Modelling large-scale human dispersals: data, pattern and process

Posted on August 24, 2015


A session video recorded from the CAA international conference:

Archaeology has largely moved forward from the simplistic ‘dots-on-the-map’ and ‘arrows-on-the-map’ approaches when it comes to studying large-scale human movements. Current models regarding spatio-temporal distribution and migration of humans often highlight the complex nature of such phenomena and the limitations that any particular data type impose on the reconstruction, be it environmental (paleoclimate, paleotopography, paleofauna and -flora), archaeological (site distribution, patterns in material culture) and other types of data (genetics, isotopes etc). Similarly the, often very coarse, resolution of the data coupled with the difficulty of integrating different types of information within one framework make the task of researching large-scale human dispersal challenging. Nevertheless, a number of recent applications employing different computational techniques show that this can be achieved. From the data acquisition, cataloguing and storing, to spatial analysis and identifying patterns and distributions in the data to building abstract and semi-realistic simulations of the processes behind the dispersals, computational techniques can aid the process of investigating human movement on various scales and allow researchers to tackle the underlying complexity of the studied systems moving the debate beyond simple intuitive models.

This session aims to summarise the recent progress in the topic, discuss major challenges and provide a base for establishing further directions of research. We invite contributions from researchers studying human movements on the meso- and macro-scale and employing any of the wide variety of techniques and theoretical frameworks within the following three themes:

DATA: spatio-temporal data acquisition and integration (for example, data types, quantifying uncertainty and biases of the data, large-scale databases, cross-platform integration);

PATTERN: spatio-temporal analysis and modelling (statistical modelling, GIS, C14 among others);

PROCESS: modelling of processes and mechanisms underpinning dispersal through simulation (agent-based and equation-based modelling, cellular automata, system-dynamics modelling, (social) network theory) and other techniques.

Michael Maerker, Christine Hertler, Iza Romanowska

Identification of Agent-Based Modeling elements in “Out of Africa” hypothese

Large scale population modelling in the deep past. Issues and concerns.

Abstract: Genetic, morphological and archaeological research suggest that the Neandertal lineage disappeared around the time that modern humans arrived in Europe. The exact process, timing
and causation are poorly understood. Landscape scale taphonomy and research intensity create a biased record. HomininSpace 2.0 is a modelling and simulation system for exploratory analysis of dispersal behaviour of hominin groups in large scale realistic landscapes and over long timescales. As a case study to validate the concept, an explicit Neandertal model is constructed and implemented. Simulation against the Neandertal archaeological record is used to identify the most likely values for key model parameters. The aim of this research is to quantitatively assess the importance of different parameters on the energy management of past hominins. As such HomininSpace offers an alternative approach to analysis of the past. HomininSpace is an agent based modelling and simulation environment where a fluctuating carrying capacity in a reconstructed paleoenvironment is the key attractor for hominin dispersal. A year by year demographic model for Neandertal groups moving through Northwest Europe is simulated from 131 ky BP to 50 ky BP. Presence and absence results are matched against the archaeological record which is stored in a comprehensive database of Checkpoints in Space and Time. These points store site name and GPS location, the archaeological material that is dated, chronometric dates assigned including accuracy and dating method, reference to the literature, and a confidence level. Each date translates into an interval that keeps track of foraging groups in the area. This paper discusses how important the availability of precise dating results can be, the issues when creating an explicit hominin model, and the concerns when evaluating simulation results. The discussion illustrates the deficiency in accurate chronological information for North-west Europe, arguably the most intensely studied Middle Paleolithic area. It will also address the unique possibilities that modelling and simulation efforts offer in using such limited amounts of data in hypothesis development and explorative analysis of large scale dispersal patterns.

Authors: Fulco Scherjon

Adoption of innovations and expansive phenomena in the 2nd millennium BC in Europe.

Abstract: The 2nd millennium BC in Central and Western Europe represents a perfect case study to test different and competing hypotheses of social dynamics and economic changes in early complex societies. Traditionally, for the European Bronze Age scholars have been able to detect the existence of macro-scale spreading phenomena whose material consequences have been recorded in the archaeological deposit. Among the most studied ones we can refer to the diffusion of cremation burials within the so called “Urnfield culture” and the introduction and spread of specific pottery and metal typologies (handles with vertical expansion, fluted pottery and bronze knives). In this presentation, after having illustrated the theoretical aspects relating to the case study, we aim to quantify episodes of adoption of innovation which took place during the 2nd millennium BC in Prehistoric Europe. In particular, our study focuses on those characterized by an expansive behaviour. In order to tackle this issue we present the results of a geostatistical analysis carried out through a computer programmed modeling of different space-time datasets. The data originate from the EUBAR database, which collects more than 1700 georeferenced and radiocarbon dated archaeological contexts of a period between the Early Bronze Age and the beginning of Iron Age from an area including the North-East of Iberian Peninsula, Southern France, Northern Italy, Switzerland, Austria and Southern Germany.

Authors: Giacomo Capuzzo, Juan Antonio Barceló

What can we learn about the environmental preferences of Neanderthals and Modern Humans?

Abstract: In this study we focus on the characterization of Neanderthals and Modern Human site locations using environmental data and different stochastic models. The models were trained using an unique spatial dataset of Neanderthal sites and a set of Modern Human find locations. We applied a boosted regression tree approach (TREENET) and a statistical mechanics approach (MAXENT) to test model robustness. As predictor variables a set of Terrain Indies based on digital elevation models and additional environmental information such as climatic and vegetational/ faunal information were utilized. A quantitative evaluation of the models was done using internal model performance indices such as the Receiver Operating Characteristics (ROC) curves for the train dataset and a validation test dataset. The dependent variable or target variable in this study are the locations of Neanderthal sites and Modern Human sites described by latitude and longitude. The information on the site location was collected from literature and own research. The study illustrates that the models are able to characterize the environmental preferences of Neanderthals an Modern Human expressed by a specific spatial distribution and a certain variable importance

Authors: Michael Märker, Michael Bolus

Using GIS and Geophysics to Examine Caesar’s Campaign against the Helvetii in 58 BC

Abstract In the first chapter of “Comentarii de Bello Gallico” Julius Caesar recounts his campaign against the Helvetii in 58 BC. He asserts that the forces arrayed against him included 92,000 warriors amongst a mobilised mass of about 368,000 Gauls. This far outnumbered his six legions of ~30,000 men. Other interpretations of the campaign calculate a much smaller Gaulish contingent; with as few as 16,000 warriors. But what were the actual numbers? The generally accepted view is that Caesar inflated them for political gain. Caesar also explains the Helvetian incursion as arising from the pressures of Germanic tribes north of the Rhine, and the constriction of the Alps and Jura on their available resources. Can we perhaps shed some light on these assertions? Were the pressures on the Helvetii due to stress on the regional carrying capacity? Or can we perceive other economic advantages behind their migration? The aim of this paper is to examine a few of these issues using new techniques for modelling human energetics and dynamic mobility. This on-going three part project is aimed at developing: 1) a large-scale GIS simulation of the economic situation across all of the Helvetian territory as it existed just prior to the war, addressing the mechanisms of energy capture, exchange, storage, and loss in the context of the various population estimates; 2) a medium-scale model for kinetic energy expenditure by both groups specifically along the Rhône defences, and; 3) remotely sensing archaeological signatures in the small scale area known as Le Mandement (located just outside of Geneva, Switzerland). The specific landscape visualisations focus on the situation as it existed prior to the war across all of the Helvetian territory, and locally in the region of the Rhône between Lac Leman and le Pas d’Ecluse. The former as an expression of potential energy sources (e.g. agricultural and pastoral productivity, plus wild and semi-domesticated resources), as well as systems of energy exchange, transport, storage, and loss. The latter is examined as a model for kinetic energy expenditure (e.g. the building and maintenance of the wall to dramatically increase the “friction” costs of the invasion), and the tenuous nature of long-range energy supply (i.e. the Roman supply lines). Ultimately these examples provide ways of illustrating patterns of past human behaviour and movements that can be spatially quantified but are perhaps difficult to identify archaeologically. They can also be seen as insights into the cognitive processes employed by past people such as Julius Caesar, who did, in fact, keep track of, evaluate, and forecast the energy costs of politics, battles, and their future payoffs. Our goal in this presentation is to present the results of the large scale GIS landscape modelling, some preliminary geophysics findings and issues on both the medium and small scales, and to take a look forward to our proposed next steps in the process.

Authors: Thomas G. Whitley, Geoff Avern, Christine Markussen, Katie Simon

An Agent-based Model to Simulate the Balkan Neolithic Expansion

Abstract Stochasticity and contingency make the simulation of the history of an archaeological society unlikely. However, the technique introduced by Braudel (1958) and the Ecole des Annales, in which the flow of historical information is broken down into temporal sequences of different durations (long, medium and short) allows modeling to focus on the fraction of total History where contingency and stochasticity will be at a minimum. This is the case with the “longue durée” of geohistory, that is to say the fraction of human activities that is mainly determined by the multi-secular (millennial) permanence of structural geo-environmental conditions. In the “longue durée” we find, in particular, the system of economic production (techniques and social relationships) that ensures the biological survival of a population and which can be summarized by the term “infrastructure”. This is the general framework for this modeling study on the Balkan Neolithic expansion. Reconstructed (estimated) geoenvironmental data (on climate and soil fertility) at the regional scale in the Balkans were incorporated into an agro-pastoral economic system obtained by ethno-archaeological inference, and into a Balkan-Anatolian anthropological model of the nuclear family. The process of Neolithic expansion in the Balkans was then simulated. What are the preferred settlement areas given by the simulation? Does the simulated pattern of expansion match the observed archaeological pattern?

Authors: Andrea Zanotti, Jean-Pierre Bocquet-Appel

High-performance agent-based models of worldwide human dispersals

Abstract: Recent advances in palaeoanthropology, archaeology, and ancient genomics, have yielded unprecedented insights into the prehistory of Homo sapiens. Worldwide spatial patterns of genetic and phenetic distance and variation, as well as archaeological findings, can be interpreted in the context of an African origin and out-of-Africa dispersal of our species during the late Pleistocene. However, quantitative tests of hypotheses about the population dynamics of the genus Homo are difficult to conduct, since models of large-scale human dispersals often neglect intrinsic stochasticity and environmental variability, and genetic patterns are modeled in terms of local populations or demes. Here we present an agent-based modeling framework for large-scale population dynamics that is able to handle millions of agents and timesteps in a geographically and ecologically structured environment. We show results from simulations of the out-of-Africa dispersal of Homo sapiens in which each agent can be thought of as a simplified, single individual. From these, we reconstruct the worldwide genetic history of our simulated populations, tracing back the complete ancestry of sample individuals. Finally, we show how large-scale parameters of population demography and diffusion affect the emerging spatiotemporal patterns and genetic signatures of the dispersal process.

Authors: Simone Callegari, John David Weissmann, George Lake, Christoph P. E. Zollikofer

Testing the Variability Selection Hypothesis on Hominin Dispersals

Abstract: The Variability Selection Hypothesis proposed by Potts (1996; 1998) postulates the evolution of behavioural plasticity among early hominins arising during periods of strong environmental fluctuations in the last 6 million years. It argues that the inconsistency in selection regimes caused by the rapid environmental fluctuations produced particularly strong selection pressure on adapting to change rather than any particular set of conditions (termed ‘adaptive complexity’, ‘adaptive flexibility’, ‘adaptive versatility’, or simply ‘versatilists organisms’). The work by Potts was further formalised by Grove (2011) in a single locus model and tested on the temperature curve spanning the last five million years. The current implementation aims to assess the implications of the Variability Selection Hypothesis on the agent’s ability to disperse, a process that is visible in the archaeological record. The model was translated into a stochastic multiagen simulation to investigate the dynamics between individuals with different positions and range on the adaptative spectrum (including the ‘versatilist’ individuals) within a nonhomogenous population. The initial results shows that using heterogeneous multi-agent simulation can successfully replicate Grove’s formal implementation but also sheds new light on how the pattern of dispersal unravels under different environmental regimes.

Authors: Iza Romanowska, Seth Bullock

Individual-based modeling of population growth and dispersal in discrete time

Abstract: There is an increasing interest in spatio-temporal models of ecological dynamics and evolutionary processes that take into account the fact that populations consist of discrete entities, i.e., individuals. Such models allow to consider individual variation explicitly and are well-suited to the study of stochastic processes. Individual-based models (IBMs) that can be analyzed analytically and numerically are one type of such discrete models. IBMs represent thus an important approach for modeling (past) human population dynamics, especially when investigating large-scale emerging patterns. A common property of individual-based growth and growth-diffusion models is however the continuous-time implementation, in which individual “actions” happen one at a time. This approach does not scale well when simulating large number of individuals, and is not easily parallelizable on distributed memory machines. For this reason, in this work we describe an individual-based stochastic model of growth and diffusion with overlapping generations which is suitable for large-scale simulations in structured environments. The model uses a discrete-time paradigm with constant time step; as a consequence all agents act simultaneously based only on information from previous time step. By describing the system with a discrete-time Master equation we show that our stochastic model approaches the Fisher-Kolmogorov model in the continuum limit. The properties of the model at different discreteness levels are analyzed by means of numerical simulations as well as analytical approximations. We confirm qualitative trends found in previous works on stochastic birth-death models and growth-diffusion models, and find some novel and interesting features; in particular, the discrete-time algorithm shows different noise properties compared to continuous-time stochastic models. We show how these features affect emergent properties of the population such as the effective carrying capacity and the dispersal speed: both tend to decrease for high level of discreteness. Due to the simultaneous acting of all individuals, the model can be parallelized and is suited for High Performance Computing. This allows to increase the spatial and temporal resolution as well as to consider larger spatial domains and longer simulation times. Thus, the model is suited for the simulation of large populations expansions during human history. We discuss possible expansions of the model and the inclusion of real observational data.

Authors: Natalie Tkachenko, Simone Callegari, John David Weissmann, Wesley P. Petersen,
George Lake, Christoph P. E. Zollikofer

Modelling glacial archaeological potential in the Pennine Alps – A multidisciplinary approach

Abstract: This project integrated historical, archaeological, and geographical knowledge to analyse the glacial archaeological potential of the Pennine Alps, located in high altitude glaciated passes (3,000 to 3,500 m asl) between Switzerland and Italy. The results document site-based archaeological information that will disappear forever once the glaciers that preserve them have melted. Therefore, the main goal of the project was to preserve archaeological heritage threatened by melting ice around the passes and safeguard fundamental, but perishable, materials in vanishing ice fields. The methods used included a historical archival text analysis, geospatial modelling, and archaeological prospection in the field. If the written sources did not provide exact information about the passes themselves or how frequently they were used in the past, the sources could still be used to demonstrate their regular usage thanks to related documentation linking political tensions or trade disputes between valleys. The information collected was used as a basis for conducting least cost path and locational analyses in GIS along with a regional scale glaciological modelling approach to determine where archaeological remains might be found in the future based on the principles of human accessibility and topographical characteristics of the terrain. One major scientific objective of this project was to use glaciological modelling to determine what the glaciers could look like in the future in this study area, in order to assess the degree of urgency for archeological prospection. In collaboration with glaciologists, glaciers were modelled in 10-year stages from now until 2100. This information was used with results from the locational analysis in GIS to predict where archaeological remains could be found in the future based on future glacier geometries and the topography of the terrain. The results of the historical and geographical aspects were used as decision support tools for conducting archaeological prospection in the field. Archaeologists conducted 20 days of prospection at 13 different sites and collected over 100 pieces of wood deposited at the glaciers surface or in their glacial margins. As yet, 36 pieces have been dated using radiocarbon analysis; 19 were dated to modern time (later than 1600 AD), seven to the Middle Age (~500-1600 AD), six to Roman time (0-500 AD), and four to Prehistoric time (earlier than 1000 BC). The majority of the ancient wood pieces are non-worked stakes which were probably used as route markers. However, wood pieces were frequently highly distorted due to ice movement and their function cannot be interpreted. The results demonstrate that humans have crossed these glaciated high altitude passes for over 3,000 years and additionally can serve to protect the fragile archaeological heritage threatened by the melting of ice.

Authors: Stephanie R Rogers, Philippe Curdy, Muriel Eschmann Richon, Ralph Lugon

Radiocarbon dates, cremations, flatgraves and the appearance of the urnfield cemeteries in Belgium

Traditionally, the Late Bronze Age is seen as the period during which the urnfield cemeteries appeared in the funerary archaeological record in Belgium. Flatgraves were dominant and replaced in most cases the former barrow tradition. Inhumation was replaced by cremation of the deceased’s body. This transition was dated around 1100 BC based on the typochronological study of the accompanying funerary goods in the burials Radiocarbon dates on cremated bone offered new insights in the origin of the flatgraves and urnfield cemeteries. The appearance of cremations and flatgraves is according the present information a more complicated evolution with regional differences. This process started earlier than assumed before. Some dates are as old as the 15th -14th centuries cal BC. This new phenomenon clearly dominates the funerary ritual from 1200 cal BC onwards, but between 1500-1200 cal BC a co-existence of both traditions of barrows and flatgraves is evident. By using Bayesian analysis we want to try to refine the chronological information concerning flatgraves and the introduction of the cremation ritual in Belgium.

To see more videos like these please go to the YouTube channel Recording Archaeology-

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