CASE

The pattern of spatial distribution of Lower Palaeolithic (LP) sites east of the Rhine is peculiar. The sites are rare; they do not come in clusters, and they do not seem to be associated with ancient river terraces. This is a robust pattern that has been recognized but not addressed as a distinct research topic so far. It may represent either a real past phenomenon such as climate variability, different dispersal routes ‘out of Africa’ or simply reflects modern research bias. A new alternative is suggested here based on recent developments in geological mapping. It is argued that uninterrupted mantel of glacial derived silt (loess) sealing interglacial soil levels may be covering traces of Lower Palaeolithic human activity at significant depths throughout most of Central and Eastern Europe.

Agent Based Modelling (ABM) provides us with a unique platform for testing large scale hypotheses. It is particularly effective when dealing with the concept of movement, be it human expansion into new lands, cultural transmission over vast distances or animal migration. Low density of Lower Palaeolithic finds in Central and Eastern Europe has been repeatedly attributed to particular dispersal routes and environmental impact. Creating a NetLogo ABM model of this process can assist in verifying this observation and revealing the pattern of the first human dispersal under constantly changing conditions of palaeoclimatic cycles. It also allows to address several methodological issues related to modelling dispersals in general, especially the application of the basic Fisher-KPP reaction-diffusion system and other mathematical models commonly used to replicate large scale human movements.

The First Out of Africa: an Agent Based Model of the earliest hominid dispersal

The study of early hominid dispersals is a complex academic issue integrating data from several very different disciplines: archaeology, anthropology, paleozoology, palaeoclimate studies and genetics. The aim of this paper is to show the potential of Agent Based Modelling (ABM) to integrate this data into one coherent framework while providing a unique platform for testing large scale hypothesis.

The current methodology for the study of dispersals is largely based on qualitative considerations. I would argue that a more quantitative approach integrating simulation with geographical methods could be more fruitful and bring new answers to old questions.

In order to test these assumptions a simple ABM model of the first Out of Africa has been developed using the popular modelling software NetLogo. The availability of different routes into Europe was the sole variable in this model. Yet, it proved useful to answer the following research question: is the lack of Lower Palaeolithic sites in Central and Eastern Europe a reflection of the dispersal routes? As a by-product of the model several unanticipated patterns emerged, showing the potential of ABM for studying early human dispersal.

The pattern of spatial distribution of Lower Palaeolithic (LP) sites east of the Rhine is peculiar. The sites are rare, they do not come in clusters, and they do not seem to be associated with ancient river terraces. This is a robust pattern that has been recognized but not addressed as a distinct research topic so far. It may represent either a real past phenomenon such as climate variability, different dispersal routes ‘out of Africa’ or simply reflects modern research bias.

A new alternative is suggested here based on recent developments in geological mapping. It will be argued that an uninterrupted mantel of glacial derived silt (loess) sealing interglacial soil levels may be covering traces of Lower Palaeolithic human activity at significant depths throughout most of Central and Eastern Europe.

SHEEP (Simulating Hominin Expansion in the Early Pleistocene) is an Agent-based model (ABM) of the first Out of Africa, designed to explore the spatial pattern of Lower Palaeolithic site distribution in Europe. The SHEEP model uses a deterministic environmental approach to evaluate potential routes into Europe and their impact on the pattern of site distribution in the eastern and western parts of the continent. The model consists of three main elements: 1) population growth, 2) a spatial spreading process and 3) the friction map, which includes both environmental and topographic information. The impact of different geographical projections on the outcome of the model has been evaluated. The results show that we are unable to reproduce the observed spatial pattern of European sites from differences in dispersal routes. This case study showcases the use of ABM as a simple and efficient tool for hypotheses testing with a high potential for archaeological applications.

With the current surge of simulation studies in archaeology there is a growing concern for the lack of engagement and feedback between modellers and domain specialists. To facilitate this dialogue I present a compact guide to the simulation modelling process applied to a common research topic and the focus of this special issue of Human Biology—human dispersals. The process of developing a simulation is divided into nine steps grouped in three phases. The conceptual phase consists of identifying research questions (step 1) and finding the most suitable method (step 2), designing the general framework and the resolution of the simulation (step 3) and then by filling in that framework with the modelled entities and the rules of interactions (step 4). This is followed by the technical phase of coding and testing (step 5), parameterising the simulation (step 6) and running it (step 7). In the final phase the results of the simulation are analysed and re-contextualised (step 8) and the findings of the model are disseminated in publications and code repositories (step 9). Each step will be defined and characterised and then illustrated with examples of published human dispersals simulation studies. While not aiming to be a comprehensive textbook- style guide to simulation, this overview of the process of modelling human dispersals should arm any non-modeller with enough understanding to evaluate the quality, strengths and weaknesses of any particular archaeological simulation and provide a starting point for further exploration of this common scientific tool.

Agent-based modelling (ABM) has taken by storm disciplines from all corners of the scientific spectrum, from ecology to transport and social sciences and it is becoming increasingly popular in archaeology. ​Now it is your turn to give it go! Learn how to use the simulation software and explore how this popular complexity science technique can complement your research. This two-day workshop will provide ​an introduction to ABM using NetLogo - an open-source platform for building agent-based models, which combines user-friendly interface​, ​simple coding language and a ​vast library of model examples​, making it an ideal starting point for entry-level agent-based modellers, as well as a useful prototyping tool for more experienced programmers.