Spatially Resolved Strontium Isotope Micro-Analysis of Lower and Middle Palaeolithic Fauna from Archaeological Sites in Israel and Southern France

Abstract

The use of strontium isotope analysis to provenance biominerals such as bone and teeth has become a regularly applied component of archaeological research. This method works by comparing the isotopic composition of these materials with regional bioavailable soil values, allowing an estimation of the distance and vector of an individual’s mobility. New advances in analytical equipment has facilitated the spatially resolved micro-analysis of strontium isotope composition using laser ablation sampling, allowing intra-sample heterogeneity to be quantified. This provides the opportunity to determine not only the overall provenance of a material, but also the degree of mobility during biomineral formation.This research applies laser ablation multi-collector inductively coupled plasma mass spectroscopy (LA-MC-ICPMS) to 90 teeth of Lower and Middle Palaeolithic faunal prey from Lower and Middle Palaeolithic archaeological sites within Israel and France. These sites span a crucial period in human evolution, characterised by the radiation of multiple hominin species and by dynamic oscillations of climate with attendant changes in fauna and flora. The strontium isotope values from LA-MC-ICPMS analysis in this thesis show a high level of intra-sample variability, which would not have been captured by a traditional analytical methodology. This suggests that, despite some problems in obtaining accurate results due to offsets between solution and laser values, strontium isotope studies that do not utilise spatially resolved micro-analysis are unable to accurately determine mobility.The results of this research demonstrate that fauna from the archaeological sites of interest—including Amud, Qafzeh, Tabun, Skhull, Holon, Bois Roche, Le Moustier, La Chapelle-aux-Saints, Les Fieux, Pech de l’Azé II and Rescoundudou—appear to have patterns of mobility that are controled by variables such as species, marine isotope stages (MIS) and regional physiography. Specifically, Persian fallow deer, bison, mountain goat/chamois and fox are frequently mobile between different geological environments during amelogenesis while wild boar and rhinoceros are sessile. The calculated range of distance for minimum possible mobility for each sample is large, ranging from 0 km to 350 km. The median values for minimum possible mobility for each species suggest that wild boar, bison and fox are mobile over the greatest distance while Bos, rhinoceros, Persian fallow deer and unidentified deer are mobile over the least. Furthermore, fauna in MIS 4 and 3 are significantly more mobile than in MIS 6 and 5. Fauna from France are more mobile than those from Israel, which is attributed to the location of the archaeological sites adjacent to significant river systems that could serve as conduits of mobility, even during inhospitable climate periods. Overall, these insights show that strontium isotope analysis can be usefully applied to quantifying mobility on a broad temporal and geographic scale, rather than simply being used, as is typical, for locating the source of material within a specific archaeological site.

Sampling Plants and Malacofauna in 87Sr/86Sr Bioavailability Studies: Implications for Isoscape Mapping and Reconstructing of Past Mobility Patterns

“…Field sampling for plants and snails was conducted in August 2013. Sampling locations (Figure 1) were based on the distribution of major geological units in the region of study, and then-specifically within each unit-selected to align as closely as possible with 24 locations included in a previous nationwide study of soil strontium isotope variability (Willmes et al, 2014) and from the doctoral thesis from one of the authors (Moffat, 2013) (see Supplementary Table 1). A handheld GPS was used to record the location of each plant and snail sampling locality (Garmin 2465, which is accurate to ± 15 m).…”

“…Soil samples had been analyzed as part of a previous unrelated study and include published and unpublished data (Moffat, 2013;Willmes et al, 2014). Soil samples were prepared following the method described in Willmes et al (2014).…”

“…Deciduous, coniferous and mixed forest habitats were grouped into a "forest" category, and pasture and complex cultivation pattern habitats into a "crop" category. Each plant and snail sampling site in the current study was associated with the closest soil sampling sites in the area (Moffat, 2013;Willmes et al, 2014). Finally, the underlying lithology of each site, as well as associated 87 Sr/ 86 Sr isotopes values, were extracted from the strontium isotope group of France map available at the IRHUM (Isotopic Reconstruction of Human Migration, www.irhumdatabase.com) FIGURE 2 | 87 Sr/ 86 Sr values of plants (grass, shrub, tree), snails and soil for each site.…”

Sampling plants and malacofauna in 87Sr/86Sr bioavailability studies: Implications for isoscape mapping and reconstructing of past mobility patterns

“…Deciduous, coniferous and mixed forest habitats were grouped into a "forest" category, and pasture and complex cultivation pattern habitats into a "crop" category. Each plant and snail sampling site in the current study was associated with the closest soil sampling sites in the area (Moffat, 2013;Willmes et al, 2014). Finally, the underlying lithology of each site, as well as associated 87 Sr/ 86 Sr isotopes values, were extracted from the strontium isotope group of France map available at the IRHUM (Isotopic Reconstruction of Human Migration, www.irhumdatabase.com) website (Willmes et al, 2014(Willmes et al, , 2018.…”

“…Here, we present a new strontium isotope bioavailability dataset for this region comprising almost 100 biological samples (plants, snails) collected at 17 different sampling locations and spanning 6 lithological units. Sampling locations were selected to align broadly with sampling locations of a previous study on soil strontium, including published and unpublished data (unpublished data from Moffat, 2013; published data from Willmes et al, 2014), allowing comparison of plant and snail measurements with soil values. The influence of a range of other variables was also explored including elevation, landuse/ forest cover, proximity to roads and rivers, and lithology.…”