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At least 73 records · Page 4Linked to original sources
USGS2007

Surficial sediment character of the New York-New Jersey offshore continental shelf region: A GIS compilation

Broad continental shelf regions such as the New York Bight are the product of a complex geologic history and dynamic oceanographic processes, dominated by the Holocene marine transgression (>100 m sea-level rise) following the end of the last Pleistocene ice advance ~ 20,000 years ago. The area of the U.S. Exclusive Economic Zone (U.S. EEZ) territory, extending 200 nautical miles seaward from the coast, is larger than the continental U.S. and contains submerged landforms that provide a variety of natural functions and societal benefits, such as: critical habitats for fisheries, ship navigation and homeland security, and engineering activities (i.e. oil and gas platforms, pipeline and cable routes, potential wind-energy-generation sites). Some parts of the continental margins, particularly inner-continental shelf regions, also contain unconsolidated hard-mineral deposits such as sand and gravel that are regarded as potential aggregate resources to meet or augment needs not met by onshore deposits (Williams, 1992). The present distribution of surficial sediment off the northeastern United States is shaped from the deposits left by the last glaciation and reflects the cumulative effects of sediment erosion, transport, sorting, and deposition by storm and tidal processes during the Holocene rise in sea level. As a result, the sediments on the sea floor represent both an historical record of former conditions and a guide to possible future sedimentary environments. The U.S. Geological Survey (USGS) through the Coastal and Marine Geology Program, in cooperation with the University of Colorado and other partners, has compiled extant sediment character and textural data as well as other geologic information on the sea floor from all regions around the U.S. into the usSEABED data system (Reid and others, 2005; Buczkowski and others, 2006; Reid and others, 2006). The usSEABED system, which contains information on sediment grain size and lithology for more than 340,500 stations within the U.S. EEZ. has been developed and populated with data as part of the USGS Marine Aggregate Resources and Processes and the National Benthic Habitats projects in order to provide the base-line data needed to update the current maps of offshore surficial geologic character and sediment distribution. The maps are also used to characterize benthic sea floor environments important for marine ecosystems. U.S. Geological Survey, Data Series 118 (Reid and others, 2005), of the usSEABED data release series, represents the combined efforts of the USGS and several other government agencies to provide a unified resource for accessing and preserving records of U.S. east coast sea floor geologic information and sediment texture data. For this present report, we have chosen to focus on the New York-New Jersey region, an area that has been intensely studied by the USGS for many years to address many complex issues. This report illustrates the uses of the usSEABED database for GIS applications, while offering additional insight into the resources and data available from the USGS and its collaborative institutions. This report is based on data contained in U.S. Geological Survey Data Series 118 (Reid and others, 2005) and shows an assortment of example GIS products that are possible using usSEABED. All data are intended to be GIS-ready and should not require any additional cleanup, formatting, or renaming of fields in order to use the data in a Geographic Information System. This project employs the Environmental Systems Research Institute's (ESRI) ArcView™ software. Many of these maps were made as part of the ongoing USGS study to assess marine aggregate resources offshore New York and New Jersey, but these maps can serve many other purposes. The marine science community, educators, students and others are encouraged to use these data to generate GIS products for their own purposes. The objectives of the Marine Aggregate Resources and Processes project are to produce a series of new geologic maps and reports of the sea floor that will provide scientific insights into the character and geologic development of U.S. continental margins and to use these maps and information to assess the potential availability of offshore sand and gravel resources. The mapping and aggregate resource assessments are being conducted on a national scale using the usSEABED data base as described in Williams and others (2003). Potential uses for these data include: (1) defining the geological variability of the sea floor in relation to benthic habitat diversity; (2) improving our understanding of the processes that control the distribution and transport of bottom sediments and benthic habitats; (3) locating aggregate resources for beach nourishment and industrial applications; and (4) providing a detailed geospatial framework for future marine science research, monitoring, and management activities. The initial assessments are in progress for the New York Bight and Louisiana offshore areas.

New Jersey, New York↗
USGS1996

The imaging node for the Planetary Data System

The Planetary Data System Imaging Node maintains and distributes the archives of planetary image data acquired from NASA's flight projects with the primary goal of enabling the science community to perform image processing and analysis on the data. The Node provides direct and easy access to the digital image archives through wide distribution of the data on CD-ROM media and on-line remote-access tools by way of Internet services. The Node provides digital image processing tools and the expertise and guidance necessary to understand the image collections. The data collections, now approaching one terabyte in volume, provide a foundation for remote sensing studies for virtually all the planetary systems in our solar system (except for Pluto). The Node is responsible for restoring data sets from past missions in danger of being lost. The Node works with active flight projects to assist in the creation of their archive products and to ensure that their products and data catalogs become an integral part of the Node's data collections.

Planetary and Space Science↗
USGS2026

Leveraging local species data, a global database, and an occupancy model to explore bee–plant interactions

Global declines in bee populations are threatening the ecosystem services they provide, including pollination. Many bee–plant interactions are understudied, producing an incomplete understanding of resulting ecosystem-level vulnerabilities. The last decade has generated a wealth of opportunistic data originating from natural history collection records, published ecological datasets, and citizen/community science initiatives in online databases such as Global Biotic Interactions (GloBI). Here, we explore hypotheses related to bee–plant interactions and detection processes using the GloBI database, curated checklists of bee and flowering plant species, and an occupancy model. We hypothesized that larger, social bees would visit a larger number of plant species, while smaller, solitary bees would visit fewer. We also predicted that flowers with open, bowl-like shapes would attract a greater diversity of bee visitors compared to closed shapes. Further, we hypothesized that both floral and bee traits, such as bright colors and conspicuous patterns, would increase detectability, and that different data collection methods would vary in their ability to capture bee–plant interactions. Lastly, we hypothesized that the interaction network generated by the output of the occupancy model, which accounted for imperfect bee–plant detection, would yield more interactions, thereby increasing measures of evenness and decreasing nestedness and specialization, as compared to the network generated from recorded interaction data. We found that smaller bees exhibited higher probabilities of plant interactions than larger bees, but we did not find evidence that bee sociality influenced the probability of interacting with plants. We found that blue flowers and closed (not-bowl-shaped) flowers had higher probabilities of bee-plant interaction than other flower colors or bowl-shaped flowers, respectively. We also found that larger bee size, blue flowers, bowl shapes, and community science sources were associated with higher detection probabilities of bee–plant interactions. Lastly, the interaction network generated by the occupancy model output showed higher levels of evenness, nestedness, and connectance than the network generated by the GloBI data. Our study is among the first to utilize occupancy modeling to directly model species' interactions, leverage aggregated, open-source databases and expert checklists, and highlight the influence of detection and collection biases on our understanding of ecological interactions.

California↗
USGS2023

Changes in habitat suitability for wintering dabbling ducks during dry conditions in the Central Valley of California

In arid and Mediterranean regions, landscape-scale wetland conservation requires understanding how wildlife responds to dynamic freshwater availability and conservation actions to enhance wetland habitat. Taking advantage of Landsat satellite data and structured and community science bird survey data, we built species distribution models to describe how three duck species, the Northern Pintail ( Anas acuta ), Green-winged Teal ( Anas crecca ), and Northern Shoveler ( Anas clypeata ), respond to freshwater supply and food resources on different flooded land cover types in the Central Valley of California. Specifically, our models compared duck habitat suitability between the wettest and driest conditions in each month from September through April. Using abundance-weighted boosted regression trees, we created three sets of species occurrence models based on different covariates: (1) near real-time (hereafter “real-time”) covariates in which duck observations were matched to the water availability within the 16-day window of a Landsat observation, (2) a combination of real-time covariates and waterfowl food resource covariates describing annual corn and rice biomass and managed wetland moist soil seed yield estimates derived from Landsat data, and (3) long-term average covariates—the most common approach to species distribution modeling—in which long-term average surface water availability was used. We modeled the monthly occurrence of three duck species as a function of surface water availability, land cover type, road density, temperature, and bird data source. We found that dry conditions result in reduced habitat suitability, with the biggest reductions in November through January and in agricultural fields; in contrast, suitability of flooded wetland habitat was relatively robust to surface water availability. When models of habitat suitability based on long-term average climate conditions were compared to models based on real-time conditions, the highest long-term suitability values occurred in areas where suitability was high regardless of whether it was a wet or a dry year. While all models performed well, the inclusion of crop and wetland plant yield covariates resulted in slightly higher model performance. Overall, species distribution models created using data on the environmental conditions present at the time of bird observations can aid conservation efforts under extreme conditions over large spatial scales.

California↗
USGS2025

Too much and not enough data: Challenges and solutions for generating information in freshwater research and monitoring

Evaluating progress toward achieving freshwater conservation and sustainability goals requires transforming diverse types of data into useful information for scientists, managers, and other interest groups. Despite substantial increases in the volume of freshwater data collected worldwide, many regions and ecosystems still lack sufficient data collection and/or data access. We illustrate how these data challenges result from a diverse set of underlying mechanisms and propose solutions that can be applied by individuals or organizations. We discuss creative approaches to address data scarcity, including the use of community science, remote-sensing, environmental sensors, and legacy datasets. We highlight the importance of coordinated data collection efforts among groups and training programs to improve data access. At the institutional level, we emphasize the power of prioritizing data curation, incentivizing data publication, and promoting research that enhances data coverage and representativeness. Some of these strategies involve technological and analytical approaches, but many necessitate shifting the priorities and incentives of organizations such as academic and government research institutions, monitoring groups, journals, and funding agencies. Our overarching goal is to stimulate discussion to narrow the data disparities hindering the understanding of freshwater processes and their change across spatial scales.

Nahuel Huapi Lake, Lake Tahoe↗
USGS2023

The NEON Ecological Forecasting Challenge

The 21st century continues to be characterized by major changes to the environment and the ecosystem services upon which society depends. Anticipating and responding to these changes requires that scientists explicitly forecast future conditions in real time (Dietze et al . 2018 ). Ecological forecasting, like weather and epidemiological forecasting, involves integrating data and models to generate quantitative predictions of the future state of ecological systems before observations are collected. The iterative cycle of creating forecasts, evaluating them with new observations, updating the models, and then making new forecasts has the potential to accelerate learning across many ecological subdisciplines. This cycle builds on openly available data, often published soon after collection, as is increasingly common in ecological observatory networks, such as the National Ecological Observatory Network (NEON). To accelerate improvements in ecological forecasting, we designed and launched the NEON Ecological Forecasting Challenge (hereafter, “Challenge”) (Figure 1 ), an open platform for the ecological and data science communities to forecast NEON data before they are collected.

Frontiers in Ecology and the Environment↗
USGS2026

Streamflow and surface-water presence data availability across the conterminous United States: A review for headwater systems

Water is essential for life on Earth, supporting ecosystems, human health, and economic activities. Hydrology relies on observational data, and this paper discusses regional and national datasets for the conterminous United States (CONUS) publicly available as of 2023, focusing on headwaters, defined as first- and second-order streams at 1:24000 scale. It identifies 72 primary and secondary datasets and 11 repositories and argues how better integration and accessibility of hydrological data can improve research. The paper distinguishes between datasets where streamflow was the primary data collection objective and those where it was secondary. This distinction highlights opportunities to consider data from efforts peripheral to hydrology but is still useful for understanding hydrologic conditions. The analysis reveals that out of about 118 000 active and inactive stream observation sites, about 6.6% and 25% are located on first- and second-order streams, respectively. This indicates a substantial data gap for headwater systems, which account for over 77% of stream length in CONUS. Federal agencies manage 72% of hydrologic monitoring sites across all stream orders, but only 34% of these are in headwater systems. Academic institutions operate about 2% of sites, with almost half (48%) in headwater systems, focusing on ecosystem research. State agencies also operate about 2% of sites, primarily on larger systems, with 19% on headwaters. Additionally, 23% of sites are managed by multiple agencies. Spatial patterns further reveal pronounced disparities among physiographic regions. Eastern and coastal provinces show relatively dense monitoring, while central and western regions show sparse coverage. These gaps reflect historical priorities, logistical constraints, funding limitations, and the high cost of continuous instrumentation. To address biases in monitoring networks, data collection could be enhanced with low-cost monitoring, community science, and remote sensing technologies. This study also notes the benefits of long-term monitoring and prioritizing retention of streamgages with longer records.

conterminous United States↗
USGS2023

Insectivorous bat foraging tracks the availability of aquatic flies (Diptera)

Rivers and their adjacent riparian zones are model ecosystems for observing cross-ecosystem energy transfers. Aquatic insects emerging from streams, for example, are resource subsidies that support riparian consumers such as birds, spiders, lizards, and bats. We collaborated with recreational river runners in Grand Canyon, Arizona, USA, to record acoustic bat activity and sample riparian insects using light traps at dusk from April through October 2017–2020. River runners collected these data on 1,428 events over 611 sampling nights at 410 sites throughout a 470-km segment of the Colorado River. We documented 71 insect taxa in light traps and recorded 19 bat species with acoustic detectors. We hypothesized that bat activity along this highly regulated river segment would be influenced primarily by variation in prey availability, as compared to other habitat descriptors. We predicted that bat activity would be positively related to aquatic insect catch rates and unrelated to terrestrial insect abundance. We fit Bayesian regression models to test these hypotheses and to quantify the relationship between bat activity and a suite of environmental variables: time of year, time of day, distance from perennial tributaries, distance from rapids, channel width, geomorphic reach, tall vegetation cover, air temperature, and lunar phase. Bat activity was positively related to the abundance of aquatic flies (Diptera), which outcompeted all other prey categories and structural habitat descriptors in our models. Within our dusk sampling period, activity of small myotis (California myotis [ Myotis californicus ] and Yuma myotis [ M. yumanensis ]) was high late in the evening and canyon bats ( Parastrellus hesperus ), conversely, were more active early in the evening. Activity of canyon bats varied seasonally, with peak activity in August. Our results support the hypothesis that aquatic prey, specifically aquatic flies, are key predictors of bat activity along a large, regulated river corridor and demonstrate the power of community science as a tool for ecosystem monitoring.

Journal of Wildlife Management↗
USGS2007

The role of fault zone drilling

The objective of fault-zone drilling projects is to directly study the physical and chemical processes that control deformation and earthquake generation within active fault zones. An enormous amount of field, laboratory, and theoretical work has been directed toward the mechanical and hydrological behavior of faults over the past several decades. Nonetheless, it is currently impossible to differentiate between – or even adequately constrain – the numerous conceptual models of active faults proposed over the years. For this reason, the Earth science community is left in the untenable position of having no generally accepted paradigm for the mechanical behavior of faults at depth. One of the primary causes for this dilemma is the difficulty of either directly observing or inferring physical properties and deformation mechanisms along faults at depth, as well as the need to observe directly key parameters such as the state of stress acting on faults at depth, pore fluid pressure (and its possible variation in space and time), and processes associated with earthquake nucleation and rupture. Today, we know very little about the composition of active faults at depth, their constitutive properties, the state of in situ stress or pore pressure within fault zones, the origin of fault-zone pore fluids, or the nature and significance of time-dependent fault-zone processes.

Book chapter↗
USGS2007

Statistical analysis of water-quality data containing multiple detection limits II: S-language software for nonparametric distribution modeling and hypothesis testing

Analysis of low concentrations of trace contaminants in environmental media often results in left-censored data that are below some limit of analytical precision. Interpretation of values becomes complicated when there are multiple detection limits in the data-perhaps as a result of changing analytical precision over time. Parametric and semi-parametric methods, such as maximum likelihood estimation and robust regression on order statistics, can be employed to model distributions of multiply censored data and provide estimates of summary statistics. However, these methods are based on assumptions about the underlying distribution of data. Nonparametric methods provide an alternative that does not require such assumptions. A standard nonparametric method for estimating summary statistics of multiply-censored data is the Kaplan-Meier (K-M) method. This method has seen widespread usage in the medical sciences within a general framework termed "survival analysis" where it is employed with right-censored time-to-failure data. However, K-M methods are equally valid for the left-censored data common in the geosciences. Our S-language software provides an analytical framework based on K-M methods that is tailored to the needs of the earth and environmental sciences community. This includes routines for the generation of empirical cumulative distribution functions, prediction or exceedance probabilities, and related confidence limits computation. Additionally, our software contains K-M-based routines for nonparametric hypothesis testing among an unlimited number of grouping variables. A primary characteristic of K-M methods is that they do not perform extrapolation and interpolation. Thus, these routines cannot be used to model statistics beyond the observed data range or when linear interpolation is desired. For such applications, the aforementioned parametric and semi-parametric methods must be used.

Computers & Geosciences↗
USGS2020

OpenCLC: An open-source software tool for similarity assessment of linear hydrographic features

The National Hydrography Dataset (NHD) is a foundational geospatial data source in the United States that enables extensive and diverse environmental research and supports decision-making in numerous contexts. However, the NHD requires regular validation and update given possible inconsistent initial collection and hydrographic changes. Furthermore, systems or tools that use NHD data must manage regular updates that occur within the high-resolution version of the NHD (NHD HR). This research contributes to filling this gap by establishing an open-source software tool named OpenCLC, which automatically identifies matching and mismatching line features between two sets of hydrographic flowlines. Aside from identifying differences among two version of NHD lines, results can be applied to improve the quality of NHD HR content. OpenCLC significantly outperforms the best available commercial off-the-shelf software in computational scalability, and it is made widely available as part of the CyberGIS Toolkit to benefit broad environmental and geospatial science communities.

SoftwareX↗
USGS2001

The Landsat 7 mission: terrestrial research and applications for the 21st century

The Landsat Earth observation approach introduced in 1972 created a new way of monitoring land cover and land use globally. The Landsat 7 mission, successfully launched on April 15, 1999, continues those observations and demonstrates significant progress in precise numerical radiometry, spectral differentiation, and seasonally repetitive monitoring. Substantial improvements in calibration procedures, both prior to launch and during normal operations, have also been made to ensure long-term stability in the acquired spectral radiometry. Landsat 7 data acquisitions are being driven by a long-term data acquisition plan that was designed to ensure that substantially cloud-free, seasonal coverage would be recorded and archived in the US for all land areas of the globe. NASA competitively selected a Landsat Science Team, consisting of representatives from US universities and government agencies, to exploit the Landsat 7 record for global change research. This team is addressing the technical and analytical means to process and analyze the core of this observation record, and for the first time in the history of the Landsat mission, the technical and operational aspects of the mission are being driven by the goals of the US science community. The expected outcome of these efforts is a rapid improvement in understanding the Earth system, as well as conceptual knowledge that will underpin significant advancements in the application of this technology for commercial, operational, educational, and research purposes. Pathways to achieve effective Landsat continuity in the early decades of the 21st century are also being given careful attention, and there is no question that the lessons learned from the Landsat 7 mission will strongly influence these next-generation sensor systems.

Remote Sensing of Environment↗
USGS2011

Extreme volcanism on Io: Latest insights at the end of Galileo era

Galileo has now completed 7 years exploring Jupiter. The spacecraft obtained breathtaking views of the four major satellites, and studied Jupiter's clouds and atmospheric composition, rings, small satellites, and magnetic field. It had five successful close flybys and many distant observations of Io. Scientists already knew from Voyager and Earth‐based astronomy that Io is by far the most volcanically active object in the solar system. Galileo has given us stunning color panoramas of Io's surface and unprecedented close views of erupting volcanoes (Figure 1) and the largest active flows observed anywhere. Among recent discoveries about Io, perhaps most astonishing since Voyager, is that some lavas possess emission temperatures greater than any lavas erupted on Earth today and possibly since the start of Earth's geologic history. The Io science community has identified three alternative interpretations of Io's hottest lavas: (1) ultramafic material similar to komatiite; (2) superheated lava; or (3) an ultra‐refractory substance deficient in silica and rich in Ca‐Al oxides.

Eos, Transactions, American Geophysical Union↗
USGS2022

Measuring and attributing sedimentary and geomorphic responses to modern climate change: Challenges and opportunities

Today, climate change is affecting virtually all terrestrial and nearshore settings. This commentary discusses the challenges of measuring climate-driven physical landscape responses to modern global warming: short and incomplete data records, land use and seismicity masking climatic effects, biases in data availability and resolution, and signal attenuation in sedimentary systems. We identify opportunities to learn from historical and paleo data, select especially sensitive study sites, and report null results to better characterize the extent and nuances of climate-change effects. We then discuss efforts to improve attribution practices, which will lead to better predictive capabilities. We encourage the earth-science community to prioritize scientific research on climate-driven physical landscape changes so that societies will be better prepared to manage the effects on health and safety, infrastructure, water–food–energy security, economics, and ecosystems that follow from climate-driven physical landscape change.

Earth's Future↗
USGS2024

Streamflow depletion caused by groundwater pumping: Fundamental research priorities for management-relevant science

Reductions in streamflow caused by groundwater pumping, known as “streamflow depletion,” link the hydrologic process of stream-aquifer interactions to human modifications of the water cycle. Isolating the impacts of groundwater pumping on streamflow is challenging because other climate and human activities concurrently impact streamflow, making it difficult to separate individual drivers of hydrologic change. In addition, there can be lags between when pumping occurs and when streamflow is affected. However, accurate quantification of streamflow depletion is critical to integrated groundwater and surface water management decision making. Here, we highlight research priorities to help advance fundamental hydrologic science and better serve the decision-making process. Key priorities include (a) linking streamflow depletion to decision-relevant outcomes such as ecosystem function and water users to align with partner needs; (b) enhancing partner trust and applicability of streamflow depletion methods through benchmarking and coupled model development; and (c) improving links between streamflow depletion quantification and decision-making processes. Catalyzing research efforts around the common goal of enhancing our streamflow depletion decision-support capabilities will require disciplinary advances within the water science community and a commitment to transdisciplinary collaboration with diverse water-connected disciplines, professions, governments, organizations, and communities.

Water Resource Research↗
USGS2010

The Martian surface

The past four years have been particularly fruitful for Martian research as the enormous volumes of data collected during the Viking mission became readily available to the general science community, and as reformatting of the remote sensing data into cartographic products made the data more useable. The 1:5,000,000‐scale map series is complete, and 1:2,000,000‐scale controlled mosaics of the entire planet are nearing completion. In addition 1:500,000‐scale mosaics have been prepared of about thirty local areas. A uniform scale, digital imaging data base is in preparation (Batson, 1986), and the infrared data have been reformatted to make it more accessible to the general user (Martin and Kieffer, 1985).

Reviews of Geophysics↗
USGS2023

Recent and future declines of a historically widespread pollinator linked to climate, land cover, and pesticides

The acute decline in global biodiversity includes not only the loss of rare species, but also the rapid collapse of common species across many different taxa. The loss of pollinating insects is of particular concern because of the ecological and economic values these species provide. The western bumble bee ( Bombus occidentalis ) was once common in western North America, but this species has become increasingly rare through much of its range. To understand potential mechanisms driving these declines, we used Bayesian occupancy models to investigate the effects of climate and land cover from 1998 to 2020, pesticide use from 2008 to 2014, and projected expected occupancy under three future scenarios. Using 14,457 surveys across 2.8 million km 2 in the western United States, we found strong negative relationships between increasing temperature and drought on occupancy and identified neonicotinoids as the pesticides of greatest negative influence across our study region. The mean predicted occupancy declined by 57% from 1998 to 2020, ranging from 15 to 83% declines across 16 ecoregions. Even under the most optimistic scenario, we found continued declines in nearly half of the ecoregions by the 2050s and mean declines of 93% under the most severe scenario across all ecoregions. This assessment underscores the tenuous future of B. occidentalis and demonstrates the scale of stressors likely contributing to rapid loss of related pollinator species throughout the globe. Scaled-up, international species-monitoring schemes and improved integration of data from formal surveys and community science will substantively improve the understanding of stressors and bumble bee population trends.

Proceedings of the National Academy of Sciences↗
USGS2007

The 1 km AVHRR global land data set: first stages in implementation

The global land 1 km data set project represents an international effort to acquire, archive, process, and distribute 1 km AVHRR data of the entire global land surface in order to meet the needs of the international science community. A network of 26 high resolution picture transmission (HRPT) stations, along with data recorded by the National Oceanic and Atmospheric Administration (NOAA), has been acquiring daily global land coverage since 1 April 1992. A data set of over 30000 AVHRR images has been archived and made available for distribution by the United States Geological Survey, EROS Data Center and the European Space Agency. Under the guidance of the International Geosphere Biosphere programme, processing standards for the AVHRR data have been developed for calibration, atmospheric correction, geometric registration, and the production of global 10-day maximum normalized difference vegetation index (NDVI) composites. The major uses of the composites are related to the study of surface vegetation cover. A prototype 10-day composite was produced for the period of 21–30 June 1992. Production of an 18-month time series of 10-day composites is underway.

International Journal of Remote Sensing↗