We describe a vision for a national-scale heavy mineral (HM) map generated through automated mineralogical identification and quantification of HMs contained in floodplain sediments from large catchments covering most of Australia. The composition of the sediments reflects the dominant rock types in each catchment, with the generally resistant HMs largely preserving the mineralogical fingerprint of their host protoliths through the weathering-transport-deposition cycle. Heavy mineral presence/absence, absolute and relative abundance, and co-occurrence are metrics useful to map, discover and interpret catchment lithotype(s), geodynamic setting, magmatism, metamorphic grade, alteration and/or mineralization. Underpinning this vision is a pilot project, focusing on a subset from the national sediment sample archive, which is used to demonstrate the feasibility of the larger, national-scale project. We preview a bespoke, cloud-based mineral network analysis (MNA) tool to visualize, explore and discover relationships between HMs as well as between them and geological settings or mineral deposits. We envisage that the Heavy Mineral Map of Australia and MNA tool will contribute significantly to mineral prospectivity analysis and modeling, particularly for technology critical elements and their host minerals, which are central to the global economy transitioning to a more sustainable, lower carbon energy model. The full, peer-reviewed article can be found here: Caritat, P. de, McInnes, B.I.A., Walker, A.T., Bastrakov, E., Rowins, S.M., Prent, A.M. 2022. The Heavy Mineral Map of Australia: vision and pilot project. Minerals, 12(8), 961, https://doi.org/10.3390/min12080961

Remotely sensed datasets provide fundamental information for understanding the chemical, physical and temporal dynamics of the atmosphere, lithosphere, biosphere and hydrosphere. Satellite remote sensing has been used extensively in mapping the nature and characteristics of the terrestrial land surface, including vegetation, rock, soil and landforms, across global to local-district scales. With the exception of hyper-arid regions, mapping rock and soil from space has been problematic because of vegetation that either masks the underlying substrate or confuses the spectral signatures of geological materials (i.e. diagnostic mineral spectral features), making them difficult to resolve. As part of the Exploring for the Future program, a new barest earth Landsat mosaic of the Australian continent using time-series analysis significantly reduces the influence of vegetation and enhances mapping of soil and exposed rock from space. Here, we provide a brief background on geological remote sensing and describe a suite of enhanced images using the barest earth Landsat mosaic for mapping surface mineralogy and geochemistry. These geological enhanced images provide improved inputs for predictive modelling of soil and rock properties over the Australian continent. In one case study, use of these products instead of existing Landsat TM band data to model chromium and sodium distribution using a random forest machine learning algorithm improved model performance by 28–46%. <b>Citation:</b> Wilford, J. and Roberts, D., 2020. Enhanced barest earth Landsat imagery for soil and lithological modelling. In: Czarnota, K., Roach, I., Abbott, S., Haynes, M., Kositcin, N., Ray, A. and Slatter, E. (eds.) Exploring for the Future: Extended Abstracts, Geoscience Australia, Canberra, 1–4.

<div>Environmental DNA (eDNA), elemental and mineralogical analyses of soil have been shown to be specific to their source material, prompting consideration of the use of dust for forensic provenancing. Dust is ubiquitous in the environment and is easily transferred to items belonging to a person of interest, making dust analysis an ideal tool in forensic casework. The advent of Next Generation Sequencing technologies means that metabarcoding of eDNA can uncover microbial, fungal, and even plant genetic fingerprints in dust particles. Combining this with elemental and mineralogical compositions offers multiple, complementary lines of evidence for tracing the origin of an unknown dust sample. This is particularly pertinent when recovering dust from a person of interest to ascertain where they may have travelled. Prior to proposing dust as a forensic trace material, however, the optimum sampling protocols and detection limits need to be established to place parameters around its utility in this context. We tested several approaches to collecting dust from different materials and determined the lowest quantity of dust that could be analysed for eDNA, geochemistry and mineralogy, whilst still yielding results capable of distinguishing between sites. We found that fungal eDNA profiles could be obtained from multiple sample types and that tape lifts were the optimum collection method for discriminating between sites. We successfully recovered both fungal and bacterial eDNA profiles down to 3&nbsp;mg of dust (the lowest tested quantity) and recovered elemental and mineralogical compositions for all tested sample quantities. We show that dust can be reliably recovered from different sample types, using different sampling techniques, and that fungal, bacterial, and elemental and mineralogical profiles, can be generated from small sample quantities, highlighting the utility of dust as a forensic provenance material.</div> <b>Citation:</b> Nicole R. Foster, Belinda Martin, Jurian Hoogewerff, Michael G. Aberle, Patrice de Caritat, Paul Roffey, Robert Edwards, Arif Malik, Priscilla Thwaites, Michelle Waycott, Jennifer Young, The utility of dust for forensic intelligence: Exploring collection methods and detection limits for environmental DNA, elemental and mineralogical analyses of dust samples, <i>Forensic Science International </i>, Volume 344, 2023, 111599, ISSN 0379-0738, https://doi.org/10.1016/j.forsciint.2023.111599. ISSN 0379-0738,

Geoscience Australia is currently assessing selected Australian sedimentary basins for their unconventional hydrocarbon resource potential, in collaboration with the Northern Territory and state governments. A study of the southern Georgina Basin is in progress, involving the compilation of a cross-border dataset of all accessible open file seismic, well, geological and geochemical data that will be publicly released in mid-2014. Major geochemical resampling of old wells has generated new information on source rock characteristics, kerogen kinetics, and gas and oil isotope geochemistry in the Georgina Basin. Preliminary 3D geology and 1D petroleum systems models have also been generated. Several cores from the Georgina Basin have been HyLogged by the geological surveys of Northern Territory, Queensland and New South Wales, using HyLogging facilities funded by AuScope Pty Ltd and CSIRO as part of the National Collaborative Research Infrastructure Strategy (NCRIS) and AuScope National Virtual Core Library (NVCL) Project. Geoscience Australia currently has a project underway to reprocess the raw HyLogging data using a common set of mineral scalars, to create an internally-consistent, basin-wide dataset. An initial composite HyLogging data package was publicly released in March 2014, including reprocessed data for 14 wells in the southern Georgina Basin, information about the processing methods used, and metadata. A second stage of the project will involve interpretation of the reprocessed data from these wells, to further examine the relationships between the spectroscopic and mineralogical properties measured by the HyLogger, and core total organic carbon (TOC), XRD, XRF and ICPMS compositional data, well log data, and biostratigraphic data. Initial work has indicated interesting trends, such as the apparent relationship between gamma intensity, core SWIR albedo (mean shortwave infrared reflectance) and quartz content. Peaks in gamma intensity broadly align with troughs in albedo, suggesting that the reduced albedo is a result of increased TOC content. However, in others cores (or even the same core), peaks in gamma intensity also appear to correlate with potassium-rich phases such as white micas and other clay minerals, thus the gamma correlation does not appear straightforward. Other preliminary observations indicate that using HyLogging data provides (i) the opportunity to review the existing formation picks in the basin from a mineralogical perspective, (ii) new information on variations in calcite/dolomite proportions in the carbonate sequences, (iii) the ability to map apatite distribution, and (iv) mineralogical evidence of sedimentary cyclicity. It is thus hoped that integrated interpretation of the HyLogging data and other data types will enable clearer delineation of the lower Arthur Creek Formation (and the 'Hot Shale' within) in the Georgina Basin, and therefore assist in constraining target intervals for future unconventional hydrocarbon resource assessments.

<div>The Heavy Mineral Map of Australia (HMMA) project1, part of Geoscience Australia’s Exploring for the Future program, determined the abundance and distribution of heavy minerals (HMs; specific gravity >2.9 g/cm3) in 1315 floodplain sediment samples obtained from Geoscience Australia’s National Geochemical Survey of Australia (NGSA) project2. Archived NGSA samples from floodplain landforms were sub-sampled with the 75-430 µm fraction subjected to dense media separation and automated mineralogy assay using a TESCAN Integrated Mineral Analysis (TIMA) instrument at Curtin University.</div><div><br></div><div>Interpretation of the massive number of mineral observations generated during the project (~150&nbsp;million mineral observations; 166 unique mineral species) required the development of a novel workflow to allow end users to discover, visualise and interpret mineral co-occurrence and spatial relationships. Mineral Network Analysis (MNA) has been shown to be a dynamic and quantitative tool capable of revealing and visualizing complex patterns of abundance, diversity and distribution in large mineralogical data sets3. To facilitate the application of MNA for the interpretation of the HMMA dataset and efficient communication of the project results, we have developed a Mineral Network Analysis for Heavy Minerals (MNA4HM) web application utilising the ‘Shiny’ platform and R package. The MNA4HM application is used to reveal (1) the abundance and co-occurrences of heavy minerals, (2) their spatial distributions, and (3) their relations to first-order geological and geomorphological features. The latter include geological provinces, mineral deposits, topography and major river basins. Visualisation of the mineral network guides parsimonious yet meaningful mapping of minerals typomorphic of particular geological environments or mineral systems. The mineralogical dataset can be filtered or styled based on mineral attributes (e.g., simplified mineralogical classes) and properties (e.g., chemical composition).</div><div><br></div><div>In this talk we will demonstrate an optimised MNA4HM workflow (identification à mapping à interpretation) for exploration targeting selected critical minerals important for the transition to a lower carbon global economy. </div><div><br></div><div>The MNA4HM application is hosted at https://geoscienceaustralia.shinyapps.io/mna4hm and is available for use by the geological community and general public.</div> This Abstract was submitted and presented to the 2023 Goldschmidt Conference Lyon, France (https://conf.goldschmidt.info/goldschmidt/2023/meetingapp.cgi)

<b>Please Note:</b> The data related to this Abstract can be obtained by contacting <a href = "mailto: clientservices@ga.gov.au">Manager Client Services</a> and quoting Catalogue number 144231. The data are arranged by regions, so please download the Data Description document found in the Downloads tab to determine your area of interest. Remotely sensed datasets provide fundamental information for understanding the chemical, physical and temporal dynamics of the atmosphere, lithosphere, biosphere and hydrosphere. Satellite remote sensing has been used extensively in mapping the nature and characteristics of the terrestrial land surface, including vegetation, rock, soil and landforms, across global to local-district scales. With the exception of hyper-arid regions, mapping rock and soil from space has been problematic because of vegetation that either masks the underlying substrate or confuses the spectral signatures of geological materials (i.e. diagnostic mineral spectral features), making them difficult to resolve. As part of the Exploring for the Future program, a new barest earth Landsat mosaic of the Australian continent using time-series analysis significantly reduces the influence of vegetation and enhances mapping of soil and exposed rock from space. Here, we provide a brief background on geological remote sensing and describe a suite of enhanced images using the barest earth Landsat mosaic for mapping surface mineralogy and geochemistry. These geological enhanced images provide improved inputs for predictive modelling of soil and rock properties over the Australian continent. In one case study, use of these products instead of existing Landsat TM band data to model chromium and sodium distribution using a random forest machine learning algorithm improved model performance by 28–46%.

Bulk quantitative mineralogy of regolith is a useful indicator of lithological precursor (protolith), degree of weathering, and soil properties affecting various potential landuse decisions. To date, no national-scale maps of regolith mineralogy are available in Australia. Catchment outlet sediments collected over 80% of the continent as part of the National Geochemical Survey of Australia (NGSA) afford a unique opportunity to rapidly and cost-effectively determine regolith mineralogy using the archived sample material. This report releases mineralogical data and metadata obtained as part of a feasibility study in a selected pilot area for such a national regolith mineralogy database and atlas. The area chosen for this study is within the Darling-Curnamona-Delamerian (DCD) region of southeastern Australia. The DCD region was selected as a ‘deep-dive’ data acquisition and analysis by the Exploration for the Future (2020-2024) federal government initiative managed at Geoscience Australia. One hundred NGSA sites from the DCD region were prepared for X-Ray Diffraction (XRD) analysis, which consisted of qualitative mineral identification of the bulk samples (i.e., ‘major’ minerals), qualitative clay mineral identification of the <2 µm grain-size fraction, and quantitative analysis of both ‘major’ and clay minerals of the bulk sample. The identified mineral phases were quartz, plagioclase, K-feldspar, calcite, dolomite, gypsum, halite, hematite, goethite, rutile, zeolite, amphibole, talc, kaolinite, illite (including muscovite and biotite), palygorskite (including interstratified illite-smectite and vermiculite), smectite (including interstratified illite-smectite), vermiculite, and chlorite. Poorly diffracting material (PDM) was also quantified and reported as ‘amorphous’. Mineral identification relied on the EVA® software, whilst quantification was performed using Siroquant®. Resulting mineral abundances are reported with a Chi-squared goodness-of-fit between the actual diffractogram and a modelled diffractogram for each sample, as well as an estimated standard error (esd) measurement of uncertainty for each mineral phase quantified. Sensitivity down to 0.1 wt% (weight percent) was achieved, with any mineral detection below that threshold reported as ‘trace’. Although detailed interpretation of the mineralogical data is outside the remit of the present data release, preliminary observations of mineral abundance patterns suggest a strong link to geology, including proximity to fresh bedrock, weathering during sediment transport, and robust relationships between mineralogy and geochemistry. The mineralogical data generated by this study are presented in Appendix A of this report and are downloadable as a .csv file. Mineral abundance or presence/absence maps are shown in Appendices B and C to document regional mineralogical patterns.

<div>This look-book was developed to accompany the specimen display in the office of the Hon Madeleine King MP, Minister for Resources and Northern Australia. It contains information about each of the specimens including their name, link to resource commodities and where they were from. </div><div><br></div><div>The collection was carefully curated to highlight some of Australia’s well known resources commodities as well as the emerging commodities that will further the Australian economy and contribute to the low energy transition. The collection has been sourced from Geoscience Australia’s National Mineral and Fossil Collection. </div><div><br></div><div>The collection focuses on critical minerals, ore minerals as well as some fuel minerals. These specimens align with some of Geoscience Australia major projects including the Exploring For the Future (EFTF) program, the Trusted Environmental and Geological Information program (TEGI) as well as the Repository and the public education and outreach program.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</div>

During the last 10-20 years, Geological Surveys around the world have undertaken a major effort towards delivering fully harmonized and tightly quality controlled low-density multi-element soil geochemical maps and datasets of vast regions including up to whole continents. Concentrations of between 45 and 60 elements commonly have been determined in a variety of different regolith types (e.g., sediment, soil). The multi-element datasets are published as complete geochemical atlases and made available to the general public. Several other geochemical datasets covering smaller areas but generally at a higher spatial density are also available. These datasets may, however, not be found by superficial internet-based searches because the elements are not mentioned individually either in the title or in the keyword lists of the original references. This publication attempts to increase the visibility and discoverability of these fundamental background datasets covering large areas up to whole continents. <b>Citation:</b> P. de Caritat, C. Reimann, D.B. Smith, X. Wang, Chemical elements in the environment: Multi-element geochemical datasets from continental- to national-scale surveys on four continents, <i>Applied Geochemistry</i>, Volume 89, 2018, Pages 150-159, ISSN 0883-2927, https://doi.org/10.1016/j.apgeochem.2017.11.010

<div>The ubiquitous nature of dust, along with localised chemical and biological signatures, makes it an ideal medium for provenance determination in a forensic context. Metabarcoding of dust can yield biological communities unique to the site of interest, similarly, geochemical and mineralogical analyses can uncover elements and minerals within dust than can be matched to a geographic location. Combining these analyses presents multiple lines of evidence as to the origin of collected dust samples. In this work, we investigated whether the time an item spent at a site collecting dust influenced the ability to assign provenance. We then integrated dust metabarcoding of bacterial and fungal communities into a framework amenable to forensic casework, (i.e., using calibrated log-likelihood ratios to predict the origin of dust samples) and assessed whether current soil metabarcoding databases could be utilised to predict dust origin. Furthermore, we tested whether both metabarcoding and geochemical/mineralogical analyses could be conducted on a single sample for situations where sampling is limited. We found both analyses could generate results capable of separating sites from a single swabbed sample and that the duration of time to accumulate dust did not impact site separation. We did find significant variation within sites at different sampling time periods, showing that bacterial and fungal community profiles vary over time and space – but not to the extent that they are non-discriminatory. We successfully modelled soil and dust samples for both bacterial and fungal diversity, developing calibrated log-likelihood ratio plots and used these to predict provenance for dust samples. We found that the temporal variation in community composition influenced our ability to predict dust provenance and recommend reference samples be collected as close to the sampling time as possible. Thus, our framework showed soil metabarcoding databases are capable of being used to predict dust provenance but the temporal variation in metabarcoded communities will need to be addressed to improve provenance estimates.&nbsp;</div> <b>Citation:</b> Nicole R. Foster, Duncan Taylor, Jurian Hoogewerff, Michael G. Aberle, Patrice de Caritat, Paul Roffey, Robert Edwards, Arif Malik, Michelle Waycott and Jennifer M. Young, The secret hidden in dust: Uncovering the potential to use biological and chemical properties of the airborne soil fraction to assign provenance and integrating this into forensic casework, <i>Forensic Science International: Genetics,</i> (2023) doi:https://doi.org/10.1016/j.fsigen.2023.102931