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204 records · Page 12Linked to original sources
USGS2012

White-nose syndrome in bats: U.S. Geological Survey updates

White-nose syndrome (WNS) is a devastating disease that has killed millions of hibernating bats since it first appeared in New York in 2007 and has spread at an alarming rate from the northeastern to the central United States and Canada. The disease is named for the white fungus Geomyces destructans that infects the skin of the muzzle, ears, and wings of hibernating bats. The U.S. Geological Survey (USGS) National Wildlife Health Center (NWHC), the USGS Fort Collins Science Center, the U.S. Fish and Wildlife Service, and other partners continue to play a primary role in WNS research. Studies conducted at the NWHC led to the discovery (Blehert and others, 2009), characterization, and naming (Gargas and others, 2009) of the cold-loving fungus G. destructans and to the development of standardized criteria for diagnosing the disease (Meteyer and others, 2009). Additionally, scientists at the NWHC have pioneered laboratory techniques for studying the effects of the fungus on hibernating bats (Lorch and others, 2011). To determine if bats are affected by white-nose syndrome, scientists look for a characteristic microscopic pattern of skin erosion caused by G. destructans (Meteyer and others, 2009). Field signs of WNS can include visible white fungal growth on the bat's muzzle, wings, or both, but these signs alone are not a reliable disease indicator - laboratory examination and testing are required for disease confirmation. Infected bats also arouse from hibernation more frequently than uninfected bats (Warnecke and others, 2012) and often display abnormal behaviors in their hibernation sites, such as congregating at or near cave openings and daytime flights during winter. These abnormal behaviors may contribute to the bat's accelerated consumption of stored fat reserves, causing emaciation, a characteristic documented in some of the bats that die with WNS. During hibernation, bats likely have lowered immunity (Bouma and others, 2010), which may facilitate the ability of G. destructans to colonize and damage large areas of wing membrane (fig. 2). A current hypothesis suggests that erosion or ulceration of wing membrane caused by the fungus has the potential to alter the physiology of hibernating bats, resulting in fatal disruption of hydration, electrolyte balance, circulation, and thermoregulation (Cryan and others, 2010). Current estimates of bat population declines in the northeastern United States since the emergence of WNS are over 80 percent (Turner and others, 2011). This sudden and widespread mortality associated with WNS is unprecedented in hibernating bats, among which large-scale disease outbreaks have not been previously documented. It is unlikely that species of bats affected by WNS will recover quickly because most are long-lived and have only a single pup per year. Consequently, repopulation after widespread mortality of breeding adults will be a slow process. Worldwide, bats play essential roles as pollinators, seed dispersers, and as primary consumers of insects. The true ecological consequences of the recent large-scale reductions in populations of hibernating bats are not yet known. However, farmers might feel the impact. A recent economic analysis indicated that insect control services (ecosystem services) provided by bats to U.S. agriculture is valued between 4 to 50 billion dollars nationwide per year (Boyles and others, 2011). The number of North American bats estimated to have died from WNS thus far had the capacity to consume up to 8,000 tons of insects per year (Boyles and others, 2011). The area of North America affected by WNS continues to expand. Within the last 2 years, the disease has been confirmed in several Central States, including Alabama, Indiana, Kentucky, Ohio, Tennessee, and Missouri. High mortality of bats has not yet been reported at these locations, and it remains to be seen if WNS will develop and manifest in other States with the same severity as that in the Northeast.

Alabama;Connecticut;Delaware;Illinois;Indiana;Iowa↗
USGS2019

The effects of management practices on grassland birds — An introduction to North American grasslands and the practices used to manage grasslands and grassland birds

The Great Plains of North America is defined as the land mass that encompasses the entire central portion of the North American continent that, at the time of European settlement, was an unbroken expanse of primarily herbaceous vegetation. The Great Plains extend from central Saskatchewan and Alberta to central Mexico and from Indiana to the Rocky Mountains. The expanses of herbaceous vegetation are often referred to as native prairie or native grasslands. Native grasslands share the characteristics of a general uniformity in vegetation structure, dominance by grasses and forbs, a near absence of trees and shrubs, annual precipitation ranging from 25 to 100 centimeters, extreme intra-annual fluctuations in temperature and precipitation, and a flat to rolling topography over which fires can spread. To the west of the Great Plains lie the sagebrush communities of the Great Basin, which extend from British Columbia and Saskatchewan to northern Arizona and New Mexico and from the eastern slopes of the Sierra Nevada and Cascade mountain ranges to western South Dakota. Sagebrush communities share similar characteristics to native grasslands, but their location east of the Rocky Mountains creates a more moderating influence from prevailing westerly winds that affect timing of peak precipitation and growth form of dominant vegetation. Native grasslands and sagebrush communities harbor a diverse array of grassland, wetland, and woodland plant and animal communities that are uniquely adapted to the natural forces of the Great Plains and Great Basin, namely the interactive forces of climate, fire, and grazing. The arrival of European settlers to North America brought profound change to native grassland and sagebrush communities, including the establishment of permanent towns and cities, the proliferation of cropland-based agricultural systems, and the suppression of wildfires. The near extirpation of bison by the 1860s paved the way for dramatic changes in the dominant grazers and a shift in the disturbance patterns that historically influenced vegetation structure. The greatest threat to native grasslands and sagebrush communities in modern times is their loss due to conversion to rowcrop agriculture and to urbanization. Concomitant with habitat loss is a precipitous decline in populations of bird species that evolved with, and are uniquely adapted to, the native grassland and sagebrush habitats. Avian population trends are linked strongly to agricultural land use. Besides outright loss of suitable breeding habitat, agricultural practices affect birds through factors such as pesticide exposure, habitat fragmentation, shifts in predator community composition, and occurrence of brood parasites. Bird populations face other stressors, such as loss of habitat to and behavioral avoidance of urbanized areas, roads, and infrastructure associated with energy production. Despite the many anthropogenic changes to North American grassland and sagebrush communities, some bird species are adaptable and opportunistic in their habitat selection and now utilize one or more human-created habitats. Human-created habitats include pastures, hayfields, agricultural terraces, crop buffer strips, field borders, grassed waterways, fencerows, road rights-of-way, airports, reclaimed coal mines, and planted wildlife cover. Fields of seeded grasslands enrolled in Federal long-term set-aside programs, such as the Conservation Reserve Program in the United States and the Permanent Cover Program in Canada, provide important nesting habitat for grassland bird species. The array of habitats used by birds makes habitat and avian management a complex undertaking, and the scale (for example, local, regional, international) at which management actions can be implemented are such that a universal approach to managing grasslands for the conservation of the entire suite of bird species does not exist. Experienced land managers recognize that it is impossible to manage for all bird species simultaneously, and thus, prioritization is necessary towards those habitats or bird species that the manager or management agency ranks highest for a specific region or management unit. The primary tools available for management are burning, grazing, mowing, herbicide application, and idling, but before choosing a particular practice, a manager will want to consider issues of seasonality, intensity, and frequency. Despite the thousands of studies that are cited in this compendium, much remains unknown about the effects of management practices on bird species. The series of species accounts in this compendium review the current state of knowledge regarding management of grassland and sagebrush bird species and summarize information on the effects of management practices on individual species. The accounts do not give definitive statements on the effects of management practices for any particular species, primarily because there are very few replicated studies in which identical management practices have been applied in the same geographical area with consistent results, which are elements necessary to provide concrete recommendations for the management of a particular species in a particular area. Documentation of the effects of management treatments on individual species through statistically sound methods that incorporate multiple years and locations will further scientists’ and land managers’ knowledge far more than 1–2-year studies that are limited in scope as well as time, but studies of that scope and breadth are rare.

Professional Paper↗
USGS2017

Multinomial N-mixture models improve the applicability of electrofishing for developing population estimates of stream-dwelling Smallmouth Bass

Failure to account for variable detection across survey conditions constrains progressive stream ecology and can lead to erroneous stream fish management and conservation decisions. In addition to variable detection’s confounding long-term stream fish population trends, reliable abundance estimates across a wide range of survey conditions are fundamental to establishing species–environment relationships. Despite major advancements in accounting for variable detection when surveying animal populations, these approaches remain largely ignored by stream fish scientists, and CPUE remains the most common metric used by researchers and managers. One notable advancement for addressing the challenges of variable detection is the multinomial N -mixture model. Multinomial N -mixture models use a flexible hierarchical framework to model the detection process across sites as a function of covariates; they also accommodate common fisheries survey methods, such as removal and capture–recapture. Effective monitoring of stream-dwelling Smallmouth Bass Micropterus dolomieu populations has long been challenging; therefore, our objective was to examine the use of multinomial N -mixture models to improve the applicability of electrofishing for estimating absolute abundance. We sampled Smallmouth Bass populations by using tow-barge electrofishing across a range of environmental conditions in streams of the Ozark Highlands ecoregion. Using an information-theoretic approach, we identified effort, water clarity, wetted channel width, and water depth as covariates that were related to variable Smallmouth Bass electrofishing detection. Smallmouth Bass abundance estimates derived from our top model consistently agreed with baseline estimates obtained via snorkel surveys. Additionally, confidence intervals from the multinomial N -mixture models were consistently more precise than those of unbiased Petersen capture–recapture estimates due to the dependency among data sets in the hierarchical framework. We demonstrate the application of this contemporary population estimation method to address a longstanding stream fish management issue. We also detail the advantages and trade-offs of hierarchical population estimation methods relative to CPUE and estimation methods that model each site separately.

Missouri, Oklahoma↗
USGS2017

The Snowmastodon Project

Studies of terrestrial biotic and environmental dynamics of the last interglacial period, Marine Oxygen Isotope Stage (MIS) 5, provide insight into the effects of long-term climate change on Pleistocene ecosystems. In North America, however, there are relatively few fossil sites that definitively date to MIS 5. Even fewer contain multiple ecosystem components (vertebrates, invertebrates, plants) that have been studied in detail, and none are located at high elevation. Thus, our view of North American ecosystems during MIS 5 is, at best, an incomplete composite view, and alpine ecosystems are entirely undocumented. The Ziegler Reservoir fossil site allows us to begin filling these gaps. Discovered on October 14, 2010 by a construction crew while enlarging a small reservoir near Snowmass Village, Colorado (USA), the site is situated high in the Rocky Mountains at an elevation of ~ 2705 m. Initial excavations exposed a series of stacked fossil ecosystems, including abundant faunal and floral components. Subsequent work revealed an exceptionally diverse biota composed of nearly 6000 large bones of late Pleistocene megafauna, including mastodons, mammoths, ground sloths, horses, camels, deer, bison, black bear, coyotes, and big horn sheep. This collection is complemented by more than 200 bones from at least 40 species of small animals including otters, muskrats, minks, rabbits, beavers, frogs, lizards, snakes, fish, and birds, and more than 20,000 salamander bones. Geomorphic evidence and multiple dating techniques show that the small, ridge-top basin containing the site was formed by a lateral lobe of a valley glacier that filled, and ultimately overtopped, the Snowmass Creek drainage during the Bull Lake glaciation (MIS 6). When the glacier receded, a lake that occupied the basin began to fill slowly with what is hypothesized to be eolian sediment and occasional input from slope failures of the impounding moraine. As sedimentation continued, the lake transformed first into a shallow pond, then a marsh, and later an alpine meadow. In all, the Ziegler Reservoir sedimentary record spans the time encompassed by the end of MIS 6, all of MIS 5 and MIS 4, and the earliest part of MIS 3. MIS 5e, which is considered to be the peak warmth of the last interglacial period, is especially well represented. Preservation of organic material at the Ziegler Reservoir fossil site is exceptional. Even after more than 100,000 years of burial, sedge and willow leaves were still green, mollusks and gastropods showed color, beetle parts remained iridescent, fossil conifer cones were intact, and an entire beach of 20-meter-long driftwood logs was found intact. The exquisite preservation allowed for detailed analysis of pollen, plant macrofossils, conifer cones, and fossil wood, as well as insects, chironomids, mollusks, ostracodes, and other invertebrates — all in addition to the spectacular faunal remains. This special volume of Quaternary Research represents a comprehensive scientific report of “The Snowmastodon Project,” as the investigations at the Ziegler Reservoir fossil site came to be known. Summarizing the work of scientists from more than 20 institutions, the volume details the environments in which the animals lived, provides insight into how they died, and forms the foundation of our understanding of alpine ecosystem dynamics during the last interglacial period in the Rocky Mountains.

Quaternary Research↗
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↗
USGS2013

Natural-color and color-infrared image mosaics of the Colorado River corridor in Arizona derived from the May 2009 airborne image collection

The Grand Canyon Monitoring and Research Center (GCMRC) of the U.S. Geological Survey (USGS) periodically collects airborne image data for the Colorado River corridor within Arizona (fig. 1) to allow scientists to study the impacts of Glen Canyon Dam water release on the corridor’s natural and cultural resources. These data are collected from just above Glen Canyon Dam (in Lake Powell) down to the entrance of Lake Mead, for a total distance of 450 kilometers (km) and within a 500-meter (m) swath centered on the river’s mainstem and its seven main tributaries (fig. 1). The most recent airborne data collection in 2009 acquired image data in four wavelength bands (blue, green, red, and near infrared) at a spatial resolution of 20 centimeters (cm). The image collection used the latest model of the Leica ADS40 airborne digital sensor (the SH52), which uses a single optic for all four bands and collects and stores band radiance in 12-bits. Davis (2012) reported on the performance of the SH52 sensor and on the processing steps required to produce the nearly flawless four-band image mosaic (sectioned into map tiles) for the river corridor. The final image mosaic has a total of only 3 km of surface defects in addition to some areas of cloud shadow because of persistent inclement weather during data collection. The 2009 four-band image mosaic is perhaps the best image dataset that exists for the entire Arizona part of the Colorado River. Some analyses of these image mosaics do not require the full 12-bit dynamic range or all four bands of the calibrated image database, in which atmospheric scattering (or haze) had not been removed from the four bands. To provide scientists and the general public with image products that are more useful for visual interpretation, the 12-bit image data were converted to 8-bit natural-color and color-infrared images, which also removed atmospheric scattering within each wavelength-band image. The conversion required an evaluation of the histograms of each band’s digital-number population within each map tile throughout the corridor and the determination of the digital numbers corresponding to the lower and upper one percent of the picture-element population within each map tile. Visual examination of the image tiles that were given a 1-percent stretch (whereby the lower 1- percent 12-bit digital number is assigned an 8-bit value of zero and the upper 1-percent 12-bit digital number is assigned an 8-bit value of 255) indicated that this stretch sufficiently removed atmospheric scattering, which provided improved image clarity and true natural colors for all surface materials. The lower and upper 1-percent, 12-bit digital numbers for each wavelength-band image in the image tiles exhibit erratic variations along the river corridor; the variations exhibited similar trends in both the lower and upper 1-percent digital numbers for all four wavelength-band images (figs. 2–5). The erratic variations are attributed to (1) daily variations in atmospheric water-vapor content due to monsoonal storms, (2) variations in channel water color due to variable sediment input from tributaries, and (3) variations in the amount of topographic shadows within each image tile, in which reflectance is dominated by atmospheric scattering. To make the surface colors of the stretched, 8-bit images consistent among adjacent image tiles, it was necessary to average both the lower and upper 1-percent digital values for each wavelength-band image over 20 river miles to subdue the erratic variations. The average lower and upper 1-percent digital numbers for each image tile (figs. 2–5) were used to convert the 12-bit image values to 8-bit values and the resulting 8-bit four-band images were stored as natural-color (red, green, and blue wavelength bands) and color-infrared (near-infrared, red, and green wavelength bands) images in embedded geotiff format, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. All image data are projected in the State Plane (SP) map projection using the central Arizona zone (202) and the North American Datum of 1983 (NAD83). The map-tile scheme used to segment the corridor image mosaic followed the standard USGS quarter-quadrangle (QQ) map borders, but the high resolution (20 cm) of the images required further quarter segmentation (QQQ) of the standard QQ tiles, where the image mosaic covered a large fraction of a QQ map tile (segmentation shown in (figure 6), where QQ_1 to QQ_4 shows the number convention used to designate a quarter of a QQ tile). To minimize the size of each image tile, each image or map tile was subset to only include that part of the tile that had image data. In addition, some QQQ image tiles within a QQ tile were combined when adjacent QQQ map tiles were small. Thus, some image tiles consist of combinations of QQQ map tiles, some consist of an entire QQ map tile, and some consist of two adjoining QQ map tiles. The final image tiles number 143, which is a large number of files to list on the Internet for both the natural-color and color-infrared images. Thus, the image tiles were placed in seven file folders based on the one-half-degree geographic boundaries within the study area (fig. 7). The map tiles in each file folder were compressed to minimize folder size for more efficient downloading. The file folders are sequentially referred to as zone 1 through zone 7, proceeding down river (fig. 7). The QQ designations of the image tiles contained within each folder or zone are shown on the index map for each respective zone (figs. 8–14).

Arizona↗