The Maoling ore field is dominated by altered-rock-type gold deposits, of which the Jinchanggou gold deposit (JGD) is a typical quartz vein–type example. The genesis of the JGD remains poorly understood. We conducted hydrothermal monazite U–Pb dating and in situ trace-element and S–Pb-isotope analysis of pyrite to constrain the metallogenic process of the JGD. Four metallogenic stages were identified: Stage Ⅰ is characterized by pure white quartz veins with subordinate fine-grained pyrite; Stage Ⅱ exhibits greater pyrite and pyrrhotite precipitation; Stage Ⅲ constitutes the dominant metallogenic period for Au precipitation, concurrent with significant lead–zinc mineralization; Stage Ⅳ is dominated by quartz and carbonate minerals with rare sulfides. Time-resolved elemental depth profiles lack any obvious Au peaks and all data points fall below the gold solid-solubility line on the Au/As diagram, indicating that gold occurs as lattice-bound Au⁺ in pyrite. A progressive increase in pyrite Co/Ni ratios is observed from Stage Ⅰ to Stage Ⅳ, whereas Py3 displays highly variable Co/Ni ratios (0.006–5.52), reflecting vigorous water–rock reaction between the ore-forming fluid and wall rock. The δ34S values of sulfides vary from +8.88‰ to +12.46‰, lying between the range of granitic sulfur and that of the Gaixian Formation (GXF), indicating that the sulfur was predominantly magmatic with contributions from the GXF. The monazite samples from quartz veins associated with sulfides yielded a lower intersection age of 164.8 ± 4.5 (MSWD = 1.5) and a concordant age of 166.7 ± 4.0 Ma (MSWD = 1.6), demonstrating that a Middle Jurassic ore-forming age. Controlled by the westward subduction of the Jurassic Paleo-Pacific plate (PPP), the ore-bearing magmatic–hydrothermal fluid that exsolved from intermediate–felsic magmas in the study area underwent continuous fluid–rock interaction with the wall rocks during upward migration along deep-seated faults. As the fluids cooled, the Au–S complexes became unstable and gold was incorporated into the pyrite lattice via isomorphous substitution, ultimately producing large-scale gold precipitation and enrichment.
Rapid and reliable identification of multivariate geochemical anomalies is critical for delineating prospective mineralized zones and reducing uncertainty in mineral exploration targeting. Extended isolation forest (EIF) is a powerful unsupervised ensemble learning algorithm that efficiently isolates anomalies from high-dimensional geochemical datasets using randomly oriented hyperplane partitions. Previous studies have demonstrated the effectiveness of EIF in multivariate geochemical anomaly detection and mineral potential modeling. However, its performance can be significantly affected by stochastic variability arising from random partitioning and random subsampling during isolation tree construction, which may result in unstable anomaly patterns and inconsistent exploration targets in complex geological environments. To mitigate this limitation, we developed a robust unsupervised framework for the identification of multivariate geochemical anomalies associated with gold mineralization in the Southwestern Yilgarn Craton, Australia. The proposed framework integrates robust factor analysis (RFA), a Jaccard-based stability index and EIF to enhance the reliability and reproducibility of anomaly detection. RFA was first applied to compositional soil geochemical data to identify the most significant pathfinder elements associated with gold mineralization, which were subsequently used as input variables for the EIF model. The model was then optimized using a Jaccard-based stability criterion to ensure consistent anomaly detection across repeated independent runs. Model performance was assessed using area under the receiver operating characteristic curve (AUC). The obtained AUC value of 0.82 indicates strong predictive capacity, confirming that the generated anomaly map effectively delineates mineralization-related geochemical patterns and provides a reliable proxy for mineral prospectivity mapping. Overall, the proposed framework offers a robust and reproducible unsupervised approach for multivariate geochemical anomaly detection with strong applicability in both greenfield and brownfield mineral exploration settings.
Water conservancy and hydropower projects enhance regional climate resilience and watershed water security yet inevitably trigger large-scale involuntary reservoir resettlement. As representative involuntarily displaced populations, reservoir resettlees' social identity directly impacts local social stability and regional sustainable socioeconomic development. Based on a ten-year longitudinal qualitative investigation including in-depth interviews and participant observation in Village Y of Wuxikou Reservoir, Jiangxi Province, this paper divides the entire resettlement process into three stages: relocation, stabilization and development. From the dual perspectives of host community identity and out-groups identity, this study explores the dynamic evolutionary rules of resettlees' social identity. The results indicate that resettlees sequentially develop alienated identity, superficial adaptive identity and segregated identity across different phases. On this basis, the core concept of differential identity is proposed, which features a dual structure of vertical temporal differentiation and horizontal spatial differentiation. This paper expands the applicable scope and explanatory power of the “differential mode of association” and social identity theory in involuntary resettlement contexts. Grounding on the differential identity framework, this paper puts forward targeted integrated governance solutions to break intergroup segregation, facilitate cross-group integration and build resilient resettlement communities consistent with Sustainable Development Goals (SDGs) 11 and 13.
The discrimination of ore deposit types is primarily based on geological, geochemical, and isotopic characteristics. Conventionally, these types are identified using specific element diagrams. However, traditional geochemical methods often fail to determine scheelite deposit types of the complex Xuefengshan Sb-Au-W metallogenic belt in China, where mineralization resulted from the superposition of multiphase geological events. Machine learning (ML) methods, have been increasingly applied to identify deposit genesis by establishing relationships between deposit characteristics and genetic types using extensive datasets. However, inaccurate data labels, the limitations of single models, and poor model interpretability lead to decreased accuracy. This study proposes a ML framework based on interpretable ensemble learning. We collects geochemical element data from typical orogenic and magmatic-hydrothermal scheelite deposits globally. Deep clustering is used to filter data and overcome the subjectivity of original data labels. An ensemble learning model is used to construct a classifier to improve the model's robustness and generalization ability. An interpretable model is introduced to analyze the contribution of individual feature elements, revealing the metallogenic genesis. This method demonstrates high accuracy on the test set. According to this method, the scheelite deposit type of the Xuefengshan metallogenic belt is primarily magmatic-hydrothermal in origin, with orogenic superposition. This helps resolve a long-standing controversy in the region and establishes a repeatable and interpretable new paradigm for ML-based discrimination of ore deposit genetic types.
Though volcanogenic massive sulfide (VMS) deposits are major global sources of indium (In), the physicochemical mechanisms and key factors controlling its significant enrichment remain poorly understood. To address the issue, this study investigates the Tiemurt VMS Pb-Zn-Cu deposit, utilizing detailed petrography, in-situ LA-ICP-MS analysis, and thermodynamic modeling to reveal the In enrichment mechanisms in VMS deposits. Petrographic observations identified two distinct generations of sphalerite corresponding to different mineralization stages. The early-stage sphalerite (Sp1) is euhedral-subhedral, associated with pyrite, and displays darker colors (red to brown), whereas the late-stage sphalerite (Sp2) is anhedral, intimately intergrown with chalcopyrite, and shows lighter colors (mainly yellow). The trace element results demonstrate that Sp1 has a significantly higher In content (average 317 ppm) than Sp2 (average 220 ppm). Additionally, In concentrations positively correlate with Fe contents. Because Fe is the primary chromophore that darkens sphalerite, this strong coupled enrichment mechanism allows macroscopic sphalerite color (red > brown > yellow) to serve as a reliable indicator for In concentration. Crystallization temperatures calculated using the GGIMFis thermometer range from 344 to 382 °C for Sp1 and 312 to 355 °C for Sp2, indicating a cooling trend during fluid evolution. Thermodynamic modeling data showed that in the early-stage hydrothermal fluids (≥360 °C), Zn2+ preferentially complexes with Cl−, leaving InCl2+ or In3+ as unstable species, and In efficiently precipitates into Sp1 under the environment of log fO2 = −32 to −26 and pH = 6–8. As the fluids cool at ~340 °C, weakened Zn2+ competition allows In3+ to form stable InCl3, and In precipitates into Sp2 under the conditions of log fO2 = −42 to −32 and pH = 5.5–11. We therefore conclude that the key factor controlling the difference in In content between Sp1 and Sp2 is the precipitation mechanism rather than migration capacity. This may be different from the In enrichment mechanism associated with magmatic hydrothermal systems, where In is mainly present as InCl3 complexes with strong migration capacity. These new findings enable us to understand how the physicochemical conditions of fluids control the enrichment of In in VMS deposits, and also highlight that the color of sphalerite can be used to target potential In resources in PbZn deposits.
The Qukulekedong Au–Sb deposit, located in the western East Kunlun Orogenic Belt, contains resources of 21.5 t Au and 73 kt Sb and has been interpreted as an intrusion-related Au–Sb system. However, the timing and exploration significance of deep, proximal skarn mineralization remain poorly constrained. Here, we present new petrographic, mineralogical, mineral geochemical, and UPb geochronological data for the intrusive rocks and newly identified deep skarn. Zircon UPb dating yielded crystallization ages of 211.5 ± 1.9 Ma for the diorite porphyry and 211.7 ± 1.1 Ma for the gabbro diorite, indicating broadly coeval Late Triassic magmatism. Garnet UPb dating of the deep skarn yielded ages of 208.4 ± 5.8 Ma and 208.2 ± 4.8 Ma, directly constraining a Late Triassic skarn mineralization event. The deep skarn is characterized by grossular-rich garnet, diopside, actinolite, vesuvianite, epidote, chlorite, pyrite, arsenopyrite, and pyrrhotite, and was subsequently overprinted by quartz–sulfide and quartz–stibnite–carbonate veins. Zircon and amphibole mineral chemistry indicate that the Late Triassic intrusions crystallized from relatively hot, hydrous magmas under near-FMQ to slightly reduced conditions. Trace-element variations in garnet record progressive fluid evolution from Grt-a, characterized by high HFSE, HREE, V, and Cr contents and high Th/U ratios, to Grt-b, characterized by lower REE and HFSE contents and a closer association with hydrous alteration minerals. These results indicate that the deep skarn represents a proximal, high-temperature component of the Qukulekedong intrusion-related Au–Sb system, thereby expanding exploration targets from shallow Au–Sb veins to deep contacts between intrusions and carbonate-bearing strata, fault-intersection zones, and skarn zones containing Grt-a-type garnet.
Reservoir resettlement is a complex, and long-term recovery process. It involves more than physical relocation, extend to livelihood reconstruction, improvement of living conditions, and psychological recovery. To design post-resettlement policies, it is crucial to understand how these areas interact. This study develops an integrated system dynamics and agent-based simulation (SD-ABS) framework to examine the multidimensional recovery trajectories of resettlers affected by the Yangtze-to-Huaihe Water Diversion Project in China. The framework captures the co-evolution of production recovery, living recovery, and psychological recovery, as well as the feedback mechanisms linking individual behaviors and system-level changes. The model is parameterized and validated using from official monitoring reports, statistical yearbooks, and household surveys. Results show production recovery strongly depends on employment opportunities, skills training, and policy timing. Growth type policies yield better long-term employment outcomes than decrease type approaches. Living recovery can be accelerated by increased investment, however the effectiveness of investment depends on its alignment with resettlers' actual needs. Psychological recovery lag behind other trends and is strongly shaped by kinship and rebuilding social network. These findings show that post-resettlement recovery is dynamic and shaped by nonlinear economic, living, and psychological factors. The proposed SD-ABS framework provides a novel way to analyze long-term recovery. The study offers practical policy insights for employment support, targeted investments, and community integration. The findings help improve resettlement management for large-scale water infrastructure projects.
The Umm Hibal area, located in the westernmost part of the South Eastern Desert of Egypt, comprises quartz syenites and peralkaline granites that host abundant accessory and ore minerals, including Fe-Ti oxides, zircon, apatite, rutile, and allanite. In this study, for the first time, lithological discrimination was achieved using Support Vector Machine and Random Forest algorithms. Among the tested models, the SVM classifier applied to the combined Sentinel-1 and Sentinel-2 datasets achieved the highest performance, with an overall classification accuracy of 98.13%, a Kappa coefficient of 0.972, and an F1-score of 0.972. These results reflect the effectiveness of integrated radar-optical data for discriminating lithological variability in mineralized peralkaline granitoid suites. Spectral analysis of PRISMA imagery identified characteristic absorption features associated with various alteration types, including phyllic, argillic, hydroxyl-bearing, ferrous-silicate, and ferrugination assemblages. Field and laboratory validation confirmed the spatial distribution and intensity of these alterations, indicating that hydrothermal overprinting had occurred in the primary magmatic rocks. Sentinel-1 SAR revealed structural patterns in NW-SE, NE-SW, and N-S orientations, and lineament density mapping further identified critical fluid pathways that control mineralization. Geochemically, the quartz syenites display remarkably homogeneous chemical compositions, characterized by relatively low silica contents (SiO2 = 64.3–67.2 wt%), Rb (48.4–69.1 ppm), moderate K2O/Na2O ratios (0.75–1.02), and high FeOt (3.45–5.81 wt%) and Al₂O3 (14.6 to 16.9 wt%), compared with peralkaline granites, which show variable silica (SiO2 = 68–78.8 wt%), FeOt (0.88–7.87 wt%), Rb (52.1–129 ppm), and Ba (187–1611 ppm). Both granitic types are enriched in rare metals, including Zr (up to 1159 ppm), Nb (183 ppm), Y (190 ppm), and REEs (695 ppm), like mineralized peralkaline A-type granites in the ANS. They exhibit characteristics of anorogenic within-plate A1-type granites that crystallized via fractional crystallization of OIB-like mafic magma. A fuzzy-logic mineral prospectivity model integrating lithological, structural, and different alteration zones successfully delineates high-priority rare-metal targets in the Umm Hibal area. The integrated approach establishes a two-stage metallogenic model in which primary HFSE-REE enrichment during prolonged fractional crystallization of OIB-like peralkaline melts was subsequently upgraded by late-stage potassic metasomatism, silicification, and structurally focused hydrothermal fluid circulation. This framework provides a directly transferable predictive model for rare-metal exploration in analogous peralkaline ring-complex systems throughout the ANS and comparable Phanerozoic intraplate alkaline provinces globally.
Several granite-hosted rare metal (Li–Nb–Ta–Rb–Be) deposits have been discovered in the Yifeng area of the Jiangnan orogenic belt (JOB), with total Li2O resource (measured + indicated + inferred) exceeding 20 Mt. The widespread occurrence of rare metal granites, aplite, and pegmatites makes the orogen a world-class rare metal province (>12.35 Mt. Li2O, 0.83 Mt. Rb2O, 0.08 Mt. Ta2O5 and 0.13 Mt. Nb2O5). Understanding the regional metallogeny is critical to evaluating the rare metal potential of the JOB. To constrain the regional metallogenic chronology and elucidate the geodynamic processes that controlled the rare metal enrichment, we conducted multi-mineral (zircon, apatite, cassiterite, and columbite-tantalite) UPb dating on rare metal granites, aplite and pegmatites from three representative deposits in the western, middle, and eastern parts of Ganfang district. New age results from the Dingxing, Dagang, and Baishuidong deposits yielded zircon UPb age of 148.4 ± 1.4 Ma for the granitic host rocks, columbite-tantalite UPb ages of 150.2–133.8 Ma, apatite UPb lower intercept ages of 139.6–136.4 Ma, and cassiterite UPb ages of 144.4–140.9 Ma. Integrated with previously published geochronological datasets from the entire JOB, three discrete episodes of regional rare metal mineralization are identified: (1) Late Jurassic mineralization (161–136 Ma) synchronous with Paleo-Pacific flat subduction beneath the Eurasian continent; (2) Early Cretaceous mineralization (134–125 Ma) triggered by slab rollback and regional lithospheric extension in post-subduction settings; (3) Late Cretaceous mineralization (108–100 Ma) associated with prolonged asthenospheric mantle upwelling and crustal remelting. We propose that coeval multi-phase magmatism and protracted magmatic–hydrothermal fluid evolution are the critical factors driving large-scale Li–Nb–Ta–Rb–Be enrichment and ore formation within the JOB. This study clarifies the chronological coupling between rare metal mineralization and Paleo-Pacific tectonic evolution, and highlights concealed Late Jurassic and Early–Late Cretaceous highly differentiated granitoids as priority exploration targets for giant rare metal deposits in the JOB.
Trace metal accumulation in aquatic systems has become a global concern due to its environmental persistence and potential impacts on water quality and human health. Small lakes within the Dongting Lake floodplain, characterized by limited water volume and weak hydrodynamic exchange, are particularly susceptible to pollutant accumulation. This study investigated 7 trace metals in the surface waters of 9 representative small lakes during a July 2023 sampling campaign to determine their concentration characteristics, possible sources, water quality status, and associated health risks. Although trace metal concentrations were generally low during the investigation period, Cu and Cd exhibited relatively high spatial variability, suggesting greater sensitivity to localized inputs. Water quality assessments showed that the measured concentrations complied with the Chinese Environmental Quality Standards for Surface Water and the World Health Organization (WHO) guideline values. Multivariate statistical analyses suggested that industrial discharge, agricultural runoff, traffic emissions, and atmospheric deposition may represent possible source-related influences. Integrated assessment using multiple water quality indices indicated low levels of trace metal pollution in the investigated lakes. Health risk assessment results showed that all hazard quotient (HQ) and hazard index (HI) values for both adults and children were within acceptable limits, with children exhibiting relatively higher risk levels, and ingestion was identified as the dominant exposure pathway. As was the primary contributor to cumulative non-carcinogenic risk, followed by Pb, whereas the contributions of other trace metals were comparatively limited. These findings reflect the spatial heterogeneity of trace metal pollution in the small lakes of the Dongting Lake floodplain. They also highlight the need for precautionary monitoring of As and Pb and the prevention of additional inputs to support the safe and sustainable use of regional water resources.
The Mimbamla iron ore prospect, situated in the Nyong Unit at the northwestern margin of the Congo Craton (CC), comprises magnetite-rich gneisses associated with garnet- and biotite–quartz gneisses. Petrography, mineral chemistry, whole-rock geochemistry, and UPb zircon–monazite geochronology was employed to assess the nature, origin, and timing of the mineralization. The magnetite gneisses lack the iron- and silica-rich banding typical of banded iron formations (BIFs) but instead display a granoblastic texture, with magnetite grains occurring as irregular stringers and lenses, sometimes arborescent, and commonly fracture-controlled and intergrown with quartz–plagioclase–biotite–amphibole–garnet–K-feldspar, reflecting metamorphic recrystallization and fluid-assisted overprinting. Accessory phases include ilmenite, apatite, and pyrite, while incipient hematitization of magnetite occurs along internal fractures. Retrograde assemblages, expressed by biotite–chlorite and plagioclase–sericite alteration, are locally developed along grain boundaries and deformation-related microfractures. The magnetite gneisses are characterized by variable Fe2O3 (16.09–41.20 wt%) and high Al2O3 (0.60–15.05 wt%) contents. Their REE signatures are marked by LREE enrichment, negative to positive Eu anomalies (Eu/EuCN = 0.29–4.41), and a strong positive correlation between Ce, Eu, and ΣREE, suggesting a possible chemical/hydrothermal Fe component subsequently diluted by detrital input. The magnetite compositions (high Ti ∼ 0.36 wt% and Al ∼ 0.81 wt%, and low Ni/Cr ratios ∼0.43) classify the deposit as hydrothermal skarn-type mineralization formed through high-temperature (>500 °C) metamorphic recrystallization and fluid-mediated overprinting of a pre-existing sedimentary protolith. Detrital zircon UPb data from the interbedded garnet-bearing gneisses yield Meso- to Neoarchean age populations and a maximum depositional age (MDA) of ∼2602 Ma, suggesting derivation from the Neo- to Mesoarchean K-rich granitoids (∼2.6–2.7 Ga), charnockites (∼2.8 Ga), and TTG suites (∼3.2–2.8 Ga) of the adjacent Archean Ntem Unit. A Neoarchean monazite upper intercept age of ∼2741 Ma, along with high and variable Th/U ratios (3.1–632.4), reflects monazite growth or recrystallization within a high-temperature metamorphic environment that may have preserved inherited components and thus provides a minimum constraint on the timing of deposition of the Mimbamla iron ore deposit. Younger zircon (∼2129 Ma) and monazite (∼2089 Ma) ages record amphibolite- to granulite-facies metamorphism during the Paleoproterozoic Eburnean–Transamazonian orogeny, which overprinted earlier mineralization.
Manganese carbonates can be formed via either diagenetic reduction of Mn oxides from hydrothermal and marine environments by organic matter, or direct growth on calcite or dolomite in anoxic environments. The Triassic Heqing manganese carbonate ores in the Heqing basin, Yunnan Province, South China provides an excellent case to show they form by redox between Mn oxides and methane during diagenesis in a low sulfate freshwater environment. The manganese ores are hosted by limestones and predominantly composed of micro-to fine-crystalline rhodochrosite and massive hausmannite. An oxic depositional environment is indicated by the bulk rocks showing negative Ce anomalies (Ce/Ce* = 0.36–1.59, average = 0.89) from which the hausmannite was deposited, and subsequently replaced or encrusted by rhodochrosite. The manganese ores exhibit no significant Eu anomaly (Eu/Eu* = 0.72–1.18, average = 1.01), and are plot on hydrogenous area of SiO2 versus Al2O3 diagram, reflecting that the manganese was supplied dominantly from chemical weathering. A low sulfate freshwater sedimentary and early diagenetic environment is indicated by low Y/Ho and La/La* ratios for the bulk rocks or Mn carbonates, the absence of pyrite and sulfate minerals. Under such an environment, hausmannite was reduced by biogenic methane and organic matter to generate rhodochrosite as shown by two mixing trends with endmember δ13C values lighter than −70‰ and − 25‰, respectively. We report a rare case showing that strongly 13C-depleted Mn carbonate ore was formed in a freshwater lacustrine environment and can serve as a methane sink.
