{"pageNumber":"246","pageRowStart":"6125","pageSize":"25","recordCount":46679,"records":[{"id":70248918,"text":"70248918 - 2020 - Local magnitude, coda magnitude, and radiated energy of volcanic tectonic earthquakes from October 2010 to December 2011 at Sinabung volcano, Indonesia","interactions":[],"lastModifiedDate":"2023-09-26T12:17:04.967803","indexId":"70248918","displayToPublicDate":"2020-05-18T07:13:08","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Local magnitude, coda magnitude, and radiated energy of volcanic tectonic earthquakes from October 2010 to December 2011 at Sinabung volcano, Indonesia","docAbstract":"

In August 2010, Sinabung volcano began erupting after more than a thousand years of dormancy. Following several weeks of phreatic eruptions, the eruptions ceased and Sinabung entered what became an inter-eruptive period of dominantly seismic unrest. While standard equations for understanding the size of an earthquake (local magnitude (ML), coda magnitude (MC), and seismic energy release (ER)) have long been developed, it is best practice to fine tune these relations for a given region and period of study to more accurately describe seismicity and to directly compare it with other volcanic systems. More accurate descriptions of magnitudes and energy release are vital to accurate volcanic eruption forecasting and evaluation of seismic and volcanic risk. In this study, we use high-frequency volcano-tectonic (VT) earthquakes recorded on a temporary three-component network installed between October 2010 and December 2011 in the region around Sinabung volcano to better constrain the seismic parameters of and better understand this previously unstudied volcano. We determine region-specific formulas for ML, MC, and ER as follows:

ML=log10A+1.1252log10r+0.0280 r−2.5427,MC=0.7764 log10tcoda+0.0676 r−0.7185,andlog10(ER)=1.5720ML+11.5258,

where A, r, and tcoda are maximum amplitude on a Wood-Anderson seismogram, hypocentral distance (km), and the coda duration (s), respectively. Constants in the ML equation have physically interpretable meanings. The constant for the geometrical spreading term (log10r term) equals one for perfect spherical spreading of the waveform. Our value is greater than one and thus suggests that wavefronts spread at a slightly different rate than for simple spherical spreading. The constant for the attenuation term (r term) is consistent with locally mapped attenuative deposits (limestones and tuffs) and previous 3D tomographic results. Our MC equation differs from a previous study, likely because different data in a different time period were used. Earthquake hypocenters are consistent with those located in previous tomographic studies, and we interpret the earthquakes in this study as distal VT earthquakes induced by continued magmatic intrusion at Sinabung over the period of October 2010–December 2011.

","language":"English","publisher":"Springer","doi":"10.1007/s00445-020-01383-7","usgsCitation":"Pagacancang, A., McCausland, W.A., Hamidah, N.N., Kristianto, Basuki, A., and Indrastuti, N., 2020, Local magnitude, coda magnitude, and radiated energy of volcanic tectonic earthquakes from October 2010 to December 2011 at Sinabung volcano, Indonesia: Bulletin of Volcanology, v. 83, 45, 16 p., https://doi.org/10.1007/s00445-020-01383-7.","productDescription":"45, 16 p.","ipdsId":"IP-112724","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":421164,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Indonesia","otherGeospatial":"Sinabung volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 94.80408011956274,\n 6.071558619518001\n ],\n [\n 94.80408011956274,\n 1.292805138355149\n ],\n [\n 101.37390433831303,\n 1.292805138355149\n ],\n [\n 101.37390433831303,\n 6.071558619518001\n ],\n [\n 94.80408011956274,\n 6.071558619518001\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"83","noUsgsAuthors":false,"publicationDate":"2020-05-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Pagacancang, Afnimar","contributorId":330169,"corporation":false,"usgs":false,"family":"Pagacancang","given":"Afnimar","email":"","affiliations":[{"id":78836,"text":"Bandung Institute of Technology (ITB)","active":true,"usgs":false}],"preferred":false,"id":884204,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCausland, Wendy A. 0000-0002-8683-1440","orcid":"https://orcid.org/0000-0002-8683-1440","contributorId":204380,"corporation":false,"usgs":true,"family":"McCausland","given":"Wendy","email":"","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":884205,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hamidah, Nimas Nurul","contributorId":330170,"corporation":false,"usgs":false,"family":"Hamidah","given":"Nimas","email":"","middleInitial":"Nurul","affiliations":[{"id":78836,"text":"Bandung Institute of Technology (ITB)","active":true,"usgs":false}],"preferred":false,"id":884206,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kristianto","contributorId":330171,"corporation":false,"usgs":false,"family":"Kristianto","affiliations":[{"id":40024,"text":"Center for Volcanology and Geologic Hazard Mitigation","active":true,"usgs":false}],"preferred":false,"id":884207,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Basuki, Ahmad","contributorId":330172,"corporation":false,"usgs":false,"family":"Basuki","given":"Ahmad","email":"","affiliations":[{"id":40024,"text":"Center for Volcanology and Geologic Hazard Mitigation","active":true,"usgs":false}],"preferred":false,"id":884208,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Indrastuti, Novianti","contributorId":204389,"corporation":false,"usgs":false,"family":"Indrastuti","given":"Novianti","email":"","affiliations":[{"id":36928,"text":"Center for Volcanology and Geological Hazard Mitigation, Bandung, Indonesia","active":true,"usgs":false}],"preferred":false,"id":884209,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70209232,"text":"ofr20201030 - 2020 - Louisiana Barrier Island Comprehensive Monitoring Program: Mapping habitats in beach, dune, and intertidal environments along the Louisiana Gulf of Mexico shoreline, 2008 and 2015–16","interactions":[],"lastModifiedDate":"2020-05-19T11:53:31.168523","indexId":"ofr20201030","displayToPublicDate":"2020-05-18T07:11:23","publicationYear":"2020","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":"2020-1030","displayTitle":"Louisiana Barrier Island Comprehensive Monitoring Program: Mapping Habitats in Beach, Dune, and Intertidal Environments Along the Louisiana Gulf of Mexico Shoreline, 2008 and 2015–16","title":"Louisiana Barrier Island Comprehensive Monitoring Program: Mapping habitats in beach, dune, and intertidal environments along the Louisiana Gulf of Mexico shoreline, 2008 and 2015–16","docAbstract":"

Barrier islands, headlands, and coastal shorelines provide numerous valuable ecosystem goods and services, including storm protection and erosion control for the mainland, habitat for fish and wildlife, salinity regulation in estuaries, carbon sequestration in marshes, and areas for recreation and tourism. These coastal features are dynamic environments because of their position at the land-sea interface. Storms, wave energy, tides, currents, and relative sea-level rise are powerful forces that shape local geomorphology and habitat distribution. In order to make more informed decisions, coastal resource managers require insights into how these dynamic systems are changing through time.

In 2005, Louisiana’s Coastal Protection and Restoration Authority, in partnership with the University of New Orleans and the U.S. Geological Survey, developed the Barrier Island Comprehensive Monitoring (BICM) Program. The goal of the BICM Program is to develop long-term datasets for habitat coverage, shoreline assessments, shoreline position, topobathymetric changes, and sediment characterization to assist with planning, designing, evaluating, and maintaining current and future barrier shorelines. The overall objectives of the study described in this report were to (1) map habitats for 2008 and 2015–16 for BICM coastal reaches and (2) map habitat change between these two time periods.

This report highlights the second phase of habitat analyses for the BICM Program. This work builds on a previous habitat analysis conducted by the University of New Orleans, which included the development of habitat maps for 1996/1998, 2001, 2004, and 2005, along with habitat change maps. For this current effort, a new 15-class habitat scheme was developed from the original BICM scheme to further delineate various dune habitats, including meadow habitat found along the backslopes of dunes, to distinguish between marsh and mangrove, and to distinguish between beach and unvegetated barrier flat habitats. Additionally, a geographic object-based image analysis-based mapping framework was used to incorporate relative topography and address elevation uncertainty in light detection and ranging data to assist with mapping dune and intertidal habitats.

For the entire BICM region, the area experiencing a change in a land/water category (that is, land gain or land loss) was 3.4 percent, of which, 59.2 percent was land gain and 40.8 percent was land loss. Areal coverages of meadow, mangrove, scrub/shrub, and vegetated dune increased from 2008 to 2015–16, whereas areal coverages of beach, grassland, and intertidal decreased. The decrease in intertidal, however, was largely due to differing water levels in the orthophotography between the two time periods. Regional analyses of habitat coverage and habitat change captured the dynamic nature of these systems and the effects of restoration efforts, most notably in the Late Lafourche Delta, Modern Delta, and Chandeleur Islands regions. For instance, in the Modern Delta region there was a marked increase in unvegetated flat, meadow, mangrove, scrub/shrub, beach, unvegetated dune, and vegetated dune. As a result, this region experienced the highest percent change for land/water classes (6.6 percent) with land gain accounting for much of this change (70.8 percent). In contrast, the Acadiana Bays region had the highest relative percent loss of all regions. The region had a percent change for land/water classes of 2.8 percent, of which, 79.7 percent was land loss.

The results of this study provide information about the areal coverage and distribution of habitats for two recent time periods and change over about an 8-year period. These data can be used to evaluate changes along the Louisiana Gulf of Mexico shoreline, including gradual changes caused by coastal processes, restoration actions, and (or) episodic events, such as hurricanes and extreme storms.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201030","collaboration":"Prepared in cooperation with the Louisiana Coastal Protection and Restoration Authority","usgsCitation":"Enwright, N.M., SooHoo, W.M., Dugas, J.L., Conzelmann, C.P., Laurenzano, C., Lee, D.M., Mouton, K., and Stelly, S.J., 2020, Louisiana Barrier Island Comprehensive Monitoring Program—Mapping habitats in beach, dune, and intertidal environments along the Louisiana Gulf of Mexico shoreline, 2008 and 2015–16: U.S. Geological Survey Open-File Report 2020–1030, 57 p., https://doi.org/10.3133/ofr20201030.","productDescription":"Report: ix, 57 p.; Data Release","numberOfPages":"72","onlineOnly":"Y","ipdsId":"IP-114268","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":436983,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YRT54Z","text":"USGS data release","linkHelpText":"Louisiana Barrier Island Comprehensive Monitoring Program - 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Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506–3152

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-05-18","noUsgsAuthors":false,"publicationDate":"2020-05-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Enwright, Nicholas M. 0000-0002-7887-3261","orcid":"https://orcid.org/0000-0002-7887-3261","contributorId":223571,"corporation":false,"usgs":true,"family":"Enwright","given":"Nicholas M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":785481,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"SooHoo, William M. 0000-0002-8652-0474","orcid":"https://orcid.org/0000-0002-8652-0474","contributorId":215849,"corporation":false,"usgs":false,"family":"SooHoo","given":"William","email":"","middleInitial":"M.","affiliations":[{"id":25340,"text":"Cherokee Nation Technologies","active":true,"usgs":false}],"preferred":false,"id":785482,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dugas, Jason L. 0000-0001-6094-7560","orcid":"https://orcid.org/0000-0001-6094-7560","contributorId":223572,"corporation":false,"usgs":true,"family":"Dugas","given":"Jason L.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":785483,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conzelmann, Craig P. 0000-0002-4227-8719","orcid":"https://orcid.org/0000-0002-4227-8719","contributorId":217968,"corporation":false,"usgs":true,"family":"Conzelmann","given":"Craig P.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":785484,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Laurenzano, Claudia 0000-0003-1406-8658","orcid":"https://orcid.org/0000-0003-1406-8658","contributorId":218316,"corporation":false,"usgs":false,"family":"Laurenzano","given":"Claudia","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":785485,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lee, Darin M.","contributorId":201671,"corporation":false,"usgs":false,"family":"Lee","given":"Darin","email":"","middleInitial":"M.","affiliations":[{"id":36230,"text":"Louisiana Coastal Protection Restoration Authority","active":true,"usgs":false}],"preferred":false,"id":785486,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mouton, Kelly 0000-0002-7692-8206","orcid":"https://orcid.org/0000-0002-7692-8206","contributorId":189444,"corporation":false,"usgs":false,"family":"Mouton","given":"Kelly","affiliations":[],"preferred":false,"id":785487,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stelly, Spencer J. 0000-0003-1050-1733","orcid":"https://orcid.org/0000-0003-1050-1733","contributorId":215852,"corporation":false,"usgs":false,"family":"Stelly","given":"Spencer","email":"","middleInitial":"J.","affiliations":[{"id":39319,"text":"Student Services Contractor at the U.S. Geological Survey Wetland and Aquatic Research Center","active":true,"usgs":false}],"preferred":false,"id":785488,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70259112,"text":"70259112 - 2020 - Natural and anthropogenic processes affecting radon releases during mining and early stage reclamation activities, Pinenut uranium mine, Arizona, USA","interactions":[],"lastModifiedDate":"2024-09-27T11:47:00.742782","indexId":"70259112","displayToPublicDate":"2020-05-18T06:45:13","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2263,"text":"Journal of Environmental Radioactivity","active":true,"publicationSubtype":{"id":10}},"title":"Natural and anthropogenic processes affecting radon releases during mining and early stage reclamation activities, Pinenut uranium mine, Arizona, USA","docAbstract":"

Radon (Rnair) was monitored in open air in publicly accessible areas surrounding the Pinenut uranium (U) mine during mining and reclamation activities in 2015–16 to address concerns about mining related effects to areas surrounding Grand Canyon National Park (GCNP) in Arizona, USA. During July 2015, Rnair concentrations associated with the ore storage pile monitoring site were larger than those at the mine vent monitoring site and likely resulted from the relatively large amount of ore stored on site during this period. Higher wind velocities at the ore pile monitoring site generally resulted in lower Rnair concentrations; however, wind velocity did not appear to be an important factor in controlling Rnair concentrations at the mine vent monitoring site. Physical disturbances of the ore pile by heavy equipment did not coincide with elevated Rnair concentrations at the ore storage pile or mine vent monitoring sites. The relative size of the ore storage pile showed a positive trend with the daily mean Rnair concentration measured at the ore pile monitoring site. Principal component analysis (PCA) was applied to the ore pile and mine vent multivariate data sets for simultaneous comparison of all measured variables during 230 days of the study period. A significant positive coefficient for Rnair was associated with a significant negative coefficient for wind speed for principal component (PC) 2ore pile. Significant, positive PC2mine vent coefficients included Rnair, wind direction, and relative ore pile size indicating that Rnair variations at the mine vent monitoring site may be affected by Rn sourced from the ore pile. The ore pile is located about 200 m south of the mine vent Rn monitor with the prevalent wind direction coming from the south. All data generated during the field study and laboratory verification tests were published by Naftz et al. (2018) and are available online at:

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvrad.2020.106266","usgsCitation":"Naftz, D.L., Walton-Day, K., Gardner, W.P., Duniway, M.C., and Bills, D.J., 2020, Natural and anthropogenic processes affecting radon releases during mining and early stage reclamation activities, Pinenut uranium mine, Arizona, USA: Journal of Environmental Radioactivity, v. 220–221, 106266, https://doi.org/10.1016/j.jenvrad.2020.106266.","productDescription":"106266","ipdsId":"IP-092059","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":467289,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvrad.2020.106266","text":"Publisher Index Page"},{"id":462316,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"220–221","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Naftz, David L. 0000-0003-1130-6892 dlnaftz@usgs.gov","orcid":"https://orcid.org/0000-0003-1130-6892","contributorId":1041,"corporation":false,"usgs":true,"family":"Naftz","given":"David","email":"dlnaftz@usgs.gov","middleInitial":"L.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":914207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walton-Day, Katherine 0000-0002-9146-6193","orcid":"https://orcid.org/0000-0002-9146-6193","contributorId":336569,"corporation":false,"usgs":true,"family":"Walton-Day","given":"Katherine","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":914208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gardner, W. Payton 0000-0003-0664-001X","orcid":"https://orcid.org/0000-0003-0664-001X","contributorId":206198,"corporation":false,"usgs":false,"family":"Gardner","given":"W.","email":"","middleInitial":"Payton","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":914209,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":914210,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bills, Donald J. 0000-0001-8955-3370 djbills@usgs.gov","orcid":"https://orcid.org/0000-0001-8955-3370","contributorId":177439,"corporation":false,"usgs":true,"family":"Bills","given":"Donald","email":"djbills@usgs.gov","middleInitial":"J.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":914211,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70211294,"text":"70211294 - 2020 - Good prospects: High-resolution telemetry data suggests novel brood-site selection behavior in waterfowl","interactions":[],"lastModifiedDate":"2020-07-22T14:36:02.905069","indexId":"70211294","displayToPublicDate":"2020-05-17T09:32:07","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5550,"text":"Animal Behavior and Cognition","active":true,"publicationSubtype":{"id":10}},"title":"Good prospects: High-resolution telemetry data suggests novel brood-site selection behavior in waterfowl","docAbstract":"Breeding success should increase with prior knowledge of the surrounding environment, which is dependent upon an animal’s ability to evaluate habitat. Prospecting for nesting locations and migratory stop-over sites are well-established behaviors among bird species. We assessed whether ducks in Suisun Marsh, California, USA, a brackish marsh, prospect for suitable wetlands in the week prior to brooding. K-means cluster analyses grouped 29 mallard and gadwall hens into 3 groups. One group (n=13) demonstrated evidence of brood site prospecting with fewest and latest pre-brooding wetland visits. Of these hens, seven visited their future brood pond an average of 1.14 times and only shortly before brooding (1.29 days), obtaining current information on habitat suitability. For the remaining 6 hens, we did not detect a brooding wetland visit which may be due to data limitations or the need to prospect the specific brood pond was precluded by having acquired sufficient familiarity with the wetland habitat during nest breaks in adjacent wetlands. The second identified group of hens (n=11) visited the brooding wetland most frequently (on 4.55 days), farther in advance (5.27 days), with the fewest unique wetland visits and the earliest brooding date (May 26). The final group of hens (n=5) were the latest to brood (Jun 21) and visited the most wetlands, possibly due to less water or more broods present across the landscape. Brood ponds were always farther from the nest than the nearest ponds indicating that habitat suitability or presence of conspecifics is more important to brood-site selection. Prospecting provides hens with knowledge about current habitat conditions and allows them to ‘crowdsource’ public information regarding use of that habitat by other brooding hens. Prospecting may therefore, benefit ducks inhabiting ephemeral habitats like those within Suisun Marsh, where brood habitat is limited, and water cover changes rapidly during the breeding season.","language":"English","publisher":"Elsevier","doi":"10.1016/j.anbehav.2020.04.013","usgsCitation":"Casazza, M.L., McDuie, F., Lorenz, A., Keiter, D.A., Yee, J.L., Overton, C.T., Peterson, S.H., Feldheim, C.L., and Ackerman, J., 2020, Good prospects: High-resolution telemetry data suggests novel brood-site selection behavior in waterfowl: Animal Behavior and Cognition, v. 164, p. 163-172, https://doi.org/10.1016/j.anbehav.2020.04.013.","productDescription":"10 p.","startPage":"163","endPage":"172","ipdsId":"IP-113757","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":456738,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.anbehav.2020.04.013","text":"Publisher Index Page"},{"id":376630,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay, Suisun Marsh","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.0684051513672,\n 38.028622234587964\n ],\n [\n -121.8610382080078,\n 38.028622234587964\n ],\n [\n -121.8610382080078,\n 38.17559185481662\n ],\n [\n -122.0684051513672,\n 38.17559185481662\n ],\n [\n -122.0684051513672,\n 38.028622234587964\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"164","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":793599,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McDuie, Fiona 0000-0002-1948-5613","orcid":"https://orcid.org/0000-0002-1948-5613","contributorId":222936,"corporation":false,"usgs":true,"family":"McDuie","given":"Fiona","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":793600,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lorenz, Austen 0000-0003-3657-5941","orcid":"https://orcid.org/0000-0003-3657-5941","contributorId":222610,"corporation":false,"usgs":true,"family":"Lorenz","given":"Austen","email":"","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":793601,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keiter, David A.","contributorId":176521,"corporation":false,"usgs":false,"family":"Keiter","given":"David","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":793602,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yee, Julie L. 0000-0003-1782-157X julie_yee@usgs.gov","orcid":"https://orcid.org/0000-0003-1782-157X","contributorId":3246,"corporation":false,"usgs":true,"family":"Yee","given":"Julie","email":"julie_yee@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":793603,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":793604,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Peterson, Sarah H. 0000-0003-2773-3901 sepeterson@usgs.gov","orcid":"https://orcid.org/0000-0003-2773-3901","contributorId":167181,"corporation":false,"usgs":true,"family":"Peterson","given":"Sarah","email":"sepeterson@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":793605,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Feldheim, Cliff L.","contributorId":206561,"corporation":false,"usgs":false,"family":"Feldheim","given":"Cliff","email":"","middleInitial":"L.","affiliations":[{"id":37342,"text":"California Department of Water Resources","active":true,"usgs":false}],"preferred":false,"id":793606,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":793607,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70216380,"text":"70216380 - 2020 - The use of Bayesian priors in Ecology: The good, the bad and the not great","interactions":[],"lastModifiedDate":"2020-11-13T15:03:28.463516","indexId":"70216380","displayToPublicDate":"2020-05-17T08:52:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"The use of Bayesian priors in Ecology: The good, the bad and the not great","docAbstract":"
  1. Bayesian data analysis (BDA) is a powerful tool for making inference from ecological data, but its full potential has yet to be realized. Despite a generally positive trajectory in research surrounding model development and assessment, far too little attention has been given to prior specification.
  2. Default priors, a sub‐class of non‐informative prior distributions that are often chosen without critical thought or evaluation, are commonly used in practice. We believe the fear of being too ‘subjective’ has prevented many researchers from using any prior information in their analyses despite the fact that defending prior choice (informative or not) promotes good statistical practice.
  3. In this commentary, we provide an overview of how BDA is currently being used in a random sample of articles, discuss implications for inference if current bad practices continue, and highlight sub‐fields where knowledge about the system has improved inference and promoted good statistical practices through the careful and justified use of informative priors.
  4. We hope to inspire a renewed discussion about the use of Bayesian priors in Ecology with particular attention paid to specification and justification. We also emphasize that all priors are the result of a subjective choice, and should be discussed in that way.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.13407","usgsCitation":"Banner, K., Irvine, K., and Rodhouse, T., 2020, The use of Bayesian priors in Ecology: The good, the bad and the not great: Methods in Ecology and Evolution, v. 11, no. 8, p. 882-889, https://doi.org/10.1111/2041-210X.13407.","productDescription":"8 p.","startPage":"882","endPage":"889","ipdsId":"IP-114762","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":456739,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.13407","text":"Publisher Index Page"},{"id":380504,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"8","noUsgsAuthors":false,"publicationDate":"2020-06-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Banner, Katharine M.","contributorId":244876,"corporation":false,"usgs":false,"family":"Banner","given":"Katharine M.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":804840,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irvine, Kathryn M. 0000-0002-6426-940X","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":244879,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":804841,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rodhouse, Thomas","contributorId":244880,"corporation":false,"usgs":false,"family":"Rodhouse","given":"Thomas","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":804842,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70211339,"text":"70211339 - 2020 - Forecasting, detecting, and tracking volcanic eruptions from space","interactions":[],"lastModifiedDate":"2020-09-01T13:52:50.822062","indexId":"70211339","displayToPublicDate":"2020-05-16T10:11:52","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5982,"text":"Remote Sensing in Earth Systems Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Forecasting, detecting, and tracking volcanic eruptions from space","docAbstract":"Satellite monitoring of volcanic activity typically includes four primary observations: (1) deformation and surface change, (2) gas emissions, (3) thermal anomalies, and (4) ash plumes. These phenomena are imaged by remote sensing data that span the electromagnetic spectrum, from microwave to ultraviolet energy and including visible and infrared wavelengths. The primary uses of satellite data in volcanology are forecasting, detecting, and tracking eruptive activity. Eruptions are often preceded by a number of indicators that are detectable from space, including surface deformation, subtle increases in surface temperature, and elevated gas emissions. The first indications of eruption, especially at remote volcanoes, are often identified in satellite data by strong thermal anomalies and/or the presence of ash and gas in the atmosphere, the recognition of which can be automated for rapid eruption detection. Once an eruption is in progress, space-based imagery of all types can track activity over time, providing information on the emplacement of volcanic deposits, the presence and character of ash plumes, and potential changes in the character of the eruption, all of which aid hazards assessment. Activity at Agung volcano, Indonesia, during 2017–2019, offers an excellent example of the importance of remote sensing datasets for forecasting, detecting, and tracking eruptions. Challenges to exploiting current and future satellite data include ensuring regular acquisitions over active volcanoes and developing tools for automated analysis of the massive volume of imagery for volcano-related signals.","language":"English","publisher":"Springer","doi":"10.1007/s41976-020-00034-x","usgsCitation":"Poland, M.P., Lopez, T., Wright, R., and Pavolonis, M.J., 2020, Forecasting, detecting, and tracking volcanic eruptions from space: Remote Sensing in Earth Systems Sciences, v. 3, no. 1, p. 55-94, https://doi.org/10.1007/s41976-020-00034-x.","productDescription":"40 p.","startPage":"55","endPage":"94","ipdsId":"IP-111491","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":376719,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-05-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":793911,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lopez, Taryn","contributorId":146828,"corporation":false,"usgs":false,"family":"Lopez","given":"Taryn","affiliations":[{"id":16753,"text":"University of Alaska Geophysical Institute","active":true,"usgs":false}],"preferred":false,"id":793912,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wright, Robert","contributorId":174413,"corporation":false,"usgs":false,"family":"Wright","given":"Robert","affiliations":[],"preferred":false,"id":793913,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pavolonis, Michael J.","contributorId":199297,"corporation":false,"usgs":false,"family":"Pavolonis","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":793914,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70212799,"text":"70212799 - 2020 - The future of sediment transport and streamflow under a changing climate and the implications for long-term resilience of the San Francisco Bay-Delta","interactions":[],"lastModifiedDate":"2020-08-28T13:39:37.495182","indexId":"70212799","displayToPublicDate":"2020-05-16T08:35:33","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"The future of sediment transport and streamflow under a changing climate and the implications for long-term resilience of the San Francisco Bay-Delta","docAbstract":"

Sedimentation and turbidity have effects on habitat suitability in the San Francisco Bay‐Delta (Bay‐Delta), concerning key species in the bay as well as the ability of the delta marshes to keep pace with sea level rise. A daily rainfall runoff and transport model of the Sacramento River Basin of northern California was developed to simulate streamflow and suspended sediment transport to the Bay‐Delta for the next century (water years, WY2010–2099). The model was calibrated to historical streamflow and sediment data and applied using 10 Global Climate Models with two representative concentration pathways (RCP) each for WY1980–2099 from the IPCC 5th Assessment Report. Results indicate average increases in peak streamflow of +58% and +66% for the RCP 4.5 and 8.5 ensembles, respectively, by mid‐century and +62 and +96% by end‐of‐century. Sediment loads increased by +39% and +69% by end‐of‐century. Suspended sediment concentrations (SSC) increased on average by +4.6% and +6.7% for RCP 4.5 and 8.5, respectively, by end‐of‐century. Individual scenario results varied, and statistically significant increasing trends of sediment loads to the Bay‐Delta were found for the RCP 4.5 and 8.5 ensembles and five individual scenarios. Increased suspended sediment loads may have negative effects such as contaminant transport but also have positive effects that help protect against sea level rise, increase turbidity and fish habitat, and sustain wetland habitats in the Bay‐Delta.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019WR026245","usgsCitation":"Stern, M.A., Flint, L.E., Flint, A., Knowles, N., and Wright, S., 2020, The future of sediment transport and streamflow under a changing climate and the implications for long-term resilience of the San Francisco Bay-Delta: Water Resources Research, v. 56, no. 9, e2019WR026245, 16 p., https://doi.org/10.1029/2019WR026245.","productDescription":"e2019WR026245, 16 p.","ipdsId":"IP-094058","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":456748,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019wr026245","text":"Publisher Index Page"},{"id":436984,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ET61S4","text":"USGS data release","linkHelpText":"Sacramento River Basin future daily streamflow and sediment HSPF outputs"},{"id":377984,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.40942382812501,\n 37.413800350662896\n ],\n [\n -119.66308593749999,\n 37.413800350662896\n ],\n [\n -119.66308593749999,\n 40.88029480552824\n ],\n [\n -123.40942382812501,\n 40.88029480552824\n ],\n [\n -123.40942382812501,\n 37.413800350662896\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"9","noUsgsAuthors":false,"publicationDate":"2020-08-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Stern, Michelle A. 0000-0003-3030-7065 mstern@usgs.gov","orcid":"https://orcid.org/0000-0003-3030-7065","contributorId":4244,"corporation":false,"usgs":true,"family":"Stern","given":"Michelle","email":"mstern@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797492,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797493,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flint, Alan L 0000-0002-5118-751X","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":239656,"corporation":false,"usgs":false,"family":"Flint","given":"Alan L","affiliations":[{"id":7065,"text":"USGS emeritus","active":true,"usgs":false}],"preferred":false,"id":797494,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knowles, Noah 0000-0001-5652-1049","orcid":"https://orcid.org/0000-0001-5652-1049","contributorId":206338,"corporation":false,"usgs":true,"family":"Knowles","given":"Noah","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":797495,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797496,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70210776,"text":"70210776 - 2020 - Projecting spatiotemporally explicit effects of climate change on stream temperature: A model comparison and implications for coldwater fishes","interactions":[],"lastModifiedDate":"2020-06-24T13:35:31.700545","indexId":"70210776","displayToPublicDate":"2020-05-16T08:27:32","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Projecting spatiotemporally explicit effects of climate change on stream temperature: A model comparison and implications for coldwater fishes","docAbstract":"Conservation planners and resource managers seek information about how the availability and locations of cold-water habitats will change in the future and how these predictions vary among models. We used a physical process-based model to demonstrate the implications of climate change for streamflow and water temperature in two watersheds with distinctive flow regimes: the Snoqualmie watershed (WA) and Siletz watershed (OR), USA. Our model incorporated a downscaled ensemble of global climate model outputs and was calibrated with in situ and remotely sensed water temperatures. We compared predictions from our processed-based model to those from a publicly available and widely used statistical model. The process-based model projected greater changes in summer maximum water temperatures for the mixed-rain-snow Snoqualmie watershed than for the rain-dominated Siletz watershed as a result of the near-complete loss of winter snowpack and significant reduction in summer flow in the Snoqualmie watershed expected by the 2080s. Both models projected generally similar future spatial patterns of maximum water temperature in the two rivers, with cool reaches distributed farther upstream and fewer in number. However, the process-based model projected higher spatial heterogeneity in water temperature due to our spatially explicit simulation of streamflow and because we calibrated the model with spatially continuous remotely sensed water temperature data. We used stream temperature projections to assess the vulnerability of Pacific salmon and trout to changes in the spatial distribution of cold-water habitats during August by the 2080s. Results suggest that salmonids may have fewer summertime cold-water habitats in both watersheds. Projected stream warming may further limit particular species and life stages, especially in the Snoqualmie watershed. Our comparison of models highlights the importance of considering what might be gained by using a process-based model for evaluating and prioritizing management actions that mitigate climate impacts on cold-water habitats for stream fishes.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2020.125066","usgsCitation":"Lee, Y., Fullerton, A.H., Sun, N., and Torgersen, C.E., 2020, Projecting spatiotemporally explicit effects of climate change on stream temperature: A model comparison and implications for coldwater fishes: Journal of Hydrology, v. 588, 125066, 16 p., https://doi.org/10.1016/j.jhydrol.2020.125066.","productDescription":"125066, 16 p.","ipdsId":"IP-107958","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":456751,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1639159","text":"External Repository"},{"id":375848,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","otherGeospatial":"Siletz River, Snoqualmie River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.07752990722655,\n 44.7384422020289\n ],\n [\n -123.85505676269531,\n 44.7384422020289\n ],\n [\n -123.85505676269531,\n 44.949735226126776\n ],\n [\n -124.07752990722655,\n 44.949735226126776\n ],\n [\n -124.07752990722655,\n 44.7384422020289\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.03750610351564,\n 47.45873704984453\n ],\n [\n -121.4208984375,\n 47.45873704984453\n ],\n [\n -121.4208984375,\n 47.755944512091666\n ],\n [\n -122.03750610351564,\n 47.755944512091666\n ],\n [\n -122.03750610351564,\n 47.45873704984453\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"588","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lee, Yeun","contributorId":225503,"corporation":false,"usgs":false,"family":"Lee","given":"Yeun","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":791363,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fullerton, Aimee H.","contributorId":146936,"corporation":false,"usgs":false,"family":"Fullerton","given":"Aimee","email":"","middleInitial":"H.","affiliations":[{"id":12641,"text":"NOAA NMFS","active":true,"usgs":false}],"preferred":false,"id":791364,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sun, Ning","contributorId":225504,"corporation":false,"usgs":false,"family":"Sun","given":"Ning","email":"","affiliations":[{"id":38914,"text":"Pacific Northwest National Laboratory","active":true,"usgs":false}],"preferred":false,"id":791365,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Torgersen, Christian E. 0000-0001-8325-2737 ctorgersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8325-2737","contributorId":146935,"corporation":false,"usgs":true,"family":"Torgersen","given":"Christian","email":"ctorgersen@usgs.gov","middleInitial":"E.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":791366,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210215,"text":"70210215 - 2020 - At the end of the road: Lessons learned from comparing model- and design-based approaches to estimate population sizes of boreal birds in Alberta, Canada","interactions":[],"lastModifiedDate":"2020-05-21T12:40:43.952582","indexId":"70210215","displayToPublicDate":"2020-05-16T07:36:29","publicationYear":"2020","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":"At the end of the road: Lessons learned from comparing model- and design-based approaches to estimate population sizes of boreal birds in Alberta, Canada","docAbstract":"Estimating population abundance is a challenging task complicated by the amount, type, and quality of available data. Conservationists have relied on design-based estimates from Partners in Flight (PIF), which primarily uses roadside data from the North American Breeding Bird Survey (BBS) to estimate populations sizes. However, the BBS was not designed to estimate population sizes. We developed models incorporating land cover and climate variables based on roadside and off-road point-count surveys. We calculated spatially explicit, model-based population estimates for 81 landbird species in Bird Conservation Region 6 in Alberta, Canada, and compared these to PIF estimates. We also developed a framework to evaluate how the differences between the detection distance, time-of-day, roadside count, and habitat representation adjustments explain discrepancies between the two estimators. We showed that the key assumptions of the PIF population size estimator were commonly violated in this region, and the two approaches provided very different population size estimates for most species. The average differences between estimators were explained by differences in the detection distance and time-of-day components, but these adjustments left much unexplained variation among species. Differences in the roadside count and habitat representation components explained most of the among-species variation. The variation caused by these factors was large enough to change the population size ranking of the species. The roadside count bias needs serious attention when roadside surveys are used to extrapolate over off-road areas. Habitat representation bias is likely prevalent in regions sparsely and non-representatively sampled by roadside surveys, such as the boreal region of North America, and thus population size estimates for these regions need to be treated with caution for certain species. Model-based integration of available data sources and additional sampling can contribute towards more accurate population size estimates for conservation in remote areas of North America.","language":"English","publisher":"Oxford Academic","doi":"10.1093/condor/duaa007","usgsCitation":"Solymos, P., Toms, J.D., Matsuoka, S.M., Cumming, S.G., Barker, N.K., Thogmartin, W.E., Stralberg, D., Crosby, A.D., Denes, F.V., Hache, S., Mahon, C.L., Schmiegelow, F.K., and Bayne, E.M., 2020, At the end of the road: Lessons learned from comparing model- and design-based approaches to estimate population sizes of boreal birds in Alberta, Canada: The Condor, v. 122, duaa007, 22 p., https://doi.org/10.1093/condor/duaa007.","productDescription":"duaa007, 22 p.","ipdsId":"IP-106038","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":456756,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/condor/duaa007","text":"Publisher Index Page"},{"id":374980,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","state":"Alberta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.0390625,\n 49.009050809382046\n ],\n [\n -110.0830078125,\n 59.99898612060444\n ],\n [\n -120.0146484375,\n 59.99898612060444\n ],\n [\n -120.10253906249999,\n 53.80065082633023\n ],\n [\n -118.6083984375,\n 53.09402405506325\n ],\n [\n -117.46582031249999,\n 52.3755991766591\n ],\n [\n -116.71874999999999,\n 51.80861475198521\n ],\n [\n -115.53222656249999,\n 50.597186230587035\n ],\n [\n -114.521484375,\n 50.00773901463687\n ],\n [\n -114.345703125,\n 49.23912083246698\n ],\n [\n -113.90625,\n 48.951366470947725\n ],\n [\n -110.0390625,\n 49.009050809382046\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"122","noUsgsAuthors":false,"publicationDate":"2020-05-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Solymos, Peter","contributorId":140674,"corporation":false,"usgs":false,"family":"Solymos","given":"Peter","affiliations":[],"preferred":false,"id":789559,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Toms, Judith D 0000-0002-8492-3384","orcid":"https://orcid.org/0000-0002-8492-3384","contributorId":224789,"corporation":false,"usgs":false,"family":"Toms","given":"Judith","email":"","middleInitial":"D","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":789560,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Matsuoka, Steven M. 0000-0001-6415-1885 smatsuoka@usgs.gov","orcid":"https://orcid.org/0000-0001-6415-1885","contributorId":184173,"corporation":false,"usgs":true,"family":"Matsuoka","given":"Steven","email":"smatsuoka@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":789561,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cumming, Steven G.","contributorId":207538,"corporation":false,"usgs":false,"family":"Cumming","given":"Steven","email":"","middleInitial":"G.","affiliations":[{"id":37556,"text":"University of Laval","active":true,"usgs":false}],"preferred":false,"id":789562,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barker, Nicole K. S.","contributorId":203720,"corporation":false,"usgs":false,"family":"Barker","given":"Nicole","email":"","middleInitial":"K. S.","affiliations":[{"id":36697,"text":"Boreal Avian Modeling Project","active":true,"usgs":false}],"preferred":false,"id":789563,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":789564,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stralberg, Diana","contributorId":187413,"corporation":false,"usgs":false,"family":"Stralberg","given":"Diana","email":"","affiliations":[],"preferred":false,"id":789565,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Crosby, Andrew D.","contributorId":141455,"corporation":false,"usgs":false,"family":"Crosby","given":"Andrew","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":789566,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Denes, Francisco V 0000-0003-2445-187X","orcid":"https://orcid.org/0000-0003-2445-187X","contributorId":224790,"corporation":false,"usgs":false,"family":"Denes","given":"Francisco","email":"","middleInitial":"V","affiliations":[{"id":36696,"text":"University of Alberta","active":true,"usgs":false}],"preferred":false,"id":789567,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hache, Samuel 0000-0003-3952-009X","orcid":"https://orcid.org/0000-0003-3952-009X","contributorId":224791,"corporation":false,"usgs":false,"family":"Hache","given":"Samuel","email":"","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":789568,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mahon, C Lisa 0000-0003-0283-057X","orcid":"https://orcid.org/0000-0003-0283-057X","contributorId":224792,"corporation":false,"usgs":false,"family":"Mahon","given":"C","email":"","middleInitial":"Lisa","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":789569,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Schmiegelow, Fiona K A 0000-0002-8219-8684","orcid":"https://orcid.org/0000-0002-8219-8684","contributorId":224793,"corporation":false,"usgs":false,"family":"Schmiegelow","given":"Fiona","email":"","middleInitial":"K A","affiliations":[{"id":36696,"text":"University of Alberta","active":true,"usgs":false}],"preferred":false,"id":789570,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Bayne, Erin M.","contributorId":140675,"corporation":false,"usgs":false,"family":"Bayne","given":"Erin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":789571,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70210502,"text":"70210502 - 2020 - Evaluating the potential role of bioactive chemicals on the distribution of invasive Asian carp upstream and downstream from river mile 278 in the Illinois waterway","interactions":[],"lastModifiedDate":"2020-06-05T12:39:41.761022","indexId":"70210502","displayToPublicDate":"2020-05-16T07:36:08","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the potential role of bioactive chemicals on the distribution of invasive Asian carp upstream and downstream from river mile 278 in the Illinois waterway","docAbstract":"Two non-native carp species have invaded the Illinois Waterway and are a threat to Great Lakes ecosystems. Poor water quality in the upper Illinois Waterway, may be a factor contributing to the stalling of the carp population front near river mile 278. In 2015, the U.S. Geological Survey collected 4 sets of water samples from two sites upstream and 4 sites downstream from river mile 278, and one tributary. Each sample was analyzed for up to 649 unique parameters of which 287 were detected including 96 pesticides, 62 pharmaceuticals, 39 wastewater indicator compounds, 29 metals, 19 volatile organic compounds (VOCs), six disinfection by-products (DBPs), five hormones, and five carboxylic acids. Potential for bioactivity was estimated by comparing chemical concentrations to aquatic life or human health criteria and to in-vitro bioactivity screening results in the U.S EPA ToxCast™ database. The resulting hazard quotients and exposure-activity ratios (EARs) are toxicity indexes, that can be used to rank potential bioactivity of individual chemicals and chemical mixtures. This analysis indicates that several bioactive chemicals (BCs) including: carbendazim, 2,4-D, metolachlor, terbuthylazine, and acetochlor (pesticides); 1,4-dioxane (VOC); metformin, diphenhydramine, sulfamethoxazole, tramadol, fexofenadine, and the anti-depressants (pharmaceuticals); bisphenol A, 4-nonylphenol, galaxolide, 4-tert-octylphenol (wastewater indicator chemical); lead and boron (metals); and estrone (hormone) all occur in the upper Illinois Waterway at concentrations that produce elevated EARs values and may be adversely affecting carp reproduction and health. The clear differences in water quality upstream and downstream from river mile 278 with higher contaminant concentrations and potential bioactivity upstream could represent a barrier to carp range expansion.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.139458","usgsCitation":"Battaglin, W., Duncker, J.J., Terrio, P.J., Bradley, P., Barber, L., and DeCicco, L.A., 2020, Evaluating the potential role of bioactive chemicals on the distribution of invasive Asian carp upstream and downstream from river mile 278 in the Illinois waterway: Science of the Total Environment, v. 735, 139458, 18 p., https://doi.org/10.1016/j.scitotenv.2020.139458.","productDescription":"139458, 18 p.","ipdsId":"IP-111948","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":456760,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2020.139458","text":"Publisher Index Page"},{"id":436985,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V75F9Q","text":"USGS data release","linkHelpText":"Laboratory results for anthropogenic bioactive chemicals in the Illinois Waterway upstream and downstream of the bigheaded carp population front (2015; ver. 2.0, March 2020)"},{"id":375390,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.12408447265625,\n 41.539421883822854\n ],\n [\n -88.23944091796875,\n 41.46537017728069\n ],\n [\n -88.2696533203125,\n 41.43654942411456\n ],\n [\n -88.4674072265625,\n 41.393294288784865\n ],\n [\n -88.63220214843749,\n 41.335575973123916\n ],\n [\n -88.68988037109375,\n 41.36031866306708\n ],\n [\n -88.80523681640625,\n 41.395354710280166\n ],\n [\n -88.9178466796875,\n 41.37474755643594\n ],\n [\n -89.08538818359375,\n 41.37474755643594\n ],\n [\n -89.34906005859375,\n 41.35413387210046\n ],\n [\n -89.44244384765625,\n 41.27161384188987\n ],\n [\n -89.40673828125,\n 41.18485540813213\n ],\n [\n -89.44244384765625,\n 41.11660732012896\n ],\n [\n -89.50836181640625,\n 41.008920735004885\n ],\n [\n -89.59899902343749,\n 40.8595252289932\n ],\n [\n -89.6099853515625,\n 40.81380923056958\n ],\n [\n -89.60174560546875,\n 40.73268976628568\n ],\n [\n -89.5880126953125,\n 40.67438908251788\n ],\n [\n -89.53033447265625,\n 40.6723059714534\n ],\n [\n -89.50836181640625,\n 40.753499070431374\n ],\n [\n -89.5001220703125,\n 40.82835864973048\n ],\n [\n -89.40948486328125,\n 40.91973905106219\n ],\n [\n -89.26666259765625,\n 41.1290213474951\n ],\n [\n -89.307861328125,\n 41.18692242290296\n ],\n [\n -89.2913818359375,\n 41.265420628926684\n ],\n [\n -89.110107421875,\n 41.29431726315258\n ],\n [\n -88.90411376953125,\n 41.30050773444147\n ],\n [\n -88.7530517578125,\n 41.261291493919884\n ],\n [\n -88.5772705078125,\n 41.2509675141624\n ],\n [\n -88.38775634765625,\n 41.31494988250965\n ],\n [\n -88.29711914062499,\n 41.352072144512924\n ],\n [\n -88.20098876953125,\n 41.304634388885916\n ],\n [\n -88.154296875,\n 41.38299120166604\n ],\n [\n -88.0609130859375,\n 41.48800607185427\n ],\n [\n -88.12408447265625,\n 41.539421883822854\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"735","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Battaglin, William A. 0000-0001-7287-7096","orcid":"https://orcid.org/0000-0001-7287-7096","contributorId":204638,"corporation":false,"usgs":true,"family":"Battaglin","given":"William A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":790408,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duncker, James J. 0000-0001-5464-7991 jduncker@usgs.gov","orcid":"https://orcid.org/0000-0001-5464-7991","contributorId":4316,"corporation":false,"usgs":true,"family":"Duncker","given":"James","email":"jduncker@usgs.gov","middleInitial":"J.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":790409,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Terrio, Paul J. 0000-0002-1515-9570 pjterrio@usgs.gov","orcid":"https://orcid.org/0000-0002-1515-9570","contributorId":3313,"corporation":false,"usgs":true,"family":"Terrio","given":"Paul","email":"pjterrio@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":790410,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bradley, Paul M. 0000-0001-7522-8606","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":221226,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":790411,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barber, Larry B. 0000-0002-0561-0831","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":218953,"corporation":false,"usgs":true,"family":"Barber","given":"Larry B.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":790412,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"DeCicco, Laura A. 0000-0002-3915-9487 ldecicco@usgs.gov","orcid":"https://orcid.org/0000-0002-3915-9487","contributorId":174716,"corporation":false,"usgs":true,"family":"DeCicco","given":"Laura","email":"ldecicco@usgs.gov","middleInitial":"A.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":790413,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70215142,"text":"70215142 - 2020 - Methane oxidation dynamics in a karst subterranean estuary","interactions":[],"lastModifiedDate":"2020-10-08T12:39:51.334849","indexId":"70215142","displayToPublicDate":"2020-05-15T07:36:18","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Methane oxidation dynamics in a karst subterranean estuary","docAbstract":"

Chemical gradients between fresh, brackish and saline waters shape biogeochemical reactions and organic matter transformation within subterranean estuaries. In the Yucatán Peninsula’s karst subterranean estuary (KSE), methane and dissolved organic matter generated during the anaerobic decomposition of tropical forest vegetation are transported into flooded cave networks where microbial consumption greatly reduces their concentrations in the groundwater. To test the hypothesis that chemoclines associated with salinity gradients of the KSE are sites of methane oxidation, we obtained methane concentration and δ13C profiles of unprecedented vertical resolution from within a fully-submerged cave system located 6.6 km inland from the coastline using the ‘OctoPiPi’ (OPP) water sampler. Along a 12–24 cm thick low-salinity-halocline at ∼4.5 m water depth, salinity increased from fresh to brackish (0.2–1.8 psu), methane concentrations decreased, and δ13C values increased, as expected for microbial methane oxidation. The underlying brackish water had elevated oxygen concentrations compared to the always anoxic freshwater, suggesting that aerobic methane oxidation is the dominant process facilitating methane consumption. By contrast, as salinity increased from 1.8 to 36 psu through a 24–36 cm thick high-salinity-halocline between the meteoric lens and the saline groundwater at ∼20 m water depth, methane concentrations and δ13C values were constant. Conservative mixing and kinetic isotope models incorporating the methane data confirm a hotspot for microbial methane oxidation at the low-salinity-halocline. At least 98% of methane originating in the anoxic freshwaters was removed before its transport via channelized flow towards the coastline. These findings provide novel insight into the spatial constraints of methane dynamics within a karst subterranean estuary.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2020.03.007","usgsCitation":"Brankovits, D., and Pohlman, J., 2020, Methane oxidation dynamics in a karst subterranean estuary: Geochimica et Cosmochimica Acta, v. 277, p. 320-333, https://doi.org/10.1016/j.gca.2020.03.007.","productDescription":"14 p.","startPage":"320","endPage":"333","ipdsId":"IP-116814","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"links":[{"id":456767,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gca.2020.03.007","text":"Publisher Index Page"},{"id":436986,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9N4H6Y4","text":"USGS data release","linkHelpText":"Vertical chemical profiles collected across haloclines in the water column of the Ox Bel Ha cave network within the coastal aquifer of the Yucatan Peninsula in January 2015 and January 2016"},{"id":379217,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","otherGeospatial":"Ox Bel Ha cave system","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.8631591796875,\n 19.81063818250419\n ],\n [\n -87.275390625,\n 19.81063818250419\n ],\n [\n -87.275390625,\n 20.396123272467616\n ],\n [\n -87.8631591796875,\n 20.396123272467616\n ],\n [\n -87.8631591796875,\n 19.81063818250419\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"277","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Brankovits, David 0000-0002-0863-5698","orcid":"https://orcid.org/0000-0002-0863-5698","contributorId":210617,"corporation":false,"usgs":true,"family":"Brankovits","given":"David","email":"","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":800983,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pohlman, John 0000-0002-3563-4586","orcid":"https://orcid.org/0000-0002-3563-4586","contributorId":220804,"corporation":false,"usgs":true,"family":"Pohlman","given":"John","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":800984,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70228556,"text":"70228556 - 2020 - A decision-support tool to prioritize candidate landscapes for lesser prairie-chicken conservation","interactions":[],"lastModifiedDate":"2022-02-14T19:36:31.861247","indexId":"70228556","displayToPublicDate":"2020-05-14T14:36:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"A decision-support tool to prioritize candidate landscapes for lesser prairie-chicken conservation","docAbstract":"

Context
Development of systematic methods for conservation planning has improved effectiveness and efficiency of implementing such plans. The lesser prairie-chicken (Tympanuchus pallidicinctus) is a grouse species of conservation concern native to the southwestern Great Plains of the United States. Recent lesser prairie-chicken conservation planning has involved identifying ecologically important areas but has not incorporated economic data into prioritization of areas to target for conservation management.

Objectives
We used the program Marxan to develop a decision-support tool for managers in Kansas to prioritize tracts for improving lesser prairie-chicken habitat quality and increasing habitat availability. We developed three different conservation scenarios and evaluated the tradeoffs among multiple planning objectives in these scenarios.

Methods
We incorporated population targets from an existing conservation plan and agricultural economic data to help select land with maximum ecological value and minimum economic productivity to prioritize for lesser prairie-chicken conservation. We compared potential conservation plans and incorporated a post hoc connectivity model to test potential for individuals to travel among habitat patches in these plans during dispersal events.

Results
We found that different conservation scenarios led to different solutions, though differences varied by ecoregion. Potential solutions for all scenarios contained habitat patches not currently included in existing conservation plans and had high connectivity potential.

Conclusions
These results provide context for spatial prioritization of lesser prairie-chicken habitat management in Kansas. Application of this approach to species of conservation interest could help managers incorporate socioeconomic factors into planning methods and identify important tracts for conservation currently overlooked by existing planning methods.

","language":"English","publisher":"Springer","doi":"10.1007/s10980-020-01024-6","usgsCitation":"Schindler, A.R., Haukos, D.A., Hagen, C., and Ross, B., 2020, A decision-support tool to prioritize candidate landscapes for lesser prairie-chicken conservation: Landscape Ecology, v. 35, p. 1417-1434, https://doi.org/10.1007/s10980-020-01024-6.","productDescription":"18 p.","startPage":"1417","endPage":"1434","ipdsId":"IP-112276","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395914,"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 -102.052001953125,\n 36.99377838872517\n ],\n [\n -98.360595703125,\n 36.99377838872517\n ],\n [\n -98.360595703125,\n 40.01078714046552\n ],\n [\n -102.052001953125,\n 40.01078714046552\n ],\n [\n -102.052001953125,\n 36.99377838872517\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","noUsgsAuthors":false,"publicationDate":"2020-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Schindler, Alexander R.","contributorId":276127,"corporation":false,"usgs":false,"family":"Schindler","given":"Alexander","email":"","middleInitial":"R.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":834583,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":834584,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hagen, Christian A.","contributorId":272575,"corporation":false,"usgs":false,"family":"Hagen","given":"Christian A.","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":834585,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ross, Beth 0000-0001-5634-4951 bross@usgs.gov","orcid":"https://orcid.org/0000-0001-5634-4951","contributorId":199242,"corporation":false,"usgs":true,"family":"Ross","given":"Beth","email":"bross@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":834586,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70211373,"text":"70211373 - 2020 - A multi-model approach toward understanding iron fouling at rock-fill drainage sites along roadways in New Hampshire, USA","interactions":[],"lastModifiedDate":"2020-07-29T13:36:16.296382","indexId":"70211373","displayToPublicDate":"2020-05-14T10:58:26","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5814,"text":"SN Applied Sciences","active":true,"publicationSubtype":{"id":10}},"title":"A multi-model approach toward understanding iron fouling at rock-fill drainage sites along roadways in New Hampshire, USA","docAbstract":"

Factors affecting iron fouling in wet areas adjacent to roadways were investigated by collecting field rock cut and aqueous physicochemical data; developing exploratory predictive models; and developing geochemical models. Basic data included the identification of iron fouling from aerial imagery and field visits at 374 New Hampshire rock cut locations, and their associated rock-fill sites. Based on field water quality measurements from wet areas at 36 of the rock-fill sites, the occurrence of iron fouling was associated with higher values of specific conductance, lower concentrations of dissolved oxygen and lower pH compared to areas without iron fouling. A statistical model, using boosted regression trees, was developed to predict the occurrence of iron fouling in wet areas adjacent to roadways where rock-fill from nearby rock cuts was used in roadway construction. The model was used to develop a continuous iron fouling probability map for the state of New Hampshire that can be used to better understand the occurrence of iron fouling. Geochemical models illustrate how iron fouling of waters increases along roadways built with fill from sulfidic rock cuts as a result of acid generation from pyrite dissolution and ferrous iron (Fe2+) oxidation and increases in areas with greater specific conductance from deicing runoff caused by cation exchange. More iron is precipitated as goethite in simulations that include pyrite, and in simulations with deicing salts added, indicating that rock-fill sites with rocks that contain pyrite and water with greater salt content could have enhanced iron fouling.

","language":"English","publisher":"Springer","doi":"10.1007/s42452-020-2849-2","usgsCitation":"Lombard, M.A., Lombard, P.J., Brown, C., and Degnan, J., 2020, A multi-model approach toward understanding iron fouling at rock-fill drainage sites along roadways in New Hampshire, USA: SN Applied Sciences, 1073, 16 p., https://doi.org/10.1007/s42452-020-2849-2.","productDescription":"1073, 16 p.","ipdsId":"IP-100784","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":456777,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s42452-020-2849-2","text":"Publisher Index Page"},{"id":436987,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TUOH95","text":"USGS data release","linkHelpText":"Iron fouling data associated with drainage from roadway sites constructed with rock fill in New 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Melissa A. 0000-0001-5924-6556 mlombard@usgs.gov","orcid":"https://orcid.org/0000-0001-5924-6556","contributorId":198254,"corporation":false,"usgs":true,"family":"Lombard","given":"Melissa","email":"mlombard@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":794079,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lombard, Pamela J. 0000-0002-0983-1906","orcid":"https://orcid.org/0000-0002-0983-1906","contributorId":203509,"corporation":false,"usgs":true,"family":"Lombard","given":"Pamela","email":"","middleInitial":"J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":794080,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Craig J. 0000-0002-3858-3964","orcid":"https://orcid.org/0000-0002-3858-3964","contributorId":210450,"corporation":false,"usgs":true,"family":"Brown","given":"Craig J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":794081,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Degnan, James R. 0000-0002-5665-9010","orcid":"https://orcid.org/0000-0002-5665-9010","contributorId":218796,"corporation":false,"usgs":true,"family":"Degnan","given":"James R.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":794082,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210180,"text":"70210180 - 2020 - Do empirical observations support commonly-held climate change range shift hypotheses? A systematic review protocol","interactions":[],"lastModifiedDate":"2020-05-19T12:35:26.049125","indexId":"70210180","displayToPublicDate":"2020-05-14T07:27:54","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5897,"text":"Environmental Evidence","active":true,"publicationSubtype":{"id":10}},"title":"Do empirical observations support commonly-held climate change range shift hypotheses? A systematic review protocol","docAbstract":"Background \nAmong the most widely anticipated climate-related impacts to biodiversity are geographic range shifts, whereby species shift their spatial distribution in response to changing climate conditions. In particular, a series of commonly articulated hypotheses have emerged: species are expected to shift their distributions to higher latitudes, greater elevations, and deeper depths in response to climate change, reflecting an underlying hypothesis that species will move to cooler locations to track spatial changes in the temperature of their current range. Yet, many species are not demonstrating range shifts consistent with these hypotheses. Resolving this discrepancy and providing effective explanations for the observed variability in species’ range shifts is urgently needed to help support a range of natural resource management decisions. Here, we propose a protocol to review the body of evidence for commonly-held climate change range shift hypotheses at the species level focusing on observed latitudinal, longitudinal, elevational, and depth shifts in response to temperature and precipitation changes. We aim to answer the question: what is the impact of anthropogenic climate change (specifically changes in temperature and precipitation) on species ranges?\n \nMethods \nIn this review protocol, we propose to conduct a systematic search of literature from internet databases and search engines in English. Articles will be screened in a two-stage process (title/abstract and full text) to evaluate whether they meet a list of eligibility criteria (e.g., presents species-level data, compares >1 time period). Initial data coding and extraction will be completed by four reviewers and checked by a secondary reviewer from among our co-authors. We will perform a formal meta-analysis to document estimated effect size using the subset of available range-shift data expressed in distance per time (e.g., km/decade). We will also use multinomial logistic regression models to assess the probability that species are shifting in a direction that supports our hypotheses (i.e. towards higher latitudes, greater elevations, and deeper depths). We will account for study methodology as a potential source of variation.","language":"English","publisher":"Springer Nature","doi":"10.1186/s13750-020-00194-9","collaboration":"","usgsCitation":"Rubenstein, M.A., Weiskopf, S.R., Carter, S., Eaton, M.J., Johnson, C., Lynch, A., Miller, B.W., Morelli, T.L., Rodriguez, M.A., Terando, A., and Thompson, L., 2020, Do empirical observations support commonly-held climate change range shift hypotheses? A systematic review protocol: Environmental Evidence, v. 9, 10, 10 p., https://doi.org/10.1186/s13750-020-00194-9.","productDescription":"10, 10 p.","ipdsId":"IP-113427","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":456784,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s13750-020-00194-9","text":"Publisher Index Page"},{"id":374913,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","noUsgsAuthors":false,"publicationDate":"2020-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Rubenstein, Madeleine A. 0000-0001-8569-781X mrubenstein@usgs.gov","orcid":"https://orcid.org/0000-0001-8569-781X","contributorId":203206,"corporation":false,"usgs":true,"family":"Rubenstein","given":"Madeleine","email":"mrubenstein@usgs.gov","middleInitial":"A.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":789445,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weiskopf, Sarah R. 0000-0002-5933-8191","orcid":"https://orcid.org/0000-0002-5933-8191","contributorId":207699,"corporation":false,"usgs":true,"family":"Weiskopf","given":"Sarah","email":"","middleInitial":"R.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":789446,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carter, Shawn 0000-0002-0045-4681","orcid":"https://orcid.org/0000-0002-0045-4681","contributorId":216490,"corporation":false,"usgs":true,"family":"Carter","given":"Shawn","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":789447,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eaton, Mitchell J. 0000-0001-7324-6333","orcid":"https://orcid.org/0000-0001-7324-6333","contributorId":213526,"corporation":false,"usgs":true,"family":"Eaton","given":"Mitchell","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":789448,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Ciara","contributorId":224775,"corporation":false,"usgs":false,"family":"Johnson","given":"Ciara","affiliations":[{"id":12909,"text":"George Mason University","active":true,"usgs":false}],"preferred":false,"id":789449,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lynch, Abigail 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":220490,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":789450,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Miller, Brian W. 0000-0003-1716-1161 bwmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-1716-1161","contributorId":191731,"corporation":false,"usgs":true,"family":"Miller","given":"Brian","email":"bwmiller@usgs.gov","middleInitial":"W.","affiliations":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"preferred":false,"id":789451,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":789452,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rodriguez, Mari Angel 0000-0002-3372-1897","orcid":"https://orcid.org/0000-0002-3372-1897","contributorId":224776,"corporation":false,"usgs":true,"family":"Rodriguez","given":"Mari","email":"","middleInitial":"Angel","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":789453,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Terando, Adam 0000-0002-9280-043X","orcid":"https://orcid.org/0000-0002-9280-043X","contributorId":205908,"corporation":false,"usgs":true,"family":"Terando","given":"Adam","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":789454,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Thompson, Laura 0000-0002-7884-6001","orcid":"https://orcid.org/0000-0002-7884-6001","contributorId":207364,"corporation":false,"usgs":true,"family":"Thompson","given":"Laura","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":789455,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70210092,"text":"ofr20201040 - 2020 - Assessment of rangeland ecosystem conditions in Grand Canyon-Parashant National Monument, Arizona","interactions":[],"lastModifiedDate":"2020-05-14T11:55:22.364325","indexId":"ofr20201040","displayToPublicDate":"2020-05-13T13:43:13","publicationYear":"2020","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":"2020-1040","displayTitle":"Assessment of Rangeland Ecosystem Conditions in Grand Canyon-Parashant National Monument, Arizona","title":"Assessment of rangeland ecosystem conditions in Grand Canyon-Parashant National Monument, Arizona","docAbstract":"

Sustainability of dryland ecosystems depends on the functionality of soil-vegetation feedbacks that affect ecosystem processes, such as nutrient cycling, water capture and retention, soil erosion and deposition, and plant establishment and reproduction. Useful, common indicators can provide information on soil and site stability, hydrologic function, and biotic integrity. Evaluation of rangeland health thus relies on describing the condition and sustainability of these individual, measurable, and observable indicators that are linked to important ecosystem processes. This report focuses on the ~200,000 acres of the Grand Canyon-Parashant National Monument that is administered by the National Park Service (NPS)—one of the largest NPS units where livestock grazing is a permitted land-use activity. Many ecosystems in the monument are characterized by a low degree of resilience to improper grazing because of low and variable precipitation. The monument is marked by a high degree of environmental heterogeneity, including a large elevation gradient, widely differing precipitation patterns, a diversity of geologic substrates, and unique combinations of plant species.

The objective of this report is to (1) increase our understanding of the underlying landscape, soil, and climate setting factors that affect Grand Canyon-Parashant National Monument dryland ecosystem structure and function (also referred to as land potential) and (2) characterize the condition of monument ecosystems in relation to management concepts, such as rangeland health.

Data were analyzed by elevation zone using both univariate and multivariate approaches. Survey results document the high level of diversity within the study area, including 15 unique soil taxa and 271 species of plants. We collected three new plant species for Grand Canyon-Parashant National Monument and 17 new species for the NPS portion of the monument. Results also document a strong association between rangeland health indicators and elevation, topographic setting, and soils. Soil factors found to explain important variation across plots include the amount of exposed bedrock, soil rockiness, soil texture (and associated hydrologic properties), and soil depth. We also found that dominant species turnover across elevation may represent species’ differences in adaptation to climates, including Larrea tridentata, Coleogyne ramosissima, and Artemisia spp. Bromus rubens is the most common invasive species of concern recorded in this study, but other common invasive species are Bromus tectorum, Erodium cicutarium, and Schismus arabicus. Correlations between an index of cattle use and indicators of rangeland health suggest that areas with high cattle use have increased bare ground, decreased ground cover, increased frequency of Schismus arabicus, decreased cover of Coleogyne ramosissima and Ephedra spp., and increased cover of Gutierrezia spp. The few strong correlations observed between indicators of vascular plant community cover or abundance and indicators of cattle activity support rangeland assessment and monitoring strategies that do not rely solely on plant-based indicators are needed.

This work supports management of dryland ecosystems, including Grand Canyon-Parashant National Monument, using concepts of land potential. We conclude the report with recommendations on improving existing land-potential-based classification systems, associated interpretations, and methods for moving forward with a Grand Canyon-Parashant National Monument rangeland monitoring program.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201040","usgsCitation":"Duniway, M.C., and Palmquist, E.C., 2020, Assessment of rangeland ecosystem conditions in Grand Canyon-Parashant National Monument, Arizona: U.S. Geological Survey Open-File Report 2020–1040, 42 p., https://doi.org/10.3133/ofr20201040.","productDescription":"Report: viii, 42 p.; Data Release","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-106479","costCenters":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"links":[{"id":374803,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SJSJHT","linkHelpText":"Rangeland Ecosystem Data, Grand Canyon - Parashant National Monument, AZ, USA"},{"id":374801,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1040/coverthb.jpg"},{"id":374802,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1040/ofr20201040.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon-Parashant National Monument","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.005126953125,\n 35.679609609368576\n ],\n [\n -111.57714843749999,\n 35.679609609368576\n ],\n [\n -111.57714843749999,\n 36.97622678464096\n ],\n [\n -114.005126953125,\n 36.97622678464096\n ],\n [\n -114.005126953125,\n 35.679609609368576\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, 
Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001

","tableOfContents":"","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2020-05-13","noUsgsAuthors":false,"publicationDate":"2020-05-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":789072,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palmquist, Emily C. 0000-0003-1069-2154 epalmquist@usgs.gov","orcid":"https://orcid.org/0000-0003-1069-2154","contributorId":5669,"corporation":false,"usgs":true,"family":"Palmquist","given":"Emily","email":"epalmquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":789073,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70259109,"text":"70259109 - 2020 - Sources and dynamics of international funding for waterfowl conservation in the Prairie Pothole Region of North America","interactions":[],"lastModifiedDate":"2024-09-27T13:14:57.340674","indexId":"70259109","displayToPublicDate":"2020-05-13T08:10:11","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3777,"text":"Wildlife Research","active":true,"publicationSubtype":{"id":10}},"title":"Sources and dynamics of international funding for waterfowl conservation in the Prairie Pothole Region of North America","docAbstract":"

Context: Funding for habitat-management programs to maintain population viability is critical for conservation of migratory species; however, such financial resources are limited and can vary greatly over time. The Prairie Pothole Region (PPR) of North America is an excellent system for examining spatiotemporal patterns of funding for waterfowl conservation, because this transboundary region is crucial for reproduction and migration of many duck species.

Aims: We examine large-scale spatiotemporal variation in funding for waterfowl habitat conservation in the PPR during 2007–2016. Specifically, we quantify major sources of funding and how funds were directed towards particular geographies within Canada and the USA. We further examine how sources and magnitude of funding changed over time and in relation to numbers of hunters.

Methods: We assembled data from multiple sources to quantify funding (in US$, 2016 values) from (1) USA states and non-government organisations (NGOs), (2) Canadian government and NGOs, and (3) major USA-based federal funding sources to the Canadian and US portions of the PPR between 2007 and 2016. We fit linear regressions to examine spatiotemporal variation in funding and in numbers of active waterfowl hunters in the USA.

Key results: Whereas annual funding for the Canadian portion was comparatively stable throughout the 10 years (range: US$25–41 million), funding for the US portion was dynamic and increased between the first (range: US$36–48 million) and second (range: US$43–117 million) 5-year intervals, despite concurrent declines in the number of active waterfowl hunters in the USA.

Conclusions: We discovered contrasting trends and dynamics in multiple streams of funding for habitat conservation on each side of the border bisecting the PPR. These findings and approaches warrant closer attention by wildlife professionals. Work is needed to analyse past and future funding for habitat conservation, which can then be used to refine plans for maintaining or recovering populations of migratory species.

Implications: Although funding for waterfowl habitat conservation in the PPR increased over the past decade, trends were inconsistent among subregions and uncertain for some major funding sources. Better understanding of the complexities in funding will help inform more efficient long-term planning efforts for conservation of waterfowl and other migratory species.

","language":"English","publisher":"CSIRO","doi":"10.1071/WR19100","usgsCitation":"Mattsson, B.J., Devries, J., Dubovsky, J.A., Semmens, D., Thogmartin, W.E., Derbridge, J.J., and Lopez-Hoffman, L., 2020, Sources and dynamics of international funding for waterfowl conservation in the Prairie Pothole Region of North America: Wildlife Research, v. 47, no. 4, p. 279-295, https://doi.org/10.1071/WR19100.","productDescription":"17 p.","startPage":"279","endPage":"295","ipdsId":"IP-101539","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":467290,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1071/wr19100","text":"Publisher Index Page"},{"id":462329,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mattsson, Brady J.","contributorId":197269,"corporation":false,"usgs":false,"family":"Mattsson","given":"Brady","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":914175,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Devries, Jim","contributorId":344571,"corporation":false,"usgs":false,"family":"Devries","given":"Jim","affiliations":[{"id":7182,"text":"Ducks Unlimited Canada","active":true,"usgs":false}],"preferred":false,"id":914176,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dubovsky, James A.","contributorId":201247,"corporation":false,"usgs":false,"family":"Dubovsky","given":"James","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":914177,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Semmens, Darius J. 0000-0001-7924-6529","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":64201,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":914178,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":914179,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Derbridge, Jonathan J. 0000-0003-3074-3166","orcid":"https://orcid.org/0000-0003-3074-3166","contributorId":290285,"corporation":false,"usgs":false,"family":"Derbridge","given":"Jonathan","email":"","middleInitial":"J.","affiliations":[{"id":62394,"text":"The University of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":914247,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lopez-Hoffman, Laura","contributorId":231064,"corporation":false,"usgs":false,"family":"Lopez-Hoffman","given":"Laura","affiliations":[{"id":28236,"text":"Univ of Arizona","active":true,"usgs":false}],"preferred":false,"id":914180,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70213352,"text":"70213352 - 2020 - Effects of climate change on plague exposure pathways and resulting disease dynamics","interactions":[],"lastModifiedDate":"2021-02-03T19:40:21.028748","indexId":"70213352","displayToPublicDate":"2020-05-12T12:24:55","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":251,"text":"Final Report","active":false,"publicationSubtype":{"id":4}},"seriesNumber":"16 RC01-012","title":"Effects of climate change on plague exposure pathways and resulting disease dynamics","docAbstract":"

Introduction and Objectives: Sylvatic plague, a zoonotic flea-borne disease, caused by the bacterium Yersinia pestis, is relevant to the Department of Defense (DOD), because prairie dogs and other susceptible rodents are present on military installations in several western states. Arthropod-borne diseases, like plague, are thought to be particularly sensitive to local climate conditions. Expected changes in temperature and humidity over the next several decades will likely increase the geographical expansion of plague outbreaks in wildlife. Through a combination of field and laboratory work, along with data-driven modeling, we evaluated the potential effects of climate change on plague exposure pathways in prairie dogs and associated rodents to provide guidance to DOD partners regarding the potential for future outbreaks. Briefly, our specific objectives were to determine the relation between local climate conditions and the prevalence of plague and other pathogens while assessing the ecological roles of specific rodent hosts and vector species in plague dynamics, evaluate flea intensity on rodent hosts and in burrows in relation to local climate conditions, and develop models to predict the effects of climate change on plague dynamics.


Technical Approach: Using data and samples collected during a large field study on the effectiveness of vaccination to manage plague in prairie dogs, we assessed rodent/flea assemblages, pathogen prevalence in fleas, and determined how local climate conditions influence flea development rates and relative abundance. Live animals (prairie dogs and some small rodents) were trapped to collect fleas and other samples on 46 prairie dog plots in 6 western states, many sites near DOD lands. At seven additional locations on a latitudinal gradient, fleas were collected from burrows several times per year to assess seasonality and effects of local climate conditions on flea abundance. These data were then used to develop predictive models that could be used to test specific hypotheses.


Results: We determined that flea developmental rates, on-host flea abundance, species composition of the flea community, and burrow temperatures varied across a latitudinal gradient. Rodent and flea community composition and abundance differed geographically and were highly specialized. Flea-switching between prairie dogs and short-lived rodents was rare. Flea development rates, on-host flea abundance, and burrow temperatures increased with increasing ambient temperature. Although relative humidity can affect flea development, burrow humidity was uniformly high (~85%) across sampling sites and seasons. A large increase in the number of fleas found on a prairie dog colony, coupled with a greater number of infested burrows, could have substantial effects on plague dynamics in the western United States as the climate warms. In addition to affecting flea load, climate change may also influence body condition of prairie dogs by reducing the amount of forage. This may result in animals being more tolerant of high flea loads (less engaged in grooming behavior) and more vulnerable to disease.

","language":"English","publisher":"Department of Defense","usgsCitation":"Rocke, T.E., Russell, R., Samuel, M., Abbott, R.C., and Poje, J., 2020, Effects of climate change on plague exposure pathways and resulting disease dynamics: Final Report 16 RC01-012, vii, 61 p.","productDescription":"vii, 61 p.","ipdsId":"IP-118526","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":378525,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":378498,"type":{"id":15,"text":"Index Page"},"url":"https://www.serdp-estcp.org/Program-Areas/Resource-Conservation-and-Resiliency/Natural-Resources/Species-Ecology-and-Management/RC-2634"}],"country":"United States","state":"Arizona, Montana, South Dakota, Texas, Utah, Wyoming","city":"Cedar City","otherGeospatial":"Buffalo Gap National Grassland, Charles M. Russell National Wildlife Refuge, Coyote Basin, Espee Ranch, Lower Brule Sioux tribal lands, Pitchfork Ranch, Rita Blanca National Grassland, Wind Cave National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.51074218749999,\n 34.92197103616377\n ],\n [\n -102.26074218749999,\n 34.92197103616377\n ],\n [\n -102.26074218749999,\n 48.86471476180277\n ],\n [\n -113.51074218749999,\n 48.86471476180277\n ],\n [\n -113.51074218749999,\n 34.92197103616377\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":799082,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Russell, Robin E. 0000-0001-8726-7303","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":219536,"corporation":false,"usgs":true,"family":"Russell","given":"Robin E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":799083,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Samuel, Michael D.","contributorId":206351,"corporation":false,"usgs":false,"family":"Samuel","given":"Michael D.","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":799084,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Abbott, Rachel C. 0000-0003-4820-9295 rabbott@usgs.gov","orcid":"https://orcid.org/0000-0003-4820-9295","contributorId":1183,"corporation":false,"usgs":true,"family":"Abbott","given":"Rachel","email":"rabbott@usgs.gov","middleInitial":"C.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":799085,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Poje, Julia","contributorId":248780,"corporation":false,"usgs":false,"family":"Poje","given":"Julia","affiliations":[{"id":13562,"text":"University of Wisconsin, Madison","active":true,"usgs":false}],"preferred":false,"id":799086,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208874,"text":"sim3453 - 2020 - Altitude of the potentiometric surface in the Mississippi River Valley alluvial aquifer, spring 2018","interactions":[],"lastModifiedDate":"2025-05-14T19:57:23.738641","indexId":"sim3453","displayToPublicDate":"2020-05-12T12:23:31","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3453","displayTitle":"Altitude of the Potentiometric Surface in the Mississippi River Valley Alluvial Aquifer, Spring 2018","title":"Altitude of the potentiometric surface in the Mississippi River Valley alluvial aquifer, spring 2018","docAbstract":"

A potentiometric-surface map for spring 2018 was created for the Mississippi River Valley alluvial (MRVA) aquifer using available groundwater-altitude data from 1,126 wells completed in the MRVA aquifer and from the altitude of the top of the water surface in area rivers from 66 streamgages. Personnel from Arkansas Natural Resources Commission, Arkansas Department of Health, Arkansas Geological Survey, Illinois Department of Agriculture, Illinois State Water Survey, Louisiana Department of Natural Resources, Louisiana Department of Transportation and Development, Mississippi Department of Environmental Quality, Missouri Department of Natural Resources, Yazoo Mississippi Delta Joint Water Management District, U.S. Department of Agriculture-Natural Resources Conservation Service, and U.S. Geological Survey (USGS) routinely collect groundwater-level data from wells screened in the MRVA aquifer. The USGS and the U.S. Army Corps of Engineers routinely collect data on river stage and streamflow for the rivers overlying the MRVA aquifer area. The potentiometric-surface map for 2018 was created utilizing existing groundwater and surface-water altitudes to support investigations to characterize the MRVA aquifer as part of the USGS Water Availability and Use Science Program.

Sufficient data were available to map the potentiometric surface of the MRVA aquifer for spring 2018 for about 87 percent of the aquifer area. The potentiometric contours ranged from 10 to 340 feet above North American Vertical Datum of 1988. The regional direction of groundwater flow was generally to the south-southwest, except in areas of groundwater-altitude depressions, where groundwater flowed into the depression, and near rivers, where flow can be from aquifer to the river or from the river into the aquifer. There are large depressions in the potentiometric-surface map in the lower one-half of the Cache region and in most of the Grand Prairie and Delta regions.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3453","programNote":"Water Availability and Use Science Program","usgsCitation":"McGuire, V.L., Seanor, R.C., Asquith, W.H., Nottmeier, A.M., Smith, D.C., Tollett, R.W., Kress, W.H., and Strauch, K.R., 2020, Altitude of the potentiometric surface in the Mississippi River Valley alluvial aquifer, spring 2018: U.S. Geological Survey Scientific Investigations Map 3453, 13 p., 5 sheets, https://dx.doi.org/10.3133/sim3453.","productDescription":"Pamphlet: vi, 13 p.; 5 Sheets: 30.00 x 46.00 inches or smaller; Data Release","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-107434","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":374521,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3453/sim3453_sheet2.pdf","text":"Sheet 2—St. Francis and Cache MAP regions","size":"3.76 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3453 Sheet 2"},{"id":374552,"rank":8,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3453/coverthb4.jpg"},{"id":374524,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3453/sim3453_sheet5.pdf","text":"Sheet 5—Atchafalaya and Deltaic and Chenier Plain MAP regions","size":"6.34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3453 Sheet 5"},{"id":374523,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3453/sim3453_sheet4.pdf","text":"Sheet 4—Delta MAP region","size":"1.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3453 Sheet 4"},{"id":374522,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3453/sim3453_sheet3.pdf","text":"Sheet 3—Boeuf and Grand Prairie MAP regions","size":"2.28 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3453 Sheet 3"},{"id":374520,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3453/sim3453_sheet1.pdf","text":"Sheet 1—All Mississippi Alluvial Plain (MAP) regions","size":"14.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3453 Sheet 1"},{"id":374519,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3453/sim3453_pamphlet.pdf","text":"Pamphlet","size":"5.44 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM Pamphlet 3453"},{"id":374525,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P992HD1R","text":"USGS data release","linkHelpText":"Datasets used to map the potentiometric surface, Mississippi River Valley alluvial aquifer, spring 2018"}],"country":"United States","otherGeospatial":"Mississippi River Valley alluvial aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.4287109375,\n 37.09023980307208\n ],\n [\n -90.087890625,\n 36.31512514748051\n ],\n [\n -91.318359375,\n 34.92197103616377\n ],\n [\n -91.8896484375,\n 33.50475906922609\n ],\n [\n -92.3291015625,\n 30.826780904779774\n ],\n [\n -91.0986328125,\n 29.76437737516313\n ],\n [\n -89.56054687499999,\n 28.92163128242129\n ],\n [\n -88.857421875,\n 29.305561325527698\n ],\n [\n -89.033203125,\n 29.611670115197377\n ],\n [\n -89.56054687499999,\n 30.486550842588485\n ],\n [\n -90.791015625,\n 30.713503990354965\n ],\n [\n -90.615234375,\n 32.175612478499325\n ],\n [\n -90.263671875,\n 33.137551192346145\n ],\n [\n -89.296875,\n 35.209721645221386\n ],\n [\n -87.978515625,\n 36.31512514748051\n ],\n [\n -87.978515625,\n 37.16031654673677\n ],\n [\n -88.8134765625,\n 37.33522435930639\n ],\n [\n -89.4287109375,\n 37.09023980307208\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-05-12","noUsgsAuthors":false,"publicationDate":"2020-05-12","publicationStatus":"PW","contributors":{"authors":[{"text":"McGuire, Virginia L. 0000-0002-3962-4158 vlmcguir@usgs.gov","orcid":"https://orcid.org/0000-0002-3962-4158","contributorId":404,"corporation":false,"usgs":true,"family":"McGuire","given":"Virginia","email":"vlmcguir@usgs.gov","middleInitial":"L.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":783792,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Seanor, Ronald C. 0000-0001-5735-5580","orcid":"https://orcid.org/0000-0001-5735-5580","contributorId":218443,"corporation":false,"usgs":true,"family":"Seanor","given":"Ronald","email":"","middleInitial":"C.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":783793,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Asquith, William H. 0000-0002-7400-1861 wasquith@usgs.gov","orcid":"https://orcid.org/0000-0002-7400-1861","contributorId":1007,"corporation":false,"usgs":true,"family":"Asquith","given":"William","email":"wasquith@usgs.gov","middleInitial":"H.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":783794,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nottmeier, Anna M. 0000-0002-0205-0955 anottmeier@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-0955","contributorId":5283,"corporation":false,"usgs":true,"family":"Nottmeier","given":"Anna","email":"anottmeier@usgs.gov","middleInitial":"M.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":783797,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, David C. 0000-0002-9645-2444 dvsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-9645-2444","contributorId":206512,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"dvsmith@usgs.gov","middleInitial":"C.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":783798,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tollett, Roland W. 0000-0002-4726-5845 rtollett@usgs.gov","orcid":"https://orcid.org/0000-0002-4726-5845","contributorId":1896,"corporation":false,"usgs":true,"family":"Tollett","given":"Roland","email":"rtollett@usgs.gov","middleInitial":"W.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":783799,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kress, Wade H. 0000-0002-6833-028X","orcid":"https://orcid.org/0000-0002-6833-028X","contributorId":223007,"corporation":false,"usgs":true,"family":"Kress","given":"Wade H.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":783795,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Strauch, Kellan R. 0000-0002-7218-2099","orcid":"https://orcid.org/0000-0002-7218-2099","contributorId":208562,"corporation":false,"usgs":true,"family":"Strauch","given":"Kellan R.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":783796,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70228550,"text":"70228550 - 2020 - Good practices for species distribution modeling of deep-sea corals and sponges for resource management: Data collection, analysis, validation, and communication","interactions":[],"lastModifiedDate":"2022-02-14T18:12:27.741823","indexId":"70228550","displayToPublicDate":"2020-05-12T11:56:02","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Good practices for species distribution modeling of deep-sea corals and sponges for resource management: Data collection, analysis, validation, and communication","docAbstract":"Resource managers in the United States and worldwide are tasked with identifying and mitigating trade-offs between human activities in the deep sea (e.g., fishing, energy development, and mining) and their impacts on habitat-forming invertebrates, including deep-sea corals and sponges (DSCS). Related management decisions require information about where DSCS occur and in what densities. Species distribution modeling (SDM) provides a cost-effective means of identifying potential DSCS habitat over large areas to inform these management decisions and data collection. Here we describe good practices for DSCS SDM, especially in the context of data collection and management applications. Managers typically need information regarding DSCS encounter probabilities, densities, and sizes, defined at sub-regional to basin-wide scales and validated using subsequent, targeted data collections. To realistically achieve these goals, we suggest analysts: 1) integrate available data sources in SDMs including fine-scale visual sampling and broad-scale resource surveys (e.g., fisheries trawl surveys); and 2) include environmental predictor variables representing multiple spatial scales, model residual spatial autocorrelation, and quantify prediction uncertainty. When possible, models fitted to presence-absence and density data are preferred over models fitted only to presence data, which are difficult to validate and can confound estimated probability of occurrence or density with sampling effort. Ensembles of models can provide robust predictions, while multi-species models leverage information across taxa and facilitate community inference. To facilitate the use of models by managers, predictions should be expressed in units that are widely understood and validated at an appropriate spatial scale using a sampling design that provides strong statistical inference. We present three case studies for the Pacific Ocean that illustrate good practices with respect to data collection, modeling, and validation; these case studies demonstrate it is possible to implement our good practices in real-world settings.","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2020.00303","usgsCitation":"Winship, A.J., Thorson, J.T., Clarke, M., Coleman, H.M., Costa, B.M., Georgian, S., Gillett, D., Gruss, A., Henderson, M., Hourigan, T.F., Huff, D.D., Kreidler, N., Pirtle, J.L., Olson, J.V., Poti, M., Rooper, C.N., Sigler, M.F., Viehman, T.S., and Whitmire, C.E., 2020, Good practices for species distribution modeling of deep-sea corals and sponges for resource management: Data collection, analysis, validation, and communication: Frontiers in Marine Science, v. 7, p. 1-7, https://doi.org/10.3389/fmars.2020.00303.","productDescription":"303, 15 p.","startPage":"1","endPage":"7","ipdsId":"IP-117999","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":456794,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2020.00303","text":"Publisher Index Page"},{"id":395904,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","noUsgsAuthors":false,"publicationDate":"2020-05-12","publicationStatus":"PW","contributors":{"editors":[{"text":"Herrera, Santiago","contributorId":278597,"corporation":false,"usgs":false,"family":"Herrera","given":"Santiago","email":"","affiliations":[{"id":16160,"text":"Lehigh University","active":true,"usgs":false}],"preferred":false,"id":834833,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Winship, Arliss J","contributorId":275149,"corporation":false,"usgs":false,"family":"Winship","given":"Arliss","email":"","middleInitial":"J","affiliations":[{"id":56719,"text":"CSS, Inc., Fairfax, VA, USA","active":true,"usgs":false}],"preferred":false,"id":834550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thorson, James T.","contributorId":146580,"corporation":false,"usgs":false,"family":"Thorson","given":"James","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":834551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clarke, M. Elizabeth","contributorId":205699,"corporation":false,"usgs":false,"family":"Clarke","given":"M. Elizabeth","affiliations":[{"id":37147,"text":"Office of the Science Director, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration. Montlake Blvd E., Seattle, WA 98112, USA.","active":true,"usgs":false}],"preferred":false,"id":834552,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coleman, Heather M.","contributorId":276106,"corporation":false,"usgs":false,"family":"Coleman","given":"Heather","email":"","middleInitial":"M.","affiliations":[{"id":16685,"text":"National Oceanic and Atmopheric Administration","active":true,"usgs":false}],"preferred":false,"id":834553,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Costa, Bryan M.","contributorId":146979,"corporation":false,"usgs":false,"family":"Costa","given":"Bryan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":834821,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Georgian, Samuel","contributorId":276107,"corporation":false,"usgs":false,"family":"Georgian","given":"Samuel","email":"","affiliations":[{"id":16685,"text":"National Oceanic and Atmopheric Administration","active":true,"usgs":false}],"preferred":false,"id":834554,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gillett, David","contributorId":276108,"corporation":false,"usgs":false,"family":"Gillett","given":"David","email":"","affiliations":[{"id":16685,"text":"National Oceanic and Atmopheric Administration","active":true,"usgs":false}],"preferred":false,"id":834555,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gruss, Arnaud","contributorId":278591,"corporation":false,"usgs":false,"family":"Gruss","given":"Arnaud","email":"","affiliations":[{"id":16685,"text":"National Oceanic and Atmopheric Administration","active":true,"usgs":false}],"preferred":false,"id":834822,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Henderson, Mark J. 0000-0002-2861-8668 mhenderson@usgs.gov","orcid":"https://orcid.org/0000-0002-2861-8668","contributorId":198609,"corporation":false,"usgs":true,"family":"Henderson","given":"Mark J.","email":"mhenderson@usgs.gov","affiliations":[],"preferred":false,"id":834549,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hourigan, Thomas F.","contributorId":146754,"corporation":false,"usgs":false,"family":"Hourigan","given":"Thomas","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":834823,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Huff, David D.","contributorId":171694,"corporation":false,"usgs":false,"family":"Huff","given":"David","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":834824,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kreidler, Nissa","contributorId":278592,"corporation":false,"usgs":false,"family":"Kreidler","given":"Nissa","email":"","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":834825,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Pirtle, Jodi L.","contributorId":211305,"corporation":false,"usgs":false,"family":"Pirtle","given":"Jodi","email":"","middleInitial":"L.","affiliations":[{"id":38223,"text":"National Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":834826,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Olson, John V.","contributorId":278593,"corporation":false,"usgs":false,"family":"Olson","given":"John","email":"","middleInitial":"V.","affiliations":[{"id":16685,"text":"National Oceanic and Atmopheric Administration","active":true,"usgs":false}],"preferred":false,"id":834827,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Poti, Matthew","contributorId":278594,"corporation":false,"usgs":false,"family":"Poti","given":"Matthew","email":"","affiliations":[{"id":16685,"text":"National Oceanic and Atmopheric Administration","active":true,"usgs":false}],"preferred":false,"id":834828,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Rooper, Christopher N.","contributorId":278595,"corporation":false,"usgs":false,"family":"Rooper","given":"Christopher","email":"","middleInitial":"N.","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":834829,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Sigler, Michael F.","contributorId":278596,"corporation":false,"usgs":false,"family":"Sigler","given":"Michael","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":834830,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Viehman, T. Shay","contributorId":259297,"corporation":false,"usgs":false,"family":"Viehman","given":"T.","email":"","middleInitial":"Shay","affiliations":[{"id":16685,"text":"National Oceanic and Atmopheric Administration","active":true,"usgs":false}],"preferred":true,"id":834831,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Whitmire, Curt E.","contributorId":205702,"corporation":false,"usgs":false,"family":"Whitmire","given":"Curt","email":"","middleInitial":"E.","affiliations":[{"id":37149,"text":"Fishery Resource Analysis and Monitoring Division, Northwest Fisheries Science Center, National Oceanic and Atmospheric Administration, 99 Pacific Street, Bldg. 255-A, Monterey, California, 97365,","active":true,"usgs":false}],"preferred":false,"id":834832,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70210023,"text":"ofr20201047 - 2020 - Black abalone surveys at Naval Base Ventura County, San Nicolas Island, California: 2019, annual report","interactions":[],"lastModifiedDate":"2020-05-13T11:43:15.475994","indexId":"ofr20201047","displayToPublicDate":"2020-05-12T08:01:56","publicationYear":"2020","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":"2020-1047","displayTitle":"Black Abalone Surveys at Naval Base Ventura County, San Nicolas Island, California: 2019, Annual Report","title":"Black abalone surveys at Naval Base Ventura County, San Nicolas Island, California: 2019, annual report","docAbstract":"

The U.S. Geological Survey Western Ecological Research Center’s Santa Cruz Field Station, Santa Cruz, California, has been funded by the U.S. Navy to continue monitoring a suite of intertidal black abalone sites at San Nicolas Island, California. The nine rocky intertidal sites were established in 1980 by Glenn VanBlaricom (then of the U.S. Fish and Wildlife Service) to study the potential impact of translocated sea otters on the intertidal black abalone population at the island. The sites were monitored from 1981 to 1997, usually annually or semi-annually. Monitoring resumed in 2001, and regular annual monitoring cycles have been conducted at the sites since then. The study sites became particularly important, from a management perspective, after a virulent disease decimated black abalone populations throughout southern California beginning in the mid-1980s. The disease, withering syndrome, was first observed on San Nicolas Island in 1992 and during the next few years reduced the population there by approximately 99 percent. The species was subsequently listed as endangered under the Endangered Species Act in 2009.

The subject of this report is the 2019 monitoring cycle of the sites and how the current status fits into the long-term data at San Nicolas Island. Since 2001, the monitored population has increased nearly tenfold to approximately 8.7 percent of the pre-disease level. This increase has resulted from generally higher levels of recruitment than seen in the first two decades of monitoring, punctuated by a few high recruitment events. Most of the population growth has been at two of the nine sites (sites 7 and 8). This pattern continued in 2019 with increasing numbers at sites 7 and 8 and the highest number of abalone counted and measured island-wide since 1996. However, counts declined at six of the sites during the last year and the increases in counts at sites 7 and 8 barely offset these losses. Recruitment rates have fallen since a peak in 2017 but 2019 continued to show some additional recruitment. The distance between adjacent black abalone, a metric relevant to potential reproduction, has decreased substantially since it was first consistently measured in 2005. Although sand burial can have devastating localized consequences to black abalone, the sand cover data we collected was not sufficient to suggest an obvious temporal or site-based pattern to sedimentation, and there is no indication that this was a factor in any of the declines recorded in 2019. Continued monitoring of these sites can provide island biologists with species trends to aid in adaptive management of the resource.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201047","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Kenner, M.C., 2020, Black abalone surveys at Naval Base Ventura County, San Nicolas Island, California: 2019, annual report: U.S. Geological Survey Open-File Report 2020–1047, 41 p., https://doi.org/10.3133/ofr20201047.","productDescription":"iv, 41 p.","numberOfPages":"41","onlineOnly":"Y","ipdsId":"IP-111797","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":374605,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1047/ofr20201047.pdf","text":"Report","size":"15 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":374604,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1047/coverthb.jpg"}],"country":"United States","state":"California","county":"Ventura County","otherGeospatial":"San Nicolas Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.59922790527342,\n 33.203647816301306\n ],\n [\n -119.42481994628906,\n 33.203647816301306\n ],\n [\n -119.42481994628906,\n 33.293229612321824\n ],\n [\n -119.59922790527342,\n 33.293229612321824\n ],\n [\n -119.59922790527342,\n 33.203647816301306\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819

","tableOfContents":"","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2020-05-12","noUsgsAuthors":false,"publicationDate":"2020-05-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Kenner, Michael C. 0000-0003-4659-461X","orcid":"https://orcid.org/0000-0003-4659-461X","contributorId":208151,"corporation":false,"usgs":true,"family":"Kenner","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":788843,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70210041,"text":"70210041 - 2020 - Inventory and analysis of groundwater resources: Theodore Roosevelt National Park, North Dakota","interactions":[],"lastModifiedDate":"2020-05-12T12:54:58.884549","indexId":"70210041","displayToPublicDate":"2020-05-12T07:51:44","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Inventory and analysis of groundwater resources: Theodore Roosevelt National Park, North Dakota","docAbstract":"Industrial and commercial developments in western North Dakota potentially could affect the sources of water that contribute to wells, spring flow, and seeps within Theodore Roosevelt National Park. Without basic water resources data, accurately predicting the effects of water withdrawals and water quality concerns related to industrial and commercial developments near the park would be challenging. Water resources in the park include surface water and groundwater. The Little Missouri River and its tributaries cross all three Theodore Roosevelt National Park units and are the primary surface-water features in the park. Groundwater resources include well discharges, springs, and seeps. The geology and hydrogeology of Theodore Roosevelt National Park are defined by the surrounding Williston Basin. Four aquifers are sources of groundwater to the park: unconsolidated aquifers including alluvial systems, the upper Fort Union aquifer, the lower Fort Union aquifer, and the Fox Hills-lower Hell Creek aquifer. \n\nData used for wells, springs, seeps, and water quality in this report were compiled from the U.S.\nGeological Survey National Water Information System or from the North Dakota State Water\nCommission. An inventory of 16 wells was completed for sites within the boundaries of the park. In addition to well data, an inventory of 11 springs and seeps was completed. The groundwater-quality analysis had two objectives: (1) to characterize the groundwater chemistry in aquifers underlying the park and (2) to spatially map selected physical properties and chemical constituents of interest. Groundwater-quality data from the North Dakota State Water Commission were summarized, mapped, and used to characterize groundwater for each aquifer in the study area. Spatial concentration distribution maps were constructed for selected physical properties and chemical constituents using summary statistics and exceedances. Piper diagrams were used to classify and characterize groundwater for each aquifer. \n\nFuture research to help fill data gaps in water resources information for Theodore Roosevelt National Park, including recommendations from previous studies, consists of the following: (1) evaluating the variability in discharge from springs and seeps in comparison to changes in precipitation or other recharge sources, (2) evaluating flow control measures for flowing artesian wells, (3) completing a water rights review, and (4) performing routine water-quality monitoring for wells and springs.","language":"English","publisher":"National Park Service","collaboration":"National Park Service Water Rights Division","usgsCitation":"Eldridge, W.G., and Medler, C.J., 2020, Inventory and analysis of groundwater resources: Theodore Roosevelt National Park, North Dakota, xviii, 125 p.","productDescription":"xviii, 125 p.","ipdsId":"IP-114231","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":374650,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":374643,"type":{"id":11,"text":"Document"},"url":"https://irma.nps.gov/DataStore/DownloadFile/639871"}],"country":"United States","state":"North Dakota","otherGeospatial":"Theodore Roosevelt National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.77685546875,\n 46.832012719114765\n ],\n [\n -103.13415527343749,\n 46.832012719114765\n ],\n [\n -103.13415527343749,\n 47.65058757118734\n ],\n [\n -103.77685546875,\n 47.65058757118734\n ],\n [\n -103.77685546875,\n 46.832012719114765\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Eldridge, William G. 0000-0002-3562-728X","orcid":"https://orcid.org/0000-0002-3562-728X","contributorId":208529,"corporation":false,"usgs":true,"family":"Eldridge","given":"William","email":"","middleInitial":"G.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788908,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Medler, Colton J. 0000-0001-6119-5065","orcid":"https://orcid.org/0000-0001-6119-5065","contributorId":201463,"corporation":false,"usgs":true,"family":"Medler","given":"Colton","email":"","middleInitial":"J.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788909,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70210018,"text":"fs20203030 - 2020 - Trends in streamflow, nutrients, and total suspended solids in the Upper White River Basin, Indiana","interactions":[],"lastModifiedDate":"2020-05-12T11:33:15.420536","indexId":"fs20203030","displayToPublicDate":"2020-05-11T15:05:45","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-3030","displayTitle":"Trends in Streamflow, Nutrients, and Total Suspended Solids in the Upper White River Basin, Indiana","title":"Trends in streamflow, nutrients, and total suspended solids in the Upper White River Basin, Indiana","docAbstract":"

The U.S. Geological Survey, in partnership with The Nature Conservancy, analyzed existing water-quality and streamflow data from three locations in the Upper White River Basin, Indiana, to estimate annual mean concentrations and fluxes and to identify and quantify changes in water quality and streamflow over time. Water-quality data used in the analyses were collected between water years 1992 and 2017. Annual mean-daily concentrations and fluxes of total suspended solids, total phosphorus as phosphorus, nitrate plus nitrite as nitrogen, and total Kjeldahl nitrogen as nitrogen were estimated for U.S. Geological Survey streamgage locations in Indiana on the Upper White River at Muncie, near Nora, and near Centerton. In addition, flow-normalized annual mean-daily concentrations and fluxes of total suspended solids, total phosphorus, nitrate plus nitrite, and total Kjeldahl nitrogen were estimated and used to assess changes in these constituents between water years 1997 and 2017. Flow normalization is a process that attempts to remove the effects of year-to-year variation in streamflow on concentrations and fluxes without removing the effects associated with seasonal and long-term (multiyear) trends in streamflow.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203030","collaboration":"Prepared in cooperation with The Nature Conservancy with generous support from the Nina Mason Pulliam Charitable Trust","usgsCitation":"Koltun, G.F., and Hauswald, C., 2020, Trends in streamflow, nutrients, and total suspended solids in the Upper White River Basin, Indiana: U.S. Geological Survey Fact Sheet 2020–3030, 6 p., https://doi.org/10.3133/fs20203030.","productDescription":"6 p.","onlineOnly":"Y","ipdsId":"IP-114324","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":374596,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3030/coverthb.jpg"},{"id":374597,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3030/fs20203030.pdf","text":"Report","size":"9.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020–3030"}],"country":"United States","state":"Indiana","otherGeospatial":"Upper White River Basin","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-86.6546,39.6001],[-86.6522,39.6087],[-86.6463,39.6128],[-86.6403,39.6201],[-86.6404,39.6305],[-86.6654,39.6305],[-86.6858,39.63],[-86.6853,39.6884],[-86.6849,39.7773],[-86.6845,39.8648],[-86.6929,39.8643],[-86.6937,39.9228],[-86.6938,39.9528],[-86.6946,40.0402],[-86.6961,40.1282],[-86.6962,40.1785],[-86.2424,40.1807],[-86.2435,40.2152],[-86.242,40.3013],[-86.2423,40.3734],[-86.2429,40.3884],[-86.2422,40.4029],[-85.8624,40.407],[-85.8621,40.3784],[-85.5784,40.3794],[-85.4451,40.3792],[-85.2205,40.379],[-85.2182,40.3073],[-85.1302,40.3082],[-85.0186,40.3092],[-84.901,40.3096],[-84.8064,40.3102],[-84.8079,40.1741],[-84.8106,40.1351],[-84.8112,40.1265],[-84.8131,40.006],[-84.8603,40.0066],[-84.8952,40.0061],[-85.2014,40.0042],[-85.2013,39.875],[-85.2133,39.8751],[-85.2205,39.8748],[-85.2214,39.7895],[-85.243,39.7902],[-85.3017,39.789],[-85.3519,39.7894],[-85.4651,39.7886],[-85.5765,39.7858],[-85.5968,39.786],[-85.6333,39.7862],[-85.6338,39.6987],[-85.6876,39.6987],[-85.7993,39.6993],[-85.913,39.6976],[-85.9518,39.6969],[-85.9523,39.638],[-85.9521,39.347],[-85.9812,39.3466],[-85.9902,39.3467],[-86.0247,39.3464],[-86.0854,39.3452],[-86.0919,39.3452],[-86.1008,39.3453],[-86.1377,39.3445],[-86.249,39.342],[-86.3566,39.3404],[-86.3816,39.3399],[-86.4631,39.3391],[-86.5732,39.3395],[-86.6309,39.3413],[-86.6309,39.3481],[-86.6323,39.4696],[-86.6859,39.47],[-86.686,39.5144],[-86.6861,39.5262],[-86.6706,39.5339],[-86.6533,39.5475],[-86.6491,39.5552],[-86.6528,39.5666],[-86.6546,39.5865],[-86.6552,39.5965],[-86.6546,39.6001]]]},\"properties\":{\"name\":\"Boone\",\"state\":\"IN\"}}]}","contact":"

Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Blvd., Suite 100
Columbus, OH 43229

","tableOfContents":"","publishedDate":"2020-05-11","noUsgsAuthors":false,"publicationDate":"2020-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Koltun, G. F. 0000-0003-0255-2960 gfkoltun@usgs.gov","orcid":"https://orcid.org/0000-0003-0255-2960","contributorId":140048,"corporation":false,"usgs":true,"family":"Koltun","given":"G.","email":"gfkoltun@usgs.gov","middleInitial":"F.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hauswald, Cassie 0000-0002-9265-0603","orcid":"https://orcid.org/0000-0002-9265-0603","contributorId":224621,"corporation":false,"usgs":false,"family":"Hauswald","given":"Cassie","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":true,"id":788823,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70209985,"text":"sir20205035 - 2020 - Ecological status of aquatic communities in selected streams in the Milwaukee Metropolitan Sewerage District planning area of Wisconsin, 2004–13","interactions":[],"lastModifiedDate":"2020-05-12T11:44:31.472549","indexId":"sir20205035","displayToPublicDate":"2020-05-11T11:54:36","publicationYear":"2020","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":"2020-5035","displayTitle":"Ecological Status of Aquatic Communities in Selected Streams in the Milwaukee Metropolitan Sewerage District Planning Area of Wisconsin, 2004–13","title":"Ecological status of aquatic communities in selected streams in the Milwaukee Metropolitan Sewerage District planning area of Wisconsin, 2004–13","docAbstract":"

A total of 14 wadable streams in urban or urbanizing watersheds near Milwaukee, Wisconsin, were sampled in 2004, 2007, 2010, and 2013 to assess the ecological status of aquatic communities (biota), including benthic algae and invertebrates, and fish. To assess temporal variation, additional community sampling was also done at a subset of three sites in 2011 and 2012. Relative abundances of each type of organism were used to calculate biological metrics, such as richness and diversity, percentages of intolerant and tolerant organisms, and indexes of biotic integrity for invertebrates and fish. Selected environmental (physical and chemical) data in the streams were collected to evaluate potential relations to the biota and the ecological health of the stream. Physical and chemical data included land use/land cover, stream discharge from U.S. Geological Survey (USGS) streamgages (except at 2 creeks that were not gaged), stream habitat, microhabitat at invertebrate collection locations, water quality (except at 2 creeks that were not gaged), field measurements of several water-quality constituents, measures of benthic algal biomass, and toxicity and chemical tests on extracts from passive samplers deployed at a subset of 6 sites. Relative abundances of organisms and biological metrics were compared among sampling years and with environmental metrics to evaluate the ecological status of these streams and determine primary stressors on the aquatic communities, with the aim of helping resource managers understand and work toward improving the ecological health of these and other urban and urbanizing rivers in the study area.

Biological metrics for most sites indicated some level of diminished ecological status when compared across all sampled sites and when compared with rating scales for selected metrics. The least degraded sites among all those sampled—indicated by aggregate bioassessments for algae, invertebrates, and fish metrics and in order starting with the best overall condition—were the Milwaukee River near Cedarburg, Menomonee River at Menomonee Falls, Jewel Creek, and Milwaukee River at Milwaukee. The most degraded sites were Menomonee River at Wauwatosa, Root River at Greenfield, Lincoln Creek, and the Kinnickinnic River. Differences in aggregate bioassessments indicate that aquatic communities at the Menomonee River at Wauwatosa site and the Root River at Greenfield site were worse in 2013 than in 2004; however, Oak Creek and Honey Creek sites were better. In 2013, several sites had less than 30-percent pollution-sensitive diatoms indicating degraded algal assemblages. Invertebrate metrics for most of the 14 sites in 2013 were lower than in 2004 and indicate that invertebrate assemblages at most sampled sites were more degraded in 2013. Tolerant fish taxa made up more than 40 percent of assemblages at most sites and nearly 100 percent of assemblages at four sites. At times, in some smaller streams, too few fish were captured to compute an Index of Biotic Integrity with confidence, and invertebrates provided a better means for assessing the ecological status and water quality. With these few exceptions, the use of all three groups of biota provided the most robust assessments at the 14 sites in 2004–13.

Physical and chemical stressors were correlated to adverse effects on aquatic biota at the sampled streams. Passive samplers were deployed at a subset of six sites in 2013. Microtox results indicated there was little or no toxicity at the Milwaukee River near Cedarburg site and at the Oak Creek site, slight toxicity at the Lincoln Creek and Honey Creek sites, and moderate toxicity at the Milwaukee River at Milwaukee site and the Little Menomonee River site; however, based on cytochrome-P450 reporter gene system toxicity tests, potential toxicity from hydrophobic organic contaminants was measured at all six sites. For all 14 sites, physical and chemical stressors related to urbanization correlated with biological metrics for algae, invertebrates, and fish. Most stressors for aquatic biota reflected an urban signature. Stressors related to ecological condition in our study were chemical and physical, such as developed land, impervious surface in the watershed, urban land in a buffer area around the stream (a 100-foot [30-meter]-wide area on each side of the stream, and maximum instantaneous discharge normalized by drainage area (a measure of flood and scour effects). Chemical stressors included low waterborne concentrations of dissolved oxygen and high concentrations of chloride, zinc and other metals, nutrients (nitrite and phosphorus), and fecal coliform bacteria.

Although algae, invertebrates, and fish did not always demonstrate a significant response to the same stressors, higher abundances of high total phosphorus-indicator diatoms, lower ratings for invertebrate biotic integrity indexes and percentages of mayflies-stoneflies-caddisflies, and lower values for fish biotic integrity indexes underscored possible adverse effects of even low levels of developed land. Developed land is typically associated with more rapid runoff, which washes chemicals from impervious surfaces into area waterways and degrades stream habitat for aquatic communities. However, with respect to at least chloride from road salt, diatoms tolerant to dissolved salts were significantly lower with as little as 1-percent mixed forest in the watershed. Lower percentages of urban land in the stream buffer correlated with healthier aquatic assemblages of algae, invertebrates, and fish. The assessment of algal, invertebrate, and fish assemblages coupled with physical and chemical data were highly useful in evaluating the ecological status of aquatic communities at the 14 sites and for determining environmental stressors that may be contributing to reduced stream condition. Some of the stressors could potentially be removed or lessened with stream rehabilitation or changes in watershed management.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205035","collaboration":"Prepared in cooperation with the Milwaukee Metropolitan Sewerage District","usgsCitation":"Scudder Eikenberry, B.C., Nott, M.A., Stewart, J.S., Sullivan, D.J., Alvarez, D.A., Bell, A.H., and Fitzpatrick, F.A., 2020, Ecological status of aquatic communities in selected streams in the Milwaukee Metropolitan Sewerage District planning area of Wisconsin, 2004–13: U.S. Geological Survey Scientific Investigations Report 2020–5035, 84 p., https://doi.org/10.3133/sir20205035.","productDescription":"Report: viii, 84 p.; Data Release; Dataset","numberOfPages":"96","onlineOnly":"Y","ipdsId":"IP-106552","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":374557,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5035/coverthb.jpg"},{"id":374558,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5035/sir20205035.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5035"},{"id":374559,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FWMODL","text":"USGS data release","linkHelpText":"Aquatic community and environmental data for 14 rivers and streams in the Milwaukee Metropolitan Sewerage District Planning Area, 2004-13"},{"id":374560,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"National Water Information System—","linkHelpText":"USGS water data for the Nation"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Milwaukee Metropolitan Sewerage District Planning Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.187255859375,\n 42.512601715736665\n ],\n [\n -87.81372070312499,\n 42.512601715736665\n ],\n [\n -87.81372070312499,\n 43.15710884095329\n ],\n [\n -88.187255859375,\n 43.15710884095329\n ],\n [\n -88.187255859375,\n 42.512601715736665\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-05-11","noUsgsAuthors":false,"publicationDate":"2020-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Eikenberry, Barbara C. Scudder 0000-0001-8058-1201 beikenberry@usgs.gov","orcid":"https://orcid.org/0000-0001-8058-1201","contributorId":172148,"corporation":false,"usgs":true,"family":"Eikenberry","given":"Barbara C. Scudder","email":"beikenberry@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":788704,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nott, Michelle A. 0000-0003-3968-7586","orcid":"https://orcid.org/0000-0003-3968-7586","contributorId":221766,"corporation":false,"usgs":true,"family":"Nott","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788705,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stewart, Jana S. 0000-0002-8121-1373 jsstewar@usgs.gov","orcid":"https://orcid.org/0000-0002-8121-1373","contributorId":539,"corporation":false,"usgs":true,"family":"Stewart","given":"Jana","email":"jsstewar@usgs.gov","middleInitial":"S.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788706,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sullivan, Daniel J. 0000-0003-2705-3738","orcid":"https://orcid.org/0000-0003-2705-3738","contributorId":204322,"corporation":false,"usgs":true,"family":"Sullivan","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788707,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Alvarez, David A. 0000-0002-6918-2709 dalvarez@usgs.gov","orcid":"https://orcid.org/0000-0002-6918-2709","contributorId":1369,"corporation":false,"usgs":true,"family":"Alvarez","given":"David","email":"dalvarez@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":788708,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bell, Amanda H. 0000-0002-7199-2145 ahbell@usgs.gov","orcid":"https://orcid.org/0000-0002-7199-2145","contributorId":1752,"corporation":false,"usgs":true,"family":"Bell","given":"Amanda","email":"ahbell@usgs.gov","middleInitial":"H.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788709,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fitzpatrick, Faith A. 0000-0002-9748-7075","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":209612,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788710,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70209987,"text":"ds1124 - 2020 - Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January through December 2016, and previously unpublished data from 2013 to 2015","interactions":[],"lastModifiedDate":"2020-05-11T20:21:59.676539","indexId":"ds1124","displayToPublicDate":"2020-05-11T11:20:43","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1124","displayTitle":"Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project, January through December 2016, and Previously Unpublished Data from 2013 to 2015","title":"Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January through December 2016, and previously unpublished data from 2013 to 2015","docAbstract":"

Environmental groundwater-quality data were collected from 648 wells as part of the National Water-Quality Assessment Project of the U.S. Geological Survey National Water-Quality Program and are included in this report. Most of the wells (514) were sampled from January through December 2016, and 60 of them were sampled in 2013 and 74 in 2014. The data were collected from seven types of well networks: principal aquifer study networks, which are used to assess the quality of groundwater used for public-water supply; land-use study networks, which are used to assess land-use effects on shallow groundwater quality; major aquifer study networks, which are used to assess the quality of groundwater used for domestic supply; enhanced trends networks, which are used to evaluate the time scales during which groundwater quality changes; vertical flow-path study networks, which are used to evaluate changes in groundwater quality from shallow to deeper depths; flow-path study networks, which are used to evaluate changes in groundwater quality from shallow to deeper depths over a horizontal distance; and modeling support studies, which are used to provide data to support groundwater modeling. Groundwater samples were analyzed for many water-quality indicators and constituents, including major ions, nutrients, trace elements, volatile organic compounds, pesticides, radionuclides, and some constituents of special interest (arsenic speciation, chromium [VI], and perchlorate). These groundwater-quality data, along with data from quality-control samples, are tabulated in this report and in an associated data release. Some data from environmental samples collected in 2013–14 and quality-control samples collected in 2012–15 also are included in the associated data release. Data from samples collected in 2016 are associated with networks described in this report and have not been published previously; data from samples collected between 2012 and 2015 are associated with networks described in previous reports in this data series.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1124","collaboration":"National Water-Quality Assessment Project","usgsCitation":"Arnold, T.L., Bexfield, L.M., Musgrove, M., Erickson, M.L., Kingsbury, J.A., Degnan, J.R., Tesoriero, A.J., Kulongoski, J.T., and Belitz, K., 2020, Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January through December 2016, and previously unpublished data from 2013 to 2015: U.S. Geological Survey Data Series 1124, 135 p., https://doi.org/10.3133/ds1124. 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Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-05-11","noUsgsAuthors":false,"publicationDate":"2020-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Arnold, Terri 0000-0003-1406-6054 tlarnold@usgs.gov","orcid":"https://orcid.org/0000-0003-1406-6054","contributorId":1598,"corporation":false,"usgs":false,"family":"Arnold","given":"Terri","email":"tlarnold@usgs.gov","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":false,"id":788711,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bexfield, Laura M. 0000-0002-1789-654X bexfield@usgs.gov","orcid":"https://orcid.org/0000-0002-1789-654X","contributorId":1273,"corporation":false,"usgs":true,"family":"Bexfield","given":"Laura","email":"bexfield@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788712,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Musgrove, MaryLynn 0000-0003-1607-3864 mmusgrov@usgs.gov","orcid":"https://orcid.org/0000-0003-1607-3864","contributorId":1316,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","email":"mmusgrov@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":788713,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erickson, Melinda L. 0000-0002-1117-2866 merickso@usgs.gov","orcid":"https://orcid.org/0000-0002-1117-2866","contributorId":3671,"corporation":false,"usgs":true,"family":"Erickson","given":"Melinda L.","email":"merickso@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788714,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kingsbury, James A. 0000-0003-4985-275X jakingsb@usgs.gov","orcid":"https://orcid.org/0000-0003-4985-275X","contributorId":883,"corporation":false,"usgs":true,"family":"Kingsbury","given":"James","email":"jakingsb@usgs.gov","middleInitial":"A.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - 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2020 - The influence of frequency and duration of seismic ground motion on the size of triggered landslides—A regional view","interactions":[],"lastModifiedDate":"2020-09-28T14:20:50.183031","indexId":"70214484","displayToPublicDate":"2020-05-11T09:18:33","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1517,"text":"Engineering Geology","active":true,"publicationSubtype":{"id":10}},"title":"The influence of frequency and duration of seismic ground motion on the size of triggered landslides—A regional view","docAbstract":"

Observation, theory, and intuition all suggest that larger earthquakes should trigger larger landslides. Many factors could contribute to this, including depth-dependent shear strength or non-linearity of ground motion in soils and rock, but we hypothesize that the key characteristics of large earthquakes causing this phenomenon are (in addition to magnitude) the frequency and duration of the strong ground motion. Because of the paucity of site-specific data for detailed analysis, we take a regional approach to this question by analyzing strong-motion records and earthquake-induced landslide (EQIL) inventories from six well-documented earthquakes. Ground motion is characterized using earthquake magnitude and the median durations and frequencies (mean periods) of subsets of strong-motion records relevant to landslide triggering. EQIL inventories are characterized using the median landslide area of the entire inventory as well as the median areas of the largest 1% of the landslides and the largest 10 landslides. We then compare ground-motion characteristics with landslide size statistics to determine possible correlations. Comparisons of all earthquake- and landslide-size statistics show strong positive correlations between landslide size and (1) magnitude, (2) ground-motion duration, and (3) mean period. Although all the ground-motion measures yield highly correlated regressions, mean period appears to be the best overall predictor of landslide size. Landslide modeling using Newmark's sliding-block method also shows that longer mean periods and durations and larger magnitudes correlate strongly with increases in modeled displacements. These results support our hypothesis that increasing period and duration of seismic ground motion are the physical factors driving increased landslide sizes for larger earthquakes. Additional studies including data from a much larger set of earthquakes is needed to confirm the results of this initial study.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.enggeo.2020.105671","usgsCitation":"Jibson, R.W., and Tanyas, H., 2020, The influence of frequency and duration of seismic ground motion on the size of triggered landslides—A regional view: Engineering Geology, v. 273, 105671, 10 p., https://doi.org/10.1016/j.enggeo.2020.105671.","productDescription":"105671, 10 p.","ipdsId":"IP-119229","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":378806,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"273","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jibson, Randall W. 0000-0003-3399-0875 jibson@usgs.gov","orcid":"https://orcid.org/0000-0003-3399-0875","contributorId":2985,"corporation":false,"usgs":true,"family":"Jibson","given":"Randall","email":"jibson@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":799701,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tanyas, Hakan","contributorId":215531,"corporation":false,"usgs":false,"family":"Tanyas","given":"Hakan","email":"","affiliations":[{"id":39272,"text":"University of Twente","active":true,"usgs":false}],"preferred":false,"id":799702,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}