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At least 343 records · Page 19Linked to original sources
USGS2020

Hydrologic modeling for flow-ecology science in the Southeastern United States and Puerto Rico

An understanding of the applicability and utility of hydrologic models is critical to support the effective management of water resources throughout the Southeastern United States (SEUS) and Puerto Rico (PR). Hydrologic models have the capacity to provide an estimate of the quantity of available water at ungauged locations (i.e., areas of the country where a U.S. Geological Survey [USGS] continuous record gauge is not installed) and provide the baseline flow information necessary to develop the linkages between water availability and characteristics of streamflow that support ecological communities (i.e., support the development of flow-ecology response models). This report inventories and then directly examines and compares a subset of hydrologic models used to estimate streamflow at a number of gauged basins across the SEUS and PR. This effort was designed to evaluate, quantify, and compare the magnitude of error and to investigate the potential causes of error associated with predicted streamflows from seven hydrologic models of varying complexity and calibration strategy. This was accomplished by computing and then comparing classical hydrologic model fit statistics (e.g., mean bias, coefficient of determination [R2], root mean squared error [RMSE], Nash-Sutcliffe Efficiency [NSE]) and understanding the bias in the prediction in these and a subset of ecologically relevant flow metrics (ERFMs). Additionally, streamflow predictions from a larger regional-scale hydrologic model were compared to those of several fine-scale hydrologic models under a range of hypothetical climate change scenarios to determine the range of predicted streamflow responses to fixed climate perturbations. A pilot study was conducted using predicted streamflow and boosted regression trees to develop a set of predictive flow-ecology response models to assess the potential change in fish species richness in the North Carolina Piedmont under several scenarios of water availability change. This report is intended to provide a general assessment of all the tools and techniques available to support hydrologic modeling for flow-ecology science in the SEUS and PR. It is our hope that the approach used herein to understand differences in streamflow predictions among a subset of hydrologic models that have been applied in the SEUS for developing flow-ecology response models will provide water resource managers and stakeholders with an informed pathway for developing the capacity to link streamflow and ecological response and an understanding of some of the limitations associated with these type of modeling efforts.

Alabama, Florida, Georgia, Mississippi, North Caro↗
USGS2022

Near-surface geophysics perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

Pointing to the Integrated, Coordinated, Open, Networked Findability, Accessibility, Interoperability, and Reusability (ICON-FAIR) principles, we have determined several opportunities for implementation within the realm of near-surface geophysics (NSG), representing a broad range of data acquisition and processing technologies. Our work explores the multifaceted community-driven nature of NSG and, by applying ICON-FAIR principles, we identify three key strategic objectives: (i) the development of an approach to integrating NSG into other geoscience data collection projects, (ii) the creation of coordinated and open standardized NSG data, and (iii) the networking of post-secondary institutions to foster an equipment sharing consortium. The precedence within the geoscientific community demonstrates that there are significant opportunities for advancing interdisciplinary applications of NSG through the implementation of structural change within the ICON-FAIR framework.

Earth and Space Science↗
USGS2023

Integrating community science and agency-collected monitoring data to expand monitoring capacity at large spatial scales

Monitoring species to better understand their status, ecology, and management needs is a major expense for agencies tasked with biodiversity conservation. Community science data have the potential to improve monitoring for minimal cost, given appropriate analytical frameworks. We describe a framework for integrating data from the eBird community science platform with agency-collected monitoring data using a multistate occupancy model. Our model accounts for the structural differences across datasets and allows for estimation of both occupancy and breeding probabilities. The framework was applied to Common Loons ( Gavia immer ) in Washington State. A total of 766 sites had observation effort, of which 713 sites had only eBird effort, 26 sites had only Washington Department of Fish and Wildlife (WDFW) effort, and 27 sites had both. We predicted that the probability of occupancy was only 0.07 (95% Bayesian credible interval, BCI = 0.02–0.51) at the 2324 sites in our sampling frame, though the probability that Common Loons were breeding at occupied sites was 0.95 (95% BCI = 0.71–1.00). We found that probability of occupancy was positively related to waterbody size (probability of a positive effect = 0.88) and negatively related to an index of human influence (probability of a negative effect = 0.94). We found that probability of breeding at occupied sites was positively related to tree canopy cover (0.86), negatively related to elevation (0.99), and negatively related to barren, scrub/shrub, and herbaceous land cover (0.98). We found that state agency biologists were 16 times more likely to detect breeding Common Loons at a site than were eBird users (0.94, 95% BCI = 0.78–0.99 for agency biologists vs. 0.08, 95% BCI = 0.06–0.10 for eBird users). However, the amount of effort expended by eBird users meant that they confirmed Common Loons at 94 sites while agency biologists confirmed them at just 24 sites, although evidence of reproduction was only contributed by agency biologists. Our results provide a better understanding of the distribution of Common Loons in Washington, while further demonstrating that community science data can be a valuable complement to agency-collected data, if appropriate frameworks are developed to integrate these data sources.

Ecosphere↗
USGS2007

Catch-and-release science and its application to conservation and management of recreational fisheries

Catch-and-release angling is a well-established practice in recreational angler behaviour and fisheries management. Accompanying this is a growing body of catch-and-release research that can be applied to reduce injury, mortality and sublethal alterations in behaviour and physiology. Here, the status of catch-and-release research from a symposium on the topic is summarised. Several general themes emerged including the need to: (1) better connect sublethal assessments to population-level processes; (2) enhance understanding of the variation in fish, fishing practices and gear and their role in catch and release; (3) better understand animal welfare issues related to catch and release; (4) increase the exchange of information on fishing-induced stress, injury and mortality between the recreational and commercial fishing sectors; and (5) improve procedures for measuring and understanding the effect of catch-and-release angling. Through design of better catch-and-release studies, strategies could be developed to further minimise stress, injury and mortality arising from catch-and-release angling. These strategies, when integrated with other fish population and fishery characteristics, can be used by anglers and managers to sustain or enhance recreational fishing resources. ?? 2007 The Authors. Journal compilation 2007 Blackwell Publishing Ltd.

Fisheries Management and Ecology↗
USGS2005

Control of Tamarix in the western United States: Implications for water salvage, wildlife use, and riparian restoration

Non-native shrub species in the genus Tamarix (saltcedar, tamarisk) have colonized hundreds of thousands of hectares of floodplains, reservoir margins, and other wetlands in western North America. Many resource managers seek to reduce saltcedar abundance and control its spread to increase the flow of water in streams that might otherwise be lost to evapotranspiration, to restore native riparian (streamside) vegetation, and to improve wildlife habitat. However, increased water yield might not always occur and has been substantially lower than expected in water salvage experiments, the potential for successful revegetation is variable, and not all wildlife taxa clearly prefer native plant habitats over saltcedar. As a result, there is considerable debate surrounding saltcedar control efforts. We review the literature on saltcedar control, water use, wildlife use, and riparian restoration to provide resource managers, researchers, and policy-makers with a balanced summary of the state of the science. To best ensure that the desired outcomes of removal programs are met, scientists and resource managers should use existing information and methodologies to carefully select and prioritize sites for removal, apply the most appropriate and cost-effective control methods, and then rigorously monitor control efficacy, revegetation success, water yield changes, and wildlife use.

Environmental Management↗
USGS2022

Predicting geothermal favorability in the western United States by using machine learning: Addressing challenges and developing solutions

Previous moderate- and high-temperature geothermal resource assessments of the western United States utilized weight-of-evidence and logistic regression methods to estimate resource favorability, but these analyses relied upon some expert decisions. While expert decisions can add confidence to aspects of the modeling process by ensuring only reasonable models are employed, expert decisions also introduce human bias into assessments. This bias presents a source of error that may affect the performance of the models and resulting resource estimates. Our study aims to reduce expert input through robust data-driven analyses and better-suited data science techniques, with the goals of saving time, reducing bias, and improving predictive ability. We present six favorability maps for geothermal resources in the western United States created using two strategies applied to three modern machine learning algorithms (logistic regression, support-vector machines, and XGBoost). To provide a direct comparison to previous assessments, we use the same input data as the 2008 U.S. Geological Survey (USGS) conventional moderate- to high-temperature geothermal resource assessment. The six new favorability maps required far less expert decision-making, but broadly agree with the previous assessment. Despite the fact that the 2008 assessment results employed linear methods, the non-linear machine learning algorithms (i.e., support-vector machines and XGBoost) produced greater agreement with the previous assessment than the linear machine learning algorithm (i.e., logistic regression). It is not surprising that geothermal systems depend on non-linear combinations of features, and we postulate that the expert decisions during the 2008 assessment accounted for system non-linearities. Substantial challenges to applying machine learning algorithms to predict geothermal resource favorability include severe class imbalance (i.e., there are very few known geothermal systems compared to the large area considered), and while there are known geothermal systems (i.e., positive labels), all other sites have an unknown status (i.e., they are unlabeled), instead of receiving a negative label (i.e., the known/proven absence of a geothermal resource). We address both challenges through a custom undersampling strategy that can be used with any algorithm and then evaluated using F1 scores.

western United States↗
USGS1997

Herbicides and their metabolites in rainfall: Origin, transport, and deposition patterns across the midwestern and northeastern United States, 1990-1991

Herbicides were detected in rainfall throughout the midwestern and northeastern United States during late spring and summer of 1990 and 1991. Herbicide concentrations exhibited distinct geographic and seasonal patterns. The highest concentrations occurred in midwestern cornbelt states following herbicide application to cropland. Volume-weighted concentrations of 0.2−0.4 μg/L for atrazine and alachlor were typical in this area during mid-April through mid-July, and weighted concentrations as large as 0.6−0.9 μg/L occurred at several sites. Concentrations of 1−3 μg/L were measured in a few individual samples. Atrazine was detected most often followed by alachlor, deethylatrazine, metolachlor, cyanazine, and deisopropylatrazine. The high ratio (∼0.5) of deethylatrazine to atrazine in rainfall suggests atmospheric degradation of atrazine. Mass deposition of herbicides was greatest in areas where herbicide use was high and decreased with distance from the cornbelt. Estimated deposition rates for both atrazine and alachlor ranged from more than 240 μg m - 2 yr - 1 for some areas in the midwestern states to less than 10 μg m - 2 yr - 1 for the New England states. The estimated annual deposition of atrazine on the Great Lakes ranged from about 12 to 63 μg m - 2 yr - 1 . The total amounts of atrazine and alachlor deposited annually in rainfall in the study area represent about 0.6% of the atrazine and 0.4% of the alachlor applied annually to crops in the study area.

Environmental Science & Technology↗
USGS2002

Groundwater contamination downstream of a contaminant penetration site. I. Extension-expansion of the contaminant plume

This study concerns the possible use of boundary layer (BL) approach for the analysis and evaluation of contaminant transport in groundwater due to contaminant penetration into the groundwater aquifer through a site of limited size. The contaminant penetration may occur through either the upper (surface) or lower (bedrock) boundary of the aquifer. Two general cases of contaminant penetration mechanisms are considered: (1) the contaminant is transferred through an interface between a contaminating and freshwater fluid phases, and (2) the contaminant arrives at groundwater by leakage and percolation. For the purpose of BL evaluation the contaminant plume is divided into three different sections: (1) the penetration section, (2) the extension-expansion section, and (3) the spearhead section. In each section a different BL method approach yields simple analytical expressions for the description of the contaminant plume migration and contaminant transport. Previous studies of the BL method can be directly applied to the evaluation of contaminant transport at the contaminant penetration section. The present study extends those studies and concerns the contaminant transport in the two other sections, which are located downstream of the penetration section. This study shows that the contaminant concentration profiles in sections 2 and 3 incorporate two BLs: (1) an inner BL adjacent to the aquifer bottom or surface boundary, and (2) an outer BL, which develops above or below the inner one. The method developed in the present study has been applied to practical issues concerning salinity penetration into groundwater in south central Kansas.

Journal of Environmental Science and Health - Part↗
USGS2026

Remote compositional analyses of space-weathered lunar maria

Visible-to-shortwave infrared (VSWIR) reflectance spectroscopy has revolutionized our understanding of planetary surface compositions. However, space-weathering processes on airless bodies complicate quantitative compositional analyses. Here, we present a framework to isolate the signatures of space weathering in VSWIR spectra of lunar maria by leveraging radiative transfer modeling under the assumptions that (i) a space-weathered target can be expressed as a mixture of fresh and fully space-weathered components and (ii) remaining signatures can be modeled by including agglutinates as an end-member component. We first validate this approach against laboratory spectra of space-weathered Apollo mare soils of known mineral compositions using a probabilistic Markov Chain Monte Carlo implementation of the Hapke radiative transfer model. Second, we illustrate how this approach can be applied to orbital Moon Mineralogy Mapper data. The proposed space-weathering correction workflow for lunar maria could be expanded to other lunar lithologies and applied to existing and future data sets.

Planetary Science Journal↗
USGS2006

The 1906 earthquake and a century of progress in understanding earthquakes and their hazards

The 18 April 1906 San Francisco earthquake killed nearly 3000 people and left 225,000 residents homeless. Three days after the earthquake, an eight-person Earthquake Investigation Commission composed of 25 geologists, seismologists, geodesists, biologists and engineers, as well as some 300 others started work under the supervision of Andrew Lawson to collect and document physical phenomena related to the quake . On 31 May 1906, the commission published a preliminary 17-page report titled "The Report of the State Earthquake Investigation Commission". The report included the bulk of the geological and morphological descriptions of the faulting, detailed reports on shaking intensity, as well as an impressive atlas of 40 oversized maps and folios. Nearly 100 years after its publication, the Commission Report remains a model for post-earthquake investigations. Because the diverse data sets were so complete and carefully documented, researchers continue to apply modern analysis techniques to learn from the 1906 earthquake. While the earthquake marked a seminal event in the history of California, it served as impetus for the birth of modern earthquake science in the United States.

GSA Today↗
USGS2020

Cooperative Fish and Wildlife Research Units program—2019 year in review postcard

Acting Chief’s Message Dear friends, I invite you to take a look at U.S. Geological Survey Circular 1463, “Cooperative Fish and Wildlife Research Units Program—2019 Year in Review,” now available at https://doi.org/10.3133/cir1463 . In this report, you will find details about the Cooperative Fish and Wildlife Research Units (CRU) program concerning fish and wildlife science, students, staffing, vacancies, research funding, outreach and training, awards, accolades, and professional services. You will also see examples of unit projects with information on how results have been or are being applied by our cooperators. Throughout the year, keep up with our research projects at https://www1.usgs.gov/coopunits/Headquarters/ . Regards, John D. Thompson

General Information Product↗
USGS2026

Assessment of groundwater quantity and quality contributions to Lake Huron

Lake Huron, one of the five Great Lakes, borders the United States and Canada, with Michigan as the only U.S. State on its shoreline. Like other freshwater lakes, it faces water-quality challenges from nutrients and chemicals applied across its drainage basin. Although past studies focused on surface-water sources, groundwater contributions remain less understood. To address this gap, the U.S. Geological Survey, as part of the Cooperative Science and Monitoring Initiative, classified drainage basins to Lake Huron into eight hydrogeologic zones based on bedrock rock type and glacial sediment transmissivity. Utilizing existing data and empirical field data, we quantified groundwater discharge and identified areas of concern for loading of chloride and nitrate to Lake Huron. Groundwater contributions, including indirect and shoreline discharge, ranged from 5.8 to 11.5 inches annually, totaling 1.9 cubic miles and 0.09 cubic mile, respectively. Hydrogeologic zones with higher glacial sediment transmissivity yielded greater indirect groundwater discharge. Chloride levels above the U.S. Environmental Protection Agency’s 250-mg/L recommendation were mainly in the Saginaw lowlands, whereas nitrate above the 10-mg/L standard was rare—found in only 11 wells. Together, the analysis of where groundwater discharge is occurring in the Lake Huron Basin and the identification of areas with potential groundwater-quality concerns can help prioritize areas that are critical to protecting the long-term health of Lake Huron.

Michigan↗
USGS2017

Five-year external reviews of the eight Department of Interior Climate Science Centers: Southeast Climate Science Center

In 2008, the U.S. Congress authorized the establishment of the National Climate Change and Wildlife Science Center (NCCWSC) within the U.S. Department of Interior (DOI). Housed administratively within the U.S. Geological Survey (USGS), NCCWSC is part of the DOI’s ongoing mission to meet the challenges of climate change and its effects on wildlife and aquatic resources. From 2010 through 2012, NCCWSC established eight regional DOI Climate Science Centers (CSCs). Each of these regional CSCs operated with the mission to “synthesize and integrate climate change impact data and develop tools that the Department’s managers and partners can use when managing the Department’s land, water, fish and wildlife, and cultural heritage resources” (Salazar 2009). The model developed by NCCWSC for the regional CSCs employed a dual approach of a federal USGS-staffed component and a parallel host-university component established competitively through a 5-year cooperative agreement with NCCWSC. At the conclusion of this 5-year agreement, a review of each CSC was undertaken, with the Southeast Climate Science Center (SE CSC) review in February 2016. The SE CSC is hosted by North Carolina State University (NCSU) in Raleigh, North Carolina, and is physically housed within the NCSU Department of Applied Ecology along with the Center for Applied Aquatic Ecology, the North Carolina Cooperative Fish and Wildlife Research Unit (CFWRU), and the North Carolina Agromedicine Institute. The U.S. Department of Agriculture Southeast Regional Climate Hub is based at NCSU as is the National Oceanic and Atmospheric Administration (NOAA) Southeast Regional Climate Center, the North Carolina Institute for Climate Studies, the North Carolina Wildlife Resources Commission, the NOAA National Weather Service, the State Climate Office of North Carolina, and the U.S. Forest Service Eastern Forest Environmental Threat Assessment Center. This creates a strong core of organizations operating in close proximity focused on climate issues. The geographic area covered by the SE CSC represents all or part of 16 states and the Caribbean Islands and has overlapping boundaries with seven Landscape Conservation Cooperatives (LCCs): Appalachian LCC, Eastern Tallgrass Prairie and Big Rivers LCC, Gulf Coast Prairie LCC, Gulf Coastal Plains and Ozarks LCC, Peninsular Florida LCC, South Atlantic LCC, and Caribbean LCC. The SE CSC region also encompasses 134 U.S. Fish and Wildlife Service refuges and 89 National Park Service (NPS) units and is home to 11 federally recognized and 54 state recognized tribes.

Report↗
USGS2018

Clarification of the term “normal material” used for standard atomic weights (IUPAC Technical Report)

The standard atomic weights of the elements apply to normal materials. Since 1984, the Commission on Isotopic Abundances and Atomic Weights (Commission) has defined a normal material as: “The material is a reasonably possible source for this element or its compounds in commerce, for industry or science; the material is not itself studied for some extraordinary anomaly and its isotopic composition has not been modified significantly in a geologically brief period.” The term “a geologically brief period” in this definition is confusing, and confusion can be reduced by revising this definition to the following, which was accepted by the Commission on Isotopic Abundances and Atomic Weights at its meeting in Groningen, Netherlands in September 2017: “ Normal materials include all substances, except (1) those subjected to substantial deliberate, undisclosed, or inadvertent artificial isotopic modification, (2) extraterrestrial materials, and (3) isotopically anomalous specimens, such as natural nuclear reactor products from Oklo (Gabon) or other unique occurrences.”

Pure and Applied Chemistry↗
USGS1988

Knowledge-based geographic information systems (KBGIS): New analytic and data management tools

In its simplest form, a geographic information system (GIS) may be viewed as a data base management system in which most of the data are spatially indexed, and upon which sets of procedures operate to answer queries about spatial entities represented in the data base. Utilization of artificial intelligence (AI) techniques can enhance greatly the capabilities of a GIS, particularly in handling very large, diverse data bases involved in the earth sciences. A KBGIS has been developed by the U.S. Geological Survey which incorporates AI techniques such as learning, expert systems, new data representation, and more. The system, which will be developed further and applied, is a prototype of the next generation of GIS's, an intelligent GIS, as well as an example of a general-purpose intelligent data handling system. The paper provides a description of KBGIS and its application, as well as the AI techniques involved. ?? 1988 International Association for Mathematical Geology.

Mathematical Geology↗
USGS2015

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

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

Georgia↗
USGS2016

U.S. Geological Survey science for the Wyoming Landscape Conservation Initiative—2015 annual report

This is the eighth annual report highlighting U.S. Geological Survey (USGS) science and decision-support activities conducted for the Wyoming Landscape Conservation Initiative (WLCI). The activities address specific management needs identified by WLCI partner agencies. In 2015, USGS scientists continued 24 WLCI projects in 5 categories: (1) acquiring and analyzing resource-condition data to form a foundation for understanding and monitoring landscape conditions and projecting changes; (2) using new technologies to improve the scope and accuracy of landscape-scale monitoring and assessments, and applying them to monitor indicators of ecosystem conditions and the effectiveness of on-the-ground habitat projects; (3) conducting research to elucidate the mechanisms that drive wildlife and habitat responses to changing land uses; (4) managing and making accessible the large number of databases, maps, and other products being developed; and (5) coordinating efforts among WLCI partners, helping them to use USGS-developed decision-support tools, and integrating WLCI outcomes with future habitat enhancement and research projects. Of the 24 projects, 21 were ongoing, including those that entered new phases or more in-depth lines of inquiry, 2 were new, and 1 was completed. A highlight of 2015 was the WLCI science conference sponsored by the USGS, Bureau of Land Management, and National Park Service in coordination with the Wyoming chapter of The Wildlife Society. Of 260 participants, 41 were USGS professionals representing 13 USGS science centers, field offices, and Cooperative Wildlife Research Units. Major themes of USGS presentations included using new technologies for developing more efficient research protocols for modeling and monitoring natural resources, researching effects of energy development and other land uses on wildlife species and habitats of concern, and modeling species distributions, population trends, habitat use, and effects of land-use changes. There was also a special session on the effectiveness of Wyoming’s Sage-Grouse Executive Order. Combined, USGS presentations provided WLCI partners with a wealth of information and conservation tools. The project completed in 2015 yielded an index of important agricultural lands in the WLCI region. The index improves upon existing measures of agricultural productivity and provides planners and managers with additional values to consider when making decisions about land use and conservation actions. The two new projects include an analysis of satellite imagery to quantify sagebrush productivity and mortality, and an evaluation of how groundwater and small streams interact in the upper Green River Basin. Initiated in response to concern among WLCI partners that large areas of sagebrush appear to have died recently, the sagebrush study objectives are to assess effects of these mortality events on overall sagebrush ecosystem productivity, evaluate the feasibility of using satellite imagery to detect patterns in sagebrush mortality over time, and identify factors driving these mortality events. The groundwater-streamflow interaction study is being conducted by hydrologists and fish ecologists to better understand how groundwater-streamflow interactions are affected by energy-resource development and how native fish communities are affected by these factors. Expected outcomes of both new projects will provide WLCI partners with additional information and decision-support tools. Highlights of ongoing science foundation activities included simulations of nine alternative build-out scenarios for oil and gas development and an associated online fact sheet that explains how the simulations were conducted, with an applied example for the Atlantic Rim. Also completed in 2015 was an update of the USGS online inventory of mineral resources data, and publication of a USGS uranium resource survey for the WLCI region. Combined, the outcomes of this work provide decisionmakers and managers with important baseline information for existing and (or) future planning and monitoring efforts. Terrestrial monitoring activities in 2015 emphasized the use of satellite data in combination with other technologies and field data to monitor, assess, and (or) forecast distribution patterns and (or) trends in sagebrush ecosystems, seasonal and migration stopover habitats used by mule deer and elk, and semi-arid aspen woodlands. Several professional papers detailing new monitoring models and results have been published. Combined, this and related work will help managers understand distribution patterns and trends among priority habitats, identify areas in need of restoration or conservation, and monitor the effectiveness of habitat-management actions. Aquatic monitoring activities entailed not only the new groundwater-streamflow interaction study already mentioned, but also continued monitoring with streamgages paired with nearby wells in the Green River Basin to assess groundwater effects on streamflow and surface water temperatures. A map that portrays groundwater levels and general direction of flow in the Green River Basin was published as well . Overall, outcomes of USGS hydrological research and monitoring will inform WLCI partners about water resources in the WLCI region and help to explain fish-community responses to energy-resource development. In 2015, USGS terrestrial wildlife ecologists continued to make crucial strides towards better understanding wildlife species responses to energy-resource development and other land-use changes. This body of research includes six taxa that require or heavily depend on sagebrush habitats: sage-grouse, pygmy rabbits, 3 songbird species, and mule deer. Native fish communities are also being evaluated. Approaches include modeling and mapping wildlife species distributions, abundances, and trends; using satellite and other technologies to track wildlife seasonal movements; conducting successive phases of research that build on the knowledge gained through prior phases to reveal the specific factors or thresholds that drive population- or individual-level responses to changes; and conducting population viability analyses. Additionally, wildlife habitat association models for pygmy rabbit and sage-grouse were combined with the oil and gas build-out scenarios to project species responses to alternative energy development scenarios. Outcomes of the wildlife response research are helping decisionmakers and managers identify specific factors that contribute to species population trends, the potential for spatial overlap between important wildlife habitats and proposed energy-resource development, locations of priority habitats for restoration and conservation, and more. Data and WLCI Web site management highlights of 2015 included not only ongoing software upgrades, but also an update of the datasets displayed in two of the online products developed for the WLCI effort: (1) a map of 15,532 oil and natural gas well pad scars and other features associated with oil and gas extraction, and (2) a map of oil and gas, oil shale, uranium, and solar energy production, both for southwestern Wyoming. In addition, a map viewer was developed for a previously published map of coal and wind production in relation to sage-grouse distribution and core management areas in southwestern Wyoming. Combined, these maps place valuable decision-support tools in the hands of WLCI partners. The USGS coordination efforts on behalf of the WLCI in 2015 included significant work on planning and executing the WLCI science conference. They also included ongoing efforts to support Local Project Development Teams and the WLCI Coordination Team (CT) with developing conservation priorities and strategies, identifying priority areas for future conservation actions, supporting the evaluation and ranking of conservation projects, and evaluating the ways in which proposed habitat projects relate to WLCI priorities. In 2015, the USGS also assisted the WLCI CT with updating the WLCI Conservation Action Plan.

Wyoming↗