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1. A Continuum from Iron Oxide Copper-Gold to Iron Oxide-Apatite Deposits: Evidence from Fe and O Stable Isotopes and Trace Element Chemistry of Magnetite

   https://doi.org/10.5382/econgeo.4752  

   Rodriguez-Mustafa, Maria A. ; Simon, Adam C. ; del Real, Irene ; Thompson, John F.H. ; Bilenker, Laura D. ; Barra, Fernando ; Bindeman, Ilya ; Cadwell, David ( November 2020 , Economic Geology)

   Iron oxide copper-gold (IOCG) and iron oxide-apatite (IOA) deposits are major sources of Fe, Cu, and Au. Magnetite is the modally dominant and commodity mineral in IOA deposits, whereas magnetite and hematite are predominant in IOCG deposits, with copper sulfides being the primary commodity minerals. It is generally accepted that IOCG deposits formed by hydrothermal processes, but there is a lack of consensus for the source of the ore fluid(s). There are multiple competing hypotheses for the formation of IOA deposits, with models that range from purely magmatic to purely hydrothermal. In the Chilean iron belt, the spatial and temporal association of IOCG and IOA deposits has led to the hypothesis that IOA and IOCG deposits are genetically connected, where S-Cu-Au–poor magnetite-dominated IOA deposits represent the stratigraphically deeper levels of S-Cu-Au–rich magnetite- and hematite-dominated IOCG deposits. Here we report minor element and Fe and O stable isotope abundances for magnetite and H stable isotope abundances for actinolite from the Candelaria IOCG deposit and Quince IOA prospect in the Chilean iron belt. Backscattered electron imaging reveals textures of igneous and magmatic-hydrothermal affinities and the exsolution of Mn-rich ilmenite from magnetite in Quince and deep levels of Candelaria (>500 m below the bottom of the open pit). Trace element concentrations in magnetite systematically increase with depth in both deposits and decrease from core to rim within magnetite grains in shallow samples from Candelaria. These results are consistent with a cooling trend for magnetite growth from deep to shallow levels in both systems. Iron isotope compositions of magnetite range from δ56Fe values of 0.11 ± 0.07 to 0.16 ± 0.05‰ for Quince and between 0.16 ± 0.03 and 0.42 ± 0.04‰ for Candelaria. Oxygen isotope compositions of magnetite range from δ18O values of 2.65 ± 0.07 to 3.33 ± 0.07‰ for Quince and between 1.16 ± 0.07 and 7.80 ± 0.07‰ for Candelaria. For cogenetic actinolite, δD values range from –41.7 ± 2.10 to –39.0 ± 2.10‰ for Quince and from –93.9 ± 2.10 to –54.0 ± 2.10‰ for Candelaria, and δ18O values range between 5.89 ± 0.23 and 6.02 ± 0.23‰ for Quince and between 7.50 ± 0.23 and 7.69 ± 0.23‰ for Candelaria. The paired Fe and O isotope compositions of magnetite and the H isotope signature of actinolite fingerprint a magmatic source reservoir for ore fluids at Candelaria and Quince. Temperature estimates from O isotope thermometry and Fe# of actinolite (Fe# = [molar Fe]/([molar Fe] + [molar Mg])) are consistent with high-temperature mineralization (600°–860°C). The reintegrated composition of primary Ti-rich magnetite is consistent with igneous magnetite and supports magmatic conditions for the formation of magnetite in the Quince prospect and the deep portion of the Candelaria deposit. The trace element variations and zonation in magnetite from shallower levels of Candelaria are consistent with magnetite growth from a cooling magmatic-hydrothermal fluid. The combined chemical and textural data are consistent with a combined igneous and magmatic-hydrothermal origin for Quince and Candelaria, where the deeper portion of Candelaria corresponds to a transitional phase between the shallower IOCG deposit and a deeper IOA system analogous to the Quince IOA prospect, providing evidence for a continuum between both deposit types.

    

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2. Phosphorus availability and leaching losses in annual and perennial cropping systems in an upper US Midwest landscape

   https://doi.org/10.5061/dryad.8sf7m0cpx  

   Hussain, Mir Zaman ; Hamilton, Stephen ; Robertson, G. Philip ; Basso, Bruno ( January 2021 , Dryad)

   Excessive phosphorus (P) applications to croplands can contribute to eutrophication of surface waters through surface runoff and subsurface (leaching) losses. We analyzed leaching losses of total dissolved P (TDP) from no-till corn, hybrid poplar (Populus nigra X P. maximowiczii), switchgrass (Panicum virgatum), miscanthus (Miscanthus giganteus), native grasses, and restored prairie, all planted in 2008 on former cropland in Michigan, USA. All crops except corn (13 kg P ha−1 year−1) were grown without P fertilization. Biomass was harvested at the end of each growing season except for poplar. Soil water at 1.2 m depth was sampled weekly to biweekly for TDP determination during March–November 2009–2016 using tension lysimeters. Soil test P (0–25 cm depth) was measured every autumn. Soil water TDP concentrations were usually below levels where eutrophication of surface waters is frequently observed (> 0.02 mg L−1) but often higher than in deep groundwater or nearby streams and lakes. Rates of P leaching, estimated from measured concentrations and modeled drainage, did not differ statistically among cropping systems across years; 7-year cropping system means ranged from 0.035 to 0.072 kg P ha−1 year−1 with large interannual variation. Leached P was positively related to STP, which decreased over the 7 years in all systems. These results indicate that both P-fertilized and unfertilized cropping systems may leach legacy P from past cropland management. Experimental details The Biofuel Cropping System Experiment (BCSE) is located at the W.K. Kellogg Biological Station (KBS) (42.3956° N, 85.3749° W; elevation 288 m asl) in southwestern Michigan, USA. This site is a part of the Great Lakes Bioenergy Research Center (www.glbrc.org) and is a Long-term Ecological Research site (www.lter.kbs.msu.edu). Soils are mesic Typic Hapludalfs developed on glacial outwash54 with high sand content (76% in the upper 150 cm) intermixed with silt-rich loess in the upper 50 cm55. The water table lies approximately 12–14 m below the surface. The climate is humid temperate with a mean annual air temperature of 9.1 °C and annual precipitation of 1005 mm, 511 mm of which falls between May and September (1981–2010)56,57. The BCSE was established as a randomized complete block design in 2008 on preexisting farmland. Prior to BCSE establishment, the field was used for grain crop and alfalfa (Medicago sativa L.) production for several decades. Between 2003 and 2007, the field received a total of ~ 300 kg P ha−1 as manure, and the southern half, which contains one of four replicate plots, received an additional 206 kg P ha−1 as inorganic fertilizer. The experimental design consists of five randomized blocks each containing one replicate plot (28 by 40 m) of 10 cropping systems (treatments) (Supplementary Fig. S1; also see Sanford et al.58). Block 5 is not included in the present study. Details on experimental design and site history are provided in Robertson and Hamilton57 and Gelfand et al.59. Leaching of P is analyzed in six of the cropping systems: (i) continuous no-till corn, (ii) switchgrass, (iii) miscanthus, (iv) a mixture of five species of native grasses, (v) a restored native prairie containing 18 plant species (Supplementary Table S1), and (vi) hybrid poplar. Agronomic management Phenological cameras and field observations indicated that the perennial herbaceous crops emerged each year between mid-April and mid-May. Corn was planted each year in early May. Herbaceous crops were harvested at the end of each growing season with the timing depending on weather: between October and November for corn and between November and December for herbaceous perennial crops. Corn stover was harvested shortly after corn grain, leaving approximately 10 cm height of stubble above the ground. The poplar was harvested only once, as the culmination of a 6-year rotation, in the winter of 2013–2014. Leaf emergence and senescence based on daily phenological images indicated the beginning and end of the poplar growing season, respectively, in each year. Application of inorganic fertilizers to the different crops followed a management approach typical for the region (Table 1). Corn was fertilized with 13 kg P ha−1 year−1 as starter fertilizer (N-P-K of 19-17-0) at the time of planting and an additional 33 kg P ha−1 year−1 was added as superphosphate in spring 2015. Corn also received N fertilizer around the time of planting and in mid-June at typical rates for the region (Table 1). No P fertilizer was applied to the perennial grassland or poplar systems (Table 1). All perennial grasses (except restored prairie) were provided 56 kg N ha−1 year−1 of N fertilizer in early summer between 2010 and 2016; an additional 77 kg N ha−1 was applied to miscanthus in 2009. Poplar was fertilized once with 157 kg N ha−1 in 2010 after the canopy had closed. Sampling of subsurface soil water and soil for P determination Subsurface soil water samples were collected beneath the root zone (1.2 m depth) using samplers installed at approximately 20 cm into the unconsolidated sand of 2Bt2 and 2E/Bt horizons (soils at the site are described in Crum and Collins54). Soil water was collected from two kinds of samplers: Prenart samplers constructed of Teflon and silica (http://www.prenart.dk/soil-water-samplers/) in replicate blocks 1 and 2 and Eijkelkamp ceramic samplers (http://www.eijkelkamp.com) in blocks 3 and 4 (Supplementary Fig. S1). The samplers were installed in 2008 at an angle using a hydraulic corer, with the sampling tubes buried underground within the plots and the sampler located about 9 m from the plot edge. There were no consistent differences in TDP concentrations between the two sampler types. Beginning in the 2009 growing season, subsurface soil water was sampled at weekly to biweekly intervals during non-frozen periods (April–November) by applying 50 kPa of vacuum to each sampler for 24 h, during which the extracted water was collected in glass bottles. Samples were filtered using different filter types (all 0.45 µm pore size) depending on the volume of leachate collected: 33-mm dia. cellulose acetate membrane filters when volumes were less than 50 mL; and 47-mm dia. Supor 450 polyethersulfone membrane filters for larger volumes. Total dissolved phosphorus (TDP) in water samples was analyzed by persulfate digestion of filtered samples to convert all phosphorus forms to soluble reactive phosphorus, followed by colorimetric analysis by long-pathlength spectrophotometry (UV-1800 Shimadzu, Japan) using the molybdate blue method60, for which the method detection limit was ~ 0.005 mg P L−1. Between 2009 and 2016, soil samples (0–25 cm depth) were collected each autumn from all plots for determination of soil test P (STP) by the Bray-1 method61, using as an extractant a dilute hydrochloric acid and ammonium fluoride solution, as is recommended for neutral to slightly acidic soils. The measured STP concentration in mg P kg−1 was converted to kg P ha−1 based on soil sampling depth and soil bulk density (mean, 1.5 g cm−3). Sampling of water samples from lakes, streams and wells for P determination In addition to chemistry of soil and subsurface soil water in the BCSE, waters from lakes, streams, and residential water supply wells were also sampled during 2009–2016 for TDP analysis using Supor 450 membrane filters and the same analytical method as for soil water. These water bodies are within 15 km of the study site, within a landscape mosaic of row crops, grasslands, deciduous forest, and wetlands, with some residential development (Supplementary Fig. S2, Supplementary Table S2). Details of land use and cover change in the vicinity of KBS are given in Hamilton et al.48, and patterns in nutrient concentrations in local surface waters are further discussed in Hamilton62. Leaching estimates, modeled drainage, and data analysis Leaching was estimated at daily time steps and summarized as total leaching on a crop-year basis, defined from the date of planting or leaf emergence in a given year to the day prior to planting or emergence in the following year. TDP concentrations (mg L−1) of subsurface soil water were linearly interpolated between sampling dates during non-freezing periods (April–November) and over non-sampling periods (December–March) based on the preceding November and subsequent April samples. Daily rates of TDP leaching (kg ha−1) were calculated by multiplying concentration (mg L−1) by drainage rates (m3 ha−1 day−1) modeled by the Systems Approach for Land Use Sustainability (SALUS) model, a crop growth model that is well calibrated for KBS soil and environmental conditions. SALUS simulates yield and environmental outcomes in response to weather, soil, management (planting dates, plant population, irrigation, N fertilizer application, and tillage), and genetics63. The SALUS water balance sub-model simulates surface runoff, saturated and unsaturated water flow, drainage, root water uptake, and evapotranspiration during growing and non-growing seasons63. The SALUS model has been used in studies of evapotranspiration48,51,64 and nutrient leaching20,65,66,67 from KBS soils, and its predictions of growing-season evapotranspiration are consistent with independent measurements based on growing-season soil water drawdown53 and evapotranspiration measured by eddy covariance68. Phosphorus leaching was assumed insignificant on days when SALUS predicted no drainage. Volume-weighted mean TDP concentrations in leachate for each crop-year and for the entire 7-year study period were calculated as the total dissolved P leaching flux (kg ha−1) divided by the total drainage (m3 ha−1). One-way ANOVA with time (crop-year) as the fixed factor was conducted to compare total annual drainage rates, P leaching rates, volume-weighted mean TDP concentrations, and maximum aboveground biomass among the cropping systems over all seven crop-years as well as with TDP concentrations from local lakes, streams, and groundwater wells. When a significant (α = 0.05) difference was detected among the groups, we used the Tukey honest significant difference (HSD) post-hoc test to make pairwise comparisons among the groups. In the case of maximum aboveground biomass, we used the Tukey–Kramer method to make pairwise comparisons among the groups because the absence of poplar data after the 2013 harvest resulted in unequal sample sizes. We also used the Tukey–Kramer method to compare the frequency distributions of TDP concentrations in all of the soil leachate samples with concentrations in lakes, streams, and groundwater wells, since each sample category had very different numbers of measurements. Individual spreadsheets in “data table_leaching_dissolved organic carbon and nitrogen.xls” 1.    annual precip_drainage 2.    biomass_corn, perennial grasses 3.    biomass_poplar 4.    annual N leaching _vol-wtd conc 5.    Summary_N leached 6.    annual DOC leachin_vol-wtd conc 7.    growing season length 8.    correlation_nh4 VS no3 9.    correlations_don VS no3_doc VS don Each spreadsheet is described below along with an explanation of variates. Note that ‘nan’ indicate data are missing or not available. First row indicates header; second row indicates units 1. Spreadsheet: annual precip_drainage Description: Precipitation measured from nearby Kellogg Biological Station (KBS) Long Term Ecological Research (LTER) Weather station, over 2009-2016 study period. Data shown in Figure 1; original data source for precipitation (https://lter.kbs.msu.edu/datatables/7). Drainage estimated from SALUS crop model. Note that drainage is percolation out of the root zone (0-125 cm). Annual precipitation and drainage values shown here are calculated for growing and non-growing crop periods. Variate    Description year    year of the observation crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” precip_G    precipitation during growing period (milliMeter) precip_NG    precipitation during non-growing period (milliMeter) drainage_G    drainage during growing period (milliMeter) drainage_NG    drainage during non-growing period (milliMeter)      2. Spreadsheet: biomass_corn, perennial grasses Description: Maximum aboveground biomass measurements from corn, switchgrass, miscanthus, native grass and restored prairie plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2015. Data shown in Figure 2.   Variate    Description year    year of the observation date    day of the observation (mm/dd/yyyy) crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” replicate    each crop has four replicated plots, R1, R2, R3 and R4 station    stations (S1, S2 and S3) of samplings within the plot. For more details, refer to link (https://data.sustainability.glbrc.org/protocols/156) species    plant species that are rooted within the quadrat during the time of maximum biomass harvest. See protocol for more information, refer to link (http://lter.kbs.msu.edu/datatables/36) For maize biomass, grain and whole biomass reported in the paper (weed biomass or surface litter are excluded). Surface litter biomass not included in any crops; weed biomass not included in switchgrass and miscanthus, but included in grass mixture and prairie. fraction    Fraction of biomass biomass_plot    biomass per plot on dry-weight basis (Grams_Per_SquareMeter) biomass_ha    biomass (megaGrams_Per_Hectare) by multiplying column biomass per plot with 0.01 3. Spreadsheet: biomass_poplar Description: Maximum aboveground biomass measurements from poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2015. Data shown in Figure 2. Note that poplar biomass was estimated from crop growth curves until the poplar was harvested in the winter of 2013-14. Variate    Description year    year of the observation method    methods of poplar biomass sampling date    day of the observation (mm/dd/yyyy) replicate    each crop has four replicated plots, R1, R2, R3 and R4 diameter_at_ground    poplar diameter (milliMeter) at the ground diameter_at_15cm    poplar diameter (milliMeter) at 15 cm height biomass_tree    biomass per plot (Grams_Per_Tree) biomass_ha    biomass (megaGrams_Per_Hectare) by multiplying biomass per tree with 0.01 4. Spreadsheet: annual N leaching_vol-wtd conc Description: Annual leaching rate (kiloGrams_N_Per_Hectare) and volume-weighted mean N concentrations (milliGrams_N_Per_Liter) of nitrate (no3) and dissolved organic nitrogen (don) in the leachate samples collected from corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2016. Data for nitrogen leached and volume-wtd mean N concentration shown in Figure 3a and Figure 3b, respectively. Note that ammonium (nh4) concentration were much lower and often undetectable (<0.07 milliGrams_N_Per_Liter). Also note that in 2009 and 2010 crop-years, data from some replicates are missing.    Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” crop-year    year of the observation replicate    each crop has four replicated plots, R1, R2, R3 and R4 no3 leached    annual leaching rates of nitrate (kiloGrams_N_Per_Hectare) don leached    annual leaching rates of don (kiloGrams_N_Per_Hectare) vol-wtd no3 conc.    Volume-weighted mean no3 concentration (milliGrams_N_Per_Liter) vol-wtd don conc.    Volume-weighted mean don concentration (milliGrams_N_Per_Liter) 5. Spreadsheet: summary_N leached Description: Summary of total amount and forms of N leached (kiloGrams_N_Per_Hectare) and the percent of applied N lost to leaching over the seven years for corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2016. Data for nitrogen amount leached shown in Figure 4a and percent of applied N lost shown in Figure 4b. Note the fraction of unleached N includes in harvest, accumulation in root biomass, soil organic matter or gaseous N emissions were not measured in the study. Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” no3 leached    annual leaching rates of nitrate (kiloGrams_N_Per_Hectare) don leached    annual leaching rates of don (kiloGrams_N_Per_Hectare) N unleached    N unleached (kiloGrams_N_Per_Hectare) in other sources are not studied % of N applied N lost to leaching    % of N applied N lost to leaching 6. Spreadsheet: annual DOC leachin_vol-wtd conc Description: Annual leaching rate (kiloGrams_Per_Hectare) and volume-weighted mean N concentrations (milliGrams_Per_Liter) of dissolved organic carbon (DOC) in the leachate samples collected from corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2016. Data for DOC leached and volume-wtd mean DOC concentration shown in Figure 5a and Figure 5b, respectively. Note that in 2009 and 2010 crop-years, water samples were not available for DOC measurements.     Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” crop-year    year of the observation replicate    each crop has four replicated plots, R1, R2, R3 and R4 doc leached    annual leaching rates of nitrate (kiloGrams_Per_Hectare) vol-wtd doc conc.    volume-weighted mean doc concentration (milliGrams_Per_Liter) 7. Spreadsheet: growing season length Description: Growing season length (days) of corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in the Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2015. Date shown in Figure S2. Note that growing season is from the date of planting or emergence to the date of harvest (or leaf senescence in case of poplar).   Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” year    year of the observation growing season length    growing season length (days) 8. Spreadsheet: correlation_nh4 VS no3 Description: Correlation of ammonium (nh4+) and nitrate (no3-) concentrations (milliGrams_N_Per_Liter) in the leachate samples from corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2013-2015. Data shown in Figure S3. Note that nh4+ concentration in the leachates was very low compared to no3- and don concentration and often undetectable in three crop-years (2013-2015) when measurements are available. Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” date    date of the observation (mm/dd/yyyy) replicate    each crop has four replicated plots, R1, R2, R3 and R4 nh4 conc    nh4 concentration (milliGrams_N_Per_Liter) no3 conc    no3 concentration (milliGrams_N_Per_Liter)   9. Spreadsheet: correlations_don VS no3_doc VS don Description: Correlations of don and nitrate concentrations (milliGrams_N_Per_Liter); and doc (milliGrams_Per_Liter) and don concentrations (milliGrams_N_Per_Liter) in the leachate samples of corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2013-2015. Data of correlation of don and nitrate concentrations shown in Figure S4 a and doc and don concentrations shown in Figure S4 b. Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” year    year of the observation don    don concentration (milliGrams_N_Per_Liter) no3     no3 concentration (milliGrams_N_Per_Liter) doc    doc concentration (milliGrams_Per_Liter) 

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3. Uranium Redox and Deposition Transitions Embedded in Deep‐Time Geochemical Models and Mineral Chemistry Networks

   https://doi.org/10.1029/2023GC011267  

   Moore, E. K. ; Li, J. ; Zhang, A. ; Hao, J. ; Morrison, S. M. ; Hummer, D. R. ; Yee, N. ( February 2024 , Geochemistry, Geophysics, Geosystems)

   Uranium (U) is an important global energy resource and a redox sensitive trace element that reflects changing environmental conditions and geochemical cycling. The redox evolution of U mineral chemistry can be interrogated to understand the formation and distribution of U deposits and the redox processes involved in U geochemistry throughout Earth history. In this study, geochemical modeling using thermodynamic data, and mineral chemistry network analysis are used to investigate U geochemistry and deposition through time. The number of U⁶⁺mineral localities surpasses the number of U⁴⁺mineral localities in the Paleoproterozoic. Moreover, the number of sedimentary U⁶⁺mineral localities increases earlier in the Phanerozoic than the number of U⁴⁺sedimentary mineral localities, likely due to the necessity of sufficient sedimentary organic matter to reduce U⁶⁺–U⁴⁺. Indeed, modeling calculations indicate that increased oxidative weathering due to surface oxygenation limited U⁴⁺uraninite (UO₂) formation from weathered granite and basalt. Louvain network community detection shows that U⁶⁺forms minerals with many more shared elements and redox states than U⁴⁺. The range of weighted Mineral Element Electronegativity Coefficient of Variation (wMEE_CV) values of U⁶⁺minerals increases through time, particularly during the Phanerozoic. Conversely, the range of wMEE_CVvalues of U⁴⁺minerals is consistent through time due to the relative abundance of uraninite, coffinite, and brannerite. The late oxidation and formation of U⁶⁺minerals compared to S⁶⁺minerals illustrates the importance of the development of land plants, organic matter deposition, and redox‐controlled U deposition from ground water in continental sediments during this time‐period.

    

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4. Triple Oxygen (δ18O, Δ17O), Hydrogen (δ2H), and Iron (δ56Fe) Stable Isotope Signatures Indicate a Silicate Magma Source and Magmatic-Hydrothermal Genesis for Magnetite Orebodies at El Laco, Chile

   https://doi.org/10.5382/econgeo.4760  

   Childress, T. ( November 2020 , Economic geology)

   null (Ed.)

   The Plio-Pleistocene El Laco iron oxide-apatite (IOA) orebodies in northern Chile are some of the most enigmatic mineral deposits on Earth, interpreted to have formed as lava flows or by hydrothermal replacement, two radically different processes. Field observations provide some support for both processes, but ultimately fail to explain all observations. Previously proposed genetic models based on observations and study of outcrop samples include (1) magnetite crystallization from an erupting immiscible Fe- and P-rich (Si-poor) melt and (2) metasomatic replacement of andesitic lava flows by a hypogene hydrothermal fluid. A more recent investigation of outcrop and drill core samples at El Laco generated data that were used to develop a new genetic model that invokes shallow emplacement and surface venting of a magnetite-bearing magmatic-hydrothermal fluid suspension. This fluid, with rheological properties similar to basaltic lava, would have been mobilized by decompression- induced collapse of the volcanic edifice. In this study, we report oxygen, including 17O, hydrogen, and iron stable isotope ratios in magnetite and bulk iron oxide (magnetite with minor secondary hematite and minor goethite) from five of seven orebodies around the El Laco volcano, excluding San Vicente Bajo and the minor Laquito deposits. Calculated values of δ18O, Δ17O, δD, and δ56Fe fingerprint the source of the ore-forming fluid(s): Δ17Osample = δ17Osample – δ18Osample * 0.5305. Magnetite and bulk iron oxide (magnetite variably altered to goethite and hematite) from Laco Sur, Cristales Grandes, and San Vicente Alto yield δ18O values that range from 4.3 to 4.5‰ (n = 5), 3.0 to 3.9‰ (n = 5), and –8.5 to –0.5‰ (n = 5), respectively. Magnetite samples from Rodados Negros are the least altered samples and were also analyzed for 17O as well as conventional 16O and 18O, yielding calculated δ18O values that range from 2.6 to 3.8‰ (n = 9) and Δ17O values that range from –0.13 to –0.07‰ (n = 5). Bulk iron oxide from Laco Norte yielded δ18O values that range from –10.2 to +4.5‰ (avg = 0.8‰, n = 18). The δ2H values of magnetite and bulk iron oxide from all five orebodies range from –192.8 to –79.9‰ (n = 28); hydrogen is present in fluid inclusions in magnetite and iron oxide, and in minor goethite. Values of δ56Fe for magnetite and bulk iron oxide from all five orebodies range from 0.04 to 0.70‰ (avg = 0.29‰, σ = 0.15‰, n = 26). The iron and oxygen isotope data are consistent with a silicate magma source for iron and oxygen in magnetite from all sampled El Laco orebodies. Oxygen (δ18O Δ +4.4 to –10.2‰) and hydrogen (δ 2H ≃ –79.9 to –192.8‰) stable isotope data for bulk iron oxide samples that contain minor goethite from Laco Norte and San Vicente Alto reveal that magnetite has been variably altered to meteoric values, consistent with goethite in equilibrium with local δ18O and δ2H meteoric values of ≃ –15.4 and –211‰, respectively. The H2O contents of iron oxide samples from Laco Norte and San Vicente Alto systematically increase with increasing abundance of goethite and decreasing values of δ18O and δ2H. The values of δ2H (≃ –88 to –140‰) and δ18O (3.0–4.5‰) for magnetite samples from Cristales Grandes, Laco Sur, and Rodados Negros are consistent with growth of magnetite from a degassing silicate melt and/or a boiling magmatic-hydrothermal fluid; the latter is also consistent with δ18O values for quartz, and salinities and homogenization temperatures for fluid inclusions trapped in apatite and clinopyroxene coeval with magnetite. The sum of the data unequivocally fingerprint a silicate magma as the source of the ore fluids responsible for mineralization at El Laco and are consistent with a model that explains mineralization as the synergistic result of common magmatic and magmatic-hydrothermal processes during the evolution of a caldera-related explosive volcanic system. 

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5. Application of an Improved Olivine-Melt Thermometer/Hygrometer to the Colima Cone Basanites and Minettes of Western Mexico: Implications for the Mantle Source of Unusually High-MgO Melts

   https://doi.org/10.1093/petrology/egad064  

   Pu, Xiaofei ; Lange, Rebecca A. ; Moore, Gordon M. ( August 2023 , Journal of Petrology)

   A collection of quaternary, high-MgO (≤13.4 wt%) basanite and minette cinder and lava cones, with an enhanced arc geochemical signature, are located along the northern margin of the N–S Colima rift in western Mexico. The Colima rift overlies the lithospheric suture between the Jalisco block and Guerrero terrane, as well as the tear between the Rivera and Cocos subducting oceanic plates. From the literature, volatile analyses of olivine-hosted melt inclusions in the Colima cone samples document notably high concentrations of dissolved H2O in the melt (≤ 7.0 wt%) as well as degassing-induced phenocryst growth over a range of depths ≤25 km. In this study, it is shown that the high-MgO character of the Colima suite reflects liquid compositions, consistent with evidence for their rapid transit to the surface, without stalling in a crustal magma chamber. The most Mg-rich olivine analyzed in each sample matches the equilibrium composition at the liquidus based on olivine-melt Mn–Mg and Fe2+–Mg exchange coefficients. Application of both a Mg- and Ni-based olivine-melt thermometer, calibrated on the same experimental data set, to the Colima cone suite provides the temperature and dissolved H2O content at the liquidus. Because the Ni thermometer is insensitive to dissolved H2O in the melt, it gives the actual temperature at the onset of olivine phenocryst growth. For the nine Colima samples that range from 13.4–9.2 wt% MgO, resulting temperatures range from 1221°C to 1056°C (± 6–11°C). In contrast, the Mg thermometer is sensitive to dissolved H2O in the melt, and its application (without a correction of H2O) gives the temperature of olivine crystallization under anhydrous conditions. When the Mg- and Ni-based temperatures are paired, the depression of the liquidus (∆T = TMg–TNi) due to dissolved H2O can be obtained. For the high-MgO (>9 wt%) Colima samples, ∆T values range from 188°C to 109°C. Corrections for the effect of pressure (i.e. evidence that phenocryst growth began at ~700 MPa), increase ∆T by ~21°C. An updated model calibration (on experiments from the literature) that relates ∆T with dissolved H2O in the melt shows that the best fit (R2 = 0.95) is linear, wt% H2O = 0.047*∆T, with a standard error of ±0.5 wt%. Although the experimental data set spans a wide range of melt composition (e.g. 47–58 wt% SiO2, 4.4–10.2 wt% MgO, 1.3–4.9 wt% Na2O, 0.1–5.0 wt% K2O, 0.3–5.3 wt% H2O), no dependence on anhydrous melt composition is resolved. Application of this updated model to the Colima suite gives H2O contents of 5.1–8.8 wt% H2O, consistent with those analyzed in olivine-hosted MIs from the literature. When the thermometry and hygrometry results for the Colima cone suite are compared to those for the adjacent calc–alkaline basalts from the Tancítaro Volcanic Field (TVF) in Michoacán, two distinct linear trends in a plot of wt% H2O vs. temperature are found, indicative of different mantle sources. It is proposed that the high-MgO (>11 wt%) Colima cone melts were derived from a phlogopite-bearing harzburgitic mantle at the base of the Jalisco block lithosphere, whereas both TVF and Colima melts with ≤10 wt% MgO were derived from the asthenosphere (i.e. arc mantle wedge). In both mantle sources, slab-derived fluids were an important source of H2O.

    

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