Complexity

Financed by

Status
In progress
Time
2023-2025

COMPLEXITY is situated at the intersection of anthropology and ecology and deals with the evolution of political complexity.

The project is financed by The European Research Council.

The prevalent view of the evolution of complex societies favours agriculture as the main factor.

How do we then explain the rise of nomadic empires?

One common explanation refers to conflict, and large-scale conflict with China has been presented as the central element in the rise of, for example, the Mongol Empire.

The Mongol EmpireIn 1242, Europe stood on the precipice of destruction. Based in Hungary and Serbia, the Mongol armies were poised for conquering the rest of Europe. Only the death of the Great Khan halted the Mongol advance, sparing Europe from the fate of an inevitable conquest. Twenty-five years after the withdrawal, the Mongol Empire reached its peak with the establishment of the Yuan dynasty – making it the largest land empire in history, stretching from the Sea of Japan to the Mediterranean Sea and the Carpathian Mountains.

Thus, pastoralists could only develop complex levels of organisation when facing strong agricultural neighbours.

But this cannot explain how pastoralists transitioned from small, kin-based groups to complex stratified societies.

COMPLEXITY’s central thesis is that before large-scale conflict is even possible, a level of within-group cooperation must be present.

Noteworthy, it is almost impossible for pastoralists to survive without cooperative labour investment and help from other households

By viewing cooperative herding groups as the building blocks of nomadic societies, COMPLEXITY aims to increase our understanding of the evolution of political complexity based on a new theoretical explanation of pastoral political organisation.

Structure

While cooperative herding has been documented, previous studies have been based on single case studies.

Evidence is also fragmented, and little systematic attempts have been made to understand general patterns of pastoral cooperation.

The first step of COMPLEXITY is thus to cross-culturally analyse and document the prevalence of cooperative herding groups by using the existing ethnographic literature and a cross-cultural database

This will be used to select four field sites in Africa and Inner Asia.

Map of cooperative herding groupsThe preliminary extent of cooperative herding groups.

Study designStudy design where the overall starting point is to select two communities at two sites within each region. Arrows indicate levels of comparison undertaken in the project: between regions; between sites; and between communities. Coloured areas on the map indicate the already documented presence of herding groups while animal figures indicate the traditional Old World nomadic pastoral zones defined by the key cultural animal

Cooperation, performance and the rise of pastoral inequality

Understanding cross-cultural diversity and patterns in behaviour is a central goal of human behavioural ecology.

Nevertheless, the predominant view of cooperation is shaped by studies focusing on food sharing among foragers.

In contrast, less focus has been placed on cooperative production, the primary form of cooperation among pastoralists.

Conceptual overviewA conceptual overview of the domain, focus, problem, mechanisms and research load in evolutionary aspects of cooperation in anthropology

The evolution of political complexity: from small-scale cooperative group to empires?

There is also a view that livestock, as the primary source of wealth, limits the development of inequalities, making pastoralism unable to support complex organisations.

However, the Gini coefficient for reindeer in Norway indicates that wealth in livestock is more unevenly distributed than for Norway in general (see this preprint).

Since we cannot observe the history of nomadic empires, COMPLEXITY’ will model if, for example, livestock as wealth can generate inequalities resulting in hierarchical power structures.

The third step is thus to combine empirical data with Agent-Based Modelling, to investigate whether cooperative herding groups can be considered prototypes for more complex organisations.