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Results for “Journal of Foraminiferal Research”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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1,660 records · Page 91Linked to original sources
USGS2026

Variable pH habitats could help prepare stone crabs for coastal acidification

Coastal acidification is being exacerbated by terrestrial organic inputs, especially after high precipitation events. Florida’s rainy season coincides with stone crab ( Menippe mercenaria) reproduction, and pH extremes could limit future harvests by reducing reproductive output. Populations that experience pH variability can serve as “natural laboratories” for estimating the tolerance of a species to coastal acidification. Here, we conducted a series of experiments to determine if ovigerous stone crabs conditioned in more variable pH habitats (seagrass) would result in faster embryonic development, greater hatching success, and higher larval survival relative to crabs conditioned in habitats with lower pH variability (sandy habitats). After field conditioning, crabs were transported to the laboratory and randomly acclimated to either a control pH (pH = ~ 7.90) or a reduced pH condition (pH = ~ 7.60) until larval release. The rate of embryo development was slower in the laboratory reduced pH treatment, however, there were no observable field condition effects on embryo development rate. Crabs conditioned in the more pH variable seagrass habitat did have greater hatching success and higher larval survival than crabs in less pH variable sandy habitats; however, larval survival was low across all treatments. These results suggest that the pH variability experienced in seagrass habitats during brooding may serve as a mechanism for stone crabs to acclimatize to extremes in seawater pH.

Marine Biology↗
USGS2025

Irrigated agriculture influences selenium levels in an endangered marsh bird

Selenium bioaccumulation in aquatic food webs poses risks to wildlife, particularly in wetlands receiving irrigation runoff. The Salton Sea, California’s largest lake, is primarily sustained by agricultural drainage. This drainage creates wetland habitat along the lakeshore that many bird species depend on, including the federally endangered Yuma Ridgway’s rail ( Rallus obsoletus yumanensis ). However, these marshes may pose an ecological trap – attracting rails despite high selenium exposure. We captured rails during the 2020–2023 breeding seasons and compared rail selenium levels within three types of marshes (fed with irrigation runoff, Colorado River water, or groundwater). We collected blood, breast feathers, and head feathers of rails in all three water sources for selenium comparisons. We tagged adult rails with GPS transmitters to locate nests and foraging locations where we collected eggshells, unhatched eggs, and prey. We assessed selenium exposure by collecting multiple prey species commonly eaten by rails in all three water sources. Selenium concentrations varied among sampling locations. Selenium concentrations in most sample types were predominately influenced by water source and marsh inflow velocity (sometimes in combination with marsh size). Distance to inflow, however, did not influence selenium concentrations in any sample type. Selenium concentrations were highest in agricultural-fed marshes compared to river-fed and spring-fed marshes. Increased marsh inflow velocities resulted in lower selenium concentrations. Given the risk of an ecological trap, our results suggest that supplementing wetlands with Colorado River water could mitigate selenium bioaccumulation in Yuma Ridgway’s rails.

California↗
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

The 2023 U.S. 50-state National Seismic Hazard Model: Changes in 2023 compared to 2018 ground motions

We present the 2023 U.S. National Seismic Hazard Model (NSHM) for all 50 states that applies new smoothed seismicity, fault rupture, and ground motion models. New data and methods are introduced in the 2023 earthquake rupture forecast that include: new earthquake catalogs - excluding induced earthquakes, alternative declustering methods, spatially smoothed seismicity distributions, full-catalog scaled rates to account for aftershocks, updated CEUS-WUS attenuation boundary, new magnitude-scaling equations, new geodetic and geologic deformation models, and alternative fault system solutions accounting for a more complete representation of epistemic uncertainty potential for earthquake generation in Alaska, Hawaii, and the conterminous U.S. Improved ground motion models consider new Next Generation Attenuation NGASubduction, modified NGA-East, and adjustments to account for regional biases in ground shaking observations. Semi-empirical and 3D simulations of ground motion are applied to account for shaking at 21 oscillator periods, 2 peak motions, and 8 site conditions. Site effects models are constructed for western U.S. basins (Seattle, Portland/Tualatin, San Francisco, Central Valley of California, Los Angeles, and Salt Lake City) and for sites with deep sedimentary wedges found across the central and eastern U.S. Gulf Coast and Atlantic coastal plain regions. These models result in substantial changes compared to the older NSHMs and are differentiated for the earthquake rupture forecast and ground motion model changes to display sensitivities and impacts.

Conference Paper↗
USGS2024

Groundwater quality and groundwater levels in Dougherty County, Georgia, April 2020 through January 2023

The Upper Floridan aquifer is the uppermost reliable groundwater source in southwest Georgia. The aquifer lies on top of the Claiborne, Clayton, and Cretaceous aquifers, all of which exhibited water-level declines in the 1960s and 1970s. The U.S. Geological Survey has been working cooperatively with Albany Utilities to monitor groundwater quality and availability in these aquifers since 1977. Flow direction in the Upper Floridan aquifer is to the south and toward the Flint River. During the past 3 years, water levels varied above and below period-of-record median values. Water levels in the Upper Floridan aquifer were primarily above or at median levels during 2020 and 2021 and at or below median levels during 2022. Water levels in the Claiborne aquifer were above median levels, whereas water levels in the Clayton aquifer were at or below median levels, and in the Cretaceous aquifer system were close to median levels. During January 2021, eight wells were sampled for major ions, including nitrate plus nitrite as nitrogen (N). Nitrate plus nitrite as N concentrations ranged from 2.3 to 10.5 milligrams per liter (mg/L). During December 2021, seven wells were sampled for major ions, including nitrate plus nitrite as N. Nitrate plus nitrite as N concentrations ranged from 3.9 to 9.9 mg/L. During November 2022, eight wells were sampled for major ions, including nitrate plus nitrite as N. Nitrate plus nitrite as N concentrations ranged from 3.9 to 10.0 mg/L. Two wells were also sampled for per- and polyfluoroalkyl substances during November 2022.

Georgia↗
USGS2024

Mapping Arundo donax (Arundo cane) with multispectral imagery before, during, and after herbicide treatment along the Rio Grande in Webb County, Texas, 2020–21

Arundo donax , commonly called Arundo cane, giant reed, or Carrizo cane, is an invasive bamboo-like perennial grass common in riparian areas throughout the southwestern United States. In Texas, not only does it negatively affect riparian ecosystems, but it has also become a problem for border security because it reduces visibility along the Rio Grande. To address these problems, in 2015 the Texas State Soil and Water Conservation Board was authorized by the Texas State Legislature to develop a program to eradicate Arundo cane along the Rio Grande. In 2020, the Texas State Soil and Water Conservation Board applied imazapyr and glyphosate herbicides along a 19.3-kilometer reach of the Rio Grande, northwest of Laredo, Texas. The U.S. Geological Survey, in cooperation with the Texas State Soil and Water Conservation Board and the Webb Soil and Water Conservation District, used WorldView-3 Standard high-resolution satellite imagery to map Arundo cane extent along the reach before , during , and after the herbicide-treatment period on June 30, 2020, September 26, 2020, and May 7, 2021, respectively. A maximum likelihood supervised classification analysis was computed on the images to map the spatial extent and estimate the area covered by Arundo cane. The estimated area covered by Arundo cane in the before classification was 1,282,000 square meters, in the during classification was 1,064,000 square meters, and in the after classification was 1,108,000 square meters. The qualitative comparison of the three images shows that there was an overall decrease in vegetation classified as Arundo cane throughout the study area.

Texas↗
USGS2026

Surface variable‐based machine learning for scalable arsenic prediction in undersampled areas

In the United States, private wells are not federally regulated, and many households do not test for Arsenic (As). Chronic exposure is linked with multiple health outcomes, and risk can change sharply over short distances and with well depth. Coarse maps or sparse sampling often miss exceedances. Most existing models operate at ∼1 km resolution and use groundwater chemistry or detailed geologic logs, which limits their use in undersampled areas where improved guidance is most needed. We overcome these limitations by developing a machine learning model for Minnesota, USA, that predicts As exposure risk using only surficial variables from remote sensing and global data sets. Variables related to surface water hydrology and geomorphology are selected based on mechanistic links that control redox conditions and As mobilization. Local training was essential, and surficial geology variables that are more sensitive to local conditions were needed to maximize model accuracy. The resulting complete model was sufficiently sensitive to generate accurate and detailed risk maps and depth profiles of As concentrations above the 10 μg/L maximum contaminant level. Accuracy depended on local training data density. We identified a training data density of 0.07 wells/km 2 as a practical target for stable county-level performance. Maps of exceedance probabilities highlight priority areas for testing that are particularly important in rural communities that have received less sampling. These results support public health action by guiding where to install wells and where to test them, how much new sampling is needed, and where treatment outreach is most urgent.

Minnesota↗
USGS2026

Satellite time series analysis to quantify changing climax ciénegas using a state and transition model approach

Ciénegas are rare wetlands in arid landscapes of the North American Southwest, historically providing critical ecological and hydrological functions but increasingly threatened by changing climate and land use pressures. This study quantifies changes in ciénega condition and floodplain dynamics using a state-and-transition model (STM) informed by expert knowledge and remote sensing. Key factors include woody plant encroachment, water availability, and soil aggradation. We mapped 31 ciénegas with high-resolution imagery and analyzed Landsat data (1985–2023) to assess vegetation health and moisture using the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Infrared Index (NDII). Results show substantial interannual variability in phenology, water stress, and soil moisture, with regional drying and elevation strongly influencing ciénega resilience. We classified ciénegas into three functional states—healthy, desiccated, and dormant—and mapped their 2023 condition. Trend analyses indicate most ciénegas exhibit greening despite drought, though localized variability underscores the need for site-specific management. None are in a stable climax (reference) state; rather, they transition among states in response to external drivers. Increasing woody plant cover and surface drying, likely linked to declining regional water tables, favor deep-rooted species over wetland grasses—a pattern mirrored in adjacent control plots. Spatially explicit analysis revealed intra-ciénega variability often masked by aggregated data, highlighting the importance of high-resolution monitoring. Seasonal and long-term trends provide context for understanding ciénega dynamics, including degradation and restoration pathways. This study emphasizes the importance of groundwater conservation and demonstrates how remote sensing supports long-term monitoring. The STM framework offers a practical tool for adaptive management to sustain freshwater resources in arid environments.

Arizona, New Mexico↗
USGS2026

Predictable seismic cycles result from structural rupture barriers on oceanic transform faults

Earthquakes of magnitude ( M ) >5.5 on oceanic transform faults (OTFs) repeatedly rupture the same locked patches, sometimes quasiperiodically. These patches are separated by “barriers” that halt earthquake propagation and slip mostly aseismically. However, the physical processes governing this systematic behavior remain unclear. We analyzed two barriers along the Gofar transform fault that have arrested ~15 M 6 earthquakes over the past three decades. Ocean bottom seismometer data indicate that the barriers hosted intense microseismicity before the mainshocks and comprise multistrand faults and transtensional stepovers with 100- to 400-m lateral offset. These characteristics contradict earthquake rupture termination models invoking velocity-strengthening friction or large geometric steps and instead point to damage-enhanced porosity and dilatancy-strengthening mechanisms. By isolating rupture segments, the barriers regulate the quasiperiodic recurrence of OTF earthquakes.

Science↗
USGS2026

Water table rise sustains carbon release from soils in wetland-dominated landscapes: An intact soil core study

Wetland-dominated landscapes influence carbon cycling through their potential to act as both carbon sinks and sources. Wetlands in low-relief landscapes have dynamic terrestrial-aquatic interfaces that change seasonally with variable surface water and groundwater levels. However, few studies have directly quantified dissolved organic matter (DOM) release and greenhouse gas (CO 2 , CH 4 ) fluxes from wetland soils along terrestrial-aquatic interfaces as they are seasonally re-saturated by groundwater. To estimate groundwater-mediated soil DOM and gas fluxes, we performed laboratory simulations of vertical groundwater rise on intact soil cores collected from four Delmarva bay wetlands located in the Mid-Atlantic United States. At each wetland, one core was collected from within the wetland basin and the other from the transitional zone at the basin edge. Cores were re-saturated with groundwater over 15 days and then kept fully saturated for an additional 25 days. Source groundwater, soil porewater, and exfiltrated surface water samples were collected and analyzed for pH, ORP, DOM concentration, and DOM optical indices. In both the wetland and transition zone cores, porewater DOM concentrations increased over the wet up and were sustained during prolonged saturation. Optical indices shifted from recently produced, microbial-like signatures towards aromatic, terrestrial-like signatures. Fluxes of CO 2 decreased as the duration of soil saturation increased and soil cores switched from CH 4 sinks to sources upon full soil core saturation. Results indicate that groundwater rise sustains carbon mobilization from soils in wetland-dominated landscapes, emphasizing the need to understand how climate-driven changes to groundwater dynamics may affect carbon fluxes along terrestrial-aquatic interfaces.

Delaware, Maryland↗
USGS2026

Critical minerals memory match game

An educational information packet about the 2025 List of Critical Minerals, which includes a memory match game about select critical minerals and how they are used.

General Information Product↗
USGS2025

Observing northern high-latitude river systems to understand changes in a warming Arctic

Purpose of Review Streams and rivers are undergoing rapid change as the Arctic warms and thaws. We review recent observations in Arctic stream systems to identify ubiquitous changes and the most useful tools for observing change and exploring the underlying processes. Recent Findings Recent literature indicates increasingly significant trends in river hydrology and chemistry due to persistent warming in the Arctic and longer observational records for analysis. However, regional differences in the magnitude and direction of these trends persist. We also observe thresholds in ground thaw and surface–groundwater interactions that can impact river hydrology and chemistry. Summary Warming and thaw are occurring rapidly at high latitudes, resulting in increasing, yet variable responses in stream systems across regions and scales. These differences highlight the need for long-term records and an interdisciplinary approach to explain trends and predict future states. Stream systems respond to multiple landscape changes related to hydrology (changing precipitation and subsurface flow), geology (ground thaw dynamics), and ecology (vegetation change).

Current Climate Change Reports↗
USGS2026

Temperate wetlands lose climate-cooling capacity under warming

Temperate inland wetlands have long been viewed as climate regulators, with sustained CO₂ sequestration offsetting continuous CH₄ emissions over centennial–millennial timescales. However, the net climatic effect of these opposing fluxes remains uncertain under anthropogenic warming as they differ in both magnitude and atmospheric lifetime. We combine 19,000 CH₄ chamber measurements from 202 temperate inland wetlands with carbon burial rates from 16 dated sediment cores in North America’s Prairie Pothole Region to estimate greenhouse gas dynamics over two centuries. Here we show that CH₄ emissions rise by ~1.39 kg CH₄ ha⁻¹ yr⁻¹ over the historical period and are projected to approach 950 kg CH₄ ha⁻¹ yr⁻¹ under high-forcing scenarios by 2100, while CO₂ sequestration is expected to decline by ~0.3 kg CO₂ ha⁻¹ yr⁻¹, driving a shift toward persistent net CO₂-equivalent source behaviour and a weakening of the long-term cooling effect that wetlands have provided under natural conditions.

Prairie Pothole Region↗
USGS2026

Bayesian belief network model to predict human-wildlife conflict in protected areas

Human-wildlife conflict (HWC) poses a pervasive global challenge, affecting livelihoods and threatening biodiversity. To better anticipate and mitigate HWC risk, we developed a large-scale predictive model using a Bayesian Belief Network (BBN). We surveyed 1,011 park rangers across 135 terrestrial protected areas in three Andean countries, documenting recent HWC incidents involving wildlife persecution or killing, livestock depredation, crop damage, or threats to human safety and property. We identified key drivers of HWC risk, including governance, wildlife acceptance, participation, and habitat quality. A sensitivity analysis revealed that enhancing governance and improving wildlife acceptance could reduce HWC risk by > 85%. The BBN model demonstrated scalability, effectively identifying strategies to reduce HWC risk at multiple scales, from individual protected areas to national networks. Our findings highlight the importance of strengthening governance, increasing wildlife acceptance, and enhancing community participation in conservation efforts. BBNs provide a flexible, cost-effective, and data-driven tool to guide protected areas and wildlife managers in monitoring, anticipating, and making informed decisions to mitigate conflict and promote coexistence.

Scientific Reports↗
USGS2026

A 481 m-high landslide-tsunami in a cruise ship-frequented Alaska fjord

Early in the morning of 10 August 2025, a >64 × 10 6 –cubic meter landslide struck Tracy Arm fjord in Alaska. The landslide was preconditioned by glacial retreat caused by climate change. The resulting 481-meter runup megatsunami followed an initial 100-meter-high breaking wave traveling at >70 meters per second. The landslide was preceded by several days of microseismicity, which increased in rate and magnitude until ~1 hour before failure. The landslide produced globally observed long-period seismic waves equivalent in size to a moment magnitude 5.4 earthquake. A long-period (~66 second) global seismic signal, produced by a landslide-induced seiche trapped within the fjord, persisted for up to 36 hours, the second time a days-long seiche had thus been observed. With fjord regions increasingly visited by cruise ships, and climate change making similar events more likely, this unanticipated, near-miss event highlights the growing risk from landslides and tsunamis in coastal environments.

Alaska↗
USGS2026

Unprecedented burning in tropical peatlands during the 20th century compared to the previous two millennia

Tropical peatland wildfire incidence has risen in recent decades, driven by drainage for land use and intensified by severe droughts with global climate change. These disturbances have altered vegetation structure, disrupted ecosystem functioning, and increased carbon emissions, particularly in Southeast Asia. However, the long-term history and characteristics of wildfires in tropical peatlands remain largely unknown. Here, we compiled fifty-eight macro-charcoal records from peatlands across the tropics, ranging from lowland forested to montane peatlands, to assess millennia-scale changes and controlling factors of tropical peatland burning. We divided the datasets into four main sub-regions: Neotropical, Afrotropical, Indomalayan and Australasian ecoregions to explore regional variability. Tropical peatlands had high burning levels between 0 and 850 ce , followed by a relatively low and stable period until a marked increase during the 20th century. The general trend in tropical peatland burning follows changes in global temperature, and climate variables that control the length and severity of drought events have a notable influence on peat burning before 1900 ce . During the 20th century, regional differences were observed, with declining fire trends in the Neotropical and Afrotropical regions and increasing fire trends in the Indomalayan and Australasian regions. This difference is likely attributable to human activities, and such intervention is also evident in palm swamps and hardwood swamps under similar wet, weakly seasonal climates. With the increase in anthropogenic pressures on peatlands and greater climate variability, future wildfires in peatlands are likely to become more frequent and widespread across all tropical ecoregions. Conservation and sustainable land-use practices could be used to mitigate and control peatland burning and protect these carbon-rich sinks.

Global Change Biology↗
USGS2026

Rapid earthquake magnitude classification via P-wave strains from borehole strainmeters and Distributed Acoustic Sensing

Distributed Acoustic Sensing (DAS) offers a promising approach for earthquake early warning (EEW) in settings where seismic networks are costly to maintain. By repurposing fiber-optic cables as dense strainmeter arrays, DAS enables real-time earthquake detection wherever those fibers are accessible. However, poor azimuthal coverage and challenges in estimating magnitude from strain measurements remain key hurdles in applying for earthquake monitoring. Here, we develop a machine learning method to distinguish large (M≥5.4) earthquakes from smaller ones within the first 4 seconds of a strain waveform after a P-wave arrival without determining location. Using ensemble decision tree models trained on borehole strainmeter data (3.5≤M≤7.1) and tested on onshore DAS waveforms (including the 2024 M7 Offshore Cape Mendocino earthquake), we find that low-frequency (0.2–0.5 Hz) continuous wavelet transform coefficients are the strongest predictors of magnitude, in addition to strain amplitude. Both DAS and borehole strainmeters effectively capture long-period strain signals, making these findings valuable for EEW systems. Our method shows high precision compared to the real-time EEW system, ShakeAlert®, supporting the position that DAS is a viable technology for earthquake monitoring and magnitude classification.

California↗
USGS2024

Rock sample photogrammetry

This step-by-step protocol describes the photogrammetry process used by the U.S. Geological Survey Spokane Imaging Lab (SPIMG) lab to create 3D models of geologic samples. Steps related to photographing small objects are applicable to photogrammetry in general, however, SPIMG-specific steps involving lab hardware and software may not be.

Protocols.io↗