Machine learning reveals the role of the landscape in the dynamics of human settlement rules between the Palaeolithic and Iron Ages in Lithuania

Collection:
Mokslo publikacijos / Scientific publications
Document Type:
Straipsnis / Article
Language:
Anglų kalba / English
Title:
Machine learning reveals the role of the landscape in the dynamics of human settlement rules between the Palaeolithic and Iron Ages in Lithuania
Authors:
In the Journal:
Quaternary international. 2020, 565, p. 109-124
Subject Category:
LT
11 tūkst. m. pr. Kr. - 12 amžius. Lietuvos priešistorė; Gyvenvietės (archeologija) / Settlements (Archaeology); Estija (Estonia); Latvija (Latvia); Lietuva (Lithuania).
Summary / Abstract:

LTReikšminiai žodžiai: Gyvenvietės; Nuspėjamieji modeliai; Miškas; Dinamika; Baltijos regionas; Human settlements; Predictive modelling; Machine learning; Forest areas; Dynamics; Baltic region.

ENSettlement distribution modelling assumes that human spatial behaviour can be revealed by using the correct set of variables. However, the regional variables of large-scale gradients are only considered rarely. Also, settlement modelling applications are often impeded by fragmentary and error-prone datasets. Thus, in current-day Lithuania, in order to study the dynamics of settlement distributional rules, we implemented a modelling strategy that involves the use of statistical and machine learning methods with null model simulations and that is less affected by the incompleteness of datasets and the scales of variables. In this study, we used regional variables in order to test their usefulness while providing a general understanding of the large-scale processes that governed settlement distribution in prehistory. This study encompassed six time intervals between the Palaeolithic and Iron Ages. The obtained results consisted of regional settlement predictive maps, estimations of random forest variable importance and performances of GAM models, as well as determinations of Besag’s Lfunctions of settlement patterns and Euclidean distances between the regional variables at the settlement sites. We detected decreasing spatial autocorrelation of the settlement prediction maps and settlement patterns, declining variable importance and model performance, as well as increasing regional environmental diversity of the settlement sites.A marked manifestation of these trends was observed between the Neolithic and Bronze Ages. This also corresponded to a major change in the constitution of the most important variables of the settlement distributions. We associate these findings with technological and lifestyle changes in the southern Baltic region, interpreting them as causing a roughening of the human adaptive landscape – increasing the specificity, number and complexity of the settlement distributional rules. Our study revealed that, even for incomplete datasets and spatial autocorrelation, the application of advanced statistical/machine learning techniques was able to provide new insights into the processes that governed the socio-cultural evolution and spatial dynamics of humans in prehistory. [From the publication]

DOI:
10.1016/j.quaint.2020.09.004
ISSN:
1040-6182
Subject:
Archeologija / Archaeology
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https://www.lituanistika.lt/content/95020
Updated:
2022-06-04 22:25:41
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