Hunter-Gatherer Economic Complexity and Population Pressure

8/3/2019 Hunter-Gatherer Economic Complexity and Population Pressure

1/39

JOURNAL OF ANTHROPOLOGICAL ARCHAEOLOGY 7, 373411 (1988)

Hunter-Gatherer Economic Complexity and PopulationPressure: A Cross-Cultural Analysis

LAWRENCE H. KEELEYDepartment of Anthropology, University of Illinois at Chicago, Box 4348,Chicago, Illinois 60680

Received February 28, 1988

This paper examines the relaionship between population pressure and so-cioeconomic complexity among hunter-gatherers. Population pressure is definedas the ratio between population density and the density of available resources.Socioeconomic complexity is measured by means of several correlated variables:storage-dependence, sedentism, social inequality, and use of a medium of ex-change. Correlations between these variables are calculated from an ethnographicsample of 94 hunter-gatherer groups. The correlations between population pres-sure and socioeconomic complexity are found to be extremely high. Two majortypes of hunter-gatherers exist which are distinguished by a number of variablesand may be termed simple and complex. Transitional groups between thesetwo types are quite rare. It is also noted that population pressure does not arise incontinental climates where famine mortality is common because of high-amplitudechanges in productivity from year to year. It is argued that population pressure isa necessary and sufficient condition for and the eff tcient cause of socioeconomiccomplexity. The widespread disavowal by archaeologists of population pressureas a possible explanation for the prehistoric development of complex hunter-gatherers has no basis in ethnographic fact . o 1988 Academic press, hc .

INTRODUCTION

This paper concerns the relationship between population pressure,defined as the ratio between human population density and resources, andsocioeconomic complexity among hunter-gatherers. Recently, archaeol-ogists have focused a considerable amount of both theoretical and sub-stantive work on the questions of how, why, where, and when complexitydevelops among prehistoric hunter-gatherers (e.g., Binford 1980;Koyama and Thomas 1982; Price and Brown 1985a). There are manyinterrelated features that characterize complex hunter-gatherers andPrice and Brown (1985b: l&13) nicely summarize them:1. more complex technologies which involve larger inventories ofitems and greater complexity in the construction of some items;

3730278-4165188 $3.00Copyright 0 1988 by Academic Press, Inc.All righ ts of reproduction in any form reserved.


2/39

374 LAWRENCE H. KEELEY2. an intensified subsistence economy that involves the exploitation ofa wide range of species and habitats as well as greater concentration on a

few staple species;3. greater sedentism in the form of longer annual occupations of spe-cific sites, even permanent occupations;4. larger and more internally differentiated settlements;5. the beginnings of occupational specialization at the individual, fa-milial, and settlement levels;6. greater territoriality evidenced by greater use of symbols of identityand intergroup conflict;7. nonequalitarian allocation of wealth, status, and authority signalled

by the presence of hereditary ranks, incipient classes, or wealth distinc-tions .However, to this list should be appended a few other features:

8. arguably the most important of these features, heavy dependence onstored foods (Testart 1982a, 1982b; Woodbum 1982);9. larger amounts and wider networks of trade, which is related to theincreasing specialization of production noted above;10. as a correlate of the above, the use of standard mediums of ex-change or primitive monies.

The explanations proposed for the development of such features havebeen many and various but two general explanatory themes can be dis-tinguished: adaptational and transformational (Gould 1985). Gould notesthe growing popularity of the latter approach which seeks the explanationfor sociocultural complexity in social or ideological factors; on the otherhand, adapatational arguments emphasize ecological, demographic, tech-nological, or economic factors as primary. Population pressure, formerlythe King Kong of prime movers in explanations of culture change(Flannery 1976), has, like that oversized ape, fallen on hard times and is,by far, the least popular of adaptational approaches. In short, the theorywhich argues that increases in population in relation to available foodresources (Cohen 1977, 1981, 1985), or decreases in resources relative topopulation (Harris 1978), forces hunter-gatherer groups to intensify andreorganize their economies is very much a minority opinion. Such inten-sification and reorganization is argued to be necessary to cope with: (1)food deficiencies or diminishing returns on subsistence labor, (2) in-creased competition with other social units for available resources, or (3)increased risks resulting from thinner subsistence cushions and/orsmaller or more circumscribed exploitation territories. However, as weshall see, the decline in the popularity of population pressure as an ex-planation for culture change cannot be attributed to its failure to with-stand empirical tests.


3/39

HUNTER-GATHERER ECONOMICS AND POPULATION PRESSURE 375Arguments both pro and con about population pressure have mostlyinvolved vague generalizations, anecdotal evidence, and extrapolation.

For example, the issue which has generated the most heat and least lightis the question of whether human populations are under natural or culturalcontrol. Population pressure critics argue that because many societiespossess methods for controlling fertility via delayed marriage, prolongedlactation, induced abortion, infanticide, etc., a groups population levelneed never reach any Malthusian limits, exceed carrying capacity, or feelany of the supposed effects of an imbalance of persons to resources(Cowgill 1975; Bronson 1975; Ellen 1982; and many others). These argu-ments represent little more than extrapolation from anecdotal data sinceit has yet to be demonstrated that a society can maintain a stable popu-lation over many generations through predominantly cultural means with-out emigration of excess numbers or the intervention of increases in nat-ural mortality via famine and disease. Dampening the propensity of pop-ulations to rise is not the same as preventing such rises. If populationsrise, however slowly, while the resource base remains the same, eventu-ally population pressure will be felt.Population-pressure proponents (e.g., Cohen 1985), on the other hand,find their support in some vague, general, and occasional regional corre-lations between higher levels of socioeconomic complexity and higherpopulation densities, both in time and in space. There are many instancesin the prehistoric record of increases in the socioeconomic complexity ofhunter-gatherers being closely correlated with evidence of increasingpopulation density: Upper Palaeolithic southwestern France (Mellars1985; Keeley 1982), Mesolithic northwestern Europe (Price 1981, 1985),The Levant in the Terminal Pleistocene (Henry 1985), the NorthwestCoast (Ames 1981), Australia (Lourandos 1980, 1985), etc. Others havenoted that more complex ethnographically known hunter-gatherers tendto have higher population densities (e.g., Testart 1982a, 1982b). Whilesuch evidence is suggestive, it is imprecise and impressionistic.Only a few studies provide data that show little connection betweendemography and social complexity. Johnson (1982) presents some cross-cultural data, including data from many agricultural societies, that sug-gests merely a weak positive relationship. Schalk (1982), focusing only onthe Northwest Coast, argues that population density is negatively or in-versely correlated with socioeconomic complexity in that region. Brown(1985:224) argues that population pressure fairs . . . poorly as an ex-planatory mechanism in explaining the development of complexity inthe midwestern Archaic-Woodland because population densities were rel-atively low. Except for Schalk, these studies do not directly addresspopulation pressure as opposed to population density while Schalkconsiders only the relationship between population and a staple food,salmon, and not very directly.


4/39

376 LAWRENCE H. KEELEYThe problem with these critiques is that they pay faint heed to the otherterm in population pressure-available resources. It is the relationship

between population and resources that is central to the concept of pop-ulation pressure. A critical resource may not necessarily be a staple food.For example, the main staples of the Tareumiut Eskimo of north Alaskawere whales and, secondarily, other sea mammals but their technologywas highly dependent on skins for clothing and watercraft. Whales do notproduce hides useful for these purposes; therefore, small sea mammalsand caribou were critical resources. Indeed, they went inland to hunt andtraded food with inland groups to obtain hides (Sheehan 1985:127,128).Ames (1981:798) notes that on the Northwest Coast, where salmon pro-vided the bulk of food, terrestrial and littoral resources such as elk, deer,molluscs, and some plants were essential to survival in the early springwhen the stored fish were depleted and salmon runs had not yet begun.These examples imply that no matter how maritime the adapatation of ahunter-gatherer group, terrestrial resources are likely to be a limitingfactor. It is then an unfavorable relationship between population and theleast-available critical resource(s) that constitutes population pressure;population density alone is not a measure of population pressure.However, the productivity of specific critical resources would undoubt-edly be related to general terrestrial productivity within a groups terri-tory. For example, the amount of hide available within a hunter-gatherergroups territory will be directly proportional to the amount of edibleplant material produced annually to support animals. Even the availabilityof some necessities for human life, whether they can be consumed di-rectly (e.g., water) or must be metabolized by organisms lower on thefood chain (minerals, fixed nitrogen, vitamins, etc.), will be correlatedwith primary productivity because such materials are either necessary toall life or must be created by the chemistry of life. Primary productivity iseither a measure of such critical resources or is the basis out of which theyemerge.The population pressure argument has a number of simple and emi-nently testable implications which are:

(1) There should be a direct and close relationship between populationdensity relative to available resources (i.e, population pressure) and so-cioeconomic complexity.(2) Specifically, the higher the intensity of population pressure (i.e.,the higher the ratio of population to resources), the more complex shouldbe the economy.(3) Ideally there should be some specifiable level of population pres-sure, regardless of the specific environment, which when reached neces-sitates the development of a more complex socioeconomy or the incur-sion of Malthusian penalties if the transformation cannot be made.


5/39

HUNTERaATHERER ECONOMICS AND POPULATION PRESSURE 377Even if all of these implications were confirmed by reliable data, itwould not necessarily strengthen the case for demographic pressure being

an independent cause or even a cause of complexity. However, if any ofthese implications are contradicted by tests, then the hypothesis is verydifficult to maintain. These implications represent the simplest and mostdirect paths to disproving this hypothesis. They are, therefore, the mainsubject of this paper.The Goals of This Study

The aim of this analysis is to obtain a measure of population pressureand see whether and to what degree it correlates with measures of socio-economic complexity among ethnographically known hunter-gatherers.In other words, its purpose is to determine how well population pressurequalifies as a necessary and sufficient condition for complexity. Thisimplies some subsidiary goals:

1. the collection of a large representative sample of ethnographicallyknown hunter-gatherers;2. the definition of one or more measures of population pressure;3. the definition of one or more measures of socioeconomic complex-ity.

I will also examine the relationship among several environmental andsocioeconomic variables that may bear on the discussion.SELECTION OF SAMPLE

Initially, the sample consisted of 123 hunting-gathering societies takenfrom Murdocks Ethnographic atlas (1967) and his Atlas of world cultures(1981). Excluded were societies with any involvement with agriculture(other than raising tobacco) or pastoralism and mounted hunters. Then,using Murdocks bibliography as well as more recent data, the primaryethnographic sources for these societies were consulted. Cases were thenexcluded for a variety of reasons. The goal then was to obtain a world-wide sample of societies that relied exclusively on a hunting-gatheringeconomy that was undistorted by involvement in other types of econo-mies. The most common reasons for exclusion were that the ethnographicsources indicated that the society practiced some horticulture, such as theAinu or the Siriano or the Walapai, or because no population data wasavailable on the group. Other reasons for exclusion included: (1) groupsfor whom substantial amounts of food were obtained by trade from agri-culturalists (e.g., Chenchu, Dorobo), such groups tend to be essentiallyan economically specialized ethnic group or caste in a larger regional


6/39

378 LAWRENCE H. KEELEYeconomy; (2) groups whose ethnographic sources only described theirsituation after their incorporation into modern mercantile economies(e.g., many Canadian groups involved in the fur trade); (3) to avoid anyredundancy, groups linguistically and culturally similar to neighboringgroups also in the sample were excluded (such as the Modocs and theCupetio in favor of the Klamaths and the Cahuilla); (4) groups with in-sufficient data such that it was impossible to code three or more of thevariables other than population density used in this study.Some groups which were excluded from Murdocks atlases because ofinsufficient data were added to the sample because better data is nowavailable. These subtractions and additions left a sample of 94 groupscovering every continent except Europe.North American groups are heavily represented because the northernand western parts of this continent had a great concentration of hunting-gathering societies at the time of European contact.

CODING OF VARIABLESAll coding was done by the author or taken directly from other sources.

The bibliographic sources for each group are primarily those given byMurdock (1967, 1981); any additional sources are listed in the bibliogra-phy of this paper. I have relied only on data specified by ethnographers aspertaining to the precontact conditions of each group.Environmental Variables

Latitude (LAZ). This is a very useful measure of the quality of agroups environment because latitude has important effects on all life:(1) With increasing latitude, potential primary productivity declines asa result of decreasing solar radiation. This means that there are decreasingdensities of all organisms, including humans, at higher latitudes.(2) Productivity is more concentrated in a shorter portion of the annualcycle as latitude increases (i.e., increasing seasonahty) leaving highertrophic levels to contend with longer and longer seasons of minimal or noproductivity.(3) Species diversity declines with latitude (Pianka 1966), thereforerisk increases proportionately as consumers options become morelimited.Thus, latitude is a measure that incorporates several intercorrelated


7/39

HUNTER-GATHERER ECONOMICS AND POPULATION PRESSURE 379variables-productivity, seasonality, diversity, and risk. Latitude wascoded as the center of a groups territory rounded to the nearest wholedegree.Primary productivity (PP). This represents the amount of new biomassproduced in a square meter of area each year. This was calculated usingRosenzweigs (1968) formula: logrOPP = (1.66 * log,, actual evapotrans-piration rate) - 1.66. Actual evapotranspiration (AE) rates were takenfrom Thomthwaite Associates (1962, 1963, 1964). The natural log of PPwas used in all analyses.Secondary biomass ratio (R). As Kelly (1985) points out, not all of theprimary productivity is equally available to higher trophic levels sincemuch of it in some environments, like forests, is trapped in relativelyindigestible materials like wood. He uses the distinction made betweenprimary biomass (i.e., producers) and secondary biomass (i.e., consum-ers). A high secondary biomass ratio means not only more potential preybut also is an indication that the plants themselves are more available tohigher trophic levels, that is, more foliage, fruits, and seeds relative towood. The secondary biomass ratios were taken from Table 3 in Kelly(1985). As some groups territories included a mix of vegetation zones,where possible, the value of R was prorated according to the percentageof area taken by by such zones. This procedure was limited by the scaleof vegetation maps available for the various regions. For the most part, Rvalues reflect the predominant type of vegetation in a groups territory.Secondary productivity index (PPI). This quantity is a more directmeasure of the productivity of an environment for human foragers. It isderived by multiplying PP by R. PPI is a rough estimate of the secondaryprimary productivity as well as a measure of the edibility of the pri-mary biomass.Available productivity index (AP). The amount of food available to anyconsumer also depends upon its trophic level since only 10-C% of theenergy at any trophic level is passed on to the next level (Odum 1985).Thus, a consumer of plants (second level) can expect no more than about15% of the available primary productivity while a predator (third level)can expect less than 2.25%. Here, I have assumed that the secondarybiomass ratio is a good estimate of the available productivity at the sec-ond trophic level. Humans, depending on their diet, operate at the secondthrough fourth levels. If we know the proportion of a groups diet ob-tained from plants versus that obtained through hunting and fishing, wemay calculate the proportion of the primary productivity available to it,given the secondary biomass factor and given the losses resulting fromtranslations between trophic levels. The formula used was

AP = (G * PPl) + (0.0225 * HF * PPl),


8/39

380 LAWRENCE H. KEELE Ywhere G = proportion of plants in diet (see below), HF = proportion ofanimal flesh in diet, PPI = secondary productivity index. The natural logof this quantity was used in analysis (LNAP).As Lee (1%8) noted, there is a latitudinal cline in hunter-gatherer diets:the higher the latitude, the less the use of plant foods. Thus, high-latitudegroups not only must cope with environments whose lack of diversityimposes great risks and whose productivity is diminished by lower andmore seasonal solar radiation but, probably as a consequence of the lat-ter, must operate at the poorer third and fourth trophic levels.Relative available productivity (LATAP). Because the primary deter-minant of productivity is latitude (r = - .831), it is desirable to excludethe latters influence from measures of available productivity. This wasachieved by using the deviations (or residuals) of LNAP from that ex-pected for its latitude on the basis of the equation: (-0.081 * LAT) +2.58. This formula represented the best-lit regression line of LNAP onlatitude. Thus, a positive value of LATAP indicates greater than (and anegative value, less than) expected productivity given the latitude of agroups territory.Index of continental&y (CONT). It may be observed in North America,that the simpler societies are restricted to the central and eastern por-tions of the continent. More complex societies occur in the western por-tions. This not only suggests some constraining role for environment butalso that the continentality of the climate may have an influence since,because of the generally westerly flow of airmasses, the western portionof North America have more maritime climates than the central and east-ern regions.An index of continentality used by climatologists is employed here(Trewartha and Horn 1980:311):

CONT = si;*FAT - 14,where, A = annual temperature range in C and LAT = latitude.This measure was designed for nontropical latitudes (Trewartha andHorn 1980: 11 ff .) and is therefore likely to give distorted estimates for thetropics.This is not just a measure of seasonal variability but also long-termvariability since continental climates are also more variable from year toyear (Trewartha and Horn 1980:212, 299, 349, 351, 362) with regard toprecipitation and temperature than maritime climates. As these two cli-matic variables are major determinants of the actual evapotranspirationrate, which is highly correlated with primary productivity (Rosenzwieg1968), continental climates must show greater amplitudes of variability in


9/39

HUNTER-GATHERER ECONOMICS AND POPULATION PRESSURE 381productivity from year to year. Thus, any hunter-gatherer adaptation tosuch climates must cope with the greater amplitude of such changes incarrying capacity.Diet

Proportion of terrestrial animal foods in diet (HZ); proportion ofaquatic animal foods in diet (FZ); proportion of plants in diet (GZ). Mostof these values were taken directly from Murdock (1967, 1981). Theywere coded as 1-9, that is, only in whole deciles such that a code of 1 =&15%, 2 = 16-25%, etc. In a few cases, where more recent ethnographicsources were available, I have modified his figures and coded the addedgroups.Population Density (PM2 and LNP = In (PM2)

Population density is simple to calculate if one has a population figurefor a group and the area of its territory. However, obtaining either ofthese quantities for hunter-gatherer groups presents some difficulties.There are problems with population estimates for the precontact situ-ation of many groups, especially in North America where postcontactdepopulation, mainly by disease, was so severe and early. Kroebers(1939) estimates were very often based on the postcontact situation or,worse, the earliest censuses. With a few groups, careful analysis of trav-ellers accounts mission records, and village and house counts has yieldedreasonable and much higher estimates (Cook 1955, 1956, 1974, 1976).Despite many temptations, I have not calculated my own population es-timates using Cooks methods for any groups except the Klamath withwhose village sites and early history I am very familiar. Because NorthAmerican precontact populations were so commonly underestimated, Ihave always used the highest population estimates available for any groupwhether North American or not. To avoid any underestimation, wherethe population figure given was a minimum, as in 500 + or more than1000, I have always added 10% more to the figure before calculating thedensity. Even so, the most likely bias remaining in the data used here isthe underestimation of the population density of the most complex NorthAmerican groups since these were usually the first to be contacted, situ-ated in areas most attractive for colonization and, because of their highdensities, most vulnerable to epidemic diseases.The areas of the various groups territories were determined from themaps found in the respective ethnographies or in areal ethnographic sur-veys such as the Handbook of North American Indians. These maps, inmany instances, represent compromises between various uncertainties


10/39

382 LAWRENCE H. KEELEYTABLE 1POPULATION DENSITY ESTIMATES FORHUNTER~ATHERER SAMPLE

1. Kung2. Hadza3. Mbuti4. Yukaghir5. Gilyak6. Andaman7. Semang8. Aranda9. WalbiriIO. Dieri11. Murngin12. Wikmunkun13. Gidjingali14. Wongaibon15. Tasmanians16. Aleut17. Nunamiut18. Tareumiut19. Chugash20. Nunivak2 1. Copper Eskimo22. Caribou Eskimo23. Angmaksalik24. Iglulik25. Polar Eskimo26. Labrador Eskimo27. Saulteaux28. Micmac29. Attaw. Cree30. Naskapi31. Ojibwa32. Kaska33. Chilcotin34. Slave35. Carrier36. Ingalik37. Tanaina38. Nabesna39. Kutchin40. Dogrib41. Chipewy42. Haida43. Thngit44. Nootka45. Tsimshim46. Twana47. Puyallup

0.250.40.450.0120.52.250.40.080.0340.050.130.52.00.50.151.790.0450.100.460.860.030.010.20.0140.0140.0450.0160.060.0370.0130.080.0260.330.0360.1%0.1070.150.020.050.0220.0102.461.001.72.120.845.0

Hitchcock 1987Woodburn 1968: 103, 105Turnbull 1965: 159, 160, Fig. 3Analogy with the Ngansan, Chard 1963: 105 and mapBlack 1973: 2. 3Radcliffe-Brown 1922: 15, 17, 18Evans 1937: 1, 2, 15, map 1Yengoyan 1968: 190Yengoyan 1968: 190Yengoyan 1968: 189Warner 1937: 16McConnel 1930: 97, 131Hiatt 1965: 17Yengoyan 1968: 190Jones 1978: 20; area from atlasKroeber 1939: 135HNAI 1984: 338, 340Oswalt 1967:HNAI 1984: 209, 213; Birket-Smith 1953: 3, 12, 22Kroeber 1939: 135Kroeber 1939: 134Kroeber 1939: 134HNAI 1984: 623, 638Kroeber 1939: 134HNAI 1984: 578, 580Kroeber 1939: 134Grant 1890: 308Kroeber 1939: 140Kroeber 1939: 141HNAI 1981: 169, 170, 172, 173Kroeber 1939: 140Kroeber 1939: 141Kroeber 1939: 138Kroeber 1939: 141HNAI 1981: 414,415,416HNAI 1981: 603, 614HNAI 1981: 625, 637, 638HNAI 1981: 564, 568HNAI 1981: 514, 516, 530; Krech 1978: 98 and Fig. 1Kroeber 1939: 141HNAI 1981: 275Kroeber 1939: 135Jorgensen 1980: 447 (coded l-5 per sq. mile;

Kroeber 1939 gives a value of 0.26)Kroeber 1939: 135Grumet 1975: 299 (pop.); Kroeber 1939: 135 (area)Elmendorf 1974Jorgensen 1980 codes as having a population densitygreater than 51mile


11/39

HUNTER-GATHERER ECONOMICS AND POPULATION PRESSURE 383

48. Quinault 1.5249. Cowichan 0.950. Yurok 4.751. Tolowa 3.652. Alsea 1.8753. Sinkyone 6.9954. Hupa 5.255. Wiyot 11.056. E. Porno 16.6751. Shasta 1.958. Coast Yuki 4.1959. Yana 1.0460. Atsugewi 1.261. Mt. Maidu 2.6562. Wintu 7.263. Sierra Miwok 1.4364. Washo 0.7565. Tubatulabal 0.7766. Lake Yokuts 7.1267. Wappo 4.368. Monachi 5.0569. Nomlaki 1.8470. Kaibab 0.0967 I. Luiseno 6.772. Mono 1.073. Agaiduka 0.0474. Kuyuidoka 0.4875. Kidutodoka 0.0376. Gosiute 0.0477. Panamint 0.05578. Yavapai 0.10679. Seri 0.1280. Kiliwa 0.8781. Serrano 0.7882. Cahuilla 2.583. Klamath 0.6584. Tenino85. Sanpoil86. Suswap87. Thompson88. Karankawa89. Aweikoma90. Botocudo91. Yaghan92. Han93. Chumash94. Guayaki

0.491.00.400.860.50.10.30.120.04221.600.067

TABLE l-Continued

Olson 1936: map 1, 22, 23Kroeber 1939:Cook 1976: 4Cook 1976: 4Kroeber 1939: 136HNAI 1978: 194Cook 1976: 4Baumhoff 1963: 231HNAI 1978: 307Cook 1976: 5, 6Baumhoff 1963: 199HNAI 1978: 361, 362HNAI 1978: 236Cook 1976: 17HNAI 1978: 324, 325Baumhoff 1963: 215Downs 1966: 4 (pop.); HNAI 1986: 468 (area)HNAI 1978: 437,439Cook 1955: 53Cook 1976: 8HNAI 1978: 426, 435Cook 1976: 14-15Kelly 1978: 5,25 and map 1HNAI 1978: 550, 557Bettinger 1982: 106Steward 1938: 189Stewart 1941: 147Stewart 1941: 146Steward 1938: 47Steward 1938: 47Schroeder 1974: 261 (pop); HNAI 1983: 39 (map)HNAI 1983: 231, 234Meigs 1939: 4, 21HNAI 1978: 570, 573Bean 1972: 23, 77Authors calculation based on village list and map inSpier 1930Murdock 1958: 299; 1980: 130, 133Ray 1933: 13, 22Teit 1909: 466 (pop.)Kroeber 1939: 138HNAI 1983: 364, 365, 359Urban 1978: 46, 47Steward and Faron 1959: 531, 532Steward and Faron 1959: 107, 108; Cooper 1946: 15, 83HNAI 1981: 507, 511King 1%9 (pop); Beals and Hester 1974 (area)Clastres 1972: 167


12/39

384 LAWRENCE H. KEEL EYbut they provide rough estimates of the territory principally exploited bya group. Because the sharing of territory is more common among the mostmobile groups, the most likely bias introduced by the use of such maps isthe overestimation of the population densities of such groups.Because of the uncertainties in the derivation of both population andarea estimates, the figures calculated and used in this study should betaken as being roughly correct within half an order of magnitude.Because of the importance of such estimates for this study and becausethe demographic information was so often missing or of poor quality inthe ethnographic sources, I have provided Table 1 which gives the densityestimate for each group and the source or sources from which they werederived. All densities are given as persons per square mile and convertedto natural logarithms for figures and calculations.Population Pressure

In order to measure different aspects of the relationship between thenumber of persons supported and the productivity per unit of area, and todeflect criticism that might attach to the use of only a single measure,three slightly different indices of population pressure were calculated forthis study.Latitude-adjusted population density (LNX). The relationship of lati-tude to population density shows an interesting pattern: in Fig. 1, we seethat there are two linear arrays of points-one stream consisting of groupswith storage codes 62 and another of groups with storage codes 3-5.These storage codes indicate increasing dependence on storage (seebelow). We note that these two lines diverge and that there are no storagecodes greater than 1 below 29 latitude. Storage economies (codes 3-5),then, are always at higher population densities than nonstorage groups(codes O-2) for any given latitude. If we are to realistically compare pop-ulation densities, we must exclude the influence of latitude. Here it isdone by determining the regression line for the nonstorage groups whichis LNP = (- 0.0516 * LAT) - 0.49, giving a predicted LNP for each

The regression equation for only the nonstorage groups was used rather than that for thewhole array of points for two reasons: (a) the use of this as baseline from which to measuredeviations gave the best separation between the storage and nonstorage groups, and (b)regression analyses with several random subsamples of the cases showed that the parame-ters of the nonstorage regression equation were more stable than those of the generalregression line. It important to note that as far as correlations between LNX and othervariables are concerned, they were precisely the same as those obtained using the deviationsfrom the general regression line or partial correlation coefftcients calculated between LNPand other variables with latitude partialled. This regression analysis as well as all otherstatistical analyses reported in this paper were conducted using the SAS package availablethrough the Computer Center of UK.


13/39

HUNTER-GATHERER ECONOMICS AND POPULATION PRESSURE 385

70.

60

SO-

:.r 40.zi-I

30.

20

lo-

O- t-5 -4 -3 -2 -1 0 1 2 3log Population Density (L OGPI

FIG. 1. Plot of latitude and log population density (LOGP).

latitude. The actual LNP is then subtracted from this predicted value toobtain LNX. LNX is equivalent to the residuals from the predicted line orlog (actual density/predicted density) and is a measure of population den-sity relative to latitude. LNX, then is an index of population pressure thatmeasures population density relative to the productive potential and theresource diversity of a groups territory.Productivity-adjusted population density (LNY). A similar pattern isevidenced between available productivity and population density withstorage societies always showing higher densities for a given LNAP thannonstorage one (Fig. 2). Thus, in a similar fashion to LNX, a measure ofpopulation density relative to available primary productivity can be cal-culated. The formula for calculating the expected LNP for a given LNAPis 0.689 * LNAP -0.644 (unlike LNX, this is the formula for the regres-sion line for the whole array, both storage and nonstorage groups). Thedeviation in log units of the actual density from the expected figure is


14/39

386 LAWRENCE H. KEEL EY,ii,c rode 5

-54 3-5 -4 -3 -2 -1 0 1 2 3 4LNAP

FIG. 2. Plot of log population density (LNP) and log availabie productivity index (LNAP).

labeled LNY and provides a most accurate measure of population pres-sure on available food resources.Another interesting observation that arose from closer inspections ofFigs. 1 and 2 as well as similar plots for other productivity variables is thatterrestrial productivity, as measured by LAT, LNPPl, and LNAP, is alimiting factor for population density, regardless of whether the groupuses marine resources. Although coastal groups, representing 37% of thesample, tend to show higher population densities for a given measure ofterrestrial productivity than noncoastal groups, the strength of the corre-lation between population density (LNP) and terrestrial productivity(LNAP) is slightly higher among such groups (r = S92) than correlationfor all groups (r = S75). In other words, the population densities ofcoastal groups, with access to marine resources, are just as, or evenmore, constrained by terrestrial productivity as interior groups.Productivity/density ratio (LNZ). A simpler formulation of LNY andLNX involves dividing the secondary productivity index (PPl) by thepopulation density (PM2) and using the natural log of this ratio in calcu-


15/39

HUNTER-GATHERER ECONOMICS AND POPULATION PRESSURE 387lations. In other words, it expresses directly the relationship of naturalproduction to persons supported per standard area. While this is a lessprecise measure of the relationship between resources and populationdensity than LNY, it is used here because it excludes the influence ofdiet, which, it may be argued, is the result of cultural choice.Socioeconomic Complexity

In this study, sedentism, storage dependence, social inequality, and theuse of a medium of exchange will be used as measures of socioculturalcomplexity. Information is widely available on these variables in the eth-nographic literature and codes for them were already available or notdifficult to formulate.Sedentism (STAY). There are many ways to define the concept of sed-entism. Kelly (1985) used several (1) the number of residential moves peryear, (2) the total distance moved per year, (3) the average distance permove, and (4) the length of stay in a winter village or camp. While thenumber and scale of residential moves may be useful for comparison tothe distribution of food resources, the length of time a group stays in asingle location during its annual cycle better conforms to our concept ofsedentary. For example, there are many groups who stay much morethan half a year in their winter village but then become very mobile duringthe warm season. A group that moves 11 times a year (e.g., Klamaths) butstays in the winter village for 6-7 months of the year is obviously moresedentary than the Mbuti who also move 11 times but stay no more than2 months at any one camp. Also, the time of the year when resources arelimited and dispersed would be when we would expect the greatest mo-bility. Thus, the strongest measure of sedentary tendencies would be thelength of stay at camps or villages occupied during such seasons. In midto high latitudes such a season is winter. Therefore, the total and longestlength of stay (in months) in a camp or village occupied during the winterhas been recorded as the variable STAY for nontropical groups. Fortropical groups, the longest stay in a dry-season camp was recorded forthis variable.Some verbal descriptions were conservatively translated into codes:most of the year = 7 months, over half of the year = 6.5 months,a few weeks = 1.5 months. There are a few cases where no informa-tion on length of stay could be obtained.Dependence on storage (STOR). The main interest of this study is howmuch a group depended on stored food within its annual cycle. The kindsof information used in constructing these codes were: (1) whether thefoods stored were staples or not; (2) the length of time during an annualcycle that stored foods provided the predominant or exclusive diet, usu-


16/39

388 LAWRENCE H. KEELEYally a season of low productivity; and (3) the extent to which trade andfeasts were supported by stored foods, implying a surplus. The codeswere as follows:Codes O-2 represent essentially nonstorage economies.

0 = No storage of food.1 = Storage of supplemental foods-mostly condiments, treats,honey, ect.2 = Some seasonal storage of staples but stored food is merely sup-plemental to fresh foods or stored food predominates in diet for periods ofless than a month.2Codes 3-5 represent storage economies.

3 = Stored foods predominate in diet during the poor season (i.e.,winter) but a period of hunger in the early spring is usual. We can termthese as marginal storage economies.4 = Stored foods adequate to carry diet over the winter without a usualperiod of hunger.5 = Stored foods accumulated in surplus and the surplus used in ex-tensive trade, ceremonial redistribution, feasting, etc. This code wastaken directly from Murdock and Morrow (1979) and is equivalent to theircodes C, G, K, and Q.3Class distinction (CL). These codes follow Murdock (1981).0 = No class distinctions.1 = Wealth distinctions.2 = Dual class distinctions with a hereditary aristocracy and common-ers.Medium of Exchange (MON). These codes follow Murdock and Mor-row (1970).. = No information or use of alien (e.g., colonial) currency.

* In applying this code, I found great variabil ity in the importance and use of stored foodsin the diets of groups so coded, implying that some further subdivision of this category mightbe useful.3 I found it dif ficult , in practice, to distinguish this category from code 4, and occasionally3, since all such groups used stored food in ceremonial feasts and many traded stored

foodstuffs. I f there are any differences between 3,4, and 5 regarding the use of stored foodsfor other than purely subsistence purposes, it is in the timing and number of feasts andgiveaways that involve stored foods: code 3 groups tended to schedule such activities inthe late fall-early winter, code 4 groups early and mid-winter, code 5 throughout the coldseason into the spring.


17/39

HUNTERdATHERER ECONOMICS AND POPULATION PRESSURE 3890 = No medium of exchange, barter only.1 = Domestically usable articles are medium of exchange.2 = Articles of conventional value or primitive monies (e.g., shellbeads, dentalium, etc.) are medium of exchange.

Control for Cultural DiffusionTo facilitate the use of statistics and to control for regional similaritiesthat might be the result of diffusion, the sample was divided into fourgroups of approximately equal size: (1) the North American Arctic andSubarctic, (2) the Northwest Coast and Plateau, (3) California and the

Great Basin, (4) the rest of the world. This procedure is a common one incross-cultural statistical research (M. Dow, pers. commun.). Threedummy variables were used to code for this:

A = rest of world,B = North American Arctic and Subartic,C = Northwest Coast and Plateau.The coding was 0 or 1, thus a group from California or the Great Basinwould be coded zero on all three variables. By partialling4 these threevariables (which would automatically partial the uncoded fourth), theinfluence of regional similarities on any correlation coefficients could beexcluded.

RESULTSSeveral points are worth noting before giving the detailed results. Thepartialling out of regional similarities had very little effect on the size ofmost correlation coefficients. For example, the correlation between LNY

and STOR was .839 before and .780 after partialling. This means that suchrelationships are largely independent of region or differences betweenregions. The exceptions are correlations with any variables that are highlycorrelated with latitude (LNPPl, LNAP, Gl, etc.) because the regional4 Partialling of correlation coefficients is a procedure by which the correlation betweentwo variables may be calculated after excluding their individual correlations with one ormore other variables. For example, a strong positive correlation between primary produc-tivi ty and population density was found but as both are highly correlated with latitude, it wasimportant to discover whether this correlation would exisit independent of the effect oflatitude. This was done laboriously here by calculating separately a latitude-relative pro-ductiv ity and a latitude-relative population density and then correlating these new variables.This could have been done much more simply by calculating the partial correlation coeffi -cient between LNAP and LNP with LAT partialled. The more laborious method wasused here so that scatter diagrams could be made for presentation. Any textbook on mul-tivariate statistics will describe in detail the rationale and techniques of partial correlation.


18/39

390 LAWRENCE H. KEELEYgroupings are roughly latitudinal. With such variables, partialling A, B,and C was equivalent to partialling latitude to some degree. Correlationsbetween variables which do not highly correlate with latitude (LATAP,CONT, LNX, LNY, LNZ, STAY, CL, STOR, MON) show little changeafter partialling for region. Therefore, all coefficients reported in the ta-bles are the raw coefficients.Environmental Factors

The correlations between the various measures of environment andother variables, along with their error probabilities, are given in Table 2.Latitude shows significant positive correlations with storage and fishingbut negative correlations with plants in the diet and population density.Its correlation with storage dependence (STOR) is principally accountedfor by the absence of storage economies below 28 latitude. Above 28latitude, there are few groups which do not practice some form of storagebut high dependence on storage does not appear to increase with latitude.Indeed, if groups at latitudes less than 25 are excluded, the correlationbetween storage-dependence and latitude drops to nothing (r = .044, N =83). Many groups in high latitudes live in highly seasonal environments,for example, the Central Eskimo, the Interior Athabaskans, the Naskapi,the Tierra de1 Fuegans, but use little or no storage of food. The seasonalproductivity of mid to high latitudes encourages storage but does notrequire it (contra Binford 1980).Latitude and productivity show significant correlations with populationdensity but these are the result of complex groups, which have higherdensities, being restricted to higher latitudes. It is clear that richer envi-ronments in terms of primary and secondary productivity are not neces-sarily the home of more complex storage-dependent groups.

TABLE 2CORRELATIONSBETWEEN ENVIRONMENTAL AND OTHERVARIABLES

GI HI FI LNP LNX LNY LNZ STOR ST AY CL MON COMPLA T - ,761 .I69 .61 I -.360 ,063 ,147 - ,013 ,412 ,208 ,261 ,131 ,269

.OC Ol 1026 .wo l .oinM A-517 .I556 .MlOl .XlOl .lm15 * .0112 .2189 .0158dLNAP .739 -.298 -.513 ,575 ,242 -304 -.I13 -.I77 -.OlO - .029 .053 - ,050

.ocQl sQ35 .culol .ooOl .0191 .%83 .2794 at?88 .9263 .7827 .62W .65tMdLATAP ,165 -.278 -.013 ,483 ,532 ,220 - ,224 ,316 ,304 ,349 ,295 ,328.I117 .@366 A989 .ccxll .oool .0332 .0303 .co19 .00546 Mm 6 .ca4s sm29dCONT ,135 .535 -447 -.646 - ,676 - ,656 ,560 - ,488 - .530 - ,547 - ,421 - ,558

.1960 .ooo1 .cmo 1 .oooI JxJo1 .mol .ooOl .oQo1 .oQo1~ .tWOl .coOl .OO Ol~

a Error probabilities; N = 94 unless marked otherw ise.bN = 82.N = 91.N = 80.


19/39

HUNTER-GATH ERER ECONOMICS AND POPUL ATION PRESSURE 391The variable with the highest number of significant negative correla-tions with the demographic and socioeconomic variables is continentality.

This indicates that the highest population densities and most complexsocieties are situated in the least seasonal environments for their respec-tive latitudes (Fig. 3). This fact and the weak effect of latitude on demog-raphy and socioeconomy suggests that only a slight degree of seasonalityis a necessary condition for the development of complex hunter-gatherersocieties but it is neither a sufficient nor a determining one.Continentality is more highly correlated with the demographic variablesthan with socioeconomic ones, implying that the correlations with socio-economy are through demographic variables and not independent ofthem.The exceptions are several groups from the tropics but, as noted above,the index used here is likely (it appears) to underestimate the continen-tality of such groups. Although the climate faced by the Yaghan wasmaritime, there can be no doubt that it was an exceptionally harsh

80

70

60

Yuke2phrr= 642 N=94symbol-storage code

K,Chl2 2 20 20 2 2 22

2 22 2 20 2 Gllyak4

23 4 3 3 333 30 0 4 3333 J

35553 J yok~ts

34 3 45 5 5

5 5-3 -2 -1 0 1 2 3

LN YFIG. 3. Plot of continentality (CONT) and log productivity-adjusted population density(LNY). Groups showing the greatest deviation from the regression line are identified.


20/39

392 LAWRENCE H. KEEL EYone, if one reads accounts of it by voyagers who faced it (see, for exam-ple, Darwins observations in The voyage of the Beagle). The highergeneral continentality of Asian climates (Trewartha and Horn 1980:31 l),explains the deviation of the Yukaghir and Gilyak. Thus, only the Tas-manians appear to be truly exceptional.Why the relative temperature range should be correlated with demog-raphy is not immediately clear. One explanation might be that coastalgroups tend to have higher densities than interior groups for any givenlatitude whether they are complex or not. However, there are many ex-ceptions. For example, the highest densities in California were, with theexception of the Chumash, found among the interior groups of the CentralValley and the foothills of the Southern Sierras. There are also many lowdensity coastal groups like the Tasmanians, the Yaghan, the Central Es-kimo, and the Micmac. The elimination of all 35 coastal groups from thesample did not substantially change the correlation coefficients betweenCONT and any of the demographic or socioeconomic variables (for ex-ample, CONT-LNX = - .588 and CONT-STAY = - .462 compared tothe correlations between the same variables given in Table 2). The mostlikely reason is that noted above, that is, continental environments aremore variable in productivity from year to year.Dietary Factors

Correlations between the dietary and other variables are shown in Ta-ble 3.The dietary variables are, of course, negatively intercorrelated. Thehigh r between Gl and Fl, as well as their high correlations with LAT-positive for Fl, negative for Gl-imply that as plant life becomes poorerand less diverse, they are replaced by aquatic animals in hunter-gathererdiets.Terrestrial animals are more important in the diet of groups occupying

TABLE 3CORRELATIONSBETWEENDIETARY ANDOTHERVARIABLES

Fl Cl LNP LNX LNY LNZ STOR STAY CL MON COMPHI - .4a3 - .m - ,662 - .632 - s73 ,593 -.417 - S76 - ,387 - .387 -.519.OtXll~ .0376 .C@Ol .tmol .fxol .oool .cQol .molb .ocm .m2c . Imo1~Fl - - .&XI ~3872 ,367 A69 - ,227 ,447 .360 ,410 ,186 ,389

.oool ,403s mo3 .ooo1 .0280 .oool .ooosb .ooo1 .0779c .ouo4~Gl - ,333 .015 -.I15 - ,334 -208 .0166 -.I88 ,049 - .055.cQlO x822 .26!+7 .oolO 444.0 .8825~ .06!20 .6(25c .627sda Error probabilities; N = 94 unless marked otherwise.bN = 82.N = 91.*N = 80.


21/39

HUNTER-GATHERER ECONOMICS AND POPULATION PRESSURE 393less productive and more continental environments. Hl is strongly neg-atively correlated with the demographic and socioeconomic variables im-plying that hunting groups tend to have low population densities and to besocioeconomically simple. As the correlations with demography arehigher than with socioeconomy, this suggests that the relationships be-tween the importance of terrestrial animals in the diet and socioeconomiccomplexity are mediated by the demographic variables. Indeed, partial-ling out of demographic variables confirms this as correlations betweenHl and the socioeconomic variables then drop to insignificance. It can beargued that higher human densities, greater sedentism, and a necessarilyheavier dependence on storage would force groups to concentrate moreon the less mobile and faster reproducing plants and fish than on landmammals (cf. Hayden 1981).Gl is negatively correlated with LAT and Fl, positively with LNAP,but essentially uncorrelated with demography and socioeconomy.The proportion of aquatic animals in the diet (Fl) shows correlationsopposite to those of HI-they are positive where those with Hl are neg-ative. Again, the partialling of demographic variables indicates that mostof the relationship between FI and the socioeconomic variables is viademography; a marginally significant relationship with storage-dependence remains, however.This analysis indicates, then, two general and relatively independentdietary trends: (1) away from plant foods with increasing latitude and (2)away from terrestrial animal foods with increasing population density.Demographic Factors

As Table 4 clearly shows, the demographic variables are highly corre-lated with the socioeconomic ones, especially sedentism and storage de-pendence. It is clear from the correlations below and Figs. 1 and 2 thatonly those groups whose population densities are high relative to theproductivity of the environment are complex.Figure 4, a plot of STAY versus LNX with each group represented byits respective storage code, reveals the existence of two distinctive groupsof societies, (1) groups with low dependence on storage (STOR < 3) and(2) those more dependent on storage (STOR > 2). An almost identicalresult can be obtained by plotting LNY or LNZ against STAY. Thenonstorage groups stay less than 5.5 months at their poor season sitesand show LNY values less than 0.17 (LNX < 1.92, LNZ > 1.7), whilestorage groups stay at their winter villages for 5 or more months withLNY values greater than -0.29 (LNX > 1.45, LNZ < 2.48). This resultconforms to Testarts (1982a, 1982b) dichotomy between storage andnonstorage economies. The absence of intermediate groups suggests that


22/39

394 LAWRENCE H. KEELEYTABLE 4

CORRELATIONS BETWEEN DEMOGRAPHIC AND SOCIOECONO MIC VARIABLESSTOR STAY CL MON COMP

LNP 335 .679 .562 ,625 .674.oool .ooolb .OOOl .0001 .oooldLNX .810 .835 ,718 .725 .a57.OOOl .OOOlb .OOOl .OOOIC .oooldLNY .839 .844 ,707 .728 ,873.OOOl .0001b .OOOl .0001 .ooOldLNZ - .790 - .808 - .645 - .758 - .842.ooOl .ooOlb .Oool .OOOl .oooldSTOR - ,881 .756 ,758.OOOlb .Oool .OOOlSTAY - - ,703 ,673.OOOlb JOOldCL - - - .625.OCQl

n Error probabilities; N = 94 unless marked otherwise.bN = 82.cN = 91.dN = 80.

the transition is unstable and probably very rapid. We note that among thestorage groups there is an obvious tendency for groups with higher rela-tive densities to stay longer in their winter village and to show greaterdependence on storage.The socioeconomic variables are closely intercorrelated and, therefore,can be combined in a principal component which corresponds tocomplexity.5 This composite complexity variable (COMP) correlates verystrongly with population pressure [LNX, LNY (Fig. 5), and LNZ].Socioeconomic Relationships

The analysis of partial correlations among the socioeconomic variablessuggests that while sedentism may be closely related to storage, its rela-tionships with social inequality and the use of a medium of exchange arenot direct. If STOR is partialled, the correlations between STAY and theother two variables drop to insignificance (STAY-CL = ,119 and STAY-MON = .02) but when STAY is partialled, the correlations betweenstorage and the other variables remain significant (STOR-CL = .406 andSTOR-MON = .472, N = 80). This result supports Testarts (1982a)5 Variables included were STOR, STAY, CL, and MON. The first principal componentexplained 79.5% of the variance. The eigenvectors were as follows: STOR 0.5363, STAY0.5154, CL 0.4783, MON 0.4669.


23/39

HUNTER-GATHERER ECONOMICS AND POPULATION PRESSURE 395111c

9

58T 7AY6

543

Saultea* 2 22222 220 22u lnddman20 02 202 1

0 22 M 02 r= 84-l0 0 S.S, N=82;,y.a 12 2 0 symbokstorage code0 0

-i -2 -i 6 ; i iLN Y

FIG. 4. Plot of sedentism (STAY) and log productivity-adjusted population density(LNY). Groups showing the greatest deviation from and extremes along the regression lineare identified.

contentions that it is the practice of storing food that encourages thedevelopment of social inequality.DISCUSSION

The strong association between demography and socioeconomic com-plexity also suggest that any claims for the prehistoric development ofcomplexity unaccompanied by increases in population pressure are to betreated with extreme skepticism. Often it is the confusion of populationdensity with population pressure that leads to such contrary claims.Brown (1985:211), as we noted above, claimed that the emergence ofcomplexity among foragers in the Lower Illinois valley was not well cor-related with demographic increase because the population density neverreached much more than 1 person/mile* during the period of greatestcomplexity. If we convert this to LNX for 40 latitude, we obtain a valueof 2.51 which compares well with the complex groups in the ethnographicsample. Schalks (1982) counterexample from the Northwest Coast alsodisappears if relative densities (Table 5) are used instead of raw densities(keep in mind the point, made above, about the limiting nature of terres-trial resources on the Northwest Coast). Given that some of the figures inTable 5 are based on the low Kroeber estimates while others are from avariety of more recent, higher, and more accurate figures, it would seem


24/39

396 LAWRENCE H. KEELEY

37

2-

1.

C0 o-MP

-1 .

-2 .

COMP= SSLNY- IT 5r= 873 N=80

/ .l. . .. , . . l. .

.

. /

. * d .X M.

9 . . . . l. . l Ser,. . ..

-3J -i-3 -2 -1 0 1 2 3

LN YFIG. 5. Plot of socioeconomic complexity index (COMP) and log productivity-adjustedpopulation density (LNY). Groups showing the greatest deviation from the regression lineare identified.

that the more complex northern groups have relative population densitiesas high or higher than the less socially complex groups to the south ofthem. Whatever the cause of socioeconomic complexity in hunter-gatherers, demographic pressure on resources must be considered a cru-TABLE 5

RELAT IVE POPULATION DENSITIES AND SOCIOECONOMIC COMPLEXITY ON THENORTHWEST COAST

Group LATYurok 41Tolowa 42Alseaa 44Twana 47Quinault 47Puyallup 47Cowichan 49Nootka 49Haida 54Tsimshim 5.5Tlingit 58

LNX4.15 2.56 3.033.94 1.57 1.963.39 2.31 1.372.74 1.68 1.093.33 1.73 2.564.52 2.71 1.952.91 1.32 1.773.54 1.79 2.194.18 2.24 2.294.08 2.07 2.293.48 1.78 2.75

LNY COMP

LIPopulation from Kroeber 1939.


25/39

HUNTER-GATHERER ECONOMICS AND POPULATION PRESSURE 397cial component of any causal models. To ignore or dismiss the role ofdemographic pressure means not only ignoring the empirical correlationsdetermined here but also the simple, and therefore robust, hypothesesthat argue that complexity and demography must be related.The most obvious pattern in this data involves the close, indeed nearlycoterminous, relationship between storage dependence, sedentism, andrelative population density. Table 6, which shows parital correlationsbetween variables with all other variables controlled, implies that therelationships between these three variables are not symmetrical-the re-lationship between relative population density and sedentism is indirectand is mediated by storage dependence.

This means that population pressure influences storage which influ-ences sedentism (or the converse) but that there is no direct, independentrelationship between sedentism and population size or density as hasoften been suggested (e.g., Harris 1978). The population increase notedamong some modem previously mobile foraging groups (e.g., Binford andChasko 1976) when they become sedentary may have more to do with theelimination of periodic famines and high infant mortality than with sed-entism. The populations of some highly mobile North American groupscontinued to fall well after they were forced into a sedentary existence onreservations (see HNAI 1986:608-619, for example) or limited their mo-bility in order to participate in some aspect of the Euro-American econ-omy. Various mobile attic and subartic groups, although becoming in-creasingly sedentary throughout the last century as a consequence of thefur trade, only showed increasing populations after the advent of im-ported foods to limit famines and after modem medicine lowered infantmortality rates (see entries under population, increase in the indices ofVolumes 5 and 6 of The Handbook of North American Indians (HNAI

TABLE 6PARTIALCORRELATIONS BETWEEN SELECTEDVARIABLES,ALLOTHERVARIABLES CONTROLLED~LNAPb AC LNPd STOR STAY CL

LAT - .460 so9 - .103 .199 .062 .282LNAP - .174 .556 - .335 - .043 496A -- - .395 .172 .028 .263LNP - - - .520 .251 .034STOR - - - - .500 .264STAY - - - - - .043a N = 82.b As latitude is partialled, equivalent to LATAP.c Latitude partialled, equivalent to CONT.d Latitude partialled, equivalent to LNX.


26/39

398 LAWRENCE H. KEELEY1984, 1981)). The history of Native American populations clearly indi-cates that the connection between decreased mobility and populationgrowth is neither obvious nor universal.With the elimination of a direct linkage between sedentism and demog-raphy, there are three alternative models that relate them indirectly. Theyare :

A. increasing sedentism requires increased storage dependence whichin turn requires or allows an increase in relative population density;B. increasing reliance on stored food requires decreased mobility and,independently, requires or allows increased density;C. increasing relative density (either through population growth or adecline in resources) requires greater storage dependence which entailsdecreased mobility.However, not all of these models are equally plausible. The first twomodels share some difficulties. Both sedentism and storage are uncorre-lated with environmental variables. As the partial correlations in Table 6indicate, sedentism can be related to environment only through a chain ofrelationships consisting, successively, of storage dependence and popu-

lation density. Since, as noted above, the weak correlation between stor-age and latitude is merely an artifact of the absence of storage economiesin the tropics, storage dependence also can only be related to environ-mental variables through population density. If storage-dependence orsedentism were causal variables, this would imply that complex groupscould occur in any kind of environment. But, as our data shows, this isnot the case, particularly in North America, as complex groups do notoccur in continental climates.The second difficulty about hypotheses that deny a seminal role topopulation pressure is that, if they address the question at all, they oftenexplain the higher population densities of more complex groups by argu-ing that the higher production and productivity of such systems permitlarger populations (Ellen 1982:269). The data presented here show suchclose relations between demography and socioeconomy that the relation-ship must be one of necessity rather than permission. The postulation ofan underlying pressure and upward creep toward higher populations willallow this data to be reconciled with the permissive argument but thisis, of course, one of the main tenets of the simplest population pressureargument. Now the only way to save such hypotheses is to argue thatsocioeconomic variables determine, with some precision, a certain levelof population density for a given resource base.Incidentally, although political data was not coded for this study, I findlittle support for Sahlins (1972: 131) contention that each political orga-


27/39

HUNTER-GATHERER ECONOMICS AND POPULATION PRESSURE 399nization harbors a coefficient of population density . . . a determinantintensity of land use (emphasis added). The atomistic Yurok showrelative population densities that are higher or the same as many groupsin central California and the Northwest Coast which have strong chiefspossessed of extra-local authority (see References Cited for references).There are many other counterexamples. This is not to deny that there isa positive relationship between density and political organization. How-ever, one may, with equal validity, claim that every population densityharbors a coefficient of political organization.But because population pressure is significantly correlated with someenvironmental variables, it cannot be said to be completely independent.Demography mediates between the environment and socioeconomic com-plexity. The most influential environmental variables are the relativeavailable productivity (LATAP) and continentality. The latter, as we ar-gued, is a measure of the variability of production. Paradoxically, popu-lation pressure is not a feature of poorer, less predictable environments.The environmental given explains about half of the variation in populationpressure which leads to the question of how these variables affect popu-lation pressure.In reading the ethnographies for this study, I received the impressionthat, outside of the humid tropics, simple hunter-gatherers were moresubject to Malthusian population controls than more complex groups.Table 7 shows data taken from a survey of North American groups fordata on the frequency of famines (which involve starvation deaths) amongvarious tribes. Famines and their attendant mortality occurred occasion-ally or even frequently in the interior subarctic, among Inland and CentralEskimo, among some Great Basin groups, very rarely on the Plateau, andwere extremely rare or never recorded in California, the NorthwestCoast, or coastal western Alaska. Such famines were brought on directlyor indirectly by climatic variation. In the north, too hard a freeze couldrestrict access to aquatic resources or too prolonged a thaw prevent themobility necessary for hunting. The regular and high-amplitude cycles inanimal populations in the north are well known and had their effect onhuman subsistence (e.g., HNAI 1981:317). While in the Great Basin,drought restricted the availability of both staple and supplemental plantfood (often the effects of drought on plant and animal abundance weredelayed a year). Annual variability of the pinyon crop is well attested(Steward 1938:27; Thomas 1972:674, 684-690). The famous Mongongonuts of the Kalahari may well follow similar patterns of extreme annualvariability. The greater magnitude of climatic variations meant that hu-man populations were trimmed by bad years with some regularity innontropical regions with low relative population densities. There is alsosome evidence that infant mortality rates were higher among simple


28/39

400 LAWRENCE H. KEELE YTABLE 7FREQUENCY OF FAMINE, CLIMATE, POPULATION PRESSURE,AND COMPLEXITY

Group Famine, CONT LNY COMPBeaver 2 - - - 1.8eHare 2d 67 -3.09 - 1.9eMountain 2 66 -3.51 -Dogrib 2 64 - 1.37 - 1.6Slave 2 62 -0.92 - 1.8eCaribou 2 61 -2.17 - 1.6Chipewyan 2 60 -0.59 - 1.8Naskapi 2 59 -1.84 -2.0Gosiute 2 52 -2.25 - 1.7eNunamiut 2 51 -1.11 -0.9Netsilik 2 49 -2.51 - 1.6eInuit 2 49 - 2.08 -1.2ePolar 2 47 -1.70 - 1.4Kaska 1 59Western Wood Cree 1 58Panamint/Koso 1 56Kotzebue S. Eskimo 1 46Kawaiisu 1 42Sanpoil 1 41Tareumiut 1 40Tubatulabal 1 37Chilocotin 1 37St. Law. I. Eskimo 1 35Klamath 1 32West Green. Eskimo 1 29

-0.94-1.63-1.120.18- 1.310.711.570.150.82-0.08-

- 1.4-1.8-0.5--0.92.10.80.7-0.0-0.2e

0.621.060.671.02-2.12

Washo 0 40 -0.8Cahuilla 0 38 2.0Shasta 0 38 1.0Maidu 0 30 1.3Nisenan 0 28 1.6eWintu 0 28 1.7Chimariko 0 21 1.3Nunivak 0 27 1.1Porno 0 24 1.9Wwpo 0 21 1.7eCahto 0 18 -Sinkyone 0 10 1.3Chumash 0 6 2.4Yurok 0 1 3.0Coast Miwok 0 1 -

0 Sources: HNAI 1984, 1981, 1978, 1986; Ray 1933; Spier 1930.* 2 = Famines, involving starvation deaths, common. 1 = Famines occasional or simplynoted as occurring. 0 = Famines very rare or unknown. Economic complexity scores (see above); e indicates an estimate.d Famines every 7 10 years, HNAIo 1981: 317.

-1.082.911.382.272.022.992.56-


29/39

HUNTER-GATHERER ECONOMICS AND POPULATION PRESSURE 401groups in continental climates in high latitudes (Laughlin 198O:ll). Thispresents something of a paradox for the population pressure argument:the most obvious sign of severe population pressure on food resources-periodic starvation-is most common in areas of the least socioeconomiccomplexity and rare or nonexistent among the more complex groups.We may ask whether starvation is a more effective impetus to socialand dietary innovation than the overwork that diminishing returns im-plies. If it is diminishing returns that begets socioeconomic develop-ments then the environmental conditions that divide simple and complexhunter-gatherers become interpretable. The environmental difference be-tween complex hunter-gatherers and their simpler counterparts is notpredictability per se but the amplitude of seasonal and year-to-year vari-ations. If we consider that human populations have inertia and cannot beadjusted via cultural means with anything approaching the speed withwhich the environment changes, then environments with sharp down-turns will apply less diminishing-returns pressure than less variable envi-ronments. Figure 6 shows what happens when slowly rising populationsmeet high-amplitude and low-amplitude falls in carrying capacity withparallel depressions of the point of diminishing returns. In the high-amplitude example, the population curve reaches carrying capacity, withdire Malthusian consequences, almost immediately after reaching thepoint of diminishing returns. At the end of the episode, when carryingcapacity again rises, the now reduced population is well below the line ofdiminishing returns and under no real compulsion to change. In the caseof a low-amplitude depression, the population remains for some timeunder the pressure of diminishing returns and.emerges from the episodestill close to the line. Under the latter circumstances it is much easier to

A -Fe.;.. \ .:.-.-\ .I-7

Y

i ik :.;I -;. ,!i.

FIG. 6. Schematic diagrams of the relationships between carrying capacity, the point ofdiminishing returns, and population density when the amplitude of a fall in carrying capacityis low (above) or high (below).


30/39

402 LAWRENCE H. KEELEYsee readaptation through dietary shifts to more reliable but more seasonalfoods that can be stored and the sedentism that such a strategy implies. Inshort, hunter-gatherers in highly variable environments of relatively lowproductivity were kept at the lowest densities by natural mortality andhad to operate at the highest mobilities over large territories to reducerisks.It is possible that populations among groups in the humid tropics werekept low by higher disease-related and infant mortality rates (Dunn 1968:225-228; Rose 1968:203-204) than found in higher latitudes or the driertropics.6Another environmental factor likely to be important is the availabilityof a storable food. Given that nonstorage economies are restricted to themost continental climates, the conditions for storage cannot be important.Desiccation and freezing are the two most common techniques used inpreparing stored food. Such environments are, by definition, during theseason of storage-winter-less humid and colder. It is the simple abun-dance and reliability of the resource that is essential. For example, manyof the Great Basin Shoshoneans alternated between a storage andnonstorage economy from year to year depending on the size of the pin-yon crop (Steward 1938; Thomas 1972) but the conditions for a prolongedstay at the winter village (as much as a whole year) could be met veryrarely, perhaps only once every decade (Thomas 1972:687). The interiorsubarctic regions are notably poor in seed crops and fish. In other words,groups in continental climates lacking large fisheries or seed crops couldnot make the adaptive shift to a storage economy when a depression in thepoint of diminishing returns made itself felt, even if they had time to reactbefore the depression in carrying capacity brought famine.There are some ethnographic and archaeological exceptions to theabove that are instructive. The Tareumiut Eskimo of Point Barrow live ina fully arctic continental climate but had a relatively complex economy.As mentioned above, their most important staple food was whale as wellas some other very large sea mammals. The Angmaksalik Eskimo ofGreenland also lived in a very poor arctic environment (although theclimate was more maritime) and indeed relied heavily on beluga and nar-whal. The archaeological exception appears to be the Upper Palaeolithicinhabitants of central and eastern European Steppe/Tundras (Soffer 1985)whose most obvious (if not necessarily most important) food source were

6 I am in the process of gathering and coding data on natural and cultural populationcontrols among hunter-gatherers. Preliminary results suggest that simple hunter-gatherersare more subject to natural population controls and only employ cultural controls, suchas infanticide, situationally under the stress of starvation. Complex hunter-gatherers, on theother hand, are less subject to natural controls and employ cultural controls in acategorical fashion (e.g., all twins killed, all first children killed, etc).


31/39

HUNTER-GATHERER ECONOMICS AND POPULATION PRESSURE 403mammoths. The tremendous amount of meat and, more importantly in ahigh protein diet, fat (Speth and Spielmann 1983) represented by just oneof these giant aquatic and terrestrial mammals would replace, in the dietof a domestic unit, very large quantities of seeds and fish. Particularlysince the cold, dry climate allows over-winter storage with very littlelabor investment in processing or storage facilities. One very large and,literally, fat package is as good as thousands of very small ones, if theclimate is cold and dry.The arguments given above imply that, outside the humid tropics, for-aging groups have no& made the transition to more complex socioecono-mies because they spend much of the time under conditions of low pop-ulation pressure as their populations are frequently trimmed by severefalls in carrying capacity, and possibly because their environments lackappropriate supplies of storable food resources.The relationship between population and critical resources-populationpressure-certainly tits the expectations of a necessary and sufficientcondition for economic complexity: when population density is in excessof a specific proportion of the gross available resources, socioeconomiccomplexity emerges and it never occurs unless this Rubicon has beenpassed (e.g., PM2/PPI > 0.1 or LNP/LAT > -0.03). The static datapresented here also indicates that the scales of population pressure andcomplexity are very closely correlated. The archaeological evidence,mentioned under the Introduction, indicates a very close dynamic rela-tionship between socioeconomic complexity and increasing populationdensity among prehistoric hunter-gatherers. Population pressure is still aforce to be reckoned with in the explanation of complexity among hunter-gatherers past and present.The argument of most proponents actually has been that populationpressure is the efficient cause of complexity and in some cases, its finalcause. The arguments of opponents have emphasized the importance ofthe material (i.e., psychological) and formal (i.e., structural) factors thatmotivate social action and structure human understandings of their cir-cumstances. Much pointless contention on these issues can be avoided ifthe distinction between efficient causes and other necessary factors ismaintained. Whether population pressure is the factor which impels so-cioeconomic change depends on its independence, which has been dis-cussed, but not resolved, above and its temporal priority, an issue unad-dressed by ethnography and beyond the current resolution of archaeol-ogy. But the simple recall of the Aristotlean typology of causes will notreconcile the contending parties, so long as adaptationalists imply that theruison detre of hereditary classes or strong chiefs is the amelioration ofpopulation pressure and transformationalists imply that demography andecology are irrelevant to the emergence of new socioeconomic forms.


32/39

404 LAWRENCE H. KEELEYCONCLUSIONS

The data compiled here indicate very clearly that population pressure,defined as the level of population density relative to available resources,is very closely correlated with economic complexity among ethnograph-ically known hunter-gatherers. Specifically, it has been demonstratedthat when the ratio between population density and available resources,as measured by latitude and edible ecological productivity, reaches acertain level, storage dependence, sedentism, wealth/class distinctions,and the use of primitive monies appear. Moreover, the intensity of thesetraits increases as the density/resource ratio increases. Thus, populationpressure fits very well the expectations for a necessary and sufficientcondition for and the efficient cause of complexity among hunter-gatherers.It has also been established that population pressure does not developin certain environments. Surprisingly, population pressure is a feature ofhunter-gatherers living in the more productive, more reliable environ-ments rather than those inhabiting the poorer, more variable regions. Itwas argued that it is the greater amplitude of variations in carrying ca-pacity in the latter environments that periodically trimmed populationsand prevented them from experiencing much of the diminishing returnsthat is the active principle in population pressure.Other results of significance include the partial correlations that suggestthat population density and sedentism are not directly related as muchprevious discussion suggests and that this relationship is mediated bydependence on stored foods. Partial correlation coefficients also indicatethat the relationship between the economic variables and the environmentare mediated by demography and are, therefore, indirect. The only ex-ception is the relationship between latitude and storage dependence-some storage of staple foods is practiced by almost all mid- and high-latitude groups but the degree of storage dependence is controlled byrelative population density. The general result of all the partial correla-tions was to demonstrate the central role of demography and its conse-quence, storage dependence, in all these relationships.It is also very clear from the bi- and trivariate plots that there areessentially two types of hunter-gatherers societies which might be termedsimple and complex. Table 8 summarizes their differences. The fact thatthere appear to be no transitional groups implies that such a state isunstable and that the transition itself is rapid.It appears that the unpopularity of population pressure explanations ofhunter-gatherer complexity, whatever the efficacy of such explanationsfor other levels of socioeconomy, has a very poor empirical basis. Itseems the current tendency away from adaptational hypotheses, partic-


33/39

HUNTER4ATHERER ECONOMICS AND POPULATION PRESSU RE 405TABLE 8

CONTRAST S BETW EEN SIMPLE AND COMPLEX HUNTER--GATHERERSSimple Complex

EnvironmentClimateVariabilityLatitudeDiet~mographyPopulationdensityDensity/

resourcel-i&i0FaminemortalityStorageResidentialmobilitySocialstratificationMedium of

exchange

Continental or humid tropicalHigh amplitude variationsAh latitudesHigh % of terrestrial animalsLower range of populationdensitiesLow population pressure

High Famines rare or unknownNo or little dependence onstored foodsNo more than S-month stay inpoor season camp or villageEgalitarian

Moderate to high dependence onstored foodsMore than S-month stay inpoor season camp or villageClasses based on wealth ordescentNone Standard valuables orcurrency

NoncontinentalLow amplitude variationsMid to high latitudes onlyFish or plants dominantHigher range of populationdensitiesHigh population pressure

ularly the simplest ones, has more to do with the winds of intellectualfashion than with scientific evaluation based on the weight of evidenceand Occams Razor.ACKNOWLEDGMENTS

This paper has been 3 years in the making and took on the guise of an obsession. Dis-cussions with a number of colleagues-James Brown, Robin Torrence, Malcolm Dow, GaryFeinman-have helped improve my analysis and line of argument and special thanks areextended to the facul ty and students of the Department of Anthropology, University ofWisconsin at Madison for a rousing discussion after my talk there on this data. I am gratefulto James Phillips, Bruce Gladfelter, Alan Kolata, and two anonymous referees for critiquingvarious drafts. Special thanks go to Douglas Price for a thoughtful commentary on the firstdraft and much encouwment. This work was partially supported by a grant from the UICDffice of Social Science Research which paid for the diligent checking of population esti-mates by my research assistant, Jennifer Blitz. Few of the above mentioned agree with thearguments made here and none of them are responsible for errors.

REFERENCES CITEDAmes, K.1981 The evolution of social ranking on the Northwest Coast of North America.American Antiquity 4637894305.


34/39

406 LAWRENCE l-l. KEELEYBaumhoff, M.1963 Ecological determinants of aboriginal California populations. University of Cal-ifornia Publications in American Archaeology and Ethnology 49:151-235.Beals, R., and Hester J.1974 Indian occupancy, subsistence and land use patterns in California. In Californiaindians, vol. 1. Garland Publishing, New York.Bean, L.1972 Mukats people: The Cahuilla Indians of Southern California. Univ. of Califor-nia Press, Berkeley.Bettinger, R.1982 Aboriginal exchange and territoriality in Owens Valley, California. In Contexts

for prehistoric exchange, edited by J. Ericson and T. Earle, pp. 103-127. Aca-demic Press, New York.Binford, L.1980 Willow smoke and dogs tails: Hunter-gatherer settlement systems and archae-ological site formation. American Antiquity 45:4-20.Binford, L., and W. Chasko1976 Nunamiut demographic history: A provocative case. In Demographic anthro-pology: Quantitative approaches, edited by E. Zubrow, pp. 63-143. Univ. ofNew Mexico Press, Albuquerque.Birket-Smith, K.1953 The Chugash eskimo. National Musseets Publikationsfond, Copenhagen,Black, L.1973 The Nivkh (Gilyak) of Sakhalin and the Lower Amur. Arctic Anthropologyl&1-106.Blundell, V.1980 Hunter-gatherer territoriality: Ideology and behavior in northwest Australia.Ethnohtstory 27103-l 18.Bronson, B.1975 The earliest farming: Demography as cause and consequence. In Population,ecology, and social evolution, edited by S. Polgar, pp. 53-78. Mouton, TheHague.Brown, J.

1985 Long-term trends to sedentism and the emergence of complexity in the Amer-ican Midwest. In Prehistoric hunter-gatherers, edited by T. D. Price and J.Brown, pp. 201-231. Academic Press, San Diego, Calif.Chard, C.1%3 The Nganasan: Wild reindeer hunters of the Taimyr Peninsula. Arctic Anthro-pology 1:105-121.Clastres, P.1972 The Guyaki. In Hunter-gatherers today, edited by M Bicchieri, pp. 138-175.Holt, Rinehart & Winston, New York.Cohen, M.1977 The food crisis in prehistory. Yale Univ. Press, New Haven.1981 Pacific coast foragers: AfBuent or overcrowded. In Afluentforagers, edited byS. Koyama and D. Thomas. Semi Ethnelogical Studies 9275-295.1985 Prehistoric hunter-gatherers: The meaning of social complexity. In Prehistorichunter-gatherers, edited by T. D. Price and J. Brown, pp. 99-119, AcademicPress, San Diego, Cali f.


35/39

HUNTER-GATHERER ECONOMICS AND POPULATION PRESSURE 407Cook, S.1955 The aboriginal population of the San Juaquin Valley, California. University of

California Anthropological Records l&31-80.1956 The aboriginal population of the North Coast of California. University o f Cali-forma Anthropological Records 16~81-130.1974 The aboriginal population of Upper California. Proceedings of the 35th Znter-national Congress of Americanists: 397403.1976 The conjZict between the California Indian and white civilization. Univ. of Cal-ifornia Press, Berkeley.Cooper, J.1946 The Yaghan. In Handbook of South American Indians, Vol. I , The marginaltribes, edited by J. Steward. Bureau of American Ethnology, Bulletin 148:81-106.Cowgill, G.1975 On causes and consequences of ancient and modem population changes. Amer-ican Anthropologist 77:505-525.Darwin, C.1909 The voyage of the Beagle. Collier & Son, New York.Downs, J.1966 The two worlds of the Washo. Holt, Rinehart & Winston, New York.Dunn, L.1968 Epidemiological factors: Health and disease in hunter-gatherers. In Man thehunter, edited by R. Lee and I. DeVore, pp. 221-228, Aldine, Chicago.Ellen, R.

1982 Environment, subsistence, and system: The ecology of small-scale social for-mations. Cambridge, New York.Elmendorf, W.1974 The Structure of Twana culture with comparative notes on the structure ofYurok culture. Research Studies on Washington State University a(3).Evan,I.1937 The Negrito of Malaya. Cambridge Univ. Press, Cambridge.Flannery, K.1976 The early Mesoamerican village. Academic Press, New York.Gould, R.1985 Now lets invent agriculture . . . In Prehistoric hunter-gatherers, edited by

T. D. Price and J. Brown, pp. 427-435. Academic Press, San Diego, CA.Grant, P.1890 The Saulteaux Indians vers 1804. In Les Bourgeois de la Compagnie du Nord-ouest: R&its de voyages, lettres et rapports intdit relatifs au nord-ouest cana-dien, edited by L. Masson, Vol. 2, pp. 306-366. A. Cot& Quebec.Grumet, R.1975 Changes in Coast Tsimshian redistributive activities in the Fort Simpson regionof British Columbia. Ethnohistory 22~295-318.Harris, D. R.1978 Settling down: An evolutionary model for the transformation of mobile bandsinto sedentary communities. In The evolution of social systems, edited by J.Friedman and M. Rowlands, pp. 401-417. Univ. of Pittsburgh Press, Pittsburgh.

Hayden, B.1981 Subsistence and ecological adaptations of modem hunter gatherers. In Omniv-orous primates: Gathering and hunting in human evolution, edited by R. S. 0.Harding and G. Teleki, pp. 344-421. Columbia Univ. Press, New York.


36/39

408 LAWRENCE H. KEELEYHenry, D.1985 Preagricultural sedentism: The Nat&an example. In Prehistoric hunter-

gatherers, edited by T. D. Price and J. Brown, pp. 365-384. Academic Press,San Diego.Hiatt, B.1%7-1968 The food quest and the economy of the Tasmanian Aborigines. Oceania 38:99-133, 19&219.Hiatt, L.l%S Kinship and conjhct. Canberra.Hitchcock, R.1987 Socioeconomic change among the Basarwa in Botswana: An ethnohistoricalanalysis. Ethnohistory 34(3):219-255.HNAI (Handbook ofNor?h American Indians)1984 Vol. 5, Arctic. Smithsonian Institution, Washington, DC.1981 Vol. 6, Sub-arctic. Smithsonian Institution, Washington, D.C.1978 Vol. 8, California. Smithsonian Institution, Washington, D.C.1983 Vol. 10, So&west. Smithsonian Institution, Washington, D.C.1986 Vol. 11, Great Basin. Smithsonian Institution, Washington, D.C.1978 Vol. 15. Northeast. Smithsonian Institution, Washington, DC.Johnson, G.1982 Organizational structure and scalar stress. In Theory and explanation in arche-ology, edited by C. Renfrew, M. Rowlands, and B. Seagraves, pp. 389-421.Academic Press, New York.Jones, R.1978 Why did Tasmanians stop eating fish? In Explorations in ethnoarchaeology,edited by R. Gould, pp. 11-47. Univ. of New Mexico Press, Albuquerque.Jorgensen, J.1980 Western indians. Freeman, San Francisco.Keeley, L.1982 Les vilages dhiver des chasseurs cueilleurs. Paper presented at CNRS Inter-national Colloquium: Les Habitats du Paleolithique Supetieur, Roanne.Kelly, I. T.1938 Southern Paiute ethnography. Anthropological Papers of the University of Utah

69.1978 Coast Miwok. In R. Heizer, Vol. Ed., Handbook of North American Indians,Vol. 8: California, pp. 414-425. Smithsonian Institute, Washington, DC.Kelly, R.1985 Hunter-gatherer mobility strategies. Journal of Anthropological Research39:277-306.King, c.1%9 Approximate 1760 Chumash village locations and population. Annual Reports ofthe University of Cafifornia Archaeological Survey ll(3).Koyama, S., and D. Thomas (editors)1982 Affluent foragers. Senri Ethnological Studies 9.Ktech, S.1978 Eastern Kutchin and the fur trade 1800-1860. Ethnohistory 23:213-235.Kroeber, A.1939 Cultural and natural areas of native North America. Univ. of California Press,Berkeley.


37/39

HUNTER-GATHERER ECONOMICS AND POPULATION PRESSURE 409Lantis, M.1946 The social culture of the Nunivak Eskimo. American Philosophical Society,

Transactions 35:153-323.Laughlin, W.1980 Aleuts: Survivors of the Bering Straits Lund Bridge. Holt, Rinehart & Winston,New York.Lee, R.1%8 What hunters do for a living, or how to make out on scarce resources. In Manthe hunter, edited by R. Lee and I. DeVore, pp. 3048. Aidine, Chicago.Lee, R., and I. DeVore (editors)1%8 Man the hunter. Aldine, Chicago.Lourandos , H.1980 Change or stability? Hydraulics, hunter-gatherers and population in temperateAustralia. World Archaeology 11:245-264.1985 Intensification and Australian prehistory. In Prehistoric hunter-gatherers, ed-ited by T. D. Price and J. Brown, pp. 385-423. Academic Press, San Diego,Cdif.McConnel, U .1930 The Wik-munkan Tribe of Cape York Peninsula, Part I. Oceania 1:97-104.Meigs, P.1939 The Kiliwa Indians of Lower California. University of California Publications inIbero-Americana 15:1-114.Mellars, P.1985 The ecological basis of social complexity in the Upper Palaeolithic of South-western France. In Prehistoric hunter-gatherers, edited by T. D. Price and J.Brown, pp. 271-298. Academic Press, San Diego, Calif.Murdock, G.1958 Social organization of the Tenino. Miscellanea Paul Rivet 1:299-312.I%7 Ethnographic arias. Univ. of Pittsburgh Press, Pittsburgh.1980 The Tenino Indians. Erhnofogy 19~129-149.1981 Atlas of world culrures. Univ. of Pittsburgh Press, Pittsburgh.Murdock

Hunter-Gatherer Economic Complexity and Population Pressure

Documents

Transcript of Hunter-Gatherer Economic Complexity and Population Pressure