https://github.com/cjabradshaw/archdatespopgrowth

Sahul-wide human population growth estimates from temporal distribution of archaeological dates

https://github.com/cjabradshaw/archdatespopgrowth

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Keywords

archaeology australia holocene late-pleistocene population-growth radiocarbon radiometric-dating sahul
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Sahul-wide human population growth estimates from temporal distribution of archaeological dates

Basic Info
  • Host: GitHub
  • Owner: cjabradshaw
  • License: mit
  • Language: R
  • Default Branch: main
  • Homepage:
  • Size: 89.8 KB
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archaeology australia holocene late-pleistocene population-growth radiocarbon radiometric-dating sahul
Created over 3 years ago · Last pushed over 3 years ago
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README.md

Sahul-wide human population growth

population growth icon DOI

Sahul-wide human population growth estimates from temporal distribution of archaeological dates between 40 ka and 5 ka

This R code recalculates Sahul-wide human population growth using a resampling approach (values originally presented in Williams, A.N., 2013. A new population curve for prehistoric Australia. Proc. R. Soc. Lond. B 280, 20130486).

This code accompanies the main analysis from this repository

General approach

  1. calibrate raw radiocarbon dates to calendar year using the rcarbon package (based on the shcal20 calibration curve for non-marine dates, and the marine20 calibration curve for marine dates [e.g., marine shells])
  2. assign calibrated dates into 200-year interval bins (iteratively, sampling from calibrated range per date)
  3. apply smoothing spline (df = 25) to number of dates per bin (iteratively)
  4. apply taphonomic correction (i.e., number of dates necessarily declines with age because of taphonomic loss - mean correction data from: Williams, A.N., 2012. The use of summed radiocarbon probability distributions in archaeology: a review of methods. J. Archaeol. Sci. 39, 578-589)
  5. calculate Williams' (2013) mean annual population growth (GRann) and instantaneous rate of exponential growth (r) for each resampled, corrected series:

GRann = 0.5(ni-1-ni)/ni

r = log(ni/ni-1)

where ni = number of dates in the older bin, ni-1 = number of dates in the younger bin

  1. correlate GRann & r for each iteration
  2. calculate 95% confidence interval of correlation
  3. plot reconstructed population growth curves per temporal bin (± 95% confidence limits)
  4. plot taphonomically corrected number of dates per temporal bin ((± 95% confidence limits)

Required R packages

  • ggplot2
  • stratigraphr
  • DescTools
  • rcarbon
  • stringr

Owner

  • Name: Corey Bradshaw
  • Login: cjabradshaw
  • Kind: user
  • Location: Adelaide, South Australia
  • Company: Flinders University

Matthew Flinders Professor of Global Ecology @GlobalEcologyFlinders @CABAH

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