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USGS2026

Mid-Cretaceous porphyritic magmatism in the Beartooth Mountains of the northern Laramide foreland and its connection to Frontier Formation sediment dispersal in Bighorn basin, Montana-Wyoming (USA), and Cordilleran tectonism

Porphyritic intrusions in the southeast Beartooth Mountains and porphyritic cobbles from the Torchlight conglomerate of the Cenomanian Frontier Formation in Bighorn basin (Montana-Wyoming, USA) bear striking resemblance. We utilize geologic mapping, petrography, geochemistry, and geochronology to characterize rocks from both locations and test whether the Beartooth Mountains area was the provenance for Bighorn basin cobbles. Mapping on Line Creek Plateau in the Beartooth Mountains shows three units with porphyritic phenocrysts consisting dominantly of plagioclase, plagioclase + potassium feldspar, and plagioclase + quartz. Petrography shows embayed quartz, opacitic rims, and zoned plagioclase. Geochemistry characterizes the intrusions as trachydacite to trachyte and trace elements exhibit enrichment in light rare earth elements and slight depletion in heavy rare earth elements relative to primitive mantle. Zircon U-Pb dating shows substantial Archean inheritance and ca. 104−92 Ma dates; some samples display multiple mid-Cretaceous date populations. Bighorn basin porphyritic cobbles exhibit similar modal mineralogy, near-identical geochemistry, and Archean inheritance and mid-Cretaceous geochronology. We suggest the porphyritic cobbles were sourced from basement-hosted porphyritic intrusions now exposed in the Beartooth Mountains, given that geochemistry does not agree with coeval volcanic sources along the Frontier Formation depositional fairway (Idaho batholith) or sedimentary-hosted Beartooth Mountains porphyritic sills intruded into Cambrian shale. Stratigraphic evidence does not support kilometer-scale mid-Cretaceous Beartooth Mountains exhumation to expose basement-hosted porphyritic intrusions, and we therefore present a volcanic hypothesis to bring rocks to the surface. This mid-Cretaceous multimillion-year magmatism is unexplained by tectonic models for the north-central Laramide foreland, and thus we further explore the emplacement processes, spatiotemporal significance, and tectonic implications of these rocks.

Montana, Wyoming↗
USGS2025

Estimated average annualized losses from potential building damage and fatalities due to earthquake-generated tsunamis in the United States

Earthquake-generated tsunamis represent substantial economic threats to states and territories in the United States (U.S.), but we are unaware of any effort to quantify potential impacts at the national level. This gap is partially due to the lack of nationally consistent data on tsunamigenic sources and associated return periods. This study addresses this issue and provides estimates of average annualized losses (AAL) for potential residential fatalities and capital stock losses associated with building damage (i.e., structural, non-structural, contents, and inventory damage) in the U.S. by curating tsunami-hazard information based on deterministic scenarios and probabilistic approaches, calculating potential losses, and estimating return periods where necessary. This assessment was done for the U.S. West Coast, Alaska, Hawaii, U.S. Pacific Territories, and U.S. Atlantic Territories. We estimate that earthquake-generated tsunamis that could affect these states and territories collectively represent $1 billion in potential AAL with 79 % of losses due to residential fatalities and 21 % of losses due to capital stock losses from building damage. We identify AAL variations based on county and county equivalents, states and territories, geographic regions, return periods, and departure-delay assumptions for evacuating residents. Results include high AAL values for potential fatalities in Puerto Rico and the U.S. Pacific Northwest region, high AAL values for potential building-related damage in Hawaii and California, and high building- and population-loss ratios for county equivalents in Alaska and U.S. territories.

International Journal of Disaster Risk Reduction↗
USGS2026

Continental-scale prediction of hydrologic signatures and processes

Understanding how dominant hydrologic processes and their drivers vary across diverse continental-scale landscapes is critical for hydrologic modeling and water management applications. Our research addresses this question by synthesizing large-sample watershed datasets, Caravan and GAGES-II, and developing random forest models to identify patterns in hydrologic function. We assessed dominant processes by examining hydrologic signatures – summary indicators of watershed function derived from hydroclimatic time series and random forest models across 14 146 gauged United States watersheds. The results reveal clear continental-scale gradients in hydrologic processes, including baseflow, overland flow, storage, and water balance losses. Our map of dominant processes highlights, for example, the transition from baseflow to fast responses and back to baseflow along the elevation gradient from the Appalachian spine, through the Piedmont, to the Eastern Coastal Plain; a distinct outer ring around the Great Lakes region; and sharp contrasts between coastal and inland processes in the West. Variable importance analysis from random forest models show that processes in the western U.S. are primarily controlled by climate, whereas in the eastern U.S., soil, geology, and topography play larger roles, with distinct human influences apparent in urban areas. Our approach of estimating dominant processes and their drivers facilitates extending process knowledge from research watersheds to the continental scale, assessing current hydrological understanding, and evaluating hydrological model structures.

conterminous United States↗
USGS2025

Comparing magmatism and hydrothermal alteration using magnetic modelling and stable isotopes at the Clementine porphyry copper prospect, Montana, USA

Recent mapping of the underexplored Clementine prospect in southwestern Montana has revealed evidence of hydrothermal alteration and mineralized breccia vein gossan interpreted to represent the upper expression of a Cretaceous, sediment-hosted copper porphyry system. The prospect is at the nexus of several Cretaceous granites, including the pre-mineralization Butte Granite and Big Hole Canyon plutons and local pre- to post-mineralization granite intrusions. Here, 3D magnetic inversions and stable isotope data are used to evaluate the spatial and genetic relationship of mineralization and Cretaceous magmatism. Magnetic inversions reveal a zone of high magnetic susceptibility beneath the prospect that is related to an exposure of unaltered, likely post-mineralization granite. The granite appears to connect to the Big Hole Canyon pluton at depth, suggesting it is a late-stage differentiate of the cooling, pre-mineralization pluton that may have been one of several potential heat sources for the mineral system at Clementine. This is supported by carbon isotope values of graphite that indicate organic material in shale of the Cretaceous Kootenai Formation was subject to metamorphism. Preliminary light hydrogen isotope values of actinolite hydrothermal orbs suggest formation following magmatic outgassing during thermal advection from an underlying intrusion.

Montana↗
USGS2025

Noble and base metal distribution and processes affecting ore tenors in the disrupted lower stratigraphy of the Stillwater Complex, USA

Exploration continues for contact-style Ni-Cu sulfide and chromitite-associated PGE mineralization in ultramafic rocks of the Stillwater Complex. At the Iron and Chrome Mountain areas, massive sulfides occur along the complex’s footwall contact and anomalous concentrations of PGE+Au are associated with the three lowermost chromitite seams. Southeast of Chrome Mountain, magmatic layering is highly disrupted by the presence of faults, magmatic breccias, serpentinized discordant dunites, pyroxenite pegmatoids, and disaggregated chromitite seams. The bulk rock chemistry, sulfide chemistry, and noble metal mineralogy of samples from this area were examined to determine the deportment of PGE and processes that led to enrichments in PGE, Au, Cu, Co and Ni. Results show that a sulfide liquid was the principal collector of PGE. If sulfide liquid was initially deposited with chromite, it was disaggregated or redistributed by subsequent melt or fluid infiltration, which may have resulted in the offset of peak PGE(+Cu, Ni) from peak Cr 2 O 3 concentrations, and upgraded PGE tenors. Upon cooling, PGE exsolved from sulfides to form discrete bismuth tellurides, arsenides, arsenic sulfides, antimonides, and alloys, commonly along the margins of sulfide globules. Calculated metal tenors are highest in the disseminated sulfides southwest of Chrome Mountain, whereas massive and net-textured sulfides near the Iron Mountain-Camp zone represent monosulfide solid solution cumulates. At progressively shallower levels, higher metal tenors combined with lower S/Se ratios are consistent with increasing R-factors from 100 to 100,000. Serpentinization and talc-tremolite alteration resulted in S loss through partial replacement of sulfides by secondary silicate+carbonate+magnetite+sulfide assemblages, further upgrading Ni-Cu-PGE tenors. The present work shows that processes responsible for the disruption of magmatic layering and post-magmatic fluid alteration along the intrusion’s lower contact led to noble and base metal enrichments.

Montana↗
USGS2026

A roadmap for identifying and interpreting physical processes and national water model prediction bias associated with baseflow index regimes across the contiguous United States

Understanding how groundwater–surface water interactions shape streamflow variability is critical for diagnosing low flow behavior and prediction bias in continental scale hydrologic models. We present a process informed framework that links observed baseflow (BF) dynamics, watershed attributes, and National Water Model (NWM) performance across the contiguous United States. Using daily observed streamflow from 797 reference quality streamgages, we developed monthly baseflow index (BFI) signatures using a streamgage specific, calibrated digital filter. Hierarchical clustering of these signatures identified seven distinct BFI regimes capturing regional and seasonal variability. We evaluated NWM v3.0 retrospective streamflow performance within each regime using multiple hydrograph and flow duration curve-based metrics. Model skill varied systematically across regimes: mixed flow systems were simulated most accurately, while predominantly BF dominated and quickflow dominated regimes exhibited substantially poorer performance. Across nearly all regimes, the NWM underestimated observed BFI magnitude and frequently failed to reproduce seasonal BF patterns, indicating systematic biases in simulated low flow contributions. To relate these regimes to potential process controls, we trained a Random Forest classifier using static watershed attributes and applied Shapley Additive Explanations to identify features most strongly associated with each regime. Results highlight regionally varying influences, including the dominant role of snow fraction and seasonal runoff timing in snow dominated basins and the importance of evapotranspiration and aridity in quickflow dominated systems. Collectively, these findings demonstrate how hydrologic signatures combined with interpretable machine learning can diagnose regime specific model biases and generate process-based hypotheses about limitations in large scale hydrologic prediction systems.

contiguous United States↗
USGS2025

Updating and recalibrating the integrated Santa Rosa Plain Hydrologic Model to assess stream depletion and to simulate future climate and management scenarios in Santa Rosa, Sonoma County, California

The Santa Rosa Plain Hydrologic Model (SRPHM) was developed and published in 2014 through a collaboration between the U.S. Geological Survey (USGS) and Sonoma Water to analyze the hydrologic system in the Santa Rosa Plain watershed, help meet the increasing demand for fresh water, and prepare for future uncertainties in water resources. The original model simulated hydrological conditions and water use from water years 1975 to 2010. Recently (2023), the USGS, in cooperation with Sonoma Water and the California State Water Resources Control Board, updated the SRPHM model to extend its simulation period to the end of the 2018 calendar year, incorporate new estimates of rural and agricultural water use, and use efficient input format for climate variables. The updated model was recalibrated, and evaluation of the new model calibration is included in this report. This report presents the results of comparing the hydraulic heads, streamflow, and groundwater budget simulated by the updated model with those generated by the original model and observed data. The main difference in the simulated budget between the original and updated SRPHM is the estimates of agricultural pumping, rural domestic pumping, and return flow generated from rural water use that was not simulated in the original model. The revised agricultural pumping is simulated using the agricultural package, which constrains pumping to available groundwater. The use of the agricultural package leads to a more realistic estimation of agricultural water use, with revised agricultural pumping being one-third less than that in the original model. The revised rural pumping is about half of the pumping in the original model because of using detailed parcel data to estimate population density in rural areas instead of coarse census tracts. Overall, average total inflows for water years 2006–10 simulated by the updated model were about 2 percent less than the original model, and the average total updated outflows were nearly 5 percent less than the original model. The updated model was then used to generate stream depletion maps, simulate climate change scenarios during 2019–99, and simulate water rights allocation using the Model for Decision Support in Integrated River Basin Management (MODSIM). The results from simulating eight future climate scenarios indicated either an increase in groundwater storage or no significant change in the next 80 years, along with an increase in recharge, an increase in actual evapotranspiration in six out of eight climate projections, and an increase in surface runoff. The increases in the simulated future groundwater storage, recharge, evapotranspiration, and runoff in most climate projections are mainly driven by the projected increase in precipitation in most of the future climate scenarios. The updated model also was used to test a pilot case study demonstrating water-resource allocation among different users with different water rights using the integrated MODSIM-Groundwater and Surface-Water Flow Model (GSFLOW) platform. The updated SRPHM serves as a valuable tool for analyzing historical and future hydrologic conditions in the Santa Rosa Plain watershed and preparing for future uncertainties.

California↗
USGS2024

Stream nitrate dynamics driven primarily by discharge and watershed physical and soil characteristics at intensively monitored sites: Insights from deep learning

We developed a suite of models using deep learning to make hindcast predictions of the 7‐day average backward‐looking nitrate concentration at 46 predominantly agricultural sites across the midwestern and eastern United States. The models used daily observations of discharge and meteorological variables and watershed attributes describing anthropogenic modification to hydrology, nitrogen application, climate, groundwater, land use, watershed physiographic attributes, and soils. Across all sites, discharge and watershed soil and physiographic attributes showed a strong influence on model performance. Analysis of drivers across sites revealed considerable regional differences related to controlling processes such as groundwater contributions. We tested several ways to pool data across sites to develop accurate models and make the most effective use of available data. Single‐site models, in which models are trained and tested at a single location, showed generally strong predictive performance (median Kling‐Gupta Efficiency = 0.66), and accuracy at poorly performing sites could be improved by grouping sites with similar characteristics. Developing a single model for all sites reduced performance at several locations with distinct characteristics, suggesting that there is a threshold of dissimilarity beyond which more data does not improve the model. While many deep learning studies have shown that national or even global models can outperform local models, it is not clear that this is true for water quality constituents. This study demonstrates how data can be combined effectively, using deep learning to develop accurate and interpretable models of instream nitrate at sites where varying processes are responsible for changes in nitrate concentration.

Water Resources Research↗
USGS2026

Predictions of anthropogenic background PFAS concentrations in soil and relation to bedrock lithology and groundwater quality

Detectable concentrations of per- and polyfluoroalkyl substances (PFAS) have been observed in soils in remote areas and presumably originate from atmospheric deposition. These anthropogenic background concentrations may enable some PFAS to leach to groundwater at levels that exceed regulatory criteria for drinking water. However, anthropogenic background soil concentrations and their connection to groundwater are not well characterized. We developed a boosted regression tree model to predict perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) concentrations in shallow soils across northern New England. Low soil pH was the most important predictor of elevated anthropogenic PFOS and PFOA concentrations in background soils, rather than potential PFAS sources, land use, or population density. Total organic carbon (TOC) was also an important predictor for PFOS soil concentrations. Model predictions indicate that 73% of the shallow soils within Maine, Vermont, and New Hampshire exceed New Hampshire’s Soil Remediation Standard for PFOS (0.5 ng/g) and 41% exceed the PFOA standard (0.4 ng/g). Analysis of soil model results and groundwater data suggests that areas with high soil pH are associated with higher groundwater detection frequencies, illustrating how areas with less retention in soil are, conversely, also areas with potentially greater groundwater vulnerability. Further analysis indicates that groundwater may be more vulnerable in calcareous lithologies.

Maine, New Hampshire, Vermont↗
USGS2025

Tracing metal sources and groundwater flow paths in the Upper Animas River watershed using rare earth elements and stable isotopes

Groundwater flow paths and processes that govern metal mobility and transport are difficult to characterize in mountainous bedrock watersheds. Despite the difficulty in holistic characterization, conceptual understanding of subsurface hydrologic and geochemical processes is key to developing remediation plans for locations affected by acid mine drainage, such as the Upper Animas River watershed in southwestern Colorado, USA. Stable isotopes of water and rare earth elements were utilized to evaluate groundwater flow and metal sources within this complex catchment. Stable isotope samples collected from draining mine adits and springs display systematic spatial variation wherein sample sites at higher elevations have greater seasonal variability than sites at lower elevations. The Upper Cement Creek watershed, where multiple draining mines are present, displays the lowest seasonal variation in stable isotopic signatures, potentially indicating the presence of a large, well-mixed volume of groundwater storage or interbasin groundwater flow. Rare earth elements display statistically significant variation between different alteration styles in the catchment. Overprinting of regional propylitic alteration is evident based on enrichment of middle rare earth elements in acidic springs and mines that are not spatially associated with surficial exposures of acid generating alteration styles. Europium anomaly and middle rare earth enrichment signatures from two flooded mine tunnels on opposite sides of a watershed divide indicate connections to the same subsurface flooded mine workings.

Colorado↗
USGS2026

High-resolution transboundary vegetation community maps of the Sonoran and Mojave Desert ecoregion to support critical landscape conservation planning and habitat management needs

We produced a 30-m resolution binational land cover map of Bird Conservation Region 33 (BCR 33) for the U.S. North American Bird Conservation Initiative. The region covers large portions of the Sonoran and Mojave Deserts. The map can support the U.S. Fish and Wildlife Service (FWS) Migratory Bird Program’s recovery planning efforts and constitutes the first known binational land cover dataset spanning sections of the United States–Mexico border and using a consistent classification system for both countries. The mapped region includes 152 distinct land cover classes, covering a total area of 38,421,453 ha (148,345 mi 2 ), of which 13,148,345 ha (52,706 mi 2 ) are located in Mexico and 24,770,640 ha (95,639 mi 2 ) in the United States. We primarily used Landsat 8 (OLI) imagery, supplemented by limited ground surveys from two field campaigns, drone-based aerial data, and existing vegetation classification frameworks from both countries. The classification applied a data-fusion approach integrating 30-m Landsat 8 imagery, decadal phenology metrics from vegetation indices, and a random forest model trained mainly with datasets from a comprehensive national mapping project from the U.S. Geological Survey (USGS) GAP Analysis Project (GAP) and federal wildland fire agencies’ Landscape Fire and Resource Management Planning Tools (LANDFIRE) (GAP/LANDFIRE) [United States side] and the National Institute of Statistics and Geography (INEGI) [Mexico side] as well as land cover maps and opportunistic open-access and field observations. Mapping of the full BCR 33 region was carried out in two phases: 1) Phase I, the prototype map, covered a smaller portion of the transboundary area and identified 31 land cover classes, and 2) Phase II, the full BCR 33 map (refer to Figure 1), which resulted in 152 land cover classes. Using a Random Forest classifier, we achieved an overall prediction accuracy of 92% for the Phase I map and 87% for the Phase II full region map. This slight decrease can be attributed to working on a larger, more complex area with a greater number of land cover classes. No formal validation was conducted, aside from using a subset of the collected field observations and training data to assess model performance during and after training. The training sites were further verified using Google Earth (Google, 2026) imagery. Two undergraduate students who worked for over a year visually inspected imagery and open access public images to confirm each training site during model training using in-house developed, online, visual tools. A portion of this field training data was reserved for model validation, and the corresponding results are to be presented in later sections. The project developed an end-to-end, medium- and fine-resolution remote sensing–based data fusion mapping approach. This effort produced a map (Nagler et al., 2025) and the online tools to support a dynamic, live, online map for visualizing the transboundary vegetation communities in BCR 33. The toolset is currently hosted by the University of Arizona (UofA) Vegetation Index and Phenology (VIP) Lab to support FWS partners (https://vip.arizona.edu/viplab_data_explorer?LCM_BCR33). The online map is designed to allow rapid updates using new training, validation, or correction data, making it dynamic and maintainable. The approach we took established a framework for rapid updating and correction of land cover maps, as the model can be quickly retrained with new field observations, updated training data, or other sources. This enables dynamic mapping and change detection of the region’s vegetation. This framework is an advance in data fusion and crowdsourced mapping of complex, vulnerable regions, providing support to regional stakeholders and the wider user community. This transboundary map can inform the protection, conservation, and restoration of vegetation, habitat, and ecosystems, particularly for threatened and endangered species across the two nations using consistent and harmonized binational mapping systems. Beyond supporting land management decisions and stakeholders in the transboundary desert ecoregions, this BCR 33 mapping effort establishes a foundation for future rapid, low-cost, cross-border land cover mapping that can benefit and advance ecosystem management.

Arizona, Baja California, California, Nevada, Sina↗
USGS2026

Age and colony variation in Adélie penguin metapopulation vital rates: Insights from a 25-year mark–recapture study

Understanding how vital rates vary with age, life-history stage, and among populations is fundamental for predicting the demographic consequences of environmental change, especially in longer-lived species with complex life histories. These species often exhibit delayed maturity and iteroparity, making nuanced demographic insights critical for assessing their long-term viability. This study investigated age- and colony-related variation in Adélie penguin vital rates including survival, recruitment, and breeding propensity. We used mark–recapture data collected over 25 years (1996–2020) from three Adélie penguin breeding colonies that differed in population sizes and trends but comprised a metapopulation located at capes Royds, Bird, and Crozier on Ross Island, Antarctica. We used multi-state models to estimate survival and detection rates relative to reproductive state and breeding colony and estimated transition probabilities reflecting movements between reproductive states and colonies. Apparent survival varied by reproductive state, colony, and age and averaged 0.80 (SD = 0.02) at Bird, and 0.72 (SD = 0.03) and 0.73 (SD = 0.03) at Crozier and Royds, respectively, for pre-breeders age 2–7 years with strong declines in pre-breeder survival after age 8. We observed less age-related variation in survival of breeders and non-breeders, but we observed differences between colonies with lower survival for breeders (0.72 to 0.80) compared to non-breeders (0.75 to 0.82). The average probability of surviving the first 2 years after fledging ranged from 0.43 (SD = 0.14) at Royds and Crozier (0.43, SD = 0.10) to 0.55 (SD = 0.15) at Bird. Movement between colonies was highest for pre-breeders (0.00%–12.00% depending on age and colony) and lowest for breeders (<0.20%). We observed the lowest age-related recruitment rates at Royds, with recruitment at Crozier almost twice as high, and intermediate at Bird. Breeding propensity was highest at Crozier and lowest at Bird. Colony-specific variation in vital rates likely contributed differently to population trajectories, suggesting that care must be taken to extrapolate vital rate estimates across colonies even within a metapopulation. These findings also highlight the importance of considering age, life-history stage, and geographic variation when assessing population vital rates in species with complex life histories.

Frontiers in Ecology and Environment↗
USGS2024

Seismicity zoning at Coso geothermal field and stress changes from fluid production and migration

The Coso geothermal field is a major geothermal power production site in the western United States. It has been observed that low-magnitude seismic events ( M < 3.71) are unevenly distributed in three distinct zones, namely, nearfield (<3 km), midfield (3–6 km), and farfield (> 6 km) from the Coso geothermal plant. These zones exhibit distinct changes in earthquake location before and during geothermal production episodes that began in 1986. After 1986, the midfield region of the main flank experiences a significantly lower seismicity rate than the surrounding areas before production episodes. During 2014–2019, the farfield earthquakes cluster in the eastern and western parts of the greater Coso area, which is discernably different from how those pre-production earthquake events were distributed along the conjugate NW-SE and SW-NW trending structures across the main flank. Here, we analyze the stage of stress with finite-element-based poroelastic simulations to illustrate how the spatiotemporal evolution of the seismicity is associated with the pattern of stress perturbations caused by fluid migration amid the operations of geothermal power plants. Generally, ∼70% of co-production seismicity is found in zones of increased Coulomb stress between 2014 and 2019 at >99% confidence. Meanwhile, the midfield zone of seismic paucity overlaps with the zone of decreasing pore-fluid pressure. Overall, the results provide a physical explanation of how decadal geothermal operations at Coso have perturbed stress-field changes and contributed to the evolving characteristic seismic pattern, shedding insights into assessing the seismic hazard in other geothermal settings.

California↗
USGS2025

Decomposing the Tea Bag Index and finding slower organic matter loss rates at higher elevations and deeper soil horizons in a minerogenic salt marsh

Environmental gradients can affect organic matter decay within and across wetlands and contribute to spatial heterogeneity in soil carbon stocks. We tested the sensitivity of decay rates to tidal flooding and soil depth in a minerogenic salt marsh using the Tea Bag Index (TBI). Tea bags were buried at 10 and 50 cm depths across an elevation gradient in a subtropical Spartina alterniflora marsh in Georgia (USA). Plant and animal communities and soil properties were characterized once, while replicate tea bags and porewaters were collected several times over 1 year. TBI decay rates were faster than prior litterbag studies in the same marsh, largely due to rapid green tea loss. Rooibos tea decay rates were more comparable to natural marsh litter, potentially suggesting that is more useful as a standardized organic matter proxy than green tea. Decay was slowest at higher marsh elevations and not consistently related to other biotic (e.g., plants, crab burrows) or abiotic factors (e.g., porewater chemistry), indicating that local hydrology strongly affected organic matter loss rates. TBI rates were 32 %–118 % faster in the 10 cm horizon than at 50 cm. Rates were fastest in the first 3 months and slowed 54 %–60 % at both depths between 3 and 6 months. Rates slowed further between 6 and 12 months, but this was more muted at 10 cm (17 %) compared to 50 cm (50 %). Slower rates at depth and with time were unlikely due to the TBI stabilization factor, which was similar across depths and decreased from 6 to 12 months. Slower decay at 50 cm demonstrates that rates were constrained by environmental conditions in the deeper horizon rather than the composition of this highly standardized litter. Overall, these patterns suggest that hydrological setting, which affects oxidant introduction and reactant removal and is often overlooked in marsh decomposition studies, may be a particularly important control on organic matter loss in the short term (3–12 months).

Georgia↗
USGS2024

Formation of vertical columnar seismic structures and seafloor depressions by groundwater discharge in the drowned Miami Terrace platform and overlying deep-water carbonates, southeastern Florida

The presence of vertical cross-formational fluid migration passageways within sedimentary basins can profoundly impact aquifer and reservoir fluid-flow and their identification is fundamental to informing management of subsurface fluid resources (groundwater, oil, gas). In an onshore and offshore southeastern part of Florida, 2D/3D seismic-reflection and bathymetry data document ∼153 vertical columnar structures composed of reflection disruptions up to 790 m in the height and averaging 360 m in diameter, and ∼219 subcircular to circular seafloor depressions up to 1334 m wide. Our study focuses on these features found within the offshore shallow-marine carbonate Miami Terrace platform, which drowned approximately at the end of the middle Miocene, and within overlying Plio-Quaternary deep-water carbonate slope and drift deposits. Most columnar structures are rooted in stratiform aquifers of the Miami Terrace platform and associated with faults or fault intersections produced by Eocene and circa late Miocene tectonics. The columns commonly terminate within the platform or as subcircular depressions along an amalgamated karstic and drowning unconformity at the platform top. The columns typically stretch upwards from a zone of deep karst cavity collapse through the Miami Terrace platform with upward decreasing sag on internal reflections. Following drowning and Plio-Quaternary partial burial of the Miami Terrace platform by deep-water deposits, the subcircular depressions and faults along the platform top were points of origin for a second phase of column growth upward into the deep-water deposits. The continuation of deep platform cavity collapse and column evolution produced pockmarks along paleo-seafloors within the deep-water deposits and at the present-day sea floor. The Plio-Quaternary pockmarks formed at water depths too deep to suggest an origin related to meteoric karst above or near sea level, but rather their formation is suggested to be related to cyclic sea level falls that drove increased groundwater head and density gradients, and seafloor discharge of offshore freshened groundwater sourced from the underlying platform. Plausibly, mixing of freshened groundwater and seawater at the seafloor discharge sites drove dissolution of the host deep-water deposits, which together with erosion by groundwater venting and current scouring formed the pockmarks. Seaward of the Plio-Quaternary seafloor pockmarks, at the late-middle Miocene upper slope of the Miami Terrace platform and along the regional karst/drowning unconformity is a slope-parallel band of ∼189 densely distributed subcircular seafloor depressions with diameters up to 1334 m at water depths up to ∼660 m. It is plausible that along the upper slope, faults and fractures produced by gravity-driven slope instability and possibly tectonics formed a dense network of fluid passageways that promoted upward artesian freshened groundwater flow to sites of discharge where mixing with seawater generated limestone dissolution and the depressions. But tectonic uplift may have forced emersion and initial meteoric sinkhole formation circa late Miocene with later enhancement by freshened groundwater discharge and bottom current erosion.

Florida↗
USGS2022

South Carolina and Landsat

South Carolina, the eighth State admitted to the union, transcends its size with its deep, rich history; striking beauty; vast natural resources; and extensive cultural diversity. Home to part of the Blue Ridge Mountains of the Central Appalachians, the Upstate is graced with more than 100 waterfalls, while the Lowcountry borders the Atlantic Ocean with 187 miles of coastline and 35 barrier islands. Forests cover two-thirds of the State, and forestry and agriculture together, as agribusiness, make up South Carolina’s leading industry. Two historic crops—cotton and tobacco—still rank in the top 10 commodities, though corn and soybeans now rank higher. Poultry, cattle, peanuts, and flowers also make the list. South Carolina’s population totals more than five million. Other residents include a variety of wildlife, bird, reptile, and fish species, including Ursus americanus (black bears), Alligator mississippiensis (American alligators), and Tursiops truncatus (bottlenose dolphins). More than 100 tree species also reside in South Carolina, which pays homage to one with its “The Palmetto State” nickname. South Carolina’s subtropical climate, long coastline, and lower elevations make it highly susceptible to tornado and hurricane activity and coastal flooding. Projected sea-level rise is a growing concern. A view from space can help monitor and manage natural resources on the land and in rivers, marshes, and the coast. Landsat reveals not just what an area looks like now, but also insights from decades ago.

South Carolina↗