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Deep subsurface organic-rich shale supports abundant, diverse, and novel fungi

As Earth’s principal reservoir of organic carbon and microbial biomass, the deep subsurface hosts microorganisms capable of mobilizing this once-sequestered carbon. Contrary to standard assumptions of eukaryotic scarcity, this study documents abundant fungal communities, ranging from 4.2 × 10 3 to 6.8 × 10 3 fungal cells mL −1 , across a methane-producing organic-rich shale 247–556 meters below the surface. Although fungal:bacterial cell ratios ranged from 1:7028 to 1:713, application of biomass conversion factors developed for oceanic systems yielded a median fungal:bacterial biomass ratio of 1:4.7. 16S rRNA gene amplicons revealed bacterial and archaeal communities mirroring those found in well-characterized extremophilic, carbon-degrading environments, while sequencing of 18S rRNA gene and ITS rRNA spacer amplicons collectively identified a eukaryotic hotspot with 689 fungal OTUs across six phyla. The dominant fungal classes, Agaricomycetes and Dothideomycetes, are well-established degraders of recalcitrant carbon compounds at the surface, suggesting they may similarly contribute to organic matter degradation and ecosystem maintenance in the subsurface. Cultivation and isolation efforts yielded 205 fungal strains, including 13 candidate novel taxa, underscoring the deep subsurface as an underexplored eukaryotic habitat. Stable carbon isotopes indicate methane is predominantly generated via microbial conversion of the fossil carbon, while water isotopes suggest in situ geochemical conditions have been relatively stable since the Late Pleistocene, with subglacial recharge as a plausible mechanism for microbial introduction. Collectively, these findings suggest that fungi are underrecognized contributors to organic matter transformation and functional diversity in the deep biosphere, revealing a critical gap in our understanding of deep subsurface ecosystem processes.

Indiana, Michigan, Ohio

Northern bobwhites select for native grasses on working grazing land

Northern bobwhite ( Colinus virginianus ; bobwhite) populations have experienced an 85% decline across most of its range since the 1960s. The most drastic decreases have been in the southeastern United States where biologists attribute the decline to widespread habitat loss, including conversion of native grasslands to tall fescue ( Lolium arundinaceum ) and other exotic cool-season grass (CSG) pasture and hayfields. Including agricultural lands in conservation programs could improve habitat conditions on a regional scale. One working-lands conservation strategy involves the use of native warm-season grasses (NWSGs) rather than cool-season exotic grasses as economically viable cattle forage. To evaluate this management practice for creating bobwhite habitat, we conducted a field study on a bobwhite population in eastern Kentucky, USA, where grazed NWSG and burned NWSG fields were adjacent to exotic grazed and exotic hayed CSG fields. Between April 2019 and October 2022, we used radio telemetry to track bobwhites to evaluate resource selection at second- and third-order scales. Bobwhites used traditionally managed CSGs less than would be expected by chance at the second-order scale in both breeding and non-breeding seasons. Bobwhite use of grazed NWSG and burned NWSG was greater than would be expected by chance at the second-order scale in both breeding and non-breeding seasons. Similarly, at the third-order scale, bobwhites used CSGs less than would be expected by chance, whereas NWSGs and woody stems were used more than by chance alone. Our study suggests that bobwhites select NWSGs at multiple spatial scales despite broad-scale availability of managed exotic CSGs. Under a working-lands framework, the integration of NWSGs into working lands could create bobwhite habitat in the southeastern United States, especially if woody stems are present.

Kentucky

Refinements to the attenuated propagation of local earthquake shaking (APPLES) ground-motion-based earthquake early warning algorithm

We refined the Attenuated ProPagation of Local Earthquake Shaking (APPLES) ground-motion-based earthquake early warning (EEW) approach, and directly compare APPLES performance with that of the source-characterization-based U.S. ShakeAlert EEW system for a suite of historical earthquakes in the U.S. West Coast and Japan. APPLES is an extension of the Propagation of Local Undamped Motion (PLUM) algorithm in which observed shaking intensity at seismic stations is used to forward-predict intensity distributions to surrounding areas using an attenuation model derived from an intensity prediction equation. We test new configuration options within APPLES, such as using the second highest estimated ground motion rather than the maximum, to better match median ground-motion observations and reduce alerts for small magnitude earthquakes, both of which are key alerting priorities within ShakeAlert. We evaluate these configurations alongside ShakeAlert by comparing the ground-motion estimation accuracy and available warning times relative to station observations and ShakeMap distributions. Our preferred APPLES configuration produces accurate ground-motion estimates and corresponds better with median observations compared to ShakeAlert’s estimates. This preferred configuration substantially reduces alert issuance for M < 5.0 earthquakes compared to the previous APPLES configuration, and alert-release criteria can further restrict alerts to primarily M ≥ 5.5 earthquakes without requiring magnitude estimation. Prioritizing matching median-observed ground motions may reduce APPLES warning times compared to configurations that were tuned to avoid missed alerts (such as those that use the maximum estimated ground motions), which can lead to shorter warning times compared to ShakeAlert for the same alert threshold. However, station-based warning time assessments demonstrate that APPLES can outperform ShakeAlert for high target thresholds. APPLES is a simple, independent EEW approach that may improve the robustness of EEW for the West Coast of the U.S.

California, Oregon, Washington

Discrete element investigation of the influence of shallow soil density on the manifestations of strike-slip surface fault rupture

This study investigates the influence of soil relative density on strike-slip surface fault rupture manifestations using three-dimensional numerical simulations performed with the discrete element method (DEM). The simulations capture the formation of distinctive fault strands within complex flower structures using tens of millions of grains. The tendency for dense soils to localize shear manifests as multiple localized shear bands within wide zones of deformation in strike-slip fault rupture, whereas diffuse shear deformation develops within narrow zones in loose soils. The spatial extents of soil deformation are consistent between simulations having similar relative densities but with different quantities of grains. However, individual shears are more distinguishable in assemblages of finer grains than in assemblages of coarser grains. The simulations show the progressive development of new shears within the bounds of previously developed shears. Shear activity transitions inward as fault activity diminishes along the outermost shears and continues along newly developed shears until a vertically dipping throughgoing shear structure develops that accommodates most of the fault displacement thereon. The throughgoing fault develops at smaller fault displacements in looser soils because the first shear rupture propagates closer to the vertical direction and does not undergo as much inward translation of shear activity, as is observed in denser soils. In all simulations, ground surface uplift develops between nonintersecting active shears, and ground surface subsidence tends to develop where new shears intersect previous shears. The surface traces in these simulations are shown to be consistent with analog models and case histories of surface fault rupture occurring in different shallow subsurface materials. Although computationally costly, these modeling results are valuable for providing a strong numerical supplement to traditional analog models used to represent the mechanics of strike-slip zones in soil, and they provide quantifiable stresses and large-strain deformations throughout the model domain.

Journal of Geotechnical and Geoenvironmental Engin

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

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

Connecticut

Following the tug of the audience from complex to simplified hazards maps at Cascade Range volcanoes

Volcano-hazard maps are broadly recognized as important tools for forecasting and managing volcanic crises and for disseminating spatial information to authorities and people at risk. As scientists, we might presume that hazards maps can be developed at the time and with the methods of our discretion, yet the co-production of maps with stakeholder groups, who have programmatic needs of their own, can sway the timing, usability, and acceptance of map products. We examine two volcano hazard map-making efforts by staff at the U.S. Geological Survey. During the 1990s and early 2000s scientists developed a series of hazard assessments and maps with detailed zonations for volcanoes in Washington and Oregon. In 2009, the National Park Service expressed the need for simplified versions of the existing hazard maps for a high-profile visitor center exhibit. This request created an opportunity for scientists to rethink the objectives, scope, content, and map representations of hazards. The primary focus of this article is a discussion of processes used by scientists to distill the most critical information within the official parent maps into a series of simplified maps using criteria specified. We contextualize this project with information about development of the parent maps, public response to the simplified hazard maps, the value of user engagement in mapmaking, and with reference to the abundance of guidance available to the next generation of hazard-mapmakers. We argue that simplified versions of maps should be developed in tandem with any hazard maps that contain technical complexities, not as a replacement, but as a mechanism to broaden awareness of hazards. We found that when scientists endeavor to design vivid and easy-to-understand maps, people in many professions find uses for them within their organization’s information products, resulting in extensive distribution.

Washington

Geologic models underpinning the 2024 U.S. Geological Survey assessment of undiscovered oil and gas resources in the Hosston and Travis Peak Formations of the onshore Gulf Coast region, U.S.A.

The Early Cretaceous (Berriasian–Hauterivian) Hosston Formation in Louisiana and eastward is time correlative to the Travis Peak Formation of Texas and southern Arkansas. The formation is a first-order clastic sequence with a regional carbonate transgressive surface as an upper contact. The Hosston and Travis Peak formations contain conventional natural gas and oil accumulations that have been produced for nearly a century. These mature reservoirs contain terrigenous fluvial-deltaic, shore-zone, and paralic deposits across the productive trend; organic-lean mudstone and siltstone lithologies are found outboard of the Lower Cretaceous shelf margin. Producing reservoirs exhibit normal pressure gradients from 0.43 to 0.55 psi/ft (9.7 to 12.4 kpa/m), depths from 4000 to over 20,000 ft (1220 to 6100 m), and temperatures from 150 to 385°F (65 to 196°C). Wells are primarily vertical completions. The number of new field wildcats has been declining since the late 1990s. This paper presents comprehensive geologic models, which include lithofacies maps, structure and isopach maps, burial history models, regional seismic interpretations, and events charts that underpin the recently completed U.S. Geological Survey assessment of undiscovered, technically recoverable hydrocarbons within the Hosston and Travis Peak formations. This study also provides geographic and stratigraphic distributions of Hosston–Travis Peak reservoir properties, including geopressure, reservoir temperature, porosity, permeability, API gravity, and gas-oil ratios. Results indicate estimated undiscovered, technically recoverable mean resources of 28 million barrels of oil and 35.8 trillion cubic ft of gas in conventional and continuous accumulations within the Lower Cretaceous Hosston and Travis Peak formations of the onshore U.S. Gulf Coast region. Quantitative assessment results are detailed in U.S. Geological Survey Fact Sheet 2025–3021 and associated Data Release.

GCAGS Journal

Remote sensing-based actual evapotranspiration assessment in a data-scarce area of Brazil: A case study of the Urucuia Aquifer System

The large groundwater reserves of the Urucuia Aquifer System (UAS) enabled agricultural development and economic growth in the western Bahia State, in northeastern Brazil. Over the last several years, concern has grown around the aquifer’s diminishing water levels, and water balance (WB) studies are in demand. Considering the lack of measured actual evapotranspiration (ET a ), a major component of the water cycle, this work uses the Operational Simplified Surface Energy Balance (SSEBop) model to estimate ET a , and compares it to basin-scale estimates from the Soil Moisture Accounting Procedure (SMAP) monthly model and from an annual WB closure method, based on gridded meteorological data and the Gravity Recovery and Climate Experiment (GRACE) product. Additionally, a comparative assessment of different versions of the SSEBop parameterization was performed. Moderate Resolution Imaging Spectroradiometer (MODIS) imagery was used to implement eight different versions of the SSEBop algorithm over the UAS between 2000 and 2013. SSEBop and SMAP ET a yielded similar seasonal patterns, with correlation coefficient (r) up to 0.65, mean difference (MD) of 0.8 mm/month and mean absolute difference (MAD) of 18.5 mm/month. Comparison of SSEBop annual ET a estimates to annual SMAP and WB closure estimates yielded low MD (12.1 and −7.3 mm/year, respectively) and MAD (82.5 and 82.8 mm/year, respectively), but also low r values (0.00 and 0.37, respectively). The comparison of the different SSEBop versions indicated the need to incorporate a calibration step of the aerodynamic heat resistance (r ah ) parameter. SSEBop results were also used for land cover and drought monitoring. Analysis indicates that agriculture, associated with an increasing trend of atmospheric evaporative demand, is responsible for the decrease in groundwater levels and streamflow in the studied time period.

Urucuia Aquifer System

Framework for mapping liquefaction hazard–Targeted design ground motions

Liquefaction-induced ground failure poses substantial challenges to geotechnical earthquake engineering design. Current approaches for designing against liquefaction hazards, as specified in most seismic provisions, focus on estimating a liquefaction factor of safety ( 𝐹⁢𝑆𝐿 ) and typically characterize earthquake loading using design parameters based on probabilistic or deterministic ground motion levels. Because 𝐹⁢𝑆𝐿 is estimated deterministically, this basis of design neglects considerable uncertainties for estimating liquefaction triggering and its consequences and results in a lack of liquefaction-specific design criteria, particularly as structural design has advanced toward risk-targeted performance objectives. This study presents a framework for developing liquefaction-targeted design criteria based on a minimum acceptable return period of liquefaction, informed by probabilistic liquefaction hazard analysis (PLHA). PLHA quantifies annualized rates of liquefaction by considering contributions from (1) the full ground-motion probability space, and (2) uncertainties in liquefaction triggering using probabilistic models. PLHA is used in this study to characterize the current, effective return periods of 𝐹⁢𝑆𝐿 ( 𝑇𝑅,𝐹⁢𝑆 ) obtained from conventional liquefaction hazard analysis (CLHA) using uniform-hazard ground motions. 𝑇𝑅,𝐹⁢𝑆 is evaluated in a parametric study of nearly 100 sites throughout the conterminous United States. The results indicate large geographic variations in acceptable liquefaction hazard levels, with implied 𝑇𝑅,𝐹⁢𝑆 ranging between approximately 1,000 to 3,000 years. To address these inconsistencies without the computational demands of full PLHA, a framework is proposed for developing a liquefaction-targeted design peak ground acceleration, 𝑃⁢𝐺⁢𝐴𝐿 , for use in liquefaction models that result in consistent liquefaction design levels across all geographic locations. The mapped 𝑃⁢𝐺⁢𝐴𝐿 is shown to be somewhat sensitive to site-specific properties, and adjustment factors are developed and presented. The proposed 𝑃⁢𝐺⁢𝐴𝐿 mapping procedure produces 𝐹⁢𝑆𝐿 estimates that are consistent with those obtained from full PLHA at a target 𝑇𝑅,𝐹⁢𝑆 , providing a promising roadmap to incorporating PLHA concepts into current liquefaction design methods.

Journal of Geotechnical and Geoenvironmental Engin

Nonstationary demographic state-space models using unreplicated counts for species undergoing environmental stressors

A fundamental task in ecological statistics is to estimate abundance and growth rate distributions from wildlife monitoring data to inform conservation management. Modeling time series of wildlife populations presents a number of challenges from both statistical and ecological perspectives, including discreteness; lack of replication; nonstationarity; and observation, demographic, and other phenomenological processes. Nonstationary dynamics are often exhibited by populations undergoing environmental stressors. Models must account for these characteristics to produce reliable estimates of abundance and trends, yet estimation can be challenging with unreplicated data. We propose nonstationary demographic state-space models using unreplicated counts for populations undergoing environmental stressors. A reduced growth rate model matches the complexity of the unreplicated count data, and a fecundity bound on growth rate distributions allows the separation of processes affecting growth rates like environmental stressors from those affecting abundance external to growth rates like migration. NDSSMs allow for the embedding of nonstationary model components, and we explore the use of changepoints, volatility clustering, and migration processes. We apply the proposed nonstationary models in case studies of herons affected by predator/competitor reestablishment and three bat species affected by a fungal pathogen causing white-nose syndrome. Nonstationary models outperform stationary models and generalized linear mixed effects models according to model scoring and visual inspection of predictions, and provide estimates more consistent with published values. Incorporating migration improves model fit universally, even with approximate one-way immigration, most likely because populations are extirpated, recolonized, and increase multiple-fold over the upper bound set by species fecundity. In addition, estimates of the timing and severity of the environmental stressor differed for models with migration. Including nonstationary and demographic components in a fecundity-bounded growth rate model improves inference and benefits interpretability of hyperparameters. In turn, this adjusts uncertainties in predictions of abundance and growth rates over time, providing the ingredients needed for informed conservation analysis and for directing future monitoring of at-risk species.

Journal of Agricultural, Biological and Environmen

Groundwater drought in the United States: Spatial and temporal variability

Many communities and ecosystems in the United States that are dependent on groundwater are potentially adversely affected by groundwater drought. We computed yearly groundwater-drought metrics and mean groundwater levels at well locations across the conterminous United States (CONUS), using data from wells and remotely sensed and modeled Gravity Recovery and Climate Experiment Drought Monitor Data Assimilation (GRACE-DADM). We also modeled the probability of low or high human impact at each well location. The spatial distribution of groundwater-drought duration and severity from 2001 to 2020 for 1,510 wells shows longer maximum duration and higher maximum severity events in drier regions like the Southwest than in wetter regions like the Northeast. Based on 613 wells in CONUS from 1981 to 2020, there are many significant decreases in drought duration and severity in the Northeast and many significant increases in annual-mean groundwater levels. In contrast, there are many significant increases in drought metrics and decreases in mean water levels in parts of the Southeast. There are major differences in trends from 2001 to 2020 between well-based and GRACE-DADM-based groundwater metrics in some CONUS regions and a very low correlation between trends at individual locations across CONUS. A potential reason for this disparity is the low GRACE-DADM resolution (∼12 km) and the potential for a large amount of groundwater variation at the local scale. Also, GRACE-DADM represents shallow, unconfined aquifers which may not match the screened interval of the monitoring wells we evaluated. Large spatial gaps in long-term, high frequency, and quality-assured groundwater-well monitoring data present a challenge for understanding groundwater-drought variability across CONUS. Remote sensing tools such as GRACE can help but cannot fully replace well monitoring, as highlighted by our study results. Substantially more long-term monitoring wells would more accurately represent groundwater-drought trends and spatial variability across CONUS, particularly in western regions.

conterminous United States

Groundwater quality near an oil field in a stream-dominated recharge setting, California, USA

Alluvial valley aquifers are important sources of water supply in many areas but effects of co-located oil and gas development on these resources have not been widely reported, especially in settings where recharge is dominated by stream infiltration. Interpreting the presence of geochemical indicators in the context of hydrology, geology, and other factors provides a more complete understanding of the relations between groundwater and sources of oil-field fluids and aids in identifying risks associated with oil and gas development. Groundwater and Salinas River water samples were collected in an alluvial valley near the San Ardo Oil Field in Monterey County, California and analyzed for a wide range of dissolved chemical, gas, and isotopic constituents to determine if oil-field fluids (water and gas from oil-producing and non-producing zones) have mixed with fresh groundwater used for supply. Hydraulic gradients, age-dating tracers, and other geochemical indicators show that recharge from the Salinas River has the potential to dilute oil-field fluids that might migrate or seep into the aquifer. Groundwater and Salinas River water collected downgradient of the San Ardo Oil Field showed little or no evidence of mixing with oil-field fluids. Some samples within the oil field contained trace amounts of hydrocarbons or elevated temperatures, indicating that any potential effects from oil-field activities are minor or have been diluted by recharge from the Salinas River. The two samples with the most geochemical evidence of potential mixing with oil-field fluids (SP-18 and GW-17) were collected west of or along the Los Lobos fault, where naturally occurring hydrocarbons are near the land surface. Those samples are also near active or inactive oil-field wells, and so anthropogenic activities and pathways cannot be ruled out as a cause of trace detections of hydrocarbons and elevated temperatures in the aquifer.

California

Hydrogeology, groundwater salinity distributions, and assessment of the effect of oil-production activities on groundwater in the Midway Valley area, western Kern County, San Joaquin Valley, California

This study seeks to determine the effects of oil field produced water disposal operations and well mechanical integrity issues on groundwater quality in oil fields in the southwest San Joaquin Valley, California. Whereas previous studies used groundwater wells to study shallow aquifers outside the oil fields, this study demonstrates that future approaches may use oil well geophysical logs to map groundwater head gradients, create salinity profiles and document changes in salinity over time in oil field areas with sparse groundwater well data and at depths greater than 330 m. We also incorporate an analysis of well histories to determine potential effects of compromised wellbore seals on changes in aquifer quality that cannot be explained by water disposal practices. Water quality in the aquifers is naturally brackish across most of the area, with better quality groundwater occurring in the eastern part. Geophysical logs are used to determine salinity variations within aquifers including the depth at which TDS exceeds 10,000 mg/L. This depth ranges from 366 m in the northwest to approximately 1,500 m in the southeast. Oil well porosity logs are used to determine water table elevations. These logs indicate the water table slopes south-southeast, showing the predominant groundwater flow direction is from oil field disposal areas toward better quality groundwater east of the oil fields. Geophysical logs show formation resistivity near some disposal facilities has decreased over time, indicating the salinity of the aquifer has increased due to disposal of saline produced water in injection wells and ponds. Oil well history analysis suggests that increased salinity over time in water-saturated sand intervals >1.5 km from disposal facilities may be caused by mechanical failures and/or incomplete borehole seals in poorly constructed or abandoned wellbores prevalent throughout the study area—particularly wells drilled prior to 1930.

California

Near-real-time earthquake-induced fatality estimation using crowdsourced data and few-shot large-language models

When a damaging earthquake occurs, immediate information about casualties (e.g., fatalities and injuries) is critical for time-sensitive decision-making by emergency response and aid agencies in the first hours and days. Systems such as the Prompt Assessment of Global Earthquakes for Response (PAGER) by the U.S. Geological Survey (USGS) were developed to provide a forecast of such impacts within about 30 min of any significant earthquake globally. However, existing disaster-induced human loss estimation systems often rely on early casualty reports manually retrieved from global traditional media, which are labor-intensive, time-consuming, and have significant time latencies. Recent approaches use keyword matching and topic modeling to identify human casualty-relevant information from social media but tend to be error-prone when dealing with complex semantics in multi-lingual text data and parsing dynamically changing and conflicting human death and injury numbers shared by various unvetted sources in social media platforms. In this work, we introduce an end-to-end framework to significantly improve the timeliness and accuracy of global earthquake-induced human loss forecasting using multi-lingual, crowdsourced social media. Our framework integrates (i) a hierarchical casualty extraction model built upon large language models, prompt design, and few-shot learning to retrieve quantitative human loss claims from social media, (ii) a physical constraint-aware, dynamic-truth discovery model that discovers the truthful human loss from massive noisy and potentially conflicting human loss claims, and (iii) a Bayesian updating loss projection model that dynamically updates the final loss estimation using discovered truths. We test the framework in real-time on a series of global earthquake events in 2021 and 2022 and show that our framework effectively automates the retrieval of casualty information faster but with comparable accuracy to those now retrieved manually by the USGS. The code associated with this work is made available at: https://github.com/SusuXu-s-Lab/Hierarchical-Earthquake-Casualty-Information-Retrieval

International Journal of Disaster Risk Reduction

Site-specific amplifications in Northwestern Turkiye: A generic approach

In this study, we derive generic site amplification functions applicable to Northwestern Türkiye and follow guidance on site classifications established by the United States National Earthquake Hazards Reduction Program (NEHRP). We employ the one-dimensional (1-D) equivalent linear ground response analysis method and focus on recordings from a select suite of free-field strong motion (SM) stations. These particular SM stations are associated with a comprehensive geotechnical site conditions dataset comprising 76 shear-wave velocity profiles. Despite their varying resolutions and depths, this diversity allows for a more representative analysis across different site conditions, enhancing the robustness of our findings. For analyses, we utilize a robust set of global ground motion records, selected from both within and outside of Türkiye, to serve as strong and weak input bedrock motions. Site amplification is determined by propagating these bedrock records through 76 site-specific Afet ve Acil Durum Yönetimi Başkanlığı (AFAD) station profiles and calculating the spectral acceleration ratio between the ground surface and the input motion. Our analyses reveal substantial disparities between the amplification functions derived from 1-D site response analyses using strong and weak input motions. These disparities are central to our analysis and inform the subsequent comparison with site amplification functions reported in the literature. We compare the generic site amplification functions derived in this study with those reported in the literature for regions with similar geological and seismic conditions to Northwestern Türkiye. For example, site amplification functions for NEHRP Site Classes C and D have been documented for Greece and the United States utilizing frequency-dependent methods such as the quarter-wavelength approximation. Our findings reveal that the generic site amplification functions derived in this study exhibit differences in peak amplitudes and predominant frequencies compared to those in the literature, reflecting regional variations in geotechnical and seismic properties. This study represents an initial effort to formulate generic site amplification functions for Türkiye, with a particular emphasis on the Northwestern region. A thorough literature review indicated no prior studies have proposed such functions specifically for this area.

Northwestern Turkiye

Shallow differentiation of primitive arc magmas at the Jurassic Emigrant Gap mafic complex, Sierra Nevada, California

The Emigrant Gap composite pluton exposes ultramafic to silicic intrusive rocks that preserve the chemical evolution of primitive mafic arc magmas and their open-system interactions in the upper crust during mid-Jurassic growth of the Sierra Nevada batholith (California). We present field and petrographic observations and mineral and whole-rock chemistry of the ~35-km 2 ultramafic to dioritic Emigrant Gap mafic complex and an adjacent penecontemporaneous ~90-km 2 granodiorite that together make up the composite pluton. In the Emigrant Gap mafic complex, four roughly central masses of dunite, wehrlite, and olivine clinopyroxenite are surrounded by weakly layered gabbronorite and non-layered diorite. The ultramafic rocks are cumulates formed from near-liquidus minerals of primitive arc magmas that accumulated in steep feeder zones with substantial modification by melt–mush reaction as primitive liquids repeatedly transited the mush-filled conduits. The dominant gabbronoritic rocks are the variably accumulative products of more advanced crystallization–differentiation of arc tholeiitic basalts and basaltic andesites. The adjacent granodiorite intrusion originated separately and preserves field and geochemical evidence for assimilation of metasedimentary rocks. Open-system hybridization between the gabbronoritic mushes and the granodioritic magma produced an intervening body of two-pyroxene diorite. We infer that the ultramafic rocks and gabbronorite of the Emigrant Gap mafic complex crystallized from near-primitive arc basaltic to basaltic andesitic magmas at ~0.15–0.3 GPa, with estimated f O 2 of ≥FMQ +1 and dissolved H 2 O concentrations of only ~0.5–2 wt %. Notably, the Emigrant Gap composite pluton is distinct from other Mesozoic plutons in the Sierra Nevada batholith because of (1) its abundance of mafic and ultramafic rocks that crystallized from relatively primitive mafic melts and (2) the low inferred H 2 O concentrations of its parental magmas, indicated by a near absence of igneous amphibole and by the intermediate rather than calcic compositions of plagioclase. A Jurassic regional extension event probably accounts for the formation of relatively dry primitive arc magmas, as well as for their ascending to the upper crust.

California

Relating systematic molecular and textural properties of graptolite pyrolyzed via gold tube hydrous pyrolysis: Implications for thermal proxies in lower Paleozoic marine shales

A series of gold tube pyrolysis experiments (72 h, 300–550 °C, 50 MPa) conducted on a graptolite-rich lower Paleozoic marine shale generated pyrolysis residues for a comprehensive evaluation of the molecular and structural variability of three types of graptolite periderm. Organic petrology, Raman spectroscopy, and field emission scanning electron microscopy (FE-SEM) with energy dispersive spectroscopy (EDS) were combined to evaluate the thermal evolution process. The three types of graptolite periderm, namely granular, non-granular, and nodular graptolite, were analyzed by Raman spectroscopy wherein point measurements were obtained after the maceral was identified and the location verified by organic petrology. Distinct thermal evolution pathways among non-granular, granular, and nodular graptolite periderms were recorded. The evolution patterns of the Raman parameters, particularly D1 and G bands, highlight the differences in geochemical composition of the graptolite periderm types and the alteration of molecular structure with increasing thermal maturity. Raman parameters D1 (position of the D1 peak), G-FWHM (full width at half maximum of the G peak), and ratios D1-FWHM/G-FWHM (full width at half maximum of the D1 peak ratioed to G-FWHM) and A D1 /A G (ratio of D1 and G peak intensities) showed effectiveness in assessing thermal maturity. Bireflectance with increasing gold tube pyrolysis temperature followed a hierarchy: non-granular > granular > nodular, reflecting different molecular alignment intensities. Qualitative FE-SEM evaluation showed that fine-grained mineral inclusions (primarily Fe-sulfide as determined via EDS) were associated with the graptolite populations, with granular graptolite containing greater amounts of coarser-grained (e.g., ∼300–1400 nm) mineral inclusions relative to non-granular and nodular graptolite, which contain finer-grained (e.g., ∼100–200 nm) inclusions difficult to resolve with optical microscopy. These findings are investigated to highlight the mechanisms that drive organic matter evolution within graptolite during thermal maturation, as well as to explore some of the limitations of using spectroscopic parameters as thermal maturity proxies.

International Journal of Coal Geology

Forecasting water levels using the ConvLSTM algorithm in the Everglades, USA

Forecasting water levels in complex ecosystems like wetlands can support effective water resource management, ecological conservation, and understanding surface and groundwater hydrology. Predictive models can be used to simulate the complex interactions among natural processes, hydrometeorological factors, and human activities. The Greater Everglades in the USA is a well-known example of an ecosystem where complexity has motivated adoption of machine learning algorithms in water level prediction studies. This paper aims to contribute to extending existing machine learning algorithms by integrating spatiotemporal data with deep-learning algorithms in the forecasting process. In this study, a deep-learning model is developed to predict water levels on a regional scale, covering a large area of approximately 9,138 square kilometers in the Everglades ecosystem. This model has the architecture of Convolutional Long Short-Term Memory which can deal with spatiotemporal data by capturing both spatial and temporal dependencies in the training data. The forecasting capabilities of this model (referred to as the global model) are assessed by comparing the global model to two Artificial Neural Networks developed at two different gaging stations, referred to here as local models. One local model is developed at a gaging station directly influenced by nearby water control structures, whereas the other is developed at a gaging station located farther away from these structures. By leveraging data from the Everglades Depth Estimation Network spanning from January 2002 to May 2023, the global and local models were trained to forecast water levels with a two-day lead time. Our findings suggest that both the global and local models perform with approximately the same level of accuracy, with Mean Absolute Relative Error values ranging from 0.38% to 1.4% at the selected stations. The developed global model has demonstrated strong potential as a standalone forecasting tool for the entire study area in the Everglades and could eliminate the need for developing multiple local models. This finding also highlights how machine learning can capture complex spatial and temporal relationships to generate accurate water level predictions on a regional scale.

Florida