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Pre-Columbian earth-builders settled along the entire southern rim of the Amazon

de Souza, Jonas Gregorio, Schaan, Denise Pahl, Robinson, Mark, Barbosa, Antonia Damasceno, Aragão, Luiz E. O. C., Marimon, Ben Hur, Marimon, Beatriz Schwantes, da Silva, Izaias Brasil, Khan, Salman Saeed, Nakahara, Francisco Ruji, Iriarte, José·2018·Nature Communications
DOI 10.1038/s41467-018-03510-7PMC PMC5871619
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Abstract

The discovery of large geometrical earthworks in interfluvial settings of southern Amazonia has challenged the idea that Pre-Columbian populations were concentrated along the major floodplains. However, a spatial gap in the archaeological record of the Amazon has limited the assessment of the territorial extent of earth-builders. Here, we report the discovery of Pre-Columbian ditched enclosures in the Tapajós headwaters. The results show that an 1800 km stretch of southern Amazonia was occupied by earth-building cultures living in fortified villages ~Cal AD 1250–1500. We model earthwork distribution in this broad region using recorded sites, with environmental and terrain variables as predictors, estimating that earthworks will be found over ~400,000 km 2 of southern Amazonia. We conclude that the interfluves and minor tributaries of southern Amazonia sustained high population densities, calling for a re-evaluation of the role of this region for Pre-Columbian cultural developments and environmental impact.

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  • Previous models also found temperature seasonality and related derivatives to be important predictors of earthworks.

    “Previous models also found temperature seasonality and related derivatives to be important predictors of earthworks (McMichael, Palace & Golightly, 2014; de Souza et al., 2018).”

    From Predicting the geographic distribution of ancient amazonian archaeological sites with machine learning (2023) · cites this paper as de Souza et al., 2018

  • LiDAR studies consistently show that settlement structures are more complex and interconnected (e.g., through road networks) than previously known.

    “Moreover, these LiDAR studies consistently show that settlement structures themselves are more complex and interconnected, through road networks for example, than what had been previously known.”

    From Predicting the geographic distribution of ancient amazonian archaeological sites with machine learning (2023) · cites this paper as de Souza et al., 2018

  • LiDAR studies show expansion of settlements and structures extending considerably farther in geographic extent than previously established through conventional fieldwork.

    “Like our machine learning model, these LiDAR studies show expansion of settlements and structures extending considerably farther in geographic extent than what had been previously established through conventional fieldwork.”

    From Predicting the geographic distribution of ancient amazonian archaeological sites with machine learning (2023) · cites this paper as de Souza et al., 2018

  • LiDAR studies are contributing to the growing evidence of Amazonian archaeological sites under vegetation or forest canopies.

    “LiDAR studies are contributing to the growing evidence of Amazonian archaeological sites under vegetation or forest canopies (de Souza et al., 2018; Iriarte et al., 2020b; Stenborg, Schaan & Figueiredo, 2018; Prümers et al., 2022).”

    From Predicting the geographic distribution of ancient amazonian archaeological sites with machine learning (2023) · cites this paper as de Souza et al., 2018

  • The general geographic distributions of earthworks and ADEs show clear patterns with the model's predictions and are consistent with previous models.

    “The general geographic distributions of earthworks and ADEs show clear patterns with the model’s predictions (Fig. 4) and are consistent with previous models (McMichael, Palace & Golightly, 2014; de Souza et al., 2018; McMichael et al., 2014; Palace et al., 2017; McMichael et al., 2017).”

    From Predicting the geographic distribution of ancient amazonian archaeological sites with machine learning (2023) · cites this paper as de Souza et al., 2018

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Metadata

Authors
de Souza, J. G., Schaan, D. P., Robinson, M., Barbosa, A. D., Aragão, L. E. O. C., Marimon, B. H., Marimon, B. S., da Silva, I. B., Khan, S. S., Nakahara, F. R., & Iriarte, J.
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2018-03-27
Volume
9
Issue
1
ISSN
2041-1723
DOI
10.1038/s41467-018-03510-7
PMC
PMC5871619
Cited by
98
References
2
Language
en
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