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USGS2007

USGS Tampa Bay Pilot Study

Many of the nation's estuaries have been environmentally stressed since the turn of the 20th century and will continue to be impacted in the future. Tampa Bay, one the Gulf of Mexico's largest estuaries, exemplifies the threats that our estuaries face (EPA Report 2001, Tampa Bay Estuary Program-Comprehensive Conservation and Management Plan (TBEP-CCMP)). More than 2 million people live in the Tampa Bay watershed, and the population constitutes to grow. Demand for freshwater resources, conversion of undeveloped areas to resident and industrial uses, increases in storm-water runoff, and increased air pollution from urban and industrial sources are some of the known human activities that impact Tampa Bay. Beginning on 2001, additional anthropogenic modifications began in Tampa Bat including construction of an underwater gas pipeline and a desalinization plant, expansion of existing ports, and increased freshwater withdrawal from three major tributaries to the bay. In January of 2001, the Tampa Bay Estuary Program (TBEP) and its partners identifies a critical need for participation from the U.S. Geological Survey (USGS) in providing multidisciplinary expertise and a regional-scale, integrated science approach to address complex scientific research issue and critical scientific information gaps that are necessary for continued restoration and preservation of Tampa Bay. Tampa Bay stakeholders identified several critical science gaps for which USGS expertise was needed (Yates et al. 2001). These critical science gaps fall under four topical categories (or system components): 1) water and sediment quality, 2) hydrodynamics, 3) geology and geomorphology, and 4) ecosystem structure and function. Scientists and resource managers participating in Tampa Bay studies recognize that it is no longer sufficient to simply examine each of these estuarine system components individually, Rather, the interrelation among system components must be understood to develop conceptual and predictive modeling tools for effective ecosystem adaptive management. As a multidisciplinary organization, the USGS possesses the capability of developing and coordinating an integrated science strategy for estuarine research founded on partnerships and collaborative efforts, multidisciplinary teams of scientists, and integrated field work, data analysis and interpretation, and product development. The primary role of the USGS in Tamps Bay research was defined with our partners based upon this capability to address estuarine issues using an integrated science approach with a regional perspective and within a national context to complement the numerous ongoing scien efforts by state and local agencies that address local issues within Tamp Bay. Six primary components of the USGS Tamp Bay Study address critical gaps within each of the the four estuarine system components and focus on: 1.) Examining how natural and man-made physical changes affect ecosystem health through mapping and modeling. 2.) Identifying sources and quality of groundwater, surface water, and sediment, 3.) Identifying sources and quality of groundwater, surface water, and sediment, 4.) Assessing the natural and man-made changes affecting wetland health and restoration, 5.) Identifying and measuring the impact of urbanization on seafloor habitats, Providing a web-based digital information management system of information for scientists and the public, including a system that supports the work of those officials who must make decisions that affect the state of the bay. The Tampa Bay Study is in its sixth year and will continue through September 2007. This paper presents a non-inclusive summary of key findings associated with the six primary project components listed above. Component 4 (above) is described in detail in the following chapter 13. More information on the Tampa Bay Study is available from our on-line digital information system for the Tampa Bay Study at http://gulfsci.usgs.gov.

Florida↗

USGS2015

Formulating the American Geophysical Union's Scientific Integrity and Professional Ethics Policy: Challenges and lessons learned

Creating an ethics policy for a large, diverse geosciences organization is a challenge, especially in the midst of the current contentious dialogue in the media related to such issues as climate change, sustaining natural resources, and responding to natural hazards. In 2011, the American Geophysical Union (AGU) took on this challenge, creating an Ethics Task Force to update their ethics policies to better support their new Strategic Plan and respond to the changing scientific research environment. Dialogue with AGU members and others during the course of creating the new policy unveiled some of the following issues to be addressed. Scientific results and individual scientists are coming under intense political and public scrutiny, with the efficacy of the science being questioned. In some cases, scientists are asked to take sides and/or provide opinions on issues beyond their research, impacting their objectivity. Pressure related to competition for funding and the need to publish high quality and quantities of papers has led to recent high-profile plagiarism, data fabrication, and conflict of interest cases. The complexities of a continuously advancing digital environment for conducting, reviewing, and publishing science has raised concerns over the ease of plagiarism, fabrication, falsification, inappropriate peer review, and the need for better accessibility of data and methods. Finally, students and scientists need consistent education and encouragement on the importance of ethics and integrity in scientific research. The new AGU Scientific Integrity and Ethics Policy tries to address these issues and provides an inspirational code of conduct to encourage a responsible, positive, open, honest scientific research environment.

Book chapter↗

USGS2025

Leveraging artificial intelligence and machine learning to advance Chesapeake Bay research and management: A review of status, challenges, and opportunities

The Chesapeake Bay and its watershed (hereafter “Chesapeake Bay region”) have been the focus of extensive restoration efforts for several decades. These restoration efforts are guided by the Chesapeake Bay Watershed Agreement (Chesapeake Executive Council 2014) which outlines 10 goals and 31 measurable outcomes. The Chesapeake Bay is globally recognized as a model for coastal restoration due to long-term investments in monitoring, modeling, implementation and research by the Chesapeake Bay Program (CBP) partnership. These monitoring network spans tidal and non-tidal regions and provides data across multiple scales. Artificial intelligence (AI), particularly machine-learning (ML) and deep learning (DL), has emerged as a powerful tool for analyzing large, complex datasets. These techniques have gained widespread adoption across various disciplines, including ecology, hydrology, and environmental science. In the Bay context, AI/ML is increasingly being used to explore drivers of environmental change, analyze system dynamics, and predict conditions in areas with limited monitoring. The CBP partnership, particularly its Scientific and Technical Advisory Committee (STAC), has increasingly recognized the growing role of AI/ML in watershed and estuarine management. Recent Chesapeake Community Research Symposium sessions and initiatives such as the Chesapeake Global Collaboratory highlight increasing regional momentum to apply big data and AI/ML for environmental solutions. Together, these developments underscore the timely need to explore how AI/ML can help advance Chesapeake Bay restoration and management. This STAC workshop, titled “Leveraging Artificial Intelligence and Machine learning to Advance Chesapeake Bay Research and Management: A review of status, challenges, and opportunities,” was held from February 24-25, 2025, in Edgewater, Maryland to bring together over 50 federal, state, and academic scientists and partners to synthesize the current state of AI/ML applications and identify research gaps in Chesapeake Bay research and management. The workshop focused on three main objectives: 1. Summarize recent AI/ML applications and lessons learned in both tidal and nontidal areas of the Chesapeake Bay region. 2. Identify challenges and gaps in applying AI/ML approaches to Chesapeake Bay data. Such challenges and gaps may include data limitations, harmonization issues, ineffective communication of AI/ML insights, and a lack of coordination among research and management institutions. 3. Develop recommendations and identify opportunities for leveraging AI/ML to address issues across the Chesapeake Bay region. Key areas of focus may include generating new information to support watershed management, delivering AI/MLgenerated insights to managers in a clear and actionable way, and fostering greater collaboration among stakeholders within the CBP Partnership. Workshop participants engaged in science presentations and breakout sessions to develop recommendations for advancing the integration of AI/ML techniques into research and management across the Chesapeake Bay region. By synthesizing current applications, identifying challenges, and exploring new opportunities, the workshop has provided valuable insights and recommendations for better leveraging AI/ML approaches to support the success of Bay restoration efforts. Together, these recommendations provide a roadmap for enhancing data-driven, science-based decision making aligned with the goals and outcomes of the Chesapeake Bay Watershed Agreement.

Delaware, Maryland, Virginia↗

USGS2013

Louisiana Barrier Island Comprehensive Monitoring (BICM) Program Summary Report: Data and Analyses 2006 through 2010

The Barrier Island Comprehensive Monitoring (BICM) program was implemented under the Louisiana Coastal Area Science and Technology (LCA S&T) office as a component of the System Wide Assessment and Monitoring (SWAMP) program. The BICM project was developed by the State of Louisiana (Coastal Protection Restoration Authority [CPRA], formerly Department of Natural Resources [DNR]) to complement other Louisiana coastal monitoring programs such as the Coastwide Reference Monitoring System-Wetlands (CRMS-Wetlands) and was a collaborative research effort by CPRA, University of New Orleans (UNO), and the U.S. Geological Survey (USGS). The goal of the BICM program was to provide long-term data on the barrier islands of Louisiana that could be used to plan, design, evaluate, and maintain current and future barrier-island restoration projects. The BICM program used both historical and newly acquired (2006 to 2010) data to assess and monitor changes in the aerial and subaqueous extent of islands, habitat types, sediment texture and geotechnical properties, environmental processes, and vegetation composition. BICM datasets included aerial still and video photography (multiple time series) for shoreline positions, habitat mapping, and land loss; light detection and ranging (lidar) surveys for topographic elevations; single-beam and swath bathymetry; and sediment grab samples. Products produced using BICM data and analyses included (but were not limited to) storm-impact assessments, rate of shoreline and bathymetric change, shoreline-erosion and accretion maps, high-resolution elevation maps, coastal-shoreline and barrier-island habitat-classification maps, and coastal surficial-sediment characterization maps. Discussions in this report summarize the extensive data-collection efforts and present brief interpretive analyses for four coastal Louisiana geographic regions. In addition, several coastal-wide and topical themes were selected that integrate the data and analyses within a broader coastal context: (1) barrier-shoreline evolution driven by rapid relative sea-level rise (RSLR), (2) hurricane impacts to the Chandeleur Islands and likelihood of island recovery, (3) impact of tropical storms on barrier shorelines, (4) Barataria Bay tidal-inlet management, and (5) habitat changes related to RSLR. The final theme addresses potential future goals of the BICM program, including rotational annual to semi-decadal monitoring, proposed new-data collection, how to incorporate technological advances with previous data-collection and monitoring protocols, and standardizing methods and quality-control assessments for continued coastal monitoring and restoration.

Louisiana↗

USGS2011

Geodatabase of Wyoming statewide oil and gas drilling activity to 2010

The U.S. Geological Survey (USGS) compiled a geographic information system (GIS) of Wyoming statewide historical oil and gas drilling activity for the Wyoming Landscape Conservation Initiative (WLCI). The WLCI is representative of the partnerships being formed by the USGS with other Department of the Interior bureaus, State and local agencies, industry, academia, and private landowners that are committed to maintaining healthy landscapes, sustaining wildlife, and preserving recreational and grazing uses as energy resources development progresses in southwestern Wyoming. This product complements the 2009 USGS publication on oil and gas development in southwestern Wyoming http://pubs.usgs.gov/ds/437/) by approximating, based on database attributes, the time frame of drilling activity for each well (start and stop dates). This GIS product also adds current oil and gas drilling activity not only in the area encompassing the WLCI, but also statewide. Oil and gas data, documentation, and spatial data processing capabilities are available and can be downloaded from the USGS website. These data originated from the Wyoming Oil and Gas Conservation Commission (WOGCC), represent decades of oil and gas drilling (1900 to 2010), and will facilitate a landscape-level approach to integrated science-based assessments, resource management and land-use decision making.

Wyoming↗

USGS2009

Coregistration of Mars Orbiter Laser Altimeter (MOLA) topography with high-resolution Mars images

Spacecraft continue to send back extraordinary amounts of data from Mars leaving scientists with the considerable task of analyzing an ever-increasing wealth of information. There are abundant uses for coregistered topography and images, but coregistering various datasets can be time-consuming and labor-intensive. We have developed a set of C-shell Unix scripts and Interactive Data Language (IDL) programs that overlay individual Mars Orbiter Laser Altimeter topography footprints on high-resolution Mars images including those from the Mars Orbiter Camera (MOC), the High Resolution Imaging Science Experiment (HiRISE), and the Context Camera (CTX). After all programs are installed, initial file customizations are made, and raw data are obtained, a user enters only three commands to overlay color-coded, scaled, and labeled topographic data on a high-resolution image. The codes have a variety of options including incremental labeling, zooming in on the topography, and shifting large-scale features to align with topography. They can be used as a group or individually. Our codes minimize human interaction in the coregistration process and produce usable, effective products.

Computers & Geosciences↗

USGS2007

A Science Plan for a Comprehensive Regional Assessment of the Atlantic Coastal Plain Aquifer System in Maryland

The Maryland Coastal Plain region is, at present, largely dependent upon ground water for its water supply. Decades of increasing pumpage have caused ground-water levels in parts of the Maryland Coastal Plain to decline by as much as 2 feet per year in some areas of southern Maryland. Continued declines at this rate could affect the long-term sustainability of ground-water resources in Maryland's heavily populated Coastal Plain communities and the agricultural industry of the Eastern Shore. In response to a recommendation in 2004 by the Advisory Committee on the Management and Protection of the State's Water Resources, the Maryland Geological Survey and the U.S. Geological Survey have developed a science plan for a comprehensive assessment that will provide new scientific information and new data management and analysis tools for the State to use in allocating ground water in the Coastal Plain. The comprehensive assessment has five goals aimed at improving the current information and tools used to understand the resource potential of the aquifer system: (1) document the geologic and hydrologic characteristics of the aquifer system in the Maryland Coastal Plain and appropriate areas of adjacent states; (2) conduct detailed studies of the regional ground-water-flow system and water budget for the aquifer system; (3) improve documentation of patterns of water quality in all Coastal Plain aquifers, including the distribution of saltwater; (4) enhance ground-water-level, streamflow, and water-quality-monitoring networks in the Maryland Coastal Plain; and (5) develop science-based tools to facilitate sound management of the ground-water resources in the Maryland Coastal Plain. The assessment, as designed, will be conducted in three phases and if fully implemented, is expected to take 7 to 8 years to complete. Phase I, which was initiated in January 2006, is an effort to assemble all the information and investigation tools needed to do a more comprehensive assessment of the aquifer system. The work will include updating the hydrogeologic framework, developing a Geographic Information System-based aquifer information system, refinement of water-use information, assessment of existing water-quality data, and development of detailed plans for ground-water-flow and management models. Phase II is an intensive study phase during which a regional ground-water-flow model will be developed and calibrated for the entire region of Maryland in the Atlantic Coastal Plain as well as appropriate areas of Delaware and Virginia. The model will be used to simulate flow and water levels in the aquifer system and to study the water budget of the system. The model analysis will be based on published information but will be supplemented with field investigations of recharge and leakage in the aquifer system. Localized and finely discretized ground-water-flow models that are embedded in the regional model will be developed for selected areas of heavy withdrawals. Other modeling studies will be conducted to better understand flow in the unconfined parts of the aquifer system and to support the recharge studies. Phase II will also include selected water-quality studies and a study to determine how hydrologic and water-quality-monitoring networks need to be enhanced to appropriately assess the sustainability of the Coastal Plain aquifer system. Phase III will be largely devoted to the development and application of a ground-water optimization model. This model will be linked to the ground-water-flow model to create a model package that can be used to test different water-management scenarios. The management criteria that will be used to develop these scenarios will be determined in consultation with a variety of state and local stakeholders and policy makers in Phases I and II of the assessment. The development of the aquifer information system is a key component of the assessment. The system will store all relevant aquifer data

Open-File Report↗

USGS2023

Long-term water-quality constituent trends in the Little Arkansas River, south-central Kansas, 1995–2021

The Equus Beds aquifer and Cheney Reservoir are primary sources for the city of Wichita’s current (2023) water supply. The Equus Beds aquifer storage and recovery (ASR) project was developed by the city of Wichita in the early 1990s to meet future water demands using the Little Arkansas River as an artificial aquifer recharge water source during above-base-flow conditions. Little Arkansas River water is removed from the river at an ASR Facility intake structure, treated using National Primary Drinking Water Regulations as a guideline, and is infiltrated into the Equus Beds aquifer through recharge basins or injected into the aquifer through recharge wells for later use. The U.S. Geological Survey, in cooperation with the city of Wichita, completed this study to quantify and characterize Little Arkansas River water-quality data. Data in this report can be used to evaluate changing conditions, provide science-based information for decision making, and help meet regulatory requirements. Continuous (hourly) physicochemical properties were measured, and discrete water-quality samples were collected from three Little Arkansas River sites located along the easternmost extent of the Equus Beds aquifer during 1995 through 2021 over a range of streamflow conditions. The Little Arkansas River at Highway 50 near Halstead, Kansas, streamgage (U.S. Geological Survey station 07143672; hereafter referred to as the “Highway 50 site”) is located upstream from the other two sites, and the Little Arkansas River near Sedgwick, Kans., streamgage (U.S. Geological Survey station 07144100; hereafter referred to as the “Sedgwick site”) is located downstream from the other two sites; these two sites bracket most of the easternmost part of the Equus Beds aquifer. The Little Arkansas River upstream of ASR Facility near Sedgwick, Kans., streamgage (U.S. Geological Survey station 375350097262800; hereafter referred to as the “Upstream ASR site”) is located between the Highway 50 and Sedgwick sites, about 14.7 river miles (mi) downstream from the Highway 50 site, about 1.7 river mi upstream from the Sedgwick site, and immediately upstream from the ASR Facility intake structure. Surrogate models for water-quality constituents of interest (including bromide, dissolved organic carbon, 2-chloro-4-isopropylamino-6-amino- s -triazine [deethylatrazine], atrazine, and metolachlor) were updated or developed using continuously measured and concomitant discrete data. These surrogate models, along with previously developed regression models, were used to compute concentrations (at the Highway 50, Sedgwick, and Upstream ASR sites) and loads (at the Highway 50 and Sedgwick sites) during the study period. Federal criteria were used to evaluate water quality. Where applicable, water-quality data were compared to Federal national drinking-water regulations. Flow-normalized water-quality constituent trends were evaluated using Weighted Regressions on Time, Discharge, and Season (WRTDS) statistical models and water-quality trends were described using WRTDS bootstrap tests. Continuously computed primary ion concentrations were generally larger at the Highway 50 site compared to the Sedgwick site. During the study period, the Federal secondary maximum contaminant level (SMCL) for dissolved solids was exceeded 57 percent of the time at the Highway 50 site and 38 percent of the time at the Sedgwick site. Computed bromide concentrations were larger at the Highway 50 site and exceeded the city of Wichita treatment threshold about 70, 21, and 19 percent of the time at the Highway 50, Sedgwick, and Upstream ASR sites, respectively. Chloride concentrations exceeded the Federal SMCL about 16 percent of the time at the Highway 50 site and did not exceed the SMCL at the Sedgwick site. Continuous arsenic concentrations exceeded the Federal Maximum Contaminant Level (MCL) 9 to 15 percent of the time at the Sedgwick and Highway 50 sites, respectively, during the study. Atrazine concentrations exceeded the Federal MCL 10 percent of the time at the Highway 50 and Sedgwick sites and 14 percent of the time at the Upstream ASR site during the study; computed glyphosate concentrations at the Sedgwick site never exceeded the MCL during the study. Little Arkansas River flow-normalized primary ion concentrations during 1995 through 2021 generally had downward trends and decreases were generally larger at the Highway 50 site compared to the Sedgwick site. Dissolved solids and chloride concentrations decreased at the Highway 50 and Sedgwick sites. Bromide had no trend at the Highway 50 site and a downward trend at the Sedgwick site. Nitrate plus nitrite and total phosphorus concentrations had upward trends at the Highway 50 site but downward trends at the Sedgwick site, whereas total organic carbon had upward trends at both sites. Nitrate plus nitrite, total nitrogen, total phosphorus, and total organic carbon fluxes had upward trends at the Highway 50 and Sedgwick sites. Suspended-sediment concentrations had an upward trend at the Highway 50 site and had no trend at the Sedgwick site. Arsenic concentrations had downward trends at the Highway 50 and Sedgwick sites. About one-quarter to one-half of the Little Arkansas River loads, including nutrients and sediment, were transported during 1 percent of the time during the study. Because streamflows are highly sensitive to climatic variation and an increase of extreme precipitation events in the Great Plains is expected, similar disproportionately large pollutant loading events may increase into the future. Continuous measurement of physicochemical properties in near-real time allowed characterization of Little Arkansas River surface water during conditions and time scales that would not have been possible otherwise and served as a complement to discrete water-quality sampling. Continuation of this water-quality monitoring will provide data to characterize changing conditions in the Little Arkansas River and possibly identify new and changing trends. Information in this report allows the city of Wichita to make informed municipal water-supply decisions using past and present water-quality conditions and trends in the watershed.

Kansas↗

USGS2009

U.S. Geological Survey Science for the Wyoming Landscape Conservation Initiative - 2008 Annual Report

The Wyoming Landscape Conservation Initiative (WLCI) was launched in 2007 in response to concerns about threats to the State's world class wildlife resources, especially the threat posed by rapidly increasing energy development in southwest Wyoming. The overriding purpose of the WLCI is to assess and enhance aquatic and terrestrial habitats at a landscape scale, while facilitating responsible energy and other types of development. The WLCI includes partners from Federal, State, and local agencies, with participation from public and private entities, industry, and landowners. As a principal WLCI partner, the U.S. Geological Survey (USGS) provides multidisciplinary scientific and technical support to inform decisionmaking in the WLCI. To address WLCI management needs, USGS has designed and implemented five integrated work activities: (1) Baseline Synthesis, (2) Targeted Monitoring and Research, (3) Integration and Coordination, (4) Data and Information Management, and (5) Decisionmaking and Evaluation. Ongoing information management of data and products acquired or generated through the integrated work activities will ensure that crucial scientific information is available to partners and stakeholders in a readily accessible and useable format for decisionmaking and evaluation. Significant progress towards WLCI goals has been achieved in many Science and Technical Assistance tasks of the work activities. Available data were identified, acquired, compiled, and integrated into a comprehensive database for use by WLCI partners and to support USGS science activities. A Web-based platform for sharing these data and products has been developed and is already in use. Numerous map products have been completed and made available to WLCI partners, and other products are in progress. Initial conceptual, habitat, and climate change models have been developed or refined. Monitoring designs for terrestrial and aquatic indicators have been completed, pilot data have been collected for terrestrial indicators, and evaluations of alternative monitoring designs are underway. Initial models and map products have been developed for assessing vegetation, surface disturbance, oil and gas resources, mineral resources, surficial geology, invasive species, aspen treatments, ungulate migration corridors, greater sage-grouse (Centrocercus urophasianus), pygmy rabbits (Brachylagus idahoensis), and songbirds, and data were collected or compiled to validate and refine the models. Coordination and collaboration among partners has led to the production of several documents addressing WLCI objectives, strategies, and guiding principles, and has facilitated implementation of on-the-ground habitat treatments.

Open-File Report↗

USGS2021

Current activity on the Martian surface: A key subject for future exploration

One of the fundamental discoveries in Mars science in the last decade has been the extent and importance of current surface activity. Recent results have shifted our view of Mars from a world where the most interesting geologic events were in the distant past (similar to the Moon) to a world that undergoes active evolution and one where understanding the present is key to deciphering the planet’s history. When input was requested for the last Planetary Science Decadal Survey, some observations of surface changes had been published, but the number of detections was small and their significance not fully appreciated. Since that time, detections have proliferated, driven primarily by the long-term operation of the Mars Reconnaissance Orbiter (MRO) and the High Resolution Imaging Science Experiment (HiRISE) as well as landed observations of aeolian activity. In addition to observed changes, theory suggests that additional important surface processes are likely active but not yet observed because orbital data are limited in space and time and landed studies are rare. Understanding current Martian surface processes is a fundamental science question in itself, as it provides a test for physical and terrestrial analog-based models of specific geological processes acting under non-Earth planetary and environmental conditions. It is also an essential step for reading Mars’ geologic history and providing input to climate models: without understanding current dynamic processes, we cannot understand how they have varied during recent climate cycles, nor how they are reflected in ancient rock or modern ice records. Understanding the rates and types of current surface activity is also highly relevant to selecting geological samples, setting Planetary Protection rules, and understanding the hazards and environment that would be experienced by future human explorers.

Bulletin of the AAS↗

USGS2019

Fault fictions: Systematic biases in the conceptualization of fault-zone architecture

Mental models are a human's internal representation of the real world and have an important role in the way we understand and reason about uncertainties, explore potential options and make decisions. Mental models have not yet received much attention in geosciences, yet systematic biases can affect any geological investigation: from how the problem is conceived, through selection of appropriate hypotheses and data collection/processing methods, to the conceptualization and communication of results. We draw on findings from cognitive science and system dynamics, with knowledge and experiences of field geology, to consider the limitations and biases presented by mental models in geoscience, and their effect on predictions of the physical properties of faults in particular. We highlight biases specific to geological investigations and propose strategies for debiasing. Doing so will enhance how multiple data sources can be brought together, and minimize controllable geological uncertainty to develop more robust geological models. Critically, there is a need for standardized procedures that guard against biases, permitting data from multiple studies to be combined and communication of assumptions to be made. While we use faults to illustrate potential biases in mental models and the implications of these biases, our findings can be applied across the geosciences.

Special Publications↗

USGS2014

Sediment data collected in 2012 from the northern Chandeleur Islands, Louisiana

As part of the Barrier Island Evolution Research project, scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center collected sediment samples from the northern Chandeleur Islands in March and September 2012. The overall objective of this project, which integrates geophysical (bathymetric, seismic, and topographic) and sedimentologic data, is to better understand the depositional and erosional processes that drive the morphologic evolution of barrier islands over annual to interannual timescales (1 to 5 years). Between June 2010 and April 2011, in response to the Deepwater Horizon oil spill, the State of Louisiana constructed a sand berm extending more than 14 kilometers along the northern Chandeleur Islands platform. The construction of the berm provided a unique opportunity to investigate how this new sediment source will interact with and affect the morphologic evolution of the barrier-island system. Data collected from this study will be used to describe differences in the physical characteristics and spatial distribution of sediments both along the axis of the berm and also along transects across the berm and onto the adjacent barrier island. Comparison of these data with data from subsequent sampling efforts will provide information about sediment interactions and movement between the berm and the natural island platform, improving our understanding of short-term morphologic change and processes in this barrier-island system. This data series serves as an archive of sediment data collected in March and September 2012 from the Chandeleur Islands sand berm and adjacent barrier-island environments. Data products include descriptive core logs, core photographs and x-radiographs, results of sediment grain-size analyses, sample location maps, and Geographic Information System data files with accompanying formal Federal Geographic Data Committee metadata.

Louisiana↗

USGS2003

Water-quality, bed-sediment, and biological data, for streams in the upper Prickly Pear Creek watershed, Montana, 2001

The upper Prickly Pear Creek watershed encompasses the upstream 15 miles of Prickly Pear Creek, south of Helena, Montana (fig. 1). The headwaters of Prickly Pear Creek and its tributaries (Beavertown Creek, Clancy Creek, Dutchman Creek, Golconda Creek, Lump Gulch, Spring Creek, and Warm Springs Creek) are primarily in the Helena National Forest, whereas the central part of the watershed primarily is within either Bureau of Land Management (BLM) or privately owned property. Three mining districts are present in the upper Prickly Pear Creek watershed: Alhambra, Clancy, and Colorado. Numerous prospects, adits, tailings piles, mills, dredge piles, and mines (mostly inactive) are located throughout the watershed. These districts contain polymetallic (Ag, Au, Cu, Pb, Zn) vein deposits and precious-metal (Au-Ag) vein and disseminated deposits that were exploited beginning in the 1860’s. Placer Au deposits in the major streams were extensively mined in the late 1800’s and early 1900’s. As part of a cooperative effort with Federal land management agencies, the U.S. Geological Survey (USGS) is currently using an integrated approach to investigate two mining impacted watersheds in the western United States (the Animas River in Colorado and the Boulder River in Montana). These studies provide the USDA Forest Service and BLM scientific data for implementing informed land-management decisions regarding cleanup of abandoned mine lands within each watershed. A similar integrated-science approach will be used to characterize the upper Prickly Pear Creek watershed with respect to water and streambed sediment chemistry, aquatic biota, and geologic framework. This integrated database presents data that will be used to identify important pathways of metals movement and biological impacts, thereby guiding resource management decisions of land-managers in several publications that are in preparation. Watershed-level characterization in terms of water quality, streambed sediment chemistry, and fish health will facilitate determinations of whether removal of contaminated materials or other cleanup activities are necessary, planning of short- and long-term restoration efforts, and development of a monitoring plan to document cleanup effectiveness.

Montana↗

USGS2010

Geographic information system datasets of regolith-thickness data, regolith-thickness contours, raster-based regolith thickness, and aquifer-test and specific-capacity data for the Lost Creek Designated Ground Water Basin, Weld, Adams, and Arapahoe Counties, Colorado

These datasets were compiled in support of U.S. Geological Survey Scientific-Investigations Report 2010-5082-Hydrogeology and Steady-State Numerical Simulation of Groundwater Flow in the Lost Creek Designated Ground Water Basin, Weld, Adams, and Arapahoe Counties, Colorado. The datasets were developed by the U.S. Geological Survey in cooperation with the Lost Creek Ground Water Management District and the Colorado Geological Survey. The four datasets are described as follows and methods used to develop the datasets are further described in Scientific-Investigations Report 2010-5082: (1) ds507_regolith_data: This point dataset contains geologic information concerning regolith (unconsolidated sediment) thickness and top-of-bedrock altitude at selected well and test-hole locations in and near the Lost Creek Designated Ground Water Basin, Weld, Adams, and Arapahoe Counties, Colorado. Data were compiled from published reports, consultant reports, and from lithologic logs of wells and test holes on file with the U.S. Geological Survey Colorado Water Science Center and the Colorado Division of Water Resources. (2) ds507_regthick_contours: This dataset consists of contours showing generalized lines of equal regolith thickness overlying bedrock in the Lost Creek Designated Ground Water Basin, Weld, Adams, and Arapahoe Counties, Colorado. Regolith thickness was contoured manually on the basis of information provided in the dataset ds507_regolith_data. (3) ds507_regthick_grid: This dataset consists of raster-based generalized thickness of regolith overlying bedrock in the Lost Creek Designated Ground Water Basin, Weld, Adams, and Arapahoe Counties, Colorado. Regolith thickness in this dataset was derived from contours presented in the dataset ds507_regthick_contours. (4) ds507_welltest_data: This point dataset contains estimates of aquifer transmissivity and hydraulic conductivity at selected well locations in the Lost Creek Designated Ground Water Basin, Weld, Adams, and Arapahoe Counties, Colorado. This dataset also contains hydrologic information used to estimate transmissivity from specific capacity at selected well locations. Data were compiled from published reports, consultant reports, and from well-test records on file with the U.S. Geological Survey Colorado Water Science Center and the Colorado Division of Water Resources.

Data Series↗

USGS2025

U.S. Geological Survey Pollinator Science Strategy, 2025–35—A Review and Look Forward

This “U.S. Geological Survey Pollinator Science Strategy, 2025–35—A Review and Look Forward” (“Pollinator Science Strategy”) describes the science vision of the U.S. Geological Survey (USGS) to support management, conservation, and policy decisions on animal pollinators and their habitats. As the science arm of the Department of the Interior, the USGS has a primary role in providing scientific information to natural resource managers and policymakers across the United States. This “Pollinator Science Strategy” was drafted by a team of USGS pollinator researchers and was further developed through feedback from Federal, State, Tribal, nongovernmental organizations, and industry partners. This “Pollinator Science Strategy” highlights the USGS’s role in the research to promote healthy pollinator populations and address partner information gaps so they can make more informed management decisions. By outlining the importance of USGS science in addressing the information needs of other agencies, organizations, and the public, the “Pollinator Science Strategy” reaffirms the USGS’s commitment to pollinator research and showcases our research priorities for 2025–35. With more than 300 research centers nationally, the USGS is equipped to address pollinator science across scales of complexity and geographic range. USGS pollinator science is organized according to the following five thematic areas: Assessing species ecology, distributions, and natural history requirements. Tracking species status and trends. Understanding species threats and stressors. Informing restoration and management actions. Developing novel methods for improving pollinator research, monitoring, and population outcomes that can benefit our Nation. Our pollinator information products and associated data are made widely available to the public to ensure scientific transparency and accessibility. This “Pollinator Science Strategy” concludes with several research goals that the USGS will work towards from 2025 to 2035, representing our vision for USGS science. These research goals include synthesizing and modernizing the latest information on pollinator threats, developing research that assists managers with habitat design and restoration, providing training to partners on native bee identification and monitoring design, and developing new technologies for assessing the status and trends of our nation’s pollinators.

Circular↗

USGS2005

Collection and analysis of high-resolution elevation data for the Lincoln Lidar Project, Lincoln, Nebraska, 2004

The Lincoln Lidar Project was a partnership developed between the U.S. Geological Survey National Center for Earth Resources Observations and Science (EROS), Lancaster County and the city of Lincoln, Nebraska. This project demonstrated a successful planning, collection, analysis and integration of high-resolution elevation information using Light Detection and Ranging, (Lidar) data. This report describes the partnership developed to collect local Lidar data and transform the data into information useable at local to national levels. This report specifically describes project planning, quality assurance, processing, transforming raw Lidar points to useable data layers, and visualizing and disseminating the raw and final products.

Nebraska↗

USGS2015

Automated calculation of surface energy fluxes with high-frequency lake buoy data

Lake Heat Flux Analyzer is a program used for calculating the surface energy fluxes in lakes according to established literature methodologies. The program was developed in MATLAB for the rapid analysis of high-frequency data from instrumented lake buoys in support of the emerging field of aquatic sensor network science. To calculate the surface energy fluxes, the program requires a number of input variables, such as air and water temperature, relative humidity, wind speed, and short-wave radiation. Available outputs for Lake Heat Flux Analyzer include the surface fluxes of momentum, sensible heat and latent heat and their corresponding transfer coefficients, incoming and outgoing long-wave radiation. Lake Heat Flux Analyzer is open source and can be used to process data from multiple lakes rapidly. It provides a means of calculating the surface fluxes using a consistent method, thereby facilitating global comparisons of high-frequency data from lake buoys.

Environmental Modelling and Software↗

USGS2017

Ecology and space: A case study in mapping harmful invasive species

The establishment and invasion of non-native plant species have the ability to alter the composition of native species and functioning of ecological systems with financial costs resulting from mitigation and loss of ecological services. Spatially documenting invasions has applications for management and theory, but the utility of maps is challenged by availability and uncertainty of data, and the reliability of extrapolating mapped data in time and space. The extent and resolution of projections also impact the ability to inform invasive species science and management. Early invasive species maps were coarse-grained representations that underscored the phenomena, but had limited capacity to direct management aside from development of watch lists for priorities for prevention and containment. Integrating mapped data sets with fine-resolution environmental variables in the context of species-distribution models allows a description of species-environment relationships and an understanding of how, why, and where invasions may occur. As with maps, the extent and resolution of models impact the resulting insight. Models of cheatgrass ( Bromus tectorum ) across a variety of spatial scales and grain result in divergent species-environment relationships. New data can improve models and efficiently direct further inventories. Mapping can target areas of greater model uncertainty or the bounds of modeled distribution to efficiently refine models and maps. This iterative process results in dynamic, living maps capable of describing the ongoing process of species invasions.

Book chapter↗