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At least 1,063 records · Page 59Linked to original sources
USGS2012

Archive of single-beam bathymetry data collected during USGS cruise 07CCT01 nearshore of Fort Massachusetts and within Camille Cut, West and East Ship Islands, Gulf Islands National Seashore, Mississippi, July 2007

The Gulf Islands National Seashore (GUIS) is composed of a series of barrier islands along the Mississippi - Alabama coastline. Historically these islands have undergone long-term shoreline change. The devastation of Hurricane Katrina in 2005 prompted questions about the stability of the barrier islands and their potential response to future storm impacts. Additionally, there was concern from the National Park Service (NPS) about the preservation of the historical Fort Massachusetts, located on West Ship Island. During the early 1900s, Ship Island was an individual island. In 1969 Hurricane Camille breached Ship Island, widening the cut and splitting it into what is now known as West Ship Island and East Ship Island. In July of 2007, the U.S. Geological Survey (USGS) was able to provide the NPS with a small bathymetric survey of Camille Cut using high-resolution single-beam bathymetry. This provided GUIS with a post-Katrina assessment of the bathymetry in Camille Cut and along the northern shoreline directly in front of Fort Massachusetts. Ultimately, this survey became an initial bathymetry dataset toward a larger USGS effort included in the Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazard Susceptibility Project ( http://ngom.usgs.gov/gomsc/mscip/ ). This report serves as an archive of the processed single-beam bathymetry. Data products herein include gridded and interpolated digital depth surfaces and x,y,z data products. Additional files include trackline maps, navigation files, geographic information system (GIS) files, Field Activity Collection System (FACS) logs, and formal Federal Geographic Data Committee (FGDC) metadata. Scanned images of the handwritten FACS logs and digital FACS logs are also provided as PDF files. Refer to the Acronyms page for description of acronyms and abbreviations used in this report or hold the cursor over an acronym for a pop-up explanation. The USGS St. Petersburg Coastal and Marine Science Center assigns a unique identifier to each cruise or field activity. For example, 07CCT01 tells us the data were collected in 2007 for the Coastal Change and Transport (CCT) study and the data were collected during the first (01) field activity for that project in that calendar year. Refer to http://walrus.wr.usgs.gov/infobank/programs/html/definition/activity.html for a detailed description of the method used to assign the field activity ID. Data were collected using a 26-foot (ft) Glacier Bay catamaran. The single-beam transducers were sled mounted on a rail attached between the catamaran hulls. Navigation was acquired using HYPACK, Inc., Hypack version 4.3a.7.1 and differentially corrected using land-based GPS stations. See the digital FACS equipment log for details about the acquisition equipment used. Raw datasets were stored digitally and processed systematically using NovAtel's Waypoint GrafNav version 7.6, SANDS version 3.7, and ESRI ArcGIS version 9.3.1. For more information on processing refer to the Equipment and Processing page.

Mississippi↗
USGS2007

Global Data Toolset (GDT)

According to the United Nations Environment Programme World Conservation Monitoring Centre (UNEP-WCMC) approximately 60 percent of the data contained in the World Database on Protected Areas (WDPA) has missing or incomplete boundary information. As a result, global analyses based on the WDPA can be inaccurate, and professionals responsible for natural resource planning and priority setting must rely on incomplete geospatial data sets. To begin to address this problem the World Data Center for Biodiversity and Ecology, in cooperation with the U. S. Geological Survey (USGS) Rocky Mountain Geographic Science Center (RMGSC), the National Biological Information Infrastructure (NBII), the Global Earth Observation System, and the Inter-American Biodiversity Information Network (IABIN) sponsored a Protected Area (PA) workshop in Asuncion, Paraguay, in November 2007. The primary goal of this workshop was to train representatives from eight South American countries on the use of the Global Data Toolset (GDT) for reviewing and editing PA data. Use of the GDT will allow PA experts to compare their national data to other data sets, including non-governmental organization (NGO) and WCMC data, in order to highlight inaccuracies or gaps in the data, and then to apply any needed edits, especially in the delineation of the PA boundaries. In addition, familiarizing the participants with the web-enabled GDT will allow them to maintain and improve their data after the workshop. Once data edits have been completed the GDT will also allow the country authorities to perform any required review and validation processing. Once validated, the data can be used to update the global WDPA and IABIN databases, which will enhance analysis on global and regional levels.

Fact Sheet↗
USGS2025

Preparation and analysis methods for fish tissue collected from Lake Koocanusa, Montana

Lake Koocanusa, a reservoir, receives mine wastes from metallurgical coal mines in the Elk River Valley of British Columbia, Canada. Selenium and other elements discharged by the mines into the waters of the United States can pose unknown risks to aquatic life. The U.S. Geological Survey Wyoming-Montana Water Science Center can collaborate with Montana Fish, Wildlife and Parks and other State and Federal agencies to design studies and to collect fish tissues to help fill this knowledge gap. This report describes the processes, techniques, and methods used to collect and analyze fish tissue collected from Lake Koocanusa; and procedures used to review and manage data, including quality assurance and quality control procedures used by the U.S. Geological Survey Wyoming-Montana Water Science Center and supporting analytical laboratories. These fish tissue collections began in 2021.

Montana↗
USGS2021

Can Landsat 7 preserve its science capability with a drifting orbit?

Since 2017, the orbit of Landsat 7 has drifted outside its nominal mission requirement toward an earlier acquisition time because of limited onboard fuel resources. This makes quantitative analyses from Landsat 7 data potentially unreliable for many scientific studies. To comprehensively understand the effect of ongoing (2018–2020) orbit drift on Landsat 7 data, we compared surface reflectance and Top-Of-Atmosphere (TOA) reflectance of growing season observations (July 1 ± 30 days) from Landsat 7 with orbit drift and Landsat 8 with nominal orbit using a total of 10,000 randomly selected Northern Hemisphere (0–75 0 N) terrestrial pixels. To evaluate the future (2021–2023) effect of Landsat 7's orbit drift, we analyzed the historical Northern Hemisphere terrestrial growing season Earth Observing-1 (EO-1) TOA reflectance images, which shared a similar orbit drift as Landsat 7 but occurred much earlier. Results suggest that Landsat 7's orbit drift has already led to a general decrease in surface reflectance and TOA reflectance in 2019 and 2020, with a limited impact (overall reflectance changes less than 0.007). The influence of orbit drift is more substantial for the two shortwave infrared (SWIR) bands and the near infrared (NIR) band, but less for the three visible bands (i.e., Red, Green, and Blue). The Normalized Difference Vegetation Index (NDVI), derived from either surface reflectance or TOA reflectance, increased less than 0.003 in 2020. According to the historical EO-1 TOA reflectance data, we estimate that the effect of Landsat 7's orbit drift will be much more dramatic in the future (e.g., the NIR and SWIR bands will decrease more than 0.015 since July 1, 2021), and for different land cover types, the effects of orbit drift are also quite different. To reduce this influence, we examined the c-factor Bidirectional Reflectance Distribution Function (BRDF) normalization approach to correct the orbit drift impact for Landsat 7 surface reflectance data collected between 2019 and 2020. We found that the c-factor BRDF can reduce the data difference substantially, but how this approach works after Landsat 7's orbit drifts further still requires more investigation. Therefore, we determined that Landsat 7 can preserve its science capability until 2020, but will be less reliable for remote sensing applications that need accurate absolute radiometric values after 2020. Correction methods such as c-factor BRDF could be a potential viable approach to maintain its science capability going forward.

Science of Remote Sensing↗
USGS2022

A reproducible and reusable pipeline for segmentation of geoscientific imagery

Segmentation of Earth science imagery is an increasingly common task. Among modern techniques that use Deep Learning, the UNet architecture has been shown to be a reliable for segmenting a range of imagery. We developed software–Segmentation Gym–to implement a data-model pipeline for segmentation of scientific imagery using a family of UNet models. With an existing set of imagery and labels, the software uses a single configuration file that handles data set creation, as well as model setup and model training. Key benefits of this software are (a) the focus on reproducible data set creation and modeling, and (b) the ability for quick model experimentation through changes to a configuration file. Quick experimentation permits researchers to prototype different model architectures, sizes, and adjust common hyperparameters to find a suitable model. We demonstrate the use of the software using a data set of 419 labeled Landsat-8 scenes of coastal environments and compare results across two model architectures, five model sizes, and three loss functions. This demonstration highlights that our software enables rapid, reproducible experimentation to determine optimal hyperparameters for specific data sets and research questions.

Earth and Space Science↗
USGS2009

A mosaic of diverse ideas: The ecological legacy of J. Frederick Grassle

During the 40 years (and counting) of his scientific career, J. Frederick Grassle has made fundamental contributions to our understanding of marine ecosystems from coral reefs to deep-sea sediments. His advocacy and passion for marine biodiversity in the form of myriad groundbreaking studies and influential reviews, his generosity of ideas and capacity to catalyze and inspire those working with him as well as the science community in general, his breakthroughs in improved ocean observation, his marine science infrastructure initiatives, together with his tireless persistence, have helped lead to major shifts in approaches to marine science and the shape of modern ocean studies to one that favours multidisciplinary research, teamwork, continuous, long-term observation, in situ experimentation, recognition of the importance of marine biodiversity, and global cooperation on research and data sharing. In shallow-water ecology, he co-discovered sibling species of Capitella spp., important not only because it is a key pollution indicator but also because the work helped to pave the way for the discovery of numerous sibling species in other taxa with major ramifications for ecological understanding. He was also a key player in the West Falmouth oil spill study which, along with complementary mesocosm experiments, remains one of the most important and detailed studies of its kind. He was also a lead player in the first biological expedition to hydrothermal vents and wrote the seminal articles that helped to inspire the flurry of vent research that followed. He is perhaps best known for his deep-sea work, where he brought submersibles to the forefront as a sampling tool, brought experimental manipulative studies to the primarily descriptive discipline of deep-sea benthic ecology, and generated tremendous excitement, debate, and rekindled interest in marine biodiversity with the first quantitative estimate of global deep-sea diversity. His efforts to document marine biodiversity resulted in the international Census of Marine Life, and his emphasis on the need for continuous, long-term ocean observation has led to breakthroughs in international cooperation in cabled observatories such as LEO-15. These efforts have also enhanced efforts to integrate ocean data on a global scale in platforms such as the Ocean Biogeographic Information System (OBIS). The diversity of his contributions to marine science mirror the immense marine diversity he has recognized, documented, and championed so effectively over the last four decades.

Deep-Sea Research Part II: Topical Studies in Ocea↗
USGS1999

Index of hydrologic characteristics and data resources for the Gwynns Falls watershed, Baltimore County and Baltimore City, Maryland

The Gwynns Falls watershed has been selected as the primary study area for the Baltimore Ecosystem Study, as part of the National Science Foundation's Long-Term Ecological Research program. Because the Baltimore Ecosystem Study will be investigating long-term hydrologic changes in the Gwynns Falls watershed, a compilation of existing data resources for the watershed is necessary. This report discusses hydrologic characteristics and presents a compilation of historical data resources for the Gwynns Falls watershed. Tables are presented that list active and discontinued continuous-record streamflow-gaging stations, nontidal crest-stage partial-record stations, low-flow partial-record stations, and water-quality partial-record stations operated by the U.S. Geological Survey, Maryland-Delaware-D. C. District, in the Gwynns Falls watershed. Statistics regarding the number of inventoried ground-water wells in or bordering the Gwynns Falls watershed also are presented. A summary of additional data resources for the Gwynns Falls watershed is provided. This includes (1) an inventory of selected U.S. Geological Survey studies and reports that contain historical data or basin characteristics for streams in the watershed, (2) a listing of indirect flood-discharge measurements that have been made at several monitoring stations in the watershed, (3) a brief discussion of channel-stability and bridge-scour data collected by the U.S. Geological Survey in the watershed during 1990?95, (4) a listing of climatological data stations in the watershed and in the surrounding regional area, and (5) a listing of other selected reports that include data or information on the Gwynns Falls watershed.

Maryland↗
USGS2017

Coastal bathymetry data collected in May 2015 from Fire Island, New York—Wilderness breach and shoreface

Scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, conducted a bathymetric survey of Fire Island from May 6-20, 2015. The USGS is involved in a post-Hurricane Sandy effort to map and monitor the morphologic evolution of the wilderness breach as a part of the Hurricane Sandy Supplemental Project GS2-2B. During this study, bathymetry data were collected with single-beam echo sounders and Global Positioning Systems, which were mounted to personal watercraft, along the Fire Island shoreface and within the wilderness breach. Additional bathymetry and elevation data were collected using backpack Global Positioning Systems on flood shoals and in shallow channels within the wilderness breach.

New York↗
USGS2005

The AmericaView Project - Putting the Earth into Your Hands

The U.S. Geological Survey (USGS) is a leader in collecting, archiving, and distributing geospatial data and information about the Earth. Providing quick, reliable access to remotely sensed images and geospatial data is the driving principle behind the AmericaView Project. A national not-for-profit organization, AmericaView, Inc. was established and is supported by the USGS to coordinate the activities of a national network of university-led consortia with the primary objective of the advancement of the science of remote sensing. Individual consortia members include academic institutions, as well as state, local, and tribal government agencies. AmericaView's focus is to expand the understanding and use of remote sensing through education and outreach efforts and to provide affordable, integrated remote sensing information access and delivery to the American public. USGS's Landsat and NASA's Earth Observing System (EOS) satellite data are downlinked from satellites or transferred from other facilities to the USGS Center for Earth Resources Observation and Science (EROS) ground receiving station in Sioux Falls, South Dakota. The data can then be transferred over high-speed networks to consortium members, where it is archived and made available for public use.

Fact Sheet↗
USGS2011

Geoinformatics in the public service: Building a cyberinfrastructure across the geological surveys

Advanced information technology infrastructure is increasingly being employed in the Earth sciences to provide researchers with efficient access to massive central databases and to integrate diversely formatted information from a variety of sources. These geoinformatics initiatives enable manipulation, modeling and visualization of data in a consistent way, and are helping to develop integrated Earth models at various scales, and from the near surface to the deep interior. This book uses a series of case studies to demonstrate computer and database use across the geosciences. Chapters are thematically grouped into sections that cover data collection and management; modeling and community computational codes; visualization and data representation; knowledge management and data integration; and web services and scientific workflows. Geoinformatics is a fascinating and accessible introduction to this emerging field for readers across the solid Earth sciences and an invaluable reference for researchers interested in initiating new cyberinfrastructure projects of their own.

Book chapter↗
USGS2021

Merging scientific silos: Integrating specialized approaches for thinking about and using spatial data that can provide new directions for persistent fisheries problems

By merging our specialization silos, fisheries professionals can expand the options that are available to them to address difficult fisheries and aquatic conservation problems, which require an understanding of spatial patterns in geographically large systems. Our purpose is to start a profession-wide conversation about additional ways to think about and use spatial data. We use case studies to illustrate how identifying and merging multiple specialized approaches (e.g., fish tracking, fish surveys, geomorphology, social science, jurisdictional viewpoints) can create an ensemble that has advantages over the use of any single approach alone. Thus, our perspective is not about solving a specific technical problem with a new tool, but about the benefits of identifying gaps in data from one specialized approach, and filling those gaps with data from other specialized approaches. If multiple approaches are coordinated through a larger, problem-specific planning strategy, the result can be better outcomes for difficult problems through creative integration. We encourage others to add constructive ideas to the views initiated here.

Fisheries Magazine↗
USGS2025

Application of a data-limited stock assessment model to understand the historical population of cisco in Lake Erie

Historically, cisco (Coregonus artedi) supported one of the largest commercial fisheries in Lake Erie with over 25 million kilograms landed in a single year during the fisheries’ peak in 1912. Like many other coregonines in the Laurentian Great Lakes, the Lake Erie cisco population eventually collapsed and is now considered extirpated. Management interest in restoring coregonine abundance and diversity across the Great Lakes motivated the development of a multi-agency, science-based framework aimed at restoring or enhancing populations. As part of that framework, we applied a data-limited model (depletion-based stock reduction analysis) to a reconstructed catch series to estimate historical levels of abundance of cisco in Lake Erie. Estimated historical carrying capacity was 171 million kilograms (66.5 kg/ha) and estimated annual exploitation was as high as 70 %. Model projections suggested the population should have rebuilt following a fishery collapse in 1925; however, the fishery remained depressed and cisco disappeared from Lake Erie despite the end of targeted exploitation in 1965. Other factors, such as habitat degradation and invasive species, are believed to have played a part in impeding recovery of cisco. The results of this study could be used in setting potential restoration targets for Lake Erie cisco given current conditions. The likelihood of achieving recovery targets based on historical population size will be dependent on the suitability of current conditions for sustaining the population.

Lake Erie↗
USGS2023

System characterization report on the Pléiades Neo Imager

Executive Summary This report addresses system characterization of the Pléiades Neo satellite and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions. Pléiades Neo is a constellation of four identical very-high-resolution optical satellites operated by Airbus Defence and Space. The first two satellites, Pléiades Neo-3 and -4, were launched in April and August 2021, respectively. The next two satellites, launched in December 2022, did not reach orbit because of Vega-C launch vehicle failure. Pléiades Neo provides several technical improvements to previous Pléiades-HR satellites, including the addition of coastal aerosol (deep blue) and red edge spectral bands, with improved ground sample distance and swath. The Pléiades Neo satellites were designed and built by Airbus Defence and Space with the high-resolution, multispectral imager for Earth imaging and use the S950 optical satellite bus. The high-resolution sensor on Pléiades Neo collects Earth data in the visible and near-infrared region with six bands and a panchromatic band. The satellites can operate off nadir to achieve a revisit of less than 1 day. More information on Pléiades Neo satellites and sensors is available in the “Land Remote Sensing Satellites Online Compendium” ( https://calval.cr.usgs.gov/apps/compendium# ) and from the manufacturer ( https://www.intelligence-airbusds.com/imagery/constellation/pleiades-Neo/ ). The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that Pléiades Neo has an interior geometric performance in the range of 0.01 meter (m; 0.008 pixel) to −0.017 m (−0.014 pixel) in band-to-band registration; an exterior geometric performance in the range of −7.015 m (−0.702 pixel) to 3.846 m (0.385 pixel) offset in comparison to Sentinel-2 using ground control points of 2.2 to 7.2 m (95-percent circular error); a radiometric performance in the range of −0.070 (minimum) to −0.053 (maximum) in offset and 1.107 (minimum) to 1.202 (maximum) in slope; and a spatial performance in the range of 1.002 to 1.226 pixels at full width at half maximum with a modulation transfer function at a Nyquist frequency in the range of 0.22 to 0.34 (bands 2–7).

Open-File Report↗
USGS2026

System characterization report on Tanager

Executive Summary This report addresses the system characterization of the Tanager satellite hyperspectral sensor created by Planet Labs PBC and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the Tanager hyperspectral sensor; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions. This report summarizes the sensor performance of the Tanager based on the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence system characterization process. In summary, we determined that the Tanager exhibits a band- to- band geometric error ranging from −0.074 to 0.097 pixel. Compared to the Landsat Operational Land Imager, geometric offsets ranged from −5.980 meters (−0.20 pixel) to 11.348 meters (0.40 pixel). Radiometric comparisons showed offsets between −0.004 and 0.056 with slopes from 0.830 to 1.066. Spectral shifts are found between 0.65 and 0.75 nanometers. Finally, spatial performance evaluation yielded a point spread function full width at half maximum of 1.27 to 1.75 pixels, a relative edge response of 0.802 to 0.651, and a modulation transfer function at Nyquist of 0.488 to 0.253.

Open-File Report↗
USGS2022

Status and trends of North American bats: Summer occupancy analysis 2010-2019

• We developed an analytical pipeline supported by web-based infrastructure for integrating continental scale bat monitoring data (stationary acoustic, mobile acoustic, and capture records) to estimate summer (May 1–Aug 31) occupancy probabilities and changes in occupancy over time for 12 North American bat species. This serves as one of multiple lines of evidence that inform the status and trends of bat populations. • We analyzed data from a total of 12 bat species (Table 1), 11 of which have tested positive for Pseudogymnoascus destructans (Pd), a fungal pathogen that causes white-nose syndrome (WNS)—a disease that has led to significant rates of mortality for subterranean hibernating bat species in North America. A twelfth species was also selected because of high rates of mortality at wind energy facilities. Additional species were considered but not selected due to data limitations. • We estimated occupancy probabilities for 2010 through 2019 for three species ( Myotis lucifugus , MYLU; Myotis septentrionalis , MYSE; and P erimyotis subflavus , PESU). For an additional nine species, we estimated occupancy probabilities for 2016 through 2019 ( Myotis evotis , MYEV; Myotis grisescens , MYGR; Myotis leibii , MYLE; Myotis thysanodes , MYTH; Myotis volans , MYVO; Myotis yumanensis , MYYU; Eptesicus fuscus , EPFU; Lasionycteris noctivagans , LANO; and Lasiurus cinereus , LACI). • For each species, we provide range-wide occupancy probability predictions (e.g., predicted summer occupancy distribution maps) each year at a spatial resolution of 100 km2 and provide regional estimates of mean occupancy probability aggregated at larger spatial scales (state/province/territory, range-wide). • For each species, we also provide trends over time (average annual change rate and total change rate) in mean occupancy probabilities at multiple spatial scales (state/province/territory, range-wide) and when possible, over multiple timescales (short, medium, long). • Results suggest that over the short-term (2016-2019), two ( Myotis lucifugus and Perimyotis subflavus ) of 12 species have experienced declines in range-wide average occupancy probability with at least 95% certainty. Seven species showed either minor increases or decreases in range-wide average occupancy probability but with less than 95% certainty in both trend indicators. Results over the longer term (eight years and 10 years of sampling) suggest that three hibernating species known to be highly affected by white-nose syndrome ( Myotis lucifugus , Myotis septentrionalis , and Perimyotis subflavus ) have experienced marked declines in range-wide average occupancy probabilities, with severity varying by species and region. Finally, the results for three species ( Eptesicus fuscus , Lasiurus cinereus , Lasionycteris noctivagans ) were inconclusive due to 1) borderline convergence issues in the model fitting procedure which suggests potentially unreliable estimates, 2) failure to reliably distinguish between false positives and true positive detections for ambiguous detections, and 3) largely uninformative covariates for occupancy and detection. • For Myotis lucifugus , Myotis septentrionalis , and Perimyotis subflavus we found meaningful associations in space and time between declining winter populations (likely a result of WNS) and summer occupancy distributions. • The representativeness of sampling data for each species’ status and trend estimates (e.g., state/province/territory) were also evaluated based on the percent of grid cells sampled each year with a goal of understanding the reliability of regional estimates and improving future monitoring efforts. • This work represents the most comprehensive effort to date to model North American bat distributions across their continental ranges. Despite current limitations highlighted in the discussion, the analytical methods and resulting status and trends estimates provide the best available science on summer bat populations across North America and will continue to improve over time as monitoring data sets and analytical methods improve. • Moving forward, our occupancy analyses will continue to improve with submission of more 1) data from currently underrepresented areas (i.e., improved geographic representation), 2) manually-vetted acoustic recordings, 3) capture records, and 4) roost location and count data (summer and winter).

Report↗
USGS2015

Tools for discovering and accessing Great Lakes scientific data

The Great Lakes Restoration Initiative (GLRI) is a multidisciplinary and interagency effort focused on the protection and restoration of the Great Lakes (GL) using the best available science and applying lessons learned from previous studies. The U.S. Geological Survey (USGS) contributes to the GLRI effort by providing resource managers with information and tools needed to meet restoration goals. This includes contributing scientific expertise and delivering findings to the GL community through meaningful information products. One of the strengths of the GLRI is its interagency approach; however, this can create challenges when coordinating the large number of restoration activities being performed by GL governments, tribes, academics, nonprofits, and industry. There is a vast array of data being produced by both the USGS and its partners, and it is crucial that scientists, managers, policymakers, and the public can easily locate the biological, geological, geospatial, and water-resources data being generated. The USGS strives to develop data products that are easy to find, easy to understand, and easy to use through Web-accessible tools that allow users to learn about the breadth and scope of GLRI activities being undertaken by the USGS and its partners. By creating tools that enable data to be shared and reused more easily, the USGS can encourage collaboration and assist the GL community in finding, interpreting, and understanding the information created during GLRI science activities.

Great Lakes↗
USGS2022

A golden era for volcanic gas geochemistry?

The exsolution, rise, expansion, and separation of volatiles from magma provides the driving force behind both effusive and explosive volcanic eruptions. The field of volcanic gas geochemistry therefore plays a key role in understanding volcanism. In this article, we summarize the most important findings of the past few decades and how these shape today’s understanding of volcanic degassing. We argue that the recent advent of automated, continuous geochemical monitoring at volcanoes now allows us to track activity from unrest to eruption, thus providing valuable insights into the behavior of volatiles throughout the entire sequence. In the next 10 years, the research community stands to benefit from the expansion of geochemical monitoring networks to many more active volcanoes. This, along with technical advances in instrumentation, and in particular the increasing role that unoccupied aircraft systems (UAS) and satellite-based observations are likely to play in collecting volcanic gas measurements, will provide a rich dataset for testing hypotheses and developing diagnostic tools for eruption forecasts. The use of consistent, well-documented analytical methods and ensuring free, public access to the collected data with few restrictions will be most beneficial to the advancement of volcanic gas science.

Bulletin of Volcanology↗
USGS2016

Persistent and novel threats to the biodiversity of Kazakhstan’s steppes and semi-deserts

Temperate grasslands have suffered disproportionally from conversion to cropland, degradation and fragmentation. A large proportion of the world’s remaining near-natural grassland is situated in Kazakhstan. We aimed to assess current and emerging threats to steppe and semi-desert biodiversity in Kazakhstan and evaluate conservation research priorities. We conducted a horizon-scanning exercise among conservationists from academia and practice. We first compiled a list of 45 potential threats. These were then ranked by the survey participants according to their perceived severity, the need for research on them, and their novelty. The highest-ranked threats were related to changes in land use (leading to habitat loss and deterioration), direct persecution of wildlife, and rapid infrastructure development due to economic and population growth. Research needs were identified largely in the same areas, and the mean scores of threat severity and research need were highly correlated. Novel threats comprised habitat loss by photovoltaic and wind power stations, climate change and changes in agriculture such as the introduction of biofuels. However, novelty was not correlated with threat severity or research priority, suggesting that the most severe threats are the established ones. Important goals towards more effective steppe and semi-desert conservation in Kazakhstan include more cross-sector collaboration (e.g. by involving stakeholders in conservation and agriculture), greater allocation of funds to under-staffed areas (e.g. protected area management), better representativeness and complementarity in the protected area system and enhanced data collection for wildlife monitoring and threat assessments (including the use of citizen-science databases).

Biodiversity and Conservation↗