Measuring allometry in dimensions of western North American Clovis points

Shott, Michael; Williams, Justin P.; Slade, Alan M.

doi:10.1016/j.jas.2021.105359

Cited by 7 publications

(5 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In LGM analyses, allometry multivariate regression tests for a relationship between the dependent differences in shape on independent differences in size [ 105 ]. CS is the standard size proxy in LGM analyses [ 106 :47], although other measurements may also be appropriate [ 85 ]. We use centroid sizes of the entire point (CSE), blade (CSB), and haft (CSH) shapes, which are calculated as the square root of the sum of the squared distances from all the LMs defining the shape to the shape’s center [ 48 , 83 ].…”

Section: Resultsmentioning

confidence: 99%

“…Hafts that are too short or narrow might allow the tool to slip or come loose in the handle rendering its use unsafe or ineffective. This assumption does not depend on how the point was attached to the handle or its shape, which for Clovis points is unknown and subject to debate (e.g., [ 22 , 26 , 42 , 85 ]). Regardless of how hafts were hafted, the strong integration of point hafts and blades indicates that proper functioning of the Clovis point required the haft and blade to be about the same width.…”

Section: Discussionmentioning

confidence: 99%

“…Changes in allometric rate and timing can make profound differences in an organism’s final phenotype [ 83 ]. In contrast to biological growth, allometric changes in chipped stone tools are in the opposite direction, tools becoming smaller through time, but mathematically the processes are identical [ 65 , 84 , 85 ]. LGM data are well-suited for allometry analysis because it treats shape independently of size.…”

Section: Incidence Of Allometry Modularity and Integration In Archaeo...mentioning

confidence: 99%

“…Shapes are rescaled to minimize size differences, so the shapes of a large Clovis cache point can be compared with a small non-cache point without the confounding effect of size. Allometry in LGM is identified by a line of best-fit in multivariate regression of shape on log-transformed size variables, usually centroid size (CS) [ 48 , 86 ], but allometry also can be studied in traditional tool dimensions, such as weight and length [e.g., 85 ].…”

Section: Incidence Of Allometry Modularity and Integration In Archaeo...mentioning

confidence: 99%

“…points is unknown and subject to debate (e.g., [22,26,42,85]). Regardless of how hafts were hafted, the strong integration of point hafts and blades indicates that proper functioning of the Clovis point required the haft and blade to be about the same width.…”

Section: Plos Onementioning

confidence: 99%

See 4 more Smart Citations

Clovis point allometry, modularity, and integration: Exploring shape variation due to tool use with landmark-based geometric morphometrics

Thulman

Shott

Slade³

et al. 2023

PLoS ONE

Self Cite

View full text Add to dashboard Cite

Landmark-based geometric morphometrics (LGM) is most often used in archaeology to characterize and differentiate groups of artifacts, but it can be used for much more. We demonstrate LGM’s power to uncover new insights by exploring stone-tool allometry, modularity, and integration using a sample of 100 western North American Clovis points. Here, allometry concerns how stone tools change in shape as their size changes through their use-lives, and modularity and integration concern how the constituent parts of a tool work together. We show that Clovis points are surprisingly complex tools. When their blades and hafts are defined technologically, rather than arbitrarily, they unambiguously exhibit allometry, and their hafts and blades are modular and highly integrated. We use these analyses to further explore questions about Clovis points, including the differences between cache and non-cache points. Finally, we use heuristic haft-size categories to examine functional constraints on the shape and size of hafts and blades. This work illustrates the importance of using accurate measurements of point components rather than estimates or proxies, which can lead to unfounded inferences. These analytical approaches and accompanying R code are easily transferable to other research questions of stone-tool use.

show abstract