... The proliferation of the technique probably began with Gamble and colleagues (2005), who first identified 'population events' across Europe through the LGM using a large radiocarbon dataset from Europe. This paved the way for a large number of other studies around the world, most notably works on population histories through the terminal Pleistocene and Holocene in Europe, North America, South America, and Japan (e.g., Barbarena, Mendez, & Eugina de Porras, 2016;Barbarena, Prates, & Eugenia de Porras, 2015;Buchannan, Collard, & Edinborough, 2008;Buchanan, Hamilton, Edinborough, O'Brien, & Collard, 2011;Collard, Buchanan, Hamilton, & O'Brien, 2010;Collard, Edinborough, Shennan, & Thomas, 2010;Crema, Habu, Kobayashi, & Madella, 2016;Downey, Randall Hass, & Shennan, 2016;Gayo, Latorre, & Santoro, 2015;Robinson, Zahid, Codding, Hass, & Kelly 2019;Shennan & Edinborough, 2007;Shennan et al., 2013) and revolutionary work to de velop a technique to correct radiocarbon data for taphonomic loss through time (e.g., Johnson & Brook, 2011;Surovell & Brantingham, 2007;Surovell, Byrd Finley, Smith, Brantingham, & Kelly, 2009;Timpson et al., 2014) and/or spatial bias (Crema, Bevan, & Shennan, 2017). Similar to other geochronological fields, in recent years, researchers are continuing to refine the technique with increasingly complex exploration of Bayesian modelling and kernel density estimates (see Crema & Shoda, 2021, for discussion and re view). ...