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USGS2023

Stratigraphic notes—Volume 1, 2022

This is the first volume in the U.S. Geological Survey (USGS) series of reports on stratigraphy entitled “Stratigraphic Notes,” which consists of short papers that highlight stratigraphic studies, changes in stratigraphic nomenclature, and explanations of stratigraphic names and concepts used on published geologic maps. “Stratigraphic Notes” is a long-term (multiyear), multivolume publication containing articles that address updates or revisions to stratigraphic nomenclature (and whose content ultimately will be incorporated by National Geologic Map Database personnel into Geolex, https://ngmdb.usgs.gov/Geolex/ ). We welcome papers for the “Stratigraphic Notes” series from geoscientists of the USGS, of State Geological Surveys, and from academicians. Papers can be submitted for publication in “Stratigraphic Notes” by contacting the USGS Geologic Names Committee ( gnc@usgs.gov ). As new “Stratigraphic Notes” volumes are published, links to the volumes will be posted at https://doi.org/10.3133/pp1879 . This first volume ("Stratigraphic notes—Volume 1, 2022") includes articles that provide guidance for those who wish to submit papers to “Stratigraphic Notes,” as well as information on how to make your manuscripts compliant for geologic names reviews and how to organize your paper’s content to facilitate inclusion of new or revised names in Geolex. This volume also includes some specific guidance on conducting geologic names reviews of geologic and hydrogeologic reports.

Professional Paper↗
USGS2025

The 3D Elevation Program—Supporting Rhode Island’s economy

Introduction High-resolution elevation data are critical to applications of landscape modeling and planning, both of which have a significant effect on Rhode Island’s economy. In these and other enterprises, program managers, while aiming to strike a balance between accuracy and cost, strive to obtain the best available elevation data to help them address a range of issues. Programs focused on climate change, environmental management, transportation design and asset management, aviation navigation and safety, riverine ecosystem management, wildlife habitat characterization and management, shellfish aquaculture, and the management and mapping of forests, parks and recreation areas, soils, wetlands, and impervious surfaces are also among the critical applications that meet the State’s management needs and depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features. The 3D Elevation Program (3DEP) is managed by the U.S. Geological Survey (USGS) in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at quality level 2 or better to meet the many needs of the Nation and Rhode Island. The status of available and in-progress 3DEP baseline lidar data in Rhode Island is shown in figure 1. 3DEP baseline lidar data include quality level 2 or better, 1-meter or better digital elevation models, and lidar point clouds, and must meet the Lidar Base Specification version 1.2 ( https://www.usgs.gov/3dep/lidarspec ) or newer requirements. The National Enhanced Elevation Assessment identified user requirements and conservatively estimated that availability of lidar data would result in at least $178,560 in new benefits annually to the State. The top 10 Rhode Island business uses for 3D elevation data, which are based on the estimated annual conservative benefits of 3DEP, are shown in table 2.

Rhode Island↗
USGS2025

Land cover change within wetland complexes at Dixie Meadows, Churchill County, Nevada: 2015 – 2023

Dixie Meadows, Nevada, is a system of geothermal springs and seeps that feed a complex of marshes and wetland meadows that are located within lands managed by the Bureau of Land Management (BLM) and the Department of Defense (DOD). A previous U.S. Geological Survey report documented variability in satellite imagery-based land cover classifications for seven wetland complexes at near monthly time intervals between October 2015 and January 2022. This report presents additional data, extending analysis to November 2023. Land cover classifications between October 2015 and November 2023 demonstrated an association between vegetation cover characteristics and surface moisture, with Class 1 having dry, bare soil or sparse upland vegetation, Class 2 having moist, bare soil or sparse to small vegetation, Class 3 having dense green vegetation with potentially saturated soil conditions, Class 4 having a mix of shallow surface water, saturated soil, and dense green vegetation, and Class 5 having open surface water. Most of the wetland complexes occur close to spring outflows primarily within land managed by the DOD, though portions are also within BLM lands. The intervening and surrounding landscape outside of the wetland complexes assessed in this study are managed by the BLM. As a result, Class 1 land covers had the largest areal coverage for BLM managed lands. Classes 2 and 3 land covers were primarily mapped inside the wetland complexes and thus had the largest area coverage within DOD managed lands. Class 4 was almost exclusively mapped within the wetland complexes and thus was largely contained within DOD managed lands. Class 5 (open water) was exclusively mapped in and adjacent to a single wetland complex with catchment ponds on land managed by the BLM. The distribution of these land cover classes over the study period was seasonally and annually variable. Land cover areas of Classes 1 and 2 were larger during the spring months. Conversely, land cover areas of Classes 3 and 4 tended to be greatest during the summer or fall. These patterns might be influenced by differences in seasonal water sources and phenology.

Nevada↗
USGS2026

Birds, breakpoints, and baselines: How citizen science data can reveal ecological boundaries in Kenya’s Upper Tana watershed

Tropical watersheds are increasingly threatened by climate change, land-use conversion, and resource extraction, yet conventional biodiversity monitoring in these systems is often spatially and temporally limited. Citizen science offers a complementary approach, enabling biodiversity data collection over large areas that can supplement professional scientific surveys. We analyzed 10 years (2012–2022) of Upper Tana Watershed bird data from the Kenya Bird Map project, covering 114 pentads (9 × 9 km) within a 17,000 km 2 watershed to assess patterns of bird community composition and distribution across this watershed and to also evaluate the effects of environmental variables, seasonality, and sampling effort to help inform improvements in future citizen science projects. Citizen (or community) scientists recorded 575 species (>50% of Kenya’s total avifauna) in 74 families. Asymptotic species accumulation indicates that most probable species present in the watershed were detected. Threshold indicator taxa analysis revealed distinct ecological boundaries along elevation (∼1,500 m), precipitation (∼1,100 mm), and mean temperature (∼19°C) gradients, corresponding to a turnover from xeric savanna to mesic montane forest assemblages. Notably, bird communities showed little seasonal differentiation between wet and dry periods, consistent with dominance by resident year-round species. Data limitations including uneven survey distribution and frequency, absence of abundance metrics, and coarse representation of local environmental conditions that likely reduced our ability to detect fine-scale species–habitat relationships. Addressing these gaps through spatially balanced sampling at greater resolution, greater survey frequency in underrepresented areas, and improved capture of habitat metrics could strengthen the use of citizen-science bird data for watershed bioassessment. Our findings demonstrate that structured citizen-science initiatives can identify ecological boundaries and inform adaptive management of tropical socio-ecological systems under rapid environmental change.

Upper Tana watershed↗
USGS2026

The Sedimentary Geochemistry and Paleoenvironments Project Phase 2 data release: An open data resource for the study of Earth's environmental history

Geochemical data from sedimentary rocks are the primary source of information regarding Earth's surface evolution through time, including its air and water envelopes and interactions with life and deep Earth processes. The Sedimentary Geochemistry and Paleoenvironments Project (SGP) is a scientific consortium centered around open data and community-driven development of cyberinfrastructure tools and resources for sedimentary geochemistry and Earth history. Here we describe the SGP Phase 2 data release, which focused on incorporating Paleoproterozoic and Mesoproterozoic (2500–1000 million years ago) data and better accommodating carbonate data. This data release was built through the involvement of >200 researchers worldwide in academia, government, and industry, and provides the largest available public data resource for our user community in the academic fields of geochemistry, sedimentology, tectonics, paleontology, Earth history, and paleoclimate, as well as the petroleum and minerals industries. The dataset now encompasses 126,006 samples and 4,132,371 geochemical analyses. In addition to direct entry by SGP Team Members, we have ingested and incorporated datasets from the Geoscience Australia OZCHEM database, the Alberta Geological Survey, and the Deep-Time Marine Sedimentary Element Database (DM-SED) compilation. This paper details sampling in the Phase 2 dataset with respect to age, geography, lithology, and other geological characteristics, documents access via our search website and API, discusses possible issues and/or biases in the dataset that could impact analyses, describes plans for governance and stewardship of data from Indigenous lands, and serves as the citable reference paper for the data release.

Chemical Geology↗
USGS2024

On connecting hydro-social parameters to vegetation greenness differences in an evolving groundwater-dependent ecosystem

Understanding groundwater-dependent ecosystems (i.e., areas with a relatively shallow water table that plays a major role in supporting vegetation health) is key to sustaining water resources in the western United States. Groundwater-dependent ecosystems (GDEs) in Colorado have non-pristine temporal and spatial patterns, compared to agro-ecosystems, which make it difficult to quantify how these ecosystems are impacted by changes in water availability. The goal of this study is to examine how key hydrosocial parameters perturb GDE water use in time and in space. The temporal approach tests for the additive impacts of precipitation, surface water discharge, surface water mass balance as a surrogate for surface–groundwater exchange, and groundwater depth on the monthly Landsat normalized difference vegetation index (NDVI). The spatial approach tests for the additive impacts of river confluences, canal augmentation, development, perennial tributary confluences, and farmland modification on temporally integrated NDVI. Model results show a temporal trend (monthly, 1984–2019) is identifiable along segments of the Arkansas River at resolutions finer than 10 km. The temporal impacts of river discharge correlate with riparian water use sooner in time compared to precipitation, but this result is spatially variable and dependent on the covariates tested. Spatially, areal segments of the Arkansas River that have confluences with perennial streams have increased cumulative vegetation density. Quantifying temporal and spatial dependencies between the sources and effects of GDEs could aid in preventing the loss of a vulnerable ecosystem to increased water demand, changing climate, and evolving irrigation methodologies.

Colorado↗
USGS2024

Uncertainty in ground-motion-to-intensity conversions significantly affects earthquake early warning alert regions

We examine how the choice of ground‐motion‐to‐intensity conversion equations (GMICEs) in earthquake early warning (EEW) systems affects resulting alert regions. We find that existing GMICEs can underestimate observed shaking at short rupture distances or overestimate the extent of low‐intensity shaking. Updated GMICEs that remove these biases would improve the accuracy of alert regions for the ShakeAlert EEW system for the West Coast of the United States. ShakeAlert uses ground‐motion prediction equations (GMPEs), which calculate spatial distributions of peak ground acceleration (PGA) and peak ground velocity (PGV) from earthquake source estimates, combined with GMICEs to translate GMPE output into modified Mercalli intensity (MMI). We find significant epistemic uncertainty in alert distances; near‐source MMI estimates from different GMICEs can differ by over 1 MMI unit, and MMI extents used for public EEW alerts can differ by hundreds of kilometers for larger magnitude earthquakes ( M ∼6.5+). We use a catalog of “Did You Feel It?” shaking reports to evaluate how well GMICEs predict observed shaking. Our preferred GMICE is the one that computes MMI using PGV for high intensities and transitions to using PGA for nondamaging intensities. These results motivate updating GMICE relationships more generally, including in ShakeMap applications.

The Seismic Record↗
USGS2026

Modeling legacy nitrogen transport under instantaneous, steady-state, and transient groundwater flow conditions

In hydrologic settings where groundwater discharge contributes substantially to surface waters, legacy nitrogen in groundwater can confound surface water nitrogen loads estimated exclusively from current terrestrial sources. Additionally, legacy nitrogen in groundwater can contribute to lagged responses to nitrogen management efforts. Some methods of estimating groundwater contributions to surface water nitrogen loads account for legacy nitrogen, while others do not. The resulting differences are rarely quantified. We used a numerical modeling framework to compare three methods of estimating time-varying annual groundwater nitrogen loads to surface water receptors on eastern Long Island, New York. The instantaneous load method used steady-state contributing areas and includes no temporal groundwater lag. The second method used numerical simulations of nitrogen loads under steady-state flow, which captures groundwater transport lags but omits the annual variability in transient hydrologic stresses. The third method numerically simulated both transient groundwater flow and nitrogen transport to explicitly capture the effects of legacy nitrogen in groundwater. Depending on antecedent nitrogen and hydrologic conditions, historical nitrogen loads estimated from the numerical simulations were sometimes similar (<10% difference) and other times substantially different (±100%) from the instantaneous load estimates. Additionally, simulated future surface water nitrogen loads responded asymptotically over several decades following reductions in terrestrial nitrogen sources, further highlighting the effect of groundwater transport lag times. The comparison of the three methods, quantification of historical interannual variability, and prediction of lagged responses to nitrogen source reductions provide important context for decision makers using estimated groundwater nitrogen loads to help evaluate nitrogen management efficacy.

New York↗
USGS2025

Collaborative drought science planning in the Colorado River Basin

The U.S. Geological Survey (USGS) is using collaborative, interdisciplinary planning to develop data and tools needed to optimize the management of water resources and land use by resource management agencies during an ongoing, multidecadal drought in the Colorado River Basin. The USGS Actionable and Strategic Integrated Science and Technology team works to build relationships with resource management agencies and other stakeholders who can benefit from the use of USGS data and products. In 2023, the Actionable and Strategic Integrated Science and Technology team hosted a series of collaborative workshops to bring together representatives of resource management agencies and other stakeholders (any person or entity with interests in a resource or location) with USGS program managers, scientists, and multidisciplinary subject matter experts to codevelop concepts for interdisciplinary drought science and technology projects to address pressing needs related to drought in the Colorado River Basin. Workshop participants identified current and recent scientific data that could be shared through a centralized online data portal. Workshop participants also identified drought science and technology needs and developed project concepts to address those science needs. Participants categorized project concepts based on their potential to develop short-, mid-, and long-term drought science data and tools, provide for the spatial or temporal expansion of ongoing USGS science projects, and address high-priority science needs. Participants developed nine project concepts: (1) understanding shifting ecohydrologic baselines, (2) San Juan River Basin synthesis, (3) incorporating dynamic land cover into hydrologic models, (4) aridification compared to drought, (5) surface water-groundwater interactions, (6) cascading effects of drought on dust, (7) cascading effects of drought on water availability, (8) cascading effects of drought on socioeconomic factors, and (9) the value of water in the Colorado River Basin. This report provides an overview of the 2023 Codesign Workshop Series, synthesized outcomes from workshop materials and discussions, and science project concepts that emerged from the collaborative meetings that will continue to be refined into science project proposals through codevelopment processes. This report also highlights lessons learned and next steps needed to receive feedback and testing of the USGS Science Collaboration Portal, continue collaboration to develop detailed specifics and steps for short-term wins, develop interdisciplinary project proposals, and implement science planning and studies.

Arizona, California, Colorado, Nevada, New Mexico,↗
USGS2026

Microplastics undergo fragmentation during pressurized membrane filtration

Low-micrometer microplastics (<10 μm) have been detected in drinking water, driving growing interest in using pressure-driven membrane filtration to remove these particles and ensure drinking water safety. However, little attention is paid to the fate of microplastics concentrated in the filtration byproduct. In this study, using well-defined polystyrene (PS) and poly(methyl methacrylate) microspheres as model particles, we observed microplastic fragmentation during nanofiltration and the subsequent release of smaller fragments. After operating for 3 h at 20 bar, 67.9 ± 8.0% of the PS spheres in the concentrate, based on particles counted in selected fields of view, were transformed into fractured particles. The characteristic Raman band signals of microplastics were significantly weakened after fragmentation, leading to detection challenges. To address this, a data processing algorithm was developed to identify PS fragments as small as 1 μm. Preliminary statistical analysis reveals that within the tested pressure range, operation time has a stronger influence on fragmentation than pressure magnitude alone and that fragmentation is further governed by the intrinsic mechanical properties of the tested model polymers. This work provides direct evidence that pressure-driven membrane processes induce microplastic fragmentation and highlights the environmental risks associated with the discharge of fragmented microplastics into the concentrate.

Environmental Science & Technology Letters↗
USGS2025

A global database of soil microbial phospholipid fatty acids and enzyme activities

Soil microbes drive ecosystem function and play a critical role in how ecosystems respond to global change. Research surrounding soil microbial communities has rapidly increased in recent decades, and substantial data relating to phospholipid fatty acids (PLFAs) and potential enzyme activity have been collected and analysed. However, studies have mostly been restricted to local and regional scales, and their accuracy and usefulness are limited by the extent of accessible data. Here we aim to improve data availability by collating a global database of soil PLFA and potential enzyme activity measurements from 12,258 georeferenced samples located across all continents, 5.1% of which have not previously been published. The database contains data relating to 113 PLFAs and 26 enzyme activities, and includes metadata such as sampling date, sample depth, and soil pH, total carbon, and total nitrogen. This database will help researchers in conducting both global- and local-scale studies to better understand soil microbial biomass and function.

Scientific Data↗
USGS2024

A robust quantitative method to distinguish runoff-generated debris flows from floods

Debris flows and floods generated by rainfall runoff occur in rocky mountainous landscapes and burned steeplands. Flow type is commonly identified post-event through interpretation of depositional structures, but these may be poorly preserved or misinterpreted. Prior research indicates that discharge magnitude is commonly amplified in debris flows relative to floods due to volumetric bulking and increased frictional resistance. Here, we use this flow amplification to develop a metric ( Q* ) to separate debris flows from floods based on the ratio of observed peak discharge to the theoretical maximum water discharge from rainfall runoff. We compile 642 observations of floods and debris flows and demonstrate that Q* distinguishes flow type to ∼92% accuracy. Q* allows for accurate identification of debris flows through simple channel cross-section surveys rather than through qualitative interpretation of deposits, and therefore should increase the performance of models and engineered structures that require accurate flow-type observations.

Geophysical Research Letters↗
USGS2025

The Mammoth magnetic anomaly, Pinal County, Arizona

A high-resolution Earth Mapping Resources Initiative airborne geophysical survey was flown in the southwest North American porphyry copper province to improve bedrock geologic maps and to identify areas that have unrecognized critical mineral resource potential. During the review of the aeromagnetic data, a distinctly monopolar-shaped, negative magnetic anomaly was observed at a flight elevation of 200 m above the ground with a maximum amplitude of –9500 nT. We have named this the Mammoth magnetic anomaly (MMA) because it is centered 12 km northeast of the town of Mammoth, Arizona, USA. The total field anomaly (TFA) contour of –500 nT enclosing the MMA defines an elongate shape measuring 2.5 km long by 1 km wide that trends northwest–southeast. Given the striking nature of this negative, monopolar-shaped magnetic anomaly, we conducted a ground campaign in May 2025 to determine its authenticity and potential relationship to critical mineral endowment. The MMA was confirmed on the ground with a TFA approaching –46,000 nT. Total magnetic intensity (TMI) observations routinely fell below the 18,000 nT operating floor of an industry-standard cesium-vapor total field magnetometer, and extremely low TMI measurements were corroborated along coincident traverse lines using two high dynamic range, but lower sensitivity, smartphone vector magnetometers. The lowest TMI values recorded by both smartphone magnetometers were 1000 nT and confirmed with multiple adjacent and crossing lines. Field observations suggest that this magnetic feature is caused by strong remanent magnetization within fine-grained magnetite hosted within locally altered Pinal Schist.

Arizona↗
USGS2024

Land-use interactions, Oil-Field infrastructure, and natural processes control hydrocarbon and arsenic concentrations in groundwater, Poso Creek Oil Field, California, USA

Like many hydrocarbon production areas in the U.S., the Poso Creek Oil Field in California includes and is adjacent to other land uses (agricultural and other developed lands) that affect the hydrology and geochemistry of the aquifer overlying and adjacent to oil development. We hypothesize that the distributions of hydrocarbons and arsenic in groundwater in such areas will be controlled by complex interactions between mixed land uses, oil-field infrastructure, and natural processes. In 2020–2021, samples of groundwater and surface water were collected and analyzed for a large suite of inorganic and organic chemicals and isotope and gas tracers to test this hypothesis. Those data are supplemented with ancillary data on historical geochemistry, hydrology, geology, and oil-field infrastructure. Hydrocarbons in groundwater (e.g., methane through pentane gases and benzene) are associated with natural processes (e.g., fault offsets or transition in sediment depositional environment) and oil-field infrastructure (e.g., fluid-migration pathways associated with uncemented annulus in oil wells or unlined pits). Arsenic concentrations >10 μg per liter (μg/L; maximum concentration 12.9 μg/L) are associated with natural processes in old, high-pH groundwater, and more recent recharge of water from natural and/or engineered recharge processes. Along the southwest margin of the oil field, pumping for drinking-water and irrigation supplies in combination with engineered groundwater recharge produce a depression in groundwater elevations where groundwater with elevated sulfate concentrations from agricultural areas and groundwater with hydrocarbons from the oil field mix to produce a zone of sulfate reduction that removes hydrocarbons and arsenic from groundwater but produces elevated sulfide (S 2- ) concentrations (maximum concentration 29 mg per liter, mg/L). In this study, multiple approaches were required to resolve the overlapping effects of land uses, oil-field infrastructure, and natural processes on the distributions of hydrocarbons and arsenic in groundwater. The combined use of geographic, historical, physical, chemical, isotopic, and other information to constrain processes could be a useful approach for studies in other hydrocarbon-production areas. This is particularly important where land uses affect aquifer hydrology to an extent that causes mixing of groundwaters with different chemical compositions.

California↗
USGS2025

Three-dimensional seismic velocity models for the San Francisco Bay region, California from joint body-wave and surface-wave tomography validated by waveform simulation

A high-resolution seismic velocity model for both P and S waves is essential for the San Francisco Bay (SFB) region to accurately simulate earthquake ground motions and assess seismic hazards in this high-risk region. We present new three-dimensional P-wave and S-wave velocity (Vp and Vs) models of the SFB region developed using joint tomographic inversion with a rich set of earthquake and active-source body-wave data and ambient-noise surface-wave data. We designed a dynamic balance strategy to effectively balance the contributions of body-wave and surface-wave data during each iteration of the inversion. Owing to the complementary resolution of body-wave and surface-wave data, our new models are significantly improved compared to previous tomographic models. Major geologic features in the SFB region, including low-velocity basins, high-velocity Franciscan Complex, granite, and gabbro rocks, and across-fault velocity contrasts, are imaged in our Vp and Vs models. Compared to the geology-based U.S. Geological Survey velocity model, our new model has better defined structures for some important areas that are of great concern for seismic hazard assessment, such as the Sacramento-San Joaquin Delta, and the 2014 magnitude 6.0 South Napa earthquake area. We validated our model by simulating waveforms for a set of moderate-magnitude earthquakes. The good performance of our model in waveform simulation indicates its potential for improving ground motion simulation and seismic hazard assessment in the SFB region.

California↗
USGS2025

SURF: An automated method for building nonplanar 3D fault models from earthquake hypocenters

Accurately characterizing 3D fault geometry is vital for improving our understanding of earthquake behavior and informing the development of seismic hazard models. Despite their importance, subsurface fault structures tend to be poorly constrained because of limitations in observational data. Improvements to the seismic networks and earthquake detection algorithms have increased the precision and volume of earthquake catalogs, which help illuminate detailed subsurface fault structure and provide the most direct information available about fault geometries at depth. We present a Python package to automate generating 3D fault geometries directly from hypocentral seismicity patterns. This method begins with clustering events based on their spatial density, identifying coherent patterns. Nearby clusters are then merged based on the similarity of their orientations. We fit nonplanar surfaces using support vector regression to balance surface accuracy with minimal deviations from planarity. The fault models are output as quadrilateral meshes at user‐defined resolution. In the process of generating the 3D fault surfaces, we compute the spatial density of seismicity around the surface and the planarity as quantitative metrics of the model outputs. As a proof of concept, we apply this approach to the San Andreas–Calaveras fault junction region and the 2019 Ridgecrest earthquake sequence, both in California, which contain complex subparallel faults well defined at the Earth’s surface and abundant microseismicity. These case studies demonstrate the method’s ability to model complex fault structures, including long continuous fault surfaces, crossing faults, variably dipping segments, and subparallel faults. We test the method on both standard network catalogs and double‐difference relocated catalogs. We find that our seismicity‐based fault model results align with published 3D models that incorporate additional constraints and interpretations ( Plesch et al. , 2020 ; Aagaard and Hirakawa, 2021 ). This workflow provides a low‐user‐input solution for estimating fault geometries at depth from earthquake catalogs.

California↗
USGS2025

Characterizing sedimentary organic carbon in a hydrothermal spreading center, the Escanaba Trough

Sediments in critical marine mineral environments are of wide importance due to their preservation of both marine minerals and organic carbon (OC) stocks. However, OC storage and cycling is often overlooked in mineral system studies. This work characterizes sedimentary OC within the Escanaba Trough, a hydrothermal sulfide system off the coast of northern California. By utilizing ROV-based push coring, we collected sediments near and far from high temperature, low temperature, and inactive vents. We applied a multipronged organic geochemical approach, measuring bulk sediment, OC fractions of varying labilities, and biomarkers to tease apart the storage, source, and cycling of OC within this complex system. In contrast to past work indicating a primarily terrestrial source to deeper, Pleistocene sediments, our results suggest a primarily marine source in surface sediments at least 50 m away from active venting. Near active venting, we see evidence of locally produced chemosynthetic OC in addition to the background marine source. This chemosynthetic OC appears to be rapidly remineralized and supports more complex deep-sea food webs compared to hemipelagic sites. Still, the greatest contribution of labile OC was observed at inactive vent sites, which we suggest is due to hydrothermal fluid alteration of more labile OC at actively venting sites. Depending on fluid temperature, hydrothermally altered OC is either preserved in the sediments as petroleum or migrated with fluid flow. Considering inactive sites are those most likely to be targeted by potential mining, we suggest additional studies could verify if these results apply at other sedimented seafloor massive sulfide systems.

California↗
USGS2025

Dating a medieval tsunami with uranium-series techniques on Caribbean corals

Uranium-series dates from coral boulders constrain the timing of a medieval tsunami from the Puerto Rico Trench. Previously reported evidence for this tsunami includes hundreds of coral boulders that came to rest hundreds of meters inland on Anegada, British Virgin Islands. New U-series dates on these coral boulders provide limiting dates for the tsunami. The narrowest limits were by dating interior bands of a coral that retains the hemispherical form of a living coral colony, and which include adjustments for the number of annual density band couplets between the dated samples and the boulder exteriors. By those limits, the tsunami dates between 1381 and 1391 CE, and likely occurred during summer or fall. The tsunami is important as the only reported sign that the eastern Puerto Rico Trench has produced a great earthquake. The dating may aid in defining the earthquake source and in communicating tsunami hazards.

British Virgin Islands, Puerto Rico↗