Lewis R. Binford

From InterSciWiki
(Redirected from Binford, Lewis R.)
Jump to: navigation, search

Ben Marwick - LRB - Leslie Gordon Freeman Obit LESLIE GORDON ("LES") FREEMAN, born in September 1935, is a product of ... Binford. Freeman was among the first coterie of the so-called New Archaeology.

Biocultural Theory: The Current State of Knowledge

By Carroll, Joseph; Clasen, Mathias; Jonsson, Emelie; Kratschmer, Alexandra Regina; McKerracher, Luseadra; Riede, Felix; Svenning, Jens-Christian; Kjærgaard, Peter C. 2015. Biocultural Theory: The Current State of Knowledge. Evolutionary Behavioral Sciences.

Abstract: Biocultural theory is an integrative research program designed to investigate the causal interactions between biological adaptations and cultural constructions. From the biocultural perspective, cultural processes are rooted in the biological necessities of the human life cycle: specifically human forms of birth, growth, survival, mating, parenting, and sociality. Conversely, from the biocultural perspective, human biological processes are constrained, organized, and developed by culture, which includes technology, culturally specific socioeconomic and political structures, religious and ideological beliefs, and artistic practices such as music, dance, painting, and storytelling. Establishing biocultural theory as a program that self-consciously encompasses the different particular forms of human evolutionary research could help scholars and scientists envision their own specialized areas of research as contributions to a coherent, collective research program. This article argues that a mature biocultural paradigm needs to be informed by at least 7 major research clusters: (a) gene-culture coevolution; (b) human life history theory; (c) evolutionary social psychology; (d) anthropological research on contemporary hunter-gatherers; (e) biocultural socioeconomic and political history; (f) evolutionary aesthetics; and (g) biocultural research in the humanities (religions, ideologies, the history of ideas, and the arts). This article explains the way these research clusters are integrated in biocultural theory, evaluates the level of development in each cluster, and locates current biocultural theory within the historical trajectory of the social sciences and the humanities. (PsycINFO Database Record (c) 2015 APA, all rights reserved)

Duran Bell

Binford p223 re the 339 foragers: "warfare and sociopolitical complexity appear correlated with h-g groups that also appear to be operating from an expansionist imperative." See generalization 7.17

For Bell introduction:

    ***

Because Bell’s marginal value of fertility is a new empirical construct that supports his view that a positive value of fertility for foragers able to expand their territory, its effect on demographically expansive foragers would lead to retention of daughters by the natal kin-group, hence what Binford (2001) calls matribias or some form of matrilineality. In this situation, he also hypothesizes that forager groups under these conditions will be territorial, which Binford (2001:426) codes in his sample of ethnographically described foragers in three categories: Generally defensive through avoidance rather than active defense (n=125), tit-for-tat (n=157), Tit-for-tat (n=157), and Generally aggressive (n=54). Higher values of this variable (coded 1-3), when multiplied by a 4-point scale for degree of territoriality as measured by ownership of resource locations (Binford 2001:426), are one of the predictors of matrifiliality among foragers (n=38, coded 3), with patrifiliality coded 2 (n=78) and the remaining foragers (n=223) coded 1. The other predictor of matrifiliality is the percentage dependence of terrestrial plants (Binford 2001:117). The predictors of matrifiliality – aggressive defense in holding resources through territoriality – are consistent with Bell’s arguments. Of the three levels of bias in “kinship structure as regards the side which is extended more or keyed upon cognitively for discussing exogamy,” compared to the preponderant cases of low bias, and patribias, matribias is numerically weakest. Because this evidence from extant foragers shows that the cases of matribias are exposed to a high degree of attack from other foragers (others seeking their land and resources), they are probably the most exposed to warfare and most likely to undergo decline and shrinkage of well-defined and defended territory.

Subsetted sample

Amber: In CFR regression equations were run using both the full 339 case file and the 142 case sample. Lew discusses the 142 case sample in detail in Chapter 5 of CFR. Where he introduces this sample (p. 144) he describes it as “a subset of those cases designed to correspond as closely as possible to the proportions of the earth’s surface covered by the twenty-eight different plant communities adapted in this study from Eyre’s classification (1968).” These cases were selected to be a proportional sample of hunter-gatherers from vegetation types,

Anthon: For subsetting, make a copy of the dependent variable, and set all values OUTSIDE the subset to missing.

dx$gath1<-dx$gatherin
z<-which(dx$hg142!=1)
is.na(dx$gath1[z])<-TRUE
  • then run everything as usual, with dx$gath1 as the dependent variable.

Overview: -lewis-binfords-population-pressure-or-equilibrium-theory

Ricardo Luz. 2015. Lewis Binfords Population-pressure-or-Equilibrium-theory: An Overview. Archaeology 323 ... and when and how agriculture originated was of interest to the newly graduated Lewis Binford, who introduced ... For Binford, these two would be the key elements required to apply his theory, not only in ... Crescent or the Near East for evidence of the shift from food foraging to food ...

Biocultural Evolution Blog

https://blogs.emory.edu/bioculturalevolution/2013/06/08/more-on-the-origins-of-biocultural/

Publications

  • Binford, Lewis R. 2001. Constructing frames of reference: An analytical method for archaeological theory building using hunter-gatherer and environmental data sets, University of California Press.
  • Binford, Lewis R. 1999. Time as a Clue to Cause? Proceedings of the British Academy 101:1-35. OXFORD UNIVERSITY PRESS INC. Not available online.

2001 Bibliography (in Excel) and finding missing references

  1. 3-3 Kubu: p507 B. Hagen. 1908. See: http://nirc.nanzan-u.ac.jp/publications/afs/pdf/a475.pdf
  2. 56-56 Mikea: Robert Kelly 1990?
  3. 70-92 Kaurareg: Haddon 1903?
  4. 201-218 Reese River Shoshone: D. Thomas 1983

Reviews

Steele, J., M. Gkiasta and S.J. Shennan. The Neolithic transition and European population history - a response. Antiquity 78: 711-713.

Shennan, S.J., (2004). Forty Years On: Review of Lewis R. Binford, Constructing Frames of Reference. Journal of Human Evolution 46: 507-515. (review article)

Michael J. Shott. 2002. Constructing frames of reference: an analytical method for archaeological theory building using ethnographic and environmental data sets. Antiquity 76(291): 266–268.

Arguably the most prominent 20th-century American archaeologist, Lewis Binford secured his reputation by decades of vigorous research devoted to how the record formed and how thereby to learn about the past. His new book (CFR) has archaeological implications, pursued in passages on the Near Eastern and other Neolithic records, but is a detailed study of 390 ethnographic hunter-gatherer cultures. CFR takes the sound view that the range of documented variation holds clues to the transformation of past hunter-gatherers. Binford's 1978 Nunamiut ethnoarchaeology partly extended arguments about Paleolithic assemblage variation advanced in the 1960s. CFR is perhaps Binford's most sustained argument yet, extending his 1968 `Post-Pleistocene adaptations' on hunter-gatherer tendency to agriculture and social complexity.

Binford's familiar style has not changed. He remains fond of neologisms (scatterplots are `property space maps', regressions `relational projections') and retains his argumentative flair. Apart from the style, a book so ambitious and important deserved much better editing for organization and continuity, especially from a major university press. Figures carry much of Binford's argument, yet many comparisons are invited between figures that plot different variable ranges or that are cluttered by shading that hampers scrutiny. CFR includes several lengthy data tables, grist for many analytical mills. Yet some listed variables are not defined for 20 pages or more after tables' appearance and some not at all, so far as I could tell. I still do not know what table 9.01% `COMSTFUN' is. Throughout, Binford creates many codes, ratios and other legitimate variables but rarely reports them by case (e.g. his packing index). CFB's scope makes it difficult to report all variables by case, but appendices could list more of them.

A synopsis at once summarizes the argument and identifies editorial and analytical problems. Chapter 4 explores the complex ecological relationship between climate and biota, culminating in regression estimates of secondary biomass, itself figuring in chapter 6's baseline `terrestrial model' of diet and population. Such a baseline highlights the ecological character of aquatic resources which, to Binford, explain much of the evolutionary potential of hunter-gatherers. Chapter 5 gauges sample representativity. Obviously, cases are biased in geographic distribution but less severely and more subtly when viewed against ecological zones. Cases are few in arid habitats and some game-rich temperate ones where agriculture now dominates. Binford concludes that hunter-gatherers largely avoided deserts and that agriculture arose in game-, not plant-rich, habitats. Persuasive and original, chapter 5 nevertheless contains editorial glitches that foreshadow later problems. The same variable is labelled differently in figures 5.06 and 5.13; particular figure 5.06 cases are discussed at length in the text but not identified in the figure; one point there seems not to correspond to any pair of values in the accompanying table, another is identified by a label that appears nowhere in that table; slight differences between two figure 5.10 maps are exaggerated, the chief reason for preferring one its `greater correspondence [to] what I accept as true' (p. 148), and tables 5.04 and 5.06 disagree in area covered by two vegetation zones. Binford parses figure 5.06 to argue positive correlation between number of hunter-gatherer cases and proportional size of global vegetation zones. This exercise is not justified statistically and the overall relationship seems negative, not positive.

sketching the four types of ecologies in ratios of plant density and forager density. Might these have to do with the plots in Project_2012#work_on_ecological_W_matrix?

(Marked for study by DRW: they are mutually exclusive overally, but he breaks them up. Insofar as I can find, Binford never says what Schott attributes. Instead he attributes of a positive correlation to types 2&3 but 1&4 are orthogonal. One must examine Tables 5.05 and 5.06 and Figure 5.06 to get the right answer. Binford's description is equivalent to controlling for the Hunter/Vegetation ratios. In types 1&2 hunters are high, vegetation is low, in types 3&4 hunters are low, vegetation low to high. More specifically types 1&2 have a much higher percentage of hunters than plants in the territory (4 to 1), while 3&4 have a ratio of 2 to 3 fewer hunter percentages than plants.).

Chapter 6 presents Binford's terrestrial model linking food supply to hunter-gatherer population. Calculations are remarkably involved, not a criticism, but certainly a difficulty. Two readings did not make clear why productivity is divided by 6300 in Eqn. 6.08a but by 63,000 in Eqn. 6.08b, nor why Step 2 changes between Eqns. 6.06 and 6.07. Binford estimates human population supportable by available plants and animals, whose abundance in turn is estimated from ecological data. These figures are integral to subsequent arguments about packing, intensification and culture change. Chapters 7-8 relate group size and mobility. For a subset of cases, figure 8.15 plots a group-size measure against annual distance travelled. Binford sees a threshold c. 400 km/year `below which groups making residential moves show a high variance trend toward reduced [group] size with increased distance moved' (p. 269). Above 400 km, group size `increases as the distance moved increases' (p. 269). The distribution of cases does not obviously follow the pattern claimed. Identifying most cases is impossible; one nearby table reports distance travelled in miles (the figure shows it in kilometres), another group size. Turning back 158 pages, another reports both quantities but nowhere is the subset of plotted cases identified. An hour's attempt to identify the seven least-mobile cases by estimating relevant values from the figure and cross-referring them to the table yielded ambiguous results; as few as six, as many as eight cases might match the estimated values. Abandoning the effort, I estimated values for the 29 cases directly from figure 8.15, then plotted and analysed results. My plot was not identical to figure 8.15 but near enough to test Binford's interpretation. Surely, if cases below 400 km travelled patterned inversely and those above that value positively with distance, estimated data should show this. Correlations were not nearly significant. There seems no statistical basis for the pattern adduced.

Chapter 9 examines Gregory Johnson's scalar-stress concept. There is not the clear demonstration claimed that six is the upper limit for number of risk-pooling units. Figure 9.04b is cited extensively but never appears, 9.04a instead mistakenly printed twice. Figures 9.07a-b use different symbols to represent the same ordinal classes, which hinders the comparison invited. Chapter 10 relates population to intensification (increased returns per unit area). Binford's key measure is a `packing index' found by dividing density by a constant derived from earlier analysis of territory and group size. Figure 10.03 plots a group-size measure against this index for plant-dependent cultures. To Binford, the relationship is `very obvious' if complex; shading suggests that group size declines, then rises, then bifurcates -- some cases rising, others declining -- with the index. None of these trends nor the thresholds defined by them are validated statistically, nor do they seem especially obvious. Similar treatment of similar plots involving these and other cases did not persuade that `packing appears to structure all of the previous relationships' (p. 377) involving group size.

Chapter 11 examines the correlation between diet diversity and population density and the relationship's implications for agricultural origins, but does not use the packing index that served in lieu of density in chapter 10. In plots of various cases, it claims threshold values of both variables at which their relationship changes abruptly. Such patterns suggest emergent properties, rapid culture change from complex interaction between causes. Thus, Binford sees `internal intensification ... related to density-dependent shifts and the synergistic interaction of limitations and changed potentials' (p. 433) as the route to agriculture. This may be true, but again the argument relies on subjective parsing of scatterplots. Figure 11.01 plots log-population density against diet diversity. Overall, the scatter is ambiguous but shading suggests a point of inflection. This rests on one case that shading must reverse to cover and on an unconvincing subdivision of a single, amorphous distribution. Figure 11.11 plots figure 11.01's variables for two subsets of cases. Now the size, pattern and placement of shading suggest no inflections but, for one subset, a diamond pattern. Diamond shading recurs in subsequent figures (e.g. 11.12, 11.15) even though many cases fall outside it and much shading is devoid of cases. Thus, shading identifies a `nearly perfect' (p. 435) diamond pattern that seems instead a very imperfect circle, itself suggesting no correlation between the variables.

Chapter 12 argues that hunter-gatherer culture change is triggered by thresholds of population density acting upon existing cultural states. The view melds population pressure with concepts of self-organization; Binford sees abrupt `flashpoints of change' (p. 437). His examination of terminal Pleistocene Near Eastern cultural sequences attributes most change to environment and population: `all historical variety arose ... from an antecedent set of density-dependent responses to packing' (p. 462). Some passages seem contradictory. Binford says `population pressure (as it is usually conceived) probably does not contribute very much to ... the appearance of horticulture and other adaptive changes' (p. 437); but `packing -- or the patterned reduction in subsistence range arising from a regional increase in population -- is a universal conditioner of change in both subsistence strategies and the labor base' (p. 442).

Binford's reputation and scholarship invite high expectations. CFR is admirably ambitious and Binford's diligence is beyond question; compiled data alone will serve many analytical purposes. His theoretical view is nuanced, no brief for crude environmental or population determinism but an argument that incorporates history, detailed ecological modelling and attempts to explain emergent change. Editorial gaffes are merely distracting and, in a book the length of CFR, perhaps inevitable. But throughout, analysis rests on subjective interpretation of evidence. CFR suggests much, and is worth reading for this reason, but does not persuade of its chief theses.

Binford's view on the critical role that population plays in social change begs an obvious question -- what causes population to rise? -- but is not invalid for that reason. Yet besides the anthropological theory that stipulates such relationships we must attend to the archaeological method and theory needed to measure population from the record. Even now, we measure population trends crudely by, for instance, site counts per unit of time or subjective comparisons of quantities of remains between periods. To ground theory that specifies far-reaching consequences of sometimes subtle population trends, casual methods will not do. As much as anything, CFR demonstrates the need for more serious thought to how the record formed and how to interpret it, not just how and why hunter-gatherer cultures changed over time.

References

BINFORD, L.R. 1968. Post-Pleistocene adaptations, in S.R. & L.R. Binford (ed.), New perspectives in archeology: 313-41. Chicago (IL): Aldine.

1978. Nunamiut archaeology. New York (NY): Academic Press.

Bibliography for: "Constructing frames of reference: an analytical method for archaeological theory building using ethnographic and environmental data sets"

Michael J. Shott "Constructing frames of reference: an analytical method for archaeological theory building using ethnographic and environmental data sets". Antiquity. FindArticles.com. 02 Apr, 2012.

COPYRIGHT 2002 Antiquity Publications, Ltd.


George Odell. 2001. Review? Research Papers R Us.

Binford

Lewis R. Binford. 1971. Mortuary Practices: Their Study and Their Potential Memoirs of the Society for American Archaeology No. 25, Approaches to the Social Dimensions of Mortuary Practices (1971), pp. 6-29. Published by: Society for American Archaeology.

Lewis R. Binford. 2004. Chapter 1: Beliefs about Death, Behavior, Mortuary Practices. In, Explaining social change : studies in honour of Colin Renfrew / edited by John F. Cherry, Chris Scarre & Stephen Shennan.

Subjects: Renfrew, Colin, 1937-; Social archaeology.

Contents:

  • Chapter 1 Beliefs about Death, Behaviour, and Mortuary Practices among Hunter-gatherers: a Search for Causal Structure? 1

LEWIS R. BINFORD

  • Chapter 2 Social Archaeology and the Unfinished Business of the Palaeolithic 17

CLIVE GAMBLE

  • Chapter 3 Stage 3 Climate and the Upper Palaeolithic Revolution in Europe: Evolutionary Perspectives 27

PAUL MELLARS

  • Chapter 4 Neo-thingness 45

IAN HODDER

  • Chapter 5 Fractal Farmers: Patterns of Neolithic Origin and Dispersal 53

ANDREW SHERRATT

  • Chapter 6 An Overview of Neolithic Settlement Patterns in Eastern Thessaly 65

MATS JOHNSON & CATHERINE PERLtS

  • Chapter 7 Figuring Out Social Archaeology at Sitagroi 81

ERNESTINE S. ELSTER

  • Chapter 8 Towards an Island of Mind? 93

CAROLINE MALONE & SIMON STODDART

  • Chapter 9 A Choreography of Construction: Monuments, Mobilization and Social Organization in

Neolithic Orkney 103 COLIN RICHARDS

  • Chapter 10 Now You See It, Now You Don't: Changing Obsidian Source Use in the

Willaumez Peninsula, Papua New Guinea 115 ROBIN TORRENCE

  • Chapter 11 Island Prehistories: a View of Orkney from South Uist 127

MIKE PARKER PEARSON

  • Chapter 12 Hail to the Chiefdom? The Quest for Social Archaeology 141

ANDREW FLEMING

  • Chapter 13 The Development of an Island Centre: Urbanization at Phylakopi on Melos 149

TODD WHITELAW

  • Chapter 14 Stating Identities: the Use of Objects in Rich Bronze Age Graves 167

MARIE LOUISE STIG SORENSEN

  • Chapter 15 The Role of Exchange Relations in the Origins of Mesopotamian Civilization 177

JOAN OATES & DAVID OATES

  • Chapter 16 Cycles of Collapse in Greek Prehistory: the House of the Tiles at Lerna

and the 'Heroon' at Lefkandi 193 JAMES WHITLEY

  • Chapter 17 Before Devanika: Social Change and State Formation in the Mekong Valley 203

CHARLES HIGHAM

  • Chapter 18 Aegean Islands and Islanders 215

CHRISTOS DOUMAS

  • Chapter 19 Aphrodite Observed: Insularity and Antiquities on Kythera through Outsiders' Eyes 227

CYPRIAN BROODBANK, JOHN BENNET & JACK L. DAVIS.

Marcus Hamilton calculated Binford branching ratios in xls for 339 foragers

  • /LRBcodebook.html: branchat ratios
  • branchrat. Horton-Strahler branching ratio, produced as slope in regression (Hamilton et al. 2007:2197)

MarcusBinfordbranchingratios.xlxs

Here is a spreadsheet of the branching ratios. Column N is the regression estimate of the average branching ratio across the levels of a single society. Columns O-S are the individual branching ratios between each level of the society, and column T is the average across these branching ratios. So, columns N and T are different estimates of the same quantity.

In response to (Drw:)

Would it be possible to send me these six numbers for each society in a 339 case csv and also the fractal number for each? We could merge that with the main *csv:

Quote from your article: "Hunter-gatherer group sizes, g, can be assigned to hierarchical organizational levels (Johnson 1982; Kelly 1995; Binford 2001). In Horton analysis, these levels are termed Horton orders, u, from the first-order terminal units to the highest order, U. We followed Binford (2001) in recognizing six levels defined as follows: g1, single individuals (total pop); g2, families estimated by dividing total population size by the number of married males, a common technique for estimating family size (famsz) in the absence of specific demographic data; g3, dispersed extended family groups defined as the average size of residential groups during the most dispersed phases of the mobility cycle (grp1); g4, aggregated groups defined as the average size of residential groups during the most aggregated phases of the mobility cycle (grp2); g5, periodic aggregations defined as multi-group socio-economic aggregations occurring at periods usually greater than every year (grp3); and gU, regional populations defined as the total size of regional ethnic units (definitions taken from Binford (2001))." drw: parentheses.

============================================================
SOURCE: Hamilton, M. J., Milne, B. T., Walker, R. S., Burger, O., & Brown, J. H. (2007). The complex structure of hunter-gatherer social networks. Proceedings of the Royal Society B: Biological Sciences, 274(1622), 2195-2203.  
doi:10.1098/rspb.2007.0564
-----------------------------------------------------------

numfam. Number of families in society (Equation: tlpop/famsz) (Hamilton et al. 2007)
Class=numeric; Type=ordinal; Number non-missing=128; Number of unique values=126
Stat    Value
nobs    128
mean    277.27
min    7.5
max    3153.2
sd    401.6

numg1. Number of group1 units in society (Equation: tlpop/group1) (Hamilton et al. 2007)
Class=numeric; Type=ordinal; Number non-missing=227; Number of unique values=196
Stat    Value
nobs    227
mean    82.964
min    2.4
max    1250
sd    129.502

numg2. Number of group2 units in society (Equation: tlpop/group2) (Hamilton et al. 2007)
Class=numeric; Type=ordinal; Number non-missing=297; Number of unique values=217
Stat    Value
nobs    297
mean    27.589
min    1
max    371.3
sd    36.91

numg3. Number of group3 units in society (Equation: tlpop/group3) (Hamilton et al. 2007)
Class=numeric; Type=ordinal; Number non-missing=216; Number of unique values=117
Stat    Value
nobs    216
mean    8.102
min    0.1
max    107.1
sd    11.25

branchrat. Horton-Strahler branching ratio, produced as slope in regression (Hamilton et al. 2007:2197)
Class=numeric; Type=ordinal; Number non-missing=339; Number of unique values=208
Stat    Value
nobs    339
mean    3.868
min    1.93
max    6.85
sd    0.896

Read about

Data

  • .Rdata file --> has latitude/longitude for conversion into W matrices; language families available from the Ethnographic Atlas, when indexed for Binford's data. Binford himself did not consider peer effects of distance or language.

Map

Pages from Marlow hunter-gatherers and human evolutionMap.png

What Binford says about Egalitarianism

  • p467-468 LONG QUOTE, esp.: "non-packed hunter-gatherers do not live in societies in which equal 'rights' are assured by the society. Rather, in their social world, trust and respect are built apon the lifelong associations and interactions of individual members. Persons who are not considered trustworthy or 'respectable' by the community may be denied not only equal access to resources but even their very right to exist, which is hardly compatible with the idea of an egalitarian society in which all individuals have rights to the cororately shared largesse."
  • p.38 classifications such as those on p.211 "--such as kin-based, egalitarian, based on mutual sharing of the products of lablr (Gould 1981:434) and on the communal use of goods and resources (Lee 1980), typified by family-centered economics (Service 1966:8) or mode of production (Sahlins 1972:41-99)-- can be seen for what they really are: different organizational features requiring an explanation rather than essential properties of hunter-gatherer system-states."
  • p.211: "more discriminating classifications .... Two well-known ... bands, tribes, chiefdoms, and states (Service 1962) or as egalitarian, ranked, stratified and state-level systems (Fried 1967)."
  • fn 6 p490: "The term 'egalitarian' makes sense only relative to stratified systems with centralized, authhoritarian, power-based decision-making. A more appropriate term for generic hunter-gatherers is nonstratified or nonranked.

What Binford says about Polygyny

  • fn 3 p490: "wide inter-household spacing in camps is related to high levels of polygyny.... [all resettled ... pressured by missionaries to give up polygyny] .... Only one polygynous group is known that maintains right camp cpacing (Altman 1997:29), but the level of polygyny and the nature of the risk-pooling associations have not been well documented."

Binford codes

Matt Grove. 2009. Hunter–gatherer movement patterns: Causes and constraints Journal of Anthropological Archaeology, Volume 28, Issue 2: 222-233.

crr: The two climatic variables employed are effective temperature (ET) and mean annual rainfall (MAR; equivalent to Binford’s ‘CRR’), and are taken from Binford (2001, pp. 60–67). ET was designed by Bailey as “a scale that would adjust warmth and length of summer together” and thus “admits a bias towards biological connections” (Bailey, 1960, p. 2) such as the reactions of plants to the length of the growing season. This in turn affects primary consumers and has repercussions at all higher trophic levels. MAR(=CRR) is the most basic and reliable of Binford’s (2001) precipitation measures and is therefore taken as the second major constraint on habitat quality. Higher values of both these measures are indicative of higher habitat quality. Finally, Binford (2001, pp. 118–129) gives data on the average number of residential moves per year (NOMOV), and the estimated total distance that these moves collectively represent per year (DISMOV). From these, average move distance (AMD) was calculated as DISMOV divided by NOMOV, and average occupation duration (AOD) as 365 divided by NOMOV. The independent variables entered into the following regression analyses therefore were G1, G2, G3, ET, MAR, and AOD; the dependent variable in all cases was AMD. All variables were log-transformed to base 10 prior to analysis; pre- and post-transformation histograms are provided for the hunting, gathering and fishing subsistence groups as Supplementary online material. In no cases do log-transformed data distributions differ significantly from normal distributions.

At this point, it is important to note a vital caveat relating to the nature of the data employed in the subsequent analyses. There is currently no adequate method available with which to control for the effects of phylogenetic inertia on the correlations presented in the results section below. Ideally, one would include in the analyses only those relocation pattern changes that arise from independent evolutionary events, rather than those that are potentially the result of shared ancestry. There is a substantial and sophisticated literature on the use of such independent contrasts in biology ( [Harvey and Pagel, 1991] and [Forsdyke, 2007]; Hansen et al., 2008; O’Connor et al., 2007; Welch and Waxman, 2008), where the appropriate phylogeny of a comparative sample would be employed as a pre-analysis filter to ensure that data points are independent. Unfortunately, no such phylogeny exists for the current data set, and what data can be gleaned from linguistic records are insufficient for this purpose. This is a substantial problem in hunter–gatherer research; due to the lack of an appropriate phylogeny, all landmark studies have thus far performed analyses on data that have not been subject to phylogenetic correction (e.g. [Binford, 2001], [Hamilton et al., 2007a], [Hamilton et al., 2007b], [Kelly, 1983], [Kelly, 1992], [Kelly, 1995], [Marlowe, 2005] and [Marlowe, 2007]). It would be highly beneficial were such a correction available in a form applicable to such data particularly since, in the absence of such a correction, no precise conclusions regarding the extent to which mobility strategies are the result of common descent rather than adaptation to a common environment are strictly possible. Ongoing research into this area may prove fruitful, but in terms of the current analyses, my approach follows that of Marlowe (2005, p. 55) in asserting that “the full range of variation and central tendencies” are our principal concerns, and that such measures are likely to be of great importance “even though there is no satisfactory phylogeny yet”.


Abstract: The study of hunter–gatherer mobility patterns is of vital importance to our understanding of the paleolithic archeological record. Such patterns necessarily comprise many interacting locales, and it is at the landscape scale that we should attempt to understand the relationship between ethnographic and archeological data. This paper derives, quantifies and tests a series of basic predictions about the effects of group size, occupation duration and habitat quality on mobility strategies using a substantial ethnographic dataset. The results demonstrate that habitat quality is the best determinant of move distances among hunter–gatherers, but that occupation duration also has an effect among those foragers who rely principally on hunting. It is suggested that three roughly concentric zones, the limit of scatter, the foraging radius, and the logistic radius, are predicted by group size and occupation duration, habitat quality, and proportions of hunting and logistical mobility, respectively. The relevance of these conclusions to more generic ecological theory is discussed in the context of evolutionary forces acting on hunter–gatherer mobility in prehistory.

Keywords Hunter–gatherer; Mobility; Group size; Occupation duration; Habitat quality; Ecological constraints; Fission–fusion; Foraging radius; Logistic radius; Site size