Articles | Volume 18, issue 9
https://doi.org/10.5194/essd-18-6925-2026
https://doi.org/10.5194/essd-18-6925-2026
Data description article
 | 
22 Sep 2026
Data description article |  | 22 Sep 2026

A random forest isoscape model of bioavailable Sr for South America: a focus on southern Brazil

Cinzia Scaggion, Tommaso Giovanardi, László Palcsu, Daniel Loponte, Mirian Carbonera, Sara Bernardini, Stefano Benazzi, Giulia Marciani, Marcos Cesar Pereira Santos, Eugenio Bortolini, Anna Cipriani, and Federico Lugli

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Cited articles

Andrushko, V. A., Buzon, M. R., Simonetti, A., and Creaser, R. A.: Strontium isotope evidence for prehistoric migration at Chokepukio, valley of Cuzco, Perù, Lat. Am. Antiq., 20, 57–75, 2009. 
Argentino, C., Lugli, F., Cipriani, A., and Panieri, G.: Testing miniaturized extraction chromatography protocols for combined 87Sr /86Sr and δ88/86Sr analyses of pore water by MC-ICP-MS, Limnol. Oceanogr.: Methods, 19, 431–440, https://doi.org/10.1002/lom3.10435, 2021. 
Armaroli, E., Lugli, F., Cipriani, A., and Tütken, T.: Spatial ecology of moose in Sweden: Combined Sr-O-C isotope analyses of bone and antler, PLoS One, 19, e0300867. https://doi.org/10.1371/journal.pone.0300867, 2024. 
Asrat, S., Lucchini, F., Tafuri, M. A., Aureli, C., Gallinaro, M., Zerboni, A., Fusco, M., and Spinapolice, E. E.: A strontium (87Sr /86Sr) isoscape of Southern Ethiopia: implications for hominin land use and faunal mobility patterns, Front. Environ. Archaeol. 4, https://doi.org/10.3389/fearc.2025.1499291, 2025. 
Avigliano, E., Chung, M.-T., Pouilly, M., Huang, K.-F., Casalinuovo, M., Dominino, J., Silva, N., Sánchez, S., Facetti, J. F., and Volpedo, A. V.: Strontium isotope mapping and its application to study the fish life history (Salminus brasiliensis) in semi-fragmented rivers (La Plata Basin, South America), Fish. Res., 265, 106741, https://doi.org/10.1016/j.fishres.2023.106741, 2023. 
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In this work, we present a new dataset of strontium isotopes from leaves collected in Santa Catarina and Rio Grande do Sul (Brazil). We combine these data with published South American records to produce a machine learning–based map of strontium isotope distribution across the continent. The dataset and model support studies of ancient mobility, provenance, and environmental and ecological processes.
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