Hostname: page-component-586b7cd67f-gb8f7 Total loading time: 0 Render date: 2024-11-30T00:10:56.720Z Has data issue: false hasContentIssue false

CLIOdynamic ARCHaeology: computational approaches to Final Palaeolithic/Early Mesolithic archaeology and climate change

Published online by Cambridge University Press:  09 June 2020

Felix Riede*
Affiliation:
Department of Archaeology and Heritage Studies, School of Culture and Society, Aarhus University, Denmark BIOCHANGE: Center for Biodiversity Dynamics in a Changing World, Department of Bioscience, Aarhus, Denmark
Shumon T. Hussain
Affiliation:
Department of Archaeology and Heritage Studies, School of Culture and Society, Aarhus University, Denmark BIOCHANGE: Center for Biodiversity Dynamics in a Changing World, Department of Bioscience, Aarhus, Denmark
Claudia Timmreck
Affiliation:
Max-Planck-Institut für Meteorologie, Hamburg, Germany
Jens-Christian Svenning
Affiliation:
BIOCHANGE: Center for Biodiversity Dynamics in a Changing World, Department of Bioscience, Aarhus, Denmark
*
*Author for correspondence: ✉ [email protected]
Rights & Permissions [Opens in a new window]

Abstract

It is often claimed that changes in material culture signify adaptations to changing environments. Deploying novel conceptual models and computational techniques, research funded by the European Research Council seeks to reconstruct the patterns and processes of cultural transmission and adaptation at the turbulent transition from the Pleistocene to the Holocene.

Type
Project Gallery
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © Antiquity Publications Ltd, 2020

Introduction

During the European Final Palaeolithic and Early Mesolithic, material culture seemingly diversified. This emergence of regional groupings, supposedly characterised by new stone tools or novel technologies, is often thought to signify adaptations to changing climates and environments. Opinions differ, however, on the degree to which environmental changes in the form of the contemporaneous climatic cycles or extreme events, such as the Laacher See volcanic eruption, forced these changes, or whether they relate primarily to dynamics of cultural transmission (see Kabacinski & Sobkowiak-Tabaka Reference Kabacinski and Sobkowiak-Tabaka2011; Riede Reference Riede2017). Furthermore, recent work reconnects with earlier critiques of Final Palaeolithic and Early Mesolithic cultural taxonomy (e.g. Kobusiewicz Reference Kobusiewicz, Street, Barton and Terberger2009) in pointing out that many of the period's cultures, industries and facies may be artefacts of research history, rather than reflecting contemporaneous cultural variability (Sauer & Riede Reference Sauer and Riede2019; Ivanovaite et al. Reference Ivanovaite, Serwatka, Hoggard, Sauer and Riede2020). Indeed, the entire cultural taxonomic framework for the Upper and Final Palaeolithic seems to be in epistemological crisis (Reynolds & Riede Reference Reynolds and Riede2019).

CLIOARCH (CLIOdynamic ARCHaeology: computational approaches to Final Palaeolithic/Early Mesolithic archaeology and climate change) seeks to revitalise cultural taxonomic research in the period from 15 000–11 000 years BP—encompassing the Late Glacial and Early Holocene—and to combine state-of-the-art climate modelling (Mauritsen et al. Reference Mauritsen2019) with fully reproducible eco-informatics methods to answer long-standing questions of cultural relations and adaptations. Finally, the project will ground-truth its in silico results through excavations, specifically targeting stratified rockshelter locales (Figure 1).

Figure 1. The five CLIOARCH work-packages in its signature visual language, arranged on an evolutionary tree inspired by one of Charles Darwin's own notebook sketches from 1837 in reference to the project's cultural evolutionary approach (cf. Archibald Reference Archibald2014; figure by the authors).

Critical research history is essential in untangling the epistemological inconsistencies that plague the Final Palaeolithic/Early Mesolithic. The turbulent times of the nineteenth and twentieth centuries during which archaeology developed as a discipline have left an indelible mark on present practice (Díaz-Andreu Reference Díaz-Andreu2007), including research on the Palaeolithic (e.g. Tomášková Reference Tomášková2003; Clark Reference Clark, Camps and Chauhan2009). CLIOARCH's point of departure is the observation that many of the Final Palaeolithic stone tool type fossils—mostly defined some time ago—no longer hold the culture-historical diagnostic power once ascribed to them (Serwatka & Riede Reference Serwatka and Riede2016), and that the many maps intended to portray contemporaneous cultural diversity are in evident contradiction to each other (Riede et al. Reference Riede, Hoggard and Shennan2019). Critically, the methods and data used to define the original cultural units or their spatial representation are rarely, if ever, transparent or reproducible. In light of recent calls for Open Science in archaeology (Marwick Reference Marwick2017) and parallel developments in quantitative history—‘cliodynamics’ (Turchin Reference Turchin2008)—CLIOARCH deploys a model- and data-driven approach to move our understanding of this period forward substantially.

CLIOARCH will use cultural evolutionary theories and methods—especially geometric morphometrics and cultural phylogenetics—to capture long-term techno-typological transformations. Cultural phylogenies have the potential to form the basis not only for refining existing taxonomies but also for rethinking adaptation (cf. Collard & Shennan Reference Collard, Shennan, Stark, Bowser and Horne2008). The project will assemble an up-to-date geo-referenced database of relevant find localities and their characteristics so that subsequent analyses and accompanying climate model simulations will be able to address change over both time and space. This will enable them to capture changing ways of relating to unstable environments and changing technological traditions. Once novel cultural taxa are identified, distribution modelling approaches (e.g. Svenning et al. Reference Svenning, Fløjgaard, Marske, Nógues-Bravo and Normand2011) can be applied to define the adaptive envelopes or niches specific to them in a statistical way that also accounts for the historical relatedness amongst these taxa. As pioneered elsewhere (e.g. Benito et al. Reference Benito, Svenning, Kellberg-Nielsen, Riede, Gil-Romera, Mailund, Kjaergaard and Sandel2017; Whitford Reference Whitford2019), distribution modelling enables us to extract the specific topographic and environmental parameters linked to different taxonomic groupings and so to infer their ecocultural adaptations. Ultimately, the predictive power of these distribution models in combination with regional registers will allow us to search for new stratified locales from the Final Palaeolithic/Early Mesolithic in a targeted manner.

Acknowledgements

The CLIOARCH project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement 817564).

References

Archibald, J.D. 2014. Aristotle's Ladder, Darwin's Tree: the evolution of visual metaphors for biological order. New York: Columbia University Press.Google Scholar
Benito, B.M., Svenning, J.-C., Kellberg-Nielsen, T., Riede, F., Gil-Romera, G., Mailund, T., Kjaergaard, P.C. & Sandel, B.S.. 2017. The ecological niche and distribution of Neanderthals during the Last Interglacial. Journal of Biogeography 44: 5161. https://doi.org/10.1111/jbi.12845CrossRefGoogle Scholar
Clark, G.A. 2009. Accidents of history: conceptual frameworks in paleoarchaeology, in Camps, M. & Chauhan, P. (ed.) Sourcebook of Paleolithic transitions: methods, theories, and interpretations: 1941. New York: Springer. https://doi.org/10.1007/978-0-387-76487-0_2CrossRefGoogle Scholar
Collard, M. & Shennan, S.J.. 2008. Patterns, process, and parsimony: studying cultural evolution with analytical techniques from evolutionary biology, in Stark, M.T., Bowser, B.J. & Horne, L. (ed.) Cultural transmission and material culture: 1733. Tucson (AZ): The University of Tucson Press.Google Scholar
Díaz-Andreu, M. 2007. A world history of nineteenth-century archaeology: nationalism, colonialism, and the past. Oxford: Oxford University Press.CrossRefGoogle Scholar
Ivanovaite, L., Serwatka, K., Hoggard, C., Sauer, F. & Riede, F.. 2020. All these fantastic cultures? Research history and regionalisation in the Late Palaeolithic tanged point cultures of Eastern Europe. European Journal of Archaeology 23: 162–85. https://doi.org/10.1017/eaa.2019.59CrossRefGoogle Scholar
Kabacinski, J. & Sobkowiak-Tabaka, I.. 2011. Environmental determinants of cultural changes in the Late Glacial and the Early Holocene on the North European Plain. Przeglad Archeolgiczny 58: 521.Google Scholar
Kobusiewicz, M. 2009. The Lyngby point as a cultural marker, in Street, M., Barton, R.N.E. & Terberger, T. (ed.) Humans, environment and chronology of the Late Glacial of the North European Plain (RGZM—Tagungen 6): 169–78. Mainz: Römisch-Germanischen Zentralmuseums.Google Scholar
Marwick, B. 2017. Computational reproducibility in archaeological research: basic principles and a case study of their implementation. Journal of Archaeological Method and Theory 24: 424–50. https://doi.org/10.1007/s10816-015-9272-9CrossRefGoogle Scholar
Mauritsen, T. et al. 2019. Developments in the MPI-M Earth System Model version 1.2 (MPI-ESM1.2) and its response to increasing CO2. Journal of Advances in Modeling Earth Systems 11: 9981038.CrossRefGoogle ScholarPubMed
Reynolds, N. & Riede, F.. 2019. House of cards: cultural taxonomy and the study of the European Upper Palaeolithic. Antiquity 93: 1350–58. https://doi.org/10.15184/aqy.2019.49CrossRefGoogle Scholar
Riede, F. 2017. Splendid isolation: the eruption of the Laacher See volcano and Southern Scandinavian Late Glacial hunter-gatherers. Aarhus: Aarhus University Press.Google Scholar
Riede, F., Hoggard, C. & Shennan, S.. 2019. Reconciling material cultures in archaeology with genetic data requires robust cultural evolutionary taxonomies. Palgrave Communications 5: 55. https://doi.org/10.1057/s41599-019-0260-7CrossRefGoogle Scholar
Sauer, F. & Riede, F.. 2019. A critical reassessment of cultural taxonomies in the Central European Late Palaeolithic. Journal of Archaeological Method and Theory 26: 155–84. https://doi.org/10.1007/s10816-018-9368-0CrossRefGoogle Scholar
Serwatka, K. & Riede, F.. 2016. 2D geometric morphometric analysis casts doubt on the validity of large tanged points as cultural markers in the European Final Palaeolithic. Journal of Archaeological Science: Reports 9: 150–59. https://doi.org/10.1016/j.jasrep.2016.07.018Google Scholar
Svenning, J.-C., Fløjgaard, C., Marske, K.A., Nógues-Bravo, D. & Normand, S.. 2011. Applications of species distribution modeling to paleobiology. Quaternary Science Reviews 30: 2930–47. https://doi.org/10.1016/j.quascirev.2011.06.012CrossRefGoogle Scholar
Tomášková, S. 2003. Nationalism, local histories and the making of data in archaeology. Journal of the Royal Anthropological Institute 9: 485507. https://doi.org/10.1111/1467-9655.00160CrossRefGoogle Scholar
Turchin, P. 2008. Arise ‘cliodynamics’. Nature 454: 34. https://doi.org/10.1038/454034aCrossRefGoogle Scholar
Whitford, B.R. 2019. Characterizing the cultural evolutionary process from eco-cultural niche models: niche construction during the Neolithic of the Struma River Valley (c. 6200–4900 BC). Archaeological and Anthropological Sciences 11: 2181–200. https://doi.org/10.1007/s12520-018-0667-xCrossRefGoogle Scholar
Figure 0

Figure 1. The five CLIOARCH work-packages in its signature visual language, arranged on an evolutionary tree inspired by one of Charles Darwin's own notebook sketches from 1837 in reference to the project's cultural evolutionary approach (cf. Archibald 2014; figure by the authors).