The critical metal germanium (Ge) is recovered as a by-product of mining other commodities, such as zinc and thermal coal. We investigated the Ge incorporation mechanism in sphalerite synthesized under hydrothermal conditions like those of sediment-hosted Zn-Pb deposits. Sphalerite +/- galena +/- barite formed via reactions of Ge +/- Fe +/- Cu +/- Ba-bearing brine with calcite and reduced sulfur at 200 degrees C and water vapor-saturated pressure. The products were examined using backscattered electron (BSE) imag-ing, electron probe microanalysis (EPMA), electron backscattered diffraction (EBSD), synchrotron X-ray fluorescence (SXRF) and micro-X-ray absorption near-edge structure (l-XANES). We show that Ge(IV) is incorporated into sphalerite and bonded with reduced sulfur, both in the experimental sphalerite and in natural zinc ore samples from the MacArthur River Zn-Pb-Ag deposits, Australia. Copper K-edge XANES spectra show that copper occurs as Cu(I) in the experimental sphalerite, consistent with previous studies on Cu in natural sphalerite. The experiments reveal that Ge(IV) substitution in sphalerite occurs with and without the presence of other metal ions (e.g., Cu(I)), indicating that Ge(IV) substitution can be accommodated via charge balance by vacancies as well as by coupled substitution in the synthesized sphalerite. Ab initio quantum chemical simulations confirm that sphalerite can readily accommodate Ge, with the crystal structure and average Zn-S, Zn-Zn, S-S distances retained when replacing > 3 mol% of the Zn sites with Ge(IV), Ge(II), Cu(I) or Fe(II), demonstrating the resilience and flexibility of the sphalerite crystal structure. These Ge incorporation mechanisms explain the previous observations of multiple ways of Ge incorporation in natural sphalerite. The study provides experimental and molecular simulation insights for understanding the processes related to the formation and extraction of Ge in zinc ores.(c) 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Manganese (Mn) oxidation in marine environments requires oxygen (O 2 ) or other reactive oxygen species in the water column, and widespread Mn oxide deposition in ancient sedimentary rocks has long been used as a proxy for oxidation. The oxygenation of Earth's atmosphere and oceans across the Archean‐Proterozoic boundary are associated with massive Mn deposits, whereas the interval from 1.8–1.0 Ga is generally believed to be a time of low atmospheric oxygen with an apparent hiatus in sedimentary Mn deposition. Here, we report geochemical and mineralogical analyses from 1.1 Ga manganiferous marine‐shelf siltstones from the Bangemall Supergroup, Western Australia, which underlie recently discovered economically significant manganese deposits. Layers bearing Mn carbonate microspheres, comparable with major global Mn deposits, reveal that intense periods of sedimentary Mn deposition occurred in the late Mesoproterozoic. Iron geochemical data suggest anoxic‐ferruginous seafloor conditions at the onset of Mn deposition, followed by oxic conditions in the water column as Mn deposition persisted and eventually ceased. These data imply there was spatially widespread surface oxygenation ~1.1 Ga with sufficiently oxic conditions in shelf environments to oxidize marine Mn(II). Comparable large stratiform Mn carbonate deposits also occur in ~1.4 Ga marine siltstones hosted in underlying sedimentary units. These deposits are greater or at least commensurate in scale (tonnage) to those that followed the major oxygenation transitions from the Neoproterozoic. Such a period of sedimentary manganogenesis is inconsistent with a model of persistently low O 2 throughout the entirety of the Mesoproterozoic and provides robust evidence for dynamic redox changes in the mid to late Mesoproterozoic.

We report new assemblages of well-preserved organic-walled microfossils from the >1.648Ga Mallapunyah Formation (McArthur Group) and the 1.78-1.73Ga McDermott Formation (Tawallah Group), McArthur Basin, Australia.These assemblages include entangled filamentous sheaths, pseudobranching filaments and akinete-like vesicles of probable cyanobacterial origin; smooth-walled vesicles, with diverse shapes, wall textures and size (up to few hundred microns), excystment structures or budding; and vesicles ornamented with concentric striations (Valeria), equatorial flange (Simia), organic plates (Dictyosphaera), and processes and other expansions from the vesicle wall (Tappania).Known fossil bacterial walls and sheaths do not show such wall ornamentation.Although filamentous protrusions are known in one archaeon and in PVC Bacteria, showing that prokaryotes may show complex morphologies supported by their cytoskeleton, the microfossils size strongly differ by one or two orders of magnitude from them.In contrast, the morphological complexity of fossils reported here is only known in eukaryotes and implies cytological sophistication for the synthesis of organic plates, external equatorial outgrowth, internal concentric ridges, and diverse protrusions indirectly evidencing the presence of a cytoskeleton.Collectively, these assemblages reveal an ecosystem with cyanobacterial mat fragments, diverse prokaryotic or eukaryotic cells, various stages of life cycle, and ornamented protists, known in the late Paleoproterozoic-Mesoproterozoic.This record pushes back the minimum age of eukaryotic fossils, previously reported at ~1.65 Ga in China and Australia.Asgard Archaeal genomes (closest relatives to eukaryotes) suggest that some cellular complexity, including the cytoskeleton, may have emerged before other eukaryotic cellular features characterizing LECA, such as the mitochondria, nucleus and endomembrane system, but the timing and relative order of evolution of these traits through eukaryogenesis is debated.The early protists reported here thrived in anoxic-suboxic sulfurlimited near-shore water, close to cyanobacterial mats.Their distinctive complex morphology suggests an earlier evolution of simpler stem eukaryotes (before LECA), in the older Paleoproterozoic or Archean record preserving large unornamented microfossils.Because of their long stratigraphic range, the fossils reported here could represent stem eukaryotes pursuing their evolution for some time after crown-group diversification, or alternatively, they provide a minimum age for LECA, consistent with several molecular clocks, perhaps with metabolically versatile mitochondria

The McArthur River (HYC) Zn-Pb-Ag deposit in the Carpentaria Zn belt, northern Australia, is one of the world’s largest and most studied sediment-hosted base metal deposits, owing to its lack of deformation and preservation of sedimentary and ore textures. However, the ore formation process (syngenetic vs. epigenetic) is still a subject of controversy. In this paper we focus on key characteristics of the HYC deposit that remain unexplained: preservation of sedimentary carbonate (dolomite) and its association with Zn, and the role of thallium (Tl) and manganese (Mn) distribution in the orebody. Our findings demonstrate a sequence of events during ore formation: Tl is hosted almost exclusively within euhedral pyritic overgrowths around early diagenetic pyrite; sphalerite mineralization occurred after Tl-bearing pyrite overgrowths, in association with acid dissolution (replacement) of laminated and nodular dolomite across the subbasin; and outer rims are enriched in Mn on preserved dolomite at the dissolution reaction front in contact with sphalerite. New thermodynamic fluid chemistry modeling demonstrates the metal distribution and paragenesis can be explained by acidic, oxidized ore fluids entering the pyrite-dolomite host lithology, allowing reduction and pH buffering by acid carbonate dissolution, resulting in stepwise metal deposition in an evolving fluid. We argue this represents strong evidence for epigenetic ore formation at HYC. Furthermore, the primary control on ore deposition is not synsedimentary faulting in the subbasin; rather, the chemical potential of sedimentary carbonate within reduced, sulfidic lithologies appears to be of critical importance to precipitation of sphalerite.

Details of the experiments, analysis, and modeling

Recently discovered Au in boulder conglomerate between the Mesoarchean West Pilbara superterrane basement and the overlying volcano-sedimentary stratigraphy of the Neoarchean Fortescue Group in Western Australia has renewed comparisons with the Witwatersrand conglomerate Au deposits in South Africa. As such, this has reignited the question of the Pilbara and Kaapvaal cratons being linked as part of the postulated Vaalbara continent during the Archean. However, little is known about the origin of the Pilbara conglomerate Au and its host conglomerates, as they are hitherto unstudied, and their formation and/or source is uncertain. Here we present a detailed study on the textures, composition, and sedimentology of one newly discovered Pilbara conglomerate Au deposit at the base of the Neoarchean Fortescue Group in the northwestern Pilbara craton. The Pilbara conglomerate Au occurrences are characteristically Ag-bearing but Hg-poor polycrystalline discoid masses that are overgrown by Au-poor chloritic halos, which are further enveloped by a hydrothermal alteration halo of disseminated Au within chlorite. Both the discoids and the auriferous chlorite halo are Ag bearing, with up to similar to 9 wt % Ag, consistent with a hydrothermal (orogenic) origin. The discoids do not display any physical or chemical evidence for sedimentary transport; thus, their formation (placer versus hydrothermal) remains unclear. However, the position of the Au in the conglomerate, limited to the basal section of the conglomerate, is difficult to account for in a purely hydrothermal deposit model. We argue the Pilbara conglomerate Au represents a modified placer deposit from a primary orogenic Au source, with surface evidence for sedimentation removed by partial dissolution during later hydrothermal alteration in the host conglomerate and the crystalline basement. While the basal Fortescue Group conglomerate Au shares commonalities with the time equivalent (>similar to 2.7 Ga) Venterspost Conglomerate Formation, which overlies the Witwatersrand Supergroup, inconsistencies remain, with different Au chemistries and tectonic, magmatic, sedimentary, and metamorphic-metallogenic histories of the Pilbara and Kaapvaal cratons prior to deposition of the >2.7 Ga conglomerate sequences. This collectively indicates the drivers of Au metallogenesis and ultimate Au deposition in conglomerate facies were fundamentally different in the Pilbara and Kaapvaal cratons.

Geobiology explores how Earth's system has changed over the course of geologic history and how living organisms on this planet are impacted by or are indeed causing these changes. For decades, geologists, paleontologists, and geochemists have generated data to investigate these topics. Foundational efforts in sedimentary geochemistry utilized spreadsheets for data storage and analysis, suitable for several thousand samples, but not practical or scalable for larger, more complex datasets. As results have accumulated, researchers have increasingly gravitated toward larger compilations and statistical tools. New data frameworks have become necessary to handle larger sample sets and encourage more sophisticated or even standardized statistical analyses. In this paper, we describe the Sedimentary Geochemistry and Paleoenvironments Project (SGP; Figure 1), which is an open, community-oriented, database-driven research consortium. The goals of SGP are to (1) create a relational database tailored to the needs of the deep-time (millions to billions of years) sedimentary geochemical research community, including assembling and curating published and associated unpublished data; (2) create a website where data can be retrieved in a flexible way; and (3) build a collaborative consortium where researchers are incentivized to contribute data by giving them priority access and the opportunity to work on exciting questions in group papers. Finally, and more idealistically, the goal was to establish a culture of modern data management and data analysis in sedimentary geochemistry. Relative to many other fields, the main emphasis in our field has been on instrument measurement of sedimentary geochemical data rather than data analysis (compared with fields like ecology, for instance, where the post-experiment ANOVA (analysis of variance) is customary). Thus, the longer-term goal was to build a collaborative environment where geobiologists and geologists can work and learn together to assess changes in geochemical signatures through Earth history. With respect to the data product, SGP is focused on assembling a well-vetted and comprehensive dataset that is tractable to multivariate statistical analyses accounting for multiple geological and methodological biases. Phase 1 of the project, which focused on the Neoproterozoic and Paleozoic, has been completed. Future phases will capture a broader range of geologic time, data types, and geography. The database contains tens of thousands of unpublished data points provided by consortium members, as well as detailed metadata that go beyond what is contained in papers. In many cases, these represent measurements that are tangential to a given published study but still of high utility to database studies; these allow the community to address questions that would be impossible to answer solely with the published data. For instance, in order to use a proxy such as Mo/TOC (total organic carbon) ratios in mudrocks deposited under a euxinic water column, the full suite of trace metal, iron speciation, and total organic carbon data is needed. Likewise, geospatial information is required to account for sampling biases, and many statistical learning approaches cannot accept, or have difficulty with, incomplete geological predictor variables. Ultimately, it is this complete data matrix that will allow for SGP's most insightful analyses. This paper serves as an introduction to SGP, the process by which our data products are created, a description of the Phase 1 data product and a citable reference for that product, a description of the SGP website and API (Application Programming Interface) for open access, and a statement of our future goals. In recent years, there has been a welcome trend in the broader geochemical community toward increased data accessibility, documentation of sample context, and sample curation, albeit with challenges still ahead (Brantley et al., 2020; Cutcher-Gershenfeld et al., 2016; Planavsky et al., 2020). First, progress has been made through journals and organizations adopting stringent data archiving rules and promoting adherence to FAIR principles—findability, accessibility, interoperability, and reusability ("FAIR Play in Geoscience Data," 2019; Wilkinson et al., 2016). Second, several databases now house geochemical data at different scales and with different focuses (Brantley et al., 2020; Gard et al., 2019; He et al., 2019; Lehnert et al., 2000). Among the largest and most active are projects such as EarthChem (earthchem.org), the Geobiodiversity Database (geobiodiversity.com), Pangaea (https://www.pangaea.de), and the StabisoDB (https://cnidaria.nat.uni-erlangen.de/stabisodb/). The SGP database was built with the data structures and standards of these other projects in mind, in keeping with FAIR principles and with the hope that data can be easily shared in the future. Consistent with the stance taken by other organizations in the community (Hanson, 2016), we also strongly encourage all members to register their samples for an International Geo Sample Number (IGSN; i.e., globally unique alphanumeric sample identifiers), which can be obtained from the System for Earth Sample Registration (www.geosamples.org). However, SGP is a domain-specific project that differs from other databases in the way the data are collected, the nature of the data collected, and the tailored way in which they are presented to our research community. Although some other databases contain sedimentary geochemical data, the vast majority of deep-time data is not available from any single source, and samples are not readily associated with critical contextual data—such as age constraints and environmental data—necessary for the types of proxy-through-time and/or environmental studies typically conducted in historical geobiology. When the SGP was founded in 2015, we believed that a "team science" philosophy would be the most effective way to move beyond spreadsheets to the type and abundance of data required. The research consortium framework we have implemented is modeled after mature consortia in human statistical genetics, such as the Psychiatric Genomics Consortium (PGC). In the PGC, researchers have aggregated data to make statistically robust observations and landmark findings not possible with the data generated by any single research group alone (Duncan et al., 2017; Schizophrenia Working group of the Psychiatric Genomics Consortium, 2014; Wray et al., 2018). Similar to biomedical research consortia, we hope that the intellectual and collaborative environment fostered by SGP will ultimately be as important as our data products or specific insights in research papers. The first priority for Phase 1 of SGP was to assemble or generate multi-proxy sedimentary geochemical data (carbon and sulfur abundances and isotopes, iron speciation, major and trace metal abundances, and trace metal isotopes, primarily from fine-grained siliciclastic rocks) from multiple regions worldwide for every Paleozoic Epoch and equivalent ~25 Myr Neoproterozoic time slice. In addition to data compilation, this has involved an effort by SGP members to generate new geochemical data from "background" intervals in the Paleozoic (i.e., not associated with events such as mass extinctions or significant climatic shifts). The first phase of data collection came to an end in 2019. At that point, a copy of the database was vetted by SGP team members and then archived—the first data "freeze" (following the best-practices approach used in medical consortia). Working groups were formed (with working group leadership established through an open call to SGP team members), and data were made available to Working group analysts via the website and through tailored queries. The first working group papers have recently been published (LeRoy et al., 2021; Lipp et al., 2021; Mehra et al., 2021), and more are in progress. Meanwhile, data collection continues, and the Phase 2 goal is to include more Mesozoic–Cenozoic and pre-Neoproterozoic time intervals and to expand the geochemical record to more diverse lithologies and grain-specific phases. The Phase 2 data freeze is currently anticipated for 2023, followed by data vetting and analyses toward group papers. SGP utilizes a relational database implemented with the PostgreSQL database management system. A full database diagram and documentation are available at https://github.com/ufarrell/sgp_phase1, and a simplified diagram is shown in Figure 2. The design was inspired by several existing data models in the geological and natural history museum communities. Tables for analytical geochemistry are from the British Geological Survey (BGS) geochemistry data model (Watson et al., 2014), with minor modifications. Tables for geological, geographical, and sample details are based on established museum collection management databases (Specify 6 https://www.specifysoftware.org/ and Arctos https://arctosdb.org/) in addition to the Observations Data Model 2 (ODM2, Horsburgh et al., 2016; Hsu et al., 2017), an information model for Earth observations. The SGP database is centered on the sample table (Figure 2). Samples are generally characterized by an individual rock sample and all resulting analyzed powders. The three key sections of the database linked to samples are (1) analytical results and associated methods, (2) geographical context, and (3) geological context. Dictionary tables (standardized lists of terms, also known as "controlled vocabularies") are based on existing community vocabularies where possible (e.g., from EarthChem, ODM2, Macrostrat, U.S. Geological Survey (USGS), and BGS). However, in many cases, these vocabularies required additions, such as the inclusion of specific sedimentary geochemical experimental methods (e.g., sequential iron extraction techniques; Poulton & Canfield, 2005). The BGS data model for analytical methods and geochemical results has been adopted almost without modification. We store analytical data in their submitted or published format and do not standardize the results to any given unit. An analytical result may be empty (NULL) only if it is below or above detection limits, and those values are also stored if they are available. If the results are published, they are linked directly to a reference work on an individual basis so that a fine-level distinction can be made between published and related unpublished data from the same samples. Any geostandards that are analyzed alongside samples in a study are also recorded. In the SGP, we make every effort not to include the same result twice. However, replicates may legitimately be added if the same sample has undergone analysis for the same analyte more than once (this could include anything from true replicate analyses using the same methods in the same laboratory to analyses of the same sample by different research groups using different methods). We do not currently assign new sample identifiers to sub-samples. A parent–child relationship may be added in Phase 2 when the focus will expand to include carbonate data. The SGP welcomes contributions from any interested researchers. Specifically, contributing data automatically makes a researcher part of the SGP Collaborative Team, rather than one needing to "join" SGP to contribute data. In the first consortium-building stage, potential collaborators were targeted if their work was particularly relevant to the Phase 1 goals, and additional researchers were recruited via SGP representation at multiple conferences. SGP collaborators are involved in providing details about their samples and providing published data tables and unpublished data from their own archives. In addition, some data have been collected from relevant published studies where the authors are not directly involved. In such cases, contextual information was coded by SGP team members using information provided in the paper. SGP collaborators are asked to fill in a template with contextual information as completely as possible, but with an emphasis on key fields such as modern latitude and longitude, stratigraphic unit name, depositional environment, and lithology. A particularly important field is interpreted age, which is a numerical estimate for the age of each sample in millions of years (Ma). Whenever possible, the original authors, who are most familiar with the samples and stratigraphic sections, are asked to provide the interpreted age. They can use whatever method with which they feel most comfortable; for example, ages may be estimated based on assumed sedimentation rates and/or linear interpolation, or groups of samples can be assigned one age based on proximity to any available time markers. A brief justification is required for each age provided, which may be used in the future to refine ages further. Maximum and minimum age estimates can also be stored, and indeed, are critical for the type of re-weighted bootstrap analyses employed by many SGP working groups (Mehra et al., 2021). A subset of samples from two USGS databases has been integrated into the SGP database. The first of the databases used is the National Geochemical Database: Rock (USGS NGDB, U.S. Geological Survey, 2008), comprising data from USGS projects from the 1960s to1990s, largely from North America. The second is the Global Geochemical Database for Critical Metals in Black Shales project (USGS CMIBS, Granitto et al., 2017), which includes predominantly Phanerozoic shale data from all continents. Data from both USGS databases lack much of the contextual information available for samples directly coded by the SGP team members (most specifically basin type, metamorphic/maturity grade, depositional environment, and detailed age justification) and there are a higher proportion of analytes with less detailed geochemical methodology. Nevertheless, they represent large numbers of samples (74% of samples in Phase 1 are from USGS sources) with age, lithology, and geographic information that can be utilized for many types of analysis. In the case of USGS NGDB, only sedimentary samples were incorporated into SGP, and in the case of USGS CMIBS, we did not include samples with lithologies indicative of ore or studies where the authors were primarily concerned with mineral deposits or studying the effects of metamorphism on shales. An attempt was made to match USGS fields to SGP fields, with some data cleaning needed in order to extract important information such as up-to-date stratigraphic names. Samples can easily be traced back to the original USGS databases using their original identifiers. The USGS NGDB data were enhanced by adding interpreted ages. Samples were matched, using a combination of stratigraphy and location, to the continuous-time age model in Macrostrat (Peters et al., 2018). Specifically, the minimum and maximum age estimates from the Macrostrat model were entered, and the interpreted age was entered as the average of these values. Only samples with matched interpreted ages were included from USGS NGDB. The USGS CMIBS samples were associated with Macrostrat continuous-time age models where possible and given age information by SGP team members where not. However, a proportion (36%) remain without ages, and filling those in is a key goal for Phase 2. These three sources of data (direct entry by SGP team members (26% of samples), the CMIBS compilation (16% of samples), and the USGS NGDB (58% of samples)) provide a robust base platform for statistical analyses of aggregated sedimentary geochemical data through Earth history. Moving forward, we will continue direct entry from SGP team members, and work toward incorporating geochemical data compiled by additional geological surveys (for instance, incorporation of the OZCHEM whole-rock database from Geoscience Australia is currently in progress). Phase 1 of data collection ended in August 2019. A static version of the database was archived and made available to collaborators through the website (sgp-search.io) and via tailored queries. Time was allowed for vetting, and any errors discovered were corrected before the final freeze in February 2020. The Phase 1 data freeze includes 82,578 samples, with 2,701,236 analytical results, and was made public through our search website in December 2020. This paper should be cited in the future use of Phase 1 data downloads. More complete information on the Phase 1 data product can be found on the SGP wiki (https://github.com/ufarrell/sgp_phase1/wiki), including summaries by age, lithology, and geochemical methodology, as well as the specifics of how USGS databases were incorporated into the SGP structure. The SGP-contributed dataset includes 20,811 samples with 518,291 results. Approximately two thirds of the data (64%) come from 160 published sources (https://github.com/ufarrell/sgp_phase1/wiki/SGP-data-references). The remaining 36% are from unpublished sources, including new and legacy data. The samples come from 942 individual sites from 46 countries (Figure 3). Consistent with the Phase 1 goals, 84% of samples were from the Neoproterozoic–Paleozoic (Figure 4). Sixty-four percent of samples are fine-grained siliciclastic rocks (shale, mudstone, or siltstone), as are the majority of uncoded lithologies (Figure 5). The data from USGS NGDB that are incorporated into the SGP database include 48,234 samples with 1,769,696 results. Nearly all (99%) of the samples are from the United States. Nineteen percent are sandstone, 13% are shale, and 29% do not have a specific lithology (although lithological details may be available in verbatim fields; Figure 5). Contextual details, including depositional environment and low-grade metamorphic bin, are mostly not available for these samples, and methodological information is sparse. In general, the USGS NGDB samples skew younger than the SGP samples: 39% are from the Paleozoic, 25% from the Mesozoic, and 33% from the Cenozoic (~3% of samples are from the Proterozoic/Archean). The USGS database provides excellent coverage of the United States, but given the remit of the organization, with strong focus on economic deposits (petroleum-producing units, phosphatic units, and sedimentary mineral deposits), the sampling may not be representative of the entire country. This is distinct from the bias present in geochemical data produced by academic researchers, which are often focused on mass extinction intervals, Earth system perturbations, and other stratigraphic boundaries. The data incorporated from USGS CMIBS into the SGP database include 12,797 samples with 409,188 results. The samples are from 45 countries, with 40% from Canada, 27% from the United States, and 13% from Australia. The majority of samples are fine-grained siliciclastic sediments (69% shale, mudstone, siltstone, or argillite; Figure 5). Sixty percent of samples with interpreted ages are Paleozoic, 24% are Mesozoic, 2% are Cenozoic, and 15% are Proterozoic/Archean. As was the case for USGS NGDB, contextual details, including depositional environment and low-grade metamorphic bin, are often missing for these samples. However, more detailed geochemical methodological information is available. Each sample in CMIBS has a "best value" result per analyte, selected from multiple values that were originally available (Granitto et al., 2017). The choice of "best value" was made using a rubric which included consideration of the sample weight, the sample "decomposition" (e.g., full vs. partial acid digestion), the instruments used in the analysis, and the detection limits (Granitto et al., 2013). The SGP search website (sgp-search.io) utilizes an intuitive user interface to query the Phase 1 database via an API. The two main search types are "samples" and "analyses," with "nhhxrf" simply being a "samples" search that excludes any handheld XRF (X-ray fluorescence) data. This methodological distinction is made because while handheld XRF data can be accurate for some elements (e.g., Ca and Fe), it is highly inaccurate for many others (e.g., S, Ni) (Rowe et al., 2012). Handheld XRF data represent 1% of the total results and 4% of SGP-contributed data; although this is a small percentage now, we anticipate continued growth given the popularity and utility of handheld XRFs. A "samples" search will list an individual sample on each row, with geological context information and geochemical analytes taking up the columns. Data are converted to one standard unit, and oxides are converted to elements (e.g., Al2O3 to Al), and values are averaged if more than one analysis was made per sample. Note, this search may average values produced using different analytical methods, although the number of samples in the database with multiple analytical values for a specific analyte is relatively small. Further, any analyses below or above detection limit are removed, as these cannot be averaged. This has implications for queries involving very low abundance elements (e.g., Ag in sedimentary rocks), as only results above detection limits, and thus higher values, will be included. We anticipate that this search will produce the optimal data output for most end-users interested in Earth history: a file with age, geological context, and geochemical data for each sample. If users are looking to delve deeper into the data and understand the analyses and procedures that were executed to obtain each sample's geochemical data, then the "analyses" search is useful because it lists every analysis recorded in the database in a separate row. The "analyses" search also allows users to show data relating to the laboratory where the sample was analyzed, the person who made the measurement, geochemical methodology, etc. At the current time, aside from the ability to exclude handheld XRF data, the "samples" and "nhhxrf" search types will not report information about, or have the ability to filter by, geochemical methodology. Users who are interested in methodological details or who would like to export a data file beyond the size limit (10 Mb) should contact the SGP Leadership Team regarding a custom SQL query. Once the user has selected a search type, samples can be filtered based on both geological context and geochemical attributes. Note that for many samples some aspects of geological contextual information are incomplete. Thus, for example, a search filtering for samples deposited in a rift basin will only return samples positively described as such and not necessarily all samples in the database deposited in rift basins. Given that samples will have non-overlapping missing data, too many filters may result in a smaller-than-expected dataset. Search results will appear in a "preview" window that can be used to check the output. Each sample also has an information icon associated with it; clicking this icon will bring up a lightbox with detailed sample information. Finally, the user may request to show reference information for their search. For "analyses" searches (where every analysis is shown as an individual row), this will return the specific literature citation for that individual analytic result. For other search types, this will return, for every sample, a concatenated list of all references whose geochemical data contributed to that specific search. When the user is satisfied with their search, they can then download a.csv file of the data and export a map showing the location and age of samples in their search. Thus, an example API call would be {"type":"samples","filters":{"country":["Argentina","Brazil","Chile","Bolivia","Colombia","Venezuela"],"toc":[2,100]},"show":["toc","fe","height_meters","section_name","country","interpreted_age"]}. This API call is making a "samples" type search for samples that originate from Argentina, Brazil, Chile, Bolivia, Colombia, or Venezuela and have 2%–100% total organic carbon (TOC) content. In other words, searching for organic-rich samples from South America. In addition, the API call is asking for a results output table with columns that show TOC (wt%), Fe (wt%), section or core name, collection height in meters, each sample's country, and the age in millions of years. Full documentation and a tutorial video are available on the website. The overarching goal of SGP was to provide intellectual and geoinformatic resources for the Earth Science community to advance our understanding of environmental changes on Earth through time. A better understanding of Earth's history requires sufficient data density, but equally importantly it means training a new generation of researchers with the data science and statistical skills to make meaningful conclusions from large sedimentary geochemical datasets. Much of the focus in SGP Phase 1 was in initiating the consortium and increasing the data product to the point where it was useful for analyses by the community. We now aim to increasingly move toward developing a community-initiated set of best practices for data management, a culture of publishing metadata, and a shared intellectual framework for analyzing such datasets. Over the course of Phase 2, we plan to continue holding annual meetings at Goldschmidt while also beginning regular video calls to share progress and ideas for data analysis. We will also develop accessible "Proxy Primer" videos to help the geobiological community understand the strengths and weaknesses of different proxies. Echoing this final point, we reiterate that the SGP is a community-oriented research consortium, and we welcome suggestions on how to best move toward our shared goals. We thank Sufian Lattouf for developing the initial version of the SGP website, and Kai Lenz, Kassie Sharp, Aaron Cole, Clare Swan, Lyna Kim, and John Freshwaters for computational assistance. We thank Erin Saupe, Itay Halevy, Jordon Hemingway, Minming Cui, Maya Gomes, Matthew Granitto, Alf Lenz, Charles Henderson, Chengsheng Jin, Clint Scott, David Champion, Jinghai Yang, Joe Shaffer, Kathy Doyle, Lei Xiang, Liam Bhajan, Patrick Sack, Paul Hoffman, Paulo Linarde Dantas Mascena, Will Thompson-Butler, and Yu Liu for their contributions to SGP. We thank Patrick Sullivan and Laramie Duncan for discussions regarding the PGC and research consortium organization. We thank the donors of The American Chemical Society Petroleum Research Fund for partial support of SGP website development (61017-ND2). EAS is funded by National Science Foundation grant (NSF) EAR-1922966. BGS authors (JE, PW) publish with permission of the Executive Director of the British Geological Survey, UKRI. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. The authors declare no conflicts of interest.

This study provides a Zn isotope characterization (delta Zn-66) of the c. 1,640 Ma clastic-dominated McArthur River Zn-Pb-Ag deposit. Dolomitic, siltstone-hosted sulfide ores were sampled in two separate drill cores. One intersects the stratiform, vertically stacked orebodies at the centre of the deposit, and the other one intersects the south-eastern periphery of the deposit. The analyzed ores show relatively invariable delta Zn-66 values typical of the continental crust (0.35 parts per thousand median with 0.05 parts per thousand standard deviation). This signature is consistent with (near-) quantitative sulfide (sphalerite) precipitation during ore formation, negligible Zn isotope fractionation during fluid transport, and perhaps muted fractionation associated with near-quantitative Zn extraction from the source. Hence, our data show that a pronounced Zn isotope fractionation pattern characterized by lower delta Zn-66 values closer to the hydrothermal source, as reported from other Zn-Pb deposits, is not developed within the McArthur River deposit. However, across some orebodies, we note a subtle Zn isotope fractionation trend that correlates with the relative abundances of several temperature-sensitive base and trace metals (Zn, Pb, and Ag). This trend can be explained by subtle influence of Rayleigh-type Zn isotope fractionation during fluid evolution and Zn sulfide precipitation. Previous studies have suggested that Zn isotopes may be useful in the exploration for economic mineralization, as these studies observed both a significant Zn isotope halo and delta Zn-66 values markedly different from the continental crust. However, because both characteristics are not observable at McArthur River, the Zn isotope system may not have been useful in finding this deposit.

Summary The flood basalts and gold-bearing basal sediments of the 2775-2629 Ma Fortescue Group unconformably overlie the Mesoarchean West Pilbara Superterrane to the south of Karratha, Western Australia. Fresh exposures of the sedimentary units are lacking and their geochemical, mineralogical composition and sequence stratigraphy under cover are largely unknown. This research outlines the results of integrated downhole geochemistry and hyperspectral mineralogy of two new diamond drill holes, 4 km apart, which intersect the Fortescue group stratigraphy into the Mesoarchean Pilbara basement. This has been combined with trace element geochemistry, and high-resolution XRF mapping of representative samples provide micro-structural insights and in-situ geochemistry with textural context. The lithostratigraphy of the holes was defined using automated geochemical logging and tessellation methods, which provide objective classification of geologic units based on geochemistry and mineralogy. Individual basalt flows within the Kylena Formation can be correlated across holes based on chlorite content and geochemistry, and a chromium-rich geochemical marker horizon has been identified at the top of the siliciclastic Hardey Formation. The granitic basement rocks show evidence of significant fluid flow are interpreted to be a southern extension of the Maitland River Supersuite, consistent with regional geophysical anomalies that show a continuous gravity low. This dataset provides an unprecedented view into the Fortescue Group stratigraphy and its geochemistry. Correlation of this dataset with previous drilling provides insights into the regional tectonic and depositional history of the basin. The depth to basement increases from 650 m to >2200 m over ~12km N-S and the thickness of the clastic sedimentary basal Hardey Formation increases from ~150 m to 1050 m respectively. This indicates significant variation in the geometry of the basement during the deposition of the basal Hardey Formation, which was likely influenced by synsedimentary rifting. This has implications on the distribution of potential gold-bearing conglomerate facies unconformably overlying the basement, and in the Hardey Formation.

Gold grains, up to 40 μm in size and containing variable percentages of admixed platinum, have been identified in coals from the Leinster Coalfield, Castlecomer, SE Ireland, for the first time. Gold mineralisation occurs in sideritic nodules in coals and in association with pyrite and anomalous selenium content. Mineralisation here may have reflected very high heat flow in foreland basins north of the emerging Variscan orogenic front, responsible for gold occurrence in the South Wales Coalfield. At Castlecomer, gold (–platinum) is attributed to precipitation with replacive pyrite and selenium from groundwaters at redox interfaces, such as siderite nodules. Pyrite in the cores of the nodules indicates fluid ingress. The underlying Caledonian basement bedrock is mineralised by gold, and thus likely provided a source for gold. The combination of the gold occurrences in coal in Castlecomer and in South Wales, proximal to the Variscan orogenic front, suggests that these coals along the front could comprise an exploration target for low-temperature concentrations of precious metals.

© Northern Territory of Australia (NT Geological Survey) 2019. With the exception of logos and where otherwise noted, all material in this publication is provided under a Creative Commons Attribution 4.0 International licence (https://creativecommons.org/licenses/by/4.0/legalcode). 1 CSIRO Mineral Resources, CSIRO Mineral Resources, 26 Dick Perry Avenue, Kensington WA 6151, Australia 2 Email: heather.sheldon@csiro.au 3 Northern Territory Geological Survey, GPO Box 4550, Darwin NT 0801, Australia Introduction

Summary Recently discovered nugget gold (Au) in boulder conglomerate between the Mesoarchean West Pilbara Superterrane basement and the overlying volcano-sedimentary stratigraphy of the Neoarchean Fortescue Group in Western Australia have drawn comparisons with the famous Witwatersrand conglomerate Au deposits. Links have also been made between the Pilbara conglomerate gold and nugget Au occurrences in Quaternary colluvial deposits throughout the region. However, little is known about the origin of these as they are hitherto critically unstudied. Therefore, any genetic link is uncertain. Understanding the source and deposition of these nugget Au deposits is critical to aid further exploration in the region. Here we present a detailed study on the texture, composition and sedimentology of the nugget Au and their host rocks. The Archean conglomerate Au is comprised of a central nugget that is overgrown by a barren chloritic halo, which is further enveloped by a wider halo of Au-bearing chlorite. The central nuggets show no evidence for sedimentary transport, and have faceted surface textures consistent with chlorite imprinting. We argue these represent a modified placer deposit, with surface evidence for sedimentation removed by partial dissolution post-deposition. The Quaternary colluvial nugget Au is hypogene in origin, with minor flattening and limited silver (Ag) leaching on their surface indicative of limited colluvial-fluvial transport from source. Furthermore, preserved facets on their surface are similar to those in the Archean conglomerate deposits. We propose the source of the Quaternary colluvial nugget Au was a modified placer deposit within a proximal Archean colluvial-conglomerate that has been eroded in situ.

The direct measurement of gases trapped in sulphide minerals shows that samples from gold-bearing deposits in Britain and Ireland are anomalously rich in methane. Chalcopyrite samples in deposits of Palaeozoic age sited in Neoproterozoic basement (Caledonides greenschist), Munster Basin (Variscides greenschist) and the Carboniferous cover (diagenetic) were compared using mass spectrometry of cold-crushed gases. All host sequences contain sources of organic matter. The content of non-aqueous gas is greater in both sets of greenschist-hosted deposits than in the diagenetic-hosted deposits. However, chalcopyrite accompanying gold in the Neoproterozoic is methane-rich, but in the low-gold Munster Basin it is methane-poor. These gas data from opaque minerals complement fluid inclusion data from gangue minerals, and add support to models for the involvement of organic species in orogenic gold mineralisation.

Summary The future of mineral resources in Australia relies on the discovery of deposits under sedimentary cover. Traditional surface geochemistry techniques are of limited use in this context, and alternative exploration tools such as the detection of soil gases are gaining increasing interest. Previous studies have highlighted the potential of soil gases, such as sulphur gases and soil gas hydrocarbons, for locating buried mineralisation. Here, we performed laboratory weathering experiments of sulphides under sterile and non-sterile conditions to gain insights into the origin of these gases. The experiments revealed that hydrocarbon gases could not be detected, suggesting they commonly originate from microbial ecosystems in the cover and/or in the soil. In addition, equilibrium thermodynamic predictions indicate a larger range of sulphur gases than detected, which suggests the experimental system did not reach thermal equilibrium. Our results also reveal that CS2 is the most abundant gas produced, and could be of particular interest as a pathfinder for mineral exploration through cover.