Experimental and model-based approaches to studying artifact use-life

Matthew Douglass and colleagues recently published a paper entitled Core Use-Life Distributions in Lithic Assemblages as a Means for Reconstructing Behavioral Patterns in the Journal of Archaeological Method and Theory (DOI 10.1007/s10816-017-9334-2). In it they outline a novel quantitative approach to study the concept of artifact use-life.

Artifact use-life refers to the timeline across which an artefact is procured, modified, used, and discarded. This process can be exceedingly complex involving aspects of recycling and reuse and is quite often spread out across landscapes. However, the concept is useful for understanding several of the archaeological record’s more important behavioral elements such as raw material use, mobility, and the choice between various technological strategies.

Untitled-1

Plot showing the non-linear relationship between flake scar count and reduction intensity. Image modified after Douglass et al. 2017. 

Archaeologists use a wide range of techniques to measure stone artefact use-lives such as measuring flake cutting edge to mass ratios, determining artefact size, and quantifying artefact retouch intensity. Most research on the topic focuses disproportionately on artefact retouch as a strategy to extending an artefact’s use-life. Retouched tools make up a minor component of the archaeological record and studies focused only on retouched tools are therefore limited in size and scope.

Cores and unretouched flakes comprise most archaeological lithic assemblages. Understanding the use-life of cores can help unlock information about the strategies humans employ to extend the life of artefacts and how these processes play out across landscapes.

Lin and colleagues outline a series of lithic reduction experiments and archaeological data to develop objective methods for measuring core use-life. Their paper focuses on reduction intensity (defined as core mass lost at predetermined lithic reduction intervals) and survivorship curves (a statistical modeling concept borrowed from engineering and demographic research that measures the number or proportion of individuals surviving to a specific event horizon [age, reduction stage etc.]).

Their results speak to variability in two archaeological case studies from Pleistocene Kenya and Holocene Australia. Lin and colleagues draw on these two case studies to examine the relationship between core use-life, aspects of raw material variability, and variations in the human use of places on the landscape.

The paper has many notable aspects:

  1. It shows the value of experimental and archaeological research strategies driven by behavioral questions (i.e. how does archaeological assemblage variability form) rather than culture-historical questions (i.e. why one type of core became another type of core).
  2. It uses a predictive modeling framework to link experimental archaeology with archaeological lithic assemblages.
  3. It focuses on data distributions and variability instead of gross overall summaries of the data (i.e. mean or median point values).
  4. The authors focus on data transparency. The paper’s statistical codes (R code) and data are available as supplementary material.

Reference:

Douglass, M.J., Lin, S.C., Braun, D.R., Plummer, T.W., 2017. Core Use-Life Distributions in Lithic Assemblages as a Means for Reconstructing Behavioral Patterns, Journal of Archaeological Method and Theory, 1-35.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s