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USGS2022

Range-wide population trend analysis for greater sage-grouse (Centrocercus urophasianus)—Updated 1960–2021

Greater sage-grouse ( Centrocercus urophasianus ) are at the center of state and national land use policies largely because of their unique life-history traits as an ecological indicator for health of sagebrush ecosystems. This updated population trend analysis provides state and federal land and wildlife managers with best-available science to help guide current management and conservation plans aimed at benefitting sage-grouse populations. This analysis relied on previously published population trend modeling methodology from Coates and others (2021) and includes the addition of three analytical updates: (1) identification of population nadirs (lowest points within cycles) at the lek (breeding ground) and neighborhood cluster (group of leks) spatial scales, (2) truncation of prior distributions on rate of change in apparent abundance values to more realistic boundaries for leks with missing data, and (3) addition of 2 years of population lek count data (2020 and 2021) to the current dataset (1953–2021). Bayesian state-space models estimated 2.9 percent average annual decline in sage-grouse populations across their geographical range, which varied among subpopulations at the largest scale of analysis, termed climate clusters (2.2–4.6). Cumulative declines were 42.5, 65.6, and 80.1 percent range-wide across short (19 years), medium (35 years), and long (55 years) temporal periods, respectively. These results indicate that range-wide populations continued to decline during 2020 and 2021, although two climate clusters (eastern area and Bi-State area) have shown growth in population abundance in recent years, indicating they have surpassed a recent population abundance nadir.

Data Report↗

USGS2022

Science mission requirements for a globally ranging, riserless drilling vessel for U.S. Scientific Ocean Drilling

Through the collection and analysis of shallow and deep subseafloor sediments, rocks, fluids, and life, scientific ocean drilling has enriched our understanding of the complex Earth system. Among other achievements, scientific ocean drilling has documented the history of Earth’s climate, the waxing and waning of polar ice sheets, the past changes in ocean and atmospheric circulation, the existence and function of microbial life in the subseafloor, the compositional variations in Earth’s crust and underlying mantle, and the physical and chemical processes acting at subduction zones, including those associated with tsunamigenic earthquakes. Over the decades, more than 12,000 articles that depend on analyses of scientific ocean drilling samples and geophysical data have been published, many detailing breakthrough contributions to global knowledge about the Earth system. Approximately 45% of these publications were led by U.S.-affiliated authors (International Ocean Discovery Program Publication Services, 2021). Since the mid-1980s, the workhorse of this multidisciplinary, international research effort has been the riserless D/V JOIDES Resolution, operated by Texas A&M University with funding from the U.S. National Science Foundation (NSF). D/V JOIDES Resolution has conducted the vast majority of scientific ocean drilling expeditions and collected most of the scientific cores over that period, including 82% of the expeditions and 93% of the cores in the last decade alone, despite being one of three platforms that is operated within the International Ocean Discovery Program. However, D/V JOIDES Resolution is approaching the end of its useful life. With a strong commitment to continue scientific ocean drilling beyond the end of the current phase, the community developed a document outlining the research frontiers that should be pursued. Exploring Earth by Scientific Ocean Drilling: 2050 Science Framework (Koppers and Coggon, 2020) describes seven scientific strategic objectives that focus on understanding interconnections within the Earth system and five flagship initiatives that integrate these objectives into long-term research efforts that address issues facing society. Additional elements in the 2050 Science Framework, including STEM education, workforce development, technology development, and innovative applications of data analytics, will advance the goals of scientific ocean drilling. Addressing the 2050 Science Framework also requires building partnerships with allied U.S. and international science programs and strengthening existing ones. To implement a significant portion of the 2050 Science Framework, the U.S. scientific community seeks to lease or acquire a newly built, globally ranging, state-of-the art, riserless drilling vessel. The many and varied technical and human resources requirements for successful accomplishment of scientific and educational goals summarized in this document and described in detail in the 2050 Science Framework require broad community input and careful consideration. Following receipt of NSF’s formal Request for Assistance to the United States Science Support Program (USSSP), the U.S. scientific ocean drilling community conducted a one-year exercise to identify its national scientific needs and priorities in order to determine the Science Mission Requirements (SMRs) presented here. This community effort included: (1) a U.S. community-wide survey to identify the specific operational and technical capabilities critical to addressing science in the 2050 Science Framework; (2) a series of online workshops focusing on critical capabilities identified by the survey; and (3) a large in-person workshop to synthesize the results of the survey and the virtual workshops (Appendix 1). The approach was designed to reach as many participants as possible. Overall, 278 survey responses were received from U.S. community members, representing 104 unique institutions from 39 states and the District of Columbia, and 137 unique individuals participated in the workshops (Appendix 2). The results of this effort comprise two classes of SMRs: Foundational Science Mission Requirements and Primary Science Mission Requirements. Foundational SMRs define minimum criteria for a new riserless drilling vessel that can address significant portions of the 2050 Science Framework. Primary SMRs build upon the Foundational SMRs and will create more robust science opportunities and data collection capabilities, will increase progress in addressing the 2050 Science Framework objectives, and will provide more real-time ship-to-shore interaction to improve science productivity, engagement, and outreach. Modern safety and environmental standards, including meeting standards to access protected waters such as exclusive economic zones, extended continental shelves, or high latitudes, while being cognizant of the vessel’s environmental footprint. Safe and efficient operations in global locations and in water depths from 70 m to 6000+ m, with total drill string length of at least 7000 m. High-quality core and data collection from a range of key subseafloor environments. Advanced heave compensation, dynamic positioning, and drill pipe stability. Modern mud and cement/casing systems. Critical onboard measurements for safety, operational decision-making, documentation of ephemeral properties, mission-specific science, and long-term science goals that extend beyond a single expedition. Designated and appropriate space for sample and data preservation. Highly skilled onboard personnel, including technical staff for curation and core handling; support for safety, time-sensitive, and critical shipboard measurements; computer support; equipment and instrument repair; application support; and data assurance. Primary Science Mission Requirements include: Flexible shipboard space for laboratories and on deck to ensure safe, successful implementation of diverse science objectives and operations. Minimizing contamination of recovered samples. Over-the-side capabilities for science-supporting technology (e.g., remotely operated vehicles, water- column sampling, sediment-water interface sampling). Downhole logging and measurements. Expanded borehole observatory capabilities. Reliable and consistent ship-to-shore communications. NSF’s investment in a new globally ranging, riserless drilling vessel will have a powerful economic multiplier effect, including the infusion of additional science support funds in the United States for training and research, the development of new technologies and tools, and the associated scientific and technical workforce development. The skills and knowledge gained through scientific ocean drilling are translatable to careers in fields such as sustainable energy development (e.g., geothermal and offshore wind), carbon sequestration, data management and cyberinfrastructure, biotechnology, communications, science education, policy, hazard mitigation, and environmental management. The United States is a leader in a well-established and internationally collaborative scientific ocean drilling community. A modern, globally ranging, riserless drilling vessel will allow the United States to expand its leadership position, address broad scientific questions that current capabilities preclude, and cultivate equitable international, multidisciplinary collaborations that will ensure scientific ocean drilling’s future success.

Report↗

USGS2000

The use of mathematical models to predict beach behavior for U.S. coastal engineering: A critical review

A number of assumed empirical relationships (e.g., the Bruun Rule, the equilibrium shoreface profile, longshore transport rate equation, beach length: durability relationship, and the renourishment factor) and deterministic numerical models (e.g., GENESIS, SBEACH) have become important tools for investigating coastal processes and for coastal engineering design in the U.S. They are also used as the basis for making public policy decisions, such as the feasibility of nourishing recreational beaches. A review of the foundations of these relationships and models, however, suggests that they are inadequate for the tasks for which they are used. Many of the assumptions used in analytical and numerical models are not valid in the context of modern oceanographic and geologic principles. We believe the models are oversimplifications of complex systems that are poorly understood. There are several reasons for this, including: (1) poor assumptions and important omissions in model formulation; (2) the use of relationships of questionable validity to predict the morphologic response to physical forcing; (3) the lack of hindsighting and objective evaluation of beach behavior predictions for engineering projects; (4) the incorrect use of model calibration and verification as assertions of model veracity; and (5) the fundamental inability to predict coastal evolution quantitatively at the engineering and planning time and space scales our society assumes and demands. It is essential that coastal geologists, beach designers and coastal modelers understand these model limitations. Each important model assumption must be examined in isolation; incorporating them into a model does not improve their validity. It is our belief that the models reviewed here should not be relied on as a design tool until they have been substantially modified and proven in real-world situations. The 'solution,' however, is not to increase the complexity of a model by increasing the number of variables. What is needed is a thoughtful review of what beach behavior questions should or could be answered by modeling. Viable alternatives to the use of models do exist to predict the behavior of beaches. Three such alternatives to models are discussed for nourished beach design.

Journal of Coastal Research↗

USGS2018

Managing the water-energy-food nexus: Opportunities in Central Asia

This article examines impacts of infrastructure development and climate variability on economic outcomes for the Amu Darya Basin in Central Asia. It aims to identify the most economically productive mix of expanded reservoir storage for economic benefit sharing to occur, in which economic welfare of all riparians is improved. Policies examined include four combinations of storage infrastructure for each of two climate futures. An empirical optimization model is developed and applied to identify opportunities for improving the welfare of Tajikistan, Uzbekistan, Afghanistan, and Turkmenistan. The analysis 1) characterizes politically constrained and economically optimized water-use patterns for these combinations of expanded reservoir storage capacity, 2) describes Pareto-Improving packages of expanded storage capacity that could raise economic welfare for all four riparians, and accounts for impacts for each of two climate scenarios. Results indicate that a combination of targeted water storage infrastructure and efficient water allocation could produce outcomes for which the discounted net present value of benefits are favorable for each riparian. Results identify a framework to provide economic motivation for all riparians to cooperate through development of water storage infrastructure. Our findings illustrate the principle that development of water infrastructure can expand the negotiation space by which all communities can gain economic benefits in the face of limited water supply. Still, despite our optimistic findings, patient and deliberate negotiation will be required to transform potential improvements into actual gains.

Journal of Hydrology↗

USGS2025

Integrating multiple indices of habitat quality to inform habitat management for a sagebrush indicator species

Robust science is needed to inform national resource management and policy decisions. Predictive species habitat maps are frequently employed in conservation decision-making but are often based on a single metric representing habitat quality. We outlined a framework that combines multiple spatially explicit indices of potential habitat quality that could be used to identify and prioritize habitat management areas, using the greater sage-grouse ( Centrocercus urophasianus ; hereafter sage-grouse) as an example species. Due to large-scale changes in sagebrush ecosystems, sage-grouse have suffered significant population declines in recent decades and have become key to land management plans throughout the western United States, where comprehensive habitat maps are crucial to effective conservation efforts. We evaluated habitat selection and survival patterns of sage-grouse across six distinct annual life stages and seasons to generate predictive habitat map surfaces, mapped the distribution of current occupancy, and combined maps of potential selection and survival patterns with space use and occupancy indices to delineate example habitat management categories. Our approach facilitates identification of priority areas to target for habitat preservation and areas where anthropogenic impacts could occur with likely minimal impact to the species. Overall, by combining indices representing selection, survival, and current occupancy, we provide a framework to allow for a flexible and targeted management approach that could be adapted to a wide variety of species.

California, Nevada↗

USGS1981

E-field ratio telluric survey near the Big Maria Mountains, Riverside County, California

The U.S. Geological Survey (USGS) under the Wilderness Act (Public Law 88-577) and the Federal Land Policy and Management Act (Public Law 94-579) has the responsibility, along with the U.S. Bureau of Mines, to survey certain areas in order to determine their mineral resource potential. This report presents results of three electric-field ratio telluric traverses conducted as part of the Bureau of Land Management Wilderness Program in the Big Maria Mountains, Riverside County, Calif. The telluric traverses were run on the southwest side of the Big Maria Mountains in an attempt to define the location of major buried faults near the eroded front of the range. E-field ratio tellurics is a descriptive name applied to the electrical exploration technique used in this survey. The telluric method refers to the measurement of the earth's electric field generated by induction from natural electromagnetic waves arriving at the surface. The E-field ratio telluric method uses a receiving array of three electrodes spaced equidistant and inline. This array is, in effect, two colinear dipoles sharing a common electrode. The potential difference across each dipole is then proportional to the component of the telluric field in the direction of the array. This configuration permits the measurement of the ratio of the telluric field at each dipole in the direction of the dipole line, and hence the name. The traverse data is extended by moving the three-electrode array forward one dipole length so that the forward electrode becomes the center electrode for the next ratio measurement. Electric-field data so obtained are proportional to the square root of the apparent resistivity of the earth at the location of the dipoles. However, because the apparent resistivity can be a function of the dipole direction, it is important to know the orientation of the dipoles with respect to major structures. Because the resistivity of fluid-saturated earth materials is largely dependent on the porosity of the rocks, the salinity of the pore fluid, and the presence of clays or similar material where surface conduction is high, alluvial fill, argillite and similar rocks tend to have low resistivities whereas igneous or high-grade metamorphic rocks have high resistivities. Variation in the electrical properties along a traverse may then be used to infer lithologic or structural changes.

California↗

USGS2006

Trade-offs across space, time, and ecosystem services

Ecosystem service (ES) trade-offs arise from management choices made by humans, which can change the type, magnitude, and relative mix of services provided by ecosystems. Trade-offs occur when the provision of one ES is reduced as a consequence of increased use of another ES. In some cases, a trade-off may be an explicit choice; but in others, trade-offs arise without premeditation or even awareness that they are taking place. Trade-offs in ES can be classified along three axes: spatial scale, temporal scale, and reversibility. Spatial scale refers to whether the effects of the trade-off are felt locally or at a distant location. Temporal scale refers to whether the effects take place relatively rapidly or slowly. Reversibility expresses the likelihood that the perturbed ES may return to its original state if the perturbation ceases. Across all four Millennium Ecosystem Assessment scenarios and selected case study examples, trade-off decisions show a preference for provisioning, regulating, or cultural services (in that order). Supporting services are more likely to be "taken for granted." Cultural ES are almost entirely unquantified in scenario modeling; therefore, the calculated model results do not fully capture losses of these services that occur in the scenarios. The quantitative scenario models primarily capture the services that are perceived by society as more important - provisioning and regulating ecosystem services - and thus do not fully capture trade-offs of cultural and supporting services. Successful management policies will be those that incorporate lessons learned from prior decisions into future management actions. Managers should complement their actions with monitoring programs that, in addition to monitoring the short-term provisions of services, also monitor the long-term evolution of slowly changing variables. Policies can then be developed to take into account ES trade-offs at multiple spatial and temporal scales. Successful strategies will recognize the inherent complexities of ecosystem management and will work to develop policies that minimize the effects of ES trade-offs. Copyright ?? 2006 by the author(s).

Ecology and Society↗

USGS2018

Land cover and land use change

Climate can affect and be affected by changes in land cover (the physical features that cover the land such as trees or pavement) and land use (human management and activities on land, such as mining or recreation). A forest, for instance, would likely include tree cover but could also include areas of recent tree removals currently covered by open grass areas. Land cover and use are inherently coupled: changes in land-use practices can change land cover, and land cover enables specific land uses. Understanding how land cover, use, condition, and management vary in space and time is challenging. Changes in land cover can occur in response to both human and climate drivers. For example, demand for new settlements often results in the permanent loss of natural and working lands, which can result in localized changes in weather patterns, temperature, and precipitation. Aggregated over large areas, these changes have the potential to influence Earth’s climate by altering regional and global circulation patterns, changing the albedo (reflectivity) of Earth’s surface, and changing the amount of carbon dioxide (CO 2 ) in the atmosphere. Conversely, climate change can also influence land cover, resulting in a loss of forest cover from climate-related increases in disturbances, the expansion of woody vegetation into grasslands, and the loss of beaches due to coastal erosion amplified by rises in sea level. Land use is also changed by both human and climate drivers. Land-use decisions are traditionally based on short-term economic factors. Land-use changes are increasingly being influenced by distant forces due to the globalization of many markets. Land use can also change due to local, state, and national policies, such as programs designed to remove cultivation from highly erodible land to mitigate degradation, legislation to address sea level rise in local comprehensive plans, or policies that reduce the rate of timber harvest on federal lands. Technological innovation has also influenced land-use change, with the expansion of cultivated lands from the development of irrigation technologies and, more recently, decreases in demand for agricultural land due to increases in crop productivity. The recent expansion of oil and gas extraction activities throughout large areas of the United States demonstrates how policy, economics, and technology can collectively influence and change land use and land cover. Decisions about land use, cover, and management can help determine society’s ability to mitigate and adapt to climate change.

Report↗

USGS2026

Advances in volcano monitoring driven by the first decade of Sentinel-1 observations

Sentinel-1 has transformed how satellite radar data (SAR and InSAR) are used in volcanology. The systematic, long-term archive and open-access policy means that volcano observatories and research organisations have invested in integrating Sentinel-1 datasets into their monitoring systems. We identify 233 high priority volcanoes and estimate that Sentinel-1 data has been used in peer-reviewed publications for 90 of them. We examine a global archive of 3.3 million automatically processed Sentinel-1 interferograms of volcanoes and use machine learning methods to identify eruptions and periods of unrest. We then review the ways in which InSAR data are being used in different contexts. At frequently erupting basaltic systems in Iceland, Hawaiʻi, the Galápagos , and Piton de la Fournaise, InSAR has become an effective monitoring tool and is integrated with other datasets and models to forecast magma pathways. For large explosive eruptions, deformation measurements often remain challenging, but SAR backscatter is increasingly used to map damaging flows and measure the changing shape of ocean islands. Sentinel-1's long archive provides critical baseline measurements that are vital for measuring slow deformation, capturing new periods of unrest and providing fresh insights into subsurface dynamics. Understanding the drivers of deformation remains challenging and typically relies on integration with external datasets. Future European Space Agency missions have the potential to improve both resolution and coverage providing an even richer dataset to further enhance global volcano monitoring

Erta Ale volcano↗

USGS1981

The Earth Resources Observation Systems data center's training technical assistance, and applications research activities

The Earth Resources Observation Systems (EROS) Data Center (EDO, administered by the U.S. Geological Survey, U.S. Department of the Interior, provides remotely sensed data to the user community and offers a variety of professional services to further the understanding and use of remote sensing technology. EDC reproduces and sells photographic and electronic copies of satellite images of areas throughout the world. Other products include aerial photographs collected by 16 organizations, including the U.S. Geological Survey and the National Aeronautics and Space Administration. Primary users of the remotely sensed data are Federal, State, and municipal government agencies, universities, foreign nations, and private industries. The professional services available at EDC are primarily directed at integrating satellite and aircraft remote sensing technology into the programs of the Department of the Interior and its cooperators. This is accomplished through formal training workshops, user assistance, cooperative demonstration projects, and access to equipment and capabilities in an advanced data analysis laboratory. In addition, other Federal agencies, State and local governments, universities, and the general public can get assistance from the EDC Staff. Since 1973, EDC has contributed to the accelerating growth in development and operational use of remotely sensed data for land resource problems through its role as educator and by conducting basic and applied remote sensing applications research. As remote sensing technology continues to evolve, EDC will continue to respond to the increasing demand for timely information on remote sensing applications. Questions most often asked about EDC's research and training programs include: Who may attend an EDC remote sensing training course? Specifically, what is taught? Who may cooperate with EDC on remote sensing projects? Are interpretation services provided on a service basis? This report attempts to define the goals and objectives of and policies on the following EDC services: Training Program. User Assistance. Data Analysis Laboratory. Cooperative Demonstration Projects. Research Projects.

Open-File Report↗

USGS2019

A draft decision framework for the National Park Service Interior Region 5 bison stewardship strategy

The Department of the Interior Bison Conservation Initiative calls for its bureaus to plan and implement collaborative American bison conservation and to ensure involvement by tribal, state, and local governments and the public in that conservation. Four independently managed and geographically separated National Park Service (NPS) units in Interior Region 5 (IR5) preserve bison and other components of a formerly contiguous Great Plains landscape. Management of bison in IR5 parks has historically been specific to each park, and livestock and range management science informed much of the decision making. In the past two decades, NPS has shifted away from managing bison from this livestock-based perspective towards a wildlife stewardship approach, including ensuring their long-term adaptive potential and considering them as just one part of a complex ecosystem. This shift requires a more holistic and cooperative approach to stewardship that is challenging not only because of limitations in funding and fluctuations in leadership priorities, but also because of the constraints imposed by the parks’ relatively small, fenced areas. The IR5 NPS Bison Stewardship Strategy (“Strategy”) will help the NPS to meet its responsibilities in cooperative stewardship of bison. The Strategy will serve to organize and consolidate the NPS’s legal and policy responsibilities within a framework of collectively defined values and objectives to support the careful and transparent decision-making processes that both guide and transcend park-specific planning. This report describes a preliminary decision framework for the Strategy, including the context, the fundamental objectives, and a range of alternative strategies developed and considered through two workshops and a series of conference calls with NPS personnel, stakeholders, and outside experts with an interest in IR5 NPS bison stewardship. Although not the Strategy itself, this framework serves as the Strategy’s starting point and identifies 14 fundamental objectives, falling in four major themes: Persistence of Wild and Healthy Bison 1. Maximize the long-term persistence of bison in IR5 parks 2. Maximize the long-term adaptive capacity of bison in North America 3. Maximize the wildness of the bison herds 4. Maximize humane treatment of bison, while allowing natural processes to occur Supporting Tribal Buffalo Culture 5. Improve relationships, trust, and communication with Tribes to enhance shared stewardship of bison within and beyond IR5 6. Maximize the number of live, healthy bison that can be transferred to tribal herds Persistence of Native Ecological Communities and Processes 7. Maximize structural and compositional heterogeneity of native prairie plant communities across space and time within each park 8. Maximize the abundance and diversity of animal species of special concern 9. Minimize the loss of native grassland within each park 10. Minimize the abundance of exotic plants in the park landscape 11. Maximize riparian area and wetland integrity Public Outreach 12. Maximize the number of healthy, wild bison that are visible to the public 13. Maximize the safety of visitors 14. Maximize public understanding of the past, present, and future of bison and Native Americans in the Great Plains The terms “minimize” and “maximize” in these objectives describe the desired direction for each individual objective. Finding the right balance among these objectives and any others identified in further work is one of the central challenges in developing the Strategy. To that end, this report also demonstrates and describes potential methods for evaluating how well alternative strategies would achieve each of the fundamental objectives.

Natural Resource Report↗

USGS2024

Simple stated preference questions can enhance transdisciplinary projects: Linking perceived risks with willingness to spray and pay

Transdisciplinary projects can uncover crucial insights on people’s past and future risk-mitigation behavior. We focus on a novel risk context: increasing health threats from ticks on Staten Island, a New York City borough where the combination of high population density and extensive park systems and green spaces has resulted in a rise in locally-acquired tick-transmitted disease cases. We administered a knowledge, attitudes, and practices survey that additionally included simple economic stated preference questions about people’s willingness to spray tick pesticides in the future. We first analyze factors that are correlated with people’s perceptions of two types of risks: exposure to ticks and infection with Lyme disease. Next, we use the nonmarket valuation questions to test people’s willingness to spray and pay as a function of attributes of the hypothetical pesticides, including cost, effectiveness, and type. Across all model specifications, overall willingness to pay (WTP) to spray increases with increases in pesticide effectiveness, as well as with favorable pesticide type (organic). We uncover threshold pesticide effectiveness levels at which WTP to spray turns positive, and we find that lower pesticide effectiveness is required for organic pesticide. Finally, we test how perceived risks and various individual-specific characteristics correlate with WTP to spray. Combinations of higher perceived risks are linked both with higher WTP and lower breakeven pesticide effectiveness. Our work shows that a broad range of variables influence demand for self-protection actions, both directly and indirectly (through their effects on perceived risks). Such insights on people’s tradeoffs carry important policy implications, but they can be missed if economic information is either not elicited or elicited alone.

New York↗

USGS2004

Approaches to simulating the “March of Bricks and Mortar”

Re-creation of the extent of urban land use at different periods in time is valuable for examining how cities grow and how policy changes influence urban dynamics. To date, there has been little focus on the modeling of historical urban extent (other than for ancient cities). Instead, current modeling research has emphasized simulating the cities of the future. Predictive models can provide insights into urban growth processes and are valuable for land-use and urban planners, yet historical trends are largely ignored. This is unfortunate since historical data exist for urban areas and can be used to quantitatively test dynamic models and theory. We maintain that understanding the growth dynamics of a region's past allows more intelligent forecasts of its future. We compare using a spatio-temporal interpolation method with an agent-based simulation approach to recreate the urban extent of Santa Barbara, California, annually from 1929 to 2001. The first method uses current yet incomplete data on the construction of homes in the region. The latter uses a Cellular Automata based model, SLEUTH, to back- or hind-cast the urban extent. The success at historical urban growth reproduction of the two approaches used in this work was quantified for comparison. The performance of each method is described, as well as the utility of each model in re-creating the history of Santa Barbara. Additionally, the models’ assumptions about space are contrasted. As a consequence, we propose that both approaches are useful in historical urban simulations, yet the cellular approach is more flexible as it can be extended for spatio-temporal extrapolation.

California↗

USGS2020

Habitat affinities and at-sea ranging behaviors among main Hawaiian Island seabirds: Breeding seabird telemetry, 2013–2016

Recent Hawaiʻi state clean energy policy mandates and federal interest in developing offshore renewable energy resources have prompted unsolicited lease requests for offshore wind energy infrastructure (OWEI) to be located in ocean waters off Hawaiʻi. This study describing at-sea ranging behaviors for five seabirds was intended to provide new information on Hawaiian breeding seabird distribution at sea, habitat utilization, and ranging behaviors within near-island waters and throughout outer continental shelf (OCS) waters surrounding the main Hawaiian Islands (MHI). We also estimate the percentage of time the five study species spent flying at altitudes equivalent to an expected rotor-swept-zone (RSZ; 30–194 m) for an offshore wind turbine and discuss potential collision risk from OWEI to the seabirds studied here. The MHI supports important seabird breeding populations and individual seabirds can now be equipped with a wide-variety of data loggers and location tracking devices that can provide complex, high-resolution information on movement patterns at sea. In this study, we used GPS loggers and temperature-depth-recorders (TDRs) to examine the at-sea distributions and ranging behaviors of five abundantly breeding species in the MHI: Red-tailed Tropicbird, Laysan Albatross, Wedge-tailed Shearwater, Brown Booby, and Red-footed Booby. We tracked these breeding seabirds from 14 different sites throughout the MHI; study colonies were located on the main islands of Maui, Oʻahu, Kauaʻi, and on associated islets. We used the Residence in Space and Time (RST) algorithm to classify behavior into resting, transiting, and searching/foraging (Torres et al. 2017). We used GPS altitude measurements to examine species-specific flight height and to estimate time spent flying in the RSZ. We mapped rediscretized tracking data for seabirds at each study colony according to behavioral class and trip type (when applicable) using kernel density estimates. During 2014–2016, we obtained GPS and TDR data from 59 and 34 Red-tailed Tropicbirds, respectively. Taken together, individuals revealed a bimodal (short- [~3 h, <100 km range] and long- [>3 d, >800 km range]) trip foraging strategy. While ranging at sea, we estimated that Red-tailed Tropicbirds spend 70.6% (95% confidence interval [CI] 70.1–71.0%) of flight time in the RSZ. TDR data for tropicbirds was noisy and we could not reliably identify dives. During 2014 and 2016, we obtained GPS data from 35 Laysan Albatrosses nesting on Kauaʻi and Oʻahu. Individuals during the mid- to late-chick rearing period engaged in a bimodal short- (<6 d, <400 km range) and long- (>6 d, >2,000 km range) trip foraging strategy. While ranging at sea, we estimated that Laysan Albatrosses spend 2.57% (95% CI 2.50–2.64%) of flight time in the RSZ. During 2013–2015, we obtained GPS and TDR data from 313 and 55 Wedge-tailed Shearwaters, respectively. Considering all the data together, individuals revealed a multi-modal trip duration foraging strategy consisting of intra-day (<24 h, <100 km range), short (<4 d, ~200 km range), and long (>4 d, ~100–400 km range) trips. While ranging at sea, we estimated that Wedge-tailed Shearwaters spend 5.20% (95% CI 5.13–5.27%) of flight time in the RSZ. Wedge-tailed Shearwaters dove to a mean (± SD) depth of 1.78 ± 1.35 m (median = 1.38 m); the deepest dive recorded was to 10.06 m. The mean dive duration for Wedge-tailed Shearwaters was 3.12 ± 3.44 s (median = 1.80 s). During 2014–2015, we obtained GPS and TDR data from 42 and 37 Brown Boobies, respectively. Almost all foraging trips (97%) were single-day trips and we did not detect any bimodality in the distribution of single-day trip durations. Brown Boobies foraged relatively close to their colony (<60 km range) and focused their at-sea use in nearshore, coastal waters off Kauaʻi and Niʻihau. While foraging at sea, we estimated that Brown Boobies spend 3.41% (95% CI 3.16–3.67%) of flight time in the RSZ

Hawaii↗

USGS1969

Disposal of liquid wastes by injection underground--Neither myth nor millennium

Injecting liquid wastes deep underground is an attractive but not necessarily practical means for disposing of them. For decades, impressive volumes of unwanted oil-field brine have been injected, currently about 10,000 acre-feet yearly. Recently, liquid industrial wastes are being injected in ever-increasing quantity. Dimensions of industrial injection wells range widely but the approximate medians are: depth, 2,660 feet; thickness of injection zone, 185 feet; injection rate, 135 gallons per minute; wellhead injection pressure, 185 pounds per square inch. Effects of deep injection are complex and not all are understood clearly. In a responsible society, injection cannot be allowed to put wastes out of mind. Injection is no more than storage--for all time in the case of the most intractable wastes--in underground space of which little is attainable in some areas and which is exhaustible in most areas. Liquid wastes range widely in character and concentration-some are incompatible one with another or with materials of the prospective injection zone; some which are reactive or chemically unstable would require pretreatment or could not be injected. Standards by which to categorize the wastes are urgently desirable. To the end that injection may be planned effectively and administered in orderly fashion, there is proposed an immediate and comprehensive canvass of all the United States to outline injection provinces and zones according to their capacities to accept waste. Much of the information needed to this end is at hand. Such a canvass would consider (1) natural zone, of groundwater circulation, from rapid to stagnant, (2) regional hydrodynamics, (3) safe injection pressures, and (4) geochemical aspects. In regard to safe pressure, definitive criteria would be sought by which to avoid recurrence of earthquake swarms such as seem to have been triggered by injection at the Rocky Mountain Arsenal well near Denver, Colo. Three of the 50 States--Missouri, .Ohio, and Texas-have statutes specifically to regulate injection of industrial wastes. Other States impose widely diverse constraints under unlike administrative authorities. Few, if any, State agencies currently have the staff skills, centralized authority, and financial resources to assure rights of the general public to be spared harm from, and to reap the benefit of accrued experience with, deep injection. Some new, fully competent institutional arrangement appears to be essential, under a unified policy. As required, such an institution might have en echelon components, respectively having nationwide, single State or major province, subprovince, or local jurisdiction.

Circular↗

USGS2021

Modeling moose habitat use by age, sex, and season in Vermont, USA using high-resolution lidar and national land cover data

Moose ( Alces alces ) populations have experienced unprecedented declines along the southern periphery of their range, including Vermont, USA. Habitat management may be used to improve the status of the population and health of individuals. To date, however, Vermont wildlife managers have been challenged to effectively use this important tool due to the lack of fine-scale information on moose space use and habitat characteristics. To assess habitat use, we combined more than 40,000 moose locations collected from radio-collared individuals (n = 74), recent land cover data, and high resolution, 3-dimensional lidar ( light detection and ranging ) data to develop Resource Utilization Functions (RUF) by age (mature and young adult), season (dormant and growth), and sex. Each RUF linked home range use to average habitat conditions within 400 m or 1 km of each 30 m 2 pixel within the home range. Across analyses, the top RUF models included both composition (as measured through the National Land Cover Database) and structure (as measured through lidar) variables, and significantly outperformed models that excluded lidar variables. These findings support the notion that lidar is an effective tool for improving the ability of models to estimate patterns of habitat use, especially for larger bodied mammals. Generally speaking, female moose actively used areas with proportionally more regenerating forest (i.e., forage < 3.0 m) and more mature forest (i.e., canopy structure > 6.0 m), while males actively used more high elevation, mixed forest types. Further, moose exhibited important seasonal differences in habitat use that likely reflect temporal changes in energetic and nutritional requirements and behavior across the year. Moose used areas with proportionally more regenerating forest (i.e., forage < 3.0 m) during the growth period and female moose had strong positive associations with lidar-derived canopy structure during the growth (but not the dormant) period. Ultimately, the resultant maps of habitat use provide a means of informing management activities (e.g., the restoration or alteration of habitats to benefit moose) and policies around land use that may contribute to population recovery.

Vermont↗

USGS2015

Design, analysis, and interpretation of field quality-control data for water-sampling projects

The process of obtaining and analyzing water samples from the environment includes a number of steps that can affect the reported result. The equipment used to collect and filter samples, the bottles used for specific subsamples, any added preservatives, sample storage in the field, and shipment to the laboratory have the potential to affect how accurately samples represent the environment from which they were collected. During the early 1990s, the U.S. Geological Survey implemented policies to include the routine collection of quality-control samples in order to evaluate these effects and to ensure that water-quality data were adequately representing environmental conditions. Since that time, the U.S. Geological Survey Office of Water Quality has provided training in how to design effective field quality-control sampling programs and how to evaluate the resultant quality-control data. This report documents that training material and provides a reference for methods used to analyze quality-control data. Quality-control data are those generated from the collection and analysis of quality-control samples, and are used to estimate the magnitude of errors in the process of obtaining environmental data. “Bias” and “variability” are the terms used in this report for the two types of errors in environmental data that are quantified by the data from quality-control samples. Bias is the systematic error inherent in a method or measurement system. Variability is the random error that occurs in independent measurements. The types of field quality-control samples discussed in this report include blanks, spikes, and replicates. Blanks are samples prepared with water that is intended to be free of measurable constituents that will be analyzed by the laboratory; blanks are used to estimate bias caused by contamination. Spiked samples are modified by addition of specific analytes; spikes are used to determine the performance of analytical methods and to estimate the potential bias due to matrix interference or analyte degradation. Replicate samples are two or more samples that are considered to be essentially identical in composition. Replicates are used to evaluate variability in analytical results. Various sub-types of these quality-control samples are defined and discussed in this report, and guidance is provided for incorporating the proper samples into the design for a project. The concept of inference space is introduced to help determine where and when quality-control samples should be collected as well as which environmental samples are related to a set of quality-control samples. The recommended basic quality-control design incorporates project-specific considerations, such as the objectives and scale of the study, and hydrologic and chemical conditions within the study area. The report provides extensive information about statistical methods used to analyze quality-control data in order to estimate potential bias and variability in environmental data. These methods include construction of confidence intervals on various statistical measures, such as the mean, percentiles and percentages, and standard deviation. The methods are used to compare quality-control results with the larger set of environmental data in order to determine whether the effects of bias and variability might interfere with interpretation of these data. Examples from published reports are presented to illustrate how the methods are applied, how bias and variability are reported, and how the interpretation of environmental data can be qualified based on the quality-control analysis.

Techniques and Methods↗

USGS2022

Integrating Bayesian networks to forecast sea-level rise impacts on barrier island characteristics and habitat availability

Evaluation of sea-level rise (SLR) impacts on coastal landforms and habitats is a persistent need for informing coastal planning and management, including policy decisions, particularly those that balance human interests and habitat protection throughout the coastal zone. Bayesian networks (BNs) are used to model barrier island change under different SLR scenarios that are relevant to management and policy decisions. BNs utilized here include a shoreline change model and two models of barrier island biogeomorphological evolution at different scales (50 and 5 m). These BNs were then linked to another BN to predict habitat availability for piping plovers ( Charadrius melodus ), a threatened shorebird reliant on beach habitats. We evaluated the performance of the two linked geomorphology BNs and further examined error rates by generating hindcasts of barrier island geomorphology and habitat availability for 2014 conditions. Geomorphology hindcasts revealed that model error declined with a greater number of known inputs, with error rates reaching 55% when multiple outputs were hindcast simultaneously. We also found that, although error in predictions of piping plover nest presence/absence increased when outputs from the geomorphology BNs were used as inputs in the piping plover habitat BN, the maximum error rate for piping plover habitat suitability in the fully-linked BNs was only 30%. Our findings suggest this approach may be useful for guiding scenario-based evaluations where known inputs can be used to constrain variables that produce higher uncertainty for morphological predictions. Overall, the approach demonstrates a way to assimilate data and model structures with uncertainty to produce forecasts to inform coastal planning and management.

New York↗