A numerical groundwater flow model of the Hualapai Valley Basin in northwestern Arizona was developed to assist water-resource managers in understanding the potential effects of projected groundwater withdrawals on groundwater levels in the basin. The Hualapai Valley Hydrologic Model (HVHM) simulates the hydrologic system for the years 1935 through 2219, including future withdrawal scenarios that simulate large-scale agricultural expansion with and without enhanced groundwater recharge from potential new infiltration basin projects. HVHM is a highly parameterized model (75,586 adjustable parameters) capable of simulating grid-scale variability in aquifer properties (for example, conductivity, specific yield, and specific storage) and system stresses (for instance, natural recharge and groundwater withdrawals). Parameter estimation and uncertainty quantification were performed using an iterative ensemble smoother software (PESTPP-IES) to produce an ensemble of models fit to historical data. Results via the future withdrawal scenario from this ensemble indicate that mean groundwater level will decline at wells in the Kingman subbasin 87 to 128 feet by the year 2050 and 204 to 241 feet by the year 2080. Mean groundwater level is expected to decline at wells in the Hualapai subbasin between 44 and 210 feet by 2050 and between 107 and 350 feet by 2080. The enhanced recharge scenario results show potential for these declines to be partially mitigated in the Kingman subbasin by between 8 and 23 feet in 2050 and between 23 and 43 feet in 2080. The enhanced recharge scenario has no simulated effect on groundwater levels in the Hualapai subbasin. All planned enhanced infiltration projects are located in the Kingman subbasin, which is simulated to become hydraulically disconnected from the Hualapai subbasin owing to groundwater-level declines before 2050. Mean depth to water in the Kingman subbasin as simulated in the future withdrawal scenario will exceed 1,200 feet between the years 2155 and 2214 (median year 2171). In the future withdrawal plus enhanced recharge scenario, mean depth to water in the Kingman subbasin exceeds 1,200 feet between the years 2163 and 2207 (median year 2180), except for one model realization in which the subbasin does not reach an mean depth to water of 1,200 feet by the end of forecast simulation (year 2220). Simulated dewatering of the basin margins reduces scenario pumping rates by as much as 7 percent in 2029 and 12 percent in 2079 below specified rates. Forecasts of groundwater-level declines are based on the reduced simulated pumping rates.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215077","collaboration":"Prepared in cooperation with Mohave County and the City of Kingman","usgsCitation":"Knight, J.E., Gungle, B., and Kennedy, J.R., 2021, Assessing potential groundwater-level declines from future withdrawals in the Hualapai Valley, northwestern Arizona: U.S. Geological Survey Scientific Investigations Report, 63 p., https://doi.org/10.3133/sir20215077.","productDescription":"Report: vii, 63 p.; Data Release","numberOfPages":"63","onlineOnly":"Y","ipdsId":"IP-118946","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":436183,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MJRMSQ","text":"USGS data release","linkHelpText":"Repeat microgravity data from the Hualapai Valley, Mohave County, Arizona, 2008-2019"},{"id":389758,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20125275","text":"Scientific Investigations Report 2012-5275","linkHelpText":"— Hydrogeologic framework and estimates of groundwater storage for the Hualapai Valley, Detrital Valley, and Sacramento Valley basins, Mohave County, Arizona"},{"id":389739,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5077/sir20215077.pdf","text":"Report","size":"26 MB"},{"id":389759,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20135122","text":"Scientific Investigations Report 2013-5122","linkHelpText":"— Preliminary groundwater flow model of the basin-fill aquifers in Detrital, Hualapai, and Sacramento Valleys, Mohave County, northwestern Arizona"},{"id":389740,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9017DI9","linkHelpText":"Data release for transient groundwater model of the Hualapai Valley Groundwater Basin, Mohave County, Arizona"},{"id":389738,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5077/covrthb.jpg"},{"id":389756,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20075182","text":"Scientific Investigations Report 2007-5182","linkHelpText":"— Ground-Water Occurrence and Movement, 2006, and Water-Level Changes in the Detrital, Hualapai, and Sacramento Valley Basins, Mohave County, Arizona"},{"id":389757,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20115159","text":"Scientific Investigations Report 2011-5159","linkHelpText":"— Groundwater budgets for Detrital, Hualapai, and Sacramento Valleys, Mohave County, Arizona, 2007-08"}],"country":"United States","state":"Arizona","otherGeospatial":"Hualapai Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.5,\n 36\n ],\n [\n -113.5,\n 36\n ],\n [\n -113.5,\n 35\n ],\n [\n -114.5,\n 35\n ],\n [\n -114.5,\n 36\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
Reproductive strategies are an essential component of invasion ecology that influence invasion success and rates of population growth. Burmese Pythons (Python bivittatus) are large constrictor snakes that were introduced to the Greater Everglades Ecosystem of southern Florida, USA, from Asia. Since their introduction, these giant constrictors have spread throughout wetlands of southern Florida while increasing in abundance and causing declines in the native species upon which they prey. Multiple paternity in reproduction could facilitate invasion success by increasing the genetic diversity produced within each reproductive event. We used Diversity Arrays Technology genome-wide genotyping to assess multiple paternity in the progeny of wild Burmese Pythons in Florida. We analyzed >4,000 single nucleotide polymorphisms from 153 neonates belonging to 4 clutches collected in southwestern Florida. Complementary hierarchical and K-means clustering analyses of the genetic distances within clutches revealed that three clutches were each fertilized by two sires, with a fourth fertilized by a single sire. The proportions of offspring attributable to each sire within multiple paternity clutches ranged from nearly even to highly skewed. Analysis of multivariate dispersion showed significantly increased genetic variability in the multiple paternity clutches. These results improve our understanding of the reproductive strategy and invasion potential of a giant constrictor with significant ecological impacts.
Most studies of the ecological effects of climate change consider only a limited number of weather drivers that could affect populations, though we know that multiple weather drivers can simultaneously affect population growth rate. Multiple drivers could simultaneously increase/decrease one vital rate, or one may increase a vital rate while another decreases the same vital rate. Considering the impact of multiple weather drivers on vital rates is particularly important in a changing climate, in which correlations among drivers may not be preserved in the future. We used a long-term dataset on the endangered red-cockaded woodpecker (Dryobates borealis) to understand how multiple weather drivers jointly affect survival and reproductive vital rates and then assessed the contributions of individual weather drivers to historical trends in vital rates over time. We found that vital rates were often influenced by more than one weather driver and that weather drivers most commonly exerted opposing effects. For instance, some weather drivers increased vital rates over time, while others acted in the opposite direction, decreasing vital rates over time. Importantly, the historical correlations among weather drivers are almost always projected to change in the future climate, such that future trends in vital rates may not match historical trends. For example, we do not find historical trends in adult survival, but changing correlations among weather drivers could generate future trends in this vital rate. Our work provides an example of how multiple weather drivers can control a variety of vital rates and also illustrates how changes in the correlation structure of weather drivers through time might substantially affect future trends in individual and population performance.
Alewife (Alosa pseudoharengus) and blueback herring (Alosa aestivalis) are iteroparous anadromous fish found throughout the East Coast of North America. The phenology of anadromous fish migrations is important for fitness, and the duration of spawning migrations has been compressed in recent years in response to climate change. Anthropogenic barriers to movement, such as dams and culverts at road-stream crossings, can further disrupt migration phenology by delaying movement and increasing predation risk. We used passive integrated transponder (PIT) telemetry to quantify upstream and downstream migratory delay at five road-stream-crossing culverts on the Herring River (MA, USA). Groundspeeds were reduced at all culverts in both directions, confirming that the culverts impede movement despite high passage proportions. The cumulative delay of the culverts on the upstream migration was sufficient to more than double the amount of time required to traverse the river if the culverts had been absent. Furthermore, the presence of snapping turtles (Chelydra serpentina) ambushing river herring within one of the culverts resulted in reduced passage rates beyond the reduction in movement caused by the physical structure itself. This highlights that physical barriers can create cascading ecological consequences and the importance of taking a holistic approach to understanding barrier effects.
Basin-centric long short-term memory (LSTM) network models have recently been shown to be an exceptionally powerful tool for stream temperature (Ts) temporal prediction (training in one period and predicting in another period at the same sites). However, spatial extrapolation is a well-known challenge to modelling Ts and it is uncertain how an LSTM-based daily Ts model will perform in unmonitored or dammed basins. Here we compiled a new benchmark dataset consisting of >400 basins across the contiguous United States in different data availability groups (DAG, meaning the daily sampling frequency) with and without major dams, and studied how to assemble suitable training datasets for predictions in basins with or without temperature monitoring. For prediction in unmonitored basins (PUB), LSTM produced a root-mean-square error (RMSE) of 1.129°C and an R2 of 0.983. While these metrics declined from LSTM's temporal prediction performance, they far surpassed traditional models' PUB values, and were competitive with traditional models' temporal prediction on calibrated sites. Even for unmonitored basins with major reservoirs, we obtained a median RMSE of 1.202°C and an R2 of 0.984. For temporal prediction, the most suitable training set was the matching DAG that the basin could be grouped into (for example, the 60% DAG was most suitable for a basin with 61% data availability). However, for PUB, a training dataset including all basins with data was consistently preferred. An input-selection ensemble moderately mitigated attribute overfitting. Our results indicate there are influential latent processes not sufficiently described by the inputs (e.g., geology, wetland covers), but temporal fluctuations can still be predicted well, and LSTM appears to be a highly accurate Ts modelling tool even for spatial extrapolation.
In regions where water resources are scarce and in high demand, it is important to safeguard against contamination of groundwater aquifers by oil-field fluids (water, gas, oil). In this context, the geochemical characterisation of these fluids is critical so that anthropogenic contaminants can be readily identified. The first step is characterising pre-development geochemical fluid signatures (i.e., those unmodified by hydrocarbon resource development) and understanding how these signatures may have been perturbed by resource production, particularly in the context of enhanced oil recovery (EOR) techniques. Here, we present noble gas isotope data in fluids produced from oil wells in several water-stressed regions in California, USA, where EOR is prevalent. In oil-field systems, only casing gases are typically collected and measured for their noble gas compositions, even when oil and/or water phases are present, due to the relative ease of gas analyses. However, this approach relies on a number of assumptions (e.g., equilibrium between phases, water-to-oil ratio (WOR) and gas-to-oil ratio (GOR) in order to reconstruct the multiphase subsurface compositions. Here, we adopt a novel, more rigorous approach, and measure noble gases in both casing gas and produced fluid (oil-water-gas mixtures) samples from the Lost Hills, Fruitvale, North and South Belridge (San Joaquin Basin, SJB) and Orcutt (Santa Maria Basin) Oil Fields. Using this method, we are able to fully characterise the distribution of noble gases within a multiphase hydrocarbon system. We find that measured concentrations in the casing gases agree with those in the gas phase in the produced fluids and thus the two sample types can be used essentially interchangeably.
EOR signatures can readily be identified by their distinct air-derived noble gas elemental ratios (e.g., 20Ne/36Ar), which are elevated compared to pre-development oil-field fluids, and conspicuously trend towards air values with respect to elemental ratios and overall concentrations. We reconstruct reservoir 20Ne/36Ar values using both casing gas and produced fluids and show that noble gas ratios in the reservoir are strongly correlated (r2 = 0.88–0.98) to the amount of water injected within ~500 m of a well. We suggest that the 20Ne/36Ar increase resulting from injection is sensitive to the volume of fluid interacting with the injectate, the effective water-to-oil ratio, and the composition of the injectate. Defining both the pre-development and injection-modified hydrocarbon reservoir compositions are crucial for distinguishing the sources of hydrocarbons observed in proximal groundwaters, and for quantifying the transport mechanisms controlling this occurrence.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2021.120540","usgsCitation":"Tyne, R.L., Barry, P.H., Karolytė, R., Bryne, D.J., Kulongoski, J.T., Hillegonds, D., and Ballentine, C.J., 2021, Investigating the effect of enhanced oil recovery on the noble gas signature of casing gases and produced waters from selected California oil fields: Chemical Geology, v. 584, 120540, 10 p., https://doi.org/10.1016/j.chemgeo.2021.120540.","productDescription":"120540, 10 p.","ipdsId":"IP-126638","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":450655,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemgeo.2021.120540","text":"Publisher Index Page"},{"id":393752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Kern County","otherGeospatial":"Fruitvale, Lost Hills and North and South Belridge Oil Fields","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.73150634765625,\n 34.4069096565206\n ],\n [\n -119.24011230468749,\n 34.4069096565206\n ],\n [\n -119.24011230468749,\n 35.85566574217861\n ],\n [\n -120.73150634765625,\n 35.85566574217861\n ],\n [\n -120.73150634765625,\n 34.4069096565206\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"584","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tyne, R. L.","contributorId":205891,"corporation":false,"usgs":false,"family":"Tyne","given":"R.","email":"","middleInitial":"L.","affiliations":[{"id":37187,"text":"Department of Earth Sciences, University of Oxford, Oxford, UK","active":true,"usgs":false}],"preferred":false,"id":829842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barry, P. H.","contributorId":270728,"corporation":false,"usgs":false,"family":"Barry","given":"P.","email":"","middleInitial":"H.","affiliations":[{"id":56200,"text":"Dept. of Marine Chem. and Geochem., Woods Hole Oceanographic Institution, Woods Hole, MA, USA","active":true,"usgs":false}],"preferred":false,"id":829843,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Karolytė, R.","contributorId":270729,"corporation":false,"usgs":false,"family":"Karolytė","given":"R.","affiliations":[{"id":56201,"text":"Dept. of Earth Sci., University of Oxford, Oxford, UK","active":true,"usgs":false}],"preferred":false,"id":829844,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bryne, D. J.","contributorId":270730,"corporation":false,"usgs":false,"family":"Bryne","given":"D.","email":"","middleInitial":"J.","affiliations":[{"id":56201,"text":"Dept. of Earth Sci., University of Oxford, Oxford, UK","active":true,"usgs":false}],"preferred":false,"id":829845,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kulongoski, Justin T. 0000-0002-3498-4154 kulongos@usgs.gov","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":173457,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin","email":"kulongos@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":829846,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hillegonds, D.J.","contributorId":205892,"corporation":false,"usgs":false,"family":"Hillegonds","given":"D.J.","email":"","affiliations":[{"id":37187,"text":"Department of Earth Sciences, University of Oxford, Oxford, UK","active":true,"usgs":false}],"preferred":false,"id":829847,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ballentine, C. J.","contributorId":224737,"corporation":false,"usgs":false,"family":"Ballentine","given":"C.","email":"","middleInitial":"J.","affiliations":[{"id":40928,"text":"Oxford University","active":true,"usgs":false}],"preferred":false,"id":829848,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70224530,"text":"70224530 - 2021 - A simplified method for rapid estimation of emergency water supply needs after earthquakes","interactions":[],"lastModifiedDate":"2022-12-23T17:20:52.03908","indexId":"70224530","displayToPublicDate":"2021-09-25T09:53:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"A simplified method for rapid estimation of emergency water supply needs after earthquakes","docAbstract":"Researchers are investigating the problem of estimating households with potable water service outages soon after an earthquake. Most of these modeling approaches are computationally intensive, have large proprietary data collection requirements or lack precision, making them unfeasible for rapid assessment, prioritization, and allocation of emergency water resources in large, complex disasters. This study proposes a new simplified analytical method—performed without proprietary water pipeline data—to estimate water supply needs after earthquakes, and a case study of its application in the HayWired earthquake scenario. In the HayWired scenario—a moment magnitude (Mw) 7.0 Hayward Fault earthquake in the San Francisco Bay Area, California (USA)—an analysis of potable water supply in two water utility districts was performed using the University of Colorado Water Network (CUWNet) model. In the case study, application of the simplified method extends these estimates of household water service outage to the nine counties adjacent to the San Francisco Bay, aggregated by a ~250 m2 (nine-arcsecond) grid. The study estimates about 1.38 million households (3.7 million residents) out of 7.6 million residents (2017, ambient, nighttime population) with potable water service outage soon after the earthquake—about an 8% increase from the HayWired scenario estimates.
","language":"English","publisher":"MDPI","doi":"10.3390/w13192635","usgsCitation":"Toland, J.C., and Wein, A., 2021, A simplified method for rapid estimation of emergency water supply needs after earthquakes: Water, v. 13, 2635, 27 p., https://doi.org/10.3390/w13192635.","productDescription":"2635, 27 p.","ipdsId":"IP-132813","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":450658,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w13192635","text":"Publisher Index Page"},{"id":389813,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.79968261718749,\n 37.24782120155428\n ],\n [\n -121.55273437499999,\n 37.24782120155428\n ],\n [\n -121.55273437499999,\n 38.324420427006544\n ],\n [\n -122.79968261718749,\n 38.324420427006544\n ],\n [\n -122.79968261718749,\n 37.24782120155428\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2021-09-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Toland, Joseph Charles 0000-0002-0092-0320","orcid":"https://orcid.org/0000-0002-0092-0320","contributorId":265976,"corporation":false,"usgs":true,"family":"Toland","given":"Joseph","email":"","middleInitial":"Charles","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":823911,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wein, Anne 0000-0002-5516-3697 awein@usgs.gov","orcid":"https://orcid.org/0000-0002-5516-3697","contributorId":589,"corporation":false,"usgs":true,"family":"Wein","given":"Anne","email":"awein@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":823912,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70252830,"text":"70252830 - 2021 - Age-0 Silver Carp otolith microchemistry and microstructure reveal multiple early life environments and protracted spawning in the upper Mississippi River","interactions":[],"lastModifiedDate":"2024-09-18T15:42:36.007312","indexId":"70252830","displayToPublicDate":"2021-09-25T06:43:02","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":"Age-0 Silver Carp otolith microchemistry and microstructure reveal multiple early life environments and protracted spawning in the upper Mississippi River","docAbstract":"Silver Carp Hypophthalmichthys molitrix are highly mobile and fecund planktivorous cyprinids that have invaded much of the Mississippi River and are known to alter food webs and compete with native planktivores. In 2016, for the first time, an abundance of age-0 Silver Carp (n = 12,208; 16–231 mm) were captured at many (n = 11) sites upstream of Lock and Dam 19 on the upper Mississippi River. Previous reports were of a few individuals at a few locations; however, effort to capture juveniles of this size was likely less in previous years. Determining the origin, frequency, and timing of the reproductive events that led to this large year-class is important for determining control strategies. We used otolith microstructure and microchemistry from age-0 Silver Carp to estimate timing and frequency of spawning and early life environments of these fish. Hatch dates were determined from the lapillus otoliths of 190 age-0 Silver Carp (16–231 mm), and early life environments were identified from otolith microchemistry for 124 of these fish (64–231 mm). Age-0 Silver Carp were collected from Pools 18 and 19 during July–October 2016 by using a variety of sampling gears. We identified 10 cohorts with hatch dates ranging from May to August 2016 and with main-stem Mississippi River (75%) and tributary (23%) early life signatures. Tributary otolith chemistry signatures were present in all cohorts between May and July (n = 8) but were absent from the August cohorts (n = 2). Our results indicate that tributaries and small tributary streams, in addition to the main-stem river, play an important role in Silver Carp recruitment in areas near the reproductive front, where management actions (e.g., contract removal and deterrents) are often targeted.
Nutrients, harmful algal blooms, and synthetic chemicals like per- and polyfluoroalkyl substances (PFAS) and 1,4-dioxane threaten Long Island’s water resources by affecting the quality of drinking water and ecologically sensitive habitats that support the diverse wildlife throughout the island. Understanding the occurrence, fate, and transport of these potentially harmful chemicals is critical to protect these vital resources. The U.S. Geological Survey (USGS) is collecting and analyzing data to support informed water-resource management decisions. This fact sheet introduces ongoing efforts and future areas of study aimed to help water professionals develop a comprehensive science strategy to address contamination of the Long Island aquifer system, the sole source of drinking water for nearly 3 million people. These studies include surface and groundwater collection and groundwater flow modeling. Funding for the data collection has been provided by the USGS, New York State Department of Environmental Conservation, New York City Department of Environmental Protection, Suffolk County Water Authority, Nassau County Department of Public Works, State and local agencies, and Tribal and Federal partners. Without the foresight and long-term commitment of these funding partners, evaluating sustainability and planning for future water needs would not be possible.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20213044","usgsCitation":"Breault, R.F., Masterson, J.P., Schubert, C.E., and Herdman, L.M., 2021, Managing water resources on Long Island, New York, with integrated, multidisciplinary science: U.S. Geological Survey Fact Sheet 2021–3044, 4 p., https://doi.org/10.3133/fs20213044.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-131602","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":389579,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2021/3044/fs20213044.pdf","text":"Report","size":"14.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2021-3044"},{"id":389578,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2021/3044/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Long Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.0478515625,\n 40.538851525354666\n ],\n [\n -73.7677001953125,\n 40.538851525354666\n ],\n [\n -73.1304931640625,\n 40.60561205826018\n ],\n [\n -72.5537109375,\n 40.76806170936614\n ],\n [\n -71.9549560546875,\n 40.97575093157534\n ],\n [\n -71.83959960937499,\n 41.10832999732831\n ],\n [\n -72.1417236328125,\n 41.24064190269475\n ],\n [\n -72.8338623046875,\n 41.10005163093046\n ],\n [\n -73.5205078125,\n 40.96330795307353\n ],\n [\n -73.883056640625,\n 40.83043687764923\n ],\n [\n -74.06982421875,\n 40.713955826286046\n ],\n [\n -74.0863037109375,\n 40.61812224225511\n ],\n [\n -74.0478515625,\n 40.538851525354666\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
The Columbia River Gorge is the Columbia River’s long-held yet evolving passage through the volcanic arc of the Cascade Range. The globally unique setting of a continental-scale river bisecting an active volcanic arc at the leading edge of a major plate boundary creates a remarkable setting where dynamic volcanic and tectonic processes interact with diverse and energetic fluvial processes. This three-day field trip explores several elements of the gorge and its remarkable geologic history—cast here as a contest between regional tectonic and volcanic processes building and displacing landscapes, and the relentless power of the Columbia River striving to maintain a smooth passage to the sea.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"From terranes to terrains: Geologic field guides on the construction and destruction of the Pacific Northwest","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2021.0062(05)","usgsCitation":"O'Connor, J., Wells, R., Bennett, S.E., Cannon, C.M., Staisch, L.M., Anderson, J.L., Pivarunas, A.F., Gordon, G.W., Blakely, R.J., Stelten, M.E., and Evarts, R.C., 2021, Arc versus river: The geology of the Columbia River Gorge, chap. of From terranes to terrains: Geologic field guides on the construction and destruction of the Pacific Northwest, v. 62, p. 131-186, https://doi.org/10.1130/2021.0062(05).","productDescription":"56 p.","startPage":"131","endPage":"186","ipdsId":"IP-130012","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science 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Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":884307,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wells, Ray 0000-0002-7796-0160","orcid":"https://orcid.org/0000-0002-7796-0160","contributorId":204016,"corporation":false,"usgs":true,"family":"Wells","given":"Ray","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":884308,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bennett, Scott E.K. 0000-0002-9772-4122 sekbennett@usgs.gov","orcid":"https://orcid.org/0000-0002-9772-4122","contributorId":5340,"corporation":false,"usgs":true,"family":"Bennett","given":"Scott","email":"sekbennett@usgs.gov","middleInitial":"E.K.","affiliations":[{"id":300,"text":"Geologic Hazards Science 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0000-0002-0003-2059","orcid":"https://orcid.org/0000-0002-0003-2059","contributorId":301014,"corporation":false,"usgs":true,"family":"Pivarunas","given":"Anthony","email":"","middleInitial":"Francis","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":884313,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gordon, Gabriel Wells 0000-0003-0937-6250 ggordon@usgs.gov","orcid":"https://orcid.org/0000-0003-0937-6250","contributorId":330200,"corporation":false,"usgs":true,"family":"Gordon","given":"Gabriel","email":"ggordon@usgs.gov","middleInitial":"Wells","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":884314,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Blakely, Richard J. 0000-0003-1701-5236 blakely@usgs.gov","orcid":"https://orcid.org/0000-0003-1701-5236","contributorId":1540,"corporation":false,"usgs":true,"family":"Blakely","given":"Richard","email":"blakely@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":884315,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Stelten, Mark E. 0000-0002-5294-3161 mstelten@usgs.gov","orcid":"https://orcid.org/0000-0002-5294-3161","contributorId":145923,"corporation":false,"usgs":true,"family":"Stelten","given":"Mark","email":"mstelten@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":884316,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Evarts, Russell C. 0000-0001-5103-9085 revarts@usgs.gov","orcid":"https://orcid.org/0000-0001-5103-9085","contributorId":295784,"corporation":false,"usgs":true,"family":"Evarts","given":"Russell","email":"revarts@usgs.gov","middleInitial":"C.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":884317,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70211246,"text":"70211246 - 2021 - Paleozoic and Mesozoic tectonic events west of the Waterbury Dome: Results of new mapping in the western Connecticut Highlands","interactions":[],"lastModifiedDate":"2022-04-19T16:09:25.677111","indexId":"70211246","displayToPublicDate":"2021-09-24T11:01:40","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Paleozoic and Mesozoic tectonic events west of the Waterbury Dome: Results of new mapping in the western Connecticut Highlands","docAbstract":"This field trip highlights the results of recent U.S. Geological Survey (USGS) bedrock geologic mapping in four 7.5 min quadrangles in the western Connecticut highlands near Southbury, Connecticut, USA. The rocks are broadly within what Rodgers (1985) called the Hartland and Gneiss Dome belts of the Connecticut Valley Synclinorium (Rodgers, 1985; Fig. 1), the latter of which is now known as the Connecticut Valley–Gaspe Trough (Hibbard et al., 2006). The mapping occurred over two intervals: 2003–2005 and 2016–present. In the first, the goal was a detailed map of the early Mesozoic Pomperaug basin, which overlaps the four quadrangles. Portions of the basin had been separately mapped during the statewide 7.5 min quadrangle mapping campaign spanning the 1950s–1970s, resulting in an inaccurate depiction of the basin on the 1985 state geologic map (Rodgers, 1985). A new map of the basin was proposed in part to benefit an ongoing project by the USGS Connecticut Water Science Center to determine the contributions of natural and artificial contaminants to a public water-supply well in Woodbury, Connecticut, under the National Water-Quality Assessment (NAWQA) Program (Starn and Brown, 2007). The NAWQA project was partially funded by the Pomperaug River Watershed Coalition, which also provided logistical support to the geologic mapping project. Mapping of the basin was also a high priority for the Connecticut State Geologist at the time (Ralph Lewis, 2002, pers. comm.). The mapping resulted in an NEIGC (New England Intercollegiate Geologic Conference) field guide (Burton et al., 2005) and a 1:12,000-scale USGS open-file map (Burton, 2006) and was funded by the USGS National Cooperative Geologic Mapping Program (NCGMP).
The second phase of the mapping began in 2016 after the discovery of elevated levels of uranium and arsenic in domestic water wells in the igneous and metamorphic rocks that surround the sedimentary and volcanic rocks of the Pomperaug basin (Flanagan and Brown, 2017). Structural measurements in the surrounding crystalline rocks were made during Pomperaug basin mapping to better understand the tectonic setting, but a revision of the crystalline map units on Rodgers’ 1985 geologic map was not attempted. Nonetheless, discrepancies were noted between the new mapping and the 1985 map, particularly within the two northern quadrangles of Woodbury and Roxbury, which were originally mapped by Gates (1954) and Gates (1959), respectively. Based on these discrepancies, a new NCGMP project was proposed to remap the Woodbury and Roxbury 7.5 min quadrangles, commencing in the fall of 2016. The expected USGS product will be a two-quadrangle, 1:24,000-scale Scientific Investigations Map (SIM).
This field guide is not meant as a comprehensive review of all of the geologic research done in this area of Connecticut; rather, it looks at previous bedrock geologic mapping from the perspective of new and recent mapping in the four-quadrangle area and discusses the structural, stratigraphic, and nomenclatural revisions necessary for the next revision of the state geologic map.
Raikoke, a small, unmonitored volcano in the Kuril Islands, erupted in June 2019. We integrate data from satellites (including Sentinel-2, TROPOMI, MODIS, Himawari-8), the International Monitoring System (IMS) infrasound network, and global lightning detection network (GLD360) with information from local authorities and social media to retrospectively characterize the eruptive sequence and improve understanding of the pre-, syn- and post- eruptive behavior. We observe six infrasound pulses beginning on 21 June at 17:49:55 UTC as well as the main Plinian phase on 21 June at 22:29 UTC. Each pulse is tracked in space and time using lightning and satellite imagery as the plumes drift eastward. Post-eruption visible satellite imagery shows expansion of the island's surface area, an increase in crater size, and a possibly-linked algal bloom south of the island. We use thermal satellite imagery and plume modeling to estimate plume height at 10–12 km asl and 1.5–2 × 106 kg/s mass eruption rate. Remote infrasound data provide insight into syn-eruptive changes in eruption intensity. Our analysis illustrates the value of interdisciplinary analyses of remote data to illuminate eruptive processes. However, our inability to identify deformation, pre-eruptive outgassing, and thermal signals, which may reflect the relatively short duration (~12 h) of the eruption and minimal land area around the volcano and/or the character of closed-system eruptions, highlights current limitations in the application of remote sensing for eruption detection and characterization.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2021.107354","usgsCitation":"McKee, K., Smith, C.M., Reath, K., Snee, E., Maher, S., Matoza, R.S., Carn, S.A., Mastin, L.G., Anderson, K.R., Damby, D., Roman, D., Degterev, A., Rybin, A., Chibisova, M., Assink, J.D., de Negri Levia, R., and Perttu, A., 2021, Evaluating the state-of-the-art in remote volcanic eruption characterization Part I: Raikoke volcano, Kuril Islands: Journal of Volcanology and Geothermal Research, v. 419, p. 1-14, https://doi.org/10.1016/j.jvolgeores.2021.107354.","productDescription":"107354, 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-131053","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":450671,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2021.107354","text":"Publisher Index Page"},{"id":389731,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Japan, Russia","state":"Hokkaido, Sakhalin Oblast","otherGeospatial":"Kuril Islands, Raikoke Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -206.73900604248047,\n 48.283078663405014\n ],\n [\n -206.7290496826172,\n 48.291531147204644\n ],\n [\n -206.73248291015625,\n 48.29963964777105\n ],\n [\n -206.74072265625,\n 48.30226606899445\n ],\n [\n -206.7620086669922,\n 48.30215187957729\n ],\n [\n -206.76630020141602,\n 48.29872607827854\n ],\n [\n -206.7688751220703,\n 48.292901688435585\n ],\n [\n -206.7688751220703,\n 48.29107429195301\n ],\n [\n -206.7614936828613,\n 48.28364982124273\n ],\n [\n -206.75445556640625,\n 48.28227903170258\n ],\n [\n -206.73900604248047,\n 48.283078663405014\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"419","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McKee, Kathleen 0000-0003-3189-9189","orcid":"https://orcid.org/0000-0003-3189-9189","contributorId":265977,"corporation":false,"usgs":false,"family":"McKee","given":"Kathleen","email":"","affiliations":[{"id":54848,"text":"Earth and Planets Laboratory, Carnegie Institution for Science, Washington, DC, USA","active":true,"usgs":false}],"preferred":false,"id":823913,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Cassandra Marie 0000-0003-2653-4249 cassandrasmith@usgs.gov","orcid":"https://orcid.org/0000-0003-2653-4249","contributorId":257000,"corporation":false,"usgs":true,"family":"Smith","given":"Cassandra","email":"cassandrasmith@usgs.gov","middleInitial":"Marie","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":823914,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reath, Kevin","contributorId":194091,"corporation":false,"usgs":false,"family":"Reath","given":"Kevin","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":823915,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Snee, Eveanjelene 0000-0002-3660-4020","orcid":"https://orcid.org/0000-0002-3660-4020","contributorId":265978,"corporation":false,"usgs":false,"family":"Snee","given":"Eveanjelene","email":"","affiliations":[{"id":54849,"text":"School of Earth and Ocean Sciences, Cardiff University, Cardiff, Wales, UK","active":true,"usgs":false}],"preferred":false,"id":823916,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maher, Sean","contributorId":265979,"corporation":false,"usgs":false,"family":"Maher","given":"Sean","affiliations":[{"id":54850,"text":"Department of Earth Science and Earth Research Institute, University of California, Santa Barbara, Santa Barbara, CA, USA","active":true,"usgs":false}],"preferred":false,"id":823917,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Matoza, Robin S.","contributorId":257265,"corporation":false,"usgs":false,"family":"Matoza","given":"Robin","email":"","middleInitial":"S.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":823918,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Carn, Simon A","contributorId":191165,"corporation":false,"usgs":false,"family":"Carn","given":"Simon","email":"","middleInitial":"A","affiliations":[],"preferred":false,"id":823919,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mastin, Larry G. 0000-0002-4795-1992 lgmastin@usgs.gov","orcid":"https://orcid.org/0000-0002-4795-1992","contributorId":555,"corporation":false,"usgs":true,"family":"Mastin","given":"Larry","email":"lgmastin@usgs.gov","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science 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Diana","contributorId":237832,"corporation":false,"usgs":false,"family":"Roman","given":"Diana","affiliations":[{"id":47620,"text":"Dept. of Terrestrial Magnetism, Carnegie Institution for Science, Washington DC 20015","active":true,"usgs":false}],"preferred":false,"id":823923,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Degterev, Artem 0000-0001-6284-8830","orcid":"https://orcid.org/0000-0001-6284-8830","contributorId":265980,"corporation":false,"usgs":false,"family":"Degterev","given":"Artem","email":"","affiliations":[{"id":54851,"text":"Sakhalin Volcanic Eruptions Response Team (SVERT), Institute of Marine Geology and Geophysics, Yuzhno-Sakhalinsk, Russia","active":true,"usgs":false}],"preferred":false,"id":823924,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rybin, Alexander 0000-0002-7734-0172","orcid":"https://orcid.org/0000-0002-7734-0172","contributorId":265981,"corporation":false,"usgs":false,"family":"Rybin","given":"Alexander","email":"","affiliations":[{"id":54851,"text":"Sakhalin Volcanic Eruptions Response Team (SVERT), Institute of Marine Geology and Geophysics, Yuzhno-Sakhalinsk, Russia","active":true,"usgs":false}],"preferred":false,"id":823925,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Chibisova, Marina 0000-0003-0677-6945","orcid":"https://orcid.org/0000-0003-0677-6945","contributorId":265982,"corporation":false,"usgs":false,"family":"Chibisova","given":"Marina","email":"","affiliations":[{"id":54851,"text":"Sakhalin Volcanic Eruptions Response Team (SVERT), Institute of Marine Geology and Geophysics, Yuzhno-Sakhalinsk, Russia","active":true,"usgs":false}],"preferred":false,"id":823926,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Assink, Jelle D.","contributorId":236650,"corporation":false,"usgs":false,"family":"Assink","given":"Jelle","email":"","middleInitial":"D.","affiliations":[{"id":47493,"text":"R and D Seismology and Acoustics, Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3731 GA De Bilt, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":823927,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"de Negri Levia, Rodrigo 0000-0003-1283-2579","orcid":"https://orcid.org/0000-0003-1283-2579","contributorId":265983,"corporation":false,"usgs":false,"family":"de Negri Levia","given":"Rodrigo","email":"","affiliations":[{"id":54852,"text":"Department of Earth Science and Earth Research Institute, University of California, Santa Barbara, Santa Barbara, CA, USA; NDC-CTBT of the Chilean Nuclear Energy Commission, Chile","active":true,"usgs":false}],"preferred":false,"id":823928,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Perttu, Anna 0000-0003-3590-1549","orcid":"https://orcid.org/0000-0003-3590-1549","contributorId":265984,"corporation":false,"usgs":false,"family":"Perttu","given":"Anna","email":"","affiliations":[{"id":48937,"text":"Earth Observatory of Singapore, Nanyang Technological University, Singapore","active":true,"usgs":false}],"preferred":false,"id":823929,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70223871,"text":"sir20215015 - 2021 - Methods for estimating regional skewness of annual peak flows in parts of eastern New York and Pennsylvania, based on data through water year 2013","interactions":[],"lastModifiedDate":"2021-09-27T12:03:37.39516","indexId":"sir20215015","displayToPublicDate":"2021-09-24T09:50:00","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":"2021-5015","displayTitle":"Methods for Estimating Regional Skewness of Annual Peak Flows in Parts of Eastern New York and Pennsylvania, Based on Data Through Water Year 2013","title":"Methods for estimating regional skewness of annual peak flows in parts of eastern New York and Pennsylvania, based on data through water year 2013","docAbstract":"Bulletin 17C (B17C) recommends fitting the log-Pearson Type III (LP−III) distribution to a series of annual peak flows at a streamgage by using the method of moments. The third moment, the skewness coefficient (or skew), is important because the magnitudes of annual exceedance probability (AEP) flows estimated by using the LP–III distribution are affected by the skew; interest is focused on the right-hand tail of the distribution, which represents the larger annual peak flows that correspond to small AEPs. For streamgages having modest record lengths, the skew is sensitive to extreme events like large floods, which cause a sample to be highly asymmetrical or “skewed.” For this reason, B17C recommends using a weighted-average skew computed from the skew of the annual peak flows for a given streamgage and a regional skew. This report presents an estimate of regional skew for a study area encompassing parts of eastern New York and Pennsylvania. A total of 232 candidate U.S. Geological Survey streamgages that were unaffected by extensive regulation, diversion, urbanization, or channelization were considered for use in the skew analysis; after screening for redundancy and pseudo record length (PRL) of at least 36 years, 183 streamgages were selected for use in the study.
Flood frequencies for candidate streamgages were analyzed by employing the expected moments algorithm, which extends the method of moments so that it can accommodate interval, censored, and historical/paleo flow data, as well as the multiple Grubbs-Beck test to identify potentially influential low floods in the data series. Bayesian weighted least squares/Bayesian generalized least squares regression was used to develop a regional skew model for the study area that would incorporate possible variables (basin characteristics) to explain the variation in skew in the study area. Ten basin characteristics were considered as possible explanatory variables; however, none produced a pseudo coefficient of determination greater than 1 percent; as a result, these characteristics did not help to explain the variation in skew in the study area. Therefore, a constant model that had a regional skew coefficient of 0.32 and an average variance of prediction at a new streamgage (AVPnew, which corresponds to the mean square error [MSE] of 0.11) was selected. The AVPnew corresponds to an effective record length of 68 years, a marked improvement over the Bulletin 17B national skew map, whose reported MSE of 0.302 indicated a corresponding effective record length of only 17 years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215015","usgsCitation":"Veilleux, A.G., and Wagner, D.M., 2021, Methods for estimating regional skewness of annual peak flows in parts of eastern New York and Pennsylvania, based on data through water year 2013: U.S. Geological Survey Scientific Investigations Report 2021–5015, 38 p., https://doi.org/10.3133/sir20215015.","productDescription":"Report: vi, 38 p.; Data Release","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-114558","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":389079,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5015/coverthb.jpg"},{"id":389080,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5015/sir20215015.pdf","text":"Report","size":"6.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5015"},{"id":389081,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PGAL0D","text":"USGS data release","linkHelpText":"Regional flood skew for parts of the mid-Atlantic region (hydrologic unit 02) in eastern New York and Pennsylvania"}],"country":"United States","state":"New York, Pennsylvania","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.56396484375,\n 39.740986355883564\n ],\n [\n -75.03662109375,\n 40.04443758460856\n ],\n [\n -74.86083984375,\n 40.34654412118006\n ],\n [\n -75.16845703124999,\n 40.713955826286046\n ],\n [\n -74.970703125,\n 41.062786068733026\n ],\n [\n -74.619140625,\n 41.393294288784865\n ],\n [\n -74.1796875,\n 41.65649719441145\n ],\n [\n -73.54248046875,\n 42.17968819665961\n ],\n [\n -73.23486328124999,\n 43.02071359427862\n ],\n [\n -73.32275390625,\n 43.628123412124616\n ],\n [\n -73.45458984375,\n 43.77109381775651\n ],\n [\n -73.80615234375,\n 43.35713822211053\n ],\n [\n -74.28955078125,\n 43.14909399920127\n ],\n [\n -74.77294921875,\n 42.79540065303723\n ],\n [\n -75.34423828125,\n 42.73087427928485\n ],\n [\n -75.82763671875,\n 42.68243539838623\n ],\n [\n -76.35498046875,\n 42.68243539838623\n ],\n [\n -76.88232421875,\n 42.68243539838623\n ],\n [\n -77.23388671874999,\n 42.45588764197166\n ],\n [\n -77.607421875,\n 42.19596877629178\n ],\n [\n -77.607421875,\n 42.01665183556825\n ],\n [\n -77.6513671875,\n 41.409775832009565\n ],\n [\n -77.80517578125,\n 41.1290213474951\n ],\n [\n -77.9150390625,\n 40.53050177574321\n ],\n [\n -78.11279296875,\n 40.16208338164617\n ],\n [\n -78.46435546875,\n 39.67337039176558\n ],\n [\n -75.56396484375,\n 39.740986355883564\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Integrated Modeling and Prediction Division
Water Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Freshwater mussels are one of the most imperiled groups of animals in the world and are among the most sensitive species to a variety of chemicals. However, little is known about the sensitivity of freshwater mussels to wastewater effluents. The objectives of the present study were to (1) assess the toxicity of a permitted effluent, which entered the Deep Fork River, Oklahoma (USA), to a unionid mussel (Lampsilis siliquoidea) and to two standard test species (cladoceran Ceriodaphnia dubia; and fathead minnow Pimephales promelas) in short-term 7-day effluent tests; (2) evaluate the relative sensitivities of the three species to potassium (K), an elevated major ion in the effluent, using 7-day toxicity tests with KCl spiked into a Deep Fork River upstream reference water; (3) determine the potential influences of background water characteristics on the acute K toxicity to the mussel (96-h exposures) and cladoceran (48-h exposure) in four reconstituted waters that mimicked the hardness and ionic composition ranges of the Deep Fork River; and (4) determine the potential influence of temperature on acute K toxicity to the mussel. The effluent was found to be toxic to mussels and cladocerans, and it contained elevated concentrations of major cations and anions relative to the upstream Deep Fork River reference water. The K concentration in the effluent was 48-fold greater than in the upstream water. Compared with the standard species, the mussel was more than 4-fold more sensitive to the effluent in the 7-day effluent tests and more than 8-fold more sensitive to K in the 7-day K toxicity tests. The acute K toxicity to the mussel decreased by a factor of 2 when the water hardness was increased from soft (42 mg/L as CaCO3) to very hard (314 mg/L as CaCO3), whereas the acute K toxicity to the cladoceran remained almost the same as hardness increased from 84 to 307 mg/L as CaCO3. Acute K toxicity to the mussel at 23 °C was similar to the toxicity at an elevated temperature of 28 °C. The overall results indicate that the two standard test species may not represent the sensitivity of the tested mussel to both the effluent and K, and the toxicity of K was influenced by the hardness in test waters, but by a limited magnitude.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry (SETAC)","doi":"10.1002/etc.5221","usgsCitation":"Kunz, J.L., Wang, N., Martinez, D., Dunn, S., Cleveland, D.M., and Steevens, J.A., 2021, The sensitivity of a unionid mussel (Lampsilis siliquoidea) to a permitted effluent and elevated potassium in the effluent: Environmental Toxicology and Chemistry, v. 40, no. 12, p. 3410-3420, https://doi.org/10.1002/etc.5221.","productDescription":"11 p.","startPage":"3410","endPage":"3420","ipdsId":"IP-129678","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":436187,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92YZGDX","text":"USGS data release","linkHelpText":"Chemical and biological data from a study on sensitivity of a unionid mussel (Lampsilis siliquoidea) to a permitted effluent and elevated potassium"},{"id":396104,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","city":"Okmulgee","otherGeospatial":"Deep Fork National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.60827636718749,\n 35.546753306701\n ],\n [\n -95.92849731445312,\n 35.546753306701\n ],\n [\n -95.92849731445312,\n 35.69968630125204\n ],\n [\n -96.60827636718749,\n 35.69968630125204\n ],\n [\n -96.60827636718749,\n 35.546753306701\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"12","noUsgsAuthors":false,"publicationDate":"2021-09-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Kunz, James L. 0000-0002-1027-158X jkunz@usgs.gov","orcid":"https://orcid.org/0000-0002-1027-158X","contributorId":3309,"corporation":false,"usgs":true,"family":"Kunz","given":"James","email":"jkunz@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":835189,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wang, Ning 0000-0002-2846-3352 nwang@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-3352","contributorId":2818,"corporation":false,"usgs":true,"family":"Wang","given":"Ning","email":"nwang@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":835190,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martinez, David","contributorId":279598,"corporation":false,"usgs":false,"family":"Martinez","given":"David","email":"","affiliations":[{"id":57309,"text":"US Fish Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":835191,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunn, Suzanne","contributorId":279599,"corporation":false,"usgs":false,"family":"Dunn","given":"Suzanne","email":"","affiliations":[{"id":57309,"text":"US Fish Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":835192,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cleveland, Danielle M. 0000-0003-3880-4584 dcleveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3880-4584","contributorId":187471,"corporation":false,"usgs":true,"family":"Cleveland","given":"Danielle","email":"dcleveland@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":835193,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Steevens, Jeffery A. 0000-0003-3946-1229","orcid":"https://orcid.org/0000-0003-3946-1229","contributorId":207511,"corporation":false,"usgs":true,"family":"Steevens","given":"Jeffery","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":835194,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70224533,"text":"70224533 - 2021 - Multidisciplinary constraints on magma compressibility, the pre-eruptive exsolved volatile fraction, and the H2O/CO2 molar ratio for the 2006 Augustine eruption, Alaska","interactions":[],"lastModifiedDate":"2021-09-24T15:09:47.418896","indexId":"70224533","displayToPublicDate":"2021-09-24T09:41:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9358,"text":"Geochemistry, Geophysics, Geosystems (G-Cubed)","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Multidisciplinary constraints on magma compressibility, the pre-eruptive exsolved volatile fraction, and the H2O/CO2 molar ratio for the 2006 Augustine eruption, Alaska","title":"Multidisciplinary constraints on magma compressibility, the pre-eruptive exsolved volatile fraction, and the H2O/CO2 molar ratio for the 2006 Augustine eruption, Alaska","docAbstract":"Geodetically modeled reservoir volume changes during volcanic eruptions are commonly much smaller than the observed eruptive volumes. This discrepancy is thought to be partially due to the compressibility of magma, which is largely controlled by the presence of exsolved volatiles. The 2006 eruption of Augustine Volcano, Alaska, produced an eruptive volume that was ∼3 times larger than the geodetically estimated syn-eruptive subsurface volume change. In this study, we use a multistep methodology that combines constraints from geodetic, volcanic gas, geologic, and petrologic data together with equations relating physical processes to observable parameters. We apply a Monte Carlo approach to quantify uncertainties. Ultimately, we solve for the exsolved volatile volume fraction and the magma compressibility. We estimate Augustine's 2006 pre-eruptive exsolved volatile phase to be ∼5.5 vol% of the magma at storage depths, yielding a bulk magma compressibility of ∼3.8 × 10−10 Pa−1. We develop a novel approach to estimate the H2O/CO2 ratio of the syn-eruptive gas emissions in the absence of direct H2O emission measurements which are hard to obtain due to the high background levels in ambient air. We find a best-fit H2O/CO2 molar ratio of 29. We also investigate the effects of applying different equations of state to our model. We find that the Ideal Gas Law might be used as a first approximation due to its simplicity; however, it overestimates volatile density and compressibility significantly at storage depths. This project capitalizes on the insights that can be gained by integrating multidisciplinary data with models of physical processes.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021GC009911","usgsCitation":"Wasser, V.K., Lopez, T., Anderson, K.R., Izbekov, P.E., and Freymueller, J., 2021, Multidisciplinary constraints on magma compressibility, the pre-eruptive exsolved volatile fraction, and the H2O/CO2 molar ratio for the 2006 Augustine eruption, Alaska: Geochemistry, Geophysics, Geosystems (G-Cubed), v. 22, no. 9, p. 1-24, https://doi.org/10.1029/2021GC009911.","productDescription":"e2021GC009911, 24 p.","startPage":"1","endPage":"24","ipdsId":"IP-116941","costCenters":[{"id":153,"text":"California Volcano Observatory","active":false,"usgs":true}],"links":[{"id":489770,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021gc009911","text":"Publisher Index Page"},{"id":389721,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Augustine Volcano, Cook Inlet","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -153.38150024414062,\n 59.404209722248545\n ],\n [\n -153.38356018066406,\n 59.411198752750096\n ],\n [\n -153.4295654296875,\n 59.417836996163324\n ],\n [\n -153.46939086914062,\n 59.40840331358838\n ],\n [\n -153.47488403320312,\n 59.39966607911177\n ],\n [\n -153.51470947265625,\n 59.395471406154286\n ],\n [\n -153.52500915527344,\n 59.38987770116238\n ],\n [\n -153.5504150390625,\n 59.39652012307085\n ],\n [\n -153.56483459472653,\n 59.39337387496283\n ],\n [\n -153.57650756835938,\n 59.38218484937568\n ],\n [\n -153.58200073242188,\n 59.37379065648717\n ],\n [\n -153.577880859375,\n 59.36924293446236\n ],\n [\n -153.55934143066406,\n 59.36644403325385\n ],\n [\n -153.5504150390625,\n 59.345795005122895\n ],\n [\n -153.55865478515625,\n 59.33564087770051\n ],\n [\n -153.5504150390625,\n 59.32968704671643\n ],\n [\n -153.52157592773438,\n 59.3167251017617\n ],\n [\n -153.42613220214844,\n 59.32443279994899\n ],\n [\n -153.41720581054688,\n 59.32022881759866\n ],\n [\n -153.39797973632812,\n 59.32583401185328\n ],\n [\n -153.358154296875,\n 59.33669144545403\n ],\n [\n -153.336181640625,\n 59.35734600959442\n ],\n [\n -153.34304809570312,\n 59.380785961506966\n ],\n [\n -153.37051391601562,\n 59.39092659116679\n ],\n [\n -153.38150024414062,\n 59.404209722248545\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","issue":"9","noUsgsAuthors":false,"publicationDate":"2021-09-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Wasser, Valerie K.","contributorId":265989,"corporation":false,"usgs":false,"family":"Wasser","given":"Valerie","email":"","middleInitial":"K.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":823947,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lopez, Taryn M.","contributorId":265990,"corporation":false,"usgs":false,"family":"Lopez","given":"Taryn M.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":823948,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Kyle R. 0000-0001-8041-3996 kranderson@usgs.gov","orcid":"https://orcid.org/0000-0001-8041-3996","contributorId":3522,"corporation":false,"usgs":true,"family":"Anderson","given":"Kyle","email":"kranderson@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":823949,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Izbekov, Pavel E.","contributorId":265991,"corporation":false,"usgs":false,"family":"Izbekov","given":"Pavel","email":"","middleInitial":"E.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":823950,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Freymueller, Jeffrey T.","contributorId":96841,"corporation":false,"usgs":false,"family":"Freymueller","given":"Jeffrey T.","affiliations":[{"id":26875,"text":"Michigan State University, East Lansing, MI","active":true,"usgs":false}],"preferred":false,"id":823951,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70262512,"text":"70262512 - 2021 - Upper Grand Coulee: New views of a channeled scabland megafloods enigma","interactions":[],"lastModifiedDate":"2025-01-17T15:29:50.650525","indexId":"70262512","displayToPublicDate":"2021-09-24T09:21:11","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Upper Grand Coulee: New views of a channeled scabland megafloods enigma","docAbstract":"New findings about old puzzles occasion rethinking of the Grand Coulee, greatest of the scabland channels. Those puzzles begin with antecedents of current upper Grand Coulee. By a recent interpretation, the upper coulee exploited the former high-level valley of a preflood trunk stream that had drained to the southwest beside and across Coulee anticline or monocline. In any case, a constriction and sharp bend in nearby Columbia valley steered Missoula floods this direction. Completion of upper Grand Coulee by megaflood erosion captured flood drainage that would otherwise have continued to enlarge Moses Coulee.
Upstream in the Sanpoil valley, deposits and shorelines of last-glacial Lake Columbia varied with the lake’s Grand Coulee outlet while also recording scores of Missoula floods. The Sanpoil evidence implies that upper Grand Coulee had approached its present intake depth early the last glaciation at latest, or more simply during a prior glaciation. An upper part of the Sanpoil section provides varve counts between the last tens of Missoula floods in a stratigraphic sequence that may now be linked to flood rhythmites of southern Washington by a set-S tephra from Mount St. Helens.
On the floor of upper Grand Coulee itself, recently found striated rock and lodgement till confirm the long-held view, which Bretz and Flint had shared, that cutting of upper Grand Coulee preceded its last-glacial occupation by the Okanogan ice lobe. A dozen or more late Missoula floods registered as sand and silt in the lee of Steamboat Rock.
Some of this field evidence about upper Grand Coulee may conflict with results of recent two-dimensional simulations for a maximum Lake Missoula. In these simulations only a barrier high above the present coulee intake enables floods to approach high-water marks near Wenatchee that predate stable blockage of Columbia valley by the Okanogan lobe. Above the walls of upper Grand Coulee, scabland limits provide high-water targets for two-dimensional simulations of watery floods. The recent models sharpen focus on water sources, prior coulee incision, and coulee’s occupation by the Okanogan ice lobe.
Field reappraisal continues downstream from Grand Coulee on Ephrata fan. There, some of the floods exiting lower Grand Coulee had bulked up with fine sediment from glacial Lake Columbia, upper coulee till, and a lower coulee lake that the fan itself impounded. Floods thus of debris-flow consistency carried outsize boulders previously thought transported by watery floods.
Below Ephrata fan, a backflooded reach of Columbia valley received Grand Coulee outflow of small, late Missoula floods. These late floods can—by varve counts in post-S-ash deposits of Sanpoil valley—be clocked now as a decade or less apart. Still farther downstream, Columbia River gorge choked the largest Missoula floods, passing peak discharge only one-third to one-half that released by the breached Lake Missoula ice dam.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"From terranes to terrains: Geologic field guides on the construction and destruction of the Pacific Northwest","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2021.0062(07)","usgsCitation":"Waitt, R.B., Atwater, B., Lehnigk, K., Larsen, I., Bjornstad, B., Hanson, M., and O'Connor, J., 2021, Upper Grand Coulee: New views of a channeled scabland megafloods enigma, chap. of From terranes to terrains: Geologic field guides on the construction and destruction of the Pacific Northwest, v. 62, p. 245-300, https://doi.org/10.1130/2021.0062(07).","productDescription":"56 p.","startPage":"245","endPage":"300","ipdsId":"IP-129810","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":481101,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/2021.0062(07)","text":"Publisher Index Page"},{"id":480733,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","otherGeospatial":"Upper Grand Coulee","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.50054736602212,\n 49.462558518080414\n ],\n [\n -125.44572643872874,\n 49.462558518080414\n ],\n [\n -125.44572643872874,\n 44.60810790414203\n ],\n [\n -117.50054736602212,\n 44.60810790414203\n ],\n [\n -117.50054736602212,\n 49.462558518080414\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"62","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Waitt, Richard B. 0000-0002-6392-5604 waitt@usgs.gov","orcid":"https://orcid.org/0000-0002-6392-5604","contributorId":2343,"corporation":false,"usgs":true,"family":"Waitt","given":"Richard","email":"waitt@usgs.gov","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":924412,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Atwater, Brian F.","contributorId":349552,"corporation":false,"usgs":true,"family":"Atwater","given":"Brian F.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":924413,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lehnigk, Karin","contributorId":349556,"corporation":false,"usgs":false,"family":"Lehnigk","given":"Karin","affiliations":[{"id":83490,"text":"University of Massachusetts, Amherst, Mass.","active":true,"usgs":false}],"preferred":false,"id":924415,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larsen, Isaac J.","contributorId":349557,"corporation":false,"usgs":false,"family":"Larsen","given":"Isaac J.","affiliations":[{"id":83490,"text":"University of Massachusetts, Amherst, Mass.","active":true,"usgs":false}],"preferred":false,"id":924416,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bjornstad, Bruce N.","contributorId":349558,"corporation":false,"usgs":false,"family":"Bjornstad","given":"Bruce N.","affiliations":[{"id":83492,"text":"Ice Age Floodscapes, Richland, Wash.","active":true,"usgs":false}],"preferred":false,"id":924417,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hanson, Michelle A.","contributorId":349554,"corporation":false,"usgs":false,"family":"Hanson","given":"Michelle A.","affiliations":[{"id":83488,"text":"Saskatchewan Geological Survey, Regina, Sask.","active":true,"usgs":false}],"preferred":false,"id":924414,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"O'Connor, Jim E. 0000-0002-7928-5883 oconnor@usgs.gov","orcid":"https://orcid.org/0000-0002-7928-5883","contributorId":140771,"corporation":false,"usgs":true,"family":"O'Connor","given":"Jim E.","email":"oconnor@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":924418,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70224546,"text":"70224546 - 2021 - The Biscuit Brook and Neversink Reservoir Watersheds: Long-term investigations of stream chemistry, soil chemistry, and aquatic ecology in the Catskill Mountains, New York, USA, 1983 to 2020","interactions":[],"lastModifiedDate":"2021-10-18T15:08:18.866454","indexId":"70224546","displayToPublicDate":"2021-09-24T08:50:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"The Biscuit Brook and Neversink Reservoir Watersheds: Long-term investigations of stream chemistry, soil chemistry, and aquatic ecology in the Catskill Mountains, New York, USA, 1983 to 2020","docAbstract":"This data note describes the Biscuit Brook and Neversink Reservoir watershed Long-Term Monitoring Data that includes: 1) stream discharge, (1983 – 2020 for Biscuit Brook and 1937 – 2020 for the Neversink Reservoir watershed), 2) stream water chemistry, 1983-2020, at 4 stations, 3) fish survey data from 16 locations in the watershed 1990-2019, 4) soil chemistry data from 2 headwater sub-watersheds, 1993-2012, and 5) periodic stream water chemistry sampling data from 364 locations throughout the watershed, 1983-2020. The Neversink Reservoir watershed in the Catskill Mountains of New York, USA drains an area of 172.5 km2. The watershed feeds one of 6 reservoirs in New York City's West of Hudson water supply, which accounts for about 90% of the city's water supply. Biscuit Brook is a 9.63 km2 tributary sub-watershed within the Neversink Reservoir watershed.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.14394","usgsCitation":"Murdoch, P.S., Burns, D., McHale, M., Siemion, J., Baldigo, B., Lawrence, G.B., George, S.D., Antidormi, M.R., and Bonville, D.B., 2021, The Biscuit Brook and Neversink Reservoir Watersheds: Long-term investigations of stream chemistry, soil chemistry, and aquatic ecology in the Catskill Mountains, New York, USA, 1983 to 2020: Hydrological Processes, v. 35, e14394, 12 p., https://doi.org/10.1002/hyp.14394.","productDescription":"e14394, 12 p.","ipdsId":"IP-126065","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":450676,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.14394","text":"Publisher Index Page"},{"id":389807,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Biscuit Brook and Neversink Reservoir Watersheds","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.62188720703125,\n 41.840920397579936\n ],\n [\n -74.60403442382812,\n 41.85319643776675\n ],\n [\n -74.53811645507812,\n 41.881831370505594\n ],\n [\n -74.44129943847656,\n 41.92629234083705\n ],\n [\n -74.28337097167969,\n 42.007978804701\n ],\n [\n -74.278564453125,\n 42.06509700139039\n ],\n [\n -74.30671691894531,\n 42.11095834849246\n ],\n [\n -74.3341827392578,\n 42.13133052651052\n ],\n [\n -74.4049072265625,\n 42.132858175814626\n ],\n [\n -74.44747924804688,\n 42.11707068963613\n ],\n [\n -74.48867797851562,\n 42.042153895364\n ],\n [\n -74.57725524902344,\n 41.984504674276074\n ],\n [\n -74.652099609375,\n 41.9528519300999\n ],\n [\n -74.73518371582031,\n 41.89869952106346\n ],\n [\n -74.74273681640625,\n 41.86291329896065\n ],\n [\n -74.70497131347656,\n 41.81636125072054\n ],\n [\n -74.64866638183594,\n 41.81175536180908\n ],\n [\n -74.62188720703125,\n 41.840920397579936\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","noUsgsAuthors":false,"publicationDate":"2021-10-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Murdoch, Peter S. 0000-0001-9243-505X pmurdoch@usgs.gov","orcid":"https://orcid.org/0000-0001-9243-505X","contributorId":2453,"corporation":false,"usgs":true,"family":"Murdoch","given":"Peter","email":"pmurdoch@usgs.gov","middleInitial":"S.","affiliations":[{"id":5067,"text":"Northeast Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":824014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Douglas A. 0000-0001-6516-2869","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":202943,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":824015,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McHale, Michael 0000-0003-3780-1816 mmchale@usgs.gov","orcid":"https://orcid.org/0000-0003-3780-1816","contributorId":177292,"corporation":false,"usgs":true,"family":"McHale","given":"Michael","email":"mmchale@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824016,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Siemion, Jason 0000-0001-5635-6469 jsiemion@usgs.gov","orcid":"https://orcid.org/0000-0001-5635-6469","contributorId":127562,"corporation":false,"usgs":true,"family":"Siemion","given":"Jason","email":"jsiemion@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824017,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baldigo, Barry P. 0000-0002-9862-9119","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":25174,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824018,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824019,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824020,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Antidormi, Michael R. 0000-0002-3967-1173 mantidormi@usgs.gov","orcid":"https://orcid.org/0000-0002-3967-1173","contributorId":150722,"corporation":false,"usgs":true,"family":"Antidormi","given":"Michael","email":"mantidormi@usgs.gov","middleInitial":"R.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824021,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bonville, Donald B. 0000-0003-4480-9381","orcid":"https://orcid.org/0000-0003-4480-9381","contributorId":248849,"corporation":false,"usgs":true,"family":"Bonville","given":"Donald","email":"","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824022,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70244091,"text":"70244091 - 2021 - Evaluating the impact of watershed development and climate change on stream ecosystems: A Bayesian network modeling approach","interactions":[],"lastModifiedDate":"2023-06-01T14:04:48.814131","indexId":"70244091","displayToPublicDate":"2021-09-24T08:41:56","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the impact of watershed development and climate change on stream ecosystems: A Bayesian network modeling approach","docAbstract":"A continuous-variable Bayesian network (cBN) model is used to link watershed development and climate change to stream ecosystem indicators. A graphical model, reflecting our understanding of the connections between climate change, weather condition, loss of natural land cover, stream flow characteristics, and stream ecosystem indicators is used as the basis for selecting flow metrics for predicting macroinvertebrate-based indicators. Selected flow metrics were then linked to variables representing watershed development and climate change. We fit the model to data from two river basins in southeast US and the resulting model was used to simulate future stream ecological conditions using projected future climate and development scenarios. The three climate models predicted varying ecological condition trajectories, but similar worst-case ecological conditions. The established modeling approach couples mechanistic understanding with field data to develop predictions of management-relevant variables across a heterogeneous landscape. We discussed the transferability of the modeling approach.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2021.117685","usgsCitation":"Qian, S.S., Kennen, J., May, J., Freeman, M., and Cuffney, T.F., 2021, Evaluating the impact of watershed development and climate change on stream ecosystems: A Bayesian network modeling approach: Water Research, v. 205, 117685, 11 p., https://doi.org/10.1016/j.watres.2021.117685.","productDescription":"117685, 11 p.","ipdsId":"IP-125255","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":450679,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.watres.2021.117685","text":"Publisher Index Page"},{"id":417645,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, South Carolina, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -79.52179800853753,\n 32.86310990611119\n ],\n [\n -78.95424437482033,\n 33.20732442214225\n ],\n [\n -78.83061042748197,\n 33.62402639579081\n ],\n [\n -78.03123021414571,\n 33.81848745598903\n ],\n [\n -77.49960057459164,\n 34.229007941502374\n ],\n [\n -77.20942075405912,\n 34.57053494448374\n ],\n [\n -78.04925882655441,\n 35.593623760054015\n ],\n [\n -79.61149509648914,\n 36.3847977489354\n ],\n [\n -80.69994996842892,\n 36.980415621762745\n ],\n [\n -81.2368093995407,\n 36.697683304342775\n ],\n [\n -81.66006417146134,\n 35.81807327161229\n ],\n [\n -80.92321025597303,\n 33.67553987083947\n ],\n [\n -80.06864524456462,\n 32.587876038945694\n ],\n [\n -79.52179800853753,\n 32.86310990611119\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"205","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Qian, Song S. 0000-0002-2346-4903","orcid":"https://orcid.org/0000-0002-2346-4903","contributorId":306033,"corporation":false,"usgs":false,"family":"Qian","given":"Song","email":"","middleInitial":"S.","affiliations":[{"id":62440,"text":"Department of Environmental Sciences, University of Toledo, Toledo, OH 43606","active":true,"usgs":false}],"preferred":false,"id":874463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennen, Jonathan G. 0000-0002-5426-4445 jgkennen@usgs.gov","orcid":"https://orcid.org/0000-0002-5426-4445","contributorId":574,"corporation":false,"usgs":true,"family":"Kennen","given":"Jonathan G.","email":"jgkennen@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"May, Jason 0000-0002-5699-2112","orcid":"https://orcid.org/0000-0002-5699-2112","contributorId":224991,"corporation":false,"usgs":false,"family":"May","given":"Jason","affiliations":[{"id":41015,"text":"Deceased (ex-USGS)","active":true,"usgs":false}],"preferred":false,"id":874465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":874466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cuffney, Thomas F 0000-0003-1164-5560","orcid":"https://orcid.org/0000-0003-1164-5560","contributorId":306032,"corporation":false,"usgs":false,"family":"Cuffney","given":"Thomas","email":"","middleInitial":"F","affiliations":[],"preferred":false,"id":874467,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70225172,"text":"70225172 - 2021 - miR133b microinjection during early development targets transcripts of sardiomyocyte ion channels and induces oil-like cardiotoxicity in zebrafish (Danio rerio) embryos","interactions":[],"lastModifiedDate":"2021-10-18T15:13:36.286802","indexId":"70225172","displayToPublicDate":"2021-09-24T07:40:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9529,"text":"Chemical Research in Toxicology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"miR133b microinjection during early development targets transcripts of sardiomyocyte ion channels and induces oil-like cardiotoxicity in zebrafish (Danio rerio) embryos","title":"miR133b microinjection during early development targets transcripts of sardiomyocyte ion channels and induces oil-like cardiotoxicity in zebrafish (Danio rerio) embryos","docAbstract":"Previous studies have shown that altered expression of a family of small noncoding RNAs (microRNAs, or miRs) regulates the expression of downstream mRNAs and is associated with diseases and developmental disorders. miR133b is highly expressed in mammalian cardiac and skeletal muscle, and aberrant expression is associated with cardiac disorders and electrophysiological changes in cardiomyocytes. Similarly, cardiac dysfunction has been observed in early life-stage mahi-mahi (Coryphaena hippurus) exposed to crude oil, a phenotype that has been associated with an upregulation of miR133b as well as subsequent downregulation of a delayed rectifier potassium channel (IKr) and calcium signaling genes that are important for proper heart development during embryogenesis. To examine the potential role of miR133b in oil-induced early life-stage cardiotoxicity in fish, cleavage-stage zebrafish (Danio rerio) embryos were either (1) microinjected with ∼3 nL of negative control miR (75 μM) or miR133b (75 μM) or (2) exposed to a treatment solution containing 5 μM benzo(a)pyrene (BaP), a model polycyclic aromatic hydrocarbon, as a positive control. At 72 h post fertilization (hpf), miR133b-injected fish exhibited BaP-like cardiovascular malformations, including a significantly increased pericardial area relative to negative control miR-injected embryos, as well as a significantly reduced eye area. qPCR revealed that miR133b microinjection decreased the abundance of cardiac-specific IKrkcnh6 at 5 hpf, which may contribute to action potential elongation in oil-exposed cardiomyocytes. Additionally, ryanodine receptor 2, a crucial calcium receptor in the sarcoplasmic reticulum, was also downregulated by miR133b. These results indicate that an oil-induced increase in miR133b may contribute to cardiac abnormalities in oil-exposed fish by targeting cardiac-specific genes essential for proper heart development.
The U.S. Geological Survey mined data from a variety of national and state agencies including USGS, Oregon Water Resources Department, National Oceanic and Atmospheric Administration, Washington Department of Ecology, Pacific Northwest National Laboratory, Portland State University, and U.S. Army Corps of Engineers. A comprehensive dataset of streamflow, stage, and tidal elevations for the Lower Columbia River basin was compiled. Data were compiled from gaging stations in Oregon and Washington along the Columbia River from Astoria to The Dalles and along the Willamette River from Salem to Portland. Tidal gages along the Washington, Oregon, and California coasts were also compiled. Seasonal maximum values were calculated for both streamflow and stage for the winter (November–March) and spring (April–July) flow seasons, as well as for the full water year when underlying data were available. The aggregated datasets are available at https://doi.org/10.5066/P9R6RT0Z.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201138","collaboration":"Prepared in cooperation with U.S. Army Corps of Engineers","usgsCitation":"Boudreau, C.L., Stewart, M.A., and Stonewall, A.J., 2021, Historical streamflow and stage data compilation for the Lower Columbia River, Pacific Northwest: U.S. Geological Survey Open-File Report 2020–1138, 50 p., https://doi.org/10.3133/ofr20201138.","productDescription":"Report: viii, 50 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-101122","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":389696,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1138/coverthb.jpg"},{"id":389697,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1138/ofr20201138.pdf","text":"Report","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1138"},{"id":389698,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9R6RT0Z","text":"USGS data release","description":"USGS Data release","linkHelpText":"Historical streamflow and stage data for the lower Columbia River basin and the coasts of Washington, Oregon, and northern California"}],"country":"United States","state":"California, Oregon, Washington","otherGeospatial":"Lower Columbia River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.63964843750001,\n 41.672911819602085\n ],\n [\n -120.80566406250001,\n 41.672911819602085\n ],\n [\n -120.80566406250001,\n 49.26780455063753\n ],\n [\n -125.63964843750001,\n 49.26780455063753\n ],\n [\n -125.63964843750001,\n 41.672911819602085\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Temperature fluctuations and climate change impacts may substantially affect spawning success of fish, especially migratory species with a limited spawning window. Factors affecting American shad (Alosa sapidissima) spawning success and survival were investigated at different temperatures and periods (peak- and late-spawning periods) during the Connecticut River, USA, spawning migration in 2017. Wild caught American shad were exposed to constant temperatures regimes of 15, 18, 21, 24 and 27 °C for 2 weeks. During the peak-spawning period, an increase in temperature (15–24 °C) was shown to increase spawning success factors, including spawning probability, number of eggs, and fertilization success, but decreased egg size. Temperatures between 18 and 27 °C did not affect these factors during the late-spawning period. Glochidia infection by the alewife floater (Anodonta implicata) was much higher in the late-spawning period and significantly decreased the survival of American shad. Further research should investigate the parasite-host relationship between the alewife floater and American shad to determine annual variability of glochidia infections and how they affect American shad from physiological and passage perspectives. Higher temperatures were shown to increase spawning success of American shad during the peak-spawning period, but temperature had no effect during the late-spawning period. However, any effect during the late-spawning period may have been masked by a high level of glochidia infection.
For species with variable phenology, it is often challenging to produce reliable estimates of population dynamics or changes in occupancy. The Arizona Toad (Anaxyrus microscaphus) is a southwestern USA endemic that has been petitioned for legal protection, but status assessments are limited by a lack of information on population trends. Also, timing and consistency of Arizona Toad breeding varies greatly, making it difficult to predict optimal survey times or effort required for detection. To help fill these information gaps, we conducted breeding season call surveys during 2013–2016 and 2019 at 86 historically occupied sites and 59 control sites across the species' range in New Mexico. We estimated variation in mean dates of arrival and departure from breeding sites, changes in occupancy, and site-level extinction since 1959 with recently developed multi-season staggered-entry models, which relax the within-season closure assumption common to most occupancy models. Optimal timing of surveys in our study areas was approximately 5–30 March. Averaged across years, estimated probability of occupancy was 0.58 (SE = 0.09) for historical sites and 0.19 (SE = 0.08) for control sites. Occupancy increased from 2013 through 2019. Notably, even though observer error was trivial, annual detection probabilities varied from 0.23 to 0.75 and declined during the study; this means naïve occupancy values would have been misleading, indicating apparent declines in toad occupancy. Occupancy was lowest during the first year of the study, possibly due to changes in stream flows and conditions in many waterbodies following extended drought and recent wildfires. Although within-season closure was violated by variable calling phenology, simple multi-season models provided nearly identical estimates as staggered-entry models. Surprisingly, extinction probability was unrelated to the number of years since the first or last record at historically occupied sites. Collectively, our results suggest a lack of large, recent declines in occupancy by Arizona Toads in New Mexico, but we still lack population information from most of the species' range.
Old-growth forests serve as critical habitat for many sensitive species, but management practices have diminished their prevalence, and former regions of old-growth are now dominated by second-growth stands lacking the structural heterogeneity, diversity, and species richness that these older forests possess. In western Washington state in the Pacific Northwest of the United States, the Olympic Habitat Development Study was designed to address this issue and hasten the development of specific old-growth features in second-growth stands using variable-density thinning. One concern with such methods, however, is the potential to introduce non-native plants, which can have negative ecological and economic impacts. Here, we examine how variable-density thinning influences desirable forest characteristics, such as increased plant species diversity, versus the less desirable effects of non-native plant species introduction. We test two hypotheses regarding plant invasions. First, thinning would promote establishment of non-native, shade-intolerant species, but their abundance would gradually decline over time. Second, thinning disturbance and increased heterogeneity of canopy cover would initially promote understory richness of all species, although richness would decline over time with canopy closure and increased cover of shrubs and regenerating trees. We found that the number and cover of non-native species initially increased after thinning, peaking at 16 species present in variable-density thinned treatments in year three. By year 17, 11 species remained throughout the seven 6.5 ha treatment plots sampled, and cover was negligible. As predicted, species richness increased following thinning, however, native species richness remained elevated through year 17, contrary to our hypothesis. Furthermore, native species diversity also increased following thinning and remained higher in thinned treatments than controls through year 17. Our results show that variable-density thinning in temperate coniferous forests can enhance native, but not exotic, plant richness and diversity in the long term.
Discoveries in the 1980s greatly expanded speleologists’ understanding of the role that hypogenic groundwater flow can play in developing caves at depth. Ascending groundwater charged with carbon dioxide and, especially, hydrogen sulfide can readily dissolve carbonate bedrock just below and above the water table. Sulfuric acid speleogenesis, in which anoxic, rising, sulfidic groundwater mixes with oxygenated cave atmosphere to form aggressive sulfuric acid (H2SO4) formed spectacular caves in Carlsbad Caverns National Park, USA. Cueva de Villa Luz in Mexico provides an aggressively active example of sulfuric acid speleogenesis processes, and the Frasassi Caves in Italy preserve the results of sulfuric acid speleogenesis in its upper levels while sulfidic groundwater currently enlarges cave passages in the lower levels.
Many caves in east-central Nevada and western Utah (USA) are products of hypogenic speleogenesis and formed before the current topography fully developed. Wet climate during the late Neogene and Pleistocene brought extensive meteoric infiltration into the caves, and calcite speleothems (e.g., stalactites, stalagmites, shields) coat the walls and floors of the caves, concealing evidence of the earlier hypogenic stage. However, by studying the speleogenetic features in well-established sulfuric acid speleogenesis caves, evidence of hypogenic, probably sulfidic, speleogenesis in many Great Basin caves can be teased out. Compelling evidence of hypogenic speleogenesis in these caves include folia, mammillaries, bubble trails, cupolas, and metatyuyamunite. Sulfuric acid speleogenesis signs include hollow coralloid stalagmites, trays, gypsum crust, pseudoscallops, rills, and acid pool notches. Lehman Caves in Great Basin National Park is particularly informative because a low-permeability capstone protected about half of the cave from significant meteoric infiltration, preserving early speleogenetic features.
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