Geologic slip rates are a time-averaged measurement of fault displacement calculated over hundreds to million-year time scales and are a primary input for probabilistic seismic hazard analyses, which forecast expected ground shaking in future earthquakes. Despite their utility for seismic hazard calculations, longer-term geologic slip rates represent a time-averaged measure of the tempo of strain release and do not measure variability across earthquake cycles. We have developed a numerical approach called STEPS (Slip Time Earthquake Path Simulations), which is built upon field-based observations and explicitly incorporates realistic variations in displacement per event and variability in the recurrence interval between earthquakes. The STEPS approach, which simulates strain release through time, relies on representing earthquake cycles as stairsteps, rather than straight-line paths, connecting per earthquake time-displacement coordinates. We simulate earthquake histories based on these input constraints using two examples: the Carrizo section of the San Andreas fault and the Toe Jam Hill fault of the Seattle fault zone. We find that modeled slip rate distributions agree with slip rates reported for the sites of interest by the original investigators, while providing a slip rate distribution that reflects the variability of earthquake frequency and displacement. The STEPS approach provides an estimate of fault slip rate uncertainty based on a synthetic suite of plausible time-displacement paths resulting from individual earthquakes, rather than measurement uncertainties associated with offset features. When considering this simulated earthquake behavior between measurements, the uncertainty associated with earthquake paths is greater than that calculated by the long-term rate.
The Cimarron River is a free-flowing river and is a major source of water as it flows across Oklahoma. Increased demand for water resources within the Cimarron River alluvial aquifer in north-central Oklahoma (primarily in Payne County) has led to increases in groundwater withdrawals for agriculture, public, irrigation, industrial, and domestic supply purposes. The Pawnee Nation of Oklahoma (Pawnee Nation) is particularly concerned about the sustainability of the Cimarron River alluvial aquifer and whether the aquifer will continue to be a viable water resource for future generations of Tribal members and residents. To better understand current (2021) water resources and possible future water availability in the Pawnee Nation Tribal jurisdictional area, the U.S. Geological Survey, in cooperation with the Bureau of Indian Affairs and the Pawnee Nation of Oklahoma, compiled available hydrogeologic data and developed conceptual and numerical groundwater-flow models for the Cimarron River alluvial aquifer in Payne County, north-central Oklahoma, including a focus area in the Pawnee Nation Tribal jurisdictional area for the 2016–18 study period.
A conceptual water budget was created to establish estimates of groundwater fluxes into and out of the aquifer through hydrologic boundaries and groundwater withdrawals for use in the numerical groundwater-flow model. The conceptual water budget focuses on the alluvial aquifer, meaning that inflows include sources of water to the aquifer and that outflows include sources of water out of the aquifer, such as base-flow contributions to the Cimarron River. The conceptual water budget was constructed by using data from 2017 (the most complete year of record for each data type included in the model) for the Pawnee Nation subdomain of the Cimarron River alluvial aquifer model extent (Pawnee Nation subdomain).
Groundwater withdrawals were estimated from groundwater-withdrawal rate information for permanent and temporary permitted wells that was obtained from the Oklahoma Water Resources Board. One-half of each annual permitted groundwater-withdrawal rate allotted was used as the estimated annual groundwater-withdrawal amount. Halving the permitted groundwater-withdrawal rate was done because permitted withdrawal rates are the maximum permitted rate and actual groundwater withdrawals are generally appreciably lower than the maximum permitted rate. Total groundwater withdrawals were estimated as 1,300 acre-feet per year for the Pawnee Nation subdomain. Various hydrogeologic data were measured to assist with model development, including depth to bedrock and water-table altitude data. In support of the model development, analyses pertaining to groundwater flow, groundwater/surface-water interactions, base flows in the Cimarron River, and lithological interpretations in the Pawnee Nation Tribal jurisdictional area were used to compute a conceptual water budget applicable to the 2016–18 study period. A numerical groundwater-flow model was developed using the hydrogeologic framework of the Cimarron River alluvial aquifer and the conceptual water budget. The numerical model consists of a single layer representing alluvium and terrace deposits within the alluvial aquifer model area. Hydraulic conductivities were estimated and modeled for the alluvium and terrace deposits in the alluvial aquifer. Base-flow values were estimated using the base-flow index from streamflow data collected at U.S. Geological Survey streamgages. Stream seepage values were derived from the mean 2017 base-flow index between certain streamgages. Hydraulic conductivities were specified an initial (before calibration) value of 120 feet per day for the alluvium deposits and 16 feet per day for the terrace deposits.
The simulated inflows in the numerical groundwater-flow model of the Pawnee Nation subdomain were higher than the inflows of conceptual water budget, and the simulated outflows were lower than the outflows of the conceptual water budget. Overall, simulated base flows matched closely to observed base flows for the 2016 and 2017 stress periods. Simulated streamflow tended to match better with the observed streamflow for 2017, which was the period with the most data for the Cimarron River alluvial aquifer model.
Streamflow capture analysis was applied to the steady-state simulation to identify areas of the aquifer where base flows in the Cimarron River were most sensitive to groundwater withdrawals. The initial base-flow value was assigned the value obtained from streamflow-routing software used to simulate stream outflow for the calibrated steady-state base model. Subsequent simulations were run in each active cell in the Pawnee Nation subdomain for a specified groundwater-withdrawal rate of 180,000 cubic feet per day. The study area that includes the Pawnee Nation subdomain is in the upper Arkansas River Basin. A groundwater-withdrawal rate of 180,000 cubic feet per second per day represents a 34 percent increase compared to the highest permitted groundwater-withdrawal rate for the study area, which corresponds to the estimated 34 percent increase in groundwater withdrawals predicted by 2060 for the upper Arkansas River Basin. Simulated streamflow capture was highest in the alluvium deposits adjacent to the Cimarron River; that is, base flow in the Cimarron River decreased the most for simulated groundwater withdrawals in the alluvium deposits adjacent to the Cimarron River. Streamflow capture increased as the distance of a well from the Cimarron River decreased in the simulation. The northeastern part of the Pawnee Nation subdomain showed greater streamflow capture in a broader area; streamflow in that part of the Pawnee Nation subdomain is likely more sensitive to groundwater withdrawals compared to other parts of the Pawnee Nation subdomain.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215073","collaboration":"Prepared in cooperation with the Bureau of Indian Affairs and the Pawnee Nation of Oklahoma","usgsCitation":"Paizis, N.C., and Trevisan, A.R., 2021, Cimarron River alluvial aquifer hydrogeologic framework, water budget, and implications for future water availability in the Pawnee Nation Tribal jurisdictional area, Payne County, Oklahoma, 2016–18: U.S. Geological Survey Scientific Investigations Report 2021–5073, 49 p., https://doi.org/10.3133/sir20215073.","productDescription":"Report: x, 49 p.; Data Release; Dataset","numberOfPages":"64","onlineOnly":"Y","ipdsId":"IP-119627","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":390181,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5073/coverthb.jpg"},{"id":390182,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5073/sir20215073.pdf","text":"Report","size":"7.46 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5073"},{"id":390184,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"},{"id":390183,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WZGYQF","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"MODFLOW-NWT model used for the simulation of the Cimarron River alluvial aquifer in the Pawnee Nation Tribal jurisdictional area in Payne County, Oklahoma, 2016–17"}],"country":"United States","state":"Oklahoma","county":"Payne County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-96.9277,36.246],[-96.8216,36.245],[-96.8212,36.1593],[-96.6245,36.1605],[-96.6228,35.9427],[-97.1428,35.9442],[-97.1423,35.9641],[-97.1557,35.9485],[-97.1729,35.9428],[-97.1872,35.9426],[-97.2013,35.9469],[-97.2163,35.9576],[-97.2252,35.9677],[-97.236,35.9683],[-97.2461,35.9721],[-97.2523,35.9744],[-97.2734,35.9734],[-97.2841,35.9767],[-97.2863,35.9795],[-97.2862,35.9835],[-97.2883,35.9931],[-97.2927,36.0004],[-97.2982,36.0091],[-97.3055,36.011],[-97.3203,36.0108],[-97.3329,36.0078],[-97.3359,36.0024],[-97.34,35.9947],[-97.3475,35.9885],[-97.3556,35.9841],[-97.3569,36.1583],[-97.1426,36.1588],[-97.1417,36.245],[-96.9277,36.246]]]},\"properties\":{\"name\":\"Payne\",\"state\":\"OK\"}}]}","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754-4501
The 2018 lower East Rift Zone (LERZ) eruption of Kīlauea, Hawai’i, provides an excellent natural laboratory with which to test models of lava flow propagation. During early stages of eruption crises, the most useful lava flow propagation equations utilize readily determined parameters and require fewer a priori assumptions about future behavior of the flow. Here, we leverage the numerous observations of lava flows collected over the duration of the eruption crisis at Kīlauea in 2018 to test simple lava flow propagation models. These models track the one-dimensional propagation of the flows according to three main rheological restraining forces: bulk viscosity, yield strength, and growth of a surface crust. We calculate the predicted changes in length through time of three flows that vary in bulk composition, crystal content, and total flow length. Cooler flows that are more crystal-rich tend to be more dominated by crust growth, though early stages of propagation can be controlled by bulk viscosity. We find that variations in effusion rate significantly impact flows that are short-lived; flows that are produced during steady-state effusion are readily approximated by average values for the entire flow. Thus, accurate knowledge of variations in effusion rate are critical to accurate lava flow propagation forecasting.
Land-use land-cover change (LULCC) has become an important topic of research for the central United States because of the extensive conversion of the natural prairie into agricultural land, especially in the northern Great Plains. As a result, shifts in the natural climate (minimum/maximum temperature, precipitation, etc.) across the north-central United States have been observed, as noted within the Fourth National Climate Assessment (NCA4) report. Thus, it is necessary to understand how further LULCC will affect the near-surface atmosphere, the lower troposphere, and the planetary boundary layer (PBL) atmosphere over this region. The goal of this work was to investigate the utility of a new future land-use land-cover (LULC) dataset within the Weather Research and Forecasting (WRF) modeling system. The present study utilizes a modeled future land-use dataset developed by the Forecasting Scenarios of Land-Use Change (FORE-SCE) model to investigate the influence of future (2050) land use on a simulated PBL development within the WRF Model. Three primary areas of LULCC were identified within the FORE-SCE future LULC dataset across Nebraska and South Dakota. Variations in LULC between the 2005 LULC control simulation and four FORE-SCE simulations affected near-surface temperature (0.5°–1°C) and specific humidity (0.3–0.5 g kg−1). The differences noted in the temperature and moisture fields affected the development of the simulated PBL, leading to variations in PBL height and convective available potential energy. Overall, utilizing the FORE-SCE dataset within WRF produced notable differences relative to the control simulation over areas of LULCC represented in the FORE-SCE dataset.
Climate-influenced changes in hydrology affect water-food-energy security that may impact up to two billion people downstream of the High Mountain Asia (HMA) region. Changes in water supply affect energy, industry, transportation, and ecosystems (agriculture, fisheries) and as a result, also affect the region's social, environmental, and economic fabrics. Sustaining the highly interconnected food-energy-water nexus (FEWN) will be a fundamental and increasing challenge under a changing climate regime. High variability in topography and distribution of glaciated and snow-covered areas in the HMA region, and scarcity of high resolution (in-situ) data make it difficult to model and project climate change impacts on individual watersheds. We lack basic understanding of the spatial and temporal variations in climate, surface impurities in snow and ice such as black carbon and dust that alter surface albedo, and glacier mass balance and dynamics. These knowledge gaps create challenges in predicting where and when the impact of changes in river flow will be the most significant economically and ecologically. In response to these challenges, the United States National Aeronautics and Space Administration (NASA) established the High Mountain Asia Team (HiMAT) in 2016 to conduct research to address knowledge gaps. This paper summarizes some of the advances HiMAT made over the past 5 years, highlights the scientific challenges in improving our understanding of the hydrology of the HMA region, and introduces an integrated assessment framework to assess the impacts of climate changes on the FEWN for the HMA region. The framework, developed under a NASA HMA project, links climate models, hydrology, hydropower, fish biology, and economic analysis. The framework could be applied to develop scientific understanding of spatio-temporal variability in water availability and the resultant downstream impacts on the FEWN to support water resource management under a changing climate regime.
Groundwater depletion is a major threat to agricultural and municipal water supply in California's Central Valley. Recent droughts during 2007–2009 and 2012–2016 exacerbated chronic groundwater depletion. However, it is unclear how much groundwater storage recovered from drought-related overdrafts during post-drought years, and how climatic conditions and water management affected recovery times. We estimated groundwater storage change in the Central Valley for April 2002 through September 2019 using four methods: GRACE satellite data, a water balance approach, a hydrologic simulation model, and monitoring wells. We also evaluated the sensitivity of drought recovery to different climate scenarios (recent climate ± droughts and future climate change scenarios: 20 GCMs and 2 RCPs) using water balance method and statistical sampling of historical climate data. Estimated Central Valley groundwater loss during the two droughts ranged from 19 km3 (2007–2009) to 28 km3 (2012–2016) (median of four methods). Median aquifer storage recovery was 34% and 19% of the overdraft during the 2010–2011 and 2017–2019 post-drought years, respectively. Numerical experiments show that recovery times are sensitive to climate forcing, with longer recovery times for a future climate scenario that replicate historical climatology relative to historical forcing with no droughts. Overdraft recovery times decrease by ∼2× with implementation of pumping restrictions (30th to 50th percentiles of historical groundwater depletion) to constrain groundwater depletion relative to no restrictions with a no-drought future climatology. This study highlights the importance of considering water management implications for future drought recoveries within the context of climate change scenarios.
The spatial distribution and depth of permafrost are changing in response to warming and landscape disturbance across northern Arctic and boreal regions. This alters the infiltration, flow, surface and subsurface distribution, and hydrologic connectivity of inland waters. Such changes in the water cycle consequently alter the source, transport, and biogeochemical cycling of aquatic carbon (C), its role in the production and emission of greenhouse gases, and C delivery to inland waters and the Arctic Ocean. Responses to permafrost thaw across heterogeneous boreal landscapes will be neither spatially uniform nor synchronous, thus giving rise to expressions of low to medium confidence in predicting hydrologic and aquatic C response despite very high confidence in projections of widespread near-surface permafrost disappearance as described in the 2019 Intergovernmental Panel on Climate Change Special Report on the Ocean and Cryosphere in a Changing Climate: Polar Regions. Here, we describe the state of the science regarding mechanisms and factors that influence aquatic C and hydrologic responses to permafrost thaw. Through synthesis of recent topical field and modeling studies and evaluation of influential landscape characteristics, we present a framework for assessing vulnerabilities of northern permafrost landscapes to specific modes of thaw affecting local to regional hydrology and aquatic C biogeochemistry and transport. Lastly, we discuss scaling challenges relevant to model prediction of these impacts in heterogeneous permafrost landscapes.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fclim.2021.730402","usgsCitation":"Walvoord, M.A., and Striegl, R.G., 2021, Complex vulnerabilities of the water and aquatic carbon cycles to permafrost thaw: Frontiers in Climate, v. 3, 730402, 15 p., https://doi.org/10.3389/fclim.2021.730402.","productDescription":"730402, 15 p.","ipdsId":"IP-131645","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":450550,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fclim.2021.730402","text":"Publisher Index Page"},{"id":390316,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Russia, United States","otherGeospatial":"Arctic","volume":"3","noUsgsAuthors":false,"publicationDate":"2021-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Walvoord, Michelle A. 0000-0003-4269-8366","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":211843,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":824775,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":824776,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70224912,"text":"sim3479 - 2021 - Vulnerability assessment in and near Theodore Roosevelt National Park, North Dakota","interactions":[],"lastModifiedDate":"2021-10-05T11:46:21.743463","indexId":"sim3479","displayToPublicDate":"2021-10-04T14:44:17","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3479","displayTitle":"Vulnerability Assessment in and near Theodore Roosevelt National Park, North Dakota","title":"Vulnerability assessment in and near Theodore Roosevelt National Park, North Dakota","docAbstract":"Theodore Roosevelt National Park is in western North Dakota and was established in 1978 under the National Wilderness Preservation system to preserve and protect the qualities of the North Dakota Badlands, including the wildlife, scenery, and wilderness. The park is made up of three units (North, Elkhorn Ranch, and South) that are connected by the Little Missouri River, which was identified by the National Park Service as a significant resource essential to fulfilling the park's purpose. The development of oil and gas (OG) resources has expanded in the past two decades in the region surrounding Theodore Roosevelt National Park. This expansion of OG development outside park boundaries increases the potential for adverse environmental and economic effects inside the park boundaries, especially for the hydrologic processes within Theodore Roosevelt National Park.
This report assesses the vulnerability of critical components that contribute to supporting plants and wildlife of the Northwestern Great Plains ecological region and Theodore Roosevelt National Park’s mission of preservation. Critical components include land cover, slope, soil saturated hydraulic conductivity, distance to Ovis canadensis (Shaw, 1804) (bighorn sheep) critical habitat, distance to springs, distance to rivers and streams, and distance to surficial aquifers. The study area included all the 12-digit hydrologic units within the watershed boundary dataset that intersect Theodore Roosevelt National Park or are within the 12-digit hydrologic units for Little Missouri River tributaries that flow into the park. Critical components that had existing publicly available geographic data were assessed and assigned vulnerability index values. These values were then summed to develop a vulnerability score and mapped. OG development and associated transportation infrastructure, referred to as “stressors” in this report, with publicly available geographic data were mapped, and then flow paths were generated starting from the stressor locations to assess their likelihood to contaminate vulnerable areas within the study area.
The North Unit had the most area with moderate, high, and very high vulnerability. These areas occurred all across the southern and eastern parts of the North Unit where the Little Missouri River, surficial aquifer, wetland type land covers, and bighorn sheep critical habitat are present. Several stressor flow paths from pipelines and highways cross these areas and may pose the most risk to the vulnerable areas identified. In the Elkhorn Ranch Unit, areas with moderate, high, and very high vulnerability were in the southeastern part of the unit, where the Little Missouri River, surficial aquifer, wetland type land covers, and bighorn sheep critical habitat are present. The stressor flow paths in the Elkhorn Ranch Unit follow the length of the Little Missouri River and all its tributaries in the study area. The stressor flow paths originated from crude oil wells and pipelines. In the South Unit, one area had moderate, high, and very high vulnerability. This area is where the Little Missouri River and bighorn sheep critical range are present. The stressor flow paths in the South Unit follow the length of the Little Missouri River and nearly all its tributaries in the study area. Several stressor flow paths cross the one identified vulnerable area that originated from crude oil wells.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3479","collaboration":"Prepared in cooperation with the Inland Oil Spill Preparedness Project","usgsCitation":"Valseth, K.J., 2021, Vulnerability assessment in and near Theodore Roosevelt National Park, North Dakota: U.S. Geological Survey Scientific Investigations Map 3479, pamphlet 9 p., 1 sheet, https://doi.org/10.3133/sim3479.","productDescription":"Pamphlet: vi, 9 p.; 1 Sheet: 23.50 x 31.10 inches; Dataset","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-122274","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":390167,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3479/sim3479_sheet1.pdf","text":"Sheet 1","size":"9.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3479 Sheet 1"},{"id":390169,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sim/3479/sim3479.xml","size":"53.7 kB","linkFileType":{"id":8,"text":"xml"},"description":"SIM 3479 Pamphlet xml"},{"id":390165,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3479/coverthb.jpg"},{"id":390168,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"},{"id":390166,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3479/sim3479_pamphlet.pdf","text":"Report","size":"2.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3479 Pamphlet"},{"id":390170,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sim/3479/images"}],"country":"United States","state":"North Dakota","otherGeospatial":"Theodore Roosevelt National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.72467041015625,\n 46.751153008636884\n ],\n [\n -103.14788818359375,\n 46.751153008636884\n ],\n [\n -103.14788818359375,\n 47.11873795272715\n ],\n [\n -103.72467041015625,\n 47.11873795272715\n ],\n [\n -103.72467041015625,\n 46.751153008636884\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503
1608 Mountain View Road
Rapid City, SD 57702
In 1999, a jet-fuels release was discovered at the Bulk Fuels Facility on Kirtland Air Force Base, Albuquerque, New Mexico. Contaminants had reached the water table and migrated north-northeast toward water-supply wells. Monitoring wells were installed downgradient from the facility to determine the primary zones of groundwater production for water-supply wells and assess contaminant presence. The monitoring wells are screened within the Santa Fe Group aquifer system, which includes clay units, at depths as great as 445 meters below land surface, and were categorized as water table, shallow, middle, deep, and aquifer-test pumping wells. Water-supply wells are screened across multiple water-bearing units within the aquifer system. All wells were sampled for major ions, trace elements, nutrients, stable isotopes, dissolved gases, tritium, carbon isotopes, and chlorofluorocarbons. The deeper and water-supply wells have evidence of longer groundwater residence times, as much as thousands of years, and water from the shallower wells shows evidence of anthropogenic nutrient inputs. Aquifer recharge is derived from either the mountain front or seepage from the Rio Grande. Dissolved-gas data indicate that the middle, deep, and aquifer-test pumping, and water-supply wells have cooler recharge temperatures than the shallower wells. Inferred groundwater age varies by method but indicates that the deeper, aquifer-test pumping, and water-supply wells have older water, as much as 15,000 years before present. Results indicate that the water-supply wells draw primarily from the middle and deeper portions of the aquifer system below the clay units and have not been affected by the contaminant plume, although some data indicate a potential for modern water entering some of the deeper and water-supply wells.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215076","collaboration":"Prepared in cooperation with the Air Force Civil Engineer Center","usgsCitation":"Travis, R.E., Bell, M.T., Linhoff, B.S., and Beisner, K.R., 2021, Utilizing multiple hydrogeologic and anthropogenic indicators to understand zones of groundwater contribution to water-supply wells near Kirtland Air Force Base Bulk Fuels Facility in southeast Albuquerque, New Mexico: U.S. Geological Survey Scientific Investigations Report 2021–5076, 28 p., https://doi.org/10.3133/sir20215076.","productDescription":"Report: viii, 28 p.; Data Release; Dataset","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-120223","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":390163,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"},{"id":389636,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5076/coverthb.jpg"},{"id":389637,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5076/sir20215076.pdf","text":"Report","size":"3.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5076"},{"id":389638,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NV9HHG","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Description of groundwater monitoring wells installed at and near Kirtland Air Force Base, Albuquerque, New Mexico, 2013–2016 (ver. 1.2, May 2019)"},{"id":389639,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5076/images/"}],"country":"United States","state":"New Mexico","city":"Albuquerque","otherGeospatial":"Kirtland Air Force Base","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.69097900390625,\n 34.89156324823376\n ],\n [\n -106.43692016601562,\n 34.90170042871546\n ],\n [\n -106.4410400390625,\n 35.081707990840705\n ],\n [\n -106.68823242187499,\n 35.068221159859256\n ],\n [\n -106.69097900390625,\n 34.89156324823376\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
The increasing incidence of wildfires across the southwestern United States (US) is altering the contemporary forest management template within historically frequent-fire conifer forests. An increasing fraction of southwestern conifer forests have recently burned, and many of these burned landscapes contain complex mosaics of surviving forest and severely burned patches without surviving conifer trees. These heterogeneous burned landscapes present unique social and ecological challenges. Severely burned patches can present numerous barriers to successful conifer regeneration, and often contain heavy downed fuels which have cascading effects on future fire behavior and conifer regeneration. Conversely, surviving forest patches are increasingly recognized for their value in postfire reforestation but often are overlooked from a management perspective.
Here we present a decision-making framework for landscape-scale management of complex postfire landscapes that allows for adaptation to a warming climate and future fire. We focus specifically on historically frequent-fire forests of the southwestern US but make connections to other forest types and other regions. Our framework depends on a spatially-explicit assessment of the mosaic of conifer forest and severely burned patches in the postfire landscape, evaluates likely vegetation trajectories, and identifies critical decision points to direct vegetation change via manipulations of fuels and live vegetation. This framework includes detailed considerations for postfire fuels management (e.g., edge hardening within live forest patches and repeat burning) and for reforestation (e.g., balancing tradeoffs between intensive and extensive planting strategies, establishing patches of seed trees, spatial planning to optimize reforestation success, and improving nursery capacity). In a future of increasing fire activity in forests where repeated low- to moderate-severity fire is essential to ecosystem resilience, the decision-making framework developed here can easily be integrated with existing postfire management strategies to optimize allocation of limited resources and more actively manage burned landscapes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2021.119678","usgsCitation":"Stevens, J., Haffey, C., Coop, J.D., Fornwalt, P.J., Yocom, L., Allen, C., Bradley, A., Burney, O.T., Carril, D., Chambers, M.E., Chapman, T.B., Haire, S.L., Hurteau, M., Iniguez, J.M., Margolis, E.Q., Marks, C., Marshall, L., Rodman, K., Stevens-Rumann, C.S., Thode, A., and Walker, J., 2021, Tamm review: Postfire landscape management in frequent-fire conifer forests of the southwestern United States: Forest Ecology and Management, v. 502, 119678, 21 p., https://doi.org/10.1016/j.foreco.2021.119678.","productDescription":"119678, 21 p.","ipdsId":"IP-130297","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":450553,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2021.119678","text":"Publisher Index 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This survey was carried out to detect the distribution of faults near the gas hydrate research well (Stratigraphic Test Well: Hydrate-01) on the North Slope of Alaska within the Prudhoe Bay Unit (PBU). The data were recorded with a single-mode DAS cable which is permanently installed and cemented behind the casing of the Hydrate-01 well. A total of 1701 shot records were successfully acquired in 12 days using a DAS interrogator with two vibroseis sources. The data were converted from strain rate to a geophone equivalent for further data processing. Traveltime tomography was carried out using the first break of each shot and was used to build a 3D tilted transverse isotropy (TTI) velocity model. The data were processed with a sequence designed to produce a precise and high resolution P wave image, that included editing, redatum, band pass filtering, denoise, upgoing / downgoing wavefield separation, deconvolution and migration. Faults around the Hydrate-01 were interpreted using the 3DVSP volume and its attributes. These faults were clearly observed in the 3DVSP volume but they cannot be recognized by an existing 3D surface seismic volume.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 14th SEGJ International Symposium","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceDate":"October 18-21, 2021","language":"English","publisher":"SEG","doi":"10.1190/segj2021-006.1","usgsCitation":"Fujimoto, A., Lim, T.K., Tamaki, M., Kawaguchi, K., Kobayashi, T., Haines, S.S., Collett, T., and Boswell, R., 2021, DAS 3DVSP survey at Stratigraphic Test Well (Hydrate-01), in Proceedings of the 14th SEGJ International Symposium, October 18-21, 2021, p. 19-22, https://doi.org/10.1190/segj2021-006.1.","productDescription":"4 p.","startPage":"19","endPage":"22","ipdsId":"IP-129862","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":421461,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2021-11-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Fujimoto, Akira","contributorId":330380,"corporation":false,"usgs":false,"family":"Fujimoto","given":"Akira","affiliations":[{"id":39359,"text":"JOGMEC","active":true,"usgs":false}],"preferred":false,"id":884811,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lim, Teck Kean","contributorId":330382,"corporation":false,"usgs":false,"family":"Lim","given":"Teck","email":"","middleInitial":"Kean","affiliations":[{"id":48092,"text":"TOYO Engineering","active":true,"usgs":false}],"preferred":false,"id":884812,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tamaki, Machiko","contributorId":330384,"corporation":false,"usgs":false,"family":"Tamaki","given":"Machiko","affiliations":[{"id":78875,"text":"JOE Co.","active":true,"usgs":false}],"preferred":false,"id":884813,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kawaguchi, Kyojiro","contributorId":330385,"corporation":false,"usgs":false,"family":"Kawaguchi","given":"Kyojiro","email":"","affiliations":[{"id":48092,"text":"TOYO Engineering","active":true,"usgs":false}],"preferred":false,"id":884814,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kobayashi, Toshiaki","contributorId":330387,"corporation":false,"usgs":false,"family":"Kobayashi","given":"Toshiaki","email":"","affiliations":[{"id":39359,"text":"JOGMEC","active":true,"usgs":false}],"preferred":false,"id":884815,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Haines, Seth S. 0000-0003-2611-8165 shaines@usgs.gov","orcid":"https://orcid.org/0000-0003-2611-8165","contributorId":1344,"corporation":false,"usgs":true,"family":"Haines","given":"Seth","email":"shaines@usgs.gov","middleInitial":"S.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":884816,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Collett, Timothy 0000-0002-7598-4708","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":220812,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":884817,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Boswell, Ray","contributorId":330389,"corporation":false,"usgs":false,"family":"Boswell","given":"Ray","affiliations":[{"id":78878,"text":"DOE NETL","active":true,"usgs":false}],"preferred":false,"id":884818,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70241791,"text":"70241791 - 2021 - Resilience of native amphibian communities following catastrophic drought: Evidence from a decade of regional-scale monitoring","interactions":[],"lastModifiedDate":"2023-03-27T12:05:50.759272","indexId":"70241791","displayToPublicDate":"2021-10-02T07:03:17","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Resilience of native amphibian communities following catastrophic drought: Evidence from a decade of regional-scale monitoring","docAbstract":"The increasing frequency and severity of drought may exacerbate ongoing global amphibian declines. However, interactions between drought and coincident stressors, coupled with high interannual variability in amphibian abundances, can mask the extent and underlying mechanisms of drought impacts. We synthesized a decade (2009–2019) of regional-scale amphibian monitoring data (2273 surveys, 233 ponds, and seven species) from across California's Bay Area and used dynamic occupancy modeling to estimate trends and drivers of species occupancy. An extreme drought during the study period resulted in substantial habitat loss, with 51% of ponds drying in the worst year of drought, compared to <20% in pre-drought years. Nearly every species exhibited reduced breeding activity during the drought, with the occupancy of some species (American bullfrogs and California newts) declining by >25%. Invasive fishes and bullfrogs were also associated with reduced amphibian occupancy, and these taxa were locally extirpated from numerous sites during drought, without subsequent recovery– suggesting that drought may present an opportunity to remove invaders. Despite a historic, multi-year drought, native amphibians rebounded quickly to pre-drought occupancy levels, demonstrating evidence of resilience. Permanent waterbodies supported higher persistence of native species during drought years than did temporary waterbodies, and we therefore highlight the value of hydroperiod diversity in promoting amphibian stability.
To assist resource managers and planners in developing informed strategies to address nitrogen loading to coastal water bodies of Long Island, New York, the U.S. Geological Survey and New York State Department of Environmental Conservation initiated a program to delineate areas contributing groundwater to coastal water bodies by assembling a comprehensive dataset of areas contributing groundwater, travel times, and groundwater discharges to streams, lakes, marine surface waters, and subsea discharge boundaries. Steady-state, 25-layer regional, three-dimensional finite-difference groundwater-flow models of average regional hydrologic conditions were used for particle-tracking analysis to delineate areas contributing groundwater to 843 water bodies. Two steady-state conditions were simulated: recent conditions from 2005 to 2015 and predevelopment conditions of about 1900. About 14 million particles were evenly distributed across the water table and tracked forward to discharge zones. Using a uniform porosity of 25 percent, simulated recent condition travel times ranged from less than 2 years to greater than 10,000 years and were visualized in 11 travel time intervals. About 85 percent of particle travel times from the water table to points of discharge are less than 100 years. Simulated particle-tracking ending zones represented 843 receiving water bodies, based on the New York State Department of Environmental Conservation water body inventory and priority water bodies list. Areal delineation of travel-time intervals and areas contributing groundwater to water bodies were generated and are summarized with total groundwater outflow for each water body.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215047","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Misut, P.E., Casamassina, N.A., and Walter, D.A., 2021, Delineation of areas contributing groundwater and travel times to receiving waters in Kings, Queens, Nassau, and Suffolk Counties, New York: U.S. Geological Survey Scientific Investigations Report 2021–5047, 61 p., https://doi.org/10.3133/sir20215047.","productDescription":"Report: iv, 61 p.; 3 Tables; Data Release","numberOfPages":"61","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-108532","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":389890,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2021/5047/sir20215047_table1.3.csv","text":"Table 1.3","size":"27.5 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Marine subsystems, estuaries, and number of receiving water bodies on Long Island, New York, associated with New York State priority water bodies"},{"id":389888,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2021/5047/sir20215047_table1.1.csv","text":"Table 1.1","size":"12.2 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Association of receiving water body index to New York State priority water body list database for water bodies on Long Island, New York"},{"id":389874,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5047/sir20215047.XML"},{"id":389876,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DKILJY","text":"USGS data release","linkHelpText":"MODFLOW–NWT and MODPATH6 used to delineate areas contributing groundwater and travel times to receiving waters of Kings, Queens, Nassau, and Suffolk Counties, New York"},{"id":389889,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2021/5047/sir20215047_table1.2.csv","text":"Table 1.2","size":"9.48 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Sum of groundwater outflows to receiving water bodies simulated by a flow model of regional hydrologic conditions from 2005 to 2015 for Long Island, New York"},{"id":389875,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5047/images/"},{"id":389872,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5047/sir20215047.pdf","text":"Report","size":"92.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5047"},{"id":389871,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5047/coverthb2.jpg"}],"country":"United States","state":"New York","county":"Kings County, Queens County, Nassau County, Suffolk County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.20166015624999,\n 40.51379915504413\n ],\n [\n -71.7572021484375,\n 40.51379915504413\n ],\n [\n -71.7572021484375,\n 41.21998578493921\n ],\n [\n -74.20166015624999,\n 41.21998578493921\n ],\n [\n -74.20166015624999,\n 40.51379915504413\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
Larval lampreys (Entosphenus tridentatus and Lampetra spp.) are vulnerable to anthropogenic water-level fluctuations that can dewater their habitat. Dewatering events occur regularly in the Columbia River Basin for operation and management of hydropower facilities, seasonal or maintenance closures of irrigation diversions, and in-water construction projects, including for habitat restoration. Salvage efforts which can be initiated before, during, and after dewatering events are resource-intensive and are conducted based on the assumption that salvage will reduce lamprey mortality. This pilot study was the first formal assessment of the efficacy of salvage efforts, evaluating the survival and performance of larval lamprey following various salvage techniques.
Lampreys were salvaged during dewatering events at three field sites under variable environmental conditions (summer and fall of 2020) and then held in the laboratory for 60 days to monitor survival, growth, and burrowing performance. Four salvage treatments were defined to represent combinations of typical salvage techniques and stressors, including multiple passes of standard electrofishing (SEF), lamprey-specific electrofishing (LEF), and modified lamprey-specific electrofishing (MLEF; probes in direct contact with dewatered, but moist substrate) as well as extended exposure on the surface and walking on sediment where lampreys were burrowed. Control groups did not experience dewatering and were collected using LEF in areas away from treatment groups. Treatments were designed to increase in intensity, from treatment 1 (walking and exposure) to treatment 4 (multiple passes of SEF, LEF and MLEF). Study sites included an earthen hatchery rearing pond (North Toutle Hatchery) dewatered in July, and two irrigation diversions (Wapato and Sunnyside diversions on Yakima River) dewatered at the end of the irrigation season in October. Treatments were executed inside circular 1 m2 enclosures that were randomly positioned in habitats expected to be dewatered. A solid, weighted ring at the bottom of the enclosure penetrated the sediment and netting extended through the water column to a floating upper ring. We deployed eight enclosures per treatment at each test site, executed the four salvage treatments, collected lamprey from within each enclosure and transported them to the laboratory, along with the control groups, for the 60-day holding period. Burrowing performance was tested in sand 1 day after the field effort and in field-collected sediment 30 days after the field effort. Mortality was documented and lamprey were measured at 1, 30, and 60 days in the laboratory and fish weights were used to calculate standard growth rate (SGR) for each site and treatment group.
We collected 328 larval lampreys at our three test sites, including 71 controls and 257 larvae exposed to dewatering and salvage treatments. Overall mortality for the 60-day laboratory holding period was 11.9%. Most mortality occurred within 1-day after treatment (51.3%) and there was limited mortality past 30 days (2.6%). At the North Toutle Hatchery, we observed substantial mortality during the field tests in July, both inside and outside of our test enclosures. Mortality within our test enclosures ranged from 96.7 to 98.8% for treatment 1, 45.9 to 52.2% for treatment 3 and 6.7 to 7.1% for treatment 4. The elevated mortality at this site and logistical challenges with the execution of treatments 1 and 2 resulted in few fish (5 total for treatment 1) or no fish (treatment 2) available for testing in the laboratory. Only one larval lamprey died during field tests at the Wapato and Sunnyside irrigation diversions during testing in October. The single mortality was in treatment 1 (11.1%) and no mortalities were observed outside of the test enclosures.
We used logistic regression to estimate survival of larval lampreys transported to the laboratory and held for 24 h. The Wapato and Sunnyside field sites were pooled for logistic regression and the North Toutle Hatchery site was analyzed separately due to dramatically different environmental conditions. We found that treatment 1 reduced larval survival more than any other treatment during both the summer and fall dewatering events. Trends among survival for treatments 2-4 were less clear. The unique stressor included in the first treatment, but not in other treatments, was a 2-hour exposure period during which larvae were left lying on the surface of the sediment. Treatment 1 also experienced a walking action (foot pressure on the surface of the exposed sediment). The walking action was also included in treatment 4, both before and after dewatering, along with multiple passes of various electrofishing techniques, as this treatment was designed to be a worst-case scenario for lamprey salvage. Despite what appeared to be significant stressors associated with treatment 4, the logistic regression for survival up to 24 hours in the laboratory showed that the odds of surviving treatment 4 were 16 times higher than the odds of surviving treatment 1 at Wapato and Sunnyside (combined). The same comparison at the North Toutle Hatchery showed the odds were 226 times higher for lamprey to survive treatment 4 compared to treatment 1.
Lamprey from all study sites initiated burrowing activity with median times less than 10.5 seconds in both sand (day 1) and field-collected sediment (day 30). The fastest burrowing start times were less than 1.0 second and the slowest was 3.2 minutes. Lamprey behavioral responses during burrowing ability tests were variable. Some lampreys immediately moved from the release location near the surface of the water toward the sediment and began burrowing while others swam around the aquarium near the surface of the water before exploring the sediment to select a burrowing location. The median time to complete burrowing for all treatment groups and sample periods ranged from 9.9 to 48.1 seconds.
No significant differences in SGR were detected between treatment and control groups at any test site. Laboratory water temperatures for the North Toutle Hatchery study groups were maintained at 15°C, giving lamprey a growth advantage compared to the Wapato and Sunnyside groups which were maintained at 10℃. SGR for lamprey collected at the North Toutle Hatchery ranged from 0.83% weight gain/day for controls to 2.04%/day for treatment 3. SGR at Wapato ranged from 0.27 to 0.67%/day and from 0.60 to 0.90 %/day at Sunnyside. Overall, SGR was consistently lower at every site for the controls compared to any of the treatment groups, although none of the differences were significant. The variability at some sites in initial lamprey size, combined with inherent variability in growth rates, limited our ability to make conclusions about how different salvage treatments influenced SGR.
Treatment 1 stood out among the salvage treatments at all study sites. In this treatment, lampreys exposed on the surface of the sediment, awaiting salvage, were vulnerable to reduced survival, even under mild environmental conditions. The risk of mortality was greatest for the summer dewatering event at the North Toutle Hatchery. The remaining treatments, even with multiple passes of various electrofishing techniques, did not generally have large negative impacts on lamprey during our tests. Lamprey survival rates for these treatments were relatively high, especially at the fall dewatering sites when environmental conditions were mild. Thus, salvage efforts, despite being resource intensive, likely have limited negative outcomes for larval lamprey and make substantial contributions to lamprey conservation efforts.
","language":"English","publisher":"Columbia Basin Fish & Wildlife Program","usgsCitation":"Liedtke, T.L., Harris, J.E., Skalicky, J.J., and Weiland, L.K., 2021, Evaluation of larval lamprey survival following salvage: A pilot study, 48 p.","productDescription":"48 p.","ipdsId":"IP-135055","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":412218,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":412172,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.cbfish.org/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Liedtke, Theresa L. 0000-0001-6063-9867 tliedtke@usgs.gov","orcid":"https://orcid.org/0000-0001-6063-9867","contributorId":2999,"corporation":false,"usgs":true,"family":"Liedtke","given":"Theresa","email":"tliedtke@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":862124,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harris, Julianne E. 0000-0003-1343-5911","orcid":"https://orcid.org/0000-0003-1343-5911","contributorId":247527,"corporation":false,"usgs":false,"family":"Harris","given":"Julianne","email":"","middleInitial":"E.","affiliations":[{"id":49569,"text":"U.S. Fish and Wildlife Service, Columbia River Fish and Wildlife Conservation Office, 1211 SE Cardinal Court, Suite 100, Vancouver, Washington 98683","active":true,"usgs":false}],"preferred":false,"id":862125,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Skalicky, Joseph J. 0000-0002-6467-5037","orcid":"https://orcid.org/0000-0002-6467-5037","contributorId":247528,"corporation":false,"usgs":false,"family":"Skalicky","given":"Joseph","email":"","middleInitial":"J.","affiliations":[{"id":49569,"text":"U.S. Fish and Wildlife Service, Columbia River Fish and Wildlife Conservation Office, 1211 SE Cardinal Court, Suite 100, Vancouver, Washington 98683","active":true,"usgs":false}],"preferred":false,"id":862126,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weiland, Lisa K. 0000-0002-9729-4062 lweiland@usgs.gov","orcid":"https://orcid.org/0000-0002-9729-4062","contributorId":3565,"corporation":false,"usgs":true,"family":"Weiland","given":"Lisa","email":"lweiland@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":862127,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70227507,"text":"70227507 - 2021 - Lake Ontario April prey fish survey and Alewife assessment, 2021","interactions":[],"lastModifiedDate":"2022-01-20T14:58:50.251696","indexId":"70227507","displayToPublicDate":"2021-10-01T08:56:20","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Lake Ontario April prey fish survey and Alewife assessment, 2021","docAbstract":"The Lake Ontario April bottom trawl survey and Alewife, Alosa psuedoharengus population assessment are conducted annually to track prey fish community status and aid management decisions related to predator-prey balance. No survey was conducted in 2020 due to the Covid-19 pandemic. The 2021 survey included 248 bottom trawls in both U.S. and Canadian waters, from March 30 - May 7 in the main lake and embayment regions, at depths ranging from 5 – 221 m (16 - 729 ft). The survey captured 947,102 fish, from 30 species with a total weight of 9,191 kg (20,220 lbs). Alewife were 89.2% of the catch by number while Rainbow Smelt, Osmerus mordax, Round Goby Neogobius melanostomus, and Deepwater Sculpin Myoxocephalus thompsonii comprised 5.6, 2.3, and 1.7% of the catch, respectively. Rainbow Smelt biomass in 2021 was among the highest values observed since 1997, especially in U.S. waters. The biomass index for Cisco, Coregonus artedii also increased, primarily due to catches and greater survey effort in the Bay of Quinte. Threespine stickleback, Gasterosteus aculeatus and Emerald Shiner, Notropis atherinoides biomasses remain low. No Bloater, Coregonus hoyi were captured during the 2021 survey.
In 2021, the lake-wide Alewife biomass index increased substantially from 2019 due to the presence of an exceptionally high catch of age-1 Alewife (2020 year class). The biomass index of adult Alewife (age-2 and up) declined slightly since 2019, which was expected since Alewife reproduction was generally below average from 2016 to 2019. Expanding the survey spatial extent from U.S. waters to a lake-wide survey in 2016 has improved our ability to estimate Alewife survival and has provided more accurate estimates of Lake Ontario Alewife biomass and density. Simulation modeling based on recent estimates of survival, growth, and reproduction suggests the adult Alewife biomass will likely increase in 2022 and 2023.
As part of a continued effort to improve prey fish surveys, we employed hydroacoustic sampling during the 2021 April trawl survey to estimate fish densities in open-water, pelagic habitats not sampled by the bottom trawl. We found fish density, in waters above the trawl headline depth (3m off bottom to surface), were approximately ~100 times lower than pelagic prey fish densities from bottom trawls. These results support the idea that at this time of year, when the warmest water is on the lake bottom, Alewife and most other prey fish primarily inhabit deep, near bottom regions and can be effectively sampled with bottom trawls. We were not able to apportion acoustics targets to species, however the low mean target strength (-43 decibels, dB) suggested these were small fishes (e.g., 100 mm). The greatest hydroacoustics densities were found near the Niagara River confluence and future surveys may use midwater trawls to determine which species these were and continue to improve this multi-agency survey.
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Jeremy","contributorId":139654,"corporation":false,"usgs":false,"family":"Holden","given":"Jeremy","affiliations":[{"id":12864,"text":"OMNRF","active":true,"usgs":false}],"preferred":false,"id":831195,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goretzke, Jessica","contributorId":268339,"corporation":false,"usgs":false,"family":"Goretzke","given":"Jessica","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":831196,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Connerton, Michael","contributorId":251649,"corporation":false,"usgs":false,"family":"Connerton","given":"Michael","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":831197,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70228736,"text":"70228736 - 2021 - Ecosystem modification and network position impact insect-mediated contaminant fluxes from a mountaintop mining-impacted river network","interactions":[],"lastModifiedDate":"2022-02-17T14:52:53.795882","indexId":"70228736","displayToPublicDate":"2021-10-01T08:41:53","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Ecosystem modification and network position impact insect-mediated contaminant fluxes from a mountaintop mining-impacted river network","docAbstract":"Aquatic-terrestrial contaminant transport via emerging aquatic insects has been studied across contaminant classes and aquatic ecosystems, but few studies have quantified the magnitude of these insect-mediated contaminant fluxes, limiting our understanding of their drivers. Using a recent conceptual model, we identified watershed mining extent, settling ponds, and network position as potential drivers of selenium (Se) fluxes from a mountaintop coal mining-impacted river network. Mining extent drove insect Se concentration (p = 0.008, R2 = 0.406), but ponding and network position were the principal drivers of Se flux through their impact on insect production. Se fluxes were 18 times higher from ponded, mined tributaries than from unponded ones and were comparable to fluxes from larger, productive mainstem sites. Thus, contaminant fluxes were highest in the river mainstem or below ponds, indicating that without considering controls on insect production, contaminant fluxes and their associated risks for predators like birds and bats can be misestimated.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2021.118257","usgsCitation":"Naslund, L.C., Gerson, J.R., Brooks, A.C., Rosemond, A.D., Walters, D., and Bernhardt, E., 2021, Ecosystem modification and network position impact insect-mediated contaminant fluxes from a mountaintop mining-impacted river network: Environmental Pollution, v. 291, 118257, 8 p., https://doi.org/10.1016/j.envpol.2021.118257.","productDescription":"118257, 8 p.","ipdsId":"IP-127990","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":450577,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envpol.2021.118257","text":"Publisher Index Page"},{"id":396095,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","county":"Lincoln County","otherGeospatial":"Mud River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.19833374023438,\n 38\n ],\n [\n -81.90650939941406,\n 38\n ],\n [\n -81.90650939941406,\n 38.2\n ],\n [\n -82.19833374023438,\n 38.2\n ],\n [\n -82.19833374023438,\n 38\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"291","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Naslund, Laura C.","contributorId":223770,"corporation":false,"usgs":false,"family":"Naslund","given":"Laura","email":"","middleInitial":"C.","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":835232,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gerson, Jacqueline R.","contributorId":198378,"corporation":false,"usgs":false,"family":"Gerson","given":"Jacqueline","email":"","middleInitial":"R.","affiliations":[{"id":27331,"text":"Duke University, Durham, NC","active":true,"usgs":false},{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":835233,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brooks, Alexander C.","contributorId":223771,"corporation":false,"usgs":false,"family":"Brooks","given":"Alexander","email":"","middleInitial":"C.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":835234,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rosemond, Amy D.","contributorId":279630,"corporation":false,"usgs":false,"family":"Rosemond","given":"Amy","email":"","middleInitial":"D.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":835235,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walters, David 0000-0002-4237-2158","orcid":"https://orcid.org/0000-0002-4237-2158","contributorId":203410,"corporation":false,"usgs":true,"family":"Walters","given":"David","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835236,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bernhardt, Emily S.","contributorId":92143,"corporation":false,"usgs":false,"family":"Bernhardt","given":"Emily S.","affiliations":[{"id":27331,"text":"Duke University, Durham, NC","active":true,"usgs":false}],"preferred":false,"id":835237,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70228948,"text":"70228948 - 2021 - Quantitative modeling of secondary migration: Understanding the origin of natural gas charge of the Haynesville Formation in the Sabine Uplift area of Louisiana and Texas","interactions":[],"lastModifiedDate":"2022-02-25T14:42:38.863117","indexId":"70228948","displayToPublicDate":"2021-10-01T08:39:21","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1717,"text":"GCAGS Journal","active":true,"publicationSubtype":{"id":10}},"title":"Quantitative modeling of secondary migration: Understanding the origin of natural gas charge of the Haynesville Formation in the Sabine Uplift area of Louisiana and Texas","docAbstract":"The Upper Jurassic (Kimmeridgian) mudstones of the Haynesville Formation in the Sabine Uplift, Louisiana and Texas, are widely considered to be a self-sourced natural gas reservoir; however, additional sources of gas may have charged the mudstones in the Louisiana portion of the uplift. Secondary migration of hydrocarbons into the Sabine Uplift from downdip, gas-generating Jurassic source rocks in the North Louisiana Salt Basin was quantitively modeled in this study. Jurassic source rocks include the Smackover, Haynesville, and Bossier Formations.
Thermodynamic equations of state were used to determine thermophysical properties of supercritical methane and water under reservoir conditions. A time-dependent derivation of Darcy’s Law for pressure-driven laminar fluid flow through porous media was used to model secondary migration at reservoir conditions. This study indicates secondary migration requires approximately 100,000 yr for pore fluids to migrate through 1.0 km of carrier beds having representative petrophysical, fluid, and reservoir properties of the Haynesville Formation. As an example migration pathway, the distance from the middle of the North Louisiana Salt Basin to the center of the Sabine Uplift is approximately 96 mi (155 km). Given migration velocities over this distance, 15.5 m.y. is required for hydrocarbons to migrate from the North Louisiana Salt Basin and charge the Haynesville Formation in the Sabine Uplift. This study also indicates supercritical water is 6 times more thermally conductive than methane under reservoir conditions; however, the relatively small volumes of migrated water likely did not transfer sufficient heat for the metagenesis of methane. Based on this study, a component of natural gas charging the Haynesville Formation of the Sabine Uplift area can reasonably be explained by lateral migration and hydrodynamic flow from thermally mature Jurassic source rocks located in adjacent basins.
","language":"English","publisher":"GCAGS","usgsCitation":"Burke, L.A., 2021, Quantitative modeling of secondary migration: Understanding the origin of natural gas charge of the Haynesville Formation in the Sabine Uplift area of Louisiana and Texas: GCAGS Journal, v. 10, p. 24-30.","productDescription":"7 p.","startPage":"24","endPage":"30","ipdsId":"IP-124868","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":396478,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":396464,"type":{"id":15,"text":"Index Page"},"url":"https://www.gcags.org/Journal/GCAGS.Journal.Vol.10.html"}],"country":"United States","state":"Louisiana, Texas","otherGeospatial":"Sabine Uplift","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.416015625,\n 29.76437737516313\n ],\n [\n -91.318359375,\n 29.76437737516313\n ],\n [\n -91.318359375,\n 33.578014746143985\n ],\n [\n -96.416015625,\n 33.578014746143985\n ],\n [\n -96.416015625,\n 29.76437737516313\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Burke, Lauri A. 0000-0002-2035-8048 lburke@usgs.gov","orcid":"https://orcid.org/0000-0002-2035-8048","contributorId":3859,"corporation":false,"usgs":true,"family":"Burke","given":"Lauri","email":"lburke@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":836018,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70236807,"text":"70236807 - 2021 - Geophysical constraints on the crustal architecture of the transtensional Warm Springs Valley fault zone, northern Walker Lane, western Nevada, USA","interactions":[],"lastModifiedDate":"2022-09-19T13:29:33.570798","indexId":"70236807","displayToPublicDate":"2021-10-01T08:24:05","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7501,"text":"JGR Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Geophysical constraints on the crustal architecture of the transtensional Warm Springs Valley fault zone, northern Walker Lane, western Nevada, USA","docAbstract":"The Walker Lane is a zone of distributed transtension where normal faults are overprinted by strike-slip motion. We use two newly-acquired high-resolution seismic reflection profiles and a reprocessed Consortium for Continental Reflection Profiling (COCORP) deep crustal reflection profile to assess the subsurface geometry of the Holocene-active, transtensional Warm Springs Valley fault zone (WSVFZ) near Reno, Nevada, USA. Our multi-scale observations extend to 12 km depth and suggest that the WSVFZ is more complex in the subsurface than implied by late Pleistocene surface fault traces. Two ~4-km-long high-resolution profiles image to a depth of ~2 km and reveal moderately dipping reflections and truncations, some of which project to mapped scarps formed in late Pleistocene surfaces. The shallow lines are co-located with COCORP profile NV 08 along ~40° N latitude. Re-analysis of the COCORP data reveals previously unidentified coherent reflections to a depth of ~12 km and a previously mapped ~30 west-dipping fault at 8-12 km. From these seismic profiles, the WSVFZ is not a simple, sub-vertical fault zone extending through the entire seismogenic crust. Instead, the reflections are consistent with a zone of steep- and moderately-dipping faults that simplify and steepen with depth before intersecting a mid-crustal, low angle (~25-30°) fault. The complex fault geometry of the WSVFZ implies that crustal shear is accommodated by a mix of dipping and subvertical faults in the transtensional northern Walker Lane. If so, transtensional fault zones may present challenges to paleoseismic and geodetic studies and require careful treatment when included in seismic hazard analyses.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JB020757","usgsCitation":"Briggs, R.W., Stephenson, W.J., McBride, J., Odum, J., Reitman, N.G., and Gold, R.D., 2021, Geophysical constraints on the crustal architecture of the transtensional Warm Springs Valley fault zone, northern Walker Lane, western Nevada, USA: JGR Solid Earth, v. 126, no. 10, e2020JB020757, 20 p., https://doi.org/10.1029/2020JB020757.","productDescription":"e2020JB020757, 20 p.","ipdsId":"IP-133139","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":406952,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Walker Lane, Warm Springs Valley fault zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.9981689453125,\n 39.620499321968104\n ],\n [\n -119.25933837890624,\n 39.620499321968104\n ],\n [\n -119.25933837890624,\n 40.245991504199026\n ],\n [\n -119.9981689453125,\n 40.245991504199026\n ],\n [\n -119.9981689453125,\n 39.620499321968104\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"126","issue":"10","noUsgsAuthors":false,"publicationDate":"2021-10-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Briggs, Richard W. 0000-0001-8108-0046 rbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-8108-0046","contributorId":139002,"corporation":false,"usgs":true,"family":"Briggs","given":"Richard","email":"rbriggs@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":852217,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stephenson, William J. 0000-0001-8699-0786 wstephens@usgs.gov","orcid":"https://orcid.org/0000-0001-8699-0786","contributorId":695,"corporation":false,"usgs":true,"family":"Stephenson","given":"William","email":"wstephens@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":852218,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McBride, J.H.","contributorId":296695,"corporation":false,"usgs":false,"family":"McBride","given":"J.H.","affiliations":[{"id":64143,"text":"Department of Geological Sciences, Brigham Young University, Provo, UT, USA","active":true,"usgs":false}],"preferred":false,"id":852219,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Odum, Jackson K. 0000-0003-4697-2430 odum@usgs.gov","orcid":"https://orcid.org/0000-0003-4697-2430","contributorId":1365,"corporation":false,"usgs":true,"family":"Odum","given":"Jackson K.","email":"odum@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":852220,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reitman, Nadine G. 0000-0002-6730-2682 nreitman@usgs.gov","orcid":"https://orcid.org/0000-0002-6730-2682","contributorId":5816,"corporation":false,"usgs":true,"family":"Reitman","given":"Nadine","email":"nreitman@usgs.gov","middleInitial":"G.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":852221,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gold, Ryan D. 0000-0002-4464-6394 rgold@usgs.gov","orcid":"https://orcid.org/0000-0002-4464-6394","contributorId":3883,"corporation":false,"usgs":true,"family":"Gold","given":"Ryan","email":"rgold@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":852222,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70225608,"text":"70225608 - 2021 - Hydrogeology and simulation of groundwater flow in Columbia County, Wisconsin","interactions":[],"lastModifiedDate":"2021-10-27T16:48:33.308605","indexId":"70225608","displayToPublicDate":"2021-10-01T08:15:46","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":5959,"text":"Wisconsin Geological and NaturalHistory Survey Bulletin","active":true,"publicationSubtype":{"id":2}},"title":"Hydrogeology and simulation of groundwater flow in Columbia County, Wisconsin","docAbstract":"This report describes the regional hydrogeology and groundwater resources of Columbia County, Wisconsin, and documents a regional groundwater flow model developed for the county. Regional hydrostratigraphic units include the unlithified aquifer, the upper bedrock aquifer, and the Elk Mound aquifer.\n\nThe unlithified aquifer consists of deposits that range in composition from sand and gravel outwash and stream deposits to silty, sandy till. This aquifer is less than 25 ft thick in much of eastern Columbia County, but consists of permeable sand and gravel extending to over 250 ft in depth in the Wisconsin River valley bottom. \n\nThe upper bedrock aquifer consists of Ordovician and upper Cambrian sedimentary formations, including sandstone, siltstone and dolomitic strata. The upper bedrock aquifer underlies the unlithified aquifer in eastern portions of the County, but is absent to the west, where these formations are largely eroded. The contact between the Tunnel City Group and Wonewoc Formation (Top of Elk Mound Group) forms the base of the upper bedrock aquifer. Bedding plane fractures are common to this aquifer, although only a portion of the observed fractures appear to be hydraulically active. The upper bedrock aquifer is a significant source of groundwater at a regional scale. Measurements of hydraulic head showed a difference of several feet across the bottom of this aquifer to the underlying Wonewoc sandstone, indicating that the basal facies of the Tunnel City Group functions as an aquitard separating the upper bedrock aquifer from the Elk Mound aquifer. Conditions vary considerably within this aquifer, depending on the local lithostratigraphy. For example, where present, the St. Lawrence Fm. and fine-grained intervals of the Tunnel City Group may be locally-extensive aquitards. \nThe Elk Mound aquifer consists of Cambrian sandstone of the Wonewoc, Eau Claire, and Mount Simon Formations. It is thin to absent in several locations but ranges up to 600 ft in thickness over much of southern Columbia County. The variation in thickness is due in large part to the irregular topography of the underlying Precambrian crystalline rock, which generally serves as the base of the groundwater system. In neighboring counties, a fine-grained facies within the Eau Claire Fm. acts as a regionally extensive aquitard, referred to as the Eau Claire aquitard. Much of the data collected and compiled for this study suggest that shale or dolomite within the Eau Claire Fm., which is the equivalent of the Eau Claire aquitard, occurs only within southwestern Columbia County. There is little to no evidence of the Eau Claire aquitard over most of the county. Where the dolomite and shale are absent, the Elk Mound aquifer is relatively homogenous and does not include a mappable aquitard. \nA three-dimensional steady-state flow model presented here represents long-term, average conditions in the regional groundwater system since about 1970. The model was constructed with the U.S. Geological Survey’s MODFLOW-NWT code; it has six layers with a uniform grid of 300 ft x 300 ft cells. Layers 1 and 2 simulate the unlithified aquifer and layer 3 represents the upper bedrock aquifer. The Elk Mound aquifer is simulated by layers 4, 5 and 6, representing the Wonewoc, Eau Claire, and Mount Simon Formations, respectively. The model extends beyond the boundaries of Columbia County to ensure that hydrologic conditions simulated within the County are consistent with regional conditions. \nRecharge to the groundwater flow model is based on results from a GIS-based soil-water-balance model. Recharge was simulated with the unsaturated zone flow (UZF) package in MODFLOW. This approach is particularly useful for quantifying groundwater discharge to riparian wetlands because UZF tracks recharge that would lead to the simulated water table exceeding the land surface (represented by the top of model layer 1) and reroutes it to nearby stream segments. The model includes pumping from 256 wells, and 178 of these are located within Columbia County. Pumping totaled about 28 million gallons per day (mgd) on average since 1970, with 7.2 mgd of the withdrawal from within the County. Model calibration was performed with the PEST parameter estimation code. Calibration targets included approximately 3,900 head measurements and 91 stream flow measurements. Four vertical-head differences across hydrogeologic units, calculated from data collected during packer testing in wells in Columbia County, were also used in model calibration. \n\nResults from the calibrated model provide a groundwater balance for the region. About 83 percent of groundwater originates as recharge to the water table, 12 percent comes from leakage from streams, and about 5 percent of the groundwater flows into the model domain from surrounding areas. About 95 percent of the simulated groundwater discharges to steams and other surface water features, about 3 percent flows across model boundaries to surrounding areas of the groundwater system, and pumping accounts for 2 percent of discharge. Simulated flow paths are relatively local, from recharge in upland areas to discharge in nearby streams and wetlands. \n\nThe model has many potential applications, including simulation of the effects of existing or proposed high-capacity wells, estimating the zone of contribution for these wells, and understanding relationships between surface water and groundwater. Future refinements to the model, such as incorporating new information about the extent and hydraulic characteristics of the Tunnel City Group, will improve its utility in understanding advective flow between the upper bedrock and Elk Mound aquifers. If seasonal or annual variations in the groundwater system are of interest, this steady-state model could be brought into a transient mode.","language":"English","publisher":"Wisconsin Geological and Natural History Survey","usgsCitation":"Gotkowitz, M., Leaf, A.T., and Sellwood, S.M., 2021, Hydrogeology and simulation of groundwater flow in Columbia County, Wisconsin: Wisconsin Geological and NaturalHistory Survey Bulletin, 51 p.","productDescription":"51 p.","ipdsId":"IP-101440","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":391008,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":391000,"type":{"id":15,"text":"Index Page"},"url":"https://wgnhs.wisc.edu/catalog/publication/000985"}],"country":"United States","state":"Wisconsin","county":"Columbia County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-89.2453,43.643],[-89.127,43.6436],[-89.1271,43.6318],[-89.007,43.6332],[-89.0063,43.548],[-89.0044,43.4616],[-89.0038,43.3737],[-89.0088,43.3738],[-89.0094,43.286],[-89.1271,43.2827],[-89.246,43.2834],[-89.3624,43.2832],[-89.3617,43.2954],[-89.4819,43.2942],[-89.6008,43.2932],[-89.7209,43.2935],[-89.7235,43.2935],[-89.7292,43.3026],[-89.7279,43.3108],[-89.7254,43.3153],[-89.7229,43.3181],[-89.7185,43.3195],[-89.7129,43.3226],[-89.7078,43.3277],[-89.7028,43.3345],[-89.6909,43.3495],[-89.684,43.3573],[-89.6783,43.3586],[-89.6708,43.3582],[-89.6613,43.3577],[-89.6456,43.36],[-89.6311,43.3646],[-89.6166,43.371],[-89.6009,43.3806],[-89.6004,43.4688],[-89.5999,43.5544],[-89.6075,43.5603],[-89.6138,43.5626],[-89.6277,43.5617],[-89.6359,43.5603],[-89.6511,43.5621],[-89.658,43.5634],[-89.6643,43.5657],[-89.6707,43.5666],[-89.6783,43.5671],[-89.6877,43.5634],[-89.6934,43.5616],[-89.6991,43.562],[-89.706,43.5648],[-89.7187,43.5652],[-89.7288,43.5661],[-89.7351,43.5693],[-89.7364,43.5743],[-89.7326,43.5793],[-89.7288,43.5829],[-89.7244,43.587],[-89.7188,43.5929],[-89.7207,43.597],[-89.727,43.5979],[-89.7428,43.597],[-89.751,43.5997],[-89.7567,43.6029],[-89.7662,43.6029],[-89.7738,43.6092],[-89.7763,43.6161],[-89.7808,43.6215],[-89.7802,43.6274],[-89.7789,43.6343],[-89.784,43.6388],[-89.7866,43.6411],[-89.779,43.6411],[-89.7195,43.643],[-89.6,43.6427],[-89.4837,43.6423],[-89.3648,43.6427],[-89.2453,43.643]]]},\"properties\":{\"name\":\"Columbia\",\"state\":\"WI\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gotkowitz, Madeline","contributorId":268135,"corporation":false,"usgs":false,"family":"Gotkowitz","given":"Madeline","affiliations":[{"id":39043,"text":"Wisconsin Geological and Natural History Survey","active":true,"usgs":false}],"preferred":false,"id":825890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leaf, Andrew T. 0000-0001-8784-4924 aleaf@usgs.gov","orcid":"https://orcid.org/0000-0001-8784-4924","contributorId":5156,"corporation":false,"usgs":true,"family":"Leaf","given":"Andrew","email":"aleaf@usgs.gov","middleInitial":"T.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":825891,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sellwood, Steven M.","contributorId":268136,"corporation":false,"usgs":false,"family":"Sellwood","given":"Steven","email":"","middleInitial":"M.","affiliations":[{"id":55571,"text":"TRC Companies, Inc.","active":true,"usgs":false}],"preferred":false,"id":825892,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70231688,"text":"70231688 - 2021 - Formation of miarolitic-class, segregation-type pegmatites in the Taishanmiao batholith, China: The role of pressure fluctuations and volatile exsolution during pegmatite formation in a closed, isochoric system","interactions":[],"lastModifiedDate":"2022-05-20T11:43:43.386642","indexId":"70231688","displayToPublicDate":"2021-10-01T06:40:27","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":738,"text":"American Mineralogist","active":true,"publicationSubtype":{"id":10}},"title":"Formation of miarolitic-class, segregation-type pegmatites in the Taishanmiao batholith, China: The role of pressure fluctuations and volatile exsolution during pegmatite formation in a closed, isochoric system","docAbstract":"The Taishanmiao granitic batholith, located in the Eastern Qinling Orogen in Henan Province, China, contains numerous small (mostly tens of centimeters in maximum dimension) bodies exhibiting textures and mineralogy characteristics of simple quartz and alkali feldspar pegmatites. Analysis of melt inclusions (MI) and fluid inclusions (FI) in pegmatitic quartz, combined with Rhyolite-MELTS modeling of the crystallization of the granite, have been applied to develop a conceptual model of the physical and geochemical processes associated with the formation of the pegmatites. These results allow us to consider the formation of the Taishanmiao pegmatites within the context of varios models that have been proposed for pegmatite formation.
Field observations and geochemical data indicate that the pegmatites represent the latest stage in the crystallization of the Taishanmiao granite and occupy ≤4 vol% of the syenogranite phase of the batholith. Results of Rhyolite-MELTS modeling suggest that the pegmatite-forming melts can be produced through continuous fractional crystallization of the Taishanmiao granitic magma, consistent with the designation of the pegmatites as a miarolitic class, segregation-type pegmatites rather than the more common intrusive-type of pegmatite. The mineral assemblage predicted by Rhyolite-MELTS after ~96% of the original granite-forming melt had crystallized consists of ~51 vol% alkali feldspar, 34 vol% quartz, 14 vol% plagioclase, 0.1 vol% biotite, and 1 vol% magnetite, similar to the alkali feldspar + quartz dominated mineralogy of the pegmatites. Moreover, the modeled residual melt composition following crystallization of ~96% of the original melt is similar to the composition of homogenized MI in quartz within the pegmatite. Rhyolite-MELTS predicts that the granite-forming melt remained volatile-undersaturated during crystallization of the batholith and contained ~6.3 wt% H2O and ~500 ppm CO2 after ~96% crystallization when the pegmatites began to develop. The Rhyolite-MELTS prediction that the melt was volatile-undersaturated at the time the pegmatites began to form, but became volatile-saturated during the early stages of pegmatite formation, is consistent with the presence of some inclusion assemblages consisting of only MI, while others contain co-existing MI and FI. The relationship between halogen (F and Cl) and Na abundances in MI is also consistent with the interpretation that the very earliest stages of pegmatite formation occurred in the presence of a volatile-undersaturated melt and that the melt became volatile saturated as crystallization progressed.
We propose a closed system, isochoric model for the formation of the pegmatites. Accordingly, the Taishanmiao granite crystallized isobarically at ~3.3 kbar, and the pegmatites began to form at ~734 °C and ~ 3.3 kbar, after ~96% of the original granitic melt had crystallized. During the final stages of crystallization of the granite, small pockets of the remaining residual melt became isolated within the enclosing granite and evolved as constant mass (closed), constant volume (isochoric) systems, similar to the manner in which volatile-rich melt inclusions in igneous phenocrysts evolve during post-entrapment crystallization under isochoric conditions. As a result of the negative volume change associated with crystallization, pressure in the pegmatite initially decreases as crystals form, and this leads to volatile exsolution from the melt phase. The changing PTX conditions produce a pressure-induced “liquidus deficit” that is analogous to liquidus undercooling and results in crystal growth as required to return the system to equilibrium PTX conditions. Owing to the complex closed system, isochoric PVTX evolution of the melt-crystal-volatile system, the pressure does not decrease rapidly or monotonically during pegmatite formation but, rather, gradually fluctuates such that at some stages in the evolution of the pegmatite the pressure is decreasing while at other times the pressure increases as the system cools to maintain mass and volume balance. This behavior, in turn, leads to alternating episodes of precipitation and dissolution that serve to coarsen (ripen) the crystals to produce the pegmatitic texture. The evolution of the pegmatitic melt described here is analogous to that which has been well-documented to occur in volatile-rich MI that undergo closed system, isochoric, post-entrapment crystallization.
","language":"English","publisher":"Mineralogical Society of America","doi":"10.2138/am-2021-7637","usgsCitation":"Yuan, Y., Moore, L., McAleer, R.J., Yuan, S., Ouyang, H., Belkin, H.E., Mao, J., Sublett, M.D., and Bodnar, R., 2021, Formation of miarolitic-class, segregation-type pegmatites in the Taishanmiao batholith, China: The role of pressure fluctuations and volatile exsolution during pegmatite formation in a closed, isochoric system: American Mineralogist, v. 106, no. 10, p. 1559-1573, https://doi.org/10.2138/am-2021-7637.","productDescription":"15 p.","startPage":"1559","endPage":"1573","ipdsId":"IP-119402","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":467224,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10919/111949","text":"External Repository"},{"id":400852,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[110.33919,18.6784],[109.47521,18.1977],[108.65521,18.50768],[108.62622,19.36789],[109.11906,19.82104],[110.2116,20.10125],[110.78655,20.07753],[111.01005,19.69593],[110.57065,19.25588],[110.33919,18.6784]]],[[[127.65741,49.76027],[129.39782,49.4406],[130.58229,48.72969],[130.98728,47.79013],[132.50667,47.78897],[133.3736,48.18344],[135.02631,48.47823],[134.50081,47.57844],[134.11236,47.21247],[133.76964,46.11693],[133.09713,45.14407],[131.88345,45.32116],[131.02521,44.96795],[131.28856,44.11152],[131.14469,42.92999],[130.63387,42.90301],[130.64002,42.39501],[129.99427,42.98539],[129.59667,42.42498],[128.05222,41.99428],[128.20843,41.46677],[127.34378,41.50315],[126.86908,41.81657],[126.18205,41.10734],[125.07994,40.56982],[124.26562,39.92849],[122.86757,39.63779],[122.13139,39.17045],[121.05455,38.89747],[121.58599,39.36085],[121.37676,39.75026],[122.1686,40.42244],[121.64036,40.94639],[120.76863,40.59339],[119.6396,39.89806],[119.02346,39.25233],[118.04275,39.20427],[117.5327,38.73764],[118.0597,38.06148],[118.87815,37.89733],[118.91164,37.44846],[119.7028,37.15639],[120.82346,37.87043],[121.71126,37.48112],[122.35794,37.45448],[122.51999,36.93061],[121.10416,36.65133],[120.63701,36.11144],[119.66456,35.60979],[119.15121,34.90986],[120.22752,34.36033],[120.62037,33.37672],[121.22901,32.46032],[121.90815,31.69217],[121.89192,30.94935],[121.26426,30.67627],[121.50352,30.14291],[122.09211,29.83252],[121.93843,29.01802],[121.68444,28.22551],[121.12566,28.13567],[120.39547,27.05321],[119.5855,25.74078],[118.65687,24.54739],[117.28161,23.6245],[115.89074,22.78287],[114.76383,22.66807],[114.15255,22.22376],[113.80678,22.54834],[113.24108,22.05137],[111.84359,21.55049],[110.78547,21.39714],[110.44404,20.34103],[109.88986,20.28246],[109.62766,21.00823],[109.86449,21.39505],[108.52281,21.71521],[108.05018,21.55238],[107.04342,21.8119],[106.56727,22.2182],[106.7254,22.79427],[105.81125,22.97689],[105.32921,23.35206],[104.47686,22.81915],[103.50451,22.70376],[102.70699,22.7088],[102.17044,22.46475],[101.65202,22.3182],[101.80312,21.17437],[101.27003,21.20165],[101.18001,21.43657],[101.15003,21.84998],[100.41654,21.55884],[99.98349,21.74294],[99.2409,22.11831],[99.53199,22.94904],[98.89875,23.14272],[98.66026,24.06329],[97.60472,23.8974],[97.72461,25.08364],[98.67184,25.9187],[98.71209,26.74354],[98.68269,27.50881],[98.24623,27.74722],[97.91199,28.33595],[97.32711,28.26158],[96.24883,28.41103],[96.58659,28.83098],[96.11768,29.4528],[95.4048,29.03172],[94.56599,29.27744],[93.41335,28.64063],[92.50312,27.89688],[91.69666,27.77174],[91.25885,28.04061],[90.73051,28.06495],[90.01583,28.29644],[89.47581,28.04276],[88.81425,27.29932],[88.73033,28.08686],[88.12044,27.87654],[86.95452,27.97426],[85.82332,28.20358],[85.01164,28.64277],[84.23458,28.83989],[83.89899,29.32023],[83.33712,29.46373],[82.32751,30.11527],[81.5258,30.42272],[81.11126,30.18348],[79.72137,30.88271],[78.73889,31.51591],[78.45845,32.61816],[79.17613,32.48378],[79.20889,32.99439],[78.81109,33.5062],[78.91227,34.32194],[77.83745,35.49401],[76.19285,35.8984],[75.8969,36.66681],[75.15803,37.13303],[74.98,37.41999],[74.82999,37.99001],[74.86482,38.37885],[74.25751,38.60651],[73.92885,38.50582],[73.67538,39.43124],[73.96001,39.66001],[73.82224,39.89397],[74.77686,40.36643],[75.46783,40.56207],[76.52637,40.42795],[76.90448,41.06649],[78.1872,41.18532],[78.54366,41.58224],[80.11943,42.12394],[80.25999,42.35],[80.18015,42.92007],[80.86621,43.18036],[79.96611,44.91752],[81.94707,45.31703],[82.45893,45.53965],[83.18048,47.33003],[85.16429,47.00096],[85.72048,47.45297],[85.76823,48.45575],[86.59878,48.54918],[87.35997,49.21498],[87.75126,49.2972],[88.01383,48.59946],[88.8543,48.06908],[90.28083,47.69355],[90.97081,46.88815],[90.58577,45.71972],[90.94554,45.28607],[92.13389,45.11508],[93.48073,44.97547],[94.68893,44.35233],[95.30688,44.24133],[95.76245,43.31945],[96.3494,42.72564],[97.45176,42.74889],[99.51582,42.52469],[100.84587,42.6638],[101.83304,42.51487],[103.31228,41.90747],[104.52228,41.90835],[104.96499,41.59741],[106.12932,42.13433],[107.74477,42.48152],[109.2436,42.51945],[110.4121,42.87123],[111.12968,43.40683],[111.82959,43.74312],[111.66774,44.07318],[111.34838,44.45744],[111.87331,45.10208],[112.43606,45.01165],[113.46391,44.80889],[114.46033,45.33982],[115.9851,45.72724],[116.71787,46.3882],[117.4217,46.67273],[118.87433,46.80541],[119.66327,46.69268],[119.77282,47.04806],[118.86657,47.74706],[118.06414,48.06673],[117.29551,47.69771],[116.30895,47.85341],[115.74284,47.72654],[115.48528,48.13538],[116.1918,49.1346],[116.6788,49.88853],[117.87924,49.51098],[119.28846,50.14288],[119.27937,50.58291],[120.18205,51.64357],[120.73819,51.96412],[120.72579,52.51623],[120.17709,52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Yabin","contributorId":291938,"corporation":false,"usgs":false,"family":"Yuan","given":"Yabin","email":"","affiliations":[{"id":51380,"text":"Chinese Academy of Geological Sciences","active":true,"usgs":false}],"preferred":false,"id":843418,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Lowell","contributorId":264239,"corporation":false,"usgs":false,"family":"Moore","given":"Lowell","email":"","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":843419,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":843420,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yuan, Shunda","contributorId":203441,"corporation":false,"usgs":false,"family":"Yuan","given":"Shunda","email":"","affiliations":[{"id":36622,"text":"Institute of Mineral Resources, Chinese Academy of Geological Sciences","active":true,"usgs":false}],"preferred":false,"id":843421,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ouyang, Hegen","contributorId":291939,"corporation":false,"usgs":false,"family":"Ouyang","given":"Hegen","email":"","affiliations":[{"id":51380,"text":"Chinese Academy of Geological Sciences","active":true,"usgs":false}],"preferred":false,"id":843422,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Belkin, Harvey E. 0000-0001-7879-6529","orcid":"https://orcid.org/0000-0001-7879-6529","contributorId":190267,"corporation":false,"usgs":false,"family":"Belkin","given":"Harvey","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":843423,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mao, Jingwen","contributorId":291940,"corporation":false,"usgs":false,"family":"Mao","given":"Jingwen","email":"","affiliations":[{"id":51380,"text":"Chinese Academy of Geological Sciences","active":true,"usgs":false}],"preferred":false,"id":843424,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sublett, Matthew D.","contributorId":291941,"corporation":false,"usgs":false,"family":"Sublett","given":"Matthew","email":"","middleInitial":"D.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":843425,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bodnar, Robert J.","contributorId":261193,"corporation":false,"usgs":false,"family":"Bodnar","given":"Robert J.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":843426,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70256533,"text":"70256533 - 2021 - Modeling distribution of endemic Bartram’s Bass Micropterus sp. cf. coosae: Disturbance and proximity to invasion source increase hybridization with invasive Alabama Bass","interactions":[],"lastModifiedDate":"2024-08-19T15:11:51.714383","indexId":"70256533","displayToPublicDate":"2021-10-01T00:00:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Modeling distribution of endemic Bartram’s Bass Micropterus sp. cf. coosae: Disturbance and proximity to invasion source increase hybridization with invasive Alabama Bass","docAbstract":"“Bartram’s Bass” Micropterus sp. cf. coosae is endemic to the upper Savannah River basin of the southeastern United States and is threatened by hybridization with invasive Alabama Bass Micropterus henshalli. Bartram’s Bass have been functionally extirpated from reservoirs, and hybrid individuals have been detected in several tributaries. However, the extent of introgression in tributaries is currently unknown. Our objectives were to (1) assess the distribution of Bartram’s Bass, native Largemouth Bass M. salmoides, invasive Alabama Bass, and their hybrids in streams of the upper Savannah River basin and (2) quantify effects of abiotic variables on the distribution of each species. We sampled 154 locations in 2017 and 2018 and assigned genetic identity using hydrolysis probes and microsatellites. We used conditional inference trees to quantify variables affecting the occurrence of each species and hybrids. We observed widespread hybridization across the basin. Pure Bartram’s Bass were collected at 27% (42) of sites, among which only 12 sites contained pure Bartram’s Bass and no other congeners. Thirty sites where pure Bartram’s Bass were collected contained hybrids. In the montane Blue Ridge ecoregion, occurrence of pure Bartram’s Bass was negatively affected by low levels of local-scale developed land cover. In the lower-relief Piedmont ecoregion, pure Bartram’s Bass were positively associated with watershed-scale forest land cover and stream gradient. Distance from a reservoir was positively associated with occurrence of pure Bartram’s Bass in both ecoregions. Pure Bartram’s Bass are likely to occur with high probability in only 16% of nonimpounded stream segments; this represents a conservative estimate, and the true number is likely lower. However, future work accounting for incomplete detection of Bartram’s Bass will help to improve confidence in true extirpations. Conservation efforts may be more successful if implemented on stream segments farther from reservoirs or upstream of dispersal barriers preventing colonization of Alabama Bass.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10637","usgsCitation":"Peoples, B., Judson, E., Darden, T.L., Farrae, D.J., Kubach, K., Leitner, J., and Scott, M.C., 2021, Modeling distribution of endemic Bartram’s Bass Micropterus sp. cf. coosae: Disturbance and proximity to invasion source increase hybridization with invasive Alabama Bass: North American Journal of Fisheries Management, v. 41, no. 5, p. 1309-1321, https://doi.org/10.1002/nafm.10637.","productDescription":"13 p.","startPage":"1309","endPage":"1321","ipdsId":"IP-152697","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":432883,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia, North Carolina, South Carolina","otherGeospatial":"Savannah River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": 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Kevin","contributorId":341212,"corporation":false,"usgs":false,"family":"Kubach","given":"Kevin","email":"","affiliations":[{"id":35670,"text":"South Carolina Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":907848,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leitner, Jean","contributorId":177201,"corporation":false,"usgs":false,"family":"Leitner","given":"Jean","email":"","affiliations":[],"preferred":false,"id":910836,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Scott, Mark C.","contributorId":341033,"corporation":false,"usgs":false,"family":"Scott","given":"Mark","email":"","middleInitial":"C.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":907849,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70224620,"text":"sir20215065 - 2021 - Conceptual and numerical groundwater flow model of the Cedar River alluvial aquifer system with simulation of drought stress on groundwater availability near Cedar Rapids, Iowa, for 2011 through 2013","interactions":[],"lastModifiedDate":"2021-10-01T12:09:28.489755","indexId":"sir20215065","displayToPublicDate":"2021-09-30T21:14:22","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5065","displayTitle":"Conceptual and Numerical Groundwater Flow Model of the Cedar River Alluvial Aquifer System with Simulation of Drought Stress on Groundwater Availability near Cedar Rapids, Iowa, for 2011 through 2013","title":"Conceptual and numerical groundwater flow model of the Cedar River alluvial aquifer system with simulation of drought stress on groundwater availability near Cedar Rapids, Iowa, for 2011 through 2013","docAbstract":"Between July 2011 and February 2013, the City of Cedar Rapids observed water level declines in their horizontal collector wells approaching 11 meters. As a result, pumping from these production wells had to be halted, and questions were raised about the reliability of the alluvial aquifer under future drought conditions. The U.S. Geological Survey, in cooperation with the City of Cedar Rapids, completed a study to better understand the effects of drought stress on the Cedar River alluvial aquifer using a numerical groundwater flow model. Previously published groundwater flow models were combined with newly collected airborne, waterborne, down-hole, and land-based geophysical survey data and provided a detailed three-dimensional lithologic model of the Cedar River alluvial aquifer and surrounding area. An improved conceptual model for the groundwater flow system and a lithologic model were used to build and inform a numerical groundwater flow model capable of simulating water levels observed in the City of Cedar Rapids horizontal collector wells during the 2012 drought. Model performance was assessed primarily on the ability of the model to simulate water table elevation at six monitoring wells. Statistical tests were used to assess the numerical model during the calibration period, and results varied from satisfactory to unsatisfactory, likely because of stage changes in the Cedar River and production well withdrawal rates near monitoring wells. Simulated water levels during the 2012 drought indicated a depression near the horizontal collector wells, although simulated elevations at these locations and at monitoring wells were generally overestimated compared to measured values. The numerical groundwater flow model was modified to account for a decrease in seepage rate caused by low flow in the Cedar River and increased production. With seepage rate modification, model results improved; the simulated water table elevations were like those observed in horizontal collector and monitoring wells. Results demonstrated the ability of the model to simulate water levels observed in the horizontal collector wells during the 2012 drought when accounting for a decrease in infiltration from the Cedar River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215065","collaboration":"Prepared in cooperation with the City of Cedar Rapids","usgsCitation":"Haj, A.E., Ha, W.S., Gruhn, L.R., Bristow, E.L., Gahala, A.M., Valder, J.F., Johnson, C.D., White, E.A., and Sterner, S.P., 2021, Conceptual and numerical groundwater flow model of the Cedar River alluvial aquifer system with simulation of drought stress on groundwater availability near Cedar Rapids, Iowa, for 2011 through 2013: U.S. Geological Survey Scientific Investigations Report 2021–5065, 59 p., https://doi.org/10.3133/sir20215065.","productDescription":"Report: ix, 59 p.; Appendix; 3 Data Releases; Dataset","numberOfPages":"74","onlineOnly":"Y","ipdsId":"IP-118762","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":390066,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5065/coverthb.jpg"},{"id":390067,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5065/sir20215065.pdf","text":"Report","size":"8.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5065"},{"id":390069,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BS882S","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Airborne electromagnetic and magnetic survey data and inverted resistivity models, Cedar Rapids, Iowa, May 2017"},{"id":390070,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96CF4L5","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"MODFLOW-NWT model used to simulate groundwater levels in the Cedar River alluvial aquifer near Cedar Rapids, Iowa"},{"id":390071,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YXJDHX","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Geophysical data collected in the Cedar River floodplain, Cedar Rapids, Iowa, 2015–2017"},{"id":390072,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"},{"id":390068,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5065/sir20215065_appendix.pdf","text":"Poster","size":"3.88 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5065 Appendix","linkHelpText":"— Geophysical methods used to better characterize surface water, alluvial aquifer, and bedrock aquifer interaction in the Cedar River Valley, Iowa"},{"id":390073,"rank":8,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5065/sir20215065.xml","size":"367 kB","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2021–5065 xml"},{"id":390074,"rank":9,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5065/images"}],"country":"United States","state":"Iowa","city":"Cedar Rapids","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.76759719848633,\n 41.99139471889533\n ],\n [\n -91.69189453125,\n 41.99139471889533\n ],\n [\n -91.69189453125,\n 42.03565184193029\n ],\n [\n -91.76759719848633,\n 42.03565184193029\n ],\n [\n -91.76759719848633,\n 41.99139471889533\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240
A U.S. Geological Survey-led assessment of data gaps and science needs across the Great Lakes ecosystem indicated the following:
• Expanded data collection or monitoring would provide basic ecosystem, social, and public health data to manage the Great Lakes system and to develop and test models and decision support tools.
• New science and advanced technologies (for example, sensors and high-performance computing capability) would improve the understanding of critical threats, such as harmful algae blooms and high-water levels.
Although there is significant scientific knowledge in specific areas or for specific topics, managers could use improved models and decision support tools, strengthened by extensive data collection and developed at multiple scales, to better inform decision making in the future. Enhanced coordination of agency efforts and associated data collection across data types (for example, prey fish populations and water levels) is needed to effectively manage the Great Lakes.
This report highlights the data gaps; benefits of better, more structured coordination; and areas of concern specifically related to data collection/measurement and science efforts. It summarizes and analyzes stakeholder feedback and information from review of scientific literature. Finally, the report outlines steps necessary to create an integrated Great Lakes science plan.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211096","usgsCitation":"Carl, L.M., Hortness, J.E., and Strach, R.M., 2021, U.S. Geological Survey Great Lakes Science Forum—Summary of remaining data and science needs and next steps: U.S. Geological Survey Open-File Report 2021–1096, 4 p., https://doi.org/10.3133/ofr20211096.","productDescription":"iii, 4 p.","numberOfPages":"12","onlineOnly":"Y","ipdsId":"IP-133589","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true}],"links":[{"id":390007,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1096/ofr20211096.xml","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2021–1096 xml"},{"id":390006,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1096/ofr20211096.pdf","text":"Report","size":"655 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1096"},{"id":390005,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1096/coverthb.jpg"}],"contact":"Director, Midwest Regional Director’s Office
U.S. Geological Survey
5957 Lakeside Boulevard
Indianapolis, IN 46278
Stocking of Rainbow Trout Oncorhynchus mykiss commonly provides seasonal or mitigation fisheries; however, these fish are usually small and ecosystem effects are spatially or temporally limited. Yet agencies receive requests to stock Rainbow Trout in relatively natural settings (i.e., not tailwater or mitigation fisheries), where introductions may have greater ecosystem consequences. The size of introduced fish is an important factor in determining biotic interactions with native species; therefore, our objectives were to assess the seasonal feeding ecology and microhabitat use of large (265–530 mm TL) nonnative Emmerson strain Rainbow Trout in a relatively unaltered, groundwater-influenced, warmwater stream of the Ozark Highlands. Rainbow Trout consumed a variety of prey; however, diets differed between cool (winter and spring) and warm (summer) seasons. Cool-season Rainbow Trout exhibited a mixed feeding strategy, with individual specialization on crayfishes and fishes and generalist feeding on Ephemeroptera and Diptera, but Gastropoda were the dominant prey. Feeding strategy in the warm season switched to individual specialization on numerous prey types. Overall, larger prey resources were important components of Rainbow Trout diets. Piscivory was relatively high in both seasons, and crayfishes were one of the most important prey types across seasons. Selection of coarse substrates and deeper-water microhabitats (>0.95 m) was similar between seasons. Rainbow Trout selected the lowest-velocity microhabitats available during the warm season and moderate velocities in the cool season. Rainbow Trout were five times more likely to be associated with cover in the warm season. Due to their higher temperature tolerance, Emmerson strain Rainbow Trout may persist in Ozark Highland streams, where they disrupt local food webs and occupy habitat otherwise selected by native fish, such as Neosho Smallmouth Bass Micropterus dolomieu velox. If native species conservation is a priority for agencies, then caution regarding Rainbow Trout stockings may be warranted.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10694","usgsCitation":"Rodger, A.W., Wolf, S.L., Starks, T.A., Burroughs, J.P., and Brewer, S.K., 2021, Seasonal diet and habitat use of large, introduced Rainbow Trout in an Ozark Highland stream: North American Journal of Fisheries Management, v. 41, no. 6, p. 1764-1780, https://doi.org/10.1002/nafm.10694.","productDescription":"17 p.","startPage":"1764","endPage":"1780","ipdsId":"IP-129494","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":397173,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Oklahoma","otherGeospatial":"Spavinaw Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.13336181640625,\n 36.22987352301491\n ],\n [\n -94.37393188476562,\n 36.22987352301491\n ],\n [\n -94.37393188476562,\n 36.46657630040234\n ],\n [\n -95.13336181640625,\n 36.46657630040234\n ],\n [\n -95.13336181640625,\n 36.22987352301491\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Rodger, A. 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P.","contributorId":288619,"corporation":false,"usgs":false,"family":"Burroughs","given":"J.","email":"","middleInitial":"P.","affiliations":[{"id":27443,"text":"Oklahoma Department of Wildlife Conservation","active":true,"usgs":false}],"preferred":false,"id":838138,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":838139,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70229778,"text":"70229778 - 2021 - Livestock grazing, climatic variation, and breeding phenology jointly shape disease dynamics and survival in a wild amphibian","interactions":[],"lastModifiedDate":"2022-03-17T16:05:37.252377","indexId":"70229778","displayToPublicDate":"2021-09-30T10:49:41","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Livestock grazing, climatic variation, and breeding phenology jointly shape disease dynamics and survival in a wild amphibian","docAbstract":"Wildlife responses to infectious disease can be influenced by environmental stressors that alter host-pathogen dynamics. We investigated how livestock grazing, climatic variation, and breeding phenology influence disease prevalence and annual survival in boreal toad (Anaxyrus boreas boreas) populations challenged with Batrachochytrium dendrobatidis (Bd), a fungal pathogen implicated in global amphibian declines. We conducted a five-year (2015–2019) capture-recapture study of boreal toads (n = 1301) inhabiting pastures grazed by cattle in western Wyoming, USA. We employed structural equation models to determine whether the effects of climatic variation on Bd prevalence were direct or mediated through effects on breeding phenology and multi-state models to explore the interplay of grazing, weather, and Bd infection on adult survival. Higher winter snowpack was linked with shorter spring breeding seasons, which were associated with lower Bd prevalence. Boreal toads infected with Bd suffered increased mortality, but only at relatively cool temperatures. Although cattle grazing created warmer microclimates, likely by reducing vegetation cover, grazing-induced habitat changes did not scale up to influence adult survival. Our results suggest that boreal toads in cooler environments face increased risk of disease-induced mortality, possibly because infected individuals are not able to elevate body temperature to reduce or clear infection. More generally, we demonstrate that host-pathogen dynamics can be shaped jointly by independent and interactive effects of livestock grazing, breeding season length, and climatic variation. Future investigations of wildlife responses to disease therefore may benefit from considering anthropogenic land use and climatic regimes, including the effect of weather on host phenology.
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