Data from: Island-wide characterization of agricultural production challenges the demographic collapse hypothesis for Rapa Nui (Easter Island)
Data files
May 15, 2024 version files 1.14 MB
-
Mulch_Estimation.zip
-
README.md
-
Supplemental_Code.R
-
Supplemental_Document.pdf
-
Training_Data.zip
Abstract
Communities in resource-poor areas face health, food production, sustainability, and overall survival challenges. Consequently, they are commonly featured in global debates surrounding societal collapse. Rapa Nui (Easter Island) is often used as an example of how over-exploitation of limited resources resulted in a catastrophic population collapse. A vital component of this narrative is that the rapid rise and fall of pre-contact Rapanui population growth rates was driven by the construction and overexploitation of once extensive rock gardens. However, the extent of island-wide rock gardening, while key for understanding food systems and demography, must be better understood. Here, we use shortwave infrared (SWIR) satellite imagery and machine learning to generate an islandwide estimate of rock gardening and re-evaluate prior population size models for Rapa Nui. We show that the extent of this agricultural infrastructure is substantially less than previously claimed and likely could not have supported the large population sizes that have been assumed.
README: Data from: Island-wide characterization of agricultural production challenges the demographic collapse hypothesis for Rapa Nui (Easter Island)
Author Information:
- Principal Investigators: Dylan S. Davis
- Co-Investigators: Robert J. DiNapoli, Gina Pakarati, Terry L. Hunt, and Carl P. Lipo
Date of data collection/creation:
2023 January
Geographic location of data collection:
Rapa Nui, Chile
Funders and sponsors of data collection:
National Science Foundation (BCS-1841420, BCS-2218602), National Geographic Society’s Enduring Impacts: Archaeology of Sustainability Program (NGS-85450R-21)
DSD is supported by a National Science Foundation SBE Fellowship (SMA-2203789).
Sharing/Access Information
License & restrictions on data reuse:
Recommended citation for the data:
suggested: Davis, D. S., R. J. DiNapoli, G. Pakarati, T. L. Hunt, and C. P. Lipo (2023). Island-wide characterization of agricultural production challenges the demographic collapse hypothesis for Rapa Nui (Easter Island). Retrieved from https://doi.org/10.5061/dryad.gqnk98swd
Related publications:
Davis, D. S., R. J. DiNapoli, G. Pakarati, T. L. Hunt, and C. P. Lipo (2024). Island-wide characterization of agricultural production challenges the demographic collapse hypothesis for Rapa Nui (Easter Island). Science Advances. https://doi.org/10.1126/sciadv.ado1459
Data & File Overview
File list:
-- Supplemental_Document.pdf - R-markdown file of machine learning script developed to identify lithic mulching features from WorldView-3 satellite imagery.
-- Supplemental_Code.R - R script contained in the Markdown file.
-- Mulch_Estimation.zip -- zip folder containing a raster dataset with cleaned lithic mulching estimations for Rapa Nui. Data was produced using a Maximum Entropy algorithm and was manually evaluated to remove errors.
-- Training_Data.zip -- zip folder containing shapefiles with training data used for machine learning classification of WorldView-3 satellite images.
Additional notes:
ESRI. (2020). ArcGIS (10.8.1). Environmental Systems Research Institute, Inc.
R Core Team. (2020). R: A language and environment for statistical computing (4.0.2). R Foundation for Statistical Computing. http://www.R-project.org/
Methodological Information
See published manuscript for methodological information.