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USGS2015

Incorporating induced seismicity in the 2014 United States National Seismic Hazard Model: results of the 2014 workshop and sensitivity studies

The U.S. Geological Survey National Seismic Hazard Model for the conterminous United States was updated in 2014 to account for new methods, input models, and data necessary for assessing the seismic ground shaking hazard from natural (tectonic) earthquakes. The U.S. Geological Survey National Seismic Hazard Model project uses probabilistic seismic hazard analysis to quantify the rate of exceedance for earthquake ground shaking (ground motion). For the 2014 National Seismic Hazard Model assessment, the seismic hazard from potentially induced earthquakes was intentionally not considered because we had not determined how to properly treat these earthquakes for the seismic hazard analysis. The phrases “potentially induced” and “induced” are used interchangeably in this report, however it is acknowledged that this classification is based on circumstantial evidence and scientific judgment. For the 2014 National Seismic Hazard Model update, the potentially induced earthquakes were removed from the NSHM’s earthquake catalog, and the documentation states that we would consider alternative models for including induced seismicity in a future version of the National Seismic Hazard Model. As part of the process of incorporating induced seismicity into the seismic hazard model, we evaluate the sensitivity of the seismic hazard from induced seismicity to five parts of the hazard model: (1) the earthquake catalog, (2) earthquake rates, (3) earthquake locations, (4) earthquake Mmax (maximum magnitude), and (5) earthquake ground motions. We describe alternative input models for each of the five parts that represent differences in scientific opinions on induced seismicity characteristics. In this report, however, we do not weight these input models to come up with a preferred final model. Instead, we present a sensitivity study showing uniform seismic hazard maps obtained by applying the alternative input models for induced seismicity. The final model will be released after further consideration of the reliability and scientific acceptability of each alternative input model. Forecasting the seismic hazard from induced earthquakes is fundamentally different from forecasting the seismic hazard for natural, tectonic earthquakes. This is because the spatio-temporal patterns of induced earthquakes are reliant on economic forces and public policy decisions regarding extraction and injection of fluids. As such, the rates of induced earthquakes are inherently variable and nonstationary. Therefore, we only make maps based on an annual rate of exceedance rather than the 50-year rates calculated for previous U.S. Geological Survey hazard maps.

Open-File Report↗

USGS2015

Evaluation and comparison of methods to estimate irrigation withdrawal for the National Water Census Focus Area Study of the Apalachicola-Chattahoochee-Flint River Basin in southwestern Georgia

Methods to estimate irrigation withdrawal using nationally available datasets and techniques that are transferable to other agricultural regions were evaluated by the U.S. Geological Survey as part of the Apalachicola-Chattahoochee-Flint (ACF) River Basin focus area study of the National Water Census (ACF–FAS). These methods investigated the spatial, temporal, and quantitative distributions of water withdrawal for irrigation in the southwestern Georgia region of the ACF–FAS, filling a vital need to inform science-based decisions regarding resource management and conservation. The crop– demand method assumed that only enough water is pumped onto a crop to satisfy the deficit between evapotranspiration and precipitation. A second method applied a geostatistical regimen of variography and conditional simulation to monthly metered irrigation withdrawal to estimate irrigation withdrawal where data do not exist. A third method analyzed Landsat satellite imagery using an automated approach to generate monthly estimates of irrigated lands. These methods were evaluated independently and compared collectively with measured water withdrawal information available in the Georgia part of the ACF–FAS, principally in the Chattahoochee-Flint River Basin. An assessment of each method’s contribution to the National Water Census program was also made to identify transfer value of the methods to the national program and other water census studies. None of the three methods evaluated represent a turnkey process to estimate irrigation withdrawal on any spatial (local or regional) or temporal (monthly or annual) extent. Each method requires additional information on agricultural practices during the growing season to complete the withdrawal estimation process. Spatial and temporal limitations inherent in identifying irrigated acres during the growing season, and in designing spatially and temporally representative monitor (meter) networks, can belie the ability of the methods to produce accurate irrigation-withdrawal estimates that can be used to produce dependable and consistent assessments of water availability and use for the National Water Census. Emerging satellite-data products and techniques for data analysis can generate high spatial-resolution estimates of irrigated-acres distributions with near-term temporal frequencies compatible with the needs of the ACF–FAS and the National Water Census.

Georgia↗

USGS2025

Spatial scale dependence of error in fractional component cover maps

Geospatial products such as fractional vegetation cover maps often report overall, pixel-wise accuracy, but decision-making with these products often occurs at coarser scales. As such, data users often desire guidance on the appropriate spatial scale to apply these data. We worked toward establishing this guidance by assessing RCMAP (Rangeland Condition Monitoring Assessment and Projection) accuracy relative to a series of high-resolution predictions of component cover. We scale the 2-m and RCMAP predictions to various focal window sizes scales ranging from 30 to 1 500 m using focal averaging. We also evaluated variation in scaling effects on error at ecoregion and pasture (mean area of 1 050 ha) scales. Our results demonstrate increased accuracy at broader windows, across all components, and most increases in accuracy level off at ∼200–600 m scales. At the scale with highest accuracy, cross-component average correlation ( r ) increased by 6.5%, and root mean square error (RMSE) was reduced 46.4% relative to 30-m scale data. Scaling-related improvements to accuracy were greatest in components such as shrub and tree with more spatially heterogeneous cover and in ecoregions with more spatially heterogenous cover. When components were aggregated at the pasture scale, r increased 10% and RMSE decreased 34.3% on average relative to the 30-m scale. Our results provide empirical data on the scale dependence of error, which fractional cover data users may consider alongside their needs when using these data. Although the general principle remains that remotely sensed products are intended to address landscape-scale questions, our analysis indicates that applying data at finer than landscape spatial scales and grouping even a handful of pixels resulted in lowered error compared to pixel-level comparisons. Our results quantify the trade-offs between data granularity and error related to scale for fractional vegetation cover.

western United States↗

USGS2023

Red Knot stopover population size and migration ecology at Delaware Bay, USA, 2023

Red Knots ( Calidris canutus rufa ) stop at Delaware Bay on the mid-Atlantic coast of North America during northward migration to feed on eggs of horseshoe crabs ( Limulus polyphemus ). We conducted a mark-recapture-resight investigation to estimate the passage population of Red Knots at Delaware Bay in 2023. We used a Bayesian analysis of a Jolly-Seber model, which accounts for turnover in the population and the probability of detection during surveys. The 2023 passage population size was estimated at 39,361 (95% credible interval: 33,724–47,556). Although there is broad overlap in the credible intervals for population estimates from 2020–2023, the population estimate for 2023 was below 40,000 birds for only the second time since 2011. Horseshoe crabs have been harvested for use as bait in eel ( Anguilla rostrata ) and whelk ( Busycon ) fisheries since at least 1990. In the late 1990s and early 2000s, the number of Red Knots counted during aerial surveys at Delaware Bay declined from ~50,000 to ~13,000 and some avian conservation biologists hypothesized that horseshoe crab harvest levels in the 1990s prevented sufficient refueling for successful migration to the Arctic breeding grounds, reproduction, and survival for the remainder of the annual cycle. Since 2013, the harvest of horseshoe crabs in the Delaware Bay region has been managed using an Adaptive Resource Management (ARM) framework. The objective of the ARM framework is to manage sustainable harvest of Delaware Bay horseshoe crabs while maintaining ecosystem integrity and supporting Red Knot recovery with adequate stopover habitat for Red Knots and other migrating shorebirds. For annual harvest recommendations, the ARM framework requires annual estimates of horseshoe crab population size and the Red Knot stopover population size. The 2023 population size estimate will inform harvest recommendations in the next management cycle for decision making by the Atlantic States Marine Fisheries Commission.

Delaware, New Jersey↗

USGS2019

Spatio-temporal population change of Arctic-breeding waterbirds on the Arctic Coastal Plain of Alaska

Rapid physical changes that are occurring in the Arctic are primary drivers of landscape change and thus may drive population dynamics of Arctic-breeding birds. Despite the importance of this region to breeding and molting waterbirds, lack of a comprehensive analysis of historic data has hindered quantifying avian population change. We estimated distribution, abundance, and spatially explicit population trend of 20 breeding waterbird species using 25 years (1992–2016) of aerial survey data collected on the Arctic Coastal Plain (ACP), Alaska. The ACP is an extensive wetland complex on Alaska’s North Slope that supports millions of breeding waterbirds and includes portions of the National Petroleum Reserve—Alaska and the Arctic National Wildlife Refuge. We summarized annual counts into approximately 6-km by 6-km grid cells and analyzed data with generalized linear mixed models that accounted for survey timing and spatio-temporal autocorrelation. Geese and swans were most abundant along the coast between Admiralty Bay and Prudhoe Bay. Sea ducks, generalist predators (i.e., jaeger, gulls, terns), and loons were most abundant between Utqiaġvik and Point Lay, Alaska. Important areas for most species included the coastal fringe near Teshekpuk Lake, the Colville River Delta, and Admiralty Bay. The National Petroleum Reserve—Alaska was an important area for all species examined. Conversely, density on the coastal plain of the Arctic National Wildlife Refuge was greater than average for 20% of species. Annual population growth rates over the 25-year survey period were variable: 13 increased (range: 1.4%–13.8%), one decreased (-3.4%), and six were stable. However, even species with no overall population trend had areas of changing population size, suggesting localized conditions affected waterbird distributions on the ACP. Our results can be used to better inform land use decisions, improve monitoring of waterbird populations, and increase understanding of avian response to ecological change in the Arctic.

Alaska↗

USGS2011

Using avian radar to examine relationships among avian activity, bird strikes, and meteorological factors

Radar systems designed to detect avian activity at airfields are useful in understanding factors that influence the risk of bird and aircraft collisions (bird strikes). We used an avian radar system to measure avian activity at Beale Air Force Base, California, USA, during 2008 and 2009. We conducted a 2-part analysis to examine relationships among avian activity, bird strikes, and meteorological and time-dependent factors. We found that avian activity around the airfield was greater at times when bird strikes occurred than on average using a permutation resampling technique. Second, we developed generalized linear mixed models of an avian activity index (AAI). Variation in AAI was first explained by seasons that were based on average migration dates of birds at the study area. We then modeled AAI by those seasons to further explain variation by meteorological factors and daily light levels within a 24- hour period. In general, avian activity increased with decreased temperature, wind, visibility, precipitation, and increased humidity and cloud cover. These effects differed by season. For example, during the spring bird migration period, most avian activity occurred before sunrise at twilight hours on clear days with low winds, whereas during fall migration, substantial activity occurred after sunrise, and birds generally were more active at lower temperatures. We report parameter estimates (i.e., constants and coefficients) averaged across models and a relatively simple calculation for safety officers and wildlife managers to predict AAI and the relative risk of bird strike based on time, date, and meteorological values. We validated model predictability and assessed model fi t. These analyses will be useful for general inference of avian activity and risk assessment efforts. Further investigation and ongoing data collection will refine these inference models and improve our understanding of factors that influence avian activity, which is necessary to inform management decisions aimed at reducing risk of bird strikes.

California↗

USGS2007

An evaluation of the effects of conservation and fishery enhancement hatcheries on wild populations of salmon

The historical, political and scientific aspects of salmon hatchery programmes designed to enhance fishery production, or to recover endangered populations, are reviewed. We start by pointing out that the establishment of hatcheries has been a political response to societal demands for harvest and conservation; given this social context, we then critically examined the levels of activity, the biological risks, and the economic analysis associated with salmon hatchery programmes. A rigorous analysis of the impacts of hatchery programmes was hindered by the lack of standardized data on release sizes and survival rates at all ecological scales, and since hatchery programme objectives are rarely defined, it was also difficult to measure their effectiveness at meeting release objectives. Debates on the genetic effects of hatchery programmes on wild fish have been dominated by whether correct management practices can reduce negative outcomes, but we noted that there has been an absence of programmatic research approaches addressing this important issue. Competitive interactions between hatchery and wild fish were observed to be complex, but studies researching approaches to reduce these interactions at all ecological scales during the entire salmon life history have been rare, and thus are not typically considered in hatchery management. Harvesting of salmon released from fishery enhancement hatcheries likely impacts vulnerable wild populations; managers have responded to this problem by mass marking hatchery fish, so that fishing effort can be directed towards hatchery populations. However, we noted that the effectiveness of this approach is dependant on accurate marking and production of hatchery fish with high survival rates, and it is not yet clear whether selective fishing will prevent overharvest of wild populations. Finally, research demonstrating disease transmission from hatchery fish to wild populations was observed to be equivocal; evidence in this area has been constrained by the lack of effective approaches to studying the fate of pathogens in the wild. We then reviewed several approaches to studying the economic consequences of hatchery activities intended to inform the social decisions surrounding programmes, but recognized that placing monetary value on conservation efforts or on hatcheries that mitigate cultural groups’ loss of historical harvest opportunities may complicate these analyses. We noted that economic issues have rarely been included in decision making on hatchery programmes. We end by identifying existing major knowledge gaps, which, if filled, could contribute towards a fuller understanding of the role that hatchery programmes could play in meeting divergent goals. However, we also recognized that many management recommendations arising from such research may involve trade-offs between different risks, and that decisions about these trade-offs must occur within a social context. Hatcheries have played an important role in sustaining some highly endangered populations, and it is possible that reform of practices will lead to an increase in the number of successful programmes. However, a serious appraisal of the role of hatcheries in meeting broader needs is urgently warranted and should take place at the scientific, but more effectively, at the societal level.

Advances in Marine Biology↗

USGS2015

Applications of optical sensors for high-frequency water-quality monitoring and research

The recent commercial availability of in-situ optical sensors, together with new techniques for data collection and analysis, provides the opportunity to monitor a wide range of water-quality constituents over time scales during which environmental conditions actually change. Traditional approaches for data collection (daily to monthly discrete samples) are often limited by high sample collection, processing, and analytical costs, difficult site access, and logistical challenges, particularly for long-term sampling at a large number of sites. Optical sensors that continuously measure constituents in the environment by absorbance or fluorescence properties (Figure 1) have had a long history of use in oceanography for measuring highly resolved concentrations and fluxes of organic matter, nutrients, and algal material. However, much of the work using commercially-available optical sensors in rivers and streams has taken place in only the last few years. Figure 1. [NOT SHOWN] Optical sensor technology is now sufficiently developed to warrant broader application for research and monitoring in coastal and freshwater systems, and the United States Geological Survey (a U.S. science agency) is now using these sensors in a variety of research and monitoring programs to better understand water quality in-situ and in real-time. Examples are numerous and range from the applications of nitrate sensors for calculating loads to estuaries susceptible to hypoxia (Pellerin et al., 2014) to the use of fluorometers to estimate methymercury fluxes (Bergamaschi et al., 2011) and disinfection byproduct formation (Carpenter et al., 2013). Transmitting these data in real-time provides information that can be used for early trend detection, help identify monitoring gaps critical for water management, and provide science-based decision support across a range of issues related to water quality, freshwater ecosystems, and human health. Despite the value of these sensors, collecting data that meet high-quality standards requires investment in and adherence to tested and established methods and protocols for sensor operation and data management (Pellerin et al., 2013). For example, optical sensor measurements can be strongly influenced by a variety of matrix effects, including water temperature, inner filtering from highly colored water, and scattering of light by suspended particles (Downing et al., 2012). Characterizing and correcting sensors for these effects – as well as the continued development of common methodologies and protocols for sensor use – will be critical to ensuring comparable measurements across sites and over time. In addition, collaborative efforts such as the Nutrient Sensor Challenge (www.nutrients-challenge.org) will continue to accelerate the development, production and use of affordable, reliable and accurate sensors for a range of environments. REFERENCES Bergamaschi .B.A., Fleck J.A., Downing B.D., Boss E., Pellerin B.A., Ganju N.K., Schoellhamer D.H., Byington A.A., Heim W.A., Stephenson M., Fujii R. (2011), Methyl mercury dynamics in a tidal wetland quantified using in situ optical measurements. Limnology and Oceanography, 56(4): 1355-1371. Carpenter K.D., Kraus T.E.C., Goldman J.H., Saraceno J., Downing B.D., Bergamaschi B.A., McGhee G., Triplett T. (2013), Sources and Characteristics of Organic Matter in the Clackamas River, Oregon, Related to the Formation of Disinfection By-products in Treated Drinking Water: U.S. Geological Survey Scientific Investigations Report 2013–5001, 78 p. Downing .B.D., Pellerin B.A., Bergamaschi B.A., Saraceno J., Kraus T.E.K. (2012), Seeing the light: The effects of particles, temperature and inner filtering on in situ CDOM fluorescence in rivers and streams. Limnology and Oceanography: Methods, 10: 767-775. Pellerin B.A., Bergamaschi B.A., Downing B.D., Saraceno J., Garrett J.D., Olsen L.D. (2013), Optical Techniques for the Determination of Nitrate in En

Conference Paper↗

USGS2009

NBII-SAIN Data Management Toolkit

The Strategic Plan for the U.S. Geological Survey Biological Informatics Program (2005-2009) recognizes the need for effective data management: Though the Federal government invests more than $600 million per year in biological data collection, it is difficult to address these issues because of limited accessibility and lack of standards for data and information...variable quality, sources, methods, and formats (for example observations in the field, museum specimens, and satellite images) present additional challenges. This is further complicated by the fast-moving target of emerging and changing technologies such as GPS and GIS. Even though these technologies offer new solutions, they also create new informatics challenges (Ruggiero and others, 2005). The USGS National Biological Information Infrastructure program, hereafter referred to as NBII, is charged with the mission to improve the way data and information are gathered, documented, stored, and accessed. The central objective of this project is a direct reflection of the purpose of NBII as described by John Mosesso, Program Manager of the U.S. Geological Survey-Biological Informatics Program-GAP Analysis: At the outset, the reason for bringing about NBII was that there were significant amounts of data and information scattered all over the U.S., not accessible, in incompatible formats, and that NBII was tasked with addressing this problem...NBII's focus is to pull data together that truly matters to someone or communities. Essentially, the core questions are: 1) what are the issues, 2) where is the data, and 3) how can we make it usable and accessible (John Mosesso, U.S. Geological Survey, oral commun., 2006). Redundancy in data collection can be a major issue when multiple stakeholders are involved with a common effort. In 2001 the U.S. General Accounting Office (USGAO) estimated that about 50 percent of the Federal government's geospatial data at the time was redundant. In addition, approximately 80 percent of the cost of a spatial information system is associated with spatial data collection and management (U.S. General Accounting Office, 2003). These figures indicate that the resources (time, personnel, money) of many agencies and organizations could be used more efficiently and effectively. Dedicated and conscientious data management coordination and documentation is critical for reducing such redundancy. Substantial cost savings and increased efficiency are direct results of a pro-active data management approach. In addition, details of projects as well as data and information are frequently lost as a result of real-world occurrences such as the passing of time, job turnover, and equipment changes and failure. A standardized, well documented database allows resource managers to identify issues, analyze options, and ultimately make better decisions in the context of adaptive management (National Land and Water Resources Audit and the Australia New Zealand Land Information Council on behalf of the Australian National Government, 2003). Many environmentally focused, scientific, or natural resource management organizations collect and create both spatial and non-spatial data in some form. Data management appropriate for those data will be contingent upon the project goal(s) and objectives and thus will vary on a case-by-case basis. This project and the resulting Data Management Toolkit, hereafter referred to as the Toolkit, is therefore not intended to be comprehensive in terms of addressing all of the data management needs of all projects that contain biological, geospatial, and other types of data. The Toolkit emphasizes the idea of connecting a project's data and the related management needs to the defined project goals and objectives from the outset. In that context, the Toolkit presents and describes the fundamental components of sound data and information management that are common to projects involving biological, geospatial, and other related data

Open-File Report↗

USGS2022

Great Lakes spatial priorities study

Spatial data about the bathymetry, habitat characteristics, underlying geology, and other features of the ocean and inland seas are essential for decision-making. Marine research and management organizations use these data to help ensure safe navigation, promote sustainable fisheries, extract energy, and protect marine habitats in the coastal and ocean waters of the U.S. Exclusive Economic Zone (EEZ) and Laurentian Great Lakes. Many of these organizations may have overlapping or shared mapping interests without knowing it. In a multi-jurisdictional planning environment, it can be challenging and cumbersome to determine where other entities have shared or overlapping mapping interests, especially across a transnational region such as the Great Lakes. State and provincial governments, federal governments, academia, tribes and First Nations, and other stakeholders from both the U.S. and Canada all have mapping interests across Great Lakes waters. Identifying and communicating target geographies for new data collection that are shared among multiple organizations can both help to avoid redundancy of new mapping efforts, and create opportunities for greater efficiency through collaboration. To address this issue, a spatial priorities study was conducted using a geospatial tool developed by the National Ocean Services National Centers for Coastal and Ocean Science (NCCOS). The tool provided an easy-to-use online interface in which programs can identify their priorities in a simple and straightforward way. This study asked representatives of Great Lakes management and science organizations to identify the areas for which they needed maps of lakebed features on a near-term, mid-term, and long-term timeframe, and why. Then, the responses were analyzed and overlaid to determine areas of shared mapping need and opportunity and to determine the types of map products needed. The analysis revealed high interest among multiple organizations in discrete geographies including the Minnesota and Wisconsin shoreline from Duluth to the eastern extent of the Bayfield Peninsula, Green Bay in Lake Michigan, and the southern coastlines of Lake Erie and Lake Ontario, the St. Marys River, and the northern Lake Superior coastal waters near Grand Portage, MN. Lower priority mapping interest were distributed widely across all lakes, but tended to be concentrated in nearshore areas (<30 m depth). The analysis also indicated that the top mapping justifications were Habitat/biota/natural area, Benthic exploration, Commercial and recreational fishing, and Scientific research. The top desired map product types were Elevation, Substrate/sub-bottom geologic characterization, and Habitat map/characterization, although participants on some lakes noted other less prevalent product types. Following from previously conducted NOAA and non-NOAA Federal spatial prioritization exercises, the results of this regional focus can help mapping organizations better understand how their priorities align with the needs of regional organizations, allow for more efficient coordination and funding, and enable partners to leverage assets and resources to fill their most pressing data and information gaps across Great Lakes waters. The U.S. Mapping Coordination Site hosts the results of this study and other spatial prioritization studies. Through this website, one can interact with the study results along with recent and planned mapping efforts. NOAA intends to update their spatial priorities on a three- to five-year basis. Future studies should strive to expand participation of federal agencies, state and local governments, federally-recognized tribes, academia, and private industry (among other stakeholders) to seek out ocean mapping partnerships in conjunction with the National Ocean Mapping, Exploration and Characterization (NOMEC) goals map once, use many times.”

Great Lakes↗

USGS2013

Merapi 2010 eruption—Chronology and extrusion rates monitored with satellite radar and used in eruption forecasting

Despite dense cloud cover, satellite-borne commercial Synthetic Aperture Radar (SAR) enabled frequent monitoring of Merapi volcano's 2010 eruption. Near-real-time interpretation of images derived from the amplitude of the SAR signals and timely delivery of these interpretations to those responsible for warnings, allowed satellite remote sensing for the first time to play an equal role with in situ seismic, geodetic and gas monitoring in guiding life-saving decisions during a major volcanic crisis. Our remotely sensed data provide an observational chronology for the main phase of the 2010 eruption, which lasted 12 days (26 October–7 November, 2010). Unlike the prolonged low-rate and relatively low explosivity dome-forming and collapse eruptions of recent decades at Merapi, the eruption began with an explosive eruption that produced a new summit crater on 26 October and was accompanied by an ash column and pyroclastic flows that extended 8 km down the flanks. This initial explosive event was followed by smaller explosive eruptions on 29 October–1 November, then by a period of rapid dome growth on 1–4 November, which produced a summit lava dome with a volume of ~ 5 × 10 6 m 3 . A paroxysmal VEI 4 magmatic eruption (with ash column to 17 km altitude) destroyed this dome, greatly enlarged the new summit crater and produced extensive pyroclastic flows (to ~ 16 km radial distance in the Gendol drainage) and surges during the night of 4–5 November. The paroxysmal eruption was followed by a period of jetting of gas and tephra and by a second short period (12 h) of rapid dome growth on 6 November. The eruption ended with low-level ash and steam emissions that buried the 6 November dome with tephra and continued at low levels until seismicity decreased to background levels by about 23 November. Our near-real-time commercial SAR documented the explosive events on 26 October and 4–5 November and high rates of dome growth (> 25 m 3 s − 1 ). An event tree analysis for the previous 2006 Merapi eruption indicated that for lava dome extrusion rates > 1.2 m 3 s − 1 , the probability of a large (1872-scale) eruption was ~ 10%. Consequently, the order-of-magnitude greater rates in 2010, along with the explosive start of the eruption on 26 October, the large volume of lava accumulating at the summit by 4 November, and the rapid and large increases in seismic energy release, deformation and gas emissions were the basis for warnings of an unusually large eruption by the Indonesian Geological Agency's Center for Volcanology and Geologic Hazard Mitigation (CVGHM) and their Volcano Research and Technology Development Center (BPPTK) in Yogyakarta — warnings that saved thousands of lives.

Merapi Volcano↗

USGS2006

Integrating Stakeholders and Users into the Geography Discipline's Research Process

Future research priorities of Geography emphasize the discipline's leadership role in the U.S. Geological Survey (USGS) in multidisciplinary and integrated research on human and environmental systems and how these systems are interrelated and respond to change Geography's research priorities also emphasize providing science that is usable to society and creating decision support products applicable to given customer problems. To achieve these goals, we must understand the relationship between our research and our customer, and how to integrate the customer into the research process. This report details the elements of the research process that help achieve the degree of stakeholder involvement necessary to ensure a successful end-product. It offers suggestions that can help researchers better understand stakeholders and customers and involve them in the research process more effectively, while preserving the integrity of the science. Its aim is to help researchers understand the problems and challenges faced by our customers and communicate the ways in which Geography can help address their problems. Adopting these guidelines can improve the efficiency of the research process and lead to higher quality output. We will be able to conduct better research because we will have an improved understanding of the research problem and the stakeholders involved. This report covers a broad range of topics, from identifying and communicating with stakeholders and users, to the use of language, to how to effectively present scientific information to the user. It does not offer a 'one size fits all' method. Instead, perhaps only specific sections are suitable for a given project and customers, depending on project scope and needs. This report is based on the objectives of Geography's strategic plan, U. S. Geological Survey's strategic plan, and Department of Interior's strategic plan. Section 2 of these guidelines describes the purpose of the research process in Geography and the need for better user involvement in the process. Section 3 explains how to conduct a stakeholder analysis. Section 4 explains how to conduct a user-needs assessment.

Open-File Report↗

USGS2013

Distribution of indoor radon concentrations in Pennsylvania, 1990-2007

Results from 548,507 indoor radon tests from a database compiled by the Pennsylvania Department of Environmental Protection, Bureau of Radiation Protection, Radon Division, are evaluated in this report in an effort to determine areas where concentrations of radon are highest. Indoor radon concentrations were aggregated according to geologic unit and hydrogeologic setting for spatial analysis. Indoor radon concentrations greater than or equal to the U.S. Environmental Protection Agency (USEPA) action level of 4 picocuries per liter (pCi/L) were observed for 39 percent of the test results; the highest concentration was 1,866.4 pCi/L. When analyzed according to Pennsylvania’s geologic units, 93 of the 188 (49.5 percent) geologic units with indoor radon concentrations had median concentrations greater than the USEPA action level of 4 pCi/L; most of these geologic units are located in the eastern part of the State and include metamorphic rocks, limestones, sandstones, shales, and glacial deposits. When analyzed according to Pennsylvania’s hydrogeologic settings, 5 of the 20 (25 percent) settings had median indoor radon concentrations greater than the USEPA action level of 4 pCi/L; these settings are located mostly in the south-central part of the State. Median indoor radon concentrations aggregated according to geologic units and hydrogeologic settings are useful for drawing general conclusions about the occurrence of indoor radon in specific geologic units and hydrogeologic settings, but the associated data and maps have limitations. The aggregated indoor radon data have testing and spatial accuracy limitations due to lack of available information regarding testing conditions and the imprecision of geocoded test locations. In addition, the associated data describing geologic units and hydrogeologic settings have spatial and interpretation accuracy limitations, which are a result of using statewide data to define conditions at test locations and geologic data that represent a broad interpretation of geologic units across the State. As a result, indoor air radon concentration distributions are not proposed for use in predicting individual concentrations at specific sites nor for use as a decision-making tool for property owners to decide whether to test for indoor radon concentrations at specific property locations.

Pennsylvania↗

USGS2010

Simulated groundwater flow in the Ogallala and Arikaree aquifers, Rosebud Indian Reservation area, South Dakota – Revisions with data through water year 2008 and simulations of potential future scenarios

The Ogallala and Arikaree aquifers are important water resources in the Rosebud Indian Reservation area and are used extensively for irrigation, municipal, and domestic water supplies. Drought or increased withdrawals from the Ogallala and Arikaree aquifers in the Rosebud Indian Reservation area have the potential to affect water levels in these aquifers. This report documents revisions and recalibration of a previously published three-dimensional, numerical groundwater-flow model for this area. Data for a 30-year period (water years 1979 through 2008) were used in steady-state and transient numerical simulations of groundwater flow. In the revised model, revisions include (1) extension of the transient calibration period by 10 years, (2) the use of inverse modeling for steady-state calibration, (3) model calibration to base flow for an additional four surface-water drainage basins, (4) improved estimation of transient aquifer recharge, (5) improved delineation of vegetation types, and (6) reduced cell size near large capacity water-supply wells. In addition, potential future scenarios were simulated to assess the potential effects of drought and increased groundwater withdrawals. The model comprised two layers: the upper layer represented the Ogallala aquifer and the lower layer represented the Arikaree aquifer. The model’s grid had 168 rows and 202 columns, most of which were 1,640 feet (500 meters) wide, with narrower rows and columns near large water-supply wells. Recharge to the Ogallala and Arikaree aquifers occurs from precipitation on the outcrop areas. The average recharge rates used for the steady-state simulation were 2.91 and 1.45 inches per year for the Ogallala aquifer and Arikaree aquifer, respectively, for a total rate of 255.4 cubic feet per second (ft 3 /s). Discharge from the aquifers occurs through evapotranspiration, discharge to streams as base flow and spring flow, and well withdrawals. Discharge rates for the steady-state simulation were 171.3 ft 3 /s for evapotranspiration, 74.4 ft 3 /s for net outflow to streams and springs, and 11.6 ft 3 /s for well withdrawals. Estimated horizontal hydraulic conductivity used for the numerical model ranged from 0.2 to 84.4 feet per day (ft/d) in the Ogallala aquifer and from 0.1 to 4.3 ft/d in the Arikaree aquifer. A uniform vertical hydraulic conductivity value of 4.2x10 -4 ft/d was estimated for the Ogallala aquifer. Vertical hydraulic conductivity was estimated for five zones in the Arikaree aquifer and ranged from 8.8x10 -5 to 3.7 ft/d. Average rates of recharge, maximum evapotranspiration, and well withdrawals were included in the steady-state simulation, whereas the time-varying rates were included in the transient simulation. Inverse modeling techniques were used for steady-state model calibration. These methods were designed to estimate parameter values that are, statistically, the most likely set of values to result in the smallest differences between simulated and observed hydraulic heads and base-flow discharges. For the steady-state simulation, the root mean square error for simulated hydraulic heads for all 383 wells was 27.3 feet. Simulated hydraulic heads were within ±50 feet of observed values for 93 percent of the wells. The potentiometric surfaces of the two aquifers calculated by the steady-state simulation established initial conditions for the transient simulation. For the transient simulation, the difference between the simulated and observed means for hydrographs was within ±40 feet for 98 percent of 44 observation wells. A sensitivity analysis was used to examine the response of the calibrated steady-state model to changes in model parameters including horizontal and vertical hydraulic conductivity, evapotranspiration, recharge, and riverbed conductance. The model was most sensitive to recharge and maximum evapotranspiration and least sensitive to riverbed and spring conductances. To simulate a potential future drought scenario, a synthetic recharge record was created, the mean of which was equal to 64 percent of the average estimated recharge rate for the 30-year calibration period. This synthetic recharge record was used to simulate the last 20 years of the calibration period under drought conditions. Compared with results of the calibrated model, decreases in hydraulic-head values for the drought scenario at the end of the simulation period were as much as 39 feet for the Ogallala aquifer. To simulate the effects of potential increases in pumping, well withdrawal rates were increased by 50 percent from those estimated for the 30-year calibration period for the last 20 years of the calibration period. Compared with results of the calibrated model, decreases in hydraulic-head values for the scenario of increased pumping at the end of the simulation period were as much as 13 feet for the Ogallala aquifer. This numerical model is suitable as a tool to help understand the flow system, to help confirm that previous estimates of aquifer properties were reasonable, and to estimate aquifer properties in areas without data. The model also is useful to help assess the effects of drought and increases in pumping by simulations of these scenarios, the results of which are not precise but may be considered when making water management decisions.

South Dakota↗

USGS2013

Method to support Total Maximum Daily Load development using hydrologic alteration as a surrogate to address aquatic life impairment in New Jersey streams

More than 300 ambient monitoring sites in New Jersey have been identified by the New Jersey Department of Environmental Protection (NJDEP) in its integrated water-quality monitoring and assessment report (that is, the 305(b) Report on general water quality and 303(d) List of waters that do not support their designated uses) as being impaired with respect to aquatic life; however, no unambiguous stressors (for example, nutrients or bacteria) have been identified. Because of the indeterminate nature of the broad range of possible impairments, surrogate measures that more holistically encapsulate the full suite of potential environmental stressors need to be developed. Streamflow alteration resulting from anthropogenic changes in the landscape is one such surrogate. For example, increases in impervious surface cover (ISC) commonly cause increases in surface runoff, which can result in “flashy” hydrology and other changes in the stream corridor that are associated with streamflow alteration. The NJDEP has indicated that methodologies to support a hydrologically based Total Maximum Daily Load (hydro-TMDL) need to be developed in order to identify hydrologic targets that represent a minimal percent deviation from a baseline condition (“minimally altered”) as a surrogate measure to meet criteria in support of designated uses. The primary objective of this study was to develop an applicable hydro-TMDL approach to address aquatic-life impairments associated with hydrologic alteration for New Jersey streams. The U.S. Geological Survey, in cooperation with the NJDEP, identified 51 non- to moderately impaired gaged streamflow sites in the Raritan River Basin for evaluation. Quantile regression (QR) analysis was used to compare flow and precipitation records and identify baseline hydrographs at 37 of these sites. At sites without an appropriately long period of record (POR) or where a baseline hydrograph could not be identified with QR, a rainfall-runoff model was used to develop simulated baseline hydrographs. The hydro-TMDL approach provided an opportunity to evaluate proportional differences in flow attributes between observed and baseline hydrographs and to develop complementary flow-ecology response relations at a subset of Raritan River Basin sites where available flow and ecological information overlapped. The New Jersey Stream Classification Tool (NJSCT) was used to determine the stream class of all 51 study sites by using either an observed or a simulated baseline hydrograph. Two New Jersey stream classes (A and C) were evaluated to help characterize the unique hydrology of the Raritan River Basin. In general, class C streams (1.99–40.7 square miles) had smaller drainage areas than class A streams (0.7–785 square miles). Many of the non-impaired and moderately impaired class A and C streams in the Raritan River Basin were found to have significant hydrologic alteration as indicated by numerous flow values that fell outside the established 25th-to-75th- and the more conservative 40th-to-60th-percentile boundaries. However, percent deviations for the class C streams (defined as moderately stable streams with moderately high base-flow contributions) were, in general, much larger than those for the class A streams (defined as semiflashy streams characterized by moderately low base flow). The greater deviations for class C streams in the hydro-TMDL assessments likely resulted from comparisons that were based solely on simulated baseline hydrographs, which were developed without considering any anthropogenic influences in the basin. In contrast, comparisons for many of the class A streams were made by using an observed baseline, which already includes an implicit level of ISC and other human influences on the landscape. By using the hydro-TMDL approach, numerous flow deviations were identified that were indicative of streams that are highly regulated by reservoirs or dams, streams that are affected by increasing amounts of surface runoff resulting from ISC, and streams that are affected by water abstraction (that is, groundwater or surface-water withdrawals used for agricultural and human supply). Eight of the reservoir- and (or) dam-affected sites showed flow deviations that are indicative of flow-managed systems. For example, indices that account for the timing and magnitude of high and low flows were often found to fall outside the 25th-to-75th-percentile range. In general, at regulated class C streams, annual summer low flows are arriving later and tend to be lower, and high flows are arriving earlier with higher magnitudes of longer duration. At class A streams, high and low flows are arriving later with an overall increase in discharge with respect to the prereservoir baseline conditions. The drainage basins of eight of the study sites had large values of ISC (>10 percent), most likely as a result of expanding urban development. In general, the magnitude and frequency of high flows at class A and C sites with high ISC are increasing and were commonly found to fall outside the 25th-to-75th-percentile range. Additionally, magnitudes of low flows are becoming lower and, although the timing of high flows was highly variable, low-flow events appeared to be arriving earlier than would be expected under normal low-flow conditions. Three of the study sites appeared to be affected by hydrologic changes associated with water abstraction. At these sites, the timing of flows appeared to be altered. For example, low flows tended to arrive earlier and high flows arrived later at two of the three sites. Additionally, the magnitude and duration of low flows were commonly less than the 25th-percentile value and the duration of high flows appeared to increase. A reduced set of hydrologic and ecological variables was used to develop univariate and multivariate flow-ecology response models for the aquatic-invertebrate assemblage. Many hydrologic variables accounting for the duration, magnitude, frequency, and timing of flows were significantly correlated with ecological response. Multiple linear regression (MLR) models were developed to provide a more holistic evaluation of the combined effects of hydrologic alteration and to identify models with two or three hydrologic variables that account for a significant proportion of the variability in invertebrate-assemblage condition as represented by assemblage metric scores. MLR models, derived on the basis of hydrologic attributes, accounted for 35 to 75 percent of the variability in assemblage condition. The hydro-TMDL method developed herein for non- to moderately impaired Raritan River Basin streams utilizes a “surrogate” approach in place of the traditional “pollutant of concern” approach commonly used for TMDL development. Managers can use the results obtained by using the hydro-TMDL method to offset the effects of impervious-surface runoff and altered streamflow and to implement measures designed to achieve the necessary load reductions for the “pollutant of concern” (that is, percentage deviations of stream-class-specific flow-index values outside the established 25th-to-75th-percentile range). In this case, such deviations could represent all or a subset of the altered flow indices that prevent the stream from meeting designated aquatic-life criteria. This hydro-TMDL uses a reference, or attainment stream approach for developing the TMDL endpoint. That is, either observed or simulated baseline hydrographs were selected as appropriate reference conditions on the basis of results of QR analysis and watershed modeling procedures, respectively. For any stream in the Raritan River Basin evaluated as part of this study, the hydro-TMDL can be expressed as the greatest amount of deviation in flow a stream can exhibit without violating the stream’s designated aquatic-life criteria. Use of this surrogate approach is appropriate because flows that fall outside the established percentile ranges are ultimately a function of many anthropogenic modifications of the landscape, including the amount of stormwater runoff generated from impervious surfaces within a given basin, the presence of manmade structures designed to retain or divert water, the magnitude of ground- and surface-water abstraction, and the presence of water-supply processes implemented to support human needs. In addition, the stream-type-specific flow indices used as the basis for the hydro-TMDL approach are useful for representing the hydrologic conditions of class A and C streams/basins because they incorporate the full spectrum of flow conditions (very low to very high) that occur in the stream system over a long period of time, as well as those flow properties that change as a result of seasonal variation. Ultimately, an estimate of the maximum percentage flow reduction that could be allowed will be needed to address the aquatic-life impairments in many of the study streams in the Raritan River Basin and will be necessary for identifying appropriate target flow conditions for hydro-TMDL implementation. As described in this report, a target flow value equal to the 25th- or 75th-percentile flow rate could be selected as the point useful for setting specific hydrologic targets. This selection, however, is a management decision that could vary depending on the designated use of the stream or other regulatory factors (for example, water-supply protection, trout production, antidegradation policies, or special protection designations). In New Jersey streams where no unambiguous stressors can be identified, State monitoring agencies, such as the NJDEP, could choose to require the implementation of a flow-based TMDL that not only supports designated uses, but meets the regulatory requirements under the Clean Water Act, and represents a balance between water supply intended to meet human needs and the conservation of ecosystem integrity.

New Jersey↗

USGS2007

A Quantitative Threats Analysis for the Florida Manatee ( Trichechus manatus latirostris )

The Florida manatee (Trichechus manatus latirostris) is an endangered marine mammal endemic to the southeastern United States. The primary threats to manatee populations are collisions with watercraft and the potential loss of warm-water refuges. For the purposes of listing, recovery, and regulation under the Endangered Species Act (ESA), an understanding of the relative effects of the principal threats is needed. This work is a quantitative approach to threats analysis, grounded in the assumption that an appropriate measure of status under the ESA is based on the risk of extinction, as quantified by the probability of quasi-extinction. This is related to the qualitative threats analyses that are more common under the ESA, but provides an additional level of rigor, objectivity, and integration. In this approach, our philosophy is that analysis of the five threat factors described in Section 4(a)(1) of the ESA can be undertaken within an integrated quantitative framework. The basis of this threats analysis is a comparative population viability analysis. This involves forecasting the Florida manatee population under different scenarios regarding the presence of threats, while accounting for process variation (environmental, demographic, and catastrophic stochasticity) as well as parametric and structural uncertainty. We used the manatee core biological model (CBM) for this viability analysis, and considered the role of five threats: watercraft-related mortality, loss of warm-water habitat in winter, mortality in water-control structures, entanglement, and red tide. All scenarios were run with an underlying parallel structure that allowed a more powerful estimation of the effects of the various threats. The results reflect our understanding of manatee ecology (as captured in the structure of the CBM), our estimates of manatee demography (as described by the parameters in the model), and our characterization of the mechanisms by which the threats act on manatees. As an example of the type of results generated, we estimated that the probability of the manatee population falling to less than 250 adults on either the Atlantic or Gulf coasts (from a current statewide population size of near 3300) within 100 years is 8.6%. Complete removal of the watercraft threat alone would reduce this risk to 0.4%; complete removal of the warm-water threat to 4.2%; removal of both threats would reduce the risk to 0.1%. The modeling approach we have taken also allows us to consider partial removal of threats, as well as removal of multiple threats simultaneously. We believe the measure we have proposed (probability of quasi-extinction over y years, with quasi-extinction defined as dropping below a threshold of z on either coast) is a suitable measure of status that integrates a number of the elements that are relevant to interpretation under the ESA (it directly integrates risk of extinction and reduction of range, and indirectly integrates loss of genetic diversity). But the identification of the time frame of interest and the tolerable risk of quasi-extinction are policy decisions, and an ecology-based quasi-extinction threshold has not yet been determined. We have endeavored to provide results over a wide range of these parameters to give decision-makers useful information to assess status. This assessment of threats suggests that watercraft-related mortality is having the greatest impact on manatee population growth and resilience. Elimination of this single threat would greatly reduce the probability of quasi-extinction. Loss of warm-water is also a significant threat, particularly over the long-term. Red tide and entanglement, while noticeable threats, have had less of an impact on the manatee population. The effect of water control structures may have already been largely mitigated. We did not, however, consider an exhaustive list of threats. Other threats (e.g., reduction of food resources due to storms and development) may play a

Open-File Report↗

USGS2023

Moderate flood level scenarios—Synthetic storm-driven flood-inundation maps for coastal communities in 10 New Jersey counties

The U.S. Geological Survey (USGS), in cooperation with the New Jersey Department of Environmental Protection (NJDEP) and the New Jersey Office of Emergency Management (NJOEM), created digital flood-inundation maps for approximately 1,430 square miles of the New Jersey coast and tidewaters through 10 coastal counties stretching from Cumberland County through Bergen County, New Jersey. The maps depict extent and depth estimates of coastal flooding corresponding to selected tidal elevations recorded by 25 real-time USGS tide gages located within the study area. The flood-inundation maps can be accessed through the USGS Interagency Flood Risk Management (InFRM) Flood Decision Support Toolbox (FDST). Previously published modeled data were utilized from the coupled ADvanced CIRCulation Model (ADCIRC) and Simulating Waves Nearshore (SWAN) model. Simulated tropical storm events were selected based on parameters including landfall location or closest approach location, maximum wind speed, central pressure, and radii of winds. Two storm events were selected per tide gage providing two “scenarios” and accompanying inundation-map libraries for each gage. Flood-inundation maps reflect between 9 to 30 stages (elevations) at each tide gage that correspond to areal extents and depths for ADCIRC-SWAN storm time steps extracted from modeled hydrographs at the gage locations. Water-surface elevations from ADCIRC-SWAN node points extending through each tide gage station extent were used to interpolate a water surface. Combining these surfaces with a geographic information system (GIS) topobathymetric digital elevation model (TBDEM) delineated the area flooded by coastal waters at each tide gage elevation. The availability of these maps to visualize potential inundation for selected water levels along with real-time water level data available online from USGS tide gages, coastal impact statements, and forecasted tide elevations from the National Weather Service (NWS) will provide emergency management personnel and residents with a link between numeric and text warning information and images of estimated inundation extents in their community. User selected display of inundation allows early response activities to NWS forecasted water level elevations or mitigation planning by selecting targeted water levels and planning critical pre-flood activities such as building elevations, early traffic pattern changes because of neighborhood building inundation levels, improved understanding about when major road access is affected, as well as for post-flood recovery efforts. A subsequent analysis of several community metrics including total structures, structure density, percent of buildings inundated, and roads and bridges affected by flooding was used to evaluate moderate flooding impacts among the mapped station extents. Initial comparisons are presented to show the variability of these characteristics within each mapped station extent then extended to evaluate impacts from moderate flooding on these same areas. The analysis used simulated inundation layers at the moderate flood stage to investigate the magnitude of inundation on building structures and major roads among the mapped station extents. Experimental equations were developed to begin testing if a mathematical equation could help identify communities that were disproportionately impacted at moderate flood stage. The community analysis of impacts to moderate flooding based on these inundation scenario maps should provide community leaders and local and state planning officials with tools to better visualize and understand how flooding begins to disrupt and damage building structures and major roads as a surrogate for direct increased risk to human life and property.

New Jersey↗

USGS2011

Range-wide assessment of livestock grazing across the sagebrush biome

Domestic livestock grazing occurs in virtually all sagebrush habitats and is a prominent disturbance factor. By affecting habitat condition and trend, grazing influences the resources required by, and thus, the distribution and abundance of sagebrush-obligate wildlife species (for example, sage-grouse Centrocercus spp.). Yet, the risks that livestock grazing may pose to these species and their habitats are not always clear. Although livestock grazing intensity and associated habitat condition may be known in many places at the local level, we have not yet been able to answer questions about use, condition, and trend at the landscape scale or at the range-wide scale for wildlife species. A great deal of information about grazing use, management regimes, and ecological condition exists at the local level (for individual livestock management units) under the oversight of organizations such as the Bureau of Land Management (BLM). However, the extent, quality, and types of existing data are unknown, which hinders the compilation, mapping, or analysis of these data. Once compiled, these data may be helpful for drawing conclusions about rangeland status, and we may be able to identify relationships between those data and wildlife habitat at the landscape scale. The overall objective of our study was to perform a range-wide assessment of livestock grazing effects (and the relevant supporting data) in sagebrush ecosystems managed by the BLM. Our assessments and analyses focused primarily on local-level management and data collected at the scale of BLM grazing allotments (that is, individual livestock management units). Specific objectives included the following: 1. Identify and refine existing range-wide datasets to be used for analyses of livestock grazing effects on sagebrush ecosystems. 2. Assess the extent, quality, and types of livestock grazing-related natural resource data collected by BLM range-wide (i.e., across allotments, districts and regions). 3. Compile and synthesize recommendations from federal and university rangeland science experts about how BLM might prioritize collection of different types of livestock grazing-related natural resource data. 4. Investigate whether range-wide datasets (Objective 1) could be used in conjunction with remotely sensed imagery to identify across broad scales (a) allotments potentially not meeting BLM Land Health Standards (LHS) and (b) allotments in which unmet standards might be attributable to livestock grazing. Objective 1: We identified four datasets that potentially could be used for analyses of livestock grazing effects on sagebrush ecosystems. First, we obtained the most current spatial data (typically up to 2007, 2008, or 2009) for all BLM allotments and compiled data into a coarse, topologically enforced dataset that delineated grazing allotment boundaries. Second, we obtained LHS evaluation data (as of 2007) for all allotments across all districts and regions; these data included date of most recent evaluation, BLM determinations of whether region-specific standards were met, and whether BLM deemed livestock to have contributed to any unmet standards. Third, we examined grazing records of three types: Actual Use (permittee-reported), Billed Use (BLM-reported), and Permitted Use (legally authorized). Finally, we explored the possibility of using existing Natural Resources Conservation Service (NRCS) Ecological Site Description (ESD) data to make up-to-date estimates of production and forage availability on BLM allotments. Objective 2: We investigated the availability of BLM livestock grazing-related monitoring data and the status of LHS across 310 randomly selected allotments in 13 BLM field offices. We found that, relative to other data types, the most commonly available monitoring data were Actual Use numbers (permittee-reported livestock numbers and season-of-use), followed by Photo Point, forage Utilization, and finally, Vegetation Trend measurement data. Data availability and frequency of data collection varied across allotments and field offices. Analysis of the BLM's LHS data indicated 67 percent of allotments analyzed were meeting standards. For those not meeting standards, livestock were considered the causal factor in 45 percent of cases (about 15 percent of all allotments). Objective 3: We sought input from 42 university and federal rangeland science experts about how best to prioritize rangeland monitoring activities associated with ascertaining livestock impacts on vegetation resources. When we presented a hypothetical scenario to these scientists and asked them to prioritize monitoring activities, the most common response was to measure ground and vegetation cover, a variable that in many cases (10 of 13 field offices sampled) BLM had already identified as a monitoring priority. Experts identified several other traditional (for example, photo points) and emerging approaches (for example, high-resolution aerial photography) to monitoring. Objective 4: We used spatial allotment data (described in Objective 1) and remotely sensed vegetation data (sagebrush cover, herbaceous vegetation cover, litter and bare soil) to assess differences in allotment LHS status ("Not met" vs. "Met"; if "Not met" - livestock-caused vs. not). We then developed logistic regression models, using vegetation variables to predict LHS status of BLM allotments in sagebrush steppe habitats in Wyoming and portions of Montana and Colorado. In general, we found that more consistent data collection at the local level might improve suitability of data for broad-scale analyses of livestock impacts. As is, data collection methodologies varied across field offices and States, and we did not find any local-level monitoring data (Actual Use, Utilization, Vegetation Trend) that had been collected consistently enough over time or space for range-wide analyses. Moreover, continued and improved emphasis on monitoring also may aid local management decisions, particularly with respect to effects of livestock grazing. Rangeland science experts identified ground cover as a high monitoring priority for assessing range condition and emphasized the importance of tracking livestock numbers and grazing dates. Ultimately, the most effective monitoring program may entail both increased data collection effort and the integration of alternative monitoring approaches (for example, remote sensing or monitoring teams). In the course of our study, we identified three additional datasets that could potentially be used for range-wide analyses: spatial allotment boundary data for all BLM allotments range-wide, LHS evaluations of BLM allotments, and livestock use data (livestock numbers and grazing dates). It may be possible to use these spatial datasets to help prioritize monitoring activities over the extensive land areas managed by BLM. We present an example of how we used spatial allotment boundary data and LHS data to test whether remotely sensed vegetation characteristics could be used to predict which allotments met or did not meet LHS. This approach may be further improved by the results of current efforts by BLM to test whether more intensive (higher resolution) LHS assessments more accurately describe land health status. Standardized data collection in more ecologically meaningful land units may improve our ability to use local-level data for broad-scale analyses.

Open-File Report↗