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USGS2008

Comparison of blood aminotransferase methods for assessment of myopathy and hepatopathy in Florida manatees (Trichechus manatus latirostris)

Muscle injury is common in Florida manatees (Trichechus manatus latirostris). Plasma aspartate amino-transferase (AST) is frequently used to assess muscular damage in capture myopathy and traumatic injury. Therefore, accurate measurement of AST and alanine aminotransferase (ALT) is important in managed, free-ranging animals, as well as in those rehabilitating from injury. Activities of these enzymes, however, are usually not increased in manatees with either acute or chronic muscle damage, despite marked increases in plasma creatine kinase activity. It is hypothesized that this absence of response is due to apoenzymes in the blood not detected by commonly used veterinary assays. Addition of coenzyme pyridoxal-5-phosphate (P5P or vitamin B6) should, therefore, result in higher measured enzyme activities. The objective of this study was to determine the most accurate, precise, and diagnostically useful method for aminotransferase measurement in manatees that can be used in veterinary practices and diagnostic laboratories. Additionally, appropriate collection and storage techniques were assessed. The use of an optimized commercial wet chemical assay with 100 ??mol P5P resulted in a positive bias of measured enzyme activities in a healthy population of animals. However, AST and ALT were still much lower than that typically observed in domestic animals and should not be used alone in the assessment of capture myopathy and muscular trauma. Additionally, the dry chemistry analyzer, typically used in clinics, reported significantly higher and less precise AST and ALT activities with poor correlation to those measured with wet chemical methods found in diagnostic laboratories. Therefore, these results cannot be clinically compared. Overall, the optimized wet chemical method was the most precise and diagnostically useful measurement of aminotransferase in samples. Additionally, there was a statistically significant difference between paired serum and plasma measurement, indicating that separate reference intervals should be established for serum and plasma. Finally, storage of these enzymes at -70??C for 1 mo resulted in up to a 25% decrease in enzymatic activity in manatee plasma. Copyright 2008 by American Association of Zoo Veterinarians.

Journal of Zoo and Wildlife Medicine↗

USGS1997

Strategic plan for the National Mapping Divison of the U.S. Geological Survey

The National Mapping Division (NMD) has developed this comprehensive strategic plan to chart its course over the next decade. To meet the challenge of the future, the NMD is changing its program emphasis, methods of responding to customer need and business practices. The NMD Strategic Plan identifies the new direction for the Division through a series of goals and actions for managers to use in formulating plans, establishing program emphasis, and determining resource needs and allocations into the next century. The Plan refines the NMD mission on the basis of several key issues that are expected to face the Division in the next decade. Th first of these is the continuing advances in technology and telecommunications. Related to this is the growth in the use of geographic information systems (GIS) and the demand for data to use in GIS's. Also, a trend exists toward decreasing cost of both the data and the systems, leading to even more demand for and use of data and technology by more users. Another is a changing customer base and increasing demand for NMD products and services. Finally, the financial resource available to the NMD are anticipated to remain relatively static. The Plan assumes that a much greater reliance on partnerships with other government agencies and the private sector for production activities will be permanent. It calls for significantly greater emphasis on the inherently governmental information management responsibilities and on geographic research to support the Division's mission. Multipartner consortia and shared funding agreements will constitute the basis for meeting most mapping needs in the future, with the NMD appropriation focused on map revision in areas of importance to the Federal Government. Mapping Centers will be encouraged to increase partnership agreements to meet mission requirements. The Division will continue to constrain employment, targeting new hiring to specific skills needed to support the revised mission in areas such as quality assurance, data standards development and maintenance, contract management, and information management. Retraining opportunities for current employees will be a high priority. The Bureau Strategic Plan was reviewed carefully to assure that the NMD Strategic Plan would be consistent with it. The Division planning team built on the conclusion of the Bureau Plan regarding the political, economic, societal, and global force that will affect our program in the future. The NMD Strategic Plan also embraces all of the core competencies and business activities.

Report↗

USGS2006

Monitoring and modeling to predict Escherichia coli at Presque Isle Beach 2, City of Erie, Erie County, Pennsylvania

The Lake Erie shoreline in Pennsylvania spans nearly 40 miles and is a valuable recreational resource for Erie County. Nearly 7 miles of the Lake Erie shoreline lies within Presque Isle State Park in Erie, Pa. Concentrations of Escherichia coli (E. coli) bacteria at permitted Presque Isle beaches occasionally exceed the single-sample bathing-water standard, resulting in unsafe swimming conditions and closure of the beaches. E. coli concentrations and other water-quality and environmental data collected at Presque Isle Beach 2 during the 2004 and 2005 recreational seasons were used to develop models using tobit regression analyses to predict E. coli concentrations. All variables statistically related to E. coli concentrations were included in the initial regression analyses, and after several iterations, only those explanatory variables that made the models significantly better at predicting E. coli concentrations were included in the final models. Regression models were developed using data from 2004, 2005, and the combined 2-year dataset. Variables in the 2004 model and the combined 2004-2005 model were log10 turbidity, rain weight, wave height (calculated), and wind direction. Variables in the 2005 model were log10 turbidity and wind direction. Explanatory variables not included in the final models were water temperature, streamflow, wind speed, and current speed; model results indicated these variables did not meet significance criteria at the 95-percent confidence level (probabilities were greater than 0.05). The predicted E. coli concentrations produced by the models were used to develop probabilities that concentrations would exceed the single-sample bathing-water standard for E. coli of 235 colonies per 100 milliliters. Analysis of the exceedence probabilities helped determine a threshold probability for each model, chosen such that the correct number of exceedences and nonexceedences was maximized and the number of false positives and false negatives was minimized. Future samples with computed exceedence probabilities higher than the selected threshold probability, as determined by the model, will likely exceed the E. coli standard and a beach advisory or closing may need to be issued; computed exceedence probabilities lower than the threshold probability will likely indicate the standard will not be exceeded. Additional data collected each year can be used to test and possibly improve the model. This study will aid beach managers in more rapidly determining when waters are not safe for recreational use and, subsequently, when to issue beach advisories or closings.

Pennsylvania↗

USGS2026

Informing policy response to declining water supply in the Colorado River basin: Linking water supply management with outcomes for fish communities

Water-supply managers in the Colorado River Basin are tasked with balancing consumptive water use with natural water supply. Decisions associated with water-supply policy can include where and how much water consumption occurs, where water could be stored, and how to operate reservoirs. Water-supply decisions often affect other resources including energy production, recreation and aquatic ecosystems. The goal of this project was to model how different water supply management scenarios might affect riverine ecosystems with a specific focus on potential impacts on federally listed fish populations, including threatened humpback chub (Gila cypha) and endangered Colorado pikeminnow (Ptychocheilus lucius) and razorback sucker (Xyrauchen texanus). Threats to these endemic species include introduced non-native fish species that often become invasive, like smallmouth bass (Micropterus dolomieu), and altered physical conditions that may favor these non-native fish species over the endemic fish species. Changes in how water supply may be managed in the Colorado River Basin can affect physical conditions in rivers by altering how much water flows through a particular river segment at a given time, by changing the extent of riverine ecosystems between reservoirs, and by determining the quality of water released from storage reservoirs with fixed release elevation (e.g., full reservoirs generally release colder water). To address our goal, we developed tools that coupled water storage models, river temperature models and fish population models to examine how different scenarios to operate Lake Mead, Lake Powell, and Flaming Gorge Reservoir, the three largest reservoirs in the watershed, may affect fish populations. We developed our work plan when available water supply was diminished. At the end of our project period (May 2022), Lake Powell and Lake Mead contained historically low water levels, and our models were being used in evaluating different options for operating Lake Powell by the Bureau of Reclamation and other stakeholders.

Arizona, Utah, Wyoming↗

USGS2017

Delineation of marsh types and marsh-type change in coastal Louisiana for 2007 and 2013

The Bureau of Ocean Energy Management researchers often require detailed information regarding emergent marsh vegetation types (such as fresh, intermediate, brackish, and saline) for modeling habitat capacities and mitigation. In response, the U.S. Geological Survey in cooperation with the Bureau of Ocean Energy Management produced a detailed change classification of emergent marsh vegetation types in coastal Louisiana from 2007 and 2013. This study incorporates two existing vegetation surveys and independent variables such as Landsat Thematic Mapper multispectral satellite imagery, high-resolution airborne imagery from 2007 and 2013, bare-earth digital elevation models based on airborne light detection and ranging, alternative contemporary land-cover classifications, and other spatially explicit variables. An image classification based on image objects was created from 2007 and 2013 National Agriculture Imagery Program color-infrared aerial photography. The final products consisted of two 10-meter raster datasets. Each image object from the 2007 and 2013 spatial datasets was assigned a vegetation classification by using a simple majority filter. In addition to those spatial datasets, we also conducted a change analysis between the datasets to produce a 10-meter change raster product. This analysis identified how much change has taken place and where change has occurred. The spatial data products show dynamic areas where marsh loss is occurring or where marsh type is changing. This information can be used to assist and advance conservation efforts for priority natural resources.

Louisiana↗

USGS1997

Collection and analysis of traditional ecological knowledge about a population of arctic tundra caribou

Aboriginal peoples want their ecological knowledge used in the management of wildlife populations. To accomplish this, management agencies will need regional summaries of aboriginal knowledge about long-term changes in the distribution and abundance of wildlife populations and ecological factors that influence those changes. Between 1983 and 1994, we developed a method for collecting Inuit knowledge about historical changes in a caribou ( Rangifer tarandus ) population on southern Baffin Island from c. 1900 to 1994. Advice from Inuit allowed us to collect and interpret their oral knowledge in culturally appropriate ways. Local Hunters and Trappers Associations (HTAs) and other Inuit identified potential informants to maximize the spatial and temporal scope of the study. In the final interview protocol, each informant (i) established his biographical map and time line, (ii) described changes in caribou distribution and density during his life, and (iii) discussed ecological factors that may have caused changes in caribou populations. Personal and parental observations of caribou distribution and abundance were reliable and precise. Inuit who had hunted caribou during periods of scarcity provided more extensive information than those hunters who had hunted mainly ringed seals ( Phoca hispida ); nevertheless, seal hunters provided information about coastal areas where caribou densities were insufficient for the needs of caribou hunters. The wording of our questions influenced the reliability of informants' answers; leading questions were especially problematic. We used only information that we considered reliable after analyzing the wording of both questions and answers from translated transcripts. This analysis may have excluded some reliable information because informants tended to understate certainty in their recollections. We tried to retain the accuracy and precision inherent in Inuit oral traditions; comparisons of information from several informants and comparisons with published and archival historical reports indicate that we retained these qualities of Inuit knowledge.

Nunavut↗

USGS2020

Final project memorandum: Identifying conservation objectives for the Gulf Coast habitats of the black skimmer and gull-billed tern

Many shorebirds and nearshore waterbirds are of conservation concern across the Gulf of Mexico due to stressors such as human disturbance, predation, and habitat loss and degradation. Conservation and protection of these birds is important for the functioning of healthy ecosystems and for maintaining biodiversity in North America. Consequently, resource managers along the Gulf need decision-aiding tools that can help to answer important conservation questions for different species (e.g., how much area should be targeted by management actions to meet a species’ needs). To address this need, project researchers developed statistical models that could help identify habitat conservation objectives and actions for bird species taking into account different Gulf coast conservation scenarios that might occur in response to sea-level rise. The project focused specifically on the Black Skimmer ( Rynchops niger ) and Gull-billed Tern ( Gelochelidon nilotica ), two species designated as U.S. Fish and Wildlife Service Species of Conservation Concern and Gulf Coast Joint Venture Priority Species. These two birds are also representative of a variety of other beach and barrier-island nesting birds whose nesting habitats are threatened by sea-level rise (e.g., Least Tern, Snowy and Wilson’s Plover). The statistical models linked each bird’s abundance to habitat characteristics that could be influenced by different management actions. This information could be used to identify conservation objectives under different conservation scenarios.

Gulf of Mexico↗

USGS2025

Benthic habitat map of Olowalu Reef, Maui, Hawaii—Geomorphological structure, biological cover, and geologic zonation determined with spectral, lidar, and acoustic data

The fringing coral reef off Olowalu, Maui, Hawaii, has been identified as a local conservation priority site. In 2007, the National Oceanic and Atmospheric Administration (NOAA) produced a benthic habitat map of the Hawaiian Islands that was used as a foundation for this study. To support place-based management of the reef in the future, the U.S. Geological Survey (USGS) mapped the geologic zone, major and dominant geomorphological structure, biological cover type, and percent of biological cover for 11 square kilometers (km 2 ) of Olowalu Reef at a minimum mapping unit (MMU) of 100 square meters (m 2 ) to create a benthic habitat map. Heads-up digitization was employed on 0.50-meter (m) natural color satellite orthoimagery with ancillary 1-m acoustic backscatter imagery from single-scan sonar (sound navigation and ranging). A 1-m, 4-m, and 8-m digital bathymetric model (DBM) was interpolated from bathymetric lidar (light detection and ranging), and various geomorphometric layers derived from the DBMs were used for habitat interpretation. Still-frame imagery of the seafloor extracted from vessel-towed underwater video transects on Olowalu Reef served as ground validation points ( n =870) during active mapping and accuracy assessment points ( n =216) for thematic accuracy assessment. Thematic accuracy was cross-validated by the Hawai‘i Department of Land and Natural Resources Division of Aquatic Resources. Final thematic accuracy was 88.8 percent for major structure, 85.6 percent for dominant structure, 86.0 percent for major biological cover, and 78.6 percent for type and percent of major biological cover. Reef and hardbottom constituted 52 percent of the total mapped habitat, comprising mostly aggregate reef (31 percent) and pavement (11 percent), with large swaths of spur-and-groove (9 percent). Of this hardbottom, 17 percent was covered with moderate (10 to <50 percent) coral and 27 percent with high coral cover (50 to <90 percent). High (50 to <90 percent) macroalgae cover dominated the continuous sand sheets in offshore bank/shelf zones. The map created in this study supplements the NOAA 2007 map and expands on the observations made by USGS sampling of the reef. The NOAA 2007 map and our map differed in total areal extent by a negligible 6 m 2 and were in general thematic agreement. Our map is intended to serve as a baseline for public access, general research, local-level management, and reef change for future studies.

Hawaii↗

USGS2013

Landsat surface reflectance quality assurance extraction (version 1.7)

The U.S. Geological Survey (USGS) Land Remote Sensing Program is developing an operational capability to produce Climate Data Records (CDRs) and Essential Climate Variables (ECVs) from the Landsat Archive to support a wide variety of science and resource management activities from regional to global scale. The USGS Earth Resources Observation and Science (EROS) Center is charged with prototyping systems and software to generate these high-level data products. Various USGS Geographic Science Centers are charged with particular ECV algorithm development and (or) selection as well as the evaluation and application demonstration of various USGS CDRs and ECVs. Because it is a foundation for many other ECVs, the first CDR in development is the Landsat Surface Reflectance Product (LSRP). The LSRP incorporates data quality information in a bit-packed structure that is not readily accessible without postprocessing services performed by the user. This document describes two general methods of LSRP quality-data extraction for use in image processing systems. Helpful hints for the installation and use of software originally developed for manipulation of Hierarchical Data Format (HDF) produced through the National Aeronautics and Space Administration (NASA) Earth Observing System are first provided for users who wish to extract quality data into separate HDF files. Next, steps follow to incorporate these extracted data into an image processing system. Finally, an alternative example is illustrated in which the data are extracted within a particular image processing system.

Techniques and Methods↗

USGS2011

Simulating potential structural and operational changes for Detroit Dam on the North Santiam River, Oregon-Interim Results

Prior to operational changes in 2007, Detroit Dam on the North Santiam River in western Oregon had a well-documented effect on downstream water temperature that was problematic for endangered salmonid fish species. In this U.S. Geological Survey study, done in cooperation with the U.S. Army Corps of Engineers, an existing calibrated CE-QUAL-W2 model of Detroit Lake (the impounded waterbody behind Detroit Dam) was used to determine how changes in dam operation or changes to the structural release points of Detroit Dam might affect downstream water temperatures under a range of historical hydrologic and meteorological conditions. Many combinations of environmental, operational, and structural options were explored with the model. Two downstream temperature targets were used along with three sets of environmental forcing conditions representing normal, hot/dry, and cool/wet conditions. Three structural options were modeled, including the use of existing outlets, one hypothetical variable-elevation outlet such as a sliding gate, and a hypothetical combination of a floating outlet and a fixed-elevation outlet. Finally, four sets of operational guidelines were explored to gain an understanding of the effects of imposing different downstream minimum streamflows or managing the level of the lake with different timelines in autumn. Several conclusions can be made from these interim model scenarios: * Temperature targets just downstream of Detroit Dam can be met through a combination of new dam outlets or a delayed drawdown of the lake in autumn. * Spring and summer dam operations greatly affect the available release temperatures and operational flexibility later in the autumn. Releasing warm water during mid-summer tends to keep more cool water available for release in autumn. * The ability to meet downstream temperature targets during spring depends on the characteristics of the available outlets. Under existing conditions, for example, although warm water sometimes is present at the lake surface, such water may not be available for release if the lake level is either well below or well above the spillway crest in spring and early summer. * Managing lake releases to meet downstream temperature targets depends on having outlet structures that can access both (warm) lake surface water and (cold) deeper lake water throughout the year. The existing outlets at Detroit Dam do not allow near-surface waters to be released during times when the lake surface level is below the spillway (spring and autumn). * Model simulations indicate that delayed drawdown of Detroit Lake in autumn would result in better control over release temperatures. * Compared to the existing outlets at Detroit Dam, floating or sliding-gate outlet structures can provide greater control over release temperatures because they provide better access to warm water at the lake surface and cooler water at depth. This report provides interim study results to the U.S. Army Corps of Engineers. The full study will be completed in 2012.

Open-File Report↗

USGS2016

Documentation and hydrologic analysis of Hurricane Sandy in New Jersey, October 29–30, 2012

In 2012, a late season tropical depression developed into a tropical storm and later a hurricane. The hurricane, named “Hurricane Sandy,” gained strength to a Category 3 storm on October 25, 2012, and underwent several transitions on its approach to the mid-Atlantic region of the eastern coast of the United States. By October 28, 2012, Hurricane Sandy had strengthened into the largest hurricane ever recorded in the North Atlantic and was tracking parallel to the east coast of United States, heading toward New Jersey. On October 29, 2012, the storm turned west-northwest and made landfall near Atlantic City, N.J. The high winds and wind-driven storm surge caused massive damage along the entire coastline of New Jersey. Millions of people were left without power or communication networks. Many homes were completely destroyed. Sand dunes were eroded, and the barrier island at Mantoloking was breached, connecting the ocean with Barnegat Bay. Several days before the storm made landfall in New Jersey, the U.S. Geological Survey (USGS) made a decision to deploy a temporary network of storm-tide sensors and barometric pressure sensors from Virginia to Maine to supplement the existing USGS and National Oceanic and Atmospheric Administration (NOAA) networks of permanent tide monitoring stations. After the storm made landfall, the USGS conducted a sensor data recovery and high-water-mark collection campaign in cooperation with the Federal Emergency Management Agency (FEMA). Peak storm-tide elevations documented at USGS tide gages, tidal crest-stage gages, temporary storm sensor locations, and high-water-mark sites indicate the area from southern Monmouth County, N.J., north through Raritan Bay, N.J., had the highest peak storm-tide elevations during this storm. The USGS tide gages at Raritan River at South Amboy and Raritan Bay at Keansburg, part of the New Jersey Tide Telemetry System, each recorded peak storm-tide elevations of greater than 13 feet (ft)—more than 5 ft higher than the previously recorded period-of-record maximum. A comparison of peak storm-tide elevations to preliminary FEMA Coastal Flood Insurance Study flood elevations indicated that these areas experienced the highest recurrence intervals along the coast of New Jersey. Analysis showed peak storm-tide elevations exceeded the 100-year FEMA flood elevations in many parts of Middlesex, Union, Essex, Hudson, and Bergen Counties, and peak storm-tide elevations at many locations in Monmouth County exceeded the 500-year recurrence interval. A level 1 HAZUS (HAZards United States) analysis was done for the counties in New Jersey affected by flooding to estimate total building stock losses. The aggregated total building stock losses estimated by HAZUS for New Jersey, on the basis of the final inundation verified by USGS high-water marks, was almost $19 billion. A comparison of Hurricane Sandy with historic coastal storms showed that peak storm-tide elevations associated with Hurricane Sandy exceeded most of the previously documented elevations associated with the storms of December 1992, March 1962, September 1960, and September 1944 at many coastal communities in New Jersey. This scientific investigation report was prepared in cooperation with FEMA to document flood processes and flood damages resulting from this storm and to assist in future flood mitigation actions in New Jersey.

New Jersey↗

USGS1997

Landsat Data

In the mid-1960's, the National Aeronautics and Space Administration (NASA) embarked on an initiative to develop and launch the first Earth monitoring satellite to meet the needs of resource managers and earth scientists. The U.S. Geological Survey (USGS) entered into a partnership with NASA in the early 1970?s to assume responsibility for archiving data and distributing data products. On July 23, 1972, NASA launched the first in a series of satellites designed to provide repetitive global coverage of the Earth?s land masses. Designated initially as the "Earth Resources Technology Satellite-A" ("ERTS-A"), it used a Nimbus-type platform that was modified to carry sensor systems and data relay equipment. When operational orbit was achieved, it was designated "ERTS-1." The satellite continued to function beyond its designed life expectancy of 1 year and finally ceased to operate on January 6, 1978, more than 5 years after its launch date. The second in this series of Earth resources satellites (designated ?ERTS-B?) was launched January 22, 1975. It was renamed "Landsat 2" by NASA, which also renamed "ERTS-1" as "Landsat 1." Three additional Landsats were launched in 1978, 1982, and 1984 (Landsats 3, 4, and 5 ). (See table 1). NASA was responsible for operating the program through the early 1980?s. In January 1983, operation of the Landsat system was transferred to the National Oceanic and Atmospheric Administration (NOAA). In October 1985, the Landsat system was commercialized and the Earth Observation Satellite Company, now Space Imaging EOSAT, assumed responsibility for its operation under contract to NOAA. Throughout these changes, the USGS EROS Data Center (EDC) retained primary responsibility as the Government archive of Landsat data. The Land Remote Sensing Policy Act of 1992 (Public Law 102-5555) officially authorized the National Satellite Land Remote Sensing Data Archive and assigned responsibility to the Department of the Interior. In addition to its Landsat data management responsibility, the EDC investigates new methods of characterizing and studying changes on the land surface with Landsat data.

Fact Sheet↗

USGS2001

Estimating monthly and annual streamflow statistics at ungaged sites in Idaho

Updated monthly and annual streamflow information for the many ungaged streams throughout Idaho is needed to assist planners and managers with issues regarding fish and wildlife, water rights, and other land and water uses. To provide this information, the U.S. Geological Survey used a multiple-regression analysis to develop equations for estimating daily mean discharge exceeded 80, 50, and 20 percent of the time each month (80-, 50-, and 20-percent monthly exceedances) and mean annual discharge values at ungaged sites. The analysis produced estimating equations that relate specific streamflow statistics to basin characteristics. The standard errors of estimate, in log 10 , of the final estimating equations ranged from a minimum of 0.072 (+18.1 to -15.3 percent) to a maximum of 0.498 (+214.8 to -68.2 percent). The estimating equations might not yield reliable results for sites with basin characteristic values outside of the range of values used to develop the equations. The equations also are not applicable for regulated streams or those that exhibit significant gains and (or) losses as a result of spring flow, seepage through permeable streambeds, or irrigation diversions. The equations generally were more reliable for estimating the high monthly streamflow statistics (20-percent exceedances) than for estimating the low streamflow statistics (80-percent exceedances) in each region and all streamflow statistics in regions where annual streamflow is relatively low.

Idaho;Montana;Nevada;Oregon;Utah;Washington;Wyomin↗

USGS2023

Improving the Midwest Climate Change Vulnerability Assessment Tool to support regional climate adaptation

An online climate vulnerability assessment dashboard was developed in 2021 through collaboration between U.S. Geological Survey (USGS) and U.S. Fish and Wildlife Service (FWS) to support regional climate adaptation efforts. The dashboard included 15 climate change impact metrics (five each from three categories: hydrology, precipitation, and temperature) and five metrics representing each watershed's capacity to adapt to changing conditions. Users could then adjust relative weights of each metric to generate vulnerability scores. The metrics included in the dashboard were identified by FWS for their programs but have broad relevance, making the dashboard useful to a wide range of stakeholders. For this project we had two primary goals: (1) update the online dashboard to better communicate the variability that is inherent in climate change projections, and (2) develop a use case example using the dashboard to collaboratively assess vulnerability of a resource of concern at a workshop with resource managers. For objective 2, we selected prairie-obligate butterflies (POBs), which are dependent on, and often restricted to, native prairie habitat. The extent of native prairie has been greatly reduced over the last two centuries resulting in a patchwork of isolated and often small tracts of land. For many POBs, declines and extirpations have been observed in recent decades. Although the causes are not always known, hypotheses include overuse of management tools (e.g., too frequent burning or overgrazing), lack of dispersal opportunities, or extreme weather events. With more extreme weather events anticipated in the future along with other changes in climate, it is important to better understand the vulnerability of POBs to design effective adaptation strategies. While research on extreme weather, climate change, and adaptation is ongoing for some prairie-obligate species, this workshop sought to take a broad perspective using POBs as the focal taxonomic group across eight U.S. States in the Midwest During the workshop we discussed weather and climate-related influences on butterfly communities and assessed climate change vulnerability using the Watershed-based Midwest Climate Change Vulnerability Assessment Tool (https://www.usgs.gov/apps/CC_Vulnerability/). We produced maps that quantify the regional vulnerability of POBs across 360 watersheds for two future emissions scenarios. The information developed during the workshop could help in regional planning for climate change adaptation and to identify avenues for research and collaboration for POBs in the Midwest.

Illinois, Indiana, Iowa, Michigan, Minnesota, Miss↗

USGS1999

Thickness of unconsolidated deposits in the towns of Solon and Taylor, Cortland County, New York

Introduction Siting of waste-disposal facilities in Cortland County poses a potential threat to local ground-water resources. An especially sensitive waste-disposal siting issue arose in 1988, when the New York State Low-Level Radioactive Waste Siting Commission (NYSLLWSC) identified 15 sites in six towns (Towns of Solon, Taylor, Freetown, Cincinnatus, Marathon, and Willet) in the eastern part of the county for possible disposal of low-level radioactive waste (New York State Low-Level Radioactive Waste Siting Commission, 1988). Eventually, two sites in the Town of Taylor became finalist sites; one was selected from the list of 15 potential sites, and the other was offered by a private landowner. Little information was available on geohydrologic conditions in eastern Cortland County, such as the extent of aquifers and the thickness of unconsolidated deposits of low permeability (such as clay and till), even though these two criteria were among those used by NYSLLWSC for selection of potential disposal sites. The source of information on thickness of drift over bedrock was the surficial geologic map of New York (Muller and Cadwell, 1986). The siting effort was terminated before a final selection was made, but the issue had made county managers aware that detailed information on the extent and thickness of unconsolidated deposits (particularly till, which typically has low permeability and can limit the migration of contaminants) is needed before sound decisions on waste-disposal siting can be made. Glaciers deposited till nearly everywhere over bedrock in the uplands of central New York, but the thickness of the till varies greatly from place to place. An analysis by Coates (1966) of 400 drillers' logs of wells in a 2,000-mi 2 area in the uplands of south-central New York (south of the Cortland County) indicated that (1) till is thin or absent on hilltops and is thickest on the lower parts of hills, (2) overall till thickness averages 60 ft, and (3) till thickness on the south, east, west, and north slopes averages 92, 52, 62, and 22 ft, respectively. Hills that have thick till on their south slopes have been referred to as till-shadowed hills by Coates (1974), who attributes this characteristic to glaciers that deposited thick amounts of till on the downflow side of a hill (analogous to flowing streams or wind that deposit sediment on the lee side of an object). Because the till on the south slopes is relatively thick and typically has low permeability, these slopes have been considered as potential areas for waste-disposal sites. In 1997, the U.S. Geological Survey (USGS), in cooperation with the Cortland County Department of Planning, began a 1-year study to map the thickness of unconsolidated deposits and the extent of valley-fill aquifers in the Towns of Solon and Taylor (an area of 60 mi 2 ) in eastern Cortland County. This report (1) depicts the thickness of unconsolidated deposits and the extent of valley-fill aquifers in the Towns of Solon and taylor in eastern Cortland County, (2) examines whether the "till-shadowed hill" concept developed by Coates (1966) is applicable in this area, and (3) provides three schematic geologic sections showing the thickness of unconsolidated deposits in the uplands in the northwestern part of the study area.

New York↗

USGS2010

Development of inferential sensors for real-time quality control of water-level data for the Everglades Depth Estimation Network

The Everglades Depth Estimation Network (EDEN) is an integrated network of real-time water-level gaging stations, ground-elevation models, and watersurface models designed to provide scientists, engineers, and water-resource managers with current (2000-present) water-depth information for the entire freshwater portion of the greater Everglades. The generation of EDEN waterlevel surfaces is derived from real-time data. Real-time data are automatically checked for outliers using minimum, maximum, and rate-of-change thresholds for each station. Smaller errors in the real-time data, such as gradual drift of malfunctioning pressure transducers, are more difficult to immediately identify with visual inspection of time-series plots and may only be identified during on-site inspections of the gages. Correcting smaller errors in the data often is time consuming and water-level data may not be finalized for several months. To provide water-level surfaces on a daily basis, EDEN needed an automated process to identify errors in water-level data and to provide estimates for missing or erroneous waterlevel data. A technology often used for industrial applications is “inferential sensor.” Rather than installing a redundant sensor to measure a process, such as an additional waterlevel gage, an inferential sensor, or virtual sensor, is developed that estimates the processes measured by the physical sensor. The advantage of an inferential sensor is that it provides a redundant signal to the sensor in the field but without exposure to environmental threats. In the event that a gage does malfunction, the inferential sensor provides an estimate for the period of missing data. The inferential sensor also can be used in the quality assurance and quality control of the data. Inferential sensors for gages in the EDEN network are currently (2010) under development. The inferential sensors will be automated so that the real-time EDEN data will continuously be compared to the inferential sensor signal and digital reports of the status of the real-time data will be sent periodically to the appropriate support personnel. The development and application of inferential sensors is easily transferable to other real-time hydrologic monitoring networks.

Florida↗

USGS2014

Status and trends of Caribbean coral reefs: 1970-2012

This it the 9th status report since the Global Coral Reef Monitoring Network (GCRMN) was founded in 1995 was the data arm of the International Coral Reef Initiative (ICRI) to document the ecological condition or corral reefs, strengthen monitoring efforts, and link existing organizations and people working on reefs worldwide. The US Government provided the initial funding to help set up a global network of coral reef workers and has continued to provide core support. Since then, the series of reports have aimed to present the current status of coral reefs of the world or particular regions, the major threats to reefs and their consequences, and any initiative undertaken under the auspices of ICRI or other bodies to arrest or reverse the decline of coral reefs. IUCN assumed responsibility for hosting the global coordination of the GCRMN in 2010 under the scientific direction of Jeremy Jackson with the following objectives: 1. Document quantitatively the global status and trends for corals, macroalgae, sea urchins, and fishes based on available data from individual scientists as well as the peer reviewed scientific literature, monitoring programs, and report. 2. Bring together regional experts in a series of workshops to involve them in data compilation, analysis, and synthesis. 3. Integrate coral reef status and trends with independent environmental, management, and socioeconomic data to better understand the primary factors responsible for coral reef decline, the possible synergies among factors that may further magnify their impacts, and how these stresses may be more effectively alleviated. Work with GCRMN partners to establish simple and practical standardized protocols for future monitoring and assessment. Disseminate information and results to help guide member state policy and actions. The overarching objective is to understand why some reefs are much healthier than others, to identify what kinds of actions have been particularly beneficial or harmful, and to vigorously communicate results in simple and straightforward terms to foster more effective conservation and management. This and subsequent reports will focus on separate biogeographic regions in a stepwise fashion and combine all of the results for a global synthesis in the coming years. We began in the wide Caribbean region because the historical data are so extensive and to refine methods of analysis before moving on to other regions. This report documents quantitative trends for Caribbean reef corals, macroalgae, sea urchins, and fishes based on data from 90 reef locations over the past 43 tears. This is the first report to combine all these disparate kinds of data in a single place to explore how the different major components of coral reef ecosystems interact on a broadly regional oceanic scale. We obtained data from more than 35,000 ecological surveys carried out by 78 principal investigators (PIs) and some 200 colleagues working in 34 countries, states, and territories throughout the wide Caribbean region. We conducted two workshops in Panama and Brisbane, Australia to bring together people who provided the data to assist in data quality control, analysis, and synthesis. The first workshop at the Smithsonian Tropical Research Institute (STRI) in the Republic of Panama 29 April to 5 May, 2012 included scientists from 18 countries and territories to verify and expand the database and to conduct exploratory analyses of status and trends. Preliminary results based on the Panama workshop were presented to the DC Marine Community and Smithsonian Institution Senate of Scientists in May 2012 and at the International Coral Reef Symposium (ICRS) and annual ICRI meeting in Cairns, Australia in July 2012. The second workshop in Brisbane, Australia in December 2012 brought together eight coral reef scientists for more detailed data analysis and organization of results for this report and subsequent publications. Subsequent presentations to solicit comments while the report was being finalized were made in 2013-2014 at the ICRI General meeting in Belize, the biennial meeting of the Association of Island Marine Laboratories in Jamaica, the Panamerican Coral Reef Congress in Merida, Mexico, the annual meeting of he Western Society of Naturalists, and numerous universities in Costa Rica, the USA and Europe. The main body of the report is in two sections. Part I provides an overview of overall status and trends and detailed analyses of the multiple factors responsible for the decline of reef corals throughout the entire wider Caribbean region. The editors are grateful to all the people who have so generously provided data and expertise, but we assume responsibility for the many statements, conclusions and recommendations and final wording of the text. Part II provides a more detailed analysis of the status and trends of coral reef ecosystems in the 32 countries, states, and territories for which we have data. The format includes maps indicating all locations sampled, a detailed table of data sources and sites surveyed, timelines of ecologically important evens, and relevant references. Each of these reports was compiled in consultation with local experts and all those who provided data and advice are listed as authors of each country report.

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USGS2016

Estimating flood magnitude and frequency at gaged and ungaged sites on streams in Alaska and conterminous basins in Canada, based on data through water year 2012

Estimates of the magnitude and frequency of floods are needed across Alaska for engineering design of transportation and water-conveyance structures, flood-insurance studies, flood-plain management, and other water-resource purposes. This report updates methods for estimating flood magnitude and frequency in Alaska and conterminous basins in Canada. Annual peak-flow data through water year 2012 were compiled from 387 streamgages on unregulated streams with at least 10 years of record. Flood-frequency estimates were computed for each streamgage using the Expected Moments Algorithm to fit a Pearson Type III distribution to the logarithms of annual peak flows. A multiple Grubbs-Beck test was used to identify potentially influential low floods in the time series of peak flows for censoring in the flood frequency analysis. For two new regional skew areas, flood-frequency estimates using station skew were computed for stations with at least 25 years of record for use in a Bayesian least-squares regression analysis to determine a regional skew value. The consideration of basin characteristics as explanatory variables for regional skew resulted in improvements in precision too small to warrant the additional model complexity, and a constant model was adopted. Regional Skew Area 1 in eastern-central Alaska had a regional skew of 0.54 and an average variance of prediction of 0.45, corresponding to an effective record length of 22 years. Regional Skew Area 2, encompassing coastal areas bordering the Gulf of Alaska, had a regional skew of 0.18 and an average variance of prediction of 0.12, corresponding to an effective record length of 59 years. Station flood-frequency estimates for study sites in regional skew areas were then recomputed using a weighted skew incorporating the station skew and regional skew. In a new regional skew exclusion area outside the regional skew areas, the density of long-record streamgages was too sparse for regional analysis and station skew was used for all estimates. Final station flood frequency estimates for all study streamgages are presented for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities. Regional multiple-regression analysis was used to produce equations for estimating flood frequency statistics from explanatory basin characteristics. Basin characteristics, including physical and climatic variables, were updated for all study streamgages using a geographical information system and geospatial source data. Screening for similar-sized nested basins eliminated hydrologically redundant sites, and screening for eligibility for analysis of explanatory variables eliminated regulated peaks, outburst peaks, and sites with indeterminate basin characteristics. An ordinary least‑squares regression used flood-frequency statistics and basin characteristics for 341 streamgages (284 in Alaska and 57 in Canada) to determine the most suitable combination of basin characteristics for a flood-frequency regression model and to explore regional grouping of streamgages for explaining variability in flood-frequency statistics across the study area. The most suitable model for explaining flood frequency used drainage area and mean annual precipitation as explanatory variables for the entire study area as a region. Final regression equations for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probability discharge in Alaska and conterminous basins in Canada were developed using a generalized least-squares regression. The average standard error of prediction for the regression equations for the various annual exceedance probabilities ranged from 69 to 82 percent, and the pseudo-coefficient of determination (pseudo-R 2 ) ranged from 85 to 91 percent. The regional regression equations from this study were incorporated into the U.S. Geological Survey StreamStats program for a limited area of the State—the Cook Inlet Basin. StreamStats is a national web-based geographic information system application that facilitates retrieval of streamflow statistics and associated information. StreamStats retrieves published data for gaged sites and, for user-selected ungaged sites, delineates drainage areas from topographic and hydrographic data, computes basin characteristics, and computes flood frequency estimates using the regional regression equations.

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