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Soil is a ubiquitous material at the Earth's surface with potential to be a useful evidence class in forensic and intelligence applications. Compositional data from a soil survey over North Canberra, Australian Capital Territory, are used to develop and test an empirical soil provenancing method. Mineralogical data from Fourier Transform InfraRed spectroscopy (FTIR) and geochemical data from X-Ray Fluorescence (XRF; for total major oxides) and Inductively Coupled Plasma-Mass Spectrometry (ICP-MS; for both total and aqua regia-soluble trace elements) are obtained from the survey's 268 topsoil samples (0-5 cm depth; 1 sample per km

Knowledge of the mechanisms governing transfer, persistence, and recovery of trace evidence, together with background prevalence in the population of interest, and other task relevant information, is key for the forensic interpretation and reconstruction of what happened at the activity level. Up to now, this informational "toolkit" has largely been developed through empirical forensic studies on specific trace materials such as glass, textile fibers, and soil. Combined with the identified systemic siloing between disciplines, while valuable, such research tends to be very material-dependent, introducing specific parameters and interpretations that may have actually impeded the recognition of underlying foundational factors applicable to most material types. In Australia, there has been a renewed interest in developing a discipline-independent framework for the interpretation and/or reconstruction of trace evidence to interpret specific circumstances in casework. In this paper, we present a discipline agnostic "way of thinking" that has been anchored in foundational science underpinning the trace evidence discipline. Physical and mechanical material properties such as material geometry and surface topography, strength, stiffness, and hardness collectively influence contact interactions through underlying friction, wear, and lubrication cause and effect mechanisms. We discuss how these fundamental factors and parameters stemming from materials science and tribology may be adopted and adapted by forensic practitioners and researchers to contribute to a better understanding of transfer, persistence, and recovery mechanisms irrespective of evidence discipline and material type. Examples are provided to demonstrate the practical significance to real-life casework and academic research.

Compositional data from a soil survey over North Canberra, Australian Capital Territory, are used to develop and test an empirical soil provenancing method. Mineralogical data from Fourier transform infrared spectroscopy (FTIR) and magnetic susceptibility (MS), and geochemical data from X‐ray fluorescence (XRF; for total major oxides) and inductively coupled plasma‐mass spectrometry (ICP‐MS; for both total and aqua regia‐soluble trace elements) are performed on the survey's 268 topsoil samples (0–5 cm depth; 1 sample per km2). Principal components (PCs) are calculated after imputation of censored data and centered log‐ratio transformation. The sequential provenancing approach is underpinned by (i) the preparation of interpolated raster grids of the soil properties (including PCs); (ii) the explicit quantification and propagation of uncertainty; (iii) the intersection of the soil property rasters with the values of the evidentiary sample (± uncertainty); and (iv) the computation of cumulative provenance rasters (“heat maps”) for the various analytical techniques. The sequential provenancing method is tested on the North Canberra soil survey with three “blind” samples representing simulated evidentiary samples. Performance metrics of precision and accuracy indicate that the FTIR and MS (mineralogy), as well as XRF and total ICP‐MS (geochemistry) analytical methods, offer the most precise and accurate provenance predictions. Inclusion of PCs in provenancing adds marginally to the performance. Maximizing the number of analytes/analytical techniques is advantageous in soil provenancing. Despite acknowledged limitations and gaps, it is concluded that the empirical soil provenancing approach can play an important role in forensic and intelligence applications.