Abstract

Soil is among the most frequently transferred trace materials in violent crime, and its examination draws on an established suite of physical, chemical and biological methods whose resolution at fine spatial scales is nonetheless limited. Over the past decade, advances in high-throughput sequencing of the bacterial 16S rRNA gene, paired with supervised machine-learning classifiers, have been proposed as a means of discriminating soils that these methods cannot readily separate. This mini-review synthesises current evidence for the use of soil microbial biogeography in forensic geolocation, with specific emphasis on three questions of direct relevance to casework: (i) what spatial resolution is achievable with current sequencing and classification pipelines; (ii) how stable are location-discriminating taxa under the storage, transport, and environmental conditions typical of forensic exhibits; and (iii) whether the resulting evidence, as currently presented, can satisfy the gatekeeping standards articulated in Daubert v. Merrell Dow Pharmaceuticals and comparable frameworks outside the United States. We distinguish geographic discrimination, closed-set classification and source attribution, and show that reported accuracies in excess of 90 % derive from closed-set classification against small reference panels rather than from validated source attribution. We outline a minimum dataset that forensic microbial geolocation reports should contain before being offered in court. We conclude that the field has demonstrated promising discriminatory capability under defined conditions, but that forensic source attribution remains insufficiently validated, and that microbial profiling is best used alongside established soil examination rather than in place of it. We set out the infrastructural and empirical priorities that would close the gap between laboratory demonstration and routine evidentiary use.