Hamilton et al. (2007) Complex structure of hunter-gatherer social networks

Hamilton MJ, Milne BT, Walker RS, Burger O, & Brown JH (2007) The complex structure of hunter-gatherer social networks. Proceedings of the Royal Society B 274, 2195-2202.

The big idea:

• Groups adjust their group size and organization in response to spatial and temporal variation in resource variation.
• The space required by an individual to meet metabolic demand decreases in larger populations, introducing an important economy of scale where population level energetic efficiency increases with population size (Hamilton et al. 2007).
• Hypothesis: this scaling relation results from the complex structure of underlying social networks, which serve to redistribute resources (such as energy, materials, and information) within the environment to group members.
• In this paper, the hypothesis is investigated by looking at the structural organization of hunter-gatherer societies.

 Getting into it:

Human social groups form a hierarchy of discrete group sizes with a constant scaling ratio of ~3 (Zhou et al. 2005).
Questions:
1.     Do we find similar scaling relations in hunter-gatherers?
2.     If so, how do these scaling relations vary across societies?
3.     What mechanisms might be hypothesized for such scaling relations?

Hierarchical networks:

• Common in nature, often exhibit self-similar scaling properties.
• Complex systems tend to self-organize or evolve structures that maximize whole-system performance by optimizing interactions among components.
• In hierarchical systems, these optimal networks are self-similar and fractal-like.
• Distribution of material or energy is optimized by minimizing network size and resistance.
• Self-similar or fractal networks are characterized by constant ratios across successive levels and power-law distributions. (I NEED TO READ UP ON THIS)
• Empirical examples of fractal-like networks:
• Branching tributaries in river drainages
• vascular systems of animals and plants.
• Analogously, self-similarity in human societies may have evolved to optimize the acquisition and distribution of fitness-related resources to group members.

Hierarchical networks in human societies:

• Many contemporary human social systems form social networks where individuals are connected to each other at multiple levels of organization. A number of examples are given.
• Does this occur in hunter-gatherer societies? They suggest it does.
• The network arises from interactions and exchanges of energy, material, and information in the context of a hierarchical group structure.
• The structure is constrained externally by seasonal variation in local ecological conditions.
• The structure is constrained internally by human life history.
• Examples of energy and material flow: food resources, trade goods, and raw materials for tools, clothing and shelter.
• Examples of information transfers: gene flow through reproduction and the exchanges of culturally transmitted information through language and other signals.

Traditional hunter-gatherer societies exhibit hierarchical structures.

• Individuals are nested within nuclear families, formed to provide parental investment to dependent offspring.
• Families fission and fuse to form larger residential foraging groups, which increase the rate and decrease the variance of resource acquisition, and which change in size and composition in response to environmental changes.
• These extended families are members of still larger groups that are dispersed over larger areas and interact with decreasing frequency, but serve to maintain social ties, conduct trade and information exchange, perform ceremonies, and exchange marriage partners (NOTE: related to Moffett’s idea of the anonymous society).

If hunter-gatherer social organization as a whole form self-similar structures, then this may reflect self-organization to optimize energy, material and information flow among group members.

The Data Set

They used the Binford (2001) data set, which represents 339 hunter-gatherer societies, and contains estimates of group sizes at multiple levels of organization.

For analysis, they used generalized Horton laws – a statistical approach designed to characterize the quantitative structure of hierarchical branching networks. (NOTE: CHECK THIS OUT).

How it works:

Hunter-gatherer group sizes, g, are assigned to hierarchical organization levels.

These levels are termed Horton orders, ω, from the first-order terminal units to the highest order, Ω.

They recognize the following six levels:

g1: single individuals.

g2: families, estimated by dividing the total population by the number of married males.

g3: dispersed extended family groups, the average size of residential groups during the most dispersed phases of the mobility cycle.

g4: aggregated groups, the average size of residential groups during the more aggregated phases of the mobility cycle.

g5: period aggregations, multi-group socio-economic aggregations occurring at periods usually greater than once per year.

gΩ: regional populations, the total size of regional ethnic units (from Binford, 2001).

The branching ratio, B, is defined for a population i at each order, and is the number of groups at order ω – 1 divided by the number of groups at order  ω.

The network is self-similar if the branching ration is constant between all levels.

They do some cool math with the data to show that that the branching ratios of the hunter-gatherer populations are self-similar. Societies are classified by continent. There is some small variation in branching ratios. Australia has a particularly high one, and this is hypothesized to be due to high levels of polygyny in aboriginal societies.

 Discussion

This model has two important implications: (i) the branching ratio is a function of density-dependent reproduction in hierarchically structured populations and (ii) family-based relationships ramify in a hierarchical self-similar fashion up through the network. The second point is consistent with extensive ethnographic observations, where individuals move through social networks as families rather than individuals per se, which fuse into residential groups of multiple families to exploit resources efficiently, and fission along similar family lines to avoid conflict and inter-personal tension (e.g. desert aborigines (Gould 1969), Mbuti ( Turnbull 1965), San ( Tanaka 1980, 1989)).

Group dynamics are governed by two kinds of forces:

cohesive forces that tend to draw and hold individuals together

disruptive forces that tend to pull individuals apart and create barriers to exchanges between them.

Examples of cohesive forces in hunter-gatherer groups include kin selection due to genetic relatedness, sharing of non-genetic material, and exchange of material resources.

There are also cohesive forces that extend to larger groups at higher levels of the societal hierarchy. These include exchange of marriage partners (to avoid inbreeding), communication about social and environmental conditions, and exchange of material resources through trade and commerce.

Examples of disruptive or antagonistic forces include competition for material resources and for mates, interpersonal conflict, and disease epidemics.  The intensity of competition, the balance between mutualistic and antagonistic interactions, and the probability of disease outbreak all increase with increasing group size. Individuals therefore aggregate into successively larger groups with successively decreasing frequencies and only for specific purposes, such as exchange of marriage partners, trade in goods that are not available locally, and defense against or competitive aggression (e.g. warfare) towards other higher-level groups.

A suggestion is that genetic relatedness, exchanges of non- genetic information, and flows of material resources, may scale similarly throughout the social hierarchy. If true, self-similarity has profound implications for understanding the complex, interacting roles of genetic, ecological and social processes in the formation and maintenance of human societies on both shorter demographic and ecological scales, and longer evolutionary and biogeographic scales.