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At least 775 records · Page 43Linked to original sources

USGS2005

Water level dynamics in wetlands and nesting success of Black Terns in Maine

The Black Tern ( Chlidonias niger ) nests in freshwater wetlands that are prone to water level fluctuations, and nest losses to flooding are common. We examined temporal patterns in water levels at six sites with Black Tern colonies in Maine and determined probabilities of flood events and associated nest loss at Douglas Pond, the location of the largest breeding colony. Daily precipitation data from weather stations and water flow data from a flow gauge below Douglas Pond were obtained for 1960-1999. Information on nest losses from three floods at Douglas Pond in 1997-1999 were used to characterize small (6% nest loss), medium (56% nest loss) and large (94% nest loss) flood events, and we calculated probabilities of these three levels of flooding occurring at Douglas Pond using historic water levels data. Water levels generally decreased gradually during the nesting season at colony sites, except at Douglas Pond where water levels fluctuated substantially in response to rain events. Annual probabilities of small, medium, and large flood events were 68%, 35%, and 13% for nests initiated during 23 May-12 July, with similar probabilities for early (23 May-12 June) and late (13 June-12 July) periods. An index of potential nest loss indicated that medium floods at Douglas Pond had the greatest potential effect on nest success because they occurred relatively frequently and inundated large proportions of nests. Nest losses at other colonies were estimated to be approximately 30% of those at Douglas Pond. Nest losses to flooding appear to be common for the Black Tern in Maine and related to spring precipitation patterns, but ultimate effects on breeding productivity are uncertain.

Maine↗

USGS2012

A history of telemetry in fishery research

Biotelemetry has been defined as “the instrumental technique for gaining and transmitting information from a living organism and its environment to a remote observer” (Slater 1965). Biotelemetry typically utilizes wireless transmission of either an audible signal or electronic data to determine location of a tagged animal. Fisheries researchers use location information to gain a variety of insights into migration, habitat use, behavior, productivity, or survival of fish. Biotelemetry can be divided into two basic categories, acoustic or radio, based on mode of transmission, mechanical or electromagnetic energy, and operating frequency. Most acoustic systems in use today transmit at low frequency, between 30 and 300 kHz, while most radio systems transmit at very high frequency, between 30 and 300 MHz (Sisak and Lotimer 1998). Acoustic telemetry is based on the principals of sonar (sound navigation and ranging), which was developed to detect submarines during World War I. The properties of acoustic systems favor their use in deep waters with high conductivity and low turbulence (Winter 1996). Radio telemetry is based on the principals of wireless radio communication, which were first demonstrated by Nikola Tesla in 1893. Radio systems are best suited in shallow waters with relatively low conductivity but have the added benefit of improved signal detection in turbulent conditions and with aerial antennas. Advances in both technologies have resulted in highly efficient transmitter and receiving systems. Advancements in products used for animal telemetry over the past 50 years have generally followed those in the electronics field (Figure 1). Bell Laboratories1 ushered in the age of digital electronics with the invention of the transistor in 1947 (Mann 2000). Today transistors are common in everyday items such as radios, televisions, hearing aids, computers, cell phones and even MP3 players. Consumer demand for inexpensive small electronic devices with increased functionality has continually driven advancements in the field of electronics. These advancements have subsequently led to improvements in biotelemetry transmitters and receivers such as miniaturization of components, increased battery performance, and more powerful micro-processing.

Book chapter↗

USGS2014

Sampling little fish in big rivers: Larval fish detection probabilities in two Lake Erie tributaries and implications for sampling effort and abundance indices

Larval fish are frequently sampled in coastal tributaries to determine factors affecting recruitment, evaluate spawning success, and estimate production from spawning habitats. Imperfect detection of larvae is common, because larval fish are small and unevenly distributed in space and time, and coastal tributaries are often large and heterogeneous. We estimated detection probabilities of larval fish from several taxa in the Maumee and Detroit rivers, the two largest tributaries of Lake Erie. We then demonstrated how accounting for imperfect detection influenced (1) the probability of observing taxa as present relative to sampling effort and (2) abundance indices for larval fish of two Detroit River species. We found that detection probabilities ranged from 0.09 to 0.91 but were always less than 1.0, indicating that imperfect detection is common among taxa and between systems. In general, taxa with high fecundities, small larval length at hatching, and no nesting behaviors had the highest detection probabilities. Also, detection probabilities were higher in the Maumee River than in the Detroit River. Accounting for imperfect detection produced up to fourfold increases in abundance indices for Lake Whitefish Coregonus clupeaformis and Gizzard Shad Dorosoma cepedianum . The effect of accounting for imperfect detection in abundance indices was greatest during periods of low abundance for both species. Detection information can be used to determine the appropriate level of sampling effort for larval fishes and may improve management and conservation decisions based on larval fish data.

Michigan, Ohio↗

USGS2015

Hydrologic influences on water-level changes in the Eastern Snake River Plain aquifer at and near the Idaho National Laboratory, Idaho, 1949-2014

The U.S. Geological Survey, in cooperation with the U.S. Department of Energy, has maintained a water-level monitoring program at the Idaho National Laboratory (INL) since 1949 to systematically measure water levels to provide long-term information on groundwater recharge, discharge, movement, and storage in the eastern Snake River Plain (ESRP) aquifer. During 2014, water levels in the ESRP aquifer reached all-time lows for the period of record, prompting this study to assess the effect that future water-level declines may have on pumps and wells. Water-level data were compared with pump-setting depth to determine the hydraulic head above the current pump setting. Additionally, geophysical logs were examined to address changes in well productivity with water-level declines. Furthermore, hydrologic factors that affect water levels in different areas of the INL were evaluated to help understand why water-level changes occur. Review of pump intake placement and 2014 water-level data indicates that 40 wells completed within the ESRP aquifer at the INL have 20 feet (ft) or less of head above the pump. Nine of the these wells are located in the northeastern and northwestern areas of the INL where recharge is predominantly affected by irrigation, wet and dry cycles of precipitation, and flow in the Big Lost River. Water levels in northeastern and northwestern wells generally show water-level fluctuations of as much as 4.5 ft seasonally and show declines as much as 25 ft during the past 14 years. In the southeastern area of the INL, seven wells were identified as having less than 20 ft of water remaining above the pump. Most of the wells in the southeast show less decline over the period of record compared with wells in the northeast; the smaller declines are probably attributable to less groundwater withdrawal from pumping of wells for irrigation. In addition, most of the southeastern wells show only about a 1–2 ft fluctuation seasonally because they are less influenced by groundwater withdrawals for irrigation. In the southwestern area of the INL, 24 wells were identified as having less than 20 ft of water remaining above the pump. Wells in the southwest also only show small 1–2 ft fluctuations seasonally because of a lack of irrigation influence. Wells show larger fluctuation in water levels closer to the Big Lost River and fluctuate in response to wet and dry cycles of recharge to the Big Lost River. Geophysical logs indicate that most of the wells evaluated will maintain their current production until the water level declines to the depth of the pump. A few of the wells may become less productive once the water level gets to within about 5 ft from the top of the pump. Wells most susceptible to future drought cycles are those in the northeastern and northwestern areas of the INL.

Idaho↗

USGS2022

Potential effects of energy development on environmental resources of the Williston Basin in Montana, North Dakota, and South Dakota—Species of conservation concern

The ecosystems of the Williston Basin provide direct and indirect benefits to society. These benefits include carbon sequestration, flood control, nutrient rich soils for agricultural productivity, and habitat for wildlife. This chapter’s main focus is on the effects of energy development on species that occupy the ecosystems in the Williston Basin. We compiled a list of documented species of conservation concern that are of most interest to Federal regulators and resource managers. Species of concern were either listed as endangered or threatened under the Endangered Species Act or listed by States as species of concern in Natural Heritage Program checklists or State Wildlife Action Plans. All told, we determined that 357 species of concern likely occupy the Williston Basin. These species represented seven different taxonomic groups: plants (native and nonnative), terrestrial invertebrates, birds, mammals, reptiles and amphibians, and fish and mussels. We reviewed the existing scientific information pertaining to potential effects of energy development on these taxonomic groups. Currently, little is known about the abundance and distribution of many of these species. But some information exists that may be useful in predicting the potential effects of energy development on certain taxonomic groups. Most of this information has been developed through scientific research focused on effects to mammal and bird populations. Effects to other taxonomic groups seems to be understudied. In general, it seems that disturbances and modifications associated with development have the potential to negatively affect a wide range of species; however, many studies produce uncertain results because they are not designed to compare populations before and after energy development takes place. Most of these studies also do not monitor resources over multiple years and thus cannot detect population trends. Likewise, there are few examples of landscape-scale assessments of the cumulative effects of energy development that could be used for species or habitat management purposes. We suggest that more research needs to be completed to measure potential effects to a broad range of species in multiple taxonomic groups. This may require also developing some understanding about the basic ecology of many of the species covered in this report. In concert with this more basic research, we also suggest that more comprehensive assessments of potential negative cumulative effects across the Williston Basin should be developed in an effort to guide more strategic management of biological resources.

Montana, North Dakota, South Dakota↗

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↗

USGS1997

Activities of the United States Geological Survey in Pennsylvania

Since the late 1800's, when the U.S. Geological Survey first established a presence in Pennsylvania, the focus of our work has changed from general hydrologic and geologic appraisals to issue-oriented investigations; from predominantly data collection to a balanced program of data collection, interpretation, and research; and from traditional, hand-drawn mapping to digitally produced coverages with specialized themes. Yet our basic mission has not changed. It is as relevant to the resource issues of today as it was when our geologists first arrived in western Pennsylvania in 1884. Continuing in this proud heritage and tradition, the U.S. Geological Survey is moving confidently toward the next century, evolving organizationally and technologically to better meet the needs of our many constituencies. One major organizational change is the recent accession of employees from the former National Biological Service, who now form the Survey's fourth program division, the Biological Resources Division. These employees join forces with colleagues in our other three divisions: Water Resources, Geologic, and National Mapping. More than any other change in decades, the addition of this biological expertise creates new and exciting opportunities for scientific research and public service. This report provides an overview of recent activities in Pennsylvania conducted by the four program divisions and is intended to inform those interested in U.S. Geological Survey products and services. Additional information is available on our home page (at http://wwwpah2o.er.usgs.gov/). Together with numerous Federal, State, and local agencies and organizations who are our customers and partners, we at the U.S. Geological Survey look forward to providing continued scientific contributions and public service to Pennsylvania and the Nation.

Pennsylvania↗

USGS2021

Oyster model inventory: Identifying critical data and modeling approaches to support restoration of oyster reefs in coastal U.S. Gulf of Mexico waters

Executive Summary Along the coast of the U.S. Gulf of Mexico, the eastern oyster ( Crassostrea virginica ) plays important ecological and economic roles. Commercial landings from this region account for more than 50 percent of all U.S. landings; these oyster reefs also provide varied ecosystem services, including nursery habitat for many fish and macroinvertebrate species, shoreline protection, and water-quality maintenance. Declining trends in both total oyster production and functional reef area across this region have spurred investment in restoration of oyster resources, with specific calls for restoration projects to develop a network of reefs and identify broodstock and sanctuary reef restoration sites. Decision making related to restoration and establishment of a network of oyster reefs in the Gulf of Mexico requires information on both the environment and the effects of the environment on the oyster life cycle (including larval movement, survival, oyster recruitment, reproduction, growth, and mortality). Here, we examined the current state of data and model development in this region with the goal of providing an overview of oyster modeling approaches and an inventory of available data and existing oyster models. This report is meant to provide an overview to managers for understanding existing efforts and identify a path forward to most efficiently inform oyster resource management and restoration planning in moving from a single reef management approach to a reef network management approach. Numerous models related to some aspect of the oyster life cycle have been built, calibrated, and validated for various Gulf of Mexico estuaries over the last few decades (over 30 models identified). These models, which could inform site restoration, can be classified into four approaches: (1) oyster Habitat Suitability Index (HSI) models; (2) larval transport models; (3) on-reef oyster models that may include oyster growth, mortality and reproduction, and substrate persistence; and (4) coupled larval transport on-reef metapopulation models that simulate the entire oyster life cycle. The data requirements, model complexity and assumptions, and transferability vary by approach. Specifically, some approaches may offer greater accessibility, flexibility, and transferability spatially or temporally, with minimal data input, but only provide broad information to support site selection. In contrast, other approaches may require significant site-specific data for their construction and validation but may provide more accurate and location-specific data to support site selection for broodstock reefs. Regardless of modeling approach used, data on environmental drivers, such as salinity, water temperature, or water flow impacting oyster metabolism and movement, are required at appropriate spatial and temporal scales. While numerous data collection platforms, environmental models, and research products exist within Gulf of Mexico estuaries to provide important environmental data to use as drivers in the oyster models, significant variability in temporal and spatial coverage of the data, and variation in the availability of future condition models, exists across estuaries. This variation influences the spatial and temporal scales at which oyster models may be developed and impacts the calibration and validation of the oyster models within a given estuary, affecting its potential ability to address specific management or restoration questions. While multiple modeling approaches exist for informing site selection of broodstock or sanctuary oyster reefs, the development, calibration, and validation of a single modeling platform presents the most efficient, transferable, and useful tool for managers across the Gulf of Mexico. The development of a single modeling platform would involve using standardized input variables, governing equations, and assumptions for the modeled oyster processes and outputs, and for standardized calibration and validation procedures that could be applied within each estuary. The differences among estuary applications would require substituting only estuary-specific environmental data, and calibrating and validating the modeling approach with local oyster data. Two modeling approaches likely to be useful include (1) development of a general geospatial HSI modeling framework that could be applied consistently across estuaries and (2) a mechanistic coupled larval transport on-reef metapopulation model requiring only estuarine specific calibration and hydrodynamic models. Both approaches benefit from existing work across multiple Gulf of Mexico estuaries and could provide valuable support for oyster restoration, but may differ in their ability to address specific questions related to oyster restoration. HSI models specifically guide restoration practitioners in determining suitable habitat based on available data. The HSI approach, while currently more widely used and accessible, requires more development of larval suitability and larval input and output components in order to inform reef connectivity. A metapopulation approach considering the full oyster life cycle that simulates both on-reef oyster growth, mortality, reproduction, substrate persistence, and larval transport (ideally with larval growth and mortality) would provide the greatest detail and level of understanding but requires significant up-front investment. The larval oyster model and on-reef oyster model are usually developed independently for systems, although the two approaches can be coupled to represent the entire oyster life cycle in order to characterize and assess a reef metapopulation. This approach may be less accessible and much more data-intensive, however, and it requires some expertise to run and apply to inform oyster resource management. Ultimately, the development of single modeling platforms for each of these approaches would provide flexible tools applicable across all Gulf of Mexico oyster supporting estuaries. By using a single platform for model development, testing, calibrating and validating, and evaluation of modeled future scenarios, oyster restoration scientists and managers would not only be able to examine different scenario outcomes within a single estuary, but could also have comparable modeled results to evaluate potential outcomes, across estuaries and regions, that are not confounded by varying modeled data inputs, governing equations, assumptions, or user judgement.

Alabama, Florida, Louisiana, Mississippi, Texas↗

USGS2019

Pallid sturgeon basin-wide contaminants assessment

Pallid sturgeon (Scaphirhynchus albus), listed as endangered in 1990 under the federal Endangered Species Act (United States Fish and Wildlife Service (USFWS), 1990), have declined due to habitat loss, commercial fishing, and hybridization. Pollution in the Missouri and Mississippi Rivers has to-date only received minor attention as a factor in the on-going decline of wild pallid sturgeon populations (Jacobson et al. 2016a; Bergman 2008). Pallid sturgeon experts and contaminant specialists conceived of the Pallid Sturgeon Basin-Wide Contaminants Assessment (Assessment) to identify potentially harmful contaminants (contaminants of concern), their distribution within pallid sturgeon habitat, and their effects on pallid sturgeon at the landscape level. Extant water quality and analytical chemistry data from samples of river water, sediment, and sturgeon tissues from past studies, assessments, or monitoring activities throughout the species’ range were used to establish a list of contaminants. The list includes: metal and non-metal elements, pesticides, organic industrial chemicals, hormones, nutrients, and other potential water quality contaminants. Environmental samples collected from January 1, 2001 through December 31, 2014, when available, were used for all evaluations. This report is effectively a screening level hazard assessment whereby contituents of concern that may pose a potential harm to pallid sturgeon have been identified. These constituents of concern warrant further examination to determine the level of risk they pose to pallid sturgeon. The Assessment process was one of comparing the existing environmental data for individual constituents to reference values for adverse effects on fish specifically or aquatic life generally. The product of the Assessment is a simplified summary that is geographically organized by pallid sturgeon management unit that generally categorizes each individual contaminant or water quality constituent according to operationally defined levels of concern. This hazard assessment identifies potential constituents of concern to pallid sturgeon and may support prioritization for future data collection and research to enable a quantitative risk assessment. Regional data density at spatial and temporal scales notwithstanding, the Assessment points to some generalities in contaminant concerns within and across management units. Metals but not pesticides are the predominant contaminant of concern in the Great Plains Management Unit (GPMU). In the Central Lowlands Management Unit (CLMU), selenium exceeds benchmark levels. Triazine herbicides are potentially of concern in all but the GPMU. Concentrations of legacy contaminants such as PCBs and DDT and its metabolites exceeded benchmarks in samples from the CLMU, Interior Highlands Mangement Unit (IHMU), and Coastal Plains Management Unit (CPMU), but local and national trends indicate environmental levels of these contaminants continue to decline. Observed concentrations of nutrients and indicators of nutrient pollution were above benchmark levels throughout the pallid sturgeon’s range; however, the significance for pallid sturgeon health specifically is unknown. Almost no information exists on contemporary contaminants of concern such as the natural and synthetic estrogens (estradiol, ethinyl estradiol, and estrone) or polybrominated diphenyls (PBDEs). There are considerable informational data gaps for contaminants throughout the species’ range. Water quality measurements were the most frequent data encountered whereas, sediment and tissue data were orders of magnitude less frequent. The paucity of sediment and tissue concentrations, particularly the latter, prevents any meaningful conclusions regarding adverse effects of these contaminants on the growth and reproduction of pallid sturgeon. However, the Assessment could form the basis for regional workshops with subject matter specialists to develop plans to evaluate the contaminants most likely to affect pallid sturgeon health.

Missouri River basin, Mississippi River basin↗

USGS2023

Effects of noise from oil and gas development on ungulates and small mammals—A science synthesis to inform National Environmental Policy Act analyses

The U.S. Geological Survey is working with Federal land management agencies to develop a series of science syntheses to support environmental effects analyses that agencies conduct to comply with the National Environmental Policy Act (NEPA). This report synthesizes science information about the potential effects of noise from oil and gas development on North American ungulates and small mammals, including rodents and leporids. We conducted a structured search of published scientific literature to find information about noise levels produced during oil and gas development, methods for analyzing sound propagation, the effects of noise on ungulates and small mammals, and measures to reduce noise emissions. We organized the sections of this synthesis to align with standard elements of NEPA analyses. We found that oil and gas development is a common source of human-caused noise on public lands and includes noise sources such as heavy construction and drilling machinery, long-term production machinery, truck traffic, and aircraft. Common techniques for predicting potential noise include field data collection using a sound level meter, inference from previously published data, and sound propagation modeling. A substantial body of research shows that human-caused noise can affect wildlife health and behavior, with variation in sensitivity to noise among species. Studies have shown consistent, detectable effects of noise on ungulates, but the amount of literature on ungulates is very small, and additional research could improve our understanding of differences in effects among species, seasons, and individual indicators of fitness. Several species of small mammals are dependent on audible signals for predator detection and communication, and noise has been shown to affect their vigilance and foraging behavior. However, other studies have documented no effects to rodents in noisy areas, and the effects of noise on small mammals may differ by species and study system. Techniques suggested in the literature for reducing noise emissions include sound barriers, seasonal and daily timing restrictions, traffic control measures, and siting infrastructure to take advantage of natural sound barriers. Public land managers can use this report by incorporating it by reference in NEPA documentation, as supplemental information, or as a general reference for literature about the effects of noise from oil and gas development on ungulates and small mammals.

Scientific Investigations Report↗

USGS2015

Resilience and risk: a demographic model to inform conservation planning for polar bears

Climate change is having widespread ecological effects, including loss of Arctic sea ice. This has led to listing of the polar bear ( Ursus maritimus ) and other ice-dependent marine mammals under the U.S. Endangered Species Act (ESA). Methods are needed to evaluate the effects of climate change on population persistence to inform recovery planning for listed species. For polar bears, this includes understanding interactions between climate and secondary factors, such as subsistence harvest, which provide economic, nutritional, or cultural value to humans. We developed a matrix-based demographic model for polar bears that can be used for population viability analysis and to evaluate the effects of human-caused removals. This model includes density-dependence (the potential for a declining environmental carrying capacity), density-independent limitation, and sex- and age-specific harvest vulnerabilities. We estimated values of adult female survival (0.93–0.96), recruitment (number of yearling cubs per adult female; 0.1–0.3), and carrying capacity (>250 animals) that must be maintained for a hypothetical population to achieve a 90-percent probability of persistence over 100 years. We also developed a state-dependent management framework, based on harvest theory and the potential biological removal method, by linking the demographic model to simulated population assessments. This framework can be used to estimate the maximum sustainable rate of human-caused removals, including subsistence harvest, which maintains a population at its maximum net productivity level. The framework also can be used to calculate a recommended sustainable harvest rate, which generally is lower than the maximum sustainable rate and depends on management objectives, the precision and frequency of population data, and risk tolerance. The historical standard 4.5-percent harvest rate for polar bears, at a 2:1 male-to-female ratio, is reasonable under many biological and management conditions, although lower or higher rates may be appropriate in some cases. Our modeling results suggest that harvest of polar bears is unlikely to accelerate population declines that result from declining carrying capacity caused by sea-ice loss, provided that several conditions are met: (1) the sustainable harvest rate reflects the population’s intrinsic growth rate, and the corresponding harvest level is obtained by applying this rate to an estimate of population size; (2) the sustainable harvest rate reflects the quality of population data (e.g., lower harvest when data are poor); and (3) the level of human-caused removals can be adjusted. Finally, our results suggest that stopgap measures (e.g., further reduction or cessation of harvest when the population size is less than a critical threshold) may be necessary to minimize the incremental risk associated with harvest, if environmental conditions are deteriorating rapidly. We suggest that the demographic model and approaches presented here can serve as a template for conservation planning for polar bears and other species facing similar challenges.

Open-File Report↗

USGS2009

Fire rehabilitation effectiveness: a chronosequence approach for the Great Basin

Federal land management agencies have invested heavily in seeding vegetation for emergency stabilization and rehabilitation (ES&R) of non-forested lands. ES&R projects are implemented to reduce post-fire dominance of non-native annual grasses, minimize probability of recurrent fire, quickly recover lost habitat for sensitive species, and ultimately result in plant communities with desirable characteristics including resistance to invasive species and resilience or ability to recover following disturbance. Land managers lack scientific evidence to verify whether seeding non-forested lands achieves their desired long-term ES&R objectives. The overall objective of our investigation is to determine if ES&R projects increase perennial plant cover, improve community composition, decrease invasive annual plant cover and result in a more desirable fuel structure relative to no treatment following fires while potentially providing habitat for Greater Sage-Grouse, a species of management concern. In addition, we provide the locations and baseline vegetation data for further studies relating to ES&R project impacts. We examined effects of seeding treatments (drill and broadcast) vs. no seeding on biotic and abiotic (bare ground and litter) variables for the dominant climate regimes and ecological types within the Great Basin. We attempted to determine seeding effectiveness to provide desired plant species cover while restricting non-native annual grass cover relative to post-treatment precipitation, post-treatment grazing level and time-since-seeding. Seedings were randomly sampled from all known post-fire seedings that occurred in the four-state area of Idaho, Nevada, Oregon and Utah. Sampling locations were stratified by major land resource area, precipitation, and loam-dominated soils to ensure an adequate spread of locations to provide inference of our findings to similar lands throughout the Great Basin. Nearly 100 sites were located that contained an ES&R project. Of these sites, 61 were seeded by using a drill, 27 were broadcast aerially, and 12 had a combination of both. We randomly sampled three burned and seeded, burned and unseeded, and unburned and unseeded locations in the vicinity of the fire, each within the same ecological site. We measured foliar cover of all plant functional groups (perennial or annual, shrub, grass, forb, native or introduced), biological soil crusts, and abiotic (bare soil and litter) variables using the line-point intercept protocol. Fuel loads and horizontal fuel continuity were measured. We applied linear mixed models to response variables (cover and density of plant groups) relative to the dependent variables (seeding treatments and precipitation/temperature relationships. Post-fire strengths with native perennial grasses or shrubs in mixes did not increase density or cover of these groups significantly relative to unseeded, burned areas. Seeded non-native perennial grasses and the shrub Bassia prostrata were effective in providing more cover in aerial and drill seedings. Seeded non-native perennial grass cover increased with increased annual precipitation regardless of seeding type. Seeding native shrubs, particularly Artemisia tridentata, did not significantly increase shrub cover in burned areas. Cover of undesirable non-native annual grasses was lower in drill seedings relative to unseeded areas but only at higher elevations. Seeding effectiveness after wildfire is unpredictable in drier, low elevation environments, and our findings indicate management objectives are more likely met when focusing efforts on higher elevation or higher precipitation locations where establishment of perennial grasses is more likely. On sites where potential for invasion and dominance of non-native annuals is high, such as lower and drier sites, intensive methods of restoration that include invasive plant control before seeding may be required. Where establishment of native perennial plants is the goal, managers might consider using native-only seed mixtures, because we found that the non-native perennials typically used in Great Basin restoration efforts are selected for their competitive nature and may reduce establishment of less competitive native species. Although we attempted to include information on livestock grazing history after seedings, we were unable to extract sufficient data from files to address this topic that may play an additional role in understanding native plant abundance post-fire seeding. Evaluation of drill and aerial seeding effects on fuel characteristics focused on two metrics that are standard inputs for fire behavior models, fuel load and fuel continuity. Fuel loads were evaluated separately for total fuel load biomass, and the individual components that sum to total biomass, namely herbaceous, shrub, shrub:herbaceous ratio, litter, 10-hour, and 100-hour fuel biomasses. Fuel continuity was evaluated using the following cover categories, total, annual grass, annual forb, perennial forb perennial grass, shrub, litter, vegetative interspace, and perennial interspace. Drill seeding did not affect fuel loads, except to reduce 10-hour fuels, probably due to mechanical destruction of dead and down fuels by the drill seeding equipment. Drill seeding did affect fuel continuity, specifically decreasing total plant cover by increasing perennial grass cover which suppressed annual grass and litter production resulting in a net decrease in continuity, but only at the elevations above approximately 1500m. Aerial seeding had no effect on any fuel load or fuel continuity category. For the Greater Sage-Grouse habitat study, we developed multi-scale empirical models of sage-grouse occupancy in 211 randomly located plots within a 40 million ha portion of the species’ range. We then used these models to predict sage-grouse habitat quality at 101 ES&R seeding projects. We compared conditions at restoration sites to published habitat guidelines. Sage-grouse occupancy was positively related to plot- and landscape-level dwarf sagebrush (Artemisia arbuscula, A. nova, A. tripartita) and big sagebrush steppe, and negatively associated with non-native grass and human development. The predicted probability of sage-grouse occupancy at treated plots was low on average (0.07–0.09) and was not significantly different from burned areas that had not been treated. Restoration was more often successful at higher elevation sites with low annual temperatures, high spring precipitation, and high plant diversity. No plots seeded after fire (n=313) met all overstory guidelines for breeding habitats, but approximately 50% met understory guidelines, particularly for perennial grasses. This trend was similar for summer habitat. Ninety-eight percent of treated plots did not meet winter habitat guidelines. Restoration actions in burned areas did not increase the probability of meeting most guideline criteria. The probability of meeting guidelines was influenced by a latitudinal gradient, local climate, and topography. Post-fire seeding treatments in Great Basin sagebrush shrublands generally have not created high quality habitat for sage-grouse. Understory conditions are more likely to be adequate than those of overstory, but in unfavorable climates, establishing forbs and reducing cheatgrass dominance is unlikely. Reestablishing sagebrush cover will require more than 20 years using the restoration methods of the past two decades. Given current fire frequencies and restoration capabilities, protection of landscapes containing a mix of dwarf sagebrush and big sagebrush steppe, minimal human development, and low non-native plant cover may provide the best opportunity for conservation of sage-grouse habitats. Our database of ES&R locations has used the Land Treatment Digital Library to archive data and location information regarding our study (see Pilliod and Welty 2013). This has contributed to two additional studies. One examined the potential spread of Bassia prostrata (aka Kochia prostrata; forage kochia) from ES&R project locations (Gray and Muir 2013). The second used remote sensing to determine the phenology of vegetation green-up on post-fire seeded sites (Sankey et al. 2013).

California;Idaho;Oregon;Utah↗

USGS2013

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Parwan mineral district in Afghanistan: Chapter CC in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Parwan mineral district, which has gold and copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006, 2007), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Parwan) and the WGS84 datum. The final image mosaics were subdivided into two overlapping tiles or quadrants because of the large size of the target area. The two image tiles (or quadrants) for the North Bamyan area are provided as embedded geotiff images, 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.

Parwan Mineral District↗

USGS2009

Quantifying the spatial details of carbon sequestration potential and performance

Upscaling the spatial and temporal changes of carbon stocks and fluxes from sites to regions is challenging owing to the spatial and temporal variances and covariance of driving variables and the uncertainties in both the model and the input data. Although various modeling approaches have been developed to facilitate the upscaling process, few deal with error transfer from model input to output, and error propagation in time and space. The author has developed the General Ensemble Biogeochemical Modelling System (GEMS) for upscaling carbon stocks and fluxes from sites to regions with measures of uncertainty. This chapter describes the GEMS model, its application to regional- and larger-scale areas, and the new results that demonstrate the challenges of upscaling. GEMS relies on site-scale biogeochemical models to simulate carbon dynamics at the site scale. The spatial deployment of the site-scale model in GEMS is based on the spatial and temporal joint frequency distribution of major driving variables (e.g., land cover and land use change, climate, soils, disturbances, and management). At the site scale, GEMS uses stochastic ensemble simulations to incorporate input uncertainty to quantify uncertainty transfer from input to output, and to identify trends in both input data and simulation results. It permits one to simulate the range of possible permutations of input values and identify the trends and variance in both the input data and results. Using data assimilation techniques, GEMS simulations can be constrained by field and satellite observations, including estimates of net primary production (NPP) from the Moderate Resolution Imaging Spectroradiometer (MODIS), grain yield and cropping practices, and forest inventories. The modeling philosophy embedded in GEMS makes it ideal for assimilating information with various uncertainties to support estimating the spatial details of carbon sequestration potential as well as dynamic monitoring of the performance of carbon sequestration activities over large areas. As a case study, GEMS is applied to simulate the spatial and temporal details of carbon sources, sinks, and uncertainty in the Ridge and Valley ecoregion in the eastern United States

Book chapter↗

USGS2006

Preliminary integrated geologic map databases for the United States: Digital data for the generalized bedrock geologic map, Yukon Flats region, east-central Alaska

The growth in the use of Geographic Information Systems (GIS) has highlighted the need for digital geologic maps that have been attributed with information about age and lithology. Such maps can be conveniently used to generate derivative maps for manifold special purposes such as mineral-resource assessment, metallogenic studies, tectonic studies, and environmental research. This report is part of a series of integrated geologic map databases that cover the entire United States. Three national-scale geologic maps that portray most or all of the United States already exist; for the conterminous U.S., King and Beikman (1974a,b) compiled a map at a scale of 1:2,500,000, Beikman (1980) compiled a map for Alaska at 1:2,500,000 scale, and for the entire U.S., Reed and others (2005a,b) compiled a map at a scale of 1:5,000,000. A digital version of the King and Beikman map was published by Schruben and others (1994). Reed and Bush (2004) produced a digital version of the Reed and others (2005a) map for the conterminous U.S. The present series of maps is intended to provide the next step in increased detail. State geologic maps that range in scale from 1:100,000 to 1:1,000,000 are available for most of the country, and digital versions of these state maps are the basis of this product. The digital geologic maps presented here are in a standardized format as ARC/INFO export files and as ArcView shape files. Data tables that relate the map units to detailed lithologic and age information accompany these GIS files. The map is delivered as a set 1:250,000-scale quadrangle files. To the best of our ability, these quadrangle files are edge-matched with respect to geology. When the maps are merged, the combined attribute tables can be used directly with the merged maps to make derivative maps.

Alaska↗

USGS2017

Patterns in Greater Sage-grouse population dynamics correspond with public grazing records at broad scales

Human land use, such as livestock grazing, can have profound yet varied effects on wildlife interacting within common ecosystems, yet our understanding of land-use effects is often generalized from short-term, local studies that may not correspond with trends at broader scales. Here we used public land records to characterize livestock grazing across Wyoming, USA, and we used Greater Sage-grouse ( Centrocercus urophasianus ) as a model organism to evaluate responses to livestock management. With annual counts of male Sage-grouse from 743 leks (breeding display sites) during 2004–2014, we modeled population trends in response to grazing level (represented by a relative grazing index) and timing across a gradient in vegetation productivity as measured by the Normalized Vegetation Difference Index (NDVI). We found grazing can have both positive and negative effects on Sage-grouse populations depending on the timing and level of grazing. Sage-grouse populations responded positively to higher grazing levels after peak vegetation productivity, but populations declined when similar grazing levels occurred earlier, likely reflecting the sensitivity of cool-season grasses to grazing during peak growth periods. We also found support for the hypothesis that effects of grazing management vary with local vegetation productivity. These results illustrate the importance of broad-scale analyses by revealing patterns in Sage-grouse population trends that may not be inferred from studies at finer scales, and could inform sustainable grazing management in these ecosystems.

Wyoming↗

USGS2005

A comparative analysis of the Global Land Cover 2000 and MODIS land cover data sets

Accurate and up-to-date global land cover data sets are necessary for various global change research studies including climate change, biodiversity conservation, ecosystem assessment, and environmental modeling. In recent years, substantial advancement has been achieved in generating such data products. Yet, we are far from producing geospatially consistent high-quality data at an operational level. We compared the recently available Global Land Cover 2000 (GLC-2000) and MODerate resolution Imaging Spectrometer (MODIS) global land cover data to evaluate the similarities and differences in methodologies and results, and to identify areas of spatial agreement and disagreement. These two global land cover data sets were prepared using different data sources, classification systems, and methodologies, but using the same spatial resolution (i.e., 1 km) satellite data. Our analysis shows a general agreement at the class aggregate level except for savannas/shrublands, and wetlands. The disagreement, however, increases when comparing detailed land cover classes. Similarly, percent agreement between the two data sets was found to be highly variable among biomes. The identified areas of spatial agreement and disagreement will be useful for both data producers and users. Data producers may use the areas of spatial agreement for training area selection and pay special attention to areas of disagreement for further improvement in future land cover characterization and mapping. Users can conveniently use the findings in the areas of agreement, whereas users might need to verify the informaiton in the areas of disagreement with the help of secondary information. Learning from past experience and building on the existing infrastructure (e.g., regional networks), further research is necessary to (1) reduce ambiguity in land cover definitions, (2) increase availability of improved spatial, spectral, radiometric, and geometric resolution satellite data, and (3) develop advanced classification algorithms.

Remote Sensing of Environment↗

USGS2019

Hurricane Sandy impacts on coastal wetland resilience

The goal of this research was to evaluate the impacts of Hurricane Sandy on surface elevation trends in estuarine marshes located across the northeast region of the United States from Virginia to Maine using data from an opportunistic (in other words, not strategic) and collaborative network (from here on, an opportunistic network) of surface elevation table-marker horizon (SET-MH) stations. First, we built a data-base of metadata for 965 individual stations from 96 unique geographical locations that included the location, geomorphic setting, and wetland type for each SET-MH station. The dominant estuarine settings included in the analyses were back-barrier lagoonal marshes and emergent marshes along embayments and tidal tributaries. We then calculated prestorm elevation trends to compare to poststorm elevation measurements to determine the storm impact on each station trend. We hypothesized that the effect of Hurricane Sandy on marsh elevation trends would differ by position relative to landfall (right or left) and distance from landfall in southern New Jersey, as both of these variables influence the presence or absence of storm surge as a result of the physical characteristics of tropical cyclones (in other words, strongest winds typically occur to the right of landfall). Storm surge was spatially less extensive and less deep (~1 meter [m]) in marshes located to the left (in other words, south) of landfall compared to marshes located to the right (in other words, north) of landfall where storm surge covered a larger area and was deeper (3–4 m). About 63 percent of 223 eligible stations had a poststorm trend that was similar to the prestorm trend (in other words, less than ±5 millimeters [mm]), indicating little storm impact on elevation trends at those sites. The remaining 37 percent of stations exhibited significant poststorm deviations from the prestorm trend (in other words, greater than ±5 mm). Of these, stations located to the left of landfall had a significant and greater deviation in their elevation trend, and the deviation was more likely to be positive (elevation gain) compared to marshes located to the right of landfall, which had a significant deviation in their elevation trend that was more likely to be negative (elevation loss). This finding is directly related to storm surge impacts on marsh sediment deposition, where deep storm surge (3–4 m) results in sediment deposition in habitats inland of coastal marshes but less so in the marshes themselves. Substrate compaction by the storm surge over-burden may have contributed to elevation loss, but this was not measured because sufficient marker horizon data were not available for analysis. In contrast, to the left of landfall the wind-driven flooding of sediment laden water pushed into the headwaters of rivers and small bays with an ~1 m surge, and resulted in more prevalent sediment deposition on the marsh surfaces and elevation gain. In general, the findings support previous research showing that the physical characteristics of the storm (for example, wind speed, storm surge height, impact angle of landfall) combined with the local wetland conditions (for example, marsh productivity, groundwater level, tide height) are important factors determining a storm’s impact on soil elevation, and that the soil elevation response can vary widely among multiple wetland sites impacted by the same storm and among different storms for the same wetland site. The final objective of this project was to create a framework using metadata from the opportunistic network of SET-MH stations that could be used to develop a strategic monitoring network designed to address specific climate change impacts and related phenomena identified by land managers and stakeholders. We evaluated the spatial distribution and density of SET-MH stations in relation to geographic coverage, marsh setting, availability of public land, and historical storm surge footprints and hurricane return intervals in order to identify gaps in our understanding of risk and our ability to assess it. Analyses revealed that the general geographic coverage of SET-MH stations is limited given the low percentage of marsh patches with stations, low density of stations, the clumped distribution of stations, and the often limited and uneven distribution of stations in wetlands with a high historical frequency of hurricane strikes and storm surge impacts. These findings can be used by managers and planners to inform the creation of a strategic monitoring network that can, in turn, inform management and adaptation plans for coastal resources in the region. Final plan designs will need to consider financial and infrastructural support required for station maintenance, as well as data collection and management over the long term.

Open-File Report↗