Abstract
The archaeological record represents a window onto the complex relationship between stone artefact variance and hominin behaviour. Differences in the shapes and sizes of stone flakes—the most abundant remains of past behaviours for much of human evolutionary history—may be underpinned by variation in a range of different environmental and behavioural factors. Controlled flake production experiments have drawn inferences between flake platform preparation behaviours, which have thus far been approximated by linear measurements, and different aspects of overall stone flake variability (Dibble and Rezek J Archaeol Sci 36:1945–1954, 2009; Lin et al. Am Antiq 724–745, 2013; Magnani et al. J Archaeol Sci 46:37–49, 2014; Rezek et al. J Archaeol Sci 38:1346–1359, 2011). However, when the results are applied to archaeological assemblages, there remains a substantial amount of unexplained variability. It is unclear whether this disparity between explanatory models and archaeological data is a result of measurement error on certain key variables, whether traditional analyses are somehow a general limiting factor, or whether there are additional flake shape and size drivers that remain unaccounted for. To try and circumvent these issues, here, we describe a shape analysis approach to assessing stone flake variability including a newly developed three-dimensional geometric morphometric method (‘3DGM’). We use 3DGM to demonstrate that a relationship between platform and flake body governs flake shape and size variability. Contingently, we show that by using this 3DGM approach, we can use flake platform attributes to both (1) make fairly accurate stone flake size predictions and (2) make relatively detailed predictions of stone flake shape. Whether conscious or instinctive, an understanding of this geometric relationship would have been critical to past knappers effectively controlling the production of desired stone flakes. However, despite being able to holistically and accurately incorporate three-dimensional flake variance into our analyses, the behavioural drivers of this variance remain elusive.
Highlights
Introduction and backgroundInterpreting variation in stone flakes is becoming one of the key focusses in reconstructions of hominin behavioural evolution (Dibble and Rezek 2009; Lin et al 2013; Magnani et al 2014; Odell 2000; Rezek et al 2011; Stout 2011)
Controlled flake production experiments have drawn inferences between flake platform preparation behaviours, which have far been approximated by linear measurements, and different aspects of overall stone flake variability (Dibble and Rezek J Archaeol Sci 36:1945– 1954, 2009; Lin et al Am Antiq 724–745, 2013; Magnani et al J Archaeol Sci 46:37–49, 2014; Rezek et al J Archaeol Sci 38:1346–1359, 2011)
Other research has emphasized the importance of variables which were exclusively associated with platform manipulation, such as platform size and exterior platform angle (EPA), with regard to control of the size and economization of knapped products (Braun et al 2009; Braun et al 2006; Dibble and Rezek 2009; Lin et al 2013; Magnani et al 2014; Rezek et al 2011)
Summary
Introduction and backgroundInterpreting variation in stone flakes is becoming one of the key focusses in reconstructions of hominin behavioural evolution (Dibble and Rezek 2009; Lin et al 2013; Magnani et al 2014; Odell 2000; Rezek et al 2011; Stout 2011). Replicative experiments tend to focus on documenting the processes of stone reduction leading to the formation of specific artefacts. This design often includes tracing the actions associated with different stages in these processes such as, for example, preparing complex core exploitation surfaces. Such approaches have established the complexity of the network of variables which influence flake morphology and have been influential in lithic analysis since the inception of interests in sequences of stone tool production (Buffon and Compte 1778 and see references in Johnson et al 1978). The application of replicative experimental approaches proliferated in the 1950s– 1960s (Bordes 1947; Bordes 1950; Bordes and Crabtree 1969; Crabtree 1966; Crabtree 1967; Crabtree 1968; Crabtree 1970; Crabtree 1972), and they still constitute the predominant way of holistically reconstructing past hominin technological decision making (Ahler 1989; Amick 1989; Amick et al 1988; Andrefsky 1986; Carr and Bradbury 2001; Eren et al 2016; Shen and Wang 2000)
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