Emily Holt, Jane A. Evans, and Richard Madgwick
Drawing on variations in bioavailable strontium in different environments to provenance biological materials has become increasingly common since its first application in archaeology almost four decades ago, and it is frequently applied to zooarchaeological materials. Provenancing biological materials, including faunal remains, using strontium isotope ratios generally requires a map of bioavailable strontium, commonly known as an isoscape, to compare results with. However, both producing the isoscape and using it to interpret results present methodological challenges that researchers must carefully consider.
To help researchers understand the complexities of strontium analysis, we reviewed current research to produce a critical synthesis and recommend best practices. We addressed sampling the archives needed to build an isoscape, applying the different mapping and modeling methods currently available, and interpreting the results of archaeological analyses against isoscapes. Our critical review is freely available to read and download from Earth-Science Reviews until May 8, 2021
Sampling
Current research indicates that, while many archives can be analyzed to produce isoscapes, modern plant materials usually provide the best approximation of bioavailable strontium. Modern plants can be used alone or combined with other archives if applying a machine learning approach to mapping. In areas where erosion has significantly shifted the location of surface sediments, modern plants may not provide an appropriate archive for building an isoscape that is applicable to archaeological materials. In these areas, alternative archives such as archaeological rodent remains may be preferable. Archaeologists should also be aware that contemporary soil treatments like fertilizers may affect the bioavailable strontium in soils. Areas used for agriculture should be avoided when sampling.

It is essential to collect appropriate metadata when sampling. Collecting metadata improves the legacy benefits of strontium data by making them more broadly applicable. These metadata and the results of the analyses should be archived in one of several online databases to maximize their usefulness.
Mapping and modeling
We found that domain mapping currently produces the most accurate, most interpretable isoscapes for most research questions. However, machine learning approaches are also powerful and promise to provide more accurate and geographically wide-ranging isoscapes over time. Machine learning is computationally intensive and may not currently be an option for many researchers, but will be more widely available in the future.
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 utilized uncritically.
Interpretation
Strontium isotope analysis is currently the best developed and understood provenance tool. However, because isotope data can only exclude options of possible origin, the development of multi-isotope methods provides the route to a more powerful future approach. Using strontium isotope analysis for provenancing is most successful when combined with other isotopes and/or trace elements as part of a likelihood approach.
Future directions
In the future, we expect that increasing amounts of primary data and the increasing application of machine learning approaches to mapping will mean that strontium analysis continues to improve as a method of provenancing.
This research was apart of the ZANBA – Zooarchaeology of the Nuragic Bronze Age, a Marie Sklodowska Curie fellowship awarded to Emily Holt.

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