Strontium (87Sr/86Sr) mapping: a critical review of methods and approaches

Holt, Emily; Evans, Jane A.; Madgwick, Richard. 2021 Strontium (87Sr/86Sr) mapping: a critical review of methods and approaches. Earth-Science Reviews, 216, 103593. 10.1016/j.earscirev.2021.103593

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Official URL: http://dx.doi.org/10.1016/j.earscirev.2021.103593

Abstract/Summary

The use of bioavailable strontium in different environments to provenance biological materials has become increasingly common since its first applications in ecology and archaeology almost four decades ago. Provenancing biological materials using strontium isotope ratios requires a map of bioavailable strontium, commonly known as an isoscape, to compare results with. Both producing the isoscape and using it to interpret results present methodological challenges that researchers must carefully consider. A review of current research indicates that, while many archives can be analyzed to produce isoscapes, modern plant materials usually provide the best approximation of bioavailable strontium and can be used alone or combined with other archives if applying machine learning. Domain mapping currently produces the most accurate, most interpretable isoscapes for most research questions; however, machine learning approaches promise to provide more accurate and geographically wide-ranging isoscapes over time. Using strontium isotope analysis for provenancing is most successful when combined with other isotopes and/or trace elements as part of a likelihood approach. Strontium isoscapes that are both appropriate and sufficiently high resolution to answer specific research questions do not exist for most parts of the world. Researchers intending to incorporate strontium analysis into their research designs should expect to conduct primary sampling and analysis to create appropriate isoscapes or refine existing ones, which should themselves not be uncritically utilized. When sampling, it is essential to collect appropriate metadata; these metadata and the results of the analyses should be archived in one of several online databases to maximize their usefulness. With increasing amounts of primary data and the likely increased availability of machine learning approaches to mapping, strontium analysis will continue to improve as a method of provenancing.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.1016/j.earscirev.2021.103593
ISSN:	00128252
Date made live:	13 Apr 2021 13:50 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/530048

Item Type:

Publication - Article

Digital Object Identifier (DOI):

10.1016/j.earscirev.2021.103593

ISSN:

00128252

Date made live:

13 Apr 2021 13:50 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/530048