Neandertal camps and hyena dens. Living floor 150A at Grotta dei Santi (Monte Argentario, Tuscany, Italy)

Abstract

Grotta dei Santi represents a very suitable investigation field for carrying out an inquiry into the Neandertal behaviour at a high-resolution time scale, in order to obtain data useful for the "functional" reading of the economic and settling strategies. This cave opens into the Monte Argentario Promontory (southern coast of Tuscany, central Italy), almost at sea-level, at the base of a limestone falaise about 50 m high. During MIS 3, when Neandertals occupied the site, there was a wide plain in front of the cave. Excavations carried out by the University of Siena over the last 11 years brought to light several Mousterian occupation phases represented, most of the times, by thin living floors separated from one another by sterile sediments. However, another "occupant", the spotted hyena (Crocuta crocuta), left clear traces in the cave in layers other than those occupied by humans. Although there usually is a clear-cut stratigraphic separation, a partial overlapping between the human and hyena occupations is sometimes documented, owing to their closeness in time. This is the case for the uppermost "living floor" of layer 150, which is the object of our study. A multidisciplinary integrated analytic methodology was applied, including lithic technology, taxonomic analysis of faunal remains, taphonomy, use-wear analysis and spatial analysis by means of a GIS platform. This approach allowed us to detect a set of parameters useful for identifying activities due to each of these two predators individually, which provided substantial information about their behaviours.

Defining and Characterising Clusters in Palaeolithic Sites: a Review of Methods and Constraints

“…Getis-Ord Gi* is the most widely used method (Sánchez-Romero et al, 2016Spagnolo et al, 2019Spagnolo et al, , 2020Mora et al, 2020;Giusti et al, 2018;inter alia). In spatial archaeology, we mainly work on analysing the distribution of materials in relatively small and limited areas (in comparison with other surfaces, such as those dealt with by geography or ecology), trying to understand the relationships of the different elements that make up the site as a whole, not only considering lithic and bone assemblages, but also structures (like hearths) or natural elements (like large blocks), and the space itself, such as cave walls.…”

“…-Applicable methods based on distance between remains: These methods use the XY coordinates of each item to calculate the distance and relation between them, evaluating their distributional patterns. Among these methods are Average Nearest Neighbour (ANN), Ripley's K Function (De la Torre et al, 2018;Giusti et al, 2018;Sánchez-Romero et al, 2020;Spagnolo et al, 2019Spagnolo et al, , 2020, General G, Getis-Ord Gi*, Global Moran's or Anselin Local Moran's I (Sánchez-Romero et al, 2016Shipton et al, 2018).…”

“…Density analysis is probably the most common method used in spatial archaeology (Sañudo et al, 2012;Sánchez-Romero et al, 2016Blasco et al, 2016;Pop et al, 2016;Spagnolo et al, 2016Spagnolo et al, , 2020Alperson-Afil, 2017;Villaverde et al, 2017;Giusti et al, 2018;Coil et al, 2020; inter alia) since it shows graphically where the entities are more or less concentrated. The use of this kind of map was introduced in the analysis of archaeological data in the 1980s (Carbonell et al, 1980;Hodder & Orton, 1976;Hodder, 1988)-drawn by hand-but it was not until the late 1990s that it experienced an increase in its application.…”

“…These methods (Table 3) allow the individual identification of levels of clustering, random or dispersion distribution of each variable in relation to the rest of the units through neighbourhood criteria. During recent years, these methods are starting to be applied to confer statistical significance on the cluster mapping Giusti et al, 2018;Mora et al, 2020;Sánchez-Romero et al, 2016Spagnolo et al, 2019Spagnolo et al, , 2020, with the aim of getting a more objective identification of the clusters in clustered distributions. These techniques can be applied to any quantitative variable, in order to assess different factors that could have boosted the concentration of materials at this point of the site.…”

“…When it comes to characterising the identified clusters, there are some widely used spatial techniques that enable the processes that could have affected the materials contained in each to be evaluated, such as analyses of orientation, slope and 3Dfabric (Benn, 1994;Bertran & Lenoble, 2002;Lenoble & Bertran, 2004;McPherron, 2005McPherron, , 2018Benito-Calvo & De la Torre, 2011;Benito-Calvo et al, 2009;García-Moreno et al, 2016;Sánchez-Romero et al, 2016;Spagnolo et al, 2020;inter alia). The isolation of the main clusters and their analysis permits the clustering features to be detailed, and therefore zooming in on the possible processes that could generate these accumulations.…”