Advances in global bioavailable strontium isoscapes

Strontium isotope ratios (Sr-87/Sr-86) are a popular tool in provenance applications in archeology, forensics, paleoecology, and environmental sciences. Using bioavailable Sr-87/Sr-86 in provenance studies requires comparing the Sr-87/Sr-86 of a sample of interest to that of Sr-87/Sr-86 baselines. Historically, these baselines required building empirical datasets from plants or local animals to characterize the Sr-87/Sr-86 available to local ecosystems (bioavailable Sr-87/Sr-86). However, researchers are increasingly relying on modeled bioavailable Sr-87/Sr-86 maps (called isoscapes). We review the advantages and limitations of existing approaches to mapping bioavailable Sr-87/Sr-86 for provenance studies and propose a globally applicable, scalable, and editable framework for creating bioavailable Sr-87/Sr-86 isoscapes. This framework relies on: 1) Compiling global bioavailable Sr-87/Sr-86 data; 2) Mapping Sr-87/Sr-86 variability in rocks; 3) Leveraging global environmental covariates; and 4) Applying a random forest regression method that integrates these data to predict bioavailable Sr-87/Sr-86. When the random-forest model is applied at the global scale it performs well (explaining 60% of the variance of the global bioavailable Sr-87/Sr-86 dataset), and accounts for geological, geomorphological and atmospheric controls. In data-rich regions (e.g., Europe), the global bioavailable Sr-87/Sr-86 isoscape can be successfully extrapolated to broad regions without bioavailable Sr-87/Sr-86 data. However, we also show that this extrapolation may not be valid in exceptionally geologically complex and data-poor regions (e.g., Madagascar). We suggest research directions to improve the accuracy of global bioavailable Sr-87/Sr-86 isoscapes, which include: 1) Increasing the collection of bioavailable datasets in data-poor regions; 2) Harmonizing data management practices and metadata collection for bioavailable Sr-87/Sr-86 data; and 3) Relying on advances in remote sensing and geological mapping techniques to improve geological covariates. While significant potential to refine Sr-87/Sr-86 isoscapes remains, the data products provided in this review form a basis for using Sr-87/Sr-86 data in large-scale provenance studies, opening new research avenues in a range of fields.