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USGS2024

Introduction to recommended capabilities and instrumentation for volcano monitoring in the United States

Introduction The National Volcano Early Warning System (NVEWS) was authorized and partially funded by the U.S. Government in 2019. In response, the U.S. Geological Survey (USGS) Volcano Hazards Program asked its scientists to reflect on and summarize their views of best practices for volcano monitoring. The goal was to review and update the recommendations of a previous report (Moran and others, 2008) and to provide a more detailed analysis of capabilities and instrumentation for monitoring networks for U.S. volcanoes. This Scientific Investigations Report and its chapters reflect those USGS scientists’ views and summaries and will serve as a guide for future network upgrades funded through NVEWS. Given the well-documented hazards posed by volcanoes to population centers and aviation (for example, Blong, 1984; Scott, 1989; Neal and others, 1997, 2019; Guffanti and others, 2010; Shroder and Papale, 2014; Prata and Rose, 2015; Palmer, 2020), volcano monitoring is critical for ensuring public safety and for mitigating the impacts of volcanic activity. Accurate and timely forecasts are facilitated by well-designed monitoring networks that are in place long enough to allow for background behavior to be recognized and understood. Because precursory signals may be limited and unrest may progress rapidly to an eruption, our goal is to deploy monitoring systems that enable detection of the reactivation of dormant volcanoes as early as possible, allowing for public safety and risk mitigation. NVEWS planning is also informed by the results of Ewert and others (2005, 2018), whereby 161 U.S. volcanoes are currently categorized and ranked commensurate with their relative threat. In each chapter, author(s) considered the need for some redundancy of instrumentation and telemetry, given the likelihood of occasional equipment failure, particularly in extreme and remote environments. Establishing digital telemetry networks requires advanced planning, sighting, radio-shot testing, and, inevitably, troubleshooting in the field. This is harder to achieve rapidly during a crisis; thus, an important goal for monitoring U.S. volcanoes is to establish digital telemetry backbones with redundancy and extra capacity to absorb additional instruments should a volcano begin to exhibit signs of unrest (fig. A1). The National Telecommunications and Information Administration (NTIA) imposed new regulations in the United States, eliminating the use of older analog radios for many purposes, which had been one previous means for redundant data delivery. However, the resulting conversion from analog to digital systems usefully enables stations to accommodate new and multivariate real-time data streams (for example, Global Navigation Satellite System [GNSS] receivers, infrasound arrays, gas spectrometers, visible and infrared cameras, and broadband seismometers). We note that other USGS and broader national and international hazard programs can leverage NVEWS instrumentation plans. Examples of this include the following: Improved seismic coverage of volcanoes will increase the capability of the USGS Earthquake Hazards Program to detect and locate earthquakes, estimate ground shaking, and provide timely early warnings through the ShakeAlert Earthquake Early Warning System (Given and others, 2018). The National Oceanic and Atmospheric Administration’s Tsunami Program will benefit from additional seismic stations, particularly within the sparsely instrumented Aleutian Islands, Northern Mariana Islands, and American Samoa. Infrasound stations can detect signals from landslides, debris flows and lahars, floods, and weather events, providing benefits to the National Weather Service and the USGS Landslide Hazards Program.

Scientific Investigations Report↗

USGS1993

Escherichia coli and fecal-coliform bacteria as indicators of recreational water quality

In 1986, the U.S. Environmental Protection Agency (USEPA) recommended that Escherichia coli (E. coli) be used in place of fecal-coliform bacteria in State recreational water-quality standards as an indicator of fecal contamination. This announcement followed an epidemiological study in which E. coli concentration was shown to be a better predictor of swimming-associated gastrointestinal illness than fecal-coliform concentration. Water-resource managers from Ohio have decided to collect information specific to their waters and decide whether to use E. coli or fecal-coliform bacteria as the basis for State recreational water-quality standards. If one indicator is a better predictor of recreational water quality than the other and if the relation between the two indicators is variable, then the indicator providing the most accurate measure of recreational water quality should be used in water-quality standards. Water-quality studies of the variability of concentrations of E. coli to fecal-coliform bacteria have shown that (1) concentrations of the two indicators are positively correlated, (2) E. coli to fecal-coliform ratios differ considerably from site to site, and (3) the E. coli criteria recommended by USEPA may be more difficult to meet than current (1992) fecal-coliform standards. In this study, a statistical analysis was done on concentrations of E. coli and fecal-coliform bacteria in water samples collected by two government agencies in Ohio-- the U.S. Geological Survey (USGS) and the Ohio River Valley Water Sanitation Commission (ORSANCO). Data were organized initially into five data sets for statistical analysis: (1) Cuyahoga River, (2) Olentangy River, (3) Scioto River, (4) Ohio River at Anderson Ferry, and (5) Ohio River at Cincinnati Water Works and Tanners Creek. The USGS collected the data in sets 1, 2, and 3, whereas ORSANCO collected the data in sets 4 and 5. The relation of E. coli to fecal-coliform concentration was investigated by use of linear-regression analysis and analysis of covariance. Log-transformed E. coli and fecal-coliform concentrations were highly correlated in all data sets (r-values ranged from 0.929 to 0.984). Linear regression analysis on USGS and ORSANCO data sets showed that concentration of E. coli could be predicted from fecal-coliform concentration (coefficients of determination (R2) ranged from 0.863 to 0.970). Results of analysis of covariance (ANCOVA) indicated that the predictive equations among the three USGS data sets and two ORSANCO data sets were not significantly different and that the data could be pooled into two large data sets, one for USGS data and one for ORSANCO data. However, results of ANCOVA indicated that USGS and ORSANCO data could not be pooled into one large data set. Predictions of E. coli concentrations calculated for USGS And ORSANCO regression relations, based on fecal-coliform concentrations set to equal Ohio water-quality standards, further showed the differences in E. coli to fecal-coliform relations among data sets. For USGS data, a predicted geometric mean of 176 col/100 mL (number of colonies per 100 milliliters) was greater than the current geometric-mean E. coli standard for bathing water of 126 col/100mL. In contrast, for ORSANCO data, the predicted geometric mean of 101 col/100 mL was less than the current E. coli standard. The risk of illness associated with predicted E. coli concentrations for USGS and ORSANCO data was evaluated by use of the USEPA regression equation that predicts swimming-related gastroenteritis rates from E. coli concentrations.1 The predicted geometric-mean E. coli concentrations for bathing water of 176 col/100 mL for USGS data and 101 col/100 mL for ORSANCO data would allow 9.4 and 7.1 gastrointestinal illnesses per 1,000 swimmers, respectively. This prediction compares well with the illness rate of 8 individuals per 1,000 swimmers estimated by the USEPA for an E. coli concentration of 126 col/100 mL. Therefore, the

Water-Resources Investigations Report↗

USGS2024

Genetic structure of restored Brook Trout populations in the Southern Appalachian Mountains indicates successful reintroductions

Wildlife reintroduction is an important conservation tool for threatened species, yet identifying appropriate source populations poses a challenge. In particular, the possibility of outbreeding depression is cited as a constraint limiting the range of candidate source populations for translocation. When multiple source lineages are mixed during reintroduction, genetic monitoring is necessary to evaluate whether sources contribute equally to subsequent generations and whether they are interbreeding as expected. Moreover, statistical analysis of genetic data should account for complex life histories that might affect the timescale of admixture and genetic drift. Here, we use samples collected over a 23-year period and a stochastic age-structured model to analyze the genetic mixing process in reintroduced Brook Trout ( Salvelinus fontinalis ) populations in the Southern Appalachians. Each restored population was seeded with two to three source populations. Previous research inferred reproductive isolation between source populations leading to a proposal of splitting the species into multiple taxa. In contrast, we found patterns of ancestry that were consistent with random mating and no advantage for one source lineage over any other. Brook Trout from different source streams are mixing as expected in the restoration sites. This result does not support the hypothesis that Brook Trout in the Southern Appalachian Mountains includes several distinct species. Mixing different sources from the same watershed seems to be an effective way to increase genetic diversity of reintroduced populations while minimizing risk to source populations.

North Carolina, Tennessee↗

USGS2023

Modeling the spatial distribution of carcasses of eagles killed by wind turbines

Currently, the US Fish and Wildlife Service makes eagle permitting and management decisions nationwide based on a limited understanding of the impacts of wind power generation on eagles, and the factors that influence risk at a given facility. Accurate estimates of eagle mortality at wind power facilities form the basis for comparing the magnitudes of mortality rates in different areas and for measuring the benefits of proposed methods of minimizing the collision-caused impacts to eagle populations. Simple counts of observed eagle carcasses at wind facilities are almost certainly underestimates of the true mortality because fatalities can be removed by scavengers, be missed by searchers, or fall outside searched areas. For the latter, models of relative carcass density as a function of distance from the turbine can be fit to observed carcass locations and used to estimate the proportion of carcasses expected to land within an area of any configuration beneath a turbine. In the USA, however, it has been difficult to estimate these models for large birds such as Bald Eagles ( Haliaeetus leucocephalus ) and Golden Eagles ( Aquila chrysaetos ) due to inadequate numbers of dead eagles found at any single facility. In this case, analysis of a surrogate species might be useful to inform carcass distributions. We chose to model the carcass distribution of White-tailed Eagles ( Haliaeetus albicilla ) in Norway as an informative surrogate for Bald Eagles and Golden Eagles in the USA. Our three best-fitting parametric models were very consistent in estimating that 50% (95% CI: 40–60%) of White-tailed Eagle carcasses land within approximately 42 m of the turbines that had 70-m hubs and approximately 40-m blades. Although our models were fit to data from White-tailed Eagles and not Bald or Golden Eagles, applying these models when calculating mortality impacts of wind developments on both eagle species will likely improve the accuracy of post-construction mortality estimates, particularly at sites where substantial areas may be unsearchable. Accurate post-construction mortality estimates can inform pre-construction fatality prediction models. Resource managers can determine whether their conditions are sufficiently similar to those we modeled to warrant the use of these models for Bald and Golden Eagle carcass distributions.

Journal of Raptor Research↗

USGS2016

Cheatgrass percent cover change: Comparing recent estimates to climate change − Driven predictions in the Northern Great Basin

Cheatgrass ( Bromus tectorum L.) is a highly invasive species in the Northern Great Basin that helps decrease fire return intervals. Fire fragments the shrub steppe and reduces its capacity to provide forage for livestock and wildlife and habitat critical to sagebrush obligates. Of particular interest is the greater sage grouse ( Centrocercus urophasianus ), an obligate whose populations have declined so severely due, in part, to increases in cheatgrass and fires that it was considered for inclusion as an endangered species. Remote sensing technologies and satellite archives help scientists monitor terrestrial vegetation globally, including cheatgrass in the Northern Great Basin. Along with geospatial analysis and advanced spatial modeling, these data and technologies can identify areas susceptible to increased cheatgrass cover and compare these with greater sage grouse priority areas for conservation (PAC). Future climate models forecast a warmer and wetter climate for the Northern Great Basin, which likely will force changing cheatgrass dynamics. Therefore, we examine potential climate-caused changes to cheatgrass. Our results indicate that future cheatgrass percent cover will remain stable over more than 80% of the study area when compared with recent estimates, and higher overall cheatgrass cover will occur with slightly more spatial variability. The land area projected to increase or decrease in cheatgrass cover equals 18% and 1%, respectively, making an increase in fire disturbances in greater sage grouse habitat likely. Relative susceptibility measures, created by integrating cheatgrass percent cover and temporal standard deviation datasets, show that potential increases in future cheatgrass cover match future projections. This discovery indicates that some greater sage grouse PACs for conservation could be at heightened risk of fire disturbance. Multiple factors will affect future cheatgrass cover including changes in precipitation timing and totals and increases in freeze-thaw cycles. Understanding these effects can help direct land management, guide scientific research, and influence policy.

Idaho, Montana, Nevada, Oregon, Utah, Washington, ↗

USGS2018

The relative importance of intrinsic and extrinsic drivers to population growth vary among local populations of Greater Sage-Grouse: An integrated population modeling approach

Consideration of ecological scale is fundamental to understanding and managing avian population growth and decline. Empirically driven models for population dynamics and demographic processes across multiple spatial scales can be powerful tools to help guide conservation actions. Integrated population models (IPMs) provide a framework for better parameter estimation by unifying multiple sources of data (e.g., count and demographic data). Hierarchical structure within such models that include random effects allow for varying degrees of data sharing across different spatiotemporal scales. We developed an IPM to investigate Greater Sage-Grouse ( Centrocercus urophasianus ) on the border of California and Nevada, known as the Bi-State Distinct Population Segment. Our analysis integrated 13 years of lek count data ( n > 2,000) and intensive telemetry (VHF and GPS; n > 350 individuals) data across 6 subpopulations. Specifically, we identified the most parsimonious models among varying random effects and density-dependent terms for each population vital rate (e.g., nest survival). Using a joint likelihood process, we integrated the lek count data with the demographic models to estimate apparent abundance and refine vital rate parameter estimates. To investigate effects of climatic conditions, we extended the model to fit a precipitation covariate for instantaneous rate of change ( r ). At a metapopulation extent (i.e. Bi-State), annual population rate of change λ ( e r ) did not favor an overall increasing or decreasing trend through the time series. However, annual changes in λ were driven by changes in precipitation (one-year lag effect). At subpopulation extents, we identified substantial variation in λ and demographic rates. One subpopulation clearly decoupled from the trend at the metapopulation extent and exhibited relatively high risk of extinction as a result of low egg fertility. These findings can inform localized, targeted management actions for specific areas, and status of the species for the larger Bi-State.

The Auk↗

USGS2008

Economic decision making and the application of nonparametric prediction models

Sustained increases in energy prices have focused attention on gas resources in low-permeability shale or in coals that were previously considered economically marginal. Daily well deliverability is often relatively small, although the estimates of the total volumes of recoverable resources in these settings are often large. Planning and development decisions for extraction of such resources must be areawide because profitable extraction requires optimization of scale economies to minimize costs and reduce risk. For an individual firm, the decision to enter such plays depends on reconnaissance-level estimates of regional recoverable resources and on cost estimates to develop untested areas. This paper shows how simple nonparametric local regression models, used to predict technically recoverable resources at untested sites, can be combined with economic models to compute regional-scale cost functions. The context of the worked example is the Devonian Antrim-shale gas play in the Michigan basin. One finding relates to selection of the resource prediction model to be used with economic models. Models chosen because they can best predict aggregate volume over larger areas (many hundreds of sites) smooth out granularity in the distribution of predicted volumes at individual sites. This loss of detail affects the representation of economic cost functions and may affect economic decisions. Second, because some analysts consider unconventional resources to be ubiquitous, the selection and order of specific drilling sites may, in practice, be determined arbitrarily by extraneous factors. The analysis shows a 15-20% gain in gas volume when these simple models are applied to order drilling prospects strategically rather than to choose drilling locations randomly. Copyright ?? 2008 Society of Petroleum Engineers.

SPE Reservoir Evaluation and Engineering↗

USGS2001

Map Showing Susceptibility to Earthquake-Induced Landsliding, San Juan Metropolitan Area, Puerto Rico

Analysis of slope angle and rock type using a geographic information system indicates that about 68 percent of the San Juan metropolitan area has low to no susceptibility to earthquake-induced landslides. This is at least partly due to the fact that 45 percent of the San Juan metropolitan area is constructed on slopes of 3 degrees or less, which are too gentle for landslides to occur. The areas with the highest susceptibility to earthquake-induced landslides account for 6 percent of the surface area. Almost one-quarter (24 percent) of the San Juan metropolitan area is moderately susceptible to earthquake-induced landslides. These areas are mainly in the southern portions of the San Juan metropolitan area, where housing development pressures are currently high because of land availability and the esthetics of greenery and hillside views. The combination of new development and moderate earthquake-induced landslide susceptibility indicate that the southern portions of the San Juan metropolitan area are be at greatest risk.

Open-File Report↗

USGS2019

Inundation, flow dynamics, and damage in the 9 January 2018 Montecito Debris-Flow Event, California, USA: Opportunities and challenges for post-wildfire risk assessment

Shortly before the beginning of the winter rainy season, one of the largest fires in California history (Thomas Fire) substantially increased the susceptibility of steep slopes in Santa Barbara and Ventura Counties to debris flows. On January 9, 2018, before the fire was fully contained, an intense burst of rain fell on the portion of the burn area above Montecito, CA. The rainfall and associated runoff triggered a series of debris flows that mobilized approximately 680,000 m3 of sediment (including boulders >4 m) at velocities up to 4 m/s down urbanized alluvial fans. The resulting destruction (including 23 fatalities, at least 167 injuries, and 408 damaged homes) underscores the need for improved understanding of debris-flow runout in the built environment, and the need for a comprehensive framework to assess the potential loss from debris flows following wildfire. We present observations of the inundation, debris-flow dynamics, and damage from the event. The data include field measurements of flow depth and deposit characteristics made 12 days after the event (before ephemeral features of the deposits were lost to recovery operations); an inventory of building damage; estimates of flow velocity; information on flow timing; soil-hydrologic properties; and post-event imagery and lidar. Together, these data provide rare spatial and dynamic constraints for testing debris-flow runout models, which are needed for advancing post-fire debris-flow hazard assessments. Our analysis also outlines a framework for translating the results of these models into estimates of economic loss based on an adaptation of the Federal Emergency Management Agency’s Hazus model for tsunamis.

California↗

USGS2011

Spatial interpolation schemes of daily precipitation for hydrologic modeling

Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs.

Colorado, Georgia↗

USGS2020

Approaches to highly parameterized inversion: PEST++ Version 5, a software suite for parameter estimation, uncertainty analysis, management optimization and sensitivity analysis

PEST++ Version 5 extends and enhances the functionality of the PEST++ Version 3 software suite, providing environmental modeling practitioners access to updated Version 3 tools as well as new tools to support decision making with environmental models. Version 5 of PEST++ includes tools for global sensitivity analysis (PESTPP-SEN); least-squares parameter estimation with integrated first-order, second-moment parameter and forecast uncertainty estimation (PESTPP-GLM); an iterative, localized ensemble smoother (PESTPP-IES); and a tool for management optimization under uncertainty (PESTPP-OPT). Additionally, all PEST++ Version 5 tools have a built-in fault-tolerant, multithreaded parallel run manager and are model independent, using the same protocol as the widely used PEST software suite. PEST++ Version 5 is consistent with PEST++ Version 3 conventions and design philosophy. The software’s emphasis continues to target efficient and optimized algorithms that have proven beneficial in decision-support settings and can accommodate large, highly parameterized problems. Expanded and new capabilities are now available to express uncertainty using Monte Carlo and analytical uncertainty approaches and allow evaluation of thousands to millions of parameters. New management optimization capabilities in Version 5 also allow environmental models to be used to answer management questions using multiple societal constraints in a risk-based framework. The PEST++ Version 5 software suite can be compiled for Microsoft Windows® and Unix-based operating systems such as Apple and Linux®; the source code is available with a Microsoft Visual Studio® 2019 solution; and CMake support for all three operating system is also provided. PEST++ Version 5 continues to build a foundation for an open-source framework capable of producing model-independent, robust, and efficient decision-support tools for large environmental models. The functionality of each of the PEST++ tools are demonstrated on a simple example problem. Implications of decisions used when using the PEST++ suite tools are also discussed.

Techniques and Methods↗

USGS2023

Identifying drivers of population dynamics for a stream breeding amphibian using time series of egg mass counts

The decline in amphibian populations is one of the starkest examples of the biodiversity crisis. For stream breeding amphibians, alterations to natural flow regimes by dams, water diversions, and climate change have been implicated in declines and extirpations. Identifying drivers of amphibian declines requires long time series of abundance data because amphibian populations can exhibit high natural variability. Multiple population viability analysis (MPVA) models integrate abundance data and share information from different populations to estimate how environmental factors influence population growth. Flow alteration has been linked to declines and extirpations in the Foothill Yellow-legged Frog ( Rana boylii ), a stream breeding amphibian native to California and Oregon. To date, no study has jointly analyzed abundance data from populations throughout the range of R. boylii in an MPVA model. We compiled time series of egg mass counts (an index of adult female abundance) from R. boylii populations in 36 focal streams and fit an MPVA model to quantify how streamflow metrics, stream temperature, and surrounding land cover affect population growth. We found population growth was positively related to stream temperature and was higher in the years following a wet year with high total annual streamflow. Density dependence was weakest (i.e., carrying capacity was highest) for streams with high seasonality of streamflow and intermediate rates of change in streamflow during spring. Our results highlight how altered streamflow can further increase the risk of decline for R. boylii populations. Managing stream conditions to better match natural flow and thermal regimes would benefit the conservation of R. boylii populations.

California, Oregon↗

USGS2024

It's about time: A multistate semicontinuous time mark–recapture model to evaluate seasonal survival and movement rates of juvenile Coho Salmon in a small coastal watershed

Objective Many mark–recapture models assume that releases and recaptures are discrete events, and researchers often aggregate continuous recapture data (e.g., passive integrated transponder [PIT] detections) into coarse temporal scales to satisfy this assumption. This temporal discretization could result in parameter biases by ignoring the individual heterogeneity in the time susceptible to mortality after recapture and the conditions experienced (e.g., temperature and predation risk) before and after recapture. Our objectives were to (1) estimate the amount of bias in survival and emigration rates due to different temporal discretization durations when recapture events occur continuously and (2) apply this semicontinuous model to estimate rates of early emigration and overwinter survival for Coho Salmon Oncorhynchus kisutch in a coastal California watershed. Methods We developed a semicontinuous time multistate mark–recapture model to separately estimated emigration and survival rates throughout the year. We used weekly time-varying occasions paired with discrete spatial states and conducted extensive simulation trials to explore potential model bias. We then applied the model to an existing 4-year dataset of Coho Salmon PIT tag detections. Result Our simulations indicated that that the amount of bias in survival and movement rates decreased as the temporal discretization duration decreased. The confidence interval of the bias estimates included zero with a duration of 8 days, indicating that this duration was sufficiently short to model movement and survival. Results from our Coho Salmon analysis suggest that overwinter survival rate ranged from 0.72 to 0.83, which is higher than previous estimates for Coho Salmon in this region. We estimate that a substantial proportion of smaller juveniles (0.21–0.28 annually) move to downstream nonnatal rearing habitats before the spring smolt migration. Conclusion Our semicontinuous modeling approach can be implemented relatively easily and used to analyze continuous detection data to accurately estimate survival and movement rates. Our analysis of Coho Salmon PIT tag detections implies that previous low estimates of apparent overwinter survival of Coho Salmon were partially due to high movement rates to alternative rearing locations. This contrasts with conclusions from the previous research that suggested that overwinter survival was a major limiting factor for population recovery and implies that species recovery may be improved by considering multiple emigration patterns in the design of future research, monitoring, and restoration projects.

California↗

USGS2006

Flood Study of Warren Brook in Alstead and Cold River in Alstead, Langdon, and Walpole, New Hampshire, 2005

This report presents water-surface elevations and profiles as determined using the U.S. Army Corps of Engineers (USACE) one-dimensional Hydrologic Engineering Center River Analysis System, also known as HEC-RAS. Steady flow water-surface profiles were developed for two stream reaches: the Cold River from its confluence with the Connecticut River in Walpole, through Alstead to the McDermott Bridge in Langdon, NH, and Warren Brook from its confluence with the Cold River to Warren Lake in Alstead, NH. Flood events of a magnitude, which are expected to be equaled or exceeded once on the average during any 10-, 50-, 100-, or 500-year period (recurrence interval), were modeled using HEC-RAS as these flood events are recognized as being significant for flood-plain management, determination of flood insurance rates, and design of structures such as bridges and culverts. These flood events are referred to as the 10-, 50-, 100-, and 500-year floods and have a 10-, 2-, 1-, and 0.2-percent chance, respectively, of being equaled or exceeded during any year. The recurrence intervals represent the long-term average between floods of a specific magnitude. The risk of experiencing rare floods at short intervals or within the same year increases when periods greater than one year are considered. The analyses in this study reflect the flooding potentials based on conditions existing in the communities of Walpole, Alstead and Langdon at the time of completion of this study.

Open-File Report↗

USGS2016

Feline immunodeficiency virus cross-species transmission: Implications for emergence of new lentiviral infections

Owing to a complex history of host-parasite coevolution, lentiviruses exhibit a high degree of species specificity. Given the well-documented viral archeology of HIV emergence following human exposures to SIV, understanding processes that promote successful cross-species lentiviral transmissions is highly relevant. We have previously reported natural cross-species transmission of a subtype of feline immunodeficiency virus, puma lentivirus A (PLVA), between bobcats ( Lynx rufus ) and mountain lions ( Puma concolor ) in a small number of animals in California and Florida. In this study we investigate host-specific selection pressures, within-host viral fitness, and inter- vs. intra-species transmission patterns among a larger collection of PLV isolates from free-ranging bobcats and mountain lions. Analysis of proviral and viral RNA levels demonstrates that PLVA fitness is severely restricted in mountain lions compared to bobcats. We document evidence of diversifying selection in three of six PLVA genomes from mountain lions, but did not detect selection among twenty PLVA isolates from bobcats. These findings support that PLVA is a bobcat-adapted virus, which is less fit in mountain lions and under intense selection pressure in the novel host. Ancestral reconstruction of transmission events reveals intraspecific PLVA transmission has occurred among panthers ( Puma concolor coryi ) in Florida following initial cross-species infection from bobcats. In contrast, interspecific transmission from bobcats to mountain lions predominates in California. These findings document outcomes of cross-species lentiviral transmission events among felids that compare to emergence of HIV from nonhuman primates. IMPORTANCE Cross-species transmission episodes can be singular, dead-end events or can result in viral replication and spread in the new species. The factors that determine which outcome will occur are complex, and the risk of new virus emergence is therefore difficult to predict. Here we use molecular techniques to evaluate transmission, fitness, and adaptation of puma lentivirus A (PLVA) between bobcats and mountain lions in two geographic regions. Our findings illustrate that mountain lion exposure to PLVA is relatively common, but does not routinely result in infections communicable in the new host. This is attributed to efficient species barriers that largely prevent lentiviral adaptation. However, the evolutionary capacity for lentiviruses to adapt to novel environments may ultimately overcome host restriction mechanisms over time and under certain ecological circumstances. This phenomenon provides a unique opportunity to examine cross-species transmission events leading to new lentiviral emergence.

California, Florida↗

USGS2014

Volcanology: Lessons learned from Synthetic Aperture Radar imagery

Twenty years of continuous Earth observation by satellite SAR have resulted in numerous new insights into active volcanism, including a better understanding of subsurface magma storage and transport, deposition of volcanic materials on the surface, and the structure and development of volcanic edifices. This massive archive of data has resulted in fundamental leaps in our understanding of how volcanoes work – for example, identifying magma accumulation at supposedly quiescent volcanoes, even in remote areas or in the absence of ground-based data. In addition, global compilations of volcanic activity facilitate comparison of deformation behavior between different volcanic arcs and statistical evaluation of the strong link between deformation and eruption. SAR data are also increasingly used in timely hazard evaluation thanks to decreases in data latency and growth in processing and analysis techniques. The existing archive of SAR imagery is on the cusp of being enhanced by a new generation of satellite SAR missions, in addition to ground-based and airborne SAR systems, which will provide enhanced temporal and spatial resolution, broader geographic coverage, and improved availability of data to the scientific community. Now is therefore an opportune time to review the contributions of SAR imagery to volcano science, monitoring, and hazard mitigation, and to explore the future potential for SAR in volcanology. Provided that the ever-growing volume of SAR data can be managed effectively, we expect the future application of SAR data to expand from being a research tool for analyzing volcanic activity after the fact, to being a monitoring and research tool capable of imaging a wide variety of processes on different temporal and spatial scales as those processes are occurring. These data can then be used to develop new models of how volcanoes work and to improve quantitative forecasts of volcanic activity as a means of mitigating risk from future eruptions.

Journal of Volcanology and Geothermal Research↗

USGS2013

Probabilistic analysis showing that a combination of bacteroides and methanobrevibacter source tracking markers is effective for identifying waters contaminated by human fecal pollution

Microbial source tracking assays to identify sources of waterborne contamination typically target genetic markers of host-specific microorganisms. However, no bacterial marker has been shown to be 100% host-specific, and cross-reactivity has been noted in studies evaluating known source samples. Using 485 challenge samples from 20 different human and animal fecal sources, this study evaluated microbial source tracking markers including the Bacteroides HF183 16S rRNA, M. smithii nifH, and Enterococcus esp gene targets that have been proposed as potential indicators of human fecal contamination. Bayes' Theorem was used to calculate the conditional probability that these markers or a combination of markers can correctly identify human sources of fecal pollution. All three human-associated markers were detected in 100% of the sewage samples analyzed. Bacteroides HF183 was the most effective marker for determining whether contamination was specifically from a human source, and greater than 98% certainty that contamination was from a human source was shown when both Bacteroides HF183 and M. smithii nifH markers were present. A high degree of certainty was attained even in cases where the prior probability of human fecal contamination was as low as 8.5%. The combination of Bacteroides HF183 and M. smithii nifH source tracking markers can help identify surface waters impacted by human fecal contamination, information useful for prioritizing restoration activities or assessing health risks from exposure to contaminated waters.

Environmental Science & Technology↗

USGS2022

Identifying translocation sites for a climate relict population of Finescale Dace

Translocation is a management strategy that seeks to address threats to fish and wildlife populations by establishing new populations in ecologically suitable areas. Populations of Finescale Dace Chrosomus neogaeus in the Great Plains may benefit from translocation, as they exhibit a climate relict natural history that has led to a disjunct distribution and minimal dispersal opportunities. We assessed the translocation suitability of sites for Finescale Dace in the Belle Fourche River basin, Wyoming–South Dakota, using a ranking approach for output from multiple analyses. We used multivariate analysis to evaluate dissimilarity in fish occurrence and habitat between sites with and without Finescale Dace in contemporary surveys (2018–2019; n = 68). We further evaluated the capacity for sites to support Finescale Dace under base case and future climate change scenarios using the predicted probability of occurrence ( P ) from species distribution models (SDMs) fitted with basinwide fish occurrence data from surveys conducted in 2008–2019 ( n = 124) and spatially continuous environmental variables, including forecasted stream temperature scenarios. Sites with Finescale Dace tended to occur close to standing waterbodies, contained emergent vegetation cover, and did not exhibit large overlap in species-space with either native or nonnative species. Predicted P of Finescale Dace exhibited nonlinear relationships with mean August stream temperature, channel slope, and base flow index. The amount of suitable habitat (i.e., high predicted P ) declined with forecasted stream warming scenarios in the SDMs. This study highlights the utility of using field observations, historical data, and forecasted climate change scenarios to assess translocation site suitability and inform management of at-risk native fish populations, and the results may be transferable to other populations with limited data or restricted distributions.

South Dakota, Wyoming↗