United States Geological Survey Research Articles

Exploring the utility of the Enhanced Vegetation Index as rainfall and agricultural proxy in a Caribbean case study event

Highly fragile small island states experience disproportionate climate impacts given their limited capacity to implement cost‐effective tools for detecting emerging signals of drying conditions and monitoring systems for sensitive sectors such as agriculture, especially for uncertain, ‘creeping’ events such as droughts. Despite the existence of open‐source Google Earth Engine datasets, untapped potential remains for their full deployment in disaster management infrastructure. Given this gap, this paper explores the utility of the Enhanced Vegetation Index (EVI) for detecting spatio‐temporal variations of Mid‐Summer Drought (MSD) impacts on vegetation in the small island of Jamaica, with emphasis on major historical drought events. Geospatial analyses of EVI datasets from the Terra Moderate‐Resolution Imaging Spectroradiometer (MODIS) between 2000−2015 archived by the United States Geological Survey (USGS), were computed, and validated by station‐based precipitation and production data for selected parishes for historical case study MSD events. Results revealed highly asymmetrical drought impacts, with Jamaica's agriculturally intense Southern coastline displaying the most stressed vegetation (EVI < 0.5). North‐Western and North‐Eastern regions had the healthiest vegetation during the MSD (EVI > 0.6). A ‘fair’ to ‘moderate’ concurrent correlation was found between EVI and precipitation (R > 0.6), with lower correlations vis‐a‐vis agricultural production (R = 0.2–0.4). The results provide evidence of EVI's utility as a drought monitoring tool in a small island context.

Land use and land cover changes, and woody vegetation status of the Tsimur Gebriel Monastery in Northern Ethiopia

Ethiopian Orthodox churches are significant habitats for endemic and threatened plant species, yet their vegetation status and the land use systems impacting them, are little known. Therefore, this study assessed the land use and land cover changes (LULCC) within a 3 kilometer buffer area and the woody vegetation status of the Tsimur Gebriel Monastery in the Tigray region, Northern Ethiopia. The United States Geological Survey's multi-dated (1986, 1999, and 2018) Landsat imagery was used for LULCC analysis. A supervised classification technique was employed for image classification using a maximum likelihood algorithm. Systematic sampling techniques were used to collect vegetation data (tree species, height, and DBH), using 20 sample plots (20 x 20 m) distanced 100 m apart. The results highlighted that among the five identified LULCC types in the buffer zone of the monastery, the farmland area has expanded from 56 to 78% at the expense of shrublands between 1986 and 2018. At the monastery, 19 woody tree species from 13 families were identified, with an evenness of 0.5 and a Shannon diversity index of 2.4. The stem density was 336 stems per hectare, and the forest cover was approximately 65%. Olea europaea was the dominant tree species, while Juniperus procera showed a lack of regeneration at the monastery. Despite the fair natural regeneration, the monastery exhibited lower species diversity, richness, and evenness. However, the monastery remains an important habitat for rare and threatened tree species and may supply seeds for the restoration of degraded lands. Therefore, establishing exclosures in the buffer zone, strengthening stone walls and enrichment planting of degraded tree species should be implemented to ensure the sustainable conservation of valuable tree species.

The Ojai California Earthquake of 20 August 2023: Earthquake Early Warning Performance and Alert Recipient Response in the Mw 5.1 Event

Abstract A magnitude 5.1 earthquake in California rarely generates more than momentary notice—a headline in local newspapers and a mention with footage on the evening news—then fades into obscurity for most people. But this earthquake, which occurred near the city of Ojai, is important for seismologists, social scientists, emergency managers, policymakers, and others who are engaged in implementing and improving earthquake early warning (EEW) technology and in assessing its value in public warnings. In this earthquake, ShakeAlert, the EEW system for the West Coast of the United States operated by the U.S. Geological Survey (USGS), was publicly activated and, for the first time, a substantial number of those who received alerts provided feedback on various aspects of the alerts they received. To capture data related to public attitudes and assessments regarding this and future alerts, a supplemental questionnaire was developed and associated with the “Did You Feel It?” (DYFI) earthquake reporting system, also operated by the USGS. The DYFI system received over 14,000 felt reports; 2490 of these were by people who received or expected to receive an alert before the onset of earthquake motion at their locations. This article analyzes the aggregate results of these EEW user reports, touching on the respondent’s situation upon receiving the alert, characteristics of the alert received, and, perhaps, most importantly, how the alert recipient responded if received before feeling earthquake motion. The new DYFI EEW supplemental questionnaire also inquired about respondent views of alert usefulness and preferences in future alerts. Our report provides a first glimpse of a range of behaviors, attitudes, and assessments by users of the recently implemented EEW system for the U.S. West Coast.

A note on the seismicity of Sumatra, western Sunda Arc, Indonesia, in relation to the potential for back-arc thrusting

The existence of back-arc thrust faults along the eastern part of the Sunda Arc, ranging westwards from Flores to the western tip of Java, has been recognised for decades. In contrast, it is still unknown whether such back-arc thrust faults exist in Sumatra, which is located in the western part of the Sunda Arc. To investigate the possible existence of back-arc thrusts in Sumatra, we examine regional earthquake data reported by the Agency for Meteorology, Climatology and Geophysics of Indonesia, as well as global earthquake data reported by the International Seismological Centre and the United States Geological Survey. It appears that back-arc thrusts in the study area are not extensively developed, unlike in the eastern Sunda Arc, which may be caused by oblique subduction beneath the Sumatran forearc. The stress associated with the trench-parallel component of subduction is largely accommodated by the ~ 1650-km-long dextral strike-slip fault zone of the Great Sumatran Fault. The seismicity data from various sources do, however, show that there is a dipping seismogenic zone in several parts of the back-arc region of Sumatra, in the opposite direction to the NNE subduction of the Indo-Australian plate. This new observation may be related to the presence of spatially intermittent back-arc thrust faults in the study area, which may need to be taken into account when improving Indonesia's national earthquake hazard maps.

Water quality fluctuations prediction and Debi estimation based on stochastic optimized weighted ensemble learning machine

Today, humanity faces the complex phenomenon of global development. Problems such as limited resources, financial constraints, time constraints, and the involved nature of issues surrounding water resources management pose challenges to effectively monitor water resources issue parameter management (WRIPM). Nevertheless, the importance of this issue cannot be ignored. The focus of this study is on WRIPM issues, and new machine learning models are utilized to investigate and estimate fluctuations in WRIPM parameters. The initial dataset utilized in this study was sourced from the US Geological Survey, specifically sampling stations information from the South Platte River in the United States. Two new models were developed: the Ensemble Bagged Machine (EBM) and the Stochastic Weighted Ensemble Bagged Machine (SWEBM), which further optimized the characteristics of the EBM model using Bayesian Optimization (BN). These models were employed to simulate Dissolved Oxygen (DO), Electrical Conductivity (EC), Power of hydrogen (pH), and river flow rate (Debi) parameters. Additionally, the research employed various scenarios for evaluation and validation. Uncertainties were calculated using the Wilson analysis. The results demonstrated the superiority of the SWEBM in all modeling aspects, yielding the best indices, namely, R2, MAE, and RMSE, at 0.984, 0.0259, and 0.0394, respectively. Performing an receiver operating characteristic analysis revealed that the area over the RROC curve value for the superior model was 36.16, demonstrating excellent performance in modeling the pH parameter. The WM analysis method confirmed that the SWEBM model was the most trustworthy, delivering the greatest precision and best modeling for the pH parameter (WOUB=0.00683, MOPE=0.00138, and STD=0.1665) even though it was slightly overestimated. The probability density function analysis revealed that the SWEBM was the best model. While other models had results that were relatively close. This research represents valuable findings that can be shared with stakeholders, including experts, scholars, and organizations responsible for overseeing water quality administration.

Mapping Lava Flows on Venus Using SAR and InSAR: Hawaiʻi Case Study

AbstractWe explore the potential for repeat‐pass SAR Interferometry (InSAR) correlation to track volcanic activity on Venus' surface motivated by future SAR missions to Earth's sister planet. We use Hawai'i as a natural laboratory to test whether InSAR can detect lava flows assuming orbital and instrument parameters similar to that of a Venus mission. Hawai'i was chosen because lava flows are frequent, and well documented by the United States Geological Survey, and because Hawai'i is a SAR supersite, where space agencies have offered open radar data sets for analysis. These data sets have different wavelengths (L, C, and X bands), bandwidths, polarizations, look angles, and a variety of orbital baselines, giving opportunity to assess the suitability of parameters for detecting lava flows. We analyze data from ALOS‐2 (L‐band), Sentinel‐1 (C‐band), and COSMO‐SkyMed (X‐band) spanning 2018 and 2022. We perform SAR amplitude and InSAR correlation analysis over temporal baselines and perpendicular baselines similar to those of a Venus mission. Fresh lava flows create a sharp, noticeable decrease in InSAR correlation that persists indefinitely for images spanning the event. The same lava flows are not always visible in the corresponding amplitude images. Moreover, noticeable decorrelation persists in image pairs acquired months after the events due to post‐emplacement contraction of flows. Post‐emplacement effects are hypothesized to last longer on the Venusian surface, increasing the likelihood of detecting Venus lava flows using InSAR. We argue for further focus on repeat‐pass InSAR capabilities in upcoming Venus missions, to detect and quantify volcanic activity on Earth's hotter twin.

Decadal changes (1980-2021) of shoreline and mangrove cover in Sundarban Delta, India using remote sensing and GIS

Abstract Being situated in the estuary of the flood-dominated Hooghly River system, the macrotidal Indian Sundarban Delta (ISD) has become one of the most complex, dynamic and rapidly changing landforms on the earth’s surface. To study horizontal areal shifting of shoreline and its impact on mangrove-cover in the region, United State Geological Survey (USGS)-satellite data of 1980, 1990, 2000, 2010 and 2021 were used. Remote sensing and GIS techniques were employed in the investigation. Simultaneous prograding and retrograding shoreline shifting was distinguished almost in all the parts, though sediment-starved eastern and macrotidally more active southern lobes experienced dominantly retreating shift, and sediment-engorged western lobe demonstrated to be more dynamic. Net areal change over north-south tracks followed the trend of decreasing accretion to increasing erosion while going from west to east, whereas that over west-east tracks followed the trend of exponentially increasing erosion while going from north to south. Overall accretion of ∼91 sq. km in the ISD accounted for augmentation of sparse vegetation of ∼13 sq. km, whereas, ∼243 sq. km erosion called for depletion of sparse & moderate vegetation of ∼18 & ∼174 sq. km respectively over the 41-year period. Various oceanographic and riparian forces and actions, episodic natural events etc. vis-a-vis several anthropogenic interventions— all together contributed to such changes. The findings may help the coastal environmentalists, professionals, planners, decision-makers and implementers in formulating and taking up of suitable strategic measures for integrated and effective coastal zone management in this estuarine wetland-forest.

Advancing freshwater science with sensor data collected by community scientists

Autonomous sensor networks providing real‐time data are growing in popularity with community scientists due to instant availability of high‐frequency data. What role does this monitoring play in watershed assessment alongside agency‐run monitoring programs? How accessible, interoperable, and reusable are the data for other researchers? We compared a community science‐led stream monitoring network—EnviroDIY—in the Delaware River Basin, in which more than 50 watershed organizations have deployed more than 100 stations monitoring temperature, electric conductivity, depth, and sometimes turbidity, with the Basin's US Geological Survey (USGS) stream gauge network. The EnviroDIY network (n = 124) complemented the USGS network (n = 102) by monitoring sites with different watershed sizes and land‐use distributions. Although data were accessible and interoperable using a web data portal, community scientists had difficulty sharing metadata that would enable data reuse outside this project and they required support analyzing these large datasets to understand threats to watershed conditions. We address those needs here with a conceptual framework for interpreting data and communicating results.

Printing Ochre

The discipline of geology was relatively new at the start of the United States Geological Survey (USGS) in the late 1800s, but through the organisation of an efficient government bureau and the voice of its printed page, it became a dominant perspective in the way generations of citizens relate to and view the natural world, human and nonhuman, life and nonlife. I choose to position my press in direct opposition to the maintenance of these dualisms. I will argue the critical role of print in facilitating USGS domination of terrestrial beings in a practical sense, yet beyond the methods and reach of publication, I believe the products of the USGS mediate our understanding of and relation to these beings. Instead, design practices can be directed towards changing attitudes and understanding between humans and nonhumans. Monika Bakke argues for the importance of artistic endeavours in addressing our collective futurity: Drawing on both life’s mineral origins and its key role in shaping mineral species, artists are turning to technoscience in order to develop, outside expert circles, better understanding of physical, chemical, and biological environments, not just of the geological past but also those to come in the future. ... Yet, their methodologies are specific to art which offers creative ontological and ethical contributions to public debate. (2017, p. 43) I am developing a design research paradigm relating to ochre as an epistemic tool for human and nonhuman intersubjectivity and ontological reconciliation or reunification between life and nonlife. I model my practice after a simplification of the USGS: to survey (observe, describe, collect) and to report (archive, document, record), with some critical variance in method and outcomes.

Particulate matter (pm10) monitoring in the United Arab Emirates using a satellite remote sensing based model

Particulate matter (PM) is one of the major factors causing air pollution, which is considered a concern for human health. Hence, measuring and monitoring the concentrations of these particles is essential. In this study, the main objective is to develop a remote sensing based PM10 monitoring model for the United Arab Emirates (UAE) using Landsat 8 imagery. Landsat 8 images acquired during the four-year period from 2016 to 2022 were obtained and used along with PM10 data collected at 41 ground monitoring stations corresponding to the acquisition of the satellite data (data from 30 stations used for model development 11 stations were used for model testing). The Landsat 8 data was obtained from the United States Geological Survey (USGS) Core Science Systems in the form of Digital Numbers (DNs). The DNs of the four optical bands of Landsat 8 were then converted to top of the atmosphere reflectance (TOA) through radiometric processing, and then used to estimate the Aerosol Optical Thickness. A spectral PM10 model was then developed through regression analysis, correlating AOT to PM10 values obtained at the ground stations. The model provided an R-squared value of 65% and a Root Mean Square Error (RMSE) of 12.55 µg/m3. The results suggest that the developed model is robust in estimating PM10 values and can therefore be used for satellite-based monitoring at any location in the UAE.

Earthquake-triggered ground-failure inventory associated with the M7.1 2018 Southcentral Alaska earthquake

The 30 November 2018, magnitude (Mw) 7.1 earthquake in Southcentral Alaska triggered substantial landslides, liquefaction, and ground cracking throughout the region, resulting in widespread geotechnical damage to buildings and infrastructure. Despite a challenging reconnaissance and remote-sensing environment, we constructed a detailed digital inventory of ground failure associated with the event from several sources. Sources included information derived from remotely sensed data, and data compiled from literature, social media postings, and earthquake damage information compiled by local, state, and federal agencies. Each instance of ground failure within the inventory contains information on the location and type of observed ground failure, and the methods and data used to document the occurrence. Where high-quality data, such as LIDAR or satellite imagery, were available and showed the ground-failure instance clearly, the extent is mapped as a polygon or polyline. All other locations are mapped as points. There are a total of 886 ground-failure instances documented within the inventory (400 landslides, 286 liquefaction features, and 200 features unattributed to specific processes). A semi-quantitative confidence scheme is used to describe mapping certainty associated with each ground-failure feature. This inventory represents a relatively moderate ground-failure-triggering event that occurred in a subarctic environment. This data paper describes the content within the inventory, the inventory data collection procedures, and limitations of the data. Events of this type are not often documented in detail; thus, adding the inventory data to the US Geological Survey Open Repository of Earthquake-Triggered Ground-Failure Inventories further diversifies the datasets available to the scientific community to be used to better understand and model earthquake-triggered ground failure.

Wetland Changes and Ecosystem Services Valuation of Kapla Beel in Assam

Background: Wetlands are productive ecosystem with immense potentiality of providing various goods and services. But they are fast depleting due to various natural and anthropogenic causes. Kapla beel is a freshwater wetland located in Barpeta district in the lower Brahmaputra valley of Assam. Area of the Kapla beel has been decreasing over the years. This study shall make an attempt to analyse the causes of land use and land cover changes of Kapla beel of Assam and assess its ecosystem services value changes during the period 1990 to 2022. Methods: To assess the changes, two Landsat images for the year 1990 and 2022 of Kapla beel were taken from the United State Geological Survey (USGS) Earth Explorer. Land-use change analysis was assessed by comparing the areas occupied by each land use in each period using the ArcGIS software. The dynamicity index is used to calculate the rate of change in land cover. In order to assess the changes in the wetland ecosystem service value due to wetland changes, Benefit Transfer Method is used which involves transferring monetary values of ecosystem services from previous studies. Result: The valuation of ecosystem services underlines the fact that wetlands are highly productive and economically viable ecosystems. Accounting of ecosystem services provides information about the need for optimal decision -making towards judicious use of wetland resources for their sustenance.

Implementation and experience of using methods for analyzing the isotopic composition of Sm and Nd, Rb and Sr in rock samples at the Geoanalitik Center for Collective Use

Research subject. AGV-2 and BHVO-2 geochemical reference materials for studying the Sm, Nd and Rb, Sr isotope systems along with various rocks and mineral samples. Materials and Methods. An analysis of the isotopic composition of Sm, Nd and Rb, Sr was carried out using Neptune Plus and Triton Plus mass spectrometers. Aim. To implement analytical techniques for the isotopic composition of Sm and Nd, Rb, and Sr in various rock and mineral samples using two types of multicollector mass spectrometers – inductively coupled plasma NeptunePlus and thermal ionization TritonPlus (Thermo-Fisher), as well as a description of the procedure of processing experimental data and the experience in using techniques at the “Geoanalitik” shared research facilities of the IGG UB RAS for the period 2015-2023. Results. The analytical techniques implemented included (1) column chromatography using various ion-exchange resins, optimised for the ratio of labour costs/quality of analytical results; (2) the measurement of isotope ratios using two types of mass spectrometers; (3) the correction of mass bias of isotope ratios and the determination of Sm and Nd, Rb, and Sr concentrations by the isotope dilution method using 149Sm+150Nd and 85Rb+84Sr spikes. Testing of the techniques was carried out using the AGV-2 and BHVO-2 geochemical reference materials; their metrological characteristics were presented. When using TritonPlus, the reproducibility (BHVO-2, n=60) of measurements of 143Nd/144Nd, 147Sm/144Nd isotope ratios and Sm and Nd concentrations are ±0.000020, ±0.0004, ±1.3 and ±0.4, respectively; indicators of correctness of determining the ratios 143Nd/144Nd and 147Sm/144Nd – 0.001 and 0.25% and concentrations of Sm and Nd – 2%; the reproducibility (BHVO-2, n=63) of measurements of 87Sr/86Sr, 87Rb/86Sr isotope ratios and concentrations (Rb and Sr) are ±0.0025%, ±1.5%, ±2%, respectively. The uncertainty of a single measurement of the 143Nd/144Nd and 87Sr/86Sr isotope ratio, represented by the standard error of the average single measurement in the sample, does not exceed 0.0025%. Conclusions: the results obtained for the geochemical reference materials are in satisfactory agreement with those provided in the GeoReM database, as well as with the certified values provided by the United States Geological Survey (USGS). The described analytical techniques are used at the “Geoanalitik” shared research facilities of the IGG UB RAS to analyse various rock and mineral samples. The work presents a number of experimental results obtained, which are subsequently used in geochronological applications.

The 2023 US National Seismic Hazard Model: Subduction ground-motion models

The US Geological Survey National Seismic Hazard Models (NSHMs) are used to calculate earthquake ground-shaking intensities for design and rehabilitation of structures in the United States. The most recent 2014 and 2018 versions of the NSHM for the conterminous United States included major updates to ground-motion models (GMMs) for active and stable crustal tectonic settings; however, the subduction zone GMMs were largely unchanged. With the recent development of the next generation attenuation-subduction (NGA-Sub) GMMs, and recent progress in the utilization of “M9” Cascadia earthquake simulations, we now have access to improved models of ground shaking in the US subduction zones and the Seattle basin. The new NGA-Sub GMMs support multi-period response spectra calculations. They provide global models and regional terms specific to Cascadia and terms that account for deep-basin effects. This article focuses on the updates to subduction GMMs for implementation in the 2023 NSHM and compares them to the GMMs of previous NSHMs. Individual subduction GMMs, their weighted averages, and their impact on the estimated mean hazard relative to the 2018 NSHM are discussed. The updated logic trees include three of the new NGA-Sub GMMs and retain two older models to represent epistemic uncertainty in both the median and standard deviation of ground-shaking intensities at all periods of interest. Epistemic uncertainty is further represented by a three-point logic tree for the NGA-Sub median models. Finally, in the Seattle region, basin amplification factors are adjusted at long periods based on the state-of-the-art M9 Cascadia earthquake simulations. The new models increase the estimated mean hazard values at short periods and short source-to-site distances for interface earthquakes, but decrease them otherwise, relative to the 2018 NSHM. On softer soils, the new models cause decreases to the estimated mean hazard for long periods in the Puget Lowlands basin but increases within the deep Seattle portion of this basin for short periods relative to the 2018 NSHM.

Burden of malignant mesothelioma in China during 1990–2019 and the projections through 2029

ObjectiveTo provide the most up-to-date data on the burden of malignant mesothelioma (MM) and the projections through 2029 in China. MethodsData on patients diagnosed with MM from China during 1990–2019 were obtained from the Global Burden of Disease (GBD) 2019 database, including annual cases and deaths data and age-standardized rates of incidence, mortality, and disability-adjusted life-years (DALYs) associated with MM among different age groups. Temporal trends during 1990–2019 were analyzed by the Joinpoint regression models using 95% confidence interval (CI), while the projections through 2029 were calculated by the Bayesian age-period-cohort model. Data on the production and consumption of asbestos in China were obtained from the United States Geological Survey on Mineral Commodity Summaries during 1996–2023. ResultsWe observed a significant elevation in incident new cases and deaths over the last 3 decades, increasing from 1193 in 1990 to 2815 in 2019 for incident cases and from 1134 in 1990 to 2773 in 2019 for death cases. We found a roughly 6% increase in the proportion of incident cases for those aged >70 years (30% in 2019 versus 24% in 1990), while for the proportion of deaths similar elevation for those aged >70 years was found. Additionally, men had significantly higher DALYs due to MM across age groups compared with women. Asbestos consumption in China dramatically dropped since 2012 and reached the bottom in 2017 with 230 kilotons. By 2029, the projected age-standardized rate for incidence and mortality is expected to reach 1.2 per million for both. ConclusionWe found, for the first time using GBD data on the Chinese population, that the burden of MM has been significantly increasing in China over the last three decades and will continue to increase in the upcoming decade, suggesting an urgent need for a complete ban on chrysotile asbestos in China.

Tracing the contribution of cattle farms to methane emissions through bibliometric analyses

Methane contributes to global warming, and livestock is one of the sources of methane production. However, methane emission studies using bibliometric tools in livestock are lacking. Given the negative impact of climate change on the ecosystem and the rise in methane emissions, it is essential to conduct a bibliometrics study to provide an overview and research trends. We used the Bibliometrix package and VOSviewer to decipher bibliometric indices for methane emissions in cattle farms (MECF). Current dataset were collected from the Web of Science (Core Collection) database, and 8,998 publications were analyzed. The most co-occurring keywords scientists preferred were methane (1528), greenhouse gas (443), methane emissions (440), and cattle (369). Methane was the most frequently used keyword in the published scientific literature. Thematic evolution of research themes and trend results highlighted carbon dioxide, methane, dairy cattle, cattle, and risk factors during 1999-2017. Chinese Academy of Sciences ranked on top with 485 publications, followed by Agriculture & Agri-Food Canada, University of Colorado, National Oceanic and Atmospheric Administration, and Aarhus University. Chinese Academy of Sciences was also the most cited organization, followed by the University of Colorado, Agriculture & Agri-Food Canada, National Oceanic and Atmospheric Administration, and United States Geological Survey. Source analysis showed that the Science of the Total Environment was cited with the highest total link strength. “Science of the Total Environment” ranked first in source core 1 with 290 citation frequencies, followed by “Journal of Dairy Science” with 223 citation frequencies. Currently, no bibliometric study has been conducted on MECF, and to fill this knowledge gap, we carried out this study to highlight methane emissions in cattle farms, aiming at a climate change perspective. In this regard, we focused on the research productivity of countries authors, journals and institutions, co-occurrence of keywords, evolution of research trends, and collaborative networking. Based on relevance degree of centrality, methane emissions and greenhouse gases appeared as basic themes, cattle, and dairy cattle appeared as emerging/declining themes, whereas, methane, greenhouse gas and nitrous oxide appeared to fall amongst basic and motor themes. On the other hand, beef cattle, rumen and dairy cow seem to be between motor and niche themes, and risk factors lie in niche themes. The present bibliometric analysis provides research progress on methane emissions in cattle farms. Current findings may provide a framework for understanding research trends and themes in methane emissions in cattle farms (MECF) research.

County-Level Atrazine Use and Gastroschisis

The incidence of gastroschisis, a birth defect involving the herniation of the small bowel through the abdominal wall, has increased in the US since the 1960s. The pesticide atrazine is a hypothesized cause of gastroschisis; however, examination of the association between atrazine and gastroschisis has been limited. To evaluate national trends in gastroschisis incidence, maternal and infant characteristics associated with gastroschisis, and whether county-level atrazine use is associated with gastroschisis. This retrospective, repeated cross-sectional study examined birth certificate data of all live births in the US and data on atrazine use from the US Geological Survey from January 1, 2009, through December 31, 2019. The data analysis was performed between August 5, 2021, and May 26, 2023. County-level atrazine use. The primary outcome was gastroschisis incidence. Covariates included maternal age, race and ethnicity, body mass index (measured by weight in kilograms divided by height in meters squared), parity, insurance type, Chlamydia infection during pregnancy, smoking, and rurality. Mixed-effects logistic regression models (year fixed effects and county random effects) were constructed using different county-level atrazine exposure variables (1-, 5-, and 10-year means). Between 2009 and 2019, 39 282 566 live births were identified, with 10 527 infant diagnoses of gastroschisis. Infants with gastroschisis were more likely to have mothers who identified as non-Hispanic White (61% vs 54%; P < .001), had a lower body mass index (median [IQR], 23.4 [20.8-27.2] vs 25.4 [22.0-30.8]; P < .001), were more likely to be nulliparous (median [IQR], 0 [0-1] vs 1 [0-2]; P < .001), and were more commonly covered by Medicaid (63% vs 43%; P < .001). During the study period, the rate (per 1000 live births) of gastroschisis decreased from 0.31 (95% CI, 0.29-0.33) to 0.22 (95% CI, 0.21-0.24). The median (IQR) county-level atrazine use estimates were higher among infants with gastroschisis (1 year, 1389 [IQR, 198-10 162] vs 1023 [IQR, 167-6960] kg; 5 years, 1425 [IQR, 273-9895] vs 1057 [IQR, 199-6926] kg; 10 years, 1508 [IQR, 286-10 271] vs 1113 [IQR, 200-6650] kg; P < .001). In adjusted models, higher county levels of atrazine (each 100 000-kg increase) were associated with a higher incidence of gastroschisis (1 year: adjusted odds ratio [AOR], 1.12 [95% CI, 1.01-1.24]; 5 years: AOR, 1.15 [95% CI, 1.02-1.30]; 10 years: AOR, 1.21 [95% CI, 1.07-1.38]). In this cross-sectional study, higher county levels of atrazine were associated with infant diagnoses of gastroschisis. While atrazine is the second-most used herbicide in the US, numerous countries around the world have banned it out of concern for adverse effects on human health. These findings suggest that exploring alternatives to atrazine in the US may be warranted.

Impacts of Gorkha Earthquakes: A Comprehensive Study

Nepal is highly vulnerable to seismic activity. This review seeks to explore the impact of earthquakes on human populations in terms of casualties and injuries, as well as to pinpoint the risk factors associated with these outcomes. An earthquake measuring 7.8 on the Richter scale struck near Gorkha, Nepal, on April 25, 2015, resulting in the loss of nearly nine thousand lives, extensive property damage, and the destruction of numerous historical and cultural landmarks. Data sourced from the UNDRR, Ministry of Home Affairs, and the United States Geological Survey were analyzed using the ArcGIS software tool. The study offers a comprehensive examination of earthquake-prone regions at regional, national, and global levels. By analyzing recent significant earthquakes along with their associated losses and damages, it underscores the importance of precautionary measures and risk analysis in reducing vulnerability and enhancing preparedness among researchers and stakeholders.

State of the Data: Assessing the FAIRness of US Geological Survey Data

In response to recent shifts towards open science that emphasize transparency, reproducibility, and access to research data, the US Geological Survey (USGS) conducted a study to assess the degree to which USGS data assets meet the FAIR data principles (Findable, Accessible, Interoperable, and Reusable). The USGS designed and applied a methodology for quantitative analysis of FAIR characteristics. A new rubric was derived from a crosswalk of existing FAIR evaluation frameworks and customized for the USGS. The rubric, consisting of 62 yes/no questions, was applied to 392 metadata records of USGS data products published between 1987 and 2022. Results were analyzed to show which FAIR characteristics were most and least present in the metadata and how these scores changed after the implementation of data policy requirements in 2016. Aggregated scores showed specific areas of strength and needed improvements. The greatest increases in FAIR scores over time were for elements that were required by new data policies, especially in the ‘Findable’ category. Based on the results, this paper presents strategies to further improve USGS alignment with FAIR. The suggested strategies are organized in four key areas: USGS data repository characteristics, training and communities of practice, data management policy considerations, and metadata standards, tools, and best practices.

Significant Earth’s responses of the 2022 Tonga eruption across Taiwan from multiple sensor observations

On 15 January 2022, a massive underwater volcano erupted in the Tonga region, releasing a significant amount of volcanic ash and gases into the atmosphere. The United States Geological Survey (USGS) estimated the seismic source to have a surface wave magnitude (Ms) of 5.8. This eruption was observed from space, and the resulting atmospheric shockwave swept across the Pacific Ocean. Reports from various locations worldwide indicated rapid fluctuations in air pressure following this event. Taiwan, situated in the western Pacific, approximately 8,500 km from the eruption source, observed significant changes. During this volcanic eruption, both rapid air pressure changes and several significant changes in the Earth’s physical parameters were observed in Taiwan. The Tonga eruption is a unique event, and comprehensive observations provide an opportunity to explore and explain the mechanisms behind this extreme event. Data from ground surface air pressure gauges, coastal tide gauges, underwater pressure gauges, infrasound sensors, digital microphones, and seismometers were collected. These data were analyzed to identify their origin and explain their interactions. The results of this study first present the detailed propagation characteristics of air pressure waves in the Taiwan region and verify the occurrence of a specific tsunami phenomenon caused by the atmospheric disturbance from the Tonga eruption. It follows a distinct mechanism, explaining its arrival time and wave height distribution around Taiwan, which is different from conventional tsunamis of tectonic origins, which are formed by rapid changes in water caused by earthquakes or underwater landslides.