Mapping of spatial variations in Sr isotope signatures (Sr/Sr) in Poland - Implications of anthropogenic Sr contamination for archaeological provenance and migration research.

This study presents first isoscape maps of strontium isotope signatures and their spatial variation in Poland, based on ~900 samples of rocks, sediments, surface water, and flora. This dataset is supplemented by Sr/Sr ratios predicted for several carbonate rock units. High, radiogenic Sr isotope ratios (>0.72), related to the Pleistocene glacial deposits, are omnipresent throughout the country and are also found in the Sudetes and the Holy Cross Mountains, where igneous and clastic Palaeozoic rocks are widely exposed. The lowest Sr signatures (<0.71) occur predominantly in the Silesian-Małopolska and Lublin uplands and are related to exposures of Palaeozoic, Mesozoic, and Neogene carbonate rocks. The large variation of Sr/Sr ratios in the environment across the country is chiefly driven by the diversity in the geological substrate, and locally, it is also influenced by anthropogenic contamination. Strontium isoscapes for the geological substrate and surface waters differ from each other, in terms of the range of Sr/Sr values and their distributional pattern. The differences result primarily from mixing processes in the geosphere (weathering), hydrosphere, and biosphere that control Sr inputs from various natural sources present in the environment. On the other side, they are also created by anthropogenic contamination of surface water and presumably of soils. This situation has important implications for future archaeological provenance and migration studies, as isoscapes for surface water and vegetation cannot be directly used to estimate the local Sr/Sr baselines for past human populations. Therefore, caution is required when modern Sr data of surface water and plants are used in archaeological research. Sr/Sr values of the geological substrate, which may be affected by anthropogenic contamination to a lesser extent than water, soil, and vegetation, are favoured for the baseline estimation for historical times.