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USGS2024

Developments in African industrial minerals for renewable energy

Introduction Africa is emerging as a leading source for minerals used in the manufacture of batteries for electric vehicles and in other renewable energy applications. New graphite, lithium, and rare-earth mines have or could be opened in African countries from 2017 through 2026. Estimates of production capacities for graphite, lithium, and rare-earth mines for 2023 and beyond are based upon supply-side assumptions, such as announced plans for new capacity construction and bankable feasibility studies, as well as projected trends that could affect current producing facilities in 2023 and planned new facilities projected to come online by 2026. Forward-looking information, including estimates of future production capacities, graphite flake distributions, and timing of the start of operations, are subject to risk factors and uncertainties that could cause actual events or results to differ significantly from expected outcomes. Projects listed in this report are presented as an indication of industry plans and are not a U.S. Geological Survey (USGS) prediction of what will take place. Only projects with planned startup dates are included in this report; ther graphite, lithium, and rare-earth projects in Africa without startup dates were known to be in various stages of development but are not included in this fact sheet.

Fact Sheet↗
USGS2026

Numerical modeling of Late Pleistocene to Holocene earthquake-induced progressive rock slope damage in the paraglacial Serpentine valley, Prince William Sound, Alaska

Landslides in deglaciating fjords pose a potential tsunami threat to nearby communities; however, processes contributing to long-term progressive rock damage and landslide conditioning remain poorly constrained in paraglacial settings. Here, we analyse the role of earthquake-induced rock mass damage over late Pleistocene to Holocene time scales, as a conditioning factor for modern landslides, using distinct element numerical modelling to assess spatial and temporal patterns of fracture propagation influenced by varying glacier thickness. Conceptualised numerical models were parameterised by in situ rock mass, glacial and topographic conditions in Serpentine valley, located in Prince William Sound, Alaska, where several large landslides are actively developing along the western valley wall. Results show that although rigid glacier buttressing reduces co-seismic rock mass damage, it does not suppress it completely, and damage occurs both above and below the glacier surface elevation. We demonstrate that topography, and especially steep slopes with topographic convexity, as well as preexisting damage of joint networks and faults inherited from tectonic and exhumation induced stresses, exert primary control on the location of new co-seismic damage. Simulations representing a simplified deglaciation sequence over the past 25 ka, with a series of 10 evenly spaced earthquakes, generated rock mass damage patterns that qualitatively match in situ landslide structural and kinematic observations at one instability in Serpentine valley. Our conceptual study helps clarify the role of repeated seismicity over glacial timescales as a long-term conditioning process for paraglacial rock slope failure, highlighting spatial and temporal patterns of progressive damage accumulation, with outcomes relevant for modern landslide hazard assessment.

Alaska↗
USGS2026

CRESCENT earthquake dynamic rupture, earthquake cycle, and tsunami code verification platform

Physics-based simulations are critical for understanding natural hazards. The increasing complexity of numerical codes requires benchmark exercises to verify that different computational methods yield consistent results when solving the same governing equations. Here, we present an open-access web platform designed for the verification of earthquake dynamic rupture, seismic cycle, and tsunami simulations. The platform architecture utilizes a modular, serverless backend on Amazon Web Services (AWS) to provide scalable file processing and visualization. A lightweight static web application provides a secure interface for uploading and managing results, while the browser-based data visualization enables interactive analysis of time series and surface grid data. By using structured JavaScript Object Notation (JSON) text files to define benchmark structures, the system remains fully extensible, allowing the addition of new scenarios without modifying the underlying software logic. The platform hosts the "The Tsunami Problem Versions" (TTPV) 1 & 2, two benchmarks for 3D fully coupled earthquake dynamic rupture and tsunami generation, and provides a framework for earthquake cycle models. This community resource aims to build trust in numerical simulations and facilitate long-term collaborative code verification as modeling software continues to evolve.

Seismica↗
USGS2025

A spatiotemporal deep learning approach for predicting daily air-water temperature signal coupling and identification of key watershed physical parameters in a montane watershed

Seasonal shifts from runoff to groundwater dominance influence daily headwater stream temperatures, especially where local groundwater input is strong. This input buffers temperature during hot periods, supporting cold-water habitats. Recent studies use air–water temperature signal metrics to identify zones of strong stream–groundwater connectivity. While Previous studies used air–water signal ratios as proxies for groundwater influence but were limited to specific sites and periods, without dynamic forecasting. This study is the first to forecast daily A r as a spatiotemporal signal using a Graph Convolutional Network–Long Short-Term Memory (GCN-LSTM) model. The model was trained using hydroclimate data (air temperature, precipitation, shortwave radiation, streamflow) and watershed physical features (e.g., sand content, slope). Results showed high predictive skill, achieving R 2 (NSE, RMSE) of 0.86 (0.73, 0.0004) for one-day-ahead to 0.52 (0.50, 0.0009) for seven-days ahead forecasts. Prior studies often have not explicitly incorporated spatial hydrogeologic drivers, but this model explicitly incorporates them to assess their impact on A r forecasting and stream-groundwater connectivity. Feature analysis identified mean sand, elevation, slope, clay, and TWI as key predictors of A r . Stronger groundwater signals appeared in hillslopes, elevations, and tributaries, highlighting watershed influence on streamflow. However, limitations include reliance on historical air–water temperature patterns for training and limited representation of extreme climate conditions. Despite these limitations, unlike previous studies relying on measured in-situ stream and air temperature, this study forecasts A r directly from climate and physiographic features after training, avoiding in-situ data requirements. Findings aiding predictions of stream ecosystem resilience.

New York↗
USGS2026

Riverscape heterogeneity shapes population diversity for a migratory fish

Habitat patch dynamics can scale up to influence population demography and diversity with implications for resilience to environmental stochasticity. But how the spatial arrangement and size of habitat patches interact with other components of habitat heterogeneity to shape population diversity at larger spatial scales is not well understood. For riverine fishes, there is increasing evidence that tributary streams provide critical demographic support to main stem rivers. However, the extent to which main stem rivers rely on demographic contributions from tributaries, and the factors underlying this dependence, have not been assessed. Here, we used genetic stock identification to evaluate the effect of tributaries on population diversity of Yellowstone cutthroat trout ( Oncorhynchus virginalis bouvieri ) occupying the main stem Snake River, Wyoming, USA. We found that the main stem relied almost entirely on tributaries for demographic support, but main stem composition varied spatially among river sections. Distance between habitat patches, catchment area, and groundwater availability acted in concert to determine the contribution of specific tributaries to the main stem, but contributions were ultimately modulated by habitat connectivity. We also found evidence for multi-scale spatial structure in tributary contributions, providing insight into untested drivers of main stem river population diversity. Our results demonstrate how spatially discrete and distributed riverscape attributes influence population diversity at broader spatial scales, illustrating how ecosystem resilience emerges from the dynamic, two-way exchange of individuals and energy across habitat networks. Management plans for large rivers that address the ecological contributions of tributaries may be needed to achieve optimal outcomes. Similarly, conservation strategies that exclusively focus on headwater streams may fail to capture the broader habitat requirements necessary to maintain robust cold-water fish populations and associated recreational fisheries, particularly under global environmental change.

Wyoming↗
USGS2026

Teach me how to pycap: A high-capacity well decision support tool using analytical solutions in Python

Regulatory agencies in humid temperate environments rely on timely evaluations of streamflow depletion and drawdown to protect aquatic ecosystems and existing water users. Numerical models offer detailed insights, but their complexity and time demands often preclude their practical use in rapid decision-making. We present pycap-dss, an open-source Python package that implements a suite of analytical solutions for estimating streamflow depletion and drawdown. The tool supports superposition of multiple wells and time-varying pumping, enabling cumulative impact assessments in situations with multiple wells and streams. The software is modular and extensible, allowing users to interchange solutions or add new analytical methods. A YAML-based configuration supports batch processing of multiple wells, and an optional AnalysisProject class facilitates integration with regulatory workflows. Rigorous unit and regression testing ensures computational reliability, and continuous integration supports ongoing development. We demonstrate deterministic examples of drawdown where multiple solutions are readily compared and streamflow depletion with multiple wells in the Central Sands region of Wisconsin. We also show the value of Monte Carlo analyses of streamflow depletion in the same Central Sands example, leveraging computational efficiency to evaluate the uncertainty of individual and cumulative streamflow depletion calculations from over 200 high-capacity wells.

Wisconsin↗
USGS2024

A journey to the center of the USGS National Strong-motion Project processing and beyond

The United States Geological Survey (USGS) National Strong Motion Project (NSMP) has the primary U.S. government responsibility to acquire, process, and disseminate significant strong-motion earthquake ground motion records measured at surficial free-field stations, structures (buildings, dams, and bridges, and geotechnical arrays to the earthquake engineering community. As a result of the deployment of modern seismic instrumentation and growth of tools such as web-services, earthquake data from U.S. and international seismic networks are more accessible than ever. Our mission is to provide raw and processed strong-motion waveforms with PGA values greater than 0.1%g for M3.0 earthquakes and larger in California and M4.0 and larger within the conterminous US, Hawaii, Puerto Rico, and Alaska. Datasets of interest to the engineering and geophysics communities, such as event sequences in areas of induced seismicity and significant global events, are also processed and posted at the Center for Engineering Strong Motion Data (CESMD) at strongmotioncenter.org when available through collaboration with the international strong-motion data community. Here we outline (1) the NSMP’s current workflow to acquire, process, and distribute data at CESMD; (2) our new endeavours and collaborations focusing on comparison and integration of waveform processing software, development of techniques for metadata quality checks before and after earthquakes, and construction of a dynamic site characterization repository; and (3) our topics for possible collaboration topics across the global strong-motion community.

Conference Paper↗
USGS2026

Spatial variation in effectiveness and costs of sagebrush restoration treatments across the western United States

Natural resource managers strive to improve restoration efficiency across the vast network of public lands of the United States, seeking the best return on investment through innovation, geographic prioritization, and adaptive management. This challenge is exemplified by ecosystems dominated by sagebrush ( Artemisia spp.), which occur across the western United States and have been degraded by increasing wildfire frequency driven by invasive plant spread, among other factors. However, both costs and effectiveness of sagebrush restoration can vary spatially due to management practices in addition to biotic and abiotic factors, and characterizing this variation could inform broad-scale planning. We leveraged published models of sagebrush recovery and treatment costs to predict and evaluate cost-effectiveness of aerial and drill seeding Artemisia spp. across 429 718 km 2 that overlapped 12 US states. Compared to natural recovery, effectiveness for both methods was generally low, yet effectiveness was often greater, and costs were always greater, for drill than aerial seeding, resulting in slightly higher cost-effectiveness on average for drill seeding. Cost-effectiveness for both treatments increased near major roads and in areas with more repeated burns. Cost-effectiveness also increased with predisturbance cover of sagebrush but decreased with herbaceous cover. However, we also identified areas where aerial seeding was more cost-effective than drill seeding, particularly with greater slope. Our results provide spatially explicit estimates and potential mechanisms of cost-effectiveness for two common seeding methods for sagebrush, which can help prioritize limited resources, guide land use, and improve restoration efficiency and effectiveness across public rangelands of the western United States.

western United States↗
USGS2025

Seismic moment and local magnitude scales in Ridgecrest, CA from the SCEC/USGS Community Stress Drop Validation Study

We illustrate the systematic difference between moment magnitude and local magnitude caused by underlying earthquake source physics, using seismic moments submitted to the Statewide California Earthquake Center/United States Geological Survey Community Stress Drop Validation Study 2019 Ridgecrest data set. While the relationship between seismic moment and moment magnitude ( M or M w ) of log 10 ( M 0 ) ~ 1.5* M is uniformly valid for all earthquake sizes by definition (Hanks and Kanamori, 1979), the relationship between local magnitude M L and moment is itself magnitude dependent. For moderate events, ~3< M < ~6, M and M L are coincident; for earthquakes smaller than ~3, M L ~ 1.0 log 10 M 0 (Hanks and Boore, 1984). This is a physical consequence of the corner frequency fc becoming larger than the upper frequency of observation and implies that M L and M differ systematically by a factor of 1.5 for these small events. While this idea is not new, we propose a new, continuous relationship between local magnitude and moment, for magnitudes 2 to 6 which extrapolates to smaller and larger magnitudes, applicable to southern California specific to the Ridgecrest region. We make use of the plethora of seismic moments as submitted by many participants of the Community Stress Drop study, compared to the Southern California Seismic Network (SCSN) catalog magnitudes. Overall, the seismic moments in the Community Study recover moment magnitude well, so we use our new M L - M 0 to convert M L to M , refining the SCSN operational M Lr scale. This systematic difference of 50% in slope between local and moment magnitude at small magnitudes has implications for spectral stress drop estimates, earthquake ground motion modeling, as well as other magnitude scales and earthquake occurrence statistics.

California↗
USGS2025

A method to obtain remotely sensed grain size distributions from nonplanar granular deposits

Constraining the grain size distribution of granular deposits with complex surfaces is difficult with existing approaches. Field and laboratory techniques are time consuming and limited by the maximum grain size that laboratories can accommodate. In this study, we present a new method to identify the coarse fraction of the grain size distribution at a debris-flow fan deposit surveyed with terrestrial laser scanning (TLS) in Glenwood Canyon, Colorado, USA. This method is a novel grain segmentation algorithm developed for application to point cloud data of deposits with complex surfaces and angular grains ranging in size from centimeters to a meter. This approach combines an existing random forest machine learning method with a novel iterative clustering algorithm. We compared the grain size distribution from our algorithm with a Wolman pebble count conducted in the field, and found a root mean squared error of less than 2 cm from the 5th to 95th percentile of the grain size distribution of grains ranging from cobble to boulder sized (6.3–78 cm in our application). Finally, we compared our new algorithm with an existing open-source grain segregation algorithm, and our method outperformed the selected alternative when applied to the debris-flow deposit point cloud.

Colorado↗
USGS2026

Stress states on the eve of past earthquakes inform earthquake rupture through fault complexity along the San Andreas and San Jacinto faults

Estimating the evolving state of stress along active fault systems can provide insight into the conditions that generated past ground‐rupturing earthquakes and influenced their ability to propagate through areas of geometric complexity, such as fault branches and stepovers. We use quasi‐static forward numerical models that incorporate the 3D complex configuration of active faults in southern California to estimate shear tractions on the geometrically complex southern San Andreas and San Jacinto faults from 1000 to 1900 C.E. These tractions include interseismic accumulation of traction due to tectonic loading, viscoelastic relaxation of shear stress within the upper crust between earthquakes, and effects of other earthquakes on the fault network. We simulate ground‐rupturing earthquakes based on the along‐strike earthquake extents modeled by Scharer and Yule (2020) , assuming that stress drop is complete in each earthquake. We use Monte Carlo simulations to estimate uncertainty in evolving shear tractions due to uncertainties in earthquake timing and in upper‐crustal viscosity. Pre‐earthquake shear tractions typically do not exceed ∼2 MPa. Although ruptures with length <200 km have pre‐earthquake shear tractions that range from near zero to ∼1.75 MPa, these tractions are not less than ∼0.4 MPa for earthquakes with rupture length >200 km. Earthquakes with long (>200 km) ruptures occur only in the single‐stranded part of the system, whereas those with short (<125 km) rupture length and high pre‐earthquake shear traction occur near fault stepovers and branches. This suggests that high accumulated shear traction encourages longer rupture propagation, but may not be sufficient to overcome geometric complexities. This modeling approach informs our understanding of rupture propagation and provides estimates of fault shear tractions that are unavailable from direct measurements.

Callifornia↗
USGS2024

Pesticide occurrence in shallow groundwater in three regions of agricultural land use: Baldwin County, the Wiregrass region, and the Tennessee River valley region of Alabama, 2009–20

As part of a cooperative investigation between the U.S. Geological Survey and the Alabama Department of Agriculture and Industries, a network of 22 groundwater wells were sampled from 2014 through 2020 for about 230 pesticide and pesticide degradate compounds. Wells were located in three regions of intensive agricultural land use in Alabama: Baldwin County, the Wiregrass region, and the Tennessee River valley region. Metolachlor sulfonic acid, a degradate of the herbicide metolachlor, was the most frequently detected compound, occurring in about 70 percent of the samples. Three other compounds, metolachlor, atrazine, and 2-chloro-4-isopropylamino-6-amino-s-triazine, were also detected in more than half of the samples. Metolachlor and its degradates accounted for 33 of the 50 greatest compound concentrations study-wide, including the maximum pesticide concentration across all compounds (62,500 nanograms per liter). The frequency and magnitude of detections of many specific pesticide compounds varied among the three regions, but all detected pesticide concentrations were well below the U.S. Environmental Protection Agency maximum contaminant levels and applicable human health benchmarks. Sample results were combined with results of previous (2009–13) sampling to provide a continuous time-series of data for 2009–20. More than half of the 289 pesticide compounds analyzed during 2009–20 were not detected in any samples. Only four compounds were detected at great enough frequency throughout the 10 sampling years to evaluate patterns of change through time. Metolachlor and its degradate, metolachlor sulfonic acid, were frequently detected in all regions. Atrazine and its degradate, 2-chloro-4-isopropylamino-6-amino-s-triazine, were also detected in wells from all regions, but the variability and magnitude of concentrations were greatest in the Tennessee River valley region. No apparent temporal pattern in concentrations was found.

Alabama↗
USGS2025

ARCHI: A new R package for automated imputation of regionally correlated hydrologic records

Missing data in hydrological records can limit resource assessment, process understanding, and predictive modeling. Here, we present ARCHI (Automated Regional Correlation Analysis for Hydrologic Record Imputation), a new, open-source software package in R designed to aggregate, impute, cluster, and visualize regionally correlated hydrologic records. ARCHI imputes missing data in “target” records by linear regression using more complete “reference” records as predictors. Automated imputation is implemented using a novel, iterative algorithm that allows each site to be considered a target or reference for regression, growing the pool of complete references with each imputed record until viable gap-filling ceases. Users can limit artifacts from spurious correlations by specifying model-acceptance criteria and applying geospatial, correlation, and group-based filters to control reference selection. ARCHI provides additional functions for visualizing results, clustering records with similar correlation structures, evaluating holdout data, and interactive parameterization with an accessible and intuitive graphical user interface (GUI). This methods brief provides an overview of the ARCHI package, modeling guidelines, and benchmarking on two regional groundwater-level datasets from the Central Valley, CA and Long Island, NY. We evaluate ARCHI alongside widely used multivariate imputation software to highlight and contextualize its computational efficiency, imputation accuracy, and model transparency when applied to large, groundwater-level datasets.

California, New York↗
USGS2024

Slip rate for the Rose Canyon fault through San Diego, California, based on analysis of GPS data: Evidence for a potential Rose Canyon–San Miguel-Vallecitos fault connection?

The Rose Canyon fault is the southern extension of the larger Newport–Inglewood–Rose Canyon fault system, which represents a major structural boundary in the Inner Continental Borderland (ICB) offshore of southern California. Ten to fifteen percent of total plate boundary motion in southern California is thought to be accommodated by the faults of the ICB, but the exact distribution of slip is uncertain. With an onshore segment, the Rose Canyon fault offers an opportunity to measure the slip rate using traditional geodetic methods. In this study, we use Global Positioning System (GPS) surface velocities from a combined campaign and continuous GPS network to constrain elastic models of the Rose Canyon fault. We then compare the observed surface velocities with proposed conceptual models of regional fault connections that facilitate the transfer of slip into the Rose Canyon fault to assess how well the observations are explained by the models. The results of elastic half‐space models suggest that the Rose Canyon fault may be slipping toward the higher end of geologic estimates, with the preferred model indicating a slip rate of 2.4 ± 0.5 mm/yr. Although limited in terms of near‐fault benchmarks, we find an improved model fit using an asymmetrical elastic half‐space model and a higher slip rate, suggesting a potential rheological contrast across the Rose Canyon fault, similar to observations from the northern Newport–Inglewood fault segments. Observed GPS surface velocities, background seismicity, and gravity anomalies south of San Diego Bay point toward a more easterly trace for the Rose Canyon fault, suggesting a possible connection with the San Miguel–Vallecitos fault system. Such a connection could increase the potential rupture lengths of future earthquakes and have important consequences for regional seismic hazards.

California↗
USGS2025

Site response and wave propagation effects in the eastern United States

Fourier amplitude spectra from regional earthquakes in the eastern United States are used in a parametric inversion for source, path, and site effects. Five earthquakes are selected for analysis during the installation of the United States National Seismic Network (US), Earthscope’s USArray Transportable Array (TA), and other temporary arrays to maximize station coverage. A global search algorithm is used to solve for site response from 0.1 to 15 Hz, corner frequency, geometrical spreading ( r - γ ), and frequency dependent anelastic attenuation in the form Q(f) = Q o f α . Tradeoff between moment and geometric spreading is handled by fixing the moment. The tradeoff between corner frequency and Q(f) is solved by selecting the value of corner frequency that minimizes an objective function defined over all stations. Values of site response and attenuation parameters show a strong spatial correlation with the physiographic provinces of the eastern United States. Site response for the Atlantic Coastal Plain is consistent with previous work using spectral ratios relative to a reference site, defined by strong resonance peaks correlated with the thickness of sediments. Site response for the other physiographic provinces is markedly different from the coastal plain, with a lack of distinct resonance peaks and a broad moderate high at frequences from 0.1 to 0.5 Hz consistent with the hard-rock geology of the regions. Like site response, Q(f) has a strong correlation with physiographic province, showing lower values on the coastal plain and higher values inland. Geometric spreading exponent, γ, decreases with increasing hypocenter distance from just above 1 at a few tens of kilometers to 0.9 at 500 km. The limited range in geometric spreading values is attributed to starting the Fourier transform window at the S ‐wave arrival for all distances and averaging over multiple wave types.

eastern United States↗
USGS2025

Bedrock geologic map of the Bellows Falls 7.5- x 15-minute quadrangle, Windham and Windsor Counties, Vermont, and Sullivan and Cheshire Counties, New Hampshire

Introduction The bedrock geology of the Bellows Falls 7.5- x 15-minute quadrangle, Vermont and New Hampshire, consists of polydeformed Ordovician to Devonian metasedimentary, metavolcanic, and metaplutonic rocks of the Connecticut Valley trough, Bronson Hill anticlinorium (or Bronson Hill terrane), and the Central Maine terrane. Previous work in this area includes a 1:62,500-scale published map and text (1946), State geologic maps of New Hampshire (1997) and Vermont (2011), and various maps and reports presented largely as parts of field trip guidebooks. A provisional open-file map of the geology of the Vermont part of the Bellows Falls 7.5- x 15-minute quadrangle, completed in 1997, is incorporated and revised on this map based on additional fieldwork. This study recognizes three major structural levels from west to east and from lowest to highest: (1) autochthonous rocks of the Connecticut Valley trough; (2) allochthonous rocks of the New Hampshire sequence and Bronson Hill arc in the Monroe thrust sheet (or nappe), including the Skitchewaug nappe; and (3) allochthonous rocks of the Fall Mountain thrust sheet or nappe.

New Hampshire, Vermont↗
USGS2026

Resurvey of the Marble Canyon and Bridge Canyon dam sites in Grand Canyon National Park—Changes in sediment storage and evidence supporting the occurrence of bedrock incision through the mid-20th century

The Bureau of Reclamation developed an extensive plan for a network of dams, water tunnels, and hydropower plants in and around Grand Canyon, Arizona, in the 1940s through 1960s. The two largest of these planned dams were the Marble Canyon and Bridge Canyon Dams on the Colorado River. Though these dams were ultimately never built, Reclamation conducted extensive topographic, bathymetric, and subsurface exploration work at the sites proposed for these dams in the 1940s and 1950s. Resurveys of these dam sites were conducted between 1998 and 2021 to determine the changes in sediment storage at these dam sites caused by the upstream construction and operation of Glen Canyon Dam and by the recession of Lake Mead, the reservoir impounded by Hoover Dam. The resurveys of the Marble Canyon dam sites indicate that the post-1950s changes in sediment storage at these dam sites are broadly consistent with flux-based estimates of voluminous sand erosion from Marble Canyon since the 1963 closure of Glen Canyon Dam. These resurveys also suggest that the pre-dam longitudinal variation in sediment thickness over bedrock played a key role in determining the locations of the sand erosion induced by Glen Canyon Dam; more sand eroded from locations where more sand was present in the 1950s. The resurvey of the Bridge Canyon dam sites indicates that the Colorado River’s incision of the Lake Mead delta is regulated both by bed-sediment grain size and downstream hydraulic controls. Finally, analyses of bed-sediment thickness and sedimentological data at the dam sites, and observations of bed scour and gravel transport, suggest that sufficient bedrock was exposed to allow bedrock incision during commonly recurring pre-dam snowmelt floods that entrained small boulders into transport.

Arizona↗
USGS2024

Deformation by pressure solution and grain boundary sliding in a retrograde shear zone in southern New England, USA

Alleghanian phyllonites in a shear zone in southern New England were formed by the retrogression and hydration of a high-grade Acadian pelitic schist. The retrogression was locally incomplete, resulting in both heterogeneous mineralogy and mineral compositions, and in many arrested reaction textures. These features, documented by backscattered electron and element map imaging, and by 40 Ar/ 39 Ar dating, provide a record of the processes active as the schist was converted to a phyllonite. On the margins of the shear zone relic biotite and garnet grains survive but are partially replaced by chlorite. Relic high-grade muscovite flakes containing up to 35 % paragonite (pg) also persist but are entrained in swarms of pg-poor muscovite flakes producing folia with an anastomosing network of muscovite grains of variable composition. Single crystals of pg-rich muscovite are truncated by muscovite in successively younger cross-cutting folia that contain decreasing pg contents, falling to <5% pg in the youngest folia. In the core of the shear zone all high-grade minerals are destroyed, but recrystallization continues with earlier greenschist facies folia replaced by lower grade and pg-poorer muscovite in younger folia. Muscovite grains in truncated folia are commonly kinked and selective recrystallization of muscovite in kink bands to pg-poor-compositions demonstrates that strain energy helped drive recrystallization. The boundaries of these new pg-poor muscovite folia are sharp, and truncations indicate that grain boundary sliding (GBS) involved dissolution. GBS also enabled folding by flexural slip along muscovite grain boundaries. Fold amplitudes increased as chlorite dissolved from fold limbs precipitated in fold hinges producing crescent-shaped saddle-reef-like structures. Together these observations of truncation and replacement by dissolution and precipitation demonstrate that pressure solution and GBS facilitated both the formation of the phyllonitic shear zone and slip along it.

Connecticut↗