The trajectory of bone surface modification studies in paleoanthropology and a new Bayesian solution to the identification controversy

Jacob A. Harris, Curtis Marean, Kiona Ogle, Jessica Thompson

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

A critical issue in human evolution is how to determine when hominins began incorporating significant amounts of meat into their diets. This fueled evolution of a larger brain and other adaptations widely considered unique to modern humans. Determination of the spatiotemporal context of this shift rests on accurate identification of fossil bone surface modifications (BSM), such as stone tool butchery marks. Multidecade-long debates over the agents responsible for individual BSM are indicative of systemic flaws in current approaches to identification. Here we review the current state of BSM studies and introduce a novel probabilistic approach to identifying agents of BSM. We use control assemblages of bones modified by modern agents to train a multivariate Bayesian probability model. The model then identifies BSM agents with associated uncertainties, serving as the basis for a predictive probabilistic algorithm. The multivariate Bayesian approach offers a novel, probabilistic, and analytical method for BSM research that overcomes much of the bias that has typified previous, more qualitative approaches.

Original languageEnglish (US)
Pages (from-to)69-81
Number of pages13
JournalJournal of Human Evolution
Volume110
DOIs
StatePublished - Sep 1 2017

Fingerprint

trajectories
bone
trajectory
bones
human evolution
paleoanthropology
Bone Surface Modifications
Paleoanthropology
Trajectory
meat
brain
train
analytical methods
analytical method
uncertainty
fossils
fossil
diet
trend

Keywords

  • Bayesian inference
  • Bone surface modification
  • Paleoanthropology
  • Taphonomy

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Education
  • Arts and Humanities (miscellaneous)

Cite this

The trajectory of bone surface modification studies in paleoanthropology and a new Bayesian solution to the identification controversy. / Harris, Jacob A.; Marean, Curtis; Ogle, Kiona; Thompson, Jessica.

In: Journal of Human Evolution, Vol. 110, 01.09.2017, p. 69-81.

Research output: Contribution to journalArticle

@article{693f38ada4f84a66adce8b2f6e9952ec,
title = "The trajectory of bone surface modification studies in paleoanthropology and a new Bayesian solution to the identification controversy",
abstract = "A critical issue in human evolution is how to determine when hominins began incorporating significant amounts of meat into their diets. This fueled evolution of a larger brain and other adaptations widely considered unique to modern humans. Determination of the spatiotemporal context of this shift rests on accurate identification of fossil bone surface modifications (BSM), such as stone tool butchery marks. Multidecade-long debates over the agents responsible for individual BSM are indicative of systemic flaws in current approaches to identification. Here we review the current state of BSM studies and introduce a novel probabilistic approach to identifying agents of BSM. We use control assemblages of bones modified by modern agents to train a multivariate Bayesian probability model. The model then identifies BSM agents with associated uncertainties, serving as the basis for a predictive probabilistic algorithm. The multivariate Bayesian approach offers a novel, probabilistic, and analytical method for BSM research that overcomes much of the bias that has typified previous, more qualitative approaches.",
keywords = "Bayesian inference, Bone surface modification, Paleoanthropology, Taphonomy",
author = "Harris, {Jacob A.} and Curtis Marean and Kiona Ogle and Jessica Thompson",
year = "2017",
month = "9",
day = "1",
doi = "10.1016/j.jhevol.2017.06.011",
language = "English (US)",
volume = "110",
pages = "69--81",
journal = "Journal of Human Evolution",
issn = "0047-2484",
publisher = "Academic Press Inc.",

}

TY - JOUR

T1 - The trajectory of bone surface modification studies in paleoanthropology and a new Bayesian solution to the identification controversy

AU - Harris, Jacob A.

AU - Marean, Curtis

AU - Ogle, Kiona

AU - Thompson, Jessica

PY - 2017/9/1

Y1 - 2017/9/1

N2 - A critical issue in human evolution is how to determine when hominins began incorporating significant amounts of meat into their diets. This fueled evolution of a larger brain and other adaptations widely considered unique to modern humans. Determination of the spatiotemporal context of this shift rests on accurate identification of fossil bone surface modifications (BSM), such as stone tool butchery marks. Multidecade-long debates over the agents responsible for individual BSM are indicative of systemic flaws in current approaches to identification. Here we review the current state of BSM studies and introduce a novel probabilistic approach to identifying agents of BSM. We use control assemblages of bones modified by modern agents to train a multivariate Bayesian probability model. The model then identifies BSM agents with associated uncertainties, serving as the basis for a predictive probabilistic algorithm. The multivariate Bayesian approach offers a novel, probabilistic, and analytical method for BSM research that overcomes much of the bias that has typified previous, more qualitative approaches.

AB - A critical issue in human evolution is how to determine when hominins began incorporating significant amounts of meat into their diets. This fueled evolution of a larger brain and other adaptations widely considered unique to modern humans. Determination of the spatiotemporal context of this shift rests on accurate identification of fossil bone surface modifications (BSM), such as stone tool butchery marks. Multidecade-long debates over the agents responsible for individual BSM are indicative of systemic flaws in current approaches to identification. Here we review the current state of BSM studies and introduce a novel probabilistic approach to identifying agents of BSM. We use control assemblages of bones modified by modern agents to train a multivariate Bayesian probability model. The model then identifies BSM agents with associated uncertainties, serving as the basis for a predictive probabilistic algorithm. The multivariate Bayesian approach offers a novel, probabilistic, and analytical method for BSM research that overcomes much of the bias that has typified previous, more qualitative approaches.

KW - Bayesian inference

KW - Bone surface modification

KW - Paleoanthropology

KW - Taphonomy

UR - http://www.scopus.com/inward/record.url?scp=85024114143&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85024114143&partnerID=8YFLogxK

U2 - 10.1016/j.jhevol.2017.06.011

DO - 10.1016/j.jhevol.2017.06.011

M3 - Article

C2 - 28778462

AN - SCOPUS:85024114143

VL - 110

SP - 69

EP - 81

JO - Journal of Human Evolution

JF - Journal of Human Evolution

SN - 0047-2484

ER -