The Oregon Department of Transportation (ODOT) and other state departments of transportation need quantitative information about the percentages of different land cover categories above any given stream crossing in the state to assess and address roadway contributions to water-quality impairments and resulting total maximum daily loads. The U.S. Geological Survey, in cooperation with ODOT and the FHWA, added roadway and land cover information to the online StreamStats application to facilitate analysis of stormwater runoff contributions from different land covers. Analysis of 25 delineated basins with drainage areas of about 100 mi2 indicates the diversity of land covers in the Willamette Valley, Oregon. On average, agricultural, developed, and undeveloped land covers comprise 15%, 2.3%, and 82% of these basin areas. On average, these basins contained about 10 mi of state highways and 222 mi of non-state roads. The Stochastic Empirical Loading and Dilution Model was used with available water-quality data to simulate long-term yields of total phosphorus from highways, non-highway roadways, and agricultural, developed, and undeveloped areas. These yields were applied to land cover areas obtained from StreamStats for the Willamette River above Wilsonville, Oregon. This analysis indicated that highway yields were larger than yields from other land covers because highway runoff concentrations were higher than other land covers and the highway is fully impervious. However, the total highway area was a fraction of the other land covers. Accordingly, highway runoff mitigation measures can be effective for managing water quality locally, they may have limited effect on achieving basin-wide stormwater reduction goals.
Data from a long-term capture-recapture program were used to assess the status and dynamics of populations of two long-lived, federally endangered catostomids in Upper Klamath Lake, Oregon. Lost River suckers (LRS; Deltistes luxatus) and shortnose suckers (SNS; Chasmistes brevirostris) have been captured and tagged with passive integrated transponder (PIT) tags during their spawning migrations in each year since 1995. In addition, beginning in 2005, individuals that had been previously PIT-tagged were re-encountered on remote underwater antennas deployed throughout sucker spawning areas. Captures and remote encounters during the spawning season in spring 2016 were incorporated into capture-recapture analyses of population dynamics.
Cormack-Jolly-Seber (CJS) open population capture-recapture models were used to estimate annual survival probabilities, and a reverse-time analog of the CJS model was used to estimate recruitment of new individuals into the spawning populations. In addition, data on the size composition of captured fish were examined to provide corroborating evidence of recruitment. Model estimates of survival and recruitment were used to derive estimates of changes in population size over time and to determine the status of the populations through 2015. Separate analyses were done for each species and also for each subpopulation of LRS. Shortnose suckers and one subpopulation of LRS migrate into tributary rivers to spawn, whereas the other LRS subpopulation spawns at groundwater upwelling areas along the eastern shoreline of the lake.
Capture-recapture analyses indicated that with a few exceptions, the survival of males and females in both Lost River sucker subpopulations was high (greater than 0.88) from 1999 to 2015. Survival was notably lower for males from the river in 2000, 2006, and 2012, and for the shoreline areas in 2002. From 2001 to 2015, the abundance of males in the lakeshore spawning subpopulation decreased by at least 64 percent and the abundance of females decreased by at least 56 percent. Capture-recapture models suggested that the abundance of both sexes in the river spawning subpopulation of LRS had increased substantially since 2006; increases were mostly due to large estimated recruitment events in 2006 and 2008. We know that the estimates in 2006 are substantially biased in favor of recruitment because of a sampling issue. We are skeptical of the magnitude of recruitment indicated by the 2008 estimates as well because (1) few small individuals that would indicate the presence of new recruits were captured in that year, and (2) recapture probabilities in recruitment models based on just physical recaptures of fish were lower than desired for robust inferences from capture-recapture models. If we assume instead that little or no recruitment occurred for this subpopulation, the abundance of both sexes in the river spawning subpopulation likely has decreased at rates similar to the rates for the lakeshore spawning subpopulation from 2002 to 2015.
Shortnose suckers experienced lower and more variable annual survival than either LRS subpopulation. Annual survival of both sexes was relatively low in 2003, 2004, 2010, and 2012. In addition, female survival was low in 1999 and 2000 while male survival was low in 2002. Survival estimate precision in early years of the study; however, are poor. Capture-recapture models and size composition data indicate that recruitment of new individuals into the SNS spawning population was trivial from 2001 to 2005. Models indicate that more than 10 percent of the population was new recruits in a number of more recent years. As a result, capture-recapture modeling suggests that the abundance of adult spawning SNS was relatively stable from 2006 to 2010. We are skeptical of the estimated recruitment in 2006 because of the known sampling issue. We also are skeptical of the estimated recruitment in other recent years because few small individuals that would indicate the presence of new recruits were captured in any of those years, and recapture probabilities in recruitment models were low. The best-case scenario for SNS, based on capture-recapture recruitment modeling, indicates that the abundance of males in the spawning population decreased by 78 percent and the abundance of females decreased by 77 percent from 2001 to 2015. Decreases in abundance for both sexes are likely greater than these estimates indicate.
Despite relatively high survival in most years, we conclude that both species have experienced substantial decreases in the abundance of spawning adults because losses from mortality have not been balanced by recruitment of new individuals. Although capture-recapture data indicate substantial recruitment of new individuals into the spawning populations for SNS and river spawning LRS in some years, size data do not corroborate these estimates. As a result, the status of the endangered sucker populations in Upper Klamath Lake remains distressed, especially for SNS. Our monitoring program provides a robust platform for estimating vital population parameters, evaluating the status of the populations, and assessing the effectiveness of conservation and recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181064","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Hewitt, D.A., Janney, E.C., Hayes, B.S., and Harris, A.C., 2018, Status and trends of adult Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) sucker populations in Upper Klamath Lake, Oregon, 2017: U.S. Geological Survey Open-File Report 2018-1064, 31 p., https://doi.org/10.3133/ofr20181064.","productDescription":"iv, 31 p.","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-096959","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":437938,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97K04NO","text":"USGS data release","linkHelpText":"Status and trends of adult Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) sucker populations in Upper Klamath Lake, Oregon, 2023"},{"id":353417,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1064/coverthb.jpg"},{"id":353418,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1064/ofr20181064.pdf","text":"Report","size":"905 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1064"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.10067749023438,\n 42.21936476344714\n ],\n [\n -121.79992675781249,\n 42.21936476344714\n ],\n [\n -121.79992675781249,\n 42.61981257367216\n ],\n [\n -122.10067749023438,\n 42.61981257367216\n ],\n [\n -122.10067749023438,\n 42.21936476344714\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
The Gunnison Basin Selenium Management Program implemented a water-quality monitoring network in 2011 in the lower Gunnison River Basin in Colorado. Selenium is a trace element that bioaccumulates in aquatic food chains and can cause reproductive failure, deformities, and other harmful effects. This report presents the percentile values of selenium because regulatory agencies in Colorado make decisions based on the U.S. Environmental Protection Agency (EPA) Clean Water Act Section 303(d) that uses percentile values of concentration. Also presented are dissolved-selenium loads at 18 sites in the lower Gunnison River Basin for water years (WYs) 2011–2016 (October 1, 2010, through September 30, 2016). Annual dissolved-selenium loads were calculated for five sites with continuous U.S. Geological Survey (USGS) streamflow-gaging stations. Annual dissolved-selenium loads for WY 2011 through WY 2016 ranged from 179 and 391 pounds (lb) at Uncompahgre River at Colona to 11,100 and 17,300 lb at Gunnison River near Grand Junction (herein called Whitewater), respectively.
Instantaneous loads were calculated for five sites with continuous U.S. Geological Survey (USGS) streamflow-gaging stations and 13 ancillary sites where discrete water-quality sampling also took place, using discrete water-quality samples and the associated discharge measurements collected during the period. Median instantaneous loads ranged from 0.01 pound per day (lb/d) at Smith Fork near Lazear to 33.0 lb/d at Whitewater. Mean instantaneous loads ranged from 0.06 lb/d at Smith Fork near Lazear to 36.2 lb/d at Whitewater. Most tributary sites in the basin had a median instantaneous dissolved-selenium load of less than 20.0 lb/day. In general, dissolved-selenium loads at Gunnison River main-stem sites showed an increase from upstream to downstream.
The State of Colorado water-quality standard for dissolved selenium of 4.6 micrograms per liter (µg/L) was compared to the 85th percentiles for dissolved selenium at selected sites. Annual 85th percentiles for dissolved selenium were calculated for the five core sites having USGS streamflow-gaging stations using estimated dissolved-selenium concentrations from linear regression models. The 85th-percentile concentrations for WYs 2011–2016 based on this method ranged from 0.62 µg/L and 1.1µg/L at Uncompahgre River at Colona to 12.1 µg/L and 18.7 µg/L at Uncompahgre River at Delta.
The 85th percentiles for dissolved selenium also were calculated for sites with sufficient data using water-quality samples collected during WYs 2011–2016. The annual 85th-percentile concentrations based on the discrete samples ranged from 0.16 µg/L and 0.17 µg/L at Gunnison River below Gunnison Tunnel to 62.2 µg/L and 170 µg/L at Loutzenhizer Arroyo at North River Road.
A trend analysis was completed for Whitewater to determine if dissolved-selenium loads are increasing or decreasing. The trend analysis indicates a decrease of 9,100 lb from WY 1986 to WY 2016, a 40.8 percent reduction during the time period. The trend analysis for the annual dissolved-selenium load for WY 1994 to WY 2016 indicates a decrease of 6,300 lb per year, or 33.3 percent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185001","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Henneberg, M.F., 2018, Assessment of dissolved-selenium concentrations and loads in the lower Gunnison River Basin, Colorado, as part of the Selenium Management Program, from 2011 to 2016: U.S. Geological Survey Scientific Investigations Report 2018–5001, 23 p., https://doi.org/10.3133/ofr20185001.","productDescription":"v, 23 p.","numberOfPages":"33","onlineOnly":"Y","ipdsId":"IP-090932","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":353466,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5001/coverthb.jpg"},{"id":353467,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5001/sir20185001.pdf","text":"Report","size":"2.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5001"}],"country":"United States","state":"Colorado","otherGeospatial":"Lower Gunnison River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.5,\n 38\n ],\n [\n -107.25,\n 38\n ],\n [\n -107.25,\n 39.25\n ],\n [\n -108.5,\n 39.25\n ],\n [\n -108.5,\n 38\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS 415
Denver, CO 80225
Direct covariance observations of the mean flow Reynolds stress and sonar images of the seafloor collected on a wave‐exposed inner continental shelf demonstrate that the drag exerted by the seabed on the overlying flow is consistent with boundary layer models for wave‐current interaction, provided that the orientation and anisotropy of the bed roughness are appropriately quantified. Large spatial and temporal variations in drag result from nonequilibrium ripple dynamics, ripple anisotropy, and the orientation of the ripples relative to the current. At a location in coarse sand characterized by large two‐dimensional orbital ripples, the observed drag shows a strong dependence on the relative orientation of the mean current to the ripple crests. At a contrasting location in fine sand, where more isotropic sub‐orbital ripples are observed, the sensitivity of the current to the orientation of the ripples is reduced. Further, at the coarse site under conditions when the currents are parallel to the ripple crests and the wave orbital diameter is smaller than the wavelength of the relic orbital ripples, the flow becomes hydraulically smooth. This transition is not observed at the fine site, where the observed wave orbital diameter is always greater than the wavelength of the observed sub‐orbital ripples. Paradoxically, the dominant along‐shelf flows often experience lower drag at the coarse site than at the fine site, despite the larger ripples, highlighting the complex dynamics controlling drag in wave‐exposed environments with heterogeneous roughness.
","language":"English","publisher":"AGU","doi":"10.1002/2017JC013252","usgsCitation":"Scully, M., Trowbridge, J., Sherwood, C.R., Jones, K.R., and Traykovski, P.A., 2018, Direct measurements of mean Reynolds stress and ripple roughness in the presence of energetic forcing by surface waves: Journal of Geophysical Research C: Oceans, v. 123, no. 4, p. 2494-2512, https://doi.org/10.1002/2017JC013252.","productDescription":"19 p.","startPage":"2494","endPage":"2512","ipdsId":"IP-088590","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468815,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/2017jc013252","text":"External Repository"},{"id":353643,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"4","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-10","publicationStatus":"PW","scienceBaseUri":"5afee6d3e4b0da30c1bfbe76","contributors":{"authors":[{"text":"Scully, Malcolm","contributorId":174993,"corporation":false,"usgs":false,"family":"Scully","given":"Malcolm","email":"","affiliations":[],"preferred":false,"id":733829,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trowbridge, John","contributorId":174994,"corporation":false,"usgs":false,"family":"Trowbridge","given":"John","email":"","affiliations":[],"preferred":false,"id":733830,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":733828,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Katie R. 0000-0003-3373-3924","orcid":"https://orcid.org/0000-0003-3373-3924","contributorId":204379,"corporation":false,"usgs":false,"family":"Jones","given":"Katie","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":733831,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Traykovski, Peter A. 0000-0002-8163-6857","orcid":"https://orcid.org/0000-0002-8163-6857","contributorId":69487,"corporation":false,"usgs":false,"family":"Traykovski","given":"Peter","email":"","middleInitial":"A.","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false}],"preferred":false,"id":733832,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196637,"text":"ofr20181037 - 2018 - Leveraging geodetic data to reduce losses from earthquakes","interactions":[],"lastModifiedDate":"2018-04-24T13:34:26","indexId":"ofr20181037","displayToPublicDate":"2018-04-23T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1037","title":"Leveraging geodetic data to reduce losses from earthquakes","docAbstract":"Seismic hazard assessments that are based on a variety of data and the best available science, coupled with rapid synthesis of real-time information from continuous monitoring networks to guide post-earthquake response, form a solid foundation for effective earthquake loss reduction. With this in mind, the Earthquake Hazards Program (EHP) of the U.S. Geological Survey (USGS) Natural Hazards Mission Area (NHMA) engages in a variety of undertakings, both established and emergent, in order to provide high quality products that enable stakeholders to take action in advance of and in response to earthquakes. Examples include the National Seismic Hazard Model (NSHM), development of tools for improved situational awareness such as earthquake early warning (EEW) and operational earthquake forecasting (OEF), research about induced seismicity, and new efforts to advance comprehensive subduction zone science and monitoring. Geodetic observations provide unique and complementary information directly relevant to advancing many aspects of these efforts (fig. 1). EHP scientists have long leveraged geodetic data for a range of influential studies, and they continue to develop innovative observation and analysis methods that push the boundaries of the field of geodesy as applied to natural hazards research. Given the ongoing, rapid improvement in availability, variety, and precision of geodetic measurements, considering ways to fully utilize this observational resource for earthquake loss reduction is timely and essential. This report presents strategies, and the underlying scientific rationale, by which the EHP could achieve the following outcomes:
A geodesy program that encompasses a balanced mix of activities to sustain missioncritical capabilities, grows new competencies through the continuum of fundamental to applied research, and ensures sufficient resources for these endeavors provides a foundation by which the EHP can be a leader in the application of geodesy to earthquake science. With this in mind the following objectives provide a framework to guide EHP efforts:
Maintaining a vibrant internal research program provides the foundation by which the EHP can remain an effective and trusted source for earthquake science. Exploiting abundant new data sources, evaluating and assimilating the latest science, and pursuing novel avenues of investigation are means to fulfilling the EHP’s core responsibilities and realizing the important scientific advances envisioned by its scientists. Central to the success of such a research program is engaging personnel with a breadth of competencies and a willingness and ability to adapt these to the program’s evolving priorities, enabling current staff to expand their skills and responsibilities, and planning holistically to meet shared workforce needs.
In parallel, collaboration with external partners to support scientific investigations that complement ongoing internal research enables the EHP to strengthen earthquake information products by incorporating alternative perspectives and approaches and to study topics and geographic regions that cannot be adequately covered internally.
With commensurate support from technical staff who possess diverse skills, including engineering, information technology, and proficiency in quantitative analysis combined with basic geophysical knowledge, the EHP can achieve the geodetic outcomes identified in this document.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181037","usgsCitation":"Murray, J.R., Roeloffs, E.A., Brooks, B.A., Langbein, J., Leith, W., Minson, S.E., Svarc, J., and Thatcher, W., 2018, Leveraging geodetic data to reduce losses from earthquakes: U.S. Geological Survey Open-File Report 2018–1037, 34 p., https://doi.org/10.3133/ofr20181037.","productDescription":"vi, 34 p.","numberOfPages":"43","onlineOnly":"Y","ipdsId":"IP-089859","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":353651,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1037/coverthb.jpg"},{"id":353652,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1037/ofr20181037.pdf","text":"Report","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1037"}],"contact":"Contact Information, Menlo Park, Calif.
Office—Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
https://earthquake.usgs.gov/
We have developed groundwater flow models to explore the possible relationship between wastewater injection and the 12 November 2014 Mw 4.8 Milan, Kansas earthquake. We calculate pore pressure increases in the uppermost crust using a suite of models in which hydraulic properties of the Arbuckle Formation and the Milan earthquake fault zone, the Milan earthquake hypocenter depth, and fault zone geometry are varied. Given pre‐earthquake injection volumes and reasonable hydrogeologic properties, significantly increasing pore pressure at the Milan hypocenter requires that most flow occur through a conductive channel (i.e., the lower Arbuckle and the fault zone) rather than a conductive 3‐D volume. For a range of reasonable lower Arbuckle and fault zone hydraulic parameters, the modeled pore pressure increase at the Milan hypocenter exceeds a minimum triggering threshold of 0.01 MPa at the time of the earthquake. Critical factors include injection into the base of the Arbuckle Formation and proximity of the injection point to a narrow fault damage zone or conductive fracture in the pre‐Cambrian basement with a hydraulic diffusivity of about 3–30 m2/s. The maximum pore pressure increase we obtain at the Milan hypocenter before the earthquake is 0.06 MPa. This suggests that the Milan earthquake occurred on a fault segment that was critically stressed prior to significant wastewater injection in the area. Given continued wastewater injection into the upper Arbuckle in the Milan region, assessment of the middle Arbuckle as a hydraulic barrier remains an important research priority.
","language":"English","publisher":"AGU","doi":"10.1002/2017GC007194","usgsCitation":"Hearn, E.H., Koltermann, C., and Rubinstein, J.R., 2018, Numerical models of pore pressure and stress changes along basement faults due to wastewater injection: Applications to the 2014 Milan, Kansas Earthquake: Geochemistry, Geophysics, Geosystems, v. 19, no. 4, p. 1178-1198, https://doi.org/10.1002/2017GC007194.","productDescription":"21 p.","startPage":"1178","endPage":"1198","ipdsId":"IP-087532","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":468814,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017gc007194","text":"Publisher Index Page"},{"id":353667,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98,\n 37\n ],\n [\n -97.3,\n 37\n ],\n [\n -97.3,\n 37.5\n ],\n [\n -98,\n 37.5\n ],\n [\n -98,\n 37\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-16","publicationStatus":"PW","scienceBaseUri":"5afee6d3e4b0da30c1bfbe6e","contributors":{"authors":[{"text":"Hearn, Elizabeth H.","contributorId":204395,"corporation":false,"usgs":false,"family":"Hearn","given":"Elizabeth","email":"","middleInitial":"H.","affiliations":[{"id":36931,"text":"Capstone Geopysics, Portola Valley, California,","active":true,"usgs":false}],"preferred":false,"id":733890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koltermann, Christine","contributorId":204396,"corporation":false,"usgs":false,"family":"Koltermann","given":"Christine","email":"","affiliations":[{"id":36932,"text":"Pegasus Geoscience, Santa Clara, California","active":true,"usgs":false}],"preferred":false,"id":733891,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rubinstein, Justin R. 0000-0003-1274-6785","orcid":"https://orcid.org/0000-0003-1274-6785","contributorId":204394,"corporation":false,"usgs":true,"family":"Rubinstein","given":"Justin","email":"","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":733889,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196617,"text":"70196617 - 2018 - The Florida manatee (Trichechus manatus latirostris) T cell receptor loci exhibit V subgroup synteny and chain-specific evolution","interactions":[],"lastModifiedDate":"2018-04-20T11:42:28","indexId":"70196617","displayToPublicDate":"2018-04-20T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1383,"text":"Developmental and Comparative Immunology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The Florida manatee (Trichechus manatus latirostris) T cell receptor loci exhibit V subgroup synteny and chain-specific evolution","title":"The Florida manatee (Trichechus manatus latirostris) T cell receptor loci exhibit V subgroup synteny and chain-specific evolution","docAbstract":"The Florida manatee (Trichechus manatus latirostris) has limited diversity in the immunoglobulin heavy chain. We therefore investigated the antigen receptor loci of the other arm of the adaptive immune system: the T cell receptor. Manatees are the first species from Afrotheria, a basal eutherian superorder, to have an in-depth characterization of all T cell receptor loci. By annotating the genome and expressed transcripts, we found that each chain has distinct features that correlates to their individual functions. The genomic organization also plays a role in modulating sequence conservation between species. There were extensive V subgroup synteny blocks in the TRA and TRB loci between T. m. latirostrisand human. Increased genomic locus complexity correlated to increased locus synteny. We also identified evidence for a VHD pseudogene for the first time in a eutherian mammal. These findings emphasize the value of including species within this basal eutherian radiation in comparative studies.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.dci.2018.04.007","usgsCitation":"Breaux, B., Hunter, M., Cruz-Schneider, M.P., Sena, L., Bonde, R.K., and Criscitiello, M.F., 2018, The Florida manatee (Trichechus manatus latirostris) T cell receptor loci exhibit V subgroup synteny and chain-specific evolution: Developmental and Comparative Immunology, v. 85, p. 71-85, https://doi.org/10.1016/j.dci.2018.04.007.","productDescription":"15 p.","startPage":"71","endPage":"85","ipdsId":"IP-093270","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468817,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.dci.2018.04.007","text":"Publisher Index Page"},{"id":353618,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"85","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6d8e4b0da30c1bfbe82","contributors":{"authors":[{"text":"Breaux, Breanna","contributorId":196396,"corporation":false,"usgs":false,"family":"Breaux","given":"Breanna","email":"","affiliations":[],"preferred":false,"id":733773,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunter, Margaret 0000-0002-4760-9302 mhunter@usgs.gov","orcid":"https://orcid.org/0000-0002-4760-9302","contributorId":140627,"corporation":false,"usgs":true,"family":"Hunter","given":"Margaret","email":"mhunter@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":733772,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cruz-Schneider, Maria Paula","contributorId":196400,"corporation":false,"usgs":false,"family":"Cruz-Schneider","given":"Maria","email":"","middleInitial":"Paula","affiliations":[],"preferred":false,"id":733774,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sena, Leonardo","contributorId":196401,"corporation":false,"usgs":false,"family":"Sena","given":"Leonardo","email":"","affiliations":[],"preferred":false,"id":733775,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bonde, Robert K. 0000-0001-9179-4376 rbonde@usgs.gov","orcid":"https://orcid.org/0000-0001-9179-4376","contributorId":2675,"corporation":false,"usgs":true,"family":"Bonde","given":"Robert","email":"rbonde@usgs.gov","middleInitial":"K.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":733776,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Criscitiello, Michael F.","contributorId":196403,"corporation":false,"usgs":false,"family":"Criscitiello","given":"Michael","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":733777,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196552,"text":"ofr20181066 - 2018 - Juvenile Lost River and shortnose sucker year class strength, survival, and growth in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California—2016 Monitoring Report","interactions":[],"lastModifiedDate":"2018-04-23T12:59:59","indexId":"ofr20181066","displayToPublicDate":"2018-04-20T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1066","title":"Juvenile Lost River and shortnose sucker year class strength, survival, and growth in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California—2016 Monitoring Report","docAbstract":"The largest populations of federally endangered Lost River (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) exist in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California. Upper Klamath Lake populations are decreasing because adult mortality, which is relatively low, is not being balanced by recruitment of young adult suckers into known spawning aggregations. Most Upper Klamath Lake juvenile sucker mortality appears to occur within the first year of life. Annual production of juvenile suckers in Clear Lake Reservoir appears to be highly variable and may not occur at all in very dry years. However, juvenile sucker survival is much higher in Clear Lake, with non-trivial numbers of suckers surviving to join spawning aggregations. Long-term monitoring of juvenile sucker populations is needed to (1) determine if there are annual and species-specific differences in production, survival, and growth, (2) to identify the season (summer or winter) in which most mortality occurs, and (3) to help identify potential causes of high juvenile sucker mortality, particularly in Upper Klamath Lake.
We initiated an annual juvenile sucker monitoring program in 2015 to track cohorts in 3 months (June, August, and September) annually in Upper Klamath Lake and Clear Lake Reservoir. We tracked annual variability in age-0 sucker apparent production, juvenile sucker apparent survival, and apparent growth. Using genetic markers, we were able to classify suckers as one of three taxa: shortnose or Klamath largescale suckers, Lost River, or suckers with genetic markers of both species (Intermediate Prob[LRS]). Using catch data, we generated taxa-specific indices of year class strength, August–September apparent survival, and overwinter apparent survival. We also examined prevalence and severity of afflictions such as parasites, wounds, and deformities.
Indices of year class strength in Upper Klamath Lake were similar for shortnose suckers in 2015 and 2016, but about twice as high for Lost River suckers and suckers having intermediate Prob[LRS] in 2016 than in 2015. Indices of apparent August–September survival were lower in 2016 (0.41) than in 2015 (1.07) for shortnose suckers and suckers identified as having intermediate Prob [LRS] (0.14 in 2016 and 1.69 in 2015). Indices of apparent August—September survival were similar in 2016 (0.16) and 2015 (0.07) for Lost River suckers. Indices of apparent survival were lower for age-0 Lost River suckers than age-0 shortnose suckers in both years. Although samples sizes are small, a declining trend in the ratio of Lost River to shortnose suckers from 28/23 (1.22) as age-0 fish in September of 2015 to 1/9 (0.11) as age-1 fish in June of 2016 is consistent with higher over winter apparent mortality for Lost River suckers than shortnose suckers in Upper Klamath Lake.
Shortnose sucker year class strength was greater in years with high Willow Creek inflows and Clear Lake surface elevation during the spawning season, indicating that access to spawning habitat was an important contributing factor. In previous sampling, age-0 sucker catch per unit effort (CPUE) was relatively high in 2011 and 2012, moderately high in 2013, and zero in 2014 and 2015. The 2011 and 2012 year classes continued to be detected, but the 2013 year class went undetected for the first time in 2016. The 2014 year class continued to be undetected in 2016. Three suckers with one annulus each on fin rays were captured in Clear Lake in 2016. Although these fish are potential representatives of the 2015 year class, they were small for their age, indicating they may have hatched in 2016. Age-0 shortnose and Lost River suckers were captured in Clear Lake in 2016, indicating new cohorts of both taxa were produced. Moderate to abundant year classes were produced in 2011, 2012, and 2016 when lake surface elevation greater than 1,378.9 m (4,524 ft) during the February–June spawning season. Also in 2011 and 2016, rapid increases in lake-surface elevation indicated potentially high Willow Creek inflows. A somewhat less abundant year class produced in 2012 than in 2011 and 2016 was associated with lower spawning season inflows. The apparently smaller 2013 year class was formed when Willow Creek inflows were apparently low and lake surface never exceeded 1,379.2 m (4,524.9 ft). In 2014 and 2015, when year-classes were small or not detected, the Clear Lake surface elevations were at or below 1,378.2 m (4,522 ft), and there was very little spring time Willow Creek inflow.
Age-0 shortnose sucker CPUE in Clear Lake was correlated with seasonal decreases in water volumes in 2016 and could not be used to create indices of August–September survival. Age-0 shortnose sucker catch rates in Clear Lake Reservoir were about seven times less in August than in September. Meanwhile, the water volume in Clear Lake Reservoir declined by about 36 percent between these two sampling periods. Higher September catch rates may have resulted from additional age-0 suckers entering the lake from the river, a concentrating effect of declining water volumes, or both.
Differences in August standard length, apparent growth rates, and the prevalence of abnormalities were consistent with healthier age-0 suckers in Clear Lake Reservoir than in Upper Klamath Lake. Age-0 suckers were larger in August in Clear Lake Reservoir than in Upper Klamath Lake, which may be due to an earlier hatch date, faster growth, or both in Clear Lake Reservoir. Sample sizes were only large enough to compare growth rates of age-0 shortnose suckers from Upper Klamath Lake in 2015 to Clear Lake Reservoir in 2016. Age-0 shortnose suckers grew more between August and September in Clear Lake Reservoir in 2016 than in Upper Klamath Lake in 2015. Petechial hemorrhages of the skin on age-0 suckers were more prevalent in Upper Klamath Lake than in Clear Lake Reservoir in 2016. Deformed opercula, black-spot forming parasites, and infections presumed to be Columnaris sp. were observed on less than 12 percent of suckers from Upper Klamath Lake but were not observed on suckers from Clear Lake Reservoir in 2016.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181066","usgsCitation":"Burdick, S.M., Ostberg, C.O., and Hoy, M.S., 2018, Juvenile Lost River and shortnose sucker year class strength, survival, and growth in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California—2016 Monitoring Report: U.S. Geological Survey Open-File Report 2018–1066, 43 p., https://doi.org/10.3133/ofr20181066.","productDescription":"vi, 43 p.","numberOfPages":"54","onlineOnly":"Y","ipdsId":"IP-094193","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":353625,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1066/coverthb.jpg"},{"id":353626,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1066/ofr20181066.pdf","text":"Report","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1066"}],"country":"United States","state":"California, Oregon","county":"Klamath County, Modoc County","otherGeospatial":"Clear Lake Reservoir, Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.11509704589845,\n 42.222924262739824\n ],\n [\n -121.75186157226561,\n 42.222924262739824\n ],\n [\n -121.75186157226561,\n 42.61829672418602\n ],\n [\n -122.11509704589845,\n 42.61829672418602\n ],\n [\n -122.11509704589845,\n 42.222924262739824\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.23687744140624,\n 41.781552998900345\n ],\n [\n -121.04736328125,\n 41.781552998900345\n ],\n [\n -121.04736328125,\n 41.94365947797709\n ],\n [\n -121.23687744140624,\n 41.94365947797709\n ],\n [\n -121.23687744140624,\n 41.781552998900345\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
Urban and exurban expansion results in habitat and biodiversity loss globally. We hypothesize that a coupled-model approach could connect urban planning for future cities with landscape ecology to consider wildland habitat connectivity. Our work combines urban growth simulations with models of wildlife corridors to examine how species will be impacted by development to test this hypothesis. We leverage a land use change model (SLEUTH) with structural and functional landscape-connectivity modeling techniques to ascertain the spatial extent and locations of connectivity related threats to a national park in southern Arizona, USA, and describe how protected areas might be impacted by urban expansion. Results of projected growth significantly altered structural connectivity (80%) when compared to current (baseline) corridor conditions. Moreover, projected growth impacted functional connectivity differently amongst species, indicating resilience of some species and near-complete displacement of others. We propose that implementing a geospatial-design-based model will allow for a better understanding of the impacts management decisions have on wildlife populations. The application provides the potential to understand both human and environmental impacts of land-system dynamics, critical for long-term sustainability.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/1747423X.2018.1455905","usgsCitation":"Perkl, R., Norman, L., Mitchell, D., Feller, M.R., Smith, G., and Wilson, N., 2018, Urban growth and landscape connectivity threats assessment at Saguaro National Park, Arizona, USA: Journal of Land Use Science, v. 13, no. 1-2, p. 102-117, https://doi.org/10.1080/1747423X.2018.1455905.","productDescription":"16 p.","startPage":"102","endPage":"117","ipdsId":"IP-072269","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":353598,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Saguaro National Park","volume":"13","issue":"1-2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-02","publicationStatus":"PW","scienceBaseUri":"5afee6d9e4b0da30c1bfbe90","contributors":{"authors":[{"text":"Perkl, Ryan","contributorId":204345,"corporation":false,"usgs":false,"family":"Perkl","given":"Ryan","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":733706,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":733705,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mitchell, David","contributorId":66956,"corporation":false,"usgs":true,"family":"Mitchell","given":"David","affiliations":[],"preferred":false,"id":733707,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Feller, Mark R. mrfeller@usgs.gov","contributorId":3904,"corporation":false,"usgs":true,"family":"Feller","given":"Mark","email":"mrfeller@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":733708,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Garrett","contributorId":204347,"corporation":false,"usgs":false,"family":"Smith","given":"Garrett","affiliations":[{"id":36922,"text":"Univ. Ariz.","active":true,"usgs":false}],"preferred":false,"id":733709,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wilson, Natalie R. 0000-0001-5145-1221","orcid":"https://orcid.org/0000-0001-5145-1221","contributorId":202534,"corporation":false,"usgs":true,"family":"Wilson","given":"Natalie R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":733710,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196575,"text":"70196575 - 2018 - Opportunistically collected data reveal habitat selection by migrating Whooping Cranes in the U.S. Northern Plains","interactions":[],"lastModifiedDate":"2018-04-19T09:26:58","indexId":"70196575","displayToPublicDate":"2018-04-19T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Opportunistically collected data reveal habitat selection by migrating Whooping Cranes in the U.S. Northern Plains","docAbstract":"The Whooping Crane (Grus americana) is a federally endangered species in the United States and Canada that relies on wetland, grassland, and cropland habitat during its long migration between wintering grounds in coastal Texas, USA, and breeding sites in Alberta and Northwest Territories, Canada. We combined opportunistic Whooping Crane sightings with landscape data to identify correlates of Whooping Crane occurrence along the migration corridor in North Dakota and South Dakota, USA. Whooping Cranes selected landscapes characterized by diverse wetland communities and upland foraging opportunities. Model performance substantially improved when variables related to detection were included, emphasizing the importance of accounting for biases associated with detection and reporting of birds in opportunistic datasets. We created a predictive map showing relative probability of occurrence across the study region by applying our model to GIS data layers; validation using independent, unbiased locations from birds equipped with platform transmitting terminals indicated that our final model adequately predicted habitat use by migrant Whooping Cranes. The probability map demonstrated that existing conservation efforts have protected much top-tier Whooping Crane habitat, especially in the portions of North Dakota and South Dakota that lie east of the Missouri River. Our results can support species recovery by informing prioritization for acquisition and restoration of landscapes that provide safe roosting and foraging habitats. Our results can also guide the siting of structures such as wind towers and electrical transmission and distribution lines, which pose a strike and mortality risk to migrating Whooping Cranes.
","language":"English","publisher":"American Ornithological Society","doi":"10.1650/CONDOR-17-80.1","usgsCitation":"Niemuth, N.D., Ryba, A.J., Pearse, A.T., Kvas, S.M., Brandt, D.A., Wangler, B., Austin, J.E., and Carlisle, M.J., 2018, Opportunistically collected data reveal habitat selection by migrating Whooping Cranes in the U.S. Northern Plains: The Condor, v. 120, no. 2, p. 343-356, https://doi.org/10.1650/CONDOR-17-80.1.","productDescription":"14 p.","startPage":"343","endPage":"356","ipdsId":"IP-076151","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468819,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-17-80.1","text":"Publisher Index Page"},{"id":353596,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota, South Dakota","volume":"120","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6d9e4b0da30c1bfbe92","contributors":{"authors":[{"text":"Niemuth, Neal D. 0009-0006-9637-5588","orcid":"https://orcid.org/0009-0006-9637-5588","contributorId":204334,"corporation":false,"usgs":false,"family":"Niemuth","given":"Neal","email":"","middleInitial":"D.","affiliations":[{"id":36919,"text":"U.S. Fish and Wildlife Service Habitat and Population Evaluation Team","active":true,"usgs":false}],"preferred":false,"id":733667,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ryba, Adam J.","contributorId":204335,"corporation":false,"usgs":false,"family":"Ryba","given":"Adam","email":"","middleInitial":"J.","affiliations":[{"id":36919,"text":"U.S. Fish and Wildlife Service Habitat and Population Evaluation Team","active":true,"usgs":false}],"preferred":false,"id":733668,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":733666,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kvas, Susan M.","contributorId":204336,"corporation":false,"usgs":false,"family":"Kvas","given":"Susan","email":"","middleInitial":"M.","affiliations":[{"id":36919,"text":"U.S. Fish and Wildlife Service Habitat and Population Evaluation Team","active":true,"usgs":false}],"preferred":false,"id":733669,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brandt, David A. 0000-0001-9786-307X dbrandt@usgs.gov","orcid":"https://orcid.org/0000-0001-9786-307X","contributorId":149929,"corporation":false,"usgs":true,"family":"Brandt","given":"David","email":"dbrandt@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":733670,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wangler, Brian","contributorId":204337,"corporation":false,"usgs":false,"family":"Wangler","given":"Brian","email":"","affiliations":[{"id":36919,"text":"U.S. Fish and Wildlife Service Habitat and Population Evaluation Team","active":true,"usgs":false}],"preferred":false,"id":733671,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Austin, Jane E. 0000-0001-8775-2210 jaustin@usgs.gov","orcid":"https://orcid.org/0000-0001-8775-2210","contributorId":146411,"corporation":false,"usgs":true,"family":"Austin","given":"Jane","email":"jaustin@usgs.gov","middleInitial":"E.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":733672,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Carlisle, Martha J.","contributorId":204338,"corporation":false,"usgs":false,"family":"Carlisle","given":"Martha","email":"","middleInitial":"J.","affiliations":[{"id":36920,"text":"U.S. Fish and Wildlife Service Ecological Serv, NE field office","active":true,"usgs":false}],"preferred":false,"id":733673,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70196386,"text":"ofr20181053 - 2018 - A time-lapse gravity survey of the Coso geothermal field, China Lake Naval Air Weapons Station, California","interactions":[],"lastModifiedDate":"2018-04-19T16:26:41","indexId":"ofr20181053","displayToPublicDate":"2018-04-19T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1053","title":"A time-lapse gravity survey of the Coso geothermal field, China Lake Naval Air Weapons Station, California","docAbstract":"We have conducted a gravity survey of the Coso geothermal field to continue the time-lapse gravity study of the area initiated in 1991. In this report, we outline a method of processing the gravity data that minimizes the random errors and instrument bias introduced into the data by the Scintrex CG-5 relative gravimeters that were used. After processing, the standard deviation of the data was estimated to be ±13 microGals. These data reveal that the negative gravity anomaly over the Coso geothermal field, centered on gravity station CER1, is continuing to increase in magnitude over time. Preliminary modeling indicates that water-table drawdown at the location of CER1 is between 65 and 326 meters over the last two decades. We note, however, that several assumptions on which the model results depend, such as constant elevation and free-water level over the study period, still require verification.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181053","collaboration":"Prepared in cooperation with the U.S. Department of the Navy Geothermal Program Office","usgsCitation":"Phelps, G., Cronkite-Ratcliff, C., and Blake, K., 2018, A time-lapse gravity survey of the Coso geothermal field, China Lake Naval Air Weapons Station, California: U.S. Geological Survey Open-File Report 2018–1053, 25 p., https://doi.org/10.3133/ofr20181053.","productDescription":"Report: v, 25 p.; Table","numberOfPages":"31","onlineOnly":"Y","ipdsId":"IP-082096","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":353589,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1053/coverthb.jpg"},{"id":353590,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1053/ofr20181053.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1053"},{"id":353607,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2018/1053/ofr20181053_table1.xlsx","text":"Table 1","size":"22 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2018-1053"}],"country":"United States","state":"California","otherGeospatial":"Coso Geothermal Field, China Lake Naval Air Weapons Station","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118,\n 35.88682489453265\n ],\n [\n -117.625,\n 35.88682489453265\n ],\n [\n -117.625,\n 36.25\n ],\n [\n -118,\n 36.25\n ],\n [\n -118,\n 35.88682489453265\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Migrating adult Alewives Alosa pseudoharengus are a source of marine-derived nutrients on the East Coast of North America, importing nitrogen and phosphorus into freshwater habitats. Juvenile migrants subsequently transport freshwater-derived nutrients into the ocean. We developed a deterministic model to explore the theoretical nutrient dynamics of Alewife migrations at differing spawner abundances. Net nutrient balance was calculated relative to these abundances along the spawner–recruit curve. The ecological consequences of these subsidies in a particular watershed depend on the magnitude of adult escapement relative to the habitat’s carrying capacity for juveniles. At low escapement levels and assuming complete habitat access, the number of recruits produced per spawner was high and juvenile nutrient export dominated. At high escapement levels, fewer recruits were produced per spawner because recruitment is density dependent. As a result, adult nutrient import dominated. At varying levels of freshwater productivity and fisheries mortality for upstream spawners, this trend remained the same while the magnitude of the endpoints changed. Productivity level was the major determinant of export, while fisheries mortality had the strongest effect on adult import. The dynamics of this nutrient trade-off are important for managers to consider as a recovering population will likely shift from net export to net import as escapement increases. This transition will be sensitive to both harvest rates and to fish passage efficacy at dams and other barriers.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/mcf2.10021","usgsCitation":"Barber, B.L., Gibson, A.J., O’Malley, A., and Zydlewski, J.D., 2018, Does what go up also come down? Using a recruitment model to balance alewife nutrient import and export: Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science, v. 10, no. 2, p. 236-254, https://doi.org/10.1002/mcf2.10021.","productDescription":"19 p.","startPage":"236","endPage":"254","ipdsId":"IP-088585","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468822,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/mcf2.10021","text":"Publisher Index Page"},{"id":356605,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-17","publicationStatus":"PW","scienceBaseUri":"5b98a2d9e4b0702d0e842ff9","contributors":{"authors":[{"text":"Barber, Betsy L.","contributorId":207173,"corporation":false,"usgs":false,"family":"Barber","given":"Betsy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":743026,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gibson, A. Jamie","contributorId":207172,"corporation":false,"usgs":false,"family":"Gibson","given":"A.","email":"","middleInitial":"Jamie","affiliations":[],"preferred":false,"id":743027,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Malley, Andrew","contributorId":169716,"corporation":false,"usgs":false,"family":"O’Malley","given":"Andrew","email":"","affiliations":[],"preferred":false,"id":743028,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":742809,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196536,"text":"ofr20181069 - 2018 - Brown trout in the Lees Ferry reach of the Colorado River—Evaluation of causal hypotheses and potential interventions","interactions":[],"lastModifiedDate":"2024-03-04T18:53:45.200748","indexId":"ofr20181069","displayToPublicDate":"2018-04-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1069","title":"Brown trout in the Lees Ferry reach of the Colorado River—Evaluation of causal hypotheses and potential interventions","docAbstract":"Over the period 2014–2016, the number of nonnative brown trout (Salmo trutta) captured during routine monitoring in the Lees Ferry reach of the Colorado River, downstream of Glen Canyon Dam, began increasing. Management agencies and stakeholders have questioned whether the increase in brown trout in the Lees Ferry reach represents a threat to the endangered humpback chub (Gila cypha), to the rainbow trout (Oncorhynchus mykiss) sport fishery, or to other resources of concern. In this report, we evaluate the evidence for the expansion of brown trout in the Lees Ferry reach, consider a range of causal hypotheses for this expansion, examine the likely efficacy of several potential management interventions to reduce brown trout, and analyze the effects of those interventions on other resources of concern.
The brown trout population at Lees Ferry historically consisted of a small number of large fish supported by low levels of immigration from downstream reaches. This population is now showing signs of sustained successful reproduction and is on the cusp of recruiting locally hatched fish into the spawning class, based on analysis with a new integrated population model. The proximate causes of this change in status are a large pulse of immigration in the fall of 2014 and higher reproductive rates in 2015–2017. The ultimate causes of this change are not clear. The pulse of immigrants from downstream reaches in fall 2014 may have been induced by three sequential high-flow releases from the dam in November of 2012–2014, but may also have been the result of a unique set of circumstances unrelated to dam operations. The increase in reproduction may have been the result of any number of changes, including an Allee effect, warmer water temperatures, a decrease in competition from rainbow trout, or fall high-flow releases. Correlations over space and time among predictor variables do not allow us to make a clear inference about the cause of the changes. Under a null causal model, and without any changes to management, we predict there is a 36-percent chance the brown trout population at Lees Ferry will not show sustained growth, and will remain around a mean size of 5,800 adults, near its current size; in contrast, we predict there is a 64-percent chance that the population has a positive intrinsic growth rate and will increase 3–10 fold over the next 20 years. A humpback chub population model linked to the brown trout model suggests an increase of brown trout of this magnitude could lead to declines in the minimum adult humpback chub population over the same time period. Forecasts of rainbow trout abundance, however, suggest that increased abundance of brown trout in the Lees Ferry reach does not pose a threat to the rainbow trout fishery there.
There are interventions that may be effective in moderating the growth of the brown trout population in the Lees Ferry reach of the Colorado River. Across causal hypotheses, we predict that removal strategies (for example, a concerted electrofishing effort or an incentivized take program targeted at large brown trout) could reduce brown trout abundance by approximately 50 percent relative to status quo management. Reductions in the frequency or a change in the seasonal timing of high-flow releases from Glen Canyon Dam could be even more effective, but only under the causal hypotheses that involve effects of such releases on immigration or reproduction. Brown trout management flows— dam releases designed to strand young fish at a vulnerable stage—may be able to reduce brown trout abundance to some degree, but are not forecast to be the most effective strategy under any causal hypothesis.
We predict that the alternative management interventions would have effects on other resource goals as well, and the pattern of these effects differs across causal hypotheses. The removal strategies would incur direct costs (on the order of $7 million over 20 years) and the mechanical removal strategy is unethical from the perspective of several tribes. The strategies that involve reducing the frequency of high-flow releases from Glen Canyon Dam would decrease the ability to transport and store sediment in the ecosystem, potentially undermining goals associated with sandbar building, recreation, and riparian vegetation, but would increase hydropower revenue. Trout management flows would reduce hydropower revenue. From the standpoint of humpback chub, the alternative strategies largely follow the effect on brown trout; when brown trout abundance is reduced, predation pressure decreases, and humpback chub viability is predicted to increase, but the variation in predicted chub viability is not large across strategies or causal hypotheses.
To design a response to brown trout, management agencies will need to navigate both the tradeoffs among resources goals and the uncertainty in the causes of the brown trout expansion. Continued monitoring, possibly coupled with new research or experimental management actions that better inform demographic and ecological dynamics, can help to reduce the causal uncertainty.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181069","collaboration":"Prepared in cooperation with the National Park Service, U.S. Fish and Wildlife Service, Arizona Game and Fish Department, and the Western Area Power Administration","usgsCitation":"Runge, M.C., Yackulic, C.B., Bair, L.S., Kennedy, T.A., Valdez, R.A., Ellsworth, C., Kershner J.L., Rogers, R.S., Trammell, M.A., and Young, K.L., 2018, Brown trout in the Lees Ferry reach of the Colorado River—Evaluation of causal hypotheses and potential interventions: U.S. Geological Survey Open-File Report 2018–1069, 83 p.,\nhttps://doi.org/10.3133/ofr20181069.","productDescription":"ix, 83 p.","numberOfPages":"94","onlineOnly":"Y","ipdsId":"IP-095595","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":353922,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FN15HC","linkHelpText":"Population dynamics of humpback chub, rainbow trout and brown trout in the Colorado River in its Grand Canyon Reach: modelling code and input data"},{"id":353488,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1069/ofr20181069.pdf","text":"Report","size":"2.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1069"},{"id":353487,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1069/coverthb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.59500122070312,\n 36.834843899148495\n ],\n [\n -111.47209167480469,\n 36.834843899148495\n ],\n [\n -111.47209167480469,\n 36.946599271636295\n ],\n [\n -111.59500122070312,\n 36.946599271636295\n ],\n [\n -111.59500122070312,\n 36.834843899148495\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road, Ste 4039
Laurel, MD 20708-4039
The purpose of this report is to present recently acquired as well as previously published geochemical and modal petrographic data for igneous rocks in the St. Francois Mountains, southeast Missouri, as part of an ongoing effort to understand the regional geology and ore deposits of the Mesoproterozoic basement rocks of southeast Missouri, USA. The report includes geochemical data that is (1) newly acquired by the U.S. Geological Survey and (2) compiled from numerous sources published during the last fifty-five years. These data are required for ongoing petrogenetic investigations of these rocks. Voluminous Mesoproterozoic igneous rocks in the St. Francois Mountains of southeast Missouri constitute the basement buried beneath Paleozoic sedimentary rock that is over 600 meters thick in places. The Mesoproterozoic rocks of southeast Missouri represent a significant component of approximately 1.4 billion-year-old (Ga) igneous rocks that crop out extensively in North America along the southeast margin of Laurentia and subsequent researchers suggested that iron oxide-copper deposits in the St. Francois Mountains are genetically associated with ca. 1.4 Ga magmatism in this region. The geochemical and modal data sets described herein were compiled to support investigations concerning the tectonic setting and petrologic processes responsible for the associated magmatism.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1080","usgsCitation":"du Bray, E.A. Day, W.C., and Meighan, C.J., 2018,Compilation of new and previously published geochemical and modal data for Mesoproterozoic igneous rocks of the St. Francois Mountains, southeast Missouri: U.S. Geological Survey Data Series 1080, 10 p., https://doi.org/10.3133/ds1080.","productDescription":"Report: iv, 10 p.; Appendixes; Data Release; Read Me","onlineOnly":"Y","ipdsId":"IP-090393","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":353360,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F79W0DSN","text":"USGS data release","linkHelpText":"Data release supporting compilation of new and previously published geochemical and modal data for Mesoproterozoic igneous rocks of the St. Francois Mountains, southeast Missouri"},{"id":353322,"rank":8,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/1080/ds1080_ReadMe.txt","text":"Read Me","size":"8.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"DS 1080 Read Me"},{"id":353316,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1080/ds1080.pdf","text":"Report","size":"48.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1080"},{"id":353317,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1080/ds1080_appendix1_MO15_17_Field_Notes.txt","text":"Appendix 1. Field Notes","size":"16.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"DS 1080 Field Notes, Text File","linkHelpText":"Definition and characterization of data fields for field notes for igneous rocks of the St. Francois Mountains, southeast Missouri collected between 2015 and 2017 (text file)"},{"id":353320,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1080/ds1080_appendix2_SE_MO_ChemData_AlteredMineralized.txt","text":"Appendix 2. Chemical Data, Altered Mineralized","size":"348 kB","linkFileType":{"id":2,"text":"txt"},"description":"DS 1080 Chemical Data, Altered Mineralized","linkHelpText":"Definition and characterization of data fields for geochemical and modal data for igneous rocks in the St. Francois Mountains, southeast Missouri (text file)"},{"id":353315,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1080/coverthb.jpg"},{"id":353321,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1080/ds1080_appendix2_SE_MO_ChemData_FreshUnaltered.txt","text":"Appendix 2. Chemical Data, Fresh Unaltered","size":"256 kB","linkFileType":{"id":2,"text":"txt"},"description":"DS 1080 Chemical Data, Fresh Unaltered","linkHelpText":"Definition and characterization of data fields for geochemical and modal data for igneous rocks in the St. Francois Mountains, southeast Missouri (text file)"},{"id":353319,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1080/ds1080_appendix2_SE_MO_ChemData.xlsx","text":"Appendix 2. Chemical Data","size":"692 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 1080 Chemical Data","linkHelpText":"Definition and characterization of data fields for geochemical and modal data for igneous rocks in the St. Francois Mountains, southeast Missouri (Excel file)"},{"id":353318,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1080/ds1080_appendix1_MO15_17_Field_Notes.xlsx","text":"Appendix 1. Field Notes","size":"28.0 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 1080 Field Notes, Excel File","linkHelpText":"Definition and characterization of data fields for field notes for igneous rocks of the St. Francois Mountains, southeast Missouri collected between 2015 and 2017 (Excel file)"}],"country":"United States","state":"Missouri","otherGeospatial":"St. Francois Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.603759765625,\n 36.848856608486905\n ],\n [\n -89.98901367187499,\n 36.848856608486905\n ],\n [\n -89.98901367187499,\n 38.496593518947584\n ],\n [\n -92.603759765625,\n 38.496593518947584\n ],\n [\n -92.603759765625,\n 36.848856608486905\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geology, Geophysics and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS-973
Denver, CO 80225-0046
This study examined titanium distribution in the Atlantic Coastal Plain of the southeastern United States; the titanium is found in heavy-mineral sands that include the minerals ilmenite (Fe2+TiO3), rutile (TiO2), or leucoxene (an alteration product of ilmenite). Deposits of heavy-mineral sands in ancient and modern coastal plains are a significant feedstock source for the titanium dioxide pigments industry. Currently, two heavy-mineral sands mining and processing operations are active in the southeast United States producing concentrates of ilmenite-leucoxene, rutile, and zircon. The results of this study indicate the potential for similar deposits in many areas of the Atlantic Coastal Plain.
This study used the titanium analyses of 3,457 stream sediment samples that were analyzed as part of the U.S. Geological Survey’s National Geochemical Survey program. This data set was analyzed by an integrated spatial modeling technique known as Bayesian hierarchical modeling to map the regional-scale, spatial distribution of titanium concentrations. In particular, clusters of anomalous concentrations of titanium occur: (1) along the Fall Zone, from Virginia to Alabama, where metamorphic and igneous rocks of the Piedmont region contact younger sediments of the Coastal Plain; (2) a paleovalley near the South Carolina and North Carolina border; (3) the upper and middle Atlantic Coastal Plain of North Carolina; (4) the majority of the Atlantic Coastal Plain of Virginia; and (5) barrier islands and stretches of the modern shoreline from South Carolina to northeast Florida. The areas mapped by this study could help mining companies delimit areas for exploration.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185045","usgsCitation":"Van Gosen, B.S, and Ellefsen, K.J., 2018, Titanium mineral resources in heavy-mineral sands in the Atlantic coastal plain of the southeastern United States: U.S. Geological Survey Scientific Investigations Report 2018–5045, 32 p., https://doi.org/10.3133/sir20185045.","productDescription":"Report: v, 32 p.; Read Me; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-092420","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":353350,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7J38R16","text":"USGS data release","linkHelpText":"Titanium concentrations in stream sediments from the Atlantic Coastal Plain of the southeastern U.S. (1975-1999)"},{"id":353348,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5045/coverthb.jpg"},{"id":353349,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5045/sir20185045.pdf","text":"Report","size":"19.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5045"},{"id":353352,"rank":4,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2018/5045/sir20185045_Readme.txt","text":"Read Me","size":"8.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2018–5045 Read Me"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.3552303599749,\n 29.6305\n ],\n [\n -76.0284,\n 29.6305\n ],\n [\n -76.0284,\n 38.4013255312409\n ],\n [\n -88.3552303599749,\n 38.4013255312409\n ],\n [\n -88.3552303599749,\n 29.6305\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS 973
Denver, CO 80225
Major and trace element and radiogenic isotopic characteristics of primitive mafic Pleistocene and Holocene lavas from Newberry Volcano, Oregon, define two groups. The first consists of dry tholeiitic high-alumina olivine basalts that are slightly enriched in highly incompatible elements. The second group consists of calc-alkaline basalts that contained 2–4 wt % H2O prior to eruption and shows strong enrichment in the light rare earth elements, Ba, and Sr, and deficits in Nb, Ta, Hf, and Zr. The tholeiitic basalts reflect 6–11% anhydrous adiabatic decompression melting of spinel peridotite. The calc-alkaline basalts derived from compositionally distinct sources with strong LIL enrichment and relative depletion in HFSE, but with Sr, Nd, Hf, and Pb isotopic composition only slightly distinct from the sources of the tholeiitic magmas. Radiogenic Os correlates with LREE enrichment in the calc-alkaline magmas, which indicates that their source materials include a contribution from a mafic component that was melted in the garnet stability field. The calc-alkaline magmas were derived by melting of peridotite metasomatized by a fluid/melt that originated by melting of a mixture of the sediment plus MORB basalt/mantle in the underlying subducting oceanic plate. While the trace element characteristics of the calc-alkaline magmas were determined by the subduction component, their isotopic characteristics were modified during transit through the mantle by interaction with the highly magmatically processed mantle wedge beneath Newberry Volcano that, without the slab component, serves as the source of the tholeiitic magmas.
Healthy streams and the fish and other organisms that live in them contribute to our quality of life. Extensive modification of the landscape in the Midwestern United States, however, has profoundly affected the condition of streams. Row crops and pavement have replaced grasslands and woodlands, streams have been straightened, and wetlands and fields have been drained. Runoff from agricultural and urban land brings sediment and chemicals to streams. What is the chemical, physical, and biological condition of Midwestern streams? Which physical and chemical stressors are adversely affecting biological communities, what are their origins, and how might we lessen or avoid their adverse effects?
In 2013, the U.S. Geological Survey (USGS) conducted the Midwest Stream Quality Assessment to evaluate how human activities affect the biological condition of Midwestern streams. In collaboration with the U.S. Environmental Protection Agency National Rivers and Streams Assessment, the USGS sampled 100 streams, chosen to be representative of the different types of watersheds in the region. Biological condition was evaluated based on the number and diversity of fish, algae, and invertebrates in the streams. Changes to the physical habitat and chemical characteristics of the streams—“stressors”—were assessed, and their relation to landscape factors and biological condition was explored by using mathematical models. The data and models help us to better understand how the human activities on the landscape are affecting streams in the region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173087","usgsCitation":"Van Metre, P.C., Mahler, B.J., Carlisle, Daren, and Coles, James, 2018, The Midwest Stream Quality Assessment—Influences of human activities on streams: U.S. Geological Survey Fact Sheet 2017–3087, 6 p., https://doi.org/10.3133/fs20173087.","productDescription":"6 p.","onlineOnly":"N","ipdsId":"IP-087878","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":350638,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3087/coverthb2.jpg"},{"id":350639,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3087/fs20173087.pdf","text":"Report","size":"2.53 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017–3087"},{"id":350640,"rank":3,"type":{"id":18,"text":"Project Site"},"url":"https://water.usgs.gov/nawqa/","text":"National Water-Quality Assessment (NAWQA) Project"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.525390625,\n 36.756490329505176\n ],\n [\n -81.93603515625,\n 36.756490329505176\n ],\n [\n -81.93603515625,\n 45.166547157856016\n ],\n [\n -98.525390625,\n 45.166547157856016\n ],\n [\n -98.525390625,\n 36.756490329505176\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"National Water-Quality Assessment (NAWQA) Project
U.S. Geological Survey
413 National Center
12201 Sunrise Valley Drive
Reston, Virginia 20192
Beginning in 2014, the U.S. Geological Survey, in collaboration with Bloom Biological, Inc., began telemetry research on golden eagles (Aquila chrysaetos) captured in the San Diego, Orange, and western Riverside Counties of southern California. This work was supported by the San Diego Association of Governments, California Department of Fish and Wildlife, the U.S. Fish and Wildlife Service, the Bureau of Land Management, and the U.S. Geological Survey. Since 2014, we have tracked more than 40 eagles, although this report focuses only on San Diego County eagles.
An important objective of this research is to develop habitat selection models for golden eagles. Here we provide predictions of population-level habitat selection for golden eagles in San Diego County based on environmental covariates related to land use and terrain.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181067","collaboration":"Prepared in cooperation with San Diego Association of Governments, U.S. Fish and Wildlife Service, Bureau of Land Management, California Department of Fish and Wildlife","usgsCitation":"Tracey, J.A., Madden, M.C., Bloom, P.H., Katzner, T.E., and Fisher, R.N., 2018, Golden eagle (Aquila chrysaetos) habitat selection as a function of land use and terrain, San Diego County, California: U.S. Geological Survey Open-File Report 2018–1067, 13 p., https://doi.org/10.3133/ofr20181067.","productDescription":"Report: iv, 13 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-096732","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":353465,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OZVGEG","text":"USGS data release","description":"USGS Data 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Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive
Sacramento, California 95819
Biodegradation of contaminants can increase the temperature in the subsurface due to heat generated from exothermic reactions, making temperature observations a potentially low-cost approach for determining microbial activity. For this technique to gain more widespread acceptance, it is necessary to better understand all the factors affecting the measured temperatures. Biodegradation has been occurring at a crude oil-contaminated site near Bemidji, Minnesota for 39 years, creating a quasi-steady-state plume of contaminants and degradation products. A model of subsurface heat generation and transport helps elucidate the contribution of microbial and infrastructure heating to observed temperature increases at this site. We created a steady-state, two-dimensional, heat transport model using previous-published parameter values for physical, chemical and biodegradation properties. Simulated temperature distributions closely match the observed average annual temperatures measured in the contaminated area at the site within less than 0.2 °C in the unsaturated zone and 0.4 °C in the saturated zone. The model results confirm that the observed subsurface heat from microbial activity is due primarily to methane oxidation in the unsaturated zone resulting in a 3.6 °C increase in average annual temperature. Another important source of subsurface heat is from the active, crude-oil pipelines crossing the site. The pipelines impact temperatures for a distance of 200 m and contribute half the heat. Model results show that not accounting for the heat from the pipelines leads to overestimating the degradation rates by a factor of 1.7, demonstrating the importance of identifying and quantifying all heat sources. The model results also highlighted a zone where previously unknown microbial activity is occurring at the site.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jconhyd.2018.03.011","usgsCitation":"Warren, E., and Bekins, B.A., 2018, Relative contributions of microbial and infrastructure heat at a crude oil-contaminated site: Journal of Contaminant Hydrology, v. 211, p. 94-103, https://doi.org/10.1016/j.jconhyd.2018.03.011.","productDescription":"10 p.","startPage":"94","endPage":"103","ipdsId":"IP-091056","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":355636,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","county":"Beltrami County","city":"Bemidji","volume":"211","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e598e4b060350a15d1e2","contributors":{"authors":[{"text":"Warren, Ean 0000-0002-2634-8289 ewarren@usgs.gov","orcid":"https://orcid.org/0000-0002-2634-8289","contributorId":206234,"corporation":false,"usgs":true,"family":"Warren","given":"Ean","email":"ewarren@usgs.gov","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":739851,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bekins, Barbara A. 0000-0002-1411-6018 babekins@usgs.gov","orcid":"https://orcid.org/0000-0002-1411-6018","contributorId":1348,"corporation":false,"usgs":true,"family":"Bekins","given":"Barbara","email":"babekins@usgs.gov","middleInitial":"A.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":739852,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70196557,"text":"70196557 - 2018 - Landscape connectivity for bobcat (Lynx rufus) and lynx (Lynx canadensis) in the Northeastern United States","interactions":[],"lastModifiedDate":"2018-04-16T17:15:30","indexId":"70196557","displayToPublicDate":"2018-04-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Landscape connectivity for bobcat (Lynx rufus) and lynx (Lynx canadensis) in the northeastern United States","title":"Landscape connectivity for bobcat (Lynx rufus) and lynx (Lynx canadensis) in the Northeastern United States","docAbstract":"Landscape connectivity is integral to the persistence of metapopulations of wide ranging carnivores and other terrestrial species. The objectives of this research were to investigate the landscape characteristics essential to use of areas by lynx and bobcats in northern New England, map a habitat availability model for each species, and explore connectivity across areas of the region likely to experience future development pressure. A Mahalanobis distance analysis was conducted on location data collected between 2005 and 2010 from 16 bobcats in western Vermont and 31 lynx in northern Maine to determine which variables were most consistent across all locations for each species using three scales based on average 1) local (15 minute) movement, 2) linear distance between daily locations, and 3) female home range size. The bobcat model providing the widest separation between used locations and random study area locations suggests that they cue into landscape features such as edge, availability of cover, and development density at different scales. The lynx model with the widest separation between random and used locations contained five variables including natural habitat, cover, and elevation—all at different scales. Shrub scrub habitat—where lynx’s preferred prey is most abundant—was represented at the daily distance moved scale. Cross validation indicated that outliers had little effect on models for either species. A habitat suitability value was calculated for each 30 m2 pixel across Vermont, New Hampshire, and Maine for each species and used to map connectivity between conserved lands within selected areas across the region. Projections of future landscape change illustrated potential impacts of anthropogenic development on areas lynx and bobcat may use, and indicated where connectivity for bobcats and lynx may be lost. These projections provided a guide for conservation of landscape permeability for lynx, bobcat, and species relying on similar habitats in the region.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0194243","usgsCitation":"Farrell, L.E., Levy, D.M., Donovan, T.M., Mickey, R.M., Howard, A., Vashon, J., Freeman, M., Royar, K., and Kilpatrick, C.W., 2018, Landscape connectivity for bobcat (Lynx rufus) and lynx (Lynx canadensis) in the Northeastern United States: PLoS ONE, v. 13, no. 3, p. 1-25, https://doi.org/10.1371/journal.pone.0194243.","productDescription":"e0194243; 25 p.","startPage":"1","endPage":"25","ipdsId":"IP-043926","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468826,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0194243","text":"Publisher Index Page"},{"id":353475,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Jennifer","contributorId":204306,"corporation":false,"usgs":false,"family":"Vashon","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":733602,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Freeman, Mark","contributorId":171650,"corporation":false,"usgs":false,"family":"Freeman","given":"Mark","email":"","affiliations":[],"preferred":false,"id":733603,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Royar, Kim","contributorId":9886,"corporation":false,"usgs":true,"family":"Royar","given":"Kim","affiliations":[],"preferred":false,"id":733604,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kilpatrick, C. William","contributorId":204307,"corporation":false,"usgs":false,"family":"Kilpatrick","given":"C.","email":"","middleInitial":"William","affiliations":[],"preferred":false,"id":733605,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70195023,"text":"sir20185024 - 2018 - Evaluating the potential for near-shore bathymetry on the Majuro Atoll, Republic of the Marshall Islands, using Landsat 8 and WorldView-3 imagery","interactions":[],"lastModifiedDate":"2019-12-30T11:31:34","indexId":"sir20185024","displayToPublicDate":"2018-04-16T00:00:00","publicationYear":"2018","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":"2018-5024","title":"Evaluating the potential for near-shore bathymetry on the Majuro Atoll, Republic of the Marshall Islands, using Landsat 8 and WorldView-3 imagery","docAbstract":"Satellite-derived near-shore bathymetry (SDB) is becoming an increasingly important method for assessing vulnerability to climate change and natural hazards in low-lying atolls of the northern tropical Pacific Ocean. Satellite imagery has become a cost-effective means for mapping near-shore bathymetry because ships cannot collect soundings safely while operating close to the shore. Also, green laser light detection and ranging (lidar) acquisitions are expensive in remote locations. Previous research has demonstrated that spectral band ratio-based techniques, commonly called the natural logarithm approach, may lead to more precise measurements and modeling of bathymetry because of the phenomenon that different substrates at the same depth have approximately equal ratio values. The goal of this research was to apply the band ratio technique to Landsat 8 at-sensor radiance imagery and WorldView-3 atmospherically corrected imagery in the coastal waters surrounding the Majuro Atoll, Republic of the Marshall Islands, to derive near-shore bathymetry that could be incorporated into a seamless topobathymetric digital elevation model of Majuro. Attenuation of light within the water column was characterized by measuring at-sensor radiance and reflectance at different depths and calculating an attenuation coefficient. Bathymetric lidar data, collected by the U.S. Naval Oceanographic Office in 2006, were used to calibrate the SDB results. The bathymetric lidar yielded a strong linear relation with water depths. The Landsat 8-derived SDB estimates derived from the blue/green band ratio exhibited a water attenuation extinction depth of 6 meters with a coefficient of determination R2=0.9324. Estimates derived from the coastal/red band ratio had an R2=0.9597. At the same extinction depth, SDB estimates derived from WorldView-3 imagery exhibited an R2=0.9574. Because highly dynamic coastal shorelines can be affected by erosion, wetland loss, hurricanes, sea-level rise, urban development, and population growth, consistent bathymetric data are needed to better understand sensitive coastal land/water interfaces in areas subject to coastal disasters.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185024","usgsCitation":"Poppenga, S.K., Palaseanu-Lovejoy, M., Gesch, D.B., Danielson, J.J., and Tyler, D.J., 2018, Evaluating the potential for near-shore bathymetry on the Majuro Atoll, Republic of the Marshall Islands, using Landsat 8 and WorldView-3 imagery: U.S. Geological Survey Scientific Investigations Report 2018–5024, 14 p., https://doi.org/10.3133/sir20185024.","productDescription":"Report: vii, 14 p.; Data Release","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-092726","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":353367,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7416VXX","text":"USGS data release","description":"USGS Data Release","linkHelpText":"One Meter Topobathymetric Digital Elevation Model for Majuro Atoll, Republic of the Marshall Islands, 1944 to 2016"},{"id":353365,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5024/coverthb2.jpg"},{"id":353366,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5024/sir20185024.pdf","text":"Report","size":"3.28 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5024"}],"country":"Republic of the Marshall Islands","otherGeospatial":"Majuro Atoll","contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center, in cooperation with the U.S. Army Corps of Engineers, Mobile District, conducted bathymetric surveys of the nearshore waters surrounding Ship and Horn Islands, Gulf Islands National Seashore, Mississippi. The objective of this study was to establish base-level elevation conditions around West Ship, East Ship, and Horn Islands and their associated active littoral system prior to restoration activities. These activities include the closure of Camille Cut and the placement of sediment in the littoral zone of East Ship Island. These surveys can be compared with future surveys to monitor sediment migration patterns post-restoration and can also be measured against historic bathymetric datasets to further our understanding of island evolution.
The USGS collected 667 line-kilometers (km) of single-beam bathymetry data and 844 line-km of interferometric swath bathymetry data in July 2016 under Field Activity Number 2016-347-FA. Data are provided in three datums: (1) the International Terrestrial Reference Frame of 2000 (ellipsoid height); (2) the North American Datum of 1983 (NAD83) CORS96 realization and the North American Vertical Datum of 1988 with respect to the GEOID12B model (orthometric height); and (3) NAD83 (CORS96) and Mean Lower Low Water (tidal datum). Data products, including x,y,zpoint datasets, trackline shapefiles, digital and handwritten Field Activity Collection Systems logs, 50-meter digital elevation model, and formal Federal Geographic Data Committee metadata, are available for download.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1081","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Mobile District","usgsCitation":"DeWitt, N.T., Stalk, C.A., Fredericks, J.J., Flocks, J.G., Kelso, K.W., Farmer, A.S., Tuten, T.M., and Buster, N.A., 2018, Nearshore coastal bathymetry data collected in 2016 from West Ship Island to Horn Island, Gulf Islands National Seashore, Mississippi: U.S. Geological Survey Data Series 1081, https://doi.org/10.3133/ds1081.","productDescription":"HTML Document; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-092109","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":353362,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1081/coverthb.jpg"},{"id":353364,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://coastal.er.usgs.gov/data-release/doi-F7B8571Q/","text":"USGS data release","description":"USGS data release","linkHelpText":"Coastal Bathymetry Data Collected in 2016 nearshore from West Ship Island to Horn Island, Gulf Islands National Seashore, Mississippi"},{"id":353363,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1081/","text":"Report HTML","linkFileType":{"id":5,"text":"html"},"description":"DS 1081"}],"country":"United States","state":"Mississippi","otherGeospatial":"Horn Islands, Gulf Islands National Seashore","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.02359008789062,\n 30.173624550358536\n ],\n [\n -88.50311279296875,\n 30.173624550358536\n ],\n [\n -88.50311279296875,\n 30.28634573802957\n ],\n [\n -89.02359008789062,\n 30.28634573802957\n ],\n [\n -89.02359008789062,\n 30.173624550358536\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th St. South
St. Petersburg, FL 33701
One important, almost ubiquitous, tool for understanding the surfaces of solid bodies throughout the solar system is the study of impact craters. While measuring a distribution of crater diameters and locations is an important tool for a wide variety of studies, so too is measuring a crater's “depth.” Depth can inform numerous studies including the strength of a surface and modification rates in the local environment. There is, however, no standard data set, definition, or technique to perform this data‐gathering task, and the abundance of different definitions of “depth” and methods for estimating that quantity can lead to misunderstandings in and of the literature. In this review, we describe a wide variety of data sets and methods to analyze those data sets that have been, are currently, or could be used to derive different types of crater depth measurements. We also recommend certain nomenclature in doing so to help standardize practice in the field. We present a review section of all crater depths that have been published on different solar system bodies which shows how the field has evolved through time and how some common assumptions might not be wholly accurate. We conclude with several recommendations for researchers which could help different data sets to be more easily understood and compared.
","language":"English","publisher":"Wiley","doi":"10.1111/maps.12956","usgsCitation":"Robbins, S.J., Watters, W.A., Chappelow, J.E., Bray, V.J., Daubar, I.J., Craddock, R.A., Beyer, R.A., Landis, M., Ostrach, L.R., Tornabene, L.L., Riggs, J.D., and Weaver, B.P., 2018, Measuring impact crater depth throughout the solar system: Meteoritics and Planetary Science, v. 53, no. 4, p. 583-637, https://doi.org/10.1111/maps.12956.","productDescription":"55 p.","startPage":"583","endPage":"637","ipdsId":"IP-080986","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":468829,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/maps.12956","text":"Publisher Index Page"},{"id":353424,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-20","publicationStatus":"PW","scienceBaseUri":"5afee6dbe4b0da30c1bfbebc","contributors":{"authors":[{"text":"Robbins, Stuart J.","contributorId":204229,"corporation":false,"usgs":false,"family":"Robbins","given":"Stuart","email":"","middleInitial":"J.","affiliations":[{"id":36712,"text":"Southwest Research Institute","active":true,"usgs":false}],"preferred":false,"id":733446,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Watters, Wesley A.","contributorId":204230,"corporation":false,"usgs":false,"family":"Watters","given":"Wesley","email":"","middleInitial":"A.","affiliations":[{"id":36886,"text":"Whitin Observatory, Department of Astronomy, Wellesley College","active":true,"usgs":false}],"preferred":false,"id":733447,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chappelow, John E.","contributorId":204231,"corporation":false,"usgs":false,"family":"Chappelow","given":"John","email":"","middleInitial":"E.","affiliations":[{"id":36887,"text":"Meteorifics Inc.","active":true,"usgs":false}],"preferred":false,"id":733448,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bray, Veronica J.","contributorId":204232,"corporation":false,"usgs":false,"family":"Bray","given":"Veronica","email":"","middleInitial":"J.","affiliations":[{"id":36888,"text":"Lunar and Planetary Laboratory, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":733449,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Daubar, Ingrid J.","contributorId":204233,"corporation":false,"usgs":false,"family":"Daubar","given":"Ingrid","email":"","middleInitial":"J.","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":733450,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Craddock, Robert A.","contributorId":204234,"corporation":false,"usgs":false,"family":"Craddock","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":36889,"text":"Center for Earth and Planetary Studies, National Air and Space Museum, MRC-315, Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":733451,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Beyer, Ross A.","contributorId":204235,"corporation":false,"usgs":false,"family":"Beyer","given":"Ross","email":"","middleInitial":"A.","affiliations":[{"id":36890,"text":"Sagan Center at the SETI Institute and NASA Ames Research Center","active":true,"usgs":false}],"preferred":false,"id":733452,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Landis, Margaret E.","contributorId":176713,"corporation":false,"usgs":false,"family":"Landis","given":"Margaret E.","affiliations":[{"id":25655,"text":"Lunar and Planetary Laboratory, 1629 E. University Blvd., The University of Arizona, Tucson, AZ 85721, United States","active":true,"usgs":false}],"preferred":false,"id":733453,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ostrach, Lillian R. 0000-0002-3107-7321 lostrach@usgs.gov","orcid":"https://orcid.org/0000-0002-3107-7321","contributorId":193078,"corporation":false,"usgs":true,"family":"Ostrach","given":"Lillian","email":"lostrach@usgs.gov","middleInitial":"R.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":733445,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Tornabene, Livio L.","contributorId":203691,"corporation":false,"usgs":false,"family":"Tornabene","given":"Livio","email":"","middleInitial":"L.","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":733454,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Riggs, Jamie D.","contributorId":204236,"corporation":false,"usgs":false,"family":"Riggs","given":"Jamie","email":"","middleInitial":"D.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":733455,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Weaver, Brian P.","contributorId":204237,"corporation":false,"usgs":false,"family":"Weaver","given":"Brian","email":"","middleInitial":"P.","affiliations":[{"id":36891,"text":"Statistical Sciences, CCS-6, Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":733456,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70196530,"text":"70196530 - 2018 - Climate stability in Central Anatolia during the Messinian Salinity Crisis","interactions":[],"lastModifiedDate":"2018-04-13T12:28:11","indexId":"70196530","displayToPublicDate":"2018-04-13T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2996,"text":"Palaeogeography, Palaeoclimatology, Palaeoecology","printIssn":"0031-0182","active":true,"publicationSubtype":{"id":10}},"title":"Climate stability in Central Anatolia during the Messinian Salinity Crisis","docAbstract":"Deposition of large amounts of evaporites and erosion of deep canyons within the Mediterranean Basin as a result of reduced basin connectivity with the Atlantic Ocean and the epicontinental Paratethys Sea characterized the Messinian Salinity Crisis (MSC, 5.97–5.33 Ma). The influence of the MSC on Mediterranean environmental conditions within the basin itself has been intensely studied from marine records, but reconstructing the impact of the MSC on circum-Mediterranean continental climate has been hampered by the absence of continuous sedimentary archives that span the duration of the event.
Here, we report results of a continental record of carbon (δ13C) and oxygen (δ18O) isotopes from lake carbonates framed by new magnetostratigraphic and 40Ar/39Ar dating, as well as by existing mammal stratigraphy (Kangal Basin, central Anatolia). The sampled section records continuous fluvio-lacustrine sedimentation from ~6.6 Ma to 4.9 Ma, which spans the MSC and the Miocene-Pliocene boundary. This dataset so far represents the only continuous continental paleoenvironmental record of the MSC in the circum-Mediterranean realm.
The Kangal Basin isotope record indicates a low degree of evaporation. Furthermore, covariance between δ13C and δ18O suggests a coupling between lake water balance and biologic productivity. Variations in δ13C and δ18O therefore likely reflect changes in the amount of incoming precipitation, rather than changes in δ18O values of incoming precipitation. The most prominent spike in δ13C and δ18O occurs during the acme of the MSC and is therefore interpreted to have resulted from a decrease in the amount of incoming moisture correlative to a period of vigorous erosion and sea level lowering in the Mediterranean Basin. Major sea level lowering of Mediterranean basin waters during the acme of the MSC could have therefore led to slightly dryer conditions over Anatolia, which is also suggested by modeling studies. Overall, changes in δ13C and δ18O values are small. Therefore, we surmise that the MSC had limited effects on the paleoenvironmental and paleoclimatic conditions in the Anatolian interior.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.palaeo.2018.03.001","usgsCitation":"Meijers, M.J., Peynircioglu, A.A., Cosca, M.A., Brocard, G.Y., Whitney, D.L., Langereis, C.G., and Mulch, A., 2018, Climate stability in Central Anatolia during the Messinian Salinity Crisis: Palaeogeography, Palaeoclimatology, Palaeoecology, v. 498, p. 53-67, https://doi.org/10.1016/j.palaeo.2018.03.001.","productDescription":"15 p.","startPage":"53","endPage":"67","ipdsId":"IP-095374","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":468827,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://dspace.library.uu.nl/handle/1874/363327","text":"External Repository"},{"id":353419,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 37.4,\n 39\n ],\n [\n 36.70,\n 39\n ],\n [\n 36.70,\n 40\n ],\n [\n 37.4,\n 40\n ],\n [\n 37.4,\n 39\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"498","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6dbe4b0da30c1bfbebe","contributors":{"authors":[{"text":"Meijers, Maud J.M.","contributorId":204225,"corporation":false,"usgs":false,"family":"Meijers","given":"Maud","email":"","middleInitial":"J.M.","affiliations":[{"id":36884,"text":"University of Frankfurt","active":true,"usgs":false}],"preferred":false,"id":733427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peynircioglu, Ahmet A","contributorId":204226,"corporation":false,"usgs":false,"family":"Peynircioglu","given":"Ahmet","email":"","middleInitial":"A","affiliations":[{"id":36885,"text":"Utrecht University","active":true,"usgs":false}],"preferred":false,"id":733428,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cosca, Michael A. 0000-0002-0600-7663 mcosca@usgs.gov","orcid":"https://orcid.org/0000-0002-0600-7663","contributorId":1000,"corporation":false,"usgs":true,"family":"Cosca","given":"Michael","email":"mcosca@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":733426,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brocard, Gilles Y.","contributorId":204227,"corporation":false,"usgs":false,"family":"Brocard","given":"Gilles","email":"","middleInitial":"Y.","affiliations":[{"id":16979,"text":"University of Pennsylvania","active":true,"usgs":false}],"preferred":false,"id":733429,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Whitney, Donna L.","contributorId":187715,"corporation":false,"usgs":false,"family":"Whitney","given":"Donna","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":733430,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Langereis, Cor G.","contributorId":204228,"corporation":false,"usgs":false,"family":"Langereis","given":"Cor","email":"","middleInitial":"G.","affiliations":[{"id":36885,"text":"Utrecht University","active":true,"usgs":false}],"preferred":false,"id":733431,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mulch, Andreas","contributorId":194317,"corporation":false,"usgs":false,"family":"Mulch","given":"Andreas","email":"","affiliations":[],"preferred":false,"id":733432,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}