Published February 11, 2022 | Version v1
Dataset Open

Data and code for "Sustainable Human Population Density in Western Europe between 560.000 and 360.000 years ago"

Creators

  • 1. Centro Nacional de Investigación sobre la Evolución Humana (CENIEH), Paseo Sierra de Atapuerca 3, 09002, Burgos, Spain
  • 2. The Role of Culture in Early Expansions of Humans, Heidelberg Academy of Sciences and Humanities at the University of Tübingen, Research Area Geography, Rümelinstr. 19-23. 72070, Tübingen, Germany
  • 3. Institute of Geography, University of Cologne, 50923 Cologne, Germany

Description

This dataset contains the modeling results GIS data (maps) of the study “Sustainable Human Population Density in Western Europe between 560.000 and 360.000 years ago” by Rodríguez et al. (2022).

The NPP data (npp.zip) was computed using an empirical formula (the Miami model) from palaeo temperature and palaeo precipitation data aggregated for each timeslice from the Oscillayers dataset (Gamisch, 2019), as defined in Rodríguez et al. (2022, in review).

The Population densities file (pop_densities.zip) contains the computed minimum and maximum population densities rasters for each of the defined MIS timeslices. With the population density value Dc in logarithmic form log(Dc).

The Species Distribution Model (sdm.7z) includes input data (folder /data), intermediate results (folder /work) and results and figures (folder /results). All modelling steps are included as an R project in the folder /scripts. The R project is subdivided into individual scripts for data preparation (1.x), sampling procedure (2.x), and model computation (3.x).

The habitat range estimation (habitat_ranges.zip) includes the potential spatial boundaries of the hominin habitat as binary raster files with 1=presence and 0=absence. The ranges rely on a dichotomic classification of the habitat suitability with a threshold value inferred from the 5% quantile of the presence data.

The habitat suitability (habitat_suitability.zip) is the result of the Species Distribution Modelling and describes the environmental suitability for hominin presence based on the sites considered in this study. The values range between 0=low and 1=high suitability. The dataset includes the mean (pred_mean) and standard deviation (pred_std) of multiple model runs.

Notes

This research was supported by the MICINN project PID2019-105101GB-I00. The funding source was not involved in the study design, nor in the collection, analysis, or interpretation of data, the writing of the report, or in the decision to submit the article for publication. The research of CW was funded by the German Research Foundation (DFG) through the Collaborative Research Centre 806 (DFG project number 57444011). The work of CS is funded by the Research Project "The Role of Culture in Early Expansions of Humans" (ROCEEH) of the Heidelberg Academy of Sciences and Humanities.

Files

habitat_range.zip

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Additional details

References

  • Rodríguez, J., Willmes, C., & Mateos, A. (2021). Shivering in the Pleistocene. Human adaptations to cold exposure in Western Europe from MIS 14 to MIS 11. Journal of Human Evolution, 153, 102966. https://doi.org/10.1016/j.jhevol.2021.102966
  • Gamisch, A. (2019). Oscillayers: A dataset for the study of climatic oscillations over Plio-Pleistocene time-scales at high spatial-temporal resolution. Global Ecology and Biogeography, 28(11), 1552–1560. https://doi.org/10.1111/geb.12979
  • R Core Team. (2021). R: A language and environment for statistical computing (Version 4.0.5). Vienna, Austria: R Foundation for Statistical Computing. Retrieved from https://www.R-project.org/
  • Muscarella, R., Galante, P.J., Soley-Guardia, M., Boria, R.A., Kass, J., Uriarte, M. and R.P. Anderson (2014). ENMeval: An R package for conducting spatially independent evaluations and estimating optimal model complexity for ecological niche models. Methods in Ecology and Evolution.
  • Hijmans R. J. (2021). raster: Geographic Data Analysis and Modeling. R package version 3.4-13. https://CRAN.R-project.org/package=raster
  • Pebesma, E., 2018. Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10 (1), 439-446, https://doi.org/10.32614/RJ-2018-009
  • Bivand R. S., Pebesma E., Gomez-Rubio V., 2013. Applied spatial data analysis with R, Second edition. Springer, NY. https://asdar-book.org/
  • Bivand R. S., Keitt T. and Rowlingson B. (2021). rgdal: Bindings for the 'Geospatial' Data Abstraction Library. R package version 1.5-23. https://CRAN.R-project.org/package=rgdal
  • Sumner M. D. (2020). spdplyr: Data Manipulation Verbs for the Spatial Classes. R package version 0.4.0. https://CRAN.R-project.org/package=spdplyr
  • Wickham H., François R., Henry L. and Müller K. (2021). dplyr: A Grammar of Data Manipulation. R package version 1.0.7. https://CRAN.R-project.org/package=dplyr
  • H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016.
  • Wickham et al., (2019). Welcome to the tidyverse. Journal of Open Source Software, 4(43), 1686, https://doi.org/10.21105/joss.01686
  • Wilke, C.O. (2020). cowplot: Streamlined Plot Theme and Plot Annotations for 'ggplot2'. R package version 1.1.1. https://CRAN.R-project.org/package=cowplot
  • QGIS Development Team (2021). QGIS Geographic Information System. Open Source Geospatial Foundation Project. http://qgis.osgeo.org