboth as conservation behavior (tractsrecently hunted are allowed to “rest,”while more productive patches are be-ing exploited),116,117 and as a tactic tomaximize yields through optimalmovement among patches.82,93,118,119

Alvard20 and Hames120 use foragingtheory to address these issues (Fig. 3).Alvard20 defines as conservationistany resource use restraint that sacri-fices short-term yield and fitness gainsin order to realize long-term benefitsfrom heightened sustainability oryield. Because OFT models identifyprecisely the behaviors expected byshort-term optimization, they providethe null hypothesis against which con-servation can be assessed. The Piro

horticulturalist-foragers of lowlandPeru select prey species matching theprediction of shorter-term optimiza-tion models, irrespective of their vul-nerability to overexploitation and de-pletion.121 When moving throughdepleted zones near to villages in or-der to hunt in more favorable distantareas, Piro (Peru)122 and Yanomamoand Ye’kwana (Venezuela)120 foragersdo not forego opportunistic chancesto harvest individuals of valuable butoverexploited species. Piro do not se-lectively avoid the more productivesex-age classes in favor of those min-imizing impact on population sustain-ability.123 Further, as prey become de-pleted, tropical foragers increase thetime they spend hunting, oppositewhat would be predicted under theconservationist view.120,124

Some important modeling work hasexamined how population dynamics

and production strategies inter-act.125,126 For instance, simulation hasbeen used to show how the differentparameter values for population den-sity, foraging effort, and resource se-lection strategies of hunter-gatherersinteract with the sustainability andpopulation dynamics of the resourceon which they depend.127,128 For ex-ample, if a predator exploits two prof-itable species that differ in their in-trinsic rate of increase (“r”), the low“r” species of the pair is vulnerable todepletion and local extinction.

Three characteristics of resources—open access, high abundance relative toneed, and a reproductive potentiallower than evolved human discountrates129—may help to explain why gen-uine conservation of game appears tobe rare in indigenous societies.20 OFT

Figure 3. The Huaorani Indians of Ecuador’sAmazon forest use blowguns and dartstipped in curare poison to hunt monkeysand birds from the canopy. Access to fire-arms and markets has changed the dy-namic between indigenous hunters andtheir faunal prey in ways being investigatedby behavioral ecologists. At its best, thiswork integrates anthropology, evolutionaryecology, population ecology, and conser-vation biology. Photograph courtesy ofFlora Lu.

Behavioral ecologistshave now successfullyapplied optimality andselectionist logic tohorticultural andpastoral productionsystems.


allows us to isolate the costs and bene-fits that must be assessed in order toseparate incidental from genuine con-servation, in ethnographic130 and in ar-chaeological131,132 contexts. Combinedwith population ecology models, OFTprovides insights into the dynamic pro-cesses linking foraging decisions totheir impacts on resource popula-tions.128 Various social constraints (in-cluding inequalities in social power)may fundamentally alter the trade-offbetween efficiency and conservation.133

More generally, success in solving con-temporary environmental problemsmay require appreciation of ourevolved dispositions with respect to pat-terns of self-interest and temporal dis-counting in the use of resources.134–136

Sexual division of labor

Overall, ethnographic tests and in-terpretive applications of OFT modelshave been reasonably successful overa broad range of systems. But failuresof model predictions can be a stimu-lus to research as well. An example isthe ongoing debate over the male-fe-male division of labor in many forag-ing societies (Figs. 3, 4). In somegroups, men pursue resources (e.g.,large game) that yield a high variance,entail greater between-householdsharing, and have greater protein andfat content than the resources prefer-entially harvested by women. This di-morphism in foraging strategy may bedue to male-female complementarity

in household provisioning and macro-nutrient balance,137–139 or it may re-flect male status competition and mat-ing investment.21,140,141 The debateamong these alternatives (and inter-mediate possibilities) has been pro-tracted, and no clear resolution is insight (see below, Parenting-MatingStrategy Interactions).

Archaeological Applicationsand Extensions

Archaeological uses of OFT havebeen hampered by the fact that directtests of the models require data onindividual decisions, taken in behav-ioral time. In contrast, the recoverablearchaeological record consists of ma-terial remains that aggregate overmultiple foragers and foraging epi-sodes. The data only indirectly reflectbehavior and are further obscured byvarious taphonomic factors. However,there has been progress in revisingOFT predictions to fit the archaeolog-ical context.142 In addition, ethnoar-chaeological applications have beendevised to serve as a bridge betweenthe short time-frame of foraging mod-els and the extended time-frame ofprehistorians.143–145

Residential movement

Drawing on archaeological observa-tions from the Owens Valley,Zeanah146 (see also Kelly88) has devel-oped a central place foraging (CPF)

model that predicts when hunter-gatherers who travel from their resi-dence (A) to a distant site (B) to gatherresources logistically, should reversethe pattern and relocate to that sec-ond site, making logistic foragingtrips back to (A).

Field processing

Archaeologists also have adaptedCPF models to predict when resourceswill undergo field processing to re-move low utility portions prior totheir transport back to a camp.77,91,147

Transport of an unprocessed resourcetakes less handling time in the fieldand thus allows for more round trips,but some part of the carried load haslittle or no value. Field processing be-fore transport lessens the number ofround trips per unit time, but the loadis composed of high-value materialsonly. Given estimates of load capaci-ties, processing costs, and the utilitiesof high and low value portions,148 themodel predicts the travel distance atwhich field processing becomes thebest option. Separating nut meats orshellfish from their shells, edible ani-mal tissues from low utility skin, car-apace, and hooves, or high-gradestone tool material from low-qualitymatrix at a quarry are potential exam-ples. Similar analyses shed light onhow the distribution and compositionof prehistoric faunal remains will beshaped through selective processingand transport.149,150

Figure 4. Huaorani females in the lowlandtropical forests of northeastern Ecuador re-turn from the garden burdened withmanioc tubers and cuttings. Although themen assist in garden clearing and weed-ing, much of the horticultural work is doneby women, a typical division of labor.Quantitative, ethnographic studies of timeallocation have illuminated the work pat-terns and subsistence contributions of dif-ferent sex-age groups, e.g., the young fe-males pictured here, but a satisfactoryexplanation for male-female division of la-bor seen in foraging and forager-horticul-turalist societies has remained elusive. Pho-tograph courtesy of Flora Lu.


Intensification

According to the prey-choice model,as the forager’s encounter rate withhigh profitability resources declines,overall foraging efficiency falls andthe best-choice diet expands to en-compass previously neglected types oflower and lower profitability. Encoun-ter rates with the most desirable re-sources might decline due to a num-ber of reasons, including foragerpopulation growth and resource over-exploitation. Empirical studies ofhunter-gatherers stimulated by forag-ing theory have shown that low-ranked resources typically are diffi-cult-to-catch or difficult-to-processitems such as small game, nuts, andseeds.

Prehistorians have combined theseobservations on foraging logic, costs,and benefits, to give a new and morespecific purchase to an old idea: re-source intensification or, more specif-ically, the broad spectrum revolution.For instance, Broughton131,132 andBroughton and Grayson151 haveshown a remarkably consistent pat-tern through late Holocene archaeo-logical sites in northern California. Al-though the precise timing and thespecies set differ by site and environ-mental zone, in each case harvests ofhighly ranked species (e.g., sturgeon,elk, white-tailed deer) drop steadilyrelative to low-ranked species (e.g.,shellfish, acorns, small mammals).Other evidence (e.g., declining size ofthe species presumed to be subject toheavy exploitation; indicators of in-creasing human density) is consistentwith a hypothesis of resource deple-tion and diet breadth expansion. Al-ternative explanations for thesechanges—new technology, of climateor habitat change affecting resourcepopulation densities—can be re-jected. Whereas acorns once sug-gested the easy bounty of the Califor-nia environment, experimentalarchaeology studies coupled to OFTmodels suggest that acorn use marksthe latter stages of a long period ofdeclining production efficiency.152 Ina like study, Edwards andO’Connell153 use foraging theory toevaluate the plausibility of several hy-potheses for the relatively late appear-ance of “broad spectrum” seeds in the

diets of arid-zone Australian Aborigi-nes.

Stiner et al.154,155 use a similar OFTapproach in their study of humanpopulation growth and resource in-tensification in early Middle- to Up-per- and Epi-Paleolithic sites in Italyand Israel. Their analysis turns on theimplications of two categories ofsmall game. In one category are“slow,” easily caught and processed,high profitability species with low fer-tility and thus, low resistance to ex-ploitation. Tortoises and marine shell-fish are “slow.” The other categoryconsists of “fast,” more difficult tocatch, low profitability species withhigh fertility and thus high resistance

to exploitation. Partridges, hare, andrabbits are “fast.” In the sites exam-ined, “slow” species appear steadily inthe archaeofaunal record throughoutthe Middle Paleolithic but are increas-ingly supplanted in importance by“fast” species in the Upper and Epi-Paleolithic. The Middle-Paleolithicpattern is consistent with a mobile,low-density population of human for-agers, opportunistically harvestinghigh-value “slow” species without theexploitation intensity that wouldcause their extirpation. Increasing hu-man density and greater sedentism inthe Upper and Epi-Paleolithic are in-

terpreted from the diminishing sizeand apparent depletion of easily har-vested “slow” species and their re-placement in the foraging schedulewith low profitability, “fast” smallgame. Biotic communities were rela-tively stable through the examinedchanges in harvests, eliminating onealternative explanation for the pat-tern.

Given their life history variabilityand potential disparities in their rank-ing as resources, small game mayprove to be more sensitive indicatorsof basic changes in the prehistoric for-aging economy than are the largegame species that typically commandthe most archaeological attention.Stiner et al.154,155 paleoanthropoloicaloffer a too rare example of the poten-tial contribution of behavioral ecologymodels to interpretation.

Domestication and agriculturalorigins

Recent work shows that OFT maybe useful in understanding the condi-tions under which domestication andagricultural production might emergeand spread.156–159 The cost-benefittrade-offs recognized in OFT modelsunderwrite a set of hypotheses con-cerning the circumstances in whichprehistoric agriculturalists wouldadopt or domesticate new crops, andtheir impact on existing agro-ecologi-cal relationships in the prehistoricsoutheastern United States. For in-stance, maize remained a minor com-ponent of garden production for some600–1,000 years after its introductioninto the Midwest and Midsouth, but itquickly came to dominate productionafter its later arrival in the interiorSoutheast.160 The use of acorns de-clined relative to hickory nuts coinci-dent with the emergence of plant hus-bandry in upland regions of theCumberland Plateau, eastern Ken-tucky.161

GROUPS AND RESOURCETRANSFERS

Foraging models concern them-selves with the short-term productiondecisions of individuals. The inputvariables to these models are environ-mental factors such as the profitabil-ity, density, distribution, and re-

Given their life historyvariability and potentialdisparities in theirranking as resources,small game may proveto be more sensitiveindicators of basicchanges in theprehistoric foragingeconomy than are thelarge game species thattypically command themost archaeologicalattention.


sponse to exploitation of potentialresources. Foraging models are theonly models a Robinson Crusoe wouldneed. However, for humans in gen-eral, their hominid antecedents, andmany other species, the harvestand/or consumption of resourceslikely occurs in a group. Attention tothe resulting social interactions addsthe evolutionary dynamics of resourcedistribution to those of production.

Models

Group-based subsistence effortsmay offer several advantages: 1) in-creased per capita encounter rate withresources, 2) reduced variation in en-counter rates, 3) reduced losses tocompetitors, and 4) increased vigi-lance and predator detection.162

Nonetheless, modeling has shownthat optimal group size itself may beunstable due to conflicts of interestbetween existing members and poten-tial joiners.163,164 Once groups exist,they provide the context for complexsocial dynamics, including competi-tion and conflict.165 Here we focus onresource transfers, which are funda-mental to these social dynamics andare well-studied in HBE.

Hand-to-mouth feeding provides noincentives to food transfers beyondprovisioning of related infants and ju-veniles until they are competent as in-dependent foragers. However, the sit-uation is different if group membersharvest one or more of their resourcesas a divisible “packet,” a unit largeenough that it cannot be consumedimmediately by the individual holdingit. The technical equivalent of thiscondition is that the value of thepacket is subject to short-term, dimin-ishing marginal returns to the individ-ual possessing it.166 This virtuallyguarantees that portions of the packetwill be valued differently by differentgroup members. Given this model ofcircumstance, a variety of evolution-ary mechanisms may come intoplay.71

All resource transfer models ad-dress a common causal circumstance,the unsynchronized acquisition ofvaluable resource packets by individ-uals within a group. The models differprimarily in their structural refine-ments (e.g., to what extent are thegroup members genetically related, or

in an ongoing social relationship?What cost-benefit constraints arepresent? What is the nature of the re-source?), and in the evolutionarymechanism they apply (e.g., individ-ual, inclusive, sexual, or group selec-tion). Simple individual-level selec-tion will generate transfer byscrounging167 (also known as toleratedtheft168) when those not possessing aresource packet benefit more by tak-ing portions than the holder can ben-efit by defending them. Resource shar-ing eliminates the involuntaryelement of coercion, replacing it withthe delayed, cost-benefit calculus ofreciprocal altruism.169 In by-productmutualism170 the individual discover-ing or possessing a resource obtains anet gain as a result of others partici-pating in its capture, defense, or con-sumption. In this case, short-term co-operation is mutually beneficial, anddefection or cheating, so important toreciprocal altruism, is not an issue.

Costly signaling,171–173 a form of by-product mutualism, is another poten-tial mechanism for resource trans-fers.174 By successfully harvesting andthen distributing difficult or danger-ous-to-capture resources, individualsreliably signal their prowess, benefit-ing themselves as well as participantswho gain both food and useful infor-mation.141 In trade or exchange,175 in-dividuals swap unlike resources orservices because both, by marginalistlogic, stand to gain by doing so. Theshow-off hypothesis176 is a transfermodel built on the mechanism of sex-ual selection. Male hunters target highvalue, high-variance resources, de-spite unfavorable average returns andlosses to group-wide sharing, becausethey are able to translate the resulting“social attention” into other benefitssuch as enhanced mating opportuni-ties. Finally, inclusive fitness selectionshould lead to transfers through kin-provisioning that balances costs andbenefits against degrees of related-ness. If individuals produce signifi-cant parts of their diet unpredictably,risk minimization is among the impor-tant benefits of resource trans-fers.177,178

Ethnographic Studies

There are several empirical studiesassessing the relative importance of one

or more of the proposed resource trans-fer hypotheses. Those that exist divergeon which mechanism appears to becausally dominant: scrounging and theshow-off hypothesis,179 trade,175,180 kin-provisioning,181 reciprocity-based risk-minimization,182,183 and costly signal-ing.141 Collectively, these studies leavethe impression that transfer behaviorsare much more diverse and situation-ally specific than has been appreciatedin the standard ethnographic literatureon “sharing.” These studies also suggestthat transfer behaviors are probablymulticausal in their origin, the result ofseveral selective pressures acting con-currently, their relative causal impor-tance depending on the situation. Laborexchange has been less studied, butmay show comparable diversity offorms and the same range of causal in-fluences.184–186

Archaeological/PrehistoricStudies

Provisioning by grandmothers

In conventional wisdom, the fea-tures by which Homo erectus is be-lieved to anticipate later hominids—male-female division of labor, lengthyjuvenile dependence, nuclear families,and central place foraging—devel-oped from a pattern in which malesprovisioned their offspring throughlarge-game hunting (viz., the huntinghypothesis). O’Connell et al.187 ques-tion this scenario and present an al-ternative, the grandmother hypothesis.In their model, the development ofmore arid and seasonal environmentsfollowing 1.8–1.7 million years ago re-duced the capacity of juveniles to pro-vision themselves with easily gatheredfruits, as occurs in most primate spe-cies and some hunter-gatherers. Thisput pressure on their caretakingmothers, who turned to a low-rankedfood source which was plentiful andgeographically widespread, but whichdemands adult skill and strength toharvest and process: tubers. Thegrowing demands of provisioningtheir developing offspring with tuberssharply constrained adult femalebirth intervals and consequently theirfertility. According to the grand-mother hypothesis, this constraintprovided an opportunity for selection:aging female relatives of these moth-


ers could offset declines in their ownfitness by stepping in to provisiontheir grandchildren, especially the off-spring of their daughters. Compara-tive life history studies of existing ver-tebrates188 suggest that a variety offeatures might have followed: reducedjuvenile mortality, delay to age of ma-turity, larger size, shortened birth in-tervals (higher fertility), and largergroup size. This also makes grand-mothering a leading evolutionary hy-pothesis for the extended, postmeno-pausal female life span ofhominids,189–192 which would evolveand be maintained by natural selec-tion if women near the end of their lifespan gain inclusive fitness by invest-ing in their grandchildren (or otherclose relatives still in or before theirreproductive prime).

If correct, the grandmother hypoth-esis shows that neither big-gamehunting nor male feeding of a femaleand her children is required to explainkey features of hominid emergence.The hypothesis combines foragingtheory observations on the gatheringtactics of Hadza mothers and theirchildren193,194 and life history pat-terns suggested by comparative stud-ies and the models of Charnov andBerrigan.14 The precise form andplausibility of the hypothesis dependsubstantially on research stimulatedby HBE.

Transfers and the exploitationof large game

Paleoanthropologists195 sometimesargue that it was the active hunting ofbig game that provided the opportu-nity and incentive for food sharing. Inthis view, big game were a resourcemade available to hominids by tech-nological or cognitive advances late inour evolutionary history. However, agood HBE case can be made for thereverse: only with the evolution of rec-iprocity or exchange-based foodtransfers did it become economicalfor individual hunters to target largegame. The effective value of a largemammal to a lone forager—whatcould be eaten and converted directlyto inclusive fitness on the short term—probably was not great enough to jus-tify the cost of attempting to pursueand capture it, even if unrelated groupmembers benefited through tolerated

theft. However, once effective systemsof reciprocity or exchange augmentthe effective value of very large pack-ets to the hunter, such prey itemswould be more likely to enter the op-timal diet.

Given social foraging and harvest oflarge-packet resources, both of whichare archaeologically visible, the vari-ety of evolutionary mechanisms thatcan generate intragroup transfers sug-gests that they will be both common-place, and diverse in form and func-tion, among our hominid ancestors.Comparative ethological and ethno-graphic evidence is consistent withthis prediction.196 Resource transfermodels also expand our sense of ap-propriate currencies beyond kilocalo-ries, perhaps modifying optimal re-source selection. Some prey typesmay be valued precisely because they

are dangerous, rare, and costly to ob-tain,141 e.g., the albino deerskins, redwoodpecker scalps, and giant obsid-ian blades displayed in certain NativeCalifornian ceremonies.197 Intragroupresource transfer models give HBEanalytical linkages between the origi-nal production focus of OFT and thedynamic social realm of resource dis-tribution.

REPRODUCTION: MATING,PARENTING, AND LIFE HISTORY

STRATEGIES

While classical sociobiology198,199

analyzed reproductive behavior interms of factors inherent in sexualreproduction, such as genetic relat-edness and gamete asymmetry, HBE

analyses focus on variation in repro-ductive behavior as a function of lo-cal ecological context. And in con-trast to evolutionary psychology,200

HBE posits that this variation in-volves phenotypic tracking of cur-rent circumstances, rather than theplayback of species-, sex-, or age-specific behavioral routines thatwere adaptive in our remote evolu-tionary history (see Box 1).201,202

Nevertheless, HBE approaches over-lap considerably with these othertwo traditions and with certain ver-sions of cultural evolution, as well aswith less explicitly neo-Darwinianfields such as demography203 and re-productive ecology.204

HBE analyses of reproductive be-havior can be divided into three broadareas: mating, parenting, and life his-tory.205–207

Mating Strategies

The distribution of key resourcesstrongly shapes the distribution ofmales and females, generally throughdifferent routes.208,209 If some malescan monopolize resources necessaryfor female survival and reproduction,they can use this control to attractmates, or to compete with other malesfor social dominance. Polygyny andincreased variance in male matingsuccess will result. Male resource con-trol coupled with female-initiatedmate choice is the basis for the “po-lygyny threshold” model30 referred toearlier. The outcome predicted by thesimplest versions of this model is anideal free distribution,210 in which thenumber of mates per male will matchthe resources each can offer, and fe-male fitness will be equal across mate-ships.

Despite its simplifying assump-tions, tests of the polygyny thresholdmodel have generally supported itsapplicability to human mating sys-tems.73,211–218 The male-controlled re-sources may be political rather thaneconomic.219 Male coercion (especiallyby agnatic kin groups) may severelyconstrain female choice.220 Femalesmated polygynously may face reducedreproductive success due to competi-tion with co-wives.221,222 The effects ofco-wife competition may be compen-sated, however, if the sons of polygy-nously married women have in-

If correct, thegrandmother hypothesisshows that neither big-game hunting nor malefeeding of a female andher children is requiredto explain key featuresof hominid emergence.


creased chances of inheriting wealthand mating polygynously them-selves.223

Polygyny has been the preferredmarriage form for the great majorityof societies in the ethnographicrecord.208 Even in putatively monoga-mous societies, extramarital matingand remarriage biased towardswealthier or more powerful males cre-ates a situation of effective polygy-ny.218 Human behavioral ecologistshave also analyzed the rare but in-triguing polyandrous case,60,202,224–226

as well as monogamous sys-tems,138,227,228 especially those involv-ing stratification and dowry.229–232

Recent work is particularly concernedwith analyzing the trade-offs betweenparental investment (see below) andmating effort, as noted above (SexualDivision of Labor).

Ethnoarchaeologists are just be-ginning to make use of HBE ap-proaches to reproduction. For in-stance, the mating tactics of hunter-gatherer males may lead to mobilityand ranging patterns different fromthose optimal for reliably securingresources.233

Parenting

Whatever the mating system, hu-man offspring require extensive andextended parental care. This parentalinvestment234 begins with the moth-er’s resource allocations during gesta-tion. HBE analyses ask how the tim-ing and amount of such investmentmight vary according to social and en-vironmental constraints. Most re-search falls into three categories:birth-spacing, differential investmentin offspring (by sex or expected repro-ductive value), and interactions be-tween mating and parenting.

Birth spacing

If parental time and resources arefinite, a shorter interbirth intervalshould result in less parental invest-ment per offspring and may eventu-ally reduce each offspring’s fitness.This is the basis of the optimal clutch-size model (Fig. 5a) of Lack.26 It pre-dicts that beyond a certain point, in-creased fertility (larger clutches, orshorter interbirth intervals) will resultin lowered overall parental reproduc-

tive success. Blurton Jones andSibly236 use this approach and data on!Kung San work effort and demogra-phy235 to show that interbirth inter-vals much shorter than the actualmode of 4 years resulted in increasedoffspring mortality, sufficient to causea net loss in expected reproductivesuccess.236 This effect did not occurfor a mother’s first interval, nor whenbirth followed the death of the preced-ing offspring; in these cases, inter-birth intervals were significantlyshorter (as the model predicted).237,238

At least one careful attempt to rep-licate the !Kung results among Acheforagers239 failed, possibly becauseoffspring mortality is more sensitiveto variation in interbirth interval inthe !Kung setting. It has also been ar-gued that the !Kung results are spuri-ous, with the long interbirth intervalsa result of female infertility due tosexually transmitted disease,240,241 anargument rebutted by BlurtonJones.242 Finally, it may be that in theAche case (and likely many others),the relationship between fertility andoffspring survival is confounded byphenotypic correlation, which gener-ally will mask the predicted functionalrelationship of the Lack mod-el,206,239,243 as illustrated in Figure 5b.

Phenotypic correlation occurs whenhidden heterogeneity in uncontrolledvariables confounds the effect of thecausal variable under investigation.For example, wealthy individualsmight tend to have more expensivehouses and more expensive cars (aphenotypic correlation), even thoughwe have good reason to expect a neg-ative correlation between investmentin houses and investment in cars dueto the fact that the same dollars can-not be spent on both.244 While thelogic of phenotypic correlation isstraightforward, uncovering hiddenheterogeneity and controlling for itseffects in nonexperimental studieslike those undertaken by HBE (andother fields studying human behaviorin naturalistic settings) are difficult. Ifselection has designed the reproduc-tive system to adjust facultatively tosituational constraints, then inter-birth intervals will be short when theparent’s resources are relatively abun-dant and long when their condition ispoor. The modal measures typically

available to us obscure this in-trasample variability. There is abun-dant evidence for such adaptive vari-ability in human reproductiveecology.203,204 One possible solution,multivariate analysis, requires largersamples than anthropologists are usu-ally able to generate. Another is to usehistorical data on individual familieswithin the sample to track functionallinks between birth spacing and re-sources, but this is obviously not anoption if the requisite time series islacking.

Differential investment

Parental investment throughout achild’s development affects thatchild’s health, survival, and futuremating success, and thus the parents’inclusive fitness. Parental fitness pay-offs depend on three sets of variables:1) the genealogical relatedness be-tween parent (or other caregiver) andoffspring, 2) the effect of investmenton the expected reproductive value ofthe offspring (as well as present andfuture siblings), and 3) the effect ofinvestment on the caregiver’s own re-productive value. Set (1) is indirectlysubject to ecological variation (e.g.,patterns of coresidence will affectthe likelihood that a social parent orother caregiver is a close genetic rela-tive), while sets (2) and (3) are moredirectly affected by ecological vari-ables, and hence at the center of HBEanalyses.

Postpartum parental investment de-cisions range chronologically fromwhether or not to keep the child—thealternatives being infanticide, aban-donment, and adopting out—to dele-gation of care to others, generally ei-ther relatives or hired laborers such aswet nurses, to the legacy the child mayreceive prior to or upon death of theparents. Fitness payoffs for nearly allof these decisions may differ accord-ing to sex of offspring. The Trivers-Willard245 prediction that parents inpoor condition or with limited re-sources will invest more heavily in off-spring with the lowest expected vari-ance in reproductive success (usuallydaughters) has received HBE atten-tion, as have a variety of other hypoth-eses (Box 3).


Parenting-mating strategyinteractions

Following the lead of primate andavian behavioral ecology, HBE re-searchers have begun to consider if

paternal care and resource provision-ing, rather than simply being forms ofparental investment, may be designedto attract or maintain a relationshipwith a mate (Fig. 6).21,138,276–278 Forexample, Albuquerque men as well as

Xhosa men in South Africa investmore time and resources in stepchil-dren who are offspring of their cur-rent mates than they do in stepchil-dren from former relationships(though less than they invest in ge-

Figure 5. A graphical model of optimal fer-tility rate, based on Lack.26 Solid diagonallines represent births per unit time, whiledashed curves represent mortality as an in-creasing function of fertility rate. The netdifference between fertility and mortality isthe number of surviving offspring, with arepresenting the maximum value this cantake for a given pair of fertility/mortalitycurves. The graph assumes that selectionfavors maximum values of a, given the con-straints a parent faces, and hence an op-timal fertility rate Fo. a: A single parent isconsidered. b: Parents with different re-source or phenotypic endowments havedistinct offspring mortality curves as a func-tion of fertility rate. Thus a “poor” parentfaces higher offspring mortality at a givenlevel of fertility, and hence a lower optimalfertility rate Fp than a higher-quality parentwith optimal fertility rate Fh. If analyses offertility and mortality do not control for thisheterogeneity, the lumped data maymake it seem that fertility rate and offspringmortality are negatively correlated. The re-sult is that the pattern of fertility optimiza-tion may be masked by phenotypic corre-lation (see text), and the prediction ofpositive correlation will be rejected eventhough correct.


netic offspring under comparable cir-cumstances).247,248 This pattern is notadaptive as parental investment perse, but does make adaptive sense ifone views it as investment in main-taining a current mating relationship(i.e., as mating effort). Unraveling in-teractions such as these is a promisingarea for future HBE research, but willrequire a great deal more theoreticaland empirical effort.

Life History Strategies

Life history theory is concernedwith the evolution of maturationrates, reproductive rates and timing,

dispersal patterns, mortality patterns,and senescence. Most HBE work onlife history thus far has focused onthree topics: 1) links between produc-tion and reproduction, 2) reproduc-tive effort and maturation, and 3) evo-lutionary explanation of the so-calleddemographic transition.

The grandmother hypothesis (de-scribed above) and related proposalstake up the issue of reproductive ef-fort and maturation, particularly thepossible evolutionary causes and con-sequences of menopause. Perhaps themost impressive work to date is thatby Hill and Hurtado,239 who devel-oped a model of reproductive timing

based on Charnov279 that successfullypredicts variation in age of reproduc-tive maturation of women in three dif-ferent populations: Ache, !Kung, andNorth America. Analyzing data fromcontemporary Chicago broken downby residential neighborhoods, Wilsonand Daly280 show how life historyvariables such as life expectancy andreproductive timing respond to varia-tion in social and ecological factorssuch as economic opportunity and ho-micide rates (Box 4).

Demographic transition

“Demographic transition” can referto any dramatic and sustained change

Box 3. Selected HBE Tests of Parental Investment Theory

The evolutionary analysis of parental investment neednot include a direct focus on ecological factors. However,HBE studies generally examine the ways in which ecolog-ical constraints shape the fitness-related costs and bene-fits of various alternative patterns of parental care, which inturn leads to predictions concerning variation in parentalinvestment decisions. These constraints can include a va-riety of economic, demographic, political, and mating

prospects for offspring that may vary by their sex or phe-notypic condition, as well as by the social status andrelationships of the parents. Some of the primary HBEpredictions about parental investment are listed below,along with a representative sample of empirical studiesthat attempt to test these predictions. Not all studies listedbelow necessarily support the prediction under test.

Predictiona Representative studies

Reduced genetic relatedness or reproductive conflicts of interestlead to lower PI

Daly and Wilson;246 Anderson et al.;247,248

Strassman249

Offspring with reduced prospects of survival receive lower PI Daly and Wilson250

Parents reduce PI per offspring as number of offspring increases Borgerhoff Mulder;251 Hill and Hurtado239

PI per child is increased when marginal benefit of PI is higher Bereczkei;252 Kaplan et al.253

Adoption and fostering are adaptively modulated according toparental circumstances

Silk;254 Pennington255

Mothers able to delegate nursing and infant care gainincreased reproductive success

Bereczkei;256 Blaffer Hrdy;257 Turke258

Postmenopausal women allocate resources and care tograndchildren or other close relatives

Hill and Hurtado;191,239 Hawkes et al.194,259

Parents with fewer resources preferentially invest in offspring(usually daughters) with lower variance in expected RS

Boone;260 Borgerhoff Mulder;251,261 Gaulin andRobbins;262 Judge and Blaffer Hrdy;263 Mealeyand Mackey264

Offspring of the sex that faces better adult economicopportunities receive higher PI

Hewlett;265 Low;266 Low and Clarke;267 Voland etal.268

Offspring of the sex that has greater probability of contributingto future support of siblings receive higher PI

Borgerhoff Mulder;251 Hewlett;265 Hill andHurtado;239 Smith and Smith269

Offspring of the sex that has greater probability of competingwith siblings for resources or mates receive lower PI

Borgerhoff Mulder;251 Mace;270 Voland et al.271

If daughters (or sons) have greater future mating opportunities,they receive higher PI

Dickemann;217 Boone;260 Bereczkei and Dunbar;272 Cronk273,274

If daughters (or sons) are better able to claim and hold politicalpower, they receive higher PI (especially inheritances)

Blaffer Hrdy and Judge;275 Boone;260 Hewlett265

Parental resources with increasing marginal benefits to offspringare characterized by unigeniture (single heirs)

Boone;260 Voland et al.268

Increasing marginal benefit of biparental care leads toincreased pair-bond stability

Hurtado and Hill;138 Blurton Jones et al.104

a PI, parental investment; RS, reproductive success.


in patterns of fertility and mortality,but conventionally it is used to labelthe rapid decline in completed familysize observed throughout Western Eu-rope in the late 18th and early 19thcenturies.281 This decline was due to acombination (not generally simulta-neous) of reduced mortality and aneven greater reduction in fertility;elsewhere in the world, populationshave shown various degrees and com-binations of these two trends, with re-sultant levels of population growth orequilibrium. While demographic tran-sition is primarily viewed as a matterof demographic rates, it is also char-acterized by greatly increased levels ofmaterial investment (including inher-ited wealth) in each child; to the ex-tent that this material investment re-duces the number of additionalchildren that can be reared, demo-graphic transition also involves an in-crease in parental investment as de-fined in evolutionary theory.234

Historical and economic demogra-phy has revealed several socioeco-nomic factors correlated with modernlow-fertility regimes, but has failed todevelop a robust explanation of demo-graphic transition that can accountfor its varied occurrence in time andspace. The conjunction of increasedwealth and decreased fertility charac-teristic of post-transition populationspresents an apparent paradox for evo-lutionary models of fertility and pa-rental investment. Indeed, it stands instark contrast to a growing body ofdata showing that in pretransition(preindustrial) societies, wealth andfertility (as well as survivorship, andhence reproductive success) are posi-tively correlated.282,283

A number of HBE researchers haverecently tackled this issue with a com-bination of analytical models, simula-tions based on dynamic modelingtechniques, and empirical studies,with some novel and promising re-sults.282,284 The key theoretical ideaexplored in this work is that ratherthan maximizing the number of off-spring raised, under at least some cir-cumstances humans might adjust fer-tility behavior in a way thatmaximizes longer-term fitness. In thesimplest formulation, this might bemeasured as number of grandchil-dren.253,285 In more complex versions,

it might be a weighted product of(heritable) wealth times children,286 afertility function weighted by risk,287

or asymptotic (long-term expected)fitness.288

Kaplan et al.253,289 and Kaplan andLancaster290 have developed an ex-planation of fertility reduction thatfocuses on parental investment toprepare offspring for successfullycompeting in labor markets where“human capital” (education and ac-quired skills) is a prime determinantof success. In their formulation, re-duced fertility and demographictransition result from high levels ofparental investment per child cou-pled with maladaptive levels of fer-tility reduction aimed at reducingthese costs across a parent’s set ofoffspring. Support for the model in-cludes the finding that parents re-spond to increased skills-based labormarket opportunities with reducedfertility, despite the fact that larger

family sizes still yield larger num-bers of grandchildren.

The dynamic optimization modeldeveloped by Mace285 is meant to ap-ply to subsistence-based societiesrather than economically modernones, but nevertheless has implica-tions for understanding demographictransition. The model predicts that in-creased productivity and reliability ofsubsistence lead to increased fertility(as observed in traditional societies):“when living conditions are easier,parents can afford more children, anddo not need to be so generous to eachchild” in order to maximize the num-ber of surviving grandchildren (p.395). It also predicts that an increasein the cost of raising children leads toa marked reduction in the optimal fer-tility rate, as well as an increase in

average inheritance and averagewealth, all features associated withpost-transition societies. Interest-ingly, reduced mortality also lowersfertility, but not by a large amount.

In another original approach to theissue, Winterhalder and Leslie287 usea risk-sensitive model of fertility opti-mization to predict that reduced fer-tility will result from any socioeco-nomic or environmental factors thatreduce the degree of unpredictablevariance in completed family size, de-crease the costs of unusually low fer-tility (such as reduced reliance onhousehold labor by offspring), or in-crease the costs of unusually high fer-tility. From the perspective of thismodel, the lowering of mortality dueto stochastic events like epidemics or

Figure 6. A Tanzanian Datoga pastoralistand his child. The extent of male parentaleffort and its relationship to mating tactics insubsistence societies are a complex andhotly debated issue in human behavioralecology. In pastoralist societies like this,even though men engage in mating effortthroughout their lives by accumulating po-lygynously married wives, deep affection isobserved between fathers and their chil-dren. Photograph courtesy of MoniqueBorgerhoff Mulder.

. . . rather thanmaximizing the numberof offspring raised, underat least somecircumstances humansmight adjust fertilitybehavior in a way thatmaximizes longer-termfitness.


subsistence failures seen in the transi-tion to modern economies would fa-vor reduced fertility simply by damp-ening the stochastic variation inrealized family size. Whether these ef-fects of risk-sensitive fertility optimi-zation are large enough to account fora substantial portion of the fertilityreduction observed in historic transi-tions is as yet unknown.

HBE AS A PROGRESSIVERESEARCH TRADITION

Although it may seem a brash claimgiven the current anthropologicalfashion for relativism, the 25-year his-tory of HBE is one of clear scientificprogress. To make this point, we sum-marize the accomplishments of HBEin terms of epistemic values.291,292

These are six characteristics thatguide pragmatic assessment of scien-tific progress. In the contemporaryambience of anthropology, even cau-tious partisans of scientific knowledgeaid themselves and the discipline byan occasional and reflective defense ofits possibilities.

Predictive Accuracy

Theory development often beginswithout the data or even the opera-tional methods needed to make test-ing feasible and convincing. Nonethe-less, given the premium on predictiveaccuracy in science, empirical confir-mations must be forthcoming. Takenindividually, HBE research projectsgenerally use more rigorous, quantita-tive methods than their ethnographiccounterparts, with good predictivesuccess. However, the number ofcompelling, data-rich HBE studies isstill quite small. The reasons are sev-eral. Relatively few anthropologistswork with behavioral ecology theory,and its data demands are extensiveand exacting. Concepts and methodsare advancing rapidly, and henceearly studies look primitive by com-parison to current standards. The useof confidence-inspiring tools such asindependent estimate of parameters,null hypotheses, and significancemeasures have lagged behind the de-velopment and interpretive use ofHBE models. On this most importantof desiderata—superior agreement

Box 4. The Wilson-Daly Study of Mortality and ReproductiveTiming in Chicago

In an innovative application of life-history analysis, Wilson and Daly280

examine the relationship between risk-taking (measured by homicide rates aswell as other risk-based causes of mortality), life expectancy (with homicideeffects statistically removed), reproductive timing, and economic inequality.Wilson and Daly propose that poor economic opportunities and lowered lifeexpectancy from extrinsic factors lead to elevated risk-taking behavior, in-cluding status contests that sometimes escalate into homicides. This steepdiscounting of future prospects should in turn favor early onset of reproduc-tion.

Analyzing data by neighborhood units (n 5 77), Wilson and Daly show thatthese measures do covary across neighborhoods in precisely the mannerpredicted: 1) Homicide rates vary 100-fold, and are highly correlated with bothmale and female life expectancy, even after homicide mortality is removed(see table, below). 2) A stepwise regression shows that the “Robin Hoodindex” (a measure of income variance within neighborhoods) is an indepen-dent predictor of homicide rates as well—local income inequality encourageslethal competition. 3) Women respond to low life expectancy with earlier onsetof reproduction, and high fertility rates in the early childbearing years (seefigure). The detailed results of this study provide compelling evidence thathumans respond to perceived variation in life chances with major shifts in lifehistory variables, even in environments far different than those experiencedduring most of human evolution.

VARIATION IN LIFE HISTORY ACROSS CHICAGO NEIGHBORHOODSa

Variable Lowest Lx Highest Lx

Male lifeexpectancy(Lx)

57.1 74.5

Homiciderate

85.2 7.0

Birth rate(womenaged15–24)

414.0 135.0

Age ofwomengivingbirth

22.6 27.3

Notes: a Data from Wilson and Daly.280 Lx, mean life expectancy at birth. The“lowest” column contains data on the 10 neighborhoods with the lowest Lx

values, and “highest” column is for the 10 with the highest Lx. Homicide rates areneighborhood averages for males and females combined, per 100,000 per year;birth rates are neighborhood averages per 1,000 women aged 15–24 per year;and the last row provides the median age of women giving birth in each set ofneighborhoods.


with observation—the HBE record ispositive but altogether too thin.

This qualified assessment does notdetract from solid and important em-pirical gains. For instance, optimalforaging theory has stimulated thegathering of extensive data on theprofitability of various classes of re-sources. These data now are at theheart of recent analyses of prehistoricresource intensification and plant do-mestication. Likewise, quantitativeHBE data on time allocation to foodproduction and net yield of foraging,both as a function of sex and age, arecentral to debates about the show-offand grandmother hypotheses,12,193

with their extensive implications forhominid life history and socioecologi-cal evolution.

Internal Coherence

The parts of a theory should coherein a logically consistent manner, with-out gaps or ad hoc elements. Relativeto sociocultural anthropology gener-ally, HBE is strong on coherence, ben-efiting from its close association withtwo relatively mature fields: econom-ics and evolutionary theory. AlthoughHBE is in the early stages of devising“families”293 of subject-specific mod-els, there is every reason to projectcumulative and coordinated develop-ment. Because of the ambitious reachof the topics it addresses, mainte-nance of internal coherence is an es-pecially important accomplishment ofHBE.

Changing ways of valuing resourcesprovide an example. Originally, re-source value was appraised in termsof the nutritional yield (e.g., calories)of the prey, an absolute and resource-specific measure. Scrounging modelshighlighted the importance of assess-ing marginal value, with its emphasison the state and needs of the foragerrelative to others in the group. Hy-potheses concerned with trade-offsbetween parental investment andmating effort suggest that value (andcurrency) may be sex- and age-spe-cific. Each of these refinements givesus new, coordinated insights into thediversity possible in optimal patternsof resource selection. Another exam-ple is the grandmother hypothesis,which links together subsistence, mat-ing and parenting behavior, and life

history theory, in a theoretically co-herent manner.

External Consistency

A theory should be consistent withrelated theories that have a general,background claim of applicability tothe subject matter. HBE’s congruencewith neo-Darwinism and micro-economic theory is primary here.HBE benefits by distancing itselffrom claims of human exceptionalismand the historical attempt to isolateanthropological from collateral the-ory in the natural and some socialsciences. Red-winged blackbirds,hunter-gatherers, and search engineson the world wide web face someof the same resource selectiontrade-offs. General models ofscrounging apply to house wrens andhunter-gatherers; those of risk-sensi-

tive adaptive tactics are equally athome in biology, anthropology, andeconomics.294 Life history compro-mises affect all primates, be theychimpanzees, early hominids in Af-rica, or the contemporary residents ofAlbuquerque.

Fertility

Does the theory, over the long term,continue to generate novel predic-tions, extensions, and modificationsnot anticipated in its original formu-lation? Those of us who set out in the1970s to test diet breadth and relatedOFT models had no inkling of the ex-tent and diversity of the HBE applica-tions that would be forthcoming. Be-cause its early critics so tightly andconfidently circumscribed the “nar-rowly defined domain”295 of HBE the-

ory, present advocates can more se-curely claim that its topical expansionrepresents genuine and unexpectedexplanatory fertility.

Unifying Power

Unifying power is the cumulativeresult of a coherent and fertile theory.Does the theory succeed in establish-ing relationships among previouslydisparate subjects? Does it achievebroad scope by uniting these subjectswithin a common explanatory frame-work? For HBE, the initial signs lookgood. Central place foraging modelshave been adapted to generate in-sights about field processing andhominid transport. Diet selectionmodels have generated new insightsinto population ecology and havegiven new purchase to long-standingarchaeological concepts such as thebroad spectrum revolution. Cost-ben-efit methods that were developed tostudy patch choice are now beingused to examine life-history trade-offsand possible causes of demographictransitions. How far this trend will go,and how well it withstands competingtheoretical developments, are issuesfor the future.

Simplicity

Simplicity is valued for analyticaland aesthetic reasons but may be themost troublesome quality of a re-search tradition to define and assess.If we focus on its fundamental theo-retical premises, and view them rela-tive to potential explanatory reach,then HBE is extraordinarily simple. Ifwe focus on the dozens of models andmyriad of hypotheses that make thesebasic premises operational, then thesituation can appear quite complex.An evaluation of simplicity dependswhere, along this axis of premises-to-empirical research, one wishes toplace the assessment.

AUGURY

Early work in behavioral ecology bybiologists, including papers nowamong the most cited in the field,were routinely rejected by the majorecological journals.76 By contrast, theanthropologists who took up HBEtypically fared well at the hands of

Simplicity is valued foranalytical and aestheticreasons but may be themost troublesomequality of a researchtradition to define andassess.


referees and editors. In subsequent in-fluence on their respective disciplines,these roles have reversed. Behavioralecology in biology has become a thriv-ing subfield. Although readily pub-lished, HBE work has not yet achievedcomparable scale or impact, and HBEremains a modest and marginalizedenterprise in contemporary anthro-pology. Some archaeologists and theoccasional cultural anthropologist fol-low the field, but it has had little im-pact, for instance, on general text-books or broader theoreticaldiscussions. Given the expansion ofHBE from foraging to take up tradi-tional problems in archaeology andanthropology, this seems likely tochange. By generating sound empiri-cal results on topics of broad interest,HBE surely will pique the curiosity ofa broader array of anthropologists.

We see several fruitful directions forHBE. First, old models are being re-visited in light of new discoveries andapplications. The original dietbreadth model is being applied withnew appreciation that resource valua-tion may be differentiated by sex, andit is being used on new problems suchas the broad spectrum revolution.Second, old models also are being re-vised in light of new methods such asevolutionary game theory and risk-sensitive or dynamic programmingapproaches. Third, the theory is beingextended from its base in ethno-graphic, hunter-gatherer studies topaleoanthropological and archaeolog-ical applications and to other produc-tion systems, efforts sometimes re-quiring new or modified models.Fourth, we expect to see new effortsthat address gaps in existing studies.For instance, most HBE work to datehas neglected proximate analysis ofthe mechanisms guiding the adaptivebehavior of individuals, be these rulesof thumb, evolved psychological dis-positions, or sociocultural inheri-tance. Likewise, it has neglected theactual histories by which such traitsdevelop in populations.296 Fifth, weforesee an elaboration of HBE theoryto help explain how complex socialinstitutions and processes (such as so-cial stratification) can emerge fromadaptively directed individual deci-sions interacting with historical con-straints. This will require that HBE be

integrated with more traditionalforms of social science theory and re-search.297 What HBE can offer in thispartnership is such tools as evolution-ary game theory133 and costly signal-ing theory.174 Finally, there are out-standing questions of synthesis.Explicitly reductionist in its methods,as HBE matures it will have to dem-onstrate that it can successfully rein-tegrate topically isolated models intoa compelling and more holistic under-standing of human adaptive behavior.

ACKNOWLEDGMENTS

If we had known at the beginningall that it would entail, we probablywould not have undertaken this re-view. Nevertheless, we thank JohnFleagle for inviting us to do so. We aregrateful to colleagues and studentswho made numerous helpful sugges-tions on earlier drafts: Michael Al-vard, Rebecca Bliege Bird, MoniqueBorgerhoff Mulder, Sheryl Gerety,Don Grayson, Craig Hadley, RayHames, Richard Klein, Geoff Kush-nick, Jim O’Connell, Joanna Scheib,and Bram Tucker. We hope we havedone justice to their generous and in-sightful efforts. Our families took noteof reduced parental investment andmate attention, but tolerated themwith humor and patience. Finally, wewish to acknowledge the senior men-tors who helped us become behavioralecologists: Ric Charnov, Steve Emlen,Gordon Orians, Brooke Thomas, andthe kind people of Muskrat Dam, In-ukjuak, Cuyo Cuyo, and Mer.

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